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203 results for “az”
Micrometeorological conditions at the CAP LTER flux tower located in the west Phoenix, AZ, USA neighborhood of Maryvale (2010-2019)
Preface ============ USERS ARE CAUTIONED THAT THE DATA PRESENTED IN THIS DATASET ARE RAW DATA DOWNLOADED DIRECTLY FROM DATA LOGGERS; THE DATA HAVE NOT BEEN PROCESSED OR CHECKED FOR ACCURACY, COMPLETENESS OR QUALITY IN ANY CAPACITY; ANY CALCULATED VALUES DERIVE DIRECTLY FROM A DATA LOGGER. Overview ============ The CAP LTER maintains a 23-m urban eddy flux tower in the west Phoenix, AZ neighborhood of Maryvale (-112.1426 W, +33.4838 N). The tower is instrumented for long-term measurement of the covariance of turbulent eddy and radiative fluxes for the purposes of urban micrometeorological research. Additional micrometerological parameters, such as precipitation, are also measured. Select soil parameters were measured from 2012 through 2016. Eddy covariance data are collected and stored at two temporal resolutions: 10 Hz and 30-minute averages. Data presented here include only 30-minute averages. Owing to large volumes, 10-Hz data are avialable by request to the CAP LTER Information Manager (caplter.data@asu.edu).
Annual summer single-day measurements of the thermal environment with a bio-meteorological sensor under trees, shade structures, and sun-exposed areas in the Rio Salado Park in Tempe, AZ, USA
We have measured the thermal environment/bio-meteorological conditions under trees, shade structures, and at sun-exposed locations in the Rio Salado Park in Tempe, AZ, USA annually since 2018 on a clear sky, hot, sunny day in June/July to track shade performance of newly planted trees over time. Measurements were taken with a mobile bio-meteorological weather station, known as MaRTy (Middel & Krayenhoff, 2019; DOI: 10.1016/j.scitotenv.2019.06.085). Since the measurement campaign began, some of the trees have died, were removed, or their environment has changed due to external events such as a bridge collapse (2020-07-29).
Wikipedia: wikipedia-az (Azerbaijani)
Wikipedia is a multilingual, web-based, free-content encyclopedia project supported by the Wikimedia Foundation and based on a model of openly editable content. EOL harvests articles from wikipedia that are indexed as species or higher taxa.<p></p><p></p>https://az.wikipedia.org/
Individually experienced temperatures: a heat exposure study in five greater Phoenix, AZ area neighborhoods (2014)
Urban environmental health hazards, including exposure to extreme heat, have become increasingly important to understand in light of ongoing climate change and urbanization. Most current knowledge about heat-health risks is based on measurements of outdoor air temperatures. Further, neighborhoods are often considered a homogenous and appropriate unit with which to assess risk and implement intervention strategies. Little is known about temperatures individuals actually experience within neighborhoods and cities, given differential access to cooling resources, complex activity patterns, and heterogeneous thermal and social environments. This dataset contains information collected during a study about individually experienced temperatures (IETs) within and between neighborhoods in Phoenix, Arizona. In September 2014, 80 research participants were recruited from 5 Phoenix-area neighborhoods and equipped with air temperature sensors that recorded IETs as they went about their daily lives. Surveys, activity log phone calls, and exit interviews were used to collect additional information from participants about demographics (age, race, gender), housing status, activities during the week, lifestyle, occupation, orientation toward the neighborhood, uses of indoor and outdoor spaces as well as public and private cooling resources. 86% of participants (69 out of 80) filled out background surveys, 89% of participants (71 out of 80) filled out daily surveys, 31% of participants (25 out of 80) engaged in activity log calls, and 48% of participants (39 out of 80) participated in exit interviews. The research team found that 1) variance in mean IET was relatively equal within each neighborhood and 2) significant differences existed in average mean IETs between neighborhoods. Data collected in this study help explain how intra-city differences in outdoor temperatures manifest themselves into IETs of urban residents. Individual differences are an overlooked determinant of heat expos
Figures 1-2. Machaerocera mexicana. 1 in First records of the grasshopper Machaerocera mexicana Saussure, 1859 (Orthoptera: Acrididae) from the United States and Sonora, Mexico Robert A. Behrstock 10359 S Thicket Place Hereford, AZ 85615 rbehrstock@cox.net
Figures 1-2. Machaerocera mexicana. 1) Male. 30 October, 2008. Cienega Creek Natural Preserve, Pima County, Arizona. Photo by Robert A. Behrstock/Naturewide Images. 2) Female. 7 October, 2010. Rancho la Brisca, Sonora, Mexico. Photo by Thomas R. Van Devender and Ana Lilia Reina.
Figure 3. Female wing. 30 October, 2008 in First records of the grasshopper Machaerocera mexicana Saussure, 1859 (Orthoptera: Acrididae) from the United States and Sonora, Mexico Robert A. Behrstock 10359 S Thicket Place Hereford, AZ 85615 rbehrstock@cox.net
Figure 3. Female wing. 30 October, 2008. Cienega Creek Natural Preserve, Pima County, Arizona. Photo by Robert A. Behrstock/Naturewide Images.
Supporting information for: An assessment of monazite fission-track thermochronology as a proxy for low-magnitude cooling, Catalina-Rincon Metamorphic Core Complex, AZ, U.S.A.
<p><span>The following supporting information contains: The detailed location and age data for the geochronological, isotopic, and geochemical data used in this study, and their associated publications. Detailed thermochronometric data and associated thermal history modelling information for all thermochronology and modelling presented in the study.</span></p>
Madách Imre: Az ember tragédiája, szinoptikus digitális kritikai kiadás
<p>Madách Imre: Az ember tragédiája<br>Informatizált kritikai kiadás<br>Bölcsészettudományi Kutatóközpont Irodalomtudományi Intézet<br>https://doi.org/10.5281/zenodo.11032651<br>Second edition<br>CC BY-NC-ND 4.0 DEED: Attribution-NonCommercial-NoDerivs 4.0 International</p>
Dataset: A2Z Smart Technologies Corp. (AZ) 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.
◂Fig. 14 Scanning electron micrographs (SEM) showing radular ribbon form, middle adhesive zone (az) and rows of dentition (rd) of Dinaride and Iberian individuals (notation denotes aspects on one Dinaride Zospeum and one Iberozospeum ribbon); (a) Z. exiguum (NMBE 553384), Križna jama, Slovenia (45.7452, 14.4673), long and narrow, tapered anterior end (tae), short adhesive zone (az), bottom furled with narrow obtuse or straight base (nosb); (b) Z. pretneri, (NMBE 553290), Gornja Cerovačka pećina, Croatia (44.2701, 15.8855), ibid., with straight base; (c) I. vasconicum, (AJC 1848), Cueva Ermita de Sandaili (42.9994, -2.4381), moderately long and broad, tapered anterior end (tae), prominent adhesive zone (az), straight base (sb); (d) I. zaldivarae, (AJC 1876), Cueva de Las Paúles (43.1282, -2.7362), ibid.; (e) Iberozospeum sp. (RMNH.MOL. 234,109), Cueva de la Foz, long and broad, ibid; (f) Iberozospeum sp., (RMNH.MOL. 234,144), Cueva de Rales, very long and broad, ibid; (g) Iberozospeum sp., (RMNH.MOL. 234,116), Cueva a Sul, long and broad, ibid; (h) Iberozospeum sp., (RMNH.MOL. 234,108), Cueva de Torcona, very long and broad, ibid. — Magnification varies for each perspective, see scale bars; all Figs imaged by M. Ruppel, (ret.) Goethe University Frankfurt am Main in Molecular investigation and description of Iberozospeum n. gen., including the description of one new species (Eupulmonata, Ellobioidea, Carychiidae)
◂Fig. 14 Scanning electron micrographs (SEM) showing radular ribbon form, middle adhesive zone (az) and rows of dentition (rd) of Dinaride and Iberian individuals (notation denotes aspects on one Dinaride Zospeum and one Iberozospeum ribbon); (a) Z. exiguum (NMBE 553384), Križna jama, Slovenia (45.7452, 14.4673), long and narrow, tapered anterior end (tae), short adhesive zone (az), bottom furled with narrow obtuse or straight base (nosb); (b) Z. pretneri, (NMBE 553290), Gornja Cerovačka pećina, Croatia (44.2701, 15.8855), ibid., with straight base; (c) I. vasconicum, (AJC 1848), Cueva Ermita de Sandaili (42.9994, -2.4381), moderately long and broad, tapered anterior end (tae), prominent adhesive zone (az), straight base (sb); (d) I. zaldivarae, (AJC 1876), Cueva de Las Paúles (43.1282, -2.7362), ibid.; (e) Iberozospeum sp. (RMNH.MOL. 234,109), Cueva de la Foz, long and broad, ibid; (f) Iberozospeum sp., (RMNH.MOL. 234,144), Cueva de Rales, very long and broad, ibid; (g) Iberozospeum sp., (RMNH.MOL. 234,116), Cueva a Sul, long and broad, ibid; (h) Iberozospeum sp., (RMNH.MOL. 234,108), Cueva de Torcona, very long and broad, ibid. — Magnification varies for each perspective, see scale bars; all Figs imaged by M. Ruppel, (ret.) Goethe University Frankfurt am Main
Little Colorado River Gorge, Grand Canyon, AZ
View of the Little Colorado River Gorge and Confluence in the Grand Canyon of Arizona. Showing Navajo Nation land and areas of the Grand Canyon National Park. About 3 miles up the Little Colorado River is the "Sipapu" or "Sipapuni", a travertine dome believed by members of the Hopi tribe to be the place of emergence into this world from a previous world that was destroyed by a flood due to the wicked or "two-heartedness" of those in the previous world. The location is sacred to the Hopi, and is currenrly part of the Navajo Nation tribal lands. Not far upstream from the Sipapu is Blue Spring, the source of the blue-green waters of the Little Colorado River, made possible because of disolved limestone calcium carbonate and trace amounts of copper sulfate. Source: Objaverse 1.0 / Sketchfab
Irradiance measurements, satellite images, and clear-sky expectations for Spring 2014 in Tucson, AZ.
<p>This dataset contains the metadata and measurements from a number of irradiance sensors and rooftop solar power systems in addition to clear-sky expectations for those sensors. Irradiance derived from images from the GOES-W satellite are also included. The dataset covers April, May, and June 2014 over the Tucson, AZ, area. The data is in a number of formats including CSV, plain text, HDF5, and netCDF4. </p> <p> </p> <p>See the following for a description of the NREL calibrated GHI sensor:</p> <p>Andreas, A.; Wilcox, S.; (2010). Observed Atmospheric and Solar Information System (OASIS); Tucson, Arizona (Data); NREL Report No. DA-5500-56494. http://dx.doi.org/10.5439/1052226</p> <p> </p> <p>More information about the custom irradiance and rooftop PV sensors can be found in:</p> <p>A. T. Lorenzo, W. F. Holmgren, M. Leuthold, C. K. Kim, A. D. Cronin, and E. A. Betterton, “Short-term PV power forecasts based on a real-time irradiance monitoring network,” in <em>2014 IEEE 40th Photovoltaic Specialist Conference (PVSC)</em>, 2014, pp. 0075–0079.</p>
tRIBS benchmark: SNOTEL point-scale simulation, Happy Jack, AZ, USA.
<p>This repository hosts the setup for executing a point-scale simulation (i.e. single computational element) of the <a href="https://wcc.sc.egov.usda.gov/nwcc/site?sitenum=969">Happy Jack SNOTEL Site</a> in northern Arizona, USA, using the TIN-Based Real-Time Integrated Basin Simulator (<a href="https://tribshms.readthedocs.io/en/latest/">tRIBS</a>). </p> <p>This repository consists of : </p> <p>(1) A data subdirectory, which contains all the necessary data to run tRIBS at Happy Jack and includes bias corrected dataset of SWE for model comparison. </p> <p>2) A doc subdirectory, which contains a jupyter notebook for analyzing and visualizing this specific benchmark case, alongside additional documentation. </p> <p>(3) A src subdirectory that is currently empty but intended to contain source code for the tRIBS executable, which can be obtained <a href="https://github.com/tribshms/tRIBS">here</a>. </p> <p>(4) A bin subdirectory, that is currently empty but intended to store the tRIBS executable, with instructions to build the model <a href="https://tribshms.readthedocs.io/en/latest/man/Model_Execution.html#compilation-instructions">here</a>. </p> <p>(5) A results subdirectory, which contains reference model output for results comparison.</p> <p>Instructions for running this benchmark are available in the README.html file within the repository, which can be opened with your web browser, and can also be found in the latest tRIBS <a href="https://tribshms.readthedocs.io/en/latest/man/Model_Execution.html#run-instructions">documentation</a>. </p> <p>Data from this model was originally collated by Gretchen Hawkins and Josh Cederstrom for their Master’s Thesis work at Arizona State University and associated publications:</p> <p>Hawkins, G.A., Vivoni, E.R., Robles-Morua, A., Mascaro, G., Rivera, E., and Dominguez, F. 2015. A Climate Change Projection for Summer Hydrologic Conditions in a Semiarid Watershed of Central Arizona. Journal of Arid Environments. 118: 9–20. <a href="https://doi.org/10.1016/j.jaridenv.2015.02.022">https://doi.org/10.1016/j.jaridenv.2015.02.022</a> </p> <p>Cederstrom, C.J., Vivoni, E.R., Mascaro, G., and Svoma, B. 2024. Forest Thinning Effects on Watershed Responses under Warming. Water Resources Research. (In Review). </p> <p>Bias corrected SWE data is from:</p> <p>Sun N, Yan H, Wigmosta MS, Leung LR, Skaggs R, Hou Z. 2019. Regional Snow Parameters Estimation for Large-domain Hydrological Applications in the Western United States. Journal of Geophysical Research: Atmospheres. 124 : 5296–5313.</p> <p>Data for this model simulation were obtained from a number of public sources: </p> <p>Meteorological forcing was obtained from the Happy Jack SNOTEL Site (https://www.nrcs.usda.gov/wps/portal/wcc/) and NLDAS-2 (https://ldas.gsfc.nasa.gov/nldas/v2/forcing). Soil properties were obtained from the Soil Survey Geographic Database (https://nrcs.app.box.com/v/soils) with derived parameters informed from the literature and calibration process. Vegetation parameters were obtained from the LANDFIRE REMAP data set (https://landfire.gov).</p> <p> </p> <p><strong>NOTE:</strong> If you encounter a situation where, after downloading and extracting the <code>happy_jack.gz</code> file, the extracted file has no extension, please follow these steps:</p> <ol> <li> <p><strong>Rename the File</strong>: Manually rename the extracted file to <code>happy_jack.zip</code>.</p> </li> <li> <p><strong>Extract Again</strong>: After renaming, unzip the <code>happy_jack.zip</code> file to access the full folder with all the necessary files.</p> </li> </ol> <p>This issue may occur if the file extraction process doesn't automatically add the <code>.zip</code> extension. By renaming the file and unzipping it again, you should be able to access the complete set of files without any issues.</p>
tRIBS benchmark: Basin-scale simulation, Big Spring, AZ, USA.
<p>This repository hosts the setup for executing a basin-scale simulation of the Big Spring watershed that drains into Sycamore Creek in northern Arizona, USA, using the TIN-Based Real-Time Integrated Basin Simulator (<a href="https://tribshms.readthedocs.io/en/latest/">tRIBS</a>). </p> <p>This repository consists of : </p> <p>(1) A data subdirectory, which contains all the necessary data to run the basin-scale simulation of Big Spring, using tRIBS. </p> <p>2) A doc subdirectory, which contains a jupyter notebook for analyzing and visualizing this specific benchmark case, alongside additional documentation. </p> <p>(3) A src subdirectory that is currently empty but intended to contain source code for the tRIBS executable, which can be obtained <a href="https://github.com/tribshms/tRIBS">here</a>. </p> <p>(4) A bin subdirectory, that is currently empty but intended to store the tRIBS executable, with instructions to build the model <a href="https://tribshms.readthedocs.io/en/latest/man/Model_Execution.html#compilation-instructions">here</a>. </p> <p>(5) A results directory, which contains reference model output for results comparison.</p> <p>Instructions for running this benchmark are available in the README.html file within the repository, which can be opened with your web browser, and can also be found in the latest tRIBS <a href="https://tribshms.readthedocs.io/en/latest/man/Model_Execution.html#run-instructions">documentation</a>. </p> <p>Data from this model were obtained from a number of public sources: </p> <p>Soil properties were obtained from ISRIC (https://www.isric.org), with tRIBS input parameters derived from the ROSETTA pedotransfer functions (<a href="https://github.com/usda-ars-ussl/rosetta-soil">https://github.com/usda-ars-ussl/rosetta-soil</a>). Precipitation and vegetation parameters related to tree height and vegetation fraction were provided by Salt River Project. Meteorological forcing was obtained from NLDAS-2 (<a href="https://ldas.gsfc.nasa.gov/nldas/v2/forcing">https://ldas.gsfc.nasa.gov/nldas/v2/forcing</a>),with rainfall data provided from Salt River Project rain gauges.</p> <p><strong>NOTE:</strong> If you encounter a situation where, after downloading and extracting the <code>big_spring.gz</code> file, the extracted file has no extension, please follow these steps:</p> <ol> <li> <p><strong>Rename the File</strong>: Manually rename the extracted file to <code>big_spring.zip</code>.</p> </li> <li> <p><strong>Extract Again</strong>: After renaming, unzip the <code>big_spring.zip</code> file to access the full folder with all the necessary files.</p> </li> </ol> <p>This issue may occur if the file extraction process doesn't automatically add the <code>.zip</code> extension. By renaming the file and unzipping it again, you should be able to access the complete set of files without any issues.</p>
[A Justitia-program és kudarca az Antall-kormány idején: Kronologikus beszámoló eseményekről és személyes emlékekről] Vázlat [Törcsi Péter interjúja (2016. november 15.)] (Budapest: Nemzeti Emlékezet Bizottsága 2016) 1:21
Open the record for dataset details and reuse information.
Az 1851 előtti ráolvasásadatok időbeli és forrástípusonkénti eloszlása
<p>The distribution of pre-1851 charm texts in time and according to types of sources</p> <p> </p>
»Valahol utat tévesztettünk?« Tűnődés az elmúlt évtizedek alakulásáról
<p><strong>TÁJAK KOROK MÚZEUMOK EGYESÜLET PÉCSI KLUBJA</strong></p> <p>KLUBFOGLALKOZÁSOK HELYSZÍNE: LENAU-HÁZ 7621 Pécs, Munkácsy M.u.8. Tel.: 332-515</p> <p>A KLUB PROGRAMJAIT A PÉCSI TÁJAK KOROK MÚZEUMOK KLUB EGYESÜLET SZERVEZI</p> <p>Postacím: CIVIL KÖZÖSSÉGEK HÁZA, 7621 Pécs, Szent István tér 17.</p> <p>Elnök: Tillai Gábor, a Magyar Köztársasági Érdemrend Lovagkeresztjével kitüntetett történész</p> <p>Titkár: Glöckler József</p> <p>Információs pont: Janus Pannonius Múzeum - Pécs, Káptalan u.5.</p> <p>Tel.: 72/514-040 Fax.: 72/514-042 e-mail: <a href="mailto:tillai.gabor@jpm.hu">tillai.gabor@jpm.hu</a></p> <p> </p> <p><strong>TKM KLUBESTEK</strong></p> <p> </p> <p> </p> <p>A Pécsi TKM Klub minden hónap 3. hétfőjén tartja összejöveteleit a Lenau-Házban 16.30 órától, ahol előadásokat hallgathat meg a klubtagság.</p> <p> </p> <p><strong>KLUBFOGLALKOZÁS:</strong></p> <p> </p> <p><strong>Szeptember 19. „</strong><em>VALAHOL UTAT TÉVESZTETTÜNK?”</em></p> <p><strong>Hétfő 17.00 </strong>Tűnődés az elmúlt évtizedek alakulásáról</p> <p> Vendég: <strong>VARGA CSABA professor emeritus (MTA Jogtudományi </strong></p> <p><strong> Intézet – Pázmány Péter Katolikus Egyetem)</strong></p>
(Anya)nyelvhasználat interetnikus közegben. Hogyan használjük magabiztosan az anyanyelvünket
<p>Az animáció röviden elmagyarázza mi a nyelvi alávetettség, és hogy miért esnek ebbe a csapdába a kisebbségi beszélők. Emellett a kis videó több nyelvi önérvényesítő technikát is bemutat.</p> <p>This animation is intended to be used as part of the Trainers' Toolkit of the LISTEN project (https://listen-europe.eu/trainers-toolkit/.</p> <p>*Full credits*</p> <p>Concept art: Réka Kassay, Sapientia University, Romania</p> <p>Animation: Vicsi Judith, Orosz Bence, Zoom Animation Studio, Romania</p> <p>Graphics: Éva Páncél, Zoom Animation Studio, Romania</p> <p>Narration text: Erika Keszeg, Bálványos Institute Romania, and Tibor Toró, Sapientia University, Romania</p> <p>Translation: Erika Keszeg</p> <p>Voice: Szabolcs Szilágyi</p>
Santa Rita Experimental Range site, station Pima County, AZ (FIPS 4019), study of county area in units of squareKilometers on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Santa Rita Experimental Range (SRE) contains county area measurements in squareKilometers units and were aggregated to a yearly timescale.
Santa Rita Experimental Range site, station Pima County, AZ (FIPS 4019), study of number of farms in units of number on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Santa Rita Experimental Range (SRE) contains number of farms measurements in number units and were aggregated to a yearly timescale.
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.