cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3886/e118365
title: Poverty or Prosperity in Northern India? New Evidence on Real Wages, 1590s-1870s

description: These files contain all the data used in the publication "Poverty or Prosperity in Northern India? New Evidence on Real Wages, 1590s-1870s". <br><br>This paper introduces a new dataset on wages in northern India (from Gujarat in the West to Bengal in the East) from the 1590s to the 1870s. It follows Allen’s subsistence basket methodology to compute internationally comparable real wages to shed light on developments in Indian living standards over time, as well as to test some of the assumptions underlying the comparative real wage methodology. It adjusts the comparative cost of living indices to take into account differences in caloric intake due to variances in heights. Furthermore, the paper discusses the male/female wage gap in northern India. We demonstrate that the Great Divergence started somewhere in the late seventeenth century. This gap widens further after the 1720s and especially after the 1800s. It is subsequently primarily England’s spurt and India’s stagnation in the first half of the nineteenth century which brought about most serious differences in the standard of living in Eurasia. If the British colonial state is to blame – as often happens in the literature on India’s persistent poverty – it is in their failure to improve the already deteriorated situation after they had become the near-undisputed masters of India since 1820.<br><br>Note on v2<br>There are two main changes compared with Version 1:<br>1. In the sheet “PricesNEI” from the Excel file “prices_north_india.xlsx”, a faulty comma in the formula of column P, caused the average price of ghi to be calculated over 4 rather than 3 columns. This was corrected and the newly calculated series of ghi were also included in the “BasketNEI” sheet of that same file and the improved CPI was used in the calculations of the real wages. As a consequence of this change, the prices of the overall basket are increased somewhat, causing a slight downward adjustment of real wages. <br> 2. In the sheet “PriceNOI”, for the years 1861-1930, the average price of millet (Column J) was accidentally calculated over columns F-I, rather than just column I. This has been corrected in this file and the newly computed CPI entered in the comparisons and real wages calculations. It has no observable consequences for the results. <br><br>We thank Joseph Enguehard (l’École normale supérieure de Lyon) for pointing us towards these issues. <br><br>Note on v3<br>There are two changes compared with v2:<br>1. In the file “7.global_comparisons”, sheet “cpi”, in the calculation of the 10-year averages for Beijing, London, Leipzig and Valencia, the range of years in the formula did not match with the decade in column A. This has been corrected. <br> 2. In that same file, sheets “skilled” and “unskilled”, in the calculation of the 10-year averages, the formula for the 1680s accidently ranged from 1678-1689 instead of 1680-1689. This has been corrected. <br><br> We thank Tamer Güven (Utrecht University) for pointing us towards these issues. <br>
DOI: 10.3886/e118365v1
title: Poverty or Prosperity in Northern India? New Evidence on Real Wages, 1590s-1870s

description: These files contain all the data used in the publication "Poverty or Prosperity in Northern India? New Evidence on Real Wages, 1590s-1870s". <br><br>This paper introduces a new dataset on wages in northern India (from Gujarat in the West to Bengal in the East) from the 1590s to the 1870s. It follows Allen’s subsistence basket methodology to compute internationally comparable real wages to shed light on developments in Indian living standards over time, as well as to test some of the assumptions underlying the comparative real wage methodology. It adjusts the comparative cost of living indices to take into account differences in caloric intake due to variances in heights. Furthermore, the paper discusses the male/female wage gap in northern India. We demonstrate that the Great Divergence started somewhere in the late seventeenth century. This gap widens further after the 1720s and especially after the 1800s. It is subsequently primarily England’s spurt and India’s stagnation in the first half of the nineteenth century which brought about most serious differences in the standard of living in Eurasia. If the British colonial state is to blame – as often happens in the literature on India’s persistent poverty – it is in their failure to improve the already deteriorated situation after they had become the near-undisputed masters of India since 1820.<br>
DOI: 10.3886/e118365v2
title: Poverty or Prosperity in Northern India? New Evidence on Real Wages, 1590s-1870s

description: These files contain all the data used in the publication "Poverty or Prosperity in Northern India? New Evidence on Real Wages, 1590s-1870s". <br><br>This paper introduces a new dataset on wages in northern India (from Gujarat in the West to Bengal in the East) from the 1590s to the 1870s. It follows Allen’s subsistence basket methodology to compute internationally comparable real wages to shed light on developments in Indian living standards over time, as well as to test some of the assumptions underlying the comparative real wage methodology. It adjusts the comparative cost of living indices to take into account differences in caloric intake due to variances in heights. Furthermore, the paper discusses the male/female wage gap in northern India. We demonstrate that the Great Divergence started somewhere in the late seventeenth century. This gap widens further after the 1720s and especially after the 1800s. It is subsequently primarily England’s spurt and India’s stagnation in the first half of the nineteenth century which brought about most serious differences in the standard of living in Eurasia. If the British colonial state is to blame – as often happens in the literature on India’s persistent poverty – it is in their failure to improve the already deteriorated situation after they had become the near-undisputed masters of India since 1820.<br><br>Note on v2<br>There are two main changes compared with Version 1:<br>1. In the sheet “PricesNEI” from the Excel file “prices_north_india.xlsx”, a faulty comma in the formula of column P, caused the average price of ghi to be calculated over 4 rather than 3 columns. This was corrected and the newly calculated series of ghi were also included in the “BasketNEI” sheet of that same file and the improved CPI was used in the calculations of the real wages. As a consequence of this change, the prices of the overall basket are increased somewhat, causing a slight downward adjustment of real wages. <br> 2. In the sheet “PriceNOI”, for the years 1861-1930, the average price of millet (Column J) was accidentally calculated over columns F-I, rather than just column I. This has been corrected in this file and the newly computed CPI entered in the comparisons and real wages calculations. It has no observable consequences for the results. <br><br>We thank Joseph Enguehard (l’École normale supérieure de Lyon) for pointing us towards these issues. <br>
DOI: 10.3886/e118365v3
title: Poverty or Prosperity in Northern India? New Evidence on Real Wages, 1590s-1870s

description: These files contain all the data used in the publication "Poverty or Prosperity in Northern India? New Evidence on Real Wages, 1590s-1870s". <br><br>This paper introduces a new dataset on wages in northern India (from Gujarat in the West to Bengal in the East) from the 1590s to the 1870s. It follows Allen’s subsistence basket methodology to compute internationally comparable real wages to shed light on developments in Indian living standards over time, as well as to test some of the assumptions underlying the comparative real wage methodology. It adjusts the comparative cost of living indices to take into account differences in caloric intake due to variances in heights. Furthermore, the paper discusses the male/female wage gap in northern India. We demonstrate that the Great Divergence started somewhere in the late seventeenth century. This gap widens further after the 1720s and especially after the 1800s. It is subsequently primarily England’s spurt and India’s stagnation in the first half of the nineteenth century which brought about most serious differences in the standard of living in Eurasia. If the British colonial state is to blame – as often happens in the literature on India’s persistent poverty – it is in their failure to improve the already deteriorated situation after they had become the near-undisputed masters of India since 1820.<br><br>Note on v2<br>There are two main changes compared with Version 1:<br>1. In the sheet “PricesNEI” from the Excel file “prices_north_india.xlsx”, a faulty comma in the formula of column P, caused the average price of ghi to be calculated over 4 rather than 3 columns. This was corrected and the newly calculated series of ghi were also included in the “BasketNEI” sheet of that same file and the improved CPI was used in the calculations of the real wages. As a consequence of this change, the prices of the overall basket are increased somewhat, causing a slight downward adjustment of real wages. <br> 2. In the sheet “PriceNOI”, for the years 1861-1930, the average price of millet (Column J) was accidentally calculated over columns F-I, rather than just column I. This has been corrected in this file and the newly computed CPI entered in the comparisons and real wages calculations. It has no observable consequences for the results. <br><br>We thank Joseph Enguehard (l’École normale supérieure de Lyon) for pointing us towards these issues. <br><br>Note on v3<br>There are two changes compared with v2:<br>1. In the file “7.global_comparisons”, sheet “cpi”, in the calculation of the 10-year averages for Beijing, London, Leipzig and Valencia, the range of years in the formula did not match with the decade in column A. This has been corrected. <br> 2. In that same file, sheets “skilled” and “unskilled”, in the calculation of the 10-year averages, the formula for the 1680s accidently ranged from 1678-1689 instead of 1680-1689. This has been corrected. <br><br> We thank Tamer Güven (Utrecht University) for pointing us towards these issues. <br>
DOI: 10.6084/m9.figshare.21220499
title: Chinese langugae textooks for Mongolian learners published in China 1949-2016

description: This dataset documents the images of the Chinese language textbooks for Mongolian learners published in China during the Republican period (1949 - 2016). The textbooks are issued by the People's Republic of China government.
DOI: 10.5281/zenodo.7084832
title: Effect of freshwater discharge from estuary dam on residual circulation in bifurcated channel

description: Zip-files contain matlab m-files and raw data of transects data in Yeoungsan Rver estuary. The code was designed to analysis the changes from the raw data. During freshwater discharge.zip file contains data set with a freshwater impact from a estuary dam, Whereas during non-freshwater discharge.zip file contains data set without a freshwater impacts period.
DOI: 10.5281/zenodo.5873711
title: Supplementary data for "Nanoscale damage production by dynamic tensile rupture in alpha-quartz"

description: In this dataset you can find sample data from simulations of crack propagation and python scripts that can be used to confirm the plots in the paper. "mainSimualtions" and "parameterVariations" contains the simulations where the crack propagates through alpha-quartz. "mainSimulations" contain the data used for the plots in the manuscript. Each folder inside "mainSimulations" is one simulation. "parameterVariations" contain data for checking sensitivity to the simulation setup. The folder contains the subfolders: compressiveStress, loadingPlane0110, loadingRate and temperature. Each folder inside the subfolders is one simulation. For each folder containing one simulations, we provide: NAME.run: The input script NAME.data: The input data job.sh: Script to run the simulation log.lammps: Thermodynamic output from the simulation fracture_displacement.npy: Output providing the crack tip position with time Note that the pressures given in the folder names and in the simulations are in bars, not MPa. "verify_quartz_parameters" contains scripts and simulations performed to verify that the simulated material has properties similar those of alpha-quartz. "mainSimualtions", "parameterVariations" and "verify_quartz_parameters" are in zip containers. In order to use them, please unzip them and leave the resulting folders in the same directory as this README file. The python scripts "NAME.py" shows how to extract the relevant data from the lammps log files, which enables reproduction of the figures in the paper. See instructions below to use the scripts. <br> Installation instructions to make the python plot scripts working, assuming you already have numpy and matplotlib: &gt; pip3 install git+https://github.com/henriasv/lammps-logfile.git<br> If this does not work, please contact Marthe Grønlie Guren, m.g.guren@geo.uio.no
DOI: 10.5445/ir/1000150871
title: Surfaced and suspended plastic: Film_HDPE_100_V5 (videos)
DOI: 10.34740/kaggle/dsv/4259225
title: AutoXGB
DOI: 10.5281/zenodo.7115401
title: Spectroscopic ellipsometry mapping of PAAO:Au (AJ-4-04-20-Au sample)

description: Spectroscopic ellipsometry measurement data obtained from the porous anodized aluminum oxide covered with gold nanoparticles (PAAO:Au). The sample was made by anodization of aluminum monocrystal in 0.3 mol/L oxalic acid at 40 V for 4 minutes and 30 seconds. Then it was dip-coated in 60 nm diameter gold nanoparticles suspension. Extraction speed was 500 nm/s. The measurements were carried out at 20 × 20 locations covering all of the sample surface (approximately 4.8 × 4.8 mm<sup>2</sup>). The coordinates of each of 400 locations are available in "mapping_points.csv" file. All measurement data is also included in a single "AJ-4-04-20-Au Ellipsometry Mapping Measurements.rar" file. Ellipsometer: rotating compensator GES5-E (Semilab). Light source: 75 W xenon short arc lamp with 185-2000 nm wavelength spectrum. Detector: UV-Vis CCD with 0.8 nm resolution. Spectral range: approximately 230-960 nm. Light incidence angles: 50°, 55°, 60°, 65°, 70°, 75°. Light beam size: microspot (365 × 470 μm<sup>2</sup> at 75° angle of incidence). The same sample was also measured using the same spectroscopic ellipsometry method before being covered with gold nanoparticles. The data can be found here: https://doi.org/10.5281/zenodo.5734486
description: The research was carried out under postdoctoral project "Patterned hybrid multilayer films for optical sensors", No. 1.1.1.2/VIAA/4/20/615.
DOI: 10.5281/zenodo.7115400
title: Spectroscopic ellipsometry mapping of PAAO:Au (AJ-4-04-20-Au sample)

description: Spectroscopic ellipsometry measurement data obtained from the porous anodized aluminum oxide covered with gold nanoparticles (PAAO:Au). The sample was made by anodization of aluminum monocrystal in 0.3 mol/L oxalic acid at 40 V for 4 minutes and 30 seconds. Then it was dip-coated in 60 nm diameter gold nanoparticles suspension. Extraction speed was 500 nm/s. The measurements were carried out at 20 × 20 locations covering all of the sample surface (approximately 4.8 × 4.8 mm<sup>2</sup>). The coordinates of each of 400 locations are available in "mapping_points.csv" file. All measurement data is also included in a single "AJ-4-04-20-Au Ellipsometry Mapping Measurements.rar" file. Ellipsometer: rotating compensator GES5-E (Semilab). Light source: 75 W xenon short arc lamp with 185-2000 nm wavelength spectrum. Detector: UV-Vis CCD with 0.8 nm resolution. Spectral range: approximately 230-960 nm. Light incidence angles: 50°, 55°, 60°, 65°, 70°, 75°. Light beam size: microspot (365 × 470 μm<sup>2</sup> at 75° angle of incidence). The same sample was also measured using the same spectroscopic ellipsometry method before being covered with gold nanoparticles. The data can be found here: https://doi.org/10.5281/zenodo.5734486
description: The research was carried out under postdoctoral project "Patterned hybrid multilayer films for optical sensors", No. 1.1.1.2/VIAA/4/20/615.
DOI: 10.17028/rd.lboro.21186076
title: Suspended sediment and spectral reflectance, Bayelva and Blomstrandbreen, Svalbard (2012, 2019 and 2021).

description: Suspended sediment and spectral reflectance data collected at two sites in Kongsfjorden, Svalbard over three separate melt seasons (2012 (Bayelva only), 2019 and 2021 (Bayelva and Blomstrandbreen). Suspended sediment data have been determined in g/l and the location of each sample is given, data are split into five separate Excel files with the Bayelva and Blomstrandbreen data in different files for 2019 and 2021 seasons. Individual spectral reflectance profiles are given for each sample location and include an average spectral reflectance profile, data are split into five separate Excel files with the Bayelva and Blomstrandbreen data in different files for 2019 and 2021 seasons. More information can be found in the first sheet of each spectral reflectance workbook explaining how the data can be used in conjunction with the suspended sediment data. These data support the publication Tallentire <em>et al</em>., (in review), with Journal of Geophysical Research: Earth Surface.
DOI: 10.17028/rd.lboro.21186076.v1
title: Suspended sediment and spectral reflectance, Bayelva and Blomstrandbreen, Svalbard (2012, 2019 and 2021).

description: Suspended sediment and spectral reflectance data collected at two sites in Kongsfjorden, Svalbard over three separate melt seasons (2012 (Bayelva only), 2019 and 2021 (Bayelva and Blomstrandbreen). Suspended sediment data have been determined in g/l and the location of each sample is given, data are split into five separate Excel files with the Bayelva and Blomstrandbreen data in different files for 2019 and 2021 seasons. Individual spectral reflectance profiles are given for each sample location and include an average spectral reflectance profile, data are split into five separate Excel files with the Bayelva and Blomstrandbreen data in different files for 2019 and 2021 seasons. More information can be found in the first sheet of each spectral reflectance workbook explaining how the data can be used in conjunction with the suspended sediment data. These data support the publication Tallentire <em>et al</em>., (in review), with Journal of Geophysical Research: Earth Surface.
DOI: 10.5281/zenodo.5796233
title: Output of dry idealized GCM simulations under perpetual solstice-like forcing

description: This repository contains the output from simulations in the Caltech idealized dry GCM that were originally reported in Hill, Bordoni, and Mitchell 2021, J. Atmos Sci. The simulations use a Newtonian cooling approximation of radiative transfer, and the Newtonian relaxation temperature field is an approximation of Earth's northern solstice. Simulations are run at three different planetary rotation rates, 1/4, 1, and 2x Earth's rotation rate. A fourth simulation is run at Earth's rotation rate but with the `delta_h` parameter that controls the magnitude of the meridional temperature gradients set to 1/6 rather than 1/15 as for the other simulations. Idealized GCM formulation: Schneider, Tapio. “The Tropopause and the Thermal Stratification in the Extratropics of a Dry Atmosphere.” Journal of the Atmospheric Sciences 61, no. 12 (June 1, 2004): 1317–40. https://doi.org/10.1175/1520-0469(2004)061&lt;1317:TTATTS&gt;2.0.CO;2. Simulations: Hill, Spencer A., Simona Bordoni, and Jonathan L. Mitchell. “Solsticial Hadley Cell Ascending Edge Theory from Supercriticality.” Journal of the Atmospheric Sciences 78, no. 6 (June 1, 2021): 1999–2011. https://doi.org/10.1175/JAS-D-20-0341.1.
description: {"references": ["Simulations: Hill, Spencer A., Simona Bordoni, and Jonathan L. Mitchell. \"Solsticial Hadley Cell Ascending Edge Theory from Supercriticality.\" Journal of the Atmospheric Sciences 78, no. 6 (June 1, 2021): 1999\u20132011. https://doi.org/10.1175/JAS-D-20-0341.1"]}
DOI: 10.6084/m9.figshare.18007046
title: Data and codes: Experimental evidence for core-Merge in the vocal communication system of a wild passerine

description: Data and R code
DOI: 10.6084/m9.figshare.4248962.v1
title: Macroalgae macromolecular database

description: A compilation of data from published literature of the macromolecular content (protein, lipid, carbohydrate) of macroalgae.<br>Accompanies paper by Fiset et al (2017) in Limnology & Oceanography: Methods. doi: 10.1002/lom3.10186.<br>
DOI: 10.17632/w2b89yr6x5.2
title: Carbon monoxide (CO) on Mars from ACS occultations (MY34-35)

description: Dataset for the publication "Climatology of the CO vertical distribution on Mars based on ACS TGO measurements"
by Fedorova et al.

Includes a list of orbits, and CO mixing ratio in ppmv from ACS/TGO solar occultation observations for Martian years  34 and 35 for three spectrometers ACS NIR, ACS MIR and ACS TIRVIM.

Data contain folders with the list of orbits and the CO volume mixing ratio with errors for each orbit of TGO where ACS instruments had measurements.
 
CO data files are named "orbXXXXXX_NY_CO_NIR(MIR or TIR).txt",
where XXXXXX is the decimal orbit number,
Y is the occultation number in orbit.
DOI: 10.21227/mps8-kb56
title: Tuberculosis (TB) Chest X-ray Database

description: A team of researchers from Qatar University, Doha, Qatar, and the University of Dhaka, Bangladesh along with their collaborators from Malaysia in collaboration with medical doctors from Hamad Medical Corporation and Bangladesh have created a database of chest X-ray images for Tuberculosis (TB) positive cases along with Normal images. In our current release, there are 3500 TB images, and 3500 normal images.Note: The research team managed to classify TB and Normal Chest X-ray images with an accuracy of 98.3%. This scholarly work is published in IEEE Access Link. Please make sure you give credit to us while using the dataset, code, and trained models.Credit should go to the following:Tawsifur Rahman, Amith Khandakar, Muhammad A. Kadir, Khandaker R. Islam, Khandaker F. Islam, Zaid B. Mahbub, Mohamed Arselene Ayari, Muhammad E. H. Chowdhury. "Reliable Tuberculosis Detection using Chest X-ray with Deep Learning, Segmentation and Visualization". [Accepted: IEEE Access] [https://arxiv.org/ftp/arxiv/papers/2007/2007.14895.pdf]