cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3235675
title: Binary Neutron Star Mergers: Mass Ejection, Electromagnetic Counterparts, and Nucleosynthesis

description: We release dynamical ejecta data from binary neutron star merger simulations. The outflows are extracted at a fixed coordinate sphere with radius 300 G/c^2 Msun (= 443 km). Only material unbound according to the geodesic criterion is considered to be part of the dynamical ejecta. See [1] for more details. Included data: `Table2.txt`: Table 2 of the paper in machine readable format `tabulated_nucsyn.h5`: nucleosynthesis yields from pre-computed parametrized trajectories. The first three indices of each dataset are Ye, entropy, and expansion timescale tau. For example `Y_final[iYe, ientr, itau, iiso]` gives the final abundance of isotope `iiso` with `A[iiso]` and `Z[iiso]` for a trajectory with initial Ye = `Ye[iYe]`, initial entropy `s[ientr]`, and expansion timescale `tau[itau]`. `tabulated_rho.h5`: gives the density scale corresponding to the Ye, entropy, and expansion timescale in `tabulated_nucsyn.h5`. `[model].tar`: ejecta data for individual simulations. The naming convention is the same as in the paper. For each model we provide: `outflow.txt`: angle integrated outflow rate and cumulated ejecta mass. Data are given in units with Msun = G = c = 1 (eg, the conversion factor for time to seconds is 4.9258e-6). `hist_entropy.dat`: histogram of the ejecta as a function of the entropy (in kb) `hist_vinf.dat`: histogram of the ejecta as a function of the asymptotic velocity (in units of c) `hist_ye.dat`: histogram of the ejecta as a function of the electron fraction Ye. `profile.txt`: time integrated ejecta profiles as a function of the polar angle. `hist_vinf_theta.h5`: histograms of the ejecta as a function of the asymptotic velocity and the polar angle. `hist_ye_theta.h5`: histograms of the ejecta as a function of the asymptotic velocity and the polar angle. `hist_ye_entropy_tau.h5`: histograms of the ejecta as a function of Ye, entropy, and expansion timescale tau. Additionally we distribute: Initial data generated with LORENE and associated EOS tables. EOS tables used for the evolution Parameter file used for each simulation For the multidimensional histograms the indices are ordered as specified in the file name, ie the file `hist_ye_theta.h5` tabulates the ejecta mass as a function of Ye (first index) and polar angle theta (second index). <br> [1] D. Radice, A. Perego, K. Hotokezaka, S. A. Fromm, S. Bernuzzi, and L. F. Roberts, <em>Binary Neutron Star Mergers: Mass Ejection, Electromagnetic Counterparts, and Nucleosynthesis</em>, ApJ 869:130 (2018), arXiv:1809.11161
description: {"references": ["D. Radice, A. Perego, K. Hotokezaka, S. A. Fromm, S. Bernuzzi, and L. F. Roberts,\u00a0Binary Neutron Star Mergers: Mass Ejection, Electromagnetic Counterparts, and Nucleosynthesis,\u00a0ApJ 869:130 (2018),\u00a0arXiv:1809.11161"]}
DOI: 10.14457/cu.the.2013.703
title: MOLECULAR MECHANISMS OF PREVENTIVE AND THERAPEUTIC ACTIVITY OF THAI PLANT EXTRACTS IN SKIN CANCER

description: Thai traditional medicine employs a wide range of indigenous herbs in the forms of tincture or tea for the cure of skin and systemic inﬂammatory diseases. UVB radiation is the most factors to induce skin damage, including skin cancer. The cutaneous squamous cell carcinoma (SCC) is the second most common form of non-melanoma skin cancer. The protection by Thai plants extracts against UVB DNA damage and cytotoxicity was investigated in human keratinocytes cell line HaCaT. High total phenolic and ﬂavonoid contents were found in the ethanol and dichloromethane fractions. Dichloromethane extract of turmeric was shown to possess the highest antioxidant activity. The maximum UV absorptions were found in the ethanol extract of turmeric and in the dichloromethane extract of ginger. These extracts stimulated the synthesis of Thioredoxin 1, an antioxidant protein, and could protect human HaCaT keratinocytes from UV-induced DNA damage and cytotoxicity. In addition, In addition, the effect of the dichloromethane extract of Turmeric, Curcumin and Resveratrol in skin cancer cell was investigated in epidermoid carcinoma cell line A-431. We found that Resveratrol, Turmeric and Curcumin suppressed cell migration and induced cell cycle arrest and apoptosis in cultured A431 skin SCC cells. These effects were associated with modulation of autophagy. Knock-down of the autophagy protein BECLIN 1 partly rescued p53 stability and led to p21-dependent cell cycle arrest. Rapamycin-mediated inhibition of mTOR increased the production of autophagosomes and greatly enhanced Turmeric and Curcumin toxicity. Moreover, A synergistic inhibitory effect on cell migration was observed in the combination Resveratrol plus rapamycin, as mTOR-dependent autophagy inducer or plus LiCl, as mTOR-independent autophagy inducer. The present data support the utilization of Thai herbs extracts in anti-UV cosmetic pharmaceuticals. Moreover, Thai herbs exert important anticancer effects toward skin carcinoma cells by limiting their cell migration and cell proliferation. These effects depend on the modulation of autophagy, a pro-survival pathway.
DOI: 10.5281/zenodo.3235674
title: Binary Neutron Star Mergers: Mass Ejection, Electromagnetic Counterparts, and Nucleosynthesis

description: We release dynamical ejecta data from binary neutron star merger simulations. The outflows are extracted at a fixed coordinate sphere with radius 300 G/c^2 Msun (= 443 km). Only material unbound according to the geodesic criterion is considered to be part of the dynamical ejecta. See [1] for more details. Included data: `Table2.txt`: Table 2 of the paper in machine readable format `tabulated_nucsyn.h5`: nucleosynthesis yields from pre-computed parametrized trajectories. The first three indices of each dataset are Ye, entropy, and expansion timescale tau. For example `Y_final[iYe, ientr, itau, iiso]` gives the final abundance of isotope `iiso` with `A[iiso]` and `Z[iiso]` for a trajectory with initial Ye = `Ye[iYe]`, initial entropy `s[ientr]`, and expansion timescale `tau[itau]`. `tabulated_rho.h5`: gives the density at T = 6 GK corresponding to the Ye, entropy, and expansion timescale used in `tabulated_nucsyn.h5`. `[model].tar`: ejecta data for individual simulations. The naming convention is the same as in the paper. For each model we provide: `outflow.txt`: angle integrated outflow rate and cumulated ejecta mass. Data are given in units with Msun = G = c = 1 (eg, the conversion factor for time to seconds is 4.9258e-6). `hist_entropy.dat`: histogram of the ejecta as a function of the entropy (in kb) `hist_vinf.dat`: histogram of the ejecta as a function of the asymptotic velocity (in units of c) `hist_ye.dat`: histogram of the ejecta as a function of the electron fraction Ye. `profile.txt`: time integrated ejecta profiles as a function of the polar angle. `hist_vinf_theta.h5`: histograms of the ejecta as a function of the asymptotic velocity and the polar angle. `hist_ye_theta.h5`: histograms of the ejecta as a function of the asymptotic velocity and the polar angle. `hist_ye_entropy_tau.h5`: histograms of the ejecta as a function of Ye, entropy, and expansion timescale tau. Additionally we distribute: Initial data generated with LORENE and associated EOS tables. EOS tables used for the evolution Parameter file used for each simulation For the multidimensional histograms the indices are ordered as specified in the file name, ie the file `hist_ye_theta.h5` tabulates the ejecta mass as a function of Ye (first index) and polar angle theta (second index). <br> [1] D. Radice, A. Perego, K. Hotokezaka, S. A. Fromm, S. Bernuzzi, and L. F. Roberts, <em>Binary Neutron Star Mergers: Mass Ejection, Electromagnetic Counterparts, and Nucleosynthesis</em>, ApJ 869:130 (2018), arXiv:1809.11161
description: {"references": ["D. Radice, A. Perego, K. Hotokezaka, S. A. Fromm, S. Bernuzzi, and L. F. Roberts,\u00a0Binary Neutron Star Mergers: Mass Ejection, Electromagnetic Counterparts, and Nucleosynthesis,\u00a0ApJ 869:130 (2018),\u00a0arXiv:1809.11161"]}
DOI: 10.7910/dvn/holxor/1sv5lq
title: 180918_MDN_PR_Fly2_002_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/holxor/26htdi
title: 180918_MDN_PR_Fly1_001_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/holxor/2c3p41
title: 180918_MDN_PR_Fly1_005_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/holxor/40qqyo
title: 180918_MDN_PR_Fly1_002_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/holxor/nh0zhp
title: 180918_MDN_PR_Fly1_003_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/holxor/od0pxb
title: 180918_MDN_PR_Fly1_004_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/holxor/peda4t
title: 180918_MDN_PR_Fly2_001_SG1_behData_images.zip

description: :unav
DOI: 10.25345/c5zw6f
title: MassIVE MSV000083875 - Endophytic Streptomyces sp. CBMAI 2043
title: mzMXL files used to create molecular network analysis.
DOI: 10.7910/dvn/3bal1o/0bc0ap
title: location.tab

description: :unav
DOI: 10.7910/dvn/3bal1o/oy6zs5
title: hs_product.tab

description: :unav
DOI: 10.7910/dvn/holxor/3wvvdd
title: 180918_MDN_PR_Fly2_003_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/holxor/9vuxzb
title: 180918_MDN_PR_Fly3_004_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/holxor/hgsrw8
title: 180918_MDN_PR_Fly3_003_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/holxor/joeppz
title: 180918_MDN_PR_Fly3_002_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/holxor/jrb3dd
title: 180918_MDN_PR_Fly3_005_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/holxor/jzklr7
title: 180918_MDN_PR_Fly2_004_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/holxor/wuyycc
title: 180918_MDN_PR_Fly3_001_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/holxor/xznvcb
title: 180918_MDN_PR_Fly2_005_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/3bal1o/fztqh8
title: sitc_product.tab

description: :unav
DOI: 10.7910/dvn/holxor/fbp9u3
title: 180919_MDN_PR_Fly5_002_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/holxor/fdx2qz
title: 180919_MDN_PR_Fly5_004_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/holxor/kbuyby
title: 180918_MDN_PR_Fly4_003_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/holxor/laa0uk
title: 180919_MDN_PR_Fly5_003_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/holxor/rgearr
title: 180918_MDN_PR_Fly4_005_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/holxor/u50as4
title: 180918_MDN_PR_Fly4_004_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/holxor/vekg7z
title: 180918_MDN_PR_Fly4_001_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/holxor/vyiknm
title: 180919_MDN_PR_Fly5_001_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/holxor/wdoboc
title: 180918_MDN_PR_Fly4_002_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/holxor/cwlsmd
title: 180921_MDN_PR_Fly10_003_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/holxor/flozwd
title: 180919_MDN_PR_Fly6_001_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/holxor/gd6nbh
title: 180920_MDN_PR_Fly9_005_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/holxor/j1mdqw
title: 180919_MDN_PR_Fly6_003_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/holxor/m4h6sh
title: 180919_MDN_PR_Fly5_005_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/holxor/rcvsxb
title: 180919_MDN_PR_Fly6_004_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/holxor/zjweqk
title: 180919_MDN_PR_Fly6_002_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/8suc9u/11k2ay
title: 180918_MDN_CsCh_Fly1_003_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/8suc9u/ezztsw
title: 180918_MDN_CsCh_Fly1_001_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/8suc9u/fl6un5
title: 180918_MDN_CsCh_Fly1_002_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/holxor/jbthay
title: 180919_MDN_PR_Fly6_005_SG1_behData_images.zip

description: :unav
DOI: 10.25345/c5v34t
title: MassIVE MSV000083876 - GNPS - Serum metabolomic changes during T. cruzi infection in mice and non-human primates
title: Methanol extraction of serum samples from mice and non-human primates, chronically infected with Trypanosoma cruzi. Polar C18 chromatography.
DOI: 10.7910/dvn/8suc9u/2nbdln
title: 180918_MDN_CsCh_Fly2_001_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/8suc9u/4xhpsi
title: 180918_MDN_CsCh_Fly2_002_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/8suc9u/b1s4cn
title: 180918_MDN_CsCh_Fly3_001_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/8suc9u/cqfguk
title: 180918_MDN_CsCh_Fly2_004_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/8suc9u/fwkujq
title: 180918_MDN_CsCh_Fly1_004_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/8suc9u/jyvkrg
title: 180918_MDN_CsCh_Fly2_003_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/8suc9u/tbk65a
title: 180918_MDN_CsCh_Fly1_005_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/8suc9u/u5dfte
title: 180918_MDN_CsCh_Fly2_005_SG1_behData_images.zip

description: :unav
DOI: 10.5066/p9vdwvjo
title: Stream Lines Used to Produce the South Carolina StreamStats 2018 Release

description: The U.S. Geological Survey South Atlantic Water Science Center, in cooperation with the South Carolina Department of Transportation, implemented a South Carolina StreamStats application in 2018. This shapefile dataset contains vector lines representing streams, rivers, and ditches that were used in preparing the underlying data for the South Carolina StreamStats application. Data were compiled from multiple sources, but principally represent lidar-derived linework from the South Carolina Department of Natural Resources and the South Carolina Lidar Consortium.The South Carolina hydrography lines were created from elevation rasters that ranged from 4 to 10 ft resolution, to produce a product of approximately 1:6,000-scale. Other sources include the 1:24,000 scale high resolution National Hydrography Dataset streamlines [for streamlines in Georgetown County (SC), NC, and GA] and the 1:4,800 scale local-resolution North Carolina Stream Mapping Project lines (mountain counties). These vector lines were used to enforce drainages on digital elevation model raster grids using the HydroDem/Agree program during data preparation.
DOI: 10.7910/dvn/8suc9u/0t1cgh
title: 180918_MDN_CsCh_Fly3_004_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/8suc9u/6vu8nm
title: 180918_MDN_CsCh_Fly3_003_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/8suc9u/bixcyz
title: 180918_MDN_CsCh_Fly3_005_SG1_behData_images.zip

description: :unav
DOI: 10.7910/dvn/8suc9u/hhiqkg
title: 180918_MDN_CsCh_Fly3_002_SG1_behData_images.zip

description: :unav
DOI: 10.17632/b4yvn8prjn.1
title: Data for: Retention of alluvial sediment in the tidal delta of a river draining a small, mountainous coastal watershed

description: This file contains supplemental data for a manuscript entitled, "Retention of alluvial sediment in the tidal delta of a river draining a small, mountainous coastal watershed," published in Continental Shelf Research. Data files include particle size distribution, sediment core chronologies, sediment elemental abundance, and sediment bulk density and organic content for eight analyzed sediment cores. Data is in excel format; description is found in at the readme tab in each file.
DOI: 10.5281/zenodo.3234688
title: Relate-estimated coalescence rates, allele ages, and selection p-values for the 1000 Genomes Project

description: <strong>Overview</strong> Coalescence rates, allele ages, and p-values for evidence of positive selection calculated for 2478 samples of the 1000 Genomes Project using Relate. We estimated the joint genealogy of all 1000 GP populations and then extracted the embedded genealogy for each population.<br> For the genealogy of each population, we jointly estimated the population size history and branch lengths. <br> Variants segregating in more than one population therefore have correlated but different allele ages in each population. Please refer to Speidel et al. Nature Genetics (2019) for more details or email leo.speidel@outlook.com for any queries. <strong>Coalescence rates</strong> The zipped directory coalescence_rates.zip contains coalescence rates for 26 populations in the 1000 Genomes Project data set. The .coal files show the haploid coalescence rates, please refer to the Relate documentation for the file format. The popsize.RData file is an R data frame storing the diploid population sizes (0.5/coalescence rate) calculated using the .coal files. The columns of this data frame, named "pop_size", are gens_ago: Time in generations at which epoch starts. (To get years from generations, we multiply by 28.) population_size: Diploid population size in this epoch. population: Name of population region: Name of region (AFR, AMR, EAS, EUR, SAS) <strong>Allele ages and selection p-values</strong> The zipped directories allele_ages_*.zip contain R data frames for each 1000GP population storing allele ages and selection p-values.<br> Please note that only mutations that segregate in the population and map to a unique branch in the Relate-estimated marginal trees are included. Selection p-values are only provided for mutations of DAF &gt; 2 that pass quality filters (see Speidel et al., 2019). To get an age estimate for a neutral mutation, use 0.5*(lower_age + upper_age). To get years from generations, we multiply by 28. The columns of these data frames, named "allele_ages", are CHR: chromosome index BP: base-pair position (GRCh37) ID: id of SNP lower_age: Age in generations of coalescence event at the lower end of the branch onto which the mutation maps upper_age: Age in generations of coalescence event at the upper end of the branch onto which the mutation maps ancestral/derived: Ancestral/derived allele upstream: Upstream (5') allele downstream: Downstream (3') allele DAF: Derived-allele frequency pvalue: log10 p-value for selection evidence
description: For R object files, use load() to load data frames into R.
description: {"references": ["Speidel et al., Nature Genetics 2019, A method for genome-wide genealogy estimation for thousands of samples. https://doi.org/10.1038/s41588-019-0484-x"]}
DOI: 10.5281/zenodo.3234689
title: Relate-estimated coalescence rates, allele ages, and selection p-values for the 1000 Genomes Project

description: <strong>Overview</strong> Coalescence rates, allele ages, and p-values for evidence of positive selection calculated for 2478 samples of the 1000 Genomes Project using Relate. We estimated the joint genealogy of all 1000 GP populations and then extracted the embedded genealogy for each population.<br> For the genealogy of each population, we jointly estimated the population size history and branch lengths. <br> Variants segregating in more than one population therefore have correlated but different allele ages in each population. Please refer to Speidel et al. Nature Genetics (2019) for more details or email leo.speidel@outlook.com for any queries. <strong>Coalescence rates</strong> The zipped directory coalescence_rates.zip contains coalescence rates for 26 populations in the 1000 Genomes Project data set. The .coal files show the haploid coalescence rates, please refer to the Relate documentation for the file format. The popsize.RData file is an R data frame storing the diploid population sizes (0.5/coalescence rate) calculated using the .coal files. The columns of this data frame, named "pop_size", are gens_ago: Time in generations at which epoch starts. (To get years from generations, we multiply by 28.) population_size: Diploid population size in this epoch. population: Name of population region: Name of region (AFR, AMR, EAS, EUR, SAS) <strong>Allele ages and selection p-values</strong> The zipped directories allele_ages_*.zip contain R data frames for each 1000GP population storing allele ages and selection p-values.<br> Please note that only mutations that segregate in the population and map to a unique branch in the Relate-estimated marginal trees are included. Selection p-values are only provided for mutations of DAF &gt; 2 that pass quality filters (see Speidel et al., 2019). To get an age estimate for a neutral mutation, use 0.5*(lower_age + upper_age). To get years from generations, we multiply by 28. The columns of these data frames, named "allele_ages", are CHR: chromosome index BP: base-pair position (GRCh37) ID: id of SNP lower_age: Age in generations of coalescence event at the lower end of the branch onto which the mutation maps upper_age: Age in generations of coalescence event at the upper end of the branch onto which the mutation maps ancestral/derived: Ancestral/derived allele upstream: Upstream (5') allele downstream: Downstream (3') allele DAF: Derived-allele frequency pvalue: log10 p-value for selection evidence
description: For R object files, use load() to load data frames into R.
description: {"references": ["Speidel et al., Nature Genetics 2019, A method for genome-wide genealogy estimation for thousands of samples. https://doi.org/10.1038/s41588-019-0484-x"]}
DOI: 10.7910/dvn/0w3vca/ablvkl
title: PSA_Functions-1.R

description: :unav
DOI: 10.5519/qd.paks3b9o
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (162 records)
DOI: 10.7910/dvn/0w3vca/9pn8gh
title: PSA Homemade4-1.R

description: :unav
DOI: 10.7910/dvn/0w3vca/dvse4e
title: OP Input for CE2-1.tab

description: :unav
DOI: 10.7910/dvn/0w3vca/gkjy0a
title: MEA-1.do

description: :unav
DOI: 10.7910/dvn/0w3vca/hyyroj
title: Pure_replication-1.do

description: :unav
DOI: 10.7910/dvn/0w3vca/qmelhs
title: Readme_Replication_Food_Cash_Vouchers-1.txt

description: :unav
DOI: 10.7910/dvn/0w3vca/s9t9nd
title: 1. Tables for JDE paper_pbr-1.do

description: :unav
DOI: 10.7910/dvn/3jzmwp/cpycpl
title: SURVEY_DATA.dta

description: :unav
DOI: 10.7910/dvn/3jzmwp/ta3h5r
title: 2_3IESurvey_Analysis 18 May 2017.do

description: :unav
DOI: 10.7910/dvn/ffxzbb/ffz71n
title: 5_Combined Baseline_Follow up_U5_3ie.tab

description: :unav
DOI: 10.7910/dvn/ffxzbb/l5u0d2
title: 3_HH_Women data_3ie_followup.tab

description: :unav
DOI: 10.7910/dvn/ffxzbb/nxlaj3
title: 2_HH and all member data_3ie_baseline.tab

description: :unav
DOI: 10.7910/dvn/ffxzbb/pedfat
title: analysis_Results in Final report.do

description: :unav
DOI: 10.7910/dvn/ffxzbb/xw18ru
title: 1_HH data_3ie_baseline.tab

description: :unav
DOI: 10.7910/dvn/cvwukp/0uiouy
title: Final Data Endline.tab

description: :unav
DOI: 10.7910/dvn/cvwukp/3vtl9y
title: Results tables acc to Report.tab

description: :unav
DOI: 10.7910/dvn/cvwukp/8a4i7f
title: 3ie_Data_Submission Details.docx

description: :unav
DOI: 10.7910/dvn/cvwukp/8egre8
title: Final Data baseline.tab

description: :unav
DOI: 10.7910/dvn/cvwukp/s9rumz
title: Merged data set.tab

description: :unav
DOI: 10.7910/dvn/cvwukp/v64qen
title: PII Information.txt

description: :unav
DOI: 10.7910/dvn/cvwukp/zpoj33
title: Secondary Analysis_HMIS   Data_2013 - 2017_Ipara_IIara_.xlsx

description: :unav
DOI: 10.7910/dvn/ffxzbb/wlxt9l
title: 3_HH_Women data_3ie_baseline.tab

description: :unav
DOI: 10.7910/dvn/ytwna2/avz45u
title: tableB6_1.txt

description: :unav
DOI: 10.7910/dvn/ytwna2/iqbgau
title: data_cace_epsoc_q1_matched.csv

description: :unav
DOI: 10.7910/dvn/ytwna2/jd9exh
title: data_epsoc_q1_matched.csv

description: :unav
DOI: 10.7910/dvn/ytwna2/jhencn
title: tableB7.txt

description: :unav
DOI: 10.7910/dvn/ytwna2/pkocy1
title: table4.txt

description: :unav
DOI: 10.7910/dvn/ytwna2/vg54r1
title: table3_2.txt

description: :unav
DOI: 10.7281/t1/em61ib/jhoctd
title: Seasonal Survey 3.zip

description: Cross sectional dataset and documentation for the third seasonal survey conducted in 2014.
DOI: 10.7281/t1/em61ib/l6lau2
title: Seasonal Survey 2.zip

description: Cross sectional dataset and documentation for the second seasonal survey conducted in 2014.
DOI: 10.7281/t1/em61ib/n50uii
title: Seasonal Survey 4.zip

description: Cross sectional dataset and documentation for the fourth seasonal survey conducted in 2015.