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146 results for “physiological parameters”
Size-Fractionated Chlorophyll a, Primary Productivity, and Photosynthetic Physiological Parameters of Phytoplankton in the Cosmonaut Sea, Southern Ocean, During Summer 2022
This dataset provides vertical distribution profiles of size-fractionated phytoplankton parameters measured in the Cosmonaut Sea, a marginal ice zone in the Southern Ocean, during the austral summer of 2022. Sampling was conducted across multiple stations spanning latitudes from approximately 33°N to 60°N and longitudes from -62°E to -67°E, focusing on surface and subsurface waters up to depths of about 40 meters. The data capture key aspects of phytoplankton physiology and productivity in this dynamic polar environment, influenced by seasonal ice melt and nutrient availability. Parameters include chlorophyll a concentrations (Chl a), primary productivity indicators such as maximum photosynthetic rates (PBm), photosynthetic efficiency (α), saturation irradiance (Ek), and integrated gross primary productivity (IGPPeu), all differentiated by size fractions: net phytoplankton (>20 μm), nano- and pico-phytoplankton (<20 μm), and total community. Additional measurements encompass photosynthetically active radiation (PAR) and mixed layer depths, providing context for light and stratification effects on phytoplankton dynamics. Data were derived from in situ incubations and fluorometric analyses, with values reported for discrete depths at each station to highlight vertical gradients in biomass and photosynthetic performance. This completed dataset is particularly valuable for studies on polar marine ecosystems, carbon cycling, and climate-driven changes in phytoplankton communities, offering insights into how size-structured assemblages respond to environmental gradients in the Southern Ocean. It does not include taxonomic details beyond general phytoplankton groupings but emphasizes physiological metrics for modeling primary production in ice-influenced regions.
Physiological parameters for three farm animal species (cattle, sheep, and swine) as the basis for the development of generic physiologically based kinetic models
<p><strong>IMPORTANT : PLEASE DISREGARD VERSION 1 OF THIS UPLOAD SINCE IT INCLUDES ERRONEOUS INFORMATION.</strong></p> <p>This excel file (DOI: 10.5281/zenodo.3433224) provides physiological parameters and their inter-individual variability (mean, coefficient of variation, sample size) for three farm animal species: cattle (<em>Bos taurus</em>), sheep (<em>Ovis aries</em>), and swine (<em>Sus scrofa domesticus</em>). These physiological parameters were estimated based on the results of extensive literature searches and specific experimental data described in Lautz et al., (2020). This file is associated with R codes (DOI: 10.5281/zenodo.3432796) for generic PBK models, partition coefficient Quantitative Structure Activity Relationship (QSAR) models for each farm animal species and parameterisation of the model.</p> <p>The full data collection and implementation of the models using case studies are described in Lautz et al., 2020 (10.1016/j.toxlet.2019.10.008).</p>
Seasonal trends in leaf level physiological parameters, obtained through gas exchange, reflectance spectroscopy and, functional trait analysis
This data package contains leaf level gas exchange, reflectance spectroscopy, and functional trait measurements collected in six common deciduous tree species across the full 2021 growth season (May -October) at the Black Rock Forest in Cornwall, New York, USA. Branches were sampled predawn using the shotgun method of branch retrieval, and re-cut under water to preserve hydraulic function before transport to the lab. Gas exchange data included in this package are stomatal response curves (irradiance response) which can be used to estimate stomatal slope and intercept. Spectroscopic data are full-range (350 – 2500 nm) leaf reflectance spectra collected on all leaves sampled for gas exchange and traits. Leaf level trait measurements include leaf mass per area (LMA), leaf dry matter content (LDMC), elemental nitrogen and carbon expressed on a per mass basis, and fitted values of Asat, Vcmax, and Rdark scaled to a reference temperature of 25C. Data from these three data tables (stomatal responce, spectra, leaf traits) can be cross referenced using the unique SampleID. Additional data tables include stomatal anatomy (stomatal density, length, and width of the guard cells), hydraulic properties estimated from pressure volume curves (relative water deficit at the turgor loss point), and predawn water potential for all sampled branches. Site level data includes the dGPS location of each sampled tree, its species, and DBH. Each tabular data file (*.csv) is accompanied by a data description (*_dd.csv) which includes relevant metadata (unit, definition, data type). Copies of all raw instrument output (spectroradiometer, LICOR, pressure chamber) and included as .zip files.
Identifying Episodes of Hypovigilance in Intensive Care Units Using Routine Physiological Parameters and Artificial Intelligence: a Derivation Study. Open Code and Dataset
<p>The purpose of this project is to detect hypogilance using the EVEILS database.</p> <p>Database is ICU data from Hôtel-Dieu De Lévis , Québec, Canada. Please cite us if you use either the data or code. </p> <p>This code was written during Raphaëlle Giguère Msc in Computer Science. The goal of her project is to detect hypovigilance using machine learning in the ICU. In this repository, you have the data set before preprocessing:</p> <ul> <li>df_hypovigilance : Contains the hours, date and value of the vigilance level, using either the RASS or Ramsay and already converted using the thresholds shown in the paper.</li> <li>raw_df : Contains the raw values from the gateway for each participant. All of the identifying values have been removed.</li> </ul> <p>At the end of the preprocessing_anonymous script, you should generate a new dataset called "df_final". This dataset is used for the training_model script.</p> <p>The cross validation employs groups of random size meaning the results might differ from time to time but should stay consistent.</p> <p> </p>
Fig. 3. Minimum spanning network for Haemoproteus and Plasmodium mitochondrial DNA cytochrome b in Spatial, temporal, molecular, and intraspecific differences of haemoparasite infection and relevant selected physiological parameters of wild birds in Georgia, USA
Fig. 3. Minimum spanning network for Haemoproteus and Plasmodium mitochondrial DNA cytochrome b haplotypes detected in four species of passerines from Georgia (USA). Circles are drawn proportional to the frequency at which haplotypes were observed. Color represents the host species from which haplotypes originated: red for Northern Cardinal (Cardinalis cardinalis), blue for Indigo Bunting (Passerina cyanea), yellow for White-throated Sparrow (Zonotrichia albicollis), and grey for Tufted Titmouse (Baeolophus bicolor). A single mutation separates nodes unless explicitly indicated by number. Letters within each node refer to Table 8 which indicates the haplotype name, sampling location, and other factors associated with hosts.
Fig. 1 in Spatial, temporal, molecular, and intraspecific differences of haemoparasite infection and relevant selected physiological parameters of wild birds in Georgia, USA
Fig. 1. Map of Georgia (USA) indicating the location of the six sampling sites for identifying haemoparasite infections of birds in the northern and southern regions of the state.
Fig. 2 in Spatial, temporal, molecular, and intraspecific differences of haemoparasite infection and relevant selected physiological parameters of wild birds in Georgia, USA
Fig. 2. Average percent cell volume (PCV) values for five target bird species from Georgia (USA). Different letters indicate significant differences between bird species (p <0.05).
FIGURE 3 in Physiological parameters of Brazilian silverside, Atherinella brasiliensis, embryos exposed to different salinities
FIGURE 3 | Heartbeats of Atherinella brasiliensis embryos between 96hpf and 216hpf raised in salinities from 10 to 35 (p <0.05).
FIGURE 4 in Physiological parameters of Brazilian silverside, Atherinella brasiliensis, embryos exposed to different salinities
FIGURE 4 | Relative expression of cftr in Atherinella brasiliensis larvae exposed to salinities 10–35.
FIGURE 2 in Physiological parameters of Brazilian silverside, Atherinella brasiliensis, embryos exposed to different salinities
FIGURE 2 | Egg chorion of Atherinella brasiliensis seen in scanning electron microscope (SEM). A. The chorion of Brazilian silverside composed of several layers. B. Detail of the filament layers. C. Image of the filament of the chorion. D. Detail of the ring formation at the base of the filament.
FIGURE 1 in Physiological parameters of Brazilian silverside, Atherinella brasiliensis, embryos exposed to different salinities
FIGURE 1 | Number of eggs of Atherinella brasiliensis laid daily in a period of 52 days from adults maintained in salinity 20 ±1.
Biologging reveals repeatable and consistent physiological parameters in free-living turtles.
<p>Associated R code and data sets for analyses related to the "Do turtles have personalities? A new methodology for assessing personality using biologging data" publication. Between-day and between-turtle repeatability can be found in R files 01 and 02. </p>
Data: More than 1000 genotypes are required to derive robust relationships between yield, yield stability and physiological parameters: a computational study on wheat crop
<p>APSIM-Wheat <strong>(</strong><a href="">www.apsim.info</a><strong>)</strong> was used to simulate a data set (for details, see Casadebaig<em> et al.</em>, 2016) with 9100 virtual genotypes (<em>N</em><sub>gen</sub>= 9100) grown under 9000 environments (<em>N</em><sub>env</sub>=9000). In short, virtual genotypes were created by varying the value of 90 independent physiological parameters in a range of ±20% from the reference cultivar <em>Hartog</em>. Environments in the dataset contain historical climate data of 125 years (1889-2013) in four locations (Emerald, Narrabri, Yanco and Merredin) in Australia, in combination with two CO<sub><sup>2</sup></sub> levels (380 and 555 ppm), three nitrogen levels (low: 50%, control: 100% and high fertilization: 100% plus 50 kg‧ha<sup>-1</sup>) and three sowing dates (early, control and late).</p>
Towards substitution of invasive telemetry: An integrated home cage concept for unobtrusive monitoring of objective physiological parameters in rodents - Minimal dataset
<p>Minimal dataset for unobtrusive monitoring of vital parameters in rodents.</p>
Motor performance in violin bowing: Effects of attentional focus on acoustical, physiological and physical parameters of a sound-producing action
<p>Violin bowing is a specialised sound-producing action, which may be affected by psychological performance techniques. In sport, attentional focus impacts motor performance, but limited evidence for this exists in music. We investigated the effects of attentional focus on acoustical, physiological, and physical parameters of violin bowing in experienced and novice violinists. Attentional focus significantly affected spectral centroid, bow contact point consistency, shoulder muscle activity, and novices’ violin sway. Performance was most improved when focusing on tactile sensations through the bow (somatic focus), compared to sound (external focus) or arm movement (internal focus). Implications for motor performance theory and pedagogy are discussed.</p>
Physiological parameters for four fish species (rainbow trout, zebra fish, fathead minnow and three-spined stickleback) as the basis for the development of generic physiologically-based kinetic models
<p>This excel file (DOI: 10.5281/zenodo.1414332) provides physiological parameters and their inter-individual variability (mean, coefficient of variation, sample size) for four fish species: rainbow trout (<em>Onchorhynchus mykiss</em>), zebrafish (<em>Danio rerio</em>), fathead minnow (<em>Pimephales promelas</em>), and three-spined stickleback (<em>Gasterosteus aculeatus</em>). These physiological parameters were estimated based on the results of extensive literature searches and specific experimental data described in Grech et al., (2018). </p> <p>This file is associated with R codes (DOI: 10.5281/zenodo.1414332) for generic PB-K models, partition coefficient Quantitative Structure Activity Relationship (QSAR) models for each fish species and parameterisation of model for males and females of each species separately.</p> <p>The full data collection and implementation of the models using case studies are described in Grech et al., 2018 (<a href="https://doi.org/10.1016/j.scitotenv.2018.09.163">https://doi.org/10.1016/j.scitotenv.2018.09.163</a>)</p>
Data of cerebral and systemic physiological parameters while wearing face masks
<p>This repository contains two data sets and two R codes.</p> <p>- Fischer_et_al_Data_masks_group_average_time_plot.txt: contains the group average data over time of two groups wearing different face masks. The corresponding R code to create plots of the data over time is the file Fischer_et_al_Masks_plot_group_average_time.R</p> <p>- Fischer_et_al_Data_masks_lme_analysis.txt: contains average data for baseline (no mask) and average data of a period where a face mask was worn for each subject. Each subject was measured twice with two different mask types. The corresponding R code to analyze the data for the effect of wearing a mask on the different parameters can be done with the file Fischer_et_al_Masks_LME_analysis.R</p>
Effects of Locally formulated Milk Replacer on Calf Growth Performance; Physiological, Hematological, and Biochemical Parameters
Open the record for dataset details and reuse information.
Fascial Mobilization Along the Vagus Nerve and Its Effects on Acute Physiological Parameters in Obstructive Sleep Apnea
ClinicalTrials.gov study NCT07169058. IPD Sharing: UNDECIDED. Countries: 1. Publications: 2.
The Effects of Listening to Fairy Tales, Listening to Fairy Tales in Their Mothers' Voices, and Watching Cartoons on Pain, Comfort Levels, and Physiological Parameters During Tracheostomy Care in a Pa
ClinicalTrials.gov study NCT07210346. IPD Sharing: NO. Countries: 1. Publications: 1.
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
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