dataesr/scientific-paragraphs-categorization huggingface dataset:
Solubility of PAHs in IL solutions The solubility limits of five PAHs (naphthalene, anthracene, phenanthrene, pyrene and coronene) were measured in seven different ILs at 298 K. The corresponding solubility data are reported in Tables S1. 1-S1. 3 of the ESI † and represented in Fig. 3. The data show that the solubility of the PAH solutes in the different IL solvents spans almost four orders of magnitude and is mainly determined by the nature of the PAH. Naphthalene and phenanthrene are the most soluble in all ILs, followed by pyrene, anthracene and coronene. Interestingly, phenanthrene is almost two orders of magnitude more soluble in ILs than its isomer anthracene. Such a fact can be explained taking into consideration the relative stabilities of the crystalline forms of the two PAHs: the melting temperature (490 K), the enthalpy of fusion at that temperature (29 kJ mol À1 ) and the enthalpy of sublimation at 298 K (98 kJ mol À1 ) are much larger than the corresponding values for phenanthrene (370 K, 16 kJ mol À1 and 91 kJ mol À1 , respectively).
Spectroscopic results IR spectroscopic data are listed in Table  4 , namely the wavenumbers of the main infrared (IR) bands identified in the differential spectra of three PAHs in different solvents, including the four ILs discussed in the previous sections. All differential spectra were obtained after subtraction of the solution spectra from the corresponding pure solvent spectra. The regions with overlapping PAH and IL bands were not considered. The behaviour of PAHs dissolved in ILs was compared with that of the same PAHs dissolved in different molecular liquids. Three non-protic, nonpolar solvents were considered: tetrachloromethane, n-decane and benzene. The two strongest bands of naphthalene are observed at ca. 790 and 480 cm À1. They are respectively attributed to CH out-of-plane bending and skeletal (CCC) out-of-plane bending vibrations.
Acknowledgements This work is part of the research program "Understanding the visco-elasticity of elastomer based nanocomposites" ( 11VEC01 ) of the  Stichting voor Fundamenteel Onderzoek der Materie (FOM) , which is financially supported by the  Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO). MMD acknowledges a stimulating conversation with Sanat Kumar.
Acknowledgments: This work was supported by  European Community 's  Seventh Framework Program  ( FP7)  under grant agreement n  285203  ( FP7 SNIFFER PROJECT ) and is continuing within the European project n  653323  ( H2020 C-BORD PROJECT ). Special thanks are due to  Nadine Vallet  of  ISIPCA  for her assistance in gas analysis and for having welcomed some experiments in her laboratory. gas cell. Maira Pôssas Abreu and Emmanuel Scorsone analyzed data. Maïra Pôssas Abreu  and  Gaelle Lissorgues  wrote the paper.
Acknowledgments: The authors wish to thanks  Olivier de Sagazan ,  Christophe Lebreton  and  Brice Le Borgne  for technological support and clean room facilities and the  ANR  for financial support. This publication is also supported by the  European Union  through the  European Regional Development Fund (ERDF) , and by the  french region of Brittany and Pays de la Loire, le Ministère  de l'enseignement supérieur et de la recherche,  Rennes Métropole , et le Conseil Départemental 35, through the  CPER Projects TechnoCap and SOPHIE/STIC & Ondes.
Acknowledgment This work was supported by  ERC   Consolidator grant  BrightSens  648528. We thank  Dr. Christian Wilms  for his suggestions,  Pichandi Ashokkumar  for the cell culture,  Romain Vauchelles  for his assistance at the PIQ platform and for the Ratio Intensity Color Version 2. 5 plugin,  Sabine Lang  for the mass measurements and  Bohdan Wasylyk  for providing the KB cells.
EXPERIMENTAL Materials Syringaldehyde, malonic acid, ferulic acid, Pd/C, norborneneendo-2,3-dicarboxylic anhydride and lithium aluminum hydride were purchased from Sigma-Aldrich. Candida antarctica Lipase B was purchased from Novozyme. Solvents were purchased from ThermoFisher Scientific and VWR. Deuterated chloroform (CDCl 3 ) and acetone ((CD 3 ) 2 CO) were purchased from Eurisotop. Column chromatographies were carried out with an automated flash chromatography (PuriFlash 4100, Interchim) and pre-packed INTERCHIM PF-30SI-HP (30 µm silica gel) columns using a gradient of cyclohexane and ethyl acetate for the elution. NMR analyses were recorded on a Bruker Fourier 300 (Supplementary Data Sheet 1). 1 H NMR spectra of samples were recorded in CDCl 3 at 300 MHz, chemical shifts were reported in parts per million (CDCl 3, CHCl 3 residual signal at δ = 7.
In this study, two types of PetroOxy measurements are employed. Single induction period runs at the three temperatures of 120 °C (393. 15 K), 140 °C (413. 15 K), and 160 °C (433. 15 K) were carried out to identify the temperature dependence of the solvent oxidation process. A second measurement consisted of running the PetroOxy for additional pressure drop criteria of 20% and 40% to obtain a limited number of experimental data points over time as the sample is oxidized. The associated recorded pressure drops are included in Supplementary Figures B. 10 and B. 11. After the test, the remaining liquid sample was transferred to a clear glass vial and stored in a refrigerator for further post-test analysis. The volume of the retained sample was assessed by photographing the vials under controlled conditions and calculating the recovered sample volume by comparing with reference volumes.
One use of quantum chemical calculation is the determination of thermodynamic parameters, such as can be used in a chemical kinetics mechanism. In the context of this study, this calculation was performed to assess and improve the quality of the RMG-predicted thermodynamic parameters for individual species in the liquid phase. The most commonly used methods for calculating molecular properties are CCSD(T) as well as CBS methods, as these methods theoretically promise the greatest accuracy, albeit at a large computational cost. As an example, many entries in the RMG kinetics database were obtained with CBS-QB3. 23, 29, 30 1] [42] [43] [44] [45] [46]  A more accessible approach in the study of a large number of compounds is to choose a computationally lighter method. 47 Density functional theory offers improved accuracy relative to semiempirical methods, while not commanding the computational costs of couple cluster computations, commonly employed in the calculation of reference values.
3. 4. Sensitivity Analysis and 0D Chemical Kinetics. Brute force sensitivity analysis can provide insights into the response of a chemical kinetics mechanism to minor or major changes in the Arrhenius parameters. This method can be employed to probe the mechanism's sensitivity to minor changes and offers the user the ability to identify reaction whose parameters exhibit a significant impact on the mechanism behavior and thus warrant a further investigation. Brute force sensitivity analysis was carried out by developing a simple dedicated C++ code to read the chemkin input file generated by RMG and write output files with adjusted Arrhenius parameters using a systematic naming pattern based on user defined parameters. In a second step, Bash with the option of GNU parallel 84 may be employed to solve the modified mechanisms using a solver of choice.
While both Hermans et al. 2  and Hoorn 1 suggest that two benzyl-peroxyls will terminate with the formation of benzyl alcohol, benzaldehyde, and oxygen, RMG favors the pathway suggested by Denisov. 73 This is outlined in reactions 23, 24, and 25. Instead of benzaldehyde, these steps lead to the formation of a benzyl-oxyl radical, RO•, which can form benzyl alcohol by hydrogen abstraction from the main fuel or another species. •+ • → - ROO ROO ROO OOR (23) -→ • + • ROO OOR RO RO 3 ( 24 ) •→ • + RO RO O 32 (25) In this work, experimental data were collected in the PetroOxy using the method outlined in Section 2. 1. The stressed sample was retained for a 10%, 20%, and 40% pressure drop condition. A comparison plot for the concentration of toluene in the experiment and the model is shown in Figure  12 , using the model concentration at 0 s as a 100% reference concentration.
ACKNOWLEDGMENTS The authors would like to thank the  ORCA developers  for organizing the 2nd ORCA User Group Meeting in Mulheim an der Ruhr (5th & 6th September 2016), which offered the opportunity for valuable general discussions on method and basis set selection and where a prerelease version of ORCA 4 was generously made available exclusively to the attendants. Further thanks go to  Dr. Karl Chatelain  for interesting discussions regarding the usage of RMG and the assessment of its behavior as well as his contributions to RMG development. Thanks for interesting discussions on quantum chemistry and chemical kinetics go to  Prof. Dr. AndréNicolle. Thanks also go to  Dr. Anthony Velge , for the development and maintenance of Cloe as well as the development of the ROP output. Lastly, thanks go to members of the experimental and analytical department, namely,  Benjamin Veyrat  (PetroOxy experiments) as well as Pascal Hayrault (GC).
data analysis and statistics Individual patient data were entered to an EXCEL file by the principal investigator. Non-parametric tests (Kruskal-Wallis H) were used to compare median levels of vitamin D (25-(OH)D 3 ) between groups. Comparisons of characteristics of patients with TB between those with normal FBG, pre-DM and DM and categorical comparisons of various 25-(OH)D 3 levels between patients with DM, pre-DM and normal FBG were carried out using the X 2 test. Relationships between 25-(OH)D 3 and associated exposure variables were evaluated with ORs and 95% CIs. We selected variables with unadjusted ORs for which the p value was <0. 05 and included these in a multivariate logistic regression model using SPSS V. 13. 0 (SPSS). Levels of significance were set at 5%.
MATERIALS AND METHODS Study design and participants. The European Prospective Investigation into Cancer and Nutrition (EPIC) study is a multicentre prospective cohort study from 23 centres in 10 European countries (Denmark, France, Germany, Greece, Italy, The Netherlands, Norway, Spain, Sweden, and the United Kingdom)  (Riboli and Kaaks, 1997). Between 1992 and 2000 over 520 000 men and women were recruited for whom socio-demographic, dietary (using validated country-specific food frequency questionnaires), lifestyle, anthropometric data and biological samples (from approximately 80% participants) were collected at baseline. Samples from all countries are stored in À 196 1C liquid nitrogen at the International Agency for Research on Cancer (IARC, Lyon, France), except Denmark (at À 150 1C under nitrogen vapour) and Sweden ( À 80 1C freezers).
HCC was defined as C22. 0. GBTC were defined as tumours in the gall bladder (C23. 9), extrahepatic bile ducts (C24. 0), ampulla of Vater (C24. 1) and biliary tract (C24. 8 and C24. 9). IHBD were defined as C22. 1. For each identified case, the histology and the methods used for diagnosis were reviewed and metastatic cases or other types of primary liver cancer were excluded. In detail, from all recruited cohort participants, 23 818 subjects with prevalent cancer other than non-melanoma skin cancer, 4380 with incomplete follow-up data or missing information on the date of diagnosis, 6192 with missing dietary information, 60 with missing lifestyle information, and 9596 who were at the top or bottom 1% of the distribution of the ratio of reported energy intake to energy requirement, and 78 with metastasis in the liver or ineligible histology code were excluded from the above classifications, which were conducted on 477 206 eligible participants.
As hepatitis infection, an established risk factor for liver cancers may alter liver function and hence circulating copper and zinc levels, additional sensitivity analyses were performed by excluding hepatitis positive subjects. Sub-group analyses based on hepatitis negative subjects were conducted using continuous unconditional logistic regression models adjusted for sex, country and age at recruitment. Additional sensitivity analyses were performed excluding samples from Denmark and Sweden, where bio-sample storage conditions differed from those at the IARC biobank. Analyses were conducted using SAS version 9. 2 (SAS Institute, Cary, NC, USA). All statistical tests were two-sided and P-values o0. 05 were considered statistically significant.
ACKNOWLEDGEMENTS This work was supported by the  French National Cancer Institute (L'Institut National du Cancer ;  INCA ; grant number  2009-139 ; PI:  M Jenab ) and the  Health Research Board of Ireland  (award number  HRA_PHS/2013/397 ; PI: DJ Hughes). 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  Danish Cancer Society (Denmark) ;  Ligue Contre le Cancer ,  Institut Gustave Roussy, Mutuelle Generale de l'Education Nationale, Institut National de la Santeet de la Recherche Medicale (INSERM) (France) ;  Deutsche Krebshilfe, Deutsches Krebsforschungszentrum and Federal Ministry of Education and Research (Germany) ; the  Hellenic Health 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);  Nordic Centre of Excellence programme on Food , Nutrition and Health.
Each child received one porridge for three consecutive days. The sequence of porridge consumption was determined using FIZZ Acquisition software (Biosystèmes, Couternon, France). There were 10 different sequences, and per group, eight (group 1) or four (group 2) children were fed porridges in the same sequence. Prior to the study's implementation, porridges were prepared during a 4-day training period to determine the appropriate water/flour ratio, and the porridges were pretested in order to determine the locally preferred consistency, which could finally be described as a spoonable consistency, able to make a heap on a spoon. This was done under supervision of a food technologist from GRET and experts from DSM and World Food Programme, together with the supervisors of the three selected study sites.
Data collection forms and record sheets were translated into French by an official translator. In order to prepare each porridge type, a pot, spoon, gas cooker, a weighing scale, and stopwatch were used by the cooks at the study sites. All equipments were coded to ensure that the same equipment was used for preparing the same porridge every day. The cooks received porridge-specific preparation instructions and prepared the same porridge once every day in the morning around 5 a. m. , for 30 days. Precise weight of flour and water (and oil for the SC porridges) used as well as final porridge weight were recorded daily by the cooks and was used to calculate porridge dry matter content (i. e. , by water loss during cooking). Prepared porridges were stored in thermos flasks to keep it warm and for easy distribution.
In addition, caregivers were given clean preweighed napkins to collect the spilt porridge. All weighing was done using an electronic scale with 0. 1 g precision (Furi ML-CF1). Samples of each prepared porridge were collected to determine dry matter content by dehydration in an oven at 105 °C until constant weight. Each day, porridge flow rate was measured using the Bostwick consistometer at 45 °C following the standard procedures as earlier described  (Mouquet, Greffeuille, & Treche, 2006). Bostwick flow rate is expressed in millimeter per 30 s and can range from 0 (almost solid porridge) to 240 mm/30 s (very fluid porridge). The caregivers received five porridges in a randomized sequence as generated by the program FIZZ Acquisition. The porridges were prepared using the same procedure as used for the 30-day consumption study.
In case of Vitazom, eeZeeBAR™, and CERELAC ® , the data on the label were used for calculations. 2. 8 | Statistical analysis 2. 8. 1 | Analysis for the consumption study For each age group, a separate intention-to-treat analysis was performed. The study protocol and statistical analysis plan specified a linear mixed model with child as random factor and with fixed effects sex, day rank of diet period (days 1, 2, or 3), order of food distribution (period in which the porridge was served), and porridge type. Age in months was included as an additional explanatory covariate. The following possible additional confounders, some of which were not known at the writing of the statistical analysis plan, were investigated by including each of them as additional fixed effect and performing a likelihood ratio test versus the original model for the main outcomes "energy intake in kilocalorie per meal" and "porridge consumption in grams per meal": canteen (for the younger group only), surveyor (person handing out and weighing the bowls), and sequence (order of porridge consumption).
Data were analyzed with the statistical software R version 3. 0. 2 (R Core Team, 2013), applying the add-on packages nlme version 3. 1-117  (Pinheiro et al. , 2014) , multcomp version 1. 3-6  (Hothorn et al. , 2008) , and lsmeans version 2. 11  (Lenth, 2014).
| Sensory study Quantitative data of the sensory study were entered in Epidata version 3. 1 (The EpiData Association, Odense, Denmark). The porridge sensory rankings regarding taste, smell, color, consistency, and overall ranking were analyzed with analysis of variance. Adjustments for multiple comparisons using a Bonferroni correction were carried out to test for significant mean differences between porridges. Pearson's chi-square test was used to evaluate data available on porridge ranking, using a significance level of p <. 05. Data were analyzed using SAS software 9 for Windows (SAS Institute Inc. , Cary, NC, USA) and Statgraphics Centurion XVI software (version 16. 1. 18; Statpoint Technologies Inc. , Warrenton, VG, USA).
| RESULTS In total, 120 eligible children with their caregivers were enrolled in the study, that is, 80 in group 1 with children aged 12-23 months and 40 in group 2 with children aged 24-35 months. After consumption day 17, one child from group 1 was lost to follow-up since the family moved away from the area, and on day 21, a child from group 1 passed away due to malaria. Consumption data of these two children were incomplete; however, all available data were used for analysis. In total, 100 of the caregivers of children who had participated in the consumption trial were enrolled for participation in the sensory study, that is, a response rate of 83% (n = 73 from group 1 and n = 27 from group 2).
Histology and Immunochemistry Analyses Paraffin-embedded 4% PAF-fixed rat colons were sectioned at 5 µm. The sections were stained with Hematoxylin Phloxine Saffron and an average of 12 crypt depths was measured per animal. For immunohistochemistry, the sections were immunolabeled with mouse monoclonal anti-GLP-1 antibody ([8G9] Abcam) and rat monoclonal anti-Ki67 antibody (DAKO, Les Ulis, France) using a detection kit (Bond Polymer Refine detection; DS9800; Leica Microsystems). The primary antibody was substituted by PBS as a negative control. The number of GLP-1-positive cells was determined by counting positive cells per µm 2 (one labeled slide per animal) of mucosa and the number of Ki67-positive cells was determined by counting the positive cells per crypt (10 per animal) using Calopix image analysis software (TRIBVN, Chatillon, France).
Statistical Analysis All statistical analysis for DNA sequences were performed using R. Principal component analyses (PCA) were computed and statistically assessed using a Monte Carlo rank test. The Wilcoxon test was applied to assess statistical significance in bacterial composition between the different samples. All values are expressed as the mean ± S. E. M. Non-parametric tests were used: The Kruskal-Wallis test followed by Dunn's adjusted multiple comparisons to compare more than two groups or Spearman test to correlate two parameters were performed using GraphPad Prism version 5. 0 for Windows (GraphPad Software, San Diego, CA, USA). A value of P < 0. 05 was considered to be statistically significant.
Sensitivity analyses were conducted using ANCOVA models that adjusted for covariates that were determined post hoc to be significantly different between groups and which may have confounded the primary results (eg, mother smoking status). Secondary endpoints were analyzed in the ITT population only. For noninferiority and superiority tests, 1-sided P values are provided and should be compared to a reference value of 0. 025. For other tests, 2-sided P values are provided and should be compared to a reference value of 0. 05. 95% CIs provide estimates for feeding effects on all endpoints. Based on prespecified guidelines in the independent Data Monitoring Committee's (DMC) charter, a single interim analysis was conducted when 134 subjects had completed their D21 visit. The interim analysis was planned to occur when the first 100 infants completed at least 21 days of full fortification; however, the analysis was conducted using data from 134 infants owing to unforeseen delays in conducting the analysis (eg, performing statistical programming, data cleaning, and query resolution) while recruitment continued.
The type 1 error rate was adjusted to account for the analysis being conducted at $70% enrollment rather than the planned 52%. The DMC consisted of independent experts (2 clinicians, 1 biostatistician) who reviewed growth, formula intake, and key biochemical data as well as AEs. The purpose of the interim analysis was to examine unblinded growth velocity results and determine whether the trial could be stopped early for success or futility, or whether the targeted sample size required adjustment (the interim statistical analysis plan was finalized before unblinding, and the analysis was unblinded only to the DMC to facilitate ethical decision-making)  (31). On April 2, 2014, the DMC recommended to stop the trial, as noninferiority and superiority in regard to the primary outcome had been demonstrated.
As these may be confounding factors in the analysis of weight gain, post hoc ANCOVAs including these parameters were performed. The post hoc results were essentially the same as the main results, indicating that differences in maternal baseline characteristics did not confound the results. Additionally, to determine the possible impact of including clustered data from twins in the analyses, a sensitivity analysis on weight gain (grams per day) from D1 to D21 accounting for the correlated multiple-birth data was performed. Again, these results were similar to those of the main analysis (weight gain 3. 2 g/ day higher in nHMF [95% CI: 0. 5, 5. 9 g/day]). Our results are consistent with those of previous studies  (36) (37) (38) (39) (40) (41) (42). A recent meta-analysis of 5 studies (comprising 352 infants with birthweight 1750 g and gestational age 34 weeks) compared growth of infants fed HM fortified with either lower-protein or higher-protein fortifier  (43).
Acknowledgments: The authors thank the families of the infants who participated in the study, as well as the research staff at each participating institution. The authors also thank  Christelle Perdrieu  and  Samir Dahbane  from the  Clinical Development Unit at the NestleResearch Center  for assistance with trial management and  Philippe Steenhout , Medical Director at NestleNutrition, for input on study design and assistance with trial supervision.
Magnetic measurements. Magnetization measurements were carried out on a vibrating sample magnetometer (PPMS, Quantum Design, Inc. , CA, USA) on suspensions of CoIONPs at 10 mM iron + cobalt concentration in acidic citrate medium. The data were corrected from the diamagnetic contribution of the acidic citrate buffer and of the sample holder. The field-dependent magnetization curves were measured at 310 K in the range between 0 and 3 × 10 4 Gauss.