cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6558815
title: Scripts for quantifying the effect of diamond nano-pillars on the fluorescence of NV centers

description: <strong>Summary</strong> Scripts and data can be used to reproduce and build on the numerical results published under the title: "Optical and Spin Properties of NV Center Ensembles in Diamond Nano-Pillars" by Kseniia Volkova, Julia Heupel, Sergei Trofimov, Fridtjof Betz, Rémi Colom, Rowan W. MacQueen, Sapida Akhundzada, Meike Reginka, Arno Ehresmann, Johann P. Reithmaier, Sven Burger, Cyril Popov, and Boris Naydenov (Nanomaterials 12(9), 1516, 2022). <strong>Method</strong> The dipole emitters are assumed to be distributed uniformly 30 nm below the top surface of the nano-pillars. They are first integrated with a trapezoidal rule along the azimuth (because of the periodicity this results in a geometrical convergence) and with a 15 point Gauss-Kronrod quadrature rule in radial direction. The main source of error results from the dipole positions being integrated only from 0 to R - min_dist, as it is challenging to model a dipole emitter located only few nanometers from the curved material interface. Further numerical parameters can be adjusted in the input files for JCMsuite. Both, a 3D setup and a 2D setup are provided. The letter exploits the rotational symmetry which results in a smaller memory footprint. Yet, as the distance of the dipole from the symmetry axis increases, many Fourier components are required which leads to long computation times. For further quantitative studies we propose the 3D setup that is the default in the script 'integration.m', which allows to integrate closer to the side walls without increasing the costs. Furthermore in the second data set, shipped together with the data published in the paper, the height has been kept constant. In the paper the height has been chosen according to the fabricated samples. The 90° angle has been assigned to the [111] samples and the correspondingt height of 1400 nm and the 35.3° angle was assigned to the [100] samples and a height of 2200 nm. <strong>Structure</strong> The directories <strong>scattering2D</strong>, <strong>scattering3D </strong>and <strong>scatteringFlat</strong> contain input files for JCMsuite. The script 'integration.m' can be used to produce new data. With 'plotresults.m' you can either plot the results produced with 'integration.m' or those which were published in the related paper. Please note that the provided example produced with the script 'integration.m' differs from the published data, which has been computed with slightly different parameters. <strong>Requirements</strong> JCMsuite 5.2.0 Matlab R2019b In order to produce new data, you must replace the corresponding place holders in the files by a path to your installation of JCMsuite. Free trial licenses are available, please refer to the homepage of JCMwave.
description: This research was funded by the EMPIR programme co-financed by the Participating States and from the European Union's Horizon 2020 research and innovation programme (project number 20FUN05, SEQUME).
DOI: 10.5281/zenodo.6558814
title: Scripts for quantifying the effect of diamond nano-pillars on the fluorescence of NV centers

description: <strong>Summary</strong> Scripts and data can be used to reproduce and build on the numerical results published under the title: "Optical and Spin Properties of NV Center Ensembles in Diamond Nano-Pillars" by Kseniia Volkova, Julia Heupel, Sergei Trofimov, Fridtjof Betz, Rémi Colom, Rowan W. MacQueen, Sapida Akhundzada, Meike Reginka, Arno Ehresmann, Johann P. Reithmaier, Sven Burger, Cyril Popov, and Boris Naydenov (Nanomaterials 12(9), 1516, 2022). <strong>Method</strong> The dipole emitters are assumed to be distributed uniformly 30 nm below the top surface of the nano-pillars. They are first integrated with a trapezoidal rule along the azimuth (because of the periodicity this results in a geometrical convergence) and with a 15 point Gauss-Kronrod quadrature rule in radial direction. The main source of error results from the dipole positions being integrated only from 0 to R - min_dist, as it is challenging to model a dipole emitter located only few nanometers from the curved material interface. Further numerical parameters can be adjusted in the input files for JCMsuite. Both, a 3D setup and a 2D setup are provided. The letter exploits the rotational symmetry which results in a smaller memory footprint. Yet, as the distance of the dipole from the symmetry axis increases, many Fourier components are required which leads to long computation times. For further quantitative studies we propose the 3D setup that is the default in the script 'integration.m', which allows to integrate closer to the side walls without increasing the costs. Furthermore in the second data set, shipped together with the data published in the paper, the height has been kept constant. In the paper the height has been chosen according to the fabricated samples. The 90° angle has been assigned to the [111] samples and the correspondingt height of 1400 nm and the 35.3° angle was assigned to the [100] samples and a height of 2200 nm. <strong>Structure</strong> The directories <strong>scattering2D</strong>, <strong>scattering3D </strong>and <strong>scatteringFlat</strong> contain input files for JCMsuite. The script 'integration.m' can be used to produce new data. With 'plotresults.m' you can either plot the results produced with 'integration.m' or those which were published in the related paper. Please note that the provided example produced with the script 'integration.m' differs from the published data, which has been computed with slightly different parameters. <strong>Requirements</strong> JCMsuite 5.2.0 Matlab R2019b In order to produce new data, you must replace the corresponding place holders in the files by a path to your installation of JCMsuite. Free trial licenses are available, please refer to the homepage of JCMwave.
description: This research was funded by the EMPIR programme co-financed by the Participating States and from the European Union's Horizon 2020 research and innovation programme (project number 20FUN05, SEQUME).
DOI: 10.5517/ccdc.csd.cc2bzcpd
title: CCDC 2174144: Experimental Crystal Structure Determination

description: Related Article: Licheng Zhang, Jinfeng Li, Ruirui Liu, Yongquan Zhou, Yuze Zhang, Lianmin Ji, Lijuan Li|2022|J.Mol.Liq.|362|119667|doi:10.1016/j.molliq.2022.119667
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.cc2bkdmy
title: CCDC 2161680: Experimental Crystal Structure Determination

description: Related Article: Damian Antoniak, Bartosz Pałuba, Michał Barbasiewicz|2022|CSD Communication|||
description: Related Article: Micha Tryniszewski, Dariusz Basiak, Micha Barbasiewicz|2022|Org.Lett.|24|4270|doi:10.1021/acs.orglett.2c01604
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.cc2bkdnz
title: CCDC 2161681: Experimental Crystal Structure Determination

description: Related Article: Damian Antoniak, Bartosz Pałuba, Michał Barbasiewicz|2022|CSD Communication|||
description: Related Article: Micha Tryniszewski, Dariusz Basiak, Micha Barbasiewicz|2022|Org.Lett.|24|4270|doi:10.1021/acs.orglett.2c01604
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.cc2bkdp0
title: CCDC 2161682: Experimental Crystal Structure Determination

description: Related Article: Damian Antoniak, Bartosz Pałuba, Michał Barbasiewicz|2022|CSD Communication|||
description: Related Article: Micha Tryniszewski, Dariusz Basiak, Micha Barbasiewicz|2022|Org.Lett.|24|4270|doi:10.1021/acs.orglett.2c01604
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.cc2bkdq1
title: CCDC 2161683: Experimental Crystal Structure Determination

description: Related Article: Damian Antoniak, Bartosz Pałuba, Michał Barbasiewicz|2022|CSD Communication|||
description: Related Article: Micha Tryniszewski, Dariusz Basiak, Micha Barbasiewicz|2022|Org.Lett.|24|4270|doi:10.1021/acs.orglett.2c01604
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.cc2bv3dq
title: CCDC 2170043: Experimental Crystal Structure Determination

description: Related Article: Xiaoli Zhang, Shumin Chen, Pengtao|2022|Inorg.Chem.Commun.|143|109718|doi:10.1016/j.inoche.2022.109718
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: 10.34740/kaggle/dsv/3918618
title: Thermal Image of Faces for Temperature Detection
DOI: 10.6084/m9.figshare.20280627
title: A scoping review key elements and effects of cardiovascular disease management programs based on community-based participatory research

description: This scoping review’s methodology had six stages: 1) identifying the research question; 2) identifying relevant studies—search strategy; 3) study selection; 4) charting the data; 5) collating, summarising, and reporting the results; and 6) consultation exercise. The databases used were PubMed, Cochrane, and CINAHL, for the period from 4 March to 3 April 2020. We selected studies 1) published after 2000; 2) targeting community residents over 18 years old; and 3) proposed a CBPR-based CVD management programme, described its development, and evaluated its effects based on its application. Data were extracted independently by each of the two researchers, using a standardised form.
DOI: 10.6084/m9.figshare.20280627.v1
title: A scoping review key elements and effects of cardiovascular disease management programs based on community-based participatory research

description: This scoping review’s methodology had six stages: 1) identifying the research question; 2) identifying relevant studies—search strategy; 3) study selection; 4) charting the data; 5) collating, summarising, and reporting the results; and 6) consultation exercise. The databases used were PubMed, Cochrane, and CINAHL, for the period from 4 March to 3 April 2020. We selected studies 1) published after 2000; 2) targeting community residents over 18 years old; and 3) proposed a CBPR-based CVD management programme, described its development, and evaluated its effects based on its application. Data were extracted independently by each of the two researchers, using a standardised form.
DOI: 10.5281/zenodo.6816322
title: data for drought prediction using deep learning algorithms

description: This dataset is monthly SPEI from 1901 to 2015 with 0.5 spatial resolution. It is standardized to [0,1] as inputs/outputs of neural network.
DOI: 10.5281/zenodo.6816321
title: data for drought prediction using deep learning algorithms

description: This dataset is monthly SPEI from 1901 to 2015 with 0.5 spatial resolution. It is standardized to [0,1] as inputs/outputs of neural network.
DOI: 10.25919/475x-xb26
title: Parkes pulsar observations with undefined project IDs for 2022APRS_08

description: Parkes pulsar observations with undefined project IDs for 2022APRS. This collection contains observations from project IDs PX085 and PX087.
DOI: 10.34740/kaggle/dsv/3927942
title: Team Fight Tactics matches
DOI: 10.5517/ccdc.csd.cc2c6bzx
title: CCDC 2180849: Experimental Crystal Structure Determination

description: Related Article: Kai Schickedanz, Michael Bolte, Matthias Wagner|2022|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.cc2c7h26
title: CCDC 2181937: Experimental Crystal Structure Determination

description: Related Article: B.I.Buzykin, I.A.Litvinsky, F.S.Levinson, A.T.Gubaidullin, E.A.Ermolaeva|2005|Butlerovskie soobshcheniya|6|7|
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.cc2c7h37
title: CCDC 2181938: Experimental Crystal Structure Determination

description: Related Article: B.I.Buzykin, I.A.Litvinsky, F.S.Levinson, A.T.Gubaidullin, E.A.Ermolaeva|2005|Butlerovskie soobshcheniya|6|7|
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.cc2c7h48
title: CCDC 2181939: Experimental Crystal Structure Determination

description: Related Article: B.I.Buzykin, I.A.Litvinsky, F.S.Levinson, A.T.Gubaidullin, E.A.Ermolaeva|2005|Butlerovskie soobshcheniya|6|7|
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.cc2c7h59
title: CCDC 2181940: Experimental Crystal Structure Determination

description: Related Article: B.I.Buzykin, I.A.Litvinsky, F.S.Levinson, A.T.Gubaidullin, E.A.Ermolaeva|2005|Butlerovskie soobshcheniya|6|7|
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.cc2bjhx9
title: CCDC 2160821: Experimental Crystal Structure Determination

description: Related Article: Galina Romanenko|2022|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.cc2bjj3j
title: CCDC 2160827: Experimental Crystal Structure Determination

description: Related Article: Galina Romanenko|2022|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.cc2bjj8p
title: CCDC 2160832: Experimental Crystal Structure Determination

description: Related Article: Galina Romanenko|2022|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.cc2bjhq3
title: CCDC 2160815: Experimental Crystal Structure Determination

description: Related Article: Galina Romanenko|2022|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: 10.5281/zenodo.6816637
title: Assessing suspended sediment fluxes with acoustic doppler current profilers: case study from large rivers in Russia

description: The dataset contains measurements of water discharge by Teledyne RDInstruments RioGrande WorkHorse ADCP unit with a working frequency of 600kHz mounted on a moving boat in 6 areas over large rivers of Russia. The dataset comprises the four largest Arctic Siberian rivers and included continuous ADCP measurements done in 2018-2020 at constant crossection at each river located upper from the impact of recipient seas (tides, surges) near the cities of Salekhard (Ob River), Igarka (Yenisey River), Zhigansk (Lena river) and Chersky (Kolyma River). Another area includes ADCP measurements over 20 transects (named S1…S26, fig. 2) in the lower 200 km of the river Selenga on 27-31July 2018. Additionally, the dataset contains ADCP measurements at 38 points along the Moskva River (named M1, M2…) and 17 tributaries (named T01, T02…) done during 2019-2020. This is a supporting material to a manuscript submitted to «Big Earth Data» journal
description: Selenga, Kolyma and Lena river ADCP profiles have been added
DOI: 10.6084/m9.figshare.20281587
title: Non-conscious bias training restores choice divergence from invisible primes

description: <strong>Non-conscious bias training restores choice divergence from invisible primes</strong> <br> <strong>Datasets and MATLAB codes to produce figures for the article.</strong>
DOI: 10.6084/m9.figshare.20281587.v1
title: Non-conscious bias training restores choice divergence from invisible primes

description: <strong>Non-conscious bias training restores choice divergence from invisible primes</strong> <br> <strong>Datasets and MATLAB codes to produce figures for the article.</strong>
DOI: 10.5281/zenodo.6616006
title: Near infrared imaging data from brown rot decayed wood

description: This dataset contains near infrared imaging data from the following publication: Belt, T.; Awais, M.; Mäkelä, M. (2022) Chemical characterization and visualization of progressive brown rot decay of wood by near infrared imaging and multivariate analysis. Frontiers in Plant Science 13:940745. DOI: 10.3389/fpls.2022.940745. Details on the samples, the decay test, and the image collection parameters can be found in the publication. The “Sample IDs and mass losses.cvs” file contains the sample ID and mass loss due to decay of each sample in the dataset. The “C puteana.mat” and “R. placenta.mat” files contain the near infrared imaging data of samples exposed to the fungus <em>Coniophora puteana</em> and the fungus <em>Rhodonia placent</em>a, respectively, organised into cell arrays of sample IDs and corresponding image files. To generate the image files, a region of interest of 551 x 384 pixels was selected from the raw image files to produce an image that contains the sample surrounded by background. The spectral data were then converted to reflectance and corrected using the calibration reflectance target values.
DOI: 10.5281/zenodo.6616005
title: Near infrared imaging data from brown rot decayed wood

description: This dataset contains near infrared imaging data from the following publication: Belt, T.; Awais, M.; Mäkelä, M. (2022) Chemical characterization and visualization of progressive brown rot decay of wood by near infrared imaging and multivariate analysis. Frontiers in Plant Science 13:940745. DOI: 10.3389/fpls.2022.940745. Details on the samples, the decay test, and the image collection parameters can be found in the publication. The “Sample IDs and mass losses.cvs” file contains the sample ID and mass loss due to decay of each sample in the dataset. The “C puteana.mat” and “R. placenta.mat” files contain the near infrared imaging data of samples exposed to the fungus <em>Coniophora puteana</em> and the fungus <em>Rhodonia placent</em>a, respectively, organised into cell arrays of sample IDs and corresponding image files. To generate the image files, a region of interest of 551 x 384 pixels was selected from the raw image files to produce an image that contains the sample surrounded by background. The spectral data were then converted to reflectance and corrected using the calibration reflectance target values.
DOI: 10.15151/esrf-es-771452399
title: The Israeli BAG

description: The BAG is quite large with 24 principal investigators covering almost all groups in Israel. The scientific topics are diverse and so different that depicting them in a short Abstract is extremely difficult. In this context BAG members are studying the parameters that govern protein assemblage, structural impacts of signaling processes in different cascades. There are several projects that are directed towards molecular recognition with implementation towards drug design. In addition, we still have the ribosome project and the design of unique antibiotics with specific functional interactions from the mycinamycins family and their resistance related mechanism compared with other macrolides and the photosystem and how it converts light into energy. Since Covid-19 is still a relevant topic as are other viral infections BAG members are and have been involved in the understanding of the infection process and the means to hinder it.
DOI: 10.15151/esrf-es-874032733
title: Post Mortem and insitu battery tomography

description: This is the continuation of the MI-1354 experiment to complete our data set with post mortem tomography and some functional charge/discharge scans.
DOI: 10.15151/esrf-es-876433142
title: Accessing orientation and residual strains in biogenic apatite biocomposites in teeth by means of X-ray absorption spectroscopy
DOI: 10.15151/esrf-es-868380093
title: preparation for experiment ch6232

description: setup preparation, alignment, calibration, reference diffraction