cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.24867261
title: Treating pain in sickle cell disease by means of focused ultrasound neuromodulation (EEG recordings)

description: We have demonstrated a novel transcranial focused ultrasound technology for pain treatment, that promises to provide non-pharmacologic chronic pain treatment for patients associated with underlying conditions such as cancer or sickle cell disease (SCD).The EEG measurements were conducted from 8 experimental in vivo mice. This work was supported in part by NIH EB029354, NS124564, and NS131069. Animal care and handling are according to the regulation of Institutional Animal Care and Use Committee of Carnegie Mellon University and Long Beach VA medical Centre and complied with National Institutes of Health guidelines. More information can be found in the corresponding manuscript:Kim MG*, Yu K*, Yeh C-Y, Fouda R, Argueta D, Kiven S, Ni Y, Niu X, Chen Q, Kim K, Gupta K, He B. Low-intensity transcranial focused ultrasound changes pain-associated behaviors by modulating pain processing brain circuits. bioRxiv: https://doi.org/10.1101/2022.12.07.519518 (*Equal contribution, first author)If anyone uses the whole or part of the dataset provided here, we kindly ask you to cite the above publication in any of your publications or presentations:Folders:EEG raw data are divided into three groups: Negative control group, tFUS with a PRF of 40 Hz, and tFUS with a PRF of 3 kHz where each data is labeled as negCtrl, tFUS40Hz, and tFUS3kHz, respectively. Data are saved in MATLAB workspace format. Each .mat file is named with [type of stimulation]_[animal number]. The 2-sec epochs are divided into four periods in the analysis described as:- Baseline epochs: 99 trials (#1-99 trial) x 2034 data points- tFUS stimulation or negative control epochs: 600 trials (#100-699 trial) x 2034 data points- Heat stimuli epochs: 40 trials (#701-740 trial) x 2034 data points- Post-treatment epochs: 459 trials (#741-1199 trial) x 2034 data points
DOI: 10.6084/m9.figshare.25043525
title: biomass.csv

description: We tested microbial effects on local adaptation in four paired populations of an abundant alpine plant from two community types, dry and moist meadow. We conducted a greenhouse experiment over five months, manipulating source population, soil moisture, and soil microbiome, and measuring plant survival and biomass to assess treatment effects.
DOI: 10.13019/caag-c375
title: a reconstructed GRACE observation dataset for China (RECTWS-CHN)

description: A long-term reconstructed TWSA dataset for China land area (RECTWS-CHN) based on the GRACE-observations.
DOI: 10.25345/c5xp6vf07
title: MassIVE MSV000093902 - leA nonenzymatic dependency on inositol-requiring enzyme 1 controls cancer cell cycle progression and tumor growth
title: Endoplasmic-reticulum resident inositol-requiring enzyme 1alpha(IRE1) supports protein homeostasis via a cytoplasmic kinase-RNase module. Known cancer dependency on IRE1 entails its enzymatic activation of the transcription factor XBP1s and of RNA decay. We discovered that some cancer cells require IRE1 but not its enzymatic activity. IRE1 knockdown, but not enzymatic inhibition or XBP1 disruption, increased DNA damage and chromosome instability while engaging the TP53 pathway and cyclin-dependent kinase inhibitors, and attenuated cell cycle progression. IRE1 depletion downregulated factors involved in chromosome replication and segregation and in chromatin remodeling. Immunoelectron microscopy indicated that endogenous IRE1 can localize to the nuclear envelope. Thus, cancer cells can require IRE1 either enzymatically or nonenzymatically, with significant implications for IRE1's biological role and therapeutic targeting.
DOI: 10.18112/openneuro.ds004907.v1.2.1
title: RestHoldMove
DOI: 10.5517/ccdc.csd.cc230qf9
title: CCDC 1937110: Experimental Crystal Structure Determination

description: Related Article: Shakhnoza Kadirova, Batirbay Torambetov, Surayyo Razzokova, Zamira Uzakbergenova, Abdurakhman Abdreymov, Dilnoza Raxmonova, Nusrat Parpiev|2022|AIP Conference Proceedings|2432|050034|doi:10.1063/5.0091014
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2c64wm
title: CCDC 2180660: Experimental Crystal Structure Determination

description: Related Article: Che Wu, Lakshmi Nishanth Kakarla, Chandru P. Chandrasekaran, Xiaodong Zhang, Joel T. Mague, Stephen Sproules, James P. Donahue|2023|Inorg.Chem.|63|173|doi:10.1021/acs.inorgchem.3c02928
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2c64xn
title: CCDC 2180661: Experimental Crystal Structure Determination

description: Related Article: Che Wu, Lakshmi Nishanth Kakarla, Chandru P. Chandrasekaran, Xiaodong Zhang, Joel T. Mague, Stephen Sproules, James P. Donahue|2023|Inorg.Chem.|63|173|doi:10.1021/acs.inorgchem.3c02928
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2g33f4
title: CCDC 2267105: Experimental Crystal Structure Determination

description: Related Article: Che Wu, Lakshmi Nishanth Kakarla, Chandru P. Chandrasekaran, Xiaodong Zhang, Joel T. Mague, Stephen Sproules, James P. Donahue|2023|Inorg.Chem.|63|173|doi:10.1021/acs.inorgchem.3c02928
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2c64yp
title: CCDC 2180662: Experimental Crystal Structure Determination

description: Related Article: Che Wu, Lakshmi Nishanth Kakarla, Chandru P. Chandrasekaran, Xiaodong Zhang, Joel T. Mague, Stephen Sproules, James P. Donahue|2023|Inorg.Chem.|63|173|doi:10.1021/acs.inorgchem.3c02928
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2gkhcx
title: CCDC 2280929: Experimental Crystal Structure Determination

description: Related Article: Xiaoli Lin, Panke Zhou, Yiqun Gao, Tao Li, Xiong Chen, Haohong Li, Rong Jiang, Zhirong Chen, Huidong Zheng|2023|Inorg.Chem.|63|775|doi:10.1021/acs.inorgchem.3c03787
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2gkhh1
title: CCDC 2280933: Experimental Crystal Structure Determination

description: Related Article: Xiaoli Lin, Panke Zhou, Yiqun Gao, Tao Li, Xiong Chen, Haohong Li, Rong Jiang, Zhirong Chen, Huidong Zheng|2023|Inorg.Chem.|63|775|doi:10.1021/acs.inorgchem.3c03787
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2gnxqs
title: CCDC 2284226: Experimental Crystal Structure Determination

description: Related Article: Rajashi Haldar, Ajay Kumar, Dipankar Mandal, Maheswaran Shanmugam|2023|Materials Horizons|11|454|doi:10.1039/D3MH01336G
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2gnxrt
title: CCDC 2284227: Experimental Crystal Structure Determination

description: Related Article: Rajashi Haldar, Ajay Kumar, Dipankar Mandal, Maheswaran Shanmugam|2023|Materials Horizons|11|454|doi:10.1039/D3MH01336G
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.10553074
title: Analysis code in support of "The Interaction Between Climate Forcing and Feedbacks"

description: Analysis code in support of Manuscript "The Interaction Between Climate Forcing and Feedbacks"

Data is already available through DOI: https://doi.org/10.26024/bzne-yf09

read_ppe2map.ipynb will create data files from the PPE output (if the files at the DOI do not work), and then the different codes herein are used to create figures in the manuscript.
DOI: 10.5281/zenodo.10547040
title: Source Data for "Submolecular-scale control of phototautomerization"

description: Source Data for "Submolecular-scale control of phototautomerization"
DOI: 10.5281/zenodo.10547041
title: Source Data for "Submolecular-scale control of phototautomerization"

description: Source Data for "Submolecular-scale control of phototautomerization"
DOI: 10.34740/kaggle/dsv/7458179
title: Forex Exchange Rates Since 2004 (Updated Daily)
DOI: 10.25345/c5sx64m6v
title: MassIVE MSV000093903 - Phosphoproteomic Analysis of PCB126 Impact on the Mouse Chronic-Binge Alcohol Feeding Model
title: Environmental pollutants, including polychlorinated biphenyls (PCBs) have been implicated in the pathogenesis of liver disease. To better understand how PCB126 promoted alcohol-associated liver disease (ALD) in our previous model, the current study utilized a phosphoproteomic approach for hypothesis generation regarding mechanisms of action. Briefly, male C57B/6J mice were exposed to 0.2 mg/kg polychlorinated biphenyl PCB126 or corn oil vehicle prior to ethanol (EtOH) or control diet feeding in the chronic-binge alcohol feeding model. Liver tissues were harvested during euthanasia and tissue collection, snap frozen in liquid nitrogen, and then were archived in a -80C freezer. For phosphoproteome analysis, six random liver tissues from four groups (N=24) were homogenized in 2% sodium dodecyl sulfate (SDS) radioimmunoprecipitation (RIPA) buffer with 1X HALT protease and phosphatase inhibitors. Lysates were trypsinized at a 1:20 (enzyme:sample) ratio and prepared following ProtiFi S-Trap mini spin column digestion protocol. Phospho-peptides were enriched with MagReSyn titanium ion - immobilized metal affinity chromatography (Ti-IMAC) microparticles following ReSyn Biosciences MagReSyn Ti-IMAC protocol. Samples were then purified using C18 PROTO 300 A Ultra MicroSpin columns, dried under a SpeedVac, and stored at -80C prior to peptide concentration assessment. Digests were fractionated by UPLC nanoflow liquid chromatography using PepMap RSLC C18 EASY-spray separating column at 40C with a 90-minute linear gradient. Eluates were introduced into an Exploris480 using an EASY-spray source (320C and 1.8kV). Full MS-ddMS2 method with a 3 second cycle time was generated in Xcalibur (v4.5.445.18) operating in positive polarity. RAW data files were separately searched in PeaksXpro (Bioinformatics Solutions Inc.; Waterloo, ON, Canada) using Denovo, PeaksDB, and PeaksPTM algorithms against the UniprotKB Mus musculus canonical protein sequences (proteomics ID: UP000000589) downloaded March 17, 2023. Label Free Quantification algorithm was then used with PeaksPTM results utilizing a mass error tolerance of 10 ppm and retention time shift tolerance of 6-minutes. Peptides were accepted at a 1% FDR threshold for consideration by the Label Free Quantification algorithm.
DOI: 10.5281/zenodo.10108270
title: Supplemental package of a study on the implications of AI-based tools for the human aspects of software engineering
DOI: 10.5281/zenodo.10108271
title: Supplemental package of a study on the implications of AI-based tools for the human aspects of software engineering
DOI: 10.5066/p9zj8olr
title: Selected inputs for examining the complex relations between climate and streamflow in the Mid-Atlantic region of the United States

description: Streams provide water for human activities and consumption in much of the world. Streamflow is largely controlled by climate forces, therefore it is likely sensitive to climate changes. We analyzed daily air temperature (AT), precipitation (P), and stream discharge (Q) metrics for 124 watersheds in Maryland, Virginia, and North Carolina, United States, from 1981 through 2020. Spatial-raster datasets of daily P in mm were downloaded from Parameter-elevation Regressions on Independent Slopes Model (PRISM; http://prism.oregonstate.edu) on March 30, 2021, and datasets of daily AT in degrees Celsius (&deg;C) were downloaded June 22, 2021, both at a 4-square kilometer (km2) resolution for the contiguous U.S. The final quarter of approved 2020 data for both datasets was downloaded between January 6 and 8, 2022. Daily mean-Q data were downloaded from the USGS&rsquo;s National Water Information System on January 5, 2022, checked for completeness, and converted to cubic meters per second. The input data sets used to derive trends and PCA results are presented here in the zip file found below. Due to Excel&rsquo;s maximum row constraints, the files have been subset by decade. Please refer to the linked manuscript below for more information.
DOI: 10.34740/kaggle/dsv/7458238
title: Trending Youtube Video Statistics (113 Countries)
DOI: 10.34740/kaggle/dsv/7458265
title: Full TMDB Movies Dataset 2023 (930K Movies)
DOI: 10.48366/r659837
title: Diffusion models for 3D content generation

description: Comparision of Diffusion models for 3D content generation
DOI: 10.6084/m9.figshare.25043654
title: Data File for "On the Long-Run Properties of Income and Stock Prices: The Stability of the 'Golden Ratios'"

description: This is the data file for "On the Long-Run Properties of Income and Stock Prices: The Stability of the 'Golden Ratios'" forthcoming at Journal of Financial Economic Policy
DOI: 10.6084/m9.figshare.25043654.v1
title: Data File for "On the Long-Run Properties of Income and Stock Prices: The Stability of the 'Golden Ratios'"

description: This is the data file for "On the Long-Run Properties of Income and Stock Prices: The Stability of the 'Golden Ratios'" forthcoming at Journal of Financial Economic Policy
DOI: 10.6084/m9.figshare.4930094
title: Bibliography for newcomers to translation & interpreting studies: 2023 edition

description: This is a bibliography for newcomers to translation and interpreting studies, and covers general introductions and reference works. We will update this bibliography approximately once a year.<br><br>Major changes in the 2023 edition: we added more works/new editions
DOI: 10.5281/zenodo.10403306
title: Processed Data of "Predicting DNA structure using a deep learning method"

description: Include all processed data of paper "Predicting DNA structure using a deep learning method".
DOI: 10.5281/zenodo.10403307
title: Processed Data of "Predicting DNA structure using a deep learning method"

description: Include all processed data of paper "Predicting DNA structure using a deep learning method".
DOI: 10.34740/kaggle/dsv/7458274
title: 2024 Urban Bliss Index
DOI: 10.3886/e195342v1
title: ECIN Replication Package for "Market intelligence gathering, asymmetric information, and the instability of money demand"

description: The observed money demand in the U.S. had a stable negative relation with the interest rate up until the 1990s. After this period, this relation fell apart and has never been restored. We show that the central bank's ability to gather information, referred to as market intelligence, matters to generate an upward-sloping money demand curve. We calibrate the model to the U.S. data for the period from 1990 to 2019 and show that market intelligence helps to match the money demand. We also show that it is beneficial for the society, since it mitigates the inefficiency associated with asymmetric information.<br>
DOI: 10.3886/e195342
title: ECIN Replication Package for "Market intelligence gathering, asymmetric information, and the instability of money demand"

description: The observed money demand in the U.S. had a stable negative relation with the interest rate up until the 1990s. After this period, this relation fell apart and has never been restored. We show that the central bank's ability to gather information, referred to as market intelligence, matters to generate an upward-sloping money demand curve. We calibrate the model to the U.S. data for the period from 1990 to 2019 and show that market intelligence helps to match the money demand. We also show that it is beneficial for the society, since it mitigates the inefficiency associated with asymmetric information.<br>
DOI: 10.6084/m9.figshare.25043633
title: UBD Policy Urban Forests Data

description: This dataset provides data on three climate change impact metrics: exposure, safety margin and risk, for 164 global cities and 3,016 tree and shrub plant species. These metrics were calculated for all five climate variables (mean annual temperature, MAT; maximum temperature of the warmest month, MTWM; minimum temperature of the coldest month, MTCM; annual precipitation, AP; precipitation of the driest quarter, PDQ), three time periods (baseline and future (2050 and 2070) and two RCPs (4.5 and 6.0).Exposure (<i>E</i>) is the degree to which a city is exposed to climatic change and is a measure of how much the climate is projected to change (for example, warmer or drier) between current and future time periods in a given location.The safety margin (<i>S</i>) describes a species’ sensitivity to climate change and indicates its potential tolerance to changing climate conditions that may exceed either of the species’ upper or lower climatic limits within a given city.The risk (<i>R</i>) refers to the potential for adverse consequences on biological systems and is calculated as the difference between the city’s extrinsic exposure to future climate change and the species’ intrinsic safety margin.More details can be found in: Esperon-Rodriguez, M., Tjoelker, M.G., Lenoir, J. <i>et al.</i> Climate change increases global risk to urban forests. <i>Nat. Clim. Chang.</i> 12, 950–955 (2022). https://doi.org/10.1038/s41558-022-01465-8
DOI: 10.6084/m9.figshare.25043633.v1
title: UBD Policy Urban Forests Data

description: This dataset provides data on three climate change impact metrics: exposure, safety margin and risk, for 164 global cities and 3,016 tree and shrub plant species. These metrics were calculated for all five climate variables (mean annual temperature, MAT; maximum temperature of the warmest month, MTWM; minimum temperature of the coldest month, MTCM; annual precipitation, AP; precipitation of the driest quarter, PDQ), three time periods (baseline and future (2050 and 2070) and two RCPs (4.5 and 6.0).Exposure (<i>E</i>) is the degree to which a city is exposed to climatic change and is a measure of how much the climate is projected to change (for example, warmer or drier) between current and future time periods in a given location.The safety margin (<i>S</i>) describes a species’ sensitivity to climate change and indicates its potential tolerance to changing climate conditions that may exceed either of the species’ upper or lower climatic limits within a given city.The risk (<i>R</i>) refers to the potential for adverse consequences on biological systems and is calculated as the difference between the city’s extrinsic exposure to future climate change and the species’ intrinsic safety margin.More details can be found in: Esperon-Rodriguez, M., Tjoelker, M.G., Lenoir, J. <i>et al.</i> Climate change increases global risk to urban forests. <i>Nat. Clim. Chang.</i> 12, 950–955 (2022). https://doi.org/10.1038/s41558-022-01465-8
DOI: 10.34740/kaggle/dsv/7458381
title: Top Spotify Songs in 73 Countries (Daily Updated)
DOI: 10.5517/ccdc.csd.cc2fg2bb
title: CCDC 2247851: Experimental Crystal Structure Determination

description: Related Article: V.V. Kuznetsov, D.V. Khakimov, A.I. Samigullina, A.S. Dmitrenok|2024|Chem.Phys.|579|112187|doi:10.1016/j.chemphys.2024.112187
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2fg2cc
title: CCDC 2247852: Experimental Crystal Structure Determination

description: Related Article: V.V. Kuznetsov, D.V. Khakimov, A.I. Samigullina, A.S. Dmitrenok|2024|Chem.Phys.|579|112187|doi:10.1016/j.chemphys.2024.112187
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2fg2dd
title: CCDC 2247853: Experimental Crystal Structure Determination

description: Related Article: V.V. Kuznetsov, D.V. Khakimov, A.I. Samigullina, A.S. Dmitrenok|2024|Chem.Phys.|579|112187|doi:10.1016/j.chemphys.2024.112187
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2fzt7h
title: CCDC 2263937: Experimental Crystal Structure Determination

description: Related Article: M. Woińska, A.A. Hoser, M.L. Chodkiewicz, K. Woźniak|2023|IUCrJ|11|45|doi:10.1107/S205225252300951X
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.