cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7910/dvn/bf2vnk/u6eawr
title: PRP_across_02_spkrJS-metadata.xml

description: :unav
DOI: 10.7910/dvn/bf2vnk/48utxa
title: DGTS_191919191919_01_spkrTS-metadata.xml

description: :unav
DOI: 10.7910/dvn/bf2vnk/hn6udk
title: GRT_RESP-hello-how_are_you_inf_01_02_03_TS-metadata.xml

description: :unav
DOI: 10.7910/dvn/bf2vnk/i9bpqk
title: S_MTN-HM_1_pl_exl_are_going_home_01_02_03_TS-metadata.xml

description: :unav
DOI: 10.7910/dvn/bf2vnk/ijdc7w
title: N_saa_savi_01_spkrFS-metadata.xml

description: :unav
DOI: 10.7910/dvn/bf2vnk/kqkdp3
title: V_draw_02_spkrJS-metadata.xml

description: :unav
DOI: 10.7910/dvn/bf2vnk/livbvr
title: S_I_will_not_give_money_01_JS-metadata.xml

description: :unav
DOI: 10.7910/dvn/bf2vnk/prz3sn
title: S_boil_3pl_form_f_the_meat_01_02_TS-metadata.xml

description: :unav
DOI: 10.7910/dvn/bf2vnk/r6o0pf
title: WH_Q_who_01_spkrJS-metadata.xml

description: :unav
DOI: 10.7910/dvn/bf2vnk/w0eabb
title: CLR_white_02_spkrJS-metadata.xml

description: :unav
DOI: 10.7910/dvn/bf2vnk/2ukcpz
title: DEM-LOC_DIST_01_02_spkrJS-metadata.xml

description: :unav
DOI: 10.7910/dvn/bf2vnk/3p35il
title: S_MTN_walk_then_go_left_then_go_right_01_02_03_TS-metadata.xml

description: :unav
DOI: 10.7910/dvn/bf2vnk/izezyd
title: V_run_3rd_sg_inf_02_spkrJS-metadata.xml

description: :unav
DOI: 10.7910/dvn/bf2vnk/jq1cyj
title: CORP_butt_01_02_03_spkrTS-metadata.xml

description: :unav
DOI: 10.7910/dvn/bf2vnk/qn8bxd
title: S_cross-3sinf_the_river_tomorrow_01_02_03_TS-metadata.xml

description: :unav
DOI: 10.7910/dvn/bf2vnk/s89rgw
title: S_Q_who_read_a_book_02_spkrJS-metadata.xml

description: :unav
DOI: 10.7910/dvn/bf2vnk/t7jy3c
title: S_ARVL_approaching_fast_3s_inf_01_02_03_TS-metadata.xml

description: :unav
DOI: 10.7910/dvn/bf2vnk/wabvu8
title: QNTY_all_everything_01_02_03_spkrTS-metadata.xml

description: :unav
DOI: 10.7910/dvn/bf2vnk/xavv65
title: S_MTN_the_elders_come_here_03_04_TS-metadata.xml

description: :unav
DOI: 10.7910/dvn/bf2vnk/7pekik
title: P_new_heart_01_spkrTS-metadata.xml

description: :unav
DOI: 10.7910/dvn/bf2vnk/9hukkg
title: S_MTN_I_am_walking_through_the_forest_01_02_03_TS-metadata.xml

description: :unav
DOI: 10.7910/dvn/bf2vnk/dozpms
title: S_ATTRB_Pablo_and_Maria_are_teachers_01_TS-metadata.xml

description: :unav
DOI: 10.7910/dvn/bf2vnk/hlqi2h
title: S_jump_1st_sg_COMPL_on_the_bed_01_spkrTS-metadata.xml

description: :unav
DOI: 10.7910/dvn/bf2vnk/kvtwd8
title: S_QNTY_few_people_ate_01_02_03_TS-metadata.xml

description: :unav
DOI: 10.7910/dvn/bf2vnk/kzo8sk
title: N_booger_03_spkrJS-metadata.xml

description: :unav
DOI: 10.7910/dvn/bf2vnk/lfelza
title: ADJ_not-difficult_01_02_03_spkrTS-metadata.xml

description: :unav
DOI: 10.7910/dvn/bf2vnk/lxkmvn
title: CMND_come_DEIXS_LOC_1st_sg_01_02_03_spkrTS-metadata.xml

description: :unav
DOI: 10.7910/dvn/bf2vnk/yskvqr
title: N_skin_05_JS-metadata.xml

description: :unav
DOI: 10.7910/dvn/bf2vnk/6jxnwn
title: V_boil_01_02_JS-metadata.xml

description: :unav
DOI: 10.7910/dvn/bf2vnk/uh5cui
title: V_sleep_01_spkrJS-metadata.xml

description: :unav
DOI: 10.7910/dvn/va3n1l/8rigcs
title: replication1_extreme_pessimists.do

description: :unav
DOI: 10.7910/dvn/va3n1l/jz7rxt
title: replication2_figures_extreme_pessimists.R

description: :unav
DOI: 10.7910/dvn/va3n1l/mgqctm
title: data_extreme_pessimists.tab

description: :unav
DOI: 10.5281/zenodo.3558775
title: Adjustments in end-effector trajectory and underlying joint angle synergies after a target switch: Order of adjustment is flexible

description: These are the data files used to perform the analyses for the paper: 'Adjustments in end-effector trajectory and underlying joint angle synergies after a target switch: Order of adjustment is flexible'.
DOI: 10.5281/zenodo.3558776
title: Adjustments in end-effector trajectory and underlying joint angle synergies after a target switch: Order of adjustment is flexible

description: These are the data files used to perform the analyses for the paper: 'Adjustments in end-effector trajectory and underlying joint angle synergies after a target switch: Order of adjustment is flexible'.
DOI: 10.5281/zenodo.3558362
title: Sounds and the city – Acoustic detection of open windows inindoor environments

description: (1) Background: Situated in the domain of urban sound scene classification by humans and machines, the research in this project will be a first step towards mapping urban noise pollution experienced indoors and finding ways to reduce its negative impact in peoples' homes. The acoustic distinction between outdoor and indoor scenes is an active research field and can be automated with some success. A much subtler difference is the change in the indoor soundscape induced by an open window. Being able to determine this, however, would allow applications in warning systems and be a prerequisite for an app-based urban sound mapping project. Acoustic detection requires neither line of sight nor sensors at the window frame or knowledge of the number of windows or their size. The task, however, varies substantially in difficulty with the amount of sound inside and outside. From the point of machine classification the lack of specificity is the most problematic aspect: Very few sounds if any can be assumed to originate exclusively from outside <em>and</em> be present at all times to aid automatic detection. The required generalisation ability, however, can be assumed for humans, who might also use very subtle cues in the change of reverberations. (2) Aims The aims are (a) to determine the degree of reliability with which an open window can be recognised by humans and machines under varying circumstances based only on acoustic cues; (b) to investigate whether the findings for humans and machines can inform each other and can be used for further application-related research, e.g., window noise cancellation. (3) Method: (a) Dataset acquisition: A recording kit consisting of a dedicated laptop and microphone will be given to volunteers. Custom-programmed software will remind the user to specify the window state (establishing the so-called ground truth). (b) Perception experiments: Thirty participants will judge whether in the recorded clips a window is open or closed. After an extended familiarisation phase, they will proceed through two testing phases: In the first phase, all clips will originate from the recording locations with which the participants have already familiarised themselves, in the second they will judge clips from locations they haven't been exposed to before (partial data sets used for the familiar/unfamiliar conditions will be counterbalanced across participants). (c) Machine recognition: We will develop a machine learning system using state-of-the-art deep learning methods (artificial neural networks with multiple layers). To encourage other researchers to also take up this research, we will organise a machine learning challenge. In the challenge, a training data set including correct labels (ground truth) and a test set without the labels are provided. Researchers from academia and industry across the world will develop their own systems and send their classification results on the test set to the organisers to evaluate and publish online.
DOI: 10.7910/dvn/hbfu8f
title: Replication Data for: Do NBA Player (Regularized) Adjusted Plus Minus Measures Need Further Adjustment? Tests toward an Adjusted, Adjusted Plus Minus Measure

description: Adjusted plus minus (APM) measures have redefined our understanding of player value in basketball and hockey, where both are team games featuring player productivity spillovers (see, e.g., Horrace et al., 2016). APM measures use (substantial lineup variation in) seasonal play-by-play data to estimate individual player contributions. If a team's overall score margin success is figuratively represented by a pie, APM measures are well-designed to slice the pie and attribute individual contributions accordingly. However, they do not account for the possibility that better players can increase the overall size of the pie and thus increase the size of the slice (overall APM value) for teammates. Herein, we use NBA player-season Real Plus Minus (RPM) data for all recorded player-seasons from 2013-19 and player lineup data to test whether RPM is related to teammate quality. We run sets of linear, fixed effect regression models to explain variation in RPM across player-seasons. We find strong evidence that RPM is related to on-court teammate quality. We run the same analysis using a neural network approach. By comparing root mean squared errors for the fixed effects linear model and the neural network, we confirm that the latter approach is more suited for the present estimation.
DOI: 10.7910/dvn/hbfu8f/a7qyqs
title: NBALineupRPM.tab

description: :unav
DOI: 10.7910/dvn/hbfu8f/nqew6n
title: summaryStats.tab

description: :unav
DOI: 10.25345/c5zh4w
title: MassIVE MSV000084637 - Urbanization Project Run 2: Matses, Tunapuco, Guayabo, Tambo, Norman, Burkina Faso. C18 Pos
title: Second run of the urbanization project. Samples were from Matses, Tunapuco, Guayabo, and Tambo populations. Also includes Norman and BF populations.
DOI: 10.25345/c5tt20
title: MassIVE MSV000084638 - Obtusaquinone is a cysteine modifying compound that targets Keap1 for degradation
title: Bovine catalase: This is an experiment to use differential cysteine alkylation to map the nature of binding of a cysteine-targeting small molecule OBT (for details of the method, please see the Method Section of the manuscript). The alkylating reagents uses besides the studied drug were iodoacetamide (IAA) and N-ethylmaleimide (NEM). As described in the manuscript the experiment includes three routes of serial alkylation experiments termed OBT, IAA, and NEM. Samples were prepared in triplicate and TMT10-plex reagents were used for labeling as follows: OBT replicate 1 (OBT1), 129c; OBT2, 130n; OBT3, 130c; IAA1, 126; IAA2, 127n; IAA3, 127c; NEM1, 128n; NEM2, 128c; NEM3, 129n. An SPS-MS3 method was used for data acquisition on an Orbitrap Fusion Lumos mass spectrometer. The RAW file for these data is catalase_diffAlk.RAW. A differential alkylation experiment was also performed as described above for bovine catalase but using recombinant human KEAP1 as substrate. One set of experiments (OBT, IAA, NEM) was performed. TMT10-plex labeling was performed as follows: OBT, 129n; IAA, 128c; NEM, 128n. An SPS-MS3 method was used for data acquisition on an Orbitrap Fusion mass spectrometer. The RAW file for these data is RAW_file: keap1_diffAlk.RAW.
DOI: 10.5281/zenodo.3558787
title: Simulation data and software scripts used in calculus of ∆36 signature from EMAC clumped O2 isotope-inclusive model

description: This publication contains simulation data and software scripts for calculating quantities related to clumped oxygen isotope signature (∆<sub>36</sub>) derivation, as described in the "static" framework of Yeung‍ et‍ al. (2016), hereinafter "Y16") and subsequently used in Yeung‍ et‍ al.‍ (2019) analysis. We provide the output of the 1950–2011 transient simulation with EMAC model with explicit "dynamic" simulation of ∆<sub>36</sub> (i.e. <sup>18</sup>O<sup>18</sup>O isotopologues undergoing transport, mixing and O(<sup>3</sup>P)-mediated isotope equilibration) to demonstrate the importance of several assumptions/simplifications involved in the static calculus. Please refer to .README.pdf for details.
description: {"references": ["NOAA PMEL Ferret (https://ferretop.pmel.noaa.gov/Ferret/)", "Veusz (https://veusz.github.io)", "netCDF (https://www.unidata.ucar.edu/software/netcdf/)"]}
DOI: 10.21227/1yd5-rn96
title: WiFi RSSI Indoor Localization

description: A reliable and comprehensive public WiFi fingerprinting database for researchers to implement and compare the indoor localization’s methods.The database contains RSSI information from 6 APs conducted in different days with the support of autonomous robot.We use an autonomous robot to collect the WiFi fingerprint data. Our 3-wheel robot has multiple sensors including wheel odometer, an inertial measurement unit (IMU), a LIDAR, sonar sensors and a color and depth (RGB-D) camera. The robot can navigate to a target location to collect WiFi fingerprints automatically. The localization accuracy of the robot is 0.07 m ± 0.02 m. The dimension of the area is 21 m × 16 m. It has three long corridors. There are six APs and five of them provide two distinct MAC address for 2.4- and 5-GHz communications channels, respectively, except for one that only operates on 2.4-GHz frequency. There is one router can provide CSI information.
DOI: 10.21227/5wpg-qf41
title: WiFi RSSI Indoor Localization

description: A reliable and comprehensive public WiFi fingerprinting database for researchers to implement and compare the indoor localization’s methods.The database contains RSSI information from 6 APs conducted in different days with the support of autonomous robot.We use an autonomous robot to collect the WiFi fingerprint data. Our 3-wheel robot has multiple sensors including wheel odometer, an inertial measurement unit (IMU), a LIDAR, sonar sensors and a color and depth (RGB-D) camera. The robot can navigate to a target location to collect WiFi fingerprints automatically. The localization accuracy of the robot is 0.07 m ± 0.02 m. The dimension of the area is 21 m × 16 m. It has three long corridors. There are six APs and five of them provide two distinct MAC address for 2.4- and 5-GHz communications channels, respectively, except for one that only operates on 2.4-GHz frequency. There is one router can provide CSI information.
DOI: 10.21227/khws-4w04
title: WiFi RSSI Indoor Localization

description: A reliable and comprehensive public WiFi fingerprinting database for researchers to implement and compare the indoor localization’s methods.The database contains RSSI information from 6 APs conducted in different days with the support of autonomous robot.We use an autonomous robot to collect the WiFi fingerprint data. Our 3-wheel robot has multiple sensors including wheel odometer, an inertial measurement unit (IMU), a LIDAR, sonar sensors and a color and depth (RGB-D) camera. The robot can navigate to a target location to collect WiFi fingerprints automatically. The localization accuracy of the robot is 0.07 m ± 0.02 m. The dimension of the area is 21 m × 16 m. It has three long corridors. There are six APs and five of them provide two distinct MAC address for 2.4- and 5-GHz communications channels, respectively, except for one that only operates on 2.4-GHz frequency. There is one router can provide CSI information.
DOI: 10.17632/rg2f35w5sk.2
title: Data for: Weather index-based insurance as a meteorological risk management alternative in viticulture

description: These files contain the commands used for the design and valuation of the insurance progammes suggested in this article as well as an analysis of their hedging effectiveness.
DOI: 10.5281/zenodo.3558821
title: MoMA Collection - Automatic Monthly Update

description: Temporary Description
DOI: 10.5281/zenodo.3558822
title: MoMA Collection - Automatic Monthly Update

description: Temporary Description
DOI: 10.17632/rg2f35w5sk.3
title: Data for: Weather index-based insurance as a meteorological risk management alternative in viticulture

description: These files contain the commands used for the design and valuation of the insurance progammes suggested in this article as well as an analysis of their hedging effectiveness.
DOI: 10.14469/hpc/6370
title: (R )-1,2-dichloropropane conf 2 G=-1038.409198, optrot = 86.62

description: Gaussian Calculation
DOI: 10.14469/hpc/6371
title: (R )-1,2-dichloropropane conf 3 G=-1038.409328, optrot = -140.24

description: Gaussian Calculation
DOI: 10.14469/hpc/6372
title: (R)-1,2-dichloropropane conf 1 G=-1038.410918, optrot = 36.07

description: Gaussian Calculation
DOI: 10.14469/hpc/6373
title: (R,R)-2,3-epoxybutane

description: Gaussian Calculation
DOI: 10.14469/hpc/6374
title: 1,2-dichloropropane conf 3 G=-1038.409328

description: Gaussian Calculation
DOI: 10.14469/hpc/6375
title: 1,2-dichloropropane conf 2 G=-1038.409198

description: Gaussian Calculation
DOI: 10.14469/hpc/6376
title: 1,2-dichloropropane conf 1 G=-1038.410918

description: Gaussian Calculation
DOI: 10.5281/zenodo.3558849
title: BC430 Asteroid Ephemerides

description: We used the new observational error model to recalculate the orbits of the 300 large asteroids that appeared in the JPL DE405 planetary ephemeris due to their potential perturbations of the orbits of the major planets (Standish 1998). These newly recalculated epoch state vectors were then integrated over the timespan 1800–2200, with mutual perturbations modeled using the best available published and estimated masses of the 300 asteroids. The resulting BC430 asteroid ephemeris are presented here.
DOI: 10.5281/zenodo.3558850
title: BC430 Asteroid Ephemerides

description: We used the new observational error model to recalculate the orbits of the 300 large asteroids that appeared in the JPL DE405 planetary ephemeris due to their potential perturbations of the orbits of the major planets (Standish 1998). These newly recalculated epoch state vectors were then integrated over the timespan 1800–2200, with mutual perturbations modeled using the best available published and estimated masses of the 300 asteroids. The resulting BC430 asteroid ephemeris are presented here.
DOI: 10.17632/rg2f35w5sk.4
title: Data for: Weather index-based insurance as a meteorological risk management alternative in viticulture

description: These files contain the commands used for the design and valuation of the insurance progammes suggested in this article as well as an analysis of their hedging effectiveness.
DOI: 10.15161/oar.it/30590
title: CovidStat project data

description: This record contains the daily updated data of the CovidStat project. CovidStat is a project carried out by the CovidStat Working Group at INFN, whose creation was promoted within the Italian National Institute of Nuclear Physics with the aim of making a statistical analysis of the data provided daily by the Civil Protection on the spread of the pandemic in Italy. CovidStat data can interactively be browsed at https://covid19.infn.it.
description: The software to process this Root TTree is in the related identifier. Be sure to use the right corresponding version, based on the data in which Root TTree was generated.
DOI: 10.14469/hpc/6381
title: (s)-lactic acid 5

description: Gaussian Calculation
DOI: 10.25403/upresearchdata.12732215
title: Millennials National Parks

description: The overall purpose of the study was to determine the travel behaviour of the Millennial market, with specific reference to nature-based holiday destinations/experiences and more particularly SANParks as a nature-based holiday destination. <br>
DOI: 10.25403/upresearchdata.12732215.v1
title: Millennials National Parks

description: The overall purpose of the study was to determine the travel behaviour of the Millennial market, with specific reference to nature-based holiday destinations/experiences and more particularly SANParks as a nature-based holiday destination. <br>
DOI: 10.14469/hpc/6377
title: (S)-lactic acid 1

description: Gaussian Calculation
DOI: 10.14469/hpc/6378
title: (S)-lactic acid 2

description: Gaussian Calculation
DOI: 10.14469/hpc/6379
title: (S)-lactic acid 3

description: Gaussian Calculation
DOI: 10.14469/hpc/6380
title: (S)-lactic acid 4

description: Gaussian Calculation
DOI: 10.25345/c5kb3c
title: MassIVE MSV000085850 - Blood to plasma processing : temperature-time
title: This dataset evaluates effects on plasma proteome of processing delay (from blood draw to the first centrifugation: 0, 6, 24, 48 and 72 hours) and temperature (room temperature or 4C). Sample names indicate corresponding conditions - e.g. 48h_RT = 48 hours at room temperature.
DOI: 10.5281/zenodo.3966234
title: Data for "Tuning parameters of dimensionality reduction methods for single-cell RNA-seq analysis"

description: The files named <code>df_scran.csv</code>, <code>df_seurat.csv</code>, <code>df_zinbwave.csv</code>, <code>df_dca.csv</code>, and <code>df_scvi.csv</code> contain one row per configuration that we ran successfully. The files named <code>DATASET.METHOD.h5ad</code> are encoded with anndata <code>v0.7.0</code> (be careful as they are not readable with previous versions) and contain 100 embeddings each. The embeddings are in the <code>obsm</code> attribute of the object. All the embeddings can be listed with the <code>obsm_keys()</code> method. The name of the embedding contains the parameters used to generate that embedding and are written like that <code>method=zinbwave.dims=10.epsilon=1000.features=300.gene_covariate=0</code>. For questions on this dataset please contact fraimundo@google.com
DOI: 10.5281/zenodo.3966233
title: Data for "Tuning parameters of dimensionality reduction methods for single-cell RNA-seq analysis"

description: The files named <code>df_scran.csv</code>, <code>df_seurat.csv</code>, <code>df_zinbwave.csv</code>, <code>df_dca.csv</code>, and <code>df_scvi.csv</code> contain one row per configuration that we ran successfully. The files named <code>DATASET.METHOD.h5ad</code> are encoded with anndata <code>v0.7.0</code> (be careful as they are not readable with previous versions) and contain 100 embeddings each. The embeddings are in the <code>obsm</code> attribute of the object. All the embeddings can be listed with the <code>obsm_keys()</code> method. The name of the embedding contains the parameters used to generate that embedding and are written like that <code>method=zinbwave.dims=10.epsilon=1000.features=300.gene_covariate=0</code>. For questions on this dataset please contact fraimundo@google.com
DOI: 10.14469/hpc/6382
title: (S)-lactic acid 5, optrot -25.08

description: Gaussian Calculation
DOI: 10.14469/hpc/6383
title: (S)-lactic acid 4, optrot

description: Gaussian Calculation
DOI: 10.14469/hpc/6384
title: (S)-lactic acid 1, optrot 31.7

description: Gaussian Calculation
DOI: 10.14469/hpc/6385
title: (S)-lactic acid 2, optrot -36.69

description: Gaussian Calculation
DOI: 10.14469/hpc/6386
title: (S)-lactic acid 3, optrot 31.78

description: Gaussian Calculation
DOI: 10.7910/dvn/h8jwlb/2vcqbo
title: Social Compact Tracker_codebook.tab

description: :unav
DOI: 10.7910/dvn/h8jwlb/ivbxhw
title: Social Compact Tracker.tab

description: :unav
DOI: 10.7910/dvn/h8jwlb/lfwroz
title: ReadMe.rtf

description: :unav
DOI: 10.7910/dvn/h8jwlb/srinso
title: Social Compact Baseline_codebook.tab

description: :unav
DOI: 10.7910/dvn/h8jwlb/wopzyw
title: Social Compact Baseline.tab

description: :unav