cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7910/dvn/bskdsd/nnq8fd
title: TableA6_IFLS.tex

description: :unav
DOI: 10.7910/dvn/bskdsd/v04hjz
title: Table3_IFLS.tab

description: :unav
DOI: 10.7910/dvn/bskdsd/kp3vvk
title: TableA14_KLPS_PanelB.tex

description: :unav
DOI: 10.7910/dvn/bskdsd/upeqt5
title: TableA15_search.tex

description: :unav
DOI: 10.7910/dvn/bskdsd/3nmhto
title: TableA2_IFLS.tex

description: :unav
DOI: 10.7910/dvn/bskdsd/2mopi4
title: FigureA8_IFLS_urban.eps

description: :unav
DOI: 10.7910/dvn/bskdsd/itpodu
title: Table6_IFLS_urban.tex

description: :unav
DOI: 10.7910/dvn/bskdsd/ajpjfn
title: 6. Cr23_ik_css_mod.do

description: :unav
DOI: 10.7910/dvn/bskdsd/jay8oh
title: IFLS.tab

description: :unav
DOI: 10.7910/dvn/bskdsd/zzsd0b
title: Table4_KLPS.tex

description: :unav
DOI: 10.7910/dvn/bskdsd/grd243
title: Figure1_IFLS_agnonag.gph

description: :unav
DOI: 10.7910/dvn/bskdsd/yufmjc
title: FigureA1.png

description: :unav
DOI: 10.7910/dvn/bskdsd/gj53pp
title: TableA16_IFLS.tex

description: :unav
DOI: 10.7910/dvn/bskdsd/zljapv
title: Figure3_IFLS.eps

description: :unav
DOI: 10.7910/dvn/bskdsd/fclpi7
title: Table1_IFLS.tex

description: :unav
DOI: 10.7910/dvn/bskdsd/crd2gg
title: TableA23_KLPS.tex

description: :unav
DOI: 10.7910/dvn/bskdsd/6dm2ms
title: TableA4_IFLS.tex

description: :unav
DOI: 10.7910/dvn/bskdsd/wtcsbi
title: TableA8_IFLS.tex

description: :unav
DOI: 10.7910/dvn/bskdsd/owy6bz
title: TableA22_IFLS_rural.tex

description: :unav
DOI: 10.7910/dvn/bskdsd/byiil0
title: Figure3_KLPS.eps

description: :unav
DOI: 10.7910/dvn/bskdsd/p18fhg
title: FigureA3.xlsx

description: :unav
DOI: 10.7910/dvn/bskdsd/latfci
title: TableA13_IFLS.tex

description: :unav
DOI: 10.7910/dvn/bskdsd/itfgtb
title: Log_HKLM.log

description: :unav
DOI: 10.7910/dvn/bskdsd/xxmpk4
title: Figure1_IFLS_ruralurban.gph

description: :unav
DOI: 10.6084/m9.figshare.5181664
title: Differential Treatment Mechanisms in Mindfulness Meditation and Progressive Muscle Relaxation

description: mechanism of mindfulness <br>
DOI: 10.6084/m9.figshare.5181670
title: Letter of the editor.docx

description: Is a principal common pathology
DOI: 10.6084/m9.figshare.5181664.v2
title: Differential Treatment Mechanisms in Mindfulness Meditation and Progressive Muscle Relaxation

description: mechanism of mindfulness <br>
DOI: 10.6084/m9.figshare.5181664.v1
title: 6.28data(80)：pre- post and follow-up.sav

description: mechanism of mindfulness <br>
DOI: 10.6084/m9.figshare.5181607
title: Data repository: Adaptations of an RNA virus to increasing thermal stress

description: Data repository and analysis scripts for pre-print version of paper "Adaptations of an RNA Virus to Increasing Thermal Stress."
DOI: 10.6084/m9.figshare.5181613
title: Investigating asymmetric salt profiles for nanopore DNA sequencing with biological porin MspA

description: Novaetaeldata.zip contains .mat files containing the consensus files used for the signal, noise, and open state analysis of different asymmetric salt profiles.<br>DNAinteractionrate_files.zip contains .mat files containing the current vs time traces used to calculate DNA interaction rates at different conditions<br>if any questions, email iancurtisnova@gmail.com
DOI: 10.6084/m9.figshare.5181607.v1
title: Data repository: Adaptations of an RNA virus to increasing thermal stress

description: Data repository and analysis scripts for pre-print version of paper "Adaptations of an RNA Virus to Increasing Thermal Stress."
DOI: 10.6084/m9.figshare.5181535
title: "Evolution of Language" paper complimentary material

description: "Evolution of Language" paper complimentary material
DOI: 10.6084/m9.figshare.12420968.v1
title: Benchmarking atlas-level data integration in single-cell genomics - integration task datasets (Immune and pancreas)

description: Pancreas, human immune cell, and human and mouse immune cell integration tasks from the manuscript "Benchmarking atlas-level data integration in single-cell genomics". <br><br>These datasets were aggregated from public datasets, cell annotations were harmonized or reannotated, and the data was consistently preprocessed using scran pooling and log+1 transformation. In the immune cell datasets an erythrocyte development trajectory was also annotated. Details on dataset preprocessing can be found in the paper and in the accompanying Github at https://www.github.com/theislab/scib.<br><br>Please cite the paper when using this dataset.<br>
DOI: 10.6084/m9.figshare.5181481
title: Relationships of Agricultural Land Use to an Expanded Road Network within Tropical Forest Landscapes of Cameroon and Republic of the Congo

description: Road building in Congo Basin forests has increased due to expansion of commercial logging, with potential to expose intact forests to greater establishment of agriculture. We developed new knowledge of agriculture clearing sizes, spatial patterns, and relationships with roads in seven case study sites comprising 7,529 km<sup>2</sup>. Using very high spatial resolution satellite imagery, we mapped roads and rivers, plus clearings for agriculture, settlements, and logging. Mapped clearings (<i>N</i> = 1,781) ranged in size from 0.008 ha to more than 300 ha; most were smallholder agriculture, with 64 percent ≤ 1 ha. Statistical tests of spatial pattern confirmed that agriculture occurred in an inhomogeneous-aggregated pattern, suggesting interactions with other landscape elements. Proximity analyses showed that 76 percent of clearings were within 1 km of a road or river. Thirty-five percent of agriculture clearings were within 1 km of main public roads built before 1990, compared to 17 percent for logging roads built after 2000. Less than 6 percent of agriculture clearings were within 1 km of logging roads with overgrown canopies, suggesting transient relationships. Results based on fine-scale data provide new empirical support for understanding the interactions between agriculture and roads in one of the remaining relatively intact forest areas of the Congo Basin.
DOI: 10.6084/m9.figshare.5181526
title: Why would apparent <i>κ</i> linearly change with O/C? Assessing the role of volatility, solubility, and surface activity of organic aerosols

description: Correlations between O/C and cloud condensation nucleus activity, represented by κ, are a computationally efficient approach to estimate the impact of aerosol aging on cloud formation and climate; however, previously reported correlations between these two variables are empirical and vary widely in their slopes and extrapolations to high O/C values. This study proposes a theoretical framework that bridges elemental ratios, volatility, solubility, and <i>κ</i>. The framework estimates intrinsic <i>κ</i> based on molecular formulas of organics composed of carbon, oxygen, and hydrogen that partition to condensed phase, and then it estimates apparent <i>κ</i> considering solubility distribution parameterized by O/C. This article applied the new framework to the two-dimensional volatility basis set (2D-VBS) and found that distribution of O/C and molecular size play key roles in determining apparent <i>κ</i>. For highly soluble organics, <i>κ</i> is dictated by gas-particle partitioning and it is unlikely for <i>κ</i> of organics to go beyond 0.3 in typical ambient organic material loadings. Sensitivity analysis showed that surface-active compounds are not likely to profoundly alter the overall trend within a reasonable range of surface activity. This framework provides a simple yet plausible explanation of why <i>κ</i> would and would not correlate with O/C; distributions of OA in the 2D-VBS as well as the presence of inorganic salts determine the trend. The framework opens up new opportunities to evaluate two-dimensional representations of organic aerosol aging using <i>κ</i>, a significant advancement from the current empirical linear fits to <i>κ</i> and O/C. Copyright © 2017 American Association for Aerosol Research
DOI: 10.6084/m9.figshare.5181481.v1
title: Relationships of Agricultural Land Use to an Expanded Road Network within Tropical Forest Landscapes of Cameroon and Republic of the Congo

description: Road building in Congo Basin forests has increased due to expansion of commercial logging, with potential to expose intact forests to greater establishment of agriculture. We developed new knowledge of agriculture clearing sizes, spatial patterns, and relationships with roads in seven case study sites comprising 7,529 km<sup>2</sup>. Using very high spatial resolution satellite imagery, we mapped roads and rivers, plus clearings for agriculture, settlements, and logging. Mapped clearings (<i>N</i> = 1,781) ranged in size from 0.008 ha to more than 300 ha; most were smallholder agriculture, with 64 percent ≤ 1 ha. Statistical tests of spatial pattern confirmed that agriculture occurred in an inhomogeneous-aggregated pattern, suggesting interactions with other landscape elements. Proximity analyses showed that 76 percent of clearings were within 1 km of a road or river. Thirty-five percent of agriculture clearings were within 1 km of main public roads built before 1990, compared to 17 percent for logging roads built after 2000. Less than 6 percent of agriculture clearings were within 1 km of logging roads with overgrown canopies, suggesting transient relationships. Results based on fine-scale data provide new empirical support for understanding the interactions between agriculture and roads in one of the remaining relatively intact forest areas of the Congo Basin.
DOI: 10.6084/m9.figshare.5181526.v2
title: Why would apparent <i>κ</i> linearly change with O/C? Assessing the role of volatility, solubility, and surface activity of organic aerosols

description: Correlations between O/C and cloud condensation nucleus activity, represented by κ, are a computationally efficient approach to estimate the impact of aerosol aging on cloud formation and climate; however, previously reported correlations between these two variables are empirical and vary widely in their slopes and extrapolations to high O/C values. This study proposes a theoretical framework that bridges elemental ratios, volatility, solubility, and <i>κ</i>. The framework estimates intrinsic <i>κ</i> based on molecular formulas of organics composed of carbon, oxygen, and hydrogen that partition to condensed phase, and then it estimates apparent <i>κ</i> considering solubility distribution parameterized by O/C. This article applied the new framework to the two-dimensional volatility basis set (2D-VBS) and found that distribution of O/C and molecular size play key roles in determining apparent <i>κ</i>. For highly soluble organics, <i>κ</i> is dictated by gas-particle partitioning and it is unlikely for <i>κ</i> of organics to go beyond 0.3 in typical ambient organic material loadings. Sensitivity analysis showed that surface-active compounds are not likely to profoundly alter the overall trend within a reasonable range of surface activity. This framework provides a simple yet plausible explanation of why <i>κ</i> would and would not correlate with O/C; distributions of OA in the 2D-VBS as well as the presence of inorganic salts determine the trend. The framework opens up new opportunities to evaluate two-dimensional representations of organic aerosol aging using <i>κ</i>, a significant advancement from the current empirical linear fits to <i>κ</i> and O/C. Copyright © 2017 American Association for Aerosol Research
DOI: 10.6084/m9.figshare.5181526.v1
title: Why would apparent κ linearly change with O/C? Assessing the Role of Volatility, Solubility, and Surface Activity of Organic Aerosols

description: Correlations between O/C and cloud condensation nucleus activity, represented by κ, are a computationally efficient approach to estimate the impact of aerosol aging on cloud formation and climate; however, previously reported correlations between these two variables are empirical and vary widely in their slopes and extrapolations to high O/C values. This study proposes a theoretical framework that bridges elemental ratios, volatility, solubility, and κ. The framework estimates intrinsic κ based on molecular formulas of organics composed of carbon, oxygen, and hydrogen that partition to condensed phase, and then it estimates apparent κ considering solubility distribution parameterized by O/C. This paper applied the new framework to the two-dimensional volatility basis set (2D-VBS) and found that distribution of O/C and molecular size play key roles in determining apparent κ. For highly soluble organics, κ is dictated by gas-particle partitioning and it is unlikely for κ of organics to go beyond 0.3 in typical ambient organic material loadings. Sensitivity analysis showed that surface-active compounds are not likely to profoundly alter the overall trend within a reasonable range of surface activity. This framework provides a simple yet plausible explanation of why κ would and would not correlate with O/C; distributions of OA in the 2D-VBS as well as the presence of inorganic salts determine the trend. The framework opens up new opportunities to evaluate two-dimensional representations of organic aerosol aging using κ, a significant advancement from the current empirical linear fits to κ and O/C.
DOI: 10.6084/m9.figshare.5181172
title: U–Pb zircon, geochemical and Sr–Nd–Hf isotopic constraints on age and origin of the intrusions from Wunugetushan porphyry deposit, Northeast China: implication for Triassic–Jurassic Cu–Mo mineralization in Mongolia–Erguna metallogenic belt

description: The Wunugetushan porphyry Cu–Mo deposit is located in northeastern China. The deposit lies within the Mongolia–Erguna metallogenic belt, which is associated with the evolution of the Mongol–Okhotsk Ocean. The multiple episodes of magmatism in the ore district, occurred from 206 to 173 Ma, can be divided into pre-mineralization stage (biotite granite), mineralization stage (monzogranitic porphyry and rhyolitic porphyry), and post-mineralization stage (andesitic porphyry). The biotite granite has (<sup>87</sup>Sr/<sup>86</sup>Sr)<i><sub>i</sub></i> values of 0.704105–0.704706, <i>ε</i><sub>Nd</sub>(<i>t</i>) values of −0.67 to −0.07, and <i>ε</i><sub>Hf</sub>(<i>t</i>) values of −0.4 to 2.8, yielding Hf two-stage model ages (<i>T</i><sub>DM2</sub>) 1250–1067 Ma, and Nd model ages of 1.04–0.96 Ga, indicating that the pre-mineralization magmas were generated by the remelting of Neoproterozoic juvenile crustal material. The monzogranitic porphyry has (<sup>87</sup>Sr/<sup>86</sup>Sr)<i><sub>i</sub></i> values of 0.704707–0.706134, <i>ε</i><sub>Nd</sub>(<i>t</i>) values of 0.29–1.33, and <i>ε</i><sub>Hf</sub>(<i>t</i>) values of 1.0–2.9, yielding <i>T</i><sub>DM2</sub> model ages of 1173–1047 Ma. The rhyolitic porphyry has (<sup>87</sup>Sr/<sup>86</sup>Sr)<i><sub>i</sub></i> ratio of 0.702129, <i>ε</i><sub>Nd</sub>(<i>t</i>) value of −0.21, and <i>ε</i><sub>Hf</sub>(<i>t</i>) values of −0.5 to 7.1, <i>T</i><sub>DM2</sub> model ages from 1269 to 782 Ma. These results show that the magmas of mineralization stage were generated by the partial melting of juvenile crust mixed with mantle-derived components. The andesitic porphyry has (<sup>87</sup>Sr/<sup>86</sup>Sr)<i><sub>i</sub></i> ratio of 0.705284, <i>ε</i><sub>Nd</sub>(<i>t</i>) value of 0.82, and <i>ε</i><sub>Hf</sub>(<i>t</i>) values from 4.1 to 7.4, indicating that the post-mineralization magma source contained more mantle-derived material. The Mesozoic Cu–Mo deposits which genetically related to Mongol–Okhotsk Ocean were temporally distributed in Middle to Late Triassic (240–230 Ma), Early Jurassic (200–180 Ma), and Later Jurassic (160–150 Ma) period. The Middle Triassic to Early Jurassic Cu–Mo mineralization was dominated by Mongol–Okhotsk oceanic plate southeast-directed subducted beneath the Erguna massif. The Later Jurassic Cu–Mo mineralization was controlled by the continent–continent collision between Siberia plate and Erguna massif.
DOI: 10.6084/m9.figshare.5181172.v1
title: U–Pb zircon, geochemical and Sr–Nd–Hf isotopic constraints on age and origin of the intrusions from Wunugetushan porphyry deposit, Northeast China: implication for Triassic–Jurassic Cu–Mo mineralization in Mongolia–Erguna metallogenic belt

description: The Wunugetushan porphyry Cu–Mo deposit is located in northeastern China. The deposit lies within the Mongolia–Erguna metallogenic belt, which is associated with the evolution of the Mongol–Okhotsk Ocean. The multiple episodes of magmatism in the ore district, occurred from 206 to 173 Ma, can be divided into pre-mineralization stage (biotite granite), mineralization stage (monzogranitic porphyry and rhyolitic porphyry), and post-mineralization stage (andesitic porphyry). The biotite granite has (<sup>87</sup>Sr/<sup>86</sup>Sr)<i><sub>i</sub></i> values of 0.704105–0.704706, <i>ε</i><sub>Nd</sub>(<i>t</i>) values of −0.67 to −0.07, and <i>ε</i><sub>Hf</sub>(<i>t</i>) values of −0.4 to 2.8, yielding Hf two-stage model ages (<i>T</i><sub>DM2</sub>) 1250–1067 Ma, and Nd model ages of 1.04–0.96 Ga, indicating that the pre-mineralization magmas were generated by the remelting of Neoproterozoic juvenile crustal material. The monzogranitic porphyry has (<sup>87</sup>Sr/<sup>86</sup>Sr)<i><sub>i</sub></i> values of 0.704707–0.706134, <i>ε</i><sub>Nd</sub>(<i>t</i>) values of 0.29–1.33, and <i>ε</i><sub>Hf</sub>(<i>t</i>) values of 1.0–2.9, yielding <i>T</i><sub>DM2</sub> model ages of 1173–1047 Ma. The rhyolitic porphyry has (<sup>87</sup>Sr/<sup>86</sup>Sr)<i><sub>i</sub></i> ratio of 0.702129, <i>ε</i><sub>Nd</sub>(<i>t</i>) value of −0.21, and <i>ε</i><sub>Hf</sub>(<i>t</i>) values of −0.5 to 7.1, <i>T</i><sub>DM2</sub> model ages from 1269 to 782 Ma. These results show that the magmas of mineralization stage were generated by the partial melting of juvenile crust mixed with mantle-derived components. The andesitic porphyry has (<sup>87</sup>Sr/<sup>86</sup>Sr)<i><sub>i</sub></i> ratio of 0.705284, <i>ε</i><sub>Nd</sub>(<i>t</i>) value of 0.82, and <i>ε</i><sub>Hf</sub>(<i>t</i>) values from 4.1 to 7.4, indicating that the post-mineralization magma source contained more mantle-derived material. The Mesozoic Cu–Mo deposits which genetically related to Mongol–Okhotsk Ocean were temporally distributed in Middle to Late Triassic (240–230 Ma), Early Jurassic (200–180 Ma), and Later Jurassic (160–150 Ma) period. The Middle Triassic to Early Jurassic Cu–Mo mineralization was dominated by Mongol–Okhotsk oceanic plate southeast-directed subducted beneath the Erguna massif. The Later Jurassic Cu–Mo mineralization was controlled by the continent–continent collision between Siberia plate and Erguna massif.
DOI: 10.6084/m9.figshare.5178769
title: The Cost of Multiple Representations: Experiment 2 data and scripts

description: Raw data and analysis scripts associated with Experiment 2 in the paper "The Cost of Multiple Representations: Learning Number Symbols with Abstract and Concrete Representations".
DOI: 10.6084/m9.figshare.5178772
title: The Cost of Multiple Representations: Experiment 3 data and scripts

description: Raw data and analysis scripts associated with Experiment 3 in the paper "The Cost of Multiple Representations: Learning Number Symbols with Abstract and Concrete Representations".
DOI: 10.6084/m9.figshare.5178772.v1
title: The Cost of Multiple Representations: Experiment 3 data and scripts

description: Raw data and analysis scripts associated with Experiment 3 in the paper "The Cost of Multiple Representations: Learning Number Symbols with Abstract and Concrete Representations".
DOI: 10.6084/m9.figshare.5178769.v1
title: The Cost of Multiple Representations: Experiment 2 data and scripts

description: Raw data and analysis scripts associated with Experiment 2 in the paper "The Cost of Multiple Representations: Learning Number Symbols with Abstract and Concrete Representations".
DOI: 10.6084/m9.figshare.5178745
title: The Cost of Multiple Representations: Experiment 1 data and scripts

description: Raw data and analysis scripts associated with Experiment 1 in the paper "The Cost of Multiple Representations: Learning Number Symbols with Abstract and Concrete Representations".
DOI: 10.6084/m9.figshare.5178745.v1
title: The Cost of Multiple Representations: Experiment 1 data and scripts

description: Raw data and analysis scripts associated with Experiment 1 in the paper "The Cost of Multiple Representations: Learning Number Symbols with Abstract and Concrete Representations".
DOI: 10.6084/m9.figshare.5178529
title: Administrative boundaries shapefile

description: Administrative boundaries shapefile (GADM)
DOI: 10.5281/zenodo.4008704
title: Supplementary data and bibliography to "The distribution of querns and millstones of Mayen lava in the Early Middle Ages (c. 500 to 1050 A.D.)"

description: Supplementary data and bibliography to “The distribution of querns and millstones of Mayen lava in the Early<br> Middle Ages (c. 500 to 1050 A.D.)”; list of findspots for the following maps: fig. 1. Findspots of basalt-like lava (tephrite) dating from c. 30 BC to 275 AD. fig. 2 Findspots of basalt-like lava (tephrite) dating from c. 275 AD to 500 AD. fig. 3 Findspots of basalt-like lava (tephrite) dating from c. 500 AD to 750 AD. fig. 5 Findspots of basalt-like lava (tephrite) dating from c. 750 AD to 1050 AD.
DOI: 10.5281/zenodo.4008703
title: Supplementary data and bibliography to "The distribution of querns and millstones of Mayen lava in the Early Middle Ages (c. 500 to 1050 A.D.)"

description: Supplementary data and bibliography to “The distribution of querns and millstones of Mayen lava in the Early<br> Middle Ages (c. 500 to 1050 A.D.)”; list of findspots for the following maps: fig. 1. Findspots of basalt-like lava (tephrite) dating from c. 30 BC to 275 AD. fig. 2 Findspots of basalt-like lava (tephrite) dating from c. 275 AD to 500 AD. fig. 3 Findspots of basalt-like lava (tephrite) dating from c. 500 AD to 750 AD. fig. 5 Findspots of basalt-like lava (tephrite) dating from c. 750 AD to 1050 AD.
DOI: 10.17632/vfxf4trtcg.3
title: rust (Hemileia vastatrix) and leaf miner (Leucoptera coffeella) in coffee crop (Coffea arabica).
DOI: 10.17632/pphgdmxkxt.1
title: Data for: Response inhibition and memory updating in the Count/Nocount task: an ERP study

description: Behavioural and ERP data.
DOI: 10.17632/h76nbndxt6.3
title: Dataset of leaf inclination angles for 71 different Eucalyptus species

description: The dataset presents leaf angle measurements for 71 different, Australia-native Eucalyptus species collected in 13 botanical gardens. This dataset is supplementary data for the submitted paper to Data in Brief [1]. The data format corresponds to the one used for reporting leaf angle measurements in TRY plant trait database. Regarding the measurements, we provide information on species, latitude, longitude, altitude, sampling date, exposition, plant growth form, comments, methods, reference, and measured leaf angles. Along with the dataset, R code (getLIAD.R) is provided which calculates Beta distribution parameters, mean and standard deviation, and de Wit distribution type from an input .csv file with leaf angle measurements (in degrees). Sample input .csv file (input_example_LIA.csv) for the R code is provided as well. Paper [1] describes the applied data collection methods and procedures. The data were collected as a part of projects from Estonian Research Council Grants PUT 232, PUT1355, Mobilitas Pluss MOBERC11, P7-Marie Curie Actions program, and Estonian Science Foundation grant no. ERMOS32. See further detail from the related article. [1] Pisek J., & Adamson, K. 2020. A dataset of leaf inclination angles for 71 different Eucalyptus species. Data in Brief (2020).