cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7786195
title: Bacteria-phage coevolution with a seed bank

description: Dormancy is an adaptation to living in fluctuating environments. It allows individuals to enter a reversible state of reduced metabolic activity when challenged by unfavorable conditions. Dormancy can also influence species interactions by providing organisms with a refuge from predators and parasites. Here we test the hypothesis that, by generating a seed bank of protected individuals, dormancy can modify the patterns and processes of antagonistic coevolution. We conducted a factorially designed experiment where we passaged a bacterial host (<em>Bacillus subtilis</em>) and its phage (SPO1) in the presence versus absence of a seed bank consisting of dormant endospores. Owing in part to the inability of phages to attach to spores, seed banks stabilized population dynamics and resulted in minimum host densities that were 30-fold higher compared to bacteria that were unable to engage in dormancy. By supplying a refuge to phage-sensitive strains, we show that seed banks retained phenotypic diversity that was otherwise lost to selection. Dormancy also stored genetic diversity. After characterizing allelic variation with pooled population sequencing, we found that seed banks retained twice as many host genes with mutations, whether phages were present or not. Based on mutational trajectories over the course of the experiment, we demonstrate that seed banks can dampen bacteria-phage coevolution. Not only does dormancy create structure and memory that buffers populations against environmental fluctuations, it also modifies species interactions in ways that can feed back onto the eco-evolutionary dynamics of microbial communities.
DOI: 10.35078/goshlz
title: Replication Data for: Ficha epidemiológica de localidade: Distrito: Caratinga| Município: Carandaí

description: Levantamento Triatomínico com operações de campo ocorridas em Minas Gerais pela Superintendência de Campanhas de Saúde Pública (SUCAM) e FUNASA (Fundação Nacional de Saúde), no período de 1979 a 1999, objetivando a busca da presença de vetores da doença de Chagas ou de vestígios dessa presença. A partir dela são orientadas as operações com inseticida (pt) Triatomine survey with field operations carried out in Minas Gerais by the Public Health Campaigns Superintendence (SUCAM) and FUNASA (National Health Foundation), from 1979 to 1999, aiming to search for the presence of Chagas disease vectors or traces of that presence. From it, operations with insecticide are guided (en) Encuesta de triatominos con operaciones de campo realizada en Minas Gerais por la Superintendencia de Campañas de Salud Pública (SUCAM) y FUNASA (Fundación Nacional de Salud), de 1979 a 1999, con el objetivo de buscar la presencia de vectores de la enfermedad de Chagas o rastros de esa presencia. Desde ella se orientan las operaciones con insecticida (es)
DOI: 10.5519/qd.7ew31oxl
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (20 records)
DOI: 10.5066/p9lsdcx7
title: Autonomous Underwater Vehicle Water-Quality and Sonar Measurements alongside Conductivity, Temperature and Depth Measurements in the Delaware River near Philadelphia, Pennsylvania, 2021

description: These datasets were created in support of the U.S. Geological Survey's (USGS) Next Generation Water Observing System (NGWOS) for the Delaware River Basin pilot study (Eberts, Wagner, and Woodside, 2019). The NGWOS utilizes real-time data, improved computational capabilities, and new technologies such as unmanned aerial vehicles (UAV) and autonomous underwater vehicles (AUV) to provide information on water quality and/or quantity, in more locations, quickly and efficiently (Eberts, Wagner, and Woodside, 2019). Combined with advanced modeling applications, the NGWOS will be an important tool for water-resource managers and emergency management. In this study, water-quality and bathymetric data were measured with an AUV during spatial surveys in the study areas near Philadelphia, PA in July 2021. Water-quality and bathymetric data were measured at various periods during the tide cycle and logged at 0.2-second intervals (5 Hz). Bathymetric data were measured using an on-board single-beam echosounder in combination with a pressure transducer. Water-quality data were measured with an EXO1 sonde built into the nose cone of the IVER3 EcoMapper AUV (YSI, 2020). The sonde was calibrated before, and checked after, each data collection trip per USGS water-quality sampling protocols (YSI, 2020; Wagner and others, 2006; Wilde, variously dated). During surveys in which the AUV was programmed to execute bank-to-bank transects, it was occasionally pushed off course by the current. Water-quality parameters measured by the AUV during the survey include: water temperature and specific conductivity (YSI sensor SKU 599870), turbidity (YSI sensor SKU 599101-01), chlorophyll and phycocyanin (YSI sensor SKU 599102-01), fluorescent dissolved organic matter (YSI sensor SKU 599104-01), and dissolved oxygen (YSI sensor SKU 599100-01). Water-quality parameters computed post survey include: salinity and density which were computed from water temperature, conductivity, vessel depth, and latitude (Jackson, 2013). Additional water-quality measurements were collected from a boat following the deployed AUV. These vertical water-quality profiles were collected with a SonTek CastAway Conductivity, Temperature, and Depth (CTD) instrument logging at 0.33-second intervals (3 Hz) (Xylem, 2017). Vertical profile measurements were made periodically by manually lowering and raising the CTD at a subset of locations while following behind the track of the AUV. Water-quality parameters measured by the CTD during the survey include water temperature, specific conductivity, and depth below water surface. The CTD also provides computed salinity, sound velocity, and water density for each measurement.
DOI: 10.6084/m9.figshare.22806485
title: Phantoms to validate ECA reconstruction

description: Phantoms are avaible in MatLab version. Phantoms are made from DCE-MRI series to validate ECA reconstruction [1]. The ECA code and detailed method are publicly avaible at https://github.com/ZhenRen1/ECA-Demo <br> Phantoms details are: AP020Phant: phantom of a IDC Grade 3 case AP045Phant: phantom of a DCIS case AP055Phant: phantom of a IDC Grade 2 case AP056Phant: phantom of a IDC Grade 3 case AP057Phant: phantom of a normal control case <br>
DOI: 10.6084/m9.figshare.22806485.v1
title: Phantoms to validate ECA reconstruction

description: Phantoms are avaible in MatLab version. Phantoms are made from DCE-MRI series to validate ECA reconstruction [1]. The ECA code and detailed method are publicly avaible at https://github.com/ZhenRen1/ECA-Demo <br> Phantoms details are: AP020Phant: phantom of a IDC Grade 3 case AP045Phant: phantom of a DCIS case AP055Phant: phantom of a IDC Grade 2 case AP056Phant: phantom of a IDC Grade 3 case AP057Phant: phantom of a normal control case <br>
DOI: 10.25919/f52e-w294
title: Parkes observations for project P1194 semester 2023APRS_01

description: Among nearly 2000 unidentified gamma-ray sources detected with the Fermi Gamma Ray Space Telescope, there are potentially many pulsars. The ultra-wide frequency coverage will enable us to detect MSPs with steep spectrum and avoid difficulties caused by interstellar scintillation and dispersive and scattering smearing. We propose to revisit highly ranked pulsar candidates that remain unidentified. Such a pilot survey will help us designing future searches of the coming 4FGL gamma-ray source catalog using the UWL. We select 11 targets and request 12 hour time in total.
DOI: 10.34740/kaggle/dsv/5324411
title: Wider Face - Torchvision Compatible
DOI: 10.5281/zenodo.7925609
title: Phytophthora in horticultural nursery green waste - a risk to plant health

description: This dataset on Zenodo accompanies the manuscript Schiffer-Forsyth <em>et al.</em> (2023), Phytophthora in horticultural nursery green waste – a risk to plant health. There are two files: metadata.tsv - plain text table as tab-separated variables raw_data.tar.gz - compressed archive of 81 paired raw FASTQ files This represents a complete Illumina MiSeq run, with the names of the unrelated samples redacted. To repeat the analysis described in the paper, first install THAPBI PICT. See https://github.com/peterjc/thapbi-pict/ for instructions. At the time of the paper, v0.14.1 was the current release (with a near-identical v1.0.0 expected to be released shortly). Next, decompress the raw data into a folder of paired gzipped FASTQ files. There is no need to decompress those: <pre><code class="language-bash"> $ tar -zxvf raw_data.tar.gz $ ls -1 raw_data/</code></pre> If you wish, verify the checksums to confirm the data integrity: <pre><code class="language-bash"> $ cd raw_data/ $ md5sum -c MD5SUM.txt $ cd ..</code></pre> Setup output directories: <pre><code class="language-bash"> $ mkdir -p intermediate/ summary/</code></pre> You can run the analysis in one step. This should take under five minutes: <pre><code class="language-bash">$ thapbi_pict pipeline -i raw_data/ \ -n raw_data/SynCtrl_*.fastq.gz \ -y raw_data/SynCtrl_*.fastq.gz \ -s intermediate/ -o summary/ \ -t metadata.tsv -x 3 -c 1,2,4,5</code></pre> The options here are as follows: -i raw_data - input directory of paired raw FASTQ files. -n raw_data/SynCtrl_*.fastq.gz - negative controls used to increase the absolute abundance threshold -y raw_data/SynCtrl_*.fastq.gz - synthetic controls used to increase the fractional abundance threshold -s intermediate/ - optional location to store intermediate files -o summary/ - output location for reports -t metadata.tsv -x 3 -c 1,2,4,5 - show and sort on metadata columns 1, 2, 4 and 5 from metadata.tsv using column 3 to cross-reference the FASTQ filename stems (semi-colon separated lists for replicates). This assumes the following key default settings: -a 100 -f 0.001 - default absolute and fractional abundance thresholds -d - - default to the provided ITS1 database With these settings, only synthetic sequences were found in the controls, and therefore the thresholds were not automatically increased any further. Note some of these options could change in future releases of the software, and in particular there would likely be additional Phytophthora species or sequences in future updates to the default database. Output file summary/ITS1.samples.onebp.xlsx (and .tsv) is equivalent to Table 2 (after pooling replicates, and applying human judgement to resolve ambiguous ITS1 markers shared by multiple species). Note <em>P. austrocedri</em> was identified in three samples, N2-Water_S2 and N2-Water_S22 described in this work, and a third sample REDACTED_S28 from another location.
DOI: 10.5281/zenodo.7925608
title: Phytophthora in horticultural nursery green waste - a risk to plant health

description: This dataset on Zenodo accompanies the manuscript Schiffer-Forsyth <em>et al.</em> (2023), Phytophthora in horticultural nursery green waste – a risk to plant health. There are two files: metadata.tsv - plain text table as tab-separated variables raw_data.tar.gz - compressed archive of 81 paired raw FASTQ files This represents a complete Illumina MiSeq run, with the names of the unrelated samples redacted. To repeat the analysis described in the paper, first install THAPBI PICT. See https://github.com/peterjc/thapbi-pict/ for instructions. At the time of the paper, v0.14.1 was the current release (with a near-identical v1.0.0 expected to be released shortly). Next, decompress the raw data into a folder of paired gzipped FASTQ files. There is no need to decompress those: <pre><code class="language-bash"> $ tar -zxvf raw_data.tar.gz $ ls -1 raw_data/</code></pre> If you wish, verify the checksums to confirm the data integrity: <pre><code class="language-bash"> $ cd raw_data/ $ md5sum -c MD5SUM.txt $ cd ..</code></pre> Setup output directories: <pre><code class="language-bash"> $ mkdir -p intermediate/ summary/</code></pre> You can run the analysis in one step. This should take under five minutes: <pre><code class="language-bash">$ thapbi_pict pipeline -i raw_data/ \ -n raw_data/SynCtrl_*.fastq.gz \ -y raw_data/SynCtrl_*.fastq.gz \ -s intermediate/ -o summary/ \ -t metadata.tsv -x 3 -c 1,2,4,5</code></pre> The options here are as follows: -i raw_data - input directory of paired raw FASTQ files. -n raw_data/SynCtrl_*.fastq.gz - negative controls used to increase the absolute abundance threshold -y raw_data/SynCtrl_*.fastq.gz - synthetic controls used to increase the fractional abundance threshold -s intermediate/ - optional location to store intermediate files -o summary/ - output location for reports -t metadata.tsv -x 3 -c 1,2,4,5 - show and sort on metadata columns 1, 2, 4 and 5 from metadata.tsv using column 3 to cross-reference the FASTQ filename stems (semi-colon separated lists for replicates). This assumes the following key default settings: -a 100 -f 0.001 - default absolute and fractional abundance thresholds -d - - default to the provided ITS1 database With these settings, only synthetic sequences were found in the controls, and therefore the thresholds were not automatically increased any further. Note some of these options could change in future releases of the software, and in particular there would likely be additional Phytophthora species or sequences in future updates to the default database. Output file summary/ITS1.samples.onebp.xlsx (and .tsv) is equivalent to Table 2 (after pooling replicates, and applying human judgement to resolve ambiguous ITS1 markers shared by multiple species). Note <em>P. austrocedri</em> was identified in three samples, N2-Water_S2 and N2-Water_S22 described in this work, and a third sample REDACTED_S28 from another location.
DOI: 10.6084/m9.figshare.22290166
title: Supplementary Tables to Brüwer et al. 2023, mSystems

description: Suplementary Tables to "<em><strong>In situ</strong></em> <strong>cell division and mortality rates of SAR11, SAR86,</strong> <em><strong>Bacteroidetes</strong></em><strong>, and</strong> <em><strong>Aurantivirga</strong></em> <strong>during phytoplankton blooms reveal differences in population controls</strong>" by Brüwer et al. 2023, mSystems
DOI: 10.6084/m9.figshare.22290166.v4
title: Supplementary Tables to Brüwer et al. 2023, mSystems

description: Suplementary Tables to "<em><strong>In situ</strong></em> <strong>cell division and mortality rates of SAR11, SAR86,</strong> <em><strong>Bacteroidetes</strong></em><strong>, and</strong> <em><strong>Aurantivirga</strong></em> <strong>during phytoplankton blooms reveal differences in population controls</strong>" by Brüwer et al. 2023, mSystems
DOI: 10.5519/qd.2dirucdw
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (822366 records)
DOI: 10.6073/pasta/9eda64cdaf74c5df938d765fa04649eb
title: Zooplankton community composition and trait data for Green Lakes Valley, 2009 - ongoing.

description: Starting in 2012 zooplankton sampling at Green Lake 4 was included in the long term monitoring data set at Niwot Ridge. Immediately after the ice has completely melted from the lakes, zooplankton samples are taken once a week for six consecutive weeks at the deepest portion of the lake from an inflatable raft. Zooplankton were sampled at the deepest location of each lake by pulling a conical net (Wisconsin net) vertically through the water column (i.e., vertical tow sample). For each zooplankton sample obtained, adult organisms were identified to species, or lowest taxonomic level (Chydoridae sp. and Bosminidae sp.). Larvae of cladocerans were counted together as neonates; calanoid and cyclopoid copepodites were counted together as nauplii. Individual body lengths of the first 50 -100 (when possible) individuals of each taxon were recorded using a calibrated eyepiece micrometer and means reported.
DOI: 10.6084/m9.figshare.3761562.v2583
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.5517/ccdc.csd.cc2dlfgx
title: CCDC 2222249: Experimental Crystal Structure Determination

description: Related Article: Zhenxin Liang, Mengyi Huang, Jinling Huang, Shuyu Zhang, Yuehong Wen, Qi-Long Zhu, Xin-Tao Wu|2023|Cryst.Growth Des.|23|3437|doi:10.1021/acs.cgd.2c01552
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.cc2dlfhy
title: CCDC 2222250: Experimental Crystal Structure Determination

description: Related Article: Zhenxin Liang, Mengyi Huang, Jinling Huang, Shuyu Zhang, Yuehong Wen, Qi-Long Zhu, Xin-Tao Wu|2023|Cryst.Growth Des.|23|3437|doi:10.1021/acs.cgd.2c01552
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.cc2dlfjz
title: CCDC 2222251: Experimental Crystal Structure Determination

description: Related Article: Zhenxin Liang, Mengyi Huang, Jinling Huang, Shuyu Zhang, Yuehong Wen, Qi-Long Zhu, Xin-Tao Wu|2023|Cryst.Growth Des.|23|3437|doi:10.1021/acs.cgd.2c01552
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.cc2dlfk0
title: CCDC 2222252: Experimental Crystal Structure Determination

description: Related Article: Zhenxin Liang, Mengyi Huang, Jinling Huang, Shuyu Zhang, Yuehong Wen, Qi-Long Zhu, Xin-Tao Wu|2023|Cryst.Growth Des.|23|3437|doi:10.1021/acs.cgd.2c01552
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.cc2dlfl1
title: CCDC 2222253: Experimental Crystal Structure Determination

description: Related Article: Zhenxin Liang, Mengyi Huang, Jinling Huang, Shuyu Zhang, Yuehong Wen, Qi-Long Zhu, Xin-Tao Wu|2023|Cryst.Growth Des.|23|3437|doi:10.1021/acs.cgd.2c01552
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/5665559
title: #ChatGPT 1000 Daily 🐦 Tweets
DOI: 10.5281/zenodo.7489364
title: Direct evidence of substorm-related impulsive injections of electrons at Mercury

description: This data set includes electron energy-time spectrograms obtained by MEA1 and MEA2 in units of differential energy flux (eV/cm^2/s/sr/eV) and energetic neutral atoms obtained by ENA in counts during BepiColombo Mio's first Mercury flyby. The data are uncalibrated, thus to properly use these data, contacting PI teams is highly recommended.
DOI: 10.5281/zenodo.7489365
title: Direct evidence of substorm-related impulsive injections of electrons at Mercury

description: This data set includes electron energy-time spectrograms obtained by MEA1 and MEA2 in units of differential energy flux (eV/cm^2/s/sr/eV) and energetic neutral atoms obtained by ENA in counts during BepiColombo Mio's first Mercury flyby. The data are uncalibrated, thus to properly use these data, contacting PI teams is highly recommended.
DOI: 10.6084/m9.figshare.22806656
title: B*51:05 Count Matrix

description: B*51:05 Count Matrix
DOI: 10.6084/m9.figshare.22806656.v1
title: B*51:05 Count Matrix

description: B*51:05 Count Matrix
DOI: 10.26093/cds/vizier.17680099
title: X-ray survey of YSOs in Orion A

description: VizieR online Data Catalogue associated with article published in journal Astronomical Journal (AAS) with title 'An X-ray survey of the young stellar population of the Lynds 1641 and iota Orionis regions.' (bibcode: 2013ApJ...768...99P)
DOI: 10.6084/m9.figshare.22806650
title: B*57:02 Count Matrix

description: B*57:02 Count Matrix
DOI: 10.6084/m9.figshare.22806650.v1
title: B*57:02 Count Matrix

description: B*57:02 Count Matrix
DOI: 10.6084/m9.figshare.22806641
title: B*14:01 Count Matrix

description: B*14:01 Count Matrix
DOI: 10.6084/m9.figshare.22806641.v1
title: B*14:01 Count Matrix

description: B*14:01 Count Matrix
DOI: 10.34740/kaggle/dsv/4229511
title: Herbarium 2021 Balanced-8K
DOI: 10.6084/m9.figshare.22806671
title: sEH dataset for GFlowNet.

description: Total unique molecule graphs = 34,012,224. Reward is from a proxy model trained to predict binding affinity to soluble epoxide hydrolase from AutoDock. We build using 18 blocks with 2 stems, and use 6 blocks per molecule. <br> block_18_stop6.pkl.gz is a dictionary mapping x (strings) to AutoDock rewards. sehstr_gbtr_allpreds.pkl.gz is a dictionary mapping x (strings) to proxy model rewards.
DOI: 10.5281/zenodo.7927158
title: Simulation data for: Poly(A)-binding protein is an ataxin-2 chaperone that regulates biomolecular condensates.

description: Trajectory data and analysis scripts for the simulation component in: <strong>Poly(A)-binding protein is an ataxin-2 chaperone that regulates biomolecular condensates, </strong>by Steven Boeynaems et al.
DOI: 10.5281/zenodo.7927157
title: Simulation data for: Poly(A)-binding protein is an ataxin-2 chaperone that regulates biomolecular condensates.

description: Trajectory data and analysis scripts for the simulation component in: <strong>Poly(A)-binding protein is an ataxin-2 chaperone that regulates biomolecular condensates, </strong>by Steven Boeynaems et al.
DOI: 10.6084/m9.figshare.22806725
title: Web photos for publication_with_grading_May_2023_SP.zip

description: The data was used to remotely detect the possible incursion of coconut rhinoceros beetle and assess damage levels using publicly available images. The method involves searching for pictures of palms and identifying those with the distinctive V-shaped cuts in fronds characteristic of CRB feeding.
DOI: 10.6084/m9.figshare.22582387
title: Dataset for Towards an Automatic Optimisation Model Generator Assisted with Generative Pre-trained Transformer.

description: Dataset for Towards an Automatic Optimisation Model Generator Assisted<br> with Generative Pre-trained Transformer <br> Preprint: https://doi.org/10.48550/arXiv.2305.05811 <br> Abstract: This article presents a framework for generating optimisation models using a pre-trained generative transformer. The framework involves specifying the features that the optimisation model should have and using a language model to generate an initial version of the model. The model is then tested and validated, and if it contains build errors, an automatic edition process is triggered. An experiment was performed using MiniZinc as the target language and two GPT-3.5 language models for generation and debugging. The results show that the use of language models for the generation of optimisation models is feasible, with some models satisfying the requested specifications, while others require further refinement. The study provides promising evidence for the use of language models in the modelling of optimisation problems and suggests avenues for future research.