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133 results for “TP”
LAGOS - Chlorophyll, TP, and water color summer epilimnetic concentrations and lake and catchment data for inland lakes in WI, MI, NY, and ME – a subset of lake data from LAGOSLimno v.1.040.1
This dataset includes lake total phosphorus (TP), true water color, and chlorophyll a (CHLa) concentrations from summer, epilimnetic water samples and is a subset of the larger LAGOS database (Lake multi-scaled geospatial and temporal database, described in Soranno et al. 2015). LAGOS compiles multiple, individual lake water chemistry datasets into an integrated database. We accessed LAGOSLIMNO version 1.040.0 for lake water chemistry data and LAGOSGEO version 1.02 for lake catchment geographic data. In the LAGOSLIMNO database, lake water chemistry data were collected from individual state agency sampling and volunteer programs designed to monitor lake water quality. Water chemistry analyses follow standard lab methods. In the LAGOSGEO database geographic data were collected from national scale geographic information systems (GIS) data layers. Lake catchments, defined as 'The area of land that drains directly into a lake, and into all upstream-connected, permanent streams to that lake exclusive of any upstream lake watersheds for lakes greater than or equal to 10 ha that are connected via permanent streams', were delineated for lakes greater than or equal to 4 ha. Lake-stream connectivity type was assigned to lakes greater than or equal to 4 ha using GIS tools that use the National Hydrology Dataset (See Soranno et al. 2015 for LAGOS geographic processing steps). A subset of lake and geographic data was created to examine spatial variation in TP and water color relationships with CHLa across broad geographic extents using spatially-varying coefficient models with a Bayesian framework. Lakes were selected that had complete records for summer epilimnetic total TP, true water color, and CHLa. In addition we selected lakes with surface area greater than or equal to 4 ha and less than 10,000 ha to exclude very small and very large lakes from the analyses. The resulting dataset includes 838 lakes in Wisconsin, Michigan, New York, and Maine with 7395 observations. The majo
LAGOS-NE Shallow Lakes: a dataset of lake variables and multi-scaled ecological context variables used to predict and compare trophic status and TP:CHLa relationships between shallow and non-shallow lakes in the Upper Midwest and Northeastern United States.
We conducted a macroscale study of 2,210 shallow lakes (mean depth ≤ 3m or a maximum depth ≤ 5m) in the Upper Midwestern and Northeastern U.S. We asked: What are the patterns and drivers of shallow lake total phosphorus (TP), chlorophyll a (CHLa), and TP–CHLa relationships at the macroscale, how do these differ from those for 4,360 non-shallow lakes, and do results differ by hydrologic connectivity class? To answer this question, we assembled the LAGOS-NE Shallow Lakes dataset described herein, a dataset derived from existing LAGOS-NE, LAGOS-DEPTH, and LAGOS-CLIMATE datasets. Response data variables were the median of available summer (e.g., 15 June to 15 September) values of total phosphorus (TP) and chlorophyll a (CHLa). Predictor variables were assembled at two spatial scales for incorporation into hierarchical models. At the local or lake-specific scale (including the individual lake, its inter-lake watershed [iws] or corresponding HU12 watershed), variables included those representing land use/cover, hydrology, climate, morphometry, and acid deposition. At the regional scale (e.g., HU4 watershed), variables included a smaller set of predictor variables for hydrology and land use/cover. The dataset also includes the unique identifier assigned by LAGOS-NE(lagoslakeid); the latitude and longitude of the study lakes; their maximum and mean depths along with a depth classification of Shallow or non-Shallow; connectivity class (i.e., whether a lake was classified as connected (with inlets and outlets) or unconnected (lacking inlets); and the zone id for the HU4 to which each lake belongs. Along with the database, we provide the R scripts for the hierarchical models predicting TP or CHLa (TPorCHL_predictive_model.R), and the TP—CHLa relationship (TP_CHL_CSI_Model.R) for depth and connectivity subsets of the study lakes.
SBC LTER: Daily averages of modeled significant wave height (Hs) and peak wave period (Tp) in the Santa Barbara Coastal area from the Coastal Data Information Program - Monitoring and Prediction System (CDIP MOP)
From http://cdip.ucsb.edu: The Coastal Data Information Program (CDIP) is a research group at Scripps Institution of Oceanography that monitors coastal waves and nearshore sand levels on regional scales. CDIP maintains a network of optimally-placed, directional wave buoys from San Diego to Eureka. The buoy measurements are used to initialize a high spatial resolution (100m x 100m) linear spectral wave propagation model. The resulting hourly hindcasts and nowcasts of CA coastal wave conditions have a level of accuracy that is not possible with more traditional wind-wave generation models that are initialized with modeled wind fields.
Hourly ERA5-land data (T2m, SD and TP) from 2015-01-01 to 2022-12-31 for Troms and Finnmark (Norway)
<p>This dataset contains hourly values of 2m air temperature, snow depth and total precipitation from the ERA5-land reanalysis from 2015-01-01 to 2022-12-31.</p> <p>The geographical area of interest corresponds to the Troms and Finnmark counties in Norway.</p> <p>Along with 10.5281/zenodo.8142734 this is to be used as input to forecast vegetation browning in Troms and Finnmark using machine learning.</p>
North-Temperate and Boreal annual median TP concentrations and seasonal climate means from 389 lakes, 1998-2017
This dataset accompanies a paper submitted for publication to Limnology and Oceanography Letters, expected publication year 2023, by Isles et al., entitled "Widespread synchrony in phosphorus concentrations in northern lakes linked to winter temperature and summer precipitation." This dataset comprises April-November median TP concentrations for 389 lakes in Fennoscandia, the north-central and northeastern USA, and central to eastern Canada, between 1998 and. 2017. The dataset also includes seasonal means for climate variables divided into winter (DJF), spring (MAM), summer (JJA), and fall (SON) means of air temperature, wind speed, and precipitation. The data all originate with publicly collected datasets, and many data source have data from additional time periods or for additional variables collected over longer time periods available from websites or through contact forms.
SWAT river water, TN & TP loads to Limfjorden under climate change scenarios (Delta change) + baseline SWAT loads 2009-2018. Paper ". Impacts of climate change on water quality, benthic mussels and suspended mussel culture in a shallow, eutrophic estuary by Maar et al. Heliyon,
<p>SWAT river water, TN & TP loads to Limfjorden under climate change scenarios (Delta change) + baseline SWAT loads 2009-2018 </p>
Fig.ç7.Ec hinoderes ohtsukai sp. nov., paratype, female (ZIHU 3980), Nomarski photomicrographs. A, Segments 5 and 6, ventral view; B, segments 8 and 9, ventral view. Abbreviations: dss, droplet-shaped sensory spot; gco2, modi ed glandular cell outlet type II; lvt, lateroventral tubule; si, sieve plate; sp, sternal plate; tp, tergal plate. in A New Brackish-water Species of Echinoderes (Kinorhyncha: Cyclorhagida) from the Seto Inland Sea, Japan
Fig.ç7.Ec hinoderes ohtsukai sp. nov., paratype, female (ZIHU 3980), Nomarski photomicrographs. A, Segments 5 and 6, ventral view; B, segments 8 and 9, ventral view. Abbreviations: dss, droplet-shaped sensory spot; gco2, modi ed glandular cell outlet type II; lvt, lateroventral tubule; si, sieve plate; sp, sternal plate; tp, tergal plate.
Figure 4. A graphic on values of TP, TN, FP, and FN for each different application process.-Cognitive Development Optimization Algorithm Based Support Vector Machines for Determining Diabetes
<p>This study has proposed a diabetes diagnosis system, which is formed via both Support Vector Machines (SVM) and Cognitive Development Optimization Algorithm (CoDOA). In this approach, the training process of the SVM has been supported with the CoDOA and after determining the most optimum sigma (σ) parameter of the Gauss (RBF) kernel function (so the most optimum SVM), a better classification formation has been tried to be achieved. In the context of the study, diabetes data set, which is related to Pima Indians, has been used for evaluating effectiveness of the proposed approach and after six different application processes, it was seen that the approach is well-enough on classification, which means being capable of determining diabetes. There are also some future works regarding the developed CoDOA-SVM based approach. In this context, there will be some more works for improving classification accuracy and also setting different optimization plans on i.e. different parameters of the kernel function. Additionally, it is aimed to evaluate the approach with datasets belonging to different diseases.</p>
Text-fig. 3. Schema of radial section of G. rudolphii (sample 99/04). t – tracheid, r – ray, bp – bordered pit, tp – taxodioid cross-field pit, gp – glyptostroboid cross-field pit. in New Fossil Woods From The Paleogene Of Doupovské Hory And České Středohoří Mts. (Bohemian Massif, Czech Republic)
Text-fig. 3. Schema of radial section of G. rudolphii (sample 99/04). t – tracheid, r – ray, bp – bordered pit, tp – taxodioid cross-field pit, gp – glyptostroboid cross-field pit.
Text-fig. 7. Schema of radial section of T. gypsaceum (sample 98/04). t – tracheid, r – ray, bp – bordered pit, tp – taxodioid pit, cp – cupressoid pit. in New Fossil Woods From The Paleogene Of Doupovské Hory And České Středohoří Mts. (Bohemian Massif, Czech Republic)
Text-fig. 7. Schema of radial section of T. gypsaceum (sample 98/04). t – tracheid, r – ray, bp – bordered pit, tp – taxodioid pit, cp – cupressoid pit.
Data underlying the article 'How nutrient retention and TN:TP ratios depend on ecosystem state in thousands of Chinese lakes'.
<div> <p>Here we share the data underlaying the publication 'How nutrient retention and TN:TP ratios depend on ecosystem<br>state in thousands of Chinese lakes' <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.scitotenv.2024.170690" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.scitotenv.2024.170690</a>.</p> </div> <div>In this study, we used data for analysis, models and R-scripts.</div> <div>The dataset contains data for the historic (2012) situation, and data for an economic-focused scenario and a sustainability-focused scenario for 2050.</div> <div> </div> <div>Raw input data originates from</div> <div>1) Climate scenario variables: HydroLAKES (Messager et al., 2016)</div> <div>2) Historic climate variables: https://doi.org/10.4121/13348004</div> <div>3) Nutrient losses to land for the SSP scenarios: Wang et al. 2020</div> <div> </div> <div>Model input and output data can be found in this database</div> <div>1) Simulated climate variables: folder 1</div> <div>2) Scenario specific parameter values: folder 1</div> <div>3) PCLake+ model output: folder 3</div> <div> </div> <div>R-scripts, as well as the used model (PCLake+), can be found in this database</div> <div>1) R-script to run PCLake+: folder 2 and 6</div> <div>2) R-script to process PCLake+ output data: folder 4</div> <div>3) PCLake+ software: folder 5: GNU LESSER GENERAL PUBLIC LICENSE, Version 3, 29 June 2007</div> <div> </div> <div>Data used for analysis can be found in this database</div> <div>1) ProcessedData.cvs: folder 4</div>
TP-TR Benchmarks from Gen-T: Table Reclamation in Data Lakes
<p>This benchmark suite was created and used in experiments of "<a href="https://arxiv.org/abs/2403.14128" target="_blank" rel="noopener">Gen-T: Table Reclamation in Data Lakes</a>", published in <a href="https://icde2024.github.io/" target="_blank" rel="noopener">ICDE 2024</a>. These three benchmarks were created to evaluate a new problem we propose called <strong>Table Reclamation</strong>. </p>
CB_TP Family of Experiments: RawData
<p>The package provides:</p> <p>1. Raw data of the family of four experiments on confirmation bias and time pressure in software testing.</p> <p>2. R Script for Hotelling's T Square statistical test.</p> <p>3. References to published material for performing meta-analysis and multilevel modelling.</p>
COVID-19 Anticoagulation in Children - Thromboprophlaxis (COVAC-TP) Trial
ClinicalTrials.gov study NCT04354155. IPD Sharing: NO. Countries: 1. Publications: 4.
Study to Compare TP-434 and Ertapenem in Community-acquired Complicated Intra-abdominal Infections
ClinicalTrials.gov study NCT01265784. IPD Sharing: Not stated. Countries: 6. Publications: 1.
Trial to Evaluate the Safety and Efficacy of TP-03 for the Treatment of Demodex Blepharitis
ClinicalTrials.gov study NCT04784091. IPD Sharing: NO. Countries: 1. Publications: 1.
Safety and Efficacy of TP-03 for the Treatment of Demodex Blepharitis
ClinicalTrials.gov study NCT04475432. IPD Sharing: NO. Countries: 1. Publications: 1.
Data for bioinformatics practical course (TP) 1 - Whole Genome Sequencing (WGS)
<p>This data are fastq (.fq) files for the Whole Genome Sequencing (WGS) TP1 (09/12/2020) of the Master Infectiologie-Vaccinologie (University of Tours)</p>
TP-K16 closed-circuit television camera
According to the manufacturer's description, the TP-K 16, as "a utility television camera, is a device converting an optical image into its counterpart electric signal which, when sent through a television monitor, is turned into an optical image again". The design of the TP-K 16 was based on an aluminium alloy frame to which housing components and printed circuit boards with transistors, integrated circuits, and capacitors were mounted. Initially, foreign components were used for its production, which were later substituted by Polish parts. A lens by Carl Zeiss from Jena, imported from the German Democratic Republic, was used in the optical system. Images are converted to electrical signals with the use of an analysing tube made by the Japanese Toshiba company – the vidikon 7262A (later substituted by the Polkolor PWM41A vidicon). Manufacturer: Zakłady Kineskopowe Unitra Polkolor, Warsaw, 1980s Inv. No.: MIM700/VI-83 Model prepared on the basis of photogrammetric measurements Licence: CC BY-NC-SA Source: Objaverse 1.0 / Sketchfab
Lake_TP: annual improved maps to understand the complete evolution of 9 thousand lakes on the Tibetan Plateau in 1991-2023
<p>Lake_TP (shapefile format): this dataset records the annual spatial distributions and water areas of 9789 lakes (over 0.1 km²) that appeared on the Tibetan Plateau from 1991 to 2023.</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)
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.