116 research outputs found

    Evaporative loss from irrigated interrows in a highly advective semi-arid agricultural area

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    Agricultural productivity has increased in the Texas High Plains at the cost of declining water tables, putting at risk the sustainability of the Ogallala Aquifer as a principal source of water for irrigated agriculture. This has led area producers to seek alternative practices that can increase water use efficiency (WUE) through more careful management of water. One potential way of improving WUE is by reducing soil evaporation (E), thus reducing overall evapotranspiration (ET). Before searching for ways to reduce E, it is first important to quantify E and understand the factors that determine its magnitude. The objectives of this study were (1) to quantify E throughout part of the growing season for irrigated cotton in a strongly advective semi-arid region; (2) to study the effects of LAI, days after irrigation, and measurement location within the row on the E/ET fraction; and (3) to study the ability of microlysimeter (ML) measures of E combined with sap flow gage measures of transpiration (T) to accurately estimate ET when compared with weighing lysimeter ET data and to assess the E/T ratio. The research was conducted in an irrigated cotton field at the Conservation & Production Research Laboratory of the USDA-ARS, Bushland, TX. ET was measured by a large weighing lysimeter, and E was measured by 10 microlysimeters that were deployed in two sets of 5 across the interrow. In addition, 10 heat balance sap flow gages were used to determine T. A moderately good agreement was found between the sum E + T and ET (SE = 1 mm or ~10% of ET). It was found that E may account for \u3e50% of ET during early stages of the growing season (LAI \u3c 0.2), significantly decreasing with increase in LAI to values near 20% at peak LAI of three. Measurement location within the north-south interrows had a distinct effect on the diurnal pattern of E, with a shift in time of peak E from west to east, a pattern that was governed by the solar radiation reaching the soil surface. However, total daily E was unaffected by position in the interrow. Under wet soil conditions, wind speed and direction affected soil evaporation. Row orientation interacted with wind direction in this study such that aerodynamic resistance to E usually increased when wind direction was perpendicular to row direction; but this interaction needs further study because it appeared to be lessened under higher wind speeds

    Redesign and initial validation of an instrument to assess the motivational qualities of music in exercise: The Brunel Music Rating Inventory-2

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    In the present study, a measure to assess the motivational qualities of music in exercise was redesigned, extending previous research efforts (Karageorghis et al., 1999). The original measure, the Brunel Music Rating Inventory (BMRI), had shown limitations in its factor structure and its applicability to non-experts in music selection. Redesign of the BMRI used in-depth interviews with eight participants (mean age 31.9 years, s¼8.9 years) to establish the initial item pool, which was examined using a series of confirmatory factor analyses. A single-factor model provided a good fit across three musical selections with different motivational qualities (comparative fit index, CFI: 0.95 – 0.98; standardized root mean residual, SRMR: 0.03 – 0.05). The single-factor model also demonstrated acceptable fit across two independent samples and both sexes using one piece of music (CFI: 0.86 – 1.00; SRMR: 0.04 – 0.07). The BMRI was designed for experts in selecting music for exercise (e.g. dance aerobic instructors), whereas the BMRI-2 can be used both by exercise instructors and participants. The psychometric properties of the BMRI-2 are stronger than those of the BMRI and it is easier to use. The BMRI-2 provides a valid and internally consistent tool by which music can be selected to accompany a bout of exercise or a training session. Furthermore, the BMRI-2 enables researchers to standardize music in experimental protocols involving exercise-related tasks

    Evaluating the two-source energy balance model using local thermal and surface flux observations in a strongly advective irrigated agricultural area

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    Application and validation of many thermal remote sensing-based energy balance models involve the use of local meteorological inputs of incoming solar radiation, wind speed and air temperature as well as accurate land surface temperature (LST), vegetation cover and surface flux measurements. For operational applications at large scales, such local information is not routinely available. In addition, the uncertainty in LST estimates can be several degrees due to sensor calibration issues, atmospheric effects and spatial variations in surface emissivity. Time differencing techniques using multi-temporal thermal remote sensing observations have been developed to reduce errors associated with deriving the surface- air temperature gradient, particularly in complex landscapes. The Dual-Temperature-Difference (DTD) method addresses these issues by utilizing the Two-Source Energy Balance (TSEB) model of Norman et al. (1995) [1], and is a relatively simple scheme requiring meteorological input from standard synoptic weather station networks or mesoscale modeling. A comparison of the TSEB and DTD schemes is performed using LST and flux observations from eddy covariance (EC) flux towers and large weighing lysimeters (LYs) in irrigated cotton fields collected during BEAREX08, a large-scale field experiment conducted in the semi-arid climate of the Texas High Plains as described by Evett et al. (2012) [2]. Model output of the energy fluxes (i.e., net radiation, soil heat flux, sensible and latent heat flux) generated with DTD and TSEB using local and remote meteorological observations are compared with EC and LY observations. The DTD method is found to be significantly more robust in flux estimation compared to the TSEB using the remote meteorological observations. However, discrepancies between model and measured fluxes are also found to be significantly affected by the local inputs of LST and vegetation cover and the representativeness of the remote sensing observations with the local flux measurement footprint

    Deriving Hourly Evapotranspiration Rates with SEBS: A Lysimetric Evaluation

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    Numerous energy balance (EB) algorithms have been developed to use remote sensing data for mapping evapotranspiration (ET) on a regional basis. Adopting any single or combination of these models for an operational ET remote sensing program requires a thorough evaluation. The Surface Energy Balance System (SEBS) was evaluated for its ability to estimate hourly ET rates of summer tall and short crops grown in the Texas High Plains by using 15 Landsat 5 Thematic Mapper scenes acquired during 2006 to 2009. Performance of SEBS was evaluated by comparing estimated hourly ET values with measured ET data from four large weighing lysimeters, each located at the center of a 4.3 ha field in the USDA-ARS Conservation and Production Research Laboratory in Bushland, TX. The performance of SEBS in estimating hourly ET was good for crops under both irrigated and dryland conditions. A locally derived, surface albedo-based soil heat flux (G) model further improved the G estimates. Root mean square error and mean bias error were 0.11 and −0.005 mm h−1, respectively, and the Nash–Sutcliff model efficiency was 0.85 between the measured and calculated hourly ET. Considering the equal or better performance with a minimal amount of ancillary data as compared to with other EB algorithms, SEBS is a promising tool for use in an operational ET remote sensing program in the semiarid Texas High Plains. However, thorough sensitivity and error propagation analyses of input variables to quantify their impact on ET estimations for the major crops in the Texas High Plains under different agroclimatological conditions are needed before adopting the SEBS into operational ET remote sensing programs for irrigation scheduling or other purposes

    Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

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    Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

    Impact of Neuroprotection on Incidence of Alzheimer's Disease

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    Converging evidence suggests that high levels of education and intellectual activity increase the cognitive reserve and reduce the risk of dementia. However, little is known about the impact that different neuroprotective strategies may have on the incidence of Alzheimer's disease. Using a simple mathematical regression model, it is shown here that age-specific counts of basic cognitive units (surrogate of neurons or synapses) in the normal population can be estimated from Alzheimer's incidence rates. Hence, the model can be used to test the effect of neuroprotection on Alzheimer's incidence. It was found that the number of basic cognitive units decreases with age, but levels off in older people. There were no gender differences after correcting for survival. The model shows that even modest neuroprotective effects on basic cognitive units can lead to dramatic reductions in the number of Alzheimer's cases. Most remarkably, a 5% increase in the cognitive reserve would prevent one third of Alzheimer's cases. These results suggest that public health policies aimed at increasing the cognitive reserve in the general population (e.g., implementing higher levels of education) are likely the most effective strategy for preventing Alzheimer's disease

    Determinants of recovery from post-COVID-19 dyspnoea: analysis of UK prospective cohorts of hospitalised COVID-19 patients and community-based controls

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    Background The risk factors for recovery from COVID-19 dyspnoea are poorly understood. We investigated determinants of recovery from dyspnoea in adults with COVID-19 and compared these to determinants of recovery from non-COVID-19 dyspnoea. Methods We used data from two prospective cohort studies: PHOSP-COVID (patients hospitalised between March 2020 and April 2021 with COVID-19) and COVIDENCE UK (community cohort studied over the same time period). PHOSP-COVID data were collected during hospitalisation and at 5-month and 1-year follow-up visits. COVIDENCE UK data were obtained through baseline and monthly online questionnaires. Dyspnoea was measured in both cohorts with the Medical Research Council Dyspnoea Scale. We used multivariable logistic regression to identify determinants associated with a reduction in dyspnoea between 5-month and 1-year follow-up. Findings We included 990 PHOSP-COVID and 3309 COVIDENCE UK participants. We observed higher odds of improvement between 5-month and 1-year follow-up among PHOSP-COVID participants who were younger (odds ratio 1.02 per year, 95% CI 1.01–1.03), male (1.54, 1.16–2.04), neither obese nor severely obese (1.82, 1.06–3.13 and 4.19, 2.14–8.19, respectively), had no pre-existing anxiety or depression (1.56, 1.09–2.22) or cardiovascular disease (1.33, 1.00–1.79), and shorter hospital admission (1.01 per day, 1.00–1.02). Similar associations were found in those recovering from non-COVID-19 dyspnoea, excluding age (and length of hospital admission). Interpretation Factors associated with dyspnoea recovery at 1-year post-discharge among patients hospitalised with COVID-19 were similar to those among community controls without COVID-19. Funding PHOSP-COVID is supported by a grant from the MRC-UK Research and Innovation and the Department of Health and Social Care through the National Institute for Health Research (NIHR) rapid response panel to tackle COVID-19. The views expressed in the publication are those of the author(s) and not necessarily those of the National Health Service (NHS), the NIHR or the Department of Health and Social Care. COVIDENCE UK is supported by the UK Research and Innovation, the National Institute for Health Research, and Barts Charity. The views expressed are those of the authors and not necessarily those of the funders
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