cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.17304097
title: Gender and Productivity Differentials in Smallholder Groundnut Farming in Malawi: Accounting for Technology Differences

description: The gender gap in agricultural productivity has been of ongoing interest to development policy and we revisit the subject in the context of groundnut, an important food and cash legume in Sub Saharan Africa. We address production technology differences between male and female managers of groundnut plots and examine the implications for the male–female difference in productivity. Using cross-sectional data, two recent stochastic meta-frontier (SMF) techniques are coupled with statistical matching to examine gender-related technology, managerial, single and total factor productivity (TFP) gaps. The results reveal different production technologies in use by male and female producers, and technology (6–7 per cent points) and managerial (3–5 per cent points) differentials, which translate into significant male advantages in land productivity (6.2 per cent) and TFP (15.3 per cent). A heterogeneity analysis provides valuable insights: Technology, managerial and TFP gaps, which favour male managers, decrease with age, years of schooling, exposure to extension, and use of hired labour and improved seeds; but increase with total cultivated area. Closing the productivity gap will require expanding female production possibilities through use of improved inputs and practices and enhancing managerial skill and know-how through extension.
DOI: 10.6084/m9.figshare.17304097.v2
title: Gender and Productivity Differentials in Smallholder Groundnut Farming in Malawi: Accounting for Technology Differences

description: The gender gap in agricultural productivity has been of ongoing interest to development policy and we revisit the subject in the context of groundnut, an important food and cash legume in Sub Saharan Africa. We address production technology differences between male and female managers of groundnut plots and examine the implications for the male–female difference in productivity. Using cross-sectional data, two recent stochastic meta-frontier (SMF) techniques are coupled with statistical matching to examine gender-related technology, managerial, single and total factor productivity (TFP) gaps. The results reveal different production technologies in use by male and female producers, and technology (6–7 per cent points) and managerial (3–5 per cent points) differentials, which translate into significant male advantages in land productivity (6.2 per cent) and TFP (15.3 per cent). A heterogeneity analysis provides valuable insights: Technology, managerial and TFP gaps, which favour male managers, decrease with age, years of schooling, exposure to extension, and use of hired labour and improved seeds; but increase with total cultivated area. Closing the productivity gap will require expanding female production possibilities through use of improved inputs and practices and enhancing managerial skill and know-how through extension.
DOI: 10.18112/openneuro.ds004166.v1.0.0
title: Effects of Forward and Backward Span Trainings on Working Memory: Evidence from a Randomized, Controlled Trial
DOI: 10.34740/kaggle/dsv/3817880
title: WallStreetBets 2022
DOI: 10.57745/bounlh/e9peeb
title: MM-CRO6-IgA1_GAGCTT-CR3MB_L001_R1.fastq.gz

description: :unav
DOI: 10.57745/bounlh/q31fwf
title: MM-CRO1-IgA2_AAACAA-CR3MB_L001_R1.fastq.gz

description: :unav
DOI: 10.57745/bounlh/2dn0f9
title: MM-CRO1-IgA1_TGCTGA-CR3MB_L001_R1.fastq.gz

description: :unav
DOI: 10.57745/bounlh/uljp6l
title: MM-CRO6-IgA1_GAGCTT-CR3MB_L001_R2.fastq.gz

description: :unav
DOI: 10.57745/bounlh/uxgazd
title: MM-CRO1-IgA1_TGCTGA-CR3MB_L001_R2.fastq.gz

description: :unav
DOI: 10.57745/bounlh/duolmu
title: MM-CRO1-IgA2_AAACAA-CR3MB_L001_R2.fastq.gz

description: :unav
DOI: 10.57745/bounlh/exx9jw
title: MM-CRO6-IgA2_AGGGAT-CR3MB_L001_R2.fastq.gz

description: :unav
DOI: 10.57745/bounlh/e1emil
title: MM-CRO7-IgA2_GCAATA-CR3MB_L001_R1.fastq.gz

description: :unav
DOI: 10.57745/bounlh/jpcu0m
title: MM-CRO7-IgA1_TCTCGG-CR3MB_L001_R2.fastq.gz

description: :unav
DOI: 10.57745/bounlh/dua02h
title: MM-CRO7-IgA2_GCAATA-CR3MB_L001_R2.fastq.gz

description: :unav
DOI: 10.57745/bounlh/zxo6o1
title: MM-CRO7-IgA1_TCTCGG-CR3MB_L001_R1.fastq.gz

description: :unav
DOI: 10.57745/bounlh/4zimxb
title: MM-CRO6-IgA2_AGGGAT-CR3MB_L001_R1.fastq.gz

description: :unav
DOI: 10.57745/bounlh/zkcymg
title: MM-CRO9-IgA2_CAATTA-CR3MB_L001_R2.fastq.gz

description: :unav
DOI: 10.57745/bounlh/wojj2w
title: MM-CRO10-IgA1_GCCAAG-CR3MB_L001_R1.fastq.gz

description: :unav
DOI: 10.57745/bounlh/adzfew
title: MM-CRO9-IgA1_AGCGAC-CR3MB_L001_R1.fastq.gz

description: :unav
DOI: 10.57745/bounlh/qo1vuz
title: MM-CRO10-IgA1_GCCAAG-CR3MB_L001_R2.fastq.gz

description: :unav
DOI: 10.57745/bounlh/6alm5e
title: MM-CRO9-IgA2_CAATTA-CR3MB_L001_R1.fastq.gz

description: :unav
DOI: 10.57745/bounlh/wtj4wp
title: MM-CRO9-IgA1_AGCGAC-CR3MB_L001_R2.fastq.gz

description: :unav
DOI: 10.57745/bounlh/4i4edl
title: MM-CRO10-IgA2_CAATGC-CR3MB_L001_R1.fastq.gz

description: :unav
DOI: 10.57745/bounlh/h0johg
title: MM-CRO11-IgA2_TGTTCG-CR3MB_L001_R2.fastq.gz

description: :unav
DOI: 10.57745/bounlh/qrj7sr
title: MM-CRO10-IgA2_CAATGC-CR3MB_L001_R2.fastq.gz

description: :unav
DOI: 10.57745/bounlh/30lhbs
title: MM-CRO11-IgA1_AGGTTC-CR3MB_L001_R2.fastq.gz

description: :unav
DOI: 10.57745/bounlh/tdmiaf
title: MM-CRO11-IgA2_TGTTCG-CR3MB_L001_R1.fastq.gz

description: :unav
DOI: 10.57745/bounlh/99qae6
title: MM-CRO11-IgA1_AGGTTC-CR3MB_L001_R1.fastq.gz

description: :unav
DOI: 10.25402/cer.20088263
title: Acute effects of resistance exercise with blood flow restriction on cardiovascular response: a meta-analysis - Appendix .doc

description: <strong>Appendix</strong> <strong>1. Search strategies</strong> Appendix 2 <strong>Table 1. </strong>Methodological quality of eligible studies, PEDRo scale <strong>Appendix</strong> <strong>4. Assessment of the quality of evidence through the grade system</strong> <br> <strong>Table 1. </strong> Quality of evidence of acute effects in the comparison between LLRT-BFR vs HLRT and LLRT-BFR vs. LLRT. <strong>Table 2.</strong> Quality of the evidence of acute effects in lower limb when comparing between LLRT-BFR vs HLRT and LLRT-BFR vs. LLRT. <strong>Table 3. </strong>Quality of evidence of acute effects in upper limbs when comparing between LLRT-BFR vs HLRT and LLRT-BFR vs. LLRT. <strong>Table 4. </strong> Quality of evidence for intermittent BRF applications between LLRT-BFR vs HLRT and LLRT-BFR vs. LLRT. <strong>Table 5.</strong> Quality of evidence for continuous BFR applications between LLRT-BFR vs HLRT and LLRT-BFR vs. LLRT. <br>
DOI: 10.25402/cer.20088263.v1
title: Acute effects of resistance exercise with blood flow restriction on cardiovascular response: a meta-analysis - Appendix .doc

description: <strong>Appendix</strong> <strong>1. Search strategies</strong> Appendix 2 <strong>Table 1. </strong>Methodological quality of eligible studies, PEDRo scale <strong>Appendix</strong> <strong>4. Assessment of the quality of evidence through the grade system</strong> <br> <strong>Table 1. </strong> Quality of evidence of acute effects in the comparison between LLRT-BFR vs HLRT and LLRT-BFR vs. LLRT. <strong>Table 2.</strong> Quality of the evidence of acute effects in lower limb when comparing between LLRT-BFR vs HLRT and LLRT-BFR vs. LLRT. <strong>Table 3. </strong>Quality of evidence of acute effects in upper limbs when comparing between LLRT-BFR vs HLRT and LLRT-BFR vs. LLRT. <strong>Table 4. </strong> Quality of evidence for intermittent BRF applications between LLRT-BFR vs HLRT and LLRT-BFR vs. LLRT. <strong>Table 5.</strong> Quality of evidence for continuous BFR applications between LLRT-BFR vs HLRT and LLRT-BFR vs. LLRT. <br>
DOI: 10.5281/zenodo.6628922
title: Doppler lidar wind profiles from Granada

description: This is data set includes Doppler wind lidar quantities which were calculated from measurements performed between 2016 and 2020 at <em>Andalusian Global Observatory of the Atmosphere</em>, AGORA, in particular, at the UGR station, Andalusian Institute for Earth System Research (IISTA-CEAMA) in Granada, Spain (37.16ºN, 3.61ºW, 680 m a.s.l.). The system is a Doppler lidar Stream Line (Halo Photonics), which is part of ACTRIS-Cloudnet (Illingworth et al., 2007). The system laser emits at 1.5 μm and the detector is heterodyne using fiber-optic technology. The measurements for this data set consisted of conical scans with constant elevation of 75° and 12 equidistant azimuth points performed every 10 min. A more detailed description of the instrument can be found in (Ortiz-Amezcua et al., 2022)
description: {"references": ["Illingworth, A.J.; Hogan, R.J.; O'Connor, E.J.; Bouniol, D.; Brooks, M.E.; Delano\u00eb, J.; Donovan, D.P.; Eastment, J.D.; Gaussiat, N.; Goddard, J.W.F.; et al. Cloudnet: Continuous evaluation of cloud profiles in seven operational models using ground-based observations. Bull. Am. Meteorol. Soc. 2007, 88, 883\u2013898", "Ortiz-Amezcua, P., Mart\u00ednez-Herrera, A., Manninen, A. J., Pentik\u00e4inen, P. P., O'Connor, E. J., Guerrero-Rascado, J. L., and Alados- Arboledas, L.: Wind and turbulence statistics in the urban boundary layer over a mountain-valley system in Granada, Spain, Remote. Sens., 14, https://doi.org/10.3390/rs14102321, 2022"]}
DOI: 10.25934/pr00006052.6
title: Available IPD datapackage for study 'A Phase III Multicenter, Randomized, Open-Label Study Evaluating the Efficacy and Safety of Atezolizumab (MPDL3280A, Anti-PD-L1 Antibody) in Combination With Carboplatin+Nab-Paclitaxel for Chemotherapy-Naive Patients With Stage IV Non-Squamous Non-Small Cell Lung Cancer'

description: This randomized Phase III, multicenter, open-label study designed to evaluate the safety and efficacy of atezolizumab (an engineered anti-programmed death-ligand 1 [PD-L1] antibody) in combination with carboplatin+nab-paclitaxel compared with treatment with carboplatin+nab-paclitaxel in chemotherapy-naive participants with Stage IV non-squamous NSCLC. Participants will be randomized in a 2:1 ratio to Arm A (Atezolizumab+Nab-Paclitaxel+Carboplatin) or Arm B (Nab-Paclitaxel+Carboplatin).
DOI: 10.25934/pr00005580.2
title: Available IPD datapackage for study 'Randomized, Multicenter, Phase III, Open-Label Study of Alectinib Versus Crizotinib in Treatment-Naive Anaplastic Lymphoma Kinase-Positive Advanced Non-Small Cell Lung Cancer'

description: This randomized, active controlled, multicenter phase III open-label study is designed to evaluate the efficacy and safety of alectinib compared with crizotinib treatment in participants with treatment-naive anaplastic lymphoma kinase-positive (ALK-positive) advanced non-small cell lung cancer (NSCLC). Participants will be randomized in a 1:1 ratio to receive either alectinib, 600 milligrams (mg) orally twice daily (BID), or crizotinib, 250 mg orally BID. Participants will receive treatment until disease progression, unacceptable toxicity, consent withdrawal or death. The study is expected to last approximately 42 months.
DOI: 10.5281/zenodo.6422233
title: EPIC: Annotated epileptic EEG independent components for artifact reduction

description: Scalp electroencephalogram is a non-invasive multi-channel biosignal that records the brain’s electrical activity. It is highly susceptible to noise that might overshadow important data. Independent component analysis is one of the most used artifact removal methods. Independent component analysis separates data into different components, although it can not automatically reject the noisy ones. Therefore, experts are needed to decide which components must be removed before reconstructing the data. To automate this method, researchers have developed classifiers to identify noisy components. However, to build these classifiers, they need annotated data. Manually classifying independent components is a time-consuming task. Furthermore, few labeled data are publicly available. This dataset is composed of a source of annotated electroencephalogram independent components acquired from patients with epilepsy (EPIC Dataset). This dataset contains 77,426 independent components obtained from approximately 613 hours of electroencephalogram, visually inspected by two experts, which was already successfully utilized to develop independent component classifiers.
description: This work is funded by FCT- Foundation for Science and Technology, I.P., within the scope of the projects: CISUC UID/CEC/00326/2020 with funds from the European Social Fund, through the Regional Operational Program Centro 2020; and project RECoD - PTDC/EEI-EEE/5788/2020 financed with national funds (PIDDAC) via the Portuguese State Budget. Fábio Lopes gratefully acknowledges the Portuguese funding institution FCT (Foundation for Science and Technology), the226 Human Capital Operational Program (POCH) and the European Union (EU) for supporting this research work under Ph.D.227 grant 2020.04537.BD.
DOI: 10.11588/data/plrqcz/qiznia
title: User_perspectives_and_preferences_on_a_novel_TB_LAM_diagnostic__Fujifilm_SILVAMP_TB_LAM__a_qualitative_study_in_Malawi_and_Zambia__AnalysisMemos.pdf

description: :unav
DOI: 10.11588/data/plrqcz/snt01u
title: User_perspectives_and_preferences_on_a_novel_TB_LAM_diagnostic__Fujifilm_SILVAMP_TB_LAM__a_qualitative_study_in_Malawi_and_Zambia__Repository.pdf

description: :unav
DOI: 10.5281/zenodo.6655759
title: Afon Hirnant gut content dataset

description: This dataset contains feeding interactions of the organisms in Afon Hirnant.
DOI: 10.5281/zenodo.6655758
title: Afon Hirnant gut content dataset

description: This dataset contains feeding interactions of the organisms in Afon Hirnant.
DOI: 10.25934/pr00006051.8
title: Available IPD datapackage for study 'A Phase III, Open-Label, Randomized Study of Atezolizumab (MPDL3280A, Anti-PD-L1 Antibody) in Combination With Carboplatin+Paclitaxel With or Without Bevacizumab Compared With Carboplatin + Paclitaxel + Bevacizumab in Chemotherapy-Naïve Patients With Stage IV Non-Squamous Non-Small Cell Lung Cancer'

description: This randomized, open-label study will evaluate the safety and efficacy of atezolizumab (an engineered anti-programmed death-ligand 1 [PD-L1] antibody) in combination with carboplatin+paclitaxel with or without bevacizumab compared with treatment with carboplatin+paclitaxel+bevacizumab in chemotherapy-naïve participants with Stage IV non-squamous NSCLC. Participants will be randomized in a 1:1:1 ratio to Arm A (Atezolizumab+Carboplatin+Paclitaxel), Arm B (Atezolizumab+Carboplatin+Paclitaxel+Bevacizumab), or Arm C (Carboplatin+Paclitaxel+Bevacizumab).
DOI: 10.5281/zenodo.6655771
title: Coilaco, Guampoe and Trancura gut content dataset

description: This dataset contains feeding interactions of the organisms in three rivers (Coilaco, Guampoe and Trancura Rivers) within the catchment of the Toltén River in south Chile, South America
DOI: 10.5281/zenodo.6655770
title: Coilaco, Guampoe and Trancura gut content dataset

description: This dataset contains feeding interactions of the organisms in three rivers (Coilaco, Guampoe and Trancura Rivers) within the catchment of the Toltén River in south Chile, South America
DOI: 10.5281/zenodo.6655757
title: Source data for the paper "A laser-assisted chlorination process for reversible writing of doping patterns in graphene"

description: Source Data supporting the plots within the paper "A laser-assisted chlorination process for reversible writing of doping patterns in graphene." Including Source Data for Figures 1-4 in the main text, and Supplementary Figures S1, S3-12, S14, S17.
DOI: 10.5281/zenodo.6655756
title: Source data for the paper "A laser-assisted chlorination process for reversible writing of doping patterns in graphene"

description: Source Data supporting the plots within the paper "A laser-assisted chlorination process for reversible writing of doping patterns in graphene." Including Source Data for Figures 1-4 in the main text, and Supplementary Figures S1, S3-12, S14, S17.
DOI: 10.5281/zenodo.6655773
title: Synthetic 3D PPGIS Data _ Turku - Finland

description: 3D PPGIS data generated synthetically in Turku, Finland. Data is created in an approximately 2 km<sup>2 </sup>area near center. 150X150 m grid cells were used for data generation.
DOI: 10.5281/zenodo.6655772
title: Synthetic 3D PPGIS Data _ Turku - Finland

description: 3D PPGIS data generated synthetically in Turku, Finland. Data is created in an approximately 2 km<sup>2 </sup>area near center. 150X150 m grid cells were used for data generation.
DOI: 10.5281/zenodo.6415108
title: OpenStreetMap+ Protected nature areas in continental Europe (IUCN status + Natura 2000)

description: Twelve maps of continental Europe indicating the protected nature area status in 2019 according to Natura 2000 and the International Union for Conservation of Nature (IUCN). The IUCN status was extracted from crowdsourced data obtained from OpenStreetMap through geofabrik.de. This dataset contains: 3 raster maps representing Natura 2000 protection status (A, B and C), named <strong>Natura2000_[status].tif</strong> 8 raster maps representing OSM-derived IUCN protection status (1a, 1b, 2, 3, 4, 5, 6, and 'other'), named <strong>OSM_IUCN_[status].tif</strong> 1 aggregated map (<strong>adm_protected.area_natura2000.osm_p_30m_0..0cm_2019..2021_eumap_epsg3035_v0.1</strong>) where each of the 11 protection statuses, as well as pixels where multiple statuses apply, are assigned a unique value. This map can also be accessed interactively at maps.opendatascience.eu. All files are provided as Cloud Optimized GeoTIFFs and projected in the Coordinate Reference System ETRS89 / LAEA Europe (= EPSG code 3035). Styling files for the aggregated raster are provided in both <strong><em>SLD</em></strong> and <strong><em>QML</em></strong> format.
description: This work is co-financed under Grant Agreement Connecting Europe Facility (CEF) Telecom project 2018-EU-IA-0095 by the European Union (https://ec.europa.eu/inea/en/connecting-europe-facility/cef-telecom/2018-eu-ia-0095).
DOI: 10.5281/zenodo.6653917
title: OpenStreetMap+ Land Use / Land Cover classes and administrative regions of Europe

description: This dataset contains 23 30m resolution raster data of continental Europe land use / land cover classes extracted from OpenStreetMap, as well as administrative areas, and a harmonized building dataset based on OpenStreetMap and Copernicus HRL Imperviousness data. The land use / land cover classes are: buildings.commercial buildings.industrial buildings.residential cemetery construction.site dump.site (landfill) farmland farmyard forest grass greenhouse harbour meadow military orchard quarry railway reservoir road salt vineyard The land use / land cover data was generated by extracting OSM vector layers from https://download.geofabrik.de/). These were then transformed into a 30 m density raster for each feature type. This was done by first creating a 10 m raster where each pixel intersecting a vector feature was assigned the value 100. These pixels were then aggregated to 10 m resolution by calculating the average of every 9 adjacent pixels. This resulted in a 0—100 density layer for the three feature types. Although the digitized building data from OSM offers the highest level of detail, its coverage across Europe is inconsistent. To supplement the building density raster in regions where crowd-sourced OSM building data was unavailable, we combined it with Copernicus High Resolution Layers (HRL) (obtained from https://land.copernicus.eu/pan-european/ high-resolution-layers), filling the non-mapped areas in OSM with the Impervious Built-up 2018 pixel values, which was averaged to 30 m. The probability values produced by the averaged aggregation were integrated in such a way that values between 0—100 refer to OSM (lowest and highest probabilities equal to 0 and 100 respectively), and the values between 101—200 refer to Copernicus HRL (lowest and highest probability equal to 200 and 101 respectively). This resulted in a raster layer where values closer to 100 are more likely to be buildings than values closer to 0 and 200. Structuring the data in this way allows us to select the higher probability building pixels in both products by the single boolean expression: Pixel &gt; 50 AND pixel &lt;150. This dataset is part of the OpenStreetMap+ was used to pre-process the LUCAS/CORINE land use / land cover samples (https://doi.org/10.5281/zenodo.4740691) used to train machine learning models in Witjes et al., 2022 (https://doi.org/10.21203/rs.3.rs-561383/v4) Each layer can be viewed interactively on the Open Data Science Europe data viewer at maps.opendatascience.eu.
description: This work has received funding from the European Union's the Innovation and Networks Executive Agency (INEA) under Grant Agreement Connecting Europe Facility (CEF) Telecom project 2018-EU-IA-0095 (https://ec.europa.eu/inea/en/connecting-europe-facility/cef-telecom/2018-eu-ia-0095).
DOI: 10.5281/zenodo.6653916
title: OpenStreetMap+ Land Use / Land Cover classes and administrative regions of Europe

description: This dataset contains 23 30m resolution raster data of continental Europe land use / land cover classes extracted from OpenStreetMap, as well as administrative areas, and a harmonized building dataset based on OpenStreetMap and Copernicus HRL Imperviousness data. The land use / land cover classes are: buildings.commercial buildings.industrial buildings.residential cemetery construction.site dump.site (landfill) farmland farmyard forest grass greenhouse harbour meadow military orchard quarry railway reservoir road salt vineyard The land use / land cover data was generated by extracting OSM vector layers from https://download.geofabrik.de/). These were then transformed into a 30 m density raster for each feature type. This was done by first creating a 10 m raster where each pixel intersecting a vector feature was assigned the value 100. These pixels were then aggregated to 10 m resolution by calculating the average of every 9 adjacent pixels. This resulted in a 0—100 density layer for the three feature types. Although the digitized building data from OSM offers the highest level of detail, its coverage across Europe is inconsistent. To supplement the building density raster in regions where crowd-sourced OSM building data was unavailable, we combined it with Copernicus High Resolution Layers (HRL) (obtained from https://land.copernicus.eu/pan-european/ high-resolution-layers), filling the non-mapped areas in OSM with the Impervious Built-up 2018 pixel values, which was averaged to 30 m. The probability values produced by the averaged aggregation were integrated in such a way that values between 0—100 refer to OSM (lowest and highest probabilities equal to 0 and 100 respectively), and the values between 101—200 refer to Copernicus HRL (lowest and highest probability equal to 200 and 101 respectively). This resulted in a raster layer where values closer to 100 are more likely to be buildings than values closer to 0 and 200. Structuring the data in this way allows us to select the higher probability building pixels in both products by the single boolean expression: Pixel &gt; 50 AND pixel &lt;150. This dataset is part of the OpenStreetMap+ was used to pre-process the LUCAS/CORINE land use / land cover samples (https://doi.org/10.5281/zenodo.4740691) used to train machine learning models in Witjes et al., 2022 (https://doi.org/10.21203/rs.3.rs-561383/v4) Each layer can be viewed interactively on the Open Data Science Europe data viewer at maps.opendatascience.eu.
description: This work has received funding from the European Union's the Innovation and Networks Executive Agency (INEA) under Grant Agreement Connecting Europe Facility (CEF) Telecom project 2018-EU-IA-0095 (https://ec.europa.eu/inea/en/connecting-europe-facility/cef-telecom/2018-eu-ia-0095).
DOI: 10.6084/m9.figshare.20088311
title: Financial data

description: The data contain information about adjuced prices at the end of trading date for USA companies in financial sector. The first column contains information abour the date. Each next column corresponds to one company. The data set time span is from 01/01/2002 until 29/12/2017.