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128 results for “shadows”
Orbital dynamic admittance and earth shadow
<p>The effects of orbital dynamics on a velocity distribution from a point source --- for example, a fragmentation --- may be studied by Housen's method. This technique permits the computation of a spatial density due to the velocity distribution as the sum over all routes between the source point and any point in space of the velocity density divided by the absolute value of the Jacobian determinant of the propagation map. The determination of all routes constitute finding all Lambert (orbital two point boundary value problem) solutions for the two points over a given elapsed time. In order to understand the observed density structures better, the dynamic admittance is introduced. It is the sum of the reciprocal absolute Jacobian determinants spanning all possible routes and is independent of the initial velocity distribution. The bands, pinch point and other features seen in the dynamic admittance plots are analyzed. The effects of the earth in reducing the number of routes, thereby casting a dynamic shadow, are demonstrated.</p>
Linked collectors and determiners for: From the shadows of the past: Moricand senior and junior, two 19 th century naturalists from Geneva, with their newly described taxa and molluscan types.
Natural history specimen data linked to collectors and determiners held within, "From the shadows of the past: Moricand senior and junior, two 19 th century naturalists from Geneva, with their newly described taxa and molluscan types". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/59e37f50-05dc-43e2-9954-f33875cbb0c6">https://bionomia.net/dataset/59e37f50-05dc-43e2-9954-f33875cbb0c6</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/59e37f50-05dc-43e2-9954-f33875cbb0c6">https://gbif.org/dataset/59e37f50-05dc-43e2-9954-f33875cbb0c6</a>. Formatted as a Frictionless Data package.
Sentinel-2 KappaZeta Cloud and Cloud Shadow Masks
<p><strong>General information</strong></p> <p>The dataset consists of 4403 labelled subscenes from 155 Sentinel-2 (S2) Level-1C (L1C) products distributed over the Northern European terrestrial area. Each S2 product was oversampled at 10 m resolution for 512 x 512 pixels subscenes. 6 L1C S2 products were labelled fully. Among other 149 S2 products the most challenging ~10 subscenes per product were selected for labelling. In total the dataset represents 4403 labelled Sentinel-2 subscenes, where each sub-tile is 512 x 512 pixels at 10 m resolution. The dataset consists of around 30 S2 products per month from April to August and 3 S2 products per month for September and October. Each selected L1C S2 product represents different clouds, such as cumulus, stratus, or cirrus, which are spread over various geographical locations in Northern Europe.</p> <p>The classification pixel-wise map consists of the following categories:</p> <ul> <li>0 – MISSING: missing or invalid pixels;</li> <li>1 – CLEAR: pixels without clouds or cloud shadows;</li> <li>2 – CLOUD SHADOW: pixels with cloud shadows;</li> <li>3 – SEMI TRANSPARENT CLOUD: pixels with thin clouds through which the land is visible; include cirrus clouds that are on the high cloud level (5-15km).</li> <li>4 – CLOUD: pixels with cloud; include stratus and cumulus clouds that are on the low cloud level (from 0-0.2km to 2km).</li> <li>5 – UNDEFINED: pixels that the labeler is not sure which class they belong to.</li> </ul> <p>The dataset was labelled using Computer Vision Annotation Tool (<a href="https://github.com/openvinotoolkit/cvat">CVAT</a>) and <a href="https://segments.ai/">Segments.ai</a>. With the possibility of integrating active learning process in Segments.ai, the labelling was performed semi-automatically.</p> <p>The dataset limitations must be considered: the data is covering only terrestrial region and does not include water areas; the dataset is not presented in winter conditions; the dataset represent summer conditions, therefore September and October contain only test products used for validation. Current subscenes do not have georeferencing, however, we are working towards including them in next version.</p> <p>More details about the dataset structure can be found in README. </p> <p><strong>Contributions and Acknowledgements</strong></p> <p>The data were annotated by Fariha Harun and Olga Wold. The data verification and Software Development was performed by Indrek Sünter, Heido Trofimov, Anton Kostiukhin, Marharyta Domnich, Mihkel Järveoja, Olga Wold. Methodology was developed by Kaupo Voormansik, Indrek Sünter, Marharyta Domnich.<br> We would like to thank Segments.ai annotation tool for instant and an individual customer support. We are grateful to European Space Agency for reviews and suggestions. We would like to extend our thanks to Prof. Gholamreza Anbarjafari for the feedback and directions.<br> The project was funded by<strong><em> European Space Agency</em></strong>, Contract No. 4000132124/20/I-DT.</p>
Shadow-wall lithography of ballistic superconductor-semiconductor quantum devices
<p>This repository contains data sets that support the conclusions and figures in the manuscript "Shadow-wall lithography of ballistic superconductor-semiconductor quantum devices".</p> <p>The Jupyter notebook "Manuscript figures.ipynb" contains all the necessary scripts to generate the figures. The measurement data is contained in the "Data" folder.</p>
Data from: Genetic diversity in a long-lived mammal is explained by the past's demographic shadow and current connectivity
<p>Within-species genetic diversity is crucial for the persistence and integrity of populations and ecosystems. Conservation actions require an understanding of factors influencing genetic diversity, especially in the context of global change. Both population size and connectivity are factors greatly influencing genetic diversity; the relative importance of these factors can however change through time. Hence, quantifying the degree to which population size or genetic connectivity are shaping genetic diversity, and at which ecological time scale (past or present), is challenging, yet essential for the development of efficient conservation strategies. In this study, we estimated the genetic diversity of 42 colonies of <i>Rhinolophus hipposideros,</i> a long-lived mammal vulnerable to global change, sampling locations spanning its continental northern range. We present an integrative approach that disentangles and quantifies the contribution of different connectivity measures in addition to contemporary colony size and historic bottlenecks in shaping genetic diversity. In our study, the best model explained 64% of the variation in genetic diversity. It included historic bottlenecks, contemporary colony sizes, connectivity and a negative interaction between the latter two. Contemporary connectivity explained most genetic diversity when considering a 65 km radius around the focal colonies, emphasizing the large geographic scale at which the positive impact of connectivity on genetic diversity is most profound and hence the minimum scale at which conservation should be planned. Our results highlight that the relative importance of the two main factors shaping genetic diversity varies through time, emphasizing the relevance of disentangling them to ensure appropriate conservation strategies.</p>
NSLS-II TES virtual beamline example for Sirepo SRW & Shadow interfaces
<p>Exported as a zip-archive from <a href="https://sirepo.com">sirepo.com</a>.</p> <p>From the following original sources:</p> <ul> <li><a href="https://www.sirepo.com/srw#/beamline/ReJMAvC6">https://www.sirepo.com/srw#/beamline/ReJMAvC6</a></li> <li><a href="https://www.sirepo.com/shadow#/beamline/TqRavgOQ">https://www.sirepo.com/shadow#/beamline/TqRavgOQ</a></li> </ul>
Data from: Genetic diversity in a long-lived mammal is explained by the past’s demographic shadow and current connectivity
Open the record for dataset details and reuse information.
Leak-resilient enzyme-free nucleic acid dynamical systems through shadow cancellation
Open the record for dataset details and reuse information.
Shadow Detection/Texture Segmentation Computer Vision Dataset
<p>A simple computer vision dataset for shadow detection and texture analysis, specifically created to help test shadow detection algorithms (and texture segmentation algorithms) for mobile robots - that is, shadow detection with an <em>active (moving) camera</em>.</p> <p>The dataset is focused around texture analysis, so each image sequence contains shadows moving in front of a number of various textured surfaces. The dataset contains four main subfolders: "active", "artificial", "kondo", and "static". The "static" folder contains ground-truthed image sequences of textured surfaces with shadows moving over them, and the "active" folder contains ground-truthed image sequences of a camera travelling over textured surfaces. The "artificial" folder contains a computer-generated 3D scene with computer-generated ground truth, but note that texture is absent from all images within. Finally, the "kondo" folder contains a series of extremely challenging images captured from a webcam mounted to a Kondo bipedal robot. This final dataset is challenging because it contains a high level of noise, flicker and interference from electrical lighting, and the poor lighting conditions make for complex shadows with large penumbrae.</p>
Dataset for Popov, Strokov, and Surdyaev 2021: Black hole shadows against an optically thick, geometrically thin disk
<p>The datasets contain images of an optically thick, geometrically thin accretion disk distorted by the presence of a Kerr black hole (i.e., black hole shadows). The images are in a compressed text format (.gz) as well as in a graphic format. The training dataset comprises 2,301 images for various values of the disk's outer radius, the spin and sense of rotation of the black hole, and for different viewing angles (w.r.t. the equatorial plane where the disk resides). The test set contains 89 images with parameters which were randomly sampled from the same ranges as in the training set. For details, see the works associated with this record.</p>
Shadow Surface Meshes
<p>This repository contains triangle meshes of the shadow-recieving surfaces of 13 ancient sundials; three of them are from Greece and 10 from Italy. The meshes are in correspondence.</p> <p>The dataset was used in the <strong>Math+ project EF2-3 "Spline Models for Shape Trajectory Analysis."</strong></p> <p>It is used in the paper "Intrinsic shape analysis in archaeology: A case study on ancient sundials" by Hanik et al. in a study that applied nonlinear shape analysis methods to archaeological data.</p>
Shadow-ArUco Dataset
<p>This dataset is composed of photos obtained by attaching multiple ArUco markers to the walls in the corner of a darkened room, projecting a video containing moving shadows and lighting patterns over the corner, and then recording the resulting scene from 6 different points of view, for a total of 8652 frames with a resolution of 800 x 600. For each image, the ground-truth labels of the markers are provided, tagged with a method based on the classic ArUco technique, and manually adding the positions and IDs of undetected markers.<br><br></p>
Moon South Pole Permanent Shadowed Regions
<p>File containing PSRs at the lunar south pole</p>
Data from: Size and Causes of the Shadow Economy in Iran: An Analysis with the MIMIC Approach
<p>All the data needed (in raw form) in order to replicate the results of the paper “Size and Causes of the Shadow Economy in Iran: An Analysis with the MIMIC Approach” is available here. Information on how to use this data to produce the results is provided within the paper and its appendices. All the data gathered here are taken from public sources, namely the “World Bank” (World Development Indicators data), “Central Bank of the Islamic Republic of Iran”, “Plan and Budget Organization of the Islamic Republic of Iran” and “Statistical Center of Iran”.</p>
Supporting code, tables and data for: Megafrugivores as fading shadows of the past: Extant frugivores and the abiotic environment as the most important determinants of the distribution of palms in Madagascar
<p>The extinction of all Madagascar's megafrugivores ca. 1000 years ago, may have left its signature on the current distribution of vertebrate-dispersed plants across the island, due to the loss of effective seed dispersal. In this study, we dissect the roles of extinct and extant frugivore distributions, abiotic variables, human impact and spatial predictors on the compositional turnover, or beta-diversity, of palm (Arecaceae) species and their fruit sizes across 40 assemblages on Madagascar. Variation partitioning showed that palm beta-diversity is mostly shaped by the distribution of extant frugivores (8 lemur, 3 bird, 2 rodent and 1 bat species) and the abiotic environment (e.g., forest cover, slope and temperature), and to a lesser extent by the distribution of extinct frugivores (5 giant lemur and 3 elephant bird<i> </i>species)<i>. </i>However, the contribution of these variables differed between dry western assemblages and wet eastern assemblages, with a more prominent role, albeit still small, of extinct megafrugivores in the west. These results suggest that palm distributions in the dry west of Madagascar, where megafrugivores were probably most abundant in the past, still show signatures of past interactions. With a fourth-corner analysis we observed that the distribution of palm species with relatively large fruits and seeds was negatively associated with home range of extant mammalian frugivores and frugivore richness of both past and extant communities, and positively associated with the hand-wing index (HWI) – a proxy for dispersal ability - of extant bird communities. This suggests that palm species with relatively large fruits tend to occur in places with fewer, small-ranged mammalian frugivores, which may indicate dysfunctional seed dispersal, although a few wide-ranging bird species may compensate this loss by dispersing the seeds of small-to medium-sized palm fruits. Our results shed new light on anachronisms in Madagascar, and how defaunation and past interactions may underlie current plant distributions.</p>
Shadowing and multiple rings in the protoplanetary disk of HD 139614
<p>This is a basic reproduction package for the paper 'Shadowing and multiple rings in the protoplanetary disk of HD 139614' by Muro-Arena et al (2022). It aims to provide the most important data products to check and reproduce the main results of the paper, listing all software used and data archives containing the public data used.</p> <p> </p> <p>It is available at - arXiv: https://ui.adsabs.harvard.edu/abs/2020A%26A...635A.121M/abstract and has been published by Astronomy and Astrophysics at https://www.aanda.org/articles/aa/full_html/2020/03/aa36509-19/aa36509-19.html</p>
Molecular Dynamics Simulation of Solar Wind Implantation in the Permanently Shadowed Regions on the Lunar Surface
<p>Supporting data for "Molecular Dynamics Simulation of Solar Wind Implantation in the Permanently Shadowed Regions on the Lunar Surface"</p>
Shadows and Gigabytes: A Taxonomy of Fan Edits of Hollywood Films
<p>The democratisation of filmmaking via digital media has been changing the nature of film adaptation, through the recent rise of fan edits of major studio films. With free access video sites like YouTube and Vimeo making anyone's professional level edits of studio film releases freely accessible by millions, the line defining the original director's intent becomes muddled. With a coming age of these fan edits being many people's introduction to classic film characters and series, there is a new level of discourse about the fidelity of the films as they had been originally released in theatres. Though many directors have released their own differing cuts of their same films, notably Ridley Scott, Oliver Stone and George Lucas, it is new territory to have critics' cuts, or as many different cuts of a film as fan communities desire to propagate. The film experience is now more malleable to suit the unique tastes of the audience participants as the fan edit grows steadily as its own genre.</p> <p>Whilst forging a method of approach to establishing an overview of this new fan cultural practice, I have developed a taxonomy by which these varied films can be aggregated, examining what is gained or lost for traditional film presentation. The traditional concept of the auteur theory is rendered obsolete in such context, and many iconic movie elements are being transformed for entirely new audiences; how does this rapidly growing trend affect the future of film spectatorship, and what does it reveal about the nature of adaptation, particularly when the original source stemmed from another medium, and how are the aspects of copyright affected? This Practice as Research thesis defines an organised taxonomy to contribute to an understanding of fan creativity, in light of how movie fan edits are shared and disseminated across fandom.</p>
Effects of Body Shadowing in LoRa Localization systems
<p>The purpose of this database of measurements with and without body obstruction is to provide the scientific community with a tool to evaluate different localisation methods in these scenarios. The measurements were performed in an outdoor environment with a semi-dense and dense vegetation, located at the Universidad del Norte in Colombia. The data presents the RSSI values transmitted by a LoRa WisTrio RAK5205 node and received by four Risinghf LoRaWAN gateways composing the network, operating at 915 MHz. Additionally, the node and gateways locations in geographic coordinates are provided. Measurements were made by placing the node on a tripod for each test position (scenario without human shadowing - NHS) and then placing the node on a person's chest (scenario with human shadowing - HS) for the same positions.</p> <p>The database is composed of three groups:<br> - Raw data:<br> RSSI_NHS_raw.csv: Containing 50 packets per position in No Human Shadowing scenario.<br> RSSI_HS_raw.csv: Containing 50 packets per position with reception at 3 or 4 gateways, in Human Shadowing scenario.<br> - Cleaned data: Only for the 16 node positions where the messages were received at the four gateways, after outlier removal (See https://www.mathworks.com/matlabcentral/fileexchange/62954-mean_removing_outliers_tukey-x-rmzerovals?s_tid=mwa_osa_a).<br> NHS_16ps.csv: Containing 40 packets per position in No Human Shadowing scenario.<br> HS4GWs_16ps.csv: Containing 40 packets per position in Human Shadowing scenario.</p> <p>Additionally, the geographical coordinates for the gateways are provided in the PosGWs.csv file.</p> <p>The methodology for data collection and the first results will be published in a research journal.</p>
Shadow Spaces for Water Stress Adaptation: Supplemental Irrigation Application in Rainfed Fig Production
<p>Data Sources is a SPSS file. Common descriptive statistics and inferential statistics are used.</p>
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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)
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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.
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