cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6073/pasta/c8d0512cc4439f61dffc87d757e6dc41
title: Snow grain data for Niwot Ridge and Green Lakes Valley, 1995 - ongoing.

description: Snow pits were excavated at various locations on Niwot Ridge and within the Green Lakes Valley. Temperature and snow density were measured at various depths throughout the snow cover profiles to characterize the temperature and snow water equivalent (SWE) of the snowpack throughout the year. Snow density was measured at 10-cm intervals using a 1000-ml cutter. Data on snow grain qualities were collected beginning in the 1994-95 snow season.
DOI: 10.6084/m9.figshare.3761562.v2287
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: 10.6073/pasta/840ebb6d2be2ea437df1a8c7023f4d2d
title: Snow cover profile data for Niwot Ridge and Green Lakes Valley, 1993 - ongoing.

description: Snow pits were excavated at various locations on Niwot Ridge and within the Green Lakes Valley. Temperature and snow density were measured at various depths throughout the snow cover profiles to characterize the temperature and snow water equivalent (SWE) of the snowpack throughout the year. Snow density was measured at 10-cm intervals using a 1000-ml cutter. Data on snow grain qualities were collected beginning in the 1994-95 snow season.
DOI: 10.6073/pasta/b92a338062c656ab70b4555629438619
title: Federal sampler data for Saddle and C1, 2016 - ongoing.

description: We use an aluminum Standard Federal Snow Sampler to measure snow depth and snow water equivalent (SWE). This device, compared to traditional snow pit techniques, provides efficient measurement capabilities that are less disruptive to the snowpack. Manual Federal Sampler measurements provide high accuracy point data to determine the amount of water in the surrounding snowpack. With a high downstream reliance on water within the regional snowpack, our weekly measurements give a time series of SWE throughout the winter season, offering consistent and dependable information for water resource planning and preparation.
DOI: 10.26208/hggw-qg95
title: Supplementary data, code, and information for ‘Global surface temperature over the past two millennia’

description: We present reconstructions of Northern and Southern Hemisphere mean surface temperature over the past two millennia based on high-resolution ‘proxy’ temperature data which retain millennial-scale variability. These reconstructions indicate that late 20th century warmth is unprecedented for at least roughly the past two millennia for the Northern Hemisphere. Conclusions for the Southern Hemisphere and global mean temperature are limited by the sparseness of available proxy data in the Southern Hemisphere at present.
DOI: 10.26208/kyqa-vs22
title: Supplementary data, code, and information for ‘Climate over Past Millennia’

description: We review evidence for climate change over the past several millennia from instrumental and high-resolution climate ‘‘proxy’’ data sources and climate modeling studies. We focus on changes over the past 1 to 2 millennia. We assess reconstructions and modeling studies analyzing a number of different climate fields, including atmospheric circulation diagnostics, precipitation, and drought. We devote particular attention to proxy-based reconstructions of temperature patterns in past centuries, which place recent large-scale warming in an appropriate longer-term context. Our assessment affirms the conclusion that late 20th century warmth is unprecedented at hemispheric and, likely, global scales. There is more tentative evidence that particular modes of climate variability, such as the El Niño/Southern Oscillation and the North Atlantic Oscillation, may have exhibited late 20th century behavior that is anomalous in a long-term context. Regional conclusions, particularly for the Southern Hemisphere and parts of the tropics where high-resolution proxy data are sparse, are more circumspect. The dramatic differences between regional and hemispheric/ global past trends, and the distinction between changes in surface temperature and precipitation/drought fields, underscore the limited utility in the use of terms such as the ‘‘Little Ice Age’’ and ‘‘Medieval Warm Period’’ for describing past climate epochs during the last millennium. Comparison of empirical evidence with proxy-based reconstructions demonstrates that natural factors appear to explain relatively well the major surface temperature changes of the past millennium through the 19th century (including hemispheric means and some spatial patterns). Only anthropogenic forcing of climate, however, can explain the recent anomalous warming in the late 20th century
DOI: 10.25919/akej-ww25
title: Parkes observations for project P595 semester 2022APRS_07

description: We propose to continue the PULSE@Parkes project in which high school students from Australia and around the World use the Parkes radio telescope in a remote observing model to observe and analyse pulsar data. The data from some PULSE@Parkes observations are used to support the space missions, other observations supplement the P456 Pulsar Timing Array project and the remainder were chosen in order to make a detailed analysis of pulsar timing irregularities and intermittency.
DOI: 10.6084/m9.figshare.20277561.v1
title: DIPY_Synb0_test_data

description: synb0 test data for dipy
DOI: 10.6084/m9.figshare.20277561.v2
title: DIPY_Synb0_test_data

description: synb0 test data for dipy
DOI: 10.6084/m9.figshare.20362251
title: S_tragus_fastQ117

description: fastQ files from site 117
DOI: 10.6084/m9.figshare.20362251.v1
title: S_tragus_fastQ117

description: fastQ files from site 117
DOI: 10.6073/pasta/b11d576b93c8c10344b0aad4a88e726c
title: Sediment elevation measurements for 10 GCE-LTER sampling sites from December 2001 to December 2019

description: Soil surface elevation was measured in tidal marshes at 10 GCE-LTER sampling sites from December 2001 to December 2019 using a sediment elevation table method. The sites represent three estuaries of the Georgia coast (USA) that vary in delivery of freshwater and sediment. The study was conducted to evaluate the effects of freshwater input on marsh accretion and subsidence. In 2013, rod SETs were added at site 11 and installed to replace broken SETs at sites 7 and 9 (which broke in 2012).
DOI: 10.6084/m9.figshare.20362299
title: S_tragus_fastQ108

description: fastq reads for site 108
DOI: 10.6084/m9.figshare.20362299.v1
title: S_tragus_fastQ108

description: fastq reads for site 108
DOI: 10.6073/pasta/460ab8788d7a4e8fcdf5e3f4b8e5f55c
title: Critical slowing down: vegetation height, cover and composition assess resilience of tidal fresh, brackish and salt marshes following experimental disturbance at twelve sites across the estuarine landscape

description: We investigated the relative recovery rates of vegetation cover, vegetation height and community composition over a period of &gt;10 years after experimental disturbance in 12 tidal marshes (two oligohaline, three mesohaline and seven polyhaline sites) across the estuarine landscape on the coast of Georgia, USA. Vegetation was removed from three by three meter plots (four per site) with herbicide in 2006 followed by repeated clipping through 2009. Vegetation height, cover and composition was assessed in experimental and control plots (4 of each per site) from 2010 to 2020. The goal of the study was to assess how quickly the sites recovered from disturbance, how this varied in different types of marshes, and how results varied depending on whether recovery was assessed by vegetation height, cover or composition.
DOI: 10.5281/zenodo.6886509
title: Stegonotus admiraltiensis zanfona 1

description: .
DOI: 10.5281/zenodo.6886508
title: Stegonotus admiraltiensis zanfona 1

description: .
DOI: 10.13012/b2idb-0410446_v1
title: "Farmer Preferences for Agricultural Soil Carbon Sequestration Schemes." Online Supplementary Appendix, Applied Economic Perspectives and Policy

description: This file contains the supplemental appendix for the article "Farmer Preferences for Agricultural Soil Carbon Sequestration Schemes" published in Applied Economic Policy and Perspectives (accepted 2017).
DOI: 10.6084/m9.figshare.20362302
title: S_tragus_fastQ31

description: fastQ reads for site 31
DOI: 10.6084/m9.figshare.20362302.v1
title: S_tragus_fastQ31

description: fastQ reads for site 31
DOI: 10.34740/kaggle/dsv/3975016
title: Elon Musk Tweets
DOI: 10.13012/b2idb-0478588_v1
title: Biotic homogenization of regional wetland plant communities within short timescales in the presence of an aggressive invader

description: This is the dataset used in the Journal of Ecology publication of the same name. It is a site by species matrix of species relative abundances. More information about this dataset: Interested parties can request data from the Critical Trends Assessment Program, which was the source for the data on the wetlands in this study. More information on the program and data requests can be obtained by visiting the program webpage. Critical Trends Assessment Program, Illinois Natural History Survey. http://wwx.inhs.illinois.edu/research/ctap/
DOI: 10.5281/zenodo.6869110
title: UG100 Dataset

description: The UG100 dataset contains the adversarial attack results of seven \(L_\infty\) approximate attacks (+ MIP) on the MNIST and CIFAR10 datasets. Specifically, it contains ~2.3k adversarial examples generated by the following attacks: Basic Iterative Method ("bim") Brendel & Bethge Attack ("brendel") Carlini & Wagner Attack ("carlini") Deepfool ("deepfool") Fast Gradient Sign Method ("fast_gradient") Projected Gradient Descent ("pgd") Uniform noise ("uniform") MIPVerify ("mip") It also includes adversarial distances (for all attacks) and bounds (for MIP), as well as MIP convergence times. Applications of this dataset include: Studying how, when and why adversarial attacks are close-to-optimal; Training classifiers that are robust to adversarial noise; Benchmarking new adversarial attacks. The companion code for this dataset is available here.
description: Please cite this dataset as: Samuele Marro and Michele Lombardi. Asymmetries in Adversarial Settings. 2022. We acknowledge the CINECA award under the ISCRA initiative, for the availability of high performance computing resources and support. We also thank Rebecca Montanari and Andrea Borghesi for their advice and support.
description: {"references": ["Alexey Kurakin, Ian Goodfellow, and Samy Bengio. Adversarial machine learning at scale. 2017", "Wieland Brendel, Jonas Rauber, Matthias K\u00fcmmerer, Ivan Ustyuzhaninov, and Matthias Bethge. Accurate, reliable and fast robustness evaluation. Advances in Neural Information Processing Systems, 32, 2019.", "Nicholas Carlini and David Wagner. Towards evaluating the robustness of neural networks. In 2017 IEEE Symposium on Security and Privacy (SP), pages 39\u201357. IEEE, 2017.", "Seyed-Mohsen Moosavi-Dezfooli, Alhussein Fawzi, and Pascal Frossard. Deepfool: a simple and accurate method to fool deep neural networks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 2574\u20132582, 2016.", "Ian Goodfellow, Jonathon Shlens, and Christian Szegedy. Explaining and harnessing adversarial examples. In International Conference on Learning Representations, 2015.", "Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu. Towards deep learning models resistant to adversarial attacks. In International Conference on Learning Representations, 2018."]}
DOI: 10.5281/zenodo.6582511
title: UG100 Dataset

description: The UG100 dataset contains the adversarial attack results of seven \(L_\infty\) approximate attacks (+ MIP) on the MNIST and CIFAR10 datasets. Specifically, it contains ~2.3k adversarial examples generated by the following attacks: Basic Iterative Method ("bim") Brendel & Bethge Attack ("brendel") Carlini & Wagner Attack ("carlini") Deepfool ("deepfool") Fast Gradient Sign Method ("fast_gradient") Projected Gradient Descent ("pgd") Uniform noise ("uniform") MIPVerify ("mip") It also includes adversarial distances (for all attacks) and bounds (for MIP), as well as MIP convergence times. Applications of this dataset include: Studying how, when and why adversarial attacks are close-to-optimal; Training classifiers that are robust to adversarial noise; Benchmarking new adversarial attacks. The companion code for this dataset is available here.
description: Please cite this dataset as: Samuele Marro and Michele Lombardi. Asymmetries in Adversarial Settings. 2022. We acknowledge the CINECA award under the ISCRA initiative, for the availability of high performance computing resources and support. We also thank Rebecca Montanari and Andrea Borghesi for their advice and support.
description: {"references": ["Alexey Kurakin, Ian Goodfellow, and Samy Bengio. Adversarial machine learning at scale. 2017", "Wieland Brendel, Jonas Rauber, Matthias K\u00fcmmerer, Ivan Ustyuzhaninov, and Matthias Bethge. Accurate, reliable and fast robustness evaluation. Advances in Neural Information Processing Systems, 32, 2019.", "Nicholas Carlini and David Wagner. Towards evaluating the robustness of neural networks. In 2017 IEEE Symposium on Security and Privacy (SP), pages 39\u201357. IEEE, 2017.", "Seyed-Mohsen Moosavi-Dezfooli, Alhussein Fawzi, and Pascal Frossard. Deepfool: a simple and accurate method to fool deep neural networks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 2574\u20132582, 2016.", "Ian Goodfellow, Jonathon Shlens, and Christian Szegedy. Explaining and harnessing adversarial examples. In International Conference on Learning Representations, 2015.", "Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu. Towards deep learning models resistant to adversarial attacks. In International Conference on Learning Representations, 2018."]}
DOI: 10.5281/zenodo.6582512
title: UG100 Dataset

description: The UG100 dataset contains the adversarial attack results of seven \(L_\infty\) approximate attacks (+ MIP) on the MNIST and CIFAR10 datasets. Specifically, it contains ~2.3k adversarial examples generated by the following attacks: Basic Iterative Method ("bim") Brendel & Bethge Attack ("brendel") Carlini & Wagner Attack ("carlini") Deepfool ("deepfool") Fast Gradient Sign Method ("fast_gradient") Projected Gradient Descent ("pgd") Uniform noise ("uniform") MIPVerify ("mip") It also includes adversarial distances (for all attacks) and bounds (for MIP), as well as MIP convergence times. Applications of this dataset include: Studying how, when and why adversarial attacks are close-to-optimal; Training classifiers that are robust to adversarial noise; Benchmarking new adversarial attacks. The companion code for this dataset is available here.
description: Please cite this dataset as: Samuele Marro and Michele Lombardi. Asymmetries in Adversarial Settings. 2022. We acknowledge the CINECA award under the ISCRA initiative, for the availability of high performance computing resources and support. We also thank Rebecca Montanari and Andrea Borghesi for their advice and support.
description: {"references": ["Alexey Kurakin, Ian Goodfellow, and Samy Bengio. Adversarial machine learning at scale. 2017", "Wieland Brendel, Jonas Rauber, Matthias K\u00fcmmerer, Ivan Ustyuzhaninov, and Matthias Bethge. Accurate, reliable and fast robustness evaluation. Advances in Neural Information Processing Systems, 32, 2019.", "Nicholas Carlini and David Wagner. Towards evaluating the robustness of neural networks. In 2017 IEEE Symposium on Security and Privacy (SP), pages 39\u201357. IEEE, 2017.", "Seyed-Mohsen Moosavi-Dezfooli, Alhussein Fawzi, and Pascal Frossard. Deepfool: a simple and accurate method to fool deep neural networks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 2574\u20132582, 2016.", "Ian Goodfellow, Jonathon Shlens, and Christian Szegedy. Explaining and harnessing adversarial examples. In International Conference on Learning Representations, 2015.", "Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu. Towards deep learning models resistant to adversarial attacks. In International Conference on Learning Representations, 2018."]}
DOI: 10.13012/b2idb-6316661_v1
title: CyberGIS-Jupyter HAND Example Notebook

description: The dataset contains a complete example (inputs, outputs, codes, intermediate results, visualization webpage) of executing Height Above Nearest Drainage HAND workflow with CyberGIS-Jupyter.
DOI: 10.13012/b2idb-3357538_v1
title: Data-Theoretic: DT-BASE - Training Quality Causal Model

description: Dataset includes structure and values of a causal model for Training Quality in nuclear power plants. Each entry refers to a piece of evidence supporting causality of the Training Quality causal model. Includes bibliographic information, context-specific text from the reference, and three weighted values; (M1) credibility of reference, (2) causality determined by the author, and (3) analysts confidence level. (M1, M2, and M3) Weight metadata are based on probability language from: IPCC, Climate change, in Synthesis Report. 2001, Intergovernmental Panel on Climate Change (IPCC). Weight Metadata: LowerBound_Probability, UpperBound_Probability, Qualitative Language 0.99, 1, Virtually Certain 0.9, 0.99, Very Likely 0.66, 0.9, Likely 0.33, 0.66, Medium Likelihood 0.1, 0.33, Unlikely 0.01, 0.1, Very Unlikely 0, 0.01, Extremely Unlikely
DOI: 10.13012/b2idb-2872989_v1
title: Data for: Sense of Belonging Predicts Perceived Helpfulness in Online Peer Help-Giving Interactions

description: This dataset was developed as part of an online survey study that explores student characteristics that may predict what one finds helpful in replies to requests for help posted to an online college course discussion forum. 223 college students enrolled in an introductory statistics course were surveyed on their sense of belonging to their course community, as well as how helpful they found 20 examples of replies to requests for help posted to a statistics course discussion forum.
DOI: 10.6084/m9.figshare.20362323
title: S_tragus_fastQ145

description: FastQ reads for site 145
DOI: 10.6084/m9.figshare.20362323.v1
title: S_tragus_fastQ145

description: FastQ reads for site 145
DOI: 10.6084/m9.figshare.20362335
title: S_tragus_fastQ56

description: fastQ sequences for site 56
DOI: 10.6084/m9.figshare.20362335.v1
title: S_tragus_fastQ56

description: fastQ sequences for site 56
DOI: 10.5281/zenodo.6886658
title: Toxicocalamus goodenoughensis zanfona 1

description: .
DOI: 10.5281/zenodo.6886657
title: Toxicocalamus goodenoughensis zanfona 1

description: .
DOI: 10.25934/pr00008302
title: A Phase II Randomized, Double-Blind, Study of Ipatasertib (GDC-0068), an Inhibitor to AKT, in Combination With Paclitaxel as Neoadjuvant Treatment for Patients With Early Stage Triple Negative Breast Cancer

description: This is a randomized, double-blind, placebo-controlled, multicenter, pre-operative Phase II study designed to estimate the efficacy of ipatasertib combined with paclitaxel chemotherapy versus placebo combined with paclitaxel chemotherapy in women with Stage Ia - IIIa triple-negative breast adenocarcinoma. The anticipated time on study treatment is 12 weeks.
DOI: 10.5281/zenodo.6886685
title: Analysis of Data Consistency of Howells' Craniometric Data Sets

description: Derived data and R scripts for analyzing the data consistency of Howells' craniometric data sets.
DOI: 10.5281/zenodo.6886684
title: Analysis of Data Consistency of Howells' Craniometric Data Sets

description: Derived data and R scripts for analyzing the data consistency of Howells' craniometric data sets.
DOI: 10.5281/zenodo.6886693
title: Trimeresurus albolabris zanfona 1

description: .
DOI: 10.5281/zenodo.6886692
title: Trimeresurus albolabris zanfona 1

description: .
DOI: 10.5281/zenodo.6851219
title: Integration of an event-driven Timepix3 hybrid pixel detector into a cryo-EM workflow

description: <strong>Abstract</strong> The development of direct electron detectors has played a key role in low-dose electron microscopy imaging applications. Monolithic active-pixel sensor (MAPS) detectors are currently widely applied for cryogenic electron microscopy (cryo-EM); however, they have best performance at 300~kV, have relatively low read-out speed and only work in imaging mode. Hybrid pixel detectors (HPDs) can operate at any energy, have a higher DQE at lower voltage, have unprecedented high time resolution, and can operate in both imaging and diffraction modes. This could make them well-suited for novel low-dose life-science applications, such as cryo-ptychography, iDPC, and liquid cell imaging. Timepix3 is not frame-based, but truly event-based, and can record individual hits with 1.56~ns time resolution. Here, we present the integration of such a detector into a cryo-EM workflow and demonstrate that it can be used for automated data collection on biological specimens. The performance of the detector in terms of MTF and DQE has been investigated at 200~kV and we studied the effect of deterministic blur. We describe a single-particle analysis structure of \SI{3}{\angstrom} resolution and compare it with Falcon3 data collected under the same microscope. These studies could pave the way toward more efficient low-dose single-particle techniques. <strong>Data description</strong> Data has been split up in several different directories. In general: each directory contains individual READMEs <strong>Flat fields</strong> Collected on both TImepix3 and Falcon3 at 200 kV using a Tecnai Arctica microscope. These data have been used for calculating NPS, ToT correction and gain correction. <strong>Knife edge</strong> Collected on both TImepix3 and Falcon3 at 200 kV using a Tecnai Arctica microscope. These data have been used for calculating MTF. <strong>ToT correction calibration file</strong> This calibration file has been used to correct all raw Timepix3 data. Including micrographs deposited in EMPIAR. <strong>Gain correction</strong> Gain correction files calculated from flat field data for several different image formation methods of the Timepix3. The Python script for calculating the gain has been included. <strong>Software</strong> The software tpx3HitParser, tpx3EventViewer and the MTF-NPS-DQE scripts have listed as related identifiers to this entry.
DOI: 10.5281/zenodo.6791408
title: Controls on nitrite oxidation in the upper Southern Ocean: insights from winter kinetics experiments in the Indian sector

description: This is a dataset to the paper "Controls on nitrite oxidation in the upper Southern Ocean: insights from winter kinetics experiments in the Indian sector" published under the Biogeosciences journal. This dataset contains rates of nitrite oxidation, kinetic parameters (half-saturation constant and maximum oxidation rate) for nitrite oxidation, latitudinal gradient of surface nitrite concentrations, integrated rates of ammonium and nitrite oxidation.
DOI: 10.5281/zenodo.6791407
title: Controls on nitrite oxidation in the upper Southern Ocean: insights from winter kinetics experiments in the Indian sector

description: This is a dataset to the paper "Controls on nitrite oxidation in the upper Southern Ocean: insights from winter kinetics experiments in the Indian sector" published under the Biogeosciences journal. This dataset contains rates of nitrite oxidation, kinetic parameters (half-saturation constant and maximum oxidation rate) for nitrite oxidation, latitudinal gradient of surface nitrite concentrations, integrated rates of ammonium and nitrite oxidation.
DOI: 10.6084/m9.figshare.20362374
title: min

description: hydrology
DOI: 10.6084/m9.figshare.20362374.v1
title: min

description: hydrology