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12,346 results for “derivatives”
CLDF dataset derived from Kleinewillinghöfer's "Bikwin-Jen Comparative Wordlist" from 2015
<p>Cite the source of the dataset as:</p> <blockquote> <p>Kleinewillinghöfer, Ulrich (2015). Bikwin-Jen Group. https://www.blogs.uni-mainz.de/fb07-adamawa/adamawa-languages/bikwin-jen-group/. Accessed on: 2020-04-15.</p> </blockquote>
CLDF dataset derived from Duong et al.'s "Language of the La Chí People" from 2020
<p>Cite the source of the dataset as:</p> <blockquote> <p>Duong, Thu Hang and Nguyen, Thu Quynh and Nguyen, Van Loi (2021): The Language of the La Chí People in Bản Díu Commune, Xín Mần District, Hà Giang Province, Vietnam. In: Studies in the Anthropology of Language in Mainland Southeast Asia. Ed. by N. J. Enfield, Jack Sidnell, and Charles H. P. Zuckermann. University of Hawaii Press: Honolulu. 124-138</p> </blockquote>
CLDF dataset derived from Othaniel's "Jen Cluster Comparative Wordlist" from 2017
<p>Cite the source of the dataset as:</p> <blockquote> <p>Othaniel, Nlabephee Kefas. 2017. A phonological comparative study of the Jen language cluster. (MA thesis, Jos: Theological College of Northern Nigeria; 1–83pp.)</p> </blockquote>
CLDF dataset derived from Kraft's "Chadic Wordlists" from 1981
<p>Cite the source of the dataset as:</p> <blockquote> <p>Kraft, Charles H. 1981. Chadic wordlists. Berlin: Dietrich Reimer.</p> </blockquote>
CLDF dataset derived from Bowern et al.'s "Hunter - Gatherer Language Database" from 2021
<p>Cite the source of the dataset as:</p> <blockquote> <p>Bowern, Claire, Patience Epps, Jane Hill, and Patrick McConvell. Hunter - Gatherer Language Database. https://huntergatherer.la.utexas.edu/ Accessed 2021-04-27.</p> </blockquote>
CLDF dataset derived from Gerardi and Reichert's "The Tupí-Guaraní Language Family: A Phylogenetic Classification" from 2021
<p>Cite the source of the dataset as:</p> <blockquote> <p>Ferraz Gerardi, Fabrício and Reichert, Stanislav (2021) The Tupí-Guaraní Language Family: A Phylogenetic Classification. Diachronica 38(2). 151--188. DOI: https://doi.org/10.1075/dia.18032.fer.</p> </blockquote>
R scripts for analyzing LiDAR data to assess forest canopy structure and perform Principal Component Analysis (PCA) on derived metrics
<p>This repository contains R scripts for analyzing LiDAR data to assess forest canopy structure and perform Principal Component Analysis (PCA) on spectral and LiDAR-derived metrics. The scripts cover LiDAR data processing, canopy height model (CHM) generation, calculation of forest canopy metrics, and PCA analysis.</p>
CLDF dataset derived from Haspelmath and Tadmor's "World Loanword Database" from 2009
<p>Cite the source of the dataset as:</p> <blockquote> <p>Haspelmath, Martin & Tadmor, Uri (eds.) 2009. World Loanword Database. Leipzig: Max Planck Institute for Evolutionary Anthropology. (Available online at http://wold.clld.org)</p> </blockquote>
Data associated with "Microbiota-derived metabolites inhibit Salmonella virulent subpopulation development by acting on single-cell behaviors"
<p>Data used for the publication Microbiota-derived metabolites inihibit Salmonella virulent subpopulation development by acting on single-cell behaviors. </p> <p> </p> <p>all_hi_2307202.csv Single-cell quantifications of Salmonella SPI-1 reporter cells grown in the presence of SCFAs.</p> <p>all_no_2307202.csv Single-cell quantifications of Salmonella SPI-1 reporter cells grown in the absence of SCFAs.</p> <p>odmeasurements.csv OD measurements of plate-reader assays of Salmonella SPI-1 reporter cells and controls grown in a range of SCFA conditions. </p> <p>gfpmeasurements.csv GFP measurements of plate-reader assays of Salmonella SPI-1 reporter cells and controls grown in a range of SCFA conditions. </p>
CLDF dataset derived from Dhakal et al.'s "South-Western Tibetic" from 2024
<p>Cite the source of the dataset as:</p> <blockquote> <p>Dhakal, D. N., List, J.-M., Roberts, S. G.(2024) A Phylogenetic Study of South-Western Tibetic. Journal of Language Evolution. https://doi.org/10.1093/jole/lzae008</p> </blockquote>
CLDF dataset derived from the Johansson et al.'s "The typology of sound symbolism" from 2020
<p>Cite the source of the dataset as:</p> <blockquote> <p>Erben Johansson, N., Anikin, A., Carling, G., & Holmer, A. (2020). The typology of sound symbolism: Defining macro-concepts via their semantic and phonetic features, Linguistic Typology , 24(2), 253-310. doi: https://doi.org/10.1515/lingty-2020-2034</p> </blockquote>
CLDF dataset derived from Lai and List's "Comparison of Rgyalrongic Languages" from 2023
<p>Cite the source of the dataset as:</p> <blockquote> <p>Lai, Yunfan and List, Johann-Mattis (2023): Lexical Data for the Historical Comparison of Rgyalrongic Languages [Dataset, Version 1.0]. Leipzig: Max Planck Institute for Evolutionary Anthropology.</p> </blockquote>
Widefield and Confocal brain images derived from experimental Middle Cerebral Artery occlusion (MCAo) in mice.
<p>This deposit contains a series of widefield and confocal brain images derived from research on cerebral ischemia carried out by the Laboratory of Neurovascular Interactions (https://elalilab.com/) at the Université Laval, Québec (Canada) directed by Dr. Ayman ElAli (<a href="mailto:ayman.el-ali@crchudequebec.ulaval.ca">ayman.el-ali@crchudequebec.ulaval.ca</a>). The experiments, data processing, and organization were performed by Daniel Manrique-Castano, former postdoctoral fellow and current research data curation officer at the Digital Research Alliance of Canada (<a href="https://daniel-manrique.github.io/">https://daniel-manrique.github.io/manrique; </a>dmanriquecastano@gmail.com).</p> <p>Given the complexity of the whole image bundle, images from the same experiment were compressed into zip files. Complementary data is available at the <strong>Open Science Framework (OSF) repository</strong> (<span><a href="https://osf.io/74mqn/" target="_blank" rel="noopener">10.17605/OSF.IO/74MQN</a>), and reproducible workflows for image processing and analysis are available on <strong>GitHub</strong> (<a href="https://doi.org/10.5281/zenodo.13948420" target="_blank" rel="noopener">10.5281/zenodo.13948420</a>)</span></p> <p> </p> <p><strong>Naming conventions for datasets</strong> (taking as an example Widefield_5x_Ipsilateral_KO_CD31-ColIV-Iba1.zip)</p> <p>Widefield: Imaging type performed (available strings = Confocal, Widefield). </p> <p>5x: Objective magnification (Available strings = 5x, 10x, 20x, 40x). </p> <p>Ipsilateral: Iaged region (Available strings = ROIs [Regions of interest], Whole [whole brain], Ipsilateral [ischemic hemisphere]). </p> <p>KO: imaging performed in PDGFRB_KLF4-KO mice (if absent, imaging performed in PDGFRB_TdTomato mice) </p> <p>CD31-ColIV-Iba1: Imaged markers (available strings = multiple, depending on the experiment). </p> <p> </p> <p><strong>Important: </strong>Each .zip file contains a README file specific to each dataset, describing the experimental conditions, naming conventions of individual images and links to additional files used for image processing.</p> <p> </p> <p> </p>
Dataset for article Photodissociation of aliphatic PAH derivatives under relevant astrophysical conditions
<p>The experimental data are provided in subfolders by species, which contain each three files:<br> (i) the normalized intensities (Eq. 1 in the article) for the mass peaks corresponding to the parent cation and its fragments as a function of the VUV irradiation time,<br> (ii) the experimental error bars associated with these intensities,<br> (iii) the curves corresponding to the fitting functions that were derived with the procedure described in Sect. 2.4.</p> <p>Each folder is named by the parents species:<br> Pyr+ for pyrene (C16H10+),<br> H6-Pyr+ for 1,2,3,6,7,8-hexahydro-pyrene (C16H16+),<br> MePyr+ for 1-methylpyrene (C17H12+),<br> EtPyr+ for 4-ethyl-pyrene (C18H14+),<br> Cor+ for coronene (C24H12+),<br> MeCor+ for methyl-coronene (C25H14+),<br> EtCor+ for ethyl-coronene (C26H16+).</p> <p>In addition, the VUV_source folder contains the measurements corresponding to the VUV source calibration (see Fig. A.1 in the article appendix).</p> <p>The folder for TD-DFT calculations gathers the calculated photoabsorption cross-sections for all species of interest (see Fig. D.1 in the article appendix).</p>
CLDF dataset derived from List and Prokić's "Benchmark Database of Phonetic Alignments" from 2014
<p>Cite the source of the dataset as:</p> <blockquote> <p>List, Johann-Mattis and Jelena Prokić. (2014). A benchmark database of phonetic alignments in historical linguistics and dialectology. In: Proceedings of the International Conference on Language Resources and Evaluation (LREC), 26 — 31 May 2014, Reykjavik. 288-294.</p> </blockquote>
CLDF dataset derived from Carling's "Diachronic Atlas of Comparative Linguistics" from 2017
<p>Cite the source of the dataset as:</p> <blockquote> <p>Carling, Gerd (ed.) 2017. Diachronic Atlas of Comparative Linguistics Online. Lund: Lund University. (DOI/URL: https://diacl.ht.lu.se/). Accessed on: 2019-02-07.</p> </blockquote>
CLDF dataset derived from List et al.'s "Database of Cross-Linguistic Colexifications (Version 1.0)" from 2014
<p>Cite the source of the dataset as:</p> <blockquote> <p>List, Johann-Mattis, Thomas Mayer, Anselm Terhalle, and Matthias Urban (2014). CLICS: Database of Cross-Linguistic Colexifications. Marburg: Forschungszentrum Deutscher Sprachatlas (Version 1.0).</p> </blockquote>
CLDF dataset derived from Satterthwaite-Phillips' "Phylogenetic Inference of the Tibeto-Burman Languages" from 2011
<p>Cite the source of the dataset as:</p> <blockquote> <p>Satterthwaite-Phillips, Damian (2011) Phylogenetic inference of the Tibeto-Burman languages or on the usefuseful of lexicostatistics (and "megalo"-comparison) for the subgrouping of Tibeto-Burman. Stanford: Stanford University.</p> </blockquote>
CLDF dataset derived from Wang's "Basic Words in Chinese Dialects" from 2004
<p>Cite the source of the dataset as:</p> <blockquote> <p>Wang, F. 2004. BCD: basic words of Chinese dialects. Unpublished dataset. [Digital version in: List, J.-M. (2015): Network perspectives on Chinese dialect history. Bulletin of Chinese Linguistics 8. 42-67.]</p> </blockquote>
Continuous process technology for glucoside production from sucrose using a whole cell-derived solid catalyst of sucrose phosphorylase
<p>We provide here the underlying data of the publication "Continuous process technology for glucoside production from sucrose using a whole cell-derived solid catalyst of sucrose phosphorylase". Please find the abstract below.</p> <p>Advanced biotransformation processes typically involve the upstream processing part performed continuously and interlinked tightly with the product isolation. Key in their development is a catalyst that is highly active, operationally robust, conveniently produced and recyclable. A promising strategy to obtain such catalyst is to encapsulate enzymes as permeabilized whole cells in porous polymer materials. Here, we show immobilization of the sucrose phosphorylase from Bifidobacterium adolescentis (P134Q-variant) by encapsulating the corresponding E. coli cells into polyacrylamide. Applying the solid catalyst, we demonstrate continuous production of the commercial extremolyte 2-α-D-glucosyl-glycerol (2-GG) from sucrose and glycerol. The solid catalyst exhibited similar activity (≥70%) as the cell free extract (~800 U g-1 cell wet weight) and showed excellent in-operando stability (40 °C) over 6 weeks in a packed-bed reactor. Systematic study of immobilization parameters related to catalyst activity led to the identification of cell loading and catalyst particle size as important factors of process optimization. Using glycerol in excess (1.8 M), we analyzed sucrose conversion dependent on space velocity (0.075 – 0.750 h-1) and revealed conditions for full conversion of up to 900 mM sucrose. The maximum 2-GG space-time yield reached was 45 g L-1 h-1 for a product concentration of 120 g L-1. Collectively, our study establishes a step-economic route towards a practical whole cell-derived solid catalyst of sucrose phosphorylase, enabling continuous production of glucosides from sucrose. This strengthens the current biomanufacturing of 2-GG, but also has significant replication potential for other sucrose-derived glucosides, promoting their industrial scale production using sucrose phosphorylase. </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.