Generalizing the Network Scale-Up Method: A New Estimator for the Size of Hidden Populations*

PubMed Central

Feehan, Dennis M.; Salganik, Matthew J.

2018-01-01

The network scale-up method enables researchers to estimate the size of hidden populations, such as drug injectors and sex workers, using sampled social network data. The basic scale-up estimator offers advantages over other size estimation techniques, but it depends on problematic modeling assumptions. We propose a new generalized scale-up estimator that can be used in settings with non-random social mixing and imperfect awareness about membership in the hidden population. Further, the new estimator can be used when data are collected via complex sample designs and from incomplete sampling frames. However, the generalized scale-up estimator also requires data from two samples: one from the frame population and one from the hidden population. In some situations these data from the hidden population can be collected by adding a small number of questions to already planned studies. For other situations, we develop interpretable adjustment factors that can be applied to the basic scale-up estimator. We conclude with practical recommendations for the design and analysis of future studies. PMID:29375167

Uncertainties in scaling factors for ab initio vibrational zero-point energies

NASA Astrophysics Data System (ADS)

Irikura, Karl K.; Johnson, Russell D.; Kacker, Raghu N.; Kessel, Rüdiger

2009-03-01

Vibrational zero-point energies (ZPEs) determined from ab initio calculations are often scaled by empirical factors. An empirical scaling factor partially compensates for the effects arising from vibrational anharmonicity and incomplete treatment of electron correlation. These effects are not random but are systematic. We report scaling factors for 32 combinations of theory and basis set, intended for predicting ZPEs from computed harmonic frequencies. An empirical scaling factor carries uncertainty. We quantify and report, for the first time, the uncertainties associated with scaling factors for ZPE. The uncertainties are larger than generally acknowledged; the scaling factors have only two significant digits. For example, the scaling factor for B3LYP/6-31G(d) is 0.9757±0.0224 (standard uncertainty). The uncertainties in the scaling factors lead to corresponding uncertainties in predicted ZPEs. The proposed method for quantifying the uncertainties associated with scaling factors is based upon the Guide to the Expression of Uncertainty in Measurement, published by the International Organization for Standardization. We also present a new reference set of 60 diatomic and 15 polyatomic "experimental" ZPEs that includes estimated uncertainties.

Predicting groundwater recharge for varying land cover and climate conditions - a global meta-study

NASA Astrophysics Data System (ADS)

Mohan, Chinchu; Western, Andrew W.; Wei, Yongping; Saft, Margarita

2018-05-01

Groundwater recharge is one of the important factors determining the groundwater development potential of an area. Even though recharge plays a key role in controlling groundwater system dynamics, much uncertainty remains regarding the relationships between groundwater recharge and its governing factors at a large scale. Therefore, this study aims to identify the most influential factors of groundwater recharge, and to develop an empirical model to estimate diffuse rainfall recharge at a global scale. Recharge estimates reported in the literature from various parts of the world (715 sites) were compiled and used in model building and testing exercises. Unlike conventional recharge estimates from water balance, this study used a multimodel inference approach and information theory to explain the relationship between groundwater recharge and influential factors, and to predict groundwater recharge at 0.5° resolution. The results show that meteorological factors (precipitation and potential evapotranspiration) and vegetation factors (land use and land cover) had the most predictive power for recharge. According to the model, long-term global average annual recharge (1981-2014) was 134 mm yr-1 with a prediction error ranging from -8 to 10 mm yr-1 for 97.2 % of cases. The recharge estimates presented in this study are unique and more reliable than the existing global groundwater recharge estimates because of the extensive validation carried out using both independent local estimates collated from the literature and national statistics from the Food and Agriculture Organization (FAO). In a water-scarce future driven by increased anthropogenic development, the results from this study will aid in making informed decisions about groundwater potential at a large scale.

Developing Multidimensional Likert Scales Using Item Factor Analysis: The Case of Four-Point Items

ERIC Educational Resources Information Center

Asún, Rodrigo A.; Rdz-Navarro, Karina; Alvarado, Jesús M.

2016-01-01

This study compares the performance of two approaches in analysing four-point Likert rating scales with a factorial model: the classical factor analysis (FA) and the item factor analysis (IFA). For FA, maximum likelihood and weighted least squares estimations using Pearson correlation matrices among items are compared. For IFA, diagonally weighted…

Development and Validation of a Coping with Discrimination Scale: Factor Structure, Reliability, and Validity

ERIC Educational Resources Information Center

Wei, Meifen; Alvarez, Alvin N.; Ku, Tsun-Yao; Russell, Daniel W.; Bonett, Douglas G.

2010-01-01

Four studies were conducted to develop and validate the Coping With Discrimination Scale (CDS). In Study 1, an exploratory factor analysis (N = 328) identified 5 factors: Education/Advocacy, Internalization, Drug and Alcohol Use, Resistance, and Detachment, with internal consistency reliability estimates ranging from 0.72 to 0.90. In Study 2, a…

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

Greenberg, Jim; Penuelas, J.; Guenther, Alex B.

To survey landscape-scale fluxes of biogenic gases, a100-meterTeflon tube was attached to a tethered balloon as a sampling inlet for a fast response Proton Transfer Reaction Mass Spectrometer (PTRMS). Along with meteorological instruments deployed on the tethered balloon and at 3-mand outputs from a regional weather model, these observations were used to estimate landscape scale biogenic volatile organic compound fluxes with two micrometeorological techniques: mixed layer variance and surface layer gradients. This highly mobile sampling system was deployed at four field sites near Barcelona to estimate landscape-scale BVOC emission factors in a relatively short period (3 weeks). The two micrometeorologicalmore » techniques agreed within the uncertainty of the flux measurements at all four sites even though the locations had considerable heterogeneity in species distribution and complex terrain. The observed fluxes were significantly different than emissions predicted with an emission model using site-specific emission factors and land-cover characteristics. Considering the wide range in reported BVOC emission factors of VOCs for individual vegetation species (more than an order of magnitude), this flux estimation technique is useful for constraining BVOC emission factors used as model inputs.« less

Linear Parameter Varying Control for Actuator Failure

NASA Technical Reports Server (NTRS)

Shin, Jong-Yeob; Wu, N. Eva; Belcastro, Christine; Bushnell, Dennis M. (Technical Monitor)

2002-01-01

A robust linear parameter varying (LPV) control synthesis is carried out for an HiMAT vehicle subject to loss of control effectiveness. The scheduling parameter is selected to be a function of the estimates of the control effectiveness factors. The estimates are provided on-line by a two-stage Kalman estimator. The inherent conservatism of the LPV design is reducing through the use of a scaling factor on the uncertainty block that represents the estimation errors of the effectiveness factors. Simulations of the controlled system with the on-line estimator show that a superior fault-tolerance can be achieved.

Trophic Scaling and Occupancy Analysis Reveals a Lion Population Limited by Top-Down Anthropogenic Pressure in the Limpopo National Park, Mozambique

PubMed Central

Everatt, Kristoffer T.; Andresen, Leah; Somers, Michael J.

2014-01-01

The African lion (Panthera Leo) has suffered drastic population and range declines over the last few decades and is listed by the IUCN as vulnerable to extinction. Conservation management requires reliable population estimates, however these data are lacking for many of the continent's remaining populations. It is possible to estimate lion abundance using a trophic scaling approach. However, such inferences assume that a predator population is subject only to bottom-up regulation, and are thus likely to produce biased estimates in systems experiencing top-down anthropogenic pressures. Here we provide baseline data on the status of lions in a developing National Park in Mozambique that is impacted by humans and livestock. We compare a direct density estimate with an estimate derived from trophic scaling. We then use replicated detection/non-detection surveys to estimate the proportion of area occupied by lions, and hierarchical ranking of covariates to provide inferences on the relative contribution of prey resources and anthropogenic factors influencing lion occurrence. The direct density estimate was less than 1/3 of the estimate derived from prey resources (0.99 lions/100 km2 vs. 3.05 lions/100 km2). The proportion of area occupied by lions was Ψ = 0.439 (SE = 0.121), or approximately 44% of a 2 400 km2 sample of potential habitat. Although lions were strongly predicted by a greater probability of encountering prey resources, the greatest contributing factor to lion occurrence was a strong negative association with settlements. Finally, our empirical abundance estimate is approximately 1/3 of a published abundance estimate derived from opinion surveys. Altogether, our results describe a lion population held below resource-based carrying capacity by anthropogenic factors and highlight the limitations of trophic scaling and opinion surveys for estimating predator populations exposed to anthropogenic pressures. Our study provides the first empirical quantification of a population that future change can be measured against. PMID:24914934

Trophic scaling and occupancy analysis reveals a lion population limited by top-down anthropogenic pressure in the Limpopo National Park, Mozambique.

PubMed

Everatt, Kristoffer T; Andresen, Leah; Somers, Michael J

2014-01-01

The African lion (Panthera Leo) has suffered drastic population and range declines over the last few decades and is listed by the IUCN as vulnerable to extinction. Conservation management requires reliable population estimates, however these data are lacking for many of the continent's remaining populations. It is possible to estimate lion abundance using a trophic scaling approach. However, such inferences assume that a predator population is subject only to bottom-up regulation, and are thus likely to produce biased estimates in systems experiencing top-down anthropogenic pressures. Here we provide baseline data on the status of lions in a developing National Park in Mozambique that is impacted by humans and livestock. We compare a direct density estimate with an estimate derived from trophic scaling. We then use replicated detection/non-detection surveys to estimate the proportion of area occupied by lions, and hierarchical ranking of covariates to provide inferences on the relative contribution of prey resources and anthropogenic factors influencing lion occurrence. The direct density estimate was less than 1/3 of the estimate derived from prey resources (0.99 lions/100 km² vs. 3.05 lions/100 km²). The proportion of area occupied by lions was Ψ = 0.439 (SE = 0.121), or approximately 44% of a 2,400 km2 sample of potential habitat. Although lions were strongly predicted by a greater probability of encountering prey resources, the greatest contributing factor to lion occurrence was a strong negative association with settlements. Finally, our empirical abundance estimate is approximately 1/3 of a published abundance estimate derived from opinion surveys. Altogether, our results describe a lion population held below resource-based carrying capacity by anthropogenic factors and highlight the limitations of trophic scaling and opinion surveys for estimating predator populations exposed to anthropogenic pressures. Our study provides the first empirical quantification of a population that future change can be measured against.

Adaptation and psychometric assessment of the Hebrew version of the Recovery Promoting Relationships Scale (RPRS).

PubMed

Moran, Galia S; Zisman-Ilani, Yaara; Garber-Epstein, Paula; Roe, David

2014-03-01

Recovery is supported by relationships that are characterized by human centeredness, empowerment and a hopeful approach. The Recovery Promoting Relationships Scale (RPRS; Russinova, Rogers, & Ellison, 2006) assesses consumer-provider relationships from the consumer perspective. Here we present the adaptation and psychometric assessment of a Hebrew version of the RPRS. The RPRS was translated to Hebrew (RPRS-Heb) using multiple strategies to assure conceptual soundness. Then 216 mental health consumers were administered the RPRS-Heb as part of a larger project initiative implementing illness management and recovery intervention (IMR) in community settings. Psychometric testing included assessment of the factor structure, reliability, and validity using the Hope Scale, the Working Alliance Inventory, and the Recovery Assessment Scale. The RPRS-Heb factor structure replicated the two factor structures found in the original scale with minor exceptions. Reliability estimates were good: Cronbach's alpha for the total scale was 0.94. An estimate of 0.93 for the Recovery-Promoting Strategies factor, and 0.86 for the Core Relationship. Concurrent validity was confirmed using the Working Alliance Scale (rp = .51, p < .001) and the Hope Scale (rp = .43, p < .001). Criterion validity was examined using the Recovery Assessment Scale (rp = .355, p < .05). The study yielded a 23-item RPRS-Heb version with a psychometrically sound factor structure, satisfactory reliability, and concurrent validity tested against the Hope, Alliance, and Recovery Assessment scales. Outcomes are discussed in the context of the original scale properties and a similar Dutch initiative. The RPRS-Heb can serve as a valuable tool for studying recovery promoting relationships with Hebrew speaking population.

Women's Self-Estimates of Competence and the Resolution of the Career/Home Conflict.

ERIC Educational Resources Information Center

Stake, Jayne E.

1979-01-01

Relationships among women's role factors, self-estimates of competence, and career commitment were investigated. Female business students and alumnae completed the Attitudes toward Women Scale, the Performance-Self-Esteem Scale (PSES), and questions regarding home and career choices. As predicted, PSES scores were related to extent of career…

Plane-dependent ML scatter scaling: 3D extension of the 2D simulated single scatter (SSS) estimate.

PubMed

Rezaei, Ahmadreza; Salvo, Koen; Vahle, Thomas; Panin, Vladimir; Casey, Michael; Boada, Fernando; Defrise, Michel; Nuyts, Johan

2017-07-24

Scatter correction is typically done using a simulation of the single scatter, which is then scaled to account for multiple scatters and other possible model mismatches. This scaling factor is determined by fitting the simulated scatter sinogram to the measured sinogram, using only counts measured along LORs that do not intersect the patient body, i.e. 'scatter-tails'. Extending previous work, we propose to scale the scatter with a plane dependent factor, which is determined as an additional unknown in the maximum likelihood (ML) reconstructions, using counts in the entire sinogram rather than only the 'scatter-tails'. The ML-scaled scatter estimates are validated using a Monte-Carlo simulation of a NEMA-like phantom, a phantom scan with typical contrast ratios of a 68 Ga-PSMA scan, and 23 whole-body 18 F-FDG patient scans. On average, we observe a 12.2% change in the total amount of tracer activity of the MLEM reconstructions of our whole-body patient database when the proposed ML scatter scales are used. Furthermore, reconstructions using the ML-scaled scatter estimates are found to eliminate the typical 'halo' artifacts that are often observed in the vicinity of high focal uptake regions.

Changes in photochemically significant solar UV spectral irradiance as estimated by the composite Mg II index and scale factors

NASA Technical Reports Server (NTRS)

Deland, Matthew T.; Cebula, Richard P.

1994-01-01

Quantitative assessment of the impact of solar ultraviolet irradiance variations on stratospheric ozone abundances currently requires the use of proxy indicators. The Mg II core-to-wing index has been developed as an indicator of solar UV activity between 175-400 nm that is independent of most instrument artifacts, and measures solar variability on both rotational and solar cycle time scales. Linear regression fits have been used to merge the individual Mg II index data sets from the Nimbus-7, NOAA-9, and NOAA-11 instruments onto a single reference scale. The change in 27-dayrunning average of the composite Mg II index from solar maximum to solar minimum is approximately 8 percent for solar cycle 21, and approximately 9 percent for solar cycle 22 through January 1992. Scaling factors based on the short-term variations in the Mg II index and solar irradiance data sets have been developed to estimate solar variability at mid-UV and near-UV wavelengths. Near 205 nm, where solar irradiance variations are important for stratospheric photo-chemistry and dynamics, the estimated change in irradiance during solar cycle 22 is approximately 10 percent using the composite Mg II index and scale factors.

Thermospheric density estimation from SLR observations of LEO satellites - A case study with the ANDE-Pollux satellite

NASA Astrophysics Data System (ADS)

Blossfeld, M.; Schmidt, M.; Erdogan, E.

2016-12-01

The thermospheric neutral density plays a crucial role within the equation of motion of Earth orbiting objects since drag, lift or side forces are one of the largest non-gravitational perturbations acting on the satellite. Precise Orbit Determination (POD) methods can be used to estimate thermospheric density variations from measured orbit determinations. One method which provides highly accurate measurements of the satellite position is Satellite Laser Ranging (SLR). Within the POD process, scaling factors are estimated frequently. These scaling factors can be either used for the scaling of the so called satellite-specific drag (ballistic) coefficients or the integrated thermospheric neutral density. We present a method for analytically model the drag coefficient based on a couple of physical assumptions and key parameters. In this paper, we investigate the possibility to use SLR observations to the very low Earth orbiting satellite ANDE-Pollux (approximately at 350km altitude) to determine scaling factors for different a priori thermospheric density models. We perform a POD for ANDE-Pollux covering 49 days between August 2009 and September 2009 which means the time span containing the largest number of observations during the short lifetime of the satellite. Finally, we compare the obtained scaled thermospheric densities w.r.t. each other

Family strengths and the Kansas Marital Satisfaction Scale: a factor analytic study.

PubMed

Schumm, W R; Bollman, S R; Jurich, A P; Hatch, R C

2001-06-01

20 new items were developed to measure six concepts of family strengths and were administered, along with the Kansas Marital Satisfaction Scale, to over 266 married subjects as part of a larger survey of current and former members of the Christian Church (Disciples of Christ). A common factor analysis suggested that most of the items were associated with their expected factors, while reliability analyses indicated that most of the scales had acceptable estimates of internal consistency. The marital satisfaction items clearly were associated with their own factor and not other factors, providing support for the unidimensional nature of the Kansas Marital Satisfaction Scale and for its construct validity.

Formation factor in Bentheimer and Fontainebleau sandstones: Theory compared with pore-scale numerical simulations

NASA Astrophysics Data System (ADS)

Ghanbarian, Behzad; Berg, Carl F.

2017-09-01

Accurate quantification of formation resistivity factor F (also called formation factor) provides useful insight into connectivity and pore space topology in fully saturated porous media. In particular the formation factor has been extensively used to estimate permeability in reservoir rocks. One of the widely applied models to estimate F is Archie's law (F = ϕ- m in which ϕ is total porosity and m is cementation exponent) that is known to be valid in rocks with negligible clay content, such as clean sandstones. In this study we compare formation factors determined by percolation and effective-medium theories as well as Archie's law with numerical simulations of electrical resistivity on digital rock models. These digital models represent Bentheimer and Fontainebleau sandstones and are derived either by reconstruction or directly from micro-tomographic images. Results show that the universal quadratic power law from percolation theory accurately estimates the calculated formation factor values in network models over the entire range of porosity. However, it crosses over to the linear scaling from the effective-medium approximation at the porosity of 0.75 in grid models. We also show that the effect of critical porosity, disregarded in Archie's law, is nontrivial, and the Archie model inaccurately estimates the formation factor in low-porosity homogeneous sandstones.

Parallel interference cancellation for CDMA applications

NASA Technical Reports Server (NTRS)

Divsalar, Dariush (Inventor); Simon, Marvin K. (Inventor); Raphaeli, Dan (Inventor)

1997-01-01

The present invention provides a method of decoding a spread spectrum composite signal, the composite signal comprising plural user signals that have been spread with plural respective codes, wherein each coded signal is despread, averaged to produce a signal value, analyzed to produce a tentative decision, respread, summed with other respread signals to produce combined interference signals, the method comprising scaling the combined interference signals with a weighting factor to produce a scaled combined interference signal, scaling the composite signal with the weighting factor to produce a scaled composite signal, scaling the signal value by the complement of the weighting factor to produce a leakage signal, combining the scaled composite signal, the scaled combined interference signal and the leakage signal to produce an estimate of a respective user signal.

Factor Analytic Validation of the Ford, Wolvin, and Chung Listening Competence Scale

ERIC Educational Resources Information Center

Mickelson, William T.; Welch, S. A.

2012-01-01

This research begins to independently and quantitatively validate the Ford, Wolvin, and Chung (2000) Listening Competency Scale. Reliability and Confirmatory Factor analyses were conducted on two independent samples. The reliability estimates were found to be below those reported by Ford, Wolvin, and Chung (2000) and below acceptable levels for…

Estimation of Crop Gross Primary Production (GPP). 2; Do Scaled (MODIS) Vegetation Indices Improve Performance?

NASA Technical Reports Server (NTRS)

Zhang, Qingyuan; Cheng, Yen-Ben; Lyapustin, Alexei I.; Wang, Yujie; Zhang, Xiaoyang; Suyker, Andrew; Verma, Shashi; Shuai, Yanmin; Middleton, Elizabeth M.

2015-01-01

Satellite remote sensing estimates of Gross Primary Production (GPP) have routinely been made using spectral Vegetation Indices (VIs) over the past two decades. The Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), the green band Wide Dynamic Range Vegetation Index (WDRVIgreen), and the green band Chlorophyll Index (CIgreen) have been employed to estimate GPP under the assumption that GPP is proportional to the product of VI and photosynthetically active radiation (PAR) (where VI is one of four VIs: NDVI, EVI, WDRVIgreen, or CIgreen). However, the empirical regressions between VI*PAR and GPP measured locally at flux towers do not pass through the origin (i.e., the zero X-Y value for regressions). Therefore they are somewhat difficult to interpret and apply. This study investigates (1) what are the scaling factors and offsets (i.e., regression slopes and intercepts) between the fraction of PAR absorbed by chlorophyll of a canopy (fAPARchl) and the VIs, and (2) whether the scaled VIs developed in (1) can eliminate the deficiency and improve the accuracy of GPP estimates. Three AmeriFlux maize and soybean fields were selected for this study, two of which are irrigated and one is rainfed. The four VIs and fAPARchl of the fields were computed with the MODerate resolution Imaging Spectroradiometer (MODIS) satellite images. The GPP estimation performance for the scaled VIs was compared to results obtained with the original VIs and evaluated with standard statistics: the coefficient of determination (R2), the root mean square error (RMSE), and the coefficient of variation (CV). Overall, the scaled EVI obtained the best performance. The performance of the scaled NDVI, EVI and WDRVIgreen was improved across sites, crop types and soil/background wetness conditions. The scaled CIgreen did not improve results, compared to the original CIgreen. The scaled green band indices (WDRVIgreen, CIgreen) did not exhibit superior performance to either the scaled EVI or NDVI in estimating crop daily GPP at these agricultural fields. The scaled VIs are more physiologically meaningful than original un-scaled VIs, but scaling factors and offsets may vary across crop types and surface conditions.

Principal axes estimation using the vibration modes of physics-based deformable models.

PubMed

Krinidis, Stelios; Chatzis, Vassilios

2008-06-01

This paper addresses the issue of accurate, effective, computationally efficient, fast, and fully automated 2-D object orientation and scaling factor estimation. The object orientation is calculated using object principal axes estimation. The approach relies on the object's frequency-based features. The frequency-based features used by the proposed technique are extracted by a 2-D physics-based deformable model that parameterizes the objects shape. The method was evaluated on synthetic and real images. The experimental results demonstrate the accuracy of the method, both in orientation and the scaling estimations.

Scaling Property of Period-n-Tupling Sequences in One-Dimensional Mappings

NASA Astrophysics Data System (ADS)

Zeng, Wan-Zhen; Hao, Bai-Lin; Wang, Guang-Rui; Chen, Shi-Gang

1984-05-01

We calculated the universal scaling function g(x) and the scaling factor α as well as the convergence rate δ for periodtripling, -quadrapling and-quintupling sequences of RL, RL^2, RLR^2, RL2 R and RL^3 types. The superstable periods are closely connected to a set of polynomial P_n defined recursively by the original mapping. Some notable properties of these polynomials are studied. Several approaches to solving the renormalization group equation and estimating the scaling factors are suggested.

Plane-dependent ML scatter scaling: 3D extension of the 2D simulated single scatter (SSS) estimate

NASA Astrophysics Data System (ADS)

Rezaei, Ahmadreza; Salvo, Koen; Vahle, Thomas; Panin, Vladimir; Casey, Michael; Boada, Fernando; Defrise, Michel; Nuyts, Johan

2017-08-01

Scatter correction is typically done using a simulation of the single scatter, which is then scaled to account for multiple scatters and other possible model mismatches. This scaling factor is determined by fitting the simulated scatter sinogram to the measured sinogram, using only counts measured along LORs that do not intersect the patient body, i.e. ‘scatter-tails’. Extending previous work, we propose to scale the scatter with a plane dependent factor, which is determined as an additional unknown in the maximum likelihood (ML) reconstructions, using counts in the entire sinogram rather than only the ‘scatter-tails’. The ML-scaled scatter estimates are validated using a Monte-Carlo simulation of a NEMA-like phantom, a phantom scan with typical contrast ratios of a 68Ga-PSMA scan, and 23 whole-body 18F-FDG patient scans. On average, we observe a 12.2% change in the total amount of tracer activity of the MLEM reconstructions of our whole-body patient database when the proposed ML scatter scales are used. Furthermore, reconstructions using the ML-scaled scatter estimates are found to eliminate the typical ‘halo’ artifacts that are often observed in the vicinity of high focal uptake regions.

The factor structure of the Social Interaction Anxiety Scale and the Social Phobia Scale.

PubMed

Heidenreich, Thomas; Schermelleh-Engel, Karin; Schramm, Elisabeth; Hofmann, Stefan G; Stangier, Ulrich

2011-05-01

The Social Interaction Anxiety Scale (SIAS) and the Social Phobia Scale (SPS) are two compendium measures that have become some of the most popular self-report scales of social anxiety. Despite their popularity, it remains unclear whether it is necessary to maintain two separate scales of social anxiety. The primary objective of the present study was to examine the factor analytic structure of both measures to determine the factorial validity of each scale. For this purpose, we administered both scales to 577 patients at the beginning of outpatient treatment. Analyzing both scales simultaneously, a CFA with two correlated factors showed a better fit to the data than a single factor model. An additional EFA with an oblique rotation on all 40 items using the WLSMV estimator further supported the two factor solution. These results suggest that the SIAS and SPS measure similar, but not identical facets of social anxiety. Thus, our findings provide support to retain the SIAS and SPS as two separate scales. Copyright © 2011 Elsevier Ltd. All rights reserved.

Impact of the galactic acceleration on the terrestrial reference frame and the scale factor in VLBI

NASA Astrophysics Data System (ADS)

Krásná, Hana; Titov, Oleg

2017-04-01

The relative motion of the solar system barycentre around the galactic centre can also be described as an acceleration of the solar system directed towards the centre of the Galaxy. So far, this effect has been omitted in the a priori modelling of the Very Long Baseline Interferometry (VLBI) observable. Therefore, it results in a systematic dipole proper motion (Secular Aberration Drift, SAD) of extragalactic radio sources building the celestial reference frame with a theoretical maximum magnitude of 5-7 microarcsec/year. In this work, we present our estimation of the SAD vector obtained within a global adjustment of the VLBI measurements (1979.0 - 2016.5) using the software VieVS. We focus on the influence of the observed radio sources with the maximum SAD effect on the terrestrial reference frame. We show that the scale factor from the VLBI measurements estimated for each source individually discloses a clear systematic aligned with the direction to the Galactic centre-anticentre. Therefore, the radio sources located near Galactic anticentre may cause a strong systematic effect, especially, in early VLBI years. For instance, radio source 0552+398 causes a difference up to 1 mm in the estimated baseline length. Furthermore, we discuss the scale factor estimated for each radio source after removal of the SAD systematic.

Hurst Estimation of Scale Invariant Processes with Stationary Increments and Piecewise Linear Drift

NASA Astrophysics Data System (ADS)

Modarresi, N.; Rezakhah, S.

The characteristic feature of the discrete scale invariant (DSI) processes is the invariance of their finite dimensional distributions by dilation for certain scaling factor. DSI process with piecewise linear drift and stationary increments inside prescribed scale intervals is introduced and studied. To identify the structure of the process, first, we determine the scale intervals, their linear drifts and eliminate them. Then, a new method for the estimation of the Hurst parameter of such DSI processes is presented and applied to some period of the Dow Jones indices. This method is based on fixed number equally spaced samples inside successive scale intervals. We also present some efficient method for estimating Hurst parameter of self-similar processes with stationary increments. We compare the performance of this method with the celebrated FA, DFA and DMA on the simulated data of fractional Brownian motion (fBm).

Validation of the Adolescent Concerns Measure (ACM): evidence from exploratory and confirmatory factor analysis.

PubMed

Ang, Rebecca P; Chong, Wan Har; Huan, Vivien S; Yeo, Lay See

2007-01-01

This article reports the development and initial validation of scores obtained from the Adolescent Concerns Measure (ACM), a scale which assesses concerns of Asian adolescent students. In Study 1, findings from exploratory factor analysis using 619 adolescents suggested a 24-item scale with four correlated factors--Family Concerns (9 items), Peer Concerns (5 items), Personal Concerns (6 items), and School Concerns (4 items). Initial estimates of convergent validity for ACM scores were also reported. The four-factor structure of ACM scores derived from Study 1 was confirmed via confirmatory factor analysis in Study 2 using a two-fold cross-validation procedure with a separate sample of 811 adolescents. Support was found for both the multidimensional and hierarchical models of adolescent concerns using the ACM. Internal consistency and test-retest reliability estimates were adequate for research purposes. ACM scores show promise as a reliable and potentially valid measure of Asian adolescents' concerns.

Zero-Point Calibration for AGN Black-Hole Mass Estimates

NASA Technical Reports Server (NTRS)

Peterson, B. M.; Onken, C. A.

2004-01-01

We discuss the measurement and associated uncertainties of AGN reverberation-based black-hole masses, since these provide the zero-point calibration for scaling relationships that allow black-hole mass estimates for quasars. We find that reverberation-based mass estimates appear to be accurate to within a factor of about 3.

Psychometric properties of the brief version of the Fear of Negative Evaluation Scale in a Turkish sample.

PubMed

Koydemir, Selda; Demir, Ayhan

2007-06-01

The purpose of the study was to report initial data on the psychometric properties of the Brief Fear of Negative Evaluation Scale. The scale was applied to a nonclinical sample of 250 (137 women, 113 men) Turkish undergraduate students selected randomly from Middle East Technical University. Their mean age was 20.4 yr. (SD= 1.9). The factor structure of the Turkish version, its criterion validity, and internal reliability coefficients were assessed. Although maximum likelihood factor analysis initially indicated that the scale had only one factor, a forced two-factor solution accounted for more variance (61%) in scale scores than a single factor. The straightforward items loaded on the first factor, and the reverse-coded items loaded on the second factor. The total score was significantly positively correlated with scores on the Revised Cheek and Buss Shyness Scale and significantly negatively correlated with scores on the Rosenberg Self-Esteem Scale. Factor 1 (straightforward items) correlated more highly with both Shyness and Self-esteem than Factor 2 (reverse-coded items). Internal consistency estimate was .94 for the Total scores, .91 for the Factor 1 (straightforward items), and .87 for the Factor 2 (reverse-coded items). No sex differences were evident for Fear of Negative Evaluation.

Factor structure and internal consistency of the Greek version of the Flow State Scale.

PubMed

Doganis, G; Iosifidou, P; Vlachopoulos, S

2000-12-01

The present study tested the internal consistency and the factor struc ture of a translated version of the Flow State Scale with Greek sport participants. Sport psychology literature is not conclusive regarding sex differences and the type of sport in flow. The sample was comprised of 144 women from interactive sports (volleyball and handball) who were drawn from the second division of the first national category. Athletes completed the scale immediately after a game. Values of Cronbach alpha were used to estimate the internal consistency of the scale and confirmatory factor analysis to examine the model. The results showed acceptable psychometric prop erties of the scale and suggest a need for improvement of the problematic items.

NMR permeability estimators in 'chalk' carbonate rocks obtained under different relaxation times and MICP size scalings

NASA Astrophysics Data System (ADS)

Rios, Edmilson Helton; Figueiredo, Irineu; Moss, Adam Keith; Pritchard, Timothy Neil; Glassborow, Brent Anthony; Guedes Domingues, Ana Beatriz; Bagueira de Vasconcellos Azeredo, Rodrigo

2016-07-01

The effect of the selection of different nuclear magnetic resonance (NMR) relaxation times for permeability estimation is investigated for a set of fully brine-saturated rocks acquired from Cretaceous carbonate reservoirs in the North Sea and Middle East. Estimators that are obtained from the relaxation times based on the Pythagorean means are compared with estimators that are obtained from the relaxation times based on the concept of a cumulative saturation cut-off. Select portions of the longitudinal (T1) and transverse (T2) relaxation-time distributions are systematically evaluated by applying various cut-offs, analogous to the Winland-Pittman approach for mercury injection capillary pressure (MICP) curves. Finally, different approaches to matching the NMR and MICP distributions using different mean-based scaling factors are validated based on the performance of the related size-scaled estimators. The good results that were obtained demonstrate possible alternatives to the commonly adopted logarithmic mean estimator and reinforce the importance of NMR-MICP integration to improving carbonate permeability estimates.

Deriving Scaling Factors Using a Global Hydrological Model to Restore GRACE Total Water Storage Changes for China's Yangtze River Basin

NASA Technical Reports Server (NTRS)

Long, Di; Yang, Yuting; Yoshihide, Wada; Hong, Yang; Liang, Wei; Chen, Yaning; Yong, Bin; Hou, Aizhong; Wei, Jiangfeng; Chen, Lu

2015-01-01

This study used a global hydrological model (GHM), PCR-GLOBWB, which simulates surface water storage changes, natural and human induced groundwater storage changes, and the interactions between surface water and subsurface water, to generate scaling factors by mimicking low-pass filtering of GRACE signals. Signal losses in GRACE data were subsequently restored by the scaling factors from PCR-GLOBWB. Results indicate greater spatial heterogeneity in scaling factor from PCR-GLOBWB and CLM4.0 than that from GLDAS-1 Noah due to comprehensive simulation of surface and subsurface water storage changes for PCR-GLOBWB and CLM4.0. Filtered GRACE total water storage (TWS) changes applied with PCR-GLOBWB scaling factors show closer agreement with water budget estimates of TWS changes than those with scaling factors from other land surface models (LSMs) in China's Yangtze River basin. Results of this study develop a further understanding of the behavior of scaling factors from different LSMs or GHMs over hydrologically complex basins, and could be valuable in providing more accurate TWS changes for hydrological applications (e.g., monitoring drought and groundwater storage depletion) over regions where human-induced interactions between surface water and subsurface water are intensive.

Item response theory analysis of the Utrecht Work Engagement Scale for Students (UWES-S) using a sample of Japanese university and college students majoring medical science, nursing, and natural science.

PubMed

Tsubakita, Takashi; Shimazaki, Kazuyo; Ito, Hiroshi; Kawazoe, Nobuo

2017-10-30

The Utrecht Work Engagement Scale for Students has been used internationally to assess students' academic engagement, but it has not been analyzed via item response theory. The purpose of this study was to conduct an item response theory analysis of the Japanese version of the Utrecht Work Engagement Scale for Students translated by authors. Using a two-parameter model and Samejima's graded response model, difficulty and discrimination parameters were estimated after confirming the factor structure of the scale. The 14 items on the scale were analyzed with a sample of 3214 university and college students majoring medical science, nursing, or natural science in Japan. The preliminary parameter estimation was conducted with the two parameter model, and indicated that three items should be removed because there were outlier parameters. Final parameter estimation was conducted using the survived 11 items, and indicated that all difficulty and discrimination parameters were acceptable. The test information curve suggested that the scale better assesses higher engagement than average engagement. The estimated parameters provide a basis for future comparative studies. The results also suggested that a 7-point Likert scale is too broad; thus, the scaling should be modified to fewer graded scaling structure.

Using Multilevel Factor Analysis with Clustered Data: Investigating the Factor Structure of the Positive Values Scale

ERIC Educational Resources Information Center

Huang, Francis L.; Cornell, Dewey G.

2016-01-01

Advances in multilevel modeling techniques now make it possible to investigate the psychometric properties of instruments using clustered data. Factor models that overlook the clustering effect can lead to underestimated standard errors, incorrect parameter estimates, and model fit indices. In addition, factor structures may differ depending on…

The Spanish version of the Emotional Labour Scale (ELS): a validation study.

PubMed

Picardo, Juan M; López-Fernández, Consuelo; Hervás, María José Abellán

2013-10-01

To validate the Spanish version of the Emotional Labour Scale (ELS), an instrument widely used to understand how professionals working with people face emotional labor in their daily job. An observational, cross-sectional and multicenter survey was used. Nursing students and their clinical tutors (n=211) completed the self-reported ELS when the clinical practice period was over. First order and second order Confirmatory Factor Analyses (CFA) were estimated in order to test the factor structure of the scale. The results of the CFA confirm a factor structure of the scale with six first order factors (duration, frequency, intensity, variety, surface acting and deep acting) and two larger second order factors named Demands (duration, frequency, intensity and variety) and Acting (surface acting and deep acting) establishing the validity of the Spanish version of the ELS. Copyright © 2012 Elsevier Ltd. All rights reserved.

Identifying forest patterns from space to explore dynamics across the circumpolar boreal

NASA Astrophysics Data System (ADS)

Montesano, P. M.; Neigh, C. S. R.; Feng, M.; Channan, S.; Sexton, J. O.; Wagner, W.; Wooten, M.; Poulter, B.; Wang, L.

2017-12-01

A variety of forest patterns are the result of interactions between broad-scale climate and local-scale site factors and history across the northernmost portion of the circumpolar boreal. Patterns of forest extent, height, and cover help describe forest structure transitions that influence future and reflect past dynamics. Coarse spaceborne observations lack structural detail at forest transitions, which inhibits understanding of these dynamics. We highlight: (1) the use of sub-meter spaceborne stereogrammetry for deriving structure estimates in boreal forests; (2) its potential to complement other spaceborne estimates of forest structure at critical scales; and (3) the potential of these sub-meter and other Landsat-derived structure estimates for improving understanding of broad-scale boreal dynamics such as carbon flux and albedo, capturing the spatial variability of the boreal-tundra biome boundary, and assessing its potential for change.

On the predictivity of pore-scale simulations: Estimating uncertainties with multilevel Monte Carlo

NASA Astrophysics Data System (ADS)

Icardi, Matteo; Boccardo, Gianluca; Tempone, Raúl

2016-09-01

A fast method with tunable accuracy is proposed to estimate errors and uncertainties in pore-scale and Digital Rock Physics (DRP) problems. The overall predictivity of these studies can be, in fact, hindered by many factors including sample heterogeneity, computational and imaging limitations, model inadequacy and not perfectly known physical parameters. The typical objective of pore-scale studies is the estimation of macroscopic effective parameters such as permeability, effective diffusivity and hydrodynamic dispersion. However, these are often non-deterministic quantities (i.e., results obtained for specific pore-scale sample and setup are not totally reproducible by another ;equivalent; sample and setup). The stochastic nature can arise due to the multi-scale heterogeneity, the computational and experimental limitations in considering large samples, and the complexity of the physical models. These approximations, in fact, introduce an error that, being dependent on a large number of complex factors, can be modeled as random. We propose a general simulation tool, based on multilevel Monte Carlo, that can reduce drastically the computational cost needed for computing accurate statistics of effective parameters and other quantities of interest, under any of these random errors. This is, to our knowledge, the first attempt to include Uncertainty Quantification (UQ) in pore-scale physics and simulation. The method can also provide estimates of the discretization error and it is tested on three-dimensional transport problems in heterogeneous materials, where the sampling procedure is done by generation algorithms able to reproduce realistic consolidated and unconsolidated random sphere and ellipsoid packings and arrangements. A totally automatic workflow is developed in an open-source code [1], that include rigid body physics and random packing algorithms, unstructured mesh discretization, finite volume solvers, extrapolation and post-processing techniques. The proposed method can be efficiently used in many porous media applications for problems such as stochastic homogenization/upscaling, propagation of uncertainty from microscopic fluid and rock properties to macro-scale parameters, robust estimation of Representative Elementary Volume size for arbitrary physics.

Estimation of the emission factors of PAHs by traffic with the model of atmospheric dispersion and deposition from heavy traffic road.

PubMed

Ozaki, N; Tokumitsu, H; Kojima, K; Kindaichi, T

2007-01-01

In order to consider the total atmospheric loadings of the PAHs (polycyclic aromatic hydrocarbons) from traffic activities, the emission factors of PAHs were estimated and from the obtained emission factors and vehicle transportation statistics, total atmospheric loadings were integrated and the loadings into the water body were estimated on a regional scale. The atmospheric concentration of PAHs was measured at the roadside of a road with heavy traffic in the Hiroshima area in Japan. The samplings were conducted in summer and winter. Atmospheric particulate matters (fine particle, 0.6-7 microm; coarse particle, over 7 microm) and their PAH concentration were measured. Also, four major emission sources (gasoline and diesel vehicle emissions, tire and asphalt debris) were assumed for vehicle transportation activities, the chemical mass balance method was applied and the source partitioning at the roadside was estimated. Furthermore, the dispersion of atmospheric particles from the vehicles was modelled and the emission factors of the sources were determined by the comparison to the chemical mass balance results. Based on emission factors derived from the modelling, an atmospheric dispersion model of nationwide scale (National Institute of Advanced Industrial Science and Technology - Atmospheric Dispersion Model for Exposure and Risk assessment) was applied, and the atmospheric concentration and loading to the ground were calculated for the Hiroshima Bay watershed area.

The Depression Anxiety Stress Scales-21 (DASS-21): further examination of dimensions, scale reliability, and correlates.

PubMed

Osman, Augustine; Wong, Jane L; Bagge, Courtney L; Freedenthal, Stacey; Gutierrez, Peter M; Lozano, Gregorio

2012-12-01

We conducted two studies to examine the dimensions, internal consistency reliability estimates, and potential correlates of the Depression Anxiety Stress Scales-21 (DASS-21; Lovibond & Lovibond, 1995). Participants in Study 1 included 887 undergraduate students (363 men and 524 women, aged 18 to 35 years; mean [M] age = 19.46, standard deviation [SD] = 2.17) recruited from two public universities to assess the specificity of the individual DASS-21 items and to evaluate estimates of internal consistency reliability. Participants in a follow-up study (Study 2) included 410 students (168 men and 242 women, aged 18 to 47 years; M age = 19.65, SD = 2.88) recruited from the same universities to further assess factorial validity and to evaluate potential correlates of the original DASS-21 total and scale scores. Item bifactor and confirmatory factor analyses revealed that a general factor accounted for the greatest proportion of common variance in the DASS-21 item scores (Study 1). In Study 2, the fit statistics showed good fit for the bifactor model. In addition, the DASS-21 total scale score correlated more highly with scores on a measure of mixed depression and anxiety than with scores on the proposed specific scales of depression or anxiety. Coefficient omega estimates for the DASS-21 scale scores were good. Further investigations of the bifactor structure and psychometric properties of the DASS-21, specifically its incremental and discriminant validity, using known clinical groups are needed. © 2012 Wiley Periodicals, Inc.

22 CFR 211.9 - Liability for loss damage or improper distribution of commodities.

Code of Federal Regulations, 2010 CFR

2010-04-01

... cargo; (B) Report on discharging method (including whether a scale was used, its type and calibration and other factors affecting its accuracy, or an explanation of why a scale was not used and how weight... customs; (D) Provide actual or estimated (if scales not used) quantity of cargo lost during discharge and...

Modeling annual mallard production in the prairie-parkland region

USGS Publications Warehouse

Miller, M.W.

2000-01-01

Biologists have proposed several environmental factors that might influence production of mallards (Anas platyrhynchos) nesting in the prairie-parkland region of the United States and Canada. These factors include precipitation, cold spring temperatures, wetland abundance, and upland breeding habitat. I used long-term historical data sets of climate, wetland numbers, agricultural land use, and size of breeding mallard populations in multiple regression analyses to model annual indices of mallard production. Models were constructed at 2 scales: a continental scale that encompassed most of the mid-continental breeding range of mallards and a stratum-level scale that included 23 portions of that same breeding range. The production index at the continental scale was the estimated age ratio of mid-continental mallards in early fall; at the stratum scale my production index was the estimated number of broods of all duck species within an aerial survey stratum. Size of breeding mallard populations in May, and pond numbers in May and July, best modeled production at the continental scale. Variables that best modeled production at the stratum scale differed by region. Crop variables tended to appear more in models for western Canadian strata; pond variables predominated in models for United States strata; and spring temperature and pond variables dominated models for eastern Canadian strata. An index of cold spring temperatures appeared in 4 of 6 models for aspen parkland strata, and in only 1 of 11 models for strata dominated by prairie. Stratum-level models suggest that regional factors influencing mallard production are not evident at a larger scale. Testing these potential factors in a manipulative fashion would improve our understanding of mallard population dynamics, improving our ability to manage the mid-continental mallard population.

On estimating the basin-scale ocean circulation from satellite altimetry. Part 1: Straightforward spherical harmonic expansion

NASA Technical Reports Server (NTRS)

Tai, Chang-Kou

1988-01-01

Direct estimation of the absolute dynamic topography from satellite altimetry has been confined to the largest scales (basically the basin-scale) owing to the fact that the signal-to-noise ratio is more unfavorable everywhere else. But even for the largest scales, the results are contaminated by the orbit error and geoid uncertainties. Recently a more accurate Earth gravity model (GEM-T1) became available, providing the opportunity to examine the whole question of direct estimation under a more critical limelight. It is found that our knowledge of the Earth's gravity field has indeed improved a great deal. However, it is not yet possible to claim definitively that our knowledge of the ocean circulation has improved through direct estimation. Yet, the improvement in the gravity model has come to the point that it is no longer possible to attribute the discrepancy at the basin scales between altimetric and hydrographic results as mostly due to geoid uncertainties. A substantial part of the difference must be due to other factors; i.e., the orbit error, or the uncertainty of the hydrographically derived dynamic topography.

Cost-effective sampling of ¹³⁷Cs-derived net soil redistribution: part 1--estimating the spatial mean across scales of variation.

PubMed

Li, Y; Chappell, A; Nyamdavaa, B; Yu, H; Davaasuren, D; Zoljargal, K

2015-03-01

The (137)Cs technique for estimating net time-integrated soil redistribution is valuable for understanding the factors controlling soil redistribution by all processes. The literature on this technique is dominated by studies of individual fields and describes its typically time-consuming nature. We contend that the community making these studies has inappropriately assumed that many (137)Cs measurements are required and hence estimates of net soil redistribution can only be made at the field scale. Here, we support future studies of (137)Cs-derived net soil redistribution to apply their often limited resources across scales of variation (field, catchment, region etc.) without compromising the quality of the estimates at any scale. We describe a hybrid, design-based and model-based, stratified random sampling design with composites to estimate the sampling variance and a cost model for fieldwork and laboratory measurements. Geostatistical mapping of net (1954-2012) soil redistribution as a case study on the Chinese Loess Plateau is compared with estimates for several other sampling designs popular in the literature. We demonstrate the cost-effectiveness of the hybrid design for spatial estimation of net soil redistribution. To demonstrate the limitations of current sampling approaches to cut across scales of variation, we extrapolate our estimate of net soil redistribution across the region, show that for the same resources, estimates from many fields could have been provided and would elucidate the cause of differences within and between regional estimates. We recommend that future studies evaluate carefully the sampling design to consider the opportunity to investigate (137)Cs-derived net soil redistribution across scales of variation. Copyright © 2014 Elsevier Ltd. All rights reserved.

Structural validity of the Wechsler Intelligence Scale for Children-Fifth Edition: Confirmatory factor analyses with the 16 primary and secondary subtests.

PubMed

Canivez, Gary L; Watkins, Marley W; Dombrowski, Stefan C

2017-04-01

The factor structure of the Wechsler Intelligence Scale for Children-Fifth Edition (WISC-V; Wechsler, 2014a) standardization sample (N = 2,200) was examined using confirmatory factor analyses (CFA) with maximum likelihood estimation for all reported models from the WISC-V Technical and Interpretation Manual (Wechsler, 2014b). Additionally, alternative bifactor models were examined and variance estimates and model-based reliability estimates (ω coefficients) were provided. Results from analyses of the 16 primary and secondary WISC-V subtests found that all higher-order CFA models with 5 group factors (VC, VS, FR, WM, and PS) produced model specification errors where the Fluid Reasoning factor produced negative variance and were thus judged inadequate. Of the 16 models tested, the bifactor model containing 4 group factors (VC, PR, WM, and PS) produced the best fit. Results from analyses of the 10 primary WISC-V subtests also found the bifactor model with 4 group factors (VC, PR, WM, and PS) produced the best fit. Variance estimates from both 16 and 10 subtest based bifactor models found dominance of general intelligence (g) in accounting for subtest variance (except for PS subtests) and large ω-hierarchical coefficients supporting general intelligence interpretation. The small portions of variance uniquely captured by the 4 group factors and low ω-hierarchical subscale coefficients likely render the group factors of questionable interpretive value independent of g (except perhaps for PS). Present CFA results confirm the EFA results reported by Canivez, Watkins, and Dombrowski (2015); Dombrowski, Canivez, Watkins, and Beaujean (2015); and Canivez, Dombrowski, and Watkins (2015). (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Gravity gradient preprocessing at the GOCE HPF

NASA Astrophysics Data System (ADS)

Bouman, J.; Rispens, S.; Gruber, T.; Schrama, E.; Visser, P.; Tscherning, C. C.; Veicherts, M.

2009-04-01

One of the products derived from the GOCE observations are the gravity gradients. These gravity gradients are provided in the Gradiometer Reference Frame (GRF) and are calibrated in-flight using satellite shaking and star sensor data. In order to use these gravity gradients for application in Earth sciences and gravity field analysis, additional pre-processing needs to be done, including corrections for temporal gravity field signals to isolate the static gravity field part, screening for outliers, calibration by comparison with existing external gravity field information and error assessment. The temporal gravity gradient corrections consist of tidal and non-tidal corrections. These are all generally below the gravity gradient error level, which is predicted to show a 1/f behaviour for low frequencies. In the outlier detection the 1/f error is compensated for by subtracting a local median from the data, while the data error is assessed using the median absolute deviation. The local median acts as a high-pass filter and it is robust as is the median absolute deviation. Three different methods have been implemented for the calibration of the gravity gradients. All three methods use a high-pass filter to compensate for the 1/f gravity gradient error. The baseline method uses state-of-the-art global gravity field models and the most accurate results are obtained if star sensor misalignments are estimated along with the calibration parameters. A second calibration method uses GOCE GPS data to estimate a low degree gravity field model as well as gravity gradient scale factors. Both methods allow to estimate gravity gradient scale factors down to the 10-3 level. The third calibration method uses high accurate terrestrial gravity data in selected regions to validate the gravity gradient scale factors, focussing on the measurement band. Gravity gradient scale factors may be estimated down to the 10-2 level with this method.

Preprocessing of gravity gradients at the GOCE high-level processing facility

NASA Astrophysics Data System (ADS)

Bouman, Johannes; Rispens, Sietse; Gruber, Thomas; Koop, Radboud; Schrama, Ernst; Visser, Pieter; Tscherning, Carl Christian; Veicherts, Martin

2009-07-01

One of the products derived from the gravity field and steady-state ocean circulation explorer (GOCE) observations are the gravity gradients. These gravity gradients are provided in the gradiometer reference frame (GRF) and are calibrated in-flight using satellite shaking and star sensor data. To use these gravity gradients for application in Earth scienes and gravity field analysis, additional preprocessing needs to be done, including corrections for temporal gravity field signals to isolate the static gravity field part, screening for outliers, calibration by comparison with existing external gravity field information and error assessment. The temporal gravity gradient corrections consist of tidal and nontidal corrections. These are all generally below the gravity gradient error level, which is predicted to show a 1/ f behaviour for low frequencies. In the outlier detection, the 1/ f error is compensated for by subtracting a local median from the data, while the data error is assessed using the median absolute deviation. The local median acts as a high-pass filter and it is robust as is the median absolute deviation. Three different methods have been implemented for the calibration of the gravity gradients. All three methods use a high-pass filter to compensate for the 1/ f gravity gradient error. The baseline method uses state-of-the-art global gravity field models and the most accurate results are obtained if star sensor misalignments are estimated along with the calibration parameters. A second calibration method uses GOCE GPS data to estimate a low-degree gravity field model as well as gravity gradient scale factors. Both methods allow to estimate gravity gradient scale factors down to the 10-3 level. The third calibration method uses high accurate terrestrial gravity data in selected regions to validate the gravity gradient scale factors, focussing on the measurement band. Gravity gradient scale factors may be estimated down to the 10-2 level with this method.

Ability Self-Estimates and Self-Efficacy: Meaningfully Distinct?

ERIC Educational Resources Information Center

Bubany, Shawn T.; Hansen, Jo-Ida C.

2010-01-01

Conceptual differences between self-efficacy and ability self-estimate scores, used in vocational psychology and career counseling, were examined with confirmatory factor analysis, discriminate relations, and reliability analysis. Results suggest that empirical differences may be due to measurement error or scale content, rather than due to the…

Estimating prevalence of coronary heart disease for small areas using collateral indicators of morbidity.

PubMed

Congdon, Peter

2010-01-01

Different indicators of morbidity for chronic disease may not necessarily be available at a disaggregated spatial scale (e.g., for small areas with populations under 10 thousand). Instead certain indicators may only be available at a more highly aggregated spatial scale; for example, deaths may be recorded for small areas, but disease prevalence only at a considerably higher spatial scale. Nevertheless prevalence estimates at small area level are important for assessing health need. An instance is provided by England where deaths and hospital admissions for coronary heart disease are available for small areas known as wards, but prevalence is only available for relatively large health authority areas. To estimate CHD prevalence at small area level in such a situation, a shared random effect method is proposed that pools information regarding spatial morbidity contrasts over different indicators (deaths, hospitalizations, prevalence). The shared random effect approach also incorporates differences between small areas in known risk factors (e.g., income, ethnic structure). A Poisson-multinomial equivalence may be used to ensure small area prevalence estimates sum to the known higher area total. An illustration is provided by data for London using hospital admissions and CHD deaths at ward level, together with CHD prevalence totals for considerably larger local health authority areas. The shared random effect involved a spatially correlated common factor, that accounts for clustering in latent risk factors, and also provides a summary measure of small area CHD morbidity.

Estimating Prevalence of Coronary Heart Disease for Small Areas Using Collateral Indicators of Morbidity

PubMed Central

Congdon, Peter

2010-01-01

Different indicators of morbidity for chronic disease may not necessarily be available at a disaggregated spatial scale (e.g., for small areas with populations under 10 thousand). Instead certain indicators may only be available at a more highly aggregated spatial scale; for example, deaths may be recorded for small areas, but disease prevalence only at a considerably higher spatial scale. Nevertheless prevalence estimates at small area level are important for assessing health need. An instance is provided by England where deaths and hospital admissions for coronary heart disease are available for small areas known as wards, but prevalence is only available for relatively large health authority areas. To estimate CHD prevalence at small area level in such a situation, a shared random effect method is proposed that pools information regarding spatial morbidity contrasts over different indicators (deaths, hospitalizations, prevalence). The shared random effect approach also incorporates differences between small areas in known risk factors (e.g., income, ethnic structure). A Poisson-multinomial equivalence may be used to ensure small area prevalence estimates sum to the known higher area total. An illustration is provided by data for London using hospital admissions and CHD deaths at ward level, together with CHD prevalence totals for considerably larger local health authority areas. The shared random effect involved a spatially correlated common factor, that accounts for clustering in latent risk factors, and also provides a summary measure of small area CHD morbidity. PMID:20195439

Multidimensional Structure of the Hypomanic Personality Scale

ERIC Educational Resources Information Center

Schalet, Benjamin D.; Durbin, C. Emily; Revelle, William

2011-01-01

The structure of the Hypomanic Personality Scale was explored in a sample of young adults (N = 884); resulting structures were validated on subsamples with measures of personality traits, internalizing symptoms, and externalizing behaviors. Hierarchical cluster analysis and estimates of general factor saturation suggested the presence of a weak…

An analysis of scientific self-efficacy as a benefit of summer research participation for underrepresented minorities in science, technology, engineering, and mathematics (STEM) fields

NASA Astrophysics Data System (ADS)

Carter, Frances D.

2011-12-01

Low participation and performance in science, technology, engineering, and mathematics (STEM) fields by U.S. citizens are widely recognized as major problems with substantial economic, political, and social ramifications. Studies of collegiate interventions designed to broaden participation in STEM fields suggest that participation in undergraduate research is a key program component that enhances such student outcomes as undergraduate GPA, graduation, persistence in a STEM major, and graduate school enrollment. However, little is known about the mechanisms that are responsible for these positive effects. The current study hypothesizes that undergraduate research participation increases scientific self-efficacy and scientific research proficiency. This hypothesis was tested using data obtained from a survey of minority students from several STEM intervention programs that offer undergraduate research opportunities. Students were surveyed both prior to and following the summer of 2010. Factor analysis was used to examine the factor structure of participants' responses on scientific self-efficacy and scientific research proficiency scales. Difference-in-difference analysis was then applied to the resulting factor score differences to estimate the relationship of summer research participation with scientific self-efficacy and scientific research proficiency. Factor analytic results replicate and further validate previous findings of a general scientific self-efficacy construct (Schultz, 2008). While the factor analytic results for the exploratory scientific research proficiency scale suggest that it was also a measureable construct, the factor structure was not generalizable over time. Potential reasons for the lack of generalizability validity for the scientific research proficiency scale are explored and recommendations for emerging scales are provided. Recent restructuring attempts within federal science agencies threaten the future of STEM intervention programs. Causal estimates of the effect of undergraduate research participation on specific and measurable benefits can play an important role in ensuring the sustainability of STEM intervention programs. Obtaining such estimates requires additional studies that, inter alia, incorporate adequate sample sizes, valid measurement scales, and the ability to account for unobserved variables. Political strategies, such as compromise, can also play an important role in ensuring the sustainability of STEM intervention programs.

Item Factor Analysis: Current Approaches and Future Directions

ERIC Educational Resources Information Center

Wirth, R. J.; Edwards, Michael C.

2007-01-01

The rationale underlying factor analysis applies to continuous and categorical variables alike; however, the models and estimation methods for continuous (i.e., interval or ratio scale) data are not appropriate for item-level data that are categorical in nature. The authors provide a targeted review and synthesis of the item factor analysis (IFA)…

Validation of the Child Premorbid Intelligence Estimate method to predict premorbid Wechsler Intelligence Scale for Children-Fourth Edition Full Scale IQ among children with brain injury.

PubMed

Schoenberg, Mike R; Lange, Rael T; Saklofske, Donald H; Suarez, Mariann; Brickell, Tracey A

2008-12-01

Determination of neuropsychological impairment involves contrasting obtained performances with a comparison standard, which is often an estimate of premorbid IQ. M. R. Schoenberg, R. T. Lange, T. A. Brickell, and D. H. Saklofske (2007) proposed the Child Premorbid Intelligence Estimate (CPIE) to predict premorbid Full Scale IQ (FSIQ) using the Wechsler Intelligence Scale for Children-4th Edition (WISC-IV; Wechsler, 2003). The CPIE includes 12 algorithms to predict FSIQ, 1 using demographic variables and 11 algorithms combining WISC-IV subtest raw scores with demographic variables. The CPIE was applied to a sample of children with acquired traumatic brain injury (TBI sample; n = 40) and a healthy demographically matched sample (n = 40). Paired-samples t tests found estimated premorbid FSIQ differed from obtained FSIQ when applied to the TBI sample (ps .02). The demographic only algorithm performed well at a group level, but estimates were restricted in range. Algorithms combining single subtest scores with demographics performed adequately. Results support the clinical application of the CPIE algorithms. However, limitations to estimating individual premorbid ability, including statistical and developmental factors, must be considered. (c) 2008 APA, all rights reserved.

Some Comments on Mapping from Disease-Specific to Generic Health-Related Quality-of-Life Scales

PubMed Central

Palta, Mari

2013-01-01

An article by Lu et al. in this issue of Value in Health addresses the mapping of treatment or group differences in disease-specific measures (DSMs) of health-related quality of life onto differences in generic health-related quality-of-life scores, with special emphasis on how the mapping is affected by the reliability of the DSM. In the proposed mapping, a factor analytic model defines a conversion factor between the scores as the ratio of factor loadings. Hence, the mapping applies to convert true underlying scales and has desirable properties facilitating the alignment of instruments and understanding their relationship in a coherent manner. It is important to note, however, that when DSM means or differences in mean DSMs are estimated, their mapping is still of a measurement error–prone predictor, and the correct conversion coefficient is the true mapping multiplied by the reliability of the DSM in the relevant sample. In addition, the proposed strategy for estimating the factor analytic mapping in practice requires assumptions that may not hold. We discuss these assumptions and how they may be the reason we obtain disparate estimates of the mapping factor in an application of the proposed methods to groups of patients. PMID:23337233

Factor structure and reliability of the childhood trauma questionnaire and prevalence estimates of trauma for male and female street youth.

PubMed

Forde, David R; Baron, Stephen W; Scher, Christine D; Stein, Murray B

2012-01-01

This study examines the psychometric properties of the Childhood Trauma Questionnaire short form (CTQ-SF) with street youth who have run away or been expelled from their homes (N = 397). Internal reliability coefficients for the five clinical scales ranged from .65 to .95. Confirmatory Factor Analysis (CFA) was used to test the five-factor structure of the scales yielding acceptable fit for the total sample. Additional multigroup analyses were performed to consider items by gender. Results provided only evidence of weak factorial invariance. Constrained models showed invariance in configuration, factor loadings, and factor covariances but failed for equality of intercepts. Mean trauma scores for street youth tended to fall in the moderate to severe range on all abuse/neglect clinical scales. Females reported higher levels of abuse and neglect. Prevalence of child maltreatment of individual forms was very high with 98% of street youth reporting one or more forms; 27.4% of males and 48.9% of females reported all five forms. Results of this study support the viability of the CTQ-SF for screening maltreatment in a highly vulnerable street population. Caution is recommended when comparing prevalence estimates for male and female street youth given the failure of the strong factorial multigroup model.

Modeling Environmental Controls on Tree Water Use at Different Temporal scales

NASA Astrophysics Data System (ADS)

Guan, H.; Wang, H.; Simmons, C. T.

2014-12-01

Vegetation covers 70% of land surface, significantly influencing water and carbon exchange between land surface and the atmosphere. Vegetation transpiration (Et) contributes 80% of the global terrestrial evapotranspiration, making an adequate illustration of how important vegetation is to any hydrological or climatological applications. Transpiration can be estimated through upscaling from sap flow measurements on selected trees. Alternatively, transpiration (or tree water use for forests) can be correlated with environmental variables or estimated in land surface simulations in which a canopy conductance (gc) model is often used. Transpiration and canopy conductance are constrained by supply and demand control factors. Some previous studies estimated Et and gc considering the stresses from both the supply (soil water condition) and demand (e.g. temperature, vapor pressure deficit, solar radiation) factors, while some only considered the demand controls. In this study, we examined the performance of two types of models at daily and half-hourly scales for transpiration and canopy conductance modelling based on a native species in South Australia. The results show that the significance of soil water condition for Et and gc modelling varies with time scales. The model parameter values also vary across time scales. This result calls for attention in choosing models and parameter values for soil-plant-atmosphere continuum and land surface modeling.

Immediately modifiable risk factors attributable to colorectal cancer in Malaysia.

PubMed

Naing, Cho; Lai, Pei Kuan; Mak, Joon Wah

2017-08-04

This study aimed to estimate potential reductions in case incidence of colorectal cancer attributable to the modifiable risk factors such as alcohol consumption, overweight and physical inactivity amongst the Malaysian population. Gender specific population-attributable fractions (PAFs) for colorectal cancer in Malaysia were estimated for the three selected risk factors (physical inactivity, overweight, and alcohol consumptions). Exposure prevalence were sourced from a large-scale national representative survey. Risk estimates of the relationship between the exposure of interest and colorectal cancer were obtained from published meta-analyses. The overall PAF was then estimated, using the 2013 national cancer incidence data from the Malaysian Cancer Registry. Overall, the mean incidence rate for colorectal cancer in Malaysia from 2008 to 2013 was 21.3 per 100,000 population, with the mean age of 61.6 years (±12.7) and the majority were men (56.6%). Amongst 369 colorectal cancer cases in 2013, 40 cases (20 men, 20 women), 10 cases (9 men, 1 woman) or 20 cases (16 men,4 women) would be prevented, if they had done physical exercises, could reduce their body weight to normal level or avoided alcohol consumption, assuming that these factors are causally related to colorectal cancer. It was estimated that 66 (17.8%;66/369) colorectal cancer cases (42 men, 24 women) who had all these three risk factors for the last 10 years would have been prevented, if they could control these three risk factors through effective preventive measures. Findings suggest that approximately 18% of colorectal cancer cases in Malaysia would be prevented through appropriate preventive measures such as doing regular physical exercises, reducing their body weight to normal level and avoiding alcohol consumption, if these factors are causally related to colorectal cancer. Scaling-up nationwide public health campaigns tailored to increase physical activity, controlling body weight within normal limits and avoid alcohol intake are recommended. Future studies with other site-specific cancers and additional risk factors are needed.

Simulation study of geometric shape factor approach to estimating earth emitted flux densities from wide field-of-view radiation measurements

NASA Technical Reports Server (NTRS)

Weaver, W. L.; Green, R. N.

1980-01-01

A study was performed on the use of geometric shape factors to estimate earth-emitted flux densities from radiation measurements with wide field-of-view flat-plate radiometers on satellites. Sets of simulated irradiance measurements were computed for unrestricted and restricted field-of-view detectors. In these simulations, the earth radiation field was modeled using data from Nimbus 2 and 3. Geometric shape factors were derived and applied to these data to estimate flux densities on global and zonal scales. For measurements at a satellite altitude of 600 km, estimates of zonal flux density were in error 1.0 to 1.2%, and global flux density errors were less than 0.2%. Estimates with unrestricted field-of-view detectors were about the same for Lambertian and non-Lambertian radiation models, but were affected by satellite altitude. The opposite was found for the restricted field-of-view detectors.

Coherence in quantum estimation

NASA Astrophysics Data System (ADS)

Giorda, Paolo; Allegra, Michele

2018-01-01

The geometry of quantum states provides a unifying framework for estimation processes based on quantum probes, and it establishes the ultimate bounds of the achievable precision. We show a relation between the statistical distance between infinitesimally close quantum states and the second order variation of the coherence of the optimal measurement basis with respect to the state of the probe. In quantum phase estimation protocols, this leads to propose coherence as the relevant resource that one has to engineer and control to optimize the estimation precision. Furthermore, the main object of the theory i.e. the symmetric logarithmic derivative, in many cases allows one to identify a proper factorization of the whole Hilbert space in two subsystems. The factorization allows one to discuss the role of coherence versus correlations in estimation protocols; to show how certain estimation processes can be completely or effectively described within a single-qubit subsystem; and to derive lower bounds for the scaling of the estimation precision with the number of probes used. We illustrate how the framework works for both noiseless and noisy estimation procedures, in particular those based on multi-qubit GHZ-states. Finally we succinctly analyze estimation protocols based on zero-temperature critical behavior. We identify the coherence that is at the heart of their efficiency, and we show how it exhibits the non-analyticities and scaling behavior proper of a large class of quantum phase transitions.

Global analysis of approaches for deriving total water storage changes from GRACE satellites and implications for groundwater storage change estimation

NASA Astrophysics Data System (ADS)

Long, D.; Scanlon, B. R.; Longuevergne, L.; Chen, X.

2015-12-01

Increasing interest in use of GRACE satellites and a variety of new products to monitor changes in total water storage (TWS) underscores the need to assess the reliability of output from different products. The objective of this study was to assess skills and uncertainties of different approaches for processing GRACE data to restore signal losses caused by spatial filtering based on analysis of 1°×1° grid scale data and basin scale data in 60 river basins globally. Results indicate that scaling factors from six land surface models (LSMs), including four models from GLDAS-1 (Noah 2.7, Mosaic, VIC, and CLM 2.0), CLM 4.0, and WGHM, are similar over most humid, sub-humid, and high-latitude regions but can differ by up to 100% over arid and semi-arid basins and areas with intensive irrigation. Large differences in TWS anomalies from three processing approaches (scaling factor, additive, and multiplicative corrections) were found in arid and semi-arid regions, areas with intensive irrigation, and relatively small basins (e.g., ≤ 200,000 km2). Furthermore, TWS anomaly products from gridded data with CLM4.0 scaling factors and the additive correction approach more closely agree with WGHM output than the multiplicative correction approach. Estimation of groundwater storage changes using GRACE satellites requires caution in selecting an appropriate approach for restoring TWS changes. A priori ground-based data used in forward modeling can provide a powerful tool for explaining the distribution of signal gains or losses caused by low-pass filtering in specific regions of interest and should be very useful for more reliable estimation of groundwater storage changes using GRACE satellites.

Measuring leader perceptions of school readiness for reforms: use of an iterative model combining classical and Rasch methods.

PubMed

Chatterji, Madhabi

2002-01-01

This study examines validity of data generated by the School Readiness for Reforms: Leader Questionnaire (SRR-LQ) using an iterative procedure that combines classical and Rasch rating scale analysis. Following content-validation and pilot-testing, principal axis factor extraction and promax rotation of factors yielded a five factor structure consistent with the content-validated subscales of the original instrument. Factors were identified based on inspection of pattern and structure coefficients. The rotated factor pattern, inter-factor correlations, convergent validity coefficients, and Cronbach's alpha reliability estimates supported the hypothesized construct properties. To further examine unidimensionality and efficacy of the rating scale structures, item-level data from each factor-defined subscale were subjected to analysis with the Rasch rating scale model. Data-to-model fit statistics and separation reliability for items and persons met acceptable criteria. Rating scale results suggested consistency of expected and observed step difficulties in rating categories, and correspondence of step calibrations with increases in the underlying variables. The combined approach yielded more comprehensive diagnostic information on the quality of the five SRR-LQ subscales; further research is continuing.

Psychometric Properties of the Death Anxiety Scale-Extended among Patients with End-Stage Renal Disease.

PubMed

Sharif Nia, Hamid; Pahlevan Sharif, Saeed; Koocher, Gerald P; Yaghoobzadeh, Ameneh; Haghdoost, Ali Akbar; Mar Win, Ma Thin; Soleimani, Mohammad Ali

2017-01-01

This study aimed to evaluate the validity and reliability of the Persian version of Death Anxiety Scale-Extended (DAS-E). A total of 507 patients with end-stage renal disease completed the DAS-E. The factor structure of the scale was evaluated using exploratory factor analysis with an oblique rotation and confirmatory factor analysis. The content and construct validity of the DAS-E were assessed. Average variance extracted, maximum shared squared variance, and average shared squared variance were estimated to assess discriminant and convergent validity. Reliability was assessed using Cronbach's alpha coefficient (α = .839 and .831), composite reliability (CR = .845 and .832), Theta (θ = .893 and .867), and McDonald Omega (Ω = .796 and .743). The analysis indicated a two-factor solution. Reliability and discriminant validity of the factors was established. Findings revealed that the present scale was a valid and reliable instrument that can be used in assessment of death anxiety in Iranian patients with end-stage renal disease.

Repeated measures from FIA data facilitates analysis across spatial scales of tree growth responses to nitrogen deposition from individual trees to whole ecoregions

Treesearch

Charles H. (Hobie) Perry; Kevin J. Horn; R. Quinn Thomas; Linda H. Pardo; Erica A.H. Smithwick; Doug Baldwin; Gregory B. Lawrence; Scott W. Bailey; Sabine Braun; Christopher M. Clark; Mark Fenn; Annika Nordin; Jennifer N. Phelan; Paul G. Schaberg; Sam St. Clair; Richard Warby; Shaun Watmough; Steven S. Perakis

2015-01-01

The abundance of temporally and spatially consistent Forest Inventory and Analysis data facilitates hierarchical/multilevel analysis to investigate factors affecting tree growth, scaling from plot-level to continental scales. Herein we use FIA tree and soil inventories in conjunction with various spatial climate and soils data to estimate species-specific responses of...

Factors Affecting Perceived Learning, Satisfaction, and Quality in the Online MBA: A Structural Equation Modeling Approach

ERIC Educational Resources Information Center

Sebastianelli, Rose; Swift, Caroline; Tamimi, Nabil

2015-01-01

The authors examined how six factors related to content and interaction affect students' perceptions of learning, satisfaction, and quality in online master of business administration (MBA) courses. They developed three scale items to measure each factor. Using survey data from MBA students at a private university, the authors estimated structural…

1km Global Terrestrial Carbon Flux: Estimations and Evaluations

NASA Astrophysics Data System (ADS)

Murakami, K.; Sasai, T.; Kato, S.; Saito, M.; Matsunaga, T.; Hiraki, K.; Maksyutov, S. S.

2017-12-01

Estimating global scale of the terrestrial carbon flux change with high accuracy and high resolution is important to understand global environmental changes. Furthermore the estimations of the global spatiotemporal distribution may contribute to the political and social activities such as REDD+. In order to reveal the current state of terrestrial carbon fluxes covering all over the world and a decadal scale. The satellite-based diagnostic biosphere model is suitable for achieving this purpose owing to observing on the present global land surface condition uniformly at some time interval. In this study, we estimated the global terrestrial carbon fluxes with 1km grids by using the terrestrial biosphere model (BEAMS). And we evaluated our new carbon flux estimations on various spatial scales and showed the transition of forest carbon stocks in some regions. Because BEAMS required high resolution meteorological data and satellite data as input data, we made 1km interpolated data using a kriging method. The data used in this study were JRA-55, GPCP, GOSAT L4B atmospheric CO2 data as meteorological data, and MODIS land product as land surface satellite data. Interpolating process was performed on the meteorological data because of insufficient resolution, but not on MODIS data. We evaluated our new carbon flux estimations using the flux tower measurement (FLUXNET2015 Datasets) in a point scale. We used 166 sites data for evaluating our model results. These flux sites are classified following vegetation type (DBF, EBF, ENF, mixed forests, grass lands, croplands, shrub lands, Savannas, wetlands). In global scale, the BEAMS estimations was underestimated compared to the flux measurements in the case of carbon uptake and release. The monthly variations of NEP showed relatively high correlations in DBF and mixed forests, but the correlation coefficients of EBF, ENF, and grass lands were less than 0.5. In the meteorological factors, air temperature and solar radiation showed very high correlations, and slight variations were showed in precipitation data. LAI data that was another large driving factor of terrestrial carbon cycle was not included in FLUXNET2015 datasets and it could not be evaluated.

[Methods and Applications to estimate the conversion factor of Resource-Based Relative Value Scale for nurse-midwife's delivery service in the national health insurance].

PubMed

Kim, Jinhyun; Jung, Yoomi

2009-08-01

This paper analyzed alternative methods of calculating the conversion factor for nurse-midwife's delivery services in the national health insurance and estimated the optimal reimbursement level for the services. A cost accounting model and Sustainable Growth Rate (SGR) model were developed to estimate the conversion factor of Resource-Based Relative Value Scale (RBRVS) for nurse-midwife's services, depending on the scope of revenue considered in financial analysis. The data and sources from the government and the financial statements from nurse-midwife clinics were used in analysis. The cost accounting model and SGR model showed a 17.6-37.9% increase and 19.0-23.6% increase, respectively, in nurse-midwife fee for delivery services in the national health insurance. The SGR model measured an overall trend of medical expenditures rather than an individual financial status of nurse-midwife clinics, and the cost analysis properly estimated the level of reimbursement for nurse-midwife's services. Normal vaginal delivery in nurse-midwife clinics is considered cost-effective in terms of insurance financing. Upon a declining share of health expenditures on midwife clinics, designing a reimbursement strategy for midwife's services could be an opportunity as well as a challenge when it comes to efficient resource allocation.

Proportion of general factor variance in a hierarchical multiple-component measuring instrument: a note on a confidence interval estimation procedure.

PubMed

Raykov, Tenko; Zinbarg, Richard E

2011-05-01

A confidence interval construction procedure for the proportion of explained variance by a hierarchical, general factor in a multi-component measuring instrument is outlined. The method provides point and interval estimates for the proportion of total scale score variance that is accounted for by the general factor, which could be viewed as common to all components. The approach may also be used for testing composite (one-tailed) or simple hypotheses about this proportion, and is illustrated with a pair of examples. ©2010 The British Psychological Society.

Testing the Factorial Invariance of the Black Racial Identity Scale across Gender

ERIC Educational Resources Information Center

Lott, Joe L., II

2011-01-01

Given that over 50 studies have been published using the Black Racial Identity Scale (BRIAS), the study of its dimensions and structural components are important to understanding Black people and the evolution of Black racial identity theory. Unconstrained and constrained confirmatory factor analysis models were estimated across males and females…

Career Adapt-Abilities Scale-France Form: Psychometric Properties and Relationships to Anxiety and Motivation

ERIC Educational Resources Information Center

Pouyaud, Jacques; Vignoli, Emmanuelle; Dosnon, Odile; Lallemand, Noelle

2012-01-01

The CAAS-France Form consists of four scales, each with six items, which measure concern, control, curiosity, and confidence as psychosocial resources for managing occupational transitions, developmental tasks, and work traumas. Internal consistency estimates for the subscale and total scores ranged from moderate to good. The factor structure was…

The Predictive Validity of the Short-Term Assessment of Risk and Treatability (START) for Multiple Adverse Outcomes in a Secure Psychiatric Inpatient Setting.

PubMed

O'Shea, Laura E; Picchioni, Marco M; Dickens, Geoffrey L

2016-04-01

The Short-Term Assessment of Risk and Treatability (START) aims to assist mental health practitioners to estimate an individual's short-term risk for a range of adverse outcomes via structured consideration of their risk ("Vulnerabilities") and protective factors ("Strengths") in 20 areas. It has demonstrated predictive validity for aggression but this is less established for other outcomes. We collated START assessments for N = 200 adults in a secure mental health hospital and ascertained 3-month risk event incidence using the START Outcomes Scale. The specific risk estimates, which are the tool developers' suggested method of overall assessment, predicted aggression, self-harm/suicidality, and victimization, and had incremental validity over the Strength and Vulnerability scales for these outcomes. The Strength scale had incremental validity over the Vulnerability scale for aggressive outcomes; therefore, consideration of protective factors had demonstrable value in their prediction. Further evidence is required to support use of the START for the full range of outcomes it aims to predict. © The Author(s) 2015.

Spacecraft mass estimation, relationships and engine data: Task 1.1 of the lunar base systems study

NASA Technical Reports Server (NTRS)

1988-01-01

A collection of scaling equations, weight statements, scaling factors, etc., useful for doing conceptual designs of spacecraft are given. Rules of thumb and methods of calculating quantities of interest are provided. Basic relationships for conventional, and several non-conventional, propulsion systems (nuclear, solar electric and solar thermal) are included. The equations and other data were taken from a number of sources and are not at all consistent with each other in level of detail or method, but provide useful references for early estimation purposes.

Estimates of solar variability using the solar backscatter ultraviolet (SBUV) 2 Mg II index from the NOAA 9 satellite

NASA Technical Reports Server (NTRS)

Cebula, Richard P.; Deland, Matthew T.; Schlesinger, Barry M.

1992-01-01

The Mg II core to wing index was first developed for the Nimbus 7 solar backscatter ultraviolet (SBUV) instrument as an indicator of solar variability on both solar 27-day rotational and solar cycle time scales. This work extends the Mg II index to the NOAA 9 SBUV 2 instrument and shows that the variations in absolute value between Mg II index data sets caused by interinstrument differences do not affect the ability to track temporal variations. The NOAA 9 Mg II index accurately represents solar rotational modulation but contains more day-to-day noise than the Nimbus 7 Mg II index. Solar variability at other UV wavelengths is estimated by deriving scale factors between the Mg II index rotational variations and at those selected wavelengths. Based on the 27-day average of the NOAA 9 Mg II index and the NOAA 9 scale factors, the solar irradiance change from solar minimum in September 1986 to the beginning of the maximum of solar cycle 22 in 1989 is estimated to be 8.6 percent at 205 nm, 3.5 percent at 250 nm, and less than 1 percent beyond 300 nm.

Estimating Facets of Psychopathy From Normal Personality Traits: A Step Toward Community Epidemiological Investigations

PubMed Central

Benning, Stephen D.; Patrick, Christopher J.; Blonigen, Daniel M.; Hicks, Brian M.; Iacono, William G.

2008-01-01

In three samples consisting of community and undergraduate men and women and incarcerated men, we examined the criterion validity of two distinct factors of psychopathy embodied in the Psychopathic Personality Inventory (PPI) as indexed by primary trait scales from the Multidimensional Personality Questionnaire (MPQ). Consistent with the PPI factors themselves, MPQ-estimated PPI-I related negatively with internalizing disorder symptoms and fearfulness and positively with thrill and adventure seeking, sociability, activity, and narcissism. MPQ-estimated PPI-II was associated negatively with socialization and positively with externalizing disorder symptoms, impulsivity, disinhibition and boredom susceptibility, and trait anxiety and negative emotionality. Additionally, PPI-I was selectively related to the interpersonal facet of Factor 1 of the Psychopathy Checklist—Revised (PCL-R), whereas PPI-II was related preferentially to Factor 2 of the PCL-R. PMID:15695739

Estimation of root zone storage capacity at the catchment scale using improved Mass Curve Technique

NASA Astrophysics Data System (ADS)

Zhao, Jie; Xu, Zongxue; Singh, Vijay P.

2016-09-01

The root zone storage capacity (Sr) greatly influences runoff generation, soil water movement, and vegetation growth and is hence an important variable for ecological and hydrological modelling. However, due to the great heterogeneity in soil texture and structure, there seems to be no effective approach to monitor or estimate Sr at the catchment scale presently. To fill the gap, in this study the Mass Curve Technique (MCT) was improved by incorporating a snowmelt module for the estimation of Sr at the catchment scale in different climatic regions. The "range of perturbation" method was also used to generate different scenarios for determining the sensitivity of the improved MCT-derived Sr to its influencing factors after the evaluation of plausibility of Sr derived from the improved MCT. Results can be showed as: (i) Sr estimates of different catchments varied greatly from ∼10 mm to ∼200 mm with the changes of climatic conditions and underlying surface characteristics. (ii) The improved MCT is a simple but powerful tool for the Sr estimation in different climatic regions of China, and incorporation of more catchments into Sr comparisons can further improve our knowledge on the variability of Sr. (iii) Variation of Sr values is an integrated consequence of variations in rainfall, snowmelt water and evapotranspiration. Sr values are most sensitive to variations in evapotranspiration of ecosystems. Besides, Sr values with a longer return period are more stable than those with a shorter return period when affected by fluctuations in its influencing factors.

The psychometric characteristics of the revised depression attitude questionnaire (R-DAQ) in Pakistani medical practitioners: a cross-sectional study of doctors in Lahore.

PubMed

Haddad, Mark; Waqas, Ahmed; Sukhera, Ahmed Bashir; Tarar, Asad Zaman

2017-07-27

Depression is common mental health problem and leading contributor to the global burden of disease. The attitudes and beliefs of the public and of health professionals influence social acceptance and affect the esteem and help-seeking of people experiencing mental health problems. The attitudes of clinicians are particularly relevant to their role in accurately recognising and providing appropriate support and management of depression. This study examines the characteristics of the revised depression attitude questionnaire (R-DAQ) with doctors working in healthcare settings in Lahore, Pakistan. A cross-sectional survey was conducted in 2015 using the revised depression attitude questionnaire (R-DAQ). A convenience sample of 700 medical practitioners based in six hospitals in Lahore was approached to participate in the survey. The R-DAQ structure was examined using Parallel Analysis from polychoric correlations. Unweighted least squares analysis (ULSA) was used for factor extraction. Model fit was estimated using goodness-of-fit indices and the root mean square of standardized residuals (RMSR), and internal consistency reliability for the overall scale and subscales was assessed using reliability estimates based on Mislevy and Bock (BILOG 3 Item analysis and test scoring with binary logistic models. Mooresville: Scientific Software, 55) and the McDonald's Omega statistic. Findings using this approach were compared with principal axis factor analysis based on Pearson correlation matrix. 601 (86%) of the doctors approached consented to participate in the study. Exploratory factor analysis of R-DAQ scale responses demonstrated the same 3-factor structure as in the UK development study, though analyses indicated removal of 7 of the 22 items because of weak loading or poor model fit. The 3 factor solution accounted for 49.8% of the common variance. Scale reliability and internal consistency were adequate: total scale standardised alpha was 0.694; subscale reliability for professional confidence was 0.732, therapeutic optimism/pessimism was 0.638, and generalist perspective was 0.769. The R-DAQ was developed with a predominantly UK-based sample of health professionals. This study indicates that this scale functions adequately and provides a valid measure of depression attitudes for medical practitioners in Pakistan, with the same factor structure as in the scale development sample. However, optimal scale function necessitated removal of several items, with a 15-item scale enabling the most parsimonious factor solution for this population.

The sensitivity of soil respiration to soil temperature, moisture, and carbon supply at the global scale.

PubMed

Hursh, Andrew; Ballantyne, Ashley; Cooper, Leila; Maneta, Marco; Kimball, John; Watts, Jennifer

2017-05-01

Soil respiration (Rs) is a major pathway by which fixed carbon in the biosphere is returned to the atmosphere, yet there are limits to our ability to predict respiration rates using environmental drivers at the global scale. While temperature, moisture, carbon supply, and other site characteristics are known to regulate soil respiration rates at plot scales within certain biomes, quantitative frameworks for evaluating the relative importance of these factors across different biomes and at the global scale require tests of the relationships between field estimates and global climatic data. This study evaluates the factors driving Rs at the global scale by linking global datasets of soil moisture, soil temperature, primary productivity, and soil carbon estimates with observations of annual Rs from the Global Soil Respiration Database (SRDB). We find that calibrating models with parabolic soil moisture functions can improve predictive power over similar models with asymptotic functions of mean annual precipitation. Soil temperature is comparable with previously reported air temperature observations used in predicting Rs and is the dominant driver of Rs in global models; however, within certain biomes soil moisture and soil carbon emerge as dominant predictors of Rs. We identify regions where typical temperature-driven responses are further mediated by soil moisture, precipitation, and carbon supply and regions in which environmental controls on high Rs values are difficult to ascertain due to limited field data. Because soil moisture integrates temperature and precipitation dynamics, it can more directly constrain the heterotrophic component of Rs, but global-scale models tend to smooth its spatial heterogeneity by aggregating factors that increase moisture variability within and across biomes. We compare statistical and mechanistic models that provide independent estimates of global Rs ranging from 83 to 108 Pg yr -1 , but also highlight regions of uncertainty where more observations are required or environmental controls are hard to constrain. © 2016 John Wiley & Sons Ltd.

Application of latent variable model in Rosenberg self-esteem scale.

PubMed

Leung, Shing-On; Wu, Hui-Ping

2013-01-01

Latent Variable Models (LVM) are applied to Rosenberg Self-Esteem Scale (RSES). Parameter estimations automatically give negative signs hence no recoding is necessary for negatively scored items. Bad items can be located through parameter estimate, item characteristic curves and other measures. Two factors are extracted with one on self-esteem and the other on the degree to take moderate views, with the later not often being covered in previous studies. A goodness-of-fit measure based on two-way margins is used but more works are needed. Results show that scaling provided by models with more formal statistical ground correlated highly with conventional method, which may provide justification for usual practice.

Some comments on mapping from disease-specific to generic health-related quality-of-life scales.

PubMed

Palta, Mari

2013-01-01

An article by Lu et al. in this issue of Value in Health addresses the mapping of treatment or group differences in disease-specific measures (DSMs) of health-related quality of life onto differences in generic health-related quality-of-life scores, with special emphasis on how the mapping is affected by the reliability of the DSM. In the proposed mapping, a factor analytic model defines a conversion factor between the scores as the ratio of factor loadings. Hence, the mapping applies to convert true underlying scales and has desirable properties facilitating the alignment of instruments and understanding their relationship in a coherent manner. It is important to note, however, that when DSM means or differences in mean DSMs are estimated, their mapping is still of a measurement error-prone predictor, and the correct conversion coefficient is the true mapping multiplied by the reliability of the DSM in the relevant sample. In addition, the proposed strategy for estimating the factor analytic mapping in practice requires assumptions that may not hold. We discuss these assumptions and how they may be the reason we obtain disparate estimates of the mapping factor in an application of the proposed methods to groups of patients. Copyright © 2013 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Validating the Multidimensional Measure of Cultural Identity Scales for Latinos Among Latina Mothers and Daughters

PubMed Central

Dillon, Frank R.; Félix-Ortiz, Maria; Rice, Christopher; De La Rosa, Mario; Rojas, Patria; Duan, Rui

2009-01-01

The psychometric properties of the Multidimensional Measure of Cultural Identity Scales for Latinos (MMCISL; Félix-Ortiz, Newcomb, & Myers, 1994) have never been examined in an adult Latina sample representing various levels of nativity and nationality. The rationale for the study was to confirm the factor structure and psychometric properties of the MMCISL with a predominantly immigrant sample of Latina mothers and daughters (n = 316). Adequate reliability estimates were found for 6 of the original 10 scales. Confirmatory factor analyses provided evidence of construct validity for the reliable scales. The Preferred Latino Affiliation scale was the only scale to meet strict measurement invariance criteria across mothers and daughters. Criterion validity was evidenced by relations between the Familiarity with Latino Culture scale and all criterion variables. Implications for acculturation and cultural identity research involving the MMCISL are discussed. PMID:19364206

On the consideration of scaling properties of extreme rainfall in Madrid (Spain) for developing a generalized intensity-duration-frequency equation and assessing probable maximum precipitation estimates

NASA Astrophysics Data System (ADS)

Casas-Castillo, M. Carmen; Rodríguez-Solà, Raúl; Navarro, Xavier; Russo, Beniamino; Lastra, Antonio; González, Paula; Redaño, Angel

2018-01-01

The fractal behavior of extreme rainfall intensities registered between 1940 and 2012 by the Retiro Observatory of Madrid (Spain) has been examined, and a simple scaling regime ranging from 25 min to 3 days of duration has been identified. Thus, an intensity-duration-frequency (IDF) master equation of the location has been constructed in terms of the simple scaling formulation. The scaling behavior of probable maximum precipitation (PMP) for durations between 5 min and 24 h has also been verified. For the statistical estimation of the PMP, an envelope curve of the frequency factor ( k m ) based on a total of 10,194 station-years of annual maximum rainfall from 258 stations in Spain has been developed. This curve could be useful to estimate suitable values of PMP at any point of the Iberian Peninsula from basic statistical parameters (mean and standard deviation) of its rainfall series. [Figure not available: see fulltext.

Mathematical modeling of a survey-meter used to measure radioactivity in human thyroids: Monte Carlo calculations of the device response and uncertainties

PubMed Central

Khrutchinsky, Arkady; Drozdovitch, Vladimir; Kutsen, Semion; Minenko, Victor; Khrouch, Valeri; Luckyanov, Nickolas; Voillequé, Paul; Bouville, André

2012-01-01

This paper presents results of Monte Carlo modeling of the SRP-68-01 survey meter used to measure exposure rates near the thyroid glands of persons exposed to radioactivity following the Chernobyl accident. This device was not designed to measure radioactivity in humans. To estimate the uncertainty associated with the measurement results, a mathematical model of the SRP-68-01 survey meter was developed and verified. A Monte Carlo method of numerical simulation of radiation transport has been used to calculate the calibration factor for the device and evaluate its uncertainty. The SRP-68-01 survey meter scale coefficient, an important characteristic of the device, was also estimated in this study. The calibration factors of the survey meter were calculated for 131I, 132I, 133I, and 135I content in the thyroid gland for six age groups of population: newborns; children aged 1 yr, 5 yr, 10 yr, 15 yr; and adults. A realistic scenario of direct thyroid measurements with an “extended” neck was used to calculate the calibration factors for newborns and one-year-olds. Uncertainties in the device calibration factors due to variability of the device scale coefficient, variability in thyroid mass and statistical uncertainty of Monte Carlo method were evaluated. Relative uncertainties in the calibration factor estimates were found to be from 0.06 for children aged 1 yr to 0.1 for 10-yr and 15-yr children. The positioning errors of the detector during measurements deviate mainly in one direction from the estimated calibration factors. Deviations of the device position from the proper geometry of measurements were found to lead to overestimation of the calibration factor by up to 24 percent for adults and up to 60 percent for 1-yr children. The results of this study improve the estimates of 131I thyroidal content and, consequently, thyroid dose estimates that are derived from direct thyroid measurements performed in Belarus shortly after the Chernobyl accident. PMID:22245289

Validation of the Weight Concerns Scale Applied to Brazilian University Students.

PubMed

Dias, Juliana Chioda Ribeiro; da Silva, Wanderson Roberto; Maroco, João; Campos, Juliana Alvares Duarte Bonini

2015-06-01

The aim of this study was to evaluate the validity and reliability of the Portuguese version of the Weight Concerns Scale (WCS) when applied to Brazilian university students. The scale was completed by 1084 university students from Brazilian public education institutions. A confirmatory factor analysis was conducted. The stability of the model in independent samples was assessed through multigroup analysis, and the invariance was estimated. Convergent, concurrent, divergent, and criterion validities as well as internal consistency were estimated. Results indicated that the one-factor model presented an adequate fit to the sample and values of convergent validity. The concurrent validity with the Body Shape Questionnaire and divergent validity with the Maslach Burnout Inventory for Students were adequate. Internal consistency was adequate, and the factorial structure was invariant in independent subsamples. The results present a simple and short instrument capable of precisely and accurately assessing concerns with weight among Brazilian university students. Copyright © 2015 Elsevier Ltd. All rights reserved.

Coastal erosion risk assessment using natural and human factors in different scales.

NASA Astrophysics Data System (ADS)

Alexandrakis, George; Kampanis, Nikolaos

2015-04-01

Climate change, including sea-level rise and increasing storms, raise the threats of coastal erosion. Mitigating and adapting to coastal erosion risks in areas of human interest, like urban areas, culture heritage sites, and areas of economic interest, present a major challenge for society. In this context, decision making needs to be based in reliable risk assessment that includes environmental, social and economic factors. By integrating coastal hazard and risk assessments maps into coastal management plans, risks in areas of interest can be reduced. To address this, the vulnerability of the coast to sea level rise and associated erosion, in terms of expected land loss and socioeconomic importance need to be identified. A holistic risk assessment based in environmental, socioeconomic and economics approach can provide managers information how to mitigate the impact of coastal erosion and plan protection measures. Such an approach needs to consider social, economic and environmental factors, which interactions can be better assessed when distributed and analysed along the geographical space. In this work, estimations of climate change impact to coastline are based on a combination of environmental and economic data analysed in a GIS database. The risk assessment is implemented through the estimation of the vulnerability and exposure variables of the coast in two scales. The larger scale estimates the vulnerability in a regional level, with the use environmental factors with the use of CVI. The exposure variable is estimated by the use of socioeconomic factors. Subsequently, a smaller scale focuses on highly vulnerable beaches with high social and economic value. The vulnerability assessment of the natural processes to the environmental characteristics of the beach is estimated with the use of the Beach Vulnerability Index. As exposure variable, the value of beach width that is capitalized in revenues is implemented through a hedonic pricing model. In this econometric modelling, Beach Value is related with economic and environmental attributes of the beach. All calculations are implemented in a GIS database, organised in five levels. In the first level the gathering of raw data is been made. In the second level data are organized in different scales. Third level, concerns the generating of new thematic data for further use. Risk assessment analysis and cost benefit analysis for protection measures is been made in level four. In the fifth level the results are transformed in user friendly form to be used by coastal managers. As case study area for the application of the method is selected Crete Island, while for the small scale the city of Rethymnon, which at the regional vulnerability analysis was found as high vulnerable. In the small scale vulnerability analysis, the sectors of the beach which are most vulnerable were identified, and risk analysis was made based on the revenue losses. Acknowledgments This work was implemented within the framework of the Action «Supporting Postdoctoral Researchers» of the Operational Program "Education and Lifelong Learning" (Action's Beneficiary: General Secretariat for Research and Technology), and is co-financed by the European Social Fund (ESF) and the Greek State.

Multiple Illuminant Colour Estimation via Statistical Inference on Factor Graphs.

PubMed

Mutimbu, Lawrence; Robles-Kelly, Antonio

2016-08-31

This paper presents a method to recover a spatially varying illuminant colour estimate from scenes lit by multiple light sources. Starting with the image formation process, we formulate the illuminant recovery problem in a statistically datadriven setting. To do this, we use a factor graph defined across the scale space of the input image. In the graph, we utilise a set of illuminant prototypes computed using a data driven approach. As a result, our method delivers a pixelwise illuminant colour estimate being devoid of libraries or user input. The use of a factor graph also allows for the illuminant estimates to be recovered making use of a maximum a posteriori (MAP) inference process. Moreover, we compute the probability marginals by performing a Delaunay triangulation on our factor graph. We illustrate the utility of our method for pixelwise illuminant colour recovery on widely available datasets and compare against a number of alternatives. We also show sample colour correction results on real-world images.

Use of satellite and modeled soil moisture data for predicting event soil loss at plot scale

NASA Astrophysics Data System (ADS)

Todisco, F.; Brocca, L.; Termite, L. F.; Wagner, W.

2015-09-01

The potential of coupling soil moisture and a Universal Soil Loss Equation-based (USLE-based) model for event soil loss estimation at plot scale is carefully investigated at the Masse area, in central Italy. The derived model, named Soil Moisture for Erosion (SM4E), is applied by considering the unavailability of in situ soil moisture measurements, by using the data predicted by a soil water balance model (SWBM) and derived from satellite sensors, i.e., the Advanced SCATterometer (ASCAT). The soil loss estimation accuracy is validated using in situ measurements in which event observations at plot scale are available for the period 2008-2013. The results showed that including soil moisture observations in the event rainfall-runoff erosivity factor of the USLE enhances the capability of the model to account for variations in event soil losses, the soil moisture being an effective alternative to the estimated runoff, in the prediction of the event soil loss at Masse. The agreement between observed and estimated soil losses (through SM4E) is fairly satisfactory with a determination coefficient (log-scale) equal to ~ 0.35 and a root mean square error (RMSE) of ~ 2.8 Mg ha-1. These results are particularly significant for the operational estimation of soil losses. Indeed, currently, soil moisture is a relatively simple measurement at the field scale and remote sensing data are also widely available on a global scale. Through satellite data, there is the potential of applying the SM4E model for large-scale monitoring and quantification of the soil erosion process.

Use of satellite and modelled soil moisture data for predicting event soil loss at plot scale

NASA Astrophysics Data System (ADS)

Todisco, F.; Brocca, L.; Termite, L. F.; Wagner, W.

2015-03-01

The potential of coupling soil moisture and a~USLE-based model for event soil loss estimation at plot scale is carefully investigated at the Masse area, in Central Italy. The derived model, named Soil Moisture for Erosion (SM4E), is applied by considering the unavailability of in situ soil moisture measurements, by using the data predicted by a soil water balance model (SWBM) and derived from satellite sensors, i.e. the Advanced SCATterometer (ASCAT). The soil loss estimation accuracy is validated using in situ measurements in which event observations at plot scale are available for the period 2008-2013. The results showed that including soil moisture observations in the event rainfall-runoff erosivity factor of the RUSLE/USLE, enhances the capability of the model to account for variations in event soil losses, being the soil moisture an effective alternative to the estimated runoff, in the prediction of the event soil loss at Masse. The agreement between observed and estimated soil losses (through SM4E) is fairly satisfactory with a determination coefficient (log-scale) equal to of ~ 0.35 and a root-mean-square error (RMSE) of ~ 2.8 Mg ha-1. These results are particularly significant for the operational estimation of soil losses. Indeed, currently, soil moisture is a relatively simple measurement at the field scale and remote sensing data are also widely available on a global scale. Through satellite data, there is the potential of applying the SM4E model for large-scale monitoring and quantification of the soil erosion process.

The role of physical habitat and sampling effort on estimates of benthic macroinvertebrate taxonomic richness at basin and site scales.

PubMed

Silva, Déborah R O; Ligeiro, Raphael; Hughes, Robert M; Callisto, Marcos

2016-06-01

Taxonomic richness is one of the most important measures of biological diversity in ecological studies, including those with stream macroinvertebrates. However, it is impractical to measure the true richness of any site directly by sampling. Our objective was to evaluate the effect of sampling effort on estimates of macroinvertebrate family and Ephemeroptera, Plecoptera, and Trichoptera (EPT) genera richness at two scales: basin and stream site. In addition, we tried to determine which environmental factors at the site scale most influenced the amount of sampling effort needed. We sampled 39 sites in the Cerrado biome (neotropical savanna). In each site, we obtained 11 equidistant samples of the benthic assemblage and multiple physical habitat measurements. The observed basin-scale richness achieved a consistent estimation from Chao 1, Jack 1, and Jack 2 richness estimators. However, at the site scale, there was a constant increase in the observed number of taxa with increased number of samples. Models that best explained the slope of site-scale sampling curves (representing the necessity of greater sampling effort) included metrics that describe habitat heterogeneity, habitat structure, anthropogenic disturbance, and water quality, for both macroinvertebrate family and EPT genera richness. Our results demonstrate the importance of considering basin- and site-scale sampling effort in ecological surveys and that taxa accumulation curves and richness estimators are good tools for assessing sampling efficiency. The physical habitat explained a significant amount of the sampling effort needed. Therefore, future studies should explore the possible implications of physical habitat characteristics when developing sampling objectives, study designs, and calculating the needed sampling effort.

Exploring the Full-Information Bifactor Model in Vertical Scaling with Construct Shift

ERIC Educational Resources Information Center

Li, Ying; Lissitz, Robert W.

2012-01-01

To address the lack of attention to construct shift in item response theory (IRT) vertical scaling, a multigroup, bifactor model was proposed to model the common dimension for all grades and the grade-specific dimensions. Bifactor model estimation accuracy was evaluated through a simulation study with manipulated factors of percentage of common…

The SASSI-3 Face Valid other Drugs Scale: A Psychometric Investigation (Substance Abuse Subtle Screening Inventory-3)

ERIC Educational Resources Information Center

Laux, John M.; Perera-Diltz, Dilani; Smirnoff, Jennifer B.; Salyers, Kathleen M.

2005-01-01

The authors investigated the psychometric capabilities of the Face Valid Other Drugs (FVOD) scale of the Substance Abuse Subtle Screening Inventory-3 (SASSI-3; G. A. Miller, 1999). Internal consistency reliability estimates and construct validity factor analysis for 230 college students provided initial support for the psychometric properties of…

Shielding evaluation for IMRT implementation in an existing accelerator vault

PubMed Central

Price, R. A.; Chibani, O.; Ma, C.‐M.

2003-01-01

A formalism is developed for evaluating the shielding in an existing vault to be used for IMRT. Existing exposure rate measurements are utilized as well as a newly developed effective modulation scaling factor. Examples are given for vaults housing 6, 10 and 18 MV linear accelerators. The use of an 18 MV Siemens linear accelerator is evaluated for IMRT delivery with respect to neutron production and the effects on individual patients. A modified modulation scaling factor is developed and the risk of the incurrence of fatal secondary malignancies is estimated. The difference in neutron production between 18 MV Varian and Siemens accelerators is estimated using Monte Carlo results. The neutron production from the Siemens accelerator is found to be approximately 4 times less than that of the Varian accelerator resulting in a risk of fatal secondary malignancy occurrence of approximately 1.6% when using the SMLC delivery technique and our measured modulation scaling factors. This compares with a previously published value of 1.6% for routine 3D CRT delivery on the Varian accelerator. PACS number(s): 87.52.Ga, 87.52.Px, 87.53.Qc, 87.53.Wz PMID:12841794

Multiscale soil moisture estimates using static and roving cosmic-ray soil moisture sensors

NASA Astrophysics Data System (ADS)

McJannet, David; Hawdon, Aaron; Baker, Brett; Renzullo, Luigi; Searle, Ross

2017-12-01

Soil moisture plays a critical role in land surface processes and as such there has been a recent increase in the number and resolution of satellite soil moisture observations and the development of land surface process models with ever increasing resolution. Despite these developments, validation and calibration of these products has been limited because of a lack of observations on corresponding scales. A recently developed mobile soil moisture monitoring platform, known as the rover, offers opportunities to overcome this scale issue. This paper describes methods, results and testing of soil moisture estimates produced using rover surveys on a range of scales that are commensurate with model and satellite retrievals. Our investigation involved static cosmic-ray neutron sensors and rover surveys across both broad (36 × 36 km at 9 km resolution) and intensive (10 × 10 km at 1 km resolution) scales in a cropping district in the Mallee region of Victoria, Australia. We describe approaches for converting rover survey neutron counts to soil moisture and discuss the factors controlling soil moisture variability. We use independent gravimetric and modelled soil moisture estimates collected across both space and time to validate rover soil moisture products. Measurements revealed that temporal patterns in soil moisture were preserved through time and regression modelling approaches were utilised to produce time series of property-scale soil moisture which may also have applications in calibration and validation studies or local farm management. Intensive-scale rover surveys produced reliable soil moisture estimates at 1 km resolution while broad-scale surveys produced soil moisture estimates at 9 km resolution. We conclude that the multiscale soil moisture products produced in this study are well suited to future analysis of satellite soil moisture retrievals and finer-scale soil moisture models.

A New Lebanese Medication Adherence Scale: Validation in Lebanese Hypertensive Adults.

PubMed

Bou Serhal, R; Salameh, P; Wakim, N; Issa, C; Kassem, B; Abou Jaoude, L; Saleh, N

2018-01-01

A new Lebanese scale measuring medication adherence considered socioeconomic and cultural factors not taken into account by the eight-item Morisky Medication Adherence Scale (MMAS-8). Objectives were to validate the new adherence scale and its prediction of hypertension control, compared to MMAS-8, and to assess adherence rates and factors. A cross-sectional study, including 405 patients, was performed in outpatient cardiology clinics of three hospitals in Beirut. Blood pressure was measured, a questionnaire filled, and sodium intake estimated by a urine test. Logistic regression defined predictors of hypertension control and adherence. 54.9% had controlled hypertension. 82.4% were adherent by the new scale, which showed good internal consistency, adequate questions (KMO coefficient = 0.743), and four factors. It predicted hypertension control (OR = 1.217; p value = 0.003), unlike MMAS-8, but the scores were correlated (ICC average measure = 0.651; p value < 0.001). Stress and smoking predicted nonadherence. This study elaborated a validated, practical, and useful tool measuring adherence to medications in Lebanese hypertensive patients.

Prospective CO 2 saline resource estimation methodology: Refinement of existing US-DOE-NETL methods based on data availability

DOE PAGES

Goodman, Angela; Sanguinito, Sean; Levine, Jonathan S.

2016-09-28

Carbon storage resource estimation in subsurface saline formations plays an important role in establishing the scale of carbon capture and storage activities for governmental policy and commercial project decision-making. Prospective CO 2 resource estimation of large regions or subregions, such as a basin, occurs at the initial screening stages of a project using only limited publicly available geophysical data, i.e. prior to project-specific site selection data generation. As the scale of investigation is narrowed and selected areas and formations are identified, prospective CO 2 resource estimation can be refined and uncertainty narrowed when site-specific geophysical data are available. Here, wemore » refine the United States Department of Energy – National Energy Technology Laboratory (US-DOE-NETL) methodology as the scale of investigation is narrowed from very large regional assessments down to selected areas and formations that may be developed for commercial storage. In addition, we present a new notation that explicitly identifies differences between data availability and data sources used for geologic parameters and efficiency factors as the scale of investigation is narrowed. This CO 2 resource estimation method is available for screening formations in a tool called CO 2-SCREEN.« less

Prospective CO 2 saline resource estimation methodology: Refinement of existing US-DOE-NETL methods based on data availability

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

Goodman, Angela; Sanguinito, Sean; Levine, Jonathan S.

Carbon storage resource estimation in subsurface saline formations plays an important role in establishing the scale of carbon capture and storage activities for governmental policy and commercial project decision-making. Prospective CO 2 resource estimation of large regions or subregions, such as a basin, occurs at the initial screening stages of a project using only limited publicly available geophysical data, i.e. prior to project-specific site selection data generation. As the scale of investigation is narrowed and selected areas and formations are identified, prospective CO 2 resource estimation can be refined and uncertainty narrowed when site-specific geophysical data are available. Here, wemore » refine the United States Department of Energy – National Energy Technology Laboratory (US-DOE-NETL) methodology as the scale of investigation is narrowed from very large regional assessments down to selected areas and formations that may be developed for commercial storage. In addition, we present a new notation that explicitly identifies differences between data availability and data sources used for geologic parameters and efficiency factors as the scale of investigation is narrowed. This CO 2 resource estimation method is available for screening formations in a tool called CO 2-SCREEN.« less

The simple procedure for the fluxgate magnetometers calibration

NASA Astrophysics Data System (ADS)

Marusenkov, Andriy

2014-05-01

The fluxgate magnetometers are widely used in geophysics investigations including the geomagnetic field monitoring at the global network of geomagnetic observatories as well as for electromagnetic sounding of the Earth's crust conductivity. For solving these tasks the magnetometers have to be calibrated with an appropriate level of accuracy. As a particular case, the ways to satisfy the recent requirements to the scaling and orientation errors of 1-second INTERNAGNET magnetometers are considered in the work. The goal of the present study was to choose a simple and reliable calibration method for estimation of scale factors and angular errors of the three-axis magnetometers in the field. There are a large number of the scalar calibration methods, which use a free rotation of the sensor in the calibration field followed by complicated data processing procedures for numerical solution of the high-order equations set. The chosen approach also exploits the Earth's magnetic field as a calibrating signal, but, in contrast to other methods, the sensor has to be oriented in some particular positions in respect to the total field vector, instead of the sensor free rotation. This allows to use very simple and straightforward linear computation formulas and, as a result, to achieve more reliable estimations of the calibrated parameters. The estimation of the scale factors is performed by the sequential aligning of each component of the sensor in two positions: parallel and anti-parallel to the Earth's magnetic field vector. The estimation of non-orthogonality angles between each pair of components is performed after sequential aligning of the components at the angles +/- 45 and +/- 135 degrees of arc in respect to the total field vector. Due to such four positions approach the estimations of the non-orthogonality angles are invariant to the zero offsets and non-linearity of transfer functions of the components. The experimental justifying of the proposed method by means of the Coil Calibration system reveals, that the achieved accuracy (<0.04 % for scale factors and 0.03 degrees of arc for angle errors) is sufficient for many applications, particularly for satisfying the INTERMAGNET requirements to 1-second instruments.

Quantifying Uncertainty in Daily Temporal Variations of Atmospheric NH3 Emissions Following Application of Chemical Fertilizers

NASA Astrophysics Data System (ADS)

Balasubramanian, S.; Koloutsou-Vakakis, S.; Rood, M. J.

2014-12-01

Improving modeling predictions of atmospheric particulate matter and deposition of reactive nitrogen requires representative emission inventories of precursor species, such as ammonia (NH3). Anthropogenic NH3 is primarily emitted to the atmosphere from agricultural sources (80-90%) with dominant contributions (56%) from chemical fertilizer usage (CFU) in regions like Midwest USA. Local crop management practices vary spatially and temporally, which influence regional air quality. To model the impact of CFU, NH3 emission inputs to chemical transport models are obtained from the National Emission Inventory (NEI). NH3 emissions from CFU are typically estimated by combining annual fertilizer sales data with emission factors. The Sparse Matrix Operator Kernel Emissions (SMOKE) model is used to disaggregate annual emissions to hourly scale using temporal factors. These factors are estimated by apportioning emissions within each crop season in proportion to the nitrogen applied and time-averaged to the hourly scale. Such approach does not reflect influence of CFU for different crops and local weather and soil conditions. This study provides an alternate approach for estimating temporal factors for NH3 emissions. The DeNitrification DeComposition (DNDC) model was used to estimate daily variations in NH3 emissions from CFU at 14 Central Illinois locations for 2002-2011. Weather, crop and soil data were provided as inputs. A method was developed to estimate site level CFU by combining planting and harvesting dates, nitrogen management and fertilizer sales data. DNDC results indicated that annual NH3 emissions were within ±15% of SMOKE estimates. Daily modeled emissions across 10 years followed similar distributions but varied in magnitudes within ±20%. Individual emission peaks on days after CFU were 2.5-8 times greater as compared to existing estimates from SMOKE. By identifying the episodic nature of NH3 emissions from CFU, this study is expected to provide improvements in predicting atmospheric particulate matter concentrations and deposition of reactive nitrogen.

Validation of a Spanish-language version of the ADHD Rating Scale IV in a Spanish sample.

PubMed

Vallejo-Valdivielso, M; Soutullo, C A; de Castro-Manglano, P; Marín-Méndez, J J; Díez-Suárez, A

2017-07-14

The purpose of this study is to validate a Spanish-language version of the 18-item ADHD Rating Scale-IV (ADHD-RS-IV.es) in a Spanish sample. From a total sample of 652 children and adolescents aged 6 to 17 years (mean age was 11.14±3.27), we included 518 who met the DSM-IV-TR criteria for ADHD and 134 healthy controls. To evaluate the factorial structure, validity, and reliability of the scale, we performed a confirmatory factor analysis (CFA) using structural equation modelling on a polychoric correlation matrix and maximum likelihood estimation. The scale's discriminant validity and predictive value were estimated using ROC (receiver operating characteristics) curve analysis. Both the full scale and the subscales of the Spanish-language version of the ADHD-RS-IV showed good internal consistency. Cronbach's alpha was 0.94 for the full scale and ≥ 0.90 for the subscales, and ordinal alpha was 0.95 and ≥ 0.90, respectively. CFA showed that a two-factor model (inattention and hyperactivity/impulsivity) provided the best fit for the data. ADHD-RS-IV.es offered good discriminant ability to distinguish between patients with ADHD and controls (AUC=0.97). The two-factor structure of the Spanish-language version of the ADHD-RS-IV (ADHD-RS-IV.es) is consistent with those of the DSM-IV-TR and DSM-5 as well as with the model proposed by the author of the original scale. Furthermore, it has good discriminant ability. ADHD-RS-IV.es is therefore a valid and reliable tool for determining presence and severity of ADHD symptoms in the Spanish population. Copyright © 2017 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.

Stable isotope signatures and trophic-step fractionation factors of fish tissues collected as non-lethal surrogates of dorsal muscle.

PubMed

Busst, Georgina M A; Bašić, Tea; Britton, J Robert

2015-08-30

Dorsal white muscle is the standard tissue analysed in fish trophic studies using stable isotope analyses. As muscle is usually collected destructively, fin tissues and scales are often used as non-lethal surrogates; we examined the utility of scales and fin tissue as muscle surrogates. The muscle, fin and scale δ(15) N and δ(13) C values from 10 cyprinid fish species determined with an elemental analyser coupled with an isotope ratio mass spectrometer were compared. The fish comprised (1) samples from the wild, and (2) samples from tank aquaria, using six species held for 120 days and fed a single food resource. Relationships between muscle, fin and scale isotope ratios were examined for each species and for the entire dataset, with the efficacy of four methods of predicting muscle isotope ratios from fin and scale values being tested. The fractionation factors between the three tissues of the laboratory fishes and their food resource were then calculated and applied to Bayesian mixing models to assess their effect on fish diet predictions. The isotopic data of the three tissues per species were distinct, but were significantly related, enabling estimations of muscle values from the two surrogates. Species-specific equations provided the least erroneous corrections of scale and fin isotope ratios (errors < 0.6‰). The fractionation factors for δ(15) N values were in the range obtained for other species, but were often higher for δ(13) C values. Their application to data from two fish populations in the mixing models resulted in significant alterations in diet predictions. Scales and fin tissue are strong surrogates of dorsal muscle in food web studies as they can provide estimates of muscle values within an acceptable level of error when species-specific methods are used. Their derived fractionation factors can also be applied to models predicting fish diet composition from δ(15) N and δ(13) C values. Copyright © 2015 John Wiley & Sons, Ltd.

Estimating terrestrial aboveground biomass estimation using lidar remote sensing: a meta-analysis

NASA Astrophysics Data System (ADS)

Zolkos, S. G.; Goetz, S. J.; Dubayah, R.

2012-12-01

Estimating biomass of terrestrial vegetation is a rapidly expanding research area, but also a subject of tremendous interest for reducing carbon emissions associated with deforestation and forest degradation (REDD). The accuracy of biomass estimates is important in the context carbon markets emerging under REDD, since areas with more accurate estimates command higher prices, but also for characterizing uncertainty in estimates of carbon cycling and the global carbon budget. There is particular interest in mapping biomass so that carbon stocks and stock changes can be monitored consistently across a range of scales - from relatively small projects (tens of hectares) to national or continental scales - but also so that other benefits of forest conservation can be factored into decision making (e.g. biodiversity and habitat corridors). We conducted an analysis of reported biomass accuracy estimates from more than 60 refereed articles using different remote sensing platforms (aircraft and satellite) and sensor types (optical, radar, lidar), with a particular focus on lidar since those papers reported the greatest efficacy (lowest errors) when used in the a synergistic manner with other coincident multi-sensor measurements. We show systematic differences in accuracy between different types of lidar systems flown on different platforms but, perhaps more importantly, differences between forest types (biomes) and plot sizes used for field calibration and assessment. We discuss these findings in relation to monitoring, reporting and verification under REDD, and also in the context of more systematic assessment of factors that influence accuracy and error estimation.

Attributable causes of cancer in Japan in 2005--systematic assessment to estimate current burden of cancer attributable to known preventable risk factors in Japan.

PubMed

Inoue, M; Sawada, N; Matsuda, T; Iwasaki, M; Sasazuki, S; Shimazu, T; Shibuya, K; Tsugane, S

2012-05-01

To contribute to evidence-based policy decision making for national cancer control, we conducted a systematic assessment to estimate the current burden of cancer attributable to known preventable risk factors in Japan in 2005. We first estimated the population attributable fractions (PAFs) of each cancer attributable to known risk factors from relative risks derived primarily from Japanese pooled analyses and large-scale cohort studies and the prevalence of exposure in the period around 1990. Using nationwide vital statistics records and incidence estimates, we then estimated the attributable cancer incidence and mortality in 2005. In 2005, ≈ 55% of cancer among men was attributable to preventable risk factors in Japan. The corresponding figure was lower among women, but preventable risk factors still accounted for nearly 30% of cancer. In men, tobacco smoking had the highest PAF (30% for incidence and 35% for mortality, respectively) followed by infectious agents (23% and 23%). In women, in contrast, infectious agents had the highest PAF (18% and 19% for incidence and mortality, respectively) followed by tobacco smoking (6% and 8%). In Japan, tobacco smoking and infections are major causes of cancer. Further control of these factors will contribute to substantial reductions in cancer incidence and mortality in Japan.

An Upscaling Method for Cover-Management Factor and Its Application in the Loess Plateau of China

PubMed Central

Zhao, Wenwu; Fu, Bojie; Qiu, Yang

2013-01-01

The cover-management factor (C-factor) is important for studying soil erosion. In addition, it is important to use sampling plot data to estimate the regional C-factor when assessing erosion and soil conservation. Here, the loess hill and gully region in Ansai County, China, was studied to determine a method for computing the C-factor. This C-factor is used in the Universal Soil Loss Equation (USLE) at a regional scale. After upscaling the slope-scale computational equation, the C-factor for Ansai County was calculated by using the soil loss ratio, precipitation and land use/cover type. The multi-year mean C-factor for Ansai County was 0.36. The C-factor values were greater in the eastern region of the county than in the western region. In addition, the lowest C-factor values were found in the southern region of the county near its southern border. These spatial differences were consistent with the spatial distribution of the soil loess ratios across areas with different land uses. Additional research is needed to determine the effects of seasonal vegetation growth changes on the C-factor, and the C-factor upscaling uncertainties at a regional scale. PMID:24113551

An upscaling method for cover-management factor and its application in the loess Plateau of China.

PubMed

Zhao, Wenwu; Fu, Bojie; Qiu, Yang

2013-10-09

The cover-management factor (C-factor) is important for studying soil erosion. In addition, it is important to use sampling plot data to estimate the regional C-factor when assessing erosion and soil conservation. Here, the loess hill and gully region in Ansai County, China, was studied to determine a method for computing the C-factor. This C-factor is used in the Universal Soil Loss Equation (USLE) at a regional scale. After upscaling the slope-scale computational equation, the C-factor for Ansai County was calculated by using the soil loss ratio, precipitation and land use/cover type. The multi-year mean C-factor for Ansai County was 0.36. The C-factor values were greater in the eastern region of the county than in the western region. In addition, the lowest C-factor values were found in the southern region of the county near its southern border. These spatial differences were consistent with the spatial distribution of the soil loess ratios across areas with different land uses. Additional research is needed to determine the effects of seasonal vegetation growth changes on the C-factor, and the C-factor upscaling uncertainties at a regional scale.

A confirmatory factor analysis of the Impact of Event Scale using a sample of World War II and Korean War veterans.

PubMed

Shevlin, M; Hunt, N; Robbins, I

2000-12-01

This study assessed the factor structure of the Impact of Event Scale (IES), a measure of intrusion and avoidance, using a sample of World War II and Korean War veterans who had experienced combat 40-50 years earlier. A series of 3 confirmatory factor analytic models were specified and estimated using LISREL 8.3. Model 1 specified a 1-factor model. Model 2 specified a correlated 2-factor model. Model 3 specified a 2-factor model with additional cross-factor loadings for Items 2 and 12. Model 3 was found to fit the data. In addition, this model was found to be a better explanation of the data than the other models. Also in addition, the correlations between the Intrusion and Avoidance factors and the 4 subscales of the 28-item General Health Questionnaire were examined to determine the distinctiveness of the two IES factors.

Modeling water quality in an urban river using hydrological factors--data driven approaches.

PubMed

Chang, Fi-John; Tsai, Yu-Hsuan; Chen, Pin-An; Coynel, Alexandra; Vachaud, Georges

2015-03-15

Contrasting seasonal variations occur in river flow and water quality as a result of short duration, severe intensity storms and typhoons in Taiwan. Sudden changes in river flow caused by impending extreme events may impose serious degradation on river water quality and fateful impacts on ecosystems. Water quality is measured in a monthly/quarterly scale, and therefore an estimation of water quality in a daily scale would be of good help for timely river pollution management. This study proposes a systematic analysis scheme (SAS) to assess the spatio-temporal interrelation of water quality in an urban river and construct water quality estimation models using two static and one dynamic artificial neural networks (ANNs) coupled with the Gamma test (GT) based on water quality, hydrological and economic data. The Dahan River basin in Taiwan is the study area. Ammonia nitrogen (NH3-N) is considered as the representative parameter, a correlative indicator in judging the contamination level over the study. Key factors the most closely related to the representative parameter (NH3-N) are extracted by the Gamma test for modeling NH3-N concentration, and as a result, four hydrological factors (discharge, days w/o discharge, water temperature and rainfall) are identified as model inputs. The modeling results demonstrate that the nonlinear autoregressive with exogenous input (NARX) network furnished with recurrent connections can accurately estimate NH3-N concentration with a very high coefficient of efficiency value (0.926) and a low RMSE value (0.386 mg/l). Besides, the NARX network can suitably catch peak values that mainly occur in dry periods (September-April in the study area), which is particularly important to water pollution treatment. The proposed SAS suggests a promising approach to reliably modeling the spatio-temporal NH3-N concentration based solely on hydrological data, without using water quality sampling data. It is worth noticing that such estimation can be made in a much shorter time interval of interest (span from a monthly scale to a daily scale) because hydrological data are long-term collected in a daily scale. The proposed SAS favorably makes NH3-N concentration estimation much easier (with only hydrological field sampling) and more efficient (in shorter time intervals), which can substantially help river managers interpret and estimate water quality responses to natural and/or manmade pollution in a more effective and timely way for river pollution management. Copyright © 2014 Elsevier Ltd. All rights reserved.

Conceptual design and analysis of a dynamic scale model of the Space Station Freedom

NASA Technical Reports Server (NTRS)

Davis, D. A.; Gronet, M. J.; Tan, M. K.; Thorne, J.

1994-01-01

This report documents the conceptual design study performed to evaluate design options for a subscale dynamic test model which could be used to investigate the expected on-orbit structural dynamic characteristics of the Space Station Freedom early build configurations. The baseline option was a 'near-replica' model of the SSF SC-7 pre-integrated truss configuration. The approach used to develop conceptual design options involved three sets of studies: evaluation of the full-scale design and analysis databases, conducting scale factor trade studies, and performing design sensitivity studies. The scale factor trade study was conducted to develop a fundamental understanding of the key scaling parameters that drive design, performance and cost of a SSF dynamic scale model. Four scale model options were estimated: 1/4, 1/5, 1/7, and 1/10 scale. Prototype hardware was fabricated to assess producibility issues. Based on the results of the study, a 1/4-scale size is recommended based on the increased model fidelity associated with a larger scale factor. A design sensitivity study was performed to identify critical hardware component properties that drive dynamic performance. A total of 118 component properties were identified which require high-fidelity replication. Lower fidelity dynamic similarity scaling can be used for non-critical components.

The Development and Psychometric Properties of the Immigration Law Concerns Scale (ILCS) for HIV Testing.

PubMed

Lechuga, Julia; Galletly, Carol L; Broaddus, Michelle R; Dickson-Gomez, Julia B; Glasman, Laura R; McAuliffe, Timothy L; Vega, Miriam Y; LeGrand, Sarah; Mena, Carla A; Barlow, Morgan L; Valera, Erik; Montenegro, Judith I

2017-11-08

To develop, pilot test, and conduct psychometric analyses of an innovative scale measuring the influence of perceived immigration laws on Latino migrants' HIV-testing behavior. The Immigration Law Concerns Scale (ILCS) was developed in three phases: Phase 1 involved a review of law and literature, generation of scale items, consultation with project advisors, and subsequent revision of the scale. Phase 2 involved systematic translation- back translation and consensus-based editorial processes conducted by members of a bilingual and multi-national study team. In Phase 3, 339 sexually active, HIV-negative Spanish-speaking, non-citizen Latino migrant adults (both documented and undocumented) completed the scale via audio computer-assisted self-interview. The psychometric properties of the scale were tested with exploratory factor analysis and estimates of reliability coefficients were generated. Bivariate correlations were conducted to test the discriminant and predictive validity of identified factors. Exploratory factor analysis revealed a three-factor, 17-item scale. subscale reliability ranged from 0.72 to 0.79. There were significant associations between the ILCS and the HIV-testing behaviors of participants. Results of the pilot test and psychometric analysis of the ILCS are promising. The scale is reliable and significantly associated with the HIV-testing behaviors of participants. Subscales related to unwanted government attention and concerns about meeting moral character requirements should be refined.

Regionalising MUSLE factors for application to a data-scarce catchment

NASA Astrophysics Data System (ADS)

Gwapedza, David; Slaughter, Andrew; Hughes, Denis; Mantel, Sukhmani

2018-04-01

The estimation of soil loss and sediment transport is important for effective management of catchments. A model for semi-arid catchments in southern Africa has been developed; however, simplification of the model parameters and further testing are required. Soil loss is calculated through the Modified Universal Soil Loss Equation (MUSLE). The aims of the current study were to: (1) regionalise the MUSLE erodibility factors and; (2) perform a sensitivity analysis and validate the soil loss outputs against independently-estimated measures. The regionalisation was developed using Geographic Information Systems (GIS) coverages. The model was applied to a high erosion semi-arid region in the Eastern Cape, South Africa. Sensitivity analysis indicated model outputs to be more sensitive to the vegetation cover factor. The simulated soil loss estimates of 40 t ha-1 yr-1 were within the range of estimates by previous studies. The outcome of the present research is a framework for parameter estimation for the MUSLE through regionalisation. This is part of the ongoing development of a model which can estimate soil loss and sediment delivery at broad spatial and temporal scales.

An Innovative Method for Estimating Soil Retention at a ...

EPA Pesticide Factsheets

Planning for a sustainable future should include an accounting of services currently provided by ecosystems such as erosion control. Retention of soil improves fertility, increases water retention, and decreases sedimentation in streams and rivers. Landscapes patterns that facilitate these services could help reduce costs for flood control, dredging of reservoirs and waterways, while maintaining habitat for fish and other species important to recreational and tourism industries. Landscape scale geospatial data available for the continental United States was leveraged to estimate sediment erosion (RUSLE-based, Renard, et al. 1997) employing recent geospatial techniques of sediment delivery ratio (SDR) estimation (Cavalli, et al. 2013). The approach was designed to derive a quantitative approximation of the ecological services provided by vegetative cover, management practices, and other surface features with respect to protecting soils from the erosion processes of detachment, transport, and deposition. Quantities of soil retained on the landscape and potential erosion for multiple land cover scenarios relative to current (NLCD 2011) conditions were calculated for each calendar month, and summed to yield annual estimations at a 30-meter grid cell. Continental-scale data used included MODIS NDVI data (2000-2014) to estimate monthly USLE C-factors, gridded soil survey geographic (gSSURGO) soils data (annual USLE K factor), PRISM rainfall data (monthly USLE

Upscaling soil saturated hydraulic conductivity from pore throat characteristics

NASA Astrophysics Data System (ADS)

Ghanbarian, Behzad; Hunt, Allen G.; Skaggs, Todd H.; Jarvis, Nicholas

2017-06-01

Upscaling and/or estimating saturated hydraulic conductivity Ksat at the core scale from microscopic/macroscopic soil characteristics has been actively under investigation in the hydrology and soil physics communities for several decades. Numerous models have been developed based on different approaches, such as the bundle of capillary tubes model, pedotransfer functions, etc. In this study, we apply concepts from critical path analysis, an upscaling technique first developed in the physics literature, to estimate saturated hydraulic conductivity at the core scale from microscopic pore throat characteristics reflected in capillary pressure data. With this new model, we find Ksat estimations to be within a factor of 3 of the average measured saturated hydraulic conductivities reported by Rawls et al. (1982) for the eleven USDA soil texture classes.

Climate fails to predict wood decomposition at regional scales

NASA Astrophysics Data System (ADS)

Bradford, Mark A.; Warren, Robert J., II; Baldrian, Petr; Crowther, Thomas W.; Maynard, Daniel S.; Oldfield, Emily E.; Wieder, William R.; Wood, Stephen A.; King, Joshua R.

2014-07-01

Decomposition of organic matter strongly influences ecosystem carbon storage. In Earth-system models, climate is a predominant control on the decomposition rates of organic matter. This assumption is based on the mean response of decomposition to climate, yet there is a growing appreciation in other areas of global change science that projections based on mean responses can be irrelevant and misleading. We test whether climate controls on the decomposition rate of dead wood--a carbon stock estimated to represent 73 +/- 6 Pg carbon globally--are sensitive to the spatial scale from which they are inferred. We show that the common assumption that climate is a predominant control on decomposition is supported only when local-scale variation is aggregated into mean values. Disaggregated data instead reveal that local-scale factors explain 73% of the variation in wood decomposition, and climate only 28%. Further, the temperature sensitivity of decomposition estimated from local versus mean analyses is 1.3-times greater. Fundamental issues with mean correlations were highlighted decades ago, yet mean climate-decomposition relationships are used to generate simulations that inform management and adaptation under environmental change. Our results suggest that to predict accurately how decomposition will respond to climate change, models must account for local-scale factors that control regional dynamics.

Cultural adaptation and psychometric assessment of Pain Catastrophizing Scale among young healthy Malay-speaking adults in military settings.

PubMed

Mohd Din, F H; Hoe, Victor C W; Chan, C K; Muslan, M A

2015-05-01

The Pain Catastrophizing Scale (PCS) is designed to assess negative thoughts in response to pain. It is composed of three domains: helplessness, rumination, and magnification. We report on the translation, adaptation, and validation of scores on a Malay-speaking version of the PCS, the PCS-MY. Guidelines for the process of cross-cultural adaptations of assessment measures were implemented. A sample of 303 young military recruits participated in the study. Factor structure, reliability, and validity of scores on the PCS-MY were examined. Convergent validity was investigated with the Positive and Negative Affect Scale, Short-form 12 version 2, and Ryff's Psychological Well-being Scale. Most participants were men, ranging in age from 19 to 26. The reliability of the PCS-MY scores was adequate (α = 0.90; mean inter-item correlation = 0.43). Confirmatory factor analysis showed that a modified version of the PCS-MY provided best fit estimates to the sample data. The PCS-MY total score was negatively correlated with mental well-being and positively correlated with negative affect (all ps < 0.001). The PCS-MY was demonstrated to have adequate reliability and validity estimates in the study sample.

Quantitative Estimation of Land Surface Characteristic Parameters and Actual Evapotranspiration in the Nagqu River Basin over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Zhong, L.; Ma, Y.; Ma, W.; Zou, M.; Hu, Y.

2016-12-01

Actual evapotranspiration (ETa) is an important component of the water cycle in the Tibetan Plateau. It is controlled by many hydrological and meteorological factors. Therefore, it is of great significance to estimate ETa accurately and continuously. It is also drawing much attention of scientific community to understand land surface parameters and land-atmosphere water exchange processes in small watershed-scale areas. Based on in-situ meteorological data in the Nagqu river basin and surrounding regions, the main meteorological factors affecting the evaporation process were quantitatively analyzed and the point-scale ETa estimation models in the study area were successfully built. On the other hand, multi-source satellite data (such as SPOT, MODIS, FY-2C) were used to derive the surface characteristics in the river basin. A time series processing technique was applied to remove cloud cover and reconstruct data series. Then improved land surface albedo, improved downward shortwave radiation flux and reconstructed normalized difference vegetation index (NDVI) were coupled into the topographical enhanced surface energy balance system to estimate ETa. The model-estimated results were compared with those ETa values determined by combinatory method. The results indicated that the model-estimated ETa agreed well with in-situ measurements with correlation coefficient, mean bias error and root mean square error of 0.836, 0.087 and 0.140 mm/h respectively.

Development and initial validation of the internalization of Asian American stereotypes scale.

PubMed

Shen, Frances C; Wang, Yu-Wei; Swanson, Jane L

2011-07-01

This research consists of four studies on the initial reliability and validity of the Internalization of Asian American Stereotypes Scale (IAASS), a self-report instrument that measures the degree Asian Americans have internalized racial stereotypes about their own group. The results from the exploratory and confirmatory factor analyses support a stable four-factor structure of the IAASS: Difficulties with English Language Communication, Pursuit of Prestigious Careers, Emotional Reservation, and Expected Academic Success. Evidence for concurrent and discriminant validity is presented. High internal-consistency and test-retest reliability estimates are reported. A discussion of how this scale can contribute to research and practice regarding internalized stereotyping among Asian Americans is provided.

Difference of stand-scale transpiration between ridge and riparian area in a watershed with Japanese cypress plantation

NASA Astrophysics Data System (ADS)

Kume, T.; Tsuruta, K.; Komatsu, H.; Shinohara, Y.; Otsuki, K.

2011-12-01

Several different methods to assess water use are available, and the sap flux measurement technique is one of the most promising methods, especially in monotonous watershed. Previously, three spatial levels of scaling have been used to obtain bottom-up transpiration estimates based on the sap flux technique: from within-tree to tree, from tree to stand, and from stand to watershed or landscape. Although there are considerable variations that must be taken into account at each step, few studies have examined plot-to-plot variability of stand-scale transpirations. To design optimum sampling method to accurately estimate transpiration at the watershed-scale, it is indispensable to understand heterogeneity of stand-scale transpiration in a forested watershed and the factors determining the heterogeneity. This study was undertaken to clarify differences of stand-scale transpirations within a watershed and the factors determining the differences. To this aim, we conducted sap flux-based transpiration estimates in two plots such as a lower riparian (RZ) and an upper ridge (UZ) zone in a watershed with Japanese cypress plantation, Kyushu, Japan in two years. Tree height and diameter of breast height (DBH) were lager in RZ than those of UZ. The stand sapwood area (As) was lager in RZ than UZ (21.9 cm2h a-1, 16.8 cm2ha-1, respectively). Stand mean sap flux (Js) in RZ was almost same as that of UZ when relatively lower Js, while, Js in RZ was higher than that of UZ when relatively higher Js (i.e., bright days in summer season). Consequently, daily stand-scale transpiration (E), which is the multiple of As and Js, differed by two times between RZ and UZ in summer season. This study found significant heterogeneity of stand-scale transpiration within the watershed and that the differences could be caused by two aspects such as stand structure and sap flux velocity.

A critical source area phosphorus index with topographic transport factors using high resolution LiDAR digital elevation models

NASA Astrophysics Data System (ADS)

Thomas, Ian; Murphy, Paul; Fenton, Owen; Shine, Oliver; Mellander, Per-Erik; Dunlop, Paul; Jordan, Phil

2015-04-01

A new phosphorus index (PI) tool is presented which aims to improve the identification of critical source areas (CSAs) of phosphorus (P) losses from agricultural land to surface waters. In a novel approach, the PI incorporates topographic indices rather than watercourse proximity as proxies for runoff risk, to account for the dominant control of topography on runoff-generating areas and P transport pathways. Runoff propensity and hydrological connectivity are modelled using the Topographic Wetness Index (TWI) and Network Index (NI) respectively, utilising high resolution digital elevation models (DEMs) derived from Light Detection and Ranging (LiDAR) to capture the influence of micro-topographic features on runoff pathways. Additionally, the PI attempts to improve risk estimates of particulate P losses by incorporating an erosion factor that accounts for fine-scale topographic variability within fields. Erosion risk is modelled using the Unit Stream Power Erosion Deposition (USPED) model, which integrates DEM-derived upslope contributing area and Universal Soil Loss Equation (USLE) factors. The PI was developed using field, sub-field and sub-catchment scale datasets of P source, mobilisation and transport factors, for four intensive agricultural catchments in Ireland representing different agri-environmental conditions. Datasets included soil test P concentrations, degree of P saturation, soil attributes, land use, artificial subsurface drainage locations, and 2 m resolution LiDAR DEMs resampled from 0.25 m resolution data. All factor datasets were integrated within a Geographical Information System (GIS) and rasterised to 2 m resolution. For each factor, values were categorised and assigned relative risk scores which ranked P loss potential. Total risk scores were calculated for each grid cell using a component formulation, which summed the products of weighted factor risk scores for runoff and erosion pathways. Results showed that the new PI was able to predict in-field risk variability and hence was able to identify CSAs at the sub-field scale. PI risk estimates and component scores were analysed at catchment and subcatchment scales, and validated using measured dissolved, particulate and total P losses at subcatchment snapshot sites and gauging stations at catchment outlets. The new PI provides CSA delineations at higher precision compared to conventional PIs, and more robust P transport risk estimates. The tool can be used to target cost-effective mitigation measures for P management within single farm units and wider catchments.

Revision, Criterion Validity, and Multi-group Assessment of the Reactions to Homosexuality Scale

PubMed Central

Smolenski, Derek J.; Diamond, Pamela M.; Ross, Michael W.; Simon Rosser, B. R.

2010-01-01

Internalized homonegativity encompasses negative attitudes toward one’s own sexual orientation, and is associated with negative mental and physical health outcomes. The Reactions to Homosexuality scale (Ross & Rosser, 1996), an instrument used to measure internalized homonegativity, has been criticized for including content irrelevant to the construct of internalized homonegativity. We revised the scale using exploratory and confirmatory factor analyses, and identified a seven-item, three-factor reduced version that demonstrated measurement invariance across racial/ethnic categorizations and between English and Spanish versions. We also investigated criterion validity by estimating correlations with hypothesized outcomes associated with outness, relationship status, sexual orientation, and gay community affiliation. The evidence of measurement invariance suggests that this scale is appropriate for pluralistic treatment or study groups. PMID:20954058

Understanding the origins of uncertainty in landscape-scale variations of emissions of nitrous oxide

NASA Astrophysics Data System (ADS)

Milne, Alice; Haskard, Kathy; Webster, Colin; Truan, Imogen; Goulding, Keith

2014-05-01

Nitrous oxide is a potent greenhouse gas which is over 300 times more radiatively effective than carbon dioxide. In the UK, the agricultural sector is estimated to be responsible for over 80% of nitrous oxide emissions, with these emissions resulting from livestock and farmers adding nitrogen fertilizer to soils. For the purposes of reporting emissions to the IPCC, the estimates are calculated using simple models whereby readily-available national or international statistics are combined with IPCC default emission factors. The IPCC emission factor for direct emissions of nitrous oxide from soils has a very large uncertainty. This is primarily because the variability of nitrous oxide emissions in space is large and this results in uncertainty that may be regarded as sample noise. To both reduce uncertainty through improved modelling, and to communicate an understanding of this uncertainty, we must understand the origins of the variation. We analysed data on nitrous oxide emission rate and some other soil properties collected from a 7.5-km transect across contrasting land uses and parent materials in eastern England. We investigated the scale-dependence and spatial uniformity of the correlations between soil properties and emission rates from farm to landscape scale using wavelet analysis. The analysis revealed a complex pattern of scale-dependence. Emission rates were strongly correlated with a process-specific function of the water-filled pore space at the coarsest scale and nitrate at intermediate and coarsest scales. We also found significant correlations between pH and emission rates at the intermediate scales. The wavelet analysis showed that these correlations were not spatially uniform and that at certain scales changes in parent material coincided with significant changes in correlation. Our results indicate that, at the landscape scale, nitrate content and water-filled pore space are key soil properties for predicting nitrous oxide emissions and should therefore be incorporated into process models and emission factors for inventory calculations.

Odds per Adjusted Standard Deviation: Comparing Strengths of Associations for Risk Factors Measured on Different Scales and Across Diseases and Populations

PubMed Central

Hopper, John L.

2015-01-01

How can the “strengths” of risk factors, in the sense of how well they discriminate cases from controls, be compared when they are measured on different scales such as continuous, binary, and integer? Given that risk estimates take into account other fitted and design-related factors—and that is how risk gradients are interpreted—so should the presentation of risk gradients. Therefore, for each risk factor X0, I propose using appropriate regression techniques to derive from appropriate population data the best fitting relationship between the mean of X0 and all the other covariates fitted in the model or adjusted for by design (X1, X2, … , Xn). The odds per adjusted standard deviation (OPERA) presents the risk association for X0 in terms of the change in risk per s = standard deviation of X0 adjusted for X1, X2, … , Xn, rather than the unadjusted standard deviation of X0 itself. If the increased risk is relative risk (RR)-fold over A adjusted standard deviations, then OPERA = exp[ln(RR)/A] = RRs. This unifying approach is illustrated by considering breast cancer and published risk estimates. OPERA estimates are by definition independent and can be used to compare the predictive strengths of risk factors across diseases and populations. PMID:26520360

Global climate impacts of country-level primary carbonaceous aerosol from solid-fuel cookstove emissions

NASA Astrophysics Data System (ADS)

Lacey, Forrest; Henze, Daven

2015-11-01

Cookstove use is globally one of the largest unregulated anthropogenic sources of primary carbonaceous aerosol. While reducing cookstove emissions through national-scale mitigation efforts has clear benefits for improving indoor and ambient air quality, and significant climate benefits from reduced green-house gas emissions, climate impacts associated with reductions to co-emitted black (BC) and organic carbonaceous aerosol are not well characterized. Here we attribute direct, indirect, semi-direct, and snow/ice albedo radiative forcing (RF) and associated global surface temperature changes to national-scale carbonaceous aerosol cookstove emissions. These results are made possible through the use of adjoint sensitivity modeling to relate direct RF and BC deposition to emissions. Semi- and indirect effects are included via global scaling factors, and bounds on these estimates are drawn from current literature ranges for aerosol RF along with a range of solid fuel emissions characterizations. Absolute regional temperature potentials are used to estimate global surface temperature changes. Bounds are placed on these estimates, drawing from current literature ranges for aerosol RF along with a range of solid fuel emissions characterizations. We estimate a range of 0.16 K warming to 0.28 K cooling with a central estimate of 0.06 K cooling from the removal of cookstove aerosol emissions. At the national emissions scale, countries’ impacts on global climate range from net warming (e.g., Mexico and Brazil) to net cooling, although the range of estimated impacts for all countries span zero given uncertainties in RF estimates and fuel characterization. We identify similarities and differences in the sets of countries with the highest emissions and largest cookstove temperature impacts (China, India, Nigeria, Pakistan, Bangladesh and Nepal), those with the largest temperature impact per carbon emitted (Kazakhstan, Estonia, and Mongolia), and those that would provide the most efficient cooling from a switch to fuel with a lower BC emission factor (Kazakhstan, Estonia, and Latvia). The results presented here thus provide valuable information for climate impact assessments across a wide range of cookstove initiatives.

Estimation and applicability of attenuation characteristics for source parameters and scaling relations in the Garhwal Kumaun Himalaya region, India

NASA Astrophysics Data System (ADS)

Singh, Rakesh; Paul, Ajay; Kumar, Arjun; Kumar, Parveen; Sundriyal, Y. P.

2018-06-01

Source parameters of the small to moderate earthquakes are significant for understanding the dynamic rupture process, the scaling relations of the earthquakes and for assessment of seismic hazard potential of a region. In this study, the source parameters were determined for 58 small to moderate size earthquakes (3.0 ≤ Mw ≤ 5.0) occurred during 2007-2015 in the Garhwal-Kumaun region. The estimated shear wave quality factor (Qβ(f)) values for each station at different frequencies have been applied to eliminate any bias in the determination of source parameters. The Qβ(f) values have been estimated by using coda wave normalization method in the frequency range 1.5-16 Hz. A frequency-dependent S wave quality factor relation is obtained as Qβ(f) = (152.9 ± 7) f(0.82±0.005) by fitting a power-law frequency dependence model for the estimated values over the whole study region. The spectral (low-frequency spectral level and corner frequency) and source (static stress drop, seismic moment, apparent stress and radiated energy) parameters are obtained assuming ω-2 source model. The displacement spectra are corrected for estimated frequency-dependent attenuation, site effect using spectral decay parameter "Kappa". The frequency resolution limit was resolved by quantifying the bias in corner frequencies, stress drop and radiated energy estimates due to finite-bandwidth effect. The data of the region shows shallow focused earthquakes with low stress drop. The estimation of Zúñiga parameter (ε) suggests the partial stress drop mechanism in the region. The observed low stress drop and apparent stress can be explained by partial stress drop and low effective stress model. Presence of subsurface fluid at seismogenic depth certainly manipulates the dynamics of the region. However, the limited event selection may strongly bias the scaling relation even after taking as much as possible precaution in considering effects of finite bandwidth, attenuation and site corrections. Although, the scaling can be improved further with the integration of large dataset of microearthquakes and use of a stable and robust approach.

Absorption properties and graphitic carbon emission factors of forest fire aerosols

Treesearch

E.M. Patterson; Charles K. McMahon; D.E. Ward

1986-01-01

Abstract. Data on the optical absorption properties (expressed as a specific absorption, Ba) of the smoke emissions from fires with forest fuels have been determined for a series of low-intensity field fires and a series of laboratory scale fires. The B, data have been used to estimate the emission factors for graphitic...

Confirmatory Factor Analysis of Persian Adaptation of Multidimensional Students' Life Satisfaction Scale (MSLSS)

ERIC Educational Resources Information Center

Hatami, Gissou; Motamed, Niloofar; Ashrafzadeh, Mahshid

2010-01-01

Validity and reliability of Persian adaptation of MSLSS in the 12-18 years, middle and high school students (430 students in grades 6-12 in Bushehr port, Iran) using confirmatory factor analysis by means of LISREL statistical package were checked. Internal consistency reliability estimates (Cronbach's coefficient [alpha]) were all above the…

A Screening-Level Approach for Comparing Risks Affecting Aquatic Ecosystem Services over Socio-Environmental Gradients

NASA Astrophysics Data System (ADS)

Harmon, T. C.; Conde, D.; Villamizar, S. R.; Reid, B.; Escobar, J.; Rusak, J.; Hoyos, N.; Scordo, F.; Perillo, G. M.; Piccolo, M. C.; Zilio, M.; Velez, M.

2015-12-01

Assessing risks to aquatic ecosystems services (ES) is challenging and time-consuming, and effective strategies for prioritizing more detailed assessment efforts are needed. We propose a screening-level risk analysis (SRA) approach that scales ES risk using socioeconomic and environmental indices to capture anthropic and climatic pressures, as well as the capacity for institutional responses to those pressures. The method considers ES within a watershed context, and uses expert input to prioritize key services and the associated pressures that threaten them. The SRA approach focuses on estimating ES risk affect factors, which are the sum of the intensity factors for all hazards or pressures affecting the ES. We estimate the pressure intensity factors in a novel manner, basing them on the nation's (i) human development (proxied by Inequality-adjusted Human Development Index, IHDI), (ii) environmental regulatory and monitoring state (Environmental Performance Index, EPI) and (iii) the current level of water stress in the watershed (baseline water stress, BWS). Anthropic intensity factors for future conditions are derived from the baseline values based on the nation's 10-year trend in IHDI and EPI; ES risks in nations with stronger records of change are rewarded more/penalized less in estimates for good/poor future management scenarios. Future climatic intensity factors are tied to water stress estimates based on two general circulation model (GCM) outcomes. We demonstrate the method for an international array of six sites representing a wide range of socio-environmental settings. The outcomes illustrate novel consequences of the scaling scheme. Risk affect factors may be greater in a highly developed region under intense climatic pressure, or in less well-developed regions due to human factors (e.g., poor environmental records). As a screening-level tool, the SRA approach offers considerable promise for ES risk comparisons among watersheds and regions so that detailed assessment, management and mitigation efforts can be effectively prioritized.

High-resolution model for estimating the economic and policy implications of agricultural soil salinization in California

NASA Astrophysics Data System (ADS)

Welle, Paul D.; Mauter, Meagan S.

2017-09-01

This work introduces a generalizable approach for estimating the field-scale agricultural yield losses due to soil salinization. When integrated with regional data on crop yields and prices, this model provides high-resolution estimates for revenue losses over large agricultural regions. These methods account for the uncertainty inherent in model inputs derived from satellites, experimental field data, and interpreted model results. We apply this method to estimate the effect of soil salinity on agricultural outputs in California, performing the analysis with both high-resolution (i.e. field scale) and low-resolution (i.e. county-scale) data sources to highlight the importance of spatial resolution in agricultural analysis. We estimate that soil salinity reduced agricultural revenues by 3.7 billion (1.7-7.0 billion) in 2014, amounting to 8.0 million tons of lost production relative to soil salinities below the crop-specific thresholds. When using low-resolution data sources, we find that the costs of salinization are underestimated by a factor of three. These results highlight the need for high-resolution data in agro-environmental assessment as well as the challenges associated with their integration.

Confirmatory Factor Analysis of the Minnesota Nicotine Withdrawal Scale

PubMed Central

Toll, Benjamin A.; O’Malley, Stephanie S.; McKee, Sherry A.; Salovey, Peter; Krishnan-Sarin, Suchitra

2008-01-01

The authors examined the factor structure of the Minnesota Nicotine Withdrawal Scale (MNWS) using confirmatory factor analysis in clinical research samples of smokers trying to quit (n = 723). Three confirmatory factor analytic models, based on previous research, were tested with each of the 3 study samples at multiple points in time. A unidimensional model including all 8 MNWS items was found to be the best explanation of the data. This model produced fair to good internal consistency estimates. Additionally, these data revealed that craving should be included in the total score of the MNWS. Factor scores derived from this single-factor, 8-item model showed that increases in withdrawal were associated with poor smoking outcome for 2 of the clinical studies. Confirmatory factor analyses of change scores showed that the MNWS symptoms cohere as a syndrome over time. Future investigators should report a total score using all of the items from the MNWS. PMID:17563141

Permeability from complex conductivity: an evaluation of polarization magnitude versus relaxation time based geophysical length scales

NASA Astrophysics Data System (ADS)

Slater, L. D.; Robinson, J.; Weller, A.; Keating, K.; Robinson, T.; Parker, B. L.

2017-12-01

Geophysical length scales determined from complex conductivity (CC) measurements can be used to estimate permeability k when the electrical formation factor F describing the ratio between tortuosity and porosity is known. Two geophysical length scales have been proposed: [1] the imaginary conductivity σ" normalized by the specific polarizability cp; [2] the time constant τ multiplied by a diffusion coefficient D+. The parameters cp and D+ account for the control of fluid chemistry and/or varying minerology on the geophysical length scale. We evaluated the predictive capability of two recently presented CC permeability models: [1] an empirical formulation based on σ"; [2] a mechanistic formulation based on τ;. The performance of the CC models was evaluated against measured permeability; this performance was also compared against that of well-established k estimation equations that use geometric length scales to represent the pore scale properties controlling fluid flow. Both CC models predict permeability within one order of magnitude for a database of 58 sandstone samples, with the exception of those samples characterized by high pore volume normalized surface area Spor and more complex mineralogy including significant dolomite. Variations in cp and D+ likely contribute to the poor performance of the models for these high Spor samples. The ultimate value of such geophysical models for permeability prediction lies in their application to field scale geophysical datasets. Two observations favor the implementation of the σ" based model over the τ based model for field-scale estimation: [1] the limited range of variation in cp relative to D+; [2] σ" is readily measured using field geophysical instrumentation (at a single frequency) whereas τ requires broadband spectral measurements that are extremely challenging and time consuming to accurately measure in the field. However, the need for a reliable estimate of F remains a major obstacle to the field-scale implementation of either of the CC permeability models for k estimation.

Unit Price Scaling Trends for Chemical Products

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

Qi, Wei; Sathre, Roger; William R. Morrow, III

2015-08-01

To facilitate early-stage life-cycle techno-economic modeling of emerging technologies, here we identify scaling relations between unit price and sales quantity for a variety of chemical products of three categories - metal salts, organic compounds, and solvents. We collect price quotations for lab-scale and bulk purchases of chemicals from both U.S. and Chinese suppliers. We apply a log-log linear regression model to estimate the price discount effect. Using the median discount factor of each category, one can infer bulk prices of products for which only lab-scale prices are available. We conduct out-of-sample tests showing that most of the price proxies deviatemore » from their actual reference prices by a factor less than ten. We also apply the bootstrap method to determine if a sample median discount factor should be accepted for price approximation. We find that appropriate discount factors for metal salts and for solvents are both -0.56, while that for organic compounds is -0.67 and is less representative due to greater extent of product heterogeneity within this category.« less

Psychometric properties of the Spanish version of the UPPS-P Impulsive Behavior Scale: A Rasch rating scale analysis and confirmatory factor analysis.

PubMed

Pilatti, Angelina; Lozano, Oscar M; Cyders, Melissa A

2015-12-01

The present study was aimed at determining the psychometric properties of the Spanish version of the UPPS-P Impulsive Behavior Scale in a sample of college students. Participants were 318 college students (36.2% men; mean age = 20.9 years, SD = 6.4 years). The psychometric properties of this Spanish version were analyzed using the Rasch model, and the factor structure was examined using confirmatory factor analysis. The verification of the global fit of the data showed adequate indexes for persons and items. The reliability estimates were high for both items and persons. Differential item functioning across gender was found for 23 items, which likely reflects known differences in impulsivity levels between men and women. The factor structure of the Spanish version of the UPPS-P replicates previous work with the original UPPS-P Scale. Overall, results suggest that test scores from the Spanish version of the UPPS-P show adequate psychometric properties to accurately assess the multidimensional model of impulsivity, which represents the most exhaustive measure of this construct. (c) 2015 APA, all rights reserved).

Scaling up from field to region for wind erosion prediction using a field-scale wind erosion model and GIS

USGS Publications Warehouse

Zobeck, T.M.; Parker, N.C.; Haskell, S.; Guoding, K.

2000-01-01

Factors that affect wind erosion such as surface vegetative and other cover, soil properties and surface roughness usually change spatially and temporally at the field-scale to produce important field-scale variations in wind erosion. Accurate estimation of wind erosion when scaling up from fields to regions, while maintaining meaningful field-scale process details, remains a challenge. The objectives of this study were to evaluate the feasibility of using a field-scale wind erosion model with a geographic information system (GIS) to scale up to regional levels and to quantify the differences in wind erosion estimates produced by different scales of soil mapping used as a data layer in the model. A GIS was used in combination with the revised wind erosion equation (RWEQ), a field-scale wind erosion model, to estimate wind erosion for two 50 km2 areas. Landsat Thematic Mapper satellite imagery from 1993 with 30 m resolution was used as a base map. The GIS database layers included land use, soils, and other features such as roads. The major land use was agricultural fields. Data on 1993 crop management for selected fields of each crop type were collected from local government agency offices and used to 'train' the computer to classify land areas by crop and type of irrigation (agroecosystem) using commercially available software. The land area of the agricultural land uses was overestimated by 6.5% in one region (Lubbock County, TX, USA) and underestimated by about 21% in an adjacent region (Terry County, TX, USA). The total estimated wind erosion potential for Terry County was about four times that estimated for adjacent Lubbock County. The difference in potential erosion among the counties was attributed to regional differences in surface soil texture. In a comparison of different soil map scales in Terry County, the generalised soil map had over 20% more of the land area and over 15% greater erosion potential in loamy sand soils than did the detailed soil map. As a result, the wind erosion potential determined using the generalised soil map Was about 26% greater than the erosion potential estimated by using the detailed soil map in Terry County. This study demonstrates the feasibility of scaling up from fields to regions to estimate wind erosion potential by coupling a field-scale wind erosion model with GIS and identifies possible sources of error with this approach.

Historical emissions of carbonaceous aerosols from biomass and fossil fuel burning for the period 1870-2000

NASA Astrophysics Data System (ADS)

Ito, Akinori; Penner, Joyce E.

2005-06-01

Historical changes of black carbon (BC) and particulate organic matter (POM) emissions from biomass burning (BB) and fossil fuel (FF) burning are estimated from 1870 to 2000. A bottom-up inventory for open vegetation (OV) burning is scaled by a top-down estimate for the year 2000. Monthly and interannual variations are derived over the time period from 1979 to 2000 based on the TOMS satellite aerosol index (AI) and this global map. Prior to 1979, emissions are scaled to a CH4 emissions inventory based on land-use change. Biofuel (BF) emissions from a recent inventory for developing countries are scaled forward and backward in time using population statistics and crop production statistics. In developed countries, wood consumption data together with emission factors for cooking and heating practices are used for biofuel estimates. For fossil fuel use, we use fuel consumption data and specific emission factors for different fuel use categories to develop an inventory over 1950-2000, and emissions are scaled to a CO2 inventory prior to that time. Technology changes for emissions from the diesel transport sector are included. During the last decade of this time period, the BC and POM emissions from biomass burning (i.e., OV + BF) contribute a significant amount to the primary sources of BC and POM and are larger than those from FF. Thus 59% of the NH BC emissions and 90% of the NH POM emissions are from BB in 2000. Fossil fuel consumption technologies are needed prior to 1990 in order to improve estimates of fossil fuel emissions during the twentieth century. These results suggest that the aerosol emissions from biomass burning need to be represented realistically in climate change assessments. The estimated emissions are available on a 1° × 1° grid for global climate modeling studies of climate changes.

Uncertainty analysis on simple mass balance model to calculate critical loads for soil acidity.

PubMed

Li, Harbin; McNulty, Steven G

2007-10-01

Simple mass balance equations (SMBE) of critical acid loads (CAL) in forest soil were developed to assess potential risks of air pollutants to ecosystems. However, to apply SMBE reliably at large scales, SMBE must be tested for adequacy and uncertainty. Our goal was to provide a detailed analysis of uncertainty in SMBE so that sound strategies for scaling up CAL estimates to the national scale could be developed. Specifically, we wanted to quantify CAL uncertainty under natural variability in 17 model parameters, and determine their relative contributions in predicting CAL. Results indicated that uncertainty in CAL came primarily from components of base cation weathering (BC(w); 49%) and acid neutralizing capacity (46%), whereas the most critical parameters were BC(w) base rate (62%), soil depth (20%), and soil temperature (11%). Thus, improvements in estimates of these factors are crucial to reducing uncertainty and successfully scaling up SMBE for national assessments of CAL.

Determining the spatial variability of wetland soil bulk density, organic matter, and the conversion factor between organic matter and organic carbon across coastal Louisiana, U.S.A.

USGS Publications Warehouse

Wang, Hongqing; Piazza, Sarai C.; Sharp, Leigh A.; Stagg, Camille L.; Couvillion, Brady R.; Steyer, Gregory D.; McGinnis, Thomas E.

2016-01-01

Soil bulk density (BD), soil organic matter (SOM) content, and a conversion factor between SOM and soil organic carbon (SOC) are often used in estimating SOC sequestration and storage. Spatial variability in BD, SOM, and the SOM–SOC conversion factor affects the ability to accurately estimate SOC sequestration, storage, and the benefits (e.g., land building area and vertical accretion) associated with wetland restoration efforts, such as marsh creation and sediment diversions. There are, however, only a few studies that have examined large-scale spatial variability in BD, SOM, and SOM–SOC conversion factors in coastal wetlands. In this study, soil cores, distributed across the entire coastal Louisiana (approximately 14,667 km2) were used to examine the regional-scale spatial variability in BD, SOM, and the SOM–SOC conversion factor. Soil cores for BD and SOM analyses were collected during 2006–09 from 331 spatially well-distributed sites in the Coastwide Reference Monitoring System network. Soil cores for the SOM–SOC conversion factor analysis were collected from 15 sites across coastal Louisiana during 2006–07. Results of a split-plot analysis of variance with incomplete block design indicated that BD and SOM varied significantly at a landscape level, defined by both hydrologic basins and vegetation types. Vertically, BD and SOM varied significantly among different vegetation types. The SOM–SOC conversion factor also varied significantly at the landscape level. This study provides critical information for the assessment of the role of coastal wetlands in large regional carbon budgets and the estimation of carbon credits from coastal restoration.

An Analysis of the Differences among Log Scaling Methods and Actual Log Volume

Treesearch

R. Edward Thomas; Neal D. Bennett

2017-01-01

Log rules estimate the volume of green lumber that can be expected to result from the sawing of a log. As such, this ability to reliably predict lumber recovery forms the foundation of log sales and purchase. The more efficient a sawmill, the less the scaling methods reflect the actual volume recovery and the greater the overrun factor. Using high-resolution scanned...

An Evaluation of the Precision of Measurement of Ryff's Psychological Well-Being Scales in a Population Sample

ERIC Educational Resources Information Center

Abbott, Rosemary A.; Ploubidis, George B.; Huppert, Felicia A.; Kuh, Diana; Croudace, Tim J.

2010-01-01

The aim of this study is to assess the effective measurement range of Ryff's Psychological Well-being scales (PWB). It applies normal ogive item response theory (IRT) methodology using factor analysis procedures for ordinal data based on a limited information estimation approach. The data come from a sample of 1,179 women participating in a…

A framework for predicting global silicate weathering and CO2 drawdown rates over geologic time-scales.

PubMed

Hilley, George E; Porder, Stephen

2008-11-04

Global silicate weathering drives long-time-scale fluctuations in atmospheric CO(2). While tectonics, climate, and rock-type influence silicate weathering, it is unclear how these factors combine to drive global rates. Here, we explore whether local erosion rates, GCM-derived dust fluxes, temperature, and water balance can capture global variation in silicate weathering. Our spatially explicit approach predicts 1.9-4.6 x 10(13) mols of Si weathered globally per year, within a factor of 4-10 of estimates of global silicate fluxes derived from riverine measurements. Similarly, our watershed-based estimates are within a factor of 4-18 (mean of 5.3) of the silica fluxes measured in the world's ten largest rivers. Eighty percent of total global silicate weathering product traveling as dissolved load occurs within a narrow range (0.01-0.5 mm/year) of erosion rates. Assuming each mol of Mg or Ca reacts with 1 mol of CO(2), 1.5-3.3 x 10(8) tons/year of CO(2) is consumed by silicate weathering, consistent with previously published estimates. Approximately 50% of this drawdown occurs in the world's active mountain belts, emphasizing the importance of tectonic regulation of global climate over geologic timescales.

Upscaling gas permeability in tight-gas sandstones

NASA Astrophysics Data System (ADS)

Ghanbarian, B.; Torres-Verdin, C.; Lake, L. W.; Marder, M. P.

2017-12-01

Klinkenberg-corrected gas permeability (k) estimation in tight-gas sandstones is essential for gas exploration and production in low-permeability porous rocks. Most models for estimating k are a function of porosity (ϕ), tortuosity (τ), pore shape factor (s) and a characteristic length scale (lc). Estimation of the latter, however, has been the subject of debate in the literature. Here we invoke two different upscaling approaches from statistical physics: (1) the EMA and (2) critical path analysis (CPA) to estimate lc from pore throat-size distribution derived from mercury intrusion capillary pressure (MICP) curve. τ is approximated from: (1) concepts of percolation theory and (2) formation resistivity factor measurements (F = τ/ϕ). We then estimate k of eighteen tight-gas sandstones from lc, τ, and ϕ by assuming two different pore shapes: cylindrical and slit-shaped. Comparison with Klinkenberg-corrected k measurements showed that τ was estimated more accurately from F measurements than from percolation theory. Generally speaking, our results implied that the EMA estimated k within a factor of two of the measurements and more precisely than CPA. We further found that the assumption of cylindrical pores yielded more accurate k estimates when τ was estimated from concepts of percolation theory than the assumption of slit-shaped pores. However, the EMA with slit-shaped pores estimated k more precisely than that with cylindrical pores when τ was estimated from F measurements.

Application of lab derived kinetic biodegradation parameters at the field scale

NASA Astrophysics Data System (ADS)

Schirmer, M.; Barker, J. F.; Butler, B. J.; Frind, E. O.

2003-04-01

Estimating the intrinsic remediation potential of an aquifer typically requires the accurate assessment of the biodegradation kinetics, the level of available electron acceptors and the flow field. Zero- and first-order degradation rates derived at the laboratory scale generally overpredict the rate of biodegradation when applied to the field scale, because limited electron acceptor availability and microbial growth are typically not considered. On the other hand, field estimated zero- and first-order rates are often not suitable to forecast plume development because they may be an oversimplification of the processes at the field scale and ignore several key processes, phenomena and characteristics of the aquifer. This study uses the numerical model BIO3D to link the laboratory and field scale by applying laboratory derived Monod kinetic degradation parameters to simulate a dissolved gasoline field experiment at Canadian Forces Base (CFB) Borden. All additional input parameters were derived from laboratory and field measurements or taken from the literature. The simulated results match the experimental results reasonably well without having to calibrate the model. An extensive sensitivity analysis was performed to estimate the influence of the most uncertain input parameters and to define the key controlling factors at the field scale. It is shown that the most uncertain input parameters have only a minor influence on the simulation results. Furthermore it is shown that the flow field, the amount of electron acceptor (oxygen) available and the Monod kinetic parameters have a significant influence on the simulated results. Under the field conditions modelled and the assumptions made for the simulations, it can be concluded that laboratory derived Monod kinetic parameters can adequately describe field scale degradation processes, if all controlling factors are incorporated in the field scale modelling that are not necessarily observed at the lab scale. In this way, there are no scale relationships to be found that link the laboratory and the field scale, accurately incorporating the additional processes, phenomena and characteristics, such as a) advective and dispersive transport of one or more contaminants, b) advective and dispersive transport and availability of electron acceptors, c) mass transfer limitations and d) spatial heterogeneities, at the larger scale and applying well defined lab scale parameters should accurately describe field scale processes.

Estimation of regional differences in wind erosion sensitivity in Hungary

NASA Astrophysics Data System (ADS)

Mezősi, G.; Blanka, V.; Bata, T.; Kovács, F.; Meyer, B.

2015-01-01

In Hungary, wind erosion is one of the most serious natural hazards. Spatial and temporal variation in the factors that determine the location and intensity of wind erosion damage are not well known, nor are the regional and local sensitivities to erosion. Because of methodological challenges, no multi-factor, regional wind erosion sensitivity map is available for Hungary. The aim of this study was to develop a method to estimate the regional differences in wind erosion sensitivity and exposure in Hungary. Wind erosion sensitivity was modelled using the key factors of soil sensitivity, vegetation cover and wind erodibility as proxies. These factors were first estimated separately by factor sensitivity maps and later combined by fuzzy logic into a regional-scale wind erosion sensitivity map. Large areas were evaluated by using publicly available data sets of remotely sensed vegetation information, soil maps and meteorological data on wind speed. The resulting estimates were verified by field studies and examining the economic losses from wind erosion as compensated by the state insurance company. The spatial resolution of the resulting sensitivity map is suitable for regional applications, as identifying sensitive areas is the foundation for diverse land development control measures and implementing management activities.

Estimation of cortical magnification from positional error in normally sighted and amblyopic subjects

PubMed Central

Hussain, Zahra; Svensson, Carl-Magnus; Besle, Julien; Webb, Ben S.; Barrett, Brendan T.; McGraw, Paul V.

2015-01-01

We describe a method for deriving the linear cortical magnification factor from positional error across the visual field. We compared magnification obtained from this method between normally sighted individuals and amblyopic individuals, who receive atypical visual input during development. The cortical magnification factor was derived for each subject from positional error at 32 locations in the visual field, using an established model of conformal mapping between retinal and cortical coordinates. Magnification of the normally sighted group matched estimates from previous physiological and neuroimaging studies in humans, confirming the validity of the approach. The estimate of magnification for the amblyopic group was significantly lower than the normal group: by 4.4 mm deg−1 at 1° eccentricity, assuming a constant scaling factor for both groups. These estimates, if correct, suggest a role for early visual experience in establishing retinotopic mapping in cortex. We discuss the implications of altered cortical magnification for cortical size, and consider other neural changes that may account for the amblyopic results. PMID:25761341

Effects of tree-to-tree variations on sap flux-based transpiration estimates in a forested watershed

NASA Astrophysics Data System (ADS)

Kume, Tomonori; Tsuruta, Kenji; Komatsu, Hikaru; Kumagai, Tomo'omi; Higashi, Naoko; Shinohara, Yoshinori; Otsuki, Kyoichi

2010-05-01

To estimate forest stand-scale water use, we assessed how sample sizes affect confidence of stand-scale transpiration (E) estimates calculated from sap flux (Fd) and sapwood area (AS_tree) measurements of individual trees. In a Japanese cypress plantation, we measured Fd and AS_tree in all trees (n = 58) within a 20 × 20 m study plot, which was divided into four 10 × 10 subplots. We calculated E from stand AS_tree (AS_stand) and mean stand Fd (JS) values. Using Monte Carlo analyses, we examined potential errors associated with sample sizes in E, AS_stand, and JS by using the original AS_tree and Fd data sets. Consequently, we defined optimal sample sizes of 10 and 15 for AS_stand and JS estimates, respectively, in the 20 × 20 m plot. Sample sizes greater than the optimal sample sizes did not decrease potential errors. The optimal sample sizes for JS changed according to plot size (e.g., 10 × 10 m and 10 × 20 m), while the optimal sample sizes for AS_stand did not. As well, the optimal sample sizes for JS did not change in different vapor pressure deficit conditions. In terms of E estimates, these results suggest that the tree-to-tree variations in Fd vary among different plots, and that plot size to capture tree-to-tree variations in Fd is an important factor. This study also discusses planning balanced sampling designs to extrapolate stand-scale estimates to catchment-scale estimates.

Quantifying the uncertainties of China's emission inventory for industrial sources: From national to provincial and city scales

NASA Astrophysics Data System (ADS)

Zhao, Yu; Zhou, Yaduan; Qiu, Liping; Zhang, Jie

2017-09-01

A comprehensive uncertainty analysis was conducted on emission inventories for industrial sources at national (China), provincial (Jiangsu), and city (Nanjing) scales for 2012. Based on various methods and data sources, Monte-Carlo simulation was applied at sector level for national inventory, and at plant level (whenever possible) for provincial and city inventories. The uncertainties of national inventory were estimated at -17-37% (expressed as 95% confidence intervals, CIs), -21-35%, -19-34%, -29-40%, -22-47%, -21-54%, -33-84%, and -32-92% for SO2, NOX, CO, TSP (total suspended particles), PM10, PM2.5, black carbon (BC), and organic carbon (OC) emissions respectively for the whole country. At provincial and city levels, the uncertainties of corresponding pollutant emissions were estimated at -15-18%, -18-33%, -16-37%, -20-30%, -23-45%, -26-50%, -33-79%, and -33-71% for Jiangsu, and -17-22%, -10-33%, -23-75%, -19-36%, -23-41%, -28-48%, -45-82%, and -34-96% for Nanjing, respectively. Emission factors (or associated parameters) were identified as the biggest contributors to the uncertainties of emissions for most source categories except iron & steel production in the national inventory. Compared to national one, uncertainties of total emissions in the provincial and city-scale inventories were not significantly reduced for most species with an exception of SO2. For power and other industrial boilers, the uncertainties were reduced, and the plant-specific parameters played more important roles to the uncertainties. Much larger PM10 and PM2.5 emissions for Jiangsu were estimated in this provincial inventory than other studies, implying the big discrepancies on data sources of emission factors and activity data between local and national inventories. Although the uncertainty analysis of bottom-up emission inventories at national and local scales partly supported the ;top-down; estimates using observation and/or chemistry transport models, detailed investigations and field measurements were recommended for further improving the emission estimates and reducing the uncertainty of inventories at local and regional scales, for both industrial and other sectors.

[Adaptation and validation of scales to measure self-efficacy and empowerment for self-care in Mexican climacteric stage women].

PubMed

Doubova, Svetlana V; Espinosa-Alarcón, Patricia; Infante, Claudia; Aguirre-Hernández, Rebeca; Rodríguez-Aguilar, Leticia; Olivares-Santos, Roberto; Pérez-Cuevas, Ricardo

2013-01-01

To adapt and validate in Spanish of Mexico scales to measure self-efficacy (SES) and empowerment for self-care (ES) among climacteric women. The study was conducted from February to July 2011 in two family medicine clinics in Mexico City. The adaptation phase was done through testing for language comprehension. To validate the scales we used the principal Axis factoring analysis with oblique rotation technique and estimation of Cronbach's alpha (CA). Three hundred eighty women aged 45-59 years participated in the study. SES had 16 items with four factors: participation in the doctor-patient relationship; in the study control of mental health and sexual changes; risk of dying from cancer, and other health risks that explained 39.8% of the variability, CA = 0.84. ES had eight items with one factor explaining 47.1% variability; CA = 0.83. Both scales had acceptable psychometric properties and are suitable for interventions aimed at improving self-care of climacteric women.

BME Estimation of Residential Exposure to Ambient PM10 and Ozone at Multiple Time Scales

PubMed Central

Yu, Hwa-Lung; Chen, Jiu-Chiuan; Christakos, George; Jerrett, Michael

2009-01-01

Background Long-term human exposure to ambient pollutants can be an important contributing or etiologic factor of many chronic diseases. Spatiotemporal estimation (mapping) of long-term exposure at residential areas based on field observations recorded in the U.S. Environmental Protection Agency’s Air Quality System often suffer from missing data issues due to the scarce monitoring network across space and the inconsistent recording periods at different monitors. Objective We developed and compared two upscaling methods: UM1 (data aggregation followed by exposure estimation) and UM2 (exposure estimation followed by data aggregation) for the long-term PM10 (particulate matter with aerodynamic diameter ≤ 10 μm) and ozone exposure estimations and applied them in multiple time scales to estimate PM and ozone exposures for the residential areas of the Health Effects of Air Pollution on Lupus (HEAPL) study. Method We used Bayesian maximum entropy (BME) analysis for the two upscaling methods. We performed spatiotemporal cross-validations at multiple time scales by UM1 and UM2 to assess the estimation accuracy across space and time. Results Compared with the kriging method, the integration of soft information by the BME method can effectively increase the estimation accuracy for both pollutants. The spatiotemporal distributions of estimation errors from UM1 and UM2 were similar. The cross-validation results indicated that UM2 is generally better than UM1 in exposure estimations at multiple time scales in terms of predictive accuracy and lack of bias. For yearly PM10 estimations, both approaches have comparable performance, but the implementation of UM1 is associated with much lower computation burden. Conclusion BME-based upscaling methods UM1 and UM2 can assimilate core and site-specific knowledge bases of different formats for long-term exposure estimation. This study shows that UM1 can perform reasonably well when the aggregation process does not alter the spatiotemporal structure of the original data set; otherwise, UM2 is preferable. PMID:19440491

Characterizing Macro Scale Patterns Of Uncertainty For Improved Operational Flood Forecasting Over The Conterminous United States

NASA Astrophysics Data System (ADS)

Vergara, H. J.; Kirstetter, P.; Gourley, J. J.; Flamig, Z.; Hong, Y.

2015-12-01

The macro scale patterns of simulated streamflow errors are studied in order to characterize uncertainty in a hydrologic modeling system forced with the Multi-Radar/Multi-Sensor (MRMS; http://mrms.ou.edu) quantitative precipitation estimates for flood forecasting over the Conterminous United States (CONUS). The hydrologic model is centerpiece of the Flooded Locations And Simulated Hydrograph (FLASH; http://flash.ou.edu) real-time system. The hydrologic model is implemented at 1-km/5-min resolution to generate estimates of streamflow. Data from the CONUS-wide stream gauge network of the United States' Geological Survey (USGS) were used as a reference to evaluate the discrepancies with the hydrological model predictions. Streamflow errors were studied at the event scale with particular focus on the peak flow magnitude and timing. A total of 2,680 catchments over CONUS and 75,496 events from a 10-year period are used for the simulation diagnostic analysis. Associations between streamflow errors and geophysical factors were explored and modeled. It is found that hydro-climatic factors and radar coverage could explain significant underestimation of peak flow in regions of complex terrain. Furthermore, the statistical modeling of peak flow errors shows that other geophysical factors such as basin geomorphometry, pedology, and land cover/use could also provide explanatory information. Results from this research demonstrate the utility of uncertainty characterization in providing guidance to improve model adequacy, parameter estimates, and input quality control. Likewise, the characterization of uncertainty enables probabilistic flood forecasting that can be extended to ungauged locations.

A New Lebanese Medication Adherence Scale: Validation in Lebanese Hypertensive Adults

PubMed Central

Wakim, N.; Issa, C.; Kassem, B.; Abou Jaoude, L.; Saleh, N.

2018-01-01

Background A new Lebanese scale measuring medication adherence considered socioeconomic and cultural factors not taken into account by the eight-item Morisky Medication Adherence Scale (MMAS-8). Objectives were to validate the new adherence scale and its prediction of hypertension control, compared to MMAS-8, and to assess adherence rates and factors. Methodology A cross-sectional study, including 405 patients, was performed in outpatient cardiology clinics of three hospitals in Beirut. Blood pressure was measured, a questionnaire filled, and sodium intake estimated by a urine test. Logistic regression defined predictors of hypertension control and adherence. Results 54.9% had controlled hypertension. 82.4% were adherent by the new scale, which showed good internal consistency, adequate questions (KMO coefficient = 0.743), and four factors. It predicted hypertension control (OR = 1.217; p value = 0.003), unlike MMAS-8, but the scores were correlated (ICC average measure = 0.651; p value < 0.001). Stress and smoking predicted nonadherence. Conclusion This study elaborated a validated, practical, and useful tool measuring adherence to medications in Lebanese hypertensive patients. PMID:29887993

Modeling Global Biogenic Emission of Isoprene: Exploration of Model Drivers

NASA Technical Reports Server (NTRS)

Alexander, Susan E.; Potter, Christopher S.; Coughlan, Joseph C.; Klooster, Steven A.; Lerdau, Manuel T.; Chatfield, Robert B.; Peterson, David L. (Technical Monitor)

1996-01-01

Vegetation provides the major source of isoprene emission to the atmosphere. We present a modeling approach to estimate global biogenic isoprene emission. The isoprene flux model is linked to a process-based computer simulation model of biogenic trace-gas fluxes that operates on scales that link regional and global data sets and ecosystem nutrient transformations Isoprene emission estimates are determined from estimates of ecosystem specific biomass, emission factors, and algorithms based on light and temperature. Our approach differs from an existing modeling framework by including the process-based global model for terrestrial ecosystem production, satellite derived ecosystem classification, and isoprene emission measurements from a tropical deciduous forest. We explore the sensitivity of model estimates to input parameters. The resulting emission products from the global 1 degree x 1 degree coverage provided by the satellite datasets and the process model allow flux estimations across large spatial scales and enable direct linkage to atmospheric models of trace-gas transport and transformation.

Clinimetric Testing of the Comprehensive Cervical Dystonia Rating Scale

PubMed Central

Comella, C. L.; Perlmutter, J.S.; Jinnah, H. A.; Waliczek, T. A.; Rosen, A. R.; Galpern, W. R.; Adler, C. H.; Barbano, R. L.; Factor, S. A.; Goetz, C.G.; Jankovic, J.; Reich, S. G.; Rodriguez, R. L.; Severt, W. L.; Zurowski, M.; Fox, S. H.; Stebbins, G.T.

2016-01-01

Objective To test the clinimetric properties of the Comprehensive Cervical Dystonia Rating Scale. Background This is a modular scale with modifications of the Toronto Western Spasmodic Torticollis Rating Scale (composed of three subscales assessing motor severity, disability and pain) now referred to as the revised Toronto Western Spasmodic Torticollis Scale-2.; a newly developed psychiatric screening instrument; and the Cervical Dystonia Impact Profile-58 as a quality of life measure. Methods Ten dystonia experts rated subjects with cervical dystonia using the comprehensive scale. Clinimetric techniques assessed each module of the scale for reliability, item correlation and factor structure. Results There were 208 cervical dystonia patients (73% women, age 59±10 years, duration 15±12 years). The internal consistency of the motor severity subscale was acceptable (Cronbach’s alpha = 0.57). Item to total correlations showed that elimination of items with low correlations (<0.20) increased alpha to 0.71. Internal consistency estimates for the subscales for disability and pain were 0.88 and 0.95 respectively. The psychiatric screening scale had a Cronbach’s alpha of 0.84 and satisfactory item to total correlations. When the subscales of the Toronto Western Spasmodic Torticollis scale -2 were combined with the psychiatric screening scale, Cronbach's alpha was 0.88, and construct validity assessment demonstrated four rational factors: motor, disability, pain and psychiatric disorders. The Cervical Dystonia Impact Profile-58 had an alpha of 0.98 and its construction was validated through a confirmatory factor analysis. Conclusions The modules of the Comprehensive Cervical Dystonia Rating Scale are internally consistent with a logical factor structure. PMID:26971359

The effects of geology and the impact of seasonal correction factors on indoor radon levels: a case study approach.

PubMed

Gillmore, Gavin K; Phillips, Paul S; Denman, Antony R

2005-01-01

Geology has been highlighted by a number of authors as a key factor in high indoor radon levels. In the light of this, this study examines the application of seasonal correction factors to indoor radon concentrations in the UK. This practice is based on an extensive database gathered by the National Radiological Protection Board over the years (small-scale surveys began in 1976 and continued with a larger scale survey in 1988) and reflects well known seasonal variations observed in indoor radon levels. However, due to the complexity of underlying geology (the UK arguably has the world's most complex solid and surficial geology over the shortest distances) and considerable variations in permeability of underlying materials it is clear that there are a significant number of occurrences where the application of a seasonal correction factor may give rise to over-estimated or under-estimated radon levels. Therefore, the practice of applying a seasonal correction should be one that is undertaken with caution, or not at all. This work is based on case studies taken from the Northamptonshire region and comparisons made to other permeable geologies in the UK.

Influence of catastrophizing, anxiety, and depression on in-hospital opioid consumption, pain, and quality of recovery after adult spine surgery

PubMed Central

Dunn, Lauren K.; Durieux, Marcel E.; Fernández, Lucas G.; Tsang, Siny; Smith-Straesser, Emily E.; Jhaveri, Hasan F.; Spanos, Shauna P.; Thames, Matthew R.; Spencer, Christopher D.; Lloyd, Aaron; Stuart, Russell; Ye, Fan; Bray, Jacob P.; Nemergut, Edward C.; Naik, Bhiken I.

2018-01-01

OBJECTIVE Perception of perioperative pain is influenced by various psychological factors. The aim of this study was to determine the impact of catastrophizing, anxiety, and depression on in-hospital opioid consumption, pain scores, and quality of recovery in adults who underwent spine surgery. METHODS Patients undergoing spine surgery were enrolled in this study, and the preoperatively completed questionnaires included the verbal rating scale (VRS), Pain Catastrophizing Scale (PCS), Hospital Anxiety and Depression Scale (HADS), and Oswestry Disability Index (ODI). Quality of recovery was assessed using the 40-item Quality of Recovery questionnaire (QoR40). Opioid consumption and pain scores according to the VRS were recorded daily until discharge. RESULTS One hundred thirty-nine patients were recruited for the study, and 101 completed the QoR40 assessment postoperatively. Patients with higher catastrophizing scores were more likely to have higher maximum pain scores postoperatively (estimate: 0.03, SE: 0.01, p = 0.02), without increased opioid use (estimate: 0.44, SE: 0.27, p = 0.11). Preoperative anxiety (estimate: 1.18, SE: 0.65, p = 0.07) and depression scores (estimate: 1.06, SE: 0.71, p = 0.14) did not correlate with increased postoperative opioid use; however, patients with higher preoperative depression scores had lower quality of recovery after surgery (estimate: −1.9, SE: 0.56, p < 0.001). CONCLUSIONS Catastrophizing, anxiety, and depression play important roles in modulating postoperative pain. Preoperative evaluation of these factors, utilizing a validated tool, helps to identify patients at risk. This might allow for earlier psychological intervention that could reduce pain severity and improve the quality of recovery. PMID:29125426

Introducing English and German versions of the Adolescent Time Attitude Scale.

PubMed

Worrell, Frank C; Mello, Zena R; Buhl, Monika

2013-08-01

In this study, the authors report on the development of English and German versions of the Adolescent Time Attitude Scale (ATAS). The ATAS consists of six subscales assessing Past Positive, Past Negative, Present Positive, Present Negative, Future Positive, and Future Negative time attitudes. The authors describe the development of the scales and present data on the reliability and structural validity of ATAS scores in samples of American (N = 300) and German (N = 316) adolescents. Internal consistency estimates for scores on the English and German versions of the ATAS were in the .70 to .80 range. Confirmatory factor analyses indicated that a six-factor structure yielded the best fit for scores and that the scores were invariant across samples.

An evaluation of sex-age-kill (SAK) model performance

USGS Publications Warehouse

Millspaugh, Joshua J.; Skalski, John R.; Townsend, Richard L.; Diefenbach, Duane R.; Boyce, Mark S.; Hansen, Lonnie P.; Kammermeyer, Kent

2009-01-01

The sex-age-kill (SAK) model is widely used to estimate abundance of harvested large mammals, including white-tailed deer (Odocoileus virginianus). Despite a long history of use, few formal evaluations of SAK performance exist. We investigated how violations of the stable age distribution and stationary population assumption, changes to male or female harvest, stochastic effects (i.e., random fluctuations in recruitment and survival), and sampling efforts influenced SAK estimation. When the simulated population had a stable age distribution and λ > 1, the SAK model underestimated abundance. Conversely, when λ < 1, the SAK overestimated abundance. When changes to male harvest were introduced, SAK estimates were opposite the true population trend. In contrast, SAK estimates were robust to changes in female harvest rates. Stochastic effects caused SAK estimates to fluctuate about their equilibrium abundance, but the effect dampened as the size of the surveyed population increased. When we considered both stochastic effects and sampling error at a deer management unit scale the resultant abundance estimates were within ±121.9% of the true population level 95% of the time. These combined results demonstrate extreme sensitivity to model violations and scale of analysis. Without changes to model formulation, the SAK model will be biased when λ ≠ 1. Furthermore, any factor that alters the male harvest rate, such as changes to regulations or changes in hunter attitudes, will bias population estimates. Sex-age-kill estimates may be precise at large spatial scales, such as the state level, but less so at the individual management unit level. Alternative models, such as statistical age-at-harvest models, which require similar data types, might allow for more robust, broad-scale demographic assessments.

Improving Factor Score Estimation Through the Use of Observed Background Characteristics

PubMed Central

Curran, Patrick J.; Cole, Veronica; Bauer, Daniel J.; Hussong, Andrea M.; Gottfredson, Nisha

2016-01-01

A challenge facing nearly all studies in the psychological sciences is how to best combine multiple items into a valid and reliable score to be used in subsequent modelling. The most ubiquitous method is to compute a mean of items, but more contemporary approaches use various forms of latent score estimation. Regardless of approach, outside of large-scale testing applications, scoring models rarely include background characteristics to improve score quality. The current paper used a Monte Carlo simulation design to study score quality for different psychometric models that did and did not include covariates across levels of sample size, number of items, and degree of measurement invariance. The inclusion of covariates improved score quality for nearly all design factors, and in no case did the covariates degrade score quality relative to not considering the influences at all. Results suggest that the inclusion of observed covariates can improve factor score estimation. PMID:28757790

An investigation of spectral change as influenced by irrigation and evapotranspiration volume estimation in western Nebraska

USGS Publications Warehouse

Seevers, P.M.; Sadowski, F.C.; Lauer, D.T.

1990-01-01

Retrospective satellite image data were evaluated for their ability to demonstrate the influence of center-pivot irrigation development in western Nebraska on spectral change and climate-related factors for the region. Periodic images of an albedo index and a normalized difference vegetation index (NDVI) were generated from calibrated Landsat multispectral scanner (MSS) data and used to monitor spectral changes associated with irrigation development from 1972 through 1986. The albedo index was not useful for monitoring irrigation development. For the NDVI, it was found that proportions of counties in irrigated agriculture, as discriminated by a threshold, were more highly correlated with reported ground estimates of irrigated agriculture than were county mean greenness values. A similar result was achieved when using coarse resolution Advanced Very High Resolution Radiometer (AVHRR) image data for estimating irrigated agriculture. The NDVI images were used to evaluate a procedure for making areal estimates of actual evapotranspiration (ET) volumes. Estimates of ET volumes for test counties, using reported ground acreages and corresponding standard crop coefficients, were correlated with the estimates of ET volume using crop coefficients scaled to NDVI values and pixel counts of crop areas. These county estimates were made under the assumption that soil water availability was unlimited. For nonirrigated vegetation, this may result in over-estimation of ET volumes. Ground information regarding crop types and acreages are required to derive the NDVI scaling factor. Potential ET, estimated with the Jensen-Haise model, is common to both methods. These results, achieved with both MSS and AVHRR data, show promise for providing climatologically important land surface information for regional and global climate models. ?? 1990 Kluwer Academic Publishers.

The Rosenberg Self-Esteem Scale: a bifactor answer to a two-factor question?

PubMed

McKay, Michael T; Boduszek, Daniel; Harvey, Séamus A

2014-01-01

Despite its long-standing and widespread use, disagreement remains regarding the structure of the Rosenberg Self-Esteem Scale (RSES). In particular, concern remains regarding the degree to which the scale assesses self-esteem as a unidimensional or multidimensional (positive and negative self-esteem) construct. Using a sample of 3,862 high school students in the United Kingdom, 4 models were tested: (a) a unidimensional model, (b) a correlated 2-factor model in which the 2 latent variables are represented by positive and negative self-esteem, (c) a hierarchical model, and (d) a bifactor model. The totality of results including item loadings, goodness-of-fit indexes, reliability estimates, and correlations with self-efficacy measures all supported the bifactor model, suggesting that the 2 hypothesized factors are better understood as "grouping" factors rather than as representative of latent constructs. Accordingly, this study supports the unidimensionality of the RSES and the scoring of all 10 items to produce a global self-esteem score.

OARE flight maneuvers and calibration measurements on STS-58

NASA Technical Reports Server (NTRS)

Blanchard, Robert C.; Nicholson, John Y.; Ritter, James R.; Larman, Kevin T.

1994-01-01

The Orbital Acceleration Research Experiment (OARE), which has flown on STS-40, STS-50, and STS-58, contains a three axis accelerometer with a single, nonpendulous, electrostatically suspended proofmass which can resolve accelerations to the nano-g level. The experiment also contains a full calibration station to permit in situ bias and scale factor calibration. This on-orbit calibration capability eliminates the large uncertainty of ground-based calibrations encountered with accelerometers flown in the past on the orbiter, thus providing absolute acceleration measurement accuracy heretofore unachievable. This is the first time accelerometer scale factor measurements have been performed on orbit. A detailed analysis of the calibration process is given along with results of the calibration factors from the on-orbit OARE flight measurements on STS-58. In addition, the analysis of OARE flight maneuver data used to validate the scale factor measurements in the sensor's most sensitive range is also presented. Estimates on calibration uncertainties are discussed. This provides bounds on the STS-58 absolute acceleration measurements for future applications.

Accuracy improvement in laser stripe extraction for large-scale triangulation scanning measurement system

NASA Astrophysics Data System (ADS)

Zhang, Yang; Liu, Wei; Li, Xiaodong; Yang, Fan; Gao, Peng; Jia, Zhenyuan

2015-10-01

Large-scale triangulation scanning measurement systems are widely used to measure the three-dimensional profile of large-scale components and parts. The accuracy and speed of the laser stripe center extraction are essential for guaranteeing the accuracy and efficiency of the measuring system. However, in the process of large-scale measurement, multiple factors can cause deviation of the laser stripe center, including the spatial light intensity distribution, material reflectivity characteristics, and spatial transmission characteristics. A center extraction method is proposed for improving the accuracy of the laser stripe center extraction based on image evaluation of Gaussian fitting structural similarity and analysis of the multiple source factors. First, according to the features of the gray distribution of the laser stripe, evaluation of the Gaussian fitting structural similarity is estimated to provide a threshold value for center compensation. Then using the relationships between the gray distribution of the laser stripe and the multiple source factors, a compensation method of center extraction is presented. Finally, measurement experiments for a large-scale aviation composite component are carried out. The experimental results for this specific implementation verify the feasibility of the proposed center extraction method and the improved accuracy for large-scale triangulation scanning measurements.

Direct system parameter identification of mechanical structures with application to modal analysis

NASA Technical Reports Server (NTRS)

Leuridan, J. M.; Brown, D. L.; Allemang, R. J.

1982-01-01

In this paper a method is described to estimate mechanical structure characteristics in terms of mass, stiffness and damping matrices using measured force input and response data. The estimated matrices can be used to calculate a consistent set of damped natural frequencies and damping values, mode shapes and modal scale factors for the structure. The proposed technique is attractive as an experimental modal analysis method since the estimation of the matrices does not require previous estimation of frequency responses and since the method can be used, without any additional complications, for multiple force input structure testing.

Compatibility check of measured aircraft responses using kinematic equations and extended Kalman filter

NASA Technical Reports Server (NTRS)

Klein, V.; Schiess, J. R.

1977-01-01

An extended Kalman filter smoother and a fixed point smoother were used for estimation of the state variables in the six degree of freedom kinematic equations relating measured aircraft responses and for estimation of unknown constant bias and scale factor errors in measured data. The computing algorithm includes an analysis of residuals which can improve the filter performance and provide estimates of measurement noise characteristics for some aircraft output variables. The technique developed was demonstrated using simulated and real flight test data. Improved accuracy of measured data was obtained when the data were corrected for estimated bias errors.

Integrating Breeding Bird Survey and demographic data to estimate Wood Duck population size in the Atlantic Flyway

USGS Publications Warehouse

Zimmerman, Guthrie S.; Sauer, John; Boomer, G. Scott; Devers, Patrick K.; Garrettson, Pamela R.

2017-01-01

The U.S. Fish and Wildlife Service (USFWS) uses data from the North American Breeding Bird Survey (BBS) to assist in monitoring and management of some migratory birds. However, BBS analyses provide indices of population change rather than estimates of population size, precluding their use in developing abundance-based objectives and limiting applicability to harvest management. Wood Ducks (Aix sponsa) are important harvested birds in the Atlantic Flyway (AF) that are difficult to detect during aerial surveys because they prefer forested habitat. We integrated Wood Duck count data from a ground-plot survey in the northeastern U.S. with AF-wide BBS, banding, parts collection, and harvest data to derive estimates of population size for the AF. Overlapping results between the smaller-scale intensive ground-plot survey and the BBS in the northeastern U.S. provided a means for scaling BBS indices to the breeding population size estimates. We applied these scaling factors to BBS results for portions of the AF lacking intensive surveys. Banding data provided estimates of annual survival and harvest rates; the latter, when combined with parts-collection data, provided estimates of recruitment. We used the harvest data to estimate fall population size. Our estimates of breeding population size and variability from the integrated population model (N̄ = 0.99 million, SD = 0.04) were similar to estimates of breeding population size based solely on data from the AF ground-plot surveys and the BBS (N̄ = 1.01 million, SD = 0.04) from 1998 to 2015. Integrating BBS data with other data provided reliable population size estimates for Wood Ducks at a scale useful for harvest and habitat management in the AF, and allowed us to derive estimates of important demographic parameters (e.g., seasonal survival rates, sex ratio) that were not directly informed by data.

Estimation of Rainfall Erosivity via 1-Minute to Hourly Rainfall Data from Taipei, Taiwan

NASA Astrophysics Data System (ADS)

Huang, Ting-Yin; Yang, Ssu-Yao; Jan, Chyan-Deng

2017-04-01

Soil erosion is a natural process on hillslopes that threats people's life and properties, having a considerable environmental and economic implications for soil degradation, agricultural activity and water quality. The rainfall erosivity factor (R-factor) in the Universal Soil Loss Equation (USLE), composed of total kinetic energy (E) and the maximum 30-min rainfall intensity (I30), is widely used as an indicator to measure the potential risks of soil loss caused by rainfall at a regional scale. This R factor can represent the detachment and entrainment involved in climate conditions on hillslopes, but lack of 30-min rainfall intensity data usually lead to apply this factor more difficult in many regions. In recent years, fixed-interval, hourly rainfall data is readily available and widely used due to the development of automatic weather stations. Here we assess the estimations of R, E, and I30 based on 1-, 5-, 10-, 15-, 30-, 60-minute rainfall data, and hourly rainfall data obtained from Taipei weather station during 2004 to 2010. Results show that there is a strong correlation among R-factors estimated from different interval rainfall data. Moreover, the shorter time-interval rainfall data (e.g., 1-min) yields larger value of R-factor. The conversion factors of rainfall erosivity (ratio of values estimated from the resolution lower than 30-min rainfall data to those estimated from 60-min and hourly rainfall data, respectively) range from 1.85 to 1.40 (resp. from 1.89 to 1.02) for 60-min (resp. hourly) rainfall data as the time resolution increasing from 30-min to 1-min. This paper provides useful information on estimating R-factor when hourly rainfall data is only available.

Odds per adjusted standard deviation: comparing strengths of associations for risk factors measured on different scales and across diseases and populations.

PubMed

Hopper, John L

2015-11-15

How can the "strengths" of risk factors, in the sense of how well they discriminate cases from controls, be compared when they are measured on different scales such as continuous, binary, and integer? Given that risk estimates take into account other fitted and design-related factors-and that is how risk gradients are interpreted-so should the presentation of risk gradients. Therefore, for each risk factor X0, I propose using appropriate regression techniques to derive from appropriate population data the best fitting relationship between the mean of X0 and all the other covariates fitted in the model or adjusted for by design (X1, X2, … , Xn). The odds per adjusted standard deviation (OPERA) presents the risk association for X0 in terms of the change in risk per s = standard deviation of X0 adjusted for X1, X2, … , Xn, rather than the unadjusted standard deviation of X0 itself. If the increased risk is relative risk (RR)-fold over A adjusted standard deviations, then OPERA = exp[ln(RR)/A] = RR(s). This unifying approach is illustrated by considering breast cancer and published risk estimates. OPERA estimates are by definition independent and can be used to compare the predictive strengths of risk factors across diseases and populations. © The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Complexity as a Factor of Quality and Cost in Large Scale Software Development.

DTIC Science & Technology

1979-12-01

allocating testing resources." [69 69I V. THE ROLE OF COMPLEXITY IN RESOURCE ESTIMATION AND ALLOCATION A. GENERAL It can be argued that blame for the...and allocation of testing resource by - identifying independent substructures and - identifying heavily used logic paths. 2. Setting a Design Threshold... RESOURCE ESTIMATION -------- 70 1. New Dynamic Field ------------------------- 70 2. Quality and Testing ----------------------- 71 3. Programming Units of

Large-area Soil Moisture Surveys Using a Cosmic-ray Rover: Approaches and Results from Australia

NASA Astrophysics Data System (ADS)

Hawdon, A. A.; McJannet, D. L.; Renzullo, L. J.; Baker, B.; Searle, R.

2017-12-01

Recent improvements in satellite instrumentation has increased the resolution and frequency of soil moisture observations, and this in turn has supported the development of higher resolution land surface process models. Calibration and validation of these products is restricted by the mismatch of scales between remotely sensed and contemporary ground based observations. Although the cosmic ray neutron soil moisture probe can provide estimates soil moisture at a scale useful for the calibration and validation purposes, it is spatially limited to a single, fixed location. This scaling issue has been addressed with the development of mobile soil moisture monitoring systems that utilizes the cosmic ray neutron method, typically referred to as a `rover'. This manuscript describes a project designed to develop approaches for undertaking rover surveys to produce soil moisture estimates at scales comparable to satellite observations and land surface process models. A custom designed, trailer-mounted rover was used to conduct repeat surveys at two scales in the Mallee region of Victoria, Australia. A broad scale survey was conducted at 36 x 36 km covering an area of a standard SMAP pixel and an intensive scale survey was conducted over a 10 x 10 km portion of the broad scale survey, which is at a scale equivalent to that used for national water balance modelling. We will describe the design of the rover, the methods used for converting neutron counts into soil moisture and discuss factors controlling soil moisture variability. We found that the intensive scale rover surveys produced reliable soil moisture estimates at 1 km resolution and the broad scale at 9 km resolution. We conclude that these products are well suited for future analysis of satellite soil moisture retrievals and finer scale soil moisture models.

Analysis of particulate emissions from tropical biomass burning using a global aerosol model and long-term surface observations

NASA Astrophysics Data System (ADS)

Reddington, Carly L.; Spracklen, Dominick V.; Artaxo, Paulo; Ridley, David A.; Rizzo, Luciana V.; Arana, Andrea

2016-09-01

We use the GLOMAP global aerosol model evaluated against observations of surface particulate matter (PM2.5) and aerosol optical depth (AOD) to better understand the impacts of biomass burning on tropical aerosol over the period 2003 to 2011. Previous studies report a large underestimation of AOD over regions impacted by tropical biomass burning, scaling particulate emissions from fire by up to a factor of 6 to enable the models to simulate observed AOD. To explore the uncertainty in emissions we use three satellite-derived fire emission datasets (GFED3, GFAS1 and FINN1). In these datasets the tropics account for 66-84 % of global particulate emissions from fire. With all emission datasets GLOMAP underestimates dry season PM2.5 concentrations in regions of high fire activity in South America and underestimates AOD over South America, Africa and Southeast Asia. When we assume an upper estimate of aerosol hygroscopicity, underestimation of AOD over tropical regions impacted by biomass burning is reduced relative to previous studies. Where coincident observations of surface PM2.5 and AOD are available we find a greater model underestimation of AOD than PM2.5, even when we assume an upper estimate of aerosol hygroscopicity. Increasing particulate emissions to improve simulation of AOD can therefore lead to overestimation of surface PM2.5 concentrations. We find that scaling FINN1 emissions by a factor of 1.5 prevents underestimation of AOD and surface PM2.5 in most tropical locations except Africa. GFAS1 requires emission scaling factor of 3.4 in most locations with the exception of equatorial Asia where a scaling factor of 1.5 is adequate. Scaling GFED3 emissions by a factor of 1.5 is sufficient in active deforestation regions of South America and equatorial Asia, but a larger scaling factor is required elsewhere. The model with GFED3 emissions poorly simulates observed seasonal variability in surface PM2.5 and AOD in regions where small fires dominate, providing independent evidence that GFED3 underestimates particulate emissions from small fires. Seasonal variability in both PM2.5 and AOD is better simulated by the model using FINN1 emissions. Detailed observations of aerosol properties over biomass burning regions are required to better constrain particulate emissions from fires.

Scaling in situ cosmogenic nuclide production rates using analytical approximations to atmospheric cosmic-ray fluxes

NASA Astrophysics Data System (ADS)

Lifton, Nathaniel; Sato, Tatsuhiko; Dunai, Tibor J.

2014-01-01

Several models have been proposed for scaling in situ cosmogenic nuclide production rates from the relatively few sites where they have been measured to other sites of interest. Two main types of models are recognized: (1) those based on data from nuclear disintegrations in photographic emulsions combined with various neutron detectors, and (2) those based largely on neutron monitor data. However, stubborn discrepancies between these model types have led to frequent confusion when calculating surface exposure ages from production rates derived from the models. To help resolve these discrepancies and identify the sources of potential biases in each model, we have developed a new scaling model based on analytical approximations to modeled fluxes of the main atmospheric cosmic-ray particles responsible for in situ cosmogenic nuclide production. Both the analytical formulations and the Monte Carlo model fluxes on which they are based agree well with measured atmospheric fluxes of neutrons, protons, and muons, indicating they can serve as a robust estimate of the atmospheric cosmic-ray flux based on first principles. We are also using updated records for quantifying temporal and spatial variability in geomagnetic and solar modulation effects on the fluxes. A key advantage of this new model (herein termed LSD) over previous Monte Carlo models of cosmogenic nuclide production is that it allows for faster estimation of scaling factors based on time-varying geomagnetic and solar inputs. Comparing scaling predictions derived from the LSD model with those of previously published models suggest potential sources of bias in the latter can be largely attributed to two factors: different energy responses of the secondary neutron detectors used in developing the models, and different geomagnetic parameterizations. Given that the LSD model generates flux spectra for each cosmic-ray particle of interest, it is also relatively straightforward to generate nuclide-specific scaling factors based on recently updated neutron and proton excitation functions (probability of nuclide production in a given nuclear reaction as a function of energy) for commonly measured in situ cosmogenic nuclides. Such scaling factors reflect the influence of the energy distribution of the flux folded with the relevant excitation functions. Resulting scaling factors indicate 3He shows the strongest positive deviation from the flux-based scaling, while 14C exhibits a negative deviation. These results are consistent with a recent Monte Carlo-based study using a different cosmic-ray physics code package but the same excitation functions.

Quantifying spatial scaling patterns and their local and regional correlates in headwater streams: Implications for resilience

USGS Publications Warehouse

Gothe, Emma; Sandin, Leonard; Allen, Craig R.; Angeler, David G.

2014-01-01

The distribution of functional traits within and across spatiotemporal scales has been used to quantify and infer the relative resilience across ecosystems. We use explicit spatial modeling to evaluate within- and cross-scale redundancy in headwater streams, an ecosystem type with a hierarchical and dendritic network structure. We assessed the cross-scale distribution of functional feeding groups of benthic invertebrates in Swedish headwater streams during two seasons. We evaluated functional metrics, i.e., Shannon diversity, richness, and evenness, and the degree of redundancy within and across modeled spatial scales for individual feeding groups. We also estimated the correlates of environmental versus spatial factors of both functional composition and the taxonomic composition of functional groups for each spatial scale identified. Measures of functional diversity and within-scale redundancy of functions were similar during both seasons, but both within- and cross-scale redundancy were low. This apparent low redundancy was partly attributable to a few dominant taxa explaining the spatial models. However, rare taxa with stochastic spatial distributions might provide additional information and should therefore be considered explicitly for complementing future resilience assessments. Otherwise, resilience may be underestimated. Finally, both environmental and spatial factors correlated with the scale-specific functional and taxonomic composition. This finding suggests that resilience in stream networks emerges as a function of not only local conditions but also regional factors such as habitat connectivity and invertebrate dispersal.

Identifying correlates of self-stigma in adults who stutter: Further establishing the construct validity of the Self-Stigma of Stuttering Scale (4S).

PubMed

Boyle, Michael P

2015-03-01

This study was set up to further establish the construct validity of the Self-Stigma of Stuttering Scale (4S) by demonstrating its associations with other established scales and replicating its original factor structure and reliability estimates. Web surveys were completed by 354 adults who stutter recruited from Board Certified Specialists in Fluency Disorders, and adult chapters of the National Stuttering Association. Participants completed a series of psychometrically validated scales measuring self-stigma, hope, empowerment, quality of life, social support, anxiety, depression, and self-rated speech disruption. Higher subscale and total stigma scores on the 4S were associated with significantly lower levels of hope, empowerment, quality of life, and social support, and significantly higher levels of anxiety, depression, and self-rated speech disruption. The original factor structure of the 4S was replicated, and reliability estimates of the subscales ranged from adequate to excellent. The findings of this study support the construct validity of the 4S and its use by clinicians and researchers intending to measure the construct of self-stigma in adults who stutter. Readers should be able to: (a) distinguish between the various components of self-stigma; (b) describe how the various components of the self-stigma model relate to hope, empowerment, quality of life, and social support, self-rated speech disruption, anxiety, and depression; (c) summarize the psychometric properties of the Self-Stigma of Stuttering Scale (4S) in terms of reliability, factor structure, and construct validity; (d) discuss how the 4S could be used in research and clinical practice. Copyright © 2015 Elsevier Inc. All rights reserved.

Iterative initial condition reconstruction

NASA Astrophysics Data System (ADS)

Schmittfull, Marcel; Baldauf, Tobias; Zaldarriaga, Matias

2017-07-01

Motivated by recent developments in perturbative calculations of the nonlinear evolution of large-scale structure, we present an iterative algorithm to reconstruct the initial conditions in a given volume starting from the dark matter distribution in real space. In our algorithm, objects are first moved back iteratively along estimated potential gradients, with a progressively reduced smoothing scale, until a nearly uniform catalog is obtained. The linear initial density is then estimated as the divergence of the cumulative displacement, with an optional second-order correction. This algorithm should undo nonlinear effects up to one-loop order, including the higher-order infrared resummation piece. We test the method using dark matter simulations in real space. At redshift z =0 , we find that after eight iterations the reconstructed density is more than 95% correlated with the initial density at k ≤0.35 h Mpc-1 . The reconstruction also reduces the power in the difference between reconstructed and initial fields by more than 2 orders of magnitude at k ≤0.2 h Mpc-1 , and it extends the range of scales where the full broadband shape of the power spectrum matches linear theory by a factor of 2-3. As a specific application, we consider measurements of the baryonic acoustic oscillation (BAO) scale that can be improved by reducing the degradation effects of large-scale flows. In our idealized dark matter simulations, the method improves the BAO signal-to-noise ratio by a factor of 2.7 at z =0 and by a factor of 2.5 at z =0.6 , improving standard BAO reconstruction by 70% at z =0 and 30% at z =0.6 , and matching the optimal BAO signal and signal-to-noise ratio of the linear density in the same volume. For BAO, the iterative nature of the reconstruction is the most important aspect.

A Multi-Scale Distribution Model for Non-Equilibrium Populations Suggests Resource Limitation in an Endangered Rodent

PubMed Central

Bean, William T.; Stafford, Robert; Butterfield, H. Scott; Brashares, Justin S.

2014-01-01

Species distributions are known to be limited by biotic and abiotic factors at multiple temporal and spatial scales. Species distribution models, however, frequently assume a population at equilibrium in both time and space. Studies of habitat selection have repeatedly shown the difficulty of estimating resource selection if the scale or extent of analysis is incorrect. Here, we present a multi-step approach to estimate the realized and potential distribution of the endangered giant kangaroo rat. First, we estimate the potential distribution by modeling suitability at a range-wide scale using static bioclimatic variables. We then examine annual changes in extent at a population-level. We define “available” habitat based on the total suitable potential distribution at the range-wide scale. Then, within the available habitat, model changes in population extent driven by multiple measures of resource availability. By modeling distributions for a population with robust estimates of population extent through time, and ecologically relevant predictor variables, we improved the predictive ability of SDMs, as well as revealed an unanticipated relationship between population extent and precipitation at multiple scales. At a range-wide scale, the best model indicated the giant kangaroo rat was limited to areas that received little to no precipitation in the summer months. In contrast, the best model for shorter time scales showed a positive relation with resource abundance, driven by precipitation, in the current and previous year. These results suggest that the distribution of the giant kangaroo rat was limited to the wettest parts of the drier areas within the study region. This multi-step approach reinforces the differing relationship species may have with environmental variables at different scales, provides a novel method for defining “available” habitat in habitat selection studies, and suggests a way to create distribution models at spatial and temporal scales relevant to theoretical and applied ecologists. PMID:25237807

Brazilian infant motor and cognitive development: Longitudinal influence of risk factors.

PubMed

Pereira, Keila Rg; Valentini, Nadia C; Saccani, Raquel

2016-12-01

Infant developmental delays have been associated with several risk factors, such as familial environmental, individual and demographic characteristics. The goal of this study was to longitudinally investigate the effects of maternal knowledge and practices, home environment and biological factors on infant motor and cognitive outcomes. This was a prospective cohort study with a sample of 49 infants from Southern Brazil. The infants were assessed three times over 4 months using the Alberta Infant Motor Scale and the Bayley Scale of Infant Development (Mental Development Scale). Parents completed the Daily Activities Scale of Infants, the Affordances in The Home Environment for Motor Development - Infant Scale, the Knowledge of Infant Development Inventory and a demographic questionnaire. Generalized estimating equation with Bonferroni method as the follow-up test and Spearman correlation and multivariate linear backward regression were used. Cognitive and motor scores were strongly associated longitudinally and increased over time. Associations between the home affordances, parental practices and knowledge, and motor and cognitive development over time were observed. This relationship explained more variability in motor and cognitive scores compared with biological factors. Variability in motor and cognitive development is better explained by environment and parental knowledge and practice. The investigation of factors associated with infant development allows the identification of infants at risk and the implementation of educational programs and parental training to minimize the effects of developmental delay. © 2016 Japan Pediatric Society.

Investigating different filter and rescaling methods on simulated GRACE-like TWS variations for hydrological applications

NASA Astrophysics Data System (ADS)

Zhang, Liangjing; Dobslaw, Henryk; Dahle, Christoph; Thomas, Maik; Neumayer, Karl-Hans; Flechtner, Frank

2017-04-01

By operating for more than one decade now, the GRACE satellite provides valuable information on the total water storage (TWS) for hydrological and hydro-meteorological applications. The increasing interest in use of the GRACE-based TWS requires an in-depth assessment of the reliability of the outputs and also its uncertainties. Through years of development, different post-processing methods have been suggested for TWS estimation. However, since GRACE offers an unique way to provide high spatial and temporal scale TWS, there is no global ground truth data available to fully validate the results. In this contribution, we re-assess a number of commonly used post-processing methods using a simulated GRACE-type gravity field time-series based on realistic orbits and instrument error assumptions as well as background error assumptions out of the updated ESA Earth System Model. Three non-isotropic filter methods from Kusche (2007) and a combined filter from DDK1 and DDK3 based on the ground tracks are tested. Rescaling factors estimated from five different hydrological models and the ensemble median are applied to the post-processed simulated GRACE-type TWS estimates to correct the bias and leakage. Time variant rescaling factors as monthly scaling factors and scaling factors for seasonal and long-term variations separately are investigated as well. Since TWS anomalies out of the post-processed simulation results can be readily compared to the time-variable Earth System Model initially used as "truth" during the forward simulation step, we are able to thoroughly check the plausibility of our error estimation assessment (Zhang et al., 2016) and will subsequently recommend a processing strategy that shall also be applied for planned GRACE and GRACE-FO Level-3 products for terrestrial applications provided by GFZ. Kusche, J., 2007:Approximate decorrelation and non-isotropic smoothing of time-variable GRACE-type gravity field models. J. Geodesy, 81 (11), 733-749, doi:10.1007/s00190-007-0143-3. Zhang L, Dobslaw H, Thomas M (2016) Globally gridded terrestrial water storage variations from GRACE satellite gravimetry for hydrometeorological applications. Geophysical Journal International 206(1):368-378, DOI 10.1093/gji/ggw153.

Estimating large carnivore populations at global scale based on spatial predictions of density and distribution – Application to the jaguar (Panthera onca)

PubMed Central

Robinson, Hugh S.; Abarca, Maria; Zeller, Katherine A.; Velasquez, Grisel; Paemelaere, Evi A. D.; Goldberg, Joshua F.; Payan, Esteban; Hoogesteijn, Rafael; Boede, Ernesto O.; Schmidt, Krzysztof; Lampo, Margarita; Viloria, Ángel L.; Carreño, Rafael; Robinson, Nathaniel; Lukacs, Paul M.; Nowak, J. Joshua; Salom-Pérez, Roberto; Castañeda, Franklin; Boron, Valeria; Quigley, Howard

2018-01-01

Broad scale population estimates of declining species are desired for conservation efforts. However, for many secretive species including large carnivores, such estimates are often difficult. Based on published density estimates obtained through camera trapping, presence/absence data, and globally available predictive variables derived from satellite imagery, we modelled density and occurrence of a large carnivore, the jaguar, across the species’ entire range. We then combined these models in a hierarchical framework to estimate the total population. Our models indicate that potential jaguar density is best predicted by measures of primary productivity, with the highest densities in the most productive tropical habitats and a clear declining gradient with distance from the equator. Jaguar distribution, in contrast, is determined by the combined effects of human impacts and environmental factors: probability of jaguar occurrence increased with forest cover, mean temperature, and annual precipitation and declined with increases in human foot print index and human density. Probability of occurrence was also significantly higher for protected areas than outside of them. We estimated the world’s jaguar population at 173,000 (95% CI: 138,000–208,000) individuals, mostly concentrated in the Amazon Basin; elsewhere, populations tend to be small and fragmented. The high number of jaguars results from the large total area still occupied (almost 9 million km2) and low human densities (< 1 person/km2) coinciding with high primary productivity in the core area of jaguar range. Our results show the importance of protected areas for jaguar persistence. We conclude that combining modelling of density and distribution can reveal ecological patterns and processes at global scales, can provide robust estimates for use in species assessments, and can guide broad-scale conservation actions. PMID:29579129

Asynchrony in the inter-annual recruitment of lake whitefish Coregonus clupeaformis in the Great Lakes region

USGS Publications Warehouse

Zischke, Mitchell T.; Bunnell, David B.; Troy, Cary D.; Berglund, Eric K.; Caroffino, David C.; Ebener, Mark P.; He, Ji X.; Sitar, Shawn P.; Hook, Tomas O.

2017-01-01

Spatially separated fish populations may display synchrony in annual recruitment if the factors that drive recruitment success, particularly abiotic factors such as temperature, are synchronised across broad spatial scales. We examined inter-annual variation in recruitment among lake whitefish (Coregonus clupeaformis) populations in lakes Huron, Michigan and Superior using fishery-dependent and -independent data from 1971 to 2014. Relative year-class strength (RYCS) was calculated from catch-curve residuals for each year class across multiple sampling years. Pairwise comparison of RYCS among datasets revealed no significant associations either within or between lakes, suggesting that recruitment of lake whitefish is spatially asynchronous. There was no consistent correlation between pairwise agreement and the distance between datasets, and models to estimate the spatial scale of recruitment synchrony did not fit well to these data. This suggests that inter-annual recruitment variation of lake whitefish is asynchronous across broad spatial scales in the Great Lakes. While our method primarily evaluated year-to-year recruitment variation, it is plausible that recruitment of lake whitefish varies at coarser temporal scales (e.g. decadal). Nonetheless, our findings differ from research on some other Coregonus species and suggest that local biotic or density-dependent factors may contribute strongly to lake whitefish recruitment rather than inter-annual variability in broad-scale abiotic factors.

Algorithm of regional surface evaporation using remote sensing: A case study of Haihe basin, China

NASA Astrophysics Data System (ADS)

Xiong, Jun; Wu, Bingfang; Yan, Nana; Hu, Minggang

2007-11-01

Evapotranspiration (ET, or latent heat flux) is the most essential and uncertain factor in water resource management. Remote sensing is a promising tool for estimation of spatial distribution of ET at regional scale with limited ground observations. We developed an algorithm for estimating regional evapotranspiration from MODIS 1b data and ancillary meteorological data. The algorithm is an integration of Penman-Monteith equation and SEBS (Surface Energy Balance System) model. The former is a combination of the energy balance theory and the mass transfer method to compute the evaporation from cropped surfaces from standard climatological records of sunshine, temperature, humidity and wind speed by introducing resistance factors, and the latter determines the spatio-temporal variability of regional evaporative condition. First, we characterized key land surface parameters on satellite over passing days, including fractional vegetation cover (fc), roughness height for momentum (z0m), net radiation (Rn) and soil heat flux (G0); Second, SEBS was applied to partition the sensible heat (H) from latent heat (LE) in combination with Planetary Boundary Layer (PBL) information from seven meteorological stations. A parameterization of surface roughness was applied at mountainous area considering topographic influence; third, we chose available surface resistance (RS) as the temporal-scaling factor. With bulk surface resistance is properly defined, P-M methods is valid for both soil and vegetation canopy. We validated ET from this algorithm with limited actual observations of ET including 2 eddy covariance system dataset and 1 lysimeter sites. Water balance equation is used as a trend-analysis tool to show the consistency between rainfall and ET on four drainage area. As a result, the prototype products showed different accuracy and applicability on different underlying and time scale, which demonstrates the potential of this approach for estimating ET from 1-km to regional spatial scale in North China Plain.

Genome-scale rates of evolutionary change in bacteria

PubMed Central

Duchêne, Sebastian; Holt, Kathryn E.; Weill, François-Xavier; Le Hello, Simon; Hawkey, Jane; Edwards, David J.; Fourment, Mathieu

2016-01-01

Estimating the rates at which bacterial genomes evolve is critical to understanding major evolutionary and ecological processes such as disease emergence, long-term host–pathogen associations and short-term transmission patterns. The surge in bacterial genomic data sets provides a new opportunity to estimate these rates and reveal the factors that shape bacterial evolutionary dynamics. For many organisms estimates of evolutionary rate display an inverse association with the time-scale over which the data are sampled. However, this relationship remains unexplored in bacteria due to the difficulty in estimating genome-wide evolutionary rates, which are impacted by the extent of temporal structure in the data and the prevalence of recombination. We collected 36 whole genome sequence data sets from 16 species of bacterial pathogens to systematically estimate and compare their evolutionary rates and assess the extent of temporal structure in the absence of recombination. The majority (28/36) of data sets possessed sufficient clock-like structure to robustly estimate evolutionary rates. However, in some species reliable estimates were not possible even with ‘ancient DNA’ data sampled over many centuries, suggesting that they evolve very slowly or that they display extensive rate variation among lineages. The robustly estimated evolutionary rates spanned several orders of magnitude, from approximately 10−5 to 10−8 nucleotide substitutions per site year−1. This variation was negatively associated with sampling time, with this relationship best described by an exponential decay curve. To avoid potential estimation biases, such time-dependency should be considered when inferring evolutionary time-scales in bacteria. PMID:28348834

Biodegradation modelling of a dissolved gasoline plume applying independent laboratory and field parameters

NASA Astrophysics Data System (ADS)

Schirmer, Mario; Molson, John W.; Frind, Emil O.; Barker, James F.

2000-12-01

Biodegradation of organic contaminants in groundwater is a microscale process which is often observed on scales of 100s of metres or larger. Unfortunately, there are no known equivalent parameters for characterizing the biodegradation process at the macroscale as there are, for example, in the case of hydrodynamic dispersion. Zero- and first-order degradation rates estimated at the laboratory scale by model fitting generally overpredict the rate of biodegradation when applied to the field scale because limited electron acceptor availability and microbial growth are not considered. On the other hand, field-estimated zero- and first-order rates are often not suitable for predicting plume development because they may oversimplify or neglect several key field scale processes, phenomena and characteristics. This study uses the numerical model BIO3D to link the laboratory and field scales by applying laboratory-derived Monod kinetic degradation parameters to simulate a dissolved gasoline field experiment at the Canadian Forces Base (CFB) Borden. All input parameters were derived from independent laboratory and field measurements or taken from the literature a priori to the simulations. The simulated results match the experimental results reasonably well without model calibration. A sensitivity analysis on the most uncertain input parameters showed only a minor influence on the simulation results. Furthermore, it is shown that the flow field, the amount of electron acceptor (oxygen) available, and the Monod kinetic parameters have a significant influence on the simulated results. It is concluded that laboratory-derived Monod kinetic parameters can adequately describe field scale degradation, provided all controlling factors are incorporated in the field scale model. These factors include advective-dispersive transport of multiple contaminants and electron acceptors and large-scale spatial heterogeneities.

Simulation study of a geometric shape factor technique for estimating earth-emitted radiant flux densities from wide-field-of-view radiation measurements

NASA Technical Reports Server (NTRS)

Weaver, W. L.; Green, R. N.

1980-01-01

Geometric shape factors were computed and applied to satellite simulated irradiance measurements to estimate Earth emitted flux densities for global and zonal scales and for areas smaller than the detector field of view (FOV). Wide field of view flat plate detectors were emphasized, but spherical detectors were also studied. The radiation field was modeled after data from the Nimbus 2 and 3 satellites. At a satellite altitude of 600 km, zonal estimates were in error 1.0 to 1.2 percent and global estimates were in error less than 0.2 percent. Estimates with unrestricted field of view (UFOV) detectors were about the same for Lambertian and limb darkening radiation models. The opposite was found for restricted field of view detectors. The UFOV detectors are found to be poor estimators of flux density from the total FOV and are shown to be much better as estimators of flux density from a circle centered at the FOV with an area significantly smaller than that for the total FOV.

Estimating Primary Production of Picophytoplankton Using the Carbon-Based Ocean Productivity Model: A Preliminary Study

PubMed Central

Liang, Yantao; Zhang, Yongyu; Wang, Nannan; Luo, Tingwei; Zhang, Yao; Rivkin, Richard B.

2017-01-01

Picophytoplankton are acknowledged to contribute significantly to primary production (PP) in the ocean while now the method to measure PP of picophytoplankton (PPPico) at large scales is not yet well established. Although the traditional 14C method and new technologies based on the use of stable isotopes (e.g., 13C) can be employed to accurately measure in situ PPPico, the time-consuming and labor-intensive shortage of these methods constrain their application in a survey on large spatiotemporal scales. To overcome this shortage, a modified carbon-based ocean productivity model (CbPM) is proposed for estimating the PPPico whose principle is based on the group-specific abundance, cellular carbon conversion factor (CCF), and temperature-derived growth rate of picophytoplankton. Comparative analysis showed that the estimated PPPico using CbPM method is significantly and positively related (r2 = 0.53, P < 0.001, n = 171) to the measured 14C uptake. This significant relationship suggests that CbPM has the potential to estimate the PPPico over large spatial and temporal scales. Currently this model application may be limited by the use of invariant cellular CCF and the relatively small data sets to validate the model which may introduce some uncertainties and biases. Model performance will be improved by the use of variable conversion factors and the larger data sets representing diverse growth conditions. Finally, we apply the CbPM-based model on the collected data during four cruises in the Bohai Sea in 2005. Model-estimated PPPico ranged from 0.1 to 11.9, 29.9 to 432.8, 5.5 to 214.9, and 2.4 to 65.8 mg C m-2 d-1 during March, June, September, and December, respectively. This study shed light on the estimation of global PPPico using carbon-based production model. PMID:29051755

Flight paths of seabirds soaring over the ocean surface enable measurement of fine-scale wind speed and direction.

PubMed

Yonehara, Yoshinari; Goto, Yusuke; Yoda, Ken; Watanuki, Yutaka; Young, Lindsay C; Weimerskirch, Henri; Bost, Charles-André; Sato, Katsufumi

2016-08-09

Ocean surface winds are an essential factor in understanding the physical interactions between the atmosphere and the ocean. Surface winds measured by satellite scatterometers and buoys cover most of the global ocean; however, there are still spatial and temporal gaps and finer-scale variations of wind that may be overlooked, particularly in coastal areas. Here, we show that flight paths of soaring seabirds can be used to estimate fine-scale (every 5 min, ∼5 km) ocean surface winds. Fine-scale global positioning system (GPS) positional data revealed that soaring seabirds flew tortuously and ground speed fluctuated presumably due to tail winds and head winds. Taking advantage of the ground speed difference in relation to flight direction, we reliably estimated wind speed and direction experienced by the birds. These bird-based wind velocities were significantly correlated with wind velocities estimated by satellite-borne scatterometers. Furthermore, extensive travel distances and flight duration of the seabirds enabled a wide range of high-resolution wind observations, especially in coastal areas. Our study suggests that seabirds provide a platform from which to measure ocean surface winds, potentially complementing conventional wind measurements by covering spatial and temporal measurement gaps.

Flight paths of seabirds soaring over the ocean surface enable measurement of fine-scale wind speed and direction

PubMed Central

Yonehara, Yoshinari; Goto, Yusuke; Yoda, Ken; Watanuki, Yutaka; Young, Lindsay C.; Weimerskirch, Henri; Bost, Charles-André; Sato, Katsufumi

2016-01-01

Ocean surface winds are an essential factor in understanding the physical interactions between the atmosphere and the ocean. Surface winds measured by satellite scatterometers and buoys cover most of the global ocean; however, there are still spatial and temporal gaps and finer-scale variations of wind that may be overlooked, particularly in coastal areas. Here, we show that flight paths of soaring seabirds can be used to estimate fine-scale (every 5 min, ∼5 km) ocean surface winds. Fine-scale global positioning system (GPS) positional data revealed that soaring seabirds flew tortuously and ground speed fluctuated presumably due to tail winds and head winds. Taking advantage of the ground speed difference in relation to flight direction, we reliably estimated wind speed and direction experienced by the birds. These bird-based wind velocities were significantly correlated with wind velocities estimated by satellite-borne scatterometers. Furthermore, extensive travel distances and flight duration of the seabirds enabled a wide range of high-resolution wind observations, especially in coastal areas. Our study suggests that seabirds provide a platform from which to measure ocean surface winds, potentially complementing conventional wind measurements by covering spatial and temporal measurement gaps. PMID:27457932

Pesticide fate on catchment scale: conceptual modelling of stream CSIA data

NASA Astrophysics Data System (ADS)

Lutz, Stefanie R.; van der Velde, Ype; Elsayed, Omniea F.; Imfeld, Gwenaël; Lefrancq, Marie; Payraudeau, Sylvain; van Breukelen, Boris M.

2017-10-01

Compound-specific stable isotope analysis (CSIA) has proven beneficial in the characterization of contaminant degradation in groundwater, but it has never been used to assess pesticide transformation on catchment scale. This study presents concentration and carbon CSIA data of the herbicides S-metolachlor and acetochlor from three locations (plot, drain, and catchment outlets) in a 47 ha agricultural catchment (Bas-Rhin, France). Herbicide concentrations at the catchment outlet were highest (62 µg L-1) in response to an intense rainfall event following herbicide application. Increasing δ13C values of S-metolachlor and acetochlor by more than 2 ‰ during the study period indicated herbicide degradation. To assist the interpretation of these data, discharge, concentrations, and δ13C values of S-metolachlor were modelled with a conceptual mathematical model using the transport formulation by travel-time distributions. Testing of different model setups supported the assumption that degradation half-lives (DT50) increase with increasing soil depth, which can be straightforwardly implemented in conceptual models using travel-time distributions. Moreover, model calibration yielded an estimate of a field-integrated isotopic enrichment factor as opposed to laboratory-based assessments of enrichment factors in closed systems. Thirdly, the Rayleigh equation commonly applied in groundwater studies was tested by our model for its potential to quantify degradation on catchment scale. It provided conservative estimates on the extent of degradation as occurred in stream samples. However, largely exceeding the simulated degradation within the entire catchment, these estimates were not representative of overall degradation on catchment scale. The conceptual modelling approach thus enabled us to upscale sample-based CSIA information on degradation to the catchment scale. Overall, this study demonstrates the benefit of combining monitoring and conceptual modelling of concentration and CSIA data and advocates the use of travel-time distributions for assessing pesticide fate and transport on catchment scale.

Psychometric properties of the Thai Spiritual Well-Being Scale.

PubMed

Chaiviboontham, Suchira; Phinitkhajorndech, Noppawan; Hanucharurnkul, Somchit; Noipiang, Thaniya

2016-04-01

The purpose of this study was to investigate the psychometric properties of the modified Thai Spiritual Well-Being Scale in patients with advanced cancer. This cross-sectional study was employed to investigate psychometric properties. Some 196 participants from three tertiary hospitals in Bangkok and suburban Thailand were asked to complete a Personal Information Questionnaire (PIQ), The Memorial Symptom Assessment Scale (MSAS), and the Spiritual Well-Being Scale (SWBS). Validity was determined by known-group, concurrent, and constructs validity. Reliability was estimated using internal consistency by Cronbach's α coefficients. Three factors were extracted: so-called existential well-being, religious well-being, and peacefulness accounted for 71.44% of total variance. The Cronbach's α coefficients for total SWB, EWB, RWB, and peacefulness were 0.96, 0.94, and 0.93, respectively. These findings indicate that the Thai SWBS is a valid and reliable instrument, and it presented one more factor than the original version.

Back to "the Future": Evidence of a Bifactor Solution for Scores on the Consideration of Future Consequences Scale.

PubMed

McKay, Michael T; Morgan, Grant B; van Exel, N Job; Worrell, Frank C

2015-01-01

Despite its widespread use, disagreement remains regarding the structure of the Consideration of Future Consequences Scale (CFCS). In particular there is disagreement regarding whether the scale assesses future orientation as a unidimensional or multidimensional (immediate and future) construct. Using 2 samples of high school students in the United Kingdom, 4 models were tested. The totality of results including item loadings, goodness-of-fit indexes, and reliability estimates all supported the bifactor model, suggesting that the 2 hypothesized factors are better understood as grouping or method factors rather than as representative of latent constructs. Accordingly this study supports the unidimensionality of the CFCS and the scoring of all 12 items to produce a global future orientation score. Researchers intending to use the CFCS, and those with existing data, are encouraged to examine a bifactor solution for the scale.

In the eye of the beholder: the effect of rater variability and different rating scales on QTL mapping.

PubMed

Poland, Jesse A; Nelson, Rebecca J

2011-02-01

The agronomic importance of developing durably resistant cultivars has led to substantial research in the field of quantitative disease resistance (QDR) and, in particular, mapping quantitative trait loci (QTL) for disease resistance. The assessment of QDR is typically conducted by visual estimation of disease severity, which raises concern over the accuracy and precision of visual estimates. Although previous studies have examined the factors affecting the accuracy and precision of visual disease assessment in relation to the true value of disease severity, the impact of this variability on the identification of disease resistance QTL has not been assessed. In this study, the effects of rater variability and rating scales on mapping QTL for northern leaf blight resistance in maize were evaluated in a recombinant inbred line population grown under field conditions. The population of 191 lines was evaluated by 22 different raters using a direct percentage estimate, a 0-to-9 ordinal rating scale, or both. It was found that more experienced raters had higher precision and that using a direct percentage estimation of diseased leaf area produced higher precision than using an ordinal scale. QTL mapping was then conducted using the disease estimates from each rater using stepwise general linear model selection (GLM) and inclusive composite interval mapping (ICIM). For GLM, the same QTL were largely found across raters, though some QTL were only identified by a subset of raters. The magnitudes of estimated allele effects at identified QTL varied drastically, sometimes by as much as threefold. ICIM produced highly consistent results across raters and for the different rating scales in identifying the location of QTL. We conclude that, despite variability between raters, the identification of QTL was largely consistent among raters, particularly when using ICIM. However, care should be taken in estimating QTL allele effects, because this was highly variable and rater dependent.

Peacekeeper Quantity-Distance Verification Program and Addendum.

DTIC Science & Technology

1984-06-01

Zelasko, Project Manager, Geomechanics Division (GD). Structural designs and details were furnished to WES by TRW. Field support was provided to WES by...discontinuities in the direction in which the internal pressure is applied . The SDOF result described in Figure 6-12B supported this assumption. Next, to estimate... apply scale factors based on a drag coefficient of 0.5 toward development of Q-D estimates. During a presentation to the Department of Defense

Development and Validation of the Five-by-Five Resilience Scale.

PubMed

DeSimone, Justin A; Harms, P D; Vanhove, Adam J; Herian, Mitchel N

2017-09-01

This article introduces a new measure of resilience and five related protective factors. The Five-by-Five Resilience Scale (5×5RS) is developed on the basis of theoretical and empirical considerations. Two samples ( N = 475 and N = 613) are used to assess the factor structure, reliability, convergent validity, and criterion-related validity of the 5×5RS. Confirmatory factor analysis supports a bifactor model. The 5×5RS demonstrates adequate internal consistency as evidenced by Cronbach's alpha and empirical reliability estimates. The 5×5RS correlates positively with the Connor-Davidson Resilience Scale (CD-RISC), a commonly used measure of resilience. The 5×5RS exhibits similar criterion-related validity to the CD-RISC as evidenced by positive correlations with satisfaction with life, meaning in life, and secure attachment style as well as negative correlations with rumination and anxious or avoidant attachment styles. 5×5RS scores are positively correlated with healthy behaviors such as exercise and negatively correlated with sleep difficulty and symptomology of anxiety and depression. The 5×5RS incrementally explains variance in some criteria above and beyond the CD-RISC. Item responses are modeled using the graded response model. Information estimates demonstrate the ability of the 5×5RS to assess individuals within at least one standard deviation of the mean on relevant latent traits.

Reliability and validity of the Malay Version of the Breast- Impact of Treatment Scale (MVBITS) in breast cancer women undergoing chemotherapy.

PubMed

Zainal, Nor Zuraida; Shuib, Norley; Bustam, Anita Zarina; Sabki, Zuraida Ahmad; Guan, Ng Chong

2013-01-01

Body image dissatisfaction among breast cancer survivors has been associated with psychological stress resultant from breast cancer and resultant surgery. This study aimed to examine the psychometric properties of the Malay Version of the Breast-Impact of Treatment Scale (MVBITS) and to investigate the associations of retained factors with the Hospital Anxiety and Depression Scale (HADS) and the Rosenberg Self-Esteem Scale (RSES). The MVBITS was 'forward-backward' translated from English to Malay and then administered to 70 female breast cancer patients who came to the Oncology Clinic of University Malaya Medical Centre, Kuala Lumpur, Malaysia to undergo chemotherapy. Principal component analysis (PCA) with varimax rotation was performed to explore the factor structure of the MVBITS. Associations of retained factors were estimated with reference to Spearman correlation coefficients. The internal consistency reliability of MVBITS was good (Cronbach's alpha 0.945) and showed temporal stability over a 3-week period. Principal component analysis suggested two factors termed as 'Intrusion' and 'Avoidance' domains. These factors explained 70.3% of the variance. Factor 1 comprised the effects of breast cancer treatment on the emotion and thought, while Factor 2 informed attempts to limit exposure of the body to self or others. The Factor 1 of MVBITS was positively correlated with total, depression and anxiety sub-scores of HADS. Factor 2 was positively correlated with total and anxiety sub-scores of HADS. MVBITS was also positively correlated with the RSES scores. The results showed that the Malay Version of Breast-Impact of Treatment Scale possesses satisfactory psychometric properties suggesting that this instrument is appropriate for assessment of body change stress among female breast cancer patients in Malaysia.

The brief multidimensional students' life satisfaction scale-college version.

PubMed

Zullig, Keith J; Huebner, E Scott; Patton, Jon M; Murray, Karen A

2009-01-01

To investigate the psychometric properties of the BMSLSS-College among 723 college students. Internal consistency estimates explored scale reliability, factor analysis explored construct validity, and known-groups validity was assessed using the National College Youth Risk Behavior Survey and Harvard School of Public Health College Alcohol Study. Criterion-related validity was explored through analyses with the CDC's health-related quality of life scale and a social isolation scale. Acceptable internal consistency reliability, construct, known-groups, and criterion-related validity were established. Findings offer preliminary support for the BMSLSS-C; it could be useful in large-scale research studies, applied screening contexts, and for program evaluation purposes toward achieving Healthy People 2010 objectives.

Linear Parameter Varying Control Synthesis for Actuator Failure, Based on Estimated Parameter

NASA Technical Reports Server (NTRS)

Shin, Jong-Yeob; Wu, N. Eva; Belcastro, Christine

2002-01-01

The design of a linear parameter varying (LPV) controller for an aircraft at actuator failure cases is presented. The controller synthesis for actuator failure cases is formulated into linear matrix inequality (LMI) optimizations based on an estimated failure parameter with pre-defined estimation error bounds. The inherent conservatism of an LPV control synthesis methodology is reduced using a scaling factor on the uncertainty block which represents estimated parameter uncertainties. The fault parameter is estimated using the two-stage Kalman filter. The simulation results of the designed LPV controller for a HiMXT (Highly Maneuverable Aircraft Technology) vehicle with the on-line estimator show that the desired performance and robustness objectives are achieved for actuator failure cases.

A Psychometric Examination of the Pathological Obsessive Compulsive Personality Scale (POPS): Initial Study in an Undergraduate Sample.

PubMed

Sadri, Shalane K; McEvoy, Peter M; Pinto, Anthony; Anderson, Rebecca A; Egan, Sarah J

2018-03-01

Obsessive-compulsive personality disorder (OCPD) has been subject to numerous definition and classification changes, which has contributed to difficulties in reliable measurement of the disorder. Consequently, OCPD measures have yielded poor validity and inconsistent prevalence estimates. Reliable and valid measures of OCPD are needed. The aim of the current study was to examine the factor structure and psychometric properties of the Pathological Obsessive Compulsive Personality Scale (POPS). Participants (N = 571 undergraduates) completed a series of self-report measures online, including the POPS. Confirmatory factor analysis was used to compare the fit of unidimensional, five factor, and bifactor models of the POPS. Convergent and divergent validity were assessed in relation to other personality dimensions. A bifactor model provided the best fit to the data, indicating that the total POPS scale and four subscales can be scored to obtain reliable indicators of OCPD. The POPS was most strongly associated with a disorder-specific measure of OCPD, however there were also positive associations with theoretically disparate constructs, thus further research is needed to clarify validity of the scale.

A wavelet analysis of scaling laws and long-memory in stock market volatility

NASA Astrophysics Data System (ADS)

Vuorenmaa, Tommi A.

2005-05-01

This paper studies the time-varying behavior of scaling laws and long-memory. This is motivated by the earlier finding that in the FX markets a single scaling factor might not always be sufficient across all relevant timescales: a different region may exist for intradaily time-scales and for larger time-scales. In specific, this paper investigates (i) if different scaling regions appear in stock market as well, (ii) if the scaling factor systematically differs from the Brownian, (iii) if the scaling factor is constant in time, and (iv) if the behavior can be explained by the heterogenuity of the players in the market and/or by intraday volatility periodicity. Wavelet method is used because it delivers a multiresolution decomposition and has excellent local adaptiviness properties. As a consequence, a wavelet-based OLS method allows for consistent estimation of long-memory. Thus issues (i)-(iv) shed light on the magnitude and behavior of a long-memory parameter, as well. The data are the 5-minute volatility series of Nokia Oyj at the Helsinki Stock Exchange around the burst of the IT-bubble. Period one represents the era of "irrational exuberance" and another the time after it. The results show that different scaling regions (i.e. multiscaling) may appear in the stock markets and not only in the FX markets, the scaling factor and the long-memory parameter are systematically different from the Brownian and they do not have to be constant in time, and that the behavior can be explained for a significant part by an intraday volatility periodicity called the New York effect. This effect was magnified by the frenzy trading of short-term speculators in the bubble period. The found stronger long-memory is also attributable to irrational exuberance.

Theoretical Insight Into the Empirical Tortuosity-Connectivity Factor in the Burdine-Brooks-Corey Water Relative Permeability Model

NASA Astrophysics Data System (ADS)

Ghanbarian, Behzad; Ioannidis, Marios A.; Hunt, Allen G.

2017-12-01

A model commonly applied to the estimation of water relative permeability krw in porous media is the Burdine-Brooks-Corey model, which relies on a simplified picture of pores as a bundle of noninterconnected capillary tubes. In this model, the empirical tortuosity-connectivity factor is assumed to be a power law function of effective saturation with an exponent (μ) commonly set equal to 2 in the literature. Invoking critical path analysis and using percolation theory, we relate the tortuosity-connectivity exponent μ to the critical scaling exponent t of percolation that characterizes the power law behavior of the saturation-dependent electrical conductivity of porous media. We also discuss the cause of the nonuniversality of μ in terms of the nonuniversality of t and compare model estimations with water relative permeability from experiments. The comparison supports determining μ from the electrical conductivity scaling exponent t, but also highlights limitations of the model.

Development and construct validity of the Classroom Strategies Scale-Observer Form.

PubMed

Reddy, Linda A; Fabiano, Gregory; Dudek, Christopher M; Hsu, Louis

2013-12-01

Research on progress monitoring has almost exclusively focused on student behavior and not on teacher practices. This article presents the development and validation of a new teacher observational assessment (Classroom Strategies Scale) of classroom instructional and behavioral management practices. The theoretical underpinnings and empirical basis for the instructional and behavioral management scales are presented. The Classroom Strategies Scale (CSS) evidenced overall good reliability estimates including internal consistency, interrater reliability, test-retest reliability, and freedom from item bias on important teacher demographics (age, educational degree, years of teaching experience). Confirmatory factor analyses (CFAs) of CSS data from 317 classrooms were carried out to assess the level of empirical support for (a) a 4 first-order factor theory concerning teachers' instructional practices, and (b) a 4 first-order factor theory concerning teachers' behavior management practice. Several fit indices indicated acceptable fit of the (a) and (b) CFA models to the data, as well as acceptable fit of less parsimonious alternative CFA models that included 1 or 2 second-order factors. Information-theory-based indices generally suggested that the (a) and (b) CFA models fit better than some more parsimonious alternative CFA models that included constraints on relations of first-order factors. Overall, CFA first-order and higher order factor results support the CSS-Observer Total, Composite, and subscales. Suggestions for future measurement development efforts are outlined. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Factor Structure and Reliability of the Childhood Trauma Questionnaire and Prevalence Estimates of Trauma for Male and Female Street Youth

ERIC Educational Resources Information Center

Forde, David R.; Baron, Stephen W.; Scher, Christine D.; Stein, Murray B.

2012-01-01

This study examines the psychometric properties of the Childhood Trauma Questionnaire short form (CTQ-SF) with street youth who have run away or been expelled from their homes (N = 397). Internal reliability coefficients for the five clinical scales ranged from 0.65 to 0.95. Confirmatory Factor Analysis (CFA) was used to test the five-factor…

The Hispanic Stress Inventory-Adolescent Version: A Culturally Informed Psychosocial Assessment

PubMed Central

Cervantes, Richard C.; Fisher, Dennis G.; Córdova, David; Napper, Lucy

2012-01-01

A 2-phase study was conducted to develop a culturally informed measure of psychosocial stress for adolescents, the Hispanic Stress Inventory-Adolescent Version (HSI-A). Phase I involved item development through the collection of open-ended focus group interview data (n=170) from a heterogeneous sample of Hispanic youth residing in the southwest and northeast United States. Phase 2 examined the psychometric properties of the HSI-A (n=1651) involving the use of factor analytic procedures to determine the underlying scale structure of the HSI-A, for foreign-born and U.S.-born participants in an aggregated analytic approach. An eight factor solution was established with factors that include Family Economic Stress, Acculturation Gaps Stress, Culture and Educational Stress, Immigration Related Stress, Discrimination Stress, Family Immigration Stress, Community and Gang Violence Stress and Family Drug Related Stress. Concurrent related validity estimates were calculated to determine relationships between HSI-A and other measures of child psychopathology, behavioral and emotional disturbances. HSI-A Total Stress Appraisal Scores were significantly correlated with both the CDI and YSR (p<.001 respectively). Reliability estimates for the HSI-A were conducted and yielded high reliability coefficients for most all factor sub-scales with HSI-A Total Stress Appraisal score reliability at alpha=.92. PMID:21942232

The determinants of dentists' productivity and the measurement of output.

PubMed

Gutacker, Nils; Harris, Anthony; Brennan, David; Hollingsworth, Bruce

2015-01-01

Improving the productivity of the healthcare system, for example by taking advantage of scale economies or encouraging substitution of expensive specialist personnel with less expensive workers, is often seen as an attractive way to meet increasing demand within a constrained budget. Using data on 558 dentists participating in the Longitudinal Study of Dentists' Practice Activity (LSDPA) survey between 1993 and 2003 linked to patient data and average fee schedules, we estimate production functions for private dental services in Australia to quantify the contribution of different capital and labour inputs and identify economies of scale in the production of dental care. Given the challenges in measuring output in the healthcare setting, we discuss three different output measures (raw activity, time-, and price-weighted activity) and test the sensitivity of results to the choice of measure. Our results suggest that expansion of the scale of dental services is unlikely to be constrained by decreasing returns to scale. We note that conclusions about the contribution of individual input factors and the estimated returns to scale are sensitive to the choice of output measure employed. Copyright © 2014 Elsevier Ltd. All rights reserved.

Flexible versus common technology to estimate economies of scale and scope in the water and sewerage industry: an application to England and Wales.

PubMed

Molinos-Senante, María; Maziotis, Alexandros

2018-05-01

The water industry presents several structures in different countries and also within countries. Hence, several studies have been conducted to evaluate the presence of economies of scope and scale in the water industry leading to inconclusive results. The lack of a common methodology has been identified as an important factor contributing to divergent conclusions. This paper evaluates, for the first time, the presence of economies of scale and scope in the water industry using a flexible technology approach integrating operational and exogenous variables of the water companies in the cost functions. The empirical application carried out for the English and Welsh water industry evidenced that the inclusion of exogenous variables accounts for significant differences in economies of scale and scope. Moreover, completely different results were obtained when the economies of scale and scope were estimated using common and flexible technology methodological approaches. The findings of this study reveal the importance of using an appropriate methodology to support policy decision-making processes to promote sustainable urban water activities.

Spatial and temporal variation in population genetic structure of wild Nile tilapia (Oreochromis niloticus) across Africa

PubMed Central

2011-01-01

Background Reconstructing the evolutionary history of a species is challenging. It often depends not only on the past biogeographic and climatic events but also the contemporary and ecological factors, such as current connectivity and habitat heterogeneity. In fact, these factors might interact with each other and shape the current species distribution. However, to what extent the current population genetic structure reflects the past and the contemporary factors is largely unknown. Here we investigated spatio-temporal genetic structures of Nile tilapia (Oreochromis niloticus) populations, across their natural distribution in Africa. While its large biogeographic distribution can cause genetic differentiation at the paleo-biogeographic scales, its restricted dispersal capacity might induce a strong genetic structure at micro-geographic scales. Results Using nine microsatellite loci and 350 samples from ten natural populations, we found the highest genetic differentiation among the three ichthyofaunal provinces and regions (Ethiopian, Nilotic and Sudano-Sahelian) (RST = 0.38 - 0.69). This result suggests the predominant effect of paleo-geographic events at macro-geographic scale. In addition, intermediate divergences were found between rivers and lakes within the regions, presumably reflecting relatively recent interruptions of gene flow between hydrographic basins (RST = 0.24 - 0.32). The lowest differentiations were observed among connected populations within a basin (RST = 0.015 in the Volta basin). Comparison of temporal sample series revealed subtle changes in the gene pools in a few generations (F = 0 - 0.053). The estimated effective population sizes were 23 - 143 and the estimated migration rate was moderate (m ~ 0.094 - 0.097) in the Volta populations. Conclusions This study revealed clear hierarchical patterns of the population genetic structuring of O. niloticus in Africa. The effects of paleo-geographic and climatic events were predominant at macro-geographic scale, and the significant effect of geographic connectivity was detected at micro-geographic scale. The estimated effective population size, the moderate level of dispersal and the rapid temporal change in genetic composition might reflect a potential effect of life history strategy on population dynamics. This hypothesis deserves further investigation. The dynamic pattern revealed at micro-geographic and temporal scales appears important from a genetic resource management as well as from a biodiversity conservation point of view. PMID:22151746

Small-scale temporal and spatial variability in the abundance of plastic pellets on sandy beaches: Methodological considerations for estimating the input of microplastics.

PubMed

Moreira, Fabiana Tavares; Prantoni, Alessandro Lívio; Martini, Bruno; de Abreu, Michelle Alves; Stoiev, Sérgio Biato; Turra, Alexander

2016-01-15

Microplastics such as pellets have been reported for many years on sandy beaches around the globe. Nevertheless, high variability is observed in their estimates and distribution patterns across the beach environment are still to be unravelled. Here, we investigate the small-scale temporal and spatial variability in the abundance of pellets in the intertidal zone of a sandy beach and evaluate factors that can increase the variability in data sets. The abundance of pellets was estimated during twelve consecutive tidal cycles, identifying the position of the high tide between cycles and sampling drift-lines across the intertidal zone. We demonstrate that beach dynamic processes such as the overlap of strandlines and artefacts of the methods can increase the small-scale variability. The results obtained are discussed in terms of the methodological considerations needed to understand the distribution of pellets in the beach environment, with special implications for studies focused on patterns of input. Copyright © 2015 Elsevier Ltd. All rights reserved.

Organic carbon stock modelling for the quantification of the carbon sinks in terrestrial ecosystems

NASA Astrophysics Data System (ADS)

Durante, Pilar; Algeet, Nur; Oyonarte, Cecilio

2017-04-01

Given the recent environmental policies derived from the serious threats caused by global change, practical measures to decrease net CO2 emissions have to be put in place. Regarding this, carbon sequestration is a major measure to reduce atmospheric CO2 concentrations within a short and medium term, where terrestrial ecosystems play a basic role as carbon sinks. Development of tools for quantification, assessment and management of organic carbon in ecosystems at different scales and management scenarios, it is essential to achieve these commitments. The aim of this study is to establish a methodological framework for the modeling of this tool, applied to a sustainable land use planning and management at spatial and temporal scale. The methodology for carbon stock estimation in ecosystems is based on merger techniques between carbon stored in soils and aerial biomass. For this purpose, both spatial variability map of soil organic carbon (SOC) and algorithms for calculation of forest species biomass will be created. For the modelling of the SOC spatial distribution at different map scales, it is necessary to fit in and screen the available information of soil database legacy. Subsequently, SOC modelling will be based on the SCORPAN model, a quantitative model use to assess the correlation among soil-forming factors measured at the same site location. These factors will be selected from both static (terrain morphometric variables) and dynamic variables (climatic variables and vegetation indexes -NDVI-), providing to the model the spatio-temporal characteristic. After the predictive model, spatial inference techniques will be used to achieve the final map and to extrapolate the data to unavailable information areas (automated random forest regression kriging). The estimated uncertainty will be calculated to assess the model performance at different scale approaches. Organic carbon modelling of aerial biomass will be estimate using LiDAR (Light Detection And Ranging) algorithms. The available LiDAR databases will be used. LiDAR statistics (which describe the LiDAR cloud point data to calculate forest stand parameters) will be correlated with different canopy cover variables. The regression models applied to the total area will produce a continuous geo-information map to each canopy variable. The CO2 estimation will be calculated by dry-mass conversion factors for each forest species (C kg-CO2 kg equivalent). The result is the organic carbon modelling at spatio-temporal scale with different levels of uncertainty associated to the predictive models and diverse detailed scales. However, one of the main expected problems is due to the heterogeneous spatial distribution of the soil information, which influences on the prediction of the models at different spatial scales and, consequently, at SOC map scale. Besides this, the variability and mixture of the forest species of the aerial biomass decrease the accuracy assessment of the organic carbon.

Investigation of scale effects in the TRF determined by VLBI

NASA Astrophysics Data System (ADS)

Wahl, Daniel; Heinkelmann, Robert; Schuh, Harald

2017-04-01

The improvement of the International Terrestrial Reference Frame (ITRF) is of great significance for Earth sciences and one of the major tasks in geodesy. The translation, rotation and the scale-factor, as well as their linear rates, are solved in a 14-parameter transformation between individual frames of each space geodetic technique and the combined frame. In ITRF2008, as well as in the current release ITRF2014, the scale-factor is provided by Very Long Baseline Interferometry (VLBI) and Satellite Laser Ranging (SLR) in equal shares. Since VLBI measures extremely precise group delays that are transformed to baseline lengths by the velocity of light, a natural constant, VLBI is the most suitable method for providing the scale. The aim of the current work is to identify possible shortcomings in the VLBI scale contribution to ITRF2008. For developing recommendations for an enhanced estimation, scale effects in the Terrestrial Reference Frame (TRF) determined with VLBI are considered in detail and compared to ITRF2008. In contrast to station coordinates, where the scale is defined by a geocentric position vector, pointing from the origin of the reference frame to the station, baselines are not related to the origin. They are describing the absolute scale independently from the datum. The more accurate a baseline length, and consequently the scale, is estimated by VLBI, the better the scale contribution to the ITRF. Considering time series of baseline length between different stations, a non-linear periodic signal can clearly be recognized, caused by seasonal effects at observation sites. Modeling these seasonal effects and subtracting them from the original data enhances the repeatability of single baselines significantly. Other effects influencing the scale strongly, are jumps in the time series of baseline length, mainly evoked by major earthquakes. Co- and post-seismic effects can be identified in the data, having a non-linear character likewise. Modeling the non-linear motion or completely excluding affected stations is another important step for an improved scale determination. In addition to the investigation of single baseline repeatabilities also the spatial transformation, which is performed for determining parameters of the ITRF2008, are considered. Since the reliability of the resulting transformation parameters is higher the more identical points are used in the transformation, an approach where all possible stations are used as control points is comprehensible. Experiments that examine the scale-factor and its spatial behavior between control points in ITRF2008 and coordinates determined by VLBI only showed that the network geometry has a large influence on the outcome as well. Introducing an unequally distributed network for the datum configuration, the correlations between translation parameters and the scale-factor can become remarkably high. Only a homogeneous spatial distribution of participating stations yields a maximally uncorrelated scale-factor that can be interpreted independent from other parameters. In the current release of the ITRF, the ITRF2014, for the first time, non-linear effects in the time series of station coordinates are taken into account. The present work shows the importance and the right direction of the modification of the ITRF calculation. But also further improvements were found which lead to an enhanced scale determination.

Is this the right normalization? A diagnostic tool for ChIP-seq normalization.

PubMed

Angelini, Claudia; Heller, Ruth; Volkinshtein, Rita; Yekutieli, Daniel

2015-05-09

Chip-seq experiments are becoming a standard approach for genome-wide profiling protein-DNA interactions, such as detecting transcription factor binding sites, histone modification marks and RNA Polymerase II occupancy. However, when comparing a ChIP sample versus a control sample, such as Input DNA, normalization procedures have to be applied in order to remove experimental source of biases. Despite the substantial impact that the choice of the normalization method can have on the results of a ChIP-seq data analysis, their assessment is not fully explored in the literature. In particular, there are no diagnostic tools that show whether the applied normalization is indeed appropriate for the data being analyzed. In this work we propose a novel diagnostic tool to examine the appropriateness of the estimated normalization procedure. By plotting the empirical densities of log relative risks in bins of equal read count, along with the estimated normalization constant, after logarithmic transformation, the researcher is able to assess the appropriateness of the estimated normalization constant. We use the diagnostic plot to evaluate the appropriateness of the estimates obtained by CisGenome, NCIS and CCAT on several real data examples. Moreover, we show the impact that the choice of the normalization constant can have on standard tools for peak calling such as MACS or SICER. Finally, we propose a novel procedure for controlling the FDR using sample swapping. This procedure makes use of the estimated normalization constant in order to gain power over the naive choice of constant (used in MACS and SICER), which is the ratio of the total number of reads in the ChIP and Input samples. Linear normalization approaches aim to estimate a scale factor, r, to adjust for different sequencing depths when comparing ChIP versus Input samples. The estimated scaling factor can easily be incorporated in many peak caller algorithms to improve the accuracy of the peak identification. The diagnostic plot proposed in this paper can be used to assess how adequate ChIP/Input normalization constants are, and thus it allows the user to choose the most adequate estimate for the analysis.

The reliability and validity of flight task workload ratings

NASA Technical Reports Server (NTRS)

Childress, M. E.; Hart, S. G.; Bortolussi, M. R.

1982-01-01

Twelve instrument-rated general aviation pilots each flew two scenarios in a motion-base simulator. During each flight, the pilots verbally estimated their workload every three minutes. Following each flight, they again estimated workload for each flight segment and also rated their overall workload, perceived performance, and 13 specific factors on a bipolar scale. The results indicate that time (a priori, inflight, or postflight) of eliciting ratings, period to be covered by the ratings (a specific moment in time or a longer period), type of rating scale, and rating method (verbal, written, or other) may be important variables. Overall workload ratings appear to be predicted by different specific scales depending upon the situation, with activity level the best predictor. Perceived performance seems to bear little relationship to observer-rated performance when pilots rate their overall performance and an observer rates specific behaviors. Perceived workload and performance also seem unrelated.

[Prognosis in pediatric traumatic brain injury. A dynamic cohort study].

PubMed

Vázquez-Solís, María G; Villa-Manzano, Alberto I; Sánchez-Mosco, Dalia I; Vargas-Lares, José de Jesús; Plascencia-Fernández, Irma

2013-01-01

traumatic brain injury is a main cause of hospital admission and death in children. Our objective was to identify prognostic factors of pediatric traumatic brain injury. this was a dynamic cohort study of traumatic brain injury with 6 months follow-up. The exposition was: mild or moderate/severe traumatic brain injury, searching for prognosis (morbidity-mortality and decreased Glasgow scale). Relative risk and logistic regression was estimated for prognostic factors. we evaluated 440 patients with mild traumatic brain injury and 98 with moderate/severe traumatic brain injury. Morbidity for mild traumatic brain injury was 1 %; for moderate/severe traumatic brain injury, 5 %. There were no deaths. Prognostic factors for moderate/severe traumatic brain injury were associated injuries (RR = 133), fractures (RR = 60), street accidents (RR = 17), night time accidents (RR = 2.3) and weekend accidents (RR = 2). Decreased Glasgow scale was found in 9 %, having as prognostic factors: visible injuries (RR = 3), grown-up supervision (RR = 2.5) and time of progress (RR = 1.6). there should be a prognosis established based on kinetic energy of the injury and not only with Glasgow Scale.

Factors affecting economies of scale in combined sewer systems.

PubMed

Maurer, Max; Wolfram, Martin; Anja, Herlyn

2010-01-01

A generic model is introduced that represents the combined sewer infrastructure of a settlement quantitatively. A catchment area module first calculates the length and size distribution of the required sewer pipes on the basis of rain patterns, housing densities and area size. These results are fed into the sewer-cost module in order to estimate the combined sewer costs of the entire catchment area. A detailed analysis of the relevant input parameters for Swiss settlements is used to identify the influence of size on costs. The simulation results confirm that an economy of scale exists for combined sewer systems. This is the result of two main opposing cost factors: (i) increased construction costs for larger sewer systems due to larger pipes and increased rain runoff in larger settlements, and (ii) lower costs due to higher population and building densities in larger towns. In Switzerland, the more or less organically grown settlement structures and limited land availability emphasise the second factor to show an apparent economy of scale. This modelling approach proved to be a powerful tool for understanding the underlying factors affecting the cost structure for water infrastructures.

An approach for estimating item sensitivity to within-person change over time: An illustration using the Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-Cog).

PubMed

Dowling, N Maritza; Bolt, Daniel M; Deng, Sien

2016-12-01

When assessments are primarily used to measure change over time, it is important to evaluate items according to their sensitivity to change, specifically. Items that demonstrate good sensitivity to between-person differences at baseline may not show good sensitivity to change over time, and vice versa. In this study, we applied a longitudinal factor model of change to a widely used cognitive test designed to assess global cognitive status in dementia, and contrasted the relative sensitivity of items to change. Statistically nested models were estimated introducing distinct latent factors related to initial status differences between test-takers and within-person latent change across successive time points of measurement. Models were estimated using all available longitudinal item-level data from the Alzheimer's Disease Assessment Scale-Cognitive subscale, including participants representing the full-spectrum of disease status who were enrolled in the multisite Alzheimer's Disease Neuroimaging Initiative. Five of the 13 Alzheimer's Disease Assessment Scale-Cognitive items demonstrated noticeably higher loadings with respect to sensitivity to change. Attending to performance change on only these 5 items yielded a clearer picture of cognitive decline more consistent with theoretical expectations in comparison to the full 13-item scale. Items that show good psychometric properties in cross-sectional studies are not necessarily the best items at measuring change over time, such as cognitive decline. Applications of the methodological approach described and illustrated in this study can advance our understanding regarding the types of items that best detect fine-grained early pathological changes in cognition. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Scale-dependent factors affecting North American river otter distribution in the midwest

USGS Publications Warehouse

Jeffress, Mackenzie R.; Paukert, C.P.; Whittier, Joanna B.; Sandercock, B.K.; Gipson, P.S.

2011-01-01

The North American river otter (Lontra canadensis) is recovering from near extirpation throughout much of its range. Although reintroductions, trapping regulations and habitat improvements have led to the reestablishment of river otters in the Midwest, little is known about how their distribution is influenced by local- and landscape-scale habitat. We conducted river otter sign surveys from Jan. to Apr. in 2008 and 2009 in eastern Kansas to assess how local- and landscape-scale habitat factors affect river otter occupancy. We surveyed three to nine 400-m stretches of stream and reservoir shorelines for 110 sites and measured local-scale variables (e.g., stream order, land cover types) within a 100 m buffer of the survey site and landscape-scale variables (e.g., road density, land cover types) for Hydrological Unit Code 14 watersheds. We then used occupancy models that account for the probability of detection to estimate occupancy as a function of these covariates using Program PRESENCE. The best-fitting model indicated river otter occupancy increased with the proportion of woodland cover and decreased with the proportion of cropland and grassland cover at the local scale. Occupancy also increased with decreased shoreline diversity, waterbody density and stream density at the landscape scale. Occupancy was not affected by land cover or human disturbance at the landscape scale. Understanding the factors and scale important to river otter occurrence will be useful in identifying areas for management and continued restoration. ?? 2011, American Midland Naturalist.

Advanced techniques for modeling avian nest survival

USGS Publications Warehouse

Dinsmore, S.J.; White, Gary C.; Knopf, F.L.

2002-01-01

Estimation of avian nest survival has traditionally involved simple measures of apparent nest survival or Mayfield constant-nest-survival models. However, these methods do not allow researchers to build models that rigorously assess the importance of a wide range of biological factors that affect nest survival. Models that incorporate greater detail, such as temporal variation in nest survival and covariates representative of individual nests represent a substantial improvement over traditional estimation methods. In an attempt to improve nest survival estimation procedures, we introduce the nest survival model now available in the program MARK and demonstrate its use on a nesting study of Mountain Plovers (Charadrius montanus Townsend) in Montana, USA. We modeled the daily survival of Mountain Plover nests as a function of the sex of the incubating adult, nest age, year, linear and quadratic time trends, and two weather covariates (maximum daily temperature and daily precipitation) during a six-year study (1995–2000). We found no evidence for yearly differences or an effect of maximum daily temperature on the daily nest survival of Mountain Plovers. Survival rates of nests tended by female and male plovers differed (female rate = 0.33; male rate = 0.49). The estimate of the additive effect for males on nest survival rate was 0.37 (95% confidence limits were 0.03, 0.71) on a logit scale. Daily survival rates of nests increased with nest age; the estimate of daily nest-age change in survival in the best model was 0.06 (95% confidence limits were 0.04, 0.09) on a logit scale. Daily precipitation decreased the probability that the nest would survive to the next day; the estimate of the additive effect of daily precipitation on the nest survival rate was −1.08 (95% confidence limits were −2.12, −0.13) on a logit scale. Our approach to modeling daily nest-survival rates allowed several biological factors of interest to be easily included in nest survival models and allowed us to generate more biologically meaningful estimates of nest survival.

AGRICULTURAL AMMONIA EMISSIONS AND AMMONIUM DEPOSITION IN THE SOUTHEAST UNITED STATES

EPA Science Inventory

The paper gives an estimate of county-scale annual ammonia (NH3) emissions in eight Southeastern States for the year 1997, using emission factors and activity data for all domestic livestock and fertilizer sources. A geographical distribution of the data yields local areas (1000...

Estimating the annual risk of HIV transmission within HIV sero-discordant couples in sub-Saharan Africa.

PubMed

Awad, Susanne F; Chemaitelly, Hiam; Abu-Raddad, Laith J

2018-01-01

To estimate the annual risk of HIV transmission (ϕ) within HIV sero-discordant couples in 23 countries in sub-Saharan Africa (SSA), by utilizing newly available national population-based data and accounting for factors known to potentially affect this estimation. We used a recently developed pair-based mathematical model that accommodates for HIV-dynamics temporal variation, sexual risk-behavior heterogeneity, and antiretroviral therapy (ART) scale-up. Estimated country-specific ϕ (in absence of ART) ranged between 4.2% (95% uncertainty interval (UI): 1.9%-6.3%) and 47.4% (95% UI: 37.2%-69.0%) per person-year (ppy), with a median of 12.4%. ϕ was strongly associated with HIV prevalence, with a Pearson correlation coefficient of 0.92, and was larger in high- versus low-HIV-prevalence countries. ϕ increased by 1.31% (95% confidence interval: 1.00%-1.55%) ppy for every 1% increase in HIV prevalence. ϕ estimates were similar to earlier estimates, and suggested considerable heterogeneity in HIV infectiousness across SSA. This heterogeneity may explain, partly, the differences in epidemic scales. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Development of the Seasonal Migrant Agricultural Worker Stress Scale in Sanliurfa, Southeast Turkey.

PubMed

Simsek, Zeynep; Ersin, Fatma; Kirmizitoprak, Evin

2016-01-01

Stress is one of the main causes of health problems, especially mental disorders. These health problems cause a significant amount of ability loss and increase cost. It is estimated that by 2020, mental disorders will constitute 15% of the total disease burden, and depression will rank second only after ischemic heart disease. Environmental experiences are paramount in increasing the liability of mental disorders in those who constantly face sustained high levels of stress. The objective of this study was to develop a stress scale for seasonal migrant agricultural workers aged 18 years and older. The sample consisted of 270 randomly selected seasonal migrant agricultural workers. The average age of the participants was 33.1 ± 14, and 50.7% were male. The Cronbach alpha coefficient and test-retest methods were used for reliability analyses. Although the factor analysis was performed for the structure validity of the scale, the Kaiser-Meyer-Olkin coefficient and Bartlett test were used to determine the convenience of the data for the factor analysis. In the reliability analyses, the Cronbach alpha coefficient of internal consistency was calculated as .96, and the test-retest reliability coefficient was .81. In the exploratory factor analysis for validity of the scale, four factors were obtained, and the factors represented workplace physical conditions (25.7% of the total variance), workplace psychosocial and economic factors (19.3% of the total variance), workplace health problems (15.2% of the total variance), and school problems (10.1% of the total variance). The four factors explained 70.3% of the total variance. As a result of the expert opinions and analyses, a stress scale with 48 items was developed. The highest score to be obtained from the scale was 144, and the lowest score was 0. The increase in the score indicates the increase in the stress levels. The findings show that the scale is a valid and reliable assessment instrument that can be used in epidemiological research and planning interventions.

[Construction of the Time Management Scale and examination of the influence of time management on psychological stress response].

PubMed

Imura, Tomoya; Takamura, Masahiro; Okazaki, Yoshihiro; Tokunaga, Satoko

2016-10-01

We developed a scale to measure time management and assessed its reliability and validity. We then used this scale to examine the impact of time management on psychological stress response. In Study 1-1, we developed the scale and assessed its internal consistency and criterion-related validity. Findings from a factor analysis revealed three elements of time management, “time estimation,” “time utilization,” and “taking each moment as it comes.” In Study 1-2, we assessed the scale’s test-retest reliability. In Study 1-3, we assessed the validity of the constructed scale. The results indicate that the time management scale has good reliability and validity. In Study 2, we performed a covariance structural analysis to verify our model that hypothesized that time management influences perceived control of time and psychological stress response, and perceived control of time influences psychological stress response. The results showed that time estimation increases the perceived control of time, which in turn decreases stress response. However, we also found that taking each moment as it comes reduces perceived control of time, which in turn increases stress response.

Adaptation to the Spanish population of the Substance Use Risk Profile Scale (SURPS) and psychometric properties.

PubMed

Fernández-Calderón, Fermín; Díaz-Batanero, Carmen; Rojas-Tejada, Antonio J; Castellanos-Ryan, Natalie; Lozano-Rojas, Óscar M

2017-07-14

The identification of different personality risk profiles for substance misuse is useful in preventing substance-related problems. This study aims to test the psychometric properties of a new version of the Substance Use Risk Profile Scale (SURPS) for Spanish college students. Cross-sectional study with 455 undergraduate students from four Spanish universities. A new version of the SURPS, adapted to the Spanish population, was administered with the Beck Hopelessness Scale, the UPPS-P Impulsive Behavior Scale, the State-Trait Anxiety Inventory (STAI) and the Alcohol Use Disorders Identification Test (AUDIT). Internal consistency reliability ranged between 0.652 and 0.806 for the four SURPS subscales, while reliability estimated by split-half coefficients varied from 0.686 to 0.829. The estimated test-retest reliability ranged between 0.733 and 0.868. The expected four-factor structure of the original scale was replicated. As evidence of convergent validity, we found that the SURPS subscales were significantly associated with other conceptually-relevant personality scales and significantly associated with alcohol use measures in theoretically-expected ways. This SURPS version may be a useful instrument for measuring personality traits related to vulnerability to substance use and misuse when targeting personality with preventive interventions.

Application of a mechanistic model as a tool for on-line monitoring of pilot scale filamentous fungal fermentation processes-The importance of evaporation effects.

PubMed

Mears, Lisa; Stocks, Stuart M; Albaek, Mads O; Sin, Gürkan; Gernaey, Krist V

2017-03-01

A mechanistic model-based soft sensor is developed and validated for 550L filamentous fungus fermentations operated at Novozymes A/S. The soft sensor is comprised of a parameter estimation block based on a stoichiometric balance, coupled to a dynamic process model. The on-line parameter estimation block models the changing rates of formation of product, biomass, and water, and the rate of consumption of feed using standard, available on-line measurements. This parameter estimation block, is coupled to a mechanistic process model, which solves the current states of biomass, product, substrate, dissolved oxygen and mass, as well as other process parameters including k L a, viscosity and partial pressure of CO 2 . State estimation at this scale requires a robust mass model including evaporation, which is a factor not often considered at smaller scales of operation. The model is developed using a historical data set of 11 batches from the fermentation pilot plant (550L) at Novozymes A/S. The model is then implemented on-line in 550L fermentation processes operated at Novozymes A/S in order to validate the state estimator model on 14 new batches utilizing a new strain. The product concentration in the validation batches was predicted with an average root mean sum of squared error (RMSSE) of 16.6%. In addition, calculation of the Janus coefficient for the validation batches shows a suitably calibrated model. The robustness of the model prediction is assessed with respect to the accuracy of the input data. Parameter estimation uncertainty is also carried out. The application of this on-line state estimator allows for on-line monitoring of pilot scale batches, including real-time estimates of multiple parameters which are not able to be monitored on-line. With successful application of a soft sensor at this scale, this allows for improved process monitoring, as well as opening up further possibilities for on-line control algorithms, utilizing these on-line model outputs. Biotechnol. Bioeng. 2017;114: 589-599. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Measurement characteristics of the levels of institutionalization scales: examining reliability and validity.

PubMed

Barab, S A; Redman, B K; Froman, R D

1998-01-01

The Level of Institutionalization (LoIn) scales were developed to assess the extent to which a health promotion program has become integrated into a health care organization. The instrument was designed specifically to measure the amount of routinization and niche saturation of four subsystems (production, maintenance, supportive, and managerial) believed to make up an organization. In this study, the LoIn scales were completed for diabetes programs in 102 general hospitals and 30 home health agencies in Maryland and Pennsylvania. Reliability estimates across the four subsystems for routines (alpha = .61) and for niche saturation (alpha = .44) were substandard. Average correlation among the four subsystems for routines was .67, and among the four subsystems for niche saturation was .38, indicating moderate to large amounts of shared variance among subsystems and challenging claims of discriminant validity. Given these large correlations and a poor fit when testing the eight-factor model, higher-order confirmatory factor analyses were carried out. Results supported the existence of two second-order factors. When collapsed into two factors, the reliabilities were adequate (routines alpha = .90; niche saturation alpha = .80). Criterion-related validity also was found between length of program existence and the routine factor.

Coastal erosion vulnerability and risk assessment focusing in tourism beach use.

NASA Astrophysics Data System (ADS)

Alexandrakis, George

2016-04-01

It is well established that the global market for tourism services is a key source of economic growth. Especially among Mediterranean countries, the tourism sector is one of the principal sectors driving national economies. With the majority of the mass tourism activities concentrated around coastal areas, coastal erosion, inter alia, poses a significant threat to coastal economies that depend heavily on revenues from tourism. The economic implications of beach erosion were mainly focused in the cost of coastal protection measures, instead of the revenue losses from tourism. For this, the vulnerability of the coast to sea level rise and associated erosion, in terms of expected land loss and economic activity need to be identified. To achieve this, a joint environmental and economic evaluation approach of the problem can provide a managerial tool to mitigate the impact of beach erosion in tourism, through realistic cost-benefit scenarios for planning alternative protection measures. Such a multipurpose tool needs to consider social, economic and environmental factors, which relationships can be better understood when distributed and analyzed along the geographical space. The risk assessment is implemented through the estimation of the vulnerability and exposure variables of the coast in two scales. The larger scale estimates the vulnerability in a regional level, with the use environmental factors with the use of CVI. The exposure variable is estimated by the use of socioeconomic factors. Subsequently, a smaller scale focuses on highly vulnerable beaches with high social and economic value. The assessment of the natural processes to the environmental characteristics of the beach is estimated with the use of the Beach Vulnerability Index (BVI) method. As exposure variable, the value of beach width that is capitalized in revenues is implemented through a hedonic pricing model. In this econometric modelling, Beach Value is related with economic and environmental attributes like, Beach width, distance from the city) of each sector, tourism attributes (Coastal business; Number of hotels; Number of hotel rooms; Room price; Beach attendance). All calculations are implemented in a GIS database, organised in five levels. As case study area for the application of the method is selected Crete Island, while for the small scale four beach tourist destinations in the Island of Crete, with different vulnerabilities. In the small scale vulnerability analysis, the sectors of the beach which are most vulnerable were identified, and risk analysis was made based on the revenue losses. Acknowledgments This work was implemented within the framework of "Post-Doctoral Excellence Scholarship. State Scholarships Foundation, Greece IKY-Siemens Action"

The calibration analysis of soil infiltration formula in farmland scale

NASA Astrophysics Data System (ADS)

Qian, Tao; Han, Na Na; Chang, Shuan Ling

2018-06-01

Soil infiltration characteristic is an important basis of farmland scale parameter estimation. Based on 12 groups of double-loop infiltration tests conducted in the test field of tianjin agricultural university west campus. Based on the calibration theory and the combination of statistics, the calibration analysis of phillips formula was carried out and the spatial variation characteristics of the calibration factor were analyzed. Results show that in study area based on the soil stability infiltration rate A calculate calibration factor αA calibration effect is best, that is suitable for the area formula of calibration infiltration and αA variation coefficient is 0.3234, with A certain degree of spatial variability.

Estimating temporal changes in soil carbon stocks at ecoregional scale in Madagascar using remote-sensing

NASA Astrophysics Data System (ADS)

Grinand, C.; Maire, G. Le; Vieilledent, G.; Razakamanarivo, H.; Razafimbelo, T.; Bernoux, M.

2017-02-01

Soil organic carbon (SOC) plays an important role in climate change regulation notably through release of CO2 following land use change such a deforestation, but data on stock change levels are lacking. This study aims to empirically assess SOC stocks change between 1991 and 2011 at the landscape scale using easy-to-access spatially-explicit environmental factors. The study area was located in southeast Madagascar, in a region that exhibits very high rate of deforestation and which is characterized by both humid and dry climates. We estimated SOC stock on 0.1 ha plots for 95 different locations in a 43,000 ha reference area covering both dry and humid conditions and representing different land cover including natural forest, cropland, pasture and fallows. We used the Random Forest algorithm to find out the environmental factors explaining the spatial distribution of SOC. We then predicted SOC stocks for two soil layers at 30 cm and 100 cm over a wider area of 395,000 ha. By changing the soil and vegetation indices derived from remote sensing images we were able to produce SOC maps for 1991 and 2011. Those estimates and their related uncertainties where combined in a post-processing step to map estimates of significant SOC variations and we finally compared the SOC change map with published deforestation maps. Results show that the geologic variables, precipitation, temperature, and soil-vegetation status were strong predictors of SOC distribution at regional scale. We estimated an average net loss of 10.7% and 5.2% for the 30 cm and the 100 cm layers respectively for deforested areas in the humid area. Our results also suggest that these losses occur within the first five years following deforestation. No significant variations were observed for the dry region. This study provides new solutions and knowledge for a better integration of soil threats and opportunities in land management policies.

Large-scale dark diversity estimates: new perspectives with combined methods.

PubMed

Ronk, Argo; de Bello, Francesco; Fibich, Pavel; Pärtel, Meelis

2016-09-01

Large-scale biodiversity studies can be more informative if observed diversity in a study site is accompanied by dark diversity, the set of absent although ecologically suitable species. Dark diversity methodology is still being developed and a comparison of different approaches is needed. We used plant data at two different scales (European and seven large regions) and compared dark diversity estimates from two mathematical methods: species co-occurrence (SCO) and species distribution modeling (SDM). We used plant distribution data from the Atlas Florae Europaeae (50 × 50 km grid cells) and seven different European regions (10 × 10 km grid cells). Dark diversity was estimated by SCO and SDM for both datasets. We examined the relationship between the dark diversity sizes (type II regression) and the overlap in species composition (overlap coefficient). We tested the overlap probability according to the hypergeometric distribution. We combined the estimates of the two methods to determine consensus dark diversity and composite dark diversity. We tested whether dark diversity and completeness of site diversity (log ratio of observed and dark diversity) are related to various natural and anthropogenic factors differently than simple observed diversity. Both methods provided similar dark diversity sizes and distribution patterns; dark diversity is greater in southern Europe. The regression line, however, deviated from a 1:1 relationship. The species composition overlap of two methods was about 75%, which is much greater than expected by chance. Both consensus and composite dark diversity estimates showed similar distribution patterns. Both dark diversity and completeness measures exhibit relationships to natural and anthropogenic factors different than those exhibited by observed richness. In summary, dark diversity revealed new biodiversity patterns which were not evident when only observed diversity was examined. A new perspective in dark diversity studies can incorporate a combination of methods.

The Balanced Inventory of Desirable Responding (BIDR): A Reliability Generalization Study

ERIC Educational Resources Information Center

Li, Andrew; Bagger, Jessica

2007-01-01

The Balanced Inventory of Desirable Responding (BIDR) is one of the most widely used social desirability scales. The authors conducted a reliability generalization study to examine the typical reliability coefficients of BIDR scores and explored factors that explained the variability of reliability estimates across studies. The results indicated…

Regional-scale controls on dissolved nitrous oxide in the Upper Mississippi River

USDA-ARS?s Scientific Manuscript database

Bottom-up estimates of riverine nitrous oxide (N2O) emissions developed by the Intergovernmental Panel on Climate Change (IPCC) assume a constant emission factor (EF5r) that predicts N2O production from anthropogenic nitrogen inputs. This relation ignores any direct stream water biochemical charact...

Measuring the Nursing Work Environment in Mainland China: Further Development of the Chinese Nursing Work Environment Scale.

PubMed

Shao, Jing; Tang, Leiwen; Ye, Zhihong

For the stabilization of the nursing profession in mainland China, a valid and reliable nursing work environment instrument, grounded in China's context, should be developed to better provide rigorous evidence for policy makers. The purpose of the current research was to further develop a scale that could capture the characteristics of the nursing work environment in mainland China. A convenience sample of 542 nurses employed in a tertiary hospital of mainland China completed the 108-item Chinese Nursing Work Environment (C-NWE) Scale (1st ed.). Items that did not differentiate between respondents with the highest and lowest 27% of total scores and those that did not meet criteria for factor loadings were set aside. Exploratory factor analysis based on the maximum likelihood method was used to identify the structure of the scale. The chi-square test was used to evaluate model fit, and expert review was conducted to test content validity. Reliability was estimated using Cronbach's alpha coefficient. The revised C-NWE Scale, which consists of nine subscales and 47 items, is a simplified version of the C-NWE (1st ed.). Using exploratory maximum likelihood factor analysis, the normed chi-square fit index for a nine-factor solution was 1.97. The content validity index for the total scale was 0.93; Cronbach's alpha was .94. Initial evidence of the psychometric properties of C-NWE scores was presented. Further studies could be conducted in various settings to identify the C-NWE Scale's validity and reliability.

Development of emission factors for polycarbonate processing.

PubMed

Rhodes, Verne L; Kriek, George; Lazear, Nelson; Kasakevich, Jean; Martinko, Marie; Heggs, R P; Holdren, M W; Wisbith, A S; Keigley, G W; Williams, J D; Chuang, J C; Satola, J R

2002-07-01

Emission factors for selected volatile organic compounds (VOCs) and particulate emissions were developed while processing eight commercial grades of polycarbonate (PC) and one grade of a PC/acrylonitrile-butadiene-styrene (ABS) blend. A small commercial-type extruder was used, and the extrusion temperature was held constant at 304 degrees C. An emission factor was calculated for each substance measured and is reported as pounds released to the atmosphere/million pounds of polymer resin processed [ppm (wt/wt)]. Scaled to production volumes, these emission factors can be used by processors to estimate emission quantities from similar PC processing operations.

Rates and potentials of soil organic carbon sequestration in agricultural lands in Japan: an assessment using a process-based model and spatially-explicit land-use change inventories

NASA Astrophysics Data System (ADS)

Yagasaki, Y.; Shirato, Y.

2013-11-01

In order to develop a system to estimate a country-scale soil organic carbon stock change (SCSC) in agricultural lands in Japan that enables to take account effect of land-use changes, climate, different agricultural activity and nature of soils, a spatially-explicit model simulation system using Rothamsted Carbon Model (RothC) integrated with spatial and temporal inventories was developed. Future scenarios on agricultural activity and land-use change were prepared, in addition to future climate projections by global climate models, with purposely selecting rather exaggerated and contrasting set of scenarios to assess system's sensitivity as well as to better factor out direct human influence in the SCSC accounting. Simulation was run from year 1970 to 2008, and to year 2020, with historical inventories and future scenarios involving target set in agricultural policy, respectively, and subsequently until year 2100 with no temporal changes in land-use and agricultural activity but with varying climate to investigate course of SCSC. Results of the country-scale SCSC simulation have indicated that conversion of paddy fields to croplands occurred during past decades, as well as a large conversion of agricultural fields to settlements or other lands that have occurred in historical period and would continue in future, could act as main factors causing greater loss of soil organic carbon (SOC) at country-scale, with reduction organic carbon input to soils and enhancement of SOC decomposition by transition of soil environment to aerobic conditions, respectively. Scenario analysis indicated that an option to increase organic carbon input to soils with intensified rotation with suppressing conversion of agricultural lands to other land-use types could achieve reduction of CO2 emission due to SCSC in the same level as that of another option to let agricultural fields be abandoned. These results emphasize that land-use changes, especially conversion of the agricultural lands to other land-use types by abandoning or urbanization accompanied by substantial changes in the rate of organic carbon input to soils, could cause a greater or comparable influence on country-scale SCSC compared with changes in management of agricultural lands. A net-net based accounting on SCSC showed potential influence of variations in future climate on SCSC, that highlighted importance of application of process-based model for estimation of this quantity. Whereas a baseline-based accounting on SCSC was shown to have robustness over variations in future climate and effectiveness to factor out direct human-induced influence on SCSC. Validation of the system's function to estimate SCSC in agricultural lands, by comparing simulation output with data from nation-wide stationary monitoring conducted during year 1979-1998, suggested that the system has an acceptable levels of validity, though only for limited range of conditions at current stage. In addition to uncertainties in estimation of the rate of organic carbon input to soils in different land-use types at large-scale, time course of SOC sequestration, supposition on land-use change pattern in future, as well as feasibility of agricultural policy planning are considered as important factors that need to be taken account in estimation on a potential of country-scale SCSC.

Neighborhood street scale elements, sedentary time and cardiometabolic risk factors in inactive ethnic minority women.

PubMed

Lee, Rebecca E; Mama, Scherezade K; Adamus-Leach, Heather J

2012-01-01

Cardiometabolic risk factors such as obesity, excess percent body fat, high blood pressure, elevated resting heart rate and sedentary behavior have increased in recent decades due to changes in the environment and lifestyle. Neighborhood micro-environmental, street scale elements may contribute to health above and beyond individual characteristics of residents. To investigate the relationship between neighborhood street scale elements and cardiometabolic risk factors among inactive ethnic minority women. Women (N = 410) completed measures of BMI, percent body fat, blood pressure, resting heart rate, sedentary behavior and demographics. Trained field assessors completed the Pedestrian Environment Data Scan in participants' neighborhoods. Data were collected from 2006-2008. Multiple regression models were conducted in 2011 to estimate the effect of environmental factors on cardiometabolic risk factors. Adjusted regression models found an inverse association between sidewalk buffers and blood pressure, between traffic control devices and resting heart rate, and a positive association between presence of pedestrian crossing aids and BMI (ps<.05). Neighborhood attractiveness and safety for walking and cycling were related to more time spent in a motor vehicle (ps<.05). Findings suggest complex relationships among micro-environmental, street scale elements that may confer important cardiometabolic benefits and risks for residents. Living in the most attractive and safe neighborhoods for physical activity may be associated with longer times spent sitting in the car.

Validation of the Italian version of the HSE Indicator Tool.

PubMed

Magnavita, N

2012-06-01

An Italian version of the Health & Safety Executive's (HSE) Management Standards Revised Indicator Tool (MS-RIT) has been used to monitor the working conditions that may lead to stress. To initially examine the factor structure of the Italian version of the MS-RIT, in comparison with the original UK tool, and to investigate its validity and reliability; second, to study the association between occupational stress and psychological distress. Workers from 17 companies self-completed the MS-RIT and the General Health Questionnaire used to measure the psychological distress while they waited for their periodic examination at the workplace. Factor analysis was employed to ascertain whether the Italian version maintained the original subdivision into seven scales. Odds ratios were calculated to estimate the risk of impairment associated with exposure to stress at the workplace. In total, 748 workers participated; the response rate was 91%. The factor structure of the Italian MS-RIT corresponded partially to the original UK version. The 'demand', 'control', 'role', ' relationship' and 'colleague-support' scales were equivalent to the UK ones. A principal factor, termed ' elasticity', incorporated the UK 'management-support' and 'change' scales. Reliability analysis of the sub-scales revealed Cronbach's alpha values ranging from 0.75 to 0.86. Our findings confirmed the usefulness of the Italian version of the HSE MS-RIT in stress control.

A Modified Rodrigues Parameter-based Nonlinear Observer Design for Spacecraft Gyroscope Parameters Estimation

NASA Astrophysics Data System (ADS)

Yong, Kilyuk; Jo, Sujang; Bang, Hyochoong

This paper presents a modified Rodrigues parameter (MRP)-based nonlinear observer design to estimate bias, scale factor and misalignment of gyroscope measurements. A Lyapunov stability analysis is carried out for the nonlinear observer. Simulation is performed and results are presented illustrating the performance of the proposed nonlinear observer under the condition of persistent excitation maneuver. In addition, a comparison between the nonlinear observer and alignment Kalman filter (AKF) is made to highlight favorable features of the nonlinear observer.

Technical efficiency of selected hospitals in Eastern Ethiopia.

PubMed

Ali, Murad; Debela, Megersa; Bamud, Tewfik

2017-12-01

This study examines the relative technical efficiency of 12 hospitals in Eastern Ethiopia. Using six-year-round panel data for the period between 2007/08 and 2012/13, this study examines the technical efficiency, total factor productivity, and determinants of the technical inefficiency of hospitals. Data envelopment analysis (DEA) and DEA- based Malmquist productivity index used to estimate relative technical efficiency, scale efficiency, and total factor productivity index of hospitals. Tobit model used to examine the determinants of the technical inefficiency of hospitals. The DEA Variable Returns to Scale (VRS) estimate indicated that 6 (50%), 5 (42%), 3 (25%), 3 (25%), 4 (33%), and 3 (25%) of the hospitals were technically inefficient while 9 (75%), 9 (75%), 7 (58%), 7 (58%), 7 (58%) and 8 (67%) of hospitals were scale inefficient between 2007/08 and 2012/13, respectively. On average, Malmquist Total Factor Productivity (MTFP) of the hospitals decreased by 3.6% over the panel period. The Tobit model shows that teaching hospital is less efficiency than other hospitals. The Tobit regression model further shows that medical doctor to total staff ratio, the proportion of outpatient visit to inpatient days, and the proportion of inpatients treated per medical doctor were negatively related with technical inefficiency of hospitals. Hence, policy interventions that help utilize excess capacity of hospitals, increase doctor to other staff ratio, and standardize number of inpatients treated per doctor would contribute to the improvement of the technical efficiency of hospitals.

Orientation to the Caregiver Role Among Latinas of Mexican Origin

PubMed Central

Mendez-Luck, Carolyn A.; John Geldhof, G.; Anthony, Katherine P.; Neil Steers, W.; Mangione, Carol M.; Hays, Ron D.

2016-01-01

Purpose of the Study: To develop the Caregiver Orientation Scale for Mexican-Origin Women and evaluate its psychometric properties. Design and Methods: We developed a questionnaire to measure domains of cultural orientation to the caregiver role based on formative research and on the Cultural Justifications for Caregiving Scale. We conducted a series of exploratory factor analyses (EFAs) on data collected from 163 caregivers. We estimated internal consistency reliability (Cronbach’s coefficient alpha) and assessed construct validity by estimating correlations between all latent factors and self-rated health, interview language, and weekly hours of care. Results: EFAs suggested four factors representing familism, obligation, burden, and caregiving intensity that displayed good fit (χ2 (df = 63) = 70.52, p = .24; RMSEA = .03 [90% CI: 0.00, 0.06]; comparative fit index = .99). Multi-item scales representing the four domains had coefficient alphas ranging from .68 to .86. Obligation was positively associated with burden (.46, p < .001) and intensity (.34, p < .01), which were themselves positively correlated (.63, p < .001). Familism was positively associated with obligation (.25, p < .05) yet negatively associated with burden (−.35, p < .01) and intensity (−.22, p < .05). Weekly hours of care were positively associated with burden (.26, p < .01) and intensity (.18, p < .05), whereas self-rated health and burden (−.21, p < .05) and Spanish language and intensity (−.31, p < .001) were negatively correlated. Implications: The study shows that Mexican-origin caregiver orientation is multidimensional and that caregivers may have conflicting motivations for caregiving. PMID:27342443

Personal Factors that Affect the Satisfaction of Female Patients Undergoing Esthetic Suture after Typical Thyroidectomy.

PubMed

Kim, Hyo Young; Kim, Jung Won; Park, Jin Hyung; Kim, Jung Hun; Han, Yea Sik

2013-07-01

In esthetic surgery, understanding the factors that influence patient satisfaction is important for successful practice. We hypothesize that the factors that influence patient satisfaction include not only aesthetic and functional outcomes, but also personal factors such as the level of familiarity with factors affecting wound healing and expectations regarding aesthetic outcome. One hundred patients who underwent esthetic closure after thyroidectomy were included in this study. In order to evaluate the individual characteristics of the patients, a preoperative survey was administered to the patients. We estimated the patient satisfaction six months postoperatively and assessed the aesthetic and functional outcomes using the Patient and Observer Scar Assessment Scale. According to the results of correlation analysis, level of familiarity with wound healing factors had a positive correlation with satisfaction. High expectations, pain, itching, and high observer scale score had negative correlations with satisfaction. The factors that were correlated with satisfaction were included in the multiple regression analysis. Level of familiarity with wound healing factors was found to have a positive relationship with satisfaction, while itching and observer scale were found to have a negative relationship with satisfaction. After excluding 10 patients who had hypertrophic scars, only level of familiarity with wound healing factors and expectations affected satisfaction. The level of familiarity with factors affecting wound healing and expectations were found to independently affect satisfaction. Improving patients' level of familiarity with wound healing factors and reducing their expectations by providing suitable preoperative education has the potential to improve patient satisfaction.

Constructing the Japanese version of the Maslach Burnout Inventory-Student Survey: Confirmatory factor analysis.

PubMed

Tsubakita, Takashi; Shimazaki, Kazuyo

2016-01-01

To examine the factorial validity of the Maslach Burnout Inventory-Student Survey, using a sample of 2061 Japanese university students majoring in the medical and natural sciences (67.9% male, 31.8% female; Mage  = 19.6 years, standard deviation = 1.5). The back-translated scale used unreversed items to assess inefficacy. The inventory's descriptive properties and Cronbach's alphas were calculated using SPSS software. The present authors compared fit indices of the null, one factor, and default three factor models via confirmatory factor analysis with maximum-likelihood estimation using AMOS software, version 21.0. Intercorrelations between exhaustion, cynicism, and inefficacy were relatively higher than in prior studies. Cronbach's alphas were 0.76, 0.85, and 0.78, respectively. Although fit indices of the hypothesized three factor model did not meet the respective criteria, the model demonstrated better fit than did the null and one factor models. The present authors added four paths between error variables within items, but the modified model did not show satisfactory fit. Subsequent analysis revealed that a bi-factor model fit the data better than did the hypothesized or modified three factor models. The Japanese version of the Maslach Burnout Inventory-Student Survey needs minor changes to improve the fit of its three factor model, but the scale as a whole can be used to adequately assess overall academic burnout in Japanese university students. Although the scale was back-translated, two items measuring exhaustion whose expressions overlapped should be modified, and all items measuring inefficacy should be reversed in order to statistically clarify the factorial difference between the scale's three factors. © 2015 The Authors. Japan Journal of Nursing Science © 2015 Japan Academy of Nursing Science.

Polish adaptation of three self-report measures of job stressors: the Interpersonal Conflict at Work Scale, the Quantitative Workload Inventory and the Organizational Constraints Scale.

PubMed

Baka, Łukasz; Bazińska, Róża

2016-01-01

The objective of the present study was to test the psychometric properties, reliability and validity of three job stressor measures, namely, the Interpersonal Conflict at Work Scale, the Organizational Constraints Scale and the Quantitative Workload Inventory. The study was conducted on two samples (N = 382 and 3368) representing a wide range of occupations. The estimation of internal consistency with Cronbach's α and the test-retest method as well as both exploratory and confirmatory factor analyses were the main statistical methods. The internal consistency of the scales proved satisfactory, ranging from 0.80 to 0.90 for Cronbach's α test and from 0.72 to 0.86 for the test-retest method. The one-dimensional structure of the three measurements was confirmed. The three scales have acceptable fit to the data. The one-factor structures and other psychometric properties of the Polish version of the scales seem to be similar to those found in the US version of the scales. It was also proved that the three job stressors are positively related to all the job strain measures. The Polish versions of the three analysed scales can be used to measure the job stressors in Polish conditions.

Polish adaptation of three self-report measures of job stressors: the Interpersonal Conflict at Work Scale, the Quantitative Workload Inventory and the Organizational Constraints Scale

PubMed Central

Baka, Łukasz; Bazińska, Róża

2016-01-01

Aim. The objective of the present study was to test the psychometric properties, reliability and validity of three job stressor measures, namely, the Interpersonal Conflict at Work Scale, the Organizational Constraints Scale and the Quantitative Workload Inventory. Method. The study was conducted on two samples (N = 382 and 3368) representing a wide range of occupations. The estimation of internal consistency with Cronbach's α and the test–retest method as well as both exploratory and confirmatory factor analyses were the main statistical methods. Results. The internal consistency of the scales proved satisfactory, ranging from 0.80 to 0.90 for Cronbach's α test and from 0.72 to 0.86 for the test–retest method. The one-dimensional structure of the three measurements was confirmed. The three scales have acceptable fit to the data. The one-factor structures and other psychometric properties of the Polish version of the scales seem to be similar to those found in the US version of the scales. It was also proved that the three job stressors are positively related to all the job strain measures. Conclusions. The Polish versions of the three analysed scales can be used to measure the job stressors in Polish conditions. PMID:26652317

Removal of Iron Oxide Scale from Feed-water in Thermal Power Plant by Using Magnetic Separation

NASA Astrophysics Data System (ADS)

Nakanishi, Motohiro; Shibatani, Saori; Mishima, Fumihito; Akiyama, Yoko; Nishijima, Shigehiro

2017-09-01

One of the factors of deterioration in thermal power generation efficiency is adhesion of the scale to inner wall in feed-water system. Though thermal power plants have employed All Volatile Treatment (AVT) or Oxygen Treatment (OT) to prevent scale formation, these treatments cannot prevent it completely. In order to remove iron oxide scale, we proposed magnetic separation system using solenoidal superconducting magnet. Magnetic separation efficiency is influenced by component and morphology of scale which changes their property depending on the type of water treatment and temperature. In this study, we estimated component and morphology of iron oxide scale at each equipment in the feed-water system by analyzing simulated scale generated in the pressure vessel at 320 K to 550 K. Based on the results, we considered installation sites of the magnetic separation system.

Investigation of the physical scaling of sea spray spume droplet production

NASA Astrophysics Data System (ADS)

Fairall, C. W.; Banner, M. L.; Peirson, W. L.; Asher, W.; Morison, R. P.

2009-10-01

In this paper we report on a laboratory study, the Spray Production and Dynamics Experiment (SPANDEX), conducted at the University of New South Wales Water Research Laboratory in Australia. The goals of SPANDEX were to illuminate physical aspects of spume droplet production and dispersion; verify theoretical simplifications used to estimate the source function from ambient droplet concentration measurements; and examine the relationship between the implied source strength and forcing parameters such as wind speed, surface turbulent stress, and wave properties. Observations of droplet profiles give reasonable confirmation of the basic power law profile relationship that is commonly used to relate droplet concentrations to the surface source strength. This essentially confirms that, even in a wind tunnel, there is a near balance between droplet production and removal by gravitational settling. The observations also indicate considerable droplet mass may be present for sizes larger than 1.5 mm diameter. Phase Doppler Anemometry observations revealed significant mean horizontal and vertical slip velocities that were larger closer to the surface. The magnitude seems too large to be an acceleration time scale effect. Scaling of the droplet production surface source strength proved to be difficult. The wind speed forcing varied only 23% and the stress increased a factor of 2.2. Yet, the source strength increased by about a factor of 7. We related this to an estimate of surface wave energy flux through calculations of the standard deviation of small-scale water surface disturbance, a wave-stress parameterization, and numerical wave model simulations. This energy index only increased by a factor of 2.3 with the wind forcing. Nonetheless, a graph of spray mass surface flux versus surface disturbance energy is quasi-linear with a substantial threshold.

The importance of regional models in assessing canine cancer incidences in Switzerland

PubMed Central

Leyk, Stefan; Brunsdon, Christopher; Graf, Ramona; Pospischil, Andreas; Fabrikant, Sara Irina

2018-01-01

Fitting canine cancer incidences through a conventional regression model assumes constant statistical relationships across the study area in estimating the model coefficients. However, it is often more realistic to consider that these relationships may vary over space. Such a condition, known as spatial non-stationarity, implies that the model coefficients need to be estimated locally. In these kinds of local models, the geographic scale, or spatial extent, employed for coefficient estimation may also have a pervasive influence. This is because important variations in the local model coefficients across geographic scales may impact the understanding of local relationships. In this study, we fitted canine cancer incidences across Swiss municipal units through multiple regional models. We computed diagnostic summaries across the different regional models, and contrasted them with the diagnostics of the conventional regression model, using value-by-alpha maps and scalograms. The results of this comparative assessment enabled us to identify variations in the goodness-of-fit and coefficient estimates. We detected spatially non-stationary relationships, in particular, for the variables related to biological risk factors. These variations in the model coefficients were more important at small geographic scales, making a case for the need to model canine cancer incidences locally in contrast to more conventional global approaches. However, we contend that prior to undertaking local modeling efforts, a deeper understanding of the effects of geographic scale is needed to better characterize and identify local model relationships. PMID:29652921

The importance of regional models in assessing canine cancer incidences in Switzerland.

PubMed

Boo, Gianluca; Leyk, Stefan; Brunsdon, Christopher; Graf, Ramona; Pospischil, Andreas; Fabrikant, Sara Irina

2018-01-01

Fitting canine cancer incidences through a conventional regression model assumes constant statistical relationships across the study area in estimating the model coefficients. However, it is often more realistic to consider that these relationships may vary over space. Such a condition, known as spatial non-stationarity, implies that the model coefficients need to be estimated locally. In these kinds of local models, the geographic scale, or spatial extent, employed for coefficient estimation may also have a pervasive influence. This is because important variations in the local model coefficients across geographic scales may impact the understanding of local relationships. In this study, we fitted canine cancer incidences across Swiss municipal units through multiple regional models. We computed diagnostic summaries across the different regional models, and contrasted them with the diagnostics of the conventional regression model, using value-by-alpha maps and scalograms. The results of this comparative assessment enabled us to identify variations in the goodness-of-fit and coefficient estimates. We detected spatially non-stationary relationships, in particular, for the variables related to biological risk factors. These variations in the model coefficients were more important at small geographic scales, making a case for the need to model canine cancer incidences locally in contrast to more conventional global approaches. However, we contend that prior to undertaking local modeling efforts, a deeper understanding of the effects of geographic scale is needed to better characterize and identify local model relationships.

Clinician and Patient-reported Outcomes Are Associated With Psychological Factors in Patients With Chronic Shoulder Pain.

PubMed

Wolfensberger, Adrian; Vuistiner, Philippe; Konzelmann, Michel; Plomb-Holmes, Chantal; Léger, Bertrand; Luthi, François

2016-09-01

Validated clinician outcome scores are considered less associated with psychosocial factors than patient-reported outcome measurements (PROMs). This belief may lead to misconceptions if both instruments are related to similar factors. We asked: In patients with chronic shoulder pain, what biopsychosocial factors are associated (1) with PROMs, and (2) with clinician-rated outcome measurements? All new patients between the ages of 18 and 65 with chronic shoulder pain from a unilateral shoulder injury admitted to a Swiss rehabilitation teaching hospital between May 2012 and January 2015 were screened for potential contributing biopsychosocial factors. During the study period, 314 patients were screened, and after applying prespecified criteria, 158 patients were evaluated. The median symptom duration was 9 months (interquartile range, 5.5-15 months), and 72% of the patients (114 patients) had rotator cuff tears, most of which were work injuries (59%, 93 patients) and were followed for a mean of 31.6 days (SD, 7.5 days). Exclusion criteria were concomitant injuries in another location, major or minor upper limb neuropathy, and inability to understand the validated available versions of PROMs. The PROMs were the DASH, the Brief Pain Inventory, and the Patient Global Impression of Change, before and after treatment (physiotherapy, cognitive therapy and vocational training). The Constant-Murley score was used as a clinician-rated outcome measurement. Statistical models were used to estimate associations between biopsychosocial factors and outcomes. Greater disability on the DASH was associated with psychological factors (Hospital Anxiety and Depression Scale, Pain Catastrophizing Scale combined coefficient, 0.64; 95% CI, 0.25-1.03; p = 0.002) and social factors (language, professional qualification combined coefficient, -6.15; 95% CI, -11.09 to -1.22; p = 0.015). Greater pain on the Brief Pain Inventory was associated with psychological factors (Hospital Anxiety and Depression Scale, Pain Catastrophizing Scale combined coefficient, 0.076; 95% CI, 0.021-0.13; p = 0.006). Poorer impression of change was associated with psychological factors (Hospital Anxiety and Depression Scale, Pain Catastrophizing Scale, Tampa Scale of Kinesiophobia coefficient, 0.93; 95% CI, 0.87-0.99; p = 0.026) and social factors (education, language, and professional qualification coefficient, 6.67; 95% CI, 2.77-16.10; p < 0.001). Worse clinician-rated outcome was associated only with psychological factors (Hospital Anxiety and Depression Scale (depression only), Pain Catastrophizing Scale, Tampa Scale of Kinesiophobia combined coefficient, -0.35; 95% CI, -0.58 to -0.12; p = 0.003). Depressive symptoms and catastrophizing appear to be key factors influencing PROMs and clinician-rated outcomes. This study suggests revisiting the Constant-Murley score. Level III, prognostic study.

Preliminary psychometric testing of the Fox Simple Quality-of-Life Scale.

PubMed

Fox, Sherry

2004-06-01

Although quality of life is extensively defined as subjective and multidimensional with both affective and cognitive components, few instruments capture important dimensions of the construct, and few are both conceptually congruent and user friendly for the clinical setting. The aim of this study was to develop and test a measure that would be easy to use clinically and capture both cognitive and affective components of quality of life. Initial item sources for the Fox Simple Quality-of-Life Scale (FSQOLS) were literature-based. Thirty items were compiled for content validity assessment by a panel of expert healthcare clinicians from various disciplines, predominantly nursing. Five items were removed as a result of the review because they reflected negatively worded or redundant items. The 25-item scale was mailed to 177 people with lung, colon, and ovarian cancer in various stages. Cancer types were selected theoretically, based on similarity in prognosis, degree of symptom burden, and possible meaning and experience. Of the 145 participants, all provided complete data on the FSQOLS. Psychometric evaluation of the FSQOLS included item-total correlations, principal components analysis with varimax rotation revealing two factors explaining 50% variance, reliability estimation using alpha estimates, and item-factor correlations. The FSQOLS exhibited significant convergent validity with four popular quality-of-life instruments: the Ferrans and Powers Quality of Life Index, the Functional Assessment of Cancer Therapy Scale, the Short-Form-36 Health Survey, and the General Well-Being Scale. Content validity of the scale was explored and supported using qualitative interviews of 14 participants with lung, colon and ovarian cancer, who were a subgroup of the sample for the initial instrument testing.

Economies of scale in federally-funded state-organized public health programs: results from the National Breast and Cervical Cancer Early Detection Programs

PubMed Central

Trogdon, Justin G.; Subramanian, Sujha; Crouse, Wesley

2018-01-01

This study investigates the existence of economies of scale in the provision of breast and cervical cancer screening and diagnostic services by state National Breast and Cervical Cancer Early Detection Program (NBCCEDP) grantees. A translog cost function is estimated as a system with input factor share equations. The estimated cost function is then used to determine output levels for which average costs are decreasing (i.e., economies of scale exist). Data were collected from all state NBCCEDP programs and District of Columbia for program years 2006–2007, 2008–2009 and 2009–2010 (N =147). Costs included all programmatic and in-kind contributions from federal and non-federal sources, allocated to breast and cervical cancer screening activities. Output was measured by women served, women screened and cancers detected, separately by breast and cervical services for each measure. Inputs included labor, rent and utilities, clinical services, and quasi-fixed factors (e.g., percent of women eligible for screening by the NBCCEDP). 144 out of 147 program-years demonstrated significant economies of scale for women served and women screened; 136 out of 145 program-years displayed significant economies of scale for cancers detected. The cost data were self-reported by the NBCCEDP State programs. Quasi-fixed inputs were allowed to affect costs but not economies of scale or the share equations. The main analysis accounted for clustering of observations within State programs, but it did not make full use of the panel data. The average cost of providing breast and cervical cancer screening services decreases as the number of women screened and served increases. PMID:24326873

Moving across scales: Challenges and opportunities in upscaling carbon fluxes

NASA Astrophysics Data System (ADS)

Naithani, K. J.

2016-12-01

Light use efficiency (LUE) type models are commonly used to upscale terrestrial C fluxes and estimate regional and global C budgets. Model parameters are often estimated for each land cover type (LCT) using flux observations from one or more eddy covariance towers, and then spatially extrapolated by integrating land cover, meteorological, and remotely sensed data. Decisions regarding the type of input data (spatial resolution of land cover data, spatial and temporal length of flux data), representation of landscape structure (land use vs. disturbance regime), and the type of modeling framework (common risk vs. hierarchical) all influence the estimates CO2 fluxes and the associated uncertainties, but are rarely considered together. This work presents a synthesis of past and present efforts for upscaling CO2 fluxes and associated uncertainties in the ChEAS (Chequamegon Ecosystem Atmosphere Study) region in northern Wisconsin and the Upper Peninsula of Michigan. This work highlights two key future research needs. First, the characterization of uncertainties due to all of the abovementioned factors reflects only a (hopefully relevant) subset the overall uncertainties. Second, interactions among these factors are likely critical, but are poorly represented by the tower network at landscape scales. Yet, results indicate significant spatial and temporal heterogeneity of uncertainty in CO2 fluxes which can inform carbon management efforts and prioritize data needs.

Estimating effects of limiting factors with regression quantiles

USGS Publications Warehouse

Cade, B.S.; Terrell, J.W.; Schroeder, R.L.

1999-01-01

In a recent Concepts paper in Ecology, Thomson et al. emphasized that assumptions of conventional correlation and regression analyses fundamentally conflict with the ecological concept of limiting factors, and they called for new statistical procedures to address this problem. The analytical issue is that unmeasured factors may be the active limiting constraint and may induce a pattern of unequal variation in the biological response variable through an interaction with the measured factors. Consequently, changes near the maxima, rather than at the center of response distributions, are better estimates of the effects expected when the observed factor is the active limiting constraint. Regression quantiles provide estimates for linear models fit to any part of a response distribution, including near the upper bounds, and require minimal assumptions about the form of the error distribution. Regression quantiles extend the concept of one-sample quantiles to the linear model by solving an optimization problem of minimizing an asymmetric function of absolute errors. Rank-score tests for regression quantiles provide tests of hypotheses and confidence intervals for parameters in linear models with heteroscedastic errors, conditions likely to occur in models of limiting ecological relations. We used selected regression quantiles (e.g., 5th, 10th, ..., 95th) and confidence intervals to test hypotheses that parameters equal zero for estimated changes in average annual acorn biomass due to forest canopy cover of oak (Quercus spp.) and oak species diversity. Regression quantiles also were used to estimate changes in glacier lily (Erythronium grandiflorum) seedling numbers as a function of lily flower numbers, rockiness, and pocket gopher (Thomomys talpoides fossor) activity, data that motivated the query by Thomson et al. for new statistical procedures. Both example applications showed that effects of limiting factors estimated by changes in some upper regression quantile (e.g., 90-95th) were greater than if effects were estimated by changes in the means from standard linear model procedures. Estimating a range of regression quantiles (e.g., 5-95th) provides a comprehensive description of biological response patterns for exploratory and inferential analyses in observational studies of limiting factors, especially when sampling large spatial and temporal scales.

Terrestrial Water Storage in African Hydrological Regimes Derived from GRACE Mission Data: Intercomparison of Spherical Harmonics, Mass Concentration, and Scalar Slepian Methods.

PubMed

Rateb, Ashraf; Kuo, Chung-Yen; Imani, Moslem; Tseng, Kuo-Hsin; Lan, Wen-Hau; Ching, Kuo-En; Tseng, Tzu-Pang

2017-03-10

Spherical harmonics (SH) and mascon solutions are the two most common types of solutions for Gravity Recovery and Climate Experiment (GRACE) mass flux observations. However, SH signals are degraded by measurement and leakage errors. Mascon solutions (the Jet Propulsion Laboratory (JPL) release, herein) exhibit weakened signals at submascon resolutions. Both solutions require a scale factor examined by the CLM4.0 model to obtain the actual water storage signal. The Slepian localization method can avoid the SH leakage errors when applied to the basin scale. In this study, we estimate SH errors and scale factors for African hydrological regimes. Then, terrestrial water storage (TWS) in Africa is determined based on Slepian localization and compared with JPL-mascon and SH solutions. The three TWS estimates show good agreement for the TWS of large-sized and humid regimes but present discrepancies for the TWS of medium and small-sized regimes. Slepian localization is an effective method for deriving the TWS of arid zones. The TWS behavior in African regimes and its spatiotemporal variations are then examined. The negative TWS trends in the lower Nile and Sahara at -1.08 and -6.92 Gt/year, respectively, are higher than those previously reported.

Terrestrial Water Storage in African Hydrological Regimes Derived from GRACE Mission Data: Intercomparison of Spherical Harmonics, Mass Concentration, and Scalar Slepian Methods

PubMed Central

Rateb, Ashraf; Kuo, Chung-Yen; Imani, Moslem; Tseng, Kuo-Hsin; Lan, Wen-Hau; Ching, Kuo-En; Tseng, Tzu-Pang

2017-01-01

Spherical harmonics (SH) and mascon solutions are the two most common types of solutions for Gravity Recovery and Climate Experiment (GRACE) mass flux observations. However, SH signals are degraded by measurement and leakage errors. Mascon solutions (the Jet Propulsion Laboratory (JPL) release, herein) exhibit weakened signals at submascon resolutions. Both solutions require a scale factor examined by the CLM4.0 model to obtain the actual water storage signal. The Slepian localization method can avoid the SH leakage errors when applied to the basin scale. In this study, we estimate SH errors and scale factors for African hydrological regimes. Then, terrestrial water storage (TWS) in Africa is determined based on Slepian localization and compared with JPL-mascon and SH solutions. The three TWS estimates show good agreement for the TWS of large-sized and humid regimes but present discrepancies for the TWS of medium and small-sized regimes. Slepian localization is an effective method for deriving the TWS of arid zones. The TWS behavior in African regimes and its spatiotemporal variations are then examined. The negative TWS trends in the lower Nile and Sahara at −1.08 and −6.92 Gt/year, respectively, are higher than those previously reported. PMID:28287453

An evaluation of three-dimensional photogrammetric and morphometric techniques for estimating volume and mass in Weddell seals Leptonychotes weddellii

PubMed Central

Ruscher-Hill, Brandi; Kirkham, Amy L.; Burns, Jennifer M.

2018-01-01

Body mass dynamics of animals can indicate critical associations between extrinsic factors and population vital rates. Photogrammetry can be used to estimate mass of individuals in species whose life histories make it logistically difficult to obtain direct body mass measurements. Such studies typically use equations to relate volume estimates from photogrammetry to mass; however, most fail to identify the sources of error between the estimated and actual mass. Our objective was to identify the sources of error that prevent photogrammetric mass estimation from directly predicting actual mass, and develop a methodology to correct this issue. To do this, we obtained mass, body measurements, and scaled photos for 56 sedated Weddell seals (Leptonychotes weddellii). After creating a three-dimensional silhouette in the image processing program PhotoModeler Pro, we used horizontal scale bars to define the ground plane, then removed the below-ground portion of the animal’s estimated silhouette. We then re-calculated body volume and applied an expected density to estimate animal mass. We compared the body mass estimates derived from this silhouette slice method with estimates derived from two other published methodologies: body mass calculated using photogrammetry coupled with a species-specific correction factor, and estimates using elliptical cones and measured tissue densities. The estimated mass values (mean ± standard deviation 345±71 kg for correction equation, 346±75 kg for silhouette slice, 343±76 kg for cones) were not statistically distinguishable from each other or from actual mass (346±73 kg) (ANOVA with Tukey HSD post-hoc, p>0.05 for all pairwise comparisons). We conclude that volume overestimates from photogrammetry are likely due to the inability of photo modeling software to properly render the ventral surface of the animal where it contacts the ground. Due to logistical differences between the “correction equation”, “silhouette slicing”, and “cones” approaches, researchers may find one technique more useful for certain study programs. In combination or exclusively, these three-dimensional mass estimation techniques have great utility in field studies with repeated measures sampling designs or where logistic constraints preclude weighing animals. PMID:29320573

Understanding Phlebotomus perniciosus abundance in south-east Spain: assessing the role of environmental and anthropic factors.

PubMed

Risueño, José; Muñoz, Clara; Pérez-Cutillas, Pedro; Goyena, Elena; Gonzálvez, Moisés; Ortuño, María; Bernal, Luis Jesús; Ortiz, Juana; Alten, Bulent; Berriatua, Eduardo

2017-04-19

Leishmaniosis is associated with Phlebotomus sand fly vector density, but our knowledge of the environmental framework that regulates highly overdispersed vector abundance distributions is limited. We used a standardized sampling procedure in the bioclimatically diverse Murcia Region in Spain and multilevel regression models for count data to estimate P. perniciosus abundance in relation to environmental and anthropic factors. Twenty-five dog and sheep premises were sampled for sand flies using adhesive and light-attraction traps, from late May to early October 2015. Temperature, relative humidity and other animal- and premise-related data recorded on site and other environmental data were extracted from digital databases using a geographical information system. The relationship between sand fly abundance and explanatory variables was analysed using binomial regression models. The total number of sand flies captured, mostly with light-attraction traps, was 3,644 specimens, including 80% P. perniciosus, the main L. infantum vector in Spain. Abundance varied between and within zones and was positively associated with increasing altitude from 0 to 900 m above sea level, except from 500 to 700 m where it was low. Populations peaked in July and especially during a 3-day heat wave when relative humidity and wind speed plummeted. Regression models indicated that climate and not land use or soil characteristics have the greatest impact on this species density on a large geographical scale. In contrast, micro-environmental factors such as animal building characteristics and husbandry practices affect sand fly population size on a smaller scale. A standardised sampling procedure and statistical analysis for highly overdispersed distributions allow reliable estimation of P. perniciosus abundance and identification of environmental drivers. While climatic variables have the greatest impact at macro-environmental scale, anthropic factors may be determinant at a micro-geographical scale. These finding may be used to elaborate predictive distribution maps useful for vector and pathogen control programs.

Trait and state anxiety across academic evaluative contexts: development and validation of the MTEA-12 and MSEA-12 scales.

PubMed

Sotardi, Valerie A

2018-05-01

Educational measures of anxiety focus heavily on students' experiences with tests yet overlook other assessment contexts. In this research, two brief multiscale questionnaires were developed and validated to measure trait evaluation anxiety (MTEA-12) and state evaluation anxiety (MSEA-12) for use in various assessment contexts in non-clinical, educational settings. The research included a cross-sectional analysis of self-report data using authentic assessment settings in which evaluation anxiety was measured. Instruments were tested using a validation sample of 241 first-year university students in New Zealand. Scale development included component structures for state and trait scales based on existing theoretical frameworks. Analyses using confirmatory factor analysis and descriptive statistics indicate that the scales are reliable and structurally valid. Multivariate general linear modeling using subscales from the MTEA-12, MSEA-12, and student grades suggest adequate criterion-related validity. Initial predictive validity in which one relevant MTEA-12 factor explained between 21% and 54% of the variance in three MSEA-12 factors. Results document MTEA-12 and MSEA-12 as reliable measures of trait and state dimensions of evaluation anxiety for test and writing contexts. Initial estimates suggest the scales as having promising validity, and recommendations for further validation are outlined.

Psychometric evaluation of the muscle appearance satisfaction scale in a Mexican male sample.

PubMed

Escoto Ponce de León, María Del Consuelo; Bosques-Brugada, Lilián Elizabeth; Camacho Ruiz, Esteban Jaime; Alvarez-Rayón, Georgina; Franco Paredes, Karina; Rodríguez Hernández, Gabriela

2017-03-02

The purpose of this study was to determine whether the muscle appearance satisfaction scale (MASS) shows acceptable psychometric properties in Mexican bodybuilders. A total of 258 Mexican male bodybuilders were recruited. Two self-report questionnaires, including the MASS and drive for muscularity scale (DMS), were administered. Six models of the latent structure of the MASS were evaluated, using confirmatory factor analysis with maximum likelihood, considering robust Satorra-Bentler correction to estimate the fit of the models to the data. Similar to the original MASS, the series of CFA confirmed that the Mexican version was well represented with the 17-item five-factor structure, which showed a good model fit [Satorra-Bentler Chi-square (109, n = 258) = 189.18, p < 0.0001; NNFI = 0.91; CFI = 0.93; IFI = 0.93; RMSEA = 0.05 (0.04, 0.07)]. Internal consistency was estimated with McDonald's omega, which was acceptable for the MASS (0.88), and their subscales (0.80 to 0.89), except for muscle checking scale (0.77). Test-retest reliability analysis showed stability of the MASS total as well as of the subscale scores over a 2-week period (intraclass correlation coefficients = 0.75-0.91). Construct validity was demonstrated by a significant positive correlation between MASS and DMS results (r = 0.75; p = 0.0001). These results were similar to those of previous studies, which demonstrate the scale's usefulness. Our results support the suitability of the MASS and its subscales to measure muscle dysmorphia symptoms in Mexican male bodybuilders.

GPS-Based Reduced Dynamic Orbit Determination Using Accelerometer Data

NASA Technical Reports Server (NTRS)

VanHelleputte, Tom; Visser, Pieter

2007-01-01

Currently two gravity field satellite missions, CHAMP and GRACE, are equipped with high sensitivity electrostatic accelerometers, measuring the non-conservative forces acting on the spacecraft in three orthogonal directions. During the gravity field recovery these measurements help to separate gravitational and non-gravitational contributions in the observed orbit perturbations. For precise orbit determination purposes all these missions have a dual-frequency GPS receiver on board. The reduced dynamic technique combines the dense and accurate GPS observations with physical models of the forces acting on the spacecraft, complemented by empirical accelerations, which are stochastic parameters adjusted in the orbit determination process. When the spacecraft carries an accelerometer, these measured accelerations can be used to replace the models of the non-conservative forces, such as air drag and solar radiation pressure. This approach is implemented in a batch least-squares estimator of the GPS High Precision Orbit Determination Software Tools (GHOST), developed at DLR/GSOC and DEOS. It is extensively tested with data of the CHAMP and GRACE satellites. As accelerometer observations typically can be affected by an unknown scale factor and bias in each measurement direction, they require calibration during processing. Therefore the estimated state vector is augmented with six parameters: a scale and bias factor for the three axes. In order to converge efficiently to a good solution, reasonable a priori values for the bias factor are necessary. These are calculated by combining the mean value of the accelerometer observations with the mean value of the non-conservative force models and empirical accelerations, estimated when using these models. When replacing the non-conservative force models with accelerometer observations and still estimating empirical accelerations, a good orbit precision is achieved. 100 days of GRACE B data processing results in a mean orbit fit of a few centimeters with respect to high-quality JPL reference orbits. This shows a slightly better consistency compared to the case when using force models. A purely dynamic orbit, without estimating empirical accelerations thus only adjusting six state parameters and the bias and scale factors, gives an orbit fit for the GRACE B test case below the decimeter level. The in orbit calibrated accelerometer observations can be used to validate the modelled accelerations and estimated empirical accelerations computed with the GHOST tools. In along track direction they show the best resemblance, with a mean correlation coefficient of 93% for the same period. In radial and normal direction the correlation is smaller. During days of high solar activity the benefit of using accelerometer observations is clearly visible. The observations during these days show fluctuations which the modelled and empirical accelerations can not follow.

North American CO2 fluxes for 2007-2015 from NOAA's CarbonTracker-Lagrange Regional Inverse Modeling Framework

NASA Astrophysics Data System (ADS)

Andrews, A. E.; Hu, L.; Thoning, K. W.; Nehrkorn, T.; Mountain, M. E.; Jacobson, A. R.; Michalak, A.; Dlugokencky, E. J.; Sweeney, C.; Worthy, D. E. J.; Miller, J. B.; Fischer, M. L.; Biraud, S.; van der Velde, I. R.; Basu, S.; Tans, P. P.

2017-12-01

CarbonTracker-Lagrange (CT-L) is a new high-resolution regional inverse modeling system for improved estimation of North American CO2 fluxes. CT-L uses footprints from the Stochastic Time-Inverted Lagrangian Transport (STILT) model driven by high-resolution (10 to 30 km) meteorological fields from the Weather Research and Forecasting (WRF) model. We performed a suite of synthetic-data experiments to evaluate a variety of inversion configurations, including (1) solving for scaling factors to an a priori flux versus additive corrections, (2) solving for fluxes at 3-hrly resolution versus at coarser temporal resolution, (3) solving for fluxes at 1o × 1o resolution versus at large eco-regional scales. Our framework explicitly and objectively solves for the optimal solution with a full error covariance matrix with maximum likelihood estimation, thereby enabling rigorous uncertainty estimates for the derived fluxes. In the synthetic-data inversions, we find that solving for weekly scaling factors of a priori Net Ecosystem Exchange (NEE) at 1o × 1o resolution with optimization of diurnal cycles of CO2 fluxes yields faithful retrieval of the specified "true" fluxes as those solved at 3-hrly resolution. In contrast, a scheme that does not allow for optimization of diurnal cycles of CO2 fluxes suffered from larger aggregation errors. We then applied the optimal inversion setup to estimate North American fluxes for 2007-2015 using real atmospheric CO2 observations, multiple prior estimates of NEE, and multiple boundary values estimated from the NOAA's global Eulerian CarbonTracker (CarbonTracker) and from an empirical approach. Our derived North American land CO2 fluxes show larger seasonal amplitude than those estimated from the CarbonTracker, removing seasonal biases in the CarbonTracker's simulated CO2 mole fractions. Independent evaluations using in-situ CO2 eddy covariance flux measurements and independent aircraft profiles also suggest an improved estimation on North American CO2 fluxes from CT-L. Furthermore, our derived CO2 flux anomalies over North America corresponding to the 2012 North American drought and the 2015 El Niño are larger than derived by the CarbonTracker. They also indicate different responses of ecosystems to those anomalous climatic events.

The Revised Child Anxiety and Depression Scale 25-Parent Version: Scale Development and Validation in a School-Based and Clinical Sample.

PubMed

Ebesutani, Chad; Korathu-Larson, Priya; Nakamura, Brad J; Higa-McMillan, Charmaine; Chorpita, Bruce

2017-09-01

To help facilitate the dissemination and implementation of evidence-based assessment practices, we examined the psychometric properties of the shortened 25-item version of the Revised Child Anxiety and Depression Scale-parent report (RCADS-25-P), which was based on the same items as the previously published shortened 25-item child version. We used two independent samples of youth-a school sample ( N = 967, Grades 3-12) and clinical sample ( N = 433; 6-18 years)-to examine the factor structure, reliability, and validity of the RCADS-25-P scale scores. Results revealed that the two-factor structure (i.e., depression and broad anxiety factor) fit the data well in both the school and clinical sample. All reliability estimates, including test-retest indices, exceeded benchmark for good reliability. In the school sample, the RCADS-25-P scale scores converged significantly with related criterion measures and diverged with nonrelated criterion measures. In the clinical sample, the RCADS-25-P scale scores successfully discriminated between those with and without target problem diagnoses. In both samples, child-parent agreement indices were in the expected ranges. Normative data were also reported. The RCADS-25-P thus demonstrated robust psychometric properties across both a school and clinical sample as an effective brief screening instrument to assess for depression and anxiety in children and adolescents.

A fuel-based approach to estimating motor vehicle exhaust emissions

NASA Astrophysics Data System (ADS)

Singer, Brett Craig

Motor vehicles contribute significantly to air pollution problems; accurate motor vehicle emission inventories are therefore essential to air quality planning. Current travel-based inventory models use emission factors measured from potentially biased vehicle samples and predict fleet-average emissions which are often inconsistent with on-road measurements. This thesis presents a fuel-based inventory approach which uses emission factors derived from remote sensing or tunnel-based measurements of on-road vehicles. Vehicle activity is quantified by statewide monthly fuel sales data resolved to the air basin level. Development of the fuel-based approach includes (1) a method for estimating cold start emission factors, (2) an analysis showing that fuel-normalized emission factors are consistent over a range of positive vehicle loads and that most fuel use occurs during loaded-mode driving, (3) scaling factors relating infrared hydrocarbon measurements to total exhaust volatile organic compound (VOC) concentrations, and (4) an analysis showing that economic factors should be considered when selecting on-road sampling sites. The fuel-based approach was applied to estimate carbon monoxide (CO) emissions from warmed-up vehicles in the Los Angeles area in 1991, and CO and VOC exhaust emissions for Los Angeles in 1997. The fuel-based CO estimate for 1991 was higher by a factor of 2.3 +/- 0.5 than emissions predicted by California's MVEI 7F model. Fuel-based inventory estimates for 1997 were higher than those of California's updated MVEI 7G model by factors of 2.4 +/- 0.2 for CO and 3.5 +/- 0.6 for VOC. Fuel-based estimates indicate a 20% decrease in the mass of CO emitted, despite an 8% increase in fuel use between 1991 and 1997; official inventory models predict a 50% decrease in CO mass emissions during the same period. Cold start CO and VOC emission factors derived from parking garage measurements were lower than those predicted by the MVEI 7G model. Current inventories in California appear to understate total exhaust CO and VOC emissions, while overstating the importance of cold start emissions. The fuel-based approach yields robust, independent, and accurate estimates of on-road vehicle emissions. Fuel-based estimates should be used to validate or adjust official vehicle emission inventories before society embarks on new, more costly air pollution control programs.

Large-scale educational telecommunications systems for the US: An analysis of educational needs and technological opportunities

NASA Technical Reports Server (NTRS)

Morgan, R. P.; Singh, J. P.; Rothenberg, D.; Robinson, B. E.

1975-01-01

The needs to be served, the subsectors in which the system might be used, the technology employed, and the prospects for future utilization of an educational telecommunications delivery system are described and analyzed. Educational subsectors are analyzed with emphasis on the current status and trends within each subsector. Issues which affect future development, and prospects for future use of media, technology, and large-scale electronic delivery within each subsector are included. Information on technology utilization is presented. Educational telecommunications services are identified and grouped into categories: public television and radio, instructional television, computer aided instruction, computer resource sharing, and information resource sharing. Technology based services, their current utilization, and factors which affect future development are stressed. The role of communications satellites in providing these services is discussed. Efforts to analyze and estimate future utilization of large-scale educational telecommunications are summarized. Factors which affect future utilization are identified. Conclusions are presented.

Incidence of skin tears in the extremities among elderly patients at a long-term medical facility in Japan: A prospective cohort study.

PubMed

Sanada, Hiromi; Nakagami, Gojiro; Koyano, Yuiko; Iizaka, Shinji; Sugama, Junko

2015-08-01

There is a lack of data from cohort studies for the incidence of skin tears among an elderly population in an Asian country. We estimated the cumulative incidence of skin tear, and identify its risk factor. The present prospective cohort study was carried out at a long-term medical facility in Japan. Participants included patients (n = 368) aged 65 years or older receiving hospital care. The 3-month cumulative incidence of skin tears was estimated by identifying them using direct inspection of the extremities. In order to find the risk factors for the skin tear incidence, odds ratios and their 95% confidence intervals of skin tear development in association with the factors were estimated using logistic regression analyses. A total of 14 patients developed skin tears, and their cumulative incidence was 3.8%. No patients with skin tears developed multiple wounds on their extremities. Half of the skin tears occurred on the outside of the right forearm, and just three skin tears were found in the lower legs. Multiple logistic analyses showed that pre-existing skin tears (odds ratio 15.42, 95% confidence interval 3.53-67.43, P < 0.001) and a 6-point decrease in the total score of the Braden Scale (odds ratio 0.10, 95% confidence interval 0.01-0.83, P < 0.033) were significantly associated with skin tear development. Patients with pre-existing skin tears and a low score of the Braden Scale have a higher risk of skin tear development during 3 months. These factors could be used to identify patients requiring prevention care for skin tears. © 2014 Japan Geriatrics Society.

A comparison of estimates of basin-scale soil-moisture evapotranspiration and estimates of riparian groundwater evapotranspiration with implications for water budgets in the Verde Valley, Central Arizona, USA

USGS Publications Warehouse

Tillman, Fred; Wiele, Stephen M.; Pool, Donald R.

2015-01-01

Population growth in the Verde Valley in Arizona has led to efforts to better understand water availability in the watershed. Evapotranspiration (ET) is a substantial component of the water budget and a critical factor in estimating groundwater recharge in the area. In this study, four estimates of ET are compared and discussed with applications to the Verde Valley. Higher potential ET (PET) rates from the soil-water balance (SWB) recharge model resulted in an average annual ET volume about 17% greater than for ET from the basin characteristics (BCM) recharge model. Annual BCM PET volume, however, was greater by about a factor of 2 or more than SWB actual ET (AET) estimates, which are used in the SWB model to estimate groundwater recharge. ET also was estimated using a method that combines MODIS-EVI remote sensing data and geospatial information and by the MODFLOW-EVT ET package as part of a regional groundwater-flow model that includes the study area. Annual ET volumes were about same for upper-bound MODIS-EVI ET for perennial streams as for the MODFLOW ET estimates, with the small differences between the two methods having minimal impact on annual or longer groundwater budgets for the study area.

Urban scale air quality modelling using detailed traffic emissions estimates

NASA Astrophysics Data System (ADS)

Borrego, C.; Amorim, J. H.; Tchepel, O.; Dias, D.; Rafael, S.; Sá, E.; Pimentel, C.; Fontes, T.; Fernandes, P.; Pereira, S. R.; Bandeira, J. M.; Coelho, M. C.

2016-04-01

The atmospheric dispersion of NOx and PM10 was simulated with a second generation Gaussian model over a medium-size south-European city. Microscopic traffic models calibrated with GPS data were used to derive typical driving cycles for each road link, while instantaneous emissions were estimated applying a combined Vehicle Specific Power/Co-operative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe (VSP/EMEP) methodology. Site-specific background concentrations were estimated using time series analysis and a low-pass filter applied to local observations. Air quality modelling results are compared against measurements at two locations for a 1 week period. 78% of the results are within a factor of two of the observations for 1-h average concentrations, increasing to 94% for daily averages. Correlation significantly improves when background is added, with an average of 0.89 for the 24 h record. The results highlight the potential of detailed traffic and instantaneous exhaust emissions estimates, together with filtered urban background, to provide accurate input data to Gaussian models applied at the urban scale.

Spatial scaling of net primary productivity using subpixel landcover information

NASA Astrophysics Data System (ADS)

Chen, X. F.; Chen, Jing M.; Ju, Wei M.; Ren, L. L.

2008-10-01

Gridding the land surface into coarse homogeneous pixels may cause important biases on ecosystem model estimations of carbon budget components at local, regional and global scales. These biases result from overlooking subpixel variability of land surface characteristics. Vegetation heterogeneity is an important factor introducing biases in regional ecological modeling, especially when the modeling is made on large grids. This study suggests a simple algorithm that uses subpixel information on the spatial variability of land cover type to correct net primary productivity (NPP) estimates, made at coarse spatial resolutions where the land surface is considered as homogeneous within each pixel. The algorithm operates in such a way that NPP obtained from calculations made at coarse spatial resolutions are multiplied by simple functions that attempt to reproduce the effects of subpixel variability of land cover type on NPP. Its application to a carbon-hydrology coupled model(BEPS-TerrainLab model) estimates made at a 1-km resolution over a watershed (named Baohe River Basin) located in the southwestern part of Qinling Mountains, Shaanxi Province, China, improved estimates of average NPP as well as its spatial variability.

Comparing estimates of EMEP MSC-W and UFORE models in air pollutant reduction by urban trees.

PubMed

Guidolotti, Gabriele; Salviato, Michele; Calfapietra, Carlo

2016-10-01

There is a growing interest to identify and quantify the benefits provided by the presence of trees in urban environment in order to improve the environmental quality in cities. However, the evaluation and estimate of plant efficiency in removing atmospheric pollutants is rather complicated, because of the high number of factors involved and the difficulty of estimating the effect of the interactions between the different components. In this study, the EMEP MSC-W model was implemented to scale-down to tree-level and allows its application to an industrial-urban green area in Northern Italy. Moreover, the annual outputs were compared with the outputs of UFORE (nowadays i-Tree), a leading model for urban forest applications. Although, EMEP/MSC-W model and UFORE are semi-empirical models designed for different applications, the comparison, based on O3, NO2 and PM10 removal, showed a good agreement in the estimates and highlights how the down-scaling methodology presented in this study may have significant opportunities for further developments.

Plant biomarkers in aerosols record isotopic discrimination of terrestrial photosynthesis.

PubMed

Conte, Maureen H; Weber, John C

2002-06-06

Carbon uptake by the oceans and by the terrestrial biosphere can be partitioned using changes in the (12)C/(13)C isotopic ratio (delta(13)C) of atmospheric carbon dioxide, because terrestrial photosynthesis strongly discriminates against (13)CO(2), whereas ocean uptake does not. This approach depends on accurate estimates of the carbon isotopic discrimination of terrestrial photosynthesis (Delta; ref. 5) at large regional scales, yet terrestrial ecosystem heterogeneity makes such estimates problematic. Here we show that ablated plant wax compounds in continental air masses can be used to estimate Delta over large spatial scales and at less than monthly temporal resolution. We measured plant waxes in continental air masses advected to Bermuda, which are mainly of North American origin, and used the wax isotopic composition to estimate Delta simply. Our estimates indicate a large (5 6 per thousand) seasonal variation in Delta of the temperate North American biosphere, with maximum discrimination occurring in late spring, coincident with the onset of production. We suggest that the observed seasonality arises from several factors, including seasonal shifts in the proportions of production by C(3) and C(4) plants, and environmentally controlled adjustments in the photosynthetic discrimination of C(3)-plant-dominated ecosystems.

Temporal scaling in information propagation.

PubMed

Huang, Junming; Li, Chao; Wang, Wen-Qiang; Shen, Hua-Wei; Li, Guojie; Cheng, Xue-Qi

2014-06-18

For the study of information propagation, one fundamental problem is uncovering universal laws governing the dynamics of information propagation. This problem, from the microscopic perspective, is formulated as estimating the propagation probability that a piece of information propagates from one individual to another. Such a propagation probability generally depends on two major classes of factors: the intrinsic attractiveness of information and the interactions between individuals. Despite the fact that the temporal effect of attractiveness is widely studied, temporal laws underlying individual interactions remain unclear, causing inaccurate prediction of information propagation on evolving social networks. In this report, we empirically study the dynamics of information propagation, using the dataset from a population-scale social media website. We discover a temporal scaling in information propagation: the probability a message propagates between two individuals decays with the length of time latency since their latest interaction, obeying a power-law rule. Leveraging the scaling law, we further propose a temporal model to estimate future propagation probabilities between individuals, reducing the error rate of information propagation prediction from 6.7% to 2.6% and improving viral marketing with 9.7% incremental customers.

Temporal scaling in information propagation

NASA Astrophysics Data System (ADS)

Huang, Junming; Li, Chao; Wang, Wen-Qiang; Shen, Hua-Wei; Li, Guojie; Cheng, Xue-Qi

2014-06-01

For the study of information propagation, one fundamental problem is uncovering universal laws governing the dynamics of information propagation. This problem, from the microscopic perspective, is formulated as estimating the propagation probability that a piece of information propagates from one individual to another. Such a propagation probability generally depends on two major classes of factors: the intrinsic attractiveness of information and the interactions between individuals. Despite the fact that the temporal effect of attractiveness is widely studied, temporal laws underlying individual interactions remain unclear, causing inaccurate prediction of information propagation on evolving social networks. In this report, we empirically study the dynamics of information propagation, using the dataset from a population-scale social media website. We discover a temporal scaling in information propagation: the probability a message propagates between two individuals decays with the length of time latency since their latest interaction, obeying a power-law rule. Leveraging the scaling law, we further propose a temporal model to estimate future propagation probabilities between individuals, reducing the error rate of information propagation prediction from 6.7% to 2.6% and improving viral marketing with 9.7% incremental customers.

Relative sensitivities of DCE-MRI pharmacokinetic parameters to arterial input function (AIF) scaling

NASA Astrophysics Data System (ADS)

Li, Xin; Cai, Yu; Moloney, Brendan; Chen, Yiyi; Huang, Wei; Woods, Mark; Coakley, Fergus V.; Rooney, William D.; Garzotto, Mark G.; Springer, Charles S.

2016-08-01

Dynamic-Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) has been used widely for clinical applications. Pharmacokinetic modeling of DCE-MRI data that extracts quantitative contrast reagent/tissue-specific model parameters is the most investigated method. One of the primary challenges in pharmacokinetic analysis of DCE-MRI data is accurate and reliable measurement of the arterial input function (AIF), which is the driving force behind all pharmacokinetics. Because of effects such as inflow and partial volume averaging, AIF measured from individual arteries sometimes require amplitude scaling for better representation of the blood contrast reagent (CR) concentration time-courses. Empirical approaches like blinded AIF estimation or reference tissue AIF derivation can be useful and practical, especially when there is no clearly visible blood vessel within the imaging field-of-view (FOV). Similarly, these approaches generally also require magnitude scaling of the derived AIF time-courses. Since the AIF varies among individuals even with the same CR injection protocol and the perfect scaling factor for reconstructing the ground truth AIF often remains unknown, variations in estimated pharmacokinetic parameters due to varying AIF scaling factors are of special interest. In this work, using simulated and real prostate cancer DCE-MRI data, we examined parameter variations associated with AIF scaling. Our results show that, for both the fast-exchange-limit (FXL) Tofts model and the water exchange sensitized fast-exchange-regime (FXR) model, the commonly fitted CR transfer constant (Ktrans) and the extravascular, extracellular volume fraction (ve) scale nearly proportionally with the AIF, whereas the FXR-specific unidirectional cellular water efflux rate constant, kio, and the CR intravasation rate constant, kep, are both AIF scaling insensitive. This indicates that, for DCE-MRI of prostate cancer and possibly other cancers, kio and kep may be more suitable imaging biomarkers for cross-platform, multicenter applications. Data from our limited study cohort show that kio correlates with Gleason scores, suggesting that it may be a useful biomarker for prostate cancer disease progression monitoring.

Environmental and social determinants of population vulnerability to Zika virus emergence at the local scale.

PubMed

Rees, Erin E; Petukhova, Tatiana; Mascarenhas, Mariola; Pelcat, Yann; Ogden, Nicholas H

2018-05-08

Zika virus (ZIKV) spread rapidly in the Americas in 2015. Targeting effective public health interventions for inhabitants of, and travellers to and from, affected countries depends on understanding the risk of ZIKV emergence (and re-emergence) at the local scale. We explore the extent to which environmental, social and neighbourhood disease intensity variables influenced emergence dynamics. Our objective was to characterise population vulnerability given the potential for sustained autochthonous ZIKV transmission and the timing of emergence. Logistic regression models estimated the probability of reporting at least one case of ZIKV in a given municipality over the course of the study period as an indicator for sustained transmission; while accelerated failure time (AFT) survival models estimated the time to a first reported case of ZIKV in week t for a given municipality as an indicator for timing of emergence. Sustained autochthonous ZIKV transmission was best described at the temporal scale of the study period (almost one year), such that high levels of study period precipitation and low mean study period temperature reduced the probability. Timing of ZIKV emergence was best described at the weekly scale for precipitation in that high precipitation in the current week delayed reporting. Both modelling approaches detected an effect of high poverty on reducing/slowing case detection, especially when inter-municipal road connectivity was low. We also found that proximity to municipalities reporting ZIKV had an effect to reduce timing of emergence when located, on average, less than 100 km away. The different modelling approaches help distinguish between large temporal scale factors driving vector habitat suitability and short temporal scale factors affecting the speed of spread. We find evidence for inter-municipal movements of infected people as a local-scale driver of spatial spread. The negative association with poverty suggests reduced case reporting in poorer areas. Overall, relatively simplistic models may be able to predict the vulnerability of populations to autochthonous ZIKV transmission at the local scale.

Achieving across-laboratory replicability in psychophysical scaling

PubMed Central

Ward, Lawrence M.; Baumann, Michael; Moffat, Graeme; Roberts, Larry E.; Mori, Shuji; Rutledge-Taylor, Matthew; West, Robert L.

2015-01-01

It is well known that, although psychophysical scaling produces good qualitative agreement between experiments, precise quantitative agreement between experimental results, such as that routinely achieved in physics or biology, is rarely or never attained. A particularly galling example of this is the fact that power function exponents for the same psychological continuum, measured in different laboratories but ostensibly using the same scaling method, magnitude estimation, can vary by a factor of three. Constrained scaling (CS), in which observers first learn a standardized meaning for a set of numerical responses relative to a standard sensory continuum and then make magnitude judgments of other sensations using the learned response scale, has produced excellent quantitative agreement between individual observers’ psychophysical functions. Theoretically it could do the same for across-laboratory comparisons, although this needs to be tested directly. We compared nine different experiments from four different laboratories as an example of the level of across experiment and across-laboratory agreement achievable using CS. In general, we found across experiment and across-laboratory agreement using CS to be significantly superior to that typically obtained with conventional magnitude estimation techniques, although some of its potential remains to be realized. PMID:26191019

Hydrogeological Controls on Regional-Scale Indirect Nitrous Oxide Emission Factors for Rivers.

PubMed

Cooper, Richard J; Wexler, Sarah K; Adams, Christopher A; Hiscock, Kevin M

2017-09-19

Indirect nitrous oxide (N 2 O) emissions from rivers are currently derived using poorly constrained default IPCC emission factors (EF 5r ) which yield unreliable flux estimates. Here, we demonstrate how hydrogeological conditions can be used to develop more refined regional-scale EF 5r estimates required for compiling accurate national greenhouse gas inventories. Focusing on three UK river catchments with contrasting bedrock and superficial geologies, N 2 O and nitrate (NO 3 - ) concentrations were analyzed in 651 river water samples collected from 2011 to 2013. Unconfined Cretaceous Chalk bedrock regions yielded the highest median N 2 O-N concentration (3.0 μg L -1 ), EF 5r (0.00036), and N 2 O-N flux (10.8 kg ha -1 a -1 ). Conversely, regions of bedrock confined by glacial deposits yielded significantly lower median N 2 O-N concentration (0.8 μg L -1 ), EF 5r (0.00016), and N 2 O-N flux (2.6 kg ha -1 a -1 ), regardless of bedrock type. Bedrock permeability is an important control in regions where groundwater is unconfined, with a high N 2 O yield from high permeability chalk contrasting with significantly lower median N 2 O-N concentration (0.7 μg L -1 ), EF 5r (0.00020), and N 2 O-N flux (2.0 kg ha -1 a -1 ) on lower permeability unconfined Jurassic mudstone. The evidence presented here demonstrates EF 5r can be differentiated by hydrogeological conditions and thus provide a valuable proxy for generating improved regional-scale N 2 O emission estimates.

Development of an instrument based on the protection motivation theory to measure factors influencing women's intention to first pap test practice.

PubMed

Hassani, Lale; Dehdari, Tahereh; Hajizadeh, Ebrahim; Shojaeizadeh, Davoud; Abedini, Mehrandokht; Nedjat, Saharnaz

2014-01-01

Given that there are many Iranian women who have never had a Pap smear, this study was designed to develop and validate a measurement tool based on the Protection Motivation Theory to assess factors influencing the Iranian women's intention to perform first Pap testing. In this psychometric research, to determine the Content Validity Index (CVI) and the Content Validity Ratio (CVR), a panel of experts (n=10) reviewed scale items. Reliability was estimated through the Intraclass Correlation Coefficient (n=30) and internal consistency (n=240). Also, factor analysis (exploratory and conformity) was performed on the data of the sample women who had never had a Pap smear test (n=240). A 26-item questionnaire was developed. The CVI and CVR scores of the scale were 0.89 and 0.90, respectively. Exploratory factor analysis loaded a 26-item with seven factors questionnaire (perceived vulnerability and severity, fear, response costs, response efficacy, self-efficacy, and protection motivation (or intention)) that jointly accounted for 72.76% of the observed variance. Confirmatory factor analysis indicated a good fit for the data. Internal consistency (range 0.70-0.93) and test-retest reliability (range 0.72-0.96) of sub-scales were acceptable. This study showed that the designed instrument was a valid and reliable tool for measuring the factors influencing the women's intention to perform their first Pap testing.

Flood frequency estimation by national-scale continuous hydrological simulations: an application in Great Britain

NASA Astrophysics Data System (ADS)

Formetta, Giuseppe; Stewart, Elizabeth; Bell, Victoria; Reynard, Nick

2017-04-01

Estimation of peak discharge for an assigned return period is a crucial issue in engineering hydrology. It is required for designing and managing hydraulic infrastructure such as dams, reservoirs and bridges. In the UK, the Flood Estimation Handbook (FEH) recommends the use of the index flood method to estimate the design flood as the product of a local scale factor (the index flood, IF) and a dimensionless regional growth factor (GF). For gauged catchments the IF is usually estimated as the median annual maximum flood (QMED), while for ungauged catchments it is computed through multiple linear regression models based on a set of morpho-climatic indices of the basin. The GF is estimated by fitting the annual maxima with the generalised logistic distribution (GL) using two methods depending on the record length and the target return period: single-site or pooled analysis. The single site-analysis estimates the GF from the annual maxima of the subject site alone; the pooled analysis uses data from a set of catchments hydrologically similar to the subject site. In this work estimates of floods up to 100-year return period obtained from the FEH approach are compared to those obtained using Grid-to-Grid, a continuous physically-based hydrological model. The model converts rainfall and potential evapotranspiration into river flows by modelling surface/sub-surface runoff, lateral water movements, and snow-pack. It is configured on a 1km2 grid resolution and it uses spatial datasets of topography, soil, and land cover. It was set up in Great Britain and has been evaluated for the period 1960-2014 in forward-mode (i.e. without parameter calibration) using daily meteorological forcing data. The modelled floods with a given return period (5,10, 30, 50, and 100 years) were computed from the modelled discharge annual maxima and compared to the FEH estimates for 100 catchments in Great Britain. Preliminary results suggest that there is a good agreement between modelled and measured floods with a correlation coefficient that ranges from 0.8 for low return periods to 0.65 for the highest. It is shown that model performance is robust and independent of catchment features such as area and mean annual rainfall. The promising results for Great Britain support the aspiration that continuous simulation from large-scale hydrological models, supported by the increasing availability of global weather, climate and hydrological products, could be used to develop robust methods to help engineers estimate design floods in regions with limited gauge data or affected by environmental change.

Psychometric Properties of the Chinese Version of the Arabic Scale of Death Anxiety.

PubMed

Qiu, Qi; Zhang, Shengyu; Lin, Xiang; Ban, Chunxia; Yang, Haibo; Liu, Zhengwen; Wang, Jingrong; Wang, Tao; Xiao, Shifu; Abdel-Khalek, Ahmed M; Li, Xia

2016-06-25

Death anxiety is regarded as a risk and maintaining factor of psychopathology. While the Arabic Scale of Death Anxiety (ASDA) is a brief, commonly used assessment, such a tool is lacking in Chinese clinical practice. The current study was conducted to develop a Chinese version of the ASDA, i.e., the ASDA(C), using a multistage back-translation technique, and examine the psychometric properties of the scale. A total of 1372 participants from hospitals and universities located in three geographic areas of China were recruited for this study. To calculate the criterion-related validity of the ASDA(C) compared to the Chinese version of the longer-form Multidimensional Orientation toward Dying and Death Inventory (MODDI-F/chin), 49 undergraduates were randomly assigned to complete both questionnaires. Of the total participants, 56 were randomly assigned to retake the ASDA(C) in order to estimate the one-week, test-retest reliability of the ASDA(C). The overall Cronbach's alpha was 0.91 for the whole scale. The one-week, test-retest reliability was 0.96. Exploratory Factor Analysis (EFA) revealed three factors, "fear of dead people and tombs," "fear of lethal disease," and "fear of postmortem events," accounted for 57.09% of the total variance. Factor structure for the three-factor model was sound. The correlation between the total scores on the ASDA(C) and the MODDI-F/chin was 0.54, indicating acceptable concurrent validity. ASDA(C) has adequate psychometrics and properties that make it a reliable and valid scale to assess death anxiety in Mandarin-speaking Chinese.

Source motion detection, estimation, and compensation for underwater acoustics inversion by wideband ambiguity lag-Doppler filtering.

PubMed

Josso, Nicolas F; Ioana, Cornel; Mars, Jérôme I; Gervaise, Cédric

2010-12-01

Acoustic channel properties in a shallow water environment with moving source and receiver are difficult to investigate. In fact, when the source-receiver relative position changes, the underwater environment causes multipath and Doppler scale changes on the transmitted signal over low-to-medium frequencies (300 Hz-20 kHz). This is the result of a combination of multiple paths propagation, source and receiver motions, as well as sea surface motion or water column fast changes. This paper investigates underwater acoustic channel properties in a shallow water (up to 150 m depth) and moving source-receiver conditions using extracted time-scale features of the propagation channel model for low-to-medium frequencies. An average impulse response of one transmission is estimated using the physical characteristics of propagation and the wideband ambiguity plane. Since a different Doppler scale should be considered for each propagating signal, a time-warping filtering method is proposed to estimate the channel time delay and Doppler scale attributes for each propagating path. The proposed method enables the estimation of motion-compensated impulse responses, where different Doppler scaling factors are considered for the different time delays. It was validated for channel profiles using real data from the BASE'07 experiment conducted by the North Atlantic Treaty Organization Undersea Research Center in the shallow water environment of the Malta Plateau, South Sicily. This paper provides a contribution to many field applications including passive ocean tomography with unknown natural sources position and movement. Another example is active ocean tomography where sources motion enables to rapidly cover one operational area for rapid environmental assessment and hydrophones may be drifting in order to avoid additional flow noise.

Development and Validation of a Unidimensional Maltreatment Scale in the Add Health Data Set

ERIC Educational Resources Information Center

Marszalek, Jacob M.; Hamilton, Jessica L.

2012-01-01

Four maltreatment items were examined from Wave III (N = 13,516) of the National Longitudinal Study of Adolescent Health. Item analysis, confirmatory factor analysis, cross-validation, reliability estimates, and convergent validity coefficients strongly supported the validity of using the four items as a unidimensional composite. Implications for…

Factors influencing stream fish recovery following a large-scale disturbance

Treesearch

William E. Ensign; Angermeier Leftwich; C. Andrew Dolloff

1997-01-01

The authors examined fish distribution and abundance in erosional habitat units in South Fork Roanoke River, VA, following a fish kill by using a reachwide sampling approach for 3 species and a representative-reach sampling approach for 10 species. Qualitative (presence-absence) and quantitative (relative abundance) estimates of distribution and abundance provided...

Effects of social organization, trap arrangement and density, sampling scale, and population density on bias in population size estimation using some common mark-recapture estimators.

PubMed

Gupta, Manan; Joshi, Amitabh; Vidya, T N C

2017-01-01

Mark-recapture estimators are commonly used for population size estimation, and typically yield unbiased estimates for most solitary species with low to moderate home range sizes. However, these methods assume independence of captures among individuals, an assumption that is clearly violated in social species that show fission-fusion dynamics, such as the Asian elephant. In the specific case of Asian elephants, doubts have been raised about the accuracy of population size estimates. More importantly, the potential problem for the use of mark-recapture methods posed by social organization in general has not been systematically addressed. We developed an individual-based simulation framework to systematically examine the potential effects of type of social organization, as well as other factors such as trap density and arrangement, spatial scale of sampling, and population density, on bias in population sizes estimated by POPAN, Robust Design, and Robust Design with detection heterogeneity. In the present study, we ran simulations with biological, demographic and ecological parameters relevant to Asian elephant populations, but the simulation framework is easily extended to address questions relevant to other social species. We collected capture history data from the simulations, and used those data to test for bias in population size estimation. Social organization significantly affected bias in most analyses, but the effect sizes were variable, depending on other factors. Social organization tended to introduce large bias when trap arrangement was uniform and sampling effort was low. POPAN clearly outperformed the two Robust Design models we tested, yielding close to zero bias if traps were arranged at random in the study area, and when population density and trap density were not too low. Social organization did not have a major effect on bias for these parameter combinations at which POPAN gave more or less unbiased population size estimates. Therefore, the effect of social organization on bias in population estimation could be removed by using POPAN with specific parameter combinations, to obtain population size estimates in a social species.

Effects of social organization, trap arrangement and density, sampling scale, and population density on bias in population size estimation using some common mark-recapture estimators

PubMed Central

Joshi, Amitabh; Vidya, T. N. C.

2017-01-01

Mark-recapture estimators are commonly used for population size estimation, and typically yield unbiased estimates for most solitary species with low to moderate home range sizes. However, these methods assume independence of captures among individuals, an assumption that is clearly violated in social species that show fission-fusion dynamics, such as the Asian elephant. In the specific case of Asian elephants, doubts have been raised about the accuracy of population size estimates. More importantly, the potential problem for the use of mark-recapture methods posed by social organization in general has not been systematically addressed. We developed an individual-based simulation framework to systematically examine the potential effects of type of social organization, as well as other factors such as trap density and arrangement, spatial scale of sampling, and population density, on bias in population sizes estimated by POPAN, Robust Design, and Robust Design with detection heterogeneity. In the present study, we ran simulations with biological, demographic and ecological parameters relevant to Asian elephant populations, but the simulation framework is easily extended to address questions relevant to other social species. We collected capture history data from the simulations, and used those data to test for bias in population size estimation. Social organization significantly affected bias in most analyses, but the effect sizes were variable, depending on other factors. Social organization tended to introduce large bias when trap arrangement was uniform and sampling effort was low. POPAN clearly outperformed the two Robust Design models we tested, yielding close to zero bias if traps were arranged at random in the study area, and when population density and trap density were not too low. Social organization did not have a major effect on bias for these parameter combinations at which POPAN gave more or less unbiased population size estimates. Therefore, the effect of social organization on bias in population estimation could be removed by using POPAN with specific parameter combinations, to obtain population size estimates in a social species. PMID:28306735

Estimation of hospital efficiency--do different definitions and casemix measures for hospital output affect the results?

PubMed

Vitikainen, Kirsi; Street, Andrew; Linna, Miika

2009-02-01

Hospital efficiency has been the subject of numerous health economics studies, but there is little evidence on how the chosen output and casemix measures affect the efficiency results. The aim of this study is to examine the robustness of efficiency results due to these factors. Comparison is made between activities and episode output measures, and two different output grouping systems (Classic and FullDRG). Non-parametric data envelopment analysis is used as an analysis technique. The data consist of all public acute care hospitals in Finland in 2005 (n=40). Efficiency estimates were not found to be highly sensitive to the choice between episode and activity descriptions of output, but more so to the choice of DRG grouping system. Estimates are most sensitive to scale assumptions, with evidence of decreasing returns to scale in larger hospitals. Episode measures are generally to be preferred to activity measures because these better capture the patient pathway, while FullDRGs are preferred to Classic DRGs particularly because of the better description of outpatient output in the former grouping system. Attention should be paid to reducing the extent of scale inefficiency in Finland.

Linking Meteorology, Air Quality Models and Observations to ...

EPA Pesticide Factsheets

Epidemiologic studies are critical in establishing the association between exposure to air pollutants and adverse health effects. Results of epidemiologic studies are used by U.S. EPA in developing air quality standards to protect the public from the health effects of air pollutants. A major challenge in environmental epidemiology is adequate exposure characterization. Numerous health studies have used measurements from a few central-site ambient monitors to characterize air pollution exposures. Relying solely on central-site ambient monitors does not account for the spatial-heterogeneity of ambient air pollution patterns, the temporal variability in ambient concentrations, nor the influence of infiltration and indoor sources. Central-site monitoring becomes even more problematic for certain air pollutants that exhibit significant spatial heterogeneity. Statistical interpolation techniques and passive monitoring methods can provide additional spatial resolution in ambient concentration estimates. In addition, spatio-temporal models, which integrate GIS data and other factors, such as meteorology, have also been developed to produce more resolved estimates of ambient concentrations. Models, such as the Community Multi-Scale Air Quality (CMAQ) model, estimate ambient concentrations by combining information on meteorology, source emissions, and chemical-fate and transport. Hybrid modeling approaches, which integrate regional scale models with local scale dispersion

Preindustrial nitrous oxide emissions from the land biosphere estimated by using a global biogeochemistry model

NASA Astrophysics Data System (ADS)

Xu, Rongting; Tian, Hanqin; Lu, Chaoqun; Pan, Shufen; Chen, Jian; Yang, Jia; Zhang, Bowen

2017-07-01

To accurately assess how increased global nitrous oxide (N2O) emission has affected the climate system requires a robust estimation of the preindustrial N2O emissions since only the difference between current and preindustrial emissions represents net drivers of anthropogenic climate change. However, large uncertainty exists in previous estimates of preindustrial N2O emissions from the land biosphere, while preindustrial N2O emissions on the finer scales, such as regional, biome, or sector scales, have not been well quantified yet. In this study, we applied a process-based Dynamic Land Ecosystem Model (DLEM) to estimate the magnitude and spatial patterns of preindustrial N2O fluxes at the biome, continental, and global level as driven by multiple environmental factors. Uncertainties associated with key parameters were also evaluated. Our study indicates that the mean of the preindustrial N2O emission was approximately 6.20 Tg N yr-1, with an uncertainty range of 4.76 to 8.13 Tg N yr-1. The estimated N2O emission varied significantly at spatial and biome levels. South America, Africa, and Southern Asia accounted for 34.12, 23.85, and 18.93 %, respectively, together contributing 76.90 % of global total emission. The tropics were identified as the major source of N2O released into the atmosphere, accounting for 64.66 % of the total emission. Our multi-scale estimates provide a robust reference for assessing the climate forcing of anthropogenic N2O emission from the land biosphere

Energy performance and greenhouse gas emissions of kelp cultivation for biogas and fertilizer recovery in Sweden.

PubMed

Pechsiri, Joseph S; Thomas, Jean-Baptiste E; Risén, Emma; Ribeiro, Mauricio S; Malmström, Maria E; Nylund, Göran M; Jansson, Anette; Welander, Ulrika; Pavia, Henrik; Gröndahl, Fredrik

2016-12-15

The cultivation of seaweed as a feedstock for third generation biofuels is gathering interest in Europe, however, many questions remain unanswered in practise, notably regarding scales of operation, energy returns on investment (EROI) and greenhouse gas (GHG) emissions, all of which are crucial to determine commercial viability. This study performed an energy and GHG emissions analysis, using EROI and GHG savings potential respectively, as indicators of commercial viability for two systems: the Swedish Seafarm project's seaweed cultivation (0.5ha), biogas and fertilizer biorefinery, and an estimation of the same system scaled up and adjusted to a cultivation of 10ha. Based on a conservative estimate of biogas yield, neither the 0.5ha case nor the up-scaled 10ha estimates met the (commercial viability) target EROI of 3, nor the European Union Renewable Energy Directive GHG savings target of 60% for biofuels, however the potential for commercial viability was substantially improved by scaling up operations: GHG emissions and energy demand, per unit of biogas, was almost halved by scaling operations up by a factor of twenty, thereby approaching the EROI and GHG savings targets set, under beneficial biogas production conditions. Further analysis identified processes whose optimisations would have a large impact on energy use and emissions (such as anaerobic digestion) as well as others embodying potential for further economies of scale (such as harvesting), both of which would be of interest for future developments of kelp to biogas and fertilizer biorefineries. Copyright © 2016. Published by Elsevier B.V.

Are you interested? A meta-analysis of relations between vocational interests and employee performance and turnover.

PubMed

Van Iddekinge, Chad H; Roth, Philip L; Putka, Dan J; Lanivich, Stephen E

2011-11-01

A common belief among researchers is that vocational interests have limited value for personnel selection. However, no comprehensive quantitative summaries of interests validity research have been conducted to substantiate claims for or against the use of interests. To help address this gap, we conducted a meta-analysis of relations between interests and employee performance and turnover using data from 74 studies and 141 independent samples. Overall validity estimates (corrected for measurement error in the criterion but not for range restriction) for single interest scales were .14 for job performance, .26 for training performance, -.19 for turnover intentions, and -.15 for actual turnover. Several factors appeared to moderate interest-criterion relations. For example, validity estimates were larger when interests were theoretically relevant to the work performed in the target job. The type of interest scale also moderated validity, such that corrected validities were larger for scales designed to assess interests relevant to a particular job or vocation (e.g., .23 for job performance) than for scales designed to assess a single, job-relevant realistic, investigative, artistic, social, enterprising, or conventional (i.e., RIASEC) interest (.10) or a basic interest (.11). Finally, validity estimates were largest when studies used multiple interests for prediction, either by using a single job or vocation focused scale (which tend to tap multiple interests) or by using a regression-weighted composite of several RIASEC or basic interest scales. Overall, the results suggest that vocational interests may hold more promise for predicting employee performance and turnover than researchers may have thought. (c) 2011 APA, all rights reserved.

Spatial and spectral simulation of LANDSAT images of agricultural areas

NASA Technical Reports Server (NTRS)

Pont, W. F., Jr. (Principal Investigator)

1982-01-01

A LANDSAT scene simulation capability was developed to study the effects of small fields and misregistration on LANDSAT-based crop proportion estimation procedures. The simulation employs a pattern of ground polygons each with a crop ID, planting date, and scale factor. Historical greenness/brightness crop development profiles generate the mean signal values for each polygon. Historical within-field covariances add texture to pixels in each polygon. The planting dates and scale factors create between-field/within-crop variation. Between field and crop variation is achieved by the above and crop profile differences. The LANDSAT point spread function is used to add correlation between nearby pixels. The next effect of the point spread function is to blur the image. Mixed pixels and misregistration are also simulated.

Satellite Sampling and Retrieval Errors in Regional Monthly Rain Estimates from TMI AMSR-E, SSM/I, AMSU-B and the TRMM PR

NASA Technical Reports Server (NTRS)

Fisher, Brad; Wolff, David B.

2010-01-01

Passive and active microwave rain sensors onboard earth-orbiting satellites estimate monthly rainfall from the instantaneous rain statistics collected during satellite overpasses. It is well known that climate-scale rain estimates from meteorological satellites incur sampling errors resulting from the process of discrete temporal sampling and statistical averaging. Sampling and retrieval errors ultimately become entangled in the estimation of the mean monthly rain rate. The sampling component of the error budget effectively introduces statistical noise into climate-scale rain estimates that obscure the error component associated with the instantaneous rain retrieval. Estimating the accuracy of the retrievals on monthly scales therefore necessitates a decomposition of the total error budget into sampling and retrieval error quantities. This paper presents results from a statistical evaluation of the sampling and retrieval errors for five different space-borne rain sensors on board nine orbiting satellites. Using an error decomposition methodology developed by one of the authors, sampling and retrieval errors were estimated at 0.25 resolution within 150 km of ground-based weather radars located at Kwajalein, Marshall Islands and Melbourne, Florida. Error and bias statistics were calculated according to the land, ocean and coast classifications of the surface terrain mask developed for the Goddard Profiling (GPROF) rain algorithm. Variations in the comparative error statistics are attributed to various factors related to differences in the swath geometry of each rain sensor, the orbital and instrument characteristics of the satellite and the regional climatology. The most significant result from this study found that each of the satellites incurred negative longterm oceanic retrieval biases of 10 to 30%.

Quantifying cancer cell receptors with paired-agent fluorescent imaging: a novel method to account for tissue optical property effects

NASA Astrophysics Data System (ADS)

Sadeghipour, Negar; Davis, Scott C.; Tichauer, Kenneth M.

2018-02-01

Dynamic fluorescence imaging approaches can be used to estimate the concentration of cell surface receptors in vivo. Kinetic models are used to generate the final estimation by taking the targeted imaging agent concentration as a function of time. However, tissue absorption and scattering properties cause the final readout signal to be on a different scale than the real fluorescent agent concentration. In paired-agent imaging approaches, simultaneous injection of a suitable control imaging agent with a targeted one can account for non-specific uptake and retention of the targeted agent. Additionally, the signal from the control agent can be a normalizing factor to correct for tissue optical property differences. In this study, the kinetic model used for paired-agent imaging analysis (i.e., simplified reference tissue model) is modified and tested in simulation and experimental data in a way that accounts for the scaling correction within the kinetic model fit to the data to ultimately extract an estimate of the targeted biomarker concentration.

Psychometric properties of the Persian version of the Intensive and Critical Care Nursing Competence Scale version-1 (ICCN-CS-1).

PubMed

Shouryabi, Ali Asghar; Ghahrisarabi, Alireza; Anboohi, Sima Zohari; Nasiri, Malihe; Rassouli, Maryam

2017-11-01

Nursing competence is highly related to patient outcomes and patient safety issues, especially in intensive care units. Competence assessment tools are needed specifically for intensive care nursing. This study was performed to determine psychometric properties of the Intensive and Critical Care Nursing Competence Scale version-1 between Iranian Nurses. The present study was a methodological research in which 289 nurses of Intensive Care Units from nine hospitals in Shahid Beheshti University of Medical Sciences in Tehran were selected between 2015 and 2016. The original version of the scale was translated into Persian and back-translated into English, and the comments of the developer were applied. The validity of the scale was the determined quality (content validity and face validity) and quantity (confirmatory factor analysis). Reliability of the scale was reported by Cronbach's alpha coefficient and Intra class Correlation Coefficient. SPSS-PC (v.21) and LISREL (v.8.5) were used to analyze the data. The intensive and critical care nursing competence scale version-1 is a self-assessment test that consists of 144 items and four domains which are the knowledge base, the skill base, the attitudes and values base and the experience base, which are divided into clinical competence and professional competence. Content and face validity was confirmed by 10 experts and 10 practitioner nurses in the intensive care units. In confirmatory factor analysis, all fitness indexes, except goodness of fit index (0.64), confirmed the four-factor structure of the ICCN-CS-1. The results of the factor analysis, load factor between 0.304 and 0.727 items was estimated; only 4 items out of 144 items, that were loaded were less than 0.3 due to high Cronbach's alpha coefficient (0.984-0.986), all items were preserved, no item was removed and 4 subscales of the original scale were confirmed. The results of this study indicated that the Persian version of "The Intensive and Critical Care Nursing Competence Scale version-1" is a valid and reliable scale for the assessment of competency among Iranian nurses, and it can be used as a reliable scale in nursing management, education and research.

[Food insecurity in the state of Nayarit, Mexico, and its association with socioeconomic factors].

PubMed

Haro-Mota, Rebeca de; Marceleño-Flores, Susana; Bojórquez-Serrano, José Irán; Nájera-González, Oyolsi

2016-08-01

Objetive: To estimate the proportion of households with food insecurity (FI) in twenty municipalities in the state of Nayarit, Mexico, and to identify the factors that determine it. FI was estimated using the harmonized version for Mexico of the Latin American and Caribbean household food security scale (ELCSA). Households were classified according to FI level: mild, moderate and severe. The distribution of FI was described by type of locality and prevalence of FI was analyzed by associated variables. 76.2% of households were identified with some FI level.The prevalence of FI was higher in rural households. Food insecurity situation was focused on households with the highest number of children under five years, highest number of older than 64 years, highest number of household members, female headship and less schooling of the household head. ELCSA can be useful to associate FI with socioeconomic factors.

Simultaneous effect of temperature, cyanide and ammonia-oxidizing bacteria concentrations on ammonia oxidation.

PubMed

Do, Hyojin; Lim, Juntaek; Shin, Seung Gu; Wu, Yi-Ju; Ahn, Johng-Hwa; Hwang, Seokhwan

2008-11-01

For biological nitrification, a set of experiments were carried out to approximate the response of lag period along with ammonia oxidation rate with respect to different concentrations of cyanide (CN-) and ammonia-oxidizing bacteria (AOB), and temperature variation in laboratory-scale batch reactors. The effects of simultaneous changes in these three factors on ammonia oxidation were quantitatively estimated and modeled using response surface analysis. The lag period and the ammonia oxidation rate responded differently to changes in the three factors. The lag period and the ammonia oxidation rate were significantly affected by the CN- and AOB concentrations, while temperature changes only affected the ammonia oxidation rate. The increase of AOB concentration and temperature alleviated the inhibition effect of cyanide on ammonia oxidation. The statistical method used in this study can be extended to estimate the quantitative effects of other environmental factors that can change simultaneously.

Factor structure of a standards-based inventory of competencies in social work with groups.

PubMed

Macgowan, Mark J; Dillon, Frank R; Spadola, Christine E

2018-01-01

This study extends previous findings on a measure of competencies based on Standards for Social Work Practice with Groups. The Inventory of Competencies in Social Work with Groups (ICSWG) measures confidence in performing the Standards. This study examines the latent structure of the Inventory, while illuminating the underlying structure of the Standards. A multinational sample of 586 persons completed the ICSWG. Exploratory factor analysis (EFA), reliability estimates, standard error of measurement estimates, and a range of validity tests were conducted. The EFA yielded a six-factor solution consisting of core values, mutuality/connectivity, collaboration, and three phases of group development (planning, beginnings/middles, endings). The alphas were .98 for the scale and ranged from .85 to .95 for the subscales. Correlations between the subscales and validators supported evidence of construct validity. The findings suggest key group work domains that should be taught and practiced in social work with groups.

The serial use of child neurocognitive tests: development versus practice effects.

PubMed

Slade, Peter D; Townes, Brenda D; Rosenbaum, Gail; Martins, Isabel P; Luis, Henrique; Bernardo, Mario; Martin, Michael D; Derouen, Timothy A

2008-12-01

When serial neurocognitive assessments are performed, 2 main factors are of importance: test-retest reliability and practice effects. With children, however, there is a third, developmental factor, which occurs as a result of maturation. Child tests recognize this factor through the provision of age-corrected scaled scores. Thus, a ready-made method for estimating the relative contribution of developmental versus practice effects is the comparison of raw (developmental and practice) and scaled (practice only) scores. Data from a pool of 507 Portuguese children enrolled in a study of dental amalgams (T. A. DeRouen, B. G. Leroux, et al., 2002; T. A. DeRouen, M. D. Martin, et al., 2006) showed that practice effects over a 5-year period varied on 8 neurocognitive tests. Simple regression equations are provided for calculating individual retest scores from initial test scores. (c) 2008 APA, all rights reserved.

Scaling up and error analysis of transpiration for Populus euphratica in a desert riparian forest

NASA Astrophysics Data System (ADS)

Si, J.; Li, W.; Feng, Q.

2013-12-01

Water consumption information of the forest stand is the most important factor for regional water resources management. However, water consumption of individual trees are usually measured based on the limited sample trees , so, it is an important issue how to realize eventual scaling up of data from a series of sample trees to entire stand. Estimation of sap flow flux density (Fd) and stand sapwood area (AS-stand) are among the most critical factors for determining forest stand transpiration using sap flow measurement. To estimate Fd, the various links in sap flow technology have great impact on the measurement of sap flow, to estimate AS-stand, an appropriate indirect technique for measuring each tree sapwood area (AS-tree) is required, because it is impossible to measure the AS-tree of all trees in a forest stand. In this study, Fd was measured in 2 mature P. euphratic trees at several radial depths, 0~10, 10~30mm, using sap flow sensors with the heat ratio method, the relationship model between AS-tree and stem diameter (DBH), growth model of AS-tree were established, using investigative original data of DBH, tree-age, and AS-tree. The results revealed that it can achieve scaling up of transpiration from sample trees to entire forest stand using AS-tree and Fd, however, the transpiration of forest stand (E) will be overvalued by 12.6% if using Fd of 0~10mm, and it will be underestimated by 25.3% if using Fd of 10~30mm, it implied that major uncertainties in mean stand Fd estimations are caused by radial variations in Fd. E will be obviously overvalued when the AS-stand is constant, this result imply that it is the key to improve the prediction accuracy that how to simulate the AS-stand changes in the day scale; They also showed that the potential errors in transpiration with a sample size of approximately ≥30 were almost stable for P.euphrtica, this suggests that to make an allometric equation it might be necessary to sample at least 30 trees.

Estimates of N2O, NO and NH3 Emissions From Croplands in East, Southeast and South Asia

NASA Astrophysics Data System (ADS)

Yan, X.; Ohara, T.; Akimoto, H.

2002-12-01

Agricultural activities have greatly altered the global nitrogen cycle and produced nitrogenous gases of environmentally significance. More than half of the global chemical nitrogen fertilizer is used for crop production in East, Southeast and South Asia where rice the center of nutrition. Emissions of nitrous oxide (N2O), nitric oxide (NO) and ammonia (NH3) from croplands in this region were estimated by considering both background emission and emissions resulted from nitrogen added to croplands, including chemical nitrogen, animal manure used as fertilizer, biological fixed nitrogen and nitrogen in crop residue returned to field. Background emission fluxes of N2O and NO from croplands were estimated at 1.16 and 0.52 kg N ha-1yr-1, respectively. A fertilizer-induced N2O emission factor of 1.25% for upland was adopted from IPCC guidelines, and a factor of 0.25% was derived for paddy field from measurements. Total N2O emission from croplands in the region was estimated at 1.16 Tg N yr-1, with 41% contributed by background emission which was not considered in previous global estimates. However, the average fertilizer-induced N2O emission is only 0.93%, lower than the default IPCC value of 1.25% due to the low emission factor from paddy field. A fertilizer-induced NO emission factor of 0.66% for upland was derived from field measurements, and a factor of 0.13% was assumed for paddy field. Total NO emission was 572 Gg N yr-1 in the region, with 38% due to background emission. Average fertilizer-induce NO emission factor was 0.48%. Extrapolating this estimate to global scale will result in a global NO emission from cropland of 1.6 Tg N yr-1, smaller than other global estimates. Total NH3 emission was estimated at 11.8 Tg N yr-1. The use of urea and ammonium bicarbonate and the cultivation of rice lead to a high average NH3 loss rate of chemical fertilizer in the region. Emissions were distributed at 0.5° grid by using a global landuse database.

MOVES (MOTOR VEHICLE EMISSION SIMULATOR) MODEL ...

EPA Pesticide Factsheets

A computer model, intended to eventually replace the MOBILE model and to incorporate the NONROAD model, that will provide the ability to estimate criteria and toxic air pollutant emission factors and emission inventories that are specific to the areas and time periods of interest, at scales ranging from local to national. Development of a new emission factor and inventory model for mobile source emissions. The model will be used by air pollution modelers within EPA, and at the State and local levels.

Development of the Muscle Dysmorphia Inventory (MDI).

PubMed

Rhea, D J; Lantz, C D; Cornelius, A E

2004-12-01

The development of the 6-factor, 27-item Muscle Dysmorphia Inventory (MDI) was based on Lantz et al. proposed model of characteristics associated with Muscle Dysmorphia. quantitative procedures including item-to-total correlations, exploratory and confirmatory factor analyses, and structure equation modeling confirmed the construct validity of the scale. Convergent validity was also tested. bodybuilding and powerlifting competition venues, weight training facilities, and university athletic venues. the 1(st) study consisted of 77 experienced male free weight lifters. The 2(nd) study consisted of 156 male non-competitive bodybuilders and weight lifters and 168 elite level powerlifters and bodybuilders. The 3(rd) study consisted of 151 male and female bodybuilders and weight lifters. each participant completed demographic information, the MDI, Drive for Thinness subscale of the Eating Disorder Inventory, and the Training Dependency subscale of the Bodybuilding Dependence Scale. Reliability estimates (Cronbach's a) ranged from 0.72 to 0.94. Factor loadings in all 3 studies supported the 6-factor structure (size/symmetry, supplement use, exercise dependence, pharmacological use, dietary behavior, and physique protection). Much of the scale validation was focused on construct validity, however, correlations with the MDI's subscales and the Training Dependency subscale of the Bodybuilding Dependence Scale and the Drive for Thinness subscale of the Eating Disorder Inventory provided evidence of convergent validity also. From these preliminary results, the MDI appears to contribute to the identification of a newly formed disorder by offering a multi-dimensional measure of factors related to Muscle Dysmorphia.

Estimating interaction on an additive scale between continuous determinants in a logistic regression model.

PubMed

Knol, Mirjam J; van der Tweel, Ingeborg; Grobbee, Diederick E; Numans, Mattijs E; Geerlings, Mirjam I

2007-10-01

To determine the presence of interaction in epidemiologic research, typically a product term is added to the regression model. In linear regression, the regression coefficient of the product term reflects interaction as departure from additivity. However, in logistic regression it refers to interaction as departure from multiplicativity. Rothman has argued that interaction estimated as departure from additivity better reflects biologic interaction. So far, literature on estimating interaction on an additive scale using logistic regression only focused on dichotomous determinants. The objective of the present study was to provide the methods to estimate interaction between continuous determinants and to illustrate these methods with a clinical example. and results From the existing literature we derived the formulas to quantify interaction as departure from additivity between one continuous and one dichotomous determinant and between two continuous determinants using logistic regression. Bootstrapping was used to calculate the corresponding confidence intervals. To illustrate the theory with an empirical example, data from the Utrecht Health Project were used, with age and body mass index as risk factors for elevated diastolic blood pressure. The methods and formulas presented in this article are intended to assist epidemiologists to calculate interaction on an additive scale between two variables on a certain outcome. The proposed methods are included in a spreadsheet which is freely available at: http://www.juliuscenter.nl/additive-interaction.xls.

Impacts of different types of measurements on estimating unsaturated flow parameters

NASA Astrophysics Data System (ADS)

Shi, Liangsheng; Song, Xuehang; Tong, Juxiu; Zhu, Yan; Zhang, Qiuru

2015-05-01

This paper assesses the value of different types of measurements for estimating soil hydraulic parameters. A numerical method based on ensemble Kalman filter (EnKF) is presented to solely or jointly assimilate point-scale soil water head data, point-scale soil water content data, surface soil water content data and groundwater level data. This study investigates the performance of EnKF under different types of data, the potential worth contained in these data, and the factors that may affect estimation accuracy. Results show that for all types of data, smaller measurements errors lead to faster convergence to the true values. Higher accuracy measurements are required to improve the parameter estimation if a large number of unknown parameters need to be identified simultaneously. The data worth implied by the surface soil water content data and groundwater level data is prone to corruption by a deviated initial guess. Surface soil moisture data are capable of identifying soil hydraulic parameters for the top layers, but exert less or no influence on deeper layers especially when estimating multiple parameters simultaneously. Groundwater level is one type of valuable information to infer the soil hydraulic parameters. However, based on the approach used in this study, the estimates from groundwater level data may suffer severe degradation if a large number of parameters must be identified. Combined use of two or more types of data is helpful to improve the parameter estimation.

Impacts of Different Types of Measurements on Estimating Unsaturatedflow Parameters

NASA Astrophysics Data System (ADS)

Shi, L.

2015-12-01

This study evaluates the value of different types of measurements for estimating soil hydraulic parameters. A numerical method based on ensemble Kalman filter (EnKF) is presented to solely or jointly assimilate point-scale soil water head data, point-scale soil water content data, surface soil water content data and groundwater level data. This study investigates the performance of EnKF under different types of data, the potential worth contained in these data, and the factors that may affect estimation accuracy. Results show that for all types of data, smaller measurements errors lead to faster convergence to the true values. Higher accuracy measurements are required to improve the parameter estimation if a large number of unknown parameters need to be identified simultaneously. The data worth implied by the surface soil water content data and groundwater level data is prone to corruption by a deviated initial guess. Surface soil moisture data are capable of identifying soil hydraulic parameters for the top layers, but exert less or no influence on deeper layers especially when estimating multiple parameters simultaneously. Groundwater level is one type of valuable information to infer the soil hydraulic parameters. However, based on the approach used in this study, the estimates from groundwater level data may suffer severe degradation if a large number of parameters must be identified. Combined use of two or more types of data is helpful to improve the parameter estimation.

Bayesian Modal Estimation of the Four-Parameter Item Response Model in Real, Realistic, and Idealized Data Sets.

PubMed

Waller, Niels G; Feuerstahler, Leah

2017-01-01

In this study, we explored item and person parameter recovery of the four-parameter model (4PM) in over 24,000 real, realistic, and idealized data sets. In the first analyses, we fit the 4PM and three alternative models to data from three Minnesota Multiphasic Personality Inventory-Adolescent form factor scales using Bayesian modal estimation (BME). Our results indicated that the 4PM fits these scales better than simpler item Response Theory (IRT) models. Next, using the parameter estimates from these real data analyses, we estimated 4PM item parameters in 6,000 realistic data sets to establish minimum sample size requirements for accurate item and person parameter recovery. Using a factorial design that crossed discrete levels of item parameters, sample size, and test length, we also fit the 4PM to an additional 18,000 idealized data sets to extend our parameter recovery findings. Our combined results demonstrated that 4PM item parameters and parameter functions (e.g., item response functions) can be accurately estimated using BME in moderate to large samples (N ⩾ 5, 000) and person parameters can be accurately estimated in smaller samples (N ⩾ 1, 000). In the supplemental files, we report annotated [Formula: see text] code that shows how to estimate 4PM item and person parameters in [Formula: see text] (Chalmers, 2012 ).

Systematic monitoring of male circumcision scale-up in Nyanza, Kenya: exploratory factor analysis of service quality instrument and performance ranking.

PubMed

Omondi Aduda, Dickens S; Ouma, Collins; Onyango, Rosebella; Onyango, Mathews; Bertrand, Jane

2014-01-01

Considerable conceptual and operational complexities related to service quality measurements and variability in delivery contexts of scaled-up medical male circumcision, pose real challenges to monitoring implementation of quality and safety. Clarifying latent factors of the quality instruments can enhance contextual applicability and the likelihood that observed service outcomes are appropriately assessed. To explore factors underlying SYMMACS service quality assessment tool (adopted from the WHO VMMC quality toolkit) and; determine service quality performance using composite quality index derived from the latent factors. Using a comparative process evaluation of Voluntary Medical Male Circumcision Scale-Up in Kenya site level data was collected among health facilities providing VMMC over two years. Systematic Monitoring of the Medical Male Circumcision Scale-Up quality instrument was used to assess availability of guidelines, supplies and equipment, infection control, and continuity of care services. Exploratory factor analysis was performed to clarify quality structure. Fifty four items and 246 responses were analyzed. Based on Eigenvalue >1.00 cut-off, factors 1, 2 & 3 were retained each respectively having eigenvalues of 5.78; 4.29; 2.99. These cumulatively accounted for 29.1% of the total variance (12.9%; 9.5%; 6.7%) with final communality estimates being 13.06. Using a cut-off factor loading value of ≥0.4, fifteen items loading on factor 1, five on factor 2 and one on factor 3 were retained. Factor 1 closely relates to preparedness to deliver safe male circumcisions while factor two depicts skilled task performance and compliance with protocols. Of the 28 facilities, 32% attained between 90th and 95th percentile (excellent); 45% between 50th and 75th percentiles (average) and 14.3% below 25th percentile (poor). the service quality assessment instrument may be simplified to have nearly 20 items that relate more closely to service outcomes. Ranking of facilities and circumcision procedure using a composite index based on these items indicates that majority performed above average.

Symptom severity of patients with advanced cancer in palliative care unit: longitudinal assessments of symptoms improvement.

PubMed

Tai, Shu-Yu; Lee, Chung-Yin; Wu, Chien-Yi; Hsieh, Hui-Ya; Huang, Joh-Jong; Huang, Chia-Tsuan; Chien, Chen-Yu

2016-03-11

This study assessed the symptom severity of patients with advanced cancer in a palliative care unit and explored the factors associated with symptom improvement. This study was conducted in a palliative care unit in Taiwan between October 2004 and December 2009. Symptom intensity was measured by the "Symptom Reporting Form", and graded on a scale of 0 to 4 (0 = none, and 4 = extreme). These measures were assessed on the 1(st), 3(rd), 5(th), and 7(th) Day in the palliative care unit. The study data comprised routine clinical records and patients' demographic data. Generalized estimating equation (GEE) was used to assess the symptom improvement, and investigate the factors associated with the symptom reporting form scores. Among the 824 recruited patients with advanced cancer, pain (78.4%), anorexia (64.4%) and constipation (63.5%) were the most common and severe symptom. After controlling for other factors in the multivariate GEE model, the day of palliative care administration was a significant factor associated with all of the scales, except Days 7 on the dyspnoea and oedema scales and Day 5 on the anxiety scale. In addition, patients aged ≥ 65 years exhibited significantly lower scores on the pain, sleep disturbance, depression, and anxiety scales than did those aged < 65 years. Moreover, female patients exhibited higher scores on the vomiting, anorexia, oedema, depression, and anxiety scales than did male patients. Furthermore, patients with gastrointestinal tract cancer exhibited higher scores on the constipation, vomiting, anorexia, oedema, depression, and anxiety scales and lower scores on the dyspnoea scale than did those with lung cancer. Patients with breast cancer exhibited higher scores on the oedema scale and lower scores on the anxiety scale. Patients with genitourinary cancer exhibited higher scores on the vomiting and oedema scales and lower scores on the dyspnoea scale. Patients with head, neck, and oral cancer exhibited lower scores on the oedema scale alone. The symptom severity declined during the first week in the palliative care unit. In addition, differences in sex and primary cancer sites may contribute to varying degrees of symptom improvement.

Orientation to the Caregiver Role Among Latinas of Mexican Origin.

PubMed

Mendez-Luck, Carolyn A; John Geldhof, G; Anthony, Katherine P; Neil Steers, W; Mangione, Carol M; Hays, Ron D

2016-12-01

To develop the Caregiver Orientation Scale for Mexican-Origin Women and evaluate its psychometric properties. We developed a questionnaire to measure domains of cultural orientation to the caregiver role based on formative research and on the Cultural Justifications for Caregiving Scale. We conducted a series of exploratory factor analyses (EFAs) on data collected from 163 caregivers. We estimated internal consistency reliability (Cronbach's coefficient alpha) and assessed construct validity by estimating correlations between all latent factors and self-rated health, interview language, and weekly hours of care. EFAs suggested four factors representing familism, obligation, burden, and caregiving intensity that displayed good fit (χ 2 (df = 63) = 70.52, p = .24; RMSEA = .03 [90% CI: 0.00, 0.06]; comparative fit index = .99). Multi-item scales representing the four domains had coefficient alphas ranging from .68 to .86. Obligation was positively associated with burden (.46, p < .001) and intensity (.34, p < .01), which were themselves positively correlated (.63, p < .001). Familism was positively associated with obligation (.25, p < .05) yet negatively associated with burden (-.35, p < .01) and intensity (-.22, p < .05). Weekly hours of care were positively associated with burden (.26, p < .01) and intensity (.18, p < .05), whereas self-rated health and burden (-.21, p < .05) and Spanish language and intensity (-.31, p < .001) were negatively correlated. The study shows that Mexican-origin caregiver orientation is multidimensional and that caregivers may have conflicting motivations for caregiving. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Validation of farm-scale methane emissions using nocturnal boundary layer budgets

NASA Astrophysics Data System (ADS)

Stieger, J.; Bamberger, I.; Buchmann, N.; Eugster, W.

2015-08-01

This study provides the first experimental validation of Swiss agricultural methane emission estimates at the farm scale. We measured CH4 concentrations at a Swiss farmstead during two intensive field campaigns in August 2011 and July 2012 to (1) quantify the source strength of livestock methane emissions using a tethered balloon system, and (2) to validate inventory emission estimates via nocturnal boundary layer (NBL) budgets. Field measurements were performed at a distance of 150 m from the nearest farm buildings with a tethered balloon system in combination with gradient measurements at eight heights on a 10 m tower to better resolve the near-surface concentrations. Vertical profiles of air temperature, relative humidity, CH4 concentration, wind speed and wind direction showed that the NBL was strongly influenced by local transport processes and by the valley wind system. Methane concentrations showed a pronounced time course, with highest concentrations in the second half of the night. NBL budget flux estimates were obtained via a time-space kriging approach. Main uncertainties of NBL budget flux estimates were associated with instationary atmospheric conditions and the estimate of the inversion height zi (top of volume integration). The mean NBL budget fluxes of 1.60 ± 0.31 μg CH4 m-2 s-1 (1.40 ± 0.50 and 1.66 ± 0.20 μg CH4 m-2 s-1 in 2011 and 2012, respectively) were in good agreement with local inventory estimates based on current livestock number and default emission factors, with 1.29 ± 0.47 and 1.74 ± 0.63 μg CH4 m-2 s-1 for 2011 and 2012, respectively. This indicates that emission factors used for the national inventory reports are adequate, and we conclude that the NBL budget approach is a useful tool to validate emission inventory estimates.

Validation of farm-scale methane emissions using nocturnal boundary layer budgets

NASA Astrophysics Data System (ADS)

Stieger, J.; Bamberger, I.; Buchmann, N.; Eugster, W.

2015-12-01

This study provides the first experimental validation of Swiss agricultural methane emission estimates at the farm scale. We measured CH4 concentrations at a Swiss farmstead during two intensive field campaigns in August 2011 and July 2012 to (1) quantify the source strength of livestock methane emissions using a tethered balloon system and (2) to validate inventory emission estimates via nocturnal boundary layer (NBL) budgets. Field measurements were performed at a distance of 150 m from the nearest farm buildings with a tethered balloon system in combination with gradient measurements at eight heights on a 10 m tower to better resolve the near-surface concentrations. Vertical profiles of air temperature, relative humidity, CH4 concentration, wind speed, and wind direction showed that the NBL was strongly influenced by local transport processes and by the valley wind system. Methane concentrations showed a pronounced time course, with highest concentrations in the second half of the night. NBL budget flux estimates were obtained via a time-space kriging approach. Main uncertainties of NBL budget flux estimates were associated with nonstationary atmospheric conditions and the estimate of the inversion height zi (top of volume integration). The mean NBL budget fluxes of 1.60 ± 0.31 μg CH4 m-2 s-1 (1.40 ± 0.50 and 1.66 ± 0.20 μg CH4 m-2 s-1 in 2011 and 2012 respectively) were in good agreement with local inventory estimates based on current livestock number and default emission factors, with 1.29 ± 0.47 and 1.74 ± 0.63 μg CH4 m-2 s-1 for 2011 and 2012 respectively. This indicates that emission factors used for the national inventory reports are adequate, and we conclude that the NBL budget approach is a useful tool to validate emission inventory estimates.

Teacher Reporting Attitudes Scale (TRAS): confirmatory and exploratory factor analyses with a Malaysian sample.

PubMed

Choo, Wan Yuen; Walsh, Kerryann; Chinna, Karuthan; Tey, Nai Peng

2013-01-01

The Teacher Reporting Attitude Scale (TRAS) is a newly developed tool to assess teachers' attitudes toward reporting child abuse and neglect. This article reports on an investigation of the factor structure and psychometric properties of the short form Malay version of the TRAS. A self-report cross-sectional survey was conducted with 667 teachers in 14 randomly selected schools in Selangor state, Malaysia. Analyses were conducted in a 3-stage process using both confirmatory (stages 1 and 3) and exploratory factor analyses (stage 2) to test, modify, and confirm the underlying factor structure of the TRAS in a non-Western teacher sample. Confirmatory factor analysis did not support a 3-factor model previously reported in the original TRAS study. Exploratory factor analysis revealed an 8-item, 4-factor structure. Further confirmatory factor analysis demonstrated appropriateness of the 4-factor structure. Reliability estimates for the four factors-commitment, value, concern, and confidence-were moderate. The modified short form TRAS (Malay version) has potential to be used as a simple tool for relatively quick assessment of teachers' attitudes toward reporting child abuse and neglect. Cross-cultural differences in attitudes toward reporting may exist and the transferability of newly developed instruments to other populations should be evaluated.

The Reliability and Validity of the Persian Version of Three-Factor Eating Questionnaire-R18 (TFEQ-R18) in Overweight and Obese Females

PubMed Central

Mostafavi, Seyed-Ali; Akhondzadeh, Shahin; Mohammadi, Mohammad Reza; Eshraghian, Mohammad Reza; Hosseini, Saeed; Chamari, Maryam; Keshavarz, Seyed Ali

2017-01-01

Objective : The Three-Factor Eating Questionnaire Reduced (TFEQ-R18) is one of the most widely used instruments for assessing eating behavior worldwide. The present study aimed at confirming the reliability and validity of the Persian version of TFEQ-R18 among overweight and obese females in Iran. Method: In the present study, 168 overweight and obese females consented to participate. We estimated the anthropometric indices and asked the participants to complete the TFEQ-R18. Beck Depression Inventory (BDI), Spielberger Anxiety Scale, Appetite Visual Analogue Rating Scale, Food Craving Questionnaire (FCQ), Compulsive Eating Scale (CES), and Restraint Eating Visual Analogue Rating Scale were performed simultaneously to assess concurrent validity. Two weeks later, TFEQ-R18 was repeated for 126 participants to assess test-retest reliability. Moreover, we reported the internal consistency and factor analysis of this questionnaire. Results: Using the results of the reliability analysis and exploratory factor analysis of the principal component by varimax rotation, we extracted 3 factors: hunger, cognitive restraint, and emotional eating. After removing the Items 16 and 18, the Cronbach’s alpha was increased to 0.73 (The Cronbach’s alpha of the factors was 0.84, 0.64, and 0.7, respectively). The results of the Pearson correlation revealed a consistency of 0.87 between the test and retest administrations (p = 0.001). Significant positive correlations were observed between TFEQ-R18 and BDI, Spielberger Anxiety Scale, FCQ, CES, appetite, body weight, fat percentage, and calorie intake. Moreover, a negative correlation was observed in Restraint Eating Visual Analogue Rating Scale and muscle percentage. Conclusion: This study aimed at presenting preliminary support for the reliability and validity of the Persian version of TFEQ-R18 and its psychometric characteristics. This instrument may be helpful in clinical practice and research studies of obesity, appetite, and eating behavior. PMID:28659982

Attitude-Independent Magnetometer Calibration for Spin-Stabilized Spacecraft

NASA Technical Reports Server (NTRS)

Natanson, Gregory

2005-01-01

The paper describes a three-step estimator to calibrate a Three-Axis Magnetometer (TAM) using TAM and slit Sun or star sensor measurements. In the first step, the Calibration Utility forms a loss function from the residuals of the magnitude of the geomagnetic field. This loss function is minimized with respect to biases, scale factors, and nonorthogonality corrections. The second step minimizes residuals of the projection of the geomagnetic field onto the spin axis under the assumption that spacecraft nutation has been suppressed by a nutation damper. Minimization is done with respect to various directions of the body spin axis in the TAM frame. The direction of the spin axis in the inertial coordinate system required for the residual computation is assumed to be unchanged with time. It is either determined independently using other sensors or included in the estimation parameters. In both cases all estimation parameters can be found using simple analytical formulas derived in the paper. The last step is to minimize a third loss function formed by residuals of the dot product between the geomagnetic field and Sun or star vector with respect to the misalignment angle about the body spin axis. The method is illustrated by calibrating TAM for the Fast Auroral Snapshot Explorer (FAST) using in-flight TAM and Sun sensor data. The estimated parameters include magnetic biases, scale factors, and misalignment angles of the spin axis in the TAM frame. Estimation of the misalignment angle about the spin axis was inconclusive since (at least for the selected time interval) the Sun vector was about 15 degrees from the direction of the spin axis; as a result residuals of the dot product between the geomagnetic field and Sun vectors were to a large extent minimized as a by-product of the second step.

An allometric pharmacokinetic/pharmacodynamics model for BI 893923, a novel IGF-1 receptor inhibitor.

PubMed

Titze, Melanie I; Schaaf, Otmar; Hofmann, Marco H; Sanderson, Michael P; Zahn, Stephan K; Quant, Jens; Lehr, Thorsten

2017-03-01

BI 893923 is a novel IGF1R/INSR inhibitor with promising anti-tumor efficacy. Dose-limiting hyperglycemia has been observed for other IGF1R/INSR inhibitors in clinical trials. To counterbalance anti-tumor efficacy with the risk of hyperglycemia and to determine the therapeutic window, we aimed to develop a translational pharmacokinetic/pharmacodynamics model for BI 893923. This aimed to translate pharmacokinetics and pharmacodynamics from animals to humans by an allometrically scaled semi-mechanistic model. Model development was based on a previously published PK/PD model for BI 893923 in mice (Titze et al., Cancer Chemother Pharmacol 77:1303-1314, 13). PK and blood glucose parameters were scaled by allometric principles using body weight as a scaling factor along with an estimation of the parameter exponents. Biomarker and tumor growth parameters were extrapolated from mouse to human using the body weight ratio as scaling factor. The allometric PK/PD model successfully described BI 893923 pharmacokinetics and blood glucose across mouse, rat, dog, minipig, and monkey. BI 893923 human exposure as well as blood glucose and tumor growth were predicted and compared for different dosing scenarios. A comprehensive risk-benefit analysis was conducted by determining the net clinical benefit for each schedule. An oral dose of 2750 mg BI 893923 divided in three evenly distributed doses was identified as the optimal human dosing regimen, predicting a tumor growth inhibition of 90.4% without associated hyperglycemia. Our model supported human therapeutic dose estimation by rationalizing the optimal efficacious dosing regimen with minimal undesired effects. This modeling approach may be useful for PK/PD scaling of other IGF1R/INSR inhibitors.

Spatial analysis of instream nitrogen loads and factors controlling nitrogen delivery to streams in the southeastern United States using spatially referenced regression on watershed attributes (SPARROW) and regional classification frameworks

USGS Publications Warehouse

Hoos, A.B.; McMahon, G.

2009-01-01

Understanding how nitrogen transport across the landscape varies with landscape characteristics is important for developing sound nitrogen management policies. We used a spatially referenced regression analysis (SPARROW) to examine landscape characteristics influencing delivery of nitrogen from sources in a watershed to stream channels. Modelled landscape delivery ratio varies widely (by a factor of 4) among watersheds in the southeastern United States - higher in the western part (Tennessee, Alabama, and Mississippi) than in the eastern part, and the average value for the region is lower compared to other parts of the nation. When we model landscape delivery ratio as a continuous function of local-scale landscape characteristics, we estimate a spatial pattern that varies as a function of soil and climate characteristics but exhibits spatial structure in residuals (observed load minus predicted load). The spatial pattern of modelled landscape delivery ratio and the spatial pattern of residuals coincide spatially with Level III ecoregions and also with hydrologic landscape regions. Subsequent incorporation into the model of these frameworks as regional scale variables improves estimation of landscape delivery ratio, evidenced by reduced spatial bias in residuals, and suggests that cross-scale processes affect nitrogen attenuation on the landscape. The model-fitted coefficient values are logically consistent with the hypothesis that broad-scale classifications of hydrologic response help to explain differential rates of nitrogen attenuation, controlling for local-scale landscape characteristics. Negative model coefficients for hydrologic landscape regions where the primary flow path is shallow ground water suggest that a lower fraction of nitrogen mass will be delivered to streams; this relation is reversed for regions where the primary flow path is overland flow.

Spatial analysis of instream nitrogen loads and factors controlling nitrogen delivery to streams in the southeastern United States using spatially referenced regression on watershed attributes (SPARROW) and regional classification frameworks

USGS Publications Warehouse

Hoos, Anne B.; McMahon, Gerard

2009-01-01

Understanding how nitrogen transport across the landscape varies with landscape characteristics is important for developing sound nitrogen management policies. We used a spatially referenced regression analysis (SPARROW) to examine landscape characteristics influencing delivery of nitrogen from sources in a watershed to stream channels. Modelled landscape delivery ratio varies widely (by a factor of 4) among watersheds in the southeastern United States—higher in the western part (Tennessee, Alabama, and Mississippi) than in the eastern part, and the average value for the region is lower compared to other parts of the nation. When we model landscape delivery ratio as a continuous function of local-scale landscape characteristics, we estimate a spatial pattern that varies as a function of soil and climate characteristics but exhibits spatial structure in residuals (observed load minus predicted load). The spatial pattern of modelled landscape delivery ratio and the spatial pattern of residuals coincide spatially with Level III ecoregions and also with hydrologic landscape regions. Subsequent incorporation into the model of these frameworks as regional scale variables improves estimation of landscape delivery ratio, evidenced by reduced spatial bias in residuals, and suggests that cross-scale processes affect nitrogen attenuation on the landscape. The model-fitted coefficient values are logically consistent with the hypothesis that broad-scale classifications of hydrologic response help to explain differential rates of nitrogen attenuation, controlling for local-scale landscape characteristics. Negative model coefficients for hydrologic landscape regions where the primary flow path is shallow ground water suggest that a lower fraction of nitrogen mass will be delivered to streams; this relation is reversed for regions where the primary flow path is overland flow.

Short-term prediction of rain attenuation level and volatility in Earth-to-Satellite links at EHF band

NASA Astrophysics Data System (ADS)

de Montera, L.; Mallet, C.; Barthès, L.; Golé, P.

2008-08-01

This paper shows how nonlinear models originally developed in the finance field can be used to predict rain attenuation level and volatility in Earth-to-Satellite links operating at the Extremely High Frequencies band (EHF, 20 50 GHz). A common approach to solving this problem is to consider that the prediction error corresponds only to scintillations, whose variance is assumed to be constant. Nevertheless, this assumption does not seem to be realistic because of the heteroscedasticity of error time series: the variance of the prediction error is found to be time-varying and has to be modeled. Since rain attenuation time series behave similarly to certain stocks or foreign exchange rates, a switching ARIMA/GARCH model was implemented. The originality of this model is that not only the attenuation level, but also the error conditional distribution are predicted. It allows an accurate upper-bound of the future attenuation to be estimated in real time that minimizes the cost of Fade Mitigation Techniques (FMT) and therefore enables the communication system to reach a high percentage of availability. The performance of the switching ARIMA/GARCH model was estimated using a measurement database of the Olympus satellite 20/30 GHz beacons and this model is shown to outperform significantly other existing models. The model also includes frequency scaling from the downlink frequency to the uplink frequency. The attenuation effects (gases, clouds and rain) are first separated with a neural network and then scaled using specific scaling factors. As to the resulting uplink prediction error, the error contribution of the frequency scaling step is shown to be larger than that of the downlink prediction, indicating that further study should focus on improving the accuracy of the scaling factor.

BF into cubic meters

Treesearch

Henry Spelter

2002-01-01

Noted forest products industry researcher and writer says the conversion factor traditionally used to convert logs measured in board feet to cubic meters has risen. In the U.S., most timber is measured in terms of board feet. The log scales currently in use to estimate lumber recovery from roundwood, however, were created in the 19th century according to sawmill...

Environmental Risk to Health of the Population

ERIC Educational Resources Information Center

Anopchenko, Tatiana Y.; Murzin, Anton D.; Kandrashina, Elena A.; Kosyakova, Inessa V.; Surnina, Olga E.

2016-01-01

Researches of the last years in the field of ecological epidemiology and the analysis of risk for health allow to claim with confidence that the polluted environment is one of the important factors defining changes of a state of health of the population. Expert opinions on the scale of this influence differ considerably now. These estimations vary…

Bayesian structural equation modeling in sport and exercise psychology.

PubMed

Stenling, Andreas; Ivarsson, Andreas; Johnson, Urban; Lindwall, Magnus

2015-08-01

Bayesian statistics is on the rise in mainstream psychology, but applications in sport and exercise psychology research are scarce. In this article, the foundations of Bayesian analysis are introduced, and we will illustrate how to apply Bayesian structural equation modeling in a sport and exercise psychology setting. More specifically, we contrasted a confirmatory factor analysis on the Sport Motivation Scale II estimated with the most commonly used estimator, maximum likelihood, and a Bayesian approach with weakly informative priors for cross-loadings and correlated residuals. The results indicated that the model with Bayesian estimation and weakly informative priors provided a good fit to the data, whereas the model estimated with a maximum likelihood estimator did not produce a well-fitting model. The reasons for this discrepancy between maximum likelihood and Bayesian estimation are discussed as well as potential advantages and caveats with the Bayesian approach.

New perspectives on the Popigai impact structure

NASA Technical Reports Server (NTRS)

Garvin, J. B.; Deino, A. L.

1992-01-01

The record of large-scale cratering on Earth is scant, and the only currently 'proven' 100-km-class impact structure known to have formed within the Cenozoic is Popigai, located in the Siberian Arctic at 71.5 deg N, 111 deg E. Popigai is clearly a multiringed impact basin formed within the crystalline shield rocks (Anabar) and platform sediments of the Siberian taiga, and estimates of the volume of preserved impact melt typically exceed 1700 cu km, which is within a factor of 2-3 of what would be predicted using scaling relationships. We present the preliminary results of an analysis of the present-day topography of the Popigai structure, together with refined absolute age estimates, in order to reconstruct the pre-erosional morphology of the basin, as well as to quantify the erosion or sediment infill rates in the Popigai region.

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

The firm yield is the maximum average daily withdrawal that can be extracted from a reservoir without risk of failure during an extended drought period. Previously developed procedures for determining the firm yield of a reservoir were refined and applied to 38 reservoir systems in Massachusetts, including 25 single- and multiple-reservoir systems that were examined during previous studies and 13 additional reservoir systems. Changes to the firm-yield model include refinements to the simulation methods and input data, as well as the addition of several scenario-testing capabilities. The simulation procedure was adapted to run at a daily time step over a 44-year simulation period, and daily streamflow and meteorological data were compiled for all the reservoirs for input to the model. Another change to the model-simulation methods is the adjustment of the scaling factor used in estimating groundwater contributions to the reservoir. The scaling factor is used to convert the daily groundwater-flow rate into a volume by multiplying the rate by the length of reservoir shoreline that is hydrologically connected to the aquifer. Previous firm-yield analyses used a constant scaling factor that was estimated from the reservoir surface area at full pool. The use of a constant scaling factor caused groundwater flows during periods when the reservoir stage was very low to be overestimated. The constant groundwater scaling factor used in previous analyses was replaced with a variable scaling factor that is based on daily reservoir stage. This change reduced instability in the groundwater-flow algorithms and produced more realistic groundwater-flow contributions during periods of low storage. Uncertainty in the firm-yield model arises from many sources, including errors in input data. The sensitivity of the model to uncertainty in streamflow input data and uncertainty in the stage-storage relation was examined. A series of Monte Carlo simulations were performed on 22 reservoirs 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.

Full-scale 3-D finite element modeling of a two-loop pressurized water reactor for heat transfer, thermal–mechanical cyclic stress analysis, and environmental fatigue life estimation

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

Mohanty, Subhasish; Soppet, William K.; Majumdar, Saurindranath

This paper discusses a system-level finite element model of a two-loop pressurized water reactor (PWR). Based on this model, system-level heat transfer analysis and subsequent sequentially coupled thermal-mechanical stress analysis were performed for typical thermal-mechanical fatigue cycles. The in-air fatigue lives of example components, such as the hot and cold legs, were estimated on the basis of stress analysis results, ASME in-air fatigue life estimation criteria, and fatigue design curves. Furthermore, environmental correction factors and associated PWR environment fatigue lives for the hot and cold legs were estimated by using estimated stress and strain histories and the approach described inmore » US-NRC report: NUREG-6909.« less

Ensemble Kalman filters for dynamical systems with unresolved turbulence

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

Grooms, Ian, E-mail: grooms@cims.nyu.edu; Lee, Yoonsang; Majda, Andrew J.

Ensemble Kalman filters are developed for turbulent dynamical systems where the forecast model does not resolve all the active scales of motion. Coarse-resolution models are intended to predict the large-scale part of the true dynamics, but observations invariably include contributions from both the resolved large scales and the unresolved small scales. The error due to the contribution of unresolved scales to the observations, called ‘representation’ or ‘representativeness’ error, is often included as part of the observation error, in addition to the raw measurement error, when estimating the large-scale part of the system. It is here shown how stochastic superparameterization (amore » multiscale method for subgridscale parameterization) can be used to provide estimates of the statistics of the unresolved scales. In addition, a new framework is developed wherein small-scale statistics can be used to estimate both the resolved and unresolved components of the solution. The one-dimensional test problem from dispersive wave turbulence used here is computationally tractable yet is particularly difficult for filtering because of the non-Gaussian extreme event statistics and substantial small scale turbulence: a shallow energy spectrum proportional to k{sup −5/6} (where k is the wavenumber) results in two-thirds of the climatological variance being carried by the unresolved small scales. Because the unresolved scales contain so much energy, filters that ignore the representation error fail utterly to provide meaningful estimates of the system state. Inclusion of a time-independent climatological estimate of the representation error in a standard framework leads to inaccurate estimates of the large-scale part of the signal; accurate estimates of the large scales are only achieved by using stochastic superparameterization to provide evolving, large-scale dependent predictions of the small-scale statistics. Again, because the unresolved scales contain so much energy, even an accurate estimate of the large-scale part of the system does not provide an accurate estimate of the true state. By providing simultaneous estimates of both the large- and small-scale parts of the solution, the new framework is able to provide accurate estimates of the true system state.« less

[Comparison of three stand-level biomass estimation methods].

PubMed

Dong, Li Hu; Li, Feng Ri

2016-12-01

At present, the forest biomass methods of regional scale attract most of attention of the researchers, and developing the stand-level biomass model is popular. Based on the forestry inventory data of larch plantation (Larix olgensis) in Jilin Province, we used non-linear seemly unrelated regression (NSUR) to estimate the parameters in two additive system of stand-level biomass equations, i.e., stand-level biomass equations including the stand variables and stand biomass equations including the biomass expansion factor (i.e., Model system 1 and Model system 2), listed the constant biomass expansion factor for larch plantation and compared the prediction accuracy of three stand-level biomass estimation methods. The results indicated that for two additive system of biomass equations, the adjusted coefficient of determination (R a 2 ) of the total and stem equations was more than 0.95, the root mean squared error (RMSE), the mean prediction error (MPE) and the mean absolute error (MAE) were smaller. The branch and foliage biomass equations were worse than total and stem biomass equations, and the adjusted coefficient of determination (R a 2 ) was less than 0.95. The prediction accuracy of a constant biomass expansion factor was relatively lower than the prediction accuracy of Model system 1 and Model system 2. Overall, although stand-level biomass equation including the biomass expansion factor belonged to the volume-derived biomass estimation method, and was different from the stand biomass equations including stand variables in essence, but the obtained prediction accuracy of the two methods was similar. The constant biomass expansion factor had the lower prediction accuracy, and was inappropriate. In addition, in order to make the model parameter estimation more effective, the established stand-level biomass equations should consider the additivity in a system of all tree component biomass and total biomass equations.

The Mindful Attention Awareness Scale: Further Examination of Dimensionality, Reliability, and Concurrent Validity Estimates.

PubMed

Osman, Augustine; Lamis, Dorian A; Bagge, Courtney L; Freedenthal, Stacey; Barnes, Sean M

2016-01-01

We examined the factor structure and psychometric properties of the Mindful Attention Awareness Scale (MAAS) in a sample of 810 undergraduate students. Using common exploratory factor analysis (EFA), we obtained evidence for a 1-factor solution (41.84% common variance). To confirm unidimensionality of the 15-item MAAS, we conducted a 1-factor confirmatory factor analysis (CFA). Results of the EFA and CFA, respectively, provided support for a unidimensional model. Using differential item functioning analysis methods within item response theory modeling (IRT-based DIF), we found that individuals with high and low levels of nonattachment responded similarly to the MAAS items. Following a detailed item analysis, we proposed a 5-item short version of the instrument and present descriptive statistics and composite score reliability for the short and full versions of the MAAS. Finally, correlation analyses showed that scores on the full and short versions of the MAAS were associated with measures assessing related constructs. The 5-item MAAS is as useful as the original MAAS in enhancing our understanding of the mindfulness construct.

A self-calibration method in single-axis rotational inertial navigation system with rotating mechanism

NASA Astrophysics Data System (ADS)

Chen, Yuanpei; Wang, Lingcao; Li, Kui

2017-10-01

Rotary inertial navigation modulation mechanism can greatly improve the inertial navigation system (INS) accuracy through the rotation. Based on the single-axis rotational inertial navigation system (RINS), a self-calibration method is put forward. The whole system is applied with the rotation modulation technique so that whole inertial measurement unit (IMU) of system can rotate around the motor shaft without any external input. In the process of modulation, some important errors can be decoupled. Coupled with the initial position information and attitude information of the system as the reference, the velocity errors and attitude errors in the rotation are used as measurement to perform Kalman filtering to estimate part of important errors of the system after which the errors can be compensated into the system. The simulation results show that the method can complete the self-calibration of the single-axis RINS in 15 minutes and estimate gyro drifts of three-axis, the installation error angle of the IMU and the scale factor error of the gyro on z-axis. The calibration accuracy of optic gyro drifts could be about 0.003°/h (1σ) as well as the scale factor error could be about 1 parts per million (1σ). The errors estimate reaches the system requirements which can effectively improve the longtime navigation accuracy of the vehicle or the boat.

Effect of Display Technology on Perceived Scale of Space.

PubMed

Geuss, Michael N; Stefanucci, Jeanine K; Creem-Regehr, Sarah H; Thompson, William B; Mohler, Betty J

2015-11-01

Our goal was to evaluate the degree to which display technologies influence the perception of size in an image. Research suggests that factors such as whether an image is displayed stereoscopically, whether a user's viewpoint is tracked, and the field of view of a given display can affect users' perception of scale in the displayed image. Participants directly estimated the size of a gap by matching the distance between their hands to the gap width and judged their ability to pass unimpeded through the gap in one of five common implementations of three display technologies (two head-mounted displays [HMD] and a back-projection screen). Both measures of gap width were similar for the two HMD conditions and the back projection with stereo and tracking. For the displays without tracking, stereo and monocular conditions differed from each other, with monocular viewing showing underestimation of size. Display technologies that are capable of stereoscopic display and tracking of the user's viewpoint are beneficial as perceived size does not differ from real-world estimates. Evaluations of different display technologies are necessary as display conditions vary and the availability of different display technologies continues to grow. The findings are important to those using display technologies for research, commercial, and training purposes when it is important for the displayed image to be perceived at an intended scale. © 2015, Human Factors and Ergonomics Society.

Incorporation of prior information on parameters into nonlinear regression groundwater flow models: 2. Applications

USGS Publications Warehouse

Cooley, Richard L.

1983-01-01

This paper investigates factors influencing the degree of improvement in estimates of parameters of a nonlinear regression groundwater flow model by incorporating prior information of unknown reliability. Consideration of expected behavior of the regression solutions and results of a hypothetical modeling problem lead to several general conclusions. First, if the parameters are properly scaled, linearized expressions for the mean square error (MSE) in parameter estimates of a nonlinear model will often behave very nearly as if the model were linear. Second, by using prior information, the MSE in properly scaled parameters can be reduced greatly over the MSE of ordinary least squares estimates of parameters. Third, plots of estimated MSE and the estimated standard deviation of MSE versus an auxiliary parameter (the ridge parameter) specifying the degree of influence of the prior information on regression results can help determine the potential for improvement of parameter estimates. Fourth, proposed criteria can be used to make appropriate choices for the ridge parameter and another parameter expressing degree of overall bias in the prior information. Results of a case study of Truckee Meadows, Reno-Sparks area, Washoe County, Nevada, conform closely to the results of the hypothetical problem. In the Truckee Meadows case, incorporation of prior information did not greatly change the parameter estimates from those obtained by ordinary least squares. However, the analysis showed that both sets of estimates are more reliable than suggested by the standard errors from ordinary least squares.

Psychometric Properties of the Chinese Version of the Arabic Scale of Death Anxiety

PubMed Central

QIU, Qi; ZHANG, Shengyu; LIN, Xiang; BAN, Chunxia; YANG, Haibo; LIU, Zhengwen; WANG, Jingrong; WANG, Tao; XIAO, Shifu; ABDEL-KHALEK, Ahmed M; LI, Xia

2016-01-01

Background Death anxiety is regarded as a risk and maintaining factor of psychopathology. While the Arabic Scale of Death Anxiety (ASDA) is a brief, commonly used assessment, such a tool is lacking in Chinese clinical practice. Aim The current study was conducted to develop a Chinese version of the ASDA, i.e., the ASDA(C), using a multistage back-translation technique, and examine the psychometric properties of the scale. Methods A total of 1372 participants from hospitals and universities located in three geographic areas of China were recruited for this study. To calculate the criterion-related validity of the ASDA(C) compared to the Chinese version of the longer-form Multidimensional Orientation toward Dying and Death Inventory (MODDI-F/chin), 49 undergraduates were randomly assigned to complete both questionnaires. Of the total participants, 56 were randomly assigned to retake the ASDA(C) in order to estimate the one-week, test-retest reliability of the ASDA(C). Results The overall Cronbach’s alpha was 0.91 for the whole scale. The one-week, test-retest reliability was 0.96. Exploratory Factor Analysis (EFA) revealed three factors, “fear of dead people and tombs,” “fear of lethal disease,” and “fear of postmortem events,” accounted for 57.09% of the total variance. Factor structure for the three-factor model was sound. The correlation between the total scores on the ASDA(C) and the MODDI-F/chin was 0.54, indicating acceptable concurrent validity. Conclusions ASDA(C) has adequate psychometrics and properties that make it a reliable and valid scale to assess death anxiety in Mandarin-speaking Chinese. PMID:28638183

Evaluating Satellite-based Rainfall Estimates for Basin-scale Hydrologic Modeling

NASA Astrophysics Data System (ADS)

Yilmaz, K. K.; Hogue, T. S.; Hsu, K.; Gupta, H. V.; Mahani, S. E.; Sorooshian, S.

2003-12-01

The reliability of any hydrologic simulation and basin outflow prediction effort depends primarily on the rainfall estimates. The problem of estimating rainfall becomes more obvious in basins with scarce or no rain gauges. We present an evaluation of satellite-based rainfall estimates for basin-scale hydrologic modeling with particular interest in ungauged basins. The initial phase of this study focuses on comparison of mean areal rainfall estimates from ground-based rain gauge network, NEXRAD radar Stage-III, and satellite-based PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) and their influence on hydrologic model simulations over several basins in the U.S. Six-hourly accumulations of the above competing mean areal rainfall estimates are used as input to the Sacramento Soil Moisture Accounting Model. Preliminary experiments for the Leaf River Basin in Mississippi, for the period of March 2000 - June 2002, reveals that seasonality plays an important role in the comparison. There is an overestimation during the summer and underestimation during the winter in satellite-based rainfall with respect to the competing rainfall estimates. The consequence of this result on the hydrologic model is that simulated discharge underestimates the major observed peak discharges during early spring for the basin under study. Future research will entail developing correction procedures, which depend on different factors such as seasonality, geographic location and basin size, for satellite-based rainfall estimates over basins with dense rain gauge network and/or radar coverage. Extension of these correction procedures to satellite-based rainfall estimates over ungauged basins with similar characteristics has the potential for reducing the input uncertainty in ungauged basin modeling efforts.

Intervening on risk factors for coronary heart disease: an application of the parametric g-formula.

PubMed

Taubman, Sarah L; Robins, James M; Mittleman, Murray A; Hernán, Miguel A

2009-12-01

Estimating the population risk of disease under hypothetical interventions--such as the population risk of coronary heart disease (CHD) were everyone to quit smoking and start exercising or to start exercising if diagnosed with diabetes--may not be possible using standard analytic techniques. The parametric g-formula, which appropriately adjusts for time-varying confounders affected by prior exposures, is especially well suited to estimating effects when the intervention involves multiple factors (joint interventions) or when the intervention involves decisions that depend on the value of evolving time-dependent factors (dynamic interventions). We describe the parametric g-formula, and use it to estimate the effect of various hypothetical lifestyle interventions on the risk of CHD using data from the Nurses' Health Study. Over the period 1982-2002, the 20-year risk of CHD in this cohort was 3.50%. Under a joint intervention of no smoking, increased exercise, improved diet, moderate alcohol consumption and reduced body mass index, the estimated risk was 1.89% (95% confidence interval: 1.46-2.41). We discuss whether the assumptions required for the validity of the parametric g-formula hold in the Nurses' Health Study data. This work represents the first large-scale application of the parametric g-formula in an epidemiologic cohort study.

An ensemble survival model for estimating relative residual longevity following stroke: Application to mortality data in the chronic dialysis population

PubMed Central

Phadnis, Milind A; Wetmore, James B; Shireman, Theresa I; Ellerbeck, Edward F; Mahnken, Jonathan D

2016-01-01

Time-dependent covariates can be modeled within the Cox regression framework and can allow both proportional and nonproportional hazards for the risk factor of research interest. However, in many areas of health services research, interest centers on being able to estimate residual longevity after the occurrence of a particular event such as stroke. The survival trajectory of patients experiencing a stroke can be potentially influenced by stroke type (hemorrhagic or ischemic), time of the stroke (relative to time zero), time since the stroke occurred, or a combination of these factors. In such situations, researchers are more interested in estimating lifetime lost due to stroke rather than merely estimating the relative hazard due to stroke. To achieve this, we propose an ensemble approach using the generalized gamma distribution by means of a semi-Markov type model with an additive hazards extension. Our modeling framework allows stroke as a time-dependent covariate to affect all three parameters (location, scale, and shape) of the generalized gamma distribution. Using the concept of relative times, we answer the research question by estimating residual life lost due to ischemic and hemorrhagic stroke in the chronic dialysis population. PMID:26403934

An ensemble survival model for estimating relative residual longevity following stroke: Application to mortality data in the chronic dialysis population.

PubMed

Phadnis, Milind A; Wetmore, James B; Shireman, Theresa I; Ellerbeck, Edward F; Mahnken, Jonathan D

2017-12-01

Time-dependent covariates can be modeled within the Cox regression framework and can allow both proportional and nonproportional hazards for the risk factor of research interest. However, in many areas of health services research, interest centers on being able to estimate residual longevity after the occurrence of a particular event such as stroke. The survival trajectory of patients experiencing a stroke can be potentially influenced by stroke type (hemorrhagic or ischemic), time of the stroke (relative to time zero), time since the stroke occurred, or a combination of these factors. In such situations, researchers are more interested in estimating lifetime lost due to stroke rather than merely estimating the relative hazard due to stroke. To achieve this, we propose an ensemble approach using the generalized gamma distribution by means of a semi-Markov type model with an additive hazards extension. Our modeling framework allows stroke as a time-dependent covariate to affect all three parameters (location, scale, and shape) of the generalized gamma distribution. Using the concept of relative times, we answer the research question by estimating residual life lost due to ischemic and hemorrhagic stroke in the chronic dialysis population.

Clustering of quasars in a wide luminosity range at redshift 4 with Subaru Hyper Suprime-Cam Wide-field imaging

NASA Astrophysics Data System (ADS)

He, Wanqiu; Akiyama, Masayuki; Bosch, James; Enoki, Motohiro; Harikane, Yuichi; Ikeda, Hiroyuki; Kashikawa, Nobunari; Kawaguchi, Toshihiro; Komiyama, Yutaka; Lee, Chien-Hsiu; Matsuoka, Yoshiki; Miyazaki, Satoshi; Nagao, Tohru; Nagashima, Masahiro; Niida, Mana; Nishizawa, Atsushi J.; Oguri, Masamune; Onoue, Masafusa; Oogi, Taira; Ouchi, Masami; Schulze, Andreas; Shirasaki, Yuji; Silverman, John D.; Tanaka, Manobu M.; Tanaka, Masayuki; Toba, Yoshiki; Uchiyama, Hisakazu; Yamashita, Takuji

2018-01-01

We examine the clustering of quasars over a wide luminosity range, by utilizing 901 quasars at \\overline{z}_phot˜ 3.8 with -24.73 < M1450 < -22.23 photometrically selected from the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) S16A Wide2 date release and 342 more luminous quasars at 3.4 < zspec < 4.6 with -28.0 < M1450 < -23.95 from the Sloan Digital Sky Survey that fall in the HSC survey fields. We measure the bias factors of two quasar samples by evaluating the cross-correlation functions (CCFs) between the quasar samples and 25790 bright z ˜ 4 Lyman break galaxies in M1450 < -21.25 photometrically selected from the HSC dataset. Over an angular scale of 10.0" to 1000.0", the bias factors are 5.93+1.34-1.43 and 2.73+2.44-2.55 for the low- and high-luminosity quasars, respectively, indicating no significant luminosity dependence of quasar clustering at z ˜ 4. It is noted that the bias factor of the luminous quasars estimated by the CCF is smaller than that estimated by the auto-correlation function over a similar redshift range, especially on scales below 40.0". Moreover, the bias factor of the less-luminous quasars implies the minimal mass of their host dark matter halos is 0.3-2 × 1012 h-1 M⊙, corresponding to a quasar duty cycle of 0.001-0.06.

Spatial abundance models and seasonal distribution for guanaco (Lama guanicoe) in central Tierra del Fuego, Argentina.

PubMed

Flores, Celina E; Deferrari, Guillermo; Collado, Leonardo; Escobar, Julio; Schiavini, Adrián

2018-01-01

Spatially explicit modelling allows to estimate population abundance and predict species' distribution in relation to environmental factors. Abiotic factors are the main determinants of a herbivore´s response to environmental heterogeneity on large spatiotemporal scales. We assessed the influence of elevation, geographic location and distance to the coast on the seasonal abundance and distribution of guanaco (Lama guanicoe) in central Tierra del Fuego, by means of spatially explicit modelling. The estimated abundance was 23,690 individuals for the non-breeding season and 33,928 individuals for the breeding season. The factors influencing distribution and abundance revealed to be the elevation for the non-breeding season, and the distance to the coast and geographic location for the breeding season. The southwest of the study area presented seasonal abundance variation and the southeast and northeast presented high abundance during both seasons. The elevation would be the driving factor of guanaco distribution, as individuals move to lower areas during the non-breeding season and ascend to high areas during the breeding season. Our results confirm that part of the guanaco population performs seasonal migratory movements and that the main valleys present important wintering habitats for guanacos as well as up-hill zones during summer. This type of study would help to avoid problems of scale mismatch and achieve better results in management actions and is an example of how to assess important seasonal habitats from evaluations of abundance and distribution patterns.

Spatial abundance models and seasonal distribution for guanaco (Lama guanicoe) in central Tierra del Fuego, Argentina

PubMed Central

Deferrari, Guillermo; Collado, Leonardo; Escobar, Julio; Schiavini, Adrián

2018-01-01

Spatially explicit modelling allows to estimate population abundance and predict species’ distribution in relation to environmental factors. Abiotic factors are the main determinants of a herbivore´s response to environmental heterogeneity on large spatiotemporal scales. We assessed the influence of elevation, geographic location and distance to the coast on the seasonal abundance and distribution of guanaco (Lama guanicoe) in central Tierra del Fuego, by means of spatially explicit modelling. The estimated abundance was 23,690 individuals for the non-breeding season and 33,928 individuals for the breeding season. The factors influencing distribution and abundance revealed to be the elevation for the non-breeding season, and the distance to the coast and geographic location for the breeding season. The southwest of the study area presented seasonal abundance variation and the southeast and northeast presented high abundance during both seasons. The elevation would be the driving factor of guanaco distribution, as individuals move to lower areas during the non-breeding season and ascend to high areas during the breeding season. Our results confirm that part of the guanaco population performs seasonal migratory movements and that the main valleys present important wintering habitats for guanacos as well as up-hill zones during summer. This type of study would help to avoid problems of scale mismatch and achieve better results in management actions and is an example of how to assess important seasonal habitats from evaluations of abundance and distribution patterns. PMID:29782523

Estimating evapotranspiration in natural and constructed wetlands

USGS Publications Warehouse

Lott, R. Brandon; Hunt, Randall J.

2001-01-01

Difficulties in accurately calculating evapotranspiration (ET) in wetlands can lead to inaccurate water balances—information important for many compensatory mitigation projects. Simple meteorological methods or off-site ET data often are used to estimate ET, but these approaches do not include potentially important site-specific factors such as plant community, root-zone water levels, and soil properties. The objective of this study was to compare a commonly used meterological estimate of potential evapotranspiration (PET) with direct measurements of ET (lysimeters and water-table fluctuations) and small-scale root-zone geochemistry in a natural and constructed wetland system. Unlike what has been commonly noted, the results of the study demonstrated that the commonly used Penman combination method of estimating PET underestimated the ET that was measured directly in the natural wetland over most of the growing season. This result is likely due to surface heterogeneity and related roughness efffects not included in the simple PET estimate. The meterological method more closely approximated season-long measured ET rates in the constructed wetland but may overestimate the ET rate late in the growing season. ET rates also were temporally variable in wetlands over a range of time scales because they can be influenced by the relation of the water table to the root zone and the timing of plant senescence. Small-scale geochemical sampling of the shallow root zone was able to provide an independent evaluation of ET rates, supporting the identification of higher ET rates in the natural wetlands and differences in temporal ET rates due to the timing of senescence. These discrepancies illustrate potential problems with extrapolating off-site estimates of ET or single measurements of ET from a site over space or time.

Estimating discharge in rivers using remotely sensed hydraulic information

USGS Publications Warehouse

Bjerklie, D.M.; Moller, D.; Smith, L.C.; Dingman, S.L.

2005-01-01

A methodology to estimate in-bank river discharge exclusively from remotely sensed hydraulic data is developed. Water-surface width and maximum channel width measured from 26 aerial and digital orthophotos of 17 single channel rivers and 41 SAR images of three braided rivers were coupled with channel slope data obtained from topographic maps to estimate the discharge. The standard error of the discharge estimates were within a factor of 1.5-2 (50-100%) of the observed, with the mean estimate accuracy within 10%. This level of accuracy was achieved using calibration functions developed from observed discharge. The calibration functions use reach specific geomorphic variables, the maximum channel width and the channel slope, to predict a correction factor. The calibration functions are related to channel type. Surface velocity and width information, obtained from a single C-band image obtained by the Jet Propulsion Laboratory's (JPL's) AirSAR was also used to estimate discharge for a reach of the Missouri River. Without using a calibration function, the estimate accuracy was +72% of the observed discharge, which is within the expected range of uncertainty for the method. However, using the observed velocity to calibrate the initial estimate improved the estimate accuracy to within +10% of the observed. Remotely sensed discharge estimates with accuracies reported in this paper could be useful for regional or continental scale hydrologic studies, or in regions where ground-based data is lacking. ?? 2004 Elsevier B.V. All rights reserved.

Identifying polar bear resource selection patterns to inform offshore development in a dynamic and changing Arctic

USGS Publications Warehouse

Wilson, Ryan R.; Horne, Jon S.; Rode, Karyn D.; Regehr, Eric V.; Durner, George M.

2014-01-01

Although sea ice loss is the primary threat to polar bears (Ursus maritimus), little can be done to mitigate its effects without global efforts to reduce greenhouse gas emissions. Other factors, however, could exacerbate the impacts of sea ice loss on polar bears, such as exposure to increased industrial activity. The Arctic Ocean has enormous oil and gas potential, and its development is expected to increase in the coming decades. Estimates of polar bear resource selection will inform managers how bears use areas slated for oil development and to help guide conservation planning. We estimated temporally-varying resource selection patterns for non-denning adult female polar bears in the Chukchi Sea population (2008–2012) at two scales (i.e., home range and weekly steps) to identify factors predictive of polar bear use throughout the year, before any offshore development. From the best models at each scale, we estimated scale-integrated resource selection functions to predict polar bear space use across the population's range and determined when bears were most likely to use the region where offshore oil and gas development in the United States is slated to occur. Polar bears exhibited significant intra-annual variation in selection patterns at both scales but the strength and annual patterns of selection differed between scales for most variables. Bears were most likely to use the offshore oil and gas planning area during ice retreat and growth with the highest predicted use occurring in the southern portion of the planning area. The average proportion of predicted high-value habitat in the planning area was >15% of the total high-value habitat for the population during sea ice retreat and growth and reached a high of 50% during November 2010. Our results provide a baseline on which to judge future changes to non-denning adult female polar bear resource selection in the Chukchi Sea and help guide offshore development in the region. Lastly, our study provides a framework for assessing potential impacts of offshore oil and gas development to other polar bear populations around the Arctic.

Estimating Ω from Galaxy Redshifts: Linear Flow Distortions and Nonlinear Clustering

NASA Astrophysics Data System (ADS)

Bromley, B. C.; Warren, M. S.; Zurek, W. H.

1997-02-01

We propose a method to determine the cosmic mass density Ω from redshift-space distortions induced by large-scale flows in the presence of nonlinear clustering. Nonlinear structures in redshift space, such as fingers of God, can contaminate distortions from linear flows on scales as large as several times the small-scale pairwise velocity dispersion σv. Following Peacock & Dodds, we work in the Fourier domain and propose a model to describe the anisotropy in the redshift-space power spectrum; tests with high-resolution numerical data demonstrate that the model is robust for both mass and biased galaxy halos on translinear scales and above. On the basis of this model, we propose an estimator of the linear growth parameter β = Ω0.6/b, where b measures bias, derived from sampling functions that are tuned to eliminate distortions from nonlinear clustering. The measure is tested on the numerical data and found to recover the true value of β to within ~10%. An analysis of IRAS 1.2 Jy galaxies yields β=0.8+0.4-0.3 at a scale of 1000 km s-1, which is close to optimal given the shot noise and finite size of the survey. This measurement is consistent with dynamical estimates of β derived from both real-space and redshift-space information. The importance of the method presented here is that nonlinear clustering effects are removed to enable linear correlation anisotropy measurements on scales approaching the translinear regime. We discuss implications for analyses of forthcoming optical redshift surveys in which the dispersion is more than a factor of 2 greater than in the IRAS data.

[Factors for sexual abuse during childhood and adolescence in students of Morelos, Mexico].

PubMed

Chavez Ayala, Ruben; Rivera-Rivera, Leonor; Angeles-Llerenas, Angélica; Díaz-Cerón, Eva; Allen-Leigh, Betania; Ponce, Eduardo Lazcano

2009-06-01

To estimate the prevalence and factors associated with sexual abuse in childhood and adolescence. Study conducted in a sample of students in the state of Morelos, Mexico, in 2004-2005. Participants (n=1730) were drawn from a cohort of 13,293 students aged 12 to 24 years. Data were collected by means of a questionnaire comprising parts of validated scales. The variables studied were: sociodemographic (gender, living area, socioeconomic status), family (parental education, parental addictions, violence between parents), individual psychological factors (self-esteem assessed using the Coopersmith Self-Esteem Inventory, depression, alcohol consumption), intrafamily violence (assessed through Strauss Scale) and sexual abuse. Multiple logistic regression assessed the risk factors associated. Odds ratios (OR) with 95% confidence intervals were estimated. Of all students studied, 4.7% (n=80) reported attempted sexual abuse and 2.9% (n=50) were victims of consummated sexual abuse. Women had higher prevalence of attempted (6.1%) abuse; 3.6% of females and 1.9% of men were sexually abused. Main perpetrators were boyfriends in women and a stranger in men. Mean age was 12.02 years old among females and 11.71 years old among men. Factors found to be associated with abuse: high parental alcohol consumption (OR = 3.37, 95% CI 1.40;8.07), violence toward the mother (OR = 4.49, 95% CI 1.54;13.10), female gender (OR = 2.47, 95% CI 1.17;5.24), being a victim of great domestic violence (OR = 3.58, 95% CI 1.32;9.67). High self-esteem was a protective factor (OR = 0.27, 95% CI 0.09;0.75). Overall sexual abuse occurs at the age of 12 in both males and females, and it is more frequent among females. Most victims do not report abuse.

Remotely sensed MODIS wetland components for assessing the variability of methane emissions in Indian tropical/subtropical wetlands

NASA Astrophysics Data System (ADS)

Bansal, Sangeeta; Katyal, Deeksha; Saluja, Ridhi; Chakraborty, Monojit; Garg, J. K.

2018-02-01

Temperature and area fluctuations in wetlands greatly influence its various physico-chemical characteristics, nutrients dynamic, rates of biomass generation and decomposition, floral and faunal composition which in turn influence methane (CH4) emission rates. In view of this, the present study attempts to up-scale point CH4 flux from the wetlands of Uttar Pradesh (UP) by modifying two-factor empirical process based CH4 emission model for tropical wetlands by incorporating MODIS derived wetland components viz. wetland areal extent and corresponding temperature factors (Ft). This study further focuses on the utility of remotely sensed temperature response of CH4 emission in terms of Ft. Ft is generated using MODIS land surface temperature products and provides an important semi-empirical input for up-scaling CH4 emissions in wetlands. Results reveal that annual mean Ft values for UP wetlands vary from 0.69 (2010-2011) to 0.71(2011-2012). The total estimated area-wise CH4 emissions from the wetlands of UP varies from 66.47 Gg yr-1with wetland areal extent and Ft value of 2564.04 km2 and 0.69 respectively in 2010-2011 to 88.39 Gg yr-1with wetland areal extent and Ft value of 2720.16 km2 and 0.71 respectively in 2011-2012. Temporal analysis of estimated CH4 emissions showed that in monsoon season estimated CH4 emissions are more sensitive to wetland areal extent while in summer season sensitivity of estimated CH4 emissions is chiefly controlled by augmented methanogenic activities at high wetland surface temperatures.

Assimilation of Gridded GRACE Terrestrial Water Storage Estimates in the North American Land Data Assimilation System

NASA Technical Reports Server (NTRS)

Kumar, Sujay V.; Zaitchik, Benjamin F.; Peters-Lidard, Christa D.; Rodell, Matthew; Reichle, Rolf; Li, Bailing; Jasinski, Michael; Mocko, David; Getirana, Augusto; De Lannoy, Gabrielle;

Quadratic Frequency Modulation Signals Parameter Estimation Based on Two-Dimensional Product Modified Parameterized Chirp Rate-Quadratic Chirp Rate Distribution.

PubMed

Qu, Zhiyu; Qu, Fuxin; Hou, Changbo; Jing, Fulong

2018-05-19

In an inverse synthetic aperture radar (ISAR) imaging system for targets with complex motion, the azimuth echo signals of the target are always modeled as multicomponent quadratic frequency modulation (QFM) signals. The chirp rate (CR) and quadratic chirp rate (QCR) estimation of QFM signals is very important to solve the ISAR image defocus problem. For multicomponent QFM (multi-QFM) signals, the conventional QR and QCR estimation algorithms suffer from the cross-term and poor anti-noise ability. This paper proposes a novel estimation algorithm called a two-dimensional product modified parameterized chirp rate-quadratic chirp rate distribution (2D-PMPCRD) for QFM signals parameter estimation. The 2D-PMPCRD employs a multi-scale parametric symmetric self-correlation function and modified nonuniform fast Fourier transform-Fast Fourier transform to transform the signals into the chirp rate-quadratic chirp rate (CR-QCR) domains. It can greatly suppress the cross-terms while strengthening the auto-terms by multiplying different CR-QCR domains with different scale factors. Compared with high order ambiguity function-integrated cubic phase function and modified Lv's distribution, the simulation results verify that the 2D-PMPCRD acquires higher anti-noise performance and obtains better cross-terms suppression performance for multi-QFM signals with reasonable computation cost.

Methods for Analysis of Urban Energy Systems: A New York City Case Study

NASA Astrophysics Data System (ADS)

Howard, Bianca

This dissertation describes methods developed for analysis of the New York City energy system. The analysis specifically aims to consider the built environment and its' impacts on greenhouse gas (GHG) emissions. Several contributions to the urban energy systems literature were made. First, estimates of annual energy intensities of the New York building stock were derived using a statistical analysis that leveraged energy consumption and tax assessor data collected by the Office of the Mayor. These estimates provided the basis for an assessment of the spatial distribution of building energy consumption. The energy consumption estimates were then leveraged to estimate the potential for combined heat and power (CHP) systems in New York City at both the building and microgrid scales. In aggregate, given the 2009 non-baseload GHG emissions factors for electricity production, these systems could reduce citywide GHG emissions by 10%. The operational characteristics of CHP systems were explored further considering different prime movers, climates, and GHG emissions factors. A combination of mixed integer linear programing and controlled random search algorithms were the methods used to determine the optimal capacity and operating strategies for the CHP systems under the various scenarios. Lastly a multi-regional unit commitment model of electricity and GHG emissions production for New York State was developed using data collected from several publicly available sources. The model was used to estimate average and marginal GHG emissions factors for New York State and New York City. The analysis found that marginal GHG emissions factors could reduce by 30% to 370 g CO2e/kWh in the next 10 years.

Identification of dominant interactions between climatic seasonality, catchment characteristics and agricultural activities on Budyko-type equation parameter estimation

NASA Astrophysics Data System (ADS)

Xing, Wanqiu; Wang, Weiguang; Shao, Quanxi; Yong, Bin

2018-01-01

Quantifying precipitation (P) partition into evapotranspiration (E) and runoff (Q) is of great importance for global and regional water availability assessment. Budyko framework serves as a powerful tool to make simple and transparent estimation for the partition, using a single parameter, to characterize the shape of the Budyko curve for a "specific basin", where the single parameter reflects the overall effect by not only climatic seasonality, catchment characteristics (e.g., soil, topography and vegetation) but also agricultural activities (e.g., cultivation and irrigation). At the regional scale, these influencing factors are interconnected, and the interactions between them can also affect the single parameter of Budyko-type equations' estimating. Here we employ the multivariate adaptive regression splines (MARS) model to estimate the Budyko curve shape parameter (n in the Choudhury's equation, one form of the Budyko framework) of the selected 96 catchments across China using a data set of long-term averages for climatic seasonality, catchment characteristics and agricultural activities. Results show average storm depth (ASD), vegetation coverage (M), and seasonality index of precipitation (SI) are three statistically significant factors affecting the Budyko parameter. More importantly, four pairs of interactions are recognized by the MARS model as: The interaction between CA (percentage of cultivated land area to total catchment area) and ASD shows that the cultivation can weaken the reducing effect of high ASD (>46.78 mm) on the Budyko parameter estimating. Drought (represented by the value of Palmer drought severity index < -0.74) and uneven distribution of annual rainfall (represented by the value of coefficient of variation of precipitation > 0.23) tend to enhance the Budyko parameter reduction by large SI (>0.797). Low vegetation coverage (34.56%) is likely to intensify the rising effect on evapotranspiration ratio by IA (percentage of irrigation area to total catchment area). The Budyko n values estimated by the MARS model reproduce the calculated ones by the observation well for the selected 96 catchments (with R = 0.817, MAE = 4.09). Compared to the multiple stepwise regression model estimating the parameter n taken the influencing factors as independent inputs, the MARS model enhances the capability of the Budyko framework for assessing water availability at regional scale using readily available data.

Using global sensitivity analysis to understand higher order interactions in complex models: an application of GSA on the Revised Universal Soil Loss Equation (RUSLE) to quantify model sensitivity and implications for ecosystem services management in Costa Rica

NASA Astrophysics Data System (ADS)

Fremier, A. K.; Estrada Carmona, N.; Harper, E.; DeClerck, F.

2011-12-01

Appropriate application of complex models to estimate system behavior requires understanding the influence of model structure and parameter estimates on model output. To date, most researchers perform local sensitivity analyses, rather than global, because of computational time and quantity of data produced. Local sensitivity analyses are limited in quantifying the higher order interactions among parameters, which could lead to incomplete analysis of model behavior. To address this concern, we performed a GSA on a commonly applied equation for soil loss - the Revised Universal Soil Loss Equation. USLE is an empirical model built on plot-scale data from the USA and the Revised version (RUSLE) includes improved equations for wider conditions, with 25 parameters grouped into six factors to estimate long-term plot and watershed scale soil loss. Despite RUSLE's widespread application, a complete sensitivity analysis has yet to be performed. In this research, we applied a GSA to plot and watershed scale data from the US and Costa Rica to parameterize the RUSLE in an effort to understand the relative importance of model factors and parameters across wide environmental space. We analyzed the GSA results using Random Forest, a statistical approach to evaluate parameter importance accounting for the higher order interactions, and used Classification and Regression Trees to show the dominant trends in complex interactions. In all GSA calculations the management of cover crops (C factor) ranks the highest among factors (compared to rain-runoff erosivity, topography, support practices, and soil erodibility). This is counter to previous sensitivity analyses where the topographic factor was determined to be the most important. The GSA finding is consistent across multiple model runs, including data from the US, Costa Rica, and a synthetic dataset of the widest theoretical space. The three most important parameters were: Mass density of live and dead roots found in the upper inch of soil (C factor), slope angle (L and S factor), and percentage of land area covered by surface cover (C factor). Our findings give further support to the importance of vegetation as a vital ecosystem service provider - soil loss reduction. Concurrent, progress is already been made in Costa Rica, where dam managers are moving forward on a Payment for Ecosystem Services scheme to help keep private lands forested and to improve crop management through targeted investments. Use of complex watershed models, such as RUSLE can help managers quantify the effect of specific land use changes. Moreover, effective land management of vegetation has other important benefits, such as bundled ecosystem services (e.g. pollination, habitat connectivity, etc) and improvements of communities' livelihoods.

Biotic and abiotic factors predicting the global distribution and population density of an invasive large mammal

PubMed Central

Lewis, Jesse S.; Farnsworth, Matthew L.; Burdett, Chris L.; Theobald, David M.; Gray, Miranda; Miller, Ryan S.

2017-01-01

Biotic and abiotic factors are increasingly acknowledged to synergistically shape broad-scale species distributions. However, the relative importance of biotic and abiotic factors in predicting species distributions is unclear. In particular, biotic factors, such as predation and vegetation, including those resulting from anthropogenic land-use change, are underrepresented in species distribution modeling, but could improve model predictions. Using generalized linear models and model selection techniques, we used 129 estimates of population density of wild pigs (Sus scrofa) from 5 continents to evaluate the relative importance, magnitude, and direction of biotic and abiotic factors in predicting population density of an invasive large mammal with a global distribution. Incorporating diverse biotic factors, including agriculture, vegetation cover, and large carnivore richness, into species distribution modeling substantially improved model fit and predictions. Abiotic factors, including precipitation and potential evapotranspiration, were also important predictors. The predictive map of population density revealed wide-ranging potential for an invasive large mammal to expand its distribution globally. This information can be used to proactively create conservation/management plans to control future invasions. Our study demonstrates that the ongoing paradigm shift, which recognizes that both biotic and abiotic factors shape species distributions across broad scales, can be advanced by incorporating diverse biotic factors. PMID:28276519

Constrained map-based inventory estimation

Treesearch

Paul C. Van Deusen; Francis A. Roesch

2007-01-01

A region can conceptually be tessellated into polygons at different scales or resolutions. Likewise, samples can be taken from the region to determine the value of a polygon variable for each scale. Sampled polygons can be used to estimate values for other polygons at the same scale. However, estimates should be compatible across the different scales. Estimates are...

Temporal variations of potential fecundity of southern blue whiting (Micromesistius australis australis) in the Southeast Pacific

NASA Astrophysics Data System (ADS)

Flores, Andrés; Wiff, Rodrigo; Díaz, Eduardo; Carvajal, Bernardita

2017-08-01

Fecundity is a key aspect of fish species reproductive biology because it relates directly to total egg production. Yet, despite such importance, fecundity estimates are lacking or scarce for several fish species. The gravimetric method is the most-used one to estimate fecundity by essentially scaling up the oocyte density to the ovary weight. It is a relatively simple and precise technique, but also time consuming because it requires counting all oocytes in an ovary subsample. The auto-diametric method, on the other hand, is relatively new for estimating fecundity, representing a rapid alternative, because it requires only an estimation of mean oocyte density from mean oocyte diameter. Using the extensive database available from commercial fishery and design surveys for southern blue whiting Micromesistius australis australis in the Southeast Pacific, we compared estimates of fecundity using both gravimetric and auto-diametric methods. Temporal variations in potential fecundity from the auto-diametric method were evaluated using generalised linear models considering predictors from maternal characteristics such as female size, condition factor, oocyte size, and gonadosomatic index. A global and time-invariant auto-diametric equation was evaluated using a simulation procedure based on non-parametric bootstrap. Results indicated there were not significant differences regarding fecundity estimates between the gravimetric and auto-diametric method (p > 0.05). Simulation showed the application of a global equation is unbiased and sufficiently precise to estimate time-invariant fecundity of this species. Temporal variations on fecundity were explained by maternal characteristic, revealing signals of fecundity down-regulation. We discuss how oocyte size and nutritional condition (measured as condition factor) are one of the important factors determining fecundity. We highlighted also the relevance of choosing the appropriate sampling period to conduct maturity studies and ensure precise estimates of fecundity of this species.

Premature mortality in India due to PM2.5 and ozone exposure

NASA Astrophysics Data System (ADS)

Ghude, Sachin D.; Chate, D. M.; Jena, C.; Beig, G.; Kumar, R.; Barth, M. C.; Pfister, G. G.; Fadnavis, S.; Pithani, Prakash

2016-05-01

This bottom-up modeling study, supported by new population census 2011 data, simulates ozone (O3) and fine particulate matter (PM2.5) exposure on local to regional scales. It quantifies, present-day premature mortalities associated with the exposure to near-surface PM2.5 and O3 concentrations in India using a regional chemistry model. We estimate that PM2.5 exposure leads to about 570,000 (CI95: 320,000-730,000) premature mortalities in 2011. On a national scale, our estimate of mortality by chronic obstructive pulmonary disease (COPD) due to O3 exposure is about 12,000 people. The Indo-Gangetic region accounts for a large part (~42%) of the estimated mortalities. The associated lost life expectancy is calculated as 3.4 ± 1.1 years for all of India with highest values found for Delhi (6.3 ± 2.2 years). The economic cost of estimated premature mortalities associated with PM2.5 and O3 exposure is about 640 (350-800) billion USD in 2011, which is a factor of 10 higher than total expenditure on health by public and private expenditure.

Measures of large-scale structure in the CfA redshift survey slices

NASA Technical Reports Server (NTRS)

De Lapparent, Valerie; Geller, Margaret J.; Huchra, John P.

1991-01-01

Variations of the counts-in-cells with cell size are used here to define two statistical measures of large-scale clustering in three 6 deg slices of the CfA redshift survey. A percolation criterion is used to estimate the filling factor which measures the fraction of the total volume in the survey occupied by the large-scale structures. For the full 18 deg slice of the CfA redshift survey, f is about 0.25 + or - 0.05. After removing groups with more than five members from two of the slices, variations of the counts in occupied cells with cell size have a power-law behavior with a slope beta about 2.2 on scales from 1-10/h Mpc. Application of both this statistic and the percolation analysis to simulations suggests that a network of two-dimensional structures is a better description of the geometry of the clustering in the CfA slices than a network of one-dimensional structures. Counts-in-cells are also used to estimate at 0.3 galaxy h-squared/Mpc the average galaxy surface density in sheets like the Great Wall.

[Factor Analysis: Principles to Evaluate Measurement Tools for Mental Health].

PubMed

Campo-Arias, Adalberto; Herazo, Edwin; Oviedo, Heidi Celina

2012-09-01

The validation of a measurement tool in mental health is a complex process that usually starts by estimating reliability, to later approach its validity. Factor analysis is a way to know the number of dimensions, domains or factors of a measuring tool, generally related to the construct validity of the scale. The analysis could be exploratory or confirmatory, and helps in the selection of the items with better performance. For an acceptable factor analysis, it is necessary to follow some steps and recommendations, conduct some statistical tests, and rely on a proper sample of participants. Copyright © 2012 Asociación Colombiana de Psiquiatría. Publicado por Elsevier España. All rights reserved.

HIV Treatment as Prevention: Modelling the Cost of Antiretroviral Treatment—State of the Art and Future Directions

PubMed Central

Meyer-Rath, Gesine; Over, Mead

2012-01-01

Policy discussions about the feasibility of massively scaling up antiretroviral therapy (ART) to reduce HIV transmission and incidence hinge on accurately projecting the cost of such scale-up in comparison to the benefits from reduced HIV incidence and mortality. We review the available literature on modelled estimates of the cost of providing ART to different populations around the world, and suggest alternative methods of characterising cost when modelling several decades into the future. In past economic analyses of ART provision, costs were often assumed to vary by disease stage and treatment regimen, but for treatment as prevention, in particular, most analyses assume a uniform cost per patient. This approach disregards variables that can affect unit cost, such as differences in factor prices (i.e., the prices of supplies and services) and the scale and scope of operations (i.e., the sizes and types of facilities providing ART). We discuss several of these variables, and then present a worked example of a flexible cost function used to determine the effect of scale on the cost of a proposed scale-up of treatment as prevention in South Africa. Adjusting previously estimated costs of universal testing and treatment in South Africa for diseconomies of small scale, i.e., more patients being treated in smaller facilities, adds 42% to the expected future cost of the intervention. PMID:22802731

More efficient parameter estimates for factor analysis of ordinal variables by ridge generalized least squares.

PubMed

Yuan, Ke-Hai; Jiang, Ge; Cheng, Ying

2017-11-01

Data in psychology are often collected using Likert-type scales, and it has been shown that factor analysis of Likert-type data is better performed on the polychoric correlation matrix than on the product-moment covariance matrix, especially when the distributions of the observed variables are skewed. In theory, factor analysis of the polychoric correlation matrix is best conducted using generalized least squares with an asymptotically correct weight matrix (AGLS). However, simulation studies showed that both least squares (LS) and diagonally weighted least squares (DWLS) perform better than AGLS, and thus LS or DWLS is routinely used in practice. In either LS or DWLS, the associations among the polychoric correlation coefficients are completely ignored. To mend such a gap between statistical theory and empirical work, this paper proposes new methods, called ridge GLS, for factor analysis of ordinal data. Monte Carlo results show that, for a wide range of sample sizes, ridge GLS methods yield uniformly more accurate parameter estimates than existing methods (LS, DWLS, AGLS). A real-data example indicates that estimates by ridge GLS are 9-20% more efficient than those by existing methods. Rescaled and adjusted test statistics as well as sandwich-type standard errors following the ridge GLS methods also perform reasonably well. © 2017 The British Psychological Society.

Comparison of local- to regional-scale estimates of ground-water recharge in Minnesota, USA

USGS Publications Warehouse

Delin, G.N.; Healy, R.W.; Lorenz, D.L.; Nimmo, J.R.

2007-01-01

Regional ground-water recharge estimates for Minnesota were compared to estimates made on the basis of four local- and basin-scale methods. Three local-scale methods (unsaturated-zone water balance, water-table fluctuations (WTF) using three approaches, and age dating of ground water) yielded point estimates of recharge that represent spatial scales from about 1 to about 1000 m2. A fourth method (RORA, a basin-scale analysis of streamflow records using a recession-curve-displacement technique) yielded recharge estimates at a scale of 10–1000s of km2. The RORA basin-scale recharge estimates were regionalized to estimate recharge for the entire State of Minnesota on the basis of a regional regression recharge (RRR) model that also incorporated soil and climate data. Recharge rates estimated by the RRR model compared favorably to the local and basin-scale recharge estimates. RRR estimates at study locations were about 41% less on average than the unsaturated-zone water-balance estimates, ranged from 44% greater to 12% less than estimates that were based on the three WTF approaches, were about 4% less than the age dating of ground-water estimates, and were about 5% greater than the RORA estimates. Of the methods used in this study, the WTF method is the simplest and easiest to apply. Recharge estimates made on the basis of the UZWB method were inconsistent with the results from the other methods. Recharge estimates using the RRR model could be a good source of input for regional ground-water flow models; RRR model results currently are being applied for this purpose in USGS studies elsewhere.

A validation study of the psychometric properties of the Groningen Reflection Ability Scale.

PubMed

Andersen, Nina Bjerre; O'Neill, Lotte; Gormsen, Lise Kirstine; Hvidberg, Line; Morcke, Anne Mette

2014-10-10

Reflection, the ability to examine critically one's own learning and functioning, is considered important for 'the good doctor'. The Groningen Reflection Ability Scale (GRAS) is an instrument measuring student reflection, which has not yet been validated beyond the original Dutch study. The aim of this study was to adapt GRAS for use in a Danish setting and to investigate the psychometric properties of GRAS-DK. We performed a cross-cultural adaptation of GRAS from Dutch to Danish. Next, we collected primary data online, performed a retest, analysed data descriptively, estimated measurement error, performed an exploratory and a confirmatory factor analysis to test the proposed three-factor structure. 361 (69%) of 523 invited students completed GRAS-DK. Their mean score was 88 (SD = 11.42; scale maximum 115). Scores were approximately normally distributed. Measurement error and test-retest score differences were acceptable, apart from a few extreme outliers. However, the confirmatory factor analysis did not replicate the original three-factor model and neither could a one-dimensional structure be confirmed. GRAS is already in use, however we advise that use of GRAS-DK for effect measurements and group comparison awaits further review and validation studies. Our negative finding might be explained by a weak conceptualisation of personal reflection.

Modeling spatial patterns of soil respiration in maize fields from vegetation and soil property factors with the use of remote sensing and geographical information system.

PubMed

Huang, Ni; Wang, Li; Guo, Yiqiang; Hao, Pengyu; Niu, Zheng

2014-01-01

To examine the method for estimating the spatial patterns of soil respiration (Rs) in agricultural ecosystems using remote sensing and geographical information system (GIS), Rs rates were measured at 53 sites during the peak growing season of maize in three counties in North China. Through Pearson's correlation analysis, leaf area index (LAI), canopy chlorophyll content, aboveground biomass, soil organic carbon (SOC) content, and soil total nitrogen content were selected as the factors that affected spatial variability in Rs during the peak growing season of maize. The use of a structural equation modeling approach revealed that only LAI and SOC content directly affected Rs. Meanwhile, other factors indirectly affected Rs through LAI and SOC content. When three greenness vegetation indices were extracted from an optical image of an environmental and disaster mitigation satellite in China, enhanced vegetation index (EVI) showed the best correlation with LAI and was thus used as a proxy for LAI to estimate Rs at the regional scale. The spatial distribution of SOC content was obtained by extrapolating the SOC content at the plot scale based on the kriging interpolation method in GIS. When data were pooled for 38 plots, a first-order exponential analysis indicated that approximately 73% of the spatial variability in Rs during the peak growing season of maize can be explained by EVI and SOC content. Further test analysis based on independent data from 15 plots showed that the simple exponential model had acceptable accuracy in estimating the spatial patterns of Rs in maize fields on the basis of remotely sensed EVI and GIS-interpolated SOC content, with R2 of 0.69 and root-mean-square error of 0.51 µmol CO2 m(-2) s(-1). The conclusions from this study provide valuable information for estimates of Rs during the peak growing season of maize in three counties in North China.

Modeling Spatial Patterns of Soil Respiration in Maize Fields from Vegetation and Soil Property Factors with the Use of Remote Sensing and Geographical Information System

PubMed Central

Huang, Ni; Wang, Li; Guo, Yiqiang; Hao, Pengyu; Niu, Zheng

2014-01-01

To examine the method for estimating the spatial patterns of soil respiration (Rs) in agricultural ecosystems using remote sensing and geographical information system (GIS), Rs rates were measured at 53 sites during the peak growing season of maize in three counties in North China. Through Pearson's correlation analysis, leaf area index (LAI), canopy chlorophyll content, aboveground biomass, soil organic carbon (SOC) content, and soil total nitrogen content were selected as the factors that affected spatial variability in Rs during the peak growing season of maize. The use of a structural equation modeling approach revealed that only LAI and SOC content directly affected Rs. Meanwhile, other factors indirectly affected Rs through LAI and SOC content. When three greenness vegetation indices were extracted from an optical image of an environmental and disaster mitigation satellite in China, enhanced vegetation index (EVI) showed the best correlation with LAI and was thus used as a proxy for LAI to estimate Rs at the regional scale. The spatial distribution of SOC content was obtained by extrapolating the SOC content at the plot scale based on the kriging interpolation method in GIS. When data were pooled for 38 plots, a first-order exponential analysis indicated that approximately 73% of the spatial variability in Rs during the peak growing season of maize can be explained by EVI and SOC content. Further test analysis based on independent data from 15 plots showed that the simple exponential model had acceptable accuracy in estimating the spatial patterns of Rs in maize fields on the basis of remotely sensed EVI and GIS-interpolated SOC content, with R2 of 0.69 and root-mean-square error of 0.51 µmol CO2 m−2 s−1. The conclusions from this study provide valuable information for estimates of Rs during the peak growing season of maize in three counties in North China. PMID:25157827

Modeling the Psychometric Properties of Complex Performance Assessment Tasks Using Confirmatory Factor Analysis: A Multistage Model for Calibrating Tasks

ERIC Educational Resources Information Center

Kahraman, Nilufer; De Champlain, Andre; Raymond, Mark

2012-01-01

Item-level information, such as difficulty and discrimination are invaluable to the test assembly, equating, and scoring practices. Estimating these parameters within the context of large-scale performance assessments is often hindered by the use of unbalanced designs for assigning examinees to tasks and raters because such designs result in very…

Prescribed fire, elk, and aspen in Grand Teton National Park

Treesearch

Ron Steffens; Diane Abendroth

2001-01-01

In Grand Teton National Park, a landscape-scale assessment of regeneration in aspen has assisted park managers in identifying aspen stands that may be at risk due to a number of interrelated factors, including ungulate browsing and suppression of wildland fire. The initial aspen survey sampled an estimated 20 percent of the park's aspen stands. Assessment of these...

Particle swarm optimization algorithm based low cost magnetometer calibration

NASA Astrophysics Data System (ADS)

Ali, A. S.; Siddharth, S., Syed, Z., El-Sheimy, N.

2011-12-01

Inertial Navigation Systems (INS) consist of accelerometers, gyroscopes and a microprocessor provide inertial digital data from which position and orientation is obtained by integrating the specific forces and rotation rates. In addition to the accelerometers and gyroscopes, magnetometers can be used to derive the absolute user heading based on Earth's magnetic field. Unfortunately, the measurements of the magnetic field obtained with low cost sensors are corrupted by several errors including manufacturing defects and external electro-magnetic fields. Consequently, proper calibration of the magnetometer is required to achieve high accuracy heading measurements. In this paper, a Particle Swarm Optimization (PSO) based calibration algorithm is presented to estimate the values of the bias and scale factor of low cost magnetometer. The main advantage of this technique is the use of the artificial intelligence which does not need any error modeling or awareness of the nonlinearity. The estimated bias and scale factor errors from the proposed algorithm improve the heading accuracy and the results are also statistically significant. Also, it can help in the development of the Pedestrian Navigation Devices (PNDs) when combined with the INS and GPS/Wi-Fi especially in the indoor environments

Demoralization Scale in Spanish-Speaking Palliative Care Patients.

PubMed

Rudilla, David; Galiana, Laura; Oliver, Amparo; Barreto, Pilar

2016-04-01

Among the approaches to the demoralization syndrome, the one proposed by Kissane et al. is prevalent in the literature. These authors developed the Demoralization Scale (DS) to assess emotional distress, conceived as demoralization. To present the Spanish adaptation of the Demoralization Scale in palliative care patients, with a new and more comprehensive approach to its factorial structure. A cross-sectional study was carried out in 226 Spanish palliative care patients in three different settings: hospital, home care unit, and continued care unit. Outcome measures included the DS and the Hospital Anxiety and Depression Scale. Analyses comprised confirmatory factor analyses to test the original, German, and Irish structure of the DS, exploratory structural equation modeling (ESEM), estimations of internal consistency, and multivariate analyses of variance for criterion-related validity. The confirmatory factor analyses showed inappropriate fit for the previous structures when studied in the Spanish version of the DS. With ESEM, the best fitting structure was the five-factor solution, without item 18. Reliability results offered good estimations of internal consistency for all the dimensions except for sense of failure. Cronbach alpha coefficients were appropriate for the dimensions of loss of meaning (0.86), helplessness (0.79), disheartenment (0.88), and dysphoria (0.80), but low reliability was found for sense of failure (0.62). Convergent and discriminant validity showed positive correlations between demoralization, anxiety, and depression. Patients with higher levels of anxiety had higher scores on every dimension of demoralization, and those with higher levels of depression had higher scores on loss of meaning, disheartenment, and sense of failure, but not on dysphoria or helplessness. The Spanish adaptation of the DS has shown appropriate psychometric properties. It has been useful to differentiate between depression and the demoralization syndrome, pointing to helplessness and dysphoria as unique characteristics of demoralized palliative care patients. Copyright © 2016. Published by Elsevier Inc.

Dynamic analysis of pan evaporation variations in the Huai River Basin, a climate transition zone in eastern China.

PubMed

Li, Meng; Chu, Ronghao; Shen, Shuanghe; Islam, Abu Reza Md Towfiqul

2018-06-01

Pan evaporation (E pan ), which we examine in this study to better understand atmospheric evaporation demand, represents a pivotal indicator of the terrestrial ecosystem and hydrological cycle, particularly in the Huai River Basin (HRB) in eastern China, where high potential risks of drought and flooding are commonly observed. In this study, we examine the spatiotemporal trend patterns of climatic factors and E pan by using the Mann-Kendall test and the Theil-Sen estimator based on a daily meteorological dataset from 89 weather stations during 1965-2013 in the HRB. Furthermore, the PenPan model is employed to estimate E pan at a monthly time scale, and a differential equation method is applied to quantify contributions from four meteorological variables to E pan trends. The results show that E pan significantly decreased (P<0.001) at an average rate of -8.119mm·a -2 at annual time scale in the whole HRB, with approximately 90% of stations occupied. Meanwhile, the generally higher E pan values were detected in the northern HRB. The values of the aerodynamic components in the PenPan model were much greater than those of the radiative components, which were responsible for the variations in the E pan trend. The significantly decreasing wind speed (u 2 ) was the most dominant factor that controlled the decreasing E pan trend at each time scale, followed by the notable decreasing net radiation (R n ) at the annual time scale also in growing season and summer. However, the second dominant factor shifted to the mean temperature (T a ) during the spring and winter and the vapor pressure deficit (vpd) during the autumn. These phenomena demonstrated a positive link between the significance of climate variables and their control over the E pan trend. Copyright © 2017 Elsevier B.V. All rights reserved.

Image-derived input function with factor analysis and a-priori information.

PubMed

Simončič, Urban; Zanotti-Fregonara, Paolo

2015-02-01

Quantitative PET studies often require the cumbersome and invasive procedure of arterial cannulation to measure the input function. This study sought to minimize the number of necessary blood samples by developing a factor-analysis-based image-derived input function (IDIF) methodology for dynamic PET brain studies. IDIF estimation was performed as follows: (a) carotid and background regions were segmented manually on an early PET time frame; (b) blood-weighted and tissue-weighted time-activity curves (TACs) were extracted with factor analysis; (c) factor analysis results were denoised and scaled using the voxels with the highest blood signal; (d) using population data and one blood sample at 40 min, whole-blood TAC was estimated from postprocessed factor analysis results; and (e) the parent concentration was finally estimated by correcting the whole-blood curve with measured radiometabolite concentrations. The methodology was tested using data from 10 healthy individuals imaged with [(11)C](R)-rolipram. The accuracy of IDIFs was assessed against full arterial sampling by comparing the area under the curve of the input functions and by calculating the total distribution volume (VT). The shape of the image-derived whole-blood TAC matched the reference arterial curves well, and the whole-blood area under the curves were accurately estimated (mean error 1.0±4.3%). The relative Logan-V(T) error was -4.1±6.4%. Compartmental modeling and spectral analysis gave less accurate V(T) results compared with Logan. A factor-analysis-based IDIF for [(11)C](R)-rolipram brain PET studies that relies on a single blood sample and population data can be used for accurate quantification of Logan-V(T) values.

Axial-vector form factors of the nucleon from lattice QCD

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

Gupta, Rajan; Jang, Yong-Chull; Lin, Huey-Wen

In this paper, we present results for the form factors of the isovector axial vector current in the nucleon state using large scale simulations of lattice QCD. The calculations were done using eight ensembles of gauge configurations generated by the MILC collaboration using the HISQ action with 2 + 1 + 1 dynamical flavors. These ensembles span three lattice spacings a ≈ 0.06 , 0.09, and 0.12 fm and light-quark masses corresponding to the pion masses M π ≈ 135, 225, and 310 MeV. High-statistics estimates allow us to quantify systematic uncertainties in the extraction of G A (Q 2)more » and the induced pseudoscalar form factor G P(Q 2) . We perform a simultaneous extrapolation in the lattice spacing, lattice volume and light-quark masses of the axial charge radius r A data to obtain physical estimates. Using the dipole ansatz to fit the Q 2 behavior we obtain r A | dipole = 0.49(3) fm , which corresponds to M A = 1.39(9) GeV , and is consistent with M A = 1.35(17) GeV obtained by the miniBooNE collaboration. The estimate obtained using the z -expansion is r A | z - expansion = 0.46(6) fm, and the combined result is r A | combined = 0.48(4) fm. Analysis of the induced pseudoscalar form factor G P (Q 2) yields low estimates for g* P and g πNN compared to their phenomenological values. To understand these, we analyze the partially conserved axial current (PCAC) relation by also calculating the pseudoscalar form factor. Lastly, we find that these low values are due to large deviations in the PCAC relation between the three form factors, and in the pion-pole dominance hypothesis.« less

Axial-vector form factors of the nucleon from lattice QCD

DOE PAGES

Gupta, Rajan; Jang, Yong-Chull; Lin, Huey-Wen; ...

2017-12-04

In this paper, we present results for the form factors of the isovector axial vector current in the nucleon state using large scale simulations of lattice QCD. The calculations were done using eight ensembles of gauge configurations generated by the MILC collaboration using the HISQ action with 2 + 1 + 1 dynamical flavors. These ensembles span three lattice spacings a ≈ 0.06 , 0.09, and 0.12 fm and light-quark masses corresponding to the pion masses M π ≈ 135, 225, and 310 MeV. High-statistics estimates allow us to quantify systematic uncertainties in the extraction of G A (Q 2)more » and the induced pseudoscalar form factor G P(Q 2) . We perform a simultaneous extrapolation in the lattice spacing, lattice volume and light-quark masses of the axial charge radius r A data to obtain physical estimates. Using the dipole ansatz to fit the Q 2 behavior we obtain r A | dipole = 0.49(3) fm , which corresponds to M A = 1.39(9) GeV , and is consistent with M A = 1.35(17) GeV obtained by the miniBooNE collaboration. The estimate obtained using the z -expansion is r A | z - expansion = 0.46(6) fm, and the combined result is r A | combined = 0.48(4) fm. Analysis of the induced pseudoscalar form factor G P (Q 2) yields low estimates for g* P and g πNN compared to their phenomenological values. To understand these, we analyze the partially conserved axial current (PCAC) relation by also calculating the pseudoscalar form factor. Lastly, we find that these low values are due to large deviations in the PCAC relation between the three form factors, and in the pion-pole dominance hypothesis.« less

eHealth literacy in chronic disease patients: An item response theory analysis of the eHealth literacy scale (eHEALS).

PubMed

Paige, Samantha R; Krieger, Janice L; Stellefson, Michael; Alber, Julia M

2017-02-01

Chronic disease patients are affected by low computer and health literacy, which negatively affects their ability to benefit from access to online health information. To estimate reliability and confirm model specifications for eHealth Literacy Scale (eHEALS) scores among chronic disease patients using Classical Test (CTT) and Item Response Theory techniques. A stratified sample of Black/African American (N=341) and Caucasian (N=343) adults with chronic disease completed an online survey including the eHEALS. Item discrimination was explored using bi-variate correlations and Cronbach's alpha for internal consistency. A categorical confirmatory factor analysis tested a one-factor structure of eHEALS scores. Item characteristic curves, in-fit/outfit statistics, omega coefficient, and item reliability and separation estimates were computed. A 1-factor structure of eHEALS was confirmed by statistically significant standardized item loadings, acceptable model fit indices (CFI/TLI>0.90), and 70% variance explained by the model. Item response categories increased with higher theta levels, and there was evidence of acceptable reliability (ω=0.94; item reliability=89; item separation=8.54). eHEALS scores are a valid and reliable measure of self-reported eHealth literacy among Internet-using chronic disease patients. Providers can use eHEALS to help identify patients' eHealth literacy skills. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Effects of spatial resolution and landscape structure on land cover characterization

NASA Astrophysics Data System (ADS)

Yang, Wenli

This dissertation addressed problems in scaling, problems that are among the main challenges in remote sensing. The principal objective of the research was to investigate the effects of changing spatial scale on the representation of land cover. A second objective was to determine the relationship between such effects, characteristics of landscape structure and scaling procedures. Four research issues related to spatial scaling were examined. They included: (1) the upscaling of Normalized Difference Vegetation Index (NDVI); (2) the effects of spatial scale on indices of landscape structure; (3) the representation of land cover databases at different spatial scales; and (4) the relationships between landscape indices and land cover area estimations. The overall bias resulting from non-linearity of NDVI in relation to spatial resolution is generally insignificant as compared to other factors such as influences of aerosols and water vapor. The bias is, however, related to land surface characteristics. Significant errors may be introduced in heterogeneous areas where different land cover types exhibit strong spectral contrast. Spatially upscaled SPOT and TM NDVIs have information content comparable with the AVHRR-derived NDVI. Indices of landscape structure and spatial resolution are generally related, but the exact forms of the relationships are subject to changes in other factors including the basic patch unit constituting a landscape and the proportional area of foreground land cover under consideration. The extent of agreement between spatially aggregated coarse resolution land cover datasets and full resolution datasets changes with the properties of the original datasets, including the pixel size and class definition. There are close relationships between landscape structure and class areas estimated from spatially aggregated land cover databases. The relationships, however, do not permit extension from one area to another. Inversion calibration across different geographic/ecological areas is, therefore, not feasible. Different rules govern the land cover area changes across resolutions when different upscaling methods are used. Special attention should be given to comparison between land cover maps derived using different methods.

Psychometric testing of the modified Care Dependency Scale (Neuro-CDS).

PubMed

Piredda, Michela; Biagioli, Valentina; Gambale, Giulia; Porcelli, Elisa; Barbaranelli, Claudio; Palese, Alvisa; De Marinis, Maria Grazia

2016-01-01

Effective measures of nursing care dependency in neurorehabilitation are warranted to plan nursing interventions to help patients avoid increasing dependency. The Care Dependency Scale (CDS) is a theory-based, comprehensive tool to evaluate functional disability. This study aimed to modify the CDS for neurological and neurorehabilitation patients (Neuro-CDS) and to test its psychometric properties in adult neurorehabilitation inpatients. Exploratory factor analysis (EFA) was performed using a Maximum Likelihood robust (MLR) estimator. The Barthel Index (BI) was used to evaluate concurrent validity. Stability was measured using the Intra-class Correlation Coefficient (ICC). The sample included 124 patients (mean age = 69.7 years, 54% male). The EFA revealed a two-factor structure with good fit indexes, Factor 1 (Physical care dependence) loaded by 11 items and Factor 2 (Psycho-social care dependence) loaded by 4 items. The correlation between factors was 0.61. Correlations between Factor 1 and the BI and between Factor 2 and the BI were r = 0.843 and r = 0.677, respectively (p <  0.001). The Cronbach's alpha coefficients were 0.99 and 0.88 (Factor 1 and 2). The ICC was 0.98. The Neuro-CDS is multidimensional, valid, reliable, straightforward, and able to measure care dependence in neurorehabilitation patients as a basis for individualized and holistic care.

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.

Hadron mass corrections in semi-inclusive deep-inelastic scattering

DOE PAGES

Guerrero Teran, Juan Vicente; Ethier, James J.; Accardi, Alberto; ...

2015-09-24

We found that the spin-dependent cross sections for semi-inclusive lepton-nucleon scattering are derived in the framework of collinear factorization, including the effects of masses of the target and produced hadron at finite Q 2. At leading order the cross sections factorize into products of parton distribution and fragmentation functions evaluated in terms of new, mass-dependent scaling variables. Furthermore, the size of the hadron mass corrections is estimated at kinematics relevant for current and future experiments, and the implications for the extraction of parton distributions from semi-inclusive measurements are discussed.

Estimation of the Relationship Between Remotely Sensed Anthropogenic Heat Discharge and Building Energy Use

NASA Technical Reports Server (NTRS)

Zhou, Yuyu; Weng, Qihao; Gurney, Kevin R.; Shuai, Yanmin; Hu, Xuefei

2012-01-01

This paper examined the relationship between remotely sensed anthropogenic heat discharge and energy use from residential and commercial buildings across multiple scales in the city of Indianapolis, Indiana, USA. The anthropogenic heat discharge was estimated with a remote sensing-based surface energy balance model, which was parameterized using land cover, land surface temperature, albedo, and meteorological data. The building energy use was estimated using a GIS-based building energy simulation model in conjunction with Department of Energy/Energy Information Administration survey data, the Assessor's parcel data, GIS floor areas data, and remote sensing-derived building height data. The spatial patterns of anthropogenic heat discharge and energy use from residential and commercial buildings were analyzed and compared. Quantitative relationships were evaluated across multiple scales from pixel aggregation to census block. The results indicate that anthropogenic heat discharge is consistent with building energy use in terms of the spatial pattern, and that building energy use accounts for a significant fraction of anthropogenic heat discharge. The research also implies that the relationship between anthropogenic heat discharge and building energy use is scale-dependent. The simultaneous estimation of anthropogenic heat discharge and building energy use via two independent methods improves the understanding of the surface energy balance in an urban landscape. The anthropogenic heat discharge derived from remote sensing and meteorological data may be able to serve as a spatial distribution proxy for spatially-resolved building energy use, and even for fossil-fuel CO2 emissions if additional factors are considered.

A Method for Semi-quantitative Assessment of Exposure to Pesticides of Applicators and Re-entry Workers: An Application in Three Farming Systems in Ethiopia.

PubMed

Negatu, Beyene; Vermeulen, Roel; Mekonnen, Yalemtshay; Kromhout, Hans

2016-07-01

To develop an inexpensive and easily adaptable semi-quantitative exposure assessment method to characterize exposure to pesticide in applicators and re-entry farmers and farm workers in Ethiopia. Two specific semi-quantitative exposure algorithms for pesticides applicators and re-entry workers were developed and applied to 601 farm workers employed in 3 distinctly different farming systems [small-scale irrigated, large-scale greenhouses (LSGH), and large-scale open (LSO)] in Ethiopia. The algorithm for applicators was based on exposure-modifying factors including application methods, farm layout (open or closed), pesticide mixing conditions, cleaning of spraying equipment, intensity of pesticide application per day, utilization of personal protective equipment (PPE), personal hygienic behavior, annual frequency of application, and duration of employment at the farm. The algorithm for re-entry work was based on an expert-based re-entry exposure intensity score, utilization of PPE, personal hygienic behavior, annual frequency of re-entry work, and duration of employment at the farm. The algorithms allowed estimation of daily, annual and cumulative lifetime exposure for applicators, and re-entry workers by farming system, by gender, and by age group. For all metrics, highest exposures occurred in LSGH for both applicators and female re-entry workers. For male re-entry workers, highest cumulative exposure occurred in LSO farms. Female re-entry workers appeared to be higher exposed on a daily or annual basis than male re-entry workers, but their cumulative exposures were similar due to the fact that on average males had longer tenure. Factors related to intensity of exposure (like application method and farm layout) were indicated as the main driving factors for estimated potential exposure. Use of personal protection, hygienic behavior, and duration of employment in surveyed farm workers contributed less to the contrast in exposure estimates. This study indicated that farmers' and farm workers' exposure to pesticides can be inexpensively characterized, ranked, and classified. Our method could be extended to assess exposure to specific active ingredients provided that detailed information on pesticides used is available. The resulting exposure estimates will consequently be used in occupational epidemiology studies in Ethiopia and other similar countries with few resources. © The Author 2016. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

Theory based scaling of edge turbulence and implications for the scrape-off layer width

NASA Astrophysics Data System (ADS)

Myra, J. R.; Russell, D. A.; Zweben, S. J.

2016-11-01

Turbulence and plasma parameter data from the National Spherical Torus Experiment (NSTX) [Ono et al., Nucl. Fusion 40, 557 (2000)] is examined and interpreted based on various theoretical estimates. In particular, quantities of interest for assessing the role of turbulent transport on the midplane scrape-off layer heat flux width are assessed. Because most turbulence quantities exhibit large scatter and little scaling within a given operation mode, this paper focuses on length and time scales and dimensionless parameters between operational modes including Ohmic, low (L), and high (H) modes using a large NSTX edge turbulence database [Zweben et al., Nucl. Fusion 55, 093035 (2015)]. These are compared with theoretical estimates for drift and interchange rates, profile modification saturation levels, a resistive ballooning condition, and dimensionless parameters characterizing L and H mode conditions. It is argued that the underlying instability physics governing edge turbulence in different operational modes is, in fact, similar, and is consistent with curvature-driven drift ballooning. Saturation physics, however, is dependent on the operational mode. Five dimensionless parameters for drift-interchange turbulence are obtained and employed to assess the importance of turbulence in setting the scrape-off layer heat flux width λq and its scaling. An explicit proportionality of the width λq to the safety factor and major radius (qR) is obtained under these conditions. Quantitative estimates and reduced model numerical simulations suggest that the turbulence mechanism is not negligible in determining λq in NSTX, at least for high plasma current discharges.

Theory based scaling of edge turbulence and implications for the scrape-off layer width

DOE PAGES

Myra, J. R.; Russell, D. A.; Zweben, S. J.

2016-11-01

Turbulence and plasma parameter data from the National Spherical Torus Experiment (NSTX) is examined and interpreted based on various theoretical estimates. In particular, quantities of interest for assessing the role of turbulent transport on the midplane scrape-off layer heat flux width are assessed. Because most turbulence quantities exhibit large scatter and little scaling within a given operation mode, this paper focuses on length and time scales and dimensionless parameters between operational modes including Ohmic, low (L), and high (H) modes using a large NSTX edge turbulence database. These are compared with theoretical estimates for drift and interchange rates, profile modificationmore » saturation levels, a resistive ballooning condition, and dimensionless parameters characterizing L and H mode conditions. It is argued that the underlying instability physics governing edge turbulence in different operational modes is, in fact, similar, and is consistent with curvature-driven drift ballooning. Saturation physics, however, is dependent on the operational mode. Five dimensionless parameters for drift-interchange turbulence are obtained and employed to assess the importance of turbulence in setting the scrape-off layer heat flux width λ q and its scaling. An explicit proportionality of the width λ q to the safety factor and major radius (qR) is obtained under these conditions. Lastly, quantitative estimates and reduced model numerical simulations suggest that the turbulence mechanism is not negligible in determining λ q in NSTX, at least for high plasma current discharges.« less

The Four-Dimensional Symptom Questionnaire (4DSQ) in the general population: scale structure, reliability, measurement invariance and normative data: a cross-sectional survey.

PubMed

Terluin, Berend; Smits, Niels; Brouwers, Evelien P M; de Vet, Henrica C W

2016-09-15

The Four-Dimensional Symptom Questionnaire (4DSQ) is a self-report questionnaire measuring distress, depression, anxiety and somatization with separate scales. The 4DSQ has extensively been validated in clinical samples, especially from primary care settings. Information about measurement properties and normative data in the general population was lacking. In a Dutch general population sample we examined the 4DSQ scales' structure, the scales' reliability and measurement invariance with respect to gender, age and education, the scales' score distributions across demographic categories, and normative data. 4DSQ data were collected in a representative Dutch Internet panel. Confirmatory factor analysis was used to examine the scales' structure. Reliability was examined by Cronbach's alpha, and coefficients omega-total and omega-hierarchical. Differential item functioning (DIF) analysis was used to evaluate measurement invariance across gender, age and education. The total response rate was 82.4 % (n = 5273/6399). The depression scale proved to be unidimensional. The other scales were best represented as bifactor models consisting of a large general factor and one or more smaller specific factors. The general factors accounted for more than 95 % of the reliable variance of the scales. Reliability was high (≥0.85) by all estimates. The distress-, depression- and anxiety scales were invariant across gender, age and education. The somatization scale demonstrated some lack of measurement invariance as a result of decreased thresholds for some of the items in young people (16-24 years) and increased thresholds in elderly people (65+ years). The somatization scale was invariant regarding gender and education. The 4DSQ scores varied significantly across demographic categories, but the explained variance was small (<6 %). Normative data were generated for gender and age categories. Approximately 17 % of the participants scored above average on de distress scale, whereas 12 % scored above average on de somatization scale. Percentages of people scoring high enough on depression or anxiety as to suspect the presence of depressive or anxiety disorder were 4.1 and 2.5 respectively. Evidence supports reliability and measurement invariance of the 4DSQ in the general Dutch population. The normative data provided in this study can be used to compare a subject's 4DSQ scores with a general population reference group.

Personality disorder traits, family environment, and alcohol misuse: a multivariate behavioural genetic analysis.

PubMed

Jang, K L; Vernon, P A; Livesley, W J

2000-06-01

This study seeks to estimate the extent to which a common genetic and environmental basis is shared between (i) traits delineating specific aspects of antisocial personality and alcohol misuse, and (ii) childhood family environments, traits delineating broad domains of personality pathology and alcohol misuse. Postal survey data were collected from monozygotic and dizygotic twin pairs. Twin pairs were recruited from Vancouver, British Columbia and London, Ontario, Canada using newspaper advertisements, media stories and twin clubs. Data obtained from 324 monozygotic and 335 dizygotic twin pairs were used to estimate the extent to which traits delineating specific antisocial personality traits and alcohol misuse shared a common genetic and environmental aetiology. Data from 81 monozygotic and 74 dizygotic twin pairs were used to estimate the degree to which traits delineating personality pathology, childhood family environment and alcohol misuse shared a common aetiology. Current alcohol misuse and personality pathology were measured using scales contained in the self-report Dimensional Assessment of Personality Pathology. Perceptions of childhood family environment were measured using the self-report Family Environment Scale. Multivariate genetic analyses showed that a subset of traits delineating components of antisocial personality (i.e. grandiosity, attention-seeking, failure to adopt social norms, interpersonal violence and juvenile antisocial behaviours) are influenced by genetic factors in common to alcohol misuse. Genetically based perceptions of childhood family environment had little relationship with alcohol misuse. Heritable personality factors that influence the perception of childhood family environment play only a small role in the liability to alcohol misuse. Instead, liability to alcohol misuse is related to genetic factors common a specific subset of antisocial personality traits describing conduct problems, narcissistic and stimulus-seeking behaviour.

Relative sensitivities of DCE-MRI pharmacokinetic parameters to arterial input function (AIF) scaling.

PubMed

Li, Xin; Cai, Yu; Moloney, Brendan; Chen, Yiyi; Huang, Wei; Woods, Mark; Coakley, Fergus V; Rooney, William D; Garzotto, Mark G; Springer, Charles S

2016-08-01

Dynamic-Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) has been used widely for clinical applications. Pharmacokinetic modeling of DCE-MRI data that extracts quantitative contrast reagent/tissue-specific model parameters is the most investigated method. One of the primary challenges in pharmacokinetic analysis of DCE-MRI data is accurate and reliable measurement of the arterial input function (AIF), which is the driving force behind all pharmacokinetics. Because of effects such as inflow and partial volume averaging, AIF measured from individual arteries sometimes require amplitude scaling for better representation of the blood contrast reagent (CR) concentration time-courses. Empirical approaches like blinded AIF estimation or reference tissue AIF derivation can be useful and practical, especially when there is no clearly visible blood vessel within the imaging field-of-view (FOV). Similarly, these approaches generally also require magnitude scaling of the derived AIF time-courses. Since the AIF varies among individuals even with the same CR injection protocol and the perfect scaling factor for reconstructing the ground truth AIF often remains unknown, variations in estimated pharmacokinetic parameters due to varying AIF scaling factors are of special interest. In this work, using simulated and real prostate cancer DCE-MRI data, we examined parameter variations associated with AIF scaling. Our results show that, for both the fast-exchange-limit (FXL) Tofts model and the water exchange sensitized fast-exchange-regime (FXR) model, the commonly fitted CR transfer constant (K(trans)) and the extravascular, extracellular volume fraction (ve) scale nearly proportionally with the AIF, whereas the FXR-specific unidirectional cellular water efflux rate constant, kio, and the CR intravasation rate constant, kep, are both AIF scaling insensitive. This indicates that, for DCE-MRI of prostate cancer and possibly other cancers, kio and kep may be more suitable imaging biomarkers for cross-platform, multicenter applications. Data from our limited study cohort show that kio correlates with Gleason scores, suggesting that it may be a useful biomarker for prostate cancer disease progression monitoring. Copyright © 2016 Elsevier Inc. All rights reserved.

Engineering aspects of geothermal development with emphasis on the Imperial Valley of California

NASA Technical Reports Server (NTRS)

Goldsmith, M.

1978-01-01

This review was prepared in support of a geothermal planning activity of the County of Imperial. Engineering features of potential geothermal development are outlined. Acreage requirements for drilling and powerplants are estimated, as are the costs for wells, fluid transmission pipes, and generating stations. Rough scaling relationships are developed for cost factors as a function of reservoir temperature. Estimates are made for cooling water requirements, and possible sources of cooling water are discussed. Availability and suitability of agricultural wastewater for cooling are emphasized. The utility of geothermal resources for fresh water production in the Imperial Valley is considered.

A simple, analytical, axisymmetric microburst model for downdraft estimation

NASA Technical Reports Server (NTRS)

Vicroy, Dan D.

1991-01-01

A simple analytical microburst model was developed for use in estimating vertical winds from horizontal wind measurements. It is an axisymmetric, steady state model that uses shaping functions to satisfy the mass continuity equation and simulate boundary layer effects. The model is defined through four model variables: the radius and altitude of the maximum horizontal wind, a shaping function variable, and a scale factor. The model closely agrees with a high fidelity analytical model and measured data, particularily in the radial direction and at lower altitudes. At higher altitudes, the model tends to overestimate the wind magnitude relative to the measured data.

Probing the largest cosmological scales with the correlation between the cosmic microwave background and peculiar velocities

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

Fosalba, Pablo; Dore, Olivier

2007-11-15

Cross correlation between the cosmic microwave background (CMB) and large-scale structure is a powerful probe of dark energy and gravity on the largest physical scales. We introduce a novel estimator, the CMB-velocity correlation, that has most of its power on large scales and that, at low redshift, delivers up to a factor of 2 higher signal-to-noise ratio than the recently detected CMB-dark matter density correlation expected from the integrated Sachs-Wolfe effect. We propose to use a combination of peculiar velocities measured from supernovae type Ia and kinetic Sunyaev-Zeldovich cluster surveys to reveal this signal and forecast dark energy constraints thatmore » can be achieved with future surveys. We stress that low redshift peculiar velocity measurements should be exploited with complementary deeper large-scale structure surveys for precision cosmology.« less

Determination of development factors of the construction market

NASA Astrophysics Data System (ADS)

Kozlova, Olga

2017-10-01

Field of housing construction constantly needs measures of business climate improvement. Provision of housing for citizens remains relatively low. Recently, state has been developing a new set of measures for shared-equity construction improvement. This area has a particular significance and scales for our country. Number of defrauded shareholders in the past allows estimate scales of losses both in the form of unfinished objects in the past and reputation losses of this direction of construction. This article proposes measures which are designed to form an informational base for forecasts of the development of construction and provide a positive result from the applied measures.

Ideal, nonideal, and no-marker variables: The confirmatory factor analysis (CFA) marker technique works when it matters.

PubMed

Williams, Larry J; O'Boyle, Ernest H

2015-09-01

A persistent concern in the management and applied psychology literature is the effect of common method variance on observed relations among variables. Recent work (i.e., Richardson, Simmering, & Sturman, 2009) evaluated 3 analytical approaches to controlling for common method variance, including the confirmatory factor analysis (CFA) marker technique. Their findings indicated significant problems with this technique, especially with nonideal marker variables (those with theoretical relations with substantive variables). Based on their simulation results, Richardson et al. concluded that not correcting for method variance provides more accurate estimates than using the CFA marker technique. We reexamined the effects of using marker variables in a simulation study and found the degree of error in estimates of a substantive factor correlation was relatively small in most cases, and much smaller than error associated with making no correction. Further, in instances in which the error was large, the correlations between the marker and substantive scales were higher than that found in organizational research with marker variables. We conclude that in most practical settings, the CFA marker technique yields parameter estimates close to their true values, and the criticisms made by Richardson et al. are overstated. (c) 2015 APA, all rights reserved).

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

NASA Astrophysics Data System (ADS)

Mishra, U.; Riley, W. J.

2015-01-01

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing heterogeneity of terrestrial hydrological and biogeochemical processes in earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a dataset with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales (s = 100, 200, 500 m, 1, 2, 5, 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions (R2 = 0.83-0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98% of variability in the variance of SOC stocks. We found moderately-accurate linear relationships between mean and higher-order moments of predicted SOC stocks (R2 ~ 0.55-0.63). Current ESMs operate at coarse spatial scales (50-100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks can improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

NASA Astrophysics Data System (ADS)

Mishra, U.; Riley, W. J.

2015-07-01

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing the heterogeneity of terrestrial hydrological and biogeochemical processes in Earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a data set with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales (s = 100, 200, and 500 m and 1, 2, 5, and 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions (R2 = 0.83-0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 m to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98 % of variability in the variance of SOC stocks. We found moderately accurate linear relationships between mean and higher-order moments of predicted SOC stocks (R2 ∼ 0.55-0.63). Current ESMs operate at coarse spatial scales (50-100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks could improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

DOE PAGES

Mishra, U.; Riley, W. J.

2015-07-02

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing the heterogeneity of terrestrial hydrological and biogeochemical processes in Earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a data setmore » with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales ( s = 100, 200, and 500 m and 1, 2, 5, and 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions ( R 2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 m to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98 % of variability in the variance of SOC stocks. We found moderately accurate linear relationships between mean and higher-order moments of predicted SOC stocks ( R 2 ∼ 0.55–0.63). Current ESMs operate at coarse spatial scales (50–100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks could improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.« less

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

DOE PAGES

Mishra, U.; Riley, W. J.

2015-01-01

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing heterogeneity of terrestrial hydrological and biogeochemical processes in earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a dataset with reasonablemore » fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales ( s = 100, 200, 500 m, 1, 2, 5, 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions ( R 2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98% of variability in the variance of SOC stocks. We found moderately-accurate linear relationships between mean and higher-order moments of predicted SOC stocks ( R 2 ~ 0.55–0.63). Current ESMs operate at coarse spatial scales (50–100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks can improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.« less

Psychometric properties of the Persian version of the Intensive and Critical Care Nursing Competence Scale version-1 (ICCN-CS-1)

PubMed Central

Shouryabi, Ali Asghar; Ghahrisarabi, Alireza; Anboohi, Sima Zohari; Nasiri, Malihe; Rassouli, Maryam

2017-01-01

Background Nursing competence is highly related to patient outcomes and patient safety issues, especially in intensive care units. Competence assessment tools are needed specifically for intensive care nursing. Objective This study was performed to determine psychometric properties of the Intensive and Critical Care Nursing Competence Scale version-1 between Iranian Nurses. Methods The present study was a methodological research in which 289 nurses of Intensive Care Units from nine hospitals in Shahid Beheshti University of Medical Sciences in Tehran were selected between 2015 and 2016. The original version of the scale was translated into Persian and back-translated into English, and the comments of the developer were applied. The validity of the scale was the determined quality (content validity and face validity) and quantity (confirmatory factor analysis). Reliability of the scale was reported by Cronbach’s alpha coefficient and Intra class Correlation Coefficient. SPSS-PC (v.21) and LISREL (v.8.5) were used to analyze the data. Results The intensive and critical care nursing competence scale version-1 is a self-assessment test that consists of 144 items and four domains which are the knowledge base, the skill base, the attitudes and values base and the experience base, which are divided into clinical competence and professional competence. Content and face validity was confirmed by 10 experts and 10 practitioner nurses in the intensive care units. In confirmatory factor analysis, all fitness indexes, except goodness of fit index (0.64), confirmed the four-factor structure of the ICCN-CS-1. The results of the factor analysis, load factor between 0.304 and 0.727 items was estimated; only 4 items out of 144 items, that were loaded were less than 0.3 due to high Cronbach’s alpha coefficient (0.984–0.986), all items were preserved, no item was removed and 4 subscales of the original scale were confirmed. Conclusion The results of this study indicated that the Persian version of “The Intensive and Critical Care Nursing Competence Scale version-1” is a valid and reliable scale for the assessment of competency among Iranian nurses, and it can be used as a reliable scale in nursing management, education and research. PMID:29403620

Sociodemographic and Medical Risk Factors Associated With Antepartum Depression.

PubMed

Babu, Giridhara R; Murthy, G V S; Singh, Neeru; Nath, Anita; Rathnaiah, Mohanbabu; Saldanha, Nolita; Deepa, R; Kinra, Sanjay

2018-01-01

The increasing recognition of antenatal depression is an emerging area of concern in developing countries. We conducted a study to estimate the prevalence of antenatal mental distress and its relation with sociodemographic factors, obstetric factors, and physiological wellbeing in pregnant women attending public health facilities in Bengaluru, South India. Nested within a cohort study, we assessed the mental status in 823 pregnant women in two public referral hospitals. Kessler Psychological Distress Scale (K-10 scale) was used to assess maternal depression. We collected information related to social-demographic characteristics and recent medical complaints. Descriptive statistics and odds ratios were calculated using SPSS version 20. Results show that 8.7% of the women exhibited symptoms of antenatal depression. Sociodemographic characteristics, such as respondent occupation, husband education, husband's occupation, total family income showed significance. First time pregnancy, anemia, and high blood pressure were also associated with mental distress. Our study has demonstrated feasibility of screening for mental health problems in public hospitals. Early detection of mental distress during pregnancy is crucial as it has a direct impact on the fetus. The public health facilities in low- and middle-income countries such as India should consider piloting and scaling up screening services for mental health conditions for pregnant women.

The knowledge, efficacy, and practices instrument for oral health providers: a validity study with dental students.

PubMed

Behar-Horenstein, Linda S; Garvan, Cyndi W; Moore, Thomas E; Catalanotto, Frank A

2013-08-01

Valid and reliable instruments to measure and assess cultural competence for oral health care providers are scarce in the literature, and most published scales have been contested due to a lack of item analysis and internal estimates of reliability. The purposes of this study were, first, to develop a standardized instrument to measure dental students' knowledge of diversity, skills in culturally competent patient-centered communication, and use of culture-centered practices in patient care and, second, to provide preliminary validity support for this instrument. The initial instrument used in this study was a thirty-six-item Likert-scale survey entitled the Knowledge, Efficacy, and Practices Instrument for Oral Health Providers (KEPI-OHP). This instrument is an adaption of an initially thirty-three-item version of the Multicultural Awareness, Knowledge, and Skills Scale-Counselor Edition (MAKSS-CE), a scale that assesses factors related to social justice, cultural differences among clients, and cross-cultural client management. After the authors conducted cognitive and expert interviews, focus groups, pilot testing, and item analysis, their initial instrument was reduced to twenty-eight items. The KEPI-OHP was then distributed to 916 dental students (response rate=48.6 percent) across the United States to measure its reliability and assess its validity. Both exploratory and confirmatory factor analyses were conducted to test the scale's validity. The modification of the survey into a sensible instrument with a relatively clear factor structure using factor analysis resulted in twenty items. A scree test suggested three expressive factors, which were retained for rotation. Bentler's comparative fit and Bentler and Bonnett's non-normed indices were 0.95 and 0.92, respectively. A three-factor solution, including efficacy of assessment, knowledge of diversity, and culture-centered practice subscales, comprised of twenty-items was identified. The KEPI-OHP was found to have reasonable internal consistency reliability to warrant its use for baseline and repeated measures in assessing changes in dental students' growth in cultural competence across four-year dental curricula.

Assessment of Evapotranspiration and Soil Moisture Content Across Different Scales of Observation

PubMed Central

Verstraeten, Willem W.; Veroustraete, Frank; Feyen, Jan

2008-01-01

The proper assessment of evapotranspiration and soil moisture content are fundamental in food security research, land management, pollution detection, nutrient flows, (wild-) fire detection, (desert) locust, carbon balance as well as hydrological modelling; etc. This paper takes an extensive, though not exhaustive sample of international scientific literature to discuss different approaches to estimate land surface and ecosystem related evapotranspiration and soil moisture content. This review presents: (i)a summary of the generally accepted cohesion theory of plant water uptake and transport including a shortlist of meteorological and plant factors influencing plant transpiration;(ii)a summary on evapotranspiration assessment at different scales of observation (sap-flow, porometer, lysimeter, field and catchment water balance, Bowen ratio, scintillometer, eddy correlation, Penman-Monteith and related approaches);(iii)a summary on data assimilation schemes conceived to estimate evapotranspiration using optical and thermal remote sensing; and(iv)for soil moisture content, a summary on soil moisture retrieval techniques at different spatial and temporal scales is presented. Concluding remarks on the best available approaches to assess evapotranspiration and soil moisture content with and emphasis on remote sensing data assimilation, are provided. PMID:27879697

Assessment of Evapotranspiration and Soil Moisture Content Across Different Scales of Observation.

PubMed

Verstraeten, Willem W; Veroustraete, Frank; Feyen, Jan

2008-01-09

The proper assessment of evapotranspiration and soil moisture content arefundamental in food security research, land management, pollution detection, nutrient flows,(wild-) fire detection, (desert) locust, carbon balance as well as hydrological modelling; etc.This paper takes an extensive, though not exhaustive sample of international scientificliterature to discuss different approaches to estimate land surface and ecosystem relatedevapotranspiration and soil moisture content. This review presents:(i) a summary of the generally accepted cohesion theory of plant water uptake andtransport including a shortlist of meteorological and plant factors influencing planttranspiration;(ii) a summary on evapotranspiration assessment at different scales of observation (sapflow,porometer, lysimeter, field and catchment water balance, Bowen ratio,scintillometer, eddy correlation, Penman-Monteith and related approaches);(iii) a summary on data assimilation schemes conceived to estimate evapotranspirationusing optical and thermal remote sensing; and(iv) for soil moisture content, a summary on soil moisture retrieval techniques atdifferent spatial and temporal scales is presented.Concluding remarks on the best available approaches to assess evapotranspiration and soilmoisture content with and emphasis on remote sensing data assimilation, are provided.

Using Scaling to Understand, Model and Predict Global Scale Anthropogenic and Natural Climate Change

NASA Astrophysics Data System (ADS)

Lovejoy, S.; del Rio Amador, L.

2014-12-01

The atmosphere is variable over twenty orders of magnitude in time (≈10-3 to 1017 s) and almost all of the variance is in the spectral "background" which we show can be divided into five scaling regimes: weather, macroweather, climate, macroclimate and megaclimate. We illustrate this with instrumental and paleo data. Based the signs of the fluctuation exponent H, we argue that while the weather is "what you get" (H>0: fluctuations increasing with scale), that it is macroweather (H<0: fluctuations decreasing with scale) - not climate - "that you expect". The conventional framework that treats the background as close to white noise and focuses on quasi-periodic variability assumes a spectrum that is in error by a factor of a quadrillion (≈ 1015). Using this scaling framework, we can quantify the natural variability, distinguish it from anthropogenic variability, test various statistical hypotheses and make stochastic climate forecasts. For example, we estimate the probability that the warming is simply a giant century long natural fluctuation is less than 1%, most likely less than 0.1% and estimate return periods for natural warming events of different strengths and durations, including the slow down ("pause") in the warming since 1998. The return period for the pause was found to be 20-50 years i.e. not very unusual; however it immediately follows a 6 year "pre-pause" warming event of almost the same magnitude with a similar return period (30 - 40 years). To improve on these unconditional estimates, we can use scaling models to exploit the long range memory of the climate process to make accurate stochastic forecasts of the climate including the pause. We illustrate stochastic forecasts on monthly and annual scale series of global and northern hemisphere surface temperatures. We obtain forecast skill nearly as high as the theoretical (scaling) predictability limits allow: for example, using hindcasts we find that at 10 year forecast horizons we can still explain ≈ 15% of the anomaly variance. These scaling hindcasts have comparable - or smaller - RMS errors than existing GCM's. We discuss how these be further improved by going beyond time series forecasts to space-time.

Landscape-Scale Soil Carbon Inventories by Microclimate Decomposition

NASA Astrophysics Data System (ADS)

Beaudette, D. E.; O'Geen, A. T.

2008-12-01

Estimation of carbon stocks in rangeland and foothill ecosystems is poised to become an important service once legislation regulating greenhouse gas emissions is passed. Trading of carbon credits and greenhouse gas emission/sequestration budgets for vegetated areas is largely dependent on an accurate and scale- dependent inventory of existing conditions. Soil survey presents one possible resource for surface carbon stocks, however these data are usually not mapped at the landscape-scale. Soil-landscape modeling techniques have been successfully used in several instances to predict the spatial variation in soil carbon. Most of these studies have used site exposure (aspect angle) as a categorical proxy for terrain-induced microclimate. Our objective was to model parameters related to soil microclimate (soil temperature and moisture) for the production of detailed maps of soil carbon and organic matter quality (i.e. C:N ratio). We used a solar radiation model and long-term monitoring of soil moisture and temperature to generate several models of soil microclimate. Parameterization of the ESRA (European Solar Radiation Atlas) solar radiation model (clear-sky version) was accomplished with daily estimates of the Linke turbidity factor, using local pyranometer measurements (11 year record). Our estimated daily radiance values correlated well with local weather station data (R2 = 0.965, p < 0.001). This model is included in the popular, open source GRASS GIS. A preliminary study based on 35 sites, spanning two contrasting landform types (and lithology), revealed a statistically significant relationship between annual radiation load and carbon (R2 = 0.75, p < 0.001). A highly significant relationship between C:N ratio and annual radiation load was identified as well (R2 = 0.99, p < 0.001). Solar radiation models are simple to use, and have the potential to refine previous soil-landscape modeling efforts that relied on aspect class or angle. Models linking surface processes with microclimate can be used to directly generate estimates of carbon, or used to down-scale soil survey-based estimates.

Vibrational spectra and ab initio analysis of tert-butyl, trimethylsilyl, and trimethylgermyl derivatives of 3,3-dimethylcyclopropene IV. 3,3-Dimethyl-1,2-bis(trimethylgermyl)cyclopropene

NASA Astrophysics Data System (ADS)

Panchenko, Yu. N.; De Maré, G. R.; Abramenkov, A. V.; Baird, M. S.; Tverezovsky, V. V.; Nizovtsev, A. V.; Bolesov, I. G.

2003-06-01

The infrared (IR) and Raman spectra of 3,3-dimethyl-1,2-bis(trimethylgermyl)cyclopropene (I) were measured in the liquid phase. Total geometry optimisation was performed at the HF/6-31G* level. The HF/6-31G*//HF6-31G* quantum mechanical force field (QMFF) was calculated and used to determine the theoretical fundamental vibrational frequencies, their predicted IR intensities, Raman activities, and Raman depolarisation ratios. Using Pulay's scaling method and the theoretical molecular geometry, the QMFF of I was scaled by a set of scaling factors comprised of elements transferred from the sets used to correct the QMFF's of 3,3-dimethylbutene-1, and 1-methyl-, 1,2-dimethyl-, and 3,3-dimethylcyclopropene (17 scale factors for a 105-dimensional problem). This set of scale factors was used previously to correct the QMFF of 3,3-dimethyl-1,2-bis(tert-butyl)cyclopropene and 3,3-dimethyl-1,2-bis(trimethylsilyl)cyclopropene. The scaled QMFF obtained was used to solve the vibrational problem. Differential Raman cross-sections were calculated using the quantum mechanical values of the Raman activities. The appropriate theoretical spectrograms for the Raman and IR spectra of I were constructed. Assignments of the experimental vibrational spectra of I are given. They take into account the calculated potential energy distributions and the correlation between the estimations of the experimental IR and Raman intensities and Raman depolarisation ratios and the corresponding theoretical values calculated using the unscaled QMFF.

What increases the risk of malnutrition in Parkinson's disease?

PubMed

Tomic, Svetlana; Pekic, Vlasta; Popijac, Zeljka; Pucic, Tomislav; Petek, Marta; Kuric, Tihana Gilman; Misevic, Sanja; Kramaric, Ruzica Palic

2017-04-15

Parkinson's disease (PD) patients are at a higher risk of malnutrition. The prevalence has been estimated to 0-24%, while 3%-60% of PD patients are reported to be at risk of malnutrition. To date, there is no clear explanation for malnutrition in these patients. The aim of this study was to determine the prevalence of malnutrition and to analyze factors that influence its appearance. The Mini Nutritional Assessment (MNA) was used to determine normal nutritional status; at risk of malnutrition; and already malnourished status. The Unified Parkinson's Disease Rating Scale (UPDRS) parts III and IV, Hoehn and Yahr scale (H&Y scale), Beck Depression Inventory (BDI), Mini Mental State Examination (MMSE), Questionnaire for Impulsive-Compulsive Disorders in Parkinson's Disease-Rating Scale - eating part (QUIP-RS) and Mini Nutritional Assessment (MNA) were used to evaluate the factors affecting patient nutritional status. Out of 96 patients, 55,2% were at risk of malnutrition, while 8,3% had already been malnourished. Age, H&Y scale, UPDRS part III, 'off' periods and depression influence negatively on MNA. More patients with 'off' periods were rigor dominant. Thyroid gland hormone therapy was related to malnutrition, while patients with normal nutritional status used ropinirole more often than pramipexole. Factors affecting nutritional status are age, motor symptoms and stage severity, 'off' states, rigidity dominant type with 'off' states, and thyroid hormone replacement therapy. Ropinirole exhibited the possible 'protective' effect against malnutrition. Copyright © 2017 Elsevier B.V. All rights reserved.

Landscape-Scale Controls on Aboveground Forest Carbon Stocks on the Osa Peninsula, Costa Rica

PubMed Central

Taylor, Philip; Asner, Gregory; Dahlin, Kyla; Anderson, Christopher; Knapp, David; Martin, Roberta; Mascaro, Joseph; Chazdon, Robin; Cole, Rebecca; Wanek, Wolfgang; Hofhansl, Florian; Malavassi, Edgar; Vilchez-Alvarado, Braulio; Townsend, Alan

2015-01-01

Tropical forests store large amounts of carbon in tree biomass, although the environmental controls on forest carbon stocks remain poorly resolved. Emerging airborne remote sensing techniques offer a powerful approach to understand how aboveground carbon density (ACD) varies across tropical landscapes. In this study, we evaluate the accuracy of the Carnegie Airborne Observatory (CAO) Light Detection and Ranging (LiDAR) system to detect top-of-canopy tree height (TCH) and ACD across the Osa Peninsula, Costa Rica. LiDAR and field-estimated TCH and ACD were highly correlated across a wide range of forest ages and types. Top-of-canopy height (TCH) reached 67 m, and ACD surpassed 225 Mg C ha-1, indicating both that airborne CAO LiDAR-based estimates of ACD are accurate in tall, high-biomass forests and that the Osa Peninsula harbors some of the most carbon-rich forests in the Neotropics. We also examined the relative influence of lithologic, topoedaphic and climatic factors on regional patterns in ACD, which are known to influence ACD by regulating forest productivity and turnover. Analyses revealed a spatially nested set of factors controlling ACD patterns, with geologic variation explaining up to 16% of the mapped ACD variation at the regional scale, while local variation in topographic slope explained an additional 18%. Lithologic and topoedaphic factors also explained more ACD variation at 30-m than at 100-m spatial resolution, suggesting that environmental filtering depends on the spatial scale of terrain variation. Our result indicate that patterns in ACD are partially controlled by spatial variation in geologic history and geomorphic processes underpinning topographic diversity across landscapes. ACD also exhibited spatial autocorrelation, which may reflect biological processes that influence ACD, such as the assembly of species or phenotypes across the landscape, but additional research is needed to resolve how abiotic and biotic factors contribute to ACD variation across high biomass, high diversity tropical landscapes. PMID:26061884

Recent changes in county-level corn yield variability in the United States from observations and crop models

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

Leng, Guoyong

The United States is responsible for 35% and 60% of global corn supply and exports. Enhanced supply stability through a reduction in the year-to-year variability of US corn yield would greatly benefit global food security. Important in this regard is to understand how corn yield variability has evolved geographically in the history and how it relates to climatic and non-climatic factors. Results showed that year-to-year variation of US corn yield has decreased significantly during 1980-2010, mainly in Midwest Corn Belt, Nebraska and western arid regions. Despite the country-scale decreasing variability, corn yield variability exhibited an increasing trend in South Dakota,more » Texas and Southeast growing regions, indicating the importance of considering spatial scales in estimating yield variability. The observed pattern is partly reproduced by process-based crop models, simulating larger areas experiencing increasing variability and underestimating the magnitude of decreasing variability. And 3 out of 11 models even produced a differing sign of change from observations. Hence, statistical model which produces closer agreement with observations is used to explore the contribution of climatic and non-climatic factors to the changes in yield variability. It is found that climate variability dominate the change trends of corn yield variability in the Midwest Corn Belt, while the ability of climate variability in controlling yield variability is low in southeastern and western arid regions. Irrigation has largely reduced the corn yield variability in regions (e.g. Nebraska) where separate estimates of irrigated and rain-fed corn yield exist, demonstrating the importance of non-climatic factors in governing the changes in corn yield variability. The results highlight the distinct spatial patterns of corn yield variability change as well as its influencing factors at the county scale. I also caution the use of process-based crop models, which have substantially underestimated the change trend of corn yield variability, in projecting its future changes.« less

Experiences from the testing of a theory for modelling groundwater flow in heterogeneous media

USGS Publications Warehouse

Christensen, S.; Cooley, R.L.

2002-01-01

Usually, small-scale model error is present in groundwater modelling because the model only represents average system characteristics having the same form as the drift and small-scale variability is neglected. These errors cause the true errors of a regression model to be correlated. Theory and an example show that the errors also contribute to bias in the estimates of model parameters. This bias originates from model nonlinearity. In spite of this bias, predictions of hydraulic head are nearly unbiased if the model intrinsic nonlinearity is small. Individual confidence and prediction intervals are accurate if the t-statistic is multiplied by a correction factor. The correction factor can be computed from the true error second moment matrix, which can be determined when the stochastic properties of the system characteristics are known.

Experience gained in testing a theory for modelling groundwater flow in heterogeneous media

USGS Publications Warehouse

Christensen, S.; Cooley, R.L.

2002-01-01

Usually, small-scale model error is present in groundwater modelling because the model only represents average system characteristics having the same form as the drift, and small-scale variability is neglected. These errors cause the true errors of a regression model to be correlated. Theory and an example show that the errors also contribute to bias in the estimates of model parameters. This bias originates from model nonlinearity. In spite of this bias, predictions of hydraulic head are nearly unbiased if the model intrinsic nonlinearity is small. Individual confidence and prediction intervals are accurate if the t-statistic is multiplied by a correction factor. The correction factor can be computed from the true error second moment matrix, which can be determined when the stochastic properties of the system characteristics are known.

Wavelet phase extracting demodulation algorithm based on scale factor for optical fiber Fabry-Perot sensing.

PubMed

Zhang, Baolin; Tong, Xinglin; Hu, Pan; Guo, Qian; Zheng, Zhiyuan; Zhou, Chaoran

2016-12-26

Optical fiber Fabry-Perot (F-P) sensors have been used in various on-line monitoring of physical parameters such as acoustics, temperature and pressure. In this paper, a wavelet phase extracting demodulation algorithm for optical fiber F-P sensing is first proposed. In application of this demodulation algorithm, search range of scale factor is determined by estimated cavity length which is obtained by fast Fourier transform (FFT) algorithm. Phase information of each point on the optical interference spectrum can be directly extracted through the continuous complex wavelet transform without de-noising. And the cavity length of the optical fiber F-P sensor is calculated by the slope of fitting curve of the phase. Theorical analysis and experiment results show that this algorithm can greatly reduce the amount of computation and improve demodulation speed and accuracy.

Association between the Center for Epidemiologic Studies Depression Scale (CES-D) and mortality in a community sample: An artifact of the somatic complaints factor?1

PubMed Central

Pettit, Jeremy W.; Lewinsohn, Peter M.; Seeley, John R.; Roberts, Robert E.; Hibbard, Judith H.; Hurtado, Arnold V.

2009-01-01

Most previous studies of the depression-mortality association have not examined distinct depressive symptom clusters. This ex post facto study examined which aspects of depression may account for its association with mortality. The Center for Epidemiologic Studies Depression Scale (CES-D) was administered to 3,867 community dwelling adults. Cox proportional hazards procedures estimated the risk of mortality as a function of depression status and each of 4 CES-D factor scores. Depressed participants (CES-D ≥ 16) had a 1.23-fold higher risk of mortality (95% CI 1.03-1.49), adjusting for sociodemographics. Somatic Complaints (SC) was the only factor to predict mortality (HR 1.19, 95% CI 1.03-1.38). After excluding SC, CES-D scores no longer predicted mortality (HR .98, 95% CI .79-1.21). The association between CES-D depressive symptoms and mortality appears to be a function of the SC factor. The association between non-somatic depressive symptoms and mortality may not be as robust as past findings suggest. PMID:19936326

Association between the Center for Epidemiologic Studies Depression Scale (CES-D) and mortality in a community sample: An artifact of the somatic complaints factor?

PubMed

Pettit, Jeremy W; Lewinsohn, Peter M; Seeley, John R; Roberts, Robert E; Hibbard, Judith H; Hurtado, Arnold V

2008-05-01

Most previous studies of the depression-mortality association have not examined distinct depressive symptom clusters. This ex post facto study examined which aspects of depression may account for its association with mortality. The Center for Epidemiologic Studies Depression Scale (CES-D) was administered to 3,867 community dwelling adults. Cox proportional hazards procedures estimated the risk of mortality as a function of depression status and each of 4 CES-D factor scores. Depressed participants (CES-D ≥ 16) had a 1.23-fold higher risk of mortality (95% CI 1.03-1.49), adjusting for sociodemographics. Somatic Complaints (SC) was the only factor to predict mortality (HR 1.19, 95% CI 1.03-1.38). After excluding SC, CES-D scores no longer predicted mortality (HR .98, 95% CI .79-1.21). The association between CES-D depressive symptoms and mortality appears to be a function of the SC factor. The association between non-somatic depressive symptoms and mortality may not be as robust as past findings suggest.

Coma Recovery Scale-Revised: evidentiary support for hierarchical grading of level of consciousness.

PubMed

Gerrard, Paul; Zafonte, Ross; Giacino, Joseph T

2014-12-01

To investigate the neurobehavioral pattern of recovery of consciousness as reflected by performance on the subscales of the Coma Recovery Scale-Revised (CRS-R). Retrospective item response theory (IRT) and factor analysis. Inpatient rehabilitation facilities. Rehabilitation inpatients (N=180) with posttraumatic disturbance in consciousness who participated in a double-blinded, randomized, controlled drug trial. Not applicable. Scores on CRS-R subscales. The CRS-R was found to fit factor analytic models adhering to the assumptions of unidimensionality and monotonicity. In addition, subscales were mutually independent based on residual correlations. Nonparametric IRT reaffirmed the finding of monotonicity. A highly constrained confirmatory factor analysis model, which imposed equal factor loadings on all items, was found to fit the data well and was used to estimate a 1-parameter IRT model. This study provides evidence of the unidimensionality of the CRS-R and supports the hierarchical structure of the CRS-R subscales, suggesting that it is an effective tool for establishing diagnosis and monitoring recovery of consciousness after severe traumatic brain injury. Copyright © 2014 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Geometric factor and influence of sensors in the establishment of a resistivity-moisture relation in soil samples

NASA Astrophysics Data System (ADS)

López-Sánchez, M.; Mansilla-Plaza, L.; Sánchez-de-laOrden, M.

2017-10-01

Prior to field scale research, soil samples are analysed on a laboratory scale for electrical resistivity calibrations. Currently, there are a variety of field instruments to estimate the water content in soils using different physical phenomena. These instruments can be used to develop moisture-resistivity relationships on the same soil samples. This assures that measurements are performed on the same material and under the same conditions (e.g., humidity and temperature). A geometric factor is applied to the location of electrodes, in order to calculate the apparent electrical resistivity of the laboratory test cells. This geometric factor can be determined in three different ways: by means of the use of an analytical approximation, laboratory trials (experimental approximation), or by the analysis of a numerical model. The first case, the analytical approximation, is not appropriate for complex cells or arrays. And both, the experimental and numerical approximation can lead to inaccurate results. Therefore, we propose a novel approach to obtain a compromise solution between both techniques, providing a more precise determination of the geometrical factor.

Marginal Emissions Factors for Electricity Generation in the Midcontinent ISO.

PubMed

Thind, Maninder P S; Wilson, Elizabeth J; Azevedo, Inês L; Marshall, Julian D

2017-12-19

Environmental consequences of electricity generation are often determined using average emission factors. However, as different interventions are incrementally pursued in electricity systems, the resulting marginal change in emissions may differ from what one would predict based on system-average conditions. Here, we estimate average emission factors and marginal emission factors for CO 2 , SO 2 , and NO x from fossil and nonfossil generators in the Midcontinent Independent System Operator (MISO) region during years 2007-2016. We analyze multiple spatial scales (all MISO; each of the 11 MISO states; each utility; each generator) and use MISO data to characterize differences between the two emission factors (average; marginal). We also explore temporal trends in emissions factors by hour, day, month, and year, as well as the differences that arise from including only fossil generators versus total generation. We find, for example, that marginal emission factors are generally higher during late-night and early morning compared to afternoons. Overall, in MISO, average emission factors are generally higher than marginal estimates (typical difference: ∼20%). This means that the true environmental benefit of an energy efficiency program may be ∼20% smaller than anticipated if one were to use average emissions factors. Our analysis can usefully be extended to other regions to support effective near-term technical, policy and investment decisions based on marginal rather than only average emission factors.

Estimating cumulative effects of clearcutting on stream temperatures

USGS Publications Warehouse

Bartholow, J.M.

2000-01-01

The Stream Segment Temperature Model was used to estimate cumulative effects of large-scale timber harvest on stream temperature. Literature values were used to create parameters for the model for two hypothetical situations, one forested and the other extensively clearcut. Results compared favorably with field studies of extensive forest canopy removal. The model provided insight into the cumulative effects of clearcutting. Change in stream shading was, as expected, the most influential factor governing increases in maximum daily water temperature, accounting for 40% of the total increase. Altered stream width was found to be more influential than changes to air temperature. Although the net effect from clearcutting was a 4oC warming, increased wind and reduced humidity tended to cool the stream. Temperature increases due to clearcutting persisted 10 km downstream into an unimpacted forest segment of the hypothetical stream, but those increases were moderated by cooler equilibrium conditions downstream. The model revealed that it is a complex set of factors, not single factors such as shade or air temperature, that governs stream temperature dynamics.

Hospital survey on patient safety culture: psychometric analysis on a Scottish sample.

PubMed

Sarac, Cakil; Flin, Rhona; Mearns, Kathryn; Jackson, Jeanette

2011-10-01

To investigate the psychometric properties of the Hospital Survey on Patient Safety Culture on a Scottish NHS data set. The data were collected from 1969 clinical staff (estimated 22% response rate) from one acute hospital from each of seven Scottish Health boards. Using a split-half validation technique, the data were randomly split; an exploratory factor analysis was conducted on the calibration data set, and confirmatory factor analyses were conducted on the validation data set to investigate and check the original US model fit in a Scottish sample. Following the split-half validation technique, exploratory factor analysis results showed a 10-factor optimal measurement model. The confirmatory factor analyses were then performed to compare the model fit of two competing models (10-factor alternative model vs 12-factor original model). An S-B scaled χ(2) square difference test demonstrated that the original 12-factor model performed significantly better in a Scottish sample. Furthermore, reliability analyses of each component yielded satisfactory results. The mean scores on the climate dimensions in the Scottish sample were comparable with those found in other European countries. This study provided evidence that the original 12-factor structure of the Hospital Survey on Patient Safety Culture scale has been replicated in this Scottish sample. Therefore, no modifications are required to the original 12-factor model, which is suggested for use, since it would allow researchers the possibility of cross-national comparisons.

Factors related to suicidal ideation in stroke patients in South Korea.

PubMed

Park, Eun-Young; Kim, Jung-Hee

2016-01-01

Suicide rates in Korea have increased dramatically. Stroke is considered one of the most debilitating neurological disorders, resulting in physical impairment, disability, and death. The present study attempted to examine factors related to suicidal ideation in community-dwelling stroke patients. The Korea Welfare Panel Study was used to investigate the relationship between demographic and psychological variables and suicidal ideation among these individuals. Depression was assessed using the Center for Epidemiological Studies Depression Scale 11 (CES-D-11). Self-esteem was assessed using Rosenberg's Self-Esteem Scale. The prevalence of suicidal thought among stroke patients was estimated at 13.99%. Multiple logistic regression analysis indicated that both older age and depression were significant independent risk factors for suicidal ideation. High-priority health care plans can prevent suicide in stroke patients suffering from depression. Assessing risk for suicide and monitoring the high-risk group is integral to health care. Stroke patients with depression, particularly older patients, would be prime targets for suicide intervention programs.

Racism in digital era: Development and initial validation of the Perceived Online Racism Scale (PORS v1.0).

PubMed

Keum, Brian TaeHyuk; Miller, Matthew J

2017-04-01

The purpose of this study was to develop the Perceived Online Racism Scale (PORS) to assess perceived online racist interpersonal interactions and exposure to online racist content among people of color. Items were developed through a multistage process involving a comprehensive literature review, focus-groups, qualitative data collection, and survey of online racism experiences. Based on a sample of 1,023 racial minority participants, exploratory and confirmatory factor analyses provided support for a 30-item bifactor model accounted by the general factor and the following 3 specific factors: (a) personal experience of racial cyber-aggression, (b) vicarious exposure to racial cyber-aggression, and (c) online-mediated exposure to racist reality. The PORS demonstrated measurement invariance across racial/ethnic groups in our sample. Internal reliability estimates for the total and subscale scores of the PORS were above .88 and the 4-week test-retest reliability was adequate. Limitations and future directions for research are discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Short Personality and Life Event scale for detection of suicide attempters.

PubMed

Artieda-Urrutia, Paula; Delgado-Gómez, David; Ruiz-Hernández, Diego; García-Vega, Juan Manuel; Berenguer, Nuria; Oquendo, Maria A; Blasco-Fontecilla, Hilario

2015-01-01

To develop a brief and reliable psychometric scale to identify individuals at risk for suicidal behaviour. Case-control study. 182 individuals (61 suicide attempters, 57 psychiatric controls, and 64 psychiatrically healthy controls) aged 18 or older, admitted to the Emergency Department at Puerta de Hierro University Hospital in Madrid, Spain. All participants completed a form including their socio-demographic and clinical characteristics, and the Personality and Life Events scale (27 items). To assess Axis I diagnoses, all psychiatric patients (including suicide attempters) were administered the Mini International Neuropsychiatric Interview. Descriptive statistics were computed for the socio-demographic factors. Additionally, χ(2) independence tests were applied to evaluate differences in socio-demographic and clinical variables, and the Personality and Life Events scale between groups. A stepwise linear regression with backward variable selection was conducted to build the Short Personality Life Event (S-PLE) scale. In order to evaluate the accuracy, a ROC analysis was conducted. The internal reliability was assessed using Cronbach's α, and the external reliability was evaluated using a test-retest procedure. The S-PLE scale, composed of just 6 items, showed good performance in discriminating between medical controls, psychiatric controls and suicide attempters in an independent sample. For instance, the S-PLE scale discriminated between past suicide and past non-suicide attempters with sensitivity of 80% and specificity of 75%. The area under the ROC curve was 88%. A factor analysis extracted only one factor, revealing a single dimension of the S-PLE scale. Furthermore, the S-PLE scale provides values of internal and external reliability between poor (test-retest: 0.55) and acceptable (Cronbach's α: 0.65) ranges. Administration time is about one minute. The S-PLE scale is a useful and accurate instrument for estimating the risk of suicidal behaviour in settings where the time is scarce. Copyright © 2015 SEP y SEPB. Published by Elsevier España. All rights reserved.

Reliability and validity of the Student Perceptions of School Cohesion Scale in a sample of Salvadoran secondary school students

PubMed Central

2009-01-01

Background Despite a growing body of research from the United States and other industrialized countries on the inverse association between supportive social relationships in the school and youth risk behavior engagement, research on the measurement of supportive school social relationships in Central America is limited. We examined the psychometric properties of the Student Perceptions of School Cohesion (SPSC) scale, a 10-item scale that asks students to rate with a 5-point Likert-type response scale their perceptions of the school social environment, in a sample of public secondary school students (mean age = 15 years) living in central El Salvador. Methods Students (n = 982) completed a self-administered questionnaire that included the SPSC scale along with measures of youth health risk behaviors based on the Center for Disease Control and Prevention's Youth Risk Behavior Survey. Exploratory factor analysis was used to assess the factor structure of the scale, and two internal consistency estimates of reliability were computed. Construct validity was assessed by examining whether students who reported low school cohesion were significantly more likely to report physical fighting and illicit drug use. Results Results indicated that the SPSC scale has three latent factors, which explained 61.6% of the variance: supportive school relationships, student-school connectedness, and student-teacher connectedness. The full scale and three subscales had good internal consistency (rs = .87 and α = .84 for the full scale; rs and α between .71 and .75 for the three subscales). Significant associations were found between the full scale and all three subscales with physical fighting (p ≤ .001) and illicit drug use (p < .05). Conclusion Findings provide evidence of reliability and validity of the SPSC for the measurement of supportive school relationships in Latino adolescents living in El Salvador. These findings provide a foundation for further research on school cohesion and health risk behavior in Latino adolescents living in the U.S. and other Latin American countries. PMID:19939259

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

Mishra, U.; Riley, W. J.

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing the heterogeneity of terrestrial hydrological and biogeochemical processes in Earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a data setmore » with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales ( s = 100, 200, and 500 m and 1, 2, 5, and 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions ( R 2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 m to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98 % of variability in the variance of SOC stocks. We found moderately accurate linear relationships between mean and higher-order moments of predicted SOC stocks ( R 2 ∼ 0.55–0.63). Current ESMs operate at coarse spatial scales (50–100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks could improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.« less

Cooperation without culture? The null effect of generalized trust on intentional homicide: a cross-national panel analysis, 1995-2009.

PubMed

Robbins, Blaine

2013-01-01

Sociologists, political scientists, and economists all suggest that culture plays a pivotal role in the development of large-scale cooperation. In this study, I used generalized trust as a measure of culture to explore if and how culture impacts intentional homicide, my operationalization of cooperation. I compiled multiple cross-national data sets and used pooled time-series linear regression, single-equation instrumental-variables linear regression, and fixed- and random-effects estimation techniques on an unbalanced panel of 118 countries and 232 observations spread over a 15-year time period. Results suggest that culture and large-scale cooperation form a tenuous relationship, while economic factors such as development, inequality, and geopolitics appear to drive large-scale cooperation.

Newly graduated nurses' occupational commitment and its associations with professional competence and work-related factors.

PubMed

Numminen, Olivia; Leino-Kilpi, Helena; Isoaho, Hannu; Meretoja, Riitta

2016-01-01

To explore newly graduated nurses' occupational commitment and its associations with their self-assessed professional competence and other work-related factors. As a factor affecting nurse turnover, newly graduated nurses' occupational commitment and its associations with work-related factors needs exploring to retain adequate workforce. Nurses' commitment has mainly been studied as organisational commitment, but newly graduated nurses' occupational commitment and its association with work-related factors needs further studying. This study used descriptive, cross-sectional, correlation design. A convenience sample of 318 newly graduated nurses in Finland participated responding to an electronic questionnaire. Statistical software, NCSS version 9, was used in data analysis. Frequencies, percentages, ranges, means and standard deviations summarised the data. Multivariate Analyses of Variance estimated associations between occupational commitment and work-related variables. IBM SPSS Amos version 22 estimated the model fit of Occupational Commitment Scale and Nurse Competence Scale. Newly graduated nurses' occupational commitment was good, affective commitment reaching the highest mean score. There was a significant difference between the nurse groups in favour of nurses at higher competence levels in all subscales except in limited alternatives occupational commitment. Multivariate analyses revealed significant associations between subscales of commitment and competence, turnover intentions, job satisfaction, earlier professional education and work sector, competence counting only through affective dimension. The association between occupational commitment and low turnover intentions and satisfaction with nursing occupation was strong. Higher general competence indicated higher overall occupational commitment. Managers' recognition of the influence of all dimensions of occupational commitment in newly graduated nurses' professional development is important. Follow-up studies of newly graduated nurses' commitment, its relationship with quality care, managers' role in enhancing commitment and evaluation of the impact of interventions on improving commitment need further studying. © 2015 John Wiley & Sons Ltd.

Bulk canopy resistance: Modeling for the estimation of actual evapotranspiration of maize

NASA Astrophysics Data System (ADS)

Gharsallah, O.; Corbari, C.; Mancini, M.; Rana, G.

2009-04-01

Due to the scarcity of water resources, the correct evaluation of water losses by the crops as evapotranspiration (ET) is very important in irrigation management. This work presents a model for estimating actual evapotranspiration on hourly and daily scales of maize crop grown in well water condition in the Lombardia Region (North Italy). The maize is a difficult crop to model from the soil-canopy-atmosphere point of view, due to its very complex architecture and big height. The present ET model is based on the Penman-Monteith equation using Katerji and Perrier approach for modelling the variable canopy resistance value (rc). In fact rc is a primary factor in the evapotranspiration process and needs to be accurately estimated. Furthermore, ET also has an aerodynamic component, hence it depends on multiple factors such as meteorological variables and crop water condition. The proposed approach appears through a linear model in which rc depends on climate variables and aerodynamic resistance [rc/ra = f(r*/ra)] where ra is the aerodynamic resistance, function of wind speed and crop height, and r* is called "critical" or "climatic" resistance. Here, under humid climate, the model has been applied with good results at both hourly and daily scales. In this study, the reached good accuracy shows that the model worked well and are clearly more accurate than those obtained by using the more diffuse and known standard FAO 56 method for well watered and stressed crops.

Validity and Reliability of a New Instrument to Measure Cancer-Related Fatigue in Adolescents

PubMed Central

Hinds, Pamela S.; Hockenberry, Marilyn; Tong, Xin; Rai, Shesh N.; Gattuso, Jamie S.; McCarthy, Kathleen; Pui, Ching-Hon; Srivastava, Deo Kumar

2008-01-01

Adolescents undergoing treatment for cancer rate fatigue as their most prevalent and intense cancer- and treatment-related effect. Parents and staff rate it similarly. Despite its reported prevalence, intensity, and distressing effects, cancer-related fatigue in adolescents is not routinely assessed during or after cancer treatment. We contend that the insufficient clinical attention is primarily due to the lack of a reliable and valid self-report instrument with which adolescent cancer-related fatigue can be measured. Our aim was to determine the reliability and construct validity of a new instrument and its ability to measure change in fatigue over time. Initial testing involved 64 adolescents undergoing curative treatment of cancer who completed the Fatigue Scale-Adolescent (FS-A) at two to four key points in treatment in one of four studies. Internal consistency estimates ranged from 0.67 to 0.95. Validity estimates involving the FS-A with the parent version ranged from 0.13 to 0.76; estimates involving the staff version and the Reynolds Depression Scale were 0.27 and 0.87 respectively. Additional validity findings included significant fatigue differences between anemic and non-anemic patients (P = 0.042) and the emergence of four factors in an exploratory factor analysis. Findings further indicate that the FS-A can be used to measure change over time (t = 2.55, P <0.01). In summary, the FS-A has moderate to strong reliability and impressive validity coefficients for a new research instrument. PMID:17629669

Temporal variation of traffic on highways and the development of accurate temporal allocation factors for air pollution analyses

NASA Astrophysics Data System (ADS)

Batterman, Stuart; Cook, Richard; Justin, Thomas

2015-04-01

Traffic activity encompasses the number, mix, speed and acceleration of vehicles on roadways. The temporal pattern and variation of traffic activity reflects vehicle use, congestion and safety issues, and it represents a major influence on emissions and concentrations of traffic-related air pollutants. Accurate characterization of vehicle flows is critical in analyzing and modeling urban and local-scale pollutants, especially in near-road environments and traffic corridors. This study describes methods to improve the characterization of temporal variation of traffic activity. Annual, monthly, daily and hourly temporal allocation factors (TAFs), which describe the expected temporal variation in traffic activity, were developed using four years of hourly traffic activity data recorded at 14 continuous counting stations across the Detroit, Michigan, U.S. region. Five sites also provided vehicle classification. TAF-based models provide a simple means to apportion annual average estimates of traffic volume to hourly estimates. The analysis shows the need to separate TAFs for total and commercial vehicles, and weekdays, Saturdays, Sundays and observed holidays. Using either site-specific or urban-wide TAFs, nearly all of the variation in historical traffic activity at the street scale could be explained; unexplained variation was attributed to adverse weather, traffic accidents and construction. The methods and results presented in this paper can improve air quality dispersion modeling of mobile sources, and can be used to evaluate and model temporal variation in ambient air quality monitoring data and exposure estimates.

Temporal variation of traffic on highways and the development of accurate temporal allocation factors for air pollution analyses

PubMed Central

Batterman, Stuart; Cook, Richard; Justin, Thomas

2015-01-01

Traffic activity encompasses the number, mix, speed and acceleration of vehicles on roadways. The temporal pattern and variation of traffic activity reflects vehicle use, congestion and safety issues, and it represents a major influence on emissions and concentrations of traffic-related air pollutants. Accurate characterization of vehicle flows is critical in analyzing and modeling urban and local-scale pollutants, especially in near-road environments and traffic corridors. This study describes methods to improve the characterization of temporal variation of traffic activity. Annual, monthly, daily and hourly temporal allocation factors (TAFs), which describe the expected temporal variation in traffic activity, were developed using four years of hourly traffic activity data recorded at 14 continuous counting stations across the Detroit, Michigan, U.S. region. Five sites also provided vehicle classification. TAF-based models provide a simple means to apportion annual average estimates of traffic volume to hourly estimates. The analysis shows the need to separate TAFs for total and commercial vehicles, and weekdays, Saturdays, Sundays and observed holidays. Using either site-specific or urban-wide TAFs, nearly all of the variation in historical traffic activity at the street scale could be explained; unexplained variation was attributed to adverse weather, traffic accidents and construction. The methods and results presented in this paper can improve air quality dispersion modeling of mobile sources, and can be used to evaluate and model temporal variation in ambient air quality monitoring data and exposure estimates. PMID:25844042

National scale biomass estimators for United States tree species

Treesearch

Jennifer C. Jenkins; David C. Chojnacky; Linda S. Heath; Richard A. Birdsey

2003-01-01

Estimates of national-scale forest carbon (C) stocks and fluxes are typically based on allometric regression equations developed using dimensional analysis techniques. However, the literature is inconsistent and incomplete with respect to large-scale forest C estimation. We compiled all available diameter-based allometric regression equations for estimating total...

DEKFIS user's guide: Discrete Extended Kalman Filter/Smoother program for aircraft and rotorcraft data consistency

NASA Technical Reports Server (NTRS)

1979-01-01

The computer program DEKFIS (discrete extended Kalman filter/smoother), formulated for aircraft and helicopter state estimation and data consistency, is described. DEKFIS is set up to pre-process raw test data by removing biases, correcting scale factor errors and providing consistency with the aircraft inertial kinematic equations. The program implements an extended Kalman filter/smoother using the Friedland-Duffy formulation.

Highlighting Uncertainty and Recommendations for Improvement of Black Carbon Biomass Fuel-Based Emission Inventories in the Indo-Gangetic Plain Region.

PubMed

Soneja, Sutyajeet I; Tielsch, James M; Khatry, Subarna K; Curriero, Frank C; Breysse, Patrick N

2016-03-01

Black carbon (BC) is a major contributor to hydrological cycle change and glacial retreat within the Indo-Gangetic Plain (IGP) and surrounding region. However, significant variability exists for estimates of BC regional concentration. Existing inventories within the IGP suffer from limited representation of rural sources, reliance on idealized point source estimates (e.g., utilization of emission factors or fuel-use estimates for cooking along with demographic information), and difficulty in distinguishing sources. Inventory development utilizes two approaches, termed top down and bottom up, which rely on various sources including transport models, emission factors, and remote sensing applications. Large discrepancies exist for BC source attribution throughout the IGP depending on the approach utilized. Cooking with biomass fuels, a major contributor to BC production has great source apportionment variability. Areas requiring attention tied to research of cookstove and biomass fuel use that have been recognized to improve emission inventory estimates include emission factors, particulate matter speciation, and better quantification of regional/economic sectors. However, limited attention has been given towards understanding ambient small-scale spatial variation of BC between cooking and non-cooking periods in low-resource environments. Understanding the indoor to outdoor relationship of BC emissions due to cooking at a local level is a top priority to improve emission inventories as many health and climate applications rely upon utilization of accurate emission inventories.

Color image lossy compression based on blind evaluation and prediction of noise characteristics

NASA Astrophysics Data System (ADS)

Ponomarenko, Nikolay N.; Lukin, Vladimir V.; Egiazarian, Karen O.; Lepisto, Leena

2011-03-01

The paper deals with JPEG adaptive lossy compression of color images formed by digital cameras. Adaptation to noise characteristics and blur estimated for each given image is carried out. The dominant factor degrading image quality is determined in a blind manner. Characteristics of this dominant factor are then estimated. Finally, a scaling factor that determines quantization steps for default JPEG table is adaptively set (selected). Within this general framework, two possible strategies are considered. A first one presumes blind estimation for an image after all operations in digital image processing chain just before compressing a given raster image. A second strategy is based on prediction of noise and blur parameters from analysis of RAW image under quite general assumptions concerning characteristics parameters of transformations an image will be subject to at further processing stages. The advantages of both strategies are discussed. The first strategy provides more accurate estimation and larger benefit in image compression ratio (CR) compared to super-high quality (SHQ) mode. However, it is more complicated and requires more resources. The second strategy is simpler but less beneficial. The proposed approaches are tested for quite many real life color images acquired by digital cameras and shown to provide more than two time increase of average CR compared to SHQ mode without introducing visible distortions with respect to SHQ compressed images.

Cross-Cultural Adaptation of the Profile Fitness Mapping Neck Questionnaire to Brazilian Portuguese: Internal Consistency, Reliability, and Construct and Structural Validity.

PubMed

Ferreira, Mariana Cândido; Björklund, Martin; Dach, Fabiola; Chaves, Thais Cristina

The purpose of this study was to adapt and evaluate the psychometric properties of the ProFitMap-neck to Brazilian Portuguese. The cross-cultural adaptation consisted of 5 stages, and 180 female patients with chronic neck pain participated in the study. A subsample (n = 30) answered the pretest, and another subsample (n = 100) answered the questionnaire a second time. Internal consistency, test-retest reliability, and construct validity (hypothesis testing and structural validity) were estimated. For construct validity, the scores of the questionnaire were correlated with the Neck Disability Index (NDI), and the Hospital Anxiety and Depression Scale (HADS), the Tampa Scale of Kinesiophobia (TSK), and the 36-item Short-Form Health Survey (SF-36). Internal consistency was determined by adequate Cronbach's α values (α > 0.70). Strong reliability was identified by high intraclass correlation coefficients (ICC > 0.75). Construct validity was identified by moderate and strong correlations of the Br-ProFitMap-neck with total NDI score (-0.56 50%, Kaiser-Meyer-Olkin index > 0.50, eigenvalue > 1, and factor loadings > 0.2. Br-ProFitMap-neck had adequate psychometric properties and can be used in clinical settings, as well as research, in patients with chronic neck pain. Copyright © 2017. Published by Elsevier Inc.

Psychometric properties of the communication skills attitude scale (CSAS) measure in a sample of Iranian medical students

PubMed Central

YAKHFOROSHHA, AFSANEH; SHIRAZI, MANDANA; YOUSEFZADEH, NASER; GHANBARNEJAD, AMIN; CHERAGHI, MOHAMMADALI; MOJTAHEDZADEH, RITA; MAHMOODI-BAKHTIARI, BEHROOZ; EMAMI, SEYED AMIR HOSSEIN

2018-01-01

Introduction: Communication skill (CS) has been regarded as one of the fundamental competencies for medical and other health care professionals. Student's attitude toward learning CS is a key factor in designing educational interventions. The original CSAS, as positive and negative subscales, was developed in the UK; however, there is no scale to measure these attitudes in Iran. The aim of this study was to assess the psychometric characteristic of the Communication Skills Attitude Scale (CSAS), in an Iranian context and to understand if it is a valid tool to assess attitude toward learning communication skills among health care professionals. Methods: Psychometric characteristics of the CSAS were assessed by using a cross-sectional design. In the current study, 410 medical students were selected using stratified sampling framework. The face validity of the scale was estimated through students and experts’ opinion. Content validity of CSAS was assessed qualitatively and quantitatively. Reliability was examined through two methods including Chronbach’s alpha coefficient and Intraclass Correlation of Coefficient (ICC). Construct validity of CSAS was assessed using confirmatory factor analysis (CFA) and explanatory factor analysis (PCA) followed by varimax rotation. Convergent and discriminant validity of the scale was measured through Spearman correlation. Statistical analysis was performed using SPSS 19 and EQS, 6.1. Results: The internal consistency and reproducibility of the total CSAS score were 0.84 (Cronbach’s alpha) and 0.81, which demonstrates an acceptable reliability of the questionnaire. The item-level content validity index (I-CVI) and the scale-level content validity index (S-CVI/Ave) demonstrated appropriate results: 0.97 and 0.94, respectively. An exploratory factor analysis (EFA) on the 25 items of the CSAS revealed 4-factor structure that all together explained %55 of the variance. Results of the confirmatory factor analysis indicated an acceptable goodness-of-fit between the model and the observed data. [χ2/df = 2.36, Comparative Fit Index (CFI) = 0.95, the GFI=0.96, Root Mean Square Error of Approximation (RMSEA) = 0.05]. Conclusion: The Persian version of CSAS is a multidimensional, valid and reliable tool for assessing attitudes towards communication skill among medical students. PMID:29344525

Use of modeled and satelite soil moisture to estimate soil erosion in central and southern Italy.

NASA Astrophysics Data System (ADS)

Termite, Loris Francesco; Massari, Christian; Todisco, Francesca; Brocca, Luca; Ferro, Vito; Bagarello, Vincenzo; Pampalone, Vincenzo; Wagner, Wolfgang

2016-04-01

This study presents an accurate comparison between two different approaches aimed to enhance accuracy of the Universal Soil Loss Equation (USLE) in estimating the soil loss at the single event time scale. Indeed it is well known that including the observed event runoff in the USLE improves its soil loss estimation ability at the event scale. In particular, the USLE-M and USLE-MM models use the observed runoff coefficient to correct the rainfall erosivity factor. In the first case, the soil loss is linearly dependent on rainfall erosivity, in the second case soil loss and erosivity are related by a power law. However, the measurement of the event runoff is not straightforward or, in some cases, possible. For this reason, the first approach used in this study is the use of Soil Moisture For Erosion (SM4E), a recent USLE-derived model in which the event runoff is replaced by the antecedent soil moisture. Three kinds of soil moisture datasets have been separately used: the ERA-Interim/Land reanalysis data of the European Centre for Medium-range Weather Forecasts (ECMWF); satellite retrievals from the European Space Agency - Climate Change Initiative (ESA-CCI); modeled data using a Soil Water Balance Model (SWBM). The second approach is the use of an estimated runoff rather than the observed. Specifically, the Simplified Continuous Rainfall-Runoff Model (SCRRM) is used to derive the runoff estimates. SCRMM requires soil moisture data as input and at this aim the same three soil moisture datasets used for the SM4E have been separately used. All the examined models have been calibrated and tested at the plot scale, using data from the experimental stations for the monitoring of the erosive processes "Masse" (Central Italy) and "Sparacia" (Southern Italy). Climatic data and runoff and soil loss measures at the event time scale are available for the period 2008-2013 at Masse and for the period 2002-2013 at Sparacia. The results show that both the approaches can provide better results than the USLE. Specifically, the SM4E model has proven to be particularly effective at Masse, providing the best soil loss estimations, especially when the modeled soil moisture is used. In this case, the RSR index (ratio between the Root Mean Square Error and the Observed Standard deviation) is equal to 0.94. Instead, the SCRRM is able to better estimate the event runoff at Sparacia than at Masse, thus resulting in good performances of the USLE-derived models using the estimated runoff; however, even at Sparacia the SM4E with modeled soil moisture gives the better soil loss estimates, with RSR = 0.54. These results open an interesting scenario in the use of empirical models to determine soil loss at a large scale, since soil moisture is a not only a simple in situ measurement, but only a widely available information on a global scale from remote sensing.

Mapping the geographic distribution of canopy species communities in lowland Amazon rainforest with CAO-AToMS (Invited)

NASA Astrophysics Data System (ADS)

Feret, J.; Asner, G. P.

2013-12-01

Mapping regional canopy diversity will greatly advance our understanding as well as the conservation of tropical rainforests. Changes in species composition across space and time are particularly important to understand the influence of climate, human activity and environmental factors on these ecosystems, but to date such monitoring is extremely challenging and is facing a scale gap between small-scale, highly detailed field studies and large-scale, low-resolution satellite observations. Advances were recently made in the field of spectroscopic imagery for the estimation of canopy alpha-diversity, and an original approach based on the segmentation of the spectral space proved its ability to estimate Shannon diversity index with unprecedented accuracy. We adapted this method in order to estimate spectral dissimilarity across landscape as a proxy for changes in species composition. We applied this approach and mapped species composition over four sites located in lowland rainforest of Peruvian Amazon. This study was based on spectroscopic imagery acquired using the Carnegie Airborne Observatory (CAO) Airborne Taxonomic Mapping System (AToMS), operating a unique sensor combining the fine spectral and spatial resolution required for such task. We obtained accurate estimation of Bray-Curtis distance between pairs of plots, which is the most commonly used metric to estimate dissimilarity in species composition (n=497 pairs, r=0.63). The maps of species composition were then compared to topo-hydrographic properties. Our results indicated a strong shift in species composition and community diversity between floodplain and terra firme terrain conditions as well as a significantly higher diversity of species communities within Amazonian floodplains. These results pave the way for global mapping of tropical canopy diversity at fine geographic resolution.

Evaluation of bio-optical algorithms to remotely sense marine primary production from space

NASA Technical Reports Server (NTRS)

Berthelot, Beatrice; Deschamps, Pierre-Yves

1994-01-01

In situ bio-optical measurements from several oceanographic campaigns were analyzed to derive a direct relationship between water column primary production P (sub t) ocean color as expressed by the ratio of reflectances R (sub 1) at 440 nm and R (sub 3) at 550 nm and photosynthetically available radiation (PAR). The study is restricted to the Morel case I waters for which the following algorithm is proposed: log (P(sub f)) = -4.286 - 1.390 log (R(sub 1)/R(sub3)) + 0.621 log (PAR), with P(sub t) in g C m(exp -2)/d and PAR in J m(exp -2)/d. Using this algorithm the rms accuracy of primary production estimate is 0.17 on a logarithmic scale, i.e., a factor of 1.5. Using spectral reflectance measurements in the entire visible spectral range, the central wavelength, spectral bandwidth, and radiometric noise level requirements are investigated for the channels to be used by an ocean color space mission dedicated to estimating global marine primary production and the associated carbon fluxes. Nearly all the useful information is provided by two channels centered at 440 nm and 550 nm, but the accuracy of primary production estimate appears weakly sensitive to spectral bandwidth, which, consequently, may be enlarged by several tens of nanometers. The sensitivity to radiometric noise, on the contrary, is strong, and a noise equivalent reflectance of 0.005 degraded the accuracy on the primary production estimate by a factor 2 (0.14-0.25 on a logarithmic scale). The results should be applicable to evaluating the primary production of oligotrophic and mesotrophic waters, which constitute most of the open ocean.

Remote sensing of exposure to NO2: Satellite versus ground-based measurement in a large urban area

NASA Astrophysics Data System (ADS)

Bechle, Matthew J.; Millet, Dylan B.; Marshall, Julian D.

2013-04-01

Remote sensing may be a useful tool for exploring spatial variability of air pollution exposure within an urban area. To evaluate the extent to which satellite data from the Ozone Monitoring Instrument (OMI) can resolve urban-scale gradients in ground-level nitrogen dioxide (NO2) within a large urban area, we compared estimates of surface NO2 concentrations derived from OMI measurements and US EPA ambient monitoring stations. OMI, aboard NASA's Aura satellite, provides daily afternoon (˜13:30 local time) measurements of NO2 tropospheric column abundance. We used scaling factors (surface-to-column ratios) to relate satellite column measurements to ground-level concentrations. We compared 4138 sets of paired data for 25 monitoring stations in the South Coast Air Basin of California for all of 2005. OMI measurements include more data gaps than the ground monitors (60% versus 5% of available data, respectively), owing to cloud contamination and imposed limits on pixel size. The spatial correlation between OMI columns and corrected in situ measurements is strong (r = 0.93 for annual average data), indicating that the within-urban spatial signature of surface NO2 is well resolved by the satellite sensor. Satellite-based surface estimates employing scaling factors from an urban model provide a reliable measure (annual mean bias: -13%; seasonal mean bias: <1% [spring] to -22% [fall]) of fine-scale surface NO2. We also find that OMI provides good spatial density in the study region (average area [km2] per measurement: 730 for the satellite sensor vs. 1100 for the monitors). Our findings indicate that satellite observations of NO2 from the OMI sensor provide a reliable measure of spatial variability in ground-level NO2 exposure for a large urban area.

Quantify the Biophysical and Socioeconomic Drivers of Changes in Forest and Agricultural Land in South and Southeast Asia

NASA Astrophysics Data System (ADS)

Xu, X.; Jain, A. K.; Calvin, K. V.

2017-12-01

Due to the rapid socioeconomic development and biophysical factors, South and Southeast Asia (SSEA) has become a hotspot region of land use and land cover changes (LULCCs) in past few decades. Uncovering the drivers of LULCC is crucial for improving the understanding of LULCC processes. Due to the differences from spatiotemporal scales, methods and data sources in previous studies, the quantitative relationships between the LULCC activities and biophysical and socioeconomic drivers at the regional scale of SSEA have not been established. Here we present a comprehensive estimation of the biophysical and socioeconomic drivers of the major LULCC activities in SSEA: changes in forest and agricultural land. We used the Climate Change Initiative land cover data developed by European Space Agency to reveal the dynamics of forest and agricultural land from 1992 to 2015. Then we synthesized 200 publications about LULCC drivers at different spatial scales in SSEA to identify the major drivers of these LULCC activities. Corresponding representative variables of the major drivers were collected. The geographically weighted regression was employed to assess the spatiotemporally heterogeneous drivers of LULCC. Moreover, we validated our results with some national level case studies in SSEA. The results showed that both biophysical conditions such as terrain, soil, and climate, and socioeconomic factors such as migration, poverty, and economy played important roles in driving the changes of forest and agricultural land. The major drivers varied in different locations and periods. Our study integrated the bottom-up knowledge from local scale case studies with the top-down estimation of LULCC drivers, therefore generated more accurate and credible results. The identified biophysical and socioeconomic components could be used to improve the LULCC modelling and projection.

Developing an African youth psychosocial assessment: an application of item response theory.

PubMed

Betancourt, Theresa S; Yang, Frances; Bolton, Paul; Normand, Sharon-Lise

2014-06-01

This study aimed to refine a dimensional scale for measuring psychosocial adjustment in African youth using item response theory (IRT). A 60-item scale derived from qualitative data was administered to 667 war-affected adolescents (55% female). Exploratory factor analysis (EFA) determined the dimensionality of items based on goodness-of-fit indices. Items with loadings less than 0.4 were dropped. Confirmatory factor analysis (CFA) was used to confirm the scale's dimensionality found under the EFA. Item discrimination and difficulty were estimated using a graded response model for each subscale using weighted least squares means and variances. Predictive validity was examined through correlations between IRT scores (θ) for each subscale and ratings of functional impairment. All models were assessed using goodness-of-fit and comparative fit indices. Fisher's Information curves examined item precision at different underlying ranges of each trait. Original scale items were optimized and reconfigured into an empirically-robust 41-item scale, the African Youth Psychosocial Assessment (AYPA). Refined subscales assess internalizing and externalizing problems, prosocial attitudes/behaviors and somatic complaints without medical cause. The AYPA is a refined dimensional assessment of emotional and behavioral problems in African youth with good psychometric properties. Validation studies in other cultures are recommended. Copyright © 2014 John Wiley & Sons, Ltd.

Vibrational spectra and ab initio analysis of tert-butyl, trimethylsilyl, and trimethylgermyl derivatives of 3,3-dimethylcyclopropene II. 3,3-Dimethyl-1,2-bis(trimethylsilyl)cyclopropene

NASA Astrophysics Data System (ADS)

Panchenko, Yu. N.; De Maré, G. R.; Abramenkov, A. V.; Baird, M. S.; Tverezovsky, V. V.; Nizovtsev, A. V.; Bolesov, I. G.

2003-07-01

The IR and Raman spectra of 3,3-dimethyl-1,2-bis(trimethylsilyl)cyclopropene (I) (synthesised using standard procedures) were measured in the liquid phase. Total geometry optimisation was performed at the HF/6-31G* level. The HF/6-31G*//HF/6-31G* quantum mechanical force field (QMFF) was calculated and used to determine the theoretical fundamental vibrational frequencies, their predicted IR intensities, Raman activities, and Raman depolarisation ratios. Using Pulay's scaling method and the theoretical molecular geometry, the QMFF of I was scaled by a set of scaling factors used previously for 3,3-dimethyl-1,2-bis(tert-butyl)cyclopropene (17 scale factors for a 105-dimensional problem). The scaled QMFF obtained was used to solve the vibrational problem. The quantum mechanical values of the Raman activities were converted to differential Raman cross sections. The figures for the experimental and theoretical Raman and IR spectra are presented. Assignments of the experimental vibrational spectra of I are given. They take into account the calculated potential energy distribution and the correlation between the estimations of the experimental IR and Raman intensities and Raman depolarisation ratios and the corresponding theoretical values (including Raman cross sections) calculated using the unscaled QMFF.

Developing an African youth psychosocial assessment: an application of item response theory

PubMed Central

BETANCOURT, THERESA S.; YANG, FRANCES; BOLTON, PAUL; NORMAND, SHARON-LISE

2014-01-01

This study aimed to refine a dimensional scale for measuring psychosocial adjustment in African youth using item response theory (IRT). A 60-item scale derived from qualitative data was administered to 667 war-affected adolescents (55% female). Exploratory factor analysis (EFA) determined the dimensionality of items based on goodness-of-fit indices. Items with loadings less than 0.4 were dropped. Confirmatory factor analysis (CFA) was used to confirm the scale's dimensionality found under the EFA. Item discrimination and difficulty were estimated using a graded response model for each subscale using weighted least squares means and variances. Predictive validity was examined through correlations between IRT scores (θ) for each subscale and ratings of functional impairment. All models were assessed using goodness-of-fit and comparative fit indices. Fisher's Information curves examined item precision at different underlying ranges of each trait. Original scale items were optimized and reconfigured into an empirically-robust 41-item scale, the African Youth Psychosocial Assessment (AYPA). Refined subscales assess internalizing and externalizing problems, prosocial attitudes/behaviors and somatic complaints without medical cause. The AYPA is a refined dimensional assessment of emotional and behavioral problems in African youth with good psychometric properties. Validation studies in other cultures are recommended. PMID:24478113

Calibrating recruitment estimates for mourning doves from harvest age ratios

USGS Publications Warehouse

Miller, David A.; Otis, David L.

2010-01-01

We examined results from the first national-scale effort to estimate mourning dove (Zenaida macroura) age ratios and developed a simple, efficient, and generalizable methodology for calibrating estimates. Our method predicted age classes of unknown-age wings based on backward projection of molt distributions from fall harvest collections to preseason banding. We estimated 1) the proportion of late-molt individuals in each age class, and 2) the molt rates of juvenile and adult birds. Monte Carlo simulations demonstrated our estimator was minimally biased. We estimated model parameters using 96,811 wings collected from hunters and 42,189 birds banded during preseason from 68 collection blocks in 22 states during the 2005–2007 hunting seasons. We also used estimates to derive a correction factor, based on latitude and longitude of samples, which can be applied to future surveys. We estimated differential vulnerability of age classes to harvest using data from banded birds and applied that to harvest age ratios to estimate population age ratios. Average, uncorrected age ratio of known-age wings for states that allow hunting was 2.25 (SD 0.85) juveniles:adult, and average, corrected ratio was 1.91 (SD 0.68), as determined from harvest age ratios from an independent sample of 41,084 wings collected from random hunters in 2007 and 2008. We used an independent estimate of differential vulnerability to adjust corrected harvest age ratios and estimated the average population age ratio as 1.45 (SD 0.52), a direct measure of recruitment rates. Average annual recruitment rates were highest east of the Mississippi River and in the northwestern United States, with lower rates between. Our results demonstrate a robust methodology for calibrating recruitment estimates for mourning doves and represent the first large-scale estimates of recruitment for the species. Our methods can be used by managers to correct future harvest survey data to generate recruitment estimates for use in formulating harvest management strategies.

Assessing network scale-up estimates for groups most at risk of HIV/AIDS: evidence from a multiple-method study of heavy drug users in Curitiba, Brazil.

PubMed

Salganik, Matthew J; Fazito, Dimitri; Bertoni, Neilane; Abdo, Alexandre H; Mello, Maeve B; Bastos, Francisco I

2011-11-15

One of the many challenges hindering the global response to the human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) epidemic is the difficulty of collecting reliable information about the populations most at risk for the disease. Thus, the authors empirically assessed a promising new method for estimating the sizes of most at-risk populations: the network scale-up method. Using 4 different data sources, 2 of which were from other researchers, the authors produced 5 estimates of the number of heavy drug users in Curitiba, Brazil. The authors found that the network scale-up and generalized network scale-up estimators produced estimates 5-10 times higher than estimates made using standard methods (the multiplier method and the direct estimation method using data from 2004 and 2010). Given that equally plausible methods produced such a wide range of results, the authors recommend that additional studies be undertaken to compare estimates based on the scale-up method with those made using other methods. If scale-up-based methods routinely produce higher estimates, this would suggest that scale-up-based methods are inappropriate for populations most at risk of HIV/AIDS or that standard methods may tend to underestimate the sizes of these populations.

Carbon storage in Chinese grassland ecosystems: Influence of different integrative methods.

PubMed

Ma, Anna; He, Nianpeng; Yu, Guirui; Wen, Ding; Peng, Shunlei

2016-02-17

The accurate estimate of grassland carbon (C) is affected by many factors at the large scale. Here, we used six methods (three spatial interpolation methods and three grassland classification methods) to estimate C storage of Chinese grasslands based on published data from 2004 to 2014, and assessed the uncertainty resulting from different integrative methods. The uncertainty (coefficient of variation, CV, %) of grassland C storage was approximately 4.8% for the six methods tested, which was mainly determined by soil C storage. C density and C storage to the soil layer depth of 100 cm were estimated to be 8.46 ± 0.41 kg C m(-2) and 30.98 ± 1.25 Pg C, respectively. Ecosystem C storage was composed of 0.23 ± 0.01 (0.7%) above-ground biomass, 1.38 ± 0.14 (4.5%) below-ground biomass, and 29.37 ± 1.2 (94.8%) Pg C in the 0-100 cm soil layer. Carbon storage calculated by the grassland classification methods (18 grassland types) was closer to the mean value than those calculated by the spatial interpolation methods. Differences in integrative methods may partially explain the high uncertainty in C storage estimates in different studies. This first evaluation demonstrates the importance of multi-methodological approaches to accurately estimate C storage in large-scale terrestrial ecosystems.

The assessment of spatial distribution of soil salinity risk using neural network.

PubMed

Akramkhanov, Akmal; Vlek, Paul L G

2012-04-01

Soil salinity in the Aral Sea Basin is one of the major limiting factors of sustainable crop production. Leaching of the salts before planting season is usually a prerequisite for crop establishment and predetermined water amounts are applied uniformly to fields often without discerning salinity levels. The use of predetermined water amounts for leaching perhaps partly emanate from the inability of conventional soil salinity surveys (based on collection of soil samples, laboratory analyses) to generate timely and high-resolution salinity maps. This paper has an objective to estimate the spatial distribution of soil salinity based on readily or cheaply obtainable environmental parameters (terrain indices, remote sensing data, distance to drains, and long-term groundwater observation data) using a neural network model. The farm-scale (∼15 km(2)) results were used to upscale soil salinity to a district area (∼300 km(2)). The use of environmental attributes and soil salinity relationships to upscale the spatial distribution of soil salinity from farm to district scale resulted in the estimation of essentially similar average soil salinity values (estimated 0.94 vs. 1.04 dS m(-1)). Visual comparison of the maps suggests that the estimated map had soil salinity that was uniform in distribution. The upscaling proved to be satisfactory; depending on critical salinity threshold values, around 70-90% of locations were correctly estimated.

Lake Erie Yellow perch age estimation based on three structures: Precision, processing times, and management implications

USGS Publications Warehouse

Vandergoot, C.S.; Bur, M.T.; Powell, K.A.

2008-01-01

Yellow perch Perca flavescens support economically important recreational and commercial fisheries in Lake Erie and are intensively managed. Age estimation represents an integral component in the management of Lake Erie yellow perch stocks, as age-structured population models are used to set safe harvest levels on an annual basis. We compared the precision associated with yellow perch (N = 251) age estimates from scales, sagittal otoliths, and anal spine sections and evaluated the time required to process and estimate age from each structure. Three readers of varying experience estimated ages. The precision (mean coefficient of variation) of estimates among readers was 1% for sagittal otoliths, 5-6% for anal spines, and 11-13% for scales. Agreement rates among readers were 94-95% for otoliths, 71-76% for anal spines, and 45-50% for scales. Systematic age estimation differences were evident among scale and anal spine readers; less-experienced readers tended to underestimate ages of yellow perch older than age 4 relative to estimates made by an experienced reader. Mean scale age tended to underestimate ages of age-6 and older fish relative to otolith ages estimated by an experienced reader. Total annual mortality estimates based on scale ages were 20% higher than those based on otolith ages; mortality estimates based on anal spine ages were 4% higher than those based on otolith ages. Otoliths required more removal and preparation time than scales and anal spines, but age estimation time was substantially lower for otoliths than for the other two structures. We suggest the use of otoliths or anal spines for age estimation in yellow perch (regardless of length) from Lake Erie and other systems where precise age estimates are necessary, because age estimation errors resulting from the use of scales could generate incorrect management decisions. ?? Copyright by the American Fisheries Society 2008.

Evaluating a Local Ensemble Transform Kalman Filter snow cover data assimilation method to estimate SWE within a high-resolution hydrologic modeling framework across Western US mountainous regions

NASA Astrophysics Data System (ADS)

Oaida, C. M.; Andreadis, K.; Reager, J. T., II; Famiglietti, J. S.; Levoe, S.

2017-12-01

Accurately estimating how much snow water equivalent (SWE) is stored in mountainous regions characterized by complex terrain and snowmelt-driven hydrologic cycles is not only greatly desirable, but also a big challenge. Mountain snowpack exhibits high spatial variability across a broad range of spatial and temporal scales due to a multitude of physical and climatic factors, making it difficult to observe or estimate in its entirety. Combing remotely sensed data and high resolution hydrologic modeling through data assimilation (DA) has the potential to provide a spatially and temporally continuous SWE dataset at horizontal scales that capture sub-grid snow spatial variability and are also relevant to stakeholders such as water resource managers. Here, we present the evaluation of a new snow DA approach that uses a Local Ensemble Transform Kalman Filter (LETKF) in tandem with the Variable Infiltration Capacity macro-scale hydrologic model across the Western United States, at a daily temporal resolution, and a horizontal resolution of 1.75 km x 1.75 km. The LETKF is chosen for its relative simplicity, ease of implementation, and computational efficiency and scalability. The modeling/DA system assimilates daily MODIS Snow Covered Area and Grain Size (MODSCAG) fractional snow cover over, and has been developed to efficiently calculate SWE estimates over extended periods of time and covering large regional-scale areas at relatively high spatial resolution, ultimately producing a snow reanalysis-type dataset. Here we focus on the assessment of SWE produced by the DA scheme over several basins in California's Sierra Nevada Mountain range where Airborne Snow Observatory data is available, during the last five water years (2013-2017), which include both one of the driest and one of the wettest years. Comparison against such a spatially distributed SWE observational product provides a greater understanding of the model's ability to estimate SWE and SWE spatial variability, and highlights under which conditions snow cover DA can add value in estimating SWE.

Estimates of genetic parameters in turkeys. 3. Sexual dimorphism and its implications in selection procedures.

PubMed

Toelle, V D; Havenstein, G B; Nestor, K E; Bacon, W L

1990-10-01

Live, carcass, and skeletal data taken at 16 wk of age on 504 female and 584 male turkeys from 34 sires and 168 dams were utilized to evaluate sex differences in genetic parameter estimates. Data were transformed to common mean and variance to evaluate possible scaling effects. Genetic parameters were estimated from transformed and untransformed data. Further analyses were conducted with a model that included sire by sex and dams within sire by sex interactions, and the variance estimates were used to calculate genetic correlations between the sexes and genetic regression parameters. Heritability estimates from transformed and untransformed data were similar, indicating that sex differences were present in the genetic parameters, but scaling effects were not an important factor. Genetic correlation estimates from paternal (PHS) and maternal (MHS) half-sib estimates were close to unity for BW (1.14, PHS; 1.09, MHS), shank width (.99, PHS; .93, MHS), breast muscle weight (1.23, PHS; 1.04, MHS), and shank length (1.09, PHS; .97, MHS). However, abdominal fat (.79, PHS; .59 MHS), total drumstick muscle weight (.75, PHS; 1.14, MHS), rough cleaned shank weight (.78, PHS; not estimatable, MHS), and shank bone density (1.00, PHS; .53, MHS) estimates were somewhat lower. The estimates suggest that the measurement of these latter "traits" at the same age in the two sexes may, in fact, be measuring different genetic effects and that selection procedures in turkeys need to take these correlations into account in order to make optimum progress. The genetic regression parameters indicated that more intense selection in the sex that has the smaller genetic variation could be practiced to make greater gains in the opposite sex.

Stacked lensing estimators and their covariance matrices: Excess surface mass density vs. Lensing shear

NASA Astrophysics Data System (ADS)

Shirasaki, Masato; Takada, Masahiro

2018-05-01

Stacked lensing is a powerful means of measuring the average mass distribution around large-scale structure tracers. There are two stacked lensing estimators used in the literature, denoted as ΔΣ and γ+, which are related as ΔΣ = Σcrγ+, where Σcr(zl, zs) is the critical surface mass density for each lens-source pair (zl and zs are lens and source redshifts, respectively). In this paper we derive a formula for the covariance matrix of ΔΣ-estimator focusing on "weight" function to improve the signal-to-noise (S/N). We assume that the lensing fields and the distribution of lensing objects obey the Gaussian statistics. With this formula, we show that, if background galaxy shapes are weighted by an amount of Σ _cr^{-2}(z_l,z_s), the ΔΣ-estimator maximizes the S/N in the shot noise limited regime. We also show that the ΔΣ-estimator with the weight Σ _cr^{-2} gives a greater (S/N)2 than that of the γ+-estimator by about 5-25% for lensing objects at redshifts comparable with or higher than the median of source galaxy redshifts for hypothetical Subaru HSC and DES surveys. However, for low-redshift lenses such as zl ≲ 0.3, the γ+-estimator has higher (S/N)2 than ΔΣ. We also discuss that the (S/N)2 for ΔΣ at large separations in the sample variance limited regime can be boosted, by up to a factor of 1.5, if one adopts a weight of Σ _cr^{-α } with α > 2. Our formula allows one to explore how the combination of the different estimators can approach an optimal estimator in all regimes of redshifts and separation scales.

Estimating Regional and National-Scale Greenhouse Gas Emissions in the Agriculture, Forestry, and Other Land Use (AFOLU) Sector using the `Agricultural and Land Use (ALU) Tool'

NASA Astrophysics Data System (ADS)

Spencer, S.; Ogle, S. M.; Wirth, T. C.; Sivakami, G.

2016-12-01

The Intergovernmental Panel on Climate Change (IPCC) provides methods and guidance for estimating anthropogenic greenhouse gas emissions for reporting to the United Nations Framework Convention on Climate Change. The methods are comprehensive and require extensive data compilation, management, aggregation, documentation and calculations of source and sink categories to achieve robust emissions estimates. IPCC Guidelines describe three estimation tiers that require increasing levels of country-specific data and method complexity. Use of higher tiers should improve overall accuracy and reduce uncertainty in estimates. The AFOLU sector represents a complex set of methods for estimating greenhouse gas emissions and carbon sinks. Major AFOLU emissions and sinks include carbon dioxide (CO2) from carbon stock change in biomass, dead organic matter and soils, urea or lime application to soils, and oxidation of carbon in drained organic soils; nitrous oxide (N2O) and methane (CH4) emissions from livestock management and biomass burning; N2O from organic amendments and fertilizer application to soils, and CH4 emissions from rice cultivation. To assist inventory compilers with calculating AFOLU-sector estimates, the Agriculture and Land Use Greenhouse Gas Inventory Tool (ALU) was designed to implement Tier 1 and 2 methods using IPCC Good Practice Guidance. It guides the compiler through activity data entry, emission factor assignment, and emissions calculations while carefully maintaining data integrity. ALU also provides IPCC defaults and can estimate uncertainty. ALU was designed to simplify the AFOLU inventory compilation process at regional or national scales, disaggregating the process into a series of steps reduces the potential for errors in the compilation process. An example application has been developed using ALU to estimate methane emissions from rice production in the United States.

Rainfall Erosivity Database on the European Scale (REDES): A product of a high temporal resolution rainfall data collection in Europe

NASA Astrophysics Data System (ADS)

Panagos, Panos; Ballabio, Cristiano; Borrelli, Pasquale; Meusburger, Katrin; Alewell, Christine

2016-04-01

The erosive force of rainfall is expressed as rainfall erosivity. Rainfall erosivity considers the rainfall amount and intensity, and is most commonly expressed as the R-factor in the (R)USLE model. The R-factor is calculated from a series of single storm events by multiplying the total storm kinetic energy with the measured maximum 30-minutes rainfall intensity. This estimation requests high temporal resolution (e.g. 30 minutes) rainfall data for sufficiently long time periods (i.e. 20 years) which are not readily available at European scale. The European Commission's Joint Research Centre(JRC) in collaboration with national/regional meteorological services and Environmental Institutions made an extensive data collection of high resolution rainfall data in the 28 Member States of the European Union plus Switzerland in order to estimate rainfall erosivity in Europe. This resulted in the Rainfall Erosivity Database on the European Scale (REDES) which included 1,541 rainfall stations in 2014 and has been updated with 134 additional stations in 2015. The interpolation of those point R-factor values with a Gaussian Process Regression (GPR) model has resulted in the first Rainfall Erosivity map of Europe (Science of the Total Environment, 511, 801-815). The intra-annual variability of rainfall erosivity is crucial for modelling soil erosion on a monthly and seasonal basis. The monthly feature of rainfall erosivity has been added in 2015 as an advancement of REDES and the respective mean annual R-factor map. Almost 19,000 monthly R-factor values of REDES contributed to the seasonal and monthly assessments of rainfall erosivity in Europe. According to the first results, more than 50% of the total rainfall erosivity in Europe takes place in the period from June to September. The spatial patterns of rainfall erosivity have significant differences between Northern and Southern Europe as summer is the most erosive period in Central and Northern Europe and autumn in the Mediterranean area. This spatio-temporal analysis of rainfall erosivity at European scale is very important for policy makers and farmers for soil conservation, optimization of agricultural land use and natural hazards prediction. REDES is also used in combination with future rainfall data from WorldClim to run climate change scenarios. The projection of REDES combined with climate change scenarios (HADGEM2, RCP4.5) and using a robust geo-statistical model resulted in a 10-20% increase of the R-factor in Europe till 2050.

Modeling Net Ecosystem Carbon Exchange of Alpine Grasslands with a Satellite-Driven Model

PubMed Central

Zhao, Yuping; Zhang, Xianzhou; Fan, Yuzhi; Shi, Peili; He, Yongtao; Yu, Guirui; Li, Yingnian

2015-01-01

Estimate of net ecosystem carbon exchange (NEE) between the atmosphere and terrestrial ecosystems, the balance of gross primary productivity (GPP) and ecosystem respiration (Reco) has significant importance for studying the regional and global carbon cycles. Using models driven by satellite data and climatic data is a promising approach to estimate NEE at regional scales. For this purpose, we proposed a semi-empirical model to estimate NEE in this study. In our model, the component GPP was estimated with a light response curve of a rectangular hyperbola. The component Reco was estimated with an exponential function of soil temperature. To test the feasibility of applying our model at regional scales, the temporal variations in the model parameters derived from NEE observations in an alpine grassland ecosystem on Tibetan Plateau were investigated. The results indicated that all the inverted parameters exhibit apparent seasonality, which is in accordance with air temperature and canopy phenology. In addition, all the parameters have significant correlations with the remote sensed vegetation indexes or environment temperature. With parameters estimated with these correlations, the model illustrated fair accuracy both in the validation years and at another alpine grassland ecosystem on Tibetan Plateau. Our results also indicated that the model prediction was less accurate in drought years, implying that soil moisture is an important factor affecting the model performance. Incorporating soil water content into the model would be a critical step for the improvement of the model. PMID:25849325

Modeling net ecosystem carbon exchange of alpine grasslands with a satellite-driven model.

PubMed

Yan, Wei; Hu, Zhongmin; Zhao, Yuping; Zhang, Xianzhou; Fan, Yuzhi; Shi, Peili; He, Yongtao; Yu, Guirui; Li, Yingnian

2015-01-01

Estimate of net ecosystem carbon exchange (NEE) between the atmosphere and terrestrial ecosystems, the balance of gross primary productivity (GPP) and ecosystem respiration (Reco) has significant importance for studying the regional and global carbon cycles. Using models driven by satellite data and climatic data is a promising approach to estimate NEE at regional scales. For this purpose, we proposed a semi-empirical model to estimate NEE in this study. In our model, the component GPP was estimated with a light response curve of a rectangular hyperbola. The component Reco was estimated with an exponential function of soil temperature. To test the feasibility of applying our model at regional scales, the temporal variations in the model parameters derived from NEE observations in an alpine grassland ecosystem on Tibetan Plateau were investigated. The results indicated that all the inverted parameters exhibit apparent seasonality, which is in accordance with air temperature and canopy phenology. In addition, all the parameters have significant correlations with the remote sensed vegetation indexes or environment temperature. With parameters estimated with these correlations, the model illustrated fair accuracy both in the validation years and at another alpine grassland ecosystem on Tibetan Plateau. Our results also indicated that the model prediction was less accurate in drought years, implying that soil moisture is an important factor affecting the model performance. Incorporating soil water content into the model would be a critical step for the improvement of the model.

Multi-scale variability and long-range memory in indoor Radon concentrations from Coimbra, Portugal

NASA Astrophysics Data System (ADS)

Donner, Reik V.; Potirakis, Stelios; Barbosa, Susana

2014-05-01

The presence or absence of long-range correlations in the variations of indoor Radon concentrations has recently attracted considerable interest. As a radioactive gas naturally emitted from the ground in certain geological settings, understanding environmental factors controlling Radon concentrations and their dynamics is important for estimating its effect on human health and the efficiency of possible measures for reducing the corresponding exposition. In this work, we re-analyze two high-resolution records of indoor Radon concentrations from Coimbra, Portugal, each of which spans several months of continuous measurements. In order to evaluate the presence of long-range correlations and fractal scaling, we utilize a multiplicity of complementary methods, including power spectral analysis, ARFIMA modeling, classical and multi-fractal detrended fluctuation analysis, and two different estimators of the signals' fractal dimensions. Power spectra and fluctuation functions reveal some complex behavior with qualitatively different properties on different time-scales: white noise in the high-frequency part, indications of some long-range correlated process dominating time scales of several hours to days, and pronounced low-frequency variability associated with tidal and/or meteorological forcing. In order to further decompose these different scales of variability, we apply two different approaches. On the one hand, applying multi-resolution analysis based on the discrete wavelet transform allows separately studying contributions on different time scales and characterize their specific correlation and scaling properties. On the other hand, singular system analysis (SSA) provides a reconstruction of the essential modes of variability. Specifically, by considering only the first leading SSA modes, we achieve an efficient de-noising of our environmental signals, highlighting the low-frequency variations together with some distinct scaling on sub-daily time-scales resembling the properties of a long-range correlated process.

Comparison of Personal Resources in Patients Who Differently Estimate the Impact of Multiple Sclerosis.

PubMed

Wilski, Maciej; Tomczak, Maciej

2017-04-01

Discrepancies between physicians' assessment and patients' subjective representations of the disease severity may influence physician-patient communication and management of a chronic illness, such as multiple sclerosis (MS). For these reasons, it is important to recognize factors that distinguish patients who differently estimate the impact of MS. The purpose of this study was to verify if the patients who overestimate or underestimate the impact of MS differ in their perception of personal resources from individuals presenting with a realistic appraisal of their physical condition. A total of 172 women and 92 men diagnosed with MS completed Multiple Sclerosis Impact Scale, University of Washington Self Efficacy Scale, Rosenberg Self-Esteem Scale, Body Esteem Scale, Brief Illness Perception Questionnaire, Treatment Beliefs Scale, Actually Received Support Scale, and Socioeconomic resources scale. Physician's assessment of health status was determined with Expanded Disability Status Scale. Linear regression analysis was conducted to identify the subsets of patients with various patterns of subjective health and Expanded Disability Status Scale (EDSS) scores. Patients overestimating the impact of their disease presented with significantly lower levels of self-esteem, self-efficacy in MS, and body esteem; furthermore, they perceived their condition more threatening than did realists and underestimators. They also assessed anti-MS treatment worse, had less socioeconomic resources, and received less support than underestimators. Additionally, underestimators presented with significantly better perception of their disease, self, and body than did realists. Self-assessment of MS-related symptoms is associated with specific perception of personal resources in coping with the disease. These findings may facilitate communication with patients and point to new directions for future research on adaptation to MS.

Effect of Variable Spatial Scales on USLE-GIS Computations

NASA Astrophysics Data System (ADS)

Patil, R. J.; Sharma, S. K.

2017-12-01

Use of appropriate spatial scale is very important in Universal Soil Loss Equation (USLE) based spatially distributed soil erosion modelling. This study aimed at assessment of annual rates of soil erosion at different spatial scales/grid sizes and analysing how changes in spatial scales affect USLE-GIS computations using simulation and statistical variabilities. Efforts have been made in this study to recommend an optimum spatial scale for further USLE-GIS computations for management and planning in the study area. The present research study was conducted in Shakkar River watershed, situated in Narsinghpur and Chhindwara districts of Madhya Pradesh, India. Remote Sensing and GIS techniques were integrated with Universal Soil Loss Equation (USLE) to predict spatial distribution of soil erosion in the study area at four different spatial scales viz; 30 m, 50 m, 100 m, and 200 m. Rainfall data, soil map, digital elevation model (DEM) and an executable C++ program, and satellite image of the area were used for preparation of the thematic maps for various USLE factors. Annual rates of soil erosion were estimated for 15 years (1992 to 2006) at four different grid sizes. The statistical analysis of four estimated datasets showed that sediment loss dataset at 30 m spatial scale has a minimum standard deviation (2.16), variance (4.68), percent deviation from observed values (2.68 - 18.91 %), and highest coefficient of determination (R2 = 0.874) among all the four datasets. Thus, it is recommended to adopt this spatial scale for USLE-GIS computations in the study area due to its minimum statistical variability and better agreement with the observed sediment loss data. This study also indicates large scope for use of finer spatial scales in spatially distributed soil erosion modelling.

Summary of groundwater-recharge estimates for Pennsylvania

USGS Publications Warehouse

Stuart O. Reese,; Risser, Dennis W.

2010-01-01

Groundwater recharge is water that infiltrates through the subsurface to the zone of saturation beneath the water table. Because recharge is a difficult parameter to quantify, it is typically estimated from measurements of other parameters like streamflow and precipitation. This report provides a general overview of processes affecting recharge in Pennsylvania and presents estimates of recharge rates from studies at various scales.The most common method for estimating recharge in Pennsylvania has been to estimate base flow from measurements of streamflow and assume that base flow (expressed in inches over the basin) approximates recharge. Statewide estimates of mean annual groundwater recharge were developed by relating base flow to basin characteristics of HUC10 watersheds (a fifth-level classification that uses 10 digits to define unique hydrologic units) using a regression equation. The regression analysis indicated that mean annual precipitation, average daily maximum temperature, percent of sand in soil, percent of carbonate rock in the watershed, and average stream-channel slope were significant factors in the explaining the variability of groundwater recharge across the Commonwealth.Several maps are included in this report to illustrate the principal factors affecting recharge and provide additional information about the spatial distribution of recharge in Pennsylvania. The maps portray the patterns of precipitation, temperature, prevailing winds across Pennsylvania’s varied physiography; illustrate the error associated with recharge estimates; and show the spatial variability of recharge as a percent of precipitation. National, statewide, regional, and local values of recharge, based on numerous studies, are compiled to allow comparison of estimates from various sources. Together these plates provide a synopsis of groundwater-recharge estimations and factors in Pennsylvania.Areas that receive the most recharge are typically those that get the most rainfall, have favorable surface conditions for infiltration, and are less susceptible to the influences of high temperatures, and thus, evapotranspiration. Areas that have less recharge in Pennsylvania are typically those with less precipitation, less permeable soils, and higher temperatures that are conducive to greater rates of evapotranspiration.

Extension of a GIS procedure for calculating the RUSLE equation LS factor

NASA Astrophysics Data System (ADS)

Zhang, Hongming; Yang, Qinke; Li, Rui; Liu, Qingrui; Moore, Demie; He, Peng; Ritsema, Coen J.; Geissen, Violette

2013-03-01

The Universal Soil Loss Equation (USLE) and revised USLE (RUSLE) are often used to estimate soil erosion at regional landscape scales, however a major limitation is the difficulty in extracting the LS factor. The geographic information system-based (GIS-based) methods which have been developed for estimating the LS factor for USLE and RUSLE also have limitations. The unit contributing area-based estimation method (UCA) converts slope length to unit contributing area for considering two-dimensional topography, however is not able to predict the different zones of soil erosion and deposition. The flowpath and cumulative cell length-based method (FCL) overcomes this disadvantage but does not consider channel networks and flow convergence in two-dimensional topography. The purpose of this research was to overcome these limitations and extend the FCL method through inclusion of channel networks and convergence flow. We developed LS-TOOL in Microsoft's.NET environment using C♯ with a user-friendly interface. Comparing the LS factor calculated with the three methodologies (UCA, FCL and LS-TOOL), LS-TOOL delivers encouraging results. In particular, LS-TOOL uses breaks in slope identified from the DEM to locate soil erosion and deposition zones, channel networks and convergence flow areas. Comparing slope length and LS factor values generated using LS-TOOL with manual methods, LS-TOOL corresponds more closely with the reality of the Xiannangou catchment than results using UCA or FCL. The LS-TOOL algorithm can automatically calculate slope length, slope steepness, L factor, S factor, and LS factors, providing the results as ASCII files which can be easily used in some GIS software. This study is an important step forward in conducting more accurate large area erosion evaluation.

A comparison of sap flux-based evapotranspiration estimates with catchment-scale water balance

Treesearch

Chelcy R. Ford; Robert M. Hubbard; Brian D. Kloeppel; James M. Vose

2007-01-01

Many researchers are using sap flux to estimate tree-level transpiration, and to scale to stand- and catchment-level transpiration; yet studies evaluating the comparability of sap flux-based estimates of transpiration (E) with alternative methods for estimating Et at this spatial scale are rare. Our ability to...

Development of an Instrument to Measure Pharmacy Student Attitudes Toward Social Media Professionalism.

PubMed

Chisholm-Burns, Marie A; Spivey, Christina A; Jaeger, Melanie C; Williams, Jennifer; George, Christa

2017-05-01

Objectives. To develop and validate a scale measuring pharmacy students' attitudes toward social media professionalism, and assess the impact of an educational presentation on social media professionalism. Methods. A social media professionalism scale was used in a pre- and post-survey to determine the effects of a social media professionalism presentation. The 26-item scale was administered to 197 first-year pharmacy (P1) students during orientation. Exploratory factor analysis was applied to determine the number of underlying factors responsible for covariation of the data. Principal components analysis was used as the extraction method. Varimax was selected as the rotation method. Cronbach's alpha was estimated. Wilcoxon signed rank test was used to compare pre- and post-scores of each item, subscale, and total scale. Results. There were 187 (95%) students who participated. The final scale had five subscales and 15 items. Subscales were named according to the professionalism tenet they best represented. Scores of items addressing reading/posting to social media during class, an employer's use of social media when making hiring decisions, and a college/university's use of social media as a measure of professional conduct significantly increased from pre-test to post-test. The "honesty and integrity" subscale score also significantly increased. Conclusion. The social media professionalism scale measures five tenets of professionalism and exhibits satisfactory reliability. The presentation improved P1 students' attitudes regarding social media professionalism.

Experimental evidence for convergent evolution of maternal care heuristics in industrialized and small-scale populations.

PubMed

Kushnick, Geoff; Hanowell, Ben; Kim, Jun-Hong; Langstieh, Banrida; Magnano, Vittorio; Oláh, Katalin

2015-06-01

Maternal care decision rules should evolve responsiveness to factors impinging on the fitness pay-offs of care. Because the caretaking environments common in industrialized and small-scale societies vary in predictable ways, we hypothesize that heuristics guiding maternal behaviour will also differ between these two types of populations. We used a factorial vignette experiment to elicit third-party judgements about likely caretaking decisions of a hypothetical mother and her child when various fitness-relevant factors (maternal age and access to resources, and offspring age, sex and quality) were varied systematically in seven populations-three industrialized and four small-scale. Despite considerable variation in responses, we found that three of five main effects, and the two severity effects, exhibited statistically significant industrialized/ small-scale population differences. All differences could be explained as adaptive solutions to industrialized versus small-scale caretaking environments. Further, we found gradients in the relationship between the population-specific estimates and national-level socio-economic indicators, further implicating important aspects of the variation in industrialized and small-scale caretaking environments in shaping heuristics. Although there is mounting evidence for a genetic component to human maternal behaviour, there is no current evidence for interpopulation variation in candidate genes. We nonetheless suggest that heuristics guiding maternal behaviour in diverse societies emerge via convergent evolution in response to similar selective pressures.

Rapid estimation of the economic consequences of global earthquakes

USGS Publications Warehouse

Jaiswal, Kishor; Wald, David J.

2011-01-01

The U.S. Geological Survey's (USGS) Prompt Assessment of Global Earthquakes for Response (PAGER) system, operational since mid 2007, rapidly estimates the most affected locations and the population exposure at different levels of shaking intensities. The PAGER system has significantly improved the way aid agencies determine the scale of response needed in the aftermath of an earthquake. For example, the PAGER exposure estimates provided reasonably accurate assessments of the scale and spatial extent of the damage and losses following the 2008 Wenchuan earthquake (Mw 7.9) in China, the 2009 L'Aquila earthquake (Mw 6.3) in Italy, the 2010 Haiti earthquake (Mw 7.0), and the 2010 Chile earthquake (Mw 8.8). Nevertheless, some engineering and seismological expertise is often required to digest PAGER's exposure estimate and turn it into estimated fatalities and economic losses. This has been the focus of PAGER's most recent development. With the new loss-estimation component of the PAGER system it is now possible to produce rapid estimation of expected fatalities for global earthquakes (Jaiswal and others, 2009). While an estimate of earthquake fatalities is a fundamental indicator of potential human consequences in developing countries (for example, Iran, Pakistan, Haiti, Peru, and many others), economic consequences often drive the responses in much of the developed world (for example, New Zealand, the United States, and Chile), where the improved structural behavior of seismically resistant buildings significantly reduces earthquake casualties. Rapid availability of estimates of both fatalities and economic losses can be a valuable resource. The total time needed to determine the actual scope of an earthquake disaster and to respond effectively varies from country to country. It can take days or sometimes weeks before the damage and consequences of a disaster can be understood both socially and economically. The objective of the U.S. Geological Survey's PAGER system is to reduce this time gap to more rapidly and effectively mobilize response. We present here a procedure to rapidly and approximately ascertain the economic impact immediately following a large earthquake anywhere in the world. In principle, the approach presented is similar to the empirical fatality estimation methodology proposed and implemented by Jaiswal and others (2009). In order to estimate economic losses, we need an assessment of the economic exposure at various levels of shaking intensity. The economic value of all the physical assets exposed at different locations in a given area is generally not known and extremely difficult to compile at a global scale. In the absence of such a dataset, we first estimate the total Gross Domestic Product (GDP) exposed at each shaking intensity by multiplying the per-capita GDP of the country by the total population exposed at that shaking intensity level. We then scale the total GDP estimated at each intensity by an exposure correction factor, which is a multiplying factor to account for the disparity between wealth and/or economic assets to the annual GDP. The economic exposure obtained using this procedure is thus a proxy estimate for the economic value of the actual inventory that is exposed to the earthquake. The economic loss ratio, defined in terms of a country-specific lognormal cumulative distribution function of shaking intensity, is derived and calibrated against the losses from past earthquakes. This report describes the development of a country or region-specific economic loss ratio model using economic loss data available for global earthquakes from 1980 to 2007. The proposed model is a potential candidate for directly estimating economic losses within the currently-operating PAGER system. PAGER's other loss models use indirect methods that require substantially more data (such as building/asset inventories, vulnerabilities, and the asset values exposed at the time of earthquake) to implement on a global basis and will thus take more time to develop and implement within the PAGER system.

Statistical interactions and Bayes estimation of log odds in case-control studies.

PubMed

Satagopan, Jaya M; Olson, Sara H; Elston, Robert C

2017-04-01

This paper is concerned with the estimation of the logarithm of disease odds (log odds) when evaluating two risk factors, whether or not interactions are present. Statisticians define interaction as a departure from an additive model on a certain scale of measurement of the outcome. Certain interactions, known as removable interactions, may be eliminated by fitting an additive model under an invertible transformation of the outcome. This can potentially provide more precise estimates of log odds than fitting a model with interaction terms. In practice, we may also encounter nonremovable interactions. The model must then include interaction terms, regardless of the choice of the scale of the outcome. However, in practical settings, we do not know at the outset whether an interaction exists, and if so whether it is removable or nonremovable. Rather than trying to decide on significance levels to test for the existence of removable and nonremovable interactions, we develop a Bayes estimator based on a squared error loss function. We demonstrate the favorable bias-variance trade-offs of our approach using simulations, and provide empirical illustrations using data from three published endometrial cancer case-control studies. The methods are implemented in an R program, and available freely at http://www.mskcc.org/biostatistics/~satagopj .

Self-Reported and Network Scale-Up Estimates of Substance Use Prevalence among University Students in Kerman, Iran.

PubMed

Zahedi, Razieh; Noroozi, Alireza; Hajebi, Ahmad; Haghdoost, Ali Akbar; Baneshi, Mohammad Reza; Sharifi, Hamid; Mirzazadeh, Ali

2018-04-30

This study aimed to estimate the prevalence of substance use among university students measured by direct and indirect methods, and to calculate the visibility factor (VF) defined as ratio of indirect to direct estimates of substance use prevalence. A cross-sectional study. Using a multistage non-random sampling approach, we recruited 2157 students from three universities in Kerman, Iran, in 2016. We collected data on substance use by individual face-to-face interview using direct (i.e. self-report of their own behaviors) and indirect (NSU: Network scale up) methods. All estimates from direct and indirect methods were weighted based on inverse probability weight of sampling university. The response rate was 83.6%. The last year prevalence of water pipe, alcohol, and cigarettes indirect method was 44.6%, 18.1%, and 13.2% respectively. Corresponding figures in NSU analysis were 36.4%, 18.2%, and 16.5% respectively. In the female population, VF for all types of substance was less than male. Considerable numbers of university students used substances like a water pipe, alcohol, and cigarettes. NSU seems a promising method, especially among male students. Among female students, direct method provided more reliable results mainly due to transmission and prestige biases.

Speech Enhancement Using Gaussian Scale Mixture Models

PubMed Central

Hao, Jiucang; Lee, Te-Won; Sejnowski, Terrence J.

2011-01-01

This paper presents a novel probabilistic approach to speech enhancement. Instead of a deterministic logarithmic relationship, we assume a probabilistic relationship between the frequency coefficients and the log-spectra. The speech model in the log-spectral domain is a Gaussian mixture model (GMM). The frequency coefficients obey a zero-mean Gaussian whose covariance equals to the exponential of the log-spectra. This results in a Gaussian scale mixture model (GSMM) for the speech signal in the frequency domain, since the log-spectra can be regarded as scaling factors. The probabilistic relation between frequency coefficients and log-spectra allows these to be treated as two random variables, both to be estimated from the noisy signals. Expectation-maximization (EM) was used to train the GSMM and Bayesian inference was used to compute the posterior signal distribution. Because exact inference of this full probabilistic model is computationally intractable, we developed two approaches to enhance the efficiency: the Laplace method and a variational approximation. The proposed methods were applied to enhance speech corrupted by Gaussian noise and speech-shaped noise (SSN). For both approximations, signals reconstructed from the estimated frequency coefficients provided higher signal-to-noise ratio (SNR) and those reconstructed from the estimated log-spectra produced lower word recognition error rate because the log-spectra fit the inputs to the recognizer better. Our algorithms effectively reduced the SSN, which algorithms based on spectral analysis were not able to suppress. PMID:21359139

Modeling change in learning strategies throughout higher education: a multi-indicator latent growth perspective.

PubMed

Coertjens, Liesje; Donche, Vincent; De Maeyer, Sven; Vanthournout, Gert; Van Petegem, Peter

2013-01-01

The change in learning strategies during higher education is an important topic of research in the Student Approaches to Learning field. Although the studies on this topic are increasingly longitudinal, analyses have continued to rely primarily on traditional statistical methods. The present research is innovative in the way it uses a multi-indicator latent growth analysis in order to more accurately estimate the general and differential development in learning strategy scales. Moreover, the predictive strength of the latent growth models are estimated. The sample consists of one cohort of Flemish University College students, 245 of whom participated in the three measurement waves by filling out the processing and regulation strategies scales of the Inventory of Learning Styles--Short Versions. Independent-samples t-tests revealed that the longitudinal group is a non-random subset of students starting University College. For each scale, a multi-indicator latent growth model is estimated using Mplus 6.1. Results suggest that, on average, during higher education, students persisting in their studies in a non-delayed manner seem to shift towards high-quality learning and away from undirected and surface-oriented learning. Moreover, students from the longitudinal group are found to vary in their initial levels, while, unexpectedly, not in their change over time. Although the growth models fit the data well, significant residual variances in the latent factors remain.

Baryons still trace dark matter: Probing CMB lensing maps for hidden isocurvature

NASA Astrophysics Data System (ADS)

Smith, Tristan L.; Muñoz, Julian B.; Smith, Rhiannon; Yee, Kyle; Grin, Daniel

2017-10-01

Compensated isocurvature perturbations (CIPs) are primordial fluctuations that balance baryon and dark-matter isocurvature to leave the total matter density unperturbed. The effects of CIPs on the cosmic microwave background (CMB) anisotropies are similar to those produced by weak lensing of the CMB: smoothing of the power spectrum and generation of non-Gaussian features. Here, an entirely new CIP contribution to the standard estimator for the lensing-potential power spectrum is derived. Planck measurements of the temperature and polarization power spectrum, as well as estimates of CMB lensing, are used to place limits on the variance of the CIP fluctuations on CMB scales, Δrms2(RCMB). The resulting constraint of Δrms2(RCMB)<4.3 ×10-3 at 95% confidence level (CL) using this new technique improves on past work by a factor of ˜3 . We find that for Planck data our constraints almost reach the sensitivity of the optimal CIP estimator. The method presented here is currently the most sensitive probe of the amplitude of a scale-invariant CIP power spectrum, ACIP, placing an upper limit of ACIP<0.017 at 95% CL. Future measurements of the large-scale CMB lensing-potential power spectrum could probe CIP amplitudes as low as Δrms2(RCMB)=8 ×10-5 at 95% CL (corresponding to ACIP=3.2 ×10-4).

Modeling Change in Learning Strategies throughout Higher Education: A Multi-Indicator Latent Growth Perspective

PubMed Central

Coertjens, Liesje; Donche, Vincent; De Maeyer, Sven; Vanthournout, Gert; Van Petegem, Peter

2013-01-01

The change in learning strategies during higher education is an important topic of research in the Student Approaches to Learning field. Although the studies on this topic are increasingly longitudinal, analyses have continued to rely primarily on traditional statistical methods. The present research is innovative in the way it uses a multi-indicator latent growth analysis in order to more accurately estimate the general and differential development in learning strategy scales. Moreover, the predictive strength of the latent growth models are estimated. The sample consists of one cohort of Flemish University College students, 245 of whom participated in the three measurement waves by filling out the processing and regulation strategies scales of the Inventory of Learning Styles – Short Versions. Independent-samples t-tests revealed that the longitudinal group is a non-random subset of students starting University College. For each scale, a multi-indicator latent growth model is estimated using Mplus 6.1. Results suggest that, on average, during higher education, students persisting in their studies in a non-delayed manner seem to shift towards high-quality learning and away from undirected and surface-oriented learning. Moreover, students from the longitudinal group are found to vary in their initial levels, while, unexpectedly, not in their change over time. Although the growth models fit the data well, significant residual variances in the latent factors remain. PMID:23844112

An Expanded Multi-scale Monte Carlo Simulation Method for Personalized Radiobiological Effect Estimation in Radiotherapy: a feasibility study

NASA Astrophysics Data System (ADS)

Zhang, Ying; Feng, Yuanming; Wang, Wei; Yang, Chengwen; Wang, Ping

2017-03-01

A novel and versatile “bottom-up” approach is developed to estimate the radiobiological effect of clinic radiotherapy. The model consists of multi-scale Monte Carlo simulations from organ to cell levels. At cellular level, accumulated damages are computed using a spectrum-based accumulation algorithm and predefined cellular damage database. The damage repair mechanism is modeled by an expanded reaction-rate two-lesion kinetic model, which were calibrated through replicating a radiobiological experiment. Multi-scale modeling is then performed on a lung cancer patient under conventional fractionated irradiation. The cell killing effects of two representative voxels (isocenter and peripheral voxel of the tumor) are computed and compared. At microscopic level, the nucleus dose and damage yields vary among all nucleuses within the voxels. Slightly larger percentage of cDSB yield is observed for the peripheral voxel (55.0%) compared to the isocenter one (52.5%). For isocenter voxel, survival fraction increase monotonically at reduced oxygen environment. Under an extreme anoxic condition (0.001%), survival fraction is calculated to be 80% and the hypoxia reduction factor reaches a maximum value of 2.24. In conclusion, with biological-related variations, the proposed multi-scale approach is more versatile than the existing approaches for evaluating personalized radiobiological effects in radiotherapy.

A proposed method to investigate reliability throughout a questionnaire.

PubMed

Wentzel-Larsen, Tore; Norekvål, Tone M; Ulvik, Bjørg; Nygård, Ottar; Pripp, Are H

2011-10-05

Questionnaires are used extensively in medical and health care research and depend on validity and reliability. However, participants may differ in interest and awareness throughout long questionnaires, which can affect reliability of their answers. A method is proposed for "screening" of systematic change in random error, which could assess changed reliability of answers. A simulation study was conducted to explore whether systematic change in reliability, expressed as changed random error, could be assessed using unsupervised classification of subjects by cluster analysis (CA) and estimation of intraclass correlation coefficient (ICC). The method was also applied on a clinical dataset from 753 cardiac patients using the Jalowiec Coping Scale. The simulation study showed a relationship between the systematic change in random error throughout a questionnaire and the slope between the estimated ICC for subjects classified by CA and successive items in a questionnaire. This slope was proposed as an awareness measure--to assessing if respondents provide only a random answer or one based on a substantial cognitive effort. Scales from different factor structures of Jalowiec Coping Scale had different effect on this awareness measure. Even though assumptions in the simulation study might be limited compared to real datasets, the approach is promising for assessing systematic change in reliability throughout long questionnaires. Results from a clinical dataset indicated that the awareness measure differed between scales.

Estimating unbiased economies of scale of HIV prevention projects: a case study of Avahan.

PubMed

Lépine, Aurélia; Vassall, Anna; Chandrashekar, Sudha; Blanc, Elodie; Le Nestour, Alexis

2015-04-01

Governments and donors are investing considerable resources on HIV prevention in order to scale up these services rapidly. Given the current economic climate, providers of HIV prevention services increasingly need to demonstrate that these investments offer good 'value for money'. One of the primary routes to achieve efficiency is to take advantage of economies of scale (a reduction in the average cost of a health service as provision scales-up), yet empirical evidence on economies of scale is scarce. Methodologically, the estimation of economies of scale is hampered by several statistical issues preventing causal inference and thus making the estimation of economies of scale complex. In order to estimate unbiased economies of scale when scaling up HIV prevention services, we apply our analysis to one of the few HIV prevention programmes globally delivered at a large scale: the Indian Avahan initiative. We costed the project by collecting data from the 138 Avahan NGOs and the supporting partners in the first four years of its scale-up, between 2004 and 2007. We develop a parsimonious empirical model and apply a system Generalized Method of Moments (GMM) and fixed-effects Instrumental Variable (IV) estimators to estimate unbiased economies of scale. At the programme level, we find that, after controlling for the endogeneity of scale, the scale-up of Avahan has generated high economies of scale. Our findings suggest that average cost reductions per person reached are achievable when scaling-up HIV prevention in low and middle income countries. Copyright © 2015 Elsevier Ltd. All rights reserved.

Evaluation of potentially modifiable physical factors as predictors of health status in knee osteoarthritis patients referred for physical therapy.

PubMed

Gonçalves, Rui Soles; Pinheiro, João Páscoa; Cabri, Jan

2012-08-01

The purpose of this cross sectional study was to estimate the contributions of potentially modifiable physical factors to variations in perceived health status in knee osteoarthritis (OA) patients referred for physical therapy. Health status was measured by three questionnaires: Knee injury and Osteoarthritis Outcome Score (KOOS); Knee Outcome Survey - Activities of Daily Living Scale (KOS-ADLS); and Medical Outcomes Study - 36 item Short Form (SF-36). Physical factors were measured by a battery of tests: body mass index (BMI); visual analog scale (VAS) of pain intensity; isometric dynamometry; universal goniometry; step test (ST); timed "up and go" test (TUGT); 20-meter walk test (20MWT); and 6-minute walk test (6MWT). All tests were administered to 136 subjects with symptomatic knee OA (94 females, 42 males; age: 67.2 ± 7.1 years). Multiple stepwise regression analyses revealed that knee muscle strength, VAS of pain intensity, 6MWT, degree of knee flexion and BMI were moderate predictors of health status. In the final models, selected combinations of these potentially modifiable physical factors explained 22% to 37% of the variance in KOOS subscale scores, 40% of the variance in the KOS-ADLS scale score, and 21% to 34% of the variance in physical health SF-36 subscale scores. More research is required in order to evaluate whether therapeutic interventions targeting these potentially modifiable physical factors would improve health status in knee OA patients. Copyright © 2011 Elsevier B.V. All rights reserved.

Spectral scaling of the aftershocks of the Tocopilla 2007 earthquake in northern Chile

NASA Astrophysics Data System (ADS)

Lancieri, M.; Madariaga, R.; Bonilla, F.

2012-04-01

We study the scaling of spectral properties of a set of 68 aftershocks of the 2007 November 14 Tocopilla (M 7.8) earthquake in northern Chile. These are all subduction events with similar reverse faulting focal mechanism that were recorded by a homogenous network of continuously recording strong motion instruments. The seismic moment and the corner frequency are obtained assuming that the aftershocks satisfy an inverse omega-square spectral decay; radiated energy is computed integrating the square velocity spectrum corrected for attenuation at high frequencies and for the finite bandwidth effect. Using a graphical approach, we test the scaling of seismic spectrum, and the scale invariance of the apparent stress drop with the earthquake size. To test whether the Tocopilla aftershocks scale with a single parameter, we introduce a non-dimensional number, ?, that should be constant if earthquakes are self-similar. For the Tocopilla aftershocks, Cr varies by a factor of 2. More interestingly, Cr for the aftershocks is close to 2, the value that is expected for events that are approximately modelled by a circular crack. Thus, in spite of obvious differences in waveforms, the aftershocks of the Tocopilla earthquake are self-similar. The main shock is different because its records contain large near-field waves. Finally, we investigate the scaling of energy release rate, Gc, with the slip. We estimated Gc from our previous estimates of the source parameters, assuming a simple circular crack model. We find that Gc values scale with the slip, and are in good agreement with those found by Abercrombie and Rice for the Northridge aftershocks.

Regional soil erosion assessment based on a sample survey and geostatistics

NASA Astrophysics Data System (ADS)

Yin, Shuiqing; Zhu, Zhengyuan; Wang, Li; Liu, Baoyuan; Xie, Yun; Wang, Guannan; Li, Yishan

2018-03-01

Soil erosion is one of the most significant environmental problems in China. From 2010 to 2012, the fourth national census for soil erosion sampled 32 364 PSUs (Primary Sampling Units, small watersheds) with the areas of 0.2-3 km2. Land use and soil erosion controlling factors including rainfall erosivity, soil erodibility, slope length, slope steepness, biological practice, engineering practice, and tillage practice for the PSUs were surveyed, and the soil loss rate for each land use in the PSUs was estimated using an empirical model, the Chinese Soil Loss Equation (CSLE). Though the information collected from the sample units can be aggregated to estimate soil erosion conditions on a large scale; the problem of estimating soil erosion condition on a regional scale has not been addressed well. The aim of this study is to introduce a new model-based regional soil erosion assessment method combining a sample survey and geostatistics. We compared seven spatial interpolation models based on the bivariate penalized spline over triangulation (BPST) method to generate a regional soil erosion assessment from the PSUs. Shaanxi Province (3116 PSUs) in China was selected for the comparison and assessment as it is one of the areas with the most serious erosion problem. Ten-fold cross-validation based on the PSU data showed the model assisted by the land use, rainfall erosivity factor (R), soil erodibility factor (K), slope steepness factor (S), and slope length factor (L) derived from a 1 : 10 000 topography map is the best one, with the model efficiency coefficient (ME) being 0.75 and the MSE being 55.8 % of that for the model assisted by the land use alone. Among four erosion factors as the covariates, the S factor contributed the most information, followed by K and L factors, and R factor made almost no contribution to the spatial estimation of soil loss. The LS factor derived from 30 or 90 m Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) data worsened the estimation when used as the covariates for the interpolation of soil loss. Due to the unavailability of a 1 : 10 000 topography map for the entire area in this study, the model assisted by the land use, R, and K factors, with a resolution of 250 m, was used to generate the regional assessment of the soil erosion for Shaanxi Province. It demonstrated that 54.3 % of total land in Shaanxi Province had annual soil loss equal to or greater than 5 t ha-1 yr-1. High (20-40 t ha-1 yr-1), severe (40-80 t ha-1 yr-1), and extreme ( > 80 t ha-1 yr-1) erosion occupied 14.0 % of the total land. The dry land and irrigated land, forest, shrubland, and grassland in Shaanxi Province had mean soil loss rates of 21.77, 3.51, 10.00, and 7.27 t ha-1 yr-1, respectively. Annual soil loss was about 207.3 Mt in Shaanxi Province, with 68.9 % of soil loss originating from the farmlands and grasslands in Yan'an and Yulin districts in the northern Loess Plateau region and Ankang and Hanzhong districts in the southern Qingba mountainous region. This methodology provides a more accurate regional soil erosion assessment and can help policymakers to take effective measures to mediate soil erosion risks.

An Improved GRACE Terrestrial Water Storage Assimilation System For Estimating Large-Scale Soil Moisture and Shallow Groundwater

NASA Astrophysics Data System (ADS)

Girotto, M.; De Lannoy, G. J. M.; Reichle, R. H.; Rodell, M.

2015-12-01

The Gravity Recovery And Climate Experiment (GRACE) mission is unique because it provides highly accurate column integrated estimates of terrestrial water storage (TWS) variations. Major limitations of GRACE-based TWS observations are related to their monthly temporal and coarse spatial resolution (around 330 km at the equator), and to the vertical integration of the water storage components. These challenges can be addressed through data assimilation. To date, it is still not obvious how best to assimilate GRACE-TWS observations into a land surface model, in order to improve hydrological variables, and many details have yet to be worked out. This presentation discusses specific recent features of the assimilation of gridded GRACE-TWS data into the NASA Goddard Earth Observing System (GEOS-5) Catchment land surface model to improve soil moisture and shallow groundwater estimates at the continental scale. The major recent advancements introduced by the presented work with respect to earlier systems include: 1) the assimilation of gridded GRACE-TWS data product with scaling factors that are specifically derived for data assimilation purposes only; 2) the assimilation is performed through a 3D assimilation scheme, in which reasonable spatial and temporal error standard deviations and correlations are exploited; 3) the analysis step uses an optimized calculation and application of the analysis increments; 4) a poor-man's adaptive estimation of a spatially variable measurement error. This work shows that even if they are characterized by a coarse spatial and temporal resolution, the observed column integrated GRACE-TWS data have potential for improving our understanding of soil moisture and shallow groundwater variations.

Assessing Potential Air Pollutant Emissions from Agricultural Feedstock Production using MOVES

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

Eberle, Annika; Warner, Ethan; Zhang, Yi Min

Biomass feedstock production is expected to grow as demand for biofuels and bioenergy increases. The change in air pollutant emissions that may result from large-scale biomass supply has implications for local air quality and human health. We developed spatially explicit emissions inventories for corn grain and six cellulosic feedstocks through the extension of the National Renewable Energy Laboratory's Feedstock Production Emissions to Air Model (FPEAM). These inventories include emissions of seven pollutants (nitrogen oxides, ammonia, volatile organic compounds, particulate matter, sulfur oxides, and carbon monoxide) generated from biomass establishment, maintenance, harvest, transportation, and biofuel preprocessing activities. By integrating the EPA'smore » MOtor Vehicle Emissions Simulator (MOVES) into FPEAM, we created a scalable framework to execute county-level runs of the MOVES-Onroad model for representative counties (i.e., those counties with the largest amount of cellulosic feedstock production in each state) on a national scale. We used these results to estimate emissions from the on-road transportation of biomass and combined them with county-level runs of the MOVES-Nonroad model to estimate emissions from agricultural equipment. We also incorporated documented emission factors to estimate emissions from chemical application and the operation of drying equipment for feedstock processing, and used methods developed by the EPA and the California Air Resources Board to estimate fugitive dust emissions. The model developed here could be applied to custom equipment budgets and is extensible to accommodate additional feedstocks and pollutants. Future work will also extend this model to analyze spatial boundaries beyond the county-scale (e.g., regional or sub-county levels).« less

Development of risk assessment tool for foundry workers.

PubMed

Mohan, G Madhan; Prasad, P S S; Mokkapati, Anil Kumar; Venkataraman, G

2008-01-01

Occupational ill-health and work-related disorders are predominant in manufacturing industries due to the inevitable presence of manual work even after several waves of industrial automation and technological advancements. Ergonomic risk factors and musculoskeletal disorders like low-back symptoms have been noted amongst foundry workers. The purpose of this study was to formulate and develop a Physical Effort Index to assess risk factor. The questionnaire tool applicable to foundry environment has been designed and validated. The data recorded through survey across the foundries has been subjected to regression analysis to correlate between proposed physical effort index and the standard Borg's Ratings of Perceived Exertion (RPE) scale. The physical efforts of sixty seven workers in various foundry shop floors were assessed subjectively. The 'Job factors' and 'Work environment' were the two major parameters considered in assessing the worker discomfort level at workplace. A relation between Borg's RPE scale and the above two parameters were arrived at, through regression analysis. The study demonstrates the prevalence of risk factors amongst foundry workers and the effectiveness of the proposed index in estimating the risk factor levels. RELEVANCE TO THE INDUSTRY: The proposed tool will assist foundry supervisors and managers to assess the risk factors and helps in better understanding of the workplace to avoid work-related disorders, ensuring better output.

Depression, Anxiety, and Regret Before and After Testing to Estimate Uveal Melanoma Prognosis.

PubMed

Schuermeyer, Isabel; Maican, Anca; Sharp, Richard; Bena, James; Triozzi, Pierre L; Singh, Arun D

2016-01-01

To our knowledge, longitudinal assessment of depression, anxiety, and decision regret (a sense of disappointment or dissatisfaction in the decision) in patients undergoing prognostication for uveal melanoma does not exist. To report on depression, anxiety, and decision regret before and after testing to estimate uveal melanoma prognosis. Prospective interventional case series conducted at an institutional referral practice of 96 patients with clinical diagnosis of uveal melanoma who underwent prognostication at the time of primary therapy. Depression, anxiety, and decision regret prior to prognostication (baseline) and at 3 and 12 months afterwards. The Hospital Anxiety and Depression Scale (HADS) and Decision Regret Scale were self-administered by the patients prior to prognostication (baseline) and at 3 and 12 months afterwards. Data were summarized using means and standard deviations for continuous measures, frequencies, and percentages for categorical factors. A mixed model was used to assess the trajectory of HADS anxiety and the associations between HADS anxiety and baseline HADS depression, baseline decision regret, prognostication test result, and adjuvant therapy, respectively, while adjusting for age and sex. Ninety-six patients (median age 60.7 years) completed baseline questionnaires. The mean (SD) HADS anxiety score at baseline (7.4 [4.0]) was higher than at 3 months (5.4 [3.7]; P < .001) or 12 months (4.7 [3.4]; P < .001), and decreased with older age (coefficient estimate [SD], -0.06 [0.02]; P < .001). The decision regret score was associated with baseline HADS depression score (coefficient estimate [SE], -1.17 [0.43]; P < .007), and HADS depression score increased with baseline HADS anxiety score (coefficient estimate [SE], 0.39 [0.06]; P < .001). Our study raises questions about decision regret in patients who agree to have a prognostic test that may not help guide treatment. Although decision regret appears to lessen or dissipate with time, study on larger numbers of patients is necessary to elucidate factors that may be addressed to mitigate decision regret.

Psychological Distress Is Associated with Greater Perceived Disability and Pain in Patients Presenting to a Shoulder Clinic.

PubMed

Menendez, Mariano E; Baker, Dustin K; Oladeji, Lasun O; Fryberger, Charles T; McGwin, Gerald; Ponce, Brent A

2015-12-16

Shoulder disorders are a common cause of disability and pain. The Shoulder Pain and Disability Index (SPADI) is a frequently employed and previously validated measure of shoulder pain and disability. Although the SPADI has high reliability and construct validity, greater differences between individual patients are often observed than would be expected on the basis of diagnosis and pathophysiology alone. This study aims to determine how psychological factors (namely depression, catastrophic thinking, and self-efficacy) affect pain and perceived disability in the shoulder. A cohort of 139 patients completed a sociodemographic survey and elements from the SPADI, Pain Self-Efficacy Questionnaire (PSEQ), Pain Catastrophizing Scale (PCS), and Patient Health Questionnaire Depression Scale (PHQ-2). Bivariate and multivariate analyses were performed to determine the association of psychosocial factors, demographic characteristics, and specific diagnosis with shoulder pain and disability. The SPADI score showed medium correlation with the PCS (r = 0.43; p < 0.001), PHQ-2 (r = 0.39; p < 0.001), and PSEQ (r = -0.45; p < 0.001). Current work status (F = 4.35; p = 0.006) and body mass index (r = 0.27; p = 0.002) were also associated with the SPADI score. In the multivariate analysis, greater catastrophic thinking (estimate, 0.003; p = 0.029), lower self-efficacy (estimate, -0.005; p = 0.001), higher body mass index (estimate, 0.006; p = 0.048), and being disabled (estimate, 0.15; p = 0.017) or retired (estimate, 0.16; p < 0.001) compared with being employed were associated with worse SPADI scores. The primary diagnosis did not have a significant relationship (p > 0.05) with the SPADI. Catastrophic thinking and decreased self-efficacy are associated with greater shoulder pain and disability. Our data support the notion that patient-to-patient variation in symptom intensity and magnitude of disability is more strongly related to psychological distress than to the specific shoulder diagnosis. Copyright © 2015 by The Journal of Bone and Joint Surgery, Incorporated.

Uncertainty in sap flow-based transpiration due to xylem properties

NASA Astrophysics Data System (ADS)

Looker, N. T.; Hu, J.; Martin, J. T.; Jencso, K. G.

2014-12-01

Transpiration, the evaporative loss of water from plants through their stomata, is a key component of the terrestrial water balance, influencing streamflow as well as regional convective systems. From a plant physiological perspective, transpiration is both a means of avoiding destructive leaf temperatures through evaporative cooling and a consequence of water loss through stomatal uptake of carbon dioxide. Despite its hydrologic and ecological significance, transpiration remains a notoriously challenging process to measure in heterogeneous landscapes. Sap flow methods, which estimate transpiration by tracking the velocity of a heat pulse emitted into the tree sap stream, have proven effective for relating transpiration dynamics to climatic variables. To scale sap flow-based transpiration from the measured domain (often <5 cm of tree cross-sectional area) to the whole-tree level, researchers generally assume constancy of scale factors (e.g., wood thermal diffusivity (k), radial and azimuthal distributions of sap velocity, and conducting sapwood area (As)) through time, across space, and within species. For the widely used heat-ratio sap flow method (HRM), we assessed the sensitivity of transpiration estimates to uncertainty in k (a function of wood moisture content and density) and As. A sensitivity analysis informed by distributions of wood moisture content, wood density and As sampled across a gradient of water availability indicates that uncertainty in these variables can impart substantial error when scaling sap flow measurements to the whole tree. For species with variable wood properties, the application of the HRM assuming a spatially constant k or As may systematically over- or underestimate whole-tree transpiration rates, resulting in compounded error in ecosystem-scale estimates of transpiration.

The reliability of multidimensional neuropsychological measures: from alpha to omega.

PubMed

Watkins, Marley W

To demonstrate that Coefficient omega, a model-based estimate, is more a more appropriate index of reliability than coefficient alpha for the multidimensional scales that are commonly employed by neuropsychologists. As an illustration, a structural model of an overarching general factor and four first-order factors for the WAIS-IV based on the standardization sample of 2200 participants was identified and omega coefficients were subsequently computed for WAIS-IV composite scores. Alpha coefficients were ≥ .90 and omega coefficients ranged from .75 to .88 for WAIS-IV factor index scores, indicating that the blend of general and group factor variance in each index score created a reliable multidimensional composite. However, the amalgam of variance from general and group factors did not allow the precision of Full Scale IQ (FSIQ) and factor index scores to be disentangled. In contrast, omega hierarchical coefficients were low for all four factor index scores (.10-.41), indicating that most of the reliable variance of each factor index score was due to the general intelligence factor. In contrast, the omega hierarchical coefficient for the FSIQ score was .84. Meaningful interpretation of WAIS-IV factor index scores as unambiguous indicators of group factors is imprecise, thereby fostering unreliable identification of neurocognitive strengths and weaknesses, whereas the WAIS-IV FSIQ score can be interpreted as a reliable measure of general intelligence. It was concluded that neuropsychologists should base their clinical decisions on reliable scores as indexed by coefficient omega.

Familiality of factor analysis-derived YBOCS dimensions in OCD-affected sibling pairs from the OCD Collaborative Genetics Study.

PubMed

Hasler, Gregor; Pinto, Anthony; Greenberg, Benjamin D; Samuels, Jack; Fyer, Abby J; Pauls, David; Knowles, James A; McCracken, James T; Piacentini, John; Riddle, Mark A; Rauch, Scott L; Rasmussen, Steven A; Willour, Virginia L; Grados, Marco A; Cullen, Bernadette; Bienvenu, O Joseph; Shugart, Yin-Yao; Liang, Kung-Yee; Hoehn-Saric, Rudolf; Wang, Ying; Ronquillo, Jonne; Nestadt, Gerald; Murphy, Dennis L

2007-03-01

Identification of familial, more homogenous characteristics of obsessive-compulsive disorder (OCD) may help to define relevant subtypes and increase the power of genetic and neurobiological studies of OCD. While factor-analytic studies have found consistent, clinically meaningful OCD symptom dimensions, there have been only limited attempts to evaluate the familiality and potential genetic basis of such dimensions. Four hundred eighteen sibling pairs with OCD were evaluated using the Structured Clinical Interview for DSM-IV and the Yale-Brown Obsessive Compulsive Scale (YBOCS) Symptom Checklist and Severity scales. After controlling for sex, age, and age of onset, robust sib-sib intraclass correlations were found for two of the four YBOCS factors: Factor IV (hoarding obsessions and compulsions (p = .001) and Factor I (aggressive, sexual, and religious obsessions, and checking compulsions; p = .002). Smaller, but still significant, familiality was found for Factor III (contamination/cleaning; p = .02) and Factor II (symmetry/ordering/arranging; p = .04). Limiting the sample to female subjects more than doubled the familiality estimates for Factor II (p = .003). Among potentially relevant comorbid conditions for genetic studies, bipolar I/II and major depressive disorder were strongly associated with Factor I (p < .001), whereas ADHD, alcohol dependence, and bulimia were associated with Factor II (p < .01). Factor-analyzed OCD symptom dimensions in sibling pairs with OCD are familial with some gender-dependence, exhibit relatively specific relationships to comorbid psychiatric disorders and thus may be useful as refined phenotypes for molecular genetic studies of OCD.

A Blind Survey for AGN in the Kepler Field through Optical Variability

NASA Astrophysics Data System (ADS)

Olling, Robert; Shaya, E. J.; Mushotzky, R.

2013-01-01

We present an initial analysis of three quarters of Kepler LLC time series of 400 small galaxies. The Kepler LLC data is sampled about twice per hour, and allows us to investigate variability on time scales between about one day and one month. The calibrated Kepler LLC light curves still contain many instrumental effects that can not be taken out in a robust manner. Instead, our analysis relies on the similarity of variability measures in the three independent quarters to decide if an galaxy shows variability, or not. We estimate that roughly 15% of our small galaxies shows variability at levels exceeding several parts per thousand (mmag) on timescales of days to weeks. However, this estimate is probably uncertain by a factor of two. Our data is more sensitive by several factors of ten as compared to extant data sets.

From direct-space discrepancy functions to crystallographic least squares.

PubMed

Giacovazzo, Carmelo

2015-01-01

Crystallographic least squares are a fundamental tool for crystal structure analysis. In this paper their properties are derived from functions estimating the degree of similarity between two electron-density maps. The new approach leads also to modifications of the standard least-squares procedures, potentially able to improve their efficiency. The role of the scaling factor between observed and model amplitudes is analysed: the concept of unlocated model is discussed and its scattering contribution is combined with that arising from the located model. Also, the possible use of an ancillary parameter, to be associated with the classical weight related to the variance of the observed amplitudes, is studied. The crystallographic discrepancy factors, basic tools often combined with least-squares procedures in phasing approaches, are analysed. The mathematical approach here described includes, as a special case, the so-called vector refinement, used when accurate estimates of the target phases are available.

Statistical properties of the anomalous scaling exponent estimator based on time-averaged mean-square displacement

NASA Astrophysics Data System (ADS)

Sikora, Grzegorz; Teuerle, Marek; Wyłomańska, Agnieszka; Grebenkov, Denis

2017-08-01

The most common way of estimating the anomalous scaling exponent from single-particle trajectories consists of a linear fit of the dependence of the time-averaged mean-square displacement on the lag time at the log-log scale. We investigate the statistical properties of this estimator in the case of fractional Brownian motion (FBM). We determine the mean value, the variance, and the distribution of the estimator. Our theoretical results are confirmed by Monte Carlo simulations. In the limit of long trajectories, the estimator is shown to be asymptotically unbiased, consistent, and with vanishing variance. These properties ensure an accurate estimation of the scaling exponent even from a single (long enough) trajectory. As a consequence, we prove that the usual way to estimate the diffusion exponent of FBM is correct from the statistical point of view. Moreover, the knowledge of the estimator distribution is the first step toward new statistical tests of FBM and toward a more reliable interpretation of the experimental histograms of scaling exponents in microbiology.

Technological renovation of thermal power plants as a long-term check factor of electricity price growth

NASA Astrophysics Data System (ADS)

Veselov, F. V.; Novikova, T. V.; Khorshev, A. A.

2015-12-01

The paper focuses on economic aspects of the Russian thermal generation sector's renovation in a competitive market environment. Capabilities of the existing competitive electricity and capacity pricing mechanisms, created during the wholesale market reform, to ensure the wide-scale modernization of thermal power plants (TPPs) are estimated. Some additional stimulating measures to focus the investment process on the renovation of the thermal generation sector are formulated, and supplementing and supporting costs are assessed. Finally, the systemic effect of decelerating wholesale electricity prices caused by efficiency improvements at thermal power plants is analyzed depending on the scales of renovation and fuel prices.

Characteristics and Impact Factors of Parameter Alpha in the Nonlinear Advection-Aridity Method for Estimating Evapotranspiration at Interannual Scale in the Loess Plateau

NASA Astrophysics Data System (ADS)

Zhou, H.; Liu, W.; Ning, T.

2017-12-01

Land surface actual evapotranspiration plays a key role in the global water and energy cycles. Accurate estimation of evapotranspiration is crucial for understanding the interactions between the land surface and the atmosphere, as well as for managing water resources. The nonlinear advection-aridity approach was formulated by Brutsaert to estimate actual evapotranspiration in 2015. Subsequently, this approach has been verified, applied and developed by many scholars. The estimation, impact factors and correlation analysis of the parameter alpha (αe) of this approach has become important aspects of the research. According to the principle of this approach, the potential evapotranspiration (ETpo) (taking αe as 1) and the apparent potential evapotranspiration (ETpm) were calculated using the meteorological data of 123 sites of the Loess Plateau and its surrounding areas. Then the mean spatial values of precipitation (P), ETpm and ETpo for 13 catchments were obtained by a CoKriging interpolation algorithm. Based on the runoff data of the 13 catchments, actual evapotranspiration was calculated using the catchment water balance equation at the hydrological year scale (May to April of the following year) by ignoring the change of catchment water storage. Thus, the parameter was estimated, and its relationships with P, ETpm and aridity index (ETpm/P) were further analyzed. The results showed that the general range of annual parameter value was 0.385-1.085, with an average value of 0.751 and a standard deviation of 0.113. The mean annual parameter αe value showed different spatial characteristics, with lower values in northern and higher values in southern. The annual scale parameter linearly related with annual P (R2=0.89) and ETpm (R2=0.49), while it exhibited a power function relationship with the aridity index (R2=0.83). Considering the ETpm is a variable in the nonlinear advection-aridity approach in which its effect has been incorporated, the relationship of precipitation and parameter (αe=1.0×10-3*P+0.301) was developed. The value of αe in this study is lower than those in the published literature. The reason is unclear at this point and yet need further investigation. The preliminary application of the nonlinear advection-aridity approach in the Loess Plateau has shown promising results.

Human land use influences chronic wasting disease prevalence in mule deer

USGS Publications Warehouse

Farnsworth, Matthew L.; Wolfe, L.L.; Hobbs, N.T.; Burnham, K.P.; Williams, E.S.; Theobald, D.M.; Conner, M.M.; Miller, M.W.

2005-01-01

Human alteration of landscapes can affect the distribution, abundance, and behavior of wildlife. We explored the effects of human land use on the prevalence of chronic wasting disease (CWD) in mule deer (Odocoileus hemionus) populations residing in north-central Colorado. We chose best approximating models estimating CWD prevalence in relation to differences in human land use, sex, and geographic location. Prevalence was higher in developed areas and among male deer, suggesting anthropogenic influences on the occurrence of disease. We also found a relatively high degree of variation in prevalence across the three study sites, suggesting that spatial patterns in disease may be influenced by other factors operating at a broader, landscape scale. Our results suggest that multiple factors, including changes in land use, differences in exposure risk between sexes, and landscape-scaled heterogeneity, are associated with CWD prevalence in north-central Colorado.

Exploring the dimensionality of digit span.

PubMed

Bowden, Stephen C; Petrauskas, Vilija M; Bardenhagen, Fiona J; Meade, Catherine E; Simpson, Leonie C

2013-04-01

The Digit Span subtest from the Wechsler Scales is used to measure Freedom from Distractibility or Working Memory. Some published research suggests that Digit Span forward should be interpreted differently from Digit Span backward. The present study explored the dimensionality of the Wechsler Memory Scale-III Digit Span (forward and backward) items in a sample of heterogeneous neuroscience patients (n = 267) using confirmatory factor analysis (CFA) for dichotomous items. Results suggested that four correlated factors underlie Digit Span, reflecting easy and hard items in both forward and backward presentation orders. The model for Digit Span was then cross-validated in a seizure disorders sample (n = 223) by replication of the CFA and by examination of measurement invariance. Measurement invariance tests of the precise numerical generalization of trait estimation across groups. Results supported measurement invariance and it was concluded that forward and backward digit span scores should be interpreted as measures of the same cognitive ability.

Random Weighting, Strong Tracking, and Unscented Kalman Filter for Soft Tissue Characterization.

PubMed

Shin, Jaehyun; Zhong, Yongmin; Oetomo, Denny; Gu, Chengfan

2018-05-21

This paper presents a new nonlinear filtering method based on the Hunt-Crossley model for online nonlinear soft tissue characterization. This method overcomes the problem of performance degradation in the unscented Kalman filter due to contact model error. It adopts the concept of Mahalanobis distance to identify contact model error, and further incorporates a scaling factor in predicted state covariance to compensate identified model error. This scaling factor is determined according to the principle of innovation orthogonality to avoid the cumbersome computation of Jacobian matrix, where the random weighting concept is adopted to improve the estimation accuracy of innovation covariance. A master-slave robotic indentation system is developed to validate the performance of the proposed method. Simulation and experimental results as well as comparison analyses demonstrate that the efficacy of the proposed method for online characterization of soft tissue parameters in the presence of contact model error.

Estimating basin scale evapotranspiration (ET) by water balance and remote sensing methods

USGS Publications Warehouse

Senay, G.B.; Leake, S.; Nagler, P.L.; Artan, G.; Dickinson, J.; Cordova, J.T.; Glenn, E.P.

2011-01-01

Evapotranspiration (ET) is an important hydrological process that can be studied and estimated at multiple spatial scales ranging from a leaf to a river basin. We present a review of methods in estimating basin scale ET and its applications in understanding basin water balance dynamics. The review focuses on two aspects of ET: (i) how the basin scale water balance approach is used to estimate ET; and (ii) how ‘direct’ measurement and modelling approaches are used to estimate basin scale ET. Obviously, the basin water balance-based ET requires the availability of good precipitation and discharge data to calculate ET as a residual on longer time scales (annual) where net storage changes are assumed to be negligible. ET estimated from such a basin water balance principle is generally used for validating the performance of ET models. On the other hand, many of the direct estimation methods involve the use of remotely sensed data to estimate spatially explicit ET and use basin-wide averaging to estimate basin scale ET. The direct methods can be grouped into soil moisture balance modelling, satellite-based vegetation index methods, and methods based on satellite land surface temperature measurements that convert potential ET into actual ET using a proportionality relationship. The review also includes the use of complementary ET estimation principles for large area applications. The review identifies the need to compare and evaluate the different ET approaches using standard data sets in basins covering different hydro-climatic regions of the world.

Improving FIA trend analysis through model-based estimation using landsat disturbance maps and the forest vegetation simulator

Treesearch

Sean P. Healey; Gretchen G. Moisen; Paul L. Patterson

2012-01-01

The Forest Inventory and Analysis (FIA) Program's panel system, in which 10-20 percent of the sample is measured in any given year, is designed to increase the currency of FIA reporting and its sensitivity to factors operating at relatively fine temporal scales. Now that much of the country has completed at least one measurement cycle over all panels, there is an...

Inter-annual variability and spatial coherence of net primary productivity across a western Oregon Cascades landscape

Treesearch

Travis J. Woolley; Mark E. Harmon; Kari B. O’Connell

2015-01-01

Inter-annual variability (IAV) of forest Net Primary Productivity (NPP) is a function of both extrinsic (e.g., climate) and intrinsic (e.g., stand dynamics) drivers. As estimates of NPP in forests are scaled from trees to stands to the landscape, an understanding of the relative effects of these factors on spatial and temporal behavior of NPP is important. Although a...

Extra dimension searches at hadron colliders to next-to-leading order-QCD

NASA Astrophysics Data System (ADS)

Kumar, M. C.; Mathews, Prakash; Ravindran, V.

2007-11-01

The quantitative impact of NLO-QCD corrections for searches of large and warped extra dimensions at hadron colliders are investigated for the Drell-Yan process. The K-factor for various observables at hadron colliders are presented. Factorisation, renormalisation scale dependence and uncertainties due to various parton distribution functions are studied. Uncertainties arising from the error on experimental data are estimated using the MRST parton distribution functions.

DE-Sync: A Doppler-Enhanced Time Synchronization for Mobile Underwater Sensor Networks.

PubMed

Zhou, Feng; Wang, Qi; Nie, DongHu; Qiao, Gang

2018-05-25

Time synchronization is the foundation of cooperative work among nodes of underwater sensor networks; it takes a critical role in the research and application of underwater sensor networks. Although numerous time synchronization protocols have been proposed for terrestrial wireless sensor networks, they cannot be directly applied to underwater sensor networks. This is because most of them typically assume that the propagation delay among sensor nodes is negligible, which is not the case in underwater sensor networks. Time synchronization is mainly affected by a long propagation delay among sensor nodes due to the low propagation speed of acoustic signals. Furthermore, sensor nodes in underwater tend to experience some degree of mobility due to wind or ocean current, or some other nodes are on self-propelled vehicles, such as autonomous underwater vehicles (AUVs). In this paper, we propose a Doppler-enhanced time synchronization scheme for mobile underwater sensor networks, called DE-Sync. Our new scheme considers the effect of the clock skew during the process of estimating the Doppler scale factor and directly substitutes the Doppler scale factor into linear regression to achieve the estimation of the clock skew and offset. Simulation results show that DE-Sync outperforms existing time synchronization protocols in both accuracy and energy efficiency.

Solution of the Eshelby problem in gradient elasticity for multilayer spherical inclusions

NASA Astrophysics Data System (ADS)

Volkov-Bogorodskii, D. B.; Lurie, S. A.

2016-03-01

We consider gradient models of elasticity which permit taking into account the characteristic scale parameters of the material. We prove the Papkovich-Neuber theorems, which determine the general form of the gradient solution and the structure of scale effects. We derive the Eshelby integral formula for the gradient moduli of elasticity, which plays the role of the closing equation in the self-consistent three-phase method. In the gradient theory of deformations, we consider the fundamental Eshelby-Christensen problem of determining the effective elastic properties of dispersed composites with spherical inclusions; the exact solution of this problem for classical models was obtained in 1976. This paper is the first to present the exact analytical solution of the Eshelby-Christensen problem for the gradient theory, which permits estimating the influence of scale effects on the stress state and the effective properties of the dispersed composites under study.We also analyze the influence of scale factors.

Anti-intellectualism and political ideology in a sample of undergraduate and graduate students.

PubMed

Laverghetta, Antonio; Stewart, Juliana; Weinstein, Lawrence

2007-12-01

To estimate correlations for scores on a student anti-intellectualism scale with scores on a measure of political conservatism, 235 students were given a survey containing a student anti-intellectualism scale, a political conservatism scale, and a demographics questionnaire identifying the participants' sex, college classification, ethnicity, political party affiliation, and self-described political ideology. The political conservatism scale contained two factors, Religiosity and Economic Conservatism, both of which were scored separately in addition to an overall Conservatism score. Students' Anti-intellectualism scores were correlated with Political Conservatism scores (r = .37, p < .01), with Religiosity scores (r = .42, p < .01), and with Economic Conservatism scores (r = .17, p < .05). An analysis of variance indicated a significant difference in students' Anti-intellectualism scores based on college classification (F4,233 = 2.27, p < .04). Specifically, freshman had significantly higher scores than graduate students.

Global-scale modeling of groundwater recharge

NASA Astrophysics Data System (ADS)

Döll, P.; Fiedler, K.

2008-05-01

Long-term average groundwater recharge, which is equivalent to renewable groundwater resources, is the major limiting factor for the sustainable use of groundwater. Compared to surface water resources, groundwater resources are more protected from pollution, and their use is less restricted by seasonal and inter-annual flow variations. To support water management in a globalized world, it is necessary to estimate groundwater recharge at the global scale. Here, we present a best estimate of global-scale long-term average diffuse groundwater recharge (i.e. renewable groundwater resources) that has been calculated by the most recent version of the WaterGAP Global Hydrology Model WGHM (spatial resolution of 0.5° by 0.5°, daily time steps). The estimate was obtained using two state-of-the-art global data sets of gridded observed precipitation that we corrected for measurement errors, which also allowed to quantify the uncertainty due to these equally uncertain data sets. The standard WGHM groundwater recharge algorithm was modified for semi-arid and arid regions, based on independent estimates of diffuse groundwater recharge, which lead to an unbiased estimation of groundwater recharge in these regions. WGHM was tuned against observed long-term average river discharge at 1235 gauging stations by adjusting, individually for each basin, the partitioning of precipitation into evapotranspiration and total runoff. We estimate that global groundwater recharge was 12 666 km3/yr for the climate normal 1961-1990, i.e. 32% of total renewable water resources. In semi-arid and arid regions, mountainous regions, permafrost regions and in the Asian Monsoon region, groundwater recharge accounts for a lower fraction of total runoff, which makes these regions particularly vulnerable to seasonal and inter-annual precipitation variability and water pollution. Average per-capita renewable groundwater resources of countries vary between 8 m3/(capita yr) for Egypt to more than 1 million m3/(capita yr) for the Falkland Islands, the global average in the year 2000 being 2091 m3/(capita yr). Regarding the uncertainty of estimated groundwater resources due to the two precipitation data sets, deviation from the mean is 1.1% for the global value, and less than 1% for 50 out of the 165 countries considered, between 1 and 5% for 62, between 5 and 20% for 43 and between 20 and 80% for 10 countries. Deviations at the grid scale can be much larger, ranging between 0 and 186 mm/yr.