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48 results for “Water age”
Text-fig. 8. Scatter diagram of SDQ vs A/L M. savini and Arvicola from different geographical provenances and ages. in Independent Water Vole (Mimomys Savini, Arvicola: Rodentia, Mammalia) Lineages In Italy And Central Europe
Text-fig. 8. Scatter diagram of SDQ vs A/L M. savini and Arvicola from different geographical provenances and ages.
Conceptualizing relationships among hyporheic exchange, storage, and water age: data represented in published figures
<p>Hyporheic exchange is a key driver of ecosystem processes in streams, yet stream ecologists often fail to leverage detailed conceptual models developed by engineers and hydrologists describing the relationship between water storage, water balance, and water age (time elapsed since a conceptual parcel of water entered the hyporheic zone) in hyporheic zones. In a companion paper (G.C. Poole et al. <em>Hyporheic Hydr</em><em>au</em><em>lic Geometry: Conceptualizing relationships among hyporheic exchange, storage, and water age</em>, published in PLoS ONE; doi:<a href="https://doi.org/10.1371/journal.pone.0262080">10.1371/journal.pone.0262080</a>), we provide visualizations of these relationships in an effort to allow non-hydrologists to grasp four primary concepts along with associated research and management implications: 1) the rate of hyporheic exchange, size of the hyporheic zone, and hyporheic water age are inexorably linked; 2) such linkages can be leveraged to build understanding of hyporheic processes; 3) the age distribution of hyporheic water and hyporheic discharge is heavily skewed toward young water ages -- at any temporal scale of observation (minutes, hours, days, or months) older hyporheic water is rare relative to younger water; 4) the age distribution of water discharged from any hyporheic zone is not the same as the age distribution of water stored within that hyporheic zone. The data set presented here represents the numerical values represented by the figures published in the companion paper.</p>
Fig. 1 in Age, Growth and Reproduction of Coryphaena hippurus (Linnaeus, 1758) in Maltese Waters, Central Mediterranean
Fig. 1: FADs setup (Adapted from Farrugia Randon, 1995).
Fig. 6 in Age, Growth and Reproduction of Coryphaena hippurus (Linnaeus, 1758) in Maltese Waters, Central Mediterranean
Fig. 6: Von Bertalanffy growth curve for males and females
Dataset from: Transport and water age dynamics in soils: a comparative study of spatially-integrated and spatially-explicit models
<p>This dataset contains high-resolution vegetated lysimeter experimental dataset carried out in EPFL, Lausanne, Switzerland in March-August 2016. The lysimeter is 100 cm long with a diameter of 120 cm. During this experiment, a simultaneous spike injection of five different solutes (2,5-DFBA, 2-TFMBA, 3,4-DFBA, 2,6-DFBA, 3-TFMBA) took place on the 3rd of March 2016 at 14:00 in an hour. The solutes' mass recovery at the bottom of lysimeter was observed for these solutes.</p> <p>This dataset contains three files which are described in the following:</p> <ul> <li>"hydrologic_data.dat" contains the hourly fluxes (precipitation, irrigation, evapotranspiration measured from load cells, and the water draining at the bottom of lysimeter ) in mm/hr between the 19th of Feb-the 1st of Sep 2016.</li> <li>"tracer_data.dat" contains the tracer concentration observed at the bottom of lysimeter in mg/L. These samples are collected at variable frequencies with an approximate average of 1.5 samples per day.</li> <li>"additional_data.dat" informs you on dry mass and soil volume in the lysimeter, vegetation type, and volume of injection per solute.</li> </ul> <p> </p>
Conceptualizing relationships among hyporheic exchange, storage, and water age: data represented in published figures
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Stand age rather than soil moisture gradient dominantly regulates the compromise between plant growth and water use of Eucalyptus urophylla in hilly South China
<p>These files contain the clinate data, the morphology characteristics, soil water content and tree normalized transpiration collected in our studied site.</p>
Water, sanitation and the risk of chronic conditions in old age: Results from the Ghana WHO SAGE 2
<p>Water and sanitation have been related to the health of populations, yet, the effects of these factors on the occurrence of chronic conditions (CC) in later life have been least explored. This study examines the association of CC with water and sanitation among older Ghanaians and whether the associations are moderated by gender and residence. Data from the WHO-SAGE Wave 2 comprising of 4735 adults aged ≥ 50 years were analyzed in this study. The primary outcome was CC and the exposures included sources of water, sanitation facilities, and the sharing of sanitation facilities. Generalized logistic regression models estimated the effects of water and sanitation indicators on the occurrence of CC. Overall, 18.8% of the sample reported at least one CC. Compared to men and rural residents, women and urban residents respectively were more likely to report CC (<em>p </em>< 0.001). After full adjustments, logistic regressions showed that the use of unimproved sanitation (OR = 1.732, CI: 1.377–5.418) and sharing of sanitation facilities (OR = 1.624, CI: 1.095–1.320) were associated with higher odds of CC. However, the use of water did not reach significance (<em>p</em> = 0.125). We found a significant interaction effect for type of toilet <strong>×</strong> gender (OR = 3.498, CI: 1.744–16.442), source of water <strong>×</strong> residence (OR = 5.935, CI: 1.320–26.685), and type of toilet <strong>× </strong>residence (OR = 1.998, CI: 1.462–8.642). The use of unimproved sanitation facilities and the sharing of sanitation facilities are associated with the occurrence of CC among older people. Policy and public health interventions targeted at improving the health and well-being of older people should conspicuously include improving access to sanitation services.</p>
Data from: Validity of bioelectrical impedance analysis in predicting total body water and adiposity among Senegalese school-aged children
Introduction: Childhood obesity is currently a serious public health challenge in developing countries. Therefore, an accurate assessment of adiposity is required. The objective of this study was to validate BIA prediction equations for the assessment of total body water and adiposity or percentage of body fat for the first time in Senegalese school-aged children. Methods: One-hundred-fifty-one (151) pupils who were 8-11 years old were randomly selected from four public schools in Dakar. The body composition measured by deuterium dilution method (DDM) was used as the reference method and compared to that predicted by BIA using a multi-frequency analyser. Stepwise backward multiple linear regression was performed to calculate TBW and %BF in a subsample, which were then validated it in the rest of the sample. The Bland and Altman approach was used to assess the agreement between the two methods (bias and limits of agreement). Results: FFM was higher in boys (24.6±6.9 kg) compared to girls (21.2±3.3 kg; P<0.001), and %BF was lower in boys (5.1±4.6 kg) compared to girls (5.3±3.8 kg; P<0.05). Overall, 11.3% of children were obese (%BF ≥25% in boys, and ≥30% in girls) and 4.6% were overweight/obese according to their BMI-z score (>+1). The equations developed were as follows: TBW=0.376(Height²/Z50)-0.470 (sex) +0.076(weight) +0.065(height)-2.28. %BF= -1.10(height²/Z50) +3.14(sex)+1.57(weight)-4.347. These specific equations showed good precision and a low and non-significant mean bias (0.11 kg, P=0.279; and 0.19 kg, P=0.764) for TBW and %BF, respectively. Conclusion: The newly developed equations can be used as an accurate and alternative tool for screening for obesity among African school-aged children in various settings
Measurement Report: Investigation of pH- and particle size-dependent chemical and optical properties of water-soluble organic carbon: implications for its sources and aging processes
<p>The original dataset of the manuscript: "Measurement Report: Investigation of pH- and particle size-dependent chemical and optical properties of water-soluble organic carbon: implications for its sources and aging processes"</p>
Linking water age, nitrate export regime, and nitrate isotope biogeochemistry in a tile-drained agricultural field
<p>This repository contains the SAS model input data and the model results that can be used to reproduce the water age results for the three study tiles presented in Yu et al. Linking water age, nitrate export regime, and nitrate isotope biogeochemistry in a tile-drained agricultural field</p> <p><strong>File 1: SAS_model_input_TileX.csv</strong></p> <p>The input data for the SAS model calibration for the three tiles.</p> <p><strong>File 2: behavioral_parameter_sets_Model#1_TileX.csv</strong></p> <p>The behavioral parameter sets obtained from the calibration of SAS model 1 (i.e., time-invariant kQ).</p> <p><strong>File 3: behavioral_parameter_sets_Model#2_TileX.csv</strong></p> <p>The behavioral parameter sets obtained from the calibration of SAS model 2 (i.e., time-variant kQ).</p> <p><strong>File 4: Cl_simulation_results_Model#1_TileX.csv</strong></p> <p>Simulated chloride concentration based on the optimal parameter set of SAS model 1 (i.e., time-invariant kQ).</p> <p><strong>File 5: Cl_simulation_results_Model#2_TileX.csv </strong></p> <p>Simulated chloride concentration based on the optimal parameter set of SAS model 2 (i.e., time-variant kQ).</p> <p><strong>File 6: median_water_age_Model#1_TileX.csv</strong></p> <p>Median water age of tile discharge based on the optimal parameter set of SAS model 1 (i.e., time-invariant kQ).</p> <p><strong>File 7: median_water_age_Model#2_TileX.csv</strong></p> <p>Median water age of tile discharge based on the optimal parameter set of SAS model 2 (i.e., time-variant kQ).</p> <p><strong>File 8: File_column_names.txt</strong></p> <p> A text file that explains the column names for each file</p>
Linking water age, nitrate export regime, and nitrate isotope biogeochemistry in a tile-drained agricultural field [Dataset]
<p>This repository contains the SAS model input data and the model results that can be used to reproduce the water age results for the three study tiles presented in Yu et al. Linking water age, nitrate export regime, and nitrate isotope biogeochemistry in a tile-drained agricultural field</p> <p><strong>File 1: SAS_model_input_TileX.csv</strong></p> <p>The input data for the SAS model calibration for the three tiles.</p> <p><strong>File 2: behavioral_parameter_sets_Model#1_TileX.csv</strong></p> <p>The behavioral parameter sets obtained from the calibration of SAS model 1 (i.e., time-invariant kQ).</p> <p><strong>File 3: behavioral_parameter_sets_Model#2_TileX.csv</strong></p> <p>The behavioral parameter sets obtained from the calibration of SAS model 2 (i.e., time-variant kQ).</p> <p><strong>File 4: Cl_simulation_results_Model#1_TileX.csv</strong></p> <p>Simulated chloride concentration based on the optimal parameter set of SAS model 1 (i.e., time-invariant kQ).</p> <p><strong>File 5: Cl_simulation_results_Model#2_TileX.csv </strong></p> <p>Simulated chloride concentration based on the optimal parameter set of SAS model 2 (i.e., time-variant kQ).</p> <p><strong>File 6: median_water_age_Model#1_TileX.csv</strong></p> <p>Median water age of tile discharge based on the optimal parameter set of SAS model 1 (i.e., time-invariant kQ).</p> <p><strong>File 7: median_water_age_Model#2_TileX.csv</strong></p> <p>Median water age of tile discharge based on the optimal parameter set of SAS model 2 (i.e., time-variant kQ).</p> <p><strong>File 8: File_column_names.txt</strong></p> <p> A text file that explains the column names for each file</p>
Hydrogen-rich Water for Molecular and Phenotypic Biomarkers of Aging
ClinicalTrials.gov study NCT04430803. IPD Sharing: NO. Countries: 1. Publications: 2.
The Effects of 8 Weeks Post Exercise Hot Water Immersion on Vascular and Cardiometabolic Health in Physically Inactive Middle-aged Adults
ClinicalTrials.gov study NCT05409404. IPD Sharing: NO. Countries: 1. Publications: 0.
The Implementation of Novel 'Heavy' Water Techniques for Determining Modulation of Muscle Protein, DNA and Lipid Synthesis Due to Ageing
ClinicalTrials.gov study NCT02152839. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Data from: Genetic estimates of population age in the water flea, Daphnia magna
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Data from: Validity of bioelectrical impedance analysis in predicting total body water and adiposity among Senegalese school-aged children
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Data from: Like a pig out of water: seaborne spread of domestic pigs in Southern Italy and Sardinia during the Bronze and Iron Ages
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Data from: Offspring provisioning explains clone specific maternal age effects on life history and lifespan in the water flea, Daphnia pulex
Genetic inheritance underpins evolutionary theories of aging, but the role that nongenetic inheritance plays is unclear. Parental age reduces the life span of offspring in a diverse array of taxa but has not been explained from an evolutionary perspective. We quantified the effect that maternal age had on the growth and maturation decisions, life history, rates of senescence, and life span of offspring from three Daphnia pulex clones collected from different populations. We then used those data to test general hypotheses proposed to explain maternal age effects on offspring life span. Three generations of breeding from young or old mothers produced dramatic differences in the life histories of fourth-generation offspring, including significant reductions in life span. The magnitude of the effect differed between clones, which suggests that genetic and nongenetic factors ultimately underpin trait inheritance and shape patterns of aging. Older parents did not transmit a senescent state to their offspring. Instead, offspring from older ancestors had increased early-life reproductive effort, which resulted in an earlier onset of reproductive senescence, and an increased rate of actuarial senescence, which shortened their life span. Our results provide a clear example of the need to consider multiple inheritance mechanisms when studying trait evolution.
Data from: Offspring provisioning explains clone specific maternal age effects on life history and lifespan in the water flea, Daphnia pulex
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