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2,863 results for “Challenge”
Fig. 3 in The Challenges of Incorporating Realistic Simulations of Marine Protists in Biogeochemically Based Mathematical Models
Fig. 3. The six stages of selective grazing, redrawn from Montagnes et al. (2008b).
Hotter deserts and the impending challenges for the spiny-tailed lizard in India
<p>Ectotherms are particularly vulnerable to climate change, especially those living in extreme areas, such as deserts, where species are already thermally constrained. Using the vulnerable herbivorous lizard, <em>Saara hardwickii</em>, as a model system, we used a multi-pronged approach to understand the thermal ecology of a desert agamid and the potential impacts of rising temperatures. Our data included field-based measures of operative temperatures, body temperatures, and activity, as well as lab-based measures of thermal limits, preferences, and sprint speed. As expected, the temperature dependence of locomotor performance and foraging activity was different, and in the worst-case global warming scenario (SSP5-8.5), potential sprint speed may decrease by up to 14.5% and foraging activity may decrease by up to 43.5% by 2099. Burrows are essential thermal refuges, and global warming projections suggest that <em>S. hardwickii </em>may be restricted to burrows for up to 9 hours per day by 2099, which would greatly limit critical activities, like foraging and seeking mating opportunities. Overall, we show that key information on thermal ecology, including temperature-sensitive behaviours in the wild, is necessary to understand the multiple ways in which increasing temperatures may influence ectothermic vertebrates, especially for species like <em>S. hardwickii </em>which are already vulnerable to environmental change.</p>
Data for: Testing the mettle of METAL: A comparison of phylogenomic methods using a challenging but well-resolved phylogeny
<p>Sequence alignments and gene trees for: Braun et al. "Testing the mettle of METAL: A comparison of phylogenomic methods using a challenging but well-resolved phylogeny." See README file for detailed description of all files.</p>
Challenges in Developing a Real-Time Bee-Counting Radar
<p>Contained herein is the data used in preparation of the paper titled “Challenges in Developing a Real-time Bee-counting Radar.” These data were gathered as part of a PhD program provisionally titled “Machine Learning to Count and Predict Bee Behaviour and Movement” due for submission in early 2024 at Bangor University, Wales, United Kingdom.</p> <p>The purpose of this data was to evaluate the possibility of creating a radar system, with companion computing system, to classify honeybee movement the entrance of the hive in real-time. Samples from core classes were recorded both by hand and later by automatic extraction tools. These core classes included: Inward, outward, hovering, and no-bee samples.</p>
DCASE 2024 Challenge Task 7 Development Dataset : Environmental Sound Scene Synthesis
<h1><strong>Description</strong></h1> <p>This dataset comprises embeddings and captions utilized as the development dataset for <a href="https://dcase.community/challenge2024/task-sound-scene-synthesis"><strong>DCASE 2024 Challenge Task 7</strong></a>, focusing on 'Environmental Sound Scene Synthesis.' The embeddings are derived from 60 different 4-second audio files formatted as mono 32-bit 32kHz, and are contained in the 'embeddings.tar.xz' file. Captions corresponding to each audio file can be found in 'caption.csv'. This dataset does not comprise the audio files, only the embeddings. Three different types of embeddings are provided: VGGish (vggish), MS-CLAP (clap-2023), and PANNs CNN14 Wavegram-Logmel (panns-wavegram-logmel). Only PANNs CNN14 Wavegram-Logmel (panns-wavegram-logmel) embeddings are used for evaluation in the challenge. For further details, please refer to the challenge website.</p> <p><strong>Contact</strong></p> <ul> <li>Modan Tailleur, modan.tailleur@ls2n.fr</li> <li>Mathieu Lagrange, mathieu.lagrange@ls2n.fr</li> </ul>
SVDD Challenge 2024: A Singing Voice Deepfake Detection Challenge (WildSVDD Track)
<p>For more information about SVDD Challenge 2024, please refer to https://challenge.singfake.org/.<br><br>WildSVDD track dataset is an extension of <a href="https://singfake.org/">SingFake</a> dataset. </p>
Paleobiogeographic insights gained from ecological niche models: progress and continued challenges
<p>The spatial distribution of individuals within ecological assemblages, and their associated traits and behaviors, are key determinants of ecosystem structure and function. Consequently, determining the spatial distribution of species, and how distributions influence patterns of species richness across ecosystems today and in the past, helps us understand what factors act as fundamental controls on biodiversity. Here, we explore how ecological niche modeling has contributed to understanding the spatiotemporal distribution of past biodiversity, and past ecological and evolutionary processes. We first perform a semi-quantitative literature review to capture studies that applied ecological niche models (ENMs) in the past, identifying 668 studies. We coded each study according to focal taxonomic groups and whether and how the study used fossil evidence, whether it relied on evidence or methods in addition to ENMs, and spatial scale and temporal intervals. We used trends in publication patterns across categories to anchor discussion of recent technical advances in niche modeling, focusing on paleobiogeographic ENM applications. We then explored the contributions of ENMs to paleobiogeography, with a particular focus on examining patterns and associated drivers of range dynamics; phylogeography and within-lineage dynamics; macroevolutionary patterns and processes, including niche change, speciation, and extinction; drivers of community assembly; and conservation paleobiogeography. Overall, ENMs are powerful tools for elucidating paleobiogeographic patterns. ENMs are most commonly used to understand Quaternary dynamics, but an increasing number of studies use ENMs to gain important insight into both ecological and evolutionary processes in pre-Quaternary times. Deeper integration with traits and phylogenies may further extend those insights.</p>
Kuopio Tomography Challenge 2023 open electrical impedance tomographic dataset (KTC 2023)
<p><strong>Notice: v3 update 17.4.2023. Ground truth images were corrected slightly. The older ground truth images had a geometric distortion caused by cropping the photographs to the outer boundary of the imaging chamber, instead of the inner boundary on which the measurement electrodes were located. In addition, version 3 now contains both the limited EIT data used in the challenge evaluation, as well as the full EIT data with no measurements left out.</strong></p> <p><strong>It is recommended to download version v3 and replace the v2 version with it if using the data for research purposes.</strong></p> <p>This dataset is primarily designed for the Kuopio Tomography Challenge 2023 (KTC 2023), but it can be used for generic algorithm research and development in 2D Electric Impedance Tomography (EIT) image reconstruction. The purpose of KTC 2023 is to develop algorithms for electric impedance tomography image reconstruction with limited data.</p> <p>The dataset contains electric impedance tomography data collected from phantoms made up of a cylindrical water chamber with inclusions of varying shapes and sizes present. The data consists of electrical measurements collected using electrodes placed at the chamber boundary, i.e. the values of electric current injected between two electrodes at a time, and the resulting voltages between adjacent electrode pairs. The data has been stored in the MATLAB .mat format.</p> <p>The training dataset contains data measured from five training phantoms. These are designed to facilitate algorithm development and benchmarking for the challenge itself. Four of the training phantoms contained inclusions, which were either resistive or conductive in comparison to the water in the imaging chamber. The fifth training phantom was the imaging chamber filled with only water. We encourage subsampling these datasets to create limited datasets and comparing the reconstruction results to the ground truth obtainable from the full electrode data.</p> <p>The actual challenge data is arranged into seven different difficulty levels, labeled 1-7, with each level containing three different phantoms, labeled A-C. As the difficulty level increases, the number of inclusions increases and their shapes become increasingly complex. Furthermore, the measurement data is made more limited by removing measurements collected by some of the electrodes. At each difficulty level above level 1, the data collected from two of the boundary electrodes is removed.</p> <p>To illustrate a solution to the KTC2023, we have included a simple example reconstruction algorithm, and a Finite Element Method based forward solver used by the reconstruction algorithm. These are provided as both Matlab and Python codes. The reconstructions were computed using linearized difference imaging, and the resulting (EIT) images were then segmented using Otsu's method.</p> <p>The competitors do not need to follow the above procedure, and are encouraged to explore various image reconstruction and segmentation techniques.</p> <p>The full data for all the test phantoms will be released after the Kuopio Tomography Challenge 2023 has ended. This data has now been added to this dataset as EvaluationData.zip.</p> <p>All measurements were conducted at the Process Tomography Laboratory at the University of Eastern Finland.</p> <p> </p> <p> </p>
Dataset for paper: The Promise and Challenges of Using LLMs to Accelerate the Screening Process of Systematic Reviews
Open the record for dataset details and reuse information.
The IBIS Challenge 2024 Benchmarking Package
<p><strong>IBIS Challenge 2024</strong></p> <p><em><strong>Benchmarking Package, 17 Nov 2024</strong></em></p> <p><a href="https://ibis.autosome.org">https://ibis.autosome.org</a></p> <p>This repository provides the IBIS benchmarking suite and the challenge 'answers', i.e. the labeled test data. This repository is accompanied by another ZENODO repo [<a href="https://doi.org/10.5281/zenodo.14174161">doi:10.5281/zenodo.14174161</a>] containing the complete data of the Codebook/GRECO-BIT open challenge in Inferring Binding Specificities of human transcription factors from multiple experimental data types. Both the Leaderboard stage and the Final stage data are included.</p> <p><em>* Please refer to the supplied README for more details.</em></p>
Challenges in adjusting scoring matrices when comparing functional motifs with non-standard compositions
<p>This research was funded by the National Science Centre in Poland (grant number 2021/41/N/ST6/01919)</p>
Challenges and limitations of applying the flux variance similarity (FVS) method to partition evapotranspiration in a montane cloud forest
<p>Dataset</p> <table> <tbody> <tr> <td>Name</td> <td>Description</td> </tr> <tr> <td>FVS_ori.zip</td> <td>the output from FVS method</td> </tr> <tr> <td>ModFVS.zip</td> <td>the output from ModFVS method</td> </tr> <tr> <td>CLM.zip</td> <td>the output from CLM </td> </tr> <tr> <td>Chilan_30min_sap_velocity_20200601_20211120_QC.csv</td> <td>the sap flow data in Chi-Lan</td> </tr> <tr> <td>*_clim.csv</td> <td>the observation data in Chi-Lan and Lien-Hua-Chih</td> </tr> </tbody> </table> <p> </p> <p>Codes for Analysis</p> <table> <tbody> <tr> <td>Name</td> <td>Description</td> </tr> <tr> <td>*.ipynb</td> <td>the python code used for analyzing output</td> </tr> <tr> <td>*_FVS_process.py</td> <td>the python code used for process ModFVS method</td> </tr> </tbody> </table> <p> </p> <p>ModFVS method (fluxpart-0.2.10+rhtest-py3-none-any.whl)</p> <ul> <li>use "pip install fluxpart-0.2.10+rhtest-py3-none-any.whl" to install the package</li> <li> <p>To specify a maximum allowable relative humidity when calculating WUE, set a value for "max_rh" in "wue_options". For example, to set the max RH to 95%, you would change your example code to this:</p> <p>wue_options = {"meas_ht": 23.7,"canopy_ht":10, "ppath": "C3","ci_mod":ci_mod, "max_rh":95}</p> </li> <li> <p>Note that this code is a fork of (https://github.com/usda-ars-ussl/fluxpart)</p> </li> </ul> <p> </p> <p> </p>
Dataset for the study "Foundation Models as Assistive Tools in Hydrometeorology: Opportunities, Challenges, and Perspectives"
<p>This dataset contains the materials, files, and codes used in the study "Foundation Models as Assistive Tools in Hydrometeorology: Opportunities, Challenges, and Perspectives". </p>
Spike-MD Data for "CryoBench: Diverse and challenging datasets for the heterogeneity problem in cryo-EM"
<p>A synthetic cryo-EM dataset with heterogeneity from a molecular dynamics simulation and ground truth atomic models, poses, labels, mask, and consensus volume:</p> <ul> <li>Spike-MD: 100k particle images (256x256, 1.5A/pix) of SARS-CoV-2 spike protein with conformations sampled from a molecular dynamics simulation from Wieczór et al. (2023)</li> <li>sampled_pdbs.xtc: atomic models stitched into a trajectory</li> <li>seed_structure.pdb: initial seed structure for .xtc trajectory</li> </ul>
Feather corticosterone reveals developmental challenges in a long‐term study of juvenile northern spotted owls
<p>1. Corticosterone is a steroid hormone integral to a variety of physiological pathways and is strongly associated with the vertebrate stress–response. In avian species, circulating corticosterone is sequestered into developing feathers and is used as an indicator of energy allocation during feather growth and widely applied in conservation physiology.</p> <p>2. The northern spotted owl (<i>Strix occidentalis caurina</i>) is a federally threatened old–growth forest obligate of conservation concern endemic to the Pacific Northwest of the United States and Canada. The effects of landscape characteristics and individual variation on early development in spotted owls remain unstudied despite long recognition of this knowledge gap and its potential importance to species conservation.</p> <p>3. We quantified corticosterone concentrations in 4,720 feathers from 1,056 juvenile spotted owls across seven study areas between 2001 and 2017. We used an information–theoretic approach to examine the environmental and individual factors related to feather corticosterone in juvenile spotted owls as an indicator of challenges during early development.</p> <p>4. Feather corticosterone was positively related to temperature and precipitation, and negatively related to juvenile mass at banding. We found strong support for an interaction between mass and precipitation, with greater amounts of precipitation being associated with higher levels of feather corticosterone in lighter juveniles. The temperature and precipitation metric with the strongest relationship with feather corticosterone occurred during the fledging period, suggesting that this period presents an energetic challenge for juvenile spotted owls. Greater juvenile mass decreased the effect of precipitation, suggesting that greater mass was important for juveniles to maintain homeostasis during fledgling.</p> <p>5. Feather corticosterone in juvenile spotted owls provided insights to the challenges faced during early development, adding to our understanding of spotted owl life history and potential for population recovery.</p>
Testing hormonal responses to real and simulated social challenges in a competitive female bird
<p>Competitive interactions often occur in series; therefore animals may respond to social challenges in ways that prepare them for success in future conflict. Changes in the production of the steroid hormone testosterone (T) are thought to mediate phenotypic responses to competition, but research over the past few decades has yielded mixed results, leading to several potential explanations as to why T does not always elevate following a social challenge. Here, we measured T levels in tree swallows (<i>Tachycineta bicolor</i>), a system in which females compete for limited nesting cavities and female aggression is at least partially mediated by T. We experimentally induced social challenges in two ways: (1) using decoys to simulate territorial intrusions and (2) removing subsets of nesting cavities to increase competition among displaced and territory-holding females. Critically, these experiments occurred pre-laying, when females are physiologically capable of rapidly increasing circulating T levels. However, despite marked aggression in both experiments, T did <i>not</i> elevate following real or simulated social challenges, and in some cases, socially-challenged females had lower T levels than controls. Likewise, the degree of aggression was negatively correlated with T levels following a simulated territorial intrusion. Though not in line with the idea that social challenges prompt T elevation in preparation for future challenges, these patterns nevertheless connect T to territorial aggression in females. Coupled with past work showing that T promotes aggression, these results suggest that T may act rapidly to allow animals to adaptively respond to the urgent demands of a competitive event.</p>
Liver and Blood Expression Prediction Generated for Opportunities and challenges for transcriptome-wide association studies
<p>db files are in sqlite format and contain weights to calculate genetic predictors of gene expression</p> <p>Blood, Liver indicate the tissue where the RNA was extracted from</p> <p>Crohns and LDL indicate that prediction models were generated using SNPs available in the GWAS summary results used in the paper (Wainberg et al <a href="https://doi.org/10.1038/s41588-019-0385-z">https://doi.org/10.1038/s41588-019-0385-z</a>)</p> <p>*txt.gz filex contain covariances between SNPs needed to run the summary version of PrediXcan or other TWAS methods</p> <p>Information about the RNAseq data can be found here https://pubmed.ncbi.nlm.nih.gov/27540175/</p> <p>Sample size n=522</p>
Data from: Nutritional challenges of feeding a mutualist: testing for a nutrient-toxin tradeoff in fungus-farming leafcutter ants
<p>The biochemical heterogeneity of food items often yields tradeoffs as each bite of food tends to contain some nutrients in surplus and others in deficit, as well as other less palatable or even toxic compounds. These multidimensional nutritional challenges are likely compounded when foraged foods are used to provision others (<i>e.g</i>. offspring or symbionts) with different physiological needs and tolerances. We explored these challenges in free-ranging colonies of leafcutter ants that navigate a diverse tropical forest to collect plant fragments they use to provision a co-evolved fungal cultivar. We tested the prediction that leafcutter farmers face provisioning tradeoffs between the nutritional quality and concentration of toxic tannins in foraged plant fragments. Chemical analyses of plant fragments sampled from the mandibles of Panamanian <i>Atta colombica </i>leafcutter ants provided little support for a nutrient-tannin foraging tradeoff. First, colonies foraged for plant fragments ranging widely in tannin concentration. Second, high tannin levels did not appear to restrict colonies from selecting plant fragments with blends of protein and carbohydrates that maximized cultivar performance when measured with <i>in vitro </i>experiments. We also tested whether tannins expand the realized nutritional niche selected by leafcutter ants into high-protein dimensions since: 1) tannins can bind proteins and reduce their accessibility during digestion, and 2) <i>in vitro</i> experiments have shown that excess protein provisioning reduces cultivar performance. Contrary to this hypothesis, the most protein-rich plant fragments did not have highest tannin levels. More generally, the approach developed here can be used to test how multidimensional interactions between nutrients and toxins shape the costs and benefits of providing care to offspring or symbionts.</p>
SC20 Reproducibility Challenge Artifacts
<p>As a part of the reproducibility initiative at the SC20 conference, students participating in the Student Cluster Competition where given the reproducibility challenge, which is a directed reproducibility exercise that reproduces a paper from the previous year’s conference. At SC20, the paper, <em>MemXCT: memory-centric X-ray CT reconstruction with massive parallelization (</em><a href="https://doi.org/10.1145/3295500.3356220">https://doi.org/10.1145/3295500.3356220)</a>, from SC19 was used. In the directed exercise, students were asked to reproduce performance characteristics of the research on a variety of architectures. This file contains the experimental setup and outputs of their work from the reproducibility challenge. It also includes the direction that students were given to the students for the exercise.</p> <p>The students then published their reports as polished critiques of the reproducibility of the original paper along with a new revision of the original paper, titled <em>MemXCT: Design, Optimization, Scaling, and Reproducibility of X-Ray Tomography</em> <em>Imaging</em> (<a href="https://doi.org/10.1109/TPDS.2021.3128032">https://doi.org/10.1109/TPDS.2021.3128032</a>), in a Special Section of the IEEE Transactions on Parallel and Distributed Systems (TPDS). The paper along with the revised papers are available at <a href="https://ieeexplore.ieee.org/xpl/tocresult.jsp?isnumber=9696253&punumber=71"> https://ieeexplore.ieee.org/xpl/tocresult.jsp?isnumber=9696253&punumber=71</a>.</p>
Artifact of "Learning and Programming Challenges of Rust: A Mixed-Methods Study"
<p>This is the artifact of paper "Learning and Programming Challenges of Rust: A Mixed-Methods Study" accepted by ICSE 2022.</p> <p>Please refer to the README for more details. The arifact is also available on <a href="https://github.com/system-pclub/rust-pc">GitHub</a>.</p> <p>When evaluating the artifact with the provided VM, we recommend using Ubuntu as the OS for the host machine to avoid compatibility issues.</p> <p> </p> <p> </p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.