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Dataset for paper entitled 'Quantification of strain fields and grain refinement in Ti-6Al-4V inter-pass rolled wire-arc AM by EBSD misorientation analysis'.
<p>Dataset for paper entitled 'Quantification of strain fields and grain refinement in Ti-6Al-4V inter-pass rolled wire-arc AM by EBSD misorientation analysis'. doi: https://doi.org/10.1016/j.matchar.2020.110673</p>
Medicago tornata Willd. ex Ces., Pass. & Gibelli (BR0000011975519)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Figure 5. Low-pass filter-EKG Through Sound-Card
<p>The low-pass filter, presented in figure 5, allows signals with frequencies up to 34 Hz (cutoff<br> frequency) to pass unaltered while it strongly attenuates those with frequencies exceeding the<br> cut-off frequency. It is an active filter, of the butterworth sallen-key type which contains one of the<br> four operational amplifiers of the TL084 integrated circuit.</p>
Рис. 1. Ctenoceratoda tancrei, бабочки из разΛичных ΛокаΛитетов: а, e — Киргизский хр., нац. парк «АΛа-Арча»; b, f — хр. ΔжумгаΛтоо, массив Сары-Кайкы; c, d, g, h — хр. МоΛΑо-Тоо, пер. Коро-Гоо. a–d — самцы, e–h — самки Fig. 1. Ctenoceratoda tancrei, the wing pattern variability: a, e — Kirghiz Mts., «Ala-Archa» national park; b, f — Dzhumgaltoo Mts., Sary-Kaiky gorge; c, d, g, h — Moldo-Too Mts., Koro-Goo Pass. a–d — males, e–h — females in Morphometric analysis of genitalia of Ctenoceratoda tancrei (Graeser, 1892) (Lepidoptera, Noctuidae)
Рис. 1. Ctenoceratoda tancrei, бабочки из разΛичных ΛокаΛитетов: а, e — Киргизский хр., нац. парк «АΛа-Арча»; b, f — хр. ΔжумгаΛтоо, массив Сары-Кайкы; c, d, g, h — хр. МоΛΑо-Тоо, пер. Коро-Гоо. a–d — самцы, e–h — самки Fig. 1. Ctenoceratoda tancrei, the wing pattern variability: a, e — Kirghiz Mts., «Ala-Archa» national park; b, f — Dzhumgaltoo Mts., Sary-Kaiky gorge; c, d, g, h — Moldo-Too Mts., Koro-Goo Pass. a–d — males, e–h — females
РИС. 5. ЗагрЯЗнение готовых обраЗцов длЯ СЭМ при длительном хранении в негерметичных условиЯх (A–C) либо при хранении проШедШих процедуру мацерированиЯ беЗ последуюЩего обеЗЗараживаниЯ (D, E). A–С. Бактерии на поверхности глохидиев (Nodularia douglasiae, р. ИлистаЯ, бассейн оЗ. Ханка, Приморский кр.). А. ВнеШний вид глохидиЯ, основное ЗагрЯЗнение на створке в верхней части фото. В. Крючок глохидиЯ, основное ЗагрЯЗнение в левой части фото. С. Створка, вид иЗнутри. D. Единичные бактерии на створке глохидиЯ, вид иЗнутри (Kunashiria japonica, оЗ. Утиное, о-в Зелёный, Курильские о-ва). E. Гифы гриба на створке глохидиЯ, вид на наружную пору (Beringiana beringiana, оЗ. АЗабачье, Камчатка). МасШтаб 50 мкм (А, C), 10 мкм (В, D), 1 мкм (Е). Микроскопы Zeiss MERLIN (А, B, C, E), Zeiss EVO 40 (D), напыление хромом (А–С), Золотом (D), углеродом (Е). FIG. 5. Contamination of the SEM ready-made samples during long-term storage under unsealed conditions (A–C) or during storage the samples that have passed the maceration procedure without subsequent disinfection (D, E). A–C. Bacteria on the glochidia surface (Nodularia douglasiae, Ilistaya River, Khanka Lake basin, Primorsky Krai). A. Glochidium with the main pollution on the valve in the upper part of the photo. B. Hook with the main pollution on the left side of the photo. C. Interior valve. D. Bacteria on the interior valve (Kunashiria japonica, Utinoe Lake, Zeliony Island, Kuril Islands). E. Fungal hyphae on the pore of exterior valve (Beringiana beringiana, Azabachye Lake, Kamchatka). Scale bars 50 μm (A, C), 10 μm (B, D), 1 μm (E). Zeiss MERLIN (A, B, C, E) and Zeiss EVO 40 (D) microscopes, sputter coating with chromium (A–C), gold (D), and carbon (E). in Методика подготовки раковин глохидиев (Bivalvia, Unionidae) длЯ работы на сканируюЩем Электронном микроскопе
РИС. 5. ЗагрЯЗнение готовых обраЗцов длЯ СЭМ при длительном хранении в негерметичных условиЯх (A–C) либо при хранении проШедШих процедуру мацерированиЯ беЗ последуюЩего обеЗЗараживаниЯ (D, E). A–С. Бактерии на поверхности глохидиев (Nodularia douglasiae, р. ИлистаЯ, бассейн оЗ. Ханка, Приморский кр.). А. ВнеШний вид глохидиЯ, основное ЗагрЯЗнение на створке в верхней части фото. В. Крючок глохидиЯ, основное ЗагрЯЗнение в левой части фото. С. Створка, вид иЗнутри. D. Единичные бактерии на створке глохидиЯ, вид иЗнутри (Kunashiria japonica, оЗ. Утиное, о-в Зелёный, Курильские о-ва). E. Гифы гриба на створке глохидиЯ, вид на наружную пору (Beringiana beringiana, оЗ. АЗабачье, Камчатка). МасШтаб 50 мкм (А, C), 10 мкм (В, D), 1 мкм (Е). Микроскопы Zeiss MERLIN (А, B, C, E), Zeiss EVO 40 (D), напыление хромом (А–С), Золотом (D), углеродом (Е). FIG. 5. Contamination of the SEM ready-made samples during long-term storage under unsealed conditions (A–C) or during storage the samples that have passed the maceration procedure without subsequent disinfection (D, E). A–C. Bacteria on the glochidia surface (Nodularia douglasiae, Ilistaya River, Khanka Lake basin, Primorsky Krai). A. Glochidium with the main pollution on the valve in the upper part of the photo. B. Hook with the main pollution on the left side of the photo. C. Interior valve. D. Bacteria on the interior valve (Kunashiria japonica, Utinoe Lake, Zeliony Island, Kuril Islands). E. Fungal hyphae on the pore of exterior valve (Beringiana beringiana, Azabachye Lake, Kamchatka). Scale bars 50 μm (A, C), 10 μm (B, D), 1 μm (E). Zeiss MERLIN (A, B, C, E) and Zeiss EVO 40 (D) microscopes, sputter coating with chromium (A–C), gold (D), and carbon (E).
A Point Cloud Dataset of Vehicles Passing Through a Toll Station for use in Training Classification Algorithms
<p>This work presents a point cloud dataset of vehicles passing through a toll station in Colombia to be used to train artificial vision and computational intelligence algorithms. This article details the process of creating the dataset, covering initial data acquisition, range information preprocessing, point cloud validation, and vehicle labeling. Additionally, a detailed description of the structure and content of the dataset is provided, along with some potential applications of its use. The dataset consists of 36,026 total object classes: 31,432 cars, campers, vans and 2-axle trucks with a single tire on the rear axle, 452 minibuses with a single tire on the rear axle, 1158 buses, 1179 2-axle small trucks, 797 2-axle large trucks, and 1008 trucks with 3 or more axles. The point clouds were captured using a LiDAR sensor and Doppler effect speed sensors. The dataset can be used to train and evaluate algorithms for range data processing, vehicle classification, vehicle counting, and traffic flow analysis. The dataset can also be used to develop new applications for intelligent transportation systems.</p> <table> <tbody> <tr> <td>Type</td> <td>Description</td> <td>Quantity</td> </tr> <tr> <td>1</td> <td>Cars, campers, vans and 2-axle trucks with<br>a single tire on the rear axle</td> <td>31,432</td> </tr> <tr> <td>2</td> <td>Minibuses with a single tire on the rear axle</td> <td>452</td> </tr> <tr> <td>3</td> <td>Buses</td> <td>1,158</td> </tr> <tr> <td>4</td> <td>Trucks with 3 or more axles</td> <td>1,008</td> </tr> <tr> <td>5</td> <td>2-axle small trucks</td> <td>1,179</td> </tr> <tr> <td>6</td> <td>2-axle large truck</td> <td>797</td> </tr> <tr> <td>Total</td> <td> </td> <td>36,026</td> </tr> </tbody> </table>
Figures 31–35 in DNA sequencing reveals three new species of Chamberlainium (Corallinales, Rhodophyta) from South Africa, all formerly passing under Spongites yendoi
Figures 31–35: Chamberlainium occidentale habit and vegetative anatomy. (31) Rock fragment with holotype specimen showing the region (white arrow) of the holotype from which all analyses were done (L 3986120, gametangial and tetrasporangial). Scale bar = 10 mm. (32) Vertical section through the margin (black arrow) showing the monomerous thallus construction with plumose medulla (M) giving rise to cortical filaments (C) that terminate in a single layer of epithallial cells (black arrowhead) (UWC 15/59). Scale bar = 50 μm. (33) Vertical section of the inner thallus showing cell fusions (f) between adjacent medullary filaments (UWC 15/56). Scale bar = 20 μm. (34) Vertical section of the outer thallus showing a single layer of epithallial cells (e) subtended by a layer of subepithallial initials (i). Note the cell fusions (f) between adjacent cortical filaments (UWC 15/59). Scale bar = 20 μm. (35) Vertical section of the outer thallus showing a single layer of epithallial cells (e) subtended by a layer of subepithallial initials (i). Note a cluster of bottle-shaped trichocytes (t) each separated by vegetative filaments (UWC 15/59). Scale bar = 20 μm.
The most remarkable migrants: Systematic analysis of the Western European insect flyway at a Pyrenean mountain pass
<p>In 1950, David and Elizabeth Lack chanced upon a huge migration of insects and birds flying through the Pyrenean Pass of Bujaruelo, later describing the spectacle as combining both grandeur with novelty. The intervening years have seen many changes to land use and climate, posing the question as to the current status of this migratory phenomenon, while a lack of quantitative data has prevented insights into the ecological impact of this mass insect migration and into the factors affecting it. To address this, we revisited the site in autumn over a 4-year period and systematically monitored diurnal insect species and numbers. We document an annual mean of 17.1 million day-flying insects from 5 orders moving south, with 'mass migration' events associated with warmer temperatures, the presence of a headwind, sunlight, low windspeed, and low rainfall. Diptera dominated the migratory assemblage and annual numbers varied by more than fourfold with larger annual migration flows associated with higher autumn temperatures in Northwest Europe. Finally, using observed environmental thresholds for migration, we estimate an annual 'bioflow' of at least 14.6 billion day-flying insects migrating south over the whole Pyrenean Mountain range, highlighting the importance of this route for seasonal insect migrants.</p>
Dataset: Society Pass Incorporated (SOPA) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Рис. 1. Bryoxena centralasiae, изменчивость крыΛового рисунка: а, λ — Киргизский хр., нац. парк «АΛа-Арча»; в, г, з — хр. ΔжумгаΛтоо, массив Сары-Кайкы; д, к, м — хр. МоΛΑо-Тоо, пер. Коро-Гоо; б, е — Ферганский хр., пер. Урумбаш; ж, и — АΛайский хр., пер. ТаΛΑык Fig. 1. Bryoxena centralasiae, the wing pattern variability: а, λ — Kirghiz Mts., «Ala-Archa» national park; в, г, з — Dzhumgaltoo Mts., Sary-Kaiky gorge; д, к, м — Moldo-Too Mts., Koro-Goo Pass; б, е — Fergansky Mts., Urumbash Pass; ж, и — Alai Mts., Taldyk Pass in Morphometric Analysis Of The Genitalia Of (Staudinger, 1882) (Lepidoptera, Noctuidae)
Рис. 1. Bryoxena centralasiae, изменчивость крыΛового рисунка: а, λ — Киргизский хр., нац. парк «АΛа-Арча»; в, г, з — хр. ΔжумгаΛтоо, массив Сары-Кайкы; д, к, м — хр. МоΛΑо-Тоо, пер. Коро-Гоо; б, е — Ферганский хр., пер. Урумбаш; ж, и — АΛайский хр., пер. ТаΛΑык Fig. 1. Bryoxena centralasiae, the wing pattern variability: а, λ — Kirghiz Mts., «Ala-Archa» national park; в, г, з — Dzhumgaltoo Mts., Sary-Kaiky gorge; д, к, м — Moldo-Too Mts., Koro-Goo Pass; б, е — Fergansky Mts., Urumbash Pass; ж, и — Alai Mts., Taldyk Pass
Fig. 4 in The Canal da Piracema at Itaipu Dam as a fish pass system
Fig. 4. Number of individuals of the principal species, according to reproductive strategy by different biotope: LDMI (long-distance migratory species), SNPC (sedentary with no parental care), SPC (sedentary with parental care), SIFE (sedentary with internal fertilization and external development), SIFI (sedentary with internal fertilization and internal development) and UNK (unknown).
Fig. 3 in The Canal da Piracema at Itaipu Dam as a fish pass system
Fig. 3. Ordination (correspondence analysis – CA; Axis 1 – CA1; Axis 2 – CA2) of the samples taken with seining nets, electrofishing, gillnets, and cast nets, at different stations located in the Canal da Piracema (a). Representation of the mean scores by fishing gears in axis 1 (b) and axis 2 (c).
Fig. 2 in The Canal da Piracema at Itaipu Dam as a fish pass system
Fig. 2. Species number by order and family. Dotted lines delimit the families in relation to the orders.
Рис. 2. Черношапочные сурки и их местообитания на хребте КоΑар: A — виΑ на ЦентраΛьный КоΑар и ΑоΛину р. СреΑний Сакукан; B — местообитание сурков поΑ переваΛом; C — местообитание сурков по берегам р. Того; D — местообитание сурков на вершине гребня, каΑр с фотоΛовушки; E — сурки; F — черношапочный сурок обΛизывает пΛасты каменного угΛя, каΑр из виΑеосъемки Fig. 2. Black-capped marmots and their habitats on the Kodar Ridge: A — view of the Central Kodar and the valley of the Middle Sakukan River; B — habitat of marmots under the mountain pass; C — habitat of marmots along the banks of the Togo River; D — marmot habitat at the top of the mountain ridge, camera trap frame; E — marmots; F — the black-capped marmot licks coal, freeze frame from video in On the ecology of the Doppelmayer`s Black-capped marmot (Marmota camtschatica doppelmayeri Birula, 1922): Kodar Mountain Ridge, Transbaikalia, Russia
Рис. 2. Черношапочные сурки и их местообитания на хребте КоΑар: A — виΑ на ЦентраΛьный КоΑар и ΑоΛину р. СреΑний Сакукан; B — местообитание сурков поΑ переваΛом; C — местообитание сурков по берегам р. Того; D — местообитание сурков на вершине гребня, каΑр с фотоΛовушки; E — сурки; F — черношапочный сурок обΛизывает пΛасты каменного угΛя, каΑр из виΑеосъемки Fig. 2. Black-capped marmots and their habitats on the Kodar Ridge: A — view of the Central Kodar and the valley of the Middle Sakukan River; B — habitat of marmots under the mountain pass; C — habitat of marmots along the banks of the Togo River; D — marmot habitat at the top of the mountain ridge, camera trap frame; E — marmots; F — the black-capped marmot licks coal, freeze frame from video
Рис. 3. Ливневый сток, прохоΔящий через территорию муниципаΛьного пΛяжа «Маяк» (фото авторов) Fig. 3. Stormwater runoff passing through the territory of "Mayak" municipal beach (photo by the authors) in Morphometric characteristics of Black Sea mussels Mytilus galloprovincialis Lam. as biomarkers of the anthropogenic impact on the Black Sea coastal biocenoses in tourist destinations
Рис. 3. Ливневый сток, прохоΔящий через территорию муниципаΛьного пΛяжа «Маяк» (фото авторов) Fig. 3. Stormwater runoff passing through the territory of "Mayak" municipal beach (photo by the authors)
Figure 10.a. Simulation's display: The characters "\__/" represents the front part of the car that should pass through the string "....==..=.==..==" representing the range of obstacles-Designing a Growing Functional Modules "Artificial Brain"
<p>Once performed the design and configuration, the controller and the local application are<br> executed by pressing the corresponding button. In case of a local simulation, two terminal windows<br> are generated. The first one, localized on the left side of the screen (figure 10.a), displays the<br> behavior of the simulation; the second one, localized on the right side of the screen (figure 10.b),<br> displays the behavior of the controller. Both application run concurrently and their respective<br> contents allow the user to observe and monitor the control session. The last text line of figure 10.b<br> displays the set of commands at cycle 201.</p>
BRAIN Journal-Swarm Robotics with Circular Formation Motion Including Obstacles Avoidance-Figure 25: The fifth obstacle with 100 robots after passing all robots
<p>The swarm movement and obstacle avoidance are shown in Figures 8, 9 and 10 for the first obstacle. Figures 11, 12 and 13 are to present the second obstacle and its avoidance. Figures 14, 15, 16 and 17 are to present the third obstacle and its avoidance. Figures 18, 19, 20 and 21 are to present the fourth obstacle and its avoidance. Figures 22, 23, 24 and 25 present the fifth obstacle and its avoidance. </p>
BRAIN Journal-Swarm Robotics with Circular Formation Motion Including Obstacles Avoidance-Figure 24: The fifth obstacle with 100 robots after passing some robots
<p>The swarm movement and obstacle avoidance are shown in Figures 8, 9 and 10 for the first obstacle. Figures 11, 12 and 13 are to present the second obstacle and its avoidance. Figures 14, 15, 16 and 17 are to present the third obstacle and its avoidance. Figures 18, 19, 20 and 21 are to present the fourth obstacle and its avoidance. Figures 22, 23, 24 and 25 present the fifth obstacle and its avoidance. </p>
BRAIN Journal-Swarm Robotics with Circular Formation Motion Including Obstacles Avoidance-Figure 23: The fifth obstacle with 100 robots before passing any robot
<p>The swarm movement and obstacle avoidance are shown in Figures 8, 9 and 10 for the first obstacle. Figures 11, 12 and 13 are to present the second obstacle and its avoidance. Figures 14, 15, 16 and 17 are to present the third obstacle and its avoidance. Figures 18, 19, 20 and 21 are to present the fourth obstacle and its avoidance. Figures 22, 23, 24 and 25 present the fifth obstacle and its avoidance. </p>
BRAIN Journal-Swarm Robotics with Circular Formation Motion Including Obstacles Avoidance-Figure 22: Fifth Obstacle (obstacle with two entries that each allow the passing of one robot)
<p>The swarm movement and obstacle avoidance are shown in Figures 8, 9 and 10 for the first obstacle. Figures 11, 12 and 13 are to present the second obstacle and its avoidance. Figures 14, 15, 16 and 17 are to present the third obstacle and its avoidance. Figures 18, 19, 20 and 21 are to present the fourth obstacle and its avoidance. Figures 22, 23, 24 and 25 present the fifth obstacle and its avoidance. </p>
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.