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  • The dataset contains multiple instances of 9 Activities of Daily Living (ADL)-related actions namely Walk, Sit Down, Stand Up, Open Door, Close Door, Pour Water, Drink Glass, Brush Teeth and Clean Table. Each of the 10 volunteers performed each activity at least 14 times, with the notable exception of the walking activity that has been performed 40 times, in different sequences and alternating the used hand. For each volunteer, the dataset contains 7 CSV files, i.e., one file for each of the 6 IMU sensors worn by the volunteer on different body parts, as described in Figure 1, namely left lower arm (lla.csv), left upper arm, (lua.csv), right lower arm (rla.csv), right upper arm (rua.csv) and right thigh (rt.csv). Each file contains the overall sequence recorded during the experiment. The first column contains a label "qags" indicating the type of recorded data (quaternions, acceleration, angular velocity). The next column is the time-stamp in milliseconds elapsed from 00:00:0.000 AM (with a 30 milliseconds sampling time). The next four columns are the quaternions (with a resolution of 0.0001 ). Following them, we have three columns with the accelerations along the x, y and z axes (with a 0.1 mG resolution). The last three columns refer to the angular velocity about the x, y and z axes (with a 0.01 dps resolution). The last CSV file (annotation.csv) contains the data labelling. The first two columns of this file contain the time in the format hh.mm.ss.000 (current day time) and in milliseconds elapsed from 00:00:0.000 AM. All the remaining columns are organised as couples where the first element represents the scope of the labelling and the second indicates whether the labelled activity is starting or ending. In the annotation file, there are four different labelling scopes. • “BothArms”: all instances of each activity are labelled independently of which arm has been used; • “RightArm”: are labelled the activity instances using only the right arm, or in case they belong to the Walk, Sit Down or the Stand Up activities; • “LeftArm”: are labelled the activity instances using only the left arm, or in case they belong to the Walk, Sit Down or the Stand Up activities; • “Locomotion”: in this scope are labelled only the instances of Walk, Sit Down and Stand Up. Finally, the last two columns report a session ID. There are four different sessions characterised by the order in which the activities are performed, and by the used arm (see also Table 3), and whether the session starts or ends. The videos recorded during the experiments have been only used for labelling purposes, and they are not published. Together with the dataset, we provide a MATLAB script named TimeStampExtraction.m that extract from the annotation and the data files, for each volunteer and for each sensor, the time stamp associated with the start and end of each ADL.
    Data Types:
    • Software/Code
    • Tabular Data
    • Dataset
  • Raw data : Use of aquaculture ponds by globally endangered red-crowned crane (Grus japonensis) during wintering period in the Yancheng National Nature Reserve, a Ramsar wetland
    Data Types:
    • Tabular Data
    • Dataset
  • Exploring the interactions between telecom vs investment, telecom vs trade, telecom vs policies and telecom, and rising prices from end-user subscriptions. Insight from a dynamic panel threshold regression
    Data Types:
    • Tabular Data
    • Dataset
  • These data were gathered from the NSQIP participant use file from the years 2012-2016 and contain all patients who underwent hysterectomy and who are Hispanic or non-Hispanic and white. Patients with cancer diagnoses or who underwent staging procedures were excluded. We used these data to determine the risk of postoperative morbidity for Hispanic patients, and identified an elevated risk of blood transfusion.
    Data Types:
    • Tabular Data
    • Dataset
  • A video of experiment of peg-in-hole
    Data Types:
    • Video
    • Dataset
  • Inhibiting the main proteasome of severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2) may serve as a treatment option for patients suffering from COVID-19. Inhibition of the main proteasome (SARS-CoV-2 Mpro) may improve patient outcomes and recovery through blocking viral replication and assembly. A literature review of potential drug treatments for COVID-19 included Nelfinavir, an HIV antiviral, and Epirubicin, an anthracycline and topoisomerase inhibitor. The mechanism of action for both drugs includes binding to SARS-CoV-2 Mpro. These data highlight in-silico binding pose energy predictions of SARS-CoV-2 Mpro (receptor) each of the two drug targets (ligands) using a Generic Evolutionary Method for Molecular Docking (iGEMDOCK). In-silico screening provides highly accurate, reproducible complex-ligand binding affinity prediction data. These data are derived from a population size of 200 and 70 docking generation trials. The 3-D Protein Data Bank (PDB) structure of the main proteasome (SARS-CoV-2 Mpro) for this investigation was derived from the RCSB Protein Data Bank (PDB ID: 6LU7). The 3-D structures of Nelfinavir and Epirubicin were derived from the PubChem database (PubChem CIDs 64143, 41867 respectively). The 3-D structures were converted from 3D conformer SDF files to Protein Data Bank (PDB) formatting through OpenBabble. The data show Nelfinavir as outcompeting Epirubicin in binding to the main proteasome (SARS-CoV-2 Mpro). The complex formation with Nelfinavir was more energetically favorable than that with Epirubicin. The data include relevant binding site residues and energy values, in units of kcal/mol. A composite of van der Waals forces, hydrogen bonding, and electrostatic charge provide the energy values.
    Data Types:
    • Tabular Data
    • Dataset
    • Document
  • Processed data used in the article "Physical and chemical properties of natural latex biomembranes associated with phototherapy designed for healing diabetic foot ulcers". We performed physical and chemical tests to evaluate the membranes: Tensile Strength Test, Thermogravimetric Analysis, Wettability Assay and Fourier-transform infrared spectroscopy.
    Data Types:
    • Tabular Data
    • Dataset
  • These data are derived from the project CONICYT/FONDECYT (grant number: 1171171) entitled "Seawater intrusions into the Valdivia-Tornagaleones estuarine system today and under future scenarios with increasing greenhouse-gas concentrations" The first sheet corresponds to records every 5 minutes of salinity and depth derived from a CTD installed at the bottom of the Río Valdivia (73,278°W, 39,8511°S) from November, 22, 2017 to July, 31, 2018. The CTD’s conductivity sensor unfortunately was configured for the range 13 a 63 mS cm-1, meaning that only salinities above about 9 PSU, depending on the river’s bottom temperature could be measured. The following sheets are hydrographic measurements, CTD casts, which were carried out along the central axes of the Valdivia river estuary between November 2017 and August 2018 just covering all four seasons of the year. CTD profiles were measured at 14 about equally spaced stations along the Valdivia river estuary during both, spring and neap tide periods of all seasons. The profiles were taken with a horizontally configured and mounted pumped Seabird 25 CTD, which allowed a slow sampling from close to the surface to close to the bottom. The raw data were processed following the manufactures guidelines and were averaged to a vertical resolution of 0.25 m. Only pressure and salinity (PSU) are available. The dates of the individual short cruises involved were 29/11/2017 (sheet 2017_11_29_spring_season_neap_t), 06/12/2017 (sheet 2017_12_06_spring_season_spring), 11/01/2018 (sheet 2018_01_11_summer_season_neap_t), 01/02/2018 (sheet 2018_02_01_summer_season_spring), 08/05/2018 (sheet 2018_05_08_fall_season_neap_tid), 17/05/2018 (sheet 2018_05_17_fall_season_spring_t), 19/08/2018 (sheet 2018_08_19_winter_season_neap_t), 12/08/2018 (sheet 2018_08_12_winter_season_spring)
    Data Types:
    • Tabular Data
    • Dataset
  • This dataset consists of COVID-19 time series data of India since 24th March 2020. The data set is for all the States and Union Territories of India and is divided into five parts, including i) Confirmed cases; ii) Death Count; iii) Recovered Cases; iv) Temperature of that place; and v) Percentage humidity in the region. The data set also provides basic details of confirmed cases and death count for all the countries of the world updated daily since 30 January 2020. The end user can contact the corresponding author (Rohit Salgotra : nicresearchgroup@gmail.com) for more details. . [Dataset is updated Thrice a Week]
    Data Types:
    • Tabular Data
    • Dataset
  • Neutron spectrum for PuBe source 54/02-107-6228 at IFIN-HH, Romania Full neutron spectrum, neutron spectrum in coincidence with the 4.4 MeV gamma ray, neutron spectrum to the ground state without gamma coincidence Smoothed once using algorithm 353QH P.-A. Söderström, Characterization of a plutonium-beryllium neutron source, Appl. Radiat. Isot., submitted
    Data Types:
    • Dataset
    • Text
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