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1,930 results for “Matrix”
Invention and application of epoch of Kifilideen's Sum Formula for Kifilideen's General Matrix Progression Series of infinite terms in solving real-world problems
<p>*Sharing a Notable Achievement* I am honored to announce that my research paper, titled 'Invention and Application of Epoch of Kifilideen’s Sum Formula for Kifilideen’s General Matrix Progression Series of Infinite Terms in Solving Real-World Problems,' was among the three papers selected by the College of Engineering (COLENG) for presentation at the recent Science and Technology Fair/Exhibition organized by Bells University of Technology, Ota, Ogun State, Nigeria, on October 28, 2024. I am delighted to share that COLENG secured the first position in the Inter-Collegiate poster competition, a testament to the outstanding collective efforts of our researchers, staff, and team members who contributed to the success. I extend my gratitude to the Dean of Engineering for his exceptional leadership and guidance, which played a pivotal role in this achievement. Congratulations to my colleagues whose papers were also presented, and to everyone who contributed to this success. Award Recognition Sincerely, Engr. Dr. Kifilideen Lekan OSANYINPEJU Agricultural and Bio-System Engineering College of Engineering Bells University of Technology, Ota, Ogun State, Nigeria</p>
Data Matrix Theme-Specific Analysis of the Recommendation on Science and Scientific Researchers (RSSR): Open Access, Open Data, and Open Science
<p>This Table sets out findings from the mapping exercise conducted as part of the objectives of subtask 6.1 of the RRING project.</p> <p>Aim: Alignment of RRI to advance the UN SDGs.</p> <p>Objectives:</p> <ul> <li>Mapping the RSSR to the SDGs </li> </ul> <p>Mapping the RSSR to the SDGs is aimed at providing new perspectives, ideas and approaches that can help to improve the operationalization and implementation of each SDG, <em>by facilitating the integration of RRI (or RRI-like) practices in the SDGs, to make them more achievable.</em> The impact of the new perspectives, ideas and approaches in SDG operationalization and implementation will be aimed at the level of <em>national and international policy (making); future research and innovation projects (in industry and academia); as well as education and training of researchers, policy makers and other stakeholders.</em></p> <p>Two documents were used for this task:</p> <ul> <li>2017 Recommendation on Science and Scientific Researchers ([RSSR], UNESCO), and</li> <li>the United Nations 2030 Agenda for Sustainable Development with the 17 Sustainable Development Goals (SDGs).</li> </ul>
Multiply improved positive matrix factorization for source apportionment of volatile organic compounds during the COVID-19 shutdown in Tianjin, China
<p>This dataset contains the input and output data of the multiple PMF for volatile organic compounds (VOCs) source apportionment in the suburbs of Tianjin, China, during the outbreak of COVID-19 period (November 2019 to March 2020).</p>
Fig. 1. Character matrix for 30 in A Relimitation And Revision Of The Australasian Ground Spider Family Lamponidae (Araneae: Gnaphosoidea)
Fig. 1. Character matrix for 30 genera; see text for character descriptions.
Fig. 1. Character matrix for 42 in A Revision Of The Australasian Ground Spiders Of The Families Ammoxenidae, Cithaeronidae, Gallieniellidae, And Trochanteriidae (Araneae: Gnaphosoidea)
Fig. 1. Character matrix for 42 genera; see text for character descriptions.
Fig. 55. Character matrix for 22 in A Generic-Level Revision Of The Spider Subfamily Coelotinae (Araneae, Amaurobiidae)
Fig. 55. Character matrix for 22 genera. See text for character description.
Figure 5 in Character-matrix based descriptions of two new nemertean (Nemertea) species
Figure 5. Carinina ochracea sp. nov. (living specimen).
Figure 8 in Character-matrix based descriptions of two new nemertean (Nemertea) species
Figure 8. Stylet and stylet basis of Raygibsonia bergi gen. et sp. nov.
Aligned DNA sequence matrix for phylogenetic analyses in the article "Our unknown neighbor: a new species of rain frog of the genus Pristimantis (Amphibia: Anura: Strabomantidae) from the city of Loja, southern Ecuador"
<p>The aligned matrix is in fasta format. Genes are arranged as follows:</p> <p>12S = 1–909</p> <p>16S = 910–1787</p> <p>RAG-1 = 1788–2399</p>
SNP genotype matrix for GWAS and Machine Learning analyses
<p><strong>SNP datasets used for GWAS and Machine Learning analyses</strong></p> <p>All datasets come from the easyGWAS website: <a href="https://easygwas.ethz.ch/down/1/">https://easygwas.ethz.ch/down/1/</a></p> <p> </p> <p><strong>=== Horton et al. 2012 ===</strong></p> <p><strong>1307 Arabidopsis genotypes x 214,057</strong> <strong>SNPs</strong></p> <p><strong>1) In the form of a genotype matrix </strong></p> <p>The file is called <a href="https://zenodo.org/api/files/d862e79f-02f2-4176-9b8e-04e48a2cf72c/horton2012.raw?versionId=2b05fb8d-b486-4f00-b7bf-bb024b892dc9">Horton2012.raw</a></p> <p><a href="https://www.nature.com/articles/ng.1042">https://www.nature.com/articles/ng.1042</a></p> <p>Preview of the first lines and columns:</p> <p>FID Chr1_657_T Chr1_3102_G Chr1_4648_A Chr1_4880_T Chr1_5975_G Chr1_6063_T Chr1_6449_C<br> 9381 2 2 2 0 0 0 0<br> 9380 0 0 0 0 0 0 2<br> 9378 2 2 2 0 0 0 0<br> 9371 2 2 2 0 0 0 0<br> 9367 0 0 0 2 0 0 0<br> 9363 2 2 2 0 0 0 0<br> 9356 0 2 2 0 0 0 0<br> 9355 2 2 2 0 0 0 0<br> 9354 2 2 2 0 0 0 0</p> <p>...etc...</p> <p>PLINK 1.9 was used to convert the .ped and .map file to a .raw format with: </p> <pre><code class="language-bash">plink --file original_data/genotype --recodeA --tab</code></pre> <p>Genotypes are encoded as 0, 1 or 2 with:</p> <pre> SNP SNP_A --- ----- A A -> 0 A C -> 1 C C -> 2 0 0 -> NA </pre> <p>Then only the Family ID was kept (same as individual ID) and other columns (Paternal ID, Maternal ID, Sex, Phenotype) were removed.</p> <p>The corresponding PLINK manual page used is here: <a href="https://zzz.bwh.harvard.edu/plink/dataman.shtml#recode">https://zzz.bwh.harvard.edu/plink/dataman.shtml#recode</a></p> <p><strong>1) In the form of set of files compatible with PLINK out of the box</strong></p> <p>The archive file is called <a href="https://zenodo.org/api/files/b34fd40e-2db1-47b0-92c8-0ad51ad92d46/AtPolyDB_call_method_75_Horton2012.tar.gz">AtPolyDB_call_method_75_Horton2012.tar.gz</a> and contains three files:</p> <ul> <li>genotype.ped: pedigree information from the 1307 ecotypes</li> <li>genotype.map: the SNP positions on the genome</li> <li>phenotypes.pheno: the phenotype value of the 1307 ecotypes</li> </ul> <p> </p>
Dataset for Assessing Multi-Dimensional Impacts of Achieving Sustainability Goals by Projecting the Sustainable Agriculture Matrix into the Future
<p>This data repository feeds into the meta-repository setup for post-processing of GCAM-SAM outputs. GitHub link of meta-repository is: <a href="https://github.com/JGCRI/Kyle-etal_2022_EF">https://github.com/JGCRI/Kyle-etal_2022_EF</a> <br> <br> Folders: <br> <strong>model/</strong> is the static version of the model used to simulate 8 scenarios. See the <a href="https://github.com/pkyle/gcam-core/tree/gpk/paper/sam">GitHub GCAM-SAM repository</a> to follow active development of this model. <br> <strong>inputs/</strong> folder contains input datasets and scripts used to prepare files while postprocessing. This is to be used with <a href="https://github.com/JGCRI/Kyle-etal_2022_EF">GitHub post-processing meta-repository</a>. <br> <strong>outdata/</strong> contains <a href="http://github.com/pkyle/gcam-core/tree/gpk/paper/sam">GCAM-SAM</a> output and <a href="http://github.com/JGCRI/Kyle-etal_2022_EF">post-processed</a> output files used to plot figures. <br> <br> Key files: <br> <em><strong>SAM-matrix.dat</strong></em> is the consolidated GCAM-SAM output. Use <em>proj_load.R</em> in the <a href="https://github.com/JGCRI/Kyle-etal_2022_EF">metarepo</a> to read the file. <br> <em><strong>region_vals.csv</strong></em> has all 8 indicators in all 8 scenarios for years 2020 till 2100 on a 10 year time step. <br> <br> Short introduction to the study:</p> <p>In this paper sustainable agriculture matrix (SAM) is estimated to 2100 using Global Change Analysis Model (GCAM). We model combinatorial variations of yield intensification, dietary shift, and greenhouse gas mitigation scenarios. Findings include scenarios having significant tradeoffs across multiple environmental, economic, and social dimensions. Assessment of these multi-dimensional tradeoffs in a consistent framework improves the quality of information for decision-making.<br> <br> Should you have any questions, feel free to reach out Page Kyle at <a href="mailto:pkyle@pnnl.gov">pkyle@pnnl.gov</a>. </p>
Raw, unprocessed SEM data images for: Figure 1: Scanning electron microscope images of "type-1 bone collagen" demineralized bone matrix fibrils
<p>Raw, unprocessed SEM data images for Figure 1 of the manuscript: Scanning electron microscope images of "type-1 bone collagen" demineralized bone matrix fibrils. (A) Fibrils from the <em>B</em>. <em>taurus</em> extant long bone control. Prominent banding (~67nm) is present that is characteristic of type-1 collagen protein fibrils (Boatman et al., 2019; Gottardi et al., 2016; Lin et al., 1993; Rabotyagova et al., 2008; Tzaphlidou, 2005). (B) Permafrost YG 610.2397 <em>M</em>. <em>primigenius</em> demineralized bone matrix fibrils. An ~67nm banding pattern on the fibrils is also observed but is somewhat less distinct in comparison to that of the extant <em>B</em>. <em>taurus</em> specimen. (C) Observed fibril structures in the temperate MOR 91.72 <em>M</em>. <em>columbi</em> specimen. Fibril banding is generally absent, suggesting the original chemical state of the type-1 collagen fibrils/sequences is substantially altered.</p>
Stereo-seq E12.5_E1S3 bin 200 expression matrix (dgC Matrix), spatial locations (.csv), and h5ad file (scanpy flavor)
<p>Expression matrix in rds file format and spatial locations of E12.5_E1S3 downloaded from the Mouse Organogenesis Spatiotemporal Transcriptomic Atlas. Files were processed using an adapted version of the STOMICS Analysis Workflow (SAW) pipeline. </p>
Correlation matrix of power spectrum
<p>Correlation matrix obtained from the BAM halo mock catalogs and the SLICS references computed in real and<br> redshift space.</p>
Mygalomorph spiders: Discrete data matrix of burrow construction behavior and somatic morphology
<p>Mygalomorph spiders (trapdoor spiders and their kin) have long been associated with high levels of homoplasy, and many convergent features can be intuitively associated with different behavioral niches. This dataset includes two discrete behavioral characters and 55 somatic morphological characters (scored from adult females), for 110 genera of mygalomorph spiders, along with a complete reference list and exemplar list used when constructing the dataset. This dataset was used to reconstruct the evolution of burrowing behavior in the Mygalomorphae, compare the influence of behavior and evolutionary history on somatic morphology, and test hypotheses of correlated evolution between specific morphological features and behavior. The results revealed the simplicity of the mygalomorph adaptive landscape, with opportunistic, web-building taxa at one end, and burrowing/nesting taxa with structurally-modified burrow entrances (e.g., a trapdoor) at the other. Shifts in behavioral niche, in both directions, are common across the evolutionary history of the Mygalomorphae, and several major clades include taxa inhabiting both behavioral extremes. Somatic morphology is heavily influenced by behavior, with taxa inhabiting the same behavioral niche often more similar morphologically than more closely-related but behaviorally-divergent taxa.</p>
Grey Level Co-Occurrence Matrix and Learning Algorithms to Quantify and Classify Use-Wear on Experimental Flint Tools
<p>These are the images and the grey levels co-occurence matrix analysis results from my experimental dataset</p>
Example gene expression matrix used in SimpleTidy_GeneCoEx repo
<p>Gene expression matrix generated by kallisto. Data from Shinozaki et al., 2018. (DOI: 10.1038/s41467-017-02782-9)</p>
Disease matrix
<p>Matrix juxtaposing 125 zoonotic diseases with disease-specific arguments on several exclusion criteria ((i) the pathogen is merely food- or waterborne, (ii) the pathogen is only relevant due to its antimicrobial resistance, (iii) the pathogen is not zoonotic or a zoonotic potential is very unlikely/not scientifically proven, (iv) the pathogen has no or only negligible public health impact, (v) the pathogen poses no or only negligible risk of introduction into the EU (i.e. reservoirs or vectors are not present), (vi) the pathogen has no animal host, (vii) the exact pathogen species is not mentioned) in the context of the initiative ‘CP-g-22-04.01 Direct grants to Member States’ authorities’ of the EU4Health Programme</p>
Accurate resampling of radial dose point kernels to a Cartesian matrix for voxelwise dose calculation
<p>Note: The version 1.1 dataset has been corrected to include only accurate kernels. Errors were found in Version 1.0 kernels with the following sizes: 1.953, 2.21, 2.4, 3.9, 4, 4.42, 4.8, and 6.8 mm</p> <p>Cartesian matrix dose point kernels, generated by resampling of prior radial dose point kernels. See accompanying paper for additional details: "<strong>Accurate resampling of radial dose point kernels to a Cartesian matrix for voxelwise dose calculation"</strong></p> <p>Refer to the upload titled "<em>Kernel_Format_README.xlsx</em>" for details regarding kernel format and modification for use.</p> <p>Source (radial) kernel generation is described in the Medical Physics article titled "Dose point kernels for 2,174 radionuclides." - https://doi.org/10.1002/mp.13789</p> <p>Source (radial) kernels can be downloaded here: https://doi.org/10.5281/zenodo.2564036</p>
Aligned DNA sequence matrix for phylogenetic analyses in the article "A new species of spiny-backed tree frog, genus Osteocephalus (Anura: Hylidae), from the Yanachaga Chemillén National Park in central Peru"
<p>Aligned DNA sequence matrix for phylogenetic analyses of the article "Systematics of Huicundomantis, a new subgenus of Pristimantis (Anura, Strabomantidae) with extraordinary cryptic diversity and eleven new species"</p> <p>The matrix is in NEXUS format and has 14791 bp and 38 terminals.</p> <p>Partitions are as follows:</p> <p>charset 12S_16S = 1-2442;<br> charset mtGenome_other_genes = 2443-9180; charset nonCoding = 3132- 3138 4776- 4857 5203- 5214;<br> charset codonPos1 = 2443-3130\3 3139-4774\3 4858-5200\3 5215-9178\3;<br> charset codonPos2 = 2444-3131\3 3140-4775\3 4859-5201\3 5216-9179\3;<br> charset codonPos3 = 2445-3129\3 3141-4773\3 4860-5202\3 5217-9180\3;<br> charset 16S_ND1nonCoding = 9181- 9428 10390- 10506 ;<br> charset 16S_ND1codonPos1 = 9429-10389\3;<br> charset 16S_ND1codonPos2 = 9430-10387\3;<br> charset 16S_ND1codonPos3 = 9431-10388\3;<br> charset POMCcodonPos1 = 10507-11068\3;<br> charset POMCcodonPos2 = 10508-11066\3;<br> charset POMCcodonPos3 = 10509-11067\3;<br> charset CO1codonPos1 = 11069-12608\3;<br> charset CO1codonPos2 = 11070-12609\3;<br> charset CO1codonPos3 = 11071-12610\3;<br> charset CytbcodonPos1 = 12611-13757\3;<br> charset CytbcodonPos2 = 12612-13758\3;<br> charset CytbcodonPos3 = 12613-13759\3;<br> charset ND2codonPos1 = 13760-14789\3;<br> charset ND2codonPos2 = 13761-14790\3;<br> charset ND2codonPos3 = 13762-14791\3;</p>
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)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.