Instrumental Variable Analysis with a Nonlinear Exposure–Outcome Relationship

PubMed Central

Davies, Neil M.; Thompson, Simon G.

2014-01-01

Background: Instrumental variable methods can estimate the causal effect of an exposure on an outcome using observational data. Many instrumental variable methods assume that the exposure–outcome relation is linear, but in practice this assumption is often in doubt, or perhaps the shape of the relation is a target for investigation. We investigate this issue in the context of Mendelian randomization, the use of genetic variants as instrumental variables. Methods: Using simulations, we demonstrate the performance of a simple linear instrumental variable method when the true shape of the exposure–outcome relation is not linear. We also present a novel method for estimating the effect of the exposure on the outcome within strata of the exposure distribution. This enables the estimation of localized average causal effects within quantile groups of the exposure or as a continuous function of the exposure using a sliding window approach. Results: Our simulations suggest that linear instrumental variable estimates approximate a population-averaged causal effect. This is the average difference in the outcome if the exposure for every individual in the population is increased by a fixed amount. Estimates of localized average causal effects reveal the shape of the exposure–outcome relation for a variety of models. These methods are used to investigate the relations between body mass index and a range of cardiovascular risk factors. Conclusions: Nonlinear exposure–outcome relations should not be a barrier to instrumental variable analyses. When the exposure–outcome relation is not linear, either a population-averaged causal effect or the shape of the exposure–outcome relation can be estimated. PMID:25166881

Regression calibration for models with two predictor variables measured with error and their interaction, using instrumental variables and longitudinal data.

PubMed

Strand, Matthew; Sillau, Stefan; Grunwald, Gary K; Rabinovitch, Nathan

2014-02-10

Regression calibration provides a way to obtain unbiased estimators of fixed effects in regression models when one or more predictors are measured with error. Recent development of measurement error methods has focused on models that include interaction terms between measured-with-error predictors, and separately, methods for estimation in models that account for correlated data. In this work, we derive explicit and novel forms of regression calibration estimators and associated asymptotic variances for longitudinal models that include interaction terms, when data from instrumental and unbiased surrogate variables are available but not the actual predictors of interest. The longitudinal data are fit using linear mixed models that contain random intercepts and account for serial correlation and unequally spaced observations. The motivating application involves a longitudinal study of exposure to two pollutants (predictors) - outdoor fine particulate matter and cigarette smoke - and their association in interactive form with levels of a biomarker of inflammation, leukotriene E4 (LTE 4 , outcome) in asthmatic children. Because the exposure concentrations could not be directly observed, we used measurements from a fixed outdoor monitor and urinary cotinine concentrations as instrumental variables, and we used concentrations of fine ambient particulate matter and cigarette smoke measured with error by personal monitors as unbiased surrogate variables. We applied the derived regression calibration methods to estimate coefficients of the unobserved predictors and their interaction, allowing for direct comparison of toxicity of the different pollutants. We used simulations to verify accuracy of inferential methods based on asymptotic theory. Copyright © 2013 John Wiley & Sons, Ltd.

Health insurance for the poor: impact on catastrophic and out-of-pocket health expenditures in Mexico

PubMed Central

Galárraga, Omar; Salinas-Rodríguez, Aarón; Sesma-Vázquez, Sergio

2009-01-01

The goal of Seguro Popular (SP) in Mexico was to improve the financial protection of the uninsured population against excessive health expenditures. This paper estimates the impact of SP on catastrophic health expenditures (CHE), as well as out-of-pocket (OOP) health expenditures, from two different sources. First, we use the SP Impact Evaluation Survey (2005–2006), and compare the instrumental variables (IV) results with the experimental benchmark. Then, we use the same IV methods with the National Health and Nutrition Survey (ENSANUT 2006). We estimate naïve models, assuming exogeneity, and contrast them with IV models that take advantage of the specific SP implementation mechanisms for identification. The IV models estimated included two-stage least squares (2SLS), bivariate probit, and two-stage residual inclusion (2SRI) models. Instrumental variables estimates resulted in comparable estimates against the “gold standard.” Instrumental variables estimates indicate a reduction of 54% in catastrophic expenditures at the national level. SP beneficiaries also had lower expenditures on outpatient and medicine expenditures. The selection-corrected protective effect is found not only in the limited experimental dataset, but also at the national level. PMID:19756796

Health insurance for the poor: impact on catastrophic and out-of-pocket health expenditures in Mexico.

PubMed

Galárraga, Omar; Sosa-Rubí, Sandra G; Salinas-Rodríguez, Aarón; Sesma-Vázquez, Sergio

2010-10-01

The goal of Seguro Popular (SP) in Mexico was to improve the financial protection of the uninsured population against excessive health expenditures. This paper estimates the impact of SP on catastrophic health expenditures (CHE), as well as out-of-pocket (OOP) health expenditures, from two different sources. First, we use the SP Impact Evaluation Survey (2005-2006), and compare the instrumental variables (IV) results with the experimental benchmark. Then, we use the same IV methods with the National Health and Nutrition Survey (ENSANUT 2006). We estimate naïve models, assuming exogeneity, and contrast them with IV models that take advantage of the specific SP implementation mechanisms for identification. The IV models estimated included two-stage least squares (2SLS), bivariate probit, and two-stage residual inclusion (2SRI) models. Instrumental variables estimates resulted in comparable estimates against the "gold standard." Instrumental variables estimates indicate a reduction of 54% in catastrophic expenditures at the national level. SP beneficiaries also had lower expenditures on outpatient and medicine expenditures. The selection-corrected protective effect is found not only in the limited experimental dataset, but also at the national level.

Evaluation of Validity and Reliability for Hierarchical Scales Using Latent Variable Modeling

ERIC Educational Resources Information Center

Raykov, Tenko; Marcoulides, George A.

2012-01-01

A latent variable modeling method is outlined, which accomplishes estimation of criterion validity and reliability for a multicomponent measuring instrument with hierarchical structure. The approach provides point and interval estimates for the scale criterion validity and reliability coefficients, and can also be used for testing composite or…

Meta-Analysis of Scale Reliability Using Latent Variable Modeling

ERIC Educational Resources Information Center

Raykov, Tenko; Marcoulides, George A.

2013-01-01

A latent variable modeling approach is outlined that can be used for meta-analysis of reliability coefficients of multicomponent measuring instruments. Important limitations of efforts to combine composite reliability findings across multiple studies are initially pointed out. A reliability synthesis procedure is discussed that is based on…

Regularization Methods for High-Dimensional Instrumental Variables Regression With an Application to Genetical Genomics

PubMed Central

Lin, Wei; Feng, Rui; Li, Hongzhe

2014-01-01

In genetical genomics studies, it is important to jointly analyze gene expression data and genetic variants in exploring their associations with complex traits, where the dimensionality of gene expressions and genetic variants can both be much larger than the sample size. Motivated by such modern applications, we consider the problem of variable selection and estimation in high-dimensional sparse instrumental variables models. To overcome the difficulty of high dimensionality and unknown optimal instruments, we propose a two-stage regularization framework for identifying and estimating important covariate effects while selecting and estimating optimal instruments. The methodology extends the classical two-stage least squares estimator to high dimensions by exploiting sparsity using sparsity-inducing penalty functions in both stages. The resulting procedure is efficiently implemented by coordinate descent optimization. For the representative L1 regularization and a class of concave regularization methods, we establish estimation, prediction, and model selection properties of the two-stage regularized estimators in the high-dimensional setting where the dimensionality of co-variates and instruments are both allowed to grow exponentially with the sample size. The practical performance of the proposed method is evaluated by simulation studies and its usefulness is illustrated by an analysis of mouse obesity data. Supplementary materials for this article are available online. PMID:26392642

Developing a theoretical model and questionnaire survey instrument to measure the success of electronic health records in residential aged care

PubMed Central

Yu, Ping; Qian, Siyu

2018-01-01

Electronic health records (EHR) are introduced into healthcare organizations worldwide to improve patient safety, healthcare quality and efficiency. A rigorous evaluation of this technology is important to reduce potential negative effects on patient and staff, to provide decision makers with accurate information for system improvement and to ensure return on investment. Therefore, this study develops a theoretical model and questionnaire survey instrument to assess the success of organizational EHR in routine use from the viewpoint of nursing staff in residential aged care homes. The proposed research model incorporates six variables in the reformulated DeLone and McLean information systems success model: system quality, information quality, service quality, use, user satisfaction and net benefits. Two variables training and self-efficacy were also incorporated into the model. A questionnaire survey instrument was designed to measure the eight variables in the model. After a pilot test, the measurement scale was used to collect data from 243 nursing staff members in 10 residential aged care homes belonging to three management groups in Australia. Partial least squares path modeling was conducted to validate the model. The validated EHR systems success model predicts the impact of the four antecedent variables—training, self-efficacy, system quality and information quality—on the net benefits, the indicator of EHR systems success, through the intermittent variables use and user satisfaction. A 24-item measurement scale was developed to quantitatively evaluate the performance of an EHR system. The parsimonious EHR systems success model and the measurement scale can be used to benchmark EHR systems success across organizations and units and over time. PMID:29315323

Evaluating disease management programme effectiveness: an introduction to instrumental variables.

PubMed

Linden, Ariel; Adams, John L

2006-04-01

This paper introduces the concept of instrumental variables (IVs) as a means of providing an unbiased estimate of treatment effects in evaluating disease management (DM) programme effectiveness. Model development is described using zip codes as the IV. Three diabetes DM outcomes were evaluated: annual diabetes costs, emergency department (ED) visits and hospital days. Both ordinary least squares (OLS) and IV estimates showed a significant treatment effect for diabetes costs (P = 0.011) but neither model produced a significant treatment effect for ED visits. However, the IV estimate showed a significant treatment effect for hospital days (P = 0.006) whereas the OLS model did not. These results illustrate the utility of IV estimation when the OLS model is sensitive to the confounding effect of hidden bias.

Density dependence and climate effects in Rocky Mountain elk: an application of regression with instrumental variables for population time series with sampling error.

PubMed

Creel, Scott; Creel, Michael

2009-11-01

1. Sampling error in annual estimates of population size creates two widely recognized problems for the analysis of population growth. First, if sampling error is mistakenly treated as process error, one obtains inflated estimates of the variation in true population trajectories (Staples, Taper & Dennis 2004). Second, treating sampling error as process error is thought to overestimate the importance of density dependence in population growth (Viljugrein et al. 2005; Dennis et al. 2006). 2. In ecology, state-space models are used to account for sampling error when estimating the effects of density and other variables on population growth (Staples et al. 2004; Dennis et al. 2006). In econometrics, regression with instrumental variables is a well-established method that addresses the problem of correlation between regressors and the error term, but requires fewer assumptions than state-space models (Davidson & MacKinnon 1993; Cameron & Trivedi 2005). 3. We used instrumental variables to account for sampling error and fit a generalized linear model to 472 annual observations of population size for 35 Elk Management Units in Montana, from 1928 to 2004. We compared this model with state-space models fit with the likelihood function of Dennis et al. (2006). We discuss the general advantages and disadvantages of each method. Briefly, regression with instrumental variables is valid with fewer distributional assumptions, but state-space models are more efficient when their distributional assumptions are met. 4. Both methods found that population growth was negatively related to population density and winter snow accumulation. Summer rainfall and wolf (Canis lupus) presence had much weaker effects on elk (Cervus elaphus) dynamics [though limitation by wolves is strong in some elk populations with well-established wolf populations (Creel et al. 2007; Creel & Christianson 2008)]. 5. Coupled with predictions for Montana from global and regional climate models, our results predict a substantial reduction in the limiting effect of snow accumulation on Montana elk populations in the coming decades. If other limiting factors do not operate with greater force, population growth rates would increase substantially.

A selective review of the first 20 years of instrumental variables models in health-services research and medicine.

PubMed

Cawley, John

2015-01-01

The method of instrumental variables (IV) is useful for estimating causal effects. Intuitively, it exploits exogenous variation in the treatment, sometimes called natural experiments or instruments. This study reviews the literature in health-services research and medical research that applies the method of instrumental variables, documents trends in its use, and offers examples of various types of instruments. A literature search of the PubMed and EconLit research databases for English-language journal articles published after 1990 yielded a total of 522 original research articles. Citations counts for each article were derived from the Web of Science. A selective review was conducted, with articles prioritized based on number of citations, validity and power of the instrument, and type of instrument. The average annual number of papers in health services research and medical research that apply the method of instrumental variables rose from 1.2 in 1991-1995 to 41.8 in 2006-2010. Commonly-used instruments (natural experiments) in health and medicine are relative distance to a medical care provider offering the treatment and the medical care provider's historic tendency to administer the treatment. Less common but still noteworthy instruments include randomization of treatment for reasons other than research, randomized encouragement to undertake the treatment, day of week of admission as an instrument for waiting time for surgery, and genes as an instrument for whether the respondent has a heritable condition. The use of the method of IV has increased dramatically in the past 20 years, and a wide range of instruments have been used. Applications of the method of IV have in several cases upended conventional wisdom that was based on correlations and led to important insights about health and healthcare. Future research should pursue new applications of existing instruments and search for new instruments that are powerful and valid.

Evaluation of Scale Reliability with Binary Measures Using Latent Variable Modeling

ERIC Educational Resources Information Center

Raykov, Tenko; Dimitrov, Dimiter M.; Asparouhov, Tihomir

2010-01-01

A method for interval estimation of scale reliability with discrete data is outlined. The approach is applicable with multi-item instruments consisting of binary measures, and is developed within the latent variable modeling methodology. The procedure is useful for evaluation of consistency of single measures and of sum scores from item sets…

Variables Affecting Preservice Teacher Candidate Identification of Teacher Sexual Misconduct

ERIC Educational Resources Information Center

Haverland, Jeffrey A.

2017-01-01

Using a quantitative research model, this study explored variables affecting pre-service teacher candidate identification of teacher sexual misconduct through a scenario-based survey instrument. Independent variables in this study were respondent gender, student gender, teacher gender, student age-related ambiguity (students depicted were 17),…

Critical evaluation of connectivity-based point of care testing systems of glucose in a hospital environment.

PubMed

Floré, Katelijne M J; Fiers, Tom; Delanghe, Joris R

2008-01-01

In recent years a number of point of care testing (POCT) glucometers were introduced on the market. We investigated the analytical variability (lot-to-lot variation, calibration error, inter-instrument and inter-operator variability) of glucose POCT systems in a university hospital environment and compared these results with the analytical needs required for tight glucose monitoring. The reference hexokinase method was compared to different POCT systems based on glucose oxidase (blood gas instruments) or glucose dehydrogenase (handheld glucometers). Based upon daily internal quality control data, total errors were calculated for the various glucose methods and the analytical variability of the glucometers was estimated. The total error of the glucometers exceeded by far the desirable analytical specifications (based on a biological variability model). Lot-to-lot variation, inter-instrument variation and inter-operator variability contributed approximately equally to total variance. As in a hospital environment, distribution of hematocrit values is broad, converting blood glucose into plasma values using a fixed factor further increases variance. The percentage of outliers exceeded the ISO 15197 criteria in a broad glucose concentration range. Total analytical variation of handheld glucometers is larger than expected. Clinicians should be aware that the variability of glucose measurements obtained by blood gas instruments is lower than results obtained with handheld glucometers on capillary blood.

Instrumental variables as bias amplifiers with general outcome and confounding.

PubMed

Ding, P; VanderWeele, T J; Robins, J M

2017-06-01

Drawing causal inference with observational studies is the central pillar of many disciplines. One sufficient condition for identifying the causal effect is that the treatment-outcome relationship is unconfounded conditional on the observed covariates. It is often believed that the more covariates we condition on, the more plausible this unconfoundedness assumption is. This belief has had a huge impact on practical causal inference, suggesting that we should adjust for all pretreatment covariates. However, when there is unmeasured confounding between the treatment and outcome, estimators adjusting for some pretreatment covariate might have greater bias than estimators without adjusting for this covariate. This kind of covariate is called a bias amplifier, and includes instrumental variables that are independent of the confounder, and affect the outcome only through the treatment. Previously, theoretical results for this phenomenon have been established only for linear models. We fill in this gap in the literature by providing a general theory, showing that this phenomenon happens under a wide class of models satisfying certain monotonicity assumptions. We further show that when the treatment follows an additive or multiplicative model conditional on the instrumental variable and the confounder, these monotonicity assumptions can be interpreted as the signs of the arrows of the causal diagrams.

Network Mendelian randomization: using genetic variants as instrumental variables to investigate mediation in causal pathways

PubMed Central

Burgess, Stephen; Daniel, Rhian M; Butterworth, Adam S; Thompson, Simon G

2015-01-01

Background: Mendelian randomization uses genetic variants, assumed to be instrumental variables for a particular exposure, to estimate the causal effect of that exposure on an outcome. If the instrumental variable criteria are satisfied, the resulting estimator is consistent even in the presence of unmeasured confounding and reverse causation. Methods: We extend the Mendelian randomization paradigm to investigate more complex networks of relationships between variables, in particular where some of the effect of an exposure on the outcome may operate through an intermediate variable (a mediator). If instrumental variables for the exposure and mediator are available, direct and indirect effects of the exposure on the outcome can be estimated, for example using either a regression-based method or structural equation models. The direction of effect between the exposure and a possible mediator can also be assessed. Methods are illustrated in an applied example considering causal relationships between body mass index, C-reactive protein and uric acid. Results: These estimators are consistent in the presence of unmeasured confounding if, in addition to the instrumental variable assumptions, the effects of both the exposure on the mediator and the mediator on the outcome are homogeneous across individuals and linear without interactions. Nevertheless, a simulation study demonstrates that even considerable heterogeneity in these effects does not lead to bias in the estimates. Conclusions: These methods can be used to estimate direct and indirect causal effects in a mediation setting, and have potential for the investigation of more complex networks between multiple interrelated exposures and disease outcomes. PMID:25150977

Application of Influence Diagrams in Identifying Soviet Satellite Missions

DTIC Science & Technology

1990-12-01

Probabilities Comparison ......................... 58 35. Continuous Model Variables ............................ 59 36. Sample Inclination Data...diagramming is a method which allows the simple construction of a model to illustrate the interrelationships which exist among variables by capturing an...environmental monitoring systems. The module also contained an array of instruments for geophysical and astrophysical experimentation . 4.3.14.3 Soyuz. The Soyuz

A Direct Latent Variable Modeling Based Method for Point and Interval Estimation of Coefficient Alpha

ERIC Educational Resources Information Center

Raykov, Tenko; Marcoulides, George A.

2015-01-01

A direct approach to point and interval estimation of Cronbach's coefficient alpha for multiple component measuring instruments is outlined. The procedure is based on a latent variable modeling application with widely circulated software. As a by-product, using sample data the method permits ascertaining whether the population discrepancy…

GENES AS INSTRUMENTS FOR STUDYING RISK BEHAVIOR EFFECTS: AN APPLICATION TO MATERNAL SMOKING AND OROFACIAL CLEFTS

PubMed Central

Jugessur, Astanand; Murray, Jeffrey C.; Moreno, Lina; Wilcox, Allen; Lie, Rolv T.

2011-01-01

This study uses instrumental variable (IV) models with genetic instruments to assess the effects of maternal smoking on the child’s risk of orofacial clefts (OFC), a common birth defect. The study uses genotypic variants in neurotransmitter and detoxification genes relateded to smoking as instruments for cigarette smoking before and during pregnancy. Conditional maximum likelihood and two-stage IV probit models are used to estimate the IV model. The data are from a population-level sample of affected and unaffected children in Norway. The selected genetic instruments generally fit the IV assumptions but may be considered “weak” in predicting cigarette smoking. We find that smoking before and during pregnancy increases OFC risk substantially under the IV model (by about 4–5 times at the sample average smoking rate). This effect is greater than that found with classical analytic models. This may be because the usual models are not able to consider self-selection into smoking based on unobserved confounders, or it may to some degree reflect limitations of the instruments. Inference based on weak-instrument robust confidence bounds is consistent with standard inference. Genetic instruments may provide a valuable approach to estimate the “causal” effects of risk behaviors with genetic-predisposing factors (such as smoking) on health and socioeconomic outcomes. PMID:22102793

Construction of the descriptive system for the assessment of quality of life AQoL-6D utility instrument

PubMed Central

2012-01-01

Background Multi attribute utility (MAU) instruments are used to include the health related quality of life (HRQoL) in economic evaluations of health programs. Comparative studies suggest different MAU instruments measure related but different constructs. The objective of this paper is to describe the methods employed to achieve content validity in the descriptive system of the Assessment of Quality of Life (AQoL)-6D, MAU instrument. Methods The AQoL program introduced the use of psychometric methods in the construction of health related MAU instruments. To develop the AQoL-6D we selected 112 items from previous research, focus groups and expert judgment and administered them to 316 members of the public and 302 hospital patients. The search for content validity across a broad spectrum of health states required both formative and reflective modelling. We employed Exploratory Factor Analysis and Structural Equation Modelling (SEM) to meet these dual requirements. Results and Discussion The resulting instrument employs 20 items in a multi-tier descriptive system. Latent dimension variables achieve sensitive descriptions of 6 dimensions which, in turn, combine to form a single latent QoL variable. Diagnostic statistics from the SEM analysis are exceptionally good and confirm the hypothesised structure of the model. Conclusions The AQoL-6D descriptive system has good psychometric properties. They imply that the instrument has achieved construct validity and provides a sensitive description of HRQoL. This means that it may be used with confidence for measuring health related quality of life and that it is a suitable basis for modelling utilities for inclusion in the economic evaluation of health programs. PMID:22507254

Construction of the descriptive system for the Assessment of Quality of Life AQoL-6D utility instrument.

PubMed

Richardson, Jeffrey R J; Peacock, Stuart J; Hawthorne, Graeme; Iezzi, Angelo; Elsworth, Gerald; Day, Neil A

2012-04-17

Multi attribute utility (MAU) instruments are used to include the health related quality of life (HRQoL) in economic evaluations of health programs. Comparative studies suggest different MAU instruments measure related but different constructs. The objective of this paper is to describe the methods employed to achieve content validity in the descriptive system of the Assessment of Quality of Life (AQoL)-6D, MAU instrument. The AQoL program introduced the use of psychometric methods in the construction of health related MAU instruments. To develop the AQoL-6D we selected 112 items from previous research, focus groups and expert judgment and administered them to 316 members of the public and 302 hospital patients. The search for content validity across a broad spectrum of health states required both formative and reflective modelling. We employed Exploratory Factor Analysis and Structural Equation Modelling (SEM) to meet these dual requirements. The resulting instrument employs 20 items in a multi-tier descriptive system. Latent dimension variables achieve sensitive descriptions of 6 dimensions which, in turn, combine to form a single latent QoL variable. Diagnostic statistics from the SEM analysis are exceptionally good and confirm the hypothesised structure of the model. The AQoL-6D descriptive system has good psychometric properties. They imply that the instrument has achieved construct validity and provides a sensitive description of HRQoL. This means that it may be used with confidence for measuring health related quality of life and that it is a suitable basis for modelling utilities for inclusion in the economic evaluation of health programs.

Too much ado about instrumental variable approach: is the cure worse than the disease?

PubMed

Baser, Onur

2009-01-01

To review the efficacy of instrumental variable (IV) models in addressing a variety of assumption violations to ensure standard ordinary least squares (OLS) estimates are consistent. IV models gained popularity in outcomes research because of their ability to consistently estimate the average causal effects even in the presence of unmeasured confounding. However, in order for this consistent estimation to be achieved, several conditions must hold. In this article, we provide an overview of the IV approach, examine possible tests to check the prerequisite conditions, and illustrate how weak instruments may produce inconsistent and inefficient results. We use two IVs and apply Shea's partial R-square method, the Anderson canonical correlation, and Cragg-Donald tests to check for weak instruments. Hall-Peixe tests are applied to see if any of these instruments are redundant in the analysis. A total of 14,952 asthma patients from the MarketScan Commercial Claims and Encounters Database were examined in this study. Patient health care was provided under a variety of fee-for-service, fully capitated, and partially capitated health plans, including preferred provider organizations, point of service plans, indemnity plans, and health maintenance organizations. We used controller-reliever copay ratio and physician practice/prescribing patterns as an instrument. We demonstrated that the former was a weak and redundant instrument producing inconsistent and inefficient estimates of the effect of treatment. The results were worse than the results from standard regression analysis. Despite the obvious benefit of IV models, the method should not be used blindly. Several strong conditions are required for these models to work, and each of them should be tested. Otherwise, bias and precision of the results will be statistically worse than the results achieved by simply using standard OLS.

The long view: Causes of climate change over the instrumental period

NASA Astrophysics Data System (ADS)

Hegerl, G. C.; Schurer, A. P.; Polson, D.; Iles, C. E.; Bronnimann, S.

2016-12-01

The period of instrumentally recorded data has seen remarkable changes in climate, with periods of rapid warming, and periods of stagnation or cooling. A recent analysis of the observed temperature change from the instrumental record confirms that most of the warming recorded since the middle of the 20rst century has been caused by human influences, but shows large uncertainty in separating greenhouse gas from aerosol response if accounting for model uncertainty. The contribution by natural forcing and internal variability to the recent warming is estimated to be small, but becomes more important when analysing climate change over earlier or shorter time periods. For example, the enigmatic early 20th century warming was a period of strong climate anomalies, including the US dustbowl drought and exceptional heat waves, and pronounced Arctic warming. Attribution results suggests that about half of the global warming 1901-1950 was forced by greenhouse gases increases, with an anomalously strong contribution by climate variability, and contributions by natural forcing. Long term variations in circulation are important for some regional climate anomalies. Precipitation is important for impacts of climate change and precipitation changes are uncertain in models. Analysis of the instrumental record suggests a human influence on mean and heavy precipitation, and supports climate model estimates of the spatial pattern of precipitation sensitivity to warming. Broadly, and particularly over ocean, wet regions are getting wetter and dry regions are getting drier. In conclusion, the historical record provides evidence for a strong response to external forcings, supports climate models, and raises questions about multi-decadal variability.

NIST/ISAC standardization study: variability in assignment of intensity values to fluorescence standard beads and in cross calibration of standard beads to hard dyed beads.

PubMed

Hoffman, Robert A; Wang, Lili; Bigos, Martin; Nolan, John P

2012-09-01

Results from a standardization study cosponsored by the International Society for Advancement of Cytometry (ISAC) and the US National Institute of Standards and Technology (NIST) are reported. The study evaluated the variability of assigning intensity values to fluorophore standard beads by bead manufacturers and the variability of cross calibrating the standard beads to stained polymer beads (hard-dyed beads) using different flow cytometers. Hard dyed beads are generally not spectrally matched to the fluorophores used to stain cells, and spectral response varies among flow cytometers. Thus if hard dyed beads are used as fluorescence calibrators, one expects calibration for specific fluorophores (e.g., FITC or PE) to vary among different instruments. Using standard beads surface-stained with specific fluorophores (FITC, PE, APC, and Pacific Blue™), the study compared the measured intensity of fluorophore standard beads to that of hard dyed beads through cross calibration on 133 different flow cytometers. Using robust CV as a measure of variability, the variation of cross calibrated values was typically 20% or more for a particular hard dyed bead in a specific detection channel. The variation across different instrument models was often greater than the variation within a particular instrument model. As a separate part of the study, NIST and four bead manufacturers used a NIST supplied protocol and calibrated fluorophore solution standards to assign intensity values to the fluorophore beads. Values assigned to the reference beads by different groups varied by orders of magnitude in most cases, reflecting differences in instrumentation used to perform the calibration. The study concluded that the use of any spectrally unmatched hard dyed bead as a general fluorescence calibrator must be verified and characterized for every particular instrument model. Close interaction between bead manufacturers and NIST is recommended to have reliable and uniformly assigned fluorescence standard beads. Copyright © 2012 International Society for Advancement of Cytometry.

The Effect of Private Insurance on the Health of Older, Working Age Adults: Evidence from the Health and Retirement Study

PubMed Central

Dor, Avi; Sudano, Joseph; Baker, David W

2006-01-01

Objective Primarily, to determine if the presence of private insurance leads to improved health status, as measured by a survey-based health score. Secondarily, to explore sensitivity of estimates to adjustments for endogeneity. The study focuses on adults in late middle age who are nearing entry into Medicare. Data Sources The analysis file is drawn from the Health and Retirement Study, a national survey of relatively older adults in the labor force. The dependent variable, an index of 5 health outcome items, was obtained from the 1996 survey. Independent variables were obtained from the 1992 survey. State-level instrumental variables were obtained from the Area Resources File and the TAXSIM file. The final sample consists of 9,034 individuals of which 1,540 were uninsured. Study Design Estimation addresses endogeneity of the insurance participation decision in health score regressions. In addition to ordinary least squares (OLS), two models are tested: an instrumental variables (IV) model, and a model with endogenous treatment effects due to Heckman (1978). Insurance participation and health behaviors enter with a lag to allow their effects to dissipate over time. Separate regressions were run for groupings of chronic conditions. Principal Findings The OLS model results in statistically significant albeit small effects of insurance on the computed health score, but the results may be downward biased. Adjusting for endogeneity using state-level instrumental variables yields up to a six-fold increase in the insurance effect. Results are consistent across IV and treatment effects models, and for major groupings of medical conditions. The insurance effect appears to be in the range of about 2–11 percent. There appear to be no significant differences in the insurance effect for subgroups with and without major chronic conditions. Conclusions Extending insurance coverage to working age adults may result in improved health. By conjecture, policies aimed at expanding coverage to this population may lead to improved health at retirement and entry to Medicare, potentially leading to savings. However, further research is needed to determine whether similar results are found when alternative measures of overall health or health scores are used. Future research should also explore the use of alternative instrumental variables. Preliminary results provide no justification for targeting certain subgroups with susceptibility to certain chronic conditions rather than broad policy interventions. PMID:16704511

Modeling the performance of direct-detection Doppler lidar systems including cloud and solar background variability.

PubMed

McGill, M J; Hart, W D; McKay, J A; Spinhirne, J D

1999-10-20

Previous modeling of the performance of spaceborne direct-detection Doppler lidar systems assumed extremely idealized atmospheric models. Here we develop a technique for modeling the performance of these systems in a more realistic atmosphere, based on actual airborne lidar observations. The resulting atmospheric model contains cloud and aerosol variability that is absent in other simulations of spaceborne Doppler lidar instruments. To produce a realistic simulation of daytime performance, we include solar radiance values that are based on actual measurements and are allowed to vary as the viewing scene changes. Simulations are performed for two types of direct-detection Doppler lidar system: the double-edge and the multichannel techniques. Both systems were optimized to measure winds from Rayleigh backscatter at 355 nm. Simulations show that the measurement uncertainty during daytime is degraded by only approximately 10-20% compared with nighttime performance, provided that a proper solar filter is included in the instrument design.

Exploration of an oculometer-based model of pilot workload

NASA Technical Reports Server (NTRS)

Krebs, M. J.; Wingert, J. W.; Cunningham, T.

1977-01-01

Potential relationships between eye behavior and pilot workload are discussed. A Honeywell Mark IIA oculometer was used to obtain the eye data in a fixed base transport aircraft simulation facility. The data were analyzed to determine those parameters of eye behavior which were related to changes in level of task difficulty of the simulated manual approach and landing on instruments. A number of trends and relationships between eye variables and pilot ratings were found. A preliminary equation was written based on the results of a stepwise linear regression. High variability in time spent on various instruments was related to differences in scanning strategy among pilots. A more detailed analysis of individual runs by individual pilots was performed to investigate the source of this variability more closely. Results indicated a high degree of intra-pilot variability in instrument scanning. No consistent workload related trends were found. Pupil diameter which had demonstrated a strong relationship to task difficulty was extensively re-exmained.

Self-Concept and Response Variability as Predictors of Leadership Effectiveness in Cooperative Extension.

ERIC Educational Resources Information Center

Dvorak, Charles F.

The research aimed at determining the extent to which two variables, self-concept and response variability, are related to one of the principal components of Fiedler's Contingency Model of leadership, the Esteem for the Least Preferred Coworker (LPC) instrument. Sixty extension workers in the Expanded Food and Nutrition Education Program in New…

College quality and hourly wages: evidence from the self-revelation model, sibling models and instrumental variables.

PubMed

Borgen, Nicolai T

2014-11-01

This paper addresses the recent discussion on confounding in the returns to college quality literature using the Norwegian case. The main advantage of studying Norway is the quality of the data. Norwegian administrative data provide information on college applications, family relations and a rich set of control variables for all Norwegian citizens applying to college between 1997 and 2004 (N = 141,319) and their succeeding wages between 2003 and 2010 (676,079 person-year observations). With these data, this paper uses a subset of the models that have rendered mixed findings in the literature in order to investigate to what extent confounding biases the returns to college quality. I compare estimates obtained using standard regression models to estimates obtained using the self-revelation model of Dale and Krueger (2002), a sibling fixed effects model and the instrumental variable model used by Long (2008). Using these methods, I consistently find increasing returns to college quality over the course of students' work careers, with positive returns only later in students' work careers. I conclude that the standard regression estimate provides a reasonable estimate of the returns to college quality. Copyright © 2014 Elsevier Inc. All rights reserved.

Robust best linear estimator for Cox regression with instrumental variables in whole cohort and surrogates with additive measurement error in calibration sample

PubMed Central

Wang, Ching-Yun; Song, Xiao

2017-01-01

SUMMARY Biomedical researchers are often interested in estimating the effect of an environmental exposure in relation to a chronic disease endpoint. However, the exposure variable of interest may be measured with errors. In a subset of the whole cohort, a surrogate variable is available for the true unobserved exposure variable. The surrogate variable satisfies an additive measurement error model, but it may not have repeated measurements. The subset in which the surrogate variables are available is called a calibration sample. In addition to the surrogate variables that are available among the subjects in the calibration sample, we consider the situation when there is an instrumental variable available for all study subjects. An instrumental variable is correlated with the unobserved true exposure variable, and hence can be useful in the estimation of the regression coefficients. In this paper, we propose a nonparametric method for Cox regression using the observed data from the whole cohort. The nonparametric estimator is the best linear combination of a nonparametric correction estimator from the calibration sample and the difference of the naive estimators from the calibration sample and the whole cohort. The asymptotic distribution is derived, and the finite sample performance of the proposed estimator is examined via intensive simulation studies. The methods are applied to the Nutritional Biomarkers Study of the Women’s Health Initiative. PMID:27546625

Inter-hospital transfer is associated with increased mortality and costs in severe sepsis and septic shock: An instrumental variables approach.

PubMed

Mohr, Nicholas M; Harland, Karisa K; Shane, Dan M; Ahmed, Azeemuddin; Fuller, Brian M; Torner, James C

2016-12-01

The objective of this study was to evaluate the impact of regionalization on sepsis survival, to describe the role of inter-hospital transfer in rural sepsis care, and to measure the cost of inter-hospital transfer in a predominantly rural state. Observational case-control study using statewide administrative claims data from 2005 to 2014 in a predominantly rural Midwestern state. Mortality and marginal costs were estimated with multivariable generalized estimating equations models and with instrumental variables models. A total of 18 246 patients were included, of which 59% were transferred between hospitals. Transferred patients had higher mortality and longer hospital length-of-stay than non-transferred patients. Using a multivariable generalized estimating equations (GEE) model to adjust for potentially confounding factors, inter-hospital transfer was associated with increased mortality (aOR 1.7, 95% CI 1.5-1.9). Using an instrumental variables model, transfer was associated with a 9.2% increased risk of death. Transfer was associated with additional costs of $6897 (95% CI $5769-8024). Even when limiting to only those patients who received care in the largest hospitals, transfer was still associated with $5167 (95% CI $3696-6638) in additional cost. The majority of rural sepsis patients are transferred, and these transferred patients have higher mortality and significantly increased cost of care. Copyright © 2016 Elsevier Inc. All rights reserved.

Inter-Hospital Transfer is Associated with Increased Mortality and Costs in Severe Sepsis and Septic Shock: An Instrumental Variables Approach

PubMed Central

Mohr, Nicholas M.; Harland, Karisa K.; Shane, Dan M.; Ahmed, Azeemuddin; Fuller, Brian M.; Torner, James C.

2016-01-01

Purpose The objective of this study was to evaluate the impact of regionalization on sepsis survival, to describe the role of inter-hospital transfer in rural sepsis care, and to measure the cost of inter-hospital transfer in a predominantly rural state. Materials and Methods Observational case-control study using statewide administrative claims data from 2005-2014 in a predominantly rural Midwestern state. Mortality and marginal costs were estimated with multivariable generalized estimating equations (GEE) models and with instrumental variables models. Results A total of 18,246 patients were included, of which 59% were transferred between hospitals. Transferred patients had higher mortality and longer hospital length-of-stay than non-transferred patients. Using a multivariable GEE model to adjust for potentially confounding factors, inter-hospital transfer was associated with increased mortality (aOR 1.7, 95%CI 1.5 – 1.9). Using an instrumental variables model, transfer was associated with a 9.2% increased risk of death. Transfer was associated with additional costs of $6,897 (95%CI $5,769-8,024). Even when limiting to only those patients who received care in the largest hospitals, transfer was still associated with $5,167 (95%CI $3,696-6,638) in additional cost. Conclusions The majority of rural sepsis patients are transferred, and these transferred patients have higher mortality and significantly increased cost of care. PMID:27546770

Filtering and Gridding Satellite Observations of Cloud Variables to Compare with Climate Model Output

NASA Astrophysics Data System (ADS)

Pitts, K.; Nasiri, S. L.; Smith, N.

2013-12-01

Global climate models have improved considerably over the years, yet clouds still represent a large factor of uncertainty for these models. Comparisons of model-simulated cloud variables with equivalent satellite cloud products are the best way to start diagnosing the differences between model output and observations. Gridded (level 3) cloud products from many different satellites and instruments are required for a full analysis, but these products are created by different science teams using different algorithms and filtering criteria to create similar, but not directly comparable, cloud products. This study makes use of a recently developed uniform space-time gridding algorithm to create a new set of gridded cloud products from each satellite instrument's level 2 data of interest which are each filtered using the same criteria, allowing for a more direct comparison between satellite products. The filtering is done via several variables such as cloud top pressure/height, thermodynamic phase, optical properties, satellite viewing angle, and sun zenith angle. The filtering criteria are determined based on the variable being analyzed and the science question at hand. Each comparison of different variables may require different filtering strategies as no single approach is appropriate for all problems. Beyond inter-satellite data comparison, these new sets of uniformly gridded satellite products can also be used for comparison with model-simulated cloud variables. Of particular interest to this study are the differences in the vertical distributions of ice and liquid water content between the satellite retrievals and model simulations, especially in the mid-troposphere where there are mixed-phase clouds to consider. This presentation will demonstrate the proof of concept through comparisons of cloud water path from Aqua MODIS retrievals and NASA GISS-E2-[R/H] model simulations archived in the CMIP5 data portal.

Two-Stage Bayesian Model Averaging in Endogenous Variable Models*

PubMed Central

Lenkoski, Alex; Eicher, Theo S.; Raftery, Adrian E.

2013-01-01

Economic modeling in the presence of endogeneity is subject to model uncertainty at both the instrument and covariate level. We propose a Two-Stage Bayesian Model Averaging (2SBMA) methodology that extends the Two-Stage Least Squares (2SLS) estimator. By constructing a Two-Stage Unit Information Prior in the endogenous variable model, we are able to efficiently combine established methods for addressing model uncertainty in regression models with the classic technique of 2SLS. To assess the validity of instruments in the 2SBMA context, we develop Bayesian tests of the identification restriction that are based on model averaged posterior predictive p-values. A simulation study showed that 2SBMA has the ability to recover structure in both the instrument and covariate set, and substantially improves the sharpness of resulting coefficient estimates in comparison to 2SLS using the full specification in an automatic fashion. Due to the increased parsimony of the 2SBMA estimate, the Bayesian Sargan test had a power of 50 percent in detecting a violation of the exogeneity assumption, while the method based on 2SLS using the full specification had negligible power. We apply our approach to the problem of development accounting, and find support not only for institutions, but also for geography and integration as development determinants, once both model uncertainty and endogeneity have been jointly addressed. PMID:24223471

The prediction of nonlinear dynamic loads on helicopters from flight variables using artificial neural networks

NASA Technical Reports Server (NTRS)

Cook, A. B.; Fuller, C. R.; O'Brien, W. F.; Cabell, R. H.

1992-01-01

A method of indirectly monitoring component loads through common flight variables is proposed which requires an accurate model of the underlying nonlinear relationships. An artificial neural network (ANN) model learns relationships through exposure to a database of flight variable records and corresponding load histories from an instrumented military helicopter undergoing standard maneuvers. The ANN model, utilizing eight standard flight variables as inputs, is trained to predict normalized time-varying mean and oscillatory loads on two critical components over a range of seven maneuvers. Both interpolative and extrapolative capabilities are demonstrated with agreement between predicted and measured loads on the order of 90 percent to 95 percent. This work justifies pursuing the ANN method of predicting loads from flight variables.

Establishing Factor Validity Using Variable Reduction in Confirmatory Factor Analysis.

ERIC Educational Resources Information Center

Hofmann, Rich

1995-01-01

Using a 21-statement attitude-type instrument, an iterative procedure for improving confirmatory model fit is demonstrated within the context of the EQS program of P. M. Bentler and maximum likelihood factor analysis. Each iteration systematically eliminates the poorest fitting statement as identified by a variable fit index. (SLD)

Estimators for longitudinal latent exposure models: examining measurement model assumptions.

PubMed

Sánchez, Brisa N; Kim, Sehee; Sammel, Mary D

2017-06-15

Latent variable (LV) models are increasingly being used in environmental epidemiology as a way to summarize multiple environmental exposures and thus minimize statistical concerns that arise in multiple regression. LV models may be especially useful when multivariate exposures are collected repeatedly over time. LV models can accommodate a variety of assumptions but, at the same time, present the user with many choices for model specification particularly in the case of exposure data collected repeatedly over time. For instance, the user could assume conditional independence of observed exposure biomarkers given the latent exposure and, in the case of longitudinal latent exposure variables, time invariance of the measurement model. Choosing which assumptions to relax is not always straightforward. We were motivated by a study of prenatal lead exposure and mental development, where assumptions of the measurement model for the time-changing longitudinal exposure have appreciable impact on (maximum-likelihood) inferences about the health effects of lead exposure. Although we were not particularly interested in characterizing the change of the LV itself, imposing a longitudinal LV structure on the repeated multivariate exposure measures could result in high efficiency gains for the exposure-disease association. We examine the biases of maximum likelihood estimators when assumptions about the measurement model for the longitudinal latent exposure variable are violated. We adapt existing instrumental variable estimators to the case of longitudinal exposures and propose them as an alternative to estimate the health effects of a time-changing latent predictor. We show that instrumental variable estimators remain unbiased for a wide range of data generating models and have advantages in terms of mean squared error. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Spatial Heterodyne Observations of Water (SHOW) vapour in the upper troposphere and lower stratosphere from a high altitude aircraft: Modelling and sensitivity analysis

NASA Astrophysics Data System (ADS)

Langille, J. A.; Letros, D.; Zawada, D.; Bourassa, A.; Degenstein, D.; Solheim, B.

2018-04-01

A spatial heterodyne spectrometer (SHS) has been developed to measure the vertical distribution of water vapour in the upper troposphere and the lower stratosphere with a high vertical resolution (∼500 m). The Spatial Heterodyne Observations of Water (SHOW) instrument combines an imaging system with a monolithic field-widened SHS to observe limb scattered sunlight in a vibrational band of water (1363 nm-1366 nm). The instrument has been optimized for observations from NASA's ER-2 aircraft as a proof-of-concept for a future low earth orbit satellite deployment. A robust model has been developed to simulate SHOW ER-2 limb measurements and retrievals. This paper presents the simulation of the SHOW ER-2 limb measurements along a hypothetical flight track and examines the sensitivity of the measurement and retrieval approach. Water vapour fields from an Environment and Climate Change Canada forecast model are used to represent realistic spatial variability along the flight path. High spectral resolution limb scattered radiances are simulated using the SASKTRAN radiative transfer model. It is shown that the SHOW instrument onboard the ER-2 is capable of resolving the water vapour variability in the UTLS from approximately 12 km - 18 km with ±1 ppm accuracy. Vertical resolutions between 500 m and 1 km are feasible. The along track sampling capability of the instrument is also discussed.

Don't Hold Back? the Effect of Grade Retention on Student Achievement

ERIC Educational Resources Information Center

Diris, Ron

2017-01-01

This study analyzes the effect of age-based retention on school achievement at different stages of education. I estimate an instrumental variable model, using the predicted probability of retention given month of birth as an instrument, while simultaneously accounting for the effect of month of birth on maturity at the time of testing. The…

On Studying Common Factor Dominance and Approximate Unidimensionality in Multicomponent Measuring Instruments with Discrete Items

ERIC Educational Resources Information Center

Raykov, Tenko; Marcoulides, George A.

2018-01-01

This article outlines a procedure for examining the degree to which a common factor may be dominating additional factors in a multicomponent measuring instrument consisting of binary items. The procedure rests on an application of the latent variable modeling methodology and accounts for the discrete nature of the manifest indicators. The method…

Toward a clearer portrayal of confounding bias in instrumental variable applications.

PubMed

Jackson, John W; Swanson, Sonja A

2015-07-01

Recommendations for reporting instrumental variable analyses often include presenting the balance of covariates across levels of the proposed instrument and levels of the treatment. However, such presentation can be misleading as relatively small imbalances among covariates across levels of the instrument can result in greater bias because of bias amplification. We introduce bias plots and bias component plots as alternative tools for understanding biases in instrumental variable analyses. Using previously published data on proposed preference-based, geography-based, and distance-based instruments, we demonstrate why presenting covariate balance alone can be problematic, and how bias component plots can provide more accurate context for bias from omitting a covariate from an instrumental variable versus non-instrumental variable analysis. These plots can also provide relevant comparisons of different proposed instruments considered in the same data. Adaptable code is provided for creating the plots.

Robust best linear estimator for Cox regression with instrumental variables in whole cohort and surrogates with additive measurement error in calibration sample.

PubMed

Wang, Ching-Yun; Song, Xiao

2016-11-01

Biomedical researchers are often interested in estimating the effect of an environmental exposure in relation to a chronic disease endpoint. However, the exposure variable of interest may be measured with errors. In a subset of the whole cohort, a surrogate variable is available for the true unobserved exposure variable. The surrogate variable satisfies an additive measurement error model, but it may not have repeated measurements. The subset in which the surrogate variables are available is called a calibration sample. In addition to the surrogate variables that are available among the subjects in the calibration sample, we consider the situation when there is an instrumental variable available for all study subjects. An instrumental variable is correlated with the unobserved true exposure variable, and hence can be useful in the estimation of the regression coefficients. In this paper, we propose a nonparametric method for Cox regression using the observed data from the whole cohort. The nonparametric estimator is the best linear combination of a nonparametric correction estimator from the calibration sample and the difference of the naive estimators from the calibration sample and the whole cohort. The asymptotic distribution is derived, and the finite sample performance of the proposed estimator is examined via intensive simulation studies. The methods are applied to the Nutritional Biomarkers Study of the Women's Health Initiative. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Falsification Testing of Instrumental Variables Methods for Comparative Effectiveness Research.

PubMed

Pizer, Steven D

2016-04-01

To demonstrate how falsification tests can be used to evaluate instrumental variables methods applicable to a wide variety of comparative effectiveness research questions. Brief conceptual review of instrumental variables and falsification testing principles and techniques accompanied by an empirical application. Sample STATA code related to the empirical application is provided in the Appendix. Comparative long-term risks of sulfonylureas and thiazolidinediones for management of type 2 diabetes. Outcomes include mortality and hospitalization for an ambulatory care-sensitive condition. Prescribing pattern variations are used as instrumental variables. Falsification testing is an easily computed and powerful way to evaluate the validity of the key assumption underlying instrumental variables analysis. If falsification tests are used, instrumental variables techniques can help answer a multitude of important clinical questions. © Health Research and Educational Trust.

Analysis of Observational Studies in the Presence of Treatment Selection Bias: Effects of Invasive Cardiac Management on AMI Survival Using Propensity Score and Instrumental Variable Methods

PubMed Central

Stukel, Thérèse A.; Fisher, Elliott S; Wennberg, David E.; Alter, David A.; Gottlieb, Daniel J.; Vermeulen, Marian J.

2007-01-01

Context Comparisons of outcomes between patients treated and untreated in observational studies may be biased due to differences in patient prognosis between groups, often because of unobserved treatment selection biases. Objective To compare 4 analytic methods for removing the effects of selection bias in observational studies: multivariable model risk adjustment, propensity score risk adjustment, propensity-based matching, and instrumental variable analysis. Design, Setting, and Patients A national cohort of 122 124 patients who were elderly (aged 65–84 years), receiving Medicare, and hospitalized with acute myocardial infarction (AMI) in 1994–1995, and who were eligible for cardiac catheterization. Baseline chart reviews were taken from the Cooperative Cardiovascular Project and linked to Medicare health administrative data to provide a rich set of prognostic variables. Patients were followed up for 7 years through December 31, 2001, to assess the association between long-term survival and cardiac catheterization within 30 days of hospital admission. Main Outcome Measure Risk-adjusted relative mortality rate using each of the analytic methods. Results Patients who received cardiac catheterization (n=73 238) were younger and had lower AMI severity than those who did not. After adjustment for prognostic factors by using standard statistical risk-adjustment methods, cardiac catheterization was associated with a 50% relative decrease in mortality (for multivariable model risk adjustment: adjusted relative risk [RR], 0.51; 95% confidence interval [CI], 0.50–0.52; for propensity score risk adjustment: adjusted RR, 0.54; 95% CI, 0.53–0.55; and for propensity-based matching: adjusted RR, 0.54; 95% CI, 0.52–0.56). Using regional catheterization rate as an instrument, instrumental variable analysis showed a 16% relative decrease in mortality (adjusted RR, 0.84; 95% CI, 0.79–0.90). The survival benefits of routine invasive care from randomized clinical trials are between 8% and 21 %. Conclusions Estimates of the observational association of cardiac catheterization with long-term AMI mortality are highly sensitive to analytic method. All standard risk-adjustment methods have the same limitations regarding removal of unmeasured treatment selection biases. Compared with standard modeling, instrumental variable analysis may produce less biased estimates of treatment effects, but is more suited to answering policy questions than specific clinical questions. PMID:17227979

Tutorial in Biostatistics: Instrumental Variable Methods for Causal Inference*

PubMed Central

Baiocchi, Michael; Cheng, Jing; Small, Dylan S.

2014-01-01

A goal of many health studies is to determine the causal effect of a treatment or intervention on health outcomes. Often, it is not ethically or practically possible to conduct a perfectly randomized experiment and instead an observational study must be used. A major challenge to the validity of observational studies is the possibility of unmeasured confounding (i.e., unmeasured ways in which the treatment and control groups differ before treatment administration which also affect the outcome). Instrumental variables analysis is a method for controlling for unmeasured confounding. This type of analysis requires the measurement of a valid instrumental variable, which is a variable that (i) is independent of the unmeasured confounding; (ii) affects the treatment; and (iii) affects the outcome only indirectly through its effect on the treatment. This tutorial discusses the types of causal effects that can be estimated by instrumental variables analysis; the assumptions needed for instrumental variables analysis to provide valid estimates of causal effects and sensitivity analysis for those assumptions; methods of estimation of causal effects using instrumental variables; and sources of instrumental variables in health studies. PMID:24599889

Evaluation of solar irradiance models for climate studies

NASA Astrophysics Data System (ADS)

Ball, William; Yeo, Kok-Leng; Krivova, Natalie; Solanki, Sami; Unruh, Yvonne; Morrill, Jeff

2015-04-01

Instruments on satellites have been observing both Total Solar Irradiance (TSI) and Spectral Solar Irradiance (SSI), mainly in the ultraviolet (UV), since 1978. Models were developed to reproduce the observed variability and to compute the variability at wavelengths that were not observed or had an uncertainty too high to determine an accurate rotational or solar cycle variability. However, various models and measurements show different solar cycle SSI variability that lead to different modelled responses of ozone and temperature in the stratosphere, mainly due to the different UV variability in each model, and the global energy balance. The NRLSSI and SATIRE-S models are the most comprehensive reconstructions of solar irradiance variability for the period from 1978 to the present day. But while NRLSSI and SATIRE-S show similar solar cycle variability below 250 nm, between 250 and 400 nm SATIRE-S typically displays 50% larger variability, which is however, still significantly less then suggested by recent SORCE data. Due to large uncertainties and inconsistencies in some observational datasets, it is difficult to determine in a simple way which model is likely to be closer to the true solar variability. We review solar irradiance variability measurements and modelling and employ new analysis that sheds light on the causes of the discrepancies between the two models and with the observations.

Optical EVPA rotations in blazars: testing a stochastic variability model with RoboPol data

NASA Astrophysics Data System (ADS)

Kiehlmann, S.; Blinov, D.; Pearson, T. J.; Liodakis, I.

2017-12-01

We identify rotations of the polarization angle in a sample of blazars observed for three seasons with the RoboPol instrument. A simplistic stochastic variability model is tested against this sample of rotation events. The model is capable of producing samples of rotations with parameters similar to the observed ones, but fails to reproduce the polarization fraction at the same time. Even though we can neither accept nor conclusively reject the model, we point out various aspects of the observations that are fully consistent with a random walk process.

[Instruments for quantitative methods of nursing research].

PubMed

Vellone, E

2000-01-01

Instruments for quantitative nursing research are a mean to objectify and measure a variable or a phenomenon in the scientific research. There are direct instruments to measure concrete variables and indirect instruments to measure abstract concepts (Burns, Grove, 1997). Indirect instruments measure the attributes by which a concept is made of. Furthermore, there are instruments for physiologic variables (e.g. for the weight), observational instruments (Check-lists e Rating Scales), interviews, questionnaires, diaries and the scales (Check-lists, Rating Scales, Likert Scales, Semantic Differential Scales e Visual Anologue Scales). The choice to select an instrument or another one depends on the research question and design. Instruments research are very useful in research both to describe the variables and to see statistical significant relationships. Very carefully should be their use in the clinical practice for diagnostic assessment.

Body mass index and employment status: A new look.

PubMed

Kinge, Jonas Minet

2016-09-01

Earlier literature has usually modelled the impact of obesity on employment status as a binary choice (employed, yes/no). I provide new evidence on the impact of obesity on employment status by treating the dependent variable as a as a multinomial choice variable. Using data from a representative English survey, with measured height and weight on parents and children, I define employment status as one of four: working; looking for paid work; permanently not working due to disability; and, looking after home or family. I use a multinomial logit model controlling for a set of covariates. I also run instrumental variable models, instrumenting for Body Mass Index (BMI) based on genetic variation in weight. I find that BMI and obesity significantly increase the probability of "not working due to disability". The results for the other employment outcomes are less clear. My findings also indicate that BMI affects employment through its effect on health. Factors other than health may be less important in explaining the impact of BMI/obesity on employment. Copyright © 2016 Elsevier B.V. All rights reserved.

Wind tunnel investigation of nacelle-airframe interference at Mach numbers of 0.9 to 1.4 - pressure data, volume 1

NASA Technical Reports Server (NTRS)

Bencze, D. P.

1976-01-01

Detailed interference force and pressure data were obtained on a representative wing-body nacelle combination at Mach numbers of 0.9 to 1.4. The model consisted of a delta wing-body aerodynamic force model with four independently supported nacelles located beneath the wing-body combination. The model was mounted on a six component force balance, and the left hand wing was pressure instrumented. Each of the two right hand nacelles was mounted on a six component force balance housed in the thickness of the nacelle, while each of the left hand nacelles was pressure instrumented. The primary variables examined included Mach number, angle of attack, nacelle position, and nacelle mass flow ratio. Nacelle axial location, relative to both the wing-body combination and to each other, was the most important variable in determining the net interference among the components.

Manufacturing challenge: An employee perception of the impact of BEM variables on motivation

NASA Astrophysics Data System (ADS)

Nyaude, Alaster

The study examines the impact of Thomas F. Gilbert's Behavior Engineering Model (BEM) variables on employee perception of motivation at an aerospace equipment manufacturing plant in Georgia. The research process involved literature review, and determination of an appropriate survey instrument for the study. The Hersey-Chevalier modified PROBE instrument (Appendix C) was used with Dr Roger Chevalier's validation. The participants' responses were further examined to determine the influence of demographic control variables of age, gender, length of service with the company and education on employee perception of motivation. The results indicated that the top three highly motivating variables were knowledge and skills, capacity and resources. Knowledge and skills was perceived to be highly motivating, capacity as second highly motivating and resources as the third highly motivating variable. Interestingly, the fourth highly motivating variable was information, the fifth was motives and the sixth was incentives. The results also showed that demographic control variables had no influence on employee perception of motivation. Further research may be required to understand to what extend these BEM variables impact employee perceptions of motivation.

Calibration of the COBE FIRAS instrument

NASA Technical Reports Server (NTRS)

Fixsen, D. J.; Cheng, E. S.; Cottingham, D. A.; Eplee, R. E., Jr.; Hewagama, T.; Isaacman, R. B.; Jensen, K. A.; Mather, J. C.; Massa, D. L.; Meyer, S. S.

1994-01-01

The Far-Infrared Absolute Spectrophotometer (FIRAS) instrument on the Cosmic Background Explorer (COBE) satellite was designed to accurately measure the spectrum of the cosmic microwave background radiation (CMBR) in the frequency range 1-95/cm with an angular resolution of 7 deg. We describe the calibration of this instrument, including the method of obtaining calibration data, reduction of data, the instrument model, fitting the model to the calibration data, and application of the resulting model solution to sky observations. The instrument model fits well for calibration data that resemble sky condition. The method of propagating detector noise through the calibration process to yield a covariance matrix of the calibrated sky data is described. The final uncertainties are variable both in frequency and position, but for a typical calibrated sky 2.6 deg square pixel and 0.7/cm spectral element the random detector noise limit is of order of a few times 10(exp -7) ergs/sq cm/s/sr cm for 2-20/cm, and the difference between the sky and the best-fit cosmic blackbody can be measured with a gain uncertainty of less than 3%.

Clouds and the Earth's Radiant Energy System (CERES) Data Products for Climate Research

NASA Technical Reports Server (NTRS)

Kato, Seiji; Loeb, Norman G.; Rutan, David A.; Rose, Fred G.

2015-01-01

NASA's Clouds and the Earth's Radiant Energy System (CERES) project integrates CERES, Moderate Resolution Imaging Spectroradiometer (MODIS), and geostationary satellite observations to provide top-of-atmosphere (TOA) irradiances derived from broadband radiance observations by CERES instruments. It also uses snow cover and sea ice extent retrieved from microwave instruments as well as thermodynamic variables from reanalysis. In addition, these variables are used for surface and atmospheric irradiance computations. The CERES project provides TOA, surface, and atmospheric irradiances in various spatial and temporal resolutions. These data sets are for climate research and evaluation of climate models. Long-term observations are required to understand how the Earth system responds to radiative forcing. A simple model is used to estimate the time to detect trends in TOA reflected shortwave and emitted longwave irradiances.

Investigation on Motorcyclist Riding Behaviour at Curve Entry Using Instrumented Motorcycle

PubMed Central

Yuen, Choon Wah; Karim, Mohamed Rehan; Saifizul, Ahmad

2014-01-01

This paper details the study on the changes in riding behaviour, such as changes in speed as well as the brake force and throttle force applied, when motorcyclists ride over a curve section road using an instrumented motorcycle. In this study, an instrumented motorcycle equipped with various types of sensors, on-board cameras, and data loggers, was developed in order to collect the riding data on the study site. Results from the statistical analysis showed that riding characteristics, such as changes in speed, brake force, and throttle force applied, are influenced by the distance from the curve entry, riding experience, and travel mileage of the riders. A structural equation modeling was used to study the impact of these variables on the change of riding behaviour in curve entry section. Four regression equations are formed to study the relationship between four dependent variables, which are speed, throttle force, front brake force, and rear brake force applied with the independent variables. PMID:24523660

Using Instrumental and Proxy Data to Determine the Causes of Fast and Slow Warming rates

NASA Astrophysics Data System (ADS)

Hegerl, G. C.; Schurer, A. P.; Obrochta, S.

2015-12-01

The recent warming 'hiatus' is subject to intense interest, with proposed causes including natural forcing and internal variability. We derive samples of all natural and interval variability from observations and a recent proxy reconstruction to investigate the likelihood that these two sources of variability could produce a hiatus or rapid warming in surface temperature. The likelihood is found to be consistent with that calculated previously for models and exhibits a similar spatial pattern, with an Interdecadal Pacific Oscillation-like structure, although with more signal in the Atlantic than in model patterns. The number and length of events increases if natural forcing is also considered, with volcanic forcing acting as a pacemaker for both fast and slow warming rates in model simulations of the last millennium, and, to a smaller extent, from observations. Big eruptions, such as Mount Tambora in 1815, or clusters of eruptions, may result in a hiatus of over 20 years. A striking finding is the smaller influence of volcanism on surface temperature warming rates in instrumental and proxy data than in climate models. This talk will discuss the possible reasons of this discrepancy.

Bias correction by use of errors-in-variables regression models in studies with K-X-ray fluorescence bone lead measurements.

PubMed

Lamadrid-Figueroa, Héctor; Téllez-Rojo, Martha M; Angeles, Gustavo; Hernández-Ávila, Mauricio; Hu, Howard

2011-01-01

In-vivo measurement of bone lead by means of K-X-ray fluorescence (KXRF) is the preferred biological marker of chronic exposure to lead. Unfortunately, considerable measurement error associated with KXRF estimations can introduce bias in estimates of the effect of bone lead when this variable is included as the exposure in a regression model. Estimates of uncertainty reported by the KXRF instrument reflect the variance of the measurement error and, although they can be used to correct the measurement error bias, they are seldom used in epidemiological statistical analyzes. Errors-in-variables regression (EIV) allows for correction of bias caused by measurement error in predictor variables, based on the knowledge of the reliability of such variables. The authors propose a way to obtain reliability coefficients for bone lead measurements from uncertainty data reported by the KXRF instrument and compare, by the use of Monte Carlo simulations, results obtained using EIV regression models vs. those obtained by the standard procedures. Results of the simulations show that Ordinary Least Square (OLS) regression models provide severely biased estimates of effect, and that EIV provides nearly unbiased estimates. Although EIV effect estimates are more imprecise, their mean squared error is much smaller than that of OLS estimates. In conclusion, EIV is a better alternative than OLS to estimate the effect of bone lead when measured by KXRF. Copyright © 2010 Elsevier Inc. All rights reserved.

The ARM Cloud Radar Simulator for Global Climate Models: Bridging Field Data and Climate Models

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

Zhang, Yuying; Xie, Shaocheng; Klein, Stephen A.

Clouds play an important role in Earth’s radiation budget and hydrological cycle. However, current global climate models (GCMs) have had difficulties in accurately simulating clouds and precipitation. To improve the representation of clouds in climate models, it is crucial to identify where simulated clouds differ from real world observations of them. This can be difficult, since significant differences exist between how a climate model represents clouds and what instruments observe, both in terms of spatial scale and the properties of the hydrometeors which are either modeled or observed. To address these issues and minimize impacts of instrument limitations, the conceptmore » of instrument “simulators”, which convert model variables into pseudo-instrument observations, has evolved with the goal to improve and to facilitate the comparison of modeled clouds with observations. Many simulators have (and continue to be developed) for a variety of instruments and purposes. A community satellite simulator package, the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP; Bodas-Salcedo et al. 2011), contains several independent satellite simulators and is being widely used in the global climate modeling community to exploit satellite observations for model cloud evaluation (e.g., Klein et al. 2013; Zhang et al. 2010). This article introduces a ground-based cloud radar simulator developed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program for comparing climate model clouds with ARM observations from its vertically pointing 35-GHz radars. As compared to CloudSat radar observations, ARM radar measurements occur with higher temporal resolution and finer vertical resolution. This enables users to investigate more fully the detailed vertical structures within clouds, resolve thin clouds, and quantify the diurnal variability of clouds. Particularly, ARM radars are sensitive to low-level clouds, which are difficult for the CloudSat radar to detect due to surface contamination (Mace et al. 2007; Marchand et al. 2008). Therefore, the ARM ground-based cloud observations can provide important observations of clouds that complement measurements from space.« less

Detecting potential anomalies in projections of rainfall trends and patterns using human observations

NASA Astrophysics Data System (ADS)

Kohfeld, K. E.; Savo, V.; Sillmann, J.; Morton, C.; Lepofsky, D.

2016-12-01

Shifting precipitation patterns are a well-documented consequence of climate change, but their spatial variability is particularly difficult to assess. While the accuracy of global models has increased, specific regional changes in precipitation regimes are not well captured by these models. Typically, researchers who wish to detect trends and patterns in climatic variables, such as precipitation, use instrumental observations. In our study, we combined observations of rainfall by subsistence-oriented communities with several metrics of rainfall estimated from global instrumental records for comparable time periods (1955 - 2005). This comparison was aimed at identifying: 1) which rainfall metrics best match human observations of changes in precipitation; 2) areas where local communities observe changes not detected by global models. The collated observations ( 3800) made by subsistence-oriented communities covered 129 countries ( 1830 localities). For comparable time periods, we saw a substantial correspondence between instrumental records and human observations (66-77%) at the same locations, regardless of whether we considered trends in general rainfall, drought, or extreme rainfall. We observed a clustering of mismatches in two specific regions, possibly indicating some climatic phenomena not completely captured by the currently available global models. Many human observations also indicated an increased unpredictability in the start, end, duration, and continuity of the rainy seasons, all of which may hamper the performance of subsistence activities. We suggest that future instrumental metrics should capture this unpredictability of rainfall. This information would be important for thousands of subsistence-oriented communities in planning, coping, and adapting to climate change.

Eliminating Survivor Bias in Two-stage Instrumental Variable Estimators.

PubMed

Vansteelandt, Stijn; Walter, Stefan; Tchetgen Tchetgen, Eric

2018-07-01

Mendelian randomization studies commonly focus on elderly populations. This makes the instrumental variables analysis of such studies sensitive to survivor bias, a type of selection bias. A particular concern is that the instrumental variable conditions, even when valid for the source population, may be violated for the selective population of individuals who survive the onset of the study. This is potentially very damaging because Mendelian randomization studies are known to be sensitive to bias due to even minor violations of the instrumental variable conditions. Interestingly, the instrumental variable conditions continue to hold within certain risk sets of individuals who are still alive at a given age when the instrument and unmeasured confounders exert additive effects on the exposure, and moreover, the exposure and unmeasured confounders exert additive effects on the hazard of death. In this article, we will exploit this property to derive a two-stage instrumental variable estimator for the effect of exposure on mortality, which is insulated against the above described selection bias under these additivity assumptions.

Development process and initial validation of the Ethical Conflict in Nursing Questionnaire-Critical Care Version.

PubMed

Falcó-Pegueroles, Anna; Lluch-Canut, Teresa; Guàrdia-Olmos, Joan

2013-06-01

Ethical conflicts are arising as a result of the growing complexity of clinical care, coupled with technological advances. Most studies that have developed instruments for measuring ethical conflict base their measures on the variables 'frequency' and 'degree of conflict'. In our view, however, these variables are insufficient for explaining the root of ethical conflicts. Consequently, the present study formulates a conceptual model that also includes the variable 'exposure to conflict', as well as considering six 'types of ethical conflict'. An instrument was then designed to measure the ethical conflicts experienced by nurses who work with critical care patients. The paper describes the development process and validation of this instrument, the Ethical Conflict in Nursing Questionnaire Critical Care Version (ECNQ-CCV). The sample comprised 205 nursing professionals from the critical care units of two hospitals in Barcelona (Spain). The ECNQ-CCV presents 19 nursing scenarios with the potential to produce ethical conflict in the critical care setting. Exposure to ethical conflict was assessed by means of the Index of Exposure to Ethical Conflict (IEEC), a specific index developed to provide a reference value for each respondent by combining the intensity and frequency of occurrence of each scenario featured in the ECNQ-CCV. Following content validity, construct validity was assessed by means of Exploratory Factor Analysis (EFA), while Cronbach's alpha was used to evaluate the instrument's reliability. All analyses were performed using the statistical software PASW v19. Cronbach's alpha for the ECNQ-CCV as a whole was 0.882, which is higher than the values reported for certain other related instruments. The EFA suggested a unidimensional structure, with one component accounting for 33.41% of the explained variance. The ECNQ-CCV is shown to a valid and reliable instrument for use in critical care units. Its structure is such that the four variables on which our model of ethical conflict is based may be studied separately or in combination. The critical care nurses in this sample present moderate levels of exposure to ethical conflict. This study represents the first evaluation of the ECNQ-CCV.

The ARM Cloud Radar Simulator for Global Climate Models: A New Tool for Bridging Field Data and Climate Models

DOE PAGES

Zhang, Yuying; Xie, Shaocheng; Klein, Stephen A.; ...

2017-08-11

Clouds play an important role in Earth’s radiation budget and hydrological cycle. However, current global climate models (GCMs) have difficulties in accurately simulating clouds and precipitation. To improve the representation of clouds in climate models, it is crucial to identify where simulated clouds differ from real world observations of them. This can be difficult, since significant differences exist between how a climate model represents clouds and what instruments observe, both in terms of spatial scale and the properties of the hydrometeors which are either modeled or observed. To address these issues and minimize impacts of instrument limitations, the concept ofmore » instrument “simulators”, which convert model variables into pseudo-instrument observations, has evolved with the goal to facilitate and to improve the comparison of modeled clouds with observations. Many simulators have been (and continue to be) developed for a variety of instruments and purposes. Finally, a community satellite simulator package, the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP; Bodas-Salcedo et al. 2011), contains several independent satellite simulators and is being widely used in the global climate modeling community to exploit satellite observations for model cloud evaluation (e.g., Kay et al. 2012; Klein et al. 2013; Suzuki et al. 2013; Zhang et al. 2010).« less

The ARM Cloud Radar Simulator for Global Climate Models: A New Tool for Bridging Field Data and Climate Models

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

Zhang, Yuying; Xie, Shaocheng; Klein, Stephen A.

Clouds play an important role in Earth’s radiation budget and hydrological cycle. However, current global climate models (GCMs) have difficulties in accurately simulating clouds and precipitation. To improve the representation of clouds in climate models, it is crucial to identify where simulated clouds differ from real world observations of them. This can be difficult, since significant differences exist between how a climate model represents clouds and what instruments observe, both in terms of spatial scale and the properties of the hydrometeors which are either modeled or observed. To address these issues and minimize impacts of instrument limitations, the concept ofmore » instrument “simulators”, which convert model variables into pseudo-instrument observations, has evolved with the goal to facilitate and to improve the comparison of modeled clouds with observations. Many simulators have been (and continue to be) developed for a variety of instruments and purposes. Finally, a community satellite simulator package, the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP; Bodas-Salcedo et al. 2011), contains several independent satellite simulators and is being widely used in the global climate modeling community to exploit satellite observations for model cloud evaluation (e.g., Kay et al. 2012; Klein et al. 2013; Suzuki et al. 2013; Zhang et al. 2010).« less

Optimal averaging of soil moisture predictions from ensemble land surface model simulations

USDA-ARS?s Scientific Manuscript database

The correct interpretation of ensemble information obtained from the parallel implementation of multiple land surface models (LSMs) requires information concerning the LSM ensemble’s mutual error covariance. Here we propose a new technique for obtaining such information using an instrumental variabl...

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

PubMed

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

2010-04-01

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

Estimation of Chinese surface NO2 concentrations combining satellite data and Land Use Regression

NASA Astrophysics Data System (ADS)

Anand, J.; Monks, P.

2016-12-01

Monitoring surface-level air quality is often limited by in-situ instrument placement and issues arising from harmonisation over long timescales. Satellite instruments can offer a synoptic view of regional pollution sources, but in many cases only a total or tropospheric column can be measured. In this work a new technique of estimating surface NO2 combining both satellite and in-situ data is presented, in which a Land Use Regression (LUR) model is used to create high resolution pollution maps based on known predictor variables such as population density, road networks, and land cover. By employing a mixed effects approach, it is possible to take advantage of the spatiotemporal variability in the satellite-derived column densities to account for daily and regional variations in surface NO2 caused by factors such as temperature, elevation, and wind advection. In this work, surface NO2 maps are modelled over the North China Plain and Pearl River Delta during high-pollution episodes by combining in-situ measurements and tropospheric columns from the Ozone Monitoring Instrument (OMI). The modelled concentrations show good agreement with in-situ data and surface NO2 concentrations derived from the MACC-II global reanalysis.

The Dependence of Cloud Property Trend Detection on Absolute Calibration Accuracy of Passive Satellite Sensors

NASA Astrophysics Data System (ADS)

Shea, Y.; Wielicki, B. A.; Sun-Mack, S.; Minnis, P.; Zelinka, M. D.

2016-12-01

Detecting trends in climate variables on global, decadal scales requires highly accurate, stable measurements and retrieval algorithms. Trend uncertainty depends on its magnitude, natural variability, and instrument and retrieval algorithm accuracy and stability. We applied a climate accuracy framework to quantify the impact of absolute calibration on cloud property trend uncertainty. The cloud properties studied were cloud fraction, effective temperature, optical thickness, and effective radius retrieved using the Clouds and the Earth's Radiant Energy System (CERES) Cloud Property Retrieval System, which uses Moderate-resolution Imaging Spectroradiometer measurements (MODIS). Modeling experiments from the fifth phase of the Climate Model Intercomparison Project (CMIP5) agree that net cloud feedback is likely positive but disagree regarding its magnitude, mainly due to uncertainty in shortwave cloud feedback. With the climate accuracy framework we determined the time to detect trends for instruments with various calibration accuracies. We estimated a relationship between cloud property trend uncertainty, cloud feedback, and Equilibrium Climate Sensitivity and also between effective radius trend uncertainty and aerosol indirect effect trends. The direct relationship between instrument accuracy requirements and climate model output provides the level of instrument absolute accuracy needed to reduce climate model projection uncertainty. Different cloud types have varied radiative impacts on the climate system depending on several attributes, such as their thermodynamic phase, altitude, and optical thickness. Therefore, we also conducted these studies by cloud types for a clearer understanding of instrument accuracy requirements needed to detect changes in their cloud properties. Combining this information with the radiative impact of different cloud types helps to prioritize among requirements for future satellite sensors and understanding the climate detection capabilities of existing sensors.

CEOS SEO and GISS Meeting

NASA Technical Reports Server (NTRS)

Killough, Brian; Stover, Shelley

2008-01-01

The Committee on Earth Observation Satellites (CEOS) provides a brief to the Goddard Institute for Space Studies (GISS) regarding the CEOS Systems Engineering Office (SEO) and current work on climate requirements and analysis. A "system framework" is provided for the Global Earth Observation System of Systems (GEOSS). SEO climate-related tasks are outlined including the assessment of essential climate variable (ECV) parameters, use of the "systems framework" to determine relevant informational products and science models and the performance of assessments and gap analyses of measurements and missions for each ECV. Climate requirements, including instruments and missions, measurements, knowledge and models, and decision makers, are also outlined. These requirements would establish traceability from instruments to products and services allowing for benefit evaluation of instruments and measurements. Additionally, traceable climate requirements would provide a better understanding of global climate models.

Satellite-based Analysis of CO Variability over the Amazon Basin

NASA Astrophysics Data System (ADS)

Deeter, M. N.; Emmons, L. K.; Martinez-Alonso, S.; Tilmes, S.; Wiedinmyer, C.

2017-12-01

Pyrogenic emissions from the Amazon Basin exert significant influence on both climate and air quality but are highly variable from year to year. The ability of models to simulate the impact of biomass burning emissions on downstream atmospheric concentrations depends on (1) the quality of surface flux estimates (i.e., emissions inventories), (2) model dynamics (e.g., horizontal winds, large-scale convection and mixing) and (3) the representation of atmospheric chemical processes. With an atmospheric lifetime of a few months, carbon monoxide (CO) is a commonly used diagnostic for biomass burning. CO products are available from several satellite instruments and allow analyses of CO variability over extended regions such as the Amazon Basin with useful spatial and temporal sampling characteristics. The MOPITT ('Measurements of Pollution in the Troposphere') instrument was launched on the NASA Terra platform near the end of 1999 and is still operational. MOPITT is uniquely capable of measuring tropospheric CO concentrations using both thermal-infrared and near-infrared observations, resulting in the ability to independently retrieve lower- and upper-troposphere CO concentrations. We exploit the 18-year MOPITT record and related datasets to analyze the variability of CO over the Amazon Basin and evaluate simulations performed with the CAM-chem chemical transport model. We demonstrate that observed differences between MOPITT observations and model simulations provide important clues regarding emissions inventories, convective mixing and long-range transport.

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

Garimella, Sarvesh; Rothenberg, Daniel A.; Wolf, Martin J.

This study investigates the measurement of ice nucleating particle (INP) concentrations and sizing of crystals using continuous flow diffusion chambers (CFDCs). CFDCs have been deployed for decades to measure the formation of INPs under controlled humidity and temperature conditions in laboratory studies and by ambient aerosol populations. These measurements have, in turn, been used to construct parameterizations for use in models by relating the formation of ice crystals to state variables such as temperature and humidity as well as aerosol particle properties such as composition and number. We show here that assumptions of ideal instrument behavior are not supported by measurements mademore » with a commercially available CFDC, the SPectrometer for Ice Nucleation (SPIN), and the instrument on which it is based, the Zurich Ice Nucleation Chamber (ZINC). Non-ideal instrument behavior, which is likely inherent to varying degrees in all CFDCs, is caused by exposure of particles to different humidities and/or temperatures than predicated from instrument theory of operation. This can result in a systematic, and variable, underestimation of reported INP concentrations. Here we find here variable correction factors from 1.5 to 9.5, consistent with previous literature values. We use a machine learning approach to show that non-ideality is most likely due to small-scale flow features where the aerosols are combined with sheath flows. Machine learning is also used to minimize the uncertainty in measured INP concentrations. Finally, we suggest that detailed measurement, on an instrument-by-instrument basis, be performed to characterize this uncertainty.« less

Uncertainty in counting ice nucleating particles with continuous flow diffusion chambers

NASA Astrophysics Data System (ADS)

Garimella, Sarvesh; Rothenberg, Daniel A.; Wolf, Martin J.; David, Robert O.; Kanji, Zamin A.; Wang, Chien; Rösch, Michael; Cziczo, Daniel J.

2017-09-01

This study investigates the measurement of ice nucleating particle (INP) concentrations and sizing of crystals using continuous flow diffusion chambers (CFDCs). CFDCs have been deployed for decades to measure the formation of INPs under controlled humidity and temperature conditions in laboratory studies and by ambient aerosol populations. These measurements have, in turn, been used to construct parameterizations for use in models by relating the formation of ice crystals to state variables such as temperature and humidity as well as aerosol particle properties such as composition and number. We show here that assumptions of ideal instrument behavior are not supported by measurements made with a commercially available CFDC, the SPectrometer for Ice Nucleation (SPIN), and the instrument on which it is based, the Zurich Ice Nucleation Chamber (ZINC). Non-ideal instrument behavior, which is likely inherent to varying degrees in all CFDCs, is caused by exposure of particles to different humidities and/or temperatures than predicated from instrument theory of operation. This can result in a systematic, and variable, underestimation of reported INP concentrations. We find here variable correction factors from 1.5 to 9.5, consistent with previous literature values. We use a machine learning approach to show that non-ideality is most likely due to small-scale flow features where the aerosols are combined with sheath flows. Machine learning is also used to minimize the uncertainty in measured INP concentrations. We suggest that detailed measurement, on an instrument-by-instrument basis, be performed to characterize this uncertainty.

Statistical framework for evaluation of climate model simulations by use of climate proxy data from the last millennium - Part 1: Theory

NASA Astrophysics Data System (ADS)

Sundberg, R.; Moberg, A.; Hind, A.

2012-08-01

A statistical framework for comparing the output of ensemble simulations from global climate models with networks of climate proxy and instrumental records has been developed, focusing on near-surface temperatures for the last millennium. This framework includes the formulation of a joint statistical model for proxy data, instrumental data and simulation data, which is used to optimize a quadratic distance measure for ranking climate model simulations. An essential underlying assumption is that the simulations and the proxy/instrumental series have a shared component of variability that is due to temporal changes in external forcing, such as volcanic aerosol load, solar irradiance or greenhouse gas concentrations. Two statistical tests have been formulated. Firstly, a preliminary test establishes whether a significant temporal correlation exists between instrumental/proxy and simulation data. Secondly, the distance measure is expressed in the form of a test statistic of whether a forced simulation is closer to the instrumental/proxy series than unforced simulations. The proposed framework allows any number of proxy locations to be used jointly, with different seasons, record lengths and statistical precision. The goal is to objectively rank several competing climate model simulations (e.g. with alternative model parameterizations or alternative forcing histories) by means of their goodness of fit to the unobservable true past climate variations, as estimated from noisy proxy data and instrumental observations.

Quality of life as a cancer nursing outcome variable.

PubMed

Padilla, G V; Grant, M M

1985-10-01

A reliable and valid multidimensional instrument for measuring quality of life in cancer patients has been developed. Furthermore, a model has been offered that describes how quality of life works as an outcome variable. Using this model, predictions were made of how nursing interventions may directly or indirectly impact on quality of life. Initial testing of the model using data from 135 colostomy patients showed how satisfaction with nursing care and personal control act as cognitive mediators of self-worth, which then impacts on dimensions of quality of life.

Conducting quality of life research in people with coronary artery disease in non-English-speaking countries: conceptual and operationalization issues.

PubMed

Saengsiri, Aem-orn; Hacker, Eileen Danaher

2015-01-01

Health-related quality of life is an important clinical outcome to measure in patients with cardiovascular disease. International nurse researchers with limited English skills and novice cardiovascular nurse researchers face numerous challenges when conducting quality of life research because of the conceptual ambiguity of the construct and subsequent operationalization issues as well as difficulty identifying conceptual models to guide their quality of life research. The overall purpose of this article was to provide guidance to cardiovascular nurse researchers (using Thailand as an example) who are interested in examining quality of life in their native country but lack access to quality of life conceptual models and instruments because of language barriers. This article will examine definitions of health-related quality of life, selection of a conceptual model to guide quality of life research, use of the conceptual model to guide selection and measurement of variables, and translation of instruments when reliable and valid instruments are not available in the native language. Ferrans' definition of quality of life and the Wilson and Cleary Revised Model of Patient Outcomes were selected to guide the research. Selection of variables/instruments flowed directly from the conceptualization of constructs identified in this model. Our study, "Examining HRQOL in Thai People With Coronary Artery Disease Following Percutaneous Coronary Intervention," serves as an exemplar to illustrate the conceptual and operational challenges associated with conducting quality of life research in Thailand. The ultimate goal of cardiovascular nursing is to help patients achieve their optimal quality of life. Thai clinicians implementing quality of life assessment in clinical practice face similar conceptual and operationalization issues, especially when using instruments that are not well established or easily interpreted. Although quality of life assessment in clinical practice improves communication between patients and healthcare providers, clear guidelines for making changes to treatment strategies based on changes in quality of life must be established.

Monolithic superelastic rods with variable flexural stiffness for spinal fusion: modeling of the processing-properties relationship.

PubMed

Facchinello, Yann; Brailovski, Vladimir; Petit, Yvan; Mac-Thiong, Jean-Marc

2014-11-01

The concept of a monolithic Ti-Ni spinal rod with variable flexural stiffness is proposed to reduce the risks associated with spinal fusion. The variable stiffness is conferred to the rod using the Joule-heating local annealing technique. The annealing temperature and the mechanical properties' distributions resulted from this thermal treatment are numerically modeled and experimentally measured. To illustrate the possible applications of such a modeling approach, two case studies are presented: (a) optimization of the Joule-heating strategy to reduce annealing time, and (b) modulation of the rod's overall flexural stiffness using partial annealing. A numerical model of a human spine coupled with the model of the variable flexural stiffness spinal rod developed in this work can ultimately be used to maximize the stabilization capability of spinal instrumentation, while simultaneously decreasing the risks associated with spinal fusion. Copyright © 2014 IPEM. Published by Elsevier Ltd. All rights reserved.

Instrumental variable specifications and assumptions for longitudinal analysis of mental health cost offsets.

PubMed

O'Malley, A James

2012-12-01

Instrumental variables (IVs) enable causal estimates in observational studies to be obtained in the presence of unmeasured confounders. In practice, a diverse range of models and IV specifications can be brought to bear on a problem, particularly with longitudinal data where treatment effects can be estimated for various functions of current and past treatment. However, in practice the empirical consequences of different assumptions are seldom examined, despite the fact that IV analyses make strong assumptions that cannot be conclusively tested by the data. In this paper, we consider several longitudinal models and specifications of IVs. Methods are applied to data from a 7-year study of mental health costs of atypical and conventional antipsychotics whose purpose was to evaluate whether the newer and more expensive atypical antipsychotic medications lead to a reduction in overall mental health costs.

Implementation of Instrumental Variable Bounds for Data Missing Not at Random.

PubMed

Marden, Jessica R; Wang, Linbo; Tchetgen, Eric J Tchetgen; Walter, Stefan; Glymour, M Maria; Wirth, Kathleen E

2018-05-01

Instrumental variables are routinely used to recover a consistent estimator of an exposure causal effect in the presence of unmeasured confounding. Instrumental variable approaches to account for nonignorable missing data also exist but are less familiar to epidemiologists. Like instrumental variables for exposure causal effects, instrumental variables for missing data rely on exclusion restriction and instrumental variable relevance assumptions. Yet these two conditions alone are insufficient for point identification. For estimation, researchers have invoked a third assumption, typically involving fairly restrictive parametric constraints. Inferences can be sensitive to these parametric assumptions, which are typically not empirically testable. The purpose of our article is to discuss another approach for leveraging a valid instrumental variable. Although the approach is insufficient for nonparametric identification, it can nonetheless provide informative inferences about the presence, direction, and magnitude of selection bias, without invoking a third untestable parametric assumption. An important contribution of this article is an Excel spreadsheet tool that can be used to obtain empirical evidence of selection bias and calculate bounds and corresponding Bayesian 95% credible intervals for a nonidentifiable population proportion. For illustrative purposes, we used the spreadsheet tool to analyze HIV prevalence data collected by the 2007 Zambia Demographic and Health Survey (DHS).

Solar array model corrections from Mars Pathfinder lander data

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

Ewell, R.C.; Burger, D.R.

1997-12-31

The MESUR solar array power model initially assumed values for input variables. After landing early surface variables such as array tilt and azimuth or early environmental variables such as array temperature can be corrected. Correction of later environmental variables such as tau versus time, spectral shift, dust deposition, and UV darkening is dependent upon time, on-board science instruments, and ability to separate effects of variables. Engineering estimates had to be made for additional shadow losses and Voc sensor temperature corrections. Some variations had not been expected such as tau versus time of day, and spectral shift versus time of day.more » Additions needed to the model are thermal mass of lander petal and correction between Voc sensor and temperature sensor. Conclusions are: the model works well; good battery predictions are difficult; inclusion of Isc and Voc sensors was valuable; and the IMP and MAE science experiments greatly assisted the data analysis and model correction.« less

Assessing the Impact of Drug Use on Hospital Costs

PubMed Central

Stuart, Bruce C; Doshi, Jalpa A; Terza, Joseph V

2009-01-01

Objective To assess whether outpatient prescription drug utilization produces offsets in the cost of hospitalization for Medicare beneficiaries. Data Sources/Study Setting The study analyzed a sample (N=3,101) of community-dwelling fee-for-service U.S. Medicare beneficiaries drawn from the 1999 and 2000 Medicare Current Beneficiary Surveys. Study Design Using a two-part model specification, we regressed any hospital admission (part 1: probit) and hospital spending by those with one or more admissions (part 2: nonlinear least squares regression) on drug use in a standard model with strong covariate controls and a residual inclusion instrumental variable (IV) model using an exogenous measure of drug coverage as the instrument. Principal Findings The covariate control model predicted that each additional prescription drug used (mean=30) raised hospital spending by $16 (p<.001). The residual inclusion IV model prediction was that each additional prescription fill reduced hospital spending by $104 (p<.001). Conclusions The findings indicate that drug use is associated with cost offsets in hospitalization among Medicare beneficiaries, once omitted variable bias is corrected using an IV technique appropriate for nonlinear applications. PMID:18783453

A Contigency Model for Predicting Institutionalization of Innovation Across Divergent Organizations.

ERIC Educational Resources Information Center

Howes, Nancy J.

This study was undertaken to compare the variables related to the successful institutionalization of changes across divergent organizations, and to design, through cross-validation, an interorganization model of change. Descriptive survey questionnaires and structured interviews were the instruments used. The respondent sample consisted of 1,500…

Determinants of Students' Outcome: A Full-Fledged Structural Equation Modelling Approach

ERIC Educational Resources Information Center

Musah, Mohammed Borhandden; Ali, Hairuddin Bin Mohd; Al-Hudawi, Shafeeq Hussain Vazhathodi; Tahir, Lokman Mohd; Daud, Khadijah Binti; Hamdan, Abdul Rahim

2015-01-01

The vibrant demand for academic excellence in the twenty-first century has brought diverse determinants of students' outcome into play. However, few studies have validated the instruments and examined the mediating effect between exogenous and endogenous variables of the student outcome model. This study, therefore, investigates the psychometric…

Past climate variability and change in the Arctic and at high latitudes

USGS Publications Warehouse

Alley, Richard B.; Brigham-Grette, Julie; Miller, Gifford H.; Polyak, Leonid; ,; ,; ,

2009-01-01

Paleoclimate records play a key role in our understanding of Earth's past and present climate system and in our confidence in predicting future climate changes. Paleoclimate data help to elucidate past and present active mechanisms of climate change by placing the short instrumental record into a longer term context and by permitting models to be tested beyond the limited time that instrumental measurements have been available.

High-Frequency X-ray Variability Detection in A Black Hole Transient with USA.

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

Shabad, Gayane

2000-10-16

Studies of high-frequency variability (above {approx}100 Hz) in X-ray binaries provide a unique opportunity to explore the fundamental physics of spacetime and matter, since the orbital timescale on the order of several milliseconds is a timescale of the motion of matter through the region located in close proximity to a compact stellar object. The detection of weak high-frequency signals in X-ray binaries depends on how well we understand the level of Poisson noise due to the photon counting statistics, i.e. how well we can understand and model the detector deadtime and other instrumental systematic effects. We describe the preflight timingmore » calibration work performed on the Unconventional Stellar Aspect (USA) X-ray detector to study deadtime and timing issues. We developed a Monte Carlo deadtime model and deadtime correction methods for the USA experiment. The instrumental noise power spectrum can be estimated within {approx}0.1% accuracy in the case when no energy-dependent instrumental effect is present. We also developed correction techniques to account for an energy-dependent instrumental effect. The developed methods were successfully tested on USA Cas A and Cygnus X-1 data. This work allowed us to make a detection of a weak signal in a black hole candidate (BHC) transient.« less

Generalized Path Analysis and Generalized Simultaneous Equations Model for Recursive Systems with Responses of Mixed Types

ERIC Educational Resources Information Center

Tsai, Tien-Lung; Shau, Wen-Yi; Hu, Fu-Chang

2006-01-01

This article generalizes linear path analysis (PA) and simultaneous equations models (SiEM) to deal with mixed responses of different types in a recursive or triangular system. An efficient instrumental variable (IV) method for estimating the structural coefficients of a 2-equation partially recursive generalized path analysis (GPA) model and…

Bias and Bias Correction in Multi-Site Instrumental Variables Analysis of Heterogeneous Mediator Effects

ERIC Educational Resources Information Center

Reardon, Sean F.; Unlu, Faith; Zhu, Pei; Bloom, Howard

2013-01-01

We explore the use of instrumental variables (IV) analysis with a multi-site randomized trial to estimate the effect of a mediating variable on an outcome in cases where it can be assumed that the observed mediator is the only mechanism linking treatment assignment to outcomes, as assumption known in the instrumental variables literature as the…

Treatment Effect Estimation Using Nonlinear Two-Stage Instrumental Variable Estimators: Another Cautionary Note.

PubMed

Chapman, Cole G; Brooks, John M

2016-12-01

To examine the settings of simulation evidence supporting use of nonlinear two-stage residual inclusion (2SRI) instrumental variable (IV) methods for estimating average treatment effects (ATE) using observational data and investigate potential bias of 2SRI across alternative scenarios of essential heterogeneity and uniqueness of marginal patients. Potential bias of linear and nonlinear IV methods for ATE and local average treatment effects (LATE) is assessed using simulation models with a binary outcome and binary endogenous treatment across settings varying by the relationship between treatment effectiveness and treatment choice. Results show that nonlinear 2SRI models produce estimates of ATE and LATE that are substantially biased when the relationships between treatment and outcome for marginal patients are unique from relationships for the full population. Bias of linear IV estimates for LATE was low across all scenarios. Researchers are increasingly opting for nonlinear 2SRI to estimate treatment effects in models with binary and otherwise inherently nonlinear dependent variables, believing that it produces generally unbiased and consistent estimates. This research shows that positive properties of nonlinear 2SRI rely on assumptions about the relationships between treatment effect heterogeneity and choice. © Health Research and Educational Trust.

The continuum of hydroclimate variability in western North America during the last millennium

USGS Publications Warehouse

Ault, Toby R.; Cole, Julia E.; Overpeck, Jonathan T.; Pederson, Gregory T.; St. George, Scott; Otto-Bliesner, Bette; Woodhouse, Connie A.; Deser, Clara

2013-01-01

The distribution of climatic variance across the frequency spectrum has substantial importance for anticipating how climate will evolve in the future. Here we estimate power spectra and power laws (ß) from instrumental, proxy, and climate model data to characterize the hydroclimate continuum in western North America (WNA). We test the significance of our estimates of spectral densities and ß against the null hypothesis that they reflect solely the effects of local (non-climate) sources of autocorrelation at the monthly timescale. Although tree-ring based hydroclimate reconstructions are generally consistent with this null hypothesis, values of ß calculated from long-moisture sensitive chronologies (as opposed to reconstructions), and other types of hydroclimate proxies, exceed null expectations. We therefore argue that there is more low-frequency variability in hydroclimate than monthly autocorrelation alone can generate. Coupled model results archived as part of the Climate Model Intercomparison Project 5 (CMIP5) are consistent with the null hypothesis and appear unable to generate variance in hydroclimate commensurate with paleoclimate records. Consequently, at decadal to multidecadal timescales there is more variability in instrumental and proxy data than in the models, suggesting that the risk of prolonged droughts under climate change may be underestimated by CMIP5 simulations of the future.

Social connections and happiness among the elder population of Taiwan.

PubMed

Hsu, H-C; Chang, W-C

2015-01-01

The purpose of this study was to examine the association between social connections and happiness among members of the elder population of Taiwan. Longitudinal panel data collected in three waves from 1999 to 2007 that are selected from national samples of Taiwanese older people were used for the analysis (n = 4731 persons). Happiness was defined as a dichotomous variable. Social connection variables included living arrangements, contacts with children/grandchildren/parents/relatives/friends, telephone contacts, providing instrumental and informational support, receiving instrumental and emotional support, and social participation. We controlled for the variables demographics, physical and mental health, economic satisfaction, and lifestyle. A generalized linear model (GLM) was applied in the analysis. Happiness remained stable over time. Receiving more emotional support and participating in social events were related to happiness at the beginning, while the effect of social participation was offset over time. Living arrangements, telephone contacts, providing social support, and receiving instrumental support were not significant. The quality of social relationships experienced is possibly more important than the quantity of social interaction for older people, and having social relationships outside the informal social network may increase happiness.

Does job insecurity deteriorate health?

PubMed

Caroli, Eve; Godard, Mathilde

2016-02-01

This paper estimates the causal effect of perceived job insecurity - that is, the fear of involuntary job loss - on health in a sample of men from 22 European countries. We rely on an original instrumental variable approach on the basis of the idea that workers perceive greater job security in countries where employment is strongly protected by the law and more so if employed in industries where employment protection legislation is more binding; that is, in induastries with a higher natural rate of dismissals. Using cross-country data from the 2010 European Working Conditions Survey, we show that, when the potential endogeneity of job insecurity is not accounted for, the latter appears to deteriorate almost all health outcomes. When tackling the endogeneity issue by estimating an instrumental variable model and dealing with potential weak-instrument issues, the health-damaging effect of job insecurity is confirmed for a limited subgroup of health outcomes; namely, suffering from headaches or eyestrain and skin problems. As for other health variables, the impact of job insecurity appears to be insignificant at conventional levels. Copyright © 2014 John Wiley & Sons, Ltd.

FFT Deconvultion of Be Star Hα Line Profiles

NASA Astrophysics Data System (ADS)

Austin, S. J.

2005-12-01

We have been monitoring the spectroscopic variability of Be stars using the UCA Fiber Fed Spectrograph. The spectra are 0.8 Angstrom/pixel resolution of the Hα line. The observed line profiles are a convolution of the actual profile and the instrumental profile. A Fast Fourier Transform (FFT) method has been used to deconvolve the observed profiles, given the instrument profile obtained by observing the narrow lines from the HgNe wavelength calibration lamp. The long-term monitoring of the spectroscopic variability of Be stars is crucial for testing the various Be star models. Deconvolved H-α line profiles, velocities, and variability are shown for gamma Cas, delta Sco, chi Oph, eta PsA, 48 Lib, and upsilon Sgr (HD181615). Funding has been provided by the UCA University Research Council and the Arkansas Space Grant Consortium.

Power calculator for instrumental variable analysis in pharmacoepidemiology

PubMed Central

Walker, Venexia M; Davies, Neil M; Windmeijer, Frank; Burgess, Stephen; Martin, Richard M

2017-01-01

Abstract Background Instrumental variable analysis, for example with physicians’ prescribing preferences as an instrument for medications issued in primary care, is an increasingly popular method in the field of pharmacoepidemiology. Existing power calculators for studies using instrumental variable analysis, such as Mendelian randomization power calculators, do not allow for the structure of research questions in this field. This is because the analysis in pharmacoepidemiology will typically have stronger instruments and detect larger causal effects than in other fields. Consequently, there is a need for dedicated power calculators for pharmacoepidemiological research. Methods and Results The formula for calculating the power of a study using instrumental variable analysis in the context of pharmacoepidemiology is derived before being validated by a simulation study. The formula is applicable for studies using a single binary instrument to analyse the causal effect of a binary exposure on a continuous outcome. An online calculator, as well as packages in both R and Stata, are provided for the implementation of the formula by others. Conclusions The statistical power of instrumental variable analysis in pharmacoepidemiological studies to detect a clinically meaningful treatment effect is an important consideration. Research questions in this field have distinct structures that must be accounted for when calculating power. The formula presented differs from existing instrumental variable power formulae due to its parametrization, which is designed specifically for ease of use by pharmacoepidemiologists. PMID:28575313

Compliance-Effect Correlation Bias in Instrumental Variables Estimators

ERIC Educational Resources Information Center

Reardon, Sean F.

2010-01-01

Instrumental variable estimators hold the promise of enabling researchers to estimate the effects of educational treatments that are not (or cannot be) randomly assigned but that may be affected by randomly assigned interventions. Examples of the use of instrumental variables in such cases are increasingly common in educational and social science…

Instrumental variable methods in comparative safety and effectiveness research.

PubMed

Brookhart, M Alan; Rassen, Jeremy A; Schneeweiss, Sebastian

2010-06-01

Instrumental variable (IV) methods have been proposed as a potential approach to the common problem of uncontrolled confounding in comparative studies of medical interventions, but IV methods are unfamiliar to many researchers. The goal of this article is to provide a non-technical, practical introduction to IV methods for comparative safety and effectiveness research. We outline the principles and basic assumptions necessary for valid IV estimation, discuss how to interpret the results of an IV study, provide a review of instruments that have been used in comparative effectiveness research, and suggest some minimal reporting standards for an IV analysis. Finally, we offer our perspective of the role of IV estimation vis-à-vis more traditional approaches based on statistical modeling of the exposure or outcome. We anticipate that IV methods will be often underpowered for drug safety studies of very rare outcomes, but may be potentially useful in studies of intended effects where uncontrolled confounding may be substantial.

Literature review of some selected types of results and statistical analyses of total-ozone data. [for the ozonosphere

NASA Technical Reports Server (NTRS)

Myers, R. H.

1976-01-01

The depletion of ozone in the stratosphere is examined, and causes for the depletion are cited. Ground station and satellite measurements of ozone, which are taken on a worldwide basis, are discussed. Instruments used in ozone measurement are discussed, such as the Dobson spectrophotometer, which is credited with providing the longest and most extensive series of observations for ground based observation of stratospheric ozone. Other ground based instruments used to measure ozone are also discussed. The statistical differences of ground based measurements of ozone from these different instruments are compared to each other, and to satellite measurements. Mathematical methods (i.e., trend analysis or linear regression analysis) of analyzing the variability of ozone concentration with respect to time and lattitude are described. Various time series models which can be employed in accounting for ozone concentration variability are examined.

Life Participation for Parents: a tool for family-centered occupational therapy.

PubMed

Fingerhut, Patricia E

2013-01-01

This study describes the continued development of the Life Participation for Parents (LPP), a measurement tool to facilitate family-centered pediatric practice. LPP questionnaires were completed by 162 parents of children with special needs receiving intervention at 15 pediatric private practice clinics. Results were analyzed to establish instrument reliability and validity. Good internal consistency (α = .90) and test-retest reliability (r = .89) were established. Construct validity was examined through assessment of internal structure and comparison of the instrument to related variables. A principal components analysis resulted in a two-factor model accounting for 43.81% of the variance. As hypothesized, the LPP correlated only moderately with the Parenting Stress Index-Short Form (r = .54). The variables of child's diagnoses, age, and time in therapy did not predict parental responses. The LPP is a reliable and valid instrument for measuring satisfaction with parental participation in life occupations. Copyright © 2013 by the American Occupational Therapy Association, Inc.

Reconstruction of total and spectral solar irradiance from 1974 to 2013 based on KPVT, SoHO/MDI, and SDO/HMI observations

NASA Astrophysics Data System (ADS)

Yeo, K. L.; Krivova, N. A.; Solanki, S. K.; Glassmeier, K. H.

2014-10-01

Context. Total and spectral solar irradiance are key parameters in the assessment of solar influence on changes in the Earth's climate. Aims: We present a reconstruction of daily solar irradiance obtained using the SATIRE-S model spanning 1974 to 2013 based on full-disc observations from the KPVT, SoHO/MDI, and SDO/HMI. Methods: SATIRE-S ascribes variation in solar irradiance on timescales greater than a day to photospheric magnetism. The solar spectrum is reconstructed from the apparent surface coverage of bright magnetic features and sunspots in the daily data using the modelled intensity spectra of these magnetic structures. We cross-calibrated the various data sets, harmonizing the model input so as to yield a single consistent time series as the output. Results: The model replicates 92% (R2 = 0.916) of the variability in the PMOD TSI composite including the secular decline between the 1996 and 2008 solar cycle minima. The model also reproduces most of the variability in observed Lyman-α irradiance and the Mg II index. The ultraviolet solar irradiance measurements from the UARS and SORCE missions are mutually consistent up to about 180 nm before they start to exhibit discrepant rotational and cyclical variability, indicative of unresolved instrumental effects. As a result, the agreement between model and measurement, while relatively good below 180 nm, starts to deteriorate above this wavelength. As with earlier similar investigations, the reconstruction cannot reproduce the overall trends in SORCE/SIM SSI. We argue, from the lack of clear solar cycle modulation in the SIM record and the inconsistency between the total flux recorded by the instrument and TSI, that unaccounted instrumental trends are present. Conclusions: The daily solar irradiance time series is consistent with observations from multiple sources, demonstrating its validity and utility for climate models. It also provides further evidence that photospheric magnetism is the prime driver of variation in solar irradiance on timescales greater than a day.

Uncertainty in counting ice nucleating particles with continuous flow diffusion chambers

DOE PAGES

Garimella, Sarvesh; Rothenberg, Daniel A.; Wolf, Martin J.; ...

2017-09-14

This study investigates the measurement of ice nucleating particle (INP) concentrations and sizing of crystals using continuous flow diffusion chambers (CFDCs). CFDCs have been deployed for decades to measure the formation of INPs under controlled humidity and temperature conditions in laboratory studies and by ambient aerosol populations. These measurements have, in turn, been used to construct parameterizations for use in models by relating the formation of ice crystals to state variables such as temperature and humidity as well as aerosol particle properties such as composition and number. We show here that assumptions of ideal instrument behavior are not supported by measurements mademore » with a commercially available CFDC, the SPectrometer for Ice Nucleation (SPIN), and the instrument on which it is based, the Zurich Ice Nucleation Chamber (ZINC). Non-ideal instrument behavior, which is likely inherent to varying degrees in all CFDCs, is caused by exposure of particles to different humidities and/or temperatures than predicated from instrument theory of operation. This can result in a systematic, and variable, underestimation of reported INP concentrations. Here we find here variable correction factors from 1.5 to 9.5, consistent with previous literature values. We use a machine learning approach to show that non-ideality is most likely due to small-scale flow features where the aerosols are combined with sheath flows. Machine learning is also used to minimize the uncertainty in measured INP concentrations. Finally, we suggest that detailed measurement, on an instrument-by-instrument basis, be performed to characterize this uncertainty.« less

Beyond annual streamflow reconstructions for the Upper Colorado River Basin: a paleo-water-balance approach

USGS Publications Warehouse

Gangopadhyay, Subhrendu; McCabe, Gregory J.; Woodhouse, Connie A.

2015-01-01

In this paper, we present a methodology to use annual tree-ring chronologies and a monthly water balance model to generate annual reconstructions of water balance variables (e.g., potential evapotrans- piration (PET), actual evapotranspiration (AET), snow water equivalent (SWE), soil moisture storage (SMS), and runoff (R)). The method involves resampling monthly temperature and precipitation from the instrumental record directed by variability indicated by the paleoclimate record. The generated time series of monthly temperature and precipitation are subsequently used as inputs to a monthly water balance model. The methodology is applied to the Upper Colorado River Basin, and results indicate that the methodology reliably simulates water-year runoff, maximum snow water equivalent, and seasonal soil moisture storage for the instrumental period. As a final application, the methodology is used to produce time series of PET, AET, SWE, SMS, and R for the 1404–1905 period for the Upper Colorado River Basin.

[A survey instrument for evaluating psychological variables and risky sexual behavior among young adults at two university centers in Mexico].

PubMed

Piña López, Julio A; Robles Montijo, Susana; Rivera Icedo, Blanca M

2007-11-01

To measure the psychometric attributes of a survey instrument designed to evaluate historical and context variables that lead to high-risk sexual behaviors among a sample of university students in Mexico. Cross-sectional study of a sample of 1 346 university students in Mexico: 784 from the Sonora State Center for Higher Education in Hermosillo, Sonora, or 33.2% of its total enrollment; and 562 from the National Autonomous University of Mexico, at Tlalnepantla campus in Mexico State, or 23.5% of its total enrollment. The study took place in Hermosillo during the month of October 2006 and in Tlalnepantla from January to March 2006. The survey had 11 questions on sociodemographics, 7 on risky sexual behaviors, 22 on related motives, 8 on social context, and 6 on physical status prior to sexual relations. The survey was evaluated in terms of how well the questions were understood, its conceptual validity, and reliability. The final version of the survey instrument was composed of 44 questions. The reliability analysis produced an overall Cronbach alpha value of 0.821, taking into account all the variables combined and grouped by factor. Three factors were found that together accounted for 38.36% of the total variance: reasons for not using a condom in the first sexual relationship or throughout life, reasons for inconsistent use of a condom with a casual sex partner, and willingness to become sexually active and to engage in casual sex. The psychometric attributes of this survey instrument were found to be satisfactory. Those interested in using this instrument should become familiar with the theoretical model on which it is based, since understanding the results depends on properly defining the historical and context variables, and their interaction.

Instrumental Variable Estimates of the Labor Market Spillover Effects of Welfare Reform. Upjohn Institute Staff Working Paper.

ERIC Educational Resources Information Center

Bartik, Timothy J.

The labor market spillover effects of welfare reform were estimated by using models that pool time-series and cross-section data from the Current Population Survey on the state-year cell means of wages, employment, and other labor market outcomes for various demographic groups. The labor market outcomes in question are dependent variables that are…

Development process and initial validation of the Ethical Conflict in Nursing Questionnaire-Critical Care Version

PubMed Central

2013-01-01

Background Ethical conflicts are arising as a result of the growing complexity of clinical care, coupled with technological advances. Most studies that have developed instruments for measuring ethical conflict base their measures on the variables ‘frequency’ and ‘degree of conflict’. In our view, however, these variables are insufficient for explaining the root of ethical conflicts. Consequently, the present study formulates a conceptual model that also includes the variable ‘exposure to conflict’, as well as considering six ‘types of ethical conflict’. An instrument was then designed to measure the ethical conflicts experienced by nurses who work with critical care patients. The paper describes the development process and validation of this instrument, the Ethical Conflict in Nursing Questionnaire Critical Care Version (ECNQ-CCV). Methods The sample comprised 205 nursing professionals from the critical care units of two hospitals in Barcelona (Spain). The ECNQ-CCV presents 19 nursing scenarios with the potential to produce ethical conflict in the critical care setting. Exposure to ethical conflict was assessed by means of the Index of Exposure to Ethical Conflict (IEEC), a specific index developed to provide a reference value for each respondent by combining the intensity and frequency of occurrence of each scenario featured in the ECNQ-CCV. Following content validity, construct validity was assessed by means of Exploratory Factor Analysis (EFA), while Cronbach’s alpha was used to evaluate the instrument’s reliability. All analyses were performed using the statistical software PASW v19. Results Cronbach’s alpha for the ECNQ-CCV as a whole was 0.882, which is higher than the values reported for certain other related instruments. The EFA suggested a unidimensional structure, with one component accounting for 33.41% of the explained variance. Conclusions The ECNQ-CCV is shown to a valid and reliable instrument for use in critical care units. Its structure is such that the four variables on which our model of ethical conflict is based may be studied separately or in combination. The critical care nurses in this sample present moderate levels of exposure to ethical conflict. This study represents the first evaluation of the ECNQ-CCV. PMID:23725477

Solar spectral irradiance variability in cycle 24: observations and models

NASA Astrophysics Data System (ADS)

Marchenko, Sergey V.; DeLand, Matthew T.; Lean, Judith L.

2016-12-01

Utilizing the excellent stability of the Ozone Monitoring Instrument (OMI), we characterize both short-term (solar rotation) and long-term (solar cycle) changes of the solar spectral irradiance (SSI) between 265 and 500 nm during the ongoing cycle 24. We supplement the OMI data with concurrent observations from the Global Ozone Monitoring Experiment-2 (GOME-2) and Solar Radiation and Climate Experiment (SORCE) instruments and find fair-to-excellent, depending on wavelength, agreement among the observations, and predictions of the Naval Research Laboratory Solar Spectral Irradiance (NRLSSI2) and Spectral And Total Irradiance REconstruction for the Satellite era (SATIRE-S) models.

Using Instrumental Variable (IV) Tests to Evaluate Model Specification in Latent Variable Structural Equation Models*

PubMed Central

Kirby, James B.; Bollen, Kenneth A.

2009-01-01

Structural Equation Modeling with latent variables (SEM) is a powerful tool for social and behavioral scientists, combining many of the strengths of psychometrics and econometrics into a single framework. The most common estimator for SEM is the full-information maximum likelihood estimator (ML), but there is continuing interest in limited information estimators because of their distributional robustness and their greater resistance to structural specification errors. However, the literature discussing model fit for limited information estimators for latent variable models is sparse compared to that for full information estimators. We address this shortcoming by providing several specification tests based on the 2SLS estimator for latent variable structural equation models developed by Bollen (1996). We explain how these tests can be used to not only identify a misspecified model, but to help diagnose the source of misspecification within a model. We present and discuss results from a Monte Carlo experiment designed to evaluate the finite sample properties of these tests. Our findings suggest that the 2SLS tests successfully identify most misspecified models, even those with modest misspecification, and that they provide researchers with information that can help diagnose the source of misspecification. PMID:20419054

Template-Directed Instrumentation Reduces Cost and Improves Efficiency for Total Knee Arthroplasty: An Economic Decision Analysis and Pilot Study.

PubMed

McLawhorn, Alexander S; Carroll, Kaitlin M; Blevins, Jason L; DeNegre, Scott T; Mayman, David J; Jerabek, Seth A

2015-10-01

Template-directed instrumentation (TDI) for total knee arthroplasty (TKA) may streamline operating room (OR) workflow and reduce costs by preselecting implants and minimizing instrument tray burden. A decision model simulated the economics of TDI. Sensitivity analyses determined thresholds for model variables to ensure TDI success. A clinical pilot was reviewed. The accuracy of preoperative templates was validated, and 20 consecutive primary TKAs were performed using TDI. The model determined that preoperative component size estimation should be accurate to ±1 implant size for 50% of TKAs to implement TDI. The pilot showed that preoperative template accuracy exceeded 97%. There were statistically significant improvements in OR turnover time and in-room time for TDI compared to an historical cohort of TKAs. TDI reduces costs and improves OR efficiency. Copyright © 2015 Elsevier Inc. All rights reserved.

The contextual effects of social capital on health: a cross-national instrumental variable analysis.

PubMed

Kim, Daniel; Baum, Christopher F; Ganz, Michael L; Subramanian, S V; Kawachi, Ichiro

2011-12-01

Past research on the associations between area-level/contextual social capital and health has produced conflicting evidence. However, interpreting this rapidly growing literature is difficult because estimates using conventional regression are prone to major sources of bias including residual confounding and reverse causation. Instrumental variable (IV) analysis can reduce such bias. Using data on up to 167,344 adults in 64 nations in the European and World Values Surveys and applying IV and ordinary least squares (OLS) regression, we estimated the contextual effects of country-level social trust on individual self-rated health. We further explored whether these associations varied by gender and individual levels of trust. Using OLS regression, we found higher average country-level trust to be associated with better self-rated health in both women and men. Instrumental variable analysis yielded qualitatively similar results, although the estimates were more than double in size in both sexes when country population density and corruption were used as instruments. The estimated health effects of raising the percentage of a country's population that trusts others by 10 percentage points were at least as large as the estimated health effects of an individual developing trust in others. These findings were robust to alternative model specifications and instruments. Conventional regression and to a lesser extent IV analysis suggested that these associations are more salient in women and in women reporting social trust. In a large cross-national study, our findings, including those using instrumental variables, support the presence of beneficial effects of higher country-level trust on self-rated health. Previous findings for contextual social capital using traditional regression may have underestimated the true associations. Given the close linkages between self-rated health and all-cause mortality, the public health gains from raising social capital within and across countries may be large. Copyright © 2011 Elsevier Ltd. All rights reserved.

The contextual effects of social capital on health: a cross-national instrumental variable analysis

PubMed Central

Kim, Daniel; Baum, Christopher F; Ganz, Michael; Subramanian, S V; Kawachi, Ichiro

2011-01-01

Past observational studies of the associations of area-level/contextual social capital with health have revealed conflicting findings. However, interpreting this rapidly growing literature is difficult because estimates using conventional regression are prone to major sources of bias including residual confounding and reverse causation. Instrumental variable (IV) analysis can reduce such bias. Using data on up to 167 344 adults in 64 nations in the European and World Values Surveys and applying IV and ordinary least squares (OLS) regression, we estimated the contextual effects of country-level social trust on individual self-rated health. We further explored whether these associations varied by gender and individual levels of trust. Using OLS regression, we found higher average country-level trust to be associated with better self-rated health in both women and men. Instrumental variable analysis yielded qualitatively similar results, although the estimates were more than double in size in women and men using country population density and corruption as instruments. The estimated health effects of raising the percentage of a country's population that trusts others by 10 percentage points were at least as large as the estimated health effects of an individual developing trust in others. These findings were robust to alternative model specifications and instruments. Conventional regression and to a lesser extent IV analysis suggested that these associations are more salient in women and in women reporting social trust. In a large cross-national study, our findings, including those using instrumental variables, support the presence of beneficial effects of higher country-level trust on self-rated health. Past findings for contextual social capital using traditional regression may have underestimated the true associations. Given the close linkages between self-rated health and all-cause mortality, the public health gains from raising social capital within countries may be large. PMID:22078106

Promoting motivation through mode of instruction: The relationship between use of affective teaching techniques and motivation to learn science

NASA Astrophysics Data System (ADS)

Sanchez Rivera, Yamil

The purpose of this study is to add to what we know about the affective domain and to create a valid instrument for future studies. The Motivation to Learn Science (MLS) Inventory is based on Krathwohl's Taxonomy of Affective Behaviors (Krathwohl et al., 1964). The results of the Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) demonstrated that the MLS Inventory is a valid and reliable instrument. Therefore, the MLS Inventory is a uni-dimensional instrument composed of 9 items with convergent validity (no divergence). The instrument had a high Chronbach Alpha value of .898 during the EFA analysis and .919 with the CFA analysis. Factor loadings on the 9 items ranged from .617 to .800. Standardized regression weights ranged from .639 to .835 in the CFA analysis. Various indices (RMSEA = .033; NFI = .987; GFI = .985; CFI = 1.000) demonstrated a good fitness of the proposed model. Hierarchical linear modeling was used to statistical analyze data where students' motivation to learn science scores (level-1) were nested within teachers (level-2). The analysis was geared toward identifying if teachers' use of affective behavior (a level-2 classroom variable) was significantly related with students' MLS scores (level-1 criterion variable). Model testing proceeded in three phases: intercept-only model, means-as-outcome model, and a random-regression coefficient model. The intercept-only model revealed an intra-class correlation coefficient of .224 with an estimated reliability of .726. Therefore, data suggested that only 22.4% of the variance in MLS scores is between-classes and the remaining 77.6% is at the student-level. Due to the significant variance in MLS scores, X2(62.756, p<.0001), teachers' TAB scores were added as a level-2 predictor. The regression coefficient was non-significant (p>.05). Therefore, the teachers' self-reported use of affective behaviors was not a significant predictor of students' motivation to learn science.

Here Be Dragons: Effective (X-ray) Timing with the Cospectrum

NASA Astrophysics Data System (ADS)

Huppenkothen, Daniela; Bachetti, Matteo

2018-01-01

In recent years, the cross spectrum has received considerable attention as a means of characterising the variability of astronomical sources as a function of wavelength. While much has been written about the statistics of time and phase lags, the cospectrum—the real part of the cross spectrum—has only recently been understood as means of mitigating instrumental effects dependent on temporal frequency in astronomical detectors, as well as a method of characterizing the coherent variability in two wavelength ranges on different time scales. In this talk, I will present recent advances made in understanding the statistical properties of cospectra, leading to much improved inferences for periodic and quasi-periodic signals. I will also present a new method to reliably mitigate instrumental effects such as dead time in X-ray detectors, and show how we can use the cospectrum to model highly variable sources such as X-ray binaries or Active Galactic Nuclei.

Suwannee River flow variability 1550-2005 CE reconstructed from a multispecies tree-ring network

NASA Astrophysics Data System (ADS)

Harley, Grant L.; Maxwell, Justin T.; Larson, Evan; Grissino-Mayer, Henri D.; Henderson, Joseph; Huffman, Jean

2017-01-01

Understanding the long-term natural flow regime of rivers enables resource managers to more accurately model water level variability. Models for managing water resources are important in Florida where population increase is escalating demand on water resources and infrastructure. The Suwannee River is the second largest river system in Florida and the least impacted by anthropogenic disturbance. We used new and existing tree-ring chronologies from multiple species to reconstruct mean March-October discharge for the Suwannee River during the period 1550-2005 CE and place the short period of instrumental flows (since 1927 CE) into historical context. We used a nested principal components regression method to maximize the use of chronologies with varying time coverage in the network. Modeled streamflow estimates indicated that instrumental period flow conditions do not adequately capture the full range of Suwannee River flow variability beyond the observational period. Although extreme dry and wet events occurred in the gage record, pluvials and droughts that eclipse the intensity and duration of instrumental events occurred during the 16-19th centuries. The most prolonged and severe dry conditions during the past 450 years occurred during the 1560s CE. In this prolonged drought period mean flow was estimated at 17% of the mean instrumental period flow. Significant peaks in spectral density at 2-7, 10, 45, and 85-year periodicities indicated the important influence of coupled oceanic-atmospheric processes on Suwannee River streamflow over the past four centuries, though the strength of these periodicities varied over time. Future water planning based on current flow expectations could prove devastating to natural and human systems if a prolonged and severe drought mirroring the 16th and 18th century events occurred. Future work in the region will focus on updating existing tree-ring chronologies and developing new collections from moisture-sensitive sites to improve understandings of past hydroclimate in the region.

PACIC Instrument: disentangling dimensions using published validation models.

PubMed

Iglesias, K; Burnand, B; Peytremann-Bridevaux, I

2014-06-01

To better understand the structure of the Patient Assessment of Chronic Illness Care (PACIC) instrument. More specifically to test all published validation models, using one single data set and appropriate statistical tools. Validation study using data from cross-sectional survey. A population-based sample of non-institutionalized adults with diabetes residing in Switzerland (canton of Vaud). French version of the 20-items PACIC instrument (5-point response scale). We conducted validation analyses using confirmatory factor analysis (CFA). The original five-dimension model and other published models were tested with three types of CFA: based on (i) a Pearson estimator of variance-covariance matrix, (ii) a polychoric correlation matrix and (iii) a likelihood estimation with a multinomial distribution for the manifest variables. All models were assessed using loadings and goodness-of-fit measures. The analytical sample included 406 patients. Mean age was 64.4 years and 59% were men. Median of item responses varied between 1 and 4 (range 1-5), and range of missing values was between 5.7 and 12.3%. Strong floor and ceiling effects were present. Even though loadings of the tested models were relatively high, the only model showing acceptable fit was the 11-item single-dimension model. PACIC was associated with the expected variables of the field. Our results showed that the model considering 11 items in a single dimension exhibited the best fit for our data. A single score, in complement to the consideration of single-item results, might be used instead of the five dimensions usually described. © The Author 2014. Published by Oxford University Press in association with the International Society for Quality in Health Care; all rights reserved.

Solar UV Variations During the Decline of Cycle 23

NASA Technical Reports Server (NTRS)

DeLand, Matthew, T.; Cebula, Richard P.

2011-01-01

Characterization of temporal and spectral variations in solar ultraviolet irradiance over a solar cycle is essential for understanding the forcing of Earth's atmosphere and climate. Satellite measurements of solar UV variability for solar cycles 21, 22, and 23 show consistent solar cycle irradiance changes at key wavelengths (e.g. 205 nm, 250 nm) within instrumental uncertainties. All historical data sets also show the same relative spectral dependence for both short-term (rotational) and long-term (solar cycle) variations. Empirical solar irradiance models also produce long-term solar UV variations that agree well with observational data. Recent UV irradiance data from the Solar Radiation and Climate Experiment (SORCE) Spectral Irradiance Monitor (SIM) and Solar Stellar Irradiance Comparison Experiment (SOLSTICE) instruments covering the declining phase of Cycle 23 present a different picture oflong-term solar variations from previous results. Time series of SIM and SOLSTICE spectral irradiance data between 2003 and 2007 show solar variations that greatly exceed both previous measurements and predicted irradiance changes over this period, and the spectral dependence of the SIM and SOLSTICE variations during these years do not show features expected from solar physics theory. The use of SORCE irradiance variations in atmospheric models yields substantially different middle atmosphere ozone responses in both magnitude and vertical structure. However, short-term solar variability derived from SIM and SOLSTICE UV irradiance data is consistent with concurrent solar UV measurements from other instruments, as well as previous results, suggesting no change in solar physics. Our analysis of short-term solar variability is much less sensitive to residual instrument response changes than the observations of long-term variations. The SORCE long-term UV results can be explained by under-correction of instrument response changes during the first few years of measurements, rather than requiring an unexpected change in the physical behavior of the Sun.

Using instrumental variables to estimate a Cox's proportional hazards regression subject to additive confounding

PubMed Central

Tosteson, Tor D.; Morden, Nancy E.; Stukel, Therese A.; O'Malley, A. James

2014-01-01

The estimation of treatment effects is one of the primary goals of statistics in medicine. Estimation based on observational studies is subject to confounding. Statistical methods for controlling bias due to confounding include regression adjustment, propensity scores and inverse probability weighted estimators. These methods require that all confounders are recorded in the data. The method of instrumental variables (IVs) can eliminate bias in observational studies even in the absence of information on confounders. We propose a method for integrating IVs within the framework of Cox's proportional hazards model and demonstrate the conditions under which it recovers the causal effect of treatment. The methodology is based on the approximate orthogonality of an instrument with unobserved confounders among those at risk. We derive an estimator as the solution to an estimating equation that resembles the score equation of the partial likelihood in much the same way as the traditional IV estimator resembles the normal equations. To justify this IV estimator for a Cox model we perform simulations to evaluate its operating characteristics. Finally, we apply the estimator to an observational study of the effect of coronary catheterization on survival. PMID:25506259

Using instrumental variables to estimate a Cox's proportional hazards regression subject to additive confounding.

PubMed

MacKenzie, Todd A; Tosteson, Tor D; Morden, Nancy E; Stukel, Therese A; O'Malley, A James

2014-06-01

The estimation of treatment effects is one of the primary goals of statistics in medicine. Estimation based on observational studies is subject to confounding. Statistical methods for controlling bias due to confounding include regression adjustment, propensity scores and inverse probability weighted estimators. These methods require that all confounders are recorded in the data. The method of instrumental variables (IVs) can eliminate bias in observational studies even in the absence of information on confounders. We propose a method for integrating IVs within the framework of Cox's proportional hazards model and demonstrate the conditions under which it recovers the causal effect of treatment. The methodology is based on the approximate orthogonality of an instrument with unobserved confounders among those at risk. We derive an estimator as the solution to an estimating equation that resembles the score equation of the partial likelihood in much the same way as the traditional IV estimator resembles the normal equations. To justify this IV estimator for a Cox model we perform simulations to evaluate its operating characteristics. Finally, we apply the estimator to an observational study of the effect of coronary catheterization on survival.

Tests of Hypotheses Arising In the Correlated Random Coefficient Model*

PubMed Central

Heckman, James J.; Schmierer, Daniel

2010-01-01

This paper examines the correlated random coefficient model. It extends the analysis of Swamy (1971), who pioneered the uncorrelated random coefficient model in economics. We develop the properties of the correlated random coefficient model and derive a new representation of the variance of the instrumental variable estimator for that model. We develop tests of the validity of the correlated random coefficient model against the null hypothesis of the uncorrelated random coefficient model. PMID:21170148

Error-in-variables models in calibration

NASA Astrophysics Data System (ADS)

Lira, I.; Grientschnig, D.

2017-12-01

In many calibration operations, the stimuli applied to the measuring system or instrument under test are derived from measurement standards whose values may be considered to be perfectly known. In that case, it is assumed that calibration uncertainty arises solely from inexact measurement of the responses, from imperfect control of the calibration process and from the possible inaccuracy of the calibration model. However, the premise that the stimuli are completely known is never strictly fulfilled and in some instances it may be grossly inadequate. Then, error-in-variables (EIV) regression models have to be employed. In metrology, these models have been approached mostly from the frequentist perspective. In contrast, not much guidance is available on their Bayesian analysis. In this paper, we first present a brief summary of the conventional statistical techniques that have been developed to deal with EIV models in calibration. We then proceed to discuss the alternative Bayesian framework under some simplifying assumptions. Through a detailed example about the calibration of an instrument for measuring flow rates, we provide advice on how the user of the calibration function should employ the latter framework for inferring the stimulus acting on the calibrated device when, in use, a certain response is measured.

Close-range laser scanning in forests: towards physically based semantics across scales.

PubMed

Morsdorf, F; Kükenbrink, D; Schneider, F D; Abegg, M; Schaepman, M E

2018-04-06

Laser scanning with its unique measurement concept holds the potential to revolutionize the way we assess and quantify three-dimensional vegetation structure. Modern laser systems used at close range, be it on terrestrial, mobile or unmanned aerial platforms, provide dense and accurate three-dimensional data whose information just waits to be harvested. However, the transformation of such data to information is not as straightforward as for airborne and space-borne approaches, where typically empirical models are built using ground truth of target variables. Simpler variables, such as diameter at breast height, can be readily derived and validated. More complex variables, e.g. leaf area index, need a thorough understanding and consideration of the physical particularities of the measurement process and semantic labelling of the point cloud. Quantified structural models provide a framework for such labelling by deriving stem and branch architecture, a basis for many of the more complex structural variables. The physical information of the laser scanning process is still underused and we show how it could play a vital role in conjunction with three-dimensional radiative transfer models to shape the information retrieval methods of the future. Using such a combined forward and physically based approach will make methods robust and transferable. In addition, it avoids replacing observer bias from field inventories with instrument bias from different laser instruments. Still, an intensive dialogue with the users of the derived information is mandatory to potentially re-design structural concepts and variables so that they profit most of the rich data that close-range laser scanning provides.

Surgical instrument similarity metrics and tray analysis for multi-sensor instrument identification

NASA Astrophysics Data System (ADS)

Glaser, Bernhard; Schellenberg, Tobias; Franke, Stefan; Dänzer, Stefan; Neumuth, Thomas

2015-03-01

A robust identification of the instrument currently used by the surgeon is crucial for the automatic modeling and analysis of surgical procedures. Various approaches for intra-operative surgical instrument identification have been presented, mostly based on radio-frequency identification (RFID) or endoscopic video analysis. A novel approach is to identify the instruments on the instrument table of the scrub nurse with a combination of video and weight information. In a previous article, we successfully followed this approach and applied it to multiple instances of an ear, nose and throat (ENT) procedure and the surgical tray used therein. In this article, we present a metric for the suitability of the instruments of a surgical tray for identification by video and weight analysis and apply it to twelve trays of four different surgical domains (abdominal surgery, neurosurgery, orthopedics and urology). The used trays were digitized at the central sterile services department of the hospital. The results illustrate that surgical trays differ in their suitability for the approach. In general, additional weight information can significantly contribute to the successful identification of surgical instruments. Additionally, for ten different surgical instruments, ten exemplars of each instrument were tested for their weight differences. The samples indicate high weight variability in instruments with identical brand and model number. The results present a new metric for approaches aiming towards intra-operative surgical instrument detection and imply consequences for algorithms exploiting video and weight information for identification purposes.

The Application of a Model of Turnover in Work Organizations to the Student Attrition Process. Air Forum 1981 Paper.

ERIC Educational Resources Information Center

Bean, John P.

A theoretical model of turnover in work organizations was applied to the college student dropout process at a major midwestern land grant university. The 854 freshmen women subjects completed a questionnaire that included measures for 14 independent variables: grades, practical value, development, routinization, instrumental communication,…

Modeling Outcomes with Floor or Ceiling Effects: An Introduction to the Tobit Model

ERIC Educational Resources Information Center

McBee, Matthew

2010-01-01

In gifted education research, it is common for outcome variables to exhibit strong floor or ceiling effects due to insufficient range of measurement of many instruments when used with gifted populations. Common statistical methods (e.g., analysis of variance, linear regression) produce biased estimates when such effects are present. In practice,…

Estimating Causal Effects of Local Air Pollution on Daily Deaths: Effect of Low Levels.

PubMed

Schwartz, Joel; Bind, Marie-Abele; Koutrakis, Petros

2017-01-01

Although many time-series studies have established associations of daily pollution variations with daily deaths, there are fewer at low concentrations, or focused on locally generated pollution, which is becoming more important as regulations reduce regional transport. Causal modeling approaches are also lacking. We used causal modeling to estimate the impact of local air pollution on mortality at low concentrations. Using an instrumental variable approach, we developed an instrument for variations in local pollution concentrations that is unlikely to be correlated with other causes of death, and examined its association with daily deaths in the Boston, Massachusetts, area. We combined height of the planetary boundary layer and wind speed, which affect concentrations of local emissions, to develop the instrument for particulate matter ≤ 2.5 μm (PM2.5), black carbon (BC), or nitrogen dioxide (NO2) variations that were independent of year, month, and temperature. We also used Granger causality to assess whether omitted variable confounding existed. We estimated that an interquartile range increase in the instrument for local PM2.5 was associated with a 0.90% increase in daily deaths (95% CI: 0.25, 1.56). A similar result was found for BC, and a weaker association with NO2. The Granger test found no evidence of omitted variable confounding for the instrument. A separate test confirmed the instrument was not associated with mortality independent of pollution. Furthermore, the association remained when all days with PM2.5 concentrations > 30 μg/m3 were excluded from the analysis (0.84% increase in daily deaths; 95% CI: 0.19, 1.50). We conclude that there is a causal association of local air pollution with daily deaths at concentrations below U.S. EPA standards. The estimated attributable risk in Boston exceeded 1,800 deaths during the study period, indicating that important public health benefits can follow from further control efforts. Citation: Schwartz J, Bind MA, Koutrakis P. 2017. Estimating causal effects of local air pollution on daily deaths: effect of low levels. Environ Health Perspect 125:23-29; http://dx.doi.org/10.1289/EHP232.

Sulfur dioxide in the Venus atmosphere: I. Vertical distribution and variability

NASA Astrophysics Data System (ADS)

Vandaele, A. C.; Korablev, O.; Belyaev, D.; Chamberlain, S.; Evdokimova, D.; Encrenaz, Th.; Esposito, L.; Jessup, K. L.; Lefèvre, F.; Limaye, S.; Mahieux, A.; Marcq, E.; Mills, F. P.; Montmessin, F.; Parkinson, C. D.; Robert, S.; Roman, T.; Sandor, B.; Stolzenbach, A.; Wilson, C.; Wilquet, V.

2017-10-01

Recent observations of sulfur containing species (SO2, SO, OCS, and H2SO4) in Venus' mesosphere have generated controversy and great interest in the scientific community. These observations revealed unexpected spatial patterns and spatial/temporal variability that have not been satisfactorily explained by models. Sulfur oxide chemistry on Venus is closely linked to the global-scale cloud and haze layers, which are composed primarily of concentrated sulfuric acid. Sulfur oxide observations provide therefore important insight into the on-going chemical evolution of Venus' atmosphere, atmospheric dynamics, and possible volcanism. This paper is the first of a series of two investigating the SO2 and SO variability in the Venus atmosphere. This first part of the study will focus on the vertical distribution of SO2, considering mostly observations performed by instruments and techniques providing accurate vertical information. This comprises instruments in space (SPICAV/SOIR suite on board Venus Express) and Earth-based instruments (JCMT). The most noticeable feature of the vertical profile of the SO2 abundance in the Venus atmosphere is the presence of an inversion layer located at about 70-75 km, with VMRs increasing above. The observations presented in this compilation indicate that at least one other significant sulfur reservoir (in addition to SO2 and SO) must be present throughout the 70-100 km altitude region to explain the inversion in the SO2 vertical profile. No photochemical model has an explanation for this behaviour. GCM modelling indicates that dynamics may play an important role in generating an inflection point at 75 km altitude but does not provide a definitive explanation of the source of the inflection at all local times or latitudes The current study has been carried out within the frame of the International Space Science Institute (ISSI) International Team entitled 'SO2 variability in the Venus atmosphere'.

Solar Spectral Irradiance Variability in Cycle 24: Model Predictions and OMI Observations

NASA Technical Reports Server (NTRS)

Marchenko, S.; DeLand, M.; Lean, J.

2016-01-01

Utilizing the excellent stability of the Ozone Monitoring Instrument (OMI), we characterize both short-term (solar rotation) and long-term (solar cycle) changes of the solar spectral irradiance (SSI) between 265-500 nanometers during the ongoing Cycle 24. We supplement the OMI data with concurrent observations from the GOME-2 (Global Ozone Monitoring Experiment - 2) and SORCE (Solar Radiation and Climate Experiment) instruments and find fair-to-excellent agreement between the observations and predictions of the NRLSSI2 (Naval Research Laboratory Solar Spectral Irradiance - post SORCE) and SATIRE-S (the Naval Research Laboratory's Spectral And Total Irradiance REconstruction for the Satellite era) models.

Statistical Time Series Models of Pilot Control with Applications to Instrument Discrimination

NASA Technical Reports Server (NTRS)

Altschul, R. E.; Nagel, P. M.; Oliver, F.

1984-01-01

A general description of the methodology used in obtaining the transfer function models and verification of model fidelity, frequency domain plots of the modeled transfer functions, numerical results obtained from an analysis of poles and zeroes obtained from z plane to s-plane conversions of the transfer functions, and the results of a study on the sequential introduction of other variables, both exogenous and endogenous into the loop are contained.

How the 2SLS/IV estimator can handle equality constraints in structural equation models: a system-of-equations approach.

PubMed

Nestler, Steffen

2014-05-01

Parameters in structural equation models are typically estimated using the maximum likelihood (ML) approach. Bollen (1996) proposed an alternative non-iterative, equation-by-equation estimator that uses instrumental variables. Although this two-stage least squares/instrumental variables (2SLS/IV) estimator has good statistical properties, one problem with its application is that parameter equality constraints cannot be imposed. This paper presents a mathematical solution to this problem that is based on an extension of the 2SLS/IV approach to a system of equations. We present an example in which our approach was used to examine strong longitudinal measurement invariance. We also investigated the new approach in a simulation study that compared it with ML in the examination of the equality of two latent regression coefficients and strong measurement invariance. Overall, the results show that the suggested approach is a useful extension of the original 2SLS/IV estimator and allows for the effective handling of equality constraints in structural equation models. © 2013 The British Psychological Society.

Social interactions and college enrollment: A combined school fixed effects/instrumental variables approach.

PubMed

Fletcher, Jason M

2015-07-01

This paper provides some of the first evidence of peer effects in college enrollment decisions. There are several empirical challenges in assessing the influences of peers in this context, including the endogeneity of high school, shared group-level unobservables, and identifying policy-relevant parameters of social interactions models. This paper addresses these issues by using an instrumental variables/fixed effects approach that compares students in the same school but different grade-levels who are thus exposed to different sets of classmates. In particular, plausibly exogenous variation in peers' parents' college expectations are used as an instrument for peers' college choices. Preferred specifications indicate that increasing a student's exposure to college-going peers by ten percentage points is predicted to raise the student's probability of enrolling in college by 4 percentage points. This effect is roughly half the magnitude of growing up in a household with married parents (vs. an unmarried household). Copyright © 2015 Elsevier Inc. All rights reserved.

Instrumental variable methods in comparative safety and effectiveness research†

PubMed Central

Brookhart, M. Alan; Rassen, Jeremy A.; Schneeweiss, Sebastian

2010-01-01

Summary Instrumental variable (IV) methods have been proposed as a potential approach to the common problem of uncontrolled confounding in comparative studies of medical interventions, but IV methods are unfamiliar to many researchers. The goal of this article is to provide a non-technical, practical introduction to IV methods for comparative safety and effectiveness research. We outline the principles and basic assumptions necessary for valid IV estimation, discuss how to interpret the results of an IV study, provide a review of instruments that have been used in comparative effectiveness research, and suggest some minimal reporting standards for an IV analysis. Finally, we offer our perspective of the role of IV estimation vis-à-vis more traditional approaches based on statistical modeling of the exposure or outcome. We anticipate that IV methods will be often underpowered for drug safety studies of very rare outcomes, but may be potentially useful in studies of intended effects where uncontrolled confounding may be substantial. PMID:20354968

Social Interactions and College Enrollment: A Combined School Fixed Effects/Instrumental Variables Approach

PubMed Central

Fletcher, Jason M.

2015-01-01

This paper provides some of the first evidence of peer effects in college enrollment decisions. There are several empirical challenges in assessing the influences of peers in this context, including the endogeneity of high school, shared group-level unobservables, and identifying policy-relevant parameters of social interactions models. This paper addresses these issues by using an instrumental variables/fixed effects approach that compares students in the same school but different grade-levels who are thus exposed to different sets of classmates. In particular, plausibly exogenous variation in peers’ parents’ college expectations are used as an instrument for peers’ college choices. Preferred specifications indicate that increasing a student’s exposure to college-going peers by ten percentage points is predicted to raise the student’s probability of enrolling in college by 4 percentage points. This effect is roughly half the magnitude of growing up in a household with married parents (vs. an unmarried household). PMID:26004476

Physicians' prescribing preferences were a potential instrument for patients' actual prescriptions of antidepressants☆

PubMed Central

Davies, Neil M.; Gunnell, David; Thomas, Kyla H.; Metcalfe, Chris; Windmeijer, Frank; Martin, Richard M.

2013-01-01

Objectives To investigate whether physicians' prescribing preferences were valid instrumental variables for the antidepressant prescriptions they issued to their patients. Study Design and Setting We investigated whether physicians' previous prescriptions of (1) tricyclic antidepressants (TCAs) vs. selective serotonin reuptake inhibitors (SSRIs) and (2) paroxetine vs. other SSRIs were valid instruments. We investigated whether the instrumental variable assumptions are likely to hold and whether TCAs (vs. SSRIs) were associated with hospital admission for self-harm or death by suicide using both conventional and instrumental variable regressions. The setting for the study was general practices in the United Kingdom. Results Prior prescriptions were strongly associated with actual prescriptions: physicians who previously prescribed TCAs were 14.9 percentage points (95% confidence interval [CI], 14.4, 15.4) more likely to prescribe TCAs, and those who previously prescribed paroxetine were 27.7 percentage points (95% CI, 26.7, 28.8) more likely to prescribe paroxetine, to their next patient. Physicians' previous prescriptions were less strongly associated with patients' baseline characteristics than actual prescriptions. We found no evidence that the estimated association of TCAs with self-harm/suicide using instrumental variable regression differed from conventional regression estimates (P-value = 0.45). Conclusion The main instrumental variable assumptions held, suggesting that physicians' prescribing preferences are valid instruments for evaluating the short-term effects of antidepressants. PMID:24075596

Field Research Validation Sites | Wind | NREL

Science.gov Websites

, independent pitch control of the Controls Advanced Research Turbine (CART) blades Variable-speed or constant CART2 600-kW Turbine Model: Westinghouse Blades: 2 Hub height: 36.6 m Rotor diameter: 42.6 m Extensively instrumented CART3 600-kW Turbine Model: Westinghouse Blades: 3 Hub height: 36.6 m Rotor diameter: 42.6 m

The Fixed-Effects Model in Returns to Schooling and Its Application to Community Colleges: A Methodological Note

ERIC Educational Resources Information Center

Dynarski, Susan; Jacob, Brian; Kreisman, Daniel

2016-01-01

The purpose of this note is to develop insight into the performance of the individual fixed-effects model when used to estimate wage returns to postsecondary schooling. We focus our attention on the returns to attending and completing community college. While other methods (instrumental variables, regression discontinuity) have been used to…

High resolution geochemical proxy record of the last 600yr in a speleothem from the northwest Iberian Peninsula

NASA Astrophysics Data System (ADS)

Iglesias González, Miguel; Pisonero, Jorge; Cheng, Hai; Edwards, R. Lawrence; Stoll, Heather

2017-04-01

In meteorology and climatology, the instrumental period is the period where we have measured directly by instrumentation, different meteorological data along the surface which allow us to determinate the evolution of the climate during the last 150 years over the world. At the beginning, the density of this data were very low, so we have to wait until the last 75-100 years to have a good network in most of the parts of the surface. This time period is very small if we want to analyze the relationship between geochemical and instrumental variability in any speleothem. So a very high resolution data is needed to determinate the connection between both of them in the instrumental period, to try to determinate de evolution of climate in the last 600 years. Here we present a high resolution speleothem record from a cave located in the middle of the Cantabrian Mountains without any anthropologic influence and with no CO2 seasonal variability. This 600yr stalagmite, dated with U/Th method with a growth rate from 100 to 200 micrometers/yr calculated with Bchron model, provide us accurate information of the climate conditions near the cave. Trace elements are analyzed at 8 micrometers intervals by Laser Ablation ICP-MS which resolves even monthly resolution during the last 600 years with special attention with Sr, Mg, Al and Si. This data, without seasonal variability and with the presence of a river inside the cave, give us very valuable information about the extreme flood events inside the cave during the whole period, which is related with the precipitations and the snow fusion events outside the cave. We identify more extremely flood events during the Little Ice Age than in the last 100yr. As well, we have trace elements data with spatial resolution of 0.2mm analyzed with ICP-AES which allow us to compare the geochemical variability with both technics. We also analyze stable isotope d13C and d18O with a spatial resolution of 0.2mm, so we are able to identify variations and all possible correlations between them, trace elements and instrumental records from the different weather stations located near the cave. We use instrumental data, and the statistical correlation between our proxy and them, to calibrate and analyze the variability along the 600yr which provide us a lot of information about the climate variability. In spite of the significate global warming during the last 25 years, we have less variability during this period than along the transition between the Medieval Warm Period and the Little Ice Age. We also analyze this variability along the 600 years with wavelet analysis, with special attention in the instrumental period. With this mathematical method, we can identify several cycles both in trace elements and stable isotopes at special scales compatible with the decadal and multidecadal variability with a value similar to very important climate index like AMO.

Insomnia and hypnotic medications are associated with suicidal ideation in a community population.

PubMed

Pigeon, Wilfred R; Woosley, Julie A; Lichstein, Kenneth L

2014-01-01

Suicidal ideation (SI), a significant predictor of suicide, is associated with sleep disturbance, which is seldom assessed using stringent diagnostic criteria and validated sleep instruments in community samples. Cross-sectional data, including sleep diaries and validated instruments, from 767 community adults were used to identify variables associated with SI and subsequently entered into a regression model to predict SI. Suicidal ideation was endorsed by 9.3% of the sample. This group differed from non-ideators on several variables, but only insomnia diagnosis, depression severity, and hypnotic medication use predicted SI. Findings confirm an association of insomnia with SI using stringent criteria and controlling for depression. If treating insomnia is a conceivable pathway to reduce SI, the apparent risk posed by hypnotics may limit treatment options.

Testing an Attribution Model of Caregiving in a Latino Sample: The Roles of Familismo and the Caregiver-Care Recipient Relationship.

PubMed

Villalobos, Bianca T; Bridges, Ana J

2016-07-01

This study tests the parameters of Weiner's attribution model of caregiving, which describes how attributions of controllability relate to emotional reactions, which in turn influence willingness to provide support to stigmatized individuals. To date, the model has not been explored in the context of cultural variables, the caregiver-recipient relationship, or types of support. The present study examined the attribution model using a Latino community sample (N = 96) that was presented with vignettes describing an individual with depression. Support was found for the basic attribution model. Familismo was predictive of attributions of controllability and the basic model was predictive of emotional support, but not instrumental support. Participants were more willing to provide instrumental support to a partner, but had more positive affective reactions toward a sibling. The findings provide important information about contextual factors that may motivate Latino caregivers to provide support. © The Author(s) 2015.

Estimating the effect of treatment rate changes when treatment benefits are heterogeneous: antibiotics and otitis media.

PubMed

Park, Tae-Ryong; Brooks, John M; Chrischilles, Elizabeth A; Bergus, George

2008-01-01

Contrast methods to assess the health effects of a treatment rate change when treatment benefits are heterogeneous across patients. Antibiotic prescribing for children with otitis media (OM) in Iowa Medicaid is the empirical example. Instrumental variable (IV) and linear probability model (LPM) are used to estimate the effect of antibiotic treatments on cure probabilities for children with OM in Iowa Medicaid. Local area physician supply per capita is the instrument in the IV models. Estimates are contrasted in terms of their ability to make inferences for patients whose treatment choices may be affected by a change in population treatment rates. The instrument was positively related to the probability of being prescribed an antibiotic. LPM estimates showed a positive effect of antibiotics on OM patient cure probability while IV estimates showed no relationship between antibiotics and patient cure probability. Linear probability model estimation yields the average effects of the treatment on patients that were treated. IV estimation yields the average effects for patients whose treatment choices were affected by the instrument. As antibiotic treatment effects are heterogeneous across OM patients, our estimates from these approaches are aligned with clinical evidence and theory. The average estimate for treated patients (higher severity) from the LPM model is greater than estimates for patients whose treatment choices are affected by the instrument (lower severity) from the IV models. Based on our IV estimates it appears that lowering antibiotic use in OM patients in Iowa Medicaid did not result in lost cures.

Simulation Studies of Satellite Laser CO2 Mission Concepts

NASA Technical Reports Server (NTRS)

Kawa, Stephan Randy; Mao, J.; Abshire, J. B.; Collatz, G. J.; Sun X.; Weaver, C. J.

2011-01-01

Results of mission simulation studies are presented for a laser-based atmospheric CO2 sounder. The simulations are based on real-time carbon cycle process modeling and data analysis. The mission concept corresponds to ASCENDS as recommended by the US National Academy of Sciences Decadal Survey. Compared to passive sensors, active (lidar) sensing of CO2 from space has several potentially significant advantages that hold promise to advance CO2 measurement capability in the next decade. Although the precision and accuracy requirements remain at unprecedented levels of stringency, analysis of possible instrument technology indicates that such sensors are more than feasible. Radiative transfer model calculations, an instrument model with representative errors, and a simple retrieval approach complete the cycle from "nature" run to "pseudodata" CO2. Several mission and instrument configuration options are examined, and the sensitivity to key design variables is shown. Examples are also shown of how the resulting pseudo-measurements might be used to address key carbon cycle science questions.

Spatial Variability of Trace Gases During DISCOVER-AQ: Planning for Geostationary Observations of Atmospheric Composition

NASA Technical Reports Server (NTRS)

Follette-Cook, Melanie B.; Pickering, K.; Crawford, J.; Appel, W.; Diskin, G.; Fried, A.; Loughner, C.; Pfister, G.; Weinheimer, A.

2015-01-01

Results from an in-depth analysis of trace gas variability in MD indicated that the variability in this region was large enough to be observable by a TEMPO-like instrument. The variability observed in MD is relatively similar to the other three campaigns with a few exceptions: CO variability in CA was much higher than in the other regions; HCHO variability in CA and CO was much lower; MD showed the lowest variability in NO2All model simulations do a reasonable job simulating O3 variability. For CO, the CACO simulations largely under over estimate the variability in the observations. The variability in HCHO is underestimated for every campaign. NO2 variability is slightly overestimated in MD, more so in CO. The TX simulation underestimates the variability in each trace gas. This is most likely due to missing emissions sources (C. Loughner, manuscript in preparation).Future Work: Where reasonable, we will use these model outputs to further explore the resolvability from space of these key trace gases using analyses of tropospheric column amounts relative to satellite precision requirements, similar to Follette-Cook et al. (2015).

Graphical Models for Quasi-Experimental Designs

ERIC Educational Resources Information Center

Steiner, Peter M.; Kim, Yongnam; Hall, Courtney E.; Su, Dan

2017-01-01

Randomized controlled trials (RCTs) and quasi-experimental designs like regression discontinuity (RD) designs, instrumental variable (IV) designs, and matching and propensity score (PS) designs are frequently used for inferring causal effects. It is well known that the features of these designs facilitate the identification of a causal estimand…

Scale Reliability Evaluation with Heterogeneous Populations

ERIC Educational Resources Information Center

Raykov, Tenko; Marcoulides, George A.

2015-01-01

A latent variable modeling approach for scale reliability evaluation in heterogeneous populations is discussed. The method can be used for point and interval estimation of reliability of multicomponent measuring instruments in populations representing mixtures of an unknown number of latent classes or subpopulations. The procedure is helpful also…

Student Effort and Performance over the Semester

ERIC Educational Resources Information Center

Krohn, Gregory A.; O'Connor, Catherine M.

2005-01-01

The authors extend the standard education production function and student time allocation analysis to focus on the interactions between student effort and performance over the semester. The purged instrumental variable technique is used to obtain consistent estimators of the structural parameters of the model using data from intermediate…

Estimating the association between metabolic risk factors and marijuana use in U.S. adults using data from the continuous National Health and Nutrition Examination Survey.

PubMed

Thompson, Christin Ann; Hay, Joel W

2015-07-01

More research is needed on the health effects of marijuana use. Results of previous studies indicate that marijuana could alleviate certain factors of metabolic syndrome, such as obesity. Data on 6281 persons from National Health and Nutrition Examination Survey from 2005 to 2012 were used to estimate the effect of marijuana use on cardiometabolic risk factors. The reliability of ordinary least squares (OLS) regression models was tested by replacing marijuana use as the risk factor of interest with alcohol and carbohydrate consumption. Instrumental variable methods were used to account for the potential endogeneity of marijuana use. OLS models show lower fasting insulin, insulin resistance, body mass index, and waist circumference in users compared with nonusers. However, when alcohol and carbohydrate intake substitute for marijuana use in OLS models, similar metabolic benefits are estimated. The Durbin-Wu-Hausman tests provide evidence of endogeneity of marijuana use in OLS models, but instrumental variables models do not yield significant estimates for marijuana use. These findings challenge the robustness of OLS estimates of a positive relationship between marijuana use and fasting insulin, insulin resistance, body mass index, and waist circumference. Copyright © 2015 Elsevier Inc. All rights reserved.

Identifying the key factors in increasing recycling and reducing residual household waste: a case study of the Flemish region of Belgium.

PubMed

Gellynck, X; Jacobsen, R; Verhelst, P

2011-10-01

The competent waste authority in the Flemish region of Belgium created the 'Implementation plan household waste 2003-2007' and the 'Implementation plan sustainable management 2010-2015' to comply with EU regulation. It incorporates European and regional requirements and describes strategies, goals, actions and instruments for the collection and treatment of household waste. The central mandatory goal is to reduce and maintain the amount of residual household waste to 150 kg per capita per year between 2010-2015. In literature, a reasonable body of information has been published on the effectiveness and efficiency of a variety of policy instruments, but the information is complex, often contradictory and difficult to interpret. The objective of this paper is to identify, through the development of a binary logistic regression model, those variables of the waste collection scheme that help municipalities to reach the mandatory 150 kg goal. The model covers a number of variables for household characteristics, provision of recycling services, frequency of waste collection and charging for waste services. This paper, however, is not about waste prevention and reuse. The dataset originates from 2003. Four out of 12 variables in the model contributed significantly: income per capita, cost of residual waste collection, collection frequency and separate curbside collection of organic waste. Copyright © 2011 Elsevier Ltd. All rights reserved.

A 507-year rainfall and runoff reconstruction for the Monsoonal North West, Australia derived from remote paleoclimate archives

NASA Astrophysics Data System (ADS)

Verdon-Kidd, Danielle C.; Hancock, Gregory R.; Lowry, John B.

2017-11-01

The Monsoonal North West (MNW) region of Australia faces a number of challenges adapting to anthropogenic climate change. These have the potential to impact on a range of industries, including agricultural, pastoral, mining and tourism. However future changes to rainfall regimes remain uncertain due to the inability of Global Climate Models to adequately capture the tropical weather/climate processes that are known to be important for this region. Compounding this is the brevity of the instrumental rainfall record for the MNW, which is unlikely to represent the full range of climatic variability. One avenue for addressing this issue (the focus of this paper) is to identify sources of paleoclimate information that can be used to reconstruct a plausible pre-instrumental rainfall history for the MNW. Adopting this approach we find that, even in the absence of local sources of paleoclimate data at a suitable temporal resolution, remote paleoclimate records can resolve 25% of the annual variability observed in the instrumental rainfall record. Importantly, the 507-year rainfall reconstruction developed using the remote proxies displays longer and more intense wet and dry periods than observed during the most recent 100 years. For example, the maximum number of consecutive years of below (above) average rainfall is 90% (40%) higher in the rainfall reconstruction than during the instrumental period. Further, implications for flood and drought risk are studied via a simple GR1A rainfall runoff model, which again highlights the likelihood of extremes greater than that observed in the limited instrumental record, consistent with previous paleoclimate studies elsewhere in Australia. Importantly, this research can assist in informing climate related risks to infrastructure, agriculture and mining, and the method can readily be applied to other regions in the MNW and beyond.

An Instrumental Variable Probit (IVP) analysis on depressed mood in Korea: the impact of gender differences and other socio-economic factors.

PubMed

Gitto, Lara; Noh, Yong-Hwan; Andrés, Antonio Rodríguez

2015-04-16

Depression is a mental health state whose frequency has been increasing in modern societies. It imposes a great burden, because of the strong impact on people's quality of life and happiness. Depression can be reliably diagnosed and treated in primary care: if more people could get effective treatments earlier, the costs related to depression would be reversed. The aim of this study was to examine the influence of socio-economic factors and gender on depressed mood, focusing on Korea. In fact, in spite of the great amount of empirical studies carried out for other countries, few epidemiological studies have examined the socio-economic determinants of depression in Korea and they were either limited to samples of employed women or did not control for individual health status. Moreover, as the likely data endogeneity (i.e. the possibility of correlation between the dependent variable and the error term as a result of autocorrelation or simultaneity, such as, in this case, the depressed mood due to health factors that, in turn might be caused by depression), might bias the results, the present study proposes an empirical approach, based on instrumental variables, to deal with this problem. Data for the year 2008 from the Korea National Health and Nutrition Examination Survey (KNHANES) were employed. About seven thousands of people (N= 6,751, of which 43% were males and 57% females), aged from 19 to 75 years old, were included in the sample considered in the analysis. In order to take into account the possible endogeneity of some explanatory variables, two Instrumental Variables Probit (IVP) regressions were estimated; the variables for which instrumental equations were estimated were related to the participation of women to the workforce and to good health, as reported by people in the sample. Explanatory variables were related to age, gender, family factors (such as the number of family members and marital status) and socio-economic factors (such as education, residence in metropolitan areas, and so on). As the results of the Wald test carried out after the estimations did not allow to reject the null hypothesis of endogeneity, a probit model was run too. Overall, women tend to develop depression more frequently than men. There is an inverse effect of education on depressed mood (probability of -24.6% to report a depressed mood due to high school education, as it emerges from the probit model marginal effects), while marital status and the number of family members may act as protective factors (probability to report a depressed mood of -1.0% for each family member). Depression is significantly associated with socio-economic conditions, such as work and income. Living in metropolitan areas is inversely correlated with depression (probability of -4.1% to report a depressed mood estimated through the probit model): this could be explained considering that, in rural areas, people rarely have immediate access to high-quality health services. This study outlines the factors that are more likely to impact on depression, and applies an IVP model to take into account the potential endogeneity of some of the predictors of depressive mood, such as female participation to workforce and health status. A probit model has been estimated too. Depression is associated with a wide range of socio-economic factors, although the strength and direction of the association can differ by gender. Prevention approaches to contrast depressive symptoms might take into consideration the evidence offered by the present study. © 2015 by Kerman University of Medical Sciences.

An Instrumental Variable Probit (IVP) analysis on depressed mood in Korea: the impact of gender differences and other socio-economic factors

PubMed Central

Gitto, Lara; Noh, Yong-Hwan; Andrés, Antonio Rodríguez

2015-01-01

Background: Depression is a mental health state whose frequency has been increasing in modern societies. It imposes a great burden, because of the strong impact on people’s quality of life and happiness. Depression can be reliably diagnosed and treated in primary care: if more people could get effective treatments earlier, the costs related to depression would be reversed. The aim of this study was to examine the influence of socio-economic factors and gender on depressed mood, focusing on Korea. In fact, in spite of the great amount of empirical studies carried out for other countries, few epidemiological studies have examined the socio-economic determinants of depression in Korea and they were either limited to samples of employed women or did not control for individual health status. Moreover, as the likely data endogeneity (i.e. the possibility of correlation between the dependent variable and the error term as a result of autocorrelation or simultaneity, such as, in this case, the depressed mood due to health factors that, in turn might be caused by depression), might bias the results, the present study proposes an empirical approach, based on instrumental variables, to deal with this problem. Methods: Data for the year 2008 from the Korea National Health and Nutrition Examination Survey (KNHANES) were employed. About seven thousands of people (N= 6,751, of which 43% were males and 57% females), aged from 19 to 75 years old, were included in the sample considered in the analysis. In order to take into account the possible endogeneity of some explanatory variables, two Instrumental Variables Probit (IVP) regressions were estimated; the variables for which instrumental equations were estimated were related to the participation of women to the workforce and to good health, as reported by people in the sample. Explanatory variables were related to age, gender, family factors (such as the number of family members and marital status) and socio-economic factors (such as education, residence in metropolitan areas, and so on). As the results of the Wald test carried out after the estimations did not allow to reject the null hypothesis of endogeneity, a probit model was run too. Results: Overall, women tend to develop depression more frequently than men. There is an inverse effect of education on depressed mood (probability of -24.6% to report a depressed mood due to high school education, as it emerges from the probit model marginal effects), while marital status and the number of family members may act as protective factors (probability to report a depressed mood of -1.0% for each family member). Depression is significantly associated with socio-economic conditions, such as work and income. Living in metropolitan areas is inversely correlated with depression (probability of -4.1% to report a depressed mood estimated through the probit model): this could be explained considering that, in rural areas, people rarely have immediate access to high-quality health services. Conclusion: This study outlines the factors that are more likely to impact on depression, and applies an IVP model to take into account the potential endogeneity of some of the predictors of depressive mood, such as female participation to workforce and health status. A probit model has been estimated too. Depression is associated with a wide range of socio-economic factors, although the strength and direction of the association can differ by gender. Prevention approaches to contrast depressive symptoms might take into consideration the evidence offered by the present study. PMID:26340392

Financial Crisis: A New Measure for Risk of Pension Fund Portfolios

PubMed Central

Cadoni, Marinella; Melis, Roberta; Trudda, Alessandro

2015-01-01

It has been argued that pension funds should have limitations on their asset allocation, based on the risk profile of the different financial instruments available on the financial markets. This issue proves to be highly relevant at times of market crisis, when a regulation establishing limits to risk taking for pension funds could prevent defaults. In this paper we present a framework for evaluating the risk level of a single financial instrument or a portfolio. By assuming that the log asset returns can be described by a multifractional Brownian motion, we evaluate the risk using the time dependent Hurst parameter H(t) which models volatility. To provide a measure of the risk, we model the Hurst parameter with a random variable with mixture of beta distribution. We prove the efficacy of the methodology by implementing it on different risk level financial instruments and portfolios. PMID:26086529

Financial Crisis: A New Measure for Risk of Pension Fund Portfolios.

PubMed

Cadoni, Marinella; Melis, Roberta; Trudda, Alessandro

2015-01-01

It has been argued that pension funds should have limitations on their asset allocation, based on the risk profile of the different financial instruments available on the financial markets. This issue proves to be highly relevant at times of market crisis, when a regulation establishing limits to risk taking for pension funds could prevent defaults. In this paper we present a framework for evaluating the risk level of a single financial instrument or a portfolio. By assuming that the log asset returns can be described by a multifractional Brownian motion, we evaluate the risk using the time dependent Hurst parameter H(t) which models volatility. To provide a measure of the risk, we model the Hurst parameter with a random variable with mixture of beta distribution. We prove the efficacy of the methodology by implementing it on different risk level financial instruments and portfolios.

Characterization and Prediction of the SPI Background

NASA Technical Reports Server (NTRS)

Teegarden, B. J.; Jean, P.; Knodlseder, J.; Skinner, G. K.; Weidenspointer, G.

2003-01-01

The INTEGRAL Spectrometer, like most gamma-ray instruments, is background dominated. Signal-to-background ratios of a few percent are typical. The background is primarily due to interactions of cosmic rays in the instrument and spacecraft. It characteristically varies by +/- 5% on time scales of days. This variation is caused mainly by fluctuations in the interplanetary magnetic field that modulates the cosmic ray intensity. To achieve the maximum performance from SPI it is essential to have a high quality model of this background that can predict its value to a fraction of a percent. In this poster we characterize the background and its variability, explore various models, and evaluate the accuracy of their predictions.

The Investigation of Laparoscopic Instrument Movement Control and Learning Effect

PubMed Central

Lin, Chiuhsiang Joe

2013-01-01

Laparoscopic surgery avoids large incisions for intra-abdominal operations as required in conventional open surgery. Whereas the patient benefits from laparoscopic techniques, the surgeon encounters new difficulties that were not present during open surgery procedures. However, limited literature has been published in the essential movement characteristics such as magnification, amplitude, and angle. For this reason, the present study aims to investigate the essential movement characteristics of instrument manipulation via Fitts' task and to develop an instrument movement time predicting model. Ten right-handed subjects made discrete Fitts' pointing tasks using a laparoscopic trainer. The experimental results showed that there were significant differences between the three factors in movement time and in throughput. However, no significant differences were observed in the improvement rate for movement time and throughput between these three factors. As expected, the movement time was rather variable and affected markedly by direction to target. The conventional Fitts' law model was extended by incorporating a directional parameter into the model. The extended model was shown to better fit the data than the conventional model. These findings pointed to a design direction for the laparoscopic surgery training program, and the predictive model can be used to establish standards in the training procedure. PMID:23984348

Assessing the Contribution of Sea Surface Temperature and Salinity to Coral δ18O using a Weighted Forward Model

NASA Astrophysics Data System (ADS)

Horlick, K. A.; Thompson, D. M.; Anderson, D. M.

2015-12-01

The isotopic ratio of 16O/18O (δ18O) in coral carbonate skeletons is a robust, high-resolution proxy for sea surface temperature (SST) and sea surface salinity (SSS) variability predating the instrumental record. Although SST and δ18O-water (correlated to SSS) variability both contribute to the δ18O signal in the coral carbonate archive, the paucity and limited temporal span of SST and SSS instrumental observations limit the ability to differentiate respective SST and SSS contribution to each δ18O record. From instrumental datasets such as HadISST v.3, ERSST, SODA, and Delcroix (2011), we forward model the δ18O ("pseudoproxy") signal using the linear bivariate forward model from Thompson 2011 ("pseudoproxy"= a1(SST)+a2(SSS)). By iteratively weighting (between 0 and 1 by 0.005) the relative contribution of SST and SSS terms to the δ18O "pseudoproxy" following Gorman et al. 2012 method, we derive the percent contributions of SST and SSS to δ18O at each site based on the weights that produce the optimal correlation to the observed coral δ18O signal. A Monte Carlo analysis of error propagation in the weighted and unweighted pseudoproxy time series was used to determine how well the weighted and unweighted forward models captured observed δ18O variance. Across the south-western Pacific (40 sites) we found that SST contributes from less than 8 to more than 78% of the variance. This work builds upon this simple forward model of coral δ18O and improves our understanding of potential sources of differences in the observed and forward modeled δ18O variability. These results may also improve SST and SSS reconstructions from corals by highlighting the reef areas whose coral δ18O signal is most heavily influenced by SST and SSS respectively. Using an inverse approach, creating a transfer function, local SST and SSS could also be reconstructed based on the site-specific weights and observed coral δ18O time series.

Blinded evaluation of interrater reliability of an operative competency assessment tool for direct laryngoscopy and rigid bronchoscopy.

PubMed

Ishman, Stacey L; Benke, James R; Johnson, Kaalan Erik; Zur, Karen B; Jacobs, Ian N; Thorne, Marc C; Brown, David J; Lin, Sandra Y; Bhatti, Nasir; Deutsch, Ellen S

2012-10-01

OBJECTIVES To confirm interrater reliability using blinded evaluation of a skills-assessment instrument to assess the surgical performance of resident and fellow trainees performing pediatric direct laryngoscopy and rigid bronchoscopy in simulated models. DESIGN Prospective, paired, blinded observational validation study. SUBJECTS Paired observers from multiple institutions simultaneously evaluated residents and fellows who were performing surgery in an animal laboratory or using high-fidelity manikins. The evaluators had no previous affiliation with the residents and fellows and did not know their year of training. INTERVENTIONS One- and 2-page versions of an objective structured assessment of technical skills (OSATS) assessment instrument composed of global and a task-specific surgical items were used to evaluate surgical performance. RESULTS Fifty-two evaluations were completed by 17 attending evaluators. The instrument agreement for the 2-page assessment was 71.4% when measured as a binary variable (ie, competent vs not competent) (κ = 0.38; P = .08). Evaluation as a continuous variable revealed a 42.9% percentage agreement (κ = 0.18; P = .14). The intraclass correlation was 0.53, considered substantial/good interrater reliability (69% reliable). For the 1-page instrument, agreement was 77.4% when measured as a binary variable (κ = 0.53, P = .0015). Agreement when evaluated as a continuous measure was 71.0% (κ = 0.54, P < .001). The intraclass correlation was 0.73, considered high interrater reliability (85% reliable). CONCLUSIONS The OSATS assessment instrument is an effective tool for evaluating surgical performance among trainees with acceptable interrater reliability in a simulator setting. Reliability was good for both the 1- and 2-page OSATS checklists, and both serve as excellent tools to provide immediate formative feedback on operational competency.

Modeling the Performance of Direct-Detection Doppler Lidar Systems in Real Atmospheres

NASA Technical Reports Server (NTRS)

McGill, Matthew J.; Hart, William D.; McKay, Jack A.; Spinhirne, James D.

1999-01-01

Previous modeling of the performance of spaceborne direct-detection Doppler lidar systems has assumed extremely idealized atmospheric models. Here we develop a technique for modeling the performance of these systems in a more realistic atmosphere, based on actual airborne lidar observations. The resulting atmospheric model contains cloud and aerosol variability that is absent in other simulations of spaceborne Doppler lidar instruments. To produce a realistic simulation of daytime performance, we include solar radiance values that are based on actual measurements and are allowed to vary as the viewing scene changes. Simulations are performed for two types of direct-detection Doppler lidar systems: the double-edge and the multi-channel techniques. Both systems were optimized to measure winds from Rayleigh backscatter at 355 nm. Simulations show that the measurement uncertainty during daytime is degraded by only about 10-20% compared to nighttime performance, provided a proper solar filter is included in the instrument design.

Using the Nobel Laureates in Economics to Teach Quantitative Methods

ERIC Educational Resources Information Center

Becker, William E.; Greene, William H.

2005-01-01

The authors show how the work of Nobel Laureates in economics can enhance student understanding and bring them up to date on topics such as probability, uncertainty and decision theory, hypothesis testing, regression to the mean, instrumental variable techniques, discrete choice modeling, and time-series analysis. (Contains 2 notes.)

Combining data visualization and statistical approaches for interpreting measurements and meta-data: Integrating heatmaps, variable clustering, and mixed regression models

EPA Science Inventory

The advent of new higher throughput analytical instrumentation has put a strain on interpreting and explaining the results from complex studies. Contemporary human, environmental, and biomonitoring data sets are comprised of tens or hundreds of analytes, multiple repeat measures...

Monthly paleostreamflow reconstruction from annual tree-ring chronologies

Treesearch

J. H. Stagge; D. E. Rosenberg; R. J. DeRose; T. M. Rittenour

2018-01-01

Paleoclimate reconstructions are increasingly used to characterize annual climate variability prior to the instrumental record, to improve estimates of climate extremes, and to provide a baseline for climate change projections. To date, paleoclimate records have seen limited engineering use to estimate hydrologic risks because water systems models and managers usually...

An Agitation Experiment with Multiple Aspects

ERIC Educational Resources Information Center

Spencer, Jordan L.

2006-01-01

This paper describes a multifaceted agitation and mixing experiment. The relatively inexpensive apparatus includes a variable-speed stirrer motor, two polycarbonate tanks, and an instrumented torque table. Students measure torque as a function of stirrer speed, and use conductive tracer data to estimate two parameters of a flow model. The effect…

Exploring the validity and reliability of a questionnaire for evaluating veterinary clinical teachers' supervisory skills during clinical rotations.

PubMed

Boerboom, T B B; Dolmans, D H J M; Jaarsma, A D C; Muijtjens, A M M; Van Beukelen, P; Scherpbier, A J J A

2011-01-01

Feedback to aid teachers in improving their teaching requires validated evaluation instruments. When implementing an evaluation instrument in a different context, it is important to collect validity evidence from multiple sources. We examined the validity and reliability of the Maastricht Clinical Teaching Questionnaire (MCTQ) as an instrument to evaluate individual clinical teachers during short clinical rotations in veterinary education. We examined four sources of validity evidence: (1) Content was examined based on theory of effective learning. (2) Response process was explored in a pilot study. (3) Internal structure was assessed by confirmatory factor analysis using 1086 student evaluations and reliability was examined utilizing generalizability analysis. (4) Relations with other relevant variables were examined by comparing factor scores with other outcomes. Content validity was supported by theory underlying the cognitive apprenticeship model on which the instrument is based. The pilot study resulted in an additional question about supervision time. A five-factor model showed a good fit with the data. Acceptable reliability was achievable with 10-12 questionnaires per teacher. Correlations between the factors and overall teacher judgement were strong. The MCTQ appears to be a valid and reliable instrument to evaluate clinical teachers' performance during short rotations.

Assessing the impact of obesity on labor market outcomes.

PubMed

Lindeboom, Maarten; Lundborg, Petter; van der Klaauw, Bas

2010-12-01

We study the effect of obesity on employment, using rich data from the British National Child Development Study (NCDS). The results show a significant negative association between obesity and employment even after controlling for a rich set of demographic, socioeconomic, environmental and behavioral variables. In order to account for the endogeneity of obesity, we use and assess instruments introduced by Cawley (2004); the obesity status of biological relatives. Using parental obesity as an instrument, we show that the association between obesity and employment is no longer significant. Similar results are obtained in a model of first differences. We provide a number of different checks on the instruments, by exploiting the richness of the NCDS data. The results show mixed evidence regarding the validity of the instruments. Copyright © 2010 Elsevier B.V. All rights reserved.

Trends and variability in the Hadley circulation over the Last Millennium from the proxy record

NASA Astrophysics Data System (ADS)

Horlick, K. A.; Noone, D.; Hakim, G. J.; Tardif, R.; Anderson, D. M.; Perkins, W. A.; Erb, M. P.; Steig, E. J.

2017-12-01

The Hadley circulation (HC) is the dominant atmospheric overturning circulation controlling variability in precipitation distribution in the tropics and subtropics, affecting agricultural production and water resource allocation, among other human civilizational dependencies. A lack of pre-instrumental data-model synthesis has been cited as the barrier to diagnostic analyses of the variability in width, position, and intensity of the HC and its response to anthropogenic forcing. We analyze the HC, and its rising limb associated with the Intertropical Convergence Zone (ITCZ), over the past 1000 years using the Last Millennium Reanalysis (LMR) (Hakim et al. 2016). The LMR systematically blends the dynamical constraints of climate models with a proxy network of coral, tree ring, and ice core records. It allows for a spatiotemporal analysis with robust uncertainty measures. A three dimensional analysis of LMR wind fields shows an centennial-scale circulatory trend over the last 200 years resembling that which might be expected from an ENSO and PDO-like structure. An observed aridification of both the central equatorial Pacific and the southwest United States, a strengthening of the east-west sea surface temperature and sea level pressure gradient in the equatorial Pacific, and a strengthening of the Walker overturning circulation suggest a more "La Niña-like" mean state. This is compared to our statistical description of the centennial-scale mean circulation and variability of the previous millennia. Similarly, precipitation and relative humidity trends suggest expansion and asymmetric meridional movement of the Hadley circulation as a result of asymmetric shifts in mean ITCZ position and intensity. These observations are then compared to free running model simulations, other instrumental reanalysis products, and late-Holocene aerosol, solar, and greenhouse forcings. This LMR reconstruction improves upon previous work by enabling a proxy-consistent, quantitative analysis of Hadley circulation intensity, structure, and variability rather than relying on simpler empirical reconstructions of variables like surface temperature alone.

Determining the Attitudes of Undergraduate Students Having Vocational Music Education towards Individual Instrument Course According to Different Variables

ERIC Educational Resources Information Center

Uluçay, Taner

2017-01-01

This study was carried out in order to determine attitudes of undergraduate students who studied music vocationally towards the individual instrument course according to the variables of grade, gender, individual instrument and graduated high school type. The research data were obtained from 102 undergraduate students studying in Erzincan…

Geostatistical Analysis of Mesoscale Spatial Variability and Error in SeaWiFS and MODIS/Aqua Global Ocean Color Data

NASA Astrophysics Data System (ADS)

Glover, David M.; Doney, Scott C.; Oestreich, William K.; Tullo, Alisdair W.

2018-01-01

Mesoscale (10-300 km, weeks to months) physical variability strongly modulates the structure and dynamics of planktonic marine ecosystems via both turbulent advection and environmental impacts upon biological rates. Using structure function analysis (geostatistics), we quantify the mesoscale biological signals within global 13 year SeaWiFS (1998-2010) and 8 year MODIS/Aqua (2003-2010) chlorophyll a ocean color data (Level-3, 9 km resolution). We present geographical distributions, seasonality, and interannual variability of key geostatistical parameters: unresolved variability or noise, resolved variability, and spatial range. Resolved variability is nearly identical for both instruments, indicating that geostatistical techniques isolate a robust measure of biophysical mesoscale variability largely independent of measurement platform. In contrast, unresolved variability in MODIS/Aqua is substantially lower than in SeaWiFS, especially in oligotrophic waters where previous analysis identified a problem for the SeaWiFS instrument likely due to sensor noise characteristics. Both records exhibit a statistically significant relationship between resolved mesoscale variability and the low-pass filtered chlorophyll field horizontal gradient magnitude, consistent with physical stirring acting on large-scale gradient as an important factor supporting observed mesoscale variability. Comparable horizontal length scales for variability are found from tracer-based scaling arguments and geostatistical decorrelation. Regional variations between these length scales may reflect scale dependence of biological mechanisms that also create variability directly at the mesoscale, for example, enhanced net phytoplankton growth in coastal and frontal upwelling and convective mixing regions. Global estimates of mesoscale biophysical variability provide an improved basis for evaluating higher resolution, coupled ecosystem-ocean general circulation models, and data assimilation.

Capacity of dental equipment to interfere with cardiac implantable electrical devices.

PubMed

Lahor-Soler, Eduard; Miranda-Rius, Jaume; Brunet-Llobet, Lluís; Sabaté de la Cruz, Xavier

2015-06-01

Patients with cardiac implantable electrical devices should take precautions when exposed to electromagnetic fields. Possible interference as a result of proximity to electromagnets or electricity flow from electronic tools employed in clinical odontology remains controversial. The objective of this study was to examine in vitro the capacity of dental equipment to provoke electromagnetic interference in pacemakers and implantable cardioverter defibrillators. Six electronic dental instruments were tested on three implantable cardioverter defibrillators and three pacemakers from different manufacturers. A simulator model, submerged in physiological saline, with elements that reproduced life-size anatomic structures was used. The instruments were analyzed at differing distances and for different time periods of application. The dental instruments studied displayed significant differences in their capacity to trigger electromagnetic interference. Significant differences in the quantity of registered interference were observed with respect to the variables manufacturer, type of cardiac implant, and application distance but not with the variable time of application. The electronic dental equipment tested at a clinical application distance (20 cm) provoked only slight interference in the pacemakers and implantable cardioverter defibrillators employed, irrespective of manufacturer. © 2015 Eur J Oral Sci.

Ontology and modeling patterns for state-based behavior representation

NASA Technical Reports Server (NTRS)

Castet, Jean-Francois; Rozek, Matthew L.; Ingham, Michel D.; Rouquette, Nicolas F.; Chung, Seung H.; Kerzhner, Aleksandr A.; Donahue, Kenneth M.; Jenkins, J. Steven; Wagner, David A.; Dvorak, Daniel L.;

Variability of the Denmark Strait overflow: Moored time series from 1996-2011

NASA Astrophysics Data System (ADS)

Jochumsen, Kerstin; Quadfasel, Detlef; Valdimarsson, Heã°Inn; Jónsson, SteingríMur

2012-12-01

The Denmark Strait overflow provides about half of the total dense water overflow from the Nordic Seas into the North Atlantic Ocean. The velocity of the overflow has been monitored in the Strait with two moored Acoustic Doppler Current Profilers since 1996 with several interruptions due to mooring losses or instrument failure. So far, overflow transports were only calculated when data from both moorings were available. In this work, we introduce a linear model to fill gaps in the time series when data from only one instrument is available. The mean overflow transport is 3.4 Sv and exhibits a variance of 2.0 Sv2. No significant trend was detected in the time series. The highest variability in the transport is associated with the passage of mesoscale eddies with time scales of 2-10 days (associated with a variance of 1.5 Sv2). Seasonal variability is weak and explains less than 5% of the variance in all time series, which is in contrast to the strong seasonal cycle found in high resolution model simulations. Interannual variability is on the order of 10% of the mean. A relation to atmospheric forcing such as the local wind stress curl, as well as to larger scale phenomena, e.g. the North Atlantic Oscillation, is not detected. Since 2005 data from moored temperature, conductivity and pressure recorders have been available as well, monitoring the hydrographic variability at the bottom of Denmark Strait. In recent years the temperature time series of the Denmark Strait overflow revealed a cooling, while the salinity stayed nearly constant.

Use of instrumental variables in the analysis of generalized linear models in the presence of unmeasured confounding with applications to epidemiological research.

PubMed

Johnston, K M; Gustafson, P; Levy, A R; Grootendorst, P

2008-04-30

A major, often unstated, concern of researchers carrying out epidemiological studies of medical therapy is the potential impact on validity if estimates of treatment are biased due to unmeasured confounders. One technique for obtaining consistent estimates of treatment effects in the presence of unmeasured confounders is instrumental variables analysis (IVA). This technique has been well developed in the econometrics literature and is being increasingly used in epidemiological studies. However, the approach to IVA that is most commonly used in such studies is based on linear models, while many epidemiological applications make use of non-linear models, specifically generalized linear models (GLMs) such as logistic or Poisson regression. Here we present a simple method for applying IVA within the class of GLMs using the generalized method of moments approach. We explore some of the theoretical properties of the method and illustrate its use within both a simulation example and an epidemiological study where unmeasured confounding is suspected to be present. We estimate the effects of beta-blocker therapy on one-year all-cause mortality after an incident hospitalization for heart failure, in the absence of data describing disease severity, which is believed to be a confounder. 2008 John Wiley & Sons, Ltd

Instrumental variables and Mendelian randomization with invalid instruments

NASA Astrophysics Data System (ADS)

Kang, Hyunseung

Instrumental variables (IV) methods have been widely used to determine the causal effect of a treatment, exposure, policy, or an intervention on an outcome of interest. The IV method relies on having a valid instrument, a variable that is (A1) associated with the exposure, (A2) has no direct effect on the outcome, and (A3) is unrelated to the unmeasured confounders associated with the exposure and the outcome. However, in practice, finding a valid instrument, especially those that satisfy (A2) and (A3), can be challenging. For example, in Mendelian randomization studies where genetic markers are used as instruments, complete knowledge about instruments' validity is equivalent to complete knowledge about the involved genes' functions. The dissertation explores the theory, methods, and application of IV methods when invalid instruments are present. First, when we have multiple candidate instruments, we establish a theoretical bound whereby causal effects are only identified as long as less than 50% of instruments are invalid, without knowing which of the instruments are invalid. We also propose a fast penalized method, called sisVIVE, to estimate the causal effect. We find that sisVIVE outperforms traditional IV methods when invalid instruments are present both in simulation studies as well as in real data analysis. Second, we propose a robust confidence interval under the multiple invalid IV setting. This work is an extension of our work on sisVIVE. However, unlike sisVIVE which is robust to violations of (A2) and (A3), our confidence interval procedure provides honest coverage even if all three assumptions, (A1)-(A3), are violated. Third, we study the single IV setting where the one IV we have may actually be invalid. We propose a nonparametric IV estimation method based on full matching, a technique popular in causal inference for observational data, that leverages observed covariates to make the instrument more valid. We propose an estimator along with inferential results that are robust to mis-specifications of the covariate-outcome model. We also provide a sensitivity analysis should the instrument turn out to be invalid, specifically violate (A3). Fourth, in application work, we study the causal effect of malaria on stunting among children in Ghana. Previous studies on the effect of malaria and stunting were observational and contained various unobserved confounders, most notably nutritional deficiencies. To infer causality, we use the sickle cell genotype, a trait that confers some protection against malaria and was randomly assigned at birth, as an IV and apply our nonparametric IV method. We find that the risk of stunting increases by 0.22 (95% CI: 0.044,1) for every malaria episode and is sensitive to unmeasured confounders.

Leveraging Observation Tools for Instructional Improvement: Exploring Variability in Uptake of Ambitious Instructional Practices

ERIC Educational Resources Information Center

Cohen, Julie; Schuldt, Lorien Chambers; Brown, Lindsay; Grossman, Pamela

2016-01-01

Background/Context: Current efforts to build rigorous teacher evaluation systems has increased interest in standardized classroom observation tools as reliable measures for assessing teaching. However, many argue these instruments can also be used to effect change in classroom practice. This study investigates a model of professional development…

Cosmological Distance Scale to Gamma-Ray Bursts

NASA Astrophysics Data System (ADS)

Azzam, W. J.; Linder, E. V.; Petrosian, V.

1993-05-01

The source counts or the so-called log N -- log S relations are the primary data that constrain the spatial distribution of sources with unknown distances, such as gamma-ray bursts. In order to test galactic, halo, and cosmological models for gamma-ray bursts we compare theoretical characteristics of the log N -- log S relations to those obtained from data gathered by the BATSE instrument on board the Compton Observatory (GRO) and other instruments. We use a new and statistically correct method, that takes proper account of the variable nature of the triggering threshold, to analyze the data. Constraints on models obtained by this comparison will be presented. This work is supported by NASA grants NAGW 2290, NAG5 2036, and NAG5 1578.

An Explanatory Model of Self-Service on the Internet

NASA Astrophysics Data System (ADS)

Oliver, Dave; Livermore, Celia Romm; Farag, Neveen Awad

This chapter describes research that identifies and classifies the dimensions of self-service activity enabled through the Internet. Self-service is effected by organizations providing ways and means whereby customers perform tasks related to the procurement of goods and services. We describe how an instrument used to measure Internet-based self-service was developed, validated and applied. The results from applying the instrument to a large number of Web sites, covering a range of industries, countries and cultures, are analyzed and discussed. The study presents a model in which type of industry, level of technological development, income and cultural factors are proposed as explanatory variables for Web-based self-service. We conclude with an assessment of this program of research’s achievements so far.

Econometrics in outcomes research: the use of instrumental variables.

PubMed

Newhouse, J P; McClellan, M

1998-01-01

We describe an econometric technique, instrumental variables, that can be useful in estimating the effectiveness of clinical treatments in situations when a controlled trial has not or cannot be done. This technique relies upon the existence of one or more variables that induce substantial variation in the treatment variable but have no direct effect on the outcome variable of interest. We illustrate the use of the technique with an application to aggressive treatment of acute myocardial infarction in the elderly.

Secular temperature trends for the southern Rocky Mountains over the last five centuries

NASA Astrophysics Data System (ADS)

Berkelhammer, M.; Stott, L. D.

2012-09-01

Pre-instrumental surface temperature variability in the Southwestern United States has traditionally been reconstructed using variations in the annual ring widths of high altitude trees that live near a growth-limiting isotherm. A number of studies have suggested that the response of some trees to temperature variations is non-stationary, warranting the development of alternative approaches towards reconstructing past regional temperature variability. Here we present a five-century temperature reconstruction for a high-altitude site in the Rocky Mountains derived from the oxygen isotopic composition of cellulose (δ18Oc) from Bristlecone Pine trees. The record is independent of the co-located growth-based reconstruction while providing the same temporal resolution and absolute age constraints. The empirical correlation between δ18Oc and instrumental temperatures is used to produce a temperature transfer function. A forward-model for cellulose isotope variations, driven by meteorological data and output from an isotope-enabled General Circulation Model, is used to evaluate the processes that propagate the temperature signal to the proxy. The cellulose record documents persistent multidecadal variations in δ18Oc that are attributable to temperature shifts on the order of 1°C but no sustained monotonic rise in temperature or a step-like increase since the late 19th century. The isotope-based temperature history is consistent with both regional wood density-based temperature estimates and some sparse early instrumental records.

Empowerment variables for rehabilitation clients on perceived beliefs concerning work quality of life domains.

PubMed

Tschopp, Molly K; Frain, Michael P; Bishop, Malachy

2009-01-01

This article describes and presents an initial analysis of variables generally associated with empowerment towards perceived beliefs concerning quality of life work domains for individuals with disabilities. The model examines the domains of importance, satisfaction, control and degree of interference of disability that an individual feels towards work. The internet based study used results from 70 individuals with disabilities in varying aspects of work. The variables composing empowerment that correlated strongly with the work domains include: self-advocacy, self-efficacy, perceived stigma, and family resiliency as measured through coping. Quality of Life concerning work was measured through the DSC-C a domain specific QOL instrument.

Update on the NASA GEOS-5 Aerosol Forecasting and Data Assimilation System

NASA Technical Reports Server (NTRS)

Colarco, Peter; da Silva, Arlindo; Aquila, Valentina; Bian, Huisheng; Buchard, Virginie; Castellanos, Patricia; Darmenov, Anton; Follette-Cook, Melanie; Govindaraju, Ravi; Keller, Christoph;

MAVEN Pickup Ion Constraints on Mars Neutral Escape

NASA Astrophysics Data System (ADS)

Rahmati, A.; Larson, D. E.; Cravens, T.; Lillis, R. J.; Dunn, P.; Halekas, J. S.; McFadden, J. P.; Mitchell, D. L.; Thiemann, E.; Connerney, J. E. P.; DiBraccio, G. A.; Espley, J. R.; Eparvier, F. G.

2017-12-01

Mars is currently losing its atmosphere mainly due to the escape of neutral hydrogen and oxygen. Directly measuring the rate of escaping neutrals is difficult, because the neutral density in the Mars exosphere is dominated, up to several Martian radii, by atoms that are gravitationally bound to the planet. Neutral atoms in the Martian exosphere, however, can get ionized, picked up, and accelerated by the solar wind motional electric field and energized to energies high enough for particle detectors to measure them. The MAVEN SEP instrument detects O+ pickup ions that are created at altitudes where the escaping part of the exosphere is dominant. Fluxes of these ions reflect neutral densities in the distant exosphere of Mars, allowing us to constrain neutral oxygen escape rates. The MAVEN SWIA and STATIC instruments measure pickup H+ and O+ created closer to Mars; comparisons of these data with models can be used to constrain exospheric hot O and thermal H densities and escape rates. In this work, pickup ion measurements from SEP, SWIA, and STATIC, taken during the first 3 Earth years of the MAVEN mission, are compared to the outputs of a pickup ion model to constrain the variability of neutral escape at Mars. The model is based on data from six MAVEN instruments, namely, MAG providing magnetic field used in calculating pickup ion trajectories, SWIA providing solar wind velocity as well as 3D pickup H+ and O+ spectra, SWEA providing solar wind electron spectrum used in electron impact ionization rate calculations, SEP providing pickup O+ spectra, STATIC providing mass resolved 3D pickup H+ and O+ spectra, and EUVM providing solar EUV spectra used in photoionization rate calculations. A variability of less than a factor of two is observed in hot oxygen escape rates, whereas thermal escape of hydrogen varies by an order of magnitude with Mars season. This hydrogen escape variability challenges our understanding of the H cycle at Mars, but is consistent with other recent measurements.

Developing and validating a measure of community capacity: Why volunteers make the best neighbours.

PubMed

Lovell, Sarah A; Gray, Andrew R; Boucher, Sara E

2015-05-01

Social support and community connectedness are key determinants of both mental and physical wellbeing. While social capital has been used to indicate the instrumental value of these social relationships, its broad and often competing definitions have hindered practical applications of the concept. Within the health promotion field, the related concept of community capacity, the ability of a group to identify and act on problems, has gained prominence (Labonte and Laverack, 2001). The goal of this study was to develop and validate a scale measuring community capacity including exploring its associations with socio-demographic and civic behaviour variables among the residents of four small (populations 1500-2000) high-deprivation towns in southern New Zealand. The full (41-item) scale was found to have strong internal consistency (Cronbach's alpha = 0.89) but a process of reducing the scale resulted in a shorter 26-item instrument with similar internal consistency (alpha 0.88). Subscales of the reduced instrument displayed at least marginally acceptable levels of internal consistency (0.62-0.77). Using linear regression models, differences in community capacity scores were found for selected criterion, namely time spent living in the location, local voting, and volunteering behaviour, although the first of these was no longer statistically significant in an adjusted model with potential confounders including age, sex, ethnicity, education, marital status, employment, household income, and religious beliefs. This provides support for the scale's concurrent validity. Differences were present between the four towns in unadjusted models and remained statistically significant in adjusted models (including variables mentioned above) suggesting, crucially, that even when such factors are accounted for, perceptions of one's community may still depend on place. Copyright © 2014. Published by Elsevier Ltd.

Assembling Large, Multi-Sensor Climate Datasets Using the SciFlo Grid Workflow System

NASA Astrophysics Data System (ADS)

Wilson, B. D.; Manipon, G.; Xing, Z.; Fetzer, E.

2008-12-01

NASA's Earth Observing System (EOS) is the world's most ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the A-Train platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over periods of years to decades. However, moving from predominantly single-instrument studies to a multi-sensor, measurement-based model for long-duration analysis of important climate variables presents serious challenges for large-scale data mining and data fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another instrument (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the cloud scenes from CloudSat, and repeat the entire analysis over years of AIRS data. To perform such an analysis, one must discover & access multiple datasets from remote sites, find the space/time matchups between instruments swaths and model grids, understand the quality flags and uncertainties for retrieved physical variables, and assemble merged datasets for further scientific and statistical analysis. To meet these large-scale challenges, we are utilizing a Grid computing and dataflow framework, named SciFlo, in which we are deploying a set of versatile and reusable operators for data query, access, subsetting, co-registration, mining, fusion, and advanced statistical analysis. SciFlo is a semantically-enabled ("smart") Grid Workflow system that ties together a peer-to-peer network of computers into an efficient engine for distributed computation. The SciFlo workflow engine enables scientists to do multi-instrument Earth Science by assembling remotely-invokable Web Services (SOAP or http GET URLs), native executables, command-line scripts, and Python codes into a distributed computing flow. A scientist visually authors the graph of operation in the VizFlow GUI, or uses a text editor to modify the simple XML workflow documents. The SciFlo client & server engines optimize the execution of such distributed workflows and allow the user to transparently find and use datasets and operators without worrying about the actual location of the Grid resources. The engine transparently moves data to the operators, and moves operators to the data (on the dozen trusted SciFlo nodes). SciFlo also deploys a variety of Data Grid services to: query datasets in space and time, locate & retrieve on-line data granules, provide on-the-fly variable and spatial subsetting, and perform pairwise instrument matchups for A-Train datasets. These services are combined into efficient workflows to assemble the desired large-scale, merged climate datasets. SciFlo is currently being applied in several large climate studies: comparisons of aerosol optical depth between MODIS, MISR, AERONET ground network, and U. Michigan's IMPACT aerosol transport model; characterization of long-term biases in microwave and infrared instruments (AIRS, MLS) by comparisons to GPS temperature retrievals accurate to 0.1 degrees Kelvin; and construction of a decade-long, multi-sensor water vapor climatology stratified by classified cloud scene by bringing together datasets from AIRS/AMSU, AMSR-E, MLS, MODIS, and CloudSat (NASA MEASUREs grant, Fetzer PI). The presentation will discuss the SciFlo technologies, their application in these distributed workflows, and the many challenges encountered in assembling and analyzing these massive datasets.

Assembling Large, Multi-Sensor Climate Datasets Using the SciFlo Grid Workflow System

NASA Astrophysics Data System (ADS)

Wilson, B.; Manipon, G.; Xing, Z.; Fetzer, E.

2009-04-01

NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over periods of years to decades. However, moving from predominantly single-instrument studies to a multi-sensor, measurement-based model for long-duration analysis of important climate variables presents serious challenges for large-scale data mining and data fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another instrument (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over years of AIRS data. To perform such an analysis, one must discover & access multiple datasets from remote sites, find the space/time "matchups" between instruments swaths and model grids, understand the quality flags and uncertainties for retrieved physical variables, assemble merged datasets, and compute fused products for further scientific and statistical analysis. To meet these large-scale challenges, we are utilizing a Grid computing and dataflow framework, named SciFlo, in which we are deploying a set of versatile and reusable operators for data query, access, subsetting, co-registration, mining, fusion, and advanced statistical analysis. SciFlo is a semantically-enabled ("smart") Grid Workflow system that ties together a peer-to-peer network of computers into an efficient engine for distributed computation. The SciFlo workflow engine enables scientists to do multi-instrument Earth Science by assembling remotely-invokable Web Services (SOAP or http GET URLs), native executables, command-line scripts, and Python codes into a distributed computing flow. A scientist visually authors the graph of operation in the VizFlow GUI, or uses a text editor to modify the simple XML workflow documents. The SciFlo client & server engines optimize the execution of such distributed workflows and allow the user to transparently find and use datasets and operators without worrying about the actual location of the Grid resources. The engine transparently moves data to the operators, and moves operators to the data (on the dozen trusted SciFlo nodes). SciFlo also deploys a variety of Data Grid services to: query datasets in space and time, locate & retrieve on-line data granules, provide on-the-fly variable and spatial subsetting, perform pairwise instrument matchups for A-Train datasets, and compute fused products. These services are combined into efficient workflows to assemble the desired large-scale, merged climate datasets. SciFlo is currently being applied in several large climate studies: comparisons of aerosol optical depth between MODIS, MISR, AERONET ground network, and U. Michigan's IMPACT aerosol transport model; characterization of long-term biases in microwave and infrared instruments (AIRS, MLS) by comparisons to GPS temperature retrievals accurate to 0.1 degrees Kelvin; and construction of a decade-long, multi-sensor water vapor climatology stratified by classified cloud scene by bringing together datasets from AIRS/AMSU, AMSR-E, MLS, MODIS, and CloudSat (NASA MEASUREs grant, Fetzer PI). The presentation will discuss the SciFlo technologies, their application in these distributed workflows, and the many challenges encountered in assembling and analyzing these massive datasets.

Short version of the "instrument for assessment of stress in nursing students" in the Brazilian reality.

PubMed

Costa, Ana Lúcia Siqueira; Silva, Rodrigo Marques da; Mussi, Fernanda Carneiro; Serrano, Patrícia Maria; Graziano, Eliane da Silva; Batista, Karla de Melo

2018-01-08

validate a short version of the Instrument for assessment of stress in nursing students in the Brazilian reality. Methodological study conducted with 1047 nursing students from five Brazilian institutions, who answered the 30 items initially distributed in eight domains. Data were analyzed in the R Statistical Package and in the latent variable analysis, using exploratory and confirmatory factor analyses, Cronbach's alpha and item-total correlation. The short version of the instrument had 19 items distributed into four domains: Environment, Professional Training, Theoretical Activities and Performance of Practical Activities. The confirmatory analysis showed absolute and parsimony fit to the proposed model with satisfactory residual levels. Alpha values ​​per factor ranged from 0.736 (Environment) to 0.842 (Performance of Practical Activities). The short version of the instrument has construct validity and reliability for application to Brazilian nursing undergraduates at any stage of the course.

New insights on short-term solar irradiance forecast for space weather applications

NASA Astrophysics Data System (ADS)

Vieira, L. A.; Dudok de Wit, T.; Balmaceda, L. A.; Dal Lago, A.; Da Silva, L. A.; Gonzalez, W. D.

2013-12-01

The conditions of the thermosphere, the ionosphere, the neutral atmosphere, and the oceans on time scales from days to millennia are highly dependent on the solar electromagnetic output, the solar irradiance. The development of physics-based solar irradiance models during the last decade improved significantly our understanding of the solar forcing on Earth's climate. These models are based on the assumption that most of the solar irradiance variability is related to the magnetic field structure of the Sun. Recently, these models were extended to allow short-term forecast (1 to 15 days) of the total and spectral solar irradiance. The extension of the irradiance models is based on solar surface magnetic flux models and/or artificial neural network models. Here, we discuss in details the irradiance forecast models based on observations of the solar surface magnetic field realized by the HMI instrument on board of SDO spacecraft. We constrained and validated the models by comparing the output of the models and observations of the solar irradiance made by instruments onboard The SORCE spacecraft. This study received funding from the European Community's Seventh Framework Programme (FP7/2007-2013, FP7-SPACE-2010-1) under the grant agreement nrs. 218816 (SOTERIA project, www.soteria-space.eu) and 261948 (ATMOP,www.atmop.eu), and by the CNPq/Brazil under the grant number 312488/2012-2. We also gratefully thank the instrument teams for making their data available.

Influence of Strategy of Learning and Achievement Motivation of Learning Achievement Class VIII Students of State Junior High School in District Blitar

ERIC Educational Resources Information Center

Ayundawati, Dyah; Setyosari, Punaji; Susilo, Herawati; Sihkabuden

2016-01-01

This study aims for know influence of problem-based learning strategies and achievement motivation on learning achievement. The method used in this research is quantitative method. The instrument used in this study is two fold instruments to measure moderator variable (achievement motivation) and instruments to measure the dependent variable (the…

The PROactive instruments to measure physical activity in patients with chronic obstructive pulmonary disease

PubMed Central

Gimeno-Santos, Elena; Raste, Yogini; Demeyer, Heleen; Louvaris, Zafeiris; de Jong, Corina; Rabinovich, Roberto A.; Hopkinson, Nicholas S.; Polkey, Michael I.; Vogiatzis, Ioannis; Tabberer, Maggie; Dobbels, Fabienne; Ivanoff, Nathalie; de Boer, Willem I.; van der Molen, Thys; Kulich, Karoly; Serra, Ignasi; Basagaña, Xavier; Troosters, Thierry; Puhan, Milo A.; Karlsson, Niklas

2015-01-01

No current patient-centred instrument captures all dimensions of physical activity in chronic obstructive pulmonary disease (COPD). Our objective was item reduction and initial validation of two instruments to measure physical activity in COPD. Physical activity was assessed in a 6-week, randomised, two-way cross-over, multicentre study using PROactive draft questionnaires (daily and clinical visit versions) and two activity monitors. Item reduction followed an iterative process including classical and Rasch model analyses, and input from patients and clinical experts. 236 COPD patients from five European centres were included. Results indicated the concept of physical activity in COPD had two domains, labelled “amount” and “difficulty”. After item reduction, the daily PROactive instrument comprised nine items and the clinical visit contained 14. Both demonstrated good model fit (person separation index >0.7). Confirmatory factor analysis supported the bidimensional structure. Both instruments had good internal consistency (Cronbach's α>0.8), test–retest reliability (intraclass correlation coefficient ≥0.9) and exhibited moderate-to-high correlations (r>0.6) with related constructs and very low correlations (r<0.3) with unrelated constructs, providing evidence for construct validity. Daily and clinical visit “PROactive physical activity in COPD” instruments are hybrid tools combining a short patient-reported outcome questionnaire and two activity monitor variables which provide simple, valid and reliable measures of physical activity in COPD patients. PMID:26022965

The PROactive instruments to measure physical activity in patients with chronic obstructive pulmonary disease.

PubMed

Gimeno-Santos, Elena; Raste, Yogini; Demeyer, Heleen; Louvaris, Zafeiris; de Jong, Corina; Rabinovich, Roberto A; Hopkinson, Nicholas S; Polkey, Michael I; Vogiatzis, Ioannis; Tabberer, Maggie; Dobbels, Fabienne; Ivanoff, Nathalie; de Boer, Willem I; van der Molen, Thys; Kulich, Karoly; Serra, Ignasi; Basagaña, Xavier; Troosters, Thierry; Puhan, Milo A; Karlsson, Niklas; Garcia-Aymerich, Judith

2015-10-01

No current patient-centred instrument captures all dimensions of physical activity in chronic obstructive pulmonary disease (COPD). Our objective was item reduction and initial validation of two instruments to measure physical activity in COPD.Physical activity was assessed in a 6-week, randomised, two-way cross-over, multicentre study using PROactive draft questionnaires (daily and clinical visit versions) and two activity monitors. Item reduction followed an iterative process including classical and Rasch model analyses, and input from patients and clinical experts.236 COPD patients from five European centres were included. Results indicated the concept of physical activity in COPD had two domains, labelled "amount" and "difficulty". After item reduction, the daily PROactive instrument comprised nine items and the clinical visit contained 14. Both demonstrated good model fit (person separation index >0.7). Confirmatory factor analysis supported the bidimensional structure. Both instruments had good internal consistency (Cronbach's α>0.8), test-retest reliability (intraclass correlation coefficient ≥0.9) and exhibited moderate-to-high correlations (r>0.6) with related constructs and very low correlations (r<0.3) with unrelated constructs, providing evidence for construct validity.Daily and clinical visit "PROactive physical activity in COPD" instruments are hybrid tools combining a short patient-reported outcome questionnaire and two activity monitor variables which provide simple, valid and reliable measures of physical activity in COPD patients. Copyright ©ERS 2015.

Gamma-ray emission from Cataclysmic variables. 1: The Compton EGRET survey

NASA Technical Reports Server (NTRS)

Schlegel, Eric M.; Barrett, Paul E.; De Jager, O. C.; Chanmugam, G.; Hunter, S.; Mattox, J.

1995-01-01

We report the results of the first gamma-ray survey of cataclysmic variables (CVs) using observations obtained with the Energetic Gamma Ray Experiment Telescope (EGRET) instrument on the Compton Observatory. We briefly describe the theoretical models that are applicable to gamma-ray emission from CVs. These models are particularly relevant to magnetic CVs containing asynchronously rotating white dwarfs. No magnetic CV was detected with an upper limit on the flux at 1 GeV of approximately 2 x 10(exp -8)/sq cm/sec, which corresponds to an upper limit on the gamma-ray luminosity of approximately 10(exp 31) ergs/sec, assuming a typical CV distance of 100 pc.

Bias and Bias Correction in Multisite Instrumental Variables Analysis of Heterogeneous Mediator Effects

ERIC Educational Resources Information Center

Reardon, Sean F.; Unlu, Fatih; Zhu, Pei; Bloom, Howard S.

2014-01-01

We explore the use of instrumental variables (IV) analysis with a multisite randomized trial to estimate the effect of a mediating variable on an outcome in cases where it can be assumed that the observed mediator is the only mechanism linking treatment assignment to outcomes, an assumption known in the IV literature as the exclusion restriction.…

The sound of oscillating air jets: Physics, modeling and simulation in flute-like instruments

NASA Astrophysics Data System (ADS)

de La Cuadra, Patricio

Flute-like instruments share a common mechanism that consists of blowing across one open end of a resonator to produce an air jet that is directed towards a sharp edge. Analysis of its operation involves various research fields including fluid dynamics, aero-acoustics, and physics. An effort has been made in this study to extend this description from instruments with fixed geometry like recorders and organ pipes to flutes played by the lips. An analysis of the jet's response to a periodic excitation is the focus of this study, as are the parameters under the player's control in forming the jet. The jet is excited with a controlled excitation consisting of two loudspeakers in opposite phase. A Schlieren system is used to visualize the jet, and image detection algorithms are developed to extract quantitative information from the images. In order to study the behavior of jets observed in different flute-like instruments, several geometries of the excitation and jet shapes are studied. The obtained data is used to propose analytical models that correctly fit the observed measurements and can be used for simulations. The control exerted by the performer on the instrument is of crucial importance in the quality of the sound produced for a number of flute-like instruments. The case of the transverse flute is experimentally studied. An ensemble of control parameters are measured and visualized in order to describe some aspects of the subtle control attained by an experienced flautist. Contrasting data from a novice flautist are compared. As a result, typical values for several non-dimensional parameters that characterize the normal operation of the instrument have been measured, and data to feed simulations has been collected. The information obtained through experimentation is combined with research developed over the last decades to put together a time-domain simulation. The model proposed is one-dimensional and driven by a single physical input. All the variables in the model are expressed in terms of pressure which allows for implementation and control in real-time. The model provides both a testbed to compare and validate measurements as well as a highly configurable and real-time musical instrument.

Parameter de-correlation and model-identification in hybrid-style terrestrial laser scanner self-calibration

NASA Astrophysics Data System (ADS)

Lichti, Derek D.; Chow, Jacky; Lahamy, Hervé

One of the important systematic error parameters identified in terrestrial laser scanners is the collimation axis error, which models the non-orthogonality between two instrumental axes. The quality of this parameter determined by self-calibration, as measured by its estimated precision and its correlation with the tertiary rotation angle κ of the scanner exterior orientation, is strongly dependent on instrument architecture. While the quality is generally very high for panoramic-type scanners, it is comparably poor for hybrid-style instruments. Two methods for improving the quality of the collimation axis error in hybrid instrument self-calibration are proposed herein: (1) the inclusion of independent observations of the tertiary rotation angle κ; and (2) the use of a new collimation axis error model. Five real datasets were captured with two different hybrid-style scanners to test each method's efficacy. While the first method achieves the desired outcome of complete decoupling of the collimation axis error from κ, it is shown that the high correlation is simply transferred to other model variables. The second method achieves partial parameter de-correlation to acceptable levels. Importantly, it does so without any adverse, secondary correlations and is therefore the method recommended for future use. Finally, systematic error model identification has been greatly aided in previous studies by graphical analyses of self-calibration residuals. This paper presents results showing the architecture dependence of this technique, revealing its limitations for hybrid scanners.

Diagnosing Students' Understanding of the Nature of Models

NASA Astrophysics Data System (ADS)

Gogolin, Sarah; Krüger, Dirk

2017-10-01

Students' understanding of models in science has been subject to a number of investigations. The instruments the researchers used are suitable for educational research but, due to their complexity, cannot be employed directly by teachers. This article presents forced choice (FC) tasks, which, assembled as a diagnostic instrument, are supposed to measure students' understanding of the nature of models efficiently, while being sensitive enough to detect differences between individuals. In order to evaluate if the diagnostic instrument is suitable for its intended use, we propose an approach that complies with the demand to integrate students' responses to the tasks into the validation process. Evidence for validity was gathered based on relations to other variables and on students' response processes. Students' understanding of the nature of models was assessed using three methods: FC tasks, open-ended tasks and interviews ( N = 448). Furthermore, concurrent think-aloud protocols ( N = 30) were performed. The results suggest that the method and the age of the students have an effect on their understanding of the nature of models. A good understanding of the FC tasks as well as a convergence in the findings across the three methods was documented for grades eleven and twelve. This indicates that teachers can use the diagnostic instrument for an efficient and, at the same time, valid diagnosis for this group. Finally, the findings of this article may provide a possible explanation for alternative findings from previous studies as a result of specific methods that were used.

Mechanisms for the Association between Maternal Employment and Child Cognitive Development. NBER Working Paper No. 13609

ERIC Educational Resources Information Center

Cawley, John; Liu, Feng

2007-01-01

Recent research has found that maternal employment is associated with worse child performance on tests of cognitive ability. This paper explores mechanisms for that correlation. We estimate models of instrumental variables using a unique dataset, the American Time Use Survey, that measure the effect of maternal employment on the mother's…

Recent Developments on Airborne Forward Looking Interferometer for the Detection of Wake Vortices

NASA Technical Reports Server (NTRS)

Daniels, Taumi S.; Smith, William L.; Kirev, Stanislav

2012-01-01

A goal of these studies was development of the measurement methods and algorithms necessary to detect wake vortex hazards in real time from either an aircraft or ground-based hyperspectral Fourier Transform Spectrometer (FTS). This paper provides an update on research to model FTS detection of wake vortices. The Terminal Area Simulation System (TASS) was used to generate wake vortex fields of 3-D winds, temperature, and absolute humidity. These fields were input to the Line by Line Radiative Transfer Model (LBLRTM), a hyperspectral radiance model in the infrared, employed for the FTS numerical modeling. An initial set of cases has been analyzed to identify a wake vortex IR signature and signature sensitivities to various state variables. Results from the numerical modeling case studies will be presented. Preliminary results indicated that an imaging IR instrument sensitive to six narrow bands within the 670 to 3150 per centimeter spectral region would be sufficient for wake vortex detection. Noise floor estimates for a recommended instrument are a current research topic.

THAT INSTRUMENT IS LOUSY! IN SEARCH OF AGREEMENT WHEN USING INSTRUMENTAL VARIABLES ESTIMATION IN SUBSTANCE USE RESEARCH

PubMed Central

Popovici, Ioana

2009-01-01

SUMMARY The primary statistical challenge that must be addressed when using cross-sectional data to estimate the consequences of consuming addictive substances is the likely endogeneity of substance use. While economists are in agreement on the need to consider potential endogeneity bias and the value of instrumental variables estimation, the selection of credible instruments is a topic of heated debate in the field. Rather than attempt to resolve this debate, our paper highlights the diversity of judgments about what constitutes appropriate instruments for substance use based on a comprehensive review of the economics literature since 1990. We then offer recommendations related to the selection of reliable instruments in future studies. PMID:20029936

Instrument characterization for the detection of long-term changes in stratospheric ozone - An analysis of the SBUV/2 radiometer

NASA Technical Reports Server (NTRS)

Frederick, J. E.; Heath, D. F.; Cebula, R. P.

1986-01-01

The scientific objective of unambiguously detecting subtle global trends in upper stratospheric ozone requires that one maintains a thorough understanding of the satellite-based remote sensors intended for this task. The instrument now in use for long term ozone monitoring is the SBUV/2 being flown on NOAA operational satellites. A critical activity in the data interpretation involves separating small changes in measurement sensitivity from true atmospheric variability. By defining the specific issues that must be addressed and presenting results derived early in the mission of the first SBUV/2 flight model, this work serves as a guide to the instrument investigations that are essential in the attempt to detect long-term changes in the ozone layer.

Validating a new device for measuring tear evaporation rates.

PubMed

Rohit, Athira; Ehrmann, Klaus; Naduvilath, Thomas; Willcox, Mark; Stapleton, Fiona

2014-01-01

To calibrate and validate a commercially available dermatology instrument to measure tear evaporation rate of contact lens wearers. A dermatology instrument was modified by attaching a swim goggle cup such that the cup sealed around the eye socket. Results for the unmodified instrument are dependent on probe area and enclosed volume. Calibration curves were established using a model eye, to account for individual variations in chamber volume and exposed area. Fifteen participants were recruited and the study included a contact lens wear and a no contact lens wear stage. Day and diurnal variation of the measurements were assessed by taking the measurement three times a day over 2 days. The coefficient of repeatability of the measurement was calculated and a linear mixed model assessed the influence of humidity, temperature, contact lens wear, day and diurnal variations on tear evaporation rate. The associations between variables were assessed using Pearson correlation coefficient. Absolute evaporation rates with and without contact lens wear were calculated based on the new calibration. The measurements were most repeatable during the evening with no lens wear (COR = 49 g m⁻² h) and least repeatable during the evening with contact lens wear (COR = 93 g m⁻² h). Humidity (p = 0.007), and contact lens wear (p < 0.01), significantly affected the tear evaporation rate. However, temperature (p = 0.54) diurnal variation (p = 0.85) and different days (p = 0.65) had no significant effect after controlling for humidity. Tear evaporation rates can be measured using a modified dermatology instrument. Measurements were higher and more variable with lens wear consistent with previous literature. Control of environmental conditions is important as a higher humidity results in a reduced evaporation rate. © 2013 The Authors Ophthalmic & Physiological Optics © 2013 The College of Optometrists.

The Flare Irradiance Spectral Model (FISM) and its Contributions to Space Weather Research, the Flare Energy Budget, and Instrument Design

NASA Technical Reports Server (NTRS)

Chamberlin, Phillip

2008-01-01

The Flare Irradiance Spectral Model (FISM) is an empirical model of the solar irradiance spectrum from 0.1 to 190 nm at 1 nm spectral resolution and on a 1-minute time cadence. The goal of FISM is to provide accurate solar spectral irradiances over the vacuum ultraviolet (VUV: 0-200 nm) range as input for ionospheric and thermospheric models. The seminar will begin with a brief overview of the FISM model, and also how the Solar Dynamics Observatory (SDO) EUV Variability Experiment (EVE) will contribute to improving FISM. Some current studies will then be presented that use FISM estimations of the solar VUV irradiance to quantify the contributions of the increased irradiance from flares to Earth's increased thermospheric and ionospheric densites. Initial results will also be presented from a study looking at the electron density increases in the Martian atmosphere during a solar flare. Results will also be shown quantifying the VUV contributions to the total flare energy budget for both the impulsive and gradual phases of solar flares. Lastly, an example of how FISM can be used to simplify the design of future solar VUV irradiance instruments will be discussed, using the future NOAA GOES-R Extreme Ultraviolet and X-Ray Sensors (EXIS) space weather instrument.

CIEL*a*b* color space predictive models for colorimetry devices--analysis of perfume quality.

PubMed

Korifi, Rabia; Le Dréau, Yveline; Antinelli, Jean-François; Valls, Robert; Dupuy, Nathalie

2013-01-30

Color perception plays a major role in the consumer evaluation of perfume quality. Consumers need first to be entirely satisfied with the sensory properties of products, before other quality dimensions become relevant. The evaluation of complex mixtures color presents a challenge even for modern analytical techniques. A variety of instruments are available for color measurement. They can be classified as tristimulus colorimeters and spectrophotometers. Obsolescence of the electronics of old tristimulus colorimeter arises from the difficulty in finding repair parts and leads to its replacement by more modern instruments. High quality levels in color measurement, i.e., accuracy and reliability in color control are the major advantages of the new generation of color instrumentation, the integrating sphere spectrophotometer. Two models of spectrophotometer were tested in transmittance mode, employing the d/0° geometry. The CIEL(*)a(*)b(*) color space parameters were measured with each instrument for 380 samples of raw materials and bases used in the perfume compositions. The results were graphically compared between the colorimeter device and the spectrophotometer devices. All color space parameters obtained with the colorimeter were used as dependent variables to generate regression equations with values obtained from the spectrophotometers. The data was statistically analyzed to create predictive model between the reference and the target instruments through two methods. The first method uses linear regression analysis and the second method consists of partial least square regression (PLS) on each component. Copyright © 2012 Elsevier B.V. All rights reserved.

Combating Unmeasured Confounding in Cross-Sectional Studies: Evaluating Instrumental-Variable and Heckman Selection Models

PubMed Central

DeMaris, Alfred

2014-01-01

Unmeasured confounding is the principal threat to unbiased estimation of treatment “effects” (i.e., regression parameters for binary regressors) in nonexperimental research. It refers to unmeasured characteristics of individuals that lead them both to be in a particular “treatment” category and to register higher or lower values than others on a response variable. In this article, I introduce readers to 2 econometric techniques designed to control the problem, with a particular emphasis on the Heckman selection model (HSM). Both techniques can be used with only cross-sectional data. Using a Monte Carlo experiment, I compare the performance of instrumental-variable regression (IVR) and HSM to that of ordinary least squares (OLS) under conditions with treatment and unmeasured confounding both present and absent. I find HSM generally to outperform IVR with respect to mean-square-error of treatment estimates, as well as power for detecting either a treatment effect or unobserved confounding. However, both HSM and IVR require a large sample to be fully effective. The use of HSM and IVR in tandem with OLS to untangle unobserved confounding bias in cross-sectional data is further demonstrated with an empirical application. Using data from the 2006–2010 General Social Survey (National Opinion Research Center, 2014), I examine the association between being married and subjective well-being. PMID:25110904

Materialists on Facebook: the self-regulatory role of social comparisons and the objectification of Facebook friends.

PubMed

Ozimek, Phillip; Baer, Fiona; Förster, Jens

2017-11-01

In this study, we examine chronic materialism as a possible motive for Facebook usage. We test an explanatory mediation model predicting that materialists use Facebook more frequently, because they compare themselves to others, they objectify and instrumentalize others, and they accumulate friends. For this, we conducted two online surveys ( N 1 = 242, N 2 = 289) assessing demographic variables, Facebook use, social comparison, materialism, objectification and instrumentalization. Results confirm the predicted mediation model. Our findings suggest that Facebook can be used as a means to an end in a way of self-regulatory processes, like satisfying of materialistic goals. The findings are the first evidence for our Social Online Self-regulation Theory (SOS-T), which contains numerous predictions that can be tested in the future.

The Use of Linear Instrumental Variables Methods in Health Services Research and Health Economics: A Cautionary Note

PubMed Central

Terza, Joseph V; Bradford, W David; Dismuke, Clara E

2008-01-01

Objective To investigate potential bias in the use of the conventional linear instrumental variables (IV) method for the estimation of causal effects in inherently nonlinear regression settings. Data Sources Smoking Supplement to the 1979 National Health Interview Survey, National Longitudinal Alcohol Epidemiologic Survey, and simulated data. Study Design Potential bias from the use of the linear IV method in nonlinear models is assessed via simulation studies and real world data analyses in two commonly encountered regression setting: (1) models with a nonnegative outcome (e.g., a count) and a continuous endogenous regressor; and (2) models with a binary outcome and a binary endogenous regressor. Principle Findings The simulation analyses show that substantial bias in the estimation of causal effects can result from applying the conventional IV method in inherently nonlinear regression settings. Moreover, the bias is not attenuated as the sample size increases. This point is further illustrated in the survey data analyses in which IV-based estimates of the relevant causal effects diverge substantially from those obtained with appropriate nonlinear estimation methods. Conclusions We offer this research as a cautionary note to those who would opt for the use of linear specifications in inherently nonlinear settings involving endogeneity. PMID:18546544

Retrieval of Methane Source Strengths in Europe Using a Simple Modeling Approach to Assess the Potential of Spaceborne Lidar Observations

NASA Technical Reports Server (NTRS)

Weaver, C.; Kiemle, C.; Kawa, S. R.; Aalto, T.; Necki, J.; Steinbacher, M.; Arduini, J.; Apadula, F.; Berkhout, H.; Hatakka, J.

2014-01-01

We investigate the sensitivity of future spaceborne lidar measurements to changes in surface methane emissions. We use surface methane observations from nine European ground stations and a Lagrangian transport model to infer surface methane emissions for 2010. Our inversion shows the strongest emissions from the Netherlands, the coal mines in Upper Silesia, Poland, and wetlands in southern Finland. The simulated methane surface concentrations capture at least half of the daily variability in the observations, suggesting that the transport model is correctly simulating the regional transport pathways over Europe. With this tool we can test whether proposed methane lidar instruments will be sensitive to changes in surface emissions. We show that future lidar instruments should be able to detect a 50% reduction in methane emissions from the Netherlands and Germany, at least during summer.

Factor analytical study of the short version of the World Health Organization Quality of Life Instrument.

PubMed

Ohaeri, Jude U; Olusina, Adewunmi K; Al-Abassi, Abdul-Hamid M

2004-01-01

The domains of the 26-item World Health Organization Quality of Life Instrument (WHOQOL-Bref) contain heterogeneous items and do not encompass the logical constructs of subjective quality of life (QOL). We compared the WHO 4-domain and 6-domain models of the WHOQOL-Bref with the 8-domain model that we obtained from factor analysis (FA). Data from 118 recently recovered Nigerian psychotic patients were used in confirmatory factor analysis (CFA) to assess goodness of fit and clarity of concept. Our FA model had superior goodness of fit for CFA and provided clarity of concept. Analysis of the WHOQOL-Bref should consider the domains from FA and include 'overall QOL' as an item and dependent variable. Subjective QOL is an aggregate of the following constructs: satisfaction with life circumstances; fulfillment of needs, and opportunity for experience in the milieu.

Modelling a solar flare from X-ray, UV, and radio observations

NASA Astrophysics Data System (ADS)

Chiuderi Drago, F.; Monsignori Fossi, B. C.

1991-03-01

A slowly evolving, flaring loop was observed by the UVSP, XRP, and HXIS instruments onboard SMM on June 10, 1980. Simultaneous radio observations from Toyokawa (Japan) are also available. The SMM instruments have an angular resolution ranging from 3 to 30 arcsec by which the loop structure may be determined. It appears that these observations cannot be accounted for by a single loop model even assuming a variable temperature and pressure. The additional presence of a hot and tenuous isothermal plasma is necessary to explain the harder emission (HXIS). X-ray and UV data are used to fit the differential emission measure as a function of temperature and a model of the flare is deduced, which is then checked against radio data. An estimate of the heating function along the loop and of the total energy content of the loop is also given.

The use of a combination of instrumental methods to assess change in sensory crispness during storage of a "Honeycrisp" apple breeding family.

PubMed

Chang, Hsueh-Yuan; Vickers, Zata M; Tong, Cindy B S

2018-04-01

Loss of crispness in apple fruit during storage reduces the fruit's fresh sensation and consumer acceptance. Apple varieties that maintain crispness thus have higher potential for longer-term consumer appeal. To efficiently phenotype crispness, several instrumental methods have been tested, but variable results were obtained when different apple varieties were assayed. To extend these studies, we assessed the extent to which instrumental measurements correlate to and predict sensory crispness, with a focus on crispness maintenance. We used an apple breeding family derived from a cross between "Honeycrisp" and "MN1764," which segregates for crispness maintenance. Three types of instrumental measurements (puncture, snapping, and mechanical-acoustic tests) and sensory evaluation were performed on fruit at harvest and after 8 weeks of cold storage. Overall, 20 genotypes from the family and the 2 parents were characterized by 19 force and acoustic measures. In general, crispness was more related to force than to acoustic measures. Force linear distance and maximum force as measured by the mechanical-acoustic test were best correlated with sensory crispness and change in crispness, respectively. The correlations varied by apple genotype. The best multiple linear regression model to predict change in sensory crispness between harvest and storage of fruit of this breeding family incorporated both force and acoustic measures. This work compared the abilities of instrumental tests to predict sensory crispness maintenance of apple fruit. The use of an instrumental method that is highly correlated to sensory crispness evaluation can enhance the efficiency and reduce the cost of measuring crispness for breeding purposes. This study showed that sensory crispness and change in crispness after storage of an apple breeding family were reliably predicted with a combination of instrumental measurements and multiple variable analyses. The strategy potentially can be applied to other apple varieties for more accurate interpretation of crispness maintenance measured instrumentally. © 2018 Wiley Periodicals, Inc.

Developing and testing a measurement tool for assessing predictors of breakfast consumption based on a health promotion model.

PubMed

Dehdari, Tahereh; Rahimi, Tahereh; Aryaeian, Naheed; Gohari, Mahmood Reza; Esfeh, Jabiz Modaresi

2014-01-01

To develop an instrument for measuring Health Promotion Model constructs in terms of breakfast consumption, and to identify the constructs that were predictors of breakfast consumption among Iranian female students. A questionnaire on Health Promotion Model variables was developed and potential predictors of breakfast consumption were assessed using this tool. One hundred female students, mean age 13 years (SD ± 1.2 years). Two middle schools from moderate-income areas in Qom, Iran. Health Promotion Model variables were assessed using a 58-item questionnaire. Breakfast consumption was also measured. Internal consistency (Cronbach alpha), content validity index, content validity ratio, multiple linear regression using stepwise method, and Pearson correlation. Content validity index and content validity ratio scores of the developed scale items were 0.89 and 0.93, respectively. Internal consistencies (range, .74-.91) of subscales were acceptable. Prior related behaviors, perceived barriers, self-efficacy, and competing demand and preferences were 4 constructs that could predict 63% variance of breakfast frequency per week among subjects. The instrument developed in this study may be a useful tool for researchers to explore factors affecting breakfast consumption among students. Students with a high level of self-efficacy, more prior related behavior, fewer perceived barriers, and fewer competing demands were most likely to regularly consume breakfast. Copyright © 2014 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

Marginalized identities, discrimination burden, and mental health: Empirical exploration of an interpersonal-level approach to modeling intersectionality

PubMed Central

Seng, Julia S; Lopez, William D; Sperlich, Mickey; Hamama, Lydia; Meldrum, Caroline D Reed

2012-01-01

Intersectionality is a term used to describe the intersecting effects of race, class, gender, and other marginalizing characteristics that contribute to social identity and affect health. Adverse health effects are thought to occur via social processes including discrimination and structural inequalities (i.e., reduced opportunities for education and income). Although intersectionality has been well-described conceptually, approaches to modeling it in quantitative studies of health outcomes are still emerging. Strategies to date have focused on modeling demographic characteristics as proxies for structural inequality. Our objective was to extend these methodological efforts by modeling intersectionality across three levels: structural, contextual, and interpersonal, consistent with a social-ecological framework. We conducted a secondary analysis of a database that included two components of a widely used survey instrument, the Everyday Discrimination Scale. We operationalized a meso- or interpersonal-level of intersectionality using two variables, the frequency score of discrimination experiences and the sum of characteristics listed as reasons for these (i.e., the person’s race, ethnicity, gender, sexual orientation, nationality, religion, disability or pregnancy status, or physical appearance). We controlled for two structural inequality factors (low education, poverty) and three contextual factors (high crime neighborhood, racial minority status, and trauma exposures). The outcome variables we modeled were posttraumatic stress disorder symptoms and a quality of life index score. We used data from 619 women who completed the Everyday Discrimination Scale for a perinatal study in the U.S. state of Michigan. Statistical results indicated that the two interpersonal-level variables (i.e., number of marginalized identities, frequency of discrimination) explained 15% of variance in posttraumatic stress symptoms and 13% of variance in quality of life scores, improving the predictive value of the models over those using structural inequality and contextual factors alone. This study’s results point to instrument development ideas to improve the statistical modeling of intersectionality in health and social science research. PMID:23089613

Marginalized identities, discrimination burden, and mental health: empirical exploration of an interpersonal-level approach to modeling intersectionality.

PubMed

Seng, Julia S; Lopez, William D; Sperlich, Mickey; Hamama, Lydia; Reed Meldrum, Caroline D

2012-12-01

Intersectionality is a term used to describe the intersecting effects of race, class, gender, and other marginalizing characteristics that contribute to social identity and affect health. Adverse health effects are thought to occur via social processes including discrimination and structural inequalities (i.e., reduced opportunities for education and income). Although intersectionality has been well-described conceptually, approaches to modeling it in quantitative studies of health outcomes are still emerging. Strategies to date have focused on modeling demographic characteristics as proxies for structural inequality. Our objective was to extend these methodological efforts by modeling intersectionality across three levels: structural, contextual, and interpersonal, consistent with a social-ecological framework. We conducted a secondary analysis of a database that included two components of a widely used survey instrument, the Everyday Discrimination Scale. We operationalized a meso- or interpersonal-level of intersectionality using two variables, the frequency score of discrimination experiences and the sum of characteristics listed as reasons for these (i.e., the person's race, ethnicity, gender, sexual orientation, nationality, religion, disability or pregnancy status, or physical appearance). We controlled for two structural inequality factors (low education, poverty) and three contextual factors (high crime neighborhood, racial minority status, and trauma exposures). The outcome variables we modeled were posttraumatic stress disorder symptoms and a quality of life index score. We used data from 619 women who completed the Everyday Discrimination Scale for a perinatal study in the U.S. state of Michigan. Statistical results indicated that the two interpersonal-level variables (i.e., number of marginalized identities, frequency of discrimination) explained 15% of variance in posttraumatic stress symptoms and 13% of variance in quality of life scores, improving the predictive value of the models over those using structural inequality and contextual factors alone. This study's results point to instrument development ideas to improve the statistical modeling of intersectionality in health and social science research. Copyright © 2012 Elsevier Ltd. All rights reserved.

Waist circumference, body mass index, and employment outcomes.

PubMed

Kinge, Jonas Minet

2017-07-01

Body mass index (BMI) is an imperfect measure of body fat. Recent studies provide evidence in favor of replacing BMI with waist circumference (WC). Hence, I investigated whether or not the association between fat mass and employment status vary by anthropometric measures. I used 15 rounds of the Health Survey for England (1998-2013), which has measures of employment status in addition to measured height, weight, and WC. WC and BMI were entered as continuous variables and obesity as binary variables defined using both WC and BMI. I used multivariate models controlling for a set of covariates. The association of WC with employment was of greater magnitude than the association between BMI and employment. I reran the analysis using conventional instrumental variables methods. The IV models showed significant impacts of obesity on employment; however, they were not more pronounced when WC was used to measure obesity, compared to BMI. This means that, in the IV models, the impact of fat mass on employment did not depend on the measure of fat mass.

Instrumental variables I: instrumental variables exploit natural variation in nonexperimental data to estimate causal relationships.

PubMed

Rassen, Jeremy A; Brookhart, M Alan; Glynn, Robert J; Mittleman, Murray A; Schneeweiss, Sebastian

2009-12-01

The gold standard of study design for treatment evaluation is widely acknowledged to be the randomized controlled trial (RCT). Trials allow for the estimation of causal effect by randomly assigning participants either to an intervention or comparison group; through the assumption of "exchangeability" between groups, comparing the outcomes will yield an estimate of causal effect. In the many cases where RCTs are impractical or unethical, instrumental variable (IV) analysis offers a nonexperimental alternative based on many of the same principles. IV analysis relies on finding a naturally varying phenomenon, related to treatment but not to outcome except through the effect of treatment itself, and then using this phenomenon as a proxy for the confounded treatment variable. This article demonstrates how IV analysis arises from an analogous but potentially impossible RCT design, and outlines the assumptions necessary for valid estimation. It gives examples of instruments used in clinical epidemiology and concludes with an outline on estimation of effects.

Instrumental variables I: instrumental variables exploit natural variation in nonexperimental data to estimate causal relationships

PubMed Central

Rassen, Jeremy A.; Brookhart, M. Alan; Glynn, Robert J.; Mittleman, Murray A.; Schneeweiss, Sebastian

2010-01-01

The gold standard of study design for treatment evaluation is widely acknowledged to be the randomized controlled trial (RCT). Trials allow for the estimation of causal effect by randomly assigning participants either to an intervention or comparison group; through the assumption of “exchangeability” between groups, comparing the outcomes will yield an estimate of causal effect. In the many cases where RCTs are impractical or unethical, instrumental variable (IV) analysis offers a nonexperimental alternative based on many of the same principles. IV analysis relies on finding a naturally varying phenomenon, related to treatment but not to outcome except through the effect of treatment itself, and then using this phenomenon as a proxy for the confounded treatment variable. This article demonstrates how IV analysis arises from an analogous but potentially impossible RCT design, and outlines the assumptions necessary for valid estimation. It gives examples of instruments used in clinical epidemiology and concludes with an outline on estimation of effects. PMID:19356901

Posthospitalization home health care use and changes in functional status in a Medicare population.

PubMed

Hadley, J; Rabin, D; Epstein, A; Stein, S; Rimes, C

2000-05-01

The objective of this work was to estimate the effect of Medicare beneficiaries' use of home health care (HHC) for 6 months after hospital discharge on the change in functional status over a 1-year period beginning before hospitalization. Data came from the Medicare Current Beneficiary Survey, which is a nationally representative sample of Medicare beneficiaries, in-person interview data, and Medicare claims for 1991 through 1994 for 2,127 nondisabled, community-dwelling, elderly Medicare beneficiaries who were hospitalized within 6 months of their annual in-person interviews. Econometric estimation with the instrumental variable method was used to correct for observational data bias, ie, the nonrandom allocation of discharged beneficiaries to the use of posthospitalization HHC. The analysis estimates a first-stage model of HHC use from which an instrumental variable estimate is constructed to estimate the effect on change in functional status. The instrumental variable estimates suggest that HHC users experienced greater improvements in functional status than nonusers as measured by the change in a continuous scale based on the number and mix of activities of daily living and instrumental activities of daily living before and after hospitalization. The estimated improvement in functional status could be as large as 13% for a 10% increase in HHC use. In contrast, estimation with the observational data on HHC use implies that HHC users had poorer health outcomes. Adjusting for potential observational data bias is critical to obtaining estimates of the relationship between the use of posthospitalization HHC and the change in health before and after hospitalization. After adjustment, the results suggest that efforts to constrain Medicare's spending for HHC, as required by the Balanced Budget Act of 1997, may lead to poorer health outcomes for some beneficiaries.

Estimating the efficacy of Alcoholics Anonymous without self-selection bias: An instrumental variables re-analysis of randomized clinical trials

PubMed Central

Humphreys, Keith; Blodgett, Janet C.; Wagner, Todd H.

2014-01-01

Background Observational studies of Alcoholics Anonymous’ (AA) effectiveness are vulnerable to self-selection bias because individuals choose whether or not to attend AA. The present study therefore employed an innovative statistical technique to derive a selection bias-free estimate of AA’s impact. Methods Six datasets from 5 National Institutes of Health-funded randomized trials (one with two independent parallel arms) of AA facilitation interventions were analyzed using instrumental variables models. Alcohol dependent individuals in one of the datasets (n = 774) were analyzed separately from the rest of sample (n = 1582 individuals pooled from 5 datasets) because of heterogeneity in sample parameters. Randomization itself was used as the instrumental variable. Results Randomization was a good instrument in both samples, effectively predicting increased AA attendance that could not be attributed to self-selection. In five of the six data sets, which were pooled for analysis, increased AA attendance that was attributable to randomization (i.e., free of self-selection bias) was effective at increasing days of abstinence at 3-month (B = .38, p = .001) and 15-month (B = 0.42, p = .04) follow-up. However, in the remaining dataset, in which pre-existing AA attendance was much higher, further increases in AA involvement caused by the randomly assigned facilitation intervention did not affect drinking outcome. Conclusions For most individuals seeking help for alcohol problems, increasing AA attendance leads to short and long term decreases in alcohol consumption that cannot be attributed to self-selection. However, for populations with high pre-existing AA involvement, further increases in AA attendance may have little impact. PMID:25421504

Estimating the efficacy of Alcoholics Anonymous without self-selection bias: an instrumental variables re-analysis of randomized clinical trials.

PubMed

Humphreys, Keith; Blodgett, Janet C; Wagner, Todd H

2014-11-01

Observational studies of Alcoholics Anonymous' (AA) effectiveness are vulnerable to self-selection bias because individuals choose whether or not to attend AA. The present study, therefore, employed an innovative statistical technique to derive a selection bias-free estimate of AA's impact. Six data sets from 5 National Institutes of Health-funded randomized trials (1 with 2 independent parallel arms) of AA facilitation interventions were analyzed using instrumental variables models. Alcohol-dependent individuals in one of the data sets (n = 774) were analyzed separately from the rest of sample (n = 1,582 individuals pooled from 5 data sets) because of heterogeneity in sample parameters. Randomization itself was used as the instrumental variable. Randomization was a good instrument in both samples, effectively predicting increased AA attendance that could not be attributed to self-selection. In 5 of the 6 data sets, which were pooled for analysis, increased AA attendance that was attributable to randomization (i.e., free of self-selection bias) was effective at increasing days of abstinence at 3-month (B = 0.38, p = 0.001) and 15-month (B = 0.42, p = 0.04) follow-up. However, in the remaining data set, in which preexisting AA attendance was much higher, further increases in AA involvement caused by the randomly assigned facilitation intervention did not affect drinking outcome. For most individuals seeking help for alcohol problems, increasing AA attendance leads to short- and long-term decreases in alcohol consumption that cannot be attributed to self-selection. However, for populations with high preexisting AA involvement, further increases in AA attendance may have little impact. Copyright © 2014 by the Research Society on Alcoholism.

Understanding Hydrological Processes in Variable Source Areas in the Glaciated Northeastern US Watersheds under Variable Climate Conditions

NASA Astrophysics Data System (ADS)

Steenhuis, T. S.; Azzaino, Z.; Hoang, L.; Pacenka, S.; Worqlul, A. W.; Mukundan, R.; Stoof, C.; Owens, E. M.; Richards, B. K.

2017-12-01

The New York City source watersheds in the Catskill Mountains' humid, temperate climate has long-term hydrological and water quality monitoring data It is one of the few catchments where implementation of source and landscape management practices has led to decreased phosphorus concentration in the receiving surface waters. One of the reasons is that landscape measures correctly targeted the saturated variable source runoff areas (VSA) in the valley bottoms as the location where most of the runoff and other nonpoint pollutants originated. Measures targeting these areas were instrumental in lowering phosphorus concentration. Further improvements in water quality can be made based on a better understanding of the flow processes and water table fluctuations in the VSA. For that reason, we instrumented a self-contained upland variable source watershed with a landscape characteristic of a soil underlain by glacial till at shallow depth similar to the Catskill watersheds. In this presentation, we will discuss our experimental findings and present a mathematical model. Variable source areas have a small slope making gravity the driving force for the flow, greatly simplifying the simulation of the flow processes. The experimental data and the model simulations agreed for both outflow and water table fluctuations. We found that while the flows to the outlet were similar throughout the year, the discharge of the VSA varies greatly. This was due to transpiration by the plants which became active when soil temperatures were above 10oC. We found that shortly after the temperature increased above 10oC the baseflow stopped and only surface runoff occurred when rainstorms exceeded the storage capacity of the soil in at least a portion of the variable source area. Since plant growth in the variable source area was a major variable determining the base flow behavior, changes in temperature in the future - affecting the duration of the growing season - will affect baseflow and related transport of nutrient and other chemicals many times more than small temperature related increases in potential evaporation rate. This in turn will directly change the water availability and pollutant transport in the many surface source watersheds with variable source area hydrology.

The added value of time-variable microgravimetry to the understanding of how volcanoes work

USGS Publications Warehouse

Carbone, Daniele; Poland, Michael; Greco, Filippo; Diament, Michel

2017-01-01

During the past few decades, time-variable volcano gravimetry has shown great potential for imaging subsurface processes at active volcanoes (including some processes that might otherwise remain “hidden”), especially when combined with other methods (e.g., ground deformation, seismicity, and gas emissions). By supplying information on changes in the distribution of bulk mass over time, gravimetry can provide information regarding processes such as magma accumulation in void space, gas segregation at shallow depths, and mechanisms driving volcanic uplift and subsidence. Despite its potential, time-variable volcano gravimetry is an underexploited method, not widely adopted by volcano researchers or observatories. The cost of instrumentation and the difficulty in using it under harsh environmental conditions is a significant impediment to the exploitation of gravimetry at many volcanoes. In addition, retrieving useful information from gravity changes in noisy volcanic environments is a major challenge. While these difficulties are not trivial, neither are they insurmountable; indeed, creative efforts in a variety of volcanic settings highlight the value of time-variable gravimetry for understanding hazards as well as revealing fundamental insights into how volcanoes work. Building on previous work, we provide a comprehensive review of time-variable volcano gravimetry, including discussions of instrumentation, modeling and analysis techniques, and case studies that emphasize what can be learned from campaign, continuous, and hybrid gravity observations. We are hopeful that this exploration of time-variable volcano gravimetry will excite more scientists about the potential of the method, spurring further application, development, and innovation.

Impact of exposure measurement error in air pollution epidemiology: effect of error type in time-series studies.

PubMed

Goldman, Gretchen T; Mulholland, James A; Russell, Armistead G; Strickland, Matthew J; Klein, Mitchel; Waller, Lance A; Tolbert, Paige E

2011-06-22

Two distinctly different types of measurement error are Berkson and classical. Impacts of measurement error in epidemiologic studies of ambient air pollution are expected to depend on error type. We characterize measurement error due to instrument imprecision and spatial variability as multiplicative (i.e. additive on the log scale) and model it over a range of error types to assess impacts on risk ratio estimates both on a per measurement unit basis and on a per interquartile range (IQR) basis in a time-series study in Atlanta. Daily measures of twelve ambient air pollutants were analyzed: NO2, NOx, O3, SO2, CO, PM10 mass, PM2.5 mass, and PM2.5 components sulfate, nitrate, ammonium, elemental carbon and organic carbon. Semivariogram analysis was applied to assess spatial variability. Error due to this spatial variability was added to a reference pollutant time-series on the log scale using Monte Carlo simulations. Each of these time-series was exponentiated and introduced to a Poisson generalized linear model of cardiovascular disease emergency department visits. Measurement error resulted in reduced statistical significance for the risk ratio estimates for all amounts (corresponding to different pollutants) and types of error. When modelled as classical-type error, risk ratios were attenuated, particularly for primary air pollutants, with average attenuation in risk ratios on a per unit of measurement basis ranging from 18% to 92% and on an IQR basis ranging from 18% to 86%. When modelled as Berkson-type error, risk ratios per unit of measurement were biased away from the null hypothesis by 2% to 31%, whereas risk ratios per IQR were attenuated (i.e. biased toward the null) by 5% to 34%. For CO modelled error amount, a range of error types were simulated and effects on risk ratio bias and significance were observed. For multiplicative error, both the amount and type of measurement error impact health effect estimates in air pollution epidemiology. By modelling instrument imprecision and spatial variability as different error types, we estimate direction and magnitude of the effects of error over a range of error types.

Invited Commentary: Using Financial Credits as Instrumental Variables for Estimating the Causal Relationship Between Income and Health.

PubMed

Pega, Frank

2016-05-01

Social epidemiologists are interested in determining the causal relationship between income and health. Natural experiments in which individuals or groups receive income randomly or quasi-randomly from financial credits (e.g., tax credits or cash transfers) are increasingly being analyzed using instrumental variable analysis. For example, in this issue of the Journal, Hamad and Rehkopf (Am J Epidemiol. 2016;183(9):775-784) used an in-work tax credit called the Earned Income Tax Credit as an instrument to estimate the association between income and child development. However, under certain conditions, the use of financial credits as instruments could violate 2 key instrumental variable analytic assumptions. First, some financial credits may directly influence health, for example, through increasing a psychological sense of welfare security. Second, financial credits and health may have several unmeasured common causes, such as politics, other social policies, and the motivation to maximize the credit. If epidemiologists pursue such instrumental variable analyses, using the amount of an unconditional, universal credit that an individual or group has received as the instrument may produce the most conceptually convincing and generalizable evidence. However, other natural income experiments (e.g., lottery winnings) and other methods that allow better adjustment for confounding might be more promising approaches for estimating the causal relationship between income and health. © The Author 2016. 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.

Estimations of natural variability between satellite measurements of trace species concentrations

NASA Astrophysics Data System (ADS)

Sheese, P.; Walker, K. A.; Boone, C. D.; Degenstein, D. A.; Kolonjari, F.; Plummer, D. A.; von Clarmann, T.

2017-12-01

In order to validate satellite measurements of atmospheric states, it is necessary to understand the range of random and systematic errors inherent in the measurements. On occasions where the measurements do not agree within those errors, a common "go-to" explanation is that the unexplained difference can be chalked up to "natural variability". However, the expected natural variability is often left ambiguous and rarely quantified. This study will look to quantify the expected natural variability of both O3 and NO2 between two satellite instruments: ACE-FTS (Atmospheric Chemistry Experiment - Fourier Transform Spectrometer) and OSIRIS (Optical Spectrograph and Infrared Imaging System). By sampling the CMAM30 (30-year specified dynamics simulation of the Canadian Middle Atmosphere Model) climate chemistry model throughout the upper troposphere and stratosphere at times and geolocations of coincident ACE-FTS and OSIRIS measurements at varying coincidence criteria, height-dependent expected values of O3 and NO2 variability will be estimated and reported on. The results could also be used to better optimize the coincidence criteria used in satellite measurement validation studies.

Titan's Upper Atmosphere from Cassini/UVIS Solar Occultations

NASA Astrophysics Data System (ADS)

Capalbo, Fernando J.; Bénilan, Yves; Yelle, Roger V.; Koskinen, Tommi T.

2015-12-01

Titan’s atmosphere is composed mainly of molecular nitrogen, methane being the principal trace gas. From the analysis of 8 solar occultations measured by the Extreme Ultraviolet channel of the Ultraviolet Imaging Spectrograph (UVIS) on board Cassini, we derived vertical profiles of N2 in the range 1100-1600 km and vertical profiles of CH4 in the range 850-1300 km. The correction of instrument effects and observational effects applied to the data are described. We present CH4 mole fractions, and average temperatures for the upper atmosphere obtained from the N2 profiles. The occultations correspond to different times and locations, and an analysis of variability of density and temperature is presented. The temperatures were analyzed as a function of geographical and temporal variables, without finding a clear correlation with any of them, although a trend of decreasing temperature toward the north pole was observed. The globally averaged temperature obtained is (150 ± 1) K. We compared our results from solar occultations with those derived from other UVIS observations, as well as studies performed with other instruments. The observational data we present confirm the atmospheric variability previously observed, add new information to the global picture of Titan’s upper atmosphere composition, variability, and dynamics, and provide new constraints to photochemical models.

Bayesian Normalization Model for Label-Free Quantitative Analysis by LC-MS

PubMed Central

Nezami Ranjbar, Mohammad R.; Tadesse, Mahlet G.; Wang, Yue; Ressom, Habtom W.

2016-01-01

We introduce a new method for normalization of data acquired by liquid chromatography coupled with mass spectrometry (LC-MS) in label-free differential expression analysis. Normalization of LC-MS data is desired prior to subsequent statistical analysis to adjust variabilities in ion intensities that are not caused by biological differences but experimental bias. There are different sources of bias including variabilities during sample collection and sample storage, poor experimental design, noise, etc. In addition, instrument variability in experiments involving a large number of LC-MS runs leads to a significant drift in intensity measurements. Although various methods have been proposed for normalization of LC-MS data, there is no universally applicable approach. In this paper, we propose a Bayesian normalization model (BNM) that utilizes scan-level information from LC-MS data. Specifically, the proposed method uses peak shapes to model the scan-level data acquired from extracted ion chromatograms (EIC) with parameters considered as a linear mixed effects model. We extended the model into BNM with drift (BNMD) to compensate for the variability in intensity measurements due to long LC-MS runs. We evaluated the performance of our method using synthetic and experimental data. In comparison with several existing methods, the proposed BNM and BNMD yielded significant improvement. PMID:26357332

Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas - a review

NASA Astrophysics Data System (ADS)

Cristiano, Elena; ten Veldhuis, Marie-claire; van de Giesen, Nick

2017-07-01

In urban areas, hydrological processes are characterized by high variability in space and time, making them sensitive to small-scale temporal and spatial rainfall variability. In the last decades new instruments, techniques, and methods have been developed to capture rainfall and hydrological processes at high resolution. Weather radars have been introduced to estimate high spatial and temporal rainfall variability. At the same time, new models have been proposed to reproduce hydrological response, based on small-scale representation of urban catchment spatial variability. Despite these efforts, interactions between rainfall variability, catchment heterogeneity, and hydrological response remain poorly understood. This paper presents a review of our current understanding of hydrological processes in urban environments as reported in the literature, focusing on their spatial and temporal variability aspects. We review recent findings on the effects of rainfall variability on hydrological response and identify gaps where knowledge needs to be further developed to improve our understanding of and capability to predict urban hydrological response.

Using Indirect Turbulence Measurements for Real-Time Parameter Estimation in Turbulent Air

NASA Technical Reports Server (NTRS)

Martos, Borja; Morelli, Eugene A.

2012-01-01

The use of indirect turbulence measurements for real-time estimation of parameters in a linear longitudinal dynamics model in atmospheric turbulence was studied. It is shown that measuring the atmospheric turbulence makes it possible to treat the turbulence as a measured explanatory variable in the parameter estimation problem. Commercial off-the-shelf sensors were researched and evaluated, then compared to air data booms. Sources of colored noise in the explanatory variables resulting from typical turbulence measurement techniques were identified and studied. A major source of colored noise in the explanatory variables was identified as frequency dependent upwash and time delay. The resulting upwash and time delay corrections were analyzed and compared to previous time shift dynamic modeling research. Simulation data as well as flight test data in atmospheric turbulence were used to verify the time delay behavior. Recommendations are given for follow on flight research and instrumentation.

Social capital, mental health and biomarkers in Chile: Assessing the effects of social capital in a middle-income country

PubMed Central

Riumallo-Herl, Carlos Javier; Kawachi, Ichiro; Avendano, Mauricio

2014-01-01

In high-income countries, higher social capital is associated with better health. However, there is little evidence of this association in low- and middle-income countries. We examine the association between social capital (social support and trust) and both self-rated and biologically assessed health outcomes in Chile, a middle-income country that experienced a major political transformation and welfare state expansion in the last two decades. Based on data from the Chilean National Health Survey (2009–10), we modeled self-rated health, depression, measured diabetes and hypertension as a function of social capital indicators, controlling for socio-economic status and health behavior. We used an instrumental variable approach to examine whether social capital was causally associated with health. We find that correlations between social capital and health observed in high-income countries are also observed in Chile. All social capital indicators are significantly associated with depression at all ages, and at least one social capital indicator is associated with self-rated health, hypertension and diabetes at ages 45 and above. Instrumental variable models suggest that associations for depression may reflect a causal effect from social capital indicators on mental well-being. Using aggregate social capital as instrument, we also find evidence that social capital may be causally associated with hypertension and diabetes, early markers of cardiovascular risk. Our findings highlight the potential role of social capital in the prevention of depression and early cardiovascular disease in middle-income countries. PMID:24495808

Cross-Cultural adaptation of the General Functioning Scale of the Family

PubMed Central

Pires, Thiago; de Assis, Simone Gonçalves; Avanci, Joviana Quintes; Pesce, Renata Pires

2016-01-01

ABSTRACT OBJECTIVE To describe the process of cross-cultural adaptation of the General Functioning Scale of the Family, a subscale of the McMaster Family Assessment Device, for the Brazilian population. METHODS The General Functioning Scale of the Family was translated into Portuguese and administered to 500 guardians of children in the second grade of elementary school in public schools of Sao Gonçalo, Rio de Janeiro, Southeastern Brazil. The types of equivalences investigated were: conceptual and of items, semantic, operational, and measurement. The study involved discussions with experts, translations and back-translations of the instrument, and psychometric assessment. Reliability and validity studies were carried out by internal consistency testing (Cronbach’s alpha), Guttman split-half correlation model, Pearson correlation coefficient, and confirmatory factor analysis. Associations between General Functioning of the Family and variables theoretically associated with the theme (father’s or mother’s drunkenness and violence between parents) were estimated by odds ratio. RESULTS Semantic equivalence was between 90.0% and 100%. Cronbach’s alpha ranged from 0.79 to 0.81, indicating good internal consistency of the instrument. Pearson correlation coefficient ranged between 0.303 and 0.549. Statistical association was found between the general functioning of the family score and the theoretically related variables, as well as good fit quality of the confirmatory analysis model. CONCLUSIONS The results indicate the feasibility of administering the instrument to the Brazilian population, as it is easy to understand and a good measurement of the construct of interest. PMID:27355464

Mixture modeling methods for the assessment of normal and abnormal personality, part I: cross-sectional models.

PubMed

Hallquist, Michael N; Wright, Aidan G C

2014-01-01

Over the past 75 years, the study of personality and personality disorders has been informed considerably by an impressive array of psychometric instruments. Many of these tests draw on the perspective that personality features can be conceptualized in terms of latent traits that vary dimensionally across the population. A purely trait-oriented approach to personality, however, might overlook heterogeneity that is related to similarities among subgroups of people. This article describes how factor mixture modeling (FMM), which incorporates both categories and dimensions, can be used to represent person-oriented and trait-oriented variability in the latent structure of personality. We provide an overview of different forms of FMM that vary in the degree to which they emphasize trait- versus person-oriented variability. We also provide practical guidelines for applying FMM to personality data, and we illustrate model fitting and interpretation using an empirical analysis of general personality dysfunction.

Collaborative Proposal: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic System Model (RASM)

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

Maslowski, Wieslaw

This project aims to develop, apply and evaluate a regional Arctic System model (RASM) for enhanced decadal predictions. Its overarching goal is to advance understanding of the past and present states of arctic climate and to facilitate improvements in seasonal to decadal predictions. In particular, it will focus on variability and long-term change of energy and freshwater flows through the arctic climate system. The project will also address modes of natural climate variability as well as extreme and rapid climate change in a region of the Earth that is: (i) a key indicator of the state of global climate throughmore » polar amplification and (ii) which is undergoing environmental transitions not seen in instrumental records. RASM will readily allow the addition of other earth system components, such as ecosystem or biochemistry models, thus allowing it to facilitate studies of climate impacts (e.g., droughts and fires) and of ecosystem adaptations to these impacts. As such, RASM is expected to become a foundation for more complete Arctic System models and part of a model hierarchy important for improving climate modeling and predictions.« less

Pilot testing model to uncover industrial symbiosis in Brazilian industrial clusters.

PubMed

Saraceni, Adriana Valélia; Resende, Luis Mauricio; de Andrade Júnior, Pedro Paulo; Pontes, Joseane

2017-04-01

The main objective of this study was to create a pilot model to uncover industrial symbiosis practices in Brazilian industrial clusters. For this purpose, a systematic revision was conducted in journals selected from two categories of the ISI Web of Knowledge: Engineering, Environmental and Engineering, Industrial. After an in-depth revision of literature, results allowed the creation of an analysis structure. A methodology based on fuzzy logic was applied and used to attribute the weights of industrial symbiosis variables. It was thus possible to extract the intensity indicators of the interrelations required to analyse the development level of each correlation between the variables. Determination of variables and their weights initially resulted in a framework for the theory of industrial symbiosis assessments. Research results allowed the creation of a pilot model that could precisely identify the loopholes or development levels in each sphere. Ontology charts for data analysis were also generated. This study contributes to science by presenting the foundations for building an instrument that enables application and compilation of the pilot model, in order to identify opportunity to symbiotic development, which derives from "uncovering" existing symbioses.

Instrumental record of debris flow initiation during natural rainfall: Implications for modeling slope stability

Treesearch

David R. Montgomery; Kevin M. Schmidt; William E. Dietrich; Jim McKean

2009-01-01

The middle of a hillslope hollow in the Oregon Coast Range failed and mobilized as a debris flow during heavy rainfall in November 1996. Automated pressure transducers recorded high spatial variability of pore water pressure within the area that mobilized as a debris flow, which initiated where local upward flow from bedrock developed into overlying colluvium....

A Short Version of SIS (Support Intensity Scale): The Utility of the Application of Artificial Adaptive Systems

ERIC Educational Resources Information Center

Gomiero, Tiziano; Croce, Luigi; Grossi, Enzo; Luc, De Vreese; Buscema, Massimo; Mantesso, Ulrico; De Bastiani, Elisa

2011-01-01

The aim of this paper is to present a shortened version of the SIS (support intensity scale) obtained by the application of mathematical models and instruments, adopting special algorithms based on the most recent developments in artificial adaptive systems. All the variables of SIS applied to 1,052 subjects with ID (intellectual disabilities)…

Simulation System for Making Political and Macroeconomical Decisions and Its Development

NASA Astrophysics Data System (ADS)

Vnukov, A. A.; Blinov, A. E.

2018-01-01

Object of this research are macroeconomic indicators, which are important to descript economic situation in a country. Purpose of this work is to identify these indicators and to analyze how the state can affect these figures with available instruments. Here was constructed a model where the targets can be calculated from raw data - tools in the field of economic policy. Software code that implements all relations among the indicators and allows to analyze with high accuracy, sufficiently successful economic policies and with the help of some tools, you can achieve better results. This model can be used to forecast macroeconomic scenarios. The corresponding values of the objective (outcome) variables are set as a consequence of the configuration data of the previous period, subject to external influences and depend on the instrumental variables. The results may be useful in economical predictions. The results were successfully checked on real scenarios of Russian, European and Chinese economics. Moreover, the results can be applied in the field of education. Program is available to use as “economical game” the educational process of the University, in which you can virtually implement various macroeconomic scenarios, draw conclusions about their success.

The Effect of Community Uninsurance Rates on Access to Health Care

PubMed Central

Sabik, Lindsay M

2012-01-01

Objective To investigate the effect of local uninsurance rates on access to health care for the uninsured and insured and improve on recent studies by controlling for time-invariant differences across markets. Data Sources Individual-level data from the 1996 and 2003 Community Tracking Study, and market-level data from other sources, including the Area Resource File and the Bureau of Primary Healthcare. Study Design Market-level fixed effects models estimate the effect of changes in uninsurance rates within markets on access to care, measured by whether individuals report forgoing necessary care. Instrumental variables models are also estimated. Principal Findings Increases in the rate of uninsurance are associated with poorer access to necessary care among the uninsured. In contrast with recent evidence, increases in uninsurance had no effect on access to care among the insured. Instrumental variables results are similar, although not statistically significant. Conclusions Changes in rates of insurance coverage are likely to affect access to care for both previously and continuously uninsured. In contrast with earlier studies, there is no evidence of spillover effects on the insured, suggesting that such policy changes may have little effect on access for those who are already insured. PMID:22172046

Mission Simulation of Space Lidar Measurements for Seasonal and Regional CO2 Variations

NASA Technical Reports Server (NTRS)

Kawa, Stephan; Collatz, G. J.; Mao, J.; Abshire, J. B.; Sun, X.; Weaver, C. J.

2010-01-01

Results of mission simulation studies are presented for a laser-based atmospheric [82 sounder. The simulations are based on real-time carbon cycle process modeling and data analysis. The mission concept corresponds to the Active Sensing of [82 over Nights, Days, and Seasons (ASCENDS) recommended by the US National Academy of Sciences Decadal Survey of Earth Science and Applications from Space. One prerequisite for meaningful quantitative sensor evaluation is realistic CO2 process modeling across a wide range of scales, i.e., does the model have representative spatial and temporal gradients? Examples of model comparison with data will be shown. Another requirement is a relatively complete description of the atmospheric and surface state, which we have obtained from meteorological data assimilation and satellite measurements from MODIS and [ALIPS0. We use radiative transfer model calculations, an instrument model with representative errors ' and a simple retrieval approach to complete the cycle from "nature" run to "pseudo-data" CO2, Several mission and instrument configuration options are examined/ and the sensitivity to key design variables is shown. We use the simulation framework to demonstrate that within reasonable technological assumptions for the system performance, relatively high measurement precision can be obtained, but errors depend strongly on environmental conditions as well as instrument specifications. Examples are also shown of how the resulting pseudo - measurements might be used to address key carbon cycle science questions.

Extreme Ultraviolet Variability Experiment (EVE) Multiple EUV Grating Spectrographs (MEGS): Radiometric Calibrations and Results

NASA Technical Reports Server (NTRS)

Hock, R. A.; Woods, T. N.; Crotser, D.; Eparvier, F. G.; Woodraska, D. L.; Chamberlin, P. C.; Woods, E. C.

2010-01-01

The NASA Solar Dynamics Observatory (SDO), scheduled for launch in early 2010, incorporates a suite of instruments including the Extreme Ultraviolet Variability Experiment (EVE). EVE has multiple instruments including the Multiple Extreme ultraviolet Grating Spectrographs (MEGS) A, B, and P instruments, the Solar Aspect Monitor (SAM), and the Extreme ultraviolet SpectroPhotometer (ESP). The radiometric calibration of EVE, necessary to convert the instrument counts to physical units, was performed at the National Institute of Standards and Technology (NIST) Synchrotron Ultraviolet Radiation Facility (SURF III) located in Gaithersburg, Maryland. This paper presents the results and derived accuracy of this radiometric calibration for the MEGS A, B, P, and SAM instruments, while the calibration of the ESP instrument is addressed by Didkovsky et al. . In addition, solar measurements that were taken on 14 April 2008, during the NASA 36.240 sounding-rocket flight, are shown for the prototype EVE instruments.

Satisfaction and adherence in patients with iron overload receiving iron chelation therapy as assessed by a newly developed patient instrument.

PubMed

Rofail, Diana; Abetz, Linda; Viala, Muriel; Gait, Claire; Baladi, Jean-Francois; Payne, Krista

2009-01-01

This study assesses satisfaction with iron chelation therapy (ICT) based on a reliable and valid instrument, and explores the relationship between satisfaction and adherence to ICT. Patients in the USA and UK completed a new "Satisfaction with ICT" (SICT) instrument consisting of 28 items, three pertaining to adherence. Simple and multivariate regression analyses assessed the relationship between satisfaction with different aspects of ICT and adherence. First assessments of the SICT instrument indicate its validity and reliability. Recommended thresholds for internal consistency, convergent validity, discriminant validity, and floor and ceiling effects were met. A number of variables were identified in the simple linear regression analyses as significant predictors of "never thinking about stopping ICT," a proxy for adherence. These significant variables were entered into the multivariate model to assess the combined factor effects, explaining 42% of the total variance of "never thinking about stopping ICT." A significant and positive relationship was demonstrated between "never thinking about stopping ICT" and age (P = 0.04), Perceived Effectiveness of ICT (P = 0.003), low Burden of ICT (P = 0.002), and low Side Effects of ICT (P = 0.01). The SICT is a reliable and valid instrument which will be useful in ICT clinical trials. Furthermore, the administration of ICT by slow subcutaneous infusion negatively impacts on satisfaction with ICT which was shown to be a determinant of adherence. This points to the need for new more convenient and less burdensome oral iron chelators to increase adherence, and ultimately to improve patient outcomes.

Validation of a Theory of Planned Behavior-Based Questionnaire to Examine Factors Associated With Milk Expression.

PubMed

Bai, Yeon K; Dinour, Lauren M

2017-11-01

A proper assessment of multidimensional needs for breastfeeding mothers in various settings is crucial to facilitate and support breastfeeding and its exclusivity. The theory of planned behavior (TPB) has been used frequently to measure factors associated with breastfeeding. Full utility of the TPB requires accurate measurement of theory constructs. Research aim: This study aimed to develop and confirm the psychometric properties of an instrument, Milk Expression on Campus, based on the TPB and to establish the reliability and validity of the instrument. In spring 2015, 218 breastfeeding (current or in the recent past) employees and students at one university campus in northern New Jersey completed the online questionnaire containing demography and theory-based items. Internal consistency (α) and split-half reliability ( r) tests and factor analyses established and confirmed the reliability and construct validity of this instrument. Milk Expression on Campus showed strong and significant reliabilities as a full scale (α = .78, r = .74, p < .001) and theory construct subscales. Validity was confirmed as psychometric properties corresponded to the factors extracted from the scale. Four factors extracted from the direct construct subscales accounted for 79.49% of the total variability. Four distinct factors from the indirect construct subscales accounted for 73.68% of the total variability. Milk Expression on Campus can serve as a model TPB-based instrument to examine factors associated with women's milk expression behavior. The utility of this instrument extends to designing effective promotion programs to foster breastfeeding and milk expression behaviors in diverse settings.

Considering quality of life for children with cancer: a systematic review of patient-reported outcome measures and the development of a conceptual model.

PubMed

Anthony, Samantha J; Selkirk, Enid; Sung, Lillian; Klaassen, Robert J; Dix, David; Scheinemann, Katrin; Klassen, Anne F

2014-04-01

An appraisal of pediatric cancer-specific quality-of-life (QOL) instruments revealed a lack of clarity about what constitutes QOL in this population. This study addresses this concern by identifying the concepts that underpin the construct of QOL as determined by a content analysis of all patient-reported outcome (PRO) instruments used in childhood cancer research. A systematic review was performed of key databases (i.e., MEDLINE, CINAHL, PsychINFO) to identify studies of QOL in children with cancer. A content analysis process was used to code and categorize all items from generic and cancer-specified PRO instruments. Our objective was to provide clarification regarding the conceptual underpinnings of these instruments, as well as to help inform the development of theory and contribute to building a conceptual framework of QOL for children with cancer. A total of 6,013 English language articles were screened, identifying 148 studies. Ten generic and ten cancer-specific PRO instruments provided 957 items. Content analysis led to the identification of four major domains of QOL (physical, psychological, social, and general health), with 11 subdomains covering 98 different concepts. While all instruments reflected items relating to the broader domains of QOL, there was substantial heterogeneity in terms of the content and variability in the distribution of items. This systematic review and the proposed model represent a useful starting point in the critical appraisal of the conceptual underpinnings of PRO instruments used in pediatric oncology and contribute to the need to place such tools under a critical, yet reflective and analytical lens.

Improved Stratospheric Temperature Retrievals for Climate Reanalysis

NASA Technical Reports Server (NTRS)

Rokke, L.; Joiner, J.

1999-01-01

The Data Assimilation Office (DAO) is embarking on plans to generate a twenty year reanalysis data set of climatic atmospheric variables. One of the focus points will be in the evaluation of the dynamics of the stratosphere. The Stratospheric Sounding Unit (SSU), flown as part of the TIROS Operational Vertical Sounder (TOVS), is one of the primary stratospheric temperature sensors flown consistently throughout the reanalysis period. Seven unique sensors made the measurements over time, with individual instrument characteristics that need to be addressed. The stratospheric temperatures being assimilated across satellite platforms will profoundly impact the reanalysis dynamical fields. To attempt to quantify aspects of instrument and retrieval bias we are carefully collecting and analyzing all available information on the sensors, their instrument anomalies, forward model errors and retrieval biases. For the retrieval of stratospheric temperatures, we adapted the minimum variance approach of Jazwinski (1970) and Rodgers (1976) and applied it to the SSU soundings. In our algorithm, the state vector contains an initial guess of temperature from a model six hour forecast provided by the Goddard EOS Data Assimilation System (GEOS/DAS). This is combined with an a priori covariance matrix, a forward model parameterization, and specifications of instrument noise characteristics. A quasi-Newtonian iteration is used to obtain convergence of the retrieved state to the measurement vector. This algorithm also enables us to analyze and address the systematic errors associated with the unique characteristics of the cell pressures on the individual SSU instruments and the resolving power of the instruments to vertical gradients in the stratosphere. The preliminary results of the improved retrievals and their assimilation as well as baseline calculations of bias and rms error between the NESDIS operational product and col-located ground measurements will be presented.

External forcing as a metronome for Atlantic multidecadal variability

NASA Astrophysics Data System (ADS)

Otterå, Odd Helge; Bentsen, Mats; Drange, Helge; Suo, Lingling

2010-10-01

Instrumental records, proxy data and climate modelling show that multidecadal variability is a dominant feature of North Atlantic sea-surface temperature variations, with potential impacts on regional climate. To understand the observed variability and to gauge any potential for climate predictions it is essential to identify the physical mechanisms that lead to this variability, and to explore the spatial and temporal characteristics of multidecadal variability modes. Here we use a coupled ocean-atmosphere general circulation model to show that the phasing of the multidecadal fluctuations in the North Atlantic during the past 600 years is, to a large degree, governed by changes in the external solar and volcanic forcings. We find that volcanoes play a particularly important part in the phasing of the multidecadal variability through their direct influence on tropical sea-surface temperatures, on the leading mode of northern-hemisphere atmosphere circulation and on the Atlantic thermohaline circulation. We suggest that the implications of our findings for decadal climate prediction are twofold: because volcanic eruptions cannot be predicted a decade in advance, longer-term climate predictability may prove challenging, whereas the systematic post-eruption changes in ocean and atmosphere may hold promise for shorter-term climate prediction.

Protecting children from myopia: a PMT perspective for improving health marketing communications.

PubMed

Lwin, May O; Saw, Seang-Mei

2007-01-01

This research examined the predictive utility of the protection motivation theory (PMT) model for myopia prevention amongst children. An integrative model for myopia prevention behavior of parents was first developed in the context of theory and survey instruments then refined using information gathered from two focus groups. Empirical data then was collected from parents of primary school children in Singapore, a country with one of the highest rates of myopia in the world, and analyzed using structural equation modeling (SEM). Our findings revealed that coping appraisal variables were more significantly associated with protection motivation, relative to threat appraisal variables. In particular, perceived self-efficacy was the strongest predictor of parental intention to enforce good visual health behaviors, while perceived severity was relatively weak. Health marketing communications and public policy implications are discussed.

Price responsiveness of demand for cigarettes: does rationality matter?

PubMed

Laporte, Audrey

2006-01-01

Meta-analysis is applied to aggregate-level studies that model the demand for cigarettes using static, myopic, or rational addiction frameworks in an attempt to synthesize key findings in the literature and to identify determinants of the variation in reported price elasticity estimates across studies. The results suggest that the rational addiction framework produces statistically similar estimates to the static framework but that studies that use the myopic framework tend to report more elastic price effects. Studies that applied panel data techniques or controlled for cross-border smuggling reported more elastic price elasticity estimates, whereas the use of instrumental variable techniques and time trends or time dummy variables produced less elastic estimates. The finding that myopic models produce different estimates than either of the other two model frameworks underscores that careful attention must be given to time series properties of the data.

Breastfeeding and the risk of childhood asthma: A two-stage instrumental variable analysis to address endogeneity.

PubMed

Sharma, Nivita D

2017-09-01

Several explanations for the inconsistent results on the effects of breastfeeding on childhood asthma have been suggested. The purpose of this study was to investigate one unexplored explanation, which is the presence of a potential endogenous relationship between breastfeeding and childhood asthma. Endogeneity exists when an explanatory variable is correlated with the error term for reasons such as selection bias, reverse causality, and unmeasured confounders. Unadjusted endogeneity will bias the effect of breastfeeding on childhood asthma. To investigate potential endogeneity, a cross-sectional study of breastfeeding practices and incidence of childhood asthma in 87 pediatric patients in Georgia, the USA, was conducted using generalized linear modeling and a two-stage instrumental variable analysis. First, the relationship between breastfeeding and childhood asthma was analyzed without considering endogeneity. Second, tests for presence of endogeneity were performed and having detected endogeneity between breastfeeding and childhood asthma, a two-stage instrumental variable analysis was performed. The first stage of this analysis estimated the duration of breastfeeding and the second-stage estimated the risk of childhood asthma. When endogeneity was not taken into account, duration of breastfeeding was found to significantly increase the risk of childhood asthma (relative risk ratio [RR]=2.020, 95% confidence interval [CI]: [1.143-3.570]). After adjusting for endogeneity, duration of breastfeeding significantly reduced the risk of childhood asthma (RR=0.003, 95% CI: [0.000-0.240]). The findings suggest that researchers should consider evaluating how the presence of endogeneity could affect the relationship between duration of breastfeeding and the risk of childhood asthma. © 2017 EAACI and John Wiley and Sons A/S. Published by John Wiley and Sons Ltd.

The FLEXTRA kit: a model for instructor support materials.

PubMed

Battles, J B; Sheridan, M M

1989-01-01

The FLEXTRA Kit is a model for the development of resource materials to support instructor-delivered continuing education. Each FLEXTRA Kit consists of camera-ready copy of handout materials; presentation slides, overheads, videotapes, etc.; evaluation instruments; and an instructor's guide. The FLEXTRA Kit is packaged in such a way that it can be easily shipped and stored. Desktop publishing makes the production of FLEXTRA Kits a cost-effective means of providing support to repeated and locally variable training events.

High energy variability of 3C 273 during the AGILE multiwavelength campaign of December 2007-January 2008

NASA Astrophysics Data System (ADS)

Pacciani, L.; Donnarumma, I.; Vittorini, V.; D'Ammando, F.; Fiocchi, M. T.; Impiombato, D.; Stratta, G.; Verrecchia, F.; Bulgarelli, A.; Chen, A. W.; Giuliani, A.; Longo, F.; Pucella, G.; Vercellone, S.; Tavani, M.; Argan, A.; Barbiellini, G.; Boffelli, F.; Caraveo, P. A.; Cattaneo, P. W.; Cocco, V.; Costa, E.; Del Monte, E.; Di Cocco, G.; Evangelista, Y.; Feroci, M.; Froysland, T.; Fuschino, F.; Galli, M.; Gianotti, F.; Labanti, C.; Lapshov, I.; Lazzarotto, F.; Lipari, P.; Marisaldi, M.; Mereghetti, S.; Morselli, A.; Pellizzoni, A.; Perotti, F.; Picozza, P.; Prest, M.; Rapisarda, M.; Soffitta, P.; Trifoglio, M.; Tosti, G.; Trois, A.; Vallazza, E.; Zanello, D.; Antonelli, L. A.; Colafrancesco, S.; Cutini, S.; Gasparrini, D.; Giommi, P.; Pittori, C.; Salotti, L.

2009-01-01

Context: We report the results of a 3-week multi-wavelength campaign targeting the flat spectrum radio quasar 3C 273 carried out with the AGILE gamma-ray mission, covering the 30 MeV-50 GeV and 18-60 keV, the REM observatory (covering the near-IR and optical), Swift (near-UV/Optical, 0.2-10 keV and 15-50 keV), INTEGRAL (3-200 keV) and Rossi XTE (2-12 keV). This is the first observational campaign including gamma-ray data, after the last EGRET observations, more than 8 years ago. Aims: This campaign has been organized by the AGILE team with the aim of observing, studying and modelling the broad band energy spectrum of the source, and its variability on a week timescale, testing the emission models describing the spectral energy distribution of this source. Methods: Our study was carried out using simultaneous light curves of the source flux from all the involved instruments, in the different energy ranges, to search for correlated variability. Then a time-resolved spectral energy distribution was used for a detailed physical modelling of the emission mechanisms. Results: The source was detected in gamma-rays only in the second week of our campaign, with a flux comparable to the level detected by EGRET in June 1991. We found an indication of a possible anti-correlation between the emission at gamma-rays and at soft and hard X-rays, supported by the complete set of instruments. Instead, optical data do not show short term variability, as expected for this source. Only in two preceding EGRET observations (in 1993 and 1997) 3C 273 showed intra-observation variability in gamma-rays. In the 1997 observation, flux variation in gamma-rays was associated with a synchrotron flare. The energy-density spectrum with almost simultaneous data partially covers the regions of synchrotron emission, the big blue bump, and the inverse-Compton. We adopted a leptonic model to explain the hard X/gamma-ray emissions, although from our analysis hadronic models cannot be ruled out. In the adopted model, the soft X-ray emission is consistent with combined synchrotron-self Compton and external Compton mechanisms, while hard X and gamma-ray emissions are compatible with external Compton from thermal photons of the disk. Under this model, the time evolution of the spectral energy distribution is well interpreted and modelled in terms of an acceleration episode of the electron population, leading to a shift in the inverse Compton peak towards higher energies.

Cross-cultural validation of instruments measuring health beliefs about colorectal cancer screening among Korean Americans.

PubMed

Lee, Shin-Young; Lee, Eunice E

2015-02-01

The purpose of this study was to report the instrument modification and validation processes to make existing health belief model scales culturally appropriate for Korean Americans (KAs) regarding colorectal cancer (CRC) screening utilization. Instrument translation, individual interviews using cognitive interviewing, and expert reviews were conducted during the instrument modification phase, and a pilot test and a cross-sectional survey were conducted during the instrument validation phase. Data analyses of the cross-sectional survey included internal consistency and construct validity using exploratory and confirmatory factor analysis. The main issues identified during the instrument modification phase were (a) cultural and linguistic translation issues and (b) newly developed items reflecting Korean cultural barriers. Cross-sectional survey analyses during the instrument validation phase revealed that all scales demonstrate good internal consistency reliability (Cronbach's alpha=.72~.88). Exploratory factor analysis showed that susceptibility and severity loaded on the same factor, which may indicate a threat variable. Items with low factor loadings in the confirmatory factor analysis may relate to (a) lack of knowledge about fecal occult blood testing and (b) multiple dimensions of the subscales. Methodological, sequential processes of instrument modification and validation, including translation, individual interviews, expert reviews, pilot testing and a cross-sectional survey, were provided in this study. The findings indicate that existing instruments need to be examined for CRC screening research involving KAs.

A critical re-evaluation of the regression model specification in the US D1 EQ-5D value function

PubMed Central

2012-01-01

Background The EQ-5D is a generic health-related quality of life instrument (five dimensions with three levels, 243 health states), used extensively in cost-utility/cost-effectiveness analyses. EQ-5D health states are assigned values on a scale anchored in perfect health (1) and death (0). The dominant procedure for defining values for EQ-5D health states involves regression modeling. These regression models have typically included a constant term, interpreted as the utility loss associated with any movement away from perfect health. The authors of the United States EQ-5D valuation study replaced this constant with a variable, D1, which corresponds to the number of impaired dimensions beyond the first. The aim of this study was to illustrate how the use of the D1 variable in place of a constant is problematic. Methods We compared the original D1 regression model with a mathematically equivalent model with a constant term. Comparisons included implications for the magnitude and statistical significance of the coefficients, multicollinearity (variance inflation factors, or VIFs), number of calculation steps needed to determine tariff values, and consequences for tariff interpretation. Results Using the D1 variable in place of a constant shifted all dummy variable coefficients away from zero by the value of the constant, greatly increased the multicollinearity of the model (maximum VIF of 113.2 vs. 21.2), and increased the mean number of calculation steps required to determine health state values. Discussion Using the D1 variable in place of a constant constitutes an unnecessary complication of the model, obscures the fact that at least two of the main effect dummy variables are statistically nonsignificant, and complicates and biases interpretation of the tariff algorithm. PMID:22244261

A critical re-evaluation of the regression model specification in the US D1 EQ-5D value function.

PubMed

Rand-Hendriksen, Kim; Augestad, Liv A; Dahl, Fredrik A

2012-01-13

The EQ-5D is a generic health-related quality of life instrument (five dimensions with three levels, 243 health states), used extensively in cost-utility/cost-effectiveness analyses. EQ-5D health states are assigned values on a scale anchored in perfect health (1) and death (0).The dominant procedure for defining values for EQ-5D health states involves regression modeling. These regression models have typically included a constant term, interpreted as the utility loss associated with any movement away from perfect health. The authors of the United States EQ-5D valuation study replaced this constant with a variable, D1, which corresponds to the number of impaired dimensions beyond the first. The aim of this study was to illustrate how the use of the D1 variable in place of a constant is problematic. We compared the original D1 regression model with a mathematically equivalent model with a constant term. Comparisons included implications for the magnitude and statistical significance of the coefficients, multicollinearity (variance inflation factors, or VIFs), number of calculation steps needed to determine tariff values, and consequences for tariff interpretation. Using the D1 variable in place of a constant shifted all dummy variable coefficients away from zero by the value of the constant, greatly increased the multicollinearity of the model (maximum VIF of 113.2 vs. 21.2), and increased the mean number of calculation steps required to determine health state values. Using the D1 variable in place of a constant constitutes an unnecessary complication of the model, obscures the fact that at least two of the main effect dummy variables are statistically nonsignificant, and complicates and biases interpretation of the tariff algorithm.

Instrumental intelligent test of food sensory quality as mimic of human panel test combining multiple cross-perception sensors and data fusion.

PubMed

Ouyang, Qin; Zhao, Jiewen; Chen, Quansheng

2014-09-02

Instrumental test of food quality using perception sensors instead of human panel test is attracting massive attention recently. A novel cross-perception multi-sensors data fusion imitating multiple mammal perception was proposed for the instrumental test in this work. First, three mimic sensors of electronic eye, electronic nose and electronic tongue were used in sequence for data acquisition of rice wine samples. Then all data from the three different sensors were preprocessed and merged. Next, three cross-perception variables i.e., color, aroma and taste, were constructed using principal components analysis (PCA) and multiple linear regression (MLR) which were used as the input of models. MLR, back-propagation artificial neural network (BPANN) and support vector machine (SVM) were comparatively used for modeling, and the instrumental test was achieved for the comprehensive quality of samples. Results showed the proposed cross-perception multi-sensors data fusion presented obvious superiority to the traditional data fusion methodologies, also achieved a high correlation coefficient (>90%) with the human panel test results. This work demonstrated that the instrumental test based on the cross-perception multi-sensors data fusion can actually mimic the human test behavior, therefore is of great significance to ensure the quality of products and decrease the loss of the manufacturers. Copyright © 2014 Elsevier B.V. All rights reserved.

Linking the variability of atmospheric carbon monoxide to climate modes in the Southern Hemisphere

NASA Astrophysics Data System (ADS)

Buchholz, Rebecca; Monks, Sarah; Hammerling, Dorit; Worden, Helen; Deeter, Merritt; Emmons, Louisa; Edwards, David

2017-04-01

Biomass burning is a major driver of atmospheric carbon monoxide (CO) variability in the Southern Hemisphere. The magnitude of emissions, such as CO, from biomass burning is connected to climate through both the availability and dryness of fuel. We investigate the link between CO and climate using satellite measured CO and climate indices. Observations of total column CO from the satellite instrument MOPITT are used to build a record of interannual variability in CO since 2001. Four biomass burning regions in the Southern Hemisphere are explored. Data driven relationships are determined between CO and climate indices for the climate modes: El Niño Southern Oscillation (ENSO); the Indian Ocean Dipole (IOD); the Tropical Southern Atlantic (TSA); and the Southern Annular Mode (SAM). Stepwise forward and backward regression is used to select the best statistical model from combinations of lagged indices. We find evidence for the importance of first-order interaction terms of the climate modes when explaining CO variability. Implications of the model results are discussed for the Maritime Southeast Asia and Australasia regions. We also draw on the chemistry-climate model CAM-chem to explain the source contribution as well as the relative contributions of emissions and meteorology to CO variability.

The productivity of mental health care: an instrumental variable approach.

PubMed

Lu, Mingshan

1999-06-01

BACKGROUND: Like many other medical technologies and treatments, there is a lack of reliable evidence on treatment effectiveness of mental health care. Increasingly, data from non-experimental settings are being used to study the effect of treatment. However, as in a number of studies using non-experimental data, a simple regression of outcome on treatment shows a puzzling negative and significant impact of mental health care on the improvement of mental health status, even after including a large number of potential control variables. The central problem in interpreting evidence from real-world or non-experimental settings is, therefore, the potential "selection bias" problem in observational data set. In other words, the choice/quantity of mental health care may be correlated with other variables, particularly unobserved variables, that influence outcome and this may lead to a bias in the estimate of the effect of care in conventional models. AIMS OF THE STUDY: This paper addresses the issue of estimating treatment effects using an observational data set. The information in a mental health data set obtained from two waves of data in Puerto Rico is explored. The results using conventional models - in which the potential selection bias is not controlled - and that from instrumental variable (IV) models - which is what was proposed in this study to correct for the contaminated estimation from conventional models - are compared. METHODS: Treatment effectiveness is estimated in a production function framework. Effectiveness is measured as the improvement in mental health status. To control for the potential selection bias problem, IV approaches are employed. The essence of the IV method is to use one or more instruments, which are observable factors that influence treatment but do not directly affect patient outcomes, to isolate the effect of treatment variation that is independent of unobserved patient characteristics. The data used in this study are the first (1992-1993) and second (1993-1994) wave of the ongoing longitudinal study Mental Health Care Utilization Among Puerto Ricans, which includes information for an island-wide probability sample of over 3000 adults living in poor areas of Puerto Rico. The instrumental variables employed in this study are travel distance and health insurance sources. RESULTS: It is very noticeable that in this study, treatment effects were found to be negative in all conventional models (in some cases, highly significant). However, after the IV method was applied, the estimated marginal effects of treatment became positive. Sensitivity analysis partly supports this conclusion. According to the IV estimation results, treatment is productive for the group in most need of mental health care. However, estimations do not find strong enough evidence to demonstrate treatment effects on other groups with less or no need. The results in this paper also suggest an important impact of the following factors on the probability of improvement in mental health status: baseline mental health status, previous treatment, sex, marital status and education. DISCUSSION: The IV approach provides a practical way to reduce the selection bias due to the confounding of treatment with unmeasured variables. The limitation of this study is that the instruments explored did not perform well enough in some IV equations, therefore the predictive power remains questionable. The most challenging part of applying the IV approach is on finding "good" instruments which influence the choice/quantity of treatment yet do not introduce further bias by being directly correlated with treatment outcome. CONCLUSIONS: The results in this paper are supportive of the concerns on the credibility of evaluation results using observation data set when the endogeneity of the treatment variable is not controlled. Unobserved factors contribute to the downward bias in the conventional models. The IV approach is shown to be an appropriate method to reduce the selection bias for the group in most need for mental health care, which is also the group of most policy and treatment concern. IMPLICATIONS FOR HEALTH CARE PROVISION AND USE: The results of this work have implications for resource allocation in mental health care. Evidence is found that mental health care provided in Puerto Rico is productive, and is most helpful for persons in most need for mental health care. According to what estimated from the IV models, on the margin, receiving formal mental health care significantly increases the probability of obtaining a better mental health outcome by 19.2%, and one unit increase in formal treatment increased the probability of becoming healthier by 6.2% to 8.4%. Consistent with other mental health literature, an individual's baseline mental health status is found to be significantly related to the probability of improvement in mental health status: individuals with previous treatment history are less likely to improve. Among demographic factors included in the production function, being female, married, and high education were found to contribute to a higher probability of improvement. IMPLICATION FOR FURTHER RESEARCH: In order to provide accurate evidence of treatment effectiveness of medical technologies to support decision making, it is important that the selection bias be controlled as rigorously as possible when using information from a non-experimental setting. More data and a longer panel are also needed to provide more valid evidence. tion.

Genetic markers as instrumental variables.

PubMed

von Hinke, Stephanie; Davey Smith, George; Lawlor, Debbie A; Propper, Carol; Windmeijer, Frank

2016-01-01

The use of genetic markers as instrumental variables (IV) is receiving increasing attention from economists, statisticians, epidemiologists and social scientists. Although IV is commonly used in economics, the appropriate conditions for the use of genetic variants as instruments have not been well defined. The increasing availability of biomedical data, however, makes understanding of these conditions crucial to the successful use of genotypes as instruments. We combine the econometric IV literature with that from genetic epidemiology, and discuss the biological conditions and IV assumptions within the statistical potential outcomes framework. We review this in the context of two illustrative applications. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

RLS Instrument Radiometric Model: Instrument performance theoretical evaluation and experimental checks

NASA Astrophysics Data System (ADS)

Quintana, César; Ramos, Gonzalo; Moral, Andoni; Rodriguez, Jose Antonio; Pérez, Carlos; Hutchinson, Ian; INGLEY, Richard; Rull, Fernando

2016-10-01

Raman Laser Spectrometer (RLS) is one of the Pasteur payload instruments located at the Rover of the ExoMars mission and within the ESA's Aurora Exploration Programme. RLS will explore the Mars surface composition through the Raman spectroscopy technique. The instrument is divided into several units: a laser for Raman emission stimulation, an internal optical head (iOH) for sample excitation and for Raman emission recovering, a spectrometer with a CCD located at its output (SPU), the optical harness (OH) for the units connection, from the laser to the excitation path of the iOH and from the iOH reception path to the spectrometer, and the corresponding electronics for the CCD operation.Due to the variability of the samples to be analyzed on Mars, a radiometry prediction for the instrument performance results to be of the critical importance. In such a framework, and taking into account the SNR (signal to noise ratio) required for the achievement of successful results from the scientific point of view (a proper information about the Mars surface composition), a radiometric model has been developed to provide the requirements for the different units, i.e. the laser irradiance, the iOH, OH, and SPU throughputs, and the samples that will be possible to be analyzed in terms of its Raman emission and the relationship of the Raman signal with respect to fluorescence emission, among others.The radiometric model fundamentals (calculations and approximations), as well as the first results obtained during the bread board characterization campaign are here reported on.

The Paired Availability Design and Related Instrumental Variable Meta-analyses | Division of Cancer Prevention

Cancer.gov

Stuart G. Baker, 2017 Introduction This software computes meta-analysis and extrapolation estimates for an instrumental variable meta-analysis of randomized trial or before-and-after studies (the latter also known as the paired availability design). The software also checks on the assumptions if sufficient data are available. |

[Modeling employee stress in psychiatric rehabilitation--effects of personal and organizational factors].

PubMed

Queri, S; Konrad, M; Keller, K

2012-08-01

Increasing stress-associated health problems in Germany often are attributed to problems on the job, in particular to rising work demands. The study includes several stress predictors from other results and from literature in one predictive model for the field of work of "psychiatric rehabilitation".A cross-sectional design was used to measure personal and organizational variables with quantitative standard questionnaires as self-ratings from n=243 pedagogically active employees from various professions. Overall stress and job stress were measured with different instruments.The sample showed above-average overall stress scores along with below-average job stress scores. The multivariate predictive model for explaining the heightened stress shows pathogenetic and salutogenetic main effects for organizational variables such as "gratification crisis" and personal variables such as "occupational self-efficacy expectations" as well as an interaction of both types of variables. There are relevant gender-specific results concerning empathy and differences between professions concerning the extent of occupational self-efficacy.The results are a matter of particular interest for the practice of workplace health promotion as well as for social work schools, the main group in our sample being social workers. © Georg Thieme Verlag KG Stuttgart · New York.

An Undergraduate Research Experience on Studying Variable Stars

NASA Astrophysics Data System (ADS)

Amaral, A.; Percy, J. R.

2016-06-01

We describe and evaluate a summer undergraduate research project and experience by one of us (AA), under the supervision of the other (JP). The aim of the project was to sample current approaches to analyzing variable star data, and topics related to the study of Mira variable stars and their astrophysical importance. This project was done through the Summer Undergraduate Research Program (SURP) in astronomy at the University of Toronto. SURP allowed undergraduate students to explore and learn about many topics within astronomy and astrophysics, from instrumentation to cosmology. SURP introduced students to key skills which are essential for students hoping to pursue graduate studies in any scientific field. Variable stars proved to be an excellent topic for a research project. For beginners to independent research, it introduces key concepts in research such as critical thinking and problem solving, while illuminating previously learned topics in stellar physics. The focus of this summer project was to compare observations with structural and evolutionary models, including modelling the random walk behavior exhibited in the (O-C) diagrams of most Mira stars. We found that the random walk could be modelled by using random fluctuations of the period. This explanation agreed well with observations.

Job demands and job strain as risk factors for employee wellbeing in elderly care: an instrumental-variables analysis.

PubMed

Elovainio, Marko; Heponiemi, Tarja; Kuusio, Hannamaria; Jokela, Markus; Aalto, Anna-Mari; Pekkarinen, Laura; Noro, Anja; Finne-Soveri, Harriet; Kivimäki, Mika; Sinervo, Timo

2015-02-01

The association between psychosocial work environment and employee wellbeing has repeatedly been shown. However, as environmental evaluations have typically been self-reported, the observed associations may be attributable to reporting bias. Applying instrumental-variable regression, we used staffing level (the ratio of staff to residents) as an unconfounded instrument for self-reported job demands and job strain to predict various indicators of wellbeing (perceived stress, psychological distress and sleeping problems) among 1525 registered nurses, practical nurses and nursing assistants working in elderly care wards. In ordinary regression, higher self-reported job demands and job strain were associated with increased risk of perceived stress, psychological distress and sleeping problems. The effect estimates for the associations of these psychosocial factors with perceived stress and psychological distress were greater, but less precisely estimated, in an instrumental-variables analysis which took into account only the variation in self-reported job demands and job strain that was explained by staffing level. No association between psychosocial factors and sleeping problems was observed with the instrumental-variable analysis. These results support a causal interpretation of high self-reported job demands and job strain being risk factors for employee wellbeing. © The Author 2014. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

The impact of fashion competence and achievement motivation toward college student’s working readiness on “Cipta Karya” subject

NASA Astrophysics Data System (ADS)

Marniati; Wibawa, S. C.

2018-01-01

This experiment aimed to know the rate of college student’s working readiness of fashion’s program study to perform ‘Cipta Karya’ related to cognitive readiness, manner readiness and skill readiness from a variable of fashion’s workmanship and achievement motivation. The subject of the experiment was 43 college students who took Cipta Karya subject. Method of collecting data used questionnaire with five alternative answers to Likert ratio model. Data analysis technique used path analysis (double regression). The instrument validity test used product moment correlation while for instrument reliability used Alpha Cronbach’s grade. The results showed (1) fashion competence was taking effect significantly on working readiness for ‘Cipta Karya’ (2) achievement motivation is taking effect significantly on working readiness for ‘cipta karya’ (3) both variables are positive. This means that fashion competence and achievement motivation have a positive effect on working readiness for ‘cipta karya’ performance.

Detection of carbon monoxide trends in the presence of interannual variability

NASA Astrophysics Data System (ADS)

Strode, Sarah A.; Pawson, Steven

2013-11-01

in fossil fuel emissions are a major driver of changes in atmospheric CO, but detection of trends in CO from anthropogenic sources is complicated by the presence of large interannual variability (IAV) in biomass burning. We use a multiyear model simulation of CO with year-specific biomass burning to predict the number of years needed to detect the impact of changes in Asian anthropogenic emissions on downwind regions. Our study includes two cases for changing anthropogenic emissions: a stepwise change of 15% and a linear trend of 3% yr-1. We first examine how well the model reproduces the observed IAV of CO over the North Pacific, since this variability impacts the time needed to detect significant anthropogenic trends. The modeled IAV over the North Pacific correlates well with that seen from the Measurements of Pollution in the Troposphere (MOPITT) instrument but underestimates the magnitude of the variability. The model predicts that a 3% yr-1 trend in Asian anthropogenic emissions would lead to a statistically significant trend in CO surface concentration in the western United States within 12 years, and accounting for Siberian boreal biomass-burning emissions greatly reduces the number of years needed for trend detection. Combining the modeled trend with the observed MOPITT variability at 500 hPa, we estimate that the 3% yr-1 trend could be detectable in satellite observations over Asia in approximately a decade. Our predicted timescales for trend detection highlight the importance of long-term measurements of CO from satellites.

Optical wavelength selection for portable hemoglobin determination by near-infrared spectroscopy method

NASA Astrophysics Data System (ADS)

Tian, Han; Li, Ming; Wang, Yue; Sheng, Dinggao; Liu, Jun; Zhang, Linna

2017-11-01

Hemoglobin concentration is commonly used in clinical medicine to diagnose anemia, identify bleeding, and manage red blood cell transfusions. The golden standard method for determining hemoglobin concentration in blood requires reagent. Spectral methods were advantageous at fast and non-reagent measurement. However, model calibration with full spectrum is time-consuming. Moreover, it is necessary to use a few variables considering size and cost of instrumentation, especially for a portable biomedical instrument. This study presents different wavelength selection methods for optical wavelengths for total hemoglobin concentration determination in whole blood. The results showed that modelling using only two wavelengths combination (1143 nm, 1298 nm) can keep on the fine predictability with full spectrum. It appears that the proper selection of optical wavelengths can be more effective than using the whole spectra for determination hemoglobin in whole blood. We also discussed the influence of water absorptivity on the wavelength selection. This research provides valuable references for designing portable NIR instruments determining hemoglobin concentration, and may provide some experience for noninvasive hemoglobin measurement by NIR methods.

Wind tunnel measurements of the power output variability and unsteady loading in a micro wind farm model

NASA Astrophysics Data System (ADS)

Bossuyt, Juliaan; Howland, Michael; Meneveau, Charles; Meyers, Johan

2015-11-01

To optimize wind farm layouts for a maximum power output and wind turbine lifetime, mean power output measurements in wind tunnel studies are not sufficient. Instead, detailed temporal information about the power output and unsteady loading from every single wind turbine in the wind farm is needed. A very small porous disc model with a realistic thrust coefficient of 0.75 - 0.85, was designed. The model is instrumented with a strain gage, allowing measurements of the thrust force, incoming velocity and power output with a frequency response up to the natural frequency of the model. This is shown by reproducing the -5/3 spectrum from the incoming flow. Thanks to its small size and compact instrumentation, the model allows wind tunnel studies of large wind turbine arrays with detailed temporal information from every wind turbine. Translating to field conditions with a length-scale ratio of 1:3,000 the frequencies studied from the data reach from 10-4 Hz up to about 6 .10-2 Hz. The model's capabilities are demonstrated with a large wind farm measurement consisting of close to 100 instrumented models. A high correlation is found between the power outputs of stream wise aligned wind turbines, which is in good agreement with results from prior LES simulations. Work supported by ERC (ActiveWindFarms, grant no. 306471) and by NSF (grants CBET-113380 and IIA-1243482, the WINDINSPIRE project).

Influence of therapist competence and quantity of cognitive behavioural therapy on suicidal behaviour and inpatient hospitalisation in a randomised controlled trial in borderline personality disorder: further analyses of treatment effects in the BOSCOT study.

PubMed

Norrie, John; Davidson, Kate; Tata, Philip; Gumley, Andrew

2013-09-01

We investigated the treatment effects reported from a high-quality randomized controlled trial of cognitive behavioural therapy (CBT) for 106 people with borderline personality disorder attending community-based clinics in the UK National Health Service - the BOSCOT trial. Specifically, we examined whether the amount of therapy and therapist competence had an impact on our primary outcome, the number of suicidal acts, using instrumental variables regression modelling. Randomized controlled trial. Participants from across three sites (London, Glasgow, and Ayrshire/Arran) were randomized equally to CBT for personality disorders (CBTpd) plus Treatment as Usual or to Treatment as Usual. Treatment as Usual varied between sites and individuals, but was consistent with routine treatment in the UK National Health Service at the time. CBTpd comprised an average 16 sessions (range 0-35) over 12 months. We used instrumental variable regression modelling to estimate the impact of quantity and quality of therapy received (recording activities and behaviours that took place after randomization) on number of suicidal acts and inpatient psychiatric hospitalization. A total of 101 participants provided full outcome data at 2 years post randomization. The previously reported intention-to-treat (ITT) results showed on average a reduction of 0.91 (95% confidence interval 0.15-1.67) suicidal acts over 2 years for those randomized to CBT. By incorporating the influence of quantity of therapy and therapist competence, we show that this estimate of the effect of CBTpd could be approximately two to three times greater for those receiving the right amount of therapy from a competent therapist. Trials should routinely control for and collect data on both quantity of therapy and therapist competence, which can be used, via instrumental variable regression modelling, to estimate treatment effects for optimal delivery of therapy. Such estimates complement rather than replace the ITT results, which are properly the principal analysis results from such trials. © 2013 The British Psychological Society.

Versailles Project on Advanced Materials and Standards Interlaboratory Study on Measuring the Thickness and Chemistry of Nanoparticle Coatings Using XPS and LEIS.

PubMed

Belsey, Natalie A; Cant, David J H; Minelli, Caterina; Araujo, Joyce R; Bock, Bernd; Brüner, Philipp; Castner, David G; Ceccone, Giacomo; Counsell, Jonathan D P; Dietrich, Paul M; Engelhard, Mark H; Fearn, Sarah; Galhardo, Carlos E; Kalbe, Henryk; Won Kim, Jeong; Lartundo-Rojas, Luis; Luftman, Henry S; Nunney, Tim S; Pseiner, Johannes; Smith, Emily F; Spampinato, Valentina; Sturm, Jacobus M; Thomas, Andrew G; Treacy, Jon P W; Veith, Lothar; Wagstaffe, Michael; Wang, Hai; Wang, Meiling; Wang, Yung-Chen; Werner, Wolfgang; Yang, Li; Shard, Alexander G

2016-10-27

We report the results of a VAMAS (Versailles Project on Advanced Materials and Standards) inter-laboratory study on the measurement of the shell thickness and chemistry of nanoparticle coatings. Peptide-coated gold particles were supplied to laboratories in two forms: a colloidal suspension in pure water and; particles dried onto a silicon wafer. Participants prepared and analyzed these samples using either X-ray photoelectron spectroscopy (XPS) or low energy ion scattering (LEIS). Careful data analysis revealed some significant sources of discrepancy, particularly for XPS. Degradation during transportation, storage or sample preparation resulted in a variability in thickness of 53 %. The calculation method chosen by XPS participants contributed a variability of 67 %. However, variability of 12 % was achieved for the samples deposited using a single method and by choosing photoelectron peaks that were not adversely affected by instrumental transmission effects. The study identified a need for more consistency in instrumental transmission functions and relative sensitivity factors, since this contributed a variability of 33 %. The results from the LEIS participants were more consistent, with variability of less than 10 % in thickness and this is mostly due to a common method of data analysis. The calculation was performed using a model developed for uniform, flat films and some participants employed a correction factor to account for the sample geometry, which appears warranted based upon a simulation of LEIS data from one of the participants and comparison to the XPS results.

Reconstructed storm tracks reveal three centuries of changing moisture delivery to North America

PubMed Central

Wise, Erika K.; Dannenberg, Matthew P.

2017-01-01

Moisture delivery to western North America is closely linked to variability in the westerly storm tracks of midlatitude cyclones, which are, in turn, modified by larger-scale features such as the El Niño–Southern Oscillation system. Instrumental and modeling data suggest that extratropical storm tracks may be intensifying and shifting poleward due to anthropogenic climate change, but it is difficult to separate recent trends from natural variability because of the large amount of decadal and longer variation in storm tracks and their limited instrumental record. We reconstruct cool-season, midlatitude Pacific storm-track position and intensity from 1693 to 1995 CE using existing tree-ring chronologies along with a network of newly developed chronologies from the U.S. Pacific Northwest, where small variations in storm-track position can have a major influence on hydroclimate patterns. Our results show high interannual-to-multidecadal variability in storm-track position and intensity over the past 303 years, with spectral signatures characteristic of tropical and northern Pacific influences. Comparison with reconstructions of precipitation and tropical sea surface temperature confirms the relationship between shifting drought patterns in the Pacific Northwest and storm-track variability through time and demonstrates the long-term influence of El Niño. These results allow us to place recent storm-track changes in the context of decadal and multidecadal fluctuations across the long-term record, showing that recent changes in storm-track intensity likely represent a warming-related increase amplified by natural decadal variability. PMID:28630900

Reconstructed storm tracks reveal three centuries of changing moisture delivery to North America.

PubMed

Wise, Erika K; Dannenberg, Matthew P

2017-06-01

Moisture delivery to western North America is closely linked to variability in the westerly storm tracks of midlatitude cyclones, which are, in turn, modified by larger-scale features such as the El Niño-Southern Oscillation system. Instrumental and modeling data suggest that extratropical storm tracks may be intensifying and shifting poleward due to anthropogenic climate change, but it is difficult to separate recent trends from natural variability because of the large amount of decadal and longer variation in storm tracks and their limited instrumental record. We reconstruct cool-season, midlatitude Pacific storm-track position and intensity from 1693 to 1995 CE using existing tree-ring chronologies along with a network of newly developed chronologies from the U.S. Pacific Northwest, where small variations in storm-track position can have a major influence on hydroclimate patterns. Our results show high interannual-to-multidecadal variability in storm-track position and intensity over the past 303 years, with spectral signatures characteristic of tropical and northern Pacific influences. Comparison with reconstructions of precipitation and tropical sea surface temperature confirms the relationship between shifting drought patterns in the Pacific Northwest and storm-track variability through time and demonstrates the long-term influence of El Niño. These results allow us to place recent storm-track changes in the context of decadal and multidecadal fluctuations across the long-term record, showing that recent changes in storm-track intensity likely represent a warming-related increase amplified by natural decadal variability.

Sexting as the mirror on the wall: Body-esteem attribution, media models, and objectified-body consciousness.

PubMed

Bianchi, Dora; Morelli, Mara; Baiocco, Roberto; Chirumbolo, Antonio

2017-12-01

Sexting motivations during adolescence are related to developmental dimensions-such as sexual identity and body-image development-or harmful intentions-such as aggression among peers and partners. Sociocultural and media models can affect explorations of sexuality and redefinitions of body image, which in turn are related to sexting behaviors and motivations. In this study, we investigated the roles of body-esteem attribution, the internalization of media models, and body objectification as predictors of three sexting motivations: sexual purposes, body-image reinforcement, and instrumental/aggravated reasons. The participants were 190 Italian adolescents aged from 13 to 20 years old (M age  = 17.4, SD age  = 1.8; 44.7% females). Sexual purposes were predicted by body-esteem attribution and body objectification; body-image reinforcement was predicted by the internalization of media models, and instrumental/aggravated reasons were not predicted by any variable. Thus, only sexual purposes and body-image reinforcement appeared to be affected by body-image concerns due to media models. Copyright © 2017 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Electron-Beam Diagnostic Methods for Hypersonic Flow Diagnostics

NASA Technical Reports Server (NTRS)

1994-01-01

The purpose of this work was the evaluation of the use of electron-bean fluorescence for flow measurements during hypersonic flight. Both analytical and numerical models were developed in this investigation to evaluate quantitatively flow field imaging concepts based upon the electron beam fluorescence technique for use in flight research and wind tunnel applications. Specific models were developed for: (1) fluorescence excitation/emission for nitrogen, (2) rotational fluorescence spectrum for nitrogen, (3) single and multiple scattering of electrons in a variable density medium, (4) spatial and spectral distribution of fluorescence, (5) measurement of rotational temperature and density, (6) optical filter design for fluorescence imaging, and (7) temperature accuracy and signal acquisition time requirements. Application of these models to a typical hypersonic wind tunnel flow is presented. In particular, the capability of simulating the fluorescence resulting from electron impact ionization in a variable density nitrogen or air flow provides the capability to evaluate the design of imaging instruments for flow field mapping. The result of this analysis is a recommendation that quantitative measurements of hypersonic flow fields using electron-bean fluorescence is a tractable method with electron beam energies of 100 keV. With lower electron energies, electron scattering increases with significant beam divergence which makes quantitative imaging difficult. The potential application of the analytical and numerical models developed in this work is in the design of a flow field imaging instrument for use in hypersonic wind tunnels or onboard a flight research vehicle.

The Role of Atmospheric Measurements in Wind Power Statistical Models

NASA Astrophysics Data System (ADS)

Wharton, S.; Bulaevskaya, V.; Irons, Z.; Newman, J. F.; Clifton, A.

2015-12-01

The simplest wind power generation curves model power only as a function of the wind speed at turbine hub-height. While the latter is an essential predictor of power output, it is widely accepted that wind speed information in other parts of the vertical profile, as well as additional atmospheric variables including atmospheric stability, wind veer, and hub-height turbulence are also important factors. The goal of this work is to determine the gain in predictive ability afforded by adding additional atmospheric measurements to the power prediction model. In particular, we are interested in quantifying any gain in predictive ability afforded by measurements taken from a laser detection and ranging (lidar) instrument, as lidar provides high spatial and temporal resolution measurements of wind speed and direction at 10 or more levels throughout the rotor-disk and at heights well above. Co-located lidar and meteorological tower data as well as SCADA power data from a wind farm in Northern Oklahoma will be used to train a set of statistical models. In practice, most wind farms continue to rely on atmospheric measurements taken from less expensive, in situ instruments mounted on meteorological towers to assess turbine power response to a changing atmospheric environment. Here, we compare a large suite of atmospheric variables derived from tower measurements to those taken from lidar to determine if remote sensing devices add any competitive advantage over tower measurements alone to predict turbine power response.

Temporal Stability of Soil Moisture and Radar Backscatter Observed by the Advanced Synthetic Aperture Radar (ASAR)

PubMed Central

Wagner, Wolfgang; Pathe, Carsten; Doubkova, Marcela; Sabel, Daniel; Bartsch, Annett; Hasenauer, Stefan; Blöschl, Günter; Scipal, Klaus; Martínez-Fernández, José; Löw, Alexander

2008-01-01

The high spatio-temporal variability of soil moisture is the result of atmospheric forcing and redistribution processes related to terrain, soil, and vegetation characteristics. Despite this high variability, many field studies have shown that in the temporal domain soil moisture measured at specific locations is correlated to the mean soil moisture content over an area. Since the measurements taken by Synthetic Aperture Radar (SAR) instruments are very sensitive to soil moisture it is hypothesized that the temporally stable soil moisture patterns are reflected in the radar backscatter measurements. To verify this hypothesis 73 Wide Swath (WS) images have been acquired by the ENVISAT Advanced Synthetic Aperture Radar (ASAR) over the REMEDHUS soil moisture network located in the Duero basin, Spain. It is found that a time-invariant linear relationship is well suited for relating local scale (pixel) and regional scale (50 km) backscatter. The observed linear model coefficients can be estimated by considering the scattering properties of the terrain and vegetation and the soil moisture scaling properties. For both linear model coefficients, the relative error between observed and modelled values is less than 5 % and the coefficient of determination (R2) is 86 %. The results are of relevance for interpreting and downscaling coarse resolution soil moisture data retrieved from active (METOP ASCAT) and passive (SMOS, AMSR-E) instruments. PMID:27879759

Prediction of future falls in a community dwelling older adult population using instrumented balance and gait analysis.

PubMed

Bauer, C M; Gröger, I; Rupprecht, R; Marcar, V L; Gaßmann, K G

2016-04-01

The role of instrumented balance and gait assessment when screening for prospective fallers is currently a topic of controversial discussion. This study analyzed the association between variables derived from static posturography, instrumented gait analysis and clinical assessments with the occurrence of prospective falls in a sample of community dwelling older people. In this study 84 older people were analyzed. Based on a prospective occurrence of falls, participants were categorized into fallers and non-fallers. Variables derived from clinical assessments, static posturography and instrumented gait analysis were evaluated with respect to the association with the occurrence of prospective falls using a forward stepwise, binary, logistic regression procedure. Fallers displayed a significantly shorter single support time during walking while counting backwards, increased mediolateral to anteroposterior sway amplitude ratio, increased fast mediolateral oscillations and a larger coefficient (Coeff) of sway direction during various static posturography tests. Previous falls were insignificantly associated with the occurrence of prospective falls. Variables derived from posturography and instrumented gait analysis showed significant associations with the occurrence of prospective falls in a sample of community dwelling older adults.

Physical fitness predicts technical-tactical and time-motion profile in simulated Judo and Brazilian Jiu-Jitsu matches.

PubMed

Coswig, Victor S; Gentil, Paulo; Bueno, João C A; Follmer, Bruno; Marques, Vitor A; Del Vecchio, Fabrício B

2018-01-01

Among combat sports, Judo and Brazilian Jiu-Jitsu (BJJ) present elevated physical fitness demands from the high-intensity intermittent efforts. However, information regarding how metabolic and neuromuscular physical fitness is associated with technical-tactical performance in Judo and BJJ fights is not available. This study aimed to relate indicators of physical fitness with combat performance variables in Judo and BJJ. The sample consisted of Judo ( n  = 16) and BJJ ( n  = 24) male athletes. At the first meeting, the physical tests were applied and, in the second, simulated fights were performed for later notational analysis. The main findings indicate: (i) high reproducibility of the proposed instrument and protocol used for notational analysis in a mobile device; (ii) differences in the technical-tactical and time-motion patterns between modalities; (iii) performance-related variables are different in Judo and BJJ; and (iv) regression models based on metabolic fitness variables may account for up to 53% of the variances in technical-tactical and/or time-motion variables in Judo and up to 31% in BJJ, whereas neuromuscular fitness models can reach values up to 44 and 73% of prediction in Judo and BJJ, respectively. When all components are combined, they can explain up to 90% of high intensity actions in Judo. In conclusion, performance prediction models in simulated combat indicate that anaerobic, aerobic and neuromuscular fitness variables contribute to explain time-motion variables associated with high intensity and technical-tactical variables in Judo and BJJ fights.

Impact of Managers' Coaching Conversations on Staff Knowledge Use and Performance in Long-Term Care Settings.

PubMed

Cummings, Greta G; Hewko, Sarah J; Wang, Mengzhe; Wong, Carol A; Laschinger, Heather K Spence; Estabrooks, Carole A

2018-02-01

Extended lifespans and complex resident care needs have amplified resource demands on nursing homes. Nurse managers play an important role in staff job satisfaction, research use, and resident outcomes. Coaching skills, developed through leadership skill-building, have been shown to be of value in nursing. To test a theoretical model of nursing home staff perceptions of their work context, their managers' use of coaching conversations, and their use of instrumental, conceptual and persuasive research. Using a two-group crossover design, 33 managers employed in seven Canadian nursing homes were invited to attend a 2-day coaching development workshop. Survey data were collected from managers and staff at three time points; we analyzed staff data (n = 333), collected after managers had completed the workshop. We used structural equation modeling to test our theoretical model of contextual characteristics as causal variables, managers' characteristics, and coaching behaviors as mediating variables and staff use of research, job satisfaction, and burnout as outcome variables. The theoretical model fit the data well (χ 2 = 58, df = 43, p = .06) indicating no significant differences between data and model-implied matrices. Resonant leadership (a relational approach to influencing change) had the strongest significant relationship with manager support, which in turn influenced frequency of coaching conversations. Coaching conversations had a positive, non-significant relationship with staff persuasive use of research, which in turn significantly increased instrumental research use. Importantly, coaching conversations were significantly, negatively related to job satisfaction. Our findings add to growing research exploring the role of context and leadership in influencing job satisfaction and use of research by healthcare practitioners. One-on-one coaching conversations may be difficult for staff not used to participating in such conversations. Resonant leadership, as expected, has a significant impact on manager support and job satisfaction among nursing home staff. © 2017 Sigma Theta Tau International.

A data assimilation technique to account for the nonlinear dependence of scattering microwave observations of precipitation

NASA Astrophysics Data System (ADS)

Haddad, Z. S.; Steward, J. L.; Tseng, H.-C.; Vukicevic, T.; Chen, S.-H.; Hristova-Veleva, S.

2015-06-01

Satellite microwave observations of rain, whether from radar or passive radiometers, depend in a very crucial way on the vertical distribution of the condensed water mass and on the types and sizes of the hydrometeors in the volume resolved by the instrument. This crucial dependence is nonlinear, with different types and orders of nonlinearity that are due to differences in the absorption/emission and scattering signatures at the different instrument frequencies. Because it is not monotone as a function of the underlying condensed water mass, the nonlinearity requires great care in its representation in the observation operator, as the inevitable uncertainties in the numerous precipitation variables are not directly convertible into an additive white uncertainty in the forward calculated observations. In particular, when attempting to assimilate such data into a cloud-permitting model, special care needs to be applied to describe and quantify the expected uncertainty in the observations operator in order not to turn the implicit white additive uncertainty on the input values into complicated biases in the calculated radiances. One approach would be to calculate the means and covariances of the nonlinearly calculated radiances given an a priori joint distribution for the input variables. This would be a very resource-intensive proposal if performed in real time. We propose a representation of the observation operator based on performing this moment calculation off line, with a dimensionality reduction step to allow for the effective calculation of the observation operator and the associated covariance in real time during the assimilation. The approach is applicable to other remotely sensed observations that depend nonlinearly on model variables, including wind vector fields. The approach has been successfully applied to the case of tropical cyclones, where the organization of the system helps in identifying the dimensionality-reducing variables.

Comparative effectiveness of chemotherapy vs resection of the primary tumour as the initial treatment in older patients with Stage IV colorectal cancer.

PubMed

Mehta, H B; Vargas, G M; Adhikari, D; Dimou, F; Riall, T S

2017-06-01

The objectives were to determine trends in the use of chemotherapy as the initial treatment and to evaluate the comparative effectiveness of initial chemotherapy vs resection of the primary tumour on survival (intention-to-treat analysis) in Stage IV colorectal cancer (CRC). This cohort study used 2000-2011 data from the Surveillance, Epidemiology, and End Results (SEER)-Medicare linked database, including patients ≥ 66 years of age presenting with Stage IV CRC. Cox proportional hazards models and instrumental variable analysis were used to compare the effectiveness of chemotherapy as the initial treatment with resection of the primary tumour as the initial treatment, with 2-year survival as the end point. The use of chemotherapy as the first treatment increased over time, from 26.8% in 2001 to 46.9% in 2009 (P < 0.0001). The traditional Cox model showed that chemotherapy as the initial treatment was associated with a higher risk of mortality [hazard ratio (HR) = 1.35; 95% CI: 1.27-1.44]. When accounting for known and unknown confounders in an instrumental variable analysis, chemotherapy as the initial treatment suggested benefit on 2-year survival (HR = 0.68; 95% CI: 0.44-1.04); however, the association did not reach statistical significance. The study findings were similar in six subgroup analyses. The use of chemotherapy as the initial therapy for CRC increased substantially from 2001 to 2009. Instrumental variable analysis found that, compared with resection, chemotherapy as the initial treatment offers similar or better 2-year survival in patients with Stage IV CRC. Given the morbidity and mortality associated with colorectal resection in elderly patients, chemotherapy provides an option to patients who are not good candidates for resection. Colorectal Disease © 2017 The Association of Coloproctology of Great Britain and Ireland.

Energy conserving schemes for the simulation of musical instrument contact dynamics

NASA Astrophysics Data System (ADS)

Chatziioannou, Vasileios; van Walstijn, Maarten

2015-03-01

Collisions are an innate part of the function of many musical instruments. Due to the nonlinear nature of contact forces, special care has to be taken in the construction of numerical schemes for simulation and sound synthesis. Finite difference schemes and other time-stepping algorithms used for musical instrument modelling purposes are normally arrived at by discretising a Newtonian description of the system. However because impact forces are non-analytic functions of the phase space variables, algorithm stability can rarely be established this way. This paper presents a systematic approach to deriving energy conserving schemes for frictionless impact modelling. The proposed numerical formulations follow from discretising Hamilton's equations of motion, generally leading to an implicit system of nonlinear equations that can be solved with Newton's method. The approach is first outlined for point mass collisions and then extended to distributed settings, such as vibrating strings and beams colliding with rigid obstacles. Stability and other relevant properties of the proposed approach are discussed and further demonstrated with simulation examples. The methodology is exemplified through a case study on tanpura string vibration, with the results confirming the main findings of previous studies on the role of the bridge in sound generation with this type of string instrument.

Spatial and Temporal Variability of Trace Gas Columns Derived from WRF/Chem Regional Model Output: Planning for Geostationary Observations of Atmospheric Composition

NASA Technical Reports Server (NTRS)

Follette-Cook, M. B.; Pickering, K.; Crawford, J.; Duncan, B.; Loughner, C.; Diskin, G.; Fried, A.; Weinheimer, A.

2015-01-01

We quantify both the spatial and temporal variability of column integrated O3, NO2, CO, SO2, and HCHO over the Baltimore / Washington, DC area using output from the Weather Research and Forecasting model with on-line chemistry (WRF/Chem) for the entire month of July 2011, coinciding with the first deployment of the NASA Earth Venture program mission Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ). Using structure function analyses, we find that the model reproduces the spatial variability observed during the campaign reasonably well, especially for O3. The Tropospheric Emissions: Monitoring of Pollution (TEMPO) instrument will be the first NASA mission to make atmospheric composition observations from geostationary orbit and partially fulfills the goals of the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission. We relate the simulated variability to the precision requirements defined by the science traceability matrices of these space-borne missions. Results for O3 from 0- 2 km altitude indicate that the TEMPO instrument would be able to observe O3 air quality events over the Mid-Atlantic area, even on days when the violations of the air quality standard are not widespread. The results further indicated that horizontal gradients in CO from 0-2 km would be observable over moderate distances (= 20 km). The spatial and temporal results for tropospheric column NO2 indicate that TEMPO would be able to observe not only the large urban plumes at times of peak production, but also the weaker gradients between rush hours. This suggests that the proposed spatial and temporal resolutions for these satellites as well as their prospective precision requirements are sufficient to answer the science questions they are tasked to address.

Multiband variability studies and novel broadband SED modeling of Mrk 501 in 2009

NASA Astrophysics Data System (ADS)

Ahnen, M. L.; Ansoldi, S.; Antonelli, L. A.; Antoranz, P.; Babic, A.; Banerjee, B.; Bangale, P.; Barres de Almeida, U.; Barrio, J. A.; Becerra González, J.; Bednarek, W.; Bernardini, E.; Berti, A.; Biasuzzi, B.; Biland, A.; Blanch, O.; Bonnefoy, S.; Bonnoli, G.; Borracci, F.; Bretz, T.; Buson, S.; Carosi, A.; Chatterjee, A.; Clavero, R.; Colin, P.; Colombo, E.; Contreras, J. L.; Cortina, J.; Covino, S.; Da Vela, P.; Dazzi, F.; De Angelis, A.; De Lotto, B.; de Oña Wilhelmi, E.; Di Pierro, F.; Doert, M.; Domínguez, A.; Dominis Prester, D.; Dorner, D.; Doro, M.; Einecke, S.; Eisenacher Glawion, D.; Elsaesser, D.; Engelkemeier, M.; Fallah Ramazani, V.; Fernández-Barral, A.; Fidalgo, D.; Fonseca, M. V.; Font, L.; Frantzen, K.; Fruck, C.; Galindo, D.; García López, R. J.; Garczarczyk, M.; Garrido Terrats, D.; Gaug, M.; Giammaria, P.; Godinović, N.; González Muñoz, A.; Gora, D.; Guberman, D.; Hadasch, D.; Hahn, A.; Hanabata, Y.; Hayashida, M.; Herrera, J.; Hose, J.; Hrupec, D.; Hughes, G.; Idec, W.; Kodani, K.; Konno, Y.; Kubo, H.; Kushida, J.; La Barbera, A.; Lelas, D.; Lindfors, E.; Lombardi, S.; Longo, F.; López, M.; López-Coto, R.; Majumdar, P.; Makariev, M.; Mallot, K.; Maneva, G.; Manganaro, M.; Mannheim, K.; Maraschi, L.; Marcote, B.; Mariotti, M.; Martínez, M.; Mazin, D.; Menzel, U.; Miranda, J. M.; Mirzoyan, R.; Moralejo, A.; Moretti, E.; Nakajima, D.; Neustroev, V.; Niedzwiecki, A.; Nievas Rosillo, M.; Nilsson, K.; Nishijima, K.; Noda, K.; Nogués, L.; Overkemping, A.; Paiano, S.; Palacio, J.; Palatiello, M.; Paneque, D.; Paoletti, R.; Paredes, J. M.; Paredes-Fortuny, X.; Pedaletti, G.; Peresano, M.; Perri, L.; Persic, M.; Poutanen, J.; Prada Moroni, P. G.; Prandini, E.; Puljak, I.; Reichardt, I.; Rhode, W.; Ribó, M.; Rico, J.; Rodriguez Garcia, J.; Saito, T.; Satalecka, K.; Schröder, S.; Schultz, C.; Schweizer, T.; Shore, S. N.; Sillanpää, A.; Sitarek, J.; Snidaric, I.; Sobczynska, D.; Stamerra, A.; Steinbring, T.; Strzys, M.; Surić, T.; Takalo, L.; Tavecchio, F.; Temnikov, P.; Terzić, T.; Tescaro, D.; Teshima, M.; Thaele, J.; Torres, D. F.; Toyama, T.; Treves, A.; Vanzo, G.; Verguilov, V.; Vovk, I.; Ward, J. E.; Will, M.; Wu, M. H.; Zanin, R.; Abeysekara, A. U.; Archambault, S.; Archer, A.; Benbow, W.; Bird, R.; Buchovecky, M.; Buckley, J. H.; Bugaev, V.; Connolly, M. P.; Cui, W.; Dickinson, H. J.; Falcone, A.; Feng, Q.; Finley, J. P.; Fleischhack, H.; Flinders, A.; Fortson, L.; Gillanders, G. H.; Griffin, S.; Grube, J.; Hütten, M.; Hanna, D.; Holder, J.; Humensky, T. B.; Kaaret, P.; Kar, P.; Kelley-Hoskins, N.; Kertzman, M.; Kieda, D.; Krause, M.; Krennrich, F.; Lang, M. J.; Maier, G.; McCann, A.; Moriarty, P.; Mukherjee, R.; Nieto, D.; O'Brien, S.; Ong, R. A.; Otte, N.; Park, N.; Perkins, J.; Pichel, A.; Pohl, M.; Popkow, A.; Pueschel, E.; Quinn, J.; Ragan, K.; Reynolds, P. T.; Richards, G. T.; Roache, E.; Rovero, A. C.; Rulten, C.; Sadeh, I.; Santander, M.; Sembroski, G. H.; Shahinyan, K.; Telezhinsky, I.; Tucci, J. V.; Tyler, J.; Wakely, S. P.; Weinstein, A.; Wilcox, P.; Wilhelm, A.; Williams, D. A.; Zitzer, B.; Razzaque, S.; Villata, M.; Raiteri, C. M.; Aller, H. D.; Aller, M. F.; Larionov, V. M.; Arkharov, A. A.; Blinov, D. A.; Efimova, N. V.; Grishina, T. S.; Hagen-Thorn, V. A.; Kopatskaya, E. N.; Larionova, L. V.; Larionova, E. G.; Morozova, D. A.; Troitsky, I. S.; Ligustri, R.; Calcidese, P.; Berdyugin, A.; Kurtanidze, O. M.; Nikolashvili, M. G.; Kimeridze, G. N.; Sigua, L. A.; Kurtanidze, S. O.; Chigladze, R. A.; Chen, W. P.; Koptelova, E.; Sakamoto, T.; Sadun, A. C.; Moody, J. W.; Pace, C.; Pearson, R.; Yatsu, Y.; Mori, Y.; Carraminyana, A.; Carrasco, L.; de la Fuente, E.; Norris, J. P.; Smith, P. S.; Wehrle, A.; Gurwell, M. A.; Zook, A.; Pagani, C.; Perri, M.; Capalbi, M.; Cesarini, A.; Krimm, H. A.; Kovalev, Y. Y.; Kovalev, Yu. A.; Ros, E.; Pushkarev, A. B.; Lister, M. L.; Sokolovsky, K. V.; Kadler, M.; Piner, G.; Lähteenmäki, A.; Tornikoski, M.; Angelakis, E.; Krichbaum, T. P.; Nestoras, I.; Fuhrmann, L.; Zensus, J. A.; Cassaro, P.; Orlati, A.; Maccaferri, G.; Leto, P.; Giroletti, M.; Richards, J. L.; Max-Moerbeck, W.; Readhead, A. C. S.

2017-07-01

Context. We present an extensive study of the BL Lac object Mrk 501 based on a data set collected during the multi-instrument campaign spanning from 2009 March 15 to 2009 August 1, which includes, among other instruments, MAGIC, VERITAS, Whipple 10 m, and Fermi-LAT to cover the γ-ray range from 0.1 GeV to 20 TeV; RXTE and Swift to cover wavelengths from UV tohard X-rays; and GASP-WEBT, which provides coverage of radio and optical wavelengths. Optical polarization measurements were provided for a fraction of the campaign by the Steward and St. Petersburg observatories. We evaluate the variability of the source and interband correlations, the γ-ray flaring activity occurring in May 2009, and interpret the results within two synchrotron self-Compton (SSC) scenarios. Aims: The multiband variability observed during the full campaign is addressed in terms of the fractional variability, and the possible correlations are studied by calculating the discrete correlation function for each pair of energy bands where the significance was evaluated with dedicated Monte Carlo simulations. The space of SSC model parameters is probed following a dedicated grid-scan strategy, allowing for a wide range of models to be tested and offering a study of the degeneracy of model-to-data agreement in the individual model parameters, hence providing a less biased interpretation than the "single-curve SSC model adjustment" typically reported in the literature. Methods: We find an increase in the fractional variability with energy, while no significant interband correlations of flux changes are found on the basis of the acquired data set. The SSC model grid-scan shows that the flaring activity around May 22 cannot be modeled adequately with a one-zone SSC scenario (using an electron energy distribution with two breaks), while it can be suitably described within a two (independent) zone SSC scenario. Here, one zone is responsible for the quiescent emission from the averaged 4.5-month observing period, while the other one, which is spatially separated from the first, dominates the flaring emission occurring at X-rays and very-high-energy (>100 GeV, VHE) γ rays. The flaring activity from May 1, which coincides with a rotation of the electric vector polarization angle (EVPA), cannot be satisfactorily reproduced by either a one-zone or a two-independent-zone SSC model, yet this is partially affected by the lack of strictly simultaneous observations and the presence of large flux changes on sub-hour timescales (detected at VHE γ rays). Results: The higher variability in the VHE emission and lack of correlation with the X-ray emission indicate that, at least during the 4.5-month observing campaign in 2009, the highest energy (and most variable) electrons that are responsible for the VHE γ rays do not make a dominant contribution to the 1 keV emission. Alternatively, there could be a very variable component contributing to the VHE γ-ray emission in addition to that coming from the SSC scenario. The studies with our dedicated SSC grid-scan show that there is some degeneracy in both the one-zone and the two-zone SSC scenarios probed, with several combinations of model parameters yielding a similar model-to-data agreement, and some parameters better constrained than others. The observed γ-ray flaring activity, with the EVPA rotation coincident with the first γ-ray flare, resembles those reported previously for low frequency peaked blazars, hence suggesting that there are many similarities in the flaring mechanisms of blazars with different jet properties.

Dynamic modal estimation using instrumental variables

NASA Technical Reports Server (NTRS)

Salzwedel, H.

1980-01-01

A method to determine the modes of dynamical systems is described. The inputs and outputs of a system are Fourier transformed and averaged to reduce the error level. An instrumental variable method that estimates modal parameters from multiple correlations between responses of single input, multiple output systems is applied to estimate aircraft, spacecraft, and off-shore platform modal parameters.

Teachers' Pedagogical Management and Instrumental Performance in Students of an Artistic Higher Education School

ERIC Educational Resources Information Center

De La Cruz Bautista, Edwin

2017-01-01

This research aims to know the relationship between the variables teachers' pedagogical management and instrumental performance in students from an Artistic Higher Education School. It is a descriptive and correlational research that seeks to find the relationship between both variables. The sample of the study consisted of 30 students of the…

Polychronometry: The Study of Time Variables in Behavior.

ERIC Educational Resources Information Center

Mackey, William Francis

There is a growing need for instrumentation which can enable us to observe and compute phenomena that take place in time. Although problems of observation, computation, interpretation and categorization vary from field to field and from problem to problem, it is possible to design an instrument for use in any situation where time-variables have to…

Predicting Preservice Music Teachers' Performance Success in Instrumental Courses Using Self-Regulated Study Strategies and Predictor Variables

ERIC Educational Resources Information Center

Ersozlu, Zehra N.; Nietfeld, John L.; Huseynova, Lale

2017-01-01

The purpose of this study was to examine the extent to which self-regulated study strategies and predictor variables predict performance success in instrumental performance college courses. Preservice music teachers (N = 123) from a music education department in two state universities in Turkey completed the Music Self-Regulated Studying…

Can Two Psychotherapy Process Measures Be Dependably Rated Simultaneously? A Generalizability Study

ERIC Educational Resources Information Center

Ulvenes, Pal G.; Berggraf, Lene; Hoffart, Asle; Levy, Raymon A.; Ablon, J. Stuart; McCullough, Leigh; Wampold, Bruce E.

2012-01-01

Observer ratings in psychotherapy are a common way of collecting information in psychotherapy research. However, human observers are imperfect instruments, and their ratings may be subject to variability from several sources. One source of variability can be raters' assessing more than 1 instrument at a time. The purpose of this research is to…

A new method for measuring lung deposition efficiency of airborne nanoparticles in a single breath

NASA Astrophysics Data System (ADS)

Jakobsson, Jonas K. F.; Hedlund, Johan; Kumlin, John; Wollmer, Per; Löndahl, Jakob

2016-11-01

Assessment of respiratory tract deposition of nanoparticles is a key link to understanding their health impacts. An instrument was developed to measure respiratory tract deposition of nanoparticles in a single breath. Monodisperse nanoparticles are generated, inhaled and sampled from a determined volumetric lung depth after a controlled residence time in the lung. The instrument was characterized for sensitivity to inter-subject variability, particle size (22, 50, 75 and 100 nm) and breath-holding time (3-20 s) in a group of seven healthy subjects. The measured particle recovery had an inter-subject variability 26-50 times larger than the measurement uncertainty and the results for various particle sizes and breath-holding times were in accordance with the theory for Brownian diffusion and values calculated from the Multiple-Path Particle Dosimetry model. The recovery was found to be determined by residence time and particle size, while respiratory flow-rate had minor importance in the studied range 1-10 L/s. The instrument will be used to investigate deposition of nanoparticles in patients with respiratory disease. The fast and precise measurement allows for both diagnostic applications, where the disease may be identified based on particle recovery, and for studies with controlled delivery of aerosol-based nanomedicine to specific regions of the lungs.

Mars Methane Detection and Variability at Gale Crater Measured by the TLS instrument in SAM on the Curiosity Rover

NASA Astrophysics Data System (ADS)

Webster, C. R.; Mahaffy, P. R.; Atreya, S. K.; Flesch, G.

2015-12-01

Over the last several years, Earth-based telescopic and Mars orbit remote sensing instruments have reported significant abundances of methane on Mars ranging to tens of parts-per-billion by volume (ppbv). These observations have reported "plumes" or localized patches of methane with variations on timescales much faster than model predictions, leading to speculation of sources from sub-surface methanogen bacteria, geological water-rock reactions, degassing of infalling comets, or UV degradation of micro-meteorites or interplanetary dust. Using the Tunable Laser Spectrometer (TLS) in the Sample Analysis at Mars (SAM) instrument suite on Curiosity, we report in situ detection of methane at background levels of ~0.7 ppbv and also in an episodic release at ten times this value. We will discuss the mechanisms that are believed contributing to these two regimes, report new measurements made since the publication in Science1, and discuss the evidence and implications for seasonal vs. episodic release. Reference 1. "Mars Methane Detection and Variability at Gale Crater", C. R. Webster et al., Science, 347, 415-417 (2015). The research described here was carried out in part at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (NASA).

An assessment of the stray-light in 25 years Dobson total ozone data at Athens, Greece

NASA Astrophysics Data System (ADS)

Christodoulakis, J.; Varotsos, C.; Cracknell, A. P.; Tzanis, C.; Neofytos, A.

2015-02-01

In this study, we investigated the susceptibility of the Dobson spectrophotometer No. 118 to stray-light interference. In this regard, a series of total ozone content measurements were carried out in Athens, Greece for airmass values (μ) extending up to μ = 5. The monochromatic-heterochromatic stray-light derived by Basher's model was used in order to evaluate the specific instrumental parameters which determine if this instrument suffers from this problem or not. The results obtained indicate that the Athens Dobson instrument appears to have an insignificant stray-light error. The comparison of the values of the same parameters measured 15 years ago with the present ones indicates the good maintenance of the Dobson spectrophotometer No. 118. This fact is of crucial importance because the variability of the daily total ozone observations collected by the Athens Dobson Station since 1989 has proved to be representative to the variability of the mean total ozone observed over the whole mid-latitude zone of the Northern Hemisphere. This stresses the point that the Athens total ozone station, being the unique Dobson station in south eastern Europe, may be assumed as a ground-truth station for the reliable conversion of the satellite radiance observations to total ozone measurements.

TITAN’S UPPER ATMOSPHERE FROM CASSINI/UVIS SOLAR OCCULTATIONS

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

Capalbo, Fernando J.; Bénilan, Yves; Yelle, Roger V.

2015-12-01

Titan’s atmosphere is composed mainly of molecular nitrogen, methane being the principal trace gas. From the analysis of 8 solar occultations measured by the Extreme Ultraviolet channel of the Ultraviolet Imaging Spectrograph (UVIS) on board Cassini, we derived vertical profiles of N{sub 2} in the range 1100–1600 km and vertical profiles of CH{sub 4} in the range 850–1300 km. The correction of instrument effects and observational effects applied to the data are described. We present CH{sub 4} mole fractions, and average temperatures for the upper atmosphere obtained from the N{sub 2} profiles. The occultations correspond to different times and locations,more » and an analysis of variability of density and temperature is presented. The temperatures were analyzed as a function of geographical and temporal variables, without finding a clear correlation with any of them, although a trend of decreasing temperature toward the north pole was observed. The globally averaged temperature obtained is (150 ± 1) K. We compared our results from solar occultations with those derived from other UVIS observations, as well as studies performed with other instruments. The observational data we present confirm the atmospheric variability previously observed, add new information to the global picture of Titan’s upper atmosphere composition, variability, and dynamics, and provide new constraints to photochemical models.« less

Results from the Rothney Astrophysical Observatory Variable Star Search Program: Background, Procedure, and Results from RAO Field 1

NASA Astrophysics Data System (ADS)

Williams, Michael D.; Milone, E. F.

2013-12-01

We describe a variable star search program and present the fully reduced results of a search in a 19 square degree (4.4 × 4.4) field centered on J2000 RA = 22:03:24, DEC= +18:54:32. The search was carried out with the Baker-Nunn Patrol Camera located at the Rothney Astrophysical Observatory in the foothills of the Canadian Rockies. A total of 26,271 stars were detected in the field, over a range of about 11-15 (instrumental) magnitudes. Our image processing made use of the IRAF version of the DAOPHOT aperture photometry routine and we used the ANOVA method to search for periodic variations in the light curves. We formally detected periodic variability in 35 stars, that we tentatively classify according to light curve characteristics: 6 EA (Algol), 5 EB (?? Lyrae), 19 EW (W UMa), and 5 RR (RR Lyrae) stars. Eleven of the detected variable stars have been reported previously in the literature. The eclipsing binary light curves have been analyzed with a package of light curve modeling programs and 25 have yielded converged solutions. Ten of these are of systems that are detached, 3 semi-detached, 10 overcontact, and 2 are of systems that appear to be in marginal contact. We discuss these results as well as the advantages and disadvantages of the instrument and of the program.

Social capital, mental health and biomarkers in Chile: assessing the effects of social capital in a middle-income country.

PubMed

Riumallo-Herl, Carlos Javier; Kawachi, Ichiro; Avendano, Mauricio

2014-03-01

In high-income countries, higher social capital is associated with better health. However, there is little evidence of this association in low- and middle-income countries. We examine the association between social capital (social support and trust) and both self-rated and biologically assessed health outcomes in Chile, a middle-income country that experienced a major political transformation and welfare state expansion in the last two decades. Based on data from the Chilean National Health Survey (2009-10), we modeled self-rated health, depression, measured diabetes and hypertension as a function of social capital indicators, controlling for socio-economic status and health behavior. We used an instrumental variable approach to examine whether social capital was causally associated with health. We find that correlations between social capital and health observed in high-income countries are also observed in Chile. All social capital indicators are significantly associated with depression at all ages, and at least one social capital indicator is associated with self-rated health, hypertension and diabetes at ages 45 and above. Instrumental variable models suggest that associations for depression may reflect a causal effect from social capital indicators on mental well-being. Using aggregate social capital as instrument, we also find evidence that social capital may be causally associated with hypertension and diabetes, early markers of cardiovascular risk. Our findings highlight the potential role of social capital in the prevention of depression and early cardiovascular disease in middle-income countries. Copyright © 2014 Elsevier Ltd. All rights reserved.

First-Passage-Time Distribution for Variable-Diffusion Processes

NASA Astrophysics Data System (ADS)

Barney, Liberty; Gunaratne, Gemunu H.

2017-05-01

First-passage-time distribution, which presents the likelihood of a stock reaching a pre-specified price at a given time, is useful in establishing the value of financial instruments and in designing trading strategies. First-passage-time distribution for Wiener processes has a single peak, while that for stocks exhibits a notable second peak within a trading day. This feature has only been discussed sporadically—often dismissed as due to insufficient/incorrect data or circumvented by conversion to tick time—and to the best of our knowledge has not been explained in terms of the underlying stochastic process. It was shown previously that intra-day variations in the market can be modeled by a stochastic process containing two variable-diffusion processes (Hua et al. in, Physica A 419:221-233, 2015). We show here that the first-passage-time distribution of this two-stage variable-diffusion model does exhibit a behavior similar to the empirical observation. In addition, we find that an extended model incorporating overnight price fluctuations exhibits intra- and inter-day behavior similar to those of empirical first-passage-time distributions.

Factorial structure of the 'ToM Storybooks': A test evaluating multiple components of Theory of Mind.

PubMed

Bulgarelli, Daniela; Testa, Silvia; Molina, Paola

2015-06-01

This study examined the factorial structure of the Theory of Mind (ToM) Storybooks, a comprehensive 93-item instrument tapping the five components in Wellman's model of ToM (emotion recognition, understanding of desire and beliefs, ability to distinguish between physical and mental entities, and awareness of the link between perception and knowledge). A sample of 681 three- to eight-year-old Italian children was divided into three age groups to assess whether factorial structure varied across different age ranges. Partial credit model analysis was applied to the data, leading to the empirical identification of 23 composite variables aggregating the ToM Storybooks items. Confirmatory factor analysis was then conducted on the composite variables, providing support for the theoretical model. There were partial differences in the specific composite variables making up the dimensions for each of the three age groups. A single test evaluating distinct dimensions of ToM is a valuable resource for clinical practice which may be used to define differential profiles for specific populations. © 2014 The British Psychological Society.

The effect of signal variability on the histograms of anthropomorphic channel outputs: factors resulting in non-normally distributed data

NASA Astrophysics Data System (ADS)

Elshahaby, Fatma E. A.; Ghaly, Michael; Jha, Abhinav K.; Frey, Eric C.

2015-03-01

Model Observers are widely used in medical imaging for the optimization and evaluation of instrumentation, acquisition parameters and image reconstruction and processing methods. The channelized Hotelling observer (CHO) is a commonly used model observer in nuclear medicine and has seen increasing use in other modalities. An anthropmorphic CHO consists of a set of channels that model some aspects of the human visual system and the Hotelling Observer, which is the optimal linear discriminant. The optimality of the CHO is based on the assumption that the channel outputs for data with and without the signal present have a multivariate normal distribution with equal class covariance matrices. The channel outputs result from the dot product of channel templates with input images and are thus the sum of a large number of random variables. The central limit theorem is thus often used to justify the assumption that the channel outputs are normally distributed. In this work, we aim to examine this assumption for realistically simulated nuclear medicine images when various types of signal variability are present.

An Evaluation of Soil Moisture Retrievals Using Aircraft and Satellite Passive Microwave Observations during SMEX02

NASA Technical Reports Server (NTRS)

Bolten, John D.; Lakshmi, Venkat

2009-01-01

The Soil Moisture Experiments conducted in Iowa in the summer of 2002 (SMEX02) had many remote sensing instruments that were used to study the spatial and temporal variability of soil moisture. The sensors used in this paper (a subset of the suite of sensors) are the AQUA satellite-based AMSR-E (Advanced Microwave Scanning Radiometer- Earth Observing System) and the aircraft-based PSR (Polarimetric Scanning Radiometer). The SMEX02 design focused on the collection of near simultaneous brightness temperature observations from each of these instruments and in situ soil moisture measurements at field- and domain- scale. This methodology provided a basis for a quantitative analysis of the soil moisture remote sensing potential of each instrument using in situ comparisons and retrieved soil moisture estimates through the application of a radiative transfer model. To this end, the two sensors are compared with respect to their estimation of soil moisture.

A dynamic response and eye scanning data base useful in the development of theories and methods for the description of control/display relationships

NASA Technical Reports Server (NTRS)

Klein, R.

1972-01-01

A set of specially prepared digital tapes is reported which contain synchronized measurements of pilot scanning behavior, control response, and vehicle response obtained during instrument landing system approaches made in a fixed-base DC-8 transport simulator. The objective of the master tape is to provide a common data base which can be used by the research community to test theories, models, and methods for describing and analyzing control/display relations and interactions. The experimental conditions and tasks used to obtain the data and the detailed format of the tapes are described. Conventional instrument panel and controls were used, with simulated vertical gust and glide slope beam bend forcing functions. Continuous pilot eye fixations and scan traffic on the panel were measured. Both flight director and standard localizer/glide slope types of approaches were made, with both fixed and variable instrument range sensitivities.

The role of updraft velocity in temporal variability of cloud hydrometeor number

NASA Astrophysics Data System (ADS)

Sullivan, Sylvia; Nenes, Athanasios; Lee, Dong Min; Oreopoulos, Lazaros

2016-04-01

Significant effort has been dedicated to incorporating direct aerosol-cloud links, through parameterization of liquid droplet activation and ice crystal nucleation, within climate models. This significant accomplishment has generated the need for understanding which parameters affecting hydrometer formation drives its variability in coupled climate simulations, as it provides the basis for optimal parameter estimation as well as robust comparison with data, and other models. Sensitivity analysis alone does not address this issue, given that the importance of each parameter for hydrometer formation depends on its variance and sensitivity. To address the above issue, we develop and use a series of attribution metrics defined with adjoint sensitivities to attribute the temporal variability in droplet and crystal number to important aerosol and dynamical parameters. This attribution analysis is done both for the NASA Global Modeling and Assimilation Office Goddard Earth Observing System Model, Version 5 and the National Center for Atmospheric Research Community Atmosphere Model Version 5.1. Within the GEOS simulation, up to 48% of temporal variability in output ice crystal number and 61% in droplet number can be attributed to input updraft velocity fluctuations, while for the CAM simulation, they explain as much as 89% of the ice crystal number variability. This above results suggest that vertical velocity in both model frameworks is seen to be a very important (or dominant) driver of hydrometer variability. Yet, observations of vertical velocity are seldomly available (or used) to evaluate the vertical velocities in simulations; this strikingly contrasts the amount and quality of data available for aerosol-related parameters. Consequentially, there is a strong need for retrievals or measurements of vertical velocity for addressing this important knowledge gap that requires a significant investment and effort by the atmospheric community. The attribution metrics as a tool of understanding for hydrometer variability can be instrumental for understanding the source of differences between models used for aerosol-cloud-climate interaction studies.

The Role of Arctic Sea Ice in Last Millennium Climate Variability: Model-Proxy Comparisons Using Ensemble Members and Novel Model Experiments.

NASA Astrophysics Data System (ADS)

Gertler, C. G.; Monier, E.; Prinn, R. G.

2016-12-01

Variability in sea ice extent is a prominent feature of forced simulations of the last millennium and reconstructions of paleoclimate using proxy records. The rapid 20th century decline in sea ice extent is most likely due to greenhouse gas forcing, but the accuracy of future projections depend on the characterization of natural variability. Declining sea ice extent affects regional climate and society, but also plays a large role in Arctic amplification, with implications for mid-latitude circulation and even large-scale climate oscillations. To characterize the effects of natural and anthropogenic climate forcing on sea ice and the related changes in large-scale atmospheric circulation, a combination of instrumental record, paleoclimate reconstructions, and general circulation models can be employed to recreate sea ice extents and the corresponding atmosphere-ocean states. Model output from the last millennium ensemble (LME) is compared to a proxy-based sea ice reconstruction and a global proxy network using a variety of statistical and data assimilation techniques. Further model runs using the Community Earth Systems Model (CESM) are performed with the same inputs as LME but forced with experimental sea ice extents, and results are contextualized within the larger ensemble by a variety of metrics.

Comparing the model-simulated global warming signal to observations using empirical estimates of unforced noise.

PubMed

Brown, Patrick T; Li, Wenhong; Cordero, Eugene C; Mauget, Steven A

2015-04-21

The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much public and scientific attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible unforced states of the climate system (the Envelope of Unforced Noise; EUN). Typically, the EUN is derived from climate models themselves, but climate models might not accurately simulate the correct characteristics of unforced GMT variability. Here, we simulate a new, empirical, EUN that is based on instrumental and reconstructed surface temperature records. We compare the forced GMT signal produced by climate models to observations while noting the range of GMT values provided by the empirical EUN. We find that the empirical EUN is wide enough so that the interdecadal variability in the rate of global warming over the 20(th) century does not necessarily require corresponding variability in the rate-of-increase of the forced signal. The empirical EUN also indicates that the reduced GMT warming over the past decade or so is still consistent with a middle emission scenario's forced signal, but is likely inconsistent with the steepest emission scenario's forced signal.

Comparing the model-simulated global warming signal to observations using empirical estimates of unforced noise

PubMed Central

Brown, Patrick T.; Li, Wenhong; Cordero, Eugene C.; Mauget, Steven A.

2015-01-01

The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much public and scientific attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible unforced states of the climate system (the Envelope of Unforced Noise; EUN). Typically, the EUN is derived from climate models themselves, but climate models might not accurately simulate the correct characteristics of unforced GMT variability. Here, we simulate a new, empirical, EUN that is based on instrumental and reconstructed surface temperature records. We compare the forced GMT signal produced by climate models to observations while noting the range of GMT values provided by the empirical EUN. We find that the empirical EUN is wide enough so that the interdecadal variability in the rate of global warming over the 20th century does not necessarily require corresponding variability in the rate-of-increase of the forced signal. The empirical EUN also indicates that the reduced GMT warming over the past decade or so is still consistent with a middle emission scenario's forced signal, but is likely inconsistent with the steepest emission scenario's forced signal. PMID:25898351

An Assessment of the Need for Standard Variable Names for Airborne Field Campaigns

NASA Astrophysics Data System (ADS)

Beach, A. L., III; Chen, G.; Northup, E. A.; Kusterer, J.; Quam, B. M.

2017-12-01

The NASA Earth Venture Program has led to a dramatic increase in airborne observations, requiring updated data management practices with clearly defined data standards and protocols for metadata. An airborne field campaign can involve multiple aircraft and a variety of instruments. It is quite common to have different instruments/techniques measure the same parameter on one or more aircraft platforms. This creates a need to allow instrument Principal Investigators (PIs) to name their variables in a way that would distinguish them across various data sets. A lack of standardization of variables names presents a challenge for data search tools in enabling discovery of similar data across airborne studies, aircraft platforms, and instruments. This was also identified by data users as one of the top issues in data use. One effective approach for mitigating this problem is to enforce variable name standardization, which can effectively map the unique PI variable names to fixed standard names. In order to ensure consistency amongst the standard names, it will be necessary to choose them from a controlled list. However, no such list currently exists despite a number of previous efforts to establish a sufficient list of atmospheric variable names. The Atmospheric Composition Variable Standard Name Working Group was established under the auspices of NASA's Earth Science Data Systems Working Group (ESDSWG) to solicit research community feedback to create a list of standard names that are acceptable to data providers and data users This presentation will discuss the challenges and recommendations of standard variable names in an effort to demonstrate how airborne metadata curation/management can be improved to streamline data ingest, improve interoperability, and discoverability to a broader user community.

A new model of wheezing severity in young children using the validated ISAAC wheezing module: A latent variable approach with validation in independent cohorts.

PubMed

Brunwasser, Steven M; Gebretsadik, Tebeb; Gold, Diane R; Turi, Kedir N; Stone, Cosby A; Datta, Soma; Gern, James E; Hartert, Tina V

2018-01-01

The International Study of Asthma and Allergies in Children (ISAAC) Wheezing Module is commonly used to characterize pediatric asthma in epidemiological studies, including nearly all airway cohorts participating in the Environmental Influences on Child Health Outcomes (ECHO) consortium. However, there is no consensus model for operationalizing wheezing severity with this instrument in explanatory research studies. Severity is typically measured using coarsely-defined categorical variables, reducing power and potentially underestimating etiological associations. More precise measurement approaches could improve testing of etiological theories of wheezing illness. We evaluated a continuous latent variable model of pediatric wheezing severity based on four ISAAC Wheezing Module items. Analyses included subgroups of children from three independent cohorts whose parents reported past wheezing: infants ages 0-2 in the INSPIRE birth cohort study (Cohort 1; n = 657), 6-7-year-old North American children from Phase One of the ISAAC study (Cohort 2; n = 2,765), and 5-6-year-old children in the EHAAS birth cohort study (Cohort 3; n = 102). Models were estimated using structural equation modeling. In all cohorts, covariance patterns implied by the latent variable model were consistent with the observed data, as indicated by non-significant χ2 goodness of fit tests (no evidence of model misspecification). Cohort 1 analyses showed that the latent factor structure was stable across time points and child sexes. In both cohorts 1 and 3, the latent wheezing severity variable was prospectively associated with wheeze-related clinical outcomes, including physician asthma diagnosis, acute corticosteroid use, and wheeze-related outpatient medical visits when adjusting for confounders. We developed an easily applicable continuous latent variable model of pediatric wheezing severity based on items from the well-validated ISAAC Wheezing Module. This model prospectively associates with asthma morbidity, as demonstrated in two ECHO birth cohort studies, and provides a more statistically powerful method of testing etiologic hypotheses of childhood wheezing illness and asthma.

Interpersonal reactivity index: analysis of invariance and gender differences in spanish youths.

PubMed

Holgado Tello, Francisco Pablo; Delgado Egido, Begoña; Carrasco Ortiz, Miguel A; Del Barrio Gandara, M V

2013-04-01

Empathy is understood as a multidimensional construct involving both cognitive and emotional factors for which, traditionally, gender differences have been reported. The Interpersonal Reactivity Index (Davis in Catalog Sel Documents Psychol 10:1-19, 1980) is an instrument made up of four subscales, each measuring a different dimension of the global concept of empathy. Attending to gender differences, the present study's objective is twofold. First, it aims to determine, conceptually speaking, whether or not the model analyzed by this instrument is equivalent for the two sexes. Second, it aims to determine which dimensions involved in empathy most strongly predict gender differences. The results convey that the proposed model is invariant between boys and girls, although the dimensions exhibited significant differences of magnitude as a function of sex. Mainly two variables (Considerate Social Style and Impassiveness) were capable of distinguishing between men and women. Possible reasons for these results are also discussed.

The relationship between alexithymia and maladaptive perfectionism in eating disorders: a mediation moderation analysis methodology.

PubMed

Marsero, S; Ruggiero, G M; Scarone, S; Bertelli, S; Sassaroli, S

2011-09-01

This work aimed to explore the relationship between alexithymia and maladaptive perfectionism in the psychological process leading to eating disorders (ED). Forty-nine individuals with ED and 49 controls completed the Concern over Mistakes subscale of the Frost Multidimensional Perfectionism Scale, the Perfectionism subscale of the Eating Disorders Inventory, the total score of the Toronto Alexithymia Scale, and the Drive for Thinness, Bulimia, and Body Dissatisfaction subscales of the Eating Disorders Inventory. We tested a model in which alexythimia is the independent variable and perfectionism is the possible mediator or moderator. Analyses confirmed the assumed model. In addition, it emerged that perfectionism played a mediating or moderating role when measured by different instruments. This result suggested that different instruments measured subtly different aspects of the same construct. Results could suggest that alexithymia is a predisposing factor for perfectionism, which in turn may lead to the development of eating disorders.

Atmospheric Aerosol Sampling with Unmanned Aircraft Systems (UAS) in Alaska: Instrument Development, Payload Integration, and Measurement Campaigns

NASA Astrophysics Data System (ADS)

Barberie, S. R.; Saiet, E., II; Hatfield, M. C.; Cahill, C. F.

2014-12-01

Atmospheric aerosols remain one of biggest variables in understanding global climate. The number of feedback loops involved in aerosol processes lead to nonlinear behavior at the systems level, making confident modeling and prediction difficult. It is therefore important to ground-truth and supplement modeling efforts with rigorous empirical measurements. To this end, the Alaska Center for Unmanned Aircraft Systems Integration (ACUASI) at the University of Alaska Fairbanks has developed a new cascade DRUM-style impactor to be mounted aboard a variety of unmanned aircraft and work in tandem with an optical particle counter for the routine collection of atmospheric aerosols. These UAS-based aerosol samplers will be employed for measurement campaigns in traditionally hazardous conditions such as volcanic plumes and over forest fires. Here we report on the development and laboratory calibration of the new instrument, the integration with UAS, and the vertical profiling campaigns being undertaken.

Aeolian Dunes: New High-Resolution Archives of Past Wind-Intensity and -Direction

NASA Astrophysics Data System (ADS)

Lindhorst, S.; Betzler, C.

2017-12-01

The understanding of the long-term variability of local wind-fields is most relevant for calibrating climate models and for the prediction of the socio-economic consequences of climate change. Continuous instrumental-based weather observations go back less than two centuries; aeolian dunes, however, contain an archive of past wind-field fluctuations which is basically unread. We present new ways to reconstruct annual to seasonal changes of wind intensity and predominant wind direction from dune-sediment composition and -geometries based on ground-penetrating radar (GPR) data, grain-size analyses and different age-dating approaches. Resulting proxy-based data series on wind are validated against instrumental based weather observations. Our approach can be applied to both recent as well as fossil dunes. Potential applications include the validation of climate models, the reconstruction of past supra-regional wind systems and the monitoring of future shifts in the climate system.

Learning styles of medical students change in relation to time.

PubMed

Gurpinar, Erol; Bati, Hilal; Tetik, Cihat

2011-09-01

The aim of the present study was to investigate if any changes exist in the learning styles of medical students over time and in relation to different curriculum models with these learning styles. This prospective cohort study was conducted in three different medical faculties, which implement problem-based learning (PBL), hybrid, and integrated curriculum models. The study instruments were Kolb's Learning Style Inventory (LSI) and a questionnaire describing the students' demographic characteristics. Sample selection was not done, and all first-year students (n = 547) were targeted. This study was designed in two phases. In the first year, the study instruments were delivered to the target group. The next year, the same instruments were delivered again to those who had fully completed the first questionnaire (n = 525). Of these, 455 students had completed the instruments truly and constituted the study group. The majority of the students were assimilators and convergers in both the first and second years. A change in learning style was observed between 2 yr in 46.9% of the students in the integrated curriculum, in 49.3% of the students in the hybrid curriculum, and 56.4% of the students in the PBL curriculum. The least and most changes observed between the learning style groups were in assimilators and divergers, respectively. Curriculum models and other independent variables had no significant effect on the change between learning styles. The learning styles of medical students may change over time. Further followup studies in larger groups are needed to clarify this relation.

Use of allele scores as instrumental variables for Mendelian randomization

PubMed Central

Burgess, Stephen; Thompson, Simon G

2013-01-01

Background An allele score is a single variable summarizing multiple genetic variants associated with a risk factor. It is calculated as the total number of risk factor-increasing alleles for an individual (unweighted score), or the sum of weights for each allele corresponding to estimated genetic effect sizes (weighted score). An allele score can be used in a Mendelian randomization analysis to estimate the causal effect of the risk factor on an outcome. Methods Data were simulated to investigate the use of allele scores in Mendelian randomization where conventional instrumental variable techniques using multiple genetic variants demonstrate ‘weak instrument’ bias. The robustness of estimates using the allele score to misspecification (for example non-linearity, effect modification) and to violations of the instrumental variable assumptions was assessed. Results Causal estimates using a correctly specified allele score were unbiased with appropriate coverage levels. The estimates were generally robust to misspecification of the allele score, but not to instrumental variable violations, even if the majority of variants in the allele score were valid instruments. Using a weighted rather than an unweighted allele score increased power, but the increase was small when genetic variants had similar effect sizes. Naive use of the data under analysis to choose which variants to include in an allele score, or for deriving weights, resulted in substantial biases. Conclusions Allele scores enable valid causal estimates with large numbers of genetic variants. The stringency of criteria for genetic variants in Mendelian randomization should be maintained for all variants in an allele score. PMID:24062299

Using SMAP Data to Investigate the Role of Soil Moisture Variability on Realtime Flood Forecasting

NASA Astrophysics Data System (ADS)

Krajewski, W. F.; Jadidoleslam, N.; Mantilla, R.

2017-12-01

The Iowa Flood Center has developed a regional high-resolution flood-forecasting model for the state of Iowa that decomposes the landscape into hillslopes of about 0.1 km2. For the model to benefit, through data assimilation, from SMAP observations of soil moisture (SM) at scales of approximately 100 km2, we are testing a framework to connect SMAP-scale observations to the small-scale SM variability calculated by our rainfall-runoff models. As a step in this direction, we performed data analyses of 15-min point SM observations using a network of about 30 TDR instruments spread throughout the state. We developed a stochastic point-scale SM model that captures 1) SM increases due to rainfall inputs, and 2) SM decay during dry periods. We use a power law model to describe soil moisture decay during dry periods, and a single parameter logistic curve to describe precipitation feedback on soil moisture. We find that the parameters of the models behave as time-independent random variables with stationary distributions. Using data-based simulation, we explore differences in the dynamical range of variability of hillslope and SMAP-scale domains. The simulations allow us to predict the runoff field and streamflow hydrographs for the state of Iowa during the three largest flooding periods (2008, 2014, and 2016). We also use the results to determine the reduction in forecast uncertainty from assimilation of unbiased SMAP-scale soil moisture observations.

SABER Observations of the OH Meinel Airglow Variability Near the Mesopause

NASA Technical Reports Server (NTRS)

Marsh, Daniel R.; Smith, Anne K.; Mlynczak, Martin G.

2005-01-01

The Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument, one of four on board the TIMED satellite, observes the OH Meinel emission at 2.0 m that peaks near the mesopause. The emission results from reactions between members of the oxygen and hydrogen chemical families that can be significantly affected by mesopause dynamics. In this study we compare SABER measurements of OH Meinel emission rates and temperatures with predictions from a 3-dimensional chemical dynamical model. In general, the model is capable of reproducing both the observed diurnal and seasonal OH Meinel emission variability. The results indicate that the diurnal tide has a large effect on the overall magnitude and temporal variation of the emission in low latitudes. This tidal variability is so dominant that the seasonal cycle in the nighttime emission depends very strongly on the local time of the analysis. At higher latitudes, the emission has an annual cycle that is due mainly to transport of oxygen by the seasonally reversing mean circulation.

10 years of BAWLing into affective and aesthetic processes in reading: what are the echoes?

PubMed Central

Jacobs, Arthur M.; Võ, Melissa L.-H.; Briesemeister, Benny B.; Conrad, Markus; Hofmann, Markus J.; Kuchinke, Lars; Lüdtke, Jana; Braun, Mario

2015-01-01

Reading is not only “cold” information processing, but involves affective and aesthetic processes that go far beyond what current models of word recognition, sentence processing, or text comprehension can explain. To investigate such “hot” reading processes, standardized instruments that quantify both psycholinguistic and emotional variables at the sublexical, lexical, inter-, and supralexical levels (e.g., phonological iconicity, word valence, arousal-span, or passage suspense) are necessary. One such instrument, the Berlin Affective Word List (BAWL) has been used in over 50 published studies demonstrating effects of lexical emotional variables on all relevant processing levels (experiential, behavioral, neuronal). In this paper, we first present new data from several BAWL studies. Together, these studies examine various views on affective effects in reading arising from dimensional (e.g., valence) and discrete emotion features (e.g., happiness), or embodied cognition features like smelling. Second, we extend our investigation of the complex issue of affective word processing to words characterized by a mixture of affects. These words entail positive and negative valence, and/or features making them beautiful or ugly. Finally, we discuss tentative neurocognitive models of affective word processing in the light of the present results, raising new issues for future studies. PMID:26089808

Quality of life, human insecurity, and distress among Palestinians in the Gaza Strip before and after the Winter 2008-2009 Israeli war.

PubMed

Hammoudeh, Weeam; Hogan, Dennis; Giacaman, Rita

2013-11-01

This study investigates changes in the quality of life (QoL) of Gaza Palestinians before and after the Israeli winter 2008-2009 war using the World Health Organization's WHOQOL-Bref; the extent to which this instrument adequately measures changing situations; and its responsiveness to locally developed human insecurity and distress measures appropriate for context. Ordinary least squares regression analysis was performed to detect how demographic and socioeconomic variables usually associated with QoL were associated with human insecurity and distress. We estimated the usual baseline model for the three QoL domains, and a second set of models including these standard variables and human insecurity and distress to assess how personal exposure to political violence affects QoL. No difference between the quality of life scores in 2005 and 2009 was found, with results suggesting lack of sensitivity of WHOQOL-Bref in capturing changes resulting from intensification of preexisting political violence. Results show that human insecurity and individual distress significantly increased in 2009 compared to 2005. Results indicate that a political domain may provide further understanding of and possibly increase the sensitivity of the instrument to detect changes in the Qol of Palestinians and possibly other populations experiencing intensified political violence.

Factor Structure, Reliability and Measurement Invariance of the Alberta Context Tool and the Conceptual Research Utilization Scale, for German Residential Long Term Care

PubMed Central

Hoben, Matthias; Estabrooks, Carole A.; Squires, Janet E.; Behrens, Johann

2016-01-01

We translated the Canadian residential long term care versions of the Alberta Context Tool (ACT) and the Conceptual Research Utilization (CRU) Scale into German, to study the association between organizational context factors and research utilization in German nursing homes. The rigorous translation process was based on best practice guidelines for tool translation, and we previously published methods and results of this process in two papers. Both instruments are self-report questionnaires used with care providers working in nursing homes. The aim of this study was to assess the factor structure, reliability, and measurement invariance (MI) between care provider groups responding to these instruments. In a stratified random sample of 38 nursing homes in one German region (Metropolregion Rhein-Neckar), we collected questionnaires from 273 care aides, 196 regulated nurses, 152 allied health providers, 6 quality improvement specialists, 129 clinical leaders, and 65 nursing students. The factor structure was assessed using confirmatory factor models. The first model included all 10 ACT concepts. We also decided a priori to run two separate models for the scale-based and the count-based ACT concepts as suggested by the instrument developers. The fourth model included the five CRU Scale items. Reliability scores were calculated based on the parameters of the best-fitting factor models. Multiple-group confirmatory factor models were used to assess MI between provider groups. Rather than the hypothesized ten-factor structure of the ACT, confirmatory factor models suggested 13 factors. The one-factor solution of the CRU Scale was confirmed. The reliability was acceptable (>0.7 in the entire sample and in all provider groups) for 10 of 13 ACT concepts, and high (0.90–0.96) for the CRU Scale. We could demonstrate partial strong MI for both ACT models and partial strict MI for the CRU Scale. Our results suggest that the scores of the German ACT and the CRU Scale for nursing homes are acceptably reliable and valid. However, as the ACT lacked strict MI, observed variables (or scale scores based on them) cannot be compared between provider groups. Rather, group comparisons should be based on latent variable models, which consider the different residual variances of each group. PMID:27656156

Comparison and covalidation of ozone anomalies and variability observed in SBUV(/2) and Umkehr northern midlatitude ozone profile estimates

NASA Astrophysics Data System (ADS)

Petropavlovskikh, I.; Ahn, Changwoo; Bhartia, P. K.; Flynn, L. E.

2005-03-01

This analysis presents comparisons of upper-stratosphere ozone information observed by two independent systems: the Solar Backscatter UltraViolet (SBUV and SBUV/2) satellite instruments, and ground-based Dobson spectrophotometers. Both the new SBUV Version 8 and the new UMK04 profile retrieval algorithms are optimized for studying long-term variability and trends in ozone. Trend analyses of the ozone time series from the SBUV(/2) data set are complex because of the multiple instruments involved, changes in the instruments' geo-location, and short periods of overlaps for inter-calibrations among different instruments. Three northern middle latitudes Dobson ground stations (Arosa, Boulder, and Tateno) are used in this analysis to validate the trend quality of the combined 25-year SBUV/2 time series, 1979 to 2003. Generally, differences between the satellite and ground-based data do not suggest any significant time-dependent shifts or trends. The shared features confirm the value of these data sets for studies of ozone variability.

A thermal control system for long-term survival of scientific instruments on lunar surface.

PubMed

Ogawa, K; Iijima, Y; Sakatani, N; Otake, H; Tanaka, S

2014-03-01

A thermal control system is being developed for scientific instruments placed on the lunar surface. This thermal control system, Lunar Mission Survival Module (MSM), was designed for scientific instruments that are planned to be operated for over a year in the future Japanese lunar landing mission SELENE-2. For the long-term operations, the lunar surface is a severe environment because the soil (regolith) temperature varies widely from nighttime -200 degC to daytime 100 degC approximately in which space electronics can hardly survive. The MSM has a tent of multi-layered insulators and performs a "regolith mound". Temperature of internal devices is less variable just like in the lunar underground layers. The insulators retain heat in the regolith soil in the daylight, and it can keep the device warm in the night. We conducted the concept design of the lunar survival module, and estimated its potential by a thermal mathematical model on the assumption of using a lunar seismometer designed for SELENE-2. Thermal vacuum tests were also conducted by using a thermal evaluation model in order to estimate the validity of some thermal parameters assumed in the computed thermal model. The numerical and experimental results indicated a sufficient survivability potential of the concept of our thermal control system.

Variability of Springtime Transpacific Pollution Transport During 2000-2006: The INTEX-5 Mission in the Context of Previous Years

NASA Technical Reports Server (NTRS)

Pfister, G. G.; Emmons, L. K.; Edwards, D. P.; Arellano, A.; Sachse, G.; Campos, T.

2010-01-01

We analyze the transport of pollution across the Pacific during the NASA INTEX-B (Intercontinental Chemical Transport Experiment Part 8) campaign in spring 2006 and examine how this year compares to the time period for 2000 through 2006. In addition to aircraft measurements of carbon monoxide (CO) collected during INTEX-B, we include in this study multi-year satellite retrievals of CO from the Measurements of Pollution in the Troposphere (MOPITT) instrument and simulations from the chemistry transport model MOZART-4. Model tracers are used to examine the contributions of different source regions and source types to pollution levels over the Pacific. Additional modeling studies are performed to separate the impacts of inter-annual variability in meteorology and .dynamics from changes in source strength. interannual variability in the tropospheric CO burden over the Pacific and the US as estimated from the MOPITT data range up to 7% and a somewhat smaller estimate (5%) is derived from the model. When keeping the emissions in the model constant between years, the year-to-year changes are reduced (2%), but show that in addition to changes in emissions, variable meteorological conditions also impact transpacific pollution transport. We estimate that about 113 of the variability in the tropospheric CO loading over the contiguous US is explained by changes in emissions and about 213 by changes in meteorology and transport. Biomass burning sources are found to be a larger driver for inter-annual variability in the CO loading compared to fossil and biofuel sources or photochemical CO production even though their absolute contributions are smaller. Source contribution analysis shows that the aircraft sampling during INTEX-B was fairly representative of the larger scale region, but with a slight bias towards higher influence from Asian contributions.

Examining the last few decades of global hydroclimate for evidence of anthropogenic change amidst natural variability

NASA Astrophysics Data System (ADS)

Seager, R.; Naik, N.; Ting, M.; Kushnir, Y.; Kelley, C. P.

2011-12-01

Climate models robustly predict that the deep tropics and mid-latitude-to-subpolar regions will moisten, and the subtropical dry zones both dry and expand, as a consequence of global warming driven by rising greenhouse gases. The models also predict that this transition to a more extreme climatological mean global hydroclimate should already be underway. Given the importance of these predictions it is an imperative that the climate science community assess whether there is evidence within the observational record that they are correct. This task is made difficult by the tremendous natural variability of the hydrological cycle on seasonal to multidecadal timescales. Here we will use instrumental observations, reanalyses, sea surface temperature forced atmosphere models and coupled model simulations, and a variety of methodologies, to attempt to separate global radiatively-forced hydroclimate change from ongoing natural variability. The results will be applied to explain trends and recent events in key regions such as Mexico, the United States and the Mediterranean. It is concluded that the signal of anthropogenic change is small compared to the amplitude of natural variability but that it is a discernible contributor. Globally the evidence reveals that radiatively-forced hydroclimate change is occurring with an amplitude and spatial pattern largely consistent with the predictions by IPCC AR4 models of hydroclimate change to date. However it will also be shown that the radiatively-forced component does not in and of itself provide a useful prediction of near term hydroclimate change because for many regions the amplitude of natural decadal variability is as large or larger. Useful predictions need to account for how natural variability may evolve as well as forced change.

Applicability of the theory of planned behavior in explaining the general practitioners eLearning use in continuing medical education.

PubMed

Hadadgar, Arash; Changiz, Tahereh; Masiello, Italo; Dehghani, Zahra; Mirshahzadeh, Nahidossadat; Zary, Nabil

2016-08-22

General practitioners (GP) update their knowledge and skills by participating in continuing medical education (CME) programs either in a traditional or an e-Learning format. GPs' beliefs about electronic format of CME have been studied but without an explicit theoretical framework which makes the findings difficult to interpret. In other health disciplines, researchers used theory of planned behavior (TPB) to predict user's behavior. In this study, an instrument was developed to investigate GPs' intention to use e-Learning in CME based on TPB. The goodness of fit of TPB was measured using confirmatory factor analysis and the relationship between latent variables was assessed using structural equation modeling. A total of 148 GPs participated in the study. Most of the items in the questionnaire related well to the TPB theoretical constructs, and the model had good fitness. The perceived behavioral control and attitudinal constructs were included, and the subjective norms construct was excluded from the structural model. The developed questionnaire could explain 66 % of the GPs' intention variance. The TPB could be used as a model to construct instruments that investigate GPs' intention to participate in e-Learning programs in CME. The findings from the study will encourage CME managers and researchers to explore the developed instrument as a mean to explain and improve the GPs' intentions to use eLearning in CME.

Estimating Uncertainty in Long Term Total Ozone Records from Multiple Sources

NASA Technical Reports Server (NTRS)

Frith, Stacey M.; Stolarski, Richard S.; Kramarova, Natalya; McPeters, Richard D.

2014-01-01

Total ozone measurements derived from the TOMS and SBUV backscattered solar UV instrument series cover the period from late 1978 to the present. As the SBUV series of instruments comes to an end, we look to the 10 years of data from the AURA Ozone Monitoring Instrument (OMI) and two years of data from the Ozone Mapping Profiler Suite (OMPS) on board the Suomi National Polar-orbiting Partnership satellite to continue the record. When combining these records to construct a single long-term data set for analysis we must estimate the uncertainty in the record resulting from potential biases and drifts in the individual measurement records. In this study we present a Monte Carlo analysis used to estimate uncertainties in the Merged Ozone Dataset (MOD), constructed from the Version 8.6 SBUV2 series of instruments. We extend this analysis to incorporate OMI and OMPS total ozone data into the record and investigate the impact of multiple overlapping measurements on the estimated error. We also present an updated column ozone trend analysis and compare the size of statistical error (error from variability not explained by our linear regression model) to that from instrument uncertainty.

Predicting Use of Nurse Care Coordination by Older Adults With Chronic Conditions.

PubMed

Vanderboom, Catherine E; Holland, Diane E; Mandrekar, Jay; Lohse, Christine M; Witwer, Stephanie G; Hunt, Vicki L

2017-07-01

To be effective, nurse care coordination must be targeted at individuals who will use the service. The purpose of this study was to identify variables that predicted use of care coordination by primary care patients. Data on the potential predictor variables were obtained from patient interviews, the electronic health record, and an administrative database of 178 adults eligible for care coordination. Use of care coordination was obtained from an administrative database. A multivariable logistic regression model was developed using a bootstrap sampling approach. Variables predicting use of care coordination were dependence in both activities of daily living (ADL) and instrumental activities of daily living (IADL; odds ratio [OR] = 5.30, p = .002), independent for ADL but dependent for IADL (OR = 2.68, p = .01), and number of prescription medications (OR = 1.12, p = .002). Consideration of these variables may improve identification of patients to target for care coordination.

The effects of types of social networks, perceived social support, and loneliness on the health of older people: accounting for the social context.

PubMed

Stephens, Christine; Alpass, Fiona; Towers, Andy; Stevenson, Brendan

2011-09-01

To use an ecological model of ageing (Berkman, Glass, Brissette, & Seeman, 2000) which includes upstream social context factors and downstream social support factors to examine the effects of social networks on health. Postal survey responses from a representative population sample of New Zealanders aged 55 to 70 years (N = 6,662). Correlations and multiple regression analyses provided support for a model in which social context contributes to social network type, which affects perceived social support and loneliness, and consequent mental and physical health. Ethnicity was related to social networks and health but this was largely accounted for by other contextual variables measuring socioeconomic status. Gender and age were also significant variables in the model. Social network type is a useful way to assess social integration within this model of cascading effects. More detailed information could be gained through the development of our network assessment instruments for older people.

Analysis of an Environmental Exposure Health Questionnaire in a Metropolitan Minority Population Utilizing Logistic Regression and Support Vector Machines

PubMed Central

Chen, Chau-Kuang; Bruce, Michelle; Tyler, Lauren; Brown, Claudine; Garrett, Angelica; Goggins, Susan; Lewis-Polite, Brandy; Weriwoh, Mirabel L; Juarez, Paul D.; Hood, Darryl B.; Skelton, Tyler

2014-01-01

The goal of this study was to analyze a 54-item instrument for assessment of perception of exposure to environmental contaminants within the context of the built environment, or exposome. This exposome was defined in five domains to include 1) home and hobby, 2) school, 3) community, 4) occupation, and 5) exposure history. Interviews were conducted with child-bearing-age minority women at Metro Nashville General Hospital at Meharry Medical College. Data were analyzed utilizing DTReg software for Support Vector Machine (SVM) modeling followed by an SPSS package for a logistic regression model. The target (outcome) variable of interest was respondent's residence by ZIP code. The results demonstrate that the rank order of important variables with respect to SVM modeling versus traditional logistic regression models is almost identical. This is the first study documenting that SVM analysis has discriminate power for determination of higher-ordered spatial relationships on an environmental exposure history questionnaire. PMID:23395953

Analysis of an environmental exposure health questionnaire in a metropolitan minority population utilizing logistic regression and Support Vector Machines.

PubMed

Chen, Chau-Kuang; Bruce, Michelle; Tyler, Lauren; Brown, Claudine; Garrett, Angelica; Goggins, Susan; Lewis-Polite, Brandy; Weriwoh, Mirabel L; Juarez, Paul D; Hood, Darryl B; Skelton, Tyler

2013-02-01

The goal of this study was to analyze a 54-item instrument for assessment of perception of exposure to environmental contaminants within the context of the built environment, or exposome. This exposome was defined in five domains to include 1) home and hobby, 2) school, 3) community, 4) occupation, and 5) exposure history. Interviews were conducted with child-bearing-age minority women at Metro Nashville General Hospital at Meharry Medical College. Data were analyzed utilizing DTReg software for Support Vector Machine (SVM) modeling followed by an SPSS package for a logistic regression model. The target (outcome) variable of interest was respondent's residence by ZIP code. The results demonstrate that the rank order of important variables with respect to SVM modeling versus traditional logistic regression models is almost identical. This is the first study documenting that SVM analysis has discriminate power for determination of higher-ordered spatial relationships on an environmental exposure history questionnaire.

Longitudinal Variations of Low-Latitude Gravity Waves and Their Impacts on the Ionosphere

NASA Astrophysics Data System (ADS)

Cullens, C. Y.; England, S.; Immel, T. J.

2014-12-01

The lower atmospheric forcing has important roles in the ionospheric variability. However, influences of lower atmospheric gravity waves on the ionospheric variability are still not clear due to the simplified gravity wave parameterizations and the limited knowledge of gravity wave distributions. In this study, we aim to study the longitudinal variations of gravity waves and their impacts of longitudinal variations of low-latitude gravity waves on the ionospheric variability. Our SABER results show that longitudinal variations of gravity waves at the lower boundary of TIME-GCM are the largest in June-August and January-February. We have implemented these low-latitude gravity wave variations from SABER instrument into TIME-GCM model. TIME-GCM simulation results of ionospheric responses to longitudinal variations of gravity waves and physical mechanisms will be discussed.

Exploring noctilucent cloud variability using the nudged and extended version of the Canadian Middle Atmosphere Model

NASA Astrophysics Data System (ADS)

Kuilman, Maartje; Karlsson, Bodil; Benze, Susanne; Megner, Linda

2017-11-01

Ice particles in the summer mesosphere - such as those connected to noctilucent clouds and polar mesospheric summer echoes - have since their discovery contributed to the uncovering of atmospheric processes on various scales ranging from interactions on molecular levels to global scale circulation patterns. While there are numerous model studies on mesospheric ice microphysics and how the clouds relate to the background atmosphere, there are at this point few studies using comprehensive global climate models to investigate observed variability and climatology of noctilucent clouds. In this study it is explored to what extent the large-scale inter-annual characteristics of noctilucent clouds are captured in a 30-year run - extending from 1979 to 2009 - of the nudged and extended version of the Canadian Middle Atmosphere Model (CMAM30). To construct and investigate zonal mean inter-seasonal variability in noctilucent cloud occurrence frequency and ice mass density in both hemispheres, a simple cloud model is applied in which it is assumed that the ice content is solely controlled by the local temperature and water vapor volume mixing ratio. The model results are compared to satellite observations, each having an instrument-specific sensitivity when it comes to detecting noctilucent clouds. It is found that the model is able to capture the onset dates of the NLC seasons in both hemispheres as well as the hemispheric differences in NLCs, such as weaker NLCs in the SH than in the NH and differences in cloud height. We conclude that the observed cloud climatology and zonal mean variability are well captured by the model.

Biomechanical risk factors for proximal junctional kyphosis: a detailed numerical analysis of surgical instrumentation variables.

PubMed

Cammarata, Marco; Aubin, Carl-Éric; Wang, Xiaoyu; Mac-Thiong, Jean-Marc

2014-04-15

Biomechanical analysis of proximal junctional kyphosis (PJK) through computer simulations and sensitivity analysis. To gain biomechanical knowledge on the risk of PJK and find surgical solutions to reduce the risks. PJK is a pathological kyphotic deformity adjacent to the instrumentation. Clinical studies have documented its risk factors, but still little is known on how it is correlated with various individual instrumentation variables. Biomechanical spine models of 6 patients with adult scoliosis were developed, validated, and then used to perform 576 simulations, varying the proximal dissection procedure, the implant type at the upper instrumented vertebra, the sagittal rod curvature, and the proximal diameter of the proximal transition rods. Four biomechanical indices--the proximal junctional kyphotic angle, thoracic kyphosis, proximal flexion force, and proximal flexion moment--were assessed. The bilateral complete facetectomy, the posterior ligaments resection, and the combination of both increased the proximal junctional kyphotic angle (respectively, by 10%, 28% and 53%) and the proximal flexion force (4%, 12%, and 22%) and moment (16%, 44%, and 83%). Compared with pedicle screws at upper instrumented vertebra, proximal transverse process hooks reduced the 3 biomechanical indices by approximately 26%. The use of proximal transition rods with reduced proximal diameter from 5.5 mm to 4 mm decreased the proximal junctional kyphotic angle (by 6%) and the proximal flexion force (4%) and moment (8%). The increase of the sagittal rod curvature from 10° to 20°, 30°, and 40° increased the proximal junctional kyphotic angle (by 6%, 13%, and 19%) and the proximal flexion force (3%, 7%, and 10%) and moment (9%, 18%, and 27%). Preserving more posterior proximal intervertebral elements, the use of transition rods and transverse process hooks at upper instrumented vertebra, and reducing the global sagittal rod curvature each decreased the 4 biomechanical indices that may be involved in PJK. N/A.

Development of an audit instrument for nursing care plans in the patient record

PubMed Central

Bjorvell, C; Thorell-Ekstrand, I; Wredling, R

2000-01-01

Objectives—To develop, validate, and test the reliability of an audit instrument that measures the extent to which patient records describe important aspects of nursing care. Material—Twenty records from each of three hospital wards were collected and audited. The auditors were registered nurses with a knowledge of nursing documentation in accordance with the VIPS model—a model designed to structure nursing documentation. (VIPS is an acronym formed from the Swedish words for wellbeing, integrity, prevention, and security.) Methods—An audit instrument was developed by determining specific criteria to be met. The audit questions were aimed at revealing the content of the patient for nursing assessment, nursing diagnosis, planned interventions, and outcome. Each of the 60 records was reviewed by the three auditors independently and the reliability of the instrument was tested by calculating the inter-rater reliability coefficient. Content validity was tested by using an expert panel and calculating the content validity ratio. The criterion related validity was estimated by the correlation between the score of the Cat-ch-Ing instrument and the score of an earlier developed and used audit instrument. The results were then tested by using Pearson's correlation coefficient. Results—The new audit instrument, named Cat-ch-Ing, consists of 17 questions designed to judge the nursing documentation. Both quantity and quality variables are judged on a rating scale from zero to three, with a maximum score of 80. The inter-rater reliability coefficients were 0.98, 0.98, and 0.92, respectively for each group of 20 records, the content validity ratio ranged between 0.20 and 1.0 and the criterion related validity showed a significant correlation of r = 0.68 (p< 0.0001, 95% CI 0.57 to 0.76) between the two audit instruments. Conclusion—The Cat-ch-Ing instrument has proved to be a valid and reliable audit instrument for nursing records when the VIPS model is used as the basis of the documentation. (Quality in Health Care 2000;9:6–13) Key Words: audit instrument; nursing care plans; quality assurance PMID:10848373

Pacific and Atlantic influences on Mesoamerican climate over the past millennium

NASA Astrophysics Data System (ADS)

Stahle, D. W.; Burnette, D. J.; Diaz, J. Villanueva; Heim, R. R.; Fye, F. K.; Paredes, J. Cerano; Soto, R. Acuna; Cleaveland, M. K.

2012-09-01

A new tree-ring reconstruction of the Palmer Drought Severity Index (PDSI) for Mesoamerica from AD 771 to 2008 identifies megadroughts more severe and sustained than any witnessed during the twentieth century. Correlation analyses indicate strong forcing of instrumental and reconstructed June PDSI over Mesoamerica from the El Niño/Southern Oscillation (ENSO). Spectral analyses of the 1,238-year reconstruction indicate significant concentrations of variance at ENSO, sub-decadal, bi-decadal, and multidecadal timescales. Instrumental and model-based analyses indicate that the Atlantic Multidecadal Oscillation is important to warm season climate variability over Mexico. Ocean-atmospheric variability in the Atlantic is not strongly correlated with the June PDSI reconstruction during the instrumental era, but may be responsible for the strong multidecadal variance detected in the reconstruction episodically over the past millennium. June drought indices in Mesoamerica are negatively correlated with gridded June PDSI over the United States from 1950 to 2005, based on both instrumental and reconstructed data. Interannual variability in this latitudinal moisture gradient is due in part to ENSO forcing, where warm events favor wet June PDSI conditions over the southern US and northern Mexico, but dryness over central and southern Mexico (Mesoamerica). Strong anti-phasing between multidecadal regimes of tree-ring reconstructed June PDSI over Mesoamerica and reconstructed summer (JJA) PDSI over the Southwest has also been detected episodically over the past millennium, including the 1950-1960s when La Niña and warm Atlantic SSTs prevailed, and the 1980-1990s when El Niño and cold Atlantic SSTs prevailed. Several Mesoamerican megadroughts are reconstructed when wetness prevailed over the Southwest, including the early tenth century Terminal Classic Drought, implicating El Niño and Atlantic SSTs in this intense and widespread drought that may have contributed to social changes in ancient Mexico.

Comparing surgical trays with redundant instruments with trays with reduced instruments: a cost analysis

PubMed Central

John-Baptiste, A.; Sowerby, L.J.; Chin, C.J.; Martin, J.; Rotenberg, B.W.

2016-01-01

Background: When prearranged standard surgical trays contain instruments that are repeatedly unused, the redundancy can result in unnecessary health care costs. Our objective was to estimate potential savings by performing an economic evaluation comparing the cost of surgical trays with redundant instruments with surgical trays with reduced instruments ("reduced trays"). Methods: We performed a cost-analysis from the hospital perspective over a 1-year period. Using a mathematical model, we compared the direct costs of trays containing redundant instruments to reduced trays for 5 otolaryngology procedures. We incorporated data from several sources including local hospital data on surgical volume, the number of instruments on redundant and reduced trays, wages of personnel and time required to pack instruments. From the literature, we incorporated instrument depreciation costs and the time required to decontaminate an instrument. We performed 1-way sensitivity analyses on all variables, including surgical volume. Costs were estimated in 2013 Canadian dollars. Results: The cost of redundant trays was $21 806 and the cost of reduced trays was $8803, for a 1-year cost saving of $13 003. In sensitivity analyses, cost savings ranged from $3262 to $21 395, based on the surgical volume at the institution. Variation in surgical volume resulted in a wider range of estimates, with a minimum of $3253 for low-volume to a maximum of $52 012 for high-volume institutions. Interpretation: Our study suggests moderate savings may be achieved by reducing surgical tray redundancy and, if applied to other surgical specialties, may result in savings to Canadian health care systems. PMID:27975045

Comparing surgical trays with redundant instruments with trays with reduced instruments: a cost analysis.

PubMed

John-Baptiste, A; Sowerby, L J; Chin, C J; Martin, J; Rotenberg, B W

2016-01-01

When prearranged standard surgical trays contain instruments that are repeatedly unused, the redundancy can result in unnecessary health care costs. Our objective was to estimate potential savings by performing an economic evaluation comparing the cost of surgical trays with redundant instruments with surgical trays with reduced instruments ("reduced trays"). We performed a cost-analysis from the hospital perspective over a 1-year period. Using a mathematical model, we compared the direct costs of trays containing redundant instruments to reduced trays for 5 otolaryngology procedures. We incorporated data from several sources including local hospital data on surgical volume, the number of instruments on redundant and reduced trays, wages of personnel and time required to pack instruments. From the literature, we incorporated instrument depreciation costs and the time required to decontaminate an instrument. We performed 1-way sensitivity analyses on all variables, including surgical volume. Costs were estimated in 2013 Canadian dollars. The cost of redundant trays was $21 806 and the cost of reduced trays was $8803, for a 1-year cost saving of $13 003. In sensitivity analyses, cost savings ranged from $3262 to $21 395, based on the surgical volume at the institution. Variation in surgical volume resulted in a wider range of estimates, with a minimum of $3253 for low-volume to a maximum of $52 012 for high-volume institutions. Our study suggests moderate savings may be achieved by reducing surgical tray redundancy and, if applied to other surgical specialties, may result in savings to Canadian health care systems.

Investigation of Music Student Efficacy as Influenced by Age, Experience, Gender, Ethnicity, and Type of Instrument Played in South Carolina

ERIC Educational Resources Information Center

White, Norman

2010-01-01

The purpose of this research study was to quantitatively examine South Carolina high school instrumental music students' self-efficacy as measured by the Generalized Self-Efficacy (GSE) instrument (Schwarzer & Jerusalem, 1993). The independent variables of age, experience, gender, ethnicity, and type of instrument played) were correlated with…

Solar radiance models for determination of ERBE scanner filter factor

NASA Technical Reports Server (NTRS)

Arduini, R. F.

1985-01-01

Shortwave spectral radiance models for use in the spectral correction algorithms for the ERBE Scanner Instrument are provided. The required data base was delivered to the ERBe Data Reduction Group in October 1984. It consisted of two sets of data files: (1) the spectral bidirectional angular models and (2) the spectral flux modes. The bidirectional models employ the angular characteristics of reflection by the Earth-atmosphere system and were derived from detailed radiance calculations using a finite difference model of the radiative transfer process. The spectral flux models were created through the use of a delta-Eddington model to economically simulate the effects of atmospheric variability. By combining these data sets, a wide range of radiances may be approximated for a number of scene types.

(In)Consistent estimates of changes in relative precipitation in an European domain over the last 350 years

NASA Astrophysics Data System (ADS)

Bothe, Oliver; Wagner, Sebastian; Zorita, Eduardo

2015-04-01

How did regional precipitation change in past centuries? We have potentially three sources of information to answer this question: There are, especially for Europe, a number of long records of local station precipitation; documentary records and natural archives of past environmental variability serve as proxy records for empirical reconstructions; in addition, simulations with coupled climate models or Earth System Models provide estimates on the spatial structure of precipitation variability. However, instrumental records rarely extend back to the 18th century, reconstructions include large uncertainties, and simulation skill is often still unsatisfactory for precipitation. Thus, we can only seek to answer to which extent the three sources provide a consistent picture of past regional precipitation changes. This presentation describes the (lack of) consistency in describing changes of the distributional properties of seasonal precipitation between the different data sources. We concentrate on England and Wales since there are two recent reconstructions and a long observation based record available for this domain. The season of interest is an extended spring (March, April, May, June, July, MAMJJ) over the past 350 years. The main simulated data stem from a regional simulation for the European domain with CCLM driven at its lateral boundaries with conditions provided by a MPI-ESM COSMOS simulation for the last millennium using a high-amplitude solar forcing. A number of simulations for the past 1000 years from the Paleoclimate Modelling Intercomparison Project Phase III provide additional information. We fit a Weibull distribution to the available data sets following the approach for calculating standardized precipitation indices. We do so over 51 year moving windows to assess the consistency of changes in the distributional properties. Changes in the percentiles for severe (and extreme) dry or wet conditions and in the Weibull standard deviations of precipitation estimates are generally not consistent among the different data sets. Only few common signals are evident. Even the relatively strong exogenous forcing history of the late 18th and early 19th century appears to have only small effects on the precipitation distributions. The reconstructions differ systematically from the long instrumental data in displaying much stronger variability compared to the observations over their common period. Distributional properties for both data sets show to some extent opposite evolutions. The reconstructions do not reliably represent the distributions in specific periods but rather reflect low-frequency changes in the mean plus a certain amount of noise. Moreover, also multi-model simulations do not agree on the changes over this period. The lack of consistent simulated relations under purely naturally forced and internal variability on multi-decadal time-scales therefore questions our ability to conclude on dynamical inferences about regional climate variability in the PMIP3 ensemble and, in turn, in climate simulations in general. The potentially opposite evolution of reconstructions and instrumental data for the chosen domain further hampers reconciling available information about past regional precipitation variability in England and Wales. However, we find some possibly surprising but encouraging agreement between the observed data and the regional simulation.

Mapping Variables.

ERIC Educational Resources Information Center

Stone, Mark H.; Wright, Benjamin D.; Stenner, A. Jackson

1999-01-01

Describes mapping variables, the principal technique for planning and constructing a test or rating instrument. A variable map is also useful for interpreting results. Provides several maps to show the importance and value of mapping a variable by person and item data. (Author/SLD)

Intelligent evaluation of color sensory quality of black tea by visible-near infrared spectroscopy technology: A comparison of spectra and color data information

NASA Astrophysics Data System (ADS)

Ouyang, Qin; Liu, Yan; Chen, Quansheng; Zhang, Zhengzhu; Zhao, Jiewen; Guo, Zhiming; Gu, Hang

2017-06-01

Instrumental test of black tea samples instead of human panel test is attracting massive attention recently. This study focused on an investigation of the feasibility for estimation of the color sensory quality of black tea samples using the VIS-NIR spectroscopy technique, comparing the performances of models based on the spectra and color information. In model calibration, the variables were first selected by genetic algorithm (GA); then the nonlinear back propagation-artificial neural network (BPANN) models were established based on the optimal variables. In comparison with the other models, GA-BPANN models from spectra data information showed the best performance, with the correlation coefficient of 0.8935, and the root mean square error of 0.392 in the prediction set. In addition, models based on the spectra information provided better performance than that based on the color parameters. Therefore, the VIS-NIR spectroscopy technique is a promising tool for rapid and accurate evaluation of the sensory quality of black tea samples.

Intelligent evaluation of color sensory quality of black tea by visible-near infrared spectroscopy technology: A comparison of spectra and color data information.

PubMed

Ouyang, Qin; Liu, Yan; Chen, Quansheng; Zhang, Zhengzhu; Zhao, Jiewen; Guo, Zhiming; Gu, Hang

2017-06-05

Instrumental test of black tea samples instead of human panel test is attracting massive attention recently. This study focused on an investigation of the feasibility for estimation of the color sensory quality of black tea samples using the VIS-NIR spectroscopy technique, comparing the performances of models based on the spectra and color information. In model calibration, the variables were first selected by genetic algorithm (GA); then the nonlinear back propagation-artificial neural network (BPANN) models were established based on the optimal variables. In comparison with the other models, GA-BPANN models from spectra data information showed the best performance, with the correlation coefficient of 0.8935, and the root mean square error of 0.392 in the prediction set. In addition, models based on the spectra information provided better performance than that based on the color parameters. Therefore, the VIS-NIR spectroscopy technique is a promising tool for rapid and accurate evaluation of the sensory quality of black tea samples. Copyright © 2017 Elsevier B.V. All rights reserved.

Extreme Ultraviolet Variability Experiment (EVE) on the Solar Dynamics Observatory (SDO): Overview of Science Objectives, Instrument Design, Data Products, and Model Developments

NASA Technical Reports Server (NTRS)

Woods, T. N.; Eparvier, F. G.; Hock, R.; Jones, A. R.; Woodraska, D.; Judge, D.; Didkovsky, L.; Lean, J.; Mariska, J.; Warren, H.;

Assessment of uncertainty in ROLO lunar irradiance for on-orbit calibration

USGS Publications Warehouse

Stone, T.C.; Kieffer, H.H.; Barnes, W.L.; Butler, J.J.

2004-01-01

A system to provide radiometric calibration of remote sensing imaging instruments on-orbit using the Moon has been developed by the US Geological Survey RObotic Lunar Observatory (ROLO) project. ROLO has developed a model for lunar irradiance which treats the primary geometric variables of phase and libration explicitly. The model fits hundreds of data points in each of 23 VNIR and 9 SWIR bands; input data are derived from lunar radiance images acquired by the project's on-site telescopes, calibrated to exoatmospheric radiance and converted to disk-equivalent reflectance. Experimental uncertainties are tracked through all stages of the data processing and modeling. Model fit residuals are ???1% in each band over the full range of observed phase and libration angles. Application of ROLO lunar calibration to SeaWiFS has demonstrated the capability for long-term instrument response trending with precision approaching 0.1% per year. Current work involves assessing the error in absolute responsivity and relative spectral response of the ROLO imaging systems, and propagation of error through the data reduction and modeling software systems with the goal of reducing the uncertainty in the absolute scale, now estimated at 5-10%. This level is similar to the scatter seen in ROLO lunar irradiance comparisons of multiple spacecraft instruments that have viewed the Moon. A field calibration campaign involving NASA and NIST has been initiated that ties the ROLO lunar measurements to the NIST (SI) radiometric scale.

Instrument scanning and controlling: Using eye movement data to understand pilot behavior and strategies

NASA Technical Reports Server (NTRS)

Dick, A. O.

1980-01-01

Eye movement data and other parameters including instrument readings, aircraft state and position variables, and control maneuvers were recorded while pilots flew ILS simulations in a B 737. The experiment itself employed seven airline pilots, each of whom flew approximately 40 approach/landing sequences. The simulator was equipped with a night visual scene but the scene was fogged out down to approximately 60 meters (200 ft). The instrument scanning appeared to follow aircraft parameters not physical position of instruments. One important implication of the results is: pilots look for categories or packets of information. Control inputs were tabulated according to throttle, wheel position, column, and pitch trim changes. Three seconds of eye movements before and after the control input were then obtained. Analysis of the eye movement data for the controlling periods showed clear patterns. The results suggest a set of miniscan patterns which are used according to the specific details of the situation. A model is developed which integrates scanning and controlling. Differentiations are made between monitoring and controlling scans.

Predicting College Women's Career Plans: Instrumentality, Work, and Family

ERIC Educational Resources Information Center

Savela, Alexandra E.; O'Brien, Karen M.

2016-01-01

This study examined how college women's instrumentality and expectations about combining work and family predicted early career development variables. Specifically, 177 undergraduate women completed measures of instrumentality (i.e., traits such as ambition, assertiveness, and risk taking), willingness to compromise career for family, anticipated…

A critical appraisal of instruments to measure outcomes of interprofessional education.

PubMed

Oates, Matthew; Davidson, Megan

2015-04-01

Interprofessional education (IPE) is believed to prepare health professional graduates for successful collaborative practice. A range of instruments have been developed to measure the outcomes of IPE. An understanding of the psychometric properties of these instruments is important if they are to be used to measure the effectiveness of IPE. This review set out to identify instruments available to measure outcomes of IPE and collaborative practice in pre-qualification health professional students and to critically appraise the psychometric properties of validity, responsiveness and reliability against contemporary standards for instrument design. Instruments were selected from a pool of extant instruments and subjected to critical appraisal to determine whether they satisfied inclusion criteria. The qualitative and psychometric attributes of the included instruments were appraised using a checklist developed for this review. Nine instruments were critically appraised, including the widely adopted Readiness for Interprofessional Learning Scale (RIPLS) and the Interdisciplinary Education Perception Scale (IEPS). Validity evidence for instruments was predominantly based on test content and internal structure. Ceiling effects and lack of scale width contribute to the inability of some instruments to detect change in variables of interest. Limited reliability data were reported for two instruments. Scale development and scoring protocols were generally reported by instrument developers, but the inconsistent application of scoring protocols for some instruments was apparent. A number of instruments have been developed to measure outcomes of IPE in pre-qualification health professional students. Based on reported validity evidence and reliability data, the psychometric integrity of these instruments is limited. The theoretical test construction paradigm on which instruments have been developed may be contributing to the failure of some instruments to detect change in variables of interest following an IPE intervention. These limitations should be considered in any future research on instrument design. © 2015 John Wiley & Sons Ltd.

Versailles Project on Advanced Materials and Standards Interlaboratory Study on Measuring the Thickness and Chemistry of Nanoparticle Coatings Using XPS and LEIS

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

Belsey, Natalie A.; Cant, David J. H.; Minelli, Caterina

We report the results of a VAMAS (Versailles Project on Advanced Materials and Standards) inter-laboratory study on the measurement of the shell thickness and chemistry of nanoparticle coatings. Peptide-coated gold particles were supplied to laboratories in two forms: a colloidal suspension in pure water and; particles dried onto a silicon wafer. Participants prepared and analyzed these samples using either X-ray photoelectron spectroscopy (XPS) or low energy ion scattering (LEIS). Careful data analysis revealed some significant sources of discrepancy, particularly for XPS. Degradation during transportation, storage or sample preparation resulted in a variability in thickness of 53 %. The calculation methodmore » chosen by XPS participants contributed a variability of 67 %. However, variability of 12 % was achieved for the samples deposited using a single method and by choosing photoelectron peaks that were not adversely affected by instrumental transmission effects. The study identified a need for more consistency in instrumental transmission functions and relative sensitivity factors, since this contributed a variability of 33 %. The results from the LEIS participants were more consistent, with variability of less than 10 % in thickness and this is mostly due to a common method of data analysis. The calculation was performed using a model developed for uniform, flat films and some participants employed a correction factor to account for the sample geometry, which appears warranted based upon a simulation of LEIS data from one of the participants and comparison to the XPS results.« less

Physical fitness predicts technical-tactical and time-motion profile in simulated Judo and Brazilian Jiu-Jitsu matches

PubMed Central

Gentil, Paulo; Bueno, João C.A.; Follmer, Bruno; Marques, Vitor A.; Del Vecchio, Fabrício B.

2018-01-01

Background Among combat sports, Judo and Brazilian Jiu-Jitsu (BJJ) present elevated physical fitness demands from the high-intensity intermittent efforts. However, information regarding how metabolic and neuromuscular physical fitness is associated with technical-tactical performance in Judo and BJJ fights is not available. This study aimed to relate indicators of physical fitness with combat performance variables in Judo and BJJ. Methods The sample consisted of Judo (n = 16) and BJJ (n = 24) male athletes. At the first meeting, the physical tests were applied and, in the second, simulated fights were performed for later notational analysis. Results The main findings indicate: (i) high reproducibility of the proposed instrument and protocol used for notational analysis in a mobile device; (ii) differences in the technical-tactical and time-motion patterns between modalities; (iii) performance-related variables are different in Judo and BJJ; and (iv) regression models based on metabolic fitness variables may account for up to 53% of the variances in technical-tactical and/or time-motion variables in Judo and up to 31% in BJJ, whereas neuromuscular fitness models can reach values up to 44 and 73% of prediction in Judo and BJJ, respectively. When all components are combined, they can explain up to 90% of high intensity actions in Judo. Discussion In conclusion, performance prediction models in simulated combat indicate that anaerobic, aerobic and neuromuscular fitness variables contribute to explain time-motion variables associated with high intensity and technical-tactical variables in Judo and BJJ fights. PMID:29844991

The Measurement of the Solar Spectral Irradiance Variability at 782 nm during the Solar Cycle 24 using the SES on-board PICARD

NASA Astrophysics Data System (ADS)

Meftah, Mustapha; Hauchecorne, Alain; Irbah, Abdanour; Bekki, Slimane

2016-04-01

A Sun Ecartometry Sensor (SES) was developed to provide the stringent pointing requirements of the PICARD satellite. The SES sensor produced an image of the Sun at 782+/-5 nm. From the SES data, we obtained a new time series of the solar spectral irradiance at 782nm from 2010 to 2014. SES observations provided a qualitatively consistent evolution of the solar spectral irradiance variability at 782 nm during the solar cycle 24. Comparisons will be made with Spectral And Total Irradiance REconstruction for the Satellite era (SATIRE-S) semi-empirical model and with the Spectral Irradiance Monitor instrument (SIM) on-board the Solar Radiation and Climate Experiment satellite (SORCE). These data will help to improve the representation of the solar forcing in the IPSL Global Circulation Model.

Factors related to the quality of life of older prisoners.

PubMed

De Smet, Stefaan; De Donder, Liesbeth; Ryan, Denis; Van Regenmortel, Sofie; Brosens, Dorien; Vandevelde, Stijn

2017-06-01

There is evidence of an increasing emphasis on the relevance of the quality of life-paradigm as an outcome measure for clients in geriatric, forensic, as well as correctional care. This paper aims to explore to what extent variables that were categorized according to the main areas of the Good Lives Model ('the self', 'the body' and 'social life') are related to the quality of life domains of older imprisoned offenders. Data were collected by means of a structured questionnaire administered in individual interviews with 93 older prisoners aged 60 years and over in 16 prisons of the Dutch-speaking region in Belgium. Characteristics of the main GLM-areas were identified by specifically designed items as well three validated instruments (psychiatric disorders, loneliness, and frailty). Dependent variables consisted of the four sub-domains of the WHOQOL-BREF instrument which measures quality of life in four domains, namely: (1) physical health, (2) psychological health, (3) social relationships, and (4) environment. Structural equation modelling (SEM) was used for statistical analysis. Individual variables, such as satisfaction with activities, were related to the older prisoners' QoL in several domains simultaneously. Other than suicidal ideation, psychopathological symptoms had no significant relation to quality of life. Approaches enabling older prisoner to disclose their interests, experiences, and feelings are important in prison. Special attention should be given to psychiatric and age-related symptoms of older prisoners, since they may not be noted by the prison staff, as older prisoners seem to be poorer self-advocates as compared to their younger peers.

Dysphagia Management and Research in an Acute-Care Military Treatment Facility: The Role of Applied Informatics.

PubMed

Solomon, Nancy Pearl; Dietsch, Angela M; Dietrich-Burns, Katie E; Styrmisdottir, Edda L; Armao, Christopher S

2016-05-01

This report describes the development and preliminary analysis of a database for traumatically injured military service members with dysphagia. A multidimensional database was developed to capture clinical variables related to swallowing. Data were derived from clinical records and instrumental swallow studies, and ranged from demographics, injury characteristics, swallowing biomechanics, medications, and standardized tools (e.g., Glasgow Coma Scale, Penetration-Aspiration Scale). Bayesian Belief Network modeling was used to analyze the data at intermediate points, guide data collection, and predict outcomes. Predictive models were validated with independent data via receiver operating characteristic curves. The first iteration of the model (n = 48) revealed variables that could be collapsed for the second model (n = 96). The ability to predict recovery from dysphagia improved from the second to third models (area under the curve = 0.68 to 0.86). The third model, based on 161 cases, revealed "initial diet restrictions" as first-degree, and "Glasgow Coma Scale, intubation history, and diet change" as second-degree associates for diet restrictions at discharge. This project demonstrates the potential for bioinformatics to advance understanding of dysphagia. This database in concert with Bayesian Belief Network modeling makes it possible to explore predictive relationships between injuries and swallowing function, individual variability in recovery, and appropriate treatment options. Reprint & Copyright © 2016 Association of Military Surgeons of the U.S.

Development of a new linearly variable edge filter (LVEF)-based compact slit-less mini-spectrometer

NASA Astrophysics Data System (ADS)

Mahmoud, Khaled; Park, Seongchong; Lee, Dong-Hoon

2018-02-01

This paper presents the development of a compact charge-coupled detector (CCD) spectrometer. We describe the design, concept and characterization of VNIR linear variable edge filter (LVEF)- based mini-spectrometer. The new instrument has been realized for operation in the 300 nm to 850 nm wavelength range. The instrument consists of a linear variable edge filter in front of CCD array. Low-size, light-weight and low-cost could be achieved using the linearly variable filters with no need to use any moving parts for wavelength selection as in the case of commercial spectrometers available in the market. This overview discusses the main components characteristics, the main concept with the main advantages and limitations reported. Experimental characteristics of the LVEFs are described. The mathematical approach to get the position-dependent slit function of the presented prototype spectrometer and its numerical de-convolution solution for a spectrum reconstruction is described. The performance of our prototype instrument is demonstrated by measuring the spectrum of a reference light source.

Can we quantify the variability of soil moisture across scales using Electromagnetic Induction ?

NASA Astrophysics Data System (ADS)

Robinet, Jérémy; von Hebel, Christian; van der Kruk, Jan; Govers, Gerard; Vanderborght, Jan

2017-04-01

Soil moisture is a key variable in many natural processes. Therefore, technological and methodological advancements are of primary importance to provide accurate measurements of spatial and temporal variability of soil moisture. In that context, ElectroMagnetic Induction (EMI) instruments are often cited as a hydrogeophysical method with a large potential, through the measurement of the soil apparent electrical conductivity (ECa). To our knowledge, no studies have evaluated the potential of EMI to characterize variability of soil moisture on both agricultural and forested land covers in a (sub-) tropical environment. These differences in land use could be critical as differences in temperature, transpiration and root water uptake can have significant effect, notably on the electrical conductivity of the pore water. In this study, we used an EMI instrument to carry out a first assessment of the impact of deforestation and agriculture on soil moisture in a subtropical region in the south of Brazil. We selected slopes of different topographies (gentle vs. steep) and contrasting land uses (natural forest vs. agriculture) within two nearby catchments. At selected locations on the slopes, we measured simultaneously ECa using EMI and a depth-weighted average of the soil moisture using TDR probes installed within soil pits. We found that the temporal variability of the soil moisture could not be measured accurately with EMI, probably because of important temporal variations of the pore water electrical conductivity and the relatively small temporal variations in soil moisture content. However, we found that its spatial variability could be effectively quantified using a non-linear relationship, for both intra- and inter-slopes variations. Within slopes, the ECa could explained between 67 and 90% of the variability of the soil moisture, while a single non-linear model for all the slopes could explain 55% of the soil moisture variability. We eventually showed that combining a specific relationship for the most degraded slope (steep slope under agriculture) and a single relationship for all the other slopes, both non-linear relations, yielded the best results with an overall explained variance of 90%. We applied the latter model to measurements of the ECa along transects at the different slopes, which allowed us to highlight the strong control of topography on the soil moisture content. We also observed a significant impact of the land use with higher moisture content on the agricultural slopes, probably due to a reduced evapotranspiration.

Instrumental variable applications using nursing home prescribing preferences in comparative effectiveness research.

PubMed

Huybrechts, Krista F; Gerhard, Tobias; Franklin, Jessica M; Levin, Raisa; Crystal, Stephen; Schneeweiss, Sebastian

2014-08-01

Nursing home residents are of particular interest for comparative effectiveness research given their susceptibility to adverse treatment effects and systematic exclusion from trials. However, the risk of residual confounding because of unmeasured markers of declining health using conventional analytic methods is high. We evaluated the validity of instrumental variable (IV) methods based on nursing home prescribing preference to mitigate such confounding, using psychotropic medications to manage behavioral problems in dementia as a case study. A cohort using linked data from Medicaid, Medicare, Minimum Data Set, and Online Survey, Certification and Reporting for 2001-2004 was established. Dual-eligible patients ≥65 years who initiated psychotropic medication use after admission were selected. Nursing home prescribing preference was characterized using mixed-effects logistic regression models. The plausibility of IV assumptions was explored, and the association between psychotropic medication class and 180-day mortality was estimated. High-prescribing and low-prescribing nursing homes differed by a factor of 2. Each preference-based IV measure described a substantial proportion of variation in psychotropic medication choice (β(IV → treatment): 0.22-0.36). Measured patient characteristics were well balanced across patient groups based on instrument status (52% average reduction in Mahalanobis distance). There was no evidence that instrument status was associated with markers of nursing home quality of care. Findings indicate that IV analyses using nursing home prescribing preference may be a useful approach in comparative effectiveness studies, and should extend naturally to analyses including untreated comparison groups, which are of great scientific interest but subject to even stronger confounding. Copyright © 2014 John Wiley & Sons, Ltd.

The radiation budget of stratocumulus clouds measured by tethered balloon instrumentation: Variability of flux measurements

NASA Technical Reports Server (NTRS)

Duda, David P.; Stephens, Graeme L.; Cox, Stephen K.

1990-01-01

Measurements of longwave and shortwave radiation were made using an instrument package on the NASA tethered balloon during the FIRE Marine Stratocumulus experiment. Radiation data from two pairs of pyranometers were used to obtain vertical profiles of the near-infrared and total solar fluxes through the boundary layer, while a pair of pyrgeometers supplied measurements of the longwave fluxes in the cloud layer. The radiation observations were analyzed to determine heating rates and to measure the radiative energy budget inside the stratocumulus clouds during several tethered balloon flights. The radiation fields in the cloud layer were also simulated by a two-stream radiative transfer model, which used cloud optical properties derived from microphysical measurements and Mie scattering theory.

Science Accomplishments from a Decade of Aura OMI/MLS Tropospheric Ozone Measurements

NASA Technical Reports Server (NTRS)

Ziemke, Jerald R.; Douglass, Anne R.; Joiner, Joanna; Duncan, Bryan N.; Olsen, Mark A.; Oman, Luke D.; Witte, Jacquelyn C.; Liu, X.; Wargan, K.; Schoeberl, Mark R.;

Children’s Bonding with Parents and Grandparents and Its Associated Factors

PubMed Central

Li, Yuli; Cui, Naixue; Cao, Fenglin; Liu, Jianghong

2015-01-01

Previous literature has focused on the importance of both parental and grandparental bonding. However, few studies have been conducted to measure children’s bonding with parents and grandparents simultaneously, especially tested by the same instrument that offers more comparable results. Therefore, we studied the relationships between parental and grandparental bonding using the Parental Bonding Instrument (PBI), and possible associations between these bonds and sociodemographic variables in 905 Chinese children aged 10–14 years. Children’s bonding with mother, father, and grandparents were positively correlated, and the final mixed-effect model showed that several sociodemographic factors (e.g., gender, only children, parents’ marital status, and mother’s occupation) were associated with parental and grandparental bonding. PMID:27284385

Cesarean delivery rates among family physicians versus obstetricians: a population-based cohort study using instrumental variable methods

PubMed Central

Dawe, Russell Eric; Bishop, Jessica; Pendergast, Amanda; Avery, Susan; Monaghan, Kelly; Duggan, Norah; Aubrey-Bassler, Kris

2017-01-01

Background: Previous research suggests that family physicians have rates of cesarean delivery that are lower than or equivalent to those for obstetricians, but adjustments for risk differences in these analyses may have been inadequate. We used an econometric method to adjust for observed and unobserved factors affecting the risk of cesarean delivery among women attended by family physicians versus obstetricians. Methods: This retrospective population-based cohort study included all Canadian (except Quebec) hospital deliveries by family physicians and obstetricians between Apr. 1, 2006, and Mar. 31, 2009. We excluded women with multiple gestations, and newborns with a birth weight less than 500 g or gestational age less than 20 weeks. We estimated the relative risk of cesarean delivery using instrumental-variable-adjusted and logistic regression. Results: The final cohort included 776 299 women who gave birth in 390 hospitals. The risk of cesarean delivery was 27.3%, and the mean proportion of deliveries by family physicians was 26.9% (standard deviation 23.8%). The relative risk of cesarean delivery for family physicians versus obstetricians was 0.48 (95% confidence interval [CI] 0.41-0.56) with logistic regression and 1.27 (95% CI 1.02-1.57) with instrumental-variable-adjusted regression. Interpretation: Our conventional analyses suggest that family physicians have a lower rate of cesarean delivery than obstetricians, but instrumental variable analyses suggest the opposite. Because instrumental variable methods adjust for unmeasured factors and traditional methods do not, the large discrepancy between these estimates of risk suggests that clinical and/or sociocultural factors affecting the decision to perform cesarean delivery may not be accounted for in our database. PMID:29233843

The development of instruments to measure the work disability assessment behaviour of insurance physicians

PubMed Central

2011-01-01

Background Variation in assessments is a universal given, and work disability assessments by insurance physicians are no exception. Little is known about the considerations and views of insurance physicians that may partly explain such variation. On the basis of the Attitude - Social norm - self Efficacy (ASE) model, we have developed measurement instruments for assessment behaviour and its determinants. Methods Based on theory and interviews with insurance physicians the questionnaire included blocks of items concerning background variables, intentions, attitudes, social norms, self-efficacy, knowledge, barriers and behaviour of the insurance physicians in relation to work disability assessment issues. The responses of 231 insurance physicians were suitable for further analysis. Factor analysis and reliability analysis were used to form scale variables and homogeneity analysis was used to form dimension variables. Thus, we included 169 of the 177 original items. Results Factor analysis and reliability analysis yielded 29 scales with sufficient reliability. Homogeneity analysis yielded 19 dimensions. Scales and dimensions fitted with the concepts of the ASE model. We slightly modified the ASE model by dividing behaviour into two blocks: behaviour that reflects the assessment process and behaviour that reflects assessment behaviour. The picture that emerged from the descriptive results was of a group of physicians who were motivated in their job and positive about the Dutch social security system in general. However, only half of them had a positive opinion about the Dutch Work and Income (Capacity for Work) Act (WIA). They also reported serious barriers, the most common of which was work pressure. Finally, 73% of the insurance physicians described the majority of their cases as 'difficult'. Conclusions The scales and dimensions developed appear to be valid and offer a promising basis for future research. The results suggest that the underlying ASE model, in modified form, is suitable for describing the assessment behaviour of insurance physicians and the determinants of this behaviour. The next step in this line of research should be to validate the model using structural equation modelling. Finally, the predictive value should be tested in relation to outcome measurements of work disability assessments. PMID:21199570

Reconstructing pre-instrumental streamflow in Eastern Australia using a water balance approach

NASA Astrophysics Data System (ADS)

Tozer, C. R.; Kiem, A. S.; Vance, T. R.; Roberts, J. L.; Curran, M. A. J.; Moy, A. D.

2018-03-01

Streamflow reconstructions based on paleoclimate proxies provide much longer records than the short instrumental period records on which water resource management plans are currently based. In Australia there is a lack of in-situ high resolution paleoclimate proxy records, but remote proxies with teleconnections to Australian climate have utility in producing streamflow reconstructions. Here we investigate, via a case study for a catchment in eastern Australia, the novel use of an Antarctic ice-core based rainfall reconstruction within a Budyko-framework to reconstruct ∼1000 years of annual streamflow. The resulting streamflow reconstruction captures interannual to decadal variability in the instrumental streamflow, validating both the use of the ice core rainfall proxy record and the Budyko-framework method. In the preinstrumental era the streamflow reconstruction shows longer wet and dry epochs and periods of streamflow variability that are higher than observed in the instrumental era. Importantly, for both the instrumental record and preinstrumental reconstructions, the wet (dry) epochs in the rainfall record are shorter (longer) in the streamflow record and this non-linearity must be considered when inferring hydroclimatic risk or historical water availability directly from rainfall proxy records alone. These insights provide a better understanding of present infrastructure vulnerability in the context of past climate variability for eastern Australia. The streamflow reconstruction presented here also provides a better understanding of the range of hydroclimatic variability possible, and therefore represents a more realistic baseline on which to quantify the potential impacts of anthropogenic climate change on water security.

Thermal control unit for long-time survival of scientific instruments on lunar surface

NASA Astrophysics Data System (ADS)

Ogawa, Kazunori; Iijima, Yuichi; Tanaka, Satoshi

A thermal control unit (lunar survival module) is being developed for scientific instruments placed on the lunar surface. This unit is designed to be used on the future Japanese lunar landing mission SELENE-2. The lunar surface is a severe environment for scientific instruments. The absence of convective cooling by an atmosphere makes the ground surface temperature variable in the wide range of -200 to 100 degC, an environment in which space electronics can hardly survive. The surface elements must have a thermal control structure to maintain the inner temperature within the operable ranges of the instruments for long-time measurements, such as 1 month or longer beyond the lunar nights. The objectives of this study are to develop a thermal control unit for the SELENE-2 mission. So far, we conducted the concept design of the lunar survival module, and estimated its potential by a thermal mathematical model on the assumption of using a lunar seismometer designed for SELENE-2. The basic structure of the thermal module is rather simple in that a heat insulating shell covers the scientific instruments. The concept is that the conical insulator retains heat in the regolith soil in the daylight, and it can keep the device warm in the night. Results of the model calculations indicated the high potential of long-time survival. A bread board model (BBM) was manufactured, and its thermal-vacuum tests were conducted in order to estimate the validity of some thermal parameters assumed in the computed thermal model. The thermal condition of the lunar surface was simulated by glass beads paved in a vacuum chamber, and a temperature-controlled container. Temperature variations of the BBM in thermal cycling tests were compared to a thermal mathematical model, and the thermal parameters were finally assessed. Feeding the test results back into the thermal model for the lunar surface, some thermal parameters were updated but there was no critical effect on the survivability. The experimental results indicated a sufficient survivability potential of the concept of our thermal control system.

Mental models of audit and feedback in primary care settings.

PubMed

Hysong, Sylvia J; Smitham, Kristen; SoRelle, Richard; Amspoker, Amber; Hughes, Ashley M; Haidet, Paul

2018-05-30

Audit and feedback has been shown to be instrumental in improving quality of care, particularly in outpatient settings. The mental model individuals and organizations hold regarding audit and feedback can moderate its effectiveness, yet this has received limited study in the quality improvement literature. In this study we sought to uncover patterns in mental models of current feedback practices within high- and low-performing healthcare facilities. We purposively sampled 16 geographically dispersed VA hospitals based on high and low performance on a set of chronic and preventive care measures. We interviewed up to 4 personnel from each location (n = 48) to determine the facility's receptivity to audit and feedback practices. Interview transcripts were analyzed via content and framework analysis to identify emergent themes. We found high variability in the mental models of audit and feedback, which we organized into positive and negative themes. We were unable to associate mental models of audit and feedback with clinical performance due to high variance in facility performance over time. Positive mental models exhibit perceived utility of audit and feedback practices in improving performance; whereas, negative mental models did not. Results speak to the variability of mental models of feedback, highlighting how facilities perceive current audit and feedback practices. Findings are consistent with prior research  in that variability in feedback mental models is associated with lower performance.; Future research should seek to empirically link mental models revealed in this paper to high and low levels of clinical performance.

Spatial variability of extreme rainfall at radar subpixel scale

NASA Astrophysics Data System (ADS)

Peleg, Nadav; Marra, Francesco; Fatichi, Simone; Paschalis, Athanasios; Molnar, Peter; Burlando, Paolo

2018-01-01

Extreme rainfall is quantified in engineering practice using Intensity-Duration-Frequency curves (IDF) that are traditionally derived from rain-gauges and more recently also from remote sensing instruments, such as weather radars. These instruments measure rainfall at different spatial scales: rain-gauge samples rainfall at the point scale while weather radar averages precipitation on a relatively large area, generally around 1 km2. As such, a radar derived IDF curve is representative of the mean areal rainfall over a given radar pixel and neglects the within-pixel rainfall variability. In this study, we quantify subpixel variability of extreme rainfall by using a novel space-time rainfall generator (STREAP model) that downscales in space the rainfall within a given radar pixel. The study was conducted using a unique radar data record (23 years) and a very dense rain-gauge network in the Eastern Mediterranean area (northern Israel). Radar-IDF curves, together with an ensemble of point-based IDF curves representing the radar subpixel extreme rainfall variability, were developed fitting Generalized Extreme Value (GEV) distributions to annual rainfall maxima. It was found that the mean areal extreme rainfall derived from the radar underestimate most of the extreme values computed for point locations within the radar pixel (on average, ∼70%). The subpixel variability of rainfall extreme was found to increase with longer return periods and shorter durations (e.g. from a maximum variability of 10% for a return period of 2 years and a duration of 4 h to 30% for 50 years return period and 20 min duration). For the longer return periods, a considerable enhancement of extreme rainfall variability was found when stochastic (natural) climate variability was taken into account. Bounding the range of the subpixel extreme rainfall derived from radar-IDF can be of major importance for different applications that require very local estimates of rainfall extremes.

Approximate Dynamic Programming Algorithms for United States Air Force Officer Sustainment

DTIC Science & Technology

2015-03-26

level of correction needed. While paying bonuses has an easily calculable cost, RIFs have more subtle costs. Mone (1994) discovered that in a steady...a regression is performed utilizing instrumental variables to minimize Bellman error. This algorithm uses a set of basis functions to approximate the...transitioned to an all-volunteer force. Charnes et al. (1972) utilize a goal programming model for General Schedule civilian manpower management in the

No Time for Dead Time: Use the Fourier Amplitude Differences to Normalize Dead-time-affected Periodograms

NASA Astrophysics Data System (ADS)

Bachetti, Matteo; Huppenkothen, Daniela

2018-02-01

Dead time affects many of the instruments used in X-ray astronomy, by producing a strong distortion in power density spectra. This can make it difficult to model the aperiodic variability of the source or look for quasi-periodic oscillations. Whereas in some instruments a simple a priori correction for dead-time-affected power spectra is possible, this is not the case for others such as NuSTAR, where the dead time is non-constant and long (∼2.5 ms). Bachetti et al. (2015) suggested the cospectrum obtained from light curves of independent detectors within the same instrument as a possible way out, but this solution has always only been a partial one: the measured rms was still affected by dead time because the width of the power distribution of the cospectrum was modulated by dead time in a frequency-dependent way. In this Letter, we suggest a new, powerful method to normalize dead-time-affected cospectra and power density spectra. Our approach uses the difference of the Fourier amplitudes from two independent detectors to characterize and filter out the effect of dead time. This method is crucially important for the accurate modeling of periodograms derived from instruments affected by dead time on board current missions like NuSTAR and Astrosat, but also future missions such as IXPE.

The EPIC-MOS Particle-Induced Background Spectra

NASA Technical Reports Server (NTRS)

Kuntz, K. D.; Sowden, S. L.

2007-01-01

In order to analyse diffuse emission that fills the field of view, one must accurately characterize the instrumental backgrounds. For the XMM-Newton EPIC instrument these backgrounds include a temporally variable "quiescent" component. as well as the strongly variable soft proton contamination. We have characterized the spectral and spatial response of the EPIC detectors to these background components and have developed tools to remove these backgrounds from observations. The "quiescent" component was characterized using a combination of the filter-wheel-closed data and a database of unexposed-region data. The soft proton contamination was characterized by differencing images and spectra taken during flared and flare-free intervals. After application of our modeled backgrounds, the differences between independent observations of the same region of "blank sky" are consistent with the statistical uncertainties except when there is clear spectral evidence of solar wind charge exchange emission. Using a large sample of blank sky data, we show that strong magnetospheric SWCX emission requires elevated solar wind fluxes; observations through the densest part of the magnetosheath are not necessarily strongly contaminated with SWCX emission.

A System Trade Study of Remote Infrared Imaging for Space Shuttle Reentry

NASA Technical Reports Server (NTRS)

Schwartz, Richard J.; Ross, Martin N.; Baize, Rosemary; Horvath, Thomas J.; Berry, Scott A.; Krasa, Paul W.

2008-01-01

A trade study reviewing the primary operational parameters concerning the deployment of imaging assets in support of the Hypersonic Thermodynamic Infrared Measurements (HYTHIRM) project was undertaken. The objective was to determine key variables and constraints for obtaining thermal images of the Space Shuttle orbiter during reentry. The trade study investigated the performance characteristics and operating environment of optical instrumentation that may be deployed during a HYTHIRM data collection mission, and specified contributions to the Point Spread Function. It also investigated the constraints that have to be considered in order to optimize deployment through the use of mission planning tools. These tools simulate the radiance modeling of the vehicle as well as the expected spatial resolution based on the Orbiter trajectory and placement of land based or airborne optical sensors for given Mach numbers. Lastly, this report focused on the tools and methodology that have to be in place for real-time mission planning in order to handle the myriad of variables such as trajectory ground track, weather, and instrumentation availability that may only be known in the hours prior to landing.

Bullying among Spanish secondary education students: the role of gender traits, sexism, and homophobia.

PubMed

Carrera-Fernández, María-Victoria; Lameiras-Fernández, María; Rodríguez-Castro, Yolanda; Vallejo-Medina, Pablo

2013-09-01

The aim of the present study was to assess the combined influence of gender stereotypes, sexism, and homophobia on attitudes toward bullying and bullying behavior. A total of 1,500 Spanish adolescents between 12 and 18 years of age (49.3% girls and 50.7% boys) completed a questionnaire that included measures of bullying, attitudes toward bullying, gender-stereotyped personality traits (instrumentality and expressiveness), hostile and benevolent sexism, and attitudes toward gay men and lesbians. First, the findings demonstrated that boys scored significantly higher on all the variables assessed except on benevolent sexism. Two similar models were obtained for both sexes. Benevolent sexism and, in boys, more positive attitudes toward gay men predicted more negative attitudes toward bullying when mediated by more expressive gender traits. An inverse pattern was also observed: Hostile sexism predicted more favorable attitudes toward bullying when mediated by instrumental gender traits. Attitudes toward bullying were highly correlated with bullying behavior. The five-predictor variables (including attitudes toward bullying) explained 58% of the variance of bullying behavior in girls and 37% of such variance in boys.

The VUV instrument SPICE for Solar Orbiter: performance ground testing

NASA Astrophysics Data System (ADS)

Caldwell, Martin E.; Morris, Nigel; Griffin, Douglas K.; Eccleston, Paul; Anderson, Mark; Pastor Santos, Carmen; Bruzzi, Davide; Tustain, Samuel; Howe, Chris; Davenne, Jenny; Grundy, Timothy; Speight, Roisin; Sidher, Sunil D.; Giunta, Alessandra; Fludra, Andrzej; Philippon, Anne; Auchere, Frederic; Hassler, Don; Davila, Joseph M.; Thompson, William T.; Schuehle, Udo H.; Meining, Stefan; Walls, Buddy; Phelan, P.; Dunn, Greg; Klein, Roman M.; Reichel, Thomas; Gyo, Manfred; Munro, Grant J.; Holmes, William; Doyle, Peter

2017-08-01

SPICE is an imaging spectrometer operating at vacuum ultraviolet (VUV) wavelengths, 70.4 - 79.0 nm and 97.3 - 104.9 nm. It is a facility instrument on the Solar Orbiter mission, which carries 10 science instruments in all, to make observations of the Sun's atmosphere and heliosphere, at close proximity to the Sun, i.e to 0.28 A.U. at perihelion. SPICE's role is to make VUV measurements of plasma in the solar atmosphere. SPICE is designed to achieve spectral imaging at spectral resolution >1500, spatial resolution of several arcsec, and two-dimensional FOV of 11 x16arcmins. The many strong constraints on the instrument design imposed by the mission requirements prevent the imaging performance from exceeding those of previous instruments, but by being closer to the sun there is a gain in spatial resolution. The price which is paid is the harsher environment, particularly thermal. This leads to some novel features in the design, which needed to be proven by ground test programs. These include a dichroic solar-transmitting primary mirror to dump the solar heat, a high in-flight temperature (60deg.C) and gradients in the optics box, and a bespoke variable-line-spacing grating to minimise the number of reflective components used. The tests culminate in the systemlevel test of VUV imaging performance and pointing stability. We will describe how our dedicated facility with heritage from previous solar instruments, is used to make these tests, and show the results, firstly on the Engineering Model of the optics unit, and more recently on the Flight Model. For the keywords, select up to 8 key terms for a search on your manuscript's subject.

Large-Scale, Parallel, Multi-Sensor Data Fusion in the Cloud

NASA Astrophysics Data System (ADS)

Wilson, B. D.; Manipon, G.; Hua, H.

2012-12-01

NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over periods of years to decades. However, moving from predominantly single-instrument studies to a multi-sensor, measurement-based model for long-duration analysis of important climate variables presents serious challenges for large-scale data mining and data fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another instrument (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over years of AIRS data. To perform such an analysis, one must discover & access multiple datasets from remote sites, find the space/time "matchups" between instruments swaths and model grids, understand the quality flags and uncertainties for retrieved physical variables, assemble merged datasets, and compute fused products for further scientific and statistical analysis. To efficiently assemble such decade-scale datasets in a timely manner, we are utilizing Elastic Computing in the Cloud and parallel map/reduce-based algorithms. "SciReduce" is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in the Cloud. Unlike Hadoop, in which simple tuples (keys & values) are passed between the map and reduce functions, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Thus, SciReduce uses the native datatypes (geolocated grids, swaths, and points) that geo-scientists are familiar with. We are deploying within SciReduce a versatile set of python operators for data lookup, access, subsetting, co-registration, mining, fusion, and statistical analysis. All operators take in sets of geo-located arrays and generate more arrays. Large, multi-year satellite and model datasets are automatically "sharded" by time and space across a cluster of nodes so that years of data (millions of granules) can be compared or fused in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP or webification URLs, thereby minimizing the size of the stored input and intermediate datasets. A typical map function might assemble and quality control AIRS Level-2 water vapor profiles for a year of data in parallel, then a reduce function would average the profiles in lat/lon bins (again, in parallel), and a final reduce would aggregate the climatology and write it to output files. We are using SciReduce to automate the production of multiple versions of a multi-year water vapor climatology (AIRS & MODIS), stratified by Cloudsat cloud classification, and compare it to models (ECMWF & MERRA reanalysis). We will present the architecture of SciReduce, describe the achieved "clock time" speedups in fusing huge datasets on our own nodes and in the Amazon Cloud, and discuss the Cloud cost tradeoffs for storage, compute, and data transfer.

Large-Scale, Parallel, Multi-Sensor Data Fusion in the Cloud

NASA Astrophysics Data System (ADS)

Wilson, B.; Manipon, G.; Hua, H.

2012-04-01

NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over periods of years to decades. However, moving from predominantly single-instrument studies to a multi-sensor, measurement-based model for long-duration analysis of important climate variables presents serious challenges for large-scale data mining and data fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another instrument (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over years of AIRS data. To perform such an analysis, one must discover & access multiple datasets from remote sites, find the space/time "matchups" between instruments swaths and model grids, understand the quality flags and uncertainties for retrieved physical variables, assemble merged datasets, and compute fused products for further scientific and statistical analysis. To efficiently assemble such decade-scale datasets in a timely manner, we are utilizing Elastic Computing in the Cloud and parallel map/reduce-based algorithms. "SciReduce" is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in the Cloud. Unlike Hadoop, in which simple tuples (keys & values) are passed between the map and reduce functions, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Thus, SciReduce uses the native datatypes (geolocated grids, swaths, and points) that geo-scientists are familiar with. We are deploying within SciReduce a versatile set of python operators for data lookup, access, subsetting, co-registration, mining, fusion, and statistical analysis. All operators take in sets of geo-arrays and generate more arrays. Large, multi-year satellite and model datasets are automatically "sharded" by time and space across a cluster of nodes so that years of data (millions of granules) can be compared or fused in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP or webification URLs, thereby minimizing the size of the stored input and intermediate datasets. A typical map function might assemble and quality control AIRS Level-2 water vapor profiles for a year of data in parallel, then a reduce function would average the profiles in bins (again, in parallel), and a final reduce would aggregate the climatology and write it to output files. We are using SciReduce to automate the production of multiple versions of a multi-year water vapor climatology (AIRS & MODIS), stratified by Cloudsat cloud classification, and compare it to models (ECMWF & MERRA reanalysis). We will present the architecture of SciReduce, describe the achieved "clock time" speedups in fusing huge datasets on our own nodes and in the Amazon Cloud, and discuss the Cloud cost tradeoffs for storage, compute, and data transfer.

Lifestyle segmentation of US food shoppers to examine organic and local food consumption.

PubMed

Nie, Cong; Zepeda, Lydia

2011-08-01

The food related lifestyle (FRL) model, widely used on European data, is applied to US data using a modified survey instrument to examine organic and local food consumption. Since empirical studies indicate these shoppers are motivated by environmental and health concerns and limited by access, the conceptual framework employs an environmental behavior model, Attitude Behavior Context (ABC), which is consistent with means-end chain theory, the Health Belief (HB) model, and the FRL model. ABC theory incorporates contextual factors that may limit consumers' ability to act on their intentions. US food shopper data was collected in 2003 (n=956) utilizing an instrument with variables adapted from the FRL, ABC, and HB models. Cluster analysis segmented food shoppers into four FRL groups: rational, adventurous, careless, and a fourth segment that had some characteristics of both conservative and uninvolved consumers. The segments exhibited significant differences in organic and local food consumption. These were correlated with consumers' environmental concerns, knowledge and practices, health concerns and practices, as well as some demographic characteristics (race, gender, age, education), income, and variables that measured access to these foods. Implications for marketing and public policy strategies to promote organic and local foods include: emphasizing taste, nutrition, value, children, and enjoyment of cooking for rational consumers; and emphasizing health, fitness, and freshness, and providing ethnic foods for adventurous consumers. While both careless and conservative/uninvolved consumers valued convenience, the former tended to be in the highest income group, while the latter were in the lowest, were more likely to be either in the youngest or oldest age groups, and were very concerned about food safety and health. Copyright © 2011 Elsevier Ltd. All rights reserved.

Precipitable Water Variability Using SSM/I and GOES VAS Pathfinder Data Sets

NASA Technical Reports Server (NTRS)

Lerner, Jeffrey A.; Jedlovec, Gary J.; Kidder, Stanley Q.

1996-01-01

Determining moisture variability for all weather scenes is critical to understanding the earth's hydrologic cycle and global climate changes. Remote sensing from geostationary satellites provides the necessary temporal and spatial resolutions necessary for global change studies. Due to antenna size constraints imposed with the use of microwave radiometers, geostationary satellites have carried instruments passively measuring radiation at infrared wavelengths or shorter. The shortfall of using infrared instruments in moisture studies lies in its inability to sense terrestrial radiation through clouds. Microwave emissions, on the other hand, are mostly unaffected by cloudy atmospheres. Land surface emissivity at microwave frequencies exhibit both high temporal and spatial variability thus confining moisture retrievals at microwave frequencies to over marine atmospheres (a near uniform cold background). This study intercompares the total column integrated water content Precipitable Water, (PW) as derived from both the Special Sensor Microwave Imager (SSM/I) and the Geostationary Operational Environmental Satellite (GOES) VISSR Atmospheric Sounder (VAS) pathfinder data sets. PW is a bulk parameter often used to quantify moisture variability and is important to understanding the earth's hydrologic cycle and climate system. This research has been spawned in an effort to combine two different algorithms which together can lead to a more comprehensive quantification of global water vapor. The approach taken here is to intercompare two independent PW retrieval algorithms and to validate the resultant retrievals against an existing data set, namely the European Center for Medium range Weather Forecasts (ECMWF) model analysis data.

Instrumental Variable Methods for Continuous Outcomes That Accommodate Nonignorable Missing Baseline Values.

PubMed

Ertefaie, Ashkan; Flory, James H; Hennessy, Sean; Small, Dylan S

2017-06-15

Instrumental variable (IV) methods provide unbiased treatment effect estimation in the presence of unmeasured confounders under certain assumptions. To provide valid estimates of treatment effect, treatment effect confounders that are associated with the IV (IV-confounders) must be included in the analysis, and not including observations with missing values may lead to bias. Missing covariate data are particularly problematic when the probability that a value is missing is related to the value itself, which is known as nonignorable missingness. In such cases, imputation-based methods are biased. Using health-care provider preference as an IV method, we propose a 2-step procedure with which to estimate a valid treatment effect in the presence of baseline variables with nonignorable missing values. First, the provider preference IV value is estimated by performing a complete-case analysis using a random-effects model that includes IV-confounders. Second, the treatment effect is estimated using a 2-stage least squares IV approach that excludes IV-confounders with missing values. Simulation results are presented, and the method is applied to an analysis comparing the effects of sulfonylureas versus metformin on body mass index, where the variables baseline body mass index and glycosylated hemoglobin have missing values. Our result supports the association of sulfonylureas with weight gain. © The Author 2017. 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.

Assimilation of MLS and OMI Ozone Data

NASA Technical Reports Server (NTRS)

Stajner, I.; Wargan, K.; Chang, L.-P.; Hayashi, H.; Pawson, S.; Froidevaux, L.; Livesey, N.

2005-01-01

Ozone data from Aura Microwave Limb Sounder (MLS) and Ozone Monitoring Instrument (OMI) were assimilated into the ozone model at NASA's Global Modeling and Assimilation Office (GMAO). This assimilation produces ozone fields that are superior to those from the operational GMAO assimilation of Solar Backscatter Ultraviolet (SBUV/2) instrument data. Assimilation of Aura data improves the representation of the "ozone hole" and the agreement with independent Stratospheric Aerosol and Gas Experiment (SAGE) III and ozone sonde data. Ozone in the lower stratosphere is captured better: mean state, vertical gradients, spatial and temporal variability are all improved. Inclusion of OMI and MLS data together, or separately, in the assimilation system provides a way of checking how consistent OMI and MLS data are with each other, and with the ozone model. We found that differences between OMI total ozone column data and model forecasts decrease after MLS data are assimilated. This indicates that MLS stratospheric ozone profiles are consistent with OMI total ozone columns. The evaluation of error characteristics of OMI and MLS ozone will continue as data from newer versions of retrievals becomes available. We report on the initial step in obtaining global assimilated ozone fields that combine measurements from different Aura instruments, the ozone model at the GMAO, and their respective error characteristics. We plan to use assimilated ozone fields in estimation of tropospheric ozone. We also plan to investigate impacts of assimilated ozone fields on numerical weather prediction through their use in radiative models and in the assimilation of infrared nadir radiance data from NASA's Advanced Infrared Sounder (AIRS).

A new method for measuring lung deposition efficiency of airborne nanoparticles in a single breath

PubMed Central

Jakobsson, Jonas K. F.; Hedlund, Johan; Kumlin, John; Wollmer, Per; Löndahl, Jakob

2016-01-01

Assessment of respiratory tract deposition of nanoparticles is a key link to understanding their health impacts. An instrument was developed to measure respiratory tract deposition of nanoparticles in a single breath. Monodisperse nanoparticles are generated, inhaled and sampled from a determined volumetric lung depth after a controlled residence time in the lung. The instrument was characterized for sensitivity to inter-subject variability, particle size (22, 50, 75 and 100 nm) and breath-holding time (3–20 s) in a group of seven healthy subjects. The measured particle recovery had an inter-subject variability 26–50 times larger than the measurement uncertainty and the results for various particle sizes and breath-holding times were in accordance with the theory for Brownian diffusion and values calculated from the Multiple-Path Particle Dosimetry model. The recovery was found to be determined by residence time and particle size, while respiratory flow-rate had minor importance in the studied range 1–10 L/s. The instrument will be used to investigate deposition of nanoparticles in patients with respiratory disease. The fast and precise measurement allows for both diagnostic applications, where the disease may be identified based on particle recovery, and for studies with controlled delivery of aerosol-based nanomedicine to specific regions of the lungs. PMID:27819335

Childhood antecedents of adult sense of belonging.

PubMed

Hagerty, Bonnie M; Williams, Reg Arthur; Oe, Hiroaki

2002-07-01

Sense of belonging has been proposed to be a basic human need, and deficits in sense of belonging have been linked to problems in social and psychological functioning. Yet, there is little evidence about what early life experiences contribute to sense of belonging. The purpose of this study was to examine potential childhood antecedents of adult sense of belonging. The sample consisted of 362 community college students ranging in age from 18 to 72 years, with a mean age of 26 years. Measures included the Sense of Belonging Instrument, the Parental Bonding Instrument, and the Childhood Adversity and Adolescent Deviance Instrument. Multiple regression analysis was used to correlate childhood antecedents with adult sense of belonging. The final reduced model included 12 variables, which accounted for 25% of the variance in sense of belonging. Significant positive antecedents with a relationship with sense of belonging were perceived caring by both mother and father while growing up, participation in high school athletic activity, and parental divorce. Significant negative variables with a relationship with sense of belonging included perceived overprotection of father, high school pregnancy, family financial problems while growing up, incest, and homosexuality. Knowledge of these factors should influence interventions with families regarding child-rearing and parenting practices, mediating the effects of crises during childhood such as divorce and teen pregnancy, and the interpersonal growth needs of teenagers. Copyright 2002 Wiley Periodicals, Inc.

8 years of Solar Spectral Irradiance Variability Observed from the ISS with the SOLAR/SOLSPEC Instrument

NASA Astrophysics Data System (ADS)

Damé, Luc; Bolsée, David; Meftah, Mustapha; Irbah, Abdenour; Hauchecorne, Alain; Bekki, Slimane; Pereira, Nuno; Cessateur, Marchand; Gäel; , Marion; et al.

2016-10-01

Accurate measurements of Solar Spectral Irradiance (SSI) are of primary importance for a better understanding of solar physics and of the impact of solar variability on climate (via Earth's atmospheric photochemistry). The acquisition of a top of atmosphere reference solar spectrum and of its temporal and spectral variability during the unusual solar cycle 24 is of prime interest for these studies. These measurements are performed since April 2008 with the SOLSPEC spectro-radiometer from the far ultraviolet to the infrared (166 nm to 3088 nm). This instrument, developed under a fruitful LATMOS/BIRA-IASB collaboration, is part of the Solar Monitoring Observatory (SOLAR) payload, externally mounted on the Columbus module of the International Space Station (ISS). The SOLAR mission, with its actual 8 years duration, will cover almost the entire solar cycle 24. We present here the in-flight operations and performances of the SOLSPEC instrument, including the engineering corrections, calibrations and improved know-how procedure for aging corrections. Accordingly, a SSI reference spectrum from the UV to the NIR will be presented, together with its variability in the UV, as measured by SOLAR/SOLSPEC for 8 years. Uncertainties on these measurements and comparisons with other instruments will be briefly discussed.

Evaluating the Vertical Distribution of Ozone and its Relationship to Pollution Events in Air Quality Models using Satellite Data

NASA Astrophysics Data System (ADS)

Osterman, G. B.; Neu, J. L.; Eldering, A.; Pinder, R. W.; Tang, Y.; McQueen, J.

2014-12-01

Most regional scale models that are used for air quality forecasts and ozone source attribution do not adequately capture the distribution of ozone in the mid- and upper troposphere, but it is unclear how this shortcoming relates to their ability to simulate surface ozone. We combine ozone profile data from the NASA Earth Observing System (EOS) Tropospheric Emission Spectrometer (TES) and a new joint product from TES and the Ozone Monitoring Instrument along with ozonesonde measurements and EPA AirNow ground station ozone data to examine air quality events during August 2006 in the Community Multi-Scale Air Quality (CMAQ) and National Air Quality Forecast Capability (NAQFC) models. We present both aggregated statistics and case-study analyses with the goal of assessing the relationship between the models' ability to reproduce surface air quality events and their ability to capture the vertical distribution of ozone. We find that the models lack the mid-tropospheric ozone variability seen in TES and the ozonesonde data, and discuss the conditions under which this variability appears to be important for surface air quality.

Towards Student Instrumentation of Computer-Based Algebra Systems in University Courses

ERIC Educational Resources Information Center

Stewart, Sepideh; Thomas, Michael O. J.; Hannah, John

2005-01-01

There are many perceived benefits of using technology, such as computer algebra systems, in undergraduate mathematics courses. However, attaining these benefits sometimes proves elusive. Some of the key variables are the teaching approach and the student instrumentation of the technology. This paper considers the instrumentation of computer-based…

Instructional Interactions of Kindergarten Mathematics Classrooms: Validating a Direct Observation Instrument

ERIC Educational Resources Information Center

Doabler, Christian; Smolkowski, Keith; Fien, Hank; Kosty, Derek B.; Cary, Mari Strand

2010-01-01

In this paper, the authors report research focused directly on the validation of the Coding of Academic Teacher-Student interactions (CATS) direct observation instrument. They use classroom information gathered by the CATS instrument to better understand the potential mediating variables hypothesized to influence student achievement. Their study's…

26 CFR 1.1275-5 - Variable rate debt instruments.

Code of Federal Regulations, 2010 CFR

2010-04-01

... nonpublicly traded property. A debt instrument (other than a tax-exempt obligation) that would otherwise... variations in the cost of newly borrowed funds in the currency in which the debt instrument is denominated... on the yield of actively traded personal property (within the meaning of section 1092(d)(1)). (ii...

Teleconnection stationarity, variability and trends of the Southern Annular Mode (SAM) during the last millennium

NASA Astrophysics Data System (ADS)

Dätwyler, Christoph; Neukom, Raphael; Abram, Nerilie J.; Gallant, Ailie J. E.; Grosjean, Martin; Jacques-Coper, Martín; Karoly, David J.; Villalba, Ricardo

2017-11-01

The Southern Annular Mode (SAM) is the leading mode of atmospheric interannual variability in the Southern Hemisphere (SH) extra-tropics. Here, we assess the stationarity of SAM spatial correlations with instrumental and paleoclimate proxy data for the past millennium. The instrumental period shows that temporal non-stationarities in SAM teleconnections are not consistent across the SH land areas. This suggests that the influence of the SAM index is modulated by regional effects. However, within key-regions with good proxy data coverage (South America, Tasmania, New Zealand), teleconnections are mostly stationary over the instrumental period. Using different stationarity criteria for proxy record selection, we provide new austral summer and annual mean SAM index reconstructions over the last millennium. Our summer SAM reconstructions are very robust to changes in proxy record selection and the selection of the calibration period, particularly on the multi-decadal timescale. In contrast, the weaker performance and lower agreement in the annual mean SAM reconstructions point towards changing teleconnection patterns that may be particularly important outside the summer months. Our results clearly portend that the temporal stationarity of the proxy-climate relationships should be taken into account in the design of comprehensive regional and hemispherical climate reconstructions. The summer SAM reconstructions show no significant relationship to solar, greenhouse gas and volcanic forcing, with the exception of an extremely strong negative anomaly following the AD 1257 Samalas eruption. Furthermore, reconstructed pre-industrial summer SAM trends are very similar to trends obtained by model control simulations. We find that recent trends in the summer SAM lie outside the 5-95% range of pre-industrial natural variability.

Is Some Provider Advice on Smoking Cessation Better Than No Advice? An Instrumental Variable Analysis of the 2001 National Health Interview Survey

PubMed Central

Bao, Yuhua; Duan, Naihua; Fox, Sarah A

2006-01-01

Research Objective To estimate the effect of provider advice in routine clinical contacts on patient smoking cessation outcome. Data Source The Sample Adult File from the 2001 National Health Interview Survey. We focus on adult patients who were either current smokers or quit during the last 12 months and had some contact with the health care providers or facilities they most often went to for acute or preventive care. Study Design We estimate a joint model of self-reported smoking cessation and ever receiving advice to quit during medical visits in the past 12 months. Because providers are more likely to advise heavier smokers and/or patients already diagnosed with smoking-related conditions, we use provider advice for diet/nutrition and for physical activity reported by the same patient as instrumental variables for smoking cessation advice to mitigate the selection bias. We conduct additional analyses to examine the robustness of our estimate against the various scenarios by which the exclusion restriction of the instrumental variables may fail. Principal Findings Provider advice doubles the chances of success in (self-reported) smoking cessation by their patients. The probability of quitting by the end of the 12-month reference period increased from 6.9 to 14.7 percent, an effect that is of both statistical (p<.001) and clinical significance. Conclusions Provider advice delivered in routine practice settings has a substantial effect on the success rate of smoking cessation among smoking patients. Providing advice consistently to all smoking patients, compared with routine care, is more effective than doubling the federal excise tax and, in the longer run, likely to outperform some of the other tobacco control policies such as banning smoking in private workplaces. PMID:17116112

A paleoclimate rainfall reconstruction in the Murray-Darling Basin (MDB), Australia: 1. Evaluation of different paleoclimate archives, rainfall networks, and reconstruction techniques

NASA Astrophysics Data System (ADS)

Ho, Michelle; Kiem, Anthony S.; Verdon-Kidd, Danielle C.

2015-10-01

From ˜1997 to 2009 the Murray-Darling Basin (MDB), Australia's largest water catchment and reputed "food bowl," experienced a severe drought termed the "Millennium Drought" or "Big Dry" followed by devastating floods in the austral summers of 2010/2011, 2011/2012, and 2012/2013. The magnitude and severity of these extreme events highlight the limitations associated with assessing hydroclimatic risk based on relatively short instrumental records (˜100 years). An option for extending hydroclimatic records is through the use of paleoclimate records. However, there are few in situ proxies of rainfall or streamflow suitable for assessing hydroclimatic risk in Australia and none are available in the MDB. In this paper, available paleoclimate records are reviewed and those of suitable quality for hydroclimatic risk assessments are used to develop preinstrumental information for the MDB. Three different paleoclimate reconstruction techniques are assessed using two instrumental rainfall networks: (1) corresponding to rainfall at locations where rainfall-sensitive Australian paleoclimate archives currently exist and (2) corresponding to rainfall at locations identified as being optimal for explaining MDB rainfall variability. It is shown that the optimized rainfall network results in a more accurate model of MDB rainfall compared to reconstructions based on rainfall at locations where paleoclimate rainfall proxies currently exist. This highlights the importance of first identifying key locations where existing and as yet unrealized paleoclimate records will be most useful in characterizing variability. These results give crucial insight as to where future investment and research into developing paleoclimate proxies for Australia could be most beneficial, with respect to better understanding instrumental, preinstrumental and potential future variability in the MDB.

Tests of Convection Electric Field Models For The January 10, 1997, Geomagnetic Storm

NASA Astrophysics Data System (ADS)

Jordanova, V.; Boonsiriseth, A.; Thorne, R.; Dotan, Y.

The January 10-11, 1997, geomagnetic storm was caused by the passage at Earth of a magnetic cloud with a negative to positive Bz variation extending for 1 day. The ge- omagnetic indices had values of minimum Dst=-83 nT and maximum Kp=6 during the period of southward IMF within the cloud. We simulate ring current development during this storm using our kinetic drift-loss model and compare the results inferred from Volland-Stern type, Weimer, and AMIE convection electric field models. A pen- etration electric field is added to the AMIE model [Boonsiriseth et al., 2001] in order to improve the agreement with measurements from the electric field instrument on Po- lar spacecraft. The ionospheric electric potentials are mapped to the equatorial plane using the Tsyganenko 1996 magnetic field model and the resulting equatorial poten- tial models are coupled with our ring current model. While the temporal evolution of the large-scale features is similar in all three convection models, detailed comparison indicates that AMIE model shows highly variable small-scale features not present in the Volland-Stern or Weimer convection models. Results from our kinetic ring current model are compared with energetic particle data from the HYDRA, TIMAS, IPS, and CAMMICE instruments on Polar to test the applicability of the convection electric field models for this storm period.

SUITS/SWUSV: a small-size mission to address solar spectral variability, space weather and solar-climate relations

NASA Astrophysics Data System (ADS)

Damé, Luc; Keckhut, Philippe; Hauchecorne, Alain; Meftah, Mustapha; Bekki, Slimane

2016-07-01

We present the SUITS/SWUSV microsatellite mission investigation: "Solar Ultraviolet Influence on Troposphere/Stratosphere, a Space Weather & Ultraviolet Solar Variability" mission. SUITS/SWUSV was developed to determine the origins of the Sun's activity, understand the flaring process (high energy flare characterization) and onset of CMEs (forecasting). Another major objective is to determine the dynamics and coupling of Earth's atmosphere and its response to solar variability (in particular UV) and terrestrial inputs. It therefore includes the prediction and detection of major eruptions and coronal mass ejections (Lyman-Alpha and Herzberg continuum imaging) the solar forcing on the climate through radiation and their interactions with the local stratosphere (UV spectral irradiance measures from 170 to 400 nm). The mission is proposed on a sun-synchronous polar orbit 18h-6h (for almost constant observing) and proposes a 7 instruments model payload of 65 kg - 65 W with: SUAVE (Solar Ultraviolet Advanced Variability Experiment), an optimized telescope for FUV (Lyman-Alpha) and MUV (200-220 nm Herzberg continuum) imaging (sources of variability); SOLSIM (Solar Spectral Irradiance Monitor), a spectrometer with 0.65 nm spectral resolution from 170 to 340 nm; SUPR (Solar Ultraviolet Passband Radiometers), with UV filter radiometers at Lyman-Alpha, Herzberg, MgII index, CN bandhead and UV bands coverage up to 400 nm; HEBS (High Energy Burst Spectrometers), a large energy coverage (a few tens of keV to a few hundreds of MeV) instrument to characterize large flares; EPT-HET (Electron-Proton Telescope - High Energy Telescope), measuring electrons, protons, and heavy ions over a large energy range; ERBO (Earth Radiative Budget and Ozone) NADIR oriented; and a vector magnetometer. Complete accommodation of the payload has been performed on a PROBA type platform very nicely. Heritage is important both for instruments (SODISM and PREMOS on PICARD, LYRA on PROBA-2, SOLSPEC on ISS,...) and platform (PROBA-2, PROBA-V,...), leading to high TRL levels (>7). SUITS/SWUSV was initially designed in view of the ESA/CAS AO for a Small Mission; it is now envisaged for a joint CNES/NASA opportunity with Europeans and Americans partners for a possible flight in 2021.

Correspondence between EQ-5D health state classifications and EQ VAS scores.

PubMed

Whynes, David K

2008-11-07

The EQ-5D health-related quality of life instrument comprises a health state classification followed by a health evaluation using a visual analogue scale (VAS). The EQ-5D has been employed frequently in economic evaluations, yet the relationship between the two parts of the instrument remains ill-understood. In this paper, we examine the correspondence between VAS scores and health state classifications for a large sample, and identify variables which contribute to determining the VAS scores independently of the health states as classified. A UK trial of management of low-grade abnormalities detected on screening for cervical pre-cancer (TOMBOLA) provided EQ-5D data for over 3,000 women. Information on distress and multi-dimensional health locus of control had been collected using other instruments. A linear regression model was fitted, with VAS score as the dependent variable. Independent variables comprised EQ-5D health state classifications, distress, locus of control, and socio-demographic characteristics. Equivalent EQ-5D and distress data, collected at twelve months, were available for over 2,000 of the women, enabling us to predict changes in VAS score over time from changes in EQ-5D classification and distress. In addition to EQ-5D health state classification, VAS score was influenced by the subject's perceived locus of control, and by her age, educational attainment, ethnic origin and smoking behaviour. Although the EQ-5D classification includes a distress dimension, the independent measure of distress was an additional determinant of VAS score. Changes in VAS score over time were explained by changes in both EQ-5D severities and distress. Women allocated to the experimental management arm of the trial reported an increase in VAS score, independently of any changes in health state and distress. In this sample, EQ VAS scores were predictable from the EQ-5D health state classification, although there also existed other group variables which contributed systematically and independently towards determining such scores. These variables comprised psychological disposition, socio-demographic factors such as age and education, clinically-important distress, and the clinical intervention itself. ISRCTN34841617.

Ascertainment-adjusted parameter estimation approach to improve robustness against misspecification of health monitoring methods

NASA Astrophysics Data System (ADS)

Juesas, P.; Ramasso, E.

2016-12-01

Condition monitoring aims at ensuring system safety which is a fundamental requirement for industrial applications and that has become an inescapable social demand. This objective is attained by instrumenting the system and developing data analytics methods such as statistical models able to turn data into relevant knowledge. One difficulty is to be able to correctly estimate the parameters of those methods based on time-series data. This paper suggests the use of the Weighted Distribution Theory together with the Expectation-Maximization algorithm to improve parameter estimation in statistical models with latent variables with an application to health monotonic under uncertainty. The improvement of estimates is made possible by incorporating uncertain and possibly noisy prior knowledge on latent variables in a sound manner. The latent variables are exploited to build a degradation model of dynamical system represented as a sequence of discrete states. Examples on Gaussian Mixture Models, Hidden Markov Models (HMM) with discrete and continuous outputs are presented on both simulated data and benchmarks using the turbofan engine datasets. A focus on the application of a discrete HMM to health monitoring under uncertainty allows to emphasize the interest of the proposed approach in presence of different operating conditions and fault modes. It is shown that the proposed model depicts high robustness in presence of noisy and uncertain prior.

Pharmaceutical industry and trade liberalization using computable general equilibrium model.

PubMed

Barouni, M; Ghaderi, H; Banouei, Aa

2012-01-01

Computable general equilibrium models are known as a powerful instrument in economic analyses and widely have been used in order to evaluate trade liberalization effects. The purpose of this study was to provide the impacts of trade openness on pharmaceutical industry using CGE model. Using a computable general equilibrium model in this study, the effects of decrease in tariffs as a symbol of trade liberalization on key variables of Iranian pharmaceutical products were studied. Simulation was performed via two scenarios in this study. The first scenario was the effect of decrease in tariffs of pharmaceutical products as 10, 30, 50, and 100 on key drug variables, and the second was the effect of decrease in other sectors except pharmaceutical products on vital and economic variables of pharmaceutical products. The required data were obtained and the model parameters were calibrated according to the social accounting matrix of Iran in 2006. The results associated with simulation demonstrated that the first scenario has increased import, export, drug supply to markets and household consumption, while import, export, supply of product to market, and household consumption of pharmaceutical products would averagely decrease in the second scenario. Ultimately, society welfare would improve in all scenarios. We presents and synthesizes the CGE model which could be used to analyze trade liberalization policy issue in developing countries (like Iran), and thus provides information that policymakers can use to improve the pharmacy economics.

A measurement model of multiple intelligence profiles of management graduates

NASA Astrophysics Data System (ADS)

Krishnan, Heamalatha; Awang, Siti Rahmah

2017-05-01

In this study, developing a fit measurement model and identifying the best fitting items to represent Howard Gardner's nine intelligences namely, musical intelligence, bodily-kinaesthetic intelligence, mathematical/logical intelligence, visual/spatial intelligence, verbal/linguistic intelligence, interpersonal intelligence, intrapersonal intelligence, naturalist intelligence and spiritual intelligence are the main interest in order to enhance the opportunities of the management graduates for employability. In order to develop a fit measurement model, Structural Equation Modeling (SEM) was applied. A psychometric test which is the Ability Test in Employment (ATIEm) was used as the instrument to measure the existence of nine types of intelligence of 137 University Teknikal Malaysia Melaka (UTeM) management graduates for job placement purposes. The initial measurement model contains nine unobserved variables and each unobserved variable is measured by ten observed variables. Finally, the modified measurement model deemed to improve the Normed chi-square (NC) = 1.331; Incremental Fit Index (IFI) = 0.940 and Root Mean Square of Approximation (RMSEA) = 0.049 was developed. The findings showed that the UTeM management graduates possessed all nine intelligences either high or low. Musical intelligence, mathematical/logical intelligence, naturalist intelligence and spiritual intelligence contributed highest loadings on certain items. However, most of the intelligences such as bodily kinaesthetic intelligence, visual/spatial intelligence, verbal/linguistic intelligence interpersonal intelligence and intrapersonal intelligence possessed by UTeM management graduates are just at the borderline.

Geophysics From Terrestrial Time-Variable Gravity Measurements

NASA Astrophysics Data System (ADS)

Van Camp, Michel; de Viron, Olivier; Watlet, Arnaud; Meurers, Bruno; Francis, Olivier; Caudron, Corentin

2017-12-01

In a context of global change and increasing anthropic pressure on the environment, monitoring the Earth system and its evolution has become one of the key missions of geosciences. Geodesy is the geoscience that measures the geometric shape of the Earth, its orientation in space, and gravity field. Time-variable gravity, because of its high accuracy, can be used to build an enhanced picture and understanding of the changing Earth. Ground-based gravimetry can determine the change in gravity related to the Earth rotation fluctuation, to celestial body and Earth attractions, to the mass in the direct vicinity of the instruments, and to vertical displacement of the instrument itself on the ground. In this paper, we review the geophysical questions that can be addressed by ground gravimeters used to monitor time-variable gravity. This is done in relation to the instrumental characteristics, noise sources, and good practices. We also discuss the next challenges to be met by ground gravimetry, the place that terrestrial gravimetry should hold in the Earth observation system, and perspectives and recommendations about the future of ground gravity instrumentation.

Effect of corruption on healthcare satisfaction in post-soviet nations: A cross-country instrumental variable analysis of twelve countries.

PubMed

Habibov, Nazim

2016-03-01

There is the lack of consensus about the effect of corruption on healthcare satisfaction in transitional countries. Interpreting the burgeoning literature on this topic has proven difficult due to reverse causality and omitted variable bias. In this study, the effect of corruption on healthcare satisfaction is investigated in a set of 12 Post-Socialist countries using instrumental variable regression on the sample of 2010 Life in Transition survey (N = 8655). The results indicate that experiencing corruption significantly reduces healthcare satisfaction. Copyright © 2016 The Author. Published by Elsevier Ltd.. All rights reserved.

Using a modified technology acceptance model to evaluate healthcare professionals' adoption of a new telemonitoring system.

PubMed

Gagnon, Marie Pierre; Orruño, Estibalitz; Asua, José; Abdeljelil, Anis Ben; Emparanza, José

2012-01-01

To examine the factors that could influence the decision of healthcare professionals to use a telemonitoring system. A questionnaire, based on the Technology Acceptance Model (TAM), was developed. A panel of experts in technology assessment evaluated the face and content validity of the instrument. Two hundred and thirty-four questionnaires were distributed among nurses and doctors of the cardiology, pulmonology, and internal medicine departments of a tertiary hospital. Cronbach alpha was calculated to measure the internal consistency of the questionnaire items. Construct validity was evaluated using interitem correlation analysis. Logistic regression analysis was performed to test the theoretical model. Adjusted odds ratios (ORs) and their 95% confidence intervals (CIs) were computed. A response rate of 39.7% was achieved. With the exception of one theoretical construct (Habit) that corresponds to behaviors that become automatized, Cronbach alpha values were acceptably high for the remaining constructs. Theoretical variables were well correlated with each other and with the dependent variable. The original TAM was good at predicting telemonitoring usage intention, Perceived Usefulness being the only significant predictor (OR: 5.28, 95% CI: 2.12-13.11). The model was still significant and more powerful when the other theoretical variables were added. However, the only significant predictor in the modified model was Facilitators (OR: 4.96, 95% CI: 1.59-15.55). The TAM is a good predictive model of healthcare professionals' intention to use telemonitoring. However, the perception of facilitators is the most important variable to consider for increasing doctors' and nurses' intention to use the new technology.

On-ground calibration of the BEPICOLOMBO/SIMBIO-SYS at instrument level

NASA Astrophysics Data System (ADS)

Rodriguez-Ferreira, J.; Poulet, F.; Eng, P.; Longval, Y.; Dassas, K.; Arondel, A.; Langevin, Y.; Capaccioni, F.; Filacchione, G.; Palumbo, P.; Cremonese, G.; Dami, M.

2012-04-01

The Mercury Planetary Orbiter/BepiColombo carries an integrated suite of instruments, the Spectrometer and Imagers for MPO BepiColombo-Integrated Observatory SYStem (SIMBIO-SYS). SIMBIO-SYS has 3 channels: a stereo imaging system (STC), a high-resolution imager (HRIC) and a visible-near-infrared imaging spectrometer (VIHI). SIMBIO-SYS will scan the surface of Mercury with these three channels and determine the physical, morphological and compositional properties of the entire planet. Before integration on the S/C, an on-ground calibration at the channels and at the instrument levels will be performed so as to describe the instrumental responses as a function of various parameters that might evolve while the instruments will be operating [1]. The Institut d'Astrophysique Spatiale (IAS) is responsible for the on-ground instrument calibration at the instrument level. During the 4 weeks of calibration campaign planned for June 2012, the instrument will be maintained in a mechanical and thermal environment simulating the space conditions. Four Optical stimuli (QTH lamp, Integrating Sphere, BlackBody with variable temperature from 50 to 1200°C and Monochromator), are placed over an optical bench to illuminate the four channels so as to make the radiometric calibration, straylight monitoring, as well as spectral proofing based on laboratory mineral samples. The instrument will be mounted on a hexapod placed inside a thermal vacuum chamber during the calibration campaign. The hexapod will move the channels within the well-characterized incoming beam. We will present the key activities of the preparation of this calibration: the derivation of the instrument radiometric model, the implementation of the optical, mechanical and software interfaces of the calibration assembly, the characterization of the optical bench and the definition of the calibration procedures.

Increasing precision of turbidity-based suspended sediment concentration and load estimates.

PubMed

Jastram, John D; Zipper, Carl E; Zelazny, Lucian W; Hyer, Kenneth E

2010-01-01

Turbidity is an effective tool for estimating and monitoring suspended sediments in aquatic systems. Turbidity can be measured in situ remotely and at fine temporal scales as a surrogate for suspended sediment concentration (SSC), providing opportunity for a more complete record of SSC than is possible with physical sampling approaches. However, there is variability in turbidity-based SSC estimates and in sediment loadings calculated from those estimates. This study investigated the potential to improve turbidity-based SSC, and by extension the resulting sediment loading estimates, by incorporating hydrologic variables that can be monitored remotely and continuously (typically 15-min intervals) into the SSC estimation procedure. On the Roanoke River in southwestern Virginia, hydrologic stage, turbidity, and other water-quality parameters were monitored with in situ instrumentation; suspended sediments were sampled manually during elevated turbidity events; samples were analyzed for SSC and physical properties including particle-size distribution and organic C content; and rainfall was quantified by geologic source area. The study identified physical properties of the suspended-sediment samples that contribute to SSC estimation variance and hydrologic variables that explained variability of those physical properties. Results indicated that the inclusion of any of the measured physical properties in turbidity-based SSC estimation models reduces unexplained variance. Further, the use of hydrologic variables to represent these physical properties, along with turbidity, resulted in a model, relying solely on data collected remotely and continuously, that estimated SSC with less variance than a conventional turbidity-based univariate model, allowing a more precise estimate of sediment loading, Modeling results are consistent with known mechanisms governing sediment transport in hydrologic systems.

Long-term total ozone observations at Arosa (Switzerland) with Dobson and Brewer instruments (1988-2007)

NASA Astrophysics Data System (ADS)

Scarnato, B.; Staehelin, J.; Stübi, R.; Schill, H.

2010-07-01

Dobson and Brewer spectrophotometers are the standard instruments for ground-based total ozone monitoring under the World Meteorological Organization's Global Atmosphere Watch program. Both types of instruments have been simultaneously used at Arosa station (Switzerland) since 1988; presently two Dobson and three Brewer instruments (one of which is type Mark III) are in operation. The large data set of quasi-simultaneous measurements (defined here as observations performed less than 10 min apart) allows for the determination of both inter- and intrainstrumental precision. The results for one standard deviation of total ozone are ±0.5% for Dobson standard wavelength pair observations and ±0.15% for Brewer total ozone measurements. To transform Dobson data into Brewer total ozone observations, empirical transfer functions are used to describe the observed difference in seasonal variations of total ozone data derived from the two types of instruments (amounting to a seasonal amplitude of approximately 2% with maximum deviation in winter). The statistical model (applied to quasi-simultaneous measurements) includes the ozone effective temperature and the air mass multiplied by total ozone (ozone slant path) as explanatory variables; it removes the seasonal cycle in the difference and it allows the significance of the proxies introduced and systematic errors in the data to be determined. However, even when these transfer functions are applied, a 3% drift over about a 10 year period (1988-1997) between Arosa's Dobson and Brewer derived total ozone data series remains unexplained, adding to the model an aerosol proxy for which only part of the drift can be removed (related to the period 1992-1996).

Development and Validation of a Comprehensive Work-Related Needs Measure.

PubMed

Gallagher, Vickie C; Maher, Liam P; Gallagher, Kevin P; Valle, Matthew

2017-01-01

In a work context, employees tend to gravitate toward situations that are most conducive to meeting their needs. The purpose of this research is threefold. First, we define and specify the psychological needs under investigation, briefly highlight extant research, and differentiate needs from other individual difference variables. Second, we demonstrate the limitations of one of the most highly cited psychological needs instruments and introduce a new needs model. Third, we develop and evaluate a multi-dimensional needs inventory using a multi-study design. The strengths and limitations of the proposed and tested model are discussed, as are implications for future research.

Influence of therapist competence and quantity of cognitive behavioural therapy on suicidal behaviour and inpatient hospitalisation in a randomised controlled trial in borderline personality disorder: Further analyses of treatment effects in the BOSCOT study

PubMed Central

Norrie, John; Davidson, Kate; Tata, Philip; Gumley, Andrew

2013-01-01

Objectives We investigated the treatment effects reported from a high-quality randomized controlled trial of cognitive behavioural therapy (CBT) for 106 people with borderline personality disorder attending community-based clinics in the UK National Health Service – the BOSCOT trial. Specifically, we examined whether the amount of therapy and therapist competence had an impact on our primary outcome, the number of suicidal acts†, using instrumental variables regression modelling. Design Randomized controlled trial. Participants from across three sites (London, Glasgow, and Ayrshire/Arran) were randomized equally to CBT for personality disorders (CBTpd) plus Treatment as Usual or to Treatment as Usual. Treatment as Usual varied between sites and individuals, but was consistent with routine treatment in the UK National Health Service at the time. CBTpd comprised an average 16 sessions (range 0–35) over 12 months. Method We used instrumental variable regression modelling to estimate the impact of quantity and quality of therapy received (recording activities and behaviours that took place after randomization) on number of suicidal acts and inpatient psychiatric hospitalization. Results A total of 101 participants provided full outcome data at 2 years post randomization. The previously reported intention-to-treat (ITT) results showed on average a reduction of 0.91 (95% confidence interval 0.15–1.67) suicidal acts over 2 years for those randomized to CBT. By incorporating the influence of quantity of therapy and therapist competence, we show that this estimate of the effect of CBTpd could be approximately two to three times greater for those receiving the right amount of therapy from a competent therapist. Conclusions Trials should routinely control for and collect data on both quantity of therapy and therapist competence, which can be used, via instrumental variable regression modelling, to estimate treatment effects for optimal delivery of therapy. Such estimates complement rather than replace the ITT results, which are properly the principal analysis results from such trials. Practitioner points Assessing the impact of the quantity and quality of therapy (competence of therapists) is complex. More competent therapists, trained in CBTpd, may significantly reduce the number of suicidal act in patients with borderline personality disorder. PMID:23420622

Integration of Error Compensation of Coordinate Measuring Machines into Feature Measurement: Part I—Model Development

PubMed Central

Calvo, Roque; D’Amato, Roberto; Gómez, Emilio; Domingo, Rosario

2016-01-01

The development of an error compensation model for coordinate measuring machines (CMMs) and its integration into feature measurement is presented. CMMs are widespread and dependable instruments in industry and laboratories for dimensional measurement. From the tip probe sensor to the machine display, there is a complex transformation of probed point coordinates through the geometrical feature model that makes the assessment of accuracy and uncertainty measurement results difficult. Therefore, error compensation is not standardized, conversely to other simpler instruments. Detailed coordinate error compensation models are generally based on CMM as a rigid-body and it requires a detailed mapping of the CMM’s behavior. In this paper a new model type of error compensation is proposed. It evaluates the error from the vectorial composition of length error by axis and its integration into the geometrical measurement model. The non-explained variability by the model is incorporated into the uncertainty budget. Model parameters are analyzed and linked to the geometrical errors and uncertainty of CMM response. Next, the outstanding measurement models of flatness, angle, and roundness are developed. The proposed models are useful for measurement improvement with easy integration into CMM signal processing, in particular in industrial environments where built-in solutions are sought. A battery of implementation tests are presented in Part II, where the experimental endorsement of the model is included. PMID:27690052

Investigation of potential factors affecting the measurement of dew point temperature in oil-soaked transformers

NASA Astrophysics Data System (ADS)

Kraus, Adam H.

Moisture within a transformer's insulation system has been proven to degrade its dielectric strength. When installing a transformer in situ, one method used to calculate the moisture content of the transformer insulation is to measure the dew point temperature of the internal gas volume of the transformer tank. There are two instruments commercially available that are designed for dew point temperature measurement: the Alnor Model 7000 Dewpointer and the Vaisala DRYCAPRTM Hand-Held Dewpoint Meter DM70. Although these instruments perform an identical task, the design technology behind each instrument is vastly different. When the Alnor Dewpointer and Vaisala DM70 instruments are used to measure the dew point of the internal gas volume simultaneously from a pressurized transformer, their differences in dew point measurement have been observed to vary as much as 30 °F. There is minimal scientific research available that focuses on the process of measuring dew point of a gas inside a pressurized transformer, let alone this observed phenomenon. The primary objective of this work was to determine what effect certain factors potentially have on dew point measurements of a transformer's internal gas volume, in hopes of understanding the root cause of this phenomenon. Three factors that were studied include (1) human error, (2) the use of calibrated and out-of-calibration instruments, and (3) the presence of oil vapor gases in the dry air sample, and their subsequent effects on the Q-value of the sampled gas. After completing this portion of testing, none of the selected variables proved to be a direct cause of the observed discrepancies between the two instruments. The secondary objective was to validate the accuracy of each instrument as compared to its respective published range by testing against a known dew point temperature produced by a humidity generator. In a select operating range of -22 °F to -4 °F, both instruments were found to be accurate and within their specified tolerances. This temperature range is frequently encountered in oil-soaked transformers, and demonstrates that both instruments can measure accurately over a limited, yet common, range despite their different design methodologies. It is clear that there is another unknown factor present in oil-soaked transformers that is causing the observed discrepancy between these instruments. Future work will include testing on newly manufactured or rewound transformers in order to investigate other variables that could be causing this discrepancy.

Early meteorological records from Latin-America and the Caribbean during the 18th and 19th centuries

NASA Astrophysics Data System (ADS)

Domínguez-Castro, Fernando; Vaquero, José Manuel; Gallego, María Cruz; Farrona, Ana María Marín; Antuña-Marrero, Juan Carlos; Cevallos, Erika Elizabeth; Herrera, Ricardo García; de La Guía, Cristina; Mejía, Raúl David; Naranjo, José Manuel; Del Rosario Prieto, María; Ramos Guadalupe, Luis Enrique; Seiner, Lizardo; Trigo, Ricardo Machado; Villacís, Marcos

2017-11-01

This paper provides early instrumental data recovered for 20 countries of Latin-America and the Caribbean (Argentina, Bahamas, Belize, Brazil, British Guiana, Chile, Colombia, Costa Rica, Cuba, Ecuador, France (Martinique and Guadalupe), Guatemala, Jamaica, Mexico, Nicaragua, Panama, Peru, Puerto Rico, El Salvador and Suriname) during the 18th and 19th centuries. The main meteorological variables retrieved were air temperature, atmospheric pressure, and precipitation, but other variables, such as humidity, wind direction, and state of the sky were retrieved when possible. In total, more than 300,000 early instrumental data were rescued (96% with daily resolution). Especial effort was made to document all the available metadata in order to allow further post-processing. The compilation is far from being exhaustive, but the dataset will contribute to a better understanding of climate variability in the region, and to enlarging the period of overlap between instrumental data and natural/documentary proxies.

Early meteorological records from Latin-America and the Caribbean during the 18th and 19th centuries.

PubMed

Domínguez-Castro, Fernando; Vaquero, José Manuel; Gallego, María Cruz; Farrona, Ana María Marín; Antuña-Marrero, Juan Carlos; Cevallos, Erika Elizabeth; Herrera, Ricardo García; de la Guía, Cristina; Mejía, Raúl David; Naranjo, José Manuel; Del Rosario Prieto, María; Ramos Guadalupe, Luis Enrique; Seiner, Lizardo; Trigo, Ricardo Machado; Villacís, Marcos

2017-11-14

This paper provides early instrumental data recovered for 20 countries of Latin-America and the Caribbean (Argentina, Bahamas, Belize, Brazil, British Guiana, Chile, Colombia, Costa Rica, Cuba, Ecuador, France (Martinique and Guadalupe), Guatemala, Jamaica, Mexico, Nicaragua, Panama, Peru, Puerto Rico, El Salvador and Suriname) during the 18th and 19th centuries. The main meteorological variables retrieved were air temperature, atmospheric pressure, and precipitation, but other variables, such as humidity, wind direction, and state of the sky were retrieved when possible. In total, more than 300,000 early instrumental data were rescued (96% with daily resolution). Especial effort was made to document all the available metadata in order to allow further post-processing. The compilation is far from being exhaustive, but the dataset will contribute to a better understanding of climate variability in the region, and to enlarging the period of overlap between instrumental data and natural/documentary proxies.

The impact of extracurricular activities participation on youth delinquent behaviors: An instrumental variables approach.

PubMed

Han, Sehee; Lee, Jonathan; Park, Kyung-Gook

2017-07-01

The purpose of this study was to examine the association between extracurricular activities (EA) participation and youth delinquency while tackling an endogeneity problem of EA participation. Using survey data of 12th graders in South Korea (n = 1943), this study employed an instrumental variables approach to address the self-selection problem of EA participation as the data for this study was based on an observational study design. We found a positive association between EA participation and youth delinquency based on conventional regression analysis. By contrast, we found a negative association between EA participation and youth delinquency based on an instrumental variables approach. These results indicate that caution should be exercised when we interpret the effect of EA participation on youth delinquency based on observational study designs. Copyright © 2017 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Equivalent Sensor Radiance Generation and Remote Sensing from Model Parameters. Part 1; Equivalent Sensor Radiance Formulation

NASA Technical Reports Server (NTRS)

Wind, Galina; DaSilva, Arlindo M.; Norris, Peter M.; Platnick, Steven E.

2013-01-01

In this paper we describe a general procedure for calculating equivalent sensor radiances from variables output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint the algorithm takes explicit account of the model subgrid variability, in particular its description of the probably density function of total water (vapor and cloud condensate.) The equivalent sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies. We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products.) We focus on clouds and cloud/aerosol interactions, because they are very important to model development and improvement.

Multi-sensor Cloud Retrieval Simulator and Remote Sensing from Model Parameters . Pt. 1; Synthetic Sensor Radiance Formulation; [Synthetic Sensor Radiance Formulation

NASA Technical Reports Server (NTRS)

Wind, G.; DaSilva, A. M.; Norris, P. M.; Platnick, S.

2013-01-01

In this paper we describe a general procedure for calculating synthetic sensor radiances from variable output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint, the algorithm takes explicit account of the model subgrid variability, in particular its description of the probability density function of total water (vapor and cloud condensate.) The simulated sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies.We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products). We focus on clouds because they are very important to model development and improvement.

A Fast and Sensitive New Satellite SO2 Retrieval Algorithm based on Principal Component Analysis: Application to the Ozone Monitoring Instrument

NASA Technical Reports Server (NTRS)

Li, Can; Joiner, Joanna; Krotkov, A.; Bhartia, Pawan K.

2013-01-01

We describe a new algorithm to retrieve SO2 from satellite-measured hyperspectral radiances. We employ the principal component analysis technique in regions with no significant SO2 to capture radiance variability caused by both physical processes (e.g., Rayleigh and Raman scattering and ozone absorption) and measurement artifacts. We use the resulting principal components and SO2 Jacobians calculated with a radiative transfer model to directly estimate SO2 vertical column density in one step. Application to the Ozone Monitoring Instrument (OMI) radiance spectra in 310.5-340 nm demonstrates that this approach can greatly reduce biases in the operational OMI product and decrease the noise by a factor of 2, providing greater sensitivity to anthropogenic emissions. The new algorithm is fast, eliminates the need for instrument-specific radiance correction schemes, and can be easily adapted to other sensors. These attributes make it a promising technique for producing longterm, consistent SO2 records for air quality and climate research.

The versatility of limb scattered sunlight measurements

NASA Astrophysics Data System (ADS)

Bourassa, A. E.; Degenstein, D. A.; Sioris, C.; Rieger, L. A.; Zawada, D.

2017-12-01

Vertically resolved measurements of limb scattered sunlight spectra in the UV-Vis-NIR spectral range have been made from several satellite instruments in low earth orbit for many years, and there has been much success in using these measurements for retrievals of trace gas and aerosol from the upper troposphere to the mesosphere. Due in a large part to improvements in radiative transfer modelling, the versatility of the limb scatter measurement has continued to grow over the last several years. Using OSIRIS and OMPS instruments as primary examples, this talk will review the current capability of limb scatter measurements, and highlight recent results on ozone variability and trends in the UTLS, the continuation of the aerosol extinction record, NO2 distributions in the upper troposphere, and a new tomographic retrieval of ozone from the OMPS measurements. The future of limb scatter observations will also be discussed, including the development of two new Canadian suborbital instrument concepts that are targeted at high spatial resolution UTLS water vapor and cloud/aerosol measurements.

The self-medication hypothesis: Evidence from terrorism and cigarette accessibility.

PubMed

Pesko, Michael F; Baum, Christopher F

2016-09-01

We use single equation and system instrumental variable models to explore if individuals smoke during times of stress (the motivation effect) and if they are successful in self-medicating short-term stress (the self-medication effect). Short-term stress is a powerful motivator of smoking, and the decision to smoke could trigger biological feedback that immediately reduces short-term stress. We use data on self-reported smoking and stress from 240,388 current and former smokers. We instrument short-term stress with temporal distance from September 11, 2001 (using date of interview). We instrument smoking with cigarette accessibility measures of cigarette price changes and distance to state borders. In the absence of accounting for endogeneity, we find that smoking is associated with increases in short-term stress. However, when we account for endogeneity we find no evidence of smoking affecting short-term stress. We do find a consistent positive effect of short-term stress on smoking. Copyright © 2016 Elsevier B.V. All rights reserved.

Understanding the Global Variability in Thermospheric Nitric Oxide Flux Using Empirical Orthogonal Functions (EOFs)

NASA Astrophysics Data System (ADS)

Flynn, Sierra; Knipp, Delores J.; Matsuo, Tomoko; Mlynczak, Martin; Hunt, Linda

2018-05-01

We present the first-ever global assessment of thermospheric nitric oxide infrared radiative flux (NOF) variability. NOF (W/m2) from 100- to 250-km altitude is extracted from 13.7 years of data from the TIMED satellite, Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument, and decomposed into four empirical orthogonal functions (EOFs) and their amplitudes. We determine the strongest modes of NOF variability in the data set and develop a compact model of NOF. The first four EOFs account for 83% of the variability in the data. We illustrate the NOF model and discuss the geophysical associations of the EOFs. The first EOF represents 69% of the total variance and correlates strongly with Kp and solar shortwave flux, suggesting that geomagnetic activity and solar weather account for a large portion of NOF variability. EOF 2 shows annual and seasonal variations, possibly due to annual and seasonal thermospheric composition and temperature changes and may represent the chemical breathing mode of NOF. EOF 3 shows annual variations and correlates with solar energetic particle events and X-flares. EOF 3 may represent winter time solar energetic particle event-enhanced diurnal tide effects. EOF 4 suggests a meridional transport mechanism at the predawn and postdusk equator after strong storms. The EOF uncertainty is verified using cross-validation analysis. Quantifying the spatial and temporal variabilities of NOF using eigenmodes will increase the understanding of how upper atmospheric nitric oxide cooling behaves and could increase the accuracy of future space weather and climate models.

Kinetic Risk Factors of Running-Related Injuries in Female Recreational Runners.

PubMed

Napier, Christopher; MacLean, Christopher L; Maurer, Jessica; Taunton, Jack E; Hunt, Michael A

2018-05-30

Our objective was to prospectively investigate the association of kinetic variables with running-related injury (RRI) risk. Seventy-four healthy female recreational runners ran on an instrumented treadmill while 3D kinetic and kinematic data were collected. Kinetic outcomes were vertical impact transient, average vertical loading rate, instantaneous vertical loading rate, active peak, vertical impulse, and peak braking force (PBF). Participants followed a 15-week half-marathon training program. Exposure time (hours of running) was calculated from start of program until onset of injury, loss to follow-up, or end of program. After converting kinetic variables from continuous to ordinal variables based on tertiles, Cox proportional hazard models with competing risks were fit for each variable independently, before analysis in a forward stepwise multivariable model. Sixty-five participants were included in the final analysis, with a 33.8% injury rate. PBF was the only kinetic variable that was a significant predictor of RRI. Runners in the highest tertile (PBF <-0.27 BW) were injured at 5.08 times the rate of those in the middle tertile and 7.98 times the rate of those in the lowest tertile. When analyzed in the multivariable model, no kinetic variables made a significant contribution to predicting injury beyond what had already been accounted for by PBF alone. Findings from this study suggest PBF is associated with a significantly higher injury hazard ratio in female recreational runners and should be considered as a target for gait retraining interventions. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Are gestational age, birth weight, and birth length indicators of favorable fetal growth conditions? A structural equation analysis of Filipino infants.

PubMed

Bollen, Kenneth A; Noble, Mark D; Adair, Linda S

2013-07-30

The fetal origins hypothesis emphasizes the life-long health impacts of prenatal conditions. Birth weight, birth length, and gestational age are indicators of the fetal environment. However, these variables often have missing data and are subject to random and systematic errors caused by delays in measurement, differences in measurement instruments, and human error. With data from the Cebu (Philippines) Longitudinal Health and Nutrition Survey, we use structural equation models, to explore random and systematic errors in these birth outcome measures, to analyze how maternal characteristics relate to birth outcomes, and to take account of missing data. We assess whether birth weight, birth length, and gestational age are influenced by a single latent variable that we call favorable fetal growth conditions (FFGC) and if so, which variable is most closely related to FFGC. We find that a model with FFGC as a latent variable fits as well as a less parsimonious model that has birth weight, birth length, and gestational age as distinct individual variables. We also demonstrate that birth weight is more reliably measured than is gestational age. FFGCs were significantly influenced by taller maternal stature, better nutritional stores indexed by maternal arm fat and muscle area during pregnancy, higher birth order, avoidance of smoking, and maternal age 20-35 years. Effects of maternal characteristics on newborn weight, length, and gestational age were largely indirect, operating through FFGC. Copyright © 2013 John Wiley & Sons, Ltd.

A thermal control system for long-term survival of scientific instruments on lunar surface

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

Ogawa, K., E-mail: ogawa@astrobio.k.u-tokyo.ac.jp; Iijima, Y.; Tanaka, S.

2014-03-15

A thermal control system is being developed for scientific instruments placed on the lunar surface. This thermal control system, Lunar Mission Survival Module (MSM), was designed for scientific instruments that are planned to be operated for over a year in the future Japanese lunar landing mission SELENE-2. For the long-term operations, the lunar surface is a severe environment because the soil (regolith) temperature varies widely from nighttime −200 degC to daytime 100 degC approximately in which space electronics can hardly survive. The MSM has a tent of multi-layered insulators and performs a “regolith mound”. Temperature of internal devices is lessmore » variable just like in the lunar underground layers. The insulators retain heat in the regolith soil in the daylight, and it can keep the device warm in the night. We conducted the concept design of the lunar survival module, and estimated its potential by a thermal mathematical model on the assumption of using a lunar seismometer designed for SELENE-2. Thermal vacuum tests were also conducted by using a thermal evaluation model in order to estimate the validity of some thermal parameters assumed in the computed thermal model. The numerical and experimental results indicated a sufficient survivability potential of the concept of our thermal control system.« less

The clinical learning environment and supervision by staff nurses: developing the instrument.

PubMed

Saarikoski, Mikko; Leino-Kilpi, Helena

2002-03-01

The aims of this study were (1) to describe students' perceptions of the clinical learning environment and clinical supervision and (2) to develop an evaluation scale by using the empirical results of this study. The data were collected using the Clinical Learning Environment and Supervision instrument (CLES). The instrument was based on the literature review of earlier studies. The derived instrument was tested empirically in a study involving nurse students (N=416) from four nursing colleges in Finland. The results demonstrated that the method of supervision, the number of separate supervision sessions and the psychological content of supervisory contact within a positive ward atmosphere are the most important variables in the students' clinical learning. The results also suggest that ward managers can create the conditions of a positive ward culture and a positive attitude towards students and their learning needs. The construct validity of the instrument was analysed by using exploratory factor analysis. The analysis indicated that the most important factor in the students' clinical learning is the supervisory relationship. The two most important factors constituting a 'good' clinical learning environment are the management style of the ward manager and the premises of nursing on the ward. The results of the factor analysis support the theoretical construction of the clinical learning environment modelled by earlier empirical studies.

The very low frequency power spectrum of Centaurus X-3

NASA Technical Reports Server (NTRS)

Gruber, D. E.

1988-01-01

The long-term variability of Cen X-3 on time scales ranging from days to years has been examined by combining data obtained by the HEAO 1 A-4 instrument with data from Vela 5B. A simple interpretation of the data is made in terms of the standard alpha-disk model of accretion disk structure and dynamics. Assuming that the low-frequency variance represents the inherent variability of the mass transfer from the companion, the decline in power at higher frequencies results from the leveling of radial structure in the accretion disk through viscous mixing. The shape of the observed power spectrum is shown to be in excellent agreement with a calculation based on a simplified form of this model. The observed low-frequency power spectrum of Cen X-3 is consistent with a disk in which viscous mixing occurs about as rapidly as possible and on the largest scale possible.

European temperature records of the past five centuries based on documentary information compared to climate simulations

NASA Astrophysics Data System (ADS)

Zorita, E.

2009-09-01

Two European temperature records for the past half-millennium, January-to-April air temperature for Stockholm (Sweden) and seasonal temperature for a Central European region, both derived from the analysis of documentary sources combined with long instrumental records, are compared with the output of forced (solar, volcanic, greenhouse gases) climate simulations with the model ECHO-G. The analysis is complemented with the long (early)-instrumental record of Central England Temperature (CET). Both approaches to study past climates (simulations and reconstructions) are burdened with uncertainties. The main objective of this comparative analysis is to identify robust features and weaknesses that may help to improve models and reconstruction methods. The results indicate a general agreement between simulations and the reconstructed Stockholm and CET records regarding the long-term temperature trend over the recent centuries, suggesting a reasonable choice of the amplitude of the solar forcing in the simulations and sensitivity of the model to the external forcing. However, the Stockholm reconstruction and the CET record also show a long and clear multi-decadal warm episode peaking around 1730, which is absent in the simulations. The uncertainties associated with the reconstruction method or with the simulated internal climate variability cannot easily explain this difference. Regarding the interannual variability, the Stockholm series displays in some periods higher amplitudes than the simulations but these differences are within the statistical uncertainty and further decrease if output from a regional model driven by the global model is used. The long-term trends in the simulations and reconstructions of the Central European temperature agree less well. The reconstructed temperature displays, for all seasons, a smaller difference between the present climate and past centuries than the simulations. Possible reasons for these differences may be related to a limitation of the traditional technique for converting documentary evidence to temperature values to capture long-term climate changes, because the documents often reflect temperatures relative to the contemporary authors' own perception of what constituted 'normal' conditions. By contrast, the simulated and reconstructed inter-annual variability is in rather good agreement.

Coverage Maximization Using Dynamic Taint Tracing

DTIC Science & Technology

2007-03-28

we do not have source code are handled, incompletely, via models of taint transfer. We use a little language to specify how taint transfers across a...n) 2.3.7 Implementation and Runtime Issues The taint graph instrumentation is a 2K line Ocaml module extending CIL and is supported by 5K lines of...modern scripting languages such as Ruby have taint modes that work similarly; however, all propagate taint at the variable rather than the byte level and

Importance of Intrinsic and Instrumental Value of Education in Pakistan

ERIC Educational Resources Information Center

Kumar, Mahendar

2017-01-01

Normally, effectiveness of any object or thing is judged by two values; intrinsic and instrumental. To compare intrinsic value of education with instrumental value, this study has used the following variables: getting knowledge for its own sake, getting knowledge for social status, getting knowledge for job or business endeavor and getting…

Remote-sensing reflectance determinations in the coastal ocean environment: impact of instrumental characteristics and environmental variability.

PubMed

Toole, D A; Siegel, D A; Menzies, D W; Neumann, M J; Smith, R C

2000-01-20

Three independent ocean color sampling methodologies are compared to assess the potential impact of instrumental characteristics and environmental variability on shipboard remote-sensing reflectance observations from the Santa Barbara Channel, California. Results indicate that under typical field conditions, simultaneous determinations of incident irradiance can vary by 9-18%, upwelling radiance just above the sea surface by 8-18%, and remote-sensing reflectance by 12-24%. Variations in radiometric determinations can be attributed to a variety of environmental factors such as Sun angle, cloud cover, wind speed, and viewing geometry; however, wind speed is isolated as the major source of uncertainty. The above-water approach to estimating water-leaving radiance and remote-sensing reflectance is highly influenced by environmental factors. A model of the role of wind on the reflected sky radiance measured by an above-water sensor illustrates that, for clear-sky conditions and wind speeds greater than 5 m/s, determinations of water-leaving radiance at 490 nm are undercorrected by as much as 60%. A data merging procedure is presented to provide sky radiance correction parameters for above-water remote-sensing reflectance estimates. The merging results are consistent with statistical and model findings and highlight the importance of multiple field measurements in developing quality coastal oceanographic data sets for satellite ocean color algorithm development and validation.

The effect of aircraft control forces on pilot performance during instrument landings in a flight simulator.

PubMed

Hewson, D J; McNair, P J; Marshall, R N

2001-07-01

Pilots may have difficulty controlling aircraft at both high and low force levels due to larger variability in force production at these force levels. The aim of this study was to measure the force variability and landing performance of pilots during an instrument landing in a flight simulator. There were 12 pilots who were tested while performing 5 instrument landings in a flight simulator, each of which required different control force inputs. Pilots can produce the least force when pushing the control column to the right, therefore the force levels for the landings were set relative to each pilot's maximum aileron-right force. The force levels for the landings were 90%, 60%, and 30% of maximal aileron-right force, normal force, and 25% of normal force. Variables recorded included electromyographic activity (EMG), aircraft control forces, aircraft attitude, perceived exertion and deviation from glide slope and heading. Multivariate analysis of variance was used to test for differences between landings. Pilots were least accurate in landing performance during the landing at 90% of maximal force (p < 0.05). There was also a trend toward decreased landing performance during the landing at 25% of normal force. Pilots were more variable in force production during the landings at 60% and 90% of maximal force (p < 0.05). Pilots are less accurate at performing instrument landings when control forces are high due to the increased variability of force production. The increase in variability at high force levels is most likely associated with motor unit recruitment, rather than rate coding. Aircraft designers need to consider the reduction in pilot performance at high force levels, as well as pilot strength limits when specifying new standards.

Spectrophotometers for plutonium monitoring in HB-line

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

Lascola, R. J.; O'Rourke, P. E.; Kyser, E. A.

2016-02-12

This report describes the equipment, control software, calibrations for total plutonium and plutonium oxidation state, and qualification studies for the instrument. It also provides a detailed description of the uncertainty analysis, which includes source terms associated with plutonium calibration standards, instrument drift, and inter-instrument variability. Also included are work instructions for instrument, flow cell, and optical fiber setup, work instructions for routine maintenance, and drawings and schematic diagrams.

A new instrument for measuring anticoagulation-related quality of life: development and preliminary validation

PubMed Central

Samsa, Greg; Matchar, David B; Dolor, Rowena J; Wiklund, Ingela; Hedner, Ewa; Wygant, Gail; Hauch, Ole; Marple, Cheryl Beadle; Edwards, Roger

2004-01-01

Background Anticoagulation can reduce quality of life, and different models of anticoagulation management might have different impacts on satisfaction with this component of medical care. Yet, to our knowledge, there are no scales measuring quality of life and satisfaction with anticoagulation that can be generalized across different models of anticoagulation management. We describe the development and preliminary validation of such an instrument – the Duke Anticoagulation Satisfaction Scale (DASS). Methods The DASS is a 25-item scale addressing the (a) negative impacts of anticoagulation (limitations, hassles and burdens); and (b) positive impacts of anticoagulation (confidence, reassurance, satisfaction). Each item has 7 possible responses. The DASS was administered to 262 patients currently receiving oral anticoagulation. Scales measuring generic quality of life, satisfaction with medical care, and tendency to provide socially desirable responses were also administered. Statistical analysis included assessment of item variability, internal consistency (Cronbach's alpha), scale structure (factor analysis), and correlations between the DASS and demographic variables, clinical characteristics, and scores on the above scales. A follow-up study of 105 additional patients assessed test-retest reliability. Results 220 subjects answered all items. Ceiling and floor effects were modest, and 25 of the 27 proposed items grouped into 2 factors (positive impacts, negative impacts, this latter factor being potentially subdivided into limitations versus hassles and burdens). Each factor had a high degree of internal consistency (Cronbach's alpha 0.78–0.91). The limitations and hassles factors consistently correlated with the SF-36 scales measuring generic quality of life, while the positive psychological impact scale correlated with age and time on anticoagulation. The intra-class correlation coefficient for test-retest reliability was 0.80. Conclusions The DASS has demonstrated reasonable psychometric properties to date. Further validation is ongoing. To the degree that dissatisfaction with anticoagulation leads to decreased adherence, poorer INR control, and poor clinical outcomes, the DASS has the potential to help identify reasons for dissatisfaction (and positive satisfaction), and thus help to develop interventions to break this cycle. As an instrument designed to be applicable across multiple models of anticoagulation management, the DASS could be crucial in the scientific comparison between those models of care. PMID:15132746

Long-term infrared monitoring of stellar sources from earth orbit

NASA Technical Reports Server (NTRS)

Maran, S. P.; Heinsheimer, T. F.; Stocker, T. L.; Anand, S. P. S.; Chapman, R. D.; Hobbs, R. W.; Michalitsanos, A. G.; Wright, F. H.; Kipp, S. L.

1976-01-01

A program is discussed which involved monitoring the photometric activity of 18 bright variable IR stars at 2.7 microns with satellite- and rocket-borne instrumentation in the period from 1971 to 1975. The stellar sample includes 3 Lb variables, 8 semiregular variables, 5 Mira-type variables, and 2 previously unknown and unclassified IR variables. Detailed light curves of many of these stars were determined for intervals of 3 yr or more; spectra from 2.7 to 20 microns were constructed for nine of them using data obtained entirely with instruments above the atmosphere. Photometric IR light curves and other data are presented for SW Virginis, R Aquilae, S Scuti, IRC 00265, RT Hydrae, S Orionis, S Canis Minoris, Omicron Ceti, and R Leonis. Several hypotheses concerning the interpretation of the IR data are examined.

Confronting weather and climate models with observational data from soil moisture networks over the United States

PubMed Central

Dirmeyer, Paul A.; Wu, Jiexia; Norton, Holly E.; Dorigo, Wouter A.; Quiring, Steven M.; Ford, Trenton W.; Santanello, Joseph A.; Bosilovich, Michael G.; Ek, Michael B.; Koster, Randal D.; Balsamo, Gianpaolo; Lawrence, David M.

2018-01-01

Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those we find that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely due to differences in instrumentation, calibration and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory) and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses outperform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Data from models and observations should be put on the same spatial and temporal scales before comparison. PMID:29645013

Confronting Weather and Climate Models with Observational Data from Soil Moisture Networks over the United States

NASA Technical Reports Server (NTRS)

Dirmeyer, Paul A.; Wu, Jiexia; Norton, Holly E.; Dorigo, Wouter A.; Quiring, Steven M.; Ford, Trenton W.; Santanello, Joseph A., Jr.; Bosilovich, Michael G.; Ek, Michael B.; Koster, Randal Dean;

Confronting weather and climate models with observational data from soil moisture networks over the United States.

PubMed

Dirmeyer, Paul A; Wu, Jiexia; Norton, Holly E; Dorigo, Wouter A; Quiring, Steven M; Ford, Trenton W; Santanello, Joseph A; Bosilovich, Michael G; Ek, Michael B; Koster, Randal D; Balsamo, Gianpaolo; Lawrence, David M

2016-04-01

Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those we find that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely due to differences in instrumentation, calibration and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory) and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses outperform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Data from models and observations should be put on the same spatial and temporal scales before comparison.

Analysis of tablet compaction. I. Characterization of mechanical behavior of powder and powder/tooling friction.

PubMed

Cunningham, J C; Sinka, I C; Zavaliangos, A

2004-08-01

In this first of two articles on the modeling of tablet compaction, the experimental inputs related to the constitutive model of the powder and the powder/tooling friction are determined. The continuum-based analysis of tableting makes use of an elasto-plastic model, which incorporates the elements of yield, plastic flow potential, and hardening, to describe the mechanical behavior of microcrystalline cellulose over the range of densities experienced during tableting. Specifically, a modified Drucker-Prager/cap plasticity model, which includes material parameters such as cohesion, internal friction, and hydrostatic yield pressure that evolve with the internal state variable relative density, was applied. Linear elasticity is assumed with the elastic parameters, Young's modulus, and Poisson's ratio dependent on the relative density. The calibration techniques were developed based on a series of simple mechanical tests including diametrical compression, simple compression, and die compaction using an instrumented die. The friction behavior is measured using an instrumented die and the experimental data are analyzed using the method of differential slices. The constitutive model and frictional properties are essential experimental inputs to the finite element-based model described in the companion article. Copyright 2004 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 93:2022-2039, 2004

Reconstruction of precipitation variability in Estonia since the eighteenth century, inferred from oak and spruce tree rings

NASA Astrophysics Data System (ADS)

Helama, Samuli; Sohar, Kristina; Läänelaid, Alar; Bijak, Szymon; Jaagus, Jaak

2018-06-01

There is plenty of evidence for intensification of the global hydrological cycle. In Europe, the northern areas are predicted to receive more precipitation in the future and observational evidence suggests a parallel trend over the past decades. As a consequence, it would be essential to place the recent trend in precipitation in the context of proxy-based estimates of reconstructed precipitation variability over the past centuries. Tree rings are frequently used as proxy data for palaeoclimate reconstructions. Here we use deciduous ( Quercus robur) and coniferous ( Picea abies) tree-ring width chronologies from western Estonia to deduce past early-summer (June) precipitation variability since 1771. Statistical model transforming our tree-ring data into estimates of precipitation sums explains 42% of the variance in instrumental variability. Comparisons with products of gridded reconstructions of soil moisture and summer precipitation illustrate robust correlations with soil moisture (Palmer Drought Severity Index), but lowered correlation with summer precipitation estimates prior to mid-nineteenth century, these instabilities possibly reflecting the general uncertainties inherent to early meteorological and proxy data. Reconstructed precipitation variability was negatively correlated to the teleconnection indices of the North Atlantic Oscillation and the Scandinavia pattern, on annual to decadal and longer scales. These relationships demonstrate the positive precipitation anomalies to result from increase in zonal inflow and cyclonic activity, the negative anomalies being linked with the high pressure conditions enhanced during the atmospheric blocking episodes. Recently, the instrumental data have demonstrated a remarkable increase in summer (June) precipitation in the study region. Our tree-ring based reconstruction reproduces this trend in the context of precipitation history since eighteenth century and quantifies the unprecedented abundance of June precipitation over the recent years.

TENI: A comprehensive battery for cognitive assessment based on games and technology.

PubMed

Delgado, Marcela Tenorio; Uribe, Paulina Arango; Alonso, Andrés Aparicio; Díaz, Ricardo Rosas

2016-01-01

TENI (Test de Evaluación Neuropsicológica Infantil) is an instrument developed to assess cognitive abilities in children between 3 and 9 years of age. It is based on a model that incorporates games and technology as tools to improve the assessment of children's capacities. The test was standardized with two Chilean samples of 524 and 82 children living in urban zones. Evidence of reliability and validity based on current standards is presented. Data show good levels of reliability for all subtests. Some evidence of validity in terms of content, test structure, and association with other variables is presented. This instrument represents a novel approach and a new frontier in cognitive assessment. Further studies with clinical, rural, and cross-cultural populations are required.

Balloon-borne radiometer measurements of Northern Hemisphere mid-latitude stratospheric HNO3 profiles spanning 12 years

NASA Astrophysics Data System (ADS)

Toohey, M.; Quine, B. M.; Strong, K.; Bernath, P. F.; Boone, C. D.; Jonsson, A. I.; McElroy, C. T.; Walker, K. A.; Wunch, D.

2007-12-01

Low-resolution atmospheric thermal emission spectra collected by balloon-borne radiometers over the time span of 1990-2002 are used to retrieve vertical profiles of HNO3, CFC-11 and CFC-12 volume mixing ratios between approximately 10 and 35 km altitude. All of the data analyzed have been collected from launches from a Northern Hemisphere mid-latitude site, during late summer, when stratospheric dynamic variability is at a minimum. The retrieval technique incorporates detailed forward modeling of the instrument and the radiative properties of the atmosphere, and obtains a best fit between modeled and measured spectra through a combination of onion-peeling and optimization steps. The retrieved HNO3 profiles are consistent over the 12-year period, and are consistent with recent measurements by the Atmospheric Chemistry Experiment-Fourier transform spectrometer satellite instrument. We therefore find no evidence of long-term changes in the HNO3 summer mid-latitude profile, although the uncertainty of our measurements precludes a conclusive trend analysis.

Balloon-borne radiometer measurement of Northern Hemisphere mid-latitude stratospheric HNO3 profiles spanning 12 years

NASA Astrophysics Data System (ADS)

Toohey, M.; Quine, B. M.; Strong, K.; Bernath, P. F.; Boone, C. D.; Jonsson, A. I.; McElroy, C. T.; Walker, K. A.; Wunch, D.

2007-08-01

Low-resolution atmospheric thermal emission spectra collected by balloon-borne radiometers over the time span of 1990-2002 are used to retrieve vertical profiles of HNO3, CFC-11 and CFC-12 volume mixing ratios between approximately 10 and 35 km altitude. All of the data analyzed have been collected from launches from a Northern Hemisphere mid-latitude site, during late summer, when stratospheric dynamic variability is at a minimum. The retrieval technique incorporates detailed forward modeling of the instrument and the radiative properties of the atmosphere, and obtains a best fit between modeled and measured spectra through a combination of onion-peeling and global optimization steps. The retrieved HNO3 profiles are consistent over the 12-year period, and are consistent with recent measurements by the Atmospheric Chemistry Experiment-Fourier transform spectrometer satellite instrument. This suggests that, to within the errors of the 1990 measurements, there has been no significant change in the HNO3 summer mid-latitude profile.

Tropospheric Ozone Source Attribution in Southern California during Summer 2014 Based on Lidar Measurements and Model Simulations

NASA Technical Reports Server (NTRS)

Granados Munoz, Maria Jose; Johnson, Matthew S.; Leblanc, Thierry

2016-01-01

In the past decades, significant efforts have been made to increase tropospheric ozone long-term monitoring. A large number of ground-based, airborne and space-borne instruments are currently providing valuable data to contribute to better understand tropospheric ozone budget and variability. Nonetheless, most of these instruments provide in-situ surface and column-integrated data, whereas vertically resolved measurements are still scarce. Besides ozonesondes and aircraft, lidar measurements have proven to be valuable tropospheric ozone profilers. Using the measurements from the tropospheric ozone differential absorption lidar (DIAL) located at the JPL Table Mountain Facility, California, and the GEOS-Chem and GEOS-5 model outputs, the impact of the North American monsoon on tropospheric ozone during summer 2014 is investigated. The influence of the Monsoon lightning-induced NOx will be evaluated against other sources (e.g. local anthropogenic emissions and the stratosphere) using also complementary data such as backward-trajectories analysis, coincident water vapor lidar measurements, and surface ozone in-situ measurements.

Pressure/temperature fluid cell apparatus for the neutron powder diffractometer instrument: probing atomic structure in situ.

PubMed

Wang, Hsiu-Wen; Fanelli, Victor R; Reiche, Helmut M; Larson, Eric; Taylor, Mark A; Xu, Hongwu; Zhu, Jinlong; Siewenie, Joan; Page, Katharine

2014-12-01

This contribution describes a new local structure compatible gas/liquid cell apparatus for probing disordered materials at high pressures and variable temperatures in the Neutron Powder Diffraction instrument at the Lujan Neutron Scattering Center, Los Alamos National Laboratory. The new sample environment offers choices for sample canister thickness and canister material type. Finite element modeling is utilized to establish maximum allowable working pressures of 414 MPa at 15 K and 121 MPa at 600 K. High quality atomic pair distribution function data extraction and modeling have been demonstrated for a calibration standard (Si powder) and for supercritical and subcritical CO2 measurements. The new sample environment was designed to specifically target experimental studies of the local atomic structures involved in geologic CO2 sequestration, but will be equally applicable to a wide variety of energy applications, including sorption of fluids on nano/meso-porous solids, clathrate hydrate formation, catalysis, carbon capture, and H2 and natural gas uptake/storage.

Generic patient-reported outcomes in child health research: a review of conceptual content using World Health Organization definitions.

PubMed

Fayed, Nora; de Camargo, Olaf Kraus; Kerr, Elizabeth; Rosenbaum, Peter; Dubey, Ankita; Bostan, Cristina; Faulhaber, Markus; Raina, Parminder; Cieza, Alarcos

2012-12-01

Our aims were to (1) describe the conceptual basis of popular generic instruments according to World Health Organization (WHO) definitions of functioning, disability, and health (FDH), and quality of life (QOL) with health-related quality of life (HRQOL) as a subcomponent of QOL; (2) map the instruments to the International Classification of Functioning, Disability and Health (ICF); and (3) provide information on how the analyzed instruments were used in the literature. This should enable users to make valid choices about which instruments have the desired content for a specific context or purpose. Child health-based literature over a 5-year period was reviewed to find research employing health status and QOL/HRQOL instruments. WHO definitions of FDH and QOL were applied to each item of the 15 most used instruments to differentiate measures of FDH and QOL/HRQOL. The ICF was used to describe the health and health-related content (if any) in those instruments. Additional aspects of instrument use were extracted from these articles. Many instruments that were used to measure QOL/HRQOL did not reflect WHO definitions of QOL. The ICF domains within instruments were highly variable with respect to whether body functions, activities and participation, or environment were emphasized. There is inconsistency among researchers about how to measure HRQOL and QOL. Moreover, when an ICF content analysis is applied, there is variability among instruments in the health components included and emphasized. Reviewing content is important for matching instruments to their intended purpose. © The Authors. Developmental Medicine & Child Neurology © 2012 Mac Keith Press.

Age-Related Changes in Bimanual Instrument Playing with Rhythmic Cueing

PubMed Central

Kim, Soo Ji; Cho, Sung-Rae; Yoo, Ga Eul

2017-01-01

Deficits in bimanual coordination of older adults have been demonstrated to significantly limit their functioning in daily life. As a bimanual sensorimotor task, instrument playing has great potential for motor and cognitive training in advanced age. While the process of matching a person’s repetitive movements to auditory rhythmic cueing during instrument playing was documented to involve motor and attentional control, investigation into whether the level of cognitive functioning influences the ability to rhythmically coordinate movement to an external beat in older populations is relatively limited. Therefore, the current study aimed to examine how timing accuracy during bimanual instrument playing with rhythmic cueing differed depending on the degree of participants’ cognitive aging. Twenty one young adults, 20 healthy older adults, and 17 older adults with mild dementia participated in this study. Each participant tapped an electronic drum in time to the rhythmic cueing provided using both hands simultaneously and in alternation. During bimanual instrument playing with rhythmic cueing, mean and variability of synchronization errors were measured and compared across the groups and the tempo of cueing during each type of tapping task. Correlations of such timing parameters with cognitive measures were also analyzed. The results showed that the group factor resulted in significant differences in the synchronization errors-related parameters. During bimanual tapping tasks, cognitive decline resulted in differences in synchronization errors between younger adults and older adults with mild dimentia. Also, in terms of variability of synchronization errors, younger adults showed significant differences in maintaining timing performance from older adults with and without mild dementia, which may be attributed to decreased processing time for bimanual coordination due to aging. Significant correlations were observed between variability of synchronization errors and performance of cognitive tasks involving executive control and cognitive flexibility when asked for bimanual coordination in response to external timing cues at adjusted tempi. Also, significant correlations with cognitive measures were more prevalent in variability of synchronization errors during alternative tapping compared to simultaneous tapping. The current study supports that bimanual tapping may be predictive of cognitive processing of older adults. Also, tempo and type of movement required for instrument playing both involve cognitive and motor loads at different levels, and such variables could be important factors for determining the complexity of the task and the involved task requirements for interventions using instrument playing. PMID:29085309

Human and natural influences on the changing thermal structure of the atmosphere

PubMed Central

Santer, Benjamin D.; Painter, Jeffrey F.; Bonfils, Céline; Mears, Carl A.; Solomon, Susan; Wigley, Tom M. L.; Gleckler, Peter J.; Schmidt, Gavin A.; Doutriaux, Charles; Gillett, Nathan P.; Taylor, Karl E.; Thorne, Peter W.; Wentz, Frank J.

2013-01-01

Since the late 1970s, satellite-based instruments have monitored global changes in atmospheric temperature. These measurements reveal multidecadal tropospheric warming and stratospheric cooling, punctuated by short-term volcanic signals of reverse sign. Similar long- and short-term temperature signals occur in model simulations driven by human-caused changes in atmospheric composition and natural variations in volcanic aerosols. Most previous comparisons of modeled and observed atmospheric temperature changes have used results from individual models and individual observational records. In contrast, we rely on a large multimodel archive and multiple observational datasets. We show that a human-caused latitude/altitude pattern of atmospheric temperature change can be identified with high statistical confidence in satellite data. Results are robust to current uncertainties in models and observations. Virtually all previous research in this area has attempted to discriminate an anthropogenic signal from internal variability. Here, we present evidence that a human-caused signal can also be identified relative to the larger “total” natural variability arising from sources internal to the climate system, solar irradiance changes, and volcanic forcing. Consistent signal identification occurs because both internal and total natural variability (as simulated by state-of-the-art models) cannot produce sustained global-scale tropospheric warming and stratospheric cooling. Our results provide clear evidence for a discernible human influence on the thermal structure of the atmosphere. PMID:24043789

Evaluating the sensitivity of EQ-5D in a sample of patients with type 2 diabetes mellitus in two tertiary health care facilities in Nigeria.

PubMed

Ekwunife, Obinna Ikechukwu; Ezenduka, Charles C; Uzoma, Bede Emeka

2016-01-12

The EQ-5D instrument is arguably the most well-known and commonly used generic measure of health status internationally. Although the instrument has been employed in outcomes studies of diabetes mellitus in many countries, it has not yet been used in Nigeria. This study was carried out to assess the sensitivity of the EQ-5D instrument in a sample of Nigerian patients with type 2 diabetes mellitus (T2DM). A cross-sectional study was conducted using the EQ-5D instrument to assess the self-reported quality of life of patients with T2DM attending two tertiary healthcare facilities in south eastern Nigeria consenting patients completed the questionnaire while waiting to see a doctor. A priori hypotheses were examined using multiple regression analysis to model the relationship between the dependent variables (EQ VAS and EQ-5D Index) and hypothesized independent variables. A total of 226 patients with T2DM participated in the study. The average age of participants was 57 years (standard deviation 10 years) and 61.1% were male. The EQ VAS score and EQ-5D index averaged 66.19 (standard deviation 15.42) and 0.78 (standard deviation 0.21) respectively. Number of diabetic complications, number of co-morbidities, patient's age and being educated predicted EQ VAS score by -6.76, -6.15, -0.22, and 4.51 respectively. Also, number of diabetic complications, number of co-morbidities, patient's age and being educated predicted EQ-5D index by -0.12, -0.07, -0.003, and 0.06 respectively.. Our findings indicate that the EQ-5D could adequately capture the burden of type 2 diabetes and related complications among Nigerian patients.

Characterizing energy budget variability at a Sahelian site: a test of NWP model behaviour

NASA Astrophysics Data System (ADS)

Mackie, Anna; Palmer, Paul I.; Brindley, Helen

2017-12-01

We use observations of surface and top-of-the-atmosphere (TOA) broadband radiation fluxes determined from the Atmospheric Radiation Measurement programme mobile facility, the Geostationary Earth Radiation Budget (GERB) and Spinning Enhanced Visible and Infrared Imager (SEVIRI) instruments and a range of meteorological variables at a site in the Sahel to test the ability of the ECMWF Integrated Forecasting System cycle 43r1 to describe energy budget variability. The model has daily average biases of -12 and 18 W m-2 for outgoing longwave and reflected shortwave TOA radiation fluxes, respectively. At the surface, the daily average bias is 12(13) W m-2 for the longwave downwelling (upwelling) radiation flux and -21(-13) W m-2 for the shortwave downwelling (upwelling) radiation flux. Using multivariate linear models of observation-model differences, we attribute radiation flux discrepancies to physical processes, and link surface and TOA fluxes. We find that model biases in surface radiation fluxes are mainly due to a low bias in ice water path (IWP), poor description of surface albedo and model-observation differences in surface temperature. We also attribute observed discrepancies in the radiation fluxes, particularly during the dry season, to the misrepresentation of aerosol fields in the model from use of a climatology instead of a dynamic approach. At the TOA, the low IWP impacts the amount of reflected shortwave radiation while biases in outgoing longwave radiation are additionally coupled to discrepancies in the surface upwelling longwave flux and atmospheric humidity.

Sources and Impacts of Modeled and Observed Low-Frequency Climate Variability

NASA Astrophysics Data System (ADS)

Parsons, Luke Alexander

Here we analyze climate variability using instrumental, paleoclimate (proxy), and the latest climate model data to understand more about the sources and impacts of low-frequency climate variability. Understanding the drivers of climate variability at interannual to century timescales is important for studies of climate change, including analyses of detection and attribution of climate change impacts. Additionally, correctly modeling the sources and impacts of variability is key to the simulation of abrupt change (Alley et al., 2003) and extended drought (Seager et al., 2005; Pelletier and Turcotte, 1997; Ault et al., 2014). In Appendix A, we employ an Earth system model (GFDL-ESM2M) simulation to study the impacts of a weakening of the Atlantic meridional overturning circulation (AMOC) on the climate of the American Tropics. The AMOC drives some degree of local and global internal low-frequency climate variability (Manabe and Stouffer, 1995; Thornalley et al., 2009) and helps control the position of the tropical rainfall belt (Zhang and Delworth, 2005). We find that a major weakening of the AMOC can cause large-scale temperature, precipitation, and carbon storage changes in Central and South America. Our results suggest that possible future changes in AMOC strength alone will not be sufficient to drive a large-scale dieback of the Amazonian forest, but this key natural ecosystem is sensitive to dry-season length and timing of rainfall (Parsons et al., 2014). In Appendix B, we compare a paleoclimate record of precipitation variability in the Peruvian Amazon to climate model precipitation variability. The paleoclimate (Lake Limon) record indicates that precipitation variability in western Amazonia is 'red' (i.e., increasing variability with timescale). By contrast, most state-of-the-art climate models indicate precipitation variability in this region is nearly 'white' (i.e., equally variability across timescales). This paleo-model disagreement in the overall structure of the variance spectrum has important consequences for the probability of multi-year drought. Our lake record suggests there is a significant background threat of multi-year, and even decade-length, drought in western Amazonia, whereas climate model simulations indicate most droughts likely last no longer than one to three years. These findings suggest climate models may underestimate the future risk of extended drought in this important region. In Appendix C, we expand our analysis of climate variability beyond South America. We use observations, well-constrained tropical paleoclimate, and Earth system model data to examine the overall shape of the climate spectrum across interannual to century frequencies. We find a general agreement among observations and models that temperature variability increases with timescale across most of the globe outside the tropics. However, as compared to paleoclimate records, climate models generate too little low-frequency variability in the tropics (e.g., Laepple and Huybers, 2014). When we compare the shape of the simulated climate spectrum to the spectrum of a simple autoregressive process, we find much of the modeled surface temperature variability in the tropics could be explained by ocean smoothing of weather noise. Importantly, modeled precipitation tends to be similar to white noise across much of the globe. By contrast, paleoclimate records of various types from around the globe indicate that both temperature and precipitation variability should experience much more low-frequency variability than a simple autoregressive or white-noise process. In summary, state-of-the-art climate models generate some degree of dynamically driven low-frequency climate variability, especially at high latitudes. However, the latest climate models, observations, and paleoclimate data provide us with drastically different pictures of the background climate system and its associated risks. This research has important consequences for improving how we simulate climate extremes as we enter a warmer (and often drier) world in the coming centuries; if climate models underestimate low-frequency variability, we will underestimate the risk of future abrupt change and extreme events, such as megadroughts.

Solar Variability Magnitudes and Timescales

NASA Astrophysics Data System (ADS)

Kopp, Greg

2015-08-01

The Sun’s net radiative output varies on timescales of minutes to many millennia. The former are directly observed as part of the on-going 37-year long total solar irradiance climate data record, while the latter are inferred from solar proxy and stellar evolution models. Since the Sun provides nearly all the energy driving the Earth’s climate system, changes in the sunlight reaching our planet can have - and have had - significant impacts on life and civilizations.Total solar irradiance has been measured from space since 1978 by a series of overlapping instruments. These have shown changes in the spatially- and spectrally-integrated radiant energy at the top of the Earth’s atmosphere from timescales as short as minutes to as long as a solar cycle. The Sun’s ~0.01% variations over a few minutes are caused by the superposition of convection and oscillations, and even occasionally by a large flare. Over days to weeks, changing surface activity affects solar brightness at the ~0.1% level. The 11-year solar cycle has comparable irradiance variations with peaks near solar maxima.Secular variations are harder to discern, being limited by instrument stability and the relatively short duration of the space-borne record. Proxy models of the Sun based on cosmogenic isotope records and inferred from Earth climate signatures indicate solar brightness changes over decades to millennia, although the magnitude of these variations depends on many assumptions. Stellar evolution affects yet longer timescales and is responsible for the greatest solar variabilities.In this talk I will summarize the Sun’s variability magnitudes over different temporal ranges, showing examples relevant for climate studies as well as detections of exo-solar planets transiting Sun-like stars.

Cocaine Dependence Treatment Data: Methods for Measurement Error Problems With Predictors Derived From Stationary Stochastic Processes

PubMed Central

Guan, Yongtao; Li, Yehua; Sinha, Rajita

2011-01-01

In a cocaine dependence treatment study, we use linear and nonlinear regression models to model posttreatment cocaine craving scores and first cocaine relapse time. A subset of the covariates are summary statistics derived from baseline daily cocaine use trajectories, such as baseline cocaine use frequency and average daily use amount. These summary statistics are subject to estimation error and can therefore cause biased estimators for the regression coefficients. Unlike classical measurement error problems, the error we encounter here is heteroscedastic with an unknown distribution, and there are no replicates for the error-prone variables or instrumental variables. We propose two robust methods to correct for the bias: a computationally efficient method-of-moments-based method for linear regression models and a subsampling extrapolation method that is generally applicable to both linear and nonlinear regression models. Simulations and an application to the cocaine dependence treatment data are used to illustrate the efficacy of the proposed methods. Asymptotic theory and variance estimation for the proposed subsampling extrapolation method and some additional simulation results are described in the online supplementary material. PMID:21984854

Review of 99 self-report measures for assessing well-being in adults: exploring dimensions of well-being and developments over time

PubMed Central

Dieppe, Paul

2016-01-01

Objective Investigators within many disciplines are using measures of well-being, but it is not always clear what they are measuring, or which instruments may best meet their objectives. The aims of this review were to: systematically identify well-being instruments, explore the variety of well-being dimensions within instruments and describe how the production of instruments has developed over time. Design Systematic searches, thematic analysis and narrative synthesis were undertaken. Data sources MEDLINE, EMBASE, EconLit, PsycINFO, Cochrane Library and CINAHL from 1993 to 2014 complemented by web searches and expert consultations through 2015. Eligibility criteria Instruments were selected for review if they were designed for adults (≥18 years old), generic (ie, non-disease or context specific) and available in an English version. Results A total of 99 measures of well-being were included, and 196 dimensions of well-being were identified within them. Dimensions clustered around 6 key thematic domains: mental well-being, social well-being, physical well-being, spiritual well-being, activities and functioning, and personal circumstances. Authors were rarely explicit about how existing theories had influenced the design of their tools; however, the 2 most referenced theories were Diener's model of subjective well-being and the WHO definition of health. The period between 1990 and 1999 produced the greatest number of newly developed well-being instruments (n=27). An illustration of the dimensions identified and the instruments that measure them is provided within a thematic framework of well-being. Conclusions This review provides researchers with an organised toolkit of instruments, dimensions and an accompanying glossary. The striking variability between instruments supports the need to pay close attention to what is being assessed under the umbrella of ‘well-being’ measurement. PMID:27388349

Utility-Based Instruments for People with Dementia: A Systematic Review and Meta-Regression Analysis.

PubMed

Li, Li; Nguyen, Kim-Huong; Comans, Tracy; Scuffham, Paul

2018-04-01

Several utility-based instruments have been applied in cost-utility analysis to assess health state values for people with dementia. Nevertheless, concerns and uncertainty regarding their performance for people with dementia have been raised. To assess the performance of available utility-based instruments for people with dementia by comparing their psychometric properties and to explore factors that cause variations in the reported health state values generated from those instruments by conducting meta-regression analyses. A literature search was conducted and psychometric properties were synthesized to demonstrate the overall performance of each instrument. When available, health state values and variables such as the type of instrument and cognitive impairment levels were extracted from each article. A meta-regression analysis was undertaken and available covariates were included in the models. A total of 64 studies providing preference-based values were identified and included. The EuroQol five-dimension questionnaire demonstrated the best combination of feasibility, reliability, and validity. Meta-regression analyses suggested that significant differences exist between instruments, type of respondents, and mode of administration and the variations in estimated utility values had influences on incremental quality-adjusted life-year calculation. This review finds that the EuroQol five-dimension questionnaire is the most valid utility-based instrument for people with dementia, but should be replaced by others under certain circumstances. Although no utility estimates were reported in the article, the meta-regression analyses that examined variations in utility estimates produced by different instruments impact on cost-utility analysis, potentially altering the decision-making process in some circumstances. Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Phonation Quotient in Women: A Measure of Vocal Efficiency Using Three Aerodynamic Instruments.

PubMed

Joshi, Ashwini; Watts, Christopher R

2017-03-01

The purpose of this study was to examine measures of vital capacity and phonation quotient across three age groups in women using three different aerodynamic instruments representing low-tech and high-tech options. This study has a prospective, repeated measures design. Fifteen women in each age group of 25-39 years, 40-59 years, and 60-79 years were assessed using maximum phonation time and vital capacity obtained from three aerodynamic instruments: a handheld analog windmill type spirometer, a handheld digital spirometer, and the Phonatory Aerodynamic System (PAS), Model 6600. Phonation quotient was calculated using vital capacity from each instrument. Analyses of variance were performed to test for main effects of the instruments and age on vital capacity and derived phonation quotient. Pearson product moment correlation was performed to assess measurement reliability (parallel forms) between the instruments. Regression equations, scatterplots, and coefficients of determination were also calculated. Statistically significant differences were found in vital capacity measures for the digital spirometer compared with the windmill-type spirometer and PAS across age groups. Strong positive correlations were present between all three instruments for both vital capacity and derived phonation quotient measurements. Measurement precision for the digital spirometer was lower than the windmill spirometer compared with the PAS. However, all three instruments had strong measurement reliability. Additionally, age did not have an effect on the measurement across instruments. These results are consistent with previous literature reporting data from male speakers and support the use of low-tech options for measurement of basic aerodynamic variables associated with voice production. Copyright © 2017 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Impact of Financial Incentives for Prenatal Care on Birth Outcomes and Spending

PubMed Central

Rosenthal, Meredith B; Li, Zhonghe; Robertson, Audra D; Milstein, Arnold

2009-01-01

Objective To evaluate the impact of offering US$100 each to patients and their obstetricians or midwives for timely and comprehensive prenatal care on low birth weight, neonatal intensive care admissions, and total pediatric health care spending in the first year of life. Data Sources/Study Setting Claims and enrollment profiles of the predominantly low-income and Hispanic participants of a union-sponsored, health insurance plan from 1998 to 2001. Study Design Panel data analysis of outcomes and spending for participants and nonparticipants using instrumental variables to account for selection bias. Data Collection/Abstraction Methods Data provided were analyzed using t-tests and chi-squared tests to compare maternal characteristics and birth outcomes for incentive program participants and nonparticipants, with and without instrumental variables to address selection bias. Adjusted variables were analyzed using logistic regression models. Principle Findings Participation in the incentive program was significantly associated with lower odds of neonatal intensive care unit admission (0.45; 95 percent CI, 0.23–0.88) and spending in the first year of life (estimated elasticity of −0.07; 95 percent CI, −0.12 to −0.01), but not low birth weight (0.53; 95 percent CI, 0.23–1.18). Conclusion The use of patient and physician incentives may be an effective mechanism for improving use of recommended prenatal care and associated outcomes, particularly among low-income women. PMID:19619248

The effects of competition on premiums: using United Healthcare's 2015 entry into Affordable Care Act's marketplaces as an instrumental variable.

PubMed

Agirdas, Cagdas; Krebs, Robert J; Yano, Masato

2018-01-08

One goal of the Affordable Care Act is to increase insurance coverage by improving competition and lowering premiums. To facilitate this goal, the federal government enacted online marketplaces in the 395 rating areas spanning 34 states that chose not to establish their own state-run marketplaces. Few multivariate regression studies analyzing the effects of competition on premiums suffer from endogeneity, due to simultaneity and omitted variable biases. However, United Healthcare's decision to enter these marketplaces in 2015 provides the researcher with an opportunity to address this endogeneity problem. Exploiting the variation caused by United Healthcare's entry decision as an instrument for competition, we study the impact of competition on premiums during the first 2 years of these marketplaces. Combining panel data from five different sources and controlling for 12 variables, we find that one more insurer in a rating area leads to a 6.97% reduction in the second-lowest-priced silver plan premium, which is larger than the estimated effects in existing literature. Furthermore, we run a threshold analysis and find that competition's effects on premiums become statistically insignificant if there are four or more insurers in a rating area. These findings are robust to alternative measures of premiums, inclusion of a non-linear term in the regression models and a county-level analysis.

Surface Meteorological Station - Astoria, OR (AST) - Raw Data

DOE Data Explorer

Gottas, Daniel

2017-10-23

A variety of instruments are used to measure various quantities related to meteorology, precipitation, and radiation near the Earth’s surface. Typically, a standard suite of instruments is deployed to monitor meteorological state variables.

Surface Meteorological Station - ESRL Short Tower, Bonneville - Raw Data

DOE Data Explorer

McCaffrey, Katherine

2017-10-23

A diversity of instruments are used to measure various quantities related to meteorology and precipitation near the Earth’s surface. Typically, a standard suite of instruments is deployed to monitor meteorological state variables.

Surface Meteorological Station - ESRL Short Tower, Condon - Reviewed Data

DOE Data Explorer

McCaffrey, Katherine

2017-10-23

A diversity of instruments are used to measure various quantities related to meteorology, precipitation, and radiation near the Earth’s surface. Typically, a standard suite of instruments is deployed to monitor meteorological state variables.

Surface Meteorological Station - ESRL Short Tower, Troutdale - Reviewed Data

DOE Data Explorer

Gottas, Daniel

2017-12-11

A diversity of instruments are used to measure various quantities related to meteorology, precipitation, and radiation near the Earth’s surface. Typically, a standard suite of instruments is deployed to monitor meteorological state variables.

Surface Meteorological Station - ESRL Short Tower, Prineville - Raw Data

DOE Data Explorer

McCaffrey, Katherine

2017-10-23

A diversity of instruments are used to measure various quantities related to meteorology, precipitation, and radiation near the Earth’s surface. Typically, a standard suite of instruments is deployed to monitor meteorological state variables.

Surface Meteorological Station - ESRL Short Tower, Troutdale - Raw Data

DOE Data Explorer

Gottas, Daniel

2017-12-11

A diversity of instruments are used to measure various quantities related to meteorology, precipitation, and radiation near the Earth’s surface. Typically, a standard suite of instruments is deployed to monitor meteorological state variables.

Surface Meteorological Station - ESRL Short Tower, Prineville - Reviewed Data

DOE Data Explorer

McCaffrey, Katherine

2017-10-23

A diversity of instruments are used to measure various quantities related to meteorology, precipitation, and radiation near the Earth’s surface. Typically, a standard suite of instruments is deployed to monitor meteorological state variables.

Surface Meteorological Station - ESRL Short Tower, Bonneville - Reviewed Data

DOE Data Explorer

McCaffrey, Katherine

2017-10-23

A diversity of instruments are used to measure various quantities related to meteorology and precipitation near the Earth’s surface. Typically, a standard suite of instruments is deployed to monitor meteorological state variables.

Surface Meteorological Station - North Bend, OR (OTH) - Raw Data

DOE Data Explorer

Gottas, Daniel

2017-10-23

A variety of instruments are used to measure various quantities related to meteorology, precipitation, and radiation near the Earth’s surface. Typically, a standard suite of instruments is deployed to monitor meteorological state variables.

Surface Meteorological Station - ESRL Short Tower, Condon - Raw Data

DOE Data Explorer

McCaffrey, Katherine

2017-10-23

A diversity of instruments are used to measure various quantities related to meteorology, precipitation, and radiation near the Earth’s surface. Typically, a standard suite of instruments is deployed to monitor meteorological state variables.

Percentage Energy from Fat Screener: Overview

Cancer.gov

A short assessment instrument to estimate an individual's usual intake of percentage energy from fat. The foods asked about on the instrument were selected because they were the most important predictors of variability in percentage energy.

Surface Meteorological Station - Forks, WA (FKS) - Raw Data

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

Gottas, Daniel

A variety of instruments are used to measure various quantities related to meteorology, precipitation, and radiation near the Earth’s surface. Typically, a standard suite of instruments is deployed to monitor meteorological state variables.

Surface Meteorological Station - Forks, WA (FKS) - Reviewed Data

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

Gottas, Daniel

A variety of instruments are used to measure various quantities related to meteorology, precipitation, and radiation near the Earth’s surface. Typically, a standard suite of instruments is deployed to monitor meteorological state variables.

A Spanish-language patient safety questionnaire to measure medical and nursing students' attitudes and knowledge.

PubMed

Mira, José J; Navarro, Isabel M; Guilabert, Mercedes; Poblete, Rodrigo; Franco, Astolfo L; Jiménez, Pilar; Aquino, Margarita; Fernández-Trujillo, Francisco J; Lorenzo, Susana; Vitaller, Julián; de Valle, Yohana Díaz; Aibar, Carlos; Aranaz, Jesús M; De Pedro, José A

2015-08-01

To design and validate a questionnaire for assessing attitudes and knowledge about patient safety using a sample of medical and nursing students undergoing clinical training in Spain and four countries in Latin America. In this cross-sectional study, a literature review was carried out and total of 786 medical and nursing students were surveyed at eight universities from five countries (Chile, Colombia, El Salvador, Guatemala, and Spain) to develop and refine a Spanish-language questionnaire on knowledge and attitudes about patient safety. The scope of the questionnaire was based on five dimensions (factors) presented in studies related to patient safety culture found in PubMed and Scopus. Based on the five factors, 25 reactive items were developed. Composite reliability indexes and Cronbach's alpha statistics were estimated for each factor, and confirmatory factor analysis was conducted to assess validity. After a pilot test, the questionnaire was refined using confirmatory models, maximum-likelihood estimation, and the variance-covariance matrix (as input). Multiple linear regression models were used to confirm external validity, considering variables related to patient safety culture as dependent variables and the five factors as independent variables. The final instrument was a structured five-point Likert self-administered survey (the "Latino Student Patient Safety Questionnaire") consisting of 21 items grouped into five factors. Compound reliability indexes (Cronbach's alpha statistic) calculated for the five factors were about 0.7 or higher. The results of the multiple linear regression analyses indicated good model fit (goodness-of-fit index: 0.9). Item-total correlations were higher than 0.3 in all cases. The convergent-discriminant validity was adequate. The questionnaire designed and validated in this study assesses nursing and medical students' attitudes and knowledge about patient safety. This instrument could be used to indirectly evaluate whether or not students in health disciplines are acquiring and thus likely to put into practice the professional skills currently considered most appropriate for patient safety.

Cisplatin and Etoposide Versus Carboplatin and Paclitaxel With Concurrent Radiotherapy for Stage III Non–Small-Cell Lung Cancer: An Analysis of Veterans Health Administration Data

PubMed Central

Santana-Davila, Rafael; Devisetty, Kiran; Szabo, Aniko; Sparapani, Rodney; Arce-Lara, Carlos; Gore, Elizabeth M.; Moran, Amy; Williams, Christina D.; Kelley, Michael J.; Whittle, Jeffrey

2015-01-01

Purpose The optimal chemotherapy regimen to use with radiotherapy in stage III non–small-cell lung cancer is unknown. Here, we compare the outcome of patents treated within the Veterans Health Administration with either etoposide-cisplatin (EP) or carboplatin-paclitaxel (CP). Methods We identified patients treated with EP and CP with concurrent radiotherapy from 2001 to 2010. Survival rates were compared using Cox proportional hazards regression models with adjustments for confounding provided by propensity score methods and an instrumental variables analysis. Comorbidities and treatment complications were identified through administrative data. Results A total of 1,842 patients were included; EP was used in 27% (n = 499). Treatment with EP was not associated with a survival advantage in a Cox proportional hazards model (hazard ratio [HR], 0.97; 95% CI, 0.85 to 1.10), a propensity score matched cohort (HR, 1.07; 95% CI, 0.91 to 1.24), or a propensity score adjusted model (HR, 0.97; 95% CI, 0.85 to 1.10). In an instrumental variables analysis, there was no survival advantage for patients treated in centers where EP was used more than 50% of the time as compared with centers where EP was used in less than 10% of the patients (HR, 1.07; 95% CI, 0.90 to 1.26). Patients treated with EP, compared with patients treated with CP, had more hospitalizations (2.4 v 1.7 hospitalizations, respectively; P < .001), outpatient visits (17.6 v 12.6 visits, respectively; P < .001), infectious complications (47.3% v 39.4%, respectively; P = .0022), acute kidney disease/dehydration (30.5% v 21.2%, respectively; P < .001), and mucositis/esophagitis (18.6% v 14.4%, respectively; P = .0246). Conclusion After accounting for prognostic variables, patients treated with EP versus CP had similar overall survival, but EP was associated with increased morbidity. PMID:25422491

Genetic instrumental variable regression: Explaining socioeconomic and health outcomes in nonexperimental data

PubMed Central

DiPrete, Thomas A.; Burik, Casper A. P.; Koellinger, Philipp D.

2018-01-01

Identifying causal effects in nonexperimental data is an enduring challenge. One proposed solution that recently gained popularity is the idea to use genes as instrumental variables [i.e., Mendelian randomization (MR)]. However, this approach is problematic because many variables of interest are genetically correlated, which implies the possibility that many genes could affect both the exposure and the outcome directly or via unobserved confounding factors. Thus, pleiotropic effects of genes are themselves a source of bias in nonexperimental data that would also undermine the ability of MR to correct for endogeneity bias from nongenetic sources. Here, we propose an alternative approach, genetic instrumental variable (GIV) regression, that provides estimates for the effect of an exposure on an outcome in the presence of pleiotropy. As a valuable byproduct, GIV regression also provides accurate estimates of the chip heritability of the outcome variable. GIV regression uses polygenic scores (PGSs) for the outcome of interest which can be constructed from genome-wide association study (GWAS) results. By splitting the GWAS sample for the outcome into nonoverlapping subsamples, we obtain multiple indicators of the outcome PGSs that can be used as instruments for each other and, in combination with other methods such as sibling fixed effects, can address endogeneity bias from both pleiotropy and the environment. In two empirical applications, we demonstrate that our approach produces reasonable estimates of the chip heritability of educational attainment (EA) and show that standard regression and MR provide upwardly biased estimates of the effect of body height on EA. PMID:29686100

Genetic instrumental variable regression: Explaining socioeconomic and health outcomes in nonexperimental data.

PubMed

DiPrete, Thomas A; Burik, Casper A P; Koellinger, Philipp D

2018-05-29

Identifying causal effects in nonexperimental data is an enduring challenge. One proposed solution that recently gained popularity is the idea to use genes as instrumental variables [i.e., Mendelian randomization (MR)]. However, this approach is problematic because many variables of interest are genetically correlated, which implies the possibility that many genes could affect both the exposure and the outcome directly or via unobserved confounding factors. Thus, pleiotropic effects of genes are themselves a source of bias in nonexperimental data that would also undermine the ability of MR to correct for endogeneity bias from nongenetic sources. Here, we propose an alternative approach, genetic instrumental variable (GIV) regression, that provides estimates for the effect of an exposure on an outcome in the presence of pleiotropy. As a valuable byproduct, GIV regression also provides accurate estimates of the chip heritability of the outcome variable. GIV regression uses polygenic scores (PGSs) for the outcome of interest which can be constructed from genome-wide association study (GWAS) results. By splitting the GWAS sample for the outcome into nonoverlapping subsamples, we obtain multiple indicators of the outcome PGSs that can be used as instruments for each other and, in combination with other methods such as sibling fixed effects, can address endogeneity bias from both pleiotropy and the environment. In two empirical applications, we demonstrate that our approach produces reasonable estimates of the chip heritability of educational attainment (EA) and show that standard regression and MR provide upwardly biased estimates of the effect of body height on EA. Copyright © 2018 the Author(s). Published by PNAS.

The Role of Initial Attack and Performer Expertise on Instrument Identification

ERIC Educational Resources Information Center

Cassidy, Jane W.; Schlegel, Amanda L.

2016-01-01

The purpose of this study was to examine the role initial attack and expertise play in the identification of instrumental tones. A stimulus CD was made of 32 excerpts of instrumental tones. Sixteen possible combinations of the variables of initial attack (present or absent), expertise (beginner versus professional), and timbre (flute, clarinet,…

Is it feasible to estimate radiosonde biases from interlaced measurements?

NASA Astrophysics Data System (ADS)

Kremser, Stefanie; Tradowsky, Jordis S.; Rust, Henning W.; Bodeker, Greg E.

2018-05-01

Upper-air measurements of essential climate variables (ECVs), such as temperature, are crucial for climate monitoring and climate change detection. Because of the internal variability of the climate system, many decades of measurements are typically required to robustly detect any trend in the climate data record. It is imperative for the records to be temporally homogeneous over many decades to confidently estimate any trend. Historically, records of upper-air measurements were primarily made for short-term weather forecasts and as such are seldom suitable for studying long-term climate change as they lack the required continuity and homogeneity. Recognizing this, the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) has been established to provide reference-quality measurements of climate variables, such as temperature, pressure, and humidity, together with well-characterized and traceable estimates of the measurement uncertainty. To ensure that GRUAN data products are suitable to detect climate change, a scientifically robust instrument replacement strategy must always be adopted whenever there is a change in instrumentation. By fully characterizing any systematic differences between the old and new measurement system a temporally homogeneous data series can be created. One strategy is to operate both the old and new instruments in tandem for some overlap period to characterize any inter-instrument biases. However, this strategy can be prohibitively expensive at measurement sites operated by national weather services or research institutes. An alternative strategy that has been proposed is to alternate between the old and new instruments, so-called interlacing, and then statistically derive the systematic biases between the two instruments. Here we investigate the feasibility of such an approach specifically for radiosondes, i.e. flying the old and new instruments on alternating days. Synthetic data sets are used to explore the applicability of this statistical approach to radiosonde change management.

Decoupling Solar Variability and Instrument Trends Using the Multiple Same-Irradiance-Level (MuSIL) Analysis Technique

NASA Astrophysics Data System (ADS)

Woods, Thomas N.; Eparvier, Francis G.; Harder, Jerald; Snow, Martin

2018-05-01

The solar spectral irradiance (SSI) dataset is a key record for studying and understanding the energetics and radiation balance in Earth's environment. Understanding the long-term variations of the SSI over timescales of the 11-year solar activity cycle and longer is critical for many Sun-Earth research topics. Satellite measurements of the SSI have been made since the 1970s, most of them in the ultraviolet, but recently also in the visible and near-infrared. A limiting factor for the accuracy of previous solar variability results is the uncertainties for the instrument degradation corrections, which need fairly large corrections relative to the amount of solar cycle variability at some wavelengths. The primary objective of this investigation has been to separate out solar cycle variability and any residual uncorrected instrumental trends in the SSI measurements from the Solar Radiation and Climate Experiment (SORCE) mission and the Thermosphere, Mesosphere, Ionosphere, Energetic, and Dynamics (TIMED) mission. A new technique called the Multiple Same-Irradiance-Level (MuSIL) analysis has been developed, which examines an SSI time series at different levels of solar activity to provide long-term trends in an SSI record, and the most common result is a downward trend that most likely stems from uncorrected instrument degradation. This technique has been applied to each wavelength in the SSI records from SORCE (2003 - present) and TIMED (2002 - present) to provide new solar cycle variability results between 27 nm and 1600 nm with a resolution of about 1 nm at most wavelengths. This technique, which was validated with the highly accurate total solar irradiance (TSI) record, has an estimated relative uncertainty of about 5% of the measured solar cycle variability. The MuSIL results are further validated with the comparison of the new solar cycle variability results from different solar cycles.

Effects of thermal deformation on optical instruments for space application

NASA Astrophysics Data System (ADS)

Segato, E.; Da Deppo, V.; Debei, S.; Cremonese, G.

2017-11-01

Optical instruments for space missions work in hostile environment, it's thus necessary to accurately study the effects of ambient parameters variations on the equipment. In particular optical instruments are very sensitive to ambient conditions, especially temperature. This variable can cause dilatations and misalignments of the optical elements, and can also lead to rise of dangerous stresses in the optics. Their displacements and the deformations degrade the quality of the sampled images. In this work a method for studying the effects of the temperature variations on the performance of imaging instrument is presented. The optics and their mountings are modeled and processed by a thermo-mechanical Finite Element Model (FEM) analysis, then the output data, which describe the deformations of the optical element surfaces, are elaborated using an ad hoc MATLAB routine: a non-linear least square optimization algorithm is adopted to determine the surface equations (plane, spherical, nth polynomial) which best fit the data. The obtained mathematical surface representations are then directly imported into ZEMAX for sequential raytracing analysis. The results are the variations of the Spot Diagrams, of the MTF curves and of the Diffraction Ensquared Energy due to simulated thermal loads. This method has been successfully applied to the Stereo Camera for the BepiColombo mission reproducing expected operative conditions. The results help to design and compare different optical housing systems for a feasible solution and show that it is preferable to use kinematic constraints on prisms and lenses to minimize the variation of the optical performance of the Stereo Camera.

Factors Influencing Physical Activity Behavior among Iranian Women with Type 2 Diabetes Using the Extended Theory of Reasoned Action.

PubMed

Didarloo, Alireza; Shojaeizadeh, Davoud; Ardebili, Hassan Eftekhar; Niknami, Shamsaddin; Hajizadeh, Ebrahim; Alizadeh, Mohammad

2011-10-01

Findings of most studies indicate that the only way to control diabetes and prevent its debilitating effects is through the continuous performance of self-care behaviors. Physical activity is a non-pharmacological method of diabetes treatment and because of its positive effects on diabetic patients, it is being increasingly considered by researchers and practitioners. This study aimed at determining factors influencing physical activity among diabetic women in Iran, using the extended theory of reasoned action in Iran. A sample of 352 women with type 2 diabetes, referring to a Diabetes Clinic in Khoy, Iran, participated in the study. Appropriate instruments were designed to measure the desired variables (knowledge of diabetes, personal beliefs, subjective norms, perceived self-efficacy, behavioral intention and physical activity behavior). The reliability and validity of the instruments were examined and approved. Statistical analyses of the study were conducted by inferential statistical techniques (independent t-test, correlations and regressions) using the SPSS package. The findings of this investigation indicated that among the constructs of the model, self efficacy was the strongest predictor of intentions among women with type 2 diabetes and both directly and indirectly affected physical activity. In addition to self efficacy, diabetic patients' physical activity also was influenced by other variables of the model and sociodemographic factors. Our findings suggest that the high ability of the theory of reasoned action extended by self-efficacy in forecasting and explaining physical activity can be a base for educational intervention. Educational interventions based on the proposed model are necessary for improving diabetics' physical activity behavior and controlling disease.

Online Impact Prioritization of Essential Climate Variables on Climate Change

NASA Astrophysics Data System (ADS)

Forsythe-Newell, S. P.; Barkstrom, B. B.; Roberts, K. P.

2007-12-01

The National Oceanic & Atmospheric Administration (NOAA)'s NCDC Scientific Data Stewardship (SDS) Team has developed an online prototype that is capable of displaying the "big picture" perspective of all Essential Climate Variable (ECV) impacts on society and value to the IPCC. This prototype ECV-Model provides the ability to visualize global ECV information with options to drill down in great detail. It offers a quantifiable prioritization of ECV impacts that potentially may significantly enhance collaboration with respect to dealing effectively with climate change. The ECV-Model prototype assures anonymity and provides an online input mechanism for subject matter experts and decision makers to access, review and submit: (1) ranking of ECV"s, (2) new ECV's and associated impact categories and (3) feedback about ECV"s, satellites, etc. Input and feedback are vetted by experts before changes or additions are implemented online. The SDS prototype also provides an intuitive one-stop web site that displays past, current and planned launches of satellites; and general as well as detailed information in conjunction with imagery. NCDC's version 1.0 release will be available to the public and provide an easy "at-a-glance" interface to rapidly identify gaps and overlaps of satellites and associated instruments monitoring climate change ECV's. The SDS version 1.1 will enhance depiction of gaps and overlaps with instruments associated with In-Situ and Satellites related to ECVs. NOAA's SDS model empowers decision makers and the scientific community to rapidly identify weaknesses and strengths in monitoring climate change ECV's and potentially significantly enhance collaboration.

Longitudinal Differences in the Low-latitude Ionosphere and in the Ionospheric Variability

NASA Astrophysics Data System (ADS)

Goncharenko, L. P.; Zhang, S.; Liu, H.; Tsugawa, T.; Batista, I. S.; Reinisch, B. W.

2017-12-01

Analysis of longitudinal differences in ionospheric parameters can illuminate variety of mechanisms responsible for ionospheric variability. In this study, we aim to 1) quantitatively describe major features of longitudinal differences in peak electron density in the low-latitude ionosphere; 2) examine differences in ionospheric variability at different longitude sectors, and 3) illustrate longitudinal differences in ionospheric response to a large disturbance event, sudden stratospheric warming of 2016. We examine NmF2 observations by a network of ionosondes in the American (30-80W) and Asian (110-170E) longitudinal sectors. Selected instruments are located in the vicinity of EIA troughs (Jicamarca, Sao Luis, Guam, Kwajalein), northern and southern crests of EIA (Boa Vista, Tucuman, Cachoeira Paulista, Okinawa), and beyond EIA crests (Ramey, Yamagawa, Kokubunji). To examine main ionospheric features at each location, we use long-term datasets collected at each site to construct empirical models that describe variations in NmF2 as a function of local time, season, solar flux, and geomagnetic activity. This set of empirical models can be used to accurately describe background ionospheric behavior and serve as a set of observational benchmarks for global circulation models. It reveals, for example, higher NmF2 in the EIA trough in the Asian sector as compared to the American sector. Further, we quantitatively describe variability in NmF2 as a difference between local observations and local empirical model, and find that American sector's EIA trough has overall higher variability that maximizes for all local times during wintertime, while Asian sector trough variability does not change significantly with season. Additionally, local empirical models are used to isolate ionospheric features resulting from dynamical disturbances of different origin (e.g. geomagnetic storms, convective activity, sudden stratospheric warming events, etc.). We illustrate this approach with the case of sudden stratospheric warming of 2016.

Assessing variable rate nitrogen fertilizer strategies within an extensively instrument field site using the MicroBasin model

NASA Astrophysics Data System (ADS)

Ward, N. K.; Maureira, F.; Yourek, M. A.; Brooks, E. S.; Stockle, C. O.

2014-12-01

The current use of synthetic nitrogen fertilizers in agriculture has many negative environmental and economic costs, necessitating improved nitrogen management. In the highly heterogeneous landscape of the Palouse region in eastern Washington and northern Idaho, crop nitrogen needs vary widely within a field. Site-specific nitrogen management is a promising strategy to reduce excess nitrogen lost to the environment while maintaining current yields by matching crop needs with inputs. This study used in-situ hydrologic, nutrient, and crop yield data from a heavily instrumented field site in the high precipitation zone of the wheat-producing Palouse region to assess the performance of the MicroBasin model. MicroBasin is a high-resolution watershed-scale ecohydrologic model with nutrient cycling and cropping algorithms based on the CropSyst model. Detailed soil mapping conducted at the site was used to parameterize the model and the model outputs were evaluated with observed measurements. The calibrated MicroBasin model was then used to evaluate the impact of various nitrogen management strategies on crop yield and nitrate losses. The strategies include uniform application as well as delineating the field into multiple zones of varying nitrogen fertilizer rates to optimize nitrogen use efficiency. We present how coupled modeling and in-situ data sets can inform agricultural management and policy to encourage improved nitrogen management.

Overtone Mobility Spectrometry (Part 2): Theoretical Considerations of Resolving Power

PubMed Central

Valentine, Stephen J.; Stokes, Sarah T.; Kurulugama, Ruwan T.; Nachtigall, Fabiane M.; Clemmer, David E.

2009-01-01

The transport of ions through multiple drift regions is modeled in order to develop an equation that is useful for an understanding of the resolving power of an overtone mobility spectrometry (OMS) technique. It is found that resolving power is influenced by a number of experimental variables, including those that define ion mobility spectrometry (IMS) resolving power: drift field (E), drift region length (L), and buffer gas temperature (T). However, unlike IMS, the resolving power of OMS is also influenced by the number of drift regions (n), harmonic frequency value (m), and the phase number (ϕ) of the applied drift field. The OMS resolving power dependence upon the new OMS variables (n, m, and ϕ) scales differently than the square root dependence of the E, L, and T variables in IMS. The results provide insight about optimal instrumental design and operation. PMID:19230705

Investigation of remote sensing techniques of measuring soil moisture

NASA Technical Reports Server (NTRS)

Newton, R. W. (Principal Investigator); Blanchard, A. J.; Nieber, J. L.; Lascano, R.; Tsang, L.; Vanbavel, C. H. M.

1981-01-01

Major activities described include development and evaluation of theoretical models that describe both active and passive microwave sensing of soil moisture, the evaluation of these models for their applicability, the execution of a controlled field experiment during which passive microwave measurements were acquired to validate these models, and evaluation of previously acquired aircraft microwave measurements. The development of a root zone soil water and soil temperature profile model and the calibration and evaluation of gamma ray attenuation probes for measuring soil moisture profiles are considered. The analysis of spatial variability of soil information as related to remote sensing is discussed as well as the implementation of an instrumented field site for acquisition of soil moisture and meteorologic information for use in validating the soil water profile and soil temperature profile models.

8 years of Solar Spectral Irradiance Observations from the ISS with the SOLAR/SOLSPEC Instrument

NASA Astrophysics Data System (ADS)

Damé, L.; Bolsée, D.; Meftah, M.; Irbah, A.; Hauchecorne, A.; Bekki, S.; Pereira, N.; Cessateur, G.; Marchand, M.; Thiéblemont, R.; Foujols, T.

2016-12-01

Accurate measurements of Solar Spectral Irradiance (SSI) are of primary importance for a better understanding of solar physics and of the impact of solar variability on climate (via Earth's atmospheric photochemistry). The acquisition of a top of atmosphere reference solar spectrum and of its temporal and spectral variability during the unusual solar cycle 24 is of prime interest for these studies. These measurements are performed since April 2008 with the SOLSPEC spectro-radiometer from the far ultraviolet to the infrared (166 nm to 3088 nm). This instrument, developed under a fruitful LATMOS/BIRA-IASB collaboration, is part of the Solar Monitoring Observatory (SOLAR) payload, externally mounted on the Columbus module of the International Space Station (ISS). The SOLAR mission, with its actual 8 years duration, will cover almost the entire solar cycle 24. We present here the in-flight operations and performances of the SOLSPEC instrument, including the engineering corrections, calibrations and improved know-how procedure for aging corrections. Accordingly, a SSI reference spectrum from the UV to the NIR will be presented, together with its UV variability, as measured by SOLAR/SOLSPEC. Uncertainties on these measurements and comparisons with other instruments will be briefly discussed.

Instrumental colour of Iberian ham subcutaneous fat and lean (biceps femoris): Influence of crossbreeding and rearing system.

PubMed

Carrapiso, Ana I; García, Carmen

2005-10-01

The influence of crossbreeding (Iberian vs Iberian×Duroc 50% pigs) and rearing system (Montanera vs Pienso) on the instrumental colour of Iberian ham (subcutaneous fat and biceps femoris muscle) and the relationships to sensory appearance and chemical composition were researched by using a factorial design. In subcutaneous fat, a significant effect (p<0.05) of crossbreeding and rearing system was found: b* and chroma were larger in hams from Iberian pigs than from Iberian×Duroc (50%) pigs, and L*, a* and chroma were larger in Pienso hams than in Montanera hams. CIEL*a*b* variables of subcutaneous fat were closely related to subcutaneous fatty acid composition, the largest correlationships involving L* (L* and 18:0, 0.652, p<0.001; L* and 18:1, -0.616, p<0.001). Instrumental colour variables and sensory appearance were also correlated (L* and fat pinkness, -0.539, p<0.001). In lean (biceps femoris), instrumental colour data was not affected by crossbreeding and rearing system. CIEL*a*b* variables were not related to chemical composition (moisture, NaCl, intramuscular fat and pigment content), although they were correlated to sensory appearance (L* and marbling, 0.419, p=0.014).

Multivariate evaluation of the cutting performance of rotary instruments with electric and air-turbine handpieces.

PubMed

Funkenbusch, Paul D; Rotella, Mario; Chochlidakis, Konstantinos; Ercoli, Carlo

2016-10-01

Laboratory studies of tooth preparation often involve single values for all variables other than the one being tested. In contrast, in clinical settings, not all variables can be adequately controlled. For example, a new dental rotary cutting instrument may be tested in the laboratory by making a specific cut with a fixed force, but, in clinical practice, the instrument must make different cuts with individual dentists applying different forces. Therefore, the broad applicability of laboratory results to diverse clinical conditions is uncertain and the comparison of effects across studies difficult. The purpose of this in vitro study was to examine the effects of 9 process variables on the dental cutting of rotary cutting instruments used with an electric handpiece and compare them with those of a previous study that used an air-turbine handpiece. The effects of 9 key process variables on the efficiency of a simulated dental cutting operation were measured. A fractional factorial experiment was conducted by using an electric handpiece in a computer-controlled, dedicated testing apparatus to simulate dental cutting procedures with Macor blocks as the cutting substrate. Analysis of variance (ANOVA) was used to assess the statistical significance (α=.05). Four variables (targeted applied load, cut length, diamond grit size, and cut type) consistently produced large, statistically significant effects, whereas 5 variables (rotation per minute, number of cooling ports, rotary cutting instrument diameter, disposability, and water flow rate) produced relatively small, statistically insignificant effects. These results are generally similar to those previously found for an air-turbine handpiece. Regardless of whether an electric or air-turbine handpiece was used, the control exerted by the dentist, simulated in this study by targeting a specific level of applied force, was the single most important factor affecting cutting efficiency. Cutting efficiency was also significantly affected by factors simulating patient/clinical circumstances and hardware choices. These results highlight the greater importance of local clinical conditions (procedure, dentist) in understanding dental cutting as opposed to other hardware-related factors. Copyright © 2016 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

Performance evaluation of the microINR® point-of-care INR-testing system.

PubMed

Joubert, J; van Zyl, M C; Raubenheimer, J

2018-04-01

Point-of-care International Normalised Ratio (INR) testing is used frequently. We evaluated the microINR ® POC system for accuracy, precision and measurement repeatability, and investigated instrument and test chip variability and error rates. Venous blood INRs of 210 patients on warfarin were obtained with Thromborel ® S on the Sysmex CS-2100i ® analyser and compared with capillary blood microINR ® values. Precision was assessed using control materials. Measurement repeatability was calculated on 51 duplicate finger-prick INRs. Triplicate finger-prick INRs using three different instruments (30 patients) and three different test chip lots (29 patients) were used to evaluate instrument and test chip variability. Linear regression analysis of microINR ® and Sysmex CS2100i ® values showed a correlation coefficient of 0.96 (P < .0001) and a positive proportional bias of 4.4%. Dosage concordance was 93.8% and clinical agreement 95.7%. All acceptance criteria based on ISO standard 17593:2007 system accuracy requirements were met. Control material coefficients of variation (CV) varied from 6.2% to 16.7%. The capillary blood measurement repeatability CV was 7.5%. No significant instrument (P = .93) or test chip (P = .81) variability was found, and the error rate was low (2.8%). The microINR ® instrument is accurate and precise for monitoring warfarin therapy. © 2017 John Wiley & Sons Ltd.

Hand-held instrument should relieve hematoma pressure

NASA Technical Reports Server (NTRS)

Raggio, L. J.; Robertson, T. L.

1967-01-01

Portable instrument relieves hematomas beneath fingernails and toenails without surgery. This device simplifies the operative procedure with an instant variable heating tip, adjustable depth settings and interchangeable tip sizes for cauterizing small areas and relieving pressurized clots.

Surface Meteorological Station - ESRL Short Tower, Wasco Airport - Raw Data

DOE Data Explorer

Gottas, Daniel

2017-12-11

A diversity of instruments are used to measure various quantities related to meteorology, precipitation, and radiation near the Earth’s surface. Typically, a standard suite of instruments is deployed to monitor meteorological state variables.

Surface Meteorological Station - ESRL Short Tower, Wasco Airport - Reviewed Data

DOE Data Explorer

Gottas, Daniel

2017-12-11

A diversity of instruments are used to measure various quantities related to meteorology, precipitation, and radiation near the Earth’s surface. Typically, a standard suite of instruments is deployed to monitor meteorological state variables.

How Financial Literacy Affects Household Wealth Accumulation.

PubMed

Behrman, Jere R; Mitchell, Olivia S; Soo, Cindy K; Bravo, David

2012-05-01

This study isolates the causal effects of financial literacy and schooling on wealth accumulation using a new household dataset and an instrumental variables (IV) approach. Financial literacy and schooling attainment are both strongly positively associated with wealth outcomes in linear regression models, whereas the IV estimates reveal even more potent effects of financial literacy. They also indicate that the schooling effect only becomes positive when interacted with financial literacy. Estimated impacts are substantial enough to imply that investments in financial literacy could have large wealth payoffs.

How Financial Literacy Affects Household Wealth Accumulation

PubMed Central

Behrman, Jere R.; Mitchell, Olivia S.; Soo, Cindy K.; Bravo, David

2012-01-01

This study isolates the causal effects of financial literacy and schooling on wealth accumulation using a new household dataset and an instrumental variables (IV) approach. Financial literacy and schooling attainment are both strongly positively associated with wealth outcomes in linear regression models, whereas the IV estimates reveal even more potent effects of financial literacy. They also indicate that the schooling effect only becomes positive when interacted with financial literacy. Estimated impacts are substantial enough to imply that investments in financial literacy could have large wealth payoffs. PMID:23355747

Speckle temporal stability in XAO coronagraphic images. II. Refine model for quasi-static speckle temporal evolution for VLT/SPHERE

NASA Astrophysics Data System (ADS)

Martinez, P.; Kasper, M.; Costille, A.; Sauvage, J. F.; Dohlen, K.; Puget, P.; Beuzit, J. L.

2013-06-01

Context. Observing sequences have shown that the major noise source limitation in high-contrast imaging is the presence of quasi-static speckles. The timescale on which quasi-static speckles evolve is determined by various factors, mechanical or thermal deformations, among others. Aims: Understanding these time-variable instrumental speckles and, especially, their interaction with other aberrations, referred to as the pinning effect, is paramount for the search for faint stellar companions. The temporal evolution of quasi-static speckles is, for instance, required for quantifying the gain expected when using angular differential imaging (ADI) and to determining the interval on which speckle nulling techniques must be carried out. Methods: Following an early analysis of a time series of adaptively corrected, coronagraphic images obtained in a laboratory condition with the high-order test bench (HOT) at ESO Headquarters, we confirm our results with new measurements carried out with the SPHERE instrument during its final test phase in Europe. The analysis of the residual speckle pattern in both direct and differential coronagraphic images enables the characterization of the temporal stability of quasi-static speckles. Data were obtained in a thermally actively controlled environment reproducing realistic conditions encountered at the telescope. Results: The temporal evolution of the quasi-static wavefront error exhibits a linear power law, which can be used to model quasi-static speckle evolution in the context of forthcoming high-contrast imaging instruments, with implications for instrumentation (design, observing strategies, data reduction). Such a model can be used for instance to derive the timescale on which non-common path aberrations must be sensed and corrected. We found in our data that quasi-static wavefront error increases with ~0.7 Å per minute.

NASA's MODIS/VIIRS Land Surface Temperature and Emissivity Products: Asssessment of Accuracy, Continuity and Science Uses

NASA Astrophysics Data System (ADS)

Hulley, G. C.; Malakar, N.; Islam, T.

2017-12-01

Land Surface Temperature and Emissivity (LST&E) are an important Earth System Data Record (ESDR) and Environmental Climate Variable (ECV) defined by NASA and GCOS respectively. LST&E data are key variables used in land cover/land use change studies, in surface energy balance and atmospheric water vapor retrieval models and retrievals, and in climate research. LST&E products are currently produced on a routine basis using data from the MODIS instruments on the NASA EOS platforms and by the VIIRS instrument on the Suomi-NPP platform that serves as a bridge between NASA EOS and the next-generation JPSS platforms. Two new NASA LST&E products for MODIS (MxD21) and VIIRS (VNP21) are being produced during 2017 using a new approach that addresses discrepancies in accuracy and consistency between the current suite of split-window based LST products. The new approach uses a Temperature Emissivity Separation (TES) algorithm, originally developed for the ASTER instrument, to physically retrieve both LST and spectral emissivity consistently for both sensors with high accuracy and well defined uncertainties. This study provides a rigorous assessment of accuracy of the MxD21/VNP21 products using temperature- and radiance-based validation strategies and demonstrates continuity between the products using collocated matchups over CONUS. We will further demonstrate potential science use of the new products with studies related to heat waves, monitoring snow melt dynamics, and land cover/land use change.

An assessment of the stray light in 25 years of Dobson total ozone data at Athens, Greece

NASA Astrophysics Data System (ADS)

Christodoulakis, J.; Varotsos, C.; Cracknell, A. P.; Tzanis, C.; Neofytos, A.

2015-07-01

In this study, we investigated the susceptibility of the Dobson spectrophotometer No. 118 to stray light interference. In this regard, a series of total ozone content measurements were carried out in Athens, Greece for air-mass values (μ) extending up to μ = 5. The monochromatic-heterochromatic stray light derived by Basher's model was used in order to evaluate the specific instrumental parameters which determine if this instrument suffers from this problem or not. The results obtained indicate that the measurements made by the Dobson instrument of the Athens station for air mass values up to 2.5, underestimates the total ozone content by 3.5 DU in average, or about 1 % of the station's mean total ozone content (TOC). The comparison of the values of the same parameters measured 15 years ago with the present ones indicates the good maintenance of the Dobson spectrophotometer No. 118. This fact is of crucial importance because the variability of the daily total ozone observations collected by the Athens Dobson Station since 1989 has proved to be representative to the variability of the mean total ozone observed over the whole mid-latitude zone of the Northern Hemisphere. This stresses the point that the Athens total ozone station, being the unique Dobson station in south-eastern Europe, may be assumed as a ground truth station for the reliable conversion of the satellite radiance observations to total ozone measurements.

Poverty and Child Development: A Longitudinal Study of the Impact of the Earned Income Tax Credit

PubMed Central

Hamad, Rita; Rehkopf, David H.

2016-01-01

Although adverse socioeconomic conditions are correlated with worse child health and development, the effects of poverty-alleviation policies are less understood. We examined the associations of the Earned Income Tax Credit (EITC) on child development and used an instrumental variable approach to estimate the potential impacts of income. We used data from the US National Longitudinal Survey of Youth (n = 8,186) during 1986–2000 to examine effects on the Behavioral Problems Index (BPI) and Home Observation Measurement of the Environment inventory (HOME) scores. We conducted 2 analyses. In the first, we used multivariate linear regressions with child-level fixed effects to examine the association of EITC payment size with BPI and HOME scores; in the second, we used EITC payment size as an instrument to estimate the associations of income with BPI and HOME scores. In linear regression models, higher EITC payments were associated with improved short-term BPI scores (per $1,000, β = −0.57; P = 0.04). In instrumental variable analyses, higher income was associated with improved short-term BPI scores (per $1,000, β = −0.47; P = 0.01) and medium-term HOME scores (per $1,000, β = 0.64; P = 0.02). Our results suggest that both EITC benefits and higher income are associated with modest but meaningful improvements in child development. These findings provide valuable information for health researchers and policymakers for improving child health and development. PMID:27056961

Instrument Suite for Vertical Characterization of the Ionosphere-Thermosphere System

NASA Technical Reports Server (NTRS)

Herrero, Federico; Jones, Hollis; Finne, Theodore; Nicholas, Andrew

2012-01-01

A document describes a suite that provides four simultaneous ion and neutral-atom measurements as a function of altitude, with variable sensitivity for neutral atmospheric species. The variable sensitivity makes it possible to extend the measurements over the altitude range of 100 to more than 700 km. The four instruments in the suite are (1) a neutral wind-temperature spectrometer (WTS), (2) an ion-drift ion-temperature spectrometer (IDTS), (3) a neutral mass spectrometer (NMS), and (4) an ion mass spectrometer (IMS).

Spatio-temporal hierarchical modeling of rates and variability of Holocene sea-level changes in the western North Atlantic and the Caribbean

NASA Astrophysics Data System (ADS)

Ashe, E.; Kopp, R. E.; Khan, N.; Horton, B.; Engelhart, S. E.

2016-12-01

Sea level varies over of both space and time. Prior to the instrumental period, the sea-level record depends upon geological reconstructions that contain vertical and temporal uncertainty. Spatio-temporal statistical models enable the interpretation of RSL and rates of change as well as the reconstruction of the entire sea-level field from such noisy data. Hierarchical models explicitly distinguish between a process level, which characterizes the spatio-temporal field, and a data level, by which sparse proxy data and its noise is recorded. A hyperparameter level depicts prior expectations about the structure of variability in the spatio-temporal field. Spatio-temporal hierarchical models are amenable to several analysis approaches, with tradeoffs regarding computational efficiency and comprehensiveness of uncertainty characterization. A fully-Bayesian hierarchical model (BHM), which places prior probability distributions upon the hyperparameters, is more computationally intensive than an empirical hierarchical model (EHM), which uses point estimates of hyperparameters, derived from the data [1]. Here, we assess the sensitivity of posterior estimates of relative sea level (RSL) and rates to different statistical approaches by varying prior assumptions about the spatial and temporal structure of sea-level variability and applying multiple analytical approaches to Holocene sea-level proxies along the Atlantic coast of North American and the Caribbean [2]. References: 1. N Cressie, Wikle CK (2011) Statistics for spatio-temporal data (John Wiley & Sons). 2. Kahn N et al. (2016). Quaternary Science Reviews (in revision).

Modeling old-age wealth with endogenous early-life outcomes: The case of Mexico

PubMed Central

DeGraff, Deborah S.; Wong, Rebeca

2014-01-01

This paper contributes to the literature on the life course and aging by examining the association between early-life outcomes and late-life well being, using data from the Mexican Health and Aging Study. Empirical research in this area has been challenged by the potential endogeneity of the early-life outcomes of interest, an issue which most studies ignore or downplay. Our contribution takes two forms: (1) we examine in detail the potential importance of two key life-cycle outcomes, age at marriage (a measure of family formation) and years of educational attainment (a measure of human capital investment) for old-age wealth, and (2) we illustrate the empirical value of past context variables that could help model the association between early-life outcomes and late-life well being. Our illustrative approach, matching macro-level historical policy and census variables to individual records to use as instruments in modeling the endogeneity of early-life behaviors, yields a statistically identified two-stage model of old-age wealth with minimum bias. We use simulations to show that the results for the model of wealth in old age are meaningfully different when comparing the approach that accounts for endogeneity with an approach that assumes exogeneity of early-life outcomes. Furthermore, our results suggest that in the Mexican case, models which ignore the potential endogeneity of early-life outcomes are likely to under-estimate the effects of such variables on old-age wealth. PMID:25170434

CO2, energy and economy interactions: A multisectoral, dynamic, computable general equilibrium model for Korea

NASA Astrophysics Data System (ADS)

Kang, Yoonyoung

While vast resources have been invested in the development of computational models for cost-benefit analysis for the "whole world" or for the largest economies (e.g. United States, Japan, Germany), the remainder have been thrown together into one model for the "rest of the world." This study presents a multi-sectoral, dynamic, computable general equilibrium (CGE) model for Korea. This research evaluates the impacts of controlling COsb2 emissions using a multisectoral CGE model. This CGE economy-energy-environment model analyzes and quantifies the interactions between COsb2, energy and economy. This study examines interactions and influences of key environmental policy components: applied economic instruments, emission targets, and environmental tax revenue recycling methods. The most cost-effective economic instrument is the carbon tax. The economic effects discussed include impacts on main macroeconomic variables (in particular, economic growth), sectoral production, and the energy market. This study considers several aspects of various COsb2 control policies, such as the basic variables in the economy: capital stock and net foreign debt. The results indicate emissions might be stabilized in Korea at the expense of economic growth and with dramatic sectoral allocation effects. Carbon dioxide emissions stabilization could be achieved to the tune of a 600 trillion won loss over a 20 year period (1990-2010). The average annual real GDP would decrease by 2.10% over the simulation period compared to the 5.87% increase in the Business-as-Usual. This model satisfies an immediate need for a policy simulation model for Korea and provides the basic framework for similar economies. It is critical to keep the central economic question at the forefront of any discussion regarding environmental protection. How much will reform cost, and what does the economy stand to gain and lose? Without this model, the policy makers might resort to hesitation or even blind speculation. With the model, the policy makers gain the power of prediction. This model serves as a tool for constructing the most effective strategy for Korea.

Variable Stars in the Field of V729 Aql

NASA Astrophysics Data System (ADS)

Cagaš, P.

2017-04-01

Wide field instruments can be used to acquire light curves of tens or even hundreds of variable stars per night, which increases the probability of new discoveries of interesting variable stars and generally increases the efficiency of observations. At the same time, wide field instruments produce a large amount of data, which must be processed using advanced software. The traditional approach, typically used by amateur astronomers, requires an unacceptable amount of time needed to process each data set. New functionality, built into SIPS software package, can shorten the time needed to obtain light curves by several orders of magnitude. Also, newly introduced SILICUPS software is intended for post-processing of stored light curves. It can be used to visualize observations from many nights, to find variable star periods, evaluate types of variability, etc. This work provides an overview of tools used to process data from the large field of view around the variable star V729 Aql. and demonstrates the results.

Evaluating nursing administration instruments.

PubMed

Huber, D L; Maas, M; McCloskey, J; Scherb, C A; Goode, C J; Watson, C

2000-05-01

To identify and evaluate available measures that can be used to examine the effects of management innovations in five important areas: autonomy, conflict, job satisfaction, leadership, and organizational climate. Management interventions target the context in which care is delivered and through which evidence for practice diffuses. These innovations need to be evaluated for their effects on desired outcomes. However, busy nurses may not have the time to locate, evaluate, and select instruments to measure expected nursing administration outcomes without research-based guidance. Multiple and complex important contextual variables need psychometrically sound and easy-to-use measurement instruments identified for use in both practice and research. An expert focus group consensus methodology was used in this evaluation research to review available instruments in the five areas and evaluate which of these instruments are psychometrically sound and easy to use in the practice setting. The result is a portfolio of measures, clustered by concept and displayed on a spreadsheet. Retrieval information is provided. The portfolio includes the expert consensus judgment as well as useful descriptive information. The research reported here identifies psychometrically sound and easy-to-use instruments for measuring five key variables to be included in a portfolio. The results of this study can be used as a beginning for saving time in instrument selection and as an aid for determining the best instrument for measuring outcomes from a clinical or management intervention.

Is foreign direct investment good for health in low and middle income countries? An instrumental variable approach.

PubMed

Burns, Darren K; Jones, Andrew P; Goryakin, Yevgeniy; Suhrcke, Marc

2017-05-01

There is a scarcity of quantitative research into the effect of FDI on population health in low and middle income countries (LMICs). This paper investigates the relationship using annual panel data from 85 LMICs between 1974 and 2012. When controlling for time trends, country fixed effects, correlation between repeated observations, relevant covariates, and endogeneity via a novel instrumental variable approach, we find FDI to have a beneficial effect on overall health, proxied by life expectancy. When investigating age-specific mortality rates, we find a stronger beneficial effect of FDI on adult mortality, yet no association with either infant or child mortality. Notably, FDI effects on health remain undetected in all models which do not control for endogeneity. Exploring the effect of sector-specific FDI on health in LMICs, we provide preliminary evidence of a weak inverse association between secondary (i.e. manufacturing) sector FDI and overall life expectancy. Our results thus suggest that FDI has provided an overall benefit to population health in LMICs, particularly in adults, yet investments into the secondary sector could be harmful to health. Copyright © 2017 Elsevier Ltd. All rights reserved.

Shape optimization techniques for musical instrument design

NASA Astrophysics Data System (ADS)

Henrique, Luis; Antunes, Jose; Carvalho, Joao S.

2002-11-01

The design of musical instruments is still mostly based on empirical knowledge and costly experimentation. One interesting improvement is the shape optimization of resonating components, given a number of constraints (allowed parameter ranges, shape smoothness, etc.), so that vibrations occur at specified modal frequencies. Each admissible geometrical configuration generates an error between computed eigenfrequencies and the target set. Typically, error surfaces present many local minima, corresponding to suboptimal designs. This difficulty can be overcome using global optimization techniques, such as simulated annealing. However these methods are greedy, concerning the number of function evaluations required. Thus, the computational effort can be unacceptable if complex problems, such as bell optimization, are tackled. Those issues are addressed in this paper, and a method for improving optimization procedures is proposed. Instead of using the local geometric parameters as searched variables, the system geometry is modeled in terms of truncated series of orthogonal space-funcitons, and optimization is performed on their amplitude coefficients. Fourier series and orthogonal polynomials are typical such functions. This technique reduces considerably the number of searched variables, and has a potential for significant computational savings in complex problems. It is illustrated by optimizing the shapes of both current and uncommon marimba bars.

Evaluation of software sensors for on-line estimation of culture conditions in an Escherichia coli cultivation expressing a recombinant protein.

PubMed

Warth, Benedikt; Rajkai, György; Mandenius, Carl-Fredrik

2010-05-03

Software sensors for monitoring and on-line estimation of critical bioprocess variables have mainly been used with standard bioreactor sensors, such as electrodes and gas analyzers, where algorithms in the software model have generated the desired state variables. In this article we propose that other on-line instruments, such as NIR probes and on-line HPLC, should be used to make more reliable and flexible software sensors. Five software sensor architectures were compared and evaluated: (1) biomass concentration from an on-line NIR probe, (2) biomass concentration from titrant addition, (3) specific growth rate from titrant addition, (4) specific growth rate from the NIR probe, and (5) specific substrate uptake rate and by-product rate from on-line HPLC and NIR probe signals. The software sensors were demonstrated on an Escherichia coli cultivation expressing a recombinant protein, green fluorescent protein (GFP), but the results could be extrapolated to other production organisms and product proteins. We conclude that well-maintained on-line instrumentation (hardware sensors) can increase the potential of software sensors. This would also strongly support the intentions with process analytical technology and quality-by-design concepts. 2010 Elsevier B.V. All rights reserved.