Default Equation Research Articles

Vapor and Liquid (p-ρ-T-x) Measurements of Binary Refrigerant Blends Containing R-134a, R-1234yf, and R-1234ze(E).

The pressure-density-temperature-composition (p-ρ-T-x) data of binary refrigerant mixtures containing R-134a (1,1,1,2-tetrafluoroethane), R-1234yf (2,3,3,3-tetrafluoropropene), and R-1234ze(E) (trans-1,3,3,3-tetrafluoropropene) were measured in both the vapor and liquid phases using a two-sinker, magnetic-suspension densimeter. The specific samples in this study comprised two compositions of approximately (0.3/0.7) and (0.7/0.3) mole fraction for each of the following three binary refrigerant blends: R-1234yf + R-134a, R-134a + R-1234ze(E), and R-1234yf + R-1234ze(E). Single-phase vapor densities were measured over a temperature range of (253 to 293) K and pressures from approximately (0.04 to 0.5) MPa. Single-phase liquid and supercritical densities were measured over a temperature range of (230 to 400) K and pressures up to 21 MPa; for refrigerant blends containing R-1234yf, the maximum pressure was limited to approximately 12 MPa. Overall relative combined, expanded (k = 2) uncertainties in density ranged from 0.043% to 0.418%, with an average uncertainty of approximately 0.06%. Here, we present measurement results, along with comparisons to available literature data and to default equations of state and mixture models included in REFPROP.

Vapor and Liquid (p-ρ-T-x) Measurements of Binary Refrigerant Blends Containing R-32, R-152a, R-227ea, R-1234yf, and R-1234ze(E).

The pressure-density-temperature-composition ( ) data of binary refrigerant mixtures containing R-32 (difluoromethane), R-152a (1,1-difluoroethane), R-227ea (1,1,1,2,3,3,3-heptafluoropropane), R-1234yf (2,3,3,3-tetrafluoropropene), and R-1234ze(E) (trans-1,3,3,3-tetrafluoropropene) were measured in both the vapor and liquid phases using a two-sinker, magnetic-suspension densimeter. The specific samples in this study comprised two compositions of approximately (0.3/0.7) and (0.7/0.3) mole fraction for each of the following four binary refrigerant blends: R-32 + R-1234yf, R-32 + R-1234ze(E), R-1234yf + R-152a, and R-1234ze(E) + R-227ea. Single-phase vapor densities were measured over a temperature range of approximately (253 to 293) K and pressures from (0.05 to 0.98) MPa. Single-phase liquid and supercritical densities were measured over a temperature range of approximately (230 to 400) K and pressures up to 22 MPa; for refrigerant blends containing R-1234yf the maximum pressure was limited to 14 MPa. Overall relative combined, expanded (k = 2) uncertainties in density ranged from 0.025% to 0.191%, with an average uncertainty of approximately 0.05%. Here, we present measurement results, along with comparisons to available literature data and to default equations of state and mixture models included in REFPROP.

Implementation of the EPIC Earthquake Early Warning System in the Bursa Province (Türkiye) and Its Surroundings

Earthquake early warning systems aim to reduce the potential danger by providing a warning in the seconds before strong ground shaking occurs. In this study, we implemented EPIC, an early warning algorithm for Bursa province and its surroundings, which is a seismically active region. We replayed 104 earthquakes of M ≥ 3.5, which occurred in and around the study area between 2012 and 2021. We derived period and amplitude-based magnitude-scaling relationships using peak displacement amplitude (Pd) and predominant period (Tpmax) parameters of the first 4 s of P-wave arrivals. We investigated the performance of magnitude-scaling relationships through testing with real-time data. We observed an improvement when comparing the magnitude estimates made with the newly developed equations with the default equations used for California. We have also found that magnitude estimation with Pd gives better results than Tpmax for estimating the accurate final magnitude. We aim to adapt the EPIC early warning system, implemented for Bursa province and its surroundings, specifically for each region of Türkiye where the earthquake risk is high.

Calibration and validation of soil water reflectometers

AbstractIn this study, we tested soil water reflectometers represented by the CS65x series soil water reflectometers. The objectives were to (a) quantify the sensing volume of the CS65x sensors, (b) evaluate common univariate and multivariate calibration models, and (c) assess the implications of using uncalibrated sensors. The support volume was determined by analyzing the response of the bulk dielectric permittivity to a changing amount of surrounding media in the radial and axial directions of the sensor. Calibration models were tested using a dataset of ∼300 soil samples spanning nine soil textural classes. A time series of rootzone soil water storage recorded in two contrasting soils and two intensive (n ∼300) spatial surveys of near‐surface soil moisture were used to quantify the implications of using uncalibrated sensors. The electromagnetic signal of CS655 was concentrated within a ∼3.5‐cm radius around the center of the sensor rods. Univariate and multivariate calibration equations reduced the mean absolute error (MAE) in soil moisture observations by ∼40% compared with factory default equations. Uncalibrated sensors did not change the pattern of soil moisture temporal dynamics but resulted in a strong bias in soil water storage in a silty clay loam soil and altered the soil moisture spatial patterns obtained in moderate to wet field conditions in a silty clay soil. The CS655 sensor with the Kargas and Soulis calibration equation (MAE = 0.026 cm3 cm−3) appears to be an acceptable candidate for deployment in soil moisture monitoring networks seeking to avoid site‐specific sensor calibrations.

Analysis of Scour Depth Around Bridge Piers With Round Nose Shape by HEC-RAS 5.0.7 Software

Local scour of bridge piers is the main reason for the failure of a hydraulic structure like abutment, bridge piers, etc. Local scours is a complex phenomenon that depends on the discharge, depth of flow, shapes of the pier and distribution of sediment particle. The problems of local scours occurred in Krueng Ineng river, Nagan Raya Regency will cause a structural collapse which has the impact of decreasing the stability of the bridge structure. In this study, the software of Hydrologic Engineering Center River Analysis System (HEC-RAS) 5.0.7 is used to evaluate local scour around the bridge pier which employs the Colorado State University method as a default equation. Flow conditions were simulated using HEC-RAS flow modeling software estimated for 100-year flood. The Results of the analysis with used the peak discharge (Qp100) that occurs in the Krueng Seunagan watershed is 1513m3/sec, pier width of Round Nose shape is 4m, and average grain size analysis D50 and D95 is 0.91mm and 4.35mm, show a maximum scour depth obtained is 5.04m. The results of this study will be a reference for the local government to planning appropriate handling for minimalizing local scours in the study area.

Balanced nutrient requirements for maize in the Northern Nigerian Savanna: Parameterization and validation of QUEFTS model

Establishing balanced nutrient requirements for maize (Zea mays L.) in the Northern Nigerian Savanna is paramount to develop site-specific fertilizer recommendations to increase maize yield, profits of farmers and avoid negative environmental impacts of fertilizer use. The model QUEFTS (QUantitative Evaluation of Fertility of Tropical Soils) was used to estimate balanced nitrogen (N), phosphorus (P) and potassium (K) requirements for maize production in the Northern Nigerian Savanna. Data from on-farm nutrient omission trials conducted in 2015 and 2016 rainy seasons in two agro-ecological zones in the Northern Nigerian Savanna (i.e. Northern Guinea Savanna “NGS” and Sudan Savanna “SS”) were used to parameterize and validate the QUEFTS model. The relations between indigenous soil N, P, and K supply and soil properties were not well described with the QUEFTS default equations and consequently new and better fitting equations were derived. The parameters of maximum accumulation (a) and dilution (d) in kg grain per kg nutrient for the QUEFTS model obtained were respectively 35 and 79 for N, 200 and 527 for P and 25 and 117 for K in the NGS zone; 32 and 79 for N, 164 and 528 for P and 24 and 136 for K in the SS zone; and 35 and 79 for N, 199 and 528 for P and 24 and 124 for K when the data of the two zones were combined. There was a close agreement between observed and parameterized QUEFTS predicted yields in each of the agro-ecological zone (R2 = 0.69 for the NGS and 0.75 for the SS). Although with a slight reduction in the prediction power, a good fit between the observed and model predicted grain yield was also detected when the data for the two agro-ecological zones were combined (R2 = 0.67). Therefore, across the two agro-ecological zones, the model predicted a linear relationship between grain yield and above-ground nutrient uptake until yield reached about 50 to 60% of the yield potential. When the yield target reached 60% of the potential yield (i.e. 6.0 t ha−1), the model showed above-ground balanced nutrient uptake of 20.7, 3.4 and 27.1 kg N, P, and K, respectively, per one tonne of maize grain. These results suggest an average NPK ratio in the plant dry matter of about 6.1:1:7.9. We concluded that the QUEFTS model can be widely used for balanced nutrient requirement estimations and development of site-specific fertilizer recommendations for maize intensification in the Northern Nigerian Savanna.

Field Calibration of PR2 Capacitance Probe in Pullman Clay‐Loam Soil of Southern High Plains

Core Ideas A noncalibrated PR2 capacitance probe showed significant deviations from actual soil water content. Calibration improved the accuracy and precision of soil moisture monitoring with the PR2. Calibration was necessary for using the PR2 probe for research‐quality soil water measurements. Multi‐depth capacitance sensors are popular to monitor soil water content for scheduling irrigation thanks to their ease of operation and maintenance. The PR2/6 Profile Probe (Delta‐T Devices) measures soil moisture by using either the manufacturer's built‐in equation or a user‐calibrated equation if the soil is high in clay or organic matter. The objectives were to evaluate the performance of the PR2/6 Profile Probe in a perennial grassland and to develop a site‐specific equation to correct probe measurements in Pullman (fine, mixed, superactive, thermic Torrertic Paleustolls) clay loam soils. Permittivity recorded by the profile probe was regressed on the gravimetrically measured soil volumetric water content (VWC). Parameters were optimized to obtain least RMSEs. The default equation provided by the manufacturer estimated VWC with average RMSE and r2 values of 0.053 m3 m–3 and 0.71, respectively. New calibration coefficients were effective in explaining 91% of the variability in soil VWC measurements and reducing RMSE to 0.017 m3 m–3. The results indicate that site‐specific calibration of the capacitance probe is necessary to attain research‐quality accuracy and precision when applied to grasslands in Pullman clay loam and associated clay loam soils.

Helmholtz free energy equation of state for propane and R134a binary mixture

In this work, a Helmholtz free energy equation of state for R290 + R134a based on the multi-fluid approximations model was developed to describe the thermophysical properties of the binary mixture. The present equation shows more competitive than the default equation in REFPROP 9.1 (Lemmon et al., 2013). It covers a temperature range of (252–400) K and pressures up to 6.1 MPa. The estimated standard uncertainties of the present equation are 0.70% and 0.90% for the bubble point and dew point pressures, 0.26 K and 0.29 K for the bubble point and dew point temperatures, 0.13% and 0.60% for the saturated liquid and vapor densities, respectively. The main purpose is to provide a useful model for R290 + R134a, and thus to promote its better applications for the design and optimization of the refrigeration systems.

Microcredit Loan Repayment Default among Small Scale Enterprises: A Double Hurdle Approach

Previous studies that analysed loan defaults have imposed the restrictive assumption that the factors which influence the probability of loan default and the rate of default are the same and with the same direction effects. This study introduces a two-stage approach by applying the double hurdle model to analyse probability of loan default and the magnitude of the default as a way of relaxing this restrictive assumption. Using the model, this study is able to isolate the determinants of default rate from the determinants of the probability of default. The control function approach is used to test and control for potential endogeneity of loan amount and profit in the probability of default equation. The model is applied to primary data from a survey of 200 small scale entrepreneurs in the Upper West Region of Ghana. Results show that enterprise size, interest rate, loan duration, level of profit and loan amount are the simultaneous determinants of probability and rate of default. The study recommends that the National Board for Small Scale Industries should intensify training programmes aimed at enhancing the managerial and technical capabilities of entrepreneurs to ensure healthy and productive management to promote enterprise growth and increase profit margins and hence reduce defaults.Keywords: Repayment, Default, Microfinance, Small Scale Enterprises, Endogeneity, Double Hurdle

Tropical Peatland Burn Depth and Combustion Heterogeneity Assessed Using UAV Photogrammetry and Airborne LiDAR

We provide the first assessment of tropical peatland depth of burn (DoB) using structure from motion (SfM) photogrammetry, applied to imagery collected using a low-cost, low-altitude unmanned aerial vehicle (UAV) system operated over a 5.2 ha tropical peatland in Jambi Province on Sumatra, Indonesia. Tropical peat soils are the result of thousands of years of dead biomass accumulation, and when burned are globally significant net sources of carbon emissions. The El Niño year of 2015 saw huge areas of Indonesia affected by tropical peatland fires, more so than any year since 1997. However, the Depth of Burn (DoB) of these 2015 fires has not been assessed, and indeed has only previously been assessed in few tropical peatland burns in Kalimantan. Therefore, DoB remains arguably the largest uncertainty when undertaking fire emissions calculations in these tropical peatland environments. We apply a SfM photogrammetric methodology to map this DoB metric, and also investigate combustion heterogeneity using orthomosaic photography collected using the UAV system. We supplement this information with pre-burn airborne light detection and ranging (LiDAR) data, reducing uncertainty by estimating pre-burn soil height more accurately than from interpolation of adjacent unburned areas alone. Our pre-and post-fire Digital Terrain Models (DTMs) show accuracies of 0.04 and 0.05 m (root-mean-square error, RMSE) respectively, compared to ground-based global navigation satellite system (GNSS) surveys. Our final DoB map of a 5.2 ha degraded peat swamp forest area neighboring Berbak National Park (Sumatra, Indonesia) shows burn depths extending from close to zero to over 1 m, with a mean (±1σ) DoB of 0.23 ± 0.19 m. This lies well within the range found by the few other studies available (on Kalimantan; none are available on Sumatra). Our combustion heterogeneity analysis suggests the deepest burns, which extend to ~1.3 m, occur around tree roots. We use these DoB data within the Intergovernmental Panel on Climate Change (IPCC) default equation for fire emissions to estimate mean carbon emissions as 134 ± 29 t·C∙ha−1 for this peatland fire, which is in an area that had not had a recorded fire previously. This is amongst the highest per unit area fuel consumption anywhere in the world for landscape fires. Our approach provides significant uncertainty reductions in such emissions calculations via the reduction in DoB uncertainty, and by using the UAV SfM approach this is accomplished at a fraction of the cost of airborne LiDAR—albeit over limited sized areas at present. Deploying this approach at locations across Indonesia, sampling a variety of fire-affected landscapes, would provide new and important DoB statistics for producing optimized carbon and greenhouse gas (GHG) emissions estimates from peatland fires.

Field Performance of Five Soil Moisture Instruments in Heavy Clay Soils

The increased use of soil moisture retrieval from satellites has heightened the need for improved accuracy of point measurements that are used to validate remotely sensed soil moisture products. A wide range of devices can be installed for operational monitoring of soil moisture; however, many of these devices have not been tested in situ in soils with a very high reactive clay content. The objective of this study was to evaluate the accuracy in field performance of five soil moisture sensors: the EnviroSCAN probe, the Diviner 2000 (both from Sentek Technologies), the Hydra Probe soil sensor (Stevens Water Monitoring Systems), the ThetaProbe ML2x (Delta-T Devices), and the ECH2O EC-5 (Decagon Devices) in soils that had about 71% clay content. The instruments' default calibrations were tested against observed soil moisture from core samples using the thermogravimetric method. New calibration equations were developed for each device, which were evaluated using an independent data set. The ThetaProbe had the lowest root mean square error (RMSE) of 0.025 m3 m−3 and mean bias error (MBE) of 0.002 m3 m−3 in the precalibration analysis. Although the Hydra Probe showed the highest precalibration errors, the instrument made the greatest improvement in post-calibration analysis, with an RMSE of 0.129 m3 m−3 using the default equation reduced to 0.014 m3 m−3 using in situ calibration, and the 0.110 m3 m−3 MBE was reduced to 0 after applying in situ calibration.

BADGER v1.0: A Fortran equation of state library

The BADGER equation of state library was developed to enable inertial confinement fusion plasma codes to more accurately model plasmas in the high-density, low-temperature regime. The code had the capability to calculate 1- and 2-T plasmas using the Thomas–Fermi model and an individual electron accounting model. Ion equation of state data can be calculated using an ideal gas model or via a quotidian equation of state with scaled binding energies. Electron equation of state data can be calculated via the ideal gas model or with an adaptation of the screened hydrogenic model with ℓ-splitting. The ionization and equation of state calculations can be done in local thermodynamic equilibrium or in a non-LTE mode using a variant of the Busquet equivalent temperature method. The code was written as a stand-alone Fortran library for ease of implementation by external codes. EOS results for aluminum are presented that show good agreement with the SESAME library and ionization calculations show good agreement with the FLYCHK code. Program summaryProgram title: BADGERLIB v1.0Catalogue identifier: AEND_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEND_v1_0.htmlProgram obtainable from: CPC Program Library, Queen’s University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 41480No. of bytes in distributed program, including test data, etc.: 2904451Distribution format: tar.gzProgramming language: Fortran 90.Computer: 32- or 64-bit PC, or Mac.Operating system: Windows, Linux, MacOS X.RAM: 249.496 kB plus 195.630 kB per isotope record in memoryClassification: 19.1, 19.7.Nature of problem:Equation of State (EOS) calculations are necessary for the accurate simulation of high energy density plasmas. Historically, most EOS codes used in these simulations have relied on an ideal gas model. This model is inadequate for low-temperature, high-density plasma conditions; the gaseous and liquid phases; and the solid phase. The BADGER code was developed to give more realistic EOS data in these regimes.Solution method:BADGER has multiple, user-selectable models to treat the ions, average-atom ionization state and electrons. Ion models are ideal gas and quotidian equation of state (QEOS), ionization models are Thomas–Fermi and individual accounting method (IEM) formulation of the screened hydrogenic model (SHM) with l-splitting, electron ionization models are ideal gas and a Helmholtz free energy minimization method derived from the SHM. The default equation of state and ionization models are appropriate for plasmas in local thermodynamic equilibrium (LTE). The code can calculate non-LTE equation of state (EOS) and ionization data using a simplified form of the Busquet equivalent-temperature method.Restrictions:Physical data are only provided for elements Z=1 to Z=86. Multiple solid phases are not currently supported. Liquid, gas and plasma phases are combined into a generalized “fluid” phase.Unusual features:BADGER divorces the calculation of average-atom ionization from the electron equation of state model, allowing the user to select ionization and electron EOS models that are most appropriate to the simulation. The included ion ideal gas model uses ground-state nuclear spin data to differentiate between isotopes of a given element.Running time:Example provided only takes a few seconds to run.

Calibration equations for two capacitance water content probes

Calibration equations for two capacitance water content probesThis paper presents the calibration equations of two capacitance probes for monitoring the soil water content in a lysimeter field. Capacitance probes provide readings at desired depths and time intervals. The calibration equations are derived by regression analysis between measurements of scaled frequency and volumetric soil water content. The calibration equations are compared with the manufacturer default equations to estimate the irrigation water depth. The accuracy of capacitance probes in monitoring soil water content increased by using the site-specific calibration equations rather than the manufacturer default equation.

Field Calibrations of Soil Moisture Sensors in a Forested Watershed

Spatially variable soil properties influence the performance of soil water content monitoring sensors. The objectives of this research were to: (i) study the spatial variability of bulk density (ρb), total porosity (θt), clay content (CC), electrical conductivity (EC), and pH in the upper Mākaha Valley watershed soils; (ii) explore the effect of variations in ρb and θt on soil water content dynamics, and (iii) establish field calibration equations for EC-20 (Decagon Devices, Inc), ML2x (Delta-T-Devices), and SM200 (Delta-T-Devices) sensors to mitigate the effect of soil spatial variability on their performance. The studied soil properties except pH varied significantly (P < 0.05) across the soil water content monitoring depths (20 and 80 cm) and six locations. There was a linear positive and a linear inverse correlation between the soil water content at sampling and ρb, and between the soil water content at sampling and θt, respectively. Values of laboratory measured actual θt correlated (r = 0.75) with those estimated from the relationship θt = 1 − ρb/ρs, where ρs is the particle density. Variations in the studied soil properties affected the performance of the default equations of the three tested sensors; they showed substantial under-estimations of the actual water content. The individual and the watershed-scale field calibrations were more accurate than their corresponding default calibrations. In conclusion, the sensors used in this study need site-specific calibrations in order to mitigate the effects of varying properties of the highly weathered tropical soils.

Bioelectrical Impedance Analysis Can Be a Useful Screen for Excess Adiposity in Spinal Muscular Atrophy

Accurate, noninvasive measures of body composition are needed for management of patients with spinal muscular atrophy. Fat mass index (fat mass/height(2) in kg/m(2)) was measured in 16 subjects with spinal muscular atrophy using 5 bioelectrical impedance analysis equations and compared with a reference method, dual-energy x-ray absorptiometry. The machine default equation, validated by Cordain, was the primary analysis. Fat mass index calculated by impedance measures differed by between -2.5 kg/m(2) and 1.7 kg/m(2) from the reference mean (8.3 ± 5.0 kg/m(2)). The Cordain equation provided the smallest difference (-0.4 ± 2.0 kg/m(2)), with correlation coefficient of 0.92. The Cordain equation showed high sensitivity (85.7%) and specificity (100%) for prediction of ''at risk for overweight'' (fat mass index > 85th percentile for age and gender). Although insufficiently accurate for use as a research tool, bioelectrical impedance can have application as a well-tolerated, noninvasive, easily used screening tool for excess adiposity in patients with spinal muscular atrophy.

Laboratory versus Field Calibration of Capacitance Probes

Capacitance probes (CP) based on responses to electromagnetic properties in soil are widely used for monitoring soil volumetric water content (θv), but proper calibration is necessary to obtain reliable results. The objectives of this study were to: (i) compare errors in evaluating θv when using soil‐specific equations as opposed to the manufacturer's default equation; (ii) compare the CP calibration equations obtained in the laboratory and in the field; and (iii) evaluate the accuracy of CP under field conditions using soil‐specific equations as opposed to the manufacturer's default equation. Laboratory and field calibrations were conducted by fitting statistical relationships between readings from CP and θv measured from soil cores. The accuracies of the obtained calibration equations were evaluated under field conditions during two irrigation cycles. In both calibration studies, the manufacturer's default equation consistently overcalculated θv (RMSE &gt; 0.044 m3 m−3), whereas custom CP calibration equations provided accurate θv determinations (RMSE &lt; 0.028 m3 m−3). Even when θv was overestimated, the manufacturer's default equation was able to reproduce θv dynamics during irrigation. Therefore, if users are interested in relative differences in θv, they may use the manufacturer's default equation. If absolute values are needed, however, soil‐specific calibration is required. The accuracy of CP in monitoring θv under field conditions was slightly better using the laboratory calibration equation (RMSE = 0.019 m3 m−3) rather than the field calibration equation (RMSE = 0.023 m3 m−3). The use of a laboratory calibration is recommended given that it is easily reproducible, facilitates work planning, and minimizes uncertainties.

The conversion of permittivity as measured by a PR2 capacitance probe into soil moisture values for Des Moines lobe soils in Iowa

Measurement of soil moisture is essential for irrigation scheduling and capacitance sensors have been widely used to monitor soil moisture at different depths. Two approaches for converting permittivity measures using the capacitance probe (PR2, Delta-T Devices) to soil water content are to (a) use the default equation and parameters provided by the manufacturer, and (b) use site specific calibration equations. The objective of this study was to evaluate the performance of the manufacturer’s default equation and in-situ calibrated equations for estimating soil water content. Permittivity measurement using the PR2 probe coincided with soil sampling during the growing seasons in 2006, 2007 and 2008 for Des Moines lobe soils in north-central Iowa. The default equation provided by Delta-T Devices for the PR2 probe estimated the soil water content for 3 years with an average root mean square error (RMSE) and index of agreement (IoA) values of 0.097 cm3/cm3 and 0.587, respectively. The default equation was calibrated by a 1-year (2006) and a 2-year (2006 + 2007) data set. The resultant statistics indicate that site specific calibration gives more accurate estimates of soil water content compared to the uncalibrated default equation. Three-year averaged RMSE and IoA values were 0.049 cm3/cm3 and 0.742 for equations calibrated by the 1-year data set, and 0.034 cm3/cm3 and 0.807 for equations calibrated by the 2-year data set. The results from this study indicate that a site specific calibration is necessary for the PR2 probe, and equations calibrated by data from a longer period performed better than data from a shorter period. Where a site-specific field calibration cannot be applied, coefficients are provided for various cropping systems in Des Moines Lobe soils of Iowa based on the results from this study.

Assessment Of Energy Expenditure During Physical Activity Using Synchronised Accelerometry And Heart Rate

PURPOSE To determine the accuracy of estimates of energy expenditure using branched equations for synchronised accelerometry and heart rate (AHR) during a 2 h period of structured activity reflecting low to moderate intensity physical activities. METHODS 10 male and 10 female subjects (mean age 26 ± 5 years, height 173 ± 7 cm and body mass 72 ± 11 kg) performed a 2 h laboratory-based protocol simulating six low to moderate intensity physical activities. Each activity lasted 8 min and was interspersed with 8 min supine rest. Activities included treadmill walking at 4.8 km.h−1, sweeping, digging in sand, simulated watering of plants, treadmill walking at 5.6 km.h−1 whilst carrying 4% body mass in each hand and folding and stacking sheets. These activities were chosen as they range from low to moderate intensity physical activity according to assigned values (2–5 metabolic equivalents). These activities include movements where the use of accelerometry and heart rate may be most limited and therefore provide data that may represent a worst-case scenario. Energy expenditure was estimated throughout using indirect calorimetry (COSMED, Italy) and AHR (Cambridge Neurotechnology Ltd., UK). Established default equations for AHR were used to estimate energy expenditure and we also developed new calibration equations derived from both group and individual data. RESULTS Mean energy expenditure across all six physical activities determined using indirect calorimetry was 3.6 ± 0.3 kcal·min−1. The comparison between methods was conducted using ordinary least-products regression. The standard error of the estimate for the prediction of energy expenditure from AHR was 0.4 kcal·min−1 for default equations, new group equations and individual calibration equations during the period of observation. If this were extrapolated to a typical day where an individual was active for 16h, this would be equivalent to 384 kcal (this represents approximately 15% of total energy expenditure if energy expenditure was 2500 kcal.day−1). CONCLUSION These results demonstrate that AHR is a promising tool for the estimation of energy expenditure during low to moderate intensity physical activities. It appears that deriving new group equations or individual calibration equations may not be necessary.

Assessment Of Energy Expenditure During Physical Activity Using Synchronised Accelerometry And Heart Rate

PURPOSE To determine the accuracy of estimates of energy expenditure using branched equations for synchronised accelerometry and heart rate (AHR) during a 2 h period of structured activity reflecting low to moderate intensity physical activities. METHODS 10 male and 10 female subjects (mean age 26 ± 5 years, height 173 ± 7 cm and body mass 72 ± 11 kg) performed a 2 h laboratory-based protocol simulating six low to moderate intensity physical activities. Each activity lasted 8 min and was interspersed with 8 min supine rest. Activities included treadmill walking at 4.8 km.h−1, sweeping, digging in sand, simulated watering of plants, treadmill walking at 5.6 km.h−1 whilst carrying 4% body mass in each hand and folding and stacking sheets. These activities were chosen as they range from low to moderate intensity physical activity according to assigned values (2–5 metabolic equivalents). These activities include movements where the use of accelerometry and heart rate may be most limited and therefore provide data that may represent a worst-case scenario. Energy expenditure was estimated throughout using indirect calorimetry (COSMED, Italy) and AHR (Cambridge Neurotechnology Ltd., UK). Established default equations for AHR were used to estimate energy expenditure and we also developed new calibration equations derived from both group and individual data. RESULTS Mean energy expenditure across all six physical activities determined using indirect calorimetry was 3.6 ± 0.3 kcal·min−1. The comparison between methods was conducted using ordinary least-products regression. The standard error of the estimate for the prediction of energy expenditure from AHR was 0.4 kcal·min−1 for default equations, new group equations and individual calibration equations during the period of observation. If this were extrapolated to a typical day where an individual was active for 16h, this would be equivalent to 384 kcal (this represents approximately 15% of total energy expenditure if energy expenditure was 2500 kcal.day−1). CONCLUSION These results demonstrate that AHR is a promising tool for the estimation of energy expenditure during low to moderate intensity physical activities. It appears that deriving new group equations or individual calibration equations may not be necessary.

ESTIMATING SOIL WATER CONTENT USING SITE-SPECIFIC CALIBRATION OF CAPACITANCE MEASUREMENTS FROM SENTEK ENVIROSCAN SYSTEMS

Newly developed sensors, including the EnviroSCAN capacitance system have the potential to monitor andestimate soil moisture content continuously at various depths. A simple site calibration of the sensors is required to obtainaccurate soil water content because these sensors are shipped with a default (uncalibrated) equation to the user. Therefore,our research objectives were: 1) to calibrate the EnviroSCAN capacitance system versus soil moisture values estimated bya neutron probe calibrated with gravimetrically measured water contents, then 2) statistically compare the calibrated soilwater content results with those estimated by the uncalibrated equation using three years of field data. Both the EnviroSCANcapacitance and the neutron probe were installed in a Warden silt loam soil planted to alfalfa. The average water contentsof the soil profile estimated by the EnviroSCAN capacitance was used to develop a site specific calibration equation bycomparing the sensors scaled frequencies for 1998 with the soil water content of the neutron probe. The site calibrationequation was then statistically validated using both 1999 and 2000 soil water contents. The statistical analyses indicated thatdiscrepancies existed between soil water contents of the site calibration equation and those estimated by the uncalibratedequation. For instance, the RRMSE values of soil water content produced from the calibrated equation were 7%, 41%, and40%, compared with uncalibrated RRMSE values of 68%, 59%, and 66%, for 1998, 1999, and 2000, respectively. Theseresults support that the site calibration equation was found to give more accurate estimates of individual values (low RRMSE)of volumetric soil water content compared to those obtained from the uncalibrated equation.