dataesr/scientific-paragraphs-categorization huggingface dataset:
Given the experiment's coordinate system, the rotation can be expressed using an axis-angle representation: i n j ,arccos ⋅ ( ) ( ) Where i and j are the unit vectors in the x (frontal axis) and y (longitudinal axis) directions, respectively. This rotation was applied to each trajectory, producing a reach with xand z-axes, or the frontal and sagittal axes, as the primary directions. Preprocessing. Missing data due to marker occlusion from each trajectory were replaced using linear interpolation with the interp1d function from SciPy  (Virtanen et al. , 2020). The locations of the missing data were recorded for visual inspection in a subsequent step. Then, a second-order low-pass Butterworth filter (250 Hz sampling frequency, 10 Hz cutoff frequency) was applied to each trajectory dimension. Velocity along each axis was calculated using a central difference method and was smoothed using the same Butterworth filter.
To address this issue, each dimension of each trajectory was parameterized using a third-order B-spline (Figure  2  Preprocessing; Gallivan and Chapman, 2014;  Ramsay & Silverman, 2005 ) with Python's SciPy library  (Virtanen et al. , 2020). The resulting B-spline function maps points of the trajectory onto their respective time stamps within a given MT. Using the parameterized trajectory, each trajectory coordinate was sampled using 100 evenly spaced time stamps between movement initiation and termination. This approach retains the temporal aspects of each reach while producing an equal number of data points across different trajectories, enabling spatial averaging. Finally, the fitted trajectories were centred at the origin and the x-coordinates of the trajectory corresponding to the target on the left were inverted so that all movements were directed to the positive x direction.
Subsequently, a third-order B-spline was applied to the coordinates of each axis to parameterize the reach trajectories. The black points were based on the original trajectory data whereas the red points were sampled from the B-spline function. Trajectory Analysis: Each trajectory starts at the home position (filled blue circle) and ends at one of the target positions (blue, unfilled squares). Trajectories from each participant within each unique combination of conditions (per target location and per gaze direction) were compiled and averaged. The cued (green) and uncued (red) average trajectories corresponding to the same target location were compared, where the B-spline function was integrated to identify the area between their respective x trajectories. area for the uncued target was subtracted from that for the cued target to derive the area between the two curves.
If the gaze cue had a facilitatory effect on the aiming movement, the cued area should be larger than the uncued, resulting in a positive area between the two curves. Alternatively, an inhibitory effect would result in a negative area. Statistical analysis. Repeated measures analysis of variance (ANOVA) was conducted on MT and RT with two withinsubject factors, SOA (3 levels: 100, 350, and 850 ms) and target (two levels: cued, uncued) using R's ez package  (Lawrence, 2016). Greenhouse-Geisser corrections were applied to factors that did not satisfy the sphericity assumption and are indicated by the decimal values in the reported degrees of freedom. For significant effects, post hoc simple contrasts with Tukey's corrections were calculated to determine the source of the effect. Another repeated measures ANOVA was conducted on trajectory areas with SOA (3 levels: 100, 350, and 850 ms) and trajectory segments (5 levels: 0%-20%,.
| Thermodynamic hydration properties by mixing calorimetry The hydration energy under mixing conditions by immersion of a powder in water is measured by mixing microcalorimetry technique. Hydration energy of powder by liquid or vapor water could (1) F = -D f ⋅ c x (2) M t M eq = 1 - 6 2 ∑ i w a i ∞ ∑ n=1 1 n 2 exp -D ⋅ n 2 ⋅ 2 ⋅ t a 2 i (3) ln M eq -M t = ln 8M eq - 2 ⋅ D f e 2 ⋅ t (4) WHC (g∕gdb) = weight of precipitate paste (g) -Sample weight (g) × 100 Sample weight (gdb) × 100 -solubility (5) %Solubility = weight of dried supernatant (g) × 100 Sample weight (gdb) (6) SI = 100 × V f -V i ∕V i TA B L E 1 Isotherm equations for experimental data fitting Model Mathematical expression GAB X = X 0 Ka w /[(1-Ka w )(1-Ka w +CKa w )] Y&N M S = A ( + ) + B M D = A ( + ) + B RH max A = w V ads D B = w V abs D = RH RH+(1-RH)E = -ERH E-(E-1)RH + E 2 (E-1) ln E-(E-1)RH E -E + 1 ln 1 -RH = RH E = e - q 1 -q l kg T Freundlich X = KP 1/n Smith X = A + (B log(1-a w )) Note: For GAB equation; X is the moisture content, X 0 is the monolayer moisture content, C and K the GAB model constants.
, 2002)  and the dimerization of the 33 kDa AOX isoform by the oxidant, diamide  (Holtzapffel et al. , 2002). Most importantly was that the quantification by densitometry of independent gels (with equal loading of proteins, supplementary data I) showed higher amount of AOX (for both the 66 kDa and 33 kDa AOX) in wild type plants while it was lower in L-GalLDH-RNAi plant lines (Figure  1D ). Taken together, these data suggest that the AOX molecules in wild type mitochondria are significantly inhibited by L-GalL due to the L-GalLDH activity. In the plant lines, the suppression of L-GalLDH enzyme could, in turn, prevent AOX inhibition by L-GalL. Interestingly, the 8-14 plant line, which has the higher L-GalLDH suppression (Figure  1B ) showed the lower level of oxidized AOX (Figure  1D ). We examined the respiratory capacity of mitochondria purified from heterotrophic tissues (fruits) of other plant species and using other respiratory substrates and inhibitors.
Cytc oxidase is a main factor affecting FAD recycling during AsA synthesis We followed changes in fluorescence of exogenously supplemented FAD in the presence of L-GalL and then assessed the effect of inhibitors on such changes. It was recorded a variation of FAD fluorescence (about 2500 Units) following incubation with L-GalL (Figure  2D ). It indicates that FAD redox state changes during AsA synthesis. All inhibitors tested in this study decreased the effect of L-GalL in FAD fluorescence, having the Cytc oxidase inhibitor, azyde, the highest effect (Figure  2D ). These data may suggest that the FAD redox state during AsA synthesis is basically controlled by Cytc oxidase, but other respiratory components could be also involved, albeit indirectly.
By measuring the H 2 O 2 level, using the Amplex Red method, an increased H 2 O 2 formation was detected within 5-15 min following incubation of mitochondria with L-GalL, having maximal H 2 O 2 increases between 5-20 mM L-GalL whereas response was extremely low or non-detected at concentrations below 5 mM L-GalL (supplementary data IV). We explored the possible sources of mitochondrial ROS during AsA synthesis. We also demonstrate the lower production of H 2 O 2 in fruit mitochondria from L-GalLDH-RNAi plant lines, which was consistent with an increased AOX respiration during AsA synthesis (supplementary data V). However, despite these mitochondria showed decreased L-GalLDH activity (lower Cytc reduction rate), their abilities to produce AsA and alter FAD redox status were similar to that of wild type fruit mitochondria (supplementary data V).
Bioinformatic analysis Progenesis QI for Proteomics Software V. 2. 0 (Nonlinear Dynamics, Newcastle, UK) were used to spectra processing and database searching conditions. The analysis were performed using following parameters: Apex3D of 150 counts for low energy threshold, 50 counts for elevated energy threshold, and 750 counts for intensity threshold; one missed cleavage, minimum fragment ion per peptide equal to two, minimum fragment ion per protein equal to five, minimum peptide per protein equal to two, fixed modifications of carbamidomethyl (C) and variable modifications of oxidation (M) and phosphoryl (STY), and a default false discovery rate (FDR) value at a 4% maximum, peptide score greater than four, and maximum mass errors of 10 ppm. The analysis used the Carica papaya v. 0. 4 protein databank from Phytozome (https://phytozome.
jgi. doe. gov/). Label-free relative quantitative analyses were performed based on the ratio of protein ion counts among contrasting samples. After data processing and to ensure the quality of results, only proteins present in 3 of 3 runs were accepted. Furthermore, differentially abundant proteins were selected based on a fold change of at least 1. 5 and ANOVA (P ≤0. 05). Functional annotation was performed using Blast2Go software v. 3. 4  (Conesa et al. , 2005).
regulated and down-regulated proteins represent those having a fold change of at least 1. 5 (ANOVA, p<0. 05) relative to the treatment without L-GalL (control). As criteria for reproducibility, only proteins identified with differential abundance were included in the table. The bioinformatic analysis used the Carica papaya v. 0. 4 protein databank from Phytozome and the functional annotation was done using Blast2Go software v. 3. 4.
ACKNOWLEDGEMENTS The authors (V. S. , M. C. , C. F. B. , A. R. F. , M. G. S. , and J. G. O. ) wish to acknowledge the  Conselho Nacional de Desenvolvimento Científico e Tecnológico  ( CNPq-Brazil ) for research fellowships. The authors L. M. M. M. and A. J. D. C. were granted with a  CAPES  ( Coordenação de Aperfeiçoamento de Pessoal de Nível Superior )-PNPD; G. M. C. S. was granted with a  FAPERJ (Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro )-PD; D. B. S. , A. S. H. , L. A. S. P. , and A. V. O.
This paper provides experimental evidence on long-term impacts for children exposed at different stages of early childhood and school-ages to five years  (2000) (2001) (2002) (2003) (2004) (2005)  of a Honduran CCT program, the Programa de Asignación Familiar (PRAF-II). This CCT, similar in design to other programs in the region, provides a unique opportunity to study long-term impacts because it was randomized across 70 municipalities and, unlike most other randomized CCT evaluations such as Mexico's PROGRESA, control municipalities were never phased into the program. Exploiting the municipality-level randomized assignment, we use individual-level data from the national census, collected 13 years after the program began (and thus eight years after it ended), to analyze impacts of the CCT on individuals in cohorts spanning nearly 25 years.
As no identifiable exogenous variation in program implementation or later program exposure exists, we abstract from such effects in this paper, as is done in most studies analyzing long-term impacts. However, the census data do provide sufficient power to study program impacts separately across groups likely to face different constraints in both the shortand long-term in the Honduran context, and thus provide insights on the potential importance of other constraints. Specifically, we analyze impacts by sex and ethnic background (nonindigenous versus indigenous), resulting in four distinct demographic groups. Because no other variables in the census can reasonably be considered exogenous 13 years after the start of the program, these are the only four groups for which we can examine heterogeneity at the individual level without introducing the typical concerns regarding the use of specification searches in heterogeneity analysis.
Data and Methodology The principal data source is the XVII Honduran National Population and Housing Census of 2013. 8 For complementary analyses, we also use the 1988 and 2001 national censuses, and the short-term program evaluation data collected for PRAF-II. For the main analyses in 2013, we limit the census sample to all individuals born in the 70 targeted rural municipalities regardless of their current residential location. For the age cohorts we study, municipality of birth together with the municipal-level randomized program assignment provides an exogenous indicator of program exposure not influenced by subsequent domestic migration or geographical sorting that may have occurred during or after the program. 9 In addition to including other typical 7 Program rules were altered in 2003, removing this possible fertility incentive, so that the short-term fertility increase most likely affected only those born in the first years after the start of the program, i.
To estimate program impacts on international migration itself, we incorporate the migrants into the individual-level census sample by assuming they were born in the municipality where the household from which they migrated is located in 2013. 10   An implication of targeting areas with the highest malnutrition rates in the country was that PRAF-II operated in regions with a high share of indigenous people. While the indigenous in Honduras comprise only 6. 5 percent of the national population, they make up 39 percent of the main analysis sample (individuals ages 6-29 in 2013 and born in one of the 70 program municipalities). We classify as indigenous all individuals who identify themselves in the census 11 as indigenous, Afro-Honduran, or black-95 percent of whom in the sample are Lenca. 12   Given randomized assignment and results in appendix C that provide evidence of balance on observables across treatment arms using data from the 1988 and 2001 population censuses, our main methodological approach is to estimate a single-difference ITT model 𝑌 !" = 𝛼 + 𝛽 ! 𝐺 !! + 𝛽 ! 𝐺 !! + 𝛽 ! 𝐺 !! + 𝛾𝑋 !" + 𝜖 !" 1 where Y ij is the outcome of interest measured in the 2013 census for individual i, born in municipality j, and G 1j takes the value 1 if municipality j benefited from the (basic) CCT and 0 otherwise.
27 Earnings data is available in the national annual labor survey in Honduras, collected in both rural and urban areas covering all of Honduras, which importantly also includes information on the municipality of birth. Acknowledging various caveats for analyses using such data (including that it is not representative at the municipality level), in appendix E we pool data from multiple rounds  (2010) (2011) (2012) (2013) (2014) (2015) (2016)  to analyze impacts on labor market activities and earnings. We find no strong domestic labor market returns to the increased human capital engendered by the CCT for the older cohorts ages 19-26 years.
Participants and recruitment The procedures for recruitment and data collection in the Enquête Littoral Souffle Air Biologie Environnement (ELISABET) cross-sectional survey (ClinicalTrials. gov Identifier: NCT02490553) have been described previously  (18). In brief, male and female participants aged from 40 to 64 were selected from electoral rolls by random sampling, with stratification for gender, age, and city (Lille or Dunkirk urban areas, in northern France) between 2011 and 2013. A registered nurse administered the study questionnaire in the participant's own home. During the visit, the nurse also took anthropometric measurement and collected a sample of peripheral venous blood. The study protocol was approved by the local institutional review board (CPP Nord Ouest IV, Lille, France; reference number: 2010-A00065-34), in compliance with the French legislation on biomedical research.
Results A total of 3275 participants were included in the ELISABET survey. We excluded 174 participants with chronic kidney disease, 21 participants with an history of haematological disorders, 178 participants who reported taking antidiabetic medication, 152 participants with missing data for Hba1c, cadmium or at least one of the covariates, and one participant with an outlier value for. Hence, 2749 participants were analysed (Figure  1 ). The characteristics of the 2749 eligible participants are summarized in Table  1. Current smokers (n=518) were younger, comprised a lower proportion of females, and had a lower educational level than never-smokers. The mean blood cadmium level were 2. 5 times greater among current smokers than among former and never-smokers (p<0. 001). Similarly, HbA1c levels were higher in current smokers than in former smokers (by 0.
Acknowledgements The authors thank the  CHRU de Lille (Lille University Hospital) , the  Université de Lille , the  Institut Pasteur de Lille , and the  Centre Hospitalier Général de Dunkerque ; the nurses, physicians and secretarial staff of the  Université de Lille  and the  Institut Pasteur de Lille ; and the  Service de Médecine du Travail , the  service de Biologie Spécialisé , and the  laboratoire d'Analyses Génomiques of Institut Pasteur de Lille ; the department of biology and the department of pulmonology of the  Centre Hospitalier Général de Dunkerque ; the  Institut de Biologie et de Pathologie of the CHRU de Lille  and the  Centre Universitaire de Mesures et d'Analyses (CUMA) of the University of Lille. The authors also thank the  French Ministère de l'Enseignement Supérieur et de la Recherche , the  Hauts de France Region  and the  European Regional Development Fund  for their financial support.
Funding information The  CHRU de Lille  sponsored the ELISABET survey. This work was funded by the  Nord Pas-de-Calais Region Council  and the  European Regional Development Fund (ERDF-FEDER  Presage  N°36034 ) as part of the  CPER Institut de Recherche en ENvironnementIndustriel (IRENI)  programme. This work is a contribution to the CPER research project CLIMIBIO. The authors thank the  French Ministère de l'Enseignement Supérieur et de la Recherche , the  Hauts de France Region  and the  European Funds for Regional Economic Development  for their financial support to this project. This work is a contribution to the CPER research project CLIMIBIO.
(  2018 ). The samples were heated from 20 to 200 °C at a heating rate of 5 °C/min. Melting temperature (Tm) was defined as the offset temperature of the melting endothermic peak (Appendix: Fig. A1 ). The measurements were done in duplicate (relative error: 10%) and were compared to data in the literature (Appendix: Fig. A2 ). Crystalline structure DSC analysis in excess water was performed on the extruded products in order to verify if all starch crystallites were molten by extrusion process. The existence of residual crystalline structure can be indicated by the presence of so-called residual gelatinization endotherm in DSC thermogram. The composites were ground into a fine powder (< 250 µm) using a cryogrinder. The sample (10 mg) and deionised water (40 mg) were directly weighed in a pan and hermetically sealed.
Image analysis Image analysis was done for at least three plane projection images of three spots in the composites. It was performed using Matlab software to determine the median particle width (D50), total area and total perimeter of protein aggregates. Firstly, CLSM images were digitised by applying a grey level threshold obtained with a k-mean algorithm  (Jain, 2010). The total area of the particles and the total perimeter of their interface with the matrix were then determined. The starch-protein interface index (Ii) was computed as the ratio of the total aggregate perimeter to the square root of the total aggregate area. Granulometry analysis was subsequently performed using mathematical morphology operations  (Devaux, Bouchet, Legland, Guillon, & Lahaye, 2008; Le Bleis, Chaunier, Montigaud, & Della Valle, 2016).
Mechanical properties Extruded materials were conditioned at a relative humidity of 59% at 20 °C for two weeks in order to obtain a uniform moisture distribution in the material (12+0. 5% wb; Appendix: Sorption isotherm measurement, Fig. A3 ). The mechanical properties of specimen strips (th x 100 x 10 mm 3 ) were determined by a three-point bending test mounted on a dynamometer (Adamel Lhomargy, France). The thickness (th) of specimens was measured at three locations with a Vernier caliper. The support span (L) was 40 mm and the crosshead speed was 100 mm/min. The tests were performed until specimens broke. Engineering stress σ (Pa) -strain ε (%) curve was derived from the force-crosshead displacement data as follows: # = $% &' ( ) (4) * = +,' ( ) ( 5 ) where F is the force (N), h is the specimen width (0.
Study Population Critically ill children between 1 and 16 years old were consecutively enrolled at the time of admission to the PICU if they were mechanically ventilated and an admission urine sample was available within 48 hours of PICU admission. Children who were on chronic steroid or immune suppressant treatment were excluded. Data were obtained from the clinical health records. Healthy children, recruited from the local community, were eligible if they were well, had a normal healthy diet, and had not received antibiotics in the prior 3 months. Approval for the study was granted by the East Midlands-Nottingham 2 Research Ethics Committee for recruitment from the PICUs at Cambridge University Hospitals NHS Foundation Trust, Great Ormond Street Hospital NHS Foundation Trust, and Imperial College Healthcare NHS Foundation Trust and from the City Road and Hampstead Research Ethics committee for recruitment of healthy children in the Cambridge vicinity.
H-NMR Spectroscopy Fecal water and urine samples were prepared for 1 H-NMR Spectroscopy according to published protocols  (12). Acquired spectroscopic data were processed using the TopSpin 3. 1 software package (Bruker Biospin, Rheinstetten, Germany). Data processing was undertaken using Matlab (Version 8. 3. 0. 532 R2014a; Mathworks, Natick, MA). Further details are given www. ccmjournal. org e729 in supplemental methods (Supplemental Digital Content 1, http://links. lww. com/CCM/E693).
Statistical Analysis Multiple linear and logistic regression analyses were applied using the Statistical Package for the Social Sciences Version 21 (SPSS Statistics 22, IBM Corp. , Armonk, NY). Categorical variables were analyzed using chi-square and Fisher exact tests as appropriate. Continuous variables were compared using two-sided t tests (for parametric variables) and the Mann-Whitney U test (nonparametric variables). A false discovery rate (FDR) was used to adjust for multiple metabolite testing. Metabolites with FDR less than 0. 05 were considered significant. Multivariate beta diversity analysis between groups, including age, gender, and diagnostic category, was performed using R studio and the Statistical Package for the Social Sciences (SPSS Statistics 22, IBM Corp. ). All presented p values were corrected for multiple comparisons using the Benjamini-Hochberg FDR method.
Aspects of the work were funded by an  Imperial College Biomedical Research Centre  award (to  Drs. Holmes  and Pathan), the  Evelyn Trust  (to  Drs. Parkhill  and Pathan), a  Wellcome Trust Core Informatics Award  (to  Dr. Parkhill ),  Great Ormond Street Hospital Children's Charity  (to  Drs. Peters  and Ramnarayan), and  a Levi-Montalcini  award from the  European Society of Intensive Care Medicine  (to  Dr. Pathan ). The research was supported by the  National Institute for Health Research Biomedical Research Centres based at Cambridge University Hospitals National Health Service (NHS) Foundation Trust, Great Ormond Street Hospital NHS Foundation Trust, Imperial College Healthcare NHS Trust , and  Imperial College London. Dr. Rodrigues Sabino 's institution received funding from  National Institute for Health Research Imperial Biomedical Research Centre Institute of Translational Medicine and Therapeutics Call for Experimental Medicine Proposals.
, 2014; Maher et al. , 2016). Similarly, several deleterious effects have been reported, such as inflammatory syndrome, oxidative stress, DNA damage and cognitive disturbances  (Babadi et al. , 2012; Barhoumi and Dewez, 2013; Huang et al. , 2014; Sadeghi, Yousefi Babadi and Espanani, 2015; Sheida et al. , 2017). However, to date, and despite numerous investigations by worldwide researchers, the effects of NPs or the mechanisms by which NPs can interact in the body are not fully understood. Interestingly, in 2015, the European Food Safety Authority (EFSA) published a report on "the scientific opinion on the re-evaluation of iron oxides and hydroxides (E172) as food additives". They concluded that an adequate assessment of the safety of E172 could not be carried out because a sufficient biological and toxicological database was not available  (Opinion, 2015).