The purpose of this national standard of data is to harmonise the minimum information for the description of Public Utilities (SUPs). It is common to all categories of easements and aims to ensure the interoperability of spatial and textual data on SUPs.The scope of the conceptual data model encompasses the concepts relating to the easements themselves, the legal acts establishing them, the managers, generators and bases.It takes place from the point of view of the service which brings together all the SUPs (community and/or DDT) and not of the department that manages the SUP, the latter being able to have its own internal data structure. This document is aimed primarily at:- DDT and local authorities responsible for managing a set of SUPs, be it for the Porter à savoir (PAC), the constitution of the annexes of the PLUs (Territorial Communities) or the Application of Sole Law;- to SUP managers wishing to draw inspiration from the conceptual data model proposed in this document;- to design offices responding to the digitalisation markets of SUPs. This national standard of SUP data is consistent and complements, in the field of easements, the CNIG national standard for the dematerialisation of POS, PLU and communal maps.

This COVADIS data standard concerns communal map documents (CCs). This data standard provides a technical framework describing in detail how to dematerialise these town planning documents in a spatial database that can be used by a GIS tool and interoperable. This standard of data covers both the graphical plans of the sectors and the information overlaying them.This standard of COVADIS data has been developed on the basis of the specifications for the dematerialisation of planning documents created in 2012 by the CNIG, itself based on the consolidated version of the urban planning code dated 16 March 2012. The recommendations of these two documents are consistent even if their purpose is not the same. The COVADIS data standard provides definitions and a structure for organising and storing spatial data from communal maps in an infrastructure, while the CNIG specification serves to frame the digitisation of these data.Part C ‘Data Structure’ presented in this COVADIS standard provides additional recommendations for the storage of data files. These are specific choices for the common data infrastructure of the ministries responsible for agriculture and sustainable development, which do not apply outside their context.

The purpose of this national standard of data is to harmonise the minimum information for the description of Public Utilities (SUPs). It is common to all categories of easements and aims to ensure the interoperability of spatial and textual data on SUPs.The scope of the conceptual data model encompasses the concepts relating to the easements themselves, the legal acts establishing them, the managers, generators and bases.It takes place from the point of view of the service which brings together all the SUPs (community and/or DDT) and not of the department that manages the SUP, the latter being able to have its own internal data structure. This document is aimed primarily at:- DDT and local authorities responsible for managing a set of SUPs, be it for the Porter à savoir (PAC), the constitution of the annexes of the PLUs (Territorial Communities) or the Application of Sole Law;- to SUP managers wishing to draw inspiration from the conceptual data model proposed in this document;- to design offices responding to the digitalisation markets of SUPs. This national standard of SUP data is consistent and complements, in the field of easements, the CNIG national standard for the dematerialisation of POS, PLU and communal maps.

This CNIG data standard concerns local planning documents (LDPs) and land use plans (POSs that are PLU). This data standard provides a technical framework describing in detail how to dematerialise these town planning documents in a spatial database that can be used by a GIS tool and interoperable. This standard of data covers both the graphical plans of sectors and the information overlaying them. This CNIG data standard was developed on the basis of the specifications for the dematerialisation of planning documents created in 2012 by the CNIG, itself based on the consolidated version of the urban planning code dated 16 March 2012. The recommendations of these two documents are consistent even if their purpose is not the same. The CNIG data standard provides definitions and a structure for organising and storing spatial data from communal maps in an infrastructure, while the CNIG specifications are used to frame the digitisation of these data. The ‘Data Structure’ section presented in this CNIG standard provides additional recommendations for the storage of data files. These are specific choices for the common data infrastructure of the ministries responsible for agriculture and sustainable development, which do not apply outside their context.

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Horizontal gene transfer (HGT) has been widely suggested to play a critical role in the environmental adaptation of microbes; however, the number and origin of the genes in microbial genomes obtained through HGT remain unknown as the frequency of detected HGT events is generally underestimated, particularly in the absence of information on donor sequences. As an alternative to phylogeny-based methods that rely on sequence alignments, we have developed an alignment-free clustering method on the basis of an unsupervised neural network “Batch-Learning Self-Organizing Map (BLSOM)” in which sequence fragments are clustered based solely on oligonucleotide similarity without taxonomical information, to detect HGT candidates and their origin in entire genomes. By mapping the microbial genomic sequences on large-scale BLSOMs constructed with nearly all prokaryotic genomes, HGT candidates can be identified, and their origin assigned comprehensively, even for microbial genomes that exhibit high novelty. By focusing on two types of Alphaproteobacteria, specifically psychrotolerant Sphingomonas strains from an Antarctic lake, we detected HGT candidates using BLSOM and found higher proportions of HGT candidates from organisms belonging to Betaproteobacteria in the genomes of these two Antarctic strains compared with those of continental strains. Further, an origin difference was noted in the HGT candidates found in the two Antarctic strains. Although their origins were highly diversified, gene functions related to the cell wall or membrane biogenesis were shared among the HGT candidates. Moreover, analyses of amino acid frequency suggested that housekeeping genes and some HGT candidates of the Antarctic strains exhibited different characteristics to other continental strains. Lys, Ser, Thr, and Val were the amino acids found to be increased in the Antarctic strains, whereas Ala, Arg, Glu, and Leu were decreased. Our findings strongly suggest a low-temperature adaptation process for microbes that may have arisen convergently as an independent evolutionary strategy in each Antarctic strain. Hence, BLSOM analysis could serve as a powerful tool in not only detecting HGT candidates and their origins in entire genomes, but also in providing novel perspectives into the environmental adaptations of microbes.

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포털 유럽연합 데이터 Map Viewing Service (WMS) of the data batch: R111-3 of Entre- Deux-Guiers approved on 29/12/1987

MCA single cell DGE data (Cells with >500UMI ) for the following manuscript:Mapping the Mouse Cell Atlas by Microwell-seqMCA_500more_dge.rar: The raw digital expression matrix (dge) of more than 400,000 single cells sorted by tissues. All cells have more than 500 transcripts. The batch genes were not removed.MCA_BatchRemove_dge.zip: The batch gene removed dge of more than 200,000 primary single cells sorted by tissues. Some tissues are not included due to relatively strong batch effects. This dataset can be used to make global tissue tSNE plot and do cross-tissue analysis.MCA_CellAssignments.csv: The annotation of cells, which includes the cell names, cluster ID, belonged tissues, experimental batches and cell barcodes.MCA_Figure2-batch-removed.txt.tar.gz: The batch removed dge of approximately 60,000 cells of high quality. 1500 cells were sampled from 43 tissues respectively. This sampled data is used for Figure 2.MCA_Figure2_Cell.info.xlsx: The annotations of cells used in Figure2. Sheet1: The annotations of each cell used in Figure2, including cell names, cluster ID, belonged tissues. Sheet2: The annotations of 98 clusters in Figure2. Sheet3: The composition of cell numbers in 98 clusters and 43 tissues. MCA_Batch Information.xlsx: The batch information, which includes the age and gender of the mouse, and experiment batches for MCA data.MCA_BatchRemoved_Merge_dge.h5ad：The updated dge with batch gene removed. It can be read with scanpy python package. About 333778 cells are included.MCA_BatchRemoved_Merge_dge_cellinfo.csv: The cell information of MCA_BatchRemoved_Merge_dge.h5ad.Batch effect removalFor cross tissue comparison, we removed the batch gene background to improve presentation. We assume that for each batch of experiment, the cell barcodes with less than 500UMI correspond to the empty beads exposed free RNA during the cell lysis, RNA capture and washing steps. The batch gene background value is defined as the average gene detection for all cellular barcodes with less than 500 UMI, multiplied by a coefficient of 2, and then rounded to the nearest integer. Genes detected in less 25% of all cells are removed from the batch gene background list. We subtract the batch gene background for each cell from the digital expression matrix before making the cross tissue comparison figures.

The different zoning of the Yvette flood risk prevention plan (PPRI) in the department of Essonne.

The Batch Freezers market report offers a thorough competitive analysis, mapping key players’ strategies, market share, and business models. It provides insights into competitor dynamics, helping companies align their strategies with the current market landscape and future trends.

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Data packages for risk management. Part of the data comes from the opendata of the respective producers and has been adapted for departmental use.

Only the digital batch data for online retrieval within 3 months from the completion of the notification or announcement process by the police agency under Article 807, Paragraph 1 of the Civil Code is provided.

These mapping layers present the food aid associations of Languedoc-Roussillon authorised, national or regional.

The rules in force provide for an enabling system for legal persons governed by private law who wish to receive public contributions for the implementation of food aid.

The Rural Code specifies that food aid shall mean the provision of food to the most deprived persons, including:

— purchases made through the European Fund for Aid to the Most Deprived, the national food aid programme or other public funds,

— the collection, sorting and processing of unsold foodstuffs meeting the requirements in force concerning the hygiene of foodstuffs, carried out by means of public contributions.

Empowerment may be granted, depending on the size of the structures (national or regional), either by the ministers responsible for food and combating social exclusion or by regional prefects.

The location was done at the mailing address.

Here each .h5 file contains matrices of 4 central bins(128bp for each bin) * 5313 epigenomic features for ~19,668 protein coding genes. The gene name/id to key name in .h5 mapping is coded in the metadata.csv file.

This CNIG data standard concerns communal map documents (CCs). This data standard provides a technical framework describing in detail how to dematerialise these town planning documents in a spatial database that can be used by a GIS tool and interoperable. This standard of data covers both the graphical plans of sectors and the information overlaying them. This CNIG data standard was developed on the basis of the specifications for the dematerialisation of planning documents created in 2012 by the CNIG, itself based on the consolidated version of the urban planning code dated 16 March 2012. The recommendations of these two documents are consistent even if their purpose is not the same. The CNIG data standard provides definitions and a structure for organising and storing spatial data from communal maps in an infrastructure, while the CNIG specifications are used to frame the digitisation of these data. The ‘Data Structure’ section presented in this CNIG standard provides additional recommendations for the storage of data files. These are specific choices for the common data infrastructure of the ministries responsible for agriculture and sustainable development, which do not apply outside their context.

The COVADIS Risk Prevention Plans (RPP) data standard includes all the technical and organisational specifications for the digital storage of geographical data represented in the PPRs. The development of a RPP is the responsibility of the State. It is decided by the Prefect. The RPPs contain three categories of information: • The regulatory mapping defines the areas in which specific regulations apply. These regulations are easement and impose requirements varying according to the hazard level to which the area is exposed. • The hazards at the origin of the risk are contained in hazard documents which may be inserted in the presentation report or annexed to the RPP. These documents are used to map the different intensity levels of each hazard considered in the risk prevention plan. • The issues identified during the preparation of the RPP can also be annexed to the approved document in the form of maps. This data standard does not consist of a complete modelling of a risk prevention plan dossier. The scope of this document is limited to geographical data in the RPPs, whether regulatory or not.

Data set for strategic noise maps of Charente’s terrestrial transport infrastructure. Data for 24H weighted average sound graduation cards (type A) greater than 55 dB(A) or nocturnal scales greater than 50 dB(A) are included; the 24-hour or night weighted average limit values (type C) maps; type B maps from the sound classification of roadways and railways. The Charente is not affected by known or foreseeable sound evolution maps (type D).

Post rendered obsolete (Article L 174-3 of the Urban Planning Code). Back to the RNU since 27/03/2017. The land use plan (POS) is digitised according to the national requirements of the CNIG. This lot informs the right to build in the municipality. In addition to regulated zoning (ZONE_URBA), it can contain up to 2 other data sets: surface requirements (PRESCRIPTION_SURF) and/or surfacing information (INFO_SURF).