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FIGURE 1 in Fish functional responses to local habitat variation in streams within multiple land uses areas in the Amazon
FIGURE 1 | Location of sampling streams (Middle Capim River basin, Pará State, Brazil). The characteristics of each land use class are described in the Material and Methods section.
FIGURE 4 in Fish responses to multiple scales in coastal blackwater Atlantic Forest streams in Southeast Brazil
FIGURE 4 | Redundancy analysis (RDA) explaining the relationship between selected local, landscape, and spatial variables and fish species. Vector lines indicate the relationship of significant environmental variables to the ordination axis. TDS – Total Dissolved Solids; AR – Areas under Regeneration; PCNM1 – Spatial Component represented by the Principal Coordinates of Neighbor Matrices. Species are indicated by black dots. Acronyms according to Tab. 3
FIGURE 3 in Fish responses to multiple scales in coastal blackwater Atlantic Forest streams in Southeast Brazil
FIGURE 3 | Venn diagram showing the variance partition of local, regional and spatial variables in explaining the composition of fish communities. a = fraction of exclusive explanation of local variables; b = fraction of exclusive explanation of landscape variables; c = fraction of exclusive explanation of spatial variables; d = fraction of shared explanation between local and landscape variables; e = fraction of shared explanation between landscape and spatial variables; f = fraction of shared explanation between local and spatial variables; g = fraction of shared explanation among local, landscape and spatial variables.
FIGURE 1 in Fish responses to multiple scales in coastal blackwater Atlantic Forest streams in Southeast Brazil
FIGURE 1 | Location of the study area in the coastal region of the state of São Paulo, indicating the Baixada Santista and Northern Coast basins and the distribution of the sampling sites in the Itapanhaú (JP1, JP2, VA), Itaguaré (MP, PM, GU), Guaratuba (P1–P6), and Una (BB1, BB2) sub-basins (Adapted from Esteves et al., 2019). In detail, sites of the Guaratuba sub-basin and main landscape types.
FIGURE 2 in Fish responses to multiple scales in coastal blackwater Atlantic Forest streams in Southeast Brazil
FIGURE 2 | Nonmetric Multidimensional Scaling (NMDS) plot of Axis 1 and Axis 2 of the total fish density of 14 blackwater streams. Stream codes according to Tab. 1.
FIGURE 1 in Body size responses to land use in stream fish: the importance of different metrics and functional groups
FIGURE 1 | Description of the four body size metrics used to investigate body size patterns in overall stream fish communities and in distinct functional groups. A. Skewness describes the tendency of value distribution being biased towards the right (negative-skewed) or left (positive-skewed). B. Kurtosis describes if the distribution of values is more flatted (platykurtic) or biased towards the center (narrow). Mean values can be the same for distinct kurtosis. Coefficient of variation (CV) describes the variation in values standardized to the mean.
Data from: Phytophthora zoospores display klinokinetic behaviour in response to a chemoattractant
<p>Data belonging to the manuscript Phytophthora zoospores display klinokinetic behaviour in response to a chemoattractant</p>
FIGURE 3 in Body size responses to land use in stream fish: the importance of different metrics and functional groups
FIGURE 3 | Clusters of fish species based on ecomorphological and trophic traits, resulting in 11 functional groups (FG). Full species names by FG are available in S2.
FIGURE 2 in Body size responses to land use in stream fish: the importance of different metrics and functional groups
FIGURE 2 | Location of the 40 stream sites where fish communities were sampled in South Brazilian grassland biome (Pampa).
Pulse Voltage Response Generation: TBSI-Lijing Battery Dataset
<p>In the retired batteries sustainable utilization scenario, preprocessing steps such as capacity grading and consistency matching is essential to determine how a battery should be reused or recycled. The conventional approach of measuring battery state of health (SOH), charge-discharge profiles, and other related properties through long-time charge-discharge cycle is both time-consuming and energy-intensive. Therefore, developing rapid, non-invasive, and sustainable preprocessing methods for randomly retired batteries is crucial. However, actual measured data in this field are very limited, both in terms of the quantity of retired batteries and the diversity of battery chemistries and materials. To address this gap, we open-source this Pulse Voltage Response Generation: TBSI-Lijing Battery Dataset to foster further academic research and industrial applications in the field of battery SOH fast estimation and consistency fast assessment. Xiamen Lijing New Energy Technology Co., Ltd., collected this dataset. The collaboration team at Tsinghua Berkeley Shenzhen Institute (TBSI) processed this dataset and utilized generative models for data augmentation, significantly enhancing the economic feasibility of large-scale battery repurposing.</p>
Maximized response by structural optimization of soft elastic composite systems
<p>This dataset contains the underlying data and numerical optimization codes for the paper</p> <p><em>L. Fischer and Andreas M. Menzel</em><br>Maximized response by structural optimization of soft elastic composite systems<br>PNAS Nexus <strong>3</strong>, <span>pgae353 </span>(2024) (DOI: <a href="https://doi.org/10.1093/pnasnexus/pgae353" target="_blank" rel="noopener">10.1093/pnasnexus/pgae353</a>).</p> <p>For more information, please see the included "Readme.txt" in the dataset "Zenodo.zip".</p>
Supplemental data for: Evaluation of SARS-CoV-2 response at the University of North Carolina (UNC) at Charlotte using percent positivity data and viral genomic sequence data.
<p>Supplemental data for:</p> <p>Evaluation of SARS-CoV-2 response at the<br>University of North Carolina (UNC) at Charlotte<br>using percent positivity data and viral genomic<br>sequence data.</p> <p>Submitted to Biocarla 2024</p> <p>https://carla2024.org/portfolios/biocarla/</p> <p>Authors:</p> <p>Daniel Janies 1,2,3 [0000−0002−7890−9906], Shirish Yasa 1,2,3 [0000−0003−3217−4921],<br>Colby T. Ford 1,3,4 [0000−0002−7859−3622] Jannatul Ferdous 2,3 [0000−0003−3053−9616],<br>William Taylor 2,3 [0009−0000−6204−1172], April Harris 2,3 [0009−0009−2557−7926],<br>Sam Kunkleman 2,3 [0000−0002−2309−6418], Juan Bolanos 2,3, Kevin Lambirth 2,3 [0000-0002-6568-543X], Denis<br>Jacob Machado 1,2,3 [0000−0001−9858−4515], Cynthia Gibas 1,2,3 [0000−0002−1288−9543],<br>and Jessica Schlueter 1,2,3 [0000−0002−6490−0580]</p> <p>Affiliations:</p> <p>1) Center for Computational Intelligence to Predict Health and Environmental Risks<br>(CIPHER), University of North Carolina at Charlotte 28223, USA<br>Correspondence to: djanies@charlotte.edu<br>https://cipher.charlotte.edu<br>2) Department of Bioinformatics and Genomics, University of North Carolina at<br>Charlotte 28223, USA https://cci.charlotte.edu/departments/<br>department-of-bioinformatics-and-genomics/<br>3) College of Computing and Informatics, University of North Carolina at Charlotte<br>28223, USA https://cci.charlotte.edu<br>4) School of Data Science, University of North Carolina at Charlotte 28223, USA<br>https://sds.charlotte.edu<br>5) Division of Research, University of North Carolina at Charlotte 28223, USA<br>https://research.charlotte.edu/</p> <p> </p>
Behavioral response of Aromia bungii adults to volatile compounds emitted by Prunus persica at different physiological status
Open the record for dataset details and reuse information.
Model output from "Potential impacts of marine fuel regulations on an Arctic stratocumulus case and its radiative response"
<p>Model output from "Potential impacts of marine fuel regulations on an Arctic stratocumulus case and its radiative response", in review at Atmospheric Chemistry and Physics, 2024, same authors.<br>The simulations were done using MIMICA version 4 (Savre at el., 2014) and the data includes all model output presented in the publication.</p>
Fig. 20 in Brachiopods and their response to the Early-Middle Frasnian biogeochemical perturbations on the South Polish carbonate shelf
Fig. 20. Spiriferid and spiriferinid brachiopods from the Frasnian of Wietrznia and Dębnik. A. Emanuella sp., ZPAL Bp 60/20, damaged shell from the middle Wietrznia Beds of Wietrznia Ie in dorsal (A1), ventral (A2), lateral (A3), posterior (A4), and anterior (A5) views. B. Eleutherokomma zarecznyi (Gürich, 1903), ZPAL Bp 60/9, incomplete shell from the Nodular Limestone (Pa. hassi Zone) of Dębnik in dorsal (B1), ventral (B2), lateral (B3), posterior (B4), and anterior (B5) views. C, D. Tenticospirifer? sp. from the middle Wietrznia Beds of Wietrznia Ie. C. Damaged ventral valve ZPAL Bp 60/24 in ventral (C1) and posterior (C2) views. D. Exterior of incomplete dorsal valve ZPAL Bp 60/25. E. Squamulariina? sp., GIUS 4−273 Wt/IM−6, ventral valve from the middle Wietrznia Beds of Wietrznia Id−W in posterior (E1) and ventral (E2) views. F, G. Cyrtospirifer bisellatus (Gürich, 1903) from the Nodular Limestone (Palmatolepis hassi Zone) of Dębnik. F. Shell ZPAL Bp 60/14 in dorsal (F1), ventral (F2), lateral (F3), posterior (F4), and anterior (F5) views. G. Exterior of large ventral valve ZPAL Bp 60/22.
Fig. 17 in Brachiopods and their response to the Early-Middle Frasnian biogeochemical perturbations on the South Polish carbonate shelf
Fig. 17. Serial sections of the shell of Atryparia (Costatrypa) sp., GIUS 4−273 Wt/EB−5, middle Wietrznia Beds of Wietrznia Id−W. Numbers refer to distance in mm from ventral umbo.
Fig. 18 in Brachiopods and their response to the Early-Middle Frasnian biogeochemical perturbations on the South Polish carbonate shelf
Fig. 18. Athyridid and atrypid brachiopods from the Frasnian of Wietrznia and Dębnik. A. Biernatella lentiformis Baliński, 1995, ZPAL Bp 60/5, complete shell from the middle Wietrznia Beds of Wietrznia Ie in dorsal (A1), ventral (A2), lateral (A3), posterior (A4), and anterior (A5) views. B. Atryparia (Costatrypa) sp., GIUS 4−273 Wt/IM−5, from the middle Wietrznia Beds of Wietrznia Id−W in dorsal (B1), ventral (B2), and lateral (B3) views. C, D. Spinatrypina (Exatrypa) cf. explanata (Schlotheim, 1820) GIUS 4−273 Wt/IM−10 (C) and GIUS 4−273 Wt/IM−13 (D) from the middle Wietrznia Beds of Wietrznia Id−W, in dorsal (C1, D1), ventral (C2, D2), and lateral (C3, D3) views. E, F. Spinatrypa semilukiana Ljaschenko, 1959 from the Nodular Limestone (Palmatolepis hassi Zone) of Dębnik. E. Shell ZPAL Bp 60/20 in dorsal (E1) and ventral (E2) views. F. Complete shell ZPAL Bp 60/8 in dorsal (F1), ventral (F2), lateral (F3), posterior (F4), and anterior (F5) views.
Fig. 19 in Brachiopods and their response to the Early-Middle Frasnian biogeochemical perturbations on the South Polish carbonate shelf
Fig. 19. Spiriferid brachiopods from the Frasnian of Wietrznia and Dębnik. A, B. Thomasaria ventosa sp. nov., ZPAL Bp 60/10 (A) and GIUS 4−273 Wt/IM−3 (B), two complete shells (A—holotype) from the middle Wietrznia Beds of Wietrznia Ie (A) and Id−W (B) in dorsal (A1, B1), ventral (A2, B2), lateral (A3, B3), posterior (A4, B4), and anterior (A5, B5) views. C. Thomasaria sp., ZPAL Bp 60/16, incomplete shell from the Nodular Limestone (Palmatolepis hassi Zone) of Dębnik in dorsal (C1), ventral (C2), lateral (C3), posterior (C4), and anterior (C5) views. D. Warrenella (Warrenella) euryglossa (Schnur, 1951), ZPAL Bp 60/6, slightly damaged shell from the middle Wietrznia Beds of Wietrznia Ie in dorsal (D1), ventral (D2), lateral (D3), posterior (D4), and anterior (D5) views.
Fig. 16 in Brachiopods and their response to the Early-Middle Frasnian biogeochemical perturbations on the South Polish carbonate shelf
Fig. 16. Rhynchonellid brachiopod Coeloterorhynchus aff. kayserii (Rigaux, 1908) from the middle Wietrznia Beds of Wietrznia Id−W. A, B. Two shells GIUS 4−273 Wt/EB−4 (A) and GIUS 4−273 Wt/EB−3 (B) in dorsal (A1, B1), ventral (A2, B2), lateral (A3, B3), posterior (A4, B4), and anterior (A5, B5) views.
Fig. 14 in Brachiopods and their response to the Early-Middle Frasnian biogeochemical perturbations on the South Polish carbonate shelf
Fig. 14. Rhynchonellid brachiopods from the middle Wietrznia Beds of Wietrznia Ie (A) and Id−W (B–F). A–C. Coeloterorhynchus schucherti (Stainbrook, 1945), ZPAL Bp 60/7 (A), GIUS 4−273 Wt/IM−12 (B), and GIUS 4−273 Wt/IM−13 (C), three complete shells in dorsal (A1, B1, C1), ventral (A2, B2, C2), lateral (A3, B3, C3), posterior (A4, B4, C4), and anterior (A5, B5, C5) views. D–F. Coeloterorhynchus dillanus (Schmidt, 1941), GIUS 4−273 Wt/EB−1 (D), GIUS 4−273 Wt/EB−2 (E), and GIUS 4−273 Wt/EB−6 (F), three complete shells in dorsal (D1, E1, F1), ventral (D2, E2, F2), lateral (D3, E3, F3), posterior (D4, E4, F4), and anterior (D5, E5, F5) views.
ScienceDex guides
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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.