cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.836514
title: Epigraph 1.3 Meteorological-Based Experimental Data

description: This file contains the complete data set of EpiGraph version 1.3.

EpiGraph is a scalable, fully distributed simulator that is able to perform large scale stochastic and realistic simulations of the propagation of the flu virus. The current implementation of EpiGraph allows modeling the population via a realistic local interconnection network based on actual individual interactions extracted from social networks and demographic data. At inter-urban scale, we use a transportation model which allows the study of the spatial dynamics of the virus propagation over large geographical areas. EpiGraph also includes a model of the interaction between influenza spreading and climatic and meteorological factors, such as temperature, atmospheric pressure and humidity levels. From the computational perspective, EpiGraph is a network I/O bound application written in C language and implemented on MPI. Internally, EpiGraph performs irregular memory access patterns related to sparse matrices used to model the individual interactions.

This distribution contains the meteorological-based experimental data used to run the experiments for the paper entitled <strong><em>Evaluating the impact of the weather conditions on the influenza propagation</em></strong>

<br>
In order to install this data set, you first need to install EpiGraph. You can download it from:

https://gitlab.arcos.inf.uc3m.es:8380/desingh/EpiGraph

Then, to install this package take the following steps:

1.- Download the file and place it in EpiGraphHome directory.

2.- Extract the tarbal in this directory. 

     tar -zxvf EpiGraph.1.3.DataMeteo.tar.gz
description: This work has been partially supported by the Spanish "Ministerio de Economía y Competitividad" under the project grant TIN2016-79637-P "Towards Unification of HPC and Big Data paradigms". The results of this work have been obtained from meteorological information provided by Spanish National Meteorological Agency, AEMET, Ministerio de Agricultura, Alimentación y Medio Ambiente.
DOI: 10.5281/zenodo.836515
title: Epigraph 1.3 Meteorological-Based Experimental Data

description: This file contains the complete data set of EpiGraph version 1.3.

EpiGraph is a scalable, fully distributed simulator that is able to perform large scale stochastic and realistic simulations of the propagation of the flu virus. The current implementation of EpiGraph allows modeling the population via a realistic local interconnection network based on actual individual interactions extracted from social networks and demographic data. At inter-urban scale, we use a transportation model which allows the study of the spatial dynamics of the virus propagation over large geographical areas. EpiGraph also includes a model of the interaction between influenza spreading and climatic and meteorological factors, such as temperature, atmospheric pressure and humidity levels. From the computational perspective, EpiGraph is a network I/O bound application written in C language and implemented on MPI. Internally, EpiGraph performs irregular memory access patterns related to sparse matrices used to model the individual interactions.

This distribution contains the meteorological-based experimental data used to run the experiments for the paper entitled <strong><em>Evaluating the impact of the weather conditions on the influenza propagation</em></strong>

<br>
In order to install this data set, you first need to install EpiGraph. You can download it from:

https://gitlab.arcos.inf.uc3m.es:8380/desingh/EpiGraph

Then, to install this package take the following steps:

1.- Download the file and place it in EpiGraphHome directory.

2.- Extract the tarbal in this directory. 

     tar -zxvf EpiGraph.1.3.DataMeteo.tar.gz
description: This work has been partially supported by the Spanish "Ministerio de Economía y Competitividad" under the project grant TIN2016-79637-P "Towards Unification of HPC and Big Data paradigms". The results of this work have been obtained from meteorological information provided by Spanish National Meteorological Agency, AEMET, Ministerio de Agricultura, Alimentación y Medio Ambiente.
DOI: 10.14457/kmutnb.the.2002.61
title: สมรรถภาพช่างฝีมืองานเชื่อมโลหะที่พึงประสงค์ตามความต้องการ ของสถานประกอบการอู่เรือเหล็กในประเทศไทย /
DOI: 10.14457/kmutnb.the.2002.62
title: กระบวนการสนับสนุนการตัดสินใจในการเลือกแนวทางการปรับผังโรงงาน กรณีศึกษา อุตสาหกรรมผลิตโซ่รถจักรยานยนต์ /
DOI: 10.14457/kmutnb.the.2002.63
title: การจัดตารางการผลิตในระบบการผลิตแบบไหล โดยสามารถจัดตารางการผลิตใหม่ได้ /
DOI: 10.14457/kmutnb.the.2002.64
title: การศึกษาประสิทธิภาพเพลาลูกเบี้ยวของเครื่องยนต์ 110 ซีซี. 4 จังหวะ สูบเดียว /
DOI: 10.14457/kmutnb.the.2002.65
title: การพัฒนาระบบสารสนเทศเพื่อรองรับการขยายงานของโครงการหนึ่งตำบล หนึ่งผลิตภัณฑ์ ในระดับจังหวัด บนเครือข่ายอินเตอร์เน็ต กรณีศึกษา : จังหวัดปราจีนบุรี /
DOI: 10.14457/kmutnb.the.2002.66
title: การปรับปรุงและการใช้งานระบบงานประมวลผลบนเครือข่ายการคำนวณกริด /
DOI: 10.14457/kmutnb.the.2002.67
title: การจัดตารางการทำงานของพนักงานแบบสับเปลี่ยนหน้าที่การทำงานสำหรับโรงภาพยนตร์ /
DOI: 10.4225/08/597e64001dcaf
title: RV Investigator Voyage IN2016_V05 End of Voyage (EOV) Archive

description: This record describes the End of Voyage (EOV) archive from the Marine National Facility (MNF) RV Investigator research voyage in2016_v05, titled "The Great Barrier Reef as a significant source of climatically relevant aerosol particles." The voyage took place from Brisbane (QLD) to Brisbane between September 28 and October 24, 2016.

This voyage consisted of three legs. Leg 1 started from Brisbane on September 28 and finished in Fitzroy Island on October 11. Leg 2 started in Fitzroy Island on October 11 and finished in Magnetic Island on October 16. Leg 3 started in Magnetic Island on October 16 and finished in Brisbane on October 24.

Supplementary project: Biogeochemical and optical properties of the Coral Sea and Queensland shelf.

Piggy-back project: Project 3DGBR - Multibeam bathymetry mapping of the Great Barrier Reef and Coral Sea.

For further information refer to the Voyage documentation links below.

Data collected include:
Acoustic Doppler Current Profiler (ADCP; 75, 150 KHz ), Fisheries echosounder (EK60),  Multibeam Echosounder (EM710, EM122), Sub-bottom Profiler (SBP120), Gravity Meter, GPS Positioning System, Doppler Velocity Log, Starboard and Portside Radiometers, Pyranometers, Radon, Ozone and Oxygen sensors,  Weather Radar, Greenhouse Gas Analysers (Aerodyne, Picarro), Air Pressure, Wind Speed and Direction sensors, Photosynthetically Active Radiation (PAR) sensor, Thermosalinograph, CTD, Expendable Bathythermographs (XBTs).

Voyage-specific data:
Aerosol Aerodynamic Particle sizer (APS), Aerosol Chemical Speciation Monitor (ACSM), Condensation Particle Counters (CPC),  Cloud Condensation Nuclei counter (CCN, ccnc), Gravity Meter, Hydrochemistry, Infrared Sea Surface Temperature Autonomous Radiometer (ISAR), Microwave Radiometer (MWR), Multiangle Absorption Photometer (MAAP), Nephelometer, pCO2 sensor, Scanning Mobility Particle Sizers (SMPS), Surface Velocity Program Drifters (SVP), Triaxus, ECO Triplet, Laser Optical Particle Counter (LOPC), Submersible Ultraviolet Nitrate Analyser (SUNA), Video.

The archive for the IN2016_V05 EOV raw data is curated by the CSIRO Oceans and Atmosphere (O&A) Information and Data Centre (IDC) in Hobart, with a permanent archive at the CSIRO Data Access Portal (DAP, https://data.csiro.au/dap/), providing access to participants and processors of the data collected in the voyage.

All voyage documentation is available electronically to MNF support via the local network. Access to voyage documentation for non-CSIRO participants can be made via DataLibrariansOAMNF@csiro.au.
DOI: 10.5281/zenodo.834786
title: Simulated Data For "Spot-On: Robust Model-Based Analysis Of Single-Particle Tracking Experiments"

description: <strong>Generation of simulated data</strong>

To systematically evaluate the performance of Spot-On as well as other common analysis tools such as MSD<sub>i</sub> and vbSPT, we considered a comprehensive set of 3480 realistic SPT simulations spanning the range of plausible dynamics. The simulations were performed using simSPT, which is freely available at GitLab: https://gitlab.com/tjian-darzacq-lab/simSPT. The simulation methods are described in detail at GitLab. A full description of the parameters which allows exact reproduction of the simulations is available together with the data (see Data Availability section). Briefly, we parameterized simSPT to consider that particles diffuse inside a sphere (the nucleus) of 8 µm diameter illuminated using HiLo illumination (assuming a HiLo beam width of 4 µm), with an axial detection range of ~700 nm, centered at the middle of the HiLo beam. Molecules are assumed to have a half-life of 4 frames (when inside the HiLo beam) and of 40 frames when outside the HiLo beam. The localization error was set to 25 nm and the simulation was run until 100000 in-focus trajectories were recorded. More specifically, the effect of the exposure time (1 ms, 4 ms, 7 ms, 13 ms, 20 ms), the free diffusion constant (from 0.5 µm²/s to 14.5 µm²/s in 0.5 µm²/s increments) and the fraction bound (from 0 % to 95 % in 5 % increments) were investigated, yielding a dataset consisting of 3480 simulations. The advantage of simulations is that the ground truth is known. This allows a quantitative assessment of which method works the best.

<strong>Content of the archives:</strong>


	170718_simSPT_simulations.zip  the code and instructions to reproduce the simulations
	4um.tar.bz2 simulated data inside a 4 µm nucleus
	20um.tar.bz2 simulated data inside a 20 µm nucleus, in which virtually no confinement occurs.
	subsampled.tar.bz2 is a set of subsampled datasets, containing either 99999, 30000, 10000, 3000, 1000, 300, 100 or 30 trajectories. Each subsampling was done 50 times, yielding 50 files per subsmpling.


<strong>Formats:</strong>

The data is provided both in CSV and .mat formats. .mat files are provided in the following dataset: 10.5281/zenodo.835541
DOI: 10.5281/zenodo.834787
title: Simulated Data For "Spot-On: Robust Model-Based Analysis Of Single-Particle Tracking Experiments"

description: <strong>Generation of simulated data</strong>

To systematically evaluate the performance of Spot-On as well as other common analysis tools such as MSD<sub>i</sub> and vbSPT, we considered a comprehensive set of 3480 realistic SPT simulations spanning the range of plausible dynamics. The simulations were performed using simSPT, which is freely available at GitLab: https://gitlab.com/tjian-darzacq-lab/simSPT. The simulation methods are described in detail at GitLab. A full description of the parameters which allows exact reproduction of the simulations is available together with the data (see Data Availability section). Briefly, we parameterized simSPT to consider that particles diffuse inside a sphere (the nucleus) of 8 µm diameter illuminated using HiLo illumination (assuming a HiLo beam width of 4 µm), with an axial detection range of ~700 nm, centered at the middle of the HiLo beam. Molecules are assumed to have a half-life of 4 frames (when inside the HiLo beam) and of 40 frames when outside the HiLo beam. The localization error was set to 25 nm and the simulation was run until 100000 in-focus trajectories were recorded. More specifically, the effect of the exposure time (1 ms, 4 ms, 7 ms, 13 ms, 20 ms), the free diffusion constant (from 0.5 µm²/s to 14.5 µm²/s in 0.5 µm²/s increments) and the fraction bound (from 0 % to 95 % in 5 % increments) were investigated, yielding a dataset consisting of 3480 simulations. The advantage of simulations is that the ground truth is known. This allows a quantitative assessment of which method works the best.

<strong>Content of the archives:</strong>


	170718_simSPT_simulations.zip  the code and instructions to reproduce the simulations
	4um.tar.bz2 simulated data inside a 4 µm nucleus
	20um.tar.bz2 simulated data inside a 20 µm nucleus, in which virtually no confinement occurs.
	subsampled.tar.bz2 is a set of subsampled datasets, containing either 99999, 30000, 10000, 3000, 1000, 300, 100 or 30 trajectories. Each subsampling was done 50 times, yielding 50 files per subsmpling.


<strong>Formats:</strong>

The data is provided both in CSV and .mat formats. .mat files are provided in the following dataset: 10.5281/zenodo.835541
DOI: 10.14457/kmutnb.the.2002.68
title: การลดต้นทุนการเคลือบผิวกระดาษด้วยการกำหนดเงื่อนไขที่เหมาะสม /
DOI: 10.14457/kmutnb.the.2002.69
title: การศึกษาผลกระทบของการวัดขนาดชิ้นงานรูปทรงผิวโค้ง 2 มิติ ด้วยวิธีพิกัดฉากกับพิกัดเชิงขั้ว /
DOI: 10.14457/kmutnb.the.2002.70
title: การศึกษาปัจจัยที่สำคัญสำหรับกระบวนการผลิตที่ไม่ต้องทำความสะอาด : กรณีศึกษา บริษัทเบนช์มาร์ค อิเล็กทรอนิกส์ (ประเทศไทย) จำกัด (มหาชน) /
DOI: 10.14457/kmutnb.the.2002.72
title: การสร้างและหาประสิทธิภาพชุดการสอน วิชาหลักการสื่อสารดาวเทียมหลักสูตรประกาศนียบัตรวิชาชีพ โรงเรียนจ่าอากาศ /
DOI: 10.14457/kmutnb.the.2002.73
title: การสร้างและหาประสิทธิภาพชุดการสอน วิชาความแข็งแรงของวัสดุ เรื่องหน่วยแรงในคาน /
DOI: 10.14457/kmutnb.the.2003.239
title: การพัฒนาบทเรียนคอมพิวเตอร์ช่วยสอนบนอินเตอร์เน็ต วิชาระบบเครือข่ายคอมพิวเตอร์สาขาคอมพิวเตอร์ธุรกิจ ระดับประกาศนียบัตรวิชาชีพชั้นสูง กรมอาชีวศึกษา /
DOI: 10.14457/kmutnb.the.2003.240
title: โปรแกรมบริหารงานเครื่องมือแพทย์ /
DOI: 10.4225/08/597e667e81357
title: Potential vegetation distribution: New South Wales - 3arcsecond gridded 1990-centred baseline predictions of the pre-clearing extents of "Keith" Vegetation Classes using kernel regression with GDM-scaled environments for Vascular Plants

description: This collection contains 3-arcsecond gridded datasets (ESRI binary float format in WGS84) showing the baseline (1990-centred) predicted potential distribution of 102 (class numbers range between 1 and 125) "Keith" Vegetation Classes for New South Wales based on their correlation with baseline ecological environments (c.1990 climates, substrate and landform). The vegetation patterns and classification derive from a map for NSW compiled by David Keith. A kernel regression was used with a geographically even sample of 9,951 locations of training classes for the 102 classes attributed with 21 GDM-scaled environmental predictors for Vascular Plants representing baseline ecological environments. The training class data input to the kernel regression is provided with this package. The GDM-scaled environmental predictors, source biological data and model fit parameters are also provided with the data package. Using the 1990 baseline training class data, and without constraining the prediction to pre-existing map boundaries, the kernel regression predicted the potential distribution of the 102 Vegetation Classes using 1990-centred (30 year average) baseline climates derived from ANUCLIM v6.1 (Xu and Hutchinson 2011) and soil/geology/landform attributes. The kernel regression generates unconstrained probabilities varying in the range from 0 and up to 1 for each of the 102 classes. The data are provided as 3-arcsecond (approximately 90m), ESRI binary float grid format in WGS84. Each class is denoted “UNCON###”, where the number refers to the code originally assigned to that class in the vegetation map. A lookup table linking the vegetation classes to the output codes and descriptive title is provided. The methods are described in "Doerr, VAJ, Williams, KJ, Drielsma, M, Doerr, ED, Davies, MJ, Love, J, Langston, A, Low Choy, S, Manion, G, Cawsey, EM, McGinness, HM, Jovanovic, T, Crawford, D, Austin, M & Ferrier, S 2013, Designing landscapes for biodiversity under climate change: Final report, National Climate Change Adaptation Research Facility, Gold Coast, 260 pp.". A plain English description of the method used (but applied Nationally) can be found in the AdaptNRM Guide “Helping biodiversity adapt to climate change: a community-level modelling approach”, available online at: www.adaptnrm.org. Source of vegetation class data: KEITH, D. A. (2002) A compilation map of native vegetation for New South Wales. NSW Biodiversity Strategy, New South Wales Government. KEITH, D. A. (2004) Ocean shores to desert dunes, Hurstville, Department of Environment and Conservation (NSW).
DOI: 10.5281/zenodo.835540
title: Simulated Data For "Spot-On: Robust Model-Based Analysis Of Single-Particle Tracking Experiments" (Matlab Format)

description: See 10.5281/zenodo.834787 for a more complete description.
DOI: 10.5281/zenodo.835541
title: Simulated Data For "Spot-On: Robust Model-Based Analysis Of Single-Particle Tracking Experiments" (Matlab Format)

description: See 10.5281/zenodo.834787 for a more complete description.
DOI: 10.17638/datacat.liverpool.ac.uk/377
title: Growth standard charts for monitoring bodyweight in dogs of different sizes - SUPPORTING DATA
DOI: 10.5517/ccdc.csd.cc1pdn91
title: CCDC 1561293: Experimental Crystal Structure Determination

description: Related Article: Milene Aparecida Rodrigues de Oliveira|2017|CSD Communication|||
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: 10.7301/z02v2d92
title: Data from "Local Interactions Underlying Collective Motion in Human Crowds"
DOI: 10.17632/j45zgyb3fv.1
title: Data for: Asymptotic *-moments of some random Vandermonde matrices

description: Mathematica files for the computations reported in Proposition 4.14.
DOI: 10.17632/j45zgyb3fv.2
title: Data for: Asymptotic *-moments of some random Vandermonde matrices

description: Mathematica files for the computations reported in Proposition 4.14.
DOI: 10.15472/4xlwgt
title: Caracterización de la avifauna en una zona delimitada entre los municipios de  Cumbitara, La Llanada, Policarpa y Los Andes Sotomayor (Nariño)

description: Caracterizar la avifauna en el polígono de la zona focalizada en Cumbitara, La Llanada, Policarpa y Los Andes Sotomayor (Nariño), para identificar áreas con valor de conservación dentro del proceso de planeación del paisaje rural como criterios para la definición de un Área Protegida y en la planeación para la recuperación de áreas que soportan servicios ecosistémicos en las zonas de bosque seco tropical.
DOI: 10.5517/ccdc.csd.cc1kv6yk
title: CCDC 1455169: Experimental Crystal Structure Determination

description: Related Article: A. Amani, Z. Derikvand, A. Azadbakht, B. Notash|2017|Iranian Journal of Crystallography and Mineralogy|25|199|
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.cc1pdrys
title: CCDC 1561406: Experimental Crystal Structure Determination

description: Related Article: S.N.Dmitrieva, A.I.Vedernikov, L.G.Kuz'mina, J.A.K.Howard, S.P.Gromov|2017|CSD Communication|||
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.cc1pdrzt
title: CCDC 1561407: Experimental Crystal Structure Determination

description: Related Article: S.N.Dmitrieva, A.I.Vedernikov, L.G.Kuz'mina, J.A.K.Howard, S.P.Gromov|2017|CSD Communication|||
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.cc1pj3p0
title: CCDC 1564622: Experimental Crystal Structure Determination

description: Related Article: Frank R. Fronczek|2017|CSD Communication|||
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.cc1pj3q1
title: CCDC 1564623: Experimental Crystal Structure Determination

description: Related Article: Frank R. Fronczek|2017|CSD Communication|||
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.cc1pdxkk
title: CCDC 1561549: Experimental Crystal Structure Determination

description: Related Article: Brian W. Skelton, Alan P. Arnold|2017|CSD Communication|||
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.cc1pj7dv
title: CCDC 1564737: Experimental Crystal Structure Determination

description: Related Article: Qiang Liu|2017|CSD Communication|||
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.cc1pf17d
title: CCDC 1561663: Experimental Crystal Structure Determination

description: Related Article: S.Z.Vatsadze, V.N.Nuriev, A.I.Vedernikov, L.G.Kuz'mina, J.A.K.Howard, S.P.Gromov|2017|CSD Communication|||
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.cc1pf18f
title: CCDC 1561664: Experimental Crystal Structure Determination

description: Related Article: Marilyn M. Olmstead, Bruce D. Hammock, Sung Hee Hwang|2017|CSD Communication|||
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.