cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25606/surf.578c6039-8792b8cf
title: The Cosmogrid Simulation: Statistical Properties of Small Dark Matter Halos (2048-567)

description: We present the results of the "Cosmogrid" cosmological N-body simulation suites based on the concordance LCDM model. The Cosmogrid simulation was performed in a 30 Mpc box with 2048³ particles. The mass of each particle is 1.28x10^5 Msun, which is sufficient to resolve ultra-faint dwarfs. We found that the halo mass function shows good agreement with the Sheth & Tormen fitting function down to ~10^7 Msun. We have analyzed the spherically averaged density profiles of the three most massive halos which are of galaxy group size and contain at least 170 million particles. The slopes of these density profiles become shallower than -1 at the inner most radius. We also find a clear correlation of halo concentration with mass. The mass dependence of the concentration parameter cannot be expressed by a single power law, however a simple model based on the Press-Schechter theory proposed by Navarro et al. gives reasonable agreement with this dependence. The spin parameter does not show a correlation with the halo mass. The probability distribution functions for both concentration and spin are well fitted by the log-normal distribution for halos with the masses larger than ~10^8 Msun. The subhalo abundance depends on the halo mass. Galaxy-sized halos have 50% more subhalos than ~10^11 Msun halos have. This is snapshot 567 of the 2048³ resolution collection.
DOI: 10.25606/surf.578c6039-88c945ff
title: The Cosmogrid Simulation: Statistical Properties of Small Dark Matter Halos (2048-522)

description: We present the results of the "Cosmogrid" cosmological N-body simulation suites based on the concordance LCDM model. The Cosmogrid simulation was performed in a 30 Mpc box with 2048³ particles. The mass of each particle is 1.28x10^5 Msun, which is sufficient to resolve ultra-faint dwarfs. We found that the halo mass function shows good agreement with the Sheth & Tormen fitting function down to ~10^7 Msun. We have analyzed the spherically averaged density profiles of the three most massive halos which are of galaxy group size and contain at least 170 million particles. The slopes of these density profiles become shallower than -1 at the inner most radius. We also find a clear correlation of halo concentration with mass. The mass dependence of the concentration parameter cannot be expressed by a single power law, however a simple model based on the Press-Schechter theory proposed by Navarro et al. gives reasonable agreement with this dependence. The spin parameter does not show a correlation with the halo mass. The probability distribution functions for both concentration and spin are well fitted by the log-normal distribution for halos with the masses larger than ~10^8 Msun. The subhalo abundance depends on the halo mass. Galaxy-sized halos have 50% more subhalos than ~10^11 Msun halos have. This is snapshot 522 of the 2048³ resolution collection.
DOI: 10.25606/surf.578c6039-f40c393f
title: The Cosmogrid Simulation: Statistical Properties of Small Dark Matter Halos (2048-020)

description: We present the results of the "Cosmogrid" cosmological N-body simulation suites based on the concordance LCDM model. The Cosmogrid simulation was performed in a 30 Mpc box with 2048³ particles. The mass of each particle is 1.28x10^5 Msun, which is sufficient to resolve ultra-faint dwarfs. We found that the halo mass function shows good agreement with the Sheth & Tormen fitting function down to ~10^7 Msun. We have analyzed the spherically averaged density profiles of the three most massive halos which are of galaxy group size and contain at least 170 million particles. The slopes of these density profiles become shallower than -1 at the inner most radius. We also find a clear correlation of halo concentration with mass. The mass dependence of the concentration parameter cannot be expressed by a single power law, however a simple model based on the Press-Schechter theory proposed by Navarro et al. gives reasonable agreement with this dependence. The spin parameter does not show a correlation with the halo mass. The probability distribution functions for both concentration and spin are well fitted by the log-normal distribution for halos with the masses larger than ~10^8 Msun. The subhalo abundance depends on the halo mass. Galaxy-sized halos have 50% more subhalos than ~10^11 Msun halos have. This is snapshot 020 of the 2048³ resolution collection.
DOI: 10.25606/surf.578c6039-22c5c9fd
title: The Cosmogrid Simulation: Statistical Properties of Small Dark Matter Halos (2048-688)

description: We present the results of the "Cosmogrid" cosmological N-body simulation suites based on the concordance LCDM model. The Cosmogrid simulation was performed in a 30 Mpc box with 2048³ particles. The mass of each particle is 1.28x10^5 Msun, which is sufficient to resolve ultra-faint dwarfs. We found that the halo mass function shows good agreement with the Sheth & Tormen fitting function down to ~10^7 Msun. We have analyzed the spherically averaged density profiles of the three most massive halos which are of galaxy group size and contain at least 170 million particles. The slopes of these density profiles become shallower than -1 at the inner most radius. We also find a clear correlation of halo concentration with mass. The mass dependence of the concentration parameter cannot be expressed by a single power law, however a simple model based on the Press-Schechter theory proposed by Navarro et al. gives reasonable agreement with this dependence. The spin parameter does not show a correlation with the halo mass. The probability distribution functions for both concentration and spin are well fitted by the log-normal distribution for halos with the masses larger than ~10^8 Msun. The subhalo abundance depends on the halo mass. Galaxy-sized halos have 50% more subhalos than ~10^11 Msun halos have. This is snapshot 688 of the 2048³ resolution collection.
DOI: 10.25606/surf.578c6039-98192104
title: The Cosmogrid Simulation: Statistical Properties of Small Dark Matter Halos (2048-499)

description: We present the results of the "Cosmogrid" cosmological N-body simulation suites based on the concordance LCDM model. The Cosmogrid simulation was performed in a 30 Mpc box with 2048³ particles. The mass of each particle is 1.28x10^5 Msun, which is sufficient to resolve ultra-faint dwarfs. We found that the halo mass function shows good agreement with the Sheth & Tormen fitting function down to ~10^7 Msun. We have analyzed the spherically averaged density profiles of the three most massive halos which are of galaxy group size and contain at least 170 million particles. The slopes of these density profiles become shallower than -1 at the inner most radius. We also find a clear correlation of halo concentration with mass. The mass dependence of the concentration parameter cannot be expressed by a single power law, however a simple model based on the Press-Schechter theory proposed by Navarro et al. gives reasonable agreement with this dependence. The spin parameter does not show a correlation with the halo mass. The probability distribution functions for both concentration and spin are well fitted by the log-normal distribution for halos with the masses larger than ~10^8 Msun. The subhalo abundance depends on the halo mass. Galaxy-sized halos have 50% more subhalos than ~10^11 Msun halos have. This is snapshot 499 of the 2048³ resolution collection.
DOI: 10.25606/surf.578c6039-a7605e4f
title: The Cosmogrid Simulation: Statistical Properties of Small Dark Matter Halos (2048-496)

description: We present the results of the "Cosmogrid" cosmological N-body simulation suites based on the concordance LCDM model. The Cosmogrid simulation was performed in a 30 Mpc box with 2048³ particles. The mass of each particle is 1.28x10^5 Msun, which is sufficient to resolve ultra-faint dwarfs. We found that the halo mass function shows good agreement with the Sheth & Tormen fitting function down to ~10^7 Msun. We have analyzed the spherically averaged density profiles of the three most massive halos which are of galaxy group size and contain at least 170 million particles. The slopes of these density profiles become shallower than -1 at the inner most radius. We also find a clear correlation of halo concentration with mass. The mass dependence of the concentration parameter cannot be expressed by a single power law, however a simple model based on the Press-Schechter theory proposed by Navarro et al. gives reasonable agreement with this dependence. The spin parameter does not show a correlation with the halo mass. The probability distribution functions for both concentration and spin are well fitted by the log-normal distribution for halos with the masses larger than ~10^8 Msun. The subhalo abundance depends on the halo mass. Galaxy-sized halos have 50% more subhalos than ~10^11 Msun halos have. This is snapshot 496 of the 2048³ resolution collection.
DOI: 10.25606/surf.578c6039-b951188a
title: The Cosmogrid Simulation: Statistical Properties of Small Dark Matter Halos (2048-019)

description: We present the results of the "Cosmogrid" cosmological N-body simulation suites based on the concordance LCDM model. The Cosmogrid simulation was performed in a 30 Mpc box with 2048³ particles. The mass of each particle is 1.28x10^5 Msun, which is sufficient to resolve ultra-faint dwarfs. We found that the halo mass function shows good agreement with the Sheth & Tormen fitting function down to ~10^7 Msun. We have analyzed the spherically averaged density profiles of the three most massive halos which are of galaxy group size and contain at least 170 million particles. The slopes of these density profiles become shallower than -1 at the inner most radius. We also find a clear correlation of halo concentration with mass. The mass dependence of the concentration parameter cannot be expressed by a single power law, however a simple model based on the Press-Schechter theory proposed by Navarro et al. gives reasonable agreement with this dependence. The spin parameter does not show a correlation with the halo mass. The probability distribution functions for both concentration and spin are well fitted by the log-normal distribution for halos with the masses larger than ~10^8 Msun. The subhalo abundance depends on the halo mass. Galaxy-sized halos have 50% more subhalos than ~10^11 Msun halos have. This is snapshot 019 of the 2048³ resolution collection.
DOI: 10.25606/surf.578c6039-d50ff4d3
title: The Cosmogrid Simulation: Statistical Properties of Small Dark Matter Halos (2048-565)

description: We present the results of the "Cosmogrid" cosmological N-body simulation suites based on the concordance LCDM model. The Cosmogrid simulation was performed in a 30 Mpc box with 2048³ particles. The mass of each particle is 1.28x10^5 Msun, which is sufficient to resolve ultra-faint dwarfs. We found that the halo mass function shows good agreement with the Sheth & Tormen fitting function down to ~10^7 Msun. We have analyzed the spherically averaged density profiles of the three most massive halos which are of galaxy group size and contain at least 170 million particles. The slopes of these density profiles become shallower than -1 at the inner most radius. We also find a clear correlation of halo concentration with mass. The mass dependence of the concentration parameter cannot be expressed by a single power law, however a simple model based on the Press-Schechter theory proposed by Navarro et al. gives reasonable agreement with this dependence. The spin parameter does not show a correlation with the halo mass. The probability distribution functions for both concentration and spin are well fitted by the log-normal distribution for halos with the masses larger than ~10^8 Msun. The subhalo abundance depends on the halo mass. Galaxy-sized halos have 50% more subhalos than ~10^11 Msun halos have. This is snapshot 565 of the 2048³ resolution collection.
DOI: 10.5281/zenodo.3402373
title: Dataset about Diada de Sant Jordi from public TV3 audiovisual archive - FIAT/IFTA Media Studies Grant

description: [eng] This a dataset related to the Diada de Sant Jordi through TV3 public audiovisual archive. This dataset contains for a total of 572 videos with title, link, length in time and the program that have published information about this day. Most of these videos belong to the news program. This dataset is published on the occasion FIAT-IFTA Media Studies Grant 2019 Additionally, three more files are included. These files include the final sample, the queries on Tv3 archive and recommended books that appear on the footage. The final sample has 337 videos and queries are useful to look by year [cat] Aquest és un dataset vinculat a la Diada de Sant Jordi dels arxius audiovisuals públics de Tv3. Aquest dataset conté un total de 572 videos amb el títol, dreçera, longitud en temps i el programa que ha publicat informació relativa aquest dia. La major part d'aquests videos corresponent corresponen als programes de notícies. Aquestes dades es publiquen amb motiu de FIAT-IFTA Media Studies Grant 2019 A més a més s'inclouen 3 fitxers. Aquests fitxes inclouen la mostra final, les cadenes de cerca a l'arxiu de Tv3 i els llibres recomanats que apareixen en els videos. La mostra final conté 339 videos i les cadenes són útils per fer cerques per any.
DOI: 10.25606/surf.578c6039-325f9e8d
title: The Cosmogrid Simulation: Statistical Properties of Small Dark Matter Halos (2048-687)

description: We present the results of the "Cosmogrid" cosmological N-body simulation suites based on the concordance LCDM model. The Cosmogrid simulation was performed in a 30 Mpc box with 2048³ particles. The mass of each particle is 1.28x10^5 Msun, which is sufficient to resolve ultra-faint dwarfs. We found that the halo mass function shows good agreement with the Sheth & Tormen fitting function down to ~10^7 Msun. We have analyzed the spherically averaged density profiles of the three most massive halos which are of galaxy group size and contain at least 170 million particles. The slopes of these density profiles become shallower than -1 at the inner most radius. We also find a clear correlation of halo concentration with mass. The mass dependence of the concentration parameter cannot be expressed by a single power law, however a simple model based on the Press-Schechter theory proposed by Navarro et al. gives reasonable agreement with this dependence. The spin parameter does not show a correlation with the halo mass. The probability distribution functions for both concentration and spin are well fitted by the log-normal distribution for halos with the masses larger than ~10^8 Msun. The subhalo abundance depends on the halo mass. Galaxy-sized halos have 50% more subhalos than ~10^11 Msun halos have. This is snapshot 687 of the 2048³ resolution collection.
DOI: 10.25606/surf.578c6039-f0b6c807
title: The Cosmogrid Simulation: Statistical Properties of Small Dark Matter Halos (2048-524)

description: We present the results of the "Cosmogrid" cosmological N-body simulation suites based on the concordance LCDM model. The Cosmogrid simulation was performed in a 30 Mpc box with 2048³ particles. The mass of each particle is 1.28x10^5 Msun, which is sufficient to resolve ultra-faint dwarfs. We found that the halo mass function shows good agreement with the Sheth & Tormen fitting function down to ~10^7 Msun. We have analyzed the spherically averaged density profiles of the three most massive halos which are of galaxy group size and contain at least 170 million particles. The slopes of these density profiles become shallower than -1 at the inner most radius. We also find a clear correlation of halo concentration with mass. The mass dependence of the concentration parameter cannot be expressed by a single power law, however a simple model based on the Press-Schechter theory proposed by Navarro et al. gives reasonable agreement with this dependence. The spin parameter does not show a correlation with the halo mass. The probability distribution functions for both concentration and spin are well fitted by the log-normal distribution for halos with the masses larger than ~10^8 Msun. The subhalo abundance depends on the halo mass. Galaxy-sized halos have 50% more subhalos than ~10^11 Msun halos have. This is snapshot 524 of the 2048³ resolution collection.
DOI: 10.5061/dryad.290nr65/1
title: Dryad Item 10.5061/DRYAD.290NR65/1

description: (:tba)
DOI: 10.5281/zenodo.3360818
title: Alignment methods for nanotomography with deep sub-pixel accuracy

description: This repository contains codes for alignment of projections for tomography and laminography. Additionally we include artificial, i.e. simulated, and experimental examples. <strong>Here you will find:</strong> 1) <em>cSAXS_matlab_tomo_shared.zip</em> - Codes and routines, as introduced in [1], for deep sub-pixel alignment and reconstruction of tomography and laminography datasets. 2) <em>example_data.mat</em> - artificial tomography dataset that serves as an example for the alignment codes. <br> <strong>Citation and acknowledgements</strong> If you use the codes from this repository here is where to find more information and the expected citation. For use or further development of the tomography and laminography alignment and reconstruction codes please cite:<br> [1] M. Odstrcil, M. Holler, J. Holler, M. Guizar-Sicairos,"Alignment methods for nanotomography with deep sub-pixel accuracy", Opt. Express, (2019). <br> <strong>Code requirements:</strong> Reconstruction scripts were tested for Matlab2018a with parallel toolkit, CUDA 9.0. NVIDIA, RHEL 7.6<br> GPU is required for the tomographic reconstruction. <br> <strong>Instalation and reconstruction:</strong> 1) Download example datasets and code from https://doi.org/10.5281/zenodo.3539550 or a measured ptychotomography dataset from https://doi.org/10.5281/zenodo.3539513<br> 2) Make sure that the downloaded datasets can be loaded by matlab<br> 3) Choose one of the provided datasets in the "run_simple_example.m" template<br> 4) Run script "run_simple_example.m". The final results will be stored in folder defined in par.output_folder <br> <strong>Example dataset</strong> contains following two variables: <em>stack_object</em> - complex valued unaligned projection with dimensions [Npix_vertical , Npix_horizontal, number_of_angles] <em>theta</em> - vector of corresponding projection angles in degrees This code and subroutines are part of a continuous development. There is no liability on PSI or cSAXS. License for the codes can be found in the individual scripts.
description: {"references": ["Michal Odstr\u010dil, Mirko Holler, J\u00f6rg Raabe, and Manuel Guizar-Sicairos, \"Alignment methods for nanotomography with deep subpixel accuracy,\" Opt. Express 27, 36637-36652 (2019)"]}
DOI: 10.5281/zenodo.3360819
title: Alignment methods for nanotomography with deep sub-pixel accuracy

description: Artifical dataset that serves as an example for tomography alignment toolkit developed at cSAXS group, Paul Scherrer Institute for reconstruction and alignment of tomography and laminography datasets. Example of simulated data are loaded from 'example_data.mat' that contains two<br> variables:<br> stack_object - complex valued unaligned projection with following dimensions [Npix_vertical , Npix_horizontal, number_of_angles]<br> theta - vector of corresponding projection angles in degrees The other useful parameters are described and can be modified in the<br> following section. Requirements:<br> Reconstruction scripts were tested for Matlab2018a and CUDA 9.0. NVIDIA<br> GPU is required for the tomographic reconstruction.<br> Instalation and reconstruction:<br> 1) Our tomography toolkit depends on cSAXS base script package: https://www.psi.ch/en/sls/csaxs/software<br> 2) Unpack cSAXS_matlab_base into folder where this script is placed<br> 3) Make sure that our example dataset 'example_data.mat' can be loaded by matlab<br> 4) Run script called "run_simple_example.m", the final results will be stored in folder defined in par.output_folder This code and subroutines are part of a continuous development. There is no<br> liability on PSI or cSAXS. Publications most relevant to this code<br> M. Odstrcil, M. Holler, J. Holler, M. Guizar-Sicairos,<br> "Alignment methods for nanotomography with deep sub-pixel accuracy", Optics Express, 2019<br> M. Guizar-Sicairos, A. Diaz, M. Holler, M. S. Lucas, A. Menzel, R. A. Wepf, and O. Bunk<br> "Phase tomography from x-ray coherent diffractive imaging projections," Opt. Express 19, 21345-21357 (2011).<br> For tomographic consistency alignment:<br> M. Guizar-Sicairos, J. J. Boon, K. Mader, A. Diaz, A. Menzel, and O. Bunk,<br> "Quantitative interior x-ray nanotomography by a hybrid imaging technique," Optica 2, 259-266 (2015).
DOI: 10.5519/qd.y8xe1s9b
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (585 records)
DOI: 10.5281/zenodo.3402167
title: Data Sets and Prediction Models Created using MLP, RNN and LSTM

description: Binary Data Sets - 2018tbi219_shuffled3.csv and 2018tbi219_shuffled5.csv - these are stratified data sets that were able to produce prediction models with high prediction rates. Models.zip - this zip file contains the prediction models created using Keras Deep Learning Algorithms: MLP, RNN and LSTM Model Creation - Python Code Snippets - Code snippets for creating the prediction models
DOI: 10.5281/zenodo.3402168
title: Data Sets and Prediction Models Created using MLP, RNN and LSTM

description: Binary Data Sets - 2018tbi219_shuffled3.csv and 2018tbi219_shuffled5.csv - these are stratified data sets that were able to produce prediction models with high prediction rates. Models.zip - this zip file contains the prediction models created using Keras Deep Learning Algorithms: MLP, RNN and LSTM Model Creation - Python Code Snippets - Code snippets for creating the prediction models
DOI: 10.21227/jxax-yf70
title: Solar Pump

description: re-experimentation. Note: All the datasets listed will be submitted. At the time of creating this link, they were even ready for upload. But I have suddenly found a new idea for improved complex, so deleted those datasets and reason for delay for new is - some errors, resdesigning, + lot personal work + pressure in getting new project + stress. How will I proceed, myself dont know but datasets/research will be uploaded. (cannot upload details as I m afraid, someoneelse will upload ).I cannot make profile hidden.This dataset is generated from a series of experiments to know the impact of and performance of the system,which will be implemented on the site for domestic/residentia.This dataset contain simulation results,comparisons,animated phase portraits for "centrifugal pumps".Basic high level diagram is very simple but analysis and internal architecture is complex.Solar Panels are connected to generate singlephase DC.MPPT algorithm( ) and is used to, which is then boosted to using , which then is converted to AC using multilevel inverterThe IGBTs are switched it is known that w but the centrifugal pump is being modelled and the laminar flow pressure differentialflow viscosity,density In this dataset, the centrifugal pump drive shaft torqueThis study anThere are some unexpected noticed in the simulated results but that has been cross verified using These kind patterns are not usually mentioned in the textbooks And the objective of this study was to observe that only without editing or just showing the . Thus, it expands experiment.