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12,393 results for “materiality”
Barefoot Rover MINS30 Material Data
<p>This archive contains test data of the Barefoot Rover wheel on MINS30 material.</p> <p>The Barefoot Rover wheel was used to demonstrate an instrumented wheel concept which utilizes a 2D pressure grid, an electrochemical impedance spectroscopy (EIS) sensor and machine learning (ML) to extract meaningful metrics from the interaction between the wheel and surface terrain. These include continuous slip/skid estimation, balance, and sharpness for engineering applications. Estimates of surface hydration, texture, terrain patterns, and regolith physical properties such as cohesion and angle of internal friction are additionally calculated for science applications. Traditional systems rely on post-processing of visual images and vehicle telemetry to estimate these metrics. Through in-situ sensing, these metrics can be calculated in near real time and made available to onboard science and engineering autonomy applications. This work aims to provide a deployable system for future planetary exploration missions to increase science and engineering capabilities through increased knowledge of the terrain.</p> <p>More detailed information about data structures, material properties and test configurations can be found here: https://github.com/JPLMLIA/Barefoot_Rover/tree/master/data</p>
Barefoot Rover WED730 Material Data
<p>This archive contains test data of the Barefoot Rover wheel on WED730 material.</p> <p>The Barefoot Rover wheel was used to demonstrate an instrumented wheel concept which utilizes a 2D pressure grid, an electrochemical impedance spectroscopy (EIS) sensor and machine learning (ML) to extract meaningful metrics from the interaction between the wheel and surface terrain. These include continuous slip/skid estimation, balance, and sharpness for engineering applications. Estimates of surface hydration, texture, terrain patterns, and regolith physical properties such as cohesion and angle of internal friction are additionally calculated for science applications. Traditional systems rely on post-processing of visual images and vehicle telemetry to estimate these metrics. Through in-situ sensing, these metrics can be calculated in near real time and made available to onboard science and engineering autonomy applications. This work aims to provide a deployable system for future planetary exploration missions to increase science and engineering capabilities through increased knowledge of the terrain.</p> <p>More detailed information about data structures, material properties and test configurations can be found here: https://github.com/JPLMLIA/Barefoot_Rover/tree/master/data</p>
Barefoot Rover GRC01 Material Data
<p>This archive contains test data of the Barefoot Rover wheel on GRC01 material.</p> <p>The Barefoot Rover wheel was used to demonstrate an instrumented wheel concept which utilizes a 2D pressure grid, an electrochemical impedance spectroscopy (EIS) sensor and machine learning (ML) to extract meaningful metrics from the interaction between the wheel and surface terrain. These include continuous slip/skid estimation, balance, and sharpness for engineering applications. Estimates of surface hydration, texture, terrain patterns, and regolith physical properties such as cohesion and angle of internal friction are additionally calculated for science applications. Traditional systems rely on post-processing of visual images and vehicle telemetry to estimate these metrics. Through in-situ sensing, these metrics can be calculated in near real time and made available to onboard science and engineering autonomy applications. This work aims to provide a deployable system for future planetary exploration missions to increase science and engineering capabilities through increased knowledge of the terrain.</p> <p>More detailed information about data structures, material properties and test configurations can be found here: https://github.com/JPLMLIA/Barefoot_Rover/tree/master/data</p>
Yes! We're open. Open science and the future of academic practices in translation and interpreting studies - Supplementary material
<p>Supplementary material to the article "<em>Yes! We’re open</em>. Open science and the future of academic practices in translation and interpreting studies" by Christian Olalla-Soler. </p> <ul> <li>Sheet 1: Translation and Interpreting Studies journals and bibliometric indicators.</li> <li>Sheet 2: Translation and Interpreting Studies articles in Scopus.</li> <li>Sheet 3: Pre-registrations related to translation and interpreting.</li> </ul> <p>Reference:</p> <p>Olalla-Soler, Christian (2021). "<em>Yes! We’re open</em>. Open science and the future of academic practices in translation and interpreting studies". <em>Translation & Interpreting</em> 13 (2): 1-28. <a href="https://doi.org/10.12807/ti.113202.2021.a01">https://doi.org/10.12807/ti.113202.2021.a01</a></p>
In situ polyaniline coating of Prussian blue as cathode material for sodium-ion battery
<p>Prussian blue has great potential for using as a sodium cathode material owing to its high working potential and cube frame structure. Herein, this work reports a two-step method to synthesize Prussian blue with ascorbic acid (AA) as the ball-milling additive, which improves electrochemical rate performance of Prussian blue during the traditional co-precipitation method. The obtained Prussian blue sample exhibited a superior specific capability (113.3 mAh g<sup>-1</sup> even at 20 C, 1 C=170 mA g<sup>-1</sup>) and a specific capacity retention of 84.8% after 100 cycles at 1 C rate. In order to enhance the cycling performance of the Prussian blue, an in situ polyaniline (PANI) coating strategy was employed in which aniline was added into the electrolyte and polymerized under electrochemical conditions. The coated anode exhibited a high specific capacity retention of 62.7% after 500 cycles, which is significantly higher than that of the non-coated sample which only remains 40.1% after 500 cycles. This development has shown a great potential as a low-cost, high-performance and environmental-friendly technology for large-scale industrial application of PB.</p>
Supplementary material_Paleoenvironment of the Cerro Negro Formation (Aptian, Early Cretaceous) of Snow Island, Antarctic Peninsula
<p>Supplementary material of the article entitled "Paleoenvironment of the Cerro Negro Formation (Aptian, Early Cretaceous) of Snow Island, Antarctic Peninsula", submitted to Anais da Academia Brasileira de Ciências</p>
Supplementary materials accompanying "Baring the bones: the lexico-semantic association of bone with strength in Melanesia and the study of colexification"
<p>Supplementary materials accompanying "Baring the bones: the lexico-semantic association of bone with strength in Melanesia and the study of colexification". Two appendices. Appendix I: Melanesian languages with associations of ‘bone’ with strength. Appendix II: Colexifications of ‘bone’ in databases.</p>
Atmosphéries and the poetics of the in situ: the role and impact of sensors in data-to-sound transposition installations - Supplementary audio material
<p>This audio file wishes to give an insight into NXI Gestatio Design Lab's <em>Atmosphéries</em> research program, and to accompany the publication "Atmosphéries and the poetics of the in situ: the role and impact of sensors in data-to-sound transposition installations". The file consists in a 7-minutes recording of the <em>Meridian Probe</em>, the last instrument designed within the <em>Atmosphéries</em> program, which allows to generate sound from on-site atmospheric data. The recorded extract then acts as a sonic representation of the atmospheric conditions found at the place of exhibition, at the time of recording - in this case, gardens of the Bussy-Rabutin's Castle (France), respectively July 31st, 2021, 17h17. For further information about the <em>Meridian Probe</em>'s design and functioning, we invite you to read the aforementioned publication.</p>
Figures 37–48 in Lectotype designations in Tetratomidae, Melandryidae, Boridae and Mycteridae, based on material in the Museum of Comparative Zoology, Harvard University (Coleoptera: Tenebrionoidea)
Figures 37–48. Dorsal and lateral habitus of newly designated lectotypes. 37–38. Orchesia gracilis Melsheimer, lectotype. 37) Dorsal habitus. 38) Lateral habitus. Scale lines = 2.0 mm. 39–40. Orchesia ornata Horn, lectotype. 39) Dorsal habitus. 40) Lateral habitus. Scale lines = 1.0 mm. 41–42. Amblyctis praeses LeConte, lectotype. 41) Dorsal habitus. 42) Lateral habitus. Scale lines = 5.0 mm. 43–44. Dircaea sericea Haldeman, female lectotype. 43) Dorsal habitus. 44) Lateral habitus. Scale lines = 2.0 mm. 45–46. Serropalpus obsoletus Haldeman, lectotype. 45) Dorsal habitus. 46) Lateral habitus. Scale lines = 5.0 mm. 47–48. Serropalpus substriatus Haldeman, lectotype. 47) Dorsal habitus. 48) Lateral habitus. Scale lines = 2.0 mm.
Figure 26–36 in Lectotype designations in Tetratomidae, Melandryidae, Boridae and Mycteridae, based on material in the Museum of Comparative Zoology, Harvard University (Coleoptera: Tenebrionoidea)
Figure 26–36. Dorsal and lateral habitus of newly designated lectotypes. 26. Melandrya striata var. bicolor Melsheimer, lectotype, lateral habitus. Scale line = 2.0 mm. 27–28. Melandrya striata var. thoracica Melsheimer, lectotype. 27) Dorsal habitus. 28) Lateral habitus. Scale lines = 5.0 mm. 29–30. Hypulus fulminans LeConte, lectotype. 29) Dorsal habitus. 30) Lateral habitus. Scale lines = 1.0 mm. 31–32. Microscapha arctica Horn, lectotype. 31) Dorsal habitus. 32) Lateral habitus. Scale lines = 0.5 mm. 33–34. Microscapha clavicornis LeConte, lectotype. 33) Dorsal habitus. 34) Lateral habitus. Scale lines = 1.0 mm. 35–36. Orchesia castanea Melsheimer, lectotype. 35) Dorsal habitus. 36) Lateral habitus. Scale lines = 2.0 mm.
Figure 14–25 in Lectotype designations in Tetratomidae, Melandryidae, Boridae and Mycteridae, based on material in the Museum of Comparative Zoology, Harvard University (Coleoptera: Tenebrionoidea)
Figure 14–25. Dorsal and lateral habitus of newly designated lectotypes. 14) Dircaea riversi LeConte, lectotype, lateral habitus. Scale line = 5.0 mm. 15–16. Hypulus trifasciatus Melsheimer, lectotype. 15) Dorsal habitus. 16) Lateral habitus. Scale lines = 2.0 mm. 17–18. Microtonus sericans LeConte, lectotype. 17) Dorsal habitus. 18) Lateral habitus. Scale lines = 1.0 mm. 19–20. Scraptia flavicollis Haldeman, lectotype. 19) Dorsal habitus. Scale line = 2.0 mm. 20) Lateral habitus. Scale line = 1.0 mm. 21–22. Scraptia rugosa Haldeman, lectotype. 21) Dorsal habitus. 22) Lateral habitus. Scale lines = 1.0 mm. 23–24. Melandrya maculata LeConte, male lectotype. 23) Dorsal habitus. 24) Lateral habitus. Scale lines = 2.0 mm. 25) Melandrya striata var. bicolor Melsheimer, lectotype, dorsal habitus.
Figures 49–58 in Lectotype designations in Tetratomidae, Melandryidae, Boridae and Mycteridae, based on material in the Museum of Comparative Zoology, Harvard University (Coleoptera: Tenebrionoidea)
Figures 49–58. Dorsal and lateral habitus of newly designated lectotypes. 49–50. Carebara longula LeConte, lectotype. 49) Dorsal habitus. 50) Lateral habitus. Scale lines = 2.0 mm. 51–52. Hallomenus quadripustulata Melsheimer, lectotype. 51) Dorsal habitus. 52) Lateral habitus. Scale lines = 1.0 mm. 53–54. Mycterus canescens Horn, male lectotype. 53) Dorsal habitus. 54) Lateral habitus. Scale lines = 2.0 mm. 55–56. Mycterus quadricollis Horn, male lectotype. 55) Dorsal habitus. 56) Lateral habitus. Scale lines = 2.0 mm. 57–58. Crymodes discicollis LeConte, lectotype. 57) Dorsal habitus. 58) Lateral habitus. Scale lines = 2.0 mm.
Figures 1–13 in Lectotype designations in Tetratomidae, Melandryidae, Boridae and Mycteridae, based on material in the Museum of Comparative Zoology, Harvard University (Coleoptera: Tenebrionoidea)
Figures 1–13. Dorsal and lateral habitus of newly designated lectotypes. 1–2. Hallomenus scapularis Melsheimer, lectotype. 1) Dorsal habitus. 2) Lateral habitus. Scale lines = 2.0 mm. 3–4. Hallomenus serricornis LeConte, lectotype. 3) Dorsal habitus. 4) Lateral habitus. Scale lines = 2.0 mm. 5–6. Hypulus bicinctus Horn, lectotype. 5) Dorsal habitus. 6) Lateral habitus. Scale lines = 2.0 mm. 7–8. Dircaea liturata LeConte, male lectotype. 7) Dorsal habitus. 8) Lateral habitus. Scale lines = 2.0 mm. 9–10. Dircaea fusca LeConte, female lectotype. 9) Dorsal habitus. 10) Lateral habitus. Scale lines = 2.0 mm. 11–12. Dircaea prona LeConte, male lectotype. 11) Dorsal habitus. 12) Lateral habitus. Scale lines = 5.0 mm. 13). Dircaea riversi LeConte, female lectotype, dorsal habitus. Scale line = 5.0 mm.
Dopant Engineering for Spiro-OMeTAD Hole-Transporting Materials towards Efficient Perovskite Solar Cells
<p>Optoelectronic, photovoltaic, and supplementary characterization data for “Dopant Engineering for Spiro-OMeTAD Hole-Transporting Materials towards Efficient Perovskite Solar Cells”, DOI:10.1002/adfm.202102124</p> <ul> <li>CV.zip: Data (cyclic voltammograms) described in Figures S3–S5 in Origin (*opj) file format.</li> <li>EPR.zip: Data (EPR spectra) described in Figure 5, Figure S2, and Table S2 in Origin (*opj) file format.</li> <li>Optical.zip: Data (UV-vis, PL, and TRPL spectra) described in Figure 4 and Table S1 in Origin (*opj) file format.</li> <li>PV.zip: Data (photovoltaic characteristics) described in the Figures 2–3, Table 1, Figure S1, and Figure S6 in Origin (*opj) file format.</li> </ul>
Supplementary material to "Exogenous corticosterone and melanin-based coloration explain variation in juvenile dispersal behaviour in the barn owl (Tyto alba)"
<p><strong>Abstract</strong></p> <p>Natal dispersal affects many processes such as population dynamics. So far, most studies have examined the intrinsic and extrinsic factors that determine the distance between the place of birth and of first breeding. In contrast, few researchers followed the first steps of dispersal soon after fledging. To study this gap, we radio-tracked 95 barn owl nestlings (<em>Tyto alba</em>) to locate their diurnal roost sites from the fledging stage until December. This was used to test whether the age of nest departure, post-fledging movements and dispersal distance were related to melanin-based coloration, which is correlated to fitness-related traits, as well as to corticosterone, a hormone that mediates a number of life history trade-offs and the physiological and behavioural responses to stressful situations. We found that the artificial administration of corticosterone delayed the age when juveniles left their parental home-range in females but not in males. During the first few months after fledging, longer dispersal distances were reached by females compared to males, by individuals marked with larger black feather spots compared to individuals with smaller spots, by larger individuals and by those experimentally treated with corticosterone. We conclude that the onset and magnitude of dispersal is sensitive to the stress hormone corticosterone, melanin-based coloration and body size. </p>
Figure 10 in The complete larval development of Sadayoshia edwardsii (Miers, 1884) (Decapoda: Anomura: Galatheidae) described from laboratory-reared material
Figure 10. Sadayoshia edwardsii (Miers, 1884), abdomen and telson. (A) First zoea, abdomen and telson, dorsal; (B) first zoea, posterodorsal margins of fourth and fifth segments, dorsal; (C) first zoea, posterolateral margin of telson, dorsal; (D) first zoea, innermost plumose seta, dorsal; (E) second zoea, fourth and fifth abdominal segments and telson, dorsal; (F) third zoea, sixth abdominal segment, uropod and telson, dorsal; (G) fourth zoea, uropod and telson, dorsal; (H) fourth zoea, first pleopod, ventral; (I) megalop, tail fan, dorsal; (J–M) megalop, first to fourth pleopods, ventral, exopodal plumose setae of second to fourth pleopods truncated. Scale bars: 0.1 mm.
Figure 9 in The complete larval development of Sadayoshia edwardsii (Miers, 1884) (Decapoda: Anomura: Galatheidae) described from laboratory-reared material
Figure 9. Sadayoshia edwardsii (Miers, 1884). (A–E) third maxilliped: (A) First zoea; (B) second zoea; (C) third zoea; (D) fourth zoea; (E) megalop (F–K) Pereiopods: (F) Second zoea; (G) third zoea; (H) fourth zoea; (I) megalop, first pereiopod; (J) megalop, second pereiopod, carpus, propodus and dactylus; (K) megalop, fifth pereopod, propodus and dactylus. Scale bars: 0.1 mm.
Figure 8 in The complete larval development of Sadayoshia edwardsii (Miers, 1884) (Decapoda: Anomura: Galatheidae) described from laboratory-reared material
Figure 8. Sadayoshia edwardsii (Miers, 1884), second maxilliped. (A) First zoea; (B) second zoea; (C) third zoea; (D) fourth zoea; (E) megalop. Scale bars: 0.1 mm.
Figure 7 in The complete larval development of Sadayoshia edwardsii (Miers, 1884) (Decapoda: Anomura: Galatheidae) described from laboratory-reared material
Figure 7. Sadayoshia edwardsii (Miers, 1884), first maxilliped (A) First zoea; (B) second zoea; (C) third zoea; (D) fourth zoea; (E) megalop. Scale bars: 0.1 mm.
Figure 6 in The complete larval development of Sadayoshia edwardsii (Miers, 1884) (Decapoda: Anomura: Galatheidae) described from laboratory-reared material
Figure 6. Sadayoshia edwardsii (Miers, 1884), maxilla. (A) First zoea; (B) second zoea; (C) third zoea; (D) fourth zoea; (E) megalop. Scale bars: 0.1 mm.
ScienceDex guides
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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.