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    NutriKG

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    NutriKG - un Graphe de Connaissances pour des Recommandations Personnalisées et Explicable

    Weed and ascochyta blight control in mowed chickpea-service plant intercrops in Western France

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    This dataset was produced over a 2-year field experiment conducted near Angers (France). The aim was to investigate the effects of intercropping chickpea with a mowed service plant to control both weeds and ascochyta blight, while mitigating interspecific competition to minimise yield reductions. Two factors were tested in this experiment: i) the species of service plant intercropped with chickpea (sole chickpea, Egyptian clover, faba bean, oat, Sudan grass), and ii) whether or not to mow the inter-rows of chickpea (no mowing, one mowing at the beginning of chickpea flowering). The experimental layout and the protocol are detailed in Guy et al. (2025)

    Planted Forest Factsheet #2 : Histoire des forêts plantées en France

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    Cette fiche retrace les principales politiques de boisements forestiers dans l'histoire de France, et leur contribution à l'obtention de la ressource dont nous disposons aujourd'hui. Malgré les conflits que ces politiques ont pu générer, il est important de comprendre qu'elles en ont été les objectifs et la variété d'enjeux auxquels les forêts plantées peuvent répondre, encore aujourd'hui

    Flow intermittence indicators from the reconstruction simulations (1960-2021) in the Bükkösdi DRN (Hungary)

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    Statistical monthly and yearly flow intermittence indicators calculated from the simulated daily state of flow in the Bükkösdi DRN (Hungary). Indicators for the reconstruction period (1960-2021)

    Concentrations of precursors of the G and G+L model cakes

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    The concentrations of glucose and leucine at different times during baking of the G and G+L model cakes at 140°C/25 Hz, 140°C/50 Hz, 170°C/25 Hz, 170°C/50 Hz, 200°C/25 Hz and 200°C/50 Hz were determined after sampling, extraction and analysis respectively by UHPLC-CAD and titration

    CSF pharmacokinetics-pharmacodynamics of linezolid in critically brain injured patients, with or without central nervous system healthcare-associated infection. The PK-Pop-LCR Study: A Multicenter Pharmacokinetics and Pharmacodynamics Population Study.

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    Context: Linezolid is an alternative to vancomycin for treating Gram-positive central nervous system (CNS) healthcare-associated infections. The recommended dosing regimen remains debated. PK-Pop-LCR is a prospective population pharmacokinetic-pharmacodynamic study which included brain injured patients with an external ventricular drainage receiving linezolid at different dosing regimens. Objective: In the attached publication, we investigated the cerebrospinal fluid (CSF) penetration of linezolid and we developed a population pharmacokinetic model using plasma and CSF data. Content and scope of the dataset: This dataset contains anonymized individual patient data and the NONMEM control stream used to build the pharmacokinetic model. An important methodological aspect is the hourly sampling of CSF through external ventricular drainage. The model describes linezolid disposition in both plasma and CSF and enables simulations under varying dosing conditions. These materials are intended to support model-informed precision dosing strategies in critically ill patients and to facilitate reproducibility and further research in CNS pharmacokinetics

    BLUPF90 Scripts for Genetic Analysis of Goose Steatosis Traits

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    This repository contains example scripts for estimating genetic parameters using the BLUPF90 software suite. The scripts handle up to four traits simultaneously (from the 15 available in the dataset data.txt found at https://doi.org/10.57745/4MI9JN ). script1.sh runs renumf90 using the parameter file renum_ex1.par. This file processes the traits LW, AFW, CW, and BMW. The model includes the effects of animal, sex, and slaughter date. Optional instructions allow blupf90+ to compute variance ratios and their standard errors. script2.sh follows a similar structure but analyzes the traits LW, BW14r, and BW26. In this case, the fixed effects used in the model are different. script3.sh runs a bivariate analysis, using a categorical data (LCAT) to describe the liver. Hence, it calls gibbsf90+ instead of blupf90+. Pay attention to the missing value code, which must be 0. gibbs_samples.R is a R program to read the output from gibbsf90+. One must provide the number of estimated components (here NCOMP = 6) and the program computes the variance ratios and their posterior distributions

    Training and development dataset for information extraction in plant epidemiomonitoring

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    The “Training and development dataset for information extraction in plant epidemiomonitoring” is the annotation set of the “Corpus for the epidemiomonitoring of plant”. The annotations include seven entity types (e.g. species, locations, disease), their normalisation by the NCBI taxonomy and GeoNames and binary (seven) and ternary relationships. The annotations refer to character positions within the documents of the corpus. The annotation guidelines give their definitions and representative examples. Both datasets are intended for the training and validation of information extraction methods

    Morphologically active reaches of the Vésubie River catchment during Storm Alex (Oct. 2020)

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    This archive gather a shapefile of polygons delineating 100-m-long river reaches of the Vésubie catchment. The polygon limits delineate the morphologically actives areas based on the difference of digitial elevation model (DTM) before and after the flood (including a coregistration of both DTM). Only reaches with consistent geomorphic activity (erosion or deposition) are included. Canopy height model (CHM) were computed in each of these polygons based on LiDAR 3D point clouds. The EPSG (reference system) is 2154 (RGF93 v1 / Lambert-93). To each polygon is attached the following metadata: ID: identification number of each tributary (1-43) and main branches (44-47) ordered by increasing drainage area; ID_reach: identification number of the reach. It is composed by the identification number of the specific (sub-)catchment (ID), followed by an progressive number; Channel: name of the (sub-)catchment/channel; Reach_d: It is composed by the name of of the specific (sub-)catchment/channel (Channel), followed by an progressive number consistent with ID_reach; System: defines the reference valley bottom stretch of each tributary; Srfc_m2 (Surface_m2): is the surface (m2) of the reach; Lngth_m (Length_m): is the longitudinal length (m) of the reach along the channel; (menan_slopr%): is he mean channel gradient computed as the difference in elevation between the upstream and the downstream end of the channel, divided by the length of the reach (Lngth_m); Drn_S_2 (Drainage_Surface_m2): is the maximum value of drainage area at reach; Depo_Vl (Depo_vol): is the sediment volume deposited inside the reach; Eros_Vl (Eros_vol): is the sediment volume eroded inside the reach; Net_Vol: is the sediment net budget of the reach; CHM2018: extension (m2) of the 2018 forest cover that was inside the reach; CHM2020: extension (m2) of the 2020 forest cover that was inside the reach; Diff_CHM: extension difference of forest cover (m2) inside the reach between 2018 and 2020. It is computed as CHM2020-CHM2018 </ul

    Données de réplication pour : Current insights on skin permeability data and QSPR modelling

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    This repository contains curated data concerning skin permeability. Skin permeability is a critical factor in pharmaceuticals, cosmetics, and occupational safety. Experimental determination of skin permeability coefficients (Kp) is time-intensive and resource-demanding, highlighting the importance of computational predictions. These data have been used for quantitative structure-property relationship (QSPR) model development. Data are critically extracted from a recently published SkinPiX dataset and the HuskinDB skin permeability database, comprising 207 curated compounds with associated Kp values and metadata. The dataset includes 3 new experimental data points measured a posteriori

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