cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21258/1540201
title: Inventaire forestier national suisse - Tableau no 893013
DOI: 10.21258/1579234
title: Inventario forestale nazionale svizzero - Tabella n. 891949
DOI: 10.5281/zenodo.4321706
title: Dataset for "Study on Reference Frames and Geographic Scale"

description: The analysis code was written in RStudio. The user data folder contains six .csv flies: Separate_pointing_errors.csv: participants' performance in the onsite pointing task Pre-Questionnaire.csv: participants' responses to the pre-questionnaire Post_Questionnaire.csv: participants' responses to the post-questionnaire Reference_frame_preference.csv: categorizing participants based on their reference frame proclivities LookingDirection_seperate.csv: participants' looking directions during maze learning Separate_time_data.csv: participants' time spent at each location in the virtual maze
DOI: 10.5281/zenodo.4321211
title: Dataset for "Study on Reference Frames and Geographic Scale"

description: The analysis code was written in RStudio. The user data folder contains six .csv flies: Separate_pointing_errors.csv: participants' performance in the onsite pointing task Pre-Questionnaire.csv: participants' responses to the pre-questionnaire Post_Questionnaire.csv: participants' responses to the post-questionnaire Reference_frame_preference.csv: categorizing participants based on their reference frame proclivities LookingDirection_seperate.csv: participants' looking directions during maze learning Separate_time_data.csv: participants' time spent at each location in the virtual maze
DOI: 10.21258/1593584
title: Inventario forestale nazionale svizzero - Tabella n. 892932
DOI: 10.21258/1530241
title: Inventaire forestier national suisse - Tableau no 899400
DOI: 10.21258/1602601
title: Inventario forestale nazionale svizzero - Tabella n. 897420
DOI: 10.21258/1533286
title: Inventaire forestier national suisse - Tableau no 899541
DOI: 10.21227/4nrv-dc38
title: Real-world falls in Multiple Sclerosis (MS)

description: Falls are a major health problem with one in three people over the age of 65 falling each year, oftentimes causing hip fractures, disability, reduced mobility, hospitalization and death. A major limitation in fall detection algorithm development is an absence of real-world falls data. Fall detection algorithms are typically trained on simulated fall data that contain a well-balanced number of examples of falls and activities of daily living. However, real-world falls occur infrequently, making them difficult to capture and causing severe data imbalance. People with multiple sclerosis (MS) fall frequently, and their risk of falling increases with disease progression. Because of their high fall incidence, people with MS provide an ideal model for studying falls. This paper describes the development of a context-aware fall detection system based on inertial sensors and time of flight sensors that is robust to imbalance, which is trained and evaluated on real-world falls in people with MS. The algorithm uses an auto-encoder that detects fall candidates using reconstruction error of accelerometer signals followed by a hyper-ensemble of balanced random forests trained using both acceleration and movement features. On a clinical dataset obtained from 25 people with MS monitored over eight weeks during free-living conditions, 54 falls were observed and our system achieved a sensitivity of 92.14%, and false-positive rate of 0.65 false alarms per day.
DOI: 10.25810/v575-3r57.24
title: Japanese Newspaper Coverage of Climate Change or Global Warming, 2000-2020 - October 2020

description: The Media and Climate Change Observatory Data monitors 120 sources (across newspapers, radio and TV) in 54 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://mecco.colorado.edu.
DOI: 10.21258/1567840
title: Inventaire forestier national suisse - Tableau no 898753
DOI: 10.25810/v575-3r57.25
title: Japanese Newspaper Coverage of Climate Change or Global Warming, 2000-2020 - November 2020

description: The Media and Climate Change Observatory Data monitors 120 sources (across newspapers, radio and TV) in 54 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://mecco.colorado.edu.
DOI: 10.21258/1529802
title: Inventaire forestier national suisse - Tableau no 897444
DOI: 10.21258/1574981
title: Inventaire forestier national suisse - Tableau no 898242
DOI: 10.21258/1621268
title: Inventario forestale nazionale svizzero - Tabella n. 896952
DOI: 10.21258/1600615
title: Inventario forestale nazionale svizzero - Tabella n. 899378
DOI: 10.21258/1600963
title: Inventario forestale nazionale svizzero - Tabella n. 899377
DOI: 10.21258/1557182
title: Inventaire forestier national suisse - Tableau no 897567
DOI: 10.21258/1618357
title: Inventario forestale nazionale svizzero - Tabella n. 897556
DOI: 10.21258/1554750
title: Inventaire forestier national suisse - Tableau no 902142
DOI: 10.21258/1616988
title: Inventario forestale nazionale svizzero - Tabella n. 898367
DOI: 10.21258/1552464
title: Inventaire forestier national suisse - Tableau no 897346
DOI: 10.21258/1622758
title: Inventario forestale nazionale svizzero - Tabella n. 898222
DOI: 10.21258/1599114
title: Inventario forestale nazionale svizzero - Tabella n. 897930
DOI: 10.21258/1571426
title: Inventaire forestier national suisse - Tableau no 891820
DOI: 10.21258/1566368
title: Inventaire forestier national suisse - Tableau no 897185
DOI: 10.21258/1573150
title: Inventaire forestier national suisse - Tableau no 891987
DOI: 10.21258/1621966
title: Inventario forestale nazionale svizzero - Tabella n. 899170
DOI: 10.21258/1537171
title: Inventaire forestier national suisse - Tableau no 899544
DOI: 10.21258/1540069
title: Inventaire forestier national suisse - Tableau no 899258
DOI: 10.21258/1560380
title: Inventaire forestier national suisse - Tableau no 899180
DOI: 10.21258/1559694
title: Inventaire forestier national suisse - Tableau no 899551
DOI: 10.21227/jar7-e493
title: A UAV aerial photograpy vehicle data set

description: This paper produces a data set containing 1127 images, using VOC12 format, the size of the image is 3840*2160, and the corresponding relation of file names
DOI: 10.21227/rxdm-mn49
title: A UAV aerial photograpy vehicle data set

description: This paper produces a data set containing 1127 images, using VOC12 format, the size of the image is 3840*2160, and the corresponding relation of file names
DOI: 10.21227/7rs5-s273
title: A UAV aerial photograpy vehicle data set

description: This paper produces a data set containing 1127 images, using VOC12 format, the size of the image is 3840*2160, and the corresponding relation of file names
DOI: 10.21227/cege-8462
title: Coronavirus (COVID-19) Geo-tagged Tweets Dataset

description: This dataset contains IDs and sentiment scores of the geo-tagged tweets related to the COVID-19 pandemic. The tweets are captured by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using 90+ different keywords and hashtags that are commonly used while referencing the pandemic. Complying with Twitter's content redistribution policy, only the tweet IDs are shared. You can re-construct the dataset by hydrating these IDs. The tweet IDs in this dataset belong to the tweets tweeted providing an exact location.The paper associated with this dataset is available here: Design and analysis of a large-scale COVID-19 tweets dataset-------------------------------------Related datasets: (a) Coronavirus (COVID-19) Tweets Sentiment Trend (Global)(b) Tweets Originating from India During COVID-19 Lockdowns-------------------------------------Below is the quick overview of this dataset.— Dataset name: GeoCOV19Tweets Dataset— Number of tweets : 280,491 tweets— Coverage : Global— Language : English (EN)— Dataset usage terms : By using this dataset, you agree to (i) use the content of this dataset and the data generated from the content of this dataset for non-commercial research only, (ii) remain in compliance with Twitter's Developer Policy and (iii) cite the following paper:Lamsal, R. Design and analysis of a large-scale COVID-19 tweets dataset. Applied Intelligence (2020). https://doi.org/10.1007/s10489-020-02029-z— Primary dataset : Coronavirus (COVID-19) Tweets Dataset (COV19Tweets Dataset)— Dataset updates : Everyday— Active keywords and hashtags: keywords.tsvPlease visit this page (primary dataset) for details regarding the collection date and time (and other notes) of each CSV file present in this dataset.
DOI: 10.21258/1562552
title: Inventaire forestier national suisse - Tableau no 898743
DOI: 10.21258/1590117
title: Inventario forestale nazionale svizzero - Tabella n. 898270
DOI: 10.21258/1531565
title: Inventaire forestier national suisse - Tableau no 899542
DOI: 10.21258/1562555
title: Inventaire forestier national suisse - Tableau no 899305
DOI: 10.21258/1557165
title: Inventaire forestier national suisse - Tableau no 897801
DOI: 10.21258/1591868
title: Inventario forestale nazionale svizzero - Tabella n. 902286
DOI: 10.21258/1616006
title: Inventario forestale nazionale svizzero - Tabella n. 898233
DOI: 10.21258/1608822
title: Inventario forestale nazionale svizzero - Tabella n. 899289
DOI: 10.21258/1621692
title: Inventario forestale nazionale svizzero - Tabella n. 891721
DOI: 10.21258/1596469
title: Inventario forestale nazionale svizzero - Tabella n. 898710
DOI: 10.21258/1584434
title: Inventario forestale nazionale svizzero - Tabella n. 898573
DOI: 10.21258/1536213
title: Inventaire forestier national suisse - Tableau no 897251
DOI: 10.21258/1611249
title: Inventario forestale nazionale svizzero - Tabella n. 899505
DOI: 10.21258/1583138
title: Inventario forestale nazionale svizzero - Tabella n. 891729
DOI: 10.21258/1594627
title: Inventario forestale nazionale svizzero - Tabella n. 898904
DOI: 10.21258/1548904
title: Inventaire forestier national suisse - Tableau no 891974
DOI: 10.21258/1605147
title: Inventario forestale nazionale svizzero - Tabella n. 898350
DOI: 10.21258/1582514
title: Inventario forestale nazionale svizzero - Tabella n. 899473
DOI: 10.21258/1588243
title: Inventario forestale nazionale svizzero - Tabella n. 898509
DOI: 10.21258/1532047
title: Inventaire forestier national suisse - Tableau no 891711
DOI: 10.21258/1570698
title: Inventaire forestier national suisse - Tableau no 898748
DOI: 10.21258/1615160
title: Inventario forestale nazionale svizzero - Tabella n. 891866
DOI: 10.21258/1605708
title: Inventario forestale nazionale svizzero - Tabella n. 899363
DOI: 10.21258/1561619
title: Inventaire forestier national suisse - Tableau no 898891
DOI: 10.21258/1538052
title: Inventaire forestier national suisse - Tableau no 893425
DOI: 10.21258/1619447
title: Inventario forestale nazionale svizzero - Tabella n. 897056
DOI: 10.21258/1594987
title: Inventario forestale nazionale svizzero - Tabella n. 899544
DOI: 10.21258/1590113
title: Inventario forestale nazionale svizzero - Tabella n. 899011
DOI: 10.21227/tf7f-2f23
title: Real-world falls in Multiple Sclerosis (MS)

description: Falls are a major health problem with one in three people over the age of 65 falling each year, oftentimes causing hip fractures, disability, reduced mobility, hospitalization and death. A major limitation in fall detection algorithm development is an absence of real-world falls data. Fall detection algorithms are typically trained on simulated fall data that contain a well-balanced number of examples of falls and activities of daily living. However, real-world falls occur infrequently, making them difficult to capture and causing severe data imbalance. People with multiple sclerosis (MS) fall frequently, and their risk of falling increases with disease progression. Because of their high fall incidence, people with MS provide an ideal model for studying falls. This paper describes the development of a context-aware fall detection system based on inertial sensors and time of flight sensors that is robust to imbalance, which is trained and evaluated on real-world falls in people with MS. The algorithm uses an auto-encoder that detects fall candidates using reconstruction error of accelerometer signals followed by a hyper-ensemble of balanced random forests trained using both acceleration and movement features. On a clinical dataset obtained from 25 people with MS monitored over eight weeks during free-living conditions, 54 falls were observed and our system achieved a sensitivity of 92.14%, and false-positive rate of 0.65 false alarms per day.
DOI: 10.21258/1594691
title: Inventario forestale nazionale svizzero - Tabella n. 892015
DOI: 10.21258/1536120
title: Inventaire forestier national suisse - Tableau no 898590
DOI: 10.21258/1575174
title: Inventaire forestier national suisse - Tableau no 896953
DOI: 10.21258/1551846
title: Inventaire forestier national suisse - Tableau no 899439
DOI: 10.21227/kt7c-pk83
title: A UAV aerial photograpy vehicle data set

description: This paper produces a data set containing 1127 images, using VOC12 format, the size of the image is 3840*2160, and the corresponding relation of file names
DOI: 10.21258/1536877
title: Inventaire forestier national suisse - Tableau no 897892
DOI: 10.34740/kaggle/dsv/1745229
title: World cities database
DOI: 10.21227/k85t-f991
title: A UAV aerial photograpy vehicle data set

description: This paper produces a data set containing 1127 images, using VOC12 format, the size of the image is 3840*2160, and the corresponding relation of file names
DOI: 10.21258/1561893
title: Inventaire forestier national suisse - Tableau no 898523
DOI: 10.21258/1600364
title: Inventario forestale nazionale svizzero - Tabella n. 891705
DOI: 10.21258/1532773
title: Inventaire forestier national suisse - Tableau no 897714
DOI: 10.21258/1612174
title: Inventario forestale nazionale svizzero - Tabella n. 902123
DOI: 10.21258/1596867
title: Inventario forestale nazionale svizzero - Tabella n. 892057
DOI: 10.21227/fekw-bd84
title: A UAV aerial photograpy vehicle data set

description: This paper produces a data set containing 1127 images, using VOC12 format, the size of the image is 3840*2160, and the corresponding relation of file names
DOI: 10.21258/1545509
title: Inventaire forestier national suisse - Tableau no 898783
DOI: 10.21258/1604665
title: Inventario forestale nazionale svizzero - Tabella n. 897871
DOI: 10.21258/1617466
title: Inventario forestale nazionale svizzero - Tabella n. 891847
DOI: 10.21258/1567900
title: Inventaire forestier national suisse - Tableau no 899310
DOI: 10.21258/1588691
title: Inventario forestale nazionale svizzero - Tabella n. 899156
DOI: 10.21258/1563778
title: Inventaire forestier national suisse - Tableau no 902279
DOI: 10.21258/1594077
title: Inventario forestale nazionale svizzero - Tabella n. 899536
DOI: 10.5281/zenodo.4322122
title: Using generalized regression neural network to retrieve bare surface soil moisture from Radarsat-2 backscatter observations, regard less of roughness effect

description: Description of soil moisture, correlation length, and RMS height from ground measurements of 147 sampling sites, full-polarized backscattering coefficients extracted from Radarsat-2 scene corresponding to those ground measurement sites.
DOI: 10.21258/1594249
title: Inventario forestale nazionale svizzero - Tabella n. 899381
DOI: 10.21258/1615757
title: Inventario forestale nazionale svizzero - Tabella n. 891975
DOI: 10.21258/1549022
title: Inventaire forestier national suisse - Tableau no 899605
DOI: 10.21258/1566292
title: Inventaire forestier national suisse - Tableau no 897365
DOI: 10.5281/zenodo.4322135
title: Using generalized regression neural network to retrieve bare surface soil moisture from Radarsat-2 backscatter observations, regard less of roughness effect

description: Description of soil moisture, correlation length, and RMS height from ground measurements of 147 sampling sites, full-polarized backscattering coefficients extracted from Radarsat-2 scene corresponding to those ground measurement sites.
DOI: 10.21258/1560579
title: Inventaire forestier national suisse - Tableau no 893460
DOI: 10.21258/1580172
title: Inventario forestale nazionale svizzero - Tabella n. 898375
DOI: 10.21258/1589958
title: Inventario forestale nazionale svizzero - Tabella n. 891939
DOI: 10.5281/zenodo.4322141
title: Using generalized regression neural network to retrieve bare surface soil moisture from Radarsat-2 backscatter observations, regard less of roughness effect

description: Description of soil moisture, correlation length, and RMS height from ground measurements of 147 sampling sites, full-polarized backscattering coefficients extracted from Radarsat-2 scene corresponding to those ground measurement sites.
DOI: 10.5281/zenodo.4322121
title: Using generalized regression neural network to retrieve bare surface soil moisture from Radarsat-2 backscatter observations, regard less of roughness effect

description: Description of soil moisture, correlation length, and RMS height from ground measurements of 147 sampling sites, full-polarized backscattering coefficients extracted from Radarsat-2 scene corresponding to those ground measurement sites.
DOI: 10.6084/m9.figshare.13378589.v1
title: COVID-19 Rumors.zip

description: A COVID-19 rumor dataset containing veracity labels, rumor sources, rumor popularity data, publication date, stance labels, and sentiment labels. Labeled and verified manually. Data are collected from both Twitter and news websites.
DOI: 10.21227/ge57-pr95
title: A UAV aerial photograpy vehicle data set

description: This paper produces a data set containing 1127 images, using VOC12 format, the size of the image is 3840*2160, and the corresponding relation of file names
DOI: 10.21258/1580568
title: Inventario forestale nazionale svizzero - Tabella n. 897504
DOI: 10.21258/1620860
title: Inventario forestale nazionale svizzero - Tabella n. 899517
DOI: 10.21258/1588828
title: Inventario forestale nazionale svizzero - Tabella n. 891745
DOI: 10.25345/c5d50z
title: MassIVE MSV000086597 - Proteogenomic insight into the basis of the insecticide tolerance/resistance of the pollen beetle
title: Biological samples of the pollen beetle were measured using nLC-MS/MS. Raw data from two experiments (A and B) are available. These experiments were performed to select novel markers for understanding resistance mechanisms with potential applicability in resistance targeting. The entire combined/txt folder from MaxQuant data processing and the protein database used for the search (45540seq_blast2go_fasta) is available for download. A) Thiacloprid and/or lambda-cyhalothrin-threatened pollen beetles 20171106_Erban_combined.txt Raw data legend: Sample No. 01-05: CON (control); Sample No. 06-10: CYH (cyhalothrin); Sample No. 11-15: THI (thiacloprid); Sample No. 16-20: C-T (cyhalothrin-thiacloprid) B) Deltamethrin-threatened pollen beetles 20150929_Erban_combined.txt Raw data legend (each sample has 3 analytical replicates): Sample No. Erban_KO1-3: cont (control-treated beetles); Sample No. Erban_BZ1-3: surv (survivors - resistant); Sample No. Erban_BM1-3: dead (dead - paralyzed) These raw LC-MS data were first used in DOI: 10.1016/j.jprot.2016.09.016.
DOI: 10.21258/1541584
title: Inventaire forestier national suisse - Tableau no 899100
DOI: 10.6084/m9.figshare.13378589.v2
title: COVID-19 Rumors.zip

description: A COVID-19 rumor dataset containing veracity labels, rumor sources, rumor popularity data, publication date, stance labels, and sentiment labels. Labeled and verified manually. Data are collected from both Twitter and news websites.
DOI: 10.21258/1589776
title: Inventario forestale nazionale svizzero - Tabella n. 899449
DOI: 10.21258/1619011
title: Inventario forestale nazionale svizzero - Tabella n. 897081
DOI: 10.21258/1607035
title: Inventario forestale nazionale svizzero - Tabella n. 902166
DOI: 10.21258/1601157
title: Inventario forestale nazionale svizzero - Tabella n. 902251
DOI: 10.21258/1586863
title: Inventario forestale nazionale svizzero - Tabella n. 899267
DOI: 10.21258/1623340
title: Inventario forestale nazionale svizzero - Tabella n. 898985
DOI: 10.6084/m9.figshare.13378628.v1
title: Non-ammocoete larvae of Palaeozoic stem lampreys

description: Included in this project: a) surface reconstruction of the oral apparatus of Pipiscius; b) dataset used for phylogenetic analysis.
DOI: 10.21258/1572863
title: Inventaire forestier national suisse - Tableau no 897790
DOI: 10.21258/1532675
title: Inventaire forestier national suisse - Tableau no 897162
DOI: 10.14457/cu.the.2019.8
title: Household pyrethroid insecticides exposure in relation to pyrethroid metabolite and GABA level effects of young children in urban area, Bangkok Thailand

description: Pyrethroids are commonly used in households and affect to nervous system in children. Data on pyrethroids exposure related to neurotransmitter gamma-aminobutyric acid (GABA) is unknown. This study investigated the relationship between 3-PBA metabolites and GABA concentrations, and also determined the factors influencing pyrethroids metabolites among young children in urban areas. A repeated cross-sectional design was designed to collect the information on PYR insecticide exposure between wet (November – December 2018) and dry (April – May 2019) seasons. To collect the data, urine samples were collected from children age 2–3 years(n = 80), and the questionnaires were used with parents. The study focused on children living in full time households where PYR insect products have been applied daily. Urine samples were analyzed for the 3-PBA metabolite using gas chromatography (GC/MS) and GABA concentrations using an enzyme-linked immunosorbent assay kit (ELISA). Spearman correlations was used to determine the relationship between 3-PBA metabolite and GABA concentrations in each season, and binary logistic regression was applied to determine an association between 3-BPA metabolite and the exposure variables in each season. Mann–Whitney U test was used to evaluate difference in continuous data between wet and dry seasons. Chi-square test was applied to present difference in categorical data between wet and dry seasons. The results revealed a negative association between an increase in 3-PBA metabolite concentrations and low GABA concentrations in urine in both seasons (rs = -0.230, p-value 0.004). This study also found the increase in 3-PBA metabolite was significantly associated with the increase in cypermethrin (rs = 0.226, p-value &lt; 0.05), and allethrin (rs = 0.274, p-value &lt; 0.05) in dry season, but not in wet season (rs = 0.160, p-value &gt; 0.05). Moreover, the association between exposure factors and 3-PBA metabolite concentrations were observed. seldom cleaned the floor was significantly associated with increased 3-PBA metabolite concentration in wet season (p-value = 0.038, OR = 0.089, 95%CI 0.009 – 0.870). In addition, genders and always walk bare feet inside household in a day were significantly associated with increased 3-PBA metabolite concentration in dry season (p-value = 0.041, OR = 0.333, 95%CI 0.116 – 0.956) and (p-value = 0.009, OR = 6.789, 95%CI 1.597 – 28.854), respectively. Hence, these factors could affect the levels of the neurotransmitter GABA in pyrethroids-exposed children. The study suggests that health education, raising awareness and strategies to reduce the risks from long-term PYR insecticide exposure of children living in households should be implemented.