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203 Research products, page 1 of 21

  • Research data
  • 2018-2022
  • Open Access
  • IE

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  • Open Access
    Authors: 
    Utkarsha Chavan;
    Publisher: Data Archiving and Networked Services (DANS)
    Countries: Ireland, Netherlands

    This is a sample calculation for the natural gas -hydrogen blend for two different gas samples. The composition of two natural gas samples is provided in two sheets. The calorific value is calculated for a blend with a molar composition of hydrogen varying from 0 to 20%. Along with calorific value (MJ/m3), Wobbe index (MJ/m3) and specific gravity are also calculated.

  • Research data . Film . 2022
    Open Access English
    Authors: 
    Stifter, David; Hayden, Deborah; White, Nora; Forsyth, Katherine; Kasten, Megan; Bălteanu, Daniel;
    Country: Ireland

    A short video about the AHRC/IRC-funded OG(H)AM project

  • Open Access English
    Authors: 
    Yan Yan; Kenneth Dawson; Gerard Cagney; Wei Zhang; Jingji Li; Camila P. Silveira; Qi Cai;
    Publisher: Zenodo
    Project: SFI | Defining the dynamic inte... (15/SIRG/3423)

    Recent observations suggest a role for complex nanoscale particulate shape in regulation of specific immune-related cellular and in vivo processes. We suspect that cellular recognition of nanostructure architecture could involve non-molecular inputs, including cellular transduction of nanoscale spatially resolved stresses induced by complex shape. Here we report nanoscale shape-dependent control of the cellular epigenome. ChIP-Seq sequencing datasets are provided.

  • Open Access
    Authors: 
    Bhupathi, Mohini; Devarapu, Ganga Chinna Rao;
    Publisher: Zenodo
    Project: EC | Career-FIT (713654), EC | Career-FIT (713654)

    The two datasets uploaded are the measurement of noise generated when the mobilefuge is placed on table with a damping pad or without a damping pad. We found that with the use of the damping pad, the noise recorded in the microphone decreased by 13dB indicating the improved stable operation of the mobilefuge.

  • Open Access English
    Authors: 
    Leahy, Paul G.; Ruth, Albert;
    Publisher: Zenodo
    Project: SFI | Paul Leahy (07/EN/E010), SFI | Paul Leahy (07/EN/E010)

    Vertical Profiles of Urban wind speed, wind direction and turbulence measured by LiDAR on campus of University College Cork, Ireland ================================= README version 1.3, 21/07/2022 ================================== Contact info: Paul Leahy, University College Cork paul.leahy@ucc.ie | +353 21 4902017 ================================ Contents 1. Measurement location and time period 2. What is measured (brief description) 3. Instrumentation 4. CSV file detailed descriptions ================================ 1. Measurement location and time period: North roof of Kane Building, University College Cork (UCC), Ireland. Lat 51 d 53 m 34 s N. Long 8 d 29 m 39 s W. Roof is c. 39 m above sea level, and c. 26 m above ground level (ground level reference point is the car park West of the UCC Kane Building). The measurements were taken over a time period of several months in the years 2013 / 2014. ================================= 2. What is measured (brief description): * LiDAR Wind speed (horizontal and vertical), wind direction, turbulence intensity at 5 altitudes; reference point (0 m) for these altitudes is the top of the LiDAR instrument c. 1.2 m above roof level. * Air temperature, atmospheric pressure, relative humidity. * Wind speed and direction from an ultrasonic anemometer mounted on top of the instrument (c. 1.2 m above roof level). * 10-minute average values (2 files) and high-resolution (c. 23 sec) data (1 file) are provided. See 'CSV file detailed description' below for detailed information. * Diagnostic information. ================================= 2.1 Surrounding terrain: Surrounding area is urban/suburban. The aspect is northerly. To the West: 2-5 storey buildings, open spaces, suburban. To the South: 2-3 storey buildings, open spaces, trees, river. To the East: 2-3 storey buildings, open spaces. To the North: A higher section of the Kane Building roof (47 m asl), 1-3 storey buildings, suburban. ================================= 3. Instrumentation: ZephIR 175 continuous wave wind profiling LiDAR with integrated sonic anemometer, temperature, humidity, air temperature pressure sensors and GPS. ================================= 4. CSV files detailed description: 4.1 Data on 10-minute averages: Filename 05092013-03122013_10min_res.csv contains: 10 minute averaged data from 05/09/2013 to 03/12/2013. Measurement altitudes: 148 m, 90 m, 69 m, 44 m, 19m above instrument level. Filename 03122013-07082014_10min_res.csv contains: 10 minute averaged data from: 03/12/2013 to 07/08/2014. Measurement altitudes: 148 m, 90 m, 50 m, 35 m, 15 m above instrument level. Note: from 19/06/2014 onwards, LiDAR data missing (MET data continues). The first two rows contain header information. Row 1 contains location information (GPS record)) and the measurement altitudes for wind speeds. Sample GPS record: N51535775W8296590 = 51 d 53.5775 m North; 8 d 29.6590 m West. Row 2 contains the data column headers including units. Wind speeds at each altitude are recorded: No of Packets (= number of scan units averaged over) [] Wind direction (mean) [deg] Horizontal wind speed (mean) & standard deviation [m/s] Vertical wind speed (mean) & standard deviation [m/s] Horizontal variance [m^2/s^2] Horizontal min [m/s] Horizontal max [m/s] TI (turbulence intensity) [] Other meteorological data: Air temperature [oC] Pressure [mbar] Rel. Humidity [%] Rain indicator [unitless] Higher values indicate more rain during the averaging interval. Wind Speed [m/s] (column 'MET Wind Speed' measured at the top of the instrument by the ultrasonic anemometer) Wind direction [deg] (column 'MET Direction' measured at the top of the instrument by the ultrasonic anemometer). Other housekeeping and diagnostic data: Instrument tilt [deg] Instrument bearing [deg] GPS data [degrees N, degrees W] Battery voltage [V] Optics, electronics and battery temperature [oC] ===================================================== 4.2 Data with high time resolution (~23 s): Filename 05092013-11112013_23s_res.csv contains: High resolution data from 05/09/2013 to 11/11/2013 Measurement altitudes: 148 m, 90 m, 69 m, 44 m, 19m. Note on time resolution: The time resolution of processed wind measurements is c. 3 seconds per wind level, and around 8 seconds to reset to the first level. A full wind profile measurement at 5 altitudes therefore takes around (5 x 3) + 8 = 23 s to complete. The raw scanning resolution of the instrument is higher than this, as each wind measurement is an average of several values. Row 1 contains location information (lat, long) and the vertical measurement levels for wind speeds. Row 2 contains the data column headers including units. Wind speeds at each altitude are recorded: No of Packets (= scan units averaged over) [] Wind direction (mean) [deg] Horizontal wind speed (mean) & standard deviation [m/s] Vertical wind speed (mean) & standard deviation [m/s] Horizontal variance [m^2/s^2] not defined as measurement interval is too short. Horizontal min [m/s] not defined as measurement interval is too short. Horizontal max [m/s] not defined as measurement interval is too short. TI (turbulence intensity) [] not defined as measurement interval is too short. Other meteorological data: Air temperature [oC] Pressure [mbar] Rel. Humidity [%] Rain indicator [unitless] Higher values indicate more rain during the scanning interval. Wind Speed [m/s] (column 'MET Wind Speed' measured at the top of the instrument by the ultrasonic anemometer) Wind direction [deg] (column 'MET Direction' measured at the top of the instrument by the ultrasonic anemometer. Other housekeeping and diagnostic data: Instrument tilt [deg] Instrument bearing [deg] GPS data [degrees N, degrees W] Battery voltage [V] Optics, electronics and battery temperature [oC] ===================================================== 4.3 Quality control indicators: 9998 atmospheric conditions which adversely affect LiDAR wind speed measurements e.g. fog 9999 high quality wind speed measurement not possible e.g. very low wind speed or obscuration of optical path Status Flag 'Green' => good ======================================================= Supported by University College Cork Strategic Research Fund and Science Foundation Ireland Stokes Lectureship in Wind Energy Engineering (grant no. 07/EN/E010), with support from Enerco Energy Ltd.

  • Open Access
    Authors: 
    Abgaz, Yalemisew; McCarren, Andrew; Buckley, Jim; Clarke, Paul;
    Publisher: Zenodo
    Project: SFI | Lero - the Irish Software... (13/RC/2094), SFI | Lero - the Irish Software... (13/RC/2094)

    This is the replication package for Decomposition of Monolithic Applications into Microservices Architectures: A Systematic Review Submitted to Transaction on Software Engineering Journal. Yalemisew Abgaz, Andrew McCarren, Peter Elger, David Solan, Neil Lapuz, Marin Bivol, Glenn Jackson, Murat Yilmaz, Jim Buckley, and Paul Clarke This package contains the following folders and files that provide additional insight to replicate the SLR. - Literature_Search_Strategy.pdf : A detailed description of the literature search outlining the steps and the results of the steps. - Literature_Search_Data: A folder containing the different stages of search results and refinements. It contains four files listing studies included from the 1st round to the 4th round of filtering. A description of each file is included in the Literature_Search_Strategy document. - Snowballing_Data: A folder containing the list of studies included in the snowballing process. - Data_Extraction.xlsx: The data extraction template and the summary of the memoing result. If you have futher questions regarding the survey, feel free to contact us via e-mail. Yalemisewm.abgaz@dcu.ie

  • Open Access
    Authors: 
    Yalemisew Abgaz; Paul M Clarke; Jim Buckley;
    Publisher: Zenodo
    Project: SFI | Lero - the Irish Software... (13/RC/2094), SFI | Lero - the Irish Software... (13/RC/2094)

    This is the replication package for Decomposition of Monolithic Applications into Microservices Architectures: A Systematic Review Submitted to Transaction on Software Engineering Journal. Yalemisew Abgaz, Andrew McCarren, Peter Elger, David Solan, Neil Lapuz, Marin Bivol, Glenn Jackson, Murat Yilmaz, Jim Buckley, and Paul Clarke This package contains the following folders and files that provide additional insight to replicate the SLR. - Literature_Search_Strategy.pdf : A detailed description of the literature search outlining the steps and the results of the steps. - Literature_Search_Data: A folder containing the different stages of search results and refinements. It contains four files listing studies included from the 1st round to the 4th round of filtering. A description of each file is included in the Literature_Search_Strategy document. - Snowballing_Data: A folder containing the list of studies included in the snowballing process. - Data_Extraction.xlsx: The data extraction template and the summary of the memoing result. If you have futher questions regarding the survey, feel free to contact us via e-mail. Yalemisewm.abgaz@dcu.ie

  • Open Access
    Authors: 
    Preethy Manoj (11407322); Rosemarie Derwin (7897721); Sherly George (7897907);
    Country: Ireland

    The findings of this review serve as a guideline in practice, education, research, and policy. Nonetheless, there is need for well-structured randomised controlled trials evaluating the effectiveness of Vitamin D3 plus calcium on the incidence of hip fracture and other fractures in older people.

  • Open Access English
    Authors: 
    Leitão, Catarina; Shumba, Jefrey; Quinn, Marian;
    Publisher: Zenodo
    Project: EC | PEAR_EC (890925), EC | PEAR_EC (890925)

    Data files related to the manuscript Perspectives and experiences of Covid-19: Two Irish studies of families in disadvantaged communities. The manuscript includes two studies. The following materials are shared below. Study 1: - Qualitative data (Microsoft Office Excel file) - Codebook for coding the qualitative data developed through content analysis (pdf file) Study 2: - Qualitative data (Microsoft Office Excel file) Data are named using the following naming convention: Project acronym_Date (YYYYMMDD)_Study_Type of data_Type of participant_Version number of the file. Both studies in the manuscript were developed by the Childhood Development Initiative (CDI), Dublin, Ireland. Study 1 was conducted within the project PEAR_EC, that has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 890925. Study 2 was conducted within the Child Poverty research project, funded by Tusla under the Area Based Childhood funding and the Child and Youth Participation Initiatives grant.

  • Research data . 2022
    Open Access English
    Authors: 
    Imran, Rahat;
    Publisher: Zenodo
    Project: EC | MUSLIMWOMENFILM (837154), EC | MUSLIMWOMENFILM (837154)

    MUSLIMWOMENFILM is a Horizon2020-funded interdisciplinary project that identifies a new object of study, Muslim women’s auto/biographical filmmaking, and maps the factors that make it distinctive within women’s and feminist cinema. As part of the project, this dataset of 290 auto/biographical film titles made by Muslim women filmmakers from Pakistan, Iran, Afghanistan, Bangladesh, and Turkey from the 1980s to date was created. The date of 1980 is significant of the advent and broad availability of video technologies, which facilitated independent filmmaking, new topics, wider audiences and exhibition, and the global emergence of a greater number of women filmmakers. The data was drawn from scholarly studies, industrial reports, governmental and non-governmental bodies, film festivals, and filmmakers’ websites. The resulting dataset includes essential data for each film, and categorizes them under a number of headings, selected to highlight important features of the films and of their auto/biographical approach. The categorization is discussed in the related text file. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 837154.

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