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opencc-by-4.0Apr 2024View details →

Redefining merit to handle "All snakes and no ladders"

alt-text: Picture of a white man and a black woman playing snakes and ladders with different boards. The black woman has many more snakes than the white man and less ladders. In one instance for the white man, there is a snake that ends on the bottom of a ladder to represent someone doing badly but still getting a promottion – this is called ‘failing up’ eg. Donald Trump. It also shows that the white man is just ahead of the black woman in his career, but who has done the best to get to that position based on the degree of difficult of their board?

opencc-by-nc-sa-4.0Aug 2024View details →

MERIT-SWORD: Bidirectional Translations Between MERIT-Basins and the SWOT River Database (SWORD)

Corresponding peer-reviewed publication This dataset corresponds to all input and output files that were used in the study reported in: <ul> <li>Wade, J., David, C.H., Collins, E.L., Altenau, E.H., Coss, S., Cerbelaud, A., Tom, M., Durand, M., Pavelsky T.M. (In Review), Bidirectional Translations Between Observational and Topography-based Hydrographic Datasets: MERIT-Basins and the SWOT River Database (SWORD).</li> </ul> When making use of any of the files in this dataset, please cite both the aforementioned article and the dataset herein.   Summary The MERIT-SWORD data product reconciles critical differences between the SWOT River Database (SWORD; Altenau et al., 2021), the hydrography dataset used to aggregate observations from the Surface Water and Ocean Topography (SWOT) Mission, and MERIT-Basins (MB; Lin et al., 2019; Yang et al., 2021), an elevation-derived vector hydrography dataset commonly used by global river routing models (Collins et al., 2024). The SWORD and MERIT-Basins river networks differ considerably in their representation of the location and extent of global river reaches, complicating potential synergistic data transfer between SWOT observations and existing hydrologic models. MERIT-SWORD aims to: <ol> <li>Generate bidirectional, one-to-many links (i.e. translations) between river reaches in SWORD and MERIT-Basins (ms_translate files).</li> <li>Provide a reach-specific evaluation of the quality of translations (ms_diagnostic files).</li> </ol>   Data sources The following sources were used to produce files in this dataset: <ul> <li>MERIT-Basins (version 1.0) derived from MERIT-Hydro (version 0.7) available under a CC BY-NC-SA 4.0 license. <a href="https://www.reachhydro.org/home/params/merit-basins">https://www.reachhydro.org/home/params/merit-basins</a></li> <li>SWOT River Database (SWORD) (version 16) available under a CC BY 4.0. https://zenodo.org/records/10013982. DOI: 10.5281/zenodo.10013982</li> <li>Mean Discharge Runoff and Storage (MeanDRS) dataset (version v0.4) available under a CC BY-NC-SA 4.0 license. <a href="../records/10013744">https://zenodo.org/records/10013744</a>. DOI: 10.5281/zenodo.10013744; 10.1038/s41561-024-01421-5</li> </ul>   Software The software that was used to produce files in this dataset are available at <a href="https://github.com/jswade/merit-sword">https://github.com/jswade/merit-sword</a>.   Primary Data Products The following files represent the primary data products of the MERIT-SWORD dataset. Each file class generally has 61 files, corresponding to the 61 global hydrologic regions (region ii). For typical use of this dataset, download the 3 following zip folders listed below. The ms_translate.zip and ms_diagnostic.zip NetCDF files are best suited for scripting applications, while the ms_translate_shp.zip shapefiles are best suited for GIS applications. The MERIT-SWORD translation tables (.nc) establish links between corresponding river reaches in MERIT-Basins and SWORD in both directions. The mb_to_sword translations relate the COMID values of all MERIT-Basins reaches in region ii (as defined by MERIT-Basins) to corresponding SWORD reach_id values, which are ranked by their degree of overlap and stored in columns sword_1 – sword_40. The partial intersecting lengths (m) of SWORD reaches within related MERIT-Basins unit catchments are stored in columns part_len_1 – part_len_40 and can be used to weight data transfers from more than one SWORD reach. The sword_to_mb translations relate the reach_id values of all SWORD reaches in region ii (as defined by SWORD) to corresponding MERIT-Basins COMID values, which are ranked by their degree of overlap and stored in columns mb_1 – mb_40. The partial intersecting lengths (m) of SWORD reaches within related MERIT-Basins unit catchments are again stored in columns part_len_1 – part_len_40. <ul> <li>ms _translate.zip <ul> <li>mb_to_sword: mb_to_sword_pfaf_ii_translate.nc</li> <li>sword_to_mb: sword_to_mb_pfaf_ii_translate.nc</li> </ul> </li> </ul>   The MERIT-SWORD diagnostic tables (.nc) contain evaluations of the quality of translations between MERIT-Basins and SWORD reaches, stored in column flag.  The mb_to_sword diagnostic files contain integer quality flags for each MERIT-Basins reach translation in region ii. The sword_to_mb diagnostic files contain integer quality flags for each SWORD reach translation in region ii. The quality flags are as follows: <ul> <li>0 = Valid translation.</li> <li>1 = Translated reaches are not topologically connected to each other.</li> <li>2 = Reach does not have a corresponding reach in the other dataset (absent translation).</li> <li>21 = Reach does not have a corresponding reach in the other dataset due to flow accumulation mismatches.</li> <li>22 = Reach does not have a corresponding reach in the other dataset because it is located in what the other dataset defines as the ocean.</li> </ul> <ul> <li>ms_diagnostic.zip <ul> <li>mb_to_sword: mb_to_sword_pfaf_ii_diagnostic.nc</li> <li>sword_to_mb: sword_to_mb_pfaf_ii_diagnostic.nc</li> </ul> </li> </ul>   For GIS applications, the translations and diagnostic tables are also available in shapefile format, joined to their respective MERIT-Basins and SWORD river vector shapefiles. The MERIT-Basins and SWORD shapefiles retain their original attribute tables, in additional to the added translation and diagnostic columns. <ul> <li>ms _translate_shp.zip <ul> <li>mb: riv_pfaf_ii_MERIT_Hydro_v07_Basins_v01_translate.shp</li> <li>sword: jj_sword_reaches_hbii_v16_translate.shp</li> </ul> </li> </ul>     Example Applications Data Products The following files are example use cases of transferring data between MERIT-Basins and SWORD. They are not required for typical use of the MERIT-SWORD dataset. The MeanDRS-to-SWORD application example files demonstrate how the MERIT-SWORD translation tables can be used to transfer discharge simulations along MERIT-Basins reaches (i.e. MeanDRS; <a href="../records/8264511">https://zenodo.org/records/8264511</a>) to corresponding SWORD reaches in region ii and continent xx. MeanDRS discharge simulations (m3 s-1) are transferred to SWORD reaches based on a weighted average translation of corresponding reaches and stored in the column meanDRS_Q. <ul> <li>app_meandrs_to_sword.zip: xx_sword_reaches_hbii_v16_meandrs.shp</li> </ul>   The SWORD-to-MERIT-Basins application example files demonstrate how the MERIT-SWORD translation tables can be used to transfer variables of interest (in this case, river width) from SWORD reaches to corresponding MERIT-Basins reaches in region ii. SWORD width estimates (m) are transferred to MERIT-Basins reaches based on a weighted average translation of corresponding reaches and stored in the column sword_wid. <ul> <li>app_sword_to_mb.zip: riv_pfaf_ii_MERIT_Hydro_v07_Basins_v01_sword.shp</li> </ul>   Intermediate Data Products The following files are intermediates used in generating the primary data. They are not required for typical use of the MERIT-SWORD dataset. The MERIT-SWORD river trace files represent our first approximation of MERIT-Basins reaches that correspond to SWORD reaches in region ii, prior to the manual removal of mistakenly included reaches. The river trace files are only used to generate the final river network files and are not used elsewhere in the dataset. <ul> <li>ms_riv_trace.zip: meritsword_pfaf_ii_trace.shp</li> </ul>   The MERIT-SWORD river network shapefiles contain the MERIT-Basins reaches that in aggregate best correspond to the location and extent of the SWORD river network for each of the Pfafstetter level 2 regions as defined by SWORD v16 (i.e. the 61 values of ii). The MERIT-SWORD river networks serve as an intermediary data product to enable reliable translations. <ul> <li>ms_riv_network.zip: meritsword_pfaf_ii_network.shp </li> </ul>   The MERIT-SWORD transpose files are used to confirm that the translation tables in one direction can recreated in their entirety using only data from the translation tables in the other direction, ensuring ~3,500 less data transfer. These files are exact copies of the files contained in ms_translate.zip. <ul> <li>ms _transpose.zip <ul> <li>mb_transposed: mb_to_sword_pfaf_ii_transpose.nc</li> <li>sword_transposed: sword_to_mb_pfaf_ii_transpose.nc</li> </ul> </li> </ul>   The MERIT-SWORD translation catchment files contain the MERIT-Basins unit catchments corresponding to each reach used in generating the mb_to_sword and sword_to_mb translations for each region ii. The files are used internally during the translation process and not required for typical dataset use. <ul> <li>ms_translate_cat.zip <ul> <li>mb_to_sword: mb_to_sword_pfaf_ii_translate_cat.nc</li> <li>sword_to_mb: sword_to_mb_pfaf_ii_translate.cat.nc</li> </ul> </li> </ul>   The hydrologic regions as defined by MERIT-Basins and SWORD are not identical and overlap in many cases, complicating translations. The region overlap files provide bidirectional mappings between region identifiers in both datasets. The files are used in most dataset scripts to determine the regional files from each dataset that need to be loaded. <ul> <li>ms_region_overlap.zip: sword_to_mb_reg_overlap.csv, sword_to_mb_reg_overlap.csv</li> </ul>   The MERIT-SWORD river edit files contain ~3,500 MERIT-Basins river reaches that were mistakenly included during river network generation and do not correspond to any SWORD reaches. These reaches are removed from the river trace files to generate the final MERIT-SWORD river network data product. <ul> <li>ms_riv_edit.zip: meritsword_edits.csv</li> </ul>   Near the antimeridian, MERIT-Basins and SWORD shapefiles differ in their longitude convention. Additionally, the SWORD dataset lacks a shapefile for region 54, which does not have any SWORD reaches. The SWORD edit files contain copies of SWORD files, altered to match the longitude convention of MERIT-Basins and including a dummy shapefile for region 54. <ul> <li>sword_edit.zip: xx_sword_reaches_hbii_v16.shp</li> </ul>   Known bugs in this dataset or the associated manuscript No bugs have been identified at this time.   References Altenau, E. H., Pavelsky, T. M., Durand, M. T., Yang, X., Frasson, R. P. de M., & Bendezu, L. (2021). The Surface Water and Ocean Topography (SWOT) Mission River Database (SWORD): A Global River Network for Satellite Data Products. Water Resources Research, 57(7), e2021WR030054. https://doi.org/10.1029/2021WR030054 Collins, E. L., David, C. H., Riggs, R., Allen, G. H., Pavelsky, T. M., Lin, P., Pan, M., Yamazaki, D., Meentemeyer, R. K., & Sanchez, G. M. (2024). Global patterns in river water storage dependent on residence time. Nature Geoscience, 1–7. https://doi.org/10.1038/s41561-024-01421-5 Lin, P., Pan, M., Beck, H. E., Yang, Y., Yamazaki, D., Frasson, R., David, C. H., Durand, M., Pavelsky, T. M., Allen, G. H., Gleason, C. J., & Wood, E. F. (2019). Global Reconstruction of Naturalized River Flows at 2.94 Million Reaches. Water Resources Research, 55(8), 6499–6516. https://doi.org/10.1029/2019WR025287 Yang, Y., Pan, M., Lin, P., Beck, H. E., Zeng, Z., Yamazaki, D., David, C. H., Lu, H., Yang, K., Hong, Y., & Wood, E. F. (2021). Global Reach-Level 3-Hourly River Flood Reanalysis (1980–2019). Bulletin of the American Meteorological Society, 102(11), E2086–E2105. https://doi.org/10.1175/BAMS-D-20-0057.1

opencc-zeroJun 2024View details →

Dataset: Merit Medical Systems, Inc. (MMSI) 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.

opencc-by-4.0Feb 2023View details →

Figures of merit that characterize silicon gate-all-around nanowire FETs affected by line edge roughness variability

Off-current, threshold voltage, sub-threshold slope and on-current values for two silicon gate-all-around nanowire FETs affected by line edge roughness (LER) variability, a 22 nm gate length device and a 10 nm gate length one. The LER profile that characterizes the roughness deformation is also included in the dataset. Different correlation length (CL) and root mean square (RMS) heights values are characterized.

zenodo36/100

The Cyclostratigraphy Intercomparison Project (CIP): consistency, merits and pitfalls

Supplementary materials for Submission: Sinnesael et al., Earth-Science Reviews "The Cyclostratigraphy Intercomparison Project (CIP): consistency, merits and pitfalls ". Earth Science Review 199, #102965, 2019.  Matthias Sinnesaela, David De Vleeschouwer, Christian Zeedenc, Sietske J. Batenburg, Anne-Christine Da Silva, Niels J. de Winter, Jaume Dinarès-Turell, Anna Joy Drury, Gabriele Gambacorta Frederik J. Hilgen, Linda A. Hinnov, Alexander J.L. Hudson, David B. Kemp, Margriet L. Lantink, Jiří Laurin, Mingsong Li, Diederik Liebrand, Chao Ma, Stephen R. Meyers, Johannes Monkenbusch, Alessandro Montanari, Theresa Nohl,Heiko Pälike, Damien Pas, Micha Ruhl, Nicolas Thibault, Maximilian Vahlenkamp, Luis Valero, Sébastien Wouters, Huaichun Wu, Philippe Claeys

opencc-by-4.0Oct 2019View details →

Multicenter Endoscopic Sleeve Gastrectomy (ESG) Trial (MERIT Trial)

ClinicalTrials.gov study NCT03406975. IPD Sharing: Not stated. Countries: 1. Publications: 2.

VA MERIT: A Comparative Efficacy Study: Treatment of Non-Healing Diabetic

ClinicalTrials.gov study NCT01450943. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.

Metacognitive and Insight Therapy for Persons With Schizophrenia (RCT MERIT)

ClinicalTrials.gov study NCT03427580. IPD Sharing: Not stated. Countries: 1. Publications: 1.

Therapeutic Merit of Solifenacin in the Mitigation of Ureteral Stent-induced Pain and Lower Urinary Tract Symptoms

ClinicalTrials.gov study NCT01381120. IPD Sharing: Not stated. Countries: 1. Publications: 5.

publicMay 2025View details →

dryad36/100

Optimization of the composition Eu5+xAl3+ySb6 and thermoelectric figure of merit

Open the record for dataset details and reuse information.

opencc-by-4.0Oct 2022View details →

Replication package for The merit primacy effect

Cappelen, A. Moene, K., Skjelbred S.-E. and Tungodden, B. (2022) The merit primacy effect, Economic Journal

opencc-by-4.0Aug 2019View details →

Earth Abundant, Non-Toxic, 3D Printed Cu2-xS with High Thermoelectric Figure of Merit

Dataset for: Earth Abundant, Non-Toxic, 3D Printed Cu2-xS with High Thermoelectric Figure of Merit The toxicity, earth abundance and manufacturing costs of thermoelectric materials are three leading reasons why thermoelectric generators are not used in wide scale applications. This is the first ever paper to tackle all three of these problems at once. A pseudo-3D printing technique is combined with Cu2-xS based inks to yield bulk samples capable of being using in traditional architecture thermoelectric generators. These bulk samples are characterized over a wide temperature range in XPS, which reveals a curing temperature of 550 K yields pure Cu2-xS samples. The thermoelectric properties of these samples are tested over a wide temperature range, with a peak ZT of 0.63 ± 0.09 being recorded at 966 K.

FIGURE 4 in Does Solidago litoralis (Asteraceae) merit specific rank? Insights from cytogenetic, molecular and ecological data

FIGURE 4. Idiograms of the four populations showing CMA 3 bands (yellow), 35S (red) and 5S (green) signals. A. S. litoralis; B. S. virgaurea (Livorno); C. S. virgaurea (Monte Pisano); D. S. virgaurea (Tre Potenze). Scale bar: 5 μm.

FIGURE 2 in Does Solidago litoralis (Asteraceae) merit specific rank? Insights from cytogenetic, molecular and ecological data

FIGURE 2. Chromomycin banding showing the GC-rich DNA regions. A. S. litoralis (partial metaphase); B. S. virgaurea (Livorno; partial metaphase); C. S. virgaurea (Monte Pisano); D. S. virgaurea (Tre Potenze). Scale bar: 10 μm.

FIGURE 1. Schiff stained metaphase plates. A. S in Does Solidago litoralis (Asteraceae) merit specific rank? Insights from cytogenetic, molecular and ecological data

FIGURE 1. Schiff stained metaphase plates. A. S. litoralis; B. S. virgaurea (Livorno); C. S. virgaurea (Monte Pisano); D. S. virgaurea (Tre Potenze). Scale bar: 10 μm.

FIGURE 3. FISH showing the chromosomes with 35S in Does Solidago litoralis (Asteraceae) merit specific rank? Insights from cytogenetic, molecular and ecological data

FIGURE 3. FISH showing the chromosomes with 35S (red) and 5S (green) signals. A. Partial metaphase of S. litoralis; B. Partial metaphase of S. virgaurea (Livorno); C. S. virgaurea (Monte Pisano); D. S. virgaurea (Tre Potenze). Scale bar: 10 μm.

FIGURE 5 in Does Solidago litoralis (Asteraceae) merit specific rank? Insights from cytogenetic, molecular and ecological data

FIGURE 5. Grime triangle showing CSR strategies calculated for each single individual. Empty dots: S. litoralis; diamonds: S. virgaurea (Livorno); filled squares: S. virgaurea (Monte Pisano); stars: S. virgaurea (Tre Potenze).

opennotspecifiedOct 2021View details →

FIGURE 3 in Does the Garra population (Teleostei: Cyprinidae: Labeoninae) from the Kol River drainage, Persian Gulf basin merit formal description?

FIGURE 3. Lateral view of three Garra individuals of different sizes; a, ZM-CBSU E811, 92.3 mm SL; b, ZM-CBSU E814, 80.4 mm SL; c, ZM-CBSU E818, 61.4 mm SL; Iran: Kol River tributary, Golabi spring.