dataesr/scientific-paragraphs-categorization huggingface dataset:
Sample A exhibits three, possibly four, metal-rich elongated features, that diagonally cross the portion of the XY plane covered by our dataset. One feature extends approximately from (X, Y) = (-1. 5 kpc, 3 kpc) to (-3 kpc, -1 kpc). A second feature stretches from (X, Y) = (1 kpc, 3. 5 kpc) to (X, Y) = (-1. 5 kpc, -1 kpc), and then continues almost vertically out to (X, Y) = (-1. 5 kpc, -3 kpc). A third feature, which possibly contains multiple segments, extends from (X, Y) = (2. 5 kpc, 1 kpc) to (X, Y) = (1 kpc, -4 kpc). This pattern becomes progressively less evident as we move from Sample A to Samples B and C. In Sample C, the elongated features disappear almost completely, and simply result in an observed asymmetry about the Sun of stars at X 0 kpc, which is typically more metal rich at Y > 0 kpc than at Y < 0 kpc.
2018; Spitoni et al. 2019 Spitoni et al. , 2022a,b;,b; Carr et al. 2022). Future works comparing observations from Gaia DR3 and groundbased surveys to sophisticated theoretical models will be able to provide further insights on the evolutionary processes that shaped the present-day appearance of the Milky Way's disc. Acknowledgements. The authors thank the referee for comments and suggestions that improved the overall quality of the paper. This work has made use of data from the European Space Agency (ESA) mission Gaia (https: //www. cosmos. esa. int/gaia), processed by the Gaia Data Processing and Analysis Consortium (DPAC, https://www. cosmos. esa. int/web/gaia/ dpac/consortium). Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement.
d'études Spatiales (CNES). ARB and ES received funding from the European Union's Horizon 2020 research and innovation program under SPACE-H2020 grant agreement number 101004214 (EXPLORE project). PRF, RD, MGL, and AS are supported by the Italian Space Agency (ASI) through contract 2018-24-HH. 0 and its addendum 2018-24-HH. 1-2022 to the National Institute for Astrophysics (INAF).
Nature database for mass reduction: Osteogenesis and bone remodeling principles mimicry The design of light and stiff mechanical part is an issue that Nature has been facing since millions of years. Numerous stiff and light solutions are present in the database of Nature  [28, 29]. Among these solutions, endoskeletons are widely spread in Nature, especially in animals. Endoskeletons are composed of bones with complex internal structure. Whether it is the internal structure of bones or designed structures seen in Section 1, they are both too complex to be manufactured through conventional manufacturing. Additive manufacturing offers new possibilities for producing this kind of structures. These manufacturing processes allow to consider the design of complex structures mimicking the bone internal structure.
Experimental test results Fig. 12  presents a picture of each printed part with their mass value and the chart of their torsional stiffness. This chart plots the measured torque as a function of the angular displacement applied on the torsion lever, for both sample. A third degree polynomial was best fitted, using least squares method, to the measured data (f 1 for BIMRIM and f 2 for TO). It can be observed that both curves present a progressive increase of their slope during the test. This chart shows that the stiffness of the bio-inspired part, p final , is substantially higher than that of the TO, p TO. The comparison of the two polynomials (f 1 and f 2 ) highlights the fact that regarding their torsional stiffness, the BIMRIM part is 27% stiffer than the TO part.
A recent review estimated that less than a third of eligible child contacts initiated TPT, and less than a third of those who initiated, completed six months of isoniazid  [38]. Qualitative research identified challenges at various levels but specifically noted a lack of training for healthcare workers and inadequate systems to monitor TPT delivery  [38, 39]. TPT completion is not monitored and reported, but plans are currently in place to include these in the National Indicator Data Set in 2022. Given the poor TPT completion rates, the anticipated revision of national TPT guidelines to include shorter regimens, such as 3 months of daily isoniazid and rifampicin (3HR), recommended by the WHO  [20] , is eagerly anticipated, while access to 3 months of once weekly rifapentine and isoniazid is not yet available.
However, more comprehensive indicators and integration of multiple data sources are needed for adequate monitoring and evaluation of child and adolescent TB care. Surveillance should include age-disaggregated data on prevention, TB disease spectrum, and post-TB morbidity and should be available to inform improvement of services at facility level. Strengthened information systems between hospitals and PHC facilities to improve linkage to care for children and adolescents can further improve outcomes  [49] [50] [51] [52] [53]. With the TB surveillance system as it is now, it is impossible to effectively monitor program performance due to lack of access to the system at district, province, and national levels, where data management and the use of data for action is compromised. A system for program monitoring, interoperable with the NHLS Laboratory information system and death notification system, is urgently required in South Africa.
Improve monitoring and evaluation frameworks and strategies The WHO has published updated and consolidated guidelines for NTPs on the management of child and adolescent TB, and the guidelines are supported by an operational handbook  [17, 18]. A number of the recommendations are directly relevant to the aforementioned needs: decentralized models of care, treatment decision approaches that can be used at all levels of care, strengthening laboratory diagnosis, including of MDR/RR TB, and updated treatment options, including those for TB meningitis and MDR TB, as well as including the recent TPT guidelines with dosage charts. The WHO guidelines and handbook are complimented by the timely report of the Defeat Childhood TB project, a multi-country assessment of childhood TB programm funded by the Elizabeth Glazer Pediatric AIDS Foundation and Unitaid, that calls national policymakers and world leaders to action  [100].
Data sources for cancer burden estimates Cancers included in the GBD study were those defined in chapter 2 (neoplasms) in the tenth revision of the International Classification of Diseases, with the exception of Kaposi sarcoma, for which most deaths are attributed to HIV/AIDS (appendix p 29). 30  Data sources used to inform the cancer estimates were obtained from vital registration systems, sample vital registration systems, verbal autopsy reports, and national and subnational population-based cancer registries. All data sources are provided with a unique identifier and compiled in the Global Health Data Exchange, which is publicly accessible.
Cancer burden estimation Cancer registry, vital registration systems, and verbal autopsy data are used to inform cancer mortality modelling in the GBD study, as one of these data sources might exist in a location where others do not. In some locations, cancer mortality data are sparse, but cancer incidence is reported by national or subnational population-based cancer registries. To maximise data informing mortality models, cancer incidence data were transformed into cancer mortality estimates with modelled mortality-toincidence ratios (MIRs). MIRs specific to cancer causes (cancer types) were modelled with a spatiotemporal Gaussian process regression (appendix pp 30-31). 1, 26 ortality estimates from MIR-transformed incidence data were then pooled with mortality data from vital registration systems and verbal autopsies and used as inputs in cancerspecific Cause of Death Ensemble models.
Third, risk factor exposure levels and distributions were modelled for each age, sex, location, and year combination with data available from See Online for appendix For the Global Health Data Exchange see http://ghdx. healthdata. org/gbd-2019 published studies, household surveys, censuses, administrative data, ground monitor data, or remote sensing data. To model risk factor exposure level, the GBD uses either Bayesian meta-regression modelling (DisMod-MR 2. 1), a flexible approach that can incorporate sex-specific and age-specific data, or spatiotemporal Gaussian process regression, the preferred approach when exposure is stable across age groups (appendix p 62). Fourth, for each risk factor, the theoretical minimum risk exposure level was identified, a counterfactual scenario in which a given population receives the optimal level of risk exposure (ie, no exposure for monotonically increasing risk functions such as smoking, the lowest point of the risk function of exposure for J-shaped or U-shaped risks such as high BMI, and the 85th percentile of exposure in cohorts and trials for protective risks such as fruit intake, weighted by the relative global magnitude of each outcome).
Data sharing This paper summarises key findings from our analysis of GBD 2019 estimates. Citations for the data used in this study can be accessed from the Global Health Data Exchange data input sources tool (http:// ghdx. healthdata. org/gbd-2019/data-input-sources). Files containing all GBD 2019 estimates are available on the Global Health Data Exchange website (http://ghdx. healthdata. org/gbd-2019) and can also be downloaded from the Global Health Data Exchange results tool (http:// healthdata. org/gbd-results-tool). Additional results can be explored through online interactive visualisations (https://vizhub. healthdata. org/gbd-compare/).
S M Aljunid Alexander von Humboldt Foundation, outside the submitted work. M Molokhia  is supported by the  National Institute for Health Research Biomedical Research Center at Guy's and St Thomas' National Health Service Foundation Trust and King's College London. L Monasta  received support from the  Italian Ministry of Health at the Institute for Maternal and Child Health IRCCS Burlo Garofolo, Trieste -Italy  ( RC 34/2017 ). U Mons  is supported by the  Marga and Walter Boll Foundation ,  Kerpen ,  Germany. M A Moosavi  acknowledges the financial support of  National Institute of Genetics Engineering and Biotechnology (NIGEB). J Musa  acknowledges support from the  NIH/FIC   K43TW011416  for research-protected time for cervical cancer research and career development at  University of Jos.
Acknowledgments We would like to thank the patients for providing study samples. The authors acknowledge the  CELLEX foundation  for providing research equipment and facilities. We thank  CERCA Program / Generalitat de Catalunya  for institutional support. We acknowledge funding from  AstraZeneca  and Tesaro supporting this study (to V. Serra). The  GHD-Pink program , the  FERO Foundation , and the  Orozco Family  provided funding for establishment of the PDX models at VHIO. This study has also been supported by the  Catalan Agency AGAUR-FEDER  ( 2017 SGR 540 ,.
Foundation ,  CRUK Grand 638 Challenge , and  Dr Josef Steiner   Foundation  outside the submitted work; also has a  Bayer  outside the submitted work. M. Espinosa-Bravo  reports grants from  FERO 643 Foundation  and  Instituto de Salud Carlos III (ISCIII)  during the conduct of the study; 644 personal fees from  Roche Ldt  and Sysmex outside the submitted work. T. Macarulla  grants, personal fees, and nonfinancial support 670 from  AstraZeneca  and  Pfizer Oncology ; personal fees from  Janssen ,  Astellas , and  Carlos III Fern  andez contract was supported by the project  ERAPERMED2019-215. 800 J. Mateo received funding from the  European Union 's  Horizon 2020 research 801 and innovation programme  under the  Marie Skłodowska-Curie  grant agreement  802 837900. S. Nik-Zainal ,  J. Dias , and  A.
23 provement of the method came from using a thin dyed-silicon replica and developing the Skin-Visiometer ® that relies on light absorption according to the thickness of the silicone material to enable computerassisted image analysis. Computer-assisted image analysis relies on measuring variations in light absorption according to the thickness of the dyed silicone. 19 Non-contact techniques have also been developed to directly assess the skin microrelief. One of the very first such devices is the SkinChip ® , a non-optical skin capacitance imaging device taking advantage of sensors designed to recognise fingerprints. 24 It provides images of the plateaus and furrows based on the distance between the capacitive sensor and the skin microrelief detected by its hydration. This approach only provides 2D information and few data despite recent improvements in image analysis.
A new connected camera, connected in real-time to data storage and analysis servers, has been specifically developed to enable acquisitions of data by the subjects themselves while living their regular daily life, which we call nomadic conditions contrary to subjects that would be required to go and/or stay in dedicated research facilities under controlled conditions (temperature, humidity etc. ). After developing software suites, the camera and its potential in analysing the skin microrelief was evaluated under nomadic conditions. The effect of three skin moisturising ingredients on the skin microrelief was also analysed, comparing results to those obtained from the evolution of untreated control skin areas.
Data acquisition with the connected camera For all parts of the study performed under nomadic conditions, each subject received a connected camera and self-acquired pictures while living their regular daily life over 8 h. Prior to the study, they received training from an experimented technician who showed them how to use the camera and perform acquisition. They also had the opportu-nity to use it under the technician's supervision. During the study, they were asked to perform acquisitions of skin regions of their inner forearm at three different time points: at an initial time (T0, in the morning), 30 min after cream application (T30min) and after 8 h (T8h, in the late afternoon). All acquisitions were performed three times in a row, repositioning the camera between each acquisition on zones drawn with a ballpen from a template grid.
Validation of the connected camera To validate the ability of the connected camera to acquire roughness data and produce reliable results, a model system consisting of natural tanned cowhide leather was first tested. The inner forearm of a single phototype II subject was also analysed. Repeatability was analysed by performing five successive acquisitions without moving the camera. The influence of the positioning of the camera was also examined by performing acquisition series of the same region while rotating it by 0 • , 90 • and 180 • , the location of the acquisition zones being outlined with a ballpen. Short-term reproducibility was determined by comparing two series of five acquisitions separated by a few minutes of interval while the camera was removed between each series. Long-term reproducibility was tested on a silicon replica of a roughness standard.
The same area was acquired in triplicate, repositioning the camera between each repetition. Acquisitions were carried out at two angles: 0 • and 90 •. Reproducibility was determined by comparing acquisition series performed at time points separated by 8 h. The capacity of the connected camera to provide repeatable and reproducible skin microrelief results under the nomadic conditions used in the study was also evaluated. For this purpose, the 3D skin roughness data extracted from images self-acquired by the cohort of phototype I-IV subjects on randomly selected zones of the volar fore-.
The four remaining zones of both forearms received either a placebo cream or one of the three creams with a moisturising ingredient, the positions of which were randomly selected. Subjects self-applied creams (20-30 mg sampled using a graduated spoon) by successive horizontal and vertical passes until penetration. All these procedures were explained to the subjects in a video that they received just before the study. Subjects self-acquired pictures of the six zones just before applying the cream, 30 min after and 8 h later. Due to a tattoo on the right forearm of a subject, a set of data for the placebo and the cream containing xylitylglucoside-anhydroxylitolxylitol had to be excluded from the analysis. Therefore, measurements from 17 subjects were considered for these two creams and the nontreated zone.
Repeatability and reproducibility on a leather model system and the forearm skin of a single subject As a preliminary step, the repeatability and reproducibility of the connected camera were analysed by studying the variability of data acquisition of the colour, gloss, roughness as well as microrelief parameters. Analysis was performed on flat model systems-a piece of natural leather and a silicon replica of a roughness standard-and, as a pilot study, on the skin of the forearm of a single subject. On leather, the L*a*b* colour parameters-the closest to the RGB data captured by the CMOS sensors of the camera-show extremely high repeatability with a maximum coefficient of variation of 0. 97% within acquisition series (Table  2 ). While including data from independent series, the L*, a* and b* parameters also show extremely high repeatability with similar coefficients of variation.
Repeatability and reproducibility of microrelief parameters under nomadic conditions During this study, data were captured by the subjects themselves while living their regular daily life, which we call nomadic conditions, compared to 'classical' studies that are performed in dedicated research facilities in a controlled environment. Therefore, it was crucial to ensure that acquisitions and results were also sound under these conditions. For doing so, data of 3D roughness parameters from the acquisitions performed by 17 subjects on the untreated skin zone of their two forearms and three time points were analysed. These represent 102 series of acquisitions performed in triplicate. Considering all series, the coefficient of variation of data from acquisitions performed at the same time, in a row, whatever time point considered, varies from a minimum of 5.
Following transport by bioaerosols, microorganisms can colonize depositional environments, cause infections, or simply decay after settling; additionally, their genetic material (free or within cells) can be transferred throughout the environment. Despite the heavy research focus on human-associated bioaerosols, most bioaerosols are derived from plants, soil  [23, 24] , and natural bodies of water  [25]. Increasingly, researchers have attempted to track the fate of bioaerosols from anthropogenic sources  [11, 13, 14]. Often researchers rely on modeling approaches or database references to infer the source community of bioaerosols  [26]. Since viable microorganisms can travel thousands of kilometres by air  [27] , the role of bioaerosols as a vector for the dissemination of ARGs is an increasingly important area of research.
Samples from human-associated sampling environments include livestock buildings, fish farms, arable fields, hospitals, and wastewater treatment plants to investigate ARG emissions. Environmental samples will also be taken from clouds, the Canadian North, a transatlantic survey, vehicle filters collected from sites across Canada, and conifer needles to inform the long-distance dispersal of ARGs. The data generated in these projects will inform culturomics and enrichment experiments, in vivo ARG transfer studies in animal models, and exposure models in humans. Finally, selected data will be used to inform risk assessment models. Table  1. Summary of sampling sites, number of samples, type of analysis, and outcomes. Samples from human-associated sampling environments include livestock buildings, fish farms, arable fields, hospitals, and wastewater treatment plants to investigate ARG emissions.
Environmental samples will also be taken from clouds, the Canadian North, a transatlantic survey, vehicle filters collected from sites across Canada, and conifer needles to inform the long-distance dispersal of ARGs. The data generated in these projects will inform culturomics and enrichment experiments, in vivo ARG transfer studies in animal models, and exposure models in humans. Finally, selected data will be used to inform risk assessment models. Together, our team proposes to estimate the contribution of agricultural and sanitation activities to ARG dispersal across Canada and the potential for long-distance transfers through a program addressing the following objectives: (i) assess ARG dispersion and associated bacterial diversity across Canada and their relationships to land use via vehicle cabin filters; (ii) assess ARG dispersion and associated bacterial diversity of bioaerosols in representative source locations by using high-volume air samplers; (iii) determine the subsequent fate of airborne ARGs; (iv) determine the potential for long-distance transport of ARGs; and (v) adding the role of bioaerosols to an integrated assessment model on AMR.
Data Management Given the interdisciplinary nature of this project, shared data collection and management practices must be implemented. The project will use a shared ARG panel (Table  3 ) and metagenomics pipeline. The limited selection of air samplers and standardized sampling design allows for uniform sampling techniques regardless of location, thus improving comparability of results from different locations and environments across Canada. All researchers will upload their data to a secure, shared data portal. Data entry will conform to a standardized format to be accessible for all team members. This shared Data collected from the various study sites will be assembled to assess ARG emissions at point sources and over long distances. These will in turn inform ARG transfer studies in animal models and transport modeling.
003-MIF and was previously supported by GRDI-AMR 1 and theOntario Ministry of Agriculture Food and Rural Affairs New Directions Research Grant ND2013-1967. PBLG is supported by a Sentinelle Nord Postdoctoral Fellowship. M-WS-G is supported by funds from the Centre de Recherche en Infectiologie Porcine et Avicole (CRIPA) and l'Institut de Recherché Robert-Sauvé en Santé et en Sécurité du Travail. CD holds a Tier 1 Canada Research Chair in Bioaerosols. JC holds a Tier 1 Canada Research Chair in Medical Genomics. IS is supported by a training program scholarship from the Institut sur la Nutrition et les Aliments Fonctionnels. VEP is supported by a grant from the LARSEM facility. AFD is supported by Fonds de Recherche du Québec -Santé (FRQ-S) and NSERC scholarships. MB Is supported by a CRIPA graduate scholarship.
darkening around lesions. Also, some of the symptom characteristics, such as darkening or yellow halo, can be convergent between two or more pathogens and bring confusion to the diagnostic. Finally, the physiological state of the plant tissues can also have an impact on the symptoms. So in many cases the size, colour and morphology of the symptoms can be similar although the plant is infected by different fungal species and there is a risk of confusion or indecidability between several symptom-causing pathogens. In this study we aimed at sampling the diversity of symptom appearance for foliar diseases on oilseed rape during the cropping season, with multiexpert annotation. We gathered a community of plant pathologists more or less trained to the diagnostic of foliar diseases of oilseed rape in order to build a database of consensual or problematic symptoms.