cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.34770/g0cf-b557
title: A reduced-turbulence regime in the Large Helical Device upon injection of low-Z materials powders

description: Recently an improved confinement regime, characterized by reduced turbulent fluctuations has been observed in the Large Helical Device upon the injection of boron powder into the plasma (Nespoli et al 2022 Nat. Phys.18 350–56). In this article, we report in more detail the experimental observations of increased plasma temperature and the decrease of turbulent fluctuations across the plasma cross section, on an extended database. In particular, we compare powders of different materials (B, C, BN), finding similar temperature improvement and turbulence response for the three cases. Modeling of the powder penetration into the plasma and of neoclassical electric field and fluxes support the interpretation of the experimental results. Additionally, we report evidence of the temperature improvement increasing with powder injection rates and decreasing for both increasing density and heating power. Though, plasma turbulence response varies depending on the initial conditions of the plasma, making it difficult to draw an inclusive description of the phenomenon.
DOI: 10.5281/zenodo.8280398
title: eurycea_bislineata_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.5281/zenodo.8280397
title: eurycea_bislineata_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.34770/3f28-m424
title: Observation of a reduced-turbulence regime with boron powder injection in a stellarator

description: In state-of-the-art stellarators, turbulence is a major cause of the degradation of plasma confinement. To maximize confinement, which eventually determines the amount of nuclear fusion reactions, turbulent transport needs to be reduced. Here we report the observation of a confinement regime in a stellarator plasma that is characterized by increased confinement and reduced turbulent fluctuations. The transition to this regime is driven by the injection of submillimetric boron powder grains into the plasma. With the line-averaged electron density being kept constant, we observe a substantial increase of stored energy and electron and ion temperatures. At the same time, the amplitude of the plasma turbulent fluctuations is halved. While lower frequency fluctuations are damped, higher frequency modes in the range between 100 and 200 kHz are excited. We have observed this regime for different heating schemes, namely with both electron and ion cyclotron resonant radio frequencies and neutral beams, for both directions of the magnetic field and both hydrogen and deuterium plasmas.
DOI: 10.6075/j0t43r83
title: Data from: Episodic Southern Ocean heat loss and its mixed layer impacts revealed by the furthest south multi-year surface flux mooring

description: This dataset contains Quality Controlled daily mean air-sea heat flux estimates from the NSF Ocean Observatories Initiative (OOI) Southern Ocean mooring site for the period February 2015 to August 2017, as used in the analysis of Ogle et al. 2018 (doi:10.1029/2017GL076909). Initial data processing and estimates of heat flux terms using a modified version of the COARE 3.5 flux algorithm from Edson et al. [2013] (documented at https://github.com/ooici) was completed by the OOI Data Team and can be obtained from the NSF OOI Data Portal https://ooinet.oceanobservatories.org/. Secondary data quality control and temporal averaging was undertaken by Sarah Ogle and Veronica Tamsitt at Scripps Institution of Oceanography. All of the variables apart from shortwave radiation have undergone the OOI QC process (http://oceanobservatories.org/quality-control/), which may include all or some of the following: global range test, spike test, and stuck value test. The upper limit of the OOI QC global range test applied to the shortwave radiation was too low, and thus we do not apply this test to the shortwave radiation data. We applied our own quality control to all of the data including removing negative SWR values, extreme spikes, repeating values, and zero wind speed values.
DOI: 10.26024/hss6-m342
title: Biogeochemical daily output from a forced ocean-ice integration of CESMv1

description: This dataset contains the forced ocean-ice simulation of CESM that is necessary to reproduce the ocean model analysis in Carranza et al. (2023) “Storms role for air-sea CO2 exchange in the Southern Ocean”, submitted to Nature Communications. It is a branch simulation of the ocean hindcast run used to initialize the Decadal Prediction Large Ensemble (DPLE, Yeager et al. 2018) for the years 2009-2014 using the CORE-Inter-Annually varying Forcing (CORE-IAF, Large & Yeager, 2008). For this study, we saved daily output for many ocean biogeochemical parameters.
DOI: 10.57982/eq5a-3n07
title: Eating, Sleeping, Consoling for Neonatal Opioid Withdrawal (ESC-NOW): a Function-Based Assessment and Management Approach

description: ESC-NOW was a cluster-randomized, controlled trial conducted at 26 U.S. hospitals, which enrolled 1305 infants with neonatal opioid withdrawal syndrome (NOWS). At a randomly assigned time, participants transitioned from usual care based on the Finnegan Neonatal Abstinence Scoring Tool�(FNAST) to the Eat, Sleep, Console (ESC) approach. The primary outcome was the time from birth until medical readiness for discharge as defined by the trial. The Eat, Sleep, Console care approach significantly decreased the number of days until infants born with NOWS were medically ready for discharge, without increasing specified adverse outcomes.
DOI: 10.5281/zenodo.8280421
title: agapornis_fischeri_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.8280420
title: agapornis_fischeri_zanfona_1.fasta.gz

description: .
DOI: 10.6084/m9.figshare.23995446
title: Microsatellite dataset Cryptopygus - Foregrounding geodiversity in landscape ecology.xlsx

description: Sampling:Transect sampling was conducted on eastern Marion Island at two sampling areas, namely Nellie Humps (NH) Skua Ridge (SR). The NH site included 24 sampling points separated from each other by a geographic distance ranging from 30 to 120 m, while the SR site comprised 21 sampling points separated by distances ranging from 60 and 190 m.<i>Cryptopygus antarcticus travei</i> specimens were collected by extracting them from sampled moss and/or ferns (approximately 10 cm<sup>3</sup>) using Berlese-Tullgren funnels. Twenty individuals of <i>C. a. travei</i><i> </i>from each sampling point were identified and sorted using a compound light microscope, and stored in absolute ethanol (Merck, South Africa).Microsatellite genotyping:Whole genomic DNA was extracted using the DNeasy<sup>®</sup> Blood and Tissue Kit (Qiagen<sup>®</sup>, Hilden, Germany), according to the manufacturer's recommendations, with minor modifications that included a longer digestion step (overnight, but not more than 20 hours) and a reduced final elution volume (75 μl instead of 100 μl). Microsatellite loci were amplified in multiplex reactions (seven multiplex sets based on the criteria described by Rastorgueff et al., 2016) using 21 highly variable and species-specific markers (Rastorgueff et al., 2016), and fragment analysis was performed on a MultiGene<sup>TM</sup> OptiMax Thermal Cycler (Applied Biosystems). Cleaned PCR amplicons were sized using the ABI Prism<sup>®</sup> 3500XL Genetic Analyser (Applied Biosystems, Foster City, California, USA). Alleles were analysed, scored, and binned manually using the Geneious v8.1.5 microsatellite plugin 1.4 (Kearse et al., 2012).The dataset added to the repository consists of the scored genotype data for all individuals from both sampling localities.
DOI: 10.6084/m9.figshare.23995446.v2
title: Microsatellite dataset Cryptopygus - Foregrounding geodiversity in landscape ecology.xlsx

description: Sampling:Transect sampling was conducted on eastern Marion Island at two sampling areas, namely Nellie Humps (NH) Skua Ridge (SR). The NH site included 24 sampling points separated from each other by a geographic distance ranging from 30 to 120 m, while the SR site comprised 21 sampling points separated by distances ranging from 60 and 190 m.<i>Cryptopygus antarcticus travei</i> specimens were collected by extracting them from sampled moss and/or ferns (approximately 10 cm<sup>3</sup>) using Berlese-Tullgren funnels. Twenty individuals of <i>C. a. travei</i><i> </i>from each sampling point were identified and sorted using a compound light microscope, and stored in absolute ethanol (Merck, South Africa).Microsatellite genotyping:Whole genomic DNA was extracted using the DNeasy<sup>®</sup> Blood and Tissue Kit (Qiagen<sup>®</sup>, Hilden, Germany), according to the manufacturer's recommendations, with minor modifications that included a longer digestion step (overnight, but not more than 20 hours) and a reduced final elution volume (75 μl instead of 100 μl). Microsatellite loci were amplified in multiplex reactions (seven multiplex sets based on the criteria described by Rastorgueff et al., 2016) using 21 highly variable and species-specific markers (Rastorgueff et al., 2016), and fragment analysis was performed on a MultiGene<sup>TM</sup> OptiMax Thermal Cycler (Applied Biosystems). Cleaned PCR amplicons were sized using the ABI Prism<sup>®</sup> 3500XL Genetic Analyser (Applied Biosystems, Foster City, California, USA). Alleles were analysed, scored, and binned manually using the Geneious v8.1.5 microsatellite plugin 1.4 (Kearse et al., 2012).The dataset added to the repository consists of the scored genotype data for all individuals from both sampling localities.
DOI: 10.6084/m9.figshare.23995446.v1
title: Microsatellite dataset Cryptopygus - Foregrounding geodiversity in landscape ecology.xlsx

description: Sampling:Transect sampling was conducted on eastern Marion Island at two sampling areas, namely Nellie Humps (NH) Skua Ridge (SR). The NH site included 24 sampling points separated from each other by a geographic distance ranging from 30 to 120 m, while the SR site comprised 21 sampling points separated by distances ranging from 60 and 190 m.<i>Cryptopygus antarcticus travei</i> specimens were collected by extracting them from sampled moss and/or ferns (approximately 10 cm<sup>3</sup>) using Berlese-Tullgren funnels. Twenty individuals of <i>C. a. travei</i><i> </i>from each sampling point were identified and sorted using a compound light microscope, and stored in absolute ethanol (Merck, South Africa).Microsatellite genotyping:Whole genomic DNA was extracted using the DNeasy<sup>®</sup> Blood and Tissue Kit (Qiagen<sup>®</sup>, Hilden, Germany), according to the manufacturer's recommendations, with minor modifications that included a longer digestion step (overnight, but not more than 20 hours) and a reduced final elution volume (75 μl instead of 100 μl). Microsatellite loci were amplified in multiplex reactions (seven multiplex sets based on the criteria described by Rastorgueff et al., 2016) using 21 highly variable and species-specific markers (Rastorgueff et al., 2016), and fragment analysis was performed on a MultiGene<sup>TM</sup> OptiMax Thermal Cycler (Applied Biosystems). Cleaned PCR amplicons were sized using the ABI Prism<sup>®</sup> 3500XL Genetic Analyser (Applied Biosystems, Foster City, California, USA). Alleles were analysed, scored, and binned manually using the Geneious v8.1.5 microsatellite plugin 1.4 (Kearse et al., 2012).The dataset added to the repository consists of the scored genotype data for all individuals from both sampling localities.
DOI: 10.5517/ccdc.csd.cc2g37mg
title: CCDC 2267235: Experimental Crystal Structure Determination

description: Related Article: Carlos D. García-Mejía, Eduardo Hernández-Vázquez, Javier Alejandro Ibarra-Hernández, Atl Tarbuck-Valle, María T. Ramírez-Apán|2023|Org.Biomol.Chem.|21|6205|doi:10.1039/D3OB00753G
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.cc2dy8vh
title: CCDC 2232677: Experimental Crystal Structure Determination

description: Related Article: Abdul K. Choudhury, Rudra Sarkar, Jagannath Bhuyan|2023|Dalton Trans.|52|11085|doi:10.1039/D3DT01309J
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.cc2fylgg
title: CCDC 2262766: Experimental Crystal Structure Determination

description: Related Article: Sudip Sarkar, Suranjan Shil, Sudip Mohapatra, Gobinda Chandra De, Sushobhan Ghosh|2023|Cryst.Growth Des.|23|6025|doi:10.1021/acs.cgd.3c00583
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.cc2ghmm7
title: CCDC 2279139: Experimental Crystal Structure Determination

description: Related Article: A.A. Yahiaoui, N. Ghichi, D. Hannachi, B. Mezhoud, A. Djedouani, K. Kraim, A. Crochet, H. Stoeckli-Evans|2023|Acta Crystallogr.,Sect.C:Cryst.Struct.Chem.|79|324|doi:10.1107/S2053229623005867
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.cc2gl148
title: CCDC 2281449: Experimental Crystal Structure Determination

description: Related Article: C. Aguilar-Lugo, M. Flores-Alamo, J.J. Sánchez García, E.I. Klimova|2023|IUCrData|8|x230616|doi:10.1107/S2414314623006168
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: 10.34683/sr182
title: StoneRounds Case: SR182
title: AD Retinitis Pigmentosa

description: StoneRounds Case SR182 was diagnosed with AD Retinitis Pigmentosa likely caused by mutations in the gene: RHO.
DOI: 10.6084/m9.figshare.24030141.v1
title: Supplementary material

description: Table S1. Genomic and epidemiologic characteristics of E. asburiae and E. huaxiensis strains isolated from human and non-human host.Table S2. Matrix of SNP-based phylogeny analysis of E. asburiae.
DOI: 10.6084/m9.figshare.24030141
title: Supplementary material

description: Table S1. Genomic and epidemiologic characteristics of E. asburiae and E. huaxiensis strains isolated from human and non-human host.Table S2. Matrix of SNP-based phylogeny analysis of E. asburiae.
DOI: 10.5281/zenodo.8280435
title: micropsitta_finschii_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.8280434
title: micropsitta_finschii_zanfona_1.fasta.gz

description: .
DOI: 10.5519/qd.zknammkt
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (7 records)
DOI: 10.6075/j0ks6phx
title: Data from: Commitment Problems or Bidding Wars? Rebel Fragmentation as Peace Building

description: Code and data formatted for Stata 14.
description: PAPER ABSTRACT: After highly fragmented civil wars, order is often secured through the selective co-optation of rebel field commanders and atomized insurgents. This paper presents a formal model of civil war settlement as a coalition formation game between various regime and rebel factions. This approach emphasizes the ability of installed civilian rulers to lure warlords into the state based on promises of future wealth, then use divide-and-rule tactics to pit different warlord factions against one another. Quantitative and qualitative data from Tajikistan, including an original data set of warlord incorporation and regime purges during wartime reconstruction, are used to evaluate the model.
DOI: 10.6075/j0c8276z
title: dataMares Collection

description: One of the current challenges in public policy development, especially when related to natural resource management and conservation, is that there are basically no tools that help easily identify and incorporate relevant scientific findings and data into public policy. This also can lead to a repetition or doubling of research efforts to collect the necessary information to develop sound policy that in some cases might already exist. The key to addressing this challenge is to develop collaborative tools where different sectors of society in general, and decision-makers in particular, can participate in the collection and exchange of information. The idea of “open science” (Reichman et al., 2011), which makes scientific research and data accessible to all levels of society, should be at the core of these efforts, focusing on enhancing accessibility, transparency, and reproducibility of scientific results. Using new technology, we can improve the data processing speed and reshape the way we compile, distribute, and provide access to relevant information, making it easier to communicate scientific data to any person interested in studying or preserving the coastal and marine ecosystems. DataMares is a free, open source, and interactive platform that aims to address this need. We aim to encourage accessibility to science and promote collaboration among scientist, decision-makers and stakeholders. With this platform we hope to bring opportunities to resolve trans-disciplinary problems related to the coastal and marine ecosystem. Currently, dataMares holds massive amounts of fishery, reef, and mangrove data (and more) pertaining to the Gulf of California and Mexico specific oceans, and delivers this information in an interactive and easily digestible manner. Since conception, we have grown tremendously and are consistently expanding our library of datasets while improving the functionality and overall usability of the platform. In order to synthesize and share the ecological and social science data collected through collaborative work, we have developed a data sharing and science communication portal that can be accessed at: http://datamares.org. Our target audiences for the portal include scientists, resource managers, conservation practitioners, fishers and other community members, and regional/national level decision-makers. DataMares adopts a broad and interdisciplinary approach to marine and coastal ecology science publication. Focal areas include fisheries, climate change, mangrove ecology, and animal behavioral studies. DataMares is not confined by a given geographic area and accepts research data from any system from the tropics to the poles. The initiative continually seeks opportunities for collaboration with independent researchers, academic institutions, organizations, and government organisms working in the same topics. We are interested in working with others to promote science communication and the use of robust scientific data for decision-making with regards to conservation and natural resource management.
DOI: 10.6075/j05d8s14
title: dataMares: Ecological Monitoring. In dataMares Collection

description: The long-term monitoring program was established in 1998 and serves as a central hub for all research of the Gulf of California Marine Program. We are building on more than a decade of surveys of nearshore marine ecosystems, like rocky reefs, in the central and southern Gulf of California. With this monitoring program we are tracking annual changes in the structure, function, and health of marine ecosystems through annual surveys of fishes and invertebrates at numerous island and coastal sites. Monitoring activities also include quantitative surveys and collections of fishes and invertebrates from mangrove estuaries, sargassum beds, seamounts, and other coastal habitats.
DOI: 10.6075/j0959hrf
title: dataMares: Ecosystem Dynamics. In dataMares Collection

description: Analyzing the relationships between different ecosystems, as well as humans and the habitats surrounding us, helps us to begin to comprehend the impact that anthropogenic activities have on the environment. By understanding the dynamics that connect diverse ecosystems with each other, and how these in turn relate and react to human activities, changes to their natural balance are revealed to us and, hopefully, the solutions we must implement to prevent catastrophic consequences.
DOI: 10.7934/p4836
title: A systematic revision of the family Harpetidae (Trilobita) (project)
DOI: 10.7934/x29462
title: A systematic revision of the family Harpetidae (Trilobita) [X29462] Matrix
DOI: 10.6075/j0dz08hv
title: dataMares: Fisheries. In dataMares Collection

description: Our fisheries program has gained considerable recognition for the research it has produced through a strong, international and regional network of collaborators from all sectors (government, public, academic, stakeholders). We produce and provide robust, high-quality scientific information related to the Gulf of California’s fisheries, marine reserves, coastal and marine ecosystems, and climate change. At the same time, we build scientific capacity in the region and broadly communicate the results of our research to all sectors and audiences to ensure that sound science is incorporated in management and policy decision processes.
DOI: 10.35078/74ykex/ik47bk
title: Ruy Nogueira A.jpg

description: :unav
DOI: 10.35078/9yoxja/thbnii
title: Adão Miranda B.jpg

description: :unav
DOI: 10.35078/g5pz1l/c348kx
title: Sercondino J. de Souza B.jpg

description: :unav
DOI: 10.35078/qmkoaw/z6nmma
title: Zeferino Alves Ferreira B.jpg

description: :unav
DOI: 10.35078/qmkoaw/zzjvtw
title: Joaquim Alves de Paula B.jpg

description: :unav
DOI: 10.35078/74ykex/j4fhz9
title: Gorduras B.jpg

description: :unav
DOI: 10.35078/9yoxja/mcogdt
title: Cedri da Silva A.jpg

description: :unav
DOI: 10.35078/g5pz1l/fjrueu
title: Limoeiro B.jpg

description: :unav
DOI: 10.35078/74ykex/bluslw
title: Barreiras II A.jpg

description: :unav
DOI: 10.35078/qmkoaw/meatbp
title: Senil Pinto B.jpg

description: :unav
DOI: 10.35078/9yoxja/2ljeff
title: Juca Pena A.jpg

description: :unav
DOI: 10.35078/g5pz1l/qosmom
title: Brits de Brito Alves B.jpg

description: :unav
DOI: 10.35078/74ykex/nzp2b4
title: José da Silva Neto A.jpg

description: :unav
DOI: 10.35078/9yoxja/qn7hvu
title: Amário B.jpg

description: :unav
DOI: 10.35078/g5pz1l/yhc9ne
title: Cidade Nova B.jpg

description: :unav
DOI: 10.35078/qmkoaw/nv0g5z
title: Heráquio Gusmão Lima A.jpg

description: :unav
DOI: 10.35078/qmkoaw/nvlhpc
title: Saquinho B.jpg

description: :unav
DOI: 10.35078/9yoxja/9tucou
title: Francisco C. de Miranda A.jpg

description: :unav
DOI: 10.35078/74ykex/xdzfsg
title: Cachoeira B.jpg

description: :unav
DOI: 10.35078/g5pz1l/yjbmmw
title: Benvindo Saúde A.jpg

description: :unav
DOI: 10.35078/9yoxja/7qwd4d
title: José Moreira A.jpg

description: :unav
DOI: 10.35078/74ykex/1vocrl
title: Hermes Inácio B.jpg

description: :unav
DOI: 10.35078/g5pz1l/vxinry
title: Pinheira D.jpg

description: :unav
DOI: 10.35078/qmkoaw/g1rybm
title: Clemente Justino da Silva A.jpg

description: :unav
DOI: 10.35078/74ykex/uvpjrk
title: Adelaide B.jpg

description: :unav
DOI: 10.35078/9yoxja/vuvy89
title: Retiro Novo Bairro B.jpg

description: :unav
DOI: 10.35078/g5pz1l/zanzoz
title: Everaldino Luiz Ferreira B.jpg

description: :unav
DOI: 10.35078/qmkoaw/pwn41n
title: Nossa Senhora das Graças B.jpg

description: :unav
DOI: 10.35078/74ykex/messjd
title: Expansão B.jpg

description: :unav