{
"@context": [
"https://www.w3.org/ns/activitystreams",
"https://purl.org/coar/notify"
],
"id": "urn:uuid:9a66a64b-9bff-489f-967d-b6aa48a24d86",
"type": [
"Offer",
"coar-notify:ReviewAction"
],
"actor": {
"id": "https://datalake.inria.fr",
"type": "Service",
"name": "Inria DataLake"
},
"origin": {
"id": "https://datalake.inria.fr",
"type": "Service",
"inbox": "https://prod-datadcis-api.inria.fr/coar/inbox"
},
"target": {
"id": "https://inria.hal.science",
"type": "Service",
"inbox": "https://inbox.hal.science"
},
"object": {
"id": "https://hal.science/hal-01485293v1",
"ietf:cite-as": null,
"sorg:citation": {
"@context": "https://doi.org/10.5063/schema/codemeta-2.0",
"type": "SoftwareSourceCode",
"name": "FlameMaster",
"codeRepository": null,
"referencePublication": null
},
"mentionType": "software",
"mentionContext": [
"For the flames discussed in the following, detailed chemistry computations of the gas phase were performed using the FlameMaster code and the chemical kinetic mechanism of Narayanaswamy et al. , which was developed with special focus on soot precursors, and which contains PAH (polycyclic aromatic hydrocarbons) chemistry up to four-ringed molecules."
]
}
}
2026-04-05 06:50:12
urn:uuid:68897c06-32fc-4c96-815a-07b0f00eacba
https://datalake.inria.fr
https://inria.hal.science
["Offer","coar-notify:ReviewAction"]
{
"@context": [
"https://www.w3.org/ns/activitystreams",
"https://purl.org/coar/notify"
],
"id": "urn:uuid:68897c06-32fc-4c96-815a-07b0f00eacba",
"type": [
"Offer",
"coar-notify:ReviewAction"
],
"actor": {
"id": "https://datalake.inria.fr",
"type": "Service",
"name": "Inria DataLake"
},
"origin": {
"id": "https://datalake.inria.fr",
"type": "Service",
"inbox": "https://prod-datadcis-api.inria.fr/coar/inbox"
},
"target": {
"id": "https://inria.hal.science",
"type": "Service",
"inbox": "https://inbox.hal.science"
},
"object": {
"id": "https://hal.science/hal-03173462v1",
"ietf:cite-as": null,
"sorg:citation": {
"@context": "https://doi.org/10.5063/schema/codemeta-2.0",
"type": "SoftwareSourceCode",
"name": "R-loops",
"codeRepository": null,
"referencePublication": null
},
"mentionType": "software",
"mentionContext": [
"The involvement of R-loops in CSR was one of the first described examples of how \"programmed\" R-loops can participate in normal cell physiology."
]
}
}
2026-04-05 06:50:12
urn:uuid:0915ce57-452e-432d-8ff4-bf91a70ae5b8
https://datalake.inria.fr
https://inria.hal.science
["Offer","coar-notify:ReviewAction"]
{
"@context": [
"https://www.w3.org/ns/activitystreams",
"https://purl.org/coar/notify"
],
"id": "urn:uuid:0915ce57-452e-432d-8ff4-bf91a70ae5b8",
"type": [
"Offer",
"coar-notify:ReviewAction"
],
"actor": {
"id": "https://datalake.inria.fr",
"type": "Service",
"name": "Inria DataLake"
},
"origin": {
"id": "https://datalake.inria.fr",
"type": "Service",
"inbox": "https://prod-datadcis-api.inria.fr/coar/inbox"
},
"target": {
"id": "https://inria.hal.science",
"type": "Service",
"inbox": "https://inbox.hal.science"
},
"object": {
"id": "https://hal.science/hal-03173462v1",
"ietf:cite-as": null,
"sorg:citation": {
"@context": "https://doi.org/10.5063/schema/codemeta-2.0",
"type": "SoftwareSourceCode",
"name": "UCSC",
"codeRepository": null,
"referencePublication": null
},
"mentionType": "software",
"mentionContext": [
"The UCSC genome browser comparison of datasets from published S9.6-based and dRNaseH1-based mapping studies is available at",
"We hope the UCSC genome browser link provided here will facilitate this process.",
"To enable data comparison and quality control, we encourage users to exploit the UCSC genome browser (http://genome.ucsc.edu/s/fredericchedinlab/hg19_DRIP_Correlation),"
]
}
}
2026-04-05 06:50:08
urn:uuid:d223188c-c914-47a5-9352-259c9390c2df
https://datalake.inria.fr
https://inria.hal.science
["Offer","coar-notify:ReviewAction"]
{
"@context": [
"https://www.w3.org/ns/activitystreams",
"https://purl.org/coar/notify"
],
"id": "urn:uuid:d223188c-c914-47a5-9352-259c9390c2df",
"type": [
"Offer",
"coar-notify:ReviewAction"
],
"actor": {
"id": "https://datalake.inria.fr",
"type": "Service",
"name": "Inria DataLake"
},
"origin": {
"id": "https://datalake.inria.fr",
"type": "Service",
"inbox": "https://prod-datadcis-api.inria.fr/coar/inbox"
},
"target": {
"id": "https://inria.hal.science",
"type": "Service",
"inbox": "https://inbox.hal.science"
},
"object": {
"id": "https://hal.science/hal-05304285v1",
"ietf:cite-as": null,
"sorg:citation": {
"@context": "https://doi.org/10.5063/schema/codemeta-2.0",
"type": "SoftwareSourceCode",
"name": "GraphPad Prism",
"codeRepository": null,
"referencePublication": null
},
"mentionType": "software",
"mentionContext": [
"Statistical analysis was performed using GraphPad Prism 8.0, followed by a one-way ANOVA with Dunnett's multiple comparison tests to assess the effects of the treatment groups compared to the control group."
]
}
}
2026-04-05 06:50:08
urn:uuid:c9ae3b6c-9282-4fac-b0e8-1909ed0ca057
https://datalake.inria.fr
https://inria.hal.science
["Offer","coar-notify:ReviewAction"]
{
"@context": [
"https://www.w3.org/ns/activitystreams",
"https://purl.org/coar/notify"
],
"id": "urn:uuid:c9ae3b6c-9282-4fac-b0e8-1909ed0ca057",
"type": [
"Offer",
"coar-notify:ReviewAction"
],
"actor": {
"id": "https://datalake.inria.fr",
"type": "Service",
"name": "Inria DataLake"
},
"origin": {
"id": "https://datalake.inria.fr",
"type": "Service",
"inbox": "https://prod-datadcis-api.inria.fr/coar/inbox"
},
"target": {
"id": "https://inria.hal.science",
"type": "Service",
"inbox": "https://inbox.hal.science"
},
"object": {
"id": "https://hal.science/hal-05304285v1",
"ietf:cite-as": null,
"sorg:citation": {
"@context": "https://doi.org/10.5063/schema/codemeta-2.0",
"type": "SoftwareSourceCode",
"name": "Origin",
"codeRepository": null,
"referencePublication": null
},
"mentionType": "software",
"mentionContext": [
"Origin software was used to calculate the peak area ratio of apatite to vaterite (A A /A V ).",
"To assess apatite formation during the setting reaction of the prepared cements, the A A /A V area ratio of the XRD peaks corresponding to apatite (25.8 \u2022 ) and vaterite (24.8 \u2022 ) was determined using Origin software."
]
}
}
2026-04-05 06:50:02
urn:uuid:4d1e5ab7-0109-4b06-bb10-26747afa6fca
https://datalake.inria.fr
https://inria.hal.science
["Offer","coar-notify:ReviewAction"]
{
"@context": [
"https://www.w3.org/ns/activitystreams",
"https://purl.org/coar/notify"
],
"id": "urn:uuid:4d1e5ab7-0109-4b06-bb10-26747afa6fca",
"type": [
"Offer",
"coar-notify:ReviewAction"
],
"actor": {
"id": "https://datalake.inria.fr",
"type": "Service",
"name": "Inria DataLake"
},
"origin": {
"id": "https://datalake.inria.fr",
"type": "Service",
"inbox": "https://prod-datadcis-api.inria.fr/coar/inbox"
},
"target": {
"id": "https://inria.hal.science",
"type": "Service",
"inbox": "https://inbox.hal.science"
},
"object": {
"id": "https://hal.science/hal-03871507v1",
"ietf:cite-as": null,
"sorg:citation": {
"@context": "https://doi.org/10.5063/schema/codemeta-2.0",
"type": "SoftwareSourceCode",
"name": "SESAM",
"codeRepository": null,
"referencePublication": null
},
"mentionType": "software",
"mentionContext": [
"adeajayi-kunle/powerspec, Ajayi, 2022) and the predictability diag- nostics based on CRPS score and location score were made with the SESAM (https://github.com/brankart/sesam,"
]
}
}
{
"@context": [
"https://www.w3.org/ns/activitystreams",
"https://purl.org/coar/notify"
],
"id": "urn:uuid:33882409-52d4-43f4-97aa-e2f617ff36ec",
"type": [
"Offer",
"coar-notify:ReviewAction"
],
"actor": {
"id": "https://datalake.inria.fr",
"type": "Service",
"name": "Inria DataLake"
},
"origin": {
"id": "https://datalake.inria.fr",
"type": "Service",
"inbox": "https://prod-datadcis-api.inria.fr/coar/inbox"
},
"target": {
"id": "https://inria.hal.science",
"type": "Service",
"inbox": "https://inbox.hal.science"
},
"object": {
"id": "https://hal.science/hal-04074631v1",
"ietf:cite-as": null,
"sorg:citation": {
"@context": "https://doi.org/10.5063/schema/codemeta-2.0",
"type": "SoftwareSourceCode",
"name": "MATLAB/SIMULINK",
"codeRepository": null,
"referencePublication": null
},
"mentionType": "software",
"mentionContext": [
"All measurements were conducted using the parameters listed in Table and under a constant stoichiometric ratio of H2 (1.1) and air (5), with a relative humidity of 15%. ) and ( ), a PEMFC model was built with the MATLAB/SIMULINK environment."
]
}
}
2026-04-05 06:49:57
urn:uuid:2e633623-44b3-4a94-afd5-b8d1f9677dee
https://datalake.inria.fr
https://inria.hal.science
["Offer","coar-notify:ReviewAction"]
{
"@context": [
"https://www.w3.org/ns/activitystreams",
"https://purl.org/coar/notify"
],
"id": "urn:uuid:2e633623-44b3-4a94-afd5-b8d1f9677dee",
"type": [
"Offer",
"coar-notify:ReviewAction"
],
"actor": {
"id": "https://datalake.inria.fr",
"type": "Service",
"name": "Inria DataLake"
},
"origin": {
"id": "https://datalake.inria.fr",
"type": "Service",
"inbox": "https://prod-datadcis-api.inria.fr/coar/inbox"
},
"target": {
"id": "https://inria.hal.science",
"type": "Service",
"inbox": "https://inbox.hal.science"
},
"object": {
"id": "https://hal.science/hal-04074631v1",
"ietf:cite-as": null,
"sorg:citation": {
"@context": "https://doi.org/10.5063/schema/codemeta-2.0",
"type": "SoftwareSourceCode",
"name": "Matlab/Simulink",
"codeRepository": null,
"referencePublication": null
},
"mentionType": "software",
"mentionContext": [
"The PEMFC model was implemented in the Matlab/Simulink environment and was designed with voltage input and current output.",
"To validate the proposed model, simulations are performed using the Matlab/Simulink environment and compared to experimental data, as detailed in Section 5."
]
}
}
2026-04-05 06:49:46
urn:uuid:a9ba42fc-3a02-4fbb-8a8e-d388cfc8506b
https://datalake.inria.fr
https://inria.hal.science
["Offer","coar-notify:ReviewAction"]
{
"@context": [
"https://www.w3.org/ns/activitystreams",
"https://purl.org/coar/notify"
],
"id": "urn:uuid:a9ba42fc-3a02-4fbb-8a8e-d388cfc8506b",
"type": [
"Offer",
"coar-notify:ReviewAction"
],
"actor": {
"id": "https://datalake.inria.fr",
"type": "Service",
"name": "Inria DataLake"
},
"origin": {
"id": "https://datalake.inria.fr",
"type": "Service",
"inbox": "https://prod-datadcis-api.inria.fr/coar/inbox"
},
"target": {
"id": "https://inria.hal.science",
"type": "Service",
"inbox": "https://inbox.hal.science"
},
"object": {
"id": "https://hal.science/lirmm-01170968v1",
"ietf:cite-as": null,
"sorg:citation": {
"@context": "https://doi.org/10.5063/schema/codemeta-2.0",
"type": "SoftwareSourceCode",
"name": "MUMmer",
"codeRepository": null,
"referencePublication": null
},
"mentionType": "software",
"mentionContext": [
"MUMmer (NUCmer) , which can deal with rearranged but slightly divergent genomes, implements a variation of this strategy, i.e. it uses exact matches that are clustered together in order to produce a non-collinear chain, but does not implement the fourth phase ('last chance alignment' phase).",
"1) MUMmer (NUCmer) produced almost perfect alignments (99.9% of identity for Lactobacillus, 92.3% for Bacillus cereus) of limited length: on average 2.0 Mb for Lactobacillus (mean coverage: 76.6%) and 3.6 Mb for Bacillus cereus (mean coverage: 69.4%).",
"This phenomenom was not observed in either MUMmer, or in YOC alignments, for which the proportion of gaps remained low, regardless of the divergence rate.",
"YOC coverages were between those of MAUVE/ProgressiveMAUVE and MUMmer.",
"Although a similar, simplified, two-phase strategy is already used in MUMmer , the solution is not entirely satisfactory.",
"To summarize, unlike classical WGA tools designed for similar genomes (like MGA, MUMmer (NUCmer), MAUVE, LAGAN, ProgressiveMAUVE), YOC focuses on almost collinear, highly divergent pairwise WGA, and simplifies the anchor based strategy by implementing only the first two phases (see Figure ), without any refinement steps like realignment, filtering, or recursive alignment.",
"Based on the preliminary results listed in Table , we decided to compare five genome aligners, MGA, MUMmer (NUCmer), MAUVE, ProgressiveMAUVE and YOC, using the intra-species pairs of genomes from Dataset 2. Given that MUMmer (NUCmer) uses exact matches (unique or not) and that it does not include the 'last chance alignment phase' , the length of its alignment can serve as a lower bound of the number of alignable positions.",
"For example, the number of aligned segments, a measure of the alignment fragmentation, is not directly comparable between MAUVE, ProgressiveMAUVE and the other genome aligners: for MUMmer (NUCmer), MAUVE and ProgressiveMAUVE it represents the number of Locally Collinear Blocks (LCBs) in the alignments, i.e. roughly the number of inversions and translocations; for MGA and YOC, it is the number of segments that are interrupted by insertions/deletions and local inversions (for YOC only).",
"Based on the preliminary results listed in Table , we decided to compare five genome aligners, MGA, MUMmer (NUCmer), MAUVE, ProgressiveMAUVE and YOC, using the intra-species pairs of genomes from Dataset 2. Given that MUMmer (NUCmer) uses exact matches (unique or not) and that it does not include the 'last chance alignment phase' , the length of its alignment can serve as a lower bound of the number of alignable positions.",
"Figure 3b shows that increasing the level of divergence mainly affected the alignment mean percentage of identity for all four tools (which decreases linearly), but had more drastic effects on MAUVE and ProgressiveMAUVE alignments than on YOC and MUMmer alignments.",
"Six genome aligners, all based on the anchoring strategy, were compared on the previously described genome datasets; two state-of-the-art aligners, MGA [4] and LAGAN [14], clearly target collinear genomes, three others, MAUVE [5], ProgressiveMAUVE [6] and MUMmer [9] are able to align either rearranged or collinear genomes whatever their type of rearrangements, while our new method, YOC, aligns pairs of collinear genomes (possibly including locally inversed segments but no translocated segments).",
"Despite many efforts in this field and the availability of numerous genome aligners, some of which were specially designed for bacterial genomes (e.g., MGA , MAUVE , ProgressiveMAUVE , MUGSY , MAGIC ) and others that target more complex genomes (e.g., MUMmer , GRIMM-Synteny , CHAINNET , PipMaker ), none is yet completely satisfactory."
]
}
}
2026-04-05 06:49:46
urn:uuid:6addf783-8f7c-4b42-95fd-0e4bf2cb9aee
https://datalake.inria.fr
https://inria.hal.science
["Offer","coar-notify:ReviewAction"]
{
"@context": [
"https://www.w3.org/ns/activitystreams",
"https://purl.org/coar/notify"
],
"id": "urn:uuid:6addf783-8f7c-4b42-95fd-0e4bf2cb9aee",
"type": [
"Offer",
"coar-notify:ReviewAction"
],
"actor": {
"id": "https://datalake.inria.fr",
"type": "Service",
"name": "Inria DataLake"
},
"origin": {
"id": "https://datalake.inria.fr",
"type": "Service",
"inbox": "https://prod-datadcis-api.inria.fr/coar/inbox"
},
"target": {
"id": "https://inria.hal.science",
"type": "Service",
"inbox": "https://inbox.hal.science"
},
"object": {
"id": "https://hal.science/lirmm-01170968v1",
"ietf:cite-as": null,
"sorg:citation": {
"@context": "https://doi.org/10.5063/schema/codemeta-2.0",
"type": "SoftwareSourceCode",
"name": "GBrowse",
"codeRepository": null,
"referencePublication": null
},
"mentionType": "software",
"mentionContext": [
"Regarding the lack of a graphic interface, several tools like ACT , Artemis , GBrowse or MOSAIC , propose adaptable graphical viewers that can be used with YOC."
]
}
}