cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.13182629.v2
title: What martian meteorites reveal about the interior and surface of Mars

description: This supporting information contains the tables captions and the references included in Table S4. The four tables consists of compilation of data and include the list of currently classified of martian meteorites (as of August 2020). <b>Table S1.</b> List of martian meteorites. LREE enrichment indicated for shergottites.<b> </b><b>Table S2</b>. Number of meteorites per type for paired groups and unpaired meteorites<b> </b><b>Table S3.</b> Compilation of martian meteorite bulk rock compositions (if no data =not analyzed or below detection)<b> </b><b>Table S4.</b> Crystallization and ejection ages of martian meteorites (references in Tables S4) including techniques used for cosmic ray ejection ages (CRE).
DOI: 10.6084/m9.figshare.7246985.v15
title: pretrained networks for deep learning applications

description: Pretrained networks for a variety of problems.<br>WBIR networks are named wbir* <br>put them all in a folder called "models" then see create_wbir_models.R for how to load them<br>wbir_random_vgg_3d --- 3dvgg initialized with random weights<br>wbir_resnet_vgg_weights --- resnet trained to mimic 2d pseudo vgg activations<br>wbir_vggtrue3d -- 3d egg trained to mimic 2d pseudo vgg activations<br>wbir_brain_age_weights -- weights for brain age<br>wbir_pseudo_vgg_ -- 2d vgg transferred to 3d
DOI: 10.17909/t9-t6cs-8p81
title: All TESS FFI files from Sectors 14-26.

description: Download scripts for all TESS FFI FITS files from Sectors 14 through 26.
DOI: 10.6084/m9.figshare.13221719.v1
title: Whole proteome-level GPS predictions (part 1)

description: This is the expanded set of all predictions for GPS, run on the entire reference proteome, including sites not known to be phosphorylated. This dataset is used to perform a fast update when new phosphosites are discovered. The uncompressed folder will yield a large CSV file with predictions in list format (i.e. one line per kinase-substrate prediction)<br>Columns in this order:substrate_id - unique substrate (accession_site) IDsubstrate_acc - Uniprot accession of substrate proteinsubstrate_name - Name of proteinsite - amino acid type and position (S5, means serine position 5)pep - 15-amino acid sequence centered on site of phosphorylationscore - prediction algorithm scoreKinase Name - name of kinase by our controlled ontology (found in this project)<br>Each entry indicates the protein at position (identified by peptide) and has a score weight prediction for the given kinase.<br>FOR FULL GPS RAW, you must combine this with the second zip part (GPS_split.z01). Please be sure to download both into the same directory before unzipping. The final, uncompressed file, is 24GB.<br>
DOI: 10.6084/m9.figshare.13221719
title: Whole proteome-level GPS predictions (part 1)

description: This is the expanded set of all predictions for GPS, run on the entire reference proteome, including sites not known to be phosphorylated. This dataset is used to perform a fast update when new phosphosites are discovered. The uncompressed folder will yield a large CSV file with predictions in list format (i.e. one line per kinase-substrate prediction)<br>Columns in this order:substrate_id - unique substrate (accession_site) IDsubstrate_acc - Uniprot accession of substrate proteinsubstrate_name - Name of proteinsite - amino acid type and position (S5, means serine position 5)pep - 15-amino acid sequence centered on site of phosphorylationscore - prediction algorithm scoreKinase Name - name of kinase by our controlled ontology (found in this project)<br>Each entry indicates the protein at position (identified by peptide) and has a score weight prediction for the given kinase.<br>FOR FULL GPS RAW, you must combine this with the second zip part (GPS_split.z01). Please be sure to download both into the same directory before unzipping. The final, uncompressed file, is 24GB.<br>
DOI: 10.6073/pasta/fccdb501ac45aa44d457ed0d5a047640
title: SBC LTER: OCEAN: Temperature to Nitrate Lookup Tables for the Southern California Bight

description: This dataset is the temperature and nitrate lookup table in the southern California Bight. The temperature and nitrate measurements were compiled from three campaigns in the Southern California Bight. The temperature and nitrate data were binned in different regions (onshore, offshore, northern, central, southern, and all regions) and seasons (summer, winter, all season) for generating the lookup table. See method for details. Please cite the following publication: Snyder, J. N., Bell, T. W., Siegel, D. A., Nidzieko, N. J., & Cavanaugh, K. C. (2020). Sea Surface Temperature Imagery Elucidates Spatiotemporal Nutrient Patterns for Offshore Kelp Aquaculture Siting in the Southern California Bight, 7(22), 1–14. https://doi.org/10.3389/fmars.2020.00022
DOI: 10.5281/zenodo.4270200
title: An agent-based model of the origins of modern linguistic complexity – supplementary information

description: A central question in the evolution of human language is whether it emerged as a result of one specific event or from a mosaic-like constellation of different phenomena and their interactions. Three potential processes have been identified by recent research as the potential <em>primum mobile</em> for the origins of modern linguistic complexity: Self-domestication, characterized by a reduction in reactive aggression and often associated with a gracilization of the face; changes in early brain development manifested by globularization of the skull; and demographic expansion of H. sapiens during the Middle Pleistocene. We developed an agent-based model to investigate how these three factors influence transmission of information within a population. Our model shows that there is an optimal degree of both hostility and mental capacity at which the amount of transmitted information is the largest. It also shows that linguistic communi- ties formed within the population are strongest under circumstances where individuals have high levels of cognitive capacity available for information processing and there is at least a certain degree of hos- tility present. In contrast, we find no significant effects related to population size.
DOI: 10.5281/zenodo.4270199
title: An agent-based model of the origins of modern linguistic complexity – supplementary information

description: A central question in the evolution of human language is whether it emerged as a result of one specific event or from a mosaic-like constellation of different phenomena and their interactions. Three potential processes have been identified by recent research as the potential <em>primum mobile</em> for the origins of modern linguistic complexity: Self-domestication, characterized by a reduction in reactive aggression and often associated with a gracilization of the face; changes in early brain development manifested by globularization of the skull; and demographic expansion of H. sapiens during the Middle Pleistocene. We developed an agent-based model to investigate how these three factors influence transmission of information within a population. Our model shows that there is an optimal degree of both hostility and mental capacity at which the amount of transmitted information is the largest. It also shows that linguistic communi- ties formed within the population are strongest under circumstances where individuals have high levels of cognitive capacity available for information processing and there is at least a certain degree of hos- tility present. In contrast, we find no significant effects related to population size.
DOI: 10.5517/ccdc.csd.cc1zfwbm
title: CCDC 1830591: Experimental Crystal Structure Determination

description: Related Article: Waqar Ahmed,  Sheng Zhang, Xiujuan Feng, Xiaoqiang Yu, Yoshinori Yamamoto, Ming Bao|2020|ChemCatChem|12|5200|doi:10.1002/cctc.202000842
DOI: 10.5517/ccdc.csd.cc232r87
title: CCDC 1939058: Experimental Crystal Structure Determination

description: Related Article: Agnieszka Wojciechowska, Tomasz Rojek, Magdalena Malik−Gajewska, Maria Jerzykiewicz, Rafał Wysokiński, Anna Gągor, Piotr Rytlewski, Zbigniew Staszak, Marek Duczmal|2020|Mater.Sci.Eng.,B|262|114723|doi:10.1016/j.mseb.2020.114723
DOI: 10.5517/ccdc.csd.cc243rz0
title: CCDC 1969832: Experimental Crystal Structure Determination

description: Related Article: Víctor Tena Pérez, Luis Apaza Ticona, Alfredo H. Cabanillas, Santiago Maderuelo Corral, Josefina Perles, Diego Fernando Rosero Valencia, Antera Martel Quintana, Montserrat Ortega Domenech, Ángel Rumbero Sánchez|2020|Phytochemistry|180|112529|doi:10.1016/j.phytochem.2020.112529
DOI: 10.5517/ccdc.csd.cc24jq4k
title: CCDC 1982268: Experimental Crystal Structure Determination

description: Related Article: İlker Cabacı, Derya Davarcı, Yunus Zorlu|2020|Polyhedron|192|114823|doi:10.1016/j.poly.2020.114823
DOI: 10.5517/ccdc.csd.cc24jq5l
title: CCDC 1982269: Experimental Crystal Structure Determination

description: Related Article: İlker Cabacı, Derya Davarcı, Yunus Zorlu|2020|Polyhedron|192|114823|doi:10.1016/j.poly.2020.114823
DOI: 10.5517/ccdc.csd.cc24jq6m
title: CCDC 1982270: Experimental Crystal Structure Determination

description: Related Article: İlker Cabacı, Derya Davarcı, Yunus Zorlu|2020|Polyhedron|192|114823|doi:10.1016/j.poly.2020.114823
DOI: 10.5517/ccdc.csd.cc253czn
title: CCDC 1999251: Experimental Crystal Structure Determination

description: Related Article: Jian Zhang, Min Song, Yun-Lin Ao, Yong Li, Xue-Yi Zou, Jie Xu, Ying Wang, Dong-Mei Zhang, Xiao-Qi Zhang, Wen-Cai Ye|2020|Org.Chem.Front.|7|3468|doi:10.1039/D0QO00751J
DOI: 10.5517/ccdc.csd.cc258fws
title: CCDC 2004115: Experimental Crystal Structure Determination

description: Related Article: Fang Yu, Benlong Luo, Ruili Sang, Li Xu|2020|Nanoscale|12|20230|doi:10.1039/D0NR05822J
DOI: 10.5517/ccdc.csd.cc258fxt
title: CCDC 2004116: Experimental Crystal Structure Determination

description: Related Article: Fang Yu, Benlong Luo, Ruili Sang, Li Xu|2020|Nanoscale|12|20230|doi:10.1039/D0NR05822J
DOI: 10.5517/ccdc.csd.cc258cpj
title: CCDC 2004047: Experimental Crystal Structure Determination

description: Related Article: Fang Yu, Benlong Luo, Ruili Sang, Li Xu|2020|Nanoscale|12|20230|doi:10.1039/D0NR05822J
DOI: 10.5517/ccdc.csd.cc25h5zv
title: CCDC 2010597: Experimental Crystal Structure Determination

description: Related Article: Gunhee Kim, Evan Lelong, Juhye Kang, Jong-Min Suh, Nathalie Le Bris, Hélène Bernard, Dongwook Kim, Raphaël Tripier, Mi Hee Lim|2020|Inorg.Chem.Front.|7|4222|doi:10.1039/D0QI00791A
DOI: 10.5517/ccdc.csd.cc25j4wr
title: CCDC 2011524: Experimental Crystal Structure Determination

description: Related Article: Gunhee Kim, Evan Lelong, Juhye Kang, Jong-Min Suh, Nathalie Le Bris, Hélène Bernard, Dongwook Kim, Raphaël Tripier, Mi Hee Lim|2020|Inorg.Chem.Front.|7|4222|doi:10.1039/D0QI00791A
DOI: 10.5517/ccdc.csd.cc25j4xs
title: CCDC 2011525: Experimental Crystal Structure Determination

description: Related Article: Gunhee Kim, Evan Lelong, Juhye Kang, Jong-Min Suh, Nathalie Le Bris, Hélène Bernard, Dongwook Kim, Raphaël Tripier, Mi Hee Lim|2020|Inorg.Chem.Front.|7|4222|doi:10.1039/D0QI00791A
DOI: 10.5517/ccdc.csd.cc25jxvh
title: CCDC 2012267: Experimental Crystal Structure Determination

description: Related Article: Ping Li, Boyu Zhu, Yao Xu, Zhiqiang Zhou, Guiwen Hu, Fan Yang, Shijie Xu, Xiaoxiang Zhang|2020|Org.Chem.Front.|7|3480|doi:10.1039/D0QO00799D
DOI: 10.5517/ccdc.csd.cc25p6hl
title: CCDC 2016379: Experimental Crystal Structure Determination

description: Related Article: Hongbo Wang, Jinnan Huo, Hongbo Tong, Xuehong Wei, Ying Zhang, Yanbo Li, Shuming Chen, Heping Shi, Ben Zhong Tang|2020|J.Mater.Chem.C|8|14208|doi:10.1039/D0TC03431B
DOI: 10.5517/ccdc.csd.cc25x206
title: CCDC 2022967: Experimental Crystal Structure Determination

description: Related Article: Deqing Hu, Lu Yang, Jie-Ping Wan|2020|Green Chemistry|22|6773|doi:10.1039/D0GC02806A
DOI: 10.5517/ccdc.csd.cc260cg2
title: CCDC 2026143: Experimental Crystal Structure Determination

description: Related Article: Shiwen Liu, Lili Wang, Zhipeng Ma, Xiaojun Zeng, Bo Xu|2020|Org.Chem.Front.|7|3474|doi:10.1039/D0QO01052A
DOI: 10.6073/pasta/60d044f4c57aea39eaeb3357cafd8556
title: SBC LTER: Ocean: Time-series: nearshore dissolved oxygen and temperature outside of reefs, ongoing since 2011

description: Dissolved oxygen (miniDOT sensors) data was collected from 6 reefs in the Santa Barbara Channel along with in situ temperature, in top, mid, and bottom water columns. Most dissolved oxygen sensors are deployed together with SBC long-term mooring instruments. Data collection intervals and miniDOT sensor depths in three water columns vary based on the site location.
DOI: 10.7298/6vtr-c668
title: Data from: Organo-organic and organo-mineral interfaces in soil at the nanometer scale
DOI: 10.5281/zenodo.4270478
title: Studying Taxonomy Enrichment on Diachronic WordNet Versions (non-restricted Russian dataset)

description: Previous dataset (RUSSE'2020) does not include short words (&lt;4 symbols), diminutives, named entities and other constraints described in the shared task paper. We remove those constraints and present a non-restricted Russian dataset and a symmetrical English dataset from WordNet database.
DOI: 10.5281/zenodo.3947993
title: Supplementary material for the publication: J. D. Nixon, K. Bhargava and E. Gaura, Analysis of standalone solar streetlights for improved energy access in displaced settlements, 2020.

description: The dataset deposited here was prepared under the EPSRC-funded Humanitarian Engineering and Energy for Displacement research project (EP/P029531/1). The project aimed to understand energy needs of displaced communities, create an evidence base on the usage of different energy interventions and provide recommendations for improved design of future energy interventions to better meet the needs of people. As part of the project, we deployed 11 advanced solar streetlights, with additional energy access provided by ground-level AC sockets, at two project sites: Gihembe refugee camp, Rwanda (4 lights) and Uttargaya settlement, Nepal (7 lights), in July 2019. The aim of this study was to (a) identify best practices in the construction, location and security measures for long-lived street lighting (b) understand how communities would use a shared energy resource when available through energy sockets, auxiliary to the main function of the streetlights. The system data used for the performance analysis for this study (July 2019 and March 2020) is deposited here along with the metadata. The results from analysis are presented in a paper titled '<strong>Analysis of standalone solar streetlights for improved energy access in displaced settlements</strong>' (currently under review). The scripts for analysis can be found at our Github account Cogent Labs under HEED_Nepal_SL and HEED_Rwanda_SL repositories.
DOI: 10.5281/zenodo.3947992
title: Supplementary material for the publication: J. D. Nixon, K. Bhargava and E. Gaura, Analysis of standalone solar streetlights for improved energy access in displaced settlements, 2020.

description: The dataset deposited here was prepared under the EPSRC-funded Humanitarian Engineering and Energy for Displacement research project (EP/P029531/1). The project aimed to understand energy needs of displaced communities, create an evidence base on the usage of different energy interventions and provide recommendations for improved design of future energy interventions to better meet the needs of people. As part of the project, we deployed 11 advanced solar streetlights, with additional energy access provided by ground-level AC sockets, at two project sites: Gihembe refugee camp, Rwanda (4 lights) and Uttargaya settlement, Nepal (7 lights), in July 2019. The aim of this study was to (a) identify best practices in the construction, location and security measures for long-lived street lighting (b) understand how communities would use a shared energy resource when available through energy sockets, auxiliary to the main function of the streetlights. The system data used for the performance analysis for this study (July 2019 and March 2020) is deposited here along with the metadata. The results from analysis are presented in a paper titled '<strong>Analysis of standalone solar streetlights for improved energy access in displaced settlements</strong>' (currently under review). The scripts for analysis can be found at our Github account Cogent Labs under HEED_Nepal_SL and HEED_Rwanda_SL repositories.
DOI: 10.5281/zenodo.3947000
title: EPSRC HEED Data Repository: Stove Use Monitoring System

description: The dataset deposited here was prepared under the EPSRC-funded Humanitarian Engineering and Energy for Displacement research project (EP/P029531/1). The project aimed to understand energy needs of displaced communities, create an evidence base on the usage of different energy interventions and provide recommendations for improved design of future energy interventions to better meet the needs of people. As part of the project, we deployed Stove Use Monitoring Systems (SUM) on clay cook stoves in Kigeme camp, Rwanda. The aim was to (a) measure and evaluate temperature profiles within stove enclosure and on the surface of stoves (b) evaluate frequency and duration of stove use. The SUM consisted of 2 sensors - a thermocouple (to measure temperature within the stove) and a Si7021 sensor (to measure temperature and humidity outside the stove), connected to an Arduino MKR GSM 1400 board. The data measured by the sensors was stored only if the change in values exceeded a set threshold for either of the readings. The SUM was powered by a re-chargeable Li-Ion battery of 3.7V and a rating of 7.59Wh. The study was conducted in 2 phases. In phase 1 (02 July 2019 to 30 September 2019), data was collected from 15 SUM and stored locally on SD card as well as communicated to a remote server via GSM. The time of data collection was recorded using GSM functionality. However, several GSM and MQTT failures were noted leading to loss of timestamp values as well as shorter battery lifetime due to re-transmission tries. In phase 2 (02 October 2019 to 17 October 2019), data was collected from 9 SUM and only stored locally on SD cards. The time of data collection was recorded using an external RTC clock connected to the Arduino board. The data from both phases of study is deposited here along with the metadata.
DOI: 10.5281/zenodo.3946999
title: EPSRC HEED Data Repository: Stove Use Monitoring System

description: The dataset deposited here was prepared under the EPSRC-funded Humanitarian Engineering and Energy for Displacement research project (EP/P029531/1). The project aimed to understand energy needs of displaced communities, create an evidence base on the usage of different energy interventions and provide recommendations for improved design of future energy interventions to better meet the needs of people. As part of the project, we deployed Stove Use Monitoring Systems (SUM) on clay cook stoves in Kigeme camp, Rwanda. The aim was to (a) measure and evaluate temperature profiles within stove enclosure and on the surface of stoves (b) evaluate frequency and duration of stove use. The SUM consisted of 2 sensors - a thermocouple (to measure temperature within the stove) and a Si7021 sensor (to measure temperature and humidity outside the stove), connected to an Arduino MKR GSM 1400 board. The data measured by the sensors was stored only if the change in values exceeded a set threshold for either of the readings. The SUM was powered by a re-chargeable Li-Ion battery of 3.7V and a rating of 7.59Wh. The study was conducted in 2 phases. In phase 1 (02 July 2019 to 30 September 2019), data was collected from 15 SUM and stored locally on SD card as well as communicated to a remote server via GSM. The time of data collection was recorded using GSM functionality. However, several GSM and MQTT failures were noted leading to loss of timestamp values as well as shorter battery lifetime due to re-transmission tries. In phase 2 (02 October 2019 to 17 October 2019), data was collected from 9 SUM and only stored locally on SD cards. The time of data collection was recorded using an external RTC clock connected to the Arduino board. The data from both phases of study is deposited here along with the metadata.
DOI: 10.5281/zenodo.4162104
title: Dataset for MD and MM/GBSA-Based Evalulation of Ternary Complexes Induced by Proteolysis Targeting Chimeras (PROTACs) for Targeted Protein Degradation

description: This is the dataset for all input files, output files/results, and submit script or its templates for running the MD and MMGBSA calculations in the paper. Four compressed archives represent the 4 systems we ran our simulations on. The general workflow for all systems follow the sequence of, after starting pose generated by protein docking, the starting frame for MD and its parameter file is generated in the Tleap folder; the MD trajectories are found in the PMEMD folders; and the energy calculations are found in the MMGBSA folders.
DOI: 10.5281/zenodo.4162103
title: Dataset for MD and MM/GBSA-Based Evalulation of Ternary Complexes Induced by Proteolysis Targeting Chimeras (PROTACs) for Targeted Protein Degradation

description: This is the dataset for all input files, output files/results, and submit script or its templates for running the MD and MMGBSA calculations in the paper. Four compressed archives represent the 4 systems we ran our simulations on. The general workflow for all systems follow the sequence of, after starting pose generated by protein docking, the starting frame for MD and its parameter file is generated in the Tleap folder; the MD trajectories are found in the PMEMD folders; and the energy calculations are found in the MMGBSA folders.
DOI: 10.18434/mds2-2316
title: Precision spectroscopy of nitrous oxide isotopocules with a cross-dispersed spectrometer and a mid-infrared frequency comb
DOI: 10.21227/6dtc-gs77
title: wind -Part 1

description: This dataset is in support of my original Research Paper " Grid-Connected Wind " submitted to "IEEE Transactions on Energy Conversion". (https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=60).This experiment is different from the exisiting approaches in the following ways(a)(b)(c)(d)(e)Abstract of the above submitted paper
DOI: 10.21227/by7m-gr04
title: wind-Part 2

description: This dataset is in support of my original Research Paper " Grid-Connected Wind " submitted to "IEEE Transactions on Energy Conversion". (https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=60)This dataset is related toThis experiment is different from the exisiting approaches in the following ways(a)(b)(c)(d)(e)Abstract of the above submitted paper
DOI: 10.21227/2crd-1y62
title: wind 3

description: This dataset is in support of my original Research Paper " Grid-Connected Wind " submitted to "IEEE Transactions on Energy Conversion". (https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=60)usaAbstract of the above submitted paper
DOI: 10.21227/5km1-5r55
title: wind -Part 1

description: This dataset is in support of my original Research Paper " Grid-Connected Wind " submitted to "IEEE Transactions on Energy Conversion". (https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=60).This dataset is related toThis experiment is different from the exisiting approaches in the following ways(a)(b)(c)(d)(e)This simulation is taken into consideration for the India, Delhiconditions, where the substation is of the local DISCOM,viz., BSES (Bombay Suburban Electric Supply),RajDhaniAbstract of the above submitted paper
DOI: 10.6084/m9.figshare.13204943
title: R0221-DLC_output

description: deeplabcut output and processed 3D reconstructions of data for rat 0221."_direct" zip files contain .csv's from the direct view and .mat files with cropping regions"_right/left" zip files contain .csv's from the mirror view and .mat files with cropping regions"_processed" files contain 3D reconstructions and reach analyses