Find research datasets worth reusing

opencc-by-4.0May 2023View details →

Absence of large-scale ice masses in central Northeast Siberia during the Late Pleistocene Dataset

Dataset for the publication: ""Absence of large-scale ice masses in central Northeast Siberia during the Late Pleistocene"

opencc-zeroMar 2023View details →

Repository for: Genetic footprints of a rapid and large-scale range expansion: The case of cyclic common vole in Spain

Te repository contains the neccesary genetic data (microsatellite allele frequencies and GenBank accesion numbers for cytb haplotypes) to be able to replicate the analyses performed in the manuscript.

opencc-by-4.0Apr 2023View details →

Diversity of Expertise is Key to Scientific Impact: a Large Scale Analysis in the Field of Computer Science

This repository is companion to a research paper with the following abstract: Understanding the relationship between the composition of a research team and the potential impact of their research papers is crucial as it can steer the development of new science policies for improving the research enterprise. Numerous studies assess how the characteristics and diversity of research teams can influence their performance across several dimensions: ethnicity, internationality, size, and others. In this paper, we explore the impact of diversity in terms of the authors’ expertise and skills. To this purpose, we retrieved 114K papers in the field of Computer Science and analysed how the diversity of research fields within a research team relates to the number of citations their papers received in the upcoming 5 years. The results show that two different metrics reflecting the diversity of expertise are directly associated with the number of citations. This suggests that, at least in Computer Science, diversity of expertise is key to scientific impact.

opencc-by-4.0Jun 2023View details →

PTVD: A Large-Scale Plot-Oriented Multimodal Dataset Based on Television Dramas

Art forms such as movies and television (TV) dramas are reflections of the real world, which have attracted much attention from the multimodal learning community recently. However, existing corpora in this domain share three limitations: i. annotated in a scene-oriented fashion, they ignore the coherence within plots; ii. their text lacks empathy and seldom mentions situational context; iii. their video clips fail to cover long-form relationship due to short duration. To address these fundamental issues, using 1,106 TV drama episodes and 24,875 informative plot-focused sentences written by professionals, with the help of 449 human annotators, we constructed PTVD, the first plot-oriented multimodal dataset in the cinema domain.

opencc-by-4.0Dec 2022View details →

Oxonium ion scanning mass spectrometry for large-scale plasma glycoproteomics

Protein glycosylation — a complex and heterogeneous post-translational modification frequently dysregulated in disease — has been difficult to analyse at scale. Here we report a data-independent-acquisition technique for the large-scale mass-spectrometric quantification of glycopeptides in plasma samples. The technique, which we named ‘OxoScan-MS’, identifies oxonium ions as glycopeptide fragments and exploits a sliding-quadrupole dimension to generate comprehensive, untargeted oxonium ion maps of precursor masses assigned to fragment ions from non-enriched plasma samples. By applying OxoScan-MS to quantify 1,002 glycopeptide features in the plasma glycoproteomes from COVID-19 patients and healthy controls, we found that severe COVID-19 induces differential glycosylation in IgA, haptoglobin, transferrin and other disease-relevant plasma glycoproteins. OxoScan-MS may allow for the quantitative mapping of glycoproteomes at the scale of hundreds to thousands of samples.

opencc-by-4.0Jun 2023View details →

The appendix for evaluating the impact of large-scale nucleic acid testing and home quarantine on COVID-19 prevention and control: a dynamic modeling approach

Appendix I: The program of evaluating the impact of large-scale nucleic acid testing and home quarantine on COVID-19 prevention and control: a dynamic modeling approach Appendix II: The sensitivity analysis of evaluating the impact of large-scale nucleic acid testing and home quarantine on COVID-19 prevention and control: a dynamic modeling approach

opencc-zeroJun 2023View details →

Data for: Sub-zero temperatures and large-scale weather patterns induce tooth damage in Icelandic arctic foxes

Tooth damage in carnivores can reflect shifts in both diet and feeding habits, and in large carnivores it is associated with increased bone consumption. Variation in tooth condition in Icelandic arctic foxes, a mesocarnivore, was recorded from 854 individual foxes spanning 29 years. We hypothesized that annual climatic variations, which can influence food abundance and accessibility, will influence tooth condition by causing dietary shifts toward less edible prey. We examined tooth condition in relation to four climatic predictors: mean annual winter temperature, indices of both the El Niño anomaly and North Atlantic subpolar gyre (SPG), and the number of rain-on-snow days (ROS). We found unequivocal evidence for a strong effect of annual climate on tooth condition. Teeth of Icelandic foxes were in better condition when winter temperatures were higher, when the SPG was more positive, and when the number of ROS was low. We also found a substantial subregional effect with foxes from northeastern Iceland having lower tooth damage than those from two western sites. Contradicting our original hypothesis that foxes from northeastern Iceland, where foxes are known to scavenge on large mammal remains (e.g., sheep and horses), would show the highest tooth damage, we suggest that western coastal sites exhibited greater tooth damage because cold winter temperatures lowered the availability of seabirds, causing a shift in diet toward abrasive marine subsidies (e.g., bivalves) and frozen beach wrack. Our study shows that monitoring tooth breakage and wear can be a useful tool for evaluating the impact of climate on carnivore populations and that climate change may influence the condition and fitness of carnivores in complex and potentially conflicting ways.

opencc-by-4.0Jul 2023View details →

Interpreting Cis-Regulatory Interactions from Large-Scale Deep Neural Networks for Genomics

Results and code to replicate analysis in "Interpreting Cis-Regulatory Interactions from Large-Scale Deep Neural Networks for Genomics" by Toneyan and Koo.

opencc-by-4.0Jul 2023View details →

1D-1V Vlasov-Poisson Simulations of Mutual Impedance Experiments in the presence of small-scale and large-scale plasma inhomogeneities - PART 1

===================================================================================================== Author        :     L. Bucciantini Date         :    05/07/2023 Laboratory    :    CNRS-LPC2E, Orléans (France) ===================================================================================================== Dear reader, we thank you for your interest in our dataset. In this document, we describe what you will find in it. In case you need help with using the dataset, or if you are interested in mutual impedance experiments, do not hesitate to contact our team in Orléans (pierre.henri@cnrs-orleans.fr, pierre.henri@oca.eu) ===================================================================================================== Topic: This dataset contains the outputs of numerical simulations performed to assess the impact of plasma inhomogeneities on the diagnostic performance of mutual impedance experiments. Numerical model: The outputs are obtained from a numerical model based on the solution of the 1D-1V Vlasov-Poisson system of equations. The scheme used to solve the model is the one developed by Mangeney et al. (2002),  A Numerical Scheme for the Integration of the Vlasov-Maxwell System of Equations. Journal of Computational Physics, (doi: https://doi.org/10.1006/jcph.2002.7071). The 1D-1V Vlasov-Poisson version of this model is described in Henri, et al. (2010), Vlasov-Poisson simulations of electrostatic parametric instability for localized Langmuir wave packets in the solar wind, Journal of Geophysical Research (Space Physics), 115, 6106 (2010) ----------------------------------------------------------------------------------------------------- What is inside the dataset: The dataset is composed of 7 different mutual impedance measurements, each corresponding to one directory (see below). The measurements (i.e. directory) correspond to small-scale plasma inhomogeneities at different positions with respect to the mutual impedance antennas, or to a large-scale plasma inhomogeneity. Each directory contains a number of folders. Each folder corresponds to the emission of a signal at different frequency. ----------------------------------------------------------------------------------------------------- List of directories: (Note : each directory corresponds to one mutual impedance measurement) L        :    These outputs correspond to one mutual impedance measurement in                 small antenna emission amplitude, which corresponds to a linear                 plasma response to the emission. s_xx     :    Each of these outputs corresponds to one mutual impedance measurement in correspondance of         a small-scale plasma inhomogeneity at xx Debye lengths of distance from the emitting antenna          ----------------------------------------------------------------------------------------------------- List of folders inside the directories: Folders begin with the name "000" and have increasing index. Inside the same directory, each folder represents a different simulation used to build the same mutual impedance measurement. ------------------------------------------------------------------------------------------------------ List of files inside the folders: density_e.npz        :    electron density inside the box, in function of time (tempo) density_p.npz        :    ion density inside the box, in function of time (tempo) E.npz            :    electric field in the box, in function of time (tempo) qrho.npz        :    electric potential in the box, in function of time (tempo) qrho_imposed.npz    :    electric charge imposed at the emitting antennas, in function of time (tempo) tempo.npz        :    time-vector for density, electric field, electric potential and charge vectors TEST_Luca.dat        :    parameters describing the characteristics of the simulated plasma box [ Note : the previous files can be opened as follows import numpy as np vector_file_name = np.load('file_name.npz') # Use these for the .npz files characteristics_of_the_box = np.genfromtxt('TEST_Luca.dat',skip_header=1) ] ------------------------------------------------------------------------------------------------------- Characteristics of the simulated plasma box (TEST_Luca.dat) nx        :    amount of spatial grid points xl        :    physical size of the spatial box, expressed in Debye length tt_w        :    time resolution for ion and electron density, electric field, electric potential and charge rap_m          :    ion-to-electron mass ratio R_p        :    ion-to-electron temperature ratio dt        :    time step used to evolve in time the numerical simulation emission    :    emission frequency power        :    amplitude of the electric charge imposed at the emitting antennas (Note : all parameters not listed here but present inside the TEST_Luca.dat file correspond to additional     functionalities of the model. For the use of this dataset, they can be discarded.)

opencc-by-4.0Jul 2023View details →

A first high-quality vector data of buildings in East Asian countries based on a comprehensive large-scale mapping framework

We generate a high-quality and complete vector data of buildings in East Asian regions, including China, Japan, North Korea, South Korea and Mongolia, filling the gaps in the existing public buildings data.

opencc-zeroJul 2023View details →

Passive electroreception in bottlenose dolphins Tursiops truncatus: implication for micro- and large-scale orientation

For the two dolphin species Sotalia guianensis and Tursiops truncatus, it was shown that the vibrissal crypts located on the rostrum represent highly innervated, ampullary electroreceptors and that both species are correspondingly sensitive to weak electric fields. For a comparative assessment of the sensitivity of the bottlenose dolphin's electroreceptive system, we determined detection thresholds for DC and AC electric fields with two bottlenose dolphins. In a psychophysical experiment, the animals were trained to respond to electric field stimuli using the go/no-go paradigm. We show that bottlenose dolphins are able to detect DC electric fields as low as 2.4 &[mu]V cm -1 and 5.5 &[mu]V cm -1, respectively, a detection threshold in the same order of magnitude as those in the platypus and the Guiana dolphin. Detection thresholds for AC fields (1, 5, and 25 Hz) were generally higher than those for DC fields, and the sensitivity for AC fields decreased with increasing frequency. Although the electroreceptive sensitivity of dolphins is lower than that of elasmobranchs, it is suggested that it allows orientation at micro and large scales. In dolphins pursuing benthic foraging strategies, electroreception may facilitate short-range prey detection and target-oriented snapping of their prey. Furthermore, we discuss that the ability to detect weak electric fields may enable dolphins to detect the Earth's magnetic field through induction-based magnetoreception, thus allowing large-scale orientation.

openagpl-3.0-or-laterJul 2023View details →

Data from "Connecting large-scale meteorological patterns to extratropical cyclones in CMIP6 climate models using self-organizing maps"

The following files were used as data and analysis in the article "Connecting large-scale meteorological patterns to extratropical cyclones in CMIP6 climate models using self-organizing maps" (<a href="https://doi.org/10.1029/2022EF003211">https://doi.org/10.1029/2022EF003211</a>). In the study, we applied self-organizing maps (SOMs) as an automated machine-learning approach to characterize the large-scale meteorological patterns (LSMP) and associated frequency and intensity of discrete extratropical cyclone (ETC) events over the northeastern U.S. The dominant patterns of geopotential height variability are identified through SOM analysis of five reanalysis products during 1980 - 2019. ETC events are tracked using TempestExtremes and are integrated with SOMs to classify the accumulated cyclone activity associated with each pattern. We then evaluate the skill of CMIP6 historical experiments in simulating the LSMP and ETC events identified in the SOM. Please see the published paper for more details. Here we have archived:  - data pre-processing scripts - code to run the self-organizing map analysis - code to calculate the SOM and ETC statistics - composites of 500-hPa geopotential height for each dataset as organized by the SOM - ETC tracking script and tracking output for each dataset - SOM output for each dataset

opencc-zeroAug 2023View details →

Data from: Hierarchical power control of a large-scale wind farm by using a data-driven optimization method

With the participation in automatic generation control (AGC), a large-scale wind farm should distribute the real-time AGC signal to numerous wind turbines (WTs). This easily leads to an expensive computation for a high-quality dispatch scheme, especially considering the wake effect among WTs. To address this problem, a hierarchical power control (HPC) is constructed based on the geographical layout and electrical connection of all the WTs. Firstly, the real-time AGC signal of the whole wind farm is distributed to multiple decoupled groups in proportion of their regulation capacities. Secondly, the AGC signal of each group is distributed to multiple WTs via the data-driven surrogate-assisted optimization, which can dramatically reduce the computation time with a small number of time-consuming objective evaluations. Besides, a high-quality dispatch scheme can be acquired by the efficient local search based on the dynamic surrogate. The effectiveness of the proposed technique is thoroughly verified with different AGC signals under different wind speeds and directions.

opencc-zeroSep 2023View details →

The evolution of the Aristolochia pallida complex (Aristolochiaceae) contradicts traditional taxonomy and reflects large-scale glacial refugia in the Mediterranean

The taxonomy of the Mediterranean Aristolochia pallida complex has been under debate for several decades with the following species currently recognized: A. pallida, A. lutea, A. nardiana, A. microstoma, A. merxmuelleri, A. croatica and A. castellana. These taxa are distributed from Iberia to Turkey. To reconstruct phylogenetic and biogeographic patterns, we employed cpDNA sequence variation using both non-coding (intron and spacer) and protein-coding regions (i.e. trnK intron, matK gene and trnK-psbA spacer). Our results show that the morphology-based traditional taxonomy was not corroborated by our phylogenetic analyses. Aristolochia pallida, A. lutea, A. nardiana and A. microstoma were not monophyletic. Instead, strong geographic signals were detected. Two major clades, one exclusively occurring in Greece and a second one of pan-Mediterranean distribution, were found. Several subclades distributed in Greece, NW Turkey, Italy, as well as amphi-Adriatic subclades and a subgroup of southern France and Spain were revealed. The distribution areas of these groups are in close vicinity to hypothesised glacial refugia areas in the Mediterranean. According to molecular clock analyses, the diversification of this complex started around 3–3.3 my, before the onset of glaciation cycles, and the further evolution of and within major lineages falls into the Pleistocene. Based on these data, we conclude that the Aristolochia pallida alliance survived in different Mediterranean refugia rarely with low, but often with a high potential for range extension, and a high degree of morphological plasticity.

opencc-by-4.0Sep 2023View details →

SyntheWorld: A Large-Scale Synthetic Dataset for Land Cover Mapping and Building Change Detection

Paper Accept by WACV 2024 [paper, supp] [<a href="https://arxiv.org/abs/2309.01907">arXiv</a>] Overview Synthetic datasets, recognized for their cost effectiveness, play a pivotal role in advancing computer vision tasks and techniques. However, when it comes to remote sensing image processing, the creation of synthetic datasets becomes challenging due to the demand for larger-scale and more diverse 3D models. This complexity is compounded by the difficulties associated with real remote sensing datasets, including limited data acquisition and high annotation costs, which amplifies the need for high-quality synthetic alternatives. To address this, we present SyntheWorld, a synthetic dataset unparalleled in quality, diversity, and scale. It includes 40,000 images with submeter-level pixels and fine-grained land cover annotations of eight categories, and it also provides 40,000 pairs of bitemporal image pairs with building change annotations for building change detection task. We conduct experiments on multiple benchmark remote sensing datasets to verify the effectiveness of SyntheWorld and to investigate the conditions under which our synthetic data yield advantages. <pre>Description ------------ This dataset has been designed for land cover mapping and building change detection tasks. File Structure and Content: --------------------------- 1. **1024.zip**: - Contains images of size 1024x1024 with a GSD (Ground Sampling Distance) of 0.6-1m. - `images` and `ss_mask` folders: Used for the land cover mapping task. - `images` folder: Post-event images for building change detection. - `small-pre-images`: Images with a minor off-nadir angle difference compared to post-event images. - `big-pre-images`: Images with a large off-nadir angle difference compared to post-event images. - `cd_mask`: Ground truth for the building change detection task. 2. **512-1.zip**, **512-2.zip**, **512-3.zip**: - Contains images of size 512x512 with a GSD of 0.3-0.6m. - `images` and `ss_mask` folders: Used for the land cover mapping task. - `images` folder: Post-event images for building change detection. - `pre-event` folder: Images for the pre-event phase. - `cd-mask`: Ground truth for building change detection. Land Cover Mapping Class Grep Map: ---------------------------------- class_grey = { "Bareland": 1, "Rangeland": 2, "Developed Space": 3, "Road": 4, "Tree": 5, "Water": 6, "Agriculture land": 7, "Building": 8, }</pre> Reference @misc{song2023syntheworld,       title={SyntheWorld: A Large-Scale Synthetic Dataset for Land Cover Mapping and Building Change Detection},        author={Jian Song and Hongruixuan Chen and Naoto Yokoya},       year={2023},       eprint={2309.01907},       archivePrefix={arXiv},       primaryClass={cs.CV} }

Fig. 4 in Geographic variation in the relationship between large-scale environmental determinants and bat species richness

Fig. 4. Spatial variation in the partial coefficients of determination (R2) for three environmental hypotheses and their shared effects. The coefficients are: energy (E), heterogeneity (H), seasonality (S), shared contribution between energy and heterogeneity (E: H), energy and seasonality (E: S), heterogeneity and seasonality (H: S), and the contribution shared among energy, heterogeneity and seasonality (E: H: S).

Fig. 2 in Geographic variation in the relationship between large-scale environmental determinants and bat species richness

Fig. 2. Distribution of coefficients of determination (R2) of GWR for the analysis of bat species richness regressed on the predictors of the three environmental hypotheses combined.

Fig. 1 in Geographic variation in the relationship between large-scale environmental determinants and bat species richness

Fig. 1. Global pattern of bat species richness. Legend corresponds to the number of bat species per 2◦ × 2◦ grid cell. Letters represent the zoogeographic realms (Holt et al. 2013): Na = Nearctic, P = Panamanian, Nt = Neotropical, Pa = Palearctic, Sa = Saharo-Arabian, At = Afrotropical, M = Madagascan, Or = Oriental, Au = Australian, Sj = Sino-Japanese, Oc = Oceanian.

Fig. 3 in Geographic variation in the relationship between large-scale environmental determinants and bat species richness

Fig. 3. Spatial non-stationarity in the effect (R2) of the predictors of the three environmental hypotheses combined to explain the global pattern of bat species richness.