cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc25pv2t
title: CCDC 2016986: Experimental Crystal Structure Determination

description: Related Article: Hideki Hayashi, Joshua E. Barker, Abel Cárdenas Valdivia, Ryohei Kishi, Samantha N. MacMillan, Carlos J. Gómez-García, Hidenori Miyauchi, Yosuke Nakamura, Masayoshi Nakano, Shin-ichiro Kato, Michael M. Haley, Juan Casado|2020|J.Am.Chem.Soc.|142|20444|doi:10.1021/jacs.0c09588
DOI: 10.5517/ccdc.csd.cc25pv3v
title: CCDC 2016987: Experimental Crystal Structure Determination

description: Related Article: Hideki Hayashi, Joshua E. Barker, Abel Cárdenas Valdivia, Ryohei Kishi, Samantha N. MacMillan, Carlos J. Gómez-García, Hidenori Miyauchi, Yosuke Nakamura, Masayoshi Nakano, Shin-ichiro Kato, Michael M. Haley, Juan Casado|2020|J.Am.Chem.Soc.|142|20444|doi:10.1021/jacs.0c09588
DOI: 10.5517/ccdc.csd.cc25pv4w
title: CCDC 2016988: Experimental Crystal Structure Determination

description: Related Article: Hideki Hayashi, Joshua E. Barker, Abel Cárdenas Valdivia, Ryohei Kishi, Samantha N. MacMillan, Carlos J. Gómez-García, Hidenori Miyauchi, Yosuke Nakamura, Masayoshi Nakano, Shin-ichiro Kato, Michael M. Haley, Juan Casado|2020|J.Am.Chem.Soc.|142|20444|doi:10.1021/jacs.0c09588
DOI: 10.5517/ccdc.csd.cc25pv5x
title: CCDC 2016989: Experimental Crystal Structure Determination

description: Related Article: Hideki Hayashi, Joshua E. Barker, Abel Cárdenas Valdivia, Ryohei Kishi, Samantha N. MacMillan, Carlos J. Gómez-García, Hidenori Miyauchi, Yosuke Nakamura, Masayoshi Nakano, Shin-ichiro Kato, Michael M. Haley, Juan Casado|2020|J.Am.Chem.Soc.|142|20444|doi:10.1021/jacs.0c09588
DOI: 10.17632/2v9g232kjs.1
title: An effective scheme to determine surface energy and its relation with adsorption energy

description: All data associated with this work
DOI: 10.5517/ccdc.csd.cc25pv6y
title: CCDC 2016990: Experimental Crystal Structure Determination

description: Related Article: Hideki Hayashi, Joshua E. Barker, Abel Cárdenas Valdivia, Ryohei Kishi, Samantha N. MacMillan, Carlos J. Gómez-García, Hidenori Miyauchi, Yosuke Nakamura, Masayoshi Nakano, Shin-ichiro Kato, Michael M. Haley, Juan Casado|2020|J.Am.Chem.Soc.|142|20444|doi:10.1021/jacs.0c09588
DOI: 10.5517/ccdc.csd.cc2671yg
title: CCDC 2032575: Experimental Crystal Structure Determination

description: Related Article: Francesca Milocco, Folkert de Vries, Imke M. A. Bartels, Remco W. A. Havenith, Jordi Cirera, Serhiy Demeshko, Franc Meyer, Edwin Otten|2020|J.Am.Chem.Soc.|142|20170|doi:10.1021/jacs.0c10010
DOI: 10.5517/ccdc.csd.cc2671zh
title: CCDC 2032576: Experimental Crystal Structure Determination

description: Related Article: Francesca Milocco, Folkert de Vries, Imke M. A. Bartels, Remco W. A. Havenith, Jordi Cirera, Serhiy Demeshko, Franc Meyer, Edwin Otten|2020|J.Am.Chem.Soc.|142|20170|doi:10.1021/jacs.0c10010
DOI: 10.5517/ccdc.csd.cc26720k
title: CCDC 2032577: Experimental Crystal Structure Determination

description: Related Article: Francesca Milocco, Folkert de Vries, Imke M. A. Bartels, Remco W. A. Havenith, Jordi Cirera, Serhiy Demeshko, Franc Meyer, Edwin Otten|2020|J.Am.Chem.Soc.|142|20170|doi:10.1021/jacs.0c10010
DOI: 10.5517/ccdc.csd.cc26721l
title: CCDC 2032578: Experimental Crystal Structure Determination

description: Related Article: Francesca Milocco, Folkert de Vries, Imke M. A. Bartels, Remco W. A. Havenith, Jordi Cirera, Serhiy Demeshko, Franc Meyer, Edwin Otten|2020|J.Am.Chem.Soc.|142|20170|doi:10.1021/jacs.0c10010
DOI: 10.5517/ccdc.csd.cc26722m
title: CCDC 2032579: Experimental Crystal Structure Determination

description: Related Article: Francesca Milocco, Folkert de Vries, Imke M. A. Bartels, Remco W. A. Havenith, Jordi Cirera, Serhiy Demeshko, Franc Meyer, Edwin Otten|2020|J.Am.Chem.Soc.|142|20170|doi:10.1021/jacs.0c10010
DOI: 10.5517/ccdc.csd.cc26724p
title: CCDC 2032581: Experimental Crystal Structure Determination

description: Related Article: Francesca Milocco, Folkert de Vries, Imke M. A. Bartels, Remco W. A. Havenith, Jordi Cirera, Serhiy Demeshko, Franc Meyer, Edwin Otten|2020|J.Am.Chem.Soc.|142|20170|doi:10.1021/jacs.0c10010
DOI: 10.17632/s3jdcpvvrk.1
title: Scatter plot of the duration of pruritus and total IgE level

description: Scatter plot of the duration of pruritus and total IgE level (r = 0.502, p-value &lt; 0.001)
DOI: 10.5517/ccdc.csd.cc26723n
title: CCDC 2032580: Experimental Crystal Structure Determination

description: Related Article: Francesca Milocco, Folkert de Vries, Imke M. A. Bartels, Remco W. A. Havenith, Jordi Cirera, Serhiy Demeshko, Franc Meyer, Edwin Otten|2020|J.Am.Chem.Soc.|142|20170|doi:10.1021/jacs.0c10010
DOI: 10.5517/ccdc.csd.cc26ngcq
title: CCDC 2045453: Experimental Crystal Structure Determination

description: Related Article: Andrés Zavaleta, Aleksandr O. Lykhin, Jorge H. S. K. Monteiro, Shoto Uchida, Thomas W. Bell, Ana de Bettencourt-Dias, Sergey A. Varganov, Judith Gallucci|2020|J.Am.Chem.Soc.|142|20306|doi:10.1021/jacs.0c08182
DOI: 10.5517/ccdc.csd.cc26ngdr
title: CCDC 2045454: Experimental Crystal Structure Determination

description: Related Article: Andrés Zavaleta, Aleksandr O. Lykhin, Jorge H. S. K. Monteiro, Shoto Uchida, Thomas W. Bell, Ana de Bettencourt-Dias, Sergey A. Varganov, Judith Gallucci|2020|J.Am.Chem.Soc.|142|20306|doi:10.1021/jacs.0c08182
DOI: 10.5517/ccdc.csd.cc26ngfs
title: CCDC 2045455: Experimental Crystal Structure Determination

description: Related Article: Andrés Zavaleta, Aleksandr O. Lykhin, Jorge H. S. K. Monteiro, Shoto Uchida, Thomas W. Bell, Ana de Bettencourt-Dias, Sergey A. Varganov, Judith Gallucci|2020|J.Am.Chem.Soc.|142|20306|doi:10.1021/jacs.0c08182
DOI: 10.5517/ccdc.csd.cc26nggt
title: CCDC 2045456: Experimental Crystal Structure Determination

description: Related Article: Jeffrey S. Derrick, Matthias Loipersberger, Ruchira Chatterjee, Diana A. Iovan, Peter T. Smith, Khetpakorn Chakarawet, Junko Yano, Jeffrey R. Long, Martin Head-Gordon, Christopher J. Chang|2020|J.Am.Chem.Soc.|142|20489|doi:10.1021/jacs.0c10664
DOI: 10.5517/ccdc.csd.cc26nghv
title: CCDC 2045457: Experimental Crystal Structure Determination

description: Related Article: Jeffrey S. Derrick, Matthias Loipersberger, Ruchira Chatterjee, Diana A. Iovan, Peter T. Smith, Khetpakorn Chakarawet, Junko Yano, Jeffrey R. Long, Martin Head-Gordon, Christopher J. Chang|2020|J.Am.Chem.Soc.|142|20489|doi:10.1021/jacs.0c10664
DOI: 10.5517/ccdc.csd.cc26ngjw
title: CCDC 2045458: Experimental Crystal Structure Determination

description: Related Article: Jeffrey S. Derrick, Matthias Loipersberger, Ruchira Chatterjee, Diana A. Iovan, Peter T. Smith, Khetpakorn Chakarawet, Junko Yano, Jeffrey R. Long, Martin Head-Gordon, Christopher J. Chang|2020|J.Am.Chem.Soc.|142|20489|doi:10.1021/jacs.0c10664
DOI: 10.17632/3v5ygd2gbz.3
title: Analysis of psoriasis-related posts on Twitter: an abundance of patient-driven advocacy versus a scarcity of dermatologists

description: Supplemental Tables
DOI: 10.17632/mtf4h8yjtw.1
title: Supporting Information for 'Mesozoic South-dipping Subduction History at Southern Tethys Ocean Constrained from Global Tectonic Reconstructions and Seismic Tomography'

description: Supporting Information for 'Mesozoic South-dipping Subduction History at Southern Tethys Ocean Constrained from Global Tectonic Reconstructions and Seismic Tomography' by Yan Peilong, Zhang Nan, Yuan Huaiyu and Liu Xiaoxu
DOI: 10.17632/r9tns5rd74.1
title: brGDGTs-based temperatures during the last deglaciation in Jierguoshan Tianchi (Moon Lake)

description: This dataset includes a time series of reconstructed summer temperature during the last deglaciation from the crater lake Jierguoshan Tianchi (Moon Lake) , Northeast China.
DOI: 10.17632/jksms4mb65.1
title: Jalgine merino 2020

description: RAW files for genome-wide association study (GWAS) of the frequency of occurrence of individual SNPs using the Ovine Infinium HD BeadChip 600K in sheep of the Jalgin merino breed with different class evaluations according to the phenotype determining productive qualities. Data presented in PLINK format.
DOI: 10.17632/zw6ypk5345.1
title: Emoji Extractions from Geotagged Twitter Data

description: We provide a filtered, pre-processed and anonymized dataset collected originally from the Twitter decahose (a random 10% sample of Twitter) over 29 days in October, 2016, to support computational social science research on how people on Twitter use emojis. The data comprises of a table with four columns and 4,057,872 rows (including a header). The fields of the table are: ID: A unique tweet ID that could also be used to ‘hydrate’ the contents of the tweet directly from Twitter. Country: The country code associated with the tweet. Language: The language metadata tag associated with the tweet. We only retain the top 30 languages (sorted by frequency of tweets) in our initial corpus. Emojis: The emojis extracted from the ‘text’ field of the tweet. The methodology that was used to extract the tweets is described in the next section. A paper that uses the data as the basis for its findings and also contains descriptive statistics: M. Kejriwal, Q. Wang, H. Li, L. Wang, An Empirical Study of Emoji Usage on Twitter in Linguistic and National Contexts. Online Social Networks and Media. In Press.
DOI: 10.17632/2b3x7pgmfx.2
title: Supporting information to the Data in Brief co-submission "Experimental and Computational Data on Two-Photon Absorption and Spectral Deconvolution of the Upper Excited States of Dye IR780"

description: The data presented here are experimental results on the two-photon absorption properties of cyanine dye IR780. The file 2PA_IR780_slopes_2.xlsx features the raw data of the logarithm of the integrated fluorescence vs. the logarithm of the peak intensity and the lines of best fit for each plot. This Excel file is organized into several tabs, each labelled with the excitation wavelength used to irradiate our samples (Rhodamines 6G and B as well as IR780); these data were featured in the Data in Brief manuscript entitled "Experimental and Computational Data on Two-Photon Absorption and Spectral Deconvolution of the Upper Excited States of Dye IR780". The file deconvolution_N_peaks.xlsx features the raw data of the deconvolution of the absorption spectrum of the upper excited states of IR780 with 5, 6, 7, 8 and 9 Gaussian functions. This Excel file contains several tabs, the first one of them being the experimental absorption spectrum of IR780; the rest of the tabs are labelled by the number of Gaussian functions employed in the deconvolution; these data were featured in the Data in Brief manuscript mentioned above. The information contained in this file shows the assignment of the bands pertaining to electronic states S2-S6; the 8-peak and 9-peak fits show suitable R-Square and Reduced Chi-Sqr values that demonstrate the coexistence of said electronic states in the spectral region 18350 - 35980 cm-1.
DOI: 10.17632/nfy7gxg38p.1
title: sandstone petrography and whole-rock geochemistry and detrital zircon geochronology results from the Sanjiang Basin

description: Table S1: Content of each mineral for the six sandstone samples Table S2: Major (wt%) and trace (ppm) elemens data for the Mesozoic strata in the Sanjiang Basin Table S3: Detrital zircons U-Pb dating data for sandstone in the Sanjiang Basin Table S4: Lu–Hf isotopic data for detrital zircons from Mesozoic strata in the Sanjiang Basin
DOI: 10.17632/p7zwd533tk.1
title: Data of The Effects of Social Commerce Environmental Characteristics on Customers' Purchase Intentions: The Chain Mediating Effect of Customer-to-Customer Interaction and Customer-perceived Value

description: Based on the Stimulus-Organism-Response model, this paper built a chained mediating model to reveal the relationships between environmental factors and customer behavior. H1a: The relationship between the interactivity and customers’ product interaction is an inverted U-shaped curve. H1b: The relationship between interactivity and customers’ interpersonal interaction is an inverted U-shaped curve. H2: The stickiness has a positive influence on customers’ product interaction(H2a) and interpersonal interaction(H2b). H3: The personalization has a positive influence on customers’ product interaction(H3a) and interpersonal interaction(H3b). H4: The sociability has a positive influence on customers’ product interaction(H4a) and interpersonal interaction(H4b). H5: Product interaction has a positive influence on customer-perceived functional value(H5a), emotional value (H5b), and social value(H5c). H6: Product interaction has a positive influence on customer-perceived functional value(H6a), emotional value (H6b), and social value(H6c). H7: Customer-perceived functional value(H7a), emotional value(H7b), and social value(H7c) have a positive influence on purchase intentions. H8a: The relationship between the interactivity of social commerce and purchase intentions is an inverted U-shaped curve. H8b: The stickiness has a positive influence on purchase intentions. H8c: The personalization has a positive influence on purchase intentions. H8d: The sociability has a positive influence on purchase intentions. H9: Customer-to-customer interaction mediates the effect of interactivity(H9a), stickiness(H9b), personalization(H9c), and sociability(H9d) on purchase intentions. H10: Customer-perceived value mediates the effect of interactivity(H10a), stickiness(H10b), personalization(H10c), and sociability(H10d) on purchase intentions. H11: Customer-to-customer interaction and customer-perceived value have a chain mediating effect between interactivity(H11a), stickiness(H11b), personalization(H11c), and sociability(H11d) and purchase intentions. Empirical analyses showed that four technical environmental characteristics will increase customers’ purchase intentions through customer-to-customer interaction and perceived value. One of these characteristics, “interactivity,” has inverted U-shaped influential effects on the whole pathway. On the other hand, three others—stickiness, personalization, and sociability—have linear influential effects.
DOI: 10.17632/hjkbkkktsc.1
title: Mt. Tai O3 datasets

description: Archived here are the observation data (hourly resolution) in 2018 at Mt. Tai as well as the LPTM output discussed in the paper: Zhang, Y., Xue, L., Li, H., Chen, T., Mu, J., Dong, C., Sun, L., Liu, H., Zhao, Y., Wu, D., Wang, X., and Wang W.: Source Apportionment of Regional Ozone Pollution Observed at Mount Tai, North China: Application of Lagrangian Photochemical Trajectory Model and Implications for Control Policy, Journal of Geophysical Research., in revirw, 2020
DOI: 10.17632/w8wk4h9hxc.1
title: Airfares in New Zealand

description: This dataset presents the domestic airfares of New Zealand’s airlines (dominating by Air New Zealand, a full-service carrier; and Jetstar, a low-cost carrier) at 12 trunk routes and 40 secondary routes in New Zealand. The data was extracted from Expedia, one of the biggest online travel meta-search engine, using a ‘web crawler’ (Octoparse.com) that collects hourly airfares of the two airlines from September 19, 2019 to December 18, 2019, a total of 90 days. It therefore provides a rich dataset of more than 162,000 observations regarding the departure time, arrival time, flight duration, airline, airfare, departure airport, arrival airport, transiting airport, and so on… That information can be conveniently used in future studies in the fields of business and economics, transportation and aviation, or management and marketing.
DOI: 10.17633/rd.brunel.13347461
title: The Stay

description: The Stay premiered at the 25th World Horror Convention & Bram Stoker Awards Weekend, USA, Atlanta, 7 May 2015.<br>TheStayTrailer - YouTube<br>The Stay (2015) - IMDb<br><br><br>
DOI: 10.17632/cpf6hvb5zs.1
title: 111

description: 111
DOI: 10.17633/rd.brunel.13347461.v1
title: The Stay

description: The Stay premiered at the 25th World Horror Convention & Bram Stoker Awards Weekend, USA, Atlanta, 7 May 2015.<br>TheStayTrailer - YouTube<br>The Stay (2015) - IMDb<br><br><br>
DOI: 10.17632/49hxy87f2s.1
title: Data for: High-resolution cooperate density inversion method for the joint inversion of gravity and its gradient data its application to mineral exploration

description: This Dataset contains four folders, which names are Model1 to Model3 and field data.
DOI: 10.17632/fbztn8bjp9.1
title: Human cytomegalovirus is present in the odontogenic epithelium of ameloblastoma

description: Data
DOI: 10.17632/f3jb5cztv6.1
title: Dataset#2 Archaeozoology of the Late Bronze Age settlements of the South Urals

description: The dataset contains tabular data, images of the environment and grazing of livestock in the South Urals, images of modification changes in bones, bone tools and flakes, evidence of osteophagy in cattle, as well as all identified pathologies of livestock. The material comes from four Late Bronze Age settlements (Zvyagino-4, Malaya Berezovaya-4, Bolshaya Berezovaya-2, Aleksandro-Nevskoe-2) in the Southern Urals (Alakul culture).
DOI: 10.17632/6ypp36rmc3.1
title: Dataset#1 Archaeozoology of the Late Bronze Age settlements of the South Urals

description: The dataset contains primary data, results of bone measurements, a list and description of pathologies of livestock from 4 settlements of the Late Bronze Age in the Southern Urals (Zvyagino-4, Malaya Berezovaya-4, Bolshaya Berezovaya-2, Aleksandro-Nevskoe-2).
DOI: 10.17632/p6sf6wtdvy.1
title: 230Th-normalised 232Th fluxes in sediment cores from the tropical Atlantic

description: In this dataset we have compiled 230Th-normalised 232Th flux data from previously published studies of tropical Atlantic sediment cores. The dataset covers the time period from the late Holocene to the last glacial maximum (~0-25 thousand years ago). The flux data are derived from measurements of 238U, 230Th and 232Th concentrations in sediment cores, mostly derived from ICPMS, with some alpha spectrometry. These data are used to infer past patterns and magnitudes of terrigenous inputs to the tropical Atlantic and how this relates to climate changes and processes.
DOI: 10.17632/dxtzpvv83k.3
title: mouse_connectome_voxelwise

description: Data used for the project entitled "Network structure of the mouse brain connectome with voxel resolution". Please cite our work if you use the data contained in this folder.
DOI: 10.17632/rnkkhwr2ch.1
title: SPunaDataset

description: This dataset was used in Delph et al (JGR), but proper acknowledgements should be given to the authors of the original data compilation: Geochemical data: see references in excel file Shear-wave velocity volume (JOINT_Vs_200_50_100.txt): Delph et al. 2017, EPSL P-wave attenuation volume (SPuna_Qp_model.txt): Liang et al. 2014, JGR
DOI: 10.17632/cv7x3yjnbj.1
title: Species Distribution Modelling and Kernel Density Analysis of Benthic Ecologically and Biologically Significant Areas (EBSAs) and Other Benthic Fauna in the Maritimes Region

description: We present input data and output maps for random forest species distribution models and kernel density estimation (KDE)-derived significant areas for benthic Ecologically and Biologically Significant Areas (EBSAs) and other benthic taxa in Fisheries and Oceans Canada’s Maritimes Region: Horse Mussel (Modiolus modiolus) Beds, Stalked Tunicate Fields, Sand Dollar Beds, Soft Coral Gardens, and Flabellum cup corals. Using a suite of sixty-six environmental variables derived from various sources and native spatial resolutions (available at DOI: 10.17632/34hhtjyyd3.1), random forest was employed to predict the probability of occurrence and biomass distribution of these taxa using data collected from DFO multispecies trawl surveys, DFO scallop stock assessment surveys, and targeted in situ benthic camera and/or video surveys. Random forest presence-absence models had excellent predictive capacity, with cross-validated Area Under the Receiver Operating Characteristic Curve (AUC) values ranging from 0.868 to 0.965. Significant concentrations (as defined by KDE) of these taxa are considered conservation priorities in the Scotian Shelf Bioregional Marine Protected Area (MPA) Network Design Strategy, and are currently being used in exploratory conservation planning analyses. Data include KDE polygons and associated position of trawl sets used to delineate the polygons, presence/absence and biomass data used for the random forest analyses, and the random forest model outputs and areas of extrapolation in GIS format. Please refer to the following citation for additional details on the data: Beazley, L., Kenchington, E., and Lirette, C. 2017. Species Distribution Modelling and Kernel Density Analysis of Benthic Ecologically and Biologically Significant Areas (EBSAs) and Other Benthic Fauna in the Maritimes Region. Can. Tech. Rep. Fish. Aquat. Sci. 3204: vi + 159p.
DOI: 10.17632/45f952y38r.4
title: KU-HAR: An Open Dataset for Human Activity Recognition

description: (Please use this version of the dataset) Human Activity Recognition (HAR) refers to the capacity of machines to perceive human actions. This dataset contains information on 18 different activities collected from 90 participants (75 male and 15 female) using smartphone sensors (Accelerometer and Gyroscope). It has 1945 raw activity samples collected directly from the participants, and 20750 subsamples extracted from them. The activities are: Stand➞ Standing still (1 min) Sit➞ Sitting still (1 min) Talk-sit➞ Talking with hand movements while sitting (1 min) Talk-stand➞ Talking with hand movements while standing or walking(1 min) Stand-sit➞ Repeatedly standing up and sitting down (5 times) Lay➞ Laying still (1 min) Lay-stand➞ Repeatedly standing up and laying down (5 times) Pick➞ Picking up an object from the floor (10 times) Jump➞ Jumping repeatedly (10 times) Push-up➞ Performing full push-ups (5 times) Sit-up➞ Performing sit-ups (5 times) Walk➞ Walking 20 meters (≈12 s) Walk-backward➞ Walking backward for 20 meters (≈20 s) Walk-circle➞ Walking along a circular path (≈ 20 s) Run➞ Running 20 meters (≈7 s) Stair-up➞ Ascending on a set of stairs (≈1 min) Stair-down➞ Descending from a set of stairs (≈50 s) Table-tennis➞ Playing table tennis (1 min) Contents of the attached .zip files are: 1.Raw_time_domian_data.zip➞ Originally collected 1945 time-domain samples in separate .csv files. The arrangement of information in each .csv file is: Column 1, 5➞ exact time (elapsed since the start) when the Accelerometer & Gyro output was recorded (in ms) Col. 2, 3, 4➞ Acceleration along X,Y,Z axes (in m/s^2) Col. 6, 7, 8➞ Rate of rotation around X,Y,Z axes (in rad/s) 2.Trimmed_interpolated_raw_data.zip➞ Unnecessary parts of the samples were trimmed (only from the beginning and the end). The samples were interpolated to keep a constant sampling rate of 100 Hz. The arrangement of information is the same as above. 3.Time_domain_subsamples.zip➞ 20750 subsamples extracted from the 1945 collected samples provided in a single .csv file. Each of them contains 3 seconds of non-overlapping data of the corresponding activity. Arrangement of information: Col. 1–300, 301–600, 601–900➞ Acc.meter X, Y, Z axes readings Col. 901–1200, 1201–1500, 1501–1800➞ Gyro X, Y, Z axes readings Col. 1801➞ Class ID (0 to 17, in the order mentioned above) Col. 1802➞ length of the each channel data in the subsample Col. 1803➞ serial no. of the subsample Gravity acceleration was omitted from the Acc.meter data, and no filter was applied to remove noise. The dataset is free to download, modify, and use. More information is provided in the data paper which is currently under review: N. Sikder, A.-A. Nahid, KU-HAR: An open dataset for heterogeneous human activity recognition, Pattern Recognit. Lett. (submitted). A preprint will be available soon. Backup: drive.google.com/drive/folders/1yrG8pwq3XMlyEGYMnM-8xnrd6js0oXA7