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2,863 results for “Challenge”
Data, scripts, and figures of the article: Evaluation of oregano essential oil in broilers challenged with a mixed Eimeria spp. and high dietary protein model of subclinical coccidiosis
<p>Data, scripts, and figures of the article "Evaluation of oregano essential oil in broilers challenged with a mixed Eimeria spp. and high dietary protein model of subclinical coccidiosis" to be published in the journal Animal - Open Space. </p>
Submitted forecasts and analysis code for "Predicting spring phenology in deciduous broadleaf forests: NEON Phenology Forecasting Community Challenge"
<p>Submitted forecasts for the 2021 Ecological Forecasting Initiative NEON Phenology Forecast Challenge and the analysis code for the accompanying manuscript. </p>
GENEA Challenge 2023 user-study video stimuli
<p>This Zenodo repository contains video stimuli in mp4 format from the user studies in the GENEA Challenge 2023.</p> <p> </p> <p><strong>Contents:</strong></p> <p>The file "monadic_videos.zip" contains the video stimuli used in the monadic evaluations of the challenge (human-likeness and speech appropriateness) and the file "dyadic_videos.zip" the video stimuli from the dyadic evaluation (appropriateness for the interlocutor).</p> <p>Video stimuli with mismatched motion are in the corresponding subfolders with the prefix "mismat_".</p> <p>The file "attention_check_examples.zip" contains examples of the attention-check videos used in the challenge.</p> <p> </p> <p>The release contains all videos used for the challenge evaluation, except for the attention-checks, where only a few examples are provided. Except for the attention-check examples for the human-likeness studies, all videos contain speech audio. This audio needs to be removed to replicate the human-likeness evaluation.</p> <p> </p> <p><strong>Attribution:</strong></p> <p>If you use this material, please cite our latest paper on the GENEA Challenge 2023. At the time of writing (2023-08-01) this is our ACM ICMI 2023 paper:</p> <p>Taras Kucherenko, Rajmund Nagy, Youngwoo Yoon, Jieyeon Woo, Teodor Nikolov, Mihail Tsakov, and Gustav Eje Henter. 2023. The GENEA Challenge 2023: A large-scale evaluation of gesture generation models in monadic and dyadic settings. In Proceedings of the ACM International Conference on Multimodal Interaction (ICMI ’23). ACM.</p> <p>Also, please cite the paper about the original dataset from Meta Research:</p> <p>Gilwoo Lee, Zhiwei Deng, Shugao Ma, Takaaki Shiratori, Siddhartha S. Srinivasa, and Yaser Sheikh. 2019. Talking With Hands 16.2M: A large-scale dataset of synchronized body-finger motion and audio for conversational motion analysis and synthesis. In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV ’19). IEEE, 763–772.</p> <p> </p> <p>Condition NA in the data contains motion from the Talking With Hands 16.2M dataset at <a href="https://github.com/facebookresearch/TalkingWithHands32M/">https://github.com/facebookresearch/TalkingWithHands32M/</a>. These stimuli, and the audio, are licensed under a CC BY NC 4.0 international license. The motion for all other conditions is released under a CC BY 4.0 international license, whose license text is reproduced in the file LICENSE.txt.</p> <p> </p> <p><strong>More information:</strong></p> <p>To find more GENEA Challenge 2023 material on the web, please see:</p> <ul> <li> <p><a href="https://genea-workshop.github.io/2023/challenge/">https://genea-workshop.github.io/2023/challenge/</a></p> </li> </ul> <p>If you have any questions or comments, please contact:</p> <ul> <li> <p>The GENEA Challenge organisers <genea-challenge@googlegroups.com></p> </li> </ul>
Figure 1 in Perspectives and challenges on isotopic ecology of terrestrial birds in Brazil
Figure 1. Flowchart of potential study themes (in bold) to be developed in isotopic ecology with terrestrial birds in Brazil. Each theme branches into several sub-themes that can be explored (first boxes below the themes) and the methods and approaches that can be employed to develop the studies (within the dashed boxes). Many methods and approaches are interchangeable among themes and subthemes (represented by the horizontal arrow). In addition, the shortcomings of stable isotope ecology that should be considered before or during the development of the studies.
A more accurate risk biomarkers recognition for Progressive Multifocal Leukoencephalopathy (PML) caused by Polyomavirus JC in patients with multiple sclerosis during treatment with disease-modifying therapies (DMTs): an ongoing clinical challenge.
<p>The therapeutic scenario for the treatment of MS has recently been characterized by a veritable revolution, which has included the introduction, for the first time, of drug treatment guidelines and the entry, in the therapeutic landscape of the last decade, of numerous new drugs that, in varying but significantly relevant ways, have proven capable of modifying the course of the disease (Disease-Modifying Therapies - DMTs). <br> While the arsenal of available drugs has resulted in advances in efficacy and selectivity, it has also exposed them to the danger of side effects, potentially serious and in some cases even fatal. Among the most important side effects, complications of infectious origin, characterized by cases of viral infection/reactivation, as in the case of JCPyV, the etiologic agent of PML, are the most represented. This study, based on the follow-up of MS patients treated with different DMTs, contributes to implementing the data in the literature regarding a greater understanding of the risks related to the administration of these drugs and more appropriate monitoring of MS treatment. The risk of JCPyV reactivation with Fingolimod and Dimethyl fumarate is lower than the risk of viral reactivation associated with natalizumab.<br> In light of the data obtained, it is possible to conclude that, in the case of natalizumab, testing for JC viruria would seem to be more useful in identifying those patients with a JCPyV-specific humoral response that is not yet detectable. In addition, our results, draw attention to the importance of analyzing the NCCR rearrangements of JCPyV. Indeed, the particular rearrangements found in plasma and PBMCs of patients with RRMS treated with natalizumab could represent an alert of neuroinvasiveness in order to detect early those patients with a higher risk of developing PML. In the case of dimethyl fumarate, it seems likely that monitoring of lymphopenia would identify a higher risk group of patients in whom alternative therapy should be sought. Prolonged lymphopenia, with absolute lymphocyte counts less than 750 lymphocytes/mL, might be the major risk factor for PML although, a greater risk might lie in the loss of CD8+ cells that are crucial for JCPyV control.<br> For fingolimod, this strategy cannot be applied because the number of circulating lymphocytes decreases while the actual lymphocyte function appears largely normal therefore, monitoring viruria and viremia along with identification of the neurotrophic variant of the virus seems a more exploitable means for risk stratification.</p> <p>In conclusion, the results of this study can be considered directly transferable to the National Health System in that, both the monitoring of JCPyV reactivation by viruria and the sequence analysis of viral NCCR and host immune set-up could play the role of translatable biomarkers in clinical practice in order to assess the risk of PML onset. In addition to improving risk stratification of this disease, these biomarkers of viral reactivation and pathogenicity could facilitate timely diagnosis, optimizing the use of health care resources and contributing to the reduction of direct and indirect costs of MS disease.</p> <p>Prezioso Carla was supported by the Italian Ministry of Health (Starting Grant: SG-2018-12366194).</p>
Logistic Activity Recognition Challenge (LARa Version 03) – A Motion Capture and Inertial Measurement Dataset
<p><strong>LARa</strong><strong> Version 03</strong> is a freely accessible logistics-dataset for human activity recognition. In the “Innovationlab Hybrid Services in Logistics” at TU Dortmund University, two picking and one packing scenarios with 16 subjects were recorded using an optical marker-based Motion Capturing system (OMoCap), Inertial Measurement Units (IMUs), and an RGB camera. Each subject was recorded for one hour (960 minutes in total). All the given data have been labelled and categorised into eight activity classes and 19 binary coarse-semantic descriptions, also called attributes. In total, the dataset contains 221 unique attribute representations.</p> <p>The <strong>dataset was created according to the guideline</strong> of the following paper: “A Tutorial on Dataset Creation for Sensor-based Human Activity Recognition”, PerCom, 2023 DOI: <a href="http://dx.doi.org/10.1109/PerComWorkshops56833.2023.10150401">10.1109/PerComWorkshops56833.2023.10150401</a></p> <p>The LARa Version 03 contains a <strong>new Annotation tool </strong>for OMoCap and RGB Videos, namely, the <strong>S</strong>equence <strong>A</strong>ttribute <strong>R</strong>etrieval <strong>A</strong>nnotator (<strong>SARA</strong>). SARA, developed and modified based on the LARa Version 02 annotation tool, includes desirable features and attempts to overcome limitations as found in the LARa annotation tool. Furthermore, few features were included based on the explorative study of previously developed annotation tools, see journal. In alignment with the LARa annotation tool, SARA focuses on OMoCap and video annotations. However, it is to be noted that SARA was not intended to be a video annotation tool with features such as subject tracking and multiple subject annotations. Here, the video is considered to be a supporting input to the OMoCap annotation. We would recommend other tools for pure video-based multiple-human activity annotation, including subject tracking, segmentation, and pose estimation. There are different ways of <strong>installing the annotation tool</strong>: Compiled binaries (executable files) for Windows and Mac can be directly downloaded from here. Python users can install the tool from https://pypi.org/project/annotation-tool/ (PyPi): “pip install annotation-tool”. For more information, please refer to the “Annotation Tool - Installation and User Manual”.</p> <p><strong>Upgrade:</strong></p> <ul> <li>Annotation tool (<strong>SARA</strong>) added (for Windows and MacOS, including an installation and user manual)</li> <li>Neural Networks updated (can be used with the annotation tool)</li> <li>OMoCap data: <ul> <li>Annotation errors corrected</li> <li>Annotations reformatted, fitting the SARA annotation tool</li> <li>“additional annotated data” extended</li> <li>“Markers_Exports” added</li> </ul> </li> <li>IMU data (MbientLab and MotionMiners Sensors) <ul> <li>Annotation errors corrected</li> </ul> </li> <li>README file (protocol) updated and extended</li> </ul> <p> </p> <p><strong>If you use this dataset for research, please cite the following paper: “LARa: Creating a Dataset for Human Activity Recognition in Logistics Using Semantic Attributes</strong><strong>”, Sensors 2020, DOI: <a href="https://doi.org/10.3390/s20154083">10.3390/s20154083</a>.</strong></p> <p><strong>If you use the Mbientlab Networks, please cite the following paper: “From Human Pose to On-Body Devices for Human-Activity Recognition”, 25th International Conference on Pattern Recognition (ICPR), 2021, DOI: </strong><a href="https://doi.org/10.1109/ICPR48806.2021.9412283"><strong>10.1109/ICPR48806.2021.9412283</strong></a><strong>.</strong></p> <p>For any questions about the dataset, please contact Friedrich Niemann at friedrich.niemann@tu-dortmund.de.</p>
Why The Perfectly Symmetric Cobalt-Pentapyridyl Loses the H2 Production Challenge: Theoretical Insight into Reaction Mechanism and Reduction Free Energies
<p>Abstract</p> <p>Researchers have extensively investigated photo-catalytic water reduction utilizing Cobalt-based catalysts with poly-pyridyl ligands. While catalysts exhibiting distorted poly-pyridyl ligand demonstrate higher H2 production yields, those with ideal octahedral coordination display poor performance. This outcome suggests the crucial role of ligand framework in catalytic activity, yet reasons behind the disparity in H2 production rates for catalysts with octahedral geometries remain unclear. We theoretically examined the water reduction mechanism of Co-based poly-pyridyl catalyst, CoPy5, having perfect octahedral coordination. We clarified the effect of octahedral coordination by utilizing each intermediate step of ECEC mechanism. We determined spin states, solvent response, electronic structures, and reduction free energies. CoPy5 with perfect octahedral coordination, alongside its distorted counterparts, exhibit similar spin states as the reaction progresses through each intermediate step. However, the first reduction free energy obtained for the CoPy5 is slightly higher than that of its distorted counterparts. Following the second protonation, resulting H2 molecule experiences limited diffusion from the Co center due to the compact structure of the CoPy5, which blocks the Co center for the next H2 production cycle. Catalysts having distorted octahedral geometries facilitate fast removal of H2 into the solvent. Thus, the reaction center becomes immediately available for subsequent H2 production.</p> <p>Computational Details</p> <p>AIMD simulations have been performed for modeling intermediate states of the ECEC mechanisms of H2 production through water splitting. Open source CP2K simulation package have been used in all simulations. PBE density functional in general gradient approximation (GGA) formalism was employed for the AIMD simulations. Goedecker-Teter-Hutter (GTH) potentials were applied for the estimation of core electron interactions with the valence shell and nucleus. Valence electrons were modeled explicitly and valence shells of Co, N, C, O and H contain 17, 5, 4, 6 and 1 electrons, respectively. DZVP-MOLOPT basis set was used for all atomic kinds. For auxiliary plane wave basis set, a cutoff of 400 Ry was utilized. Dispersion interactions were taken into consideration by applying Vydrov and Van Voorhis vdW density functional, in the revised form (rVV10). Periodic boundary<br> conditions and spin polarization were always applied. For the CoPy5 complex, AIMD simulations were carried out in a box defined as cubic with explicit water environment. The CoPy5 catalyst was first solvated in 215 water molecules and the simulation volume was relaxed by performing AIMD simulations for approximately 20 ps in the isothermal-isobaric ensemble (NPT). Cubic simulation box volume was determined as 6163.28 ̊A3. Following the determination of the simulation box size, each intermediate step were modeled by applying AIMD simulations in the canonical ensemble (NVT) for approximately 20 ps. Time step was set to 0.5 fs. Canonical sampling through velocity rescaling (CSVR) thermostat with a time constant of 100 fs was applied in order to keep<br> the simulation temperature at 300 K.</p> <p>Please see the corresponding article for more details.</p>
Structural and functional effects of global invasion pressure on benthic marine communities – patterns, challenges and priorities
<p>Here we present datasets underlying the results of the study examining patterns of structural and functional community-level change in a range of well-studied marine ecosystems with documented histories of bioinvasion. For the purpose of the study, the authors identified six regions with extensive bay-scale datasets on native and non-indigenous benthic species assemblages, allowing paired comparisons in time (years to decades; retrospective datasets) or space (high vs. low proximity to hotspots of NIS introductions within a region; cross-sectional datasets) representing differences in bioinvasion pressure (Table 1). These sites were: 1) coastal waters of British Columbia, Canada (BC); 2) San Francisco Bay, USA (SF); 3) Ilha Grande Bay, Brazil (BR); 4) North-Eastern Baltic Sea, Estonia (BS); 5) estuaries of New South Wales, Australia (AU) and 6) Waitematā Harbour, New Zealand (NZ). These six regions are generally at mid- to higher-latitudes, with one low-latitude site (BR). The study sites encompassed surveys of benthic communities: fouling assemblages (BC and AU), subtidal reefs (BR and BS), and soft-sediment benthos (SF, BS, and NZ).</p> <p>Three data files are provided for each study region and include:</p> <ul> <li>benthic community data (XX_species.csv)</li> <li>binary (0/1) biological trait information compiled for all species in the dataset (XX_traits.csv)</li> <li>additional explanatory variables considered for each study region - bioinvasion pressure and spatial variables (XX_env.csv)</li> </ul> <p>For detailed information on datasets and methods description please refer to the original manuscript by Zaiko et al.</p>
DroughtScope dataset for AI4EO IMAGIN-e Challenge
<p>Climate change poses new challenges to the food industry, which is required to optimise production in terms of quantity and quality of products against reduced water and land availability due to increased periods of drought and urbanisation. The availability of accurate and real-time information about ET is expected to improve decision-making concerning the optimisation of agricultural practice by properly allocating the resources needed. In this regard, the idea of using real-time ET estimates has a significant societal value, as it contributes to <strong>sustainable agriculture</strong>, <strong>food security</strong>, <strong>water conservation</strong>, and <strong>climate change adaptation</strong>. The envisioned business model includes data-driven agricultural consulting services, a subscription-based platform and partnerships with agritech companies.<br> Evapotranspiration (ET) data helps irrigation planning and is a powerful tool for managing land and water resources. Water scarcity makes knowledge of crop water consumption essential for water budgeting of connected ecosystems like agriculture, industry and cities. In a context in which severe droughts induce farmers to change crop typology to face reduced water availability, even in areas historically characterised by water abundance, offline processing of satellite data can result in delayed or sub-optimal decision-making. Timely information about the status of the cultivations can dramatically reduce water consumption, leading to cost savings, increased quality and quantity of food production and profitability. In this context, exploiting pre-trained models is an enabling factor for onboard processing, which is not feasible for direct retrieval of ET from measured brightness temperature via computationally expensive radiative transfer models.<br> This project aims to develop a decision support system helping public and private agrifood decision-makers optimise water resource management. Our solution provides <strong>early warnings</strong> about <strong>crop water stress</strong> based on the estimate of the evaporative stress index (<strong>ESI</strong>), which is one of the most important indicators of stress conditions identified in the literature.<br> <strong>Main innovations</strong></p> <ul> <li>Original deep learning architecture to infer information typically contained in the thermal domain from the near-infrared one</li> <li>Real-time onboard estimates thanks to lightweight processing</li> <li>Multi-task architecture for ESI estimation and LULC mapping</li> </ul> <p><strong>Benefits for users/stakeholders</strong></p> <ul> <li>Optimization of water resources management to tackle increasing water scarcity</li> <li>Possibility to implement local actions based on daily warning maps</li> <li>Optimization of food production</li> <li>Reduction of costs and resources employed for field monitoring</li> </ul> <p><strong>Benefits for the scientific community</strong></p> <ul> <li>Availability of new data with better resolution of the ones today available provided by the ECOSTRESS mission</li> <li>Daily LULC maps to tackle with high-dynamic phenomena (river mobility, sedimentation, deforestation)</li> </ul> <p><strong>Data</strong><br> This research exploits L1C data from the <strong>IMAGIN-e hyperspectral</strong> (HS) sensor, which features 50 spectral bands within the range [450,950] nm with a spatial resolution of 45 metres. The primary data sources are integrated with auxiliary data useful for classifying agricultural lands and estimating Evapotranspiration (ET).<br> To this end, we use the <strong>ESA WorldCover 2021</strong> dataset (<a href="https://worldcover2021.esa.int/">https://worldcover2021.esa.int/</a>) as the ground truth for Crop Classification; the original dataset at 10m spatial resolution is resampled at 45 meters with a max-voting strategy. Finally, a binary map is obtained in the code, considering only the Cropland values as 1 and 0 otherwise.<br> For ET training, we have considered <strong>ECOSTRESS</strong> data as a reference. ECOSTRESS provides ET data based on the Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) method, with a spatial resolution of approximately 70 metres, which will be rescaled to 45 metres for consistency with input HS data.<br> The patches (14) included in the dataset are a stack of all these data. So we have 54 channels in this order:</p> <ul> <li>1:50: hyperspectral bands</li> <li>51: ESA WorldCover 2021 at 45m</li> <li>52: Evaporative Stress Index (ESI)</li> <li>53: Quality Control Band</li> <li>54: Evapotranspiration</li> </ul> <p>In the data folder are also available original ESI and LULC data.</p>
Validation dataset for the ICASSP-2024 3D-CBCT challenge
<p>Validation Dataset for the ICASSP-2024 3D-CBCT challenge</p> <p>https://sites.google.com/view/icassp2024-spgc-3dcbct/home</p> <p>Please dowload all files into one folder, and then merge them together with:</p> <pre><code class="language-bash">$ zip -s 0 validate.zip --out validate_unsplit.zip </code></pre> <p>This will create a new zip file, "validate_unsplit.zip" that then you can unzip with your favourite tool, e.g.</p> <pre><code class="language-bash">$ unzip validate_unsplit.zip</code></pre> <p> </p> <p>The CBCT geometry required to be used</p> <p>image size : [300 300 300] mm<br> image shape : [256 256 256] voxels<br> voxel size : [1.171875 1.171875 1.171875] mm<br> detector shape : [256 256] pixels<br> detector size : [600, 600] mm<br> pixel size : [2.34375, 2.34375] mm<br> distance source origin (axis of rotation, center of image) : 575 mm<br> distance source to detector : 1050 mm</p> <p> </p> <p> </p> <p>Remember that to be part of the challenge you need to register in the webpage above.</p> <p> </p>
Dataset: Challenges, Strengths, and Strategies of People with ADHD in Software Engineering: A Case Study
<p>This dataset accompanies the paper "Challenges, Strengths, and Strategies of People with ADHD in Software Engineering: A Case Study". It contains interview guides as well as anonymous interview transcripts for six interviewees who explicitly consented to the publication.</p> <p>Specifically:</p> <ul> <li>Interview transcripts are Excel files starting with "<strong>interview</strong>".</li> <li>The interview instruments used for the 19 interviews are named "<strong>interview_guide_professionals</strong>" followed by a version number. V1 was used for the first 3 interviews, V2 for the 9 following interviews, and V3 for the remaining 7.</li> <li><strong>manager_feedback_guide.pdf</strong> is the interview guide used for discussions with the 4 managers. The preliminary results we showed them are depicted in <strong>01_challenges_themes_relations_noStrat_v2</strong>, <strong>02_strengths_themes_relations_v1</strong> and <strong>02_strengths_themes_relations_v2</strong></li> <li><strong>consent_form.pdf</strong> is a PDF version of the online form used to handle consent and intake of interviewees.</li> </ul>
"The sound comes from a meadow in the Sierra Nevada Mountains in California. The meadow is at an elevation of 2400 meters near a mountain named Olancha Peak, which is 3700 meters in altitude. Ihave a group of friends with which Ibackpack (trek) into the mountains. Our goal was to spend some time in the mountains and hike to the top of Olancha Peak (…) By the time we reached the meadow, we were in a forest and there was still snow on the ground in some places. We took the trip in June of 2006. The Sierra Nevada Mountains are a large mountain range. Much of the range is protected by national parks or preserved areas we call 'wilderness areas' (…) Ihave been backpacking for nearly 40 years and Iwill hopefully continue with this challenging activity for 40 years more! Many of my friends are much younger than Iam and it gives me much satisfaction to be able to have as much or more stamina for this activity than they have! When we are on these trips, we hike up peaks, catch fish, drink some whiskey around campfires and enjoy our time in the beautiful solitude. My memories of this trip were of the steep, hot hike from the desert to the cool meadow; the overall beauty of the nature, the absolute solitude of our campsite near the meadow; the strenuous hike to the top of Olancha Peak; the camaraderie of my friends; and, of course the sound of the frogs in the meadow. The frog sounds were astounding to me and Iwould listen in awe of the creature's instinctual desire to reproduce and continue the existence of their kind. Surely there were different species in the meadow for some of the frog sounds were different than others. The sounds only occurred after the Sun went down for the evening. Istood next to the creek in the meadow and recorded the sounds using my digital camera." [Peter/plentz1960]16 in Collecting Sounds. Online Sharing of Field Recordings as Cultural Practice
"The sound comes from a meadow in the Sierra Nevada Mountains in California. The meadow is at an elevation of 2400 meters near a mountain named Olancha Peak, which is 3700 meters in altitude. Ihave a group of friends with which Ibackpack (trek) into the mountains. Our goal was to spend some time in the mountains and hike to the top of Olancha Peak (…) By the time we reached the meadow, we were in a forest and there was still snow on the ground in some places. We took the trip in June of 2006. The Sierra Nevada Mountains are a large mountain range. Much of the range is protected by national parks or preserved areas we call 'wilderness areas' (…) Ihave been backpacking for nearly 40 years and Iwill hopefully continue with this challenging activity for 40 years more! Many of my friends are much younger than Iam and it gives me much satisfaction to be able to have as much or more stamina for this activity than they have! When we are on these trips, we hike up peaks, catch fish, drink some whiskey around campfires and enjoy our time in the beautiful solitude. My memories of this trip were of the steep, hot hike from the desert to the cool meadow; the overall beauty of the nature, the absolute solitude of our campsite near the meadow; the strenuous hike to the top of Olancha Peak; the camaraderie of my friends; and, of course the sound of the frogs in the meadow. The frog sounds were astounding to me and Iwould listen in awe of the creature's instinctual desire to reproduce and continue the existence of their kind. Surely there were different species in the meadow for some of the frog sounds were different than others. The sounds only occurred after the Sun went down for the evening. Istood next to the creek in the meadow and recorded the sounds using my digital camera." [Peter/plentz1960]16
Phylogenomics and Intergenomic Conflict in a Challenging Orchid Clade (Calypsoinae): Monophyly of Corallorhiza, Paraphyly of Oreorchis, and Resurrection of Kitigorchis
<p>Dataset S1: Concatenated nuclear sequence capture data (Angiosperms353) for Calypsoinae. This nexus file contains a partition block, which can be used to plit the data into individual alignments (in R, Trifusion, SequenceMatrix, etc.).</p> <p>Dataset S2: Concatenated nuclear sequence capture data (Angiosperms353) for Calypsoinae without partition block.</p> <p>Dataset S3: Concatenated mitochondrial sequence data for Calypsoinae.</p> <p>Dataset S4: Concatenated plastid gene sequence data for Calypsoinae.</p> <p> </p>
Study in Cat-Allergic Patients With Asthma to Evaluate the Efficacy of a Single Dose of REGN1908-1909 to Reduce Bronchoconstriction Upon Cat Allergen Challenge
ClinicalTrials.gov study NCT03838731. IPD Sharing: YES. Countries: 1. Publications: 1.
Deep learning models challenge the prevailing assumption that face-like effects for objects of expertise support domain-general mechanisms
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Data from: Ability of seedlings to survive heat and drought portends future demographic challenges for five southwestern US conifers
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Age, but not an immune challenge, triggers terminal investment in the Pacific field cricket
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Data from: Estimating a physiologically-based threshold to oxygen and temperature from marine monitoring data reveals challenges and opportunities for forecasting distribution shifts
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Immune challenge affects reproductive behaviour in the Guppy (Poecilia reticulata)
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Data from: Nitrogen fertilization challenges the climate benefit of cellulosic biofuels
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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.