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182 results for “MSS”
MCR LTER: Reference: Satellite Remote Sensing: Landsat MSS in 1979
This LTER Remote Sensing spatial raster dataset consists of Landsat Multi-Spectral Scanner (MSS) image data collected in 1979 over the island of Moorea and Tahiti. These are reference data, from the USGS EROS archive, not data generated by MCR LTER. This product was created by the U.S. Geological Survey (USGS) and contains Landsat data files in Geographic Tagged Image-File Format (GeoTIFF). NASA Landsat Program, 2010, Landsat MSS scene L3057072_07219790206_MTL, LPGS_11.2.1, USGS, Sioux Falls, 1979-02-06.
APPENDIX 2 in Cholevinae (Coleoptera: Leiodidae) of the Sierra de Guadarrama National Park, Spain: occurrence in the MSS of a siliceous landscape
APPENDIX 2. — Distribution maps of all the Cholevinae species collected in the MSS of the Sierra de Guadarrama National Park, except for Choleva (Cholevopsis) punctata Brisout, 1866.
FIG. 6 in Cholevinae (Coleoptera: Leiodidae) of the Sierra de Guadarrama National Park, Spain: occurrence in the MSS of a siliceous landscape
FIG. 6. — Relation between the pronotum width (PWmid) and the pronotum length (PL) of both sexes of Choleva (Cholevopsis) punctata Brisout, 1866.
FIG. 3 in Cholevinae (Coleoptera: Leiodidae) of the Sierra de Guadarrama National Park, Spain: occurrence in the MSS of a siliceous landscape
FIG. 3. — Distribution of Choleva (Cholevopsis) punctata Brisout, 1866 in the MSS of the Sierra de Guadarrama National Park. Legends and symbols: ● subterranean sampling devices (SSDs); Δ, talus pitfall traps (TSP); ● and presence of C. (C.) punctata. The combination of the different manifestations of the aedeagus with the different morphologies of the metatrochanter is shown for each SSD following the classification of Figs 6; 7.
FIG. 9 in Cholevinae (Coleoptera: Leiodidae) of the Sierra de Guadarrama National Park, Spain: occurrence in the MSS of a siliceous landscape
FIG. 9. — Female genitalia of Choleva (Cholevopsis) punctata Brisout, 1866: A, left lateral vision; B dorsal vision without IX ltg and IX mtg; C, dorsal vision with complete genital shield; D, ventral vision; E, detail of the female genital armor. Scale bars: A, D, 0.5 mm; E, 0.2 mm. Abbreviations: see Material and methods. The abbreviations associated with the genital shield are those used by Deuve (1993).
FIG. 8 in Cholevinae (Coleoptera: Leiodidae) of the Sierra de Guadarrama National Park, Spain: occurrence in the MSS of a siliceous landscape
FIG. 8. — The morphological diversity of the Choleva (Cholevopsis) punctata Brisout, 1866 metatrochanter from Sierra de Guadarrama: A-F, external spiny angle (hollow arrow with continuous contour), inner spiny angle (hollow arrow with discontinuous contour), and medial spine (solid arrow). Scale bar: 1 mm.
FIG. 7 in Cholevinae (Coleoptera: Leiodidae) of the Sierra de Guadarrama National Park, Spain: occurrence in the MSS of a siliceous landscape
FIG. 7. — Different states of evagination of the inner sac with respect to the median lobe of the aedeagus of Choleva (Cholevopsis) punctata Brisout, 1866. Categorized in columns (I-IV states) and in rows. Abbreviations: lat, lateral view; v, ventral view. Scale bars: 1 mm.
FIG. 1 in Cholevinae (Coleoptera: Leiodidae) of the Sierra de Guadarrama National Park, Spain: occurrence in the MSS of a siliceous landscape
FIG. 1. — Locations of the 33 scree slopes and four talus that were sampled in the Sierra de Guadarrama National Park and in the surrounding area. Symbols: ●, subterranean sampling devices (SSDs); ∆, talus pitfall traps (TSPs).
FIG. 2 in Cholevinae (Coleoptera: Leiodidae) of the Sierra de Guadarrama National Park, Spain: occurrence in the MSS of a siliceous landscape
FIG. 2. — Sampled habitats and sampling devices: A, a typical scree slope; B, placement of a subterranean sampling device (SSD); C, a talus on a scree slope; D, placement of a talus slope pitfall traps (TSP).
FIG. 5 in Cholevinae (Coleoptera: Leiodidae) of the Sierra de Guadarrama National Park, Spain: occurrence in the MSS of a siliceous landscape
FIG. 5. — Habitus of Cholevinae Kirby, 1837 species captured in this study: A, Speonemadus angusticollis (Kraatz, 1870); B, Speonemadus clathratus (Perris, 1864); C, Speonemadus vandalitiae (Heyden, 1870); D, Attumbra josephinae josephinae (Saulcy, 1862); E, Catops fuliginosus Erichson, 1837; F, Catops fuscus fuscus (Panzer, 1794); G, Catopsimorphus (Attiscurra) marqueti Fairmaire, 1857; H, Catopsimorphus (Weiratherella) rougeti Saulcy, 1864; I, Choleva (Choleva) cisteloides (Frolich, 1799); J, Choleva (Cholevopsis) punctata Brisout, 1866; K, Sciodrepoides watsoni watsoni (Spence, 1815); L, Ptomaphagus (Ptomaphagus) tenuicornis tenuicornis (Rosenhauer, 1856). Scale bars: 1 mm.
FIG. 4 in Cholevinae (Coleoptera: Leiodidae) of the Sierra de Guadarrama National Park, Spain: occurrence in the MSS of a siliceous landscape
FIG. 4. — Species accumulation curves for the complete inventory of the Sierra de Guadarrama National Park: A, sample-based species accumulation curve using the subterranean sampling devices (SSDs) as effort units (empty circles); 95% confidence interval as grey bands, and Chao2 curve (stripped line); B, nonparametric richness estimators.
SDUST2020 MSS: A global 1′×1′ mean sea surface model determined from multi-satellite altimetry data
<p>SDUST2020 MSS (Shandong University of Science and Technology 2020 mean sea surface) model with a grid of 1′×1′ is established with 19-year moving average method from multi-satellite altimetry data over 27-year (from January 1993 to December 2019). Its spatial coverage is 80°S-84°N. The missions data of Topex/Poseidon, Jason-1, Jason-2, Jason-3, ERS-1, ERS-2, GFO, Envisat, SARAL, HY-2A, Sentinel-3A and Cryosat-2 are ingested in the SDUST2020 MSS model.</p>
OCR model for Pracalit for Sanskrit and Newar MSS 16th to 19th C., Ground Truth
<p>Ground truth data (png and xml files) for a an OCR model. Will be continually updated.</p> <p>Originally trained on Transkribus with a PyLaia model created from ground truth data based on transcripts into Pracalit Unicode of four Nepalese manuscripts. The manuscripts used to create this model are Staatsbibliothek zu Berlin's Hitopadeśa (MIK I 4851) (mixed Newar and Sanskrit dating to 1561) and Vetālapañcaviṃśati (HS. Or. 6414) (Newar dating to 1675) as well as Cambridge Digital Library's Avalokiteśvaraguṇakāraṇḍavyūha (MS Add. 1322) (Sanskrit, 18th century) and the Royal Asiatic Society Online Collection's Madhyamasvayaṃbhūpurāṇa (RAS Hodgson MS 23) (Newar and Sanskrit dating to c. 1800).</p> <p>The training was done on 441 pages and validation on 242 pages.</p> <p>This model does not recognise spacing, except for large gaps (i.e. for pictures or string holes). Newar word divider markers may not be represented or may be transcribed as virama. In general, the model is made for MSS with scriptio continua and will transcribe into scriptio continua into Pracalit Unicode.</p> <p>Transcription was performed by Dr Alexander O'Neill (SOAS University of London). Transcription of the Vetālapañcaviṃśati (HS. Or. 6414) and Madhyamasvayaṃbhūpurāṇa (RAS Hodgson MS 23) was aided by unpublished materials provided by Dr Felix Otter (Philipps-Universität Marburg), as well as the published transcription in Shakya, Min Bahadur, and Shanta Harsha Bajracharya, eds. "Svayambhū Purāṇa." Lalitpur: Nagarjuna Institute of Exact Methods, 2001. The transcription of Avalokiteśvaraguṇakāraṇḍavyūha (MS Add. 1322) was aided by the transcription provided by the Digital Sanskrit Buddhist Canon Project based on Lokesh Chandra, "Guṇakāraṇḍavyūhasūtram," New Delhi: International Academy of Indian Culture, 1999.</p>
Dataset: Maison Solutions Inc. (MSS) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
FIG. 5 in Polydesmid millipedes in the MSS of the northern Iberian Peninsula (Diplopoda, Polydesmida, Polydesmidae)
FIG. 5. — Gonopods of two of the six species collected: A-C, right (A, C) and left (B) gonopods of Polydesmus asturiensis Djursvoll, 2019 from Llobango (LLO) in mesal (A), lateral (B) and ventro-anteromesal (C) view; D-F, left (D) and right (E-F) gonopods of Polydesmus racovitzai BrÖlemann, 1910 from Sierra del Mencilla (MEF) in lateral (D) and mesal (E-F) view. Scale bars: A-C, 0.1 mm; D, 0.2 mm; E, 0.1 mm; F, 0.2 mm.
FIG. 4 in Polydesmid millipedes in the MSS of the northern Iberian Peninsula (Diplopoda, Polydesmida, Polydesmidae)
FIG. 4. — Gonopods of four of the six species collected: A, left gonopod of Archipolydesmus osellai Ceuca, 1968 from the Sierra de Mencilla (MEF) in lateral view; B, right gonopod of Polydesmus angustus Latzel, 1884 from the Sierra Mediana (PES) in mesal view; C, left gonopod of Polydesmus coriaceus Porat, 1870 from the Sierra de Santo Domingo (SDF) in lateral view; D, left gonopod of Propolydesmus dismilus (Berlese, 1891) from the Sierra de Luesia (SL1) in lateral view. Scale bars: 0.5 mm.
FIG. 2 in Polydesmid millipedes in the MSS of the northern Iberian Peninsula (Diplopoda, Polydesmida, Polydesmidae)
FIG. 2. — Examples of sampled landscapes: A, scree in the glacier circus of Mencilla (MEB); B, beech forest over scree in Moncayo mountain (MOF); C, forested scree in the Sierra de Santo Domingo (SDF); D, alluvial debris in the Arba de Luesia river (SL2); E, scree in the Piedras Luengas Pass (PLB); F, scree in Calar de San Martino (CMA).
FIG. 1 in Polydesmid millipedes in the MSS of the northern Iberian Peninsula (Diplopoda, Polydesmida, Polydesmidae)
FIG. 1. — Location of sampling sites and installation of subterranean sampling devices (SSDs): A, physical map of the northern Iberian Peninsula with sampling points marked in green (Cantabrian Range), yellow (Iberian System) and blue (Pyrenees); codes as in Table 1; B, hole digging in a scree; C, multiperforated tube (1 m) placed in the hole; D, buried tube with open top and pitfall trap about to be installed inside; E, fully installed SSD and covered with stones.
Strong histopathological relevance patches for MSI vs. MSS classification
<p>This is a subset of dataset "Histological images for MSI vs. MSS classification in gastrointestinal cancer, FFPE samples" CRC_DX[1]. For more details, please visit [1]. After a fused distillation, a neural network based framework will vote for the candidates for the histopathological strong relevance patches. We incorporate the morphology knowledge from pathologists to sort out the most representative samples and tag them to this subdata.</p> <p>The dataset has two labels i.e., MSIMUT_strong and MSS_strong.</p> <p>MSIMUT_strong : 28 307 patches.</p> <p>MSS_strong : 27 146 patches.</p> <p>[1] Histological images for MSI vs. MSS classification in gastrointestinal cancer, FFPE samples. https://doi.org/10.5281/zenodo.2530835</p>
Cell Graph data for predicting MSI vs. MSS from histological images
<p><strong>Abstract: </strong>The cell graph data extracted from histological images for predicting microstatellite status. This is a patch-level (patch refers to the sub-image tessellated from the whole-slide image) binary classification task: the two datasets classify images patches to either MSS (microsatellite stable) or MSIMUT (microsatellite instable or highly mutated). The original histology patches are available from [1]. </p> <p><strong>Cell Graph Contraction:</strong> In this dataset, we establish a cell graph for each patch. The cell graph can represent the cell-cell interaction and the collection of cell graphs for all patches provide a precise characterization of tumor microenvironment. With only the availability of raw image patches, we leverage the nuclei regions segmented by a well-tuned CA<sup>2.5</sup>-Net [2] to extract the node features of each single nuclei node. And then we extract a total number of 94 pre-defined pathomics features for each nuclei region as the corresponding graph node feature. As the morphological signals are believed relative to cell-cell interplay, the cell-specific features which include the nuclei coordination, optical, and representations, then characterize the cell-level morphological behavior. We then calculate the pair-wise Euclidean distance between nuclei centroids to establish edges of a cell graph</p> <p><strong>Reference</strong></p> <p>For more details about the construction of cell-graph, please visit our paper: https://arxiv.org/abs/2206.07599.</p> <p>The associated codes and usage for the datasets are available at: https://github.com/yiqings/HEGnnEnhanceCnn.</p> <p>[1] Histological images for MSI vs. MSS classification in gastrointestinal cancer, FFPE samples. https://doi.org/10.5281/zenodo.2530835</p> <p>[2] Huang, J., Shen, Y., Shen, D., & Ke, J. (2021, September). CA 2.5-Net Nuclei Segmentation Framework with a Microscopy Cell Benchmark Collection. In <em>International Conference on Medical Image Computing and Computer-Assisted Intervention</em> (pp. 445-454). Springer, Cham.</p>
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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
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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.