Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
589
datasets available to search
ShareScore release 0.9.0
Dataset results
589 results for “natural materials”
Correspondence of the natural oscillation frequencies of perforated plates depending on the type of holes, plate material and thickness, type of fixing (CCCS or CSCS)
<p>The method involved the analysis of oscillations of base plates: solid non-perforated and with round holes, as well as perforated plates with holes of complex geometry in the form of a five-petal epicycloid.</p> <p>As a result of the modeling (Abaqus), the natural oscillations frequencies of the studied plates were obtained depending on the type of perforation, material, thickness and type of their fixing. The use of different materials (steel and aluminium) showed an insignificant influence on the natural oscillation frequency of the plates. It was found that the plate thickness has the greatest influence (31.85– 33.35%), the following are the hole parameters: partition width between holes; pitch between hole centers.</p> <p>Analysis of the results showed that the natural vibrations of plates with holes of complex geometry differ by up to 7% compared to plates with basic round holes. </p>
Supplementary material for "High semi-natural vegetation cover and heterogeneity of field sizes promote bird beta-diversity at larger scales in Ethiopian Highlands"
<p><strong>Abstract</strong></p> <ol> <li>The intensification of farming practices exerts detrimental effects on biodiversity. Most research has focused on declines in species richness at local scales (alpha-diversity) although species loss is exacerbated by biotic homogenization that operates at larger scales (i.e., affecting beta-diversity). The majority of studies have been conducted in temperate, industrialized countries while tropical areas remain poorly studied. Agricultural landscapes of sub-Saharan Africa are still largely dominated by small-scale subsistence farming, but strenuous efforts to intensify farming practices are currently spreading to meet a growing food demand. It is therefore crucial to understand how these intensified practices affect biodiversity to mitigate their negative impacts. </li> <li>We investigated how farming system (small- vs large-scale farming) and landscape complexity (semi-natural vegetation cover) drive bird species composition, community turnover, and beta-diversity patterns in Ethiopian Highlands’ agroecosystems. We evaluated the following hypotheses: (1) large-scale farming homogenizes bird communities, (2) community turnover is higher in small-scale farms, (3) interactive effects between landscape complexity and farming systems shape avian communities, (4) heterogeneity of field sizes increases community turnover at larger scales. </li> <li>Bird communities underwent greater compositional changes along the landscape complexity than along the agricultural intensity gradient. Contrary to our expectations, beta-diversity was not significantly lower within large-scale farms (no biotic homogenization), and complex landscapes that still offer a high amount of semi-natural vegetation promoted community turnover in both farming systems. </li> <li>Semi-natural vegetation cover mediated how avian communities responded to agricultural intensification: the compositional differences between small- and large-scale farms increased with vegetation cover, further promoting avian community heterogeneity at the landscape level.</li> <li>The heterogeneity in field sizes also enhanced bird community turnover, suggesting that a combination of both small- and large-scale farming systems within a given landscape unit would promote beta-diversity at larger scales, provided large-scale farms do not become dominant.</li> <li>Synthesis and applications: Landscape complexity shaped avian communities to a stronger degree than farming intensity, emphasizing the importance of semi-natural vegetation and landscape heterogeneity for the maintenance of diverse bird communities and for achieving multifunctional landscapes promoting biodiversity and associated ecosystem services on the High Ethiopian plateaus. <br> </li> </ol>
Supplementary material 3 from: Bongard C, Butler K, Fulthorpe R (2013) Investigation of fungal root colonizers of the invasive plant Vincetoxicum rossicum and co-occurring local native plants in a field and woodland area in Southern Ontario. Nature Conservation 4: 55-76. https://doi.org/10.3897/natureconservation.4.3578
Supplementary material 3 from: Bongard C, Butler K, Fulthorpe R (2013) Investigation of fungal root colonizers of the invasive plant Vincetoxicum rossicum and co-occurring local native plants in a field and woodland area in Southern Ontario. Nature Conservation 4: 55-76. https://doi.org/10.3897/natureconservation.4.3578
Supplementary material for "Increased sensitivity of marine invertebrates to metal toxicity in the past two decades linked to Climate Change and Ocean Acidification: revelations from a natural population of sea urchins in the Mediterranean Sea." by "Davide Sartori, Guido Scatena, Cristina Vrinceanu, Andrea Gaion".
<p>Satellite observations of environmental factors and effect concentration 50 for copper to sea urchin, from 2003 to 2022.</p>
On the nature of mixed-type features in materials datasets
<p>We provide four crystalline materials datasets that contain both numerical and categorical features of materials.</p> <ol> <li>The Lattice dataset [1,2] contains 1,439 binary AB body-centered cubic crystals, as described by 12 numerical and 9 categorical variables. The lattice constant is considered as the physical property of interest.</li> <li>The TC dataset [2,3] contains 101 binary alloys of transition and rare earth metals, as described by 15 numerical and 17 categorical features. The Curie temperature (TC) is considered as the property of interest.</li> <li>The Octet binary materials dataset [4] contains 82 materials, as described by 11 numerical and 2 categorical features. The difference in LDA energy between RS and ZB (∆E = E(RS) − E(ZB)) in eV is considered as the physical property of interest.</li> <li>The Fm3m dataset [5] contains 239 binary compounds collected from the Materials Project, as described by 12 numerical and 17 categorical variables. The formation of energy is considered as the physical property of interest.</li> </ol> <p>References:</p> <p>[1] K. Takahashi, L. Takahashi, J. D. Baran, and Y. Tanaka, "Descriptors for predicting the lattice constant of body centered cubic crystal", The Journal of chemical physics 146, 204104 (2017).<br> [2] D.-N. Nguyen, T.-L. Pham, V.-C. Nguyen, T.-D. Ho, T. Tran, K. Takahashi, and H.-C. Dam, "Committee machine that votes for similarity between materials", IUCrJ 5, 830-840 (2018).<br> [3] Y. Xu, M. Yamazaki, and P. Villars, "Inorganic materials database for exploring the nature of material", Japanese Journal of Applied Physics 50, 11RH02 (2011).<br> [4] L. M. Ghiringhelli, J. Vybiral, S. V. Levchenko, C. Draxl, and M. Scheer, "Big data of materials science: critical role of the descriptor", Physical review letters 114, 105503 (2015).<br> [5] A. Jain, S. P. Ong, G. Hautier, W. Chen, W. D. Richards, S. Dacek, S. Cholia, D. Gunter, D. Skinner, G. Ceder, et al., "Commentary: The materials project: A materials genome approach to accelerating materials innovation", Apl Materials 1, 011002 (2013).</p>
I-Seed_DS1 – CHARACTERIZATION OF BIOMECHANICS AND MATERIALS OF NATURAL SEEDS MODEL
<p>Dataset I-Seed_DS1 focus on bioengineering investigations of plant seed models, to define useful specifications for the design of the artificial systems in terms of multi-functional materials and morphological computation.</p> <p>Task 3.1. Erodium cicutarium seeds: from natural features to robotic specifics.</p> <p>Task 3.2. Samara seeds: from natural features to robotic specifics</p>
Fig. 5. Baetis flaveola F.-J. Pictet, 1843 in Mayfly types and additional material (Insecta: Ephemeroptera) examined by F.-J. Pictet and A.-E. Pictet, housed in the Museums of Natural History of Geneva and Vienna
Fig. 5. Baetis flaveola F.-J. Pictet, 1843 nom. dub. (A) Syntype [?]. (B) Labels of syntype [?] 1. Scale bar: 5 mm. (C) Syntype [?] 2. Scale bar: 5 mm. (D) Labels of syntype [?] 2. Scale bar: 5 mm.
Fig. 1 in Mayfly types and additional material (Insecta: Ephemeroptera) examined by F.-J. Pictet and A.-E. Pictet, housed in the Museums of Natural History of Geneva and Vienna
Fig. 1. François-Jules Pictet de la Rive (1809-1872) in his library. Oil painting, without date or signature; attributed to a Mr Kaiser (according to an inscription on the back of the painting). Courtesy of the Fondation des Archives de la Famille Pictet, Geneva.
Data and code for article "Nature reserve customized method of photo and video camera traps materials processing using two-stage neural network approach"
<p><strong>DESCRIPTION</strong> 📓</p> <p>"data" folder directory contains the datasets for classification and detection. </p> <ol> <li>The detection dataset has <strong>YOLOv5 format</strong> and contains three classes <strong>[tigers, leopards, empty]</strong>. The class empty is about <strong>10%</strong> of the total data. The leopard and tiger classes contain <strong>3500</strong> images each. The entire amount of data for the detection task is <strong>7600</strong> images.</li> <li>The classification dataset contains two classes <strong>[tigers, leopards]</strong>. Images for classification are cropped images from the detection task using bounding boxes. Each class has <strong>3500</strong> images</li> </ol> <p> </p> <p>The "weights" folder contains pretrained models for classification and detection tasks. </p> <ul> <li>The detector weights were pre-trained on <strong>231k</strong> images from camera traps located throughout Russia.</li> <li>The classifier weights were pre-trained on <strong>416k</strong> images that were cropped with <strong>bounding boxes</strong> from photographs for the detection task. Some of the images for the classification task were taken from the <strong>Internet</strong>. The classifiers were trained for <strong>29 classes</strong>.</li> <li>You can also find folder <strong>tigers_vs_leopards</strong> in both the detection and classification directory, where there are weights that have been trained on a part of the camera trap images available at the link below.</li> </ul> <p><em>Classification weights</em></p> <ol> <li>EfficientNetv2-M</li> <li><strong>ResNeSt-101e</strong> (🚀 RECOMMENDED)</li> <li>ResNet-101d</li> <li>ReXnet-100</li> <li>SeResNet-152d</li> </ol> <p><em>Detection weights</em></p> <ol> <li>YOLOR-W6-1280</li> <li>YOLOX-X-640</li> <li>YOLOv5-X-640</li> <li>YOLOv5-X-1280</li> <li>YOLOv5-M6-1280</li> <li><strong>YOLOv5-L6-1280</strong> (🚀 RECOMMENDED)</li> </ol> <p>Read README.md file for more details</p>
Supplementary material 2 from: Trochet A, Schmeller D (2013) Effectiveness of the Natura 2000 network to cover threatened species. Nature Conservation 4: 35-53. https://doi.org/10.3897/natureconservation.4.3626
Supplementary material 2 from: Trochet A, Schmeller D (2013) Effectiveness of the Natura 2000 network to cover threatened species. Nature Conservation 4: 35-53. https://doi.org/10.3897/natureconservation.4.3626
Supplementary material 1 from: Gruber B, Evans D, Henle K, Bauch B, Schmeller D, Dziock F, Henry P, Lengyel S, Margules C, Dormann C (2012) "Mind the gap!" – How well does Natura 2000 cover species of European interest? Nature Conservation 3: 45-62. https://doi.org/10.3897/natureconservation.3.3732
The table shows the 54 gap species ordered by species group. Please note: The comment column is based on expert opinion of the European Topic Centre, which has the latest version of the Natura2000 data base and also knowledge on confidential sites, which are deleted from the public version of the data base to protect rare species.
Supplementary material 1 from: Schmeller D, Maier A, Evans D, Henle K (2012) National responsibilities for conserving habitats – a freely scalable method. Nature Conservation 3: 21-44. https://doi.org/10.3897/natureconservation.3.3710
The annex does provide a more detailed comparison of the different biogeographic maps. It further gives a list of all forest habitats given in the EU Habitats Direction
Supplementary material 1 from: Schmeller D, Henle K, Loyau A, Besnard A, Henry P (2012) Bird-monitoring in Europe – a first overview of practices, motivations and aims. Nature Conservation 2: 41-57. https://doi.org/10.3897/natureconservation.2.3644
The questionnaire was designed to assess how biodiversity monitoring schemes were carried out and what the motivation was to launch that scheme.
Supplementary material 1 from: Pontoppidan M, Nachman G (2013) Changes in behavioural responses to infrastructure affect local and regional connectivity – a simulation study on pond breeding amphibians. Nature Conservation 5: 13-28. https://doi.org/10.3897/natureconservation.5.4611
Full model description following the ODD-template suggested by Grimm et al. (2006, 2010) and model parameterisation. (doi: 10.3897/natureconservation.5.4611.app). File format: Adobe PDF document (pdf).:
Supplementary material 1 from: Bongard C, Butler K, Fulthorpe R (2013) Investigation of fungal root colonizers of the invasive plant Vincetoxicum rossicum and co-occurring local native plants in a field and woodland area in Southern Ontario. Nature Conservation 4: 55-76. https://doi.org/10.3897/natureconservation.4.3578
Supplementary material 1 from: Bongard C, Butler K, Fulthorpe R (2013) Investigation of fungal root colonizers of the invasive plant Vincetoxicum rossicum and co-occurring local native plants in a field and woodland area in Southern Ontario. Nature Conservation 4: 55-76. https://doi.org/10.3897/natureconservation.4.3578
Supplementary material 1 from: Pontoppidan M, Nachman G (2013) Spatial Amphibian Impact Assessment – a management tool for assessment of road effects on regional populations of Moor frogs (Rana arvalis). Nature Conservation 5: 29-52. https://doi.org/10.3897/natureconservation.5.4612
Full model description following the protocol suggested by Grimm et al. (2006, 2010) and model parameterisation. (doi: 10.3897/natureconservation.5.4612.app). File format: Adobe PDF document (pdf).:
Map. Species diversity of Diplopoda within the Sikhote-Alin State Nature Biosphere Reserve. The numbers of the natural landmarks (1–18) are explained in the "Material and Methods section" Карта. ВиΑовое разнообразие Αвупарноногих многоножек в Сихотэ-АΛинском заповеΑнике. Номера урочищ (1–18) поясняются в разΑеΛе «МатериаΛ и метоΑы» in Review of the millipedes of the Sikhote-Alin State Nature Biosphere Reserve (Far East of Russia), with detection of the morphological variability of Diplomaragna terricolor (Attems, 1899) (Diplopoda)
Map. Species diversity of Diplopoda within the Sikhote-Alin State Nature Biosphere Reserve. The numbers of the natural landmarks (1–18) are explained in the "Material and Methods section" Карта. ВиΑовое разнообразие Αвупарноногих многоножек в Сихотэ-АΛинском заповеΑнике. Номера урочищ (1–18) поясняются в разΑеΛе «МатериаΛ и метоΑы»
Рис. 1. Пункты сбора материаΛов в районе Ботчинского заповеΑника. Пункты сбора обозначены красными кружками, наибоΛее крупный из которых соответствует основному месту сбора — корΑону «ТепΛый КΛюч». Номера пунктов сбора соответствуют номерам в тексте при их описании. БΛизко распоΛоженные пункты сборов показаны оΑним симвоΛом Fig. 1. Points of collection of materials in the area of the Botchinsky Nature Reserve. Collection points are marked with red circles, the largest of which corresponds to the main collection point — the cordon "Teply Klyuch". The collection point numbers correspond to the numbers in the text when they are described. Closely located collection points are shown with one symbol in Fauna of the geometrid moths (Lepidoptera, Geometridae) of the eastern Sikhote-Alin in the area of the Botchinsky State Nature Reserve I: History of research and subfamilies Archiearinae, Ennominae, Desmobathrinae, and Geometrinae
Рис. 1. Пункты сбора материаΛов в районе Ботчинского заповеΑника. Пункты сбора обозначены красными кружками, наибоΛее крупный из которых соответствует основному месту сбора — корΑону «ТепΛый КΛюч». Номера пунктов сбора соответствуют номерам в тексте при их описании. БΛизко распоΛоженные пункты сборов показаны оΑним симвоΛом Fig. 1. Points of collection of materials in the area of the Botchinsky Nature Reserve. Collection points are marked with red circles, the largest of which corresponds to the main collection point — the cordon "Teply Klyuch". The collection point numbers correspond to the numbers in the text when they are described. Closely located collection points are shown with one symbol
Figure. Food preferences of Chinese mole shrew (Anourosorex squamipes) from an urban area. a, b, c, d. Mean relative consumption along six trials for each food set are shown in a, b, c, d, respectively. (see materials and methods for details on the calculation of relative consumption). in Natural animal food preference of Chinese mole shrew (Anourosorex squamipes) from an urban area: a laboratory study
Figure. Food preferences of Chinese mole shrew (Anourosorex squamipes) from an urban area. a, b, c, d. Mean relative consumption along six trials for each food set are shown in a, b, c, d, respectively. (see materials and methods for details on the calculation of relative consumption).
Linked collectors and determiners for: Catalogue of the type material in the entomological collection of the Natural History Museum of Denmark: basal hexapods.
Natural history specimen data linked to collectors and determiners held within, "Catalogue of the type material in the entomological collection of the Natural History Museum of Denmark: basal hexapods". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/ec2c4620-dc5c-4aa2-91b2-f122e35610b3">https://bionomia.net/dataset/ec2c4620-dc5c-4aa2-91b2-f122e35610b3</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/ec2c4620-dc5c-4aa2-91b2-f122e35610b3">https://gbif.org/dataset/ec2c4620-dc5c-4aa2-91b2-f122e35610b3</a>. Formatted as a Frictionless Data package.
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.