cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5285/60f9b354-2cbf-4d4d-84f7-13c9224f82d4
title: Exuviae krill flux in the northern Scotia Sea from January 2018 to December 2018

description: This dataset is referring to 1-year time series of particle flux, as measured by a shelf moored sediment traps (WCB) located in the Southern Ocean (northern Scotia Sea sector), a globally important region of atmospheric CO2 drawdown. This sector holds &gt;50% of the circumpolar krill stock of Antarctic krill and is the geographic focus for the krill fishing industry. The dataset includes the specific contribution of krill components to the total C flux parameters (such as exuviae, faecal pellets and carcasses) within a period from January to December 2018. Values of krill seasonal standing stock estimated from krill standard lengths is also included in the dataset. The dataset allow the quantification of the relevant contribution of krill to the POC flux. Since abundance of Krill around South Georgia is environmentally influenced, the dataset highlights the sensitivity of POC flux to rapid regional environmental change.
description: Sample were collected by using sediment trap deployed on bottom-tethered moorings during WCB cruise JR16003. Once in the laboratory, sample were then divided into a series of replicate fractions for subsequent analysis using a McLane rotary sample splitter (McLane Labs, Falmouth, MA, USA). POC was measured by combustion in an elemental analyser (CHN); Krill faecal pellets were counted under light microscopy. The dimensions of krill faecal pellets were measured (length and width) using an ocular micrometer. Exuviae and carcasses of krill were picked out under a light microscope and their dimensions measured. They were then rinsed and dried at 60 °C for 24 hours before their dry weight (DW) was measured. The length of the uropod from exuviae randomly picked from each sediment trap sample bottle was measured. Krill total length was estimated from uropod length.
description: - Sediment trap deployed on fixed mooring platform - Sediment trap splitter - CHN auto-analyser - Light microscope - 60 °C owen and balance for dry mass calculation
description: Physical data acquired during the sediment trap deployment suggest the record was not subjected to major hydrodynamic biases since mean current velocities near to the sediment traps were &lt; 10 cm s-1 and we assumed no significant lateral advection occurred.
DOI: 10.5281/zenodo.4110654
title: Exsolution of Catalytically Active Ir Nanoparticles from Strontium Titanate_Raw Data

description: Raw data files.
DOI: 10.5281/zenodo.4110653
title: Exsolution of Catalytically Active Ir Nanoparticles from Strontium Titanate_Raw Data

description: Raw data files.
DOI: 10.5281/zenodo.4115206
title: Dataset associated to "Unraveling the relative role of light and water competition between lianas and trees in tropical forests: A vegetation model analysis"

description: This dataset includes all the codes necessary to reproduce the simulations presented in the paper "Unraveling the relative role of light and water competition between lianas and trees in tropical forests: A vegetation model analysis" published in Journal of Ecology. More precisely, it includes the version of the codes used to generate the results for the vegetation model (ED2), the analysis platform (PEcAn), as well as the meterological drivers (Drivers) and the initial conditions (IC) of the model and the priors and posterior parameter distributions.
DOI: 10.5281/zenodo.4115205
title: Dataset associated to "Unraveling the relative role of light and water competition between lianas and trees in tropical forests: A vegetation model analysis"

description: This dataset includes all the codes necessary to reproduce the simulations presented in the paper "Unraveling the relative role of light and water competition between lianas and trees in tropical forests: A vegetation model analysis" published in Journal of Ecology. More precisely, it includes the version of the codes used to generate the results for the vegetation model (ED2), the analysis platform (PEcAn), as well as the meterological drivers (Drivers) and the initial conditions (IC) of the model and the priors and posterior parameter distributions.
DOI: 10.6084/m9.figshare.13122488
title: Sanitary sewage disinfection with ultraviolet radiation and ultrasound

description: In the present scenario, the globe is facing a horrible situation due to an infectious virus SARS-CoV-2. Its RNA was found in sewage waters, there are still no studies on RNA contamination detected in the sewage, however, a possible treatment of sewage is suggested in this work. The disinfection stage is extremely important in the treatment of effluents, minimizing the impacts on the receiving body and promoting public health. In this context, the sequential use of ultrasound and ultraviolet radiation, on a bench scale, was investigated as a way to improve the disinfection of domestic effluents from the septic tank and of an anaerobic filter. The better quality of the anaerobic filter effluent influenced the performance of both processes, decreasing the concentration of organic load and turbidity, even so, the concentration of total coliforms and <i>Escherichia coli</i> occurred in the lowest quality effluent (septic tank). In the sequential application, synergistic effects of more than 1 log of inactivity were found. It is suggested that the disinfection methods applied in this work to inactivate gram-negative bacteria (<i>E. coli</i>) can also be applied to secondary treatment effluents, as well as being better tested for viruses, protozoa, and helminths.
DOI: 10.6084/m9.figshare.13122488.v1
title: Sanitary sewage disinfection with ultraviolet radiation and ultrasound

description: In the present scenario, the globe is facing a horrible situation due to an infectious virus SARS-CoV-2. Its RNA was found in sewage waters, there are still no studies on RNA contamination detected in the sewage, however, a possible treatment of sewage is suggested in this work. The disinfection stage is extremely important in the treatment of effluents, minimizing the impacts on the receiving body and promoting public health. In this context, the sequential use of ultrasound and ultraviolet radiation, on a bench scale, was investigated as a way to improve the disinfection of domestic effluents from the septic tank and of an anaerobic filter. The better quality of the anaerobic filter effluent influenced the performance of both processes, decreasing the concentration of organic load and turbidity, even so, the concentration of total coliforms and <i>Escherichia coli</i> occurred in the lowest quality effluent (septic tank). In the sequential application, synergistic effects of more than 1 log of inactivity were found. It is suggested that the disinfection methods applied in this work to inactivate gram-negative bacteria (<i>E. coli</i>) can also be applied to secondary treatment effluents, as well as being better tested for viruses, protozoa, and helminths.
DOI: 10.21227/fvqh-e338
title: Model 3

description: Improvement upon the method 1 and 2 based on ratios and linear relations but introducing clutering as a pre-processing technique.
DOI: 10.6084/m9.figshare.13122521
title: muscimol_traces.mat

description: Widefield fluorescence before and after topical muscimol application
DOI: 10.6084/m9.figshare.13122521.v1
title: muscimol_traces.mat

description: Widefield fluorescence before and after topical muscimol application
DOI: 10.5967/99jc-8578
title: DATA EXTRACT: Student eLearning Metrics Joined with COVID-19 Survey Responses
DOI: 10.5285/dc91f5e39ae34fd883af81dfdbaf659c
title: Monthly mean climate data from a transient simulation with the Whole Atmosphere Community Climate Model eXtension (WACCM-X) from 1950 to 2015

description: This dataset comprises monthly mean data from a global, transient simulation with the Whole Atmosphere Community Climate Model eXtension (WACCM-X) from 1950 to 2015. WACCM-X is a global atmosphere model covering altitudes from the surface up to ~500 km, i.e. including the troposphere, stratosphere, mesosphere and thermosphere. WACCM-X version 2.0 (Liu et al., 2018) was used, part of the Community Earth System Model (CESM) release 2.1.0 made available by the US National Center for Atmospheric Research. The model was run in free-running mode with a horizontal resolution of 1.9° latitude 2.5° longitude (giving 96 latitude points and 144 longitude points) and 126 vertical levels. Further description of the model and simulation setup is provided by Cnossen (2020) and references therein. A large number of variables are included on standard monthly mean output files on the model grid, while selected variables are also offered interpolated to a constant height grid or vertically integrated in height (details below). Zonal mean and global mean output files are included as well. The following data file types are included: 1)Monthly mean output on the full grid for the full set of variables; [DFT] = '' 2)Zonal mean monthly mean output for the full set of variables; [DFT] = _zm 3)Global mean monthly mean output for the full set of variables; [DFT] = _gm 4)Height-interpolated/-integrated output on the full grid for selected variables; [DFT] = _ht A cos(latitude) weighting was used when calculating the global means. Data were interpolated to a set of constant heights (61 levels in total) using the Z3GM variable (for variables output on midpoints, with "lev" as the vertical coordinate) or the Z3GMI variable (for variables output on interfaces, with "ilev" as the vertical coordinate) stored on the original output files (type 1 above). Interpolation was done separately for each longitude, latitude and time. Mass density (DEN [g/cm3]) was calculated from the M_dens, N2_vmr, O2, and O variables on the original data files before interpolation to constant height levels. The Joule heating power QJ [W/m3] was calculated using Q_J=_P B^2 [(u_i-u_n )^2+(v_i-v_n )^2+(w_i-w_n )^2] with P = Pedersen conductivity [S], B = geomagnetic field strength [T], ui, vi, and wi = zonal, meridional, and vertical ion velocities [m/s] and un, vn, and wn = neutral wind velocities [m/s]. QJ was integrated vertically in height (using a 2.5 km height grid spacing rather than the 61 levels on output file type 4) to give the JHH variable on the type 4 data files. The QJOULE variable also given is the Joule heating rate [K/s] at each of the 61 height levels. All data are provided as monthly mean files with one time record per file, giving 792 files for each data file type for the period 1950-2015 (66 years).
DOI: 10.5281/zenodo.4115185
title: Time Series Charactersitics of Forecasting Competitions

description: We calculate different time series characteristics for our data set (libra) and the time series competitions M1, M3, M4, NN3, NN5, NNGC1, and Tourism.
DOI: 10.21227/4vf9-y182
title: Model2.2.0

description: KNN new preprocess
DOI: 10.5281/zenodo.4114532
title: Research data - reactive pulse simulations

description: Codes useful to perform the numerical simulations that validate the analytical results we derived to predict effective kinetics driven by dynamic concentration gradients under coupled diffusion and reaction for a range of Damköhler numbers and reaction order. Reactive_pulse_generator.m is the code to do the numerical simulations, save data, and compare to analytical results. pdex1PDE.m, pdex1IC.m, pdex1BC.m are codes used to define pdepe's Matlab method parameters, initial conditions, and boundary conditions respectively.
DOI: 10.5281/zenodo.4114531
title: Research data - reactive pulse simulations

description: Codes useful to perform the numerical simulations that validate the analytical results we derived to predict effective kinetics driven by dynamic concentration gradients under coupled diffusion and reaction for a range of Damköhler numbers and reaction order. Reactive_pulse_generator.m is the code to do the numerical simulations, save data, and compare to analytical results. pdex1PDE.m, pdex1IC.m, pdex1BC.m are codes used to define pdepe's Matlab method parameters, initial conditions, and boundary conditions respectively.
DOI: 10.25318/82-003-x202001000001-fra
title: Associations entre la réception de soins palliatifs en milieu hospitalier et les résultats en matière de soins de courte durée : une étude rétrospective

description: La présente étude permet d'examiner la réception des soins palliatifs en milieu hospitalier et son association avec le lieu de décès, ainsi qu'avec l'admission dans les unités de soins intensifs et l'utilisation des lits pour les patients nécessitant un autre niveau de soins à l'hôpital au cours des 30 derniers jours de vie.
DOI: 10.5281/zenodo.4115300
title: Time Series Charactersitics of Forecasting Competitions

description: We calculate different time series characteristics for our data set (libra) and the time series competitions M1, M3, M4, NN3, NN5, NNGC1, and Tourism.
DOI: 10.25345/c5m20s
title: MassIVE MSV000086343 - GNPS ononis spinosa hairy root old sample
title: Aqueous methanolic extract of O. spinosa hairy root cultures
DOI: 10.5281/zenodo.4115327
title: Time Series Charactersitics of Forecasting Competitions

description: We calculate different time series characteristics for our data set (libra) and the time series competitions M1, M3, M4, NN3, NN5, NNGC1, and Tourism.
DOI: 10.21227/v848-aq44
title: Baseline1

description: Baseline, new preprocess.Other NaN with mean of knewn months.
DOI: 10.5281/zenodo.4115334
title: Time Series Charactersitics of Forecasting Competitions

description: We calculate different time series characteristics for our data set (libra) and the time series competitions M1, M3, M4, NN3, NN5, NNGC1, and Tourism.
DOI: 10.5517/ccdc.csd.cc21h0m6
title: CCDC 1891267: Experimental Crystal Structure Determination

description: Related Article: Volodymyr Bon, Irena Senkovska, Jack D. Evans, Michelle Wöllner, Markus Hölzel, Stefan Kaskel|2019|J.Mater.Chem.A|7|12681|doi:10.1039/C9TA00825J
DOI: 10.5517/ccdc.csd.cc21h0n7
title: CCDC 1891268: Experimental Crystal Structure Determination

description: Related Article: Volodymyr Bon, Irena Senkovska, Jack D. Evans, Michelle Wöllner, Markus Hölzel, Stefan Kaskel|2019|J.Mater.Chem.A|7|12681|doi:10.1039/C9TA00825J
DOI: 10.5517/ccdc.csd.cc21h0p8
title: CCDC 1891269: Experimental Crystal Structure Determination

description: Related Article: Volodymyr Bon, Irena Senkovska, Jack D. Evans, Michelle Wöllner, Markus Hölzel, Stefan Kaskel|2019|J.Mater.Chem.A|7|12681|doi:10.1039/C9TA00825J
DOI: 10.5517/ccdc.csd.cc21w67d
title: CCDC 1902973: Experimental Crystal Structure Determination

description: Related Article: Bertram Peters, Silke Santner, Carsten Donsbach, Pascal Vöpel, Bernd Smarsly, Stefanie Dehnen|2019|Chemical Science|10|5211|doi:10.1039/C9SC01358J
DOI: 10.5517/ccdc.csd.cc21w414
title: CCDC 1902905: Experimental Crystal Structure Determination

description: Related Article: Bertram Peters, Silke Santner, Carsten Donsbach, Pascal Vöpel, Bernd Smarsly, Stefanie Dehnen|2019|Chemical Science|10|5211|doi:10.1039/C9SC01358J
DOI: 10.5517/ccdc.csd.cc22y8ht
title: CCDC 1934756: Experimental Crystal Structure Determination

description: Related Article: Verónica Conejo-Rodríguez, Marconi N. Peñas-Defrutos, Pablo Espinet|2019|Dalton Trans.|48|10412|doi:10.1039/C9DT01618J
DOI: 10.5517/ccdc.csd.cc23078n
title: CCDC 1936640: Experimental Crystal Structure Determination

description: Related Article: Davide Bernasconi, Simone Bordignon, Federica Rossi, Emanuele Priola, Carlo Nervi, Roberto Gobetto, Dario Voinovich, Dritan Hasa, Nghia Tuan Duong, Yusuke Nishiyama, Michele R. Chierotti
|2020|Cryst.Growth Des.|20|906|doi:10.1021/acs.cgd.9b01299
DOI: 10.5517/ccdc.csd.cc2381r6
title: CCDC 1944157: Experimental Crystal Structure Determination

description: Related Article: Gregory R. Lorzing,  Eric J. Gosselin,  Benjamin A. Trump,  Arthur H. P. York,  Arni Sturluson,  Casey A. Rowland, Glenn P. A. Yap,  Craig M. Brown,  Cory M. Simon,  Eric D. Bloch|2019|J.Am.Chem.Soc.|141|12128|doi:10.1021/jacs.9b05872
DOI: 10.5517/ccdc.csd.cc218bqd
title: CCDC 1884853: Experimental Crystal Structure Determination

description: Related Article: Shuai Yu|2019|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc238hhd
title: CCDC 1944583: Experimental Crystal Structure Determination

description: Related Article: Afsaneh Khansari, Macguire R. Bryant, Daniel R. Jenkinson, Geoffrey B. Jameson, Omid T. Qazvini, Lujia Liu, Andrew D. Burrows, Shane G. Telfer, Christopher Richardson|2019|CrystEngComm|21|7498|doi:10.1039/C9CE01669D
DOI: 10.5517/ccdc.csd.cc23bnw0
title: CCDC 1946672: Experimental Crystal Structure Determination

description: Related Article: Abdelaziz Jouaiti, Philippe Grosshans, Nathalie Kyritsakas, Sylvie Ferlay, Marc Henry, Mir Wais Hosseini|2020|CrystEngComm|22|1746|doi:10.1039/C9CE01781J
DOI: 10.5517/ccdc.csd.cc23bnx1
title: CCDC 1946673: Experimental Crystal Structure Determination

description: Related Article: Abdelaziz Jouaiti, Philippe Grosshans, Nathalie Kyritsakas, Sylvie Ferlay, Marc Henry, Mir Wais Hosseini|2020|CrystEngComm|22|1746|doi:10.1039/C9CE01781J
DOI: 10.5517/ccdc.csd.cc23dw6m
title: CCDC 1948790: Experimental Crystal Structure Determination

description: Related Article: Yong Yan, Elliot J. Carrington, Rémi Pétuya, George F. S. Whitehead, Ajay Verma, Rebecca K. Hylton, Chiu C. Tang, Neil G. Berry, George R. Darling, Matthew S. Dyer, Dmytro Antypov, Alexandros P. Katsoulidis, Matthew J. Rosseinsky|2020|J.Am.Chem.Soc.|142|14903|doi:10.1021/jacs.0c03853
DOI: 10.5517/ccdc.csd.cc23dwr5
title: CCDC 1948807: Experimental Crystal Structure Determination

description: Related Article: Yong Yan, Elliot J. Carrington, Rémi Pétuya, George F. S. Whitehead, Ajay Verma, Rebecca K. Hylton, Chiu C. Tang, Neil G. Berry, George R. Darling, Matthew S. Dyer, Dmytro Antypov, Alexandros P. Katsoulidis, Matthew J. Rosseinsky|2020|J.Am.Chem.Soc.|142|14903|doi:10.1021/jacs.0c03853
DOI: 10.5517/ccdc.csd.cc23dz7r
title: CCDC 1948884: Experimental Crystal Structure Determination

description: Related Article: Thanh Binh Nguyen, Tuan Minh Nguyen, Pascal Retailleau|2020|Chem.-Eur.J.|26|4682|doi:10.1002/chem.201905597
DOI: 10.5517/ccdc.csd.cc23n2d8
title: CCDC 1955709: Experimental Crystal Structure Determination

description: Related Article: Kang Cai, Yi Shi, Changsu Cao, Suneal Vemuri, Binbin Cui, Dengke Shen, Huang Wu, Long Zhang, Yunyan Qiu, Hongliang Chen, Yang Jiao, Charlotte L. Stern, Fehaid M. Alsubaie, Hai Xiao, Jun Li, J. Fraser Stoddart|2020|Chemical Science|11|107|doi:10.1039/C9SC04860J
DOI: 10.5281/zenodo.4115348
title: Time Series Charactersitics of Forecasting Competitions

description: We calculate different time series characteristics for our data set (libra) and the time series competitions M1, M3, M4, NN3, NN5, NNGC1, and Tourism.
DOI: 10.5281/zenodo.4115184
title: Time Series Charactersitics of Forecasting Competitions

description: We calculate different time series characteristics for our data set (libra) and the time series competitions M1, M3, M4, NN3, NN5, NNGC1, and Tourism.
DOI: 10.5281/zenodo.4115345
title: Time Series Charactersitics of Libra and existing Forecasting Competitions

description: We calculate different time series characteristics for our data set (libra) and the time series competitions M1, M3, M4, NN3, NN5, NNGC1, and Tourism.
DOI: 10.5281/zenodo.4115344
title: Time Series Charactersitics of Libra and existing Forecasting Competitions

description: We calculate different time series characteristics for our data set (libra) and the time series competitions M1, M3, M4, NN3, NN5, NNGC1, and Tourism.
DOI: 10.25573/data.13122581
title: San Blas, all data

description: The San Blas field station was established in 1977 and closed on June 1, 1998. The station was situated on an island adjacent to Punta de San Blas, on the Caribbean coast of Panama 120 km east of the Panama Canal, midway to the Panama/Colombia border. That island is at the western end of Kuna Yala, an indigenous reserve (also known as the Comarca de San Blas) that stretches along 160 km of the eastern coast of Panama. Smithsonian scientists started working in Kuna Yala in 1970. The field station supported short-term biological studies in addition to as well as long-term meteorological and biological monitoring. Physical Monitoring activities began at the San Blas station in 1992.<br>Monitoring activities included the measurement of air temperature, precipitation, solar radiation, wind speed and direction, sea level, water temperature and salinity.
DOI: 10.25573/data.13122626.v1
title: Monthly summary - San Blas

description: The San Blas field station was established in 1977 and closed on June 1, 1998. The station was situated on an island adjacent to Punta de San Blas, on the Caribbean coast of Panama 120 km east of the Panama Canal, midway to the Panama/Colombia border. That island is at the western end of Kuna Yala, an indigenous reserve (also known as the Comarca de San Blas) that stretches along 160 km of the eastern coast of Panama. Smithsonian scientists started working in Kuna Yala in 1970. The field station supported short-term biological studies in addition to as well as long-term meteorological and biological monitoring. Physical Monitoring activities began at the San Blas station in 1992.<br>Monitoring activities included the measurement of air temperature, precipitation, solar radiation, wind speed and direction, sea level, water temperature and salinity.<br><br>
DOI: 10.25573/data.13122626
title: Monthly summary - San Blas

description: The San Blas field station was established in 1977 and closed on June 1, 1998. The station was situated on an island adjacent to Punta de San Blas, on the Caribbean coast of Panama 120 km east of the Panama Canal, midway to the Panama/Colombia border. That island is at the western end of Kuna Yala, an indigenous reserve (also known as the Comarca de San Blas) that stretches along 160 km of the eastern coast of Panama. Smithsonian scientists started working in Kuna Yala in 1970. The field station supported short-term biological studies in addition to as well as long-term meteorological and biological monitoring. Physical Monitoring activities began at the San Blas station in 1992.<br>Monitoring activities included the measurement of air temperature, precipitation, solar radiation, wind speed and direction, sea level, water temperature and salinity.<br><br>
DOI: 10.17632/w8p8jr95mn.1
title: Data for: Seagrass colonization affect the vertical organization of microbial communities in sediment
DOI: 10.6084/m9.figshare.13122497
title: Functional area identification results of the traditional model and scoring evaluation model.

description: Real-time and accurate functional area maps are essential for urban planning. Functional areas (commercial zones, public service zones, residential zones, industrial zones, transportation zones and scenic zones) are identified by the scoring evaluation model and traditional model.<br>
DOI: 10.6084/m9.figshare.13122497.v1
title: Functional area identification results of the traditional model and scoring evaluation model.

description: Real-time and accurate functional area maps are essential for urban planning. Functional areas (commercial zones, public service zones, residential zones, industrial zones, transportation zones and scenic zones) are identified by the scoring evaluation model and traditional model.<br>
DOI: 10.6084/m9.figshare.13122632.v1
title: ROR Data Dump 6.0 (October 2020)

description: ROR data download. Based on GRID release 10.6084/m9.figshare.13084304
DOI: 10.6084/m9.figshare.13122632
title: ROR Data Dump 6.0 (October 2020)

description: ROR data download. Based on GRID release 10.6084/m9.figshare.13084304
DOI: 10.5281/zenodo.4114420
title: Supporting datasets

description: Datasets supporting forcing
DOI: 10.6084/m9.figshare.13122749
title: Untitled Item

description: Comparison of algorithm’s <b>average </b>(5 times run) recall values for different injection types and final results of proposed method.
DOI: 10.6084/m9.figshare.13122749.v1
title: Untitled Item

description: Comparison of algorithm’s <b>average </b>(5 times run) recall values for different injection types and final results of proposed method.