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299
datasets available to search
ShareScore release 0.9.0
Dataset results
299 results for “water analysis”
FIGURE 19. Hydrochus variabiloides n in Taxonomy of Venezuelan water beetles in the genus Hydrochus Leach, 1817, and an analysis of male genitalia morphology (Coleoptera: Hydrochidae)
FIGURE 19. Hydrochus variabiloides n. sp., habitus and male genitalia of holotype.
FIGURE 28. Hydrochus leei n in Taxonomy of Venezuelan water beetles in the genus Hydrochus Leach, 1817, and an analysis of male genitalia morphology (Coleoptera: Hydrochidae)
FIGURE 28. Hydrochus leei n. sp., habitus and male genitalia of holotype.
FIGURE 24. Hydrochus pictus n in Taxonomy of Venezuelan water beetles in the genus Hydrochus Leach, 1817, and an analysis of male genitalia morphology (Coleoptera: Hydrochidae)
FIGURE 24. Hydrochus pictus n. sp., habitus and male genitalia of holotype.
FIGURE 29 in Taxonomy of Venezuelan water beetles in the genus Hydrochus Leach, 1817, and an analysis of male genitalia morphology (Coleoptera: Hydrochidae)
FIGURE 29. Hydrochus soekhnandanae Makhan, habitus and male genitalia
Dataset for water-sensitive paper analysis
<p>The file "representation.jpg" shows the water-sensitive papers (WSP) placement. In each collection 8 WSP are placed: 2 in a place without canopy (Z1 and Z2); 3 in different positions of the canopy (one at the end closest to the sprayer (A1), one in the middle (A2) and another at the end furthest from the sprayer (A3); and another 3 placed in another vineyard in the same way as above.</p>
Shallow subsurface water-ice distribution in the lunar south pole: Analysis based on Mini-RF and multi-metrics
Open the record for dataset details and reuse information.
Transcription analysis of different water use efficiency genotypes in soybean leaf
GEO Series GSE158762. Glycine max. 6 samples. Type: Expression profiling by high throughput sequencing.
Transcriptome analysis using RNA sequencing conducted for wild type (Col-0) and ahl10-1 mutant under control conditions and after 96 h at moderate low water potential (-0.7 MPa)
GEO Series GSE112368. Arabidopsis thaliana. 12 samples. Type: Expression profiling by high throughput sequencing.
Integrative Analysis of Sorghum Bicolor Green Prop Roots Under Elevated CO2 and Water Deficit Conditions
GEO Series GSE179109. Sorghum bicolor. 8 samples. Type: Expression profiling by high throughput sequencing.
Comparative transcriptome analysis of responses to water deficit in Solanum lycopersicum and S. pimpinellifolium roots
GEO Series GSE39894. Solanum lycopersicum; Solanum pimpinellifolium. 46 samples. Type: Expression profiling by array.
Antimicrobial mechanism analysis of an oil-in-water micro-emulsion by DNA microarray-mediated transcriptional profiling of Escherichia coli
GEO Series GSE50556. Escherichia coli. 4 samples. Type: Expression profiling by array.
Comparative analysis of Calanus finmarchicus collected from surface and deep waters in Gulf of Maine
GEO Series GSE33086. Calanus finmarchicus. 10 samples. Type: Expression profiling by array.
Transcriptome analysis of Oshsfa2e mutant plants under controlled drought stress and well-watered conditions at vegetative stage
GEO Series GSE65025. Oryza sativa Japonica Group. 8 samples. Type: Expression profiling by high throughput sequencing.
Data and generating files for the manuscript "A Multi-Model Analysis of Solute Plume Behavior in a Synthetic Braided-River Deposit", submitted to Water Resources Research, August 2018.
<p>Data and generating files for the manuscript "A Multi-Model Analysis of Solute Plume Behavior in a Synthetic Braided-River Deposit", submitted to Water Resources Research, August 2018.</p> <p>This zipped folder contains the codes and data generated for the manuscript. The main routine for generating the ensembles is fidelity/run_fidelity.py. The folders 'dtgeostats', 'flowtrans', and 'hyvr' contain utilities for generating parameter fields and running flow-and-transport simulations. Note that the codes and data are provided as-is and relative pathways, etc. in the code may not function correctly. The data can be found in the fidelity/runfiles/braid005 directory and includes the outputs for the synthetic virtual reality (fidelity/runfiles/braid005/braid_vr) and the following model ensembles: object-based with no conditioning (fidelity/runfiles/braid005/braid_1a), object-based with soft conditioning (fidelity/runfiles/braid005/braid_1b), MPS (fidelity/runfiles/braid005/braid_2a/), isotropic multi-Gaussian (fidelity/runfiles/braid005/braid_3/isn/), and anisotropic multi-Gaussian (fidelity/runfiles/braid005/braid_3/ann/) .</p>
Ensuring the Sustainability of Traditional Water Systems: A Comprehensive Emic-ethic Analysis of Qanats in Arid Regions
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Texture analysis and machine learning to predict water T2 and fat fraction from non-quantitative MRI of thigh muscles in Facioscapulohumeral muscular dystrophy
<p><strong>Introduction</strong>. This database includes the radiomic features used as covariates to train machine learning algorithms in the paper “ Texture analysis and machine learning to predict water T2 and fat fraction from non-quantitative MRI of thigh muscles in Facioscapulohumeral muscular dystrophy”.</p> <p><strong>Purpose</strong>. Quantitative MRI (qMRI) plays a crucial role for assessing disease progression and treatment response in neuromuscular disorders, but the required MRI sequences are not routinely available in every center. The aim of this study was to predict qMRI values of water T2 (wT2) and fat fraction (FF) from conventional MRI, using texture analysis and machine learning.</p> <p><strong>Method</strong>. Fourteen patients affected by Facioscapulohumeral muscular dystrophy were imaged at both thighs using conventional and quantitative MR sequences. Muscle FF and wT2 were calculated for each muscle of the thighs. Forty-seven texture features were extracted for each muscle on the images obtained with conventional MRI. Multiple machine learning regressors were trained to predict qMRI values from the texture analysis dataset.</p> <p><strong>Results</strong>. Eight machine learning methods (linear, ridge and lasso regression, tree, random forest (RF), generalized additive model (GAM), k-nearest-neighbor (kNN) and support vector machine (SVM) provided mean absolute errors ranging from 0.110 to 0.133 for FF and 0.068 to 0.115 for wT2. The most accurate methods were RF, SVM and kNN to predict FF, and tree, RF and kNN to predict wT2.</p> <p><strong>Conclusion</strong>. This study demonstrates that it is possible to estimate with good accuracy qMRI parameters starting from texture analysis of conventional MRI.</p>
Transcriptomic analysis of three Sorghum bicolor landraces following progressive water stress and re-watering
GEO Series GSE92487. Sorghum bicolor. 27 samples. Type: Expression profiling by array.
Analysis data of stream water drained from sub-catchments with different ranges of permafrost area percentage in the headwater region of the Heihe River
<p>Here we provide the analysis data of stream water drained from sub-catchments with different ranges of permafrost area percentage in the headwater region of the Heihe River.</p>
Characterization of the Ross Ice Shelf Basal Melting Variability Based on a Mixing Ratios Analysis of Simulated Water Masses
<p>These folder contains the files related to the publication submitted to the Geophysical Research Letters with the same title. It contains the files necessary to reproduce the figures of the paper submitted.</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)
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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.