Piecewise SALT sampling for estimating suspended sediment yields

Treesearch

Robert B. Thomas

1989-01-01

A probability sampling method called SALT (Selection At List Time) has been developed for collecting and summarizing data on delivery of suspended sediment in rivers. It is based on sampling and estimating yield using a suspended-sediment rating curve for high discharges and simple random sampling for low flows. The method gives unbiased estimates of total yield and...

Quantifying Accurate Calorie Estimation Using the "Think Aloud" Method

ERIC Educational Resources Information Center

Holmstrup, Michael E.; Stearns-Bruening, Kay; Rozelle, Jeffrey

2013-01-01

Objective: Clients often have limited time in a nutrition education setting. An improved understanding of the strategies used to accurately estimate calories may help to identify areas of focused instruction to improve nutrition knowledge. Methods: A "Think Aloud" exercise was recorded during the estimation of calories in a standard dinner meal…

Evaluation of Rgb-Based Vegetation Indices from Uav Imagery to Estimate Forage Yield in Grassland

NASA Astrophysics Data System (ADS)

Lussem, U.; Bolten, A.; Gnyp, M. L.; Jasper, J.; Bareth, G.

2018-04-01

Monitoring forage yield throughout the growing season is of key importance to support management decisions on grasslands/pastures. Especially on intensely managed grasslands, where nitrogen fertilizer and/or manure are applied regularly, precision agriculture applications are beneficial to support sustainable, site-specific management decisions on fertilizer treatment, grazing management and yield forecasting to mitigate potential negative impacts. To support these management decisions, timely and accurate information is needed on plant parameters (e.g. forage yield) with a high spatial and temporal resolution. However, in highly heterogeneous plant communities such as grasslands, assessing their in-field variability non-destructively to determine e.g. adequate fertilizer application still remains challenging. Especially biomass/yield estimation, as an important parameter in assessing grassland quality and quantity, is rather laborious. Forage yield (dry or fresh matter) is mostly measured manually with rising plate meters (RPM) or ultrasonic sensors (handheld or mounted on vehicles). Thus the in-field variability cannot be assessed for the entire field or only with potential disturbances. Using unmanned aerial vehicles (UAV) equipped with consumer grade RGB cameras in-field variability can be assessed by computing RGB-based vegetation indices. In this contribution we want to test and evaluate the robustness of RGB-based vegetation indices to estimate dry matter forage yield on a recently established experimental grassland site in Germany. Furthermore, the RGB-based VIs are compared to indices computed from the Yara N-Sensor. The results show a good correlation of forage yield with RGB-based VIs such as the NGRDI with R2 values of 0.62.

Seismic Methods of Identifying Explosions and Estimating Their Yield

NASA Astrophysics Data System (ADS)

Walter, W. R.; Ford, S. R.; Pasyanos, M.; Pyle, M. L.; Myers, S. C.; Mellors, R. J.; Pitarka, A.; Rodgers, A. J.; Hauk, T. F.

2014-12-01

Seismology plays a key national security role in detecting, locating, identifying and determining the yield of explosions from a variety of causes, including accidents, terrorist attacks and nuclear testing treaty violations (e.g. Koper et al., 2003, 1999; Walter et al. 1995). A collection of mainly empirical forensic techniques has been successfully developed over many years to obtain source information on explosions from their seismic signatures (e.g. Bowers and Selby, 2009). However a lesson from the three DPRK declared nuclear explosions since 2006, is that our historic collection of data may not be representative of future nuclear test signatures (e.g. Selby et al., 2012). To have confidence in identifying future explosions amongst the background of other seismic signals, and accurately estimate their yield, we need to put our empirical methods on a firmer physical footing. Goals of current research are to improve our physical understanding of the mechanisms of explosion generation of S- and surface-waves, and to advance our ability to numerically model and predict them. As part of that process we are re-examining regional seismic data from a variety of nuclear test sites including the DPRK and the former Nevada Test Site (now the Nevada National Security Site (NNSS)). Newer relative location and amplitude techniques can be employed to better quantify differences between explosions and used to understand those differences in term of depth, media and other properties. We are also making use of the Source Physics Experiments (SPE) at NNSS. The SPE chemical explosions are explicitly designed to improve our understanding of emplacement and source material effects on the generation of shear and surface waves (e.g. Snelson et al., 2013). Finally we are also exploring the value of combining seismic information with other technologies including acoustic and InSAR techniques to better understand the source characteristics. Our goal is to improve our explosion models

Estimation of dew yield from radiative condensers by means of an energy balance model

NASA Astrophysics Data System (ADS)

Maestre-Valero, J. F.; Ragab, R.; Martínez-Alvarez, V.; Baille, A.

2012-08-01

SummaryThis paper presents an energy balance modelling approach to predict the nightly water yield and the surface temperature (Tf) of two passive radiative dew condensers (RDCs) tilted 30° from horizontal. One was fitted with a white hydrophilic polyethylene foil recommended for dew harvest and the other with a black polyethylene foil widely used in horticulture. The model was validated in south-eastern Spain by comparing the simulation outputs with field measurements of Tf and dew yield. The results indicate that the model is robust and accurate in reproducing the behaviour of the two RDCs, especially in what refers to Tf, whose estimates were very close to the observations. The results were somewhat less precise for dew yield, with a larger scatter around the 1:1 relationship. A sensitivity analysis showed that the simulated dew yield was highly sensitive to changes in relative humidity and downward longwave radiation. The proposed approach provides a useful tool to water managers for quantifying the amount of dew that could be harvested as a valuable water resource in arid, semiarid and water stressed regions.

Explosion yield estimation from pressure wave template matching

PubMed Central

Arrowsmith, Stephen; Bowman, Daniel

2017-01-01

A method for estimating the yield of explosions from shock-wave and acoustic-wave measurements is presented. The method exploits full waveforms by comparing pressure measurements against an empirical stack of prior observations using scaling laws. The approach can be applied to measurements across a wide-range of source-to-receiver distances. The method is applied to data from two explosion experiments in different regions, leading to mean relative errors in yield estimates of 0.13 using prior data from the same region, and 0.2 when applied to a new region. PMID:28618805

Growth and Yield Estimation for Loblolly Pine in the West Gulf

Treesearch

Paul A. Murphy; Herbert S. Sternitzke

1979-01-01

An equation system is developed to estimate current yield, projected basal area, and projected volume for merchantable natural stands on a per-acre basis. These estimates indicate yields that can be expected from woods-run conditions.

Canopy Chlorophyll Density Based Index for Estimating Nitrogen Status and Predicting Grain Yield in Rice

PubMed Central

Liu, Xiaojun; Zhang, Ke; Zhang, Zeyu; Cao, Qiang; Lv, Zunfu; Yuan, Zhaofeng; Tian, Yongchao; Cao, Weixing; Zhu, Yan

2017-01-01

Canopy chlorophyll density (Chl) has a pivotal role in diagnosing crop growth and nutrition status. The purpose of this study was to develop Chl based models for estimating N status and predicting grain yield of rice (Oryza sativa L.) with Leaf area index (LAI) and Chlorophyll concentration of the upper leaves. Six field experiments were conducted in Jiangsu Province of East China during 2007, 2008, 2009, 2013, and 2014. Different N rates were applied to generate contrasting conditions of N availability in six Japonica cultivars (9915, 27123, Wuxiangjing 14, Wuyunjing 19, Yongyou 8, and Wuyunjing 24) and two Indica cultivars (Liangyoupei 9, YLiangyou 1). The SPAD values of the four uppermost leaves and LAI were measured from tillering to flowering growth stages. Two N indicators, leaf N accumulation (LNA) and plant N accumulation (PNA) were measured. The LAI estimated by LAI-2000 and LI-3050C were compared and calibrated with a conversion equation. A linear regression analysis showed significant relationships between Chl value and N indicators, the equations were as follows: PNA = (0.092 × Chl) − 1.179 (R2 = 0.94, P < 0.001, relative root mean square error (RRMSE) = 0.196), LNA = (0.052 × Chl) − 0.269 (R2 = 0.93, P < 0.001, RRMSE = 0.185). Standardized method was used to quantity the correlation between Chl value and grain yield, normalized yield = (0.601 × normalized Chl) + 0.400 (R2 = 0.81, P < 0.001, RRMSE = 0.078). Independent experimental data also validated the use of Chl value to accurately estimate rice N status and predict grain yield. PMID:29163568

Effects of stage of pregnancy on variance components, daily milk yields and 305-day milk yield in Holstein cows, as estimated by using a test-day model.

PubMed

Yamazaki, T; Hagiya, K; Takeda, H; Osawa, T; Yamaguchi, S; Nagamine, Y

2016-08-01

Pregnancy and calving are elements indispensable for dairy production, but the daily milk yield of cows decline as pregnancy progresses, especially during the late stages. Therefore, the effect of stage of pregnancy on daily milk yield must be clarified to accurately estimate the breeding values and lifetime productivity of cows. To improve the genetic evaluation model for daily milk yield and determine the effect of the timing of pregnancy on productivity, we used a test-day model to assess the effects of stage of pregnancy on variance component estimates, daily milk yields and 305-day milk yield during the first three lactations of Holstein cows. Data were 10 646 333 test-day records for the first lactation; 8 222 661 records for the second; and 5 513 039 records for the third. The data were analyzed within each lactation by using three single-trait random regression animal models: one model that did not account for the stage of pregnancy effect and two models that did. The effect of stage of pregnancy on test-day milk yield was included in the model by applying a regression on days pregnant or fitting a separate lactation curve for each days open (days from calving to pregnancy) class (eight levels). Stage of pregnancy did not affect the heritability estimates of daily milk yield, although the additive genetic and permanent environmental variances in late lactation were decreased by accounting for the stage of pregnancy effect. The effects of days pregnant on daily milk yield during late lactation were larger in the second and third lactations than in the first lactation. The rates of reduction of the 305-day milk yield of cows that conceived fewer than 90 days after the second or third calving were significantly (P<0.05) greater than that after the first calving. Therefore, we conclude that differences between the negative effects of early pregnancy in the first, compared with later, lactations should be included when determining the optimal number of days open

Minimum number of measurements for evaluating soursop (Annona muricata L.) yield.

PubMed

Sánchez, C F B; Teodoro, P E; Londoño, S; Silva, L A; Peixoto, L A; Bhering, L L

2017-05-31

Repeatability studies on fruit species are of great importance to identify the minimum number of measurements necessary to accurately select superior genotypes. This study aimed to identify the most efficient method to estimate the repeatability coefficient (r) and predict the minimum number of measurements needed for a more accurate evaluation of soursop (Annona muricata L.) genotypes based on fruit yield. Sixteen measurements of fruit yield from 71 soursop genotypes were carried out between 2000 and 2016. In order to estimate r with the best accuracy, four procedures were used: analysis of variance, principal component analysis based on the correlation matrix, principal component analysis based on the phenotypic variance and covariance matrix, and structural analysis based on the correlation matrix. The minimum number of measurements needed to predict the actual value of individuals was estimated. Principal component analysis using the phenotypic variance and covariance matrix provided the most accurate estimates of both r and the number of measurements required for accurate evaluation of fruit yield in soursop. Our results indicate that selection of soursop genotypes with high fruit yield can be performed based on the third and fourth measurements in the early years and/or based on the eighth and ninth measurements at more advanced stages.

Assessing the likely value of gravity and drawdown measurements to constrain estimates of hydraulic conductivity and specific yield during unconfined aquifer testing

USGS Publications Warehouse

Blainey, Joan B.; Ferré, Ty P.A.; Cordova, Jeffrey T.

2007-01-01

Pumping of an unconfined aquifer can cause local desaturation detectable with high‐resolution gravimetry. A previous study showed that signal‐to‐noise ratios could be predicted for gravity measurements based on a hydrologic model. We show that although changes should be detectable with gravimeters, estimations of hydraulic conductivity and specific yield based on gravity data alone are likely to be unacceptably inaccurate and imprecise. In contrast, a transect of low‐quality drawdown data alone resulted in accurate estimates of hydraulic conductivity and inaccurate and imprecise estimates of specific yield. Combined use of drawdown and gravity data, or use of high‐quality drawdown data alone, resulted in unbiased and precise estimates of both parameters. This study is an example of the value of a staged assessment regarding the likely significance of a new measurement method or monitoring scenario before collecting field data.

Estimating yellow-poplar growth and yield

Treesearch

Donald E. Beck

1989-01-01

Yellow-poplar grows in essentially pure, even-aged stands, so you can make growth and yield estimates from relatively few stand characteristics. The tables and models described here require only measures of stand age, stand basal area in trees 4.5 inches and larger, and site index. They were developed by remeasuring (at 5-year intervals over a 20-year period) many...

Estimation of rice yield affected by drought and relation between rice yield and TVDI

NASA Astrophysics Data System (ADS)

Hongo, C.; Tamura, E.; Sigit, G.

2016-12-01

Impact of climate change is not only seen on food production but also on food security and sustainable development of society. Adaptation to climate change is a pressing issue throughout the world to reduce the risks along with the plans and strategies for food security and sustainable development. As a key adaptation to the climate change, agricultural insurance is expected to play an important role in stabilizing agricultural production through compensating the losses caused by the climate change. As the adaptation, the Government of Indonesia has launched agricultural insurance program for damage of rice by drought, flood and pest and disease. The Government started a pilot project in 2013 and this year the pilot project has been extended to 22 provinces. Having the above as background, we conducted research on development of new damage assessment method for rice using remote sensing data which could be used for evaluation of damage ratio caused by drought in West Java, Indonesia. For assessment of the damage ratio, estimation of rice yield is a key. As the result of our study, rice yield affected by drought in dry season could be estimated at level of 1 % significance using SPOT 7 data taken in 2015, and the validation result was 0.8t/ha. Then, the decrease ratio in rice yield about each individual paddy field was calculated using data of the estimated result and the average yield of the past 10 years. In addition, TVDI (Temperature Vegetation Dryness Index) which was calculated from Landsat8 data in heading season indicated the dryness in low yield area. The result suggests that rice yield was affected by irrigation water shortage around heading season as a result of the decreased precipitation by El Nino. Through our study, it becomes clear that the utilization of remote sensing data can be promising for assessment of the damage ratio of rice production precisely, quickly and quantitatively, and also it can be incorporated into the insurance procedures.

Methods for accurate estimation of net discharge in a tidal channel

USGS Publications Warehouse

Simpson, M.R.; Bland, R.

2000-01-01

Accurate estimates of net residual discharge in tidally affected rivers and estuaries are possible because of recently developed ultrasonic discharge measurement techniques. Previous discharge estimates using conventional mechanical current meters and methods based on stage/discharge relations or water slope measurements often yielded errors that were as great as or greater than the computed residual discharge. Ultrasonic measurement methods consist of: 1) the use of ultrasonic instruments for the measurement of a representative 'index' velocity used for in situ estimation of mean water velocity and 2) the use of the acoustic Doppler current discharge measurement system to calibrate the index velocity measurement data. Methods used to calibrate (rate) the index velocity to the channel velocity measured using the Acoustic Doppler Current Profiler are the most critical factors affecting the accuracy of net discharge estimation. The index velocity first must be related to mean channel velocity and then used to calculate instantaneous channel discharge. Finally, discharge is low-pass filtered to remove the effects of the tides. An ultrasonic velocity meter discharge-measurement site in a tidally affected region of the Sacramento-San Joaquin Rivers was used to study the accuracy of the index velocity calibration procedure. Calibration data consisting of ultrasonic velocity meter index velocity and concurrent acoustic Doppler discharge measurement data were collected during three time periods. Two sets of data were collected during a spring tide (monthly maximum tidal current) and one of data collected during a neap tide (monthly minimum tidal current). The relative magnitude of instrumental errors, acoustic Doppler discharge measurement errors, and calibration errors were evaluated. Calibration error was found to be the most significant source of error in estimating net discharge. Using a comprehensive calibration method, net discharge estimates developed from the three

Estimating sugarcane yield potential using an in-season determination of normalized difference vegetative index.

PubMed

Lofton, Josh; Tubana, Brenda S; Kanke, Yumiko; Teboh, Jasper; Viator, Howard; Dalen, Marilyn

2012-01-01

Estimating crop yield using remote sensing techniques has proven to be successful. However, sugarcane possesses unique characteristics; such as, a multi-year cropping cycle and plant height-limiting for midseason fertilizer application timing. Our study objective was to determine if sugarcane yield potential could be estimated using an in-season estimation of normalized difference vegetative index (NDVI). Sensor readings were taken using the GreenSeeker® handheld sensor from 2008 to 2011 in St. Gabriel and Jeanerette, LA, USA. In-season estimates of yield (INSEY) values were calculated by dividing NDVI by thermal variables. Optimum timing for estimating sugarcane yield was between 601-750 GDD. In-season estimated yield values improved the yield potential (YP) model compared to using NDVI. Generally, INSEY value showed a positive exponential relationship with yield (r(2) values 0.48 and 0.42 for cane tonnage and sugar yield, respectively). When models were separated based on canopy structure there was an increase the strength of the relationship for the erectophile varieties (r(2) 0.53 and 0.47 for cane tonnage and sugar yield, respectively); however, the model for planophile varieties weakened slightly. Results of this study indicate using an INSEY value for predicting sugarcane yield shows potential of being a valuable management tool for sugarcane producers in Louisiana.

Accurate estimation of sigma(exp 0) using AIRSAR data

NASA Technical Reports Server (NTRS)

Holecz, Francesco; Rignot, Eric

1995-01-01

During recent years signature analysis, classification, and modeling of Synthetic Aperture Radar (SAR) data as well as estimation of geophysical parameters from SAR data have received a great deal of interest. An important requirement for the quantitative use of SAR data is the accurate estimation of the backscattering coefficient sigma(exp 0). In terrain with relief variations radar signals are distorted due to the projection of the scene topography into the slant range-Doppler plane. The effect of these variations is to change the physical size of the scattering area, leading to errors in the radar backscatter values and incidence angle. For this reason the local incidence angle, derived from sensor position and Digital Elevation Model (DEM) data must always be considered. Especially in the airborne case, the antenna gain pattern can be an additional source of radiometric error, because the radar look angle is not known precisely as a result of the the aircraft motions and the local surface topography. Consequently, radiometric distortions due to the antenna gain pattern must also be corrected for each resolution cell, by taking into account aircraft displacements (position and attitude) and position of the backscatter element, defined by the DEM data. In this paper, a method to derive an accurate estimation of the backscattering coefficient using NASA/JPL AIRSAR data is presented. The results are evaluated in terms of geometric accuracy, radiometric variations of sigma(exp 0), and precision of the estimated forest biomass.

Estimating national crop yield potential and the relevance of weather data sources

NASA Astrophysics Data System (ADS)

Van Wart, Justin

2011-12-01

To determine where, when, and how to increase yields, researchers often analyze the yield gap (Yg), the difference between actual current farm yields and crop yield potential. Crop yield potential (Yp) is the yield of a crop cultivar grown under specific management limited only by temperature and solar radiation and also by precipitation for water limited yield potential (Yw). Yp and Yw are critical components of Yg estimations, but are very difficult to quantify, especially at larger scales because management data and especially daily weather data are scarce. A protocol was developed to estimate Yp and Yw at national scales using site-specific weather, soils and management data. Protocol procedures and inputs were evaluated to determine how to improve accuracy of Yp, Yw and Yg estimates. The protocol was also used to evaluate raw, site-specific and gridded weather database sources for use in simulations of Yp or Yw. The protocol was applied to estimate crop Yp in US irrigated maize and Chinese irrigated rice and Yw in US rainfed maize and German rainfed wheat. These crops and countries account for >20% of global cereal production. The results have significant implications for past and future studies of Yp, Yw and Yg. Accuracy of national long-term average Yp and Yw estimates was significantly improved if (i) > 7 years of simulations were performed for irrigated and > 15 years for rainfed sites, (ii) > 40% of nationally harvested area was within 100 km of all simulation sites, (iii) observed weather data coupled with satellite derived solar radiation data were used in simulations, and (iv) planting and harvesting dates were specified within +/- 7 days of farmers actual practices. These are much higher standards than have been applied in national estimates of Yp and Yw and this protocol is a substantial step in making such estimates more transparent, robust, and straightforward. Finally, this protocol may be a useful tool for understanding yield trends and directing

A Comparison of Machine Learning Approaches for Corn Yield Estimation

NASA Astrophysics Data System (ADS)

Kim, N.; Lee, Y. W.

2017-12-01

Machine learning is an efficient empirical method for classification and prediction, and it is another approach to crop yield estimation. The objective of this study is to estimate corn yield in the Midwestern United States by employing the machine learning approaches such as the support vector machine (SVM), random forest (RF), and deep neural networks (DNN), and to perform the comprehensive comparison for their results. We constructed the database using satellite images from MODIS, the climate data of PRISM climate group, and GLDAS soil moisture data. In addition, to examine the seasonal sensitivities of corn yields, two period groups were set up: May to September (MJJAS) and July and August (JA). In overall, the DNN showed the highest accuracies in term of the correlation coefficient for the two period groups. The differences between our predictions and USDA yield statistics were about 10-11 %.

Spatial variability effects on precision and power of forage yield estimation

USDA-ARS?s Scientific Manuscript database

Spatial analyses of yield trials are important, as they adjust cultivar means for spatial variation and improve the statistical precision of yield estimation. While the relative efficiency of spatial analysis has been frequently reported in several yield trials, its application on long-term forage y...

Accurate Satellite-Derived Estimates of Tropospheric Ozone Radiative Forcing

NASA Technical Reports Server (NTRS)

Joiner, Joanna; Schoeberl, Mark R.; Vasilkov, Alexander P.; Oreopoulos, Lazaros; Platnick, Steven; Livesey, Nathaniel J.; Levelt, Pieternel F.

2008-01-01

Estimates of the radiative forcing due to anthropogenically-produced tropospheric O3 are derived primarily from models. Here, we use tropospheric ozone and cloud data from several instruments in the A-train constellation of satellites as well as information from the GEOS-5 Data Assimilation System to accurately estimate the instantaneous radiative forcing from tropospheric O3 for January and July 2005. We improve upon previous estimates of tropospheric ozone mixing ratios from a residual approach using the NASA Earth Observing System (EOS) Aura Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS) by incorporating cloud pressure information from OMI. Since we cannot distinguish between natural and anthropogenic sources with the satellite data, our estimates reflect the total forcing due to tropospheric O3. We focus specifically on the magnitude and spatial structure of the cloud effect on both the shortand long-wave radiative forcing. The estimates presented here can be used to validate present day O3 radiative forcing produced by models.

Accurate age estimation in small-scale societies

PubMed Central

Smith, Daniel; Gerbault, Pascale; Dyble, Mark; Migliano, Andrea Bamberg; Thomas, Mark G.

2017-01-01

Precise estimation of age is essential in evolutionary anthropology, especially to infer population age structures and understand the evolution of human life history diversity. However, in small-scale societies, such as hunter-gatherer populations, time is often not referred to in calendar years, and accurate age estimation remains a challenge. We address this issue by proposing a Bayesian approach that accounts for age uncertainty inherent to fieldwork data. We developed a Gibbs sampling Markov chain Monte Carlo algorithm that produces posterior distributions of ages for each individual, based on a ranking order of individuals from youngest to oldest and age ranges for each individual. We first validate our method on 65 Agta foragers from the Philippines with known ages, and show that our method generates age estimations that are superior to previously published regression-based approaches. We then use data on 587 Agta collected during recent fieldwork to demonstrate how multiple partial age ranks coming from multiple camps of hunter-gatherers can be integrated. Finally, we exemplify how the distributions generated by our method can be used to estimate important demographic parameters in small-scale societies: here, age-specific fertility patterns. Our flexible Bayesian approach will be especially useful to improve cross-cultural life history datasets for small-scale societies for which reliable age records are difficult to acquire. PMID:28696282

Accurate age estimation in small-scale societies.

PubMed

Diekmann, Yoan; Smith, Daniel; Gerbault, Pascale; Dyble, Mark; Page, Abigail E; Chaudhary, Nikhil; Migliano, Andrea Bamberg; Thomas, Mark G

2017-08-01

Precise estimation of age is essential in evolutionary anthropology, especially to infer population age structures and understand the evolution of human life history diversity. However, in small-scale societies, such as hunter-gatherer populations, time is often not referred to in calendar years, and accurate age estimation remains a challenge. We address this issue by proposing a Bayesian approach that accounts for age uncertainty inherent to fieldwork data. We developed a Gibbs sampling Markov chain Monte Carlo algorithm that produces posterior distributions of ages for each individual, based on a ranking order of individuals from youngest to oldest and age ranges for each individual. We first validate our method on 65 Agta foragers from the Philippines with known ages, and show that our method generates age estimations that are superior to previously published regression-based approaches. We then use data on 587 Agta collected during recent fieldwork to demonstrate how multiple partial age ranks coming from multiple camps of hunter-gatherers can be integrated. Finally, we exemplify how the distributions generated by our method can be used to estimate important demographic parameters in small-scale societies: here, age-specific fertility patterns. Our flexible Bayesian approach will be especially useful to improve cross-cultural life history datasets for small-scale societies for which reliable age records are difficult to acquire.

Linear unmixing of multidate hyperspectral imagery for crop yield estimation

USDA-ARS?s Scientific Manuscript database

In this paper, we have evaluated an unsupervised unmixing approach, vertex component analysis (VCA), for the application of crop yield estimation. The results show that abundance maps of the vegetation extracted by the approach are strongly correlated to the yield data (the correlation coefficients ...

Estimation of Rice Crop Yields Using Random Forests in Taiwan

NASA Astrophysics Data System (ADS)

Chen, C. F.; Lin, H. S.; Nguyen, S. T.; Chen, C. R.

2017-12-01

Rice is globally one of the most important food crops, directly feeding more people than any other crops. Rice is not only the most important commodity, but also plays a critical role in the economy of Taiwan because it provides employment and income for large rural populations. The rice harvested area and production are thus monitored yearly due to the government's initiatives. Agronomic planners need such information for more precise assessment of food production to tackle issues of national food security and policymaking. This study aimed to develop a machine-learning approach using physical parameters to estimate rice crop yields in Taiwan. We processed the data for 2014 cropping seasons, following three main steps: (1) data pre-processing to construct input layers, including soil types and weather parameters (e.g., maxima and minima air temperature, precipitation, and solar radiation) obtained from meteorological stations across the country; (2) crop yield estimation using the random forests owing to its merits as it can process thousands of variables, estimate missing data, maintain the accuracy level when a large proportion of the data is missing, overcome most of over-fitting problems, and run fast and efficiently when handling large datasets; and (3) error verification. To execute the model, we separated the datasets into two groups of pixels: group-1 (70% of pixels) for training the model and group-2 (30% of pixels) for testing the model. Once the model is trained to produce small and stable out-of-bag error (i.e., the mean squared error between predicted and actual values), it can be used for estimating rice yields of cropping seasons. The results obtained from the random forests-based regression were compared with the actual yield statistics indicated the values of root mean square error (RMSE) and mean absolute error (MAE) achieved for the first rice crop were respectively 6.2% and 2.7%, while those for the second rice crop were 5.3% and 2

Determination of the optimal level for combining area and yield estimates

NASA Technical Reports Server (NTRS)

Bauer, M. E. (Principal Investigator); Hixson, M. M.; Jobusch, C. D.

1981-01-01

Several levels of obtaining both area and yield estimates of corn and soybeans in Iowa were considered: county, refined strata, refined/split strata, crop reporting district, and state. Using the CCEA model form and smoothed weather data, regression coefficients at each level were derived to compute yield and its variance. Variances were also computed with stratum level. The variance of the yield estimates was largest at the state and smallest at the county level for both crops. The refined strata had somewhat larger variances than those associated with the refined/split strata and CRD. For production estimates, the difference in standard deviations among levels was not large for corn, but for soybeans the standard deviation at the state level was more than 50% greater than for the other levels. The refined strata had the smallest standard deviations. The county level was not considered in evaluation of production estimates due to lack of county area variances.

Classical and Bayesian Seismic Yield Estimation: The 1998 Indian and Pakistani Tests

NASA Astrophysics Data System (ADS)

Shumway, R. H.

2001-10-01

- The nuclear tests in May, 1998, in India and Pakistan have stimulated a renewed interest in yield estimation, based on limited data from uncalibrated test sites. We study here the problem of estimating yields using classical and Bayesian methods developed by Shumway (1992), utilizing calibration data from the Semipalatinsk test site and measured magnitudes for the 1998 Indian and Pakistani tests given by Murphy (1998). Calibration is done using multivariate classical or Bayesian linear regression, depending on the availability of measured magnitude-yield data and prior information. Confidence intervals for the classical approach are derived applying an extension of Fieller's method suggested by Brown (1982). In the case where prior information is available, the posterior predictive magnitude densities are inverted to give posterior intervals for yield. Intervals obtained using the joint distribution of magnitudes are comparable to the single-magnitude estimates produced by Murphy (1998) and reinforce the conclusion that the announced yields of the Indian and Pakistani tests were too high.

Classical and Bayesian Seismic Yield Estimation: The 1998 Indian and Pakistani Tests

NASA Astrophysics Data System (ADS)

Shumway, R. H.

The nuclear tests in May, 1998, in India and Pakistan have stimulated a renewed interest in yield estimation, based on limited data from uncalibrated test sites. We study here the problem of estimating yields using classical and Bayesian methods developed by Shumway (1992), utilizing calibration data from the Semipalatinsk test site and measured magnitudes for the 1998 Indian and Pakistani tests given by Murphy (1998). Calibration is done using multivariate classical or Bayesian linear regression, depending on the availability of measured magnitude-yield data and prior information. Confidence intervals for the classical approach are derived applying an extension of Fieller's method suggested by Brown (1982). In the case where prior information is available, the posterior predictive magnitude densities are inverted to give posterior intervals for yield. Intervals obtained using the joint distribution of magnitudes are comparable to the single-magnitude estimates produced by Murphy (1998) and reinforce the conclusion that the announced yields of the Indian and Pakistani tests were too high.

The estimation of rice paddy yield with GRAMI crop model and Geostationary Ocean Color Imager (GOCI) image over South Korea

NASA Astrophysics Data System (ADS)

Yeom, J. M.; Kim, H. O.

2014-12-01

In this study, we estimated the rice paddy yield with moderate geostationary satellite based vegetation products and GRAMI model over South Korea. Rice is the most popular staple food for Asian people. In addition, the effects of climate change are getting stronger especially in Asian region, where the most of rice are cultivated. Therefore, accurate and timely prediction of rice yield is one of the most important to accomplish food security and to prepare natural disasters such as crop defoliation, drought, and pest infestation. In the present study, GOCI, which is world first Geostationary Ocean Color Image, was used for estimating temporal vegetation indices of the rice paddy by adopting atmospheric correction BRDF modeling. For the atmospheric correction with LUT method based on Second Simulation of the Satellite Signal in the Solar Spectrum (6S), MODIS atmospheric products such as MOD04, MOD05, MOD07 from NASA's Earth Observing System Data and Information System (EOSDIS) were used. In order to correct the surface anisotropy effect, Ross-Thick Li-Sparse Reciprocal (RTLSR) BRDF model was performed at daily basis with 16day composite period. The estimated multi-temporal vegetation images was used for crop classification by using high resolution satellite images such as Rapideye, KOMPSAT-2 and KOMPSAT-3 to extract the proportional rice paddy area in corresponding a pixel of GOCI. In the case of GRAMI crop model, initial conditions are determined by performing every 2 weeks field works at Chonnam National University, Gwangju, Korea. The corrected GOCI vegetation products were incorporated with GRAMI model to predict rice yield estimation. The predicted rice yield was compared with field measurement of rice yield.

Estimated loads and yields of suspended soils and water-quality constituents in Kentucky streams

USGS Publications Warehouse

Crain, Angela S.

2001-01-01

Loads and yields of suspended solids, nutrients, major ions, trace elements, organic carbon, fecal coliform, dissolved oxygen, and alkalinity were estimated for 22 streams in 11 major river basins in Kentucky. Mean daily discharge was estimated at ungaged stations or stations with incomplete discharge records using drainage-area ratio, regression analysis, or a combination of the two techniques. Streamflow was partitioned into total and base flow and used to estimate loads and yields for suspended solids and water-quality constituents by use of the ESTIMATOR and FLUX computer programs. The relative magnitude of constituent transport to streams from groundand surface-water sources was determined for the 22 stations. Nutrient and suspended solids yields for drainage basins with relatively homogenous land use were used to estimate the total-flow and base-flow yields of nutrient and suspended solids for forested, agricultural, and urban land. Yields of nutrients?nitrite plus nitrate, ammonia plus organic nitrogen, and total phosphorus?in forested drainage basins were generally less than 1 ton per square mile per year ((ton/mi2)/yr) and were generally less than 2 (ton/mi2)/yr in agricultural drainage basins. The smallest total-flow yields for nitrogen (nitrite plus nitrate) was estimated at Levisa Fork at Paintsville in which 95 percent of the land is forested. This site also had one of the smallest total-flow yields for ammonia plus organic nitrogen. In general, nutrient yields from forested lands were lower than those from urban and agricultural land. Some of the largest estimated total-flow yields of nutrients among agricultural basins were for streams in the Licking River Basin, the North Fork Licking River near Milford, and the South Fork Licking River at Cynthiana. Agricultural land constitutes greater than 75 percent of the drainage area in these two basins. Possible sources of nutrients discharging into the Licking River are farm and residential fertilizers

An Accurate Link Correlation Estimator for Improving Wireless Protocol Performance

PubMed Central

Zhao, Zhiwei; Xu, Xianghua; Dong, Wei; Bu, Jiajun

2015-01-01

Wireless link correlation has shown significant impact on the performance of various sensor network protocols. Many works have been devoted to exploiting link correlation for protocol improvements. However, the effectiveness of these designs heavily relies on the accuracy of link correlation measurement. In this paper, we investigate state-of-the-art link correlation measurement and analyze the limitations of existing works. We then propose a novel lightweight and accurate link correlation estimation (LACE) approach based on the reasoning of link correlation formation. LACE combines both long-term and short-term link behaviors for link correlation estimation. We implement LACE as a stand-alone interface in TinyOS and incorporate it into both routing and flooding protocols. Simulation and testbed results show that LACE: (1) achieves more accurate and lightweight link correlation measurements than the state-of-the-art work; and (2) greatly improves the performance of protocols exploiting link correlation. PMID:25686314

Toward accurate and precise estimates of lion density.

PubMed

Elliot, Nicholas B; Gopalaswamy, Arjun M

2017-08-01

Reliable estimates of animal density are fundamental to understanding ecological processes and population dynamics. Furthermore, their accuracy is vital to conservation because wildlife authorities rely on estimates to make decisions. However, it is notoriously difficult to accurately estimate density for wide-ranging carnivores that occur at low densities. In recent years, significant progress has been made in density estimation of Asian carnivores, but the methods have not been widely adapted to African carnivores, such as lions (Panthera leo). Although abundance indices for lions may produce poor inferences, they continue to be used to estimate density and inform management and policy. We used sighting data from a 3-month survey and adapted a Bayesian spatially explicit capture-recapture (SECR) model to estimate spatial lion density in the Maasai Mara National Reserve and surrounding conservancies in Kenya. Our unstructured spatial capture-recapture sampling design incorporated search effort to explicitly estimate detection probability and density on a fine spatial scale, making our approach robust in the context of varying detection probabilities. Overall posterior mean lion density was estimated to be 17.08 (posterior SD 1.310) lions >1 year old/100 km 2 , and the sex ratio was estimated at 2.2 females to 1 male. Our modeling framework and narrow posterior SD demonstrate that SECR methods can produce statistically rigorous and precise estimates of population parameters, and we argue that they should be favored over less reliable abundance indices. Furthermore, our approach is flexible enough to incorporate different data types, which enables robust population estimates over relatively short survey periods in a variety of systems. Trend analyses are essential to guide conservation decisions but are frequently based on surveys of differing reliability. We therefore call for a unified framework to assess lion numbers in key populations to improve management and

Impacts of Different Assimilation Methodologies on Crop Yield Estimates Using Active and Passive Microwave Dataset at L-Band

NASA Astrophysics Data System (ADS)

Liu, P.; Bongiovanni, T. E.; Monsivais-Huertero, A.; Bindlish, R.; Judge, J.

2013-12-01

Accurate estimates of crop yield are important for managing agricultural production and food security. Although the crop growth models, such as the Decision Support System Agrotechnology Transfer (DSSAT), have been used to simulate crop growth and development, the crop yield estimates still diverge from the reality due to different sources of errors in the models and computation. Auxiliary observations may be incorporated into such dynamic models to improve predictions using data assimilation. Active and passive (AP) microwave observations at L-band (1-2 GHz) are sensitive to dielectric and geometric properties of soil and vegetation, including soil moisture (SM), vegetation water content (VWC), surface roughness, and vegetation structure. Because SM and VWC are one of the governing factors in estimating crop yield, microwave observations may be used to improve crop yield estimates. Current studies have shown that active observations are more sensitive to the surface roughness of soil and vegetation structure during the growing season, while the passive observations are more sensitive to the SM. Backscatter and emission models linked with the DSSAT model (DSSAT-A-P) allow assimilation of microwave observations of backscattering coefficient (σ0) and brightness temperature (TB) may provide biophysically realistic estimates of model states and parameters. The present ESA Soil Moisture Ocean Salinity (SMOS) mission provides passive observations at 1.41 GHz at 25 km every 2-3 days, and the NASA/CNDAE Aquarius mission provides L-band AP observations at spatial resolution of 150 km with a repeat coverage of 7 days for global SM products. In 2014, the planned NASA Soil Moisture Active Passive mission will provide AP observations at 1.26 and 1.41 GHz at the spatial resolutions of 3 and 30 km, respectively, with a repeat coverage of 2-3 days. The goal of this study is to understand the impacts of assimilation of asynchronous and synchronous AP observations on crop yield

High sample throughput genotyping for estimating C-lineage introgression in the dark honeybee: an accurate and cost-effective SNP-based tool.

PubMed

Henriques, Dora; Browne, Keith A; Barnett, Mark W; Parejo, Melanie; Kryger, Per; Freeman, Tom C; Muñoz, Irene; Garnery, Lionel; Highet, Fiona; Jonhston, J Spencer; McCormack, Grace P; Pinto, M Alice

2018-06-04

The natural distribution of the honeybee (Apis mellifera L.) has been changed by humans in recent decades to such an extent that the formerly widest-spread European subspecies, Apis mellifera mellifera, is threatened by extinction through introgression from highly divergent commercial strains in large tracts of its range. Conservation efforts for A. m. mellifera are underway in multiple European countries requiring reliable and cost-efficient molecular tools to identify purebred colonies. Here, we developed four ancestry-informative SNP assays for high sample throughput genotyping using the iPLEX Mass Array system. Our customized assays were tested on DNA from individual and pooled, haploid and diploid honeybee samples extracted from different tissues using a diverse range of protocols. The assays had a high genotyping success rate and yielded accurate genotypes. Performance assessed against whole-genome data showed that individual assays behaved well, although the most accurate introgression estimates were obtained for the four assays combined (117 SNPs). The best compromise between accuracy and genotyping costs was achieved when combining two assays (62 SNPs). We provide a ready-to-use cost-effective tool for accurate molecular identification and estimation of introgression levels to more effectively monitor and manage A. m. mellifera conservatories.

Model-assisted forest yield estimation with light detection and ranging

Treesearch

Jacob L. Strunk; Stephen E. Reutebuch; Hans-Erik Andersen; Peter J. Gould; Robert J. McGaughey

2012-01-01

Previous studies have demonstrated that light detection and ranging (LiDAR)-derived variables can be used to model forest yield variables, such as biomass, volume, and number of stems. However, the next step is underrepresented in the literature: estimation of forest yield with appropriate confidence intervals. It is of great importance that the procedures required for...

Exoplanet Yield Estimation for Decadal Study Concepts using EXOSIMS

NASA Astrophysics Data System (ADS)

Morgan, Rhonda; Lowrance, Patrick; Savransky, Dmitry; Garrett, Daniel

2016-01-01

The anticipated upcoming large mission study concepts for the direct imaging of exo-earths present an exciting opportunity for exoplanet discovery and characterization. While these telescope concepts would also be capable of conducting a broad range of astrophysical investigations, the most difficult technology challenges are driven by the requirements for imaging exo-earths. The exoplanet science yield for these mission concepts will drive design trades and mission concept comparisons.To assist in these trade studies, the Exoplanet Exploration Program Office (ExEP) is developing a yield estimation tool that emphasizes transparency and consistent comparison of various design concepts. The tool will provide a parametric estimate of science yield of various mission concepts using contrast curves from physics-based model codes and Monte Carlo simulations of design reference missions using realistic constraints, such as solar avoidance angles, the observatory orbit, propulsion limitations of star shades, the accessibility of candidate targets, local and background zodiacal light levels, and background confusion by stars and galaxies. The python tool utilizes Dmitry Savransky's EXOSIMS (Exoplanet Open-Source Imaging Mission Simulator) design reference mission simulator that is being developed for the WFIRST Preliminary Science program. ExEP is extending and validating the tool for future mission concepts under consideration for the upcoming 2020 decadal review. We present a validation plan and preliminary yield results for a point design.

[Regional scale remote sensing-based yield estimation of winter wheat by using MODIS-NDVI data: a case study of Jining City in Shandong Province].

PubMed

Ren, Jianqiang; Chen, Zhongxin; Tang, Huajun

2006-12-01

Taking Jining City of Shandong Province, one of the most important winter wheat production regions in Huanghuaihai Plain as an example, the winter wheat yield was estimated by using the 250 m MODIS-NDVI data smoothed by Savitzky-Golay filter. The NDVI values between 0. 20 and 0. 80 were selected, and the sum of NDVI value for each county was calculated to build its relation with winter wheat yield. By using stepwise regression method, the linear regression model between NDVI and winter wheat yield was established, with the precision validated by the ground survey data. The results showed that the relative error of predicted yield was between -3.6% and 3.9%, suggesting that the method was relatively accurate and feasible.

Field design factors affecting the precision of ryegrass forage yield estimation

USDA-ARS?s Scientific Manuscript database

Field-based agronomic and genetic research relies heavily on the data generated from field evaluations. Therefore, it is imperative to optimize the precision and accuracy of yield estimates in cultivar evaluation trials to make reliable selections. Experimental error in yield trials is sensitive to ...

Accurate isotopic fission yields of electromagnetically induced fission of 238U measured in inverse kinematics at relativistic energies

NASA Astrophysics Data System (ADS)

Pellereau, E.; Taïeb, J.; Chatillon, A.; Alvarez-Pol, H.; Audouin, L.; Ayyad, Y.; Bélier, G.; Benlliure, J.; Boutoux, G.; Caamaño, M.; Casarejos, E.; Cortina-Gil, D.; Ebran, A.; Farget, F.; Fernández-Domínguez, B.; Gorbinet, T.; Grente, L.; Heinz, A.; Johansson, H.; Jurado, B.; Kelić-Heil, A.; Kurz, N.; Laurent, B.; Martin, J.-F.; Nociforo, C.; Paradela, C.; Pietri, S.; Rodríguez-Sánchez, J. L.; Schmidt, K.-H.; Simon, H.; Tassan-Got, L.; Vargas, J.; Voss, B.; Weick, H.

2017-05-01

SOFIA (Studies On Fission with Aladin) is a novel experimental program, dedicated to accurate measurements of fission-fragment isotopic yields. The setup allows us to fully identify, in nuclear charge and mass, both fission fragments in coincidence for the whole fission-fragment range. It was installed at the GSI facility (Darmstadt), to benefit from the relativistic heavy-ion beams available there, and thus to use inverse kinematics. This paper reports on fission yields obtained in electromagnetically induced fission of 238U.

Polynomial Fitting of DT-MRI Fiber Tracts Allows Accurate Estimation of Muscle Architectural Parameters

PubMed Central

Damon, Bruce M.; Heemskerk, Anneriet M.; Ding, Zhaohua

2012-01-01

Fiber curvature is a functionally significant muscle structural property, but its estimation from diffusion-tensor MRI fiber tracking data may be confounded by noise. The purpose of this study was to investigate the use of polynomial fitting of fiber tracts for improving the accuracy and precision of fiber curvature (κ) measurements. Simulated image datasets were created in order to provide data with known values for κ and pennation angle (θ). Simulations were designed to test the effects of increasing inherent fiber curvature (3.8, 7.9, 11.8, and 15.3 m−1), signal-to-noise ratio (50, 75, 100, and 150), and voxel geometry (13.8 and 27.0 mm3 voxel volume with isotropic resolution; 13.5 mm3 volume with an aspect ratio of 4.0) on κ and θ measurements. In the originally reconstructed tracts, θ was estimated accurately under most curvature and all imaging conditions studied; however, the estimates of κ were imprecise and inaccurate. Fitting the tracts to 2nd order polynomial functions provided accurate and precise estimates of κ for all conditions except very high curvature (κ=15.3 m−1), while preserving the accuracy of the θ estimates. Similarly, polynomial fitting of in vivo fiber tracking data reduced the κ values of fitted tracts from those of unfitted tracts and did not change the θ values. Polynomial fitting of fiber tracts allows accurate estimation of physiologically reasonable values of κ, while preserving the accuracy of θ estimation. PMID:22503094

Graphical user interface for yield and dose estimations for cyclotron-produced technetium

NASA Astrophysics Data System (ADS)

Hou, X.; Vuckovic, M.; Buckley, K.; Bénard, F.; Schaffer, P.; Ruth, T.; Celler, A.

2014-07-01

The cyclotron-based 100Mo(p,2n)99mTc reaction has been proposed as an alternative method for solving the shortage of 99mTc. With this production method, however, even if highly enriched molybdenum is used, various radioactive and stable isotopes will be produced simultaneously with 99mTc. In order to optimize reaction parameters and estimate potential patient doses from radiotracers labeled with cyclotron produced 99mTc, the yields for all reaction products must be estimated. Such calculations, however, are extremely complex and time consuming. Therefore, the objective of this study was to design a graphical user interface (GUI) that would automate these calculations, facilitate analysis of the experimental data, and predict dosimetry. The resulting GUI, named Cyclotron production Yields and Dosimetry (CYD), is based on Matlab®. It has three parts providing (a) reaction yield calculations, (b) predictions of gamma emissions and (c) dosimetry estimations. The paper presents the outline of the GUI, lists the parameters that must be provided by the user, discusses the details of calculations and provides examples of the results. Our initial experience shows that the proposed GUI allows the user to very efficiently calculate the yields of reaction products and analyze gamma spectroscopy data. However, it is expected that the main advantage of this GUI will be at the later clinical stage when entering reaction parameters will allow the user to predict production yields and estimate radiation doses to patients for each particular cyclotron run.

Graphical user interface for yield and dose estimations for cyclotron-produced technetium.

PubMed

Hou, X; Vuckovic, M; Buckley, K; Bénard, F; Schaffer, P; Ruth, T; Celler, A

2014-07-07

The cyclotron-based (100)Mo(p,2n)(99m)Tc reaction has been proposed as an alternative method for solving the shortage of (99m)Tc. With this production method, however, even if highly enriched molybdenum is used, various radioactive and stable isotopes will be produced simultaneously with (99m)Tc. In order to optimize reaction parameters and estimate potential patient doses from radiotracers labeled with cyclotron produced (99m)Tc, the yields for all reaction products must be estimated. Such calculations, however, are extremely complex and time consuming. Therefore, the objective of this study was to design a graphical user interface (GUI) that would automate these calculations, facilitate analysis of the experimental data, and predict dosimetry. The resulting GUI, named Cyclotron production Yields and Dosimetry (CYD), is based on Matlab®. It has three parts providing (a) reaction yield calculations, (b) predictions of gamma emissions and (c) dosimetry estimations. The paper presents the outline of the GUI, lists the parameters that must be provided by the user, discusses the details of calculations and provides examples of the results. Our initial experience shows that the proposed GUI allows the user to very efficiently calculate the yields of reaction products and analyze gamma spectroscopy data. However, it is expected that the main advantage of this GUI will be at the later clinical stage when entering reaction parameters will allow the user to predict production yields and estimate radiation doses to patients for each particular cyclotron run.

Estimating yield gaps at the cropping system level.

PubMed

Guilpart, Nicolas; Grassini, Patricio; Sadras, Victor O; Timsina, Jagadish; Cassman, Kenneth G

2017-05-01

Yield gap analyses of individual crops have been used to estimate opportunities for increasing crop production at local to global scales, thus providing information crucial to food security. However, increases in crop production can also be achieved by improving cropping system yield through modification of spatial and temporal arrangement of individual crops. In this paper we define the cropping system yield potential as the output from the combination of crops that gives the highest energy yield per unit of land and time, and the cropping system yield gap as the difference between actual energy yield of an existing cropping system and the cropping system yield potential. Then, we provide a framework to identify alternative cropping systems which can be evaluated against the current ones. A proof-of-concept is provided with irrigated rice-maize systems at four locations in Bangladesh that represent a range of climatic conditions in that country. The proposed framework identified (i) realistic alternative cropping systems at each location, and (ii) two locations where expected improvements in crop production from changes in cropping intensity (number of crops per year) were 43% to 64% higher than from improving the management of individual crops within the current cropping systems. The proposed framework provides a tool to help assess food production capacity of new systems ( e.g. with increased cropping intensity) arising from climate change, and assess resource requirements (water and N) and associated environmental footprint per unit of land and production of these new systems. By expanding yield gap analysis from individual crops to the cropping system level and applying it to new systems, this framework could also be helpful to bridge the gap between yield gap analysis and cropping/farming system design.

Factors Affecting Firm Yield and the Estimation of Firm Yield for Selected Streamflow-Dominated Drinking-Water-Supply Reservoirs in Massachusetts

USGS Publications Warehouse

Waldron, Marcus C.; Archfield, Stacey A.

2006-01-01

Factors affecting reservoir firm yield, as determined by application of the Massachusetts Department of Environmental Protection's Firm Yield Estimator (FYE) model, were evaluated, modified, and tested on 46 streamflow-dominated reservoirs representing 15 Massachusetts drinking-water supplies. The model uses a mass-balance approach to determine the maximum average daily withdrawal rate that can be sustained during a period of record that includes the 1960s drought-of-record. The FYE methodology to estimate streamflow to the reservoir at an ungaged site was tested by simulating streamflow at two streamflow-gaging stations in Massachusetts and comparing the simulated streamflow to the observed streamflow. In general, the FYE-simulated flows agreed well with observed flows. There were substantial deviations from the measured values for extreme high and low flows. A sensitivity analysis determined that the model's streamflow estimates are most sensitive to input values for average annual precipitation, reservoir drainage area, and the soil-retention number-a term that describes the amount of precipitation retained by the soil in the basin. The FYE model currently provides the option of using a 1,000-year synthetic record constructed by randomly sampling 2-year blocks of concurrent streamflow and precipitation records 500 times; however, the synthetic record has the potential to generate records of precipitation and streamflow that do not reflect the worst historical drought in Massachusetts. For reservoirs that do not have periods of drawdown greater than 2 years, the bootstrap does not offer any additional information about the firm yield of a reservoir than the historical record does. For some reservoirs, the use of a synthetic record to determine firm yield resulted in as much as a 30-percent difference between firm-yield values from one simulation to the next. Furthermore, the assumption that the synthetic traces of streamflow are statistically equivalent to the

Explosive Yield Estimation using Fourier Amplitude Spectra of Velocity Histories

NASA Astrophysics Data System (ADS)

Steedman, D. W.; Bradley, C. R.

2016-12-01

The Source Physics Experiment (SPE) is a series of explosive shots of various size detonated at varying depths in a borehole in jointed granite. The testbed includes an extensive array of accelerometers for measuring the shock environment close-in to the explosive source. One goal of SPE is to develop greater understanding of the explosion phenomenology in all regimes: from near-source, non-linear response to the far-field linear elastic region, and connecting the analyses from the respective regimes. For example, near-field analysis typically involves review of kinematic response (i.e., acceleration, velocity and displacement) in the time domain and looks at various indicators (e.g., peaks, pulse duration) to facilitate comparison among events. Review of far-field data more often is based on study of response in the frequency domain to facilitate comparison of event magnitudes. To try to "bridge the gap" between approaches, we have developed a scaling law for Fourier amplitude spectra of near-field velocity histories that successfully collapses data from a wide range of yields (100 kg to 5000 kg) and range to sensors in jointed granite. Moreover, we show that we can apply this scaling law to data from a new event to accurately estimate the explosive yield of that event. This approach presents a new way of working with near-field data that will be more compatible with traditional methods of analysis of seismic data and should serve to facilitate end-to-end event analysis. The goal is that this new approach to data analysis will eventually result in improved methods for discrimination of event type (i.e., nuclear or chemical explosion, or earthquake) and magnitude.

Application of a rising plate meter to estimate forage yield on dairy farms in Pennsylvania

USDA-ARS?s Scientific Manuscript database

Accurately assessing pasture forage yield is necessary for producers who want to budget feed expenses and make informed pasture management decisions. Clipping and weighing forage from a known area is a direct method to measure pasture forage yield, however it is time consuming. The rising plate mete...

Study on paddy rice yield estimation based on multisource data and the Grey system theory

NASA Astrophysics Data System (ADS)

Deng, Wensheng; Wang, Wei; Liu, Hai; Li, Chen; Ge, Yimin; Zheng, Xianghua

2009-10-01

The paddy rice is our important crops. In study of the paddy rice yield estimation, compared with the scholars who usually only take the remote sensing data or meteorology as the influence factors, we combine the remote sensing and the meteorological data to make the monitoring result closer reality. Although the gray system theory has used in many aspects, it is applied very little in paddy rice yield estimation. This study introduces it to the paddy rice yield estimation, and makes the yield estimation model. This can resolve small data sets problem that can not be solved by deterministic model. It selects some regions in Jianghan plain for the study area. The data includes multi-temporal remote sensing image, meteorological and statistic data. The remote sensing data is the 16-day composite images (250-m spatial resolution) of MODIS. The meteorological data includes monthly average temperature, sunshine duration and rain fall amount. The statistical data is the long-term paddy rice yield of the study area. Firstly, it extracts the paddy rice planting area from the multi-temporal MODIS images with the help of GIS and RS. Then taking the paddy rice yield as the reference sequence, MODIS data and meteorological data as the comparative sequence, computing the gray correlative coefficient, it selects the yield estimation factor based on the grey system theory. Finally, using the factors, it establishes the yield estimation model and does the result test. The result indicated that the method is feasible and the conclusion is credible. It can provide the scientific method and reference value to carry on the region paddy rice remote sensing estimation.

Refinement and evaluation of the Massachusetts firm-yield estimator model version 2.0

USGS Publications Warehouse

Levin, Sara B.; Archfield, Stacey A.; Massey, Andrew J.

2011-01-01

to assess the sensitivity of firm-yield estimates to errors in daily-streamflow input data. Results of the Monte Carlo simulations indicate that underestimation in the lowest stream inflows can cause firm yields to be underestimated by an average of 1 to 10 percent. Errors in the stage-storage relation can arise when the point density of bathymetric survey measurements is too low. Existing bathymetric surfaces were resampled using hypothetical transects of varying patterns and point densities in order to quantify the uncertainty in stage-storage relations. Reservoir-volume calculations and resulting firm yields were accurate to within 5 percent when point densities were greater than 20 points per acre of reservoir surface. Methods for incorporating summer water-demand-reduction scenarios into the firm-yield model were developed as well as the ability to relax the no-fail reliability criterion. Although the original firm-yield model allowed monthly reservoir releases to be specified, there have been no previous studies examining the feasibility of controlled releases for downstream flows from Massachusetts reservoirs. Two controlled-release scenarios were tested—with and without a summer water-demand-reduction scenario—for a scenario with a no-fail criterion and a scenario that allows for a 1-percent failure rate over the entire simulation period. Based on these scenarios, about one-third of the reservoir systems were able to support the flow-release scenarios at their 2000–2004 usage rates. Reservoirs with higher storage ratios (reservoir storage capacity to mean annual streamflow) and lower demand ratios (mean annual water demand to annual firm yield) were capable of higher downstream release rates. For the purposes of this research, all reservoir systems were assumed to have structures which enable controlled releases, although this assumption may not be true for many of the reservoirs studied.

A Remote Sensing-Derived Corn Yield Assessment Model

NASA Astrophysics Data System (ADS)

Shrestha, Ranjay Man

Agricultural studies and food security have become critical research topics due to continuous growth in human population and simultaneous shrinkage in agricultural land. In spite of modern technological advancements to improve agricultural productivity, more studies on crop yield assessments and food productivities are still necessary to fulfill the constantly increasing food demands. Besides human activities, natural disasters such as flood and drought, along with rapid climate changes, also inflect an adverse effect on food productivities. Understanding the impact of these disasters on crop yield and making early impact estimations could help planning for any national or international food crisis. Similarly, the United States Department of Agriculture (USDA) Risk Management Agency (RMA) insurance management utilizes appropriately estimated crop yield and damage assessment information to sustain farmers' practice through timely and proper compensations. Through County Agricultural Production Survey (CAPS), the USDA National Agricultural Statistical Service (NASS) uses traditional methods of field interviews and farmer-reported survey data to perform annual crop condition monitoring and production estimations at the regional and state levels. As these manual approaches of yield estimations are highly inefficient and produce very limited samples to represent the entire area, NASS requires supplemental spatial data that provides continuous and timely information on crop production and annual yield. Compared to traditional methods, remote sensing data and products offer wider spatial extent, more accurate location information, higher temporal resolution and data distribution, and lower data cost--thus providing a complementary option for estimation of crop yield information. Remote sensing derived vegetation indices such as Normalized Difference Vegetation Index (NDVI) provide measurable statistics of potential crop growth based on the spectral reflectance and could

Waveform inversion of acoustic waves for explosion yield estimation

DOE PAGES

Kim, K.; Rodgers, A. J.

2016-07-08

We present a new waveform inversion technique to estimate the energy of near-surface explosions using atmospheric acoustic waves. Conventional methods often employ air blast models based on a homogeneous atmosphere, where the acoustic wave propagation effects (e.g., refraction and diffraction) are not taken into account, and therefore, their accuracy decreases with increasing source-receiver distance. In this study, three-dimensional acoustic simulations are performed with a finite difference method in realistic atmospheres and topography, and the modeled acoustic Green's functions are incorporated into the waveform inversion for the acoustic source time functions. The strength of the acoustic source is related to explosionmore » yield based on a standard air blast model. The technique was applied to local explosions (<10 km) and provided reasonable yield estimates (<~30% error) in the presence of realistic topography and atmospheric structure. In conclusion, the presented method can be extended to explosions recorded at far distance provided proper meteorological specifications.« less

Waveform inversion of acoustic waves for explosion yield estimation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, K.; Rodgers, A. J.

We present a new waveform inversion technique to estimate the energy of near-surface explosions using atmospheric acoustic waves. Conventional methods often employ air blast models based on a homogeneous atmosphere, where the acoustic wave propagation effects (e.g., refraction and diffraction) are not taken into account, and therefore, their accuracy decreases with increasing source-receiver distance. In this study, three-dimensional acoustic simulations are performed with a finite difference method in realistic atmospheres and topography, and the modeled acoustic Green's functions are incorporated into the waveform inversion for the acoustic source time functions. The strength of the acoustic source is related to explosionmore » yield based on a standard air blast model. The technique was applied to local explosions (<10 km) and provided reasonable yield estimates (<~30% error) in the presence of realistic topography and atmospheric structure. In conclusion, the presented method can be extended to explosions recorded at far distance provided proper meteorological specifications.« less

Effect of Anisotropic Yield Function Evolution on Estimation of Forming Limit Diagram

NASA Astrophysics Data System (ADS)

Bandyopadhyay, K.; Basak, S.; Choi, H. J.; Panda, S. K.; Lee, M. G.

2017-09-01

In case of theoretical prediction of the FLD, the variations in yield stress and R-values along different material directions, were long been implemented to enhance the accuracy. Although influences of different yield models and hardening laws on formability were well addressed, anisotropic evolution of yield loci under monotonic loading with different deformation modes is yet to be explored. In the present study, Marciniak-Kuckzinsky (M-K) model was modified to incorporate the change in the shape of the initial yield function with evolution due to anisotropic hardening. Swift’s hardening law along with two different anisotropic yield criteria, namely Hill48 and Yld2000-2d were implemented in the model. The Hill48 yield model was applied with non-associated flow rule to comprehend the effect of variations in both yield stress and R-values. The numerically estimated FLDs were validated after comparing with FLD evaluated through experiments. A low carbon steel was selected, and hemispherical punch stretching test was performed for FLD evaluation. Additionally, the numerically estimated FLDs were incorporated in FE simulations to predict limiting dome heights for validation purpose. Other formability performances like strain distributions over the deformed cup surface were validated with experimental results.

A spectral-spatial-dynamic hierarchical Bayesian (SSD-HB) model for estimating soybean yield

NASA Astrophysics Data System (ADS)

Kazama, Yoriko; Kujirai, Toshihiro

2014-10-01

A method called a "spectral-spatial-dynamic hierarchical-Bayesian (SSD-HB) model," which can deal with many parameters (such as spectral and weather information all together) by reducing the occurrence of multicollinearity, is proposed. Experiments conducted on soybean yields in Brazil fields with a RapidEye satellite image indicate that the proposed SSD-HB model can predict soybean yield with a higher degree of accuracy than other estimation methods commonly used in remote-sensing applications. In the case of the SSD-HB model, the mean absolute error between estimated yield of the target area and actual yield is 0.28 t/ha, compared to 0.34 t/ha when conventional PLS regression was applied, showing the potential effectiveness of the proposed model.

Estimated suspended-sediment loads and yields in the French and Brandywine Creek Basins, Chester County, Pennsylvania, water years 2008-09

USGS Publications Warehouse

Sloto, Ronald A.; Olson, Leif E.

2011-01-01

Turbidity and suspended-sediment concentration data were collected by the U.S. Geological Survey (USGS) at four stream stations--French Creek near Phoenixville, West Branch Brandywine Creek near Honey Brook, West Branch Brandywine Creek at Modena, and East Branch Brandywine Creek below Downingtown--in Chester County, Pa. Sedimentation and siltation is the leading cause of stream impairment in Chester County, and these data are critical for quantifying sediment transport. This study was conducted by the USGS in cooperation with the Chester County Water Resources Authority and the Chester County Health Department. Data from optical turbidity sensors deployed at the four stations were recorded at 15- or 30-minute intervals by a data logger and uploaded every 1 to 4 hours to the USGS database. Most of the suspended-sediment samples were collected using automated samplers. The use of optical sensors to continuously monitor turbidity provided an accurate estimate of sediment fluctuations without the collection and analysis costs associated with intensive sampling during storms. Turbidity was used as a surrogate for suspended-sediment concentration (SSC), which is a measure of sedimentation and siltation. Regression models were developed between SSC and turbidity for each of the monitoring stations using SSC data collected from the automated samplers and turbidity data collected at each station. Instantaneous suspended-sediment loads (SSL) were computed from time-series turbidity and discharge data for the 2008 and 2009 water years using the regression equations. The instantaneous computations of SSL were summed to provide daily, storm, and water year annual loads. The annual SSL contributed from each basin was divided by the upstream drainage area to estimate the annual sediment yield. For all four basins, storms provided more than 96 percent of the annual SSL. In each basin, four storms generally provided over half the annual SSL each water year. Stormflows with the

On the accurate estimation of gap fraction during daytime with digital cover photography

NASA Astrophysics Data System (ADS)

Hwang, Y. R.; Ryu, Y.; Kimm, H.; Macfarlane, C.; Lang, M.; Sonnentag, O.

2015-12-01

Digital cover photography (DCP) has emerged as an indirect method to obtain gap fraction accurately. Thus far, however, the intervention of subjectivity, such as determining the camera relative exposure value (REV) and threshold in the histogram, hindered computing accurate gap fraction. Here we propose a novel method that enables us to measure gap fraction accurately during daytime under various sky conditions by DCP. The novel method computes gap fraction using a single DCP unsaturated raw image which is corrected for scattering effects by canopies and a reconstructed sky image from the raw format image. To test the sensitivity of the novel method derived gap fraction to diverse REVs, solar zenith angles and canopy structures, we took photos in one hour interval between sunrise to midday under dense and sparse canopies with REV 0 to -5. The novel method showed little variation of gap fraction across different REVs in both dense and spares canopies across diverse range of solar zenith angles. The perforated panel experiment, which was used to test the accuracy of the estimated gap fraction, confirmed that the novel method resulted in the accurate and consistent gap fractions across different hole sizes, gap fractions and solar zenith angles. These findings highlight that the novel method opens new opportunities to estimate gap fraction accurately during daytime from sparse to dense canopies, which will be useful in monitoring LAI precisely and validating satellite remote sensing LAI products efficiently.

Estimating the Effective Permittivity for Reconstructing Accurate Microwave-Radar Images.

PubMed

Lavoie, Benjamin R; Okoniewski, Michal; Fear, Elise C

2016-01-01

We present preliminary results from a method for estimating the optimal effective permittivity for reconstructing microwave-radar images. Using knowledge of how microwave-radar images are formed, we identify characteristics that are typical of good images, and define a fitness function to measure the relative image quality. We build a polynomial interpolant of the fitness function in order to identify the most likely permittivity values of the tissue. To make the estimation process more efficient, the polynomial interpolant is constructed using a locally and dimensionally adaptive sampling method that is a novel combination of stochastic collocation and polynomial chaos. Examples, using a series of simulated, experimental and patient data collected using the Tissue Sensing Adaptive Radar system, which is under development at the University of Calgary, are presented. These examples show how, using our method, accurate images can be reconstructed starting with only a broad estimate of the permittivity range.

Yield gap analyses to estimate attainable bovine milk yields and evaluate options to increase production in Ethiopia and India.

PubMed

Mayberry, Dianne; Ash, Andrew; Prestwidge, Di; Godde, Cécile M; Henderson, Ben; Duncan, Alan; Blummel, Michael; Ramana Reddy, Y; Herrero, Mario

2017-07-01

Livestock provides an important source of income and nourishment for around one billion rural households worldwide. Demand for livestock food products is increasing, especially in developing countries, and there are opportunities to increase production to meet local demand and increase farm incomes. Estimating the scale of livestock yield gaps and better understanding factors limiting current production will help to define the technological and investment needs in each livestock sector. The aim of this paper is to quantify livestock yield gaps and evaluate opportunities to increase dairy production in Sub-Saharan Africa and South Asia, using case studies from Ethiopia and India. We combined three different methods in our approach. Benchmarking and a frontier analysis were used to estimate attainable milk yields based on survey data. Household modelling was then used to simulate the effects of various interventions on dairy production and income. We tested interventions based on improved livestock nutrition and genetics in the extensive lowland grazing zone and highland mixed crop-livestock zones of Ethiopia, and the intensive irrigated and rainfed zones of India. Our analyses indicate that there are considerable yield gaps for dairy production in both countries, and opportunities to increase production using the interventions tested. In some cases, combined interventions could increase production past currently attainable livestock yields.

Covariance Matrix Evaluations for Independent Mass Fission Yields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Terranova, N., E-mail: nicholas.terranova@unibo.it; Serot, O.; Archier, P.

2015-01-15

Recent needs for more accurate fission product yields include covariance information to allow improved uncertainty estimations of the parameters used by design codes. The aim of this work is to investigate the possibility to generate more reliable and complete uncertainty information on independent mass fission yields. Mass yields covariances are estimated through a convolution between the multi-Gaussian empirical model based on Brosa's fission modes, which describe the pre-neutron mass yields, and the average prompt neutron multiplicity curve. The covariance generation task has been approached using the Bayesian generalized least squared method through the CONRAD code. Preliminary results on mass yieldsmore » variance-covariance matrix will be presented and discussed from physical grounds in the case of {sup 235}U(n{sub th}, f) and {sup 239}Pu(n{sub th}, f) reactions.« less

Winter wheat yield estimation of remote sensing research based on WOFOST crop model and leaf area index assimilation

NASA Astrophysics Data System (ADS)

Chen, Yanling; Gong, Adu; Li, Jing; Wang, Jingmei

2017-04-01

Accurate crop growth monitoring and yield predictive information are significant to improve the sustainable development of agriculture and ensure the security of national food. Remote sensing observation and crop growth simulation models are two new technologies, which have highly potential applications in crop growth monitoring and yield forecasting in recent years. However, both of them have limitations in mechanism or regional application respectively. Remote sensing information can not reveal crop growth and development, inner mechanism of yield formation and the affection of environmental meteorological conditions. Crop growth simulation models have difficulties in obtaining data and parameterization from single-point to regional application. In order to make good use of the advantages of these two technologies, the coupling technique of remote sensing information and crop growth simulation models has been studied. Filtering and optimizing model parameters are key to yield estimation by remote sensing and crop model based on regional crop assimilation. Winter wheat of GaoCheng was selected as the experiment object in this paper. And then the essential data was collected, such as biochemical data and farmland environmental data and meteorological data about several critical growing periods. Meanwhile, the image of environmental mitigation small satellite HJ-CCD was obtained. In this paper, research work and major conclusions are as follows. (1) Seven vegetation indexes were selected to retrieve LAI, and then linear regression model was built up between each of these indexes and the measured LAI. The result shows that the accuracy of EVI model was the highest (R2=0.964 at anthesis stage and R2=0.920 at filling stage). Thus, EVI as the most optimal vegetation index to predict LAI in this paper. (2) EFAST method was adopted in this paper to conduct the sensitive analysis to the 26 initial parameters of the WOFOST model and then a sensitivity index was constructed

Estimating variability in grain legume yields across Europe and the Americas

NASA Astrophysics Data System (ADS)

Cernay, Charles; Ben-Ari, Tamara; Pelzer, Elise; Meynard, Jean-Marc; Makowski, David

2015-06-01

Grain legume production in Europe has recently come under scrutiny. Although legume crops are often promoted to provide environmental services, European farmers tend to turn to non-legume crops. It is assumed that high variability in legume yields explains this aversion, but so far this hypothesis has not been tested. Here, we estimate the variability of major grain legume and non-legume yields in Europe and the Americas from yield time series over 1961-2013. Results show that grain legume yields are significantly more variable than non-legume yields in Europe. These differences are smaller in the Americas. Our results are robust at the level of the statistical methods. In all regions, crops with high yield variability are allocated to less than 1% of cultivated areas. Although the expansion of grain legumes in Europe may be hindered by high yield variability, some species display risk levels compatible with the development of specialized supply chains.

Combined inverse-forward artificial neural networks for fast and accurate estimation of the diffusion coefficients of cartilage based on multi-physics models.

PubMed

Arbabi, Vahid; Pouran, Behdad; Weinans, Harrie; Zadpoor, Amir A

2016-09-06

Analytical and numerical methods have been used to extract essential engineering parameters such as elastic modulus, Poisson׳s ratio, permeability and diffusion coefficient from experimental data in various types of biological tissues. The major limitation associated with analytical techniques is that they are often only applicable to problems with simplified assumptions. Numerical multi-physics methods, on the other hand, enable minimizing the simplified assumptions but require substantial computational expertise, which is not always available. In this paper, we propose a novel approach that combines inverse and forward artificial neural networks (ANNs) which enables fast and accurate estimation of the diffusion coefficient of cartilage without any need for computational modeling. In this approach, an inverse ANN is trained using our multi-zone biphasic-solute finite-bath computational model of diffusion in cartilage to estimate the diffusion coefficient of the various zones of cartilage given the concentration-time curves. Robust estimation of the diffusion coefficients, however, requires introducing certain levels of stochastic variations during the training process. Determining the required level of stochastic variation is performed by coupling the inverse ANN with a forward ANN that receives the diffusion coefficient as input and returns the concentration-time curve as output. Combined together, forward-inverse ANNs enable computationally inexperienced users to obtain accurate and fast estimation of the diffusion coefficients of cartilage zones. The diffusion coefficients estimated using the proposed approach are compared with those determined using direct scanning of the parameter space as the optimization approach. It has been shown that both approaches yield comparable results. Copyright © 2016 Elsevier Ltd. All rights reserved.

Quasi-closed phase forward-backward linear prediction analysis of speech for accurate formant detection and estimation.

PubMed

Gowda, Dhananjaya; Airaksinen, Manu; Alku, Paavo

2017-09-01

Recently, a quasi-closed phase (QCP) analysis of speech signals for accurate glottal inverse filtering was proposed. However, the QCP analysis which belongs to the family of temporally weighted linear prediction (WLP) methods uses the conventional forward type of sample prediction. This may not be the best choice especially in computing WLP models with a hard-limiting weighting function. A sample selective minimization of the prediction error in WLP reduces the effective number of samples available within a given window frame. To counter this problem, a modified quasi-closed phase forward-backward (QCP-FB) analysis is proposed, wherein each sample is predicted based on its past as well as future samples thereby utilizing the available number of samples more effectively. Formant detection and estimation experiments on synthetic vowels generated using a physical modeling approach as well as natural speech utterances show that the proposed QCP-FB method yields statistically significant improvements over the conventional linear prediction and QCP methods.

Sustainable-yield estimation for the Sparta Aquifer in Union County, Arkansas

USGS Publications Warehouse

Hays, Phillip D.

2000-01-01

Options for utilizing alternative sources of water to alleviate overdraft from the Sparta aquifer and ensure that the aquifer can continue to provide abundant water of excellent quality for the future are being evaluated by water managers in Union County. Sustainable yield is a critical element in identifying and designing viable water supply alternatives. With sustainable yield defined and a knowledge of total water demand in an area, any unmet demand can be calculated. The ground-water flow model of the Sparta aquifer was used to estimate sustainable yield using an iterative approach. The Sparta aquifer is a confined aquifer of regional importance that comprises a sequence of unconsolidated sand units that are contained within the Sparta Sand. Currently, the rate of withdrawal in some areas greatly exceeds the rate of recharge to the aquifer and considerable water-level declines have occurred. Ground-water flow model results indicate that the aquifer cannot continue to meet growing water-use demands indefinitely and that water levels will drop below the top of the primary producing sand unit in Union County (locally termed the El Dorado sand) by 2008 if current water-use trends continue. Declines of that magnitude will initiate dewatering of the El Dorado sand. The sustainable yield of the aquifer was calculated by targeting a specified minimum acceptable water level within Union County and varying Union County pumpage within the model to achieve the target water level. Selection of the minimum target water level for sustainable-yield estimation was an important criterion for the modeling effort. In keeping with the State Critical Ground-Water Area designation criteria and the desire of water managers in Union County to improve aquifer conditions and bring the area out of the Critical Ground-Water Area designation, the approximate altitude of the top of the Sparta Sand in central Union County was used as the minimum water level target for estimation of

Accurate quantum yields by laser gain vs absorption spectroscopy - Investigation of Br/Br(asterisk) channels in photofragmentation of Br2 and IBr

NASA Technical Reports Server (NTRS)

Haugen, H. K.; Weitz, E.; Leone, S. R.

1985-01-01

Various techniques have been used to study photodissociation dynamics of the halogens and interhalogens. The quantum yields obtained by these techniques differ widely. The present investigation is concerned with a qualitatively new approach for obtaining highly accurate quantum yields for electronically excited states. This approach makes it possible to obtain an accuracy of 1 percent to 3 percent. It is shown that measurement of the initial transient gain/absorption vs the final absorption in a single time-resolved signal is a very accurate technique in the study of absolute branching fractions in photodissociation. The new technique is found to be insensitive to pulse and probe laser characteristics, molecular absorption cross sections, and absolute precursor density.

The description of a method for accurately estimating creatinine clearance in acute kidney injury.

PubMed

Mellas, John

2016-05-01

Acute kidney injury (AKI) is a common and serious condition encountered in hospitalized patients. The severity of kidney injury is defined by the RIFLE, AKIN, and KDIGO criteria which attempt to establish the degree of renal impairment. The KDIGO guidelines state that the creatinine clearance should be measured whenever possible in AKI and that the serum creatinine concentration and creatinine clearance remain the best clinical indicators of renal function. Neither the RIFLE, AKIN, nor KDIGO criteria estimate actual creatinine clearance. Furthermore there are no accepted methods for accurately estimating creatinine clearance (K) in AKI. The present study describes a unique method for estimating K in AKI using urine creatinine excretion over an established time interval (E), an estimate of creatinine production over the same time interval (P), and the estimated static glomerular filtration rate (sGFR), at time zero, utilizing the CKD-EPI formula. Using these variables estimated creatinine clearance (Ke)=E/P * sGFR. The method was tested for validity using simulated patients where actual creatinine clearance (Ka) was compared to Ke in several patients, both male and female, and of various ages, body weights, and degrees of renal impairment. These measurements were made at several serum creatinine concentrations in an attempt to determine the accuracy of this method in the non-steady state. In addition E/P and Ke was calculated in hospitalized patients, with AKI, and seen in nephrology consultation by the author. In these patients the accuracy of the method was determined by looking at the following metrics; E/P>1, E/P<1, E=P in an attempt to predict progressive azotemia, recovering azotemia, or stabilization in the level of azotemia respectively. In addition it was determined whether Ke<10 ml/min agreed with Ka and whether patients with AKI on renal replacement therapy could safely terminate dialysis if Ke was greater than 5 ml/min. In the simulated patients there

A method to accurately estimate the muscular torques of human wearing exoskeletons by torque sensors.

PubMed

Hwang, Beomsoo; Jeon, Doyoung

2015-04-09

In exoskeletal robots, the quantification of the user's muscular effort is important to recognize the user's motion intentions and evaluate motor abilities. In this paper, we attempt to estimate users' muscular efforts accurately using joint torque sensor which contains the measurements of dynamic effect of human body such as the inertial, Coriolis, and gravitational torques as well as torque by active muscular effort. It is important to extract the dynamic effects of the user's limb accurately from the measured torque. The user's limb dynamics are formulated and a convenient method of identifying user-specific parameters is suggested for estimating the user's muscular torque in robotic exoskeletons. Experiments were carried out on a wheelchair-integrated lower limb exoskeleton, EXOwheel, which was equipped with torque sensors in the hip and knee joints. The proposed methods were evaluated by 10 healthy participants during body weight-supported gait training. The experimental results show that the torque sensors are to estimate the muscular torque accurately in cases of relaxed and activated muscle conditions.

A Method to Accurately Estimate the Muscular Torques of Human Wearing Exoskeletons by Torque Sensors

PubMed Central

Hwang, Beomsoo; Jeon, Doyoung

2015-01-01

In exoskeletal robots, the quantification of the user’s muscular effort is important to recognize the user’s motion intentions and evaluate motor abilities. In this paper, we attempt to estimate users’ muscular efforts accurately using joint torque sensor which contains the measurements of dynamic effect of human body such as the inertial, Coriolis, and gravitational torques as well as torque by active muscular effort. It is important to extract the dynamic effects of the user’s limb accurately from the measured torque. The user’s limb dynamics are formulated and a convenient method of identifying user-specific parameters is suggested for estimating the user’s muscular torque in robotic exoskeletons. Experiments were carried out on a wheelchair-integrated lower limb exoskeleton, EXOwheel, which was equipped with torque sensors in the hip and knee joints. The proposed methods were evaluated by 10 healthy participants during body weight-supported gait training. The experimental results show that the torque sensors are to estimate the muscular torque accurately in cases of relaxed and activated muscle conditions. PMID:25860074

A robust and accurate center-frequency estimation (RACE) algorithm for improving motion estimation performance of SinMod on tagged cardiac MR images without known tagging parameters.

PubMed

Liu, Hong; Wang, Jie; Xu, Xiangyang; Song, Enmin; Wang, Qian; Jin, Renchao; Hung, Chih-Cheng; Fei, Baowei

2014-11-01

A robust and accurate center-frequency (CF) estimation (RACE) algorithm for improving the performance of the local sine-wave modeling (SinMod) method, which is a good motion estimation method for tagged cardiac magnetic resonance (MR) images, is proposed in this study. The RACE algorithm can automatically, effectively and efficiently produce a very appropriate CF estimate for the SinMod method, under the circumstance that the specified tagging parameters are unknown, on account of the following two key techniques: (1) the well-known mean-shift algorithm, which can provide accurate and rapid CF estimation; and (2) an original two-direction-combination strategy, which can further enhance the accuracy and robustness of CF estimation. Some other available CF estimation algorithms are brought out for comparison. Several validation approaches that can work on the real data without ground truths are specially designed. Experimental results on human body in vivo cardiac data demonstrate the significance of accurate CF estimation for SinMod, and validate the effectiveness of RACE in facilitating the motion estimation performance of SinMod. Copyright © 2014 Elsevier Inc. All rights reserved.

Atmospheric Fluorescence Yield

NASA Technical Reports Server (NTRS)

Adams, James H., Jr.; Christl, M. J.; Fountain, W. F.; Gregory, J. C.; Martens, K.; Sokolsky, P.; Whitaker, Ann F. (Technical Monitor)

2001-01-01

Several existing and planned experiments estimate the energies of ultra-high energy cosmic rays from air showers using the atmospheric fluorescence from these showers. Accurate knowledge of the conversion from atmospheric fluorescence to energy loss by ionizing particles in the atmosphere is key to this technique. In this paper we discuss a small balloon-borne instrument to make the first in situ measurements versus altitude of the atmospheric fluorescence yield. The instrument can also be used in the lab to investigate the dependence of the fluorescence yield in air on temperature, pressure and the concentrations of other gases that present in the atmosphere. The results can be used to explore environmental effects on and improve the accuracy of cosmic ray energy measurements for existing ground-based experiments and future space-based experiments.

Evaluating accuracy of DSSAT model for soybean yield estimation using satellite weather data

NASA Astrophysics Data System (ADS)

Ovando, Gustavo; Sayago, Silvina; Bocco, Mónica

2018-04-01

Crop models allow simulating the development and yield of the crops, to represent and to evaluate the influence of multiple factors. The DSSAT cropping system model is one of the most widely used and contains CROPGRO module for soybean. This crop has a great importance for many southern countries of Latin America and for Argentina. Solar radiation and rainfall are necessary variables as inputs for crop models; however these data are not as readily available. The satellital products from Clouds and Earth's Radiant Energy System (CERES) and Tropic Rainfall Measurement Mission (TRMM) provide continuous spatial and temporal information of solar radiation and precipitation, respectively. This study evaluates and quantifies the uncertainty in estimating soybean yield using a DSSAT model, when recorded weather data are replaced with CERES and TRMM ones. Different percentages of data replacements, soybean maturity groups and planting dates are considered, for 2006-2016 period in Oliveros (Argentina). Results show that CERES and TRMM products can be used for soybean yield estimation with DSSAT considering that: percentage of data replacement, campaign, planting date and maturity group, determine the amounts and trends of yield errors. Replacements with CERES data up to 30% result in %RMSE lower than 10% in 87% of the cases; while the replacement with TRMM data presents the best statisticals in campaigns with high yields. Simulations based entirely on CERES solar radiation give better results than those with TRMM. In general, similar percentages of replacement show better performance in the estimation of soybean yield for solar radiation than the replacement of precipitation values.

A fast and accurate frequency estimation algorithm for sinusoidal signal with harmonic components

NASA Astrophysics Data System (ADS)

Hu, Jinghua; Pan, Mengchun; Zeng, Zhidun; Hu, Jiafei; Chen, Dixiang; Tian, Wugang; Zhao, Jianqiang; Du, Qingfa

2016-10-01

Frequency estimation is a fundamental problem in many applications, such as traditional vibration measurement, power system supervision, and microelectromechanical system sensors control. In this paper, a fast and accurate frequency estimation algorithm is proposed to deal with low efficiency problem in traditional methods. The proposed algorithm consists of coarse and fine frequency estimation steps, and we demonstrate that it is more efficient than conventional searching methods to achieve coarse frequency estimation (location peak of FFT amplitude) by applying modified zero-crossing technique. Thus, the proposed estimation algorithm requires less hardware and software sources and can achieve even higher efficiency when the experimental data increase. Experimental results with modulated magnetic signal show that the root mean square error of frequency estimation is below 0.032 Hz with the proposed algorithm, which has lower computational complexity and better global performance than conventional frequency estimation methods.

Calibrating SALT: a sampling scheme to improve estimates of suspended sediment yield

Treesearch

Robert B. Thomas

1986-01-01

Abstract - SALT (Selection At List Time) is a variable probability sampling scheme that provides unbiased estimates of suspended sediment yield and its variance. SALT performs better than standard schemes which are estimate variance. Sampling probabilities are based on a sediment rating function which promotes greater sampling intensity during periods of high...

Lamb mode selection for accurate wall loss estimation via guided wave tomography

NASA Astrophysics Data System (ADS)

Huthwaite, P.; Ribichini, R.; Lowe, M. J. S.; Cawley, P.

2014-02-01

Guided wave tomography offers a method to accurately quantify wall thickness losses in pipes and vessels caused by corrosion. This is achieved using ultrasonic waves transmitted over distances of approximately 1-2m, which are measured by an array of transducers and then used to reconstruct a map of wall thickness throughout the inspected region. To achieve accurate estimations of remnant wall thickness, it is vital that a suitable Lamb mode is chosen. This paper presents a detailed evaluation of the fundamental modes, S0 and A0, which are of primary interest in guided wave tomography thickness estimates since the higher order modes do not exist at all thicknesses, to compare their performance using both numerical and experimental data while considering a range of challenging phenomena. The sensitivity of A0 to thickness variations was shown to be superior to S0, however, the attenuation from A0 when a liquid loading was present was much higher than S0. A0 was less sensitive to the presence of coatings on the surface of than S0.

SATe-II: very fast and accurate simultaneous estimation of multiple sequence alignments and phylogenetic trees.

PubMed

Liu, Kevin; Warnow, Tandy J; Holder, Mark T; Nelesen, Serita M; Yu, Jiaye; Stamatakis, Alexandros P; Linder, C Randal

2012-01-01

Highly accurate estimation of phylogenetic trees for large data sets is difficult, in part because multiple sequence alignments must be accurate for phylogeny estimation methods to be accurate. Coestimation of alignments and trees has been attempted but currently only SATé estimates reasonably accurate trees and alignments for large data sets in practical time frames (Liu K., Raghavan S., Nelesen S., Linder C.R., Warnow T. 2009b. Rapid and accurate large-scale coestimation of sequence alignments and phylogenetic trees. Science. 324:1561-1564). Here, we present a modification to the original SATé algorithm that improves upon SATé (which we now call SATé-I) in terms of speed and of phylogenetic and alignment accuracy. SATé-II uses a different divide-and-conquer strategy than SATé-I and so produces smaller more closely related subsets than SATé-I; as a result, SATé-II produces more accurate alignments and trees, can analyze larger data sets, and runs more efficiently than SATé-I. Generally, SATé is a metamethod that takes an existing multiple sequence alignment method as an input parameter and boosts the quality of that alignment method. SATé-II-boosted alignment methods are significantly more accurate than their unboosted versions, and trees based upon these improved alignments are more accurate than trees based upon the original alignments. Because SATé-I used maximum likelihood (ML) methods that treat gaps as missing data to estimate trees and because we found a correlation between the quality of tree/alignment pairs and ML scores, we explored the degree to which SATé's performance depends on using ML with gaps treated as missing data to determine the best tree/alignment pair. We present two lines of evidence that using ML with gaps treated as missing data to optimize the alignment and tree produces very poor results. First, we show that the optimization problem where a set of unaligned DNA sequences is given and the output is the tree and alignment of

Similar Estimates of Temperature Impacts on Global Wheat Yield by Three Independent Methods

NASA Technical Reports Server (NTRS)

Liu, Bing; Asseng, Senthold; Muller, Christoph; Ewart, Frank; Elliott, Joshua; Lobell, David B.; Martre, Pierre; Ruane, Alex C.; Wallach, Daniel; Jones, James W.;

Similar estimates of temperature impacts on global wheat yield by three independent methods

NASA Astrophysics Data System (ADS)

Liu, Bing; Asseng, Senthold; Müller, Christoph; Ewert, Frank; Elliott, Joshua; Lobell, David B.; Martre, Pierre; Ruane, Alex C.; Wallach, Daniel; Jones, James W.; Rosenzweig, Cynthia; Aggarwal, Pramod K.; Alderman, Phillip D.; Anothai, Jakarat; Basso, Bruno; Biernath, Christian; Cammarano, Davide; Challinor, Andy; Deryng, Delphine; Sanctis, Giacomo De; Doltra, Jordi; Fereres, Elias; Folberth, Christian; Garcia-Vila, Margarita; Gayler, Sebastian; Hoogenboom, Gerrit; Hunt, Leslie A.; Izaurralde, Roberto C.; Jabloun, Mohamed; Jones, Curtis D.; Kersebaum, Kurt C.; Kimball, Bruce A.; Koehler, Ann-Kristin; Kumar, Soora Naresh; Nendel, Claas; O'Leary, Garry J.; Olesen, Jørgen E.; Ottman, Michael J.; Palosuo, Taru; Prasad, P. V. Vara; Priesack, Eckart; Pugh, Thomas A. M.; Reynolds, Matthew; Rezaei, Ehsan E.; Rötter, Reimund P.; Schmid, Erwin; Semenov, Mikhail A.; Shcherbak, Iurii; Stehfest, Elke; Stöckle, Claudio O.; Stratonovitch, Pierre; Streck, Thilo; Supit, Iwan; Tao, Fulu; Thorburn, Peter; Waha, Katharina; Wall, Gerard W.; Wang, Enli; White, Jeffrey W.; Wolf, Joost; Zhao, Zhigan; Zhu, Yan

2016-12-01

The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO2 fertilization effects, produce similar estimates of temperature impact on wheat yields at global and national scales. With a 1 °C global temperature increase, global wheat yield is projected to decline between 4.1% and 6.4%. Projected relative temperature impacts from different methods were similar for major wheat-producing countries China, India, USA and France, but less so for Russia. Point-based and grid-based simulations, and to some extent the statistical regressions, were consistent in projecting that warmer regions are likely to suffer more yield loss with increasing temperature than cooler regions. By forming a multi-method ensemble, it was possible to quantify `method uncertainty’ in addition to model uncertainty. This significantly improves confidence in estimates of climate impacts on global food security.

Serial fusion of Eulerian and Lagrangian approaches for accurate heart-rate estimation using face videos.

PubMed

Gupta, Puneet; Bhowmick, Brojeshwar; Pal, Arpan

2017-07-01

Camera-equipped devices are ubiquitous and proliferating in the day-to-day life. Accurate heart rate (HR) estimation from the face videos acquired from the low cost cameras in a non-contact manner, can be used in many real-world scenarios and hence, require rigorous exploration. This paper has presented an accurate and near real-time HR estimation system using these face videos. It is based on the phenomenon that the color and motion variations in the face video are closely related to the heart beat. The variations also contain the noise due to facial expressions, respiration, eye blinking and environmental factors which are handled by the proposed system. Neither Eulerian nor Lagrangian temporal signals can provide accurate HR in all the cases. The cases where Eulerian temporal signals perform spuriously are determined using a novel poorness measure and then both the Eulerian and Lagrangian temporal signals are employed for better HR estimation. Such a fusion is referred as serial fusion. Experimental results reveal that the error introduced in the proposed algorithm is 1.8±3.6 which is significantly lower than the existing well known systems.

Accurate Initial State Estimation in a Monocular Visual–Inertial SLAM System

PubMed Central

Chen, Jing; Zhou, Zixiang; Leng, Zhen; Fan, Lei

2018-01-01

The fusion of monocular visual and inertial cues has become popular in robotics, unmanned vehicles and augmented reality fields. Recent results have shown that optimization-based fusion strategies outperform filtering strategies. Robust state estimation is the core capability for optimization-based visual–inertial Simultaneous Localization and Mapping (SLAM) systems. As a result of the nonlinearity of visual–inertial systems, the performance heavily relies on the accuracy of initial values (visual scale, gravity, velocity and Inertial Measurement Unit (IMU) biases). Therefore, this paper aims to propose a more accurate initial state estimation method. On the basis of the known gravity magnitude, we propose an approach to refine the estimated gravity vector by optimizing the two-dimensional (2D) error state on its tangent space, then estimate the accelerometer bias separately, which is difficult to be distinguished under small rotation. Additionally, we propose an automatic termination criterion to determine when the initialization is successful. Once the initial state estimation converges, the initial estimated values are used to launch the nonlinear tightly coupled visual–inertial SLAM system. We have tested our approaches with the public EuRoC dataset. Experimental results show that the proposed methods can achieve good initial state estimation, the gravity refinement approach is able to efficiently speed up the convergence process of the estimated gravity vector, and the termination criterion performs well. PMID:29419751

Novel serologic biomarkers provide accurate estimates of recent Plasmodium falciparum exposure for individuals and communities

PubMed Central

Helb, Danica A.; Tetteh, Kevin K. A.; Felgner, Philip L.; Skinner, Jeff; Hubbard, Alan; Arinaitwe, Emmanuel; Mayanja-Kizza, Harriet; Ssewanyana, Isaac; Kamya, Moses R.; Beeson, James G.; Tappero, Jordan; Smith, David L.; Crompton, Peter D.; Rosenthal, Philip J.; Dorsey, Grant; Drakeley, Christopher J.; Greenhouse, Bryan

2015-01-01

Tools to reliably measure Plasmodium falciparum (Pf) exposure in individuals and communities are needed to guide and evaluate malaria control interventions. Serologic assays can potentially produce precise exposure estimates at low cost; however, current approaches based on responses to a few characterized antigens are not designed to estimate exposure in individuals. Pf-specific antibody responses differ by antigen, suggesting that selection of antigens with defined kinetic profiles will improve estimates of Pf exposure. To identify novel serologic biomarkers of malaria exposure, we evaluated responses to 856 Pf antigens by protein microarray in 186 Ugandan children, for whom detailed Pf exposure data were available. Using data-adaptive statistical methods, we identified combinations of antibody responses that maximized information on an individual’s recent exposure. Responses to three novel Pf antigens accurately classified whether an individual had been infected within the last 30, 90, or 365 d (cross-validated area under the curve = 0.86–0.93), whereas responses to six antigens accurately estimated an individual’s malaria incidence in the prior year. Cross-validated incidence predictions for individuals in different communities provided accurate stratification of exposure between populations and suggest that precise estimates of community exposure can be obtained from sampling a small subset of that community. In addition, serologic incidence predictions from cross-sectional samples characterized heterogeneity within a community similarly to 1 y of continuous passive surveillance. Development of simple ELISA-based assays derived from the successful selection strategy outlined here offers the potential to generate rich epidemiologic surveillance data that will be widely accessible to malaria control programs. PMID:26216993

Novel serologic biomarkers provide accurate estimates of recent Plasmodium falciparum exposure for individuals and communities.

PubMed

Helb, Danica A; Tetteh, Kevin K A; Felgner, Philip L; Skinner, Jeff; Hubbard, Alan; Arinaitwe, Emmanuel; Mayanja-Kizza, Harriet; Ssewanyana, Isaac; Kamya, Moses R; Beeson, James G; Tappero, Jordan; Smith, David L; Crompton, Peter D; Rosenthal, Philip J; Dorsey, Grant; Drakeley, Christopher J; Greenhouse, Bryan

2015-08-11

Tools to reliably measure Plasmodium falciparum (Pf) exposure in individuals and communities are needed to guide and evaluate malaria control interventions. Serologic assays can potentially produce precise exposure estimates at low cost; however, current approaches based on responses to a few characterized antigens are not designed to estimate exposure in individuals. Pf-specific antibody responses differ by antigen, suggesting that selection of antigens with defined kinetic profiles will improve estimates of Pf exposure. To identify novel serologic biomarkers of malaria exposure, we evaluated responses to 856 Pf antigens by protein microarray in 186 Ugandan children, for whom detailed Pf exposure data were available. Using data-adaptive statistical methods, we identified combinations of antibody responses that maximized information on an individual's recent exposure. Responses to three novel Pf antigens accurately classified whether an individual had been infected within the last 30, 90, or 365 d (cross-validated area under the curve = 0.86-0.93), whereas responses to six antigens accurately estimated an individual's malaria incidence in the prior year. Cross-validated incidence predictions for individuals in different communities provided accurate stratification of exposure between populations and suggest that precise estimates of community exposure can be obtained from sampling a small subset of that community. In addition, serologic incidence predictions from cross-sectional samples characterized heterogeneity within a community similarly to 1 y of continuous passive surveillance. Development of simple ELISA-based assays derived from the successful selection strategy outlined here offers the potential to generate rich epidemiologic surveillance data that will be widely accessible to malaria control programs.

Accurate Attitude Estimation Using ARS under Conditions of Vehicle Movement Based on Disturbance Acceleration Adaptive Estimation and Correction

PubMed Central

Xing, Li; Hang, Yijun; Xiong, Zhi; Liu, Jianye; Wan, Zhong

2016-01-01

This paper describes a disturbance acceleration adaptive estimate and correction approach for an attitude reference system (ARS) so as to improve the attitude estimate precision under vehicle movement conditions. The proposed approach depends on a Kalman filter, where the attitude error, the gyroscope zero offset error and the disturbance acceleration error are estimated. By switching the filter decay coefficient of the disturbance acceleration model in different acceleration modes, the disturbance acceleration is adaptively estimated and corrected, and then the attitude estimate precision is improved. The filter was tested in three different disturbance acceleration modes (non-acceleration, vibration-acceleration and sustained-acceleration mode, respectively) by digital simulation. Moreover, the proposed approach was tested in a kinematic vehicle experiment as well. Using the designed simulations and kinematic vehicle experiments, it has been shown that the disturbance acceleration of each mode can be accurately estimated and corrected. Moreover, compared with the complementary filter, the experimental results have explicitly demonstrated the proposed approach further improves the attitude estimate precision under vehicle movement conditions. PMID:27754469

Accurate Attitude Estimation Using ARS under Conditions of Vehicle Movement Based on Disturbance Acceleration Adaptive Estimation and Correction.

PubMed

Xing, Li; Hang, Yijun; Xiong, Zhi; Liu, Jianye; Wan, Zhong

2016-10-16

This paper describes a disturbance acceleration adaptive estimate and correction approach for an attitude reference system (ARS) so as to improve the attitude estimate precision under vehicle movement conditions. The proposed approach depends on a Kalman filter, where the attitude error, the gyroscope zero offset error and the disturbance acceleration error are estimated. By switching the filter decay coefficient of the disturbance acceleration model in different acceleration modes, the disturbance acceleration is adaptively estimated and corrected, and then the attitude estimate precision is improved. The filter was tested in three different disturbance acceleration modes (non-acceleration, vibration-acceleration and sustained-acceleration mode, respectively) by digital simulation. Moreover, the proposed approach was tested in a kinematic vehicle experiment as well. Using the designed simulations and kinematic vehicle experiments, it has been shown that the disturbance acceleration of each mode can be accurately estimated and corrected. Moreover, compared with the complementary filter, the experimental results have explicitly demonstrated the proposed approach further improves the attitude estimate precision under vehicle movement conditions.

Estimating the impact of mineral aerosols on crop yields in food insecure regions using statistical crop models

NASA Astrophysics Data System (ADS)

Hoffman, A.; Forest, C. E.; Kemanian, A.

2016-12-01

A significant number of food-insecure nations exist in regions of the world where dust plays a large role in the climate system. While the impacts of common climate variables (e.g. temperature, precipitation, ozone, and carbon dioxide) on crop yields are relatively well understood, the impact of mineral aerosols on yields have not yet been thoroughly investigated. This research aims to develop the data and tools to progress our understanding of mineral aerosol impacts on crop yields. Suspended dust affects crop yields by altering the amount and type of radiation reaching the plant, modifying local temperature and precipitation. While dust events (i.e. dust storms) affect crop yields by depleting the soil of nutrients or by defoliation via particle abrasion. The impact of dust on yields is modeled statistically because we are uncertain which impacts will dominate the response on national and regional scales considered in this study. Multiple linear regression is used in a number of large-scale statistical crop modeling studies to estimate yield responses to various climate variables. In alignment with previous work, we develop linear crop models, but build upon this simple method of regression with machine-learning techniques (e.g. random forests) to identify important statistical predictors and isolate how dust affects yields on the scales of interest. To perform this analysis, we develop a crop-climate dataset for maize, soybean, groundnut, sorghum, rice, and wheat for the regions of West Africa, East Africa, South Africa, and the Sahel. Random forest regression models consistently model historic crop yields better than the linear models. In several instances, the random forest models accurately capture the temperature and precipitation threshold behavior in crops. Additionally, improving agricultural technology has caused a well-documented positive trend that dominates time series of global and regional yields. This trend is often removed before regression with

Soil Moisture as an Estimator for Crop Yield in Germany

NASA Astrophysics Data System (ADS)

Peichl, Michael; Meyer, Volker; Samaniego, Luis; Thober, Stephan

2015-04-01

Annual crop yield depends on various factors such as soil properties, management decisions, and meteorological conditions. Unfavorable weather conditions, e.g. droughts, have the potential to drastically diminish crop yield in rain-fed agriculture. For example, the drought in 2003 caused direct losses of 1.5 billion EUR only in Germany. Predicting crop yields allows to mitigate negative effects of weather extremes which are assumed to occur more often in the future due to climate change. A standard approach in economics is to predict the impact of climate change on agriculture as a function of temperature and precipitation. This approach has been developed further using concepts like growing degree days. Other econometric models use nonlinear functions of heat or vapor pressure deficit. However, none of these approaches uses soil moisture to predict crop yield. We hypothesize that soil moisture is a better indicator to explain stress on plant growth than estimations based on precipitation and temperature. This is the case because the latter variables do not explicitly account for the available water content in the root zone, which is the primary source of water supply for plant growth. In this study, a reduced form panel approach is applied to estimate a multivariate econometric production function for the years 1999 to 2010. Annual crop yield data of various crops on the administrative district level serve as depending variables. The explanatory variable of major interest is the Soil Moisture Index (SMI), which quantifies anomalies in root zone soil moisture. The SMI is computed by the mesoscale Hydrological Model (mHM, www.ufz.de/mhm). The index represents the monthly soil water quantile at a 4 km2 grid resolution covering entire Germany. A reduced model approach is suitable because the SMI is the result of a stochastic weather process and therefore can be considered exogenous. For the ease of interpretation a linear functionality is preferred. Meteorological

Do We Know Whether Researchers and Reviewers are Estimating Risk and Benefit Accurately?

PubMed

Hey, Spencer Phillips; Kimmelman, Jonathan

2016-10-01

Accurate estimation of risk and benefit is integral to good clinical research planning, ethical review, and study implementation. Some commentators have argued that various actors in clinical research systems are prone to biased or arbitrary risk/benefit estimation. In this commentary, we suggest the evidence supporting such claims is very limited. Most prior work has imputed risk/benefit beliefs based on past behavior or goals, rather than directly measuring them. We describe an approach - forecast analysis - that would enable direct and effective measure of the quality of risk/benefit estimation. We then consider some objections and limitations to the forecasting approach. © 2016 John Wiley & Sons Ltd.

Intraocular lens power estimation by accurate ray tracing for eyes underwent previous refractive surgeries

NASA Astrophysics Data System (ADS)

Yang, Que; Wang, Shanshan; Wang, Kai; Zhang, Chunyu; Zhang, Lu; Meng, Qingyu; Zhu, Qiudong

2015-08-01

For normal eyes without history of any ocular surgery, traditional equations for calculating intraocular lens (IOL) power, such as SRK-T, Holladay, Higis, SRK-II, et al., all were relativley accurate. However, for eyes underwent refractive surgeries, such as LASIK, or eyes diagnosed as keratoconus, these equations may cause significant postoperative refractive error, which may cause poor satisfaction after cataract surgery. Although some methods have been carried out to solve this problem, such as Hagis-L equation[1], or using preoperative data (data before LASIK) to estimate K value[2], no precise equations were available for these eyes. Here, we introduced a novel intraocular lens power estimation method by accurate ray tracing with optical design software ZEMAX. Instead of using traditional regression formula, we adopted the exact measured corneal elevation distribution, central corneal thickness, anterior chamber depth, axial length, and estimated effective lens plane as the input parameters. The calculation of intraocular lens power for a patient with keratoconus and another LASIK postoperative patient met very well with their visual capacity after cataract surgery.

Accurate estimation of human body orientation from RGB-D sensors.

PubMed

Liu, Wu; Zhang, Yongdong; Tang, Sheng; Tang, Jinhui; Hong, Richang; Li, Jintao

2013-10-01

Accurate estimation of human body orientation can significantly enhance the analysis of human behavior, which is a fundamental task in the field of computer vision. However, existing orientation estimation methods cannot handle the various body poses and appearances. In this paper, we propose an innovative RGB-D-based orientation estimation method to address these challenges. By utilizing the RGB-D information, which can be real time acquired by RGB-D sensors, our method is robust to cluttered environment, illumination change and partial occlusions. Specifically, efficient static and motion cue extraction methods are proposed based on the RGB-D superpixels to reduce the noise of depth data. Since it is hard to discriminate all the 360 (°) orientation using static cues or motion cues independently, we propose to utilize a dynamic Bayesian network system (DBNS) to effectively employ the complementary nature of both static and motion cues. In order to verify our proposed method, we build a RGB-D-based human body orientation dataset that covers a wide diversity of poses and appearances. Our intensive experimental evaluations on this dataset demonstrate the effectiveness and efficiency of the proposed method.

Estimating oak growth and yield

Treesearch

Martin E. Dale; Donald E. Hilt

1989-01-01

Yields from upland oak stands vary widely from stand to stand due to differences in age, site quality, species composition, and stand structure. Cutting history and other past disturbances such as grazing or fire also affect yields.

Seismic Yield Estimates of UTTR Surface Explosions

NASA Astrophysics Data System (ADS)

Hayward, C.; Park, J.; Stump, B. W.

2016-12-01

Since 2007 the Utah Test and Training Range (UTTR) has used explosive demolition as a method to destroy excess solid rocket motors ranging in size from 19 tons to less than 2 tons. From 2007 to 2014, 20 high quality seismic stations within 180 km recorded most of the more than 200 demolitions. This provides an interesting dataset to examine seismic source scaling for surface explosions. Based upon observer records, shots were of 4 sizes, corresponding to the size of the rocket motors. Instrument corrections for the stations were quality controlled by examining the P-wave amplitudes of all magnitude 6.5-8 earthquakes from 30 to 90 degrees away. For each station recording, the instrument corrected RMS seismic amplitude in the first 10 seconds after the P-onset was calculated. Waveforms at any given station for all the observed explosions are nearly identical. The observed RMS amplitudes were fit to a model including a term for combined distance and station correction, a term for observed RMS amplitude, and an error term for the actual demolition size. The observed seismic yield relationship is RMS=k*Weight2/3 . Estimated yields for the largest shots vary by about 50% from the stated weights, with a nearly normal distribution.

Estimating chlorophyll content and photochemical yield of photosystem II (ΦPSII) using solar-induced chlorophyll fluorescence measurements at different growing stages of attached leaves

PubMed Central

Tubuxin, Bayaer; Rahimzadeh-Bajgiran, Parinaz; Ginnan, Yusaku; Hosoi, Fumiki; Omasa, Kenji

2015-01-01

This paper illustrates the possibility of measuring chlorophyll (Chl) content and Chl fluorescence parameters by the solar-induced Chl fluorescence (SIF) method using the Fraunhofer line depth (FLD) principle, and compares the results with the standard measurement methods. A high-spectral resolution HR2000+ and an ordinary USB4000 spectrometer were used to measure leaf reflectance under solar and artificial light, respectively, to estimate Chl fluorescence. Using leaves of Capsicum annuum cv. ‘Sven’ (paprika), the relationships between the Chl content and the steady-state Chl fluorescence near oxygen absorption bands of O2B (686nm) and O2A (760nm), measured under artificial and solar light at different growing stages of leaves, were evaluated. The Chl fluorescence yields of ΦF 686nm/ΦF 760nm ratios obtained from both methods correlated well with the Chl content (steady-state solar light: R2 = 0.73; artificial light: R2 = 0.94). The SIF method was less accurate for Chl content estimation when Chl content was high. The steady-state solar-induced Chl fluorescence yield ratio correlated very well with the artificial-light-induced one (R2 = 0.84). A new methodology is then presented to estimate photochemical yield of photosystem II (ΦPSII) from the SIF measurements, which was verified against the standard Chl fluorescence measurement method (pulse-amplitude modulated method). The high coefficient of determination (R2 = 0.74) between the ΦPSII of the two methods shows that photosynthesis process parameters can be successfully estimated using the presented methodology. PMID:26071530

Accurate position estimation methods based on electrical impedance tomography measurements

NASA Astrophysics Data System (ADS)

Vergara, Samuel; Sbarbaro, Daniel; Johansen, T. A.

2017-08-01

than 0.05% of the tomograph radius value. These results demonstrate that the proposed approaches can estimate an object’s position accurately based on EIT measurements if enough process information is available for training or modelling. Since they do not require complex calculations it is possible to use them in real-time applications without requiring high-performance computers.

Comparison Between the Use of SAR and Optical Data for Wheat Yield Estimations Using Crop Model Assimilation

NASA Astrophysics Data System (ADS)

Silvestro, Paolo Cosmo; Yang, Hao; Jin, X. L.; Yang, Guijun; Casa, Raffaele; Pignatti, Stefano

2016-08-01

The ultimate aim of this work is to develop methods for the assimilation of the biophysical variables estimated by remote sensing in a suitable crop growth model. Two strategies were followed, one based on the use of Leaf Area Index (LAI) estimated by optical data, and the other based on the use of biomass estimated by SAR. The first one estimates LAI from the reflectance measured by the optical sensors on board of HJ1A, HJ1B and Landsat, using a method based on the training of artificial neural networks (ANN) with PROSAIL model simulations. The retrieved LAI is used to improve wheat yield estimation, using assimilation methods based on the Ensemble Kalman Filter, which assimilate the biophysical variables into growth crop model. The second strategy estimates biomass from SAR imagery. Polarimetric decomposition methods were used based on multi-temporal fully polarimetric Radarsat-2 data during the entire growing season. The estimated biomass was assimilating to FAO Aqua crop model for improving the winter wheat yield estimation, with the Particle Swarm Optimization (PSO) method. These procedures were used in a spatial application with data collected in the rural area of Yangling (Shaanxi Province) in 2014 and were validated for a number of wheat fields for which ground yield data had been recorded and according to statistical yield data for the area.

Wheat yield estimation at the farm level using TM Landsat and agrometeorological data

NASA Technical Reports Server (NTRS)

Rudorff, B. F. T.; Batista, G. T.

1991-01-01

A model for estimating wheat yields on the farm level was developed, that integrates the Landsat TM data and agrometeorological information. Results obtained for a test site in southern Brasil for years of 1986 and 1987 show that the vegetation index derived from Landsat TM could account for the 60 to 40 percent wheat-yield variability observed between the two crop years. Compared to results using either the Landsat TM vegetation index or the agrometeorological data alone, the joint use of both types of data in a single model yielded a significant improvement.

Fast and accurate spectral estimation for online detection of partial broken bar in induction motors

NASA Astrophysics Data System (ADS)

Samanta, Anik Kumar; Naha, Arunava; Routray, Aurobinda; Deb, Alok Kanti

2018-01-01

In this paper, an online and real-time system is presented for detecting partial broken rotor bar (BRB) of inverter-fed squirrel cage induction motors under light load condition. This system with minor modifications can detect any fault that affects the stator current. A fast and accurate spectral estimator based on the theory of Rayleigh quotient is proposed for detecting the spectral signature of BRB. The proposed spectral estimator can precisely determine the relative amplitude of fault sidebands and has low complexity compared to available high-resolution subspace-based spectral estimators. Detection of low-amplitude fault components has been improved by removing the high-amplitude fundamental frequency using an extended-Kalman based signal conditioner. Slip is estimated from the stator current spectrum for accurate localization of the fault component. Complexity and cost of sensors are minimal as only a single-phase stator current is required. The hardware implementation has been carried out on an Intel i7 based embedded target ported through the Simulink Real-Time. Evaluation of threshold and detectability of faults with different conditions of load and fault severity are carried out with empirical cumulative distribution function.

Estimates of Sputter Yields of Solar-Wind Heavy Ions of Lunar Regolith Materials

NASA Technical Reports Server (NTRS)

Barghouty, Abdulmasser F.; Adams, James H., Jr.

2008-01-01

At energies of approximately 1 keV/amu, solar-wind protons and heavy ions interact with the lunar surface materials via a number of microscopic interactions that include sputtering. Solar-wind induced sputtering is a main mechanism by which the composition of the topmost layers of the lunar surface can change, dynamically and preferentially. This work concentrates on sputtering induced by solar-wind heavy ions. Sputtering associated with slow (speeds the electrons speed in its first Bohr orbit) and highly charged ions are known to include both kinetic and potential sputtering. Potential sputtering enjoys some unique characteristics that makes it of special interest to lunar science and exploration. Unlike the yield from kinetic sputtering where simulation and approximation schemes exist, the yield from potential sputtering is not as easy to estimate. This work will present a preliminary numerical scheme designed to estimate potential sputtering yields from reactions relevant to this aspect of solar-wind lunar-surface coupling.

Mixture models reveal multiple positional bias types in RNA-Seq data and lead to accurate transcript concentration estimates.

PubMed

Tuerk, Andreas; Wiktorin, Gregor; Güler, Serhat

2017-05-01

Accuracy of transcript quantification with RNA-Seq is negatively affected by positional fragment bias. This article introduces Mix2 (rd. "mixquare"), a transcript quantification method which uses a mixture of probability distributions to model and thereby neutralize the effects of positional fragment bias. The parameters of Mix2 are trained by Expectation Maximization resulting in simultaneous transcript abundance and bias estimates. We compare Mix2 to Cufflinks, RSEM, eXpress and PennSeq; state-of-the-art quantification methods implementing some form of bias correction. On four synthetic biases we show that the accuracy of Mix2 overall exceeds the accuracy of the other methods and that its bias estimates converge to the correct solution. We further evaluate Mix2 on real RNA-Seq data from the Microarray and Sequencing Quality Control (MAQC, SEQC) Consortia. On MAQC data, Mix2 achieves improved correlation to qPCR measurements with a relative increase in R2 between 4% and 50%. Mix2 also yields repeatable concentration estimates across technical replicates with a relative increase in R2 between 8% and 47% and reduced standard deviation across the full concentration range. We further observe more accurate detection of differential expression with a relative increase in true positives between 74% and 378% for 5% false positives. In addition, Mix2 reveals 5 dominant biases in MAQC data deviating from the common assumption of a uniform fragment distribution. On SEQC data, Mix2 yields higher consistency between measured and predicted concentration ratios. A relative error of 20% or less is obtained for 51% of transcripts by Mix2, 40% of transcripts by Cufflinks and RSEM and 30% by eXpress. Titration order consistency is correct for 47% of transcripts for Mix2, 41% for Cufflinks and RSEM and 34% for eXpress. We, further, observe improved repeatability across laboratory sites with a relative increase in R2 between 8% and 44% and reduced standard deviation.

Estimating the potential refolding yield of recombinant proteins expressed as inclusion bodies.

PubMed

Ho, Jason G S; Middelberg, Anton P J

2004-09-05

Recombinant protein production in bacteria is efficient except that insoluble inclusion bodies form when some gene sequences are expressed. Such proteins must undergo renaturation, which is an inefficient process due to protein aggregation on dilution from concentrated denaturant. In this study, the protein-protein interactions of eight distinct inclusion-body proteins are quantified, in different solution conditions, by measurement of protein second virial coefficients (SVCs). Protein solubility is shown to decrease as the SVC is reduced (i.e., as protein interactions become more attractive). Plots of SVC versus denaturant concentration demonstrate two clear groupings of proteins: a more aggregative group and a group having higher SVC and better solubility. A correlation of the measured SVC with protein molecular weight and hydropathicity, that is able to predict which group each of the eight proteins falls into, is presented. The inclusion of additives known to inhibit aggregation during renaturation improves solubility and increases the SVC of both protein groups. Furthermore, an estimate of maximum refolding yield (or solubility) using high-performance liquid chromatography was obtained for each protein tested, under different environmental conditions, enabling a relationship between "yield" and SVC to be demonstrated. Combined, the results enable an approximate estimation of the maximum refolding yield that is attainable for each of the eight proteins examined, under a selected chemical environment. Although the correlations must be tested with a far larger set of protein sequences, this work represents a significant move beyond empirical approaches for optimizing renaturation conditions. The approach moves toward the ideal of predicting maximum refolding yield using simple bioinformatic metrics that can be estimated from the gene sequence. Such a capability could potentially "screen," in silico, those sequences suitable for expression in bacteria from those

Estimation of corn yield using multi-temporal optical and radar satellite data and artificial neural networks

NASA Astrophysics Data System (ADS)

Fieuzal, R.; Marais Sicre, C.; Baup, F.

2017-05-01

The yield forecasting of corn constitutes a key issue in agricultural management, particularly in the context of demographic pressure and climate change. This study presents two methods to estimate yields using artificial neural networks: a diagnostic approach based on all the satellite data acquired throughout the agricultural season, and a real-time approach, where estimates are updated after each image was acquired in the microwave and optical domains (Formosat-2, Spot-4/5, TerraSAR-X, and Radarsat-2) throughout the crop cycle. The results are based on the Multispectral Crop Monitoring experimental campaign conducted by the CESBIO (Centre d'Études de la BIOsphère) laboratory in 2010 over an agricultural region in southwestern France. Among the tested sensor configurations (multi-frequency, multi-polarization or multi-source data), the best yield estimation performance (using the diagnostic approach) is obtained with reflectance acquired in the red wavelength region, with a coefficient of determination of 0.77 and an RMSE of 6.6 q ha-1. In the real-time approach the combination of red reflectance and CHH backscattering coefficients provides the best compromise between the accuracy and earliness of the yield estimate (more than 3 months before the harvest), with an R2 of 0.69 and an RMSE of 7.0 q ha-1 during the development of the central stem. The two best yield estimates are similar in most cases (for more than 80% of the monitored fields), and the differences are related to discrepancies in the crop growth cycle and/or the consequences of pests.

Estimating diversification rates for higher taxa: BAMM can give problematic estimates of rates and rate shifts.

PubMed

Meyer, Andreas L S; Wiens, John J

2018-01-01

Estimates of diversification rates are invaluable for many macroevolutionary studies. Recently, an approach called BAMM (Bayesian Analysis of Macro-evolutionary Mixtures) has become widely used for estimating diversification rates and rate shifts. At the same time, several articles have concluded that estimates of net diversification rates from the method-of-moments (MS) estimators are inaccurate. Yet, no studies have compared the ability of these two methods to accurately estimate clade diversification rates. Here, we use simulations to compare their performance. We found that BAMM yielded relatively weak relationships between true and estimated diversification rates. This occurred because BAMM underestimated the number of rates shifts across each tree, and assigned high rates to small clades with low rates. Errors in both speciation and extinction rates contributed to these errors, showing that using BAMM to estimate only speciation rates is also problematic. In contrast, the MS estimators (particularly using stem group ages), yielded stronger relationships between true and estimated diversification rates, by roughly twofold. Furthermore, the MS approach remained relatively accurate when diversification rates were heterogeneous within clades, despite the widespread assumption that it requires constant rates within clades. Overall, we caution that BAMM may be problematic for estimating diversification rates and rate shifts. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Efficient SRAM yield optimization with mixture surrogate modeling

NASA Astrophysics Data System (ADS)

Zhongjian, Jiang; Zuochang, Ye; Yan, Wang

2016-12-01

Largely repeated cells such as SRAM cells usually require extremely low failure-rate to ensure a moderate chi yield. Though fast Monte Carlo methods such as importance sampling and its variants can be used for yield estimation, they are still very expensive if one needs to perform optimization based on such estimations. Typically the process of yield calculation requires a lot of SPICE simulation. The circuit SPICE simulation analysis accounted for the largest proportion of time in the process yield calculation. In the paper, a new method is proposed to address this issue. The key idea is to establish an efficient mixture surrogate model. The surrogate model is based on the design variables and process variables. This model construction method is based on the SPICE simulation to get a certain amount of sample points, these points are trained for mixture surrogate model by the lasso algorithm. Experimental results show that the proposed model is able to calculate accurate yield successfully and it brings significant speed ups to the calculation of failure rate. Based on the model, we made a further accelerated algorithm to further enhance the speed of the yield calculation. It is suitable for high-dimensional process variables and multi-performance applications.

Soil Water Availability Modulation Over Estimated Relative Yield Losses in Wheat (Triticum aestivum L.) Due to Ozone Exposure

PubMed Central

De la Torre, Daniel; Sierra, Maria Jose

2007-01-01

The approach developed by Fuhrer in 1995 to estimate wheat yield losses induced by ozone and modulated by the soil water content (SWC) was applied to the data on Catalonian wheat yields. The aim of our work was to apply this approach and adjust it to Mediterranean environmental conditions by means of the necessary corrections. The main objective pursued was to prove the importance of soil water availability in the estimation of relative wheat yield losses as a factor that modifies the effects of tropospheric ozone on wheat, and to develop the algorithms required for the estimation of relative yield losses, adapted to the Mediterranean environmental conditions. The results show that this is an easy way to estimate relative yield losses just using meteorological data, without using ozone fluxes, which are much more difficult to calculate. Soil water availability is very important as a modulating factor of the effects of ozone on wheat; when soil water availability decreases, almost twice the amount of accumulated exposure to ozone is required to induce the same percentage of yield loss as in years when soil water availability is high. PMID:17619747

Competitive Abilities in Experimental Microcosms Are Accurately Predicted by a Demographic Index for R*

PubMed Central

Murrell, Ebony G.; Juliano, Steven A.

2012-01-01

Resource competition theory predicts that R*, the equilibrium resource amount yielding zero growth of a consumer population, should predict species' competitive abilities for that resource. This concept has been supported for unicellular organisms, but has not been well-tested for metazoans, probably due to the difficulty of raising experimental populations to equilibrium and measuring population growth rates for species with long or complex life cycles. We developed an index (Rindex) of R* based on demography of one insect cohort, growing from egg to adult in a non-equilibrium setting, and tested whether Rindex yielded accurate predictions of competitive abilities using mosquitoes as a model system. We estimated finite rate of increase (λ′) from demographic data for cohorts of three mosquito species raised with different detritus amounts, and estimated each species' Rindex using nonlinear regressions of λ′ vs. initial detritus amount. All three species' Rindex differed significantly, and accurately predicted competitive hierarchy of the species determined in simultaneous pairwise competition experiments. Our Rindex could provide estimates and rigorous statistical comparisons of competitive ability for organisms for which typical chemostat methods and equilibrium population conditions are impractical. PMID:22970128

Branch and bound algorithm for accurate estimation of analytical isotropic bidirectional reflectance distribution function models.

PubMed

Yu, Chanki; Lee, Sang Wook

2016-05-20

We present a reliable and accurate global optimization framework for estimating parameters of isotropic analytical bidirectional reflectance distribution function (BRDF) models. This approach is based on a branch and bound strategy with linear programming and interval analysis. Conventional local optimization is often very inefficient for BRDF estimation since its fitting quality is highly dependent on initial guesses due to the nonlinearity of analytical BRDF models. The algorithm presented in this paper employs L₁-norm error minimization to estimate BRDF parameters in a globally optimal way and interval arithmetic to derive our feasibility problem and lower bounding function. Our method is developed for the Cook-Torrance model but with several normal distribution functions such as the Beckmann, Berry, and GGX functions. Experiments have been carried out to validate the presented method using 100 isotropic materials from the MERL BRDF database, and our experimental results demonstrate that the L₁-norm minimization provides a more accurate and reliable solution than the L₂-norm minimization.

Comparison of statistical models for analyzing wheat yield time series.

PubMed

Michel, Lucie; Makowski, David

2013-01-01

The world's population is predicted to exceed nine billion by 2050 and there is increasing concern about the capability of agriculture to feed such a large population. Foresight studies on food security are frequently based on crop yield trends estimated from yield time series provided by national and regional statistical agencies. Various types of statistical models have been proposed for the analysis of yield time series, but the predictive performances of these models have not yet been evaluated in detail. In this study, we present eight statistical models for analyzing yield time series and compare their ability to predict wheat yield at the national and regional scales, using data provided by the Food and Agriculture Organization of the United Nations and by the French Ministry of Agriculture. The Holt-Winters and dynamic linear models performed equally well, giving the most accurate predictions of wheat yield. However, dynamic linear models have two advantages over Holt-Winters models: they can be used to reconstruct past yield trends retrospectively and to analyze uncertainty. The results obtained with dynamic linear models indicated a stagnation of wheat yields in many countries, but the estimated rate of increase of wheat yield remained above 0.06 t ha⁻¹ year⁻¹ in several countries in Europe, Asia, Africa and America, and the estimated values were highly uncertain for several major wheat producing countries. The rate of yield increase differed considerably between French regions, suggesting that efforts to identify the main causes of yield stagnation should focus on a subnational scale.

Comparison of Statistical Models for Analyzing Wheat Yield Time Series

PubMed Central

Michel, Lucie; Makowski, David

2013-01-01

The world's population is predicted to exceed nine billion by 2050 and there is increasing concern about the capability of agriculture to feed such a large population. Foresight studies on food security are frequently based on crop yield trends estimated from yield time series provided by national and regional statistical agencies. Various types of statistical models have been proposed for the analysis of yield time series, but the predictive performances of these models have not yet been evaluated in detail. In this study, we present eight statistical models for analyzing yield time series and compare their ability to predict wheat yield at the national and regional scales, using data provided by the Food and Agriculture Organization of the United Nations and by the French Ministry of Agriculture. The Holt-Winters and dynamic linear models performed equally well, giving the most accurate predictions of wheat yield. However, dynamic linear models have two advantages over Holt-Winters models: they can be used to reconstruct past yield trends retrospectively and to analyze uncertainty. The results obtained with dynamic linear models indicated a stagnation of wheat yields in many countries, but the estimated rate of increase of wheat yield remained above 0.06 t ha−1 year−1 in several countries in Europe, Asia, Africa and America, and the estimated values were highly uncertain for several major wheat producing countries. The rate of yield increase differed considerably between French regions, suggesting that efforts to identify the main causes of yield stagnation should focus on a subnational scale. PMID:24205280

Use of vegetation health data for estimation of aus rice yield in bangladesh.

PubMed

Rahman, Atiqur; Roytman, Leonid; Krakauer, Nir Y; Nizamuddin, Mohammad; Goldberg, Mitch

2009-01-01

Rice is a vital staple crop for Bangladesh and surrounding countries, with interannual variation in yields depending on climatic conditions. We compared Bangladesh yield of aus rice, one of the main varieties grown, from official agricultural statistics with Vegetation Health (VH) Indices [Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and Vegetation Health Index (VHI)] computed from Advanced Very High Resolution Radiometer (AVHRR) data covering a period of 15 years (1991-2005). A strong correlation was found between aus rice yield and VCI and VHI during the critical period of aus rice development that occurs during March-April (weeks 8-13 of the year), several months in advance of the rice harvest. Stepwise principal component regression (PCR) was used to construct a model to predict yield as a function of critical-period VHI. The model reduced the yield prediction error variance by 62% compared with a prediction of average yield for each year. Remote sensing is a valuable tool for estimating rice yields well in advance of harvest and at a low cost.

Use of Vegetation Health Data for Estimation of Aus Rice Yield in Bangladesh

PubMed Central

Rahman, Atiqur; Roytman, Leonid; Krakauer, Nir Y.; Nizamuddin, Mohammad; Goldberg, Mitch

2009-01-01

Rice is a vital staple crop for Bangladesh and surrounding countries, with interannual variation in yields depending on climatic conditions. We compared Bangladesh yield of aus rice, one of the main varieties grown, from official agricultural statistics with Vegetation Health (VH) Indices [Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and Vegetation Health Index (VHI)] computed from Advanced Very High Resolution Radiometer (AVHRR) data covering a period of 15 years (1991–2005). A strong correlation was found between aus rice yield and VCI and VHI during the critical period of aus rice development that occurs during March–April (weeks 8–13 of the year), several months in advance of the rice harvest. Stepwise principal component regression (PCR) was used to construct a model to predict yield as a function of critical-period VHI. The model reduced the yield prediction error variance by 62% compared with a prediction of average yield for each year. Remote sensing is a valuable tool for estimating rice yields well in advance of harvest and at a low cost. PMID:22574057

Estimating soybean genetic gain for yield in the northern United States – Influence of cropping history

USDA-ARS?s Scientific Manuscript database

Mean on-farm USA soybean yield increased at a rate of 21.3 kg per ha per year between 1924 and 2010, due to adoption of yield-enhancing genetic and agronomic technologies. To estimate annual rates of genetic yield gain in three northern USA soybean maturity groups (MG) and determine if these estimat...

Rapid and Accurate Multiple Testing Correction and Power Estimation for Millions of Correlated Markers

PubMed Central

Han, Buhm; Kang, Hyun Min; Eskin, Eleazar

2009-01-01

With the development of high-throughput sequencing and genotyping technologies, the number of markers collected in genetic association studies is growing rapidly, increasing the importance of methods for correcting for multiple hypothesis testing. The permutation test is widely considered the gold standard for accurate multiple testing correction, but it is often computationally impractical for these large datasets. Recently, several studies proposed efficient alternative approaches to the permutation test based on the multivariate normal distribution (MVN). However, they cannot accurately correct for multiple testing in genome-wide association studies for two reasons. First, these methods require partitioning of the genome into many disjoint blocks and ignore all correlations between markers from different blocks. Second, the true null distribution of the test statistic often fails to follow the asymptotic distribution at the tails of the distribution. We propose an accurate and efficient method for multiple testing correction in genome-wide association studies—SLIDE. Our method accounts for all correlation within a sliding window and corrects for the departure of the true null distribution of the statistic from the asymptotic distribution. In simulations using the Wellcome Trust Case Control Consortium data, the error rate of SLIDE's corrected p-values is more than 20 times smaller than the error rate of the previous MVN-based methods' corrected p-values, while SLIDE is orders of magnitude faster than the permutation test and other competing methods. We also extend the MVN framework to the problem of estimating the statistical power of an association study with correlated markers and propose an efficient and accurate power estimation method SLIP. SLIP and SLIDE are available at http://slide.cs.ucla.edu. PMID:19381255

Integrating remote sensing, geographic information system and modeling for estimating crop yield

NASA Astrophysics Data System (ADS)

Salazar, Luis Alonso

This thesis explores various aspects of the use of remote sensing, geographic information system and digital signal processing technologies for broad-scale estimation of crop yield in Kansas. Recent dry and drought years in the Great Plains have emphasized the need for new sources of timely, objective and quantitative information on crop conditions. Crop growth monitoring and yield estimation can provide important information for government agencies, commodity traders and producers in planning harvest, storage, transportation and marketing activities. The sooner this information is available the lower the economic risk translating into greater efficiency and increased return on investments. Weather data is normally used when crop yield is forecasted. Such information, to provide adequate detail for effective predictions, is typically feasible only on small research sites due to expensive and time-consuming collections. In order for crop assessment systems to be economical, more efficient methods for data collection and analysis are necessary. The purpose of this research is to use satellite data which provides 50 times more spatial information about the environment than the weather station network in a short amount of time at a relatively low cost. Specifically, we are going to use Advanced Very High Resolution Radiometer (AVHRR) based vegetation health (VH) indices as proxies for characterization of weather conditions.

Dual-component video image analysis system (VIASCAN) as a predictor of beef carcass red meat yield percentage and for augmenting application of USDA yield grades.

PubMed

Cannell, R C; Tatum, J D; Belk, K E; Wise, J W; Clayton, R P; Smith, G C

1999-11-01

An improved ability to quantify differences in the fabrication yields of beef carcasses would facilitate the application of value-based marketing. This study was conducted to evaluate the ability of the Dual-Component Australian VIASCAN to 1) predict fabricated beef subprimal yields as a percentage of carcass weight at each of three fat-trim levels and 2) augment USDA yield grading, thereby improving accuracy of grade placement. Steer and heifer carcasses (n = 240) were evaluated using VIASCAN, as well as by USDA expert and online graders, before fabrication of carcasses to each of three fat-trim levels. Expert yield grade (YG), online YG, VIASCAN estimates, and VIASCAN estimated ribeye area used to augment actual and expert grader estimates of the remaining YG factors (adjusted fat thickness, percentage of kidney-pelvic-heart fat, and hot carcass weight), respectively, 1) accounted for 51, 37, 46, and 55% of the variation in fabricated yields of commodity-trimmed subprimals, 2) accounted for 74, 54, 66, and 75% of the variation in fabricated yields of closely trimmed subprimals, and 3) accounted for 74, 54, 71, and 75% of the variation in fabricated yields of very closely trimmed subprimals. The VIASCAN system predicted fabrication yields more accurately than current online yield grading and, when certain VIASCAN-measured traits were combined with some USDA yield grade factors in an augmentation system, the accuracy of cutability prediction was improved, at packing plant line speeds, to a level matching that of expert graders applying grades at a comfortable rate.

The Remote Food Photography Method accurately estimates dry powdered foods—the source of calories for many infants

PubMed Central

Duhé, Abby F.; Gilmore, L. Anne; Burton, Jeffrey H.; Martin, Corby K.; Redman, Leanne M.

2016-01-01

Background Infant formula is a major source of nutrition for infants with over half of all infants in the United States consuming infant formula exclusively or in combination with breast milk. The energy in infant powdered formula is derived from the powder and not the water making it necessary to develop methods that can accurately estimate the amount of powder used prior to reconstitution. Objective To assess the use of the Remote Food Photography Method (RFPM) to accurately estimate the weight of infant powdered formula before reconstitution among the standard serving sizes. Methods For each serving size (1-scoop, 2-scoop, 3-scoop, and 4-scoop), a set of seven test bottles and photographs were prepared including the recommended gram weight of powdered formula of the respective serving size by the manufacturer, three bottles and photographs containing 15%, 10%, and 5% less powdered formula than recommended, and three bottles and photographs containing 5%, 10%, and 15% more powdered formula than recommended (n=28). Ratio estimates of the test photographs as compared to standard photographs were obtained using standard RFPM analysis procedures. The ratio estimates and the United States Department of Agriculture (USDA) data tables were used to generate food and nutrient information to provide the RFPM estimates. Statistical Analyses Performed Equivalence testing using the two one-sided t- test (TOST) approach was used to determine equivalence between the actual gram weights and the RFPM estimated weights for all samples, within each serving size, and within under-prepared and over-prepared bottles. Results For all bottles, the gram weights estimated by the RFPM were within 5% equivalence bounds with a slight under-estimation of 0.05 g (90% CI [−0.49, 0.40]; p<0.001) and mean percent error ranging between 0.32% and 1.58% among the four serving sizes. Conclusion The maximum observed mean error was an overestimation of 1.58% of powdered formula by the RFPM under

Home Circadian Phase Assessments with Measures of Compliance Yield Accurate Dim Light Melatonin Onsets

PubMed Central

Burgess, Helen J.; Wyatt, James K.; Park, Margaret; Fogg, Louis F.

2015-01-01

Study Objectives: There is a need for the accurate assessment of circadian phase outside of the clinic/laboratory, particularly with the gold standard dim light melatonin onset (DLMO). We tested a novel kit designed to assist in saliva sampling at home for later determination of the DLMO. The home kit includes objective measures of compliance to the requirements for dim light and half-hourly saliva sampling. Design: Participants were randomized to one of two 10-day protocols. Each protocol consisted of two back-to-back home and laboratory phase assessments in counterbalanced order, separated by a 5-day break. Setting: Laboratory or participants' homes. Participants: Thirty-five healthy adults, age 21–62 y. Interventions: N/A. Measurements and Results: Most participants received at least one 30-sec epoch of light > 50 lux during the home phase assessments (average light intensity 4.5 lux), but on average for < 9 min of the required 8.5 h. Most participants collected every saliva sample within 5 min of the scheduled time. Ninety-two percent of home DLMOs were not affected by light > 50 lux or sampling errors. There was no significant difference between the home and laboratory DLMOs (P > 0.05); on average the home DLMOs occurred 9.6 min before the laboratory DLMOs. The home DLMOs were highly correlated with the laboratory DLMOs (r = 0.91, P < 0.001). Conclusions: Participants were reasonably compliant to the home phase assessment procedures. The good agreement between the home and laboratory dim light melatonin onsets (DLMOs) demonstrates that including objective measures of light exposure and sample timing during home saliva sampling can lead to accurate home DLMOs. Clinical Trial Registration: Circadian Phase Assessments at Home, http://clinicaltrials.gov/show/NCT01487252, NCT01487252. Citation: Burgess HJ, Wyatt JK, Park M, Fogg LF. Home circadian phase assessments with measures of compliance yield accurate dim light melatonin onsets. SLEEP 2015;38(6):889–897

A photometric method for the estimation of the oil yield of oil shale

USGS Publications Warehouse

Cuttitta, Frank

1951-01-01

A method is presented for the distillation and photometric estimation of the oil yield of oil-bearing shales. The oil shale is distilled in a closed test tube and the oil extracted with toluene. The optical density of the toluene extract is used in the estimation of oil content and is converted to percentage of oil by reference to a standard curve. This curve is obtained by relating the oil yields determined by the Fischer assay method to the optical density of the toluene extract of the oil evolved by the new procedure. The new method gives results similar to those obtained by the Fischer assay method in a much shorter time. The applicability of the new method to oil-bearing shale and phosphatic shale has been tested.

Cotton yield estimation using very high-resolution digital images acquired on a low-cost small unmanned aerial vehicle

USDA-ARS?s Scientific Manuscript database

Yield estimation is a critical task in crop management. A number of traditional methods are available for crop yield estimation but they are costly, time-consuming and difficult to expand to a relatively large field. Remote sensing provides techniques to develop quick coverage over a field at any sc...

Yield and depth Estimation of Selected NTS Nuclear and SPE Chemical Explosions Using Source Equalization by modeling Local and Regional Seismograms (Invited)

NASA Astrophysics Data System (ADS)

Saikia, C. K.; Roman-nieves, J. I.; Woods, M. T.

2013-12-01

Source parameters of nuclear and chemical explosions are often estimated by matching either the corner frequency and spectral level of a single event or the spectral ratio when spectra from two events are available with known source parameters for one. In this study, we propose an alternative method in which waveforms from two or more events can be simultaneously equalized by setting the differential of the processed seismograms at one station from any two individual events to zero. The method involves convolving the equivalent Mueller-Murphy displacement source time function (MMDSTF) of one event with the seismogram of the second event and vice-versa, and then computing their difference seismogram. MMDSTF is computed at the elastic radius including both near and far-field terms. For this method to yield accurate source parameters, an inherent assumption is that green's functions for the any paired events from the source to a receiver are same. In the frequency limit of the seismic data, this is a reasonable assumption and is concluded based on the comparison of green's functions computed for flat-earth models at various source depths ranging from 100m to 1Km. Frequency domain analysis of the initial P wave is, however, sensitive to the depth phase interaction, and if tracked meticulously can help estimating the event depth. We applied this method to the local waveforms recorded from the three SPE shots and precisely determined their yields. These high-frequency seismograms exhibit significant lateral path effects in spectrogram analysis and 3D numerical computations, but the source equalization technique is independent of any variation as long as their instrument characteristics are well preserved. We are currently estimating the uncertainty in the derived source parameters assuming the yields of the SPE shots as unknown. We also collected regional waveforms from 95 NTS explosions at regional stations ALQ, ANMO, CMB, COR, JAS LON, PAS, PFO and RSSD. We are

Estimated winter wheat yield from crop growth predicted by LANDSAT

NASA Technical Reports Server (NTRS)

Kanemasu, E. T.

1977-01-01

An evapotranspiration and growth model for winter wheat is reported. The inputs are daily solar radiation, maximum temperature, minimum temperature, precipitation/irrigation and leaf area index. The meteorological data were obtained from National Weather Service while LAI was obtained from LANDSAT multispectral scanner. The output provides daily estimates of potential evapotranspiration, transpiration, evaporation, soil moisture (50 cm depth), percentage depletion, net photosynthesis and dry matter production. Winter wheat yields are correlated with transpiration and dry matter accumulation.

Exoplanet Classification and Yield Estimates for Direct Imaging Missions

NASA Astrophysics Data System (ADS)

Kopparapu, Ravi Kumar; Hébrard, Eric; Belikov, Rus; Batalha, Natalie M.; Mulders, Gijs D.; Stark, Chris; Teal, Dillon; Domagal-Goldman, Shawn; Mandell, Avi

2018-04-01

Future NASA concept missions that are currently under study, like the Habitable Exoplanet Imaging Mission (HabEx) and the Large Ultra-violet Optical Infra Red Surveyor, could discover a large diversity of exoplanets. We propose here a classification scheme that distinguishes exoplanets into different categories based on their size and incident stellar flux, for the purpose of providing the expected number of exoplanets observed (yield) with direct imaging missions. The boundaries of this classification can be computed using the known chemical behavior of gases and condensates at different pressures and temperatures in a planetary atmosphere. In this study, we initially focus on condensation curves for sphalerite ZnS, {{{H}}}2{{O}}, {CO}}2, and {CH}}4. The order in which these species condense in a planetary atmosphere define the boundaries between different classes of planets. Broadly, the planets are divided into rocky planets (0.5–1.0 R ⊕), super-Earths (1.0–1.75 R ⊕), sub-Neptunes (1.75–3.5 R ⊕), sub-Jovians (3.5–6.0 R ⊕), and Jovians (6–14.3 R ⊕) based on their planet sizes, and “hot,” “warm,” and “cold” based on the incident stellar flux. We then calculate planet occurrence rates within these boundaries for different kinds of exoplanets, η planet, using the community coordinated results of NASA’s Exoplanet Program Analysis Group’s Science Analysis Group-13 (SAG-13). These occurrence rate estimates are in turn used to estimate the expected exoplanet yields for direct imaging missions of different telescope diameters.

Finding the most accurate method to measure head circumference for fetal weight estimation.

PubMed

Schmidt, Ulrike; Temerinac, Dunja; Bildstein, Katharina; Tuschy, Benjamin; Mayer, Jade; Sütterlin, Marc; Siemer, Jörn; Kehl, Sven

2014-07-01

Accurate measurement of fetal head biometry is important for fetal weight estimation (FWE) and is therefore an important prognostic parameter for neonatal morbidity and mortality and a valuable tool for determining the further obstetric management. Measurement of the head circumference (HC) in particular is employed in many commonly used weight equations. The aim of the present study was to find the most accurate method to measure head circumference for fetal weight estimation. This prospective study included 481 term pregnancies. Inclusion criteria were a singleton pregnancy and ultrasound examination with complete fetal biometric parameters within 3 days of delivery, and an absence of structural or chromosomal malformations. Different methods were used for ultrasound measurement of the HC (ellipse-traced, ellipse-calculated, and circle-calculated). As a reference method, HC was also determined using a measuring tape immediately after birth. FWE was carried out with Hadlock formulas, including either HC or biparietal diameter (BPD), and differences were compared using percentage error (PE), absolute percentage error (APE), limits of agreement (LOA), and cumulative distribution. The ellipse-traced method showed the best results for FWE among all of the ultrasound methods assessed. It had the lowest median APE and the narrowest LOA. With regard to the cumulative distribution, it included the largest number of cases at a discrepancy level of ±10%. The accuracy of BPD was similar to that of the ellipse-traced method when it was used instead of HC for weight estimation. Differences between the three techniques for calculating HC were small but significant. For clinical use, the ellipse-traced method should be recommended. However, when BPD is used instead of HC for FWE, the accuracy is similar to that of the ellipse-traced method. The BPD might therefore be a good alternative to head measurements in estimating fetal weight. Copyright © 2014 Elsevier Ireland Ltd. All

Estimation of genetic parameters for milk yield in Murrah buffaloes by Bayesian inference.

PubMed

Breda, F C; Albuquerque, L G; Euclydes, R F; Bignardi, A B; Baldi, F; Torres, R A; Barbosa, L; Tonhati, H

2010-02-01

Random regression models were used to estimate genetic parameters for test-day milk yield in Murrah buffaloes using Bayesian inference. Data comprised 17,935 test-day milk records from 1,433 buffaloes. Twelve models were tested using different combinations of third-, fourth-, fifth-, sixth-, and seventh-order orthogonal polynomials of weeks of lactation for additive genetic and permanent environmental effects. All models included the fixed effects of contemporary group, number of daily milkings and age of cow at calving as covariate (linear and quadratic effect). In addition, residual variances were considered to be heterogeneous with 6 classes of variance. Models were selected based on the residual mean square error, weighted average of residual variance estimates, and estimates of variance components, heritabilities, correlations, eigenvalues, and eigenfunctions. Results indicated that changes in the order of fit for additive genetic and permanent environmental random effects influenced the estimation of genetic parameters. Heritability estimates ranged from 0.19 to 0.31. Genetic correlation estimates were close to unity between adjacent test-day records, but decreased gradually as the interval between test-days increased. Results from mean squared error and weighted averages of residual variance estimates suggested that a model considering sixth- and seventh-order Legendre polynomials for additive and permanent environmental effects, respectively, and 6 classes for residual variances, provided the best fit. Nevertheless, this model presented the largest degree of complexity. A more parsimonious model, with fourth- and sixth-order polynomials, respectively, for these same effects, yielded very similar genetic parameter estimates. Therefore, this last model is recommended for routine applications. Copyright 2010 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Sediment yield estimation in mountain catchments of the Camastra reservoir, southern Italy: a comparison among different empirical methods

NASA Astrophysics Data System (ADS)

Lazzari, Maurizio; Danese, Maria; Gioia, Dario; Piccarreta, Marco

2013-04-01

Sedimentary budget estimation is an important topic for both scientific and social community, because it is crucial to understand both dynamics of orogenic belts and many practical problems, such as soil conservation and sediment accumulation in reservoir. Estimations of sediment yield or denudation rates in southern-central Italy are generally obtained by simple empirical relationships based on statistical regression between geomorphic parameters of the drainage network and the measured suspended sediment yield at the outlet of several drainage basins or through the use of models based on sediment delivery ratio or on soil loss equations. In this work, we perform a study of catchment dynamics and an estimation of sedimentary yield for several mountain catchments of the central-western sector of the Basilicata region, southern Italy. Sediment yield estimation has been obtained through both an indirect estimation of suspended sediment yield based on the Tu index (mean annual suspension sediment yield, Ciccacci et al., 1980) and the application of the Rusle (Renard et al., 1997) and the USPED (Mitasova et al., 1996) empirical methods. The preliminary results indicate a reliable difference between the RUSLE and USPED methods and the estimation based on the Tu index; a critical data analysis of results has been carried out considering also the present-day spatial distribution of erosion, transport and depositional processes in relation to the maps obtained from the application of those different empirical methods. The studied catchments drain an artificial reservoir (i.e. the Camastra dam), where a detailed evaluation of the amount of historical sediment storage has been collected. Sediment yield estimation obtained by means of the empirical methods have been compared and checked with historical data of sediment accumulation measured in the artificial reservoir of the Camastra dam. The validation of such estimations of sediment yield at the scale of large catchments

Estimation efficiency of usage satellite derived and modelled biophysical products for yield forecasting

NASA Astrophysics Data System (ADS)

Kolotii, Andrii; Kussul, Nataliia; Skakun, Sergii; Shelestov, Andrii; Ostapenko, Vadim; Oliinyk, Tamara

2015-04-01

Efficient and timely crop monitoring and yield forecasting are important tasks for ensuring of stability and sustainable economic development [1]. As winter crops pay prominent role in agriculture of Ukraine - the main focus of this study is concentrated on winter wheat. In our previous research [2, 3] it was shown that usage of biophysical parameters of crops such as FAPAR (derived from Geoland-2 portal as for SPOT Vegetation data) is far more efficient for crop yield forecasting to NDVI derived from MODIS data - for available data. In our current work efficiency of usage such biophysical parameters as LAI, FAPAR, FCOVER (derived from SPOT Vegetation and PROBA-V data at resolution of 1 km and simulated within WOFOST model) and NDVI product (derived from MODIS) for winter wheat monitoring and yield forecasting is estimated. As the part of crop monitoring workflow (vegetation anomaly detection, vegetation indexes and products analysis) and yield forecasting SPIRITS tool developed by JRC is used. Statistics extraction is done for landcover maps created in SRI within FP-7 SIGMA project. Efficiency of usage satellite based and modelled with WOFOST model biophysical products is estimated. [1] N. Kussul, S. Skakun, A. Shelestov, O. Kussul, "Sensor Web approach to Flood Monitoring and Risk Assessment", in: IGARSS 2013, 21-26 July 2013, Melbourne, Australia, pp. 815-818. [2] F. Kogan, N. Kussul, T. Adamenko, S. Skakun, O. Kravchenko, O. Kryvobok, A. Shelestov, A. Kolotii, O. Kussul, and A. Lavrenyuk, "Winter wheat yield forecasting in Ukraine based on Earth observation, meteorological data and biophysical models," International Journal of Applied Earth Observation and Geoinformation, vol. 23, pp. 192-203, 2013. [3] Kussul O., Kussul N., Skakun S., Kravchenko O., Shelestov A., Kolotii A, "Assessment of relative efficiency of using MODIS data to winter wheat yield forecasting in Ukraine", in: IGARSS 2013, 21-26 July 2013, Melbourne, Australia, pp. 3235 - 3238.

Are rapid population estimates accurate? A field trial of two different assessment methods.

PubMed

Grais, Rebecca F; Coulombier, Denis; Ampuero, Julia; Lucas, Marcelino E S; Barretto, Avertino T; Jacquier, Guy; Diaz, Francisco; Balandine, Serge; Mahoudeau, Claude; Brown, Vincent

2006-09-01

Emergencies resulting in large-scale displacement often lead to populations resettling in areas where basic health services and sanitation are unavailable. To plan relief-related activities quickly, rapid population size estimates are needed. The currently recommended Quadrat method estimates total population by extrapolating the average population size living in square blocks of known area to the total site surface. An alternative approach, the T-Square, provides a population estimate based on analysis of the spatial distribution of housing units taken throughout a site. We field tested both methods and validated the results against a census in Esturro Bairro, Beira, Mozambique. Compared to the census (population: 9,479), the T-Square yielded a better population estimate (9,523) than the Quadrat method (7,681; 95% confidence interval: 6,160-9,201), but was more difficult for field survey teams to implement. Although applicable only to similar sites, several general conclusions can be drawn for emergency planning.

Simple agrometeorological models for estimating Guineagrass yield in Southeast Brazil.

PubMed

Pezzopane, José Ricardo Macedo; da Cruz, Pedro Gomes; Santos, Patricia Menezes; Bosi, Cristiam; de Araujo, Leandro Coelho

2014-09-01

The objective of this work was to develop and evaluate agrometeorological models to simulate the production of Guineagrass. For this purpose, we used forage yield from 54 growing periods between December 2004-January 2007 and April 2010-March 2012 in irrigated and non-irrigated pastures in São Carlos, São Paulo state, Brazil (latitude 21°57'42″ S, longitude 47°50'28″ W and altitude 860 m). Initially we performed linear regressions between the agrometeorological variables and the average dry matter accumulation rate for irrigated conditions. Then we determined the effect of soil water availability on the relative forage yield considering irrigated and non-irrigated pastures, by means of segmented linear regression among water balance and relative production variables (dry matter accumulation rates with and without irrigation). The models generated were evaluated with independent data related to 21 growing periods without irrigation in the same location, from eight growing periods in 2000 and 13 growing periods between December 2004-January 2007 and April 2010-March 2012. The results obtained show the satisfactory predictive capacity of the agrometeorological models under irrigated conditions based on univariate regression (mean temperature, minimum temperature and potential evapotranspiration or degreedays) or multivariate regression. The response of irrigation on production was well correlated with the climatological water balance variables (ratio between actual and potential evapotranspiration or between actual and maximum soil water storage). The models that performed best for estimating Guineagrass yield without irrigation were based on minimum temperature corrected by relative soil water storage, determined by the ratio between the actual soil water storage and the soil water holding capacity.irrigation in the same location, in 2000, 2010 and 2011. The results obtained show the satisfactory predictive capacity of the agrometeorological models under

Rapid and accurate species tree estimation for phylogeographic investigations using replicated subsampling.

PubMed

Hird, Sarah; Kubatko, Laura; Carstens, Bryan

2010-11-01

We describe a method for estimating species trees that relies on replicated subsampling of large data matrices. One application of this method is phylogeographic research, which has long depended on large datasets that sample intensively from the geographic range of the focal species; these datasets allow systematicists to identify cryptic diversity and understand how contemporary and historical landscape forces influence genetic diversity. However, analyzing any large dataset can be computationally difficult, particularly when newly developed methods for species tree estimation are used. Here we explore the use of replicated subsampling, a potential solution to the problem posed by large datasets, with both a simulation study and an empirical analysis. In the simulations, we sample different numbers of alleles and loci, estimate species trees using STEM, and compare the estimated to the actual species tree. Our results indicate that subsampling three alleles per species for eight loci nearly always results in an accurate species tree topology, even in cases where the species tree was characterized by extremely rapid divergence. Even more modest subsampling effort, for example one allele per species and two loci, was more likely than not (>50%) to identify the correct species tree topology, indicating that in nearly all cases, computing the majority-rule consensus tree from replicated subsampling provides a good estimate of topology. These results were supported by estimating the correct species tree topology and reasonable branch lengths for an empirical 10-locus great ape dataset. Copyright © 2010 Elsevier Inc. All rights reserved.

Accurate estimation of object location in an image sequence using helicopter flight data

NASA Technical Reports Server (NTRS)

Tang, Yuan-Liang; Kasturi, Rangachar

1994-01-01

In autonomous navigation, it is essential to obtain a three-dimensional (3D) description of the static environment in which the vehicle is traveling. For a rotorcraft conducting low-latitude flight, this description is particularly useful for obstacle detection and avoidance. In this paper, we address the problem of 3D position estimation for static objects from a monocular sequence of images captured from a low-latitude flying helicopter. Since the environment is static, it is well known that the optical flow in the image will produce a radiating pattern from the focus of expansion. We propose a motion analysis system which utilizes the epipolar constraint to accurately estimate 3D positions of scene objects in a real world image sequence taken from a low-altitude flying helicopter. Results show that this approach gives good estimates of object positions near the rotorcraft's intended flight-path.

A Theoretical Model for Estimation of Yield Strength of Fiber Metal Laminate

NASA Astrophysics Data System (ADS)

Bhat, Sunil; Nagesh, Suresh; Umesh, C. K.; Narayanan, S.

2017-08-01

The paper presents a theoretical model for estimation of yield strength of fiber metal laminate. Principles of elasticity and formulation of residual stress are employed to determine the stress state in metal layer of the laminate that is found to be higher than the stress applied over the laminate resulting in reduced yield strength of the laminate in comparison with that of the metal layer. The model is tested over 4A-3/2 Glare laminate comprising three thin aerospace 2014-T6 aluminum alloy layers alternately bonded adhesively with two prepregs, each prepreg built up of three uni-directional glass fiber layers laid in longitudinal and transverse directions. Laminates with prepregs of E-Glass and S-Glass fibers are investigated separately under uni-axial tension. Yield strengths of both the Glare variants are found to be less than that of aluminum alloy with use of S-Glass fiber resulting in higher laminate yield strength than with the use of E-Glass fiber. Results from finite element analysis and tensile tests conducted over the laminates substantiate the theoretical model.

Accurate reconstruction of viral quasispecies spectra through improved estimation of strain richness

PubMed Central

2015-01-01

Background Estimating the number of different species (richness) in a mixed microbial population has been a main focus in metagenomic research. Existing methods of species richness estimation ride on the assumption that the reads in each assembled contig correspond to only one of the microbial genomes in the population. This assumption and the underlying probabilistic formulations of existing methods are not useful for quasispecies populations where the strains are highly genetically related. The lack of knowledge on the number of different strains in a quasispecies population is observed to hinder the precision of existing Viral Quasispecies Spectrum Reconstruction (QSR) methods due to the uncontrolled reconstruction of a large number of in silico false positives. In this work, we formulated a novel probabilistic method for strain richness estimation specifically targeting viral quasispecies. By using this approach we improved our recently proposed spectrum reconstruction pipeline ViQuaS to achieve higher levels of precision in reconstructed quasispecies spectra without compromising the recall rates. We also discuss how one other existing popular QSR method named ShoRAH can be improved using this new approach. Results On benchmark data sets, our estimation method provided accurate richness estimates (< 0.2 median estimation error) and improved the precision of ViQuaS by 2%-13% and F-score by 1%-9% without compromising the recall rates. We also demonstrate that our estimation method can be used to improve the precision and F-score of ShoRAH by 0%-7% and 0%-5% respectively. Conclusions The proposed probabilistic estimation method can be used to estimate the richness of viral populations with a quasispecies behavior and to improve the accuracy of the quasispecies spectra reconstructed by the existing methods ViQuaS and ShoRAH in the presence of a moderate level of technical sequencing errors. Availability http://sourceforge.net/projects/viquas/ PMID:26678073

Comparison of specific-yield estimates for calculating evapotranspiration from diurnal groundwater-level fluctuations

NASA Astrophysics Data System (ADS)

Gribovszki, Zoltán

2018-05-01

Methods that use diurnal groundwater-level fluctuations are commonly used for shallow water-table environments to estimate evapotranspiration (ET) and recharge. The key element needed to obtain reliable estimates is the specific yield (Sy), a soil-water storage parameter that depends on unsaturated soil-moisture and water-table fluxes, among others. Soil-moisture profile measurement down to the water table, along with water-table-depth measurements, can provide a good opportunity to calculate Sy values even on a sub-daily scale. These values were compared with Sy estimates derived by traditional techniques, and it was found that slug-test-based Sy values gave the most similar results in a sandy soil environment. Therefore, slug-test methods, which are relatively cheap and require little time, were most suited to estimate Sy using diurnal fluctuations. The reason for this is that the timeframe of the slug-test measurement is very similar to the dynamic of the diurnal signal. The dynamic characteristic of Sy was also analyzed on a sub-daily scale (depending mostly on the speed of drainage from the soil profile) and a remarkable difference was found in Sy with respect to the rate of change of the water table. When comparing constant and sub-daily (dynamic) Sy values for ET estimation, the sub-daily Sy application yielded higher correlation, but only a slightly smaller deviation from the control ET method, compared with the usage of constant Sy.

Estimating patient dose from CT exams that use automatic exposure control: Development and validation of methods to accurately estimate tube current values.

PubMed

McMillan, Kyle; Bostani, Maryam; Cagnon, Christopher H; Yu, Lifeng; Leng, Shuai; McCollough, Cynthia H; McNitt-Gray, Michael F

2017-08-01

The vast majority of body CT exams are performed with automatic exposure control (AEC), which adapts the mean tube current to the patient size and modulates the tube current either angularly, longitudinally or both. However, most radiation dose estimation tools are based on fixed tube current scans. Accurate estimates of patient dose from AEC scans require knowledge of the tube current values, which is usually unavailable. The purpose of this work was to develop and validate methods to accurately estimate the tube current values prescribed by one manufacturer's AEC system to enable accurate estimates of patient dose. Methods were developed that took into account available patient attenuation information, user selected image quality reference parameters and x-ray system limits to estimate tube current values for patient scans. Methods consistent with AAPM Report 220 were developed that used patient attenuation data that were: (a) supplied by the manufacturer in the CT localizer radiograph and (b) based on a simulated CT localizer radiograph derived from image data. For comparison, actual tube current values were extracted from the projection data of each patient. Validation of each approach was based on data collected from 40 pediatric and adult patients who received clinically indicated chest (n = 20) and abdomen/pelvis (n = 20) scans on a 64 slice multidetector row CT (Sensation 64, Siemens Healthcare, Forchheim, Germany). For each patient dataset, the following were collected with Institutional Review Board (IRB) approval: (a) projection data containing actual tube current values at each projection view, (b) CT localizer radiograph (topogram) and (c) reconstructed image data. Tube current values were estimated based on the actual topogram (actual-topo) as well as the simulated topogram based on image data (sim-topo). Each of these was compared to the actual tube current values from the patient scan. In addition, to assess the accuracy of each method in estimating

Remote sensing and modelling of vegetation dynamics for early estimation and spatial analysis of grain yields in semiarid context in central Tunisia

NASA Astrophysics Data System (ADS)

Chahbi, Aicha; Zribi, Mehrez; Lili-Chabaane, Zohra

2016-04-01

In arid and semi-arid areas, population growth, urbanization, food security and climate change have an impact on agriculture in general and particular on the cereal production. Therefore to improve food security in arid countries, crop canopy monitoring and yield forecasting cereals are needed. Many models, based on the use of remote sensing or agro-meteorological models, have been developed to estimate the biomass and grain yield of cereals. Through the use of a rich database, acquired over a period of two years for more than 80 test fields, and from optical satellite SPOT/HRV images, the aim of the present study is to evaluate the feasibility of two yield prediction approaches. The first approach is based on the application of the semi-empirical growth model SAFY, developed to simulate the dynamics of the LAI and the grain yield, at the field scale. The model is able to reproduce the time evolution of the leaf area index of all fields with acceptable error. However, an inter-comparison between ground yield measurements and SAFY model simulations reveals that the yields are under-estimated by this model. We can explain the limits of the semi-empirical model SAFY by its simplicity and also by various factors that were not considered (fertilization, irrigation,...). To improve the yield estimation, a new approach is proposed: the grain yield is estimated in function of the LAI in the growth period between 25 March and 5 April. The LAI of this period is estimated by SAFY model. A linear relationship is developed between the measured grain yield and the LAI area of the maximum growth period.This approach is robust, the measured and estimated grain yields are well correlated. Following the validation of this approach, yield estimations are proposed for the entire studied site using the SPOT/HRV images.

OCO-2 Solar-induced Fluorescence Data Portal and Applications to Crop Yield Estimation

NASA Astrophysics Data System (ADS)

Zhai, A. J.; Jiang, J. H.; Frankenberg, C.; Yung, Y. L.; Choi, Y. S.

2016-12-01

Solar-induced fluorescence (SIF) is a direct byproduct of photosynthesis and is an index that can represent overall plant productivity level of any region around the globe. Recently, in 2014, NASA launched the Orbiting Carbon Observatory 2 (OCO-2) satellite, which collects SIF measurements at a higher spatial resolution than any previous instrument has. We have first assembled a web-based data portal, which can be easily utilized by both farmers and researchers, to allow convenient access to the SIF data from OCO-2. One possible use of SIF is to estimate agricultural status of crop fields anywhere in the world. We are using OCO-2 level 2 measurements in conjunction with the USDA's Cropland Data Layer and reported crop yield data to study how effectively SIF can estimate agricultural yield on various types of landscape and various species of crops. Results, methods, and future implications will be presented.

Transthoracic echocardiography: an accurate and precise method for estimating cardiac output in the critically ill patient.

PubMed

Mercado, Pablo; Maizel, Julien; Beyls, Christophe; Titeca-Beauport, Dimitri; Joris, Magalie; Kontar, Loay; Riviere, Antoine; Bonef, Olivier; Soupison, Thierry; Tribouilloy, Christophe; de Cagny, Bertrand; Slama, Michel

2017-06-09

% yielded a sensitivity of 88% and specificity of 66% for detecting a ΔCO-PAC of more than 10%. In critically ill mechanically ventilated patients, CO-TTE is an accurate and precise method for estimating CO. Furthermore, CO-TTE can accurately track variations in CO.

Accurate Orientation Estimation Using AHRS under Conditions of Magnetic Distortion

PubMed Central

Yadav, Nagesh; Bleakley, Chris

2014-01-01

Low cost, compact attitude heading reference systems (AHRS) are now being used to track human body movements in indoor environments by estimation of the 3D orientation of body segments. In many of these systems, heading estimation is achieved by monitoring the strength of the Earth's magnetic field. However, the Earth's magnetic field can be locally distorted due to the proximity of ferrous and/or magnetic objects. Herein, we propose a novel method for accurate 3D orientation estimation using an AHRS, comprised of an accelerometer, gyroscope and magnetometer, under conditions of magnetic field distortion. The system performs online detection and compensation for magnetic disturbances, due to, for example, the presence of ferrous objects. The magnetic distortions are detected by exploiting variations in magnetic dip angle, relative to the gravity vector, and in magnetic strength. We investigate and show the advantages of using both magnetic strength and magnetic dip angle for detecting the presence of magnetic distortions. The correction method is based on a particle filter, which performs the correction using an adaptive cost function and by adapting the variance during particle resampling, so as to place more emphasis on the results of dead reckoning of the gyroscope measurements and less on the magnetometer readings. The proposed method was tested in an indoor environment in the presence of various magnetic distortions and under various accelerations (up to 3 g). In the experiments, the proposed algorithm achieves <2° static peak-to-peak error and <5° dynamic peak-to-peak error, significantly outperforming previous methods. PMID:25347584

The validation study on a three-dimensional burn estimation smart-phone application: accurate, free and fast?

PubMed

Cheah, A K W; Kangkorn, T; Tan, E H; Loo, M L; Chong, S J

2018-01-01

Accurate total body surface area burned (TBSAB) estimation is a crucial aspect of early burn management. It helps guide resuscitation and is essential in the calculation of fluid requirements. Conventional methods of estimation can often lead to large discrepancies in burn percentage estimation. We aim to compare a new method of TBSAB estimation using a three-dimensional smart-phone application named 3D Burn Resuscitation (3D Burn) against conventional methods of estimation-Rule of Palm, Rule of Nines and the Lund and Browder chart. Three volunteer subjects were moulaged with simulated burn injuries of 25%, 30% and 35% total body surface area (TBSA), respectively. Various healthcare workers were invited to use both the 3D Burn application as well as the conventional methods stated above to estimate the volunteer subjects' burn percentages. Collective relative estimations across the groups showed that when used, the Rule of Palm, Rule of Nines and the Lund and Browder chart all over-estimated burns area by an average of 10.6%, 19.7%, and 8.3% TBSA, respectively, while the 3D Burn application under-estimated burns by an average of 1.9%. There was a statistically significant difference between the 3D Burn application estimations versus all three other modalities ( p  < 0.05). Time of using the application was found to be significantly longer than traditional methods of estimation. The 3D Burn application, although slower, allowed more accurate TBSAB measurements when compared to conventional methods. The validation study has shown that the 3D Burn application is useful in improving the accuracy of TBSAB measurement. Further studies are warranted, and there are plans to repeat the above study in a different centre overseas as part of a multi-centre study, with a view of progressing to a prospective study that compares the accuracy of the 3D Burn application against conventional methods on actual burn patients.

The Remote Food Photography Method Accurately Estimates Dry Powdered Foods-The Source of Calories for Many Infants.

PubMed

Duhé, Abby F; Gilmore, L Anne; Burton, Jeffrey H; Martin, Corby K; Redman, Leanne M

2016-07-01

Infant formula is a major source of nutrition for infants, with more than half of all infants in the United States consuming infant formula exclusively or in combination with breast milk. The energy in infant powdered formula is derived from the powder and not the water, making it necessary to develop methods that can accurately estimate the amount of powder used before reconstitution. Our aim was to assess the use of the Remote Food Photography Method to accurately estimate the weight of infant powdered formula before reconstitution among the standard serving sizes. For each serving size (1 scoop, 2 scoops, 3 scoops, and 4 scoops), a set of seven test bottles and photographs were prepared as follow: recommended gram weight of powdered formula of the respective serving size by the manufacturer; three bottles and photographs containing 15%, 10%, and 5% less powdered formula than recommended; and three bottles and photographs containing 5%, 10%, and 15% more powdered formula than recommended (n=28). Ratio estimates of the test photographs as compared to standard photographs were obtained using standard Remote Food Photography Method analysis procedures. The ratio estimates and the US Department of Agriculture data tables were used to generate food and nutrient information to provide the Remote Food Photography Method estimates. Equivalence testing using the two one-sided t tests approach was used to determine equivalence between the actual gram weights and the Remote Food Photography Method estimated weights for all samples, within each serving size, and within underprepared and overprepared bottles. For all bottles, the gram weights estimated by the Remote Food Photography Method were within 5% equivalence bounds with a slight underestimation of 0.05 g (90% CI -0.49 to 0.40; P<0.001) and mean percent error ranging between 0.32% and 1.58% among the four serving sizes. The maximum observed mean error was an overestimation of 1.58% of powdered formula by the Remote

Magnetic gaps in organic tri-radicals: From a simple model to accurate estimates.

PubMed

Barone, Vincenzo; Cacelli, Ivo; Ferretti, Alessandro; Prampolini, Giacomo

2017-03-14

The calculation of the energy gap between the magnetic states of organic poly-radicals still represents a challenging playground for quantum chemistry, and high-level techniques are required to obtain accurate estimates. On these grounds, the aim of the present study is twofold. From the one side, it shows that, thanks to recent algorithmic and technical improvements, we are able to compute reliable quantum mechanical results for the systems of current fundamental and technological interest. From the other side, proper parameterization of a simple Hubbard Hamiltonian allows for a sound rationalization of magnetic gaps in terms of basic physical effects, unraveling the role played by electron delocalization, Coulomb repulsion, and effective exchange in tuning the magnetic character of the ground state. As case studies, we have chosen three prototypical organic tri-radicals, namely, 1,3,5-trimethylenebenzene, 1,3,5-tridehydrobenzene, and 1,2,3-tridehydrobenzene, which differ either for geometric or electronic structure. After discussing the differences among the three species and their consequences on the magnetic properties in terms of the simple model mentioned above, accurate and reliable values for the energy gap between the lowest quartet and doublet states are computed by means of the so-called difference dedicated configuration interaction (DDCI) technique, and the final results are discussed and compared to both available experimental and computational estimates.

Using Smartphone Sensors for Improving Energy Expenditure Estimation

PubMed Central

Zhu, Jindan; Das, Aveek K.; Zeng, Yunze; Mohapatra, Prasant; Han, Jay J.

2015-01-01

Energy expenditure (EE) estimation is an important factor in tracking personal activity and preventing chronic diseases, such as obesity and diabetes. Accurate and real-time EE estimation utilizing small wearable sensors is a difficult task, primarily because the most existing schemes work offline or use heuristics. In this paper, we focus on accurate EE estimation for tracking ambulatory activities (walking, standing, climbing upstairs, or downstairs) of a typical smartphone user. We used built-in smartphone sensors (accelerometer and barometer sensor), sampled at low frequency, to accurately estimate EE. Using a barometer sensor, in addition to an accelerometer sensor, greatly increases the accuracy of EE estimation. Using bagged regression trees, a machine learning technique, we developed a generic regression model for EE estimation that yields upto 96% correlation with actual EE. We compare our results against the state-of-the-art calorimetry equations and consumer electronics devices (Fitbit and Nike+ FuelBand). The newly developed EE estimation algorithm demonstrated superior accuracy compared with currently available methods. The results were calibrated against COSMED K4b2 calorimeter readings. PMID:27170901

Using Smartphone Sensors for Improving Energy Expenditure Estimation.

PubMed

Pande, Amit; Zhu, Jindan; Das, Aveek K; Zeng, Yunze; Mohapatra, Prasant; Han, Jay J

2015-01-01

Energy expenditure (EE) estimation is an important factor in tracking personal activity and preventing chronic diseases, such as obesity and diabetes. Accurate and real-time EE estimation utilizing small wearable sensors is a difficult task, primarily because the most existing schemes work offline or use heuristics. In this paper, we focus on accurate EE estimation for tracking ambulatory activities (walking, standing, climbing upstairs, or downstairs) of a typical smartphone user. We used built-in smartphone sensors (accelerometer and barometer sensor), sampled at low frequency, to accurately estimate EE. Using a barometer sensor, in addition to an accelerometer sensor, greatly increases the accuracy of EE estimation. Using bagged regression trees, a machine learning technique, we developed a generic regression model for EE estimation that yields upto 96% correlation with actual EE. We compare our results against the state-of-the-art calorimetry equations and consumer electronics devices (Fitbit and Nike+ FuelBand). The newly developed EE estimation algorithm demonstrated superior accuracy compared with currently available methods. The results were calibrated against COSMED K4b2 calorimeter readings.

Estimates of genetic and environmental (co)variances for first lactation on milk yield, survival, and calving interval.

PubMed

Dong, M C; van Vleck, L D

1989-03-01

Variance and covariance components for milk yield, survival to second freshening, calving interval in first lactation were estimated by REML with the expectation and maximization algorithm for an animal model which included herd-year-season effects. Cows without calving interval but with milk yield were included. Each of the four data sets of 15 herds included about 3000 Holstein cows. Relationships across herds were ignored to enable inversion of the coefficient matrix of mixed model equations. Quadratics and their expectations were accumulated herd by herd. Heritability of milk yield (.32) agrees with reports by same methods. Heritabilities of survival (.11) and calving interval(.15) are slightly larger and genetic correlations smaller than results from different methods of estimation. Genetic correlation between milk yield and calving interval (.09) indicates genetic ability to produce more milk is lightly associated with decreased fertility.

Methods for the accurate estimation of confidence intervals on protein folding ϕ-values

PubMed Central

Ruczinski, Ingo; Sosnick, Tobin R.; Plaxco, Kevin W.

2006-01-01

ϕ-Values provide an important benchmark for the comparison of experimental protein folding studies to computer simulations and theories of the folding process. Despite the growing importance of ϕ measurements, however, formulas to quantify the precision with which ϕ is measured have seen little significant discussion. Moreover, a commonly employed method for the determination of standard errors on ϕ estimates assumes that estimates of the changes in free energy of the transition and folded states are independent. Here we demonstrate that this assumption is usually incorrect and that this typically leads to the underestimation of ϕ precision. We derive an analytical expression for the precision of ϕ estimates (assuming linear chevron behavior) that explicitly takes this dependence into account. We also describe an alternative method that implicitly corrects for the effect. By simulating experimental chevron data, we show that both methods accurately estimate ϕ confidence intervals. We also explore the effects of the commonly employed techniques of calculating ϕ from kinetics estimated at non-zero denaturant concentrations and via the assumption of parallel chevron arms. We find that these approaches can produce significantly different estimates for ϕ (again, even for truly linear chevron behavior), indicating that they are not equivalent, interchangeable measures of transition state structure. Lastly, we describe a Web-based implementation of the above algorithms for general use by the protein folding community. PMID:17008714

Analytic model to estimate thermonuclear neutron yield in z-pinches using the magnetic Noh problem

NASA Astrophysics Data System (ADS)

Allen, Robert C.

The objective was to build a model which could be used to estimate neutron yield in pulsed z-pinch experiments, benchmark future z-pinch simulation tools and to assist scaling for breakeven systems. To accomplish this, a recent solution to the magnetic Noh problem was utilized which incorporates a self-similar solution with cylindrical symmetry and azimuthal magnetic field (Velikovich, 2012). The self-similar solution provides the conditions needed to calculate the time dependent implosion dynamics from which batch burn is assumed and used to calculate neutron yield. The solution to the model is presented. The ion densities and time scales fix the initial mass and implosion velocity, providing estimates of the experimental results given specific initial conditions. Agreement is shown with experimental data (Coverdale, 2007). A parameter sweep was done to find the neutron yield, implosion velocity and gain for a range of densities and time scales for DD reactions and a curve fit was done to predict the scaling as a function of preshock conditions.

An accurate estimation method of kinematic viscosity for standard viscosity liquids

NASA Astrophysics Data System (ADS)

Kurano, Y.; Kobayashi, H.; Yoshida, K.; Imai, H.

1992-07-01

Deming's method of least squares is introduced to make an accurate kinematic viscosity estimation for a series of 13 standard-viscosity liquids at any desired temperature. The empirical ASTM kinematic viscosity-temperature equation is represented in the form loglog( v+c)=a-b log T, where v (in mm2. s-1) is the kinematic viscosity at temperature T (in K), a and b are the constants for a given liquid, and c has a variable value. In the present application, however, c is assumed to have a constant value for each standard-viscosity liquid, as do a and b in the ASTM equation. This assumption has since been verified experimentally for all standard-viscosity liquids. The kinematic viscosities for the 13 standard-viscosity liquids have been measured with a high accuracy in the temperature range of 20 40°C using a series of the NRLM capillary master viscometers with an automatic flow time detection system. The deviations between measured and estimated kinematic viscosities were less than ±0.04% for the 10 standard-viscosity liquids JS2.5 to JS2000 and ±0.11% for the 3 standard-viscosity liquids JS15H to JS200H, respectively. From the above investigation, it was revealed that the uncertainty in the present estimation method is less than one-third that in the usual ASTM method.

Cancer Risk Estimates from Space Flight Estimated Using Yields of Chromosome Damage in Astronaut's Blood Lymphocytes

NASA Technical Reports Server (NTRS)

George, Kerry A.; Rhone, J.; Chappell, L. J.; Cucinotta, F. A.

2011-01-01

To date, cytogenetic damage has been assessed in blood lymphocytes from more than 30 astronauts before and after they participated in long-duration space missions of three months or more on board the International Space Station. Chromosome damage was assessed using fluorescence in situ hybridization whole chromosome analysis techniques. For all individuals, the frequency of chromosome damage measured within a month of return from space was higher than their preflight yield, and biodosimetry estimates were within the range expected from physical dosimetry. Follow up analyses have been performed on most of the astronauts at intervals ranging from around 6 months to many years after flight, and the cytogenetic effects of repeat long-duration missions have so far been assessed in four individuals. Chromosomal aberrations in peripheral blood lymphocytes have been validated as biomarkers of cancer risk and cytogenetic damage can therefore be used to characterize excess health risk incurred by individual crewmembers after their respective missions. Traditional risk assessment models are based on epidemiological data obtained on Earth in cohorts exposed predominantly to acute doses of gamma-rays, and the extrapolation to the space environment is highly problematic, involving very large uncertainties. Cytogenetic damage could play a key role in reducing uncertainty in risk estimation because it is incurred directly in the space environment, using specimens from the astronauts themselves. Relative cancer risks were estimated from the biodosimetry data using the quantitative approach derived from the European Study Group on Cytogenetic Biomarkers and Health database. Astronauts were categorized into low, medium, or high tertiles according to their yield of chromosome damage. Age adjusted tertile rankings were used to estimate cancer risk and results were compared with values obtained using traditional modeling approaches. Individual tertile rankings increased after space

Machine-smoking studies of cigarette filter color to estimate tar yield by visual assessment and through the use of a colorimeter.

PubMed

Morton, Michael J; Williams, David L; Hjorth, Heather B; Smith, Jennifer H

2010-04-01

This paper explores using the intensity of the stain on the end of the filter ("filter color") as a vehicle for estimating cigarette tar yield, both by instrument reading of the filter color and by visual comparison to a template. The correlation of machine-measured tar yield to filter color measured with a colorimeter was reasonably strong and was relatively unaffected by different puff volumes or different tobacco moistures. However, the correlation of filter color to machine-measured nicotine yield was affected by the moisture content of the cigarette. Filter color, as measured by a colorimeter, was generally comparable to filter extraction of either nicotine or solanesol in its correlation to machine-smoked tar yields. It was found that the color of the tar stain changes over time. Panelists could generally correctly order the filters from machine-smoked cigarettes by tar yield using the intensity of the tar stain. However, there was considerable variation in the panelist-to-panelist tar yield estimates. The wide person-to-person variation in tar yield estimates, and other factors discussed in the text could severely limit the usefulness and practicality of this approach for visually estimating the tar yield of machine-smoked cigarettes. Copyright 2009 Elsevier Inc. All rights reserved.

Temperature Increase Reduces Global Yields of Major Crops in Four Independent Estimates

NASA Technical Reports Server (NTRS)

Zhao, Chuang; Liu, Bing; Piao, Shilong; Wang, Xuhui; Lobell, David B.; Huang, Yao; Huang, Mengtian; Yao, Yitong; Bassu, Simona; Ciais, Philippe;

Temperature increase reduces global yields of major crops in four independent estimates

PubMed Central

Zhao, Chuang; Piao, Shilong; Wang, Xuhui; Lobell, David B.; Huang, Yao; Huang, Mengtian; Yao, Yitong; Bassu, Simona; Ciais, Philippe; Durand, Jean-Louis; Elliott, Joshua; Ewert, Frank; Janssens, Ivan A.; Li, Tao; Lin, Erda; Liu, Qiang; Martre, Pierre; Peng, Shushi; Wallach, Daniel; Wang, Tao; Wu, Donghai; Liu, Zhuo; Zhu, Yan; Zhu, Zaichun; Asseng, Senthold

2017-01-01

Wheat, rice, maize, and soybean provide two-thirds of human caloric intake. Assessing the impact of global temperature increase on production of these crops is therefore critical to maintaining global food supply, but different studies have yielded different results. Here, we investigated the impacts of temperature on yields of the four crops by compiling extensive published results from four analytical methods: global grid-based and local point-based models, statistical regressions, and field-warming experiments. Results from the different methods consistently showed negative temperature impacts on crop yield at the global scale, generally underpinned by similar impacts at country and site scales. Without CO2 fertilization, effective adaptation, and genetic improvement, each degree-Celsius increase in global mean temperature would, on average, reduce global yields of wheat by 6.0%, rice by 3.2%, maize by 7.4%, and soybean by 3.1%. Results are highly heterogeneous across crops and geographical areas, with some positive impact estimates. Multimethod analyses improved the confidence in assessments of future climate impacts on global major crops and suggest crop- and region-specific adaptation strategies to ensure food security for an increasing world population. PMID:28811375

Temperature increase reduces global yields of major crops in four independent estimates.

PubMed

Zhao, Chuang; Liu, Bing; Piao, Shilong; Wang, Xuhui; Lobell, David B; Huang, Yao; Huang, Mengtian; Yao, Yitong; Bassu, Simona; Ciais, Philippe; Durand, Jean-Louis; Elliott, Joshua; Ewert, Frank; Janssens, Ivan A; Li, Tao; Lin, Erda; Liu, Qiang; Martre, Pierre; Müller, Christoph; Peng, Shushi; Peñuelas, Josep; Ruane, Alex C; Wallach, Daniel; Wang, Tao; Wu, Donghai; Liu, Zhuo; Zhu, Yan; Zhu, Zaichun; Asseng, Senthold

2017-08-29

Wheat, rice, maize, and soybean provide two-thirds of human caloric intake. Assessing the impact of global temperature increase on production of these crops is therefore critical to maintaining global food supply, but different studies have yielded different results. Here, we investigated the impacts of temperature on yields of the four crops by compiling extensive published results from four analytical methods: global grid-based and local point-based models, statistical regressions, and field-warming experiments. Results from the different methods consistently showed negative temperature impacts on crop yield at the global scale, generally underpinned by similar impacts at country and site scales. Without CO 2 fertilization, effective adaptation, and genetic improvement, each degree-Celsius increase in global mean temperature would, on average, reduce global yields of wheat by 6.0%, rice by 3.2%, maize by 7.4%, and soybean by 3.1%. Results are highly heterogeneous across crops and geographical areas, with some positive impact estimates. Multimethod analyses improved the confidence in assessments of future climate impacts on global major crops and suggest crop- and region-specific adaptation strategies to ensure food security for an increasing world population.

Invited review: A commentary on predictive cheese yield formulas.

PubMed

Emmons, D B; Modler, H W

2010-12-01

Predictive cheese yield formulas have evolved from one based only on casein and fat in 1895. Refinements have included moisture and salt in cheese and whey solids as separate factors, paracasein instead of casein, and exclusion of whey solids from moisture associated with cheese protein. The General, Barbano, and Van Slyke formulas were tested critically using yield and composition of milk, whey, and cheese from 22 vats of Cheddar cheese. The General formula is based on the sum of cheese components: fat, protein, moisture, salt, whey solids free of fat and protein, as well as milk salts associated with paracasein. The testing yielded unexpected revelations. It was startling that the sum of components in cheese was <100%; the mean was 99.51% (N × 6.31). The mean predicted yield was only 99.17% as a percentage of actual yields (PY%AY); PY%AY is a useful term for comparisons of yields among vats. The PY%AY correlated positively with the sum of components (SofC) in cheese. The apparent low estimation of SofC led to the idea of adjusting upwards, for each vat, the 5 measured components in the formula by the observed SofC, as a fraction. The mean of the adjusted predicted yields as percentages of actual yields was 99.99%. The adjusted forms of the General, Barbano, and Van Slyke formulas gave predicted yields equal to the actual yields. It was apparent that unadjusted yield formulas did not accurately predict yield; however, unadjusted PY%AY can be useful as a control tool for analyses of cheese and milk. It was unexpected that total milk protein in the adjusted General formula gave the same predicted yields as casein and paracasein, indicating that casein or paracasein may not always be necessary for successful yield prediction. The use of constants for recovery of fat and protein in the adjusted General formula gave adjusted predicted yields equal to actual yields, indicating that analyses of cheese for protein and fat may not always be necessary for yield prediction

Paddy crop yield estimation in Kashmir Himalayan rice bowl using remote sensing and simulation model.

PubMed

Muslim, Mohammad; Romshoo, Shakil Ahmad; Rather, A Q

2015-06-01

The Kashmir Himalayan region of India is expected to be highly prone to the change in agricultural land use because of its geo-ecological fragility, strategic location vis-à-vis the Himalayan landscape, its trans-boundary river basins, and inherent socio-economic instabilities. Food security and sustainability of the region are thus greatly challenged by these impacts. The effect of future climate change, increased competition for land and water, labor from non-agricultural sectors, and increasing population adds to this complex problem. In current study, paddy rice yield at regional level was estimated using GIS-based environment policy integrated climate (GEPIC) model. The general approach of current study involved combining regional level crop database, regional soil data base, farm management data, and climatic data outputs with GEPIC model. The simulated yield showed that estimated production to be 4305.55 kg/ha (43.05 q h(-1)). The crop varieties like Jhelum, K-39, Chenab, China 1039, China-1007, and Shalimar rice-1 grown in plains recorded average yield of 4783.3 kg/ha (47.83 q ha(-1)). Meanwhile, high altitude areas with varieties like Kohsaar, K-78 (Barkat), and K-332 recorded yield of 4102.2 kg/ha (41.02 q ha(-1)). The observed and simulated yield showed a good match with R (2) = 0.95, RMSE = 132.24 kg/ha, respectively.

Accurate estimations of electromagnetic transitions of Sn IV for stellar and interstellar media

NASA Astrophysics Data System (ADS)

Biswas, Swapan; Das, Arghya; Bhowmik, Anal; Majumder, Sonjoy

2018-04-01

Here we report on accurate ab initio calculations to study astrophysically important electromagnetic transition parameters among different low-lying states of Sn IV. Our ab initio calculations are based on the sophisticated relativistic coupled-cluster theory, which almost exhausts many important electron correlations. To establish the accuracy of the calculations, we compare our results with the available experiments and estimates the transition amplitudes in length and velocity gauged forms. Most of these allowed and forbidden transition wavelengths lie in the infrared region, and they can be observed in the different cool stellar and interstellar media. For the improvement of uncertainty, we use experimental energies to the estimations of the above transition parameters. The presented data will be helpful to find the abundances of the ion in different astrophysical and laboratory plasma.

Accurate estimations of electromagnetic transitions of Sn IV for stellar and interstellar media

NASA Astrophysics Data System (ADS)

Biswas, Swapan; Das, Arghya; Bhowmik, Anal; Majumder, Sonjoy

2018-07-01

Here, we report on accurate ab initio calculations to study astrophysically important electromagnetic transition parameters among different low-lying states of Sn IV. Our ab initio calculations are based on the sophisticated relativistic coupled cluster theory, which almost exhausts many important electron correlations. To establish the accuracy of the calculations, we compare our results with the available experiments and estimate the transition amplitudes in length and velocity gauged forms. Most of these allowed and forbidden transition wavelengths lie in the infrared region, and they can be observed in the different cool stellar and interstellar media. For the improvement of uncertainty, we use experimental energies to the estimations of the above transition parameters. The presented data will be helpful to find the abundances of the ion in different astrophysical and laboratory plasma.

Number of pins in two-stage stratified sampling for estimating herbage yield

Treesearch

William G. O' Regan; C. Eugene Conrad

1975-01-01

In a two-stage stratified procedure for sampling herbage yield, plots are stratified by a pin frame in stage one, and clipped. In stage two, clippings from selected plots are sorted, dried, and weighed. Sample size and distribution of plots between the two stages are determined by equations. A way to compute the effect of number of pins on the variance of estimated...

Repeatability estimates for oleoresin yield measurements in three species of the southern pines

Treesearch

James H. Roberds; Brain L. Strom

2006-01-01

Repeatability was estimated for constitutive oleoresin yield measurements in 10 stands of three species of pines native to southeastern United States. Trees of these species that discharge large quantities of oleoresin upon wounding are considered to be most resistant to attack by southern pine beetle (Dendroctonus frontalis Zimmermann). Oleoresin...

MIDAS robust trend estimator for accurate GPS station velocities without step detection

NASA Astrophysics Data System (ADS)

Blewitt, Geoffrey; Kreemer, Corné; Hammond, William C.; Gazeaux, Julien

2016-03-01

Automatic estimation of velocities from GPS coordinate time series is becoming required to cope with the exponentially increasing flood of available data, but problems detectable to the human eye are often overlooked. This motivates us to find an automatic and accurate estimator of trend that is resistant to common problems such as step discontinuities, outliers, seasonality, skewness, and heteroscedasticity. Developed here, Median Interannual Difference Adjusted for Skewness (MIDAS) is a variant of the Theil-Sen median trend estimator, for which the ordinary version is the median of slopes vij = (xj-xi)/(tj-ti) computed between all data pairs i > j. For normally distributed data, Theil-Sen and least squares trend estimates are statistically identical, but unlike least squares, Theil-Sen is resistant to undetected data problems. To mitigate both seasonality and step discontinuities, MIDAS selects data pairs separated by 1 year. This condition is relaxed for time series with gaps so that all data are used. Slopes from data pairs spanning a step function produce one-sided outliers that can bias the median. To reduce bias, MIDAS removes outliers and recomputes the median. MIDAS also computes a robust and realistic estimate of trend uncertainty. Statistical tests using GPS data in the rigid North American plate interior show ±0.23 mm/yr root-mean-square (RMS) accuracy in horizontal velocity. In blind tests using synthetic data, MIDAS velocities have an RMS accuracy of ±0.33 mm/yr horizontal, ±1.1 mm/yr up, with a 5th percentile range smaller than all 20 automatic estimators tested. Considering its general nature, MIDAS has the potential for broader application in the geosciences.

Using normalized difference vegetation index (NDVI) to estimate sugarcane yield and yield components

USDA-ARS?s Scientific Manuscript database

Sugarcane (Saccharum spp.) yield and yield components are important traits for growers and scientists to evaluate and select cultivars. Collection of these yield data would be labor intensive and time consuming in the early selection stages of sugarcane breeding cultivar development programs with a ...

Rapid and accurate estimation of release conditions in the javelin throw.

PubMed

Hubbard, M; Alaways, L W

1989-01-01

We have developed a system to measure initial conditions in the javelin throw rapidly enough to be used by the thrower for feedback in performance improvement. The system consists of three subsystems whose main tasks are: (A) acquisition of automatically digitized high speed (200 Hz) video x, y position data for the first 0.1-0.2 s of the javelin flight after release (B) estimation of five javelin release conditions from the x, y position data and (C) graphical presentation to the thrower of these release conditions and a simulation of the subsequent flight together with optimal conditions and flight for the sam release velocity. The estimation scheme relies on a simulation model and is at least an order of magnitude more accurate than previously reported measurements of javelin release conditions. The system provides, for the first time ever in any throwing event, the ability to critique nearly instantly in a precise, quantitative manner the crucial factors in the throw which determine the range. This should be expected to much greater control and consistency of throwing variables by athletes who use system and could even lead to an evolution of new throwing techniques.

Prediction of County-Level Corn Yields Using an Energy-Crop Growth Index.

NASA Astrophysics Data System (ADS)

Andresen, Jeffrey A.; Dale, Robert F.; Fletcher, Jerald J.; Preckel, Paul V.

1989-01-01

Weather conditions significantly affect corn yields. while weather remains as the major uncontrolled variable in crop production, an understanding of the influence of weather on yields can aid in early and accurate assessment of the impact of weather and climate on crop yields and allow for timely agricultural extension advisories to help reduce farm management costs and improve marketing, decisions. Based on data for four representative countries in Indiana from 1960 to 1984 (excluding 1970 because of the disastrous southern corn leaf blight), a model was developed to estimate corn (Zea mays L.) yields as a function of several composite soil-crop-weather variables and a technology-trend marker, applied nitrogen fertilizer (N). The model was tested by predicting corn yields for 15 other counties. A daily energy-crop growth (ECG) variable in which different weights were used for the three crop-weather variables which make up the daily ECG-solar radiation intercepted by the canopy, a temperature function, and the ratio of actual to potential evapotranspiration-performed better than when the ECG components were weighted equally. The summation of the weighted daily ECG over a relatively short period (36 days spanning silk) was found to provide the best index for predicting county average corn yield. Numerical estimation results indicate that the ratio of actual to potential evapotranspiration (ET/PET) is much more important than the other two ECG factors in estimating county average corn yield in Indiana.

Accurate estimation of motion blur parameters in noisy remote sensing image

NASA Astrophysics Data System (ADS)

Shi, Xueyan; Wang, Lin; Shao, Xiaopeng; Wang, Huilin; Tao, Zhong

2015-05-01

The relative motion between remote sensing satellite sensor and objects is one of the most common reasons for remote sensing image degradation. It seriously weakens image data interpretation and information extraction. In practice, point spread function (PSF) should be estimated firstly for image restoration. Identifying motion blur direction and length accurately is very crucial for PSF and restoring image with precision. In general, the regular light-and-dark stripes in the spectrum can be employed to obtain the parameters by using Radon transform. However, serious noise existing in actual remote sensing images often causes the stripes unobvious. The parameters would be difficult to calculate and the error of the result relatively big. In this paper, an improved motion blur parameter identification method to noisy remote sensing image is proposed to solve this problem. The spectrum characteristic of noisy remote sensing image is analyzed firstly. An interactive image segmentation method based on graph theory called GrabCut is adopted to effectively extract the edge of the light center in the spectrum. Motion blur direction is estimated by applying Radon transform on the segmentation result. In order to reduce random error, a method based on whole column statistics is used during calculating blur length. Finally, Lucy-Richardson algorithm is applied to restore the remote sensing images of the moon after estimating blur parameters. The experimental results verify the effectiveness and robustness of our algorithm.

Estimates of genetics and phenotypics parameters for the yield and quality of soybean seeds.

PubMed

Zambiazzi, E V; Bruzi, A T; Guilherme, S R; Pereira, D R; Lima, J G; Zuffo, A M; Ribeiro, F O; Mendes, A E S; Godinho, S H M; Carvalho, M L M

2017-09-27

Estimating genotype x environment (GxE) parameters for quality and yield in soybean seed grown in different environments in Minas Gerais State was the goal of this study, as well as to evaluate interaction effects of GxE for soybean seeds yield and quality. Seeds were produced in three locations in Minas Gerais State (Lavras, Inconfidentes, and Patos de Minas) in 2013/14 and 2014/15 seasons. Field experiments were conducted in randomized blocks in a factorial 17 x 6 (GxE), and three replications. Seed yield and quality were evaluated for germination in substrates paper and sand, seedling emergence, speed emergency index, mechanical damage by sodium hypochlorite, electrical conductivity, speed aging, vigor and viability of seeds by tetrazolium test in laboratory using completely randomized design. Quadratic component genotypic, GXE variance component, genotype determination coefficient, genetic variation coefficient and environmental variation coefficient were estimated using the Genes software. Percentage analysis of genotypes contribution, environments and genotype x environment interaction were conducted by sites combination two by two and three sites combination, using the R software. Considering genotypes selection of broad adaptation, TMG 1179 RR, CD 2737 RR, and CD 237 RR associated better yield performance at high physical and physiological potential of seed. Environmental effect was more expressive for most of the characters related to soybean seed quality. GxE interaction effects were expressive though genotypes did not present coincidental behavior in different environments.

Accurate paleointensities - the multi-method approach

NASA Astrophysics Data System (ADS)

de Groot, Lennart

2016-04-01

The accuracy of models describing rapid changes in the geomagnetic field over the past millennia critically depends on the availability of reliable paleointensity estimates. Over the past decade methods to derive paleointensities from lavas (the only recorder of the geomagnetic field that is available all over the globe and through geologic times) have seen significant improvements and various alternative techniques were proposed. The 'classical' Thellier-style approach was optimized and selection criteria were defined in the 'Standard Paleointensity Definitions' (Paterson et al, 2014). The Multispecimen approach was validated and the importance of additional tests and criteria to assess Multispecimen results must be emphasized. Recently, a non-heating, relative paleointensity technique was proposed -the pseudo-Thellier protocol- which shows great potential in both accuracy and efficiency, but currently lacks a solid theoretical underpinning. Here I present work using all three of the aforementioned paleointensity methods on suites of young lavas taken from the volcanic islands of Hawaii, La Palma, Gran Canaria, Tenerife, and Terceira. Many of the sampled cooling units are <100 years old, the actual field strength at the time of cooling is therefore reasonably well known. Rather intuitively, flows that produce coherent results from two or more different paleointensity methods yield the most accurate estimates of the paleofield. Furthermore, the results for some flows pass the selection criteria for one method, but fail in other techniques. Scrutinizing and combing all acceptable results yielded reliable paleointensity estimates for 60-70% of all sampled cooling units - an exceptionally high success rate. This 'multi-method paleointensity approach' therefore has high potential to provide the much-needed paleointensities to improve geomagnetic field models for the Holocene.

The yield and decay coefficients of exoelectrogenic bacteria in bioelectrochemical systems.

PubMed

Wilson, Erica L; Kim, Younggy

2016-05-01

In conventional wastewater treatment, waste sludge management and disposal contribute the major cost for wastewater treatment. Bioelectrochemical systems, as a potential alternative for future wastewater treatment and resources recovery, are expected to produce small amounts of waste sludge because exoelectrogenic bacteria grow on anaerobic respiration and form highly populated biofilms on bioanode surfaces. While waste sludge production is governed by the yield and decay coefficient, none of previous studies have quantified these kinetic constants for exoelectrogenic bacteria. For yield coefficient estimation, we modified McCarty's free energy-based model by using the bioanode potential for the free energy of the electron acceptor reaction. The estimated true yield coefficient ranged 0.1 to 0.3 g-VSS (volatile suspended solids) g-COD(-1) (chemical oxygen demand), which is similar to that of most anaerobic microorganisms. The yield coefficient was sensitively affected by the bioanode potential and pH while the substrate and bicarbonate concentrations had relatively minor effects on the yield coefficient. In lab-scale experiments using microbial electrolysis cells, the observed yield coefficient (including the effect of cell decay) was found to be 0.020 ± 0.008 g-VSS g-COD(-1), which is an order of magnitude smaller than the theoretical estimation. Based on the difference between the theoretical and experimental results, the decay coefficient was approximated to be 0.013 ± 0.002 d(-1). These findings indicate that bioelectrochemical systems have potential for future wastewater treatment with reduced waste sludge as well as for resources recovery. Also, the found kinetic information will allow accurate estimation of wastewater treatment performance in bioelectrochemical systems. Copyright © 2016 Elsevier Ltd. All rights reserved.

MIDAS robust trend estimator for accurate GPS station velocities without step detection

PubMed Central

Kreemer, Corné; Hammond, William C.; Gazeaux, Julien

2016-01-01

Abstract Automatic estimation of velocities from GPS coordinate time series is becoming required to cope with the exponentially increasing flood of available data, but problems detectable to the human eye are often overlooked. This motivates us to find an automatic and accurate estimator of trend that is resistant to common problems such as step discontinuities, outliers, seasonality, skewness, and heteroscedasticity. Developed here, Median Interannual Difference Adjusted for Skewness (MIDAS) is a variant of the Theil‐Sen median trend estimator, for which the ordinary version is the median of slopes vij = (xj–xi)/(tj–ti) computed between all data pairs i > j. For normally distributed data, Theil‐Sen and least squares trend estimates are statistically identical, but unlike least squares, Theil‐Sen is resistant to undetected data problems. To mitigate both seasonality and step discontinuities, MIDAS selects data pairs separated by 1 year. This condition is relaxed for time series with gaps so that all data are used. Slopes from data pairs spanning a step function produce one‐sided outliers that can bias the median. To reduce bias, MIDAS removes outliers and recomputes the median. MIDAS also computes a robust and realistic estimate of trend uncertainty. Statistical tests using GPS data in the rigid North American plate interior show ±0.23 mm/yr root‐mean‐square (RMS) accuracy in horizontal velocity. In blind tests using synthetic data, MIDAS velocities have an RMS accuracy of ±0.33 mm/yr horizontal, ±1.1 mm/yr up, with a 5th percentile range smaller than all 20 automatic estimators tested. Considering its general nature, MIDAS has the potential for broader application in the geosciences. PMID:27668140

MIDAS robust trend estimator for accurate GPS station velocities without step detection.

PubMed

Blewitt, Geoffrey; Kreemer, Corné; Hammond, William C; Gazeaux, Julien

2016-03-01

Automatic estimation of velocities from GPS coordinate time series is becoming required to cope with the exponentially increasing flood of available data, but problems detectable to the human eye are often overlooked. This motivates us to find an automatic and accurate estimator of trend that is resistant to common problems such as step discontinuities, outliers, seasonality, skewness, and heteroscedasticity. Developed here, Median Interannual Difference Adjusted for Skewness (MIDAS) is a variant of the Theil-Sen median trend estimator, for which the ordinary version is the median of slopes v ij  = ( x j -x i )/( t j -t i ) computed between all data pairs i  >  j . For normally distributed data, Theil-Sen and least squares trend estimates are statistically identical, but unlike least squares, Theil-Sen is resistant to undetected data problems. To mitigate both seasonality and step discontinuities, MIDAS selects data pairs separated by 1 year. This condition is relaxed for time series with gaps so that all data are used. Slopes from data pairs spanning a step function produce one-sided outliers that can bias the median. To reduce bias, MIDAS removes outliers and recomputes the median. MIDAS also computes a robust and realistic estimate of trend uncertainty. Statistical tests using GPS data in the rigid North American plate interior show ±0.23 mm/yr root-mean-square (RMS) accuracy in horizontal velocity. In blind tests using synthetic data, MIDAS velocities have an RMS accuracy of ±0.33 mm/yr horizontal, ±1.1 mm/yr up, with a 5th percentile range smaller than all 20 automatic estimators tested. Considering its general nature, MIDAS has the potential for broader application in the geosciences.

Specific Yields Estimated from Gravity Change during Pumping Test

NASA Astrophysics Data System (ADS)

Chen, K. H.; Hwang, C.; Chang, L. C.

2017-12-01

Specific yield (Sy) is the most important parameter to describe available groundwater capacity in an unconfined aquifer. When estimating Sy by a field pumping test, aquifer heterogeneity and well performers will cause a large uncertainty. In this study, we use a gravity-based method to estimate Sy. At the time of pumping test, amounts of mass (groundwater) are forced to be taken out. If drawdown corn is big and close enough to high precision gravimeter, the gravity change can be detected. The gravity-based method use gravity observations that are independent from traditional flow computation. Only the drawdown corn should be modeled with observed head and hydrogeology data. The gravity method can be used in most groundwater field tests, such as locally pumping/injection tests initiated by active man-made or annual variations due to natural sources. We apply our gravity method at few sites in Taiwan situated over different unconfined aquifer. Here pumping tests for Sy determinations were also carried out. We will discuss why the gravity method produces different results from traditional pumping test, field designs and limitations of the gravity method.

Using groundwater levels to estimate recharge

USGS Publications Warehouse

Healy, R.W.; Cook, P.G.

2002-01-01

Accurate estimation of groundwater recharge is extremely important for proper management of groundwater systems. Many different approaches exist for estimating recharge. This paper presents a review of methods that are based on groundwater-level data. The water-table fluctuation method may be the most widely used technique for estimating recharge; it requires knowledge of specific yield and changes in water levels over time. Advantages of this approach include its simplicity and an insensitivity to the mechanism by which water moves through the unsaturated zone. Uncertainty in estimates generated by this method relate to the limited accuracy with which specific yield can be determined and to the extent to which assumptions inherent in the method are valid. Other methods that use water levels (mostly based on the Darcy equation) are also described. The theory underlying the methods is explained. Examples from the literature are used to illustrate applications of the different methods.

Estimating the remaining useful life of bearings using a neuro-local linear estimator-based method.

PubMed

Ahmad, Wasim; Ali Khan, Sheraz; Kim, Jong-Myon

2017-05-01

Estimating the remaining useful life (RUL) of a bearing is required for maintenance scheduling. While the degradation behavior of a bearing changes during its lifetime, it is usually assumed to follow a single model. In this letter, bearing degradation is modeled by a monotonically increasing function that is globally non-linear and locally linearized. The model is generated using historical data that is smoothed with a local linear estimator. A neural network learns this model and then predicts future levels of vibration acceleration to estimate the RUL of a bearing. The proposed method yields reasonably accurate estimates of the RUL of a bearing at different points during its operational life.

Crop suitability monitoring for improved yield estimations with 100m PROBA-V data

NASA Astrophysics Data System (ADS)

Özüm Durgun, Yetkin; Gilliams, Sven; Gobin, Anne; Duveiller, Grégory; Djaby, Bakary; Tychon, Bernard

2015-04-01

This study has been realised within the framework of a PhD targeting to advance agricultural monitoring with improved yield estimations using SPOT VEGETATION remotely sensed data. For the first research question, the aim was to improve dry matter productivity (DMP) for C3 and C4 plants by adding a water stress factor. Additionally, the relation between the actual crop yield and DMP was studied. One of the limitations was the lack of crop specific maps which leads to the second research question on 'crop suitability monitoring'. The objective of this work is to create a methodological approach based on the spectral and temporal characteristics of PROBA-V images and ancillary data such as meteorology, soil and topographic data to improve the estimation of annual crop yields. The PROBA-V satellite was launched on 6th May 2013, and was designed to bridge the gap in space-borne vegetation measurements between SPOT-VGT (March 1998 - May 2014) and the upcoming Sentinel-3 satellites scheduled for launch in 2015/2016. PROBA -V has products in four spectral bands: BLUE (centred at 0.463 µm), RED (0.655 µm), NIR (0.845 µm), and SWIR (1.600 µm) with a spatial resolution ranging from 1km to 300m. Due to the construction of the sensor, the central camera can provide a 100m data product with a 5 to 8 days revisiting time. Although the 100m data product is still in test phase a methodology for crop suitability monitoring was developed. The multi-spectral composites, NDVI (Normalised Difference Vegetation Index) (NIR_RED/NIR+RED) and NDII (Normalised Difference Infrared Index) (NIR-SWIR/NIR+SWIR) profiles are used in addition to secondary data such as digital elevation data, precipitation, temperature, soil types and administrative boundaries to improve the accuracy of crop yield estimations. The methodology is evaluated on several FP7 SIGMA test sites for the 2014 - 2015 period. Reference data in the form of vector GIS with boundaries and cover type of agricultural fields are

Effects of Source RDP Models and Near-source Propagation: Implication for Seismic Yield Estimation

NASA Astrophysics Data System (ADS)

Saikia, C. K.; Helmberger, D. V.; Stead, R. J.; Woods, B. B.

- It has proven difficult to uniquely untangle the source and propagation effects on the observed seismic data from underground nuclear explosions, even when large quantities of near-source, broadband data are available for analysis. This leads to uncertainties in our ability to quantify the nuclear seismic source function and, consequently the accuracy of seismic yield estimates for underground explosions. Extensive deterministic modeling analyses of the seismic data recorded from underground explosions at a variety of test sites have been conducted over the years and the results of these studies suggest that variations in the seismic source characteristics between test sites may be contributing to the observed differences in the magnitude/yield relations applicable at those sites. This contributes to our uncertainty in the determination of seismic yield estimates for explosions at previously uncalibrated test sites. In this paper we review issues involving the relationship of Nevada Test Site (NTS) source scaling laws to those at other sites. The Joint Verification Experiment (JVE) indicates that a magnitude (mb) bias (δmb) exists between the Semipalatinsk test site (STS) in the former Soviet Union (FSU) and the Nevada test site (NTS) in the United States. Generally this δmb is attributed to differential attenuation in the upper-mantle beneath the two test sites. This assumption results in rather large estimates of yield for large mb tunnel shots at Novaya Zemlya. A re-examination of the US testing experiments suggests that this δmb bias can partly be explained by anomalous NTS (Pahute) source characteristics. This interpretation is based on the modeling of US events at a number of test sites. Using a modified Haskell source description, we investigated the influence of the source Reduced Displacement Potential (RDP) parameters ψ ∞ , K and B by fitting short- and long-period data simultaneously, including the near-field body and surface waves. In general

Development of estimation method for crop yield using MODIS satellite imagery data and process-based model for corn and soybean in US Corn-Belt region

NASA Astrophysics Data System (ADS)

Lee, J.; Kang, S.; Jang, K.; Ko, J.; Hong, S.

2012-12-01

Crop productivity is associated with the food security and hence, several models have been developed to estimate crop yield by combining remote sensing data with carbon cycle processes. In present study, we attempted to estimate crop GPP and NPP using algorithm based on the LUE model and a simplified respiration model. The state of Iowa and Illinois was chosen as the study site for estimating the crop yield for a period covering the 5 years (2006-2010), as it is the main Corn-Belt area in US. Present study focuses on developing crop-specific parameters for corn and soybean to estimate crop productivity and yield mapping using satellite remote sensing data. We utilized a 10 km spatial resolution daily meteorological data from WRF to provide cloudy-day meteorological variables but in clear-say days, MODIS-based meteorological data were utilized to estimate daily GPP, NPP, and biomass. County-level statistics on yield, area harvested, and productions were used to test model predicted crop yield. The estimated input meteorological variables from MODIS and WRF showed with good agreements with the ground observations from 6 Ameriflux tower sites in 2006. For examples, correlation coefficients ranged from 0.93 to 0.98 for Tmin and Tavg ; from 0.68 to 0.85 for daytime mean VPD; from 0.85 to 0.96 for daily shortwave radiation, respectively. We developed county-specific crop conversion coefficient, i.e. ratio of yield to biomass on 260 DOY and then, validated the estimated county-level crop yield with the statistical yield data. The estimated corn and soybean yields at the county level ranged from 671 gm-2 y-1 to 1393 gm-2 y-1 and from 213 gm-2 y-1 to 421 gm-2 y-1, respectively. The county-specific yield estimation mostly showed errors less than 10%. Furthermore, we estimated crop yields at the state level which were validated against the statistics data and showed errors less than 1%. Further analysis for crop conversion coefficient was conducted for 200 DOY and 280 DOY

Using NOAA/AVHRR based remote sensing data and PCR method for estimation of Aus rice yield in Bangladesh

NASA Astrophysics Data System (ADS)

Nizamuddin, Mohammad; Akhand, Kawsar; Roytman, Leonid; Kogan, Felix; Goldberg, Mitch

2015-06-01

Rice is a dominant food crop of Bangladesh accounting about 75 percent of agricultural land use for rice cultivation and currently Bangladesh is the world's fourth largest rice producing country. Rice provides about two-third of total calorie supply and about one-half of the agricultural GDP and one-sixth of the national income in Bangladesh. Aus is one of the main rice varieties in Bangladesh. Crop production, especially rice, the main food staple, is the most susceptible to climate change and variability. Any change in climate will, thus, increase uncertainty regarding rice production as climate is major cause year-to-year variability in rice productivity. This paper shows the application of remote sensing data for estimating Aus rice yield in Bangladesh using official statistics of rice yield with real time acquired satellite data from Advanced Very High Resolution Radiometer (AVHRR) sensor and Principal Component Regression (PCR) method was used to construct a model. The simulated result was compared with official agricultural statistics showing that the error of estimation of Aus rice yield was less than 10%. Remote sensing, therefore, is a valuable tool for estimating crop yields well in advance of harvest, and at a low cost.

Online evaluation of a commercial video image analysis system (Computer Vision System) to predict beef carcass red meat yield and for augmenting the assignment of USDA yield grades. United States Department of Agriculture.

PubMed

Cannell, R C; Belk, K E; Tatum, J D; Wise, J W; Chapman, P L; Scanga, J A; Smith, G C

2002-05-01

Objective quantification of differences in wholesale cut yields of beef carcasses at plant chain speeds is important for the application of value-based marketing. This study was conducted to evaluate the ability of a commercial video image analysis system, the Computer Vision System (CVS) to 1) predict commercially fabricated beef subprimal yield and 2) augment USDA yield grading, in order to improve accuracy of grade assessment. The CVS was evaluated as a fully installed production system, operating on a full-time basis at chain speeds. Steer and heifer carcasses (n = 296) were evaluated using CVS, as well as by USDA expert and online graders, before the fabrication of carcasses into industry-standard subprimal cuts. Expert yield grade (YG), online YG, CVS estimated carcass yield, and CVS measured ribeye area in conjunction with expert grader estimates of the remaining YG factors (adjusted fat thickness, percentage of kidney-pelvic-heart fat, hot carcass weight) accounted for 67, 39, 64, and 65% of the observed variation in fabricated yields of closely trimmed subprimals. The dual component CVS predicted wholesale cut yields more accurately than current online yield grading, and, in an augmentation system, CVS ribeye measurement replaced estimated ribeye area in determination of USDA yield grade, and the accuracy of cutability prediction was improved, under packing plant conditions and speeds, to a level close to that of expert graders applying grades at a comfortable rate of speed offline.

Estimation of genomic breeding values for milk yield in UK dairy goats.

PubMed

Mucha, S; Mrode, R; MacLaren-Lee, I; Coffey, M; Conington, J

2015-11-01

The objective of this study was to estimate genomic breeding values for milk yield in crossbred dairy goats. The research was based on data provided by 2 commercial goat farms in the UK comprising 590,409 milk yield records on 14,453 dairy goats kidding between 1987 and 2013. The population was created by crossing 3 breeds: Alpine, Saanen, and Toggenburg. In each generation the best performing animals were selected for breeding, and as a result, a synthetic breed was created. The pedigree file contained 30,139 individuals, of which 2,799 were founders. The data set contained test-day records of milk yield, lactation number, farm, age at kidding, and year and season of kidding. Data on milk composition was unavailable. In total 1,960 animals were genotyped with the Illumina 50K caprine chip. Two methods for estimation of genomic breeding value were compared-BLUP at the single nucleotide polymorphism level (BLUP-SNP) and single-step BLUP. The highest accuracy of 0.61 was obtained with single-step BLUP, and the lowest (0.36) with BLUP-SNP. Linkage disequilibrium (r(2), the squared correlation of the alleles at 2 loci) at 50 kb (distance between 2 SNP) was 0.18. This is the first attempt to implement genomic selection in UK dairy goats. Results indicate that the single-step method provides the highest accuracy for populations with a small number of genotyped individuals, where the number of genotyped males is low and females are predominant in the reference population. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Utilizing Adjoint-Based Error Estimates for Surrogate Models to Accurately Predict Probabilities of Events

DOE PAGES

Butler, Troy; Wildey, Timothy

2018-01-01

In thist study, we develop a procedure to utilize error estimates for samples of a surrogate model to compute robust upper and lower bounds on estimates of probabilities of events. We show that these error estimates can also be used in an adaptive algorithm to simultaneously reduce the computational cost and increase the accuracy in estimating probabilities of events using computationally expensive high-fidelity models. Specifically, we introduce the notion of reliability of a sample of a surrogate model, and we prove that utilizing the surrogate model for the reliable samples and the high-fidelity model for the unreliable samples gives preciselymore » the same estimate of the probability of the output event as would be obtained by evaluation of the original model for each sample. The adaptive algorithm uses the additional evaluations of the high-fidelity model for the unreliable samples to locally improve the surrogate model near the limit state, which significantly reduces the number of high-fidelity model evaluations as the limit state is resolved. Numerical results based on a recently developed adjoint-based approach for estimating the error in samples of a surrogate are provided to demonstrate (1) the robustness of the bounds on the probability of an event, and (2) that the adaptive enhancement algorithm provides a more accurate estimate of the probability of the QoI event than standard response surface approximation methods at a lower computational cost.« less

Utilizing Adjoint-Based Error Estimates for Surrogate Models to Accurately Predict Probabilities of Events

DOE Office of Scientific and Technical Information (OSTI.GOV)

Butler, Troy; Wildey, Timothy

In thist study, we develop a procedure to utilize error estimates for samples of a surrogate model to compute robust upper and lower bounds on estimates of probabilities of events. We show that these error estimates can also be used in an adaptive algorithm to simultaneously reduce the computational cost and increase the accuracy in estimating probabilities of events using computationally expensive high-fidelity models. Specifically, we introduce the notion of reliability of a sample of a surrogate model, and we prove that utilizing the surrogate model for the reliable samples and the high-fidelity model for the unreliable samples gives preciselymore » the same estimate of the probability of the output event as would be obtained by evaluation of the original model for each sample. The adaptive algorithm uses the additional evaluations of the high-fidelity model for the unreliable samples to locally improve the surrogate model near the limit state, which significantly reduces the number of high-fidelity model evaluations as the limit state is resolved. Numerical results based on a recently developed adjoint-based approach for estimating the error in samples of a surrogate are provided to demonstrate (1) the robustness of the bounds on the probability of an event, and (2) that the adaptive enhancement algorithm provides a more accurate estimate of the probability of the QoI event than standard response surface approximation methods at a lower computational cost.« less

Infrasound Propagation Modeling for Explosive Yield Estimation

NASA Astrophysics Data System (ADS)

Howard, J. E.; Golden, P.; Negraru, P.

2013-12-01

This study focuses on developing methods of estimating the size or yield of HE surface explosions from local and regional infrasound measurements in the southwestern United States. A munitions disposal facility near Mina, Nevada provides a repeating ground-truth source for this study, with charge weights ranging from 870 - 3800 lbs. Detonation logs and GPS synchronized videos were obtained for a sample of shots representing the full range of weights. These are used to calibrate a relationship between charge weight and spectral level from seismic waveforms recorded at the Nevada Seismic Array (NVAR) at a distance of 36 km. Origin times and yields for the remaining shots are inferred from the seismic recordings at NVAR. Infrasound arrivals from the detonations have been continuously recorded on three four-element, small aperture infrasound arrays since late 2009. NVIAR is collocated with NVAR at a range of approximately 36 km to the northeast. FALN and DNIAR are located at ranges of 154 km to the north, and 293 km to the southeast respectively. Travel times and amplitudes for stratospheric arrivals at DNIAR show strong seasonal variability with the largest amplitudes and celerities occurring during the winter months when the stratospheric winds are favorable. Stratospheric celerities for FNIAR to the north are more consistent as they are not strongly affected by the predominantly meridional stratospheric winds. Tropospheric arrivals at all three arrays show considerable variability that does not appear to be a seasonal effect. Naval Research Laboratory Ground to Space (NRL-G2S) Mesoscale models are used to specify the atmosphere along the propagation path for each detonation. Ray-tracing is performed for each source/receiver pair to identify events for which the models closely match the travel-time observations. This subset of events is used to establish preliminary wind correction formulas using wind values from the G2S profile for the entire propagation path. These

Estimating milk yield and value losses from increased somatic cell count on US dairy farms.

PubMed

Hadrich, J C; Wolf, C A; Lombard, J; Dolak, T M

2018-04-01

Milk loss due to increased somatic cell counts (SCC) results in economic losses for dairy producers. This research uses 10 mo of consecutive dairy herd improvement data from 2013 and 2014 to estimate milk yield loss using SCC as a proxy for clinical and subclinical mastitis. A fixed effects regression was used to examine factors that affected milk yield while controlling for herd-level management. Breed, milking frequency, days in milk, seasonality, SCC, cumulative months with SCC greater than 100,000 cells/mL, lactation, and herd size were variables included in the regression analysis. The cumulative months with SCC above a threshold was included as a proxy for chronic mastitis. Milk yield loss increased as the number of test days with SCC ≥100,000 cells/mL increased. Results from the regression were used to estimate a monetary value of milk loss related to SCC as a function of cow and operation related explanatory variables for a representative dairy cow. The largest losses occurred from increased cumulative test days with a SCC ≥100,000 cells/mL, with daily losses of $1.20/cow per day in the first month to $2.06/cow per day in mo 10. Results demonstrate the importance of including the duration of months above a threshold SCC when estimating milk yield losses. Cows with chronic mastitis, measured by increased consecutive test days with SCC ≥100,000 cells/mL, resulted in higher milk losses than cows with a new infection. This provides farm managers with a method to evaluate the trade-off between treatment and culling decisions as it relates to mastitis control and early detection. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Identification of saline soils with multi-year remote sensing of crop yields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lobell, D; Ortiz-Monasterio, I; Gurrola, F C

2006-10-17

Soil salinity is an important constraint to agricultural sustainability, but accurate information on its variation across agricultural regions or its impact on regional crop productivity remains sparse. We evaluated the relationships between remotely sensed wheat yields and salinity in an irrigation district in the Colorado River Delta Region. The goals of this study were to (1) document the relative importance of salinity as a constraint to regional wheat production and (2) develop techniques to accurately identify saline fields. Estimates of wheat yield from six years of Landsat data agreed well with ground-based records on individual fields (R{sup 2} = 0.65).more » Salinity measurements on 122 randomly selected fields revealed that average 0-60 cm salinity levels > 4 dS m{sup -1} reduced wheat yields, but the relative scarcity of such fields resulted in less than 1% regional yield loss attributable to salinity. Moreover, low yield was not a reliable indicator of high salinity, because many other factors contributed to yield variability in individual years. However, temporal analysis of yield images showed a significant fraction of fields exhibited consistently low yields over the six year period. A subsequent survey of 60 additional fields, half of which were consistently low yielding, revealed that this targeted subset had significantly higher salinity at 30-60 cm depth than the control group (p = 0.02). These results suggest that high subsurface salinity is associated with consistently low yields in this region, and that multi-year yield maps derived from remote sensing therefore provide an opportunity to map salinity across agricultural regions.« less

Estimates of nitrate loads and yields from groundwater to streams in the Chesapeake Bay watershed based on land use and geology

USGS Publications Warehouse

Terziotti, Silvia; Capel, Paul D.; Tesoriero, Anthony J.; Hopple, Jessica A.; Kronholm, Scott C.

2018-03-07

The water quality of the Chesapeake Bay may be adversely affected by dissolved nitrate carried in groundwater discharge to streams. To estimate the concentrations, loads, and yields of nitrate from groundwater to streams for the Chesapeake Bay watershed, a regression model was developed based on measured nitrate concentrations from 156 small streams with watersheds less than 500 square miles (mi2 ) at baseflow. The regression model has three predictive variables: geologic unit, percent developed land, and percent agricultural land. Comparisons of estimated and actual values within geologic units were closely matched. The coefficient of determination (R2 ) for the model was 0.6906. The model was used to calculate baseflow nitrate concentrations at over 83,000 National Hydrography Dataset Plus Version 2 catchments and aggregated to 1,966 total 12-digit hydrologic units in the Chesapeake Bay watershed. The modeled output geospatial data layers provided estimated annual loads and yields of nitrate from groundwater into streams. The spatial distribution of annual nitrate yields from groundwater estimated by this method was compared to the total watershed yields of all sources estimated from a Chesapeake Bay SPAtially Referenced Regressions On Watershed attributes (SPARROW) water-quality model. The comparison showed similar spatial patterns. The regression model for groundwater contribution had similar but lower yields, suggesting that groundwater is an important source of nitrogen for streams in the Chesapeake Bay watershed.

Estimating daily fat yield from a single milking on test day for herds with a robotic milking system.

PubMed

Peeters, R; Galesloot, P J B

2002-03-01

The objective of this study was to estimate the daily fat yield and fat percentage from one sampled milking per cow per test day in an automatic milking system herd, when the milking times and milk yields of all individual milkings are recorded by the automatic milking system. Multiple regression models were used to estimate the 24-h fat percentage when only one milking is sampled for components and milk yields and milking times are known for all milkings in the 24-h period before the sampled milking. In total, 10,697 cow test day records, from 595 herd tests at 91 Dutch herds milked with an automatic milking system, were used. The best model to predict 24-h fat percentage included fat percentage, protein percentage, milk yield and milking interval of the sampled milking, milk yield, and milking interval of the preceding milking, and the interaction between milking interval and the ratio of fat and protein percentage of the sampled milking. This model gave a standard deviation of the prediction error (SE) for 24-h fat percentage of 0.321 and a correlation between the predicted and actual 24-h fat percentage of 0.910. For the 24-h fat yield, we found SE = 90 g and correlation = 0.967. This precision is slightly better than that of present a.m.-p.m. testing schemes. Extra attention must be paid to correctly matching the sample jars and the milkings. Furthermore, milkings with an interval of less than 4 h must be excluded from sampling as well as milkings that are interrupted or that follow an interrupted milking. Under these restrictions (correct matching, interval of at least 4 h, and no interrupted milking), one sampled milking suffices to get a satisfactory estimate for the test-day fat yield.

EarthSat spring wheat yield system test 1975

NASA Technical Reports Server (NTRS)

1976-01-01

The results of an operational test of the EarthSat System during the period 1 June - 30 August 1975 over the spring wheat regions of North Dakota, South Dakota, and Minnesota are presented. The errors associated with each sub-element of the system during the operational test and the sensitivity of the complete system and each major functional sub-element of the system to the observed errors were evaluated. Evaluations and recommendations for future operational users of the system include: (1) changes in various system sub-elements, (2) changes in the yield model to affect improved accuracy, (3) changes in the number of geobased cells needed to develop an accurate aggregated yield estimate, (4) changes associated with the implementation of future operational satellites and data processing systems, and (5) detailed system documentation.

Single-cell entropy for accurate estimation of differentiation potency from a cell's transcriptome

NASA Astrophysics Data System (ADS)

Teschendorff, Andrew E.; Enver, Tariq

2017-06-01

The ability to quantify differentiation potential of single cells is a task of critical importance. Here we demonstrate, using over 7,000 single-cell RNA-Seq profiles, that differentiation potency of a single cell can be approximated by computing the signalling promiscuity, or entropy, of a cell's transcriptome in the context of an interaction network, without the need for feature selection. We show that signalling entropy provides a more accurate and robust potency estimate than other entropy-based measures, driven in part by a subtle positive correlation between the transcriptome and connectome. Signalling entropy identifies known cell subpopulations of varying potency and drug resistant cancer stem-cell phenotypes, including those derived from circulating tumour cells. It further reveals that expression heterogeneity within single-cell populations is regulated. In summary, signalling entropy allows in silico estimation of the differentiation potency and plasticity of single cells and bulk samples, providing a means to identify normal and cancer stem-cell phenotypes.

Single-cell entropy for accurate estimation of differentiation potency from a cell's transcriptome

PubMed Central

Teschendorff, Andrew E.; Enver, Tariq

2017-01-01

The ability to quantify differentiation potential of single cells is a task of critical importance. Here we demonstrate, using over 7,000 single-cell RNA-Seq profiles, that differentiation potency of a single cell can be approximated by computing the signalling promiscuity, or entropy, of a cell's transcriptome in the context of an interaction network, without the need for feature selection. We show that signalling entropy provides a more accurate and robust potency estimate than other entropy-based measures, driven in part by a subtle positive correlation between the transcriptome and connectome. Signalling entropy identifies known cell subpopulations of varying potency and drug resistant cancer stem-cell phenotypes, including those derived from circulating tumour cells. It further reveals that expression heterogeneity within single-cell populations is regulated. In summary, signalling entropy allows in silico estimation of the differentiation potency and plasticity of single cells and bulk samples, providing a means to identify normal and cancer stem-cell phenotypes. PMID:28569836

Accurate van der Waals coefficients from density functional theory

PubMed Central

Tao, Jianmin; Perdew, John P.; Ruzsinszky, Adrienn

2012-01-01

The van der Waals interaction is a weak, long-range correlation, arising from quantum electronic charge fluctuations. This interaction affects many properties of materials. A simple and yet accurate estimate of this effect will facilitate computer simulation of complex molecular materials and drug design. Here we develop a fast approach for accurate evaluation of dynamic multipole polarizabilities and van der Waals (vdW) coefficients of all orders from the electron density and static multipole polarizabilities of each atom or other spherical object, without empirical fitting. Our dynamic polarizabilities (dipole, quadrupole, octupole, etc.) are exact in the zero- and high-frequency limits, and exact at all frequencies for a metallic sphere of uniform density. Our theory predicts dynamic multipole polarizabilities in excellent agreement with more expensive many-body methods, and yields therefrom vdW coefficients C6, C8, C10 for atom pairs with a mean absolute relative error of only 3%. PMID:22205765

Spectral estimates of intercepted solar radiation by corn and soybean canopies

NASA Technical Reports Server (NTRS)

Gallo, K. P.; Brooks, C. C.; Daughtry, C. S. T.; Bauer, M. E.; Vanderbilt, V. C.

1982-01-01

Attention is given to the development of methods for combining spectral and meteorological data in crop yield models which are capable of providing accurate estimates of crop condition and yields throughout the growing season. The present investigation is concerned with initial tests of these concepts using spectral and agronomic data acquired in controlled experiments. The data were acquired at the Purdue University Agronomy Farm, 10 km northwest of West Lafayette, Indiana. Data were obtained throughout several growing seasons for corn and soybeans. Five methods or models for predicting yields were examined. On the basis of the obtained results, it is concluded that estimating intercepted solar radiation using spectral data is a viable approach for merging spectral and meteorological data in crop yield models.

Comparing algorithms for estimating foliar biomass of conifers in the Pacific Northwest

Treesearch

Crystal L. Raymond; Donald McKenzie

2013-01-01

Accurate estimates of foliar biomass (FB) are important for quantifying carbon storage in forest ecosystems, but FB is not always reported in regional or national inventories. Foliar biomass also drives key ecological processes in ecosystem models. Published algorithms for estimating FB in conifer species of the Pacific Northwest can yield signifi cantly different...

Atomic Oxygen Erosion Yield Predictive Tool for Spacecraft Polymers in Low Earth Orbit

NASA Technical Reports Server (NTRS)

Bank, Bruce A.; de Groh, Kim K.; Backus, Jane A.

2008-01-01

A predictive tool was developed to estimate the low Earth orbit (LEO) atomic oxygen erosion yield of polymers based on the results of the Polymer Erosion and Contamination Experiment (PEACE) Polymers experiment flown as part of the Materials International Space Station Experiment 2 (MISSE 2). The MISSE 2 PEACE experiment accurately measured the erosion yield of a wide variety of polymers and pyrolytic graphite. The 40 different materials tested were selected specifically to represent a variety of polymers used in space as well as a wide variety of polymer chemical structures. The resulting erosion yield data was used to develop a predictive tool which utilizes chemical structure and physical properties of polymers that can be measured in ground laboratory testing to predict the in-space atomic oxygen erosion yield of a polymer. The properties include chemical structure, bonding information, density and ash content. The resulting predictive tool has a correlation coefficient of 0.914 when compared with actual MISSE 2 space data for 38 polymers and pyrolytic graphite. The intent of the predictive tool is to be able to make estimates of atomic oxygen erosion yields for new polymers without requiring expensive and time consumptive in-space testing.

Prediction of beef carcass salable yield and trimmable fat using bioelectrical impedance analysis.

PubMed

Zollinger, B L; Farrow, R L; Lawrence, T E; Latman, N S

2010-03-01

Bioelectrical impedance technology (BIA) is capable of providing an objective method of beef carcass yield estimation with the rapidity of yield grading. Electrical resistance (Rs), reactance (Xc), impedance (I), hot carcass weight (HCW), fat thickness between the 12th and 13th ribs (FT), estimated percentage kidney, pelvic, and heart fat (KPH%), longissimus muscle area (LMA), length between electrodes (LGE) as well as three derived carcass values that included electrical volume (EVOL), reactive density (XcD), and resistive density (RsD) were determined for the carcasses of 41 commercially fed cattle. Carcasses were subsequently fabricated into salable beef products reflective of industry standards. Equations were developed to predict percentage salable carcass yield (SY%) and percentage trimmable fat (FT%). Resulting equations accounted for 81% and 84% of variation in SY% and FT%, respectively. These results indicate that BIA technology is an accurate predictor of beef carcass composition. Copyright 2009 Elsevier Ltd. All rights reserved.

Frost trends and their estimated impact on yield in the Australian wheatbelt

PubMed Central

Zheng, Bangyou; Chapman, Scott C.; Christopher, Jack T.; Frederiks, Troy M.; Chenu, Karine

2015-01-01

Radiant spring frosts occurring during reproductive developmental stages can result in catastrophic yield loss for wheat producers. To better understand the spatial and temporal variability of frost, the occurrence and impact of frost events on rain-fed wheat production was estimated across the Australian wheatbelt for 1957–2013 using a 0.05 ° gridded weather data set. Simulated yield outcomes at 60 key locations were compared with those for virtual genotypes with different levels of frost tolerance. Over the last six decades, more frost events, later last frost day, and a significant increase in frost impact on yield were found in certain regions of the Australian wheatbelt, in particular in the South-East and West. Increasing trends in frost-related yield losses were simulated in regions where no significant trend of frost occurrence was observed, due to higher mean temperatures accelerating crop development and causing sensitive post-heading stages to occur earlier, during the frost risk period. Simulations indicated that with frost-tolerant lines the mean national yield could be improved by up to 20% through (i) reduced frost damage (~10% improvement) and (ii) the ability to use earlier sowing dates (adding a further 10% improvement). In the simulations, genotypes with an improved frost tolerance to temperatures 1 °C lower than the current 0 °C reference provided substantial benefit in most cropping regions, while greater tolerance (to 3 °C lower temperatures) brought further benefits in the East. The results indicate that breeding for improved reproductive frost tolerance should remain a priority for the Australian wheat industry, despite warming climates. PMID:25922479

Frost trends and their estimated impact on yield in the Australian wheatbelt.

PubMed

Zheng, Bangyou; Chapman, Scott C; Christopher, Jack T; Frederiks, Troy M; Chenu, Karine

2015-06-01

Radiant spring frosts occurring during reproductive developmental stages can result in catastrophic yield loss for wheat producers. To better understand the spatial and temporal variability of frost, the occurrence and impact of frost events on rain-fed wheat production was estimated across the Australian wheatbelt for 1957-2013 using a 0.05 ° gridded weather data set. Simulated yield outcomes at 60 key locations were compared with those for virtual genotypes with different levels of frost tolerance. Over the last six decades, more frost events, later last frost day, and a significant increase in frost impact on yield were found in certain regions of the Australian wheatbelt, in particular in the South-East and West. Increasing trends in frost-related yield losses were simulated in regions where no significant trend of frost occurrence was observed, due to higher mean temperatures accelerating crop development and causing sensitive post-heading stages to occur earlier, during the frost risk period. Simulations indicated that with frost-tolerant lines the mean national yield could be improved by up to 20% through (i) reduced frost damage (~10% improvement) and (ii) the ability to use earlier sowing dates (adding a further 10% improvement). In the simulations, genotypes with an improved frost tolerance to temperatures 1 °C lower than the current 0 °C reference provided substantial benefit in most cropping regions, while greater tolerance (to 3 °C lower temperatures) brought further benefits in the East. The results indicate that breeding for improved reproductive frost tolerance should remain a priority for the Australian wheat industry, despite warming climates. © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology.

BIOACCESSIBILITY TESTS ACCURATELY ESTIMATE ...

EPA Pesticide Factsheets

Hazards of soil-borne Pb to wild birds may be more accurately quantified if the bioavailability of that Pb is known. To better understand the bioavailability of Pb to birds, we measured blood Pb concentrations in Japanese quail (Coturnix japonica) fed diets containing Pb-contaminated soils. Relative bioavailabilities were expressed by comparison with blood Pb concentrations in quail fed a Pb acetate reference diet. Diets containing soil from five Pb-contaminated Superfund sites had relative bioavailabilities from 33%-63%, with a mean of about 50%. Treatment of two of the soils with P significantly reduced the bioavailability of Pb. The bioaccessibility of the Pb in the test soils was then measured in six in vitro tests and regressed on bioavailability. They were: the “Relative Bioavailability Leaching Procedure” (RBALP) at pH 1.5, the same test conducted at pH 2.5, the “Ohio State University In vitro Gastrointestinal” method (OSU IVG), the “Urban Soil Bioaccessible Lead Test”, the modified “Physiologically Based Extraction Test” and the “Waterfowl Physiologically Based Extraction Test.” All regressions had positive slopes. Based on criteria of slope and coefficient of determination, the RBALP pH 2.5 and OSU IVG tests performed very well. Speciation by X-ray absorption spectroscopy demonstrated that, on average, most of the Pb in the sampled soils was sorbed to minerals (30%), bound to organic matter 24%, or present as Pb sulfate 18%. Ad

The limits of crop productivity: validating theoretical estimates and determining the factors that limit crop yields in optimal environments

NASA Technical Reports Server (NTRS)

Bugbee, B.; Monje, O.

1992-01-01

Plant scientists have sought to maximize the yield of food crops since the beginning of agriculture. There are numerous reports of record food and biomass yields (per unit area) in all major crop plants, but many of the record yield reports are in error because they exceed the maximal theoretical rates of the component processes. In this article, we review the component processes that govern yield limits and describe how each process can be individually measured. This procedure has helped us validate theoretical estimates and determine what factors limit yields in optimal environments.

SpotCaliper: fast wavelet-based spot detection with accurate size estimation.

PubMed

Püspöki, Zsuzsanna; Sage, Daniel; Ward, John Paul; Unser, Michael

2016-04-15

SpotCaliper is a novel wavelet-based image-analysis software providing a fast automatic detection scheme for circular patterns (spots), combined with the precise estimation of their size. It is implemented as an ImageJ plugin with a friendly user interface. The user is allowed to edit the results by modifying the measurements (in a semi-automated way), extract data for further analysis. The fine tuning of the detections includes the possibility of adjusting or removing the original detections, as well as adding further spots. The main advantage of the software is its ability to capture the size of spots in a fast and accurate way. http://bigwww.epfl.ch/algorithms/spotcaliper/ zsuzsanna.puspoki@epfl.ch Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Automatic yield-line analysis of slabs using discontinuity layout optimization

PubMed Central

Gilbert, Matthew; He, Linwei; Smith, Colin C.; Le, Canh V.

2014-01-01

The yield-line method of analysis is a long established and extremely effective means of estimating the maximum load sustainable by a slab or plate. However, although numerous attempts to automate the process of directly identifying the critical pattern of yield-lines have been made over the past few decades, to date none has proved capable of reliably analysing slabs of arbitrary geometry. Here, it is demonstrated that the discontinuity layout optimization (DLO) procedure can successfully be applied to such problems. The procedure involves discretization of the problem using nodes inter-connected by potential yield-line discontinuities, with the critical layout of these then identified using linear programming. The procedure is applied to various benchmark problems, demonstrating that highly accurate solutions can be obtained, and showing that DLO provides a truly systematic means of directly and reliably automatically identifying yield-line patterns. Finally, since the critical yield-line patterns for many problems are found to be quite complex in form, a means of automatically simplifying these is presented. PMID:25104905

Easy and accurate variance estimation of the nonparametric estimator of the partial area under the ROC curve and its application.

PubMed

Yu, Jihnhee; Yang, Luge; Vexler, Albert; Hutson, Alan D

2016-06-15

The receiver operating characteristic (ROC) curve is a popular technique with applications, for example, investigating an accuracy of a biomarker to delineate between disease and non-disease groups. A common measure of accuracy of a given diagnostic marker is the area under the ROC curve (AUC). In contrast with the AUC, the partial area under the ROC curve (pAUC) looks into the area with certain specificities (i.e., true negative rate) only, and it can be often clinically more relevant than examining the entire ROC curve. The pAUC is commonly estimated based on a U-statistic with the plug-in sample quantile, making the estimator a non-traditional U-statistic. In this article, we propose an accurate and easy method to obtain the variance of the nonparametric pAUC estimator. The proposed method is easy to implement for both one biomarker test and the comparison of two correlated biomarkers because it simply adapts the existing variance estimator of U-statistics. In this article, we show accuracy and other advantages of the proposed variance estimation method by broadly comparing it with previously existing methods. Further, we develop an empirical likelihood inference method based on the proposed variance estimator through a simple implementation. In an application, we demonstrate that, depending on the inferences by either the AUC or pAUC, we can make a different decision on a prognostic ability of a same set of biomarkers. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

GPS Water Vapor Tomography Based on Accurate Estimations of the GPS Tropospheric Parameters

NASA Astrophysics Data System (ADS)

Champollion, C.; Masson, F.; Bock, O.; Bouin, M.; Walpersdorf, A.; Doerflinger, E.; van Baelen, J.; Brenot, H.

2003-12-01

The Global Positioning System (GPS) is now a common technique for the retrieval of zenithal integrated water vapor (IWV). Further applications in meteorology need also slant integrated water vapor (SIWV) which allow to precisely define the high variability of tropospheric water vapor at different temporal and spatial scales. Only precise estimations of IWV and horizontal gradients allow the estimation of accurate SIWV. We present studies developed to improve the estimation of tropospheric water vapor from GPS data. Results are obtained from several field experiments (MAP, ESCOMPTE, OHM-CV, IHOP, .). First IWV are estimated using different GPS processing strategies and results are compared to radiosondes. The role of the reference frame and the a priori constraints on the coordinates of the fiducial and local stations is generally underestimated. It seems to be of first order in the estimation of the IWV. Second we validate the estimated horizontal gradients comparing zenith delay gradients and single site gradients. IWV, gradients and post-fit residuals are used to construct slant integrated water delays. Validation of the SIWV is under progress comparing GPS SIWV, Lidar measurements and high resolution meteorological models (Meso-NH). A careful analysis of the post-fit residuals is needed to separate tropospheric signal from multipaths. The slant tropospheric delays are used to study the 3D heterogeneity of the troposphere. We develop a tomographic software to model the three-dimensional distribution of the tropospheric water vapor from GPS data. The software is applied to the ESCOMPTE field experiment, a dense network of 17 dual frequency GPS receivers operated in southern France. Three inversions have been successfully compared to three successive radiosonde launches. Good resolution is obtained up to heights of 3000 m.

An evaluation of the lamb vision system as a predictor of lamb carcass red meat yield percentage.

PubMed

Brady, A S; Belk, K E; LeValley, S B; Dalsted, N L; Scanga, J A; Tatum, J D; Smith, G C

2003-06-01

An objective method for predicting red meat yield in lamb carcasses is needed to accurately assess true carcass value. This study was performed to evaluate the ability of the lamb vision system (LVS; Research Management Systems USA, Fort Collins, CO) to predict fabrication yields of lamb carcasses. Lamb carcasses (n = 246) were evaluated using LVS and hot carcass weight (HCW), as well as by USDA expert and on-line graders, before fabrication of carcass sides to either bone-in or boneless cuts. On-line whole number, expert whole-number, and expert nearest-tenth USDA yield grades and LVS + HCW estimates accounted for 53, 52, 58, and 60%, respectively, of the observed variability in boneless, saleable meat yields, and accounted for 56, 57, 62, and 62%, respectively, of the variation in bone-in, saleable meat yields. The LVS + HCW system predicted 77, 65, 70, and 87% of the variation in weights of boneless shoulders, racks, loins, and legs, respectively, and 85, 72, 75, and 86% of the variation in weights of bone-in shoulders, racks, loins, and legs, respectively. Addition of longissimus muscle area (REA), adjusted fat thickness (AFT), or both REA and AFT to LVS + HCW models resulted in improved prediction of boneless saleable meat yields by 5, 3, and 5 percentage points, respectively. Bone-in, saleable meat yield estimations were improved in predictive accuracy by 7.7, 6.6, and 10.1 percentage points, and in precision, when REA alone, AFT alone, or both REA and AFT, respectively, were added to the LVS + HCW output models. Use of LVS + HCW to predict boneless red meat yields of lamb carcasses was more accurate than use of current on-line whole-number, expert whole-number, or expert nearest-tenth USDA yield grades. Thus, LVS + HCW output, when used alone or in combination with AFT and/or REA, improved on-line estimation of boneless cut yields from lamb carcasses. The ability of LVS + HCW to predict yields of wholesale cuts suggests that LVS could be used as an objective

Estimation methods and parameter assessment for ethanol yields from total soluble solids of sweet sorghum

USDA-ARS?s Scientific Manuscript database

Estimation methods and evaluation of ethanol yield from sweet sorghum (Sorghum bicolor (L.) Moench.) based on agronomic production traits and juice characteristics is important for developing parents and inbred lines of sweet sorghum that can be used by the bio-ethanol industry. The objectives of th...

Estimating Gravity Biases with Wavelets in Support of a 1-cm Accurate Geoid Model

NASA Astrophysics Data System (ADS)

Ahlgren, K.; Li, X.

2017-12-01

Systematic errors that reside in surface gravity datasets are one of the major hurdles in constructing a high-accuracy geoid model at high resolutions. The National Oceanic and Atmospheric Administration's (NOAA) National Geodetic Survey (NGS) has an extensive historical surface gravity dataset consisting of approximately 10 million gravity points that are known to have systematic biases at the mGal level (Saleh et al. 2013). As most relevant metadata is absent, estimating and removing these errors to be consistent with a global geopotential model and airborne data in the corresponding wavelength is quite a difficult endeavor. However, this is crucial to support a 1-cm accurate geoid model for the United States. With recently available independent gravity information from GRACE/GOCE and airborne gravity from the NGS Gravity for the Redefinition of the American Vertical Datum (GRAV-D) project, several different methods of bias estimation are investigated which utilize radial basis functions and wavelet decomposition. We estimate a surface gravity value by incorporating a satellite gravity model, airborne gravity data, and forward-modeled topography at wavelet levels according to each dataset's spatial wavelength. Considering the estimated gravity values over an entire gravity survey, an estimate of the bias and/or correction for the entire survey can be found and applied. In order to assess the accuracy of each bias estimation method, two techniques are used. First, each bias estimation method is used to predict the bias for two high-quality (unbiased and high accuracy) geoid slope validation surveys (GSVS) (Smith et al. 2013 & Wang et al. 2017). Since these surveys are unbiased, the various bias estimation methods should reflect that and provide an absolute accuracy metric for each of the bias estimation methods. Secondly, the corrected gravity datasets from each of the bias estimation methods are used to build a geoid model. The accuracy of each geoid model

MODIS Data Assimilation in the CROPGRO model for improving soybean yield estimations

NASA Astrophysics Data System (ADS)

Richetti, J.; Monsivais-Huertero, A.; Ahmad, I.; Judge, J.

2017-12-01

Soybean is one of the main agricultural commodities in the world. Thus, having better estimates of its agricultural production is important. Improving the soybean crop models in Brazil is crucial for better understanding of the soybean market and enhancing decision making, because Brazil is the second largest soybean producer in the world, Parana state is responsible for almost 20% of it, and by itself would be the fourth greatest soybean producer in the world. Data assimilation techniques provide a method to improve spatio-temporal continuity of crops through integration of remotely sensed observations and crop growth models. This study aims to use MODIS EVI to improve DSSAT-CROPGRO soybean yield estimations in the Parana state, southern Brazil. The method uses the Ensemble Kalman filter which assimilates MODIS Terra and Aqua combined products (MOD13Q1 and MYD13Q1) into the CROPGRO model to improve the agricultural production estimates through update of light interception data over time. Expected results will be validated with monitored commercial farms during the period of 2013-2014.

Image Based Mango Fruit Detection, Localisation and Yield Estimation Using Multiple View Geometry

PubMed Central

Stein, Madeleine; Bargoti, Suchet; Underwood, James

2016-01-01

This paper presents a novel multi-sensor framework to efficiently identify, track, localise and map every piece of fruit in a commercial mango orchard. A multiple viewpoint approach is used to solve the problem of occlusion, thus avoiding the need for labour-intensive field calibration to estimate actual yield. Fruit are detected in images using a state-of-the-art faster R-CNN detector, and pair-wise correspondences are established between images using trajectory data provided by a navigation system. A novel LiDAR component automatically generates image masks for each canopy, allowing each fruit to be associated with the corresponding tree. The tracked fruit are triangulated to locate them in 3D, enabling a number of spatial statistics per tree, row or orchard block. A total of 522 trees and 71,609 mangoes were scanned on a Calypso mango orchard near Bundaberg, Queensland, Australia, with 16 trees counted by hand for validation, both on the tree and after harvest. The results show that single, dual and multi-view methods can all provide precise yield estimates, but only the proposed multi-view approach can do so without calibration, with an error rate of only 1.36% for individual trees. PMID:27854271

Satellite-based assessment of grassland yields

NASA Astrophysics Data System (ADS)

Grant, K.; Siegmund, R.; Wagner, M.; Hartmann, S.

2015-04-01

Cutting date and frequency are important parameters determining grassland yields in addition to the effects of weather, soil conditions, plant composition and fertilisation. Because accurate and area-wide data of grassland yields are currently not available, cutting frequency can be used to estimate yields. In this project, a method to detect cutting dates via surface changes in radar images is developed. The combination of this method with a grassland yield model will result in more reliable and regional-wide numbers of grassland yields. For the test-phase of the monitoring project, a study area situated southeast of Munich, Germany, was chosen due to its high density of managed grassland. For determining grassland cutting robust amplitude change detection techniques are used evaluating radar amplitude or backscatter statistics before and after the cutting event. CosmoSkyMed and Sentinel-1A data were analysed. All detected cuts were verified according to in-situ measurements recorded in a GIS database. Although the SAR systems had various acquisition geometries, the amount of detected grassland cut was quite similar. Of 154 tested grassland plots, covering in total 436 ha, 116 and 111 cuts were detected using CosmoSkyMed and Sentinel-1A radar data, respectively. Further improvement of radar data processes as well as additional analyses with higher sample number and wider land surface coverage will follow for optimisation of the method and for validation and generalisation of the results of this feasibility study. The automation of this method will than allow for an area-wide and cost efficient cutting date detection service improving grassland yield models.

Dating Tips for Divergence-Time Estimation.

PubMed

O'Reilly, Joseph E; Dos Reis, Mario; Donoghue, Philip C J

2015-11-01

The molecular clock is the only viable means of establishing an accurate timescale for Life on Earth, but it remains reliant on a capricious fossil record for calibration. 'Tip-dating' promises a conceptual advance, integrating fossil species among their living relatives using molecular/morphological datasets and evolutionary models. Fossil species of known age establish calibration directly, and their phylogenetic uncertainty is accommodated through the co-estimation of time and topology. However, challenges remain, including a dearth of effective models of morphological evolution, rate correlation, the non-random nature of missing characters in fossil data, and, most importantly, accommodating uncertainty in fossil age. We show uncertainty in fossil-dating propagates to divergence-time estimates, yielding estimates that are older and less precise than those based on traditional node calibration. Ultimately, node and tip calibrations are not mutually incompatible and may be integrated to achieve more accurate and precise evolutionary timescales. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Simple yet Accurate Method for the Estimation of the Biovolume of Planktonic Microorganisms.

PubMed

Saccà, Alessandro

2016-01-01

Determining the biomass of microbial plankton is central to the study of fluxes of energy and materials in aquatic ecosystems. This is typically accomplished by applying proper volume-to-carbon conversion factors to group-specific abundances and biovolumes. A critical step in this approach is the accurate estimation of biovolume from two-dimensional (2D) data such as those available through conventional microscopy techniques or flow-through imaging systems. This paper describes a simple yet accurate method for the assessment of the biovolume of planktonic microorganisms, which works with any image analysis system allowing for the measurement of linear distances and the estimation of the cross sectional area of an object from a 2D digital image. The proposed method is based on Archimedes' principle about the relationship between the volume of a sphere and that of a cylinder in which the sphere is inscribed, plus a coefficient of 'unellipticity' introduced here. Validation and careful evaluation of the method are provided using a variety of approaches. The new method proved to be highly precise with all convex shapes characterised by approximate rotational symmetry, and combining it with an existing method specific for highly concave or branched shapes allows covering the great majority of cases with good reliability. Thanks to its accuracy, consistency, and low resources demand, the new method can conveniently be used in substitution of any extant method designed for convex shapes, and can readily be coupled with automated cell imaging technologies, including state-of-the-art flow-through imaging devices.

A Simple yet Accurate Method for the Estimation of the Biovolume of Planktonic Microorganisms

PubMed Central

2016-01-01

Determining the biomass of microbial plankton is central to the study of fluxes of energy and materials in aquatic ecosystems. This is typically accomplished by applying proper volume-to-carbon conversion factors to group-specific abundances and biovolumes. A critical step in this approach is the accurate estimation of biovolume from two-dimensional (2D) data such as those available through conventional microscopy techniques or flow-through imaging systems. This paper describes a simple yet accurate method for the assessment of the biovolume of planktonic microorganisms, which works with any image analysis system allowing for the measurement of linear distances and the estimation of the cross sectional area of an object from a 2D digital image. The proposed method is based on Archimedes’ principle about the relationship between the volume of a sphere and that of a cylinder in which the sphere is inscribed, plus a coefficient of ‘unellipticity’ introduced here. Validation and careful evaluation of the method are provided using a variety of approaches. The new method proved to be highly precise with all convex shapes characterised by approximate rotational symmetry, and combining it with an existing method specific for highly concave or branched shapes allows covering the great majority of cases with good reliability. Thanks to its accuracy, consistency, and low resources demand, the new method can conveniently be used in substitution of any extant method designed for convex shapes, and can readily be coupled with automated cell imaging technologies, including state-of-the-art flow-through imaging devices. PMID:27195667

Estimating crop yields and crop evapotranspiration distributions from remote sensing and geospatial agricultural data

NASA Astrophysics Data System (ADS)

Smith, T.; McLaughlin, D.

2017-12-01

Growing more crops to provide a secure food supply to an increasing global population will further stress land and water resources that have already been significantly altered by agriculture. The connection between production and resource use depends on crop yields and unit evapotranspiration (UET) rates that vary greatly, over both time and space. For regional and global analyses of food security it is appropriate to treat yield and UET as uncertain variables conditioned on climatic and soil properties. This study describes how probability distributions of these variables can be estimated by combining remotely sensed land use and evapotranspiration data with in situ agronomic and soils data, all available at different resolutions and coverages. The results reveal the influence of water and temperature stress on crop yield at large spatial scales. They also provide a basis for stochastic modeling and optimization procedures that explicitly account for uncertainty in the environmental factors that affect food production.

Estimating yields of salt- and water-stressed forages with remote sensing in the visible and near infrared.

PubMed

Poss, J A; Russell, W B; Grieve, C M

2006-01-01

In arid irrigated regions, the proportion of crop production under deficit irrigation with poorer quality water is increasing as demand for fresh water soars and efforts to prevent saline water table development occur. Remote sensing technology to quantify salinity and water stress effects on forage yield can be an important tool to address yield loss potential when deficit irrigating with poor water quality. Two important forages, alfalfa (Medicago sativa L.) and tall wheatgrass (Agropyron elongatum L.), were grown in a volumetric lysimeter facility where rootzone salinity and water content were varied and monitored. Ground-based hyperspectral canopy reflectance in the visible and near infrared (NIR) were related to forage yields from a broad range of salinity and water stress conditions. Canopy reflectance spectra were obtained in the 350- to 1000-nm region from two viewing angles (nadir view, 45 degrees from nadir). Nadir view vegetation indices (VI) were not as strongly correlated with leaf area index changes attributed to water and salinity stress treatments for both alfalfa and wheatgrass. From a list of 71 VIs, two were selected for a multiple linear-regression model that estimated yield under varying salinity and water stress conditions. With data obtained during the second harvest of a three-harvest 100-d growing period, regression coefficients for each crop were developed and then used with the model to estimate fresh weights for preceding and succeeding harvests during the same 100-d interval. The model accounted for 72% of the variation in yields in wheatgrass and 94% in yields of alfalfa within the same salinity and water stress treatment period. The model successfully predicted yield in three out of four cases when applied to the first and third harvest yields. Correlations between indices and yield increased as canopy development progressed. Growth reductions attributed to simultaneous salinity and water stress were well characterized, but the

Rapid, cost-effective and accurate quantification of Yucca schidigera Roezl. steroidal saponins using HPLC-ELSD method.

PubMed

Tenon, Mathieu; Feuillère, Nicolas; Roller, Marc; Birtić, Simona

2017-04-15

Yucca GRAS-labelled saponins have been and are increasingly used in food/feed, pharmaceutical or cosmetic industries. Existing techniques presently used for Yucca steroidal saponin quantification remain either inaccurate and misleading or accurate but time consuming and cost prohibitive. The method reported here addresses all of the above challenges. HPLC/ELSD technique is an accurate and reliable method that yields results of appropriate repeatability and reproducibility. This method does not over- or under-estimate levels of steroidal saponins. HPLC/ELSD method does not require each and every pure standard of saponins, to quantify the group of steroidal saponins. The method is a time- and cost-effective technique that is suitable for routine industrial analyses. HPLC/ELSD methods yield a saponin fingerprints specific to the plant species. As the method is capable of distinguishing saponin profiles from taxonomically distant species, it can unravel plant adulteration issues. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Estimating climate change, CO2 and technology development effects on wheat yield in northeast Iran

NASA Astrophysics Data System (ADS)

Bannayan, M.; Mansoori, H.; Rezaei, E. Eyshi

2014-04-01

Wheat is the main food for the majority of Iran's population. Precise estimation of wheat yield change in future is essential for any possible revision of management strategies. The main objective of this study was to evaluate the effects of climate change, CO2 concentration, technology development and their integrated effects on wheat production under future climate change. This study was performed under two scenarios of the IPCC Special Report on Emission Scenarios (SRES): regional economic (A2) and global environmental (B1). Crop production was projected for three future time periods (2020, 2050 and 2080) in comparison with a baseline year (2005) for Khorasan province located in the northeast of Iran. Four study locations in the study area included Mashhad, Birjand, Bojnourd and Sabzevar. The effect of technology development was calculated by fitting a regression equation between the observed wheat yields against historical years considering yield potential increase and yield gap reduction as technology development. Yield relative increase per unit change of CO2 concentration (1 ppm-1) was considered 0.05 % and was used to implement the effect of elevated CO2. The HadCM3 general circulation model along with the CSM-CERES-Wheat crop model were used to project climate change effects on wheat crop yield. Our results illustrate that, among all the factors considered, technology development provided the highest impact on wheat yield change. Highest wheat yield increase across all locations and time periods was obtained under the A2 scenario. Among study locations, Mashhad showed the highest change in wheat yield. Yield change compared to baseline ranged from -28 % to 56 % when the integration of all factors was considered across all locations. It seems that achieving higher yield of wheat in future may be expected in northeast Iran assuming stable improvements in production technology.

Estimating climate change, CO2 and technology development effects on wheat yield in northeast Iran.

PubMed

Bannayan, M; Mansoori, H; Rezaei, E Eyshi

2014-04-01

Wheat is the main food for the majority of Iran's population. Precise estimation of wheat yield change in future is essential for any possible revision of management strategies. The main objective of this study was to evaluate the effects of climate change, CO2 concentration, technology development and their integrated effects on wheat production under future climate change. This study was performed under two scenarios of the IPCC Special Report on Emission Scenarios (SRES): regional economic (A2) and global environmental (B1). Crop production was projected for three future time periods (2020, 2050 and 2080) in comparison with a baseline year (2005) for Khorasan province located in the northeast of Iran. Four study locations in the study area included Mashhad, Birjand, Bojnourd and Sabzevar. The effect of technology development was calculated by fitting a regression equation between the observed wheat yields against historical years considering yield potential increase and yield gap reduction as technology development. Yield relative increase per unit change of CO2 concentration (1 ppm(-1)) was considered 0.05 % and was used to implement the effect of elevated CO2. The HadCM3 general circulation model along with the CSM-CERES-Wheat crop model were used to project climate change effects on wheat crop yield. Our results illustrate that, among all the factors considered, technology development provided the highest impact on wheat yield change. Highest wheat yield increase across all locations and time periods was obtained under the A2 scenario. Among study locations, Mashhad showed the highest change in wheat yield. Yield change compared to baseline ranged from -28 % to 56 % when the integration of all factors was considered across all locations. It seems that achieving higher yield of wheat in future may be expected in northeast Iran assuming stable improvements in production technology.

Correlation, path analysis and heritability estimation for agronomic traits contribute to yield on soybean

NASA Astrophysics Data System (ADS)

Sulistyo, A.; Purwantoro; Sari, K. P.

2018-01-01

Selection is a routine activity in plant breeding programs that must be done by plant breeders in obtaining superior plant genotypes. The use of appropriate selection criteria will determine the effectiveness of selection activities. The purpose of this study was to analysis the inheritable agronomic traits that contribute to soybean yield. A total of 91 soybean lines were planted in Muneng Experimental Station, Probolinggo District, East Java Province, Indonesia in 2016. All soybean lines were arranged in randomized complete block design with two replicates. Correlation analysis, path analysis and heritability estimation were performed on days to flowering, days to maturing, plant height, number of branches, number of fertile nodes, number of filled pods, weight of 100 seeds, and yield to determine selection criteria on soybean breeding program. The results showed that the heritability value of almost all agronomic traits observed is high except for the number of fertile nodes with low heritability. The result of correlation analysis shows that days to flowering, plant height and number of fertile nodes have positive correlation with seed yield per plot (0.056, 0.444, and 0.100, respectively). In addition, path analysis showed that plant height and number of fertile nodes have highest positive direct effect on soybean yield. Based on this result, plant height can be selected as one of selection criteria in soybean breeding program to obtain high yielding soybean variety.

Characterization of a signal recording system for accurate velocity estimation using a VISAR

NASA Astrophysics Data System (ADS)

Rav, Amit; Joshi, K. D.; Singh, Kulbhushan; Kaushik, T. C.

2018-02-01

The linearity of a signal recording system (SRS) in time as well as in amplitude are important for the accurate estimation of the free surface velocity history of a moving target during shock loading and unloading when measured using optical interferometers such as a velocity interferometer system for any reflector (VISAR). Signal recording being the first step in a long sequence of signal processes, the incorporation of errors due to nonlinearity, and low signal-to-noise ratio (SNR) affects the overall accuracy and precision of the estimation of velocity history. In shock experiments the small duration (a few µs) of loading/unloading, the reflectivity of moving target surface, and the properties of optical components, control the amount of input of light to the SRS of a VISAR and this in turn affects the linearity and SNR of the overall measurement. These factors make it essential to develop in situ procedures for (i) minimizing the effect of signal induced noise and (ii) determine the linear region of operation for the SRS. Here we report on a procedure for the optimization of SRS parameters such as photodetector gain, optical power, aperture etc, so as to achieve a linear region of operation with a high SNR. The linear region of operation so determined has been utilized successfully to estimate the temporal history of the free surface velocity of the moving target in shock experiments.

Evaluating the capabilities of watershed-scale models in estimating sediment yield at field-scale.

PubMed

Sommerlot, Andrew R; Nejadhashemi, A Pouyan; Woznicki, Sean A; Giri, Subhasis; Prohaska, Michael D

2013-09-30

Many watershed model interfaces have been developed in recent years for predicting field-scale sediment loads. They share the goal of providing data for decisions aimed at improving watershed health and the effectiveness of water quality conservation efforts. The objectives of this study were to: 1) compare three watershed-scale models (Soil and Water Assessment Tool (SWAT), Field_SWAT, and the High Impact Targeting (HIT) model) against calibrated field-scale model (RUSLE2) in estimating sediment yield from 41 randomly selected agricultural fields within the River Raisin watershed; 2) evaluate the statistical significance among models; 3) assess the watershed models' capabilities in identifying areas of concern at the field level; 4) evaluate the reliability of the watershed-scale models for field-scale analysis. The SWAT model produced the most similar estimates to RUSLE2 by providing the closest median and the lowest absolute error in sediment yield predictions, while the HIT model estimates were the worst. Concerning statistically significant differences between models, SWAT was the only model found to be not significantly different from the calibrated RUSLE2 at α = 0.05. Meanwhile, all models were incapable of identifying priorities areas similar to the RUSLE2 model. Overall, SWAT provided the most correct estimates (51%) within the uncertainty bounds of RUSLE2 and is the most reliable among the studied models, while HIT is the least reliable. The results of this study suggest caution should be exercised when using watershed-scale models for field level decision-making, while field specific data is of paramount importance. Copyright © 2013 Elsevier Ltd. All rights reserved.

Coplanar electrode microfluidic chip enabling accurate sheathless impedance cytometry.

PubMed

De Ninno, Adele; Errico, Vito; Bertani, Francesca Romana; Businaro, Luca; Bisegna, Paolo; Caselli, Federica

2017-03-14

Microfluidic impedance cytometry offers a simple non-invasive method for single-cell analysis. Coplanar electrode chips are especially attractive due to ease of fabrication, yielding miniaturized, reproducible, and ultimately low-cost devices. However, their accuracy is challenged by the dependence of the measured signal on particle trajectory within the interrogation volume, that manifests itself as an error in the estimated particle size, unless any kind of focusing system is used. In this paper, we present an original five-electrode coplanar chip enabling accurate particle sizing without the need for focusing. The chip layout is designed to provide a peculiar signal shape from which a new metric correlating with particle trajectory can be extracted. This metric is exploited to correct the estimated size of polystyrene beads of 5.2, 6 and 7 μm nominal diameter, reaching coefficient of variations lower than the manufacturers' quoted values. The potential impact of the proposed device in the field of life sciences is demonstrated with an application to Saccharomyces cerevisiae yeast.

Estimating the Effect of Climate Change on Crop Yields and Farmland Values: The Importance of Extreme Temperatures

EPA Pesticide Factsheets

This is a presentation titled Estimating the Effect of Climate Change on Crop Yields and Farmland Values: The Importance of Extreme Temperatures that was given for the National Center for Environmental Economics

Epoch length to accurately estimate the amplitude of interference EMG is likely the result of unavoidable amplitude cancellation

PubMed Central

Keenan, Kevin G.; Valero-Cuevas, Francisco J.

2008-01-01

Researchers and clinicians routinely rely on interference electromyograms (EMGs) to estimate muscle forces and command signals in the neuromuscular system (e.g., amplitude, timing, and frequency content). The amplitude cancellation intrinsic to interference EMG, however, raises important questions about how to optimize these estimates. For example, what should the length of the epoch (time window) be to average an EMG signal to reliably estimate muscle forces and command signals? Shorter epochs are most practical, and significant reductions in epoch have been reported with high-pass filtering and whitening. Given that this processing attenuates power at frequencies of interest (< 250 Hz), however, it is unclear how it improves the extraction of physiologically-relevant information. We examined the influence of amplitude cancellation and high-pass filtering on the epoch necessary to accurately estimate the “true” average EMG amplitude calculated from a 28 s EMG trace (EMGref) during simulated constant isometric conditions. Monte Carlo iterations of a motor-unit model simulating 28 s of surface EMG produced 245 simulations under 2 conditions: with and without amplitude cancellation. For each simulation, we calculated the epoch necessary to generate average full-wave rectified EMG amplitudes that settled within 5% of EMGref. For the no-cancellation EMG, the necessary epochs were short (e.g., < 100 ms). For the more realistic interference EMG (i.e., cancellation condition), epochs shortened dramatically after using high-pass filter cutoffs above 250 Hz, producing epochs short enough to be practical (i.e., < 500 ms). We conclude that the need to use long epochs to accurately estimate EMG amplitude is likely the result of unavoidable amplitude cancellation, which helps to clarify why high-pass filtering (> 250 Hz) improves EMG estimates. PMID:19081815

Are Physician Estimates of Asthma Severity Less Accurate in Black than in White Patients?

PubMed Central

Wu, Albert W.; Merriman, Barry; Krishnan, Jerry A.; Diette, Gregory B.

2007-01-01

Background Racial differences in asthma care are not fully explained by socioeconomic status, care access, and insurance status. Appropriate care requires accurate physician estimates of severity. It is unknown if accuracy of physician estimates differs between black and white patients, and how this relates to asthma care disparities. Objective We hypothesized that: 1) physician underestimation of asthma severity is more frequent among black patients; 2) among black patients, physician underestimation of severity is associated with poorer quality asthma care. Design, Setting and Patients We conducted a cross-sectional survey among adult patients with asthma cared for in 15 managed care organizations in the United States. We collected physicians’ estimates of their patients’ asthma severity. Physicians’ estimates of patients’ asthma as being less severe than patient-reported symptoms were classified as underestimates of severity. Measurements Frequency of underestimation, asthma care, and communication. Results Three thousand four hundred and ninety-four patients participated (13% were black). Blacks were significantly more likely than white patients to have their asthma severity underestimated (OR = 1.39, 95% CI 1.08–1.79). Among black patients, underestimation was associated with less use of daily inhaled corticosteroids (13% vs 20%, p < .05), less physician instruction on management of asthma flare-ups (33% vs 41%, p < .0001), and lower ratings of asthma care (p = .01) and physician communication (p = .04). Conclusions Biased estimates of asthma severity may contribute to racially disparate asthma care. Interventions to improve physicians’ assessments of asthma severity and patient–physician communication may minimize racial disparities in asthma care. PMID:17453263

On-line prediction of yield grade, longissimus muscle area, preliminary yield grade, adjusted preliminary yield grade, and marbling score using the MARC beef carcass image analysis system.

PubMed

Shackelford, S D; Wheeler, T L; Koohmaraie, M

2003-01-01

The present experiment was conducted to evaluate the ability of the U.S. Meat Animal Research Center's beef carcass image analysis system to predict calculated yield grade, longissimus muscle area, preliminary yield grade, adjusted preliminary yield grade, and marbling score under commercial beef processing conditions. In two commercial beef-processing facilities, image analysis was conducted on 800 carcasses on the beef-grading chain immediately after the conventional USDA beef quality and yield grades were applied. Carcasses were blocked by plant and observed calculated yield grade. The carcasses were then separated, with 400 carcasses assigned to a calibration data set that was used to develop regression equations, and the remaining 400 carcasses assigned to a prediction data set used to validate the regression equations. Prediction equations, which included image analysis variables and hot carcass weight, accounted for 90, 88, 90, 88, and 76% of the variation in calculated yield grade, longissimus muscle area, preliminary yield grade, adjusted preliminary yield grade, and marbling score, respectively, in the prediction data set. In comparison, the official USDA yield grade as applied by online graders accounted for 73% of the variation in calculated yield grade. The technology described herein could be used by the beef industry to more accurately determine beef yield grades; however, this system does not provide an accurate enough prediction of marbling score to be used without USDA grader interaction for USDA quality grading.

Accurate and quantitative polarization-sensitive OCT by unbiased birefringence estimator with noise-stochastic correction

NASA Astrophysics Data System (ADS)

Kasaragod, Deepa; Sugiyama, Satoshi; Ikuno, Yasushi; Alonso-Caneiro, David; Yamanari, Masahiro; Fukuda, Shinichi; Oshika, Tetsuro; Hong, Young-Joo; Li, En; Makita, Shuichi; Miura, Masahiro; Yasuno, Yoshiaki

2016-03-01

Polarization sensitive optical coherence tomography (PS-OCT) is a functional extension of OCT that contrasts the polarization properties of tissues. It has been applied to ophthalmology, cardiology, etc. Proper quantitative imaging is required for a widespread clinical utility. However, the conventional method of averaging to improve the signal to noise ratio (SNR) and the contrast of the phase retardation (or birefringence) images introduce a noise bias offset from the true value. This bias reduces the effectiveness of birefringence contrast for a quantitative study. Although coherent averaging of Jones matrix tomography has been widely utilized and has improved the image quality, the fundamental limitation of nonlinear dependency of phase retardation and birefringence to the SNR was not overcome. So the birefringence obtained by PS-OCT was still not accurate for a quantitative imaging. The nonlinear effect of SNR to phase retardation and birefringence measurement was previously formulated in detail for a Jones matrix OCT (JM-OCT) [1]. Based on this, we had developed a maximum a-posteriori (MAP) estimator and quantitative birefringence imaging was demonstrated [2]. However, this first version of estimator had a theoretical shortcoming. It did not take into account the stochastic nature of SNR of OCT signal. In this paper, we present an improved version of the MAP estimator which takes into account the stochastic property of SNR. This estimator uses a probability distribution function (PDF) of true local retardation, which is proportional to birefringence, under a specific set of measurements of the birefringence and SNR. The PDF was pre-computed by a Monte-Carlo (MC) simulation based on the mathematical model of JM-OCT before the measurement. A comparison between this new MAP estimator, our previous MAP estimator [2], and the standard mean estimator is presented. The comparisons are performed both by numerical simulation and in vivo measurements of anterior and

Estimation of genetic parameters and selection of high-yielding, upright common bean lines with slow seed-coat darkening.

PubMed

Alvares, R C; Silva, F C; Melo, L C; Melo, P G S; Pereira, H S

2016-11-21

Slow seed coat darkening is desirable in common bean cultivars and genetic parameters are important to define breeding strategies. The aims of this study were to estimate genetic parameters for plant architecture, grain yield, grain size, and seed-coat darkening in common bean; identify any genetic association among these traits; and select lines that associate desirable phenotypes for these traits. Three experiments were set up in the winter 2012 growing season, in Santo Antônio de Goiás and Brasília, Brazil, including 220 lines obtained from four segregating populations and five parents. A triple lattice 15 x 15 experimental design was used. The traits evaluated were plant architecture, grain yield, grain size, and seed-coat darkening. Analyses of variance were carried out and genetic parameters such as heritability, gain expected from selection, and correlations, were estimated. For selection of superior lines, a "weight-free and parameter-free" index was used. The estimates of genetic variance, heritability, and gain expected from selection were high, indicating good possibility for success in selection of the four traits. The genotype x environment interaction was proportionally more important for yield than for the other traits. There was no strong genetic correlation observed among the four traits, which indicates the possibility of selection of superior lines with many traits. Considering simultaneous selection, it was not possible to join high genetic gains for the four traits. Forty-four lines that combined high yield, more upright plant architecture, slow darkening grains, and commercial grade size were selected.

Soviet test yields

NASA Astrophysics Data System (ADS)

Vergino, Eileen S.

Soviet seismologists have published descriptions of 96 nuclear explosions conducted from 1961 through 1972 at the Semipalatinsk test site, in Kazakhstan, central Asia [Bocharov et al., 1989]. With the exception of releasing news about some of their peaceful nuclear explosions (PNEs) the Soviets have never before published such a body of information.To estimate the seismic yield of a nuclear explosion it is necessary to obtain a calibrated magnitude-yield relationship based on events with known yields and with a consistent set of seismic magnitudes. U.S. estimation of Soviet test yields has been done through application of relationships to the Soviet sites based on the U.S. experience at the Nevada Test Site (NTS), making some correction for differences due to attenuation and near-source coupling of seismic waves.

GT0 Explosion Sources for IMS Infrasound Calibration: Charge Design and Yield Estimation from Near-source Observations

NASA Astrophysics Data System (ADS)

Gitterman, Y.; Hofstetter, R.

2014-03-01

Three large-scale on-surface explosions were conducted by the Geophysical Institute of Israel (GII) at the Sayarim Military Range, Negev desert, Israel: about 82 tons of strong high explosives in August 2009, and two explosions of about 10 and 100 tons of ANFO explosives in January 2011. It was a collaborative effort between Israel, CTBTO, USA and several European countries, with the main goal to provide fully controlled ground truth (GT0) infrasound sources, monitored by extensive observations, for calibration of International Monitoring System (IMS) infrasound stations in Europe, Middle East and Asia. In all shots, the explosives were assembled like a pyramid/hemisphere on dry desert alluvium, with a complicated explosion design, different from the ideal homogenous hemisphere used in similar experiments in the past. Strong boosters and an upward charge detonation scheme were applied to provide more energy radiated to the atmosphere. Under these conditions the evaluation of the actual explosion yield, an important source parameter, is crucial for the GT0 calibration experiment. Audio-visual, air-shock and acoustic records were utilized for interpretation of observed unique blast effects, and for determination of blast wave parameters suited for yield estimation and the associated relationships. High-pressure gauges were deployed at 100-600 m to record air-blast properties, evaluate the efficiency of the charge design and energy generation, and provide a reliable estimation of the charge yield. The yield estimators, based on empirical scaled relations for well-known basic air-blast parameters—the peak pressure, impulse and positive phase duration, as well as on the crater dimensions and seismic magnitudes, were analyzed. A novel empirical scaled relationship for the little-known secondary shock delay was developed, consistent for broad ranges of ANFO charges and distances, which facilitates using this stable and reliable air-blast parameter as a new potential

Ethiopian Wheat Yield and Yield Gap Estimation: A Spatial Small Area Integrated Data Approach

NASA Astrophysics Data System (ADS)

Mann, M.; Warner, J.

2015-12-01

Despite the collection of routine annual agricultural surveys and significant advances in GIS and remote sensing products, little econometric research has been undertaken in predicting developing nation's agricultural yields. In this paper, we explore the determinants of wheat output per hectare in Ethiopia during the 2011-2013 Meher crop seasons aggregated to the woreda administrative area. Using a panel data approach, combining national agricultural field surveys with relevant GIS and remote sensing products, the model explains nearly 40% of the total variation in wheat output per hectare across the country. The model also identifies specific contributors to wheat yields that include farm management techniques (eg. area planted, improved seed, fertilizer, irrigation), weather (eg. rainfall), water availability (vegetation and moisture deficit indexes) and policy intervention. Our findings suggest that woredas produce between 9.8 and 86.5% of their potential wheat output per hectare given their altitude, weather conditions, terrain, and plant health. At the median, Amhara, Oromiya, SNNP, and Tigray produce 48.6, 51.5, 49.7, and 61.3% of their local attainable yields, respectively. This research has a broad range of applications, especially from a public policy perspective: identifying causes of yield fluctuations, remotely evaluating larger agricultural intervention packages, and analyzing relative yield potential. Overall, the combination of field surveys with spatial data can be used to identify management priorities for improving production at a variety of administrative levels.

Estimation of genetic parameters for heat stress, including dominance gene effects, on milk yield in Thai Holstein dairy cattle.

PubMed

Boonkum, Wuttigrai; Duangjinda, Monchai

2015-03-01

Heat stress in tropical regions is a major cause that strongly negatively affects to milk production in dairy cattle. Genetic selection for dairy heat tolerance is powerful technique to improve genetic performance. Therefore, the current study aimed to estimate genetic parameters and investigate the threshold point of heat stress for milk yield. Data included 52 701 test-day milk yield records for the first parity from 6247 Thai Holstein dairy cattle, covering the period 1990 to 2007. The random regression test day model with EM-REML was used to estimate variance components, genetic parameters and milk production loss. A decline in milk production was found when temperature and humidity index (THI) exceeded a threshold of 74, also it was associated with the high percentage of Holstein genetics. All variance component estimates increased with THI. The estimate of heritability of test-day milk yield was 0.231. Dominance variance as a proportion to additive variance (0.035) indicated that non-additive effects might not be of concern for milk genetics studies in Thai Holstein cattle. Correlations between genetic and permanent environmental effects, for regular conditions and due to heat stress, were - 0.223 and - 0.521, respectively. The heritability and genetic correlations from this study show that simultaneous selection for milk production and heat tolerance is possible. © 2014 Japanese Society of Animal Science.

Growth and yield models for central hardwoods

Treesearch

Martin E. Dale; Donald E. Hilt

1989-01-01

Over the last 20 years computers have become an efficient tool to estimate growth and yield. Computerized yield estimates vary from simple approximation or interpolation of traditional normal yield tables to highly sophisticated programs that simulate the growth and yield of each individual tree.

Assimilating Remote Sensing Observations of Leaf Area Index and Soil Moisture for Wheat Yield Estimates: An Observing System Simulation Experiment

NASA Technical Reports Server (NTRS)

Nearing, Grey S.; Crow, Wade T.; Thorp, Kelly R.; Moran, Mary S.; Reichle, Rolf H.; Gupta, Hoshin V.

2012-01-01

Observing system simulation experiments were used to investigate ensemble Bayesian state updating data assimilation of observations of leaf area index (LAI) and soil moisture (theta) for the purpose of improving single-season wheat yield estimates with the Decision Support System for Agrotechnology Transfer (DSSAT) CropSim-Ceres model. Assimilation was conducted in an energy-limited environment and a water-limited environment. Modeling uncertainty was prescribed to weather inputs, soil parameters and initial conditions, and cultivar parameters and through perturbations to model state transition equations. The ensemble Kalman filter and the sequential importance resampling filter were tested for the ability to attenuate effects of these types of uncertainty on yield estimates. LAI and theta observations were synthesized according to characteristics of existing remote sensing data, and effects of observation error were tested. Results indicate that the potential for assimilation to improve end-of-season yield estimates is low. Limitations are due to a lack of root zone soil moisture information, error in LAI observations, and a lack of correlation between leaf and grain growth.

Evaluation of gravimetric techniques to estimate the microvascular filtration coefficient

PubMed Central

Dongaonkar, R. M.; Laine, G. A.; Stewart, R. H.

2011-01-01

Microvascular permeability to water is characterized by the microvascular filtration coefficient (Kf). Conventional gravimetric techniques to estimate Kf rely on data obtained from either transient or steady-state increases in organ weight in response to increases in microvascular pressure. Both techniques result in considerably different estimates and neither account for interstitial fluid storage and lymphatic return. We therefore developed a theoretical framework to evaluate Kf estimation techniques by 1) comparing conventional techniques to a novel technique that includes effects of interstitial fluid storage and lymphatic return, 2) evaluating the ability of conventional techniques to reproduce Kf from simulated gravimetric data generated by a realistic interstitial fluid balance model, 3) analyzing new data collected from rat intestine, and 4) analyzing previously reported data. These approaches revealed that the steady-state gravimetric technique yields estimates that are not directly related to Kf and are in some cases directly proportional to interstitial compliance. However, the transient gravimetric technique yields accurate estimates in some organs, because the typical experimental duration minimizes the effects of interstitial fluid storage and lymphatic return. Furthermore, our analytical framework reveals that the supposed requirement of tying off all draining lymphatic vessels for the transient technique is unnecessary. Finally, our numerical simulations indicate that our comprehensive technique accurately reproduces the value of Kf in all organs, is not confounded by interstitial storage and lymphatic return, and provides corroboration of the estimate from the transient technique. PMID:21346245

The effect of flow data resolution on sediment yield estimation and channel design

NASA Astrophysics Data System (ADS)

Rosburg, Tyler T.; Nelson, Peter A.; Sholtes, Joel S.; Bledsoe, Brian P.

2016-07-01

The decision to use either daily-averaged or sub-daily streamflow records has the potential to impact the calculation of sediment transport metrics and stream channel design. Using bedload and suspended load sediment transport measurements collected at 138 sites across the United States, we calculated the effective discharge, sediment yield, and half-load discharge using sediment rating curves over long time periods (median record length = 24 years) with both daily-averaged and sub-daily streamflow records. A comparison of sediment transport metrics calculated with both daily-average and sub-daily stream flow data at each site showed that daily-averaged flow data do not adequately represent the magnitude of high stream flows at hydrologically flashy sites. Daily-average stream flow data cause an underestimation of sediment transport and sediment yield (including the half-load discharge) at flashy sites. The degree of underestimation was correlated with the level of flashiness and the exponent of the sediment rating curve. No consistent relationship between the use of either daily-average or sub-daily streamflow data and the resultant effective discharge was found. When used in channel design, computed sediment transport metrics may have errors due to flow data resolution, which can propagate into design slope calculations which, if implemented, could lead to unwanted aggradation or degradation in the design channel. This analysis illustrates the importance of using sub-daily flow data in the calculation of sediment yield in urbanizing or otherwise flashy watersheds. Furthermore, this analysis provides practical charts for estimating and correcting these types of underestimation errors commonly incurred in sediment yield calculations.

CUFID-query: accurate network querying through random walk based network flow estimation.

PubMed

Jeong, Hyundoo; Qian, Xiaoning; Yoon, Byung-Jun

2017-12-28

Functional modules in biological networks consist of numerous biomolecules and their complicated interactions. Recent studies have shown that biomolecules in a functional module tend to have similar interaction patterns and that such modules are often conserved across biological networks of different species. As a result, such conserved functional modules can be identified through comparative analysis of biological networks. In this work, we propose a novel network querying algorithm based on the CUFID (Comparative network analysis Using the steady-state network Flow to IDentify orthologous proteins) framework combined with an efficient seed-and-extension approach. The proposed algorithm, CUFID-query, can accurately detect conserved functional modules as small subnetworks in the target network that are expected to perform similar functions to the given query functional module. The CUFID framework was recently developed for probabilistic pairwise global comparison of biological networks, and it has been applied to pairwise global network alignment, where the framework was shown to yield accurate network alignment results. In the proposed CUFID-query algorithm, we adopt the CUFID framework and extend it for local network alignment, specifically to solve network querying problems. First, in the seed selection phase, the proposed method utilizes the CUFID framework to compare the query and the target networks and to predict the probabilistic node-to-node correspondence between the networks. Next, the algorithm selects and greedily extends the seed in the target network by iteratively adding nodes that have frequent interactions with other nodes in the seed network, in a way that the conductance of the extended network is maximally reduced. Finally, CUFID-query removes irrelevant nodes from the querying results based on the personalized PageRank vector for the induced network that includes the fully extended network and its neighboring nodes. Through extensive

Estimating 3D tilt from local image cues in natural scenes

PubMed Central

Burge, Johannes; McCann, Brian C.; Geisler, Wilson S.

2016-01-01

Estimating three-dimensional (3D) surface orientation (slant and tilt) is an important first step toward estimating 3D shape. Here, we examine how three local image cues from the same location (disparity gradient, luminance gradient, and dominant texture orientation) should be combined to estimate 3D tilt in natural scenes. We collected a database of natural stereoscopic images with precisely co-registered range images that provide the ground-truth distance at each pixel location. We then analyzed the relationship between ground-truth tilt and image cue values. Our analysis is free of assumptions about the joint probability distributions and yields the Bayes optimal estimates of tilt, given the cue values. Rich results emerge: (a) typical tilt estimates are only moderately accurate and strongly influenced by the cardinal bias in the prior probability distribution; (b) when cue values are similar, or when slant is greater than 40°, estimates are substantially more accurate; (c) when luminance and texture cues agree, they often veto the disparity cue, and when they disagree, they have little effect; and (d) simplifying assumptions common in the cue combination literature is often justified for estimating tilt in natural scenes. The fact that tilt estimates are typically not very accurate is consistent with subjective impressions from viewing small patches of natural scene. The fact that estimates are substantially more accurate for a subset of image locations is also consistent with subjective impressions and with the hypothesis that perceived surface orientation, at more global scales, is achieved by interpolation or extrapolation from estimates at key locations. PMID:27738702

Estimation of sediment yield from subsequent expanded landslides after heavy rainfalls : a case study in central Hokkaido, Japan

NASA Astrophysics Data System (ADS)

Koshimizu, K.; Uchida, T.

2015-12-01

Initial large-scale sediment yield caused by heavy rainfall or major storms have made a strong impression on us. Previous studies focusing on landslide management investigated the initial sediment movement and its mechanism. However, integrated management of catchment-scale sediment movements requires estimating the sediment yield, which is produced by the subsequent expanded landslides due to rainfall, in addition to the initial landslide movement. This study presents a quantitative analysis of expanded landslides by surveying the Shukushubetsu River basin, at the foot of the Hidaka mountain range in central Hokkaido, Japan. This area recorded heavy rainfall in 2003, reaching a maximum daily precipitation of 388 mm. We extracted the expanded landslides from 2003 to 2008 using aerial photographs taken over the river area. In particular, we calculated the probability of expansion for each landslide, the ratio of the landslide area in 2008 as compared with that in 2003, and the amount of the expanded landslide area corresponding to the initial landslide area. As a result, it is estimated 24% about probability of expansion for each landslide. In addition, each expanded landslide area is smaller than the initial landslide area. Furthermore, the amount of each expanded landslide area in 2008 is approximately 7% of their landslide area in 2003. Therefore, the sediment yield from subsequent expanded landslides is equal to or slightly greater than the sediment yield in a typical base flow. Thus, we concluded that the amount of sediment yield from subsequent expanded landslides is lower than that of initial large-scale sediment yield caused by a heavy rainfall in terms of effect on management of catchment-scale sediment movement.

The accuracy of less: Natural bounds explain why quantity decreases are estimated more accurately than quantity increases.

PubMed

Chandon, Pierre; Ordabayeva, Nailya

2017-02-01

Five studies show that people, including experts such as professional chefs, estimate quantity decreases more accurately than quantity increases. We argue that this asymmetry occurs because physical quantities cannot be negative. Consequently, there is a natural lower bound (zero) when estimating decreasing quantities but no upper bound when estimating increasing quantities, which can theoretically grow to infinity. As a result, the "accuracy of less" disappears (a) when a numerical or a natural upper bound is present when estimating quantity increases, or (b) when people are asked to estimate the (unbounded) ratio of change from 1 size to another for both increasing and decreasing quantities. Ruling out explanations related to loss aversion, symbolic number mapping, and the visual arrangement of the stimuli, we show that the "accuracy of less" influences choice and demonstrate its robustness in a meta-analysis that includes previously published results. Finally, we discuss how the "accuracy of less" may explain asymmetric reactions to the supersizing and downsizing of food portions, some instances of the endowment effect, and asymmetries in the perception of increases and decreases in physical and psychological distance. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Using operational data to estimate the reliable yields of water-supply wells

NASA Astrophysics Data System (ADS)

Misstear, Bruce D. R.; Beeson, Sarah

The reliable yield of a water-supply well depends on many different factors, including the properties of the well and the aquifer; the capacities of the pumps, raw-water mains, and treatment works; the interference effects from other wells; and the constraints imposed by ion licences, water quality, and environmental issues. A relatively simple methodology for estimating reliable yields has been developed that takes into account all of these factors. The methodology is based mainly on an analysis of water-level and source-output data, where such data are available. Good operational data are especially important when dealing with wells in shallow, unconfined, fissure-flow aquifers, where actual well performance may vary considerably from that predicted using a more analytical approach. Key issues in the yield-assessment process are the identification of a deepest advisable pumping water level, and the collection of the appropriate well, aquifer, and operational data. Although developed for water-supply operators in the United Kingdom, this approach to estimating the reliable yields of water-supply wells using operational data should be applicable to a wide range of hydrogeological conditions elsewhere. Résumé La productivité d'un puits capté pour l'adduction d'eau potable dépend de différents facteurs, parmi lesquels les propriétés du puits et de l'aquifère, la puissance des pompes, le traitement des eaux brutes, les effets d'interférences avec d'autres puits et les contraintes imposées par les autorisations d'exploitation, par la qualité des eaux et par les conditions environnementales. Une méthodologie relativement simple d'estimation de la productivité qui prenne en compte tous ces facteurs a été mise au point. Cette méthodologie est basée surtout sur une analyse des données concernant le niveau piézométrique et le débit de prélèvement, quand ces données sont disponibles. De bonnes données opérationnelles sont particuli

Genetic parameters for test-day yield of milk, fat and protein in buffaloes estimated by random regression models.

PubMed

Aspilcueta-Borquis, Rúsbel R; Araujo Neto, Francisco R; Baldi, Fernando; Santos, Daniel J A; Albuquerque, Lucia G; Tonhati, Humberto

2012-08-01

The test-day yields of milk, fat and protein were analysed from 1433 first lactations of buffaloes of the Murrah breed, daughters of 113 sires from 12 herds in the state of São Paulo, Brazil, born between 1985 and 2007. For the test-day yields, 10 monthly classes of lactation days were considered. The contemporary groups were defined as the herd-year-month of the test day. Random additive genetic, permanent environmental and residual effects were included in the model. The fixed effects considered were the contemporary group, number of milkings (1 or 2 milkings), linear and quadratic effects of the covariable cow age at calving and the mean lactation curve of the population (modelled by third-order Legendre orthogonal polynomials). The random additive genetic and permanent environmental effects were estimated by means of regression on third- to sixth-order Legendre orthogonal polynomials. The residual variances were modelled with a homogenous structure and various heterogeneous classes. According to the likelihood-ratio test, the best model for milk and fat production was that with four residual variance classes, while a third-order Legendre polynomial was best for the additive genetic effect for milk and fat yield, a fourth-order polynomial was best for the permanent environmental effect for milk production and a fifth-order polynomial was best for fat production. For protein yield, the best model was that with three residual variance classes and third- and fourth-order Legendre polynomials were best for the additive genetic and permanent environmental effects, respectively. The heritability estimates for the characteristics analysed were moderate, varying from 0·16±0·05 to 0·29±0·05 for milk yield, 0·20±0·05 to 0·30±0·08 for fat yield and 0·18±0·06 to 0·27±0·08 for protein yield. The estimates of the genetic correlations between the tests varied from 0·18±0·120 to 0·99±0·002; from 0·44±0·080 to 0·99±0·004; and from 0·41±0·080 to

Bone orientation and position estimation errors using Cosserat point elements and least squares methods: Application to gait.

PubMed

Solav, Dana; Camomilla, Valentina; Cereatti, Andrea; Barré, Arnaud; Aminian, Kamiar; Wolf, Alon

2017-09-06

The aim of this study was to analyze the accuracy of bone pose estimation based on sub-clusters of three skin-markers characterized by triangular Cosserat point elements (TCPEs) and to evaluate the capability of four instantaneous physical parameters, which can be measured non-invasively in vivo, to identify the most accurate TCPEs. Moreover, TCPE pose estimations were compared with the estimations of two least squares minimization methods applied to the cluster of all markers, using rigid body (RBLS) and homogeneous deformation (HDLS) assumptions. Analysis was performed on previously collected in vivo treadmill gait data composed of simultaneous measurements of the gold-standard bone pose by bi-plane fluoroscopy tracking the subjects' knee prosthesis and a stereophotogrammetric system tracking skin-markers affected by soft tissue artifact. Femur orientation and position errors estimated from skin-marker clusters were computed for 18 subjects using clusters of up to 35 markers. Results based on gold-standard data revealed that instantaneous subsets of TCPEs exist which estimate the femur pose with reasonable accuracy (median root mean square error during stance/swing: 1.4/2.8deg for orientation, 1.5/4.2mm for position). A non-invasive and instantaneous criteria to select accurate TCPEs for pose estimation (4.8/7.3deg, 5.8/12.3mm), was compared with RBLS (4.3/6.6deg, 6.9/16.6mm) and HDLS (4.6/7.6deg, 6.7/12.5mm). Accounting for homogeneous deformation, using HDLS or selected TCPEs, yielded more accurate position estimations than RBLS method, which, conversely, yielded more accurate orientation estimations. Further investigation is required to devise effective criteria for cluster selection that could represent a significant improvement in bone pose estimation accuracy. Copyright © 2017 Elsevier Ltd. All rights reserved.

Ion Yields in the Coupled Chemical and Physical Dynamics Model of Matrix-Assisted Laser Desorption/Ionization

NASA Astrophysics Data System (ADS)

Knochenmuss, Richard

2015-08-01

The Coupled Chemical and Physical Dynamics (CPCD) model of matrix assisted laser desorption ionization has been restricted to relative rather than absolute yield comparisons because the rate constant for one step in the model was not accurately known. Recent measurements are used to constrain this constant, leading to good agreement with experimental yield versus fluence data for 2,5-dihydroxybenzoic acid. Parameters for alpha-cyano-4-hydroxycinnamic acid are also estimated, including contributions from a possible triplet state. The results are compared with the polar fluid model, the CPCD is found to give better agreement with the data.

Estimation of monthly water yields and flows for 1951-2012 for the United States portion of the Great Lakes Basin with AFINCH

USGS Publications Warehouse

Luukkonen, Carol L.; Holtschlag, David J.; Reeves, Howard W.; Hoard, Christopher J.; Fuller, Lori M.

2015-01-01

Monthly water yields from 105,829 catchments and corresponding flows in 107,691 stream segments were estimated for water years 1951–2012 in the Great Lakes Basin in the United States. Both sets of estimates were computed by using the Analysis of Flows In Networks of CHannels (AFINCH) application within the NHDPlus geospatial data framework. AFINCH provides an environment to develop constrained regression models to integrate monthly streamflow and water-use data with monthly climatic data and fixed basin characteristics data available within NHDPlus or supplied by the user. For this study, the U.S. Great Lakes Basin was partitioned into seven study areas by grouping selected hydrologic subregions and adjoining cataloguing units. This report documents the regression models and data used to estimate monthly water yields and flows in each study area. Estimates of monthly water yields and flows are presented in a Web-based mapper application. Monthly flow time series for individual stream segments can be retrieved from the Web application and used to approximate monthly flow-duration characteristics and to identify possible trends.

Ultrasonic data compression via parameter estimation.

PubMed

Cardoso, Guilherme; Saniie, Jafar

2005-02-01

Ultrasonic imaging in medical and industrial applications often requires a large amount of data collection. Consequently, it is desirable to use data compression techniques to reduce data and to facilitate the analysis and remote access of ultrasonic information. The precise data representation is paramount to the accurate analysis of the shape, size, and orientation of ultrasonic reflectors, as well as to the determination of the properties of the propagation path. In this study, a successive parameter estimation algorithm based on a modified version of the continuous wavelet transform (CWT) to compress and denoise ultrasonic signals is presented. It has been shown analytically that the CWT (i.e., time x frequency representation) yields an exact solution for the time-of-arrival and a biased solution for the center frequency. Consequently, a modified CWT (MCWT) based on the Gabor-Helstrom transform is introduced as a means to exactly estimate both time-of-arrival and center frequency of ultrasonic echoes. Furthermore, the MCWT also has been used to generate a phase x bandwidth representation of the ultrasonic echo. This representation allows the exact estimation of the phase and the bandwidth. The performance of this algorithm for data compression and signal analysis is studied using simulated and experimental ultrasonic signals. The successive parameter estimation algorithm achieves a data compression ratio of (1-5N/J), where J is the number of samples and N is the number of echoes in the signal. For a signal with 10 echoes and 2048 samples, a compression ratio of 96% is achieved with a signal-to-noise ratio (SNR) improvement above 20 dB. Furthermore, this algorithm performs robustly, yields accurate echo estimation, and results in SNR enhancements ranging from 10 to 60 dB for composite signals having SNR as low as -10 dB.

Can administrative health utilisation data provide an accurate diabetes prevalence estimate for a geographical region?

PubMed

Chan, Wing Cheuk; Papaconstantinou, Dean; Lee, Mildred; Telfer, Kendra; Jo, Emmanuel; Drury, Paul L; Tobias, Martin

2018-05-01

To validate the New Zealand Ministry of Health (MoH) Virtual Diabetes Register (VDR) using longitudinal laboratory results and to develop an improved algorithm for estimating diabetes prevalence at a population level. The assigned diabetes status of individuals based on the 2014 version of the MoH VDR is compared to the diabetes status based on the laboratory results stored in the Auckland regional laboratory result repository (TestSafe) using the New Zealand diabetes diagnostic criteria. The existing VDR algorithm is refined by reviewing the sensitivity and positive predictive value of the each of the VDR algorithm rules individually and as a combination. The diabetes prevalence estimate based on the original 2014 MoH VDR was 17% higher (n = 108,505) than the corresponding TestSafe prevalence estimate (n = 92,707). Compared to the diabetes prevalence based on TestSafe, the original VDR has a sensitivity of 89%, specificity of 96%, positive predictive value of 76% and negative predictive value of 98%. The modified VDR algorithm has improved the positive predictive value by 6.1% and the specificity by 1.4% with modest reductions in sensitivity of 2.2% and negative predictive value of 0.3%. At an aggregated level the overall diabetes prevalence estimated by the modified VDR is 5.7% higher than the corresponding estimate based on TestSafe. The Ministry of Health Virtual Diabetes Register algorithm has been refined to provide a more accurate diabetes prevalence estimate at a population level. The comparison highlights the potential value of a national population long term condition register constructed from both laboratory results and administrative data. Copyright © 2018 Elsevier B.V. All rights reserved.

Estimating bottomland hardwood growth and yield

Treesearch

1989-01-01

Most bottomland hardwoods grow on very productive sites-site index 70 or more. A fully stocked immature stand (table 1, fig. 1) requires tending throughout its life. The goal is to attain a stand of approximately 50 high quality trees of commercial species per acre at maturity. Releasing these crop trees can result in the cumulative yield of 2,000-4,000 board feet per...

Experimental demonstration of cheap and accurate phase estimation

NASA Astrophysics Data System (ADS)

Rudinger, Kenneth; Kimmel, Shelby; Lobser, Daniel; Maunz, Peter

We demonstrate experimental implementation of robust phase estimation (RPE) to learn the phases of X and Y rotations on a trapped Yb+ ion qubit.. Unlike many other phase estimation protocols, RPE does not require ancillae nor near-perfect state preparation and measurement operations. Additionally, its computational requirements are minimal. Via RPE, using only 352 experimental samples per phase, we estimate phases of implemented gates with errors as small as 10-4 radians, as validated using gate set tomography. We also demonstrate that these estimates exhibit Heisenberg scaling in accuracy. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Generating Converged Accurate Free Energy Surfaces for Chemical Reactions with a Force-Matched Semiempirical Model.

PubMed

Kroonblawd, Matthew P; Pietrucci, Fabio; Saitta, Antonino Marco; Goldman, Nir

2018-04-10

We demonstrate the capability of creating robust density functional tight binding (DFTB) models for chemical reactivity in prebiotic mixtures through force matching to short time scale quantum free energy estimates. Molecular dynamics using density functional theory (DFT) is a highly accurate approach to generate free energy surfaces for chemical reactions, but the extreme computational cost often limits the time scales and range of thermodynamic states that can feasibly be studied. In contrast, DFTB is a semiempirical quantum method that affords up to a thousandfold reduction in cost and can recover DFT-level accuracy. Here, we show that a force-matched DFTB model for aqueous glycine condensation reactions yields free energy surfaces that are consistent with experimental observations of reaction energetics. Convergence analysis reveals that multiple nanoseconds of combined trajectory are needed to reach a steady-fluctuating free energy estimate for glycine condensation. Predictive accuracy of force-matched DFTB is demonstrated by direct comparison to DFT, with the two approaches yielding surfaces with large regions that differ by only a few kcal mol -1 .

Generating Converged Accurate Free Energy Surfaces for Chemical Reactions with a Force-Matched Semiempirical Model

DOE PAGES

Kroonblawd, Matthew P.; Pietrucci, Fabio; Saitta, Antonino Marco; ...

2018-03-15

Here, we demonstrate the capability of creating robust density functional tight binding (DFTB) models for chemical reactivity in prebiotic mixtures through force matching to short time scale quantum free energy estimates. Molecular dynamics using density functional theory (DFT) is a highly accurate approach to generate free energy surfaces for chemical reactions, but the extreme computational cost often limits the time scales and range of thermodynamic states that can feasibly be studied. In contrast, DFTB is a semiempirical quantum method that affords up to a thousandfold reduction in cost and can recover DFT-level accuracy. Here, we show that a force-matched DFTBmore » model for aqueous glycine condensation reactions yields free energy surfaces that are consistent with experimental observations of reaction energetics. Convergence analysis reveals that multiple nanoseconds of combined trajectory are needed to reach a steady-fluctuating free energy estimate for glycine condensation. Predictive accuracy of force-matched DFTB is demonstrated by direct comparison to DFT, with the two approaches yielding surfaces with large regions that differ by only a few kcal mol –1.« less

Generating Converged Accurate Free Energy Surfaces for Chemical Reactions with a Force-Matched Semiempirical Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kroonblawd, Matthew P.; Pietrucci, Fabio; Saitta, Antonino Marco

Here, we demonstrate the capability of creating robust density functional tight binding (DFTB) models for chemical reactivity in prebiotic mixtures through force matching to short time scale quantum free energy estimates. Molecular dynamics using density functional theory (DFT) is a highly accurate approach to generate free energy surfaces for chemical reactions, but the extreme computational cost often limits the time scales and range of thermodynamic states that can feasibly be studied. In contrast, DFTB is a semiempirical quantum method that affords up to a thousandfold reduction in cost and can recover DFT-level accuracy. Here, we show that a force-matched DFTBmore » model for aqueous glycine condensation reactions yields free energy surfaces that are consistent with experimental observations of reaction energetics. Convergence analysis reveals that multiple nanoseconds of combined trajectory are needed to reach a steady-fluctuating free energy estimate for glycine condensation. Predictive accuracy of force-matched DFTB is demonstrated by direct comparison to DFT, with the two approaches yielding surfaces with large regions that differ by only a few kcal mol –1.« less

Fast and Accurate Learning When Making Discrete Numerical Estimates.

PubMed

Sanborn, Adam N; Beierholm, Ulrik R

2016-04-01

Many everyday estimation tasks have an inherently discrete nature, whether the task is counting objects (e.g., a number of paint buckets) or estimating discretized continuous variables (e.g., the number of paint buckets needed to paint a room). While Bayesian inference is often used for modeling estimates made along continuous scales, discrete numerical estimates have not received as much attention, despite their common everyday occurrence. Using two tasks, a numerosity task and an area estimation task, we invoke Bayesian decision theory to characterize how people learn discrete numerical distributions and make numerical estimates. Across three experiments with novel stimulus distributions we found that participants fell between two common decision functions for converting their uncertain representation into a response: drawing a sample from their posterior distribution and taking the maximum of their posterior distribution. While this was consistent with the decision function found in previous work using continuous estimation tasks, surprisingly the prior distributions learned by participants in our experiments were much more adaptive: When making continuous estimates, participants have required thousands of trials to learn bimodal priors, but in our tasks participants learned discrete bimodal and even discrete quadrimodal priors within a few hundred trials. This makes discrete numerical estimation tasks good testbeds for investigating how people learn and make estimates.

Fast and Accurate Learning When Making Discrete Numerical Estimates

PubMed Central

Sanborn, Adam N.; Beierholm, Ulrik R.

2016-01-01

Many everyday estimation tasks have an inherently discrete nature, whether the task is counting objects (e.g., a number of paint buckets) or estimating discretized continuous variables (e.g., the number of paint buckets needed to paint a room). While Bayesian inference is often used for modeling estimates made along continuous scales, discrete numerical estimates have not received as much attention, despite their common everyday occurrence. Using two tasks, a numerosity task and an area estimation task, we invoke Bayesian decision theory to characterize how people learn discrete numerical distributions and make numerical estimates. Across three experiments with novel stimulus distributions we found that participants fell between two common decision functions for converting their uncertain representation into a response: drawing a sample from their posterior distribution and taking the maximum of their posterior distribution. While this was consistent with the decision function found in previous work using continuous estimation tasks, surprisingly the prior distributions learned by participants in our experiments were much more adaptive: When making continuous estimates, participants have required thousands of trials to learn bimodal priors, but in our tasks participants learned discrete bimodal and even discrete quadrimodal priors within a few hundred trials. This makes discrete numerical estimation tasks good testbeds for investigating how people learn and make estimates. PMID:27070155

Estimating regional wheat yield from the shape of decreasing curves of green area index temporal profiles retrieved from MODIS data

NASA Astrophysics Data System (ADS)

Kouadio, Louis; Duveiller, Grégory; Djaby, Bakary; El Jarroudi, Moussa; Defourny, Pierre; Tychon, Bernard

2012-08-01

Earth observation data, owing to their synoptic, timely and repetitive coverage, have been recognized as a valuable tool for crop monitoring at different levels. At the field level, the close correlation between green leaf area (GLA) during maturation and grain yield in wheat revealed that the onset and rate of senescence appeared to be important factors for determining wheat grain yield. Our study sought to explore a simple approach for wheat yield forecasting at the regional level, based on metrics derived from the senescence phase of the green area index (GAI) retrieved from remote sensing data. This study took advantage of recent methodological improvements in which imagery with high revisit frequency but coarse spatial resolution can be exploited to derive crop-specific GAI time series by selecting pixels whose ground-projected instantaneous field of view is dominated by the target crop: winter wheat. A logistic function was used to characterize the GAI senescence phase and derive the metrics of this phase. Four regression-based models involving these metrics (i.e., the maximum GAI value, the senescence rate and the thermal time taken to reach 50% of the green surface in the senescent phase) were related to official wheat yield data. The performances of such models at this regional scale showed that final yield could be estimated with an RMSE of 0.57 ton ha-1, representing about 7% as relative RMSE. Such an approach may be considered as a first yield estimate that could be performed in order to provide better integrated yield assessments in operational systems.

ROI on yield data analysis systems through a business process management strategy

NASA Astrophysics Data System (ADS)

Rehani, Manu; Strader, Nathan; Hanson, Jeff

2005-05-01

The overriding motivation for yield engineering is profitability. This is achieved through application of yield management. The first application is to continually reduce waste in the form of yield loss. New products, new technologies and the dynamic state of the process and equipment keep introducing new ways to cause yield loss. In response, the yield management efforts have to continually come up with new solutions to minimize it. The second application of yield engineering is to aid in accurate product pricing. This is achieved through predicting future results of the yield engineering effort. The more accurate the yield prediction, the more accurate the wafer start volume, the more accurate the wafer pricing. Another aspect of yield prediction pertains to gauging the impact of a yield problem and predicting how long that will last. The ability to predict such impacts again feeds into wafer start calculations and wafer pricing. The question then is that if the stakes on yield management are so high why is it that most yield management efforts are run like science and engineering projects and less like manufacturing? In the eighties manufacturing put the theory of constraints1 into practice and put a premium on stability and predictability in manufacturing activities, why can't the same be done for yield management activities? This line of introspection led us to define and implement a business process to manage the yield engineering activities. We analyzed the best known methods (BKM) and deployed a workflow tool to make them the standard operating procedure (SOP) for yield managment. We present a case study in deploying a Business Process Management solution for Semiconductor Yield Engineering in a high-mix ASIC environment. We will present a description of the situation prior to deployment, a window into the development process and a valuation of the benefits.

Magnetic dipole moment estimation and compensation for an accurate attitude control in nano-satellite missions

NASA Astrophysics Data System (ADS)

Inamori, Takaya; Sako, Nobutada; Nakasuka, Shinichi

2011-06-01

Nano-satellites provide space access to broader range of satellite developers and attract interests as an application of the space developments. These days several new nano-satellite missions are proposed with sophisticated objectives such as remote-sensing and observation of astronomical objects. In these advanced missions, some nano-satellites must meet strict attitude requirements for obtaining scientific data or images. For LEO nano-satellite, a magnetic attitude disturbance dominates over other environmental disturbances as a result of small moment of inertia, and this effect should be cancelled for a precise attitude control. This research focuses on how to cancel the magnetic disturbance in orbit. This paper presents a unique method to estimate and compensate the residual magnetic moment, which interacts with the geomagnetic field and causes the magnetic disturbance. An extended Kalman filter is used to estimate the magnetic disturbance. For more practical considerations of the magnetic disturbance compensation, this method has been examined in the PRISM (Pico-satellite for Remote-sensing and Innovative Space Missions). This method will be also used for a nano-astrometry satellite mission. This paper concludes that use of the magnetic disturbance estimation and compensation are useful for nano-satellites missions which require a high accurate attitude control.

Conversion of calibration curves for accurate estimation of molecular weight averages and distributions of polyether polyols by conventional size exclusion chromatography.

PubMed

Xu, Xiuqing; Yang, Xiuhan; Martin, Steven J; Mes, Edwin; Chen, Junlan; Meunier, David M

2018-08-17

Accurate measurement of molecular weight averages (M¯ n, M¯ w, M¯ z ) and molecular weight distributions (MWD) of polyether polyols by conventional SEC (size exclusion chromatography) is not as straightforward as it would appear. Conventional calibration with polystyrene (PS) standards can only provide PS apparent molecular weights which do not provide accurate estimates of polyol molecular weights. Using polyethylene oxide/polyethylene glycol (PEO/PEG) for molecular weight calibration could improve the accuracy, but the retention behavior of PEO/PEG is not stable in THF-based (tetrahydrofuran) SEC systems. In this work, two approaches for calibration curve conversion with narrow PS and polyol molecular weight standards were developed. Equations to convert PS-apparent molecular weight to polyol-apparent molecular weight were developed using both a rigorous mathematical analysis and graphical plot regression method. The conversion equations obtained by the two approaches were in good agreement. Factors influencing the conversion equation were investigated. It was concluded that the separation conditions such as column batch and operating temperature did not have significant impact on the conversion coefficients and a universal conversion equation could be obtained. With this conversion equation, more accurate estimates of molecular weight averages and MWDs for polyether polyols can be achieved from conventional PS-THF SEC calibration. Moreover, no additional experimentation is required to convert historical PS equivalent data to reasonably accurate molecular weight results. Copyright © 2018. Published by Elsevier B.V.

Ocean Lidar Measurements of Beam Attenuation and a Roadmap to Accurate Phytoplankton Biomass Estimates

NASA Astrophysics Data System (ADS)

Hu, Yongxiang; Behrenfeld, Mike; Hostetler, Chris; Pelon, Jacques; Trepte, Charles; Hair, John; Slade, Wayne; Cetinic, Ivona; Vaughan, Mark; Lu, Xiaomei; Zhai, Pengwang; Weimer, Carl; Winker, David; Verhappen, Carolus C.; Butler, Carolyn; Liu, Zhaoyan; Hunt, Bill; Omar, Ali; Rodier, Sharon; Lifermann, Anne; Josset, Damien; Hou, Weilin; MacDonnell, David; Rhew, Ray

2016-06-01

Beam attenuation coefficient, c, provides an important optical index of plankton standing stocks, such as phytoplankton biomass and total particulate carbon concentration. Unfortunately, c has proven difficult to quantify through remote sensing. Here, we introduce an innovative approach for estimating c using lidar depolarization measurements and diffuse attenuation coefficients from ocean color products or lidar measurements of Brillouin scattering. The new approach is based on a theoretical formula established from Monte Carlo simulations that links the depolarization ratio of sea water to the ratio of diffuse attenuation Kd and beam attenuation C (i.e., a multiple scattering factor). On July 17, 2014, the CALIPSO satellite was tilted 30° off-nadir for one nighttime orbit in order to minimize ocean surface backscatter and demonstrate the lidar ocean subsurface measurement concept from space. Depolarization ratios of ocean subsurface backscatter are measured accurately. Beam attenuation coefficients computed from the depolarization ratio measurements compare well with empirical estimates from ocean color measurements. We further verify the beam attenuation coefficient retrievals using aircraft-based high spectral resolution lidar (HSRL) data that are collocated with in-water optical measurements.

Growth and yield in Eucalyptus globulus

Treesearch

James A. Rinehart; Richard B. Standiford

1983-01-01

A study of the major Eucalyptus globulus stands throughout California conducted by Woodbridge Metcalf in 1924 provides a complete and accurate data set for generating variable site-density yield models. Two models were developed using linear regression techniques. Model I depicts a linear relationship between age and yield best used for stands between five and fifteen...

Estimation of plant disease severity visually, by digital photography and image analysis, and by hyperspectral imaging

USDA-ARS?s Scientific Manuscript database

Reliable, precise and accurate estimates of disease severity are important for predicting yield loss, monitoring and forecasting epidemics, for assessing crop germplasm for disease resistance, and for understanding fundamental biological processes including co-evolution. In some situations poor qual...

Spatial Distribution of Hydrologic Ecosystem Service Estimates: Comparing Two Models

NASA Astrophysics Data System (ADS)

Dennedy-Frank, P. J.; Ghile, Y.; Gorelick, S.; Logsdon, R. A.; Chaubey, I.; Ziv, G.

2014-12-01

We compare estimates of the spatial distribution of water quantity provided (annual water yield) from two ecohydrologic models: the widely-used Soil and Water Assessment Tool (SWAT) and the much simpler water models from the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) toolbox. These two models differ significantly in terms of complexity, timescale of operation, effort, and data required for calibration, and so are often used in different management contexts. We compare two study sites in the US: the Wildcat Creek Watershed (2083 km2) in Indiana, a largely agricultural watershed in a cold aseasonal climate, and the Upper Upatoi Creek Watershed (876 km2) in Georgia, a mostly forested watershed in a temperate aseasonal climate. We evaluate (1) quantitative estimates of water yield to explore how well each model represents this process, and (2) ranked estimates of water yield to indicate how useful the models are for management purposes where other social and financial factors may play significant roles. The SWAT and InVEST models provide very similar estimates of the water yield of individual subbasins in the Wildcat Creek Watershed (Pearson r = 0.92, slope = 0.89), and a similar ranking of the relative water yield of those subbasins (Spearman r = 0.86). However, the two models provide relatively different estimates of the water yield of individual subbasins in the Upper Upatoi Watershed (Pearson r = 0.25, slope = 0.14), and very different ranking of the relative water yield of those subbasins (Spearman r = -0.10). The Upper Upatoi watershed has a significant baseflow contribution due to its sandy, well-drained soils. InVEST's simple seasonality terms, which assume no change in storage over the time of the model run, may not accurately estimate water yield processes when baseflow provides such a strong contribution. Our results suggest that InVEST users take care in situations where storage changes are significant.

Conjunctive-use optimization model and sustainable-yield estimation for the Sparta aquifer of southeastern Arkansas and north-central Louisiana

USGS Publications Warehouse

McKee, Paul W.; Clark, Brian R.; Czarnecki, John B.

2004-01-01

Conjunctive-use optimization modeling was done to assist water managers and planners by estimating the maximum amount of ground water that hypothetically could be withdrawn from wells within the Sparta aquifer indefinitely without violating hydraulic-head or stream-discharge constraints. The Sparta aquifer is largely a confined aquifer of regional importance that comprises a sequence of unconsolidated sand units that are contained within the Sparta Sand. In 2000, more than 35.4 million cubic feet per day (Mft3/d) of water were withdrawn from the aquifer by more than 900 wells, primarily for industry, municipal supply, and crop irrigation in Arkansas. Continued, heavy withdrawals from the aquifer have caused several large cones of depression, lowering hydraulic heads below the top of the Sparta Sand in parts of Union and Columbia Counties and several areas in north-central Louisiana. Problems related to overdraft in the Sparta aquifer can result in increased drilling and pumping costs, reduced well yields, and degraded water quality in areas of large drawdown. A finite-difference ground-water flow model was developed for the Sparta aquifer using MODFLOW, primarily in eastern and southeastern Arkansas and north-central Louisiana. Observed aquifer conditions in 1997 supported by numerical simulations of ground-water flow show that continued pumping at withdrawal rates representative of 1990 - 1997 rates cannot be sustained indefinitely without causing hydraulic heads to drop substantially below the top of the Sparta Sand in southern Arkansas and north-central Louisiana. Areas of ground-water levels below the top of the Sparta Sand have been designated as Critical Ground-Water Areas by the State of Arkansas. A steady-state conjunctive-use optimization model was developed to simulate optimized surface-water and ground-water withdrawals while maintaining hydraulic-head and streamflow constraints, thus determining the 'sustainable yield' for the aquifer. Initial attempts

ASTRAL, DRAGON and SEDAN scores predict stroke outcome more accurately than physicians.

PubMed

Ntaios, G; Gioulekas, F; Papavasileiou, V; Strbian, D; Michel, P

2016-11-01

ASTRAL, SEDAN and DRAGON scores are three well-validated scores for stroke outcome prediction. Whether these scores predict stroke outcome more accurately compared with physicians interested in stroke was investigated. Physicians interested in stroke were invited to an online anonymous survey to provide outcome estimates in randomly allocated structured scenarios of recent real-life stroke patients. Their estimates were compared to scores' predictions in the same scenarios. An estimate was considered accurate if it was within 95% confidence intervals of actual outcome. In all, 244 participants from 32 different countries responded assessing 720 real scenarios and 2636 outcomes. The majority of physicians' estimates were inaccurate (1422/2636, 53.9%). 400 (56.8%) of physicians' estimates about the percentage probability of 3-month modified Rankin score (mRS) > 2 were accurate compared with 609 (86.5%) of ASTRAL score estimates (P < 0.0001). 394 (61.2%) of physicians' estimates about the percentage probability of post-thrombolysis symptomatic intracranial haemorrhage were accurate compared with 583 (90.5%) of SEDAN score estimates (P < 0.0001). 160 (24.8%) of physicians' estimates about post-thrombolysis 3-month percentage probability of mRS 0-2 were accurate compared with 240 (37.3%) DRAGON score estimates (P < 0.0001). 260 (40.4%) of physicians' estimates about the percentage probability of post-thrombolysis mRS 5-6 were accurate compared with 518 (80.4%) DRAGON score estimates (P < 0.0001). ASTRAL, DRAGON and SEDAN scores predict outcome of acute ischaemic stroke patients with higher accuracy compared to physicians interested in stroke. © 2016 EAN.

BIOACCESSIBILITY TESTS ACCURATELY ESTIMATE BIOAVAILABILITY OF LEAD TO QUAIL

EPA Science Inventory

Hazards of soil-borne Pb to wild birds may be more accurately quantified if the bioavailability of that Pb is known. To better understand the bioavailability of Pb to birds, we measured blood Pb concentrations in Japanese quail (Coturnix japonica) fed diets containing Pb-contami...

Accurate method for preoperative estimation of the right graft volume in adult-to-adult living donor liver transplantation.

PubMed

Khalaf, H; Shoukri, M; Al-Kadhi, Y; Neimatallah, M; Al-Sebayel, M

2007-06-01

Accurate estimation of graft volume is crucial to avoid small-for-size syndrome following adult-to-adult living donor liver transplantation AALDLT). Herein, we combined radiological and mathematical approaches for preoperative assessment of right graft volume. The right graft volume was preoperatively estimated in 31 live donors using two methods: first, the radiological graft volume (RGV) by computed tomography (CT) volumetry and second, a calculated graft volume (CGV) obtained by multiplying the standard liver volume by the percentage of the right graft volume (given by CT). Both methods were compared to the actual graft volume (AGV) measured during surgery. The graft recipient weight ratio (GRWR) was also calculated using all three volumes (RGV, CGV, and AGV). Lin's concordance correlation coefficient (CCC) was used to assess the agreement between AGV and both RGV and CGV. This was repeated using the GRWR measurements. The mean percentage of right graft volume was 62.4% (range, 55%-68%; SD +/- 3.27%). The CCC between AGV and RGV versus CGV was 0.38 and 0.66, respectively. The CCC between GRWR using AGV and RGV versus CGV was 0.63 and 0.88, respectively (P < .05). According to the Landis and Kock benchmark, the CGV correlated better with AGV when compared to RGV. The better correlation became even more apparent when applied to GRWR. In our experience, CGV showed a better correlation with AGV compared with the RGV. Using CGV in conjunction with RGV may be of value for a more accurate estimation of right graft volume for AALDLT.

Source spectral variation and yield estimation for small, near-source explosions

NASA Astrophysics Data System (ADS)

Yoo, S.; Mayeda, K. M.

2012-12-01

Significant S-wave generation is always observed from explosion sources which can lead to difficulty in discriminating explosions from natural earthquakes. While there are numerous S-wave generation mechanisms that are currently the topic of significant research, the mechanisms all remain controversial and appear to be dependent upon the near-source emplacement conditions of that particular explosion. To better understand the generation and partitioning of the P and S waves from explosion sources and to enhance the identification and discrimination capability of explosions, we investigate near-source explosion data sets from the 2008 New England Damage Experiment (NEDE), the Humble-Redwood (HR) series of explosions, and a Massachusetts quarry explosion experiment. We estimate source spectra and characteristic source parameters using moment tensor inversions, direct P and S waves multi-taper analysis, and improved coda spectral analysis using high quality waveform records from explosions from a variety of emplacement conditions (e.g., slow/fast burning explosive, fully tamped, partially tamped, single/ripple-fired, and below/above ground explosions). The results from direct and coda waves are compared to theoretical explosion source model predictions. These well-instrumented experiments provide us with excellent data from which to document the characteristic spectral shape, relative partitioning between P and S-waves, and amplitude/yield dependence as a function of HOB/DOB. The final goal of this study is to populate a comprehensive seismic source reference database for small yield explosions based on the results and to improve nuclear explosion monitoring capability.

Multiple-trait random regression models for the estimation of genetic parameters for milk, fat, and protein yield in buffaloes.

PubMed

Borquis, Rusbel Raul Aspilcueta; Neto, Francisco Ribeiro de Araujo; Baldi, Fernando; Hurtado-Lugo, Naudin; de Camargo, Gregório M F; Muñoz-Berrocal, Milthon; Tonhati, Humberto

2013-09-01

In this study, genetic parameters for test-day milk, fat, and protein yield were estimated for the first lactation. The data analyzed consisted of 1,433 first lactations of Murrah buffaloes, daughters of 113 sires from 12 herds in the state of São Paulo, Brazil, with calvings from 1985 to 2007. Ten-month classes of lactation days were considered for the test-day yields. The (co)variance components for the 3 traits were estimated using the regression analyses by Bayesian inference applying an animal model by Gibbs sampling. The contemporary groups were defined as herd-year-month of the test day. In the model, the random effects were additive genetic, permanent environment, and residual. The fixed effects were contemporary group and number of milkings (1 or 2), the linear and quadratic effects of the covariable age of the buffalo at calving, as well as the mean lactation curve of the population, which was modeled by orthogonal Legendre polynomials of fourth order. The random effects for the traits studied were modeled by Legendre polynomials of third and fourth order for additive genetic and permanent environment, respectively, the residual variances were modeled considering 4 residual classes. The heritability estimates for the traits were moderate (from 0.21-0.38), with higher estimates in the intermediate lactation phase. The genetic correlation estimates within and among the traits varied from 0.05 to 0.99. The results indicate that the selection for any trait test day will result in an indirect genetic gain for milk, fat, and protein yield in all periods of the lactation curve. The accuracy associated with estimated breeding values obtained using multi-trait random regression was slightly higher (around 8%) compared with single-trait random regression. This difference may be because to the greater amount of information available per animal. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Drogue pose estimation for unmanned aerial vehicle autonomous aerial refueling system based on infrared vision sensor

NASA Astrophysics Data System (ADS)

Chen, Shanjun; Duan, Haibin; Deng, Yimin; Li, Cong; Zhao, Guozhi; Xu, Yan

2017-12-01

Autonomous aerial refueling is a significant technology that can significantly extend the endurance of unmanned aerial vehicles. A reliable method that can accurately estimate the position and attitude of the probe relative to the drogue is the key to such a capability. A drogue pose estimation method based on infrared vision sensor is introduced with the general goal of yielding an accurate and reliable drogue state estimate. First, by employing direct least squares ellipse fitting and convex hull in OpenCV, a feature point matching and interference point elimination method is proposed. In addition, considering the conditions that some infrared LEDs are damaged or occluded, a missing point estimation method based on perspective transformation and affine transformation is designed. Finally, an accurate and robust pose estimation algorithm improved by the runner-root algorithm is proposed. The feasibility of the designed visual measurement system is demonstrated by flight test, and the results indicate that our proposed method enables precise and reliable pose estimation of the probe relative to the drogue, even in some poor conditions.

A scalable satellite-based crop yield mapper: Integrating satellites and crop models for field-scale estimation in India

NASA Astrophysics Data System (ADS)

Jain, M.; Singh, B.; Srivastava, A.; Lobell, D. B.

2015-12-01

Food security will be challenged over the upcoming decades due to increased food demand, natural resource degradation, and climate change. In order to identify potential solutions to increase food security in the face of these changes, tools that can rapidly and accurately assess farm productivity are needed. With this aim, we have developed generalizable methods to map crop yields at the field scale using a combination of satellite imagery and crop models, and implement this approach within Google Earth Engine. We use these methods to examine wheat yield trends in Northern India, which provides over 15% of the global wheat supply and where over 80% of farmers rely on wheat as a staple food source. In addition, we identify the extent to which farmers are shifting sow date in response to heat stress, and how well shifting sow date reduces the negative impacts of heat stress on yield. To identify local-level decision-making, we map wheat sow date and yield at a high spatial resolution (30 m) using Landsat satellite imagery from 1980 to the present. This unique dataset allows us to examine sow date decisions at the field scale over 30 years, and by relating these decisions to weather experienced over the same time period, we can identify how farmers learn and adapt cropping decisions based on weather through time.

Removing the thermal component from heart rate provides an accurate VO2 estimation in forest work.

PubMed

Dubé, Philippe-Antoine; Imbeau, Daniel; Dubeau, Denise; Lebel, Luc; Kolus, Ahmet

2016-05-01

Heart rate (HR) was monitored continuously in 41 forest workers performing brushcutting or tree planting work. 10-min seated rest periods were imposed during the workday to estimate the HR thermal component (ΔHRT) per Vogt et al. (1970, 1973). VO2 was measured using a portable gas analyzer during a morning submaximal step-test conducted at the work site, during a work bout over the course of the day (range: 9-74 min), and during an ensuing 10-min rest pause taken at the worksite. The VO2 estimated, from measured HR and from corrected HR (thermal component removed), were compared to VO2 measured during work and rest. Varied levels of HR thermal component (ΔHRTavg range: 0-38 bpm) originating from a wide range of ambient thermal conditions, thermal clothing insulation worn, and physical load exerted during work were observed. Using raw HR significantly overestimated measured work VO2 by 30% on average (range: 1%-64%). 74% of VO2 prediction error variance was explained by the HR thermal component. VO2 estimated from corrected HR, was not statistically different from measured VO2. Work VO2 can be estimated accurately in the presence of thermal stress using Vogt et al.'s method, which can be implemented easily by the practitioner with inexpensive instruments. Copyright © 2015 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Accurate relative location estimates for the North Korean nuclear tests using empirical slowness corrections

NASA Astrophysics Data System (ADS)

Gibbons, S. J.; Pabian, F.; Näsholm, S. P.; Kværna, T.; Mykkeltveit, S.

2017-01-01

velocity gradients reduce the residuals, the relative location uncertainties and the sensitivity to the combination of stations used. The traveltime gradients appear to be overestimated for the regional phases, and teleseismic relative location estimates are likely to be more accurate despite an apparent lower precision. Calibrations for regional phases are essential given that smaller magnitude events are likely not to be recorded teleseismically. We discuss the implications for the absolute event locations. Placing the 2006 event under a local maximum of overburden at 41.293°N, 129.105°E would imply a location of 41.299°N, 129.075°E for the January 2016 event, providing almost optimal overburden for the later four events.

Random Regression Models Using Legendre Polynomials to Estimate Genetic Parameters for Test-day Milk Protein Yields in Iranian Holstein Dairy Cattle.

PubMed

Naserkheil, Masoumeh; Miraie-Ashtiani, Seyed Reza; Nejati-Javaremi, Ardeshir; Son, Jihyun; Lee, Deukhwan

2016-12-01

The objective of this study was to estimate the genetic parameters of milk protein yields in Iranian Holstein dairy cattle. A total of 1,112,082 test-day milk protein yield records of 167,269 first lactation Holstein cows, calved from 1990 to 2010, were analyzed. Estimates of the variance components, heritability, and genetic correlations for milk protein yields were obtained using a random regression test-day model. Milking times, herd, age of recording, year, and month of recording were included as fixed effects in the model. Additive genetic and permanent environmental random effects for the lactation curve were taken into account by applying orthogonal Legendre polynomials of the fourth order in the model. The lowest and highest additive genetic variances were estimated at the beginning and end of lactation, respectively. Permanent environmental variance was higher at both extremes. Residual variance was lowest at the middle of the lactation and contrarily, heritability increased during this period. Maximum heritability was found during the 12th lactation stage (0.213±0.007). Genetic, permanent, and phenotypic correlations among test-days decreased as the interval between consecutive test-days increased. A relatively large data set was used in this study; therefore, the estimated (co)variance components for random regression coefficients could be used for national genetic evaluation of dairy cattle in Iran.

Random Regression Models Using Legendre Polynomials to Estimate Genetic Parameters for Test-day Milk Protein Yields in Iranian Holstein Dairy Cattle

PubMed Central

Naserkheil, Masoumeh; Miraie-Ashtiani, Seyed Reza; Nejati-Javaremi, Ardeshir; Son, Jihyun; Lee, Deukhwan

2016-01-01

The objective of this study was to estimate the genetic parameters of milk protein yields in Iranian Holstein dairy cattle. A total of 1,112,082 test-day milk protein yield records of 167,269 first lactation Holstein cows, calved from 1990 to 2010, were analyzed. Estimates of the variance components, heritability, and genetic correlations for milk protein yields were obtained using a random regression test-day model. Milking times, herd, age of recording, year, and month of recording were included as fixed effects in the model. Additive genetic and permanent environmental random effects for the lactation curve were taken into account by applying orthogonal Legendre polynomials of the fourth order in the model. The lowest and highest additive genetic variances were estimated at the beginning and end of lactation, respectively. Permanent environmental variance was higher at both extremes. Residual variance was lowest at the middle of the lactation and contrarily, heritability increased during this period. Maximum heritability was found during the 12th lactation stage (0.213±0.007). Genetic, permanent, and phenotypic correlations among test-days decreased as the interval between consecutive test-days increased. A relatively large data set was used in this study; therefore, the estimated (co)variance components for random regression coefficients could be used for national genetic evaluation of dairy cattle in Iran. PMID:26954192

Bioaccessibility tests accurately estimate bioavailability of lead to quail

USDA-ARS?s Scientific Manuscript database

Hazards of soil-borne Pb to wild birds may be more accurately quantified if the bioavailability of that Pb is known. To better understand the bioavailability of Pb, we incorporated Pb-contaminated soils or Pb acetate into diets for Japanese quail (Coturnix japonica), fed the quail for 15 days, and ...

A reassessment of ground water flow conditions and specific yield at Borden and Cape Cod

USGS Publications Warehouse

Grimestad, Garry

2002-01-01

Recent widely accepted findings respecting the origin and nature of specific yield in unconfined aquifers rely heavily on water level changes observed during two pumping tests, one conducted at Borden, Ontario, Canada, and the other at Cape Cod, Massachusetts. The drawdown patterns observed during those tests have been taken as proof that unconfined specific yield estimates obtained from long-duration pumping tests should approach the laboratory-estimated effective porosity of representative aquifer formation samples. However, both of the original test reports included direct or referential descriptions of potential supplemental sources of pumped water that would have introduced intractable complications and errors into straightforward interpretations of the drawdown observations if actually present. Searches for evidence of previously neglected sources were performed by screening the original drawdown observations from both locations for signs of diagnostic skewing that should be present only if some of the extracted water was derived from sources other than main aquifer storage. The data screening was performed using error-guided computer assisted fitting techniques, capable of accurately sensing and simulating the effects of a wide range of non-traditional and external sources. The drawdown curves from both tests proved to be inconsistent with traditional single-source pumped aquifer models but consistent with site-specific alternatives that included significant contributions of water from external sources. The corrected pumping responses shared several important features. Unsaturated drainage appears to have ceased effectively at both locations within the first day of pumping, and estimates of specific yield stabilized at levels considerably smaller than the corresponding laboratory-measured or probable effective porosity. Separate sequential analyses of progressively later field observations gave stable and nearly constant specific yield estimates for each

Estimation of groundwater consumption by phreatophytes using diurnal water table fluctuations: A saturated‐unsaturated flow assessment

USGS Publications Warehouse

Loheide, Steven P.; Butler, James J.; Gorelick, Steven M.

2005-01-01

Groundwater consumption by phreatophytes is a difficult‐to‐measure but important component of the water budget in many arid and semiarid environments. Over the past 70 years the consumptive use of groundwater by phreatophytes has been estimated using a method that analyzes diurnal trends in hydrographs from wells that are screened across the water table (White, 1932). The reliability of estimates obtained with this approach has never been rigorously evaluated using saturated‐unsaturated flow simulation. We present such an evaluation for common flow geometries and a range of hydraulic properties. Results indicate that the major source of error in the White method is the uncertainty in the estimate of specific yield. Evapotranspirative consumption of groundwater will often be significantly overpredicted with the White method if the effects of drainage time and the depth to the water table on specific yield are ignored. We utilize the concept of readily available specific yield as the basis for estimation of the specific yield value appropriate for use with the White method. Guidelines are defined for estimating readily available specific yield based on sediment texture. Use of these guidelines with the White method should enable the evapotranspirative consumption of groundwater to be more accurately quantified.

Genetic correlations among body condition score, yield, and fertility in first-parity cows estimated by random regression models.

PubMed

Veerkamp, R F; Koenen, E P; De Jong, G

2001-10-01

Twenty type classifiers scored body condition (BCS) of 91,738 first-parity cows from 601 sires and 5518 maternal grandsires. Fertility data during first lactation were extracted for 177,220 cows, of which 67,278 also had a BCS observation, and first-lactation 305-d milk, fat, and protein yields were added for 180,631 cows. Heritabilities and genetic correlations were estimated using a sire-maternal grandsire model. Heritability of BCS was 0.38. Heritabilities for fertility traits were low (0.01 to 0.07), but genetic standard deviations were substantial, 9 d for days to first service and calving interval, 0.25 for number of services, and 5% for first-service conception. Phenotypic correlations between fertility and yield or BCS were small (-0.15 to 0.20). Genetic correlations between yield and all fertility traits were unfavorable (0.37 to 0.74). Genetic correlations with BCS were between -0.4 and -0.6 for calving interval and days to first service. Random regression analysis (RR) showed that correlations changed with days in milk for BCS. Little agreement was found between variances and correlations from RR, and analysis including a single month (mo 1 to 10) of data for BCS, especially during early and late lactation. However, this was due to excluding data from the conventional analysis, rather than due to the polynomials used. RR and a conventional five-traits model where BCS in mo 1, 4, 7, and 10 was treated as a separate traits (plus yield or fertility) gave similar results. Thus a parsimonious random regression model gave more realistic estimates for the (co)variances than a series of bivariate analysis on subsets of the data for BCS. A higher genetic merit for yield has unfavorable effects on fertility, but the genetic correlation suggests that BCS (at some stages of lactation) might help to alleviate the unfavorable effect of selection for higher yield on fertility.

Experimental Demonstration of a Cheap and Accurate Phase Estimation

DOE PAGES

Rudinger, Kenneth; Kimmel, Shelby; Lobser, Daniel; ...

2017-05-11

We demonstrate an experimental implementation of robust phase estimation (RPE) to learn the phase of a single-qubit rotation on a trapped Yb + ion qubit. Here, we show this phase can be estimated with an uncertainty below 4 × 10 -4 rad using as few as 176 total experimental samples, and our estimates exhibit Heisenberg scaling. Unlike standard phase estimation protocols, RPE neither assumes perfect state preparation and measurement, nor requires access to ancillae. We crossvalidate the results of RPE with the more resource-intensive protocol of gate set tomography.

Satellite techniques yield insight into devastating rainfall from Hurricane Mitch

NASA Astrophysics Data System (ADS)

Ferraro, R.; Vicente, G.; Ba, M.; Gruber, A.; Scofield, R.; Li, Q.; Weldon, R.

Hurricane Mitch may prove to be one of the most devastating tropical cyclones to affect the western hemisphere. Heavy rains over Central America from October 28, 1998, to November 1, 1998, caused widespread flooding and mud slides in Nicaragua and Honduras resulting in thousands of deaths and missing persons. News reports indicated entire towns being swept away, destruction of national economies and infrastructure, and widespread disease in the aftermath of the storm, which some estimates suggested dropped as much as 1300 mm of rain.However, in view of the widespread damage it is difficult to determine the actual amounts and distribution of rainfall. More accurate means of determining the rainfall associated with Mitch are vital for diagnosing and understanding the evolution of this disaster and for developing new mitigation strategies for future tropical cyclones. Satellite data may prove to be a reliable resource for accurate rainfall analysis and have yielded apparently reliable figures for Hurricane Mitch.

Line-Constrained Camera Location Estimation in Multi-Image Stereomatching.

PubMed

Donné, Simon; Goossens, Bart; Philips, Wilfried

2017-08-23

Stereomatching is an effective way of acquiring dense depth information from a scene when active measurements are not possible. So-called lightfield methods take a snapshot from many camera locations along a defined trajectory (usually uniformly linear or on a regular grid-we will assume a linear trajectory) and use this information to compute accurate depth estimates. However, they require the locations for each of the snapshots to be known: the disparity of an object between images is related to both the distance of the camera to the object and the distance between the camera positions for both images. Existing solutions use sparse feature matching for camera location estimation. In this paper, we propose a novel method that uses dense correspondences to do the same, leveraging an existing depth estimation framework to also yield the camera locations along the line. We illustrate the effectiveness of the proposed technique for camera location estimation both visually for the rectification of epipolar plane images and quantitatively with its effect on the resulting depth estimation. Our proposed approach yields a valid alternative for sparse techniques, while still being executed in a reasonable time on a graphics card due to its highly parallelizable nature.

Spot urine sodium measurements do not accurately estimate dietary sodium intake in chronic kidney disease.

PubMed

Dougher, Carly E; Rifkin, Dena E; Anderson, Cheryl Am; Smits, Gerard; Persky, Martha S; Block, Geoffrey A; Ix, Joachim H

2016-08-01

Sodium intake influences blood pressure and proteinuria, yet the impact on long-term outcomes is uncertain in chronic kidney disease (CKD). Accurate assessment is essential for clinical and public policy recommendations, but few large-scale studies use 24-h urine collections. Recent studies that used spot urine sodium and associated estimating equations suggest that they may provide a suitable alternative, but their accuracy in patients with CKD is unknown. We compared the accuracy of 4 equations [the Nerbass, INTERSALT (International Cooperative Study on Salt, Other Factors, and Blood Pressure), Tanaka, and Kawasaki equations] that use spot urine sodium to estimate 24-h sodium excretion in patients with moderate to advanced CKD. We evaluated the accuracy of spot urine sodium to predict mean 24-h urine sodium excretion over 9 mo in 129 participants with stage 3-4 CKD. Spot morning urine sodium was used in 4 estimating equations. Bias, precision, and accuracy were assessed and compared across each equation. The mean age of the participants was 67 y, 52% were female, and the mean estimated glomerular filtration rate was 31 ± 9 mL · min(-1) · 1.73 m(-2) The mean ± SD number of 24-h urine collections was 3.5 ± 0.8/participant, and the mean 24-h sodium excretion was 168.2 ± 67.5 mmol/d. Although the Tanaka equation demonstrated the least bias (mean: -8.2 mmol/d), all 4 equations had poor precision and accuracy. The INTERSALT equation demonstrated the highest accuracy but derived an estimate only within 30% of mean measured sodium excretion in only 57% of observations. Bland-Altman plots revealed systematic bias with the Nerbass, INTERSALT, and Tanaka equations, underestimating sodium excretion when intake was high. These findings do not support the use of spot urine specimens to estimate dietary sodium intake in patients with CKD and research studies enriched with patients with CKD. The parent data for this study come from a clinical trial that was registered at

Estimation of Wheat Plant Density at Early Stages Using High Resolution Imagery

PubMed Central

Liu, Shouyang; Baret, Fred; Andrieu, Bruno; Burger, Philippe; Hemmerlé, Matthieu

2017-01-01

Crop density is a key agronomical trait used to manage wheat crops and estimate yield. Visual counting of plants in the field is currently the most common method used. However, it is tedious and time consuming. The main objective of this work is to develop a machine vision based method to automate the density survey of wheat at early stages. RGB images taken with a high resolution RGB camera are classified to identify the green pixels corresponding to the plants. Crop rows are extracted and the connected components (objects) are identified. A neural network is then trained to estimate the number of plants in the objects using the object features. The method was evaluated over three experiments showing contrasted conditions with sowing densities ranging from 100 to 600 seeds⋅m-2. Results demonstrate that the density is accurately estimated with an average relative error of 12%. The pipeline developed here provides an efficient and accurate estimate of wheat plant density at early stages. PMID:28559901

The shared and unique values of optical, fluorescence, thermal and microwave satellite data for estimating large-scale crop yields

USDA-ARS?s Scientific Manuscript database

Large-scale crop monitoring and yield estimation are important for both scientific research and practical applications. Satellite remote sensing provides an effective means for regional and global cropland monitoring, particularly in data-sparse regions that lack reliable ground observations and rep...

Hydrogen atoms can be located accurately and precisely by x-ray crystallography.

PubMed

Woińska, Magdalena; Grabowsky, Simon; Dominiak, Paulina M; Woźniak, Krzysztof; Jayatilaka, Dylan

2016-05-01

Precise and accurate structural information on hydrogen atoms is crucial to the study of energies of interactions important for crystal engineering, materials science, medicine, and pharmacy, and to the estimation of physical and chemical properties in solids. However, hydrogen atoms only scatter x-radiation weakly, so x-rays have not been used routinely to locate them accurately. Textbooks and teaching classes still emphasize that hydrogen atoms cannot be located with x-rays close to heavy elements; instead, neutron diffraction is needed. We show that, contrary to widespread expectation, hydrogen atoms can be located very accurately using x-ray diffraction, yielding bond lengths involving hydrogen atoms (A-H) that are in agreement with results from neutron diffraction mostly within a single standard deviation. The precision of the determination is also comparable between x-ray and neutron diffraction results. This has been achieved at resolutions as low as 0.8 Å using Hirshfeld atom refinement (HAR). We have applied HAR to 81 crystal structures of organic molecules and compared the A-H bond lengths with those from neutron measurements for A-H bonds sorted into bonds of the same class. We further show in a selection of inorganic compounds that hydrogen atoms can be located in bridging positions and close to heavy transition metals accurately and precisely. We anticipate that, in the future, conventional x-radiation sources at in-house diffractometers can be used routinely for locating hydrogen atoms in small molecules accurately instead of large-scale facilities such as spallation sources or nuclear reactors.

Hydrogen atoms can be located accurately and precisely by x-ray crystallography

PubMed Central

Woińska, Magdalena; Grabowsky, Simon; Dominiak, Paulina M.; Woźniak, Krzysztof; Jayatilaka, Dylan

2016-01-01

Precise and accurate structural information on hydrogen atoms is crucial to the study of energies of interactions important for crystal engineering, materials science, medicine, and pharmacy, and to the estimation of physical and chemical properties in solids. However, hydrogen atoms only scatter x-radiation weakly, so x-rays have not been used routinely to locate them accurately. Textbooks and teaching classes still emphasize that hydrogen atoms cannot be located with x-rays close to heavy elements; instead, neutron diffraction is needed. We show that, contrary to widespread expectation, hydrogen atoms can be located very accurately using x-ray diffraction, yielding bond lengths involving hydrogen atoms (A–H) that are in agreement with results from neutron diffraction mostly within a single standard deviation. The precision of the determination is also comparable between x-ray and neutron diffraction results. This has been achieved at resolutions as low as 0.8 Å using Hirshfeld atom refinement (HAR). We have applied HAR to 81 crystal structures of organic molecules and compared the A–H bond lengths with those from neutron measurements for A–H bonds sorted into bonds of the same class. We further show in a selection of inorganic compounds that hydrogen atoms can be located in bridging positions and close to heavy transition metals accurately and precisely. We anticipate that, in the future, conventional x-radiation sources at in-house diffractometers can be used routinely for locating hydrogen atoms in small molecules accurately instead of large-scale facilities such as spallation sources or nuclear reactors. PMID:27386545

Simulated yields for managed northern hardwood stands

Treesearch

Dale S. Solomon; William B. Leak; William B. Leak

1986-01-01

Board-foot and cubic-foot yields developed with the forest growth model SlMTlM are presented for northern hardwood stands grown with and without management. SIMTIM has been modified to include more accurate growth rates by species, a new stocking chart, and yields that reflect species values and quality classes. Treatments range from no thinning to intensive quality...

Estimation of yield and water requirements of maize crops combining high spatial and temporal resolution images with a simple crop model, in the perspective of the Sentinel-2 mission

NASA Astrophysics Data System (ADS)

Battude, Marjorie; Bitar, Ahmad Al; Brut, Aurore; Cros, Jérôme; Dejoux, Jean-François; Huc, Mireille; Marais Sicre, Claire; Tallec, Tiphaine; Demarez, Valérie

2016-04-01

Water resources are under increasing pressure as a result of global change and of a raising competition among the different users (agriculture, industry, urban). It is therefore important to develop tools able to estimate accurately crop water requirements in order to optimize irrigation while maintaining acceptable production. In this context, remote sensing is a valuable tool to monitor vegetation development and water demand. This work aims at developing a robust and generic methodology mainly based on high resolution remote sensing data to provide accurate estimates of maize yield and water needs at the watershed scale. Evapotranspiration (ETR) and dry aboveground biomass (DAM) of maize crops were modeled using time series of GAI images used to drive a simple agro-meteorological crop model (SAFYE, Duchemin et al., 2005). This model is based on a leaf partitioning function (Maas, 1993) for the simulation of crop biomass and on the FAO-56 methodology for the ETR simulation. The model also contains a module to simulate irrigation. This study takes advantage of the SPOT4 and SPOT5 Take5 experiments initiated by CNES (http://www.cesbio.ups-tlse.fr/multitemp/). They provide optical images over the watershed from February to May 2013 and from April to August 2015 respectively, with a temporal and spatial resolution similar to future images from the Sentinel-2 and VENμS missions. This dataset was completed with LandSat8 and Deimos1 images in order to cover the whole growing season while reducing the gaps in remote sensing time series. Radiometric, geometric and atmospheric corrections were achieved by the THEIA land data center, and the KALIDEOS processing chain. The temporal dynamics of the green area index (GAI) plays a key role in soil-plant-atmosphere interactions and in biomass accumulation process. Consistent seasonal dynamics of the remotely sensed GAI was estimated by applying a radiative transfer model based on artificial neural networks (BVNET, Baret

A robust statistical estimation (RoSE) algorithm jointly recovers the 3D location and intensity of single molecules accurately and precisely

NASA Astrophysics Data System (ADS)

Mazidi, Hesam; Nehorai, Arye; Lew, Matthew D.

2018-02-01

In single-molecule (SM) super-resolution microscopy, the complexity of a biological structure, high molecular density, and a low signal-to-background ratio (SBR) may lead to imaging artifacts without a robust localization algorithm. Moreover, engineered point spread functions (PSFs) for 3D imaging pose difficulties due to their intricate features. We develop a Robust Statistical Estimation algorithm, called RoSE, that enables joint estimation of the 3D location and photon counts of SMs accurately and precisely using various PSFs under conditions of high molecular density and low SBR.

Intercomparison of Soil Moisture, Evaporative Stress, and Vegetation Indices for Estimating Corn and Soybean Yields Over the U.S.

NASA Technical Reports Server (NTRS)

Mladenova, Iliana E.; Bolten, John D.; Crow, Wade T.; Anderson, Martha C.; Hain, C. R.; Johnson, David M.; Mueller, Rick

2017-01-01

This paper presents an intercomparative study of 12 operationally produced large-scale datasets describing soil moisture, evapotranspiration (ET), and or vegetation characteristics within agricultural regions of the contiguous United States (CONUS). These datasets have been developed using a variety of techniques, including, hydrologic modeling, satellite-based retrievals, data assimilation, and survey in-field data collection. The objectives are to assess the relative utility of each dataset for monitoring crop yield variability, to quantitatively assess their capacity for predicting end-of-season corn and soybean yields, and to examine the evolution of the yield-index correlations during the growing season. This analysis is unique both with regards to the number and variety of examined yield predictor datasets and the detailed assessment of the water availability timing on the end-of-season crop production during the growing season. Correlation results indicate that over CONUS, at state-level soil moisture and ET indices can provide better information for forecasting corn and soybean yields than vegetation-based indices such as normalized difference vegetation index. The strength of correlation with corn and soybean yields strongly depends on the interannual variability in yield measured at a given location. In this case study, some of the remotely derived datasets examined provide skill comparable to that of in situ field survey-based data further demonstrating the utility of these remote sensing-based approaches for estimating crop yield.

Brazilian Soybean Yields and Yield Gaps Vary with Farm Size

NASA Astrophysics Data System (ADS)

Jeffries, G. R.; Cohn, A.; Griffin, T. S.; Bragança, A.

2017-12-01

Understanding the farm size-specific characteristics of crop yields and yield gaps may help to improve yields by enabling better targeting of technical assistance and agricultural development programs. Linking remote sensing-based yield estimates with property boundaries provides a novel view of the relationship between farm size and yield structure (yield magnitude, gaps, and stability over time). A growing literature documents variations in yield gaps, but largely ignores the role of farm size as a factor shaping yield structure. Research on the inverse farm size-productivity relationship (IR) theory - that small farms are more productive than large ones all else equal - has documented that yield magnitude may vary by farm size, but has not considered other yield structure characteristics. We examined farm size - yield structure relationships for soybeans in Brazil for years 2001-2015. Using out-of-sample soybean yield predictions from a statistical model, we documented 1) gaps between the 95th percentile of attained yields and mean yields within counties and individual fields, and 2) yield stability defined as the standard deviation of time-detrended yields at given locations. We found a direct relationship between soy yields and farm size at the national level, while the strength and the sign of the relationship varied by region. Soybean yield gaps were found to be inversely related to farm size metrics, even when yields were only compared to farms of similar size. The relationship between farm size and yield stability was nonlinear, with mid-sized farms having the most stable yields. The work suggests that farm size is an important factor in understanding yield structure and that opportunities for improving soy yields in Brazil are greatest among smaller farms.

Accurate Biomass Estimation via Bayesian Adaptive Sampling

NASA Technical Reports Server (NTRS)

Wheeler, Kevin R.; Knuth, Kevin H.; Castle, Joseph P.; Lvov, Nikolay

2005-01-01

The following concepts were introduced: a) Bayesian adaptive sampling for solving biomass estimation; b) Characterization of MISR Rahman model parameters conditioned upon MODIS landcover. c) Rigorous non-parametric Bayesian approach to analytic mixture model determination. d) Unique U.S. asset for science product validation and verification.

Genetic parameters for body condition score, body weight, milk yield, and fertility estimated using random regression models.

PubMed

Berry, D P; Buckley, F; Dillon, P; Evans, R D; Rath, M; Veerkamp, R F

2003-11-01

Genetic (co)variances between body condition score (BCS), body weight (BW), milk yield, and fertility were estimated using a random regression animal model extended to multivariate analysis. The data analyzed included 81,313 BCS observations, 91,937 BW observations, and 100,458 milk test-day yields from 8725 multiparous Holstein-Friesian cows. A cubic random regression was sufficient to model the changing genetic variances for BCS, BW, and milk across different days in milk. The genetic correlations between BCS and fertility changed little over the lactation; genetic correlations between BCS and interval to first service and between BCS and pregnancy rate to first service varied from -0.47 to -0.31, and from 0.15 to 0.38, respectively. This suggests that maximum genetic gain in fertility from indirect selection on BCS should be based on measurements taken in midlactation when the genetic variance for BCS is largest. Selection for increased BW resulted in shorter intervals to first service, but more services and poorer pregnancy rates; genetic correlations between BW and pregnancy rate to first service varied from -0.52 to -0.45. Genetic selection for higher lactation milk yield alone through selection on increased milk yield in early lactation is likely to have a more deleterious effect on genetic merit for fertility than selection on higher milk yield in late lactation.

Specific yield: compilation of specific yields for various materials

USGS Publications Warehouse

Johnson, A.I.

1967-01-01

Specific yield is defined as the ratio of (1) the volume of water that a saturated rock or soil will yield by gravity to (2) the total volume of the rock or soft. Specific yield is usually expressed as a percentage. The value is not definitive, because the quantity of water that will drain by gravity depends on variables such as duration of drainage, temperature, mineral composition of the water, and various physical characteristics of the rock or soil under consideration. Values of specific yields nevertheless offer a convenient means by which hydrologists can estimate the water-yielding capacities of earth materials and, as such, are very useful in hydrologic studies. The present report consists mostly of direct or modified quotations from many selected reports that present and evaluate methods for determining specific yield, limitations of those methods, and results of the determinations made on a wide variety of rock and soil materials. Although no particular values are recommended in this report, a table summarizes values of specific yield, and their averages, determined for 10 rock textures. The following is an abstract of the table. [Table

Simple method for quick estimation of aquifer hydrogeological parameters

NASA Astrophysics Data System (ADS)

Ma, C.; Li, Y. Y.

2017-08-01

Development of simple and accurate methods to determine the aquifer hydrogeological parameters was of importance for groundwater resources assessment and management. Aiming at the present issue of estimating aquifer parameters based on some data of the unsteady pumping test, a fitting function of Theis well function was proposed using fitting optimization method and then a unitary linear regression equation was established. The aquifer parameters could be obtained by solving coefficients of the regression equation. The application of the proposed method was illustrated, using two published data sets. By the error statistics and analysis on the pumping drawdown, it showed that the method proposed in this paper yielded quick and accurate estimates of the aquifer parameters. The proposed method could reliably identify the aquifer parameters from long distance observed drawdowns and early drawdowns. It was hoped that the proposed method in this paper would be helpful for practicing hydrogeologists and hydrologists.

Satellite-based assessment of yield variation and its determinants in smallholder African systems

PubMed Central

Lobell, David B.

2017-01-01

The emergence of satellite sensors that can routinely observe millions of individual smallholder farms raises possibilities for monitoring and understanding agricultural productivity in many regions of the world. Here we demonstrate the potential to track smallholder maize yield variation in western Kenya, using a combination of 1-m Terra Bella imagery and intensive field sampling on thousands of fields over 2 y. We find that agreement between satellite-based and traditional field survey-based yield estimates depends significantly on the quality of the field-based measures, with agreement highest (R2 up to 0.4) when using precise field measures of plot area and when using larger fields for which rounding errors are smaller. We further show that satellite-based measures are able to detect positive yield responses to fertilizer and hybrid seed inputs and that the inferred responses are statistically indistinguishable from estimates based on survey-based yields. These results suggest that high-resolution satellite imagery can be used to make predictions of smallholder agricultural productivity that are roughly as accurate as the survey-based measures traditionally used in research and policy applications, and they indicate a substantial near-term potential to quickly generate useful datasets on productivity in smallholder systems, even with minimal or no field training data. Such datasets could rapidly accelerate learning about which interventions in smallholder systems have the most positive impact, thus enabling more rapid transformation of rural livelihoods. PMID:28202728

Satellite-based assessment of yield variation and its determinants in smallholder African systems.

PubMed

Burke, Marshall; Lobell, David B

2017-02-28

The emergence of satellite sensors that can routinely observe millions of individual smallholder farms raises possibilities for monitoring and understanding agricultural productivity in many regions of the world. Here we demonstrate the potential to track smallholder maize yield variation in western Kenya, using a combination of 1-m Terra Bella imagery and intensive field sampling on thousands of fields over 2 y. We find that agreement between satellite-based and traditional field survey-based yield estimates depends significantly on the quality of the field-based measures, with agreement highest ([Formula: see text] up to 0.4) when using precise field measures of plot area and when using larger fields for which rounding errors are smaller. We further show that satellite-based measures are able to detect positive yield responses to fertilizer and hybrid seed inputs and that the inferred responses are statistically indistinguishable from estimates based on survey-based yields. These results suggest that high-resolution satellite imagery can be used to make predictions of smallholder agricultural productivity that are roughly as accurate as the survey-based measures traditionally used in research and policy applications, and they indicate a substantial near-term potential to quickly generate useful datasets on productivity in smallholder systems, even with minimal or no field training data. Such datasets could rapidly accelerate learning about which interventions in smallholder systems have the most positive impact, thus enabling more rapid transformation of rural livelihoods.

Nut crop yield records show that budbreak-based chilling requirements may not reflect yield decline chill thresholds

NASA Astrophysics Data System (ADS)

Pope, Katherine S.; Dose, Volker; Da Silva, David; Brown, Patrick H.; DeJong, Theodore M.

2015-06-01

Warming winters due to climate change may critically affect temperate tree species. Insufficiently cold winters are thought to result in fewer viable flower buds and the subsequent development of fewer fruits or nuts, decreasing the yield of an orchard or fecundity of a species. The best existing approximation for a threshold of sufficient cold accumulation, the "chilling requirement" of a species or variety, has been quantified by manipulating or modeling the conditions that result in dormant bud breaking. However, the physiological processes that affect budbreak are not the same as those that determine yield. This study sought to test whether budbreak-based chilling thresholds can reasonably approximate the thresholds that affect yield, particularly regarding the potential impacts of climate change on temperate tree crop yields. County-wide yield records for almond ( Prunus dulcis), pistachio ( Pistacia vera), and walnut ( Juglans regia) in the Central Valley of California were compared with 50 years of weather records. Bayesian nonparametric function estimation was used to model yield potentials at varying amounts of chill accumulation. In almonds, average yields occurred when chill accumulation was close to the budbreak-based chilling requirement. However, in the other two crops, pistachios and walnuts, the best previous estimate of the budbreak-based chilling requirements was 19-32 % higher than the chilling accumulations associated with average or above average yields. This research indicates that physiological processes beyond requirements for budbreak should be considered when estimating chill accumulation thresholds of yield decline and potential impacts of climate change.

dropEst: pipeline for accurate estimation of molecular counts in droplet-based single-cell RNA-seq experiments.

PubMed

Petukhov, Viktor; Guo, Jimin; Baryawno, Ninib; Severe, Nicolas; Scadden, David T; Samsonova, Maria G; Kharchenko, Peter V

2018-06-19

Recent single-cell RNA-seq protocols based on droplet microfluidics use massively multiplexed barcoding to enable simultaneous measurements of transcriptomes for thousands of individual cells. The increasing complexity of such data creates challenges for subsequent computational processing and troubleshooting of these experiments, with few software options currently available. Here, we describe a flexible pipeline for processing droplet-based transcriptome data that implements barcode corrections, classification of cell quality, and diagnostic information about the droplet libraries. We introduce advanced methods for correcting composition bias and sequencing errors affecting cellular and molecular barcodes to provide more accurate estimates of molecular counts in individual cells.

Airborne and ground-based remote sensing for the estimation of evapotranspiration and yield of bean, potato, and sugar beet crops

NASA Astrophysics Data System (ADS)

Jayanthi, Harikishan

The focus of this research was two-fold: (1) extend the reflectance-based crop coefficient approach to non-grain (potato and sugar beet), and vegetable crops (bean), and (2) develop vegetation index (VI)-yield statistical models for potato and sugar beet crops using high-resolution aerial multispectral imagery. Extensive crop biophysical sampling (leaf area index and aboveground dry biomass sampling) and canopy reflectance measurements formed the backbone of developing of canopy reflectance-based crop coefficients for bean, potato, and sugar beet crops in this study. Reflectance-based crop coefficient equations were developed for the study crops cultivated in Kimberly, Idaho, and subsequently used in water availability simulations in the plant root zone during 1998 and 1999 seasons. The simulated soil water profiles were compared with independent measurements of actual soil water profiles in the crop root zone in selected fields. It is concluded that the canopy reflectance-based crop coefficient technique can be successfully extended to non-grain crops as well. While the traditional basal crop coefficients generally expect uniform growth in a region the reflectance-based crop coefficients represent the actual crop growth pattern (in less than ideal water availability conditions) in individual fields. Literature on crop canopy interactions with sunlight states that there is a definite correspondence between leaf area index progression in the season and the final yield. In case of crops like potato and sugar beet, the yield is influenced not only on how early and how quickly the crop establishes its canopy but also on how long the plant stands on the ground in a healthy state. The integrated area under the crop growth curve has shown excellent correlations with hand-dug samples of potato and sugar beet crops in this research. Soil adjusted vegetation index-yield models were developed, and validated using multispectral aerial imagery. Estimated yield images were

The origin and evolution of safe-yield policies in the Kansas groundwater management districts

USGS Publications Warehouse

Sophocleous, M.

2000-01-01

The management of groundwater resources in Kansas continues to evolve. Declines in the High Plains aquifer led to the establishment of groundwater management districts in the mid-1970s and reduced streamflows prompted the enactment of minimum desirable streamflow standards in the mid-1980s. Nonetheless, groundwater levels and streamflows continued to decline, although at reduced rates compared to premid-1980s rates. As a result, "safe-yield" policies were revised to take into account natural groundwater discharge in the form of stream baseflow. These policies, although a step in the right direction, are deficient in several ways. In addition to the need for more accurate recharge data, pumping-induced streamflow depletion, natural stream losses, and groundwater evapotranspiration need to be accounted for in the revised safe-yield policies. Furthermore, the choice of the 90% flow-duration statistic as a measure of baseflow needs to be reevaluated, as it significantly underestimates mean baseflow estimated from baseflow separation computer programs; moreover, baseflow estimation needs to be refined and validated. ?? 2000 International Association for Mathematical Geology.

Does bioelectrical impedance analysis accurately estimate the condition of threatened and endangered desert fish species?

USGS Publications Warehouse

Dibble, Kimberly L.; Yard, Micheal D.; Ward, David L.; Yackulic, Charles B.

2017-01-01

Bioelectrical impedance analysis (BIA) is a nonlethal tool with which to estimate the physiological condition of animals that has potential value in research on endangered species. However, the effectiveness of BIA varies by species, the methodology continues to be refined, and incidental mortality rates are unknown. Under laboratory conditions we tested the value of using BIA in addition to morphological measurements such as total length and wet mass to estimate proximate composition (lipid, protein, ash, water, dry mass, energy density) in the endangered Humpback Chub Gila cypha and Bonytail G. elegans and the species of concern Roundtail Chub G. robusta and conducted separate trials to estimate the mortality rates of these sensitive species. Although Humpback and Roundtail Chub exhibited no or low mortality in response to taking BIA measurements versus handling for length and wet-mass measurements, Bonytails exhibited 14% and 47% mortality in the BIA and handling experiments, respectively, indicating that survival following stress is species specific. Derived BIA measurements were included in the best models for most proximate components; however, the added value of BIA as a predictor was marginal except in the absence of accurate wet-mass data. Bioelectrical impedance analysis improved the R2 of the best percentage-based models by no more than 4% relative to models based on morphology. Simulated field conditions indicated that BIA models became increasingly better than morphometric models at estimating proximate composition as the observation error around wet-mass measurements increased. However, since the overall proportion of variance explained by percentage-based models was low and BIA was mostly a redundant predictor, we caution against the use of BIA in field applications for these sensitive fish species.

Background estimation and player detection in badminton video clips using histogram of pixel values along temporal dimension

NASA Astrophysics Data System (ADS)

Peng, Yahui; Ma, Xiao; Gao, Xinyu; Zhou, Fangxu

2015-12-01

Computer vision is an important tool for sports video processing. However, its application in badminton match analysis is very limited. In this study, we proposed a straightforward but robust histogram-based background estimation and player detection methods for badminton video clips, and compared the results with the naive averaging method and the mixture of Gaussians methods, respectively. The proposed method yielded better background estimation results than the naive averaging method and more accurate player detection results than the mixture of Gaussians player detection method. The preliminary results indicated that the proposed histogram-based method could estimate the background and extract the players accurately. We conclude that the proposed method can be used for badminton player tracking and further studies are warranted for automated match analysis.

Incentives Increase Participation in Mass Dog Rabies Vaccination Clinics and Methods of Coverage Estimation Are Assessed to Be Accurate

PubMed Central

Steinmetz, Melissa; Czupryna, Anna; Bigambo, Machunde; Mzimbiri, Imam; Powell, George; Gwakisa, Paul

2015-01-01

In this study we show that incentives (dog collars and owner wristbands) are effective at increasing owner participation in mass dog rabies vaccination clinics and we conclude that household questionnaire surveys and the mark-re-sight (transect survey) method for estimating post-vaccination coverage are accurate when all dogs, including puppies, are included. Incentives were distributed during central-point rabies vaccination clinics in northern Tanzania to quantify their effect on owner participation. In villages where incentives were handed out participation increased, with an average of 34 more dogs being vaccinated. Through economies of scale, this represents a reduction in the cost-per-dog of $0.47. This represents the price-threshold under which the cost of the incentive used must fall to be economically viable. Additionally, vaccination coverage levels were determined in ten villages through the gold-standard village-wide census technique, as well as through two cheaper and quicker methods (randomized household questionnaire and the transect survey). Cost data were also collected. Both non-gold standard methods were found to be accurate when puppies were included in the calculations, although the transect survey and the household questionnaire survey over- and under-estimated the coverage respectively. Given that additional demographic data can be collected through the household questionnaire survey, and that its estimate of coverage is more conservative, we recommend this method. Despite the use of incentives the average vaccination coverage was below the 70% threshold for eliminating rabies. We discuss the reasons and suggest solutions to improve coverage. Given recent international targets to eliminate rabies, this study provides valuable and timely data to help improve mass dog vaccination programs in Africa and elsewhere. PMID:26633821

Water Quality in the Upper Anacostia River, Maryland: Continuous and Discrete Monitoring with Simulations to Estimate Concentrations and Yields, 2003-05

USGS Publications Warehouse

Miller, Cherie V.; Gutierrez-Magness, Angelica L.; Feit Majedi, Brenda L.; Foster, Gregory D.

2007-01-01

concentrations of total phosphorus and total nitrogen had lower values of multiple R2 than suspended sediment, but the estimated bias for all the models was similar. The models for total nitrogen and total phosphorus tended to under-predict high concentrations and to over-predict low concentrations as compared to measured values. Annual yields (loads per square area in kilograms per year per square kilometer) were estimated for suspended sediment, total nitrogen, and total phosphorus using the U.S. Geological Survey models ESTIMATOR and LOADEST. The model LOADEST used hourly time steps and allowed the use of turbidity, which is strongly correlated to concentrations of suspended sediment, as a predictor variable. Annual yields for total nitrogen and total phosphorus were slightly higher but similar to previous estimates for other watersheds of the Chesapeake Bay, but annual yields for suspended sediment were higher by an order of magnitude for the two Anacostia River stations. Annual yields of suspended sediment at the two Anacostia River stations ranged from 131,000 to 248,000 kilograms per year per square kilometer for 2004 and 2005. LOADEST estimates were similar to those determined with ESTIMATOR, but had reduced errors associated with the estimates.

Guidelines for Estimating Cone and Seed Yields of Southern Pines

Treesearch

James P. Barnett

1999-01-01

Our ability to predict cone and seed yields of southern pines (Pinus spp.) prior to collection is important when scheduling and allocating resources. Many managers have enough historical data to predict their orchards' yield; but such data are generally unavailable for some species and for collections outside of orchards. Guidelines are...

Use of multi-temporal UAV-derived imagery for estimating individual tree growth in Pinus pinea stands

Treesearch

Juan Guerra-Hernández; Eduardo González-Ferreiro; Vicente Monleon; Sonia Faias; Margarida Tomé; Ramón Díaz-Varela

2017-01-01

High spatial resolution imagery provided by unmanned aerial vehicles (UAVs) can yield accurate and efficient estimation of tree dimensions and canopy structural variables at the local scale. We flew a low-cost, lightweight UAV over an experimental Pinus pinea L. plantation (290 trees distributed over 16 ha with different fertirrigation treatments)...

Benefits of seasonal forecasts of crop yields

NASA Astrophysics Data System (ADS)

Sakurai, G.; Okada, M.; Nishimori, M.; Yokozawa, M.

2017-12-01

Major factors behind recent fluctuations in food prices include increased biofuel production and oil price fluctuations. In addition, several extreme climate events that reduced worldwide food production coincided with upward spikes in food prices. The stabilization of crop yields is one of the most important tasks to stabilize food prices and thereby enhance food security. Recent development of technologies related to crop modeling and seasonal weather forecasting has made it possible to forecast future crop yields for maize and soybean. However, the effective use of these technologies remains limited. Here we present the potential benefits of seasonal crop-yield forecasts on a global scale for choice of planting day. For this purpose, we used a model (PRYSBI-2) that can well replicate past crop yields both for maize and soybean. This model system uses a Bayesian statistical approach to estimate the parameters of a basic process-based model of crop growth. The spatial variability of model parameters was considered by estimating the posterior distribution of the parameters from historical yield data by using the Markov-chain Monte Carlo (MCMC) method with a resolution of 1.125° × 1.125°. The posterior distributions of model parameters were estimated for each spatial grid with 30 000 MCMC steps of 10 chains each. By using this model and the estimated parameter distributions, we were able to estimate not only crop yield but also levels of associated uncertainty. We found that the global average crop yield increased about 30% as the result of the optimal selection of planting day and that the seasonal forecast of crop yield had a large benefit in and near the eastern part of Brazil and India for maize and the northern area of China for soybean. In these countries, the effects of El Niño and Indian Ocean dipole are large. The results highlight the importance of developing a system to forecast global crop yields.

Full-Waveform Envelope Templates for Low Magnitude Discrimination and Yield Estimation at Local and Regional Distances with Application to the North Korean Nuclear Tests

NASA Astrophysics Data System (ADS)

Yoo, S. H.

2017-12-01

Monitoring seismologists have successfully used seismic coda for event discrimination and yield estimation for over a decade. In practice seismologists typically analyze long-duration, S-coda signals with high signal-to-noise ratios (SNR) at regional and teleseismic distances, since the single back-scattering model reasonably predicts decay of the late coda. However, seismic monitoring requirements are shifting towards smaller, locally recorded events that exhibit low SNR and short signal lengths. To be successful at characterizing events recorded at local distances, we must utilize the direct-phase arrivals, as well as the earlier part of the coda, which is dominated by multiple forward scattering. To remedy this problem, we have developed a new hybrid method known as full-waveform envelope template matching to improve predicted envelope fits over the entire waveform and account for direct-wave and early coda complexity. We accomplish this by including a multiple forward-scattering approximation in the envelope modeling of the early coda. The new hybrid envelope templates are designed to fit local and regional full waveforms and produce low-variance amplitude estimates, which will improve yield estimation and discrimination between earthquakes and explosions. To demonstrate the new technique, we applied our full-waveform envelope template-matching method to the six known North Korean (DPRK) underground nuclear tests and four aftershock events following the September 2017 test. We successfully discriminated the event types and estimated the yield for all six nuclear tests. We also applied the same technique to the 2015 Tianjin explosions in China, and another suspected low-yield explosion at the DPRK test site on May 12, 2010. Our results show that the new full-waveform envelope template-matching method significantly improves upon longstanding single-scattering coda prediction techniques. More importantly, the new method allows monitoring seismologists to extend

Crop monitoring & yield forecasting system based on Synthetic Aperture Radar (SAR) and process-based crop growth model: Development and validation in South and South East Asian Countries

NASA Astrophysics Data System (ADS)

Setiyono, T. D.

2014-12-01

Accurate and timely information on rice crop growth and yield helps governments and other stakeholders adapting their economic policies and enables relief organizations to better anticipate and coordinate relief efforts in the wake of a natural catastrophe. Such delivery of rice growth and yield information is made possible by regular earth observation using space-born Synthetic Aperture Radar (SAR) technology combined with crop modeling approach to estimate yield. Radar-based remote sensing is capable of observing rice vegetation growth irrespective of cloud coverage, an important feature given that in incidences of flooding the sky is often cloud-covered. The system allows rapid damage assessment over the area of interest. Rice yield monitoring is based on a crop growth simulation and SAR-derived key information, particularly start of season and leaf growth rate. Results from pilot study sites in South and South East Asian countries suggest that incorporation of SAR data into crop model improves yield estimation for actual yields. Remote-sensing data assimilation into crop model effectively capture responses of rice crops to environmental conditions over large spatial coverage, which otherwise is practically impossible to achieve. Such improvement of actual yield estimates offers practical application such as in a crop insurance program. Process-based crop simulation model is used in the system to ensure climate information is adequately captured and to enable mid-season yield forecast.

Multilevel eEmpirical Bayes modeling for improved estimation of toxicant formulations tosuppress parasitic sea lamprey in the Upper Great Lakes

USGS Publications Warehouse

Hatfield, Laura A.; Gutreuter, Steve; Boogaard, Michael A.; Carlin, Bradley P.

2011-01-01

Estimation of extreme quantal-response statistics, such as the concentration required to kill 99.9% of test subjects (LC99.9), remains a challenge in the presence of multiple covariates and complex study designs. Accurate and precise estimates of the LC99.9 for mixtures of toxicants are critical to ongoing control of a parasitic invasive species, the sea lamprey, in the Laurentian Great Lakes of North America. The toxicity of those chemicals is affected by local and temporal variations in water chemistry, which must be incorporated into the modeling. We develop multilevel empirical Bayes models for data from multiple laboratory studies. Our approach yields more accurate and precise estimation of the LC99.9 compared to alternative models considered. This study demonstrates that properly incorporating hierarchical structure in laboratory data yields better estimates of LC99.9 stream treatment values that are critical to larvae control in the field. In addition, out-of-sample prediction of the results of in situ tests reveals the presence of a latent seasonal effect not manifest in the laboratory studies, suggesting avenues for future study and illustrating the importance of dual consideration of both experimental and observational data.

Adjusting slash pine growth and yield for silvicultural treatments

Treesearch

Stephen R. Logan; Barry D. Shiver

2006-01-01

With intensive silvicultural treatments such as fertilization and competition control now commonplace in today's slash pine (Pinus elliottii Engelm.) plantations, a method to adjust current growth and yield models is required to accurately account for yield increases due to these practices. Some commonly used ad-hoc methods, such as raising site...

A comparison of approaches for estimating bottom-sediment mass in large reservoirs

USGS Publications Warehouse

Juracek, Kyle E.

2006-01-01

Estimates of sediment and sediment-associated constituent loads and yields from drainage basins are necessary for the management of reservoir-basin systems to address important issues such as reservoir sedimentation and eutrophication. One method for the estimation of loads and yields requires a determination of the total mass of sediment deposited in a reservoir. This method involves a sediment volume-to-mass conversion using bulk-density information. A comparison of four computational approaches (partition, mean, midpoint, strategic) for using bulk-density information to estimate total bottom-sediment mass in four large reservoirs indicated that the differences among the approaches were not statistically significant. However, the lack of statistical significance may be a result of the small sample size. Compared to the partition approach, which was presumed to provide the most accurate estimates of bottom-sediment mass, the results achieved using the strategic, mean, and midpoint approaches differed by as much as ?4, ?20, and ?44 percent, respectively. It was concluded that the strategic approach may merit further investigation as a less time consuming and less costly alternative to the partition approach.

How accurate is the Pearson r-from-Z approximation? A Monte Carlo simulation study.

PubMed

Hittner, James B; May, Kim

2012-01-01

The Pearson r-from-Z approximation estimates the sample correlation (as an effect size measure) from the ratio of two quantities: the standard normal deviate equivalent (Z-score) corresponding to a one-tailed p-value divided by the square root of the total (pooled) sample size. The formula has utility in meta-analytic work when reports of research contain minimal statistical information. Although simple to implement, the accuracy of the Pearson r-from-Z approximation has not been empirically evaluated. To address this omission, we performed a series of Monte Carlo simulations. Results indicated that in some cases the formula did accurately estimate the sample correlation. However, when sample size was very small (N = 10) and effect sizes were small to small-moderate (ds of 0.1 and 0.3), the Pearson r-from-Z approximation was very inaccurate. Detailed figures that provide guidance as to when the Pearson r-from-Z formula will likely yield valid inferences are presented.

Advantage of multiple spot urine collections for estimating daily sodium excretion: comparison with two 24-h urine collections as reference.

PubMed

Uechi, Ken; Asakura, Keiko; Ri, Yui; Masayasu, Shizuko; Sasaki, Satoshi

2016-02-01

Several estimation methods for 24-h sodium excretion using spot urine sample have been reported, but accurate estimation at the individual level remains difficult. We aimed to clarify the most accurate method of estimating 24-h sodium excretion with different numbers of available spot urine samples. A total of 370 participants from throughout Japan collected multiple 24-h urine and spot urine samples independently. Participants were allocated randomly into a development and a validation dataset. Two estimation methods were established in the development dataset using the two 24-h sodium excretion samples as reference: the 'simple mean method' estimated by multiplying the sodium-creatinine ratio by predicted 24-h creatinine excretion, whereas the 'regression method' employed linear regression analysis. The accuracy of the two methods was examined by comparing the estimated means and concordance correlation coefficients (CCC) in the validation dataset. Mean sodium excretion by the simple mean method with three spot urine samples was closest to that by 24-h collection (difference: -1.62  mmol/day). CCC with the simple mean method increased with an increased number of spot urine samples at 0.20, 0.31, and 0.42 using one, two, and three samples, respectively. This method with three spot urine samples yielded higher CCC than the regression method (0.40). When only one spot urine sample was available for each study participant, CCC was higher with the regression method (0.36). The simple mean method with three spot urine samples yielded the most accurate estimates of sodium excretion. When only one spot urine sample was available, the regression method was preferable.

Genetic Analysis of Milk Yield in First-Lactation Holstein Friesian in Ethiopia: A Lactation Average vs Random Regression Test-Day Model Analysis

PubMed Central

Meseret, S.; Tamir, B.; Gebreyohannes, G.; Lidauer, M.; Negussie, E.

2015-01-01

The development of effective genetic evaluations and selection of sires requires accurate estimates of genetic parameters for all economically important traits in the breeding goal. The main objective of this study was to assess the relative performance of the traditional lactation average model (LAM) against the random regression test-day model (RRM) in the estimation of genetic parameters and prediction of breeding values for Holstein Friesian herds in Ethiopia. The data used consisted of 6,500 test-day (TD) records from 800 first-lactation Holstein Friesian cows that calved between 1997 and 2013. Co-variance components were estimated using the average information restricted maximum likelihood method under single trait animal model. The estimate of heritability for first-lactation milk yield was 0.30 from LAM whilst estimates from the RRM model ranged from 0.17 to 0.29 for the different stages of lactation. Genetic correlations between different TDs in first-lactation Holstein Friesian ranged from 0.37 to 0.99. The observed genetic correlation was less than unity between milk yields at different TDs, which indicated that the assumption of LAM may not be optimal for accurate evaluation of the genetic merit of animals. A close look at estimated breeding values from both models showed that RRM had higher standard deviation compared to LAM indicating that the TD model makes efficient utilization of TD information. Correlations of breeding values between models ranged from 0.90 to 0.96 for different group of sires and cows and marked re-rankings were observed in top sires and cows in moving from the traditional LAM to RRM evaluations. PMID:26194217

Assimilating remote sensing observations of leaf area index and soil moisture for wheat yield estimates: An observing system simulation experiment

USDA-ARS?s Scientific Manuscript database

We develop a robust understanding of the effects of assimilating remote sensing observations of leaf area index and soil moisture (in the top 5 cm) on DSSAT-CSM CropSim-Ceres wheat yield estimates. Synthetic observing system simulation experiments compare the abilities of the Ensemble Kalman Filter...

Assimilating a synthetic Kalman filter leaf area index series into the WOFOST model to improve regional winter wheat yield estimation

USDA-ARS?s Scientific Manuscript database

The scale mismatch between remotely sensed observations and crop growth models simulated state variables decreases the reliability of crop yield estimates. To overcome this problem, we used a two-step data assimilation phases: first we generated a complete leaf area index (LAI) time series by combin...

High-order computer-assisted estimates of topological entropy

NASA Astrophysics Data System (ADS)

Grote, Johannes

The concept of Taylor Models is introduced, which offers highly accurate C0-estimates for the enclosures of functional dependencies, combining high-order Taylor polynomial approximation of functions and rigorous estimates of the truncation error, performed using verified interval arithmetic. The focus of this work is on the application of Taylor Models in algorithms for strongly nonlinear dynamical systems. A method to obtain sharp rigorous enclosures of Poincare maps for certain types of flows and surfaces is developed and numerical examples are presented. Differential algebraic techniques allow the efficient and accurate computation of polynomial approximations for invariant curves of certain planar maps around hyperbolic fixed points. Subsequently we introduce a procedure to extend these polynomial curves to verified Taylor Model enclosures of local invariant manifolds with C0-errors of size 10-10--10 -14, and proceed to generate the global invariant manifold tangle up to comparable accuracy through iteration in Taylor Model arithmetic. Knowledge of the global manifold structure up to finite iterations of the local manifold pieces enables us to find all homoclinic and heteroclinic intersections in the generated manifold tangle. Combined with the mapping properties of the homoclinic points and their ordering we are able to construct a subshift of finite type as a topological factor of the original planar system to obtain rigorous lower bounds for its topological entropy. This construction is fully automatic and yields homoclinic tangles with several hundred homoclinic points. As an example rigorous lower bounds for the topological entropy of the Henon map are computed, which to the best knowledge of the authors yield the largest such estimates published so far.

New optical package and algorithms for accurate estimation and interactive recording of the cloud cover information over land and sea

NASA Astrophysics Data System (ADS)

Krinitskiy, Mikhail; Sinitsyn, Alexey; Gulev, Sergey

2014-05-01

Cloud fraction is a critical parameter for the accurate estimation of short-wave and long-wave radiation - one of the most important surface fluxes over sea and land. Massive estimates of the total cloud cover as well as cloud amount for different layers of clouds are available from visual observations, satellite measurements and reanalyses. However, these data are subject of different uncertainties and need continuous validation against highly accurate in-situ measurements. Sky imaging with high resolution fish eye camera provides an excellent opportunity for collecting cloud cover data supplemented with additional characteristics hardly available from routine visual observations (e.g. structure of cloud cover under broken cloud conditions, parameters of distribution of cloud dimensions). We present operational automatic observational package which is based on fish eye camera taking sky images with high resolution (up to 1Hz) in time and a spatial resolution of 968x648px. This spatial resolution has been justified as an optimal by several sensitivity experiments. For the use of the package at research vessel when the horizontal positioning becomes critical, a special extension of the hardware and software to the package has been developed. These modules provide the explicit detection of the optimal moment for shooting. For the post processing of sky images we developed a software realizing the algorithm of the filtering of sunburn effect in case of small and moderate could cover and broken cloud conditions. The same algorithm accurately quantifies the cloud fraction by analyzing color mixture for each point and introducing the so-called "grayness rate index" for every pixel. The accuracy of the algorithm has been tested using the data collected during several campaigns in 2005-2011 in the North Atlantic Ocean. The collection of images included more than 3000 images for different cloud conditions supplied with observations of standard parameters. The system is

An improved estimator for the hydration of fat-free mass from in vivo measurements subject to additive technical errors.

PubMed

Kinnamon, Daniel D; Lipsitz, Stuart R; Ludwig, David A; Lipshultz, Steven E; Miller, Tracie L

2010-04-01

The hydration of fat-free mass, or hydration fraction (HF), is often defined as a constant body composition parameter in a two-compartment model and then estimated from in vivo measurements. We showed that the widely used estimator for the HF parameter in this model, the mean of the ratios of measured total body water (TBW) to fat-free mass (FFM) in individual subjects, can be inaccurate in the presence of additive technical errors. We then proposed a new instrumental variables estimator that accurately estimates the HF parameter in the presence of such errors. In Monte Carlo simulations, the mean of the ratios of TBW to FFM was an inaccurate estimator of the HF parameter, and inferences based on it had actual type I error rates more than 13 times the nominal 0.05 level under certain conditions. The instrumental variables estimator was accurate and maintained an actual type I error rate close to the nominal level in all simulations. When estimating and performing inference on the HF parameter, the proposed instrumental variables estimator should yield accurate estimates and correct inferences in the presence of additive technical errors, but the mean of the ratios of TBW to FFM in individual subjects may not.

Multi-approach assessment of the spatial distribution of the specific yield: application to the Crau plain aquifer, France

NASA Astrophysics Data System (ADS)

Seraphin, Pierre; Gonçalvès, Julio; Vallet-Coulomb, Christine; Champollion, Cédric

2018-03-01

Spatially distributed values of the specific yield, a fundamental parameter for transient groundwater mass balance calculations, were obtained by means of three independent methods for the Crau plain, France. In contrast to its traditional use to assess recharge based on a given specific yield, the water-table fluctuation (WTF) method, applied using major recharging events, gave a first set of reference values. Then, large infiltration processes recorded by monitored boreholes and caused by major precipitation events were interpreted in terms of specific yield by means of a one-dimensional vertical numerical model solving Richards' equations within the unsaturated zone. Finally, two gravity field campaigns, at low and high piezometric levels, were carried out to assess the groundwater mass variation and thus alternative specific yield values. The range obtained by the WTF method for this aquifer made of alluvial detrital material was 2.9- 26%, in line with the scarce data available so far. The average spatial value of specific yield by the WTF method (9.1%) is consistent with the aquifer scale value from the hydro-gravimetric approach. In this investigation, an estimate of the hitherto unknown spatial distribution of the specific yield over the Crau plain was obtained using the most reliable method (the WTF method). A groundwater mass balance calculation over the domain using this distribution yielded similar results to an independent quantification based on a stable isotope-mixing model. This agreement reinforces the relevance of such estimates, which can be used to build a more accurate transient hydrogeological model.

Multi-approach assessment of the spatial distribution of the specific yield: application to the Crau plain aquifer, France

NASA Astrophysics Data System (ADS)

Seraphin, Pierre; Gonçalvès, Julio; Vallet-Coulomb, Christine; Champollion, Cédric

2018-06-01

Spatially distributed values of the specific yield, a fundamental parameter for transient groundwater mass balance calculations, were obtained by means of three independent methods for the Crau plain, France. In contrast to its traditional use to assess recharge based on a given specific yield, the water-table fluctuation (WTF) method, applied using major recharging events, gave a first set of reference values. Then, large infiltration processes recorded by monitored boreholes and caused by major precipitation events were interpreted in terms of specific yield by means of a one-dimensional vertical numerical model solving Richards' equations within the unsaturated zone. Finally, two gravity field campaigns, at low and high piezometric levels, were carried out to assess the groundwater mass variation and thus alternative specific yield values. The range obtained by the WTF method for this aquifer made of alluvial detrital material was 2.9- 26%, in line with the scarce data available so far. The average spatial value of specific yield by the WTF method (9.1%) is consistent with the aquifer scale value from the hydro-gravimetric approach. In this investigation, an estimate of the hitherto unknown spatial distribution of the specific yield over the Crau plain was obtained using the most reliable method (the WTF method). A groundwater mass balance calculation over the domain using this distribution yielded similar results to an independent quantification based on a stable isotope-mixing model. This agreement reinforces the relevance of such estimates, which can be used to build a more accurate transient hydrogeological model.

MISSE 2 PEACE Polymers Experiment Atomic Oxygen Erosion Yield Error Analysis

NASA Technical Reports Server (NTRS)

McCarthy, Catherine E.; Banks, Bruce A.; deGroh, Kim, K.

2010-01-01

Atomic oxygen erosion of polymers in low Earth orbit (LEO) poses a serious threat to spacecraft performance and durability. To address this, 40 different polymer samples and a sample of pyrolytic graphite, collectively called the PEACE (Polymer Erosion and Contamination Experiment) Polymers, were exposed to the LEO space environment on the exterior of the International Space Station (ISS) for nearly 4 years as part of the Materials International Space Station Experiment 1 & 2 (MISSE 1 & 2). The purpose of the PEACE Polymers experiment was to obtain accurate mass loss measurements in space to combine with ground measurements in order to accurately calculate the atomic oxygen erosion yields of a wide variety of polymeric materials exposed to the LEO space environment for a long period of time. Error calculations were performed in order to determine the accuracy of the mass measurements and therefore of the erosion yield values. The standard deviation, or error, of each factor was incorporated into the fractional uncertainty of the erosion yield for each of three different situations, depending on the post-flight weighing procedure. The resulting error calculations showed the erosion yield values to be very accurate, with an average error of 3.30 percent.

Adoption of an unmanned helicopter for low-altitude remote sensing to estimate yield and total biomass of a rice crop

USDA-ARS?s Scientific Manuscript database

A radio-controlled unmanned helicopter-based LARS (Low-Altitude Remote Sensing) platform was used to acquire quality images of high spatial and temporal resolution, in order to estimate yield and total biomass of a rice crop (Oriza Sativa, L.). Fifteen rice field plots with five N-treatments (0, 33,...

Advances in regional crop yield estimation over the United States using satellite remote sensing data

NASA Astrophysics Data System (ADS)

Johnson, D. M.; Dorn, M. F.; Crawford, C.

2015-12-01

Since the dawn of earth observation imagery, particularly from systems like Landsat and the Advanced Very High Resolution Radiometer, there has been an overarching desire to regionally estimate crop production remotely. Research efforts integrating space-based imagery into yield models to achieve this need have indeed paralleled these systems through the years, yet development of a truly useful crop production monitoring system has been arguably mediocre in coming. As a result, relatively few organizations have yet to operationalize the concept, and this is most acute in regions of the globe where there are not even alternative sources of crop production data being collected. However, the National Agricultural Statistics Service (NASS) has continued to push for this type of data source as a means to complement its long-standing, traditional crop production survey efforts which are financially costly to the government and create undue respondent burden on farmers. Corn and soybeans, the two largest field crops in the United States, have been the focus of satellite-based production monitoring by NASS for the past decade. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) has been seen as the most pragmatic input source for modeling yields primarily based on its daily revisit capabilities and reasonable ground sample resolution. The research methods presented here will be broad but provides a summary of what is useful and adoptable with satellite imagery in terms of crop yield estimation. Corn and soybeans will be of particular focus but other major staple crops like wheat and rice will also be presented. NASS will demonstrate that while MODIS provides a slew of vegetation related products, the traditional normalized difference vegetation index (NDVI) is still ideal. Results using land surface temperature products, also generated from MODIS, will also be shown. Beyond the MODIS data itself, NASS research has also focused efforts on understanding a

Predicting red meat yields in carcasses from beef-type and calf-fed Holstein steers using the United States Department of Agriculture calculated yield grade.

PubMed

Lawrence, T E; Elam, N A; Miller, M F; Brooks, J C; Hilton, G G; VanOverbeke, D L; McKeith, F K; Killefer, J; Montgomery, T H; Allen, D M; Griffin, D B; Delmore, R J; Nichols, W T; Streeter, M N; Yates, D A; Hutcheson, J P

2010-06-01

Analyses were conducted to evaluate the ability of the USDA yield grade equation to detect differences in subprimal yield of beef-type steers and calf-fed Holstein steers that had been fed zilpaterol hydrochloride (ZH; Intervet Inc., Millsboro, DE) as well as those that had not been fed ZH. Beef-type steer (n = 801) and calf-fed Holstein steer (n = 235) carcasses were fabricated into subprimal cuts and trim. Simple correlations between calculated yield grades and total red meat yields ranged from -0.56 to -0.62 for beef-type steers. Reliable correlations from calf-fed Holstein steers were unobtainable; the probability of a type I error met or exceeded 0.39. Linear models were developed for the beef-type steers to predict total red meat yield based on calculated USDA yield grade within each ZH duration. At an average calculated USDA yield grade of 2.9, beef-type steer carcasses that had not been fed ZH had an estimated 69.4% red meat yield, whereas those fed ZH had an estimated 70.7% red meat yield. These results indicate that feeding ZH increased red meat yield by 1.3% at a constant calculated yield grade. However, these data also suggest that the calculated USDA yield grade score is a poor and variable estimator (adjusted R(2) of 0.31 to 0.38) of total red meat yield of beef-type steer carcasses, regardless of ZH feeding. Moreover, no relationship existed (adjusted R(2) of 0.00 to 0.01) for calf-fed Holstein steer carcasses, suggesting the USDA yield grade is not a valid estimate of calf-fed Holstein red meat yield.

Assessing Sediment Yield and the Effect of Best Management Practices on Sediment Yield Reduction for Tutuila Island, American Samoa

NASA Astrophysics Data System (ADS)

Leta, O. T.; Dulai, H.; El-Kadi, A. I.

2017-12-01

Upland soil erosion and sedimentation are the main threats for riparian and coastal reef ecosystems in Pacific islands. Here, due to small size of the watersheds and steep slope, the residence time of rainfall runoff and its suspended load is short. Fagaalu bay, located on the island of Tutuila (American Samoa) has been identified as a priority watershed, due to degraded coral reef condition and reduction of stream water quality from heavy anthropogenic activity yielding high nutrients and sediment loads to the receiving water bodies. This study aimed to estimate the sediment yield to the Fagaalu stream and assess the impact of Best Management Practices (BMP) on sediment yield reduction. For this, the Soil and Water Assessment Tool (SWAT) model was applied, calibrated, and validated for both daily streamflow and sediment load simulation. The model also estimated the sediment yield contributions from existing land use types of Fagaalu and identified soil erosion prone areas for introducing BMP scenarios in the watershed. Then, three BMP scenarios, such as stone bund, retention pond, and filter strip were treated on bare (quarry area), agricultural, and shrub land use types. It was found that the bare land with quarry activity yielded the highest annual average sediment yield of 133 ton per hectare (t ha-1) followed by agriculture (26.1 t ha-1) while the lowest sediment yield of 0.2 t ha-1 was estimated for the forested part of the watershed. Additionally, the bare land area (2 ha) contributed approximately 65% (207 ha) of the watershed's sediment yield, which is 4.0 t ha-1. The latter signifies the high impact as well as contribution of anthropogenic activity on sediment yield. The use of different BMP scenarios generally reduced the sediment yield to the coastal reef of Fagaalu watershed. However, treating the quarry activity area with stone bund showed the highest sediment yield reduction as compared to the other two BMP scenarios. This study provides an estimate

Yield gap mapping as a support tool for risk management in agriculture

NASA Astrophysics Data System (ADS)

Lahlou, Ouiam; Imani, Yasmina; Slimani, Imane; Van Wart, Justin; Yang, Haishun

2016-04-01

The increasing frequency and magnitude of droughts in Morocco and the mounting losses from extended droughts in the agricultural sector emphasized the need to develop reliable and timely tools to manage drought and to mitigate resulting catastrophic damage. In 2011, Morocco launched a cereals multi-risk insurance with drought as the most threatening and the most frequent hazard in the country. However, and in order to assess the gap and to implement the more suitable compensation, it is essential to quantify the potential yield in each area. In collaboration with the University of Nebraska-Lincoln, a study is carried out in Morocco and aims to determine the yield potentials and the yield gaps in the different agro-climatic zones of the country. It fits into the large project: Global Yield Gap and Water Productivity Atlas: http://www.yieldgap.org/. The yield gap (Yg) is the magnitude and difference between crop yield potential (Yp) or water limited yield potential (Yw) and actual yields, reached by farmers. World Food Studies (WOFOST), which is a Crop simulation mechanistic model, has been used for this purpose. Prior to simulations, reliable information about actual yields, weather data, crop management data and soil data have been collected in 7 Moroccan buffer zones considered, each, within a circle of 100 km around a weather station point, homogenously spread across the country and where cereals are widely grown. The model calibration was also carried out using WOFOST default varieties data. The map-based results represent a robust tool, not only for drought insurance organization, but for agricultural and agricultural risk management. Moreover, accurate and geospatially granular estimates of Yg and Yw will allow to focus on regions with largest unexploited yield gaps and greatest potential to close them, and consequently to improve food security in the country.

Simulating effects of microtopography on wetland specific yield and hydroperiod

USGS Publications Warehouse

Summer, David M.; Wang, Xixi

2011-01-01

Specific yield and hydroperiod have proven to be useful parameters in hydrologic analysis of wetlands. Specific yield is a critical parameter to quantitatively relate hydrologic fluxes (e.g., rainfall, evapotranspiration, and runoff) and water level changes. Hydroperiod measures the temporal variability and frequency of land-surface inundation. Conventionally, hydrologic analyses used these concepts without considering the effects of land surface microtopography and assumed a smoothly-varying land surface. However, these microtopographic effects could result in small-scale variations in land surface inundation and water depth above or below the land surface, which in turn affect ecologic and hydrologic processes of wetlands. The objective of this chapter is to develop a physically-based approach for estimating specific yield and hydroperiod that enables the consideration of microtopographic features of wetlands, and to illustrate the approach at sites in the Florida Everglades. The results indicate that the physically-based approach can better capture the variations of specific yield with water level, in particular when the water level falls between the minimum and maximum land surface elevations. The suggested approach for hydroperiod computation predicted that the wetlands might be completely dry or completely wet much less frequently than suggested by the conventional approach neglecting microtopography. One reasonable generalization may be that the hydroperiod approaches presented in this chapter can be a more accurate prediction tool for water resources management to meet the specific hydroperiod threshold as required by a species of plant or animal of interest.

Biogas and methane yield in response to co- and separate digestion of biomass wastes.

PubMed

Adelard, Laetitia; Poulsen, Tjalfe G; Rakotoniaina, Volana

2015-01-01

The impact of co-digestion as opposed to separate digestion, on biogas and methane yield (apparent synergetic effects) was investigated for three biomass materials (pig manure, cow manure and food waste) under mesophilic conditions over a 36 day period. In addition to the three biomass materials (digested separately), 13 biomass mixtures (co-digested) were used. Two approaches for modelling biogas and methane yield during co-digestion, based on volatile solids concentration and ultimate gas and methane potentials, were evaluated. The dependency of apparent synergetic effects on digestion time and biomass mixture composition was further assessed using measured cumulative biogas and methane yields and specific biogas and methane generation rates. Results indicated that it is possible, based on known volatile solids concentration and ultimate biogas or methane yields for a set of biomass materials digested separately, to accurately estimate gas yields for biomass mixtures made from these materials using calibrated models. For the biomass materials considered here, modelling indicated that the addition of pig manure is the main cause of synergetic effects. Co-digestion generally resulted in improved ultimate biogas and methane yields compared to separate digestion. Biogas and methane production was furthermore significantly higher early (0-7 days) and to some degree also late (above 20 days) in the digestion process during co-digestion. © The Author(s) 2014.

Estimating Model Probabilities using Thermodynamic Markov Chain Monte Carlo Methods

NASA Astrophysics Data System (ADS)

Ye, M.; Liu, P.; Beerli, P.; Lu, D.; Hill, M. C.

2014-12-01

Markov chain Monte Carlo (MCMC) methods are widely used to evaluate model probability for quantifying model uncertainty. In a general procedure, MCMC simulations are first conducted for each individual model, and MCMC parameter samples are then used to approximate marginal likelihood of the model by calculating the geometric mean of the joint likelihood of the model and its parameters. It has been found the method of evaluating geometric mean suffers from the numerical problem of low convergence rate. A simple test case shows that even millions of MCMC samples are insufficient to yield accurate estimation of the marginal likelihood. To resolve this problem, a thermodynamic method is used to have multiple MCMC runs with different values of a heating coefficient between zero and one. When the heating coefficient is zero, the MCMC run is equivalent to a random walk MC in the prior parameter space; when the heating coefficient is one, the MCMC run is the conventional one. For a simple case with analytical form of the marginal likelihood, the thermodynamic method yields more accurate estimate than the method of using geometric mean. This is also demonstrated for a case of groundwater modeling with consideration of four alternative models postulated based on different conceptualization of a confining layer. This groundwater example shows that model probabilities estimated using the thermodynamic method are more reasonable than those obtained using the geometric method. The thermodynamic method is general, and can be used for a wide range of environmental problem for model uncertainty quantification.

Spot urine sodium measurements do not accurately estimate dietary sodium intake in chronic kidney disease12

PubMed Central

Dougher, Carly E; Rifkin, Dena E; Anderson, Cheryl AM; Smits, Gerard; Persky, Martha S; Block, Geoffrey A; Ix, Joachim H

2016-01-01

Background: Sodium intake influences blood pressure and proteinuria, yet the impact on long-term outcomes is uncertain in chronic kidney disease (CKD). Accurate assessment is essential for clinical and public policy recommendations, but few large-scale studies use 24-h urine collections. Recent studies that used spot urine sodium and associated estimating equations suggest that they may provide a suitable alternative, but their accuracy in patients with CKD is unknown. Objective: We compared the accuracy of 4 equations [the Nerbass, INTERSALT (International Cooperative Study on Salt, Other Factors, and Blood Pressure), Tanaka, and Kawasaki equations] that use spot urine sodium to estimate 24-h sodium excretion in patients with moderate to advanced CKD. Design: We evaluated the accuracy of spot urine sodium to predict mean 24-h urine sodium excretion over 9 mo in 129 participants with stage 3–4 CKD. Spot morning urine sodium was used in 4 estimating equations. Bias, precision, and accuracy were assessed and compared across each equation. Results: The mean age of the participants was 67 y, 52% were female, and the mean estimated glomerular filtration rate was 31 ± 9 mL · min–1 · 1.73 m–2. The mean ± SD number of 24-h urine collections was 3.5 ± 0.8/participant, and the mean 24-h sodium excretion was 168.2 ± 67.5 mmol/d. Although the Tanaka equation demonstrated the least bias (mean: −8.2 mmol/d), all 4 equations had poor precision and accuracy. The INTERSALT equation demonstrated the highest accuracy but derived an estimate only within 30% of mean measured sodium excretion in only 57% of observations. Bland-Altman plots revealed systematic bias with the Nerbass, INTERSALT, and Tanaka equations, underestimating sodium excretion when intake was high. Conclusion: These findings do not support the use of spot urine specimens to estimate dietary sodium intake in patients with CKD and research studies enriched with patients with CKD. The parent data for this

Robust dynamic myocardial perfusion CT deconvolution for accurate residue function estimation via adaptive-weighted tensor total variation regularization: a preclinical study.

PubMed

Zeng, Dong; Gong, Changfei; Bian, Zhaoying; Huang, Jing; Zhang, Xinyu; Zhang, Hua; Lu, Lijun; Niu, Shanzhou; Zhang, Zhang; Liang, Zhengrong; Feng, Qianjin; Chen, Wufan; Ma, Jianhua

2016-11-21

Dynamic myocardial perfusion computed tomography (MPCT) is a promising technique for quick diagnosis and risk stratification of coronary artery disease. However, one major drawback of dynamic MPCT imaging is the heavy radiation dose to patients due to its dynamic image acquisition protocol. In this work, to address this issue, we present a robust dynamic MPCT deconvolution algorithm via adaptive-weighted tensor total variation (AwTTV) regularization for accurate residue function estimation with low-mA s data acquisitions. For simplicity, the presented method is termed 'MPD-AwTTV'. More specifically, the gains of the AwTTV regularization over the original tensor total variation regularization are from the anisotropic edge property of the sequential MPCT images. To minimize the associative objective function we propose an efficient iterative optimization strategy with fast convergence rate in the framework of an iterative shrinkage/thresholding algorithm. We validate and evaluate the presented algorithm using both digital XCAT phantom and preclinical porcine data. The preliminary experimental results have demonstrated that the presented MPD-AwTTV deconvolution algorithm can achieve remarkable gains in noise-induced artifact suppression, edge detail preservation, and accurate flow-scaled residue function and MPHM estimation as compared with the other existing deconvolution algorithms in digital phantom studies, and similar gains can be obtained in the porcine data experiment.

Optimizing rice yields while minimizing yield-scaled global warming potential.

PubMed

Pittelkow, Cameron M; Adviento-Borbe, Maria A; van Kessel, Chris; Hill, James E; Linquist, Bruce A

2014-05-01

To meet growing global food demand with limited land and reduced environmental impact, agricultural greenhouse gas (GHG) emissions are increasingly evaluated with respect to crop productivity, i.e., on a yield-scaled as opposed to area basis. Here, we compiled available field data on CH4 and N2 O emissions from rice production systems to test the hypothesis that in response to fertilizer nitrogen (N) addition, yield-scaled global warming potential (GWP) will be minimized at N rates that maximize yields. Within each study, yield N surplus was calculated to estimate deficit or excess N application rates with respect to the optimal N rate (defined as the N rate at which maximum yield was achieved). Relationships between yield N surplus and GHG emissions were assessed using linear and nonlinear mixed-effects models. Results indicate that yields increased in response to increasing N surplus when moving from deficit to optimal N rates. At N rates contributing to a yield N surplus, N2 O and yield-scaled N2 O emissions increased exponentially. In contrast, CH4 emissions were not impacted by N inputs. Accordingly, yield-scaled CH4 emissions decreased with N addition. Overall, yield-scaled GWP was minimized at optimal N rates, decreasing by 21% compared to treatments without N addition. These results are unique compared to aerobic cropping systems in which N2 O emissions are the primary contributor to GWP, meaning yield-scaled GWP may not necessarily decrease for aerobic crops when yields are optimized by N fertilizer addition. Balancing gains in agricultural productivity with climate change concerns, this work supports the concept that high rice yields can be achieved with minimal yield-scaled GWP through optimal N application rates. Moreover, additional improvements in N use efficiency may further reduce yield-scaled GWP, thereby strengthening the economic and environmental sustainability of rice systems. © 2013 John Wiley & Sons Ltd.

Concentrations, and Estimated Loads and Yields of Total Nitrogen and Total Phosphorus at Selected Stations in Kentucky, 1979-2004

USGS Publications Warehouse

Crain, Angela S.; Martin, Gary R.

2009-01-01

To evaluate the State's water quality, the Kentucky Division of Water collects data from a statewide network of primary ambient stream water-quality monitoring stations and flexible, rotating watershed-monitoring stations. This ambient stream water-quality monitoring network program is directed to assess the conditions of surface waters throughout Kentucky. Water samples were collected monthly for the majority of the stations from 1979 to 1998, which represented agricultural, undeveloped (mainly forested), and areas of mixed land use/land cover. In 1998, the number of water samples collected was reduced to a collection frequency of six times per year (every 2 months) every 4 of 5 years, because a new monitoring network was implemented involving a 5-year rotating Basin Management Unit scheme of monitoring. This report presents the results of a study conducted by the U.S. Geological Survey, in cooperation with the Kentucky Energy and Environment Cabinet-Kentucky Division of Water, to summarize concentrations of total nitrogen and total phosphorus and provide estimates of total nitrogen and total phosphorus loads and yields in 55 selected streams in Kentucky's ambient stream water-quality monitoring network, which was operated from 1979 through 2004. Streams in predominately agricultural basins had higher concentrations of total nitrogen (TN) and concentrations of total phosphorus (TP) than streams in predominately undeveloped (forested) basins. Streams in basins in intensely developed karst areas characterized by caves, springs, sinkholes, and sinking streams had a higher median concentration of TN (1.5 milligrams per liter [mg/L]) than streams in basins with limited or no karst areas (0.63 mg/L). As with TN, median concentrations of TP also were higher in areas of intense karst (0.05 mg/L) than in areas with limited or no karst (0.02 mg/L). The U.S. Environmental Protection Agency (USEPA) has recommended ecoregional nutrient water-quality criteria as a starting

An Accurate Absorption-Based Net Primary Production Model for the Global Ocean

NASA Astrophysics Data System (ADS)

Silsbe, G.; Westberry, T. K.; Behrenfeld, M. J.; Halsey, K.; Milligan, A.

2016-02-01

As a vital living link in the global carbon cycle, understanding how net primary production (NPP) varies through space, time, and across climatic oscillations (e.g. ENSO) is a key objective in oceanographic research. The continual improvement of ocean observing satellites and data analytics now present greater opportunities for advanced understanding and characterization of the factors regulating NPP. In particular, the emergence of spectral inversion algorithms now permits accurate retrievals of the phytoplankton absorption coefficient (aΦ) from space. As NPP is the efficiency in which absorbed energy is converted into carbon biomass, aΦ measurements circumvents chlorophyll-based empirical approaches by permitting direct and accurate measurements of phytoplankton energy absorption. It has long been recognized, and perhaps underappreciated, that NPP and phytoplankton growth rates display muted variability when normalized to aΦ rather than chlorophyll. Here we present a novel absorption-based NPP model that parameterizes the underlying physiological mechanisms behind this muted variability, and apply this physiological model to the global ocean. Through a comparison against field data from the Hawaii and Bermuda Ocean Time Series, we demonstrate how this approach yields more accurate NPP measurements than other published NPP models. By normalizing NPP to satellite estimates of phytoplankton carbon biomass, this presentation also explores the seasonality of phytoplankton growth rates across several oceanic regions. Finally, we discuss how future advances in remote-sensing (e.g. hyperspectral satellites, LIDAR, autonomous profilers) can be exploited to further improve absorption-based NPP models.

Effect of incomplete pedigrees on estimates of inbreeding and inbreeding depression for days to first service and summit milk yield in Holsteins and Jerseys.

PubMed

Cassell, B G; Adamec, V; Pearson, R E

2003-09-01

A method to measure completeness of pedigree information is applied to populations of Holstein (registered and grade) and Jersey (largely registered) cows. Inbreeding coefficients where missing ancestors make no contribution were compared to a method using average relationships for missing ancestors. Estimated inbreeding depression was from an animal model that simultaneously adjusted for breeding values. Inbreeding and its standard deviation increased with more information, from 0.04 +/- 0.84 to 1.65 +/- 2.05 and 2.06 +/- 2.22 for grade Holsteins with <31%, 31 to 70%, and 71 to 100% complete five-generation pedigrees. Inbreeding from the method of average relationships for missing ancestors was 2.75 +/- 1.06, 3.10 +/- 2.21, and 2.89 +/- 2.37 for the same groups. Pedigrees of registered Holsteins and Jerseys were over 97% and over 89% complete, respectively. Inbreeding depression in days to first service and summit milk yield was estimated from both methods. Inbreeding depression for days to first service was not consistently significant for grade Holsteins and ranged from -0.37 d/1% increase in inbreeding (grade Holstein pedigrees <31% complete) to 0.15 d for grade Holstein pedigrees >70% complete. Estimates were similar for both methods. Inbreeding depression for registered Holsteins and Jerseys were positive (undesirable) but not significant for days to first service. Inbreeding depressed summit milk yield significantly in all groups by both methods. Summit milk yield declined by -0.12 to -0.06 kg/d per 1% increase in inbreeding in Holsteins and by -0.08 kg/1% increase in inbreeding in Jerseys. Pedigrees of grade animals are frequently incomplete and can yield misleading estimates of inbreeding depression. This problem is not overcome by inserting average relationships for missing ancestors in calculation of inbreeding coefficients.

On the Yield Strength of Oceanic Lithosphere

NASA Astrophysics Data System (ADS)

Jain, C.; Korenaga, J.; Karato, S. I.

2017-12-01

The origin of plate tectonic convection on Earth is intrinsically linked to the reduction in the strength of oceanic lithosphere at plate boundaries. A few mechanisms, such as deep thermal cracking [Korenaga, 2007] and strain localization due to grain-size reduction [e.g., Ricard and Bercovici, 2009], have been proposed to explain this reduction in lithospheric strength, but the significance of these mechanisms can be assessed only if we have accurate estimates on the strength of the undamaged oceanic lithosphere. The Peierls mechanism is likely to govern the rheology of old oceanic lithosphere [Kohlstedt et al., 1995], but the flow-law parameters for the Peierls mechanism suggested by previous studies do not agree with each other. We thus reanalyze the relevant experimental deformation data of olivine aggregates using Markov chain Monte Carlo inversion, which can handle the highly nonlinear constitutive equation of the Peierls mechanism [Korenaga and Karato, 2008; Mullet et al., 2015]. Our inversion results indicate nontrivial nonuniqueness in every flow-law parameter for the Peierls mechanism. Moreover, the resultant flow laws, all of which are consistent with the same experimental data, predict substantially different yield stresses under lithospheric conditions and could therefore have different implications for the origin of plate tectonics. We discuss some future directions to improve our constraints on lithospheric yield strength.

Joint Bayesian inference for near-surface explosion yield

NASA Astrophysics Data System (ADS)

Bulaevskaya, V.; Ford, S. R.; Ramirez, A. L.; Rodgers, A. J.

2016-12-01

A near-surface explosion generates seismo-acoustic motion that is related to its yield. However, the recorded motion is affected by near-source effects such as depth-of-burial, and propagation-path effects such as variable geology. We incorporate these effects in a forward model relating yield to seismo-acoustic motion, and use Bayesian inference to estimate yield given recordings of the seismo-acoustic wavefield. The Bayesian approach to this inverse problem allows us to obtain the probability distribution of plausible yield values and thus quantify the uncertainty in the yield estimate. Moreover, the sensitivity of the acoustic signal falls as a function of the depth-of-burial, while the opposite relationship holds for the seismic signal. Therefore, using both the acoustic and seismic wavefield data allows us to avoid the trade-offs associated with using only one of these signals alone. In addition, our inference framework allows for correlated features of the same data type (seismic or acoustic) to be incorporated in the estimation of yield in order to make use of as much information from the same waveform as possible. We demonstrate our approach with a historical dataset and a contemporary field experiment.

PROMAB-GIS: A GIS based Tool for Estimating Runoff and Sediment Yield in running Waters

NASA Astrophysics Data System (ADS)

Jenewein, S.; Rinderer, M.; Ploner, A.; Sönser, T.

2003-04-01

In recent times settlements have expanded, traffic and tourist activities have increased in most alpine regions. As a consequence, on the one hand humans and goods are affected by natural hazard processes more often, while on the other hand the demand for protection by both technical constructions and planning measures carried out by public authorities is growing. This situation results in an ever stronger need of reproducibility, comparability, transparency of all methods applied in modern natural hazard management. As a contribution to a new way of coping this situation Promab-GIS Version 1.0 has been developed. Promab-Gis has been designed as a model for time- and space-dependent determination of both runoff and bedload transport in rivers of small alpine catchment areas. The estimation of the unit hydrograph relies upon the "rational formula" and the time-area curves of the watershed. The time area diagram is a graph of cumulative drainage area contributing to discharge at the watershed outlet within a specified time of travel. The sediment yield is estimated for each cell of the channel network by determining the actual process type (erosion, transport or accumulation). Two types of transport processes are considered, sediment transport and debris flows. All functions of Promab-GIS are integrated in the graphical user interface of ArcView as pull-up menus and tool buttons. Hence the application of Promab-GIS does not rely on a sophisticated knowledge of GIS in general, respectively the ArcView software. However, despite the use of computer assistance, Promab-GIS still is an expert support system. In order to obtain plausible results, the users must be familiar with all the relevant processes controlling runoff and sediment yield in torrent catchments.

Concentrations, and estimated loads and yields of nutrients and suspended sediment in the Little River basin, Kentucky, 2003-04

USGS Publications Warehouse

Crain, Angela S.

2006-01-01

Nutrients, primarily nitrogen and phosphorus compounds, naturally occur but also are applied to land in the form of commercial fertilizers and livestock waste to enhance plant growth. Concentrations, estimated loads and yields, and sources of nitrite plus nitrate, total phosphorus, and orthophosphate were evaluated in streams of the Little River Basin to assist the Commonwealth of Kentucky in developing 'total maximum daily loads' (TMDLs) for streams in the basin. The Little River Basin encompasses about 600 square miles in Christian and Trigg Counties, and a portion of Caldwell County in western Kentucky. Water samples were collected in streams in the Little River Basin during 2003-04 as part of a study conducted in cooperation with the Kentucky Department of Agriculture. A total of 92 water samples were collected at four fixed-network sites from March through November 2003 and from February through November 2004. An additional 20 samples were collected at five synoptic-network sites during the same period. Median concentrations of nitrogen, phosphorus, and suspended sediment varied spatially and seasonally. Concentrations of nitrogen were higher in the spring (March-May) after fertilizer application and runoff. The highest concentration of nitrite plus nitrate-5.7 milligrams per liter (mg/L)-was detected at the South Fork Little River site. The Sinking Fork near Cadiz site had the highest median concentration of nitrite plus nitrate (4.6 mg/L). The North Fork Little River site and the Little River near Cadiz site had higher concentrations of orthophosphate in the fall and lower concentrations in the spring. Concentrations of orthophosphate remained high during the summer (June-August) at the North Fork Little River site possibly because of the contribution of wastewater effluent to streamflow. Fifty-eight percent of the concentrations of total phosphorus at the nine sites exceeded the U.S. Environmental Protection Agency recommended maximum concentration limit of

Assimilation of Remotely Sensed Soil Moisture Profiles into a Crop Modeling Framework for Reliable Yield Estimations

NASA Astrophysics Data System (ADS)

Mishra, V.; Cruise, J.; Mecikalski, J. R.

2017-12-01

Much effort has been expended recently on the assimilation of remotely sensed soil moisture into operational land surface models (LSM). These efforts have normally been focused on the use of data derived from the microwave bands and results have often shown that improvements to model simulations have been limited due to the fact that microwave signals only penetrate the top 2-5 cm of the soil surface. It is possible that model simulations could be further improved through the introduction of geostationary satellite thermal infrared (TIR) based root zone soil moisture in addition to the microwave deduced surface estimates. In this study, root zone soil moisture estimates from the TIR based Atmospheric Land Exchange Inverse (ALEXI) model were merged with NASA Soil Moisture Active Passive (SMAP) based surface estimates through the application of informational entropy. Entropy can be used to characterize the movement of moisture within the vadose zone and accounts for both advection and diffusion processes. The Principle of Maximum Entropy (POME) can be used to derive complete soil moisture profiles and, fortuitously, only requires a surface boundary condition as well as the overall mean moisture content of the soil column. A lower boundary can be considered a soil parameter or obtained from the LSM itself. In this study, SMAP provided the surface boundary while ALEXI supplied the mean and the entropy integral was used to tie the two together and produce the vertical profile. However, prior to the merging, the coarse resolution (9 km) SMAP data were downscaled to the finer resolution (4.7 km) ALEXI grid. The disaggregation scheme followed the Soil Evaporative Efficiency approach and again, all necessary inputs were available from the TIR model. The profiles were then assimilated into a standard agricultural crop model (Decision Support System for Agrotechnology, DSSAT) via the ensemble Kalman Filter. The study was conducted over the Southeastern United States for the

A near-optimal low complexity sensor fusion technique for accurate indoor localization based on ultrasound time of arrival measurements from low-quality sensors

NASA Astrophysics Data System (ADS)

Mitilineos, Stelios A.; Argyreas, Nick D.; Thomopoulos, Stelios C. A.

2009-05-01

A fusion-based localization technique for location-based services in indoor environments is introduced herein, based on ultrasound time-of-arrival measurements from multiple off-the-shelf range estimating sensors which are used in a market-available localization system. In-situ field measurements results indicated that the respective off-the-shelf system was unable to estimate position in most of the cases, while the underlying sensors are of low-quality and yield highly inaccurate range and position estimates. An extensive analysis is performed and a model of the sensor-performance characteristics is established. A low-complexity but accurate sensor fusion and localization technique is then developed, which consists inof evaluating multiple sensor measurements and selecting the one that is considered most-accurate based on the underlying sensor model. Optimality, in the sense of a genie selecting the optimum sensor, is subsequently evaluated and compared to the proposed technique. The experimental results indicate that the proposed fusion method exhibits near-optimal performance and, albeit being theoretically suboptimal, it largely overcomes most flaws of the underlying single-sensor system resulting in a localization system of increased accuracy, robustness and availability.

Climate change impacts on crop yield: evidence from China.

PubMed

Wei, Taoyuan; Cherry, Todd L; Glomrød, Solveig; Zhang, Tianyi

2014-11-15

When estimating climate change impact on crop yield, a typical assumption is constant elasticity of yield with respect to a climate variable even though the elasticity may be inconstant. After estimating both constant and inconstant elasticities with respect to temperature and precipitation based on provincial panel data in China 1980-2008, our results show that during that period, the temperature change contributes positively to total yield growth by 1.3% and 0.4% for wheat and rice, respectively, but negatively by 12% for maize. The impacts of precipitation change are marginal. We also compare our estimates with other studies and highlight the implications of the inconstant elasticities for crop yield, harvest and food security. We conclude that climate change impact on crop yield would not be an issue in China if positive impacts of other socio-economic factors continue in the future. Copyright © 2014 Elsevier B.V. All rights reserved.

Accurate Visual Heading Estimation at High Rotation Rate Without Oculomotor or Static-Depth Cues

NASA Technical Reports Server (NTRS)

Stone, Leland S.; Perrone, John A.; Null, Cynthia H. (Technical Monitor)

1995-01-01

It has been claimed that either oculomotor or static depth cues provide the signals about self-rotation necessary approx.-1 deg/s. We tested this hypothesis by simulating self-motion along a curved path with the eyes fixed in the head (plus or minus 16 deg/s of rotation). Curvilinear motion offers two advantages: 1) heading remains constant in retinotopic coordinates, and 2) there is no visual-oculomotor conflict (both actual and simulated eye position remain stationary). We simulated 400 ms of rotation combined with 16 m/s of translation at fixed angles with respect to gaze towards two vertical planes of random dots initially 12 and 24 m away, with a field of view of 45 degrees. Four subjects were asked to fixate a central cross and to respond whether they were translating to the left or right of straight-ahead gaze. From the psychometric curves, heading bias (mean) and precision (semi-interquartile) were derived. The mean bias over 2-5 runs was 3.0, 4.0, -2.0, -0.4 deg for the first author and three naive subjects, respectively (positive indicating towards the rotation direction). The mean precision was 2.0, 1.9, 3.1, 1.6 deg. respectively. The ability of observers to make relatively accurate and precise heading judgments, despite the large rotational flow component, refutes the view that extra-flow-field information is necessary for human visual heading estimation at high rotation rates. Our results support models that process combined translational/rotational flow to estimate heading, but should not be construed to suggest that other cues do not play an important role when they are available to the observer.

Covariance generation and uncertainty propagation for thermal and fast neutron induced fission yields

NASA Astrophysics Data System (ADS)

Terranova, Nicholas; Serot, Olivier; Archier, Pascal; De Saint Jean, Cyrille; Sumini, Marco

2017-09-01

Fission product yields (FY) are fundamental nuclear data for several applications, including decay heat, shielding, dosimetry, burn-up calculations. To be safe and sustainable, modern and future nuclear systems require accurate knowledge on reactor parameters, with reduced margins of uncertainty. Present nuclear data libraries for FY do not provide consistent and complete uncertainty information which are limited, in many cases, to only variances. In the present work we propose a methodology to evaluate covariance matrices for thermal and fast neutron induced fission yields. The semi-empirical models adopted to evaluate the JEFF-3.1.1 FY library have been used in the Generalized Least Square Method available in CONRAD (COde for Nuclear Reaction Analysis and Data assimilation) to generate covariance matrices for several fissioning systems such as the thermal fission of U235, Pu239 and Pu241 and the fast fission of U238, Pu239 and Pu240. The impact of such covariances on nuclear applications has been estimated using deterministic and Monte Carlo uncertainty propagation techniques. We studied the effects on decay heat and reactivity loss uncertainty estimation for simplified test case geometries, such as PWR and SFR pin-cells. The impact on existing nuclear reactors, such as the Jules Horowitz Reactor under construction at CEA-Cadarache, has also been considered.

Using age on clothes size label to estimate weight in emergency paediatric patients.

PubMed

Elgie, Laura D; Williams, Andrew R

2012-10-01

To study formulae that estimate children's weight using their actual age. To determine whether using the age on their clothes size label in these formulae can estimate weight when their actual age is unknown. The actual age and age on the clothes labels of 188 children were inserted into formulae that estimate children's weight. These estimates were compared with their actual weight. Bland-Altman plots calculated the precision and accuracy of each of these estimates. In all formulae, using age on the clothes sizes label provided a more precise estimate than the child's actual age. In emergencies where a child's age is unknown, use of the age on their clothes label in weight-estimating formulae yields acceptable weight estimates. Even in situations where a child's age is known, the age on their clothes label may provide a more accurate and precise weight estimate than the actual age.

OP-Yield Version 1.00 user's guide

Treesearch

Martin W. Ritchie; Jianwei Zhang

2018-01-01

OP-Yield is a Microsoft Excel™ spreadsheet with 14 specified user inputs to derive custom yield estimates using the original Oliver and Powers (1978) functions as the foundation. It presents yields for ponderosa pine (Pinus ponderosa Lawson & C. Lawson) plantations in northern California. The basic model forms for dominantand...

Multilevel Empirical Bayes Modeling for Improved Estimation of Toxicant Formulations to Suppress Parasitic Sea Lamprey in the Upper Great Lakes

USGS Publications Warehouse

Hatfield, L.A.; Gutreuter, S.; Boogaard, M.A.; Carlin, B.P.

2011-01-01

Estimation of extreme quantal-response statistics, such as the concentration required to kill 99.9% of test subjects (LC99.9), remains a challenge in the presence of multiple covariates and complex study designs. Accurate and precise estimates of the LC99.9 for mixtures of toxicants are critical to ongoing control of a parasitic invasive species, the sea lamprey, in the Laurentian Great Lakes of North America. The toxicity of those chemicals is affected by local and temporal variations in water chemistry, which must be incorporated into the modeling. We develop multilevel empirical Bayes models for data from multiple laboratory studies. Our approach yields more accurate and precise estimation of the LC99.9 compared to alternative models considered. This study demonstrates that properly incorporating hierarchical structure in laboratory data yields better estimates of LC99.9 stream treatment values that are critical to larvae control in the field. In addition, out-of-sample prediction of the results of in situ tests reveals the presence of a latent seasonal effect not manifest in the laboratory studies, suggesting avenues for future study and illustrating the importance of dual consideration of both experimental and observational data. ?? 2011, The International Biometric Society.

Determining site index accurately in even-aged stands

Treesearch

Gayne G. Erdmann; Ralph M., Jr. Peterson

1992-01-01

Good site index estimates are necessary for intensive forest management. To get tree age used in determining site index, increment cores are commonly used. The diffuse-porous rings of northern hardwoods, though, are difficult to count in cores, so many site index estimates are imprecise. Also, measuring the height of standing trees is more difficult and less accurate...

National Variation in Crop Yield Production Functions

NASA Astrophysics Data System (ADS)

Devineni, N.; Rising, J. A.

2017-12-01

A new multilevel model for yield prediction at the county scale using regional climate covariates is presented in this paper. A new crop specific water deficit index, growing degree days, extreme degree days, and time-trend as an approximation of technology improvements are used as predictors to estimate annual crop yields for each county from 1949 to 2009. Every county in the United States is allowed to have unique parameters describing how these weather predictors are related to yield outcomes. County-specific parameters are further modeled as varying according to climatic characteristics, allowing the prediction of parameters in regions where crops are not currently grown and into the future. The structural relationships between crop yield and regional climate as well as trends are estimated simultaneously. All counties are modeled in a single multilevel model with partial pooling to automatically group and reduce estimation uncertainties. The model captures up to 60% of the variability in crop yields after removing the effect of technology, does well in out of sample predictions and is useful in relating the climate responses to local bioclimatic factors. We apply the predicted growing models in a cost-benefit analysis to identify the most economically productive crop in each county.

Brazil soybean yield covariance model

NASA Technical Reports Server (NTRS)

Callis, S. L.; Sakamoto, C.

1984-01-01

A model based on multiple regression was developed to estimate soybean yields for the seven soybean-growing states of Brazil. The meteorological data of these seven states were pooled and the years 1975 to 1980 were used to model since there was no technological trend in the yields during these years. Predictor variables were derived from monthly total precipitation and monthly average temperature.

Estimating agricultural yield gap in Africa using MODIS NDVI dataset

NASA Astrophysics Data System (ADS)

Luan, Y.; Zhu, W.; Luo, X.; Liu, J.; Cui, X.

2013-12-01

Global agriculture has undergone a period of rapid intensification characterized as 'Green Revolution', except for Africa, which is the region most affected by unreliable food access and undernourishment. Increasing crop production will be one of the most challenges and most effectual way to mitigate food insecurity there, as Africa's agricultural yield is on a much lower level comparing to global average. In this study we characterize cropland vegetation phenology in Africa based on MODIS NDVI time series between 2000 and 2012. Cumulated NDVI is a proxy for net primary productivity and used as an indicator for evaluating the potential yield gap in Africa. It is achieved via translating the gap between optimum attainable productivity level in each classification of cropping systems and actual productivity level by the relationship of cumulated NDVI and cereal-equivalent production. The results show most of cropland area in Africa have decreasing trend in cumulated NDVI, distributing in the Nile Delta, Eastern Africa and central of semi-arid to arid savanna area, except significant positive cumulated NDVI trends are mainly found between Senegal and Benin. Using cumulated NDVI and statistics of cereal equivalent production, we find remarkable potential yield gap at the Horn of East Africa (especially in Somalia), Northern Africa (Morocco, Algeria and Tunisia). Meanwhile, countries locating at the savanna area near Sahel desert and South Africa also show significant potential, though they already have a relatively high level of productivity. Our results can help provide policy recommendation for local government or NGO to tackle food security problems by identifying zones with high potential of yield improvement.

Assessment of uncertainties in soil erosion and sediment yield estimates at ungauged basins: an application to the Garra River basin, India

NASA Astrophysics Data System (ADS)

Swarnkar, Somil; Malini, Anshu; Tripathi, Shivam; Sinha, Rajiv

2018-04-01

High soil erosion and excessive sediment load are serious problems in several Himalayan river basins. To apply mitigation procedures, precise estimation of soil erosion and sediment yield with associated uncertainties are needed. Here, the revised universal soil loss equation (RUSLE) and the sediment delivery ratio (SDR) equations are used to estimate the spatial pattern of soil erosion (SE) and sediment yield (SY) in the Garra River basin, a small Himalayan tributary of the River Ganga. A methodology is proposed for quantifying and propagating uncertainties in SE, SDR and SY estimates. Expressions for uncertainty propagation are derived by first-order uncertainty analysis, making the method viable even for large river basins. The methodology is applied to investigate the relative importance of different RUSLE factors in estimating the magnitude and uncertainties in SE over two distinct morphoclimatic regimes of the Garra River basin, namely the upper mountainous region and the lower alluvial plains. Our results suggest that average SE in the basin is very high (23 ± 4.7 t ha-1 yr-1) with higher values in the upper mountainous region (92 ± 15.2 t ha-1 yr-1) compared to the lower alluvial plains (19.3 ± 4 t ha-1 yr-1). Furthermore, the topographic steepness (LS) and crop practice (CP) factors exhibit higher uncertainties than other RUSLE factors. The annual average SY is estimated at two locations in the basin - Nanak Sagar Dam (NSD) for the period 1962-2008 and Husepur gauging station (HGS) for 1987-2002. The SY at NSD and HGS are estimated to be 6.9 ± 1.2 × 105 t yr-1 and 6.7 ± 1.4 × 106 t yr-1, respectively, and the estimated 90 % interval contains the observed values of 6.4 × 105 t yr-1 and 7.2 × 106 t yr-1, respectively. The study demonstrated the usefulness of the proposed methodology for quantifying uncertainty in SE and SY estimates at ungauged basins.

Argentina soybean yield model

NASA Technical Reports Server (NTRS)

Callis, S. L.; Sakamoto, C.

1984-01-01

A model based on multiple regression was developed to estimate soybean yields for the country of Argentina. A meteorological data set was obtained for the country by averaging data for stations within the soybean growing area. Predictor variables for the model were derived from monthly total precipitation and monthly average temperature. A trend variable was included for the years 1969 to 1978 since an increasing trend in yields due to technology was observed between these years.

Robust dynamic myocardial perfusion CT deconvolution for accurate residue function estimation via adaptive-weighted tensor total variation regularization: a preclinical study

NASA Astrophysics Data System (ADS)

Zeng, Dong; Gong, Changfei; Bian, Zhaoying; Huang, Jing; Zhang, Xinyu; Zhang, Hua; Lu, Lijun; Niu, Shanzhou; Zhang, Zhang; Liang, Zhengrong; Feng, Qianjin; Chen, Wufan; Ma, Jianhua

2016-11-01

Dynamic myocardial perfusion computed tomography (MPCT) is a promising technique for quick diagnosis and risk stratification of coronary artery disease. However, one major drawback of dynamic MPCT imaging is the heavy radiation dose to patients due to its dynamic image acquisition protocol. In this work, to address this issue, we present a robust dynamic MPCT deconvolution algorithm via adaptive-weighted tensor total variation (AwTTV) regularization for accurate residue function estimation with low-mA s data acquisitions. For simplicity, the presented method is termed ‘MPD-AwTTV’. More specifically, the gains of the AwTTV regularization over the original tensor total variation regularization are from the anisotropic edge property of the sequential MPCT images. To minimize the associative objective function we propose an efficient iterative optimization strategy with fast convergence rate in the framework of an iterative shrinkage/thresholding algorithm. We validate and evaluate the presented algorithm using both digital XCAT phantom and preclinical porcine data. The preliminary experimental results have demonstrated that the presented MPD-AwTTV deconvolution algorithm can achieve remarkable gains in noise-induced artifact suppression, edge detail preservation, and accurate flow-scaled residue function and MPHM estimation as compared with the other existing deconvolution algorithms in digital phantom studies, and similar gains can be obtained in the porcine data experiment.

Fission yield and criticality excursion code

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blanchard, A.

2000-06-30

The ANSI/ANS 8.3 standard allows a maximum yield not to exceed 2 x 10 fissions to calculate requiring the alarm system to be effective. It is common practice to use this allowance or to develop some other yield based on past criticality accident history or excursion experiments. The literature on the subject of yields discusses maximum yields larger and somewhat smaller than the ANS 8.3 permissive value. The ability to model criticality excursions and vary the various parameters to determine a credible maximum yield for operational specific cases has been available for some time but is not in common usemore » by criticality safety specialists. The topic of yields for various solution, metal, oxide powders, etc. in various geometry's and containers has been published by laboratory specialists or university staff and students for many decades but have not been available to practitioners. The need for best-estimate calculations of fission yields with a well-validated criticality excursion code has long been recognized. But no coordinated effort has been made so far to develop a generalized and well-validated excursion code for different types of systems. In this paper, the current practices to estimate fission yields are summarized along with its shortcomings for the 12-Rad zone (at SRS) and Criticality Alarm System (CAS) calculations. Finally the need for a user-friendly excursion code is reemphasized.« less

Children Can Accurately Monitor and Control Their Number-Line Estimation Performance

ERIC Educational Resources Information Center

Wall, Jenna L.; Thompson, Clarissa A.; Dunlosky, John; Merriman, William E.

2016-01-01

Accurate monitoring and control are essential for effective self-regulated learning. These metacognitive abilities may be particularly important for developing math skills, such as when children are deciding whether a math task is difficult or whether they made a mistake on a particular item. The present experiments investigate children's ability…

Toward more accurate loss tangent measurements in reentrant cavities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moyer, R. D.

1980-05-01

Karpova has described an absolute method for measurement of dielectric properties of a solid in a coaxial reentrant cavity. His cavity resonance equation yields very accurate results for dielectric constants. However, he presented only approximate expressions for the loss tangent. This report presents more exact expressions for that quantity and summarizes some experimental results.

Estimation of biogas and methane yields in an UASB treating potato starch processing wastewater with backpropagation artificial neural network.

PubMed

Antwi, Philip; Li, Jianzheng; Boadi, Portia Opoku; Meng, Jia; Shi, En; Deng, Kaiwen; Bondinuba, Francis Kwesi

2017-03-01

Three-layered feedforward backpropagation (BP) artificial neural networks (ANN) and multiple nonlinear regression (MnLR) models were developed to estimate biogas and methane yield in an upflow anaerobic sludge blanket (UASB) reactor treating potato starch processing wastewater (PSPW). Anaerobic process parameters were optimized to identify their importance on methanation. pH, total chemical oxygen demand, ammonium, alkalinity, total Kjeldahl nitrogen, total phosphorus, volatile fatty acids and hydraulic retention time selected based on principal component analysis were used as input variables, whiles biogas and methane yield were employed as target variables. Quasi-Newton method and conjugate gradient backpropagation algorithms were best among eleven training algorithms. Coefficient of determination (R 2 ) of the BP-ANN reached 98.72% and 97.93% whiles MnLR model attained 93.9% and 91.08% for biogas and methane yield, respectively. Compared with the MnLR model, BP-ANN model demonstrated significant performance, suggesting possible control of the anaerobic digestion process with the BP-ANN model. Copyright © 2016 Elsevier Ltd. All rights reserved.

A novel SURE-based criterion for parametric PSF estimation.

PubMed

Xue, Feng; Blu, Thierry

2015-02-01

We propose an unbiased estimate of a filtered version of the mean squared error--the blur-SURE (Stein's unbiased risk estimate)--as a novel criterion for estimating an unknown point spread function (PSF) from the degraded image only. The PSF is obtained by minimizing this new objective functional over a family of Wiener processings. Based on this estimated blur kernel, we then perform nonblind deconvolution using our recently developed algorithm. The SURE-based framework is exemplified with a number of parametric PSF, involving a scaling factor that controls the blur size. A typical example of such parametrization is the Gaussian kernel. The experimental results demonstrate that minimizing the blur-SURE yields highly accurate estimates of the PSF parameters, which also result in a restoration quality that is very similar to the one obtained with the exact PSF, when plugged into our recent multi-Wiener SURE-LET deconvolution algorithm. The highly competitive results obtained outline the great potential of developing more powerful blind deconvolution algorithms based on SURE-like estimates.

Adaptive Green-Kubo estimates of transport coefficients from molecular dynamics based on robust error analysis.

PubMed

Jones, Reese E; Mandadapu, Kranthi K

2012-04-21

We present a rigorous Green-Kubo methodology for calculating transport coefficients based on on-the-fly estimates of: (a) statistical stationarity of the relevant process, and (b) error in the resulting coefficient. The methodology uses time samples efficiently across an ensemble of parallel replicas to yield accurate estimates, which is particularly useful for estimating the thermal conductivity of semi-conductors near their Debye temperatures where the characteristic decay times of the heat flux correlation functions are large. Employing and extending the error analysis of Zwanzig and Ailawadi [Phys. Rev. 182, 280 (1969)] and Frenkel [in Proceedings of the International School of Physics "Enrico Fermi", Course LXXV (North-Holland Publishing Company, Amsterdam, 1980)] to the integral of correlation, we are able to provide tight theoretical bounds for the error in the estimate of the transport coefficient. To demonstrate the performance of the method, four test cases of increasing computational cost and complexity are presented: the viscosity of Ar and water, and the thermal conductivity of Si and GaN. In addition to producing accurate estimates of the transport coefficients for these materials, this work demonstrates precise agreement of the computed variances in the estimates of the correlation and the transport coefficient with the extended theory based on the assumption that fluctuations follow a Gaussian process. The proposed algorithm in conjunction with the extended theory enables the calculation of transport coefficients with the Green-Kubo method accurately and efficiently.

Adaptive Green-Kubo estimates of transport coefficients from molecular dynamics based on robust error analysis

NASA Astrophysics Data System (ADS)

Jones, Reese E.; Mandadapu, Kranthi K.

2012-04-01

We present a rigorous Green-Kubo methodology for calculating transport coefficients based on on-the-fly estimates of: (a) statistical stationarity of the relevant process, and (b) error in the resulting coefficient. The methodology uses time samples efficiently across an ensemble of parallel replicas to yield accurate estimates, which is particularly useful for estimating the thermal conductivity of semi-conductors near their Debye temperatures where the characteristic decay times of the heat flux correlation functions are large. Employing and extending the error analysis of Zwanzig and Ailawadi [Phys. Rev. 182, 280 (1969)], 10.1103/PhysRev.182.280 and Frenkel [in Proceedings of the International School of Physics "Enrico Fermi", Course LXXV (North-Holland Publishing Company, Amsterdam, 1980)] to the integral of correlation, we are able to provide tight theoretical bounds for the error in the estimate of the transport coefficient. To demonstrate the performance of the method, four test cases of increasing computational cost and complexity are presented: the viscosity of Ar and water, and the thermal conductivity of Si and GaN. In addition to producing accurate estimates of the transport coefficients for these materials, this work demonstrates precise agreement of the computed variances in the estimates of the correlation and the transport coefficient with the extended theory based on the assumption that fluctuations follow a Gaussian process. The proposed algorithm in conjunction with the extended theory enables the calculation of transport coefficients with the Green-Kubo method accurately and efficiently.

Reservoir evaluation of thin-bedded turbidites and hydrocarbon pore thickness estimation for an accurate quantification of resource

NASA Astrophysics Data System (ADS)

Omoniyi, Bayonle; Stow, Dorrik

2016-04-01

One of the major challenges in the assessment of and production from turbidite reservoirs is to take full account of thin and medium-bedded turbidites (<10cm and <30cm respectively). Although such thinner, low-pay sands may comprise a significant proportion of the reservoir succession, they can go unnoticed by conventional analysis and so negatively impact on reserve estimation, particularly in fields producing from prolific thick-bedded turbidite reservoirs. Field development plans often take little note of such thin beds, which are therefore bypassed by mainstream production. In fact, the trapped and bypassed fluids can be vital where maximising field value and optimising production are key business drivers. We have studied in detail, a succession of thin-bedded turbidites associated with thicker-bedded reservoir facies in the North Brae Field, UKCS, using a combination of conventional logs and cores to assess the significance of thin-bedded turbidites in computing hydrocarbon pore thickness (HPT). This quantity, being an indirect measure of thickness, is critical for an accurate estimation of original-oil-in-place (OOIP). By using a combination of conventional and unconventional logging analysis techniques, we obtain three different results for the reservoir intervals studied. These results include estimated net sand thickness, average sand thickness, and their distribution trend within a 3D structural grid. The net sand thickness varies from 205 to 380 ft, and HPT ranges from 21.53 to 39.90 ft. We observe that an integrated approach (neutron-density cross plots conditioned to cores) to HPT quantification reduces the associated uncertainties significantly, resulting in estimation of 96% of actual HPT. Further work will focus on assessing the 3D dynamic connectivity of the low-pay sands with the surrounding thick-bedded turbidite facies.

Accurate Estimation of Solvation Free Energy Using Polynomial Fitting Techniques

PubMed Central

Shyu, Conrad; Ytreberg, F. Marty

2010-01-01

This report details an approach to improve the accuracy of free energy difference estimates using thermodynamic integration data (slope of the free energy with respect to the switching variable λ) and its application to calculating solvation free energy. The central idea is to utilize polynomial fitting schemes to approximate the thermodynamic integration data to improve the accuracy of the free energy difference estimates. Previously, we introduced the use of polynomial regression technique to fit thermodynamic integration data (Shyu and Ytreberg, J Comput Chem 30: 2297–2304, 2009). In this report we introduce polynomial and spline interpolation techniques. Two systems with analytically solvable relative free energies are used to test the accuracy of the interpolation approach. We also use both interpolation and regression methods to determine a small molecule solvation free energy. Our simulations show that, using such polynomial techniques and non-equidistant λ values, the solvation free energy can be estimated with high accuracy without using soft-core scaling and separate simulations for Lennard-Jones and partial charges. The results from our study suggest these polynomial techniques, especially with use of non-equidistant λ values, improve the accuracy for ΔF estimates without demanding additional simulations. We also provide general guidelines for use of polynomial fitting to estimate free energy. To allow researchers to immediately utilize these methods, free software and documentation is provided via http://www.phys.uidaho.edu/ytreberg/software. PMID:20623657

Estimating the potential intensification of global grazing systems based on climate adjusted yield gap analysis

NASA Astrophysics Data System (ADS)

Sheehan, J. J.

2016-12-01

We report here a first-of-its-kind analysis of the potential for intensification of global grazing systems. Intensification is calculated using the statistical yield gap methodology developed previously by others (Mueller et al 2012 and Licker et al 2010) for global crop systems. Yield gaps are estimated by binning global pasture land area into 100 equal area sized bins of similar climate (defined by ranges of rainfall and growing degree days). Within each bin, grid cells of pastureland are ranked from lowest to highest productivity. The global intensification potential is defined as the sum of global production across all bins at a given percentile ranking (e.g. performance at the 90th percentile) divided by the total current global production. The previous yield gap studies focused on crop systems because productivity data on these systems is readily available. Nevertheless, global crop land represents only one-third of total global agricultural land, while pasture systems account for the remaining two-thirds. Thus, it is critical to conduct the same kind of analysis on what is the largest human use of land on the planet—pasture systems. In 2013, Herrero et al announced the completion of a geospatial data set that augmented the animal census data with data and modeling about production systems and overall food productivity (Herrero et al, PNAS 2013). With this data set, it is now possible to apply yield gap analysis to global pasture systems. We used the Herrero et al data set to evaluate yield gaps for meat and milk production from pasture based systems for cattle, sheep and goats. The figure included with this abstract shows the intensification potential for kcal per hectare per year of meat and milk from global cattle, sheep and goats as a function of increasing levels of performance. Performance is measured as the productivity achieved at a given ranked percentile within each bin.We find that if all pasture land were raised to their 90th percentile of

Argentina wheat yield model

NASA Technical Reports Server (NTRS)

Callis, S. L.; Sakamoto, C.

1984-01-01

Five models based on multiple regression were developed to estimate wheat yields for the five wheat growing provinces of Argentina. Meteorological data sets were obtained for each province by averaging data for stations within each province. Predictor variables for the models were derived from monthly total precipitation, average monthly mean temperature, and average monthly maximum temperature. Buenos Aires was the only province for which a trend variable was included because of increasing trend in yield due to technology from 1950 to 1963.

Argentina corn yield model

NASA Technical Reports Server (NTRS)

Callis, S. L.; Sakamoto, C.

1984-01-01

A model based on multiple regression was developed to estimate corn yields for the country of Argentina. A meteorological data set was obtained for the country by averaging data for stations within the corn-growing area. Predictor variables for the model were derived from monthly total precipitation, average monthly mean temperature, and average monthly maximum temperature. A trend variable was included for the years 1965 to 1980 since an increasing trend in yields due to technology was observed between these years.

13C-Labeled Gluconate Tracing as a Direct and Accurate Method for Determining the Pentose Phosphate Pathway Split Ratio in Penicillium chrysogenum

PubMed Central

Kleijn, Roelco J.; van Winden, Wouter A.; Ras, Cor; van Gulik, Walter M.; Schipper, Dick; Heijnen, Joseph J.

2006-01-01

In this study we developed a new method for accurately determining the pentose phosphate pathway (PPP) split ratio, an important metabolic parameter in the primary metabolism of a cell. This method is based on simultaneous feeding of unlabeled glucose and trace amounts of [U-13C]gluconate, followed by measurement of the mass isotopomers of the intracellular metabolites surrounding the 6-phosphogluconate node. The gluconate tracer method was used with a penicillin G-producing chemostat culture of the filamentous fungus Penicillium chrysogenum. For comparison, a 13C-labeling-based metabolic flux analysis (MFA) was performed for glycolysis and the PPP of P. chrysogenum. For the first time mass isotopomer measurements of 13C-labeled primary metabolites are reported for P. chrysogenum and used for a 13C-based MFA. Estimation of the PPP split ratio of P. chrysogenum at a growth rate of 0.02 h−1 yielded comparable values for the gluconate tracer method and the 13C-based MFA method, 51.8% and 51.1%, respectively. A sensitivity analysis of the estimated PPP split ratios showed that the 95% confidence interval was almost threefold smaller for the gluconate tracer method than for the 13C-based MFA method (40.0 to 63.5% and 46.0 to 56.5%, respectively). From these results we concluded that the gluconate tracer method permits accurate determination of the PPP split ratio but provides no information about the remaining cellular metabolism, while the 13C-based MFA method permits estimation of multiple fluxes but provides a less accurate estimate of the PPP split ratio. PMID:16820467

A new method of estimating thermal performance of embryonic development rate yields accurate prediction of embryonic age in wild reptile nests.

PubMed

Rollinson, Njal; Holt, Sarah M; Massey, Melanie D; Holt, Richard C; Nancekivell, E Graham; Brooks, Ronald J

2018-05-01

Temperature has a strong effect on ectotherm development rate. It is therefore possible to construct predictive models of development that rely solely on temperature, which have applications in a range of biological fields. Here, we leverage a reference series of development stages for embryos of the turtle Chelydra serpentina, which was described at a constant temperature of 20 °C. The reference series acts to map each distinct developmental stage onto embryonic age (in days) at 20 °C. By extension, an embryo taken from any given incubation environment, once staged, can be assigned an equivalent age at 20 °C. We call this concept "Equivalent Development", as it maps the development stage of an embryo incubated at a given temperature to its equivalent age at a reference temperature. In the laboratory, we used the concept of Equivalent Development to estimate development rate of embryos of C. serpentina across a series of constant temperatures. Using these estimates of development rate, we created a thermal performance curve measured in units of Equivalent Development (TPC ED ). We then used the TPC ED to predict developmental stage of embryos in several natural turtle nests across six years. We found that 85% of the variation of development stage in natural nests could be explained. Further, we compared the predictive accuracy of the model based on the TPC ED to the predictive accuracy of a degree-day model, where development is assumed to be linearly related to temperature and the amount of accumulated heat is summed over time. Information theory suggested that the model based on the TPC ED better describes variation in developmental stage in wild nests than the degree-day model. We suggest the concept of Equivalent Development has several strengths and can be broadly applied. In particular, studies on temperature-dependent sex determination may be facilitated by the concept of Equivalent Development, as development age maps directly onto the

Wheat productivity estimates using LANDSAT data

NASA Technical Reports Server (NTRS)

Nalepka, R. F.; Colwell, J. E. (Principal Investigator); Rice, D. P.; Bresnahan, P. A.

1977-01-01

The author has identified the following significant results. Large area LANDSAT yield estimates were generated. These results were compared with estimates computed using a meteorological yield model (CCEA). Both of these estimates were compared with Kansas Crop and Livestock Reporting Service (KCLRS) estimates of yield, in an attempt to assess the relative and absolute accuracy of the LANDSAT and CCEA estimates. Results were inconclusive. A large area direct wheat prediction procedure was implemented. Initial results have produced a wheat production estimate comparable with the KCLRS estimate.

Global Crop Yields, Climatic Trends and Technology Enhancement

NASA Astrophysics Data System (ADS)

Najafi, E.; Devineni, N.; Khanbilvardi, R.; Kogan, F.

2016-12-01

During the last decades the global agricultural production has soared up and technology enhancement is still making positive contribution to yield growth. However, continuing population, water crisis, deforestation and climate change threaten the global food security. Attempts to predict food availability in the future around the world can be partly understood from the impact of changes to date. A new multilevel model for yield prediction at the country scale using climate covariates and technology trend is presented in this paper. The structural relationships between average yield and climate attributes as well as trends are estimated simultaneously. All countries are modeled in a single multilevel model with partial pooling and/or clustering to automatically group and reduce estimation uncertainties. El Niño Southern Oscillation (ENSO), Palmer Drought Severity Index (PDSI), Geopotential height (GPH), historical CO2 level and time-trend as a relatively reliable approximation of technology measurement are used as predictors to estimate annual agricultural crop yields for each country from 1961 to 2007. Results show that these indicators can explain the variability in historical crop yields for most of the countries and the model performs well under out-of-sample verifications.

Developing accurate survey methods for estimating population sizes and trends of the critically endangered Nihoa Millerbird and Nihoa Finch.

USGS Publications Warehouse

Gorresen, P. Marcos; Camp, Richard J.; Brinck, Kevin W.; Farmer, Chris

2012-01-01

Point-transect surveys indicated that millerbirds were more abundant than shown by the striptransect method, and were estimated at 802 birds in 2010 (95%CI = 652 – 964) and 704 birds in 2011 (95%CI = 579 – 837). Point-transect surveys yielded population estimates with improved precision which will permit trends to be detected in shorter time periods and with greater statistical power than is available from strip-transect survey methods. Mean finch population estimates and associated uncertainty were not markedly different among the three survey methods, but the performance of models used to estimate density and population size are expected to improve as the data from additional surveys are incorporated. Using the pointtransect survey, the mean finch population size was estimated at 2,917 birds in 2010 (95%CI = 2,037 – 3,965) and 2,461 birds in 2011 (95%CI = 1,682 – 3,348). Preliminary testing of the line-transect method in 2011 showed that it would not generate sufficient detections to effectively model bird density, and consequently, relatively precise population size estimates. Both species were fairly evenly distributed across Nihoa and appear to occur in all or nearly all available habitat. The time expended and area traversed by observers was similar among survey methods; however, point-transect surveys do not require that observers walk a straight transect line, thereby allowing them to avoid culturally or biologically sensitive areas and minimize the adverse effects of recurrent travel to any particular area. In general, pointtransect surveys detect more birds than strip-survey methods, thereby improving precision and resulting population size and trend estimation. The method is also better suited for the steep and uneven terrain of Nihoa

Improved patient size estimates for accurate dose calculations in abdomen computed tomography

NASA Astrophysics Data System (ADS)

Lee, Chang-Lae

2017-07-01

The radiation dose of CT (computed tomography) is generally represented by the CTDI (CT dose index). CTDI, however, does not accurately predict the actual patient doses for different human body sizes because it relies on a cylinder-shaped head (diameter : 16 cm) and body (diameter : 32 cm) phantom. The purpose of this study was to eliminate the drawbacks of the conventional CTDI and to provide more accurate radiation dose information. Projection radiographs were obtained from water cylinder phantoms of various sizes, and the sizes of the water cylinder phantoms were calculated and verified using attenuation profiles. The effective diameter was also calculated using the attenuation of the abdominal projection radiographs of 10 patients. When the results of the attenuation-based method and the geometry-based method shown were compared with the results of the reconstructed-axial-CT-image-based method, the effective diameter of the attenuation-based method was found to be similar to the effective diameter of the reconstructed-axial-CT-image-based method, with a difference of less than 3.8%, but the geometry-based method showed a difference of less than 11.4%. This paper proposes a new method of accurately computing the radiation dose of CT based on the patient sizes. This method computes and provides the exact patient dose before the CT scan, and can therefore be effectively used for imaging and dose control.

Estimation of quantum yields of weak fluorescence from eosin Y dimers formed in aqueous solutions.

PubMed

Enoki, Masami; Katoh, Ryuzi

2018-05-17

We studied the weak fluorescence from the dimer of eosin Y (EY) in aqueous solutions. We used a newly developed ultrathin optical cell with a thickness ranging from of the order of microns to several hundreds of microns to successfully measure the fluorescence spectra of highly concentrated aqueous solutions of EY without artifacts caused by the reabsorption of fluorescence. The spectra we obtained were similar to the fluorescence spectrum of the EY monomer; almost no fluorescence was observed from the EY dimer. By a careful comparison of the spectra of solutions at low and high concentrations of EY, we succeeded in extracting the fluorescence spectrum of the EY dimer. The fluorescence quantum yield of the EY dimer was estimated to be 0.005.

Estimating rice yield related traits and quantitative trait loci analysis under different nitrogen treatments using a simple tower-based field phenotyping system with modified single-lens reflex cameras

NASA Astrophysics Data System (ADS)

Naito, Hiroki; Ogawa, Satoshi; Valencia, Milton Orlando; Mohri, Hiroki; Urano, Yutaka; Hosoi, Fumiki; Shimizu, Yo; Chavez, Alba Lucia; Ishitani, Manabu; Selvaraj, Michael Gomez; Omasa, Kenji

2017-03-01

Application of field based high-throughput phenotyping (FB-HTP) methods for monitoring plant performance in real field conditions has a high potential to accelerate the breeding process. In this paper, we discuss the use of a simple tower based remote sensing platform using modified single-lens reflex cameras for phenotyping yield traits in rice under different nitrogen (N) treatments over three years. This tower based phenotyping platform has the advantages of simplicity, ease and stability in terms of introduction, maintenance and continual operation under field conditions. Out of six phenological stages of rice analyzed, the flowering stage was the most useful in the estimation of yield performance under field conditions. We found a high correlation between several vegetation indices (simple ratio (SR), normalized difference vegetation index (NDVI), transformed vegetation index (TVI), corrected transformed vegetation index (CTVI), soil-adjusted vegetation index (SAVI) and modified soil-adjusted vegetation index (MSAVI)) and multiple yield traits (panicle number, grain weight and shoot biomass) across a three trials. Among all of the indices studied, SR exhibited the best performance in regards to the estimation of grain weight (R2 = 0.80). Under our tower-based field phenotyping system (TBFPS), we identified quantitative trait loci (QTL) for yield related traits using a mapping population of chromosome segment substitution lines (CSSLs) and a single nucleotide polymorphism data set. Our findings suggest the TBFPS can be useful for the estimation of yield performance during early crop development. This can be a major opportunity for rice breeders whom desire high throughput phenotypic selection for yield performance traits.

Combined use of Landsat-8 and Sentinel-2A images for winter crop mapping and winter wheat yield assessment at regional scale.

PubMed

Skakun, Sergii; Vermote, Eric; Roger, Jean-Claude; Franch, Belen

2017-01-01

Timely and accurate information on crop yield is critical to many applications within agriculture monitoring. Thanks to its coverage and temporal resolution, coarse spatial resolution satellite imagery has always been a source of valuable information for yield forecasting and assessment at national and regional scales. With availability of free images acquired by Landsat-8 and Sentinel-2 remote sensing satellites, it becomes possible to enable temporal resolution of an image every 3-5 days, and therefore, to develop next generation agriculture products at higher spatial resolution (30 m). This paper explores the combined use of Landsat-8 and Sentinel-2A for winter crop mapping and winter wheat assessment at regional scale. For the former, we adapt a previously developed approach for Moderate Resolution Imaging Spectroradiometer (MODIS) at 250 m resolution that allows automatic mapping of winter crops taking into account knowledge on crop calendar and without ground truth data. For the latter, we use a generalized winter wheat yield model that is based on NDVI-peak estimation and MODIS data, and further downscaled to be applicable at 30 m resolution. We show that integration of Landsat-8 and Sentinel-2A has a positive impact both for winter crop mapping and winter wheat yield assessment. In particular, the error of winter wheat yield estimates can be reduced up to 1.8 times comparing to the single satellite usage.

How accurately can we estimate energetic costs in a marine top predator, the king penguin?

PubMed

Halsey, Lewis G; Fahlman, Andreas; Handrich, Yves; Schmidt, Alexander; Woakes, Anthony J; Butler, Patrick J

2007-01-01

King penguins (Aptenodytes patagonicus) are one of the greatest consumers of marine resources. However, while their influence on the marine ecosystem is likely to be significant, only an accurate knowledge of their energy demands will indicate their true food requirements. Energy consumption has been estimated for many marine species using the heart rate-rate of oxygen consumption (f(H) - V(O2)) technique, and the technique has been applied successfully to answer eco-physiological questions. However, previous studies on the energetics of king penguins, based on developing or applying this technique, have raised a number of issues about the degree of validity of the technique for this species. These include the predictive validity of the present f(H) - V(O2) equations across different seasons and individuals and during different modes of locomotion. In many cases, these issues also apply to other species for which the f(H) - V(O2) technique has been applied. In the present study, the accuracy of three prediction equations for king penguins was investigated based on validity studies and on estimates of V(O2) from published, field f(H) data. The major conclusions from the present study are: (1) in contrast to that for walking, the f(H) - V(O2) relationship for swimming king penguins is not affected by body mass; (2) prediction equation (1), log(V(O2) = -0.279 + 1.24log(f(H) + 0.0237t - 0.0157log(f(H)t, derived in a previous study, is the most suitable equation presently available for estimating V(O2) in king penguins for all locomotory and nutritional states. A number of possible problems associated with producing an f(H) - V(O2) relationship are discussed in the present study. Finally, a statistical method to include easy-to-measure morphometric characteristics, which may improve the accuracy of f(H) - V(O2) prediction equations, is explained.

A proposed method to estimate premorbid full scale intelligence quotient (FSIQ) for the Canadian Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) using demographic and combined estimation procedures.

PubMed

Schoenberg, Mike R; Lange, Rael T; Saklofske, Donald H

2007-11-01

Establishing a comparison standard in neuropsychological assessment is crucial to determining change in function. There is no available method to estimate premorbid intellectual functioning for the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV). The WISC-IV provided normative data for both American and Canadian children aged 6 to 16 years old. This study developed regression algorithms as a proposed method to estimate full-scale intelligence quotient (FSIQ) for the Canadian WISC-IV. Participants were the Canadian WISC-IV standardization sample (n = 1,100). The sample was randomly divided into two groups (development and validation groups). The development group was used to generate regression algorithms; 1 algorithm only included demographics, and 11 combined demographic variables with WISC-IV subtest raw scores. The algorithms accounted for 18% to 70% of the variance in FSIQ (standard error of estimate, SEE = 8.6 to 14.2). Estimated FSIQ significantly correlated with actual FSIQ (r = .30 to .80), and the majority of individual FSIQ estimates were within +/-10 points of actual FSIQ. The demographic-only algorithm was less accurate than algorithms combining demographic variables with subtest raw scores. The current algorithms yielded accurate estimates of current FSIQ for Canadian individuals aged 6-16 years old. The potential application of the algorithms to estimate premorbid FSIQ is reviewed. While promising, clinical validation of the algorithms in a sample of children and/or adolescents with known neurological dysfunction is needed to establish these algorithms as a premorbid estimation procedure.

Skin temperature over the carotid artery provides an accurate noninvasive estimation of core temperature in infants and young children during general anesthesia.

PubMed

Jay, Ollie; Molgat-Seon, Yannick; Chou, Shirley; Murto, Kimmo

2013-12-01

The accurate measurement of core temperature is an essential aspect of intraoperative management in children. Invasive measurement sites are accurate but carry some health risks and cannot be used in certain patients. An accurate form of noninvasive thermometry is therefore needed. Our aim was to develop, and subsequently validate, separate models for estimating core temperature using different skin temperatures with an individualized correction factor. Forty-eight pediatric patients (0-36 months) undergoing elective surgery were separated into a modeling group (MG, n = 28) and validation group (VG, n = 20). Skin temperature was measured over the carotid artery (Tsk_carotid ), upper abdomen (Tsk_abd ), and axilla (Tsk_axilla ), while nasopharyngeal temperature (Tnaso ) was measured as a reference. In the MG, derived models for estimating Tnaso were: Tsk_carotid  + 0.52; Tsk_abd  + (0.076[body mass] + 0.02); and Tsk_axilla  + (0.081[body mass]-0.66). After adjusting raw Tsk_carotid, Tsk_abd , and Tsk_axilla values in the independent VG using these models, the mean bias (Predicted Tnaso - Actual Tnaso [with 95% confidence intervals]) was +0.03[+0.53, -0.50]°C, -0.05[+1.02, -1.07]°C, and -0.06[+1.21, -1.28°C], respectively. The percentage of values within ±0.5°C of Tnaso was 93.2%, 75.4%, and 66.1% for Tsk_carotid, Tsk_abd , and Tsk_axilla , respectively. Sensitivity and specificity for detecting hypothermia (Tnaso  < 36.0°C) was 0.88 and 0.91 for Tsk_carotid , 0.61 and 0.76 for Tsk_abd , and 0.91 and 0.73 for Tsk_axilla . Goodness-of-fit (R(2) ) relative to the line-of-identity was 0.74 (Tsk_carotid ), 0.34 (Tsk_abd ), and 0.15 (Tsk_axilla ). Skin temperature over the carotid artery, with a simple correction factor of +0.52°C, provides a viable noninvasive estimate of Tnaso in young children during elective surgery with a general anesthetic. © 2013 John Wiley & Sons Ltd.

Combined Use of Landsat-8 and Sentinel-2A Images for Winter Crop Mapping and Winter Wheat Yield Assessment at Regional Scale

NASA Technical Reports Server (NTRS)

Skakun, Sergii; Vermote, Eric; Roger, Jean-Claude; Franch, Belen

2017-01-01

Timely and accurate information on crop yield and production is critical to many applications within agriculture monitoring. Thanks to its coverage and temporal resolution, coarse spatial resolution satellite imagery has always been a source of valuable information for yield forecasting and assessment at national and regional scales. With availability of free images acquired by Landsat-8 and Sentinel-2 remote sensing satellites, it becomes possible to provide temporal resolution of an image every 3-5 days, and therefore, to develop next generation agriculture products at higher spatial resolution (10-30 m). This paper explores the combined use of Landsat-8 and Sentinel-2A for winter crop mapping and winter wheat yield assessment at regional scale. For the former, we adapt a previously developed approach for the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument at 250 m resolution that allows automatic mapping of winter crops taking into account a priori knowledge on crop calendar. For the latter, we use a generalized winter wheat yield forecasting model that is based on estimation of the peak Normalized Difference Vegetation Index (NDVI) from MODIS image time-series, and further downscaled to be applicable at 30 m resolution. We show that integration of Landsat-8 and Sentinel-2A improves both winter crop mapping and winter wheat yield assessment. In particular, the error of winter wheat yield estimates can be reduced up to 1.8 times compared to using a single satellite.

The Massachusetts Sustainable-Yield Estimator: A decision-support tool to assess water availability at ungaged stream locations in Massachusetts

USGS Publications Warehouse

Archfield, Stacey A.; Vogel, Richard M.; Steeves, Peter A.; Brandt, Sara L.; Weiskel, Peter K.; Garabedian, Stephen P.

2010-01-01

Federal, State and local water-resource managers require a variety of data and modeling tools to better understand water resources. The U.S. Geological Survey, in cooperation with the Massachusetts Department of Environmental Protection, has developed a statewide, interactive decision-support tool to meet this need. The decision-support tool, referred to as the Massachusetts Sustainable-Yield Estimator (MA SYE) provides screening-level estimates of the sustainable yield of a basin, defined as the difference between the unregulated streamflow and some user-specified quantity of water that must remain in the stream to support such functions as recreational activities or aquatic habitat. The MA SYE tool was designed, in part, because the quantity of surface water available in a basin is a time-varying quantity subject to competing demands for water. To compute sustainable yield, the MA SYE tool estimates a daily time series of unregulated, daily mean streamflow for a 44-year period of record spanning October 1, 1960, through September 30, 2004. Selected streamflow quantiles from an unregulated, daily flow-duration curve are estimated by solving six regression equations that are a function of physical and climate basin characteristics at an ungaged site on a stream of interest. Streamflow is then interpolated between the estimated quantiles to obtain a continuous daily flow-duration curve. A time series of unregulated daily streamflow subsequently is created by transferring the timing of the daily streamflow at a reference streamgage to the ungaged site by equating exceedence probabilities of contemporaneous flow at the two locations. One of 66 reference streamgages is selected by kriging, a geostatistical method, which is used to map the spatial relation among correlations between the time series of the logarithm of daily streamflows at each reference streamgage and the ungaged site. Estimated unregulated, daily mean streamflows show good agreement with observed

Spatial and Temporal Uncertainty of Crop Yield Aggregations

NASA Technical Reports Server (NTRS)

Porwollik, Vera; Mueller, Christoph; Elliott, Joshua; Chryssanthacopoulos, James; Iizumi, Toshichika; Ray, Deepak K.; Ruane, Alex C.; Arneth, Almut; Balkovic, Juraj; Ciais, Philippe;

Light- and water-use efficiency model synergy: a revised look at crop yield estimation for agricultural decision-making

NASA Astrophysics Data System (ADS)

Marshall, M.; Tu, K. P.

2015-12-01

Large-area crop yield models (LACMs) are commonly employed to address climate-driven changes in crop yield and inform policy makers concerned with climate change adaptation. Production efficiency models (PEMs), a class of LACMs that rely on the conservative response of carbon assimilation to incoming solar radiation absorbed by a crop contingent on environmental conditions, have increasingly been used over large areas with remote sensing spectral information to improve the spatial resolution of crop yield estimates and address important data gaps. Here, we present a new PEM that combines model principles from the remote sensing-based crop yield and evapotranspiration (ET) model literature. One of the major limitations of PEMs is that they are evaluated using data restricted in both space and time. To overcome this obstacle, we first validated the model using 2009-2014 eddy covariance flux tower Gross Primary Production data in a rice field in the Central Valley of California- a critical agro-ecosystem of the United States. This evaluation yielded a Willmot's D and mean absolute error of 0.81 and 5.24 g CO2/d, respectively, using CO2, leaf area, temperature, and moisture constraints from the MOD16 ET model, Priestley-Taylor ET model, and the Global Production Efficiency Model (GLOPEM). A Monte Carlo simulation revealed that the model was most sensitive to the Enhanced Vegetation Index (EVI) input, followed by Photosynthetically Active Radiation, vapor pressure deficit, and air temperature. The model will now be evaluated using 30 x 30m (Landsat resolution) biomass transects developed in 2011 and 2012 from spectroradiometric and other non-destructive in situ metrics for several cotton, maize, and rice fields across the Central Valley. Finally, the model will be driven by Daymet and MODIS data over the entire State of California and compared with county-level crop yield statistics. It is anticipated that the new model will facilitate agro-climatic decision-making in

Performance evaluation of ocean color satellite models for deriving accurate chlorophyll estimates in the Gulf of Saint Lawrence

NASA Astrophysics Data System (ADS)

Montes-Hugo, M.; Bouakba, H.; Arnone, R.

2014-06-01

The understanding of phytoplankton dynamics in the Gulf of the Saint Lawrence (GSL) is critical for managing major fisheries off the Canadian East coast. In this study, the accuracy of two atmospheric correction techniques (NASA standard algorithm, SA, and Kuchinke's spectral optimization, KU) and three ocean color inversion models (Carder's empirical for SeaWiFS (Sea-viewing Wide Field-of-View Sensor), EC, Lee's quasi-analytical, QAA, and Garver- Siegel-Maritorena semi-empirical, GSM) for estimating the phytoplankton absorption coefficient at 443 nm (aph(443)) and the chlorophyll concentration (chl) in the GSL is examined. Each model was validated based on SeaWiFS images and shipboard measurements obtained during May of 2000 and April 2001. In general, aph(443) estimates derived from coupling KU and QAA models presented the smallest differences with respect to in situ determinations as measured by High Pressure liquid Chromatography measurements (median absolute bias per cruise up to 0.005, RMSE up to 0.013). A change on the inversion approach used for estimating aph(443) values produced up to 43.4% increase on prediction error as inferred from the median relative bias per cruise. Likewise, the impact of applying different atmospheric correction schemes was secondary and represented an additive error of up to 24.3%. By using SeaDAS (SeaWiFS Data Analysis System) default values for the optical cross section of phytoplankton (i.e., aph(443) = aph(443)/chl = 0.056 m2mg-1), the median relative bias of our chl estimates as derived from the most accurate spaceborne aph(443) retrievals and with respect to in situ determinations increased up to 29%.

Accounting for the decrease of photosystem photochemical efficiency with increasing irradiance to estimate quantum yield of leaf photosynthesis.

PubMed

Yin, Xinyou; Belay, Daniel W; van der Putten, Peter E L; Struik, Paul C

2014-12-01

Maximum quantum yield for leaf CO2 assimilation under limiting light conditions (Φ CO2LL) is commonly estimated as the slope of the linear regression of net photosynthetic rate against absorbed irradiance over a range of low-irradiance conditions. Methodological errors associated with this estimation have often been attributed either to light absorptance by non-photosynthetic pigments or to some data points being beyond the linear range of the irradiance response, both causing an underestimation of Φ CO2LL. We demonstrate here that a decrease in photosystem (PS) photochemical efficiency with increasing irradiance, even at very low levels, is another source of error that causes a systematic underestimation of Φ CO2LL. A model method accounting for this error was developed, and was used to estimate Φ CO2LL from simultaneous measurements of gas exchange and chlorophyll fluorescence on leaves using various combinations of species, CO2, O2, or leaf temperature levels. The conventional linear regression method under-estimated Φ CO2LL by ca. 10-15%. Differences in the estimated Φ CO2LL among measurement conditions were generally accounted for by different levels of photorespiration as described by the Farquhar-von Caemmerer-Berry model. However, our data revealed that the temperature dependence of PSII photochemical efficiency under low light was an additional factor that should be accounted for in the model.

Ground-Water Contributions to Reservoir Storage and the Effect on Estimates of Firm Yield for Reservoirs in Massachusetts

USGS Publications Warehouse

Archfield, Stacey A.; Carlson, Carl S.

2006-01-01

Potential ground-water contributions to reservoir storage were determined for nine reservoirs in Massachusetts that had shorelines in contact with sand and gravel aquifers. The effect of ground water on firm yield was not only substantial, but furthermore, the firm yield of a reservoir in contact with a sand and gravel aquifer was always greater when the ground-water contribution was included in the water balance. Increases in firm yield ranged from 2 to 113 percent, with a median increase in firm yield of 10 percent. Additionally, the increase in firm yield in two reservoirs was greater than 85 percent. This study identified a set of equations that are based on an analytical solution to the ground-water-flow equation for the case of one-dimensional flow in a finite-width aquifer bounded by a linear surface-water feature such as a stream. These equations, which require only five input variables, were incorporated into an existing firm-yield-estimator (FYE) model, and the potential effect of ground water on firm yield was evaluated. To apply the FYE model to a reservoir in Massachusetts, the model requires that the drainage area to the reservoir be clearly defined and that some surface water flows into the reservoir. For surface-water-body shapes having a more realistic representation of a reservoir shoreline than a stream, a comparison of ground-water-flow rates simulated by the ground-water equations with flow rates simulated by a two-dimensional, finite-difference ground-water-flow model indicate that the agreement between the simulated flow rates is within ?10 percent when the ratio of the distance from the reservoir shoreline to the aquifer boundary to the length of shoreline in contact with the aquifer is between values of 0.5 and 3.5. Idealized reservoir-aquifer systems were assumed to verify that the ground-water-flow equations were implemented correctly into the existing FYE model; however, the modified FYE model has not been validated through a comparison

Spectral considerations for modeling yield of canola

USDA-ARS?s Scientific Manuscript database

Conspicuous yellow flowers that are present in a Brassica oilseed crop such as canola require careful consideration when selecting a spectral index for yield estimation. This study evaluated spectral indices for multispectral sensors that correlate with the seed yield of Brassica oilseed crops. A ...

Estimation of suspended-sediment rating curves and mean suspended-sediment loads

USGS Publications Warehouse

Crawford, Charles G.

1991-01-01

A simulation study was done to evaluate: (1) the accuracy and precision of parameter estimates for the bias-corrected, transformed-linear and non-linear models obtained by the method of least squares; (2) the accuracy of mean suspended-sediment loads calculated by the flow-duration, rating-curve method using model parameters obtained by the alternative methods. Parameter estimates obtained by least squares for the bias-corrected, transformed-linear model were considerably more precise than those obtained for the non-linear or weighted non-linear model. The accuracy of parameter estimates obtained for the biascorrected, transformed-linear and weighted non-linear model was similar and was much greater than the accuracy obtained by non-linear least squares. The improved parameter estimates obtained by the biascorrected, transformed-linear or weighted non-linear model yield estimates of mean suspended-sediment load calculated by the flow-duration, rating-curve method that are more accurate and precise than those obtained for the non-linear model.

Toward accurate and valid estimates of greenhouse gas reductions from bikeway projects.

DOT National Transportation Integrated Search

2016-07-31

We sought to accurately and validly model emissions generating and activities, including changes in traveler behavior and thus GHG : emissions in the wake of bikeway projects. We wanted the results to be applicable to practice and policy in Californi...

Estimates of spatial and temporal variation of energy crops biomass yields in the US

NASA Astrophysics Data System (ADS)

Song, Y.; Jain, A. K.; Landuyt, W.; Kheshgi, H. S.

2013-12-01

Perennial grasses, such as switchgrass (Panicum viragatum) and Miscanthus (Miscanthus x giganteus) have been identified for potential use as biomass feedstocks in the US. Current research on perennial grass biomass production has been evaluated on small-scale plots. However, the extent to which this potential can be realized at a landscape-scale will depend on the biophysical potential to grow these grasses with minimum possible amount of land that needs to be diverted from food to fuel production. To assess this potential three questions about the biomass yield for these grasses need to be answered: (1) how the yields for different grasses are varied spatially and temporally across the US; (2) whether the yields are temporally stable or not; and (3) how the spatial and temporal trends in yields of these perennial grasses are controlled by limiting factors, including soil type, water availability, climate, and crop varieties. To answer these questions, the growth processes of the perennial grasses are implemented into a coupled biophysical, physiological and biogeochemical model (ISAM). The model has been applied to quantitatively investigate the spatial and temporal trends in biomass yields for over the period 1980 -2010 in the US. The bioenergy grasses considered in this study include Miscanthus, Cave-in-Rock switchgrass and Alamo switchgrass. The effects of climate, soil and topography on the spatial and temporal trends of biomass yields are quantitatively analyzed using principal component analysis and GIS based geographically weighted regression. The spatial temporal trend results are evaluated further to classify each part of the US into four homogeneous potential yield zones: high and stable yield zone (HS), high but unstable yield zone (HU), low and stable yield zone (LS) and low but unstable yield zone (LU). Our preliminary results indicate that the yields for perennial grasses among different zones are strongly related to the different controlling factors