Search results for "measured [angular distribution]"
showing 10 items of 17 documents
Current Predictive Resting Metabolic Rate Equations Are Not Sufficient to Determine Proper Resting Energy Expenditure in Olympic Young Adult National…
2021
Predictive resting metabolic rate (RMR) equations are widely used to determine athletes’ resting energy expenditure (REE). However, it remains unclear whether these predictive RMR equations accurately predict REE in the athletic populations. The purpose of the study was to compare 12 prediction equations (Harris-Benedict, Mifflin, Schofield, Cunningham, Owen, Liu’s, De Lorenzo) with measured RMR in Turkish national team athletes and sedentary controls. A total of 97 participants, 49 athletes (24 females, 25 males), and 48 sedentary (28 females, 20 males), were recruited from Turkey National Olympic Teams at the Ministry of Youth and Sports. RMR was measured using a Fitmate GS (Cosmed, Italy…
Within-Day Energy Deficiency and Metabolic Perturbation in Male Endurance Athletes.
2018
Endurance athletes are at increased risk of relative energy deficiency associated with metabolic perturbation and impaired health. We aimed to estimate and compare within-day energy balance in male athletes with suppressed and normal resting metabolic rate (RMR) and explore whether within-day energy deficiency is associated with endocrine markers of energy deficiency. A total of 31 male cyclists, triathletes, and long-distance runners recruited from regional competitive sports clubs were included. The protocol comprised measurements of RMR by ventilated hood and energy intake and energy expenditure to predict RMRratio (measured RMR/predicted RMR), energy availability, 24-hr energy balance a…
Women’s empowerment and child mortality: the case of Bangladesh
2018
Experimental conditions for respiration and growth studies of F0 and F1 larval and juvenile European seabass Dicentrarchus labrax
2022
Water parameters in the 2 years before spawning of F0 (08.02.2016-06.03.2018) and during larval and juvenile phase of F1: Larval period until 17.05.2018 (48 dph, 900 dd) and 01.06.2018 (63 dph, ~900 dd) for warm and cold life condition respectively, for the juveniles until 28.09.2018 (180 dph, ~4000 dd) and 12.02.2019 (319 dph, ~5100 dd) for warm and cold conditioned fish respectively. Means ± s.e. over all replicate tanks per condition. Temperature (Temp.), pH (free scale), salinity, oxygen and total alkalinity (TA) were measured weekly in F1 and monthly in F0; sea water (SW) measurements were conducted in 2017 and 2018. Water parameters during larval and early juvenile phase of F0: Larval…
Global distributions of diazotrophs abundance and biomass - Depth integrated values computed from a collection of source datasets - Contribution to t…
2013
The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedente…
Global distributions of diazotrophs nitrogen fixation rates - Depth integrated values computed from a collection of source datasets - Contribution to…
2013
The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedente…
Global distributions of diazotrophs Gamma-A nifH genes abundance - Depth integrated values computed from a collection of source datasets - Contributi…
2013
The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedente…
From pioneering to implementing automated blood pressure measurement in clinical practice: Thomas Pickeringʼs legacy
2010
Thomas G. Pickering spent most of his scientific career in carrying out research on clinical hypertension and blood pressure (BP) measurement. In our review of Pickering's seminal work, we first focused on white-coat hypertension and masked hypertension, two terms that he had introduced. Next, we highlighted the early publications of Pickering on diurnal BP variability and on the clinical application of self-measured BP. Pickering's work inspired many investigators worldwide and constituted a solid basis for further research. Pickering's original ideas led to algorithms for risk stratification involving white-coat hypertension and masked hypertension, diurnal BP variability, and self-measur…
Hypernuclear spectroscopy of products from Li-6 projectiles on a carbon target at 2 A GeV
2013
WOS: 000322848900009
Fine structure in the beta-delayed proton decay of 33Ar
1996
9 pages, 2 figures, 2 tables.-- PACS nrs.: 21.60.Cs; 23.40.−s; 27.30.+t; 29.30.Ep.