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586 results for “March”
Lowpoly Marching Band Hat (Green)
A shako (Marching Band Hat) is a tall, cylindrical military cap, usually with a visor, and sometimes tapered at the top. It is usually adorned with some kind of ornamental plate or badge on the front, metallic or otherwise, and often has a feather, plume, or pompom attached at the top. *1 model (low poly) with textures and materials. Source: Objaverse 1.0 / Sketchfab
A Study to Evaluate the Efficacy and Safety of Maralixibat in Subjects With Progressive Familial Intrahepatic Cholestasis (MARCH-PFIC)
ClinicalTrials.gov study NCT03905330. IPD Sharing: NO. Countries: 17. Publications: 1.
A Pragmatic Trial to Determine the Benefit of Behaviorally Enhanced Exercise Incentives and Corticosteroid Injections in Osteoarthritis of the Knee Marching On for Veterans With Osteoarthritis of the
ClinicalTrials.gov study NCT05035810. IPD Sharing: NO. Countries: 1. Publications: 2.
Vessel traffic observations and associated waterbird surveys, March 2020 – February 2021, Roberts Point and Ogden Point, Victoria, BC, Canada
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Data for continuous and discrete measurements of carbonate parameters in a productive coastal region in the Northwestern Pacific (36°09'13.5''N, 129°24'04.9''E) from January to September in 2019 and from March to December in 2020
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Supplemental material for: Increased large vessel occlusive strokes following the Christchurch 2019 March 15 terror attack
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Data from: "Transcriptome sequencing of the Antarctic Colobanthus quitensis (Kunth) Bartl (Caryophillaceae)" in Genomic Resources Notes Accepted 1 February 2015 – 31 March 2015
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Dead mammal walking: a month-long march by a bison (Bison bison) after an ungulate-vehicle collision
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Introgression dynamics from invasive pigs into wild boar following the March 2011 natural and anthropogenic disasters at Fukushima
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East Africa preterm birth initiative birth register data (March 2016 - October 2016)
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Community gardening in disadvantaged neighborhoods in Phoenix, Arizona, March 2010: Aligning programs with perceptions
This study examined a struggling community gardening program in a low-income minority community in Phoenix, Arizona. The gardening program exists within a larger local food initiative organized by a nonprofit community development organization. The nonprofit's goals for the community gardening program are to provide residents with opportunities for education, extra income and socializing. In partnership with the nonprofit and local residents, we undertook a study to determine the potential for increasing the recruitment and retention of local gardeners in order to sustain a successful community gardening program. We used interviews and participant observation to create an exploratory survey that measured residents' perceptions of benefits and burdens associated with gardening. Results revealed that while respondents had a level of gardening interest and experience in the community, they also lacked awareness about the gardening program. Perceptions of the benefits and burdens of gardening varied among current gardeners, ex-gardeners, and people who had never gardened. The benefits of gardening suggested by many residents differed from the local food initiative goals. If community gardens and local food initiatives are to succeed, organizers should align their programs with the desires of neighborhood residents and educate them about a wide range of potential benefits of gardening to both individuals and neighborhoods.
Wordpress blog export, posts from 2006--7 March, 2020..
<p>An XML archive of the blogs posted at https://www.ch.ic.ac.uk/rzepa/blog during the period 2008-2020.</p>
Metop-B direct readout data and products from SMHI, Norrköping, Sweden, March 10th, 2020, 11 UTC
<p>Metop-B direct readout data and products from SMHI, Norrköping, Sweden, March 10th, 2020, 11:19 UTC</p>
Metop-B direct readout data and products from SMHI, Norrköping, Sweden, March 10th, 2020
<p>Metop-B direct readout data and cloud products received and derived at SMHI, Norrköping, Sweden. Data are from 07:59 to 08:13 UTC March 10th, 2020</p>
St Kitts Mosquito Survey and Model November 2017 to March 2019
<p>Background: High quality mosquito surveys that collect fine resolution local data on<br> mosquito species' abundances provide baseline data to help us understand potential<br> host-pathogen-mosquito relationships, accurately predict disease transmission, and<br> target mosquito control efforts in areas at risk of mosquito borne diseases.</p> <p>Methods: As part of an investigation into arboviral sylvatic cycles on the Caribbean<br> island of St. Kitts, we carried out an island wide mosquito survey from November 2017<br> to March 2019. Using Biogents Sentinel 2 and miniature CDC light traps that were set<br> monthly and run for 48 hour intervals, we collected mosquitoes from a total of 30 sites<br> distributed across the five common land covers on the island (agricultural, mangrove,<br> rainforest, scrub, and urban). We developed a mixed effects negative binomial<br> regression model to predict the effects of land cover, seasonality, and precipitation on<br> observed counts of the most abundant mosquito species we found.</p> <p>Results: We captured 10 of the 14 mosquito species reported on the island, the four<br> most abundant being Aedes taeniorhynchus , Culex quinquefasciatus , Aedes<br> aegpyti , and Deinocerites magnus. Sampling in the mangroves yielded the most<br> mosquitoes, with Ae. taeniorhynchus, Cx. quinquefasciatus, and De. magnus<br> predominating. Aedes aegypti was recovered primarily from urban and agricultural<br> habitats, but also at lower frequency in other land covers. Psorophora pygmaea and<br> Toxorhynchites guadeloupensis were only captured in scrub habitat. Capture rates in<br> rainforests were low. Our models indicated the relative abundance of the four most<br> common species varied seasonally and with land cover. They also suggested that the<br> extent to which monthly average precipitation influenced counts varied according to<br> species.</p> <p>Conclusions: This study demonstrates there is high seasonality in mosquito<br> abundances and that land cover influenced the distribution and abundance of mosquito<br> species on St. Kitts. Further, human-adapted mosquito species (e.g. Ae. aegypti and<br> Cx. quinquefasciatus ) that are known vectors for many human relevant pathogens are<br> the most wide-spread (across land covers) and the least responsive to seasonal<br> variation in precipitation.</p>
Cold and warm temperature advection mask for the Antarctic Circumnavigation Expedition from December 2016 – March 2017.
<p><strong>Dataset abstract</strong></p> <p>This dataset contains a mask for the identification of cold and warm temperature advection along the Antarctic Circumnavigation Expedition (ACE) track based on a simple method using the difference between the sea surface and air temperature. This mask is a combination of measured air temperature and sea surface temperature during ACE.</p> <p><strong>Dataset contents</strong></p> <ul> <li>coldwarm_mask_1h.csv, data file, comma-separated values</li> <li>data_file_header.txt, metadata, text</li> <li>README.txt, metadata, text</li> <li>change_log.txt</li> </ul> <p><strong>Dataset license</strong></p> <p>This cold and warm temperature advection mask dataset from ACE is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0</p> <p><strong>Change log</strong></p> <p>v1.1 - data file updated using new input dataset of measured air and sea surface temperature</p> <ul> <li>data file modified</li> <li>README updated accordingly with details of processing and change_log.txt</li> <li>added change_log.txt file</li> </ul> <p>v1.0 - initial release of dataset</p>
Finland COVID-19 R-value estimate March - August
<p>This dataset contains the time-dependent effective reproduction number R<sub>t</sub> of the COVID-19 epidemic in Finland for the period Feb 27th 2020 - August 14th 2020. The reproduction number was estimated using the daily new coronavirus cases in <a href="https://thl.fi/en/web/thlfi-en/statistics/statistical-databases/open-data/confirmed-corona-cases-in-finland-covid-19-">the infectious diseases registry of Finland</a> with an unscented RTS smoother and the SEIR epidemic model.</p> <p>The SEIR model was defined as<br> <span class="math-tex">\(S(t+1) = S(t) - \frac{R_t(t)}{T_i} I(t) \frac{S(t)}{N} + \omega_{S}\\ E(t+1) = E(t) + \frac{R_t(t)}{T_i} I(t) \frac{S(t)}{N} - \frac{E(t)}{T_e} + \omega_{E}\\ I(t+1) = I(t) + \frac{E(t)}{T_e}-\frac{I(t)}{T_i} + \omega_{I} \\ R_t(t+1) = R_t(t) + \omega_{R_t}\)</span></p> <p>with S, E, and I being the susceptible, exposed, and infective populations, R<sub>t</sub> the time-dependent effective reproduction number, and ωs are normally distributed random numbers with zero mean and small (1e-8) variance except for ω<sub>Rt</sub> whose variance was set to 0.00025. The exposed state duration was set to T<sub>e</sub>=3 days and infective state duration T<sub>i</sub>=5 days.</p> <p>The measurement model (from the SEIR state to observed daily new cases) was defined as<br> <span class="math-tex">\(P_\text{new cases}(k) \propto \mathcal{N}\left[ \alpha \frac{R_t(t-5 days)}{T_i}I(t-5\text{days}) \frac{S(t-5\text{days})}{N}, \sigma_\text{new cases}^2(t) \right]\)</span>, i.e., via a time-delayed gaussian process whose variance was computed by the observed daily new cases with a 7-day rolling mean. Here the detection rate α is set to 10%, but has no significant affect on the computed R-values.</p> <p> </p> <p>The data is a CSV-format file with the columns</p> <ul> <li>date = ISO 8601 date string</li> <li>Rt = maximum a posteriori estimate of R<sub>t</sub></li> <li>Rt_lower50 = lower limit of the 50% credible interval for R<sub>t</sub></li> <li>Rt_upper50 = upper limit of the 50% credible interval for R<sub>t</sub></li> <li>Rt_lower90 = lower limit of the 90% credible interval for R<sub>t</sub></li> <li>Rt_upper90 = upper limit of the 90% credible interval for R<sub>t</sub></li> </ul>
Data from: Onshore industrial wind turbine locations for the United States up to March 2014
Wind energy is a rapidly growing form of renewable energy in the United States. While summary information on the total amounts of installed capacity are available by state, a free, centralized, national, turbine-level, geospatial dataset useful for scientific research, land and resource management, and other uses did not exist. Available in multiple formats and in a web application, these public domain data provide industrial-scale onshore wind turbine locations in the United States up to March 2014, corresponding facility information, and turbine technical specifications. Wind turbine records have been collected and compiled from various public sources, digitized or position verified from aerial imagery, and quality assured and quality controlled. Technical specifications for turbines were assigned based on the wind turbine make and model as described in public literature. In some cases, turbines were not seen in imagery or turbine information did not exist or was difficult to obtain. Uncertainty associated with these is recorded in a confidence rating.
Figure 2. from Bridging the distributional gap of Tylorida striata (Thorell, 1877) and new synonymy (Araneae: Tetragnathidae) - Biodiversity Data Journal 3: e4878 (26 March 2015) https://doi.org/10.3897/BDJ.3.e4878
Figure 2. - Tyloridastriata, live female from India (BNHS Sp. 139).
Ebro Shelf circulation (March-August 2014)
<p>The files publicated here are the ROMS model output used to analyze the circulation at the North Ebro Shelf under NW wind-jet conditions in the article: <em>Ràfols, L., Grifoll, M., Jordà, G., Espino, M., Sairouní, A. and Bravo, M. Shelf circulation induced by an orographic wind jet. Journal of Geophysical Research - Oceans. Manuscript under review.</em></p> <p>The model was run for 6 months (from 1 March until 1 Setember 2014; the numbers of the files correspond to each simulated month) and was forced with atmospheric data from the WRF model implemented at the Catalan Service of Metheorology (http://meteo.cat/). The initial and boundary conditions were generated using data from the IBI-MFC model (http://marine.copernicus.eu).</p>
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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.