cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.12998738
title: data_MS# 2020JB020917

description: Load-displacement curves from nanoindentation tests on shale samples in parallel and perpendicular directions. Two material properties known as the indentation modulus (also referred to as the reduced modulus), and hardness can be calculated using the recorded load-displacement curve along with the deformation of the surface.
DOI: 10.6084/m9.figshare.12998738.v2
title: data_MS# 2020JB020917

description: Load-displacement curves from nanoindentation tests on shale samples in parallel and perpendicular directions. Two material properties known as the indentation modulus (also referred to as the reduced modulus), and hardness can be calculated using the recorded load-displacement curve along with the deformation of the surface.
DOI: 10.6084/m9.figshare.12997061.v1
title: R0230_20181022a_videos

description: Rat 0230, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.6084/m9.figshare.12996806
title: R0229_20181029a_videos

description: Rat 0229, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.5281/zenodo.4047101
title: Changing Brine Inputs into Hydrothermal Fluids: Southern Cleft Segment, Juan de Fuca Ridge

description: In 2016 temperature recorders were recovered, temperatures were measured, and fluid samples were collected from Vent 1, a high temperature (338°C) hydrothermal discharge site on the southern Cleft Segment of the Juan de Fuca Ridge. Coupled with previous sampling efforts, this collection represents a 32-year record of discharge from a single chimney structure, the longest record to date. Remarkably, the fluid has remained brine-dominated for more than three decades. This brine formed during phase separation and segregation prior to initial observations in 1984. Although the chloride concentration of the discharging fluid has decreased with time, the fluid temperature has remained nearly constant for at least 3.3 years and probably for 15 or even 22 years. Compositions of the discharging fluids are consistent with inputs from a deep-sourced brine, which was last equilibrated at &gt;400° C at a depth consistent with the base of the sheeted dikes and the brittle-ductile transition. This brine mixed (diffusion or dispersion) with a likely non-phase-separated, hydrothermal fluid prior to discharge. A survey of hydrothermal endmember fluids with chlorinities in excess of 700 mmol/kg shows, with the exception of Fe, a single trend between major ion concentrations and chlorinity even though data are from a range of crustal compositions, spreading rates, and water and magma depths. Calculated deep-sourced brines from hydrothermal fluid data are similar to data based on fluid inclusions and estimates of brine assimilation in magmas. A better understanding of brines is required given their potential duration of discharge and capacity for mobilizing metals. The data in the attached 10 tables represent the supplemental data in a paper published in <em>Geochemistry, Geophysics, Geosystems</em>. The data include temperature data from long-term records, chemical data from hydrothermal effluent from Vent 1 on the Cleft Segment, sediment data, and sulfide chimney data.
description: related information will appear in Wheat, C.G., R. A. Zierenberg, J. B. Paduan, D. W. Caress, D. A. Clague, and W. W. Chadwick Jr. 2020. Changing Brine Inputs into Hydrothermal Fluids: Southern Cleft Segment, Juan de Fuca Ridge, Geochemistry, Geophysics, Geosystems, in press 2020.
description: {"references": ["Wheat, C.G., R. A. Zierenberg, J. B. Paduan, D. W. Caress, D. A. Clague, and W. W. Chadwick Jr. 2020. Changing Brine Inputs into Hydrothermal Fluids: Southern Cleft Segment, Juan de Fuca Ridge, Geochemistry, Geophysics, Geosystems, in press 2020."]}
DOI: 10.5281/zenodo.4047100
title: Changing Brine Inputs into Hydrothermal Fluids: Southern Cleft Segment, Juan de Fuca Ridge

description: In 2016 temperature recorders were recovered, temperatures were measured, and fluid samples were collected from Vent 1, a high temperature (338°C) hydrothermal discharge site on the southern Cleft Segment of the Juan de Fuca Ridge. Coupled with previous sampling efforts, this collection represents a 32-year record of discharge from a single chimney structure, the longest record to date. Remarkably, the fluid has remained brine-dominated for more than three decades. This brine formed during phase separation and segregation prior to initial observations in 1984. Although the chloride concentration of the discharging fluid has decreased with time, the fluid temperature has remained nearly constant for at least 3.3 years and probably for 15 or even 22 years. Compositions of the discharging fluids are consistent with inputs from a deep-sourced brine, which was last equilibrated at &gt;400° C at a depth consistent with the base of the sheeted dikes and the brittle-ductile transition. This brine mixed (diffusion or dispersion) with a likely non-phase-separated, hydrothermal fluid prior to discharge. A survey of hydrothermal endmember fluids with chlorinities in excess of 700 mmol/kg shows, with the exception of Fe, a single trend between major ion concentrations and chlorinity even though data are from a range of crustal compositions, spreading rates, and water and magma depths. Calculated deep-sourced brines from hydrothermal fluid data are similar to data based on fluid inclusions and estimates of brine assimilation in magmas. A better understanding of brines is required given their potential duration of discharge and capacity for mobilizing metals. The data in the attached 10 tables represent the supplemental data in a paper published in <em>Geochemistry, Geophysics, Geosystems</em>. The data include temperature data from long-term records, chemical data from hydrothermal effluent from Vent 1 on the Cleft Segment, sediment data, and sulfide chimney data.
description: related information will appear in Wheat, C.G., R. A. Zierenberg, J. B. Paduan, D. W. Caress, D. A. Clague, and W. W. Chadwick Jr. 2020. Changing Brine Inputs into Hydrothermal Fluids: Southern Cleft Segment, Juan de Fuca Ridge, Geochemistry, Geophysics, Geosystems, in press 2020.
description: {"references": ["Wheat, C.G., R. A. Zierenberg, J. B. Paduan, D. W. Caress, D. A. Clague, and W. W. Chadwick Jr. 2020. Changing Brine Inputs into Hydrothermal Fluids: Southern Cleft Segment, Juan de Fuca Ridge, Geochemistry, Geophysics, Geosystems, in press 2020."]}
DOI: 10.6084/m9.figshare.12998999
title: Raw data identification colour experiment Senegalese sole

description: This dataset is from a study performed in Senegalese sole juveniles to distinguish individuals for behavioural purposes. The study showed that dye-based tagging method is useful to differentiate individuals to study behaviour in this marine flatfish species.
DOI: 10.6084/m9.figshare.12998999.v1
title: Raw data identification colour experiment Senegalese sole

description: This dataset is from a study performed in Senegalese sole juveniles to distinguish individuals for behavioural purposes. The study showed that dye-based tagging method is useful to differentiate individuals to study behaviour in this marine flatfish species.
DOI: 10.5281/zenodo.4048214
title: Wireless Sensor Network Deployments (2013-2017)

description: <strong>Wireless Sensor Network Deployments (2013-2017)</strong> This is an open data repositiory. It is concerned with systematically reviewing scientific publications containing actual Wireless Sensor Network deployments in five year span from 2013 to 2017. <strong><em>Identification</em></strong> Articles were first searched for in SCOPUS and Web of Science databases on 2018-06-12 using these queries/settings: SCOPUS Query: KEY({sensor network} OR {sensor networks}) AND TITLE-ABS-KEY(test* OR experiment* OR deploy*) AND NOT TITLE-ABS-KEY(review) AND NOT TITLE-ABS-KEY(simulat*) AND ( LIMIT-TO ( PUBYEAR,2017 ) OR LIMIT-TO ( PUBYEAR,2016 ) OR LIMIT-TO ( PUBYEAR,2015 ) OR LIMIT-TO ( PUBYEAR,2014 ) OR LIMIT-TO ( PUBYEAR,2013 ) ) Raw results: 11536 articles De-duplicated results: 11374 articles Contained 4814 articles not found in Web of Science Web Of Science Querry: TS = ("sensor network" OR "sensor networks") AND TS = (test* OR experiment* OR deploy*) NOT TI="review" NOT TS=simulat* Additional query parameters: Indexes=SCI-EXPANDED, SSCI, A&HCI, CPCI-S, CPCI-SSH, BKCI-S, BKCI-SSH, ESCI, CCR-EXPANDED, IC Timespan=2013-2017 Raw results: 10204 articles De-duplicated results: 10196 Contained 3636 articles not found in SCOPUS Final results When article results were merged from both databases finally 15010 articles were identified as possible candiates. Of those 6560 were found in both databases. <em><strong>Screening</strong></em> Data was exported as bibtex files and imported in Mendeley software for screening. 4910 articles were left after the screening phase <em><strong>Eligibility check</strong></em> Then all screened included articles were checked for eligibility and 3017 eligible articles were identified. <em><strong>Data extraction</strong></em> In these articles 3059 wireless sensor network deployments were identified and codified data extracted from them. <em><strong>Timeline</strong></em> This data analysis took total time (including validation and error checking) from 2018-06-12 till 2020-05-29, after which the data was prepared for publiching till 2020-07-02.
DOI: 10.5281/zenodo.4048213
title: Wireless Sensor Network Deployments (2013-2017)

description: <strong>Wireless Sensor Network Deployments (2013-2017)</strong> This is an open data repositiory. It is concerned with systematically reviewing scientific publications containing actual Wireless Sensor Network deployments in five year span from 2013 to 2017. <strong><em>Identification</em></strong> Articles were first searched for in SCOPUS and Web of Science databases on 2018-06-12 using these queries/settings: SCOPUS Query: KEY({sensor network} OR {sensor networks}) AND TITLE-ABS-KEY(test* OR experiment* OR deploy*) AND NOT TITLE-ABS-KEY(review) AND NOT TITLE-ABS-KEY(simulat*) AND ( LIMIT-TO ( PUBYEAR,2017 ) OR LIMIT-TO ( PUBYEAR,2016 ) OR LIMIT-TO ( PUBYEAR,2015 ) OR LIMIT-TO ( PUBYEAR,2014 ) OR LIMIT-TO ( PUBYEAR,2013 ) ) Raw results: 11536 articles De-duplicated results: 11374 articles Contained 4814 articles not found in Web of Science Web Of Science Querry: TS = ("sensor network" OR "sensor networks") AND TS = (test* OR experiment* OR deploy*) NOT TI="review" NOT TS=simulat* Additional query parameters: Indexes=SCI-EXPANDED, SSCI, A&HCI, CPCI-S, CPCI-SSH, BKCI-S, BKCI-SSH, ESCI, CCR-EXPANDED, IC Timespan=2013-2017 Raw results: 10204 articles De-duplicated results: 10196 Contained 3636 articles not found in SCOPUS Final results When article results were merged from both databases finally 15010 articles were identified as possible candiates. Of those 6560 were found in both databases. <em><strong>Screening</strong></em> Data was exported as bibtex files and imported in Mendeley software for screening. 4910 articles were left after the screening phase <em><strong>Eligibility check</strong></em> Then all screened included articles were checked for eligibility and 3017 eligible articles were identified. <em><strong>Data extraction</strong></em> In these articles 3059 wireless sensor network deployments were identified and codified data extracted from them. <em><strong>Timeline</strong></em> This data analysis took total time (including validation and error checking) from 2018-06-12 till 2020-05-29, after which the data was prepared for publiching till 2020-07-02.
DOI: 10.5517/ccdc.csd.cc1pvst4
title: CCDC 1574887: Experimental Crystal Structure Determination

description: Related Article: Christopher J. Clemett, Robert A. Faulkner, Craig R. Rice, Christopher Slater, Christopher J. Wedge, Martina Whitehead|2019|Dalton Trans.|48|8427|doi:10.1039/C9DT01063G
description: Related Article: Christopher H. L. Slater, Craig Rice|2019|Thesis|||
DOI: 10.5517/ccdc.csd.cc1z9s35
title: CCDC 1826647: Experimental Crystal Structure Determination

description: Related Article: Craig R. Rice, Christopher Slater, Robert A. Faulkner, Robert L. Allan|2018|Angew.Chem.,Int.Ed.|57|13071|doi:10.1002/anie.201805633
description: Related Article: Christopher H. L. Slater, Craig Rice|2019|Thesis|||
DOI: 10.5517/ccdc.csd.cc1z9s46
title: CCDC 1826648: Experimental Crystal Structure Determination

description: Related Article: Craig R. Rice, Christopher Slater, Robert A. Faulkner, Robert L. Allan|2018|Angew.Chem.,Int.Ed.|57|13071|doi:10.1002/anie.201805633
description: Related Article: Christopher H. L. Slater, Craig Rice|2019|Thesis|||
DOI: 10.5517/ccdc.csd.cc1z9s57
title: CCDC 1826649: Experimental Crystal Structure Determination

description: Related Article: Craig R. Rice, Christopher Slater, Robert A. Faulkner, Robert L. Allan|2018|Angew.Chem.,Int.Ed.|57|13071|doi:10.1002/anie.201805633
description: Related Article: Christopher H. L. Slater, Craig Rice|2019|Thesis|||
DOI: 10.5517/ccdc.csd.cc1z9s68
title: CCDC 1826650: Experimental Crystal Structure Determination

description: Related Article: Craig R. Rice, Christopher Slater, Robert A. Faulkner, Robert L. Allan|2018|Angew.Chem.,Int.Ed.|57|13071|doi:10.1002/anie.201805633
description: Related Article: Christopher H. L. Slater, Craig Rice|2019|Thesis|||
DOI: 10.5517/ccdc.csd.cc1z9s8b
title: CCDC 1826652: Experimental Crystal Structure Determination

description: Related Article: Craig R. Rice, Christopher Slater, Robert A. Faulkner, Robert L. Allan|2018|Angew.Chem.,Int.Ed.|57|13071|doi:10.1002/anie.201805633
description: Related Article: Christopher H. L. Slater, Craig Rice|2019|Thesis|||
DOI: 10.5517/ccdc.csd.cc1z9s9c
title: CCDC 1826653: Experimental Crystal Structure Determination

description: Related Article: Craig R. Rice, Christopher Slater, Robert A. Faulkner, Robert L. Allan|2018|Angew.Chem.,Int.Ed.|57|13071|doi:10.1002/anie.201805633
description: Related Article: Christopher H. L. Slater, Craig Rice|2019|Thesis|||
DOI: 10.5517/ccdc.csd.cc1z9sbd
title: CCDC 1826654: Experimental Crystal Structure Determination

description: Related Article: Craig R. Rice, Christopher Slater, Robert A. Faulkner, Robert L. Allan|2018|Angew.Chem.,Int.Ed.|57|13071|doi:10.1002/anie.201805633
description: Related Article: Christopher H. L. Slater, Craig Rice|2019|Thesis|||
DOI: 10.5517/ccdc.csd.cc1z9scf
title: CCDC 1826655: Experimental Crystal Structure Determination

description: Related Article: Craig R. Rice, Christopher Slater, Robert A. Faulkner, Robert L. Allan|2018|Angew.Chem.,Int.Ed.|57|13071|doi:10.1002/anie.201805633
description: Related Article: Christopher H. L. Slater, Craig Rice|2019|Thesis|||
DOI: 10.5517/ccdc.csd.cc1z9sdg
title: CCDC 1826656: Experimental Crystal Structure Determination

description: Related Article: Craig R. Rice, Christopher Slater, Robert A. Faulkner, Robert L. Allan|2018|Angew.Chem.,Int.Ed.|57|13071|doi:10.1002/anie.201805633
description: Related Article: Christopher H. L. Slater, Craig Rice|2019|Thesis|||
DOI: 10.5517/ccdc.csd.cc1z9shk
title: CCDC 1826659: Experimental Crystal Structure Determination

description: Related Article: Craig R. Rice, Christopher Slater, Robert A. Faulkner, Robert L. Allan|2018|Angew.Chem.,Int.Ed.|57|13071|doi:10.1002/anie.201805633
description: Related Article: Christopher H. L. Slater, Craig Rice|2019|Thesis|||
DOI: 10.5517/ccdc.csd.cc1z9sjl
title: CCDC 1826660: Experimental Crystal Structure Determination

description: Related Article: Craig R. Rice, Christopher Slater, Robert A. Faulkner, Robert L. Allan|2018|Angew.Chem.,Int.Ed.|57|13071|doi:10.1002/anie.201805633
description: Related Article: Christopher H. L. Slater, Craig Rice|2019|Thesis|||
DOI: 10.5517/ccdc.csd.cc1z9skm
title: CCDC 1826661: Experimental Crystal Structure Determination

description: Related Article: Craig R. Rice, Christopher Slater, Robert A. Faulkner, Robert L. Allan|2018|Angew.Chem.,Int.Ed.|57|13071|doi:10.1002/anie.201805633
description: Related Article: Christopher H. L. Slater, Craig Rice|2019|Thesis|||
DOI: 10.5517/ccdc.csd.cc1z9sln
title: CCDC 1826662: Experimental Crystal Structure Determination

description: Related Article: Craig R. Rice, Christopher Slater, Robert A. Faulkner, Robert L. Allan|2018|Angew.Chem.,Int.Ed.|57|13071|doi:10.1002/anie.201805633
description: Related Article: Christopher H. L. Slater, Craig Rice|2019|Thesis|||
DOI: 10.5517/ccdc.csd.cc1zr8zz
title: CCDC 1839632: Experimental Crystal Structure Determination

description: Related Article: Craig R. Rice, Christopher Slater, Robert A. Faulkner, Robert L. Allan|2018|Angew.Chem.,Int.Ed.|57|13071|doi:10.1002/anie.201805633
description: Related Article: Christopher H. L. Slater, Craig Rice|2019|Thesis|||
DOI: 10.5517/ccdc.csd.cc209j0w
title: CCDC 1856187: Experimental Crystal Structure Determination

description: Related Article: Evan N. Keyzer|2019|Thesis|||
description: Related Article: Evan N. Keyzer, Jeongjae Lee, Zigeng Liu, Andrew D. Bond, Dominic S. Wright, Clare P. Grey|2019|J.Mater.Chem.A|7|2677|doi:10.1039/C8TA10295C
DOI: 10.5517/ccdc.csd.cc209j1x
title: CCDC 1856188: Experimental Crystal Structure Determination

description: Related Article: Evan N. Keyzer|2019|Thesis|||
description: Related Article: Evan N. Keyzer, Jeongjae Lee, Zigeng Liu, Andrew D. Bond, Dominic S. Wright, Clare P. Grey|2019|J.Mater.Chem.A|7|2677|doi:10.1039/C8TA10295C
DOI: 10.5517/ccdc.csd.cc1z9smp
title: CCDC 1826663: Experimental Crystal Structure Determination

description: Related Article: Craig R. Rice, Christopher Slater, Robert A. Faulkner, Robert L. Allan|2018|Angew.Chem.,Int.Ed.|57|13071|doi:10.1002/anie.201805633
description: Related Article: Christopher H. L. Slater, Craig Rice|2019|Thesis|||
DOI: 10.5517/ccdc.csd.cc23q3vt
title: CCDC 1957676: Experimental Crystal Structure Determination

description: Related Article: Christopher J. Clemett, Robert A. Faulkner, Gary Midgley, Christopher Slater, Craig R. Rice|2020|Polyhedron|182|114483|doi:10.1016/j.poly.2020.114483
description: Related Article: Christopher H. L. Slater, Craig Rice|2019|Thesis|||
DOI: 10.5517/ccdc.csd.cc23q3wv
title: CCDC 1957677: Experimental Crystal Structure Determination

description: Related Article: Christopher J. Clemett, Robert A. Faulkner, Gary Midgley, Christopher Slater, Craig R. Rice|2020|Polyhedron|182|114483|doi:10.1016/j.poly.2020.114483
description: Related Article: Christopher H. L. Slater, Craig Rice|2019|Thesis|||
DOI: 10.5517/ccdc.csd.cc23q3xw
title: CCDC 1957678: Experimental Crystal Structure Determination

description: Related Article: Christopher J. Clemett, Robert A. Faulkner, Gary Midgley, Christopher Slater, Craig R. Rice|2020|Polyhedron|182|114483|doi:10.1016/j.poly.2020.114483
description: Related Article: Christopher H. L. Slater, Craig Rice|2019|Thesis|||
DOI: 10.7298/4fhq-e356
title: Data from: Thermal transport of helium-3 in a strongly confining channel
DOI: 10.6084/m9.figshare.12999098
title: 100d fasttext (CBOW) embeddings for Cyrillic Uzbek using webcrawl v1 corpus

description: 100-dimensional fasttext CBOW word embeddings for the Cyrillic Uzbek language. Trained using the webcrawl corpus v1.
DOI: 10.6084/m9.figshare.12999098.v1
title: uzb-cyrl-webcrawl-v1-fasttext-cbow-100d

description: 100-dimensional fasttext CBOW word embeddings for the Cyrillic Uzbek language. Trained using the webcrawl corpus v1.
DOI: 10.6084/m9.figshare.12998987
title: Problem 1b

description: Generated data based on problem 1a using y = 3x + 6
DOI: 10.6084/m9.figshare.12998987.v2
title: Problem 1b

description: Generated data based on problem 1a using y = 3x + 6
DOI: 10.6084/m9.figshare.12998987.v1
title: Problem 1b

description: Generated data based on problem 1a using y = 3x + 6
DOI: 10.5281/zenodo.4048230
title: Location of ground stations, targets and spacecraft

description: Datasets included with Article:<br> "Data sink selection using consensus leadership: improving target connectivity for a spacecraft constellation"
DOI: 10.5281/zenodo.4048229
title: Location of ground stations, targets and spacecraft

description: Datasets included with Article:<br> "Data sink selection using consensus leadership: improving target connectivity for a spacecraft constellation"
DOI: 10.5281/zenodo.3836504
title: User Experience Optimization Experiment Simulations

description: # The `uxo_sim` Package A package for simulations of data matching industry UX optimization experiments, as discussed in: ```<br> @article{van_adelsberg_modeling_2019,<br> title = {Modeling {A}/{B} {Test} {Data} is {Hard}: {Effects} of {Overdispersion}, {RandomWalks}, and {Cointegration}},<br> language = {en},<br> journal = {NeurIPS 2019 Workshop on Robust AI in Financial Services: Data, Fairness, Explainability, Trustworthiness, and Privacy},<br> author = {van Adelsberg, Matthew and Sweeney, Mackenzie},<br> month = dec,<br> year = {2019}<br> }<br> ``` The code for running the simulations is included, along with figures and CSV files for each of three specific simulation runs that are used in a publication currently under review for ICML 2020. ## Packages: 1. `data`: code for running the simulations to produce datasets<br> 2. `viz`: code for visualizing the simulation outputs ## Scripts: 1. `save_datasets`: save CSV for each simulated dataset in the `inventory`<br> 2. `save_figs`: save PNG figure for each simulated dataset in `plots` ## Simulation Datasets: ### `fixed_effects_od_20_21_seed27` Data is simulated from a beta-binomial distribution with overdispersion parameter `gamma=0.01` for each of the two treatments and rates `theta=0.20` and `theta=0.21`. This corresponds to beta distribution parameters `alpha, beta = 19.8, 79.2` and `alpha, beta = 20.79, 78.21`. ### `drift_down_then_up` Data is simulated from a beta-binomial distribution with overdispersion parameter `gamma=0.01` for each of the two treatments. The rates start at `theta=0.20` and `theta=0.21` and then: 1. decrease by 0.005 each day for 20 days<br> 2. increase by 0.005 each day for 30 days<br> 3. stay constant for 10 days The corresponding beta distribution parameters on each day are a function of `theta, gamma` and can be obtained via this function (implemented in `uxo_sims.data.simulations`:<br> ```python<br> def alpha_beta_from_gamma_theta(gamma, theta):<br> virtual_sample_size = 1 / gamma - 1<br> alpha = theta * virtual_sample_size<br> beta = virtual_sample_size - alpha<br> return alpha, beta<br> ``` <br> ### `arm_addition` Data is simulated from a beta-binomial distribution with overdispersion parameter `gamma=0.01` for each of the two treatments. The rates start at `theta=0.10` and `theta=0.11` and increase by 0.005 each day for 40 days. The corresponding beta distribution parameters can be obtained with the same function as indicated in `drift_down_then_up`.
description: These datasets were used in a research paper titled "Effects of Model Misspecification on BayesianBandits: Case Studies in UX Optimization," published in the proceedings of the International Conference on Data Mining, 2020.