dataesr/scientific-paragraphs-categorization huggingface dataset:
DATA AVAILABILITY STATEMENT Wind datasets used in the current study are available by http://www. meteo. fr/ for the ARPEGE dataset and by http://www. hnms. gr for the meteorological stations. The DYNED-Atlas data base for the Mediterranean Sea (https://doi. org/10. 14768/2019130201. 2)) is available at https: //www. lmd. polytechnique. fr/dyned/.
Statistical Analysis Data were analyzed using the Statistical Package for the Social Sciences (SPSS Version 22. 0, Chicago, IL, USA). Descriptive analysis, including frequency (percent) and mean (standard deviation), was performed to present an overview of the findings. Fisher's exact test was conducted to determine the associations between knowledge and practice scores by demo-graphic. Mann-Whitney U test was used to compare the attitude scores by demographic. Spearman correlation was used to determine the correlation between knowledge, attitude, and practice scores with age. All p-values ≤ 0. 05 were considered statistically significant.
The aforementioned findings suggest that the ongoing intensive health-awareness campaigns by the local government and the Ministry of Health have been effective in encouraging the community to take appropriate actions to reduce the spread of COVID-19. This study had several limitations that must be acknowledged. Firstly, the collected data were self-reported by the respondents through an online questionnaire. Self-reported data cannot be independently verified and may be prone to response bias, such as exaggerated or understated responses by individuals. Secondly, the poorly chosen distribution channels through social media can lead to biased data and limit the generalizability of the findings. Finally, most of the respondents were highly educated and from the Makkah region. Vulnerable people in Saudi Arabia, such as rural people with low educational levels, are more likely to have poor knowledge, negative attitudes, and inappropriate preventive practices.
Materials and Methods Population The multicenter, longitudinal ECLIPSE cohort study (Clinicaltrials. gov NCT00292552) was conducted to identify surrogate markers of COPD progression. 19 2164 current or ex-smokers (≥10 pack-years) with Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage 2 to 4 and 582 smokers or never smokers with normal lung function who served as controls were recruited from 12 countries. 20, 21 atients' characteristics, blood samples and pulmonary function tests were obtained at baseline. Chest CT-scan was performed on all participants with the following protocol: 120-kV peak, 40 mA, and 1. 00-or 1. 25-mm slice thickness, at full inspiration. All subjects on whom a valid CT-scan slice at T12-L1 was obtained, to assess liver mean CT attenuation, were included.
Liver Density Assessment Liver density was quantified by measuring mean organ attenuation in Hounsfield unit (HU) by the same investigator using the body composition analysis platform of the Institut universitaire de cardiologie et de pneumologie de Québec and a validated image analysis software (Slice-O-Matic, Tomovision, Montréal, Québec, Canada) according to standardized techniques. 22, 23 A standardized segmentation protocol was followed by the evaluator consisting in using an automated segmentation tool to identify the liver perimeter (Figure  1 ) and then manually remove all potential artefact such as the gall blatter or the portal vein. To ensure validity, a sample of all segmented images were randomly selected and redone by the same evaluator to assess for intra-observer variation.
03%. 34 oreover, intra and interobserver variabilities exist in the quantification of FLD from a biopsy. 35 Noninvasive tests (including biological scores and imaging) are cheaper, more easily repeatable, and lead to less interobserver variability, severe adverse events, refusal and bias than biopsy. 34 sing imaging data already available to the clinicians, screening for FLD could be performed in several patients with COPD. There are currently two methods to assess liver density from a CT scan. In the present investigation, we measured the mean organ attenuation with standardized segmentation which is more complex compared to the multiple region of interest (ROI) methods,  17  but encompasses a larger area of evaluation which may improve the assessment in case of focal fatty infiltration. 36, 37 In our experience, there is little variation between these techniques as long as they are performed on non-enhanced CT.
Funding The ECLIPSE study was funded by GlaxoSmithKline (GSK). GSK had no role in the design of the study, analysis, interpretation of results, writing of the article or approval of the article. DV was a recipient of research fellowship grants from the Fonds de la Recherche Québec -Santé, from Institut Universitaire de Cardiologie et de Pneumologie de Québec-Université Laval and from the Agir pour les maladies Chroniques foundation. J-PD is the scientific director of the International Chair on Cardiometabolic Risk, which is based at the Faculty of Medicine, Université Laval. FM holds a GSK/Canadian Institute of Health Research (CIHR) Research Chair on COPD at Université Laval.
Subjective Qualitative Evaluation of Image Quality All CTPAs were randomized, anonymized, and independently evaluated on standard LCD monitors by two radiologists with 3 and 7 years of experience, respectively, who were blinded to all patient data and reconstruction parameters. Readers were asked to subjectively rate the overall image quality on 0. 5-mm (AiCE) and 1-mm (AIDR 3D) axial slices using a five-point scale ranging from 1 to 5: 1 = very poor image quality with no diagnostic information, 2 = low image quality that reduces the confidence in making diagnosis, 3 = moderate image quality sufficient to make diagnosis, 4 = good image quality clearly demonstrating anatomical structures, 5 = excellent image quality enabling excellent differentiation of even small anatomical structures. Observers also reported their diagnostic confidence to detect or exclude central, segmental, and subsegmental pulmonary embolic defects: 1 = no confidence; 2 = confident; 3 = very confident.
00-0. 20 as poor, 0. 21-0. 40 as fair, 0. 41-0. 60 as moderate, 0. 61-0. 80 as substantial, and 0. 81-1. 00 as excellent agreement. Subgroups analyses were also conducted according to the BMI (<25 kg/m 2 , 25-30 kg/m 2 , >30 kg/m 2 ) in order to evaluate the impact of weight on image quality and radiation dose. All statistical tests were performed using the STATA ® software (version 13; StataCorp; College Station, TX, USA) and Excel Software (version 2016; Redmond, WA, USA).
The strength of the present study was that our sample of 93 patients was larger than prior studies using DLR. To our knowledge, this is the only and largest comparative study to date evaluating DLR versus hybrid-IR for CTPA. Another important finding from the present study is the increased efficacy in image noise management reported for large and heavy patients with DLR. Indeed, even though SNRD and CNRD inevitably decrease in heavier patients due to the photo starvation, our study suggested a slower decrease with DLR than with hybrid-IR  [33, 34]. We hypothesize that the artificially decreased tube current in the training dataset mimics the photon starvation in large patients, thus helping to explain our findings. Additionally, our increasing experience with DLR (AiCE) has changed our approach to CTPA as most of the radiologists in our institution now use lung reconstructions for assessment of acute distal PE.
Seawater Mg:Ca and Sr:Ca ratios are biogeochemical parameters reflecting the Earth-oceanatmosphere dynamic exchange of elements. The ratios dependence on the physical and chemical environment, facilitates their use as tools in marine sciences. It has been ~130 years since the last global survey. Here, we present a new measured single-laboratory global dataset, combined with previous data, to test the assumption of limited seawater Mg:Ca and Sr:Ca variability across marine environments. There is high variability in open ocean upwelling and polar regions, shelves, neritic, and river-influenced areas, where Mg:Ca and Sr:Ca range ~4. 40-6. 40 mmol:mol and ~6. 95-9. 80 mmol:mol, respectively. Open-ocean seawater Mg:Ca is semi-conservative (~4. 90 to 5. 30 mol:mol), while Sr:Ca is more variable and non-conservative (~7.
Results The present study measured modern seawater Mg:Ca and Sr:Ca ratios in more than 1100 samples from 79 research cruises and expeditions worldwide, which were compared with published data, and then merged into a master databank deposited at the NOAA National Center for Environmental Information (NCEI) under Accession Number 0171017 in http://accession. nodc. noaa. gov/0171017 (SI Appendix 1, 2). The seawater Ca, Mg, Sr, Mg:Ca, and Sr:Ca data followed normal distribution curves (Anderson-Darling P < 0. 005). The following ranges and observations emerged from separating the data using quartiles and confidence intervals, as well as graphical representations. The distribution of seawater Mg:Ca in the euphotic zone varied between 4. 95 and 5. 30 mol:mol with some peaks up to 5. 40 mol:mol in all open ocean settings at all latitudes, while seawater Sr:Ca was more variable, from 7.
Cross plots of Ca, Mg, and Sr vs TA reflected the ocean water masses and interior processes shifting the ratios via the hydrothermal, calcification, and dissolution effects at large (Fig. 3a ). Cross plots of Mg and Sr vs Ca, and of Sr vs Mg showed how all elements correlated with each other (r2 values between 0. 60 and 0. 97 in all cases; Fig. 3b ), with deviations being explained by the different ecosystems water masses and processes such as river discharge (dilution and minerals addition), glacier impact (meltwater discharge, leading to dilution but also weathered minerals), hydrothermal impact (heavy metals and minerals addition), coastal processes (consumption/dissolution), and upwelling (minerals addition, consumption/dissolution) (Fig. 4d ). In general, the newly measured dataset greatly expanded literature data in the ranges, with no major disagreements, in terms of values around the same Longhurst provinces/regional areas, and processes (Fig.
This was very obvious when dassifying data as "Coastal Seas" and "Open Ocean" to show the broad vs narrow ranges, and the ratios non-conservative vs semi-conservative behavior (Fig. 4c ). The ratio groupings were compared to recent reconstructions of seawater Mg:Ca and Sr:Ca ratios (3, 7) from younger Earth history suggesting that the increase in ratios during the Neogene (20 million years) is within the same range of variability shown in modern ocean elemental ratios of most regions investigated here (Fig. 5 ). Surprisingly, our dataset ranges agreed well with the range calculation using tropical shelf echinoderms ossicles  (23) , where it was concluded that modern seawater Mg:Ca ranged from 4. 0 to 6. 4 mol:mol. This is in total agreement with our measurements (Fig. 4, 5 ), despite the published study  (23)  using only one group of organisms.
Additionally, our dataset ranges also agreed with a model estimation based on modified equations from foraminifera calibrations  (24) , which shows that modern seawater Mg:Ca ranges from 4. 60 to 5. 70 mol:mol. When we compared the modern ocean Mg:Ca variability to experimental data describing the correlation between seawater and biogenic carbonate Mg:Ca ratios (Fig. 5a ), it emerged that the natural variability of seawater Mg:Ca can be responsible for significant changes in the Mg:Ca ratio of biogenic carbonates. For example, carbonates of scleractinian corals doubled their skeleton Mg:Ca ratio from 0. 15 to 0. 30 mol:mol when seawater Mg:Ca increases from 3. 80 to 6. 70 mol:mol (Fig. 5a ), while other organisms also had significant increases. This can be further related to physiological traits, organism adaptation, enhancing uptake and skeletal growth with reduction in the consumed element in the surrounding seawater.
3, 4 ). The assumption of homogeneity in elemental ratios as currently used in marine sciences is mostly applicable to open ocean conditions (not in all cases), additionally to the deep ocean, and, in particular, to bottom water masses or at mid-ocean ridge flanks. Yet, many samples used in e. g. paleo-reconstruction studies have been obtained in shelves and marginal seas aiming to reconstruct open ocean or extrapolating results to the global ocean (SI Appendix Fig. S2 ). These studies are mostly focused on temporal variability around a fixed location, while, our dataset, sheds light on the spatial ratios' variability at a fixed point in time, to then consider the likely variability that occurred in the past. The open and deep ocean represent the majority of the oceanic water by volume, but many key biogeochemical processes impacting the ratios directly or indirectly, take place in continental margins, including slope, shelf, and neritic areas, where e.
3a ). The TA and DIC relation, in particular, with seawater Mg:Ca, was magnified in continental margin upwelling areas, which in this dataset corresponds to the east Pacific in the California Current (NOAA cruises) (Fig. 3, 4 ). In this particular case, seawater has a higher acidity (higher DIC and CO2, lower pHtotal), which in turn dissolves carbonates faster due to a shallower saturation horizon. This results in overall higher seawater Mg:Ca and Sr:Ca ratios with respect to the reference IAPSO standard, with a few exceptions. As a general rule, coastal sea samples in the Indian, Pacific, and Atlantic Ocean, exhibited higher seawater Mg:Ca and Sr:Ca ratios than open ocean regions, driven by a combination of biological and chemical processes (Fig. 4c ). Regions of riverine and glacial meltwater input influence TA concentrations, acting as competing sources and sinks.
Freshwater discharges act to dilute seawater carbonate and bicarbonate (the principal components of seawater TA), lowering salinity, and thus reducing TA. However, these water sources could contribute dissolved minerals that increase TA, and indirectly shift seawater Mg:Ca and Sr:Ca ratios, as seen in this dataset, e. g. in the river discharge and glacial melting samples around the Atlantic Ocean (Fig. 3 ). In polar regions, carbon cycling in sea ice brines leads to the abiotic precipitation of carbonates in the ice, which can be released to the upper ocean during ice melt, shifting also seawater Mg:Ca and Sr:Ca ratios. This, at the local/regional level, is an additional TA source when the precipitated carbonate is also dissolved. TA is semi-conservative and can be used as a tracer for ocean circulation and mixing as different water masses have different TA signatures as well as seawater Mg:Ca and Sr:Ca ratios (assuming semi-conservative behavior in the open ocean).
Our dataset suggests that the application of constant seawater elemental ratios needs to be carefully considered and could be a confounding factor in experimental work, if the regional and ecosystem dimensions are not considered. Another challenge is that modern interpretations of past seawater conditions rely on the fossil carbonate record being related to a homogeneous seawater composition  (23, 24, 41) , but they do not account for the environmental conditions and variability experienced by those organisms. Factors such as a life history in varying seawater ratios, or organisms living in ancient coastal regions or estuaries with seawater elemental ratios different from the assumed open ocean conditions, are two examples where fossil signals could be potentially miss-interpreted. For instance, the projected variability of calcite Mg:Ca and Sr:Ca ratios in many organisms over the range of modern ocean seawater ratios is between 1 and 2 units, which is equivalent to a temperature range greater than 5 °C for foraminifera (3) (Fig.
5 mol:mol could be applied for the last 60 million years. This correction would mostly agree with other paleoreconstructions based on different organisms and techniques  (24). Based on our dataset, we support this error correction, and further propose that a seawater Mg:Ca confidence interval of between 1 and 1. 5 mol:mol may be more appropriate to include most environmental and ecosystem-based variability. For seawater Sr:Ca, this goes up to 1. 9 mmol:mol (Fig. 5 ) to account for possible environmental variability. The notion that different procedures to reconstruct seawater ratios resulted in secular variability for different ecosystems seems logical when comparing the various methods and marine taxa, which consequently reflect the inhabited environment (Fig. 5 ). Published studies and equations use benthic/planktonic foraminifera, bivalves and belemnites, turritellid snails, CCVs, halite fluid inclusions, and echinoderm ossicles, to reconstruct seawater ratios.
After 1 year in storage, no signs of seawater evaporation were observed (< 0. 05% Mg/Ca and Sr/Ca ratios variability)  (5). At the Institute of Geosciences, Kiel üniversity, Germany, all samples were analyzed in the same laboratory and machine by the same person for Ca, Mg, Sr with simultaneous data acquisition using an inductively coupled plasma -optical emission spectrometer (ICP-OES) SPECTRO Ciros™ CCD SOP. Samples were 50-fold diluted with 2% (v/v) freshly subboiled in HNO3 and introduced with a GE Seaspray™ micro-nebulizer and thermostatized Cinnabar™ cyclonic spray chamber. Sample preparation was performed under Class-100 clean bench conditions with ultrapure reagents (Elga Labwater). The following emission lines were selected: Ca: 317. 933 (II); Mg: 279. 553nm (II); Sr: 407. 771nm (II), 421.
552nm (II), and measured simultaneously within the same preselected acquisition interval ("Phase 3"). A combined intensity calibration and drift-correction procedure using IAPSO standards  (46, 47)  was applied for data processing (Appendix 4). Every batch of 6 samples was bracketed by an IAPSO measurement for normalization to Mg:Ca = 5. 140 mol:mol and Sr:Ca = 8. 280 mmol:mol. A stepwise linear drift correction was applied over a batch of 6 samples during all the analyses. Then, every second batch of 6 samples, a one sample replicate measurement was done from the previous batch. The final data are used as drift-corrected after applying the normalization factors for Mg:Ca and Sr:Ca ratios following the stepwise drift-correction (see Appendix 4). Results were normalized to an external standard (IAPSO, ORIL, ü.
K. using Mg:Ca = 5. 140 mol:mol, Sr:Ca = 8. 280 mmol:mol). This approach minimizes variability, which re: IAPSO was 0. 6 to 0. 7% overall. Mean uncertainty from duplicate measurements per sample on 33 randomly chosen samples was 0. 1-0. 2 and 0. 1-0. 4 %RSD (1SD) for seawater Mg:Ca and Sr:Ca, respectively (see Appendix 4). This is well below 1% uncertainty for the dataset, which provides confidence in the accuracy of the data. The new measured dataset was complemented with a seawater Mg:Ca and Sr:Ca ratios literature survey (Fig. 4d ; SI Appendix 2). Publications and reports methods sections were screened for data quality and analytical clarity to mine comparable data to our dataset based on standards used, and analytical method/accuracy. We also put together a table on the historical use of seawater Mg:Ca and Sr:Ca ratios in the last 100 years (SI Appendix Table  S3 ).
The final seawater Mg:Ca and Sr:Ca ratios database (Appendix 3) was combined with seawater environmental metadata mined from GLODAPv2  (48, 49) , and used to analyze and classify seawater Mg:Ca and Sr:Ca ratios as a function of environmental variables (Appendix 3). ArcGIS 10. 0 (ESRI 2011) and the 3-D analytical tool "NEAR 3-D analysis" were used to link environmental seawater conditions with the sample's seawater ratios. When the prediction was not sufficiently accurate, the closest value was manually selected. For comparison purposes, the GEMS-GLORI database, despite being compiled from primary and secondary sources, was used to provide a distribution map of seawater Mg:Ca ratios from river mouths/plumes around the world (Appendix 6; SI Appendix Fig. S1 ), but it was not added to the statistical analyses or mechanistic assessments.
Lastly, various paleo proxies' global databases were mined to provide distribution maps of paleo reconstructions (SI Appendix Fig. S2 ), to identify where the majority of the paleo work has been conducted around the world. The seawater Mg:Ca and Sr:Ca ratios were classified by Ocean, Longhurst Province, Ecosystem type, Latitude, Longitude, Depth (in 5 intervals) (Appendix 3), and then by all the metadata (chemistry). Ratios were mapped globally (Fig. 1 ; SI Appendix S1), vs depth and by ecosystem (Fig. 1, 3 ). Ratios were also plotted against each property (Fig. 2 ). Data were tested for normality using the Anderson-Darling test (95% confidence), and element correlations were assessed using Pearson coefficients. The ratios data ranges used were decided using normality curves quartiles Q2 and Q3.
). Extended seawater Mg:Ca ratios data from river mouths can be found in SI Appendix Fig. S1. The final databases are deposited at the NOAA National Center for Environmental Information (NCEI) under Accession Number 0171017 in http://accession. nodc. noaa. gov/0171017(DOI:10. 7289/V5571996). Ca ratios data from river mouths to assess coastal waters can be found in SI Appendix Fig. S1.
work and wrote the paper after all cruises and ICP-OES measurements were finished. K. B. and U. W. measured samples and D. G. S. developed the method and processed the raw data. M. K. , R. B. , and  D. O. B. J. mined literature data and did Fig. s, with M. L. and D. G. S. The following authors collected samples and coordinated work: M. L. , D. G. S. , M. N. M. , A. D. , D. I. R. , D. G. , R. A. F. , M. L. , S. B. , A. P. , M. G. , L. B. , J. C. , J. B. R. , C. P. , S. O. , K. R. , L. M. J. , A. K. , R. W. , O. G. , L. M. , J. B. , C. A. , N. D. , S. Z. , J. L. A. , A. d. L. , R. S. L. , P. J. , B. T. , P. B. D. B. , L. L. , F. E. P. , S. E. H. , X. G. C. , L. C. T. and  J. S. H. Competing  interests: The authors declare no competing financial interests. Data and materials availability: The data presented in this manuscript are available at the  NOAA National Center for Environmental Information (NCEI)  under Accession Number  0171017  in http://accession.
). Extended seawater Mg:Ca ratios data from river mouths can be found in SI Appendix Fig. S1. The final databases are deposited at the NOAA National Center for Environmental Information (NCEI) under Accession Number 0171017 in http://accession. nodc. noaa. gov/0171017(DOI:10. 7289/V5571996). Ca ratios data from river mouths to assess coastal waters can be found in SI Appendix Fig. S1. Fig. 2. Modern ocean seawater Mg:Ca and Sr:Ca ratios versus environmental parameters. Data horizontally classified for seawater Mg:Ca (a) and Sr:Ca (b) ratios as a function of environmental variables (GLODAPv2; 41, 42) from the largest to the smallest dimension, and vertically in five depth intervals of 0-5 m, 5-200 m, 100-1000 m, 1000-2500 m, and +2500 m. Data within the red lines represent literature assumed knowledge of modern seawater ratios.
, 2007; Le Roux et al. 2012; Pratte et al. , 2020). REE occur, often together, in accessory minerals such as phosphates, carbonates, fluorides, and silicates in pegmatites, granites and other metamorphic and igneous rocks  (Tyler, 2004). In addition to these indirect mineralogical identification tools, X-ray diffraction (XRD) mineral analysis can be a valuable complement to geochemical datasets in peat paleodust studies  (Sjöström et al. , 2019). Despite the established use of peat records, methodological questions remain. Peat paleodust studies rarely compare within site deposition rates, or explore links between peatland development, mineral dust deposition and peat accumulation rates (PAR). This leads to a lack of understanding regarding the links between dust deposition and accumulation rates; the role of local factors (i.