cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3886/e152561
title: Accurately Predicting Hit Songs using Neurophysiology and Machine Learning

description: Observed and synthetic neurophysiologic data collected while listening to songs
DOI: 10.3886/e152561v1
title: Accurately Predicting Hit Songs using Neurophysiology and Machine Learning

description: Observed and synthetic neurophysiologic data collected while listening to songs
DOI: 10.21227/5ch0-8b29
title: FOG severity EEG/EMG

description: The data contains 13 Healthy controls
DOI: 10.5281/zenodo.5573950
title: Martian Dust Storms and Gravity Waves: Disentangling Water Transport to the Upper Atmosphere

description: The data for GRL article figures.
DOI: 10.5281/zenodo.4715013
title: Martian Dust Storms and Gravity Waves: Disentangling Water Transport to the Upper Atmosphere

description: The data for GRL article figures.
DOI: 10.3886/e113971v1-98980
title: Replication data for: Consumption Inequality

description: In this essay, we discuss the importance of consumption inequality in the debate concerning the measurement of disparities in economic well-being. We summarize the advantages and disadvantages of using consumption as opposed to income for measuring trends in economic well-being. We critically evaluate the available evidence on these trends, and in particular discuss how the literature has evolved in its assessment of whether consumption inequality has grown as much as or less than income inequality. We provide some novel evidence on three relatively unexplored themes: inequality in different spending components, inequality in leisure time, and intergenerational consumption mobility.
DOI: 10.6084/m9.figshare.16822261
title: Barnes et al. 2021 Burn Trial Data

description: Data associated with published research examining litter flammability of tall grass prairie and sericea lespedeza litter (a non-native plant species)
DOI: 10.6084/m9.figshare.16822261.v1
title: Barnes et al. 2021 Burn Trial Data.xlsx

description: Data associated with published research examining litter flammability of tall grass prairie and sericea lespedeza litter (a non-native plant species)
DOI: 10.14272/iowubgjsywbqtk-spfgksoksa-n.1
title: C32H46CuF6N6P
title: InChI=1S/C30H43N5.C2H3N.Cu.F6P/c1-19-12-14-23(29(3,4)5)26-21(19)17-34(32-26)28(25-11-9-10-16-31-25)35-18-22-20(2)13-15-24(27(22)33-35)30(6,7)8;1-2-3;;1-7(2,3,4,5)6/h9-11,16-20,23-24,28H,12-15H2,1-8H3;1H3;;/q;;+1;-1/t19-,20-,23-,24-;;;/m1.../s1

description: This dataset contains experimental data from a sample (InChI=1S/C30H43N5.C2H3N.Cu.F6P/c1-19-12-14-23(29(3,4)5)26-21(19)17-34(32-26)28(25-11-9-10-16-31-25)35-18-22-20(2)13-15-24(27(22)33-35)30(6,7)8;1-2-3;;1-7(2,3,4,5)6/h9-11,16-20,23-24,28H,12-15H2,1-8H3;1H3;;/q;;+1;-1/t19-,20-,23-,24-;;;/m1.../s1). The datasets from the following experiments are available: 1H nuclear magnetic resonance spectroscopy (1H NMR) 13C nuclear magnetic resonance spectroscopy (13C NMR) 19F nuclear magnetic resonance spectroscopy (19F NMR) proton-decoupled 31P nuclear magnetic resonance spectroscopy (31P{1H}-NMR)
DOI: 10.14272/iowubgjsywbqtk-spfgksoksa-n/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) ()
title: InChI=1S/C30H43N5.C2H3N.Cu.F6P/c1-19-12-14-23(29(3,4)5)26-21(19)17-34(32-26)28(25-11-9-10-16-31-25)35-18-22-20(2)13-15-24(27(22)33-35)30(6,7)8;1-2-3;;1-7(2,3,4,5)6/h9-11,16-20,23-24,28H,12-15H2,1-8H3;1H3;;/q;;+1;-1/t19-,20-,23-,24-;;;/m1.../s1

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C NMR (100 MHz, CD2Cl2, ppm) δ = 154.6 (C-5), 153.5 (2C, C-8), 152.6 (C-17), 149.3 (C-1), 139.9 (C-3), 128.5 (d, 2C, C-7), 126.9 (d, 2C, C-9), 125.8 (C-2), 125.4 (C-4), 73.0 (d, C-6), 43.1 (d, 2C, C-13), 36.3 (d, 2C, C-15), 32.9 (d, 2C, C-11), 28.6 (d, 6C, C-16), 27.9 (d, 2C, C-10), 25.0 (d, 2C, C-12), 21.3 (d, 2C, C-14), 3.4 (C-18).
DOI: 10.14272/iowubgjsywbqtk-spfgksoksa-n/chmo0000889
title: proton-decoupled 31P nuclear magnetic resonance spectroscopy (31P{1H}-NMR) ()
title: InChI=1S/C30H43N5.C2H3N.Cu.F6P/c1-19-12-14-23(29(3,4)5)26-21(19)17-34(32-26)28(25-11-9-10-16-31-25)35-18-22-20(2)13-15-24(27(22)33-35)30(6,7)8;1-2-3;;1-7(2,3,4,5)6/h9-11,16-20,23-24,28H,12-15H2,1-8H3;1H3;;/q;;+1;-1/t19-,20-,23-,24-;;;/m1.../s1

description: dataset for proton-decoupled 31P nuclear magnetic resonance spectroscopy (31P{1H}-NMR) 31P {1H} NMR (162 MHz, CD2Cl2): δ = 144.1 (sept, J = 715 Hz) ppm.
DOI: 10.14272/iowubgjsywbqtk-spfgksoksa-n/chmo0000597
title: 19F nuclear magnetic resonance spectroscopy (19F NMR) ()
title: InChI=1S/C30H43N5.C2H3N.Cu.F6P/c1-19-12-14-23(29(3,4)5)26-21(19)17-34(32-26)28(25-11-9-10-16-31-25)35-18-22-20(2)13-15-24(27(22)33-35)30(6,7)8;1-2-3;;1-7(2,3,4,5)6/h9-11,16-20,23-24,28H,12-15H2,1-8H3;1H3;;/q;;+1;-1/t19-,20-,23-,24-;;;/m1.../s1

description: dataset for 19F nuclear magnetic resonance spectroscopy (19F NMR) 19F {1H} NMR ( 377 MHz, CD2Cl2): δ = -73.1 (d, J = 711 Hz) ppm.
DOI: 10.14272/iowubgjsywbqtk-spfgksoksa-n/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) ()
title: InChI=1S/C30H43N5.C2H3N.Cu.F6P/c1-19-12-14-23(29(3,4)5)26-21(19)17-34(32-26)28(25-11-9-10-16-31-25)35-18-22-20(2)13-15-24(27(22)33-35)30(6,7)8;1-2-3;;1-7(2,3,4,5)6/h9-11,16-20,23-24,28H,12-15H2,1-8H3;1H3;;/q;;+1;-1/t19-,20-,23-,24-;;;/m1.../s1

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (400 MHz, CD2Cl2, ppm) δ = 8.56 (d, 3J = 4.8 Hz, 1H, H-1), 7.94 (m, 2H, H-3, H-4), 7.61 (d, 3J = 6.8 Hz, 2H, H-7), 7.49 (m, 2H, H-2, H-6), 2.66 (t, 3J = 8.0 Hz, 2H, H-13), 2.50 (m, 2H, H-10), 2.34 (s, 3H, H-18), 1.90 (m, 2H, H-12), 1.84 (m, 2H, H-11), 1.67 (m, 2H, H-12), 1.08 (2xs, 6H, H-14), 0.96 (m, 2H, H-11), 0.82 (2xs, 18H, H-16).
DOI: 10.14272/nwktucndipmmkm-tzyajkajsa-n.1
title: C30H43N5
title: InChI=1S/C30H43N5/c1-19-12-14-23(29(3,4)5)26-21(19)17-34(32-26)28(25-11-9-10-16-31-25)35-18-22-20(2)13-15-24(27(22)33-35)30(6,7)8/h9-11,16-20,23-24,28H,12-15H2,1-8H3/t19-,20-,23-,24-/m0/s1

description: This dataset contains experimental data from a sample (InChI=1S/C30H43N5/c1-19-12-14-23(29(3,4)5)26-21(19)17-34(32-26)28(25-11-9-10-16-31-25)35-18-22-20(2)13-15-24(27(22)33-35)30(6,7)8/h9-11,16-20,23-24,28H,12-15H2,1-8H3/t19-,20-,23-,24-/m0/s1). The datasets from the following experiments are available: 1H nuclear magnetic resonance spectroscopy (1H NMR) 13C nuclear magnetic resonance spectroscopy (13C NMR)
DOI: 10.14272/nwktucndipmmkm-tzyajkajsa-n/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) ()
title: InChI=1S/C30H43N5/c1-19-12-14-23(29(3,4)5)26-21(19)17-34(32-26)28(25-11-9-10-16-31-25)35-18-22-20(2)13-15-24(27(22)33-35)30(6,7)8/h9-11,16-20,23-24,28H,12-15H2,1-8H3/t19-,20-,23-,24-/m0/s1

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C NMR (100 MHz, CD2Cl2, ppm) δ = 157.0 (C-5), 152.7 (d, 2C, C-8), 149.9 (C-1), 137.3 (C-3), 126.0 (d, 2C, C-9), 125.9 (d, 2C, C-7), 124.0 (C-2), 122.6 (C-4), 79.4 (C-6), 45.5 (d, 2C, C-12), 34.6 (d, 2C, C-15), 33.9 (d, 2C, C-11), 29.0 (2C, C-10), 28.3 (6C, C-16), 26.8 (d, 2C, C-13), 21.7 (d, 2C, C-14).
DOI: 10.14272/nwktucndipmmkm-tzyajkajsa-n/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) ()
title: InChI=1S/C30H43N5/c1-19-12-14-23(29(3,4)5)26-21(19)17-34(32-26)28(25-11-9-10-16-31-25)35-18-22-20(2)13-15-24(27(22)33-35)30(6,7)8/h9-11,16-20,23-24,28H,12-15H2,1-8H3/t19-,20-,23-,24-/m0/s1

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (400 MHz, CD2Cl2, ppm) δ = 8.58 (qd, 3J = 4.8 Hz, 4J = 0.8 Hz, 1H, H-1), 7.70 (dt, 3J = 8.0 Hz, 4J = 1.6 Hz, 1H, H-3), 7.45 (s, 1H, H-6), 7.27 (m, 3H, H-2, H-7), 6.99 (d, 3J = 7.6 Hz, 1H, H-4), 2.54 (m, 4H, H-10, H-13), 2.01 (m, 2H, H-12), 1.89 (m, 2H, H-11), 1.42 (m, 2H, H-12), 1.22 (m, 2H-11), 1.12 (2xd, 3J = 6.4 Hz, 6H, H-14), 0.99 (2xs, 18H, H-16).
DOI: 10.6084/m9.figshare.16778803
title: raw data.xls

description: To obtain a representative sample of college students in Jiangsu province, this cross-sectional survey adopted multi-stage cluster sampling method, and four universities located in four cities in Jiangsu province are purposefully selected. Each selected university was stratified by specialties (literature and history, science and engineering, medicine, and other specialties), and one class within the specialty was subsequently sampled as a unit, proportional to the number of students in different grades (from freshman to senior) in the whole sample. Each student was invited to complete a series of questionnaires that measures parent-child attachment, school bonding, and social adaptation status. 1,440 students were invited to participate in the study, and a total of 1,320 agreed to participate, representing a response rate of 91.7%. The studies involving human participants were reviewed and approved by Ethics Committee of Kangda College of Nanjing Medical University. The patients/participants all provided their written informed consent to participate in this study.
DOI: 10.6084/m9.figshare.16778803.v1
title: raw data.xls

description: To obtain a representative sample of college students in Jiangsu province, this cross-sectional survey adopted multi-stage cluster sampling method, and four universities located in four cities in Jiangsu province are purposefully selected. Each selected university was stratified by specialties (literature and history, science and engineering, medicine, and other specialties), and one class within the specialty was subsequently sampled as a unit, proportional to the number of students in different grades (from freshman to senior) in the whole sample. Each student was invited to complete a series of questionnaires that measures parent-child attachment, school bonding, and social adaptation status. 1,440 students were invited to participate in the study, and a total of 1,320 agreed to participate, representing a response rate of 91.7%. The studies involving human participants were reviewed and approved by Ethics Committee of Kangda College of Nanjing Medical University. The patients/participants all provided their written informed consent to participate in this study.
DOI: 10.14272/uqzcbwvoivxjni-uhfffaoysa-n.1
title: C24H32CuF6N6O2P
title: InChI=1S/C22H29N5O2.C2H3N.Cu.F6P/c1-21(2,3)17-11-13-26(24-17)19(27-14-12-18(25-27)22(4,5)6)15-9-8-10-16(23-15)20(28)29-7;1-2-3;;1-7(2,3,4,5)6/h8-14,19H,1-7H3;1H3;;/q;;+1;-1

description: This dataset contains experimental data from a sample (InChI=1S/C22H29N5O2.C2H3N.Cu.F6P/c1-21(2,3)17-11-13-26(24-17)19(27-14-12-18(25-27)22(4,5)6)15-9-8-10-16(23-15)20(28)29-7;1-2-3;;1-7(2,3,4,5)6/h8-14,19H,1-7H3;1H3;;/q;;+1;-1). The datasets from the following experiments are available: 1H nuclear magnetic resonance spectroscopy (1H NMR) 13C nuclear magnetic resonance spectroscopy (13C NMR) 19F nuclear magnetic resonance spectroscopy (19F NMR) proton-decoupled 31P nuclear magnetic resonance spectroscopy (31P{1H}-NMR)
DOI: 10.14272/uqzcbwvoivxjni-uhfffaoysa-n/chmo0000889
title: proton-decoupled 31P nuclear magnetic resonance spectroscopy (31P{1H}-NMR) ()
title: InChI=1S/C22H29N5O2.C2H3N.Cu.F6P/c1-21(2,3)17-11-13-26(24-17)19(27-14-12-18(25-27)22(4,5)6)15-9-8-10-16(23-15)20(28)29-7;1-2-3;;1-7(2,3,4,5)6/h8-14,19H,1-7H3;1H3;;/q;;+1;-1

description: dataset for proton-decoupled 31P nuclear magnetic resonance spectroscopy (31P{1H}-NMR) 31P {1H} NMR (162 MHz, CD2Cl2): δ = -144.2 (sept, J = 711.2 Hz) ppm.
DOI: 10.14272/uqzcbwvoivxjni-uhfffaoysa-n/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) ()
title: InChI=1S/C22H29N5O2.C2H3N.Cu.F6P/c1-21(2,3)17-11-13-26(24-17)19(27-14-12-18(25-27)22(4,5)6)15-9-8-10-16(23-15)20(28)29-7;1-2-3;;1-7(2,3,4,5)6/h8-14,19H,1-7H3;1H3;;/q;;+1;-1

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C NMR (100 MHz, CD2Cl2, ppm) δ = 165.5 (C-10), 165.2 (C-9, 2C), 153.4 (C-5), 147.9 (C-3), 141.4 (C-1), 133.5 (C-7, 2C), 128.8 (C-2), 127.0 (C-4), 117.1 (C-14), 104.6 (C-8, 2C), 73.2 (C-6), 54.2 (C-11), 32.7 (C-12, 2C), 30.5 (C-13, 6C), 3.1 (C-15).
DOI: 10.14272/uqzcbwvoivxjni-uhfffaoysa-n/chmo0000597
title: 19F nuclear magnetic resonance spectroscopy (19F NMR) ()
title: InChI=1S/C22H29N5O2.C2H3N.Cu.F6P/c1-21(2,3)17-11-13-26(24-17)19(27-14-12-18(25-27)22(4,5)6)15-9-8-10-16(23-15)20(28)29-7;1-2-3;;1-7(2,3,4,5)6/h8-14,19H,1-7H3;1H3;;/q;;+1;-1

description: dataset for 19F nuclear magnetic resonance spectroscopy (19F NMR) 19F {1H} NMR (377 MHz, CD2Cl2): δ = -71.9 (d, J = 711.0 Hz) ppm.
DOI: 10.14272/uqzcbwvoivxjni-uhfffaoysa-n/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) ()
title: InChI=1S/C22H29N5O2.C2H3N.Cu.F6P/c1-21(2,3)17-11-13-26(24-17)19(27-14-12-18(25-27)22(4,5)6)15-9-8-10-16(23-15)20(28)29-7;1-2-3;;1-7(2,3,4,5)6/h8-14,19H,1-7H3;1H3;;/q;;+1;-1

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (400 MHz, CD2Cl2, ppm) δ = 8.16 (m, 2H, H-3, H-4), 8.01 (d, 3J = 2.6 Hz, 2H, H-7), 7.91 (d, 3J = 7.3 Hz, 1H, H-2), 7.85 (s, 1H, H-6), 6.27 (d, 3J = 2.6 Hz, 2H, H-8), 4.03 (s, 3H, H-11), 2.31 (s, 3H, H-15), 1.39 (s, 18H, H-13).
DOI: 10.14272/fhxonrjrowmhdx-qujlyijbsa-n.1
title: C56H70Cu2F12N10P2
title: InChI=1S/2C28H35N5.2Cu.2F6P/c2*1-25(2)19-10-12-27(25,5)22-17(19)15-32(30-22)24(21-9-7-8-14-29-21)33-16-18-20-11-13-28(6,23(18)31-33)26(20,3)4;;;2*1-7(2,3,4,5)6/h2*7-9,14-16,19-20,24H,10-13H2,1-6H3;;;;/q;;2*+1;2*-1/t2*19-,20-,27+,28+;;;;/m11..../s1

description: This dataset contains experimental data from a sample (InChI=1S/2C28H35N5.2Cu.2F6P/c2*1-25(2)19-10-12-27(25,5)22-17(19)15-32(30-22)24(21-9-7-8-14-29-21)33-16-18-20-11-13-28(6,23(18)31-33)26(20,3)4;;;2*1-7(2,3,4,5)6/h2*7-9,14-16,19-20,24H,10-13H2,1-6H3;;;;/q;;2*+1;2*-1/t2*19-,20-,27+,28+;;;;/m11..../s1). The datasets from the following experiments are available: 1H nuclear magnetic resonance spectroscopy (1H NMR) 13C nuclear magnetic resonance spectroscopy (13C NMR) 19F nuclear magnetic resonance spectroscopy (19F NMR) proton-decoupled 31P nuclear magnetic resonance spectroscopy (31P{1H}-NMR)
DOI: 10.14272/fhxonrjrowmhdx-qujlyijbsa-n/chmo0000597
title: 19F nuclear magnetic resonance spectroscopy (19F NMR) ()
title: InChI=1S/2C28H35N5.2Cu.2F6P/c2*1-25(2)19-10-12-27(25,5)22-17(19)15-32(30-22)24(21-9-7-8-14-29-21)33-16-18-20-11-13-28(6,23(18)31-33)26(20,3)4;;;2*1-7(2,3,4,5)6/h2*7-9,14-16,19-20,24H,10-13H2,1-6H3;;;;/q;;2*+1;2*-1/t2*19-,20-,27+,28+;;;;/m11..../s1

description: dataset for 19F nuclear magnetic resonance spectroscopy (19F NMR) 19F {1H} NMR (377 MHz, CD2Cl2): δ = -71.3 (d, J = 711 Hz) ppm.
DOI: 10.14272/fhxonrjrowmhdx-qujlyijbsa-n/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) ()
title: InChI=1S/2C28H35N5.2Cu.2F6P/c2*1-25(2)19-10-12-27(25,5)22-17(19)15-32(30-22)24(21-9-7-8-14-29-21)33-16-18-20-11-13-28(6,23(18)31-33)26(20,3)4;;;2*1-7(2,3,4,5)6/h2*7-9,14-16,19-20,24H,10-13H2,1-6H3;;;;/q;;2*+1;2*-1/t2*19-,20-,27+,28+;;;;/m11..../s1

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C NMR (100 MHz, CD2Cl2, ppm) δ = 171.3 (2C, C-9), 170.2 (2C, C-9), 151.4 (2C, C-5), 150.6 (2C, C-4), 142.0 (2C, C-2), 129.8 (d, 4C, C-8), 129.1 (2C, C-1), 128.1 (d, 4C, C-7), 126.9 (2C, C-3), 73.0 (2C, C-6), 62.7 (2C, C-14), 61.4 (2C, C-14), 51.9 (d, 4C, C-13), 47.6 (d, 4C, C-10), 34.0 (d, 4C, C-12), 27.3 (d, 4C, C-11), 20.9 (d, 4C, C-16/17), 18.9 (d, 4C, C-16/17), 10.9 (d, 4C, C-15).
DOI: 10.14272/fhxonrjrowmhdx-qujlyijbsa-n/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) ()
title: InChI=1S/2C28H35N5.2Cu.2F6P/c2*1-25(2)19-10-12-27(25,5)22-17(19)15-32(30-22)24(21-9-7-8-14-29-21)33-16-18-20-11-13-28(6,23(18)31-33)26(20,3)4;;;2*1-7(2,3,4,5)6/h2*7-9,14-16,19-20,24H,10-13H2,1-6H3;;;;/q;;2*+1;2*-1/t2*19-,20-,27+,28+;;;;/m11..../s1

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (400 MHz, CD2Cl2, ppm) δ = 8.22 (d, 3J = 7.6 Hz, 2H, H-1), 8.14 (td, 3J = 8.1 Hz, 4J = 1.5 Hz, 2H, H-2), 8.07 (s, 2H, H-6), 8.01 (s, 2H, H-7), 7.95 (s, 2H, H-7), 7.65 (dd, 3J = 5.1 Hz, 4J = 1.5 Hz, 2H, H-4), 7.42 (t, 3J = 6.2 Hz, 2H, H-3), 2.92 (m, 4H, H-10), 2.09 (m, 4H, H-11), 1.73 (m, 4H, H-12), 1.20 (m, 4H, H-11), 1.03 (m, 4H, H-12), 0.87 (s, 6H, H-16/17), 0.85 (s, 6H, H-16/17), 0.62 (s, 6H, H-16/17), 0.55 (s, 6H, H-15), 0.53 (s, 6H, H-15), 0.50 (s, 6H, H-16/17).
DOI: 10.14272/fhxonrjrowmhdx-qujlyijbsa-n/chmo0000889
title: proton-decoupled 31P nuclear magnetic resonance spectroscopy (31P{1H}-NMR) ()
title: InChI=1S/2C28H35N5.2Cu.2F6P/c2*1-25(2)19-10-12-27(25,5)22-17(19)15-32(30-22)24(21-9-7-8-14-29-21)33-16-18-20-11-13-28(6,23(18)31-33)26(20,3)4;;;2*1-7(2,3,4,5)6/h2*7-9,14-16,19-20,24H,10-13H2,1-6H3;;;;/q;;2*+1;2*-1/t2*19-,20-,27+,28+;;;;/m11..../s1

description: dataset for proton-decoupled 31P nuclear magnetic resonance spectroscopy (31P{1H}-NMR) 31P {1H} NMR (162 MHz, CD2Cl2): δ = -143.9 (sept, J = 711 Hz) ppm.
DOI: 10.6084/m9.figshare.16822333
title: Fig 5

description: Mammalian sperm hyperactivation regulates navigation via physical boundaries and promotes pseudo-chemotaxis<br>
DOI: 10.6084/m9.figshare.16822333.v1
title: Fig 5

description: Mammalian sperm hyperactivation regulates navigation via physical boundaries and promotes pseudo-chemotaxis<br>
DOI: 10.6084/m9.figshare.16822330.v1
title: Fig 4

description: Mammalian sperm hyperactivation regulates navigation via physical boundaries and promotes pseudo-chemotaxis<br>
DOI: 10.6084/m9.figshare.16822330
title: Fig 4

description: Mammalian sperm hyperactivation regulates navigation via physical boundaries and promotes pseudo-chemotaxis<br>
DOI: 10.6084/m9.figshare.16822327
title: Fig 3

description: Mammalian sperm hyperactivation regulates navigation via physical boundaries and promotes pseudo-chemotaxis<br>
DOI: 10.6084/m9.figshare.16822327.v1
title: Fig 3

description: Mammalian sperm hyperactivation regulates navigation via physical boundaries and promotes pseudo-chemotaxis<br>
DOI: 10.6084/m9.figshare.16822321
title: Fig 2

description: Mammalian sperm hyperactivation regulates navigation via physical boundaries and promotes pseudo-chemotaxis<br>
DOI: 10.6084/m9.figshare.16822321.v1
title: Fig 2

description: Mammalian sperm hyperactivation regulates navigation via physical boundaries and promotes pseudo-chemotaxis<br>
DOI: 10.6084/m9.figshare.16822312.v1
title: Fig 1

description: Mammalian sperm hyperactivation regulates navigation via physical boundaries and promotes pseudo-chemotaxis<br>
DOI: 10.6084/m9.figshare.16822312
title: Fig 1

description: Mammalian sperm hyperactivation regulates navigation via physical boundaries and promotes pseudo-chemotaxis<br>
DOI: 10.5281/zenodo.5527877
title: Dataset: Environmental Impact on the Long-Term Connectivity and Link Quality of an Outdoor LoRa Network

description: This repository contains the long-term connectivity and link quality dataset collected on ChirpBox over 4 months (May -- September 2021) in the city of Shanghai, China. In addition to the dataset itself, we provide evaluation scripts for data analysis and visualization, in order to facilitate data exploration and re-use. To make it clear how to use the scripts, we provide a <em>Jupyter notebook -- </em> <strong>dataset.ipynb</strong> for dataset visualization. <strong>List of files:</strong> <em>dataset_03052021_15092021.csv</em> The dataset includes LoRa connectivity and link quality, as well as environmental information, collected from May 3 to September 15, 2021. <em>data_analysis.py</em> The script for dataset analysis and visualization. One can use the functions in this script to derive network-level statistics (e.g., in terms of average number of correctly-exchanged packets), link-level statistics (e.g., in terms of SNR, RSS, and PRR), and node-level statistics(e.g., in terms of number of neighbours and temperature evolution over time). <em>metadata_processing.py</em> The script for pre-processing metadata into CSV files. One can use the functions in this script to convert metadata for each measurement saved in TXT and JSON formats to CSV files that include attributes such as link quality, connectivity, and environmental information, an example of which is <strong>dataset_03052021_15092021.csv</strong>. <em>dataset.ipynb </em> The Jupiter notebook contains examples of visualization and metadata pre-processing of datasets with functions in <strong>data_analysis.py</strong> and <strong>metadata_processing.py</strong>. <em>topology_map.png</em> The node deployment map used to create topology figures. A usage example is <strong>Figure 1</strong> shown in the notebook <strong>dataset.ipynb</strong>. <em>dataset_metadata.zip</em> The dataset metadata is stored in TXT and JSON formats. Among them, link quality, connectivity and on-board sensor data are stored in TXT files and weather information are stored in JOSN files. <em>README.md</em> The README.md explains all the files in this repository and gives some examples of how to use the provided scripts to analyze the dataset.
DOI: 10.34740/kaggle/dsv/2712214
title: Food Calories DataBase in Portuguese
DOI: 10.5281/zenodo.5573997
title: 17 lines_CN_2019-2020

description: Ivan I. Motsnyi 17 lines_CN_2019-2020
DOI: 10.5281/zenodo.5573996
title: 17 lines_CN_2019-2020

description: Ivan I. Motsnyi 17 lines_CN_2019-2020
DOI: 10.5281/zenodo.5553309
title: Pollination success increases with plant diversity in high Andean communities

description: Pollinator-mediated plant-plant interactions have traditionally been viewed within the competition paradigm. However, facilitation via pollinator sharing might be the rule rather than the exception in harsh environments. Moreover, plant diversity could be playing a key role in fostering pollinator-mediated facilitation. We examined a total of 9,371 stigmas of 88 species from nine high-Andean communities in NW Patagonia, and we explored the prevalent sign of the relation between conspecific pollen receipt and heterospecific pollen diversity, and assessed whether the incidence of different outcomes varies with altitude and whether pollen receipt relates to plant diversity.
DOI: 10.5281/zenodo.5553308
title: Pollination success increases with plant diversity in high Andean communities

description: Pollinator-mediated plant-plant interactions have traditionally been viewed within the competition paradigm. However, facilitation via pollinator sharing might be the rule rather than the exception in harsh environments. Moreover, plant diversity could be playing a key role in fostering pollinator-mediated facilitation. We examined a total of 9,371 stigmas of 88 species from nine high-Andean communities in NW Patagonia, and we explored the prevalent sign of the relation between conspecific pollen receipt and heterospecific pollen diversity, and assessed whether the incidence of different outcomes varies with altitude and whether pollen receipt relates to plant diversity.
DOI: 10.5519/qd.zizbjojx
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (4922935 records)
DOI: 10.34740/kaggle/dsv/2712593
title: Food Calories DataBase in Portuguese
DOI: 10.25345/c5756p
title: MassIVE MSV000088237 - Integrated Proteomic and Metabolomic Analysis of MELAS Due to the Rare Mitochondrial Pathogenic Variant m.14453G&gt;A
title: To gain insights into the pathogenic signature of MELAS, we designed a comprehensive strategy by integrating mass spectrometry-based proteomics and metabolomics in the well-established ex-vivo cellular paradigm, patient-derived dermal fibroblasts, which harbor the ultra-rare MELAS pathogenic variant m.14453G&gt;A, affecting the mitochondrial-encoded subunit NADH dehydrogenase 6 of the OXPHOS Complex I. The mother of the patient, who have no mitochondrial disease, participated in this study as the healthy control. Global proteomics was achieved by data-dependent acquisition (DDA) and data-independent acquisitions (DIA). Comprehensive metabolite coverage was achieved from polar and nonpolar metabolites in both reverse phase and HILIC LC-MS/MS analyses.
DOI: 10.5517/ccdc.csd.cc247pvy
title: CCDC 1973610: Experimental Crystal Structure Determination

description: Related Article: Wenbo Liu, Na’na Li, Xia Zhang, Yu Zhao, Ziao Zong, Ruixue Wu, Jiaping Tong, Caifeng Bi, Feng Shao, Yuhua Fan|2021|Cryst.Growth Des.|21|5558|doi:10.1021/acs.cgd.1c00359