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51 results for “Daylighting”
Spectral dataset of daylights and surface properties of natural objects measured in Japan
<p>This is a spectral dataset of natural objects and daylights collected in Japan. </p> <p>We collected 359 natural objects and measured the reflectance of all objects and the transmittance of 75 leaves. We also measured daylights from dawn till dusk on four different days using a white plate placed (i) under the direct sun and (ii) under the casted shadow (in total 359 measurements). We also separately measured daylights at five different locations (including a sports ground, a space between tall buildings and a forest) with minimum time intervals to reveal the influence of surrounding environments on the spectral composition of daylights reaching the ground (in total 118 measurements).</p> <div> <div> <div> <p>If you use this dataset in your research, please cite the following publication.</p> </div> </div> </div> <div> <div> <div> </div> </div> </div> <div>Morimoto, T., Zhang, C., Fukuda, K., & Uchikawa, K. (2022). Spectral measurement of daylights and surface properties of natural objects in Japan. <em>Optics express</em>, <em>30</em>(3), 3183. https://doi.org/10.1364/OE.441063</div> <p> </p> <p>Dataset contains following Excel spread sheets and csv files:</p> <p><strong>(A) Surface properties of natural objects</strong></p> <p><strong> (A-1) Reflectance_ver1-2.xlsx and .csv</strong></p> <p><strong> (A-2) Transmittance_FrontSideUp_ver1-2.xlsx and .csv</strong></p> <p><strong> (A-2) Transmittance_BackSideUp_ver1-2.xlsx and .csv</strong></p> <p><strong>(B) Daylight measurements</strong></p> <p> <strong>(B-1) Daylight_TimeLapse_v1-2.xlsx and .csv</strong></p> <p> <strong>(B-2) Daylight_DifferentLocations_v1-2.xlsx and .csv</strong></p> <p> </p> <p>Data description</p> <p><strong>(A) Surface properties</strong></p> <p><strong>(A-1) Reflectance_ver1-2.xlsx and .csv</strong></p> <p>This file contains surface spectral reflectance data (380 - 780 nm, 5 nm step) of 359 natural objects, including 200 flowers, 113 leaves, 23 fruits, 6 vegetables, 8 barks, and 9 stones measured by a spectrophotometer (SR-2A, Topcon, Tokyo, Japan). Photos of all samples are included in the .xlsx file.</p> <p>For the analysis presented in the paper, we identified reflectance pairs that have a Pearson’s correlation coefficient across 401 spectral channels of more than 0.999 and removed one of reflectances from each pair. The column 'Used in analysis' indicates whether or not each sample is used for the analysis (TRUE indicates used and FALSE indicate not used).</p> <p>At the time of collection, we noted the scientific names of flowers, leaves and barks from a name board provided by the Tokyo Institute of Technology in which samples are collected. If not available, we used a smartphone software which automatically identifies the scientific name from an input image (<em>PictureThis - Plant Identifier</em> developed by Glority Global Group Ltd.). The names of 2 flowers and 9 stones whose name could not be identified through either method were left blank.</p> <p><strong>(A-2) Transmittance_FrontSideUp_v1-2.xlsx and .csv</strong></p> <p>This file contains surface spectral transmittance data (380 - 780 nm, 5 nm step) for 75 leaves measured by a spectrophotometer (SR-2A, Topcon, Tokyo, Japan). Photos of all samples are included in the .xlsx file.</p> <p>For this data, the transmittance was measured with the front-side of leaves up (the light was transmitted from the back side of the leaves). This is the data presented in the associated article.</p> <p><strong>(A-3) Transmittance_BackSideUp_v1-2.xlsx and .csv</strong></p> <p>Spectral transmittance data of the same leaves presented in (A-2).</p> <p>For this data, the transmittance was measured with the back-side of leaves up (the light was transmitted from the front side of the leaves).</p> <p> </p> <p><strong>(B) Daylight measurements</strong></p> <p><strong>(B-1) Daylight_TimeLapse_ver1-2.xlsx and .csv</strong></p> <p>This file contains daylight spectra from sunrise to sunset on four different days (2013/11/20, 2013/12/24, 2014/07/03 and 2014/10/27) measured by a spectrophotometer (SR-LEDW, Topcon, Tokyo, Japan) with a wavelength range from 380 nm to 780 nm with 1 nm step. We measured the reflected light from the white calibration plate placed either under a direct sunlight or under a casted shadow.</p> <p>The column 'Cloud cover' provides visual estimate of percentage of cloud cover across the sky at the time of each measurement. The column 'Red lamp' indicates whether an aircraft warning lamp at the measurement site was on (circle) or off (blank).</p> <p><strong>(B-2) Daylight_DifferentLocations_ver1-2.xlsx and .csv</strong></p> <p>This file includes daylight spectra measured at five different sites within the Suzukakedai Campus of Tokyo Institute of Technology with minimum time gap on 2014/07/08, using a spectroradiometer (IM-1000, Topcon) from 380 nm to 780 nm with 1 nm step. The instrument was oriented either towards the sun or towards the zenith sky. When the instrument was oriented to the sun, we measured spectra in two ways: (i) one using a black cylinder covering the photodetector and (ii) the other without using a cylinder.</p> <p>The column 'Cylinder' indicates whether the black cylinder was used (circle) or not (cross). The column 'Cloud cover' shows the visual estimate of percentage of cloud cover at the time of each measurement. The column 'Sun hidden in clouds' denotes whether the measurement was taken when the sun was covered by clouds (circle) or not (blank).</p>
Daily maps for global daylight length at 30 arc seconds resolution (2022)
<p>Overview:<br> Daily maps for global daylight length, calculated for the year 2022.</p> <p>Processing steps:<br> For each day within the year 2022, the photoperiod (sunshine hours on flat terrain) are calculated using the SOLPOS algorithm developed by the National Renewable Energy Laboratory (NREL), USA. Resultant values have been converted from hours to minutes.</p> <p>File naming scheme (DDD = day within year) (min is abbreviation for minute):<br> <code>daylight_min_2022_DDD.tif</code></p> <p>Projection + EPSG code:<br> Latitude-Longitude/WGS84 (EPSG: 4326)</p> <p>Spatial extent:<br> north: 90<br> south: -90<br> west: -180<br> east: 180</p> <p>Spatial resolution:<br> 30 arc seconds (approx. 1000 m)</p> <p>Temporal resolution:<br> Daily</p> <p>Pixel values:<br> unit: minutes</p> <p>Software used:<br> GDAL 3.2.2 and GRASS GIS 8.2.0</p> <p>License: CC-BY-SA 4.0</p> <p>Processed by:<br> mundialis GmbH & Co. KG, Germany (<a href="https://www.mundialis.de/">https://www.mundialis.de/</a>)</p> <p>Reference: National Renewable Energy Laboratory (NREL): SOLPOS 2.0 sun position algorithm (https://www.nrel.gov/grid/solar-resource/solpos.html)</p>
SKYSPECTRA: an opensource data package for worldwide spectral daylight
<p>SKYSPECTRA is an open-source data package comprising spectral daylight measurements collected from various sources worldwide. The dataset encompasses measurements from both long-term measurement sites and specific periods or experiments. </p> <h2>Terms of use</h2> <p>For use of the dataset in research cite the paper titled <strong>skyspectra: an opensource data package of worldwide spectral daylight, </strong>presented at the CIE conference 2023, Slovenia, September 18-20 2023. The paper details the schema of the data package and will be publicly available soon.</p> <blockquote> <p><strong>Balakrishnan, P.</strong>, Diakite-Kortlever, A., Dumortier, D., Hernández-Andrés, J., Kenny, P., Maskarenj, M., Pierson, C., Thorseth, A., Xue, P., & Knoop, M. (2023). <em>SKYSPECTRA: An Opensource Data Package of Worldwide Spectral Daylight</em>. In <em>Proceedings of 30th session of CIE Conference, </em>15–23 September 2023. Ljubljana, Slovenia. DOI:10.25039/x50.2023.OP026</p> </blockquote> <div> <div> <div> <h2>Funding </h2> <div> <div> <div> <p>This project is funded by the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Individual Fellowship (grant agreement No. 101032279)</p> <h2>Data availability </h2> <ul> <li>Measurement data is between <code>360 nm to 800 nm</code> wavelength</li> <li>Timestamps with solar elevation angle <code>equal to or above 15 degrees</code></li> <li>Timestamps for two dates in the months of <code>March, June, September, and December</code> (when available)</li> <li>Timestamps with <code>clear and overcast sky conditions</code> (when available)</li> <li>Locations-<code>Berlin, Beijing, Granada, Singapore, Vaulx en Velin</code> (updates of other locations are ongoing) </li> </ul> <h2>Data structure </h2> <p>Measurement datasets include four data frames or tables in .csv format, each representing a distinct type of spectral daylight measurements.</p> <ul> <li><code><strong>spectral_horizontal_irradiance.csv:</strong></code> spectral irradiance measurements of global and diffuse visible radiation recorded on a horizontal plane</li> <li><code><strong>spectral_tilt_irradiance.csv:</strong> </code>spectral irradiance measurements of global and diffuse visible radiation recorded on a tilted plane (not available currently)</li> <li><code><strong>spectral_patch_radiance.csv:</strong></code> spectral radiance measurements of visible radiation from patches of sky</li> <li><strong><code>spectral_direct_irradiance.csv:</code></strong> spectral irradiance measurements of visible radiation directly from the sun</li> </ul> <p>Supplementary datasets include four data frames or tables in .csv format, each representing additional information for each measurement. </p> <ul> <li><code><strong>meta_location.csv:</strong></code> information about the geographical location and immediate environment of where the measurements were taken</li> <li><code><strong>meta_weather.csv:</strong></code> information on sky conditions when the measurements were taken.</li> <li><code><strong>meta_sun_positions.csv:</strong></code> information about sun angles and true solar time when the measurements were taken.</li> <li><strong><code>meta_measurement_parameters.csv:</code></strong> information about specific measurement parameters used for each measurement.</li> </ul> <h2>Data collection</h2> <p>This data package contains a subset of the worldwide spectral daylight measurements collected to explore geographic variations in daylight spectral characteristics, an ongoing effort led by the CIE Technical Committee (TC 3-60). For more information on the data collection process and the templates used refer to the paper <em>skyspectra: an opensource data package of worldwide spectral daylight </em>mentioned above. </p> </div> </div> </div> </div> </div> </div>
Fig. 4 in Population size, distribution and daylight behaviour of Irrawaddy dolphins (Orcaella brevirostris) in Penang Island, Malaysia
Fig. 4. Distribution of sightings based on behavioural observations recorded in west Penang throughout the period of the study.
Fig. 2 in Population size, distribution and daylight behaviour of Irrawaddy dolphins (Orcaella brevirostris) in Penang Island, Malaysia
Fig. 2. Discovery curve showing the accumulation of new individuals identified during the period of study, related to the effort in hours per month when sighting were recorded. LDF = Left dorsal fin; RDF = Right dorsal fin; OBP = regardless of side.
Fig. 3. A in Population size, distribution and daylight behaviour of Irrawaddy dolphins (Orcaella brevirostris) in Penang Island, Malaysia
Fig. 3. A, individuals with the widest range of distribution during the time of the study; B, distribution of the sightings with the tide level (m) recorded for each sighting.
Fig. 5 in Population size, distribution and daylight behaviour of Irrawaddy dolphins (Orcaella brevirostris) in Penang Island, Malaysia
Fig. 5. The pattern of movement tracked when the Irrawaddy dolphins were feeding. The actual track is that of the boat following the dolphins. Some loops have been tagged as an example of what they look like (see inset). The movement was recorded 400 m from Pantai Kerachut while following a group of dolphins outside the survey path, west Penang.
Study of the Effects of Daylighting and Artificial Lighting at 59° Latitude on Mental States, Behaviour and Perception - Dataset
<p>Dataset relative to manuscript "Study of the Effects of Daylighting and Artificial Lighting at 59° Latitude on Mental States, Behaviour and Perception", submitted to Sustainability journal</p>
Dead By Daylight - Meg Thomas (DBD)
Meg Thomas is a girl from a Survival Multiplayer Horror Game called Dead By Daylight. Shes one of the Survivors. Source: Objaverse 1.0 / Sketchfab
Self-reported preferences for Daylight Saving Time meet fundamentals of human physiology: correlations in the 2018 Public Consultation by the European Commission
<p>Dataset for the preprint entitled "Preferences for Daylight Saving Time meet fundamentals of human physiology:<br>correlations in the 2018 Public Consultation by the European Commission"</p> <p> </p> <p>Data by 2018 Member State (28 rows)</p> <p>Variables in the dataset: 19.</p> <p> </p> <p>No headers in the main csv file.</p> <p>The meta csv contains variable descriptions. One row per one variable (column) in the main dataset. </p> <p> </p> <p> </p>
Fig. 1 in Population size, distribution and daylight behaviour of Irrawaddy dolphins (Orcaella brevirostris) in Penang Island, Malaysia
Fig. 1. Penang Island. Shown are the survey trackline west of island and fishing villages.
Daylight-mediated Photodynamic Therapy of Actinic Keratoses:Comparing 0.2%HAL With 16%MAL
ClinicalTrials.gov study NCT02149342. IPD Sharing: YES. Countries: 1. Publications: 1.
Data from: Exploiting mycorrhizas in broad daylight: partial mycoheterotrophy is a common nutritional strategy in meadow orchids.
Partial mycoheterotrophy (PMH) is a nutritional mode in which plants utilize organic matter, i.e. carbon, both from photosynthesis and a fungal source. The latter reverses the direction of plant-to-fungus carbon flow as usually assumed in mycorrhizal mutualisms. Based on significant enrichment in the heavy isotope 13C, a growing number of PMH orchid species have been identified. These PMH orchids are mostly associated with fungi simultaneously forming ectomycorrhizas with forest trees. In contrast, the much more common orchids that associate with rhizoctonia fungi, which are decomposers, have stable isotope profiles most often characterized by high 15N enrichment and high nitrogen concentrations but either an insignificant 13C enrichment or depletion relative to autotrophic plants. Using hydrogen stable isotope abundances recent investigations showed PMH in rhizoctonia-associated orchids growing under light-limited conditions. Hydrogen isotope abundances can be used as substitute for carbon isotope abundances in cases where autotrophic and heterotrophic carbon sources are insufficiently distinctive to indicate PMH. To determine whether rhizoctonia-associated orchids growing in habitats with high irradiance feature PMH as a nutritional mode, we sampled 13 orchid species growing in montane meadows, four forest orchid species and 34 autotrophic reference species. We analysed δ2H, δ13C, δ15N and δ18O and determined nitrogen concentrations. Orchid mycorrhizal fungi were identified by DNA sequencing. As expected, we found high enrichments in 2H, 13C, 15N and nitrogen concentrations in the ectomycorrhiza-associated forest orchids, and the rhizoctonia-associated Neottia cordata from a forest site was identified as PMH. Most orchids inhabiting sunny meadows lacked 13C enrichment or were even significantly depleted in 13C relative to autotrophic references. However, we infer PMH for the majority of these meadow orchids due to both significant 2H and 15N enrichment and high nitrogen concentrations. Pseudorchis albida was the sole autotrophic orchid in this study as it exhibited neither enrichment in any isotope nor a distinctive leaf nitrogen concentration. Synthesis. Our findings demonstrate that partial mycoheterotrophy is a trophic continuum between the extreme endpoints of autotrophy and full mycoheterotrophy, ranging from marginal to pronounced. In rhizoctonia-associated orchids, partial mycoheterotrophy plays a far greater role than previously assumed, even in full light conditions.
Estimating density of mountain hares using distance sampling: a comparison of daylight visual surveys, night-time thermal imaging and camera traps
<p><a name="_Hlk58254629"></a></p> <p><a name="_Hlk58254629">Surveying cryptic, nocturnal animals is logistically challenging. Consequently, density estimates may be imprecise and uncertain. Survey innovations mitigate ecological and observational difficulties contributing to estimation variance. Thus, comparisons of survey techniques are critical to evaluate estimates of abundance. We simultaneously compared three methods for observing mountain hare (<i>Lepus timidus</i>) using Distance sampling to estimate abundance. Daylight visual surveys achieved 41 detections, estimating density at 14.3 hares km<sup>-2</sup> (95%CI 6.3–32.5) resulting in the lowest estimate and widest confidence interval. Night-time thermal imaging achieved 206 detections, estimating density at 12.1 hares km<sup>-2 </sup>(95%CI 7.6–19.4). Thermal imaging captured more observations at furthest distances, and detected larger group sizes. Camera traps achieved 3,705 night-time detections, estimating density at 22.6 hares km<sup>-2 </sup>(95%CI 17.1–29.9). Between the methods, detections were spatially correlated, although the estimates of density varied. Our results suggest that daylight visual surveys tended to underestimate density, failing to reflect nocturnal activity. Thermal imaging captured nocturnal activity, providing a higher detection rate, but required fine weather. Camera traps captured nocturnal activity, and operated 24/7 throughout harsh weather, but needed careful consideration of empirical assumptions. </a>We discuss the merits and limitations of each method with respect to the estimation of population density in the field.</p>
Figure 1 in Phyllostomid bats flying in daylight: a case from the Neotropics
Figure 1. Diurnal foraging and drinking activities in phyllostomid non-haematophagous bats in an Amazon Forest remnant, midwest Brazil. (a) Phyllostomus sp. drinking water in a temporary pond on a dirty road inside a forest remnant; (b) Phyllostomus sp. feeding on termites in flight; (c) Artibeus sp. roosting in tree foliage, in the vicinity of a pond; and (d) Dermanura sp. captured in a mist net. Photographs by the authors.
Daylight-controlled Lighting Adjusted for Geographical Orientation : Effects on Recovery, Energy Consumption and User Satisfaction
ClinicalTrials.gov study NCT05868291. IPD Sharing: Not stated. Countries: 1. Publications: 1.
The Extended CTA for the Successful Screening of Cardioaortic Thrombus in Acute Ischemic Stroke and TIA (DAYLIGHT) Trial
ClinicalTrials.gov study NCT05522244. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Daylight PDT for Actinic Keratoses: a Multicentre Study Comparing Two Photosensitizers (BF-200 ALA Versus MAL)
ClinicalTrials.gov study NCT02464709. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Daylight Photodynamic Therapy for Actinic Keratosis and Skin Field Cancerization
ClinicalTrials.gov study NCT03013647. IPD Sharing: YES. Countries: 1. Publications: 4.
Indoor Daylight Photo Dynamic Therapy for Actinic Keratosis
ClinicalTrials.gov study NCT03805737. IPD Sharing: NO. Countries: 1. Publications: 10.
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