cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.23728/b2share.061ebbcf764544b59ce834c316f07045
title: Undetected BVOCs from Norway spruce drive total ozone reactivity measurements

description: Biogenic Volatile Organic Compounds (BVOCs) are continuously emitted from terrestrial vegetation into the atmosphere and react with various atmospheric oxidants, with ozone being an important one. The reaction between BVOCs and ozone can lead to low volatile organic compounds, other pollutants, and the formation of secondary organic aerosols. To understand the chemical and physical processes taking place in the atmosphere, a complete picture of the BVOCs emitted is necessary. However, the large pool of BVOCs present makes it difficult to detect every compound. The total ozone reactivity method can help understand the ozone reactive potential of all BVOCs emitted into the atmosphere and also help determine if current analytical techniques can measure the total BVOC budget. In this study, we measured the total ozone reactivity from the emissions of a Norway spruce tree in Hyytiälä in late summer using the Total Ozone Reactivity Monitor (TORM) built at the Finnish Meteorological Institute (FMI). We also conducted chemical characterisation and quantification of the BVOC emissions using a gas chromatograph coupled with a mass spectrometer (GC-MS). The measured total ozone reactivity reached up to 7.3 $\times$ 10$^{-9}$ \unit{m^{3}\,s^{-2}\,g^{-1}}, which corresponds to 64 \unit{\mu g\,g^{-1}\,h^{-1}} of \chem{\alpha}-pinene. Stress-related sesquiterpenes such as \chem{\beta}-farnesene and \chem{\alpha}-farnesene, and an unidentified sesquiterpene contributed the most to the observed emissions. However, the observed emissions made up only 35\% of the measured total ozone reactivity, with sesquiterpenes being the most important sink for the ozone. High total ozone reactivity was especially seen during high temperature periods, with up to 95\% of the reactivity remaining unexplained. Emissions of unidentified stress-related compounds could be the reason for the high fraction of missing reactivity
DOI: 10.5281/zenodo.4429262
title: SH2-containing-inositol-5-phosphatases (INPP5D); A Target Enabling Package

description: SH2-containing-inositol-5-phosphatases (SHIP1 and SHIP2, coded for by genes <em>INPP5D</em> and <em>INPPL1</em>, respectively) dephosphorylate phosphatidylinositol-3,4,5-trisphosphate (PI(3,4,5)P<sub>3</sub>) to produce phosphatidylinositol-3,4-bisphosphate (PI(3,4)P<sub>2</sub>). This is an important part of the PI3K/AKT/mTOR signalling pathway. The SHIPs have been linked to a range of conditions, including cancer, diabetes, hypertension, and graft versus host disease. A link has also been demonstrated by GWAS between a non-coding mutation in the <em>INPP5D</em> (SHIP1) gene and increased risk of late-onset Alzheimer’s disease. The role of SHIP1 in Alzheimer’s disease is believed to be mediated through inflammatory processes such as the regulation of microglia and cytokine release. The distinction between the effects of SHIP1 and SHIP2 on these processes is not fully understood. In this TEP we present an apo structure of the phosphatase and C2 domains of SHIP1 and a structure with a magnesium ion and a phosphate ion bound to the active site. We also present 91 fragment bound structures that may act as starting points for the modulation of SHIP1. We are also able to crystallise an equivalent construct of SHIP2 and purify a range of other inositol-5-phosphatases to serve as a selectivity panel for the development of specific compounds. An assay has also been developed.
description: This document represents version 1 of the TEP datasheet and includes all updates on the project as of November 2020. For more information about TEPs and the TEP Programme, please visit https://thesgc.org/tep.
DOI: 10.5281/zenodo.5530410
title: Webis Clickbait Corpus 2017 (Webis-Clickbait-17)

description: The Webis Clickbait Corpus 2017 (Webis-Clickbait-17) comprises a total of 38,517 Twitter posts from 27 major US news publishers. In addition to the posts, information about the articles linked in the posts are included. The posts had been published between November 2016 and June 2017. To avoid publisher and topical biases, a maximum of ten posts per day and publisher were sampled. All posts were annotated on a 4-point scale [not click baiting (0.0), slightly click baiting (0.33), considerably click baiting (0.66), heavily click baiting (1.0)] by five annotators from Amazon Mechanical Turk. A total of 9,276 posts are considered clickbait by the majority of annotators. In terms of its size, this corpus outranges the Webis Clickbait Corpus 2016 by one order of magnitude. The corpus is divided into two logical parts, a training and a test dataset. The training dataset has been released in the course of the Clickbait Challenge and a download link is provided below. To allow for an objective evaulatuion of clickbait detection systems, the test dataset is available only through the Evaluation-as-a-Service platform TIRA at the moment. On TIRA, developers can deploy clickbait detection systems and execute them against the test dataset. The performance of the submitted systems can be viewed on the TIRA page of the Clickbait Challenge. To make working with the Webis Clickbait Corpus 2017 convenient, and to allow for its validation and replication, we are developing and sharing a number of software tags: Corpus Viewer. Our Django web service for exploring corpora. For importing the Webis Clickbait Corpus 2017 into the corpus viewer, we provide an appropriate configuration file. MTurk Manager. Our Django web service for conducting sophisticated crowd sourcing tasks on Amazon Mechanical Turk. The service allows to manage projects, upload batches of HITS, apply custom reviewing interfaces, and more. To make the clickbait crowd-sourcing task replicable, we share the worker template that we used to instruct the workers and to display the tweets. Also shared is a reviewing template that can be used to accept/reject assignments and to assess the quality of the received annotations quickly. Web Archiver. Software for archiving web pages as WARC files and reproducing them later on. This software can be used to open the WARC archives provided above. In addition to the corpus "clickbait17-train-170630.zip", we provide the original WARC archives of the articles that are linked in the posts. They are split in 5 archives that can be extracted separately.
DOI: 10.6084/m9.figshare.16910170
title: Data and Code for "Evolutionary dynamics of mutants that modify population structure"

description: Data and Code for "Evolutionary dynamics of mutants that modify population structure": Python scripts used to compute the data and Mathematica notebooks used to produce the plots.
DOI: 10.6084/m9.figshare.21343359.v1
title: Dataset for: Food limitation reduces risk avoidance by prey, but does not increase kill rates in a simple predator-prey system

description: Datasets used to fit seasonal resource selection functions (RSFs) to puma, vicuña, and kill site GPS data. Vicuña data is split by the two study sites (LL: Llano de los Leones, SGC: San Guillermo Canyon). We also include the dataset used to compare kill rates between the growing (GS) and the non-growing (NGS) seasons.
DOI: 10.21227/g4y0-sw34
title: UCI datasets

description: The UCI dataset is a data repository maintained and made available by the University of California, Irvine that is widely used for machine learning and data mining research. The dataset covers a wide range of fields and topics, including but not limited to medicine, biology, social sciences, physics, engineering, and more. The uniqueness of this dataset is that it contains data from multiple different domains and sources, allowing researchers to explore and analyze the data from different perspectives and contexts. This experiment applies it to cluster analysis, and the main datasets used are eight synthetic datasets and six real datasets.
DOI: 10.14459/2023mp1725057
title: The Performance of Post-Quantum TLS 1.3: Raw Data

description: This Dataset contains PCAPs for the reproducibility of the paper "The Performance of Post-Quantum TLS 1.3": Quantum Computers (QCs) differ radically from traditional computers and can efficiently solve mathematical problems fundamental to our current cryptographic algorithms. Although existing QCs need to accommodate more qubits to break cryptographic algorithms, the concern of "Store-Now-Decrypt-Later" (i.e., adversaries store encrypted data today and decrypt them once powerful QCs become available) highlights the necessity to adopt quantum-safe approaches as soon as possible. In this work, we investigate the performance impact of Post-Quantum Cryptography (PQC) on TLS1.3. Different signature algorithms and key agreements (as proposed by the National Institute of Standards and Technology (NIST)) are examined through black- and white-box measurements to get precise handshake latencies and computational costs per participating library. Our results reveal that HQC and Kyber are on par with our current state-of-the-art, while Dilithium and Falcon are even faster. We observed no performance drawback from using hybrid algorithms; moreover, on higher NIST security levels, PQC outperformed any algorithm in use today. Hence, we conclude that post-quantum TLS is suitable for adoption in today’s systems.
DOI: 10.26050/wdcc/cd3_wam_c-rea6
title: coastDat-3 WAM wave hindcast for the period 1995 - 2018 covering the North and Baltic Sea with COSMO-REA6 atmospheric forcing

description: Project: coastDat-3 - CoastDat-3 (https://www.coastdat.de/about_us/) comprises a compilation of consistent hindcasts obtained from numerical models. The atmospheric part of the dataset is simulated by using the COSMO in CLimate Mode version 5 (http://www.clm-community.eu) with different boundary conditions. The objective is to provide a consistent meteo-marine data set. Summary: This is a wave hindcast for the period 1995 - 2018 covering the North and Baltic Sea. The simulation has been performed with the spectral wave model WAM Version 4.6.2. The model domain covers the area from approx 49.2° N to 66.6° N and 9.8° W to 31.6° E, with a spatial resolution of 0.044 degree latitude x 0.044 degree longitude (approx. 5 by 5 km) on a rotated grid with the coordinates of the rotated north pole 140°W E and 32° N. Integrated parameter derived from 2D spectra are available every hour. Atmospheric forcing was obtained from the COSMO-REA6 regional atmospheric reanalysis (https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/qj.2486) provided by the German Weather Service (DWD) . Lateral boundary conditions were obtained from corresponding coarse grid hindcast covering most of the Northeast Atlantic driven by the same atmospheric forcing.
DOI: 10.5281/zenodo.10022527
title: Analogue Memristive Devices based on La2NiO4+δ as Synapses for Spiking Neural Networks
DOI: 10.5281/zenodo.10022526
title: Analogue Memristive Devices based on La2NiO4+δ as Synapses for Spiking Neural Networks
DOI: 10.5281/zenodo.10224919
title: Instrumentos de medida del uso de las Tecnologías de la Información y Comunicación
DOI: 10.5281/zenodo.10224920
title: Instrumentos de medida del uso de las Tecnologías de la Información y Comunicación
DOI: 10.5281/zenodo.10225182
title: VAMDC extraction with identifier = 14d9f7c5-aa3b-444a-8620-6a12e5c52fc2

description: This is a dataset extracted from https://cdms.astro.uni-koeln.de/jpl/tap/ VAMDC node.
Query originating this dataset: query=select species; 
 Data source version: 2019-11-27
Data format: XSAMS 12.07
Query uuid in VAMDC query store: 14d9f7c5-aa3b-444a-8620-6a12e5c52fc2
DOI: 10.25340/r4/c0wcb7
title: Related Data for: Many-dimensional model of adolescent school enjoyment: A test using machine learning from behavioral and social-emotional problems

description: There is an emerging, many-dimensional model of human functioning that has yet to be rigorously tested in adolescent psychopathology. The model is based, in part, on research suggesting stronger predictive power at the level of single items compared to the commonly used smaller number of higher-level constructs represented by scores or factors. Here, the model is tested in research relevant for the understanding how psychopathology relates to adolescent school enjoyment. We compared, explained, and clustered machine learning model results from a set of 99 self-reported items from different instruments that measured the behavioral and social-emotional problems of adolescents to predict school enjoyment. There is support for a many-dimensional model. Individual items had unique variances beyond noise that incrementally added out-of-sample predictive power above construct-level prediction, particularly for nonlinear machine learning classifiers. Explainable machine learning uncovered important predictors of low school enjoyment, and these were specific nuances of withdrawn/depressive behaviors, elevated fears and anxieties, lowered sensation-seeking, and some conduct problems—what we term risk nuances (cf. risk factors). Clustering further identified shared risk nuances among different groups of individuals with low school enjoyment. Our results suggest that item nuances are important in revealing many ways in which adolescents’ behavioral and social-emotional problems relate to school enjoyment at the individual and group levels. A many-dimensional model can complement current descriptive, predictive, and intervention efforts in adolescent psychopathology.
DOI: 10.6084/m9.figshare.24679431
title: scaleModel.py

description: Python file
DOI: 10.6084/m9.figshare.24679431.v1
title: scaleModel.py

description: Python file
DOI: 10.6084/m9.figshare.24679437
title: scale_model_data.xlsx

description: Scale model data
DOI: 10.6084/m9.figshare.24679434
title: config_files.zip

description: Config files
DOI: 10.5281/zenodo.10225187
title: Data set for Dermal Biomimicry: Human dermal decellularized ECM Hydrogels as Fidelity-Rich Scaffolds for In Vitro Skin Models.

description: Data set for the article Dermal Biomimicry: Human dermal decellularized ECM Hydrogels as Fidelity-Rich Scaffolds for In Vitro Skin Models.
DOI: 10.5281/zenodo.10225186
title: Data set for Dermal Biomimicry: Human dermal decellularized ECM Hydrogels as Fidelity-Rich Scaffolds for In Vitro Skin Models.

description: Data set for the article Dermal Biomimicry: Human dermal decellularized ECM Hydrogels as Fidelity-Rich Scaffolds for In Vitro Skin Models.
DOI: 10.25606/surf.ac5083969f9ad7e0
title: LDBC Graphalytics graphs (2023)

description: Data sets for the LDBC Graphalytics benchmark.
DOI: 10.5281/zenodo.10171744
title: USPTO Dataset for: Fast Chemical Reaction Condition Suggestion via Rule-Based Classification and Similarity Search

description: USPTO database that is analyzed with Rxn-INSIGHT (https://github.com/mrodobbe/Rxn-INSIGHT).
This gzip file contains a very large Pandas DataFrame that can be loaded via pd.read_parquet('uspto_rxn_insight.gzip'). Because of the large size of the data, PyArrow version 13.0 must be used. 
To use parquet in Pandas, install PyArrow and fastparquet using pip:
pip install pyarrow==13.0pip install fastparquet
description: Fast Chemical Reaction Condition Suggestion via Rule-Based Classification and Similarity Search
The challenge of devising pathways for organic synthesis remains a central issue in the field of medicinal chemistry. Over the span of six decades, computer-aided synthesis planning has given rise to a plethora of potent tools for formulating synthetic routes. Nevertheless, a significant expert task still looms: determining the appropriate solvent, catalyst, and reagents when provided with a set of reactants to achieve and optimize the desired product for a specific step in the synthesis process. Typically, chemists identify key functional groups and rings that exert crucial influences at the reaction center, classify reactions into categories, and may assign them names. This research introduces Rxn-INSIGHT, an open-source algorithm based on the bond-electron matrix approach, with the purpose of automating this endeavor. Rxn-INSIGHT not only streamlines the process but also facilitates extensive querying of reaction databases, effectively replicating the thought processes of an organic chemist. The core functions of the algorithm encompass the classification and naming of reactions, extraction of functional groups, rings, and scaffolds from the involved chemical entities, and the provision of reaction condition recommendations based on the similarity and prevalence of reactions. The performance of our rule-based model has been rigorously assessed against a carefully curated benchmark dataset, exhibiting an accuracy rate exceeding 90% in reaction classification and surpassing 95% in reaction naming. Notably, it has been discerned that a pivotal factor in selecting analogous reactions lies in the analysis of ring structures participating in the reactions. An examination of ring structures within the USPTO chemical reaction database reveals that with just 35 unique rings, a remarkable 75% of all rings found in nearly 1 million products can be encompassed. Furthermore, Rxn-INSIGHT is proficient in suggesting appropriate choices for solvents, catalysts, and reagents in entirely novel reactions, all within the span of a second, utilizing nothing more than an everyday laptop.
DOI: 10.5281/zenodo.10171745
title: USPTO Dataset for: Fast Chemical Reaction Condition Suggestion via Rule-Based Classification and Similarity Search

description: USPTO database that is analyzed with Rxn-INSIGHT (https://github.com/mrodobbe/Rxn-INSIGHT).
This gzip file contains a very large Pandas DataFrame that can be loaded via pd.read_parquet('uspto_rxn_insight.gzip'). Because of the large size of the data, PyArrow version 13.0 must be used. 
To use parquet in Pandas, install PyArrow and fastparquet using pip:
pip install pyarrow==13.0pip install fastparquet
description: Fast Chemical Reaction Condition Suggestion via Rule-Based Classification and Similarity Search
The challenge of devising pathways for organic synthesis remains a central issue in the field of medicinal chemistry. Over the span of six decades, computer-aided synthesis planning has given rise to a plethora of potent tools for formulating synthetic routes. Nevertheless, a significant expert task still looms: determining the appropriate solvent, catalyst, and reagents when provided with a set of reactants to achieve and optimize the desired product for a specific step in the synthesis process. Typically, chemists identify key functional groups and rings that exert crucial influences at the reaction center, classify reactions into categories, and may assign them names. This research introduces Rxn-INSIGHT, an open-source algorithm based on the bond-electron matrix approach, with the purpose of automating this endeavor. Rxn-INSIGHT not only streamlines the process but also facilitates extensive querying of reaction databases, effectively replicating the thought processes of an organic chemist. The core functions of the algorithm encompass the classification and naming of reactions, extraction of functional groups, rings, and scaffolds from the involved chemical entities, and the provision of reaction condition recommendations based on the similarity and prevalence of reactions. The performance of our rule-based model has been rigorously assessed against a carefully curated benchmark dataset, exhibiting an accuracy rate exceeding 90% in reaction classification and surpassing 95% in reaction naming. Notably, it has been discerned that a pivotal factor in selecting analogous reactions lies in the analysis of ring structures participating in the reactions. An examination of ring structures within the USPTO chemical reaction database reveals that with just 35 unique rings, a remarkable 75% of all rings found in nearly 1 million products can be encompassed. Furthermore, Rxn-INSIGHT is proficient in suggesting appropriate choices for solvents, catalysts, and reagents in entirely novel reactions, all within the span of a second, utilizing nothing more than an everyday laptop.
DOI: 10.5281/zenodo.10225340
title: Raw Data
title: ¬¬Microgeographic differentiation in thermal and antipredator responses and their carry-over effects across life stages in a damselfly
DOI: 10.5281/zenodo.10225341
title: Raw Data
title: ¬¬Microgeographic differentiation in thermal and antipredator responses and their carry-over effects across life stages in a damselfly
DOI: 10.34740/kaggle/ds/4084841
title: Cricket World Cup 2023
DOI: 10.5284/1116041
title: Digital Data From the Archaeology Audience Network Project

description: When deposited, this collection will comprise the digital archive for the Archaeology Audience Network Project, a 2-year project that brings together many of the UK's leading archaeological organisations to build the most accurate picture to date of the audiences that public and community archaeology attracts and engages with in England and make it freely accessible online.
DOI: 10.5281/zenodo.10219517
title: Output files for MOM5 driven by JRA55-do at 1-degree and 0.25-degree horizontal resolution

description: Output files from different MOM simulations driven by JRA55-do surface dataset following the OMIP-2 protocol.  Datasets include the sixth cycle for:
1/ MOM5-LR: MOM5 at 1-degree resolution driven by JRA55-do.
2/ MOM5-HR: MOM5 at 0.25-degree resolution driven by JRA55-do
3/ MOM5-LR-winds: as in 1/ but using CORE-II zonal and meridional surface winds
4/ MOM5-LR-heat: as in 1/ but using CORE-II shortwave and longwave fluxes
DOI: 10.6084/m9.figshare.24645360
title: Systematic map from the <i>Global review of the Important Plant Areas approach</i>

description: Dataset of publications included in the systematic map undertaken for the <i>Global review of the Important Plant Areas approach</i>, a chapter in the PhD thesis <i>Plant conservation in Colombia: </i><i>Interdisciplinary approaches for the protection of useful plant species</i> (Kor, 2023).This systematic map can be filtered by a range of variables including location, publication year, language, study country, and IPA focus, with links to all literature sources provided where available. Please read the "Notes" sheet in the workbook for the search strategy and inclusion criteria used and definitions of the categories assigned to the variables.
DOI: 10.6084/m9.figshare.24645360.v1
title: Publications from Global IPA Review

description: Dataset of publications included in the systematic map undertaken for the <i>Global review of the Important Plant Areas approach</i>, a chapter in the the PhD thesis <i>Plant conservation in Colombia: </i><i>Interdisciplinary approaches for the protection of useful plant species</i> (Kor, 2023).This systematic map can be filtered by a range of variables including location, publication year, language, study country, and IPA focus, and links to all literature sources are provided where available. Please read the "Notes" sheet in the workbook for the search strategy and inclusion criteria used.
DOI: 10.57745/myg65v
title: HongistoM_JAmCeramSoc_101111jace19304_ReadMe_20230707_V0 .txt

description: Read me file
DOI: 10.57745/zdibdv
title: HongistoM_JAmCeramSoc_101111jace19304_DSCYbdopedB50glasses_20230707_V0.opj

description: OPJ Data of Table 1 of the article.
DOI: 10.5525/gla.researchdata.1541
title: Differential Rotation in Convecting Spherical Shells with Non-Uniform Viscosity and Entropy Diffusivity

description: The data is either in ascii text format or in the format of FORTRAN ".F" files or Python ".py" files.
DOI: 10.6084/m9.figshare.23550075.v1
title: CAS 滑坡数据集：用于山体滑坡检测深度学习的大规模多传感器数据集

description: 在这项工作中，我们提出了CAS滑坡数据集，这是一个用于基于深度学习的滑坡检测的大规模多传感器数据集，由中国科学院（CAS）山地灾害与环境研究所的人工智能小组开发。该数据集旨在解决滑坡识别中遇到的挑战。随着气候变化和地震导致的山体滑坡发生率增加，人们越来越需要一个精确而全面的数据集来支持快速有效的山体滑坡识别。与现有数据集的数据集大小、覆盖范围、传感器类型和分辨率限制相比，CAS 滑坡数据集包括 20,958 张图像，整合了来自 &lt;&gt; 个地区的卫星和无人机数据。为了确保可靠性和适用性，我们建立了一种稳健的方法来评估数据集的质量。我们建议使用CAS滑坡数据集作为构建滑坡识别模型的基准，并促进深度学习技术的发展。研究人员可以利用该数据集获得增强的预测、监测和分析能力，从而推进自动滑坡检测。如果您打算使用我们的数据集，请通过引用我们在您的项目中的工作来感谢我们的研究。