cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/425bgjyzfb.1
title: The effect of amount and frequency of water supply on development of rangeland seedlings grasses

description: The data was created to study the effects of amount and frequency of watering on seedlings of two rangeland grass species, kleingrass (Panicum coloratum) and blue grama (Bouteloua gracilis). The study was conducted under greenhouse conditions, simulating five-month precipitation regimes based on long-term precipitation average (LPA) in the arid portion of the southwestern High Plains of Texas, USA. The watering regimes were: 1) LPA, 2) dry (75% of the LPA), and 3) wet (average of ten years in the LPA with highest precipitation).
DOI: 10.5281/zenodo.3829150
title: Rapid hematoma growth triggers spreading depolarizations in experimental intracortical hemorrhage (1)

description: This dataset is related to "Rapid hematoma growth triggers spreading depolarizations in experimental intracortical hemorrhage" (Fischer P., Sugimoto K., Chung DY., Tamim I., Takizawa T., Qin T. et al.). Part 1 of 2
DOI: 10.5281/zenodo.3829149
title: Rapid hematoma growth triggers spreading depolarizations in experimental intracortical hemorrhage (1)

description: This dataset is related to "Rapid hematoma growth triggers spreading depolarizations in experimental intracortical hemorrhage" (Fischer P., Sugimoto K., Chung DY., Tamim I., Takizawa T., Qin T. et al.). Part 1 of 2
DOI: 10.5281/zenodo.3940932
title: Rapid hematoma growth triggers spreading depolarizations in experimental intracortical hemorrhage (2)

description: This dataset is related to "Rapid hematoma growth triggers spreading depolarizations in experimental intracortical hemorrhage" (Fischer P., Sugimoto K., Chung DY., Tamim I., Takizawa T., Qin T. et al.). Part 2 of 2
DOI: 10.5281/zenodo.3940931
title: Rapid hematoma growth triggers spreading depolarizations in experimental intracortical hemorrhage (2)

description: This dataset is related to "Rapid hematoma growth triggers spreading depolarizations in experimental intracortical hemorrhage" (Fischer P., Sugimoto K., Chung DY., Tamim I., Takizawa T., Qin T. et al.). Part 2 of 2
DOI: 10.21227/n520-aw71
title: Image Dataset of Aedes and Culex Mosquito Species

description: Mosquito bites result in the deaths of more than 1 million people every year. Certain species of mosquitos like Aedes are the main vector of arboviruses that cause Dengue, Malaria and Yellow fever. Image based mosquito species classification can be helpful to implement strategies to prevent the spread of mosquito borne disease. Automated mosquito species classification can aid in laborious and time consuming task of entomologists besides enhancing accuracy.
DOI: 10.5281/zenodo.3939182
title: Controlling inorganic symmetry using optical chirality (Data)

description: Data for paper entitled "Controlling inorganic symmetry using optical chirality". Numerical data for graphs shown in figures 2, 3 and 4.
DOI: 10.5281/zenodo.3939181
title: Controlling inorganic symmetry using optical chirality (Data)

description: Data for paper entitled "Controlling inorganic symmetry using optical chirality". Numerical data for graphs shown in figures 2, 3 and 4.
DOI: 10.5281/zenodo.3940992
title: supplementary material for Thapa et al. 2020

description: Supplementary material related to Thapa et al. 2020- publication by the Klutstein and Kravchenko-Balasha labs
DOI: 10.5281/zenodo.3940991
title: supplementary material for Thapa et al. 2020

description: Supplementary material related to Thapa et al. 2020- publication by the Klutstein and Kravchenko-Balasha labs
DOI: 10.21227/w2kz-wm82
title: Image Dataset of Aedes and Culex Mosquito Species

description: Mosquito bites result in the deaths of more than 1 million people every year. Certain species of mosquitos like Aedes are the main vector of arboviruses that cause Dengue, Malaria and Yellow fever. Image based mosquito species classification can be helpful to implement strategies to prevent the spread of mosquito borne disease. Automated mosquito species classification can aid in laborious and time consuming task of entomologists besides enhancing accuracy.
DOI: 10.21227/0hzr-c403
title: Image Dataset of Aedes and Culex Mosquito Species

description: Mosquito bites result in the deaths of more than 1 million people every year. Certain species of mosquitos like Aedes are the main vector of arboviruses that cause Dengue, Malaria and Yellow fever. Image based mosquito species classification can be helpful to implement strategies to prevent the spread of mosquito borne disease. Automated mosquito species classification can aid in laborious and time consuming task of entomologists besides enhancing accuracy.
DOI: 10.5281/zenodo.593967
title: 2014 global soil survey (GSS) report

description: The files in this repository generate the 2014 Global Soil Survey report and contain the soil test data for samples tested from September 2013 to 31 August 2014.
DOI: 10.3886/e117242
title: A General Approach to Detecting Migration Events in Digital Trace Data

description: Empirical research on migration has historically been fraught with measurement challenges. Recently, the increasing ubiquity of digital trace data — from mobile phones, social media, and related sources of ‘big data’ — has created new opportunities for the quantitative analysis of migration. However, most existing work relies on relatively ad hoc methods for inferring migration. Here, we develop and validate a novel and general approach to detecting migration events in trace data. We benchmark this method using two different trace datasets: four years of mobile phone metadata from a single country’s monopoly operator, and three years of geo-tagged Twitter data. The novel measures accurately reflect existing knowledge of migration in these contexts, and also provide more granular insight into migration spells and types than what are captured in standard survey instruments.
DOI: 10.21227/rd5s-gt46
title: Image Dataset of Aedes and Culex Mosquito Species

description: Mosquito bites result in the deaths of more than 1 million people every year. Certain species of mosquitos like Aedes are the main vector of arboviruses that cause Dengue, Malaria and Yellow fever. Image based mosquito species classification can be helpful to implement strategies to prevent the spread of mosquito borne disease. Automated mosquito species classification can aid in laborious and time consuming task of entomologists besides enhancing accuracy.
DOI: 10.21227/fgn0-5h18
title: Image Dataset of Aedes and Culex Mosquito Species

description: Mosquito bites result in the deaths of more than 1 million people every year. Certain species of mosquitos like Aedes are the main vector of arboviruses that cause Dengue, Malaria and Yellow fever. Image based mosquito species classification can be helpful to implement strategies to prevent the spread of mosquito borne disease. Automated mosquito species classification can aid in laborious and time consuming task of entomologists besides enhancing accuracy.
DOI: 10.7910/dvn/j7byrx/hmtikh
title: india-news-headlines.v3.tab

description: Column 1: publish_date (yyyyMMdd format) Column 2: headline_category (ascii, dot delimited, lowercase) Column 3: headline_text (english, rare non-ascii)
DOI: 10.7910/dvn/j7byrx/durqwx
title: india-news-headlines.v4.tab
DOI: 10.14272/wybximmfdvnqov-uhfffaoysa-n.1
title: methyl 4-[3-amino-4-(4-methoxycarbonylphenyl)phenyl]benzoate
title: InChI=1S/C22H19NO4/c1-26-21(24)16-7-3-14(4-8-16)18-11-12-19(20(23)13-18)15-5-9-17(10-6-15)22(25)27-2/h3-13H,23H2,1-2H3

description: This dataset contains experimental data from a sample (methyl 4-[3-amino-4-(4-methoxycarbonylphenyl)phenyl]benzoate, InChI=1S/C22H19NO4/c1-26-21(24)16-7-3-14(4-8-16)18-11-12-19(20(23)13-18)15-5-9-17(10-6-15)22(25)27-2/h3-13H,23H2,1-2H3). The datasets from the following experiments are available: 1H nuclear magnetic resonance spectroscopy (1H NMR) 13C nuclear magnetic resonance spectroscopy (13C NMR) mass spectrometry (MS) high-resolution mass spectrometry (HRMS) infrared absorption spectroscopy (IR)
DOI: 10.14272/wybximmfdvnqov-uhfffaoysa-n/chmo0000630
title: infrared absorption spectroscopy (IR) (methyl 4-[3-amino-4-(4-methoxycarbonylphenyl)phenyl]benzoate)
title: InChI=1S/C22H19NO4/c1-26-21(24)16-7-3-14(4-8-16)18-11-12-19(20(23)13-18)15-5-9-17(10-6-15)22(25)27-2/h3-13H,23H2,1-2H3

description: dataset for infrared absorption spectroscopy (IR) IR (ATR, ṽ) = 3454, 3373, 3033, 2997, 2948, 2890, 2847, 1703, 1639, 1605, 1578, 1567, 1551, 1527, 1490, 1455, 1435, 1398, 1333, 1312, 1292, 1278, 1231, 1197, 1184, 1159, 1112, 1103, 1017, 1001, 983, 966, 946, 902, 877, 861, 851, 829, 816, 766, 737, 707, 701, 639, 626, 578, 558, 516, 500, 482, 460, 425, 405, 384 cm–1.
DOI: 10.14272/wybximmfdvnqov-uhfffaoysa-n/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) (methyl 4-[3-amino-4-(4-methoxycarbonylphenyl)phenyl]benzoate)
title: InChI=1S/C22H19NO4/c1-26-21(24)16-7-3-14(4-8-16)18-11-12-19(20(23)13-18)15-5-9-17(10-6-15)22(25)27-2/h3-13H,23H2,1-2H3

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (500 MHz, DMSO-d6, ppm) δ = 8.05–8.04 (m, 2H, CH), 8.04–8.03 (m, 2H, CH), 7.78–7.76 (m, 2H, CH), 7.65–7.63 (m, 2H, CH), 7.17 (d, 1H, J = 8.1 Hz, CH), 7.16 (d, 1H, J = 1.8 Hz, CH), 7.02 (dd, 1H, J = 8.1 Hz, J = 1.8 Hz, CH), 5.13 (s, 2H, NH2), 3.88 (s, 6H, CO2CH3).
DOI: 10.14272/wybximmfdvnqov-uhfffaoysa-n/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) (methyl 4-[3-amino-4-(4-methoxycarbonylphenyl)phenyl]benzoate)
title: InChI=1S/C22H19NO4/c1-26-21(24)16-7-3-14(4-8-16)18-11-12-19(20(23)13-18)15-5-9-17(10-6-15)22(25)27-2/h3-13H,23H2,1-2H3

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C NMR (125 MHz, DMSO-d6, ppm) δ = 166.1 (CO2CH3), 166.0 (CO2CH3), 145.4 (Cq), 144.8 (Cq), 144.1 (Cq), 139.4 (Cq), 130.9 (CH), 129.8 (2C, CH), 129.6 (2C, CH), 128.9 (2C, CH), 128.4 (Cq), 127.9 (Cq), 126.6 (2C, CH), 124.7 (Cq), 115.7 (CH), 114.0 (CH), 52.1 (2C, CO2CH3).
DOI: 10.14272/wybximmfdvnqov-uhfffaoysa-n/chmo0000498
title: high-resolution mass spectrometry (HRMS) (methyl 4-[3-amino-4-(4-methoxycarbonylphenyl)phenyl]benzoate)
title: InChI=1S/C22H19NO4/c1-26-21(24)16-7-3-14(4-8-16)18-11-12-19(20(23)13-18)15-5-9-17(10-6-15)22(25)27-2/h3-13H,23H2,1-2H3

description: dataset for high-resolution mass spectrometry (HRMS) HRMS–EI (m/z): [M]+ calcd for C22H19NO4, 361.1314; found, 361.1316.
DOI: 10.14272/wybximmfdvnqov-uhfffaoysa-n/chmo0000470
title: mass spectrometry (MS) (methyl 4-[3-amino-4-(4-methoxycarbonylphenyl)phenyl]benzoate)
title: InChI=1S/C22H19NO4/c1-26-21(24)16-7-3-14(4-8-16)18-11-12-19(20(23)13-18)15-5-9-17(10-6-15)22(25)27-2/h3-13H,23H2,1-2H3

description: dataset for mass spectrometry (MS) FAB (m/z): 362 [M + H]+, 361 [M]+.
DOI: 10.14272/ionbhnfwefnuee-uhfffaoysa-n.1
title: 4-[3-amino-4-(4-carboxyphenyl)phenyl]benzoic acid
title: InChI=1S/C20H15NO4/c21-18-11-16(12-1-5-14(6-2-12)19(22)23)9-10-17(18)13-3-7-15(8-4-13)20(24)25/h1-11H,21H2,(H,22,23)(H,24,25)

description: This dataset contains experimental data from a sample (4-[3-amino-4-(4-carboxyphenyl)phenyl]benzoic acid, InChI=1S/C20H15NO4/c21-18-11-16(12-1-5-14(6-2-12)19(22)23)9-10-17(18)13-3-7-15(8-4-13)20(24)25/h1-11H,21H2,(H,22,23)(H,24,25)). The datasets from the following experiments are available: 1H nuclear magnetic resonance spectroscopy (1H NMR) 13C nuclear magnetic resonance spectroscopy (13C NMR) mass spectrometry (MS) high-resolution mass spectrometry (HRMS) infrared absorption spectroscopy (IR) mass spectrometry (MS)
DOI: 10.14272/ionbhnfwefnuee-uhfffaoysa-n/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) (4-[3-amino-4-(4-carboxyphenyl)phenyl]benzoic acid)
title: InChI=1S/C20H15NO4/c21-18-11-16(12-1-5-14(6-2-12)19(22)23)9-10-17(18)13-3-7-15(8-4-13)20(24)25/h1-11H,21H2,(H,22,23)(H,24,25)

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (500 MHz, DMSO-d6, ppm) δ = 8.08–8.06 (m, 2H, CH), 8.06–8.04 (m, 2H, CH), 7.81–7.79 (m, 2H, CH), 7.73–7.71 (m, 3H, CH), 7.61–7.59 (d, 2H, J = 8.0 Hz, CH), 7.46–7.45 (d, 2H, J = 8.0 Hz, CH). Missing signals (2H, CO2H).
DOI: 10.14272/ionbhnfwefnuee-uhfffaoysa-n/chmo0000470
title: mass spectrometry (MS) (4-[3-amino-4-(4-carboxyphenyl)phenyl]benzoic acid)
title: InChI=1S/C20H15NO4/c21-18-11-16(12-1-5-14(6-2-12)19(22)23)9-10-17(18)13-3-7-15(8-4-13)20(24)25/h1-11H,21H2,(H,22,23)(H,24,25)

description: dataset for mass spectrometry (MS) EI (m/z, 70 eV, 220 °C): 333 (5) [M]+, 98 (100).
DOI: 10.14272/ionbhnfwefnuee-uhfffaoysa-n/chmo0000630
title: infrared absorption spectroscopy (IR) (4-[3-amino-4-(4-carboxyphenyl)phenyl]benzoic acid)
title: InChI=1S/C20H15NO4/c21-18-11-16(12-1-5-14(6-2-12)19(22)23)9-10-17(18)13-3-7-15(8-4-13)20(24)25/h1-11H,21H2,(H,22,23)(H,24,25)

description: dataset for infrared absorption spectroscopy (IR) IR (ATR, ṽ) = 3031, 2944, 2883, 1686, 1606, 1584, 1572, 1545, 1517, 1487, 1428, 1405, 1383, 1313, 1296, 1230, 1181, 1115, 1102, 1081, 1016, 1006, 833, 812, 773, 728, 704, 698, 686, 645, 578, 557, 520, 507, 465, 443, 407 cm–1.
DOI: 10.14272/ionbhnfwefnuee-uhfffaoysa-n/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) (4-[3-amino-4-(4-carboxyphenyl)phenyl]benzoic acid)
title: InChI=1S/C20H15NO4/c21-18-11-16(12-1-5-14(6-2-12)19(22)23)9-10-17(18)13-3-7-15(8-4-13)20(24)25/h1-11H,21H2,(H,22,23)(H,24,25)

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C NMR (125 MHz, DMSO-d6, ppm) δ = 167.1 (CO2H), 167.0 (CO2H), 143.1 (Cq), 141.5 (Cq), 139.7 (2C, Cq), 135.5 (Cq), 131.7 (CH), 131.4 (Cq), 130.1 (2C, CH), 130.1 (Cq), 129.7 (2C, CH), 129.2 (2C, CH), 126.7 (2C, CH), 123.0 (CH), 119.7 (CH).
DOI: 10.14272/ionbhnfwefnuee-uhfffaoysa-n/chmo0000498
title: high-resolution mass spectrometry (HRMS) (4-[3-amino-4-(4-carboxyphenyl)phenyl]benzoic acid)
title: InChI=1S/C20H15NO4/c21-18-11-16(12-1-5-14(6-2-12)19(22)23)9-10-17(18)13-3-7-15(8-4-13)20(24)25/h1-11H,21H2,(H,22,23)(H,24,25)

description: dataset for high-resolution mass spectrometry (HRMS) HRMS–EI (m/z): [M]+ calcd for C20H15NO4, 333.1001; found, 333.1002.
DOI: 10.14272/ionbhnfwefnuee-uhfffaoysa-n/chmo0000470.1
title: mass spectrometry (MS) (4-[3-amino-4-(4-carboxyphenyl)phenyl]benzoic acid)
title: InChI=1S/C20H15NO4/c21-18-11-16(12-1-5-14(6-2-12)19(22)23)9-10-17(18)13-3-7-15(8-4-13)20(24)25/h1-11H,21H2,(H,22,23)(H,24,25)

description: dataset for mass spectrometry (MS) EI (m/z, 70 eV, 100 °C): 334 (9), 333 (43) [M]+, 294 (9), 293 (67), 292 (10), 291 (66), 242 (20), 225 (9), 214 (15), 213 (100).
DOI: 10.7910/dvn/zj2eex/hknc8m
title: Fig7.7z

description: :unav
DOI: 10.14272/uvybpuvkqlfzae-zzxkwvifsa-n.1
title: C5H9N3O2
title: InChI=1S/C5H9N3O2/c1-8(2)3-6-5(10)7-4-9/h3-4H,1-2H3,(H,7,9,10)/b6-3+

description: This dataset contains experimental data from a sample (InChI=1S/C5H9N3O2/c1-8(2)3-6-5(10)7-4-9/h3-4H,1-2H3,(H,7,9,10)/b6-3+). The datasets from the following experiments are available: 1H nuclear magnetic resonance spectroscopy (1H NMR) 13C nuclear magnetic resonance spectroscopy (13C NMR) mass spectrometry (MS) infrared absorption spectroscopy (IR)
DOI: 10.14272/uvybpuvkqlfzae-zzxkwvifsa-n/chmo0000470
title: mass spectrometry (MS) ()
title: InChI=1S/C5H9N3O2/c1-8(2)3-6-5(10)7-4-9/h3-4H,1-2H3,(H,7,9,10)/b6-3+

description: dataset for mass spectrometry (MS) FAB (m/z): 144 [M + H]+. EI (m/z, 70 eV, 70 °C): 143 (23) [M]+, 115 (91) [MH–CHO]+, 99 (100) [M–NHCHO]+.
DOI: 10.14272/uvybpuvkqlfzae-zzxkwvifsa-n/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) ()
title: InChI=1S/C5H9N3O2/c1-8(2)3-6-5(10)7-4-9/h3-4H,1-2H3,(H,7,9,10)/b6-3+

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C NMR (125 MHz, DMSO-d6, ppm) δ = 164.9 (CHO), 161.7 (NHCON), 161.4 (N=CH), 40.9 (NCH3), 34.9 (NCH3).
DOI: 10.14272/uvybpuvkqlfzae-zzxkwvifsa-n/chmo0000630
title: infrared absorption spectroscopy (IR) ()
title: InChI=1S/C5H9N3O2/c1-8(2)3-6-5(10)7-4-9/h3-4H,1-2H3,(H,7,9,10)/b6-3+

description: dataset for infrared absorption spectroscopy (IR) IR (ATR, ṽ) = 3388, 3228, 3146, 3084, 3063, 2966, 2931, 2914, 2874, 2815, 1714, 1652, 1598, 1570, 1487, 1453, 1431, 1419, 1358, 1339, 1255, 1225, 1203, 1108, 1060, 1043, 1013, 882, 786, 766, 633, 601, 528, 398 cm–1.
DOI: 10.14272/uvybpuvkqlfzae-zzxkwvifsa-n/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) ()
title: InChI=1S/C5H9N3O2/c1-8(2)3-6-5(10)7-4-9/h3-4H,1-2H3,(H,7,9,10)/b6-3+

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (500 MHz, DMSO-d6, ppm) δ = 10.21 (bs, 1H, CHO), 9.07 (bs, 1H, NH), 8.50 (s, 1H, N=CH), 3.15 (s, 3H, NCH3), 3.01 (s, 3H, NCH3).
DOI: 10.5519/qd.cfi7rmgn
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.18112/openneuro.ds003012.v1.0.0
title: action-in-auctions
DOI: 10.5281/zenodo.3940706
title: Multi-label Pathway Prediction based on Active Dataset Subsampling

description: We include samples of various data types used in the work "Multi-label Pathway Prediction based on Active Dataset Subsampling" (under-review) More information about the software package and instructions are provided in hallamlab/leADS
DOI: 10.21227/yec9-yy29
title: Thermal image dataset for person detection - UNIRI-TID

description: We build an original dataset of thermal videos and images that simulate illegal movements around the border and in protected areas and are designed for training machines and deep learning models. The videos are recorded in areas around the forest, at night, in different weather conditions – in the clear weather, in the rain, and in the fog, and with people in different body positions (upright, hunched) and movement speeds (regu- lar walking, running) at different ranges from the camera. In addition to using standard camera lenses, telephoto lenses were also used to test their impact on the quality of thermal images and person detection in different weather conditions and distance from the camera. The obtained dataset comprises 7412 manually labeled images extracted from video frames captured in the long-wave infrared (LWIR) a segment of the electromagnetic (EM) spectrum.
DOI: 10.21227/23f6-t211
title: Thermal image dataset for person detection - UNIRI-TID

description: We build an original dataset of thermal videos and images that simulate illegal movements around the border and in protected areas and are designed for training machines and deep learning models. The videos are recorded in areas around the forest, at night, in different weather conditions – in the clear weather, in the rain, and in the fog, and with people in different body positions (upright, hunched) and movement speeds (regu- lar walking, running) at different ranges from the camera. In addition to using standard camera lenses, telephoto lenses were also used to test their impact on the quality of thermal images and person detection in different weather conditions and distance from the camera. The obtained dataset comprises 7412 manually labeled images extracted from video frames captured in the long-wave infrared (LWIR) a segment of the electromagnetic (EM) spectrum.
DOI: 10.5281/zenodo.3941291
title: Squamous cell carcinoma of the lung: gene expression and network analysis during carcinogenesis (additional data)

description: Additional files regarding the results of the research.
DOI: 10.5281/zenodo.3941290
title: Squamous cell carcinoma of the lung: gene expression and network analysis during carcinogenesis (additional data)

description: Additional files regarding the results of the research.
DOI: 10.21227/nq4r-2c81
title: Thermal image dataset for person detection - UNIRI-TID

description: We build an original dataset of thermal videos and images that simulate illegal movements around the border and in protected areas and are designed for training machines and deep learning models. The videos are recorded in areas around the forest, at night, in different weather conditions – in the clear weather, in the rain, and in the fog, and with people in different body positions (upright, hunched) and movement speeds (regu- lar walking, running) at different ranges from the camera. In addition to using standard camera lenses, telephoto lenses were also used to test their impact on the quality of thermal images and person detection in different weather conditions and distance from the camera. The obtained dataset comprises 7412 manually labeled images extracted from video frames captured in the long-wave infrared (LWIR) a segment of the electromagnetic (EM) spectrum.
DOI: 10.5281/zenodo.3941297
title: Carbon stocks from rangeland riparian restoration, northern California

description: Data on carbon accumulation in soils and woody biomass as a result of rangeland riparian restoration in northern California. These data accompany a paper expected to appear in Carbon Balance and Management.
DOI: 10.5281/zenodo.3560993
title: Carbon stocks from rangeland riparian restoration, northern California

description: Data on carbon accumulation in soils and woody biomass as a result of rangeland riparian restoration in northern California. These data accompany a paper expected to appear in Carbon Balance and Management.
DOI: 10.21227/yyv1-fc43
title: Thermal image dataset for person detection - UNIRI-TID

description: We build an original dataset of thermal videos and images that simulate illegal movements around the border and in protected areas and are designed for training machines and deep learning models. The videos are recorded in areas around the forest, at night, in different weather conditions – in the clear weather, in the rain, and in the fog, and with people in different body positions (upright, hunched) and movement speeds (regu- lar walking, running) at different ranges from the camera. In addition to using standard camera lenses, telephoto lenses were also used to test their impact on the quality of thermal images and person detection in different weather conditions and distance from the camera. The obtained dataset comprises 7412 manually labeled images extracted from video frames captured in the long-wave infrared (LWIR) a segment of the electromagnetic (EM) spectrum.
DOI: 10.21227/er0j-3h84
title: Thermal image dataset for person detection - UNIRI-TID

description: We build an original dataset of thermal videos and images that simulate illegal movements around the border and in protected areas and are designed for training machines and deep learning models. The videos are recorded in areas around the forest, at night, in different weather conditions – in the clear weather, in the rain, and in the fog, and with people in different body positions (upright, hunched) and movement speeds (regu- lar walking, running) at different ranges from the camera. In addition to using standard camera lenses, telephoto lenses were also used to test their impact on the quality of thermal images and person detection in different weather conditions and distance from the camera. The obtained dataset comprises 7412 manually labeled images extracted from video frames captured in the long-wave infrared (LWIR) a segment of the electromagnetic (EM) spectrum.
DOI: 10.25919/5f0b975d30471
title: Parkes observations for project P1063 semester 2020APRS_10

description: We propose to use the Parkes UWL receiver for monitoring a small sub-set of the FAST-discovered pulsars, with special properties. The Parkes UWL system provides a unique capability for studying the pulsars over wide bandwidths. The observation proposed will provide significant insight into the special emission properties of these new discoveries and facilitate science.