A new approach used to explore associations of current Ambrosia pollen levels with current and past meteorological elements.

PubMed

Matyasovszky, István; Makra, László; Csépe, Zoltán; Deák, Áron József; Pál-Molnár, Elemér; Fülöp, Andrea; Tusnády, Gábor

2015-09-01

The paper examines the sensitivity of daily airborne Ambrosia (ragweed) pollen levels of a current pollen season not only on daily values of meteorological variables during this season but also on the past meteorological conditions. The results obtained from a 19-year data set including daily ragweed pollen counts and ten daily meteorological variables are evaluated with special focus on the interactions between the phyto-physiological processes and the meteorological elements. Instead of a Pearson correlation measuring the strength of the linear relationship between two random variables, a generalised correlation that measures every kind of relationship between random vectors was used. These latter correlations between arrays of daily values of the ten meteorological elements and the array of daily ragweed pollen concentrations during the current pollen season were calculated. For the current pollen season, the six most important variables are two temperature variables (mean and minimum temperatures), two humidity variables (dew point depression and rainfall) and two variables characterising the mixing of the air (wind speed and the height of the planetary boundary layer). The six most important meteorological variables before the current pollen season contain four temperature variables (mean, maximum, minimum temperatures and soil temperature) and two variables that characterise large-scale weather patterns (sea level pressure and the height of the planetary boundary layer). Key periods of the past meteorological variables before the current pollen season have been identified. The importance of this kind of analysis is that a knowledge of the past meteorological conditions may contribute to a better prediction of the upcoming pollen season.

Mismeasurement and the resonance of strong confounders: uncorrelated errors.

PubMed

Marshall, J R; Hastrup, J L

1996-05-15

Greenland first documented (Am J Epidemiol 1980; 112:564-9) that error in the measurement of a confounder could resonate--that it could bias estimates of other study variables, and that the bias could persist even with statistical adjustment for the confounder as measured. An important question is raised by this finding: can such bias be more than trivial within the bounds of realistic data configurations? The authors examine several situations involving dichotomous and continuous data in which a confounder and a null variable are measured with error, and they assess the extent of resultant bias in estimates of the effect of the null variable. They show that, with continuous variables, measurement error amounting to 40% of observed variance in the confounder could cause the observed impact of the null study variable to appear to alter risk by as much as 30%. Similarly, they show, with dichotomous independent variables, that 15% measurement error in the form of misclassification could lead the null study variable to appear to alter risk by as much as 50%. Such bias would result only from strong confounding. Measurement error would obscure the evidence that strong confounding is a likely problem. These results support the need for every epidemiologic inquiry to include evaluations of measurement error in each variable considered.

AN IMPROVED STRATEGY FOR REGRESSION OF BIOPHYSICAL VARIABLES AND LANDSAT ETM+ DATA. (R828309)

EPA Science Inventory

Empirical models are important tools for relating field-measured biophysical variables to remote sensing data. Regression analysis has been a popular empirical method of linking these two types of data to provide continuous estimates for variables such as biomass, percent wood...

A Multivariate Model of Parent-Adolescent Relationship Variables in Early Adolescence

ERIC Educational Resources Information Center

McKinney, Cliff; Renk, Kimberly

2011-01-01

Given the importance of predicting outcomes for early adolescents, this study examines a multivariate model of parent-adolescent relationship variables, including parenting, family environment, and conflict. Participants, who completed measures assessing these variables, included 710 culturally diverse 11-14-year-olds who were attending a middle…

Predictive factors of difficulty in lower third molar extraction: A prospective cohort study.

PubMed

Alvira-González, J; Figueiredo, R; Valmaseda-Castellón, E; Quesada-Gómez, C; Gay-Escoda, C

2017-01-01

Several publications have measured the difficulty of third molar removal, trying to establish the main risk factors, however several important preoperative and intraoperative variables are overlooked. A prospective cohort study comprising a total of 130 consecutive lower third molar extractions was performed. The outcome variables used to measure the difficulty of the extraction were operation time and a 100mm visual analogue scale filled by the surgeon at the end of the surgical procedure. The predictors were divided into 4 different groups (demographic, anatomic, radiographic and operative variables). A descriptive, bivariate and multivariate analysis of the data was performed. Patients' weight, the presence of bulbous roots, the need to perform crown and root sectioning of the lower third molar and Pell and Gregory 123 classification significantly influenced both outcome variables (p< 0.05). Certain anatomical, radiological and operative variables appear to be important factors in the assessment of surgical difficulty in the extraction of lower third molars.

Identify the dominant variables to predict stream water temperature

NASA Astrophysics Data System (ADS)

Chien, H.; Flagler, J.

2016-12-01

Stream water temperature is a critical variable controlling water quality and the health of aquatic ecosystems. Accurate prediction of water temperature and the assessment of the impacts of environmental variables on water temperature variation are critical for water resources management, particularly in the context of water quality and aquatic ecosystem sustainability. The objective of this study is to measure stream water temperature and air temperature and to examine the importance of streamflow on stream water temperature prediction. The measured stream water temperature and air temperature will be used to test two hypotheses: 1) streamflow is a relatively more important factor than air temperature in regulating water temperature, and 2) by combining air temperature and streamflow data stream water temperature can be more accurately estimated. Water and air temperature data loggers are placed at two USGS stream gauge stations #01362357and #01362370, located in the upper Esopus Creek watershed in Phonecia, NY. The ARIMA (autoregressive integrated moving average) time series model is used to analyze the measured water temperature data, identify the dominant environmental variables, and predict the water temperature with identified dominant variable. The preliminary results show that streamflow is not a significant variable in predicting stream water temperature at both USGS gauge stations. Daily mean air temperature is sufficient to predict stream water temperature at this site scale.

Heterogeneity of Prognostic Studies of 24-Hour Blood Pressure Variability: Systematic Review and Meta-Analysis

PubMed Central

Taylor, Kathryn S.; Heneghan, Carl J.; Stevens, Richard J.; Adams, Emily C.; Nunan, David; Ward, Alison

2015-01-01

In addition to mean blood pressure, blood pressure variability is hypothesized to have important prognostic value in evaluating cardiovascular risk. We aimed to assess the prognostic value of blood pressure variability within 24 hours. Using MEDLINE, EMBASE and Cochrane Library to April 2013, we conducted a systematic review of prospective studies of adults, with at least one year follow-up and any day, night or 24-hour blood pressure variability measure as a predictor of one or more of the following outcomes: all-cause mortality, cardiovascular mortality, all cardiovascular events, stroke and coronary heart disease. We examined how blood pressure variability is defined and how its prognostic use is reported. We analysed relative risks adjusted for covariates including the appropriate mean blood pressure and considered the potential for meta-analysis. Our analysis of methods included 24 studies and analysis of predictions included 16 studies. There were 36 different measures of blood pressure variability and 13 definitions of night- and day-time periods. Median follow-up was 5.5 years (interquartile range 4.2–7.0). Comparing measures of dispersion, coefficient of variation was less well researched than standard deviation. Night dipping based on percentage change was the most researched measure and the only measure for which data could be meaningfully pooled. Night dipping or lower night-time blood pressure was associated with lower risk of cardiovascular events. The interpretation and use in clinical practice of 24-hour blood pressure variability, as an important prognostic indicator of cardiovascular events, is hampered by insufficient evidence and divergent methodologies. We recommend greater standardisation of methods. PMID:25984791

Body size as a latent variable in a structural equation model: thermal acclimation and energetics of the leaf-eared mouse.

PubMed

Nespolo, Roberto F; Arim, Matías; Bozinovic, Francisco

2003-07-01

Body size is one of the most important determinants of energy metabolism in mammals. However, the usual physiological variables measured to characterize energy metabolism and heat dissipation in endotherms are strongly affected by thermal acclimation, and are also correlated among themselves. In addition to choosing the appropriate measurement of body size, these problems create additional complications when analyzing the relationships among physiological variables such as basal metabolism, non-shivering thermogenesis, thermoregulatory maximum metabolic rate and minimum thermal conductance, body size dependence, and the effect of thermal acclimation on them. We measured these variables in Phyllotis darwini, a murid rodent from central Chile, under conditions of warm and cold acclimation. In addition to standard statistical analyses to determine the effect of thermal acclimation on each variable and the body-mass-controlled correlation among them, we performed a Structural Equation Modeling analysis to evaluate the effects of three different measurements of body size (body mass, m(b); body length, L(b) and foot length, L(f)) on energy metabolism and thermal conductance. We found that thermal acclimation changed the correlation among physiological variables. Only cold-acclimated animals supported our a priori path models, and m(b) appeared to be the best descriptor of body size (compared with L(b) and L(f)) when dealing with energy metabolism and thermal conductance. However, while m(b) appeared to be the strongest determinant of energy metabolism, there was an important and significant contribution of L(b) (but not L(f)) to thermal conductance. This study demonstrates how additional information can be drawn from physiological ecology and general organismal studies by applying Structural Equation Modeling when multiple variables are measured in the same individuals.

[Development and validation of quality standards for colonoscopy].

PubMed

Sánchez Del Río, Antonio; Baudet, Juan Salvador; Naranjo Rodríguez, Antonio; Campo Fernández de Los Ríos, Rafael; Salces Franco, Inmaculada; Aparicio Tormo, Jose Ramón; Sánchez Muñoz, Diego; Llach, Joseph; Hervás Molina, Antonio; Parra-Blanco, Adolfo; Díaz Acosta, Juan Antonio

2010-01-30

Before starting programs for colorectal cancer screening it is necessary to evaluate the quality of colonoscopy. Our objectives were to develop a group of quality indicators of colonoscopy easily applicable and to determine the variability of their achievement. After reviewing the bibliography we prepared 21 potential indicators of quality that were submitted to a process of selection in which we measured their facial validity, content validity, reliability and viability of their measurement. We estimated the variability of their achievement by means of the coefficient of variability (CV) and the variability of the achievement of the standards by means of chi(2). Six indicators overcome the selection process: informed consent, medication administered, completed colonoscopy, complications, every polyp removed and recovered, and adenoma detection rate in patients older than 50 years. 1928 colonoscopies were included from eight endoscopy units. Every unit included the same number of colonoscopies selected by means of simple random sampling with substitution. There was an important variability in the achievement of some indicators and standards: medication administered (CV 43%, p<0.01), complications registered (CV 37%, p<0.01), every polyp removed and recovered (CV 12%, p<0.01) and adenoma detection rate in older than fifty years (CV 2%, p<0.01). We have validated six quality indicators for colonoscopy which are easily measurable. An important variability exists in the achievement of some indicators and standards. Our data highlight the importance of the development of continuous quality improvement programmes for colonoscopy before starting colorectal cancer screening. Copyright (c) 2009 Elsevier España, S.L. All rights reserved.

Integrating satellite remote sensing data and field data to predict rangeland structural indicators at the continental scale

NASA Astrophysics Data System (ADS)

Zhang, J.; Okin, G.

2016-12-01

Rangelands provide a variety of important ecosystem goods and services across drylands globally. They are also the most important emitters of dust across the globe. Field data collection based on points does not represent spatially continuous information about surface variables and, given the vast size of the world's rangelands, cannot cover even a small fraction of their area. Remote sensing is potentially a labor- and time-saving method to observe important rangeland vegetation variables at both temporal and spatial scales. Information on vegetation cover, bare gap size, and plant height provide key rangeland vegetation variables in arid and semiarid rangelands, in part because they strongly impact dust emission and determine wildlife habitat characteristics. This study reports on relationships between remote sensing in the reflected solar spectrum and field measures related to these three variables, and shows how these relationships can be extended to produce spatially and temporally continuous datasets coupled with quantitative estimates of error. Field data for this study included over 3,800 Assessment, Inventory, and Monitoring (AIM) measurements on Bureau of Land Management (BLM) lands throughout the western US. Remote sensing data were derived from MODIS nadir BRDF-adjusted reflectance (NBAR) and Landsat 8 OLI surface reflectance. Normalized bare gap size, total foliar cover, herbaceous cover and herbaceous height exhibit the greatest predictability from remote sensing variables with physically-reasonable relationships between remote sensing variables and field measures. Data fields produced using these relationships across the western US exhibit good agreement with independent high-resolution imagery.

Submesoscale Sea Surface Temperature Variability from UAV and Satellite Measurements

NASA Astrophysics Data System (ADS)

Castro, S. L.; Emery, W. J.; Tandy, W., Jr.; Good, W. S.

2017-12-01

Technological advances in spatial resolution of observations have revealed the importance of short-lived ocean processes with scales of O(1km). These submesoscale processes play an important role for the transfer of energy from the meso- to small scales and for generating significant spatial and temporal intermittency in the upper ocean, critical for the mixing of the oceanic boundary layer. Submesoscales have been observed in sea surface temperatures (SST) from satellites. Satellite SST measurements are spatial averages over the footprint of the satellite. When the variance of the SST distribution within the footprint is small, the average value is representative of the SST over the whole pixel. If the variance is large, the spatial heterogeneity is a source of uncertainty in satellite derived SSTs. Here we show evidence that the submesoscale variability in SSTs at spatial scales of 1km is responsible for the spatial variability within satellite footprints. Previous studies of the spatial variability in SST, using ship-based radiometric data suggested that variability at scales smaller than 1 km is significant and affects the uncertainty of satellite-derived skin SSTs. We examine data collected by a calibrated thermal infrared radiometer, the Ball Experimental Sea Surface Temperature (BESST), flown on a UAV over the Arctic Ocean and compare them with coincident measurements from the MODIS spaceborne radiometer to assess the spatial variability of SST within 1 km pixels. By taking the standard deviation of all the BESST measurements within individual MODIS pixels we show that significant spatial variability exists within the footprints. The distribution of the surface variability measured by BESST shows a peak value of O(0.1K) with 95% of the pixels showing σ < 0.45K. More importantly, high-variability pixels are located at density fronts in the marginal ice zone, which are a primary source of submesoscale intermittency near the surface in the Arctic Ocean. Wavenumber spectra of the BESST SSTs indicate a spectral slope of -2, consistent with the presence of submesoscale processes. Furthermore, not only is the BESST wavenumber spectra able to match the MODIS SST spectra well, but also extends the spectral slope of -2 by 2 decades relative to MODIS, from wavelengths of 8km to 0.08km.

Environmental variables measured at multiple spatial scales exert uneven influence on fish assemblages of floodplain lakes

USGS Publications Warehouse

Dembkowski, Daniel J.; Miranda, Leandro E.

2014-01-01

We examined the interaction between environmental variables measured at three different scales (i.e., landscape, lake, and in-lake) and fish assemblage descriptors across a range of over 50 floodplain lakes in the Mississippi Alluvial Valley of Mississippi and Arkansas. Our goal was to identify important local- and landscape-level determinants of fish assemblage structure. Relationships between fish assemblage structure and variables measured at broader scales (i.e., landscape-level and lake-level) were hypothesized to be stronger than relationships with variables measured at finer scales (i.e., in-lake variables). Results suggest that fish assemblage structure in floodplain lakes was influenced by variables operating on three different scales. However, and contrary to expectations, canonical correlations between in-lake environmental characteristics and fish assemblage structure were generally stronger than correlations between landscape-level and lake-level variables and fish assemblage structure, suggesting a hierarchy of influence. From a resource management perspective, our study suggests that landscape-level and lake-level variables may be manipulated for conservation or restoration purposes, and in-lake variables and fish assemblage structure may be used to monitor the success of such efforts.

Climatic extremes improve predictions of spatial patterns of tree species

USGS Publications Warehouse

Zimmermann, N.E.; Yoccoz, N.G.; Edwards, T.C.; Meier, E.S.; Thuiller, W.; Guisan, Antoine; Schmatz, D.R.; Pearman, P.B.

2009-01-01

Understanding niche evolution, dynamics, and the response of species to climate change requires knowledge of the determinants of the environmental niche and species range limits. Mean values of climatic variables are often used in such analyses. In contrast, the increasing frequency of climate extremes suggests the importance of understanding their additional influence on range limits. Here, we assess how measures representing climate extremes (i.e., interannual variability in climate parameters) explain and predict spatial patterns of 11 tree species in Switzerland. We find clear, although comparably small, improvement (+20% in adjusted D2, +8% and +3% in cross-validated True Skill Statistic and area under the receiver operating characteristics curve values) in models that use measures of extremes in addition to means. The primary effect of including information on climate extremes is a correction of local overprediction and underprediction. Our results demonstrate that measures of climate extremes are important for understanding the climatic limits of tree species and assessing species niche characteristics. The inclusion of climate variability likely will improve models of species range limits under future conditions, where changes in mean climate and increased variability are expected.

Kernel-Based Measure of Variable Importance for Genetic Association Studies.

PubMed

Gallego, Vicente; Luz Calle, M; Oller, Ramon

2017-06-17

The identification of genetic variants that are associated with disease risk is an important goal of genetic association studies. Standard approaches perform univariate analysis where each genetic variant, usually Single Nucleotide Polymorphisms (SNPs), is tested for association with disease status. Though many genetic variants have been identified and validated so far using this univariate approach, for most complex diseases a large part of their genetic component is still unknown, the so called missing heritability. We propose a Kernel-based measure of variable importance (KVI) that provides the contribution of a SNP, or a group of SNPs, to the joint genetic effect of a set of genetic variants. KVI can be used for ranking genetic markers individually, sets of markers that form blocks of linkage disequilibrium or sets of genetic variants that lie in a gene or a genetic pathway. We prove that, unlike the univariate analysis, KVI captures the relationship with other genetic variants in the analysis, even when measured at the individual level for each genetic variable separately. This is specially relevant and powerful for detecting genetic interactions. We illustrate the results with data from an Alzheimer's disease study and show through simulations that the rankings based on KVI improve those rankings based on two measures of importance provided by the Random Forest. We also prove with a simulation study that KVI is very powerful for detecting genetic interactions.

The effect of virtual reality on gait variability.

PubMed

Katsavelis, Dimitrios; Mukherjee, Mukul; Decker, Leslie; Stergiou, Nicholas

2010-07-01

Optic Flow (OF) plays an important role in human locomotion and manipulation of OF characteristics can cause changes in locomotion patterns. The purpose of the study was to investigate the effect of the velocity of optic flow on the amount and structure of gait variability. Each subject underwent four conditions of treadmill walking at their self-selected pace. In three conditions the subjects walked in an endless virtual corridor, while a fourth control condition was also included. The three virtual conditions differed in the speed of the optic flow displayed as follows--same speed (OFn), faster (OFf), and slower (OFs) than that of the treadmill. Gait kinematics were tracked with an optical motion capture system. Gait variability measures of the hip, knee and ankle range of motion and stride interval were analyzed. Amount of variability was evaluated with linear measures of variability--coefficient of variation, while structure of variability i.e., its organization over time, were measured with nonlinear measures--approximate entropy and detrended fluctuation analysis. The linear measures of variability, CV, did not show significant differences between Non-VR and VR conditions while nonlinear measures of variability identified significant differences at the hip, ankle, and in stride interval. In response to manipulation of the optic flow, significant differences were observed between the three virtual conditions in the following order: OFn greater than OFf greater than OFs. Measures of structure of variability are more sensitive to changes in gait due to manipulation of visual cues, whereas measures of the amount of variability may be concealed by adaptive mechanisms. Visual cues increase the complexity of gait variability and may increase the degrees of freedom available to the subject. Further exploration of the effects of optic flow manipulation on locomotion may provide us with an effective tool for rehabilitation of subjects with sensorimotor issues.

Variation in soil carbon dioxide efflux at two spatial scales in a topographically complex boreal forest

USGS Publications Warehouse

Kelsey, Katharine C.; Wickland, Kimberly P.; Striegl, Robert G.; Neff, Jason C.

2012-01-01

Carbon dynamics of high-latitude regions are an important and highly uncertain component of global carbon budgets, and efforts to constrain estimates of soil-atmosphere carbon exchange in these regions are contingent on accurate representations of spatial and temporal variability in carbon fluxes. This study explores spatial and temporal variability in soilatmosphere carbon dynamics at both fine and coarse spatial scales in a high-elevation, permafrost-dominated boreal black spruce forest. We evaluate the importance of landscape-level investigations of soil-atmosphere carbon dynamics by characterizing seasonal trends in soil-atmosphere carbon exchange, describing soil temperature-moisture-respiration relations, and quantifying temporal and spatial variability at two spatial scales: the plot scale (0–5 m) and the landscape scale (500–1000 m). Plot-scale spatial variability (average variation on a given measurement day) in soil CO2 efflux ranged from a coefficient of variation (CV) of 0.25 to 0.69, and plot-scale temporal variability (average variation of plots across measurement days) in efflux ranged from a CV of 0.19 to 0.36. Landscape-scale spatial and temporal variability in efflux was represented by a CV of 0.40 and 0.31, respectively, indicating that plot-scale spatial variability in soil respiration is as great as landscape-scale spatial variability at this site. While soil respiration was related to soil temperature at both the plot- and landscape scale, landscape-level descriptions of soil moisture were necessary to define soil respiration-moisture relations. Soil moisture variability was also integral to explaining temporal variability in soil respiration. Our results have important implications for research efforts in high-latitude regions where remote study sites make landscape-scale field campaigns challenging.

Acclimatization of the crustose coralline alga Porolithon onkodes to variable pCO₂.

PubMed

Johnson, Maggie D; Moriarty, Vincent W; Carpenter, Robert C

2014-01-01

Ocean acidification (OA) has important implications for the persistence of coral reef ecosystems, due to potentially negative effects on biomineralization. Many coral reefs are dynamic with respect to carbonate chemistry, and experience fluctuations in pCO₂ that exceed OA projections for the near future. To understand the influence of dynamic pCO₂ on an important reef calcifier, we tested the response of the crustose coralline alga Porolithon onkodes to oscillating pCO₂. Individuals were exposed to ambient (400 µatm), high (660 µatm), or variable pCO₂ (oscillating between 400/660 µatm) treatments for 14 days. To explore the potential for coralline acclimatization, we collected individuals from low and high pCO₂ variability sites (upstream and downstream respectively) on a back reef characterized by unidirectional water flow in Moorea, French Polynesia. We quantified the effects of treatment on algal calcification by measuring the change in buoyant weight, and on algal metabolism by conducting sealed incubations to measure rates of photosynthesis and respiration. Net photosynthesis was higher in the ambient treatment than the variable treatment, regardless of habitat origin, and there was no effect on respiration or gross photosynthesis. Exposure to high pCO₂ decreased P. onkodes calcification by >70%, regardless of the original habitat. In the variable treatment, corallines from the high variability habitat calcified 42% more than corallines from the low variability habitat. The significance of the original habitat for the coralline calcification response to variable, high pCO₂ indicates that individuals existing in dynamic pCO₂ habitats may be acclimatized to OA within the scope of in situ variability. These results highlight the importance of accounting for natural pCO₂ variability in OA manipulations, and provide insight into the potential for plasticity in habitat and species-specific responses to changing ocean chemistry.

An improved strategy for regression of biophysical variables and Landsat ETM+ data.

Treesearch

Warren B. Cohen; Thomas K. Maiersperger; Stith T. Gower; David P. Turner

2003-01-01

Empirical models are important tools for relating field-measured biophysical variables to remote sensing data. Regression analysis has been a popular empirical method of linking these two types of data to provide continuous estimates for variables such as biomass, percent woody canopy cover, and leaf area index (LAI). Traditional methods of regression are not...

Relationships between Admission Variables and Outcome Variables in a Special Education Graduate Program

ERIC Educational Resources Information Center

LaFave, Matthew

2012-01-01

The need for well-prepared special education teachers has made it important to examine how to best select candidates for special education teacher education programs, or at least to determine which, if any, admission variables relate to program outcome measures. This study used archival data from 148 students to investigate the relationships among…

Sentient Structures: Optimising Sensor Layouts for Direct Measurement of Discrete Variables

DTIC Science & Technology

2008-11-01

1 Sentient Structures Optimising Sensor Layouts for Direct Measurement of Discrete Variables Report to US Air Force...TITLE AND SUBTITLE Sentient Structures 5a. CONTRACT NUMBER FA48690714045 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Donald Price...optimal sensor placements is an important requirement for the development of sentient structures. An optimal sensor layout is attained when a limited

Solar diameter measurements for study of Sun climate coupling

NASA Technical Reports Server (NTRS)

Hill, H. A.

1981-01-01

Variability in solar shape and diameters was examined as a possible probe of an important climatic driving function, solar luminosity variability. The techniques and facilities developed for measuring the solar diameter were used. The observing program and the requisite data reduction were conducted simultaneously. The development of a technique to calibrate the scale in the telescope field progressed to the design and construction phase.

Measuring motivation in schizophrenia: Is a general state of motivation necessary for task-specific motivation?

PubMed Central

Choi, Jimmy; Choi, Kee-Hong; Reddy, Felice; Fiszdon, Joanna M.

2014-01-01

Despite the important role of motivation in rehabilitation and functional outcomes in schizophrenia, to date, there has been little emphasis on how motivation is assessed. This is important, since different measures may tap potentially discrete motivational constructs, which in turn may have very different associations to important outcomes. In the current study, we used baseline data from 71 schizophrenia spectrum outpatients enrolled in a rehabilitation program to examine the relationship between task-specific motivation, as measured by the Intrinsic Motivation Inventory (IMI), and a more general state of volition/initiation, as measured by the three item Quality of Life (QLS) motivation index. We also examined the relationship of these motivation measures to demographic, clinical and functional variables relevant to rehabilitation outcomes. The two motivation measures were not correlated, and participants with low general state motivation exhibited a full range of task-specific motivation. Only the QLS motivation index correlated with variables relevant to rehabilitation outcomes. The lack of associations between QLS motivation index and IMI subscales suggests that constructs tapped by these measures may be divergent in schizophrenia, and specifically that task-specific intrinsic motivation is not contingent on a general state of motivation. That is, even in individuals with a general low motivational state (i.e. amotivation), interventions aimed at increasing task-specific motivation may still be effective. Moreover, the pattern of interrelationships between the QLS motivation index and variables relevant to psychosocial rehabilitation supports its use in treatment outcome studies. PMID:24529609

Dynamic Modeling of the Main Blow in Basic Oxygen Steelmaking Using Measured Step Responses

NASA Astrophysics Data System (ADS)

Kattenbelt, Carolien; Roffel, B.

2008-10-01

In the control and optimization of basic oxygen steelmaking, it is important to have an understanding of the influence of control variables on the process. However, important process variables such as the composition of the steel and slag cannot be measured continuously. The decarburization rate and the accumulation rate of oxygen, which can be derived from the generally measured waste gas flow and composition, are an indication of changes in steel and slag composition. The influence of the control variables on the decarburization rate and the accumulation rate of oxygen can best be determined in the main blow period. In this article, the measured step responses of the decarburization rate and the accumulation rate of oxygen to step changes in the oxygen blowing rate, lance height, and the addition rate of iron ore during the main blow are presented. These measured step responses are subsequently used to develop a dynamic model for the main blow. The model consists of an iron oxide and a carbon balance and an additional equation describing the influence of the lance height and the oxygen blowing rate on the decarburization rate. With this simple dynamic model, the measured step responses can be explained satisfactorily.

Chapter One: Exposure Measurements.

EPA Science Inventory

Determining human exposure to suspended particualte concentrations requires measurements that quantify different particle properties in microenvironments where people live, work, and play. Particle mass, size, and chemical composition are important exposure variables, and these ...

CHAPTER ONE: EXPOSURE MEASUREMENTS.

EPA Science Inventory

Determining human exposure to suspended particualte concentrations requires measurements that quantify different particle properties in microenvironments where people live, work, and play. Particle mass, size, and chemical composition are important exposure variables, and these ...

Importance of Non-invasive Right and Left Ventricular Variables on Exercise Capacity in Patients with Tetralogy of Fallot Hemodynamics.

PubMed

Meierhofer, Christian; Tavakkoli, Timon; Kühn, Andreas; Ulm, Kurt; Hager, Alfred; Müller, Jan; Martinoff, Stefan; Ewert, Peter; Stern, Heiko

2017-12-01

Good quality of life correlates with a good exercise capacity in daily life in patients with tetralogy of Fallot (ToF). Patients after correction of ToF usually develop residual defects such as pulmonary regurgitation or stenosis of variable severity. However, the importance of different hemodynamic parameters and their impact on exercise capacity is unclear. We investigated several hemodynamic parameters measured by cardiovascular magnetic resonance (CMR) and echocardiography and evaluated which parameter has the most pronounced effect on maximal exercise capacity determined by cardiopulmonary exercise testing (CPET). 132 patients with ToF-like hemodynamics were tested during routine follow-up with CMR, echocardiography and CPET. Right and left ventricular volume data, ventricular ejection fraction and pulmonary regurgitation were evaluated by CMR. Echocardiographic pressure gradients in the right ventricular outflow tract and through the tricuspid valve were measured. All data were classified and correlated with the results of CPET evaluations of these patients. The analysis was performed using the Random Forest model. In this way, we calculated the importance of the different hemodynamic variables related to the maximal oxygen uptake in CPET (VO 2 %predicted). Right ventricular pressure showed the most important influence on maximal oxygen uptake, whereas pulmonary regurgitation and right ventricular enddiastolic volume were not important hemodynamic variables to predict maximal oxygen uptake in CPET. Maximal exercise capacity was only very weakly influenced by right ventricular enddiastolic volume and not at all by pulmonary regurgitation in patients with ToF. The variable with the most pronounced influence was the right ventricular pressure.

Predictive factors of difficulty in lower third molar extraction: A prospective cohort study

PubMed Central

Alvira-González, Joaquín; Valmaseda-Castellón, Eduard; Quesada-Gómez, Carmen; Gay-Escoda, Cosme

2017-01-01

Background Several publications have measured the difficulty of third molar removal, trying to establish the main risk factors, however several important preoperative and intraoperative variables are overlooked. Material and Methods A prospective cohort study comprising a total of 130 consecutive lower third molar extractions was performed. The outcome variables used to measure the difficulty of the extraction were operation time and a 100mm visual analogue scale filled by the surgeon at the end of the surgical procedure. The predictors were divided into 4 different groups (demographic, anatomic, radiographic and operative variables). A descriptive, bivariate and multivariate analysis of the data was performed. Results Patients’ weight, the presence of bulbous roots, the need to perform crown and root sectioning of the lower third molar and Pell and Gregory 123 classification significantly influenced both outcome variables (p< 0.05). Conclusions Certain anatomical, radiological and operative variables appear to be important factors in the assessment of surgical difficulty in the extraction of lower third molars. Key words:Third molar, surgical extraction, surgical difficulty. PMID:27918736

Infrastructure features outperform environmental variables explaining rabbit abundance around motorways.

PubMed

Planillo, Aimara; Malo, Juan E

2018-01-01

Human disturbance is widespread across landscapes in the form of roads that alter wildlife populations. Knowing which road features are responsible for the species response and their relevance in comparison with environmental variables will provide useful information for effective conservation measures. We sampled relative abundance of European rabbits, a very widespread species, in motorway verges at regional scale, in an area with large variability in environmental and infrastructure conditions. Environmental variables included vegetation structure, plant productivity, distance to water sources, and altitude. Infrastructure characteristics were the type of vegetation in verges, verge width, traffic volume, and the presence of embankments. We performed a variance partitioning analysis to determine the relative importance of two sets of variables on rabbit abundance. Additionally, we identified the most important variables and their effects model averaging after model selection by AICc on hypothesis-based models. As a group, infrastructure features explained four times more variability in rabbit abundance than environmental variables, being the effects of the former critical in motorway stretches located in altered landscapes with no available habitat for rabbits, such as agricultural fields. Model selection and Akaike weights showed that verge width and traffic volume are the most important variables explaining rabbit abundance index, with positive and negative effects, respectively. In the light of these results, the response of species to the infrastructure can be modulated through the modification of motorway features, being some of them manageable in the design phase. The identification of such features leads to suggestions for improvement through low-cost corrective measures and conservation plans. As a general indication, keeping motorway verges less than 10 m wide will prevent high densities of rabbits and avoid the unwanted effects that rabbit populations can generate in some areas.

Self-reported personality variability across the social network is associated with interpersonal dysfunction.

PubMed

Clifton, Allan; Kuper, Laura E

2011-04-01

We describe 2 studies (n=52 and n=82) examining variability in perceptions of personality using a social network methodology. Undergraduate participants completed self-report measures of personality and interpersonal dysfunction and then subsequently reported on their personalities with each of 30 members of their social networks. Results across the 2 studies found substantial variability in participants' perceived personalities within their social networks. Measures of interpersonal dysfunction were associated with the amount of variability in dyadic ratings of personality, specifically Agreeableness and Openness to Experience. Results suggest that personality variability across interpersonal contexts may be an important individual difference related to social behavior and dysfunction. © 2011 The Authors. Journal of Personality © 2011, Wiley Periodicals, Inc.

Comparing Selections of Environmental Variables for Ecological Studies: A Focus on Terrain Attributes.

PubMed

Lecours, Vincent; Brown, Craig J; Devillers, Rodolphe; Lucieer, Vanessa L; Edinger, Evan N

2016-01-01

Selecting appropriate environmental variables is a key step in ecology. Terrain attributes (e.g. slope, rugosity) are routinely used as abiotic surrogates of species distribution and to produce habitat maps that can be used in decision-making for conservation or management. Selecting appropriate terrain attributes for ecological studies may be a challenging process that can lead users to select a subjective, potentially sub-optimal combination of attributes for their applications. The objective of this paper is to assess the impacts of subjectively selecting terrain attributes for ecological applications by comparing the performance of different combinations of terrain attributes in the production of habitat maps and species distribution models. Seven different selections of terrain attributes, alone or in combination with other environmental variables, were used to map benthic habitats of German Bank (off Nova Scotia, Canada). 29 maps of potential habitats based on unsupervised classifications of biophysical characteristics of German Bank were produced, and 29 species distribution models of sea scallops were generated using MaxEnt. The performances of the 58 maps were quantified and compared to evaluate the effectiveness of the various combinations of environmental variables. One of the combinations of terrain attributes-recommended in a related study and that includes a measure of relative position, slope, two measures of orientation, topographic mean and a measure of rugosity-yielded better results than the other selections for both methodologies, confirming that they together best describe terrain properties. Important differences in performance (up to 47% in accuracy measurement) and spatial outputs (up to 58% in spatial distribution of habitats) highlighted the importance of carefully selecting variables for ecological applications. This paper demonstrates that making a subjective choice of variables may reduce map accuracy and produce maps that do not adequately represent habitats and species distributions, thus having important implications when these maps are used for decision-making.

Patterns in the species-environment relationship depend on both scale and choice of response variables

Treesearch

Samuel A. Cushman; Kevin McGarigal

2004-01-01

Multi-scale investigations of species/environment relationships are an important tool in ecological research. The scale at which independent and dependent variables are measured, and how they are coded for analysis, can strongly influence the relationships that are discovered. However, little is known about how the coding of the dependent variable set influences...

Physical attraction to reliable, low variability nervous systems: Reaction time variability predicts attractiveness.

PubMed

Butler, Emily E; Saville, Christopher W N; Ward, Robert; Ramsey, Richard

2017-01-01

The human face cues a range of important fitness information, which guides mate selection towards desirable others. Given humans' high investment in the central nervous system (CNS), cues to CNS function should be especially important in social selection. We tested if facial attractiveness preferences are sensitive to the reliability of human nervous system function. Several decades of research suggest an operational measure for CNS reliability is reaction time variability, which is measured by standard deviation of reaction times across trials. Across two experiments, we show that low reaction time variability is associated with facial attractiveness. Moreover, variability in performance made a unique contribution to attractiveness judgements above and beyond both physical health and sex-typicality judgements, which have previously been associated with perceptions of attractiveness. In a third experiment, we empirically estimated the distribution of attractiveness preferences expected by chance and show that the size and direction of our results in Experiments 1 and 2 are statistically unlikely without reference to reaction time variability. We conclude that an operating characteristic of the human nervous system, reliability of information processing, is signalled to others through facial appearance. Copyright © 2016 Elsevier B.V. All rights reserved.

Running Technique is an Important Component of Running Economy and Performance

PubMed Central

FOLLAND, JONATHAN P.; ALLEN, SAM J.; BLACK, MATTHEW I.; HANDSAKER, JOSEPH C.; FORRESTER, STEPHANIE E.

2017-01-01

ABSTRACT Despite an intuitive relationship between technique and both running economy (RE) and performance, and the diverse techniques used by runners to achieve forward locomotion, the objective importance of overall technique and the key components therein remain to be elucidated. Purpose This study aimed to determine the relationship between individual and combined kinematic measures of technique with both RE and performance. Methods Ninety-seven endurance runners (47 females) of diverse competitive standards performed a discontinuous protocol of incremental treadmill running (4-min stages, 1-km·h−1 increments). Measurements included three-dimensional full-body kinematics, respiratory gases to determine energy cost, and velocity of lactate turn point. Five categories of kinematic measures (vertical oscillation, braking, posture, stride parameters, and lower limb angles) and locomotory energy cost (LEc) were averaged across 10–12 km·h−1 (the highest common velocity < velocity of lactate turn point). Performance was measured as season's best (SB) time converted to a sex-specific z-score. Results Numerous kinematic variables were correlated with RE and performance (LEc, 19 variables; SB time, 11 variables). Regression analysis found three variables (pelvis vertical oscillation during ground contact normalized to height, minimum knee joint angle during ground contact, and minimum horizontal pelvis velocity) explained 39% of LEc variability. In addition, four variables (minimum horizontal pelvis velocity, shank touchdown angle, duty factor, and trunk forward lean) combined to explain 31% of the variability in performance (SB time). Conclusions This study provides novel and robust evidence that technique explains a substantial proportion of the variance in RE and performance. We recommend that runners and coaches are attentive to specific aspects of stride parameters and lower limb angles in part to optimize pelvis movement, and ultimately enhance performance. PMID:28263283

Calculations Supporting Management Zones

USDA-ARS?s Scientific Manuscript database

Since the early 1990’s the tools of precision farming (GPS, yield monitors, soil sensors, etc.) have documented how spatial and temporal variability are important factors impacting crop yield response. For precision farming, variability can be measured then used to divide up a field so that manageme...

Body Fat Percentage Prediction Using Intelligent Hybrid Approaches

PubMed Central

Shao, Yuehjen E.

2014-01-01

Excess of body fat often leads to obesity. Obesity is typically associated with serious medical diseases, such as cancer, heart disease, and diabetes. Accordingly, knowing the body fat is an extremely important issue since it affects everyone's health. Although there are several ways to measure the body fat percentage (BFP), the accurate methods are often associated with hassle and/or high costs. Traditional single-stage approaches may use certain body measurements or explanatory variables to predict the BFP. Diverging from existing approaches, this study proposes new intelligent hybrid approaches to obtain fewer explanatory variables, and the proposed forecasting models are able to effectively predict the BFP. The proposed hybrid models consist of multiple regression (MR), artificial neural network (ANN), multivariate adaptive regression splines (MARS), and support vector regression (SVR) techniques. The first stage of the modeling includes the use of MR and MARS to obtain fewer but more important sets of explanatory variables. In the second stage, the remaining important variables are served as inputs for the other forecasting methods. A real dataset was used to demonstrate the development of the proposed hybrid models. The prediction results revealed that the proposed hybrid schemes outperformed the typical, single-stage forecasting models. PMID:24723804

Modeling variability and scale integration of LAI measurements

Treesearch

Kris Nackaerts; Pol Coppin

2000-01-01

Rapid and reliable estimation of leaf area at various scales is important for research on chance detection of leaf area index (LAI) as an indicator of ecosystem condition. It is of utmost importance to know to what extent boundary and illumination conditions, data aggregation method, and sampling scheme influence the relative accuracy of stand-level LAI measurements....

Variability of hazardous air pollutants in an urban area

NASA Astrophysics Data System (ADS)

Spicer, Chester W.; Buxton, Bruce E.; Holdren, Michael W.; Smith, Deborah L.; Kelly, Thomas J.; Rust, Steven W.; Pate, Alan D.; Sverdrup, George M.; Chuang, Jane C.

The variability of hazardous air pollutants (HAPs) is an important factor in determining human exposure to such chemicals, and in designing HAP measurement programs. This study has investigated the factors which contribute to HAP variability in an urban area. Six measurement sites separated by up to 12 km collected data with 3 h time resolution to examine spatial variability within neighborhoods and between neighborhoods. The measurements were made in Columbus, OH. The 3 h results also were used to study temporal variability, and duplicate samples collected at each site were used to determine the component of variability attributable to the measurement process. Hourly samples collected over 10 days at one site provided further insight into the temporal resolution needed to capture short-term peak concentrations. Measurements at the 6 spatial sites focused on 78 chemicals. Twenty-three of these species were found in at least 95% of the 3 h samples, and 39 chemicals were present at least 60% of the time. The relative standard deviations for most of these 39 frequently detected chemicals was 1.0 or lower. Variability was segmented into temporal, spatial, and measurement components. Temporal variation was the major contributor to HAP variability for 19 of the 39 frequently detected compounds, based on the 3 h data. Measurement imprecision contributed less than 25% for most of the volatile organic species, but 30% or more of the variability for carbonyl compounds, trace elements, and particle-bound extractable organic mass. Interestingly, the spatial component contributed less than 20% of the total variability for all the chemicals except sulfur. Based on the data with hourly resolution, peak to median ratios (hourly peak to 24 h median) averaged between 2 and 4 for most of the volatile organic compounds, but there were two species with peak to median ratios of about 10.

The Importance of Measurement Data Spacing

ERIC Educational Resources Information Center

Seixas, T. M.; da Silva, M. A. Salgueiro

2015-01-01

When conducting experiments involving the measurement of physically related quantities, choosing an appropriate spacing for the experimental independent variable is a crucial procedure whose consequences may go beyond data graphical visualization. This is particularly true if the measured quantities are nonlinearly related and experimental errors…

Ensemble simulations of the role of the stratosphere in the attribution of northern extratropical tropospheric ozone variability

NASA Astrophysics Data System (ADS)

Hess, P.; Kinnison, D.; Tang, Q.

2015-03-01

Despite the need to understand the impact of changes in emissions and climate on tropospheric ozone, the attribution of tropospheric interannual ozone variability to specific processes has proven difficult. Here, we analyze the stratospheric contribution to tropospheric ozone variability and trends from 1953 to 2005 in the Northern Hemisphere (NH) mid-latitudes using four ensemble simulations of the free running (FR) Whole Atmosphere Community Climate Model (WACCM). The simulations are externally forced with observed time-varying (1) sea-surface temperatures (SSTs), (2) greenhouse gases (GHGs), (3) ozone depleting substances (ODS), (4) quasi-biennial oscillation (QBO), (5) solar variability (SV) and (6) stratospheric sulfate surface area density (SAD). A detailed representation of stratospheric chemistry is simulated, including the ozone loss due to volcanic eruptions and polar stratospheric clouds. In the troposphere, ozone production is represented by CH4-NOx smog chemistry, where surface chemical emissions remain interannually constant. Despite the simplicity of its tropospheric chemistry, at many NH measurement locations, the interannual ozone variability in the FR WACCM simulations is significantly correlated with the measured interannual variability. This suggests the importance of the external forcing applied in these simulations in driving interannual ozone variability. The variability and trend in the simulated 1953-2005 tropospheric ozone from 30 to 90° N at background surface measurement sites, 500 hPa measurement sites and in the area average are largely explained on interannual timescales by changes in the 30-90° N area averaged flux of ozone across the 100 hPa surface and changes in tropospheric methane concentrations. The average sensitivity of tropospheric ozone to methane (percent change in ozone to a percent change in methane) from 30 to 90° N is 0.17 at 500 hPa and 0.21 at the surface; the average sensitivity of tropospheric ozone to the 100 hPa ozone flux (percent change in ozone to a percent change in the ozone flux) from 30 to 90° N is 0.19 at 500 hPa and 0.11 at the surface. The 30-90° N simulated downward residual velocity at 100 hPa increased by 15% between 1953 and 2005. However, the impact of this on the 30-90° N 100 hPa ozone flux is modulated by the long-term changes in stratospheric ozone. The ozone flux decreases from 1965 to 1990 due to stratospheric ozone depletion, but increases again by approximately 7% from 1990 to 2005. The first empirical orthogonal function of interannual ozone variability explains from 40% (at the surface) to over 80% (at 150 hPa) of the simulated ozone interannual variability from 30 to 90° N. This identified mode of ozone variability shows strong stratosphere-troposphere coupling, demonstrating the importance of the stratosphere in an attribution of tropospheric ozone variability. The simulations, with no change in emissions, capture almost 50% of the measured ozone change during the 1990s at a variety of locations. This suggests that a large portion of the measured change is not due to changes in emissions, but can be traced to changes in large-scale modes of ozone variability. This emphasizes the difficulty in the attribution of ozone changes, and the importance of natural variability in understanding the trends and variability of ozone. We find little relation between the El Niño-Southern Oscillation (ENSO) index and large-scale tropospheric ozone variability over the long-term record.

Drivers of inter-year variability of plant production and decomposers across contrasting island ecosystems.

PubMed

Wardle, David A; Jonsson, Micael; Kalela-Brundin, Maarit; Lagerström, Anna; Bardgett, Richard D; Yeates, Gregor W; Nilsson, Marie-Charlotte

2012-03-01

Despite the likely importance of inter-year dynamics of plant production and consumer biota for driving community- and ecosystem-level processes, very few studies have explored how and why these dynamics vary across contrasting ecosystems. We utilized a well-characterized system of 30 lake islands in the boreal forest zone of northern Sweden across which soil fertility and productivity vary considerably, with larger islands being more fertile and productive than smaller ones. In this system we assessed the inter-year dynamics of several measures of plant production and the soil microbial community (primary consumers in the decomposer food web) for each of nine years, and soil microfaunal groups (secondary and tertiary consumers) for each of six of those years. We found that, for measures of plant production and each of the three consumer trophic levels, inter-year dynamics were strongly affected by island size. Further, many variables were strongly affected by island size (and thus bottom-up regulation by soil fertility and resources) in some years, but not in other years, most likely due to inter-year variation in climatic conditions. For each of the plant and microbial variables for which we had nine years of data, we also determined the inter-year coefficient of variation (CV), an inverse measure of stability. We found that CVs of some measures of plant productivity were greater on large islands, whereas those of other measures were greater on smaller islands; CVs of microbial variables were unresponsive to island size. We also found that the effects of island size on the temporal dynamics of some variables were related to inter-year variability of macroclimatic variables. As such, our results show that the inter-year dynamics of both plant productivity and decomposer biota across each of three trophic levels, as well as the inter-year stability of plant productivity, differ greatly across contrasting ecosystems, with potentially important but largely overlooked implications for community and ecosystem processes.

Correlation and simple linear regression.

PubMed

Zou, Kelly H; Tuncali, Kemal; Silverman, Stuart G

2003-06-01

In this tutorial article, the concepts of correlation and regression are reviewed and demonstrated. The authors review and compare two correlation coefficients, the Pearson correlation coefficient and the Spearman rho, for measuring linear and nonlinear relationships between two continuous variables. In the case of measuring the linear relationship between a predictor and an outcome variable, simple linear regression analysis is conducted. These statistical concepts are illustrated by using a data set from published literature to assess a computed tomography-guided interventional technique. These statistical methods are important for exploring the relationships between variables and can be applied to many radiologic studies.

On the Temporal Variability of Low-Mode Internal Tides in the Deep Ocean

NASA Technical Reports Server (NTRS)

Ray, Richard D.; Zaron, E. D.

2010-01-01

In situ measurements of internal tides are typically characterized by high temporal variability, with strong dependence on stratification, mesoscale eddies, and background currents commonly observed. Thus, it is surprising to find phase-locked internal tides detectable by satellite altimetry. An important question is how much tidal variability is missed by altimetry. We address this question in several ways. We subset the altimetry by season and find only very small changes -- an important exception being internal tides in the South China Sea where we observe strong seasonal dependence. A wavenumber-domain analysis confirms that throughout most of the global ocean there is little temporal variability in altimetric internal-tide signals, at least in the first baroclinic mode, which is the mode that dominates surface elevation. The analysis shows higher order modes to be significantly more variable. The results of this study have important practical implications for the anticipated SWOT wide-swath altimeter mission, for which removal of internal tide signals is critical for observing non-tidal submesoscale phenomena.

Quantifying Error in Survey Measures of School and Classroom Environments

ERIC Educational Resources Information Center

Schweig, Jonathan David

2014-01-01

Developing indicators that reflect important aspects of school and classroom environments has become central in a nationwide effort to develop comprehensive programs that measure teacher quality and effectiveness. Formulating teacher evaluation policy necessitates accurate and reliable methods for measuring these environmental variables. This…

The effects of a confidant and a peer group on the well-being of single elders.

PubMed

Gupta, V; Korte, C

1994-01-01

A study of 100 elderly people was carried out to compare the predictions of well-being derived from the confidant model with those derived from the Weiss model. The confidant model predicts that the most important feature of a person's social network for the well-being of that person is whether or not the person has a confidant. The Weiss model states that different persons are needed to fulfill the different needs of the person and in particular that a confidant is important to the need for intimacy and emotional security while a peer group of social friends is needed to fulfill sociability and identity needs. The two models were evaluated by comparing the relative influence of the confidant variable with the peer group variable on subject's well-being. Regression analysis was carried out on the well-being measure using as predictor variables the confidant variable, peer group variable, age, health, and financial status. The confidant and peer group variables were of equal importance to well-being, thus confirming the Weiss model.

Multivariate Analysis of Genotype-Phenotype Association.

PubMed

Mitteroecker, Philipp; Cheverud, James M; Pavlicev, Mihaela

2016-04-01

With the advent of modern imaging and measurement technology, complex phenotypes are increasingly represented by large numbers of measurements, which may not bear biological meaning one by one. For such multivariate phenotypes, studying the pairwise associations between all measurements and all alleles is highly inefficient and prevents insight into the genetic pattern underlying the observed phenotypes. We present a new method for identifying patterns of allelic variation (genetic latent variables) that are maximally associated-in terms of effect size-with patterns of phenotypic variation (phenotypic latent variables). This multivariate genotype-phenotype mapping (MGP) separates phenotypic features under strong genetic control from less genetically determined features and thus permits an analysis of the multivariate structure of genotype-phenotype association, including its dimensionality and the clustering of genetic and phenotypic variables within this association. Different variants of MGP maximize different measures of genotype-phenotype association: genetic effect, genetic variance, or heritability. In an application to a mouse sample, scored for 353 SNPs and 11 phenotypic traits, the first dimension of genetic and phenotypic latent variables accounted for >70% of genetic variation present in all 11 measurements; 43% of variation in this phenotypic pattern was explained by the corresponding genetic latent variable. The first three dimensions together sufficed to account for almost 90% of genetic variation in the measurements and for all the interpretable genotype-phenotype association. Each dimension can be tested as a whole against the hypothesis of no association, thereby reducing the number of statistical tests from 7766 to 3-the maximal number of meaningful independent tests. Important alleles can be selected based on their effect size (additive or nonadditive effect on the phenotypic latent variable). This low dimensionality of the genotype-phenotype map has important consequences for gene identification and may shed light on the evolvability of organisms. Copyright © 2016 by the Genetics Society of America.

Invasibility of mature and 15-year-old deciduous forests by exotic plants

Treesearch

Cynthia D. Huebner; Patrick C. Tobin

2006-01-01

High species richness, resource availability and disturbance are community characteristics associated with forest invasibility. We categorized commonly measured community variables, including species composition, topography, and landscape features, within both mature and 15-year-old clearcuts in West Virginia, USA. We evaluated the importance of each variable for...

Centering Effects in HLM Level-1 Predictor Variables.

ERIC Educational Resources Information Center

Schumacker, Randall E.; Bembry, Karen

Research has suggested that important research questions can be addressed with meaningful interpretations using hierarchical linear modeling (HLM). The proper interpretation of results, however, is invariably linked to the choice of centering for the Level-1 predictor variables that produce the outcome measure for the Level-2 regression analysis.…

State Test Results Are Predictable

ERIC Educational Resources Information Center

Tienken, Christopher H.

2014-01-01

Out-of-school, community demographic and family-level variables have an important influence on student achievement as measured by large-scale standardized tests. Studies described here demonstrated that about half of the test score is accounted for by variables outside the control of teachers and school administrators. The results from these…

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…

ARTS III Computer Systems Performance Measurement Prototype Implementation

DOT National Transportation Integrated Search

1974-04-01

Direct measurement of computer systems is of vital importance in: a) developing an intelligent grasp of the variables which affect overall performance; b)tuning the systsem for optimum benefit; c)determining under what conditions saturation threshold...

Assessing medication effects in the MTA study using neuropsychological outcomes.

PubMed

Epstein, Jeffery N; Conners, C Keith; Hervey, Aaron S; Tonev, Simon T; Arnold, L Eugene; Abikoff, Howard B; Elliott, Glen; Greenhill, Laurence L; Hechtman, Lily; Hoagwood, Kimberly; Hinshaw, Stephen P; Hoza, Betsy; Jensen, Peter S; March, John S; Newcorn, Jeffrey H; Pelham, William E; Severe, Joanne B; Swanson, James M; Wells, Karen; Vitiello, Benedetto; Wigal, Timothy

2006-05-01

While studies have increasingly investigated deficits in reaction time (RT) and RT variability in children with attention deficit/hyperactivity disorder (ADHD), few studies have examined the effects of stimulant medication on these important neuropsychological outcome measures. 316 children who participated in the Multimodal Treatment Study of Children with ADHD (MTA) completed the Conners' Continuous Performance Test (CPT) at the 24-month assessment point. Outcome measures included standard CPT outcomes (e.g., errors of commission, mean hit reaction time (RT)) and RT indicators derived from an Ex-Gaussian distributional model (i.e., mu, sigma, and tau). Analyses revealed significant effects of medication across all neuropsychological outcome measures. Results on the Ex-Gaussian outcome measures revealed that stimulant medication slows RT and reduces RT variability. This demonstrates the importance of including analytic strategies that can accurately model the actual distributional pattern, including the positive skew. Further, the results of the study relate to several theoretical models of ADHD.

The vertical dependence in the horizontal variability of salinity and temperature at the ocean surface

NASA Astrophysics Data System (ADS)

Asher, W.; Drushka, K.; Jessup, A. T.; Clark, D.

2016-02-01

Satellite-mounted microwave radiometers measure sea surface salinity (SSS) as an area-averaged quantity in the top centimeter of the ocean over the footprint of the instrument. If the horizontal variability in SSS is large inside this footprint, sub-grid-scale variability in SSS can affect comparison of the satellite-retrieved SSS with in situ measurements. Understanding the magnitude of horizontal variability in SSS over spatial scales that are relevant to the satellite measurements is therefore important. Horizontal variability of SSS at the ocean surface can be studied in situ using data recorded by thermosalinographs (TSGs) that sample water from a depth of a few meters. However, it is possible measurements made at this depth might underestimate the horizontal variability at the surface because salinity and temperature can become vertically stratified in a very near surface layer due to the effects of rain, solar heating, and evaporation. This vertical stratification could prevent horizontal gradients from propagating to the sampling depths of ship-mounted TSGs. This presentation will discuss measurements made using an underway salinity profiling system installed on the R/V Thomas Thompson that made continuous measurements of SSS and SST in the Pacific Ocean. The system samples at nominal depths of 2-m, 3-m, and 5-m, allowing the depth dependence of the horizontal variability in SSS and SST to be measured. Horizontal variability in SST is largest at low wind speeds during daytime, when a diurnal warm layer forms. In contrast, the diurnal signal in the variability of SSS was smaller with variability being slightly larger at night. When studied as a function of depth, the results show that over 100-km scales, the horizontal variability in both SSS and SST at a depth of 2 m is approximately a factor of 4 higher than the variability at 5 m.

Application of kernel principal component analysis and computational machine learning to exploration of metabolites strongly associated with diet.

PubMed

Shiokawa, Yuka; Date, Yasuhiro; Kikuchi, Jun

2018-02-21

Computer-based technological innovation provides advancements in sophisticated and diverse analytical instruments, enabling massive amounts of data collection with relative ease. This is accompanied by a fast-growing demand for technological progress in data mining methods for analysis of big data derived from chemical and biological systems. From this perspective, use of a general "linear" multivariate analysis alone limits interpretations due to "non-linear" variations in metabolic data from living organisms. Here we describe a kernel principal component analysis (KPCA)-incorporated analytical approach for extracting useful information from metabolic profiling data. To overcome the limitation of important variable (metabolite) determinations, we incorporated a random forest conditional variable importance measure into our KPCA-based analytical approach to demonstrate the relative importance of metabolites. Using a market basket analysis, hippurate, the most important variable detected in the importance measure, was associated with high levels of some vitamins and minerals present in foods eaten the previous day, suggesting a relationship between increased hippurate and intake of a wide variety of vegetables and fruits. Therefore, the KPCA-incorporated analytical approach described herein enabled us to capture input-output responses, and should be useful not only for metabolic profiling but also for profiling in other areas of biological and environmental systems.

Fear of pain, pain catastrophizing, and acute pain perception: relative prediction and timing of assessment.

PubMed

Hirsh, Adam T; George, Steven Z; Bialosky, Joel E; Robinson, Michael E

2008-09-01

Pain-related fear and catastrophizing are important variables of consideration in an individual's pain experience. Methodological limitations of previous studies limit strong conclusions regarding these relationships. In this follow-up study, we examined the relationships between fear of pain, pain catastrophizing, and experimental pain perception. One hundred healthy volunteers completed the Fear of Pain Questionnaire (FPQ-III), Pain Catastrophizing Scale (PCS), and Coping Strategies Questionnaire-Catastrophizing scale (CSQ-CAT) before undergoing the cold pressor test (CPT). The CSQ-CAT and PCS were completed again after the CPT, with participants instructed to complete these measures based on their experience during the procedure. Measures of pain threshold, tolerance, and intensity were collected and served as dependent variables in separate regression models. Sex, pain catastrophizing, and pain-related fear were included as predictor variables. Results of regression analyses indicated that after controlling for sex, pain-related fear was a consistently stronger predictor of pain in comparison to catastrophizing. These results were consistent when separate measures (CSQ-CAT vs PCS) and time points (pretask vs "in vivo") of catastrophizing were used. These findings largely corroborate those from our previous study and are suggestive of the absolute and relative importance of pain-related fear in the experimental pain experience. Although pain-related fear has received less attention in the experimental literature than pain catastrophizing, results of the current study are consistent with clinical reports highlighting this variable as an important aspect of the experience of pain.

Acclimatization of the Crustose Coralline Alga Porolithon onkodes to Variable pCO2

PubMed Central

Johnson, Maggie D.; Moriarty, Vincent W.; Carpenter, Robert C.

2014-01-01

Ocean acidification (OA) has important implications for the persistence of coral reef ecosystems, due to potentially negative effects on biomineralization. Many coral reefs are dynamic with respect to carbonate chemistry, and experience fluctuations in pCO2 that exceed OA projections for the near future. To understand the influence of dynamic pCO2 on an important reef calcifier, we tested the response of the crustose coralline alga Porolithon onkodes to oscillating pCO2. Individuals were exposed to ambient (400 µatm), high (660 µatm), or variable pCO2 (oscillating between 400/660 µatm) treatments for 14 days. To explore the potential for coralline acclimatization, we collected individuals from low and high pCO2 variability sites (upstream and downstream respectively) on a back reef characterized by unidirectional water flow in Moorea, French Polynesia. We quantified the effects of treatment on algal calcification by measuring the change in buoyant weight, and on algal metabolism by conducting sealed incubations to measure rates of photosynthesis and respiration. Net photosynthesis was higher in the ambient treatment than the variable treatment, regardless of habitat origin, and there was no effect on respiration or gross photosynthesis. Exposure to high pCO2 decreased P. onkodes calcification by >70%, regardless of the original habitat. In the variable treatment, corallines from the high variability habitat calcified 42% more than corallines from the low variability habitat. The significance of the original habitat for the coralline calcification response to variable, high pCO2 indicates that individuals existing in dynamic pCO2 habitats may be acclimatized to OA within the scope of in situ variability. These results highlight the importance of accounting for natural pCO2 variability in OA manipulations, and provide insight into the potential for plasticity in habitat and species-specific responses to changing ocean chemistry. PMID:24505305

Behavioral biomarkers of aging: illustration of a multivariate approach for detecting age-related behavioral changes.

PubMed

Markowska, A L; Breckler, S J

1999-12-01

The goal of the current project is to develop a multivariate statistical strategy for the formation of behavioral indices of performance and, further, to apply this strategy to establish the relationship between age and important characteristics of performance. The strategy was to begin with a large set of measures that span a broad range of behaviors. The behavioral effects of the following variables were examined: Age (4, 12, 24, and 30 months), genotype [Fischer 344 and a hybrid (F1) of Fischer 344 and Brown Norway (F344xBN)], gender (Fischer 344 males and Fischer 344 females), long-term diet (ad lib diet or dietary restriction beginning at 4 months of age), and short-term diet (ad lib diet or dietary restriction during testing). The behavioral measures were grouped into conceptually related indicators. The indicators within a set were submitted to a principal component analysis to help identify the summary indices of performance, which were formed with the assumption that these component scores would offer more reliable and valid measures of relevant aspects of behavioral performance than would individual measures taken alone. In summary, this approach has made a number of important contributions. It has provided sensitive and selective measures of performance that indicated contributions of all variables: psychological process, age, genotype, gender, long-term and short-term diet and has increased the sensitivity of behavioral measures to age-related behavioral impairment. It has also improved task-manageability by decreasing the number of meaningful variables without losing important information, consequently providing a simplification of the pattern of changes.

Spatial Variability of Snowpack Properties On Small Slopes

NASA Astrophysics Data System (ADS)

Pielmeier, C.; Kronholm, K.; Schneebeli, M.; Schweizer, J.

The spatial variability of alpine snowpacks is created by a variety of parameters like deposition, wind erosion, sublimation, melting, temperature, radiation and metamor- phism of the snow. Spatial variability is thought to strongly control the avalanche initi- ation and failure propagation processes. Local snowpack measurements are currently the basis for avalanche warning services and there exist contradicting hypotheses about the spatial continuity of avalanche active snow layers and interfaces. Very little about the spatial variability of the snowpack is known so far, therefore we have devel- oped a systematic and objective method to measure the spatial variability of snowpack properties, layering and its relation to stability. For a complete coverage, the analysis of the spatial variability has to entail all scales from mm to km. In this study the small to medium scale spatial variability is investigated, i.e. the range from centimeters to tenths of meters. During the winter 2000/2001 we took systematic measurements in lines and grids on a flat snow test field with grid distances from 5 cm to 0.5 m. Fur- thermore, we measured systematic grids with grid distances between 0.5 m and 2 m in undisturbed flat fields and on small slopes above the tree line at the Choerbschhorn, in the region of Davos, Switzerland. On 13 days we measured the spatial pattern of the snowpack stratigraphy with more than 110 snow micro penetrometer measure- ments at slopes and flat fields. Within this measuring grid we placed 1 rutschblock and 12 stuffblock tests to measure the stability of the snowpack. With the large num- ber of measurements we are able to use geostatistical methods to analyse the spatial variability of the snowpack. Typical correlation lengths are calculated from semivari- ograms. Discerning the systematic trends from random spatial variability is analysed using statistical models. Scale dependencies are shown and recurring scaling patterns are outlined. The importance of the small and medium scale spatial variability for the larger (kilometer) scale spatial variability as well as for the avalanche formation are discussed. Finally, an outlook on spatial models for the snowpack variability is given.

The Effects of Media Reports on Disease Spread and Important Public Health Measurements

PubMed Central

Collinson, Shannon; Khan, Kamran; Heffernan, Jane M.

2015-01-01

Controlling the spread of influenza to reduce the effects of infection on a population is an important mandate of public health. Mass media reports on an epidemic or pandemic can provide important information to the public, and in turn, can induce positive healthy behaviour practices (i.e., handwashing, social distancing) in the individuals, that will reduce the probability of contracting the disease. Mass media fatigue, however, can dampen these effects. Mathematical models can be used to study the effects of mass media reports on epidemic/pandemic outcomes. In this study we employ a stochastic agent based model to provide a quantification of mass media reports on the variability in important public health measurements. We also include mass media report data compiled by the Global Public Health Intelligence Network, to study the effects of mass media reports in the 2009 H1N1 pandemic. We find that the report rate and the rate at which individuals relax their healthy behaviours (media fatigue) greatly affect the variability in important public health measurements. When the mass media reporting data is included in the model, two peaks of infection result. PMID:26528909

Computer system performance measurement techniques for ARTS III computer systems.

DOT National Transportation Integrated Search

1973-12-01

Direct measurement of computer systems is of vital importance in: a) developing an intelligent grasp of the variables which affect overall performance; b)tuning the system for optimum benefit; c)determining under what conditions saturation thresholds...

Improving power to detect changes in blood miRNA expression by accounting for sources of variability in experimental designs.

PubMed

Daniels, Sarah I; Sillé, Fenna C M; Goldbaum, Audrey; Yee, Brenda; Key, Ellen F; Zhang, Luoping; Smith, Martyn T; Thomas, Reuben

2014-12-01

Blood miRNAs are a new promising area of disease research, but variability in miRNA measurements may limit detection of true-positive findings. Here, we measured sources of miRNA variability and determine whether repeated measures can improve power to detect fold-change differences between comparison groups. Blood from healthy volunteers (N = 12) was collected at three time points. The miRNAs were extracted by a method predetermined to give the highest miRNA yield. Nine different miRNAs were quantified using different qPCR assays and analyzed using mixed models to identify sources of variability. A larger number of miRNAs from a publicly available blood miRNA microarray dataset with repeated measures were used for a bootstrapping procedure to investigate effects of repeated measures on power to detect fold changes in miRNA expression for a theoretical case-control study. Technical variability in qPCR replicates was identified as a significant source of variability (P < 0.05) for all nine miRNAs tested. Variability was larger in the TaqMan qPCR assays (SD = 0.15-0.61) versus the qScript qPCR assays (SD = 0.08-0.14). Inter- and intraindividual and extraction variability also contributed significantly for two miRNAs. The bootstrapping procedure demonstrated that repeated measures (20%-50% of N) increased detection of a 2-fold change for approximately 10% to 45% more miRNAs. Statistical power to detect small fold changes in blood miRNAs can be improved by accounting for sources of variability using repeated measures and choosing appropriate methods to minimize variability in miRNA quantification. This study demonstrates the importance of including repeated measures in experimental designs for blood miRNA research. See all the articles in this CEBP Focus section, "Biomarkers, Biospecimens, and New Technologies in Molecular Epidemiology." ©2014 American Association for Cancer Research.

Identifying biotic integrity and water chemistry relations in nonwadeable rivers of Wisconsin: Toward the development of nutrient criteria

USGS Publications Warehouse

Weigel, B.M.; Robertson, Dale M.

2007-01-01

We sampled 41 sites on 34 nonwadeable rivers that represent the types of rivers in Wisconsin, and the kinds and intensities of nutrient and other anthropogenic stressors upon each river type. Sites covered much of United States Environmental Protection Agency national nutrient ecoregions VII-Mostly Glaciated Dairy Region, and VIII-Nutrient Poor, Largely Glaciated upper Midwest. Fish, macroinvertebrates, and three categories of environmental variables including nutrients, other water chemistry, and watershed features were collected using standard protocols. We summarized fish assemblages by index of biotic integrity (IBI) and its 10 component measures, and macroinvertebrates by 2 organic pollution tolerance and 12 proportional richness measures. All biotic and environmental variables represented a wide range of conditions, with biotic measures ranging from poor to excellent status, despite nutrient concentrations being consistently higher than reference concentrations reported for the regions. Regression tree analyses of nutrients on a suite of biotic measures identified breakpoints in total phosphorus (~0.06 mg/l) and total nitrogen (~0.64 mg/l) concentrations at which biotic assemblages were consistently impaired. Redundancy analyses (RDA) were used to identify the most important variables within each of the three environmental variable categories, which were then used to determine the relative influence of each variable category on the biota. Nutrient measures, suspended chlorophyll a, water clarity, and watershed land cover type (forest or row-crop agriculture) were the most important variables and they explained significant amounts of variation within the macroinvertebrate (R 2 = 60.6%) and fish (R 2 = 43.6%) assemblages. The environmental variables selected in the macroinvertebrate model were correlated to such an extent that partial RDA analyses could not attribute variation explained to individual environmental categories, assigning 89% of the explained variation to interactions among the categories. In contrast, partial RDA attributed much of the explained variation to the nutrient (25%) and other water chemistry (38%) categories for the fish model. Our analyses suggest that it would be beneficial to develop criteria based upon a suite of biotic and nutrient variables simultaneously to deem waters as not meeting their designated uses. ?? 2007 Springer Science+Business Media, LLC.

Identifying biotic integrity and water chemistry relations in nonwadeable rivers of Wisconsin: toward the development of nutrient criteria.

PubMed

Weigel, Brian M; Robertson, Dale M

2007-10-01

We sampled 41 sites on 34 nonwadeable rivers that represent the types of rivers in Wisconsin, and the kinds and intensities of nutrient and other anthropogenic stressors upon each river type. Sites covered much of United States Environmental Protection Agency national nutrient ecoregions VII--Mostly Glaciated Dairy Region, and VIII--Nutrient Poor, Largely Glaciated upper Midwest. Fish, macroinvertebrates, and three categories of environmental variables including nutrients, other water chemistry, and watershed features were collected using standard protocols. We summarized fish assemblages by index of biotic integrity (IBI) and its 10 component measures, and macroinvertebrates by 2 organic pollution tolerance and 12 proportional richness measures. All biotic and environmental variables represented a wide range of conditions, with biotic measures ranging from poor to excellent status, despite nutrient concentrations being consistently higher than reference concentrations reported for the regions. Regression tree analyses of nutrients on a suite of biotic measures identified breakpoints in total phosphorus (approximately 0.06 mg/l) and total nitrogen (approximately 0.64 mg/l) concentrations at which biotic assemblages were consistently impaired. Redundancy analyses (RDA) were used to identify the most important variables within each of the three environmental variable categories, which were then used to determine the relative influence of each variable category on the biota. Nutrient measures, suspended chlorophyll a, water clarity, and watershed land cover type (forest or row-crop agriculture) were the most important variables and they explained significant amounts of variation within the macroinvertebrate (R(2) = 60.6%) and fish (R(2) = 43.6%) assemblages. The environmental variables selected in the macroinvertebrate model were correlated to such an extent that partial RDA analyses could not attribute variation explained to individual environmental categories, assigning 89% of the explained variation to interactions among the categories. In contrast, partial RDA attributed much of the explained variation to the nutrient (25%) and other water chemistry (38%) categories for the fish model. Our analyses suggest that it would be beneficial to develop criteria based upon a suite of biotic and nutrient variables simultaneously to deem waters as not meeting their designated uses.

Partitioning the variability of fasting plasma glucose levels in pedigrees. Genetic and environmental factors.

PubMed

Boehnke, M; Moll, P P; Kottke, B A; Weidman, W H

1987-04-01

Fasting plasma glucose measurements made in 1972-1977 on normoglycemic individuals in three-generation Caucasian pedigrees from Rochester, Minnesota were analyzed. The authors determined the contributions of polygenic loci and environmental factors to fasting plasma glucose variability in these pedigrees. To that end, fasting plasma glucose measurements were normalized by an inverse normal scores transformation and then regressed separately for males and females on measured concomitants including age, body mass index (weight/height2), season of measurement, sex hormone use, and diuretic use. The authors found that 27.7% of the variability in normalized fasting plasma glucose in these pedigrees is explained by these measured concomitants. Subsequent variance components analysis suggested that unmeasured polygenic loci and unmeasured shared environmental factors together account for at least an additional 36.7% of the variability in normalized fasting plasma glucose, with genes alone accounting for at least 27.3%. These results are consistent with the known familiality of diabetes, for which fasting plasma glucose level is an important predictor. Further, these familial factors provide an explanation for at least half the variability in normalized fasting plasma glucose which remains after regression on known concomitants.

Some Behaviorial Science Measurement Concerns and Proposals.

PubMed

Nesselroade, John R; Molenaar, Peter C M

2016-01-01

Primarily from a measurement standpoint, we question some basic beliefs and procedures characterizing the scientific study of human behavior. The relations between observed and unobserved variables are key to an empirical approach to building explanatory theories and we are especially concerned about how the former are used as proxies for the latter. We believe that behavioral science can profitably reconsider the prevailing version of this arrangement because of its vulnerability to limiting idiosyncratic aspects of observed/unobserved variable relations. We describe a general measurement approach that takes into account idiosyncrasies that should be irrelevant to the measurement process but can intrude and may invalidate it in ways that distort and weaken relations among theoretically important variables. To clarify further our major concerns, we briefly describe one version of the measurement approach that fundamentally supports the individual as the primary unit of analysis orientation that we believe should be preeminent in the scientific study of human behavior.

On measures of association among genetic variables

PubMed Central

Gianola, Daniel; Manfredi, Eduardo; Simianer, Henner

2012-01-01

Summary Systems involving many variables are important in population and quantitative genetics, for example, in multi-trait prediction of breeding values and in exploration of multi-locus associations. We studied departures of the joint distribution of sets of genetic variables from independence. New measures of association based on notions of statistical distance between distributions are presented. These are more general than correlations, which are pairwise measures, and lack a clear interpretation beyond the bivariate normal distribution. Our measures are based on logarithmic (Kullback-Leibler) and on relative ‘distances’ between distributions. Indexes of association are developed and illustrated for quantitative genetics settings in which the joint distribution of the variables is either multivariate normal or multivariate-t, and we show how the indexes can be used to study linkage disequilibrium in a two-locus system with multiple alleles and present applications to systems of correlated beta distributions. Two multivariate beta and multivariate beta-binomial processes are examined, and new distributions are introduced: the GMS-Sarmanov multivariate beta and its beta-binomial counterpart. PMID:22742500

Application of automated measurement stations for continuous water quality monitoring of the Dender river in Flanders, Belgium.

PubMed

Vandenberghe, V; Goethals, P L M; Van Griensven, A; Meirlaen, J; De Pauw, N; Vanrolleghem, P; Bauwens, W

2005-09-01

During the summer of 1999, two automated water quality measurement stations were installed along the Dender river in Belgium. The variables dissolved oxygen, temperature, conductivity, pH, rain-intensity, flow and solar radiation were measured continuously. In this paper these on-line measurement series are presented and interpreted using also additional measurements and ecological expert-knowledge. The purpose was to demonstrate the variability in time and space of the aquatic processes and the consequences of conducting and interpreting discrete measurements for river quality assessment and management. The large fluctuations of the data illustrated the importance of continuous measurements for the complete description and modelling of the biological processes in the river.

Wind direction variability in Afternoon and Sunset Turbulence

NASA Astrophysics Data System (ADS)

Nilsson, Erik; Lothon, Marie; Lohou, Fabienne; Mahrt, Larry

2014-05-01

Understanding wind direction (WD) variability better is important for several reasons. Air pollution models need information about how variable wind direction is in different conditions (Davies and Thomson 1999). Accurate predictions of dispersion are important for human health and safety and allow for adaptation planning (Nagle et al. 2011). Other applications include horizontal diffusion, efficiency and fatigue of wind machines and air-sea interaction (Mahrt 2011). Most studies of wind direction variability have focused on nocturnal conditions because of greater variability in light winds. Modelling WD variability in transition periods when both mean wind speed and variance of the wind components are in a state of change can, however, also be very challenging and has not been the focus of earlier studies. The evening transitioning to the nocturnal boundary layer can play an important role in the diffusion process of pollutants and scalars emitted at surface and transported within the atmosphere. The Boundary Layer Late Afternoon and Sunset Turbulence (BLLAST) field campaign that took place in southern France in June and July 2011 focused on the decaying turbulence of the late afternoon boundary layer and related issues (Lothon et al. 2012). We analyse field measurements from BLLAST to investigate WD variability in the evening transition period. Standard deviations of horizontal wind direction fluctuations in the lowest 60 m of the boundary layer have been examined for dependence on mean wind speed, higher order moments and averaging time. Measurement results are interpreted using measured and idealized probability density functions of horizontal wind vectors. These are also used to develop analytical functions describing how WD variability depends on wind speed, variance and other controlling factors in the atmospheric boundary layer. References: Davies B.M., Thomson D.J., 1999. Comparison of some parameterizations of wind direction variability with observations, Atmospheric Enviroment 33, 4909-4917. Lothon M. et al., 2012. The Boundary-Layer Late Afternoon and Sunset Turbulence field experiment, Proc. of the 20th Symposium on Boundary-Layers and Turbulence, 7-13 July, Boston, MA, USA. Mahrt L., 2011. Surface Wind Direction Variability, Journal of Applied Meteorology and Climatology 50. 144-152. Nagle J.C., 2011. Adapting to Pollution, Research Roundtable on Climate Change, Adaptation, and Enviromental Law, Northwestern Law Searle Center, Legal and Regulatory Studies 7-18 April, IL, USA.

Gender differences in foot shape: a study of Chinese young adults.

PubMed

Hong, Youlian; Wang, Lin; Xu, Dong Qing; Li, Jing Xian

2011-06-01

One important extrinsic factor that causes foot deformity and pain in women is footwear. Women's sports shoes are designed as smaller versions of men's shoes. Based on this, the current study aims to identify foot shape in 1,236 Chinese young adult men and 1,085 Chinese young adult women. Three-dimensional foot shape data were collected through video filming. Nineteen foot shape variables were measured, including girth (4 variables), length (4 variables), width (3 variables), height (7 variables), and angle (1 variable). A comparison of foot measures within the range of the common foot length (FL) categories indicates that women showed significantly smaller values of foot measures in width, height, and girth than men. Three foot types were classified, and distributions of different foot shapes within the same FL were found between women and men. Foot width, medial ball length, ball angle, and instep height showed significant differences among foot types in the same FL for both genders. There were differences in the foot shape between Chinese young women and men, which should be considered in the design of Chinese young adults' sports shoes.

An hourly variation in zoo visitor interest: measurement and significance for animal welfare research.

PubMed

Davey, Gareth

2006-01-01

A methodological difficulty facing welfare research on nonhuman animals in the zoo is the large number of uncontrolled variables due to variation within and between study sites. Zoo visitors act as uncontrolled variables, with number, density, size, and behavior constantly changing. This is worrisome because previous research linked visitor variables to animal behavioral changes indicative of stress. There are implications for research design: Studies not accounting for visitors' effect on animal welfare risk confounding (visitor) variables distorting their findings. Zoos need methods to measure and minimize effects of visitor behavior and to ensure that there are no hidden variables in research models. This article identifies a previously unreported variable--hourly variation (decrease) in visitor interest--that may impinge on animal welfare and validates a methodology for measuring it. That visitor interest wanes across the course of the day has important implications for animal welfare management; visitor effects on animal welfare are likely to occur, or intensify, during the morning or in earlier visits when visitor interest is greatest. This article discusses this issue and possible solutions to reduce visitor effects on animal well-being.

Importance of physical and hydraulic characteristics to unionid mussels: A retrospective analysis in a reach of large river

USGS Publications Warehouse

Zigler, S.J.; Newton, T.J.; Steuer, J.J.; Bartsch, M.R.; Sauer, J.S.

2008-01-01

Interest in understanding physical and hydraulic factors that might drive distribution and abundance of freshwater mussels has been increasing due to their decline throughout North America. We assessed whether the spatial distribution of unionid mussels could be predicted from physical and hydraulic variables in a reach of the Upper Mississippi River. Classification and regression tree (CART) models were constructed using mussel data compiled from various sources and explanatory variables derived from GIS coverages. Prediction success of CART models for presence-absence of mussels ranged from 71 to 76% across three gears (brail, sled-dredge, and dive-quadrat) and 51% of the deviance in abundance. Models were largely driven by shear stress and substrate stability variables, but interactions with simple physical variables, especially slope, were also important. Geospatial models, which were based on tree model results, predicted few mussels in poorly connected backwater areas (e.g., floodplain lakes) and the navigation channel, whereas main channel border areas with high geomorphic complexity (e.g., river bends, islands, side channel entrances) and small side channels were typically favorable to mussels. Moreover, bootstrap aggregation of discharge-specific regression tree models of dive-quadrat data indicated that variables measured at low discharge were about 25% more predictive (PMSE = 14.8) than variables measured at median discharge (PMSE = 20.4) with high discharge (PMSE = 17.1) variables intermediate. This result suggests that episodic events such as droughts and floods were important in structuring mussel distributions. Although the substantial mussel and ancillary data in our study reach is unusual, our approach to develop exploratory statistical and geospatial models should be useful even when data are more limited. ?? 2007 Springer Science+Business Media B.V.

Ground-based measurement of surface temperature and thermal emissivity

NASA Technical Reports Server (NTRS)

Owe, M.; Van De Griend, A. A.

1994-01-01

Motorized cable systems for transporting infrared thermometers have been used successfully during several international field campaigns. Systems may be configured with as many as four thermal sensors up to 9 m above the surface, and traverse a 30 m transect. Ground and canopy temperatures are important for solving the surface energy balance. The spatial variability of surface temperature is often great, so that averaged point measurements result in highly inaccurate areal estimates. The cable systems are ideal for quantifying both temporal and spatial variabilities. Thermal emissivity is also necessary for deriving the absolute physical temperature, and measurements may be made with a portable measuring box.

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.

Seasonal variability of near surface soil water and groundwater tables in Florida : phase II.

DOT National Transportation Integrated Search

2008-01-01

The seasonal high groundwater table (SHGWT) is a critical measure for design projects requiring : surface water permits including roadway design and detention or retention pond design. Accurately : measuring and, more importantly, predicting water ta...

TEMPORAL VARIABILITY MEASUREMENT OF SPECIFIC VOLATILE ORGANIC COMPOUNDS

EPA Science Inventory

Methodology was developed to determine unambiguously trace levels of volatile organic compounds as they vary in concentration over a variety of time scales. his capability is important because volatile organic compounds (VOCs) are usually measure by time-integrative techniques th...

A rigorous assessment of tree height measurements obtained using airborne LIDAR and conventional field methods.

Treesearch

Hans-Erik Andersen; Stephen E. Reutebuch; Robert J. McGaughey

2006-01-01

Tree height is an important variable in forest inventory programs but is typically time-consuming and costly to measure in the field using conventional techniques. Airborne light detection and ranging (LIDAR) provides individual tree height measurements that are highly correlated with field-derived measurements, but the imprecision of conventional field techniques does...

Human and methodological sources of variability in the measurement of urinary 8-oxo-7,8-dihydro-2'-deoxyguanosine.

PubMed

Barregard, Lars; Møller, Peter; Henriksen, Trine; Mistry, Vilas; Koppen, Gudrun; Rossner, Pavel; Sram, Radim J; Weimann, Allan; Poulsen, Henrik E; Nataf, Robert; Andreoli, Roberta; Manini, Paola; Marczylo, Tim; Lam, Patricia; Evans, Mark D; Kasai, Hiroshi; Kawai, Kazuaki; Li, Yun-Shan; Sakai, Kazuo; Singh, Rajinder; Teichert, Friederike; Farmer, Peter B; Rozalski, Rafal; Gackowski, Daniel; Siomek, Agnieszka; Saez, Guillermo T; Cerda, Concha; Broberg, Karin; Lindh, Christian; Hossain, Mohammad Bakhtiar; Haghdoost, Siamak; Hu, Chiung-Wen; Chao, Mu-Rong; Wu, Kuen-Yuh; Orhan, Hilmi; Senduran, Nilufer; Smith, Raymond J; Santella, Regina M; Su, Yali; Cortez, Czarina; Yeh, Susan; Olinski, Ryszard; Loft, Steffen; Cooke, Marcus S

2013-06-20

Urinary 8-oxo-7,8-dihydro-2'-deoxyguanosine (8-oxodG) is a widely used biomarker of oxidative stress. However, variability between chromatographic and ELISA methods hampers interpretation of data, and this variability may increase should urine composition differ between individuals, leading to assay interference. Furthermore, optimal urine sampling conditions are not well defined. We performed inter-laboratory comparisons of 8-oxodG measurement between mass spectrometric-, electrochemical- and ELISA-based methods, using common within-technique calibrants to analyze 8-oxodG-spiked phosphate-buffered saline and urine samples. We also investigated human subject- and sample collection-related variables, as potential sources of variability. Chromatographic assays showed high agreement across urines from different subjects, whereas ELISAs showed far more inter-laboratory variation and generally overestimated levels, compared to the chromatographic assays. Excretion rates in timed 'spot' samples showed strong correlations with 24 h excretion (the 'gold' standard) of urinary 8-oxodG (rp 0.67-0.90), although the associations were weaker for 8-oxodG adjusted for creatinine or specific gravity (SG). The within-individual excretion of 8-oxodG varied only moderately between days (CV 17% for 24 h excretion and 20% for first void, creatinine-corrected samples). This is the first comprehensive study of both human and methodological factors influencing 8-oxodG measurement, providing key information for future studies with this important biomarker. ELISA variability is greater than chromatographic assay variability, and cannot determine absolute levels of 8-oxodG. Use of standardized calibrants greatly improves intra-technique agreement and, for the chromatographic assays, importantly allows integration of results for pooled analyses. If 24 h samples are not feasible, creatinine- or SG-adjusted first morning samples are recommended.

Comparison of High-Frequency Solar Irradiance: Ground Measured vs. Satellite-Derived

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

Lave, Matthew; Weekley, Andrew

2016-11-21

High-frequency solar variability is an important to grid integration studies, but ground measurements are scarce. The high resolution irradiance algorithm (HRIA) has the ability to produce 4-sceond resolution global horizontal irradiance (GHI) samples, at locations across North America. However, the HRIA has not been extensively validated. In this work, we evaluate the HRIA against a database of 10 high-frequency ground-based measurements of irradiance. The evaluation focuses on variability-based metrics. This results in a greater understanding of the errors in the HRIA as well as suggestions for improvement to the HRIA.

Habitat characteristics affecting fish assemblages on a Hawaiian coral reef

USGS Publications Warehouse

Friedlander, A.M.; Parrish, J.D.

1998-01-01

Habitat characteristics of a reef were examined as potential influences on fish assemblage structure, using underwater visual census to estimate numbers and biomass of all fishes visible on 42 benthic transects and making quantitative measurements of 13 variables of the corresponding physical habitat and sessile biota. Fish assemblages in the diverse set of benthic habitats were grouped by detrended correspondence analysis, and associated with six major habitat types. Statistical differences were shown between a number of these habitat types for various ensemble variables of the fish assemblages. Overall, both for complete assemblages and for component major trophic and mobility guilds, these variables tended to have higher values where reef substratum was more structurally or topographically complex, and closer to reef edges. When study sites were separately divided into five depth strata, the deeper strata tended to have statistically higher values of ensemble variables for the fish assemblages. Patterns with depth varied among the various trophic and mobility guilds. Multiple linear regression models indicated that for the complete assemblages and for most trophic and mobility guilds, a large part of the variability for most ensemble variables was explained by measures of holes in the substratum, with important contributions from measured substratum rugosity and depth. A strong linear relationship found by regression of mean fish length on mean volume of holes in the reef surface emphasized the importance of shelter for fish assemblages. Results of this study may have practical applications in designing reserve areas as well as theoretical value in helping to explain the organization of reef fish assemblages.

Assessing the accuracy and stability of variable selection ...

EPA Pesticide Factsheets

Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological datasets there is limited guidance on variable selection methods for RF modeling. Typically, either a preselected set of predictor variables are used, or stepwise procedures are employed which iteratively add/remove variables according to their importance measures. This paper investigates the application of variable selection methods to RF models for predicting probable biological stream condition. Our motivating dataset consists of the good/poor condition of n=1365 stream survey sites from the 2008/2009 National Rivers and Stream Assessment, and a large set (p=212) of landscape features from the StreamCat dataset. Two types of RF models are compared: a full variable set model with all 212 predictors, and a reduced variable set model selected using a backwards elimination approach. We assess model accuracy using RF's internal out-of-bag estimate, and a cross-validation procedure with validation folds external to the variable selection process. We also assess the stability of the spatial predictions generated by the RF models to changes in the number of predictors, and argue that model selection needs to consider both accuracy and stability. The results suggest that RF modeling is robust to the inclusion of many variables of moderate to low importance. We found no substanti

Interpersonal problem-solving deficits in self-poisoning patients.

PubMed

McLeavey, B C; Daly, R J; Murray, C M; O'Riordan, J; Taylor, M

1987-01-01

Self-poisoning patients (n = 40) were compared with psychiatric patients (n = 40) and nonpatient controls (n = 20) on measures of interpersonal problem-solving skills and locus of control in an effort to determine the importance of these cognitive and personality variables in self-poisoning behavior. The psychiatric and self-poisoning groups showed deficits on measures assessing interpersonal problem solving when compared with nonpatient controls. The self-poisoning group performed below the level of the psychiatric patients on all except one test, on which they performed at the level of the psychiatric group. Locus of control did not differentiate self-poisoning patients from nonpatient controls, and it was concluded that this variable is not an important factor in self-poisoning behavior.

Relationships of field habitat measurements, visual habitat indices, and land cover to benthic macroinvertebrates in urbanized streams of the Santa Clara Valley, California

USGS Publications Warehouse

Fend, S.V.; Carter, J.L.; Kearns, F.R.

2005-01-01

We evaluated several approaches for measuring natural and anthropogenic habitat characteristics to predict benthic macroinvertebrate assemblages over a range of urban intensity at 85 stream sites in the Santa Clara Valley, California. Land cover was summarized as percentage urban land cover and impervious area within upstream buffers and the upstream subwatersheds. Field measurements characterized water chemistry, channel slope, sediment, and riparian canopy. In . addition to applying the visual-based habitat assessment in U.S. Environmental Protection Agency's rapid bioassessment protocol, we developed a simplified urban habitat assessment index based on turbidity, fine sediment deposition, riparian condition, and channel modification. Natural and anthropogenic habitat variables covaried along longitudinal stream gradients and were highly correlated with elevation. At the scale of the entire watershed, benthic macroinvertebrate measures were equally correlated with variables expressing natural gradients and urbanization effects. When natural gradients were reduced by partitioning sites into ecoregion subsection groupings, habitat variables most highly correlated with macroinvertebrate measures differed between upland and valley floor site groups. Among the valley floor sites, channel slope and physical modification of channel and riparian habitats appeared more important than upstream land cover or water quality in determining macroinvertebrate richness and ordination scores. Among upland sites, effects of upstream reservoir releases on habitat quality appeared important. Rapid habitat evaluation methods appeared to be an effective method for describing habitat features important to benthic macroinvertebrates when adapted for the region and the disturbance of interest. ?? 2005 by the American Fisheries Society.

Influence of meteorological variables on rainfall partitioning for deciduous and coniferous tree species in urban area

NASA Astrophysics Data System (ADS)

Zabret, Katarina; Rakovec, Jože; Šraj, Mojca

2018-03-01

Rainfall partitioning is an important part of the ecohydrological cycle, influenced by numerous variables. Rainfall partitioning for pine (Pinus nigra Arnold) and birch (Betula pendula Roth.) trees was measured from January 2014 to June 2017 in an urban area of Ljubljana, Slovenia. 180 events from more than three years of observations were analyzed, focusing on 13 meteorological variables, including the number of raindrops, their diameter, and velocity. Regression tree and boosted regression tree analyses were performed to evaluate the influence of the variables on rainfall interception loss, throughfall, and stemflow in different phenoseasons. The amount of rainfall was recognized as the most influential variable, followed by rainfall intensity and the number of raindrops. Higher rainfall amount, intensity, and the number of drops decreased percentage of rainfall interception loss. Rainfall amount and intensity were the most influential on interception loss by birch and pine trees during the leafed and leafless periods, respectively. Lower wind speed was found to increase throughfall, whereas wind direction had no significant influence. Consideration of drop size spectrum properties proved to be important, since the number of drops, drop diameter, and median volume diameter were often recognized as important influential variables.

Incorporating Measurement Nonequivalence in a Cross-Study Latent Growth Curve Analysis

ERIC Educational Resources Information Center

Flora, David B.; Curran, Patrick J.; Hussong, Andrea M.; Edwards, Michael C.

2008-01-01

A large literature emphasizes the importance of testing for measurement equivalence in scales that may be used as observed variables in structural equation modeling applications. When the same construct is measured across more than one developmental period, as in a longitudinal study, it can be especially critical to establish measurement…

Fuel temperature counter

Treesearch

John R. Murray; Charles W. Philpot

1963-01-01

Fuel temperature is and has always been difficult to measure. To understand better the problem of fire and fire weather behavior, it is important to measure this variable. We have developed for field use a new fuel temperature counter which can be used to obtain such measurements quickly and easily. This electronic recording instrument is easy to construct and operate...

Use of Wearable Sensors and Biometric Variables in an Artificial Pancreas System.

PubMed

Turksoy, Kamuran; Monforti, Colleen; Park, Minsun; Griffith, Garett; Quinn, Laurie; Cinar, Ali

2017-03-07

An artificial pancreas (AP) computes the optimal insulin dose to be infused through an insulin pump in people with Type 1 Diabetes (T1D) based on information received from a continuous glucose monitoring (CGM) sensor. It has been recognized that exercise is a major challenge in the development of an AP system. The use of biometric physiological variables in an AP system may be beneficial for prevention of exercise-induced challenges and better glucose regulation. The goal of the present study is to find a correlation between biometric variables such as heart rate (HR), heat flux (HF), skin temperature (ST), near-body temperature (NBT), galvanic skin response (GSR), and energy expenditure (EE), 2D acceleration-mean of absolute difference (MAD) and changes in glucose concentrations during exercise via partial least squares (PLS) regression and variable importance in projection (VIP) in order to determine which variables would be most useful to include in a future artificial pancreas. PLS and VIP analyses were performed on data sets that included seven different types of exercises. Data were collected from 26 clinical experiments. Clinical results indicate ST to be the most consistently important (important for six out of seven tested exercises) variable over all different exercises tested. EE and HR are also found to be important variables over several types of exercise. We also found that the importance of GSR and NBT observed in our experiments might be related to stress and the effect of changes in environmental temperature on glucose concentrations. The use of the biometric measurements in an AP system may provide better control of glucose concentration.

Relative importance of expertise, lifting height and weight lifted on posture and lumbar external loading during a transfer task in manual material handling.

PubMed

Plamondon, André; Larivière, Christian; Delisle, Alain; Denis, Denys; Gagnon, Denis

2012-01-01

The objective of this study was to measure the effect size of three important factors in manual material handling, namely expertise, lifting height and weight lifted. The effect of expertise was evaluated by contrasting 15 expert and 15 novice handlers, the effect of the weight lifted with a 15-kg box and a 23-kg box and the effect of lifting height with two different box heights: ground level and a 32 cm height. The task consisted of transferring a series of boxes from a conveyor to a hand trolley. Lifting height and weight lifted had more effect size than expertise on external back loading variables (moments) while expertise had low impact. On the other hand, expertise showed a significant effect of posture variables on the lumbar spine and knees. All three factors are important, but for a reduction of external back loading, the focus should be on the lifting height and weight lifted. The objective was to measure the effect size of three important factors in a transfer of boxes from a conveyor to a hand trolley. Lifting height and weight lifted had more effect size than expertise on external back loading variables but expertise was a major determinant in back posture.

The Impact of Sub-Skills and Item Content on Students' Skills with Regard to the Control-of-Variables Strategy

ERIC Educational Resources Information Center

Schwichow, Martin; Christoph, Simon; Boone, William J.; Härtig, Hendrik

2016-01-01

The so-called control-of-variables strategy (CVS) incorporates the important scientific reasoning skills of designing controlled experiments and interpreting experimental outcomes. As CVS is a prominent component of science standards appropriate assessment instruments are required to measure these scientific reasoning skills and to evaluate the…

The Prediction of Labor Force Status: Implications from International Adult Skill Assessments. Research Report. ETS RR-16-11

ERIC Educational Resources Information Center

Li, Tongyun; von Davier, Matthias; Hancock, Gregory R.

2016-01-01

This report investigates the prediction of labor force status using observed variables, such as gender, age, and immigrant status, and more importantly, measured skill variables, including literacy proficiency and a categorical rating of educational attainment based on the 1994 International Adult Literacy Survey (IALS), the 2003 Adult Literacy…

Communication cost of simulating Bell correlations.

PubMed

Toner, B F; Bacon, D

2003-10-31

What classical resources are required to simulate quantum correlations? For the simplest and most important case of local projective measurements on an entangled Bell pair state, we show that exact simulation is possible using local hidden variables augmented by just one bit of classical communication. Certain quantum teleportation experiments, which teleport a single qubit, therefore admit a local hidden variables model.

Evaluation of anti-migration properties of biliary covered self-expandable metal stents.

PubMed

Minaga, Kosuke; Kitano, Masayuki; Imai, Hajime; Harwani, Yogesh; Yamao, Kentaro; Kamata, Ken; Miyata, Takeshi; Omoto, Shunsuke; Kadosaka, Kumpei; Sakurai, Toshiharu; Nishida, Naoshi; Kudo, Masatoshi

2016-08-14

To assess anti-migration potential of six biliary covered self-expandable metal stents (C-SEMSs) by using a newly designed phantom model. In the phantom model, the stent was placed in differently sized holes in a silicone wall and retracted with a retraction robot. Resistance force to migration (RFM) was measured by a force gauge on the stent end. Radial force (RF) was measured with a RF measurement machine. Measured flare structure variables were the outer diameter, height, and taper angle of the flare (ODF, HF, and TAF, respectively). Correlations between RFM and RF or flare variables were analyzed using a linear correlated model. Out of the six stents, five stents were braided, the other was laser-cut. The RF and RFM of each stent were expressed as the average of five replicate measurements. For all six stents, RFM and RF decreased as the hole diameter increased. For all six stents, RFM and RF correlated strongly when the stent had not fully expanded. This correlation was not observed in the five braided stents excluding the laser cut stent. For all six stents, there was a strong correlation between RFM and TAF when the stent fully expanded. For the five braided stents, RFM after full stent expansion correlated strongly with all three stent flare structure variables (ODF, HF, and TAF). The laser-cut C-SEMS had higher RFMs than the braided C-SEMSs regardless of expansion state. RF was an important anti-migration property when the C-SEMS did not fully expand. Once fully expanded, stent flare structure variables plays an important role in anti-migration.

Video Game Telemetry as a Critical Tool in the Study of Complex Skill Learning

PubMed Central

Thompson, Joseph J.; Blair, Mark R.; Chen, Lihan; Henrey, Andrew J.

2013-01-01

Cognitive science has long shown interest in expertise, in part because prediction and control of expert development would have immense practical value. Most studies in this area investigate expertise by comparing experts with novices. The reliance on contrastive samples in studies of human expertise only yields deep insight into development where differences are important throughout skill acquisition. This reliance may be pernicious where the predictive importance of variables is not constant across levels of expertise. Before the development of sophisticated machine learning tools for data mining larger samples, and indeed, before such samples were available, it was difficult to test the implicit assumption of static variable importance in expertise development. To investigate if this reliance may have imposed critical restrictions on the understanding of complex skill development, we adopted an alternative method, the online acquisition of telemetry data from a common daily activity for many: video gaming. Using measures of cognitive-motor, attentional, and perceptual processing extracted from game data from 3360 Real-Time Strategy players at 7 different levels of expertise, we identified 12 variables relevant to expertise. We show that the static variable importance assumption is false - the predictive importance of these variables shifted as the levels of expertise increased - and, at least in our dataset, that a contrastive approach would have been misleading. The finding that variable importance is not static across levels of expertise suggests that large, diverse datasets of sustained cognitive-motor performance are crucial for an understanding of expertise in real-world contexts. We also identify plausible cognitive markers of expertise. PMID:24058656

Video game telemetry as a critical tool in the study of complex skill learning.

PubMed

Thompson, Joseph J; Blair, Mark R; Chen, Lihan; Henrey, Andrew J

2013-01-01

Cognitive science has long shown interest in expertise, in part because prediction and control of expert development would have immense practical value. Most studies in this area investigate expertise by comparing experts with novices. The reliance on contrastive samples in studies of human expertise only yields deep insight into development where differences are important throughout skill acquisition. This reliance may be pernicious where the predictive importance of variables is not constant across levels of expertise. Before the development of sophisticated machine learning tools for data mining larger samples, and indeed, before such samples were available, it was difficult to test the implicit assumption of static variable importance in expertise development. To investigate if this reliance may have imposed critical restrictions on the understanding of complex skill development, we adopted an alternative method, the online acquisition of telemetry data from a common daily activity for many: video gaming. Using measures of cognitive-motor, attentional, and perceptual processing extracted from game data from 3360 Real-Time Strategy players at 7 different levels of expertise, we identified 12 variables relevant to expertise. We show that the static variable importance assumption is false--the predictive importance of these variables shifted as the levels of expertise increased--and, at least in our dataset, that a contrastive approach would have been misleading. The finding that variable importance is not static across levels of expertise suggests that large, diverse datasets of sustained cognitive-motor performance are crucial for an understanding of expertise in real-world contexts. We also identify plausible cognitive markers of expertise.

Variability in PAH-DNA adduct measurements in peripheral mononuclear cells: implications for quantitative cancer risk assessment.

PubMed

Dickey, C; Santella, R M; Hattis, D; Tang, D; Hsu, Y; Cooper, T; Young, T L; Perera, F P

1997-10-01

Biomarkers such as DNA adducts have significant potential to improve quantitative risk assessment by characterizing individual differences in metabolism of genotoxins and DNA repair and accounting for some of the factors that could affect interindividual variation in cancer risk. Inherent uncertainty in laboratory measurements and within-person variability of DNA adduct levels over time are putatively unrelated to cancer risk and should be subtracted from observed variation to better estimate interindividual variability of response to carcinogen exposure. A total of 41 volunteers, both smokers and nonsmokers, were asked to provide a peripheral blood sample every 3 weeks for several months in order to specifically assess intraindividual variability of polycyclic aromatic hydrocarbon (PAH)-DNA adduct levels. The intraindividual variance in PAH-DNA adduct levels, together with measurement uncertainty (laboratory variability and unaccounted for differences in exposure), constituted roughly 30% of the overall variance. An estimated 70% of the total variance was contributed by interindividual variability and is probably representative of the true biologic variability of response to carcinogenic exposure in lymphocytes. The estimated interindividual variability in DNA damage after subtracting intraindividual variability and measurement uncertainty was 24-fold. Inter-individual variance was higher (52-fold) in persons who constitutively lack the Glutathione S-Transferase M1 (GSTM1) gene which is important in the detoxification pathway of PAH. Risk assessment models that do not consider the variability of susceptibility to DNA damage following carcinogen exposure may underestimate risks to the general population, especially for those people who are most vulnerable.

A comparison of technologies used for estimation of body temperature.

PubMed

Mangat, Jasdip; Standley, Thomas; Prevost, Andrew; Vasconcelos, Joana; White, Paul

2010-09-01

Body temperature measurement is an important clinical parameter. The performance of a number of non-invasive thermometers was measured by comparing intra- and inter-operator variability (n = 100) and clinical accuracy (n = 61). Variability was elevated in febrile compared to normothermic subjects for axillary and oral electronic contact thermometer measures and a temporal artery thermometer (p < 0.001 for both). Temporal artery thermometry and one mode of an infrared tympanic thermometer demonstrated significant clinical inaccuracy (p < 0.001 for both). Electronic contact thermometer repeatability and reproducibility are highly variable in febrile adults both in the axilla and oral cavity. Infrared thermometry of the skin over the superficial temporal artery is unreliable for measuring core body temperature, particularly in febrile subjects and patients in theatre. The infrared tympanic thermometers tested are acceptable for clinical practice; however, care should be exercised with the different modes of operation offered.

Exploring factors related to physical activity in cervical dystonia.

PubMed

Zetterberg, Lena; Urell, Charlotte; Anens, Elisabeth

2015-12-01

People with disabilities have reported worse health status than people without disabilities and receiving fewer preventive health services such as counseling around exercise habits. This is noteworthy considering the negative consequences associated with physical inactivity. No research has been conducted on physical activity in cervical dystonia (CD), despite its possible major impact on self-perceived health and disability. Considering the favorable consequences associated with physical activity it is important to know how to promote physical activity behavior in CD. Knowledge of variables important for such behavior in CD is therefore crucial. The aim of this study was to explore factors related to physical activity in individuals with cervical dystonia. Subjects included in this cross-sectional study were individuals diagnosed with CD and enrolled at neurology clinics (n = 369). Data was collected using one surface mailed self-reported questionnaire. Physical activity was the primary outcome variable, measured with the Physical Activity Disability Survey. Secondary outcome variables were: impact of dystonia measured with the Cervical Dystonia Impact Scale; fatigue measured with the Fatigue Severity Scale; confidence when carrying out physical activity measured with the Exercise Self-Efficacy Scale; confidence in performing daily activities without falling measured with the Falls Efficacy Scale; enjoyment of activity measured with Enjoyment of Physical Activity Scale, and social influences on physical activity measured with Social Influences on Physical Activity in addition to demographic characteristics such as age, education level and employment status. The questionnaire was completed by 173 individuals (47% response rate). The multivariate association between related variables and physical activity showed that employment, self-efficacy for physical activity, education level and consequences for daily activities explained 51% of the variance in physical activity (Adj R 0.51, F (5, 162) = 35.611, p = 0.000). Employment and self-efficacy for physical activity contributed most strongly to the association with physical activity. Considering the favorable consequences associated with physical activity it could be important to support the individuals with CD to remain in work and self-efficacy to physical activity as employment and self-efficacy had significant influence on physical activity level. Future research is needed to evaluate causal effects of physical activity on consequences related to CD.

Importance of fishing as a segmentation variable in the application of a social worlds model

USGS Publications Warehouse

Gigliotti, Larry M.; Chase, Loren

2017-01-01

Market segmentation is useful to understanding and classifying the diverse range of outdoor recreation experiences sought by different recreationists. Although many different segmentation methodologies exist, many are complex and difficult to measure accurately during in-person intercepts, such as that of creel surveys. To address that gap in the literature, we propose a single-item measure of the importance of fishing as a surrogate to often overly- or needlesslycomplex segmentation techniques. The importance of fishing item is a measure of the value anglers place on the activity or a coarse quantification of how central the activity is to the respondent’s lifestyle (scale: 0 = not important, 1 = slightly, 2 = moderately, 3 = very, and 4 = fishing is my most important recreational activity). We suggest the importance scale may be a proxy measurement for segmenting anglers using the social worlds model as a theoretical framework. Vaske (1980) suggested that commitment to recreational activities may be best understood in relation to social group participation and the social worlds model provides a rich theoretical framework for understanding social group segments. Unruh (1983) identified four types of actor involvement in social worlds: strangers, tourists, regulars, and insiders, differentiated by four characteristics (orientation, experiences, relationships, and commitment). We evaluated the importance of fishing as a segmentation variable using data collected by a mixed-mode survey of South Dakota anglers fishing in 2010. We contend that this straightforward measurement may be useful for segmenting outdoor recreation activities when more complicated segmentation schemes are not suitable. Further, this index, when coupled with the social worlds model, provides a valuable framework for understanding the segments and making management decisions.

Patients' preferences for different corticosteroid vehicles are highly variable.

PubMed

Felix, Kayla; Unrue, Emily; Inyang, Meyene; Cardwell, Leah A; Oussedik, Elias; Richardson, Irma; Feldman, Steven R

2018-05-17

Topical corticosteroids, available in an array of vehicles are used to control a variety of inflammatory skin diseases. Patients' preferences for different vehicles may affect their willingness to use treatment. We assess corticosteroid vehicle preference and potential impact of topical characteristics on adherence and quality of life in patients with psoriasis. Subjects with psoriasis were recruited from Wake Forest University Dermatology Clinic. Subjects sampled desoximetasone 0.25% spray, betamethasone valerate 0.1% cream, triamcinolone acetonide 0.1% ointment, fluocinonide 0.05% gel, betamethasone valerate 0.1% lotion, clobetasol propionate 0.05% foam, and fluocinonide 0.05% solution in a predetermined randomized order. Subjects completed a Vehicle Preference Measure, Determinants of Adherence Measure and a Determinants of Quality of Life Measure. Patients preferences for the various products were highly variable. Regarding determinants of adherence, patients' perception of absorption of the medication was ranked as 'quite important/extremely important' by 85% of total subjects. A majority of patients rated medication side effects as 'quite important/extremely important' when asked to consider topical characteristics' effect on quality of life. There was wide variation in patient preference for topical medication vehicles used for treating psoriasis. Several vehicle characteristics were considered important to adherence. Given the marked variation in vehicle preference, topical treatment should be individualized according to patients' preferences.

Sensitivity study on durability variables of marine concrete structures

NASA Astrophysics Data System (ADS)

Zhou, Xin'gang; Li, Kefei

2013-06-01

In order to study the influence of parameters on durability of marine concrete structures, the parameter's sensitivity analysis was studied in this paper. With the Fick's 2nd law of diffusion and the deterministic sensitivity analysis method (DSA), the sensitivity factors of apparent surface chloride content, apparent chloride diffusion coefficient and its time dependent attenuation factor were analyzed. The results of the analysis show that the impact of design variables on concrete durability was different. The values of sensitivity factor of chloride diffusion coefficient and its time dependent attenuation factor were higher than others. Relative less error in chloride diffusion coefficient and its time dependent attenuation coefficient induces a bigger error in concrete durability design and life prediction. According to probability sensitivity analysis (PSA), the influence of mean value and variance of concrete durability design variables on the durability failure probability was studied. The results of the study provide quantitative measures of the importance of concrete durability design and life prediction variables. It was concluded that the chloride diffusion coefficient and its time dependent attenuation factor have more influence on the reliability of marine concrete structural durability. In durability design and life prediction of marine concrete structures, it was very important to reduce the measure and statistic error of durability design variables.

Empirical spatial econometric modelling of small scale neighbourhood

NASA Astrophysics Data System (ADS)

Gerkman, Linda

2012-07-01

The aim of the paper is to model small scale neighbourhood in a house price model by implementing the newest methodology in spatial econometrics. A common problem when modelling house prices is that in practice it is seldom possible to obtain all the desired variables. Especially variables capturing the small scale neighbourhood conditions are hard to find. If there are important explanatory variables missing from the model, the omitted variables are spatially autocorrelated and they are correlated with the explanatory variables included in the model, it can be shown that a spatial Durbin model is motivated. In the empirical application on new house price data from Helsinki in Finland, we find the motivation for a spatial Durbin model, we estimate the model and interpret the estimates for the summary measures of impacts. By the analysis we show that the model structure makes it possible to model and find small scale neighbourhood effects, when we know that they exist, but we are lacking proper variables to measure them.

Catecholamines and cognition after traumatic brain injury

PubMed Central

Jenkins, Peter O.; Mehta, Mitul A.

2016-01-01

Abstract Cognitive problems are one of the main causes of ongoing disability after traumatic brain injury. The heterogeneity of the injuries sustained and the variability of the resulting cognitive deficits makes treating these problems difficult. Identifying the underlying pathology allows a targeted treatment approach aimed at cognitive enhancement. For example, damage to neuromodulatory neurotransmitter systems is common after traumatic brain injury and is an important cause of cognitive impairment. Here, we discuss the evidence implicating disruption of the catecholamines (dopamine and noradrenaline) and review the efficacy of catecholaminergic drugs in treating post-traumatic brain injury cognitive impairments. The response to these therapies is often variable, a likely consequence of the heterogeneous patterns of injury as well as a non-linear relationship between catecholamine levels and cognitive functions. This individual variability means that measuring the structure and function of a person’s catecholaminergic systems is likely to allow more refined therapy. Advanced structural and molecular imaging techniques offer the potential to identify disruption to the catecholaminergic systems and to provide a direct measure of catecholamine levels. In addition, measures of structural and functional connectivity can be used to identify common patterns of injury and to measure the functioning of brain ‘networks’ that are important for normal cognitive functioning. As the catecholamine systems modulate these cognitive networks, these measures could potentially be used to stratify treatment selection and monitor response to treatment in a more sophisticated manner. PMID:27256296

Neuropsychological test performance and prediction of functional capacities among Spanish-speaking and English-speaking patients with dementia.

PubMed

Loewenstein, D A; Rubert, M P; Argüelles, T; Duara, R

1995-03-01

Neuropsychological measures have been widely used by clinicians to assist them in making judgments regarding a cognitively impaired patient's ability to independently perform important activities of daily living. However, important questions have been raised concerning the degree to which neuropsychological instruments can predict a broad array of specific functional capacities required in the home environment. In the present study, we examined 127 English-speaking and 56 Spanish-speaking patients with Alzheimer's disease (AD) and determined the extent to which various neuropsychological measures and demographic variables were predictive of performance on functional measures administered within the clinical setting. Among English-speaking AD patients, Block Design and Digit-Span of the WAIS-R, as well as tests of language were among the strongest predictors of functional performance. For Spanish-speakers, Block Design, The Mini-Mental State Evaluation (MMSE) and Digit Span had the optimal predictive power. When stepwise regression was conducted on the entire sample of 183 subjects, ethnicity emerged as a statistically significant predictor variable on one of the seven functional tests (writing a check). Despite the predictive power of several of the neuropsychological measures for both groups, most of the variability in objective functional performance could not be explained in our regression models. As a result, it would appear prudent to include functional measures as part of a comprehensive neuropsychological evaluation for dementia.

Measuring farm sustainability using data envelope analysis with principal components: the case of Wisconsin cranberry.

PubMed

Dong, Fengxia; Mitchell, Paul D; Colquhoun, Jed

2015-01-01

Measuring farm sustainability performance is a crucial component for improving agricultural sustainability. While extensive assessments and indicators exist that reflect the different facets of agricultural sustainability, because of the relatively large number of measures and interactions among them, a composite indicator that integrates and aggregates over all variables is particularly useful. This paper describes and empirically evaluates a method for constructing a composite sustainability indicator that individually scores and ranks farm sustainability performance. The method first uses non-negative polychoric principal component analysis to reduce the number of variables, to remove correlation among variables and to transform categorical variables to continuous variables. Next the method applies common-weight data envelope analysis to these principal components to individually score each farm. The method solves weights endogenously and allows identifying important practices in sustainability evaluation. An empirical application to Wisconsin cranberry farms finds heterogeneity in sustainability practice adoption, implying that some farms could adopt relevant practices to improve the overall sustainability performance of the industry. Copyright © 2014 Elsevier Ltd. All rights reserved.

Test systems for measuring ocular parameters and visual function in mice.

PubMed

Schaeffel, Frank

2008-05-01

New techniques are described to measure refractive state, pupil responses, corneal curvature, ocular dimensions and spatial vision in mice. These variables are important for studies on myopia development in mice, but they are also valuable for phenotyping mouse mutants and for pharmacological studies.

Canonical Measure of Correlation (CMC) and Canonical Measure of Distance (CMD) between sets of data. Part 3. Variable selection in classification.

PubMed

Ballabio, Davide; Consonni, Viviana; Mauri, Andrea; Todeschini, Roberto

2010-01-11

In multivariate regression and classification issues variable selection is an important procedure used to select an optimal subset of variables with the aim of producing more parsimonious and eventually more predictive models. Variable selection is often necessary when dealing with methodologies that produce thousands of variables, such as Quantitative Structure-Activity Relationships (QSARs) and highly dimensional analytical procedures. In this paper a novel method for variable selection for classification purposes is introduced. This method exploits the recently proposed Canonical Measure of Correlation between two sets of variables (CMC index). The CMC index is in this case calculated for two specific sets of variables, the former being comprised of the independent variables and the latter of the unfolded class matrix. The CMC values, calculated by considering one variable at a time, can be sorted and a ranking of the variables on the basis of their class discrimination capabilities results. Alternatively, CMC index can be calculated for all the possible combinations of variables and the variable subset with the maximal CMC can be selected, but this procedure is computationally more demanding and classification performance of the selected subset is not always the best one. The effectiveness of the CMC index in selecting variables with discriminative ability was compared with that of other well-known strategies for variable selection, such as the Wilks' Lambda, the VIP index based on the Partial Least Squares-Discriminant Analysis, and the selection provided by classification trees. A variable Forward Selection based on the CMC index was finally used in conjunction of Linear Discriminant Analysis. This approach was tested on several chemical data sets. Obtained results were encouraging.

Instrumenting an upland research catchment in Canterbury, New Zealand to study controls on variability of soil moisture, shallow groundwater and streamflow

NASA Astrophysics Data System (ADS)

McMillan, Hilary; Srinivasan, Ms

2015-04-01

Hydrologists recognise the importance of vertical drainage and deep flow paths in runoff generation, even in headwater catchments. Both soil and groundwater stores are highly variable over multiple scales, and the distribution of water has a strong control on flow rates and timing. In this study, we instrumented an upland headwater catchment in New Zealand to measure the temporal and spatial variation in unsaturated and saturated-zone responses. In NZ, upland catchments are the source of much of the water used in lowland agriculture, but the hydrology of such catchments and their role in water partitioning, storage and transport is poorly understood. The study area is the Langs Gully catchment in the North Branch of the Waipara River, Canterbury: this catchment was chosen to be representative of the foothills environment, with lightly managed dryland pasture and native Matagouri shrub vegetation cover. Over a period of 16 months we measured continuous soil moisture at 32 locations and near-surface water table (< 2 m) at 14 locations, as well as measuring flow at 3 stream gauges. The distributed measurement sites were located to allow comparisons between North and South facing locations, near-stream versus hillslope locations, and convergent versus divergent hillslopes. We found that temporal variability is strongly controlled by the climatic seasonal cycle, for both soil moisture and water table, and for both the mean and extremes of their distributions. Groundwater is a larger water storage component than soil moisture, and the difference increases with catchment wetness. The spatial standard deviation of both soil moisture and groundwater is larger in winter than in summer. It peaks during rainfall events due to partial saturation of the catchment, and also rises in spring as different locations dry out at different rates. The most important controls on spatial variability are aspect and distance from stream. South-facing and near-stream locations have higher water tables and more, larger soil moisture wetting events. Typical hydrological models do not explicitly account for aspect, but our results suggest that it is an important factor in hillslope runoff generation. Co-measurement of soil moisture and water table level allowed us to identify interrelationships between the two. Locations where water tables peaked closest to the surface had consistently wetter soils and higher water tables. These wetter sites were the same across seasons. However, temporary patterns of strong soil moisture response to summer storms did not correspond to the wetter sites. Total catchment spatial variability is composed of multiple variability sources, and the dominant type is sensitive to those stores that are close to a threshold such as field capacity or saturation. Therefore, we classified spatial variability as 'summer mode' or 'winter mode'. In summer mode, variability is controlled by shallow processes e.g. interactions of water with soils and vegetation. In winter mode, variability is controlled by deeper processes e.g. groundwater movement and bypass flow. Double flow peaks observed during some events show the direct impact of groundwater variability on runoff generation. Our results suggest that emergent catchment behaviour depends on the combination of these multiple, time varying components of variability.

The importance of normalisation in the construction of deprivation indices.

PubMed

Gilthorpe, M S

1995-12-01

Measuring socio-economic deprivation is a major challenge usually addressed through the use of composite indices. This paper aims to clarify the technical details regarding composite index construction. The distribution of some variables, for example unemployment, varies over time, and these variations must be considered when composite indices are periodically re-evaluated. The process of normalisation is examined in detail and particular attention is paid to the importance of symmetry and skewness of the composite variable distributions. Four different solutions of the Townsend index of socioeconomic deprivation are compared to reveal the effects that differing transformation processes have on the meaning or interpretation of the final index values. Differences in the rank order and the relative separation between values are investigated. Constituent variables which have been transformed to yield a more symmetric distribution provide indices that behave similarly, irrespective of the actual transformation methods adopted. Normalisation is seen to be of less importance than the removal of variable skewness. Furthermore, the degree of success of the transformation in removing skewness has a major effect in determining the variation between the individual electoral ward scores. Constituent variables undergoing no transformation produce an index that is distorted by the inherent variable skewness, and this index is not consistent between re-evaluations, either temporally or spatially. Effective transformation of constituent variables should always be undertaken when generating a composite index. The most important aspect is the removal of variable skewness. There is no need for the transformed variables to be normally distributed, only symmetrically distributed, before standardisation. Even where additional parameter weights are to be applied, which significantly alter the final index, appropriate transformation procedures should be adopted for the purpose of consistency over time and between different geographical areas.

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.

Using a respiratory navigator significantly reduces variability when quantifying left ventricular torsion with cardiovascular magnetic resonance.

PubMed

Hamlet, Sean M; Haggerty, Christopher M; Suever, Jonathan D; Wehner, Gregory J; Andres, Kristin N; Powell, David K; Charnigo, Richard J; Fornwalt, Brandon K

2017-03-01

Left ventricular (LV) torsion is an important indicator of cardiac function that is limited by high inter-test variability (50% of the mean value). We hypothesized that this high inter-test variability is partly due to inconsistent breath-hold positions during serial image acquisitions, which could be significantly improved by using a respiratory navigator for cardiovascular magnetic resonance (CMR) based quantification of LV torsion. We assessed respiratory-related variability in measured LV torsion with two distinct experimental protocols. First, 17 volunteers were recruited for CMR with cine displacement encoding with stimulated echoes (DENSE) in which a respiratory navigator was used to measure and then enforce variability in end-expiratory position between all LV basal and apical acquisitions. From these data, we quantified the inter-test variability of torsion in the absence and presence of enforced end-expiratory position variability, which established an upper bound for the expected torsion variability. For the second experiment (in 20 new, healthy volunteers), 10 pairs of cine DENSE basal and apical images were each acquired from consecutive breath-holds and consecutive navigator-gated scans (with a single acceptance position). Inter-test variability of torsion was compared between the breath-hold and navigator-gated scans to quantify the variability due to natural breath-hold variation. To demonstrate the importance of these variability reductions, we quantified the reduction in sample size required to detect a clinically meaningful change in LV torsion with the use of a respiratory navigator. The mean torsion was 3.4 ± 0.2°/cm. From the first experiment, enforced variability in end-expiratory position translated to considerable variability in measured torsion (0.56 ± 0.34°/cm), whereas inter-test variability with consistent end-expiratory position was 57% lower (0.24 ± 0.16°/cm, p < 0.001). From the second experiment, natural respiratory variability from consecutive breath-holds translated to a variability in torsion of 0.24 ± 0.10°/cm, which was significantly higher than the variability from navigator-gated scans (0.18 ± 0.06°/cm, p = 0.02). By using a respiratory navigator with DENSE, theoretical sample sizes were reduced from 66 to 16 and 26 to 15 as calculated from the two experiments. A substantial portion (22-57%) of the inter-test variability of LV torsion can be reduced by using a respiratory navigator to ensure a consistent breath-hold position between image acquisitions.

Chapter 13: Assessing Persistence and Other Evaluation Issues Cross-Cutting Protocol. The Uniform Methods Project: Methods for Determining Energy Efficiency Savings for Specific Measures

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

Kurnik, Charles W; Violette, Daniel M.

Addressing other evaluation issues that have been raised in the context of energy efficiency programs, this chapter focuses on methods used to address the persistence of energy savings, which is an important input to the benefit/cost analysis of energy efficiency programs and portfolios. In addition to discussing 'persistence' (which refers to the stream of benefits over time from an energy efficiency measure or program), this chapter provides a summary treatment of these issues -Synergies across programs -Rebound -Dual baselines -Errors in variables (the measurement and/or accuracy of input variables to the evaluation).

Personality as a Source of Individual Differences in Cognition among Older African Americans

PubMed Central

Aiken-Morgan, Adrienne T.; Bichsel, Jacqueline; Allaire, Jason C.; Savla, Jyoti; Edwards, Christopher L.; Whitfield, Keith E.

2012-01-01

Previous research suggests that demographic factors are important correlates of cognitive functioning in African Americans; however, less attention has been given to the influence of personality. The present study explored how dimensions and facets of personality predicted individual variability in cognition in a sample of older African Americans from the Baltimore Study of Black Aging. Cognition was assessed by verbal learning and attention/working memory measures. Personality was measured by the NEO Personality Inventory. Linear regressions controlling for demographic factors showed that Neuroticism, Openness, and Agreeableness were significant regression predictors of cognitive performance. Individual facets of all five personality dimensions were also associated with cognitive performance. These findings suggest personality is important in understanding variability in cognition among older African Americans. PMID:22962505

Measuring the Impact of Environment on the Health of Large Cities.

PubMed

Stauber, Christine; Adams, Ellis A; Rothenberg, Richard; Dai, Dajun; Luo, Ruiyan; Weaver, Scott R; Prasad, Amit; Kano, Megumi; Heath, John

2018-06-09

The relative significance of indicators and determinants of health is important for local public health workers and planners. Of similar importance is a method for combining and evaluating such markers. We used a recently developed index, the Urban Health Index (UHI), to examine the impact of environmental variables on the overall health of cities. We used the UHI to rank 57 of the world’s largest cities (based on population size) in low- and middle-income countries. We examined nine variables in various combinations that were available from the Demographic and Health Surveys conducted in these countries. When arranged in ascending order, the distribution of UHIs follows the previously described pattern of gradual linear increase, with departures at each tail. The rank order of cities did not change materially with the omission of variables about women’s health knowledge or childhood vaccinations. Omission of environmental variables (a central water supply piped into homes, improved sanitation, and indoor solid fuel use) altered the rank order considerably. The data suggest that environmental indicators, measures of key household level risk to health, may play a vital role in the overall health of urban communities.

The use of random forests in modelling short-term air pollution effects based on traffic and meteorological conditions: A case study in Wrocław.

PubMed

Kamińska, Joanna A

2018-07-01

Random forests, an advanced data mining method, are used here to model the regression relationships between concentrations of the pollutants NO 2 , NO x and PM 2.5 , and nine variables describing meteorological conditions, temporal conditions and traffic flow. The study was based on hourly values of wind speed, wind direction, temperature, air pressure and relative humidity, temporal variables, and finally traffic flow, in the two years 2015 and 2016. An air quality measurement station was selected on a main road, located a short distance (40 m) from a large intersection equipped with a traffic flow measurement system. Nine different time subsets were defined, based among other things on the climatic conditions in Wrocław. An analysis was made of the fit of models created for those subsets, and of the importance of the predictors. Both the fit and the importance of particular predictors were found to be dependent on season. The best fit was obtained for models created for the six-month warm season (April-September) and for the summer season (June-August). The most important explanatory variable in the models of concentrations of nitrogen oxides was traffic flow, while in the case of PM 2.5 the most important were meteorological conditions, in particular temperature, wind speed and wind direction. Temporal variables (except for month in the case of PM 2.5 ) were found to have no significant effect on the concentrations of the studied pollutants. Copyright © 2018 Elsevier Ltd. All rights reserved.

What can surface measurements of long-lived trace gases tell us about interannual variability in UTLS transport?

NASA Astrophysics Data System (ADS)

Ray, E. A.; Daniel, J. S.; Montzka, S. A.; Portmann, R. W.; Yu, P.; Rosenlof, K. H.; Moore, F. L.

2017-12-01

We use surface measurements of a number of long-lived trace gases, including CFC-11, CFC-12 and N2O, and a 3-box model to estimate the interannual variability of bulk stratospheric transport characteristics. Coherent features among the different surface measurements suggest that there have been periods over the last two decades with significant variability in the amount of stratospheric loss transported downward to the troposphere both globally and between the NH and SH. This is especially apparent around the year 2000 and in the recent period since 2013 when surface measurements suggest an overall slowdown of the transport of stratospheric air to the troposphere as well as a shift towards a relatively stronger stratospheric circulation in the SH compared to the NH. We compare these results to stratospheric satellite measurements, residual circulation estimates and global model simulations to check for consistency. The implications of not accounting for interannual variability in stratospheric loss transported to the surface in emission estimates of long-lived trace gases can be significant, including for those gases monitored by the Montreal Protocol and/or of climatic importance.

Metacommunity composition of web-spiders in a fragmented neotropical forest: relative importance of environmental and spatial effects.

PubMed

Baldissera, Ronei; Rodrigues, Everton N L; Hartz, Sandra M

2012-01-01

The distribution of beta diversity is shaped by factors linked to environmental and spatial control. The relative importance of both processes in structuring spider metacommunities has not yet been investigated in the Atlantic Forest. The variance explained by purely environmental, spatially structured environmental, and purely spatial components was compared for a metacommunity of web spiders. The study was carried out in 16 patches of Atlantic Forest in southern Brazil. Field work was done in one landscape mosaic representing a slight gradient of urbanization. Environmental variables encompassed plot- and patch-level measurements and a climatic matrix, while principal coordinates of neighbor matrices (PCNMs) acted as spatial variables. A forward selection procedure was carried out to select environmental and spatial variables influencing web-spider beta diversity. Variation partitioning was used to estimate the contribution of pure environmental and pure spatial effects and their shared influence on beta-diversity patterns, and to estimate the relative importance of selected environmental variables. Three environmental variables (bush density, land use in the surroundings of patches, and shape of patches) and two spatial variables were selected by forward selection procedures. Variation partitioning revealed that 15% of the variation of beta diversity was explained by a combination of environmental and PCNM variables. Most of this variation (12%) corresponded to pure environmental and spatially environmental structure. The data indicated that (1) spatial legacy was not important in explaining the web-spider beta diversity; (2) environmental predictors explained a significant portion of the variation in web-spider composition; (3) one-third of environmental variation was due to a spatial structure that jointly explains variation in species distributions. We were able to detect important factors related to matrix management influencing the web-spider beta-diversity patterns, which are probably linked to historical deforestation events.

Use of Wearable Sensors and Biometric Variables in an Artificial Pancreas System

PubMed Central

Turksoy, Kamuran; Monforti, Colleen; Park, Minsun; Griffith, Garett; Quinn, Laurie; Cinar, Ali

2017-01-01

An artificial pancreas (AP) computes the optimal insulin dose to be infused through an insulin pump in people with Type 1 Diabetes (T1D) based on information received from a continuous glucose monitoring (CGM) sensor. It has been recognized that exercise is a major challenge in the development of an AP system. The use of biometric physiological variables in an AP system may be beneficial for prevention of exercise-induced challenges and better glucose regulation. The goal of the present study is to find a correlation between biometric variables such as heart rate (HR), heat flux (HF), skin temperature (ST), near-body temperature (NBT), galvanic skin response (GSR), and energy expenditure (EE), 2D acceleration-mean of absolute difference (MAD) and changes in glucose concentrations during exercise via partial least squares (PLS) regression and variable importance in projection (VIP) in order to determine which variables would be most useful to include in a future artificial pancreas. PLS and VIP analyses were performed on data sets that included seven different types of exercises. Data were collected from 26 clinical experiments. Clinical results indicate ST to be the most consistently important (important for six out of seven tested exercises) variable over all different exercises tested. EE and HR are also found to be important variables over several types of exercise. We also found that the importance of GSR and NBT observed in our experiments might be related to stress and the effect of changes in environmental temperature on glucose concentrations. The use of the biometric measurements in an AP system may provide better control of glucose concentration. PMID:28272368

Using variable homography to measure emergent fibers on textile fabrics

NASA Astrophysics Data System (ADS)

Xu, Jun; Cudel, Christophe; Kohler, Sophie; Fontaine, Stéphane; Haeberlé, Olivier; Klotz, Marie-Louise

2011-07-01

A fabric's smoothness is a key factor to determine the quality of textile finished products and has great influence on the functionality of industrial textiles and high-end textile products. With popularization of the 'zero defect' industrial concept, identifying and measuring defective material in the early stage of production is of great interest for the industry. In the current market, many systems are able to achieve automatic monitoring and control of fabric, paper, and nonwoven material during the entire production process, however online measurement of hairiness is still an open topic and highly desirable for industrial applications. In this paper we propose a computer vision approach, based on variable homography, which can be used to measure the emergent fiber's length on textile fabrics. The main challenges addressed in this paper are the application of variable homography to textile monitoring and measurement, as well as the accuracy of the estimated calculation. We propose that a fibrous structure can be considered as a two-layer structure and then show how variable homography can estimate the length of the fiber defects. Simulations are carried out to show the effectiveness of this method to measure the emergent fiber's length. The true lengths of selected fibers are measured precisely using a digital optical microscope, and then the same fibers are tested by our method. Our experimental results suggest that smoothness monitored by variable homography is an accurate and robust method for quality control of important industrially fabrics.

Agricultural disturbance response models for invertebrate and algal metrics from streams at two spatial scales within the U.S.

USGS Publications Warehouse

Waite, Ian R.

2014-01-01

As part of the USGS study of nutrient enrichment of streams in agricultural regions throughout the United States, about 30 sites within each of eight study areas were selected to capture a gradient of nutrient conditions. The objective was to develop watershed disturbance predictive models for macroinvertebrate and algal metrics at national and three regional landscape scales to obtain a better understanding of important explanatory variables. Explanatory variables in models were generated from landscape data, habitat, and chemistry. Instream nutrient concentration and variables assessing the amount of disturbance to the riparian zone (e.g., percent row crops or percent agriculture) were selected as most important explanatory variable in almost all boosted regression tree models regardless of landscape scale or assemblage. Frequently, TN and TP concentration and riparian agricultural land use variables showed a threshold type response at relatively low values to biotic metrics modeled. Some measure of habitat condition was also commonly selected in the final invertebrate models, though the variable(s) varied across regions. Results suggest national models tended to account for more general landscape/climate differences, while regional models incorporated both broad landscape scale and more specific local-scale variables.

Solar diameter measurements for study of Sun climate coupling

NASA Technical Reports Server (NTRS)

Hill, H. A.

1983-01-01

Changes in solar shape and diameter were detected as a possible probe of variability in solar luminosity, an important climatic driving function. A technique was designed which will allow the calibration of the telescope field, providing a scale for long-term comparison of these and future measurements.

Rapid Assessment Of The Fundamental Property Variation Of Wood

Treesearch

Chi-Leung So; Leslie H. Groom; Timothy G. Rials; Rebecca Snell; Stephen S. Kelley; Robert Meglen

2002-01-01

Abstract - Genetic variation, site conditions, silvicultural treatments, seasonal effects, and their complex interaction are all vitally-important factors accounting for the variability and quality of the raw material produced - wood. Quality can be measured in several ways that generally influence the end use. The most desirable measure is the...

How to Measure Diversity When You Must

ERIC Educational Resources Information Center

Budescu, David V.; Budescu, Mia

2012-01-01

Racial/ethnic diversity has become an increasingly important variable in the social sciences. Research from multiple disciplines consistently demonstrates the tremendous impact of ethnic diversity on individuals and organizations. Investigators use a variety of measures, and their choices can affect the conclusions that can be drawn and limit the…

Model averaging and muddled multimodel inferences.

PubMed

Cade, Brian S

2015-09-01

Three flawed practices associated with model averaging coefficients for predictor variables in regression models commonly occur when making multimodel inferences in analyses of ecological data. Model-averaged regression coefficients based on Akaike information criterion (AIC) weights have been recommended for addressing model uncertainty but they are not valid, interpretable estimates of partial effects for individual predictors when there is multicollinearity among the predictor variables. Multicollinearity implies that the scaling of units in the denominators of the regression coefficients may change across models such that neither the parameters nor their estimates have common scales, therefore averaging them makes no sense. The associated sums of AIC model weights recommended to assess relative importance of individual predictors are really a measure of relative importance of models, with little information about contributions by individual predictors compared to other measures of relative importance based on effects size or variance reduction. Sometimes the model-averaged regression coefficients for predictor variables are incorrectly used to make model-averaged predictions of the response variable when the models are not linear in the parameters. I demonstrate the issues with the first two practices using the college grade point average example extensively analyzed by Burnham and Anderson. I show how partial standard deviations of the predictor variables can be used to detect changing scales of their estimates with multicollinearity. Standardizing estimates based on partial standard deviations for their variables can be used to make the scaling of the estimates commensurate across models, a necessary but not sufficient condition for model averaging of the estimates to be sensible. A unimodal distribution of estimates and valid interpretation of individual parameters are additional requisite conditions. The standardized estimates or equivalently the t statistics on unstandardized estimates also can be used to provide more informative measures of relative importance than sums of AIC weights. Finally, I illustrate how seriously compromised statistical interpretations and predictions can be for all three of these flawed practices by critiquing their use in a recent species distribution modeling technique developed for predicting Greater Sage-Grouse (Centrocercus urophasianus) distribution in Colorado, USA. These model averaging issues are common in other ecological literature and ought to be discontinued if we are to make effective scientific contributions to ecological knowledge and conservation of natural resources.

Model averaging and muddled multimodel inferences

USGS Publications Warehouse

Cade, Brian S.

2015-01-01

Three flawed practices associated with model averaging coefficients for predictor variables in regression models commonly occur when making multimodel inferences in analyses of ecological data. Model-averaged regression coefficients based on Akaike information criterion (AIC) weights have been recommended for addressing model uncertainty but they are not valid, interpretable estimates of partial effects for individual predictors when there is multicollinearity among the predictor variables. Multicollinearity implies that the scaling of units in the denominators of the regression coefficients may change across models such that neither the parameters nor their estimates have common scales, therefore averaging them makes no sense. The associated sums of AIC model weights recommended to assess relative importance of individual predictors are really a measure of relative importance of models, with little information about contributions by individual predictors compared to other measures of relative importance based on effects size or variance reduction. Sometimes the model-averaged regression coefficients for predictor variables are incorrectly used to make model-averaged predictions of the response variable when the models are not linear in the parameters. I demonstrate the issues with the first two practices using the college grade point average example extensively analyzed by Burnham and Anderson. I show how partial standard deviations of the predictor variables can be used to detect changing scales of their estimates with multicollinearity. Standardizing estimates based on partial standard deviations for their variables can be used to make the scaling of the estimates commensurate across models, a necessary but not sufficient condition for model averaging of the estimates to be sensible. A unimodal distribution of estimates and valid interpretation of individual parameters are additional requisite conditions. The standardized estimates or equivalently the tstatistics on unstandardized estimates also can be used to provide more informative measures of relative importance than sums of AIC weights. Finally, I illustrate how seriously compromised statistical interpretations and predictions can be for all three of these flawed practices by critiquing their use in a recent species distribution modeling technique developed for predicting Greater Sage-Grouse (Centrocercus urophasianus) distribution in Colorado, USA. These model averaging issues are common in other ecological literature and ought to be discontinued if we are to make effective scientific contributions to ecological knowledge and conservation of natural resources.

The relative influence of nutrients and habitat on stream metabolism in agricultural streams

USGS Publications Warehouse

Frankforter, J.D.; Weyers, H.S.; Bales, J.D.; Moran, P.W.; Calhoun, D.L.

2010-01-01

Stream metabolism was measured in 33 streams across a gradient of nutrient concentrations in four agricultural areas of the USA to determine the relative influence of nutrient concentrations and habitat on primary production (GPP) and respiration (CR-24). In conjunction with the stream metabolism estimates, water quality and algal biomass samples were collected, as was an assessment of habitat in the sampling reach. When data for all study areas were combined, there were no statistically significant relations between gross primary production or community respiration and any of the independent variables. However, significant regression models were developed for three study areas for GPP (r 2 = 0.79-0.91) and CR-24 (r 2 = 0.76-0.77). Various forms of nutrients (total phosphorus and area-weighted total nitrogen loading) were significant for predicting GPP in two study areas, with habitat variables important in seven significant models. Important physical variables included light availability, precipitation, basin area, and in-stream habitat cover. Both benthic and seston chlorophyll were not found to be important explanatory variables in any of the models; however, benthic ash-free dry weight was important in two models for GPP. ?? 2009 The Author(s).

Strategies for minimizing sample size for use in airborne LiDAR-based forest inventory

USGS Publications Warehouse

Junttila, Virpi; Finley, Andrew O.; Bradford, John B.; Kauranne, Tuomo

2013-01-01

Recently airborne Light Detection And Ranging (LiDAR) has emerged as a highly accurate remote sensing modality to be used in operational scale forest inventories. Inventories conducted with the help of LiDAR are most often model-based, i.e. they use variables derived from LiDAR point clouds as the predictive variables that are to be calibrated using field plots. The measurement of the necessary field plots is a time-consuming and statistically sensitive process. Because of this, current practice often presumes hundreds of plots to be collected. But since these plots are only used to calibrate regression models, it should be possible to minimize the number of plots needed by carefully selecting the plots to be measured. In the current study, we compare several systematic and random methods for calibration plot selection, with the specific aim that they be used in LiDAR based regression models for forest parameters, especially above-ground biomass. The primary criteria compared are based on both spatial representativity as well as on their coverage of the variability of the forest features measured. In the former case, it is important also to take into account spatial auto-correlation between the plots. The results indicate that choosing the plots in a way that ensures ample coverage of both spatial and feature space variability improves the performance of the corresponding models, and that adequate coverage of the variability in the feature space is the most important condition that should be met by the set of plots collected.

Evaluation of anti-migration properties of biliary covered self-expandable metal stents

PubMed Central

Minaga, Kosuke; Kitano, Masayuki; Imai, Hajime; Harwani, Yogesh; Yamao, Kentaro; Kamata, Ken; Miyata, Takeshi; Omoto, Shunsuke; Kadosaka, Kumpei; Sakurai, Toshiharu; Nishida, Naoshi; Kudo, Masatoshi

2016-01-01

AIM: To assess anti-migration potential of six biliary covered self-expandable metal stents (C-SEMSs) by using a newly designed phantom model. METHODS: In the phantom model, the stent was placed in differently sized holes in a silicone wall and retracted with a retraction robot. Resistance force to migration (RFM) was measured by a force gauge on the stent end. Radial force (RF) was measured with a RF measurement machine. Measured flare structure variables were the outer diameter, height, and taper angle of the flare (ODF, HF, and TAF, respectively). Correlations between RFM and RF or flare variables were analyzed using a linear correlated model. RESULTS: Out of the six stents, five stents were braided, the other was laser-cut. The RF and RFM of each stent were expressed as the average of five replicate measurements. For all six stents, RFM and RF decreased as the hole diameter increased. For all six stents, RFM and RF correlated strongly when the stent had not fully expanded. This correlation was not observed in the five braided stents excluding the laser cut stent. For all six stents, there was a strong correlation between RFM and TAF when the stent fully expanded. For the five braided stents, RFM after full stent expansion correlated strongly with all three stent flare structure variables (ODF, HF, and TAF). The laser-cut C-SEMS had higher RFMs than the braided C-SEMSs regardless of expansion state. CONCLUSION: RF was an important anti-migration property when the C-SEMS did not fully expand. Once fully expanded, stent flare structure variables plays an important role in anti-migration. PMID:27570427

Mountain Hydrology of the Semi-Arid Western U.S.: Research Needs, Opportunities and Challenges

NASA Astrophysics Data System (ADS)

Bales, R.; Dozier, J.; Molotch, N.; Painter, T.; Rice, R.

2004-12-01

In the semi-arid Western U.S., water resources are being stressed by the combination of climate warming, changing land use, and population growth. Multiple consensus planning documents point to this region as perhaps the highest priority for new hydrologic understanding. Three main hydrologic issues illustrate research needs in the snow-driven hydrology of the region. First, despite the hydrologic importance of mountainous regions, the processes controlling their energy, water and biogeochemical fluxes are not well understood. Second, there exists a need to realize, at various spatial and temporal scales, the feedback systems between hydrological fluxes and biogeochemical and ecological processes. Third, the paucity of adequate observation networks in mountainous regions hampers improvements in understanding these processes. For example, we lack an adequate description of factors controlling the partitioning of snowmelt into runoff versus infiltration and evapotranspiration, and need strategies to accurately measure the variability of precipitation, snow cover and soil moisture. The amount of mountain-block and mountain-front recharge and how recharge patterns respond to climate variability are poorly known across the mountainous West. Moreover, hydrologic modelers and those measuring important hydrologic variables from remote sensing and distributed in situ sites have failed to bridge rifts between modeling needs and available measurements. Research and operational communities will benefit from data fusion/integration, improved measurement arrays, and rapid data access. For example, the hydrologic modeling community would advance if given new access to single rather than disparate sources of bundles of cutting-edge remote sensing retrievals of snow covered area and albedo, in situ measurements of snow water equivalent and precipitation, and spatio-temporal fields of variables that drive models. In addition, opportunities exist for the deployment of new technologies, taking advantage of research in spatially distributed sensor networks that can enhance data recovery and analysis.

Prediction of Psilocybin Response in Healthy Volunteers

PubMed Central

Studerus, Erich; Gamma, Alex; Kometer, Michael; Vollenweider, Franz X.

2012-01-01

Responses to hallucinogenic drugs, such as psilocybin, are believed to be critically dependent on the user's personality, current mood state, drug pre-experiences, expectancies, and social and environmental variables. However, little is known about the order of importance of these variables and their effect sizes in comparison to drug dose. Hence, this study investigated the effects of 24 predictor variables, including age, sex, education, personality traits, drug pre-experience, mental state before drug intake, experimental setting, and drug dose on the acute response to psilocybin. The analysis was based on the pooled data of 23 controlled experimental studies involving 409 psilocybin administrations to 261 healthy volunteers. Multiple linear mixed effects models were fitted for each of 15 response variables. Although drug dose was clearly the most important predictor for all measured response variables, several non-pharmacological variables significantly contributed to the effects of psilocybin. Specifically, having a high score in the personality trait of Absorption, being in an emotionally excitable and active state immediately before drug intake, and having experienced few psychological problems in past weeks were most strongly associated with pleasant and mystical-type experiences, whereas high Emotional Excitability, low age, and an experimental setting involving positron emission tomography most strongly predicted unpleasant and/or anxious reactions to psilocybin. The results confirm that non-pharmacological variables play an important role in the effects of psilocybin. PMID:22363492

Prediction of psilocybin response in healthy volunteers.

PubMed

Studerus, Erich; Gamma, Alex; Kometer, Michael; Vollenweider, Franz X

2012-01-01

Responses to hallucinogenic drugs, such as psilocybin, are believed to be critically dependent on the user's personality, current mood state, drug pre-experiences, expectancies, and social and environmental variables. However, little is known about the order of importance of these variables and their effect sizes in comparison to drug dose. Hence, this study investigated the effects of 24 predictor variables, including age, sex, education, personality traits, drug pre-experience, mental state before drug intake, experimental setting, and drug dose on the acute response to psilocybin. The analysis was based on the pooled data of 23 controlled experimental studies involving 409 psilocybin administrations to 261 healthy volunteers. Multiple linear mixed effects models were fitted for each of 15 response variables. Although drug dose was clearly the most important predictor for all measured response variables, several non-pharmacological variables significantly contributed to the effects of psilocybin. Specifically, having a high score in the personality trait of Absorption, being in an emotionally excitable and active state immediately before drug intake, and having experienced few psychological problems in past weeks were most strongly associated with pleasant and mystical-type experiences, whereas high Emotional Excitability, low age, and an experimental setting involving positron emission tomography most strongly predicted unpleasant and/or anxious reactions to psilocybin. The results confirm that non-pharmacological variables play an important role in the effects of psilocybin.

Measurement and meaning of salivary cortisol: a focus on health and disease in children.

PubMed

Jessop, David S; Turner-Cobb, Julie M

2008-01-01

Measurement of salivary cortisol can provide important information about hypothalamic-pituitary-adrenal (HPA) axis activity under normal conditions and in response to stress. However, there are many variables relating to the measurement of cortisol in saliva which may introduce error and therefore may render difficult the comparison and interpretation of data between, and within, laboratories. This review addresses the effects of gender, age, time and location of sampling, units of measurement, assay conditions and compliance with the protocol, all of which have the potential to impact upon the precision, accuracy and reliability of salivary cortisol measurements in the literature. Some of these factors are applicable to both adults and children, but the measurement of salivary cortisol in children introduces aspects of unique variability which demand special attention. The specific focus of this review is upon the somewhat neglected area of methodological variability of salivary cortisol measurement in children. In addition to these methodological issues, the review highlights the use of salivary cortisol measurements to provide information about HPA axis dysfunction associated with psycho- and patho-physiological conditions in children. Novel applications for salivary cortisol measurements in future research into HPA axis activity in children are also discussed.

Correcting Measurement Error in Latent Regression Covariates via the MC-SIMEX Method

ERIC Educational Resources Information Center

Rutkowski, Leslie; Zhou, Yan

2015-01-01

Given the importance of large-scale assessments to educational policy conversations, it is critical that subpopulation achievement is estimated reliably and with sufficient precision. Despite this importance, biased subpopulation estimates have been found to occur when variables in the conditioning model side of a latent regression model contain…

Human thermal comfort in urban outdoor spaces

Treesearch

Lee P. Herrington; J. S. Vittum

1977-01-01

Measurements of the physical environment of urban open spaces in Syracuse, New York, were used to compute the physiological responses of human users of the spaces. These calculations were then used to determine what environmental variables were both important to human comfort and susceptible to control by site design. Although air temperature and humidity are important...

Measurement of in-field variability for active seeding depth applications in southeastern U.S.

USDA-ARS?s Scientific Manuscript database

Planting remains one of the most important if not the most important field operation with mistakes potentially impacting profitability. Planter performance is defined by the ability of the planter to accurately place seed into the soil at an adequate and pre-determined depth. However, planter perfor...

VARIABILITY OF VISUAL FIELD MEASUREMENTS IS CORRELATED WITH THE GRADIENT OF VISUAL SENSITIVITY

PubMed Central

Wyatt, Harry J.; Dul, Mitchell W.; Swanson, William H.

2007-01-01

Conventional static automated perimetry provides important clinical information, but its utility is limited by considerable test-retest variability. Fixational eye movements during testing could contribute to variability. To assess this possibility, it is important to know how much sensitivity change would be caused by a given eye movement. To investigate this, we have evaluated the gradient, the rate at which sensitivity changes with location. We tested one eye each, twice within 3 weeks, of 29 patients with glaucoma, 17 young normal subjects and 13 older normal subjects. The 10-2 test pattern with the SITA Standard algorithm was used to assess sensitivity at locations with 2° spacing. Variability and gradient were calculated at individual test locations. Matrix correlations were determined between variability and gradient, and were substantial for the patients with glaucoma. The results were consistent with a substantial contribution to test-retest variability from small fixational eye movements interacting with visual field gradient. Successful characterization of the gradient of sensitivity appears to require sampling at relatively close spacing, as in the 10-2 test pattern. PMID:17320924

Variability of visual field measurements is correlated with the gradient of visual sensitivity.

PubMed

Wyatt, Harry J; Dul, Mitchell W; Swanson, William H

2007-03-01

Conventional static automated perimetry provides important clinical information, but its utility is limited by considerable test-retest variability. Fixational eye movements during testing could contribute to variability. To assess this possibility, it is important to know how much sensitivity change would be caused by a given eye movement. To investigate this, we have evaluated the gradient, the rate at which sensitivity changes with location. We tested one eye each, twice within 3 weeks, of 29 patients with glaucoma, 17 young normal subjects and 13 older normal subjects. The 10-2 test pattern with the SITA Standard algorithm was used to assess sensitivity at locations with 2 degrees spacing. Variability and gradient were calculated at individual test locations. Matrix correlations were determined between variability and gradient, and were substantial for the patients with glaucoma. The results were consistent with a substantial contribution to test-retest variability from small fixational eye movements interacting with visual field gradient. Successful characterization of the gradient of sensitivity appears to require sampling at relatively close spacing, as in the 10-2 test pattern.

Identifying Social Trust in Cross-Country Analysis: Do We Really Measure the Same?

ERIC Educational Resources Information Center

Torpe, Lars; Lolle, Henrik

2011-01-01

Many see trust as an important social resource for the welfare of individuals as well as nations. It is therefore important to be able to identify trust and explain its sources. Cross-country survey analysis has been an important tool in this respect, and often one single variable is used to identify social trust understood as trust in strangers,…

How do measurement duration and timing interact to influence estimation of basal physiological variables of a nocturnal rodent?

PubMed

Connolly, M K; Cooper, C E

2014-12-01

Metabolic rate and evaporative water loss are two commonly measured physiological variables. It is therefore important, especially for comparative studies, that these variables (and others) are measured under standardised conditions, of which a resting state during the inactive phase is part of the accepted criteria. Here we show how measurement duration and timing affect these criteria and impact on the estimation of basal metabolic rate (oxygen consumption and carbon dioxide production) and standard evaporative water loss of a small nocturnal rodent. Oxygen consumption, carbon dioxide production and evaporative water loss all decreased over the duration of an experiment. Random assortment of hourly values indicated that this was an animal rather than a random effect for up to 11h. Experimental start time also had a significant effect on measurement of physiological variables. A longer time period was required to achieve minimal carbon dioxide consumption and evaporative water loss when experiments commenced earlier in the day; however, experiments with earlier start times had a lower overall estimates of minimal oxygen consumption and carbon dioxide production. For this species, measurement duration of at least 8h, ideally commencing between before the inactive phase at 03:00h and 05:00h, is required to obtain minimal standard values for physiological variables. Up to 80% of recently published studies measuring basal metabolic rate and/or evaporative water loss of small nocturnal mammals may overestimate basal values due to insufficiently long measurement duration. Copyright © 2014 Elsevier Inc. All rights reserved.

A Test of the Big Fish in a Little Pond Hypothesis: An Investigation into the Feelings of Seven-Year-Old Pupils in School.

ERIC Educational Resources Information Center

Tymms, Peter

2001-01-01

The feelings (self-concepts and attitudes) of 21,000 British 7-year-olds toward math, reading, and school were investigated using multivariate multilevel models. The most important explanatory variables were the teacher and pupils' academic level. Other variables (age, sex, and first language) were weakly connected to attitude measures. (Contains…

Inventory-based sensitivity analysis of the Large Tree Diameter Growth Submodel of the Southern Variant of the FVS

Treesearch

Giorgio Vacchiano; John D. Shaw; R. Justin DeRose; James N. Long

2008-01-01

Diameter increment is an important variable in modeling tree growth. Most facets of predicted tree development are dependent in part on diameter or diameter increment, the most commonly measured stand variable. The behavior of the Forest Vegetation Simulator (FVS) largely relies on the performance of the diameter increment model and the subsequent use of predicted dbh...

Human and Methodological Sources of Variability in the Measurement of Urinary 8-Oxo-7,8-dihydro-2′-deoxyguanosine

PubMed Central

Møller, Peter; Henriksen, Trine; Mistry, Vilas; Koppen, Gudrun; Rossner, Pavel; Sram, Radim J.; Weimann, Allan; Poulsen, Henrik E.; Nataf, Robert; Andreoli, Roberta; Manini, Paola; Marczylo, Tim; Lam, Patricia; Evans, Mark D.; Kasai, Hiroshi; Kawai, Kazuaki; Li, Yun-Shan; Sakai, Kazuo; Singh, Rajinder; Teichert, Friederike; Farmer, Peter B.; Rozalski, Rafal; Gackowski, Daniel; Siomek, Agnieszka; Saez, Guillermo T.; Cerda, Concha; Broberg, Karin; Lindh, Christian; Hossain, Mohammad Bakhtiar; Haghdoost, Siamak; Hu, Chiung-Wen; Chao, Mu-Rong; Wu, Kuen-Yuh; Orhan, Hilmi; Senduran, Nilufer; Smith, Raymond J.; Santella, Regina M.; Su, Yali; Cortez, Czarina; Yeh, Susan; Olinski, Ryszard; Loft, Steffen

2013-01-01

Abstract Aims: Urinary 8-oxo-7,8-dihydro-2′-deoxyguanosine (8-oxodG) is a widely used biomarker of oxidative stress. However, variability between chromatographic and ELISA methods hampers interpretation of data, and this variability may increase should urine composition differ between individuals, leading to assay interference. Furthermore, optimal urine sampling conditions are not well defined. We performed inter-laboratory comparisons of 8-oxodG measurement between mass spectrometric-, electrochemical- and ELISA-based methods, using common within-technique calibrants to analyze 8-oxodG-spiked phosphate-buffered saline and urine samples. We also investigated human subject- and sample collection-related variables, as potential sources of variability. Results: Chromatographic assays showed high agreement across urines from different subjects, whereas ELISAs showed far more inter-laboratory variation and generally overestimated levels, compared to the chromatographic assays. Excretion rates in timed ‘spot’ samples showed strong correlations with 24 h excretion (the ‘gold’ standard) of urinary 8-oxodG (rp 0.67–0.90), although the associations were weaker for 8-oxodG adjusted for creatinine or specific gravity (SG). The within-individual excretion of 8-oxodG varied only moderately between days (CV 17% for 24 h excretion and 20% for first void, creatinine-corrected samples). Innovation: This is the first comprehensive study of both human and methodological factors influencing 8-oxodG measurement, providing key information for future studies with this important biomarker. Conclusion: ELISA variability is greater than chromatographic assay variability, and cannot determine absolute levels of 8-oxodG. Use of standardized calibrants greatly improves intra-technique agreement and, for the chromatographic assays, importantly allows integration of results for pooled analyses. If 24 h samples are not feasible, creatinine- or SG-adjusted first morning samples are recommended. Antioxid. Redox Signal. 18, 2377–2391. PMID:23198723

Can we "predict" long-term outcome for ambulatory transcutaneous electrical nerve stimulation in patients with chronic pain?

PubMed

Köke, Albère J; Smeets, Rob J E M; Perez, Roberto S; Kessels, Alphons; Winkens, Bjorn; van Kleef, Maarten; Patijn, Jacob

2015-03-01

Evidence for effectiveness of transcutaneous electrical nerve stimulation (TENS) is still inconclusive. As heterogeneity of chronic pain patients might be an important factor for this lack of efficacy, identifying factors for a successful long-term outcome is of great importance. A prospective study was performed to identify variables with potential predictive value for 2 outcome measures on long term (6 months); (1) continuation of TENS, and (2) a minimally clinical important pain reduction of ≥ 33%. At baseline, a set of risk factors including pain-related variables, psychological factors, and disability was measured. In a multiple logistic regression analysis, higher patient's expectations, neuropathic pain, no severe pain (< 80 mm visual analogue scale [VAS]) were independently related to long-term continuation of TENS. For the outcome "minimally clinical important pain reduction," the multiple logistic regression analysis indicated that no multisited pain (> 2 pain locations) and intermittent pain were positively and independently associated with a minimally clinical important pain reduction of ≥ 33%. The results showed that factors associated with a successful outcome in the long term are dependent on definition of successful outcome. © 2014 World Institute of Pain.

What predictors matter: Risk factors for late adolescent outcomes.

PubMed

Wall-Wieler, Elizabeth; Roos, Leslie L; Chateau, Dan G; Rosella, Laura C

2016-06-27

A life course approach and linked Manitoba data from birth to age 18 were used to facilitate comparisons of two important outcomes: high school graduation and Attention-Deficit/Hyperactivity Disorder (ADHD). With a common set of variables, we sought to answer the following questions: Do the measures predicting high school graduation differ from those that predict ADHD? Which factors are most important? How well do the models fit each outcome? Administrative data from the Population Health Research Data Repository at the Manitoba Centre for Health Policy were used to conduct one of the strongest observational designs: multilevel modelling of large population (n = 62,739) and sibling (n = 29,444) samples. Variables included are neighbourhood characteristics, measures of family stability, and mental and physical health conditions in childhood and adolescence. The adverse childhood experiences important for each outcome differ. While family instability and economic adversity more strongly affect failing to graduate from high school, adverse health events in childhood and early adolescence have a greater effect on late adolescent ADHD. The variables included in the model provided excellent accuracy and discrimination. These results offer insights on the role of several family and social variables and can serve as the basis for reliable, valid prediction tools that can identify high-risk individuals. Applying such a tool at the population level would provide insight into the future burden of these outcomes in an entire region or nation and further quantify the burden of risk in the population.

Original method to compute epipoles using variable homography: application to measure emergent fibers on textile fabrics

NASA Astrophysics Data System (ADS)

Xu, Jun; Cudel, Christophe; Kohler, Sophie; Fontaine, Stéphane; Haeberlé, Olivier; Klotz, Marie-Louise

2012-04-01

Fabric's smoothness is a key factor in determining the quality of finished textile products and has great influence on the functionality of industrial textiles and high-end textile products. With popularization of the zero defect industrial concept, identifying and measuring defective material in the early stage of production is of great interest to the industry. In the current market, many systems are able to achieve automatic monitoring and control of fabric, paper, and nonwoven material during the entire production process, however online measurement of hairiness is still an open topic and highly desirable for industrial applications. We propose a computer vision approach to compute epipole by using variable homography, which can be used to measure emergent fiber length on textile fabrics. The main challenges addressed in this paper are the application of variable homography on textile monitoring and measurement, as well as the accuracy of the estimated calculation. We propose that a fibrous structure can be considered as a two-layer structure, and then we show how variable homography combined with epipolar geometry can estimate the length of the fiber defects. Simulations are carried out to show the effectiveness of this method. The true length of selected fibers is measured precisely using a digital optical microscope, and then the same fibers are tested by our method. Our experimental results suggest that smoothness monitored by variable homography is an accurate and robust method of quality control for important industrial fabrics.

Impact of daily mood, work hours, and iso-strain variables on self-reported health behaviors.

PubMed

Jones, Fiona; O'Connor, Daryl B; Conner, Mark; McMillan, Brian; Ferguson, Eamonn

2007-11-01

Four hundred and twenty-two employees completed daily diaries measuring positive affect, negative affect, work hours, and health behaviors (snacking, smoking, exercise, alcohol, caffeine consumption) on work days over a 4-week period. In addition, measures of job demands, job control, and social support (iso-strain variables) were completed on 1 occasion. Multilevel random coefficient modeling was used to examine relationships between the job characteristics, daily work variables, and self-reported health behaviors. Results indicated a more important role for within-person daily fluctuations than for between-persons variations in predicting health behaviors. Whereas negative affect was negatively related to health behavior for both men and women, work hours had negative impacts for women only. Iso-strain variables showed few main effects and a modest number of interactions with daily variables (mainly for men). Findings point to the limited impact of stable features of work design compared to the effects of daily work stressors on health behaviors. (c) 2007 APA

Impact damage resistance of composite fuselage structure, part 1

NASA Technical Reports Server (NTRS)

Dost, E. F.; Avery, W. B.; Ilcewicz, L. B.; Grande, D. H.; Coxon, B. R.

1992-01-01

The impact damage resistance of laminated composite transport aircraft fuselage structures was studied experimentally. A statistically based designed experiment was used to examine numerous material, laminate, structural, and extrinsic (e.g., impactor type) variables. The relative importance and quantitative measure of the effect of each variable and variable interactions on responses including impactor dynamic response, visibility, and internal damage state were determined. The study utilized 32 three-stiffener panels, each with a unique combination of material type, material forms, and structural geometry. Two manufacturing techniques, tow placement and tape lamination, were used to build panels representative of potential fuselage crown, keel, and lower side-panel designs. Various combinations of impactor variables representing various foreign-object-impact threats to the aircraft were examined. Impacts performed at different structural locations within each panel (e.g., skin midbay, stiffener attaching flange, etc.) were considered separate parallel experiments. The relationship between input variables, measured damage states, and structural response to this damage are presented including recommendations for materials and impact test methods for fuselage structure.

Recurrence-plot-based measures of complexity and their application to heart-rate-variability data.

PubMed

Marwan, Norbert; Wessel, Niels; Meyerfeldt, Udo; Schirdewan, Alexander; Kurths, Jürgen

2002-08-01

The knowledge of transitions between regular, laminar or chaotic behaviors is essential to understand the underlying mechanisms behind complex systems. While several linear approaches are often insufficient to describe such processes, there are several nonlinear methods that, however, require rather long time observations. To overcome these difficulties, we propose measures of complexity based on vertical structures in recurrence plots and apply them to the logistic map as well as to heart-rate-variability data. For the logistic map these measures enable us not only to detect transitions between chaotic and periodic states, but also to identify laminar states, i.e., chaos-chaos transitions. The traditional recurrence quantification analysis fails to detect the latter transitions. Applying our measures to the heart-rate-variability data, we are able to detect and quantify the laminar phases before a life-threatening cardiac arrhythmia occurs thereby facilitating a prediction of such an event. Our findings could be of importance for the therapy of malignant cardiac arrhythmias.

A window on the deep ocean: The special value of ocean bottom pressure for monitoring the large-scale, deep-ocean circulation

NASA Astrophysics Data System (ADS)

Hughes, Chris W.; Williams, Joanne; Blaker, Adam; Coward, Andrew; Stepanov, Vladimir

2018-02-01

We show how, by focusing on bottom pressure measurements particularly on the global continental slope, it is possible to avoid the "fog" of mesoscale variability which dominates most observables in the deep ocean. This makes it possible to monitor those aspects of the ocean circulation which are most important for global scale ocean variability and climate. We therefore argue that such measurements should be considered an important future component of the Global Ocean Observing System, to complement the present open-ocean and coastal elements. Our conclusions are founded on both theoretical arguments, and diagnostics from a fine-resolution ocean model that has realistic amplitudes and spectra of mesoscale variability. These show that boundary pressure variations are coherent over along-slope distances of tens of thousands of kilometres, for several vertical modes. We illustrate the value of this in the model Atlantic, by determining the time for boundary and equatorial waves to complete a circuit of the northern basin (115 and 205 days for the first and second vertical modes), showing how the boundary features compare with basin-scale theoretical models, and demonstrating the ability to monitor the meridional overturning circulation using these boundary measurements. Finally, we discuss applicability to the real ocean and make recommendations on how to make such measurements without contamination from instrumental drift.

Success strivings and their relationship to affective work behaviors: gender differences.

PubMed

Chusmir, L H; Parker, B

1992-02-01

Gender differences in the importance of six life success dimensions and their relationships to job satisfaction, job involvement, and propensity to stay on the job were examined among 756 working women and men in southeast Florida. Results showed that the female participants rated family relationships, personal fulfillment, and security as more important success measures than their male counterparts did, and they rated status/wealth as less important. Professional fulfillment and security were not significantly different. The relationships between measures of success and work behaviors also varied significantly by gender, even after controlling for demographic and job position variables.

Relevance of anisotropy and spatial variability of gas diffusivity for soil-gas transport

NASA Astrophysics Data System (ADS)

Schack-Kirchner, Helmer; Kühne, Anke; Lang, Friederike

2017-04-01

Models of soil gas transport generally do not consider neither direction dependence of gas diffusivity, nor its small-scale variability. However, in a recent study, we could provide evidence for anisotropy favouring vertical gas diffusion in natural soils. We hypothesize that gas transport models based on gas diffusion data measured with soil rings are strongly influenced by both, anisotropy and spatial variability and the use of averaged diffusivities could be misleading. To test this we used a 2-dimensional model of soil gas transport to under compacted wheel tracks to model the soil-air oxygen distribution in the soil. The model was parametrized with data obtained from soil-ring measurements with its central tendency and variability. The model includes vertical parameter variability as well as variation perpendicular to the elongated wheel track. Different parametrization types have been tested: [i)]Averaged values for wheel track and undisturbed. em [ii)]Random distribution of soil cells with normally distributed variability within the strata. em [iii)]Random distributed soil cells with uniformly distributed variability within the strata. All three types of small-scale variability has been tested for [j)] isotropic gas diffusivity and em [jj)]reduced horizontal gas diffusivity (constant factor), yielding in total six models. As expected the different parametrizations had an important influence to the aeration state under wheel tracks with the strongest oxygen depletion in case of uniformly distributed variability and anisotropy towards higher vertical diffusivity. The simple simulation approach clearly showed the relevance of anisotropy and spatial variability in case of identical central tendency measures of gas diffusivity. However, until now it did not consider spatial dependency of variability, that could even aggravate effects. To consider anisotropy and spatial variability in gas transport models we recommend a) to measure soil-gas transport parameters spatially explicit including different directions and b) to use random-field stochastic models to assess the possible effects for gas-exchange models.

Measuring ICT Use and Contributing Conditions in Primary Schools

ERIC Educational Resources Information Center

Vanderlinde, Ruben; Aesaert, Koen; van Braak, Johan

2015-01-01

Information and communication technology (ICT) use became of major importance for primary schools across the world as ICT has the potential to foster teaching and learning processes. ICT use is therefore a central measurement concept (dependent variable) in many ICT integration studies. This data paper presents two datasets (2008 and 2011) that…

Predicting Word Reading and Comprehension with Executive Function and Speed Measures across Development: A Latent Variable Analysis

ERIC Educational Resources Information Center

Christopher, Micaela E.; Miyake, Akira; Keenan, Janice M.; Pennington, Bruce; DeFries, John C.; Wadsworth, Sally J.; Willcutt, Erik; Olson, Richard K.

2012-01-01

The present study explored whether different executive control and speed measures (working memory, inhibition, processing speed, and naming speed) independently predict individual differences in word reading and reading comprehension. Although previous studies suggest these cognitive constructs are important for reading, the authors analyze the…

Finding Autonomy in Activity: Development and Validation of a Democratic Classroom Survey

ERIC Educational Resources Information Center

Hur, Eun Hye; Glassman, Michael; Kim, Yunhwan

2013-01-01

This paper developed a Democratic Classroom Survey to measure students' perceived democratic environment of the classroom. Perceived democratic environment is one of the most important variables for understanding classroom activity and indeed any type of group activity, but actually measuring perceptions in an objective manner has been…

Regression dilution bias: tools for correction methods and sample size calculation.

PubMed

Berglund, Lars

2012-08-01

Random errors in measurement of a risk factor will introduce downward bias of an estimated association to a disease or a disease marker. This phenomenon is called regression dilution bias. A bias correction may be made with data from a validity study or a reliability study. In this article we give a non-technical description of designs of reliability studies with emphasis on selection of individuals for a repeated measurement, assumptions of measurement error models, and correction methods for the slope in a simple linear regression model where the dependent variable is a continuous variable. Also, we describe situations where correction for regression dilution bias is not appropriate. The methods are illustrated with the association between insulin sensitivity measured with the euglycaemic insulin clamp technique and fasting insulin, where measurement of the latter variable carries noticeable random error. We provide software tools for estimation of a corrected slope in a simple linear regression model assuming data for a continuous dependent variable and a continuous risk factor from a main study and an additional measurement of the risk factor in a reliability study. Also, we supply programs for estimation of the number of individuals needed in the reliability study and for choice of its design. Our conclusion is that correction for regression dilution bias is seldom applied in epidemiological studies. This may cause important effects of risk factors with large measurement errors to be neglected.

Relation of agronomic and multispectral reflectance characteristics of spring wheat canopies

NASA Technical Reports Server (NTRS)

Bauer, M. E. (Principal Investigator); Ahlrichs, J. S.

1982-01-01

The relationships between crop canopy variables such as leaf area index (LAI) and their multispectral reflectance properties were investigated along with the potential for estimating canopy variables from remotely sensed reflectance measurements. Reflectance spectra over the 0.4 to 2.5 micron wavelength range were acquired during each of the major development stages of spring wheat canopies at Williston, North Dakota, during three seasons. Treatments included planting date, N fertilization, cultivar, and soil moisture. Agronomic measurements included development stage, biomass, LAI, and percent soil cover. High correlations were found between reflectance and percent cover, LAI, and biomass. A near infrared wavelength band, 0.76 to 0.90 microns, was most important in explaining variation in LAI and percent cover, while a middle infrared band, 2.08 to 2.35 microns, explained the most variation in biomass and plant water content. Transformations, including the near infrared/red reflectance ratio and greenness index, were also highly correlated to canopy variables. The relationship of canopy variables to reflectance decreased as the crop began to ripen. the canopy variables could be accurately predicted using measurements from three to five wavelength bands. The wavelength bands proposed for the thematic mapper sensor were more strongly related to the canopy variables than the LANDSAT MSS bands.

Observations and Models of Highly Intermittent Phytoplankton Distributions

PubMed Central

Mandal, Sandip; Locke, Christopher; Tanaka, Mamoru; Yamazaki, Hidekatsu

2014-01-01

The measurement of phytoplankton distributions in ocean ecosystems provides the basis for elucidating the influences of physical processes on plankton dynamics. Technological advances allow for measurement of phytoplankton data to greater resolution, displaying high spatial variability. In conventional mathematical models, the mean value of the measured variable is approximated to compare with the model output, which may misinterpret the reality of planktonic ecosystems, especially at the microscale level. To consider intermittency of variables, in this work, a new modelling approach to the planktonic ecosystem is applied, called the closure approach. Using this approach for a simple nutrient-phytoplankton model, we have shown how consideration of the fluctuating parts of model variables can affect system dynamics. Also, we have found a critical value of variance of overall fluctuating terms below which the conventional non-closure model and the mean value from the closure model exhibit the same result. This analysis gives an idea about the importance of the fluctuating parts of model variables and about when to use the closure approach. Comparisons of plot of mean versus standard deviation of phytoplankton at different depths, obtained using this new approach with real observations, give this approach good conformity. PMID:24787740

Variability of the human heart rate as a diagnostic instrument obtained by mean of a wireless monitor

NASA Astrophysics Data System (ADS)

Barajas Mauricio, Sánchez; Hernández González, Martha Alicia; Figueroa Vega, Nicte; Malacara Hernández, Juan Manuel; Fraga Teodoro, Córdova

2014-11-01

Introduction: Heart rate variability (HRV) is the cyclic measurement of RR intervals between normal beats. Aim: To determine the VFC via a wireless Polar monitor. Material and methods: 100 symptomatic menopausal women were studied for measurements of HRV were I post a Polar RS400 Watch four hrs. Results: Obtained through the fast Fourier transform, the frequency domain HRV low frequency (LF) 0.04-0.15 Hz, high frequency (HF) 0.15-0.4Hz and the ratio LF / HF. Conclusion: obtaining HRV is important for cardiovascular autonomic assessment in menopausal women.

Contrasting determinants for the introduction and establishment success of exotic birds in Taiwan using decision trees models.

PubMed

Liang, Shih-Hsiung; Walther, Bruno Andreas; Shieh, Bao-Sen

2017-01-01

Biological invasions have become a major threat to biodiversity, and identifying determinants underlying success at different stages of the invasion process is essential for both prevention management and testing ecological theories. To investigate variables associated with different stages of the invasion process in a local region such as Taiwan, potential problems using traditional parametric analyses include too many variables of different data types (nominal, ordinal, and interval) and a relatively small data set with too many missing values. We therefore used five decision tree models instead and compared their performance. Our dataset contains 283 exotic bird species which were transported to Taiwan; of these 283 species, 95 species escaped to the field successfully (introduction success); of these 95 introduced species, 36 species reproduced in the field of Taiwan successfully (establishment success). For each species, we collected 22 variables associated with human selectivity and species traits which may determine success during the introduction stage and establishment stage. For each decision tree model, we performed three variable treatments: (I) including all 22 variables, (II) excluding nominal variables, and (III) excluding nominal variables and replacing ordinal values with binary ones. Five performance measures were used to compare models, namely, area under the receiver operating characteristic curve (AUROC), specificity, precision, recall, and accuracy. The gradient boosting models performed best overall among the five decision tree models for both introduction and establishment success and across variable treatments. The most important variables for predicting introduction success were the bird family, the number of invaded countries, and variables associated with environmental adaptation, whereas the most important variables for predicting establishment success were the number of invaded countries and variables associated with reproduction. Our final optimal models achieved relatively high performance values, and we discuss differences in performance with regard to sample size and variable treatments. Our results showed that, for both the establishment model and introduction model, the number of invaded countries was the most important or second most important determinant, respectively. Therefore, we suggest that future success for introduction and establishment of exotic birds may be gauged by simply looking at previous success in invading other countries. Finally, we found that species traits related to reproduction were more important in establishment models than in introduction models; importantly, these determinants were not averaged but either minimum or maximum values of species traits. Therefore, we suggest that in addition to averaged values, reproductive potential represented by minimum and maximum values of species traits should be considered in invasion studies.

Contrasting determinants for the introduction and establishment success of exotic birds in Taiwan using decision trees models

PubMed Central

Liang, Shih-Hsiung; Walther, Bruno Andreas

2017-01-01

Background Biological invasions have become a major threat to biodiversity, and identifying determinants underlying success at different stages of the invasion process is essential for both prevention management and testing ecological theories. To investigate variables associated with different stages of the invasion process in a local region such as Taiwan, potential problems using traditional parametric analyses include too many variables of different data types (nominal, ordinal, and interval) and a relatively small data set with too many missing values. Methods We therefore used five decision tree models instead and compared their performance. Our dataset contains 283 exotic bird species which were transported to Taiwan; of these 283 species, 95 species escaped to the field successfully (introduction success); of these 95 introduced species, 36 species reproduced in the field of Taiwan successfully (establishment success). For each species, we collected 22 variables associated with human selectivity and species traits which may determine success during the introduction stage and establishment stage. For each decision tree model, we performed three variable treatments: (I) including all 22 variables, (II) excluding nominal variables, and (III) excluding nominal variables and replacing ordinal values with binary ones. Five performance measures were used to compare models, namely, area under the receiver operating characteristic curve (AUROC), specificity, precision, recall, and accuracy. Results The gradient boosting models performed best overall among the five decision tree models for both introduction and establishment success and across variable treatments. The most important variables for predicting introduction success were the bird family, the number of invaded countries, and variables associated with environmental adaptation, whereas the most important variables for predicting establishment success were the number of invaded countries and variables associated with reproduction. Discussion Our final optimal models achieved relatively high performance values, and we discuss differences in performance with regard to sample size and variable treatments. Our results showed that, for both the establishment model and introduction model, the number of invaded countries was the most important or second most important determinant, respectively. Therefore, we suggest that future success for introduction and establishment of exotic birds may be gauged by simply looking at previous success in invading other countries. Finally, we found that species traits related to reproduction were more important in establishment models than in introduction models; importantly, these determinants were not averaged but either minimum or maximum values of species traits. Therefore, we suggest that in addition to averaged values, reproductive potential represented by minimum and maximum values of species traits should be considered in invasion studies. PMID:28316893

Novel measures of response performance and inhibition in children with ADHD.

PubMed

Morein-Zamir, Sharon; Hommersen, Paul; Johnston, Charlotte; Kingstone, Alan

2008-11-01

Fifteen children with ADHD aged 8 to 12 years and age and gender matched controls performed two different stopping tasks to examine response performance and inhibition and their respective moment-to-moment variability. One task was the well-established stop-signal task, while the other was a novel tracking task where the children tracked a spaceship on the screen until an alarm indicated they should stop. Although performance was discrete in the stop signal task and continuous in the tracking task, in both tasks latencies to the stop signal were significantly slowed in children with ADHD. Go performance and variability did not significantly differ between ADHD and control children in either task. Importantly, stopping latency in the novel spaceship tracking task also was more variable in children with ADHD. As stopping variability cannot be measured using the standard stop signal task, the new task offers compelling support for the heretofore untested prediction that stopping is both slowed and more variable in children with ADHD. The results support a response inhibition impairment in ADHD, whilst limiting the extent of an intra-trial variability deficit.

Characteristics of temperature rise in variable inductor employing magnetorheological fluid driven by a high-frequency pulsed voltage source

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

Lee, Ho-Young; Kang, In Man, E-mail: imkang@ee.knu.ac.kr; Shon, Chae-Hwa

2015-05-07

A variable inductor with magnetorheological (MR) fluid has been successfully applied to power electronics applications; however, its thermal characteristics have not been investigated. To evaluate the performance of the variable inductor with respect to temperature, we measured the characteristics of temperature rise and developed a numerical analysis technique. The characteristics of temperature rise were determined experimentally and verified numerically by adopting a multiphysics analysis technique. In order to accurately estimate the temperature distribution in a variable inductor with an MR fluid-gap, the thermal solver should import the heat source from the electromagnetic solver to solve the eddy current problem. Tomore » improve accuracy, the B–H curves of the MR fluid under operating temperature were obtained using the magnetic property measurement system. In addition, the Steinmetz equation was applied to evaluate the core loss in a ferrite core. The predicted temperature rise for a variable inductor showed good agreement with the experimental data and the developed numerical technique can be employed to design a variable inductor with a high-frequency pulsed voltage source.« less

Gaussian Mixture Model of Heart Rate Variability

PubMed Central

Costa, Tommaso; Boccignone, Giuseppe; Ferraro, Mario

2012-01-01

Heart rate variability (HRV) is an important measure of sympathetic and parasympathetic functions of the autonomic nervous system and a key indicator of cardiovascular condition. This paper proposes a novel method to investigate HRV, namely by modelling it as a linear combination of Gaussians. Results show that three Gaussians are enough to describe the stationary statistics of heart variability and to provide a straightforward interpretation of the HRV power spectrum. Comparisons have been made also with synthetic data generated from different physiologically based models showing the plausibility of the Gaussian mixture parameters. PMID:22666386

Physical and psychosocial prerequisites of functioning in relation to work ability and general subjective well-being among office workers.

PubMed

Sjögren-Rönkä, Tuulikki; Ojanen, Markku T; Leskinen, Esko K; Tmustalampi, Sirpa; Mälkiä, Esko A

2002-06-01

The purpose of the study was to investigate the physical and psychological prerequisites of functioning, as well as the social environment at work and personal factors, in relation to work ability and general subjective well-being in a group of office workers. The study was a descriptive cross-sectional investigation, using path analysis, of office workers. The subjects comprised 88 volunteers, 24 men and 64 women, from the same workplace [mean age 45.7 (SD 8.6) years]. The independent variables were measured using psychosocial and physical questionnaires and physical measurements. The first dependent variable, work ability, was measured by a work ability index. The second dependent variable, general subjective well-being, was assessed by life satisfaction and meaning of life. The variables were structured according to a modified version of the International Classification of Functioning, Disability and Health. Forward flexion of the spine, intensity of musculoskeletal symptoms, self-confidence, and mental stress at work explained 58% of work ability and had indirect effects on general subjective well-being. Self-confidence, mood, and work ability had a direct effect on general subjective well-being. The model developed explained 68% of general subjective well-being. Age played a significant role in this study population. The prerequisites of physical functioning are important in maintaining work ability, particularly among aging workers, and psychological prerequisites of functioning are of even greater importance in maintaining general subjective well-being.

A Framework to Guide the Assessment of Human-Machine Systems.

PubMed

Stowers, Kimberly; Oglesby, James; Sonesh, Shirley; Leyva, Kevin; Iwig, Chelsea; Salas, Eduardo

2017-03-01

We have developed a framework for guiding measurement in human-machine systems. The assessment of safety and performance in human-machine systems often relies on direct measurement, such as tracking reaction time and accidents. However, safety and performance emerge from the combination of several variables. The assessment of precursors to safety and performance are thus an important part of predicting and improving outcomes in human-machine systems. As part of an in-depth literature analysis involving peer-reviewed, empirical articles, we located and classified variables important to human-machine systems, giving a snapshot of the state of science on human-machine system safety and performance. Using this information, we created a framework of safety and performance in human-machine systems. This framework details several inputs and processes that collectively influence safety and performance. Inputs are divided according to human, machine, and environmental inputs. Processes are divided into attitudes, behaviors, and cognitive variables. Each class of inputs influences the processes and, subsequently, outcomes that emerge in human-machine systems. This framework offers a useful starting point for understanding the current state of the science and measuring many of the complex variables relating to safety and performance in human-machine systems. This framework can be applied to the design, development, and implementation of automated machines in spaceflight, military, and health care settings. We present a hypothetical example in our write-up of how it can be used to aid in project success.

Gait variability and basal ganglia disorders: stride-to-stride variations of gait cycle timing in Parkinson's disease and Huntington's disease

NASA Technical Reports Server (NTRS)

Hausdorff, J. M.; Cudkowicz, M. E.; Firtion, R.; Wei, J. Y.; Goldberger, A. L.

1998-01-01

The basal ganglia are thought to play an important role in regulating motor programs involved in gait and in the fluidity and sequencing of movement. We postulated that the ability to maintain a steady gait, with low stride-to-stride variability of gait cycle timing and its subphases, would be diminished with both Parkinson's disease (PD) and Huntington's disease (HD). To test this hypothesis, we obtained quantitative measures of stride-to-stride variability of gait cycle timing in subjects with PD (n = 15), HD (n = 20), and disease-free controls (n = 16). All measures of gait variability were significantly increased in PD and HD. In subjects with PD and HD, gait variability measures were two and three times that observed in control subjects, respectively. The degree of gait variability correlated with disease severity. In contrast, gait speed was significantly lower in PD, but not in HD, and average gait cycle duration and the time spent in many subphases of the gait cycle were similar in control subjects, HD subjects, and PD subjects. These findings are consistent with a differential control of gait variability, speed, and average gait cycle timing that may have implications for understanding the role of the basal ganglia in locomotor control and for quantitatively assessing gait in clinical settings.

Reliability of the Parabola Approximation Method in Heart Rate Variability Analysis Using Low-Sampling-Rate Photoplethysmography.

PubMed

Baek, Hyun Jae; Shin, JaeWook; Jin, Gunwoo; Cho, Jaegeol

2017-10-24

Photoplethysmographic signals are useful for heart rate variability analysis in practical ambulatory applications. While reducing the sampling rate of signals is an important consideration for modern wearable devices that enable 24/7 continuous monitoring, there have not been many studies that have investigated how to compensate the low timing resolution of low-sampling-rate signals for accurate heart rate variability analysis. In this study, we utilized the parabola approximation method and measured it against the conventional cubic spline interpolation method for the time, frequency, and nonlinear domain variables of heart rate variability. For each parameter, the intra-class correlation, standard error of measurement, Bland-Altman 95% limits of agreement and root mean squared relative error were presented. Also, elapsed time taken to compute each interpolation algorithm was investigated. The results indicated that parabola approximation is a simple, fast, and accurate algorithm-based method for compensating the low timing resolution of pulse beat intervals. In addition, the method showed comparable performance with the conventional cubic spline interpolation method. Even though the absolute value of the heart rate variability variables calculated using a signal sampled at 20 Hz were not exactly matched with those calculated using a reference signal sampled at 250 Hz, the parabola approximation method remains a good interpolation method for assessing trends in HRV measurements for low-power wearable applications.

A brief review and clinical application of heart rate variability biofeedback in sports, exercise, and rehabilitation medicine.

PubMed

Prinsloo, Gabriell E; Rauch, H G Laurie; Derman, Wayne E

2014-05-01

An important component of the effective management of chronic noncommunicable disease is the assessment and management of psychosocial stress. The measurement and modulation of heart rate variability (HRV) may be valuable in this regard. To describe the measurement and physiological control of HRV; to describe the impact of psychosocial stress on cardiovascular disease, metabolic syndrome, and chronic respiratory disease, and the relationship between these diseases and changes in HRV; and to describe the influence of biofeedback and exercise on HRV and the use of HRV biofeedback in the management of chronic disease. The PubMed, Medline, and Embase databases were searched (up to August 2013). Additional articles were obtained from the reference lists of relevant articles and reviews. Articles were individually selected for further review based on the quality and focus of the study, and the population studied. Heart rate variability is reduced in stress and in many chronic diseases, and may even predict the development and prognosis of some diseases. Heart rate variability can be increased with both exercise and biofeedback. Although the research on the effect of exercise is conflicting, there is evidence that aerobic training may increase HRV and cardiac vagal tone both in healthy individuals and in patients with disease. Heart rate variability biofeedback is also an effective method of increasing HRV and cardiac vagal tone, and has been shown to decrease stress and reduce the morbidity and mortality of disease. The assessment and management of psychosocial stress is a challenging but important component of effective comprehensive lifestyle interventions for the management of noncommunicable disease. It is, therefore, important for the sports and exercise physician to have an understanding of the therapeutic use of HRV modulation, both in the reduction of stress and in the management of chronic disease.

Assessing Soil Organic C Stability at the Continental Scale: An Analysis of Soil C and Radiocarbon Profiles Across the NEON Sites

NASA Astrophysics Data System (ADS)

Heckman, K. A.; Gallo, A.; Hatten, J. A.; Swanston, C.; McKnight, D. M.; Strahm, B. D.; Sanclements, M.

2017-12-01

Soil carbon stocks have become recognized as increasingly important in the context of climate change and global C cycle modeling. As modelers seek to identify key parameters affecting the size and stability of belowground C stocks, attention has been drawn to the mineral matrix and the soil physiochemical factors influenced by it. Though clay content has often been utilized as a convenient and key explanatory variable for soil C dynamics, its utility has recently come under scrutiny as new paradigms of soil organic matter stabilization have been developed. We utilized soil cores from a range of National Ecological Observatory Network (NEON) experimental plots to examine the influence of physicochemical parameters on soil C stocks and turnover, and their relative importance in comparison to climatic variables. Soils were cored at NEON sites, sampled by genetic horizon, and density separated into light fractions (particulate organics neither occluded within aggregates nor associated with mineral surfaces), occluded fractions (particulate organics occluded within aggregates), and heavy fractions (organics associated with mineral surfaces). Bulk soils and density fractions were measured for % C and radiocarbon abundance (as a measure of C stability). Carbon and radiocarbon abundances were examined among fractions and in the context of climatic variables (temperature, precipitation, elevation) and soil physiochemical variables (% clay and pH). No direct relationships between temperature and soil C or radiocarbon abundances were found. As a whole, soil radiocarbon abundance in density fractions decreased in the order of light>heavy>occluded, highlighting the importance of both surface sorption and aggregation to the preservation of organics. Radiocarbon abundance was correlated with pH, with variance also grouping by dominate vegetation type. Soil order was also identified as an important proxy variable for C and radiocarbon abundance. Preliminary results suggest that both integrative proxies as well as physicochemical properties may be needed to account for variation in soil C abundance and stability at the continental scale.

Estimation of electrical conductivity distribution within the human head from magnetic flux density measurement.

PubMed

Gao, Nuo; Zhu, S A; He, Bin

2005-06-07

We have developed a new algorithm for magnetic resonance electrical impedance tomography (MREIT), which uses only one component of the magnetic flux density to reconstruct the electrical conductivity distribution within the body. The radial basis function (RBF) network and simplex method are used in the present approach to estimate the conductivity distribution by minimizing the errors between the 'measured' and model-predicted magnetic flux densities. Computer simulations were conducted in a realistic-geometry head model to test the feasibility of the proposed approach. Single-variable and three-variable simulations were performed to estimate the brain-skull conductivity ratio and the conductivity values of the brain, skull and scalp layers. When SNR = 15 for magnetic flux density measurements with the target skull-to-brain conductivity ratio being 1/15, the relative error (RE) between the target and estimated conductivity was 0.0737 +/- 0.0746 in the single-variable simulations. In the three-variable simulations, the RE was 0.1676 +/- 0.0317. Effects of electrode position uncertainty were also assessed by computer simulations. The present promising results suggest the feasibility of estimating important conductivity values within the head from noninvasive magnetic flux density measurements.

Single-cell measurement of red blood cell oxygen affinity.

PubMed

Di Caprio, Giuseppe; Stokes, Chris; Higgins, John M; Schonbrun, Ethan

2015-08-11

Oxygen is transported throughout the body by hemoglobin (Hb) in red blood cells (RBCs). Although the oxygen affinity of blood is well-understood and routinely assessed in patients by pulse oximetry, variability at the single-cell level has not been previously measured. In contrast, single-cell measurements of RBC volume and Hb concentration are taken millions of times per day by clinical hematology analyzers, and they are important factors in determining the health of the hematologic system. To better understand the variability and determinants of oxygen affinity on a cellular level, we have developed a system that quantifies the oxygen saturation, cell volume, and Hb concentration for individual RBCs in high throughput. We find that the variability in single-cell saturation peaks at an oxygen partial pressure of 2.9%, which corresponds to the maximum slope of the oxygen-Hb dissociation curve. In addition, single-cell oxygen affinity is positively correlated with Hb concentration but independent of osmolarity, which suggests variation in the Hb to 2,3-diphosphoglycerate (2-3 DPG) ratio on a cellular level. By quantifying the functional behavior of a cellular population, our system adds a dimension to blood cell analysis and other measurements of single-cell variability.

Single-cell measurement of red blood cell oxygen affinity

PubMed Central

Di Caprio, Giuseppe; Stokes, Chris; Higgins, John M.; Schonbrun, Ethan

2015-01-01

Oxygen is transported throughout the body by hemoglobin (Hb) in red blood cells (RBCs). Although the oxygen affinity of blood is well-understood and routinely assessed in patients by pulse oximetry, variability at the single-cell level has not been previously measured. In contrast, single-cell measurements of RBC volume and Hb concentration are taken millions of times per day by clinical hematology analyzers, and they are important factors in determining the health of the hematologic system. To better understand the variability and determinants of oxygen affinity on a cellular level, we have developed a system that quantifies the oxygen saturation, cell volume, and Hb concentration for individual RBCs in high throughput. We find that the variability in single-cell saturation peaks at an oxygen partial pressure of 2.9%, which corresponds to the maximum slope of the oxygen–Hb dissociation curve. In addition, single-cell oxygen affinity is positively correlated with Hb concentration but independent of osmolarity, which suggests variation in the Hb to 2,3-diphosphoglycerate (2–3 DPG) ratio on a cellular level. By quantifying the functional behavior of a cellular population, our system adds a dimension to blood cell analysis and other measurements of single-cell variability. PMID:26216973

Correspondence of biological condition models of California streams at statewide and regional scales.

PubMed

May, Jason T; Brown, Larry R; Rehn, Andrew C; Waite, Ian R; Ode, Peter R; Mazor, Raphael D; Schiff, Kenneth C

2015-01-01

We used boosted regression trees (BRT) to model stream biological condition as measured by benthic macroinvertebrate taxonomic completeness, the ratio of observed to expected (O/E) taxa. Models were developed with and without exclusion of rare taxa at a site. BRT models are robust, requiring few assumptions compared with traditional modeling techniques such as multiple linear regression. The BRT models were constructed to provide baseline support to stressor delineation by identifying natural physiographic and human land use gradients affecting stream biological condition statewide and for eight ecological regions within the state, as part of the development of numerical biological objectives for California's wadeable streams. Regions were defined on the basis of ecological, hydrologic, and jurisdictional factors and roughly corresponded with ecoregions. Physiographic and land use variables were derived from geographic information system coverages. The model for the entire state (n = 1,386) identified a composite measure of anthropogenic disturbance (the sum of urban, agricultural, and unmanaged roadside vegetation land cover) within the local watershed as the most important variable, explaining 56% of the variance in O/E values. Models for individual regions explained between 51 and 84% of the variance in O/E values. Measures of human disturbance were important in the three coastal regions. In the South Coast and Coastal Chaparral, local watershed measures of urbanization were the most important variables related to biological condition, while in the North Coast the composite measure of human disturbance at the watershed scale was most important. In the two mountain regions, natural gradients were most important, including slope, precipitation, and temperature. The remaining three regions had relatively small sample sizes (n ≤ 75 sites) and had models that gave mixed results. Understanding the spatial scale at which land use and land cover affect taxonomic completeness is imperative for sound management. Our results suggest that invertebrate taxonomic completeness is affected by human disturbance at the statewide and regional levels, with some differences among regions in the importance of natural gradients and types of human disturbance. The construction and application of models similar to the ones presented here could be useful in the planning and prioritization of actions for protection and conservation of biodiversity in California streams.

Correspondence of biological condition models of California streams at statewide and regional scales

USGS Publications Warehouse

May, Jason T.; Brown, Larry R.; Rehn, Andrew C.; Waite, Ian R.; Ode, Peter R; Mazor, Raphael D; Schiff, Kenneth C

2015-01-01

We used boosted regression trees (BRT) to model stream biological condition as measured by benthic macroinvertebrate taxonomic completeness, the ratio of observed to expected (O/E) taxa. Models were developed with and without exclusion of rare taxa at a site. BRT models are robust, requiring few assumptions compared with traditional modeling techniques such as multiple linear regression. The BRT models were constructed to provide baseline support to stressor delineation by identifying natural physiographic and human land use gradients affecting stream biological condition statewide and for eight ecological regions within the state, as part of the development of numerical biological objectives for California’s wadeable streams. Regions were defined on the basis of ecological, hydrologic, and jurisdictional factors and roughly corresponded with ecoregions. Physiographic and land use variables were derived from geographic information system coverages. The model for the entire state (n = 1,386) identified a composite measure of anthropogenic disturbance (the sum of urban, agricultural, and unmanaged roadside vegetation land cover) within the local watershed as the most important variable, explaining 56 % of the variance in O/E values. Models for individual regions explained between 51 and 84 % of the variance in O/E values. Measures of human disturbance were important in the three coastal regions. In the South Coast and Coastal Chaparral, local watershed measures of urbanization were the most important variables related to biological condition, while in the North Coast the composite measure of human disturbance at the watershed scale was most important. In the two mountain regions, natural gradients were most important, including slope, precipitation, and temperature. The remaining three regions had relatively small sample sizes (n ≤ 75 sites) and had models that gave mixed results. Understanding the spatial scale at which land use and land cover affect taxonomic completeness is imperative for sound management. Our results suggest that invertebrate taxonomic completeness is affected by human disturbance at the statewide and regional levels, with some differences among regions in the importance of natural gradients and types of human disturbance. The construction and application of models similar to the ones presented here could be useful in the planning and prioritization of actions for protection and conservation of biodiversity in California streams.

Dimensions Underlying Measures of Disability, Personal Factors, and Health Status in Cervical Radiculopathy

PubMed Central

Halvorsen, Marie; Kierkegaard, Marie; Harms-Ringdahl, Karin; Peolsson, Anneli; Dedering, Åsa

2015-01-01

Abstract This cross-sectional study sought to identify dimensions underlying measures of impairment, disability, personal factors, and health status in patients with cervical radiculopathy. One hundred twenty-four patients with magnetic resonance imaging-verified cervical radiculopathy, attending a neurosurgery clinic in Sweden, participated. Data from clinical tests and questionnaires on disability, personal factors, and health status were used in a principal-component analysis (PCA) with oblique rotation. The PCA supported a 3-component model including 14 variables from clinical tests and questionnaires, accounting for 73% of the cumulative percentage. The first component, pain and disability, explained 56%. The second component, health, fear-avoidance beliefs, kinesiophobia, and self-efficacy, explained 9.2%. The third component including anxiety, depression, and catastrophizing explained 7.6%. The strongest-loading variables of each dimension were “present neck pain intensity,” “fear avoidance,” and “anxiety.” The three underlying dimensions identified and labeled Pain and functioning, Health, beliefs, and kinesiophobia, and Mood state and catastrophizing captured aspects of importance for cervical radiculopathy. Since the variables “present neck pain intensity,” “fear avoidance,” and “anxiety” had the strongest loading in each of the three dimensions; it may be important to include them in a reduced multidimensional measurement set in cervical radiculopathy. PMID:26091482

Dimensions Underlying Measures of Disability, Personal Factors, and Health Status in Cervical Radiculopathy: A Cross-Sectional Study.

PubMed

Halvorsen, Marie; Kierkegaard, Marie; Harms-Ringdahl, Karin; Peolsson, Anneli; Dedering, Åsa

2015-06-01

This cross-sectional study sought to identify dimensions underlying measures of impairment, disability, personal factors, and health status in patients with cervical radiculopathy. One hundred twenty-four patients with magnetic resonance imaging-verified cervical radiculopathy, attending a neurosurgery clinic in Sweden, participated. Data from clinical tests and questionnaires on disability, personal factors, and health status were used in a principal-component analysis (PCA) with oblique rotation. The PCA supported a 3-component model including 14 variables from clinical tests and questionnaires, accounting for 73% of the cumulative percentage. The first component, pain and disability, explained 56%. The second component, health, fear-avoidance beliefs, kinesiophobia, and self-efficacy, explained 9.2%. The third component including anxiety, depression, and catastrophizing explained 7.6%. The strongest-loading variables of each dimension were "present neck pain intensity," "fear avoidance," and "anxiety." The three underlying dimensions identified and labeled Pain and functioning, Health, beliefs, and kinesiophobia, and Mood state and catastrophizing captured aspects of importance for cervical radiculopathy. Since the variables "present neck pain intensity," "fear avoidance," and "anxiety" had the strongest loading in each of the three dimensions; it may be important to include them in a reduced multidimensional measurement set in cervical radiculopathy.

Four Dimensions of Student Leadership: What Predicts Students' Attitudes toward Leadership Development?

ERIC Educational Resources Information Center

Shertzer, John; Wall, Vernon; Frandsen, Alisa; Guo, Yan; Whalen, Donald F.; Shelley, Mack C., II

2005-01-01

Multiple regression was performed on four dependent variables derived from the results of a student survey measuring attitudes about student leadership: (a) leadership is important to the student, (b) the student considers himself or herself to be a leader, (c) leadership will be important to the student after college, and (d) leaders need to be…

Measuring and modeling CO2 and H2O fluxes in complex terrain

Treesearch

Diego A. Riveros-Iregui; Brian L. McGlynn

2008-01-01

The feedbacks between the water and the carbon cycles are of critical importance to global carbon balances. Forests and forest soils in northern latitudes are important carbon pools because of their potential as sinks for atmospheric carbon. However there are significant unknowns related to the effects of hydrologic variability, mountainous terrain, and landscape...

Measures of Heart Rate Variability and How They Relate to Age, Gender, Emotional Behavior, and Academic Achievement in Elementary School Children in Adventist and Public Schools

ERIC Educational Resources Information Center

Dalton, Marilee Serns

2013-01-01

The analysis of heart rate variability (HRV) is one tool shown to be of value in examining heart-brain interactions. HRV is remarkably responsive to emotion, and the importance of emotional state in cognitive function is increasingly being recognized and socio-emotional learning strategies being utilized in the classroom. Consequently, the…

Quantifying Spatial and Seasonal Variability in Atmospheric Ammonia with In Situ and Space-Based Observations

NASA Technical Reports Server (NTRS)

Pinder, Robert W.; Walker, John T.; Bash, Jesse O.; Cady-Pereira, Karen E.; Henze, Daven K.; Luo, Mingzhao; Osterman, Gregory B.; Shepard, Mark W.

2011-01-01

Ammonia plays an important role in many biogeochemical processes, yet atmospheric mixing ratios are not well known. Recently, methods have been developed for retrieving NH3 from space-based observations, but they have not been compared to in situ measurements. We have conducted a field campaign combining co-located surface measurements and satellite special observations from the Tropospheric Emission Spectrometer (TES). Our study includes 25 surface monitoring sites spanning 350 km across eastern North Carolina, a region with large seasonal and spatial variability in NH3. From the TES spectra, we retrieve a NH3 representative volume mixing ratio (RVMR), and we restrict our analysis to times when the region of the atmosphere observed by TES is representative of the surface measurement. We find that the TES NH3 RVMR qualitatively captures the seasonal and spatial variability found in eastern North Carolina. Both surface measurements and TES NH3 show a strong correspondence with the number of livestock facilities within 10 km of the observation. Furthermore, we find that TES H3 RVMR captures the month-to-month variability present in the surface observations. The high correspondence with in situ measurements and vast spatial coverage make TES NH3 RVMR a valuable tool for understanding regional and global NH3 fluxes.

Variability of carotid artery measurements on 3-Tesla MRI and its impact on sample size calculation for clinical research.

PubMed

Syed, Mushabbar A; Oshinski, John N; Kitchen, Charles; Ali, Arshad; Charnigo, Richard J; Quyyumi, Arshed A

2009-08-01

Carotid MRI measurements are increasingly being employed in research studies for atherosclerosis imaging. The majority of carotid imaging studies use 1.5 T MRI. Our objective was to investigate intra-observer and inter-observer variability in carotid measurements using high resolution 3 T MRI. We performed 3 T carotid MRI on 10 patients (age 56 +/- 8 years, 7 male) with atherosclerosis risk factors and ultrasound intima-media thickness > or =0.6 mm. A total of 20 transverse images of both right and left carotid arteries were acquired using T2 weighted black-blood sequence. The lumen and outer wall of the common carotid and internal carotid arteries were manually traced; vessel wall area, vessel wall volume, and average wall thickness measurements were then assessed for intra-observer and inter-observer variability. Pearson and intraclass correlations were used in these assessments, along with Bland-Altman plots. For inter-observer variability, Pearson correlations ranged from 0.936 to 0.996 and intraclass correlations from 0.927 to 0.991. For intra-observer variability, Pearson correlations ranged from 0.934 to 0.954 and intraclass correlations from 0.831 to 0.948. Calculations showed that inter-observer variability and other sources of error would inflate sample size requirements for a clinical trial by no more than 7.9%, indicating that 3 T MRI is nearly optimal in this respect. In patients with subclinical atherosclerosis, 3 T carotid MRI measurements are highly reproducible and have important implications for clinical trial design.

[Diabetes type 1 in young adults: The relationship between psycho-social variables, glycemic control, depression and anxiety].

PubMed

Steinsdottir, Fjola Katrin; Halldorsdottir, Hildur; Gudmundsdottir, Arna; Arnardottir, Steinunn; Smari, Jakop; Arnarson, Eirikur Orn

2008-12-01

The aim of the present study was to investigate whether psycho-social variables, for example social support and task- and emotion-oriented coping would predict psychological and physical well being among young adults with diabetes. Participants were 56 individuals in their twenties suffering from type 1 diabetes. Response rate was 78%. The participants came from the whole of Iceland, 64.3% from the Greater Reykjavík area and 33.9% from rural areas. One participant did not indicate his place of residence. Self-assessment scales were used to assess depression, anxiety, task-, avoidance- and emotion-oriented coping, social support and problems relating to diabetes. Additional information was obtained from patients' records concerning the results of blood glucose measurements (HbA1c). Good social support was related to less anxiety and depression and to less self-reported problems related to having diabetes. Emotion-oriented coping was related to not feeling well and task- oriented coping to feeling better. No relationship was found between psychosocial variables and blood glucose measurements and a limited relationship between self-reported problems related to having diabetes and these measurements. Social support and coping are strongly related to measurements of depression, anxiety and problems related to having diabetes in the present age group. The results indicate that it is very important to teach and strengthen usage, as possible, of task-oriented coping instead of emotion-oriented coping. The results also indicate that social support is highly important for young adults with diabetes type 1. It is clear that friends and family have to be more involved in the treatment and also more educated about the disease and the importance of giving the right kind of support.

Genetic Influence on Slope Variability in a Childhood Reflexive Attention Task.

PubMed

Lundwall, Rebecca A; Watkins, Jeffrey K

2015-01-01

Individuals are not perfectly consistent, and interindividual variability is a common feature in all varieties of human behavior. Some individuals respond more variably than others, however, and this difference may be important to understanding how the brain works. In this paper, we explore genetic contributions to response time (RT) slope variability on a reflexive attention task. We are interested in such variability because we believe it is an important part of the overall picture of attention that, if understood, has the potential to improve intervention for those with attentional deficits. Genetic association studies are valuable in discovering biological pathways of variability and several studies have found such associations with a sustained attention task. Here, we expand our knowledge to include a reflexive attention task. We ask whether specific candidate genes are associated with interindividual variability on a childhood reflexive attention task in 9-16 year olds. The genetic makers considered are on 11 genes: APOE, BDNF, CHRNA4, COMT, DRD4, HTR4, IGF2, MAOA, SLC5A7, SLC6A3, and SNAP25. We find significant associations with variability with markers on nine and we discuss the results in terms of neurotransmitters associated with each gene and the characteristics of the associated measures from the reflexive attention task.

Functionality predictors in acquired brain damage.

PubMed

Huertas Hoyas, E; Pedrero Pérez, E J; Águila Maturana, A M; García López-Alberca, S; González Alted, C

2015-01-01

Most individuals who have survived an acquired brain injury present consequences affecting the sensorimotor, cognitive, affective or behavioural components. These deficits affect the proper performance of daily living activities. The aim of this study is to identify functional differences between individuals with unilateral acquired brain injury using functional independence, capacity, and performance of daily activities. Descriptive cross-sectional design with a sample of 58 people, with right-sided injury (n=14 TBI; n=15 stroke) or left-sided injury (n = 14 TBI, n = 15 stroke), right handed, and with a mean age of 47 years and time since onset of 4 ± 3.65 years. The functional assessment/functional independence measure (FIM/FAM) and the International Classification of Functioning (ICF) were used for the study. The data showed significant differences (P<.000), and a large size effect (dr=0.78) in the cross-sectional estimates, and point to fewer restrictions for patients with a lesion on their right side. The major differences were in the variables 'speaking' and 'receiving spoken messages' (ICF variables), and 'Expression', 'Writing' and 'intelligible speech' (FIM/FAM variables). In the linear regression analysis, the results showed that only 4 FIM/FAM variables, taken together, predict 44% of the ICF variance, which measures the ability of the individual, and up to 52% of the ICF, which measures the individual's performance. Gait alone predicts a 28% of the variance. It seems that individuals with acquired brain injury in the left hemisphere display important differences regarding functional and communication variables. The motor aspects are an important prognostic factor in functional rehabilitation. Copyright © 2013 Sociedad Española de Neurología. Published by Elsevier España, S.L.U. All rights reserved.

New Observations of the Martian Ionosphere and its Variability - An Overview

NASA Astrophysics Data System (ADS)

Kopf, Andrew J.

2017-04-01

The Martian ionosphere is a highly variable system, owed to the strong influence of the Sun on its properties and behavior, particularly at higher altitudes. Recent measurements from the MAVEN and Mars Express spacecraft have allowed for a more complete understanding of the ionosphere and its variability from two different perspectives. Due to the low-altitude periapsis of its orbit, MAVEN has allowed for the first in-situ ionospheric studies since Viking, yielding detailed direct measurements of the ionosphere's structure, composition, and dynamics, as well as its rate of loss to space. Mars Express has over a decade of continuous ionospheric observation of the red planet, with the unique ability to remotely sound the ionosphere. These features enable Mars Express to make long-period ionospheric measurements on each orbit, at all local times and solar zenith angles. Utilized together, these two spacecraft form a powerful observational suite that has provided new insights into this dynamic environment. This talk will highlight several important recent results in the study of the Martian ionosphere and its variability.

The respiration pattern as an indicator of the anaerobic threshold.

PubMed

Mirmohamadsadeghi, Leila; Vesin, Jean-Marc; Lemay, Mathieu; Deriaz, Olivier

2015-08-01

The anaerobic threshold (AT) is a good index of personal endurance but needs a laboratory setting to be determined. It is important to develop easy AT field measurements techniques in order to rapidly adapt training programs. In the present study, it is postulated that the variability of the respiratory parameters decreases with exercise intensity (especially at the AT level). The aim of this work was to assess, on healthy trained subjects, the putative relationships between the variability of some respiration parameters and the AT. The heart rate and respiratory variables (volume, rate) were measured during an incremental exercise performed on a treadmill by healthy moderately trained subjects. Results show a decrease in the variance of 1/tidal volume with the intensity of exercise. Consequently, the cumulated variance (sum of the variance measured at each level of the exercise) follows an exponential relationship with respect to the intensity to reach eventually a plateau. The amplitude of this plateau is closely related to the AT (r=-0.8). It is concluded that the AT is related to the variability of the respiration.

Validity of temporomandibular disorder examination procedures for assessment of temporomandibular joint status.

PubMed

Schmitter, Marc; Kress, Bodo; Leckel, Michael; Henschel, Volkmar; Ohlmann, Brigitte; Rammelsberg, Peter

2008-06-01

This hypothesis-generating study was performed to determine which items in the Research Diagnostic Criteria for Temporomandibular Disorders (RDC/TMD) and additional diagnostic tests have the best predictive accuracy for joint-related diagnoses. One hundred forty-nine TMD patients and 43 symptom-free subjects were examined in clinical examinations and with magnetic resonance imaging (MRI). The importance of each variable of the clinical examination for correct joint-related diagnosis was assessed by using MRI diagnoses. For this purpose, "random forest" statistical software (based on classification trees) was used. Maximum unassisted jaw opening, maximum assisted jaw opening, history of locked jaw, joint sound with and without compression, joint pain, facial pain, pain on palpation of the lateral pterygoid area, and overjet proved suitable for distinguishing between subtypes of joint-related TMD. Measurement of excursion, protrusion, and midline deviation were less important. The validity of clinical TMD examination procedures can be enhanced by using the 16 variables of greatest importance identified in this study. In addition to other variables, maximum unassisted and assisted opening and a history of locked jaw were important when assessing the status of the TMJ.

Exploring Job Satisfaction of Nursing Faculty: Theoretical Approaches.

PubMed

Wang, Yingchen; Liesveld, Judy

2015-01-01

The Future of Nursing report identified the shortage of nursing faculty as 1 of the barriers to nursing education. In light of this, it is becoming increasingly important to understand the work-life of nursing faculty. The current research focused on job satisfaction of nursing faculty from 4 theoretical perspectives: human capital theory, which emphasizes the expected monetary and nonmonetary returns for any career choices; structural theory, which emphasizes the impact of institutional features on job satisfaction; positive extrinsic environment by self-determination theory, which asserts that a positive extrinsic environment promotes competency and effective outcomes at work; and psychological theory, which emphasizes the proposed relationship between job performance and satisfaction. In addition to the measures for human capital theory, institutional variables (from structural theory and self-determination theory), and productivity measures (from psychological theory), the authors also selected sets of variables for personal characteristics to investigate their effects on job satisfaction. The results indicated that variables related to human capital theory, especially salary, contributed the most to job satisfaction, followed by those related to institutional variables. Personal variables and productivity variables as a whole contributed as well. The only other variable with marginal significance was faculty's perception of institutional support for teaching. Published by Elsevier Inc.

Temporal Variability of Observed and Simulated Hyperspectral Earth Reflectance

NASA Technical Reports Server (NTRS)

Roberts, Yolanda; Pilewskie, Peter; Kindel, Bruce; Feldman, Daniel; Collins, William D.

2012-01-01

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is a climate observation system designed to study Earth's climate variability with unprecedented absolute radiometric accuracy and SI traceability. Observation System Simulation Experiments (OSSEs) were developed using GCM output and MODTRAN to simulate CLARREO reflectance measurements during the 21st century as a design tool for the CLARREO hyperspectral shortwave imager. With OSSE simulations of hyperspectral reflectance, Feldman et al. [2011a,b] found that shortwave reflectance is able to detect changes in climate variables during the 21st century and improve time-to-detection compared to broadband measurements. The OSSE has been a powerful tool in the design of the CLARREO imager and for understanding the effect of climate change on the spectral variability of reflectance, but it is important to evaluate how well the OSSE simulates the Earth's present-day spectral variability. For this evaluation we have used hyperspectral reflectance measurements from the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY), a shortwave spectrometer that was operational between March 2002 and April 2012. To study the spectral variability of SCIAMACHY-measured and OSSE-simulated reflectance, we used principal component analysis (PCA), a spectral decomposition technique that identifies dominant modes of variability in a multivariate data set. Using quantitative comparisons of the OSSE and SCIAMACHY PCs, we have quantified how well the OSSE captures the spectral variability of Earth?s climate system at the beginning of the 21st century relative to SCIAMACHY measurements. These results showed that the OSSE and SCIAMACHY data sets share over 99% of their total variance in 2004. Using the PCs and the temporally distributed reflectance spectra projected onto the PCs (PC scores), we can study the temporal variability of the observed and simulated reflectance spectra. Multivariate time series analysis of the PC scores using techniques such as Singular Spectrum Analysis (SSA) and Multichannel SSA will provide information about the temporal variability of the dominant variables. Quantitative comparison techniques can evaluate how well the OSSE reproduces the temporal variability observed by SCIAMACHY spectral reflectance measurements during the first decade of the 21st century. PCA of OSSE-simulated reflectance can also be used to study how the dominant spectral variables change on centennial scales for forced and unforced climate change scenarios. To have confidence in OSSE predictions of the spectral variability of hyperspectral reflectance, it is first necessary for us to evaluate the degree to which the OSSE simulations are able to reproduce the Earth?s present-day spectral variability.

Sexy but often unreliable: the impact of unreliability on the replicability of experimental findings with implicit measures.

PubMed

Lebel, Etienne P; Paunonen, Sampo V

2011-04-01

Implicit measures have contributed to important insights in almost every area of psychology. However, various issues and challenges remain concerning their use, one of which is their considerable variation in reliability, with many implicit measures having questionable reliability. The goal of the present investigation was to examine an overlooked consequence of this liability with respect to replication, when such implicit measures are used as dependent variables in experimental studies. Using a Monte Carlo simulation, the authors demonstrate that a higher level of unreliability in such dependent variables is associated with substantially lower levels of replicability. The results imply that this overlooked consequence can have far-reaching repercussions for the development of a cumulative science. The authors recommend the routine assessment and reporting of the reliability of implicit measures and also urge the improvement of implicit measures with low reliability.

Facial Features: What Women Perceive as Attractive and What Men Consider Attractive.

PubMed

Muñoz-Reyes, José Antonio; Iglesias-Julios, Marta; Pita, Miguel; Turiegano, Enrique

2015-01-01

Attractiveness plays an important role in social exchange and in the ability to attract potential mates, especially for women. Several facial traits have been described as reliable indicators of attractiveness in women, but very few studies consider the influence of several measurements simultaneously. In addition, most studies consider just one of two assessments to directly measure attractiveness: either self-evaluation or men's ratings. We explored the relationship between these two estimators of attractiveness and a set of facial traits in a sample of 266 young Spanish women. These traits are: facial fluctuating asymmetry, facial averageness, facial sexual dimorphism, and facial maturity. We made use of the advantage of having recently developed methodologies that enabled us to measure these variables in real faces. We also controlled for three other widely used variables: age, body mass index and waist-to-hip ratio. The inclusion of many different variables allowed us to detect any possible interaction between the features described that could affect attractiveness perception. Our results show that facial fluctuating asymmetry is related both to self-perceived and male-rated attractiveness. Other facial traits are related only to one direct attractiveness measurement: facial averageness and facial maturity only affect men's ratings. Unmodified faces are closer to natural stimuli than are manipulated photographs, and therefore our results support the importance of employing unmodified faces to analyse the factors affecting attractiveness. We also discuss the relatively low equivalence between self-perceived and male-rated attractiveness and how various anthropometric traits are relevant to them in different ways. Finally, we highlight the need to perform integrated-variable studies to fully understand female attractiveness.

Facial Features: What Women Perceive as Attractive and What Men Consider Attractive

PubMed Central

Muñoz-Reyes, José Antonio; Iglesias-Julios, Marta; Pita, Miguel; Turiegano, Enrique

2015-01-01

Attractiveness plays an important role in social exchange and in the ability to attract potential mates, especially for women. Several facial traits have been described as reliable indicators of attractiveness in women, but very few studies consider the influence of several measurements simultaneously. In addition, most studies consider just one of two assessments to directly measure attractiveness: either self-evaluation or men's ratings. We explored the relationship between these two estimators of attractiveness and a set of facial traits in a sample of 266 young Spanish women. These traits are: facial fluctuating asymmetry, facial averageness, facial sexual dimorphism, and facial maturity. We made use of the advantage of having recently developed methodologies that enabled us to measure these variables in real faces. We also controlled for three other widely used variables: age, body mass index and waist-to-hip ratio. The inclusion of many different variables allowed us to detect any possible interaction between the features described that could affect attractiveness perception. Our results show that facial fluctuating asymmetry is related both to self-perceived and male-rated attractiveness. Other facial traits are related only to one direct attractiveness measurement: facial averageness and facial maturity only affect men's ratings. Unmodified faces are closer to natural stimuli than are manipulated photographs, and therefore our results support the importance of employing unmodified faces to analyse the factors affecting attractiveness. We also discuss the relatively low equivalence between self-perceived and male-rated attractiveness and how various anthropometric traits are relevant to them in different ways. Finally, we highlight the need to perform integrated-variable studies to fully understand female attractiveness. PMID:26161954

[Bioacoustic of the advertisement call of Ceratophrys cranwelli (Anura: Ceratophryidae)].

PubMed

Valetti, Julián Alonso; Salas, Nancy Edith; Martino, Adolfo Ludovico

2013-03-01

The advertisement call plays an important role in the life history of anuran amphibians, mainly during the breeding season. Call features represent an important character to discriminate species, and sound emissions are very effective to assure or reinforce genetic incompatibility, especially in the case of sibling species. Since frogs are ectotherms, acoustic properties of their calls will vary with temperature. In this study, we described the advertisement call of C. cranwelli, quantifying the temperature effect on its components. The acoustic emissions were recorded during 2007 using a DAT record Sony TCD-100 with stereo microphone ECM-MS907 Sony and tape TDK DAT-RGX 60. As males emit their calls floating in temporary ponds, water temperatures were registered after recording the advertisement calls with a digital thermometer TES 1300+/-0.1 degreeC. Altogether, 54 calls from 18 males were analyzed. The temporal variables of each advertisement call were measured using oscillograms and sonograms and the analyses of dominant frequency were performed using a spectrogram. Multiple correlation analysis was used to identify the temperature-dependent acoustic variables and the temperature effect on these variables was quantified using linear regression models. The advertisement call of C. cranwelli consists of a single pulse group. Call duration, Pulse duration and Pulse interval decreased with the temperature, whereas the Pulse rate increased with temperature. The temperature-dependent variables were standardized at 25 degreeC according to the linear regression model obtained. The acoustic variables that were correlated with the temperature are the variables which emissions depend on laryngeal muscles and the temperature constraints the contractile properties of muscles. Our results indicated that temperature explains an important fraction of the variability in some acoustic variables (79% in the Pulse rate), and demonstrated the importance of considering the effect of temperature in acoustic components. The results suggest that acoustic variables show geographic variation to compare data with previous works.

UK Renal Registry 16th annual report: chapter 12 biochemical variables amongst UK adult dialysis patients in 2012: national and centre-specific analyses.

PubMed

Nicholas, Johann; Shaw, Catriona; Pitcher, David; Dawnay, Anne

2013-01-01

The UK Renal Association clinical practice guidelines include clinical performance measures for biochemical variables in dialysis patients. The UK Renal Registry (UKRR) annually audits dialysis centre performance against these measures as part of its role in promoting continuous quality improvement. Cross sectional performance analyses were undertaken to compare dialysis centre achievement of clinical audit measures for prevalent haemodialysis (HD) and peritoneal dialysis (PD) cohorts in 2012. The biochemical variables studied were phosphate, adjusted calcium, parathyroid hormone, bicarbonate and total cholesterol. In addition, longitudinal analyses were performed (2002-2012) to show changes in achievement of clinical performance measures over time. Fifty-six percent of HD and 61% of PD patients achieved a phosphate within the range recommended by the RA clinical practice guidelines. Seventy-seven percent of HD and 78% of PD patients had adjusted calcium between 2.2-2.5 mmol/L. Fifty-eight percent of HD and 65% of PD patients had parathyroid hormone between 16-72 pmol/L. Fifty-nine percent of HD and 80% of PD patients achieved the audit measure for bicarbonate. There was significant inter-centre variation for all variables studied. The UKRR consistently demonstrates significant inter-centre variation in achievement of biochemical clinical audit measures. Understanding the causes of this variation is an important part of improving the care of dialysis patients in the UK.

Chapter 9 Biochemical variables amongst UK adult dialysis patients in 2010: national and centre-specific analyses.

PubMed

Pruthi, Rishi; Pitcher, David; Dawnay, Anne

2012-01-01

The UK Renal Association clinical practice guidelines include clinical performance measures for biochemical variables in dialysis patients. The UK Renal Registry (UKRR) annually audits dialysis centre performance against these measures as part of its role in promoting continuous quality improvement. Cross sectional performance analyses were undertaken to compare dialysis centre achievement of clinical audit measures for prevalent haemodialysis (HD) and peritoneal dialysis (PD) cohorts in 2010. The biochemical variables studied were phosphate, adjusted calcium, parathyroid hormone, bicarbonate and total cholesterol. In addition longitudinal analyses were performed (2000-2010) to show changes in achievement of clinical performance measures over time. Fifty-six percent of HD and 69% of PD patients achieved a phosphate within the range recommended by the RA clinical practice guidelines. Seventy-five percent of HD and 76% of PD patients had adjusted calcium between 2.2-2.5 mmol/L. Twenty-eight percent of HD and 31% of PD patients had parathyroid hormone between 16- 32 pmol/L. Sixty percent of HD and 80% of PD patients achieved the audit measure for bicarbonate. There was significant inter-centre variation for all variables studied. The UKRR consistently demonstrates significant inter-centre variation in achievement of biochemical clinical audit measures. Understanding the causes of this variation is an important part of improving the care of dialysis patients in the UK. Copyright © 2012 S. Karger AG, Basel.

Post-fire reconstructions of fire intensity from fire severity data: quantifying the role of spatial variability of fire intensity on forest dynamics

NASA Astrophysics Data System (ADS)

Baker, Patrick; Oborne, Lisa

2015-04-01

Large, high-intensity fires have direct and long-lasting effects on forest ecosystems and present a serious threat to human life and property. However, even within the most catastrophic fires there is important variability in local-scale intensity that has important ramifications for forest mortality and regeneration. Quantifying this variability is difficult due to the rarity of catastrophic fire events, the extreme conditions at the time of the fires, and their large spatial extent. Instead fire severity is typically measured or estimated from observed patterns of vegetation mortality; however, differences in species- and size-specific responses to fires often makes fire severity a poor proxy for fire intensity. We developed a statistical method using simple, plot-based measurements of individual tree mortality to simultaneously estimate plot-level fire intensity and species-specific mortality patterns as a function of tree size. We applied our approach to an area of forest burned in the catastrophic Black Saturday fires that occurred near Melbourne, Australia, in February 2009. Despite being the most devastating fire in the past 70 years and our plots being located in the area that experienced some of the most intense fires in the 350,000 ha fire complex, we found that the estimated fire intensity was highly variable at multiple spatial scales. All eight tree species in our study differed in their susceptibility to fire-induced mortality, particularly among the largest size classes. We also found that seedling height and species richness of the post-fire seedling communities were both positively correlated with fire intensity. Spatial variability in disturbance intensity has important, but poorly understood, consequences for the short- and long-term dynamics of forests in the wake of catastrophic wildfires. Our study provides a tool to estimate fire intensity after a fire has passed, allowing new opportunities for linking spatial variability in fire intensity to forest ecosystem dynamics.

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis

DOE PAGES

Sakhanenko, Nikita A.; Kunert-Graf, James; Galas, David J.

2017-10-13

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. Here, we present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discretemore » variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis—that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. Finally, we illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.« less

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis

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

Sakhanenko, Nikita A.; Kunert-Graf, James; Galas, David J.

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. Here, we present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discretemore » variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis—that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. Finally, we illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.« less

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis.

PubMed

Sakhanenko, Nikita A; Kunert-Graf, James; Galas, David J

2017-12-01

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. We present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discrete variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis-that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. We illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.

Ocean angular momentum signals in a climate model and implications for Earth rotation

NASA Astrophysics Data System (ADS)

Ponte, R. M.; Rajamony, J.; Gregory, J. M.

2002-03-01

Estimates of ocean angular momentum (OAM) provide an integrated measure of variability in ocean circulation and mass fields and can be directly related to observed changes in Earth rotation. We use output from a climate model to calculate 240 years of 3-monthly OAM values (two equatorial terms L1 and L2, related to polar motion or wobble, and axial term L3, related to length of day variations) representing the period 1860-2100. Control and forced runs permit the study of the effects of natural and anthropogenically forced climate variability on OAM. All OAM components exhibit a clear annual cycle, with large decadal modulations in amplitude, and also longer period fluctuations, all associated with natural climate variability in the model. Anthropogenically induced signals, inferred from the differences between forced and control runs, include an upward trend in L3, related to inhomogeneous ocean warming and increases in the transport of the Antarctic Circumpolar Current, and a significantly weaker seasonal cycle in L2 in the second half of the record, related primarily to changes in seasonal bottom pressure variability in the Southern Ocean and North Pacific. Variability in mass fields is in general more important to OAM signals than changes in circulation at the seasonal and longer periods analyzed. Relation of OAM signals to changes in surface atmospheric forcing are discussed. The important role of the oceans as an excitation source for the annual, Chandler and Markowitz wobbles, is confirmed. Natural climate variability in OAM and related excitation is likely to measurably affect the Earth rotation, but anthropogenically induced effects are comparatively weak.

The use of auxiliary variables in capture-recapture and removal experiments

USGS Publications Warehouse

Pollock, K.H.; Hines, J.E.; Nichols, J.D.

1984-01-01

The dependence of animal capture probabilities on auxiliary variables is an important practical problem which has not been considered in the development of estimation procedures for capture-recapture and removal experiments. In this paper the linear logistic binary regression model is used to relate the probability of capture to continuous auxiliary variables. The auxiliary variables could be environmental quantities such as air or water temperature, or characteristics of individual animals, such as body length or weight. Maximum likelihood estimators of the population parameters are considered for a variety of models which all assume a closed population. Testing between models is also considered. The models can also be used when one auxiliary variable is a measure of the effort expended in obtaining the sample.

Factors Associated with HIV Testing Among Participants from Substance Use Disorder Treatment Programs in the US: A Machine Learning Approach.

PubMed

Pan, Yue; Liu, Hongmei; Metsch, Lisa R; Feaster, Daniel J

2017-02-01

HIV testing is the foundation for consolidated HIV treatment and prevention. In this study, we aim to discover the most relevant variables for predicting HIV testing uptake among substance users in substance use disorder treatment programs by applying random forest (RF), a robust multivariate statistical learning method. We also provide a descriptive introduction to this method for those who are unfamiliar with it. We used data from the National Institute on Drug Abuse Clinical Trials Network HIV testing and counseling study (CTN-0032). A total of 1281 HIV-negative or status unknown participants from 12 US community-based substance use disorder treatment programs were included and were randomized into three HIV testing and counseling treatment groups. The a priori primary outcome was self-reported receipt of HIV test results. Classification accuracy of RF was compared to logistic regression, a standard statistical approach for binary outcomes. Variable importance measures for the RF model were used to select the most relevant variables. RF based models produced much higher classification accuracy than those based on logistic regression. Treatment group is the most important predictor among all covariates, with a variable importance index of 12.9%. RF variable importance revealed that several types of condomless sex behaviors, condom use self-efficacy and attitudes towards condom use, and level of depression are the most important predictors of receipt of HIV testing results. There is a non-linear negative relationship between count of condomless sex acts and the receipt of HIV testing. In conclusion, RF seems promising in discovering important factors related to HIV testing uptake among large numbers of predictors and should be encouraged in future HIV prevention and treatment research and intervention program evaluations.

Joint measurements of black carbon and particle mass for heavy-duty diesel vehicles using a portable emission measurement system

EPA Science Inventory

The black carbon (BC) emitted from heavy-duty diesel vehicles(HDDVs) is an important source of urban atmospheric pollution and createsstrong climate-forcing impacts. The emission ratio of BC to totalparticle mass (PM) (i.e., BC/PM ratio) is an essential variable used toestimate t...

The Respective Advantages and Disadvantages of Different Ways of Measuring the Instructional Sensitivity of Reading Comprehension Test Items.

ERIC Educational Resources Information Center

Perkins, Kyle

In this paper four classes of procedures for measuring the instructional sensitivity of reading comprehension test items are reviewed. True experimental designs are not recommended because some of the most important reading comprehension variables do not lend themselves to experimental manipulation. "Ex post facto" factorial designs are…

Predicting Well-being Longitudinally for Mothers Rearing Offspring with Intellectual and Developmental Disabilities

PubMed Central

Grein, Katherine A.; Glidden, Laraine Masters

2014-01-01

Background Well-being outcomes for parents of children with intellectual and developmental disabilities (IDD) may vary from positive to negative at different times and for different measures of well-being. Predicting and explaining this variability has been a major focus of family research for reasons that have both theoretical and applied implications. Methods The current study used data from a 23-year longitudinal investigation of adoptive and birth parents of children with IDD to determine which early child, mother, and family characteristics would predict the variance in maternal outcomes 20 years after their original measurement. Using hierarchical regression analyses, we tested the predictive power of variables measured when children were 7 years old on outcomes of maternal well-being when children were 26 years old. Outcome variables included maternal self-report measures of depression and well–being. Results Final models of well-being accounted for 20% to 34% of variance. For most outcomes, Family Accord and/or the personality variable of Neuroticism (emotional stability/instability) were significant predictors, but some variables demonstrated a different pattern. Conclusions These findings confirm that 1) Characteristics of the child, mother, and family during childhood can predict outcomes of maternal well-being 20 years later; and 2) Different predictor-outcome relationships can vary substantially, highlighting the importance of using multiple measures to gain a more comprehensive understanding of maternal well-being. These results have implications for refining prognoses for parents and for tailoring service delivery to individual child, parent, and family characteristics. PMID:25185956

Ozone Lidar Observations for Air Quality Studies

NASA Technical Reports Server (NTRS)

Wang, Lihua; Newchurch, Mike; Kuang, Shi; Burris, John F.; Huang, Guanyu; Pour-Biazar, Arastoo; Koshak, William; Follette-Cook, Melanie B.; Pickering, Kenneth E.; McGee, Thomas J.;

Snowpack spatial variability: Towards understanding its effect on remote sensing measurements and snow slope stability

NASA Astrophysics Data System (ADS)

Marshall, Hans-Peter

The distribution of water in the snow-covered areas of the world is an important climate change indicator, and it is a vital component of the water cycle. At local and regional scales, the snow water equivalent (SWE), the amount of liquid water a given area of the snowpack represents, is very important for water resource management, flood forecasting, and prediction of available hydropower energy. Measurements from only a few automatic weather stations, such as the SNOTEL network, or sparse manual snowpack measurements are typically extrapolated for estimating SWE over an entire basin. Widespread spatial variability in the distribution of SWE and snowpack stratigraphy at local scales causes large errors in these basin estimates. Remote sensing measurements offer a promising alternative, due to their large spatial coverage and high temporal resolution. Although snow cover extent can currently be estimated from remote sensing data, accurately quantifying SWE from remote sensing measurements has remained difficult, due to a high sensitivity to variations in grain size and stratigraphy. In alpine snowpacks, the large degree of spatial variability of snowpack properties and geometry, caused by topographic, vegetative, and microclimatic effects, also makes prediction of snow avalanches very difficult. Ground-based radar and penetrometer measurements can quickly and accurately characterize snowpack properties and SWE in the field. A portable lightweight radar was developed, and allows a real-time estimate of SWE to within 10%, as well as measurements of depths of all major density transitions within the snowpack. New analysis techniques developed in this thesis allow accurate estimates of mechanical properties and an index of grain size to be retrieved from the SnowMicroPenetrometer. These two tools together allow rapid characterization of the snowpack's geometry, mechanical properties, and SWE, and are used to guide a finite element model to study the stress distribution on a slope. The ability to accurately characterize snowpack properties at much higher resolutions and spatial extent than previously possible will hopefully help lead to a more complete understanding of spatial variability, its effect on remote sensing measurements and snow slope stability, and result in improvements in avalanche prediction and accuracy of SWE estimates from space.

Cognitive functioning and everyday problem solving in older adults.

PubMed

Burton, Catherine L; Strauss, Esther; Hultsch, David F; Hunter, Michael A

2006-09-01

The relationship between cognitive functioning and a performance-based measure of everyday problem-solving, the Everyday Problems Test (EPT), thought to index instrumental activities of daily living (IADL), was examined in 291 community-dwelling non-demented older adults. Performance on the EPT was found to vary according to age, cognitive status, and education. Hierarchical regression analyses revealed that, after adjusting for demographic and health variables, measures of cognitive functioning accounted for 23.6% of the variance in EPT performance. In particular, measures of global cognitive status, cognitive decline, speed of processing, executive functioning, episodic memory, and verbal ability were significant predictors of EPT performance. These findings suggest that cognitive functioning along with demographic variables are important determinants of everyday problem-solving.

Unidimensional versus multidimensional approaches to the assessment of acculturation for Asian American populations.

PubMed

Abe-Kim, J; Okazaki, S; Goto, S G

2001-08-01

This study used generational status and the Suinn-Lew Asian Self-Identity Acculturation scale to examine unidimensional versus multidimensional approaches to the conceptualization and measurement of acculturation and their relationships to relevant cultural indicator variables, including measures of Individualism-Collectivism, Independent-Interdependent Self-Construal, Loss of Face, and Impression Management. Multivariate analyses of covariance and partial correlations were used to examine the relationship between the acculturation models and each set of cultural indicator variables while controlling for socioeconomic status. Given that acculturation differences are often cited as evidence for a culture effect between groups, the present findings of an uneven nature of these relationships as a function of the particular acculturation measurement strategy have important implications for research on Asian Americans.

Interannual Variability in the Position and Strength of the East Asian Jet Stream and Its Relation to Large - scale Circulation

NASA Astrophysics Data System (ADS)

Chan, Duo; Zhang, Yang; Wu, Qigang

2013-04-01

East Asian Jet Stream (EASJ) is charactered by obvious interannual variability in strength and position (latitude), with wide impacts on East Asian climate in all seasons. In this study, two indices are established to measure the interannual variability in intensity and position of EAJS. Possible causing factors, including both local signals and non-local large-scale circulation, are examined using NCAP-NCAR reanalysis data to investigate their relations with jet variation. Our analysis shows that the relationship between the interannual variations of EASJ and these factors depends on seasons. In the summer, both the intensity and position of EASJ are closely related to the meridional gradient of local surface temperature, but display no apparent relationship with the larg-scale circulation. In cold seasons (autumn, winter and spring), both the local factor and the large-scale circulation, i.e. the Pacific/North American teleconnection pattern (PNA), play important roles in the interannual variability of the jet intensity. The variability in the jet position, however, is more correlated to the Arctic Oscillation (AO), especially in winter. Diagnostic analysis indicates that transient eddy activity plays an important role in connecting the interannual variability of EASJ position with AO.

Population dynamics of pond zooplankton II Daphnia ambigua Scourfield

USGS Publications Warehouse

Angino, E.E.; Armitage, K.B.; Saxena, B.

1973-01-01

Calcium was the most important of 27 environmental components affecting density for a 50 week period. Simultaneous stepwise regression accounted for more variability in total number/1 and in the number of ovigerous females/1 than did any of the lag analyses; 1-week lag accounted for the greatest amount of variability in clutch size. Total number and clutch size were little affected by measures of food. ?? 1973 Dr. W. Junk b.v. Publishers.

A descriptivist approach to trait conceptualization and inference.

PubMed

Jonas, Katherine G; Markon, Kristian E

2016-01-01

In their recent article, How Functionalist and Process Approaches to Behavior Can Explain Trait Covariation, Wood, Gardner, and Harms (2015) underscore the need for more process-based understandings of individual differences. At the same time, the article illustrates a common error in the use and interpretation of latent variable models: namely, the misuse of models to arbitrate issues of causation and the nature of latent variables. Here, we explain how latent variables can be understood simply as parsimonious summaries of data, and how statistical inference can be based on choosing those summaries that minimize information required to represent the data using the model. Although Wood, Gardner, and Harms acknowledge this perspective, they underestimate its significance, including its importance to modeling and the conceptualization of psychological measurement. We believe this perspective has important implications for understanding individual differences in a number of domains, including current debates surrounding the role of formative versus reflective latent variables. (c) 2015 APA, all rights reserved).

High variability of the subjective visual vertical test of vertical perception, in some people with neck pain - Should this be a standard measure of cervical proprioception?

PubMed

Treleaven, Julia; Takasaki, Hiroshi

2015-02-01

Subjective visual vertical (SVV) assesses visual dependence for spacial orientation, via vertical perception testing. Using the computerized rod-and-frame test (CRFT), SVV is thought to be an important measure of cervical proprioception and might be greater in those with whiplash associated disorder (WAD), but to date research findings are inconsistent. The aim of this study was to investigate the most sensitive SVV error measurement to detect group differences between no neck pain control, idiopathic neck pain (INP) and WAD subjects. Cross sectional study. Neck Disability Index (NDI), Dizziness Handicap Inventory short form (DHIsf) and the average constant error (CE), absolute error (AE), root mean square error (RMSE), and variable error (VE) of the SVV were obtained from 142 subjects (48 asymptomatic, 36 INP, 42 WAD). The INP group had significantly (p < 0.03) greater VE and RMSE when compared to both the control and WAD groups. There were no differences seen between the WAD and controls. The results demonstrated that people with INP (not WAD), had an altered strategy for maintaining the perception of vertical by increasing variability of performance. This may be due to the complexity of the task. Further, the SVV performance was not related to reported pain or dizziness handicap. These findings are inconsistent with other measures of cervical proprioception in neck pain and more research is required before the SVV can be considered an important measure and utilized clinically. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

Normative Measurements of Grip and Pinch Strengths of 21st Century Korean Population

PubMed Central

Shim, Jin Hee; Kim, Jin Soo; Lee, Dong Chul; Ki, Sae Hwi; Yang, Jae Won; Jeon, Man Kyung; Lee, Sang Myung

2013-01-01

Background Measuring grip and pinch strength is an important part of hand injury evaluation. Currently, there are no standardized values of normal grip and pinch strength among the Korean population, and lack of such data prevents objective evaluation of post-surgical recovery in strength. This study was designed to establish the normal values of grip and pinch strength among the healthy Korean population and to identify any dependent variables affecting grip and pinch strength. Methods A cross-sectional study was carried out. The inclusion criterion was being a healthy Korean person without a previous history of hand trauma. The grip strength was measured using a Jamar dynamometer. Pulp and key pinch strength were measured with a hydraulic pinch gauge. Intra-individual and inter-individual variations in these variables were analyzed in a standardized statistical manner. Results There were a total of 336 healthy participants between 13 and 77 years of age. As would be expected in any given population, the mean grip and pinch strength was greater in the right hand than the left. Male participants (137) showed mean strengths greater than female participants (199) when adjusted for age. Among the male participants, anthropometric variables correlated positively with grip strength, but no such correlations were identifiable in female participants in a statistically significant way. Conclusions Objective measurements of hand strength are an important component of hand injury evaluation, and population-specific normative data are essential for clinical and research purposes. This study reports updated normative hand strengths of the South Korean population in the 21st century. PMID:23362480

Atmospheric Ice-Nucleating Particles in the Dusty Tropical Atlantic

NASA Astrophysics Data System (ADS)

Price, H. C.; Baustian, K. J.; McQuaid, J. B.; Blyth, A.; Bower, K. N.; Choularton, T.; Cotton, R. J.; Cui, Z.; Field, P. R.; Gallagher, M.; Hawker, R.; Merrington, A.; Miltenberger, A.; Neely, R. R., III; Parker, S. T.; Rosenberg, P. D.; Taylor, J. W.; Trembath, J.; Vergara-Temprado, J.; Whale, T. F.; Wilson, T. W.; Young, G.; Murray, B. J.

2018-02-01

Desert dust is one of the most important atmospheric ice-nucleating aerosol species around the globe. However, there have been very few measurements of ice-nucleating particle (INP) concentrations in dusty air close to desert sources. In this study we report the concentration of INPs in dust laden air over the tropical Atlantic within a few days' transport of one of the world's most important atmospheric sources of desert dust, the Sahara. These measurements were performed as part of the Ice in Clouds Experiment-Dust campaign based in Cape Verde, during August 2015. INP concentrations active in the immersion mode, determined using a droplet-on-filter technique, ranged from around 102 m-3 at -12°C to around 105 m-3 at -23°C. There is about 2 orders of magnitude variability in INP concentration for a particular temperature, which is determined largely by the variability in atmospheric dust loading. These measurements were made at altitudes from 30 to 3,500 m in air containing a range of dust loadings. The ice active site density (ns) for desert dust dominated aerosol derived from our measurements agrees with several laboratory-based parameterizations for ice nucleation by desert dust within 1 to 2 orders of magnitude. The small variability in ns values determined from our measurements (within about 1 order of magnitude) is striking given that the back trajectory analysis suggests that the sources of dust were geographically diverse. This is consistent with previous work, which indicates that desert dust's ice-nucleating activity is only weakly dependent on source.

Patient-reported non-adherence and immunosuppressant trough levels are associated with rejection after renal transplantation.

PubMed

Scheel, Jennifer; Reber, Sandra; Stoessel, Lisa; Waldmann, Elisabeth; Jank, Sabine; Eckardt, Kai-Uwe; Grundmann, Franziska; Vitinius, Frank; de Zwaan, Martina; Bertram, Anna; Erim, Yesim

2017-03-29

Different measures of non-adherence to immunosuppressant (IS) medication have been found to be associated with rejection episodes after successful transplantation. The aim of the current study was to investigate whether graft rejection after renal transplantation is associated with patient-reported IS medication non-adherence and IS trough level variables (IS trough level variability and percentage of sub-therapeutic IS trough levels). Patient-reported non-adherence, IS trough level variability, percentage of sub-therapeutic IS trough levels, and acute biopsy-proven late allograft rejections were assessed in 267 adult renal transplant recipients who were ≥12 months post-transplantation. The rate of rejection was 13.5%. IS trough level variability, percentage of sub-therapeutic IS trough levels as well as patient-reported non-adherence were all significantly and positively associated with rejection, but not with each other. Logistic regression analyses revealed that only the percentage of sub-therapeutic IS trough levels and age at transplantation remained significantly associated with rejection. Particularly, the percentage of sub-therapeutic IS trough levels is associated with acute rejections after kidney transplantation whereas IS trough level variability and patient-reported non-adherence seem to be of subordinate importance. Patient-reported non-adherence and IS trough level variables were not correlated; thus, non-adherence should always be measured in a multi-methodological approach. Further research concerning the best combination of non-adherence measures is needed.

ORES - Objective Referenced Evaluation in Science.

ERIC Educational Resources Information Center

Shaw, Terry

Science process skills considered important in making decisions and solving problems include: observing, classifying, measuring, using numbers, using space/time relationships, communicating, predicting, inferring, manipulating variables, making operational definitions, forming hypotheses, interpreting data, and experimenting. This 60-item test,…

Sustained attention and heart rate variability in children and adolescents with ADHD.

PubMed

Griffiths, Kristi R; Quintana, Daniel S; Hermens, Daniel F; Spooner, Chris; Tsang, Tracey W; Clarke, Simon; Kohn, Michael R

2017-03-01

The autonomic nervous system (ANS) plays an important role in attention and self-regulation by modulating physiological arousal to meet environmental demands. Core symptoms of ADHD such as inattention and behavioral disinhibition may be related to dysregulation of the ANS, however previous findings have been equivocal. We examined autonomic activity and reactivity by assessing heart rate variability (HRV) in a large sample of un-medicated children and adolescents (6-19 years) with ADHD (n=229) compared to typically-developing controls (n=244) during rest and sustained attention. Four heart rate variability measures were extracted: Root mean square of successive differences between inter-beat-intervals (rMSSD), absolute high frequency (HFA) power, absolute low frequency (LFA) power and ratio of low frequency power to high frequency power (LF/HF). There were no group differences in HFA or rMSSD, even when assessing across child and adolescent groups separately, by gender or ADHD subtype. LF/HF however was higher in ADHD during both rest and sustained attention conditions, particularly in male children. Sustained attention was impaired in ADHD relative to controls, and a higher LF/HF ratio during sustained attention was associated with poorer performance in both groups. Lower rMSSD and HFA were associated with higher anxiety, oppositional behaviors and social problems, supporting prevailing theories that these measures index emotion regulation and adaptive social behavior. Different measures of heart rate variability provide important insights into the sustained attention and emotional and behavioral regulation impairments observed in ADHD and may aid in delineating ADHD pathophysiology. Copyright © 2017 Elsevier B.V. All rights reserved.

Favre-Averaged Turbulence Statistics in Variable Density Mixing of Buoyant Jets

NASA Astrophysics Data System (ADS)

Charonko, John; Prestridge, Kathy

2014-11-01

Variable density mixing of a heavy fluid jet with lower density ambient fluid in a subsonic wind tunnel was experimentally studied using Particle Image Velocimetry and Planar Laser Induced Fluorescence to simultaneously measure velocity and density. Flows involving the mixing of fluids with large density ratios are important in a range of physical problems including atmospheric and oceanic flows, industrial processes, and inertial confinement fusion. Here we focus on buoyant jets with coflow. Results from two different Atwood numbers, 0.1 (Boussinesq limit) and 0.6 (non-Boussinesq case), reveal that buoyancy is important for most of the turbulent quantities measured. Statistical characteristics of the mixing important for modeling these flows such as the PDFs of density and density gradients, turbulent kinetic energy, Favre averaged Reynolds stress, turbulent mass flux velocity, density-specific volume correlation, and density power spectra were also examined and compared with previous direct numerical simulations. Additionally, a method for directly estimating Reynolds-averaged velocity statistics on a per-pixel basis is extended to Favre-averages, yielding improved accuracy and spatial resolution as compared to traditional post-processing of velocity and density fields.

Multivariate Analysis of Solar Spectral Irradiance Measurements

NASA Technical Reports Server (NTRS)

Pilewskie, P.; Rabbette, M.

2001-01-01

Principal component analysis is used to characterize approximately 7000 downwelling solar irradiance spectra retrieved at the Southern Great Plains site during an Atmospheric Radiation Measurement (ARM) shortwave intensive operating period. This analysis technique has proven to be very effective in reducing a large set of variables into a much smaller set of independent variables while retaining the information content. It is used to determine the minimum number of parameters necessary to characterize atmospheric spectral irradiance or the dimensionality of atmospheric variability. It was found that well over 99% of the spectral information was contained in the first six mutually orthogonal linear combinations of the observed variables (flux at various wavelengths). Rotation of the principal components was effective in separating various components by their independent physical influences. The majority of the variability in the downwelling solar irradiance (380-1000 nm) was explained by the following fundamental atmospheric parameters (in order of their importance): cloud scattering, water vapor absorption, molecular scattering, and ozone absorption. In contrast to what has been proposed as a resolution to a clear-sky absorption anomaly, no unexpected gaseous absorption signature was found in any of the significant components.

Optoacoustic Monitoring of Physiologic Variables

PubMed Central

Esenaliev, Rinat O.

2017-01-01

Optoacoustic (photoacoustic) technique is a novel diagnostic platform that can be used for noninvasive measurements of physiologic variables, functional imaging, and hemodynamic monitoring. This technique is based on generation and time-resolved detection of optoacoustic (thermoelastic) waves generated in tissue by short optical pulses. This provides probing of tissues and individual blood vessels with high optical contrast and ultrasound spatial resolution. Because the optoacoustic waves carry information on tissue optical and thermophysical properties, detection, and analysis of the optoacoustic waves allow for measurements of physiologic variables with high accuracy and specificity. We proposed to use the optoacoustic technique for monitoring of a number of important physiologic variables including temperature, thermal coagulation, freezing, concentration of molecular dyes, nanoparticles, oxygenation, and hemoglobin concentration. In this review we present origin of contrast and high spatial resolution in these measurements performed with optoacoustic systems developed and built by our group. We summarize data obtained in vitro, in experimental animals, and in humans on monitoring of these physiologic variables. Our data indicate that the optoacoustic technology may be used for monitoring of cerebral blood oxygenation in patients with traumatic brain injury and in neonatal patients, central venous oxygenation monitoring, total hemoglobin concentration monitoring, hematoma detection and characterization, monitoring of temperature, and coagulation and freezing boundaries during thermotherapy. PMID:29311964

Optoacoustic Monitoring of Physiologic Variables.

PubMed

Esenaliev, Rinat O

2017-01-01

Optoacoustic (photoacoustic) technique is a novel diagnostic platform that can be used for noninvasive measurements of physiologic variables, functional imaging, and hemodynamic monitoring. This technique is based on generation and time-resolved detection of optoacoustic (thermoelastic) waves generated in tissue by short optical pulses. This provides probing of tissues and individual blood vessels with high optical contrast and ultrasound spatial resolution. Because the optoacoustic waves carry information on tissue optical and thermophysical properties, detection, and analysis of the optoacoustic waves allow for measurements of physiologic variables with high accuracy and specificity. We proposed to use the optoacoustic technique for monitoring of a number of important physiologic variables including temperature, thermal coagulation, freezing, concentration of molecular dyes, nanoparticles, oxygenation, and hemoglobin concentration. In this review we present origin of contrast and high spatial resolution in these measurements performed with optoacoustic systems developed and built by our group. We summarize data obtained in vitro , in experimental animals, and in humans on monitoring of these physiologic variables. Our data indicate that the optoacoustic technology may be used for monitoring of cerebral blood oxygenation in patients with traumatic brain injury and in neonatal patients, central venous oxygenation monitoring, total hemoglobin concentration monitoring, hematoma detection and characterization, monitoring of temperature, and coagulation and freezing boundaries during thermotherapy.

Nowcasting of Low-Visibility Procedure States with Ordered Logistic Regression at Vienna International Airport

NASA Astrophysics Data System (ADS)

Kneringer, Philipp; Dietz, Sebastian; Mayr, Georg J.; Zeileis, Achim

2017-04-01

Low-visibility conditions have a large impact on aviation safety and economic efficiency of airports and airlines. To support decision makers, we develop a statistical probabilistic nowcasting tool for the occurrence of capacity-reducing operations related to low visibility. The probabilities of four different low visibility classes are predicted with an ordered logistic regression model based on time series of meteorological point measurements. Potential predictor variables for the statistical models are visibility, humidity, temperature and wind measurements at several measurement sites. A stepwise variable selection method indicates that visibility and humidity measurements are the most important model inputs. The forecasts are tested with a 30 minute forecast interval up to two hours, which is a sufficient time span for tactical planning at Vienna Airport. The ordered logistic regression models outperform persistence and are competitive with human forecasters.

A Probabilistic Method for Estimation of Bowel Wall Thickness in MR Colonography

PubMed Central

Menys, Alex; Jaffer, Asif; Bhatnagar, Gauraang; Punwani, Shonit; Atkinson, David; Halligan, Steve; Hawkes, David J.; Taylor, Stuart A.

2017-01-01

MRI has recently been applied as a tool to quantitatively evaluate the response to therapy in patients with Crohn’s disease, and is the preferred choice for repeated imaging. Bowel wall thickness on MRI is an important biomarker of underlying inflammatory activity, being abnormally increased in the acute phase and reducing in response to successful therapy; however, a poor level of interobserver agreement of measured thickness is reported and therefore a system for accurate, robust and reproducible measurements is desirable. We propose a novel method for estimating bowel wall-thickness to improve the poor interobserver agreement of the manual procedure. We show that the variability of wall thickness measurement between the algorithm and observer measurements (0.25mm ± 0.81mm) has differences which are similar to observer variability (0.16mm ± 0.64mm). PMID:28072831

Evaluating the performance of ENVI-met model in diurnal cycles for different meteorological conditions

NASA Astrophysics Data System (ADS)

Acero, Juan A.; Arrizabalaga, Jon

2018-01-01

Urban areas are known to modify meteorological variables producing important differences in small spatial scales (i.e. microscale). These affect human thermal comfort conditions and the dispersion of pollutants, especially those emitted inside the urban area, which finally influence quality of life and the use of public open spaces. In this study, the diurnal evolution of meteorological variables measured in four urban spaces is compared with the results provided by ENVI-met (v 4.0). Measurements were carried out during 3 days with different meteorological conditions in Bilbao in the north of the Iberian Peninsula. The evaluation of the model accuracy (i.e. the degree to which modelled values approach measured values) was carried out with several quantitative difference metrics. The results for air temperature and humidity show a good agreement of measured and modelled values independently of the regional meteorological conditions. However, in the case of mean radiant temperature and wind speed, relevant differences are encountered highlighting the limitation of the model to estimate these meteorological variables precisely during diurnal cycles, in the considered evaluation conditions (sites and weather).

Wind erosion in semiarid landscapes: Predictive models and remote sensing methods for the influence of vegetation

NASA Technical Reports Server (NTRS)

Musick, H. Brad

1993-01-01

The objectives of this research are: to develop and test predictive relations for the quantitative influence of vegetation canopy structure on wind erosion of semiarid rangeland soils, and to develop remote sensing methods for measuring the canopy structural parameters that determine sheltering against wind erosion. The influence of canopy structure on wind erosion will be investigated by means of wind-tunnel and field experiments using structural variables identified by the wind-tunnel and field experiments using model roughness elements to simulate plant canopies. The canopy structural variables identified by the wind-tunnel and field experiments as important in determining vegetative sheltering against wind erosion will then be measured at a number of naturally vegetated field sites and compared with estimates of these variables derived from analysis of remotely sensed data.

Determining the spatial variability of crop yields of two different climatic regions in Southwest Germany

NASA Astrophysics Data System (ADS)

Eshonkulov, Ravshan; Poyda, Arne; Ingwersen, Joachim; Streck, Thilo

2017-04-01

Assessing the spatial variability of soil physical properties is crucial for agricultural land management. We determined the spatial variability within two agricultural fields in the regions of Kraichgau and Swabian Jura in Southwest Germany. We determined soil physical properties and recorded the temporal development of soil mineral nitrogen (N) and water content as well as that of plant variables (phenology, biomass, leaf area index (LAI), N content, green vegetation fraction (GVF). The work was conducted during the vegetation periods of 2015 and 2016 in winter wheat, and winter rapeseed in Kraichgau and winter barley and silage maize on Swabian Jura. Measurements were taken in three-weekly intervals. On each field, we identified three plots with reduced plant development using high-resolution (RapidEye) satellite images ("cold spots"). Measurements taken on these cold spots were compared to those from five established (long-term) reference plots representing the average field variability. The software EXPERT-N was used to simulate the soil crop system at both cold spots and reference plots. Sensitivity analyses were conducted to identify the most important parameters for the determination of spatial variability in crop growth dynamics.

Verification of models for ballistic movement time and endpoint variability.

PubMed

Lin, Ray F; Drury, Colin G

2013-01-01

A hand control movement is composed of several ballistic movements. The time required in performing a ballistic movement and its endpoint variability are two important properties in developing movement models. The purpose of this study was to test potential models for predicting these two properties. Twelve participants conducted ballistic movements of specific amplitudes using a drawing tablet. The measured data of movement time and endpoint variability were then used to verify the models. This study was successful with Hoffmann and Gan's movement time model (Hoffmann, 1981; Gan and Hoffmann 1988) predicting more than 90.7% data variance for 84 individual measurements. A new theoretically developed ballistic movement variability model, proved to be better than Howarth, Beggs, and Bowden's (1971) model, predicting on average 84.8% of stopping-variable error and 88.3% of aiming-variable errors. These two validated models will help build solid theoretical movement models and evaluate input devices. This article provides better models for predicting end accuracy and movement time of ballistic movements that are desirable in rapid aiming tasks, such as keying in numbers on a smart phone. The models allow better design of aiming tasks, for example button sizes on mobile phones for different user populations.

Effects of measurement errors on psychometric measurements in ergonomics studies: Implications for correlations, ANOVA, linear regression, factor analysis, and linear discriminant analysis.

PubMed

Liu, Yan; Salvendy, Gavriel

2009-05-01

This paper aims to demonstrate the effects of measurement errors on psychometric measurements in ergonomics studies. A variety of sources can cause random measurement errors in ergonomics studies and these errors can distort virtually every statistic computed and lead investigators to erroneous conclusions. The effects of measurement errors on five most widely used statistical analysis tools have been discussed and illustrated: correlation; ANOVA; linear regression; factor analysis; linear discriminant analysis. It has been shown that measurement errors can greatly attenuate correlations between variables, reduce statistical power of ANOVA, distort (overestimate, underestimate or even change the sign of) regression coefficients, underrate the explanation contributions of the most important factors in factor analysis and depreciate the significance of discriminant function and discrimination abilities of individual variables in discrimination analysis. The discussions will be restricted to subjective scales and survey methods and their reliability estimates. Other methods applied in ergonomics research, such as physical and electrophysiological measurements and chemical and biomedical analysis methods, also have issues of measurement errors, but they are beyond the scope of this paper. As there has been increasing interest in the development and testing of theories in ergonomics research, it has become very important for ergonomics researchers to understand the effects of measurement errors on their experiment results, which the authors believe is very critical to research progress in theory development and cumulative knowledge in the ergonomics field.

The EOS Aura Mission

NASA Technical Reports Server (NTRS)

Schoeberl, Mark R.; Douglass, A. R.; Hilsenrath, E.; Luce, M.; Barnett, J.; Beer, R.; Waters, J.; Gille, J.; Levelt, P. F.; DeCola, P.;

Assessing soil compaction on Forest Inventory & Analysis phase 3 field plots using a pocket penetrometer

Treesearch

Michael C. Amacher; Katherine P. O' Neill

2004-01-01

Soil compaction is an important indicator of soil quality, yet few practical methods are available to quantitatively measure this variable. Although an assessment of the areal extent of soil compaction is included as part of the soil indicator portion of the Forest Inventory & Analysis (FIA) program, no quantitative measurement of the degree of soil compaction...

Modeling and measurement of the detector presampling MTF of a variable resolution x-ray CT scanner.

PubMed

Melnyk, Roman; DiBianca, Frank A

2007-03-01

The detector presampling modulation transfer function (MTF) of a 576-channel variable resolution x-ray (VRX) computed tomography (CT) scanner was evaluated in this study. The scanner employs a VRX detector, which provides increased spatial resolution by matching the scanner's field of view (FOV) to the size of an object being imaged. Because spatial resolution is the parameter the scanner promises to improve, the evaluation of this resolution is important. The scanner's pre-reconstruction spatial resolution, represented by the detector presampling MTF, was evaluated using both modeling (Monte Carlo simulation) and measurement (the moving slit method). The theoretical results show the increase in the cutoff frequency of the detector presampling MTF from 1.39 to 43.38 cycles/mm as the FOV of the VRX CT scanner decreases from 32 to 1 cm. The experimental results are in reasonable agreement with the theoretical data. Some discrepancies between the measured and the modeled detector presampling MTFs can be explained by the limitations of the model. At small FOVs (1-8 cm), the MTF measurements were limited by the size of the focal spot. The obtained results are important for further development of the VRX CT scanner.

Modeling and measurement of the detector presampling MTF of a variable resolution x-ray CT scanner

PubMed Central

Melnyk, Roman; DiBianca, Frank A.

2007-01-01

The detector presampling MTF of a 576-channel variable resolution x-ray (VRX) CT scanner was evaluated in this study. The scanner employs a VRX detector, which provides increased spatial resolution by matching the scanner’s field of view (FOV) to the size of an object being imaged. Because spatial resolution is the parameter the scanner promises to improve, the evaluation of this resolution is important. The scanner’s pre-reconstruction spatial resolution, represented by the detector presampling MTF, was evaluated using both modeling (Monte Carlo simulation) and measurement (the moving slit method). The theoretical results show the increase in the cutoff frequency of the detector presampling MTF from 1.39 cy/mm to 43.38 cy/mm as the FOV of the VRX CT scanner decreases from 32 cm to 1 cm. The experimental results are in reasonable agreement with the theoretical data. Some discrepancies between the measured and the modeled detector presampling MTFs can be explained by the limitations of the model. At small FOVs (1–8 cm), the MTF measurements were limited by the size of the focal spot. The obtained results are important for further development of the VRX CT scanner. PMID:17369872

INFANT HEALTH PRODUCTION FUNCTIONS: WHAT A DIFFERENCE THE DATA MAKE

PubMed Central

Reichman, Nancy E.; Corman, Hope; Noonan, Kelly; Dave, Dhaval

2008-01-01

SUMMARY We examine the extent to which infant health production functions are sensitive to model specification and measurement error. We focus on the importance of typically unobserved but theoretically important variables (typically unobserved variables, TUVs), other non-standard covariates (NSCs), input reporting, and characterization of infant health. The TUVs represent wantedness, taste for risky behavior, and maternal health endowment. The NSCs include father characteristics. We estimate the effects of prenatal drug use, prenatal cigarette smoking, and First trimester prenatal care on birth weight, low birth weight, and a measure of abnormal infant health conditions. We compare estimates using self-reported inputs versus input measures that combine information from medical records and self-reports. We find that TUVs and NSCs are significantly associated with both inputs and outcomes, but that excluding them from infant health production functions does not appreciably affect the input estimates. However, using self-reported inputs leads to overestimated effects of inputs, particularly prenatal care, on outcomes, and using a direct measure of infant health does not always yield input estimates similar to those when using birth weight outcomes. The findings have implications for research, data collection, and public health policy. PMID:18792077

Suicidal Ideation and Schizophrenia: Contribution of Appraisal, Stigmatization, and Cognition.

PubMed

Stip, Emmanuel; Caron, Jean; Tousignant, Michel; Lecomte, Yves

2017-10-01

To predict suicidal ideation in people with schizophrenia, certain studies have measured its relationship with the variables of defeat and entrapment. The relationships are positive, but their interactions remain undefined. To further their understanding, this research sought to measure the relationship between suicidal ideation with the variables of loss, entrapment, and humiliation. The convenience sample included 30 patients with schizophrenia spectrum disorders. The study was prospective (3 measurement times) during a 6-month period. Results were analyzed by stepwise multiple regression. The contribution of the 3 variables to the variance of suicidal ideation was not significant at any of the 3 times (T1: 16.2%, P = 0.056; T2: 19.9%, P = 0.117; T3: 11.2%, P = 0.109). Further analyses measured the relationship between the variables of stigmatization, perceived cognitive dysfunction, symptoms, depression, self-esteem, reason to live, spirituality, social provision, and suicidal ideation. Stepwise multiple regression demonstrated that the contribution of the variables of stigmatization and perceived cognitive dysfunction to the variance of suicidal ideation was significant at all 3 times (T1: 41.7.5%, P = 0.000; T2: 35.2%, P = 0.001; T3: 21.5%, P = 0.012). Yet, over time, the individual contribution of the variables changed: T1, stigmatization (β = 0.518; P = 0.002); T2, stigmatization (β = 0.394; P = 0.025) and perceived cognitive dysfunction (β = 0.349; P = 0.046). Then, at T3, only perceived cognitive dysfunction contributed significantly to suicidal ideation (β = 0.438; P = 0.016). The results highlight the importance of the contribution of the variables of perceived cognitive dysfunction and stigmatization in the onset of suicidal ideation in people with schizophrenia spectrum disorders.

Suicidal Ideation and Schizophrenia: Contribution of Appraisal, Stigmatization, and Cognition

PubMed Central

Stip, Emmanuel; Caron, Jean; Tousignant, Michel

2017-01-01

Objective: To predict suicidal ideation in people with schizophrenia, certain studies have measured its relationship with the variables of defeat and entrapment. The relationships are positive, but their interactions remain undefined. To further their understanding, this research sought to measure the relationship between suicidal ideation with the variables of loss, entrapment, and humiliation. Method: The convenience sample included 30 patients with schizophrenia spectrum disorders. The study was prospective (3 measurement times) during a 6-month period. Results were analyzed by stepwise multiple regression. Results: The contribution of the 3 variables to the variance of suicidal ideation was not significant at any of the 3 times (T1: 16.2%, P = 0.056; T2: 19.9%, P = 0.117; T3: 11.2%, P = 0.109). Further analyses measured the relationship between the variables of stigmatization, perceived cognitive dysfunction, symptoms, depression, self-esteem, reason to live, spirituality, social provision, and suicidal ideation. Stepwise multiple regression demonstrated that the contribution of the variables of stigmatization and perceived cognitive dysfunction to the variance of suicidal ideation was significant at all 3 times (T1: 41.7.5%, P = 0.000; T2: 35.2%, P = 0.001; T3: 21.5%, P = 0.012). Yet, over time, the individual contribution of the variables changed: T1, stigmatization (β = 0.518; P = 0.002); T2, stigmatization (β = 0.394; P = 0.025) and perceived cognitive dysfunction (β = 0.349; P = 0.046). Then, at T3, only perceived cognitive dysfunction contributed significantly to suicidal ideation (β = 0.438; P = 0.016). Conclusion: The results highlight the importance of the contribution of the variables of perceived cognitive dysfunction and stigmatization in the onset of suicidal ideation in people with schizophrenia spectrum disorders. PMID:28673099

Part mutual information for quantifying direct associations in networks.

PubMed

Zhao, Juan; Zhou, Yiwei; Zhang, Xiujun; Chen, Luonan

2016-05-03

Quantitatively identifying direct dependencies between variables is an important task in data analysis, in particular for reconstructing various types of networks and causal relations in science and engineering. One of the most widely used criteria is partial correlation, but it can only measure linearly direct association and miss nonlinear associations. However, based on conditional independence, conditional mutual information (CMI) is able to quantify nonlinearly direct relationships among variables from the observed data, superior to linear measures, but suffers from a serious problem of underestimation, in particular for those variables with tight associations in a network, which severely limits its applications. In this work, we propose a new concept, "partial independence," with a new measure, "part mutual information" (PMI), which not only can overcome the problem of CMI but also retains the quantification properties of both mutual information (MI) and CMI. Specifically, we first defined PMI to measure nonlinearly direct dependencies between variables and then derived its relations with MI and CMI. Finally, we used a number of simulated data as benchmark examples to numerically demonstrate PMI features and further real gene expression data from Escherichia coli and yeast to reconstruct gene regulatory networks, which all validated the advantages of PMI for accurately quantifying nonlinearly direct associations in networks.

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.

Descriptive statistics: the specification of statistical measures and their presentation in tables and graphs. Part 7 of a series on evaluation of scientific publications.

PubMed

Spriestersbach, Albert; Röhrig, Bernd; du Prel, Jean-Baptist; Gerhold-Ay, Aslihan; Blettner, Maria

2009-09-01

Descriptive statistics are an essential part of biometric analysis and a prerequisite for the understanding of further statistical evaluations, including the drawing of inferences. When data are well presented, it is usually obvious whether the author has collected and evaluated them correctly and in keeping with accepted practice in the field. Statistical variables in medicine may be of either the metric (continuous, quantitative) or categorical (nominal, ordinal) type. Easily understandable examples are given. Basic techniques for the statistical description of collected data are presented and illustrated with examples. The goal of a scientific study must always be clearly defined. The definition of the target value or clinical endpoint determines the level of measurement of the variables in question. Nearly all variables, whatever their level of measurement, can be usefully presented graphically and numerically. The level of measurement determines what types of diagrams and statistical values are appropriate. There are also different ways of presenting combinations of two independent variables graphically and numerically. The description of collected data is indispensable. If the data are of good quality, valid and important conclusions can already be drawn when they are properly described. Furthermore, data description provides a basis for inferential statistics.

Estimating an area-level socioeconomic status index and its association with colonoscopy screening adherence.

PubMed

Wheeler, David C; Czarnota, Jenna; Jones, Resa M

2017-01-01

Socioeconomic status (SES) is often considered a risk factor for health outcomes. SES is typically measured using individual variables of educational attainment, income, housing, and employment variables or a composite of these variables. Approaches to building the composite variable include using equal weights for each variable or estimating the weights with principal components analysis or factor analysis. However, these methods do not consider the relationship between the outcome and the SES variables when constructing the index. In this project, we used weighted quantile sum (WQS) regression to estimate an area-level SES index and its effect in a model of colonoscopy screening adherence in the Minnesota-Wisconsin Metropolitan Statistical Area. We considered several specifications of the SES index including using different spatial scales (e.g., census block group-level, tract-level) for the SES variables. We found a significant positive association (odds ratio = 1.17, 95% CI: 1.15-1.19) between the SES index and colonoscopy adherence in the best fitting model. The model with the best goodness-of-fit included a multi-scale SES index with 10 variables at the block group-level and one at the tract-level, with home ownership, race, and income among the most important variables. Contrary to previous index construction, our results were not consistent with an assumption of equal importance of variables in the SES index when explaining colonoscopy screening adherence. Our approach is applicable in any study where an SES index is considered as a variable in a regression model and the weights for the SES variables are not known in advance.

What variables can influence clinical reasoning?

PubMed

Ashoorion, Vahid; Liaghatdar, Mohammad Javad; Adibi, Peyman

2012-12-01

Clinical reasoning is one of the most important competencies that a physician should achieve. Many medical schools and licensing bodies try to predict it based on some general measures such as critical thinking, personality, and emotional intelligence. This study aimed at providing a model to design the relationship between the constructs. Sixty-nine medical students participated in this study. A battery test devised that consist four parts: Clinical reasoning measures, personality NEO inventory, Bar-On EQ inventory, and California critical thinking questionnaire. All participants completed the tests. Correlation and multiple regression analysis consumed for data analysis. There is low to moderate correlations between clinical reasoning and other variables. Emotional intelligence is the only variable that contributes clinical reasoning construct (r=0.17-0.34) (R(2) chnage = 0.46, P Value = 0.000). Although, clinical reasoning can be considered as a kind of thinking, no significant correlation detected between it and other constructs. Emotional intelligence (and its subscales) is the only variable that can be used for clinical reasoning prediction.

Comparison of modelling accuracy with and without exploiting automated optical monitoring information in predicting the treated wastewater quality.

PubMed

Tomperi, Jani; Leiviskä, Kauko

2018-06-01

Traditionally the modelling in an activated sludge process has been based on solely the process measurements, but as the interest to optically monitor wastewater samples to characterize the floc morphology has increased, in the recent years the results of image analyses have been more frequently utilized to predict the characteristics of wastewater. This study shows that the traditional process measurements or the automated optical monitoring variables by themselves are not capable of developing the best predictive models for the treated wastewater quality in a full-scale wastewater treatment plant, but utilizing these variables together the optimal models, which show the level and changes in the treated wastewater quality, are achieved. By this early warning, process operation can be optimized to avoid environmental damages and economic losses. The study also shows that specific optical monitoring variables are important in modelling a certain quality parameter, regardless of the other input variables available.

Assessing the accuracy and stability of variable selection methods for random forest modeling in ecology.

PubMed

Fox, Eric W; Hill, Ryan A; Leibowitz, Scott G; Olsen, Anthony R; Thornbrugh, Darren J; Weber, Marc H

2017-07-01

Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological data sets, there is limited guidance on variable selection methods for RF modeling. Typically, either a preselected set of predictor variables are used or stepwise procedures are employed which iteratively remove variables according to their importance measures. This paper investigates the application of variable selection methods to RF models for predicting probable biological stream condition. Our motivating data set consists of the good/poor condition of n = 1365 stream survey sites from the 2008/2009 National Rivers and Stream Assessment, and a large set (p = 212) of landscape features from the StreamCat data set as potential predictors. We compare two types of RF models: a full variable set model with all 212 predictors and a reduced variable set model selected using a backward elimination approach. We assess model accuracy using RF's internal out-of-bag estimate, and a cross-validation procedure with validation folds external to the variable selection process. We also assess the stability of the spatial predictions generated by the RF models to changes in the number of predictors and argue that model selection needs to consider both accuracy and stability. The results suggest that RF modeling is robust to the inclusion of many variables of moderate to low importance. We found no substantial improvement in cross-validated accuracy as a result of variable reduction. Moreover, the backward elimination procedure tended to select too few variables and exhibited numerous issues such as upwardly biased out-of-bag accuracy estimates and instabilities in the spatial predictions. We use simulations to further support and generalize results from the analysis of real data. A main purpose of this work is to elucidate issues of model selection bias and instability to ecologists interested in using RF to develop predictive models with large environmental data sets.

[Patients' perspective and economic variables as objectives in clinical trials: added value to clinical parameters].

PubMed

Bovaira-García, M J; Soler-Company, E

2012-01-01

Patient-reported outcome (PRO) measures complement traditional biomedical outcome measures. The purpose of this study was to evaluate the use of PRO measures including health-related quality of life (HRQoL) questionnaires as a measurement of efficacy and the frequency of inclusion of economic variables related to direct and indirect costs in the design of clinical trials and phase IV observational studies. Moreover, for the trials quality score were measured, and if there were any relationship between the quality study design score and the PRO inclusion. Retrospective observational study of the clinical trials and phase IV observational studies approved by a Clinical Research Ethics Committee (2008-2010). We gathered data concerning general aspects including medical specialty, pathology, methodological quality based on Jadad scale (0-5), inclusion of PRO and economic variables. For clinical trials including HRQoL measurements, we analysed the type of questionnaire in use. Where there were no HRQoL measurements, we analysed if their inclusion would have been proper or not. A total of 70 protocols (59 CTs and 11 phase IV observational studies) were analysed; 37 (52.8%) included PRO measures, and 3 protocols (4.3%) used them as a primary endpoint. Data analysis by therapeutic area showed that PRO measures were most commonly studied in the fields of endocrinology, neurology, digestive diseases, and cardiology. The average quality score for the trials was 2.8. The trials with more PRO inclusion in their end points had a significantly higher quality score. Only 13 (22%) clinical trials and 2 (18.2%) phase IV observational studies included economic variables. The emergence of economic variables in clinical trials and phase IV observational studies evaluated was low, however, more than half of the revised protocols have included PRO measures, reflecting the importance of these parameters in the assessment of the effectiveness of drug treatments, although its use is still not systematic. Copyright © 2011 SECA. Published by Elsevier Espana. All rights reserved.

Why risk managers need information about spatio-temporal variability of natural hazards. Examples from practice

NASA Astrophysics Data System (ADS)

Zischg, Andreas

2013-04-01

Integrated risk management consists of risk prevention, early warning, intervention during an event and restoration/re-construction after an event. The prevention phase consists of land use planning measures with a long-term time horizon and of structural measures that sometimes have a lifespan of more than 30-50 years. In this case, it is important to analyse the long-term evolvement of natural risks due to climate changes or land use changes. Besides of this, the spatial and temporal variability of a natural hazard process during the course of an event is also important. The shift from "static" hazard and risk assessment towards a "dynamic" assessment offers benefits for improving the intervention phase in risk management. This contribution describes some examples and points out the benefits of this shift for risk management. One example is the variable disposition of small alpine catchments for runoff and its relevance for early warning. The disposition for runoff depends on the actual status of environmental variables such as soil moisture and the snowpack characteristics. A feasibility study showed how the monitoring of soil moisture and the status of the snowpack can be incorporated into a rule base for describing the temporal variability of the disposition for high runoff in alpine catchments. The study showed that this information about the system state of alpine catchments can be used to improve the assessment of the consequences of a weather forecast for risk management. Another example is the use of snowpack and weather monitoring and traffic intensity measurements for avalanche risk management on alpine roads. Here, the information about the spatio-temporal variability of the snow avalanches and the presence of vehicles can be used for improving the procedures for road closure and re-opening. Another example is the preparation of intervention plans for fire brigades and other relief units during urban floods. The simulation of the temporal evolvement of a single flood event (time horizon of 0-24 hours) provides information for the elaboration of the intervention tactic. The following questions can be answered only by knowing the temporal and spatial evolvement during an event itself: Which intervention priorities have to be set if the resources of the relief units are limited? Which early interventions could be turn out to be unhelpful because in a later step the object to be protected will be flooded anyway? What is the time available for setting up object protection measures and other flood protection measures? The most important factor to implement the theory in practice is the focus on the interlinkages between the simulation of all possible scenarios in advance (scenario techniques, analysing the time-steps in flood simulation), the monitoring system (now-casting, real-time-data), the scenarios of intervention measures and their interdependency with the hazard scenarios. The interlinkages can be set up and described with the expert system approach.

Relation of physical and chemical characteristics of streams to fish communities in the Red River of the North basin, Minnesota and North Dakota, 1993-95

USGS Publications Warehouse

Goldstein, R.M.; Stauffer, J.C.; Larson, P.R.; Lorenz, D.L.

1996-01-01

Within the instream habitat data set, measures of habitat volume (channel width and depth) and habitat diversity were most significant in explaining the variability of the fish communities. The amount of nonagricultural land and riparian zone integrity from the terrestrial habitat data set were also useful in explaining fish community composition. Variability of mean monthly discharge and the frequency of high and low discharge events during the three years prior to fish sampling were the most influential of the hydrologic variables.The first two axes of the canonical correspondence analysis accounted for 43.3 percent of the variation in the fish community and 52.5 percent of the variation in the environmental-species relation. Water-quality indicators such as the percent of fine material in suspended sediment, minimum dissolved oxygen concentrations, minimum concentrations of dissolved organic carbon, and the range of concentrations of major ions and nutrients were the variables that were most important in the canonical correspondence analysis of water-quality data with fish. No single environmental variable or data set appeared to be more important than another in explaining variation in the fish community. The environmental factors affecting the fish communities of the Red River of the North are interrelated. For the most part, instream environmental conditions (instream habitat, hydrology, and water chemistry) appear to be more important in explaining variability in fish community composition than factors related to the agricultural nature of the basin.

Analysis of vegetation changes in Rock Creek Park, 1991-2007

USGS Publications Warehouse

Hatfield, Jeff S.; Krafft, Cairn

2009-01-01

Vegetation data collected at Rock Creek Park every 4 years during 1991-2007 were analyzed for differences among 3 regions within the park and among years. The variables measured and analyzed were percentage of twigs browsed, percentage of canopy cover, species richness of herbaceous plants, number of tree seedlings in each of 7 height classes, tree seedling stocking rate for low deer density and high deer density areas, percentage of tree and shrub cover < 2 m in height, mean diameter at breast height (DBH) of trees > 1 cm DBH, number of tree stems > 1 cm DBH, species richness of trees and shrubs, and mean height of the 5 tallest trees in each plot quadrant. Repeated measures analysis of variance (ANOVA) was used to test for differences and, except for some differences in tree species composition among the 3 regions, no differences (P > 0.01) were found among the 3 regions in the variables discussed above. Many of the variables showed very significant differences (P < 0.01) among years, and causative factors should be investigated further. In addition, importance values were calculated for the 10 most important tree species in each region and changes over time were reported. Future sampling recommendations are also discussed.

Air Quality and Meteorological Boundary Conditions during the MCMA-2003 Field Campaign

NASA Astrophysics Data System (ADS)

Sosa, G.; Arriaga, J.; Vega, E.; Magaña, V.; Caetano, E.; de Foy, B.; Molina, L. T.; Molina, M. J.; Ramos, R.; Retama, A.; Zaragoza, J.; Martínez, A. P.; Márquez, C.; Cárdenas, B.; Lamb, B.; Velasco, E.; Allwine, E.; Pressley, S.; Westberg, H.; Reyes, R.

2004-12-01

A comprehensive field campaign to characterize photochemical smog in the Mexico City Metropolitan Area (MCMA) was conducted during April 2003. An important number of equipment was deployed all around the urban core and its surroundings to measure gas and particles composition from the various sources and receptor sites. In addition to air quality measurements, meteorology variables were also taken by regular weather meteorological stations, tethered balloons, radiosondes, sodars and lidars. One important issue with regard to the field campaign was the characterization of the boundary conditions in order to feed meteorological and air quality models. Four boundary sites were selected to measure continuously criteria pollutants, VOC and meteorological variables at surface level. Vertical meteorological profiles were measured at three other sites : radiosondes in Tacubaya site were launched every six hours daily; tethered balloons were launched at CENICA and FES-Cuautitlan sites according to the weather conditions, and one sodar was deployed at UNAM site in the south of the city. Additionally to these measurements, two fixed meteorological monitoring networks deployed along the city were available to complement these measurements. In general, we observed that transport of pollutants from the city to the boundary sites changes every day, according to the coupling between synoptic and local winds. This effect were less important at elevated sites such as Cerro de la Catedral and ININ, where synoptic wind were more dominant during the field campaign. Also, local sources nearby boundary sites hide the influence of pollution coming from the city some days, particularly at the La Reforma site.

Success in everyday physics: The role of personality and academic variables

NASA Astrophysics Data System (ADS)

Norvilitis, Jill M.; Reid, Howard M.; Norvilitis, Bret M.

2002-05-01

Two studies examined students' intuitive physics ability and characteristics associated with physics competence. In Study 1, although many students did well on a physics quiz, more than 25% of students performed below levels predicted by chance. Better performance on the physics quiz was related to physics grades, highest level of math taken, and students' perceived scholastic competence, but was not related to a number of other hypothesized personality variables. Study 2 further explored personality and academic variables and also examined students' awareness of their own physics ability. Results indicate that the personality variables were again unrelated to ability, but narcissism may be related to subjects' estimates of knowledge. Also, academic variables and how important students think it is to understand the physical world are related to both measured and estimated physics proficiency.

Drivers for spatial variability in agricultural soil organic carbon stocks in Germany

NASA Astrophysics Data System (ADS)

Vos, Cora; Don, Axel; Hobley, Eleanor; Prietz, Roland; Heidkamp, Arne; Freibauer, Annette

2017-04-01

Soil organic carbon is one of the largest components of the global carbon cycle. It has recently gained importance in global efforts to mitigate climate change through carbon sequestration. In order to find locations suitable for carbon sequestration, and estimate the sequestration potential, however, it is necessary to understand the factors influencing the high spatial variability of soil organic carbon stocks. Due to numerous interacting factors that influence its dynamics, soil organic carbon stocks are difficult to predict. In the course of the German Agricultural Soil Inventory over 2500 agricultural sites were sampled and their soil organic carbon stocks determined. Data relating to more than 200 potential drivers of SOC stocks were compiled from laboratory measurements, farmer questionnaires and climate stations. The aims of this study were to 1) give an overview of soil organic carbon stocks in Germany's agricultural soils, 2) to quantify and explain the influence of explanatory variables on soil organic carbon stocks. Two different machine learning algorithms were used to identify the most important variables and multiple regression models were used to explore the influence of those variables. Models for predicting carbon stocks in different depth increments between 0-100 cm were developed, explaining up to 62% (validation, 98% calibration) of total variance. Land-use, land-use history, clay content and electrical conductivity were main predictors in the topsoil, while bedrock material, relief and electrical conductivity governed the variability of subsoil carbon stocks. We found 32% of all soils to be deeply anthropogenically transformed. The influence of climate related variables was surprisingly small (≤5% of explained variance), while site variables explained a large share of soil carbon variability (46-100% of explained variance), in particular in the subsoil. Thus, the understanding of SOC dynamics at regional scale requires a thorough description of the variability in soil physical parameters. Agronomic management impact on SOC stocks is important near the soil surface, but is mainly attributable to land-use and not to other management factors on this large regional scale. The importance of historical land-use practices as well as anthropogenic soil transformations to SOC stocks highlights the need for prudent soil management and conservation policies.

Decadal variability of surface incident solar radiation over China: Observations, satellite retrievals, and reanalyses

NASA Astrophysics Data System (ADS)

Wang, Kaicun; Ma, Qian; Li, Zhijun; Wang, Jiankai

2015-07-01

Existing studies have shown that observed surface incident solar radiation (Rs) over China may have important inhomogeneity issues. This study provides metadata and reference data to homogenize observed Rs, from which the decadal variability of Rs over China can be accurately derived. From 1958 to 1990, diffuse solar radiation (Rsdif) and direct solar radiation (Rsdir) were measured separately, and Rs was calculated as their sum. The pyranometers used to measure Rsdif had a strong sensitivity drift problem, which introduced a spurious decreasing trend into the observed Rsdif and Rs data, whereas the observed Rsdir did not suffer from this sensitivity drift problem. From 1990 to 1993, instruments and measurement methods were replaced and measuring stations were restructured in China, which introduced an abrupt increase in the observed Rs. Intercomparisons between observation-based and model-based Rs performed in this research show that sunshine duration (SunDu)-derived Rs is of high quality and can be used as reference data to homogenize observed Rs data. The homogenized and adjusted data of observed Rs combines the advantages of observed Rs in quantifying hourly to monthly variability and SunDu-derived Rs in depicting decadal variability and trend. Rs averaged over 105 stations in China decreased at -2.9 W m-2 per decade from 1961 to 1990 and remained stable afterward. This decadal variability is confirmed by the observed Rsdir and diurnal temperature ranges, and can be reproduced by high-quality Earth System Models. However, neither satellite retrievals nor reanalyses can accurately reproduce such decadal variability over China.

Analysis of the impact of safeguards criteria

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

Mullen, M.F.; Reardon, P.T.

As part of the US Program of Technical Assistance to IAEA Safeguards, the Pacific Northwest Laboratory (PNL) was asked to assist in developing and demonstrating a model for assessing the impact of setting criteria for the application of IAEA safeguards. This report presents the results of PNL's work on the task. The report is in three parts. The first explains the technical approach and methodology. The second contains an example application of the methodology. The third presents the conclusions of the study. PNL used the model and computer programs developed as part of Task C.5 (Estimation of Inspection Efforts) ofmore » the Program of Technical Assistance. The example application of the methodology involves low-enriched uranium conversion and fuel fabrication facilities. The effects of variations in seven parameters are considered: false alarm probability, goal probability of detection, detection goal quantity, the plant operator's measurement capability, the inspector's variables measurement capability, the inspector's attributes measurement capability, and annual plant throughput. Among the key results and conclusions of the analysis are the following: the variables with the greatest impact on the probability of detection are the inspector's measurement capability, the goal quantity, and the throughput; the variables with the greatest impact on inspection costs are the throughput, the goal quantity, and the goal probability of detection; there are important interactions between variables. That is, the effects of a given variable often depends on the level or value of some other variable. With the methodology used in this study, these interactions can be quantitatively analyzed; reasonably good approximate prediction equations can be developed using the methodology described here.« less

Management, morphological, and environmental factors influencing Douglas-fir bark furrows in the Oregon Coast Range

USGS Publications Warehouse

Sheridan, Christopher D.; Puettmann, Klaus J.; Huso, Manuela M.P.; Hagar, Joan C.; Falk, Kristen R.

2013-01-01

Many land managers in the Pacific Northwest have the goal of increasing late-successional forest structures. Despite the documented importance of Douglas-fir tree bark structure in forested ecosystems, little is known about factors influencing bark development and how foresters can manage development. This study investigated the relative importance of tree size, growth, environmental factors, and thinning on Douglas-fir bark furrow characteristics in the Oregon Coast Range. Bark furrow depth, area, and bark roughness were measured for Douglas-fir trees in young heavily thinned and unthinned sites and compared to older reference sites. We tested models for relationships between bark furrow response and thinning, tree diameter, diameter growth, and environmental factors. Separately, we compared bark responses measured on trees used by bark-foraging birds with trees with no observed usage. Tree diameter and diameter growth were the most important variables in predicting bark characteristics in young trees. Measured environmental variables were not strongly related to bark characteristics. Bark furrow characteristics in old trees were influenced by tree diameter and surrounding tree densities. Young trees used by bark foragers did not have different bark characteristics than unused trees. Efforts to enhance Douglas-fir bark characteristics should emphasize retention of larger diameter trees' growth enhancement.

Reference intervals for plasma concentrations of adrenal steroids measured by LC-MS/MS: Impact of gender, age, oral contraceptives, body mass index and blood pressure status.

PubMed

Eisenhofer, Graeme; Peitzsch, Mirko; Kaden, Denise; Langton, Katharina; Pamporaki, Christina; Masjkur, Jimmy; Tsatsaronis, George; Mangelis, Anastasios; Williams, Tracy A; Reincke, Martin; Lenders, Jacques W M; Bornstein, Stefan R

2017-07-01

Mass spectrometric-based measurements of the steroid metabolome have been introduced to diagnose disorders featuring abnormal steroidogenesis. Defined reference intervals are important for interpreting such data. Liquid chromatography-tandem mass spectrometry was used to establish reference intervals for 16 steroids (pregnenolone, progesterone, 11-deoxycorticosterone, corticosterone, aldosterone, 18-oxocortisol, 18-hydroxycortisol, 17-hydroxyprogesterone, 21-deoxycortisol, 11-deoxycortisol, cortisol, cortisone, dehydroepiandrosterone, dehydroepiandrosterone-sulfate, androstenedione, testosterone) measured in plasma from 525 volunteers with (n=227) and without (n=298) hypertension, including 68 women on oral contraceptives. Women showed variable plasma concentrations of several steroids associated with menstrual cycle phase, menopause and oral contraceptive use. Progesterone was higher in females than males, but most other steroids were higher in males than females and almost all declined with advancing age. Using models that corrected for age and gender, body mass index showed weak negative relationships with corticosterone, 21-deoxycortisol, cortisol, cortisone, testosterone, progesterone, 17-hydroxyprogesterone and 11-deoxycorticosterone, but a positive relationship with 18-hydroxycortisol. Hypertensives and normotensives showed negligible differences in plasma concentrations of steroids. Age and gender are the most important variables for plasma steroid reference intervals, which have been established here according to those variables for a panel of 16 steroids primarily useful for diagnosis and subtyping of patients with endocrine hypertension. Copyright © 2017. Published by Elsevier B.V.

Religious pro-sociality? Experimental evidence from a sample of 766 Spaniards.

PubMed

Brañas-Garza, Pablo; Espín, Antonio M; Neuman, Shoshana

2014-01-01

This study explores the relationship between several personal religion-related variables and social behaviour, using three paradigmatic economic games: the dictator (DG), ultimatum (UG), and trust (TG) games. A large carefully designed sample of the urban adult population in Granada (Spain) is employed (N = 766). From participants' decisions in these games we obtain measures of altruism, bargaining behaviour and sense of fairness/equality, trust, and positive reciprocity. Three dimensions of religiosity are examined: (i) religious denomination; (ii) intensity of religiosity, measured by active participation at church services; and (iii) conversion out into a different denomination than the one raised in. The major results are: (i) individuals with "no religion" made decisions closer to rational selfish behaviour in the DG and the UG compared to those who affiliate with a "standard" religious denomination; (ii) among Catholics, intensity of religiosity is the key variable that affects social behaviour insofar as religiously-active individuals are generally more pro-social than non-active ones; and (iii) the religion raised in seems to have no effect on pro-sociality, beyond the effect of the current measures of religiosity. Importantly, behaviour in the TG is not predicted by any of the religion-related variables we analyse. While the results partially support the notion of religious pro-sociality, on the other hand, they also highlight the importance of closely examining the multidimensional nature of both religiosity and pro-social behaviour.

The influence of contour line size and location on the reproducibility of topographic measurement with the Heidelberg Retina Tomograph.

PubMed

Roff, E J; Hosking, S L; Barnes, D A

2001-05-01

The recommended contour line (CL) location with the Heidelberg Retina Tomograph (HRT) is on the inner edge of Elschnig's scleral ring. This study investigated HRT parameter reproducibility when: (i) the CL size is altered relative to Elschnig's ring; (ii) the CL is either redrawn or imported between images. Using the HRT, seven 10 degrees images were acquired for 10 normal volunteers and 10 primary open angle glaucoma (POAG) subjects. A CL was drawn on one image for each subject using Elschnig's scleral ring for reference and imported into subsequent images. The CL diameter was then (a) increased by 50 microns; (b) increased by 100 microns; and (c) decreased by 50 microns. To investigate the effect of the method of contour line transfer between images a CL was: (1) defined for one image and imported to 6 subsequent images; (2) drawn separately for each image. Parameter variability improved as the size of the CL increased for the normal group relative to Elschnig's ring but was unchanged in the POAG group. The export/import function (method 1) resulted in better parameter reproducibility than the redrawing method for both groups. The exporting and importing function resulted in better parameter variability for both subject groups and should be used for transferring CLs across images for the same subject. Increasing the overall CL size relative to Elschnig's scleral ring improved the reproducibility of the measured parameters in the normal group. No significant difference in parameter variability was observed for the POAG group. This suggests that the reproducibility of HRT images are affected more by the variation in topography between images than change in CL definition.

Technical Note: The Initial Stages of Statistical Data Analysis

PubMed Central

Tandy, Richard D.

1998-01-01

Objective: To provide an overview of several important data-related considerations in the design stage of a research project and to review the levels of measurement and their relationship to the statistical technique chosen for the data analysis. Background: When planning a study, the researcher must clearly define the research problem and narrow it down to specific, testable questions. The next steps are to identify the variables in the study, decide how to group and treat subjects, and determine how to measure, and the underlying level of measurement of, the dependent variables. Then the appropriate statistical technique can be selected for data analysis. Description: The four levels of measurement in increasing complexity are nominal, ordinal, interval, and ratio. Nominal data are categorical or “count” data, and the numbers are treated as labels. Ordinal data can be ranked in a meaningful order by magnitude. Interval data possess the characteristics of ordinal data and also have equal distances between levels. Ratio data have a natural zero point. Nominal and ordinal data are analyzed with nonparametric statistical techniques and interval and ratio data with parametric statistical techniques. Advantages: Understanding the four levels of measurement and when it is appropriate to use each is important in determining which statistical technique to use when analyzing data. PMID:16558489

THE VARIABILITY OF HCN IN TITAN’S UPPER ATMOSPHERE AS IMPLIED BY THE CASSINI ION-NEUTRAL MASS SPECTROMETER MEASUREMENTS

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

Cui, J.; Cao, Y.-T.; Lavvas, P. P.

2016-07-20

HCN is an important constituent in Titan’s upper atmosphere, serving as the main coolant in the local energy budget. In this study, we derive the HCN abundance at the altitude range of 960–1400 km, combining the Ion-Neutral Mass Spectrometer data acquired during a large number of Cassini flybys with Titan. Typically, the HCN abundance declines modestly with increasing altitude and flattens to a near constant level above 1200 km. The data reveal a tendency for dayside depletion of HCN, which is clearly visible below 1000 km but weakens with increasing altitude. Despite the absence of convincing anti-correlation between HCN volumemore » mixing ratio and neutral temperature, we argue that the variability in HCN abundance makes an important contribution to the large temperature variability observed in Titan’s upper atmosphere.« less

Has competition increased hospital technical efficiency?

PubMed

Lee, Keon-Hyung; Park, Jungwon; Lim, Seunghoo; Park, Sang-Chul

2015-01-01

Hospital competition and managed care have affected the hospital industry in various ways including technical efficiency. Hospital efficiency has become an important topic, and it is important to properly measure hospital efficiency in order to evaluate the impact of policies on the hospital industry. The primary independent variable is hospital competition. By using the 2001-2004 inpatient discharge data from Florida, we calculate the degree of hospital competition in Florida for 4 years. Hospital efficiency scores are developed using the Data Envelopment Analysis and by using the selected input and output variables from the American Hospital Association's Annual Survey of Hospitals for those acute care general hospitals in Florida. By using the hospital efficiency score as a dependent variable, we analyze the effects of hospital competition on hospital efficiency from 2001 to 2004 and find that when a hospital was located in a less competitive market in 2003, its technical efficiency score was lower than those in a more competitive market.

Introduction to the use of regression models in epidemiology.

PubMed

Bender, Ralf

2009-01-01

Regression modeling is one of the most important statistical techniques used in analytical epidemiology. By means of regression models the effect of one or several explanatory variables (e.g., exposures, subject characteristics, risk factors) on a response variable such as mortality or cancer can be investigated. From multiple regression models, adjusted effect estimates can be obtained that take the effect of potential confounders into account. Regression methods can be applied in all epidemiologic study designs so that they represent a universal tool for data analysis in epidemiology. Different kinds of regression models have been developed in dependence on the measurement scale of the response variable and the study design. The most important methods are linear regression for continuous outcomes, logistic regression for binary outcomes, Cox regression for time-to-event data, and Poisson regression for frequencies and rates. This chapter provides a nontechnical introduction to these regression models with illustrating examples from cancer research.

A multivariate model of parent-adolescent relationship variables in early adolescence.

PubMed

McKinney, Cliff; Renk, Kimberly

2011-08-01

Given the importance of predicting outcomes for early adolescents, this study examines a multivariate model of parent-adolescent relationship variables, including parenting, family environment, and conflict. Participants, who completed measures assessing these variables, included 710 culturally diverse 11-14-year-olds who were attending a middle school in a Southeastern state. The parents of a subset of these adolescents (i.e., 487 mother-father pairs) participated in this study as well. Correlational analyses indicate that authoritative and authoritarian parenting, family cohesion and adaptability, and conflict are significant predictors of early adolescents' internalizing and externalizing problems. Structural equation modeling analyses indicate that fathers' parenting may not predict directly externalizing problems in male and female adolescents but instead may act through conflict. More direct relationships exist when examining mothers' parenting. The impact of parenting, family environment, and conflict on early adolescents' internalizing and externalizing problems and the importance of both gender and cross-informant ratings are emphasized.

Kinematic measures of Arm-trunk movements during unilateral and bilateral reaching predict clinically important change in perceived arm use in daily activities after intensive stroke rehabilitation.

PubMed

Chen, Hao-ling; Lin, Keh-chung; Liing, Rong-jiuan; Wu, Ching-yi; Chen, Chia-ling

2015-09-21

Kinematic analysis has been used to objectively evaluate movement patterns, quality, and strategies during reaching tasks. However, no study has investigated whether kinematic variables during unilateral and bilateral reaching tasks predict a patient's perceived arm use during activities of daily living (ADL) after an intensive intervention. Therefore, this study investigated whether kinematic measures during unilateral and bilateral reaching tasks before an intervention can predict clinically meaningful improvement in perceived arm use during ADL after intensive poststroke rehabilitation. The study was a secondary analysis of 120 subjects with chronic stroke who received 90-120 min of intensive intervention every weekday for 3-4 weeks. Reaching kinematics during unilateral and bilateral tasks and the Motor Activity Log (MAL) were evaluated before and after the intervention. Kinematic variables explained 22 and 11 % of the variance in actual amount of use (AOU) and quality of movement (QOM), respectively, of MAL improvement during unilateral reaching tasks. Kinematic variables also explained 21 and 31 % of the variance in MAL-AOU and MAL-QOM, respectively, during bilateral reaching tasks. Selected kinematic variables, including endpoint variables, trunk involvement, and joint recruitment and interjoint coordination, were significant predictors for improvement in perceived arm use during ADL (P < 0.05). Arm-trunk kinematics may be used to predict clinically meaningful improvement in perceived arm use during ADL after intensive rehabilitation. Involvement of interjoint coordination and trunk control variables as predictors in bilateral reaching models indicates that a high level of motor control (i.e., multijoint coordination) and trunk stability may be important in obtaining treatment gains in arm use, especially for bilateral daily activities, in intensive rehabilitation after stroke.

Spatial Distribution of a Large Herbivore Community at Waterholes: An Assessment of Its Stability over Years in Hwange National Park, Zimbabwe.

PubMed

Chamaillé-Jammes, Simon; Charbonnel, Anaïs; Dray, Stéphane; Madzikanda, Hillary; Fritz, Hervé

2016-01-01

The spatial structuring of populations or communities is an important driver of their functioning and their influence on ecosystems. Identifying the (in)stability of the spatial structure of populations is a first step towards understanding the underlying causes of these structures. Here we studied the relative importance of spatial vs. interannual variability in explaining the patterns of abundance of a large herbivore community (8 species) at waterholes in Hwange National Park (Zimbabwe). We analyzed census data collected over 13 years using multivariate methods. Our results showed that variability in the census data was mostly explained by the spatial structure of the community, as some waterholes had consistently greater herbivore abundance than others. Some temporal variability probably linked to Park-scale migration dependent on annual rainfall was noticeable, however. Once this was accounted for, little temporal variability remained to be explained, suggesting that other factors affecting herbivore abundance over time had a negligible effect at the scale of the study. The extent of spatial and temporal variability in census data was also measured for each species. This study could help in projecting the consequences of surface water management, and more generally presents a methodological framework to simultaneously address the relative importance of spatial vs. temporal effects in driving the distribution of organisms across landscapes.

Spatial Distribution of a Large Herbivore Community at Waterholes: An Assessment of Its Stability over Years in Hwange National Park, Zimbabwe

PubMed Central

Chamaillé-Jammes, Simon; Charbonnel, Anaïs; Dray, Stéphane; Madzikanda, Hillary; Fritz, Hervé

2016-01-01

The spatial structuring of populations or communities is an important driver of their functioning and their influence on ecosystems. Identifying the (in)stability of the spatial structure of populations is a first step towards understanding the underlying causes of these structures. Here we studied the relative importance of spatial vs. interannual variability in explaining the patterns of abundance of a large herbivore community (8 species) at waterholes in Hwange National Park (Zimbabwe). We analyzed census data collected over 13 years using multivariate methods. Our results showed that variability in the census data was mostly explained by the spatial structure of the community, as some waterholes had consistently greater herbivore abundance than others. Some temporal variability probably linked to Park-scale migration dependent on annual rainfall was noticeable, however. Once this was accounted for, little temporal variability remained to be explained, suggesting that other factors affecting herbivore abundance over time had a negligible effect at the scale of the study. The extent of spatial and temporal variability in census data was also measured for each species. This study could help in projecting the consequences of surface water management, and more generally presents a methodological framework to simultaneously address the relative importance of spatial vs. temporal effects in driving the distribution of organisms across landscapes. PMID:27074044

Measuring high spatiotemporal variability in saltation intensity using a low-cost Saltation Detection System: Wind tunnel and field experiments

NASA Astrophysics Data System (ADS)

de Winter, W.; van Dam, D. B.; Delbecque, N.; Verdoodt, A.; Ruessink, B. G.; Sterk, G.

2018-04-01

The commonly observed over prediction of aeolian saltation transport on sandy beaches is, at least in part, caused by saltation intermittency. To study small-scale saltation processes, high frequency saltation sensors are required on a high spatial resolution. Therefore, we developed a low-cost Saltation Detection System (SalDecS) with the aim to measure saltation intensity at a frequency of 10 Hz and with a spatial resolution of 0.10 m in wind-normal direction. Linearity and equal sensitivity of the saltation sensors were investigated during wind tunnel and field experiments. Wind tunnel experiments with a set of 7 SalDec sensors revealed that the variability of sensor sensitivity is at maximum 9% during relatively low saltation intensities. During more intense saltation the variability of sensor sensitivity decreases. A sigmoidal fit describes the relation between mass flux and sensor output measured during 5 different wind conditions. This indicates an increasing importance of sensor saturation with increasing mass flux. We developed a theoretical model to simulate and describe the effect of grain size, grain velocity and saltation intensity on sensor saturation. Time-averaged field measurements revealed sensitivity equality for 85 out of a set of 89 horizontally deployed SalDec sensors. On these larger timescales (hours) saltation variability imposed by morphological features, such as sand strips, can be recognized. We conclude that the SalDecS can be used to measure small-scale spatiotemporal variabilities of saltation intensity to investigate saltation characteristics related to wind turbulence.

Predicting well-being longitudinally for mothers rearing offspring with intellectual and developmental disabilities.

PubMed

Grein, K A; Glidden, L M

2015-07-01

Well-being outcomes for parents of children with intellectual and developmental disabilities (IDD) may vary from positive to negative at different times and for different measures of well-being. Predicting and explaining this variability has been a major focus of family research for reasons that have both theoretical and applied implications. The current study used data from a 23-year longitudinal investigation of adoptive and birth parents of children with IDD to determine which early child, mother and family characteristics would predict the variance in maternal outcomes 20 years after their original measurement. Using hierarchical regression analyses, we tested the predictive power of variables measured when children were 7 years old on outcomes of maternal well-being when children were 26 years old. Outcome variables included maternal self-report measures of depression and well-being. Final models of well-being accounted for 20% to 34% of variance. For most outcomes, Family Accord and/or the personality variable of Neuroticism (emotional stability/instability) were significant predictors, but some variables demonstrated a different pattern. These findings confirm that (1) characteristics of the child, mother and family during childhood can predict outcomes of maternal well-being 20 years later; and (2) different predictor-outcome relationships can vary substantially, highlighting the importance of using multiple measures to gain a more comprehensive understanding of maternal well-being. These results have implications for refining prognoses for parents and for tailoring service delivery to individual child, parent and family characteristics. © 2014 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.

Atmospheric modeling to assess wind dependence in tracer dilution method measurements of landfill methane emissions.

PubMed

Taylor, Diane M; Chow, Fotini K; Delkash, Madjid; Imhoff, Paul T

2018-03-01

The short-term temporal variability of landfill methane emissions is not well understood due to uncertainty in measurement methods. Significant variability is seen over short-term measurement campaigns with the tracer dilution method (TDM), but this variability may be due in part to measurement error rather than fluctuations in the actual landfill emissions. In this study, landfill methane emissions and TDM-measured emissions are simulated over a real landfill in Delaware, USA using the Weather Research and Forecasting model (WRF) for two emissions scenarios. In the steady emissions scenario, a constant landfill emissions rate is prescribed at each model grid point on the surface of the landfill. In the unsteady emissions scenario, emissions are calculated at each time step as a function of the local surface wind speed, resulting in variable emissions over each 1.5-h measurement period. The simulation output is used to assess the standard deviation and percent error of the TDM-measured emissions. Eight measurement periods are simulated over two different days to look at different conditions. Results show that standard deviation of the TDM- measured emissions does not increase significantly from the steady emissions simulations to the unsteady emissions scenarios, indicating that the TDM may have inherent errors in its prediction of emissions fluctuations. Results also show that TDM error does not increase significantly from the steady to the unsteady emissions simulations. This indicates that introducing variability to the landfill emissions does not increase errors in the TDM at this site. Across all simulations, TDM errors range from -15% to 43%, consistent with the range of errors seen in previous TDM studies. Simulations indicate diurnal variations of methane emissions when wind effects are significant, which may be important when developing daily and annual emissions estimates from limited field data. Copyright © 2017 Elsevier Ltd. All rights reserved.

Seasonal and interannual variability of climate and vegetation indices across the Amazon.

PubMed

Brando, Paulo M; Goetz, Scott J; Baccini, Alessandro; Nepstad, Daniel C; Beck, Pieter S A; Christman, Mary C

2010-08-17

Drought exerts a strong influence on tropical forest metabolism, carbon stocks, and ultimately the flux of carbon to the atmosphere. Satellite-based studies have suggested that Amazon forests green up during droughts because of increased sunlight, whereas field studies have reported increased tree mortality during severe droughts. In an effort to reconcile these apparently conflicting findings, we conducted an analysis of climate data, field measurements, and improved satellite-based measures of forest photosynthetic activity. Wet-season precipitation and plant-available water (PAW) decreased over the Amazon Basin from 1996-2005, and photosynthetically active radiation (PAR) and air dryness (expressed as vapor pressure deficit, VPD) increased from 2002-2005. Using improved enhanced vegetation index (EVI) measurements (2000-2008), we show that gross primary productivity (expressed as EVI) declined with VPD and PAW in regions of sparse canopy cover across a wide range of environments for each year of the study. In densely forested areas, no climatic variable adequately explained the Basin-wide interannual variability of EVI. Based on a site-specific study, we show that monthly EVI was relatively insensitive to leaf area index (LAI) but correlated positively with leaf flushing and PAR measured in the field. These findings suggest that production of new leaves, even when unaccompanied by associated changes in LAI, could play an important role in Basin-wide interannual EVI variability. Because EVI variability was greatest in regions of lower PAW, we hypothesize that drought could increase EVI by synchronizing leaf flushing via its effects on leaf bud development.

Students' daily emotions in the classroom: intra-individual variability and appraisal correlates.

PubMed

Ahmed, Wondimu; van der Werf, Greetje; Minnaert, Alexander; Kuyper, Hans

2010-12-01

Recent literature on emotions in education has shown that competence- and value-related beliefs are important sources of students' emotions; nevertheless, the role of these antecedents in students' daily functioning in the classroom is not yet well-known. More importantly, to date we know little about intra-individual variability in students' daily emotions. The objectives of the study were (1) to examine within-student variability in emotional experiences and (2) to investigate how competence and value appraisals are associated with emotions. It was hypothesized that emotions would show substantial within-student variability and that there would be within-person associations between competence and value appraisals and the emotions. (s) The sample consisted of 120 grade 7 students (52%, girls) in 5 randomly selected classrooms in a secondary school. A diary method was used to acquire daily process variables of emotions and appraisals. Daily emotions and daily appraisals were assessed using items adapted from existing measures. Multi-level modelling was used to test the hypotheses. As predicted, the within-person variability in emotional states accounted for between 41% (for pride) and 70% (for anxiety) of total variability in the emotional states. Also as hypothesized, the appraisals were generally associated with the emotions. The within-student variability in emotions and appraisals clearly demonstrates the adaptability of students with respect to situational affordances and constraints in their everyday classroom experiences. The significant covariations between the appraisals and emotions suggest that within-student variability in emotions is systematic.

Interannual Variability of Ammonia Concentrations over the United States: Sources and Implications for Inorganic Particulate Matter

NASA Astrophysics Data System (ADS)

Schiferl, L. D.; Heald, C. L.; Van Damme, M.; Pierre-Francois, C.; Clerbaux, C.

2015-12-01

Modern agricultural practices have greatly increased the emission of ammonia (NH3) to the atmosphere. Recent controls to reduce the emissions of sulfur and nitrogen oxides (SOX and NOX) have increased the importance of understanding the role ammonia plays in the formation of surface fine inorganic particulate matter (PM2.5) in the United States. In this study, we identify the interannual variability in ammonia concentration, explore the sources of this variability and determine their contribution to the variability in surface PM2.5 concentration. Over the summers of 2008-2012, measurements from the Ammonia Monitoring Network (AMoN) and the Infrared Atmospheric Sounding Interferometer (IASI) satellite instrument show considerable variability in both surface and column ammonia concentrations (+/- 29% and 28% of the mean), respectively. This observed variability is larger than that simulated by the GEOS-Chem chemical transport model, where meteorology dominates the variability in ammonia and PM2.5 concentrations compared to the changes caused by SOX and NOX reductions. Our initial simulation does not include year-to-year changes in ammonia agricultural emissions. We use county-wide information on fertilizer sales and livestock populations, as well as meteorological variations to account for the interannual variability in agricultural activity and ammonia volatilization. These sources of ammonia emission variability are important for replicating observed variations in ammonia and PM2.5, highlighting how accurate ammonia emissions characterization is central to PM air quality prediction.

Analytical and biological variability in biomarker measurement in the Hispanic Community Health Study/Study of Latinos.

PubMed

Thyagarajan, Bharat; Howard, Annie Green; Durazo-Arvizu, Ramon; Eckfeldt, John H; Gellman, Marc D; Kim, Ryung S; Liu, Kiang; Mendez, Armando J; Penedo, Frank J; Talavera, Gregory A; Youngblood, Marston E; Zhao, Lihui; Sotres-Alvarez, Daniela

2016-12-01

Biomarker variability, which includes within-individual variability (CV I ), between-individual variability (CV G ) and methodological variability (CV P + A ) is an important determinant of our ability to detect biomarker-disease associations. Estimates of CV I and CV G may be population specific and little data exists on biomarker variability in diverse Hispanic populations. Hence, we evaluated all 3 components of biomarker variability in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) using repeat blood collections (n=58) and duplicate blood measurements (n=761-929 depending on the biomarker). We estimated the index of individuality (II) ((CV I +CV P + A )/CV G ) for 41 analytes and evaluated differences in the II across sexes and age groups. Biomarkers such as fasting glucose, triglycerides and ferritin had substantially higher inter-individual variability and lower II in HCHS/SOL as compared to the published literature. We also found significant sex-specific differences in the II for neutrophil count, platelet count, hemoglobin, % eosinophils and fasting glucose. The II for fasting insulin, post oral glucose tolerance test glucose and cystatin C was significantly higher among the 18-44y age group as compared to the 45+y age group. The implications of these findings for determining biomarker-disease associations in Hispanic populations need to be evaluated in future studies. Copyright © 2016 Elsevier B.V. All rights reserved.

System Complexity Reduction via Feature Selection

ERIC Educational Resources Information Center

Deng, Houtao

2011-01-01

This dissertation transforms a set of system complexity reduction problems to feature selection problems. Three systems are considered: classification based on association rules, network structure learning, and time series classification. Furthermore, two variable importance measures are proposed to reduce the feature selection bias in tree…

Systems effects on family planning innovativeness.

PubMed

Lee, S B

1983-12-01

Data from Korea were used to explore the importance of community level variables in explaining family planning adoption at the individual level. An open system concept was applied, assuming that individual family planning behavior is influenced by both environmental and individual factors. The environmental factors were measured at the village level and designated as community characteristics. The dimension of communication network variables was introduced. Each individual was characterized in terms of the degree of her involvement in family planning communication with others in her village. It was assumed that the nature of the communication network linking individuals with each other effects family planning adoption at the individual level. Specific objectives were to determine 1) the relative importance of the specific independent variables in explaining family planning adoption and 2) the relative importance of the community level variables in comparison with the individual level variables in explaining family planning adoption at the individual level. The data were originally gathered in a 1973 research project on Korea's mothers' clubs. 1047 respondents were interviewed, comprising all married women in 25 sample villages having mothers' clubs. The dependent variable was family planning adoption behavior, defined as current use of any of the modern methods of family planning. The independent variables were defined at 3 levels: individual, community, and at a level intermediate between them involving communication links between individuals. More of the individual level independent variables were significantly correlated with the dependent variables than the community level variables. Among those variables with statistically significant correlations, the correlation coefficients were consistently higher for the individual level than for the community level variables. More of the variance in the dependent variable was explained by individual level than by community level variables. Community level variables accounted for only about 2.5% of the total variance in the dependent variable, in marked contrast to the result showing individual level variables accounting for as much as 19% of the total variance. When both individual and community level variables were entered into a multiple correlation analysis, a multiple correlation coefficient of .4714 was obtained together they explained about 20% of the total variance. The 2 communication network variables--connectedness and integrativeness--were correlated with the dependent variable at much higher levels than most of the individual or community level variables. Connectedness accounted for the greatest amount of the total variance. The communication network variables as a group explained as much of the total variance in the dependent variable as the individual level variables and greatly more that the community level variables.

CO2 variability from in situ and vertical column measurements in Mexico City

NASA Astrophysics Data System (ADS)

Baylon, J. L.; Grutter, M.; Stremme, W.; Bezanilla, A.; Plaza, E.

2014-12-01

UNAM started a program to measure, among many other atmospheric parameters, greenhouse gas concentrations at six stations in the Mexican territory as part of the "Red Universitaria de Observatorios Atmosfericos", RUOA (www.ruoa.unam.mx). In this work we present recent time series of CO2 measured at the station located in the university campus in Mexico City, and compare them to total vertical columns of this gas measured at the same location. In situ measurements are continuously carried out with a cavity ring-down spectrometer (Picarro Inc., G2401) since July 2014 and the columns are retrieved from solar absorption measurements taken with a Fourier transform infrared spectrometer (Bruker, Vertex 80) when conditions allow. The retrieval method is described and results of the comparison of both techniques and a detailed analysis of the variability of this important greenhouse gas is presented. Simultaneous surface and column CO2 data are useful to constrain models and estimate emissions.

Human Movement Variability, Nonlinear Dynamics, and Pathology: Is There A Connection?

PubMed Central

Stergiou, Nicholas; Decker, Leslie M.

2011-01-01

Fields studying movement generation, including robotics, psychology, cognitive science and neuroscience utilize concepts and tools related to the pervasiveness of variability in biological systems. The concept of variability and the measures for nonlinear dynamics used to evaluate this concept open new vistas for research in movement dysfunction of many types. This review describes innovations in the exploration of variability and their potential importance in understanding human movement. Far from being a source of error, evidence supports the presence of an optimal state of variability for healthy and functional movement. This variability has a particular organization and is characterized by a chaotic structure. Deviations from this state can lead to biological systems that are either overly rigid and robotic or noisy and unstable. Both situations result in systems that are less adaptable to perturbations, such as those associated with unhealthy pathological states or absence of skillfulness. PMID:21802756

Controlling for confounding variables in MS-omics protocol: why modularity matters.

PubMed

Smith, Rob; Ventura, Dan; Prince, John T

2014-09-01

As the field of bioinformatics research continues to grow, more and more novel techniques are proposed to meet new challenges and improvements upon solutions to long-standing problems. These include data processing techniques and wet lab protocol techniques. Although the literature is consistently thorough in experimental detail and variable-controlling rigor for wet lab protocol techniques, bioinformatics techniques tend to be less described and less controlled. As the validation or rejection of hypotheses rests on the experiment's ability to isolate and measure a variable of interest, we urge the importance of reducing confounding variables in bioinformatics techniques during mass spectrometry experimentation. © The Author 2013. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Variability of blood alcohol content (BAC) determinations: the role of measurement uncertainty, significant figures, and decision rules for compliance assessment in the frame of a multiple BAC threshold law.

PubMed

Zamengo, Luca; Frison, Giampietro; Tedeschi, Gianpaola; Frasson, Samuela; Zancanaro, Flavio; Sciarrone, Rocco

2014-10-01

The measurement of blood-alcohol content (BAC) is a crucial analytical determination required to assess if an offence (e.g. driving under the influence of alcohol) has been committed. For various reasons, results of forensic alcohol analysis are often challenged by the defence. As a consequence, measurement uncertainty becomes a critical topic when assessing compliance with specification limits for forensic purposes. The aims of this study were: (1) to investigate major sources of variability for BAC determinations; (2) to estimate measurement uncertainty for routine BAC determinations; (3) to discuss the role of measurement uncertainty in compliance assessment; (4) to set decision rules for a multiple BAC threshold law, as provided in the Italian Highway Code; (5) to address the topic of the zero-alcohol limit from the forensic toxicology point of view; and (6) to discuss the role of significant figures and rounding errors on measurement uncertainty and compliance assessment. Measurement variability was investigated by the analysis of data collected from real cases and internal quality control. The contribution of both pre-analytical and analytical processes to measurement variability was considered. The resulting expanded measurement uncertainty was 8.0%. Decision rules for the multiple BAC threshold Italian law were set by adopting a guard-banding approach. 0.1 g/L was chosen as cut-off level to assess compliance with the zero-alcohol limit. The role of significant figures and rounding errors in compliance assessment was discussed by providing examples which stressed the importance of these topics for forensic purposes. Copyright © 2014 John Wiley & Sons, Ltd.

Accounting for measurement error: a critical but often overlooked process.

PubMed

Harris, Edward F; Smith, Richard N

2009-12-01

Due to instrument imprecision and human inconsistencies, measurements are not free of error. Technical error of measurement (TEM) is the variability encountered between dimensions when the same specimens are measured at multiple sessions. A goal of a data collection regimen is to minimise TEM. The few studies that actually quantify TEM, regardless of discipline, report that it is substantial and can affect results and inferences. This paper reviews some statistical approaches for identifying and controlling TEM. Statistically, TEM is part of the residual ('unexplained') variance in a statistical test, so accounting for TEM, which requires repeated measurements, enhances the chances of finding a statistically significant difference if one exists. The aim of this paper was to review and discuss common statistical designs relating to types of error and statistical approaches to error accountability. This paper addresses issues of landmark location, validity, technical and systematic error, analysis of variance, scaled measures and correlation coefficients in order to guide the reader towards correct identification of true experimental differences. Researchers commonly infer characteristics about populations from comparatively restricted study samples. Most inferences are statistical and, aside from concerns about adequate accounting for known sources of variation with the research design, an important source of variability is measurement error. Variability in locating landmarks that define variables is obvious in odontometrics, cephalometrics and anthropometry, but the same concerns about measurement accuracy and precision extend to all disciplines. With increasing accessibility to computer-assisted methods of data collection, the ease of incorporating repeated measures into statistical designs has improved. Accounting for this technical source of variation increases the chance of finding biologically true differences when they exist.

Variability in the Results of Meta-Analysis as a Function of Comparing Effect Sizes Based on Scores from Noncomparable Measures: A Simulation Study

ERIC Educational Resources Information Center

Nugent, William R.

2017-01-01

Meta-analysis is a significant methodological advance that is increasingly important in research synthesis. Fundamental to meta-analysis is the presumption that effect sizes, such as the standardized mean difference (SMD), based on scores from different measures are comparable. It has been argued that population observed score SMDs based on scores…

MISST: The Multi-Sensor Improved Sea Surface Temperature Project

DTIC Science & Technology

2009-06-01

climate change studies, fisheries management, and a wide range of other applications. Measurements are taken by several satellites carrying infrared and...TEMPERATURE PROJECT ABSTRACT. Sea surface temperature (SST) measurements are vital to global weather prediction, climate change studies, fisheries management...important variables related to the global ocean-atmosphere system. It is a key indicator of climate change , is widely applied to studies of upper

School Context Matters: The Impacts of Concentrated Poverty and Racial Segregation on Childhood Obesity.

PubMed

Piontak, Joy Rayanne; Schulman, Michael D

2016-12-01

Schools are important sites for interventions to prevent childhood obesity. This study examines how variables measuring the socioeconomic and racial composition of schools and counties affect the likelihood of obesity among third to fifth grade children. Body mass index data were collected from third to fifth grade public school students by teachers from 317 urban and rural North Carolina schools in 38 counties. Multilevel models are used to examine county-, school-, and individual-level effects. Low concentrations of poverty at the school level are associated with lower odds of obesity. Schools in rural counties had significantly higher rates of obesity, net the other variables in the model. Students in minority-segregated schools had higher rates of obesity than those in more racially diverse schools, but the effect was not statistically significant once school-level poverty was controlled. Place-based inequalities are important determinants of health inequalities. The results of this study show that school-level variables related to poverty are important for understanding and confronting childhood obesity. © 2016, American School Health Association.

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.

The Importance of and the Complexities Associated With Measuring Continuity of Care During Resident Training: Possible Solutions Do Exist.

PubMed

Carney, Patricia A; Conry, Colleen M; Mitchell, Karen B; Ericson, Annie; Dickinson, W Perry; Martin, James C; Carek, Peter J; Douglass, Alan B; Eiff, M Patrice

2016-04-01

Evolutions in care delivery toward the patient-centered medical home have influenced important aspects of care continuity. Primary responsibility for a panel of continuity patients is a foundational requirement in family medicine residencies. In this paper we characterize challenges in measuring continuity of care in residency training in this new era of primary care. We synthesized the literature and analyzed information from key informant interviews and group discussions with residency faculty and staff to identify the challenges and possible solutions for measuring continuity of care during family medicine training. We specifically focused on measuring interpersonal continuity at the patient level, resident level, and health care team level. Challenges identified in accurately measuring interpersonal continuity of care during residency training include: (1) variability in empanelment approaches for all patients, (2) scheduling complexity in different types of visits, (3) variability in ability to attain continuity counts at the level of the resident, and (4) shifting make-up of health care teams, especially in residency training. Possible solutions for each challenge are presented. Philosophical issues related to continuity are discussed, including whether true continuity can be achieved during residency training and whether qualitative rather than quantitative measures of continuity are better suited to residencies. Measuring continuity of care in residency training is challenging but possible, though improvements in precision and assessment of the comprehensive nature of the relationships are needed. Definitions of continuity during training and the role continuity measurement plays in residency need further study.

Developing consensus measures for global programs: lessons from the Global Alliance for Chronic Diseases Hypertension research program.

PubMed

Riddell, Michaela A; Edwards, Nancy; Thompson, Simon R; Bernabe-Ortiz, Antonio; Praveen, Devarsetty; Johnson, Claire; Kengne, Andre P; Liu, Peter; McCready, Tara; Ng, Eleanor; Nieuwlaat, Robby; Ovbiagele, Bruce; Owolabi, Mayowa; Peiris, David; Thrift, Amanda G; Tobe, Sheldon; Yusoff, Khalid

2017-03-15

The imperative to improve global health has prompted transnational research partnerships to investigate common health issues on a larger scale. The Global Alliance for Chronic Diseases (GACD) is an alliance of national research funding agencies. To enhance research funded by GACD members, this study aimed to standardise data collection methods across the 15 GACD hypertension research teams and evaluate the uptake of these standardised measurements. Furthermore we describe concerns and difficulties associated with the data harmonisation process highlighted and debated during annual meetings of the GACD funded investigators. With these concerns and issues in mind, a working group comprising representatives from the 15 studies iteratively identified and proposed a set of common measures for inclusion in each of the teams' data collection plans. One year later all teams were asked which consensus measures had been implemented. Important issues were identified during the data harmonisation process relating to data ownership, sharing methodologies and ethical concerns. Measures were assessed across eight domains; demographic; dietary; clinical and anthropometric; medical history; hypertension knowledge; physical activity; behavioural (smoking and alcohol); and biochemical domains. Identifying validated measures relevant across a variety of settings presented some difficulties. The resulting GACD hypertension data dictionary comprises 67 consensus measures. Of the 14 responding teams, only two teams were including more than 50 consensus variables, five teams were including between 25 and 50 consensus variables and four teams were including between 6 and 24 consensus variables, one team did not provide details of the variables collected and two teams did not include any of the consensus variables as the project had already commenced or the measures were not relevant to their study. Deriving consensus measures across diverse research projects and contexts was challenging. The major barrier to their implementation was related to the time taken to develop and present these measures. Inclusion of consensus measures into future funding announcements would facilitate researchers integrating these measures within application protocols. We suggest that adoption of consensus measures developed here, across the field of hypertension, would help advance the science in this area, allowing for more comparable data sets and generalizable inferences.

Automatic algorithm for monitoring systolic pressure variation and difference in pulse pressure.

PubMed

Pestel, Gunther; Fukui, Kimiko; Hartwich, Volker; Schumacher, Peter M; Vogt, Andreas; Hiltebrand, Luzius B; Kurz, Andrea; Fujita, Yoshihisa; Inderbitzin, Daniel; Leibundgut, Daniel

2009-06-01

Difference in pulse pressure (dPP) reliably predicts fluid responsiveness in patients. We have developed a respiratory variation (RV) monitoring device (RV monitor), which continuously records both airway pressure and arterial blood pressure (ABP). We compared the RV monitor measurements with manual dPP measurements. ABP and airway pressure (PAW) from 24 patients were recorded. Data were fed to the RV monitor to calculate dPP and systolic pressure variation in two different ways: (a) considering both ABP and PAW (RV algorithm) and (b) ABP only (RV(slim) algorithm). Additionally, ABP and PAW were recorded intraoperatively in 10-min intervals for later calculation of dPP by manual assessment. Interobserver variability was determined. Manual dPP assessments were used for comparison with automated measurements. To estimate the importance of the PAW signal, RV(slim) measurements were compared with RV measurements. For the 24 patients, 174 measurements (6-10 per patient) were recorded. Six observers assessed dPP manually in the first 8 patients (10-min interval, 53 measurements); no interobserver variability occurred using a computer-assisted method. Bland-Altman analysis showed acceptable bias and limits of agreement of the 2 automated methods compared with the manual method (RV: -0.33% +/- 8.72% and RV(slim): -1.74% +/- 7.97%). The difference between RV measurements and RV(slim) measurements is small (bias -1.05%, limits of agreement 5.67%). Measurements of the automated device are comparable with measurements obtained by human observers, who use a computer-assisted method. The importance of the PAW signal is questionable.

Freedom of choice of specialist physicians is important to Swiss resident: a cross-sectional study.

PubMed

Peytremann-Bridevaux, Isabelle; Ruffieux, Christiane; Burnand, Bernard

2011-12-19

To assess how important the possibility to choose specialist physicians is for Swiss residents and to determine which variables are associated with this opinion. This cross-sectional study used data from the 2007 Swiss population-based health survey and included 13,642 non-institutionalised adults who responded to the telephone and paper questionnaires. The dependent variable included answers to the question "How important is it for you to be able to choose the specialist you would like to visit?" Independent variables included socio-demographics, health and past year healthcare use measures. Crude and adjusted logistic regressions for the importance of being able to choose specialist physicians were performed, accounting for the survey design. 45% of participants found it very important to be able to choose the specialist physician they wanted to visit. The answers "rather important", "rather not important" and "not important" were reported by 28%, 20% and 7% of respondents. Women, individuals in middle/high executive position, those with an ordinary insurance scheme, those reporting ≥2 chronic conditions or poorer subjective health, or those who had had ≥2 outpatient visits in the preceding year were more likely to find this choice very important. In 2007, almost half of all Swiss residents found it very important to be able to choose his/her specialist physician. The further development of physician networks or other chronic disease management initiatives in Switzerland, towards integrated care, need to pay attention to the freedom of choice of specialist physicians that Swiss residents value. Future surveys should provide information on access and consultations with specialist physicians.

Screening large-scale association study data: exploiting interactions using random forests.

PubMed

Lunetta, Kathryn L; Hayward, L Brooke; Segal, Jonathan; Van Eerdewegh, Paul

2004-12-10

Genome-wide association studies for complex diseases will produce genotypes on hundreds of thousands of single nucleotide polymorphisms (SNPs). A logical first approach to dealing with massive numbers of SNPs is to use some test to screen the SNPs, retaining only those that meet some criterion for further study. For example, SNPs can be ranked by p-value, and those with the lowest p-values retained. When SNPs have large interaction effects but small marginal effects in a population, they are unlikely to be retained when univariate tests are used for screening. However, model-based screens that pre-specify interactions are impractical for data sets with thousands of SNPs. Random forest analysis is an alternative method that produces a single measure of importance for each predictor variable that takes into account interactions among variables without requiring model specification. Interactions increase the importance for the individual interacting variables, making them more likely to be given high importance relative to other variables. We test the performance of random forests as a screening procedure to identify small numbers of risk-associated SNPs from among large numbers of unassociated SNPs using complex disease models with up to 32 loci, incorporating both genetic heterogeneity and multi-locus interaction. Keeping other factors constant, if risk SNPs interact, the random forest importance measure significantly outperforms the Fisher Exact test as a screening tool. As the number of interacting SNPs increases, the improvement in performance of random forest analysis relative to Fisher Exact test for screening also increases. Random forests perform similarly to the univariate Fisher Exact test as a screening tool when SNPs in the analysis do not interact. In the context of large-scale genetic association studies where unknown interactions exist among true risk-associated SNPs or SNPs and environmental covariates, screening SNPs using random forest analyses can significantly reduce the number of SNPs that need to be retained for further study compared to standard univariate screening methods.

Determining the Ocean's Role on the Variable Gravity Field on Earth Rotation

NASA Technical Reports Server (NTRS)

Ponte, Rui M.

1999-01-01

A number of ocean models of different complexity have been used to study changes in the oceanic mass field and angular momentum and their relation to the variable Earth rotation and gravity field. Time scales examined range from seasonal to a few days. Results point to the importance of oceanic signals in driving polar motion, in particular the Chandler and annual wobbles. Results also show that oceanic signals have a measurable impact on length-of-day variations. Various circulation features and associated mass signals, including the North Pacific subtropical gyre, the equatorial currents, and the Antarctic Circumpolar Current play a significant role in oceanic angular momentum variability.

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.

Competition in health insurance markets: limitations of current measures for policy analysis.

PubMed

Scanlon, Dennis P; Chernew, Michael; Swaminathan, Shailender; Lee, Woolton

2006-12-01

Health care reform proposals often rely on increased competition in health insurance markets to drive improved performance in health care costs, access, and quality. We examine a range of data issues related to the measures of health insurance competition used in empirical studies published from 1994-2004. The literature relies exclusively on market structure and penetration variables to measure competition. While these measures are correlated, the degree of correlation is modest, suggesting that choice of measure could influence empirical results. Moreover, certain measurement issues such as the lack of data on PPO enrollment, the treatment of small firms, and omitted market characteristics also could affect the conclusions in empirical studies. Importantly, other types of measures related to competition (e.g., the availability of information on price and outcomes, degree of entry barriers, etc.) are important from both a theoretical and policy perspective, but their impact on market outcomes has not been widely studied.

Sea Surface Salinity Variability from Simulations and Observations: Preparing for Aquarius

NASA Technical Reports Server (NTRS)

Jacob, S. Daniel; LeVine, David M.

2010-01-01

Oceanic fresh water transport has been shown to play an important role in the global hydrological cycle. Sea surface salinity (SSS) is representative of the surface fresh water fluxes and the upcoming Aquarius mission scheduled to be launched in December 2010 will provide excellent spatial and temporal SSS coverage to better estimate the net exchange. In most ocean general circulation models, SSS is relaxed to climatology to prevent model drift. While SST remains a well observed variable, relaxing to SST reduces the range of SSS variability in the simulations (Fig.1). The main objective of the present study is to simulate surface tracers using a primitive equation ocean model for multiple forcing data sets to identify and establish a baseline SSS variability. The simulated variability scales are compared to those from near-surface argo salinity measurements.

Evaluation of variable selection methods for random forests and omics data sets.

PubMed

Degenhardt, Frauke; Seifert, Stephan; Szymczak, Silke

2017-10-16

Machine learning methods and in particular random forests are promising approaches for prediction based on high dimensional omics data sets. They provide variable importance measures to rank predictors according to their predictive power. If building a prediction model is the main goal of a study, often a minimal set of variables with good prediction performance is selected. However, if the objective is the identification of involved variables to find active networks and pathways, approaches that aim to select all relevant variables should be preferred. We evaluated several variable selection procedures based on simulated data as well as publicly available experimental methylation and gene expression data. Our comparison included the Boruta algorithm, the Vita method, recurrent relative variable importance, a permutation approach and its parametric variant (Altmann) as well as recursive feature elimination (RFE). In our simulation studies, Boruta was the most powerful approach, followed closely by the Vita method. Both approaches demonstrated similar stability in variable selection, while Vita was the most robust approach under a pure null model without any predictor variables related to the outcome. In the analysis of the different experimental data sets, Vita demonstrated slightly better stability in variable selection and was less computationally intensive than Boruta.In conclusion, we recommend the Boruta and Vita approaches for the analysis of high-dimensional data sets. Vita is considerably faster than Boruta and thus more suitable for large data sets, but only Boruta can also be applied in low-dimensional settings. © The Author 2017. Published by Oxford University Press.

An evaluation of the relative quality of dike pools for benthic macroinvertebrates in the Lower Missouri River, USA

USGS Publications Warehouse

Poulton, B.C.; Allert, A.L.

2012-01-01

A habitat-based aquatic macroinvertebrate study was initiated in the Lower Missouri River to evaluate relative quality and biological condition of dike pool habitats. Water-quality and sediment-quality parameters and macroinvertebrate assemblage structure were measured from depositional substrates at 18 sites. Sediment porewater was analysed for ammonia, sulphide, pH and oxidation-reduction potential. Whole sediments were analysed for particle-size distribution, organic carbon and contaminants. Field water-quality parameters were measured at subsurface and at the sediment-water interface. Pool area adjacent and downstream from each dike was estimated from aerial photography. Macroinvertebrate biotic condition scores were determined by integrating the following indicator response metrics: % of Ephemeroptera (mayflies), % of Oligochaeta worms, Shannon Diversity Index and total taxa richness. Regression models were developed for predicting macroinvertebrate scores based on individual water-quality and sediment-quality variables and a water/sediment-quality score that integrated all variables. Macroinvertebrate scores generated significant determination coefficients with dike pool area (R2=0.56), oxidation–reduction potential (R2=0.81) and water/sediment-quality score (R2=0.71). Dissolved oxygen saturation, oxidation-reduction potential and total ammonia in sediment porewater were most important in explaining variation in macroinvertebrate scores. The best two-variable regression models included dike pool size + the water/sediment-quality score (R2=0.84) and dike pool size + oxidation-reduction potential (R2=0.93). Results indicate that dike pool size and chemistry of sediments and overlying water can be used to evaluate dike pool quality and identify environmental conditions necessary for optimizing diversity and productivity of important aquatic macroinvertebrates. A combination of these variables could be utilized for measuring the success of habitat enhancement activities currently being implemented in this system.

Combining geodiversity with climate and topography to account for threatened species richness.

PubMed

Tukiainen, Helena; Bailey, Joseph J; Field, Richard; Kangas, Katja; Hjort, Jan

2017-04-01

Understanding threatened species diversity is important for long-term conservation planning. Geodiversity-the diversity of Earth surface materials, forms, and processes-may be a useful biodiversity surrogate for conservation and have conservation value itself. Geodiversity and species richness relationships have been demonstrated; establishing whether geodiversity relates to threatened species' diversity and distribution pattern is a logical next step for conservation. We used 4 geodiversity variables (rock-type and soil-type richness, geomorphological diversity, and hydrological feature diversity) and 4 climatic and topographic variables to model threatened species diversity across 31 of Finland's national parks. We also analyzed rarity-weighted richness (a measure of site complementarity) of threatened vascular plants, fungi, bryophytes, and all species combined. Our 1-km 2 resolution data set included 271 threatened species from 16 major taxa. We modeled threatened species richness (raw and rarity weighted) with boosted regression trees. Climatic variables, especially the annual temperature sum above 5 °C, dominated our models, which is consistent with the critical role of temperature in this boreal environment. Geodiversity added significant explanatory power. High geodiversity values were consistently associated with high threatened species richness across taxa. The combined effect of geodiversity variables was even more pronounced in the rarity-weighted richness analyses (except for fungi) than in those for species richness. Geodiversity measures correlated most strongly with species richness (raw and rarity weighted) of threatened vascular plants and bryophytes and were weakest for molluscs, lichens, and mammals. Although simple measures of topography improve biodiversity modeling, our results suggest that geodiversity data relating to geology, landforms, and hydrology are also worth including. This reinforces recent arguments that conserving nature's stage is an important principle in conservation. © 2016 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.

Value of travel-time reliability : commuters' route-choice behavior in the Twin Cities.

DOT National Transportation Integrated Search

2011-10-01

Travel-time variability is a noteworthy factor in network performance. It measures the temporal uncertainty experienced by users in their : movement between any two nodes in a network. The importance of the time variance depends on the penalties incu...

Life satisfaction and student engagement in adolescents.

PubMed

Lewis, Ashley D; Huebner, E Scott; Malone, Patrick S; Valois, Robert F

2011-03-01

Situated within a positive psychology perspective, this study explored linkages between adolescent students' positive subjective well-being and their levels of engagement in schooling. Specifically, using structural equation modeling techniques, we evaluated the nature and directionality of longitudinal relationships between life satisfaction and student engagement variables. It was hypothesized that adolescents' life satisfaction and student engagement variables would show bidirectional relationships. To test this hypothesis, 779 students (53% female, 62% Caucasian) in a Southeastern US middle school completed a measure of global life satisfaction and measures of cognitive, emotional, and behavioral engagement at two time points, 5 months apart. A statistically significant bidirectional relationship between life satisfaction and cognitive engagement was found; however, non-significant relationships were found between life satisfaction and emotional and behavioral student engagement. The findings provide important evidence of the role of early adolescents' life satisfaction in their engagement in schooling during the important transition grades between elementary and high school. The findings also help extend the positive psychology perspective to the relatively neglected context of education.

Demographic, Maltreatment, and Neurobiological Correlates of PTSD Symptoms in Children and Adolescents

PubMed Central

Hooper, Stephen R.; Woolley, Donald P.; Shenk, Chad E.

2010-01-01

Objective To examine the relationships of demographic, maltreatment, neurostructural and neuropsychological measures with total posttraumatic stress disorder (PTSD) symptoms. Methods Participants included 216 children with maltreatment histories (N = 49), maltreatment and PTSD (N = 49), or no maltreatment (N = 118). Participants received diagnostic interviews, brain imaging, and neuropsychological evaluations. Results We examined a hierarchical regression model comprised of independent variables including demographics, trauma and maltreatment-related variables, and hippocampal volumes and neuropsychological measures to model PTSD symptoms. Important independent contributors to this model were SES, and General Maltreatment and Sexual Abuse Factors. Although hippocampal volumes were not significant, Visual Memory was a significant contributor to this model. Conclusions Similar to adult PTSD, pediatric PTSD symptoms are associated with lower Visual Memory performance. It is an important correlate of PTSD beyond established predictors of PTSD symptoms. These results support models of developmental traumatology and suggest that treatments which enhance visual memory may decrease symptoms of PTSD. PMID:20008084

Auxiliary variables for numerically solving nonlinear equations with softly broken symmetries.

PubMed

Olum, Ken D; Masoumi, Ali

2017-06-01

General methods for solving simultaneous nonlinear equations work by generating a sequence of approximate solutions that successively improve a measure of the total error. However, if the total error function has a narrow curved valley, the available techniques tend to find the solution after a very large number of steps, if ever. The solver first converges rapidly to the valley, but once there it converges extremely slowly to the solution. In this paper we show that in the specific physically important case where these valleys are the result of a softly broken symmetry, the solution can often be found much more quickly by adding the generators of the softly broken symmetry as auxiliary variables. This makes the number of variables more than the equations and hence there will be a family of solutions, any one of which would be acceptable. We present a procedure for finding solutions in this case and apply it to several simple examples and an important problem in the physics of false vacuum decay. We also provide a Mathematica package that implements Powell's hybrid method with the generalization to allow more variables than equations.

Psychosocial variables of sexual satisfaction in Chile.

PubMed

Barrientos, Jaime E; Páez, Dario

2006-01-01

This study analyzed psychosocial variables of sexual satisfaction in Chile using data from the COSECON survey. Participants were 5,407 subjects (2,244 min and 3,163 women, aged 18-69 years). We used a cross-sectional questionnaire with a national probability sample. Data were collected using a thorough sexual behavior questionnaire consisting of 190 face-to-face questions and 24 self-reported questions. A single item included in the COSECON questionnaire assessed sexual satisfaction. Results showed that high education level, marital status, and high socioeconomic levels were associated with sexual satisfaction in women but not in men. The results also showed important gender differences and sustain the idea that sexuality changes may be more present in middle and high social classes. The proximal variables typically used for measuring sexual satisfaction, such as the frequency of sexual intercourse and orgasm, showed a positive but smaller association with sexual satisfaction. Other important variables related to sexual satisfaction were being in love with the partner and having a steady partner. The results confirmed previous findings and are discussed in the frame of approaches like the exchange, equity, and sexual scripts theories.

Information content of MOPITT CO profile retrievals: Temporal and geographical variability

NASA Astrophysics Data System (ADS)

Deeter, M. N.; Edwards, D. P.; Gille, J. C.; Worden, H. M.

2015-12-01

Satellite measurements of tropospheric carbon monoxide (CO) enable a wide array of applications including studies of air quality and pollution transport. The MOPITT (Measurements of Pollution in the Troposphere) instrument on the Earth Observing System Terra platform has been measuring CO concentrations globally since March 2000. As indicated by the Degrees of Freedom for Signal (DFS), the standard metric for trace-gas retrieval information content, MOPITT retrieval performance varies over a wide range. We show that both instrumental and geophysical effects yield significant geographical and temporal variability in MOPITT DFS values. Instrumental radiance uncertainties, which describe random errors (or "noise") in the calibrated radiances, vary over long time scales (e.g., months to years) and vary between the four detector elements of MOPITT's linear detector array. MOPITT retrieval performance depends on several factors including thermal contrast, fine-scale variability of surface properties, and CO loading. The relative importance of these various effects is highly variable, as demonstrated by analyses of monthly mean DFS values for the United States and the Amazon Basin. An understanding of the geographical and temporal variability of MOPITT retrieval performance is potentially valuable to data users seeking to limit the influence of the a priori through data filtering. To illustrate, it is demonstrated that calculated regional-average CO mixing ratios may be improved by excluding observations from a subset of pixels in MOPITT's linear detector array.

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.

Risk perception measures' associations with behavior intentions, affect, and cognition following colon cancer screening messages.

PubMed

Dillard, Amanda J; Ferrer, Rebecca A; Ubel, Peter A; Fagerlin, Angela

2012-01-01

Risk perception is important for motivating health behavior (e.g., Janz & Becker, 1984), but different measures of the construct may change how important that relationship appears. In two studies, we examined associations between four measures of risk perception, health behavior intentions and possible behavioral determinants. Participants in these studies, who were due for colorectal cancer screening, read an online message about the importance of screening to reduce the chance of cancer. We examined bivariate and multivariate associations between risk perception measures, including absolute, comparative, and feelings-of-risk, and behavioral intentions to screen, general worry, and knowledge and attitudes related to screening. Results across the two studies were consistent, with all risk perception measures being correlated with intentions and attitudes. Multivariate analyses revealed that feelings-of-risk was most predictive of all variables, with the exception of general worry, for which comparative measures were the most predictive. Researchers interested in risk perception should assess feelings-of-risk along with more traditional measures. Those interested in influencing health behavior specifically should attempt to increase feelings of vulnerability rather than numerical risk.

Intra-individual variability in day-to-day and month-to-month measurements of physical activity and sedentary behaviour at work and in leisure-time among Danish adults.

PubMed

Pedersen, E S L; Danquah, I H; Petersen, C B; Tolstrup, J S

2016-12-03

Accelerometers can obtain precise measurements of movements during the day. However, the individual activity pattern varies from day-to-day and there is limited evidence on measurement days needed to obtain sufficient reliability. The aim of this study was to examine variability in accelerometer derived data on sedentary behaviour and physical activity at work and in leisure-time during week days among Danish office employees. We included control participants (n = 135) from the Take a Stand! Intervention; a cluster randomized controlled trial conducted in 19 offices. Sitting time and physical activity were measured using an ActiGraph GT3X+ fixed on the thigh and data were processed using Acti4 software. Variability was examined for sitting time, standing time, steps and time spent in moderate-to-vigorous physical activity (MVPA) per day by multilevel mixed linear regression modelling. Results of this study showed that the number of days needed to obtain a reliability of 80% when measuring sitting time was 4.7 days for work and 5.5 days for leisure time. For physical activity at work, 4.0 days and 4.2 days were required to measure steps and MVPA, respectively. During leisure time, more monitoring time was needed to reliably estimate physical activity (6.8 days for steps and 5.8 days for MVPA). The number of measurement days needed to reliably estimate activity patterns was greater for leisure time than for work time. The domain specific variability is of great importance to researchers and health promotion workers planning to use objective measures of sedentary behaviour and physical activity. Clinical trials NCT01996176 .

A multi-scale comparison of trait linkages to environmental and spatial variables in fish communities across a large freshwater lake.

PubMed

Strecker, Angela L; Casselman, John M; Fortin, Marie-Josée; Jackson, Donald A; Ridgway, Mark S; Abrams, Peter A; Shuter, Brian J

2011-07-01

Species present in communities are affected by the prevailing environmental conditions, and the traits that these species display may be sensitive indicators of community responses to environmental change. However, interpretation of community responses may be confounded by environmental variation at different spatial scales. Using a hierarchical approach, we assessed the spatial and temporal variation of traits in coastal fish communities in Lake Huron over a 5-year time period (2001-2005) in response to biotic and abiotic environmental factors. The association of environmental and spatial variables with trophic, life-history, and thermal traits at two spatial scales (regional basin-scale, local site-scale) was quantified using multivariate statistics and variation partitioning. We defined these two scales (regional, local) on which to measure variation and then applied this measurement framework identically in all 5 study years. With this framework, we found that there was no change in the spatial scales of fish community traits over the course of the study, although there were small inter-annual shifts in the importance of regional basin- and local site-scale variables in determining community trait composition (e.g., life-history, trophic, and thermal). The overriding effects of regional-scale variables may be related to inter-annual variation in average summer temperature. Additionally, drivers of fish community traits were highly variable among study years, with some years dominated by environmental variation and others dominated by spatially structured variation. The influence of spatial factors on trait composition was dynamic, which suggests that spatial patterns in fish communities over large landscapes are transient. Air temperature and vegetation were significant variables in most years, underscoring the importance of future climate change and shoreline development as drivers of fish community structure. Overall, a trait-based hierarchical framework may be a useful conservation tool, as it highlights the multi-scaled interactive effect of variables over a large landscape.

Characteristics explaining performance in downhill mountain biking.

PubMed

Chidley, Joel B; MacGregor, Alexandra L; Martin, Caoimhe; Arthur, Calum A; Macdonald, Jamie H

2015-03-01

To identify physiological, psychological, and skill characteristics that explain performance in downhill (DH) mountain-bike racing. Four studies were used to (1) identify factors potentially contributing to DH performance (using an expert focus group), (2) develop and validate a measure of rider skill (using video analysis and expert judge evaluation), (3) evaluate whether physiological, psychological, and skill variables contribute to performance at a DH competition, and (4) test the specific contribution of aerobic capacity to DH performance. STUDY 1 identified aerobic capacity, handgrip endurance, anaerobic power, rider skill, and self-confidence as potentially important for DH. In study 2 the rider-skill measure displayed good interrater reliability. Study 3 found that rider skill and handgrip endurance were significantly related to DH ride time (β=-0.76 and -0.14, respectively; R2=.73), with exploratory analyses suggesting that DH ride time may also be influenced by self-confidence and aerobic capacity. Study 4 confirmed aerobic capacity as an important variable influencing DH performance (for a DH ride, mean oxygen uptake was 49±5 mL·kg(-1)·min(-1), and 90% of the ride was completed above the 1st ventilatory threshold). In order of importance, rider skill, handgrip endurance, self-confidence, and aerobic capacity were identified as variables influencing DH performance. Practically, this study provides a novel assessment of rider skill that could be used by coaches to monitor training and identify talent. Novel intervention targets to enhance DH performance were also identified, including self-confidence and aerobic capacity.

Prediction of Carcass Composition Using Carcass Grading Traits in Hanwoo Steers.

PubMed

Lee, Jooyoung; Won, Seunggun; Lee, Jeongkoo; Kim, Jongbok

2016-09-01

The prediction of carcass composition in Hanwoo steers is very important for value-based marketing, and the improvement of prediction accuracy and precision can be achieved through the analyses of independent variables using a prediction equation with a sufficient dataset. The present study was conducted to develop a prediction equation for Hanwoo carcass composition for which data was collected from 7,907 Hanwoo steers raised at a private farm in Gangwon Province, South Korea, and slaughtered in the period between January 2009 and September 2014. Carcass traits such as carcass weight (CWT), back fat thickness (BFT), eye-muscle area (EMA), and marbling score (MAR) were used as independent variables for the development of a prediction equation for carcass composition, such as retail cut weight and percentage (RC, and %RC, respectively), trimmed fat weight and percentage (FAT, and %FAT, respectively), and separated bone weight and percentage (BONE, and %BONE), and its feasibility for practical use was evaluated using the estimated retail yield percentage (ELP) currently used in Korea. The equations were functions of all the variables, and the significance was estimated via stepwise regression analyses. Further, the model equations were verified by means of the residual standard deviation and the coefficient of determination (R(2)) between the predicted and observed values. As the results of stepwise analyses, CWT was the most important single variable in the equation for RC and FAT, and BFT was the most important variable for the equation of %RC and %FAT. The precision and accuracy of three variable equation consisting CWT, BFT, and EMA were very similar to those of four variable equation that included all for independent variables (CWT, BFT, EMA, and MAR) in RC and FAT, while the three variable equations provided a more accurate prediction for %RC. Consequently, the three-variable equation might be more appropriate for practical use than the four-variable equation based on its easy and cost-effective measurement. However, a relatively high average difference for the ELP in absolute value implies a revision of the official equation may be required, although the current official equation for predicting RC with three variables is still valid.

Variability and Correlations in Primary Visual Cortical Neurons Driven by Fixational Eye Movements

PubMed Central

McFarland, James M.; Cumming, Bruce G.

2016-01-01

The ability to distinguish between elements of a sensory neuron's activity that are stimulus independent versus driven by the stimulus is critical for addressing many questions in systems neuroscience. This is typically accomplished by measuring neural responses to repeated presentations of identical stimuli and identifying the trial-variable components of the response as noise. In awake primates, however, small “fixational” eye movements (FEMs) introduce uncontrolled trial-to-trial differences in the visual stimulus itself, potentially confounding this distinction. Here, we describe novel analytical methods that directly quantify the stimulus-driven and stimulus-independent components of visual neuron responses in the presence of FEMs. We apply this approach, combined with precise model-based eye tracking, to recordings from primary visual cortex (V1), finding that standard approaches that ignore FEMs typically miss more than half of the stimulus-driven neural response variance, creating substantial biases in measures of response reliability. We show that these effects are likely not isolated to the particular experimental conditions used here, such as the choice of visual stimulus or spike measurement time window, and thus will be a more general problem for V1 recordings in awake primates. We also demonstrate that measurements of the stimulus-driven and stimulus-independent correlations among pairs of V1 neurons can be greatly biased by FEMs. These results thus illustrate the potentially dramatic impact of FEMs on measures of signal and noise in visual neuron activity and also demonstrate a novel approach for controlling for these eye-movement-induced effects. SIGNIFICANCE STATEMENT Distinguishing between the signal and noise in a sensory neuron's activity is typically accomplished by measuring neural responses to repeated presentations of an identical stimulus. For recordings from the visual cortex of awake animals, small “fixational” eye movements (FEMs) inevitably introduce trial-to-trial variability in the visual stimulus, potentially confounding such measures. Here, we show that FEMs often have a dramatic impact on several important measures of response variability for neurons in primary visual cortex. We also present an analytical approach for quantifying signal and noise in visual neuron activity in the presence of FEMs. These results thus highlight the importance of controlling for FEMs in studies of visual neuron function, and demonstrate novel methods for doing so. PMID:27277801

The influence of betamethasone on fetal heart rate variability, obtained by non-invasive fetal electrocardiogram recordings.

PubMed

Verdurmen, Kim M J; Warmerdam, Guy J J; Lempersz, Carlijn; Hulsenboom, Alexandra D J; Renckens, Joris; Dieleman, Jeanne P; Vullings, Rik; van Laar, Judith O E H; Oei, S Guid

2018-04-01

Betamethasone is widely used to enhance fetal lung maturation in case of threatened preterm labour. Fetal heart rate variability is one of the most important parameters to assess in fetal monitoring, since it is a reliable indicator for fetal distress. To describe the effect of betamethasone on fetal heart rate variability, by applying spectral analysis on non-invasive fetal electrocardiogram recordings. Prospective cohort study. Patients that require betamethasone, with a gestational age from 24 weeks onwards. Fetal heart rate variability parameters on day 1, 2, and 3 after betamethasone administration are compared to a reference measurement. Following 68 inclusions, 12 patients remained with complete series of measurements and sufficient data quality. During day 1, an increase in absolute fetal heart rate variability values was seen. During day 2, a decrease in these values was seen. All trends indicate to return to pre-medication values on day 3. Normalised high- and low-frequency power show little changes during the study period. The changes in fetal heart rate variability following betamethasone administration show the same pattern when calculated by spectral analysis of the fetal electrocardiogram, as when calculated by cardiotocography. Since normalised spectral values show little changes, the influence of autonomic modulation seems minor. Copyright © 2018 Elsevier B.V. All rights reserved.

Variable Stiffness Panel Structural Analyses With Material Nonlinearity and Correlation With Tests

NASA Technical Reports Server (NTRS)

Wu, K. Chauncey; Gurdal, Zafer

2006-01-01

Results from structural analyses of three tow-placed AS4/977-3 composite panels with both geometric and material nonlinearities are presented. Two of the panels have variable stiffness layups where the fiber orientation angle varies as a continuous function of location on the panel planform. One variable stiffness panel has overlapping tow bands of varying thickness, while the other has a theoretically uniform thickness. The third panel has a conventional uniform-thickness [plus or minus 45](sub 5s) layup with straight fibers, providing a baseline for comparing the performance of the variable stiffness panels. Parametric finite element analyses including nonlinear material shear are first compared with material characterization test results for two orthotropic layups. This nonlinear material model is incorporated into structural analysis models of the variable stiffness and baseline panels with applied end shortenings. Measured geometric imperfections and mechanical prestresses, generated by forcing the variable stiffness panels from their cured anticlastic shapes into their flatter test configurations, are also modeled. Results of these structural analyses are then compared to the measured panel structural response. Good correlation is observed between the analysis results and displacement test data throughout deep postbuckling up to global failure, suggesting that nonlinear material behavior is an important component of the actual panel structural response.

Variability in Cadence During Forced Cycling Predicts Motor Improvement in Individuals With Parkinson’s Disease

PubMed Central

Ridgel, Angela L.; Abdar, Hassan Mohammadi; Alberts, Jay L.; Discenzo, Fred M.; Loparo, Kenneth A.

2014-01-01

Variability in severity and progression of Parkinson’s disease symptoms makes it challenging to design therapy interventions that provide maximal benefit. Previous studies showed that forced cycling, at greater pedaling rates, results in greater improvements in motor function than voluntary cycling. The precise mechanism for differences in function following exercise is unknown. We examined the complexity of biomechanical and physiological features of forced and voluntary cycling and correlated these features to improvements in motor function as measured by the Unified Parkinson’s Disease Rating Scale (UPDRS). Heart rate, cadence, and power were analyzed using entropy signal processing techniques. Pattern variability in heart rate and power were greater in the voluntary group when compared to forced group. In contrast, variability in cadence was higher during forced cycling. UPDRS Motor III scores predicted from the pattern variability data were highly correlated to measured scores in the forced group. This study shows how time series analysis methods of biomechanical and physiological parameters of exercise can be used to predict improvements in motor function. This knowledge will be important in the development of optimal exercise-based rehabilitation programs for Parkinson’s disease. PMID:23144045

Beyond R 0: Demographic Models for Variability of Lifetime Reproductive Output

PubMed Central

Caswell, Hal

2011-01-01

The net reproductive rate measures the expected lifetime reproductive output of an individual, and plays an important role in demography, ecology, evolution, and epidemiology. Well-established methods exist to calculate it from age- or stage-classified demographic data. As an expectation, provides no information on variability; empirical measurements of lifetime reproduction universally show high levels of variability, and often positive skewness among individuals. This is often interpreted as evidence of heterogeneity, and thus of an opportunity for natural selection. However, variability provides evidence of heterogeneity only if it exceeds the level of variability to be expected in a cohort of identical individuals all experiencing the same vital rates. Such comparisons require a way to calculate the statistics of lifetime reproduction from demographic data. Here, a new approach is presented, using the theory of Markov chains with rewards, obtaining all the moments of the distribution of lifetime reproduction. The approach applies to age- or stage-classified models, to constant, periodic, or stochastic environments, and to any kind of reproductive schedule. As examples, I analyze data from six empirical studies, of a variety of animal and plant taxa (nematodes, polychaetes, humans, and several species of perennial plants). PMID:21738586

Does bisphenol A induce superfeminization in Marisa cornuarietis? Part I: intra- and inter-laboratory variability in test endpoints.

PubMed

Forbes, Valery E; Selck, Henriette; Palmqvist, Annemette; Aufderheide, John; Warbritton, Ryan; Pounds, Nadine; Thompson, Roy; van der Hoeven, Nelly; Caspers, Norbert

2007-03-01

It has been claimed that bisphenol A (BPA) induces superfeminization in the freshwater gastropod, Marisa cornuarietis. To explore the reproducibility of prior work, here we present results from a three-laboratory study, the objectives of which were to determine the mean and variability in test endpoints (i.e., adult fecundity, egg hatchability, and juvenile growth) under baseline conditions and to identify the sources of variability. A major source of variability for all of the measured endpoints was due to differences within and among individuals. With few exceptions, variability among laboratories and among replicate tanks within laboratories contributed little to the observed variability in endpoints. The results highlight the importance of obtaining basic knowledge of husbandry requirements and baseline information on life-history traits of potential test species prior to designing toxicity test protocols. Understanding of the levels and sources of endpoint variability is essential so that statistically robust and ecologically relevant tests of chemicals can be conducted.

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.

A new solar reference spectrum from 165 to 3088 nm

NASA Astrophysics Data System (ADS)

Damé, Luc; Meftah, Mustapha; Bolsée, David; Pereira, Nuno; Bekki, Slimane; Hauchecorne, Alain; Irbah, Abdenour; Cessateur, Gaël; Sluse, Dominique

2017-04-01

Since April 5, 2008 and until February 15, 2017 the SOLAR/SOLSPEC spectro-radiometer on the International Space Station performed accurate measurements of Solar Spectral Irradiance (SSI) from the far ultraviolet to the infrared (165 nm to 3088 nm). These measurements 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). In particular, a new reference solar spectrum is established covering most of the unusual solar cycle 24 from minimum in 2008 to maximum. Temporal variability in the UV (165 to 400 nm) is presented in several wavelengths bands. These results are possible thanks to revised engineering corrections, improved calibrations and new procedures to account for thermal and aging advanced corrections. Uncertainties on these measurements are evaluated and compare favorably with other instruments.

A population survey on legislative measures to restrict smoking in Ontario: 4. Variables related to knowledge of active and passive smoking health effects and to predicted behavior of smokers and nonsmokers.

PubMed

Pederson, L L; Bull, S B; Ashley, M J; Lefcoe, N M

1989-01-01

Results from the further analysis of a population survey on legislative measures to restrict smoking revealed that identification of subgroups of smokers is more reliable than identification of subgroups of nonsmokers when a variety of attitudes were the measures of interest. A similar pattern emerged when analyses were carried out on knowledge of active and passive smoking health effects and on predicted personal and general compliance. Because distinct sets of variables were found to be related to distinct outcomes, program planning for changes in knowledge and behavior might, of necessity, have to be different. Media messages might be useful for changes in knowledge, while actual experience might be more important for attitude and behavior change.

Reproducibility and reliability of the ankle-brachial index as assessed by vascular experts, family physicians and nurses.

PubMed

Holland-Letz, Tim; Endres, Heinz G; Biedermann, Stefanie; Mahn, Matthias; Kunert, Joachim; Groh, Sabine; Pittrow, David; von Bilderling, Peter; Sternitzky, Reinhardt; Diehm, Curt

2007-05-01

The reliability of ankle-brachial index (ABI) measurements performed by different observer groups in primary care has not yet been determined. The aims of the study were to provide precise estimates for all effects influencing the variability of the ABI (patients' individual variability, intra- and inter-observer variability), with particular focus on the performance of different observer groups. Using a partially balanced incomplete block design, 144 unselected individuals aged > or = 65 years underwent double ABI measurements by one vascular surgeon or vascular physician, one family physician and one nurse with training in Doppler sonography. Three groups comprising a total of 108 individuals were analyzed (only two with ABI < 0.90). Errors for two repeated measurements for all three observer groups did not differ (experts 8.5%, family physicians 7.7%, and nurses 7.5%, p = 0.39). There was no relevant bias among observer groups. Intra-observer variability expressed as standard deviation divided by the mean was 8%, and inter-observer variability was 9%. In conclusion, reproducibility of the ABI measurement was good in this cohort of elderly patients who almost all had values in the normal range. The mean error of 8-9% within or between observers is smaller than with established screening measures. Since there were no differences among observers with different training backgrounds, our study confirms the appropriateness of ABI assessment for screening peripheral arterial disease (PAD) and generalized atherosclerosis in the primary case setting. Given the importance of the early detection and management of PAD, this diagnostic tool should be used routinely as a standard for PAD screening. Additional studies will be required to confirm our observations in patients with PAD of various severities.

Analysis of Fluctuating Static Pressure Measurements in a Large High Reynolds Number Transonic Cryogenic Wind Tunnel. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Igoe, William B.

1991-01-01

Dynamic measurements of fluctuating static pressure levels were made using flush mounted high frequency response pressure transducers at eleven locations in the circuit of the National Transonic Facility (NTF) over the complete operating range of this wind tunnel. Measurements were made at test section Mach numbers from 0.2 to 1.2, at pressure from 1 to 8.6 atmospheres and at temperatures from ambient to -250 F, resulting in dynamic flow disturbance measurements at the highest Reynolds numbers available in a transonic ground test facility. Tests were also made independently at variable Mach number, variable Reynolds number, and variable drivepower, each time keeping the other two variables constant thus allowing for the first time, a distinct separation of these three important variables. A description of the NTF emphasizing its flow quality features, details on the calibration of the instrumentation, results of measurements with the test section slots covered, downstream choke, effects of liquid nitrogen injection and gaseous nitrogen venting, comparisons between air and nitrogen, isolation of the effects of Mach number, Reynolds number, and fan drive power, and identification of the sources of significant flow disturbances is included. The results indicate that primary sources of flow disturbance in the NTF may be edge-tones generated by test section sidewall re-entry flaps and the venting of nitrogen gas from the return leg of the tunnel circuit between turns 3 and 4 in the cryogenic mode of operation. The tests to isolate the effects of Mach number, Reynolds number, and drive power indicate that Mach number effects predominate. A comparison with other transonic wind tunnels shows that the NTF has low levels of test section fluctuating static pressure especially in the high subsonic Mach number range from 0.7 to 0.9.

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

PubMed

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.

Pragmatic nihilism: how a Theory of Nothing can help health psychology progress.

PubMed

Peters, Gjalt-Jorn Ygram; Crutzen, Rik

2017-06-01

Health psychology developed a plethora of theories to explain and change a wide variety of behaviours. Several attempts have been undertaken to build integrative theories, some even striving for a Theory of Everything. We argue against these efforts, arguing that instead a 'pragmatic nihilism' perspective may be more fruitful to understand and change health behaviours. The first tenet of pragmatic nihilism is that psychological variables are usefully considered as metaphors rather than referring to entities that exist in the mind. As a consequence, the second tenet emphasizes theories' definitions and guidelines for the operationalisation of those variables. The third tenet of pragmatic nihilism is that each operationalisation represents an intersection of a variety of dimensions, such as behavioural specificity and duration, and most importantly, psychological aggregation level. Any operationalisation thus represents a number of choices regarding these dimensions. Pragmatic nihilism has two implications. First, it provides a foundation that enables integrating theories in a more flexible and accurate manner than made possible by integrative theories. Second, it emphasizes the importance of operationalisations, underlining the importance of investing in the careful development of measurement instruments, thorough reporting of measurement instruments' specifics and performance, and full disclosure of the instruments themselves.

Indicator organisms in meat and poultry slaughter operations: their potential use in process control and the role of emerging technologies.

PubMed

Saini, Parmesh K; Marks, Harry M; Dreyfuss, Moshe S; Evans, Peter; Cook, L Victor; Dessai, Uday

2011-08-01

Measuring commonly occurring, nonpathogenic organisms on poultry products may be used for designing statistical process control systems that could result in reductions of pathogen levels. The extent of pathogen level reduction that could be obtained from actions resulting from monitoring these measurements over time depends upon the degree of understanding cause-effect relationships between processing variables, selected output variables, and pathogens. For such measurements to be effective for controlling or improving processing to some capability level within the statistical process control context, sufficiently frequent measurements would be needed to help identify processing deficiencies. Ultimately the correct balance of sampling and resources is determined by those characteristics of deficient processing that are important to identify. We recommend strategies that emphasize flexibility, depending upon sampling objectives. Coupling the measurement of levels of indicator organisms with practical emerging technologies and suitable on-site platforms that decrease the time between sample collections and interpreting results would enhance monitoring process control.

Spatial Variability of Soil-Water Storage in the Southern Sierra Critical Zone Observatory: Measurement and Prediction

NASA Astrophysics Data System (ADS)

Oroza, C.; Bales, R. C.; Zheng, Z.; Glaser, S. D.

2017-12-01

Predicting the spatial distribution of soil moisture in mountain environments is confounded by multiple factors, including complex topography, spatial variably of soil texture, sub-surface flow paths, and snow-soil interactions. While remote-sensing tools such as passive-microwave monitoring can measure spatial variability of soil moisture, they only capture near-surface soil layers. Large-scale sensor networks are increasingly providing soil-moisture measurements at high temporal resolution across a broader range of depths than are accessible from remote sensing. It may be possible to combine these in-situ measurements with high-resolution LIDAR topography and canopy cover to estimate the spatial distribution of soil moisture at high spatial resolution at multiple depths. We study the feasibility of this approach using six years (2009-2014) of daily volumetric water content measurements at 10-, 30-, and 60-cm depths from the Southern Sierra Critical Zone Observatory. A non-parametric, multivariate regression algorithm, Random Forest, was used to predict the spatial distribution of depth-integrated soil-water storage, based on the in-situ measurements and a combination of node attributes (topographic wetness, northness, elevation, soil texture, and location with respect to canopy cover). We observe predictable patterns of predictor accuracy and independent variable ranking during the six-year study period. Predictor accuracy is highest during the snow-cover and early recession periods but declines during the dry period. Soil texture has consistently high feature importance. Other landscape attributes exhibit seasonal trends: northness peaks during the wet-up period, and elevation and topographic-wetness index peak during the recession and dry period, respectively.

Effects of agri-environmental schemes on farmland birds: do food availability measurements improve patterns obtained from simple habitat models?

PubMed Central

Ponce, Carlos; Bravo, Carolina; Alonso, Juan Carlos

2014-01-01

Studies evaluating agri-environmental schemes (AES) usually focus on responses of single species or functional groups. Analyses are generally based on simple habitat measurements but ignore food availability and other important factors. This can limit our understanding of the ultimate causes determining the reactions of birds to AES. We investigated these issues in detail and throughout the main seasons of a bird's annual cycle (mating, postfledging and wintering) in a dry cereal farmland in a Special Protection Area for farmland birds in central Spain. First, we modeled four bird response parameters (abundance, species richness, diversity and “Species of European Conservation Concern” [SPEC]-score), using detailed food availability and vegetation structure measurements (food models). Second, we fitted new models, built using only substrate composition variables (habitat models). Whereas habitat models revealed that both, fields included and not included in the AES benefited birds, food models went a step further and included seed and arthropod biomass as important predictors, respectively, in winter and during the postfledging season. The validation process showed that food models were on average 13% better (up to 20% in some variables) in predicting bird responses. However, the cost of obtaining data for food models was five times higher than for habitat models. This novel approach highlighted the importance of food availability-related causal processes involved in bird responses to AES, which remained undetected when using conventional substrate composition assessment models. Despite their higher costs, measurements of food availability add important details to interpret the reactions of the bird community to AES interventions and thus facilitate evaluating the real efficiency of AES programs. PMID:25165523

Potential utilization for the evaluation of particulate and gaseous pollutants at an urban site near a major highway.

PubMed

Agudelo-Castañeda, Dayana M; Teixeira, Elba C; Schneider, Ismael L; Pereira, Felipe N; Oliveira, Marcos L S; Taffarel, Silvio R; Sehn, Janaína L; Ramos, Claudete G; Silva, Luis F O

2016-02-01

Works of particle number and mass concentration variability have a great importance since they may indicate better the influence of vehicle emissions in an urban region. Moreover, the importance of this work lies in the fact that there are few studies in Brazil, where the fuel used has unique characteristics. Consequently, this paper presents measurements of particle number (size range 0.3-10 μm), particle mass (PM10, PM2.5, PM1), O3 and NOx (NO, NO2), in a site near a major highway at the Metropolitan Area of Porto Alegre, south Brazil. Measurements were carried out during two years: 2012 and 2013. Particle number and mass concentrations were measured using an optical counter with a PM10 analyzer. Results showed that concentrations of N0.3-1 (0.3-1 μm) were the highest, although similar to N1-2.5 (1-2.5 μm). Daily variability of the analyzed pollutants followed the traffic pattern. Moreover, NO2, O3, and particle number were higher during the day, whereas NO, NOx, and particle matter showed higher concentrations during nighttime. Traffic influence was evidenced by the mean concentrations of weekends and weekdays, being higher for the latter. Correlation of particles and gases with meteorological variables, together with the application of PCA confirmed the influence of vehicle exhaust discharges. Copyright © 2015 Elsevier B.V. All rights reserved.

Religious Pro-Sociality? Experimental Evidence from a Sample of 766 Spaniards

PubMed Central

Brañas-Garza, Pablo; Espín, Antonio M.; Neuman, Shoshana

2014-01-01

This study explores the relationship between several personal religion-related variables and social behaviour, using three paradigmatic economic games: the dictator (DG), ultimatum (UG), and trust (TG) games. A large carefully designed sample of the urban adult population in Granada (Spain) is employed (N = 766). From participants' decisions in these games we obtain measures of altruism, bargaining behaviour and sense of fairness/equality, trust, and positive reciprocity. Three dimensions of religiosity are examined: (i) religious denomination; (ii) intensity of religiosity, measured by active participation at church services; and (iii) conversion out into a different denomination than the one raised in. The major results are: (i) individuals with “no religion” made decisions closer to rational selfish behaviour in the DG and the UG compared to those who affiliate with a “standard” religious denomination; (ii) among Catholics, intensity of religiosity is the key variable that affects social behaviour insofar as religiously-active individuals are generally more pro-social than non-active ones; and (iii) the religion raised in seems to have no effect on pro-sociality, beyond the effect of the current measures of religiosity. Importantly, behaviour in the TG is not predicted by any of the religion-related variables we analyse. While the results partially support the notion of religious pro-sociality, on the other hand, they also highlight the importance of closely examining the multidimensional nature of both religiosity and pro-social behaviour. PMID:25115938

Looking Ahead in Educational Testing and Assessment.

ERIC Educational Resources Information Center

Masters, Geoff N.

Limitations seen in traditional educational procedures are discussed, and three new directions are suggested as being important emphases for testing. A new perception of measurement in which children have positions along particular concept dimensions or "lines" is discussed in terms of traditional testing notions including variables, item banks…

Value of travel-time reliability : commuters' route-choice behavior in the Twin Cities, phase 2.

DOT National Transportation Integrated Search

2012-04-01

Travel-time variability is a noteworthy factor in network performance. It measures the temporal uncertainty : experienced by users in their movement between any two nodes in a network. The importance : of the time variance depends on the penalties in...

Adoptive Parents' Attitudes Toward Open Birth Records.

ERIC Educational Resources Information Center

Geissinger, Shirley

1984-01-01

Investigated adoptive parents' (N=42) attitudes toward the open birth record issues using a mail survey. Analysis indicated that parental fear was the most important variable. Most supported a measure allowing adult adoptees access to birth records, provided such access was agreeable to birth and adoptive parents. (JAC)

Assessing Medication Effects in the MTA Study Using Neuropsychological Outcomes

ERIC Educational Resources Information Center

Epstein, Jeffery N.; Conners, C. Keith; Hervey, Aaron S.; Tonev, Simon T.; Arnold, L. Eugene; Abikoff, Howard B.; Elliott, Glen; Greenhill, Laurence L.; Hechtman, Lily; Hoagwood, Kimberly; Hinshaw, Stephen P.; Hoza, Betsy; Jensen, Peter S.; March, John S.; Newcorn, Jeffrey H.; Pelham, William E.; Severe, Joanne B.; Swanson, James M.; Wells, Karen; Vitiello, Benedetto; Wigal, Timothy

2006-01-01

Background: While studies have increasingly investigated deficits in reaction time (RT) and RT variability in children with attention deficit/hyperactivity disorder (ADHD), few studies have examined the effects of stimulant medication on these important neuropsychological outcome measures. Methods: 316 children who participated in the Multimodal…

COSmic-ray soil moisture observing system (COSMOS) in grazing-cap fields at El Reno, Oklahoma

USDA-ARS?s Scientific Manuscript database

Soil water content (SWC), especially over large areas, is an important variable needed by hydrological, meteorological, climatological, agricultural, and environmental scientists. Point measurements of SWC are impractical to obtain over extensive areas; thus, methods that provide real-time, hectare...

Why Summary Comorbidity Measures Such As the Charlson Comorbidity Index and Elixhauser Score Work.

PubMed

Austin, Steven R; Wong, Yu-Ning; Uzzo, Robert G; Beck, J Robert; Egleston, Brian L

2015-09-01

Comorbidity adjustment is an important component of health services research and clinical prognosis. When adjusting for comorbidities in statistical models, researchers can include comorbidities individually or through the use of summary measures such as the Charlson Comorbidity Index or Elixhauser score. We examined the conditions under which individual versus summary measures are most appropriate. We provide an analytic proof of the utility of comorbidity summary measures when used in place of individual comorbidities. We compared the use of the Charlson and Elixhauser scores versus individual comorbidities in prognostic models using a SEER-Medicare data example. We examined the ability of summary comorbidity measures to adjust for confounding using simulations. We devised a mathematical proof that found that the comorbidity summary measures are appropriate prognostic or adjustment mechanisms in survival analyses. Once one knows the comorbidity score, no other information about the comorbidity variables used to create the score is generally needed. Our data example and simulations largely confirmed this finding. Summary comorbidity measures, such as the Charlson Comorbidity Index and Elixhauser scores, are commonly used for clinical prognosis and comorbidity adjustment. We have provided a theoretical justification that validates the use of such scores under many conditions. Our simulations generally confirm the utility of the summary comorbidity measures as substitutes for use of the individual comorbidity variables in health services research. One caveat is that a summary measure may only be as good as the variables used to create it.

Harmonization of blood-based indicators of iron status: making the hard work matter.

PubMed

Hoofnagle, Andrew N

2017-12-01

Blood-based indicators that are used in the assessment of iron status are assumed to be accurate. In practice, inaccuracies in these measurements exist and stem from bias and variability. For example, the analytic variability of serum ferritin measurements across laboratories is very high (>15%), which increases the rate of misclassification in clinical and epidemiologic studies. The procedures that are used in laboratory medicine to minimize bias and variability could be used effectively in clinical research studies, particularly in the evaluation of iron deficiency and its associated anemia in pregnancy and early childhood and in characterizing states of iron repletion and excess. The harmonization and standardization of traditional and novel bioindicators of iron status will allow results from clinical studies to be more meaningfully translated into clinical practice by providing a firm foundation for clinical laboratories to set appropriate cutoffs. In addition, proficiency testing monitors the performance of the methods over time. It is important that measures of iron status be evaluated, validated, and performed in a manner that is consistent with standard procedures in laboratory medicine. © 2017 American Society for Nutrition.

Variability of Kelvin wave momentum flux from high-resolution radiosonde and radio occultation data

NASA Astrophysics Data System (ADS)

Sjoberg, J. P.; Zeng, Z.; Ho, S. P.; Birner, T.; Anthes, R. A.; Johnson, R. H.

2017-12-01

Direct measurement of momentum flux from Kelvin waves in the stratosphere remains challenging. Constraining this flux from observations is an important step towards constraining the flux from models. Here we present results from analyses using linear theory to estimate the Kelvin wave amplitudes and momentum fluxes from both high-resolution radiosondes and from radio occultation (RO) data. These radiosonde data are from a contiguous 11-year span of soundings performed at two Department of Energy Atmospheric Radiation Measurement sites, while the RO data span 14 years from multiple satellite missions. Daily time series of the flux from both sources are found to be in quantitative agreement with previous studies. Climatological analyses of these data reveal the expected seasonal cycle and variability associated with the quasi-biennial oscillation. Though both data sets provide measurements on distinct spatial and temporal scales, the estimated flux from each provides insight into separate but complimentary aspects of how the Kelvin waves affect the stratosphere. Namely, flux derived from radiosonde sites provide details on the regional Kelvin wave variability, while the flux from RO data are zonal mean estimates.

Stability measures in arid ecosystems

NASA Astrophysics Data System (ADS)

Nosshi, M. I.; Brunsell, N. A.; Koerner, S.

2015-12-01

Stability, the capacity of ecosystems to persist in the face of change, has proven its relevance as a fundamental component of ecological theory. Here, we would like to explore meaningful and quantifiable metrics to define stability, with a focus on highly variable arid and semi-arid savanna ecosystems. Recognizing the importance of a characteristic timescale to any definition of stability, our metrics will be focused scales from annual to multi-annual, capturing different aspects of stability. Our three measures of stability, in increasing order of temporal scale, are: (1) Ecosystem resistance, quantified as the degree to which the system maintains its mean state in response to a perturbation (drought), based on inter-annual variability in Normalized Difference Vegetation Index (NDVI). (2) An optimization approach, relevant to arid systems with pulse dynamics, that models vegetation structure and function based on a trade off between the ability to respond to resource availability and avoid stress. (3) Community resilience, measured as species turnover rate (β diversity). Understanding the nature of stability in structurally-diverse arid ecosystems, which are highly variable, yields theoretical insight which has practical implications.

Buffer Optimization of Thermal Melt Assays of Plasmodium Proteins for Detection of Small-Molecule Ligands

PubMed Central

Crowther, Gregory J.; Napuli, Alberto J.; Thomas, Andrew P.; Chung, Diana J.; Kovzun, Kuzma V.; Leibly, David J.; Castaneda, Lisa J.; Bhandari, Janhavi; Damman, Christopher J.; Hui, Raymond; Hol, Wim G. J.; Buckner, Frederick S.; Verlinde, Christophe L. M. J.; Zhang, Zhongsheng; Fan, Erkang; Van Voorhis, Wesley C.

2010-01-01

In the last decade, thermal melt/thermal shift assays have become a common tool for identifying ligands and other factors that stabilize specific proteins. Increased stability is indicated by an increase in the protein's melting temperature (Tm). In optimizing the assays for subsequent screening of compound libraries, it is important to minimize the variability of Tm measurements so as to maximize the assay's ability to detect potential ligands. Here we present an investigation of Tm variability in recombinant proteins from Plasmodium parasites. Ligands of Plasmodium proteins are particularly interesting as potential starting points for drugs for malaria, and new drugs are urgently needed. A single standard buffer (100 mM HEPES, pH 7.5, 150 mM NaCl) permitted estimation of Tm for 58 of 61 Plasmodium proteins tested. However, with several proteins, Tm could not be measured with a consistency suitable for high-throughput screening unless alternative protein-specific buffers were employed. We conclude that buffer optimization to minimize variability in Tm measurements increases the success of thermal melt screens involving proteins for which a standard buffer is suboptimal. PMID:19470714

Implications for Nucleus Heterogeneity from the Comparison of Pre- and Post-Equinox Neutral ROSINA Observations Inbound and Outbound Beyond 3 AU

NASA Astrophysics Data System (ADS)

Luspay-Kuti, A.; Altwegg, K.; Berthelier, J. J.; Beth, A.; Dhooghe, F.; Fiethe, B.; Fuselier, S. A.; Gombosi, T. I.; Hansen, K. C.; Hässig, M.; Mall, U.; Mandt, K.; Mousis, O.; Steven, P. M.; Rubin, M.; Trattner, K. J.; Tzou, C. Y.; Wurz, P.

2017-12-01

Pre-equinox ROSINA/DFMS measurements revealed a strongly heterogeneous coma. The concentrations of major and various minor volatile species were found to depend on the latitude and longitude of the nadir point of the spacecraft. The observed time variability of coma species remained consistent for about three months up to equinox. The chemical variability could be generally interpreted in terms of temperature and seasonal effects superposed on some kind of nucleus heterogeneity. We compare here pre-equinox (inbound) ROSINA/DFMS measurements from 2014 to measurements taken after the outbound equinox in 2016, both at heliocentric distances larger than 3 AU. For a direct comparison we limit our observations to the southern, poorly illuminated hemisphere only. We report the similarities and differences in the concentrations and time variability of neutral species under similar insolation conditions (heliocentric distance, season) pre- and post-equinox, and interpret them in light of the pre-equinox observations. Such direct comparison of the neutral behavior is important to better understand the evolution of cometary outgassing.

Geomorphic determinants of species composition of alpine tundra, Glacier National Park, U.S.A.

USGS Publications Warehouse

George P. Malanson,; Bengtson, Lindsey E.; Fagre, Daniel B.

2012-01-01

Because the distribution of alpine tundra is associated with spatially limited cold climates, global warming may threaten its local extent or existence. This notion has been challenged, however, based on observations of the diversity of alpine tundra in small areas primarily due to topographic variation. The importance of diversity in temperature or moisture conditions caused by topographic variation is an open question, and we extend this to geomorphology more generally. The extent to which geomorphic variation per se, based on relatively easily assessed indicators, can account for the variation in alpine tundra community composition is analyzed versus the inclusion of broad indicators of regional climate variation. Visual assessments of topography are quantified and reduced using principal components analysis (PCA). Observations of species cover are reduced using detrended correspondence analysis (DCA). A “best subsets” regression approach using the Akaike Information Criterion for selection of variables is compared to a simple stepwise regression with DCA scores as the dependent variable and scores on significant PCA axes plus more direct measures of topography as independent variables. Models with geographic coordinates (representing regional climate gradients) excluded explain almost as much variation in community composition as models with them included, although they are important contributors to the latter. The geomorphic variables in the model are those associated with local moisture differences such as snowbeds. The potential local variability of alpine tundra can be a buffer against climate change, but change in precipitation may be as important as change in temperature.

Reliability-Productivity Curve, a Tool for Adaptation Measures Identification

NASA Astrophysics Data System (ADS)

Chávez-Jiménez, A.; Granados, A.; Garrote, L. M.

2015-12-01

Due to climate change effects, water scarcity problems would intensify in several regions. These problems are going to impact negatively in the water low-priority demands, since these will be reduced in favor of those with high-priority. An example would be the reduction of agriculture water resources in favor of the urban ones. Then, it is important the evaluation of adaptation measures for a better water resources management. An important tool to face this challenge is the economic valuation of the water demands' impact within a water resources system. In agriculture this valuation is usually performed through the water productivity evaluation. The water productivity evaluation requires detailed information regarding the different crops like the applied technology, the agricultural supplies management, the water availability, etc. This is a restriction for an evaluation at basin scale due to the difficulty of gathers this level of detailed information. Besides, only the water availability is taken into account, but not the period when the water is distributed (i.e. water resources reliability). Water resources reliability is one of the most important variables in water resources management. This research proposes a methodology to determine the agriculture water productivity, using as variables the crops information, the crops price, the water resources availability, and the water resources reliability, at a basin scale. This methodology would allow identifying general water resources adaptation measures, providing the basis for further detailed studies in critical regions.

Application of Linear Mixed-Effects Models in Human Neuroscience Research: A Comparison with Pearson Correlation in Two Auditory Electrophysiology Studies.

PubMed

Koerner, Tess K; Zhang, Yang

2017-02-27

Neurophysiological studies are often designed to examine relationships between measures from different testing conditions, time points, or analysis techniques within the same group of participants. Appropriate statistical techniques that can take into account repeated measures and multivariate predictor variables are integral and essential to successful data analysis and interpretation. This work implements and compares conventional Pearson correlations and linear mixed-effects (LME) regression models using data from two recently published auditory electrophysiology studies. For the specific research questions in both studies, the Pearson correlation test is inappropriate for determining strengths between the behavioral responses for speech-in-noise recognition and the multiple neurophysiological measures as the neural responses across listening conditions were simply treated as independent measures. In contrast, the LME models allow a systematic approach to incorporate both fixed-effect and random-effect terms to deal with the categorical grouping factor of listening conditions, between-subject baseline differences in the multiple measures, and the correlational structure among the predictor variables. Together, the comparative data demonstrate the advantages as well as the necessity to apply mixed-effects models to properly account for the built-in relationships among the multiple predictor variables, which has important implications for proper statistical modeling and interpretation of human behavior in terms of neural correlates and biomarkers.

Factors related to achievement in sophomore organic chemistry at the University of Arkansas

NASA Astrophysics Data System (ADS)

Lindsay, Harriet Arlene

The purpose of this study was to identify the significant cognitive and non-cognitive variables that related to achievement in the first semester of organic chemistry at the University of Arkansas. Cognitive variables included second semester general chemistry grade, ACT composite score, ACT English, mathematics, reading, and science reasoning subscores, and spatial ability. Non-cognitive variables included anxiety, confidence, effectance motivation, and usefulness. Using a correlation research design, the individual relationships between organic chemistry achievement and each of the cognitive variables and non-cognitive variables were assessed. In addition, the relationships between organic chemistry achievement and combinations of these independent variables were explored. Finally, gender- and instructor-related differences in the relationships between organic chemistry achievement and the independent variables were investigated. The samples consisted of volunteers from the Fall 1999 and Fall 2000 sections of Organic Chemistry I at the University of Arkansas. All students in each section were asked to participate. Data for spatial ability and non-cognitive independent variables were collected using the Purdue Visualization of Rotations test and the modified Fennema-Sherman Attitude Scales. Data for other independent variables, including ACT scores and second semester general chemistry grades, were obtained from the Office of Institutional Research. The dependent variable, organic chemistry achievement, was measured by each student's accumulated points in the course and consisted of scores on quizzes and exams in the lecture section only. These totals were obtained from the lecture instructor at the end of each semester. Pearson correlation and stepwise multiple regression analyses were used to measure the relationships between organic chemistry achievement and the independent variables. Prior performance in chemistry as measured by second semester general chemistry grade was the best indicator of performance in organic chemistry. The importance of other independent variables in explaining organic chemistry achievement varied between instructors. In addition, gender differences were found in the explanations of organic chemistry achievement variance provided by this study. In general, males exhibited stronger correlations between independent variables and organic chemistry achievement than females. The report contains 19 tables detailing the statistical analyses. Suggestions for improved practice and further research are also included

Bird diversity along a gradient of fragmented habitats of the Cerrado.

PubMed

Jesus, Shayana DE; Pedro, Wagner A; Bispo, Arthur A

2018-01-01

Understanding the factors that affect biodiversity is of central interest to ecology, and essential to species conservation and ecosystems management. We sampled bird communities in 17 forest fragments in the Cerrado biome, the Central-West region of Brazil. We aimed to know the communities structure pattern and the influence of geographical distance and environmental variables on them, along a gradient of fragmented habitats at both local and landscape scales. Eight structural variables of the fragments served as an environmental distance measurement at the local scale while five metrics served as an environmental distance measurement at the landscape scale. Species presence-absence data were used to calculate the dissimilarity index. Beta diversity was calculated using three indices (βsim, βnes and βsor), representing the spatial species turnover, nestedness and total beta diversity, respectively. Spatial species turnover was the predominant pattern in the structure of the communities. Variations in beta diversity were explained only by the environmental variables of the landscape with spatial configuration being more important than the composition. This fact indicates that, in Cerrado of Goiás avian communities structure, deterministic ecological processes associated to differences in species responses to landscape fragmentation are more important than stochastic processes driven by species dispersal.

Systematic studies of modified vocalization: effects of speech rate and instatement style during metronome stimulation.

PubMed

Davidow, Jason H; Bothe, Anne K; Richardson, Jessica D; Andreatta, Richard D

2010-12-01

This study introduces a series of systematic investigations intended to clarify the parameters of the fluency-inducing conditions (FICs) in stuttering. Participants included 11 adults, aged 20-63 years, with typical speech-production skills. A repeated measures design was used to examine the relationships between several speech production variables (vowel duration, voice onset time, fundamental frequency, intraoral pressure, pressure rise time, transglottal airflow, and phonated intervals) and speech rate and instatement style during metronome-entrained rhythmic speech. Measures of duration (vowel duration, voice onset time, and pressure rise time) differed across different metronome conditions. When speech rates were matched between the control condition and metronome condition, voice onset time was the only variable that changed. Results confirm that speech rate and instatement style can influence speech production variables during the production of fluency-inducing conditions. Future studies of normally fluent speech and of stuttered speech must control both features and should further explore the importance of voice onset time, which may be influenced by rate during metronome stimulation in a way that the other variables are not.

What variables can influence clinical reasoning?

PubMed Central

Ashoorion, Vahid; Liaghatdar, Mohammad Javad; Adibi, Peyman

2012-01-01

Background: Clinical reasoning is one of the most important competencies that a physician should achieve. Many medical schools and licensing bodies try to predict it based on some general measures such as critical thinking, personality, and emotional intelligence. This study aimed at providing a model to design the relationship between the constructs. Materials and Methods: Sixty-nine medical students participated in this study. A battery test devised that consist four parts: Clinical reasoning measures, personality NEO inventory, Bar-On EQ inventory, and California critical thinking questionnaire. All participants completed the tests. Correlation and multiple regression analysis consumed for data analysis. Results: There is low to moderate correlations between clinical reasoning and other variables. Emotional intelligence is the only variable that contributes clinical reasoning construct (r=0.17-0.34) (R2 chnage = 0.46, P Value = 0.000). Conclusion: Although, clinical reasoning can be considered as a kind of thinking, no significant correlation detected between it and other constructs. Emotional intelligence (and its subscales) is the only variable that can be used for clinical reasoning prediction. PMID:23853636

Association between prolonged breast-feeding and early childhood caries: a hierarchical approach.

PubMed

Nunes, Ana Margarida Melo; Alves, Claudia Maria Coelho; Borba de Araújo, Fernando; Ortiz, Tânia Mara Lopes; Ribeiro, Marizélia Rodrigues Costa; Silva, Antônio Augusto Moura da; Ribeiro, Cecília Claudia Costa

2012-12-01

This study was conducted to investigate the association between prolonged breastfeeding and early childhood caries(ECC) with adjustment for important confounders, using hieraschical approach. This retrospective cohort study involved 260 low-income children (18-42 months). The number of decayed teeth was used as a measure of caries. Following a theoretical framework, the hierarchical model was built in a forward fashion, by adding the following levels in succession: level 1: age; level 2: social variables; level 3: health variables; level 4: behavioral variables; level 5: oral hygiene-related variables; level 6: oral hygiene quality measured by visible plaque; and level 7: contamination by mutans streptococci. Sequential forward multiple Poisson regression analysis was employed. Breast-feeding was not a risk factor for ECC after adjustment for some confounders (incidence density ratio, 1.15; 95% confidence interval, 0.84-1.59, P = 0.363). Prolonged breast-feeding was not a risk factor for ECC while age, high sucrose comption between main meals and the quality of oral higiene were associated with disease in children. © 2012 John Wiley & Sons A/S.

The declining influence of family background on educational attainment in Australia: The role of measured and unmeasured influences.

PubMed

Marks, Gary N; Mooi-Reci, Irma

2016-01-01

The paper examines changes in the influence of family background, including socioeconomic and social background variables on educational attainment in Australia for cohorts born between 1890 and 1982. We test hypotheses from modernization theory on sibling data using random effects models and find: (i) substantial declines in the influence of family background on educational attainment (indicated by the sibling intraclass correlations); (ii) declines in the effects of both economic and cultural socioeconomic background variables; (iii) changes in the effects of some social background variables (e.g., family size); (iv) and declines in the extent that socioeconomic and social background factors account for variation in educational attainment. Unmeasured family background factors are more important, and proportionally increasingly so, for educational attainment than the measured socioeconomic and social background factors analyzed. Fixed effects models showed steeper declines in the effects of socioeconomic background variables than in standard analyses suggesting that unmeasured family factors associated with socioeconomic background obscure the full extent of the decline. Copyright © 2015 Elsevier Inc. All rights reserved.

Seasonal and interannual variability of climate and vegetation indices across the Amazon

PubMed Central

Brando, Paulo M.; Goetz, Scott J.; Baccini, Alessandro; Nepstad, Daniel C.; Beck, Pieter S. A.; Christman, Mary C.

2010-01-01

Drought exerts a strong influence on tropical forest metabolism, carbon stocks, and ultimately the flux of carbon to the atmosphere. Satellite-based studies have suggested that Amazon forests green up during droughts because of increased sunlight, whereas field studies have reported increased tree mortality during severe droughts. In an effort to reconcile these apparently conflicting findings, we conducted an analysis of climate data, field measurements, and improved satellite-based measures of forest photosynthetic activity. Wet-season precipitation and plant-available water (PAW) decreased over the Amazon Basin from 1996−2005, and photosynthetically active radiation (PAR) and air dryness (expressed as vapor pressure deficit, VPD) increased from 2002–2005. Using improved enhanced vegetation index (EVI) measurements (2000–2008), we show that gross primary productivity (expressed as EVI) declined with VPD and PAW in regions of sparse canopy cover across a wide range of environments for each year of the study. In densely forested areas, no climatic variable adequately explained the Basin-wide interannual variability of EVI. Based on a site-specific study, we show that monthly EVI was relatively insensitive to leaf area index (LAI) but correlated positively with leaf flushing and PAR measured in the field. These findings suggest that production of new leaves, even when unaccompanied by associated changes in LAI, could play an important role in Basin-wide interannual EVI variability. Because EVI variability was greatest in regions of lower PAW, we hypothesize that drought could increase EVI by synchronizing leaf flushing via its effects on leaf bud development. PMID:20679201

Measuring phenological variability from satellite imagery

USGS Publications Warehouse

Reed, Bradley C.; Brown, Jesslyn F.; Vanderzee, D.; Loveland, Thomas R.; Merchant, James W.; Ohlen, Donald O.

1994-01-01

Vegetation phenological phenomena are closely related to seasonal dynamics of the lower atmosphere and are therefore important elements in global models and vegetation monitoring. Normalized difference vegetation index (NDVI) data derived from the National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer (AVHRR) satellite sensor offer a means of efficiently and objectively evaluating phenological characteristics over large areas. Twelve metrics linked to key phenological events were computed based on time-series NDVI data collected from 1989 to 1992 over the conterminous United States. These measures include the onset of greenness, time of peak NDVI, maximum NDVI, rate of greenup, rate of senescence, and integrated NDVI. Measures of central tendency and variability of the measures were computed and analyzed for various land cover types. Results from the analysis showed strong coincidence between the satellite-derived metrics and predicted phenological characteristics. In particular, the metrics identified interannual variability of spring wheat in North Dakota, characterized the phenology of four types of grasslands, and established the phenological consistency of deciduous and coniferous forests. These results have implications for large- area land cover mapping and monitoring. The utility of re- motely sensed data as input to vegetation mapping is demonstrated by showing the distinct phenology of several land cover types. More stable information contained in ancillary data should be incorporated into the mapping process, particularly in areas with high phenological variability. In a regional or global monitoring system, an increase in variability in a region may serve as a signal to perform more detailed land cover analysis with higher resolution imagery.

Women Who Work, Part 2: Married Women in the Labour Force: The Influence of Age, Education, Child-Bearing Status and Residence. Special Labour Force Studies Series B, No. 2.

ERIC Educational Resources Information Center

Allingham, John D.; Spencer, Byron G.

To followup an earlier study of the relative importance of age, education, and marital status as variables influencing female participation in the labor force, this research attempts to measure the relative importance of similar factors in determining whether or not a woman works or wishes to work. Particular emphasis was given to such…

Climate and soil attributes determine plant species turnover in global drylands.

PubMed

Ulrich, Werner; Soliveres, Santiago; Maestre, Fernando T; Gotelli, Nicholas J; Quero, José L; Delgado-Baquerizo, Manuel; Bowker, Matthew A; Eldridge, David J; Ochoa, Victoria; Gozalo, Beatriz; Valencia, Enrique; Berdugo, Miguel; Escolar, Cristina; García-Gómez, Miguel; Escudero, Adrián; Prina, Aníbal; Alfonso, Graciela; Arredondo, Tulio; Bran, Donaldo; Cabrera, Omar; Cea, Alex; Chaieb, Mohamed; Contreras, Jorge; Derak, Mchich; Espinosa, Carlos I; Florentino, Adriana; Gaitán, Juan; Muro, Victoria García; Ghiloufi, Wahida; Gómez-González, Susana; Gutiérrez, Julio R; Hernández, Rosa M; Huber-Sannwald, Elisabeth; Jankju, Mohammad; Mau, Rebecca L; Hughes, Frederic Mendes; Miriti, Maria; Monerris, Jorge; Muchane, Muchai; Naseri, Kamal; Pucheta, Eduardo; Ramírez-Collantes, David A; Raveh, Eran; Romão, Roberto L; Torres-Díaz, Cristian; Val, James; Veiga, José Pablo; Wang, Deli; Yuan, Xia; Zaady, Eli

2014-12-01

Geographic, climatic, and soil factors are major drivers of plant beta diversity, but their importance for dryland plant communities is poorly known. This study aims to: i) characterize patterns of beta diversity in global drylands, ii) detect common environmental drivers of beta diversity, and iii) test for thresholds in environmental conditions driving potential shifts in plant species composition. 224 sites in diverse dryland plant communities from 22 geographical regions in six continents. Beta diversity was quantified with four complementary measures: the percentage of singletons (species occurring at only one site), Whittake's beta diversity (β(W)), a directional beta diversity metric based on the correlation in species occurrences among spatially contiguous sites (β(R 2 )), and a multivariate abundance-based metric (β(MV)). We used linear modelling to quantify the relationships between these metrics of beta diversity and geographic, climatic, and soil variables. Soil fertility and variability in temperature and rainfall, and to a lesser extent latitude, were the most important environmental predictors of beta diversity. Metrics related to species identity (percentage of singletons and β(W)) were most sensitive to soil fertility, whereas those metrics related to environmental gradients and abundance ((β(R 2 )) and β(MV)) were more associated with climate variability. Interactions among soil variables, climatic factors, and plant cover were not important determinants of beta diversity. Sites receiving less than 178 mm of annual rainfall differed sharply in species composition from more mesic sites (> 200 mm). Soil fertility and variability in temperature and rainfall are the most important environmental predictors of variation in plant beta diversity in global drylands. Our results suggest that those sites annually receiving ~ 178 mm of rainfall will be especially sensitive to future climate changes. These findings may help to define appropriate conservation strategies for mitigating effects of climate change on dryland vegetation.

Momentum, sensible heat and CO2 correlation coefficient variability: what can we learn from 20 years of continuous eddy covariance measurements?

NASA Astrophysics Data System (ADS)

Hurdebise, Quentin; Heinesch, Bernard; De Ligne, Anne; Vincke, Caroline; Aubinet, Marc

2017-04-01

Long-term data series of carbon dioxide and other gas exchanges between terrestrial ecosystems and atmosphere become more and more numerous. Long-term analyses of such exchanges require a good understanding of measurement conditions during the investigated period. Independently of climate drivers, measurements may indeed be influenced by measurement conditions themselves subjected to long-term variability due to vegetation growth or set-up changes. The present research refers to the Vielsalm Terrestrial Observatory (VTO) an ICOS candidate site located in a mixed forest (beech, silver fir, Douglas fir, Norway spruce) in the Belgian Ardenne. Fluxes of momentum, carbon dioxide and sensible heat have been continuously measured there by eddy covariance for more than 20 years. During this period, changes in canopy height and measurement height occurred. The correlation coefficients (for momemtum, sensible heat and CO2) and the normalized standard deviations measured for the past 20 years at the Vielsalm Terrestrial Observatory (VTO) were analysed in order to define how the fluxes, independently of climate conditions, were affected by the surrounding environment evolution, including tree growth, forest thinning and tower height change. A relationship between canopy aerodynamic distance and the momentum correlation coefficient was found which is characteristic of the roughness sublayer, and suggests that momentum transport processes were affected by z-d. In contrast, no relationship was found for sensible heat and CO2 correlation coefficients, suggesting that the z-d variability observed did not affect their turbulent transport. There were strong differences in these coefficients, however, between two wind sectors, characterized by contrasted stands (height differences, homogeneity) and different hypotheses were raised to explain it. This study highlighted the importance of taking the surrounding environment variability into account in order to ensure the spatio-temporal consistency of datasets.

Relationships between reef fish communities and remotely sensed rugosity measurements in Biscayne National Park, Florida, USA

USGS Publications Warehouse

Kuffner, Ilsa B.; Brock, John C.; Grober-Dunsmore, Rikki; Bonito, Victor E.; Hickey, T. Donald; Wright, C. Wayne

2007-01-01

The realization that coral reef ecosystem management must occur across multiple spatial scales and habitat types has led scientists and resource managers to seek variables that are easily measured over large areas and correlate well with reef resources. Here we investigate the utility of new technology in airborne laser surveying (NASA Experimental Advanced Airborne Research Lidar (EAARL)) in assessing topographical complexity (rugosity) to predict reef fish community structure on shallow (n = 10–13 per reef). Rugosity at each station was assessed in situ by divers using the traditional chain-transect method (10-m scale), and remotely using the EAARL submarine topography data at multiple spatial scales (2, 5, and 10 m). The rugosity and biological datasets were analyzed together to elucidate the predictive power of EAARL rugosity in describing the variance in reef fish community variables and to assess the correlation between chain-transect and EAARL rugosity. EAARL rugosity was not well correlated with chain-transect rugosity, or with species richness of fishes (although statistically significant, the amount of variance explained by the model was very low). Variance in reef fish community attributes was better explained in reef-by-reef variability than by physical variables. However, once the reef-by-reef variability was taken into account in a two-way analysis of variance, the importance of rugosity could be seen on individual reefs. Fish species richness and abundance were statistically higher at high rugosity stations compared to medium and low rugosity stations, as predicted by prior ecological research. The EAARL shows promise as an important mapping tool for reef resource managers as they strive to inventory and protect coral reef resources.

Prey-mediated behavioral responses of feeding blue whales in controlled sound exposure experiments.

PubMed

Friedlaender, A S; Hazen, E L; Goldbogen, J A; Stimpert, A K; Calambokidis, J; Southall, B L

2016-06-01

Behavioral response studies provide significant insights into the nature, magnitude, and consequences of changes in animal behavior in response to some external stimulus. Controlled exposure experiments (CEEs) to study behavioral response have faced challenges in quantifying the importance of and interaction among individual variability, exposure conditions, and environmental covariates. To investigate these complex parameters relative to blue whale behavior and how it may change as a function of certain sounds, we deployed multi-sensor acoustic tags and conducted CEEs using simulated mid-frequency active sonar (MFAS) and pseudo-random noise (PRN) stimuli, while collecting synoptic, quantitative prey measures. In contrast to previous approaches that lacked such prey data, our integrated approach explained substantially more variance in blue whale dive behavioral responses to mid-frequency sounds (r2 = 0.725 vs. 0.14 previously). Results demonstrate that deep-feeding whales respond more clearly and strongly to CEEs than those in other behavioral states, but this was only evident with the increased explanatory power provided by incorporating prey density and distribution as contextual covariates. Including contextual variables increases the ability to characterize behavioral variability and empirically strengthens previous findings that deep-feeding blue whales respond significantly to mid-frequency sound exposure. However, our results are only based on a single behavioral state with a limited sample size, and this analytical framework should be applied broadly across behavioral states. The increased capability to describe and account for individual response variability by including environmental variables, such as prey, that drive foraging behavior underscores the importance of integrating these and other relevant contextual parameters in experimental designs. Our results suggest the need to measure and account for the ecological dynamics of predator-prey interactions when studying the effects of anthropogenic disturbance in feeding animals.

Variable selection for marginal longitudinal generalized linear models.

PubMed

Cantoni, Eva; Flemming, Joanna Mills; Ronchetti, Elvezio

2005-06-01

Variable selection is an essential part of any statistical analysis and yet has been somewhat neglected in the context of longitudinal data analysis. In this article, we propose a generalized version of Mallows's C(p) (GC(p)) suitable for use with both parametric and nonparametric models. GC(p) provides an estimate of a measure of model's adequacy for prediction. We examine its performance with popular marginal longitudinal models (fitted using GEE) and contrast results with what is typically done in practice: variable selection based on Wald-type or score-type tests. An application to real data further demonstrates the merits of our approach while at the same time emphasizing some important robust features inherent to GC(p).

[Behavioral gender differences in school relationships].

PubMed

Postigo Zegarra, Silvia; González Barrón, Remedios; Mateu Marqués, Carmen; Ferrero Berlanga, Javier; Martorell Pallás, Carmen

2009-08-01

Adolescents take on different social roles mediated by gender, which affect the development of their identity and the expression of school violence. The purpose of this work is to study the behavioral differences in bullying depending on gender. The sample (N=641) is aged between 12 and 16 years old. Personal variables are assessed by self-reports, and relational variables by sociometric measures. Results indicate a large incidence of bullying, peer rejection, and school maladjustment among boys. Girls report more relational aggressions, acceptance and social skills, but also higher personal maladjustment. Female victims are rejected the most. Gender differences seem more relevant in relational variables, suggesting the special importance of the relational context in bullying.

Hydrologic Remote Sensing and Land Surface Data Assimilation.

PubMed

Moradkhani, Hamid

2008-05-06

Accurate, reliable and skillful forecasting of key environmental variables such as soil moisture and snow are of paramount importance due to their strong influence on many water resources applications including flood control, agricultural production and effective water resources management which collectively control the behavior of the climate system. Soil moisture is a key state variable in land surface-atmosphere interactions affecting surface energy fluxes, runoff and the radiation balance. Snow processes also have a large influence on land-atmosphere energy exchanges due to snow high albedo, low thermal conductivity and considerable spatial and temporal variability resulting in the dramatic change on surface and ground temperature. Measurement of these two variables is possible through variety of methods using ground-based and remote sensing procedures. Remote sensing, however, holds great promise for soil moisture and snow measurements which have considerable spatial and temporal variability. Merging these measurements with hydrologic model outputs in a systematic and effective way results in an improvement of land surface model prediction. Data Assimilation provides a mechanism to combine these two sources of estimation. Much success has been attained in recent years in using data from passive microwave sensors and assimilating them into the models. This paper provides an overview of the remote sensing measurement techniques for soil moisture and snow data and describes the advances in data assimilation techniques through the ensemble filtering, mainly Ensemble Kalman filter (EnKF) and Particle filter (PF), for improving the model prediction and reducing the uncertainties involved in prediction process. It is believed that PF provides a complete representation of the probability distribution of state variables of interests (according to sequential Bayes law) and could be a strong alternative to EnKF which is subject to some limitations including the linear updating rule and assumption of jointly normal distribution of errors in state variables and observation.

Developing a Scale to Measure Students' Attitudes toward Chemistry Lessons

ERIC Educational Resources Information Center

Cheung, Derek

2009-01-01

Students' attitudes toward chemistry lessons in school are important dependent variables in curriculum evaluation. Although a variety of instruments have been developed by researchers to evaluate student attitudes, they are plagued with problems such as the lack of theoretical rationale and of empirical evidence to support the construct validity…

Self-Directed Learning Research in the Community/Junior College: Description, Conclusions, and Recommendations.

ERIC Educational Resources Information Center

Long, Huey B.; Walsh, Stephen M.

1993-01-01

Offers an analysis of 11 dissertations focusing on self-directed learning (SDL) in community colleges, highlighting the importance of promoting SDL, the relationship between the level of SDL and other variables, verification and measurement of time spent on SDL projects, and effects of SDL. (DMM)

Toys That Squeak: Toy Type Impacts Quality and Quantity of Parent-Child Interactions

ERIC Educational Resources Information Center

Miller, Jennifer L.; Lossia, Amanda; Suarez-Rivera, Catalina; Gros-Louis, Julie

2017-01-01

Given the dependent nature of parent-infant interactions necessary for language development, it is important to understand how context may influence these interactions. This study examines how contextual variables influence communicative, cognitive and social measures of parent-infant interactions. Specifically, how do feedback toys and…

Thermocouples for forest fire research

Treesearch

Erwin H. Breuer

1965-01-01

Thermocouples have proved valuable in research conducted by the Fire Physics Project at the Northern Forest Fire Laboratory because they can measure several important fire variables besides flame and convection column temperatures. These include rate of spread and flame residence time. Describes a simple, rapid method of fabrication and reports useful and diverse...

Factors Important in the Formation of Preschoolers' Friendships.

ERIC Educational Resources Information Center

Drewry, Debra L.; Clark, Maxine L.

Reciprocity of friendships and variables related to popularity were studied in 47 male and 25 female preschoolers, of whom 15 percent were nonwhite. Subjects were administered the Peabody Picture Vocabulary Test, the Primary Self Concept Inventory, and a sociometric measure which yielded data on popularity and type of friendship pairings…

Valid and Reliable Science Content Assessments for Science Teachers

ERIC Educational Resources Information Center

Tretter, Thomas R.; Brown, Sherri L.; Bush, William S.; Saderholm, Jon C.; Holmes, Vicki-Lynn

2013-01-01

Science teachers' content knowledge is an important influence on student learning, highlighting an ongoing need for programs, and assessments of those programs, designed to support teacher learning of science. Valid and reliable assessments of teacher science knowledge are needed for direct measurement of this crucial variable. This paper…

Quantifying Spatial and Seasonal Variability in Atmospheric Ammonia with In Situ and Space-Based Observations

EPA Science Inventory

Ammonia plays an important role in many biogeochemical processes, yet atmospheric mixing ratios arc not well known. Recently, methods have been developed for retrieving NH₃ from space-based observations, but they have not been compared to in situ measurements. We have ...

Environmental factors affecting understory diversity in second-growth deciduous forests

Treesearch

Cynthia D. Huebner; J.C. Randolph; G.R. Parker

1995-01-01

The purpose of this study was to determine the most important nonanthropogenic factors affecting understory (herbs, shrubs and low-growing vines) diversity in forested landscapes of southern Indiana. Fourteen environmental variables were measured for 46 sites. Multiple regression analysis showed significant positive correlation between understory diversity and tree...

Interpreting Physiological Data from Riparian Vegetation: Cautions and Complications

Treesearch

John G. Williams

1989-01-01

Water potential and stomatal conductance are important indicators of the response of vegetation to manipulations of riparian systems. However, interpretation of measurements of these variables is not always straightforward. An extensive monitoring program along the Carmel River in central California, carried out by the Monterey Peninsula Water Management District,...

METHOD EVALUATION TO MEASURE PERSISTENT BIOACCUMULATIVE TOXIC POLLUTANTS IN COW MILK

EPA Science Inventory

It is important to understand the persistent and bioaccumulative toxic (PBT) levels in milk, as milk fat may be one of the highest dietary sources of PBT exposure. Analysis of milk also allows the opportunity to investigate geographic variability, as milk is produced and distrib...

Implicit Attitudes toward Violence among Male Perpetrators of Intimate Partner Violence: A Preliminary Investigation

ERIC Educational Resources Information Center

Eckhardt, Christopher I.; Samper, Rita; Suhr, Laura; Holtzworth-Munroe, Amy

2012-01-01

Whereas cognitive variables are hypothesized to play an important role in intimate partner violence (IPV) etiology and intervention, cognitive assessment methods have largely targeted offenders' explicit, controlled cognitive processing using paper-and-pencil questionnaires prone to social desirability biases. Using an implicit measure of…

Mobile phones and malaria: modeling human and parasite travel

PubMed Central

Buckee, Caroline O.; Wesolowski, Amy; Eagle, Nathan; Hansen, Elsa; Snow, Robert W.

2013-01-01

Human mobility plays an important role in the dissemination of malaria parasites between regions of variable transmission intensity. Asymptomatic individuals can unknowingly carry parasites to regions where mosquito vectors are available, for example, undermining control programs and contributing to transmission when they travel. Understanding how parasites are imported between regions in this way is therefore an important goal for elimination planning and the control of transmission, and would enable control programs to target the principal sources of malaria. Measuring human mobility has traditionally been difficult to do on a population scale, but the widespread adoption of mobile phones in low-income settings presents a unique opportunity to directly measure human movements that are relevant to the spread of malaria. Here, we discuss the opportunities for measuring human mobility using data from mobile phones, as well as some of the issues associated with combining mobility estimates with malaria infection risk maps to meaningfully estimate routes of parasite importation. PMID:23478045

Stochastic effects in EUV lithography: random, local CD variability, and printing failures

NASA Astrophysics Data System (ADS)

De Bisschop, Peter

2017-10-01

Stochastic effects in lithography are usually quantified through local CD variability metrics, such as line-width roughness or local CD uniformity (LCDU), and these quantities have been measured and studied intensively, both in EUV and optical lithography. Next to the CD-variability, stochastic effects can also give rise to local, random printing failures, such as missing contacts or microbridges in spaces. When these occur, there often is no (reliable) CD to be measured locally, and then such failures cannot be quantified with the usual CD-measuring techniques. We have developed algorithms to detect such stochastic printing failures in regular line/space (L/S) or contact- or dot-arrays from SEM images, leading to a stochastic failure metric that we call NOK (not OK), which we consider a complementary metric to the CD-variability metrics. This paper will show how both types of metrics can be used to experimentally quantify dependencies of stochastic effects to, e.g., CD, pitch, resist, exposure dose, etc. As it is also important to be able to predict upfront (in the OPC verification stage of a production-mask tape-out) whether certain structures in the layout are likely to have a high sensitivity to stochastic effects, we look into the feasibility of constructing simple predictors, for both stochastic CD-variability and printing failure, that can be calibrated for the process and exposure conditions used and integrated into the standard OPC verification flow. Finally, we briefly discuss the options to reduce stochastic variability and failure, considering the entire patterning ecosystem.

Association of Day Length and Weather Conditions with Physical Activity Levels in Older Community Dwelling People

PubMed Central

Witham, Miles D.; Donnan, Peter T.; Vadiveloo, Thenmalar; Sniehotta, Falko F.; Crombie, Iain K.; Feng, Zhiqiang; McMurdo, Marion E. T.

2014-01-01

Background Weather is a potentially important determinant of physical activity. Little work has been done examining the relationship between weather and physical activity, and potential modifiers of any relationship in older people. We therefore examined the relationship between weather and physical activity in a cohort of older community-dwelling people. Methods We analysed prospectively collected cross-sectional activity data from community-dwelling people aged 65 and over in the Physical Activity Cohort Scotland. We correlated seven day triaxial accelerometry data with daily weather data (temperature, day length, sunshine, snow, rain), and a series of potential effect modifiers were tested in mixed models: environmental variables (urban vs rural dwelling, percentage of green space), psychological variables (anxiety, depression, perceived behavioural control), social variables (number of close contacts) and health status measured using the SF-36 questionnaire. Results 547 participants, mean age 78.5 years, were included in this analysis. Higher minimum daily temperature and longer day length were associated with higher activity levels; these associations remained robust to adjustment for other significant associates of activity: age, perceived behavioural control, number of social contacts and physical function. Of the potential effect modifier variables, only urban vs rural dwelling and the SF-36 measure of social functioning enhanced the association between day length and activity; no variable modified the association between minimum temperature and activity. Conclusions In older community dwelling people, minimum temperature and day length were associated with objectively measured activity. There was little evidence for moderation of these associations through potentially modifiable health, environmental, social or psychological variables. PMID:24497925

Association of day length and weather conditions with physical activity levels in older community dwelling people.

PubMed

Witham, Miles D; Donnan, Peter T; Vadiveloo, Thenmalar; Sniehotta, Falko F; Crombie, Iain K; Feng, Zhiqiang; McMurdo, Marion E T

2014-01-01

Weather is a potentially important determinant of physical activity. Little work has been done examining the relationship between weather and physical activity, and potential modifiers of any relationship in older people. We therefore examined the relationship between weather and physical activity in a cohort of older community-dwelling people. We analysed prospectively collected cross-sectional activity data from community-dwelling people aged 65 and over in the Physical Activity Cohort Scotland. We correlated seven day triaxial accelerometry data with daily weather data (temperature, day length, sunshine, snow, rain), and a series of potential effect modifiers were tested in mixed models: environmental variables (urban vs rural dwelling, percentage of green space), psychological variables (anxiety, depression, perceived behavioural control), social variables (number of close contacts) and health status measured using the SF-36 questionnaire. 547 participants, mean age 78.5 years, were included in this analysis. Higher minimum daily temperature and longer day length were associated with higher activity levels; these associations remained robust to adjustment for other significant associates of activity: age, perceived behavioural control, number of social contacts and physical function. Of the potential effect modifier variables, only urban vs rural dwelling and the SF-36 measure of social functioning enhanced the association between day length and activity; no variable modified the association between minimum temperature and activity. In older community dwelling people, minimum temperature and day length were associated with objectively measured activity. There was little evidence for moderation of these associations through potentially modifiable health, environmental, social or psychological variables.

Non-destructive technique for determining the viability of soybean (Glycine max) seeds using FT-NIR spectroscopy.

PubMed

Kusumaningrum, Dewi; Lee, Hoonsoo; Lohumi, Santosh; Mo, Changyeun; Kim, Moon S; Cho, Byoung-Kwan

2018-03-01

The viability of seeds is important for determining their quality. A high-quality seed is one that has a high capability of germination that is necessary to ensure high productivity. Hence, developing technology for the detection of seed viability is a high priority in agriculture. Fourier transform near-infrared (FT-NIR) spectroscopy is one of the most popular devices among other vibrational spectroscopies. This study aims to use FT-NIR spectroscopy to determine the viability of soybean seeds. Viable and artificial ageing seeds as non-viable soybeans were used in this research. The FT-NIR spectra of soybean seeds were collected and analysed using a partial least-squares discriminant analysis (PLS-DA) to classify viable and non-viable soybean seeds. Moreover, the variable importance in projection (VIP) method for variable selection combined with the PLS-DA was employed. The most effective wavelengths were selected by the VIP method, which selected 146 optimal variables from the full set of 1557 variables. The results demonstrated that the FT-NIR spectral analysis with the PLS-DA method that uses all variables or the selected variables showed good performance based on the high value of prediction accuracy for soybean viability with an accuracy close to 100%. Hence, FT-NIR techniques with a chemometric analysis have the potential for rapidly measuring soybean seed viability. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

The variability of the Atlantic meridional circulation since 1980, as hindcast by a data-driven nonlinear systems model

NASA Astrophysics Data System (ADS)

Ayala-Solares, J. R.; Wei, Hua-Liang; Bigg, G. R.

2018-06-01

The Atlantic meridional overturning circulation (AMOC), an important component of the climate system, has only been directly measured since the RAPID array's installation across the Atlantic at 26°N in 2004. This has shown that the AMOC strength is highly variable on monthly timescales; however, after an abrupt, short-lived, halving of the strength of the AMOC early in 2010, its mean has remained 15% below its pre-2010 level. To attempt to understand the reasons for this variability, we use a control systems identification approach to model the AMOC, with the RAPID data of 2004-2017 providing a trial and test data set. After testing to find the environmental variables, and systems model, that allow us to best match the RAPID observations, we reconstruct AMOC variation back to 1980. Our reconstruction suggests that there is inter-decadal variability in the strength of the AMOC, with periods of both weaker flow than recently, and flow strengths similar to the late 2000s, since 1980. Recent signs of weakening may therefore not reflect the beginning of a sustained decline. It is also shown that there may be predictive power for AMOC variability of around 6 months, as ocean density contrasts between the source and sink regions for the North Atlantic Drift, with lags up to 6 months, are found to be important components of the systems model.

Distribution of Reynolds stress carried by mesoscale variability in the Antarctic Circumpolar Current

NASA Technical Reports Server (NTRS)

Johnson, Thomas J.; Stewart, Robert H.; Shum, C. K.; Tapley, Byron D.

1992-01-01

Satellite altimeter data collected by the Geosat Exact Repeat Mission were used to investigate turbulent stress resulting from the variability of surface geostrophic currents in the Antarctic Circumpolar Current. The altimeter measured sea level along the subsatellite track. The variability of the along-track slope of sea level is directly proportional to the variability of surface geostrophic currents in the cross-track direction. Because the grid of crossover points is dense at high latitudes, the satellite data could be used for mapping the temporal and spatial variability of the current. Two and a half years of data were used to compute the statistical structure of the variability. The statistics included the probability distribution functions for each component of the current, the time-lagged autocorrelation functions of the variability, and the Reynolds stress produced by the variability. The results demonstrate that stress is correlated with bathymetry. In some areas the distribution of negative stress indicate that eddies contribute to an acceleration of the mean flow, strengthening the hypothesis that baroclinic instability makes important contributions to strong oceanic currents.

Testing a model of physical activity among mothers and fathers of young children: integrating self-determined motivation, planning, and the theory of planned behavior.

PubMed

Hamilton, Kyra; Cox, Stephen; White, Katherine M

2012-02-01

Parents are at risk for inactivity; however, research into understanding parental physical activity (PA) is scarce. We integrated self-determined motivation, planning, and the theory of planned behavior (TPB) to better understand parental PA. Parents (252 mothers, 206 fathers) completed a main questionnaire assessing measures underpinning these constructs and a 1-week follow-up of PA behavior to examine whether self-determined motivation indirectly influenced intention via the TPB variables (i.e., attitude, subjective norm, and perceived behavioral control) and intention indirectly influenced behavior via planning. We found self-determined motivation on intention was fully mediated by the TPB variables and intention on behavior was partially mediated by the planning variables. In addition, slight differences in the model's paths between the sexes were revealed. The results illustrate the range of important determinants of parental PA and provide support for the integrated model in explaining PA decision making as well as the importance of examining sex differences.

A hybrid machine learning model to estimate nitrate contamination of production zone groundwater in the Central Valley, California

NASA Astrophysics Data System (ADS)

Ransom, K.; Nolan, B. T.; Faunt, C. C.; Bell, A.; Gronberg, J.; Traum, J.; Wheeler, D. C.; Rosecrans, C.; Belitz, K.; Eberts, S.; Harter, T.

2016-12-01

A hybrid, non-linear, machine learning statistical model was developed within a statistical learning framework to predict nitrate contamination of groundwater to depths of approximately 500 m below ground surface in the Central Valley, California. A database of 213 predictor variables representing well characteristics, historical and current field and county scale nitrogen mass balance, historical and current landuse, oxidation/reduction conditions, groundwater flow, climate, soil characteristics, depth to groundwater, and groundwater age were assigned to over 6,000 private supply and public supply wells measured previously for nitrate and located throughout the study area. The machine learning method, gradient boosting machine (GBM) was used to screen predictor variables and rank them in order of importance in relation to the groundwater nitrate measurements. The top five most important predictor variables included oxidation/reduction characteristics, historical field scale nitrogen mass balance, climate, and depth to 60 year old water. Twenty-two variables were selected for the final model and final model errors for log-transformed hold-out data were R squared of 0.45 and root mean square error (RMSE) of 1.124. Modeled mean groundwater age was tested separately for error improvement in the model and when included decreased model RMSE by 0.5% compared to the same model without age and by 0.20% compared to the model with all 213 variables. 1D and 2D partial plots were examined to determine how variables behave individually and interact in the model. Some variables behaved as expected: log nitrate decreased with increasing probability of anoxic conditions and depth to 60 year old water, generally decreased with increasing natural landuse surrounding wells and increasing mean groundwater age, generally increased with increased minimum depth to high water table and with increased base flow index value. Other variables exhibited much more erratic or noisy behavior in the model making them more difficult to interpret but highlighting the usefulness of the non-linear machine learning method. 2D interaction plots show probability of anoxic groundwater conditions largely control estimated nitrate concentrations compared to the other predictors.

Optimal auxiliary-covariate-based two-phase sampling design for semiparametric efficient estimation of a mean or mean difference, with application to clinical trials.

PubMed

Gilbert, Peter B; Yu, Xuesong; Rotnitzky, Andrea

2014-03-15

To address the objective in a clinical trial to estimate the mean or mean difference of an expensive endpoint Y, one approach employs a two-phase sampling design, wherein inexpensive auxiliary variables W predictive of Y are measured in everyone, Y is measured in a random sample, and the semiparametric efficient estimator is applied. This approach is made efficient by specifying the phase two selection probabilities as optimal functions of the auxiliary variables and measurement costs. While this approach is familiar to survey samplers, it apparently has seldom been used in clinical trials, and several novel results practicable for clinical trials are developed. We perform simulations to identify settings where the optimal approach significantly improves efficiency compared to approaches in current practice. We provide proofs and R code. The optimality results are developed to design an HIV vaccine trial, with objective to compare the mean 'importance-weighted' breadth (Y) of the T-cell response between randomized vaccine groups. The trial collects an auxiliary response (W) highly predictive of Y and measures Y in the optimal subset. We show that the optimal design-estimation approach can confer anywhere between absent and large efficiency gain (up to 24 % in the examples) compared to the approach with the same efficient estimator but simple random sampling, where greater variability in the cost-standardized conditional variance of Y given W yields greater efficiency gains. Accurate estimation of E[Y | W] is important for realizing the efficiency gain, which is aided by an ample phase two sample and by using a robust fitting method. Copyright © 2013 John Wiley & Sons, Ltd.

Optimal Auxiliary-Covariate Based Two-Phase Sampling Design for Semiparametric Efficient Estimation of a Mean or Mean Difference, with Application to Clinical Trials

PubMed Central

Gilbert, Peter B.; Yu, Xuesong; Rotnitzky, Andrea

2014-01-01

To address the objective in a clinical trial to estimate the mean or mean difference of an expensive endpoint Y, one approach employs a two-phase sampling design, wherein inexpensive auxiliary variables W predictive of Y are measured in everyone, Y is measured in a random sample, and the semi-parametric efficient estimator is applied. This approach is made efficient by specifying the phase-two selection probabilities as optimal functions of the auxiliary variables and measurement costs. While this approach is familiar to survey samplers, it apparently has seldom been used in clinical trials, and several novel results practicable for clinical trials are developed. Simulations are performed to identify settings where the optimal approach significantly improves efficiency compared to approaches in current practice. Proofs and R code are provided. The optimality results are developed to design an HIV vaccine trial, with objective to compare the mean “importance-weighted” breadth (Y) of the T cell response between randomized vaccine groups. The trial collects an auxiliary response (W) highly predictive of Y, and measures Y in the optimal subset. We show that the optimal design-estimation approach can confer anywhere between absent and large efficiency gain (up to 24% in the examples) compared to the approach with the same efficient estimator but simple random sampling, where greater variability in the cost-standardized conditional variance of Y given W yields greater efficiency gains. Accurate estimation of E[Y∣W] is important for realizing the efficiency gain, which is aided by an ample phase-two sample and by using a robust fitting method. PMID:24123289

Water and growth: An econometric analysis of climate and policy impacts

NASA Astrophysics Data System (ADS)

Khan, Hassaan Furqan; Morzuch, Bernard J.; Brown, Casey M.

2017-06-01

Water-related hazards such as floods, droughts, and disease cause damage to an economy through the destruction of physical capital including property and infrastructure, the loss of human capital, and the interruption of economic activities, like trade and education. The question for policy makers is whether the impacts of water-related risk accrue to manifest as a drag on economic growth at a scale suggesting policy intervention. In this study, the average drag on economic growth from water-related hazards faced by society at a global level is estimated. We use panel regressions with various specifications to investigate the relationship between economic growth and hydroclimatic variables at the country-river basin level. In doing so, we make use of surface water runoff variables never used before. The analysis of the climate variables shows that water availability and water hazards have significant effects on economic growth, providing further evidence beyond earlier studies finding that precipitation extremes were at least as important or likely more important than temperature effects. We then incorporate a broad set of variables representing the areas of infrastructure, institutions, and information to identify the characteristics of a region that determine its vulnerability to water-related risks. The results identify water scarcity, governance, and agricultural intensity as the most relevant measures affecting vulnerabilities to climate variability effects.

Measuring surface flow velocity with smartphones: potential for citizen observatories

NASA Astrophysics Data System (ADS)

Weijs, Steven V.; Chen, Zichong; Brauchli, Tristan; Huwald, Hendrik

2014-05-01

Stream flow velocity is an important variable for discharge estimation and research on sediment dynamics. Given the influence of the latter on rating curves (stage-discharge relations), and the relative scarcity of direct streamflow measurements, surface velocity measurements can offer important information for, e.g., flood warning, hydropower, and hydrological science and engineering in general. With the growing amount of sensing and computing power in the hands of more outdoorsy individuals, and the advances in image processing techniques, there is now a tremendous potential to obtain hydrologically relevant data from motivated citizens. This is the main focus of the interdisciplinary "WeSenseIt" project, a citizen observatory of water. In this subproject, we investigate the feasibility of stream flow surface velocity measurements from movie clips taken by (smartphone-) cameras. First results from movie-clip derived velocity information will be shown and compared to reference measurements.

Monitoring ecosystem quality and function in arid settings of the Mojave Desert

USGS Publications Warehouse

Belnap, Jayne; Webb, Robert H.; Miller, Mark E.; Miller, David M.; DeFalco, Lesley A.; Medica, Philip A.; Brooks, Matthew L.; Esque, Todd C.; Bedford, Dave

2008-01-01

Monitoring ecosystem quality and function in the Mojave Desert is both a requirement of state and Federal government agencies and a means for determining potential long-term changes induced by climatic fluctuations and land use. Because it is not feasible to measure every attribute and process in the desert ecosystem, the choice of what to measure and where to measure it is the most important starting point of any monitoring program. In the Mojave Desert, ecosystem function is strongly influenced by both abiotic and biotic factors, and an understanding of the temporal and spatial variability induced by climate and landform development is needed to determine where site-specific measurements should be made. We review a wide variety of techniques for sampling, assessing, and measuring climatic variables, desert soils, biological soil crusts, annual and perennial vegetation, reptiles, and small mammals. The complete array of ecosystem attributes and processes that we describe are unlikely to be measured or monitored at any given location, but the array of possibilities allows for the development of specific monitoring protocols, which can be tailored to suit the needs of land-management agencies.

Stochastic Time Models of Syllable Structure

PubMed Central

Shaw, Jason A.; Gafos, Adamantios I.

2015-01-01

Drawing on phonology research within the generative linguistics tradition, stochastic methods, and notions from complex systems, we develop a modelling paradigm linking phonological structure, expressed in terms of syllables, to speech movement data acquired with 3D electromagnetic articulography and X-ray microbeam methods. The essential variable in the models is syllable structure. When mapped to discrete coordination topologies, syllabic organization imposes systematic patterns of variability on the temporal dynamics of speech articulation. We simulated these dynamics under different syllabic parses and evaluated simulations against experimental data from Arabic and English, two languages claimed to parse similar strings of segments into different syllabic structures. Model simulations replicated several key experimental results, including the fallibility of past phonetic heuristics for syllable structure, and exposed the range of conditions under which such heuristics remain valid. More importantly, the modelling approach consistently diagnosed syllable structure proving resilient to multiple sources of variability in experimental data including measurement variability, speaker variability, and contextual variability. Prospects for extensions of our modelling paradigm to acoustic data are also discussed. PMID:25996153

Continuous Measurement of Methane Ebullition Flux from a Northern Peatland using a Fast Methane Analyzer

NASA Astrophysics Data System (ADS)

Zhongjie, Y.; Schafer, K. V.; Slater, L. D.; Varner, R. K.; Amante, J.; Comas, X.; Reeve, A. S.; Alcivar, W.; Gonzalez, D.

2012-12-01

Northern peatlands are an important source of methane (CH4) release to the atmosphere, estimated at between 20 and 50 Tg/yr. Recent work on CH4 emissions from peatlands has demonstrated that ebullition can be a more important emission pathway than previously assumed. However, accurate quantification of the atmospheric CH4 burden due to ebullition is still very limited because ebullition exhibits high spatiotemporal variability such that sudden episodic events are difficult to capture and quantify with existing experimental methods. We have initiated a novel measurement program to better quantify the spatiotemporal variability in CH4 flux in peatlands, and to examine potential effects of vegetation and environmental factors, e.g. atmospheric pressure, water table, etc on these releases. A flow-through system was designed, consisting of a closed static chamber and a fast methane analyzer (FMA) (LI-COR model 7700) that has been employed at both the field and laboratory scale. The CH4 concentration in the air flowing through the chamber is continuously measured by the analyzer and used to reconstruct continuous CH4 emission fluxes. The high sampling rate of the FMA makes it sensitive to both ebullition and diffusion of gaseous CH4, capturing short duration, episodic ebullition fluxes. Non-steady static chamber measurements were also conducted to cross-validate the continuous measurements. Results acquired during summer 2011 show that episodic ebullition occurred more frequently at the pool site where previous studies indicate extensive wood layers at depth and the vegetation was a mix of Sphagnum and wooded heath. During a 3 day period of continuous measurements captured the passage of a tropical storm Irene, where short term episodic releases of CH4, ranging from 113 mg CH4/m2/d to 202 mg CH4/m2/d, were observed at the time of lowest atmospheric pressure, providing new evidence that atmospheric pressure is an important factor to controlling CH4 ebullition from peatlands. While traditional techniques, e.g. static chamber measurement can only occasionally detect the occurrence of ebullition, the continuous measurement by using a flow-through system is able to resolve spatiotemporal complexity of episodic CH4 ebullition events. These continuous CH4 measurements provide new insights into the timing of CH4 ebullition from peatlands to the atmosphere as climate changes and the role of environmental variables in regulating these CH4 releases.

The contribution of individual psychological resilience in determining the professional quality of life of Australian nurses

PubMed Central

Hegney, Desley G.; Rees, Clare S.; Eley, Robert; Osseiran-Moisson, Rebecca; Francis, Karen

2015-01-01

Research Topic: The aim of this study was to determine the relative contribution of trait negative affect and individual psychological resilience in explaining the professional quality of life of nurses. Materials and Methods: One thousand, seven hundred and forty-three Australian nurses from the public, private, and aged care sectors completed an online Qualtrics survey. The survey collected demographic data as well as measures of depression, anxiety and stress, trait negative affect, resilience, and professional quality of life. Results: Significant positive relationships were observed between anxiety, depression and stress, trait negative affectivity, burnout, and secondary traumatic stress (compassion fatigue). Significant negative relationships were observed between each of the aforementioned variables and resilience and compassion satisfaction (CS). Results of mediated regression analysis indicated that resilience partially mediates the relationship between trait negative affect and CS. Conclusion: Results confirm the importance of both trait negative affect and resilience in explaining positive aspects of professional quality of life. Importantly, resilience was confirmed as a key variable impacting levels of CS and thus a potentially important variable to target in interventions aimed at improving nurse’s professional quality of life. PMID:26539150

Decadal changes of reference crop evapotranspiration attribution: Spatial and temporal variability over China 1960-2011

NASA Astrophysics Data System (ADS)

Fan, Ze-Xin; Thomas, Axel

2018-05-01

Atmospheric evaporative demand can be used as a measure of the hydrological cycle and the global energy balance. Its long-term variation and the role of driving climatic factors have received increasingly attention in climate change studies. FAO-Penman-Monteith reference crop evapotranspiration rates were estimated for 644 meteorological stations over China for the period 1960-2011 to analyze spatial and temporal attribution variability. Attribution of climatic variables to reference crop evapotranspiration rates was not stable over the study period. While for all of China the contribution of sunshine duration remained relatively stable, the importance of relative humidity increased considerably during the last two decades, particularly in winter. Spatially distributed attribution analysis shows that the position of the center of maximum contribution of sunshine duration has shifted from Southeast to Northeast China while in West China the contribution of wind speed has decreased dramatically. In contrast relative humidity has become an important factor in most parts of China. Changes in the Asian Monsoon circulation may be responsible for altered patterns of cloudiness and a general decrease of wind speeds over China. The continuously low importance of temperature confirms that global warming does not necessarily lead to rising atmospheric evaporative demand.

Identification of ecological thresholds from variations in phytoplankton communities among lakes: contribution to the definition of environmental standards.

PubMed

Roubeix, Vincent; Danis, Pierre-Alain; Feret, Thibaut; Baudoin, Jean-Marc

2016-04-01

In aquatic ecosystems, the identification of ecological thresholds may be useful for managers as it can help to diagnose ecosystem health and to identify key levers to enable the success of preservation and restoration measures. A recent statistical method, gradient forest, based on random forests, was used to detect thresholds of phytoplankton community change in lakes along different environmental gradients. It performs exploratory analyses of multivariate biological and environmental data to estimate the location and importance of community thresholds along gradients. The method was applied to a data set of 224 French lakes which were characterized by 29 environmental variables and the mean abundances of 196 phytoplankton species. Results showed the high importance of geographic variables for the prediction of species abundances at the scale of the study. A second analysis was performed on a subset of lakes defined by geographic thresholds and presenting a higher biological homogeneity. Community thresholds were identified for the most important physico-chemical variables including water transparency, total phosphorus, ammonia, nitrates, and dissolved organic carbon. Gradient forest appeared as a powerful method at a first exploratory step, to detect ecological thresholds at large spatial scale. The thresholds that were identified here must be reinforced by the separate analysis of other aquatic communities and may be used then to set protective environmental standards after consideration of natural variability among lakes.

The characterization of an air pollution episode using satellite total ozone measurements

NASA Technical Reports Server (NTRS)

Fishman, Jack; Shipham, Mark C.; Vukovich, Fred M.; Cahoon, Donald R.

1987-01-01

A case study is presented which demonstrates that measurements of total ozone from a space-based platform can be used to study a widespread air pollution episode over the southeastern U.S. In particular, the synoptic-scale distribution of surface-level ozone obtained from an independent analysis of ground-based monitoring stations appears to be captured by the synoptic-scale distribution of total ozone, even though about 90 percent of the total ozone is in the stratosphere. Additional analyses of upper air meteorological data, other satellite imagery, and in situ aircraft measurements of ozone likewise support the fact that synoptic-scale variability of tropospheric ozone is primarily responsible for the observed variability in total ozone under certain conditions. The use of the type of analysis discussed in this study may provide an important technique for understanding the global budget of tropospheric ozone.

Appraisal of Weather Research and Forecasting Model Downscaling of Hydro-meteorological Variables and their Applicability for Discharge Prediction: Prognostic Approach for Ungauged Basin

NASA Astrophysics Data System (ADS)

Srivastava, P. K.; Han, D.; Rico-Ramirez, M. A.; Bray, M.; Islam, T.; Petropoulos, G.; Gupta, M.

2015-12-01

Hydro-meteorological variables such as Precipitation and Reference Evapotranspiration (ETo) are the most important variables for discharge prediction. However, it is not always possible to get access to them from ground based measurements, particularly in ungauged catchments. The mesoscale model WRF (Weather Research & Forecasting model) can be used for prediction of hydro-meteorological variables. However, hydro-meteorologists would like to know how well the downscaled global data products are as compared to ground based measurements and whether it is possible to use the downscaled data for ungauged catchments. Even with gauged catchments, most of the stations have only rain and flow gauges installed. Measurements of other weather hydro-meteorological variables such as solar radiation, wind speed, air temperature, and dew point are usually missing and thus complicate the problems. In this study, for downscaling the global datasets, the WRF model is setup over the Brue catchment with three nested domains (D1, D2 and D3) of horizontal grid spacing of 81 km, 27 km and 9 km are used. The hydro-meteorological variables are downscaled using the WRF model from the National Centers for Enviromental Prediction (NCEP) reanalysis datasets and subsequently used for the ETo estimation using the Penman Monteith equation. The analysis of weather variables and precipitation are compared against the ground based datasets, which indicate that the datasets are in agreement with the observed datasets for complete monitoring period as well as during the seasons except precipitation whose performance is poorer in comparison to the measured rainfall. After a comparison, the WRF estimated precipitation and ETo are then used as a input parameter in the Probability Distributed Model (PDM) for discharge prediction. The input data and model parameter sensitivity analysis and uncertainty estimation are also taken into account for the PDM calibration and prediction following the Generalised Likelihood Uncertainty Estimation (GLUE) approach. The overall analysis suggests that the uncertainty estimates in predicted discharge using WRF downscaled ETo have comparable performance to ground based observed datasets and hence is promising for discharge prediction in the absence of ground based measurements.

Community Capacity for Watershed Conservation: A Quantitative Assessment of Indicators and Core Dimensions

NASA Astrophysics Data System (ADS)

Brinkman, Elliot; Seekamp, Erin; Davenport, Mae A.; Brehm, Joan M.

2012-10-01

Community capacity for watershed management has emerged as an important topic for the conservation of water resources. While much of the literature on community capacity has focused primarily on theory construction, there have been few efforts to quantitatively assess community capacity variables and constructs, particularly for watershed management and conservation. This study seeks to identify predictors of community capacity for watershed conservation in southwestern Illinois. A subwatershed-scale survey of residents from four communities located within the Lower Kaskaskia River watershed of southwestern Illinois was administered to measure three specific capacity variables: community empowerment, shared vision and collective action. Principal component analysis revealed key dimensions of each variable. Specifically, collective action was characterized by items relating to collaborative governance and social networks, community empowerment was characterized by items relating to community competency and a sense of responsibility and shared vision was characterized by items relating to perceptions of environmental threats, issues with development, environmental sense of place and quality of life. From the emerging factors, composite measures were calculated to determine the extent to which each variable contributed to community capacity. A stepwise regression revealed that community empowerment explained most of the variability in the composite measure of community capacity for watershed conservation. This study contributes to the theoretical understanding of community capacity by quantifying the role of collective action, community empowerment and shared vision in community capacity, highlighting the need for multilevel interaction to address watershed issues.

The behaviour of random forest permutation-based variable importance measures under predictor correlation.

PubMed

Nicodemus, Kristin K; Malley, James D; Strobl, Carolin; Ziegler, Andreas

2010-02-27

Random forests (RF) have been increasingly used in applications such as genome-wide association and microarray studies where predictor correlation is frequently observed. Recent works on permutation-based variable importance measures (VIMs) used in RF have come to apparently contradictory conclusions. We present an extended simulation study to synthesize results. In the case when both predictor correlation was present and predictors were associated with the outcome (HA), the unconditional RF VIM attributed a higher share of importance to correlated predictors, while under the null hypothesis that no predictors are associated with the outcome (H0) the unconditional RF VIM was unbiased. Conditional VIMs showed a decrease in VIM values for correlated predictors versus the unconditional VIMs under HA and was unbiased under H0. Scaled VIMs were clearly biased under HA and H0. Unconditional unscaled VIMs are a computationally tractable choice for large datasets and are unbiased under the null hypothesis. Whether the observed increased VIMs for correlated predictors may be considered a "bias" - because they do not directly reflect the coefficients in the generating model - or if it is a beneficial attribute of these VIMs is dependent on the application. For example, in genetic association studies, where correlation between markers may help to localize the functionally relevant variant, the increased importance of correlated predictors may be an advantage. On the other hand, we show examples where this increased importance may result in spurious signals.

Colored Dissolved Organic Matter in Shallow Estuaries: The Effects of Source and Transport on Light Attenuation and Measurement

NASA Astrophysics Data System (ADS)

Oestreich, W. K.; Ganju, N. K.; Pohlman, J.; Suttles, S. E.

2014-12-01

Light is of great importance to the health and ecological function of shallow estuaries. Primary production in such estuaries, which is typically dominated by seagrass, is contingent upon light penetration to the deeper part of the estuarine water column. A major component contributing to light attenuation in these systems is colored dissolved organic matter (CDOM). CDOM is most often measured via a proxy, fluorescing dissolved organic matter (fDOM), due to the ease of taking rapid, accurate fDOM measurements. Fluorescence data can then be converted to absorbance by CDOM for use in light attenuation models. However, this fDOM-CDOM conversion has proven to be quite variable between estuaries, and even between sites along a given estuary. We displayed and attempted to explain this variability through the study of three diverse estuaries: West Falmouth Harbor (MA), Barnegat Bay (NJ), and Chincoteague Bay (MD/VA). Land use surrounding these estuaries ranges from wastewater treatment to agricultural operations and residential communities. Measurements of fDOM and absorbance by CDOM (quantified via spectrophotometer measurement of 0.2μm-filtered samples) were taken along a gradient from terrestrial to oceanic end-members. These measurements yielded highly variable fDOM-CDOM relationships between estuaries. The mean ratio of absorption coefficient at 340nm (m-1) to fDOM (QSU) was much higher in West Falmouth Harbor (0.874) than in Barnegat Bay (0.227) and Chincoteague Bay (0.173). This fDOM-CDOM relationship was also observed to be variable between sites within West Falmouth Harbor and Barnegat Bay, but consistent throughout sites along Chincoteague Bay. This variability, both within and between estuaries, is likely due to differing CDOM sources as a result of differences in land use in the areas surrounding these estuaries. Stable carbon isotope analysis of DOC from each site and hydrodynamic model results will be used to differentiate sources and further elucidate the fDOM-CDOM relationship.

Inferential consequences of modeling rather than measuring snow accumulation in studies of animal ecology

USGS Publications Warehouse

Cross, Paul C.; Klaver, Robert W.; Brennan, Angela; Creel, Scott; Beckmann, Jon P.; Higgs, Megan D.; Scurlock, Brandon M.

2013-01-01

Abstract. It is increasingly common for studies of animal ecology to use model-based predictions of environmental variables as explanatory or predictor variables, even though model prediction uncertainty is typically unknown. To demonstrate the potential for misleading inferences when model predictions with error are used in place of direct measurements, we compared snow water equivalent (SWE) and snow depth as predicted by the Snow Data Assimilation System (SNODAS) to field measurements of SWE and snow depth. We examined locations on elk (Cervus canadensis) winter ranges in western Wyoming, because modeled data such as SNODAS output are often used for inferences on elk ecology. Overall, SNODAS predictions tended to overestimate field measurements, prediction uncertainty was high, and the difference between SNODAS predictions and field measurements was greater in snow shadows for both snow variables compared to non-snow shadow areas. We used a simple simulation of snow effects on the probability of an elk being killed by a predator to show that, if SNODAS prediction uncertainty was ignored, we might have mistakenly concluded that SWE was not an important factor in where elk were killed in predatory attacks during the winter. In this simulation, we were interested in the effects of snow at finer scales (2) than the resolution of SNODAS. If bias were to decrease when SNODAS predictions are averaged over coarser scales, SNODAS would be applicable to population-level ecology studies. In our study, however, averaging predictions over moderate to broad spatial scales (9–2200 km2) did not reduce the differences between SNODAS predictions and field measurements. This study highlights the need to carefully evaluate two issues when using model output as an explanatory variable in subsequent analysis: (1) the model’s resolution relative to the scale of the ecological question of interest and (2) the implications of prediction uncertainty on inferences when using model predictions as explanatory or predictor variables.

When a gold standard isn't so golden: Lack of prediction of subjective sleep quality from sleep polysomnography.

PubMed

Kaplan, Katherine A; Hirshman, Jason; Hernandez, Beatriz; Stefanick, Marcia L; Hoffman, Andrew R; Redline, Susan; Ancoli-Israel, Sonia; Stone, Katie; Friedman, Leah; Zeitzer, Jamie M

2017-02-01

Reports of subjective sleep quality are frequently collected in research and clinical practice. It is unclear, however, how well polysomnographic measures of sleep correlate with subjective reports of prior-night sleep quality in elderly men and women. Furthermore, the relative importance of various polysomnographic, demographic and clinical characteristics in predicting subjective sleep quality is not known. We sought to determine the correlates of subjective sleep quality in older adults using more recently developed machine learning algorithms that are suitable for selecting and ranking important variables. Community-dwelling older men (n=1024) and women (n=459), a subset of those participating in the Osteoporotic Fractures in Men study and the Study of Osteoporotic Fractures study, respectively, completed a single night of at-home polysomnographic recording of sleep followed by a set of morning questions concerning the prior night's sleep quality. Questionnaires concerning demographics and psychological characteristics were also collected prior to the overnight recording and entered into multivariable models. Two machine learning algorithms, lasso penalized regression and random forests, determined variable selection and the ordering of variable importance separately for men and women. Thirty-eight sleep, demographic and clinical correlates of sleep quality were considered. Together, these multivariable models explained only 11-17% of the variance in predicting subjective sleep quality. Objective sleep efficiency emerged as the strongest correlate of subjective sleep quality across all models, and across both sexes. Greater total sleep time and sleep stage transitions were also significant objective correlates of subjective sleep quality. The amount of slow wave sleep obtained was not determined to be important. Overall, the commonly obtained measures of polysomnographically-defined sleep contributed little to subjective ratings of prior-night sleep quality. Though they explained relatively little of the variance, sleep efficiency, total sleep time and sleep stage transitions were among the most important objective correlates. Published by Elsevier B.V.

When a gold standard isn't so golden: Lack of prediction of subjective sleep quality from sleep polysomnography

PubMed Central

Kaplan, Katherine A.; Hirshman, Jason; Hernandez, Beatriz; Stefanick, Marcia L.; Hoffman, Andrew R.; Redline, Susan; Ancoli-Israel, Sonia; Stone, Katie; Friedman, Leah; Zeitzer, Jamie M.

2016-01-01

Background Reports of subjective sleep quality are frequently collected in research and clinical practice. It is unclear, however, how well polysomnographic measures of sleep correlate with subjective reports of prior-night sleep quality in elderly men and women. Furthermore, the relative importance of various polysomnographic, demographic and clinical characteristics in predicting subjective sleep quality is not known. We sought to determine the correlates of subjective sleep quality in in older adults using more recently developed machine learning algorithms that are suitable for selecting and ranking important variables. Methods Community-dwelling older men (n=1024) and women (n=459), a subset of those participating in the Osteoporotic Fractures in Men study and the Study of Osteoporotic Fractures study, respectively, completed a single night of at-home polysomnographic recording of sleep followed by a set of morning questions concerning the prior night's sleep quality. Questionnaires concerning demographics and psychological characteristics were also collected prior to the overnight recording and entered into multivariable models. Two machine learning algorithms, lasso penalized regression and random forests, determined variable selection and the ordering of variable importance separately for men and women. Results Thirty-eight sleep, demographic and clinical correlates of sleep quality were considered. Together, these multivariable models explained only 11-17% of the variance in predicting subjective sleep quality. Objective sleep efficiency emerged as the strongest correlate of subjective sleep quality across all models, and across both sexes. Greater total sleep time and sleep stage transitions were also significant objective correlates of subjective sleep quality. The amount of slow wave sleep obtained was not determined to be important. Conclusions Overall, the commonly obtained measures of polysomnographically-defined sleep contributed little to subjective ratings of prior-night sleep quality. Though they explained relatively little of the variance, sleep efficiency, total sleep time and sleep stage transitions were among the most important objective correlates. PMID:27889439

Temporal Variability of Canopy Light Use Efficiency and its Environmental Controls in a Subtropical Mangrove Wetland

NASA Astrophysics Data System (ADS)

Zhu, X.

2016-12-01

Mangrove wetlands play an important role in global carbon cycle due to their strong carbon sequestration resulting from high plant carbon assimilation and low soil respiration. However, temporal variability of carbon sequestration in mangrove wetlands is less understood since carbon processes of mangrove wetlands are influenced by many complicated and concurrent environmental controls including tidal activities, site climate and soil conditions. Canopy light use efficiency (LUE), is the most important plant physiological parameter that can be used to describe the temporal dynamics of canopy photosynthesis, and therefore a better characterization of temporal variability of canopy LUE will improve our understanding in mangrove photosynthesis and carbon balance. One of our aims is to study the temporal variability of canopy LUE and its environmental controls in a subtropical mangrove wetland. Half-hourly canopy LUE is derived from eddy covariance (EC) carbon flux and photosynthesis active radiation observations, and half-hourly environmental controls we measure include temperature, humidity, precipitation, radiation, tidal height, salinity, etc. Another aim is to explore the links between canopy LUE and spectral indices derived from near-surface tower-based remote sensing (normalized difference vegetation index, enhanced vegetation index, photochemical reflectance index, solar-induced chlorophyll fluorescence, etc.), and then identify potential quantitative relationships for developing remote sensing-based estimation methods of canopy LUE. At present, some instruments in our in-situ observation system have not yet been installed (planned in next months) and therefore we don't have enough measurements to support our analysis. However, a preliminary analysis of our historical EC and climate observations in past several years indicates that canopy LUE shows strong temporal variability and is greatly affected by environmental factors such as tidal activity. Detailed and systematic analyses of temporal variability of canopy LUE and its environmental controls and potential remote sensing estimation methods will be conducted when our in-situ observation system is ready in near future.

Water vapour fluxes trends on different time scales and their relationship with weather and soil drivers: a case study from a dehesa site in South Spain

NASA Astrophysics Data System (ADS)

Polo, María José; Egüen, Marta; Andreu, Ana; Carpintero, Elisabet; Gómez-Giráldez, Pedro; Patrocinio González-Dugo, María

2017-04-01

Water vapour fluxes between the soil surface and the atmosphere constitute one of the most important components of the water cycle in the continental areas. Their regime directly affect the availability of water to plants, water storage in surface bodies, air humidity in the boundary layer, snow persistence… among others, and the list of indirectly affected processes comprises a large number of components. Water potential or wetness gradients are some of the main drivers of water vapour fluxes to the atmosphere; soil humidity is usually monitored as key variable in many hydrological and environmental studies, and its estimated series are used to calibrate and validate the modelling of certain hydrological processes. However, such results may differ when water fluxes are used instead of water state variables, such as humidity. This work shows the analysis of high resolution water vapour fluxes series from a dehesa area in South Spain where a complete energy and water fluxes/variables monitoring site has been operating for the last four years. The results include pasture and tree vegetated control points. The daily water budget calculation on both types of sites has been performed from weather and energy fluxes measurements, and soil moisture measurements, and the results have been aggregated on a weekly, monthly and seasonal basis. Comparison between observed trends of soil moisture and calculated trends of water vapour fluxes is included to show the differences arising in terms of the regime of the dominant weather variables in this type of ecosystems. The results identify significant thresholds for each weather variable driver and highlight the importance of the wind regime, which is the somehow forgotten variable in future climate impacts on hydrology. Further work is being carried out to assess water cycle potential trends under future climate conditions and their impacts on the vegetation in dehesa ecosystems.

Improving spatial prediction of Schistosoma haematobium prevalence in southern Ghana through new remote sensors and local water access profiles.

PubMed

Kulinkina, Alexandra V; Walz, Yvonne; Koch, Magaly; Biritwum, Nana-Kwadwo; Utzinger, Jürg; Naumova, Elena N

2018-06-04

Schistosomiasis is a water-related neglected tropical disease. In many endemic low- and middle-income countries, insufficient surveillance and reporting lead to poor characterization of the demographic and geographic distribution of schistosomiasis cases. Hence, modeling is relied upon to predict areas of high transmission and to inform control strategies. We hypothesized that utilizing remotely sensed (RS) environmental data in combination with water, sanitation, and hygiene (WASH) variables could improve on the current predictive modeling approaches. Schistosoma haematobium prevalence data, collected from 73 rural Ghanaian schools, were used in a random forest model to investigate the predictive capacity of 15 environmental variables derived from RS data (Landsat 8, Sentinel-2, and Global Digital Elevation Model) with fine spatial resolution (10-30 m). Five methods of variable extraction were tested to determine the spatial linkage between school-based prevalence and the environmental conditions of potential transmission sites, including applying the models to known human water contact locations. Lastly, measures of local water access and groundwater quality were incorporated into RS-based models to assess the relative importance of environmental and WASH variables. Predictive models based on environmental characterization of specific locations where people contact surface water bodies offered some improvement as compared to the traditional approach based on environmental characterization of locations where prevalence is measured. A water index (MNDWI) and topographic variables (elevation and slope) were important environmental risk factors, while overall, groundwater iron concentration predominated in the combined model that included WASH variables. The study helps to understand localized drivers of schistosomiasis transmission. Specifically, unsatisfactory water quality in boreholes perpetuates reliance of surface water bodies, indirectly increasing schistosomiasis risk and resulting in rapid reinfection (up to 40% prevalence six months following preventive chemotherapy). Considering WASH-related risk factors in schistosomiasis prediction can help shift the focus of control strategies from treating symptoms to reducing exposure.

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

Hardin, Ernest; Hadgu, Teklu; Greenberg, Harris

This report is one follow-on to a study of reference geologic disposal design concepts (Hardin et al. 2011a). Based on an analysis of maximum temperatures, that study concluded that certain disposal concepts would require extended decay storage prior to emplacement, or the use of small waste packages, or both. The study used nominal values for thermal properties of host geologic media and engineered materials, demonstrating the need for uncertainty analysis to support the conclusions. This report is a first step that identifies the input parameters of the maximum temperature calculation, surveys published data on measured values, uses an analytical approachmore » to determine which parameters are most important, and performs an example sensitivity analysis. Using results from this first step, temperature calculations planned for FY12 can focus on only the important parameters, and can use the uncertainty ranges reported here. The survey of published information on thermal properties of geologic media and engineered materials, is intended to be sufficient for use in generic calculations to evaluate the feasibility of reference disposal concepts. A full compendium of literature data is beyond the scope of this report. The term “uncertainty” is used here to represent both measurement uncertainty and spatial variability, or variability across host geologic units. For the most important parameters (e.g., buffer thermal conductivity) the extent of literature data surveyed samples these different forms of uncertainty and variability. Finally, this report is intended to be one chapter or section of a larger FY12 deliverable summarizing all the work on design concepts and thermal load management for geologic disposal (M3FT-12SN0804032, due 15Aug2012).« less

Physical activity levels of older community-dwelling adults are influenced by summer weather variables.

PubMed

Brandon, Caitlin A; Gill, Dawn P; Speechley, Mark; Gilliland, Jason; Jones, Gareth R

2009-04-01

Adequate daily physical activity (PA) is important for maintaining functional capacity and independence in older adults. However, most older adults in Canada do not engage in enough PA to sustain fitness and functional independence. Environmental influences, such as warmer daytime temperatures, may influence PA participation; however, few studies have examined the effect of summertime temperatures on PA levels in older adults. This investigation measured the influence of summertime weather variables on PA in 48 community-dwelling older adults who were randomly recruited from a local seniors' community centre. Each participant wore an accelerometer for a single 7-consecutive-day period (between 30 May and 9 August 2006) during waking hours, and completed a PA logbook to remark on major daily PA events. Local weather variables were collected from a national weather service and compared with PA counts per minute. Regression analysis revealed a curvilinear relationship between log-transformed PA and mean daily temperature (r2 = 0.025; p < 0.05). Linear mixed effects models that accounted for repeated measures nested within individuals were performed for monthly periods, meteorological variables, sex, age, and estimated maximal oxygen consumption, with PA as the dependent variable. Age and Air Quality Index remained significant variables within the model. Higher fitness levels had no effect on allowing individuals to perform more vigorous PA in warmer temperatures.

Individual variability and environmental characteristics influence older adults' abilities to manage everyday technology.

PubMed

Malinowsky, Camilla; Almkvist, Ove; Nygård, Louise; Kottorp, Anders

2012-03-01

The ability to manage everyday technology (ET), such as computers and microwave ovens, is increasingly required in the performance of everyday activities and participation in society. This study aimed to identify aspects that influence the ability to manage ET among older adults with and without cognitive impairment. Older adults with mild Alzheimer's disease and mild cognitive impairment and without known cognitive impairment were assessed as they managed their ET at home. Data were collected using the Management of Everyday Technology Assessment (META). Rasch-based measures of the person's ability to manage ET were analyzed. These measures were used as dependent variables in backward procedure ANOVA analyses. Different predefined aspects that could influence the ability to manage ET were used as independent variables. Three aspects had a significant effect upon the ability to manage ET. These were: (1) variability in intrapersonal capacities (such as "the capacity to pay attention and focus", (2) environmental characteristics (such as "the impact of the design") and (3) diagnostic group. Variability in intrapersonal capacities seems to be of more importance than the actual level of intrapersonal capacity in relation to the ability to manage ET for this sample. This implies that investigations of ability to manage ET should also include intraperson variability. Additionally, adaptations in environmental characteristics could simplify the management of ET to support older adults as technology users.

Characterization of blood lipoproteins and validation of cholesterol and triacylglycerol assays for free-ranging polar bears (Ursus maritimus).

PubMed

Whiteman, John P; Frank, Nicholas; Greller, Katie A; Harlow, Henry J; Ben-David, Merav

2013-05-01

Blood triacylglycerol (TG) and lipoproteins are important variables for evaluating nutritional status of wildlife, but measurements are often expensive and difficult. Performance of a small, portable blood analyzer intended for human medical diagnostics was evaluated in measuring these variables in plasma and serum from free-ranging polar bears (Ursus maritimus), which are experiencing nutritional stress related to sea ice loss. The analyzer accurately tracked changes in concentration of total cholesterol (Ctotal), cholesterol associated with high-density lipoprotein (CHDL), and TG during a validation protocol of diluting samples and spiking them with exogenous cholesterol and glycerol. Values of Ctotal and TG agreed well with values obtained by other methods (ultracentrifugation followed by colorimetric assays); agreement was variable for values of cholesterol associated with specific lipoproteins. Similar to a study of captive polar bears, ultracentrifugation methods revealed greater TG in very low-density lipoproteins than in low-density lipoprotein, which is unusual and merits additional study.

Informed consent for MRI and fMRI research: Analysis of a sample of Canadian consent documents

PubMed Central

2011-01-01

Background Research ethics and the measures deployed to ensure ethical oversight of research (e.g., informed consent forms, ethics review) are vested with extremely important ethical and practical goals. Accordingly, these measures need to function effectively in real-world research and to follow high level standards. Methods We examined approved consent forms for Magnetic Resonance Imaging (MRI) and functional Magnetic Resonance Imaging (fMRI) studies approved by Canadian research ethics boards (REBs). Results We found evidence of variability in consent forms in matters of physical and psychological risk reporting. Approaches used to tackle the emerging issue of incidental findings exposed extensive variability between and within research sites. Conclusion The causes of variability in approved consent forms and studies need to be better understood. However, mounting evidence of administrative and practical hurdles within current ethics governance systems combined with potential sub-optimal provision of information to and protection of research subjects support other calls for more scrutiny of research ethics practices and applicable revisions. PMID:21235768

Variability of PCB burden in 5 fish and sharks species of the French Mediterranean continental slope.

PubMed

Cresson, Pierre; Fabri, Marie Claire; Miralles, Françoise Marco; Dufour, Jean-Louis; Elleboode, Romain; Sevin, Karine; Mahé, Kelig; Bouchoucha, Marc

2016-05-01

Despite being generally located far from contamination sources, deep marine ecosystems are impacted by chemicals like PCB. The PCB contamination in five fish and shark species collected in the continental slope of the Gulf of Lions (NW Mediterranean Sea) was measured, with a special focus on intra- and interspecific variability and on the driving factors. Significant differences occurred between species. Higher values were measured in Scyliorhinus canicula, Galeus melastomus and Helicolenus dactylopterus and lower values in Phycis blennoides and Lepidorhombus boscii. These differences might be explained by specific abilities to accumulate and eliminate contaminant, mostly through cytochrome P450 pathway. Interindividual variation was also high and no correlation was observed between contamination and length, age or trophic level. Despite its major importance, actual bioaccumulation of PCB in deep fish is not as documented as in other marine ecosystems, calling for a better assessment of the factors driving individual bioaccumulation mechanisms and originating high variability in PCB contamination. Copyright © 2016 Elsevier Ltd. All rights reserved.

In Situ Global Sea Surface Salinity and Variability from the NCEI Global Thermosalinograph Database

NASA Astrophysics Data System (ADS)

Wang, Z.; Boyer, T.; Zhang, H. M.

2017-12-01

Sea surface salinity (SSS) plays an important role in the global ocean circulations. The variations of sea surface salinity are key indicators of changes in air-sea water fluxes. Using nearly 30 years of in situ measurements of sea surface salinity from thermosalinographs, we will evaluate the variations of the sea surface salinity in the global ocean. The sea surface salinity data used are from our newly-developed NCEI Global Thermosalinograph Database - NCEI-TSG. This database provides a comprehensive set of quality-controlled in-situ sea-surface salinity and temperature measurements collected from over 340 vessels during the period 1989 to the present. The NCEI-TSG is the world's most complete TSG dataset, containing all data from the different TSG data assembly centers, e.g. COAPS (SAMOS), IODE (GOSUD) and AOML, with more historical data from NCEI's archive to be added. Using this unique dataset, we will investigate the spatial variations of the global SSS and its variability. Annual and interannual variability will also be studied at selected regions.

Success in baccalaureate nursing programs: a matter of accommodation?

PubMed

Haislett, J; Hughes, R B; Atkinson, G; Williams, C L

1993-02-01

This article explores student learning styles as an important variable in four-year baccalaureate nursing programs. Student learning styles were assessed by Kolb's Learning Style Inventory-1985 (LSI-1985), which identifies the accommodator, diverger, assimilator, and converger learning styles. The authors examined the relationship between learning style and academic performance as measured by grade-point ratio (GPR) and studied behaviors and attitudes as measured by Brown and Holtzman's (1964) Survey of Study Habits and Attitudes. Analysis indicated that this sample (N = 100) included mainly assimilators and divergers, making reflective observation the most common mode of learning. Compared to the accommodator/converger group, the assimilator/diverger group earned a significantly higher GPR, significantly better scores on the study habits variable of Work Methods (WM), and moderately better scores on the study attitude variable of Educational Acceptance (EA). Accommodators were identified as the most at-risk learning style group, and specific interventions were suggested to assist accommodators in adapting to the academic rigors of a nursing curriculum.

Atlas of relations between climatic parameters and distributions of important trees and shrubs in North America: Revisions for all taxa from the United States and Canada and new taxa from the western United States

USGS Publications Warehouse

Thompson, Robert S.; Anderson, Katherine H.; Pelltier, Richard T.; Strickland, Laura E.; Shafer, Sarah L.; Bartlein, Patrick J.; McFadden, Andrew K.

2015-01-01

This volume of the atlas provides numerous changes, updates, and enhancements from previous volumes. Its geographic coverage is now restricted to Canada and the continental United States, and the source and time period of the climatic data have changed. New variables were added, including monthly values for temperature and precipitation, and measures of interannual variability. The distribution maps for all previously published species were redigitized, some distribution maps were revised, and 148 new species were added from the arid and semiarid western United States. The graphical displays were expanded to illustrate the new climatic variables, and the data tables were modified to provide more detail on the population distributions of plant taxa relative to climatic variables.

Variance-based interaction index measuring heteroscedasticity

NASA Astrophysics Data System (ADS)

Ito, Keiichi; Couckuyt, Ivo; Poles, Silvia; Dhaene, Tom

2016-06-01

This work is motivated by the need to deal with models with high-dimensional input spaces of real variables. One way to tackle high-dimensional problems is to identify interaction or non-interaction among input parameters. We propose a new variance-based sensitivity interaction index that can detect and quantify interactions among the input variables of mathematical functions and computer simulations. The computation is very similar to first-order sensitivity indices by Sobol'. The proposed interaction index can quantify the relative importance of input variables in interaction. Furthermore, detection of non-interaction for screening can be done with as low as 4 n + 2 function evaluations, where n is the number of input variables. Using the interaction indices based on heteroscedasticity, the original function may be decomposed into a set of lower dimensional functions which may then be analyzed separately.

Emission of volatile organic compounds from silage: Compounds, sources, and implications

NASA Astrophysics Data System (ADS)

Hafner, Sasha D.; Howard, Cody; Muck, Richard E.; Franco, Roberta B.; Montes, Felipe; Green, Peter G.; Mitloehner, Frank; Trabue, Steven L.; Rotz, C. Alan

2013-10-01

Silage, fermented cattle feed, has recently been identified as a significant source of volatile organic compounds (VOCs) to the atmosphere. A small number of studies have measured VOC emission from silage, but not enough is known about the processes involved to accurately quantify emission rates and identify practices that could reduce emissions. Through a literature review, we have focused on identifying the most important compounds emitted from corn silage (the most common type of silage in the US) and the sources of these compounds by quantifying their production and emission potential in silage and describing production pathways. We reviewed measurements of VOC emission from silage and assessed the importance of individual silage VOCs through a quantitative analysis of VOC concentrations within silage. Measurements of VOC emission from silage and VOCs present within silage indicated that alcohols generally make the largest contribution to emission from corn silage, in terms of mass emitted and potential ozone formation. Ethanol is the dominant alcohol in corn silage; excluding acids, it makes up more than half of the mean mass of VOCs present. Acids, primarily acetic acid, may be important when emission is high and all VOCs are nearly depleted by emission. Aldehydes and esters, which are more volatile than acids and alcohols, are important when exposure is short, limiting emission of more abundant but less volatile compounds. Variability in silage VOC concentrations is very high; for most alcohols and acids, tolerance intervals indicate that 25% of silages have concentrations a factor of two away from median values, and possibly much further. This observation suggests that management practices can significantly influence VOC concentrations. Variability also makes prediction of emissions difficult. The most important acids, alcohols, and aldehydes present in silage are probably produced by bacteria (and, in the case of ethanol, yeasts) during fermentation and storage of silage. Aldehydes may also be produced aerobically by spoilage microorganisms through the oxidation of alcohols. Abiotic reactions may be important for production of methanol and esters. Although silage additives appear to affect VOC production in individual studies, bacterial inoculants have not shown a consistent effect on ethanol, and effects on other VOCs have not been studied. Production of acetic acid is understood, and production could be minimized, but a decrease could lead to an increase in other, more volatile and more reactive, VOCs. Chemical additives designed for controlling yeasts and undesirable bacteria show promise for reducing ethanol production in corn silage. More work is needed to understand silage VOC production and emission from silage, including: additional measurements of VOC concentrations or production in silage of all types, and an exploration of the causes of variability; accurate on-farm measurements of VOC emission, including an assessment of the importance of individual ensiling stages and practices that could reduce emission of existing VOCs; and work on understanding the sources of silage VOCs and possible approaches for reducing production.

A method for developing outcome measures in the clinical laboratory.

PubMed

Jones, J

1996-01-01

Measuring and reporting outcomes in health care is becoming more important for quality assessment, utilization assessment, accreditation standards, and negotiating contracts in managed care. How does one develop an outcome measure for the laboratory to assess the value of the services? A method is described which outlines seven steps in developing outcome measures for a laboratory service or process. These steps include the following: 1. Identify the process or service to be monitored for performance and outcome assessment. 2. If necessary, form an multidisciplinary team of laboratory staff, other department staff, physicians, and pathologists. 3. State the purpose of the test or service including a review of published data for the clinical pathological correlation. 4. Prepare a process cause and effect diagram including steps critical to the outcome. 5. Identify key process variables that contribute to positive or negative outcomes. 6. Identify outcome measures that are not process measures. 7. Develop an operational definition, identify data sources, and collect data. Examples, including a process cause and effect diagram, process variables, and outcome measures, are given using the Therapeutic Drug Monitoring service (TDM). A summary of conclusions and precautions for outcome measurement is then provided.

Real versus Simulated Mobile Phone Exposures in Experimental Studies

PubMed Central

Panagopoulos, Dimitris J.; Johansson, Olle; Carlo, George L.

2015-01-01

We examined whether exposures to mobile phone radiation in biological/clinical experiments should be performed with real-life Electromagnetic Fields (EMFs) emitted by commercially available mobile phone handsets, instead of simulated EMFs emitted by generators or test phones. Real mobile phone emissions are constantly and unpredictably varying and thus are very different from simulated emissions which employ fixed parameters and no variability. This variability is an important parameter that makes real emissions more bioactive. Living organisms seem to have decreased defense against environmental stressors of high variability. While experimental studies employing simulated EMF-emissions present a strong inconsistency among their results with less than 50% of them reporting effects, studies employing real mobile phone exposures demonstrate an almost 100% consistency in showing adverse effects. This consistency is in agreement with studies showing association with brain tumors, symptoms of unwellness, and declines in animal populations. Average dosimetry in studies with real emissions can be reliable with increased number of field measurements, and variation in experimental outcomes due to exposure variability becomes less significant with increased number of experimental replications. We conclude that, in order for experimental findings to reflect reality, it is crucially important that exposures be performed by commercially available mobile phone handsets. PMID:26346766

Impact of Antarctic Polar Front Variability on Southern Ocean Biogeochemistry

NASA Astrophysics Data System (ADS)

Freeman, N. M.; Lovenduski, N. S.; Gent, P. R.

2016-12-01

The Antarctic Polar Front (PF) is an important biogeochemical divide in the Southern Ocean, often coinciding with sharp gradients in silicate and nitrate concentration at the surface. Variability in the PF has the potential to influence Southern Ocean biogeochemistry and biological productivity both locally and at the basin scale. Characterizing PF variability is important for contextualizing recent biogeochemical observations from ORCAS, SOCCOM, and the Drake Passage time-series, as well as for understanding how anthropogenic change is influencing Southern Ocean biogeochemistry. Here, we employ a suite of remote sensing observations and output from the Community Earth System Model (CESM) to better understand the relationship between the PF and local biogeochemistry in the Southern Ocean. Using microwave SST measurements spanning 2002-2014 that avoid cloud contamination, we show that the PF has shifted northward (southward) in the Pacific (Indian) sector and intensified at nearly all longitudes along its circumpolar path. We identify the PF in CESM at both coarse (1°x1°) and fine (0.1°x0.1°) horizontal resolutions using temperature and silicate gradient maxima, and quantify its spatial and temporal variability. We further investigate co-variance between the position and intensity of the PF and local phytoplankton community structure.

The effect of newly induced mutations on the fitness of genotypes and populations of yeast (Saccharomyces cerevisiae).

PubMed

Orthen, E; Lange, P; Wöhrmann, K

1984-12-01

This paper analyses the fate of artificially induced mutations and their importance to the fitness of populations of the yeast, Saccharomyces cerevisiae, an increasingly important model organism in population genetics. Diploid strains, treated with UV and EMS, were cultured asexually for approximately 540 generations and under conditions where the asexual growth was interrupted by a sexual phase. Growth rates of 100 randomly sampled diploid clones were estimated at the beginning and at the end of the experiment. After the induction of sporulation the growth rates of 100 randomly sampled spores were measured. UV and EMS treatment decreases the average growth rate of the clones significantly but increases the variability in comparison to the untreated control. After selection over approximately 540 generations, variability in growth rates was reduced to that of the untreated control. No increase in mean population fitness was observed. However, the results show that after selection there still exists a large amount of hidden genetic variability in the populations which is revealed when the clones are cultivated in environments other than those in which selection took place. A sexual phase increased the reduction of the induced variability.

How spatial and temporal rainfall variability affect runoff across basin scales: insights from field observations in the (semi-)urbanised Charlotte watershed

NASA Astrophysics Data System (ADS)

Ten Veldhuis, M. C.; Smith, J. A.; Zhou, Z.

2017-12-01

Impacts of rainfall variability on runoff response are highly scale-dependent. Sensitivity analyses based on hydrological model simulations have shown that impacts are likely to depend on combinations of storm type, basin versus storm scale, temporal versus spatial rainfall variability. So far, few of these conclusions have been confirmed on observational grounds, since high quality datasets of spatially variable rainfall and runoff over prolonged periods are rare. Here we investigate relationships between rainfall variability and runoff response based on 30 years of radar-rainfall datasets and flow measurements for 16 hydrological basins ranging from 7 to 111 km2. Basins vary not only in scale, but also in their degree of urbanisation. We investigated temporal and spatial variability characteristics of rainfall fields across a range of spatial and temporal scales to identify main drivers for variability in runoff response. We identified 3 ranges of basin size with different temporal versus spatial rainfall variability characteristics. Total rainfall volume proved to be the dominant agent determining runoff response at all basin scales, independent of their degree of urbanisation. Peak rainfall intensity and storm core volume are of secondary importance. This applies to all runoff parameters, including runoff volume, runoff peak, volume-to-peak and lag time. Position and movement of the storm with respect to the basin have a negligible influence on runoff response, with the exception of lag times in some of the larger basins. This highlights the importance of accuracy in rainfall estimation: getting the position right but the volume wrong will inevitably lead to large errors in runoff prediction. Our study helps to identify conditions where rainfall variability matters for correct estimation of the rainfall volume as well as the associated runoff response.

The variability of the force produced by the plantar flexor muscles does not associate with postural sway in older adults during upright standing.

PubMed

Barbosa, Roberto N; Silva, Nilson R S; Santos, Daniel P R; Moraes, Renato; Gomes, Matheus M

2018-05-31

The force variability of the plantar flexor muscles (PFM) appears to be directly related to the control of upright standing. Nevertheless, this association is still uncertain in older adults. This study aimed to evaluate the relationship between PFM force variability and postural sway in the upright standing in older women. Forty older women performed submaximal plantar flexion movements measured by force transducers coupled to an experimental chair. They performed this task during three sets of 20 s at 5% and 10% of their maximum voluntary isometric contraction with and without the aid of visual feedback of the force produced. The volunteers then stood barefoot, with eyes closed and feet parallel on a force platform, which allowed the measurement of the center of pressure displacement in the anteroposterior direction. The results did not indicate a significant association between force variability of the PFMs and postural sway in older women. It can be inferred that the force variability of the PFM does not play an important role in controlling the posture in this population, suggesting that other factors may influence the functioning of the postural control system in older adults. Copyright © 2018. Published by Elsevier B.V.

Multivariate statistical analysis of a high rate biofilm process treating kraft mill bleach plant effluent.

PubMed

Goode, C; LeRoy, J; Allen, D G

2007-01-01

This study reports on a multivariate analysis of the moving bed biofilm reactor (MBBR) wastewater treatment system at a Canadian pulp mill. The modelling approach involved a data overview by principal component analysis (PCA) followed by partial least squares (PLS) modelling with the objective of explaining and predicting changes in the BOD output of the reactor. Over two years of data with 87 process measurements were used to build the models. Variables were collected from the MBBR control scheme as well as upstream in the bleach plant and in digestion. To account for process dynamics, a variable lagging approach was used for variables with significant temporal correlations. It was found that wood type pulped at the mill was a significant variable governing reactor performance. Other important variables included flow parameters, faults in the temperature or pH control of the reactor, and some potential indirect indicators of biomass activity (residual nitrogen and pH out). The most predictive model was found to have an RMSEP value of 606 kgBOD/d, representing a 14.5% average error. This was a good fit, given the measurement error of the BOD test. Overall, the statistical approach was effective in describing and predicting MBBR treatment performance.

Diurnal variability in riverine dissolved organic matter composition determined by in situ optical measurement in the San Joaquin River (California, USA)

USGS Publications Warehouse

Spencer, R.G.M.; Pellerin, B.A.; Bergamaschi, B.A.; Downing, B.D.; Kraus, T.E.C.; Smart, D.R.; Dahlgren, R.A.; Hernes, P.J.

2007-01-01

Dissolved organic matter (DOM) concentration and composition in riverine and stream systems are known to vary with hydrological and productivity cycles over the annual and interannual time scales. Rivers are commonly perceived as homogeneous with respect to DOM concentration and composition, particularly under steady flow conditions over short time periods. However, few studies have evaluated the impact of short term variability ( < 1 day) on DOM dynamics. This study examined whether diurnal processes measurably altered DOM concentration and composition in the hypereutrophic San Joaquin River (California) during a relatively quiescent period. We evaluated the efficacy of using optical in situ measurements to reveal changes in DOM which may not be evident from bulk dissolved organic carbon (DOC) measurement alone. The in situ optical measurements described in this study clearly showed for the first time diurnal variations in DOM measurements, which have previously been related to both composition and concentration, even though diurnal changes were not well reflected in bulk DOC concentrations. An apparent asynchronous trend of DOM absorbance and chlorophyll-a in comparison to chromophoric dissolved organic matter (CDOM) fluorescence and spectral slope S290-350 suggests that no one specific CDOM spectrophotometric measurement explains absolutely DOM diurnal variation in this system; the measurement of multiple optical parameters is therefore recommended. The observed diurnal changes in DOM composition, measured by in situ optical instrumentation likely reflect both photochemical and biologically-mediated processes. The results of this study highlight that short-term variability in DOM composition may complicate trends for studies aiming to distinguish different DOM sources in riverine systems and emphasizes the importance of sampling specific study sites to be compared at the same time of day. The utilization of in situ optical technology allows short-term variability in DOM dynamics to be monitored and serves to increase our understanding of its processing and fundamental role in the aquatic environment. Copyright ?? 2007 John Wiley & Sons, Ltd.

Temporal upscaling of instantaneous evapotranspiration on clear-sky days using the constant reference evaporative fraction method with fixed or variable surface resistances at two cropland sites

NASA Astrophysics Data System (ADS)

Tang, Ronglin; Li, Zhao-Liang; Sun, Xiaomin; Bi, Yuyun

2017-01-01

Surface evapotranspiration (ET) is an important component of water and energy in land and atmospheric systems. This paper investigated whether using variable surface resistances in the reference ET estimates from the full-form Penman-Monteith (PM) equation could improve the upscaled daily ET estimates in the constant reference evaporative fraction (EFr, the ratio of actual to reference grass/alfalfa ET) method on clear-sky days using ground-based measurements. Half-hourly near-surface meteorological variables and eddy covariance (EC) system-measured latent heat flux data on clear-sky days were collected at two sites with different climatic conditions, namely, the subhumid Yucheng station in northern China and the arid Yingke site in northwestern China and were used as the model input and ground-truth, respectively. The results showed that using the Food and Agriculture Organization (FAO)-PM equation, the American Society of Civil Engineers-PM equation, and the full-form PM equation to estimate the reference ET in the constant EFr method produced progressively smaller upscaled daily ET at a given time from midmorning to midafternoon. Using all three PM equations produced the best results at noon at both sites regardless of whether the energy imbalance of the EC measurements was closed. When the EC measurements were not corrected for energy imbalance, using variable surface resistance in the full-form PM equation could improve the ET upscaling in the midafternoon, but worse results may occur in the midmorning to noon. Site-to-site and time-to-time variations were found in the performances of a given PM equation (with fixed or variable surface resistances) before and after the energy imbalance was closed.

Surface and Tropospheric Ozone Profile Variability (1999-2014) at the TOLNet Site of Table Mountain, California

NASA Astrophysics Data System (ADS)

Granados-Muñoz, M. J.; Leblanc, T.

2015-12-01

Ozone in the lower troposphere acts as an air pollutant affecting human health and vegetation. Tropospheric ozone sources and variability are not yet fully identified or understood and recent studies reveal the importance of increasing the number of tropospheric ozone profiling stations and long term measurements. As part of the international monitoring network NDACC, and the U.S.-based network TOLNet, a differential absorption lidar has been performing tropospheric ozone measurements (3-20 km) at the JPL Table Mountain Facility (TMF, California) since 1999, and surface measurements have been performed since 2013 with a UV photometric analyzer. Because of the site's geolocation and high elevation, background tropospheric ozone, unaffected by the boundary layer dynamics and local anthropogenic emissions of ozone precursors, is usually expected. However, transboundary ozone contributions such as stratospheric intrusions and Asian pollution episodes are frequently detected. In this study, a statistical analysis of the 14-year lidar profiles and the 2.5-year surface data is presented. Seasonal, interannual and diurnal variability and its possible causes (e.g. El Nino/La Nina events, North American Monsoon) are investigated. Together with the high elevation surface data gathered at TMF, surface data from ARB stations nearby are analyzed to understand the lowermost tropospheric ozone variability component. The frequency of stratospheric intrusions and Asian pollution episodes reaching the Western U.S. is also examined in an attempt to understand the relative contribution of each process to the observed variability throughout the troposphere. The Table Mountain surface and lidar measurements are expected to contribute significantly to the emerging system of global air quality observations, and to the improvement of global and regional data assimilation and modeling.

Weighing risk factors associated with bee colony collapse disorder by classification and regression tree analysis.

PubMed

VanEngelsdorp, Dennis; Speybroeck, Niko; Evans, Jay D; Nguyen, Bach Kim; Mullin, Chris; Frazier, Maryann; Frazier, Jim; Cox-Foster, Diana; Chen, Yanping; Tarpy, David R; Haubruge, Eric; Pettis, Jeffrey S; Saegerman, Claude

2010-10-01

Colony collapse disorder (CCD), a syndrome whose defining trait is the rapid loss of adult worker honey bees, Apis mellifera L., is thought to be responsible for a minority of the large overwintering losses experienced by U.S. beekeepers since the winter 2006-2007. Using the same data set developed to perform a monofactorial analysis (PloS ONE 4: e6481, 2009), we conducted a classification and regression tree (CART) analysis in an attempt to better understand the relative importance and interrelations among different risk variables in explaining CCD. Fifty-five exploratory variables were used to construct two CART models: one model with and one model without a cost of misclassifying a CCD-diagnosed colony as a non-CCD colony. The resulting model tree that permitted for misclassification had a sensitivity and specificity of 85 and 74%, respectively. Although factors measuring colony stress (e.g., adult bee physiological measures, such as fluctuating asymmetry or mass of head) were important discriminating values, six of the 19 variables having the greatest discriminatory value were pesticide levels in different hive matrices. Notably, coumaphos levels in brood (a miticide commonly used by beekeepers) had the highest discriminatory value and were highest in control (healthy) colonies. Our CART analysis provides evidence that CCD is probably the result of several factors acting in concert, making afflicted colonies more susceptible to disease. This analysis highlights several areas that warrant further attention, including the effect of sublethal pesticide exposure on pathogen prevalence and the role of variability in bee tolerance to pesticides on colony survivorship.

Diurnal and vertical variability of the sensible heat and carbon dioxide budgets in the atmospheric surface layer

USGS Publications Warehouse

Casso-Torralba, P.; de Arellano, J. V. -G.; Bosveld, F.; Soler, M.R.; Vermeulen, A.; Werner, C.; Moors, E.

2008-01-01

The diurnal and vertical variability of heat and carbon dioxide (CO2) in the atmospheric surface layer are studied by analyzing measurements from a 213 in tower in Cabauw (Netherlands). Observations of thermodynamic variables and CO2 mixing ratio as well as vertical profiles of the turbulent fluxes are used to retrieve the contribution of the budget terms in the scalar conservation equation. On the basis of the daytime evolution of turbulent fluxes, we calculate the budget terms by assuming that turbulent fluxes follow a linear profile with height. This assumption is carefully tested and the deviation ftom linearity is quantified. The budget calculation allows us to assess the importance of advection of heat and CO2 during day hours for three selected days. It is found that, under nonadvective conditions, the diurnal variability of temperature and CO2 is well reproduced from the flux divergence measurements. Consequently, the vertical transport due to the turbulent flux plays a major role in the daytime evolution of both scalars and the advection is a relatively small contribution. During the analyzed days with a strong contribution of advection of either heat or carbon dioxide, the flux divergence is still an important contribution to the budget. For heat, the quantification of the advection contribution is in close agreement with results from a numerical model. For carbon dioxide, we qualitatively corroborate the results with a Lagrangian transport model. Our estimation of advection is compared with, traditional estimations based on the Net Ecosystem-atmosphere Exchange (NEE). Copyright 2008 by the American Geophysical Union.

The nature of solar brightness variations

NASA Astrophysics Data System (ADS)

Shapiro, A. I.; Solanki, S. K.; Krivova, N. A.; Cameron, R. H.; Yeo, K. L.; Schmutz, W. K.

2017-09-01

Determining the sources of solar brightness variations1,2, often referred to as solar noise3, is important because solar noise limits the detection of solar oscillations3, is one of the drivers of the Earth's climate system4,5 and is a prototype of stellar variability6,7—an important limiting factor for the detection of extrasolar planets. Here, we model the magnetic contribution to solar brightness variability using high-cadence8,9 observations from the Solar Dynamics Observatory (SDO) and the Spectral And Total Irradiance REconstruction (SATIRE)10,11 model. The brightness variations caused by the constantly evolving cellular granulation pattern on the solar surface were computed with the Max Planck Institute for Solar System Research (MPS)/University of Chicago Radiative Magnetohydrodynamics (MURaM)12 code. We found that the surface magnetic field and granulation can together precisely explain solar noise (that is, solar variability excluding oscillations) on timescales from minutes to decades, accounting for all timescales that have so far been resolved or covered by irradiance measurements. We demonstrate that no other sources of variability are required to explain the data. Recent measurements of Sun-like stars by the COnvection ROtation and planetary Transits (CoRoT)13 and Kepler14 missions uncovered brightness variations similar to that of the Sun, but with a much wider variety of patterns15. Our finding that solar brightness variations can be replicated in detail with just two well-known sources will greatly simplify future modelling of existing CoRoT and Kepler as well as anticipated Transiting Exoplanet Survey Satellite16 and PLAnetary Transits and Oscillations of stars (PLATO)17 data.

Selecting an Informative/Discriminating Multivariate Response for Inverse Prediction

DOE PAGES

Thomas, Edward V.; Lewis, John R.; Anderson-Cook, Christine M.; ...

2017-11-21

nverse prediction is important in a wide variety of scientific and engineering contexts. One might use inverse prediction to predict fundamental properties/characteristics of an object using measurements obtained from it. This can be accomplished by “inverting” parameterized forward models that relate the measurements (responses) to the properties/characteristics of interest. Sometimes forward models are science based; but often, forward models are empirically based, using the results of experimentation. For empirically-based forward models, it is important that the experiments provide a sound basis to develop accurate forward models in terms of the properties/characteristics (factors). While nature dictates the causal relationship between factorsmore » and responses, experimenters can influence control of the type, accuracy, and precision of forward models that can be constructed via selection of factors, factor levels, and the set of trials that are performed. Whether the forward models are based on science, experiments or both, researchers can influence the ability to perform inverse prediction by selecting informative response variables. By using an errors-in-variables framework for inverse prediction, this paper shows via simple analysis and examples how the capability of a multivariate response (with respect to being informative and discriminating) can vary depending on how well the various responses complement one another over the range of the factor-space of interest. Insights derived from this analysis could be useful for selecting a set of response variables among candidates in cases where the number of response variables that can be acquired is limited by difficulty, expense, and/or availability of material.« less

Selecting an Informative/Discriminating Multivariate Response for Inverse Prediction

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

Thomas, Edward V.; Lewis, John R.; Anderson-Cook, Christine M.

nverse prediction is important in a wide variety of scientific and engineering contexts. One might use inverse prediction to predict fundamental properties/characteristics of an object using measurements obtained from it. This can be accomplished by “inverting” parameterized forward models that relate the measurements (responses) to the properties/characteristics of interest. Sometimes forward models are science based; but often, forward models are empirically based, using the results of experimentation. For empirically-based forward models, it is important that the experiments provide a sound basis to develop accurate forward models in terms of the properties/characteristics (factors). While nature dictates the causal relationship between factorsmore » and responses, experimenters can influence control of the type, accuracy, and precision of forward models that can be constructed via selection of factors, factor levels, and the set of trials that are performed. Whether the forward models are based on science, experiments or both, researchers can influence the ability to perform inverse prediction by selecting informative response variables. By using an errors-in-variables framework for inverse prediction, this paper shows via simple analysis and examples how the capability of a multivariate response (with respect to being informative and discriminating) can vary depending on how well the various responses complement one another over the range of the factor-space of interest. Insights derived from this analysis could be useful for selecting a set of response variables among candidates in cases where the number of response variables that can be acquired is limited by difficulty, expense, and/or availability of material.« less

Two Brief Measures of Alcohol Use Produce Different Results: AUDIT-C and Quick Drinking Screen.

PubMed

Letourneau, Brian; Sobell, Linda Carter; Sobell, Mark B; Agrawal, Sangeeta; Gioia, Christopher J

2017-05-01

Several psychometrically sound measures of alcohol use have been developed to assess drinking. The Alcohol Use Disorders Identification Test (AUDIT) and its shorter counterpart the AUDIT-C, which contains the first 3 AUDIT questions, were developed by the World Health Organization and have become the preferred brief measures for screening and evaluating problem severity. This study compared the first 3 questions on the AUDIT with another psychometrically sound brief measure of alcohol use, the Quick Drinking Screen (QDS). Data were obtained from a randomized controlled trial of a mail-based intervention promoting self-change with 472 alcohol abusers (n = 280, no prior alcohol treatment; n = 192, prior alcohol treatment). Participants' retrospective self-reports of alcohol consumption were collected using the QDS and the 3 AUDIT-C questions and compared. Although both measures contain similar questions (2 quantity-frequency and 1 binge drinking), they differ in 2 important ways: (i) temporal interval over which data are collected, and (ii) formatting of response options (i.e., a continuous number vs. categorical). Intraclass correlations for drinking variables were moderate to moderately high. A repeated-measures MANOVA using treatment condition and gender as variables revealed significant differences in absolute values between the 2 drinking measures with the QDS showing greater consumption on almost all variables. Participants' numerical answers on the QDS were compared to their categorical answers to the similar alcohol use questions on the AUDIT-C. The comparison revealed that participants' answers on the AUDIT-C were associated with extreme variability compared to their QDS answers. This variability suggests the AUDIT-C would be unreliable as a quantitative measure of alcohol consumption. The differences between the 3 alcohol use questions on the AUDIT-C and the same questions on the QDS may reflect the imprecision of the AUDIT-C's drinking response categories. Results suggest that the QDS can be used to identify risky drinking and to provide a more informative characterization of a drinker's alcohol consumption than that provided by the AUDIT-C. Copyright © 2017 by the Research Society on Alcoholism.

Two Brief Measures of Alcohol Use Produce Different Results: AUDIT-C and Quick Drinking Screen

PubMed Central

Letourneau, Brian; Sobell, Linda Carter; Sobell, Mark B.; Agrawal, Sangeeta; Gioia, Christopher J.

2017-01-01

Background Several psychometrically sound measures of alcohol use have been developed to assess drinking. The AUDIT, and its shorter counterpart the AUDIT-C, which contains the first three AUDIT questions, were developed by the World Health Organization and have become the preferred brief measures for screening and evaluating problem severity. This study compared the first three questions on the AUDIT with another psychometrically sound brief measure of alcohol use, the Quick Drinking Screen (QDS). Methods Data were obtained from a randomized controlled trial of a mail-based intervention promoting self-change with 472 alcohol abusers (n = 280, no prior alcohol treatment; n = 192, prior alcohol treatment). Participants’ retrospective self-reports of alcohol consumption were collected using the QDS and the three AUDIT-C questions and compared. Although both measures contain similar questions (2 quantity-frequency and 1 binge drinking), they differ in two important ways: (a) temporal interval over which data are collected, and (b) formatting of response options (i.e., a continuous number vs. categorical). Results Intraclass correlations for drinking variables were moderate to moderately high. A repeated measures MANOVA using treatment condition and gender as variables revealed significant differences in absolute values between the two drinking measures with the QDS showing greater consumption on almost all variables. Participants’ numerical answers on the QDS were compared to their categorical answers to the similar alcohol use questions on the AUDIT-C. The comparison revealed that participants’ answers on the AUDIT-C were associated with extreme variability compared to their QDS answers. This variability suggests the AUDIT-C would be unreliable as a quantitative measure of alcohol consumption. Conclusions The differences between the three alcohol use questions on the AUDIT-C’s and the same questions on the QDS may reflect the imprecision of the AUDIT-C’s drinking response categories. Results suggest that the QDS can be used to identify risky drinking and to provide a more informative characterization of a drinker’s alcohol consumption than that provided by the AUDIT-C. PMID:28247424

Measurement of the setting expansion of phosphate-bonded investment materials: Part I - Development of the Casting-Ring Test.

PubMed

Lloyd, C H; Yearn, J A; Cowper, G A; Blavier, J; Vanderdonckt, M

2004-07-01

The setting expansion is an important property for a phosphate-bonded investment material. This research was undertaken to investigate a test that might be suitable for its measurement when used in a Standard. In the 'Casting-Ring Test', the investment sample is contained in a steel ring and expands to displace a precisely positioned pin. Variables with the potential to alter routine reproduction of the value were investigated. The vacuum-mixer model is a production laboratory variable that must not be ignored and for this reason, experiments were repeated using a different vacuum-mixer located at a second test site. Restraint by the rigid ring material increased expansion, while force on the pin reduced it. Expansion was specific to the lining selected. Increased environmental temperature decreased the final value. Expansion was still taking place at a time at which its value might be measured. However, when these factors are set, the reproducibility of values for setting expansion was good at both test sites (coefficient of variation 14%, at most). The results revealed that with the control that is available reliable routine measurement is possible in a Standard test. The inter-laboratory variable, vacuum-mixer model, produced significant differences and it should be the subject of further investigation.

Interrater reliability: the kappa statistic.

PubMed

McHugh, Mary L

2012-01-01

The kappa statistic is frequently used to test interrater reliability. The importance of rater reliability lies in the fact that it represents the extent to which the data collected in the study are correct representations of the variables measured. Measurement of the extent to which data collectors (raters) assign the same score to the same variable is called interrater reliability. While there have been a variety of methods to measure interrater reliability, traditionally it was measured as percent agreement, calculated as the number of agreement scores divided by the total number of scores. In 1960, Jacob Cohen critiqued use of percent agreement due to its inability to account for chance agreement. He introduced the Cohen's kappa, developed to account for the possibility that raters actually guess on at least some variables due to uncertainty. Like most correlation statistics, the kappa can range from -1 to +1. While the kappa is one of the most commonly used statistics to test interrater reliability, it has limitations. Judgments about what level of kappa should be acceptable for health research are questioned. Cohen's suggested interpretation may be too lenient for health related studies because it implies that a score as low as 0.41 might be acceptable. Kappa and percent agreement are compared, and levels for both kappa and percent agreement that should be demanded in healthcare studies are suggested.

The "Mars-Sun Connection" and the Impact of Solar Variability on Mars Weather and Climate

NASA Astrophysics Data System (ADS)

Hassler, D. M.; Grinspoon, D.

2004-05-01

We develop the scientific case to measure simultaneously the UV and near-UV solar irradiance incident on the Mars atmosphere and at the Martian surface, to explore the effects and influence of Solar variability and "Space Weather" on Mars weather and climate, its implications for life, and the implications for astronaut safety on future manned Mars missions. The UV flux at the Martian surface is expected to be highly variable, due to diurnal, daily, and seasonal variations in opacity of atmospheric dust and clouds, as well as diurnal and seasonal variations in ozone, water vapor and other absorbing species. This flux has been modeled (Kuhn and Atreya, 1979), but never measured directly from the Martian surface. By directly observing the UV and near UV solar irradiance both at the top of the atmosphere and at the Martian surface we will be able to directly constrain important model parameters necessary to understand the variations of atmospheric dynamics which drive both Mars weather and climate. Directly measuring the solar UV radiation incident upon the Mars atmosphere and at the Martian surface also has important implications for astronaut safety on future manned Mars missions. The flux at the surface of Mars at 250 nm is also believed to be approximately 3000 times greater than that on Earth. This presents potential hazards to future human explorers as well as challenges for future agriculture such as may be carried out in surface greenhouses to provide food for human colonists. A better understanding of the surface flux will aid in designing appropriate protection against these hazards.

The ``Mars-Sun Connection" and the Impact of Solar Variability on Mars Weather and Climate

NASA Astrophysics Data System (ADS)

Hassler, D. M.; Grinspoon, D. H.

2003-05-01

We develop the scientific case to measure simultaneously the UV and near-UV solar irradiance incident on the Mars atmosphere and at the Martian surface, to explore the effects and influence of Solar variability and ``Space Weather" on Mars weather and climate, its implications for life, and the implications for astronaut safety on future manned Mars missions. The UV flux at the Martian surface is expected to be highly variable, due to diurnal, daily, and seasonal variations in opacity of atmospheric dust and clouds, as well as diurnal and seasonal variations in ozone, water vapor and other absorbing species. This flux has been modeled (Kuhn and Atreya, 1979), but never measured directly from the Martian surface. By directly observing the UV and near UV solar irradiance both at the top of the atmosphere and at the Martian surface we will be able to directly constrain important model parameters necessary to understand the variations of atmospheric dynamics which drive both Mars weather and climate. Directly measuring the solar UV radiation incident upon the Mars atmosphere and at the Martian surface also has important implications for astronaut safety on future manned Mars missions. The flux at the surface of Mars at 250 nm is also believed to be approximately 3000 times greater than that on Earth. This presents potential hazards to future human explorers as well as challenges for future agriculture such as may be carried out in surface greenhouses to provide food for human colonists. A better understanding of the surface flux will aid in designing appropriate protection against these hazards.

Temporal variation in photosynthetically active radiation (par) in mesic southern Appalachian hardwood forests with and without Rhododendron understories

Treesearch

Barton D. Clinton

1995-01-01

Understanding spatial and temporal variation in the understory light regime of southern Appalachian forests is central to understanding regeneration patterns of overstory species. One of the important contributors to this variability is the distribution of evergreen shrub species, primarily Rhododendron maximum L. We measured photosynthetically...

Temporal Variation in Photosynthetically Active Radiation (PAR) in Mesic Southern Appalachian Hardwood Forest with and without Rhododendron Understories

Treesearch

Barton D. Clinton

1995-01-01

Understanding spatial and temporal variation in, the understory light regime of southern Appalachian forests is central to understanding regeneration patterns of overstory species. One of the important contributors to this variability is the distribution of evergreen shrub species, primarily Rhododendrun maximun L, We measured...

Confidence Intervals for Squared Semipartial Correlation Coefficients: The Effect of Nonnormality

ERIC Educational Resources Information Center

Algina, James; Keselman, H. J.; Penfield, Randall D.

2010-01-01

The increase in the squared multiple correlation coefficient ([delta]R[superscript 2]) associated with a variable in a regression equation is a commonly used measure of importance in regression analysis. Algina, Keselman, and Penfield found that intervals based on asymptotic principles were typically very inaccurate, even though the sample size…

Women's and Men's Marriages: Marital Satisfaction, Perceived Control, and Attitudes toward Women.

ERIC Educational Resources Information Center

Madden, Margaret E.

Previous research on marriage indicates that perceptions of control are important to marital satisfaction. To investigate the relationship between attributions of personal control and other variables in marriage, e.g., measures of satisfaction, decision making, and task performance, and attributions of control over decisions and tasks, and to…

Substantive Nonadditivity in Rural Sociological Research: A Note on Induced Collinearity and Measurement and Testing of Effects.

ERIC Educational Resources Information Center

Miller, Michael K.; Farmer, Frank L.

Theories employed to explain regularities in social behavior often contain explicit or implicit reference to the presence of nonlinear and/or nonadditive (i.e., multiplicative) relationships among germane variables. While such nonadditive features are theoretically important, the inclusion of quadratic or multiplicative terms in structural…

Do Students in Secondary Education Manifest Sexist Attitudes?

ERIC Educational Resources Information Center

Pozo, Carmen; Martos, Maria J.; Morillejo, Enrique Alonso

2010-01-01

Introduction: Sexism and sexist attitudes can give rise to gender violence. It is therefore important to analyze these variables at an early age (in secondary school classrooms); from this analysis we will have a basis for intervention. Method: The study sample consists of 962 secondary school students. Measuring instruments were used to assess…

Attitudes toward Information Competency of University Students in Social Sciences

ERIC Educational Resources Information Center

Pinto, María; Fernández-Pascual, Rosaura; Gómez-Hernández, José A.; Cuevas, Aurora; Granell, Ximo; Puertas, Susana; Guerrero, David; Gómez, Carmen; Palomares, Rocío

2016-01-01

This paper examines students' self-assessment of their information literacy, presenting a study involving 1,575 social science students at five Spanish universities. Data were collected and analyzed through a validated instrument that measures the variables of (1) the students' belief in the importance of information literacy skills; (2)…

Differing Reactions to Television in Kibbutz and City Children.

ERIC Educational Resources Information Center

Huesmann, L. Rowell; Bachrach, Riva S.

Children's social and cultural environments may affect their perceptions of the reality of television violence. One of the problems in measuring the importance of societal variables is the difficulty in finding children whose social environments have differed for most of their lives in well prescribed ways. An exception to this are kibbutz- and…

Mapping and imputing potential productivity of Pacific Northwest forests using climate variables

Treesearch

Gregory Latta; Hailemariam Temesgen; Tara Barrett

2009-01-01

Regional estimation of potential forest productivity is important to diverse applications, including biofuels supply, carbon sequestration, and projections of forest growth. Using PRISM (Parameter-elevation Regressions on Independent Slopes Model) climate and productivity data measured on a grid of 3356 Forest Inventory and Analysis plots in Oregon and Washington, we...

Urban Teachers' Perceptions of Critical Variables in Measuring Teacher Effectiveness

ERIC Educational Resources Information Center

Flores, JuanPablo

2013-01-01

This quantitative and qualitative study sought to examine the factors that teachers in a poor socio-economic, high-minority, urban, inner-city school district determined were important when gauging their effectiveness in the classroom. The study focused on the selection of specific factors by approximately seventy-five teachers from seven of eight…

The Continued Assessment of Self-Continuity and Identity

ERIC Educational Resources Information Center

Dunkel, Curtis S.; Minor, Leslie; Babineau, Maureen

2010-01-01

Studies have found that self-continuity is predictive of a substantial number of important outcome variables. However, a recent series of studies brings into question the traditional method of measuring self-continuity in favor of an alternative (B. M. Baird, K. Le, & R. E. Lucas, 2006). The present study represents a further comparison of…

Variables Associated with Enhanced Sustainability of School-Wide Positive Behavioral Interventions and Supports

ERIC Educational Resources Information Center

McIntosh, Kent; Kim, Jerin; Mercer, Sterett H.; Strickland-Cohen, M. Kathleen; Horner, Robert H.

2015-01-01

Practice sustainability is important to ensure that students have continued access to evidence-based practices. In this study, respondents from a national sample of 860 schools at varying stages of implementing school-wide positive behavioral interventions and supports (SWPBIS) were administered a research-validated measure of factors predicting…

Exploring a Measure of Science Attitude for Different Groups of Students Enrolled in Introductory College Chemistry

ERIC Educational Resources Information Center

Villafañe, Sachel M.; Lewis, Jennifer E.

2016-01-01

Decisions about instruction, research, or policy often require the interpretation of student assessment scores. Increasingly, attitudinal variables are included in an assessment strategy, and it is important to ensure that interpretations of students' attitudinal status are based on instrument scores that apply similarly for diverse students. In…

IN SITU HIGH TEMPORAL RESOLUTION ANALYSIS OF ELEMENTAL MERCURY IN NATURAL WATER (R827915)

EPA Science Inventory

Abstract

Volatilization of elemental Hg represents an important Hg flux for many aquatic systems. In order to model this flux accurately, it is necessary to measure elemental Hg concentrations in air and water, as well as meteorological variables. Up to now, temporal r...

Quantifying spatial and temporal variability in atmospheric ammonia with in situ and space-based observations--article

EPA Science Inventory

Ammonia plays an important role in many biogeochemical processes, yet atmospheric mixing ratios are not well known. Recently, methods have been developed for retrieving NH3 from space-based observations, but they have not been compared to in situ measurements. We have conducted a...

Measuring Teacher Quality: Continuing the Search for Policy-Relevant Predictors of Student Achievement

ERIC Educational Resources Information Center

Knoeppel, Robert C.; Logan, Joyce P.; Keiser, Clare M.

2005-01-01

The purpose of this study was to investigate the potential viability of the variable certification by the National Board for Professional Teaching Standards (NBPTS) as a policy-relevant predictor of student achievement. Because research has identified the teacher as the most important school-related predictor of student achievement, more research…

Socioeconomic status, parenting, and externalizing problems in African American single-mother homes: A person-oriented approach.

PubMed

Anton, Margaret T; Jones, Deborah J; Youngstrom, Eric A

2015-06-01

African American youth, particularly those from single-mother homes, are overrepresented in statistics on externalizing problems. The family is a central context in which to understand externalizing problems; however, reliance on variable-oriented approaches to the study of parenting, which originate from work with intact, middle-income, European American families, may obscure important information regarding variability in parenting styles among African American single mothers, and in turn, variability in youth outcomes as well. The current study demonstrated that within African American single-mother families: (a) a person-, rather than variable-, oriented approach to measuring parenting style may further elucidate variability; (b) socioeconomic status may provide 1 context within which to understanding variability in parenting style; and (c) 1 marker of socioeconomic status, income, and parenting style may each explain variability in youth externalizing problems; however, the interaction between income and parenting style was not significant. Findings have potential implications for better understanding the specific contexts in which externalizing problems may be most likely to occur within this at-risk and underserved group. (c) 2015 APA, all rights reserved).

Organizational variables on nurses' job performance in Turkey: nursing assessments.

PubMed

Top, Mehmet

2013-01-01

The purpose of this study was to describe the influence of organizational variables on hospital staff nurses' job performance as reported by staff nurses in two cities in Turkey. Hospital ownership status, employment status were examined for their effect on this influence. The reported influence of organizational variables on job performance was measured by a questionnaire developed for this study. Nurses were asked to evaluate the influence of 28 organizational variables on their job performance using a five-point Likert-type scale (1- Never effective, 5- Very effective). The study used comparative and descriptive study design. The staff nurses who were included in this study were 831 hospital staff nurses. Descriptive statistics, frequencies, t-test, ANOVA and factor analysis were used for data analysis. The study showed the relative importance of the 28 organizational variables in influencing nurses' job performance. Nurses in this study reported that workload and technological support are the most influential organizational variables on their job performance. Factor analysis yielded a five-factor model that explained 53.99% of total variance. Administratively controllable influence job organizational variables influence job performance of nurses in different magnitude.

Socioeconomic Status, Parenting, and Externalizing Problems in African American Single-Mother Homes: A Person-Oriented Approach

PubMed Central

Anton, Margaret T.; Jones, Deborah J.; Youngstrom, Eric A.

2016-01-01

African American youth, particularly those from single-mother homes, are overrepresented in statistics on externalizing problems. The family is a central context in which to understand externalizing problems; however, reliance on variable-oriented approaches to the study of parenting, which originate from work with intact, middle-income, European American families, may obscure important information regarding variability in parenting styles among African American single mothers, and in turn, variability in youth outcomes as well. The current study demonstrated that within African American single-mother families: (a) a person-, rather than variable-, oriented approach to measuring parenting style may further elucidate variability; (b) socioeconomic status may provide 1 context within which to understanding variability in parenting style; and (c) 1 marker of socioeconomic status, income, and parenting style may each explain variability in youth externalizing problems; however, the interaction between income and parenting style was not significant. Findings have potential implications for better understanding the specific contexts in which externalizing problems may be most likely to occur within this at-risk and underserved group. PMID:26053349

Habitat shifts in rainbow trout: competitive influences of brown trout.

PubMed

Gatz, A J; Sale, M J; Loar, J M

1987-11-01

We compared habitat use by rainbow trout sympatric (three streams) and allopatric (two streams) with brown trout to determine whether competition occurred between these two species in the southern Appalachian Mountains. We measured water depth, water velocity, substrate, distance to overhead vegetation, sunlight, and surface turbulence both where we collected trout and for the streams in general. This enabled us to separate the effects of habitat availability from possible competitive effects. The results provided strong evidence for asymmetrical interspecific competition. Habitat use varied significantly between allopatric and sympatric rainbow trout in 68% of the comparisons made. Portions of some differences refelected differences in habitats available in the several streams. However, for all habitat variables measured except sunlight, rainbow trout used their preferred habitats less in sympatry with brown trout than in allopatry if brown trout also preferred the same habitats. Multivariate analysis indicated that water velocity and its correlates (substrate particle size and surface turbulence) were the most critical habitat variables in the interaction between the species, cover in the form of shade and close overhead vegetation was second most important, and water depth was least important.

Evaluation of alternative model selection criteria in the analysis of unimodal response curves using CART

USGS Publications Warehouse

Ribic, C.A.; Miller, T.W.

1998-01-01

We investigated CART performance with a unimodal response curve for one continuous response and four continuous explanatory variables, where two variables were important (ie directly related to the response) and the other two were not. We explored performance under three relationship strengths and two explanatory variable conditions: equal importance and one variable four times as important as the other. We compared CART variable selection performance using three tree-selection rules ('minimum risk', 'minimum risk complexity', 'one standard error') to stepwise polynomial ordinary least squares (OLS) under four sample size conditions. The one-standard-error and minimum-risk-complexity methods performed about as well as stepwise OLS with large sample sizes when the relationship was strong. With weaker relationships, equally important explanatory variables and larger sample sizes, the one-standard-error and minimum-risk-complexity rules performed better than stepwise OLS. With weaker relationships and explanatory variables of unequal importance, tree-structured methods did not perform as well as stepwise OLS. Comparing performance within tree-structured methods, with a strong relationship and equally important explanatory variables, the one-standard-error-rule was more likely to choose the correct model than were the other tree-selection rules 1) with weaker relationships and equally important explanatory variables; and 2) under all relationship strengths when explanatory variables were of unequal importance and sample sizes were lower.

Prognostic importance of glycaemic variability on hospital mortality in patients hospitalised in Internal Medicine Departments.

PubMed

Sáenz-Abad, D; Gimeno-Orna, J A; Pérez-Calvo, J I

2015-12-01

The objective was to assess the prognostic importance of various glycaemic control measures on hospital mortality. Retrospective, analytical cohort study that included patients hospitalised in internal medicine departments with a diagnosis related to diabetes mellitus (DM), excluding acute decompensations. The clinical endpoint was hospital mortality. We recorded clinical, analytical and glycaemic control-related variables (scheduled insulin administration, plasma glycaemia at admission, HbA1c, mean glycaemia (MG) and in-hospital glycaemic variability and hypoglycaemia). The measurement of hospital mortality predictors was performed using univariate and multivariate logistic regression. A total of 384 patients (50.3% men) were included. The mean age was 78.5 (SD, 10.3) years. The DM-related diagnoses were type 2 diabetes (83.6%) and stress hyperglycaemia (6.8%). Thirty-one (8.1%) patients died while in hospital. In the multivariate analysis, the best model for predicting mortality (R(2)=0.326; P<.0001) consisted, in order of importance, of age (χ(2)=8.19; OR=1.094; 95% CI 1.020-1.174; P=.004), Charlson index (χ(2)=7.28; OR=1.48; 95% CI 1.11-1.99; P=.007), initial glycaemia (χ(2)=6.05; OR=1.007; 95% CI 1.001-1.014; P=.014), HbA1c (χ(2)=5.76; OR=0.59; 95% CI 0.33-1; P=.016), glycaemic variability (χ(2)=4.41; OR=1.031; 95% CI 1-1.062; P=.036), need for corticosteroid treatment (χ(2)=4.03; OR=3.1; 95% CI 1-9.64; P=.045), administration of scheduled insulin (χ(2)=3.98; OR=0.26; 95% CI 0.066-1; P=.046) and systolic blood pressure (χ(2)=2.92; OR=0.985; 95% CI 0.97-1.003; P=.088). An increase in initial glycaemia and in-hospital glycaemic variability predict the risk of mortality for hospitalised patients with DM. Copyright © 2015 Elsevier España, S.L.U. y Sociedad Española de Medicina Interna (SEMI). All rights reserved.

Distance correlation methods for discovering associations in large astrophysical databases

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

Martínez-Gómez, Elizabeth; Richards, Mercedes T.; Richards, Donald St. P., E-mail: elizabeth.martinez@itam.mx, E-mail: mrichards@astro.psu.edu, E-mail: richards@stat.psu.edu

2014-01-20

High-dimensional, large-sample astrophysical databases of galaxy clusters, such as the Chandra Deep Field South COMBO-17 database, provide measurements on many variables for thousands of galaxies and a range of redshifts. Current understanding of galaxy formation and evolution rests sensitively on relationships between different astrophysical variables; hence an ability to detect and verify associations or correlations between variables is important in astrophysical research. In this paper, we apply a recently defined statistical measure called the distance correlation coefficient, which can be used to identify new associations and correlations between astrophysical variables. The distance correlation coefficient applies to variables of any dimension,more » can be used to determine smaller sets of variables that provide equivalent astrophysical information, is zero only when variables are independent, and is capable of detecting nonlinear associations that are undetectable by the classical Pearson correlation coefficient. Hence, the distance correlation coefficient provides more information than the Pearson coefficient. We analyze numerous pairs of variables in the COMBO-17 database with the distance correlation method and with the maximal information coefficient. We show that the Pearson coefficient can be estimated with higher accuracy from the corresponding distance correlation coefficient than from the maximal information coefficient. For given values of the Pearson coefficient, the distance correlation method has a greater ability than the maximal information coefficient to resolve astrophysical data into highly concentrated horseshoe- or V-shapes, which enhances classification and pattern identification. These results are observed over a range of redshifts beyond the local universe and for galaxies from elliptical to spiral.« less

Presentation a New Model to Measure National Power of the Countries

NASA Astrophysics Data System (ADS)

Hafeznia, Mohammad Reza; Hadi Zarghani, Seyed; Ahmadipor, Zahra; Roknoddin Eftekhari, Abdelreza

In this research, based on the assessment of previous models for the evaluation of national power, a new model is presented to measure national power; it is much better than previous models. Paying attention to all the aspects of national power (economical, social, cultural, political, military, astro-space, territorial, scientific and technological and transnational), paying attention to the usage of 87 factors, stressing the usage of new and strategically compatible variables to the current time are some of the benefits of this model. Also using the Delphi method and referring to the opinions of experts about determining the role and importance of variables affecting national power, the option of drawing out the global power structure are some the other advantages that this model has compared to previous ones.

Modeling of vegetation canopy reflectance: Status, issues and recommended future strategy

NASA Technical Reports Server (NTRS)

Goel, N. S. (Editor)

1982-01-01

Various technical issues related to mapping of vegetative type, condition and stage of maturity, utilizing remotely sensed spectral data are reviewed. The existing knowledge base of models, especially of radiative properties of the vegetation canopy and atmosphere, is reviewed to establish the state of the art for addressing the problem of vegetation mapping. Activities to advance the state of the art are recommended. They include working on canopy reflectance and atmospheric scattering models, and field measurements of canopy reflectance as well as of canopy components. Leaf area index (LAI) and solar radiation interception (SRI) are identified as the two most important vegetation variables requiring further investigation. It is recommended that activities related to sensing them or understanding their relationships with measurable variables, should be encouraged and supported.

3D Volumetric Analysis of Wind Turbine Wake Properties in the Atmosphere Using High-Resolution Doppler Lidar

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

Banta, Robert M.; Pichugina, Yelena L.; Brewer, W. Alan

Wind turbine wakes in the atmosphere are three-dimensional (3D) and time dependent. An important question is how best to measure atmospheric wake properties, both for characterizing these properties observationally and for verification of numerical, conceptual, and physical (e.g., wind tunnel) models of wakes. Here a scanning, pulsed, coherent Doppler lidar is used to sample a turbine wake using 3D volume scan patterns that envelop the wake and simultaneously measure the inflow profile. The volume data are analyzed for quantities of interest, such as peak velocity deficit, downwind variability of the deficit, and downwind extent of the wake, in a mannermore » that preserves the measured data. For the case study presented here, in which the wake was well defined in the lidar data, peak deficits of up to 80% were measured 0.6-2 rotor diameters (D) downwind of the turbine, and the wakes extended more than 11D downwind. Temporal wake variability over periods of minutes and the effects of atmospheric gusts and lulls in the inflow are demonstrated in the analysis. Lidar scanning trade-offs important to ensuring that the wake quantities of interest are adequately sampled by the scan pattern, including scan coverage, number of scans per volume, data resolution, and scan-cycle repeat interval, are discussed.« less

Prediction of fruit and vegetable intake: The importance of contextualizing motivation.

PubMed

Evans, Rachel; Kawabata, Masato; Thomas, Shirley

2015-09-01

Motivation is identified as a key antecedent of self-regulated behaviour, such as eating fruit and vegetables. However, inaccurate measurement of this construct may lead to poor prediction of behaviour and inflate the impact of post-motivational factors, such as planning, in models of health behaviour. This study explored the properties of a newly identified measure of motivation, termed behavioural resolve (Rhodes & Horne, 2013, Psychol. Sport Exerc., 14, 455-460), in relation to intention, planning, and fruit and vegetable intake (FVI). Prospective self-report survey. University students living in the United Kingdom completed two online surveys. The first assessed demographic and predictor variables (intention, behavioural resolve, action planning, and coping planning). The second, completed approximately 2 weeks later, measured average daily FVI and perceived experience of obstacles to FVI. At Time 1, there were 195 respondents, with 139 providing follow-up data. All predictor variables were significantly correlated with FVI. Two independent multiple hierarchical regression analyses revealed that both intention and behavioural resolve were significant predictors of FVI, but behavioural resolve explained greater FVI variance (40.1%) than intention (36.4%). Furthermore, action planning showed incremental predictive utility over intention, but not behavioural resolve, in predicting FVI. The results indicated that motivation is an important determinant of FVI for students, with behavioural resolve demonstrating advantages over intention as a measure of this domain and a predictor of FVI behaviour. © 2014 The British Psychological Society.

3D sorghum reconstructions from depth images identify QTL regulating shoot architecture

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

Mccormick, Ryan F.; Truong, Sandra K.; Mullet, John E.

Dissecting the genetic basis of complex traits is aided by frequent and nondestructive measurements. Advances in range imaging technologies enable the rapid acquisition of three-dimensional (3D) data from an imaged scene. A depth camera was used to acquire images of sorghum (Sorghum bicolor), an important grain, forage, and bioenergy crop, at multiple developmental time points from a greenhouse-grown recombinant inbred line population. A semiautomated software pipeline was developed and used to generate segmented, 3D plant reconstructions from the images. Automated measurements made from 3D plant reconstructions identified quantitative trait loci for standard measures of shoot architecture, such as shoot height,more » leaf angle, and leaf length, and for novel composite traits, such as shoot compactness. The phenotypic variability associated with some of the quantitative trait loci displayed differences in temporal prevalence; for example, alleles closely linked with the sorghum Dwarf3 gene, an auxin transporter and pleiotropic regulator of both leaf inclination angle and shoot height, influence leaf angle prior to an effect on shoot height. Furthermore, variability in composite phenotypes that measure overall shoot architecture, such as shoot compactness, is regulated by loci underlying component phenotypes like leaf angle. As such, depth imaging is an economical and rapid method to acquire shoot architecture phenotypes in agriculturally important plants like sorghum to study the genetic basis of complex traits.« less

Improved Kalman Filter Method for Measurement Noise Reduction in Multi Sensor RFID Systems

PubMed Central

Eom, Ki Hwan; Lee, Seung Joon; Kyung, Yeo Sun; Lee, Chang Won; Kim, Min Chul; Jung, Kyung Kwon

2011-01-01

Recently, the range of available Radio Frequency Identification (RFID) tags has been widened to include smart RFID tags which can monitor their varying surroundings. One of the most important factors for better performance of smart RFID system is accurate measurement from various sensors. In the multi-sensing environment, some noisy signals are obtained because of the changing surroundings. We propose in this paper an improved Kalman filter method to reduce noise and obtain correct data. Performance of Kalman filter is determined by a measurement and system noise covariance which are usually called the R and Q variables in the Kalman filter algorithm. Choosing a correct R and Q variable is one of the most important design factors for better performance of the Kalman filter. For this reason, we proposed an improved Kalman filter to advance an ability of noise reduction of the Kalman filter. The measurement noise covariance was only considered because the system architecture is simple and can be adjusted by the neural network. With this method, more accurate data can be obtained with smart RFID tags. In a simulation the proposed improved Kalman filter has 40.1%, 60.4% and 87.5% less Mean Squared Error (MSE) than the conventional Kalman filter method for a temperature sensor, humidity sensor and oxygen sensor, respectively. The performance of the proposed method was also verified with some experiments. PMID:22346641

Improved Kalman filter method for measurement noise reduction in multi sensor RFID systems.

PubMed

Eom, Ki Hwan; Lee, Seung Joon; Kyung, Yeo Sun; Lee, Chang Won; Kim, Min Chul; Jung, Kyung Kwon

2011-01-01

Recently, the range of available radio frequency identification (RFID) tags has been widened to include smart RFID tags which can monitor their varying surroundings. One of the most important factors for better performance of smart RFID system is accurate measurement from various sensors. In the multi-sensing environment, some noisy signals are obtained because of the changing surroundings. We propose in this paper an improved Kalman filter method to reduce noise and obtain correct data. Performance of Kalman filter is determined by a measurement and system noise covariance which are usually called the R and Q variables in the Kalman filter algorithm. Choosing a correct R and Q variable is one of the most important design factors for better performance of the Kalman filter. For this reason, we proposed an improved Kalman filter to advance an ability of noise reduction of the Kalman filter. The measurement noise covariance was only considered because the system architecture is simple and can be adjusted by the neural network. With this method, more accurate data can be obtained with smart RFID tags. In a simulation the proposed improved Kalman filter has 40.1%, 60.4% and 87.5% less mean squared error (MSE) than the conventional Kalman filter method for a temperature sensor, humidity sensor and oxygen sensor, respectively. The performance of the proposed method was also verified with some experiments.

3D sorghum reconstructions from depth images identify QTL regulating shoot architecture

DOE PAGES

Mccormick, Ryan F.; Truong, Sandra K.; Mullet, John E.

2016-08-15

Dissecting the genetic basis of complex traits is aided by frequent and nondestructive measurements. Advances in range imaging technologies enable the rapid acquisition of three-dimensional (3D) data from an imaged scene. A depth camera was used to acquire images of sorghum (Sorghum bicolor), an important grain, forage, and bioenergy crop, at multiple developmental time points from a greenhouse-grown recombinant inbred line population. A semiautomated software pipeline was developed and used to generate segmented, 3D plant reconstructions from the images. Automated measurements made from 3D plant reconstructions identified quantitative trait loci for standard measures of shoot architecture, such as shoot height,more » leaf angle, and leaf length, and for novel composite traits, such as shoot compactness. The phenotypic variability associated with some of the quantitative trait loci displayed differences in temporal prevalence; for example, alleles closely linked with the sorghum Dwarf3 gene, an auxin transporter and pleiotropic regulator of both leaf inclination angle and shoot height, influence leaf angle prior to an effect on shoot height. Furthermore, variability in composite phenotypes that measure overall shoot architecture, such as shoot compactness, is regulated by loci underlying component phenotypes like leaf angle. As such, depth imaging is an economical and rapid method to acquire shoot architecture phenotypes in agriculturally important plants like sorghum to study the genetic basis of complex traits.« less

Analysis and validation of ozone variability observed by lidar during the ESCOMPTE-2001 campaign

NASA Astrophysics Data System (ADS)

Ancellet, G.; Ravetta, F.

2005-03-01

An ozone lidar was successfully operated as a ground-based instrument during the ESCOMPTE experiment in June/July 2001. Ozone profiles were measured between 0.5 and 5 km. Moreover, simultaneous measurements of the lidar scattering ratio (SR) at 316 nm diagnosed the diurnal evolution of the PBL top. Comparison of this data set with in-situ measurements by ultralight aircraft (ULM) and balloon soundings supports the existence of well-defined layers over the whole altitude range. Differences between measurements techniques are not due to instrumental inaccuracies but point towards the existence of ozone plumes with sharp horizontal gradients. This is indeed supported by aircraft horizontal cross-section available twice a day at two different levels in the planetary boundary layer (PBL) and the free troposphere. Analysis of the ozone data set has shown a good correlation between surface meteorological conditions, surface ozone measurements and lidar ozone profiles in the PBL. Observed ozone maxima or minima are linked either to sea breeze circulation bringing polluted air masses over the lidar or synoptic flows bringing air with background O 3 values into the region. The observed variability of the ozone field is very large over the whole altitude range. Although it is the result of local temporal variability and advection of spatial inhomogenities, the latter proved to be an important contribution.

Application of Linear Mixed-Effects Models in Human Neuroscience Research: A Comparison with Pearson Correlation in Two Auditory Electrophysiology Studies

PubMed Central

Koerner, Tess K.; Zhang, Yang

2017-01-01

Neurophysiological studies are often designed to examine relationships between measures from different testing conditions, time points, or analysis techniques within the same group of participants. Appropriate statistical techniques that can take into account repeated measures and multivariate predictor variables are integral and essential to successful data analysis and interpretation. This work implements and compares conventional Pearson correlations and linear mixed-effects (LME) regression models using data from two recently published auditory electrophysiology studies. For the specific research questions in both studies, the Pearson correlation test is inappropriate for determining strengths between the behavioral responses for speech-in-noise recognition and the multiple neurophysiological measures as the neural responses across listening conditions were simply treated as independent measures. In contrast, the LME models allow a systematic approach to incorporate both fixed-effect and random-effect terms to deal with the categorical grouping factor of listening conditions, between-subject baseline differences in the multiple measures, and the correlational structure among the predictor variables. Together, the comparative data demonstrate the advantages as well as the necessity to apply mixed-effects models to properly account for the built-in relationships among the multiple predictor variables, which has important implications for proper statistical modeling and interpretation of human behavior in terms of neural correlates and biomarkers. PMID:28264422

An analysis of carbon and radiocarbon profiles across a range ecosystems types

NASA Astrophysics Data System (ADS)

Heckman, K. A.; Gallo, A.; Hatten, J. A.; Swanston, C.; Strahm, B. D.; Sanclements, M.

2016-12-01

Soil carbon stocks have become recognized as increasingly important in the context of climate change and global C cycle modeling. As modelers seek to identify key parameters affecting the size and stability of belowground C stocks, attention has been drawn to the mineral matrix and the soil physiochemical factors influenced by it. Though clay content has often been utilized as a convenient and key explanatory variable for soil C dynamics, its utility has recently come under scrutiny as new paradigms of soil organic matter stabilization have been developed. We utilized soil cores from a range of National Ecological Observatory Network (NEON) experimental plots to examine the influence of mineralogical parameters on soil C stocks and turnover and their relative importance in comparison to climatic variables. Results are presented for a total of 11 NEON sites, spanning Alfisols, Entisols, Mollisols and Spodosols. Soils were sampled by genetic horizon, density separated according to density fractionation: light fractions (particulate organics neither occluded within aggregates nor associated with mineral surfaces), occluded fractions (particulate organics occluded within aggregates), and heavy fractions (organics associated with mineral surfaces). Bulk soils and density fractions were measured for % C and radiocarbon abundance (as a measure of C stability). Carbon and radiocarbon abundances were examined among fractions and in the context of climatic variables (temperature, precipitation, elevation) and soil physiochemical variables (% clay and pH). No direct relationships between temperature and soil C or radiocarbon abundances were found. As a whole, soil radiocarbon abundance in density fractions decreased in the order of light>heavy>occluded, highlighting the importance of both surface sorption and aggregation to the preservation of organics. Radiocarbon concentrations of the heavy fraction (mineral adsorbed) were significantly, though weakly, correlated with pH (r2 = 0.35, p = 0.02), though C concentrations were not. Data suggest an important role for both aggregation and soil chemistry in regulating soil C cycling across a diversity of soil orders. The current presented results serve as a preliminary report on a project spanning 40 NEON sites and a range of physiochemical analyses.

Predicting arsenic in drinking water wells of the Central Valley, California

USGS Publications Warehouse

Ayotte, Joseph; Nolan, Bernard T.; Gronberg, JoAnn M.

2016-01-01

Probabilities of arsenic in groundwater at depths used for domestic and public supply in the Central Valley of California are predicted using weak-learner ensemble models (boosted regression trees, BRT) and more traditional linear models (logistic regression, LR). Both methods captured major processes that affect arsenic concentrations, such as the chemical evolution of groundwater, redox differences, and the influence of aquifer geochemistry. Inferred flow-path length was the most important variable but near-surface-aquifer geochemical data also were significant. A unique feature of this study was that previously predicted nitrate concentrations in three dimensions were themselves predictive of arsenic and indicated an important redox effect at >10 μg/L, indicating low arsenic where nitrate was high. Additionally, a variable representing three-dimensional aquifer texture from the Central Valley Hydrologic Model was an important predictor, indicating high arsenic associated with fine-grained aquifer sediment. BRT outperformed LR at the 5 μg/L threshold in all five predictive performance measures and at 10 μg/L in four out of five measures. BRT yielded higher prediction sensitivity (39%) than LR (18%) at the 10 μg/L threshold–a useful outcome because a major objective of the modeling was to improve our ability to predict high arsenic areas.

Can global navigation satellite system signals reveal the ecological attributes of forests?

NASA Astrophysics Data System (ADS)

Liu, Jingbin; Hyyppä, Juha; Yu, Xiaowei; Jaakkola, Anttoni; Liang, Xinlian; Kaartinen, Harri; Kukko, Antero; Zhu, Lingli; Wang, Yunsheng; Hyyppä, Hannu

2016-08-01

Forests have important impacts on the global carbon cycle and climate, and they are also related to a wide range of industrial sectors. Currently, one of the biggest challenges in forestry research is effectively and accurately measuring and monitoring forest variables, as the exploitation potential of forest inventory products largely depends on the accuracy of estimates and on the cost of data collection. A low-cost crowdsourcing solution is needed for forest inventory to collect forest variables. Here, we propose global navigation satellite system (GNSS) signals as a novel type of observables for predicting forest attributes and show the feasibility of utilizing GNSS signals for estimating important attributes of forest plots, including mean tree height, mean diameter at breast height, basal area, stem volume and tree biomass. The prediction accuracies of the proposed technique were better in boreal forest conditions than those of the conventional techniques of 2D remote sensing. More importantly, this technique provides a novel, cost-effective way of collecting large-scale forest measurements in the crowdsourcing context. This technique can be applied by, for example, harvesters or persons hiking or working in forests because GNSS devices are widely used, and the field operation of this technique is simple and does not require professional forestry skills.

Monthly means of selected climate variables for 1985 - 1989

NASA Technical Reports Server (NTRS)

Schubert, S.; Wu, C.-Y.; Zero, J.; Schemm, J.-K.; Park, C.-K.; Suarez, M.

1992-01-01

Meteorologists are accustomed to viewing instantaneous weather maps, since these contain the most relevant information for the task of producing short-range weather forecasts. Climatologists, on the other hand, tend to deal with long-term means, which portray the average climate. The recent emphasis on dynamical extended-range forecasting and, in particular measuring and predicting short term climate change makes it important that we become accustomed to looking at variations on monthly and longer time scales. A convenient toll for researchers to familiarize themselves with the variability which occurs in selected parameters on these time scales is provided. The format of the document was chosen to help facilitate the intercomparison of various parameters and highlight the year-to-year variability in monthly means.

Physical Exercise Improves Heart Rate Variability in Patients with Type 2 Diabetes: A Systematic Review.

PubMed

Villafaina, Santos; Collado-Mateo, Daniel; Fuentes, Juan Pedro; Merellano-Navarro, Eugenio; Gusi, Narcis

2017-09-23

The aim of the present systematic review is to provide an up-to-date analysis of the research on the effects of exercise programs on heart rate variability (HRV) in individuals with type 2 diabetes mellitus (T2DM). An electronic search of the literature (PubMed, PEDro and Web of Science) was performed. "HRV", "heart rate variability", "exercise", "physical" and "diabetes" were the terms used for article retrieval. Lastly, 15 articles were selected. PRISMA methodology was employed and data were extracted according to the PICOS approach. Although HRV is not routinely measured in the management of T2DM, it is an important measure due to its relation with mortality and diabetic neuropathy. Physical exercise has become a therapy for T2DM, because it improves physical fitness and functional capacity, enhances metabolic control and insulin sensitivity, reduces inflammatory markers and neuropathy symptoms and can increase the regenerative capacity of cutaneous axons, slowing or preventing neuropathy progression. However, it is not clear to what extent physical exercise can improve HRV in this population. Participation in the 15 selected studies was similar in men and women (48.01% men and 51.99% women). All the intervention programs included aerobic training, and it was complemented by strength training in four studies. Duration of physical exercise sessions ranged between 30 and 75 min, the frequency being between 2 and 7 days/week. Statistically significant improvements in groups with diabetes, relative to baseline, were observed in nine studies. More than 3 days per week of aerobic training, complemented by strength training, during at least 3 months seems to improve HRV in T2DM. Weekly frequency might be the most important factor to improve HRV. These aspects could help to design better programs based in scientific evidence, incorporating HRV as an important variable associated with diabetic neuropathy and mortality.

Hydrogeomorphological variability and ecological impacts in straight and restored river reach sections

NASA Astrophysics Data System (ADS)

Schäppi, B.; Molnar, P.; Perona, P.; Tockner, K.; Burlando, P.

2009-04-01

Healthy floodplain ecosystems are characterized by high habitat diversity which tends to be lost in straightened channelized rivers. River restoration projects aim to increase habitat heterogeneity by re-establishing natural flow conditions and/or re-activating geomorphic processes in straightened reaches. The success of such projects is usually measured by means of structural and functional hydrogeomorphic and ecological indicators. Important indicators include flow variables and morphological features such as flow depth, velocity, shore line length, exposed gravel area and wetted river width. Also important are the rates at which these variables and features change under varying streamflow. A high spatial variability in the indicators is generally connected with high habitat diversity. The temporal availability and spatial distribution of both aquatic and riparian habitats control the composition and diversity of benthic organisms, fish, and riparian communities. Spatial heterogeneity provides refugia, i.e. areas from which recolonization after a disturbance event may occur. In addition, it facilitates the transfer of organisms and matter across the aquatic and terrestrial interface, thereby increasing the overall functional performance of coupled river-riparian ecosystems. However the habitat diversity can be maintained over time only if there are frequent disturbances such as periodic floods that reset the system and create new germination sites for pioneer vegetation and rework the channel bed to form new aquatic habitat. Therefore the flow and morphology indicators need to be investigated on spatial as well as on temporal scales. Traditionally, these indicators are measured in the field albeit most measurements can be carried out only at low flow conditions. We propose that flow simulations with a 2d hydrodynamic model may be used for a fast and convenient assessment of indicators of flow variables and morphological features with relatively little calibration required and we illustrate an example thereof. The advantage of using computer simulations as compared to field observations is that a range of discharges can be investigated. Using a flood frequency analysis the return period of simulated flows can be estimated and translated into frequency-dependent habitat types. In order to investigate how flow variables change, we conducted a series of 2d flow simulations at different flow rates along the prealpine Thur River (Switzerland) consisting of both restored and straight reaches. Restoration basically consisted of widening the river cross-section and allowing a natural morphology to form. The simulated flow variables (flow depth and velocity) were then analyzed separately for the two reaches. The distributions of the both variables for the restored reach were significantly different from the straight reach, most notably an increase in the variance was observed. In order to analyze the temporal variability we investigated the development of the riverbed morphology over time using different digital elevation models combined with cross section data measured at annual intervals. Spatially explicit erosion and deposition patterns were derived from this analysis. The riverbed topography at different dates was then used to analyze the temporal evolution of the flow indicators for the different flow conditions. Comparisons between the restored and straight reaches allow us to assess the success of river restoration in terms of flow variability and morphological complexity.

Species associations structured by environment and land-use history promote beta-diversity in a temperate forest.

PubMed

Murphy, Stephen J; Audino, Livia D; Whitacre, James; Eck, Jenalle L; Wenzel, John W; Queenborough, Simon A; Comita, Liza S

2015-03-01

Patterns of diversity and community composition in forests are controlled by a combination of environmental factors, historical events, and stochastic or neutral mechanisms. Each of these processes has been linked to forest community assembly, but their combined contributions to alpha and beta-diversity in forests has not been well explored. Here we use variance partitioning to analyze approximately 40,000 individual trees of 49 species, collected within 137 ha of sampling area spread across a 900-ha temperate deciduous forest reserve in Pennsylvania to ask (1) To what extent is site-to-site variation in species richness and community composition of a temperate forest explained by measured environmental gradients and by spatial descriptors (used here to estimate dispersal-assembly or unmeasured, spatially structured processes)? (2) How does the incorporation of land-use history information increase the importance attributed to deterministic community assembly? and (3) How do the distributions and abundances of individual species within the community correlate with these factors? Environmental variables (i.e., topography, soils, and distance to stream), spatial descriptors (i.e., spatial eigenvectors derived from Cartesian coordinates), and land-use history variables (i.e., land-use type and intensity, forest age, and distance to road), explained about half of the variation in both species richness and community composition. Spatial descriptors explained the most variation, followed by measured environmental variables and then by land- use history. Individual species revealed variable responses to each of these sets of predictor variables. Several species were associated with stream habitats, and others were strictly delimited across opposing north- and south-facing slopes. Several species were also associated with areas that experienced recent (i.e., <100 years) human land-use impacts. These results indicate that deterministic factors, including environmental and land-use history variables, are important drivers of community response. The large amount of "unexplained" variation seen here (about 50%) is commonly observed in other such studies attempting to explain distribution and abundance patterns of plant communities. Determining whether such large fractions of unaccounted for variation are caused by a lack of sufficient data, or are an indication of stochastic features of forest communities globally, will remain an important challenge for ecologists in the future.

Salivary cortisol in ambulatory assessment--some dos, some don'ts, and some open questions.

PubMed

Kudielka, Brigitte M; Gierens, Andrea; Hellhammer, Dirk H; Wüst, Stefan; Schlotz, Wolff

2012-05-01

The impact of stress on health and disease is an important research topic in psychosomatic medicine. Because research on hypothalamic-pituitary-adrenal (HPA) axis regulation under controlled laboratory studies lacks ecological validity, it needs to be complemented by a research program that includes momentary ambulatory assessment. The measurement of salivary cortisol offers the possibility to trace the free steroid hormone concentrations in ambulant settings. Therefore, in this article, we first discuss the role of salivary cortisol in ambulatory monitoring. We start with a brief description of HPA axis regulation, and we then consider cortisol assessments in other organic materials, followed by a presentation of common salivary markers of HPA axis regulation suitable for ambulatory assessment. We further provide an overview on assessment designs and sources of variability within and between subjects (intervening variables), acknowledge the issue of (non)compliance, and address statistical aspects. We further give an overview of associations with psychosocial and health-related variables relevant for ambulatory assessment. Finally, we deal with preanalytical aspects of laboratory salivary cortisol analysis. The relative simplicity of salivary cortisol assessment protocols may lead to an overoptimistic view of the robustness of this method. We thus discuss several important issues related to the collection and storage of saliva samples and present empirical data on the stability of salivary cortisol measurements over time.

Evaluating the importance of policy amenable factors in explaining influenza vaccination: a cross-sectional multinational study

PubMed Central

Wheelock, Ana; Miraldo, Marisa; Thomson, Angus; Vincent, Charles; Sevdalis, Nick

2017-01-01

Objectives Despite continuous efforts to improve influenza vaccination coverage, uptake among high-risk groups remains suboptimal. We aimed to identify policy amenable factors associated with vaccination and to measure their importance in order to assist in the monitoring of vaccination sentiment and the design of communication strategies and interventions to improve vaccination rates. Setting The USA, the UK and France. Participants A total of 2412 participants were surveyed across the three countries. Outcome measures Self-reported influenza vaccination. Methods Between March and April 2014, a stratified random sampling strategy was employed with the aim of obtaining nationally representative samples in the USA, the UK and France through online databases and random-digit dialling. Participants were asked about vaccination practices, perceptions and feelings. Multivariable logistic regression was used to identify factors associated with past influenza vaccination. Results The models were able to explain 64%–80% of the variance in vaccination behaviour. Overall, sociopsychological variables, which are inherently amenable to policy, were better at explaining past vaccination behaviour than demographic, socioeconomic and health variables. Explanatory variables included social influence (physician), influenza and vaccine risk perceptions and traumatic childhood experiences. Conclusions Our results indicate that evidence-based sociopsychological items should be considered for inclusion into national immunisation surveys to gauge the public’s views, identify emerging concerns and thus proactively and opportunely address potential barriers and harness vaccination drivers. PMID:28706088

Correlational analysis and predictive validity of psychological constructs related with pain in fibromyalgia

PubMed Central

2011-01-01

Background Fibromyalgia (FM) is a prevalent and disabling disorder characterized by a history of widespread pain for at least three months. Pain is considered a complex experience in which affective and cognitive aspects are crucial for prognosis. The aim of this study is to assess the importance of pain-related psychological constructs on function and pain in patients with FM. Methods Design Multicentric, naturalistic, one-year follow-up study. Setting and study sample. Patients will be recruited from primary care health centres in the region of Aragon, Spain. Patients considered for inclusion are those aged 18-65 years, able to understand Spanish, who fulfil criteria for primary FM according to the American College of Rheumatology, with no previous psychological treatment. Measurements The variables measured will be the following: main variables (pain assessed with a visual analogue scale and with sphygmomanometer and general function assessed with Fibromyalgia Impact Questionnaire, and), psychological constructs (pain catastrophizing, pain acceptance, mental defeat, psychological inflexibility, perceived injustice, mindfulness, and positive and negative affect), and secondary variables (sociodemographic variables, anxiety and depression assessed with Hospital Anxiety and Depression Scale, and psychiatric interview assessed with MINI). Assessments will be carried at baseline and at one-year follow-up. Main outcome Pain Visual Analogue Scale. Analysis The existence of differences in socio-demographic, main outcome and other variables regarding pain-related psychological constructs will be analysed using Chi Square test for qualitative variables, or Student t test or variance analysis, respectively, for variables fulfilling the normality hypothesis. To assess the predictive value of pain-related psychological construct on main outcome variables at one-year follow-up, use will be made of a logistic regression analysis adjusted for socio-demographic and clinical variables. A Spearman Rho non-parametric correlation matrix will be developed to determine possible overlapping between pain-related psychological constructs. Discussion In recent years, the relevance of cognitive and affective aspects for the treatment of chronic pain, not only in FM but also in other chronic pain diseases, has been widely acknowledged. However, the relative importance of these psychological constructs, the relationship and possible overlapping between them, or the exact meaning of them in pain are not enough known. PMID:21214948

Different Measures of Structural Similarity Tap Different Aspects of Visual Object Processing

PubMed Central

Gerlach, Christian

2017-01-01

The structural similarity of objects has been an important variable in explaining why some objects are easier to categorize at a superordinate level than to individuate, and also why some patients with brain injury have more difficulties in recognizing natural (structurally similar) objects than artifacts (structurally distinct objects). In spite of its merits as an explanatory variable, structural similarity is not a unitary construct, and it has been operationalized in different ways. Furthermore, even though measures of structural similarity have been successful in explaining task and category-effects, this has been based more on implication than on direct empirical demonstrations. Here, the direct influence of two different measures of structural similarity, contour overlap and within-item structural diversity, on object individuation (object decision) and superordinate categorization performance is examined. Both measures can account for performance differences across objects, but in different conditions. It is argued that this reflects differences between the measures in whether they tap: (i) global or local shape characteristics, and (ii) between- or within-category structural similarity. PMID:28861027

Relationship Between Manometric and Videofluoroscopic Measures of Swallow Function in Healthy Adults and Patients Treated for Head and Neck Cancer with Various Modalities

PubMed Central

Rademaker, Alfred W.; Lazarus, Cathy; Boeckxstaens, Guy; Kahrilas, Peter J.; Logemann, Jerilyn A.

2010-01-01

Pharyngeal manometry complements the modified barium swallow with videofluoroscopy (VFS) in diagnosing pressure-related causes of dysphagia. When manometric analysis is not feasible, it would be ideal if pressure information about the swallow could be inferred accurately from the VFS evaluation. Swallowing function was examined using VFS and concurrent manometry in 18 subjects (11 head and neck patients treated with various modalities and 7 healthy adults). Nonparametric univariate and multivariate analyses revealed significant relationships between manometric and fluoroscopic variables. Increases in pressure wave amplitude were significantly correlated with increased duration of tongue base to pharyngeal wall contact, reduced bolus transit times, and oropharyngeal residue. Pharyngeal residue was the most important VFS variable in reflecting pharyngeal pressure measurements. Certain VFS measures were significantly correlated with measures of pressure assessed with manometry. Further research is needed before observations and measures from VFS alone may be deemed sufficient for determining pressure-generation difficulties during the swallow in patients who are unable or unwilling to submit to manometric testing. PMID:18956228

Propagation of uncertainty in nasal spray in vitro performance models using Monte Carlo simulation: Part II. Error propagation during product performance modeling.

PubMed

Guo, Changning; Doub, William H; Kauffman, John F

2010-08-01

Monte Carlo simulations were applied to investigate the propagation of uncertainty in both input variables and response measurements on model prediction for nasal spray product performance design of experiment (DOE) models in the first part of this study, with an initial assumption that the models perfectly represent the relationship between input variables and the measured responses. In this article, we discard the initial assumption, and extended the Monte Carlo simulation study to examine the influence of both input variable variation and product performance measurement variation on the uncertainty in DOE model coefficients. The Monte Carlo simulations presented in this article illustrate the importance of careful error propagation during product performance modeling. Our results show that the error estimates based on Monte Carlo simulation result in smaller model coefficient standard deviations than those from regression methods. This suggests that the estimated standard deviations from regression may overestimate the uncertainties in the model coefficients. Monte Carlo simulations provide a simple software solution to understand the propagation of uncertainty in complex DOE models so that design space can be specified with statistically meaningful confidence levels. (c) 2010 Wiley-Liss, Inc. and the American Pharmacists Association

Weather explains high annual variation in butterfly dispersal

PubMed Central

Rytteri, Susu; Heikkinen, Risto K.; Heliölä, Janne; von Bagh, Peter

2016-01-01

Weather conditions fundamentally affect the activity of short-lived insects. Annual variation in weather is therefore likely to be an important determinant of their between-year variation in dispersal, but conclusive empirical studies are lacking. We studied whether the annual variation of dispersal can be explained by the flight season's weather conditions in a Clouded Apollo (Parnassius mnemosyne) metapopulation. This metapopulation was monitored using the mark–release–recapture method for 12 years. Dispersal was quantified for each monitoring year using three complementary measures: emigration rate (fraction of individuals moving between habitat patches), average residence time in the natal patch, and average distance moved. There was much variation both in dispersal and average weather conditions among the years. Weather variables significantly affected the three measures of dispersal and together with adjusting variables explained 79–91% of the variation observed in dispersal. Different weather variables became selected in the models explaining variation in three dispersal measures apparently because of the notable intercorrelations. In general, dispersal rate increased with increasing temperature, solar radiation, proportion of especially warm days, and butterfly density, and decreased with increasing cloudiness, rainfall, and wind speed. These results help to understand and model annually varying dispersal dynamics of species affected by global warming. PMID:27440662

Microlensing makes lensed quasar time delays significantly time variable

NASA Astrophysics Data System (ADS)

Tie, S. S.; Kochanek, C. S.

2018-01-01

The time delays of gravitationally lensed quasars are generally believed to be unique numbers whose measurement is limited only by the quality of the light curves and the models for the contaminating contribution of gravitational microlensing to the light curves. This belief is incorrect - gravitational microlensing also produces changes in the actual time delays on the ∼day(s) light-crossing time-scale of the emission region. This is due to a combination of the inclination of the disc relative to the line of sight and the differential magnification of the temperature fluctuations producing the variability. We demonstrate this both mathematically and with direct calculations using microlensing magnification patterns. Measuring these delay fluctuations can provide a physical scale for microlensing observations, removing the need for priors on either the microlens masses or the component velocities. That time delays in lensed quasars are themselves time variable likely explains why repeated delay measurements of individual lensed quasars appear to vary by more than their estimated uncertainties. This effect is also a new important systematic problem for attempts to use time delays in lensed quasars for cosmology or to detect substructures (satellites) in lens galaxies.

Determination of riverbank erosion probability using Locally Weighted Logistic Regression

NASA Astrophysics Data System (ADS)

Ioannidou, Elena; Flori, Aikaterini; Varouchakis, Emmanouil A.; Giannakis, Georgios; Vozinaki, Anthi Eirini K.; Karatzas, George P.; Nikolaidis, Nikolaos

2015-04-01

Riverbank erosion is a natural geomorphologic process that affects the fluvial environment. The most important issue concerning riverbank erosion is the identification of the vulnerable locations. An alternative to the usual hydrodynamic models to predict vulnerable locations is to quantify the probability of erosion occurrence. This can be achieved by identifying the underlying relations between riverbank erosion and the geomorphological or hydrological variables that prevent or stimulate erosion. Thus, riverbank erosion can be determined by a regression model using independent variables that are considered to affect the erosion process. The impact of such variables may vary spatially, therefore, a non-stationary regression model is preferred instead of a stationary equivalent. Locally Weighted Regression (LWR) is proposed as a suitable choice. This method can be extended to predict the binary presence or absence of erosion based on a series of independent local variables by using the logistic regression model. It is referred to as Locally Weighted Logistic Regression (LWLR). Logistic regression is a type of regression analysis used for predicting the outcome of a categorical dependent variable (e.g. binary response) based on one or more predictor variables. The method can be combined with LWR to assign weights to local independent variables of the dependent one. LWR allows model parameters to vary over space in order to reflect spatial heterogeneity. The probabilities of the possible outcomes are modelled as a function of the independent variables using a logistic function. Logistic regression measures the relationship between a categorical dependent variable and, usually, one or several continuous independent variables by converting the dependent variable to probability scores. Then, a logistic regression is formed, which predicts success or failure of a given binary variable (e.g. erosion presence or absence) for any value of the independent variables. The erosion occurrence probability can be calculated in conjunction with the model deviance regarding the independent variables tested. The most straightforward measure for goodness of fit is the G statistic. It is a simple and effective way to study and evaluate the Logistic Regression model efficiency and the reliability of each independent variable. The developed statistical model is applied to the Koiliaris River Basin on the island of Crete, Greece. Two datasets of river bank slope, river cross-section width and indications of erosion were available for the analysis (12 and 8 locations). Two different types of spatial dependence functions, exponential and tricubic, were examined to determine the local spatial dependence of the independent variables at the measurement locations. The results show a significant improvement when the tricubic function is applied as the erosion probability is accurately predicted at all eight validation locations. Results for the model deviance show that cross-section width is more important than bank slope in the estimation of erosion probability along the Koiliaris riverbanks. The proposed statistical model is a useful tool that quantifies the erosion probability along the riverbanks and can be used to assist managing erosion and flooding events. Acknowledgements This work is part of an on-going THALES project (CYBERSENSORS - High Frequency Monitoring System for Integrated Water Resources Management of Rivers). The project has been co-financed by the European Union (European Social Fund - ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: THALES. Investing in knowledge society through the European Social Fund.

Demographic and social variables associated with psychiatric and school-related indicators for Asian/Pacific-Islander adolescents.

PubMed

Hishinuma, Earl S; Johnson, Ronald C; Carlton, Barry S; Andrade, Naleen N; Nishimura, Stephanie T; Goebert, Deborah A; Yuen, Noelle Y C; Wegner, Eldon L; Makini, George K; Nahulu, Linda B; Else, Iwalani R N; Chang, Janice Y

2004-12-01

Factors associated with Asian/Pacific-Islander adolescent adjustment is a greatly neglected research area. The purpose of the present study was to investigate the relation between demographic, social and adjustment measures based on a large-scale investigation of Asian/Pacific-Islander youths. A total of 2577 adolescents were surveyed across 4 public schools in Hawai'i during the 1992--1993 school year. Three social variables (number of relatives frequently seen, family support and friends' support) exhibited statistically significant but low correlations. Family support had the highest negative association with the four psychiatric symptoms (depression, anxiety, aggression, substance use). Friends' support was inconsistently associated with the adjustment measures, and the number of relatives frequently seen resulted in negligible effects. In contrast, demographic variables, especially ethnicity, played a much greater role in the association with the four school-related measures (grade-point average, absences, suspensions, conduct infractions). For Asian/Pacific-Islander youths, the quality of the social supports, including family relations, may be particularly important in the adolescents' adjustment. When examining school-related outcomes, demographic variables, with particular emphases on ethnicity and culture, must be considered. When developing and implementing prevention and intervention services and programs, consideration of family and ethnic-cultural influences should be taken into account, with further research needed in several related domains: other SES influences, life stressors, migration-generational effects, ethnic identity, self-concept indicators and socio-political aspects.

Deriving Surface NO2 Mixing Ratios from DISCOVER-AQ ACAM Observations: A Method to Assess Surface NO2 Spatial Variability

NASA Astrophysics Data System (ADS)

Silverman, M. L.; Szykman, J.; Chen, G.; Crawford, J. H.; Janz, S. J.; Kowalewski, M. G.; Lamsal, L. N.; Long, R.

2015-12-01

Studies have shown that satellite NO2 columns are closely related to ground level NO2 concentrations, particularly over polluted areas. This provides a means to assess surface level NO2 spatial variability over a broader area than what can be monitored from ground stations. The characterization of surface level NO2 variability is important to understand air quality in urban areas, emissions, health impacts, photochemistry, and to evaluate the performance of chemical transport models. Using data from the NASA DISCOVER-AQ campaign in Baltimore/Washington we calculate NO2 mixing ratios from the Airborne Compact Atmospheric Mapper (ACAM), through four different methods to derive surface concentration from column measurements. High spectral resolution lidar (HSRL) mixed layer heights, vertical P3B profiles, and CMAQ vertical profiles are used to scale ACAM vertical column densities. The derived NO2 mixing ratios are compared to EPA ground measurements taken at Padonia and Edgewood. We find similar results from scaling with HSRL mixed layer heights and normalized P3B vertical profiles. The HSRL mixed layer heights are then used to scale ACAM vertical column densities across the DISCOVER-AQ flight pattern to assess spatial variability of NO2 over the area. This work will help define the measurement requirements for future satellite instruments.

Using geomorphological variables to predict the spatial distribution of plant species in agricultural drainage networks

PubMed Central

Bailly, Jean-Stéphane; Vinatier, Fabrice

2018-01-01

To optimize ecosystem services provided by agricultural drainage networks (ditches) in headwater catchments, we need to manage the spatial distribution of plant species living in these networks. Geomorphological variables have been shown to be important predictors of plant distribution in other ecosystems because they control the water regime, the sediment deposition rates and the sun exposure in the ditches. Whether such variables may be used to predict plant distribution in agricultural drainage networks is unknown. We collected presence and absence data for 10 herbaceous plant species in a subset of a network of drainage ditches (35 km long) within a Mediterranean agricultural catchment. We simulated their spatial distribution with GLM and Maxent model using geomorphological variables and distance to natural lands and roads. Models were validated using k-fold cross-validation. We then compared the mean Area Under the Curve (AUC) values obtained for each model and other metrics issued from the confusion matrices between observed and predicted variables. Based on the results of all metrics, the models were efficient at predicting the distribution of seven species out of ten, confirming the relevance of geomorphological variables and distance to natural lands and roads to explain the occurrence of plant species in this Mediterranean catchment. In particular, the importance of the landscape geomorphological variables, ie the importance of the geomorphological features encompassing a broad environment around the ditch, has been highlighted. This suggests that agro-ecological measures for managing ecosystem services provided by ditch plants should focus on the control of the hydrological and sedimentological connectivity at the catchment scale. For example, the density of the ditch network could be modified or the spatial distribution of vegetative filter strips used for sediment trapping could be optimized. In addition, the vegetative filter strips could constitute new seed bank sources for species that are affected by the distance to natural lands and roads. PMID:29360857

The Importance of Postural Control in Relation to Technical Abilities in Small-Sided Soccer Games

PubMed Central

Edis, Çağlar; Vurgun, Hikmet

2016-01-01

Abstract Making assessments regarding postural control and balance is very important for injury prevention in soccer. However, there has been no study that has associated postural control variables with branch-specific technical properties in a game. The aim of the present study was to determine the relationships between variables designating postural control levels and technical performance variables in different (1:1, 2:2 and 3:3) small-sided games (SSGs). Sixteen trained male amateur soccer players volunteered to take part in the study (age 17.2 ± 1.02 years, body height 176.25 ± 0.07 m, body mass 67.67 ± 13.27 kg). Following familiarization sessions, postural control was evaluated using one-leg and both-leg quiet-stance positions by measuring postural sway with a Tekscan HR Mat™ in anterior–posterior and medial–lateral directions. Later, 1:1, 2:2 and 3:3 SSGs were performed at two-day intervals and the technical variables specified for each game were analyzed. A Spearman’s rank-order correlation analysis demonstrated the relationship between postural control and soccer-specific technical variables in 1:1 (r-values ranging from 0.582 to 0.776), 2:2 (rvalues ranging from 0.511 to 0.740) and 3:3 (r-values ranging from 0.502 to 0.834) SSGs. In addition, a Wilcoxon signed rank test revealed differences between SSGs in terms of several variables. The results of the study showed that higher postural control levels are among the important variables that affect success in the performance of technical skills under rival pressure and suddenly changing conditions. Therefore, it is recommended that in addition to its use for injury prevention purposes, balance training should be conducted to improve branch-specific technical skills and to increase the levels of their successful performance in a game. PMID:28149410

The Importance of Postural Control in Relation to Technical Abilities in Small-Sided Soccer Games.

PubMed

Edis, Çağlar; Vural, Faik; Vurgun, Hikmet

2016-12-01

Making assessments regarding postural control and balance is very important for injury prevention in soccer. However, there has been no study that has associated postural control variables with branch-specific technical properties in a game. The aim of the present study was to determine the relationships between variables designating postural control levels and technical performance variables in different (1:1, 2:2 and 3:3) small-sided games (SSGs). Sixteen trained male amateur soccer players volunteered to take part in the study (age 17.2 ± 1.02 years, body height 176.25 ± 0.07 m, body mass 67.67 ± 13.27 kg). Following familiarization sessions, postural control was evaluated using one-leg and both-leg quiet-stance positions by measuring postural sway with a Tekscan HR Mat™ in anterior-posterior and medial-lateral directions. Later, 1:1, 2:2 and 3:3 SSGs were performed at two-day intervals and the technical variables specified for each game were analyzed. A Spearman's rank-order correlation analysis demonstrated the relationship between postural control and soccer-specific technical variables in 1:1 (r-values ranging from 0.582 to 0.776), 2:2 (rvalues ranging from 0.511 to 0.740) and 3:3 (r-values ranging from 0.502 to 0.834) SSGs. In addition, a Wilcoxon signed rank test revealed differences between SSGs in terms of several variables. The results of the study showed that higher postural control levels are among the important variables that affect success in the performance of technical skills under rival pressure and suddenly changing conditions. Therefore, it is recommended that in addition to its use for injury prevention purposes, balance training should be conducted to improve branch-specific technical skills and to increase the levels of their successful performance in a game.

Using geomorphological variables to predict the spatial distribution of plant species in agricultural drainage networks.

PubMed

Rudi, Gabrielle; Bailly, Jean-Stéphane; Vinatier, Fabrice

2018-01-01

To optimize ecosystem services provided by agricultural drainage networks (ditches) in headwater catchments, we need to manage the spatial distribution of plant species living in these networks. Geomorphological variables have been shown to be important predictors of plant distribution in other ecosystems because they control the water regime, the sediment deposition rates and the sun exposure in the ditches. Whether such variables may be used to predict plant distribution in agricultural drainage networks is unknown. We collected presence and absence data for 10 herbaceous plant species in a subset of a network of drainage ditches (35 km long) within a Mediterranean agricultural catchment. We simulated their spatial distribution with GLM and Maxent model using geomorphological variables and distance to natural lands and roads. Models were validated using k-fold cross-validation. We then compared the mean Area Under the Curve (AUC) values obtained for each model and other metrics issued from the confusion matrices between observed and predicted variables. Based on the results of all metrics, the models were efficient at predicting the distribution of seven species out of ten, confirming the relevance of geomorphological variables and distance to natural lands and roads to explain the occurrence of plant species in this Mediterranean catchment. In particular, the importance of the landscape geomorphological variables, ie the importance of the geomorphological features encompassing a broad environment around the ditch, has been highlighted. This suggests that agro-ecological measures for managing ecosystem services provided by ditch plants should focus on the control of the hydrological and sedimentological connectivity at the catchment scale. For example, the density of the ditch network could be modified or the spatial distribution of vegetative filter strips used for sediment trapping could be optimized. In addition, the vegetative filter strips could constitute new seed bank sources for species that are affected by the distance to natural lands and roads.

Analysis of the association between isokinetic knee strength with offensive and defensive jumping capacity in high-level female volleyball athletes.

PubMed

Sattler, Tine; Sekulic, Damir; Esco, Michael R; Mahmutovic, Ifet; Hadzic, Vedran

2015-09-01

Isokinetic-knee-strength was hypothesized to be an important factor related to jumping performance. However, studies examining this relation among elite female athletes and sport-specific jumps are lacking. This investigation determined the influence of isokinetic-knee flexor/extensor strength measures on spike-jump (offensive) and block-jump (defensive) performance among high-level female volleyball players. Cross-sectional laboratory study. Eighty-two female volleyball athletes (age = 21.3 ± 3.8 years, height = 175.4 ± 6.76 cm, and weight = 68.29 ± 8.53 kg) volunteered to participate in this study. The studied variables included spike-jump and block-jump performance and a set of isokinetic tests to evaluate the eccentric and concentric strength capacities of the knee extensors (quadriceps - Q), and flexors (hamstring - H) for both legs. Both jumping tests showed high intra-session reliability (ICC of 0.87 and 0.95 for spike-jump and block-jump, respectively). The athletes were clustered into three achievement-groups based on their spike-jump and block-jump performances. For the block-jump, ANOVA identified significant differences between achievement-groups for all isokinetic variables except the Right-Q-Eccentric-Strength. When observed for spike-jump, achievement-groups differed significantly in all tests but Right-H-Concentric-Strength. Discriminant canonical analysis showed that the isokinetic-strength variables were more associated with block-jump then spike-jump-performance. The eccentric isokinetic measures were relatively less important determinants of block-jump than for the spike-jump performance. Data support the hypothesis of the importance of isokinetic strength measures for the expression of rapid muscular performance in volleyball. The results point to the necessity of the differential approach in sport training for defensive and offensive duties. Copyright © 2014 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.