dataesr/scientific-paragraphs-categorization huggingface dataset:
The solubility of barium in the (U,Pu)O 2 fuel matrix is very low due to its large ionic radius. At low oxygen potentials, it is found in the socalled grey phase of general formula (Ba,Sr,Cs)(Zr,U,Mo,RE)O 3 (RE = rare earths) with perovskite structure  [4] [5] [6] [7] [8] , while it is stable in the Ba(Mo,U)O 4 scheelite phase at high oxygen potentials  [5, [7] [8] [9]. For a thorough safety assessment of nuclear fuel behaviour under operation and in accidental conditions, a complete thermodynamic description of the multi-component system Ba-Sr-Cs-Zr-U-Pu-Mo-RE-O is therefore necessary. A number of thermodynamic and thermophysical data on the oxide phases formed in this system have been reported, but the knowledge is still limited. Nevertheless, a thermodynamic model has been developed using a CALPHAD (CALculation of PHAse Diagram) approach within the TAF-ID project (Thermodynamics of Advanced Fuels -International Database) of the OECD/NEA  [10].
More specifically, thermodynamic assessments of the Ba-Zr-O, Ba-U-O, Cs-Mo-O, Cs-U-O, Cs-Zr-O and Sr-Zr-O sub-systems have been made. The present work reports, next to the experimental studies, a CALPHAD model for the Ba-Mo-O system. It constitutes another building unit of the multi-element database of the TAF-ID. It also contributes to improving our knowledge of the still poorly understood thermochemistry of Ba and Mo fission product phases under severe accident conditions, which is key for a more reliable assessment of the source term in the SA codes. The interest in the phase relationships in the Ba-Mo-O system does not limit itself to nuclear energy applications, however. Molybdate materials have received quite some attention in recent years because of their interesting properties for applications in photoluminescence  [11] [12] [13] , solid-state lasers  [14, 15] , photocatalysts  [16, 17] , gas sensing  [18] , microwave  [19, 20] , or thermoelectric applications  [21].
BaMoO 4 for instance shows photoluminescence  [12, 22]  and can be used as host material for lanthanide cations (activated phosphors)  [22]. In this work, we report a literature review of the thermodynamic and phase diagram data available on the Ba-Mo-O system, the synthesis and structural characterization of BaMoO 4 , BaMoO 3 , and BaMo 3 O 10 , the measurement of the low-temperature heat capacity of the former two phases, the determination of the transition enthalpy associated with the peritectic decomposition of BaMo 3 O 10 , and phase diagram measurements in the BaMoO 4 -MoO 3 pseudo-binary section. Using these data as input, a CALPHAD model of the Ba-Mo-O system is then developed, that is compatible with the current descriptions and formalisms used in the TAF-ID database  [10].
Constituting binary sub-systems A thermodynamic assessment of the three binary sub-systems, i. e. Ba-O, Ba-Mo, and Mo-O, is already available as part of the TAF-ID database of the OECD/NEA  [10]. The latter were used as basis for the present assessment, and this work therefore focuses on the phase equilibria in the ternary system. The corresponding binary phase diagrams are shown in Fig. 1a-c.
Binary Ba-O system The description initially present in the TAF-ID database for Ba-O was inherited from the Fuelbase project  [23] , based on the work by Zimmermann et al. [25]. The current description was built starting from the later assessment by Zhou et al. [26] , that allows to better describe the heat capacity data for BaO 2 , following measurements reported subsequently to the work of Zimmermann et al. The description of the condensed phases BaO and BaO 2 by Zhou et al. have been modified to be consistent with the current models in the TAF-ID, however. The O 2- 2 species has not been considered in the model for the liquid phase, but rather has been replaced by a neutral O species. The stability of the liquid phase for compositions richer in oxygen than BaO has not been forced as in the original description, since no experimental information was available on this issue.
The solid phases have been considered as stoichiometric. The BaO 2 homogeneity range modelled by Zimmermann et al. and by Zhou et al. is in fact considered too large according to  [27]  and  [28]. This simplification implied a slight modification of the BaO 2 stoichiometric compound description, so as to maintain the agreement with the oxygen pressure data over the BaO-BaO 2 region. The description of the gaseous species in this system, and in particular of the binary species BaO and Ba 2 O, has been extracted from the substance SGTE (Scientific Group Thermodata Europe) database. The thermodynamic function for the gaseous Ba.
Phase diagram data in the BaO-MoO 3 pseudo-binary section There is no source in the literature reporting (to the best of our knowledge) a phase diagram over the complete composition range between BaO and MoO 3. BaMoO 4 is found on the BaO-MoO 3 pseudobinary section at the composition x(MoO 3 ) = 0. 5. Phase equilibrium data in the BaO-BaMoO 4 section were reported by Yanushkevich and Zhukovskii  [68] , while a sketch of the BaMoO 4 -MoO 3 section was reported by Ustinov et al. [56]  and Zhukovskii et al. [69]. However, the latter two sets of data are in rather poor agreement as seen in Fig. 12. Yanushkevich and Zhukovskii studied the BaO-BaMoO 4 section using X-ray and visual polythermal techniques  [68]  on BaCO 3 -MoO 3 mixtures after thermal treatment. Two intermediate compounds were identified on the pseudo-binary section, namely Ba 2 MoO 5 and Ba 3 MoO 6 , with transition temperatures T = 1573 K (peritectic) and T~1825 K (congruent melting), respectively.
Thermodynamic modelling assessment Dash et al. [53]  reported a thermodynamic model for the Ba-Mo-O system using the SOLGASMIX-PV program  [70]. The authors considered 9 compounds in this system: BaMoO 3 , BaMoO 4 , BaMo 2 O 7 , BaMo 3 O 10 , BaMo 4 O 13 , Ba 2 MoO 5 , Ba 2 Mo 5 O 17 , Ba 3 MoO 6 , and Ba 3 Mo 7 O 24. The Gibbs energy functions for the ternary phases were estimated using the additive oxide method for the standard entropy and enthalpy of formation, and using the rule of Neumann-Kopp for the heat capacity, when no experimental data were available in the literature. Only the computed isothermal section of the Ba-Mo-O phase diagram at T = 700 K is shown in their work. The authors reported O 2 (g), BaO(g), BaMoO 4 (g) and BaMoO 3 (g) to be the predominant vapour species in all ternary phase fields, and over pure compounds.
The position of the pre-peak was selected from the first node of the first derivative. Several acquisitions were performed on the same sample and summed up to improve the signal-to-noise ratio. Before averaging the scans, each spectrum was aligned using the XANES spectrum of a metallic molybdenum reference foil measured before and after the series of samples under investigation (i. e. MoO 2 , MoO 3 , BaMoO 3 , and BaMoO 4 ). The ATHENA software  [72]  was used to normalize the spectra.
It should be noted that with the present measurement configuration, the data could be collected up to a maximum temperature of about 1173 K, due to excessive boron nitride oxidation above the latter temperature, which affected the shape of the heat flow baseline curve. One typical measurement consisted in three heating cycles with 10 K ⋅ min -1 heating rate. The data collected on the first heating ramp were not considered for the analysis, however. The first heating cycle was used to equilibrate the samples, and the data collected in the subsequent two cycles were used for the analysis. The shape of the heat flow signal was mostly identical on the second and third cycles, indicating that thermodynamic equilibrium conditions were reached. After the TG-DSC measurements, selected samples were analysed using X-ray diffraction to confirm the nature of the observed transitions.
Thermodynamic models The thermodynamic parameters of the Ba-Mo-O CALPHAD model were optimized using the PARROT module of the Thermo-Calc software (Version 2016b)  [77, 78]. The hexavalent barium molybdates BaMoO 4 , Ba 3 MoO 6 , Ba 2 MoO 5 , BaMo 2 O 7 , and BaMo 3 O 10 were treated as stoichiometric compounds. BaMoO 3 was described with a more general formalism for a perovskite phase, compatible with the description of the grey-phase (Ba,Sr)(Zr,U,Mo)O 3 in the TAF-ID database  [10]. The Gibbs energy functions of all the phases are referred to the enthalpy of the pure elements in their stable state at room temperature 298. 15 K and 1 bar ( o H SER i (298. 15 K)). Note that the gas phase included in the present model was not optimized, and will be the subject of future works. The optimized parameters of the binary constituting sub-systems Ba-Mo and Ba-O can be found in Tables  B.
Binary oxides The binary oxides BaO 2 , MoO 2 , Mo 4 O 11 , Mo 8 O 23 , Mo 9 O 26 , and MoO 3 are described as stoichiometric compounds. The corresponding Gibbs energy functions have the same form as in Eq. (  7 ): G φ (T) - ∑ n φ i i o H SER i (298. 15 K) = a + b⋅T + c⋅T⋅lnT + ∑ d n T n (8) where n φ i is the number of atoms of the i th element in the oxide formula. These are taken from the TAF-ID database  [10].
BaMoO 3 perovskite The descriptions adopted for the BaUO 3 and BaZrO 3 perovskites in the TAF-ID database is also adopted in this work for BaMoO 3 to enable extrapolations to higher order systems, and the modelling of the multicomponent grey-phase formed in irradiated fuel Ba(Zr,U,Mo)O 3. A three-sublattice model is used with Ba 2+ and Mo 4+ cations on the second sublattice, i. e. (Ba 2+ )(Mo 4+ ,Ba 2+ )(O -2 ) 3. The corresponding higherorder model for the grey-phase in the TAF-ID is (Ba 2+ )(Zr 4+ ,U 4+ ,U 6+ , Mo 4+ ,Ba 2+ )(O -2 ) 3. The partial substitution of the U 4+ by Ba 2+ on the second sublattice allows to reproduce the stability of the perovskite along the BaUO 3 -Ba 3 UO 6 tie-line in the Ba-U-O system  [10]. The Gibss energy functions of the (Ba 2+ )(Mo 4+ )(O -2 ) 3 and (Ba 2+ )(Ba 2+ )(O -2 ) 3 end-members take the same forms as Eq.
Gas phase The gas phase is described by an ideal mixture of (Ba, Ba G φ = Σ i y o i G φ i + RTΣ i y i lny i + RTlnP / P o (13) where y i is the fraction of the species i in the gas phase, o G φ i the standard Gibbs energy of the gaseous species i, and P o the standard pressure. The function for BaMoO 4 is taken from the SGTE database  [81]. Note that the computed pressures in the ternary system Ba-Mo-O are not commented in this work, and will be the subject of future work in our research group. We refer the reader to the Appendix for the expressions of the gaseous functions of the binary species.
Acknowledgements The experimental work was funded by the  OECD/NEA TCOFF (Thermodynamic Characterisation of Fuel Debris and Fission Products Based on Scenario Analysis of Severe Accident Progression at Fukushima-Daiichi Nuclear Power Station ) project. Modelling of the Ba-Mo-O system was supported by the  OECD/NEA TAF-ID  ( Thermodynamics of Advanced Fuels -International Database)  project. The authors would like to thank  D. Banerjee  ( KU Leuven, Department of Chemistry ) for his help with the XANES measurements at the  BM26A-DUBBLE Beamline  at the  ESRF.
19 SNPs with high imputation quality (imputation r 2 > 0. 5) were included. Overlapping participants between datasets were excluded from the iCOGS dataset as the OncoArray provides a better genomic coverage than the iCOGS array. Demographic and epidemiologic data were harmonised across BCAC sites based on a standardised protocol and derived with respect to a reference date, which was date at diagnosis for cases and date at interview for controls. For controls and cases from the nested case-control studies, data from the baseline interview were considered, or if available, follow-up information. Chosen characteristics of the two datasets, including self-reported smoking behaviours (e. g. , smoking status, smoking heaviness and smoking duration, including age at smoking initiation and lifetime smoking exposure) are shown in Supplementary Table  1.
Heterogeneity was tested employing the likelihood ratio test (LRT) for evaluating the multiplicative interaction terms in nested models. Polytomous regression was used to estimate the association according to oestrogen receptor (ER) status. Scaling was applied to convert the wPGSs for CPD into meaningful units through dividing them by linear regression coefficients of self-reported CPD (0. 35 per pack of cigarettes per day). The regression coefficient of CPD was derived from a meta-analysis of iCOGS and OncoArray data on smoking behaviours among 26,072 among ever-smoker controls (8490 and 17,703 controls of iCOGS and OncoArray, respectively). Two-sample MR analyses. Five different two-sample MR methods using summary association data were applied: inverse-variance weighted (IVW),  28  MR Egger,  29  weighted median,  30  weighted mode,  31  and robust adjusted profile score (RAPS).
13, 47, 48 Despite early evidence against a differential association by ER status, 2,3 recent epidemiologic studies reported a stronger association for risk of ER-positive breast cancer. 10, 13, 41 We did not find clear evidence for heterogeneity by ER status although power to detect effect heterogeneity was limited particularly due to the small sample size for ER-negative disease. 2] [43]  We addressed this issue by excluding SNPs associated with alcohol intake from the wPGS. However, the results did not change significantly in sensitivity analyses with wPGS, including the overlapping alcohol consumption-associated SNPs (Supplementary Table  7 ). Also, our multivariable analyses adjusting for alcohol consumption yielded association estimates that remained unchanged. The lower precision can be attributed to the reduced dataset that required information on alcohol intake with the ensuing diminished power.
Strengths and limitations Despite the relatively large sample size used for our analyses, weak statistical power to detect modest associations should be considered when interpreting the results. The power calculation shows that our study had 68% power to detect an OR of 1. 20 per SD change in LSI but only around 9% power for an OR of 1. 05 in combined dataset (iCOGS and OncoArray) (Supplementary Table  3 ). Since the reported order of magnitude for associations with CPD is around 1. 05 per ten cigarettes,  13  we cannot exclude that the lack of association observed in the MR analysis particularly regarding CPD may be due to limited power. The unit for LSI is not scaled due to the nature of the phenotype. The reported order of magnitude for associations with LSI can therefore not be directly compared with the relative risk estimates for smoking from observational studies.
ACKNOWLEDGEMENTS We thank all the individuals who took part in these studies and all the researchers, clinicians, technicians and administrative staff who have enabled this work to be carried out. The COGS study would not have been possible without the contributions of the following:  Andrew Berchuck  (OCAC),  Rosalind A. Eeles ,  Ali Amin Al Olama ,  Zsofia Kote-Jarai ,  Sara Benlloch  (PRACTICAL),  Antonis Antoniou , and  Lesley McGuffog  (CIMBA),  Andrew Lee , and  Ed Dicks ,  Craig Luccarini  and the staff of the  Centre for Genetic Epidemiology Laboratory ,  Anna Gonzalez-Neira  and the staff of the CNIO genotyping unit, and  Daniel C. Tessier ,  Francois Bacot ,  Daniel Vincent ,  Sylvie LaBoissière  and  Frederic Robidoux  and the staff of the  McGill University and Génome Québec Innovation Centre ,  Sune F.
P. H. , R. M. T. and  A. Cox. are subject editors for the British Journal of Cancer. P. D. P. P. , E. J. S. and  K. Cz. are editorial board members for the  British Journal of Cancer. The remaining authors declare no competing interests. Funding information BCAC is funded by  Cancer Research UK  [ C1287/A16563 ,  C1287/A10118 ], the  European Union 's  Horizon 2020 Research and Innovation Programme  (grant numbers  634935  and  633784  for BRIDGES and B-CAST respectively), and by the  European Community´s Seventh Framework Programme  under grant agreement number  223175  (grant number  HEALTH-F2-2009-223175 ) (COGS). The  EU Horizon 2020 Research and Innovation Programme  funding source had no role in study design, data collection, data analysis, data interpretation or writing of the report.
Genotyping of the OncoArray was funded by the  NIH  Grant  U19 CA148065 , and  Cancer UK  Grant  C1287/A16563  and the  PERSPECTIVE  project supported by the  Government of Canada through Genome Canada  and the  Canadian Institutes of Health Research  (grant  GPH-129344 ) and, the  Ministère de l'Économie, Science et Innovation du Québec through Genome Québec  and the  PSR-SIIRI-701 grant , and the  Quebec Breast Cancer Foundation. Funding for the iCOGS infrastructure came from: the  European Community 's  Seventh Framework Programme  under grant agreement  n°223175  ( HEALTH-F2-2009-223175 ) (COGS),  Cancer Research UK  ( C1287/A10118 ,  C1287/A10710 ,  C12292/A11174 ,  C1281/ A12014 ,  C5047/A8384 ,  C5047/A15007 ,  C5047/A10692 ,  C8197/A16565 ), the  National Institutes of Health  ( CA128978 ) and  Post-Cancer GWAS initiative  ( 1U19 CA148537 ,  1U19 CA148065  and  1U19 CA148112  -the  GAME-ON initiative ), the  Department of Defence  ( W81XWH-10-1-0341 ), the  Canadian Institutes of Health Research (CIHR)  for the  CIHR Team in Familial Risks of Breast Cancer , and  Komen Foundation  for the Cure, the  Breast Cancer Research Foundation , and the  Ovarian Cancer Research Fund.
The  DRIVE Consortium  was funded by  U19 CA148065. The  Australian Breast Cancer Family Study (ABCFS)  was supported by grant  UM1 CA164920  from the  National Cancer Institute (USA). The content of this manuscript does not necessarily reflect the views or policies of the  National Cancer Institute  or any of the collaborating centres in the  Breast Cancer Family Registry (BCFR) , nor does mention of trade names, commercial products, or organisations imply endorsement by the  USA Government  or the BCFR. The ABCFS was also supported by the  National Health and Medical Research Council of Australia , the  New South Wales Cancer Council , the  Victorian Health Promotion Foundation (Australia)  and the  Victorian Breast Cancer Research Consortium. J. L. H. is a  National Health and Medical Research Council  ( NHMRC) Senior Principal Research Fellow.
M. C. S. is a  NHMRC Senior Research Fellow. The ABCS study was supported by the  Dutch Cancer Society  [grants NKI 2007-3839; 2009 4363]. The  Australian Breast Cancer Tissue Bank (ABCTB)  was supported by the  National Health and Medical Research Council of Australia , The  Cancer Institute NSW  and the  National Breast Cancer Foundation. The AHS study is supported by the intramural research program of the  National Institutes of Health , the  National Cancer Institute  (grant number  Z01-CP010119 ), and the  National Institute of Environmental Health Sciences  (grant number  Z01-ES049030 ). The work of the BBCC was partly funded by  ELAN-Fond of the University Hospital of Erlangen. The BBCS is funded by  Cancer Research UK  and  Breast Cancer Now and acknowledges NHS  funding to the  NIHR Biomedical Research Centre , and the  National Cancer Research Network (NCRN).
The BCEES was funded by the  National Health and Medical Research Council, Australia. For the  BCFR-NY, BCFR-PA, BCFR-UT , this work was supported by grant  UM1 CA164920  from the  National Cancer Institute. The content of this manuscript does not necessarily reflect the views or policies of the  National Cancer Institute  or any of the collaborating centres in the  Breast Cancer Family Registry (BCFR) , nor does mention of trade names, commercial products, or organisations imply endorsement by the  US Government  or the BCFR. For BIGGS, ES is supported by  NIHR Comprehensive Biomedical Research Centre, Guy's & St. Thomas' NHS Foundation Trust  in partnership with King's  College London, United Kingdom. IT is supported by the  Oxford Biomedical Research Centre. The  BREast Oncology GAlician Network (BREOGAN)  is funded by  Acción Estratégica de Salud del Instituto de Salud Carlos III   FIS PI12/02125 / Cofinanciado FEDER ;  Acción Estratégica de Salud del Instituto de Salud Carlos III FIS Intrasalud  ( PI13/01136 );  Programa Grupos Emergentes ,  Cancer Genetics Unit, Instituto de Investigacion Biomedica Galicia Sur.
Xerencia de Xestion Integrada de Vigo-SERGAS ,  Instituto de Salud Carlos III, Spain ; Grant  10CSA012E ,  Consellería de Industria Programa Sectorial de Investigación Aplicada, PEME I + D e I + D Suma del Plan Gallego de Investigación, Desarrollo e Innovación Tecnológica de la Consellería de Industria de la Xunta de Galicia, Spain ; Grant  EC11-192. Fomento de la Investigación Clínica Independiente ,  Ministerio de Sanidad, Servicios Sociales e Igualdad, Spain ; and Grant  FEDER-Innterconecta. Ministerio de Economia y Competitividad, Xunta de Galicia, Spain. The BSUCH study was supported by the  Dietmar-Hopp Foundation , the  Helmholtz Society  and the  German Cancer Research Center (DKFZ). CBCS is funded by the  Canadian Cancer Society  (grant #  313404 ) and the  Canadian Institutes of Health Research.
The CTS was initially supported by the  California Breast Cancer Act of 1993  and the  California Breast Cancer Research Fund  (contract  97-10500 ) and is currently funded through the  National Institutes of Health  ( R01 CA77398 ,  UM1 CA164917  and  U01 CA199277 ). Collection of cancer incidence data was supported by the  California Department of Public Health  as part of the statewide cancer reporting program mandated by  California Health and Safety Code Section 103885. The University of Westminster curates the DietCompLyf database funded by  Against Breast Cancer Registered Charity  No. 1121258  and the  NCRN. The coordination of EPIC is financially supported by the  European Commission (DG-SANCO)  and the  International Agency for Research on Cancer. The national cohorts are supported by:  Ligue Contre le Cancer ,  Institut Gustave Roussy, Mutuelle Générale de l'Education Nationale ,  Institut National de la Santé et de la Recherche Médicale (INSERM) (France) ;  German Cancer Aid ,  German Cancer Research Center (DKFZ) ,  Federal Ministry of Education and Research (BMBF) (Germany) ; the  Hellenic Health Foundation , the  Stavros Niarchos Foundation (Greece) ;  Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy and National Research Council (Italy) ;  Dutch Ministry of Public Health, Welfare and Sports (VWS) ,  Netherlands Cancer Registry (NKR) ,  LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland) ,  World Cancer Research Fund (WCRF) ,  Statistics Netherlands  (The Netherlands);  Health Research Fund (FIS) ,  PI13/ Mendelian randomisation study of smoking exposure  in relation to breast.
The HMBCS was supported by a grant from the  Friends of Hannover Medical School  and by the  Rudolf Bartling Foundation. The HUBCS was supported by a grant from the  German Federal Ministry of Research and Education  ( RUS08/017 ), M. B. was supported by grant  17-44-020498 ,  17-29-06014  of the  Russian Foundation for Basic Research , E. K was supported by the program for support the bioresource collections  №007-030164/2 , and the study was performed as part of the assignment of the  Ministry of Science and Higher Education of the Russian Federation  ( №АААА-А16-116020350032-1 ). Financial support for KARBAC was provided through the regional agreement on medical training and clinical research (ALF) between  Stockholm County Council and Karolinska Institutet , the  Swedish Cancer Society , The Gustav V Jubilee foundation and Bert von Kantzows foundation.