dataesr/scientific-paragraphs-categorization huggingface dataset:
Quality of the Transnational Collaboration and Scientific Exchange None of the partners or countries has all the knowledge, tools, and/or data that are essential to develop an effective open access platform for microbiota, food, and health. This platform brings together amongst others the data of the previously founded JPI HDHL INTIMIC projects. The collaboration was formed by a national (nine countries) selection of partners. Within nine countries, partner groups were selected due to their wide range of experience in data sharing, nutrition, microbiology, data analysis, ontologies, medicine, metabolomics, and other backgrounds that are relevant for the platform. During the preparatory meeting (in 2018) the selected partners defined the main goals and structure of the platform. This procedure ensured that there would be a direct connection between the expertise in the group, the aims of the current proposal (see Table  1 ), and the aims in the call.
Data Capture and Sharing One central aim is the identification of animal and human (intervention and observational) studies from knowledge platform (KP)-INTIMIC partners with a wealth of data relevant to nutrition and the intestinal microbiota. This includes metadata of these studies in order to define ontologies and standardization strategies (WPs 2 and 4) and to define use cases on specific microbiota-related research questions (WPs 6 and 7). Metadata includes, among others, general information on the study (name of study, study web links, funding body, scope, study design, and recruitment), information on measurement of the microbiota (type of samples collected, analysis method, sequencing platform), other laboratory measurements in biological samples (candidate biomarkers, metabolomics, genomics, proteomics), exposure measurements (dietary intake, alcohol and tobacco consumption, physical activity, sedentary behavior, anthropometric measurements, sociodemographic information, and health status), and health-related outcomes.
This also includes information on signed informed consents, ethics committee approval, and whether data owners may share raw data or metadata within and outside the KP-INTIMIC consortium. The INTIMIC knowledge platform offers and expands the DASH-IN infrastructure previously developed in ENPADASI  [17] , which allows data owners and researchers to share their data and metadata for future research. The DASH-IN infrastructure encompasses two different types of infrastructure: on the one hand the Nutritional Phenotype database (www. dbnp. org , access date 20 March 2022), which is a single central database that facilitates data integration and pooled analysis of individual-level data, and DataSHIELD  [16] , an open source software project which allows federated joint analyses of individual-level data from several studies conducted without physically transferring their data into a single central database, as a way to circumvent privacy, ethical, and legal constraints of observational studies that often preclude physical sharing of data  [18].
Standardization and Guidelines for Microbiome Analysis The aim of this line of work is to develop a collection of standard operating procedures and tools for the standardization of both wet lab and data analysis procedures. This will be achieved by pooling the expertise of the partners, by collecting information on existing relevant initiatives and by comparing methods in order to determine the overall comparability of microbiome studies. The INTIMIC knowledge platform is creating an inventory of methods leading to a database of standard operating procedures for microbiome sequencing and data analysis. Special attention is paid to methods for analysis of low biomass samples and less frequently used sample materials, as well as comparison of marker-based and whole metagenome shotgun-based sequencing techniques.
Defining a Reference Microbiome This line of work focuses on describing the inter-individual variation in the taxonomic and functional composition of the human gut microbiota through the integration of 16S rRNA and metagenomic datasets. The working group takes advantage of the many datasets that have become available in recent years from projects such as MetaHit  [19, 20] , the Human Microbiome Project (HMP)  [21] , and datasets derived from JPI HDHL projects. The integration of datasets derived using different library preparation procedures is challenging since biases related to these procedures need to be taken into account. As part of its work the working group develops methods for evaluating these biases as well as biases related to the bioinformatics methods that are used. Methods and data that are developed in this working group will be used to compare the microbiota of different populations and age groups and to identify characteristics of the microbiota under specific health conditions and dietary regimes.
Standardization of Other Data and Development of Ontologies The aim of this working group is to provide a standardized dataset and ontologies to unravel correlations among data originating from different areas of research relative to the axis of functional food, intestinal metabolomics, and human health. Indeed, in connection with the functional food axis and human health, a specific part within this consortium initiative is dedicated to intestinal microbiota-related metabolite and protein analyses. The opportunity to analyze metabolomics and metaproteomics data within interconnected databases from many cohorts allows a comprehensive overview of microbiota composition as well as its downstream production in terms of whole metabolite and protein sets, and therefore its functions. In order to fulfil this objective, the merged data need to be harmonized and the associated measurable variables require an accurate curation.
Human Association Studies By conducting joint analyses of human study data from various sources identified within the network, the KP-INTIMIC contributes to answer research questions aiming to understand the relationships between the microbiota, diet, and health in the areas of early infancy, ageing, and the development of chronic and sub-chronic diseases. Addressing these questions requires data from observational and intervention human datasets (identified in the data capture and sharing working group), as well as harmonization of data and tools such as common bioinformatics pipelines (such as DADA2, QIIME I, QIIME 2) for standardization of microbiome analysis and data processing developed in other working groups. To accommodate changes in diet and health status throughout life, four case studies are proposed:.
Supplementing formula with pre-or probiotics has been proposed to make gut colonization following formula feeding more similar to breastfeeding. Some interventional studies in humans have been conducted in this respect  [32] [33] [34]  in addition to studies with child cohorts from farmers where raw milk was used as part of the daily nutrition. Protocols of these interventional studies are compared and merged to provide guidelines and ensure efficacy of future studies. Since data on intervention studies is often limited and inconsistent, datasets are enriched with publicly available data from various databases. Inflammatory and metabolic factors play an important role in the development of chronic diseases  [35]. Some dietary and nutritional factors are related to inflammatory and metabolic factors and associated diseases, and they have been suggested to modulate the composition and function of the gut microbiota  [1, 2, 36, 37].
This work creates a system that allows generalized data sharing and a much better use of nutritional study data for future analyses across data sets and study types. Datasets may be used by lawmakers, medical doctors, and funding institutions. Our project grants intelligent access and categorization of big data (e. g. , microbiome, metabolomics), including negative results and unpublished information, which is often unstructured and poorly accessible. The potential outcomes will be easier access to medically and nutritionally relevant datasets, and exploitation of both published and unreleased datasets to the benefit of the wider EU-based scientific community. In the longer term, this platform will contribute to formulate better and more informed hypotheses for future studies, and, in some cases, make it possible to answer questions without having to conduct additional studies.
For data collection, DAta SHaring In Nutrition (DASH-IN), the system developed by ENPADASI (http://www. enpadasi. eu/ access date 20 March 2022), is used. This is a combination of the earlier developed tools Phenotype database (www. dbnp. org, access date 20 March 2022) and OPAL/DataSHIELD • Create a catalogue of studies on microbiome, nutrition, and health; • Define, for each study type, the vocabulary and metadata variables (e. g. , timeline infor- mation, participant characteristics, etc. ) necessary to minimally define the study setup; • Create a catalogue of standard operating procedures for microbiome analyses; • Define a reference microbiome for subtypes of subjects; • Bring together standards relevant for the community for other (omics) data; • Create relevant ontologies where needed.
Dynamic Light Scattering (DLS) The CNDs' diameter was assessed by dynamic light scattering (DLS). The measurement was carried out at 25 • C on a Zetasizer Nano-ZS ZEN3600 instrument (Malvern Instruments, Malvern, UK) equipped with a 4 mW He-Ne laser with a light wavelength of 632. 8 nm, and backscattering angle of 173 • , using a disposable DTS 1070 cell. The solid sample of CNDs was redispersed in deionized water at a concentration of 1 mg/mL. Data are presented as % by number.
Acknowledgments: The authors thank the  Carbon Nanotechnology Group, Dept. of Chemical and Pharmaceutical Sciences, University of Trieste , mainly,  Maurizio Prato  for  Julio Bartoli  to develop the synthetic carbon nanodots methodology and the  Laboratory for Surface Science (LSC)  of the  Brazilian Nanotechnology National Laboratory (LNNano, CNPEM/MCTI ), for the AFM images, and  Marisa M. Beppu  from the  School of Chemical Engineering-Unicamp  and the students under her supervision:  Rogério A. Batagliogli ,  Thiago B. Taketa , and  Laise M. Lopes  for the fluorescence analysis. The figures were created using the Mind The Graph platform.
Instruments Assessment of ADHD, SUD and other comorbidities are done in accordance with local clinical routines and regulations. Information on the diagnostic procedure, e. g. , the use of structured interviews, along with all other data collection, is entered and stored in a webbased electronic case report form (eCRF), provided by Clindox ® , which fits within the rules of regulation for Good Clinical Practice (GCP: European Medicines Agency, 2002) and the General Data Protection Regulation (GDPR). Information on provided treatment modalities, such as psychological and pharmacological treatments, including stimulant dosing, sociodemographic data (housing, employment, level of education etc. ), age, gender, previous treatments, other psychiatric comorbidities, adverse events (in relation to ADHD medications) and misuse/diversion of prescriptive drugs was collected by clinicians at each site through patient interviews and patient files upon entering the data into the eCRF.
Given the large sample size in the present study, including a variety of detailed longitudinal data, this dataset provides an opportunity to explore sex differences in SUD patients with comorbid ADHD, and to analyse the association with treatment outcome measures. A large proportion (40. 8%) reported that they had not previously received any ADHD treatment prior to enrolment in our study, while most (71. 1%) had previously received SUD treatment. This speaks to the importance of screening for ADHD in SUD treatment-seeking patients. Furthermore, our sample partly consists of participants with a severe and complex psychiatric burden, where a majority presented with at least one other psychiatric comorbidity (61. 4%), and almost half our sample (46. 9%) were diagnosed with two or more co-current SUDs.
However, the naturalistic design is also one of the most important limitations. For instance, the treatments are not blinded nor randomly allocated, thus causing inferential challenges and difficulties in controlling for selection and information bias and/or confounding. Finally, a limitation is that different sites vary in diagnostic and treatment procedures. The main purpose of the study is, however, descriptive and aims to describe this specific  patient population and the treatments provided to them. The study will provide information on treatment effects and the clinical course of these disorders with simultaneously collected data on substance use, ADHD-symptoms, and quality of life. Data analysis will consider limitations, including the use of propensity scores to control for baseline differences between groups.
Acknowledgements CB was supported by the  Stockholm County Council  (combined residency and PhD training program). We thank  Sofie Verspreet ,  Meike van Vlastuin ,  Jacomine de Boer ,  Michelle van Dusseldorp ,  Karolien Van der Donck ,  Anna Boormans ,  Cor Verbrugge ,  Peter Greven ,  Pol Ibañez Jimenez ,  Tamás Kárpáti ,  Attila Császár ,  Eva Debusscher ,  Maeva Fortias ,  Lucia Romo ,  Sara Thisner Lindstedt , Hannes stenström, Ebba thurezon,  Miklos Szabo  and  Moa Nordin  for excellent assistance in conducting this study.
In 2006, many public services are created across France to undertake inspections and visit households not connected to a sewer network. Before OWTS had generally received little attention from inhabitants, and some communication was necessary to support the public acceptance of a centralized management. Based on European requirements  (Water Framework Directive, 2000) , the French inspection plan relied on rehabilitating too old or dysfunctional devices and was supported by financial support through water agencies (state public institution in charge of implementing the river basin management plan and which provides significant contribution to actions of common interest). For example, more than 20,000 rehabilitation projects have been funded between 2013 and 2017 in the Rhône-Mediterranean watershed (average cost of 8300 euros per infrastructure  ( Prébay, 2018 ) ).
But the question of the upgrading level and whether grants are available is still pregnant for dwellers. At the management level, public officers are specifically dedicated to the control of the device with regard to technical standards and national regulations and they are supposed to register all the systems in public databases (www. data. eaufrance. fr). Except for the control during operation, design and implementation inspections require public servants to check if the consultant and the installer respect methodological and technical guidelines. Note that for OWTS inter-municipality management is economically preferable for public services (sufficient number of devices), and that in France delegation agreement are rare (basic control mission do not require extensive technical skills or large-scale pooling of resources).
Overview of the Montpellier case study: a science-practice collaborative project To support OWTS management, soils suitability maps (soil investigations at the district scale and recommendation of OWTS device) is available and corresponds to a rare example of soils consideration as ecological interfaces in urban planning  ( Bispo et al. , 2016 ). Still, mapping of soils characteristics (infiltration rate for example) is extremely demanding with regard to field investigation. Suitability maps thus generally only delimit areas where some device should be restricted. For example, in the main problematic OWTS sector in the Montpellier intermunicipality (presented in Section 2. 1 ), sand filters are recommended. Mainly implemented before 2014, we note the significant presence of activated device on the few data available in OWTS database in 2018.
The initial methodology was built on the assumption that measurement of soil properties in laboratory could supplement in-situ percolation tests for the characterization of biophysical processes  ( Nasri et al. , 2015b ). First, the compilation of in-situ percolation test measurements (available in public authorities' databases,  mainly from design studies by private consultants) present a high variability at the neighborhood scale ( Fig. 4  ). To address surfaced contestations, six soil samples were excavated at various depth all around the district  ( Daudin, 2018 ). The physicochemical properties measured in private laboratory (soil texture and organic carbon content) have been used in empirical regressions to assess hydraulic properties (calculated hydraulic conductivity at saturation, averaged on six couplings of pedotransfer functions identified in  Nasri et al.
Many punctual and spatialized data can be aggregated, but one need to be very careful during the analysis because of the diversity in map scales, quantity of punctual data and metrology used for physicochemical parameters estimation. This heterogeneity is currently a big challenge for any kind of data management (harmonization issues), while it is a major source of money savings for soil digital mapping (expansive field investigations). For example, the long duration over which in-situ percolation test have been used for OWTS design studies make these data records precious for hydraulic conductivity characterization, but the establishment of a comparison basis for diverse sectorial databases is not simple (coupling of in-situ observations and development of local pedotransfer functions). Finally, the soil-based new insights on the studied district did not help OWTS managers in their day-to-day problems.
Soil hydraulic functions Many countries, including France, have a land use planning at a municipal scale. The respective authorities determine the legal uses. Generally considered as a support for infrastructure and housing, soils are still not well represented in the Ecosystem Services concepts  ( Blanchart et al. , 2018 ). We posit that OWTS as NBS could contribute to improve land-use changes on a knowledge basis. Hydraulic functions of soils (not only infiltration rate but all information that support soil-water interaction assessment, like piezometric surface or soil moisture) have many other potential applications in urban hydrology, for example flood prevention modeling could be refined by integrating permeable areas. However, spatial distribution of soils horizons and their complex interactions in the landscape is a real technical barrier to the establishment of operational soil databases for decision-making.
Considering the necessary tradeoff between sophistication of composite indicators and availability of requisite data  ( Gómez-Álvarez et al. , 2018 ) , OWTS might be a great opportunity for fine-tuning soil data and support the consideration of soils services in urban planning and water management. Aggregation of soil and water databases would need further investigation, for example using data sciences products (for example remote sensing of soil moisture at the plot scale  ( El Hajj et al. , 2017 ) ). Note that the underlying idea of gathering dispersed data between organizations (research, municipalities, consultants, …) would need dedicated specifications in contracts (partnerships, market offers) and skills to operate capitalization (from raw data to transferable information). The latter could be strengthened by digital assessment (for example data mining  ( Boulil et al.
Funding sources The initial work was supported by the inter-municipality of Montpellier Méditerranée Métropole (3M) during a collaborative project with the Conservatoire National des Arts et Métiers (CNAM). Montpellier inter-municipality provided financial support for the conduct of the research, in the collection and analysis of the data. The funding source (from April to October 2018) had no involvement in the decision to submit the article for publication.
Acknowledgments The authors are grateful to the department of Water and Sanitation of  3M , in particular to the " 3M-ANC  " project team  Sylvie Heinimann-Luna ,  Yvon Danvert ,  Vincent Chiron ,  Nicolas Philippe ,  Louis Moulis  and  Behzad Nasri. Special thanks to VC and NP for their engagement in their day-to-day mission, without which this work would not have been initiated. We are also very grateful to all the actors who accepted informal discussion and open debate (owners, consultants, installers and local authorities). This work would not have been achieved without great advice from  Gilian Cadic  ( AgroParisTech, G-EAU laboratory ) and the funding of the  ANCRES  project ( GESSOL program ,  MEEDDM-CDGDD-DRI R-2011-8C-0028-A0 ).
The waveguide is terminated 500 µm from the microchannel to guarantee the illumination of the entire height of the channel by exploiting the divergence of light at the waveguide output. The signal is externally collected by a four-quadrant photodetector and the light distribution is subsequently analyzed. Using this approach, the authors have been able to successfully classify different algae populations, benefiting from the pattern recognition feature of the neural network toolbox in MATLAB for signal analysis  [53]. In the previous application, the use of an optical waveguide for sample illumination has allowed ease of use and a precise and stable alignment between optical and fluidic components. To increase the imaging capabilities of integrated devices also other optical components should be integrated on chip, such as lenses, mirrors or filters.
Abstract. MDAL is the operational Meteosat Second Generation (MSG)-derived daily surface albedo product that has been generated and disseminated in near real time by EU-METSAT Satellite Application Facility for Land Surface Analysis (LSA-SAF) since 2005. We propose and evaluate an update to the MDAL retrieval algorithm which introduces the accounting for aerosol effects as well as other scientific developments: pre-processing recalibration of radiances acquired by the SEVIRI instrument aboard MSG and improved coefficients for atmospheric correction as well as for albedo conversion from narrow-to broadband. We compare the performance of MDAL broadband albedos pre-and post-upgrade with respect to three types of reference data: the EPS Ten-Day Albedo product ETAL is used as the primary reference, while albedo derived from in situ flux measurements acquired by ground stations and MODIS MCD43D albedo data are used to complete the validation.
For black-sky albedo we similarly see improvements for all seasons when averaged over the full data set, although sub-regions exhibit clear seasonal dependence: the performance of the upgraded MDAL version is generally diminished in local winter but better in local summer. The comparison with in situ observations is less conclusive due to the well-known problem of the spatial representativeness of near-ground observations with respect to satellite pixel footprint sizes. Comparison with MODIS at the same locations shows mixed results in terms of change in performance following the proposed upgrade but proves the good quality of the MDAL products in general. Based on the evidence presented in this study, we consider the updated algorithm version to be able to deliver a valuable improvement of the operational MDAL product.
Updated narrow-to broadband conversion coefficients. The narrow-to broadband conversion in the MDAL retrieval algorithm involves a set of conversion coefficients which are estimated by using synthetic albedos which were generated with the SAIL (Scattering by Arbitrary Inclined Leaves;  Verhoef, 1984)  canopy reflectance model for different surface types (for more details on the procedure, see Sect. 2. 5. 2 in  Carrer et al. , 2021). The database of synthetic spectral reflectances used to calculate albedos has been updated to include a more exhaustive set of vegetation and bare-soil surfaces and has been used to obtain conversion coefficients for MDAL v2 (values of coefficients are given in the Appendix, Table  A2 ). The same updated database has been used for other LSA-SAF albedo products (e.