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26,784 results for “M.”
High-resolution (5 m) surface water persistence map for 2021 in East-Africa
<p>Raster surface water image highlighting the percentage of time in 2021 that there was water at a certain pixel in East Africa. </p> <p>Script which classifies individual countries: <a href="https://code.earthengine.google.com/3f508773522979dfa62a75bda7750b5f?noload=true">https://code.earthengine.google.com/3f508773522979dfa62a75bda7750b5f?noload=true</a></p> <p>Script which combines the individual maps and filters the end-result: <a href="https://code.earthengine.google.com/ed8ee1bbade0b51f3759565b30da37ab?noload=true">https://code.earthengine.google.com/ed8ee1bbade0b51f3759565b30da37ab?noload=true</a></p> <p> </p>
FIG. 25. — A-M, Malumella oblonga n. gen., n in The species of Lageninae Brady, 1881 (Foraminifera) from the Pliocene-Early Pleistocene of north-western France, Fécamp (Seine-Maritime, France) and St Erth (Cornwall, United Kingdom)
FIG. 25. — A-M, Malumella oblonga n. gen., n. sp.: A-D, holotype, Mernel (MNHN.F.F67711); A, lateral view; B, perforated wall; C, D, oral and basal views; E-I, paratype, Auxais (MNHN.F.F67712); E, lateral view; F, perforated wall; G, H, oral and basal views; I, enlargement basal views; N-P, Malumella suboblonga n. gen., n. sp., la Bouillonnaie, holotype (MNHN.F.F67714): N, lateral view; O, perforated wall; P, perforated wall on the neck. Scale bars: A, E, J, L, N, 200 µm; B, F, K, M, O, 50 µm; C, D, G, H, 100 µm; I, 20 µm; P, 10 µm.
FIG. 21. — A-M in The species of Lageninae Brady, 1881 (Foraminifera) from the Pliocene-Early Pleistocene of north-western France, Fécamp (Seine-Maritime, France) and St Erth (Cornwall, United Kingdom)
FIG. 21. — A-M, Lagunculella flexa (Cushman & Gray, 1946), n. comb.: A, SSL (MNHN.F.F67693), basal view; C-F, la Chênelière (MNHN.F.F67694): C, lateral, D, enlargement neck; E, F, oral and basal views; G-J, la Sautré (MNHN.F.F67695): G, lateral view; H, perforated wall; I, J, oral and basal views; K-M, la Pugle (MNHN.F.F67696) in lateral, oral and basal views; N-P, Lagunculella ovoidea n. gen., n. sp., la Pugle, holotype (MNHN.F.F67697) in lateral, oral and basal views. Scale bars: A, B, I, J, N, O, P, 100 µm; C, E, F, G, K, 200 µm; D, L, M, 50 µm; H, 20 µm.
Data for: Predicting age and mass at maturity from feeding behavior and diet in M. sexta: An empirical test of a life history model
<p>Feeding for most animals involves bouts of active ingestion alternating with bouts of no ingestion. In insects, the temporal patterning of bouts varies widely with resource quality and is known to affect growth, development time, and fitness. However, the precise impacts of resource quality and feeding behavior on insect life history traits is poorly understood. To explore and better understand the connections between feeding behavior, resource quality and insect life history traits, we combined laboratory experiments with a recently proposed mechanistic model of insect growth and development for a larval herbivore, <em>Manduca sexta</em>. We ran feeding trials for 4<sup>th</sup> and 5<sup>th</sup> instar larvae across different diet types (two hostplants and artificial diet) and used these data to parameterize a joint model of age and mass at maturity that incorporates both insect feeding behavior and hormonal activity. We found that the estimated durations of both feeding and non-feeding bouts were significantly shorter on low- than on high-quality diets. We then explored how well the fitted model predicted historical out-of-sample data on age and mass of <em>M</em>.<em> sexta</em>. We found that the model accurately described qualitative outcomes for the out-of-sample data, notably that a low-quality diet results in reduced mass and later age at maturity compared to high-quality diets. Our results clearly demonstrate the importance of diet quality on multiple components of insect feeding behavior (feeding and non-feeding), and partially validate a joint model of insect life history. We discuss the implications of these findings with respect to insect herbivory and discuss ways in which our model could be improved or extended to other systems.</p>
RVFV data aligning only to M-Fragment to test the PARANOiD pipeline
<p>PARANOiD is a versatile software for fully automated analysis of iCLIP and iCLIP2 data. It contains all steps necessary for preprocessing, the determination of cross-link locations and several additional steps, which can be used to detect specific characteristics, e.g. definite distances between cross-link events or identify binding motifs. The cross-link sites are presented as WIG files that can be easily visualized e.g. using IGV, for which a config file is offered. Additionally, results are offered as statistical plots for a quick overview and as standardized bioinformatics file formats or TSV files, which can be used for further analysis steps.</p> <p>The data provided are used as a test case for PARANOiD.</p> <p>The data was extracted from RVFV MP-12 virions (virion-reads-M-fragment-only.fastq) and BHK cells infected with RVFV (BHK-reads-M-fragment-only.fastq) applying the iCLIP2 method for RVFV N iCLIP. Three independent biological replicates were performed for each sample. Sequencing was performed using the MiSeq Sequencer (Illumina) with MiSeq Reagent Kit v2 Micro (Illumina) for N-iCLIP from virus particles and MiSeq Reagent Kit v3 (Illumina) for N-iCLIP from infected BHK cells.</p> <p>The original reads have been aligned to the RVFV MP-12 reference genome and only reads aligning to the M-fragments were extracted. The whole dataset will be publish at a later date</p> <p>File description:</p> <p>virion-reads-M-fragment-only.fastq - Reads obtained from RVFV virions</p> <p>BHK-reads-M-fragment-only.fastq - Reads obtained from BHK cells infected with RVFV</p> <p>reference_RVFV.fasta - RVFV MP-12 reference genome</p> <p>barcodes-RVFV.tsv - Barcodes for virion-reads-M-fragment-only.fastq</p> <p>barcodes-RVFV-merge-all.tsv - Barcodes for merging all samples of virion-reads-M-fragment-only.fastq</p> <p>barcodes-BHK.tsv - Barcodes for BHK-reads-M-fragment-only.fastq</p> <p>barcodes-BHK-merge-all.tsv - Barcodes for merging all relevant samples of BHK-reads-M-fragment-only.fastq</p>
Supplementary data and code to "Known allosteric proteins have central roles in genetic disease" by G. Abrusan, D. Ascher and M. Inouye, PLOS Computational Biology 18(2):e1009806.
<p>Scripts and data to reproduce the figures and supplementary figures of "G. Abrusan, D. Ascher and M. Inouye (2022) Known allosteric proteins have central roles in genetic disease." PLOS Computational Biology 18(2):e1009806. https://doi.org/10.1371/journal.pcbi.1009806.</p>
Supplementary data for the manuscript entitled "Evolution of the convective boundary layer in a WRF simulation nested down to 100 m resolution during a cloud-free case of LAFE 2017 and comparison to observations" (JGR Atmospheres)
<p>This dataset contains additional material to reproduce the simulation and some of the figures of the manuscipt entitled "Evolution of the convective boundary layer in a WRF simulation nested down to 100 m resolution during a cloud-free case of LAFE 2017 and comparison to observations" in the Journal of Geophysical Reasseach - Atmospheres.</p>
Tsetse flies (Glossina m. morsitans) choose birthing sites guided by substrate cues with no evidence for a role of pheromones
<p>Tsetse flies significantly impact public health and economic development in sub-Saharan African countries by transmitting the fatal disease African trypanosomiasis. Unusually, instead of laying eggs, tsetse birth a single larva that immediately burrows into the soil to pupate. Where the female chooses to larviposit is therefore crucial for offspring survival. Previous laboratory studies suggested that a putative larval pheromone, n-pentadecane, attracts gravid female <em>Glossina morsitans</em> <em>morsitans</em> to appropriate larviposition sites. However, this attraction could not be reproduced in field experiments. Here, we resolve this disparity by designing naturalistic laboratory experiments that closely mimic the physical characteristics found in the wild. We show that gravid <em>G.</em> <em>m. morsitans</em> were neither attracted to the putative pheromone nor, interestingly, to pupae placed in the soil. In contrast, females appear to choose larviposition sites based on environmental substrate cues. We conclude that, among the many cues that likely contribute to larviposition choice in nature, substrate features are a main determinant, while we failed to find evidence of a role of pheromones.</p>
A 5 m topographic wetness index (TWI) across France
<p>The topographic wetness index (TWI) characterizes potential soil wetness as a function of the contributing area and local slope. It was derived from the national airborne DTM (RGE ALTI ®) at 5 m spatial resolution, which is available from the website of the French National Geographic Institute (IGN) (<a href="https://geoservices.ign.fr/">https://geoservices.ign.fr/</a>).</p> <p>Dataset includes:</p> <ul> <li>280 GeoTIFF raster files (TWI_000.tif) projected in the French Lambert-93 system (EPSG code 2154), each file corresponding to a 50 x 50 km tile. The number indicates the tile of interest ;</li> <li>1 vector tile index at Google Earth format (tile_index.kmz) showing the location of each tile. This file has been created to facilitate download layer only on area of interest.</li> </ul> <p>To reduce storage space and download time, each raster file has been packed at 7-Zip freeware format.</p> <p>A complete description of the dataset can be found in Panhelleux, L., Rapinel, S., Lemercier, B., Gayet, G., Hubert-Moy, L., 2023. A 5 m dataset of digital terrain model derivatives across mainland France. Data in Brief 109369. https://doi.org/10.1016/j.dib.2023.109369</p>
A 5 m vertical distance to channel network index (VDCNI) across France
<p>The vertical distance to channel network index (VDCNI) expresses the vertical height (in meter) between the elevation of a pixel and the nearest channel. It was derived from the national airborne DTM (RGE ALTI ®) at 5 m spatial resolution, which is available from the website of the French National Geographic Institute (IGN) (<a href="https://geoservices.ign.fr/">https://geoservices.ign.fr/</a>), and the GIS layer of the channel network in the national hydrological database <a href="https://www.sandre.eaufrance.fr/atlas/srv/fre/catalog.search#/metadata/3b3d3c56-d9b6-4625-a57e-ba054e798274">https://www.sandre.eaufrance.fr/atlas/srv/fre/catalog.search#/metadata/3b3d3c56-d9b6-4625-a57e-ba054e798274</a>.</p> <p>Dataset includes:</p> <ul> <li>280 GeoTIFF raster files (VDCNI_000.tif) projected in the French Lambert-93 system (EPSG code 2154), each file corresponding to a 50 x 50 km tile. The number indicates the tile of interest ;</li> <li>1 vector tile index at Google Earth format (tile_index.kmz) showing the location of each tile. This file has been created to facilitate download layer only on area of interest.</li> </ul> <p>To reduce storage space and download time, each raster file has been packed at 7-Zip freeware format.</p> <p>A complete description of the dataset can be found in Panhelleux, L., Rapinel, S., Lemercier, B., Gayet, G., Hubert-Moy, L., 2023. A 5 m dataset of digital terrain model derivatives across mainland France. Data in Brief 109369. https://doi.org/10.1016/j.dib.2023.109369</p>
A 5 m multi-scale topographic position color composite (MTPCC) across France
<p>The multi-scale topographic position color composite (MTPCC) describes the position of a pixel relative to its neighborhood at several spatial scales. It was derived from the national airborne DTM (RGE ALTI ®) at 5 m spatial resolution, which is available from the website of the French National Geographic Institute (IGN) (<a href="https://geoservices.ign.fr/">https://geoservices.ign.fr/</a>).</p> <p>Dataset includes:</p> <ul> <li>280 GeoTIFF raster files (MTPCC_000.tif) projected in the French Lambert-93 system (EPSG code 2154), each file corresponding to a 50 x 50 km tile. The number indicates the tile of interest ;</li> <li>1 vector tile index at Google Earth format (tile_index.kmz) showing the location of each tile. This file has been created to facilitate download layer only on area of interest.</li> </ul> <p>To reduce storage space and download time, each raster file has been packed at 7-Zip freeware format.</p> <p>A complete description of the dataset can be found in Panhelleux, L., Rapinel, S., Lemercier, B., Gayet, G., Hubert-Moy, L., 2023. A 5 m dataset of digital terrain model derivatives across mainland France. Data in Brief 109369. https://doi.org/10.1016/j.dib.2023.109369</p>
FIG. 5. — Paramicrosphaeropsis zagrosensis M in Revision of the Microsphaeropsis complex with addition of four new Paramicrosphaeropsis L.W.Hou, L.Cai & Crous species from Zagrosian forest trees in Iran
FIG. 5. — Paramicrosphaeropsis zagrosensis M.Mehrabi-Koushki, S.Artand, K.D.Hyde & Jayaward., sp. nov. (holo-, IRAN[17600F]): A, B, eight-days colony on OA (top and reverse); C, D, eight-days colony on PDA (top and reverse); E, F, old colony on OA (top and reverse); G-I, pycnidia; J, pycnidal wall; K, conidiogenous cells; L, conidia. Scale bars: G, H, 500 µm; I, 200 µm; J, 50 µm; K, L, 20 µm.
FIG. 4. — Paramicrosphaeropsis salandica M in Revision of the Microsphaeropsis complex with addition of four new Paramicrosphaeropsis L.W.Hou, L.Cai & Crous species from Zagrosian forest trees in Iran
FIG. 4. — Paramicrosphaeropsis salandica M.Mehrabi-Koushki, S.Artand, K.D.Hyde & Jayaward., sp. nov. (holo-, IRAN[18137F]): A, B, colony on OA (eightdays and old); C, D, colony on PDA (eight-days and old); E-G pycnidia; H, pycnidal wall; I, conidiogenous cells; J, conidia. Scale bars: E, 500 µm; F, 200 µm; G, 105 µm; H-J, 20 µm.
FIG. 3. — Paramicrosphaeropsis pistacicola M in Revision of the Microsphaeropsis complex with addition of four new Paramicrosphaeropsis L.W.Hou, L.Cai & Crous species from Zagrosian forest trees in Iran
FIG. 3. — Paramicrosphaeropsis pistacicola M.Mehrabi-Koushki, S.Artand, K.D.Hyde & Jayaward., sp. nov. (holo-, IRAN[17598F]): A, B, eight-days colony on OA (top and reverse); C, D, eight-days colony on PDA (top and reverse); E, old colony on OA (top); F, G, pycnidia; H, pycnidal wall; I, conidiogenous cells; J, conidia. Scale bars: F, 500 µm; G, H, 50 µm; I, J, 20 µm.
FIG. 2. — Paramicrosphaeropsis amygdalus M in Revision of the Microsphaeropsis complex with addition of four new Paramicrosphaeropsis L.W.Hou, L.Cai & Crous species from Zagrosian forest trees in Iran
FIG. 2. — Paramicrosphaeropsis amygdalus M.Mehrabi-Koushki, S.Artand, K.D.Hyde & Jayaward., sp. nov. (holo-, IRAN[17595F]): A, B, eight-days colony on OA (top and reverse); C, D, old colony on OA (top and reverse); E, F, old colony on PDA (top and reverse); G-I, pycnidia; J, pycnidium extruding conidia; K, pycnidal wall; L, conidiogenous cells; M, conidia. Scale bars: G, 500 µm; H, 200 µm; I, 105 µm; J, 50 µm; K-M, 20 µm.
FIG. 15. — B, C, F, H, I, K, M-P, R, S in Modern taxonomic approaches to identifying diatrypaceous fungi from marine habitats, with a novel genus Halocryptovalsa Dayarathne & K.D.Hyde, gen. nov.
FIG. 15. — B, C, F, H, I, K, M-P, R, S, Halodiatrype salinicola Dayarathne & K.D.Hyde (MFLU 15-0179 – holotype); A, D, E, G, J, L, O, P, T, U, Halodiatrype avicenniae Dayarathne & K.D.Hyde (MFLU 16-1185 – holotype and MFLU – 16-1197):A, B, horizontal section of ascoma (MFLU 16-1185,MFLU 15-0179);C, D, vertical section through ascoma (MFLU 15-0179, MFLU 16-1185); E, F, peridium (MFLU 16-1185, MFLU 15-0179); G, H, section through neck (MFLU 16-1185, MFLU 15-0179); I, J, asci (MFLU 15-0179 (in Congo red), MFLU 16-1185); K, L, paraphyses (MFLU 15-0179, MFLU 16-1185); M-P, ascospores (MFLU 15-0179, MFLU 16-1185); Q, conidia from culture on PDA (MFLU 18-0150); R-U, culture on PDA (MFLU 15-0179, MFLU 16-1185) Scale bars: A, 1000 µm; B, 500 µm; C, D, I-L, 100 μm; E, F, Q, 20 μm; G-H, 50 μm; M-P, 10 μm
FIG. 13 in Disentangling cryptic species in the Marasmius haematocephalus (Mont.) Fr. and M. siccus (Schwein.) Fr. species complexes (Agaricales, Basidiomycota)
FIG. 13. — Pictures of fresh basidiomata of Marasmius haematocephalus (Mont.) Fr.: A, JO533 from Atlantic Rainforest (epitype); B, JO1363 from Amazon Forest. Scale bars: 10 mm.
FIG. 17. — Marasmius roseus J.S in Disentangling cryptic species in the Marasmius haematocephalus (Mont.) Fr. and M. siccus (Schwein.) Fr. species complexes (Agaricales, Basidiomycota)
FIG. 17. — Marasmius roseus J.S. Oliveira, sp. nov. (JO352): A, Siccus-type broom cells of the pileipellis (type 1); B, Siccus- to Rotalis-type broom cells (type 2). Scale bar: 10 µm.
FIG. 16. — Marasmius roseus J.S in Disentangling cryptic species in the Marasmius haematocephalus (Mont.) Fr. and M. siccus (Schwein.) Fr. species complexes (Agaricales, Basidiomycota)
FIG. 16. — Marasmius roseus J.S. Oliveira, sp. nov. (JO352): A, basidiomata; B, basidiospores; C, basidioles; D, pleurocystidia; E, cheilocystidia. Scale bar: A, 10.5 mm; B-E, 10 µm.
FIG. 6 in Disentangling cryptic species in the Marasmius haematocephalus (Mont.) Fr. and M. siccus (Schwein.) Fr. species complexes (Agaricales, Basidiomycota)
FIG. 6. — Pictures of fresh basidiomata: A, Marasmius bambusinus (Fr.) Fr. (JO343); B, M. gardneri Singer (JO491). Scale bars: 10 mm.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.