Black Male Labor Force Participation.

ERIC Educational Resources Information Center

Baer, Roger K.

This study attempts to test (via multiple regression analysis) hypothesized relationships between designated independent variables and age specific incidences of labor force participation for black male subpopulations in 54 Standard Metropolitan Statistical Areas. Leading independent variables tested include net migration, earnings, unemployment,…

Advanced statistics: linear regression, part I: simple linear regression.

PubMed

Marill, Keith A

2004-01-01

Simple linear regression is a mathematical technique used to model the relationship between a single independent predictor variable and a single dependent outcome variable. In this, the first of a two-part series exploring concepts in linear regression analysis, the four fundamental assumptions and the mechanics of simple linear regression are reviewed. The most common technique used to derive the regression line, the method of least squares, is described. The reader will be acquainted with other important concepts in simple linear regression, including: variable transformations, dummy variables, relationship to inference testing, and leverage. Simplified clinical examples with small datasets and graphic models are used to illustrate the points. This will provide a foundation for the second article in this series: a discussion of multiple linear regression, in which there are multiple predictor variables.

Post-processing method for wind speed ensemble forecast using wind speed and direction

NASA Astrophysics Data System (ADS)

Sofie Eide, Siri; Bjørnar Bremnes, John; Steinsland, Ingelin

2017-04-01

Statistical methods are widely applied to enhance the quality of both deterministic and ensemble NWP forecasts. In many situations, like wind speed forecasting, most of the predictive information is contained in one variable in the NWP models. However, in statistical calibration of deterministic forecasts it is often seen that including more variables can further improve forecast skill. For ensembles this is rarely taken advantage of, mainly due to that it is generally not straightforward how to include multiple variables. In this study, it is demonstrated how multiple variables can be included in Bayesian model averaging (BMA) by using a flexible regression method for estimating the conditional means. The method is applied to wind speed forecasting at 204 Norwegian stations based on wind speed and direction forecasts from the ECMWF ensemble system. At about 85 % of the sites the ensemble forecasts were improved in terms of CRPS by adding wind direction as predictor compared to only using wind speed. On average the improvements were about 5 %, but mainly for moderate to strong wind situations. For weak wind speeds adding wind direction had more or less neutral impact.

The association between sexual satisfaction and body image in women.

PubMed

Pujols, Yasisca; Seal, Brooke N; Meston, Cindy M

2010-02-01

Although sexual functioning has been linked to sexual satisfaction, it only partially explains the degree to which women report being sexually satisfied. Other factors include quality of life, relational variables, and individual factors such as body image. Of the few studies that have investigated the link between body image and sexual satisfaction, most have considered body image to be a single construct and have shown mixed results. The present study assessed multiple body image variables in order to better understand which aspects of body image influence multiple domains of sexual satisfaction, including sexual communication, compatibility, contentment, personal concern, and relational concern in a community sample of women. Women between the ages of 18 and 49 years in sexual relationships (N = 154) participated in an Internet survey that assessed sexual functioning, five domains of sexual satisfaction, and several body image variables. Body image variables included the sexual attractiveness, weight concern, and physical condition subscales of the Body Esteem Scale, the appearance-based subscale of the Cognitive Distractions During Sexual Activity Scale, and body mass index. Total score of the Sexual Satisfaction Scale for Women was the main outcome measure. Sexual functioning was measured by a modified Female Sexual Function Index. Consistent with expectations, correlations indicated significant positive relationships between sexual functioning, sexual satisfaction, and all body image variables. A multiple regression analysis revealed that sexual satisfaction was predicted by high body esteem and low frequency of appearance-based distracting thoughts during sexual activity, even after controlling for sexual functioning status. Several aspects of body image, including weight concern, physical condition, sexual attractiveness, and thoughts about the body during sexual activity predict sexual satisfaction in women. The findings suggest that women who experience low sexual satisfaction may benefit from treatments that target these specific aspects of body image.

Determinants of Employment Status among People with Multiple Sclerosis.

ERIC Educational Resources Information Center

Roessler, Richard T.; Fitzgerald, Shawn M.; Rumrill, Phillip D.; Koch, Lynn C.

2001-01-01

Identifies factors predicting employment or lack thereof among adults with multiple sclerosis (MS). Results included the following variables as the best predictors of employment: symptom persistence, severity of symptoms, educational attainment, and presence of cognitive limitations. The relevance of the findings for rehabilitation assessment and…

Multiple Case Study of STEM in School-Based Agricultural Education

ERIC Educational Resources Information Center

Stubbs, Eric A.; Myers, Brian E.

2015-01-01

This multiple case study investigated the integration of science, technology, engineering, and mathematics (STEM) in three Florida high school agriculture programs. Observations, interviews, documents, and artifacts provided qualitative data that indicated the types of STEM knowledge taught. Variables of interest included student and teacher…

The Effects of Home-School Dissonance on African American Male High School Students

ERIC Educational Resources Information Center

Brown-Wright, Lynda; Tyler, Kenneth Maurice

2010-01-01

The current study examined associations between home-school dissonance and several academic and psychological variables among 80 African American male high school students. Regression analyses revealed that home-school dissonance significantly predicted multiple academic and psychological variables, including amotivation, academic cheating,…

Upper-Division Student Difficulties with Separation of Variables

ERIC Educational Resources Information Center

Wilcox, Bethany R.; Pollock, Steven J.

2015-01-01

Separation of variables can be a powerful technique for solving many of the partial differential equations that arise in physics contexts. Upper-division physics students encounter this technique in multiple topical areas including electrostatics and quantum mechanics. To better understand the difficulties students encounter when utilizing the…

Soil Cd, Cr, Cu, Ni, Pb and Zn sorption and retention models using SVM: Variable selection and competitive model.

PubMed

González Costa, J J; Reigosa, M J; Matías, J M; Covelo, E F

2017-09-01

The aim of this study was to model the sorption and retention of Cd, Cu, Ni, Pb and Zn in soils. To that extent, the sorption and retention of these metals were studied and the soil characterization was performed separately. Multiple stepwise regression was used to produce multivariate models with linear techniques and with support vector machines, all of which included 15 explanatory variables characterizing soils. When the R-squared values are represented, two different groups are noticed. Cr, Cu and Pb sorption and retention show a higher R-squared; the most explanatory variables being humified organic matter, Al oxides and, in some cases, cation-exchange capacity (CEC). The other group of metals (Cd, Ni and Zn) shows a lower R-squared, and clays are the most explanatory variables, including a percentage of vermiculite and slime. In some cases, quartz, plagioclase or hematite percentages also show some explanatory capacity. Support Vector Machine (SVM) regression shows that the different models are not as regular as in multiple regression in terms of number of variables, the regression for nickel adsorption being the one with the highest number of variables in its optimal model. On the other hand, there are cases where the most explanatory variables are the same for two metals, as it happens with Cd and Cr adsorption. A similar adsorption mechanism is thus postulated. These patterns of the introduction of variables in the model allow us to create explainability sequences. Those which are the most similar to the selectivity sequences obtained by Covelo (2005) are Mn oxides in multiple regression and change capacity in SVM. Among all the variables, the only one that is explanatory for all the metals after applying the maximum parsimony principle is the percentage of sand in the retention process. In the competitive model arising from the aforementioned sequences, the most intense competitiveness for the adsorption and retention of different metals appears between Cr and Cd, Cu and Zn in multiple regression; and between Cr and Cd in SVM regression. Copyright © 2017 Elsevier B.V. All rights reserved.

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

NASA Technical Reports Server (NTRS)

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

2010-01-01

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

Clinical implications of single- versus multiple-site keloid disorder: a retrospective study in an Asian population.

PubMed

Park, Tae Hwan; Park, Ji Hae; Tirgan, Michael H; Halim, Ahmad Sukari; Chang, Choong Hyun

2015-02-01

There is strong evidence of genetic susceptibility in individuals with keloid disorder. The purpose of this cross-sectional study was to determine the clinical relevance of our proposed variables on the multiplicity of keloids by further investigating the presence of other keloids and a family history. This was a retrospective review, using institutional review board-approved questionnaires, of patients with keloids who were seen at Kangbuk Samsung Hospital between December 2002 and February 2010. Eight hundred sixty-eight patients were included in our study. Comparisons between the 2 groups were made using Mann-Whitney tests for continuous variables and χ2 tests for categorical variables. In our patient group, younger age of onset and the presence of family history were significantly associated with the occurrence of keloids at multiple sites. The locations of extra-auricular keloids, in order of frequency, included the shoulder; anterior chest, including the breasts; deltoid; trunk and pubic area; upper extremities; lower extremities; and other sites. As compared to secondary keloids, primary keloids were significantly associated with both a lower degree of recurrence and the presence of other keloids. The presence or absence of family history was significantly associated with the presence or absence of other keloids and primary or secondary keloids. Keloid disorder is one of the most frustrating problems in wound healing and advances in our understanding of the differences of occurrence at a single site versus multiple sites might help in understanding pathogenesis and improving treatment.

Relationship among several measurements of slipperiness obtained in a laboratory environment.

PubMed

Chang, Wen-Ruey; Chang, Chien-Chi

2018-04-01

Multiple sensing mechanisms could be used in forming responses to avoid slips, but previous studies, correlating only two parameters, revealed a limited picture of this complex system. In this study, the participants walked as fast as possible without a slip under 15 conditions of different degrees of slipperiness. The relationships among various response parameters, including perceived slipperiness rating, utilized coefficient of friction (UCOF), slipmeter measurement and kinematic parameters, were evaluated. The results showed that the UCOF, perceived rating and heel angle had higher adjusted R 2 values as dependent variables in the multiple linear regressions with the remaining variables in the final pool as independent variables. Although each variable in the final data pool could reflect some measurement of slipperiness, these three variables are more inclusive than others in representing the other variables and were bigger predictors of other variables, so they could be better candidates for measurements of slipperiness. Copyright © 2017 Elsevier Ltd. All rights reserved.

Climatological Modeling of Monthly Air Temperature and Precipitation in Egypt through GIS Techniques

NASA Astrophysics Data System (ADS)

El Kenawy, A.

2009-09-01

This paper describes a method for modeling and mapping four climatic variables (maximum temperature, minimum temperature, mean temperature and total precipitation) in Egypt using a multiple regression approach implemented in a GIS environment. In this model, a set of variables including latitude, longitude, elevation within a distance of 5, 10 and 15 km, slope, aspect, distance to the Mediterranean Sea, distance to the Red Sea, distance to the Nile, ratio between land and water masses within a radius of 5, 10, 15 km, the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Water Index (NDWI), the Normalized Difference Temperature Index (NDTI) and reflectance are included as independent variables. These variables were integrated as raster layers in MiraMon software at a spatial resolution of 1 km. Climatic variables were considered as dependent variables and averaged from quality controlled and homogenized 39 series distributing across the entire country during the period of (1957-2006). For each climatic variable, digital and objective maps were finally obtained using the multiple regression coefficients at monthly, seasonal and annual timescale. The accuracy of these maps were assessed through cross-validation between predicted and observed values using a set of statistics including coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), mean bias Error (MBE) and D Willmott statistic. These maps are valuable in the sense of spatial resolution as well as the number of observatories involved in the current analysis.

Variability in large-scale wind power generation: Variability in large-scale wind power generation

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

Kiviluoma, Juha; Holttinen, Hannele; Weir, David

2015-10-25

The paper demonstrates the characteristics of wind power variability and net load variability in multiple power systems based on real data from multiple years. Demonstrated characteristics include probability distribution for different ramp durations, seasonal and diurnal variability and low net load events. The comparison shows regions with low variability (Sweden, Spain and Germany), medium variability (Portugal, Ireland, Finland and Denmark) and regions with higher variability (Quebec, Bonneville Power Administration and Electric Reliability Council of Texas in North America; Gansu, Jilin and Liaoning in China; and Norway and offshore wind power in Denmark). For regions with low variability, the maximum 1more » h wind ramps are below 10% of nominal capacity, and for regions with high variability, they may be close to 30%. Wind power variability is mainly explained by the extent of geographical spread, but also higher capacity factor causes higher variability. It was also shown how wind power ramps are autocorrelated and dependent on the operating output level. When wind power was concentrated in smaller area, there were outliers with high changes in wind output, which were not present in large areas with well-dispersed wind power.« less

Clinical Trials With Large Numbers of Variables: Important Advantages of Canonical Analysis.

PubMed

Cleophas, Ton J

2016-01-01

Canonical analysis assesses the combined effects of a set of predictor variables on a set of outcome variables, but it is little used in clinical trials despite the omnipresence of multiple variables. The aim of this study was to assess the performance of canonical analysis as compared with traditional multivariate methods using multivariate analysis of covariance (MANCOVA). As an example, a simulated data file with 12 gene expression levels and 4 drug efficacy scores was used. The correlation coefficient between the 12 predictor and 4 outcome variables was 0.87 (P = 0.0001) meaning that 76% of the variability in the outcome variables was explained by the 12 covariates. Repeated testing after the removal of 5 unimportant predictor and 1 outcome variable produced virtually the same overall result. The MANCOVA identified identical unimportant variables, but it was unable to provide overall statistics. (1) Canonical analysis is remarkable, because it can handle many more variables than traditional multivariate methods such as MANCOVA can. (2) At the same time, it accounts for the relative importance of the separate variables, their interactions and differences in units. (3) Canonical analysis provides overall statistics of the effects of sets of variables, whereas traditional multivariate methods only provide the statistics of the separate variables. (4) Unlike other methods for combining the effects of multiple variables such as factor analysis/partial least squares, canonical analysis is scientifically entirely rigorous. (5) Limitations include that it is less flexible than factor analysis/partial least squares, because only 2 sets of variables are used and because multiple solutions instead of one is offered. We do hope that this article will stimulate clinical investigators to start using this remarkable method.

Statistical methods and regression analysis of stratospheric ozone and meteorological variables in Isfahan

NASA Astrophysics Data System (ADS)

Hassanzadeh, S.; Hosseinibalam, F.; Omidvari, M.

2008-04-01

Data of seven meteorological variables (relative humidity, wet temperature, dry temperature, maximum temperature, minimum temperature, ground temperature and sun radiation time) and ozone values have been used for statistical analysis. Meteorological variables and ozone values were analyzed using both multiple linear regression and principal component methods. Data for the period 1999-2004 are analyzed jointly using both methods. For all periods, temperature dependent variables were highly correlated, but were all negatively correlated with relative humidity. Multiple regression analysis was used to fit the meteorological variables using the meteorological variables as predictors. A variable selection method based on high loading of varimax rotated principal components was used to obtain subsets of the predictor variables to be included in the linear regression model of the meteorological variables. In 1999, 2001 and 2002 one of the meteorological variables was weakly influenced predominantly by the ozone concentrations. However, the model did not predict that the meteorological variables for the year 2000 were not influenced predominantly by the ozone concentrations that point to variation in sun radiation. This could be due to other factors that were not explicitly considered in this study.

The comparison of multiple F-wave variable studies and magnetic resonance imaging examinations in the assessment of cervical radiculopathy.

PubMed

Lin, Chu-Hsu; Tsai, Yuan-Hsiung; Chang, Chia-Hao; Chen, Chien-Min; Hsu, Hung-Chih; Wu, Chun-Yen; Hong, Chang-Zern

2013-09-01

The aims of this study were to investigate the correlation of the findings of multiple median and ulnar F-wave variables and magnetic resonance imaging examinations in the prediction of cervical radiculopathy. The data of 68 patients who underwent both nerve conduction studies of the upper extremities and cervical spine magnetic resonance imaging within 3 mos of the nerve conduction studies were retrospectively reviewed and reinterpreted. The associations between multiple median and ulnar F-wave variables (including persistence, chronodispersion, and minimal, maximal, and mean latencies) and magnetic resonance imaging evidence of lower cervical spondylotic radiculopathy (i.e., C7, C8, and T1 radiculopathy) were investigated. Patients with lower cervical radiculopathy exhibited reduced right median F-wave persistence (P = 0.011), increased right ulnar F-wave chronodispersion (P = 0.041), and a trend toward increased left ulnar F-wave chronodispersion (P = 0.059); however, there were no other consistent significant differences in the F-wave variables between patients with and patients without magnetic resonance imaging evidence of lower cervical radiculopathy. In comparison with normal reference values established previously, the sensitivity and positive predictive value of F-wave variable abnormalities for predicting lower cervical radiculopathy were low. There was a low correlation between F-wave studies and magnetic resonance imaging examinations. The diagnostic utility of multiple F-wave variables in the prediction of cervical radiculopathy was not supported by this study.

Datalist: A Value Added Service to Enable Easy Data Selection

NASA Technical Reports Server (NTRS)

Li, Angela; Hegde, Mahabaleshwa; Bryant, Keith; Seiler, Edward; Shie, Chung-Lin; Teng, William; Liu, Zhong; Hearty, Thomas; Shen, Suhung; Kempler, Steven;

[Non-linear canonical correlation analysis between anthropometric indicators and multiple metabolic abnormalities].

PubMed

Fu, Xiaoli; Liu, Li; Ping, Zhiguang; Li, Linlin

2013-09-01

To define the general correlation between anthropometric indicators and multiple metabolic abnormalities, and to put forward some particular suggestions for the prevention of multiple metabolic abnormalities. A random cluster sampling was carried out in one county of Henan Province. Questionnaire, physical examination and biochemical tests were admitted to the adult inhabitants. Non-linear canonical correlation analysis (NLCCA) was applied with OVERALS of SPSS 13.0. The coefficients of canonical correlation and multiple correlation were calculated. The plot of centroids labeled by variables showed the correlation among various indicators. In total, 2,914 objects were investigated. It included 1,134 (38.9%) males and 1,780 (61.1%) females (60.0%). The average age was (50.58 +/- 13.70) years old. The fitting result of NLCCA were as follows: the loss of 0.577 accounting for 28.8% of the total variation was relatively small, and indicated that the two sets of variables of this study, namely sets of biochemical indicators (including serum total cholesterol, total triglyceride, high-density lipoprotein cholesterol, low density lipoprotein cholesterol and fasting plasma glucose) and sets of others (including gender, BMI and waist circumference) were closely related and often changed synchronously. Multivariate correlation coefficient showed that internal indicators of the above two sets were closely related respectively and often showed the multiple anomalies of the same set. The diagram of the center of gravity of the association of various indicators showed that the symptoms of metabolic abnormalities increased with age. Women were more liable to have metabolic abnormalities. Overweight and obese people often suffer multiple metabolic disorders. Waist circumference was positively correlated with metabolic abnormalities. (1) Biochemical indicators and anthropometric often change in combination. (2) Much attention should be paid to older people especially middle-aged or older men and older women in primary prevention. (3) Overweight and abdominal obesity can be considered the sensitive predictive indicator of multiple metabolic abnormalities. (4) Nonlinear canonical correlation and center of gravity Figure had the advantage of analyze the correlation between multiple sets of variables.

Origins of extrinsic variability in eukaryotic gene expression

NASA Astrophysics Data System (ADS)

Volfson, Dmitri; Marciniak, Jennifer; Blake, William J.; Ostroff, Natalie; Tsimring, Lev S.; Hasty, Jeff

2006-02-01

Variable gene expression within a clonal population of cells has been implicated in a number of important processes including mutation and evolution, determination of cell fates and the development of genetic disease. Recent studies have demonstrated that a significant component of expression variability arises from extrinsic factors thought to influence multiple genes simultaneously, yet the biological origins of this extrinsic variability have received little attention. Here we combine computational modelling with fluorescence data generated from multiple promoter-gene inserts in Saccharomyces cerevisiae to identify two major sources of extrinsic variability. One unavoidable source arising from the coupling of gene expression with population dynamics leads to a ubiquitous lower limit for expression variability. A second source, which is modelled as originating from a common upstream transcription factor, exemplifies how regulatory networks can convert noise in upstream regulator expression into extrinsic noise at the output of a target gene. Our results highlight the importance of the interplay of gene regulatory networks with population heterogeneity for understanding the origins of cellular diversity.

Origins of extrinsic variability in eukaryotic gene expression

NASA Astrophysics Data System (ADS)

Volfson, Dmitri; Marciniak, Jennifer; Blake, William J.; Ostroff, Natalie; Tsimring, Lev S.; Hasty, Jeff

2006-03-01

Variable gene expression within a clonal population of cells has been implicated in a number of important processes including mutation and evolution, determination of cell fates and the development of genetic disease. Recent studies have demonstrated that a significant component of expression variability arises from extrinsic factors thought to influence multiple genes in concert, yet the biological origins of this extrinsic variability have received little attention. Here we combine computational modeling with fluorescence data generated from multiple promoter-gene inserts in Saccharomyces cerevisiae to identify two major sources of extrinsic variability. One unavoidable source arising from the coupling of gene expression with population dynamics leads to a ubiquitous noise floor in expression variability. A second source which is modeled as originating from a common upstream transcription factor exemplifies how regulatory networks can convert noise in upstream regulator expression into extrinsic noise at the output of a target gene. Our results highlight the importance of the interplay of gene regulatory networks with population heterogeneity for understanding the origins of cellular diversity.

Military Enlistments: What Can We Learn from Geographic Variation? Technical Report 620.

ERIC Educational Resources Information Center

Brown, Charles

Some economic variables were examined that affect enlistment decisions and therefore affect the continued success of the All-Volunteer Force. The study used a multiple regression, pooled cross-section/time-series model over the 1975-1982 period, including pay, unemployment, educational benefits, and recruiting resources as independent variables.…

A Simulation Study of Missing Data with Multiple Missing X's

ERIC Educational Resources Information Center

Rubright, Jonathan D.; Nandakumar, Ratna; Glutting, Joseph J.

2014-01-01

When exploring missing data techniques in a realistic scenario, the current literature is limited: most studies only consider consequences with data missing on a single variable. This simulation study compares the relative bias of two commonly used missing data techniques when data are missing on more than one variable. Factors varied include type…

Verification of Causal Influences of Reasoning Skills and Epistemology on Physics Conceptual Learning

ERIC Educational Resources Information Center

Ding, Lin

2014-01-01

This study seeks to test the causal influences of reasoning skills and epistemologies on student conceptual learning in physics. A causal model, integrating multiple variables that were investigated separately in the prior literature, is proposed and tested through path analysis. These variables include student preinstructional reasoning skills…

Fourier analysis of blazar variability

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

Finke, Justin D.; Becker, Peter A., E-mail: justin.finke@nrl.navy.mil

Blazars display strong variability on multiple timescales and in multiple radiation bands. Their variability is often characterized by power spectral densities (PSDs) and time lags plotted as functions of the Fourier frequency. We develop a new theoretical model based on the analysis of the electron transport (continuity) equation, carried out in the Fourier domain. The continuity equation includes electron cooling and escape, and a derivation of the emission properties includes light travel time effects associated with a radiating blob in a relativistic jet. The model successfully reproduces the general shapes of the observed PSDs and predicts specific PSD and timemore » lag behaviors associated with variability in the synchrotron, synchrotron self-Compton, and external Compton emission components, from submillimeter to γ-rays. We discuss applications to BL Lacertae objects and to flat-spectrum radio quasars (FSRQs), where there are hints that some of the predicted features have already been observed. We also find that FSRQs should have steeper γ-ray PSD power-law indices than BL Lac objects at Fourier frequencies ≲ 10{sup –4} Hz, in qualitative agreement with previously reported observations by the Fermi Large Area Telescope.« less

Multi-way multi-group segregation and diversity indices.

PubMed

Gorelick, Root; Bertram, Susan M

2010-06-01

How can we compute a segregation or diversity index from a three-way or multi-way contingency table, where each variable can take on an arbitrary finite number of values and where the index takes values between zero and one? Previous methods only exist for two-way contingency tables or dichotomous variables. A prototypical three-way case is the segregation index of a set of industries or departments given multiple explanatory variables of both sex and race. This can be further extended to other variables, such as disability, number of years of education, and former military service. We extend existing segregation indices based on Euclidean distance (square of coefficient of variation) and Boltzmann/Shannon/Theil index from two-way to multi-way contingency tables by including multiple summations. We provide several biological applications, such as indices for age polyethism and linkage disequilibrium. We also provide a new heuristic conceptualization of entropy-based indices. Higher order association measures are often independent of lower order ones, hence an overall segregation or diversity index should be the arithmetic mean of the normalized association measures at all orders. These methods are applicable when individuals self-identify as multiple races or even multiple sexes and when individuals work part-time in multiple industries. The policy implications of this work are enormous, allowing people to rigorously test whether employment or biological diversity has changed.

The Association Between Sexual Satisfaction and Body Image in Women

PubMed Central

Pujols, Yasisca; Meston, Cindy M.; Seal, Brooke N.

2010-01-01

Introduction Although sexual functioning has been linked to sexual satisfaction, it only partially explains the degree to which women report being sexually satisfied. Other factors include quality of life, relational variables, and individual factors such as body image. Of the few studies that have investigated the link between body image and sexual satisfaction, most have considered body image to be a single construct and have shown mixed results. Aim The present study assessed multiple body image variables in order to better understand which aspects of body image influence multiple domains of sexual satisfaction, including sexual communication, compatibility, contentment, personal concern, and relational concern in a community sample of women. Methods Women between the ages of 18 and 49 years in sexual relationships (N = 154) participated in an Internet survey that assessed sexual functioning, five domains of sexual satisfaction, and several body image variables. Main Outcome Measures Body image variables included the sexual attractiveness, weight concern, and physical condition subscales of the Body Esteem Scale, the appearance-based subscale of the Cognitive Distractions During Sexual Activity Scale, and body mass index. Total score of the Sexual Satisfaction Scale for Women was the main outcome measure. Sexual functioning was measured by a modified Female Sexual Function Index. Results Consistent with expectations, correlations indicated significant positive relationships between sexual functioning, sexual satisfaction, and all body image variables. A multiple regression analysis revealed that sexual satisfaction was predicted by high body esteem and low frequency of appearance-based distracting thoughts during sexual activity, even after controlling for sexual functioning status. Conclusion Several aspects of body image, including weight concern, physical condition, sexual attractiveness, and thoughts about the body during sexual activity predict sexual satisfaction in women. The findings suggest that women who experience low sexual satisfaction may benefit from treatments that target these specific aspects of body image. PMID:19968771

Toroid cavity/coil NMR multi-detector

DOEpatents

Gerald, II, Rex E.; Meadows, Alexander D.; Gregar, Joseph S.; Rathke, Jerome W.

2007-09-18

An analytical device for rapid, non-invasive nuclear magnetic resonance (NMR) spectroscopy of multiple samples using a single spectrometer is provided. A modified toroid cavity/coil detector (TCD), and methods for conducting the simultaneous acquisition of NMR data for multiple samples including a protocol for testing NMR multi-detectors are provided. One embodiment includes a plurality of LC resonant circuits including spatially separated toroid coil inductors, each toroid coil inductor enveloping its corresponding sample volume, and tuned to resonate at a predefined frequency using a variable capacitor. The toroid coil is formed into a loop, where both ends of the toroid coil are brought into coincidence. Another embodiment includes multiple micro Helmholtz coils arranged on a circular perimeter concentric with a central conductor of the toroid cavity.

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

Penna, M.L.; Duchiade, M.P.

The authors report the results of an investigation into the possible association between air pollution and infant mortality from pneumonia in the Rio de Janeiro Metropolitan Area. This investigation employed multiple linear regression analysis (stepwise method) for infant mortality from pneumonia in 1980, including the study population's areas of residence, incomes, and pollution exposure as independent variables. With the income variable included in the regression, a statistically significant association was observed between the average annual level of particulates and infant mortality from pneumonia. While this finding should be accepted with caution, it does suggest a biological association between these variables.more » The authors' conclusion is that air quality indicators should be included in studies of acute respiratory infections in developing countries.« less

Genetic variability in cereal isolates of the Fusarium incarnatum-equiseti species complex

USDA-ARS?s Scientific Manuscript database

The F. incarnatum-equiseti species complex (FIESC) includes fungi associated with diseases of multiple agricultural crops. Although members of FIESC are considered moderately aggressive, they produce diverse mycotoxins, including trichothecenes. Because FIESC exhibits cryptic speciation, DNA-based p...

Regional Climate Simulation and Data Assimilation with Variable-Resolution GCMs

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, Michael S.

2002-01-01

Variable resolution GCMs using a global stretched grid (SG) with enhanced regional resolution over one or multiple areas of interest represents a viable new approach to regional climateklimate change and data assimilation studies and applications. The multiple areas of interest, at least one within each global quadrant, include the major global mountains and major global monsoonal circulations over North America, South America, India-China, and Australia. They also can include the polar domains, and the European and African regions. The SG-approach provides an efficient regional downscaling to mesoscales, and it is an ideal tool for representing consistent interactions of globaYlarge- and regionallmeso- scales while preserving the high quality of global circulation. Basically, the SG-GCM simulations are no different from those of the traditional uniform-grid GCM simulations besides using a variable-resolution grid. Several existing SG-GCMs developed by major centers and groups are briefly described. The major discussion is based on the GEOS (Goddard Earth Observing System) SG-GCM regional climate simulations.

A Decision Support Prototype Tool for Predicting Student Performance in an ODL Environment

ERIC Educational Resources Information Center

Kotsiantis, S. B.; Pintelas, P. E.

2004-01-01

Machine Learning algorithms fed with data sets which include information such as attendance data, test scores and other student information can provide tutors with powerful tools for decision-making. Until now, much of the research has been limited to the relation between single variables and student performance. Combining multiple variables as…

Predicting Middle School Students' Use of Web 2.0 Technologies out of School Using Home and School Technological Variables

ERIC Educational Resources Information Center

Hughes, Joan E.; Read, Michelle F.; Jones, Sara; Mahometa, Michael

2015-01-01

This study used multiple regression to identify predictors of middle school students' Web 2.0 activities out of school, a construct composed of 15 technology activities. Three middle schools participated, where sixth- and seventh-grade students completed a questionnaire. Independent predictor variables included three demographic and five computer…

Earpiece with sensors to measure/monitor multiple physiological variables

NASA Technical Reports Server (NTRS)

Cooper, Tommy G. (Inventor); Schulze, Arthur E. (Inventor)

2003-01-01

An apparatus and method for positioning sensors relative to one another and anatomic features in a non-invasive device for measuring and monitoring multiple physiological variables from a single site uses an earpiece incorporating a shielded pulse oximetry sensor (POS) having a miniaturized set of LEDs and photosensors configured for pulse oximetry measurements in the reflectance mode and located in the earpiece so as to position the POS against a rear wall of an ear canal. The earpiece also includes a thermopile of no larger than 7 mm. in diameter located on the earpiece to so as to position the thermopile past a second turn of an external auditory meatus so as to view the tympanic membrane. The thermopile includes a reference temperature sensor attached to its base for ambient temperature compensation.

System and method for optimal load and source scheduling in context aware homes

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

Shetty, Pradeep; Foslien Graber, Wendy; Mangsuli, Purnaprajna R.

A controller for controlling energy consumption in a home includes a constraints engine to define variables for multiple appliances in the home corresponding to various home modes and persona of an occupant of the home. A modeling engine models multiple paths of energy utilization of the multiple appliances to place the home into a desired state from a current context. An optimal scheduler receives the multiple paths of energy utilization and generates a schedule as a function of the multiple paths and a selected persona to place the home in a desired state.

Effects of Ensemble Configuration on Estimates of Regional Climate Uncertainties

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

Goldenson, N.; Mauger, G.; Leung, L. R.

Internal variability in the climate system can contribute substantial uncertainty in climate projections, particularly at regional scales. Internal variability can be quantified using large ensembles of simulations that are identical but for perturbed initial conditions. Here we compare methods for quantifying internal variability. Our study region spans the west coast of North America, which is strongly influenced by El Niño and other large-scale dynamics through their contribution to large-scale internal variability. Using a statistical framework to simultaneously account for multiple sources of uncertainty, we find that internal variability can be quantified consistently using a large ensemble or an ensemble ofmore » opportunity that includes small ensembles from multiple models and climate scenarios. The latter also produce estimates of uncertainty due to model differences. We conclude that projection uncertainties are best assessed using small single-model ensembles from as many model-scenario pairings as computationally feasible, which has implications for ensemble design in large modeling efforts.« less

[Prediction model of health workforce and beds in county hospitals of Hunan by multiple linear regression].

PubMed

Ling, Ru; Liu, Jiawang

2011-12-01

To construct prediction model for health workforce and hospital beds in county hospitals of Hunan by multiple linear regression. We surveyed 16 counties in Hunan with stratified random sampling according to uniform questionnaires,and multiple linear regression analysis with 20 quotas selected by literature view was done. Independent variables in the multiple linear regression model on medical personnels in county hospitals included the counties' urban residents' income, crude death rate, medical beds, business occupancy, professional equipment value, the number of devices valued above 10 000 yuan, fixed assets, long-term debt, medical income, medical expenses, outpatient and emergency visits, hospital visits, actual available bed days, and utilization rate of hospital beds. Independent variables in the multiple linear regression model on county hospital beds included the the population of aged 65 and above in the counties, disposable income of urban residents, medical personnel of medical institutions in county area, business occupancy, the total value of professional equipment, fixed assets, long-term debt, medical income, medical expenses, outpatient and emergency visits, hospital visits, actual available bed days, utilization rate of hospital beds, and length of hospitalization. The prediction model shows good explanatory and fitting, and may be used for short- and mid-term forecasting.

Shuttle ku-band communications/radar technical concepts

NASA Technical Reports Server (NTRS)

Griffin, J. W.; Kelley, J. S.; Steiner, A. W.; Vang, H. A.; Zrubek, W. E.; Huth, G. K.

1985-01-01

Technical data on the Shuttle Orbiter K sub u-band communications/radar system are presented. The more challenging aspects of the system design and development are emphasized. The technical problems encountered and the advancements made in solving them are discussed. The radar functions are presented first. Requirements and design/implementation approaches are discussed. Advanced features are explained, including Doppler measurement, frequency diversity, multiple pulse repetition frequencies and pulse widths, and multiple modes. The communications functions that are presented include advances made because of the requirements for multiple communications modes. Spread spectrum, quadrature phase shift keying (QPSK), variable bit rates, and other advanced techniques are discussed. Performance results and conclusions reached are outlined.

Relationships between Lifestyle, Living Environments, and Incidence of Hypertension in Japan (in Men): Based on Participant’s Data from the Nationwide Medical Check-Up

PubMed Central

Oka, Mayumi; Yamamoto, Mio; Mure, Kanae; Takeshita, Tatsuya; Arita, Mikio

2016-01-01

This study aims to investigate factors that contribute to the differences in incidence of hypertension between different regions in Japan, by accounting for not only individual lifestyles, but also their living environments. The target participants of this survey were individuals who received medical treatment for hypertension, as well as hypertension patients who have not received any treatment. The objective variable for analysis was the incidence of hypertension as data aggregated per prefecture. We used data (in men) including obesity, salt intake, vegetable intake, habitual alcohol consumption, habitual smoking, and number of steps walked per day. The variables within living environment included number of rail stations, standard/light vehicle usage, and slope of habitable land. In addition, we analyzed data for the variables related to medical environment including, participation rate in medical check-ups and number of hospitals. We performed multiple stepwise regression analyses to elucidate the correlation of these variables by using hypertension incidence as the objective variable. Hypertension incidence showed a significant negative correlation with walking and medical check-ups, and a significant positive correlation with light-vehicle usage and slope. Between the number of steps and variables related to the living environment, number of rail stations showed a significant positive correlation, while, standard- and light-vehicle usage showed significant negative correlation. Moreover, with stepwise multiple regression analysis, walking showed the strongest effect. The differences in daily walking based on living environment were associated with the disparities in the hypertension incidence in Japan. PMID:27788198

Employment among Working-Age Adults with Multiple Sclerosis: A Data-Mining Approach to Identifying Employment Interventions

ERIC Educational Resources Information Center

Bishop, Malachy; Chan, Fong; Rumrill, Phillip D., Jr.; Frain, Michael P.; Tansey, Timothy N.; Chiu, Chung-Yi; Strauser, David; Umeasiegbu, Veronica I.

2015-01-01

Purpose: To examine demographic, functional, and clinical multiple sclerosis (MS) variables affecting employment status in a national sample of adults with MS in the United States. Method: The sample included 4,142 working-age (20-65 years) Americans with MS (79.1% female) who participated in a national survey. The mean age of participants was…

Hierarchical, parallel computing strategies using component object model for process modelling responses of forest plantations to interacting multiple stresses

Treesearch

J. G. Isebrands; G. E. Host; K. Lenz; G. Wu; H. W. Stech

2000-01-01

Process models are powerful research tools for assessing the effects of multiple environmental stresses on forest plantations. These models are driven by interacting environmental variables and often include genetic factors necessary for assessing forest plantation growth over a range of different site, climate, and silvicultural conditions. However, process models are...

Predicting Speech Intelligibility with A Multiple Speech Subsystems Approach in Children with Cerebral Palsy

PubMed Central

Lee, Jimin; Hustad, Katherine C.; Weismer, Gary

2014-01-01

Purpose Speech acoustic characteristics of children with cerebral palsy (CP) were examined with a multiple speech subsystem approach; speech intelligibility was evaluated using a prediction model in which acoustic measures were selected to represent three speech subsystems. Method Nine acoustic variables reflecting different subsystems, and speech intelligibility, were measured in 22 children with CP. These children included 13 with a clinical diagnosis of dysarthria (SMI), and nine judged to be free of dysarthria (NSMI). Data from children with CP were compared to data from age-matched typically developing children (TD). Results Multiple acoustic variables reflecting the articulatory subsystem were different in the SMI group, compared to the NSMI and TD groups. A significant speech intelligibility prediction model was obtained with all variables entered into the model (Adjusted R-squared = .801). The articulatory subsystem showed the most substantial independent contribution (58%) to speech intelligibility. Incremental R-squared analyses revealed that any single variable explained less than 9% of speech intelligibility variability. Conclusions Children in the SMI group have articulatory subsystem problems as indexed by acoustic measures. As in the adult literature, the articulatory subsystem makes the primary contribution to speech intelligibility variance in dysarthria, with minimal or no contribution from other systems. PMID:24824584

Predicting speech intelligibility with a multiple speech subsystems approach in children with cerebral palsy.

PubMed

Lee, Jimin; Hustad, Katherine C; Weismer, Gary

2014-10-01

Speech acoustic characteristics of children with cerebral palsy (CP) were examined with a multiple speech subsystems approach; speech intelligibility was evaluated using a prediction model in which acoustic measures were selected to represent three speech subsystems. Nine acoustic variables reflecting different subsystems, and speech intelligibility, were measured in 22 children with CP. These children included 13 with a clinical diagnosis of dysarthria (speech motor impairment [SMI] group) and 9 judged to be free of dysarthria (no SMI [NSMI] group). Data from children with CP were compared to data from age-matched typically developing children. Multiple acoustic variables reflecting the articulatory subsystem were different in the SMI group, compared to the NSMI and typically developing groups. A significant speech intelligibility prediction model was obtained with all variables entered into the model (adjusted R2 = .801). The articulatory subsystem showed the most substantial independent contribution (58%) to speech intelligibility. Incremental R2 analyses revealed that any single variable explained less than 9% of speech intelligibility variability. Children in the SMI group had articulatory subsystem problems as indexed by acoustic measures. As in the adult literature, the articulatory subsystem makes the primary contribution to speech intelligibility variance in dysarthria, with minimal or no contribution from other systems.

A Unified Framework for Association Analysis with Multiple Related Phenotypes

PubMed Central

Stephens, Matthew

2013-01-01

We consider the problem of assessing associations between multiple related outcome variables, and a single explanatory variable of interest. This problem arises in many settings, including genetic association studies, where the explanatory variable is genotype at a genetic variant. We outline a framework for conducting this type of analysis, based on Bayesian model comparison and model averaging for multivariate regressions. This framework unifies several common approaches to this problem, and includes both standard univariate and standard multivariate association tests as special cases. The framework also unifies the problems of testing for associations and explaining associations – that is, identifying which outcome variables are associated with genotype. This provides an alternative to the usual, but conceptually unsatisfying, approach of resorting to univariate tests when explaining and interpreting significant multivariate findings. The method is computationally tractable genome-wide for modest numbers of phenotypes (e.g. 5–10), and can be applied to summary data, without access to raw genotype and phenotype data. We illustrate the methods on both simulated examples, and to a genome-wide association study of blood lipid traits where we identify 18 potential novel genetic associations that were not identified by univariate analyses of the same data. PMID:23861737

Using a Bayesian network to predict barrier island geomorphologic characteristics

USGS Publications Warehouse

Gutierrez, Ben; Plant, Nathaniel G.; Thieler, E. Robert; Turecek, Aaron

2015-01-01

Quantifying geomorphic variability of coastal environments is important for understanding and describing the vulnerability of coastal topography, infrastructure, and ecosystems to future storms and sea level rise. Here we use a Bayesian network (BN) to test the importance of multiple interactions between barrier island geomorphic variables. This approach models complex interactions and handles uncertainty, which is intrinsic to future sea level rise, storminess, or anthropogenic processes (e.g., beach nourishment and other forms of coastal management). The BN was developed and tested at Assateague Island, Maryland/Virginia, USA, a barrier island with sufficient geomorphic and temporal variability to evaluate our approach. We tested the ability to predict dune height, beach width, and beach height variables using inputs that included longer-term, larger-scale, or external variables (historical shoreline change rates, distances to inlets, barrier width, mean barrier elevation, and anthropogenic modification). Data sets from three different years spanning nearly a decade sampled substantial temporal variability and serve as a proxy for analysis of future conditions. We show that distinct geomorphic conditions are associated with different long-term shoreline change rates and that the most skillful predictions of dune height, beach width, and beach height depend on including multiple input variables simultaneously. The predictive relationships are robust to variations in the amount of input data and to variations in model complexity. The resulting model can be used to evaluate scenarios related to coastal management plans and/or future scenarios where shoreline change rates may differ from those observed historically.

Multicollinearity is a red herring in the search for moderator variables: A guide to interpreting moderated multiple regression models and a critique of Iacobucci, Schneider, Popovich, and Bakamitsos (2016).

PubMed

McClelland, Gary H; Irwin, Julie R; Disatnik, David; Sivan, Liron

2017-02-01

Multicollinearity is irrelevant to the search for moderator variables, contrary to the implications of Iacobucci, Schneider, Popovich, and Bakamitsos (Behavior Research Methods, 2016, this issue). Multicollinearity is like the red herring in a mystery novel that distracts the statistical detective from the pursuit of a true moderator relationship. We show multicollinearity is completely irrelevant for tests of moderator variables. Furthermore, readers of Iacobucci et al. might be confused by a number of their errors. We note those errors, but more positively, we describe a variety of methods researchers might use to test and interpret their moderated multiple regression models, including two-stage testing, mean-centering, spotlighting, orthogonalizing, and floodlighting without regard to putative issues of multicollinearity. We cite a number of recent studies in the psychological literature in which the researchers used these methods appropriately to test, to interpret, and to report their moderated multiple regression models. We conclude with a set of recommendations for the analysis and reporting of moderated multiple regression that should help researchers better understand their models and facilitate generalizations across studies.

A Cautious Note on Auxiliary Variables That Can Increase Bias in Missing Data Problems.

PubMed

Thoemmes, Felix; Rose, Norman

2014-01-01

The treatment of missing data in the social sciences has changed tremendously during the last decade. Modern missing data techniques such as multiple imputation and full-information maximum likelihood are used much more frequently. These methods assume that data are missing at random. One very common approach to increase the likelihood that missing at random is achieved consists of including many covariates as so-called auxiliary variables. These variables are either included based on data considerations or in an inclusive fashion; that is, taking all available auxiliary variables. In this article, we point out that there are some instances in which auxiliary variables exhibit the surprising property of increasing bias in missing data problems. In a series of focused simulation studies, we highlight some situations in which this type of biasing behavior can occur. We briefly discuss possible ways how one can avoid selecting bias-inducing covariates as auxiliary variables.

Variables affecting the financial viability of your practice: a case study.

PubMed

Binderman, J

2001-01-01

Utilizing the discussion of variables affecting practice financial viability, a case study is considered. The case study reveals the relative impact multiple variables have upon the bottom line, including: practice capacity, percentage of capitation, and fee-for-service in the practice, as well as patient visit rates and patient churning. This article presents basic financial information through a case study model, utilizing a series of worksheets that can be adapted to any practice situation to encourage improved financial viability.

Gorlin-Goltz syndrome.

PubMed

Kohli, Munish; Kohli, Monica; Sharma, Naresh; Siddiqui, Saif Rauf; Tulsi, S P S

2010-01-01

Gorlin-Goltz syndrome is an inherited autosomal dominant disorder with complete penetrance and extreme variable expressivity. The authors present a case of an 11-year-old girl with typical features of Gorlin-Goltz syndrome with special respect to medical and dental problems which include multiple bony cage deformities like spina bifida with scoliosis having convexity to the left side, presence of an infantile uterus and multiple odonogenic keratocysts in the maxillofacial region.

Adaptive control of a jet turboshaft engine driving a variable pitch propeller using multiple models

NASA Astrophysics Data System (ADS)

Ahmadian, Narjes; Khosravi, Alireza; Sarhadi, Pouria

2017-08-01

In this paper, a multiple model adaptive control (MMAC) method is proposed for a gas turbine engine. The model of a twin spool turbo-shaft engine driving a variable pitch propeller includes various operating points. Variations in fuel flow and propeller pitch inputs produce different operating conditions which force the controller to be adopted rapidly. Important operating points are three idle, cruise and full thrust cases for the entire flight envelope. A multi-input multi-output (MIMO) version of second level adaptation using multiple models is developed. Also, stability analysis using Lyapunov method is presented. The proposed method is compared with two conventional first level adaptation and model reference adaptive control techniques. Simulation results for JetCat SPT5 turbo-shaft engine demonstrate the performance and fidelity of the proposed method.

Microcephaly, ectodermal dysplasia, multiple skeletal anomalies and distinctive facial appearance: delineation of cerebro-dermato-osseous-dysplasia.

PubMed

Castori, Marco; Pascolini, Giulia; Parisi, Valentina; Sana, Maria Elena; Novelli, Antonio; Nürnberg, Peter; Iascone, Maria; Grammatico, Paola

2015-04-01

In 1980, a novel multiple malformation syndrome has been described in a 17-year-old woman with micro- and turricephaly, intellectual disability, distinctive facial appearance, congenital atrichia, and multiple skeletal anomalies mainly affecting the limbs. Four further sporadic patients and a couple of affected sibs are also reported with a broad clinical variability. Here, we describe a 4-year-old girl strikingly resembling the original report. Phenotype comparison identified a recurrent pattern of multisystem features involving the central nervous system, and skin and bones in five sporadic patients (including ours), while the two sibs and a further sporadic case show significant phenotypic divergence. Marked clinical variability within the same entity versus syndrome splitting is discussed and the term "cerebro-dermato-osseous dysplasia" is introduced to define this condition. © 2015 Wiley Periodicals, Inc.

Intellectual Capital.

ERIC Educational Resources Information Center

Snyder, Herbert W.; Pierce, Jennifer Burek

2002-01-01

This review focuses on intellectual capital and its relationship to information professionals. Discusses asset recognition; national practices and the acceptance of intellectual capital; definitions of intellectual capital; measuring intellectual capital, including multiple and single variable measures; managing intellectual capital; and knowledge…

The Influence of the Student Mobility Rate on the Graduation Rate in the State of New Jersey

ERIC Educational Resources Information Center

Ross, Lavetta S.

2016-01-01

This study examined the influence of the student mobility rate on the high school graduation rate of schools in the state of New Jersey. Variables found to have an influence on the graduation rate in the extant literature were evaluated and reported. The analysis included multiple and hierarchical regression models for school variables (i.e.,…

A Comparison between Multiple Regression Models and CUN-BAE Equation to Predict Body Fat in Adults

PubMed Central

Fuster-Parra, Pilar; Bennasar-Veny, Miquel; Tauler, Pedro; Yañez, Aina; López-González, Angel A.; Aguiló, Antoni

2015-01-01

Background Because the accurate measure of body fat (BF) is difficult, several prediction equations have been proposed. The aim of this study was to compare different multiple regression models to predict BF, including the recently reported CUN-BAE equation. Methods Multi regression models using body mass index (BMI) and body adiposity index (BAI) as predictors of BF will be compared. These models will be also compared with the CUN-BAE equation. For all the analysis a sample including all the participants and another one including only the overweight and obese subjects will be considered. The BF reference measure was made using Bioelectrical Impedance Analysis. Results The simplest models including only BMI or BAI as independent variables showed that BAI is a better predictor of BF. However, adding the variable sex to both models made BMI a better predictor than the BAI. For both the whole group of participants and the group of overweight and obese participants, using simple models (BMI, age and sex as variables) allowed obtaining similar correlations with BF as when the more complex CUN-BAE was used (ρ = 0:87 vs. ρ = 0:86 for the whole sample and ρ = 0:88 vs. ρ = 0:89 for overweight and obese subjects, being the second value the one for CUN-BAE). Conclusions There are simpler models than CUN-BAE equation that fits BF as well as CUN-BAE does. Therefore, it could be considered that CUN-BAE overfits. Using a simple linear regression model, the BAI, as the only variable, predicts BF better than BMI. However, when the sex variable is introduced, BMI becomes the indicator of choice to predict BF. PMID:25821960

A comparison between multiple regression models and CUN-BAE equation to predict body fat in adults.

PubMed

Fuster-Parra, Pilar; Bennasar-Veny, Miquel; Tauler, Pedro; Yañez, Aina; López-González, Angel A; Aguiló, Antoni

2015-01-01

Because the accurate measure of body fat (BF) is difficult, several prediction equations have been proposed. The aim of this study was to compare different multiple regression models to predict BF, including the recently reported CUN-BAE equation. Multi regression models using body mass index (BMI) and body adiposity index (BAI) as predictors of BF will be compared. These models will be also compared with the CUN-BAE equation. For all the analysis a sample including all the participants and another one including only the overweight and obese subjects will be considered. The BF reference measure was made using Bioelectrical Impedance Analysis. The simplest models including only BMI or BAI as independent variables showed that BAI is a better predictor of BF. However, adding the variable sex to both models made BMI a better predictor than the BAI. For both the whole group of participants and the group of overweight and obese participants, using simple models (BMI, age and sex as variables) allowed obtaining similar correlations with BF as when the more complex CUN-BAE was used (ρ = 0:87 vs. ρ = 0:86 for the whole sample and ρ = 0:88 vs. ρ = 0:89 for overweight and obese subjects, being the second value the one for CUN-BAE). There are simpler models than CUN-BAE equation that fits BF as well as CUN-BAE does. Therefore, it could be considered that CUN-BAE overfits. Using a simple linear regression model, the BAI, as the only variable, predicts BF better than BMI. However, when the sex variable is introduced, BMI becomes the indicator of choice to predict BF.

Exploring the Associations Among Nutrition, Science, and Mathematics Knowledge for an Integrative, Food-Based Curriculum.

PubMed

Stage, Virginia C; Kolasa, Kathryn M; Díaz, Sebastián R; Duffrin, Melani W

2018-01-01

Explore associations between nutrition, science, and mathematics knowledge to provide evidence that integrating food/nutrition education in the fourth-grade curriculum may support gains in academic knowledge. Secondary analysis of a quasi-experimental study. Sample included 438 students in 34 fourth-grade classrooms across North Carolina and Ohio; mean age 10 years old; gender (I = 53.2% female; C = 51.6% female). Dependent variable = post-test-nutrition knowledge; independent variables = baseline-nutrition knowledge, and post-test science and mathematics knowledge. Analyses included descriptive statistics and multiple linear regression. The hypothesized model predicted post-nutrition knowledge (F(437) = 149.4, p < .001; Adjusted R = .51). All independent variables were significant predictors with positive association. Science and mathematics knowledge were predictive of nutrition knowledge indicating use of an integrative science and mathematics curriculum to improve academic knowledge may also simultaneously improve nutrition knowledge among fourth-grade students. Teachers can benefit from integration by meeting multiple academic standards, efficiently using limited classroom time, and increasing nutrition education provided in the classroom. © 2018, American School Health Association.

Monitoring and identification of spatiotemporal landscape changes in multiple remote sensing images by using a stratified conditional Latin hypercube sampling approach and geostatistical simulation.

PubMed

Lin, Yu-Pin; Chu, Hone-Jay; Huang, Yu-Long; Tang, Chia-Hsi; Rouhani, Shahrokh

2011-06-01

This study develops a stratified conditional Latin hypercube sampling (scLHS) approach for multiple, remotely sensed, normalized difference vegetation index (NDVI) images. The objective is to sample, monitor, and delineate spatiotemporal landscape changes, including spatial heterogeneity and variability, in a given area. The scLHS approach, which is based on the variance quadtree technique (VQT) and the conditional Latin hypercube sampling (cLHS) method, selects samples in order to delineate landscape changes from multiple NDVI images. The images are then mapped for calibration and validation by using sequential Gaussian simulation (SGS) with the scLHS selected samples. Spatial statistical results indicate that in terms of their statistical distribution, spatial distribution, and spatial variation, the statistics and variograms of the scLHS samples resemble those of multiple NDVI images more closely than those of cLHS and VQT samples. Moreover, the accuracy of simulated NDVI images based on SGS with scLHS samples is significantly better than that of simulated NDVI images based on SGS with cLHS samples and VQT samples, respectively. However, the proposed approach efficiently monitors the spatial characteristics of landscape changes, including the statistics, spatial variability, and heterogeneity of NDVI images. In addition, SGS with the scLHS samples effectively reproduces spatial patterns and landscape changes in multiple NDVI images.

Variables associated with health-related quality of life in a Brazilian sample of patients from a tertiary outpatient clinic for depression and anxiety disorders.

PubMed

Schwab, Bianca; Daniel, Heloisa Silveira; Lutkemeyer, Carine; Neves, João Arthur Lange Lins; Zilli, Louise Nassif; Guarnieri, Ricardo; Diaz, Alexandre Paim; Michels, Ana Maria Maykot Prates

2015-01-01

Health-related quality of life (HRQOL) assessment tools have been broadly used in the medical context. These tools are used to measure the subjective impact of the disease on patients. The objective of this study was to evaluate the variables associated with HRQOL in a Brazilian sample of patients followed up in a tertiary outpatient clinic for depression and anxiety disorders. Cross-sectional study. Independent variables were those included in a sociodemographic questionnaire and the Hospital Anxiety and Depression Scale (HADS) scores. Dependent variables were those included in the short version of the World Health Organization Quality of Life (WHOQOL-BREF) and the scores for its subdomains (overall quality of life and general health, physical health, psychological health, social relationships, and environment). A multiple linear regression analysis was used to find the variables independently associated with each outcome. Seventy-five adult patients were evaluated. After multiple linear regression analysis, the HADS scores were associated with all outcomes, except social relationships (p = 0.08). Female gender was associated with poor total scores, as well as psychological health and environment. Unemployment was associated with poor physical health. Identifying the factors associated with HRQOL and recognizing that depression and anxiety are major factors are essential to improve the care of patients.

Biostatistics Series Module 10: Brief Overview of Multivariate Methods.

PubMed

Hazra, Avijit; Gogtay, Nithya

2017-01-01

Multivariate analysis refers to statistical techniques that simultaneously look at three or more variables in relation to the subjects under investigation with the aim of identifying or clarifying the relationships between them. These techniques have been broadly classified as dependence techniques, which explore the relationship between one or more dependent variables and their independent predictors, and interdependence techniques, that make no such distinction but treat all variables equally in a search for underlying relationships. Multiple linear regression models a situation where a single numerical dependent variable is to be predicted from multiple numerical independent variables. Logistic regression is used when the outcome variable is dichotomous in nature. The log-linear technique models count type of data and can be used to analyze cross-tabulations where more than two variables are included. Analysis of covariance is an extension of analysis of variance (ANOVA), in which an additional independent variable of interest, the covariate, is brought into the analysis. It tries to examine whether a difference persists after "controlling" for the effect of the covariate that can impact the numerical dependent variable of interest. Multivariate analysis of variance (MANOVA) is a multivariate extension of ANOVA used when multiple numerical dependent variables have to be incorporated in the analysis. Interdependence techniques are more commonly applied to psychometrics, social sciences and market research. Exploratory factor analysis and principal component analysis are related techniques that seek to extract from a larger number of metric variables, a smaller number of composite factors or components, which are linearly related to the original variables. Cluster analysis aims to identify, in a large number of cases, relatively homogeneous groups called clusters, without prior information about the groups. The calculation intensive nature of multivariate analysis has so far precluded most researchers from using these techniques routinely. The situation is now changing with wider availability, and increasing sophistication of statistical software and researchers should no longer shy away from exploring the applications of multivariate methods to real-life data sets.

Perceptions of variability in facial emotion influence beliefs about the stability of psychological characteristics.

PubMed

Weisbuch, Max; Grunberg, Rebecca L; Slepian, Michael L; Ambady, Nalini

2016-10-01

Beliefs about the malleability versus stability of traits (incremental vs. entity lay theories) have a profound impact on social cognition and self-regulation, shaping phenomena that range from the fundamental attribution error and group-based stereotyping to academic motivation and achievement. Less is known about the causes than the effects of these lay theories, and in the current work the authors examine the perception of facial emotion as a causal influence on lay theories. Specifically, they hypothesized that (a) within-person variability in facial emotion signals within-person variability in traits and (b) social environments replete with within-person variability in facial emotion encourage perceivers to endorse incremental lay theories. Consistent with Hypothesis 1, Study 1 participants were more likely to attribute dynamic (vs. stable) traits to a person who exhibited several different facial emotions than to a person who exhibited a single facial emotion across multiple images. Hypothesis 2 suggests that social environments support incremental lay theories to the extent that they include many people who exhibit within-person variability in facial emotion. Consistent with Hypothesis 2, participants in Studies 2-4 were more likely to endorse incremental theories of personality, intelligence, and morality after exposure to multiple individuals exhibiting within-person variability in facial emotion than after exposure to multiple individuals exhibiting a single emotion several times. Perceptions of within-person variability in facial emotion-rather than perceptions of simple diversity in facial emotion-were responsible for these effects. Discussion focuses on how social ecologies shape lay theories. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Older age, higher perceived disability and depressive symptoms predict the amount and severity of work-related difficulties in persons with multiple sclerosis.

PubMed

Raggi, Alberto; Giovannetti, Ambra Mara; Schiavolin, Silvia; Brambilla, Laura; Brenna, Greta; Confalonieri, Paolo Agostino; Cortese, Francesca; Frangiamore, Rita; Leonardi, Matilde; Mantegazza, Renato Emilio; Moscatelli, Marco; Ponzio, Michela; Torri Clerici, Valentina; Zaratin, Paola; De Torres, Laura

2018-04-16

This cross-sectional study aims to identify the predictors of work-related difficulties in a sample of employed persons with multiple sclerosis as addressed with the Multiple Sclerosis Questionnaire for Job Difficulties. Hierarchical linear regression analysis was conducted to identify predictors of work difficulties: predictors included demographic variables (age, formal education), disease duration and severity, perceived disability and psychological variables (cognitive dysfunction, depression and anxiety). The targets were the questionnaire's overall score and its six subscales. A total of 177 participants (108 females, aged 21-63) were recruited. Age, perceived disability and depression were direct and significant predictors of the questionnaire total score, and the final model explained 43.7% of its variation. The models built on the questionnaire's subscales show that perceived disability and depression were direct and significant predictors of most of its subscales. Our results show that, among patients with multiple sclerosis, those who were older, with higher perceived disability and higher depression symptoms have more and more severe work-related difficulties. The Multiple Sclerosis Questionnaire for Job Difficulties can be fruitfully exploited to plan tailored actions to limit the likelihood of near-future job loss in persons of working age with multiple sclerosis. Implications for rehabilitation Difficulties with work are common among people with multiple sclerosis and are usually addressed in terms of unemployment or job loss. The Multiple Sclerosis Questionnaire for Job Difficulties is a disease-specific questionnaire developed to address the amount and severity of work-related difficulties. We found that work-related difficulties were associated to older age, higher perceived disability and depressive symptoms. Mental health issues and perceived disability should be consistently included in future research targeting work-related difficulties.

Gorlin-Goltz syndrome

PubMed Central

Kohli, Munish; Kohli, Monica; Sharma, Naresh; Siddiqui, Saif Rauf; Tulsi, S.P.S.

2010-01-01

Gorlin-Goltz syndrome is an inherited autosomal dominant disorder with complete penetrance and extreme variable expressivity. The authors present a case of an 11-year-old girl with typical features of Gorlin-Goltz syndrome with special respect to medical and dental problems which include multiple bony cage deformities like spina bifida with scoliosis having convexity to the left side, presence of an infantile uterus and multiple odonogenic keratocysts in the maxillofacial region. PMID:22442551

A multiple deficit model of reading disability and attention-deficit/hyperactivity disorder: searching for shared cognitive deficits.

PubMed

McGrath, Lauren M; Pennington, Bruce F; Shanahan, Michelle A; Santerre-Lemmon, Laura E; Barnard, Holly D; Willcutt, Erik G; Defries, John C; Olson, Richard K

2011-05-01

This study tests a multiple cognitive deficit model of reading disability (RD), attention-deficit/hyperactivity disorder (ADHD), and their comorbidity. A structural equation model (SEM) of multiple cognitive risk factors and symptom outcome variables was constructed. The model included phonological awareness as a unique predictor of RD and response inhibition as a unique predictor of ADHD. Processing speed, naming speed, and verbal working memory were modeled as potential shared cognitive deficits. Model fit indices from the SEM indicated satisfactory fit. Closer inspection of the path weights revealed that processing speed was the only cognitive variable with significant unique relationships to RD and ADHD dimensions, particularly inattention. Moreover, the significant correlation between reading and inattention was reduced to non-significance when processing speed was included in the model, suggesting that processing speed primarily accounted for the phenotypic correlation (or comorbidity) between reading and inattention. This study illustrates the power of a multiple deficit approach to complex developmental disorders and psychopathologies, particularly for exploring comorbidities. The theoretical role of processing speed in the developmental pathways of RD and ADHD and directions for future research are discussed. © 2010 The Authors. Journal of Child Psychology and Psychiatry © 2010 Association for Child and Adolescent Mental Health.

Meteorological Contribution to Variability in Particulate Matter Concentrations

NASA Astrophysics Data System (ADS)

Woods, H. L.; Spak, S. N.; Holloway, T.

2006-12-01

Local concentrations of fine particulate matter (PM) are driven by a number of processes, including emissions of aerosols and gaseous precursors, atmospheric chemistry, and meteorology at local, regional, and global scales. We apply statistical downscaling methods, typically used for regional climate analysis, to estimate the contribution of regional scale meteorology to PM mass concentration variability at a range of sites in the Upper Midwestern U.S. Multiple years of daily PM10 and PM2.5 data, reported by the U.S. Environmental Protection Agency (EPA), are correlated with large-scale meteorology over the region from the National Centers for Environmental Prediction (NCEP) reanalysis data. We use two statistical downscaling methods (multiple linear regression, MLR, and analog) to identify which processes have the greatest impact on aerosol concentration variability. Empirical Orthogonal Functions of the NCEP meteorological data are correlated with PM timeseries at measurement sites. We examine which meteorological variables exert the greatest influence on PM variability, and which sites exhibit the greatest response to regional meteorology. To evaluate model performance, measurement data are withheld for limited periods, and compared with model results. Preliminary results suggest that regional meteorological processes account over 50% of aerosol concentration variability at study sites.

BOREAS RSS-8 BIOME-BGC Model Simulations at Tower Flux Sites in 1994

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Nickeson, Jaime (Editor); Kimball, John

2000-01-01

BIOME-BGC is a general ecosystem process model designed to simulate biogeochemical and hydrologic processes across multiple scales (Running and Hunt, 1993). In this investigation, BIOME-BGC was used to estimate daily water and carbon budgets for the BOREAS tower flux sites for 1994. Carbon variables estimated by the model include gross primary production (i.e., net photosynthesis), maintenance and heterotrophic respiration, net primary production, and net ecosystem carbon exchange. Hydrologic variables estimated by the model include snowcover, evaporation, transpiration, evapotranspiration, soil moisture, and outflow. The information provided by the investigation includes input initialization and model output files for various sites in tabular ASCII format.

Water Column Variability in Coastal Regions

DTIC Science & Technology

1997-09-30

to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data... 1 . REPORT DATE 30 SEP 1997 2. REPORT TYPE 3. DATES COVERED 00-00-1997 to 00-00-1997 4. TITLE AND SUBTITLE Water Column Variability in...Andrews, Woods, and Kester deployed a spar buoy at a central location in Narragansett Bay to obtain time-series variations at multiple depths ( 1 , 4

Should "Multiple Imputations" Be Treated as "Multiple Indicators"?

ERIC Educational Resources Information Center

Mislevy, Robert J.

1993-01-01

Multiple imputations for latent variables are constructed so that analyses treating them as true variables have the correct expectations for population characteristics. Analyzing multiple imputations in accordance with their construction yields correct estimates of population characteristics, whereas analyzing them as multiple indicators generally…

The Mediated MIMIC Model for Understanding the Underlying Mechanism of DIF.

PubMed

Cheng, Ying; Shao, Can; Lathrop, Quinn N

2016-02-01

Due to its flexibility, the multiple-indicator, multiple-causes (MIMIC) model has become an increasingly popular method for the detection of differential item functioning (DIF). In this article, we propose the mediated MIMIC model method to uncover the underlying mechanism of DIF. This method extends the usual MIMIC model by including one variable or multiple variables that may completely or partially mediate the DIF effect. If complete mediation effect is found, the DIF effect is fully accounted for. Through our simulation study, we find that the mediated MIMIC model is very successful in detecting the mediation effect that completely or partially accounts for DIF, while keeping the Type I error rate well controlled for both balanced and unbalanced sample sizes between focal and reference groups. Because it is successful in detecting such mediation effects, the mediated MIMIC model may help explain DIF and give guidance in the revision of a DIF item.

The Mediated MIMIC Model for Understanding the Underlying Mechanism of DIF

PubMed Central

Cheng, Ying; Shao, Can; Lathrop, Quinn N.

2015-01-01

Due to its flexibility, the multiple-indicator, multiple-causes (MIMIC) model has become an increasingly popular method for the detection of differential item functioning (DIF). In this article, we propose the mediated MIMIC model method to uncover the underlying mechanism of DIF. This method extends the usual MIMIC model by including one variable or multiple variables that may completely or partially mediate the DIF effect. If complete mediation effect is found, the DIF effect is fully accounted for. Through our simulation study, we find that the mediated MIMIC model is very successful in detecting the mediation effect that completely or partially accounts for DIF, while keeping the Type I error rate well controlled for both balanced and unbalanced sample sizes between focal and reference groups. Because it is successful in detecting such mediation effects, the mediated MIMIC model may help explain DIF and give guidance in the revision of a DIF item.

The Power of Algebra.

ERIC Educational Resources Information Center

Boiteau, Denise; Stansfield, David

This document describes mathematical programs on the basic concepts of algebra produced by Louisiana Public Broadcasting. Programs included are: (1) "Inverse Operations"; (2) "The Order of Operations"; (3) "Basic Properties" (addition and multiplication of numbers and variables); (4) "The Positive and Negative…

Inter-individual cognitive variability in children with Asperger's syndrome

PubMed Central

Gonzalez-Gadea, Maria Luz; Tripicchio, Paula; Rattazzi, Alexia; Baez, Sandra; Marino, Julian; Roca, Maria; Manes, Facundo; Ibanez, Agustin

2014-01-01

Multiple studies have tried to establish the distinctive profile of individuals with Asperger's syndrome (AS). However, recent reports suggest that adults with AS feature heterogeneous cognitive profiles. The present study explores inter-individual variability in children with AS through group comparison and multiple case series analysis. All participants completed an extended battery including measures of fluid and crystallized intelligence, executive functions, theory of mind, and classical neuropsychological tests. Significant group differences were found in theory of mind and other domains related to global information processing. However, the AS group showed high inter-individual variability (both sub- and supra-normal performance) on most cognitive tasks. Furthermore, high fluid intelligence correlated with less general cognitive impairment, high cognitive flexibility, and speed of motor processing. In light of these findings, we propose that children with AS are characterized by a distinct, uneven pattern of cognitive strengths and weaknesses. PMID:25132817

Assessment of Communications-related Admissions Criteria in a Three-year Pharmacy Program

PubMed Central

Tejada, Frederick R.; Lang, Lynn A.; Purnell, Miriam; Acedera, Lisa; Ngonga, Ferdinand

2015-01-01

Objective. To determine if there is a correlation between TOEFL and other admissions criteria that assess communications skills (ie, PCAT variables: verbal, reading, essay, and composite), interview, and observational scores and to evaluate TOEFL and these admissions criteria as predictors of academic performance. Methods. Statistical analyses included two sample t tests, multiple regression and Pearson’s correlations for parametric variables, and Mann-Whitney U for nonparametric variables, which were conducted on the retrospective data of 162 students, 57 of whom were foreign-born. Results. The multiple regression model of the other admissions criteria on TOEFL was significant. There was no significant correlation between TOEFL scores and academic performance. However, significant correlations were found between the other admissions criteria and academic performance. Conclusion. Since TOEFL is not a significant predictor of either communication skills or academic success of foreign-born PharmD students in the program, it may be eliminated as an admissions criterion. PMID:26430273

Assessment of Communications-related Admissions Criteria in a Three-year Pharmacy Program.

PubMed

Parmar, Jayesh R; Tejada, Frederick R; Lang, Lynn A; Purnell, Miriam; Acedera, Lisa; Ngonga, Ferdinand

2015-08-25

To determine if there is a correlation between TOEFL and other admissions criteria that assess communications skills (ie, PCAT variables: verbal, reading, essay, and composite), interview, and observational scores and to evaluate TOEFL and these admissions criteria as predictors of academic performance. Statistical analyses included two sample t tests, multiple regression and Pearson's correlations for parametric variables, and Mann-Whitney U for nonparametric variables, which were conducted on the retrospective data of 162 students, 57 of whom were foreign-born. The multiple regression model of the other admissions criteria on TOEFL was significant. There was no significant correlation between TOEFL scores and academic performance. However, significant correlations were found between the other admissions criteria and academic performance. Since TOEFL is not a significant predictor of either communication skills or academic success of foreign-born PharmD students in the program, it may be eliminated as an admissions criterion.

Women's perceptions of their male batterers' characteristics and level of violence.

PubMed

Torres, Sara; Han, Hae-Ra

2003-01-01

This article describes the characteristics of male perpetrators of domestic violence and their relationship to the level of violence. The data about the male partners obtained from 151 battered women were used for this analysis. Using multiple regression, demographic variables and three behavioral indicators, including use of alcohol before a violent episode, history of arrests, and the generality of violence, were examined together for their relationship with the violence scores. With the level of violence as measured by the Conflict Tactics Scale (CTS) as the dependent variable, demographic variables explained 19.1% of the variability, with the behavioral indicators accounting for an additional 4.6% of the variability. Several research and clinical implications are addressed.

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

The Role of Neighborhood Ecological Assets and Activity Involvement in Youth Developmental Outcomes: Differential Impacts of Asset Poor and Asset Rich Neighborhoods

ERIC Educational Resources Information Center

Urban, Jennifer Brown; Lewin-Bizan, Selva; Lerner, Richard M.

2009-01-01

Developmental system theories recognize that variables from multiple levels of organization within the bioecology of human development contribute to adolescent development, including individual factors, family factors and the neighborhood which includes extracurricular activities. Extracurricular activities provide a context for youth development,…

Argentina soybean yield model

NASA Technical Reports Server (NTRS)

Callis, S. L.; Sakamoto, C.

1984-01-01

A model based on multiple regression was developed to estimate soybean yields for the country of Argentina. A meteorological data set was obtained for the country by averaging data for stations within the soybean growing area. Predictor variables for the model were derived from monthly total precipitation and monthly average temperature. A trend variable was included for the years 1969 to 1978 since an increasing trend in yields due to technology was observed between these years.

Moving Beyond Univariate Post-Hoc Testing in Exercise Science: A Primer on Descriptive Discriminate Analysis.

PubMed

Barton, Mitch; Yeatts, Paul E; Henson, Robin K; Martin, Scott B

2016-12-01

There has been a recent call to improve data reporting in kinesiology journals, including the appropriate use of univariate and multivariate analysis techniques. For example, a multivariate analysis of variance (MANOVA) with univariate post hocs and a Bonferroni correction is frequently used to investigate group differences on multiple dependent variables. However, this univariate approach decreases power, increases the risk for Type 1 error, and contradicts the rationale for conducting multivariate tests in the first place. The purpose of this study was to provide a user-friendly primer on conducting descriptive discriminant analysis (DDA), which is a post-hoc strategy to MANOVA that takes into account the complex relationships among multiple dependent variables. A real-world example using the Statistical Package for the Social Sciences syntax and data from 1,095 middle school students on their body composition and body image are provided to explain and interpret the results from DDA. While univariate post hocs increased the risk for Type 1 error to 76%, the DDA identified which dependent variables contributed to group differences and which groups were different from each other. For example, students in the very lean and Healthy Fitness Zone categories for body mass index experienced less pressure to lose weight, more satisfaction with their body, and higher physical self-concept than the Needs Improvement Zone groups. However, perceived pressure to gain weight did not contribute to group differences because it was a suppressor variable. Researchers are encouraged to use DDA when investigating group differences on multiple correlated dependent variables to determine which variables contributed to group differences.

Cognitive declines in healthy aging: evidence from multiple aspects of interference resolution.

PubMed

Pettigrew, Corinne; Martin, Randi C

2014-06-01

The present study tested the hypothesis that older adults show age-related deficits in interference resolution, also referred to as inhibitory control. Although oftentimes considered as a unitary aspect of executive function, various lines of work support the notion that interference resolution may be better understood as multiple constructs, including resistance to proactive interference (PI) and response-distractor inhibition (e.g., Friedman & Miyake, 2004). Using this dichotomy, the present study assessed whether older adults (relative to younger adults) show impaired performance across both, 1, or neither of these interference resolution constructs. To do so, we used multiple tasks to tap each construct and examined age effects at both the single task and latent variable levels. Older adults consistently demonstrated exaggerated interference effects across resistance to PI tasks. Although the results for the response-distractor inhibition tasks were less consistent at the individual task level analyses, age effects were evident on multiple tasks, as well as at the latent variable level. However, results of the latent variable modeling suggested declines in interference resolution are best explained by variance that is common to the 2 interference resolution constructs measured herein. Furthermore, the effect of age on interference resolution was found to be both distinct from declines in working memory, and independent of processing speed. These findings suggest multiple cognitive domains are independently sensitive to age, but that declines in the interference resolution constructs measured herein may originate from a common cause. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Maternal risk factors predicting child physical characteristics and dysmorphology in fetal alcohol syndrome and partial fetal alcohol syndrome.

PubMed

May, Philip A; Tabachnick, Barbara G; Gossage, J Phillip; Kalberg, Wendy O; Marais, Anna-Susan; Robinson, Luther K; Manning, Melanie; Buckley, David; Hoyme, H Eugene

2011-12-01

Previous research in South Africa revealed very high rates of fetal alcohol syndrome (FAS), of 46-89 per 1000 among young children. Maternal and child data from studies in this community summarize the multiple predictors of FAS and partial fetal alcohol syndrome (PFAS). Sequential regression was employed to examine influences on child physical characteristics and dysmorphology from four categories of maternal traits: physical, demographic, childbearing, and drinking. Then, a structural equation model (SEM) was constructed to predict influences on child physical characteristics. Individual sequential regressions revealed that maternal drinking measures were the most powerful predictors of a child's physical anomalies (R² = .30, p < .001), followed by maternal demographics (R² = .24, p < .001), maternal physical characteristics (R²=.15, p < .001), and childbearing variables (R² = .06, p < .001). The SEM utilized both individual variables and the four composite categories of maternal traits to predict a set of child physical characteristics, including a total dysmorphology score. As predicted, drinking behavior is a relatively strong predictor of child physical characteristics (β = 0.61, p < .001), even when all other maternal risk variables are included; higher levels of drinking predict child physical anomalies. Overall, the SEM model explains 62% of the variance in child physical anomalies. As expected, drinking variables explain the most variance. But this highly controlled estimation of multiple effects also reveals a significant contribution played by maternal demographics and, to a lesser degree, maternal physical and childbearing variables. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Probabilistic lifetime strength of aerospace materials via computational simulation

NASA Technical Reports Server (NTRS)

Boyce, Lola; Keating, Jerome P.; Lovelace, Thomas B.; Bast, Callie C.

1991-01-01

The results of a second year effort of a research program are presented. The research included development of methodology that provides probabilistic lifetime strength of aerospace materials via computational simulation. A probabilistic phenomenological constitutive relationship, in the form of a randomized multifactor interaction equation, is postulated for strength degradation of structural components of aerospace propulsion systems subjected to a number of effects of primitive variables. These primitive variables often originate in the environment and may include stress from loading, temperature, chemical, or radiation attack. This multifactor interaction constitutive equation is included in the computer program, PROMISS. Also included in the research is the development of methodology to calibrate the constitutive equation using actual experimental materials data together with the multiple linear regression of that data.

NESSTI: Norms for Environmental Sound Stimuli

PubMed Central

Hocking, Julia; Dzafic, Ilvana; Kazovsky, Maria; Copland, David A.

2013-01-01

In this paper we provide normative data along multiple cognitive and affective variable dimensions for a set of 110 sounds, including living and manmade stimuli. Environmental sounds are being increasingly utilized as stimuli in the cognitive, neuropsychological and neuroimaging fields, yet there is no comprehensive set of normative information for these type of stimuli available for use across these experimental domains. Experiment 1 collected data from 162 participants in an on-line questionnaire, which included measures of identification and categorization as well as cognitive and affective variables. A subsequent experiment collected response times to these sounds. Sounds were normalized to the same length (1 second) in order to maximize usage across multiple paradigms and experimental fields. These sounds can be freely downloaded for use, and all response data have also been made available in order that researchers can choose one or many of the cognitive and affective dimensions along which they would like to control their stimuli. Our hope is that the availability of such information will assist researchers in the fields of cognitive and clinical psychology and the neuroimaging community in choosing well-controlled environmental sound stimuli, and allow comparison across multiple studies. PMID:24023866

Evaluating choices by single neurons in the frontal lobe: outcome value encoded across multiple decision variables

PubMed Central

Kennerley, Steven W.; Wallis, Jonathan D.

2009-01-01

Damage to the frontal lobe can cause severe decision-making impairments. A mechanism that may underlie this is that neurons in the frontal cortex encode many variables that contribute to the valuation of a choice, such as its costs, benefits and probability of success. However, optimal decision-making requires that one considers these variables, not only when faced with the choice, but also when evaluating the outcome of the choice, in order to adapt future behaviour appropriately. To examine the role of the frontal cortex in encoding the value of different choice outcomes, we simultaneously recorded the activity of multiple single neurons in the anterior cingulate cortex (ACC), orbitofrontal cortex (OFC) and lateral prefrontal cortex (LPFC) while subjects evaluated the outcome of choices involving manipulations of probability, payoff and cost. Frontal neurons encoded many of the parameters that enabled the calculation of the value of these variables, including the onset and offset of reward and the amount of work performed, and often encoded the value of outcomes across multiple decision variables. In addition, many neurons encoded both the predicted outcome during the choice phase of the task as well as the experienced outcome in the outcome phase of the task. These patterns of selectivity were more prevalent in ACC relative to OFC and LPFC. These results support a role for the frontal cortex, principally ACC, in selecting between choice alternatives and evaluating the outcome of that selection thereby ensuring that choices are optimal and adaptive. PMID:19453638

Effects of electrofishing gear type on spatial and temporal variability in fish community sampling

USGS Publications Warehouse

Meador, M.R.; McIntyre, J.P.

2003-01-01

Fish community data collected from 24 major river basins between 1993 and 1998 as part of the U.S. Geological Survey's National Water-Quality Assessment Program were analyzed to assess multiple-reach (three consecutive reaches) and multiple-year (three consecutive years) variability in samples collected at a site. Variability was assessed using the coefficient of variation (CV; SD/mean) of species richness, the Jaccard index (JI), and the percent similarity index (PSI). Data were categorized by three electrofishing sample collection methods: backpack, towed barge, and boat. Overall, multiple-reach CV values were significantly lower than those for multiple years, whereas multiple-reach JI and PSI values were significantly greater than those for multiple years. Multiple-reach and multiple-year CV values did not vary significantly among electrofishing methods, although JI and PSI values were significantly greatest for backpack electrofishing across multiple reaches and multiple years. The absolute difference between mean species richness for multiple-reach samples and mean species richness for multiple-year samples was 0.8 species (9.5% of total species richness) for backpack samples, 1.7 species (10.1%) for towed-barge samples, and 4.5 species (24.4%) for boat-collected samples. Review of boat-collected fish samples indicated that representatives of four taxonomic families - Catostomidae, Centrarchidae, Cyprinidae, and Ictaluridae - were collected at all sites. Of these, catostomids exhibited greater interannual variability than centrarchids, cyprinids, or ictalurids. Caution should be exercised when combining boat-collected fish community data from different years because of relatively high interannual variability, which is primarily due to certain relatively mobile species. Such variability may obscure longer-term trends.

How Variables Uncorrelated with the Dependent Variable Can Actually Make Excellent Predictors: The Important Suppressor Variable Case.

ERIC Educational Resources Information Center

Woolley, Kristin K.

Many researchers are unfamiliar with suppressor variables and how they operate in multiple regression analyses. This paper describes the role suppressor variables play in a multiple regression model and provides practical examples that explain how they can change research results. A variable that when added as another predictor increases the total…

Multiple imputation by chained equations for systematically and sporadically missing multilevel data.

PubMed

Resche-Rigon, Matthieu; White, Ian R

2018-06-01

In multilevel settings such as individual participant data meta-analysis, a variable is 'systematically missing' if it is wholly missing in some clusters and 'sporadically missing' if it is partly missing in some clusters. Previously proposed methods to impute incomplete multilevel data handle either systematically or sporadically missing data, but frequently both patterns are observed. We describe a new multiple imputation by chained equations (MICE) algorithm for multilevel data with arbitrary patterns of systematically and sporadically missing variables. The algorithm is described for multilevel normal data but can easily be extended for other variable types. We first propose two methods for imputing a single incomplete variable: an extension of an existing method and a new two-stage method which conveniently allows for heteroscedastic data. We then discuss the difficulties of imputing missing values in several variables in multilevel data using MICE, and show that even the simplest joint multilevel model implies conditional models which involve cluster means and heteroscedasticity. However, a simulation study finds that the proposed methods can be successfully combined in a multilevel MICE procedure, even when cluster means are not included in the imputation models.

An open-source software package for multivariate modeling and clustering: applications to air quality management.

PubMed

Wang, Xiuquan; Huang, Guohe; Zhao, Shan; Guo, Junhong

2015-09-01

This paper presents an open-source software package, rSCA, which is developed based upon a stepwise cluster analysis method and serves as a statistical tool for modeling the relationships between multiple dependent and independent variables. The rSCA package is efficient in dealing with both continuous and discrete variables, as well as nonlinear relationships between the variables. It divides the sample sets of dependent variables into different subsets (or subclusters) through a series of cutting and merging operations based upon the theory of multivariate analysis of variance (MANOVA). The modeling results are given by a cluster tree, which includes both intermediate and leaf subclusters as well as the flow paths from the root of the tree to each leaf subcluster specified by a series of cutting and merging actions. The rSCA package is a handy and easy-to-use tool and is freely available at http://cran.r-project.org/package=rSCA . By applying the developed package to air quality management in an urban environment, we demonstrate its effectiveness in dealing with the complicated relationships among multiple variables in real-world problems.

Bayesian dynamical systems modelling in the social sciences.

PubMed

Ranganathan, Shyam; Spaiser, Viktoria; Mann, Richard P; Sumpter, David J T

2014-01-01

Data arising from social systems is often highly complex, involving non-linear relationships between the macro-level variables that characterize these systems. We present a method for analyzing this type of longitudinal or panel data using differential equations. We identify the best non-linear functions that capture interactions between variables, employing Bayes factor to decide how many interaction terms should be included in the model. This method punishes overly complicated models and identifies models with the most explanatory power. We illustrate our approach on the classic example of relating democracy and economic growth, identifying non-linear relationships between these two variables. We show how multiple variables and variable lags can be accounted for and provide a toolbox in R to implement our approach.

Exploring the facilitators and barriers to engagement in physical activity for people with multiple sclerosis.

PubMed

Kayes, Nicola M; McPherson, Kathryn M; Schluter, Philip; Taylor, Denise; Leete, Marta; Kolt, Gregory S

2011-01-01

To explore the relationship that cognitive behavioural and other previously identified variables have with physical activity engagement in people with multiple sclerosis (MS). This study adopted a cross-sectional questionnaire design. Participants were 282 individuals with MS. Outcome measures included the Physical Activity Disability Survey--Revised, Cognitive and Behavioural Responses to Symptoms Questionnaire, Barriers to Health Promoting Activities for Disabled Persons Scale, Multiple Sclerosis Self-efficacy Scale, Self-Efficacy for Chronic Diseases Scales and Chalder Fatigue Questionnaire. Multivariable stepwise regression analyses found that greater self-efficacy, greater reported mental fatigue and lower number of perceived barriers to physical activity accounted for a significant proportion of variance in physical activity behaviour, over that accounted for by illness-related variables. Although fear-avoidance beliefs accounted for a significant proportion of variance in the initial analyses, its effect was explained by other factors in the final multivariable analyses. Self-efficacy, mental fatigue and perceived barriers to physical activity are potentially modifiable variables which could be incorporated into interventions designed to improve physical activity engagement. Future research should explore whether a measurement tool tailored to capture beliefs about physical activity identified by people with MS would better predict participation in physical activity.

Does weather shape rodents? Climate related changes in morphology of two heteromyid species

NASA Astrophysics Data System (ADS)

Wolf, Mosheh; Friggens, Michael; Salazar-Bravo, Jorge

2009-01-01

Geographical variation in morphometric characters in heteromyid rodents has often correlated with climate gradients. Here, we used the long-term database of rodents trapped in the Sevilleta National Wildlife Refuge in New Mexico, USA to test whether significant annual changes in external morphometric characters are observed in a region with large variations in temperature and precipitation. We looked at the relationships between multiple temperature and precipitation variables and a number of morphological traits (body mass, body, tail, hind leg, and ear length) for two heteromyid rodents, Dipodomys merriami and Perognathus flavescens. Because these rodents can live multiple years in the wild, the climate variables for the year of the capture and the previous 2 years were included in the analyses. Using multiple linear regressions, we found that all of our morphometric traits, with the exception of tail length in D. merriami, had a significant relationship with one or more of the climate variables used. Our results demonstrate that effects of climate change on morphological traits occur over short periods, even in noninsular mammal populations. It is unclear, though, whether these changes are the result of morphological plasticity or natural selection.

A multiple-time-scale turbulence model based on variable partitioning of turbulent kinetic energy spectrum

NASA Technical Reports Server (NTRS)

Kim, S.-W.; Chen, C.-P.

1987-01-01

A multiple-time-scale turbulence model of a single point closure and a simplified split-spectrum method is presented. In the model, the effect of the ratio of the production rate to the dissipation rate on eddy viscosity is modeled by use of the multiple-time-scales and a variable partitioning of the turbulent kinetic energy spectrum. The concept of a variable partitioning of the turbulent kinetic energy spectrum and the rest of the model details are based on the previously reported algebraic stress turbulence model. Example problems considered include: a fully developed channel flow, a plane jet exhausting into a moving stream, a wall jet flow, and a weakly coupled wake-boundary layer interaction flow. The computational results compared favorably with those obtained by using the algebraic stress turbulence model as well as experimental data. The present turbulence model, as well as the algebraic stress turbulence model, yielded significantly improved computational results for the complex turbulent boundary layer flows, such as the wall jet flow and the wake boundary layer interaction flow, compared with available computational results obtained by using the standard kappa-epsilon turbulence model.

A multiple-time-scale turbulence model based on variable partitioning of the turbulent kinetic energy spectrum

NASA Technical Reports Server (NTRS)

Kim, S.-W.; Chen, C.-P.

1989-01-01

A multiple-time-scale turbulence model of a single point closure and a simplified split-spectrum method is presented. In the model, the effect of the ratio of the production rate to the dissipation rate on eddy viscosity is modeled by use of the multiple-time-scales and a variable partitioning of the turbulent kinetic energy spectrum. The concept of a variable partitioning of the turbulent kinetic energy spectrum and the rest of the model details are based on the previously reported algebraic stress turbulence model. Example problems considered include: a fully developed channel flow, a plane jet exhausting into a moving stream, a wall jet flow, and a weakly coupled wake-boundary layer interaction flow. The computational results compared favorably with those obtained by using the algebraic stress turbulence model as well as experimental data. The present turbulence model, as well as the algebraic stress turbulence model, yielded significantly improved computational results for the complex turbulent boundary layer flows, such as the wall jet flow and the wake boundary layer interaction flow, compared with available computational results obtained by using the standard kappa-epsilon turbulence model.

SeqFIRE: a web application for automated extraction of indel regions and conserved blocks from protein multiple sequence alignments.

PubMed

Ajawatanawong, Pravech; Atkinson, Gemma C; Watson-Haigh, Nathan S; Mackenzie, Bryony; Baldauf, Sandra L

2012-07-01

Analyses of multiple sequence alignments generally focus on well-defined conserved sequence blocks, while the rest of the alignment is largely ignored or discarded. This is especially true in phylogenomics, where large multigene datasets are produced through automated pipelines. However, some of the most powerful phylogenetic markers have been found in the variable length regions of multiple alignments, particularly insertions/deletions (indels) in protein sequences. We have developed Sequence Feature and Indel Region Extractor (SeqFIRE) to enable the automated identification and extraction of indels from protein sequence alignments. The program can also extract conserved blocks and identify fast evolving sites using a combination of conservation and entropy. All major variables can be adjusted by the user, allowing them to identify the sets of variables most suited to a particular analysis or dataset. Thus, all major tasks in preparing an alignment for further analysis are combined in a single flexible and user-friendly program. The output includes a numbered list of indels, alignments in NEXUS format with indels annotated or removed and indel-only matrices. SeqFIRE is a user-friendly web application, freely available online at www.seqfire.org/.

Visual variability affects early verb learning.

PubMed

Twomey, Katherine E; Lush, Lauren; Pearce, Ruth; Horst, Jessica S

2014-09-01

Research demonstrates that within-category visual variability facilitates noun learning; however, the effect of visual variability on verb learning is unknown. We habituated 24-month-old children to a novel verb paired with an animated star-shaped actor. Across multiple trials, children saw either a single action from an action category (identical actions condition, for example, travelling while repeatedly changing into a circle shape) or multiple actions from that action category (variable actions condition, for example, travelling while changing into a circle shape, then a square shape, then a triangle shape). Four test trials followed habituation. One paired the habituated verb with a new action from the habituated category (e.g., 'dacking' + pentagon shape) and one with a completely novel action (e.g., 'dacking' + leg movement). The others paired a new verb with a new same-category action (e.g., 'keefing' + pentagon shape), or a completely novel category action (e.g., 'keefing' + leg movement). Although all children discriminated novel verb/action pairs, children in the identical actions condition discriminated trials that included the completely novel verb, while children in the variable actions condition discriminated the out-of-category action. These data suggest that - as in noun learning - visual variability affects verb learning and children's ability to form action categories. © 2014 The British Psychological Society.

A Survey of Phase Variable Candidates of Human Locomotion

PubMed Central

Villarreal, Dario J.; Gregg, Robert D.

2014-01-01

Studies show that the human nervous system is able to parameterize gait cycle phase using sensory feedback. In the field of bipedal robots, the concept of a phase variable has been successfully used to mimic this behavior by parameterizing the gait cycle in a time-independent manner. This approach has been applied to control a powered transfemoral prosthetic leg, but the proposed phase variable was limited to the stance period of the prosthesis only. In order to achieve a more robust controller, we attempt to find a new phase variable that fully parameterizes the gait cycle of a prosthetic leg. The angle with respect to a global reference frame at the hip is able to monotonically parameterize both the stance and swing periods of the gait cycle. This survey looks at multiple phase variable candidates involving the hip angle with respect to a global reference frame across multiple tasks including level-ground walking, running, and stair negotiation. In particular, we propose a novel phase variable candidate that monotonically parameterizes the whole gait cycle across all tasks, and does so particularly well across level-ground walking. In addition to furthering the design of robust robotic prosthetic leg controllers, this survey could help neuroscientists and physicians study human locomotion across tasks from a time-independent perspective. PMID:25570873

POLO2: a user's guide to multiple Probit Or LOgit analysis

Treesearch

Robert M. Russell; N. E. Savin; Jacqueline L. Robertson

1981-01-01

This guide provides instructions for the use of POLO2, a computer program for multivariate probit or logic analysis of quantal response data. As many as 3000 test subjects may be included in a single analysis. Including the constant term, up to nine explanatory variables may be used. Examples illustrating input, output, and uses of the program's special features...

Argentina wheat yield model

NASA Technical Reports Server (NTRS)

Callis, S. L.; Sakamoto, C.

1984-01-01

Five models based on multiple regression were developed to estimate wheat yields for the five wheat growing provinces of Argentina. Meteorological data sets were obtained for each province by averaging data for stations within each province. Predictor variables for the models were derived from monthly total precipitation, average monthly mean temperature, and average monthly maximum temperature. Buenos Aires was the only province for which a trend variable was included because of increasing trend in yield due to technology from 1950 to 1963.

Argentina corn yield model

NASA Technical Reports Server (NTRS)

Callis, S. L.; Sakamoto, C.

1984-01-01

A model based on multiple regression was developed to estimate corn yields for the country of Argentina. A meteorological data set was obtained for the country by averaging data for stations within the corn-growing area. Predictor variables for the model were derived from monthly total precipitation, average monthly mean temperature, and average monthly maximum temperature. A trend variable was included for the years 1965 to 1980 since an increasing trend in yields due to technology was observed between these years.

The influence of talker and foreign-accent variability on spoken word identification.

PubMed

Bent, Tessa; Holt, Rachael Frush

2013-03-01

In spoken word identification and memory tasks, stimulus variability from numerous sources impairs performance. In the current study, the influence of foreign-accent variability on spoken word identification was evaluated in two experiments. Experiment 1 used a between-subjects design to test word identification in noise in single-talker and two multiple-talker conditions: multiple talkers with the same accent and multiple talkers with different accents. Identification performance was highest in the single-talker condition, but there was no difference between the single-accent and multiple-accent conditions. Experiment 2 further explored word recognition for multiple talkers in single-accent versus multiple-accent conditions using a mixed design. A detriment to word recognition was observed in the multiple-accent condition compared to the single-accent condition, but the effect differed across the language backgrounds tested. These results demonstrate that the processing of foreign-accent variation may influence word recognition in ways similar to other sources of variability (e.g., speaking rate or style) in that the inclusion of multiple foreign accents can result in a small but significant performance decrement beyond the multiple-talker effect.

Diffusion-weighted magnetic resonance imaging in the characterization of testicular germ cell neoplasms: Effect of ROI methods on apparent diffusion coefficient values and interobserver variability.

PubMed

Tsili, Athina C; Ntorkou, Alexandra; Astrakas, Loukas; Xydis, Vasilis; Tsampalas, Stavros; Sofikitis, Nikolaos; Argyropoulou, Maria I

2017-04-01

To evaluate the difference in apparent diffusion coefficient (ADC) measurements at diffusion-weighted (DW) magnetic resonance imaging of differently shaped regions-of-interest (ROIs) in testicular germ cell neoplasms (TGCNS), the diagnostic ability of differently shaped ROIs in differentiating seminomas from nonseminomatous germ cell neoplasms (NSGCNs) and the interobserver variability. Thirty-three TGCNs were retrospectively evaluated. Patients underwent MR examinations, including DWI on a 1.5-T MR system. Two observers measured mean tumor ADCs using four distinct ROI methods: round, square, freehand and multiple small, round ROIs. The interclass correlation coefficient was analyzed to assess interobserver variability. Statistical analysis was used to compare mean ADC measurements among observers, methods and histologic types. All ROI methods showed excellent interobserver agreement, with excellent correlation (P<0.001). Multiple, small ROIs provided the lower mean ADC in TGCNs. Seminomas had lower mean ADC compared to NSGCNs for each ROI method (P<0.001). Round ROI proved the most accurate method in characterizing TGCNS. Interobserver variability in ADC measurement is excellent, irrespective of the ROI shape. Multiple, small round ROIs and round ROI proved the more accurate methods for ADC measurement in the characterization of TGCNs and in the differentiation between seminomas and NSGCNs, respectively. Copyright © 2017 Elsevier B.V. All rights reserved.

Sharing Teaching Ideas.

ERIC Educational Resources Information Center

Mathematics Teacher, 1985

1985-01-01

Discusses: (1) use of matrix techniques to write secret codes (includes ready-to-duplicate worksheets); (2) a method of multiplication and division of polynomials in one variable that is not tedius, time-consuming, or dependent on guesswork; and (3) adding and subtracting rational expressions and solving rational equations. (JN)

Multi-scale monitoring for improved nutrient management

USDA-ARS?s Scientific Manuscript database

In many watersheds, monitoring at the outlet of small watersheds has not been able to demonstrate that conservation efforts have had any impact on stream water quality. Reasons are multiple including legacy issues, time for the conservation practices to have any benefit, temporal variability of weat...

How Do We Match Instructional Effectiveness with Learning Curves?

ERIC Educational Resources Information Center

Branum-Martin, Lee; Mehta, Paras D.; Taylor, W. Patrick; Carlson, Coleen D.; Lei, Xiaoxuan; Hunter, C. Vincent; Francis, David J.

2015-01-01

In order to examine the effectiveness of instruction, the authors confront formidable statistical problems, including multivariate structure of classroom observations, longitudinal dependence of both classroom observations and student outcomes. As the authors begin to examine instruction, classroom observations involve multiple variables for which…

Neurofibromatosis.

PubMed

Korf, Bruce R

2013-01-01

The "neurofibromatoses" are a set of distinct genetic disorders that have in common the occurrence of tumors of the nerve sheath. They include NF1, NF2, and schwannomatosis. All are dominantly inherited with a high rate of new mutation and variable expression. NF1 includes effects on multiple systems of the body. The major NF1-associated tumor is the neurofibroma. In addition, clinical manifestations include bone dysplasia, learning disabilities, and an increased risk of malignancy. NF2 includes schwannomas of multiple cranial and spinal nerves, especially the vestibular nerve, as well as other tumors such as meningiomas and ependymomas. The schwannomatosis phenotype is limited to multiple schwannomas, and usually presents with pain. The genes that underlie each of the disorders are known: NF1 for neurofibromatosis type 1, NF2 for neurofibromatosis type 2, and INI1/SMARCB1 for schwannomatosis. Genetic testing is possible to identify mutations. Insights into pathogenesis are beginning to suggest new treatment strategies, and therapeutic trials with several new forms of treatment are underway. Copyright © 2013 Elsevier B.V. All rights reserved.

Passive detection of vehicle loading

NASA Astrophysics Data System (ADS)

McKay, Troy R.; Salvaggio, Carl; Faulring, Jason W.; Salvaggio, Philip S.; McKeown, Donald M.; Garrett, Alfred J.; Coleman, David H.; Koffman, Larry D.

2012-01-01

The Digital Imaging and Remote Sensing Laboratory (DIRS) at the Rochester Institute of Technology, along with the Savannah River National Laboratory is investigating passive methods to quantify vehicle loading. The research described in this paper investigates multiple vehicle indicators including brake temperature, tire temperature, engine temperature, acceleration and deceleration rates, engine acoustics, suspension response, tire deformation and vibrational response. Our investigation into these variables includes building and implementing a sensing system for data collection as well as multiple full-scale vehicle tests. The sensing system includes; infrared video cameras, triaxial accelerometers, microphones, video cameras and thermocouples. The full scale testing includes both a medium size dump truck and a tractor-trailer truck on closed courses with loads spanning the full range of the vehicle's capacity. Statistical analysis of the collected data is used to determine the effectiveness of each of the indicators for characterizing the weight of a vehicle. The final sensing system will monitor multiple load indicators and combine the results to achieve a more accurate measurement than any of the indicators could provide alone.

Clustering "N" Objects into "K" Groups under Optimal Scaling of Variables.

ERIC Educational Resources Information Center

van Buuren, Stef; Heiser, Willem J.

1989-01-01

A method based on homogeneity analysis (multiple correspondence analysis or multiple scaling) is proposed to reduce many categorical variables to one variable with "k" categories. The method is a generalization of the sum of squared distances cluster analysis problem to the case of mixed measurement level variables. (SLD)

Data and code for the exploratory data analysis of the electrical energy demand in the time domain in Greece.

PubMed

Tyralis, Hristos; Karakatsanis, Georgios; Tzouka, Katerina; Mamassis, Nikos

2017-08-01

We present data and code for visualizing the electrical energy data and weather-, climate-related and socioeconomic variables in the time domain in Greece. The electrical energy data include hourly demand, weekly-ahead forecasted values of the demand provided by the Greek Independent Power Transmission Operator and pricing values in Greece. We also present the daily temperature in Athens and the Gross Domestic Product of Greece. The code combines the data to a single report, which includes all visualizations with combinations of all variables in multiple time scales. The data and code were used in Tyralis et al. (2017) [1].

Resource utilization in home health care: results of a prospective study.

PubMed

Trisolini, M G; Thomas, C P; Cashman, S B; Payne, S M

1994-01-01

Resource utilization in home health care has become an issue of concern due to rising costs and recent initiatives to develop prospective payment systems for home health care. A number of issues remain unresolved for the development of prospective reimbursement in this sector, including the types of variables to be included as payment variables and appropriate measures of resource use. This study supplements previous work on home health case-mix by analyzing the factors affecting one aspect of resource use for skilled nursing visits--visit length--and explores the usefulness of several specially collected variables which are not routinely available in administrative records. A data collection instrument was developed with a focus group of skilled nurses, identifying a range of variables hypothesized to affect visit length. Five categories of variables were studied using multiple regression analysis: provider-related; patient's socio-economic status; patient's clinical status; patient's support services; and visit-specific. The final regression model identifies 9 variables which significantly affect visit time. Five of the 9 are visit-specific variables, a significant finding since these are not routinely collected. Case-mix systems which include visit time as a measure of resource use will need to investigate visit-specific variables, as this study indicates they could have the largest influence on visit time. Two other types of resources used in home health care, supplies and security drivers, were also investigated in less detail.

Measuring Radiofrequency and Microwave Radiation from Varying Signal Strengths

NASA Technical Reports Server (NTRS)

Davis, Bette; Gaul, W. C.

2007-01-01

This viewgraph presentation discusses the process of measuring radiofrequency and microwave radiation from various signal strengths. The topics include: 1) Limits and Guidelines; 2) Typical Variable Standard (IEEE) Frequency Dependent; 3) FCC Standard 47 CFR 1.1310; 4) Compliance Follows Unity Rule; 5) Multiple Sources Contribute; 6) Types of RF Signals; 7) Interfering Radiations; 8) Different Frequencies Different Powers; 9) Power Summing - Peak Power; 10) Contribution from Various Single Sources; 11) Total Power from Multiple Sources; 12) Are You Out of Compliance?; and 13) In Compliance.

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

Huang, Yang; Liu, Zhiqiang, E-mail: lzq@semi.ac.cn, E-mail: spring@semi.ac.cn; Yi, Xiaoyan, E-mail: lzq@semi.ac.cn, E-mail: spring@semi.ac.cn

To evaluate electron leakage in InGaN/GaN multiple quantum well (MQW) light emitting diodes (LEDs), analytic models of ballistic and quasi-ballistic transport are developed. With this model, the impact of critical variables effecting electron leakage, including the electron blocking layer (EBL), structure of multiple quantum wells (MQWs), polarization field, and temperature are explored. The simulated results based on this model shed light on previously reported experimental observations and provide basic criteria for suppressing electron leakage, advancing the design of InGaN/GaN LEDs.

Molecular typing of Chinese Streptococcus pyogenes isolates.

PubMed

You, Yuanhai; Wang, Haibin; Bi, Zhenwang; Walker, Mark; Peng, Xianhui; Hu, Bin; Zhou, Haijian; Song, Yanyan; Tao, Xiaoxia; Kou, Zengqiang; Meng, Fanliang; Zhang, Menghan; Bi, Zhenqiang; Luo, Fengji; Zhang, Jianzhong

2015-06-01

Streptococcus pyogenes causes human infections ranging from mild pharyngitis and impetigo to serious diseases including necrotizing fasciitis and streptococcal toxic shock syndrome. The objective of this study was to compare molecular emm typing and pulsed field gel electrophoresis (PFGE) with multiple-locus variable-number tandem-repeat analysis (MLVA) for genotyping of Chinese S. pyogenes isolates. Molecular emm typing and PFGE were performed using standard protocols. Seven variable number tandem repeat (VNTR) loci reported in a previous study were used to genotype 169 S. pyogenes geographically-diverse isolates from China isolated from a variety of disease syndromes. Multiple-locus variable-number tandem-repeat analysis provided greater discrimination between isolates when compared to emm typing and PFGE. Removal of a single VNTR locus (Spy2) reduced the sensitivity by only 0.7%, which suggests that Spy2 was not informative for the isolates screened. The results presented support the use of MLVA as a powerful epidemiological tool for genotyping S. pyogenes clinical isolates. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multiple linear regression and regression with time series error models in forecasting PM10 concentrations in Peninsular Malaysia.

PubMed

Ng, Kar Yong; Awang, Norhashidah

2018-01-06

Frequent haze occurrences in Malaysia have made the management of PM 10 (particulate matter with aerodynamic less than 10 μm) pollution a critical task. This requires knowledge on factors associating with PM 10 variation and good forecast of PM 10 concentrations. Hence, this paper demonstrates the prediction of 1-day-ahead daily average PM 10 concentrations based on predictor variables including meteorological parameters and gaseous pollutants. Three different models were built. They were multiple linear regression (MLR) model with lagged predictor variables (MLR1), MLR model with lagged predictor variables and PM 10 concentrations (MLR2) and regression with time series error (RTSE) model. The findings revealed that humidity, temperature, wind speed, wind direction, carbon monoxide and ozone were the main factors explaining the PM 10 variation in Peninsular Malaysia. Comparison among the three models showed that MLR2 model was on a same level with RTSE model in terms of forecasting accuracy, while MLR1 model was the worst.

A psycholinguistic database for traditional Chinese character naming.

PubMed

Chang, Ya-Ning; Hsu, Chun-Hsien; Tsai, Jie-Li; Chen, Chien-Liang; Lee, Chia-Ying

2016-03-01

In this study, we aimed to provide a large-scale set of psycholinguistic norms for 3,314 traditional Chinese characters, along with their naming reaction times (RTs), collected from 140 Chinese speakers. The lexical and semantic variables in the database include frequency, regularity, familiarity, consistency, number of strokes, homophone density, semantic ambiguity rating, phonetic combinability, semantic combinability, and the number of disyllabic compound words formed by a character. Multiple regression analyses were conducted to examine the predictive powers of these variables for the naming RTs. The results demonstrated that these variables could account for a significant portion of variance (55.8%) in the naming RTs. An additional multiple regression analysis was conducted to demonstrate the effects of consistency and character frequency. Overall, the regression results were consistent with the findings of previous studies on Chinese character naming. This database should be useful for research into Chinese language processing, Chinese education, or cross-linguistic comparisons. The database can be accessed via an online inquiry system (http://ball.ling.sinica.edu.tw/namingdatabase/index.html).

Characterization of Escherichia coli O157:H7 in New Zealand using multiple-locus variable-number tandem-repeat analysis.

PubMed

Dyet, K H; Robertson, I; Turbitt, E; Carter, P E

2011-03-01

Recently, multiple-locus variable-number tandem-repeat analysis (MLVA) has been proposed as an alternative to pulsed-field gel electrophoresis (PFGE) for characterization of Escherichia coli O157:H7. In this study we characterized 118 E. coli O157:H7 isolates from cases of gastrointestinal disease in New Zealand using XbaI PFGE profiles and a MLVA scheme that assessed variability in eight polymorphic loci. The 118 isolates characterized included all 80 E. coli O157:H7 referred to New Zealand's Enteric Reference Laboratory in 2006 and 29 phage-type 2 isolates from 2005. When applied to these isolates the discriminatory power of PFGE and MLVA was not significantly different. However, MLVA data may be more epidemiologically relevant as isolates from family clusters of disease had identical MLVA profiles, even when the XbaI PFGE profiles differed slightly. Furthermore, most isolates with indistinguishable XbaI PFGE profiles that did not appear to be epidemiologically related had distinct MLVA profiles.

Addressing Gender Equity in Nonfaculty Salaries.

ERIC Educational Resources Information Center

Toukoushian, Robert K.

2000-01-01

Discusses methodology of gender equity studies on noninstructional employees of colleges and universities, including variable selection in the multiple regression model and alternative approaches for measuring wage gaps. Analysis of staff data at one institution finds that experience and market differences account for 80 percent of gender pay…

Predicting daily use of urban forest recreation sites

Treesearch

John F. Dwyer

1988-01-01

A multiple linear regression model explains 90% of the variance in daily use of an urban recreation site. Explanatory variables include season, day of the week, and weather. The results offer guides for recreation site planning and management as well as suggestions for improving the model.

The Relationship of Item-Level Response Times with Test-Taker and Item Variables in an Operational CAT Environment. LSAC Research Report Series.

ERIC Educational Resources Information Center

Swygert, Kimberly A.

In this study, data from an operational computerized adaptive test (CAT) were examined in order to gather information concerning item response times in a CAT environment. The CAT under study included multiple-choice items measuring verbal, quantitative, and analytical reasoning. The analyses included the fitting of regression models describing the…

Forecasting models for sugi (Cryptomeria japonica D. Don) pollen count showing an alternate dispersal rhythm.

PubMed

Ito, Yukiko; Hattori, Reiko; Mase, Hiroki; Watanabe, Masako; Shiotani, Itaru

2008-12-01

Pollen information is indispensable for allergic individuals and clinicians. This study aimed to develop forecasting models for the total annual count of airborne pollen grains based on data monitored over the last 20 years at the Mie Chuo Medical Center, Tsu, Mie, Japan. Airborne pollen grains were collected using a Durham sampler. Total annual pollen count and pollen count from October to December (OD pollen count) of the previous year were transformed to logarithms. Regression analysis of the total pollen count was performed using variables such as the OD pollen count and the maximum temperature for mid-July of the previous year. Time series analysis revealed an alternate rhythm of the series of total pollen count. The alternate rhythm consisted of a cyclic alternation of an "on" year (high pollen count) and an "off" year (low pollen count). This rhythm was used as a dummy variable in regression equations. Of the three models involving the OD pollen count, a multiple regression equation that included the alternate rhythm variable and the interaction of this rhythm with OD pollen count showed a high coefficient of determination (0.844). Of the three models involving the maximum temperature for mid-July, those including the alternate rhythm variable and the interaction of this rhythm with maximum temperature had the highest coefficient of determination (0.925). An alternate pollen dispersal rhythm represented by a dummy variable in the multiple regression analysis plays a key role in improving forecasting models for the total annual sugi pollen count.

[Factors Influencing Quality of Life of Alcoholics Anonymous Members in Korea].

PubMed

Yoo, Jae Soon; Lee, Jongeun; Park, Woo Young

2016-04-01

The purpose of this study was to determine quality of life (QOL) related factors in Alcoholics Anonymous (AA) members based on PRECEDE Model. A cross sectional survey was conducted with participants (N =203) from AA meeting in 11 alcohol counsel centers all over South Korea. Data were collected using a specially designed questionnaire based on the PRECEDE model and including QOL, epidemiological factors (including depression and perceived health status), behavioral factors (continuous abstinence and physical health status and practice), predisposing factors (abstinence self-efficacy and self-esteem), reinforcing factors (social capital and family functioning), and enabling factors. Data were analyzed using t-test, one way ANOVA, Tukey HSD test and hierarchical multiple regression analysis with SPSS (ver. 21.0). Of the educational diagnostic variables, self-esteem (β=.23), family functioning (β=.12), abstinence self-efficacy (β=.12) and social capital (β=.11) were strong influential factors in AA members' QOL. In addition, epidemiological diagnostic variables such as depression (β=-.44) and perceived health status (β=.35) were the main factors in QOL. Also, physical health status and practice (β=.106), one of behavioral diagnostic variables was a beneficial factor in QOL. Hierarchical multiple regression analysis showed the determinant variables accounted for 44.0% of the variation in QOL (F=25.76, p<.001). The finding of the study can be used as a framework for planning interventions in order to promote the quality of life of AA members. It is necessary to develop nursing intervention strategies for strengthening educational and epidemiological diagnostic variables in order to improve AA members' QOL.

Regional Drought Monitoring Based on Multi-Sensor Remote Sensing

NASA Astrophysics Data System (ADS)

Rhee, Jinyoung; Im, Jungho; Park, Seonyoung

2014-05-01

Drought originates from the deficit of precipitation and impacts environment including agriculture and hydrological resources as it persists. The assessment and monitoring of drought has traditionally been performed using a variety of drought indices based on meteorological data, and recently the use of remote sensing data is gaining much attention due to its vast spatial coverage and cost-effectiveness. Drought information has been successfully derived from remotely sensed data related to some biophysical and meteorological variables and drought monitoring is advancing with the development of remote sensing-based indices such as the Vegetation Condition Index (VCI), Vegetation Health Index (VHI), and Normalized Difference Water Index (NDWI) to name a few. The Scaled Drought Condition Index (SDCI) has also been proposed to be used for humid regions proving the performance of multi-sensor data for agricultural drought monitoring. In this study, remote sensing-based hydro-meteorological variables related to drought including precipitation, temperature, evapotranspiration, and soil moisture were examined and the SDCI was improved by providing multiple blends of the multi-sensor indices for different types of drought. Multiple indices were examined together since the coupling and feedback between variables are intertwined and it is not appropriate to investigate only limited variables to monitor each type of drought. The purpose of this study is to verify the significance of each variable to monitor each type of drought and to examine the combination of multi-sensor indices for more accurate and timely drought monitoring. The weights for the blends of multiple indicators were obtained from the importance of variables calculated by non-linear optimization using a Machine Learning technique called Random Forest. The case study was performed in the Republic of Korea, which has four distinct seasons over the course of the year and contains complex topography with a variety of land cover types. Remote sensing data from the Tropical Rainfall Measuring Mission satellite (TRMM) and Moderate Resolution Imaging Spectroradiometer (MODIS), and Advanced Microwave Scanning Radiometer-EOS (AMSR-E) sensors were obtained for the period from 2000 to 2012, and observation data from 99 weather stations, 441 streamflow gauges, as well as the gridded observation data from Asian Precipitation Highly-Resolved Observational Data Integration Towards Evaluation of the Water Resources (APHRODITE) were obtained for validation. The objective blends of multiple indicators helped better assessment of various types of drought, and can be useful for drought early warning system. Since the improved SDCI is based on remotely sensed data, it can be easily applied to regions with limited or no observation data for drought assessment and monitoring.

Cardiovascular Physiology Teaching: Computer Simulations vs. Animal Demonstrations.

ERIC Educational Resources Information Center

Samsel, Richard W.; And Others

1994-01-01

At the introductory level, the computer provides an effective alternative to using animals for laboratory teaching. Computer software can simulate the operation of multiple organ systems. Advantages of software include alteration of variables that are not easily changed in vivo, repeated interventions, and cost-effective hands-on student access.…

Screen Layout Design: Research into the Overall Appearance of the Screen.

ERIC Educational Resources Information Center

Grabinger, R. Scott

1989-01-01

Examines the current state of research into the visual effects of screen designs used in computer-assisted instruction and suggests areas for future efforts. Topics discussed include technical elements and comprehensibility elements in layout design; single element and multiple element research methodologies; dependent variables; and learning…

An Agitation Experiment with Multiple Aspects

ERIC Educational Resources Information Center

Spencer, Jordan L.

2006-01-01

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

The Effects of Market Structure on Television News Pricing.

ERIC Educational Resources Information Center

Wirth, Michael O.; Wollert, James A.

Multiple regression techniques were used to examine the business side of local television news operations for November 1978. Research questions examined the effect of several variables on local television news prices (advertising rates), including type of ownership, network affiliation/signal type, market size, cable network penetration, market…

Instructive Feedback Embedded within Group Instruction for Children Diagnosed with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Leaf, Justin B.; Cihon, Joseph H.; Alcalay, Aditt; Mitchell, Erin; Townley-Cochran, Donna; Miller, Kevin; Leaf, Ronald; Taubman, Mitchell; McEachin, John

2017-01-01

The present study evaluated the effects of instructive feedback embedded within a group discrete trial teaching to teach tact relations to nine children diagnosed with autism spectrum disorder using a nonconcurrent multiple-baseline design. Dependent variables included correct responses for: primary targets (directly taught), secondary targets…

Homing success in wintering sparrows

Treesearch

C. John Ralph; L. Richard Mewaldt

1976-01-01

The ability of birds to return "home" after displacement is generallywell known but poorly understood because of the multiplicity of variablesthat affect homing performance. These variables can include age andprevious experience of the bird, as well as the timing and distance of thedisplacement. The phenomenon of homing is also difficult to interpretbecause,...

Rural Economic Development: What Makes Rural Communities Grow?

ERIC Educational Resources Information Center

Aldrich, Lorna; Kusmin, Lorin

This report identifies local factors that foster rural economic growth. A review of the literature revealed potential indicators of county economic growth, and those indicators were then tested against data for nonmetro counties during the 1980s using multiple regression analysis. The principal variables examined included demographic and labor…

PARTIAL LEAST SQUARE ANALYSES FOR ASSOCIATION OF LANDSCAPE METRICS WITH WATER BIOLOGICAL AND CHEMICAL PROPERTIES IN THE SAVANNAH RIVER BASIN

EPA Science Inventory

Surface water quality is related to conditions in the surrounding geophysical environment, including soils, landcover, and anthropogenic activities. A number of statistical methods may be used to analyze and explore relationships among variables. Single-, multiple- and multivaria...

An Evaluation of Curriculum Materials Based Upon the Socio-Scientific Reasoning Model.

ERIC Educational Resources Information Center

Henkin, Gayle; And Others

To address the need to develop a scientifically literate citizenry, the socio-scientific reasoning model was created to guide curriculum development. Goals of this developmental approach include increasing: (1) students' skills in dealing with problems containing multiple interacting variables; (2) students' decision-making skills incorporating a…

Trispyrazolylborate Complexes: An Advanced Synthesis Experiment Using Paramagnetic NMR, Variable-Temperature NMR, and EPR Spectroscopies

ERIC Educational Resources Information Center

Abell, Timothy N.; McCarrick, Robert M.; Bretz, Stacey Lowery; Tierney, David L.

2017-01-01

A structured inquiry experiment for inorganic synthesis has been developed to introduce undergraduate students to advanced spectroscopic techniques including paramagnetic nuclear magnetic resonance and electron paramagnetic resonance. Students synthesize multiple complexes with unknown first row transition metals and identify the unknown metals by…

Molar Functional Relations and Clinical Behavior Analysis: Implications for Assessment and Treatment

ERIC Educational Resources Information Center

Waltz, Thomas J.; Follette, William C.

2009-01-01

The experimental analysis of behavior has identified several molar functional relations that are highly relevant to clinical behavior analysis. These include matching, discounting, momentum, and variability. Matching provides a broader analysis of how multiple sources of reinforcement influence how individuals choose to allocate their time and…

A comprehensive methodology for the multidimensional and synchronic data collecting in soundscape.

PubMed

Kogan, Pablo; Turra, Bruno; Arenas, Jorge P; Hinalaf, María

2017-02-15

The soundscape paradigm is comprised of complex living systems where individuals interact moment-by-moment among one another and with the physical environment. The real environments provide promising conditions to reveal deep soundscape behavior, including the multiple components involved and their interrelations as a whole. However, measuring and analyzing the numerous simultaneous variables of soundscape represents a challenge that is not completely understood. This work proposes and applies a comprehensive methodology for multidimensional and synchronic data collection in soundscape. The soundscape variables were organized into three main entities: experienced environment, acoustic environment, and extra-acoustic environment, containing, in turn, subgroups of variables called components. The variables contained in these components were acquired through synchronic field techniques that include surveys, acoustic measurements, audio recordings, photography, and video. The proposed methodology was tested, optimized, and applied in diverse open environments, including squares, parks, fountains, university campuses, streets, and pedestrian areas. The systematization of this comprehensive methodology provides a framework for soundscape research, a support for urban and environment management, and a preliminary procedure for standardization in soundscape data collecting. Copyright © 2016 Elsevier B.V. All rights reserved.

Illness perception, treatment beliefs, self-esteem, and self-efficacy as correlates of self-management in multiple sclerosis.

PubMed

Wilski, M; Tasiemski, T

2016-05-01

Self-management of a disease is considered one of the most important factors affecting the treatment outcome. The research on the correlates of self-management in multiple sclerosis (MS) is limited. The aim of this study was to determine if personal factors, such as illness perception, treatment beliefs, self-esteem and self-efficacy, are correlates of self-management in MS. This cross-sectional study included 210 patients with MS who completed Multiple Sclerosis Self-Management Scale - Revised, Brief Illness Perception Questionnaire, Treatment Beliefs Scale, Rosenberg Self-Esteem Scale, and Generalized Self-Efficacy Scale. The patients were recruited from a MS rehabilitation clinic. Demographic data and illness-related problems of the study participants were collected with a self-report survey. Correlation and regression analyses were performed to determine associations between variables. Four factors: age at the time of the study (β = 0.14, P = 0.032), timeline (β = 0.16, P = 0.018), treatment control (β = 0.17, P = 0.022), and general self-efficacy (β = 0.19, P = 0.014) turned out to be the significant correlates of self-management in MS. The model including these variables explained 25% of variance in self-management in MS. Personal factors, such as general self-efficacy, perception of treatment control and realistic MS timeline perspective, are more salient correlates of self-management in MS than the objective clinical variables, such as the severity, type, and duration of MS. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Architecture Adaptive Computing Environment

NASA Technical Reports Server (NTRS)

Dorband, John E.

2006-01-01

Architecture Adaptive Computing Environment (aCe) is a software system that includes a language, compiler, and run-time library for parallel computing. aCe was developed to enable programmers to write programs, more easily than was previously possible, for a variety of parallel computing architectures. Heretofore, it has been perceived to be difficult to write parallel programs for parallel computers and more difficult to port the programs to different parallel computing architectures. In contrast, aCe is supportable on all high-performance computing architectures. Currently, it is supported on LINUX clusters. aCe uses parallel programming constructs that facilitate writing of parallel programs. Such constructs were used in single-instruction/multiple-data (SIMD) programming languages of the 1980s, including Parallel Pascal, Parallel Forth, C*, *LISP, and MasPar MPL. In aCe, these constructs are extended and implemented for both SIMD and multiple- instruction/multiple-data (MIMD) architectures. Two new constructs incorporated in aCe are those of (1) scalar and virtual variables and (2) pre-computed paths. The scalar-and-virtual-variables construct increases flexibility in optimizing memory utilization in various architectures. The pre-computed-paths construct enables the compiler to pre-compute part of a communication operation once, rather than computing it every time the communication operation is performed.

A review of covariate selection for non-experimental comparative effectiveness research.

PubMed

Sauer, Brian C; Brookhart, M Alan; Roy, Jason; VanderWeele, Tyler

2013-11-01

This paper addresses strategies for selecting variables for adjustment in non-experimental comparative effectiveness research and uses causal graphs to illustrate the causal network that relates treatment to outcome. Variables in the causal network take on multiple structural forms. Adjustment for a common cause pathway between treatment and outcome can remove confounding, whereas adjustment for other structural types may increase bias. For this reason, variable selection would ideally be based on an understanding of the causal network; however, the true causal network is rarely known. Therefore, we describe more practical variable selection approaches based on background knowledge when the causal structure is only partially known. These approaches include adjustment for all observed pretreatment variables thought to have some connection to the outcome, all known risk factors for the outcome, and all direct causes of the treatment or the outcome. Empirical approaches, such as forward and backward selection and automatic high-dimensional proxy adjustment, are also discussed. As there is a continuum between knowing and not knowing the causal, structural relations of variables, we recommend addressing variable selection in a practical way that involves a combination of background knowledge and empirical selection and that uses high-dimensional approaches. This empirical approach can be used to select from a set of a priori variables based on the researcher's knowledge to be included in the final analysis or to identify additional variables for consideration. This more limited use of empirically derived variables may reduce confounding while simultaneously reducing the risk of including variables that may increase bias. Copyright © 2013 John Wiley & Sons, Ltd.

A Review of Covariate Selection for Nonexperimental Comparative Effectiveness Research

PubMed Central

Sauer, Brian C.; Brookhart, Alan; Roy, Jason; Vanderweele, Tyler

2014-01-01

This paper addresses strategies for selecting variables for adjustment in non-experimental comparative effectiveness research (CER), and uses causal graphs to illustrate the causal network that relates treatment to outcome. Variables in the causal network take on multiple structural forms. Adjustment for on a common cause pathway between treatment and outcome can remove confounding, while adjustment for other structural types may increase bias. For this reason variable selection would ideally be based on an understanding of the causal network; however, the true causal network is rarely know. Therefore, we describe more practical variable selection approaches based on background knowledge when the causal structure is only partially known. These approaches include adjustment for all observed pretreatment variables thought to have some connection to the outcome, all known risk factors for the outcome, and all direct causes of the treatment or the outcome. Empirical approaches, such as forward and backward selection and automatic high-dimensional proxy adjustment, are also discussed. As there is a continuum between knowing and not knowing the causal, structural relations of variables, we recommend addressing variable selection in a practical way that involves a combination of background knowledge and empirical selection and that uses the high-dimensional approaches. This empirical approach can be used to select from a set of a priori variables based on the researcher’s knowledge to be included in the final analysis or to identify additional variables for consideration. This more limited use of empirically-derived variables may reduce confounding while simultaneously reducing the risk of including variables that may increase bias. PMID:24006330

The Heterogeneity in Retrieved Relations between the Personality Trait ‘Harm Avoidance’ and Gray Matter Volumes Due to Variations in the VBM and ROI Labeling Processing Settings

PubMed Central

Van Schuerbeek, Peter; Baeken, Chris; De Mey, Johan

2016-01-01

Concerns are raising about the large variability in reported correlations between gray matter morphology and affective personality traits as ‘Harm Avoidance’ (HA). A recent review study (Mincic 2015) stipulated that this variability could come from methodological differences between studies. In order to achieve more robust results by standardizing the data processing procedure, as a first step, we repeatedly analyzed data from healthy females while changing the processing settings (voxel-based morphology (VBM) or region-of-interest (ROI) labeling, smoothing filter width, nuisance parameters included in the regression model, brain atlas and multiple comparisons correction method). The heterogeneity in the obtained results clearly illustrate the dependency of the study outcome to the opted analysis settings. Based on our results and the existing literature, we recommended the use of VBM over ROI labeling for whole brain analyses with a small or intermediate smoothing filter (5-8mm) and a model variable selection step included in the processing procedure. Additionally, it is recommended that ROI labeling should only be used in combination with a clear hypothesis and that authors are encouraged to report their results uncorrected for multiple comparisons as supplementary material to aid review studies. PMID:27096608

Estimation of streamflow, base flow, and nitrate-nitrogen loads in Iowa using multiple linear regression models

USGS Publications Warehouse

Schilling, K.E.; Wolter, C.F.

2005-01-01

Nineteen variables, including precipitation, soils and geology, land use, and basin morphologic characteristics, were evaluated to develop Iowa regression models to predict total streamflow (Q), base flow (Qb), storm flow (Qs) and base flow percentage (%Qb) in gauged and ungauged watersheds in the state. Discharge records from a set of 33 watersheds across the state for the 1980 to 2000 period were separated into Qb and Qs. Multiple linear regression found that 75.5 percent of long term average Q was explained by rainfall, sand content, and row crop percentage variables, whereas 88.5 percent of Qb was explained by these three variables plus permeability and floodplain area variables. Qs was explained by average rainfall and %Qb was a function of row crop percentage, permeability, and basin slope variables. Regional regression models developed for long term average Q and Qb were adapted to annual rainfall and showed good correlation between measured and predicted values. Combining the regression model for Q with an estimate of mean annual nitrate concentration, a map of potential nitrate loads in the state was produced. Results from this study have important implications for understanding geomorphic and land use controls on streamflow and base flow in Iowa watersheds and similar agriculture dominated watersheds in the glaciated Midwest. (JAWRA) (Copyright ?? 2005).

A method for analyzing temporal patterns of variability of a time series from Poincare plots.

PubMed

Fishman, Mikkel; Jacono, Frank J; Park, Soojin; Jamasebi, Reza; Thungtong, Anurak; Loparo, Kenneth A; Dick, Thomas E

2012-07-01

The Poincaré plot is a popular two-dimensional, time series analysis tool because of its intuitive display of dynamic system behavior. Poincaré plots have been used to visualize heart rate and respiratory pattern variabilities. However, conventional quantitative analysis relies primarily on statistical measurements of the cumulative distribution of points, making it difficult to interpret irregular or complex plots. Moreover, the plots are constructed to reflect highly correlated regions of the time series, reducing the amount of nonlinear information that is presented and thereby hiding potentially relevant features. We propose temporal Poincaré variability (TPV), a novel analysis methodology that uses standard techniques to quantify the temporal distribution of points and to detect nonlinear sources responsible for physiological variability. In addition, the analysis is applied across multiple time delays, yielding a richer insight into system dynamics than the traditional circle return plot. The method is applied to data sets of R-R intervals and to synthetic point process data extracted from the Lorenz time series. The results demonstrate that TPV complements the traditional analysis and can be applied more generally, including Poincaré plots with multiple clusters, and more consistently than the conventional measures and can address questions regarding potential structure underlying the variability of a data set.

Models and mosaics: investigating cross-cultural differences in risk perception and risk preference.

PubMed

Weber, E U; Hsee, C K

1999-12-01

In this article, we describe a multistudy project designed to explain observed cross-national differences in risk taking between respondents from the People's Republic of China and the United States. Using this example, we develop the following recommendations for cross-cultural investigations. First, like all psychological research, cross-cultural studies should be model based. Investigators should commit themselves to a model of the behavior under study that explicitly specifies possible causal constructs or variables hypothesized to influence the behavior, as well as the relationship between those variables, and allows for individual, group, or cultural differences in the value of these variables or in the relationship between them. This moves the focus from a simple demonstration of cross-national differences toward a prediction of the behavior, including its cross-national variation. Ideally, the causal construct hypothesized and shown to differ between cultures should be demonstrated to serve as a moderator or a mediator between culture and observed behavioral differences. Second, investigators should look for converging evidence for hypothesized cultural effects on behavior by looking at multiple dependent variables and using multiple methodological approaches. Thus, the data collection that will allow for the establishment of conclusive causal connections between a cultural variable and some target behavior can be compared with the creation of a mosaic.

gHRV: Heart rate variability analysis made easy.

PubMed

Rodríguez-Liñares, L; Lado, M J; Vila, X A; Méndez, A J; Cuesta, P

2014-08-01

In this paper, the gHRV software tool is presented. It is a simple, free and portable tool developed in python for analysing heart rate variability. It includes a graphical user interface and it can import files in multiple formats, analyse time intervals in the signal, test statistical significance and export the results. This paper also contains, as an example of use, a clinical analysis performed with the gHRV tool, namely to determine whether the heart rate variability indexes change across different stages of sleep. Results from tests completed by researchers who have tried gHRV are also explained: in general the application was positively valued and results reflect a high level of satisfaction. gHRV is in continuous development and new versions will include suggestions made by testers. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Factors Associated with Falls in Community-Dwelling Older People with Focus on Participation in Sport Organizations: The Japan Gerontological Evaluation Study Project

PubMed Central

Hayashi, Takahiro; Kondo, Katsunori; Suzuki, Kayo; Yamada, Minoru; Matsumoto, Daisuke

2014-01-01

Objective. Promoting participation in sport organizations may be a population strategy for preventing falls in older people. In this study, we examined whether participation in sport organizations is associated with fewer falls in older people even after adjusting for multiple individual and environmental factors. Methods. We used the Japan Gerontological Evaluation Study data of 90,610 people (31 municipalities) who were not eligible for public long-term care. Logistic regression analysis was performed, with multiple falls over the past year as the dependent variable and participation in a sport organization as the independent variable, controlling for 13 factors. These included individual factors related to falls, such as age and sex, and environmental factors such as population density of the habitable area. Results. A total of 6,391 subjects (7.1%) had a history of multiple falls. Despite controlling for 13 variables, those who participated in a sport organization at least once a week were approximately ≥20% less likely to fall than those who did not participate at all (once a week; odds ratio = 0.82 and 95% confidence interval = 0.72–0.95). Conclusion. Participation in a sport organization at least once per week might help prevent falls in the community-dwelling older people. PMID:24955360

Obesity and the community food environment: a systematic review.

PubMed

Holsten, Joanna E

2009-03-01

To examine the relationship between obesity and the community and/or consumer food environment. A comprehensive literature search of multiple databases was conducted and seven studies were identified for review. Studies were selected if they measured BMI and environmental variables related to food outlets. Environmental variables included the geographic arrangement of food stores or restaurants in communities and consumer conditions such as food price and availability within each outlet. The study designs, methods, limitations and results related to obesity and the food environment were reviewed, and implications for future research were synthesized. The reviewed studies used cross-sectional designs to examine the community food environment defined as the number per capita, proximity or density of food outlets. Most studies indirectly identified food outlets through large databases. The studies varied substantially in sample populations, outcome variables, units of measurement and data analysis. Two studies did not find any significant association between obesity rates and community food environment variables. Five studies found significant results. Many of the studies were subject to limitations that may have mitigated the validity of the results. Research examining obesity and the community or consumer food environment is at an early stage. The most pertinent gaps include primary data at the individual level, direct measures of the environment, studies examining the consumer environment and study designs involving a time sequence. Future research should directly measure multiple levels of the food environment and key confounders at the individual level.

Psychosocial and cognitive factors associated with adherence to dietary and fluid restriction regimens by people on chronic haemodialysis.

PubMed

Sensky, T; Leger, C; Gilmour, S

1996-01-01

Failure by people on chronic haemodialysis to adhere adequately to dietary and fluid restrictions can have serious medical consequences. Numerous psychosocial factors possibly associated with adherence have been investigated in previous research. However, most previous studies have examined one or a few variables in isolation, and have tended to focus on sociodemographic variables not easily amenable to intervention. Much previous work has tended to ignore potential differences in adherence between male and female dialysands. Sociodemographic and psychosocial factors associated with adherence to dietary and fluid restrictions were investigated in 45 people on haemodialysis attending one renal unit, excluding those with a residual urine volume > 500 ml/day. Multiple regression analyses were used to estimate the contribution to adherence of a range of variables, including gender, age, duration of dialysis, affective disturbance, past psychiatric history, health locus of control, social adjustment and social supports. Adherence to diet (measured by predialysis serum potassium) and to fluid restriction (interdialysis weight gain) were not linked, and had different psychosocial correlates. Regression models of four different aspects of adherence revealed very distinct psychosocial correlates, with contributions to adherence from complex interactions between psychosocial and cognitive variables, notably gender, age, social adjustment, health locus of control, and depression. The findings cast doubt on the results of many previous studies which have used simple models of adherence. Adherence is likely to be influenced in a complex manner by multiple factors including age, gender, locus of control, social adjustment, and past psychiatric history.

Genomic variability of Helicobacter pylori isolates of gastric regions from two Colombian populations

PubMed Central

Matta, Andrés Jenuer; Pazos, Alvaro Jairo; Bustamante-Rengifo, Javier Andrés; Bravo, Luis Eduardo

2017-01-01

AIM To compare the genomic variability and the multiple colonization of Helicobacter pylori (H. pylori) in patients with chronic gastritis from two Colombian populations with contrast in the risk of developing gastric cancer (GC): Túquerres-Nariño (High risk) and Tumaco-Nariño (Low risk). METHODS Four hundred and nine patients from both genders with dyspeptic symptoms were studied. Seventy-two patients were included in whom H. pylori was isolated from three anatomic regions of the gastric mucosa, (31/206) of the high risk population of GC (Túquerres) and (41/203) of the low risk population of GC (Tumaco). The isolates were genotyped by PCR-RAPD. Genetic diversity between the isolates was evaluated by conglomerates analysis and multiple correspondence analyses. RESULTS The proportion of virulent genotypes of H. pylori was 99% in Túquerres and 94% in Tumaco. The coefficient of similarity of Nei-Li showed greater genetic diversity among isolates of Túquerres (0.13) than those of Tumaco (0.07). After adjusting by age, gender and type of gastritis, the multiple colonization was 1.7 times more frequent in Túquerres than in Tumaco (P = 0.05). CONCLUSION In Túquerres, high risk of GC there was a greater probability of multiple colonization by H. pylori. From the analysis of the results of the PCR-RAPD, it was found higher genetic variability in the isolates of H. pylori in the population of high risk for the development of GC. PMID:28223724

Assessing the effects of multiple stressors on the functioning of Mediterranean rivers using poplar wood breakdown.

PubMed

Aristi, Ibon; Díez, Jose Ramon; Larrañaga, Aitor; Navarro-Ortega, Alícia; Barceló, Damià; Elosegi, Arturo

2012-12-01

Mediterranean rivers in the Iberian Peninsula are being increasingly affected by human activities, which threaten their ecological status. A clear picture of how do these multiple stressors affect river ecosystem functioning is still lacking. We addressed this question by measuring a key ecosystem process, namely breakdown of organic matter, at 66 sites distributed across Mediterranean Spain. We performed breakdown experiments by measuring the mass lost by wood sticks for 54 to 106 days. Additionally, we gathered data on physico-chemical, biological and geomorphological characteristics of study sites. Study sites spanned a broad range of environmental characteristics and breakdown rates varied fiftyfold across sites. No clear geographic patterns were found between or within basins. 90th quantile regressions performed to link breakdown rates with environmental characteristics included the following 7 variables in the model, in decreasing order of importance: altitude, water content in phosphorus, catchment area, toxicity, invertebrate-based biotic index, riparian buffer width, and diatom-based quality index. Breakdown rate was systematically low in high-altitude rivers with few human impacts, but showed a high variability in areas affected by human activity. This increase in variability is the result of the influence of multiple stressors acting simultaneously, as some of these can promote whereas others slow down the breakdown of organic matter. Therefore, stick breakdown gives information on the intensity of a key ecosystem process, which would otherwise be very difficult to predict based on environmental variables. Copyright © 2012 Elsevier B.V. All rights reserved.

Application of effective discharge analysis to environmental flow decision-making

USGS Publications Warehouse

McKay, S. Kyle; Freeman, Mary C.; Covich, A.P.

2016-01-01

Well-informed river management decisions rely on an explicit statement of objectives, repeatable analyses, and a transparent system for assessing trade-offs. These components may then be applied to compare alternative operational regimes for water resource infrastructure (e.g., diversions, locks, and dams). Intra- and inter-annual hydrologic variability further complicates these already complex environmental flow decisions. Effective discharge analysis (developed in studies of geomorphology) is a powerful tool for integrating temporal variability of flow magnitude and associated ecological consequences. Here, we adapt the effectiveness framework to include multiple elements of the natural flow regime (i.e., timing, duration, and rate-of-change) as well as two flow variables. We demonstrate this analytical approach using a case study of environmental flow management based on long-term (60 years) daily discharge records in the Middle Oconee River near Athens, GA, USA. Specifically, we apply an existing model for estimating young-of-year fish recruitment based on flow-dependent metrics to an effective discharge analysis that incorporates hydrologic variability and multiple focal taxa. We then compare three alternative methods of environmental flow provision. Percentage-based withdrawal schemes outcompete other environmental flow methods across all levels of water withdrawal and ecological outcomes.

Merits and limitations of optimality criteria method for structural optimization

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Guptill, James D.; Berke, Laszlo

1993-01-01

The merits and limitations of the optimality criteria (OC) method for the minimum weight design of structures subjected to multiple load conditions under stress, displacement, and frequency constraints were investigated by examining several numerical examples. The examples were solved utilizing the Optimality Criteria Design Code that was developed for this purpose at NASA Lewis Research Center. This OC code incorporates OC methods available in the literature with generalizations for stress constraints, fully utilized design concepts, and hybrid methods that combine both techniques. Salient features of the code include multiple choices for Lagrange multiplier and design variable update methods, design strategies for several constraint types, variable linking, displacement and integrated force method analyzers, and analytical and numerical sensitivities. The performance of the OC method, on the basis of the examples solved, was found to be satisfactory for problems with few active constraints or with small numbers of design variables. For problems with large numbers of behavior constraints and design variables, the OC method appears to follow a subset of active constraints that can result in a heavier design. The computational efficiency of OC methods appears to be similar to some mathematical programming techniques.

Application of Effective Discharge Analysis to Environmental Flow Decision-Making.

PubMed

McKay, S Kyle; Freeman, Mary C; Covich, Alan P

2016-06-01

Well-informed river management decisions rely on an explicit statement of objectives, repeatable analyses, and a transparent system for assessing trade-offs. These components may then be applied to compare alternative operational regimes for water resource infrastructure (e.g., diversions, locks, and dams). Intra- and inter-annual hydrologic variability further complicates these already complex environmental flow decisions. Effective discharge analysis (developed in studies of geomorphology) is a powerful tool for integrating temporal variability of flow magnitude and associated ecological consequences. Here, we adapt the effectiveness framework to include multiple elements of the natural flow regime (i.e., timing, duration, and rate-of-change) as well as two flow variables. We demonstrate this analytical approach using a case study of environmental flow management based on long-term (60 years) daily discharge records in the Middle Oconee River near Athens, GA, USA. Specifically, we apply an existing model for estimating young-of-year fish recruitment based on flow-dependent metrics to an effective discharge analysis that incorporates hydrologic variability and multiple focal taxa. We then compare three alternative methods of environmental flow provision. Percentage-based withdrawal schemes outcompete other environmental flow methods across all levels of water withdrawal and ecological outcomes.

Adherence and health literacy as related to outcome of patients treated for rheumatoid arthritis : Analyses of a large-scale observational study.

PubMed

Kuipers, J G; Koller, M; Zeman, F; Müller, K; Rüffer, J U

2018-04-24

Disabilities in daily living and quality of life are key endpoints for evaluating the treatment outcome for rheumatoid arthritis (RA). Factors possibly contributing to good outcome are adherence and health literacy. The survey included a representative nationwide sample of German rheumatologists and their patients with RA. The physician questionnaire included the disease activity score (DAS28) and medical prescriptions. The patient questionnaire included fatigue (EORTC QLQ-FA13), health assessment questionnaire (HAQ), quality of life (SF-12), health literacy (HELP), and patients' listings of their medications. Adherence was operationalized as follows: patient-reported (CQR5), behavioral (concordance between physicians' and patients' listings of medications), physician-assessed, and a combined measure of physician rating (1 = very adherent, 0 = less adherent) and the match between physicians' prescriptions and patients' accounts of their medications (1 = perfect match, 0 = no perfect match) that yielded three categories of adherence: high, medium, and low. Simple and multiple linear regressions (controlling for age, sex, smoking, drinking alcohol, and sport) were calculated using adherence and health literacy as predictor variables, and disease activity and patient-reported outcomes as dependent variables. 708 pairs of patient and physician questionnaires were analyzed. The mean patient age (73% women) was 60 years (SD = 12). Multiple regression analyses showed that high adherence was significantly associated with 5/7 outcome variables and health literacy with 7/7 outcome variables. Adherence and health literacy had weak but consistent effects on most outcomes. Thus, enhancing adherence and understanding of medical information could improve outcome, which should be investigated in future interventional studies.

Generalized Likelihood Uncertainty Estimation (GLUE) methodology for optimization of extraction in natural products.

PubMed

Maulidiani; Rudiyanto; Abas, Faridah; Ismail, Intan Safinar; Lajis, Nordin H

2018-06-01

Optimization process is an important aspect in the natural product extractions. Herein, an alternative approach is proposed for the optimization in extraction, namely, the Generalized Likelihood Uncertainty Estimation (GLUE). The approach combines the Latin hypercube sampling, the feasible range of independent variables, the Monte Carlo simulation, and the threshold criteria of response variables. The GLUE method is tested in three different techniques including the ultrasound, the microwave, and the supercritical CO 2 assisted extractions utilizing the data from previously published reports. The study found that this method can: provide more information on the combined effects of the independent variables on the response variables in the dotty plots; deal with unlimited number of independent and response variables; consider combined multiple threshold criteria, which is subjective depending on the target of the investigation for response variables; and provide a range of values with their distribution for the optimization. Copyright © 2018 Elsevier Ltd. All rights reserved.

Study preferences for exemplar variability in self-regulated category learning.

PubMed

Wahlheim, Christopher N; DeSoto, K Andrew

2017-02-01

Increasing exemplar variability during category learning can enhance classification of novel exemplars from studied categories. Four experiments examined whether participants preferred variability when making study choices with the goal of later classifying novel exemplars. In Experiments 1-3, participants were familiarised with exemplars of birds from multiple categories prior to making category-level assessments of learning and subsequent choices about whether to receive more variability or repetitions of exemplars during study. After study, participants classified novel exemplars from studied categories. The majority of participants showed a consistent preference for variability in their study, but choices were not related to category-level assessments of learning. Experiment 4 provided evidence that study preferences were based primarily on theoretical beliefs in that most participants indicated a preference for variability on questionnaires that did not include prior experience with exemplars. Potential directions for theoretical development and applications to education are discussed.

The Detection and Interpretation of Interaction Effects between Continuous Variables in Multiple Regression.

ERIC Educational Resources Information Center

Jaccard, James; And Others

1990-01-01

Issues in the detection and interpretation of interaction effects between quantitative variables in multiple regression analysis are discussed. Recent discussions associated with problems of multicollinearity are reviewed in the context of the conditional nature of multiple regression with product terms. (TJH)

Factors associated with mouth breathing in children with -developmental -disabilities.

PubMed

de Castilho, Lia Silva; Abreu, Mauro Henrique Nogueira Guimarães; de Oliveira, Renata Batista; Souza E Silva, Maria Elisa; Resende, Vera Lúcia Silva

2016-01-01

To investigate the prevalence and factors associated with mouth breathing among patients with developmental disabilities of a dental service. We analyzed 408 dental records. Mouth breathing was reported by the patients' parents and from direct observation. Other variables were as -follows: history of asthma, bronchitis, palate shape, pacifier use, thumb -sucking, nail biting, use of medications, gastroesophageal reflux, bruxism, gender, age, and diagnosis of the patient. Statistical analysis included descriptive analysis with ratio calculation and multiple logistic regression. Variables with p < 0.25 were included in the model to estimate the adjusted OR (95% CI), calculated by the forward stepwise method. Variables with p ​​< 0.05 were kept in the model. Being male (p = 0.016) and use of centrally acting drugs (p = 0.001) were the variables that remained in the model. Among patients with -developmental disabilities, boys and psychotropic drug users had a greater chance of being mouth breathers. © 2016 Special Care Dentistry Association and Wiley Periodicals, Inc.

Predicting hydrological response to forest changes by simple statistical models: the selection of the best indicator of forest changes with a hydrological perspective

NASA Astrophysics Data System (ADS)

Ning, D.; Zhang, M.; Ren, S.; Hou, Y.; Yu, L.; Meng, Z.

2017-01-01

Forest plays an important role in hydrological cycle, and forest changes will inevitably affect runoff across multiple spatial scales. The selection of a suitable indicator for forest changes is essential for predicting forest-related hydrological response. This study used the Meijiang River, one of the headwaters of the Poyang Lake as an example to identify the best indicator of forest changes for predicting forest change-induced hydrological responses. Correlation analysis was conducted first to detect the relationships between monthly runoff and its predictive variables including antecedent monthly precipitation and indicators for forest changes (forest coverage, vegetation indices including EVI, NDVI, and NDWI), and by use of the identified predictive variables that were most correlated with monthly runoff, multiple linear regression models were then developed. The model with best performance identified in this study included two independent variables -antecedent monthly precipitation and NDWI. It indicates that NDWI is the best indicator of forest change in hydrological prediction while forest coverage, the most commonly used indicator of forest change is insignificantly related to monthly runoff. This highlights the use of vegetation index such as NDWI to indicate forest changes in hydrological studies. This study will provide us with an efficient way to quantify the hydrological impact of large-scale forest changes in the Meijiang River watershed, which is crucial for downstream water resource management and ecological protection in the Poyang Lake basin.

[Predicting the outcome in severe injuries: an analysis of 2069 patients from the trauma register of the German Society of Traumatology (DGU)].

PubMed

Rixen, D; Raum, M; Bouillon, B; Schlosser, L E; Neugebauer, E

2001-03-01

On hospital admission numerous variables are documented from multiple trauma patients. The value of these variables to predict outcome are discussed controversially. The aim was the ability to initially determine the probability of death of multiple trauma patients. Thus, a multivariate probability model was developed based on data obtained from the trauma registry of the Deutsche Gesellschaft für Unfallchirurgie (DGU). On hospital admission the DGU trauma registry collects more than 30 variables prospectively. In the first step of analysis those variables were selected, that were assumed to be clinical predictors for outcome from literature. In a second step a univariate analysis of these variables was performed. For all primary variables with univariate significance in outcome prediction a multivariate logistic regression was performed in the third step and a multivariate prognostic model was developed. 2069 patients from 20 hospitals were prospectively included in the trauma registry from 01.01.1993-31.12.1997 (age 39 +/- 19 years; 70.0% males; ISS 22 +/- 13; 18.6% lethality). From more than 30 initially documented variables, the age, the GCS, the ISS, the base excess (BE) and the prothrombin time were the most important prognostic factors to predict the probability of death (P(death)). The following prognostic model was developed: P(death) = 1/1 + e(-[k + beta 1(age) + beta 2(GCS) + beta 3(ISS) + beta 4(BE) + beta 5(prothrombin time)]) where: k = -0.1551, beta 1 = 0.0438 with p < 0.0001, beta 2 = -0.2067 with p < 0.0001, beta 3 = 0.0252 with p = 0.0071, beta 4 = -0.0840 with p < 0.0001 and beta 5 = -0.0359 with p < 0.0001. Each of the five variables contributed significantly to the multifactorial model. These data show that the age, GCS, ISS, base excess and prothrombin time are potentially important predictors to initially identify multiple trauma patients with a high risk of lethality. With the base excess and prothrombin time value, as only variables of this multifactorial model that can be therapeutically influenced, it might be possible to better guide early and aggressive therapy.

Association of glycaemic variability evaluated by continuous glucose monitoring with diabetic peripheral neuropathy in type 2 diabetic patients.

PubMed

Hu, Yu-Ming; Zhao, Li-Hua; Zhang, Xiu-Lin; Cai, Hong-Li; Huang, Hai-Yan; Xu, Feng; Chen, Tong; Wang, Xue-Qin; Guo, Ai-Song; Li, Jian-An; Su, Jian-Bin

2018-05-01

Diabetic peripheral neuropathy (DPN), a common microvascular complication of diabetes, is linked to glycaemic derangements. Glycaemic variability, as a pattern of glycaemic derangements, is a key risk factor for diabetic complications. We investigated the association of glycaemic variability with DPN in a large-scale sample of type 2 diabetic patients. In this cross-sectional study, we enrolled 982 type 2 diabetic patients who were screened for DPN and monitored by a continuous glucose monitoring (CGM) system between February 2011 and January 2017. Multiple glycaemic variability parameters, including the mean amplitude of glycaemic excursions (MAGE), mean of daily differences (MODD), standard deviation of glucose (SD), and 24-h mean glucose (24-h MG), were calculated from glucose profiles obtained from CGM. Other possible risks for DPN were also examined. Of the recruited type 2 diabetic patients, 20.1% (n = 197) presented with DPN, and these patients also had a higher MAGE, MODD, SD, and 24-h MG than patients without DPN (p < 0.001). Using univariate and multiple logistic regression analyses, MAGE and conventional risks including diabetic duration, HOMA-IR, and hemoglobin A1c (HbA1c) were found to be independent contributors to DPN, and the corresponding odds ratios (95% confidence interval) were 4.57 (3.48-6.01), 1.10 (1.03-1.17), 1.24 (1.09-1.41), and 1.33 (1.15-1.53), respectively. Receiver operating characteristic analysis indicated that the optimal MAGE cutoff value for predicting DPN was 4.60 mmol/L; the corresponding sensitivity was 64.47%, and the specificity was 75.54%. In addition to conventional risks including diabetic duration, HOMA-IR and HbA1c, increased glycaemic variability assessed by MAGE is a significant independent contributor to DPN in type 2 diabetic patients.

A Brief History of the use of Electromagnetic Induction Techniques in Soil Survey

NASA Astrophysics Data System (ADS)

Brevik, Eric C.; Doolittle, James

2017-04-01

Electromagnetic induction (EMI) has been used to characterize the spatial variability of soil properties since the late 1970s. Initially used to assess soil salinity, the use of EMI in soil studies has expanded to include: mapping soil types; characterizing soil water content and flow patterns; assessing variations in soil texture, compaction, organic matter content, and pH; and determining the depth to subsurface horizons, stratigraphic layers or bedrock, among other uses. In all cases the soil property being investigated must influence soil apparent electrical conductivity (ECa) either directly or indirectly for EMI techniques to be effective. An increasing number and diversity of EMI sensors have been developed in response to users' needs and the availability of allied technologies, which have greatly improved the functionality of these tools and increased the amount and types of data that can be gathered with a single pass. EMI investigations provide several benefits for soil studies. The large amount of georeferenced data that can be rapidly and inexpensively collected with EMI provides more complete characterization of the spatial variations in soil properties than traditional sampling techniques. In addition, compared to traditional soil survey methods, EMI can more effectively characterize diffuse soil boundaries and identify included areas of dissimilar soils within mapped soil units, giving soil scientists greater confidence when collecting spatial soil information. EMI techniques do have limitations; results are site-specific and can vary depending on the complex interactions among multiple and variable soil properties. Despite this, EMI techniques are increasingly being used to investigate the spatial variability of soil properties at field and landscape scales. The future should witness a greater use of multiple-frequency and multiple-coil EMI sensors and integration with other sensors to assess the spatial variability of soil properties. Data analysis will be improved with advanced processing and presentation systems and more sophisticated geostatistical modeling algorithms will be developed and used to interpolate EMI data, improve the resolution of subsurface features, and assess soil properties.

Effect Of Long-Period Earthquake Ground Motions On Nonlinear Vibration Of Shells With Variable Thickness

NASA Astrophysics Data System (ADS)

Abdikarimov, R.; Bykovtsev, A.; Khodzhaev, D.; Research Team Of Geotechnical; Structural Engineers

2010-12-01

Long-period earthquake ground motions (LPEGM) with multiple oscillations have become a crucial consideration in seismic hazard assessment because of the rapid increase of tall buildings and special structures (SP).Usually, SP refers to innovative long-span structural systems. More specifically, they include many types of structures, such as: geodesic showground; folded plates; and thin shells. As continuation of previous research (Bykovtsev, Abdikarimov, Khodzhaev 2003, 2010) analysis of nonlinear vibrations (NV) and dynamic stability of SP simulated as shells with variable rigidity in geometrically nonlinear statement will be presented for two cases. The first case will represent NV example of a viscoelastic orthotropic cylindrical shell with radius R, length L and variable thickness h=h(x,y). The second case will be NV example of a viscoelastic shell with double curvature, variable thickness, and bearing the concentrated masses. In both cases we count, that the SP will be operates under seismic load generated by LPEGM with multiple oscillations. For different seismic loads simulations, Bykovtsev’s Model and methodology was used for generating LPEGM time history. The methodology for synthesizing LPEGM from fault with multiple segmentations was developed by Bykovtev (1978-2010) and based on 3D-analytical solutions by Bykovtsev-Kramarovskii (1987&1989) constructed for faults with multiple segmentations. This model is based on a kinematics description of displacement function on the fault and included in consideration of all possible combinations of 3 components of vector displacement (two slip vectors and one tension component). The opportunities to take into consideration fault segmentations with both shear and tension vector components of displacement on the fault plane provide more accurate LPEGM evaluations. Radiation patterns and directivity effects were included in the model and more physically realistic results for simulated LPEGM were considered. The system of nonlinear integro-differential equations (NIDE) with variable coefficients concerning a deflection w=w(x,y) and displacements u=u(x,y), v=v(x,y) was used for construction mathematical model of the problem. The Kichhoff-Love hypothesis was used as basis for description physical and geometrical relations and construction of a discrete model of nonlinear problems dynamic theory of viscoelasticity. The most effective variational Bubnov-Galerkin method was used for obtaining Volterra type system of NIDE. The integration of the obtained equations system was carried out with the help of the numerical method based on quadrature formula. The computer codes on algorithmic language Delphi were created for investigation amplitude-time, deflected mode and torque-time characteristic of vibrations of the viscoelastic shells. For real composite materials at wide ranges of change of physical-mechanical and geometrical parameters the behavior of shells were investigated. Calculations were carried out at different laws of change of thickness. Results will be presented as graphs and tables.

Multiple periodic-soliton solutions of the (3+1)-dimensional generalised shallow water equation

NASA Astrophysics Data System (ADS)

Li, Ye-Zhou; Liu, Jian-Guo

2018-06-01

Based on the extended variable-coefficient homogeneous balance method and two new ansätz functions, we construct auto-Bäcklund transformation and multiple periodic-soliton solutions of (3 {+} 1)-dimensional generalised shallow water equations. Completely new periodic-soliton solutions including periodic cross-kink wave, periodic two-solitary wave and breather type of two-solitary wave are obtained. In addition, cross-kink three-soliton and cross-kink four-soliton solutions are derived. Furthermore, propagation characteristics and interactions of the obtained solutions are discussed and illustrated in figures.

Health-related quality of life in multiple sclerosis: role of cognitive appraisals of self, illness and treatment.

PubMed

Wilski, Maciej; Tasiemski, Tomasz

2016-07-01

Health-related quality of life (HRQoL) is considered an important measure of treatment and rehabilitation outcomes in multiple sclerosis (MS) patients. In this study, we used multivariate regression analysis to examine the role of cognitive appraisals, adjusted for clinical, socioeconomic and demographic variables, as correlates of HRQoL in MS. The cross-sectional study included 257 MS patients, who completed Multiple Sclerosis Impact Scale, Generalized Self-Efficacy Scale, Rosenberg Self-Esteem Scale, Brief Illness Perception Questionnaire, Treatment Beliefs Scale, Actually Received Support Scale (a part of Berlin Social Support Scale) and Socioeconomic Resources Scale. Demographic and clinical characteristics of the participants were collected with a self-report survey. Correlation and regression analyses were conducted to determine associations between the variables. Five variables, illness identity (β = 0.29, p ≤ 0.001), self-esteem (β = -0.22, p ≤ 0.001), general self-efficacy (β = -0.21, p ≤ 0.001), disability subgroup "EDSS" (β = 0.14, p = 0.006) and age (β = 0.12, p = 0.012), were significant correlates of HRQoL in MS. These variables explained 46 % of variance in the dependent variable. Moreover, we identified correlates of physical and psychological dimensions of HRQoL. Cognitive appraisals, such as general self-efficacy, self-esteem and illness perception, are more salient correlates of HRQoL than social support, socioeconomic resources and clinical characteristics, such as type and duration of MS. Therefore, interventions aimed at cognitive appraisals may also improve HRQoL of MS patients.

Complementary Roles for Amygdala and Periaqueductal Gray in Temporal-Difference Fear Learning

ERIC Educational Resources Information Center

Cole, Sindy; McNally, Gavan P.

2009-01-01

Pavlovian fear conditioning is not a unitary process. At the neurobiological level multiple brain regions and neurotransmitters contribute to fear learning. At the behavioral level many variables contribute to fear learning including the physical salience of the events being learned about, the direction and magnitude of predictive error, and the…

The Measurement and Cost of Removing Unexplained Gender Differences in Faculty Salaries.

ERIC Educational Resources Information Center

Becker, William E.; Toutkoushian, Robert K.

1995-01-01

In assessing sex-discrimination suit damages, debate rages over the type and number of variables included in a single-equation model of the salary-determination process. This article considers single- and multiple-equation models, providing 36 different damage calculations. For University of Minnesota data, equalization cost hinges on the…

Choice between Single and Multiple Reinforcers in Concurrent-Chains Schedules

ERIC Educational Resources Information Center

Mazur, James E.

2006-01-01

Pigeons responded on concurrent-chains schedules with equal variable-interval schedules as initial links. One terminal link delivered a single reinforcer after a fixed delay, and the other terminal link delivered either three or five reinforcers, each preceded by a fixed delay. Some conditions included a postreinforcer delay after the single…

Fiscal Viability, Conjunctive and Compensatory Models, and Career-Ladder Decisions: An Empirical Investigation.

ERIC Educational Resources Information Center

Mehrens, William A.; And Others

A study was undertaken to explore cost-effective ways of making career ladder teacher evaluation system decisions based on fewer measures, assessing the relationship of observational variables to other data and final decisions, and comparison of compensatory and conjunctive decision models. Data included multiple scores from eight data sources in…

Predictors of College Readiness: An Analysis of the Student Readiness Inventory

ERIC Educational Resources Information Center

Wilson, James K., III

2012-01-01

The purpose of this study was to better predict how a first semester college freshman becomes prepared for college. The theoretical framework guiding this study is Vrooms' expectancy theory, motivation plays a key role in success. This study used a hierarchical multiple regression model. The independent variables of interest included high school…

Missouri Ozark forest soils: perspectives and realities

Treesearch

R. David. Hammer

1997-01-01

Ozark forest soils are dynamic in space and time, and most formed in multiple parent materials. Erosion and mass movement have been variable and extensive. Soil attributes including texture, cation exchange capacity, and mineralogy are related to geologic strata and to geomorphic conditions. Soil organic carbon content is influenced by surface shape, position in...

Growth and demography of Pinaleno high elevation forests

Treesearch

Christopher O' Connor; Donald A. Falk; Ann M. Lynch; Craig P. Wilcox; Thomas W. Swetnam; Tyson L. Swetnam

2010-01-01

The project goal is to understand how multiple disturbance events including fire, insect outbreaks, and climate variability interact in space and time, and how they combine to influence forest species composition, spatial structure, and tree population dynamics in high elevation forests of the Pinaleno Mountains. Information from each of these components is needed in...

Multiple Logistic Regression Analysis of Cigarette Use among High School Students

ERIC Educational Resources Information Center

Adwere-Boamah, Joseph

2011-01-01

A binary logistic regression analysis was performed to predict high school students' cigarette smoking behavior from selected predictors from 2009 CDC Youth Risk Behavior Surveillance Survey. The specific target student behavior of interest was frequent cigarette use. Five predictor variables included in the model were: a) race, b) frequency of…

Correlation Study of Physics Achievement, Learning Strategy, Attitude and Gender in an Introductory Physics Course

ERIC Educational Resources Information Center

Sezgin Selcuk, Gamze

2010-01-01

This study investigates the relationship between multiple predictors of physics achievement including reported use of four learning strategy clusters (elaboration, organization, comprehension monitoring and rehearsal), attitudes towards physics (sense of care and sense of interest) and a demographic variable (gender) in order to determine the…

Relationships between Observations of Elementary Mathematics Instruction and Student Achievement: Exploring Variability across Districts

ERIC Educational Resources Information Center

Lynch, Kathleen; Chin, Mark; Blazar, David

2017-01-01

Much debate surrounding teacher quality has focused on students' standardized test scores, but recent federal and state initiatives have emphasized the use of multiple measures to evaluate teacher quality, including classroom observations. In this study, we explore differences across school districts in the relationship between student achievement…

Clinical dysphagia risk predictors after prolonged orotracheal intubation

PubMed Central

de Medeiros, Gisele Chagas; Sassi, Fernanda Chiarion; Mangilli, Laura Davison; Zilberstein, Bruno; de Andrade, Claudia Regina Furquim

2014-01-01

OBJECTIVES: To elucidate independent risk factors for dysphagia after prolonged orotracheal intubation. METHODS: The participants were 148 consecutive patients who underwent clinical bedside swallowing assessments from September 2009 to September 2011. All patients had received prolonged orotracheal intubations and were admitted to one of several intensive care units of a large Brazilian school hospital. The correlations between the conducted water swallow test results and dysphagia risk levels were analyzed for statistical significance. RESULTS: Of the 148 patients included in the study, 91 were male and 57 were female (mean age, 53.64 years). The univariate analysis results indicated that specific variables, including extraoral loss, multiple swallows, cervical auscultation, vocal quality, cough, choking, and other signs, were possible significant high-risk indicators of dysphagia onset. The multivariate analysis results indicated that cervical auscultation and coughing were independent predictive variables for high dysphagia risk. CONCLUSIONS: Patients displaying extraoral loss, multiple swallows, cervical auscultation, vocal quality, cough, choking and other signs should benefit from early swallowing evaluations. Additionally, early post-extubation dysfunction recognition is paramount in reducing the morbidity rate in this high-risk population. PMID:24473554

Underlying-event sensitive observables in Drell–Yan production using GENEVA

DOE PAGES

Alioli, Simone; Bauer, Christian W.; Guns, Sam; ...

2016-11-09

We present an extension of the Geneva Monte Carlo framework to include multiple parton interactions (MPI) provided by Pythia8. This allows us to obtain predictions for underlying-event sensitive measurements in Drell–Yan production, in conjunction with Geneva ’s fully differential NNLO calculation, NNLL' resummation for the 0-jet resolution variable (beam thrust), and NLL resummation for the 1-jet resolution variable. We describe the interface with the parton-shower algorithm and MPI model of Pythia8, which preserves both the precision of the partonic N-jet cross sections in Geneva as well as the shower accuracy and good description of soft hadronic physics of Pythia8. Wemore » present results for several underlying-event sensitive observables and compare to data from ATLAS and CMS as well as to standalone Pythia8 predictions. This includes a comparison with the recent ATLAS measurement of the beam thrust spectrum, which provides a potential avenue to fully disentangle the physical effects from the primary hard interaction, primary soft radiation, multiple parton interactions, and nonperturbative hadronization.« less

Underlying-event sensitive observables in Drell–Yan production using GENEVA

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

Alioli, Simone; Bauer, Christian W.; Guns, Sam

We present an extension of the Geneva Monte Carlo framework to include multiple parton interactions (MPI) provided by Pythia8. This allows us to obtain predictions for underlying-event sensitive measurements in Drell–Yan production, in conjunction with Geneva ’s fully differential NNLO calculation, NNLL' resummation for the 0-jet resolution variable (beam thrust), and NLL resummation for the 1-jet resolution variable. We describe the interface with the parton-shower algorithm and MPI model of Pythia8, which preserves both the precision of the partonic N-jet cross sections in Geneva as well as the shower accuracy and good description of soft hadronic physics of Pythia8. Wemore » present results for several underlying-event sensitive observables and compare to data from ATLAS and CMS as well as to standalone Pythia8 predictions. This includes a comparison with the recent ATLAS measurement of the beam thrust spectrum, which provides a potential avenue to fully disentangle the physical effects from the primary hard interaction, primary soft radiation, multiple parton interactions, and nonperturbative hadronization.« less

Clinical dysphagia risk predictors after prolonged orotracheal intubation.

PubMed

Medeiros, Gisele Chagas de; Sassi, Fernanda Chiarion; Mangilli, Laura Davison; Zilberstein, Bruno; Andrade, Claudia Regina Furquim de

2014-01-01

To elucidate independent risk factors for dysphagia after prolonged orotracheal intubation. The participants were 148 consecutive patients who underwent clinical bedside swallowing assessments from September 2009 to September 2011. All patients had received prolonged orotracheal intubations and were admitted to one of several intensive care units of a large Brazilian school hospital. The correlations between the conducted water swallow test results and dysphagia risk levels were analyzed for statistical significance. Of the 148 patients included in the study, 91 were male and 57 were female (mean age, 53.64 years). The univariate analysis results indicated that specific variables, including extraoral loss, multiple swallows, cervical auscultation, vocal quality, cough, choking, and other signs, were possible significant high-risk indicators of dysphagia onset. The multivariate analysis results indicated that cervical auscultation and coughing were independent predictive variables for high dysphagia risk. Patients displaying extraoral loss, multiple swallows, cervical auscultation, vocal quality, cough, choking and other signs should benefit from early swallowing evaluations. Additionally, early post-extubation dysfunction recognition is paramount in reducing the morbidity rate in this high-risk population.

Work-related problems in multiple sclerosis: a literature review on its associates and determinants.

PubMed

Raggi, Alberto; Covelli, Venusia; Schiavolin, Silvia; Scaratti, Chiara; Leonardi, Matilde; Willems, Michelle

2016-01-01

To explore which variables are associated to or determinants of work-related difficulties or unemployment in persons with multiple sclerosis (MS). Papers published between 1993 and February 2015 were included. Quality was judged as poor, acceptable, good or excellent. Determinants were extracted from prospective and retrospective data, associated variables from cross-sectional data; variables were grouped by similarity. Evidence was judged as strong if there were at least two good studies reporting the same results; limited if there was only one good and some acceptable studies. Forty-two papers were selected, for a total of 31,192 patients (75% females). Work-related difficulties were referred as unemployment, lower amount of worked hours or job cessation. Strong evidence of impact over work-related difficulties was found for a core set of variables, i.e., expanded disability status scale, MS duration, patients' age, fatigue and walking problems. Little evidence exists on the impact of contextual factors. Most of the variables identified as associated to or determinants of work-related difficulties can be treated through rehabilitative interventions. It is important that future research addresses not only unemployment issues in MS, but also the amount and severity of problems affecting work-related tasks relying on specific assessment instruments. Multiple sclerosis (MS) affects young persons of working age and limitation in work activities is part of MS-related disability, but they are not consistently addressed in MS research: EDSS, MS duration, patients' age, fatigue, walking problems, cognitive and neuropsychological impairments were the factors most commonly found as associated to or determinant of difficulties with work. Evidence exists that rehabilitation interventions are effective for fatigue, cognitive impairment, mobility and walking difficulties. However, research did not address the impact of rehabilitation programmes on vocational outcomes. Rehabilitation researchers should include MS-specific assessment instruments for work-related difficulties to standardised clinical protocols, so that the benefits of rehabilitation on persons' ability to work can be demonstrated directly: in this way, cost-benefit balance analyses can be added to the evaluation of treatment effectiveness.

Multiple Sclerosis and Catastrophic Health Expenditure in Iran.

PubMed

Juyani, Yaser; Hamedi, Dorsa; Hosseini Jebeli, Seyede Sedighe; Qasham, Maryam

2016-09-01

There are many disabling medical conditions which can result in catastrophic health expenditure. Multiple Sclerosis is one of the most costly medical conditions through the world which encounter families to the catastrophic health expenditures. This study aims to investigate on what extent Multiple sclerosis patients face catastrophic costs. This study was carried out in Ahvaz, Iran (2014). The study population included households that at least one of their members suffers from MS. To analyze data, Logit regression model was employed by using the default software STATA12. 3.37% of families were encountered with catastrophic costs. Important variables including brand of drug, housing, income and health insurance were significantly correlated with catastrophic expenditure. This study suggests that although a small proportion of MS patients met the catastrophic health expenditure, mechanisms that pool risk and cost (e.g. health insurance) are required to protect them and improve financial and access equity in health care.

Tehran Survey of Potential Risk Factors for Multiple Births.

PubMed

Omani Samani, Reza; Almasi-Hashiani, Amir; Vesali, Samira; Shokri, Fatemeh; Cheraghi, Rezvaneh; Torkestani, Farahnaz; Sepidarkish, Mahdi

2017-10-01

The multiple pregnancy incidence is increasing worldwide. This increased incidence is concerning to the health care system. This study aims to determine the frequency of multiple pregnancy and identify factors that affect this frequency in Tehran, Iran. This cross-sectional study included 5170 mothers in labor between July 6-21, 2015 from 103 hospitals with Obstetrics and Gynecology Wards. The questionnaire used in this study consisted of five parts: demographic characteristics; information related to pregnancy; information related to the infant; information regarding the multiple pregnancy; and information associated with infertility. We recruited 103 trained midwives to collect data related to the questionnaire from eligible participants through an interview and medical records review. Frequencies and odds ratios (OR) for the association between multiple pregnancy and the selected characteristics (maternal age, economic status, history of multiple pregnancy in first-degree relatives, and reproductive history) were computed by multiple logistic regression. Stata software, version 13 (Stata Corp, College Station, TX, USA) was used for all statistical analyses. Multiple pregnancy had a prevalence of 1.48% [95% confidence interval (CI): 1.19-1.85]. After controlling for confounding variables, we observed a significant association between frequency of multiple pregnancy and mother's age (OR=1.04, 95% CI: 1.001-1.09, P=0.044), assisted reproductive technique (ART, OR=6.11, 95% CI: 1.7- 21.97, P=0.006), and history of multiple pregnancy in the mother's family (OR=5.49, 95% CI: 3.55-9.93, P=0.001). The frequency of multiple pregnancy approximated results reported in previous studies in Iran. Based on the results, we observed significantly greater frequency of multiple pregnancy in older women, those with a history of ART, and a history of multiple pregnancy in the mother's family compared to the other variables. Copyright© by Royan Institute. All rights reserved.

A Methodological Review of Meditation Research

PubMed Central

Thomas, John W.; Cohen, Marc

2014-01-01

Despite over 50 years of research into the states of consciousness induced by various meditation practices, no clear neurophysiological signatures of these states have been found. Much of this failure can be attributed to the narrow range of variables examined in most meditation studies, with the focus being restricted to a search for correlations between neurophysiological measures and particular practices, without documenting the content and context of these practices. We contend that more meaningful results can be obtained by expanding the methodological paradigm to include multiple domains including: the cultural setting (“the place”), the life situation of the meditator (“the person”), details of the particular meditation practice (‘the practice’), and the state of consciousness of the meditator (“the phenomenology”). Inclusion of variables from all these domains will improve the ability to predict the psychophysiological variables (“the psychophysiology”) associated with specific meditation states and thus explore the mysteries of human consciousness. PMID:25071607

Variable selection in near-infrared spectroscopy: benchmarking of feature selection methods on biodiesel data.

PubMed

Balabin, Roman M; Smirnov, Sergey V

2011-04-29

During the past several years, near-infrared (near-IR/NIR) spectroscopy has increasingly been adopted as an analytical tool in various fields from petroleum to biomedical sectors. The NIR spectrum (above 4000 cm(-1)) of a sample is typically measured by modern instruments at a few hundred of wavelengths. Recently, considerable effort has been directed towards developing procedures to identify variables (wavelengths) that contribute useful information. Variable selection (VS) or feature selection, also called frequency selection or wavelength selection, is a critical step in data analysis for vibrational spectroscopy (infrared, Raman, or NIRS). In this paper, we compare the performance of 16 different feature selection methods for the prediction of properties of biodiesel fuel, including density, viscosity, methanol content, and water concentration. The feature selection algorithms tested include stepwise multiple linear regression (MLR-step), interval partial least squares regression (iPLS), backward iPLS (BiPLS), forward iPLS (FiPLS), moving window partial least squares regression (MWPLS), (modified) changeable size moving window partial least squares (CSMWPLS/MCSMWPLSR), searching combination moving window partial least squares (SCMWPLS), successive projections algorithm (SPA), uninformative variable elimination (UVE, including UVE-SPA), simulated annealing (SA), back-propagation artificial neural networks (BP-ANN), Kohonen artificial neural network (K-ANN), and genetic algorithms (GAs, including GA-iPLS). Two linear techniques for calibration model building, namely multiple linear regression (MLR) and partial least squares regression/projection to latent structures (PLS/PLSR), are used for the evaluation of biofuel properties. A comparison with a non-linear calibration model, artificial neural networks (ANN-MLP), is also provided. Discussion of gasoline, ethanol-gasoline (bioethanol), and diesel fuel data is presented. The results of other spectroscopic techniques application, such as Raman, ultraviolet-visible (UV-vis), or nuclear magnetic resonance (NMR) spectroscopies, can be greatly improved by an appropriate feature selection choice. Copyright © 2011 Elsevier B.V. All rights reserved.

Neural correlates of gait variability in people with multiple sclerosis with fall history.

PubMed

Kalron, Alon; Allali, Gilles; Achiron, Anat

2018-05-28

Investigate the association between step time variability and related brain structures in accordance with fall status in people with multiple sclerosis (PwMS). The study included 225 PwMS. A whole-brain MRI was performed by a high-resolution 3.0-Telsa MR scanner in addition to volumetric analysis based on 3D T1-weighted images using the FreeSurfer image analysis suite. Step time variability was measured by an electronic walkway. Participants were defined as "fallers" (at least two falls during the previous year) and "non-fallers". One hundred and five PwMS were defined as fallers and had a greater step time variability compared to non-fallers (5.6% (S.D.=3.4) vs. 3.4% (S.D.=1.5); p=0.001). MS fallers exhibited a reduced volume in the left caudate and both cerebellum hemispheres compared to non-fallers. By using a linear regression analysis no association was found between gait variability and related brain structures in the total cohort and non-fallers group. However, the analysis found an association between the left hippocampus and left putamen volumes with step time variability in the faller group; p=0.031, 0.048, respectively, controlling for total cranial volume, walking speed, disability, age and gender. Nevertheless, according to the hierarchical regression model, the contribution of these brain measures to predict gait variability was relatively small compared to walking speed. An association between low left hippocampal, putamen volumes and step time variability was found in PwMS with a history of falls, suggesting brain structural characteristics may be related to falls and increased gait variability in PwMS. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Fusing Data Mining, Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression

PubMed Central

Dipnall, Joanna F.

2016-01-01

Background Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took account of missing data and complex survey design to identify key biomarkers associated with depression from a large epidemiological study. Methods The study used a three-step methodology amalgamating multiple imputation, a machine learning boosted regression algorithm and logistic regression, to identify key biomarkers associated with depression in the National Health and Nutrition Examination Study (2009–2010). Depression was measured using the Patient Health Questionnaire-9 and 67 biomarkers were analysed. Covariates in this study included gender, age, race, smoking, food security, Poverty Income Ratio, Body Mass Index, physical activity, alcohol use, medical conditions and medications. The final imputed weighted multiple logistic regression model included possible confounders and moderators. Results After the creation of 20 imputation data sets from multiple chained regression sequences, machine learning boosted regression initially identified 21 biomarkers associated with depression. Using traditional logistic regression methods, including controlling for possible confounders and moderators, a final set of three biomarkers were selected. The final three biomarkers from the novel hybrid variable selection methodology were red cell distribution width (OR 1.15; 95% CI 1.01, 1.30), serum glucose (OR 1.01; 95% CI 1.00, 1.01) and total bilirubin (OR 0.12; 95% CI 0.05, 0.28). Significant interactions were found between total bilirubin with Mexican American/Hispanic group (p = 0.016), and current smokers (p<0.001). Conclusion The systematic use of a hybrid methodology for variable selection, fusing data mining techniques using a machine learning algorithm with traditional statistical modelling, accounted for missing data and complex survey sampling methodology and was demonstrated to be a useful tool for detecting three biomarkers associated with depression for future hypothesis generation: red cell distribution width, serum glucose and total bilirubin. PMID:26848571

Fusing Data Mining, Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression.

PubMed

Dipnall, Joanna F; Pasco, Julie A; Berk, Michael; Williams, Lana J; Dodd, Seetal; Jacka, Felice N; Meyer, Denny

2016-01-01

Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took account of missing data and complex survey design to identify key biomarkers associated with depression from a large epidemiological study. The study used a three-step methodology amalgamating multiple imputation, a machine learning boosted regression algorithm and logistic regression, to identify key biomarkers associated with depression in the National Health and Nutrition Examination Study (2009-2010). Depression was measured using the Patient Health Questionnaire-9 and 67 biomarkers were analysed. Covariates in this study included gender, age, race, smoking, food security, Poverty Income Ratio, Body Mass Index, physical activity, alcohol use, medical conditions and medications. The final imputed weighted multiple logistic regression model included possible confounders and moderators. After the creation of 20 imputation data sets from multiple chained regression sequences, machine learning boosted regression initially identified 21 biomarkers associated with depression. Using traditional logistic regression methods, including controlling for possible confounders and moderators, a final set of three biomarkers were selected. The final three biomarkers from the novel hybrid variable selection methodology were red cell distribution width (OR 1.15; 95% CI 1.01, 1.30), serum glucose (OR 1.01; 95% CI 1.00, 1.01) and total bilirubin (OR 0.12; 95% CI 0.05, 0.28). Significant interactions were found between total bilirubin with Mexican American/Hispanic group (p = 0.016), and current smokers (p<0.001). The systematic use of a hybrid methodology for variable selection, fusing data mining techniques using a machine learning algorithm with traditional statistical modelling, accounted for missing data and complex survey sampling methodology and was demonstrated to be a useful tool for detecting three biomarkers associated with depression for future hypothesis generation: red cell distribution width, serum glucose and total bilirubin.

Modeling non-linear growth responses to temperature and hydrology in wetland trees

NASA Astrophysics Data System (ADS)

Keim, R.; Allen, S. T.

2016-12-01

Growth responses of wetland trees to flooding and climate variations are difficult to model because they depend on multiple, apparently interacting factors, but are a critical link in hydrological control of wetland carbon budgets. To more generally understand tree growth to hydrological forcing, we modeled non-linear responses of tree ring growth to flooding and climate at sub-annual time steps, using Vaganov-Shashkin response functions. We calibrated the model to six baldcypress tree-ring chronologies from two hydrologically distinct sites in southern Louisiana, and tested several hypotheses of plasticity in wetlands tree responses to interacting environmental variables. The model outperformed traditional multiple linear regression. More importantly, optimized response parameters were generally similar among sites with varying hydrological conditions, suggesting generality to the functions. Model forms that included interacting responses to multiple forcing factors were more effective than were single response functions, indicating the principle of a single limiting factor is not correct in wetlands and both climatic and hydrological variables must be considered in predicting responses to hydrological or climate change.

Integrated presentation of ecological risk from multiple stressors

NASA Astrophysics Data System (ADS)

Goussen, Benoit; Price, Oliver R.; Rendal, Cecilie; Ashauer, Roman

2016-10-01

Current environmental risk assessments (ERA) do not account explicitly for ecological factors (e.g. species composition, temperature or food availability) and multiple stressors. Assessing mixtures of chemical and ecological stressors is needed as well as accounting for variability in environmental conditions and uncertainty of data and models. Here we propose a novel probabilistic ERA framework to overcome these limitations, which focusses on visualising assessment outcomes by construct-ing and interpreting prevalence plots as a quantitative prediction of risk. Key components include environmental scenarios that integrate exposure and ecology, and ecological modelling of relevant endpoints to assess the effect of a combination of stressors. Our illustrative results demonstrate the importance of regional differences in environmental conditions and the confounding interactions of stressors. Using this framework and prevalence plots provides a risk-based approach that combines risk assessment and risk management in a meaningful way and presents a truly mechanistic alternative to the threshold approach. Even whilst research continues to improve the underlying models and data, regulators and decision makers can already use the framework and prevalence plots. The integration of multiple stressors, environmental conditions and variability makes ERA more relevant and realistic.

Social Cognitive Correlates of Physical Activity in Black Individuals With Multiple Sclerosis.

PubMed

Kinnett-Hopkins, Dominique; Motl, Robert W

2016-04-01

To examine variables from social cognitive theory as correlates of physical activity in black and white individuals with multiple sclerosis (MS). Cross-sectional. National survey. Black (n=151) and white (n=185) individuals with MS were recruited through the North American Research Committee on Multiple Sclerosis Registry. Not applicable. The battery of questionnaires included information on demographic and clinical characteristics, physical activity, exercise self-efficacy, function, social support, exercise outcome expectations, and exercise goal setting and planning. Black individuals with MS reported significantly lower levels of physical activity compared with white individuals with MS. Physical activity levels were significantly correlated with self-efficacy, outcome expectations, functional limitations as impediments, and goal setting in black participants with MS. The pattern and magnitude of correlations were comparable with those observed in white participants based on Fisher z tests. Researchers should consider applying behavioral interventions that target social cognitive theory variables for increasing physical activity levels among black individuals with MS. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Integrated presentation of ecological risk from multiple stressors.

PubMed

Goussen, Benoit; Price, Oliver R; Rendal, Cecilie; Ashauer, Roman

2016-10-26

Current environmental risk assessments (ERA) do not account explicitly for ecological factors (e.g. species composition, temperature or food availability) and multiple stressors. Assessing mixtures of chemical and ecological stressors is needed as well as accounting for variability in environmental conditions and uncertainty of data and models. Here we propose a novel probabilistic ERA framework to overcome these limitations, which focusses on visualising assessment outcomes by construct-ing and interpreting prevalence plots as a quantitative prediction of risk. Key components include environmental scenarios that integrate exposure and ecology, and ecological modelling of relevant endpoints to assess the effect of a combination of stressors. Our illustrative results demonstrate the importance of regional differences in environmental conditions and the confounding interactions of stressors. Using this framework and prevalence plots provides a risk-based approach that combines risk assessment and risk management in a meaningful way and presents a truly mechanistic alternative to the threshold approach. Even whilst research continues to improve the underlying models and data, regulators and decision makers can already use the framework and prevalence plots. The integration of multiple stressors, environmental conditions and variability makes ERA more relevant and realistic.

Seasonally asymmetric enhancement of northern vegetation productivity

NASA Astrophysics Data System (ADS)

Park, T.; Myneni, R.

2017-12-01

Multiple evidences of widespread greening and increasing terrestrial carbon uptake have been documented. In particular, enhanced gross productivity of northern vegetation has been a critical role leading to observed carbon uptake trend. However, seasonal photosynthetic activity and its contribution to observed annual carbon uptake trend and interannual variability are not well understood. Here, we introduce a multiple-source of datasets including ground, atmospheric and satellite observations, and multiple process-based global vegetation models to understand how seasonal variation of land surface vegetation controls a large-scale carbon exchange. Our analysis clearly shows a seasonally asymmetric enhancement of northern vegetation productivity in growing season during last decades. Particularly, increasing gross productivity in late spring and early summer is obvious and dominant driver explaining observed trend and variability. We observe more asymmetric productivity enhancement in warmer region and this spatially varying asymmetricity in northern vegetation are likely explained by canopy development rate, thermal and light availability. These results imply that continued warming may facilitate amplifying asymmetric vegetation activity and cause these trends to become more pervasive, in turn warming induced regime shift in northern land.

Multiplicative processes in visual cognition

NASA Astrophysics Data System (ADS)

Credidio, H. F.; Teixeira, E. N.; Reis, S. D. S.; Moreira, A. A.; Andrade, J. S.

2014-03-01

The Central Limit Theorem (CLT) is certainly one of the most important results in the field of statistics. The simple fact that the addition of many random variables can generate the same probability curve, elucidated the underlying process for a broad spectrum of natural systems, ranging from the statistical distribution of human heights to the distribution of measurement errors, to mention a few. An extension of the CLT can be applied to multiplicative processes, where a given measure is the result of the product of many random variables. The statistical signature of these processes is rather ubiquitous, appearing in a diverse range of natural phenomena, including the distributions of incomes, body weights, rainfall, and fragment sizes in a rock crushing process. Here we corroborate results from previous studies which indicate the presence of multiplicative processes in a particular type of visual cognition task, namely, the visual search for hidden objects. Precisely, our results from eye-tracking experiments show that the distribution of fixation times during visual search obeys a log-normal pattern, while the fixational radii of gyration follow a power-law behavior.

Variables Associated with Communicative Participation in People with Multiple Sclerosis: A Regression Analysis

ERIC Educational Resources Information Center

Baylor, Carolyn; Yorkston, Kathryn; Bamer, Alyssa; Britton, Deanna; Amtmann, Dagmar

2010-01-01

Purpose: To explore variables associated with self-reported communicative participation in a sample (n = 498) of community-dwelling adults with multiple sclerosis (MS). Method: A battery of questionnaires was administered online or on paper per participant preference. Data were analyzed using multiple linear backward stepwise regression. The…

Investigating Factorial Invariance of Latent Variables Across Populations When Manifest Variables Are Missing Completely

PubMed Central

Widaman, Keith F.; Grimm, Kevin J.; Early, Dawnté R.; Robins, Richard W.; Conger, Rand D.

2013-01-01

Difficulties arise in multiple-group evaluations of factorial invariance if particular manifest variables are missing completely in certain groups. Ad hoc analytic alternatives can be used in such situations (e.g., deleting manifest variables), but some common approaches, such as multiple imputation, are not viable. At least 3 solutions to this problem are viable: analyzing differing sets of variables across groups, using pattern mixture approaches, and a new method using random number generation. The latter solution, proposed in this article, is to generate pseudo-random normal deviates for all observations for manifest variables that are missing completely in a given sample and then to specify multiple-group models in a way that respects the random nature of these values. An empirical example is presented in detail comparing the 3 approaches. The proposed solution can enable quantitative comparisons at the latent variable level between groups using programs that require the same number of manifest variables in each group. PMID:24019738

Prediction of the birch pollen season characteristics in Cracow, Poland using an 18-year data series.

PubMed

Dorota, Myszkowska

2013-03-01

The aim of the study was to construct the model forecasting the birch pollen season characteristics in Cracow on the basis of an 18-year data series. The study was performed using the volumetric method (Lanzoni/Burkard trap). The 98/95 % method was used to calculate the pollen season. The Spearman's correlation test was applied to find the relationship between the meteorological parameters and pollen season characteristics. To construct the predictive model, the backward stepwise multiple regression analysis was used including the multi-collinearity of variables. The predictive models best fitted the pollen season start and end, especially models containing two independent variables. The peak concentration value was predicted with the higher prediction error. Also the accuracy of the models predicting the pollen season characteristics in 2009 was higher in comparison with 2010. Both, the multi-variable model and one-variable model for the beginning of the pollen season included air temperature during the last 10 days of February, while the multi-variable model also included humidity at the beginning of April. The models forecasting the end of the pollen season were based on temperature in March-April, while the peak day was predicted using the temperature during the last 10 days of March.

The Role of C-Peptide as Marker of Cardiometabolic Risk in Women With Polycystic Ovary Syndrome: A Controlled Study

PubMed Central

de Medeiros, Sebastiao Freitas; Angelo, Laura Camila Antunes; de Medeiros, Matheus Antonio Souto; Banhara, Camila Regis; Barbosa, Bruna Barcelo; Yamamoto, Marcia Marly Winck

2018-01-01

Background The aim of this study was to examine the role of C-peptide as a biological marker of cardiometabolic risk in polycystic ovary syndrome (PCOS). Methods This case-control study enrolled 385 PCOS patients and 240 normal cycling women. Anthropometric and clinical variables were taken at first visit. Fasting C-peptide, glucose, lipids, and hormone measurements were performed. Simple and multiple correlations between C-peptide and other variables associated with dysmetabolism and cardiovascular disease were examined. Results C-peptide was well correlated with several anthropometric, metabolic, and endocrine parameters. In PCOS patients, stepwise multiple regression including C-peptide as the criterion variable and other predictors of cardiovascular disease risk provided a significant model in which the fasting C-peptide/glucose ratio, glucose, body weight, and free estrogen index (FEI) were retained (adjusted R2 = 0.988, F = 7.161, P = 0.008). Conclusion C-peptide levels alone or combined with C-peptide/glucose ratio, glucose, body weight, and FEI provided a significant model to identify PCOS patients with higher risk of future cardiometabolic diseases. PMID:29416587

Systematic Review of Correlates and Determinants of Physical Activity in Persons With Multiple Sclerosis.

PubMed

Streber, René; Peters, Stefan; Pfeifer, Klaus

2016-04-01

To review the current evidence regarding correlates and determinants of physical activity (PA) in persons with multiple sclerosis (pwMS). PubMed and Scopus (1980 to January 2015) and reference lists of eligible studies. Eligible studies include adults with multiple sclerosis; have a cross-sectional or prospective observational design; or examine the effect of a theory-based intervention trial on PA, including a mediation analysis. Eligible studies also apply a quantitative assessment of PA and correlates or proposed mediators and are published in English or German language. Two reviewers independently evaluated the risk of bias, extracted data, and categorized variables according to the International Classification of Functioning, Disability and Health. Consistency and the direction of associations were evaluated with a semiquantitative approach. Fifty-six publications with data from observational studies and 2 interventional studies provided evidence for 86 different variables. Consistent correlates of PA were the disability level, walking limitations in particular, PA-related self-efficacy, self-regulation constructs, employment status, and educational level. One interventional study provided evidence for a causal relation between self-regulation and PA. However, 59 of the 86 investigated variables in observational studies are based on 1 or 2 study findings, and most results stem from cross-sectional designs. Beside the importance of the general disability level and walking limitations, the results highlight the importance of personal factors (eg, PA-related self-efficacy, self-regulatory constructs, sociodemographic factors). Limitations and implications of the current review are discussed. Research that is more rigorous is needed to better understand what affects PA in pwMS. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Prevalence of consistent condom use with various types of sex partners and associated factors among money boys in Changsha, China.

PubMed

Wang, Lian-Hong; Yan, Jin; Yang, Guo-Li; Long, Shuo; Yu, Yong; Wu, Xi-Lin

2015-04-01

Money boys with inconsistent condom use (less than 100% of the time) are at high risk of infection by human immunodeficiency virus (HIV) or sexually transmitted infection (STI), but relatively little research has examined their risk behaviors. We investigated the prevalence of consistent condom use (100% of the time) and associated factors among money boys. A cross-sectional study using a structured questionnaire was conducted among money boys in Changsha, China, between July 2012 and January 2013. Independent variables included socio-demographic data, substance abuse history, work characteristics, and self-reported HIV and STI history. Dependent variables included the consistent condom use with different types of sex partners. Among the participants, 82.4% used condoms consistently with male clients, 80.2% with male sex partners, and 77.1% with female sex partners in the past 3 months. A multiple stepwise logistic regression model identified four statistically significant factors associated with lower likelihoods of consistent condom use with male clients: age group, substance abuse, lack of an "employment" arrangement, and having no HIV test within the prior 6 months. In a similar model, only one factor associated significantly with lower likelihoods of consistent condom use with male sex partners was identified in multiple stepwise logistic regression analyses: having no HIV test within the prior six months. As for female sex partners, two significant variables were statistically significant in the multiple stepwise logistic regression analysis: having no HIV test within the prior 6 months and having STI history. Interventions which are linked with more realistic and acceptable HIV prevention methods are greatly warranted and should increase risk awareness and the behavior of consistent condom use in both commercial and personal relationship. © 2015 International Society for Sexual Medicine.

Consistent patterns of variation in macrobenthic assemblages and environmental variables over multiple spatial scales using taxonomic and functional approaches.

PubMed

Veiga, Puri; Torres, Ana Catarina; Aneiros, Fernando; Sousa-Pinto, Isabel; Troncoso, Jesús S; Rubal, Marcos

2016-09-01

Spatial variability of environmental factors and macrobenthos, using species and functional groups, was examined over the same scales (100s of cm to >100 km) in intertidal sediments of two transitional water systems. The objectives were to test if functional groups were a good species surrogate and explore the relationship between environmental variables and macrobenthos. Environmental variables, diversity and the multivariate assemblage structure showed the highest variability at the scale of 10s of km. However, abundance was more variable at 10s of m. Consistent patterns were achieved using species and functional groups therefore, these may be a good species surrogate. Total carbon, salinity and silt/clay were the strongest correlated with macrobenthic assemblages. Results are valuable for design and interpretation of future monitoring programs including detection of anthropogenic disturbances in transitional systems and propose improvements in environmental variable sampling to refine the assessment of their relationship with biological data across spatial scales. Copyright © 2016 Elsevier Ltd. All rights reserved.

Action-specific effects in aviation: what determines judged runway size?

PubMed

Gray, Rob; Navia, José Antonio; Allsop, Jonathan

2014-01-01

Several recent studies have shown that the performance of a skill that involves acting on a goal object can influence one's judgment of the size of that object. The present study investigated this effect in an aviation context. Novice pilots were asked to perform a series of visual approach and landing manoeuvres in a flight simulator. After each landing, participants next performed a task in which runway size was judged for different simulated altitudes. Gaze behaviour and control stick kinematics were also analyzed. There were significant relationships between judged runway size and multiple action-related variables including touchdown velocity, time fixating the runway, and the magnitude and frequency of control inputs. These findings suggest that relationship between the perception of a target object and action is not solely determined by performance success or failure but rather involves a relationship between multiple variables that reflect the actor's ability.

Meteorological adjustment of yearly mean values for air pollutant concentration comparison

NASA Technical Reports Server (NTRS)

Sidik, S. M.; Neustadter, H. E.

1976-01-01

Using multiple linear regression analysis, models which estimate mean concentrations of Total Suspended Particulate (TSP), sulfur dioxide, and nitrogen dioxide as a function of several meteorologic variables, two rough economic indicators, and a simple trend in time are studied. Meteorologic data were obtained and do not include inversion heights. The goodness of fit of the estimated models is partially reflected by the squared coefficient of multiple correlation which indicates that, at the various sampling stations, the models accounted for about 23 to 47 percent of the total variance of the observed TSP concentrations. If the resulting model equations are used in place of simple overall means of the observed concentrations, there is about a 20 percent improvement in either: (1) predicting mean concentrations for specified meteorological conditions; or (2) adjusting successive yearly averages to allow for comparisons devoid of meteorological effects. An application to source identification is presented using regression coefficients of wind velocity predictor variables.

Factors predictive of immediate breast reconstruction following mastectomy for invasive breast cancer in Australia.

PubMed

Roder, D; Zorbas, H; Kollias, J; Pyke, C; Walters, D; Campbell, I; Taylor, C; Webster, F

2013-12-01

To investigate person, cancer and treatment determinants of immediate breast reconstruction (IBR) in Australia. Bi-variable and multi-variable analyses of the Quality Audit database. Of 12,707 invasive cancers treated by mastectomy circa 1998-2010, 8% had IBR. This proportion increased over time and reduced from 29% in women below 30 years to approximately 1% in those aged 70 years or more. Multiple regression indicated that other IBR predictors included: high socio-economic status; private health insurance; being asymptomatic; a metropolitan rather than inner regional treatment centre; higher surgeon case load; small tumour size; negative nodal status, positive progesterone receptor status; more cancer foci; multiple affected breast quadrants; synchronous bilateral cancer; not having neo-adjuvant chemotherapy, adjuvant radiotherapy or adjuvant hormone therapy; and receiving ovarian ablation. Variations in access to specialty services and other possible causes of variations in IBR rates need further investigation. Copyright © 2013 Elsevier Ltd. All rights reserved.

Reduction and Analysis of GALFACTS Data in Search of Compact Variable Sources

NASA Astrophysics Data System (ADS)

Wenger, Trey; Barenfeld, S.; Ghosh, T.; Salter, C.

2012-01-01

The Galactic ALFA Continuum Transit Survey (GALFACTS) is an all-Arecibo sky, full-Stokes survey from 1225 to 1525 MHz using the multibeam Arecibo L-band Feed Array (ALFA). Using data from survey field N1, the first field covered by GALFACTS, we are searching for compact sources that vary in intensity and/or polarization. The multistep procedure for reducing the data includes radio frequency interference (RFI) removal, source detection, Gaussian fitting in multiple dimensions, polarization leakage calibration, and gain calibration. We have developed code to analyze and calculate the calibration parameters from the N1 calibration sources, and apply these to the data of the main run. For detected compact sources, our goal is to compare results from multiple passes over a source to search for rapid variability, as well as to compare our flux densities with those from the NRAO VLA Sky Survey (NVSS) to search for longer time-scale variations.

Does Variability Across Events Affect Verb Learning in English, Mandarin and Korean?

PubMed Central

Childers, Jane B.; Paik, Jae H.; Flores, Melissa; Lai, Gabrielle; Dolan, Megan

2016-01-01

Extending new verbs is important to becoming a productive speaker of a language. Prior results show children have difficulty extending verbs when they have seen events with varied agents. This paper further examines the impact of variability on verb learning, and asks whether this interacts with event complexity or differs by language. Children (aged 2 ½- to 3-years) in the U.S., China, Korea and Singapore learned verbs linked to simple and complex events. Sets of events included one or three agents, and children were asked to extend the verb at test. Children learning verbs linked to simple movements performed similarly across conditions. However, children learning verbs linked to events with multiple objects were less successful if those events were enacted by multiple agents. A follow-up study rules out an influence of event order. Overall, similar patterns of results emerged across languages, suggesting common cognitive processes support children’s verb learning. PMID:27457679

Characterizing Individual Differences in Functional Connectivity Using Dual-Regression and Seed-Based Approaches

PubMed Central

Smith, David V.; Utevsky, Amanda V.; Bland, Amy R.; Clement, Nathan; Clithero, John A.; Harsch, Anne E. W.; Carter, R. McKell; Huettel, Scott A.

2014-01-01

A central challenge for neuroscience lies in relating inter-individual variability to the functional properties of specific brain regions. Yet, considerable variability exists in the connectivity patterns between different brain areas, potentially producing reliable group differences. Using sex differences as a motivating example, we examined two separate resting-state datasets comprising a total of 188 human participants. Both datasets were decomposed into resting-state networks (RSNs) using a probabilistic spatial independent components analysis (ICA). We estimated voxelwise functional connectivity with these networks using a dual-regression analysis, which characterizes the participant-level spatiotemporal dynamics of each network while controlling for (via multiple regression) the influence of other networks and sources of variability. We found that males and females exhibit distinct patterns of connectivity with multiple RSNs, including both visual and auditory networks and the right frontal-parietal network. These results replicated across both datasets and were not explained by differences in head motion, data quality, brain volume, cortisol levels, or testosterone levels. Importantly, we also demonstrate that dual-regression functional connectivity is better at detecting inter-individual variability than traditional seed-based functional connectivity approaches. Our findings characterize robust—yet frequently ignored—neural differences between males and females, pointing to the necessity of controlling for sex in neuroscience studies of individual differences. Moreover, our results highlight the importance of employing network-based models to study variability in functional connectivity. PMID:24662574

Characterizing Uncertainty and Variability in PBPK Models ...

EPA Pesticide Factsheets

Mode-of-action based risk and safety assessments can rely upon tissue dosimetry estimates in animals and humans obtained from physiologically-based pharmacokinetic (PBPK) modeling. However, risk assessment also increasingly requires characterization of uncertainty and variability; such characterization for PBPK model predictions represents a continuing challenge to both modelers and users. Current practices show significant progress in specifying deterministic biological models and the non-deterministic (often statistical) models, estimating their parameters using diverse data sets from multiple sources, and using them to make predictions and characterize uncertainty and variability. The International Workshop on Uncertainty and Variability in PBPK Models, held Oct 31-Nov 2, 2006, sought to identify the state-of-the-science in this area and recommend priorities for research and changes in practice and implementation. For the short term, these include: (1) multidisciplinary teams to integrate deterministic and non-deterministic/statistical models; (2) broader use of sensitivity analyses, including for structural and global (rather than local) parameter changes; and (3) enhanced transparency and reproducibility through more complete documentation of the model structure(s) and parameter values, the results of sensitivity and other analyses, and supporting, discrepant, or excluded data. Longer-term needs include: (1) theoretic and practical methodological impro

Identification of the need for home visiting nurse: development of a new assessment tool.

PubMed

Taguchi, Atsuko; Nagata, Satoko; Naruse, Takashi; Kuwahara, Yuki; Yamaguchi, Takuhiro; Murashima, Sachiyo

2014-01-01

To develop a Home Visiting Nursing Service Need Assessment Form (HVNS-NAF) to standardize the decision about the need for home visiting nursing service. The sample consisted of older adults who had received coordinated services by care managers. We defined the need for home visiting nursing service by elderly individuals as the decision of the need by a care manager so that the elderly can continue to live independently. Explanatory variables included demographic factors, medical procedure, severity of illness, and caregiver variables. Multiple logistic regression was carried out after univariate analyses to decide the variables to include and the weight of each variable in the HVNS-NAF. We then calculated the sensitivity and specificity of each cutoff value, and defined the score with the highest sensitivity and specificity as the cutoff value. Nineteen items were included in the final HVNS-NAF. When the cutoff value was 2 points, the sensitivity was 77.0%, specificity 68.5%, and positive predictive value 56.8%. HVNS-NAF is the first validated standard based on characteristics of elderly clients who required home visiting nursing service. Using the HVNS-NAF may result in reducing the unmet need for home visiting nursing service and preventing hospitalization.

Nonparametric relevance-shifted multiple testing procedures for the analysis of high-dimensional multivariate data with small sample sizes.

PubMed

Frömke, Cornelia; Hothorn, Ludwig A; Kropf, Siegfried

2008-01-27

In many research areas it is necessary to find differences between treatment groups with several variables. For example, studies of microarray data seek to find a significant difference in location parameters from zero or one for ratios thereof for each variable. However, in some studies a significant deviation of the difference in locations from zero (or 1 in terms of the ratio) is biologically meaningless. A relevant difference or ratio is sought in such cases. This article addresses the use of relevance-shifted tests on ratios for a multivariate parallel two-sample group design. Two empirical procedures are proposed which embed the relevance-shifted test on ratios. As both procedures test a hypothesis for each variable, the resulting multiple testing problem has to be considered. Hence, the procedures include a multiplicity correction. Both procedures are extensions of available procedures for point null hypotheses achieving exact control of the familywise error rate. Whereas the shift of the null hypothesis alone would give straight-forward solutions, the problems that are the reason for the empirical considerations discussed here arise by the fact that the shift is considered in both directions and the whole parameter space in between these two limits has to be accepted as null hypothesis. The first algorithm to be discussed uses a permutation algorithm, and is appropriate for designs with a moderately large number of observations. However, many experiments have limited sample sizes. Then the second procedure might be more appropriate, where multiplicity is corrected according to a concept of data-driven order of hypotheses.

Prediction of performance on the RCMP physical ability requirement evaluation.

PubMed

Stanish, H I; Wood, T M; Campagna, P

1999-08-01

The Royal Canadian Mounted Police use the Physical Ability Requirement Evaluation (PARE) for screening applicants. The purposes of this investigation were to identify those field tests of physical fitness that were associated with PARE performance and determine which most accurately classified successful and unsuccessful PARE performers. The participants were 27 female and 21 male volunteers. Testing included measures of aerobic power, anaerobic power, agility, muscular strength, muscular endurance, and body composition. Multiple regression analysis revealed a three-variable model for males (70-lb bench press, standing long jump, and agility) explaining 79% of the variability in PARE time, whereas a one-variable model (agility) explained 43% of the variability for females. Analysis of the classification accuracy of the males' data was prohibited because 91% of the males passed the PARE. Classification accuracy of the females' data, using logistic regression, produced a two-variable model (agility, 1.5-mile endurance run) with 93% overall classification accuracy.

Do climate variables and human density affect Achatina fulica (Bowditch) (Gastropoda: Pulmonata) shell length, total weight and condition factor?

PubMed

Albuquerque, F S; Peso-Aguiar, M C; Assunção-Albuquerque, M J T; Gálvez, L

2009-08-01

The length-weight relationship and condition factor have been broadly investigated in snails to obtain the index of physical condition of populations and evaluate habitat quality. Herein, our goal was to describe the best predictors that explain Achatina fulica biometrical parameters and well being in a recently introduced population. From November 2001 to November 2002, monthly snail samples were collected in Lauro de Freitas City, Bahia, Brazil. Shell length and total weight were measured in the laboratory and the potential curve and condition factor were calculated. Five environmental variables were considered: temperature range, mean temperature, humidity, precipitation and human density. Multiple regressions were used to generate models including multiple predictors, via model selection approach, and then ranked with AIC criteria. Partial regressions were used to obtain the separated coefficients of determination of climate and human density models. A total of 1.460 individuals were collected, presenting a shell length range between 4.8 to 102.5 mm (mean: 42.18 mm). The relationship between total length and total weight revealed that Achatina fulica presented a negative allometric growth. Simple regression indicated that humidity has a significant influence on A. fulica total length and weight. Temperature range was the main variable that influenced the condition factor. Multiple regressions showed that climatic and human variables explain a small proportion of the variance in shell length and total weight, but may explain up to 55.7% of the condition factor variance. Consequently, we believe that the well being and biometric parameters of A. fulica can be influenced by climatic and human density factors.

Tests of Multiplicative Models in Psychology: A Case Study Using the Unified Theory of Implicit Attitudes, Stereotypes, Self-Esteem, and Self-Concept

ERIC Educational Resources Information Center

Blanton, Hart; Jaccard, James

2006-01-01

Theories that posit multiplicative relationships between variables are common in psychology. A. G. Greenwald et al. recently presented a theory that explicated relationships between group identification, group attitudes, and self-esteem. Their theory posits a multiplicative relationship between concepts when predicting a criterion variable.…

Efficient Approaches for Propagating Hydrologic Forcing Uncertainty: High-Resolution Applications Over the Western United States

NASA Astrophysics Data System (ADS)

Hobbs, J.; Turmon, M.; David, C. H.; Reager, J. T., II; Famiglietti, J. S.

2017-12-01

NASA's Western States Water Mission (WSWM) combines remote sensing of the terrestrial water cycle with hydrological models to provide high-resolution state estimates for multiple variables. The effort includes both land surface and river routing models that are subject to several sources of uncertainty, including errors in the model forcing and model structural uncertainty. Computational and storage constraints prohibit extensive ensemble simulations, so this work outlines efficient but flexible approaches for estimating and reporting uncertainty. Calibrated by remote sensing and in situ data where available, we illustrate the application of these techniques in producing state estimates with associated uncertainties at kilometer-scale resolution for key variables such as soil moisture, groundwater, and streamflow.

Multiple and variable speed electrical generator systems for large wind turbines

NASA Technical Reports Server (NTRS)

Andersen, T. S.; Hughes, P. S.; Kirschbaum, H. S.; Mutone, G. A.

1982-01-01

A cost effective method to achieve increased wind turbine generator energy conversion and other operational benefits through variable speed operation is presented. Earlier studies of multiple and variable speed generators in wind turbines were extended for evaluation in the context of a specific large sized conceptual design. System design and simulation have defined the costs and performance benefits which can be expected from both two speed and variable speed configurations.

Multiple Access Points within the Online Classroom: Where Students Look for Information

ERIC Educational Resources Information Center

Steele, John; Nordin, Eric J.; Larson, Elizabeth; McIntosh, Daniel

2017-01-01

The purpose of this study is to examine the impact of information placement within the confines of the online classroom architecture. Also reviewed was the impact of other variables such as course design, teaching presence and student patterns in looking for information. The sample population included students from a major online university in…

Multi scale habitat relationships of Martes americana in northern Idaho, U.S.A.

Treesearch

Tzeidle N. Wasserman; Samuel A. Cushman; David O. Wallin; Jim Hayden

2012-01-01

We used bivariate scaling and logistic regression to investigate multiple-scale habitat selection by American marten (Martes americana). Bivariate scaling reveals dramatic differences in the apparent nature and strength of relationships between marten occupancy and a number of habitat variables across a range of spatial scales. These differences include reversals in...

Toward an Index of Well-Being for the Fifty U.S. States

ERIC Educational Resources Information Center

Pesta, Bryan J.; McDaniel, Michael A.; Bertsch, Sharon

2010-01-01

Well-being is a construct spanning multiple disciplines including psychology, economics, health, and public policy. In many ways, well-being is a nexus of inter-correlated variables, much like the "g" nexus. Here, we created an index of well-being for the geographical and political subdivisions of the United States (i.e., states). The…

Time dependent emission line profiles in the radially streaming particle model of Seyfert galaxy nuclei and quasi-stellar objects

NASA Technical Reports Server (NTRS)

Hubbard, R.

1974-01-01

The radially-streaming particle model for broad quasar and Seyfert galaxy emission features is modified to include sources of time dependence. The results are suggestive of reported observations of multiple components, variability, and transient features in the wings of Seyfert and quasi-stellar emission lines.

Quantitative assessment of cervical vertebral maturation using cone beam computed tomography in Korean girls.

PubMed

Byun, Bo-Ram; Kim, Yong-Il; Yamaguchi, Tetsutaro; Maki, Koutaro; Son, Woo-Sung

2015-01-01

This study was aimed to examine the correlation between skeletal maturation status and parameters from the odontoid process/body of the second vertebra and the bodies of third and fourth cervical vertebrae and simultaneously build multiple regression models to be able to estimate skeletal maturation status in Korean girls. Hand-wrist radiographs and cone beam computed tomography (CBCT) images were obtained from 74 Korean girls (6-18 years of age). CBCT-generated cervical vertebral maturation (CVM) was used to demarcate the odontoid process and the body of the second cervical vertebra, based on the dentocentral synchondrosis. Correlation coefficient analysis and multiple linear regression analysis were used for each parameter of the cervical vertebrae (P < 0.05). Forty-seven of 64 parameters from CBCT-generated CVM (independent variables) exhibited statistically significant correlations (P < 0.05). The multiple regression model with the greatest R (2) had six parameters (PH2/W2, UW2/W2, (OH+AH2)/LW2, UW3/LW3, D3, and H4/W4) as independent variables with a variance inflation factor (VIF) of <2. CBCT-generated CVM was able to include parameters from the second cervical vertebral body and odontoid process, respectively, for the multiple regression models. This suggests that quantitative analysis might be used to estimate skeletal maturation status.

The role of family planning communications--an agent of reinforcement or change.

PubMed

Chen, E C

1981-12-01

Results are presented of a multiple classification analysis of responses to a 1972 KAP survey in Taiwan of 2013 married women aged 18-34 designed to determine whether family planning communication is primarily a reinforcement agent or a change agent. 2 types of independent variables, social demographic variables including age, number of children, residence, education, employment status, and duration of marriage; and social climate variables including ever receiving family planning information from mass media and ever discussing family planning with others, were used. KAP levels, the dependent variables, were measured by 2 variables each: awareness of effective methods and awareness of government supply of contraceptives for knowledge, wish for additional children and approve of 2-child family for attitude, and never use contraception and neither want children nor use contraception for practice. Social demographic and attitudinal variables were found to be the critical ones, while social climate and knowledge variables had only negligible effects on various stages of family planning adoption, indicating that family planning communications functioned primarily as a reinforcement agent. The effects of social demographic variables were prominent in all stages of contraceptive adoption. Examination of effects of individual variables on various stages of family planning adoption still supported the argument that family planning communications played a reinforcement role. Family planning communications functioned well in diffusing family planning knowledge and accessibility, but social demographic variables and desire for additional children were the most decisive influences on use of contraception.

Quality of search strategies reported in systematic reviews published in stereotactic radiosurgery.

PubMed

Faggion, Clovis M; Wu, Yun-Chun; Tu, Yu-Kang; Wasiak, Jason

2016-06-01

Systematic reviews require comprehensive literature search strategies to avoid publication bias. This study aimed to assess and evaluate the reporting quality of search strategies within systematic reviews published in the field of stereotactic radiosurgery (SRS). Three electronic databases (Ovid MEDLINE(®), Ovid EMBASE(®) and the Cochrane Library) were searched to identify systematic reviews addressing SRS interventions, with the last search performed in October 2014. Manual searches of the reference lists of included systematic reviews were conducted. The search strategies of the included systematic reviews were assessed using a standardized nine-question form based on the Cochrane Collaboration guidelines and Assessment of Multiple Systematic Reviews checklist. Multiple linear regression analyses were performed to identify the important predictors of search quality. A total of 85 systematic reviews were included. The median quality score of search strategies was 2 (interquartile range = 2). Whilst 89% of systematic reviews reported the use of search terms, only 14% of systematic reviews reported searching the grey literature. Multiple linear regression analyses identified publication year (continuous variable), meta-analysis performance and journal impact factor (continuous variable) as predictors of higher mean quality scores. This study identified the urgent need to improve the quality of search strategies within systematic reviews published in the field of SRS. This study is the first to address how authors performed searches to select clinical studies for inclusion in their systematic reviews. Comprehensive and well-implemented search strategies are pivotal to reduce the chance of publication bias and consequently generate more reliable systematic review findings.

The use of intelligent database systems in acute pancreatitis--a systematic review.

PubMed

van den Heever, Marc; Mittal, Anubhav; Haydock, Matthew; Windsor, John

2014-01-01

Acute pancreatitis (AP) is a complex disease with multiple aetiological factors, wide ranging severity, and multiple challenges to effective triage and management. Databases, data mining and machine learning algorithms (MLAs), including artificial neural networks (ANNs), may assist by storing and interpreting data from multiple sources, potentially improving clinical decision-making. 1) Identify database technologies used to store AP data, 2) collate and categorise variables stored in AP databases, 3) identify the MLA technologies, including ANNs, used to analyse AP data, and 4) identify clinical and non-clinical benefits and obstacles in establishing a national or international AP database. Comprehensive systematic search of online reference databases. The predetermined inclusion criteria were all papers discussing 1) databases, 2) data mining or 3) MLAs, pertaining to AP, independently assessed by two reviewers with conflicts resolved by a third author. Forty-three papers were included. Three data mining technologies and five ANN methodologies were reported in the literature. There were 187 collected variables identified. ANNs increase accuracy of severity prediction, one study showed ANNs had a sensitivity of 0.89 and specificity of 0.96 six hours after admission--compare APACHE II (cutoff score ≥8) with 0.80 and 0.85 respectively. Problems with databases were incomplete data, lack of clinical data, diagnostic reliability and missing clinical data. This is the first systematic review examining the use of databases, MLAs and ANNs in the management of AP. The clinical benefits these technologies have over current systems and other advantages to adopting them are identified. Copyright © 2013 IAP and EPC. Published by Elsevier B.V. All rights reserved.

Multiple imputation in the presence of non-normal data.

PubMed

Lee, Katherine J; Carlin, John B

2017-02-20

Multiple imputation (MI) is becoming increasingly popular for handling missing data. Standard approaches for MI assume normality for continuous variables (conditionally on the other variables in the imputation model). However, it is unclear how to impute non-normally distributed continuous variables. Using simulation and a case study, we compared various transformations applied prior to imputation, including a novel non-parametric transformation, to imputation on the raw scale and using predictive mean matching (PMM) when imputing non-normal data. We generated data from a range of non-normal distributions, and set 50% to missing completely at random or missing at random. We then imputed missing values on the raw scale, following a zero-skewness log, Box-Cox or non-parametric transformation and using PMM with both type 1 and 2 matching. We compared inferences regarding the marginal mean of the incomplete variable and the association with a fully observed outcome. We also compared results from these approaches in the analysis of depression and anxiety symptoms in parents of very preterm compared with term-born infants. The results provide novel empirical evidence that the decision regarding how to impute a non-normal variable should be based on the nature of the relationship between the variables of interest. If the relationship is linear in the untransformed scale, transformation can introduce bias irrespective of the transformation used. However, if the relationship is non-linear, it may be important to transform the variable to accurately capture this relationship. A useful alternative is to impute the variable using PMM with type 1 matching. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Treatment of multiple unresectable basal cell carcinomas from Gorlin-Goltz syndrome: a case report.

PubMed

Ojevwe, Fidelis O; Ojevwe, Cindy D; Zacny, James P; Dudek, Arkadiusz Z; Lin, Amy; Kohlitz, Patrick

2015-03-01

Nevoid basal cell carcinoma syndrome (NBCCS), which is also known by other names, including Gorlin-Goltz syndrome and multiple basal-cell carcinoma (BCC) syndrome, is a rare multi-systemic disease inherited in a dominant autosomal manner with complete penetrance and variable expressivity. The main clinical manifestations include multiple BCCs, odontogenic keratocysts of the jaw, hyperkeratosis of the palms and soles, skeletal abnormalities, intracranial calcifications and facial deformities. A 31-year-old male diagnosed with Gorlin-Goltz syndrome with multiple unresectable facial BCCs was treated with the Hedgehog inhibitor vismodegib. After one month of therapy on vismodegib, there were significant reductions in the size of multiple BCCs on the patient's face. The patient remains on this therapy. Hedgehog pathway inhibition is an effective strategy to treat unresectable BCCs from Gorlin-Goltz syndrome. Although vismodegib shows some promising clinical results in the early phase of its use, there are concerns of possible resistance developing within months. Duration of therapy, role of maintenance treatment and drug modification to reduce resistance need to be explored in future case studies. Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Analysis of Genome-Wide Association Studies with Multiple Outcomes Using Penalization

PubMed Central

Liu, Jin; Huang, Jian; Ma, Shuangge

2012-01-01

Genome-wide association studies have been extensively conducted, searching for markers for biologically meaningful outcomes and phenotypes. Penalization methods have been adopted in the analysis of the joint effects of a large number of SNPs (single nucleotide polymorphisms) and marker identification. This study is partly motivated by the analysis of heterogeneous stock mice dataset, in which multiple correlated phenotypes and a large number of SNPs are available. Existing penalization methods designed to analyze a single response variable cannot accommodate the correlation among multiple response variables. With multiple response variables sharing the same set of markers, joint modeling is first employed to accommodate the correlation. The group Lasso approach is adopted to select markers associated with all the outcome variables. An efficient computational algorithm is developed. Simulation study and analysis of the heterogeneous stock mice dataset show that the proposed method can outperform existing penalization methods. PMID:23272092

The association between histological, macroscopic and magnetic resonance imaging assessed synovitis in end-stage knee osteoarthritis: a cross-sectional study.

PubMed

Riis, R G C; Gudbergsen, H; Simonsen, O; Henriksen, M; Al-Mashkur, N; Eld, M; Petersen, K K; Kubassova, O; Bay Jensen, A C; Damm, J; Bliddal, H; Arendt-Nielsen, L; Boesen, M

2017-02-01

To investigate the association between magnetic resonance imaging (MRI), macroscopic and histological assessments of synovitis in end-stage knee osteoarthritis (KOA). Synovitis of end-stage osteoarthritic knees was assessed using non-contrast-enhanced (CE), contrast-enhanced magnetic resonance imaging (CE-MRI) and dynamic contrast-enhanced (DCE)-MRI prior to (TKR) and correlated with microscopic and macroscopic assessments of synovitis obtained intraoperatively. Multiple bivariate correlations were used with a pre-specified threshold of 0.70 for significance. Also, multiple regression analyses with different subsets of MRI-variables as explanatory variables and the histology score as outcome variable were performed with the intention to find MRI-variables that best explain the variance in histological synovitis (i.e., highest R 2 ). A stepped approach was taken starting with basic characteristics and non-CE MRI-variables (model 1), after which CE-MRI-variables were added (model 2) with the final model also including DCE-MRI-variables (model 3). 39 patients (56.4% women, mean age 68 years, Kellgren-Lawrence (KL) grade 4) had complete MRI and histological data. Only the DCE-MRI variable MExNvoxel (surrogate of the volume and degree of synovitis) and the macroscopic score showed correlations above the pre-specified threshold for acceptance with histological inflammation. The maximum R 2 -value obtained in Model 1 was R 2  = 0.39. In Model 2, where the CE-MRI-variables were added, the highest R 2  = 0.52. In Model 3, a four-variable model consisting of the gender, one CE-MRI and two DCE-MRI-variables yielded a R 2  = 0.71. DCE-MRI is correlated with histological synovitis in end-stage KOA and the combination of CE and DCE-MRI may be a useful, non-invasive tool in characterising synovitis in KOA. Copyright © 2016 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Motivational and Volitional Variables Associated with Stages of Change for Exercise in Multiple Sclerosis: A Multiple Discriminant Analysis

ERIC Educational Resources Information Center

Chiu, Chung-Yi; Fitzgerald, Sandra D.; Strand, David M.; Muller, Veronica; Brooks, Jessica; Chan, Fong

2012-01-01

The main objective of this study was to determine whether motivational and volitional variables identified in the health action process approach (HAPA) model can be used to successfully differentiate people with multiple sclerosis (MS) in different stages of change for exercise and physical activity. Ex-post-facto design using multiple…

Modeling variably saturated multispecies reactive groundwater solute transport with MODFLOW-UZF and RT3D

USGS Publications Warehouse

Bailey, Ryan T.; Morway, Eric D.; Niswonger, Richard G.; Gates, Timothy K.

2013-01-01

A numerical model was developed that is capable of simulating multispecies reactive solute transport in variably saturated porous media. This model consists of a modified version of the reactive transport model RT3D (Reactive Transport in 3 Dimensions) that is linked to the Unsaturated-Zone Flow (UZF1) package and MODFLOW. Referred to as UZF-RT3D, the model is tested against published analytical benchmarks as well as other published contaminant transport models, including HYDRUS-1D, VS2DT, and SUTRA, and the coupled flow and transport modeling system of CATHY and TRAN3D. Comparisons in one-dimensional, two-dimensional, and three-dimensional variably saturated systems are explored. While several test cases are included to verify the correct implementation of variably saturated transport in UZF-RT3D, other cases are included to demonstrate the usefulness of the code in terms of model run-time and handling the reaction kinetics of multiple interacting species in variably saturated subsurface systems. As UZF1 relies on a kinematic-wave approximation for unsaturated flow that neglects the diffusive terms in Richards equation, UZF-RT3D can be used for large-scale aquifer systems for which the UZF1 formulation is reasonable, that is, capillary-pressure gradients can be neglected and soil parameters can be treated as homogeneous. Decreased model run-time and the ability to include site-specific chemical species and chemical reactions make UZF-RT3D an attractive model for efficient simulation of multispecies reactive transport in variably saturated large-scale subsurface systems.

Method and apparatus for multiple-projection, dual-energy x-ray absorptiometry scanning

NASA Technical Reports Server (NTRS)

Feldmesser, Howard S. (Inventor); Magee, Thomas C. (Inventor); Charles, Jr., Harry K. (Inventor); Beck, Thomas J. (Inventor)

2007-01-01

Methods and apparatuses for advanced, multiple-projection, dual-energy X-ray absorptiometry scanning systems include combinations of a conical collimator; a high-resolution two-dimensional detector; a portable, power-capped, variable-exposure-time power supply; an exposure-time control element; calibration monitoring; a three-dimensional anti-scatter-grid; and a gantry-gantry base assembly that permits up to seven projection angles for overlapping beams. Such systems are capable of high precision bone structure measurements that can support three dimensional bone modeling and derivations of bone strength, risk of injury, and efficacy of countermeasures among other properties.

Item Response Theory with Covariates (IRT-C): Assessing Item Recovery and Differential Item Functioning for the Three-Parameter Logistic Model

ERIC Educational Resources Information Center

Tay, Louis; Huang, Qiming; Vermunt, Jeroen K.

2016-01-01

In large-scale testing, the use of multigroup approaches is limited for assessing differential item functioning (DIF) across multiple variables as DIF is examined for each variable separately. In contrast, the item response theory with covariate (IRT-C) procedure can be used to examine DIF across multiple variables (covariates) simultaneously. To…

[Study on correction of data bias caused by different missing mechanisms in survey of medical expenditure among students enrolling in Urban Resident Basic Medical Insurance].

PubMed

Zhang, Haixia; Zhao, Junkang; Gu, Caijiao; Cui, Yan; Rong, Huiying; Meng, Fanlong; Wang, Tong

2015-05-01

The study of the medical expenditure and its influencing factors among the students enrolling in Urban Resident Basic Medical Insurance (URBMI) in Taiyuan indicated that non response bias and selection bias coexist in dependent variable of the survey data. Unlike previous studies only focused on one missing mechanism, a two-stage method to deal with two missing mechanisms simultaneously was suggested in this study, combining multiple imputation with sample selection model. A total of 1 190 questionnaires were returned by the students (or their parents) selected in child care settings, schools and universities in Taiyuan by stratified cluster random sampling in 2012. In the returned questionnaires, 2.52% existed not missing at random (NMAR) of dependent variable and 7.14% existed missing at random (MAR) of dependent variable. First, multiple imputation was conducted for MAR by using completed data, then sample selection model was used to correct NMAR in multiple imputation, and a multi influencing factor analysis model was established. Based on 1 000 times resampling, the best scheme of filling the random missing values is the predictive mean matching (PMM) method under the missing proportion. With this optimal scheme, a two stage survey was conducted. Finally, it was found that the influencing factors on annual medical expenditure among the students enrolling in URBMI in Taiyuan included population group, annual household gross income, affordability of medical insurance expenditure, chronic disease, seeking medical care in hospital, seeking medical care in community health center or private clinic, hospitalization, hospitalization canceled due to certain reason, self medication and acceptable proportion of self-paid medical expenditure. The two-stage method combining multiple imputation with sample selection model can deal with non response bias and selection bias effectively in dependent variable of the survey data.

Missing Data and Multiple Imputation: An Unbiased Approach

NASA Technical Reports Server (NTRS)

Foy, M.; VanBaalen, M.; Wear, M.; Mendez, C.; Mason, S.; Meyers, V.; Alexander, D.; Law, J.

2014-01-01

The default method of dealing with missing data in statistical analyses is to only use the complete observations (complete case analysis), which can lead to unexpected bias when data do not meet the assumption of missing completely at random (MCAR). For the assumption of MCAR to be met, missingness cannot be related to either the observed or unobserved variables. A less stringent assumption, missing at random (MAR), requires that missingness not be associated with the value of the missing variable itself, but can be associated with the other observed variables. When data are truly MAR as opposed to MCAR, the default complete case analysis method can lead to biased results. There are statistical options available to adjust for data that are MAR, including multiple imputation (MI) which is consistent and efficient at estimating effects. Multiple imputation uses informing variables to determine statistical distributions for each piece of missing data. Then multiple datasets are created by randomly drawing on the distributions for each piece of missing data. Since MI is efficient, only a limited number, usually less than 20, of imputed datasets are required to get stable estimates. Each imputed dataset is analyzed using standard statistical techniques, and then results are combined to get overall estimates of effect. A simulation study will be demonstrated to show the results of using the default complete case analysis, and MI in a linear regression of MCAR and MAR simulated data. Further, MI was successfully applied to the association study of CO2 levels and headaches when initial analysis showed there may be an underlying association between missing CO2 levels and reported headaches. Through MI, we were able to show that there is a strong association between average CO2 levels and the risk of headaches. Each unit increase in CO2 (mmHg) resulted in a doubling in the odds of reported headaches.

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

Modulation of brain activity by multiple lexical and word form variables in visual word recognition: A parametric fMRI study.

PubMed

Hauk, Olaf; Davis, Matthew H; Pulvermüller, Friedemann

2008-09-01

Psycholinguistic research has documented a range of variables that influence visual word recognition performance. Many of these variables are highly intercorrelated. Most previous studies have used factorial designs, which do not exploit the full range of values available for continuous variables, and are prone to skewed stimulus selection as well as to effects of the baseline (e.g. when contrasting words with pseudowords). In our study, we used a parametric approach to study the effects of several psycholinguistic variables on brain activation. We focussed on the variable word frequency, which has been used in numerous previous behavioural, electrophysiological and neuroimaging studies, in order to investigate the neuronal network underlying visual word processing. Furthermore, we investigated the variable orthographic typicality as well as a combined variable for word length and orthographic neighbourhood size (N), for which neuroimaging results are still either scarce or inconsistent. Data were analysed using multiple linear regression analysis of event-related fMRI data acquired from 21 subjects in a silent reading paradigm. The frequency variable correlated negatively with activation in left fusiform gyrus, bilateral inferior frontal gyri and bilateral insulae, indicating that word frequency can affect multiple aspects of word processing. N correlated positively with brain activity in left and right middle temporal gyri as well as right inferior frontal gyrus. Thus, our analysis revealed multiple distinct brain areas involved in visual word processing within one data set.

Individual Differences in Pain: Understanding the Mosaic that Makes Pain Personal

PubMed Central

Fillingim, Roger B.

2016-01-01

The experience of pain is characterized by tremendous inter-individual variability. Multiple biological and psychosocial variables contribute to these individual differences in pain, including demographic variables, genetic factors, and psychosocial processes. For example, sex, age and ethnic group differences in the prevalence of chronic pain conditions have been widely reported. Moreover, these demographic factors have been associated with responses to experimentally-induced pain. Similarly, both genetic and psychosocial factors contribute to clinical and experimental pain responses. Importantly, these different biopsychosocial influences interact with each other in complex ways to sculpt the experience of pain. Some genetic associations with pain have been found to vary across sex and ethnic group. Moreover, genetic factors also interact with psychosocial factors, including stress and pain catastrophizing, to influence pain. The individual and combined influences of these biological and psychosocial variables results in a unique mosaic of factors that contributes pain in each individual. Understanding these mosaics is critically important in order to provide optimal pain treatment, and future research to further elucidate the nature of these biopsychosocial interactions is needed in order to provide more informed and personalized pain care. PMID:27902569

Using intraindividual variability to detect malingering in cognitive performance.

PubMed

Strauss, E; Hultsch, D F; Hunter, M; Slick, D J; Patry, B; Levy-Bencheton, J

1999-11-01

The utility of measures for detecting malingering was evaluated using a simulation design in which half the participants were encouraged to do their best and half were asked to feign head injury. Particular attention was focused on the utility of repeated assessment (intraindividual variability) in discriminating the groups. Participants were tested on three occasions on measures commonly used to detect malingering including a specific symptom validity test (SVT). The results indicated that multiple measures of malingering obtained in single assessment (occasion one) discriminated the groups effectively. In addition, however, intraindividual variability in performance, particularly of indicators from the SVT, provided unique information beyond level of performance. The results suggest that response inconsistency across testing sessions may be a clinically useful measure for the detection of malingering.

A robust variable sampling time BLDC motor control design based upon μ-synthesis.

PubMed

Hung, Chung-Wen; Yen, Jia-Yush

2013-01-01

The variable sampling rate system is encountered in many applications. When the speed information is derived from the position marks along the trajectory, one would have a speed dependent sampling rate system. The conventional fixed or multisampling rate system theory may not work in these cases because the system dynamics include the uncertainties which resulted from the variable sampling rate. This paper derived a convenient expression for the speed dependent sampling rate system. The varying sampling rate effect is then translated into multiplicative uncertainties to the system. The design then uses the popular μ-synthesis process to achieve a robust performance controller design. The implementation on a BLDC motor demonstrates the effectiveness of the design approach.

A Robust Variable Sampling Time BLDC Motor Control Design Based upon μ-Synthesis

PubMed Central

Yen, Jia-Yush

2013-01-01

The variable sampling rate system is encountered in many applications. When the speed information is derived from the position marks along the trajectory, one would have a speed dependent sampling rate system. The conventional fixed or multisampling rate system theory may not work in these cases because the system dynamics include the uncertainties which resulted from the variable sampling rate. This paper derived a convenient expression for the speed dependent sampling rate system. The varying sampling rate effect is then translated into multiplicative uncertainties to the system. The design then uses the popular μ-synthesis process to achieve a robust performance controller design. The implementation on a BLDC motor demonstrates the effectiveness of the design approach. PMID:24327804

Increasing Self-Regulation and Classroom Participation of a Child Who Is Deafblind.

PubMed

Nelson, Catherine; Hyte, Holly A; Greenfield, Robin

2016-01-01

Self-regulation has been identified as essential to school success. However, for a variety of reasons, its development may be compromised in children and youth who are deafblind. A single-case multiple-baseline study of a child who was deafblind examined the effects of three groups of evidence-based interventions on variables thought to be associated with self-regulation. The dependent variables were (a) frequency and duration of behaviors thought to indicate dysregulation, (b) active participation in school activities, and (c) time from onset of behaviors indicating dysregulation until achievement of a calm, regulated state. The interventions, which included provision of meaningful, enjoyable, and interactive activities, anticipatory strategies, and calming strategies, significantly influenced the dependent variables and are described in detail.

The relationship between attendance at birth and maternal mortality rates: an exploration of United Nations' data sets including the ratios of physicians and nurses to population, GNP per capita and female literacy.

PubMed

Robinson, J J; Wharrad, H

2001-05-01

The relationship between attendance at birth and maternal mortality rates: an exploration of United Nations' data sets including the ratios of physicians and nurses to population, GNP per capita and female literacy. This is the third and final paper drawing on data taken from United Nations (UN) data sets. The first paper examined the global distribution of health professionals (as measured by ratios of physicians and nurses to population), and its relationship to gross national product per capita (GNP) (Wharrad & Robinson 1999). The second paper explored the relationships between the global distribution of physicians and nurses, GNP, female literacy and the health outcome indicators of infant and under five mortality rates (IMR and u5MR) (Robinson & Wharrad 2000). In the present paper, the global distribution of health professionals is explored in relation to maternal mortality rates (MMRs). The proportion of births attended by medical and nonmedical staff defined as "attendance at birth by trained personnel" (physicians, nurses, midwives or primary health care workers trained in midwifery skills), is included as an additional independent variable in the regression analyses, together with the ratio of physicians and nurses to population, female literacy and GNP. To extend our earlier analyses by considering the relationships between the global distribution of health professionals (ratios of physicians and nurses to population, and the proportion of births attended by trained health personnel), GNP, female literacy and MMR.

Evaluating the performance of different predictor strategies in regression-based downscaling with a focus on glacierized mountain environments

NASA Astrophysics Data System (ADS)

Hofer, Marlis; Nemec, Johanna

2016-04-01

This study presents first steps towards verifying the hypothesis that uncertainty in global and regional glacier mass simulations can be reduced considerably by reducing the uncertainty in the high-resolution atmospheric input data. To this aim, we systematically explore the potential of different predictor strategies for improving the performance of regression-based downscaling approaches. The investigated local-scale target variables are precipitation, air temperature, wind speed, relative humidity and global radiation, all at a daily time scale. Observations of these target variables are assessed from three sites in geo-environmentally and climatologically very distinct settings, all within highly complex topography and in the close proximity to mountain glaciers: (1) the Vernagtbach station in the Northern European Alps (VERNAGT), (2) the Artesonraju measuring site in the tropical South American Andes (ARTESON), and (3) the Brewster measuring site in the Southern Alps of New Zealand (BREWSTER). As the large-scale predictors, ERA interim reanalysis data are used. In the applied downscaling model training and evaluation procedures, particular emphasis is put on appropriately accounting for the pitfalls of limited and/or patchy observation records that are usually the only (if at all) available data from the glacierized mountain sites. Generalized linear models and beta regression are investigated as alternatives to ordinary least squares regression for the non-Gaussian target variables. By analyzing results for the three different sites, five predictands and for different times of the year, we look for systematic improvements in the downscaling models' skill specifically obtained by (i) using predictor data at the optimum scale rather than the minimum scale of the reanalysis data, (ii) identifying the optimum predictor allocation in the vertical, and (iii) considering multiple (variable, level and/or grid point) predictor options combined with state-of-art empirical feature selection tools. First results show that in particular for air temperature, those downscaling models based on direct predictor selection show comparative skill like those models based on multiple predictors. For all other target variables, however, multiple predictor approaches can considerably outperform those models based on single predictors. Including multiple variable types emerges as the most promising predictor option (in particular for wind speed at all sites), even if the same predictor set is used across the different cases.

The M Word: Multicollinearity in Multiple Regression.

ERIC Educational Resources Information Center

Morrow-Howell, Nancy

1994-01-01

Notes that existence of substantial correlation between two or more independent variables creates problems of multicollinearity in multiple regression. Discusses multicollinearity problem in social work research in which independent variables are usually intercorrelated. Clarifies problems created by multicollinearity, explains detection of…

Subject order-independent group ICA (SOI-GICA) for functional MRI data analysis.

PubMed

Zhang, Han; Zuo, Xi-Nian; Ma, Shuang-Ye; Zang, Yu-Feng; Milham, Michael P; Zhu, Chao-Zhe

2010-07-15

Independent component analysis (ICA) is a data-driven approach to study functional magnetic resonance imaging (fMRI) data. Particularly, for group analysis on multiple subjects, temporally concatenation group ICA (TC-GICA) is intensively used. However, due to the usually limited computational capability, data reduction with principal component analysis (PCA: a standard preprocessing step of ICA decomposition) is difficult to achieve for a large dataset. To overcome this, TC-GICA employs multiple-stage PCA data reduction. Such multiple-stage PCA data reduction, however, leads to variable outputs due to different subject concatenation orders. Consequently, the ICA algorithm uses the variable multiple-stage PCA outputs and generates variable decompositions. In this study, a rigorous theoretical analysis was conducted to prove the existence of such variability. Simulated and real fMRI experiments were used to demonstrate the subject-order-induced variability of TC-GICA results using multiple PCA data reductions. To solve this problem, we propose a new subject order-independent group ICA (SOI-GICA). Both simulated and real fMRI data experiments demonstrated the high robustness and accuracy of the SOI-GICA results compared to those of traditional TC-GICA. Accordingly, we recommend SOI-GICA for group ICA-based fMRI studies, especially those with large data sets. Copyright 2010 Elsevier Inc. All rights reserved.

Vulnerability of riparian obligate species to the interactive effect of fire, climate and hydrological change

Treesearch

Megan M. Friggens; Rachel Loehman; Lisa Holsinger; Deborah Finch

2014-01-01

Climate change is expected to have multiple direct and indirect impacts on ecosystems in the interior western U.S. (Christensen et al., 2007; IPCC 2013). Global climate predictions for the Southwest include higher temperatures, more variable rainfall, and more drought periods, which will likely exacerbate the ongoing issues relating to wildfire and water allocation in...

Empirical analyses of plant-climate relationships for the western United States

Treesearch

Gerald E. Rehfeldt; Nicholas L. Crookston; Marcus V. Warwell; Jeffrey S. Evans

2006-01-01

The Random Forests multiple-regression tree was used to model climate profiles of 25 biotic communities of the western United States and nine of their constituent species. Analyses of the communities were based on a gridded sample of ca. 140,000 points, while those for the species used presence-absence data from ca. 120,000 locations. Independent variables included 35...

Description of the MHS Health Level 7 Microbiology Laboratory for Public Health Surveillance

DTIC Science & Technology

2012-10-01

included, among others, respiratory infections (e.g., pandemic influenza, pertussis), skin and soft tissue infections (e.g., methicillin resistant ... Staphylococcus aureus ) and gastrointestinal infections (e.g., salmonellosis, norovirus). Positive microbiology results can be matched with outpatient or... Staphylococcus aureus . Laboratory Test Result Due to the structure of the laboratory data, results could be identified across multiple variables and

Probabilistic Based Modeling and Simulation Assessment

DTIC Science & Technology

2010-06-01

different crash and blast scenarios. With the integration of the high fidelity neck and head model, a methodology to calculate the probability of injury...variability, correlation, and multiple (often competing) failure metrics. Important scenarios include vehicular collisions, blast /fragment impact, and...first area of focus is to develop a methodology to integrate probabilistic analysis into finite element analysis of vehicle collisions and blast . The

Probabilistic-Based Modeling and Simulation Assessment

DTIC Science & Technology

2010-06-01

developed to determine the relative importance of structural components of the vehicle under differnet crash and blast scenarios. With the integration of...the vehicle under different crash and blast scenarios. With the integration of the high fidelity neck and head model, a methodology to calculate the...parameter variability, correlation, and multiple (often competing) failure metrics. Important scenarios include vehicular collisions, blast /fragment

Effects of a 10-Week High-Intensity Exercise Intervention on College Staff with Psychological Burnout and Multiple Risk Factors

ERIC Educational Resources Information Center

Dreyer, Lukas; Dreyer, Sonja; Rankin, Dean

2012-01-01

This study examined the effect of a 10-week physical exercise program on the health status of college staff. Eighty-one participants were pre-tested on 22 variables including physical fitness, biochemical status, psychological health, and morphological measures. Participants in an experimental group (n = 61) received a 10-week intervention…

Substance Use and PTSD Symptoms Impact the Likelihood of Rape and Revictimization in College Women

ERIC Educational Resources Information Center

Messman-Moore, Terri L.; Ward, Rose Marie; Brown, Amy L.

2009-01-01

The present study utilized a mixed retrospective and prospective design with an 8-month follow-up period to test a model of revictimization that included multiple childhood (i.e., child sexual, physical, and emotional abuse) and situational variables (i.e., substance use, sexual behavior) for predicting rape among 276 college women. It was of…

Multi-Elements in Waters and Sediments of Shallow Lakes: Relationships with Water, Sediment, and Watershed Characteristics.

PubMed

Kissoon, La Toya T; Jacob, Donna L; Hanson, Mark A; Herwig, Brian R; Bowe, Shane E; Otte, Marinus L

2015-06-01

We measured concentrations of multiple elements, including rare earth elements, in waters and sediments of 38 shallow lakes of varying turbidity and macrophyte cover in the Prairie Parkland (PP) and Laurentian Mixed Forest (LMF) provinces of Minnesota. PP shallow lakes had higher element concentrations in waters and sediments compared to LMF sites. Redundancy analysis indicated that a combination of site- and watershed-scale features explained a large proportion of among-lake variability in element concentrations in lake water and sediments. Percent woodland cover in watersheds, turbidity, open water area, and macrophyte cover collectively explained 65.2 % of variation in element concentrations in lake waters. Sediment fraction smaller than 63 µm, percent woodland in watersheds, open water area, and sediment organic matter collectively explained 64.2 % of variation in element concentrations in lake sediments. In contrast to earlier work on shallow lakes, our results showed the extent to which multiple elements in shallow lake waters and sediments were influenced by a combination of variables including sediment characteristics, lake morphology, and percent land cover in watersheds. These results are informative because they help illustrate the extent of functional connectivity between shallow lakes and adjacent lands within these lake watersheds.

Preferential Cyclooxygenase 2 Inhibitors as a Nonhormonal Method of Emergency Contraception: A Look at the Evidence.

PubMed

Weiss, Erich A; Gandhi, Mona

2016-04-01

To review the literature surrounding the use of preferential cyclooxygenase 2 (COX-2) inhibitors as an alternative form of emergency contraception. MEDLINE (1950 to February 2014) was searched using the key words cyclooxygenase or COX-2 combined with contraception, emergency contraception, or ovulation. Results were limited to randomized control trials, controlled clinical trials, and clinical trials. Human trials that measured the effects of COX inhibition on female reproductive potential were included for review. The effects of the COX-2 inhibitors rofecoxib, celecoxib, and meloxicam were evaluated in 6 trials. Each of which was small in scope, enrolled women of variable fertility status, used different dosing regimens, included multiple end points, and had variable results. Insufficient evidence exists to fully support the use of preferential COX-2 inhibitors as a form of emergency contraception. Although all trials resulted in a decrease in ovulatory cycles, outcomes varied between dosing strategies and agents used. A lack of homogeneity in these studies makes comparisons difficult. However, success of meloxicam in multiple trials warrants further study. Larger human trials are necessary before the clinical utility of this method of emergency contraception can be fully appreciated. © The Author(s) 2014.

Nerve fibre layer analysis with GDx with a variable corneal compensator in patients with multiple sclerosis.

PubMed

Della Mea, Giovanni; Bacchetti, Sonia; Zeppieri, Marco; Brusini, Paolo; Cutuli, Daniela; Gigli, Gian Luigi

2007-01-01

To evaluate the ability of GDx with variable corneal compensator (VCC) compared to visual-evoked potentials (VEPs) and standard automated perimetry (SAP) in the detection of early optic nerve damage in patients with multiple sclerosis (MS). 46 eyes of 23 MS patients were included. Ten of them had a history of acute retrobulbar optic neuritis. A control group of 20 normal subjects was also included. All subjects underwent a complete ophthalmological examination and testing with SAP, GDx VCC and VEPs. 19 eyes (41.3%) were abnormal with GDx VCC compared to 38 eyes (82.6%) with SAP and 31 (64.4%) with VEPs. In the optic neuritis group, 9 eyes (69.2%) had optic nerve pallor; SAP was abnormal in 8 of these eyes (61.5%) while VEPs and GDx VCC were abnormal in 6 eyes (46.1%). 2/20 eyes (10.0%) in the control group gave a false-positive abnormal result with SAP. GDx VCC and VEP were normal for all the eyes in the control group. GDx VCC is less able to detect early defects in MS patients compared to the currently used standard techniques of SAP and VEPs. Copyright (c) 2007 S. Karger AG, Basel.

Multi-Elements in Waters and Sediments of Shallow Lakes: Relationships with Water, Sediment, and Watershed Characteristics

PubMed Central

Jacob, Donna L.; Hanson, Mark A.; Herwig, Brian R.; Bowe, Shane E.; Otte, Marinus L.

2015-01-01

We measured concentrations of multiple elements, including rare earth elements, in waters and sediments of 38 shallow lakes of varying turbidity and macrophyte cover in the Prairie Parkland (PP) and Laurentian Mixed Forest (LMF) provinces of Minnesota. PP shallow lakes had higher element concentrations in waters and sediments compared to LMF sites. Redundancy analysis indicated that a combination of site- and watershed-scale features explained a large proportion of among-lake variability in element concentrations in lake water and sediments. Percent woodland cover in watersheds, turbidity, open water area, and macrophyte cover collectively explained 65.2 % of variation in element concentrations in lake waters. Sediment fraction smaller than 63 µm, percent woodland in watersheds, open water area, and sediment organic matter collectively explained 64.2 % of variation in element concentrations in lake sediments. In contrast to earlier work on shallow lakes, our results showed the extent to which multiple elements in shallow lake waters and sediments were influenced by a combination of variables including sediment characteristics, lake morphology, and percent land cover in watersheds. These results are informative because they help illustrate the extent of functional connectivity between shallow lakes and adjacent lands within these lake watersheds. PMID:26074657

MS in self-identified Hispanic/Latino individuals living in the US

PubMed Central

Amezcua, Lilyana; Oksenberg, Jorge R; McCauley, Jacob L

2017-01-01

Self-identified Hispanic/Latino individuals living with multiple sclerosis (MS) in the continental United States (US) are a diverse group that represents different cultural and ancestral backgrounds. A marked variability in the way MS affects various subgroups of Hispanics in the US has been observed. We reviewed and synthesized available data about MS in Hispanics in the US. There are likely a host of multifactorial elements contributing to these observations that could be explained by genetic, environmental, and social underpinnings. Barriers to adequate MS care in Hispanics are likely to include delivery of culturally competent care and social and economic disadvantages. Considerable efforts, including the formation of a national consortium known as the Alliance for Research in Hispanic Multiple Sclerosis (ARHMS), are underway to help further explore these various factors. PMID:28979795

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

Stratification of a cityscape using census and land use variables for inventory of building materials

USGS Publications Warehouse

Rosenfield, G.H.; Fitzpatrick-Lins, K.; Johnson, T.L.

1987-01-01

A cityscape (or any landscape) can be stratified into environmental units using multiple variables of information. For the purposes of sampling building materials, census and land use variables were used to identify similar strata. In the Metropolitan Statistical Area of a cityscape, the census tract is the smallest unit for which census data are summarized and digitized boundaries are available. For purposes of this analysis, census data on total population, total number of housing units, and number of singleunit dwellings were aggregated into variables of persons per square kilometer and proportion of housing units in single-unit dwellings. The level 2 categories of the U.S. Geological Survey's land use and land cover data base were aggregated into variables of proportion of residential land with buildings, proportion of nonresidential land with buildings, and proportion of open land. The cityscape was stratified, from these variables, into environmental strata of Urban Central Business District, Urban Livelihood Industrial Commercial, Urban Multi-Family Residential, Urban Single Family Residential, Non-Urban Suburbanizing, and Non-Urban Rural. The New England region was chosen as a region with commonality of building materials, and a procedure developed for trial classification of census tracts into one of the strata. Final stratification was performed by discriminant analysis using the trial classification and prior probabilities as weights. The procedure was applied to several cities, and the results analyzed by correlation analysis from a field sample of building materials. The methodology developed for stratification of a cityscape using multiple variables has application to many other types of environmental studies, including forest inventory, hydrologic unit management, waste disposal, transportation studies, and other urban studies. Multivariate analysis techniques have recently been used for urban stratification in England. ?? 1987 Annals of Regional Science.

The Enduring Challenge of Determining Pneumonia Etiology in Children: Considerations for Future Research Priorities

PubMed Central

Hammitt, Laura L.; Murdoch, David R.; O’Brien, Katherine L.; Scott, J. Anthony G.

2017-01-01

Abstract Pneumonia kills more children each year worldwide than any other disease. Nonetheless, accurately determining the causes of childhood pneumonia has remained elusive. Over the past century, the focus of pneumonia etiology research has shifted from studies of lung aspirates and postmortem specimens intent on identifying pneumococcal disease to studies of multiple specimen types distant from the lung that are tested for multiple pathogens. Some major challenges facing modern pneumonia etiology studies include the use of nonspecific and variable case definitions, poor access to pathologic lung tissue and to specimens from fatal cases, poor diagnostic accuracy of assays (especially when testing nonpulmonary specimens), and the interpretation of results when multiple pathogens are detected in a given individual. The future of childhood pneumonia etiology research will likely require integrating data from complementary approaches, including applications of advanced molecular diagnostics and vaccine probe studies, as well as a renewed emphasis on lung aspirates from radiologically confirmed pneumonia and postmortem examinations. PMID:28575369

Aggression at Age 5 as a Function of Prenatal Exposure to Cocaine, Gender, and Environmental Risk

PubMed Central

Bendersky, Margaret; Bennett, David; Lewis, Michael

2006-01-01

Objective To examine childhood aggression at age 5 in a multiple risk model that includes cocaine exposure, environmental risk, and gender as predictors. Methods Aggression was assessed in 206 children by using multiple methods including teacher report, parent report, child’s response to hypothetical provocations, and child’s observed behavior. Also examined was a composite score that reflected high aggression across contexts. Results Multiple regression analyses indicated that a significant amount of variance in each of the aggression measures and the composite was explained by the predictors. The variables that were independently related differed depending on the outcome. Cocaine exposure, gender, and environmental risk were all related to the composite aggression score. Conclusions Cocaine exposure, being male, and a high-risk environment were all predictive of aggressive behavior at 5 years. It is this group of exposed boys at high environmental risk that is most likely to show continued aggression over time. PMID:15827351

Experience by children and adolescents of more than one type of maltreatment: Association of different classes of maltreatment profiles with clinical outcome variables.

PubMed

Witt, Andreas; Münzer, Annika; Ganser, Helene G; Fegert, Jörg M; Goldbeck, Lutz; Plener, Paul L

2016-07-01

Most victims of child abuse have experienced more than one type of maltreatment, yet there is a lack of understanding of the impact of specific combinations of types of maltreatment. This study aimed to identify meaningful classes of maltreatment profiles and to associate them with short-term clinical outcomes. A total of 358 German children and adolescents aged 4-17 with a known history of child maltreatment were included in the study. Through interviews and questionnaires, information was obtained from participants and their primary caregivers on history of maltreatment, sociodemographics, psychopathology, level of psychosocial functioning, and health-related quality of life. Types of abuse were categorized into six major groups: sexual abuse in general, sexual abuse with penetration, physical abuse, emotional abuse, neglect, and exposure to domestic violence. A latent class analysis (LCA) was performed to determine distinct multi-type maltreatment profiles, which were then assessed for their associations with the sociodemographic and clinical outcome variables. The LCA revealed that participants could be categorized into three meaningful classes according to history of maltreatment: (1) experience of multiple types of maltreatment excluding sexual abuse (63.1%), (2) experience of multiple types of maltreatment including sexual abuse (26.5%), and (3) experience of predominantly sexual abuse (10.3%). Members of Class 2 showed significantly worse short-term outcomes on psychopathology, level of functioning, and quality of life compared to the other classes. Three distinct profiles of multiple types of maltreatment were empirically identified in this sample. Exposure to multiple types of abuse was associated with poorer outcomes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Plenoptic particle image velocimetry with multiple plenoptic cameras

NASA Astrophysics Data System (ADS)

Fahringer, Timothy W.; Thurow, Brian S.

2018-07-01

Plenoptic particle image velocimetry was recently introduced as a viable three-dimensional, three-component velocimetry technique based on light field cameras. One of the main benefits of this technique is its single camera configuration allowing the technique to be applied in facilities with limited optical access. The main drawback of this configuration is decreased accuracy in the out-of-plane dimension. This work presents a solution with the addition of a second plenoptic camera in a stereo-like configuration. A framework for reconstructing volumes with multiple plenoptic cameras including the volumetric calibration and reconstruction algorithms, including: integral refocusing, filtered refocusing, multiplicative refocusing, and MART are presented. It is shown that the addition of a second camera improves the reconstruction quality and removes the ‘cigar’-like elongation associated with the single camera system. In addition, it is found that adding a third camera provides minimal improvement. Further metrics of the reconstruction quality are quantified in terms of a reconstruction algorithm, particle density, number of cameras, camera separation angle, voxel size, and the effect of common image noise sources. In addition, a synthetic Gaussian ring vortex is used to compare the accuracy of the single and two camera configurations. It was determined that the addition of a second camera reduces the RMSE velocity error from 1.0 to 0.1 voxels in depth and 0.2 to 0.1 voxels in the lateral spatial directions. Finally, the technique is applied experimentally on a ring vortex and comparisons are drawn from the four presented reconstruction algorithms, where it was found that MART and multiplicative refocusing produced the cleanest vortex structure and had the least shot-to-shot variability. Filtered refocusing is able to produce the desired structure, albeit with more noise and variability, while integral refocusing struggled to produce a coherent vortex ring.

Heart rate variability.

PubMed

Cygankiewicz, Iwona; Zareba, Wojciech

2013-01-01

Heart rate variability (HRV) provides indirect insight into autonomic nervous system tone, and has a well-established role as a marker of cardiovascular risk. Recent decades brought an increasing interest in HRV assessment as a diagnostic tool in detection of autonomic impairment, and prediction of prognosis in several neurological disorders. Both bedside analysis of simple markers of HRV, as well as more sophisticated HRV analyses including time, frequency domain and nonlinear analysis have been proven to detect early autonomic involvement in several neurological disorders. Furthermore, altered HRV parameters were shown to be related with cardiovascular risk, including sudden cardiac risk, in patients with neurological diseases. This chapter aims to review clinical and prognostic application of HRV analysis in diabetes, stroke, multiple sclerosis, muscular dystrophies, Parkinson's disease and epilepsy. © 2013 Elsevier B.V. All rights reserved.

Selection of latent variables for multiple mixed-outcome models

PubMed Central

ZHOU, LING; LIN, HUAZHEN; SONG, XINYUAN; LI, YI

2014-01-01

Latent variable models have been widely used for modeling the dependence structure of multiple outcomes data. However, the formulation of a latent variable model is often unknown a priori, the misspecification will distort the dependence structure and lead to unreliable model inference. Moreover, multiple outcomes with varying types present enormous analytical challenges. In this paper, we present a class of general latent variable models that can accommodate mixed types of outcomes. We propose a novel selection approach that simultaneously selects latent variables and estimates parameters. We show that the proposed estimator is consistent, asymptotically normal and has the oracle property. The practical utility of the methods is confirmed via simulations as well as an application to the analysis of the World Values Survey, a global research project that explores peoples’ values and beliefs and the social and personal characteristics that might influence them. PMID:27642219

Increasing Megadrought Risk at the Intersection of Decadal to Centennial Variability and Climate Change

NASA Astrophysics Data System (ADS)

Overpeck, J. T.; Parsons, L. A.; Loope, G. R.; Ault, T.; Cole, J. E.; Otto-Bliesner, B. L.; Buckle, N.; Stevenson, S.; Fasullo, J.

2016-12-01

Even more than the 1930's U.S. Dust Bowl Drought, the 20th century Sahel drought stands out as the most unprecedented drought of the instrumental era, in part because it extended over multiple decades. Paleoclimatic evidence makes it clear that this Sahel drought was nonetheless not really unprecedented - droughts many decades long have occurred in sub-Saharan Africa regularly over the last several thousand years, and these constitute what is now increasingly referred to as "megadrought." Paleoclimatic evidence also makes it clear that all drought-prone semi-arid and arid regions of the globe, including southwestern North America, southeastern Australia, and the Mediterranean/Middle Eastern region likely experienced multiple such multidecadal megadroughts in recent pre-Anthropocene Earth history. In other regions of the globe, including parts of South Asia and Amazonia, short but devastating droughts of the last 50-150 years, were also eclipsed in recent Earth history by much more serious megadrought, although these megadroughts were shorter than the multidecadal droughts of Africa or SW North America. In the past, megadroughts have occurred for reasons that are increasingly well understood in terms of ocean-atmosphere dynamics that led to unusually persistent precipitation deficits. Many of these same dynamics are well simulated in state-of-the-art Earth System Models, and yet comparisons between simulated and observed paleohydroclimatic variability suggests the models generally underestimate the risk of megadrought. Paleohydroclimatic records in some cases overestimate drought persistence, but there appear to be other issues at play that need to be better understood and simulated: positive land-atmosphere feedbacks, overly energetic interannual (i.e., ENSO) modes of variability, and insufficient internal multidecadal to centennial coupled climate system variability. Taking these issues and the impact of anthropogenic climate change into account means that the risk of megadrought is increasing significantly in many regions of the globe as the planet warms - tools, including critical paleoclimatic data, are being developed to help anticipate and adapt to this growing challenge.

SU-E-T-344: Dynamic Electron Beam Therapy Using Multiple Apertures in a Single Cut-Out

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

Rodrigues, A; Yin, F; Wu, Q

2015-06-15

Purpose: Few leaf electron collimators (FLEC) or electron MLCs (eMLC) are highly desirable for dynamic electron beam therapies as they produce multiple apertures within a single delivery to achieve conformal dose distributions. However, their clinical implementation has been challenging. Alternatively, multiple small apertures in a single cut-out with variable jaw sizes could be utilized in a single dynamic delivery. In this study, we investigate dosimetric characteristics of such arrangement. Methods: Monte Carlo (EGSnrc/BEAMnrc/DOSXYnrc) simulations utilized validated Varian TrueBeam phase spaces. Investigated quantities included: Energy (6 MeV), jaw size (1×1 to 22×22 cm {sup 2}; centered to aperture), applicator/cut-out (15×15 cm{supmore » 2}), aperture (1×1, 2×2, 3×3, 4×4 cm{sup 2}), and aperture placement (on/off central axis). Three configurations were assessed: (1) single aperture on-axis, (2) single aperture off-axis, and (3) multiple apertures. Reference was configuration (1) with standard jaw size. Aperture placement and jaw size were optimized to maintain reference dosimetry and minimize leakage through unused apertures to <5%. Comparison metrics included depth dose and orthogonal profiles. Results: Configuration (1) and (2): Jaw openings were reduced to 10×10 cm{sup 2} without affecting dosimetry (gamma 2%/1mm) regardless of on- or off-axis placement. For smaller jaw sizes, reduced surface (<2%, 5% for 1×1 cm{sup 2} aperture) and increased Bremsstrahlung (<2%, 10% for 1×1 cm{sup 2} aperture) dose was observed. Configuration (3): Optimal aperture placement was in the corners (order: 1×1, 4×4, 2×2, 3×3 cm{sup 2}) and jaw sizes were 4×4, 4×4, 7×7, and 5×5 cm{sup 2} (apertures: 1×1, 2×2, 3×3, 4×4 cm{sup 2} ). Asymmetric leakage was found from upper and lower jaws. Leakage was generally within 5% with a maximum of 10% observed for the 1×1 cm{sup 2} aperture irradiation. Conclusion: Multiple apertures in a single cut-out with variable jaw size can be used in a single dynamic delivery, providing a practical alternative to FLEC or eMLC. Future simulations will expand on all variables.« less

A Source Area Approach Demonstrates Moderate Predictive Ability but Pronounced Variability of Invasive Species Traits

PubMed Central

Essl, Franz; Dullinger, Stefan

2016-01-01

The search for traits that make alien species invasive has mostly concentrated on comparing successful invaders and different comparison groups with respect to average trait values. By contrast, little attention has been paid to trait variability among invaders. Here, we combine an analysis of trait differences between invasive and non-invasive species with a comparison of multidimensional trait variability within these two species groups. We collected data on biological and distributional traits for 1402 species of the native, non-woody vascular plant flora of Austria. We then compared the subsets of species recorded and not recorded as invasive aliens anywhere in the world, respectively, first, with respect to the sampled traits using univariate and multiple regression models; and, second, with respect to their multidimensional trait diversity by calculating functional richness and dispersion metrics. Attributes related to competitiveness (strategy type, nitrogen indicator value), habitat use (agricultural and ruderal habitats, occurrence under the montane belt), and propagule pressure (frequency) were most closely associated with invasiveness. However, even the best multiple model, including interactions, only explained a moderate fraction of the differences in invasive success. In addition, multidimensional variability in trait space was even larger among invasive than among non-invasive species. This pronounced variability suggests that invasive success has a considerable idiosyncratic component and is probably highly context specific. We conclude that basing risk assessment protocols on species trait profiles will probably face hardly reducible uncertainties. PMID:27187616

A Source Area Approach Demonstrates Moderate Predictive Ability but Pronounced Variability of Invasive Species Traits.

PubMed

Klonner, Günther; Fischer, Stefan; Essl, Franz; Dullinger, Stefan

2016-01-01

The search for traits that make alien species invasive has mostly concentrated on comparing successful invaders and different comparison groups with respect to average trait values. By contrast, little attention has been paid to trait variability among invaders. Here, we combine an analysis of trait differences between invasive and non-invasive species with a comparison of multidimensional trait variability within these two species groups. We collected data on biological and distributional traits for 1402 species of the native, non-woody vascular plant flora of Austria. We then compared the subsets of species recorded and not recorded as invasive aliens anywhere in the world, respectively, first, with respect to the sampled traits using univariate and multiple regression models; and, second, with respect to their multidimensional trait diversity by calculating functional richness and dispersion metrics. Attributes related to competitiveness (strategy type, nitrogen indicator value), habitat use (agricultural and ruderal habitats, occurrence under the montane belt), and propagule pressure (frequency) were most closely associated with invasiveness. However, even the best multiple model, including interactions, only explained a moderate fraction of the differences in invasive success. In addition, multidimensional variability in trait space was even larger among invasive than among non-invasive species. This pronounced variability suggests that invasive success has a considerable idiosyncratic component and is probably highly context specific. We conclude that basing risk assessment protocols on species trait profiles will probably face hardly reducible uncertainties.

Characterizing individual differences in functional connectivity using dual-regression and seed-based approaches.

PubMed

Smith, David V; Utevsky, Amanda V; Bland, Amy R; Clement, Nathan; Clithero, John A; Harsch, Anne E W; McKell Carter, R; Huettel, Scott A

2014-07-15

A central challenge for neuroscience lies in relating inter-individual variability to the functional properties of specific brain regions. Yet, considerable variability exists in the connectivity patterns between different brain areas, potentially producing reliable group differences. Using sex differences as a motivating example, we examined two separate resting-state datasets comprising a total of 188 human participants. Both datasets were decomposed into resting-state networks (RSNs) using a probabilistic spatial independent component analysis (ICA). We estimated voxel-wise functional connectivity with these networks using a dual-regression analysis, which characterizes the participant-level spatiotemporal dynamics of each network while controlling for (via multiple regression) the influence of other networks and sources of variability. We found that males and females exhibit distinct patterns of connectivity with multiple RSNs, including both visual and auditory networks and the right frontal-parietal network. These results replicated across both datasets and were not explained by differences in head motion, data quality, brain volume, cortisol levels, or testosterone levels. Importantly, we also demonstrate that dual-regression functional connectivity is better at detecting inter-individual variability than traditional seed-based functional connectivity approaches. Our findings characterize robust-yet frequently ignored-neural differences between males and females, pointing to the necessity of controlling for sex in neuroscience studies of individual differences. Moreover, our results highlight the importance of employing network-based models to study variability in functional connectivity. Copyright © 2014 Elsevier Inc. All rights reserved.

Dysglycemia, Glycemic Variability, and Outcome After Cardiac Arrest and Temperature Management at 33°C and 36°C.

PubMed

Borgquist, Ola; Wise, Matt P; Nielsen, Niklas; Al-Subaie, Nawaf; Cranshaw, Julius; Cronberg, Tobias; Glover, Guy; Hassager, Christian; Kjaergaard, Jesper; Kuiper, Michael; Smid, Ondrej; Walden, Andrew; Friberg, Hans

2017-08-01

Dysglycemia and glycemic variability are associated with poor outcomes in critically ill patients. Targeted temperature management alters blood glucose homeostasis. We investigated the association between blood glucose concentrations and glycemic variability and the neurologic outcomes of patients randomized to targeted temperature management at 33°C or 36°C after cardiac arrest. Post hoc analysis of the multicenter TTM-trial. Primary outcome of this analysis was neurologic outcome after 6 months, referred to as "Cerebral Performance Category." Thirty-six sites in Europe and Australia. All 939 patients with out-of-hospital cardiac arrest of presumed cardiac cause that had been included in the TTM-trial. Targeted temperature management at 33°C or 36°C. Nonparametric tests as well as multiple logistic regression and mixed effects logistic regression models were used. Median glucose concentrations on hospital admission differed significantly between Cerebral Performance Category outcomes (p < 0.0001). Hyper- and hypoglycemia were associated with poor neurologic outcome (p = 0.001 and p = 0.054). In the multiple logistic regression models, the median glycemic level was an independent predictor of poor Cerebral Performance Category (Cerebral Performance Category, 3-5) with an odds ratio (OR) of 1.13 in the adjusted model (p = 0.008; 95% CI, 1.03-1.24). It was also a predictor in the mixed model, which served as a sensitivity analysis to adjust for the multiple time points. The proportion of hyperglycemia was higher in the 33°C group compared with the 36°C group. Higher blood glucose levels at admission and during the first 36 hours, and higher glycemic variability, were associated with poor neurologic outcome and death. More patients in the 33°C treatment arm had hyperglycemia.

The psychological factor 'self-blame' predicts overuse injury among top-level Swedish track and field athletes: a 12-month cohort study.

PubMed

Timpka, Toomas; Jacobsson, Jenny; Dahlström, Örjan; Kowalski, Jan; Bargoria, Victor; Ekberg, Joakim; Nilsson, Sverker; Renström, Per

2015-11-01

Athletes' psychological characteristics are important for understanding sports injury mechanisms. We examined the relevance of psychological factors in an integrated model of overuse injury risk in athletics/track and field. Swedish track and field athletes (n=278) entering a 12-month injury surveillance in March 2009 were also invited to complete a psychological survey. Simple Cox proportional hazards models were compiled for single explanatory variables. We also tested multiple models for 3 explanatory variable groupings: an epidemiological model without psychological variables, a psychological model excluding epidemiological variables and an integrated (combined) model. The integrated multiple model included the maladaptive coping behaviour self-blame (p=0.007; HR 1.32; 95% CI 1.08 to 1.61), and an interaction between athlete category and injury history (p<0.001). Youth female (p=0.034; HR 0.51; 95% CI 0.27 to 0.95) and youth male (p=0.047; HR 0.49; 95% CI 0.24 to 0.99) athletes with no severe injury the previous year were at half the risk of sustaining a new injury compared with the reference group. A training load index entered the epidemiological multiple model, but not the integrated model. The coping behaviour self-blame replaced training load in an integrated explanatory model of overuse injury risk in athletes. What seemed to be more strongly related to the likelihood of overuse injury was not the athletics load per se, but, rather, the load applied in situations when the athlete's body was in need of rest. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

VoxelStats: A MATLAB Package for Multi-Modal Voxel-Wise Brain Image Analysis.

PubMed

Mathotaarachchi, Sulantha; Wang, Seqian; Shin, Monica; Pascoal, Tharick A; Benedet, Andrea L; Kang, Min Su; Beaudry, Thomas; Fonov, Vladimir S; Gauthier, Serge; Labbe, Aurélie; Rosa-Neto, Pedro

2016-01-01

In healthy individuals, behavioral outcomes are highly associated with the variability on brain regional structure or neurochemical phenotypes. Similarly, in the context of neurodegenerative conditions, neuroimaging reveals that cognitive decline is linked to the magnitude of atrophy, neurochemical declines, or concentrations of abnormal protein aggregates across brain regions. However, modeling the effects of multiple regional abnormalities as determinants of cognitive decline at the voxel level remains largely unexplored by multimodal imaging research, given the high computational cost of estimating regression models for every single voxel from various imaging modalities. VoxelStats is a voxel-wise computational framework to overcome these computational limitations and to perform statistical operations on multiple scalar variables and imaging modalities at the voxel level. VoxelStats package has been developed in Matlab(®) and supports imaging formats such as Nifti-1, ANALYZE, and MINC v2. Prebuilt functions in VoxelStats enable the user to perform voxel-wise general and generalized linear models and mixed effect models with multiple volumetric covariates. Importantly, VoxelStats can recognize scalar values or image volumes as response variables and can accommodate volumetric statistical covariates as well as their interaction effects with other variables. Furthermore, this package includes built-in functionality to perform voxel-wise receiver operating characteristic analysis and paired and unpaired group contrast analysis. Validation of VoxelStats was conducted by comparing the linear regression functionality with existing toolboxes such as glim_image and RMINC. The validation results were identical to existing methods and the additional functionality was demonstrated by generating feature case assessments (t-statistics, odds ratio, and true positive rate maps). In summary, VoxelStats expands the current methods for multimodal imaging analysis by allowing the estimation of advanced regional association metrics at the voxel level.

Integrated presentation of ecological risk from multiple stressors

PubMed Central

Goussen, Benoit; Price, Oliver R.; Rendal, Cecilie; Ashauer, Roman

2016-01-01

Current environmental risk assessments (ERA) do not account explicitly for ecological factors (e.g. species composition, temperature or food availability) and multiple stressors. Assessing mixtures of chemical and ecological stressors is needed as well as accounting for variability in environmental conditions and uncertainty of data and models. Here we propose a novel probabilistic ERA framework to overcome these limitations, which focusses on visualising assessment outcomes by construct-ing and interpreting prevalence plots as a quantitative prediction of risk. Key components include environmental scenarios that integrate exposure and ecology, and ecological modelling of relevant endpoints to assess the effect of a combination of stressors. Our illustrative results demonstrate the importance of regional differences in environmental conditions and the confounding interactions of stressors. Using this framework and prevalence plots provides a risk-based approach that combines risk assessment and risk management in a meaningful way and presents a truly mechanistic alternative to the threshold approach. Even whilst research continues to improve the underlying models and data, regulators and decision makers can already use the framework and prevalence plots. The integration of multiple stressors, environmental conditions and variability makes ERA more relevant and realistic. PMID:27782171

cit: hypothesis testing software for mediation analysis in genomic applications.

PubMed

Millstein, Joshua; Chen, Gary K; Breton, Carrie V

2016-08-01

The challenges of successfully applying causal inference methods include: (i) satisfying underlying assumptions, (ii) limitations in data/models accommodated by the software and (iii) low power of common multiple testing approaches. The causal inference test (CIT) is based on hypothesis testing rather than estimation, allowing the testable assumptions to be evaluated in the determination of statistical significance. A user-friendly software package provides P-values and optionally permutation-based FDR estimates (q-values) for potential mediators. It can handle single and multiple binary and continuous instrumental variables, binary or continuous outcome variables and adjustment covariates. Also, the permutation-based FDR option provides a non-parametric implementation. Simulation studies demonstrate the validity of the cit package and show a substantial advantage of permutation-based FDR over other common multiple testing strategies. The cit open-source R package is freely available from the CRAN website (https://cran.r-project.org/web/packages/cit/index.html) with embedded C ++ code that utilizes the GNU Scientific Library, also freely available (http://www.gnu.org/software/gsl/). joshua.millstein@usc.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Exploring High-D Spaces with Multiform Matrices and Small Multiples

PubMed Central

MacEachren, Alan; Dai, Xiping; Hardisty, Frank; Guo, Diansheng; Lengerich, Gene

2011-01-01

We introduce an approach to visual analysis of multivariate data that integrates several methods from information visualization, exploratory data analysis (EDA), and geovisualization. The approach leverages the component-based architecture implemented in GeoVISTA Studio to construct a flexible, multiview, tightly (but generically) coordinated, EDA toolkit. This toolkit builds upon traditional ideas behind both small multiples and scatterplot matrices in three fundamental ways. First, we develop a general, MultiForm, Bivariate Matrix and a complementary MultiForm, Bivariate Small Multiple plot in which different bivariate representation forms can be used in combination. We demonstrate the flexibility of this approach with matrices and small multiples that depict multivariate data through combinations of: scatterplots, bivariate maps, and space-filling displays. Second, we apply a measure of conditional entropy to (a) identify variables from a high-dimensional data set that are likely to display interesting relationships and (b) generate a default order of these variables in the matrix or small multiple display. Third, we add conditioning, a kind of dynamic query/filtering in which supplementary (undisplayed) variables are used to constrain the view onto variables that are displayed. Conditioning allows the effects of one or more well understood variables to be removed from the analysis, making relationships among remaining variables easier to explore. We illustrate the individual and combined functionality enabled by this approach through application to analysis of cancer diagnosis and mortality data and their associated covariates and risk factors. PMID:21947129

Primary care physicians' willingness to disclose oncology errors involving multiple providers to patients.

PubMed

Mazor, Kathleen; Roblin, Douglas W; Greene, Sarah M; Fouayzi, Hassan; Gallagher, Thomas H

2016-10-01

Full disclosure of harmful errors to patients, including a statement of regret, an explanation, acceptance of responsibility and commitment to prevent recurrences is the current standard for physicians in the USA. To examine the extent to which primary care physicians' perceptions of event-level, physician-level and organisation-level factors influence intent to disclose a medical error in challenging situations. Cross-sectional survey containing two hypothetical vignettes: (1) delayed diagnosis of breast cancer, and (2) care coordination breakdown causing a delayed response to patient symptoms. In both cases, multiple physicians shared responsibility for the error, and both involved oncology diagnoses. The study was conducted in the context of the HMO Cancer Research Network Cancer Communication Research Center. Primary care physicians from three integrated healthcare delivery systems located in Washington, Massachusetts and Georgia; responses from 297 participants were included in these analyses. The dependent variable intent to disclose included intent to provide an apology, an explanation, information about the cause and plans for preventing recurrences. Independent variables included event-level factors (responsibility for the event, perceived seriousness of the event, predictions about a lawsuit); physician-level factors (value of patient-centred communication, communication self-efficacy and feelings about practice); organisation-level factors included perceived support for communication and time constraints. A majority of respondents would not fully disclose in either situation. The strongest predictors of disclosure were perceived personal responsibility, perceived seriousness of the event and perceived value of patient-centred communication. These variables were consistently associated with intent to disclose. To make meaningful progress towards improving disclosure; physicians, risk managers, organisational leaders, professional organisations and accreditation bodies need to understand the factors which influence disclosure. Such an understanding is required to inform institutional policies and provider training. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas, USA

USGS Publications Warehouse

Ohlmacher, G.C.; Davis, J.C.

2003-01-01

Landslides in the hilly terrain along the Kansas and Missouri rivers in northeastern Kansas have caused millions of dollars in property damage during the last decade. To address this problem, a statistical method called multiple logistic regression has been used to create a landslide-hazard map for Atchison, Kansas, and surrounding areas. Data included digitized geology, slopes, and landslides, manipulated using ArcView GIS. Logistic regression relates predictor variables to the occurrence or nonoccurrence of landslides within geographic cells and uses the relationship to produce a map showing the probability of future landslides, given local slopes and geologic units. Results indicated that slope is the most important variable for estimating landslide hazard in the study area. Geologic units consisting mostly of shale, siltstone, and sandstone were most susceptible to landslides. Soil type and aspect ratio were considered but excluded from the final analysis because these variables did not significantly add to the predictive power of the logistic regression. Soil types were highly correlated with the geologic units, and no significant relationships existed between landslides and slope aspect. ?? 2003 Elsevier Science B.V. All rights reserved.

Female homicide in Rio Grande do Sul, Brazil.

PubMed

Leites, Gabriela Tomedi; Meneghel, Stela Nazareth; Hirakata, Vania Noemi

2014-01-01

This study aimed to assess the female homicide rate due to aggression in Rio Grande do Sul, Brazil, using this as a "proxy" of femicide. This was an ecological study which correlated the female homicide rate due to aggression in Rio Grande do Sul, according to the 35 microregions defined by the Brazilian Institute of Geography and Statistics (IBGE), with socioeconomic and demographic variables access and health indicators. Pearson's correlation test was performed with the selected variables. After this, multiple linear regressions were performed with variables with p < 0.20. The standardized average of female homicide rate due to aggression in the period from 2003 to 2007 was 3.1 obits per 100 thousand. After multiple regression analysis, the final model included male mortality due to aggression (p = 0.016), the percentage of hospital admissions for alcohol (p = 0.005) and the proportion of ill-defined deaths (p = 0.015). The model have an explanatory power of 39% (adjusted r2 = 0.391). The results are consistent with other studies and indicate a strong relationship between structural violence in society and violence against women, in addition to a higher incidence of female deaths in places with high alcohol hospitalization.

Multiple regression technique for Pth degree polynominals with and without linear cross products

NASA Technical Reports Server (NTRS)

Davis, J. W.

1973-01-01

A multiple regression technique was developed by which the nonlinear behavior of specified independent variables can be related to a given dependent variable. The polynomial expression can be of Pth degree and can incorporate N independent variables. Two cases are treated such that mathematical models can be studied both with and without linear cross products. The resulting surface fits can be used to summarize trends for a given phenomenon and provide a mathematical relationship for subsequent analysis. To implement this technique, separate computer programs were developed for the case without linear cross products and for the case incorporating such cross products which evaluate the various constants in the model regression equation. In addition, the significance of the estimated regression equation is considered and the standard deviation, the F statistic, the maximum absolute percent error, and the average of the absolute values of the percent of error evaluated. The computer programs and their manner of utilization are described. Sample problems are included to illustrate the use and capability of the technique which show the output formats and typical plots comparing computer results to each set of input data.

Determining the effect of key climate drivers on global hydropower production

NASA Astrophysics Data System (ADS)

Galelli, S.; Ng, J. Y.; Lee, D.; Block, P. J.

2017-12-01

Accounting for about 17% of total global electrical power production, hydropower is arguably the world's main renewable energy source and a key asset to meet Paris climate agreements. A key component of hydropower production is water availability, which depends on both precipitation and multiple drivers of climate variability acting at different spatial and temporal scales. To understand how these drivers impact global hydropower production, we study the relation between four patterns of ocean-atmosphere climate variability (i.e., El Niño Southern Oscillation, Pacific Decadal Oscillation, North Atlantic Oscillation, and Atlantic Multidecadal Oscillation) and monthly time series of electrical power production for over 1,500 hydropower reservoirs—obtained via simulation with a high-fidelity dam model forced with 20th century climate conditions. Notably significant relationships between electrical power productions and climate variability are found in many climate sensitive regions globally, including North and South America, East Asia, West Africa, and Europe. Coupled interactions from multiple, simultaneous climate drivers are also evaluated. Finally, we highlight the importance of using these climate drivers as an additional source of information within reservoir operating rules where the skillful predictability of inflow exists.

The predictors of chemistry achievement of 12th grade students in secondary schools in the United Arab Emirates

NASA Astrophysics Data System (ADS)

Khalaf, Ali Khalfan

2000-10-01

The purpose of this study is to explore variables related to chemistry achievement of 12th grade science students in the United Arab Emirates (UAE). The focus is to identify student, teacher, and school variables that predict chemistry achievement. The analysis sample included 204 males and 252 females in 66 classes in 60 schools from 10 districts or bureaus of education in the UAE. Thirty-two male and 33 female chemistry teachers and 60 school principals were included. The Khalaf Chemistry Achievement Test, GALT, the Student Questionnaire, Teacher Questionnaire, and School Information Questionnaire were administered. Descriptive statistics, correlations, analyses of variance, factor analysis, and stepwise multiple linear regression analyses were done. The results indicate that demographic, home environment, prior knowledge, scholastic ability, attitudes and perceptions related to chemistry and science, and student perception of instructional practices variables correlated with student chemistry achievement. The amount of help teachers received from the supervisor, class size, and courses in geology were teacher variables that correlated with class chemistry achievement. Nine school variables involving school, division, and class sizes correlated with school chemistry achievement. Analyses of variance revealed significant interaction effects: district by school size and district by student gender. In two districts, students in small schools achieved better than those in large schools. Generally female students achieved equal to or better than males. Three factors from the factor analysis: School Size, Prior Student Achievement, and Student Perception of Teacher Effectiveness, correlated with school chemistry achievement. The results of the multiple linear regression indicated that the factors of Prior Student Achievement, Student Perception of Teacher Effectiveness, and Teacher Experience and Expertise accounted for 45% of the variance in school chemistry achievement. Results indicate that the strongest predictors of chemistry achievement are prior achievement in science, Arabic language, and mathematics; student perception of teacher effectiveness; and teacher experience and expertise. Females tend to achieve better in chemistry than males. No nationality differences were found and the relationship of school size to chemistry achievement was inconclusive. Recommendations related to chemistry and science are presented. These include curriculum, school practice, teacher professional development, and future research.

Neuroanatomy of pseudobulbar affect : a quantitative MRI study in multiple sclerosis.

PubMed

Ghaffar, Omar; Chamelian, Laury; Feinstein, Anthony

2008-03-01

Pseudobulbar affect (PBA) is defined as episodes of involuntary crying, laughing, or both in the absence of a matching subjective mood state. This neuropsychiatric syndrome can be found in a number of neurological disorders including multiple sclerosis (MS). The aim of this study was to identify neuroanatomical correlates of PBA in multiple sclerosis (MS) using a case-control 1.5T MRI study. MS patients with (n = 14) and without (n = 14) PBA were matched on demographic, disease course, and disability variables. Comorbid psychiatric disorders including depressive and anxiety disorders were absent. Hypo- and hyperintense lesion volumes plus measurements of atrophy were obtained and localized anatomically according to parcellated brain regions. Between-group statistical comparisons were undertaken with alpha set at 0.01 for the primary analysis. Discrete differences in lesion volume were noted in six regions: Brainstem hypointense lesions, bilateral inferior parietal and medial inferior frontal hyperintense lesions, and right medial superior frontal hyperintense lesions were all significantly higher in the PBA group. A logistic regression model identified four of these variables (brainstem hypointense, left inferior parietal hyperintense, and left and right medial inferior frontal hyperintense lesion volumes) that accounted for 70% of the variance when it came to explaining the presence of PBA. In conclusion, MS patients with PBA have a distinct distribution of brain lesions when compared to a matched MS sample without PBA. The lesion data support a widely-dispersed neural network involving frontal, parietal, and brainstem regions in the pathophysiology of PBA.

PROMISE: a tool to identify genomic features with a specific biologically interesting pattern of associations with multiple endpoint variables.

PubMed

Pounds, Stan; Cheng, Cheng; Cao, Xueyuan; Crews, Kristine R; Plunkett, William; Gandhi, Varsha; Rubnitz, Jeffrey; Ribeiro, Raul C; Downing, James R; Lamba, Jatinder

2009-08-15

In some applications, prior biological knowledge can be used to define a specific pattern of association of multiple endpoint variables with a genomic variable that is biologically most interesting. However, to our knowledge, there is no statistical procedure designed to detect specific patterns of association with multiple endpoint variables. Projection onto the most interesting statistical evidence (PROMISE) is proposed as a general procedure to identify genomic variables that exhibit a specific biologically interesting pattern of association with multiple endpoint variables. Biological knowledge of the endpoint variables is used to define a vector that represents the biologically most interesting values for statistics that characterize the associations of the endpoint variables with a genomic variable. A test statistic is defined as the dot-product of the vector of the observed association statistics and the vector of the most interesting values of the association statistics. By definition, this test statistic is proportional to the length of the projection of the observed vector of correlations onto the vector of most interesting associations. Statistical significance is determined via permutation. In simulation studies and an example application, PROMISE shows greater statistical power to identify genes with the interesting pattern of associations than classical multivariate procedures, individual endpoint analyses or listing genes that have the pattern of interest and are significant in more than one individual endpoint analysis. Documented R routines are freely available from www.stjuderesearch.org/depts/biostats and will soon be available as a Bioconductor package from www.bioconductor.org.

Multiple-source multiple-harmonic active vibration control of variable section cylindrical structures: A numerical study

NASA Astrophysics Data System (ADS)

Liu, Jinxin; Chen, Xuefeng; Gao, Jiawei; Zhang, Xingwu

2016-12-01

Air vehicles, space vehicles and underwater vehicles, the cabins of which can be viewed as variable section cylindrical structures, have multiple rotational vibration sources (e.g., engines, propellers, compressors and motors), making the spectrum of noise multiple-harmonic. The suppression of such noise has been a focus of interests in the field of active vibration control (AVC). In this paper, a multiple-source multiple-harmonic (MSMH) active vibration suppression algorithm with feed-forward structure is proposed based on reference amplitude rectification and conjugate gradient method (CGM). An AVC simulation scheme called finite element model in-loop simulation (FEMILS) is also proposed for rapid algorithm verification. Numerical studies of AVC are conducted on a variable section cylindrical structure based on the proposed MSMH algorithm and FEMILS scheme. It can be seen from the numerical studies that: (1) the proposed MSMH algorithm can individually suppress each component of the multiple-harmonic noise with an unified and improved convergence rate; (2) the FEMILS scheme is convenient and straightforward for multiple-source simulations with an acceptable loop time. Moreover, the simulations have similar procedure to real-life control and can be easily extended to physical model platform.

Evidence for higher reaction time variability for children with ADHD on a range of cognitive tasks including reward and event rate manipulations

PubMed Central

Epstein, Jeffery N.; Langberg, Joshua M.; Rosen, Paul J.; Graham, Amanda; Narad, Megan E.; Antonini, Tanya N.; Brinkman, William B.; Froehlich, Tanya; Simon, John O.; Altaye, Mekibib

2012-01-01

Objective The purpose of the research study was to examine the manifestation of variability in reaction times (RT) in children with Attention Deficit Hyperactivity Disorder (ADHD) and to examine whether RT variability presented differently across a variety of neuropsychological tasks, was present across the two most common ADHD subtypes, and whether it was affected by reward and event rate (ER) manipulations. Method Children with ADHD-Combined Type (n=51), ADHD-Predominantly Inattentive Type (n=53) and 47 controls completed five neuropsychological tasks (Choice Discrimination Task, Child Attentional Network Task, Go/No-Go task, Stop Signal Task, and N-back task), each allowing trial-by-trial assessment of reaction times. Multiple indicators of RT variability including RT standard deviation, coefficient of variation and ex-Gaussian tau were used. Results Children with ADHD demonstrated greater RT variability than controls across all five tasks as measured by the ex-Gaussian indicator tau. There were minimal differences in RT variability across the ADHD subtypes. Children with ADHD also had poorer task accuracy than controls across all tasks except the Choice Discrimination task. Although ER and reward manipulations did affect children’s RT variability and task accuracy, these manipulations largely did not differentially affect children with ADHD compared to controls. RT variability and task accuracy were highly correlated across tasks. Removing variance attributable to RT variability from task accuracy did not appreciably affect between-group differences in task accuracy. Conclusions High RT variability is a ubiquitous and robust phenomenon in children with ADHD. PMID:21463041

Identification of the need for home visiting nurse: development of a new assessment tool

PubMed Central

Taguchi, Atsuko; Nagata, Satoko; Naruse, Takashi; Kuwahara, Yuki; Yamaguchi, Takuhiro; Murashima, Sachiyo

2014-01-01

Objective To develop a Home Visiting Nursing Service Need Assessment Form (HVNS-NAF) to standardize the decision about the need for home visiting nursing service. Methods The sample consisted of older adults who had received coordinated services by care managers. We defined the need for home visiting nursing service by elderly individuals as the decision of the need by a care manager so that the elderly can continue to live independently. Explanatory variables included demographic factors, medical procedure, severity of illness, and caregiver variables. Multiple logistic regression was carried out after univariate analyses to decide the variables to include and the weight of each variable in the HVNS-NAF. We then calculated the sensitivity and specificity of each cutoff value, and defined the score with the highest sensitivity and specificity as the cutoff value. Results Nineteen items were included in the final HVNS-NAF. When the cutoff value was 2 points, the sensitivity was 77.0%, specificity 68.5%, and positive predictive value 56.8%. Conclusions HVNS-NAF is the first validated standard based on characteristics of elderly clients who required home visiting nursing service. Using the HVNS-NAF may result in reducing the unmet need for home visiting nursing service and preventing hospitalization. PMID:24665229

Variable Stars in M13. II.The Red Variables and the Globular Cluster Period-Luminosity Relation

NASA Astrophysics Data System (ADS)

Osborn, W.; Layden, A.; Kopacki, G.; Smith, H.; Anderson, M.; Kelly, A.; McBride, K.; Pritzl, B.

2017-06-01

New CCD observations have been combined with archival data to investigate the nature of the red variables in the globular cluster M13. Mean magnitudes, colors and variation ranges on the UBVIC system have been determined for the 17 cataloged red variables. 15 of the stars are irregular or semi-regular variables that lie at the top of the red giant branch in the color-magnitude diagram. Two stars are not, including one with a well-defined period and a light curve shape indicating it is an ellipsoidal or eclipsing variable. All stars redder than (V-IC)0=1.38 mag vary, with the amplitudes being larger with increased stellar luminosity and with bluer filter passband. Searches of the data for periodicities yielded typical variability cycle times ranging from 30 d up to 92 d for the most luminous star. Several stars have evidence of multiple periods. The stars' period-luminosity diagram compared to those from microlensing survey data shows that most M13 red variables are overtone pulsators. Comparison with the diagrams for other globular clusters shows a correlation between red variable luminosity and cluster metallicity.

Learning style and concept acquisition of community college students in introductory biology

NASA Astrophysics Data System (ADS)

Bobick, Sandra Burin

This study investigated the influence of learning style on concept acquisition within a sample of community college students in a general biology course. There are two subproblems within the larger problem: (1) the influence of demographic variables (age, gender, number of college credits, prior exposure to scientific information) on learning style, and (2) the correlations between prior scientific knowledge, learning style and student understanding of the concept of the gene. The sample included all students enrolled in an introductory general biology course during two consecutive semesters at an urban community college. Initial data was gathered during the first week of the semester, at which time students filled in a short questionnaire (age, gender, number of college credits, prior exposure to science information either through reading/visual sources or a prior biology course). Subjects were then given the Inventory of Learning Processes-Revised (ILP-R) which measures general preferences in five learning styles; Deep Learning; Elaborative Learning, Agentic Learning, Methodical Learning and Literal Memorization. Subjects were then given the Gene Conceptual Knowledge pretest: a 15 question objective section and an essay section. Subjects were exposed to specific concepts during lecture and laboratory exercises. At the last lab, students were given the Genetics Conceptual Knowledge Posttest. Pretest/posttest gains were correlated with demographic variables and learning styles were analyzed for significant correlations. Learning styles, as the independent variable in a simultaneous multiple regression, were significant predictors of results on the gene assessment tests, including pretest, posttest and gain. Of the learning styles, Deep Learning accounted for the greatest positive predictive value of pretest essay and pretest objective results. Literal Memorization was a significant negative predictor for posttest essay, essay gain and objective gain. Simultaneous multiple regression indicated that demographic variables were significant positive predictors for Methodical, Deep and Elaborative Learning Styles. Stepwise multiple regression resulted in number of credits, Read Science and gender (female) as significant predictors of learning styles. The findings of this study emphasize the importance of learning styles in conceptual understanding of the gene and the correlation of nonformal exposure to science information with learning style and conceptual understanding.

Validating the absolute reliability of a fat free mass estimate equation in hemodialysis patients using near-infrared spectroscopy.

PubMed

Kono, Kenichi; Nishida, Yusuke; Moriyama, Yoshihumi; Taoka, Masahiro; Sato, Takashi

2015-06-01

The assessment of nutritional states using fat free mass (FFM) measured with near-infrared spectroscopy (NIRS) is clinically useful. This measurement should incorporate the patient's post-dialysis weight ("dry weight"), in order to exclude the effects of any change in water mass. We therefore used NIRS to investigate the regression, independent variables, and absolute reliability of FFM in dry weight. The study included 47 outpatients from the hemodialysis unit. Body weight was measured before dialysis, and FFM was measured using NIRS before and after dialysis treatment. Multiple regression analysis was used to estimate the FFM in dry weight as the dependent variable. The measured FFM before dialysis treatment (Mw-FFM), and the difference between measured and dry weight (Mw-Dw) were independent variables. We performed Bland-Altman analysis to detect errors between the statistically estimated FFM and the measured FFM after dialysis treatment. The multiple regression equation to estimate the FFM in dry weight was: Dw-FFM = 0.038 + (0.984 × Mw-FFM) + (-0.571 × [Mw-Dw]); R(2)  = 0.99). There was no systematic bias between the estimated and the measured values of FFM in dry weight. Using NIRS, FFM in dry weight can be calculated by an equation including FFM in measured weight and the difference between the measured weight and the dry weight. © 2015 The Authors. Therapeutic Apheresis and Dialysis © 2015 International Society for Apheresis.

Determinants of child maltreatment in Nepal: Results from the 2014 Nepal multiple indicator cluster survey (the 2014 NMICS).

PubMed

Atteraya, Madhu Sudhan; Ebrahim, Nasser B; Gnawali, Shreejana

2018-02-01

We examined the prevalence of child maltreatment as measured by the level of physical (moderate to severe) and emotional abuse and child labor, and the associated household level determinants of child maltreatment in Nepal. We used a nationally representative data set from the fifth round of the Nepal Multiple Indicator Cluster Survey (the 2014 NMICS). The main independent variables were household level characteristics. Dependent variables included child experience of moderate to severe physical abuse, emotional abuse, and child labor (domestic work and economic activities). Bivariate analyses and logistic regressions were used to examine the associations between independent and dependent variables. The results showed that nearly half of the children (49.8%) had experienced moderate physical abuse, 21.5% experienced severe physical abuse, and 77.3% experienced emotional abuse. About 27% of the children had engaged in domestic work and 46.7% in various economic activities. At bivariate level, educational level of household's head and household wealth status had shown significant statistical association with child maltreatment (p<0.001). Results from multivariate logistic regressions showed that higher education levels and higher household wealth status protected children from moderate to severe physical abuse, emotional abuse and child labor. In general, child maltreatment is a neglected social issue in Nepal and the high rates of child maltreatment calls for mass awareness programs focusing on parents, and involving all stakeholders including governments, local, and international organizations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evaluating the Use of Existing Data Sources, Probabilistic Linkage, and Multiple Imputation to Build Population-based Injury Databases Across Phases of Trauma Care

PubMed Central

Newgard, Craig; Malveau, Susan; Staudenmayer, Kristan; Wang, N. Ewen; Hsia, Renee Y.; Mann, N. Clay; Holmes, James F.; Kuppermann, Nathan; Haukoos, Jason S.; Bulger, Eileen M.; Dai, Mengtao; Cook, Lawrence J.

2012-01-01

Objectives The objective was to evaluate the process of using existing data sources, probabilistic linkage, and multiple imputation to create large population-based injury databases matched to outcomes. Methods This was a retrospective cohort study of injured children and adults transported by 94 emergency medical systems (EMS) agencies to 122 hospitals in seven regions of the western United States over a 36-month period (2006 to 2008). All injured patients evaluated by EMS personnel within specific geographic catchment areas were included, regardless of field disposition or outcome. The authors performed probabilistic linkage of EMS records to four hospital and postdischarge data sources (emergency department [ED] data, patient discharge data, trauma registries, and vital statistics files) and then handled missing values using multiple imputation. The authors compare and evaluate matched records, match rates (proportion of matches among eligible patients), and injury outcomes within and across sites. Results There were 381,719 injured patients evaluated by EMS personnel in the seven regions. Among transported patients, match rates ranged from 14.9% to 87.5% and were directly affected by the availability of hospital data sources and proportion of missing values for key linkage variables. For vital statistics records (1-year mortality), estimated match rates ranged from 88.0% to 98.7%. Use of multiple imputation (compared to complete case analysis) reduced bias for injury outcomes, although sample size, percentage missing, type of variable, and combined-site versus single-site imputation models all affected the resulting estimates and variance. Conclusions This project demonstrates the feasibility and describes the process of constructing population-based injury databases across multiple phases of care using existing data sources and commonly available analytic methods. Attention to key linkage variables and decisions for handling missing values can be used to increase match rates between data sources, minimize bias, and preserve sampling design. PMID:22506952

Relative efficiency of joint-model and full-conditional-specification multiple imputation when conditional models are compatible: The general location model.

PubMed

Seaman, Shaun R; Hughes, Rachael A

2018-06-01

Estimating the parameters of a regression model of interest is complicated by missing data on the variables in that model. Multiple imputation is commonly used to handle these missing data. Joint model multiple imputation and full-conditional specification multiple imputation are known to yield imputed data with the same asymptotic distribution when the conditional models of full-conditional specification are compatible with that joint model. We show that this asymptotic equivalence of imputation distributions does not imply that joint model multiple imputation and full-conditional specification multiple imputation will also yield asymptotically equally efficient inference about the parameters of the model of interest, nor that they will be equally robust to misspecification of the joint model. When the conditional models used by full-conditional specification multiple imputation are linear, logistic and multinomial regressions, these are compatible with a restricted general location joint model. We show that multiple imputation using the restricted general location joint model can be substantially more asymptotically efficient than full-conditional specification multiple imputation, but this typically requires very strong associations between variables. When associations are weaker, the efficiency gain is small. Moreover, full-conditional specification multiple imputation is shown to be potentially much more robust than joint model multiple imputation using the restricted general location model to mispecification of that model when there is substantial missingness in the outcome variable.

Climatic and Landscape Influences on Fire Regimes from 1984 to 2010 in the Western United States

PubMed Central

Liu, Zhihua; Wimberly, Michael C.

2015-01-01

An improved understanding of the relative influences of climatic and landscape controls on multiple fire regime components is needed to enhance our understanding of modern fire regimes and how they will respond to future environmental change. To address this need, we analyzed the spatio-temporal patterns of fire occurrence, size, and severity of large fires (> 405 ha) in the western United States from 1984–2010. We assessed the associations of these fire regime components with environmental variables, including short-term climate anomalies, vegetation type, topography, and human influences, using boosted regression tree analysis. Results showed that large fire occurrence, size, and severity each exhibited distinctive spatial and spatio-temporal patterns, which were controlled by different sets of climate and landscape factors. Antecedent climate anomalies had the strongest influences on fire occurrence, resulting in the highest spatial synchrony. In contrast, climatic variability had weaker influences on fire size and severity and vegetation types were the most important environmental determinants of these fire regime components. Topography had moderately strong effects on both fire occurrence and severity, and human influence variables were most strongly associated with fire size. These results suggest a potential for the emergence of novel fire regimes due to the responses of fire regime components to multiple drivers at different spatial and temporal scales. Next-generation approaches for projecting future fire regimes should incorporate indirect climate effects on vegetation type changes as well as other landscape effects on multiple components of fire regimes. PMID:26465959

[Comparison of three methods for measuring multiple morbidity according to the use of health resources in primary healthcare].

PubMed

Sicras-Mainar, Antoni; Velasco-Velasco, Soledad; Navarro-Artieda, Ruth; Blanca Tamayo, Milagrosa; Aguado Jodar, Alba; Ruíz Torrejón, Amador; Prados-Torres, Alexandra; Violan-Fors, Concepción

2012-06-01

To compare three methods of measuring multiple morbidity according to the use of health resources (cost of care) in primary healthcare (PHC). Retrospective study using computerized medical records. Thirteen PHC teams in Catalonia (Spain). Assigned patients requiring care in 2008. The socio-demographic variables were co-morbidity and costs. Methods of comparison were: a) Combined Comorbidity Index (CCI): an index itself was developed from the scores of acute and chronic episodes, b) Charlson Index (ChI), and c) Adjusted Clinical Groups case-mix: resource use bands (RUB). The cost model was constructed by differentiating between fixed (operational) and variable costs. 3 multiple lineal regression models were developed to assess the explanatory power of each measurement of co-morbidity which were compared from the determination coefficient (R(2)), p< .05. The study included 227,235 patients. The mean unit of cost was €654.2. The CCI explained an R(2)=50.4%, the ChI an R(2)=29.2% and BUR an R(2)=39.7% of the variability of the cost. The behaviour of the ICC is acceptable, albeit with low scores (1 to 3 points), showing inconclusive results. The CCI may be a simple method of predicting PHC costs in routine clinical practice. If confirmed, these results will allow improvements in the comparison of the case-mix. Copyright © 2011 Elsevier España, S.L. All rights reserved.

Multi-scale models of grassland passerine abundance in a fragmented system in Wisconsin

USGS Publications Warehouse

Renfrew, R.B.; Ribic, C.A.

2008-01-01

Fragmentation of grasslands has been implicated in grassland bird population declines. Multi-scale models are being increasingly used to assess potential factors that influence grassland bird presence, abundance, and productivity. However, studies rarely assess fragmentation metrics, and seldom evaluate more than two scales or interactions among scales. We evaluated the relative importance of characteristics at multiple scales to patterns in relative abundance of Savannah Sparrow (Passerculus sandwichensis), Grasshopper Sparrow (Ammodramus savannarum), Eastern Meadowlark (Sturnella magna), and Bobolink (Dolichonyx oryzivorus). We surveyed birds in 74 southwestern Wisconsin pastures from 1997 to 1999 and compared models with explanatory variables from multiple scales: within-patch vegetation structure (microhabitat), patch (macrohabitat), and three landscape extents. We also examined interactions between macrohabitat and landscape factors. Core area of pastures was an important predictor of relative abundance, and composition of the landscape was more important than configuration. Relative abundance was frequently higher in pastures with more core area and in landscapes with more grassland and less wooded area. The direction and strength of the effect of core pasture size on relative abundance changed depending on amount of wooded area in the landscape. Relative abundance of grassland birds was associated with landscape variables more frequently at the 1200-m scale than at smaller scales. To develop better predictive models, parameters at multiple scales and their interactive effects should be included, and results should be evaluated in the context of microhabitat variability, landscape composition, and fragmentation in the study area. ?? 2007 Springer Science+Business Media B.V.

Turning challenges into design principles: Telemonitoring systems for patients with multiple chronic conditions.

PubMed

Sultan, Mehwish; Kuluski, Kerry; McIsaac, Warren J; Cafazzo, Joseph A; Seto, Emily

2018-01-01

People with multiple chronic conditions often struggle with managing their health. The purpose of this research was to identify specific challenges of patients with multiple chronic conditions and to use the findings to form design principles for a telemonitoring system tailored for these patients. Semi-structured interviews with 15 patients with multiple chronic conditions and 10 clinicians were conducted to gain an understanding of their needs and preferences for a smartphone-based telemonitoring system. The interviews were analyzed using a conventional content analysis technique, resulting in six themes. Design principles developed from the themes included that the system must be modular to accommodate various combinations of conditions, reinforce a routine, consolidate record keeping, as well as provide actionable feedback to the patients. Designing an application for multiple chronic conditions is complex due to variability in patient conditions, and therefore, design principles developed in this study can help with future innovations aimed to help manage this population.

Human and bovine viruses and bacteria at three Great Lakes beaches: Environmental variable associations and health risk

USGS Publications Warehouse

Corsi, Steven R.; Borchardt, Mark A.; Carvin, Rebecca B.; Burch, Tucker R; Spencer, Susan K.; Lutz, Michelle A.; McDermott, Colleen M.; Busse, Kimberly M.; Kleinheinz, Gregory; Feng, Xiaoping; Zhu, Jun

2016-01-01

Waterborne pathogens were measured at three beaches in Lake Michigan, environmental factors for predicting pathogen concentrations were identified, and the risk of swimmer infection and illness was estimated. Waterborne pathogens were detected in 96% of samples collected at three Lake Michigan beaches in summer, 2010. Samples were quantified for 22 pathogens in four microbial categories (human viruses, bovine viruses, protozoa, and pathogenic bacteria). All beaches had detections of human and bovine viruses and pathogenic bacteria indicating influence of multiple contamination sources at these beaches. Occurrence ranged from 40 to 87% for human viruses, 65–87% for pathogenic bacteria, and 13–35% for bovine viruses. Enterovirus, adenovirus A, Salmonella spp., Campylobacter jejuni, bovine polyomavirus, and bovine rotavirus A were present most frequently. Variables selected in multiple regression models used to explore environmental factors that influence pathogens included wave direction, cloud cover, currents, and water temperature. Quantitative Microbial Risk Assessment was done for C. jejuni, Salmonella spp., and enteroviruses to estimate risk of infection and illness. Median infection risks for one-time swimming events were approximately 3 × 10–5, 7 × 10–9, and 3 × 10–7 for C. jejuni, Salmonella spp., and enteroviruses, respectively. Results highlight the importance of investigating multiple pathogens within multiple categories to avoid underestimating the prevalence and risk of waterborne pathogens.

Quantitative Assessment of Cervical Vertebral Maturation Using Cone Beam Computed Tomography in Korean Girls

PubMed Central

Byun, Bo-Ram; Kim, Yong-Il; Maki, Koutaro; Son, Woo-Sung

2015-01-01

This study was aimed to examine the correlation between skeletal maturation status and parameters from the odontoid process/body of the second vertebra and the bodies of third and fourth cervical vertebrae and simultaneously build multiple regression models to be able to estimate skeletal maturation status in Korean girls. Hand-wrist radiographs and cone beam computed tomography (CBCT) images were obtained from 74 Korean girls (6–18 years of age). CBCT-generated cervical vertebral maturation (CVM) was used to demarcate the odontoid process and the body of the second cervical vertebra, based on the dentocentral synchondrosis. Correlation coefficient analysis and multiple linear regression analysis were used for each parameter of the cervical vertebrae (P < 0.05). Forty-seven of 64 parameters from CBCT-generated CVM (independent variables) exhibited statistically significant correlations (P < 0.05). The multiple regression model with the greatest R 2 had six parameters (PH2/W2, UW2/W2, (OH+AH2)/LW2, UW3/LW3, D3, and H4/W4) as independent variables with a variance inflation factor (VIF) of <2. CBCT-generated CVM was able to include parameters from the second cervical vertebral body and odontoid process, respectively, for the multiple regression models. This suggests that quantitative analysis might be used to estimate skeletal maturation status. PMID:25878721

Caries risk assessment in schoolchildren - a form based on Cariogram® software

PubMed Central

CABRAL, Renata Nunes; HILGERT, Leandro Augusto; FABER, Jorge; LEAL, Soraya Coelho

2014-01-01

Identifying caries risk factors is an important measure which contributes to best understanding of the cariogenic profile of the patient. The Cariogram® software provides this analysis, and protocols simplifying the method were suggested. Objectives The aim of this study was to determine whether a newly developed Caries Risk Assessment (CRA) form based on the Cariogram® software could classify schoolchildren according to their caries risk and to evaluate relationships between caries risk and the variables in the form. Material and Methods 150 schoolchildren aged 5 to 7 years old were included in this survey. Caries prevalence was obtained according to International Caries Detection and Assessment System (ICDAS) II. Information for filling in the form based on Cariogram® was collected clinically and from questionnaires sent to parents. Linear regression and a forward stepwise multiple regression model were applied to correlate the variables included in the form with the caries risk. Results Caries prevalence, in primary dentition, including enamel and dentine carious lesions was 98.6%, and 77.3% when only dentine lesions were considered. Eighty-six percent of the children were classified as at moderate caries risk. The forward stepwise multiple regression model result was significant (R2=0.904; p<0.00001), showing that the most significant factors influencing caries risk were caries experience, oral hygiene, frequency of food consumption, sugar consumption and fluoride sources. Conclusion The use of the form based on the Cariogram® software enabled classification of the schoolchildren at low, moderate and high caries risk. Caries experience, oral hygiene, frequency of food consumption, sugar consumption and fluoride sources are the variables that were shown to be highly correlated with caries risk. PMID:25466473

Twentieth century warming of the tropical Atlantic captured by Sr-U paleothermometry

NASA Astrophysics Data System (ADS)

Alpert, Alice E.; Cohen, Anne L.; Oppo, Delia W.; DeCarlo, Thomas M.; Gaetani, Glenn A.; Hernandez-Delgado, Edwin A.; Winter, Amos; Gonneea, Meagan E.

2017-02-01

Coral skeletons are valuable archives of past ocean conditions. However, interpretation of coral paleotemperature records is confounded by uncertainties associated with single-element ratio thermometers, including Sr/Ca. A new approach, Sr-U, uses U/Ca to constrain the influence of Rayleigh fractionation on Sr/Ca. Here we build on the initial Pacific Porites Sr-U calibration to include multiple Atlantic and Pacific coral genera from multiple coral reef locations spanning a temperature range of 23.15-30.12°C. Accounting for the wintertime growth cessation of one Bermuda coral, we show that Sr-U is strongly correlated with the average water temperature at each location (r2 = 0.91, P < 0.001, n = 19). We applied the multispecies spatial calibration between Sr-U and temperature to reconstruct a 96 year long temperature record at Mona Island, Puerto Rico, using a coral not included in the calibration. Average Sr-U derived temperature for the period 1900-1996 is within 0.12°C of the average instrumental temperature at this site and captures the twentieth century warming trend of 0.06°C per decade. Sr-U also captures the timing of multiyear variability but with higher amplitude than implied by the instrumental data. Mean Sr-U temperatures and patterns of multiyear variability were replicated in a second coral in the same grid box. Conversely, Sr/Ca records from the same two corals were inconsistent with each other and failed to capture absolute sea temperatures, timing of multiyear variability, or the twentieth century warming trend. Our results suggest that coral Sr-U paleothermometry is a promising new tool for reconstruction of past ocean temperatures.

Twentieth century warming of the tropical Atlantic captured by Sr-U paleothermometry

USGS Publications Warehouse

Alpert, Alice E.; Cohen, Anne L.; Oppo, Delia W.; DeCarlo, Thomas M.; Gaetani, Glenn A.; Hernandez-Delgado, Edwin A.; Winter, Amos; Gonneea, Meagan

2017-01-01

Coral skeletons are valuable archives of past ocean conditions. However, interpretation of coral paleotemperature records is confounded by uncertainties associated with single-element ratio thermometers, including Sr/Ca. A new approach, Sr-U, uses U/Ca to constrain the influence of Rayleigh fractionation on Sr/Ca. Here we build on the initial Pacific Porites Sr-U calibration to include multiple Atlantic and Pacific coral genera from multiple coral reef locations spanning a temperature range of 23.15–30.12°C. Accounting for the wintertime growth cessation of one Bermuda coral, we show that Sr-U is strongly correlated with the average water temperature at each location (r2 = 0.91, P < 0.001, n = 19). We applied the multispecies spatial calibration between Sr-U and temperature to reconstruct a 96 year long temperature record at Mona Island, Puerto Rico, using a coral not included in the calibration. Average Sr-U derived temperature for the period 1900–1996 is within 0.12°C of the average instrumental temperature at this site and captures the twentieth century warming trend of 0.06°C per decade. Sr-U also captures the timing of multiyear variability but with higher amplitude than implied by the instrumental data. Mean Sr-U temperatures and patterns of multiyear variability were replicated in a second coral in the same grid box. Conversely, Sr/Ca records from the same two corals were inconsistent with each other and failed to capture absolute sea temperatures, timing of multiyear variability, or the twentieth century warming trend. Our results suggest that coral Sr-U paleothermometry is a promising new tool for reconstruction of past ocean temperatures.

What is the relationship between renal function and visit-to-visit blood pressure variability in primary care? Retrospective cohort study from routinely collected healthcare data.

PubMed

Lasserson, Daniel S; Scherpbier de Haan, Nynke; de Grauw, Wim; van der Wel, Mark; Wetzels, Jack F; O'Callaghan, Christopher A

2016-06-10

To determine the relationship between renal function and visit-to-visit blood pressure (BP) variability in a cohort of primary care patients. Retrospective cohort study from routinely collected healthcare data. Primary care in Nijmegen, the Netherlands, from 2007 to 2012. 19 175 patients who had a measure of renal function, and 7 separate visits with BP readings in the primary care record. Visit-to-visit variability in systolic BP, calculated from the first 7 office measurements, including SD, successive variation, absolute real variation and metrics of variability shown to be independent of mean. Multiple linear regression was used to analyse the influence of estimated glomerular filtration rate (eGFR) on BP variability measures with adjustment for age, sex, diabetes, mean BP, proteinuria, cardiovascular disease, time interval between measures and antihypertensive use. In the patient cohort, 57% were women, mean (SD) age was 65.5 (12.3) years, mean (SD) eGFR was 75.6 (18.0) mL/min/1.73m(2) and SD systolic BP 148.3 (21.4) mm Hg. All BP variability measures were negatively correlated with eGFR and positively correlated with age. However, multiple linear regressions demonstrated consistent, small magnitude negative relationships between eGFR and all measures of BP variability adjusting for confounding variables. Worsening renal function is associated with small increases in measures of visit-to-visit BP variability after adjustment for confounding factors. This is seen across the spectrum of renal function in the population, and provides a mechanism whereby chronic kidney disease may raise the risk of cardiovascular events. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Exploring correlates of diabetes-related stress among adults with Type 1 diabetes in the T1D exchange clinic registry.

PubMed

Boden, Matthew Tyler; Gala, Sasha

2018-04-01

To explore relations between diabetes-related stress and multiple sociodemographic, diabetes health, other health, and treatment-related variables among a large sample of adults with Type 1 Diabetes (T1D). The sample consisted of 10,821 adults (over 18 years old) enrolled in the T1D Exchange Clinic Registry. The T1D Exchange clinic network consists of 67 diabetes clinical centers throughout the United States selected to broadly represent pediatric and adult patients with T1D. Variables were assessed through participant self-report and extraction of clinic chart data. Univariate and multiple linear regression (with simultaneous entry of all predictors) analyses were conducted. Robustly associated with increased diabetes-related stress across analyses were multiple sociodemographic (female [vs. male], native Hawaiian/other Pacific islander [vs. white/Caucasian], decreased age and diabetes duration), diabetes health (higher HbA1c), other health (lower general health, presence of major life stress and depression, less physical activity), and treatment related variables (use of injections/pen or combination injection/pen/pump [vs. pump], use of CGM, increased frequency of missing insulin doses and BG checking, decreased frequency of BG checking prior to bolus, receipt of mental health treatment). We replicated and extended research demonstrating that diabetes-related stress among people with T1D occurs at higher levels among those with particular sociodemographic characteristics and is associated with a range poorer diabetes health and other health variables, and multiple treatment-related variables. The strong incremental prediction of diabetes-related stress by multiple variables in our study suggests that a multi-variable, personalized approach may increase the effectiveness of treatments for diabetes-related stress. Published by Elsevier B.V.

Parental education predicts change in intelligence quotient after childhood epilepsy surgery.

PubMed

Meekes, Joost; van Schooneveld, Monique M J; Braams, Olga B; Jennekens-Schinkel, Aag; van Rijen, Peter C; Hendriks, Marc P H; Braun, Kees P J; van Nieuwenhuizen, Onno

2015-04-01

To know whether change in the intelligence quotient (IQ) of children who undergo epilepsy surgery is associated with the educational level of their parents. Retrospective analysis of data obtained from a cohort of children who underwent epilepsy surgery between January 1996 and September 2010. We performed simple and multiple regression analyses to identify predictors associated with IQ change after surgery. In addition to parental education, six variables previously demonstrated to be associated with IQ change after surgery were included as predictors: age at surgery, duration of epilepsy, etiology, presurgical IQ, reduction of antiepileptic drugs, and seizure freedom. We used delta IQ (IQ 2 years after surgery minus IQ shortly before surgery) as the primary outcome variable, but also performed analyses with pre- and postsurgical IQ as outcome variables to support our findings. To validate the results we performed simple regression analysis with parental education as the predictor in specific subgroups. The sample for regression analysis included 118 children (60 male; median age at surgery 9.73 years). Parental education was significantly associated with delta IQ in simple regression analysis (p = 0.004), and also contributed significantly to postsurgical IQ in multiple regression analysis (p = 0.008). Additional analyses demonstrated that parental education made a unique contribution to prediction of delta IQ, that is, it could not be replaced by the illness-related variables. Subgroup analyses confirmed the association of parental education with IQ change after surgery for most groups. Children whose parents had higher education demonstrate on average a greater increase in IQ after surgery and a higher postsurgical--but not presurgical--IQ than children whose parents completed at most lower secondary education. Parental education--and perhaps other environmental variables--should be considered in the prognosis of cognitive function after childhood epilepsy surgery. Wiley Periodicals, Inc. © 2015 International League Against Epilepsy.

Systematic correlation of environmental exposure and physiological and self-reported behaviour factors with leukocyte telomere length.

PubMed

Patel, Chirag J; Manrai, Arjun K; Corona, Erik; Kohane, Isaac S

2017-02-01

It is hypothesized that environmental exposures and behaviour influence telomere length, an indicator of cellular ageing. We systematically associated 461 indicators of environmental exposures, physiology and self-reported behaviour with telomere length in data from the US National Health and Nutrition Examination Survey (NHANES) in 1999-2002. Further, we tested whether factors identified in the NHANES participants are also correlated with gene expression of telomere length modifying genes. We correlated 461 environmental exposures, behaviours and clinical variables with telomere length, using survey-weighted linear regression, adjusting for sex, age, age squared, race/ethnicity, poverty level, education and born outside the USA, and estimated the false discovery rate to adjust for multiple hypotheses. We conducted a secondary analysis to investigate the correlation between identified environmental variables and gene expression levels of telomere-associated genes in publicly available gene expression samples. After correlating 461 variables with telomere length, we found 22 variables significantly associated with telomere length after adjustment for multiple hypotheses. Of these varaibales, 14 were associated with longer telomeres, including biomarkers of polychlorinated biphenyls([PCBs; 0.1 to 0.2 standard deviation (SD) increase for 1 SD increase in PCB level, P  < 0.002] and a form of vitamin A, retinyl stearate. Eight variables associated with shorter telomeres, including biomarkers of cadmium, C-reactive protein and lack of physical activity. We could not conclude that PCBs are correlated with gene expression of telomere-associated genes. Both environmental exposures and chronic disease-related risk factors may play a role in telomere length. Our secondary analysis found no evidence of association between PCBs/smoking and gene expression of telomere-associated genes. All correlations between exposures, behaviours and clinical factors and changes in telomere length will require further investigation regarding biological influence of exposure. © The Author 2016. Published by Oxford University Press on behalf of the International Epidemiological Association

Inter-Annual and Shorter-Term Variability in Physical and Biological Characteristics Across Barrow Canyon in August - September 2005-2014

NASA Astrophysics Data System (ADS)

Ashjian, C. J.; Okkonen, S. R.; Campbell, R. G.; Alatalo, P.

2014-12-01

Late summer physical and biological conditions along a 37-km transect crossing Barrow Canyon have been described for the past ten years as part of an ongoing program, supported by multiple funding sources including the NSF AON, focusing on inter-annual variability and the formation of a bowhead whale feeding hotspot near Barrow. These repeated transects (at least two per year, separated in time by days-weeks) provide an opportunity to assess the inter-annual and shorter term (days-weeks) changes in hydrographic structure, ocean temperature, current velocity and transport, chlorophyll fluorescence, nutrients, and micro- and mesozooplankton community composition and abundance. Inter-annual variability in all properties was high and was associated with larger scale, meteorological forcing. Shorter-term variability could also be high but was strongly influenced by changes in local wind forcing. The sustained sampling at this location provided critical measures of inter-annual variability that should permit detection of longer-term trends that are associated with ongoing climate change.

Evaluating shrub-associated spatial patterns of soil properties in a shrub-steppe ecosystem using multiple-variable geostatistics

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

Halvorson, J.J.; Smith, J.L.; Bolton, H. Jr.

1995-09-01

Geostatistics are often calculated for a single variable at a time, even though many natural phenomena are functions of several variables. The objective of this work was to demonstrate a nonparametric approach for assessing the spatial characteristics of multiple-variable phenomena. Specifically, we analyzed the spatial characteristics of resource islands in the soil under big sagebrush (Artemisia tridentala Nutt.), a dominant shrub in the intermountain western USA. For our example, we defined resource islands as a function of six soil variables representing concentrations of soil resources, populations of microorganisms, and soil microbial physiological variables. By collectively evaluating the indicator transformations ofmore » these individual variables, we created a new data set, termed a multiple-variable indicator transform or MVIT. Alternate MVITs were obtained by varying the selection criteria. Each MVIT was analyzed with variography to characterize spatial continuity, and with indicator kriging to predict the combined probability of their occurrence at unsampled locations in the landscape. Simple graphical analysis and variography demonstrated spatial dependence for all individual soil variables. Maps derived from ordinary kriging of MVITs suggested that the combined probabilities for encountering zones of above-median resources were greatest near big sagebrush. 51 refs., 5 figs., 1 tab.« less

Mean Comparison: Manifest Variable versus Latent Variable

ERIC Educational Resources Information Center

Yuan, Ke-Hai; Bentler, Peter M.

2006-01-01

An extension of multiple correspondence analysis is proposed that takes into account cluster-level heterogeneity in respondents' preferences/choices. The method involves combining multiple correspondence analysis and k-means in a unified framework. The former is used for uncovering a low-dimensional space of multivariate categorical variables…

Categorical Variables in Multiple Regression: Some Cautions.

ERIC Educational Resources Information Center

O'Grady, Kevin E.; Medoff, Deborah R.

1988-01-01

Limitations of dummy coding and nonsense coding as methods of coding categorical variables for use as predictors in multiple regression analysis are discussed. The combination of these approaches often yields estimates and tests of significance that are not intended by researchers for inclusion in their models. (SLD)

Novel associations between contaminant body burdens and biomarkers of reproductive condition in male Common Carp along multiple gradients of contaminant exposure in Lake Mead National Recreation Area, USA

USGS Publications Warehouse

Patino, Reynaldo; VanLandeghem, Matthew M.; Goodbred, Steven L.; Orsak, Erik; Jenkins, Jill A.; Echols, Kathy R.; Rosen, Michael R.; Torres, Leticia

2015-01-01

Adult male Common Carp were sampled in 2007/08 over a full reproductive cycle at Lake Mead National Recreation Area. Sites sampled included a stream dominated by treated wastewater effluent, a lake basin receiving the streamflow, an upstream lake basin (reference), and a site below Hoover Dam. Individual body burdens for 252 contaminants were measured, and biological variables assessed included physiological [plasma vitellogenin (VTG), estradiol-17β (E2), 11-ketotestosterone (11KT)] and organ [gonadosomatic index (GSI)] endpoints. Patterns in contaminant composition and biological condition were determined by Principal Component Analysis, and their associations modeled by Principal Component Regression. Three spatially distinct but temporally stable gradients of contaminant distribution were recognized: a contaminant mixture typical of wastewaters (PBDEs, methyl triclosan, galaxolide), PCBs, and DDTs. Two spatiotemporally variable patterns of biological condition were recognized: a primary pattern consisting of reproductive condition variables (11KT, E2, GSI), and a secondary pattern including general condition traits (condition factor, hematocrit, fork length). VTG was low in all fish, indicating low estrogenic activity of water at all sites. Wastewater contaminants associated negatively with GSI, 11KT and E2; PCBs associated negatively with GSI and 11KT; and DDTs associated positively with GSI and 11KT. Regression of GSI on sex steroids revealed a novel, nonlinear association between these variables. Inclusion of sex steroids in the GSI regression on contaminants rendered wastewater contaminants nonsignificant in the model and reduced the influence of PCBs and DDTs. Thus, the influence of contaminants on GSI may have been partially driven by organismal modes-of-action that include changes in sex steroid production. The positive association of DDTs with 11KT and GSI suggests that lifetime, sub-lethal exposures to DDTs have effects on male carp opposite of those reported by studies where exposure concentrations were relatively high. Lastly, this study highlighted advantages of multivariate/multiple regression approaches for exploring associations between complex contaminant mixtures and gradients and reproductive condition in wild fishes.

Novel associations between contaminant body burdens and biomarkers of reproductive condition in male Common Carp along multiple gradients of contaminant exposure in Lake Mead National Recreation Area, USA.

PubMed

Patiño, Reynaldo; VanLandeghem, Matthew M; Goodbred, Steven L; Orsak, Erik; Jenkins, Jill A; Echols, Kathy; Rosen, Michael R; Torres, Leticia

2015-08-01

Adult male Common Carp were sampled in 2007/08 over a full reproductive cycle at Lake Mead National Recreation Area. Sites sampled included a stream dominated by treated wastewater effluent, a lake basin receiving the streamflow, an upstream lake basin (reference), and a site below Hoover Dam. Individual body burdens for 252 contaminants were measured, and biological variables assessed included physiological [plasma vitellogenin (VTG), estradiol-17β (E2), 11-ketotestosterone (11KT)] and organ [gonadosomatic index (GSI)] endpoints. Patterns in contaminant composition and biological condition were determined by Principal Component Analysis, and their associations modeled by Principal Component Regression. Three spatially distinct but temporally stable gradients of contaminant distribution were recognized: a contaminant mixture typical of wastewaters (PBDEs, methyl triclosan, galaxolide), PCBs, and DDTs. Two spatiotemporally variable patterns of biological condition were recognized: a primary pattern consisting of reproductive condition variables (11KT, E2, GSI), and a secondary pattern including general condition traits (condition factor, hematocrit, fork length). VTG was low in all fish, indicating low estrogenic activity of water at all sites. Wastewater contaminants associated negatively with GSI, 11KT and E2; PCBs associated negatively with GSI and 11KT; and DDTs associated positively with GSI and 11KT. Regression of GSI on sex steroids revealed a novel, nonlinear association between these variables. Inclusion of sex steroids in the GSI regression on contaminants rendered wastewater contaminants nonsignificant in the model and reduced the influence of PCBs and DDTs. Thus, the influence of contaminants on GSI may have been partially driven by organismal modes-of-action that include changes in sex steroid production. The positive association of DDTs with 11KT and GSI suggests that lifetime, sub-lethal exposures to DDTs have effects on male carp opposite of those reported by studies where exposure concentrations were relatively high. Lastly, this study highlighted advantages of multivariate/multiple regression approaches for exploring associations between complex contaminant mixtures and gradients and reproductive condition in wild fishes. Published by Elsevier Inc.

The Relationship Between Gratitude and Loneliness: The Potential Benefits of Gratitude for Promoting Social Bonds.

PubMed

Caputo, Andrea

2015-05-01

This paper explores the potential role of gratitude on the reduction of loneliness feelings, even controlling for several variables related to social desirability, well-being (subjective happiness and life satisfaction) and socio-demographic characteristics. Through a web-based survey a convenience sample of 197 participants completed an online questionnaire including these measures. Correlation analyses and four-step hierarchical multiple regression analyses were conducted. The results show a negative correlation between gratitude and loneliness; specifically, gratitude succeeds in accounting for up to almost one-fifth of the total variability of loneliness even controlling for further variables. Being female, not having a stable and consolidated relationship and not participating in the labor force represent some risk factors affecting loneliness which should be taken into account in further research.

The Relationship Between Gratitude and Loneliness: The Potential Benefits of Gratitude for Promoting Social Bonds

PubMed Central

Caputo, Andrea

2015-01-01

This paper explores the potential role of gratitude on the reduction of loneliness feelings, even controlling for several variables related to social desirability, well-being (subjective happiness and life satisfaction) and socio-demographic characteristics. Through a web-based survey a convenience sample of 197 participants completed an online questionnaire including these measures. Correlation analyses and four-step hierarchical multiple regression analyses were conducted. The results show a negative correlation between gratitude and loneliness; specifically, gratitude succeeds in accounting for up to almost one-fifth of the total variability of loneliness even controlling for further variables. Being female, not having a stable and consolidated relationship and not participating in the labor force represent some risk factors affecting loneliness which should be taken into account in further research. PMID:27247660

Travel and the home advantage.

PubMed

Pace, A; Carron, A V

1992-03-01

The purpose of the present study was to examine the relative contributions of various travel related variables to visiting team success in the National Hockey League. A multiple regression design was used with game outcome as the dependent variable. The independent variables of interest included, as main effects and interactions, number of time zones crossed, direction of travel, distance traveled, preparation/adjustment time, time of season, game number on the road trip, and the home stand. Visiting team success was negatively associated with the interaction of number of time zones crossed and increased preparation time between games, and was positively associated with game number on the road. It was concluded that only a small portion of the variance in the home advantage/visitor disadvantage can be explained by travel related factors.

Managing multiple funding streams and agendas to achieve local and global health and research objectives: lessons from the field

PubMed Central

Holmes, Charles B.; Sikazwe, Izukanji; Raelly, Roselyne; Freeman, Bethany; Wambulawae, Inonge; Silwizya, Geoffrey; Topp, Stephanie; Chilengi, Roma; Henostroza, German; Kapambwe, Sharon; Simbeye, Darius; Sibajene, Sheila; Chi, Harmony; Godfrey, Katy; Chi, Benjamin; Moore, Carolyn Bolton

2014-01-01

Multiple funding sources provide research and program implementation organizations a broader base of funding and facilitate synergy, but also entail challenges that include varying stakeholder expectations, unaligned grant cycles, and highly variable reporting requirements. Strong governance and strategic planning are essential to ensure alignment of goals and agendas. Systems to track budgets and outputs as well as procurement and human resources are required. A major goal is to transition leadership and operations to local ownership. This article details successful approaches used by the newly independent non-governmental organization, the Centre for Infectious Disease Research in Zambia (CIDRZ). PMID:24321983

Comparison of multipoint linkage analyses for quantitative traits in the CEPH data: parametric LOD scores, variance components LOD scores, and Bayes factors.

PubMed

Sung, Yun Ju; Di, Yanming; Fu, Audrey Q; Rothstein, Joseph H; Sieh, Weiva; Tong, Liping; Thompson, Elizabeth A; Wijsman, Ellen M

2007-01-01

We performed multipoint linkage analyses with multiple programs and models for several gene expression traits in the Centre d'Etude du Polymorphisme Humain families. All analyses provided consistent results for both peak location and shape. Variance-components (VC) analysis gave wider peaks and Bayes factors gave fewer peaks. Among programs from the MORGAN package, lm_multiple performed better than lm_markers, resulting in less Markov-chain Monte Carlo (MCMC) variability between runs, and the program lm_twoqtl provided higher LOD scores by also including either a polygenic component or an additional quantitative trait locus.

Comparison of multipoint linkage analyses for quantitative traits in the CEPH data: parametric LOD scores, variance components LOD scores, and Bayes factors

PubMed Central

Sung, Yun Ju; Di, Yanming; Fu, Audrey Q; Rothstein, Joseph H; Sieh, Weiva; Tong, Liping; Thompson, Elizabeth A; Wijsman, Ellen M

2007-01-01

We performed multipoint linkage analyses with multiple programs and models for several gene expression traits in the Centre d'Etude du Polymorphisme Humain families. All analyses provided consistent results for both peak location and shape. Variance-components (VC) analysis gave wider peaks and Bayes factors gave fewer peaks. Among programs from the MORGAN package, lm_multiple performed better than lm_markers, resulting in less Markov-chain Monte Carlo (MCMC) variability between runs, and the program lm_twoqtl provided higher LOD scores by also including either a polygenic component or an additional quantitative trait locus. PMID:18466597

Managing multiple funding streams and agendas to achieve local and global health and research objectives: lessons from the field.

PubMed

Holmes, Charles B; Sikazwe, Izukanji; Raelly, Roselyne L; Freeman, Bethany L; Wambulawae, Inonge; Silwizya, Geoffrey; Topp, Stephanie M; Chilengi, Roma; Henostroza, German; Kapambwe, Sharon; Simbeye, Darius; Sibajene, Sheila; Chi, Harmony; Godfrey, Katy; Chi, Benjamin; Moore, Carolyn Bolton

2014-01-01

Multiple funding sources provide research and program implementation organizations a broader base of funding and facilitate synergy, but also entail challenges that include varying stakeholder expectations, unaligned grant cycles, and highly variable reporting requirements. Strong governance and strategic planning are essential to ensure alignment of goals and agendas. Systems to track budgets and outputs, as well as procurement and human resources are required. A major goal of funders is to transition leadership and operations to local ownership. This article details successful approaches used by the newly independent nongovernmental organization, the Centre for Infectious Disease Research in Zambia.

A hybrid approach to estimating national scale spatiotemporal variability of PM2.5 in the contiguous United States.

PubMed

Beckerman, Bernardo S; Jerrett, Michael; Serre, Marc; Martin, Randall V; Lee, Seung-Jae; van Donkelaar, Aaron; Ross, Zev; Su, Jason; Burnett, Richard T

2013-07-02

Airborne fine particulate matter exhibits spatiotemporal variability at multiple scales, which presents challenges to estimating exposures for health effects assessment. Here we created a model to predict ambient particulate matter less than 2.5 μm in aerodynamic diameter (PM2.5) across the contiguous United States to be applied to health effects modeling. We developed a hybrid approach combining a land use regression model (LUR) selected with a machine learning method, and Bayesian Maximum Entropy (BME) interpolation of the LUR space-time residuals. The PM2.5 data set included 104,172 monthly observations at 1464 monitoring locations with approximately 10% of locations reserved for cross-validation. LUR models were based on remote sensing estimates of PM2.5, land use and traffic indicators. Normalized cross-validated R(2) values for LUR were 0.63 and 0.11 with and without remote sensing, respectively, suggesting remote sensing is a strong predictor of ground-level concentrations. In the models including the BME interpolation of the residuals, cross-validated R(2) were 0.79 for both configurations; the model without remotely sensed data described more fine-scale variation than the model including remote sensing. Our results suggest that our modeling framework can predict ground-level concentrations of PM2.5 at multiple scales over the contiguous U.S.

Results of the 2005 AORN salary survey--trends for perioperative nursing.

PubMed

Bacon, Donald

2005-12-01

AORN conducted its annual compensation survey for perioperative nurses in August 2005. A multiple regression model was used to examine how a variety of variables, including job title, education level, certification, experience, and geographic region, affect nursing compensation. This survey also examines the effect of other forms of compensation (eg, on-call compensation, overtime, bonuses, shift differential) on average base compensation rates.

Results of the 2006 AORN salary survey: trends for perioperative nursing.

PubMed

Bacon, Donald

2006-12-01

AORN CONDUCTED ITS ANNUAL compensation survey for perioperative nurses in August 2006. MULTIPLE REGRESSION MODEL was used to examine how a variety of variables, including job title, education level, certification, experience, and geographic region, affect nursing compensation. THIS SURVEY ALSO EXAMINES the effect of other forms of compensation (eg, on-call compensation, overtime, bonuses, shift differential) on average base compensation rates.

Modeling contemporary climate profiles of whitebark pine (Pinus albicaulis) and predicting responses to global warming

Treesearch

Marcus V. Warwell; Gerald E. Rehfeldt; Nicholas L. Crookston

2006-01-01

The Random Forests multiple regression tree was used to develop an empirically-based bioclimate model for the distribution of Pinus albicaulis (whitebark pine) in western North America, latitudes 31° to 51° N and longitudes 102° to 125° W. Independent variables included 35 simple expressions of temperature and precipitation and their interactions....

MURI: Impact of Oceanographic Variability on Acoustic Communications

DTIC Science & Technology

2012-09-30

ACSSC.2010.5757934 (2010). [published] [50] K. Tu, T.M. Duman, J.G. Proakis, and M. Stojanovic, “Cooperative MIMO - OFDM communications: Receiver...considered across bands of frequencies in the range 1-50 kHz. Multiple source and receiver cases ( MIMO ) will be of particular interest. Validating...Parabolic Equation (PE) acoustic models. Communication receiver design has included processors for orthogonal frequency division multiplexing ( OFDM

Load sensing system

DOEpatents

Sohns, Carl W.; Nodine, Robert N.; Wallace, Steven Allen

1999-01-01

A load sensing system inexpensively monitors the weight and temperature of stored nuclear material for long periods of time in widely variable environments. The system can include an electrostatic load cell that encodes weight and temperature into a digital signal which is sent to a remote monitor via a coaxial cable. The same cable is used to supply the load cell with power. When multiple load cells are used, vast

Effect of occupational health nursing practice on musculoskeletal pains among hospital nursing staff in South Korea.

PubMed

Kim, Yeon-Ha; Jung, Moon-Hee

2016-01-01

The purpose of this study was to identify whether occupational health nursing variables serve as the contributing factors to musculoskeletal pains (MSP). A self-administered questionnaire composed of demographic characteristics, the practice of occupational health nursing and information regarding MSP was designed based on in-depth interviews with eight nurses. This study included 226 hospital nursing staff who worked at three university hospitals located in Seoul, South Korea. Statistical analysis was performed by using SPSS and AMOS 19.0. Shoulder and neck pains occurred when subjects worked more than 46 h/week. Subjects who performed 'work-time adjustment' had lesser chance of having shoulder, leg/foot and wrist/finger pains. Overtime work hours showed an indirect effect on multiple sites of MSP by mediator variable, which was 'work-time adjustment'. Organized night duty days eventually decreased multiple sites of MSP. Administration strategies for nurses to adjust work-time within 46 h/week should be considered.

A multiple mediational test of the relationship between childhood maltreatment and non-suicidal self-injury.

PubMed

Shenk, Chad E; Noll, Jennie G; Cassarly, Jennifer A

2010-04-01

Post-traumatic stress symptoms, depressive symptoms, and psychological dysregulation have been shown to mediate the relationship between child maltreatment and non-suicidal self-injury. However, these proposed mediators often co-occur and previous research has not tested mediation when all variables are assessed simultaneously. The current study sought to advance the literature on maltreatment and self-injury by estimating the mediational effects of post-traumatic stress symptoms, depressive symptoms, and psychological dysregulation in the same multiple mediator model. Both maltreated (n = 129) and non-maltreated (n = 82) adolescent females, consisting of Caucasian (55%), African-American (37%), and Bi-racial (8%) backgrounds, participated in the study. Results indicated that only post-traumatic stress symptoms mediated the relationship between maltreatment and self-injury when all variables were included in the model. Overall, post-traumatic symptoms represented a unique pathway from maltreatment to self-injury and warrant special attention when assessing and treating such behavior with adolescent females.

Exploring relations among mindfulness facets and various meditation practices: Do they work in different ways?

PubMed

Cebolla, Ausiàs; Campos, Daniel; Galiana, Laura; Oliver, Amparo; Tomás, Jose Manuel; Feliu-Soler, Albert; Soler, Joaquim; García-Campayo, Javier; Demarzo, Marcelo; Baños, Rosa María

2017-03-01

Several meditation practices are associated with mindfulness-based interventions but little is known about their specific effects on the development of different mindfulness facets. This study aimed to assess the relations among different practice variables, types of meditation, and mindfulness facets. The final sample was composed of 185 participants who completed an on-line survey, including information on the frequency and duration of each meditation practice, lifetime practice, and the Five Facet Mindfulness Questionnaire. A Multiple Indicators Multiple Causes structural model was specified, estimated, and tested. Results showed that the Model's overall fit was adequate: χ 2 (1045)=1542.800 (p<0.001), CFI=0.902, RMSEA=0.042. Results revealed that mindfulness facets were uniquely related to the different variables and types of meditation. Our findings showed the importance of specific practices in promoting mindfulness, compared to compassion and informal practices, and they pointed out which one fits each mindfulness facet better. Copyright © 2017 Elsevier Inc. All rights reserved.

An algorithm of improving speech emotional perception for hearing aid

NASA Astrophysics Data System (ADS)

Xi, Ji; Liang, Ruiyu; Fei, Xianju

2017-07-01

In this paper, a speech emotion recognition (SER) algorithm was proposed to improve the emotional perception of hearing-impaired people. The algorithm utilizes multiple kernel technology to overcome the drawback of SVM: slow training speed. Firstly, in order to improve the adaptive performance of Gaussian Radial Basis Function (RBF), the parameter determining the nonlinear mapping was optimized on the basis of Kernel target alignment. Then, the obtained Kernel Function was used as the basis kernel of Multiple Kernel Learning (MKL) with slack variable that could solve the over-fitting problem. However, the slack variable also brings the error into the result. Therefore, a soft-margin MKL was proposed to balance the margin against the error. Moreover, the relatively iterative algorithm was used to solve the combination coefficients and hyper-plane equations. Experimental results show that the proposed algorithm can acquire an accuracy of 90% for five kinds of emotions including happiness, sadness, anger, fear and neutral. Compared with KPCA+CCA and PIM-FSVM, the proposed algorithm has the highest accuracy.

High frequency, spontaneous motA mutations in Campylobacter jejuni strain 81-176.

PubMed

Mohawk, Krystle L; Poly, Frédéric; Sahl, Jason W; Rasko, David A; Guerry, Patricia

2014-01-01

Campylobacter jejuni is an important cause of bacterial diarrhea worldwide. The pathogenesis of C. jejuni is poorly understood and complicated by phase variation of multiple surface structures including lipooligosaccharide, capsule, and flagellum. When C. jejuni strain 81-176 was plated on blood agar for single colonies, the presence of translucent, non-motile colonial variants was noted among the majority of opaque, motile colonies. High-throughput genomic sequencing of two flagellated translucent and two opaque variants as well as the parent strain revealed multiple genetic changes compared to the published genome. However, the only mutated open reading frame common between the two translucent variants and absent from the opaque variants and the parent was motA, encoding a flagellar motor protein. A total of 18 spontaneous motA mutations were found that mapped to four distinct sites in the gene, with only one class of mutation present in a phase variable region. This study exemplifies the mutative/adaptive properties of C. jejuni and demonstrates additional variability in C. jejuni beyond phase variation.

Surgical Management of Carney Complex-Associated Pituitary Pathology.

PubMed

Lonser, Russell R; Mehta, Gautam U; Kindzelski, Bogdan A; Ray-Chaudhury, Abhik; Vortmeyer, Alexander O; Dickerman, Robert; Oldfield, Edward H

2017-05-01

Carney complex (CNC) is a familial neoplasia syndrome that is associated with pituitary-associated hypersecretion of growth hormone (GH) (acromegaly). The underlying cause of pituitary GH hypersecretion and its management have been incompletely defined. To provide biological insight into CNC-associated pituitary pathology and improve management, we analyzed findings in CNC patients who underwent transsphenoidal surgery. Consecutive CNC patients at the National Institutes of Health with acromegaly and imaging evidence of a pituitary adenoma(s) who underwent transsphenoidal resection of tumor(s) were included. Prospectively acquired magnetic resonance imaging and biochemical, surgical, and histological data were analyzed. Seven acromegalic CNC patients (2 male, 5 female) were included. The mean age at surgery was 29.7 years (range, 18-44 years). The mean follow-up was 4.7 years (range, 0.2-129 months). Magnetic resonance imaging revealed a single pituitary adenoma in 4 patients and multiple pituitary adenomas in 3 patients. Whereas patients with single discrete pituitary adenomas underwent selective adenomectomy, patients with multiple adenomas underwent selective adenomectomy of multiple tumors, as well as partial or total hypophysectomy. All adenomas were either GH and prolactin positive or exclusively prolactin positive. Pituitary tissue surrounding the adenomas in patients with multiple adenomas revealed hyperplastic GH- and prolactin-positive tissue. CNC-associated acromegaly results from variable pituitary pathology, including a single GH-secreting adenoma or multiple GH-secreting adenomas and/or GH hypersecretion of the pituitary gland surrounding multiple adenomas. Although selective adenomectomy is the preferred treatment for cases of GH-secreting adenomas, multiple adenomas with associated pituitary gland GH hypersecretion may require partial or complete hypophysectomy to achieve biochemical remission. Copyright © 2017 by the Congress of Neurological Surgeons

Surgical Management of Carney Complex–Associated Pituitary Pathology

PubMed Central

Mehta, Gautam U.; Kindzelski, Bogdan A.; Ray-Chaudhury, Abhik; Vortmeyer, Alexander O.; Dickerman, Robert; Oldfield, Edward H.

2017-01-01

Abstract BACKGROUND: Carney complex (CNC) is a familial neoplasia syndrome that is associated with pituitary-associated hypersecretion of growth hormone (GH) (acromegaly). The underlying cause of pituitary GH hypersecretion and its management have been incompletely defined. OBJECTIVE: To provide biological insight into CNC-associated pituitary pathology and improve management, we analyzed findings in CNC patients who underwent transsphenoidal surgery. METHODS: Consecutive CNC patients at the National Institutes of Health with acromegaly and imaging evidence of a pituitary adenoma(s) who underwent transsphenoidal resection of tumor(s) were included. Prospectively acquired magnetic resonance imaging and biochemical, surgical, and histological data were analyzed. RESULTS: Seven acromegalic CNC patients (2 male, 5 female) were included. The mean age at surgery was 29.7 years (range, 18-44 years). The mean follow-up was 4.7 years (range, 0.2-129 months). Magnetic resonance imaging revealed a single pituitary adenoma in 4 patients and multiple pituitary adenomas in 3 patients. Whereas patients with single discrete pituitary adenomas underwent selective adenomectomy, patients with multiple adenomas underwent selective adenomectomy of multiple tumors, as well as partial or total hypophysectomy. All adenomas were either GH and prolactin positive or exclusively prolactin positive. Pituitary tissue surrounding the adenomas in patients with multiple adenomas revealed hyperplastic GH- and prolactin-positive tissue. CONCLUSION: CNC-associated acromegaly results from variable pituitary pathology, including a single GH-secreting adenoma or multiple GH-secreting adenomas and/or GH hypersecretion of the pituitary gland surrounding multiple adenomas. Although selective adenomectomy is the preferred treatment for cases of GH-secreting adenomas, multiple adenomas with associated pituitary gland GH hypersecretion may require partial or complete hypophysectomy to achieve biochemical remission. PMID:27509071

Trajectory controllability of semilinear systems with multiple variable delays in control

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

Klamka, Jerzy, E-mail: Jerzy.Klamka@polsl.pl, E-mail: Michal.Niezabitowski@polsl.pl; Niezabitowski, Michał, E-mail: Jerzy.Klamka@polsl.pl, E-mail: Michal.Niezabitowski@polsl.pl

In this paper, finite-dimensional dynamical control system described by semilinear differential state equation with multiple variable delays in control are considered. The concept of controllability we extend on trajectory controllability for systems with multiple point delays in control. Moreover, remarks and comments on the relationships between different concepts of controllability are presented. Finally, simple numerical example, which illustrates theoretical considerations is also given. The possible extensions are also proposed.

Access to Care and Satisfaction Among Health Center Patients With Chronic Conditions.

PubMed

Shi, Leiyu; Lee, De-Chih; Haile, Geraldine Pierre; Liang, Hailun; Chung, Michelle; Sripipatana, Alek

This study examined access to care and satisfaction among health center patients with chronic conditions. Data for this study were obtained from the 2009 Health Center Patient Survey. Dependent variables of interest included 5 measures of access to and satisfaction with care, whereas the main independent variable was number of chronic conditions. Results of bivariate analysis and multiple logistic regressions showed that patients with chronic conditions had significantly higher odds of reporting access barriers than those without chronic conditions. Our results suggested that additional efforts and resources are necessary to address the needs of health center patients with chronic conditions.

F100(3) parallel compressor computer code and user's manual

NASA Technical Reports Server (NTRS)

Mazzawy, R. S.; Fulkerson, D. A.; Haddad, D. E.; Clark, T. A.

1978-01-01

The Pratt & Whitney Aircraft multiple segment parallel compressor model has been modified to include the influence of variable compressor vane geometry on the sensitivity to circumferential flow distortion. Further, performance characteristics of the F100 (3) compression system have been incorporated into the model on a blade row basis. In this modified form, the distortion's circumferential location is referenced relative to the variable vane controlling sensors of the F100 (3) engine so that the proper solution can be obtained regardless of distortion orientation. This feature is particularly important for the analysis of inlet temperature distortion. Compatibility with fixed geometry compressor applications has been maintained in the model.

Channel Access in Erlang

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

Nicklaus, Dennis J.

2013-10-13

We have developed an Erlang language implementation of the Channel Access protocol. Included are low-level functions for encoding and decoding Channel Access protocol network packets as well as higher level functions for monitoring or setting EPICS process variables. This provides access to EPICS process variables for the Fermilab Acnet control system via our Erlang-based front-end architecture without having to interface to C/C++ programs and libraries. Erlang is a functional programming language originally developed for real-time telecommunications applications. Its network programming features and list management functions make it particularly well-suited for the task of managing multiple Channel Access circuits and PVmore » monitors.« less

Effects of Example Variability and Prior Knowledge in How Students Learn to Solve Equations

ERIC Educational Resources Information Center

Guo, Jian-Peng; Yang, Ling-Yan; Ding, Yi

2014-01-01

Researchers have consistently demonstrated that multiple examples are better than one example in facilitating learning because the comparison evoked by multiple examples supports learning and transfer. However, research outcomes are unclear regarding the effects of example variability and prior knowledge on learning from comparing multiple…

"L"-Bivariate and "L"-Multivariate Association Coefficients. Research Report. ETS RR-08-40

ERIC Educational Resources Information Center

Kong, Nan; Lewis, Charles

2008-01-01

Given a system of multiple random variables, a new measure called the "L"-multivariate association coefficient is defined using (conditional) entropy. Unlike traditional correlation measures, the L-multivariate association coefficient measures the multiassociations or multirelations among the multiple variables in the given system; that…

Learning and serial effects on verbal memory in mild cognitive impairment.

PubMed

Campos-Magdaleno, María; Díaz-Bóveda, Rosalía; Juncos-Rabadán, Onésimo; Facal, David; Pereiro, Arturo X

2016-01-01

The objective of this study was to examine different patterns of learning and episodic memory in 3 mild cognitive impairment (MCI) groups and a control group by administering the California Verbal Learning Test (CVLT) and using serial position effect as a principal variable. The study sample included 3 groups of patients with MCI (n = 90) divided into single-domain amnestic, multiple-domain amnestic, and multiple-domain nonamnestic MCI and a group of healthy controls (n = 60). We compared the performance of each group on several CVLT measures used in previous research, and we included a new measure that provides specific information about the serial effect. Data showed a similar pattern of learning and memory impairment in both amnestic MCI groups (i.e., no differences between the multiple-domain and single-domain subtypes); the recency effect was significantly higher in both amnestic MCI groups than in all other groups, and the primacy effect was only lower in the multiple-domain amnestic MCI subtype. Verbal learning and memory profiles of patients with amnestic MCI were very similar, independent of the presence of deficits in cognitive domains other than episodic memory. Results are discussed in light of the unitary-store model of memory.

PROMISE: a tool to identify genomic features with a specific biologically interesting pattern of associations with multiple endpoint variables

PubMed Central

Pounds, Stan; Cheng, Cheng; Cao, Xueyuan; Crews, Kristine R.; Plunkett, William; Gandhi, Varsha; Rubnitz, Jeffrey; Ribeiro, Raul C.; Downing, James R.; Lamba, Jatinder

2009-01-01

Motivation: In some applications, prior biological knowledge can be used to define a specific pattern of association of multiple endpoint variables with a genomic variable that is biologically most interesting. However, to our knowledge, there is no statistical procedure designed to detect specific patterns of association with multiple endpoint variables. Results: Projection onto the most interesting statistical evidence (PROMISE) is proposed as a general procedure to identify genomic variables that exhibit a specific biologically interesting pattern of association with multiple endpoint variables. Biological knowledge of the endpoint variables is used to define a vector that represents the biologically most interesting values for statistics that characterize the associations of the endpoint variables with a genomic variable. A test statistic is defined as the dot-product of the vector of the observed association statistics and the vector of the most interesting values of the association statistics. By definition, this test statistic is proportional to the length of the projection of the observed vector of correlations onto the vector of most interesting associations. Statistical significance is determined via permutation. In simulation studies and an example application, PROMISE shows greater statistical power to identify genes with the interesting pattern of associations than classical multivariate procedures, individual endpoint analyses or listing genes that have the pattern of interest and are significant in more than one individual endpoint analysis. Availability: Documented R routines are freely available from www.stjuderesearch.org/depts/biostats and will soon be available as a Bioconductor package from www.bioconductor.org. Contact: stanley.pounds@stjude.org Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19528086

Reliability of Classifying Multiple Sclerosis Disease Activity Using Magnetic Resonance Imaging in a Multiple Sclerosis Clinic

PubMed Central

Altay, Ebru Erbayat; Fisher, Elizabeth; Jones, Stephen E.; Hara-Cleaver, Claire; Lee, Jar-Chi; Rudick, Richard A.

2013-01-01

Objective To assess the reliability of new magnetic resonance imaging (MRI) lesion counts by clinicians in a multiple sclerosis specialty clinic. Design An observational study. Setting A multiple sclerosis specialty clinic. Patients Eighty-five patients with multiple sclerosis participating in a National Institutes of Health–supported longitudinal study were included. Intervention Each patient had a brain MRI scan at entry and 6 months later using a standardized protocol. Main Outcome Measures The number of new T2 lesions, newly enlarging T2 lesions, and gadolinium-enhancing lesions were measured on the 6-month MRI using a computer-based image analysis program for the original study. For this study, images were reanalyzed by an expert neuroradiologist and 3 clinician raters. The neuroradiologist evaluated the original image pairs; the clinicians evaluated image pairs that were modified to simulate clinical practice. New lesion counts were compared across raters, as was classification of patients as MRI active or inactive. Results Agreement on lesion counts was highest for gadolinium-enhancing lesions, intermediate for new T2 lesions, and poor for enlarging T2 lesions. In 18% to 25% of the cases, MRI activity was classified differently by the clinician raters compared with the neuroradiologist or computer program. Variability among the clinical raters for estimates of new T2 lesions was affected most strongly by the image modifications that simulated low image quality and different head position. Conclusions Between-rater variability in new T2 lesion counts may be reduced by improved standardization of image acquisitions, but this approach may not be practical in most clinical environments. Ultimately, more reliable, robust, and accessible image analysis methods are needed for accurate multiple sclerosis disease-modifying drug monitoring and decision making in the routine clinic setting. PMID:23599930

Recurrent transient ischaemic attack and early risk of stroke: data from the PROMAPA study.

PubMed

Purroy, Francisco; Jiménez Caballero, Pedro Enrique; Gorospe, Arantza; Torres, María José; Alvarez-Sabin, José; Santamarina, Estevo; Martínez-Sánchez, Patricia; Cánovas, David; Freijo, María José; Egido, Jose Antonio; Ramírez-Moreno, Jose M; Alonso-Arias, Arantza; Rodríguez-Campello, Ana; Casado, Ignacio; Delgado-Mederos, Raquel; Martí-Fàbregas, Joan; Fuentes, Blanca; Silva, Yolanda; Quesada, Helena; Cardona, Pere; Morales, Ana; de la Ossa, Natalia Pérez; García-Pastor, Antonio; Arenillas, Juan F; Segura, Tomas; Jiménez, Carmen; Masjuán, Jaime

2013-06-01

Many guidelines recommend urgent intervention for patients with two or more transient ischaemic attacks (TIAs) within 7 days (multiple TIAs) to reduce the early risk of stroke. To determine whether all patients with multiple TIAs have the same high early risk of stroke. Between April 2008 and December 2009, we included 1255 consecutive patients with a TIA from 30 Spanish stroke centres (PROMAPA study). We prospectively recorded clinical characteristics. We also determined the short-term risk of stroke (at 7 and 90 days). Aetiology was categorised using the TOAST (Trial of Org 10172 in Acute Stroke Treatment) classification. Clinical variables and extracranial vascular imaging were available and assessed in 1137/1255 (90.6%) patients. 7-Day and 90-day stroke risk were 2.6% and 3.8%, respectively. Large-artery atherosclerosis (LAA) was confirmed in 190 (16.7%) patients. Multiple TIAs were seen in 274 (24.1%) patients. Duration <1 h (OR=2.97, 95% CI 2.20 to 4.01, p<0.001), LAA (OR=1.92, 95% CI 1.35 to 2.72, p<0.001) and motor weakness (OR=1.37, 95% CI 1.03 to 1.81, p=0.031) were independent predictors of multiple TIAs. The subsequent risk of stroke in these patients at 7 and 90 days was significantly higher than the risk after a single TIA (5.9% vs 1.5%, p<0.001 and 6.8% vs 3.0%, respectively). In the logistic regression model, among patients with multiple TIAs, no variables remained as independent predictors of stroke recurrence. According to our results, multiple TIAs within 7 days are associated with a greater subsequent risk of stroke than after a single TIA. Nevertheless, we found no independent predictor of stroke recurrence among these patients.

Factor analysis and multiple regression between topography and precipitation on Jeju Island, Korea

NASA Astrophysics Data System (ADS)

Um, Myoung-Jin; Yun, Hyeseon; Jeong, Chang-Sam; Heo, Jun-Haeng

2011-11-01

SummaryIn this study, new factors that influence precipitation were extracted from geographic variables using factor analysis, which allow for an accurate estimation of orographic precipitation. Correlation analysis was also used to examine the relationship between nine topographic variables from digital elevation models (DEMs) and the precipitation in Jeju Island. In addition, a spatial analysis was performed in order to verify the validity of the regression model. From the results of the correlation analysis, it was found that all of the topographic variables had a positive correlation with the precipitation. The relations between the variables also changed in accordance with a change in the precipitation duration. However, upon examining the correlation matrix, no significant relationship between the latitude and the aspect was found. According to the factor analysis, eight topographic variables (latitude being the exception) were found to have a direct influence on the precipitation. Three factors were then extracted from the eight topographic variables. By directly comparing the multiple regression model with the factors (model 1) to the multiple regression model with the topographic variables (model 3), it was found that model 1 did not violate the limits of statistical significance and multicollinearity. As such, model 1 was considered to be appropriate for estimating the precipitation when taking into account the topography. In the study of model 1, the multiple regression model using factor analysis was found to be the best method for estimating the orographic precipitation on Jeju Island.

Gene-gene-environment interactions between drugs, transporters, receptors, and metabolizing enzymes: Statins, SLCO1B1, and CYP3A4 as an example.

PubMed

Sadee, Wolfgang

2013-09-01

Pharmacogenetic biomarker tests include mostly specific single gene-drug pairs, capable of accounting for a portion of interindividual variability in drug response and toxicity. However, multiple genes are likely to contribute, either acting independently or epistatically, with the CYP2C9-VKORC1-warfarin test panel, an example of a clinically used gene-gene-dug interaction. I discuss here further instances of gene-gene-drug interactions, including a proposed dynamic effect on statin therapy by genetic variants in both a transporter (SLCO1B1) and a metabolizing enzyme (CYP3A4) in liver cells, the main target site where statins block cholesterol synthesis. These examples set a conceptual framework for developing diagnostic panels involving multiple gene-drug combinations. Copyright © 2013 Wiley Periodicals, Inc.

How potentially predictable are midlatitude ocean currents?

PubMed Central

Nonaka, Masami; Sasai, Yoshikazu; Sasaki, Hideharu; Taguchi, Bunmei; Nakamura, Hisashi

2016-01-01

Predictability of atmospheric variability is known to be limited owing to significant uncertainty that arises from intrinsic variability generated independently of external forcing and/or boundary conditions. Observed atmospheric variability is therefore regarded as just a single realization among different dynamical states that could occur. In contrast, subject to wind, thermal and fresh-water forcing at the surface, the ocean circulation has been considered to be rather deterministic under the prescribed atmospheric forcing, and it still remains unknown how uncertain the upper-ocean circulation variability is. This study evaluates how much uncertainty the oceanic interannual variability can potentially have, through multiple simulations with an eddy-resolving ocean general circulation model driven by the observed interannually-varying atmospheric forcing under slightly different conditions. These ensemble “hindcast” experiments have revealed substantial uncertainty due to intrinsic variability in the extratropical ocean circulation that limits potential predictability of its interannual variability, especially along the strong western boundary currents (WBCs) in mid-latitudes, including the Kuroshio and its eastward extention. The intrinsic variability also greatly limits potential predictability of meso-scale oceanic eddy activity. These findings suggest that multi-member ensemble simulations are essential for understanding and predicting variability in the WBCs, which are important for weather and climate variability and marine ecosystems. PMID:26831954

Health-Related Quality of Life Among Central Appalachian Residents in Mountaintop Mining Counties

PubMed Central

Hendryx, Michael

2011-01-01

Objectives. We examined the health-related quality of life of residents in mountaintop mining counties of Appalachia using the 2006 national Behavioral Risk Factor Surveillance System. Methods. Dependent variables included self-rated health; the number of poor physical, poor mental, and activity limitation days (in the past 30 days); and the Healthy Days Index. Independent variables included metropolitan status, primary care physician supply, and Behavioral Risk Factor Surveillance System behavioral and demographic variables. We compared dependent variables across 3 categories: mountaintop mining (yes or no), other coal mining (yes or no), and a referent nonmining group. We used SUDAAN MULTILOG and multiple linear regression models with post hoc least squares means to test mountaintop mining effects after adjusting for covariates. Results. Residents of mountaintop mining counties reported significantly more days of poor physical, mental, and activity limitation and poorer self-rated health (P < .01) compared with the other county groupings. Results were generally consistent in separate analyses by gender and age. Conclusions. Mountaintop mining areas are associated with the greatest reductions in health-related quality of life even when compared with counties with other forms of coal mining. PMID:21421943

Multi-epoch BVRI Photometry of Luminous Stars in M31 and M33

NASA Astrophysics Data System (ADS)

Martin, John C.; Humphreys, Roberta M.

2017-09-01

We present the first four years of BVRI photometry from an on-going survey to annually monitor the photometric behavior of evolved luminous stars in M31 and M33. Photometry was measured for 199 stars at multiple epochs, including 9 classic Luminous Blue Variables (LBVs), 22 LBV candidates, 10 post-RGB A/F type hypergiants, and 18 B[e] supergiants. At all epochs, the brightness is measured in the V-band and at least one other band to a precision of 0.04-0.10 mag down to a limiting magnitude of 19.0-19.5. Thirty three stars in our survey exhibit significant variability, including at least two classic LBVs caught in S Doradus-type outbursts. A hyperlinked version of the photometry catalog is at http://go.uis.edu/m31m33photcat.

Advanced Multiple In-Multiple Out (MIMO) Antenna Communications for Airborne Networks

DTIC Science & Technology

2015-03-01

are airborne and both employ multiple antennas. On the other hand, the conventionally studied MIMO wireless communication is based on the premise that...architecture as the central idea, upon which our proposed solutions are based . Hence, to facilitate experiments, we also de- velop a GNU Radio/USRP based D...decoder. 2.2 Variable Rate MIMO In this part of the report we develop a variable rate MIMO scheme, based on D-BLAST transceiver architecture, to

Model assessment using a multi-metric ranking technique

NASA Astrophysics Data System (ADS)

Fitzpatrick, P. J.; Lau, Y.; Alaka, G.; Marks, F.

2017-12-01

Validation comparisons of multiple models presents challenges when skill levels are similar, especially in regimes dominated by the climatological mean. Assessing skill separation will require advanced validation metrics and identifying adeptness in extreme events, but maintain simplicity for management decisions. Flexibility for operations is also an asset. This work postulates a weighted tally and consolidation technique which ranks results by multiple types of metrics. Variables include absolute error, bias, acceptable absolute error percentages, outlier metrics, model efficiency, Pearson correlation, Kendall's Tau, reliability Index, multiplicative gross error, and root mean squared differences. Other metrics, such as root mean square difference and rank correlation were also explored, but removed when the information was discovered to be generally duplicative to other metrics. While equal weights are applied, weights could be altered depending for preferred metrics. Two examples are shown comparing ocean models' currents and tropical cyclone products, including experimental products. The importance of using magnitude and direction for tropical cyclone track forecasts instead of distance, along-track, and cross-track are discussed. Tropical cyclone intensity and structure prediction are also assessed. Vector correlations are not included in the ranking process, but found useful in an independent context, and will be briefly reported.

Variability in postural control with and without balance-based torso- weighting in people with multiple sclerosis and healthy controls.

PubMed

Hunt, Charlotte M; Widener, Gail; Allen, Diane D

2014-10-01

People with multiple sclerosis (MS) have diminished postural control, and center of pressure (COP) displacement varies more in this population than in healthy controls. Balance-based torso-weighting (BBTW) can improve clinical balance and mobility in people with MS, and exploration using both linear and nonlinear measures of COP may help determine whether BBTW optimizes movement variability. The aim of this study was to investigate the effects of BBTW on people with MS and healthy controls during quiet standing. This was a quasi-experimental study comparing COP variability between groups, between eye closure conditions, and between weighting conditions in the anterior-posterior and medial-lateral directions. Twenty participants with MS and 18 healthy controls stood on a forceplate in 4 conditions: eyes open and closed and with and without BBTW. Linear measures of COP displacement included range and root mean square (RMS). Nonlinear measures included approximate entropy (ApEn) and Lyapunov exponent (LyE). Three-way repeated-measures analyses of variance compared measures across groups and conditions. The association between weighting response and baseline nonlinear variables was examined. When significant associations were found, MS subgroups were created and compared. The MS and control groups had significantly different range, RMS, and ApEn values. The eyes-open and eyes-closed conditions had significantly different range and RMS values. Change with weighting correlated with LyE (r=-.70) and ApEn (r=-.59). Two MS subgroups, with low and high baseline LyE values, responded to BBTW in opposite directions, with a significant main effect for weighting condition for the LyE variable in the medial-lateral direction. The small samples and no identification of impairments related to LyE at baseline were limitations of the study. The LyE may help differentiate subgroups who respond differently to BBTW. In both subgroups, LyE values moved toward the average of healthy controls, suggesting that BBTW may help optimize movement variability in people with MS. © 2014 American Physical Therapy Association.

Variability in Postural Control With and Without Balance-Based Torso- Weighting in People With Multiple Sclerosis and Healthy Controls

PubMed Central

Widener, Gail; Allen, Diane D.

2014-01-01

Background People with multiple sclerosis (MS) have diminished postural control, and center of pressure (COP) displacement varies more in this population than in healthy controls. Balance-based torso-weighting (BBTW) can improve clinical balance and mobility in people with MS, and exploration using both linear and nonlinear measures of COP may help determine whether BBTW optimizes movement variability. Objective The aim of this study was to investigate the effects of BBTW on people with MS and healthy controls during quiet standing. Design This was a quasi-experimental study comparing COP variability between groups, between eye closure conditions, and between weighting conditions in the anterior-posterior and medial-lateral directions. Methods Twenty participants with MS and 18 healthy controls stood on a forceplate in 4 conditions: eyes open and closed and with and without BBTW. Linear measures of COP displacement included range and root mean square (RMS). Nonlinear measures included approximate entropy (ApEn) and Lyapunov exponent (LyE). Three-way repeated-measures analyses of variance compared measures across groups and conditions. The association between weighting response and baseline nonlinear variables was examined. When significant associations were found, MS subgroups were created and compared. Results The MS and control groups had significantly different range, RMS, and ApEn values. The eyes-open and eyes-closed conditions had significantly different range and RMS values. Change with weighting correlated with LyE (r=−.70) and ApEn (r=−.59). Two MS subgroups, with low and high baseline LyE values, responded to BBTW in opposite directions, with a significant main effect for weighting condition for the LyE variable in the medial-lateral direction. Limitations The small samples and no identification of impairments related to LyE at baseline were limitations of the study. Conclusions The LyE may help differentiate subgroups who respond differently to BBTW. In both subgroups, LyE values moved toward the average of healthy controls, suggesting that BBTW may help optimize movement variability in people with MS. PMID:24903118

Use of principal-component, correlation, and stepwise multiple-regression analyses to investigate selected physical and hydraulic properties of carbonate-rock aquifers

USGS Publications Warehouse

Brown, C. Erwin

1993-01-01

Correlation analysis in conjunction with principal-component and multiple-regression analyses were applied to laboratory chemical and petrographic data to assess the usefulness of these techniques in evaluating selected physical and hydraulic properties of carbonate-rock aquifers in central Pennsylvania. Correlation and principal-component analyses were used to establish relations and associations among variables, to determine dimensions of property variation of samples, and to filter the variables containing similar information. Principal-component and correlation analyses showed that porosity is related to other measured variables and that permeability is most related to porosity and grain size. Four principal components are found to be significant in explaining the variance of data. Stepwise multiple-regression analysis was used to see how well the measured variables could predict porosity and (or) permeability for this suite of rocks. The variation in permeability and porosity is not totally predicted by the other variables, but the regression is significant at the 5% significance level. ?? 1993.

Kinematic foot types in youth with equinovarus secondary to hemiplegia.

PubMed

Krzak, Joseph J; Corcos, Daniel M; Damiano, Diane L; Graf, Adam; Hedeker, Donald; Smith, Peter A; Harris, Gerald F

2015-02-01

Elevated kinematic variability of the foot and ankle segments exists during gait among individuals with equinovarus secondary to hemiplegic cerebral palsy (CP). Clinicians have previously addressed such variability by developing classification schemes to identify subgroups of individuals based on their kinematics. To identify kinematic subgroups among youth with equinovarus secondary to CP using 3-dimensional multi-segment foot and ankle kinematics during locomotion as inputs for principal component analysis (PCA), and K-means cluster analysis. In a single assessment session, multi-segment foot and ankle kinematics using the Milwaukee Foot Model (MFM) were collected in 24 children/adolescents with equinovarus and 20 typically developing children/adolescents. PCA was used as a data reduction technique on 40 variables. K-means cluster analysis was performed on the first six principal components (PCs) which accounted for 92% of the variance of the dataset. The PCs described the location and plane of involvement in the foot and ankle. Five distinct kinematic subgroups were identified using K-means clustering. Participants with equinovarus presented with variable involvement ranging from primary hindfoot or forefoot deviations to deformtiy that included both segments in multiple planes. This study provides further evidence of the variability in foot characteristics associated with equinovarus secondary to hemiplegic CP. These findings would not have been detected using a single segment foot model. The identification of multiple kinematic subgroups with unique foot and ankle characteristics has the potential to improve treatment since similar patients within a subgroup are likely to benefit from the same intervention(s). Copyright © 2014 Elsevier B.V. All rights reserved.

Clustering of metabolic and cardiovascular risk factors in the polycystic ovary syndrome: a principal component analysis.

PubMed

Stuckey, Bronwyn G A; Opie, Nicole; Cussons, Andrea J; Watts, Gerald F; Burke, Valerie

2014-08-01

Polycystic ovary syndrome (PCOS) is a prevalent condition with heterogeneity of clinical features and cardiovascular risk factors that implies multiple aetiological factors and possible outcomes. To reduce a set of correlated variables to a smaller number of uncorrelated and interpretable factors that may delineate subgroups within PCOS or suggest pathogenetic mechanisms. We used principal component analysis (PCA) to examine the endocrine and cardiometabolic variables associated with PCOS defined by the National Institutes of Health (NIH) criteria. Data were retrieved from the database of a single clinical endocrinologist. We included women with PCOS (N = 378) who were not taking the oral contraceptive pill or other sex hormones, lipid lowering medication, metformin or other medication that could influence the variables of interest. PCA was performed retaining those factors with eigenvalues of at least 1.0. Varimax rotation was used to produce interpretable factors. We identified three principal components. In component 1, the dominant variables were homeostatic model assessment (HOMA) index, body mass index (BMI), high density lipoprotein (HDL) cholesterol and sex hormone binding globulin (SHBG); in component 2, systolic blood pressure, low density lipoprotein (LDL) cholesterol and triglycerides; in component 3, total testosterone and LH/FSH ratio. These components explained 37%, 13% and 11% of the variance in the PCOS cohort respectively. Multiple correlated variables from patients with PCOS can be reduced to three uncorrelated components characterised by insulin resistance, dyslipidaemia/hypertension or hyperandrogenaemia. Clustering of risk factors is consistent with different pathogenetic pathways within PCOS and/or differing cardiometabolic outcomes. Copyright © 2014 Elsevier Inc. All rights reserved.

Use of allele scores as instrumental variables for Mendelian randomization

PubMed Central

Burgess, Stephen; Thompson, Simon G

2013-01-01

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

Kinematic foot types in youth with equinovarus secondary to hemiplegia

PubMed Central

Krzak, Joseph J.; Corcos, Daniel M.; Damiano, Diane L.; Graf, Adam; Hedeker, Donald; Smith, Peter A.; Harris, Gerald F.

2015-01-01

Background Elevated kinematic variability of the foot and ankle segments exists during gait among individuals with equinovarus secondary to hemiplegic cerebral palsy (CP). Clinicians have previously addressed such variability by developing classification schemes to identify subgroups of individuals based on their kinematics. Objective To identify kinematic subgroups among youth with equinovarus secondary to CP using 3-dimensional multi-segment foot and ankle kinematics during locomotion as inputs for principal component analysis (PCA), and K-means cluster analysis. Methods In a single assessment session, multi-segment foot and ankle kinematics using the Milwaukee Foot Model (MFM) were collected in 24 children/adolescents with equinovarus and 20 typically developing children/adolescents. Results PCA was used as a data reduction technique on 40 variables. K-means cluster analysis was performed on the first six principal components (PCs) which accounted for 92% of the variance of the dataset. The PCs described the location and plane of involvement in the foot and ankle. Five distinct kinematic subgroups were identified using K-means clustering. Participants with equinovarus presented with variable involvement ranging from primary hindfoot or forefoot deviations to deformtiy that included both segments in multiple planes. Conclusion This study provides further evidence of the variability in foot characteristics associated with equinovarus secondary to hemiplegic CP. These findings would not have been detected using a single segment foot model. The identification of multiple kinematic subgroups with unique foot and ankle characteristics has the potential to improve treatment since similar patients within a subgroup are likely to benefit from the same intervention(s). PMID:25467429

Statistical grand rounds: understanding the mechanism: mediation analysis in randomized and nonrandomized studies.

PubMed

Mascha, Edward J; Dalton, Jarrod E; Kurz, Andrea; Saager, Leif

2013-10-01

In comparative clinical studies, a common goal is to assess whether an exposure, or intervention, affects the outcome of interest. However, just as important is to understand the mechanism(s) for how the intervention affects outcome. For example, if preoperative anemia was shown to increase the risk of postoperative complications by 15%, it would be important to quantify how much of that effect was due to patients receiving intraoperative transfusions. Mediation analysis attempts to quantify how much, if any, of the effect of an intervention on outcome goes though prespecified mediator, or "mechanism" variable(s), that is, variables sitting on the causal pathway between exposure and outcome. Effects of an exposure on outcome can thus be divided into direct and indirect, or mediated, effects. Mediation is claimed when 2 conditions are true: the exposure affects the mediator and the mediator (adjusting for the exposure) affects the outcome. Understanding how an intervention affects outcome can validate or invalidate one's original hypothesis and also facilitate further research to modify the responsible factors, and thus improve patient outcome. We discuss the proper design and analysis of studies investigating mediation, including the importance of distinguishing mediator variables from confounding variables, the challenge of identifying potential mediators when the exposure is chronic versus acute, and the requirements for claiming mediation. Simple designs are considered, as well as those containing multiple mediators, multiple outcomes, and mixed data types. Methods are illustrated with data collected by the National Surgical Quality Improvement Project (NSQIP) and utilized in a companion paper which assessed the effects of preoperative anemic status on postoperative outcomes.

Stride dynamics, gait variability and prospective falls risk in active community dwelling older women.

PubMed

Paterson, Kade; Hill, Keith; Lythgo, Noel

2011-02-01

Measures of walking instability such as stride dynamics and gait variability have been shown to identify future fallers in older adult populations with gait limitations or mobility disorders. This study investigated whether measures of walking instability can predict future fallers (over a prospective 12 month period) in a group of healthy and active older women. Ninety-seven healthy active women aged between 55 and 90 years walked for 7 min around a continuous walking circuit. Gait data recorded by a GAITRite(®) walkway and foot-mounted accelerometers were used to calculate measures of stride dynamics and gait variability. The participant's physical function and balance were assessed. Fall incidence was monitored over the following 12 months. Inter-limb differences (p≤0.04) in stride dynamics were found for fallers (one or more falls) aged over 70 years, and multiple fallers (two or more falls) aged over 55 years, but not in non-fallers or a combined group of single and non-fallers. No group differences were found in the measures of physical function, balance or gait, including variability. Additionally, no gait variable predicted falls. Reduced coordination of inter-limb dynamics was found in active healthy older fallers and multiple fallers despite no difference in other measures of intrinsic falls risk. Evaluating inter-limb dynamics may be a clinically sensitive technique to detect early gait instability and falls risk in high functioning older adults, prior to change in other measures of physical function, balance and gait. Copyright © 2010 Elsevier B.V. All rights reserved.

The Impacts of Communication and Multiple Identifications on Intent to Leave: A Multimethodological Exploration.

ERIC Educational Resources Information Center

Scott, Craig R.; Connaughton, Stacey L.; Diaz-Saenz, Hector R.; Maguire, Katheryn; Ramirez, Ruben; Richardson, Brian; Shaw, Sandra Pride; Morgan, Dianne

1999-01-01

Contributes to scholarship on voluntary turnover by examining the impact of several communication variables and multiple targets of identification on intent to leave. Finds that supervisor/coworker relationships have the strongest association (among communication variables) with intent to leave. Finds a complex relationship between three different…

RAWS II: A MULTIPLE REGRESSION ANALYSIS PROGRAM,

DTIC Science & Technology

This memorandum gives instructions for the use and operation of a revised version of RAWS, a multiple regression analysis program. The program...of preprocessed data, the directed retention of variable, listing of the matrix of the normal equations and its inverse, and the bypassing of the regression analysis to provide the input variable statistics only. (Author)

Multiple indicators, multiple causes measurement error models

DOE PAGES

Tekwe, Carmen D.; Carter, Randy L.; Cullings, Harry M.; ...

2014-06-25

Multiple indicators, multiple causes (MIMIC) models are often employed by researchers studying the effects of an unobservable latent variable on a set of outcomes, when causes of the latent variable are observed. There are times, however, when the causes of the latent variable are not observed because measurements of the causal variable are contaminated by measurement error. The objectives of this study are as follows: (i) to develop a novel model by extending the classical linear MIMIC model to allow both Berkson and classical measurement errors, defining the MIMIC measurement error (MIMIC ME) model; (ii) to develop likelihood-based estimation methodsmore » for the MIMIC ME model; and (iii) to apply the newly defined MIMIC ME model to atomic bomb survivor data to study the impact of dyslipidemia and radiation dose on the physical manifestations of dyslipidemia. Finally, as a by-product of our work, we also obtain a data-driven estimate of the variance of the classical measurement error associated with an estimate of the amount of radiation dose received by atomic bomb survivors at the time of their exposure.« less

Multiple Indicators, Multiple Causes Measurement Error Models

PubMed Central

Tekwe, Carmen D.; Carter, Randy L.; Cullings, Harry M.; Carroll, Raymond J.

2014-01-01

Multiple Indicators, Multiple Causes Models (MIMIC) are often employed by researchers studying the effects of an unobservable latent variable on a set of outcomes, when causes of the latent variable are observed. There are times however when the causes of the latent variable are not observed because measurements of the causal variable are contaminated by measurement error. The objectives of this paper are: (1) to develop a novel model by extending the classical linear MIMIC model to allow both Berkson and classical measurement errors, defining the MIMIC measurement error (MIMIC ME) model, (2) to develop likelihood based estimation methods for the MIMIC ME model, (3) to apply the newly defined MIMIC ME model to atomic bomb survivor data to study the impact of dyslipidemia and radiation dose on the physical manifestations of dyslipidemia. As a by-product of our work, we also obtain a data-driven estimate of the variance of the classical measurement error associated with an estimate of the amount of radiation dose received by atomic bomb survivors at the time of their exposure. PMID:24962535

Multiple indicators, multiple causes measurement error models

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

Tekwe, Carmen D.; Carter, Randy L.; Cullings, Harry M.

Multiple indicators, multiple causes (MIMIC) models are often employed by researchers studying the effects of an unobservable latent variable on a set of outcomes, when causes of the latent variable are observed. There are times, however, when the causes of the latent variable are not observed because measurements of the causal variable are contaminated by measurement error. The objectives of this study are as follows: (i) to develop a novel model by extending the classical linear MIMIC model to allow both Berkson and classical measurement errors, defining the MIMIC measurement error (MIMIC ME) model; (ii) to develop likelihood-based estimation methodsmore » for the MIMIC ME model; and (iii) to apply the newly defined MIMIC ME model to atomic bomb survivor data to study the impact of dyslipidemia and radiation dose on the physical manifestations of dyslipidemia. Finally, as a by-product of our work, we also obtain a data-driven estimate of the variance of the classical measurement error associated with an estimate of the amount of radiation dose received by atomic bomb survivors at the time of their exposure.« less

Multilevel built environment features and individual odds of overweight and obesity in Utah

PubMed Central

Xu, Yanqing; Wen, Ming; Wang, Fahui

2015-01-01

Based on the data from the Behavioral Risk Factor Surveillance System (BRFSS) in 2007, 2009 and 2011 in Utah, this research uses multilevel modeling (MLM) to examine the associations between neighborhood built environments and individual odds of overweight and obesity after controlling for individual risk factors. The BRFSS data include information on 21,961 individuals geocoded to zip code areas. Individual variables include BMI (body mass index) and socio-demographic attributes such as age, gender, race, marital status, education attainment, employment status, and whether an individual smokes. Neighborhood built environment factors measured at both zip code and county levels include street connectivity, walk score, distance to parks, and food environment. Two additional neighborhood variables, namely the poverty rate and urbanicity, are also included as control variables. MLM results show that at the zip code level, poverty rate and distance to parks are significant and negative covariates of the odds of overweight and obesity; and at the county level, food environment is the sole significant factor with stronger fast food presence linked to higher odds of overweight and obesity. These findings suggest that obesity risk factors lie in multiple neighborhood levels and built environment features need to be defined at a neighborhood size relevant to residents' activity space. PMID:26251559

Understanding the Interdependencies Between Composition, Microstructure, and Continuum Variables and Their Influence on the Fracture Toughness of α/β-Processed Ti-6Al-4V

NASA Astrophysics Data System (ADS)

Collins, P. C.; Koduri, S.; Dixit, V.; Fraser, H. L.

2018-03-01

The fracture toughness of a material depends upon the material's composition and microstructure, as well as other material properties operating at the continuum level. The interrelationships between these variables are complex, and thus difficult to interpret, especially in multi-component, multi-phase ductile engineering alloys such as α/β-processed Ti-6Al-4V (nominal composition, wt pct). Neural networks have been used to elucidate how variables such as composition and microstructure influence the fracture toughness directly ( i.e., via a crack initiation or propagation mechanism)—and independent of the influence of the same variables influence on the yield strength and plasticity of the material. The variables included in the models and analysis include (i) alloy composition, specifically, Al, V, O, and Fe; (ii) materials microstructure, including phase fractions and average sizes of key microstructural features; (iii) the yield strength and reduction in area obtained from uniaxial tensile tests; and (iv) an assessment of the degree to which plane strain conditions were satisfied by including a factor related to the plane strain thickness. Once trained, virtual experiments have been conducted which permit the determination of each variable's functional dependency on the resulting fracture toughness. Given that the database includes both K 1 C and K Q values, as well as the in-plane component of the stress state of the crack tip, it is possible to quantitatively assess the effect of sample thickness on K Q and the degree to which the K Q and K 1 C values may vary. These interpretations drawn by comparing multiple neural networks have a significant impact on the general understanding of how the microstructure influences the fracture toughness in ductile materials, as well as an ability to predict the fracture toughness of α/β-processed Ti-6Al-4V.

Case Study Research Methodology in Nursing Research.

PubMed

Cope, Diane G

2015-11-01

Through data collection methods using a holistic approach that focuses on variables in a natural setting, qualitative research methods seek to understand participants' perceptions and interpretations. Common qualitative research methods include ethnography, phenomenology, grounded theory, and historic research. Another type of methodology that has a similar qualitative approach is case study research, which seeks to understand a phenomenon or case from multiple perspectives within a given real-world context.

Propeller/fan-pitch feathering apparatus

NASA Technical Reports Server (NTRS)

Schilling, Jan C. (Inventor); Adamson, Arthur P. (Inventor); Bathori, Julius (Inventor); Walker, Neil (Inventor)

1990-01-01

A pitch feathering system for a gas turbine driven aircraft propeller having multiple variable pitch blades utilizes a counter-weight linked to the blades. The weight is constrained to move, when effecting a pitch change, only in a radial plane and about an axis which rotates about the propeller axis. The system includes a linkage allowing the weight to move through a larger angle than the associated pitch change of the blade.

Description of the supporting factors of final project in Mathematics and Natural Sciences Faculty of Syiah Kuala University with multiple correspondence analysis

NASA Astrophysics Data System (ADS)

Rusyana, Asep; Nurhasanah; Maulizasari

2018-05-01

Syiah Kuala University (Unsyiah) is hoped to have graduates who are qualified for working or creating a field of work. A final project course implementation process must be effective. This research uses data from the evaluation conducted by Mathematics and Natural Sciences Faculty (FMIPA) of Unsyiah. Some of the factors that support the completion of the final project are duration, guidance, the final project seminars, facility, public impact, and quality. This research aims to know the factors that have a relationship with the completion of the final project and identify similarities among variables. The factors that support the completion of the final project at every study program in FMIPA are (1) duration, (2) guidance and (3) facilities. These factors are examined for the correlations by chi-square test. After that, the variables are analyzed with multiple correspondence analysis. Based on the plot of correspondence, the activities of the guidance and facilities in Informatics Study Program are included in the fair category, while the guidance and facilities in the Chemistry are included in the best category. Besides that, students in Physics can finish the final project with the fastest completion duration, while students in Pharmacy finish for the longest time.

Multiobjective evolutionary optimization of water distribution systems: Exploiting diversity with infeasible solutions.

PubMed

Tanyimboh, Tiku T; Seyoum, Alemtsehay G

2016-12-01

This article investigates the computational efficiency of constraint handling in multi-objective evolutionary optimization algorithms for water distribution systems. The methodology investigated here encourages the co-existence and simultaneous development including crossbreeding of subpopulations of cost-effective feasible and infeasible solutions based on Pareto dominance. This yields a boundary search approach that also promotes diversity in the gene pool throughout the progress of the optimization by exploiting the full spectrum of non-dominated infeasible solutions. The relative effectiveness of small and moderate population sizes with respect to the number of decision variables is investigated also. The results reveal the optimization algorithm to be efficient, stable and robust. It found optimal and near-optimal solutions reliably and efficiently. The real-world system based optimization problem involved multiple variable head supply nodes, 29 fire-fighting flows, extended period simulation and multiple demand categories including water loss. The least cost solutions found satisfied the flow and pressure requirements consistently. The best solutions achieved indicative savings of 48.1% and 48.2% based on the cost of the pipes in the existing network, for populations of 200 and 1000, respectively. The population of 1000 achieved slightly better results overall. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Ventilator-associated pneumonia: the influence of bacterial resistance, prescription errors, and de-escalation of antimicrobial therapy on mortality rates.

PubMed

Souza-Oliveira, Ana Carolina; Cunha, Thúlio Marquez; Passos, Liliane Barbosa da Silva; Lopes, Gustavo Camargo; Gomes, Fabiola Alves; Röder, Denise Von Dolinger de Brito

2016-01-01

Ventilator-associated pneumonia is the most prevalent nosocomial infection in intensive care units and is associated with high mortality rates (14-70%). This study evaluated factors influencing mortality of patients with Ventilator-associated pneumonia (VAP), including bacterial resistance, prescription errors, and de-escalation of antibiotic therapy. This retrospective study included 120 cases of Ventilator-associated pneumonia admitted to the adult adult intensive care unit of the Federal University of Uberlândia. The chi-square test was used to compare qualitative variables. Student's t-test was used for quantitative variables and multiple logistic regression analysis to identify independent predictors of mortality. De-escalation of antibiotic therapy and resistant bacteria did not influence mortality. Mortality was 4 times and 3 times higher, respectively, in patients who received an inappropriate antibiotic loading dose and in patients whose antibiotic dose was not adjusted for renal function. Multiple logistic regression analysis revealed the incorrect adjustment for renal function was the only independent factor associated with increased mortality. Prescription errors influenced mortality of patients with Ventilator-associated pneumonia, underscoring the challenge of proper Ventilator-associated pneumonia treatment, which requires continuous reevaluation to ensure that clinical response to therapy meets expectations. Copyright © 2016. Published by Elsevier Editora Ltda.

Do urban environments increase the risk of anxiety, depression and psychosis? An epidemiological study.

PubMed

McKenzie, Karen; Murray, Aja; Booth, Tom

2013-09-25

The present study aimed to investigate whether there is an association between type of living environment (urban versus rural) and anxiety, depression and psychosis in the Scottish population. Data were obtained from the Scottish Neighbourhood Statistics database on Scottish Index of Multiple Deprivation and urban-rural classifications for 6505 data zones across Scotland. Multiple regression was used to test the association between prescriptions for psychotropic medication for anxiety, depression and psychosis, and type of living environment according to urban-rural classification, controlling for a range of socio-economic factors. Urban-rural classification significantly predicted poorer mental health both before (β=-.29) and after (β=-.20) controlling for a large number of socio-economic variables, with more urban areas having higher rates of prescription for psychotropic medication for anxiety, depression and psychosis. The current study focussed on macro-level variables and did not include individual level data. As such, the study did not include data on individual diagnoses, but instead used drug prescriptions for anxiety, depression and psychosis as a proxy for level of affective disorders within data zones. More urban living environments in Scotland are associated with higher rates of prescription for psychotropic medication for anxiety, depression and psychosis. © 2013 Elsevier B.V. All rights reserved.

A framework for measurement and harmonization of pediatric multiple sclerosis etiologic research studies: The Pediatric MS Tool-Kit.

PubMed

Magalhaes, Sandra; Banwell, Brenda; Bar-Or, Amit; Fortier, Isabel; Hanwell, Heather E; Lim, Ming; Matt, Georg E; Neuteboom, Rinze F; O'Riordan, David L; Schneider, Paul K; Pugliatti, Maura; Shatenstein, Bryna; Tansey, Catherine M; Wassmer, Evangeline; Wolfson, Christina

2018-06-01

While studying the etiology of multiple sclerosis (MS) in children has several methodological advantages over studying etiology in adults, studies are limited by small sample sizes. Using a rigorous methodological process, we developed the Pediatric MS Tool-Kit, a measurement framework that includes a minimal set of core variables to assess etiological risk factors. We solicited input from the International Pediatric MS Study Group to select three risk factors: environmental tobacco smoke (ETS) exposure, sun exposure, and vitamin D intake. To develop the Tool-Kit, we used a Delphi study involving a working group of epidemiologists, neurologists, and content experts from North America and Europe. The Tool-Kit includes six core variables to measure ETS, six to measure sun exposure, and six to measure vitamin D intake. The Tool-Kit can be accessed online ( www.maelstrom-research.org/mica/network/tool-kit ). The goals of the Tool-Kit are to enhance exposure measurement in newly designed pediatric MS studies and comparability of results across studies, and in the longer term to facilitate harmonization of studies, a methodological approach that can be used to circumvent issues of small sample sizes. We believe the Tool-Kit will prove to be a valuable resource to guide pediatric MS researchers in developing study-specific questionnaire.

Use of multi-node wells in the Groundwater-Management Process of MODFLOW-2005 (GWM-2005)

USGS Publications Warehouse

Ahlfeld, David P.; Barlow, Paul M.

2013-01-01

Many groundwater wells are open to multiple aquifers or to multiple intervals within a single aquifer. These types of wells can be represented in numerical simulations of groundwater flow by use of the Multi-Node Well (MNW) Packages developed for the U.S. Geological Survey’s MODFLOW model. However, previous versions of the Groundwater-Management (GWM) Process for MODFLOW did not allow the use of multi-node wells in groundwater-management formulations. This report describes modifications to the MODFLOW–2005 version of the GWM Process (GWM–2005) to provide for such use with the MNW2 Package. Multi-node wells can be incorporated into a management formulation as flow-rate decision variables for which optimal withdrawal or injection rates will be determined as part of the GWM–2005 solution process. In addition, the heads within multi-node wells can be used as head-type state variables, and, in that capacity, be included in the objective function or constraint set of a management formulation. Simple head bounds also can be defined to constrain water levels at multi-node wells. The report provides instructions for including multi-node wells in the GWM–2005 data-input files and a sample problem that demonstrates use of multi-node wells in a typical groundwater-management problem.

A Tracking Analyst for large 3D spatiotemporal data from multiple sources (case study: Tracking volcanic eruptions in the atmosphere)

NASA Astrophysics Data System (ADS)

Gad, Mohamed A.; Elshehaly, Mai H.; Gračanin, Denis; Elmongui, Hicham G.

2018-02-01

This research presents a novel Trajectory-based Tracking Analyst (TTA) that can track and link spatiotemporally variable data from multiple sources. The proposed technique uses trajectory information to determine the positions of time-enabled and spatially variable scatter data at any given time through a combination of along trajectory adjustment and spatial interpolation. The TTA is applied in this research to track large spatiotemporal data of volcanic eruptions (acquired using multi-sensors) in the unsteady flow field of the atmosphere. The TTA enables tracking injections into the atmospheric flow field, the reconstruction of the spatiotemporally variable data at any desired time, and the spatiotemporal join of attribute data from multiple sources. In addition, we were able to create a smooth animation of the volcanic ash plume at interactive rates. The initial results indicate that the TTA can be applied to a wide range of multiple-source data.

Multiple regression for physiological data analysis: the problem of multicollinearity.

PubMed

Slinker, B K; Glantz, S A

1985-07-01

Multiple linear regression, in which several predictor variables are related to a response variable, is a powerful statistical tool for gaining quantitative insight into complex in vivo physiological systems. For these insights to be correct, all predictor variables must be uncorrelated. However, in many physiological experiments the predictor variables cannot be precisely controlled and thus change in parallel (i.e., they are highly correlated). There is a redundancy of information about the response, a situation called multicollinearity, that leads to numerical problems in estimating the parameters in regression equations; the parameters are often of incorrect magnitude or sign or have large standard errors. Although multicollinearity can be avoided with good experimental design, not all interesting physiological questions can be studied without encountering multicollinearity. In these cases various ad hoc procedures have been proposed to mitigate multicollinearity. Although many of these procedures are controversial, they can be helpful in applying multiple linear regression to some physiological problems.

The Association Between Premedical Curricular and Admission Requirements and Medical School Performance and Residency Placement: A Study of Two Admission Routes.

PubMed

George, Paul; Park, Yoon Soo; Ip, Julianne; Gruppuso, Philip A; Adashi, Eli Y

2016-03-01

The curricular elements of undergraduate premedical education are the subject of an ongoing debate. The Warren Alpert Medical School of Brown University (AMS) matriculates students via the traditional premedical route (TPM) and an eight-year baccalaureate/MD program-the Program in Liberal Medical Education (PLME)-which provides students with a broad and liberal education. Using the juxtaposition of these two admission routes, the authors aimed to determine whether there is an association between highly distinct premedical curricular and admission requirements and medical school performance and residency placement. The cohorts studied included all of the PLME (n = 295) and TPM (n = 215) students who graduated from the AMS between 2010 and 2015. Outcome variables consisted of multiple measures of medical school performance, including standardized multiple-choice examination scores and honors grades, and residency placement. The authors employed unadjusted tests of averages and proportions (independent t tests and chi-square tests) to compare variables. The TPM students attained marginally, but statistically significantly, higher average scores on standardized multiple-choice examinations than their PLME counterparts. The number of undergraduate premedical science courses completed by PLME students accounted for less than 4% of the variance in key metrics of medical school performance. The residency placement record of the PLME and TPM cohorts proved comparable. These findings suggest that the association between medical school performance and residency placement and undergraduate premedical curricular and admission requirements is weak. Further study is needed to determine the optimal premedical preparation of students.

Landscape effects on mallard habitat selection at multiple spatial scales during the non-breeding period

USGS Publications Warehouse

Beatty, William S.; Webb, Elisabeth B.; Kesler, Dylan C.; Raedeke, Andrew H.; Naylor, Luke W.; Humburg, Dale D.

2014-01-01

Previous studies that evaluated effects of landscape-scale habitat heterogeneity on migratory waterbird distributions were spatially limited and temporally restricted to one major life-history phase. However, effects of landscape-scale habitat heterogeneity on long-distance migratory waterbirds can be studied across the annual cycle using new technologies, including global positioning system satellite transmitters. We used Bayesian discrete choice models to examine the influence of local habitats and landscape composition on habitat selection by a generalist dabbling duck, the mallard (Anas platyrhynchos), in the midcontinent of North America during the non-breeding period. Using a previously published empirical movement metric, we separated the non-breeding period into three seasons, including autumn migration, winter, and spring migration. We defined spatial scales based on movement patterns such that movements >0.25 and <30.00 km were classified as local scale and movements >30.00 km were classified as relocation scale. Habitat selection at the local scale was generally influenced by local and landscape-level variables across all seasons. Variables in top models at the local scale included proximities to cropland, emergent wetland, open water, and woody wetland. Similarly, variables associated with area of cropland, emergent wetland, open water, and woody wetland were also included at the local scale. At the relocation scale, mallards selected resource units based on more generalized variables, including proximity to wetlands and total wetland area. Our results emphasize the role of landscape composition in waterbird habitat selection and provide further support for local wetland landscapes to be considered functional units of waterbird conservation and management.

Functional Capacity Evaluation in Different Societal Contexts: Results of a Multicountry Study.

PubMed

Ansuategui Echeita, Jone; Bethge, Matthias; van Holland, Berry J; Gross, Douglas P; Kool, Jan; Oesch, Peter; Trippolini, Maurizio A; Chapman, Elizabeth; Cheng, Andy S K; Sellars, Robert; Spavins, Megan; Streibelt, Marco; van der Wurff, Peter; Reneman, Michiel F

2018-05-25

Purpose To examine factors associated with Functional Capacity Evaluation (FCE) results in patients with painful musculoskeletal conditions, with focus on social factors across multiple countries. Methods International cross-sectional study was performed within care as usual. Simple and multiple multilevel linear regression analyses which considered measurement's dependency within clinicians and country were conducted: FCE characteristics and biopsychosocial variables from patients and clinicians as independent variables; and FCE results (floor-to-waist lift, six-minute walk, and handgrip strength) as dependent variables. Results Data were collected for 372 patients, 54 clinicians, 18 facilities and 8 countries. Patients' height and reported pain intensity were consistently associated with every FCE result. Patients' sex, height, reported pain intensity, effort during FCE, social isolation, and disability, clinician's observed physical effort, and whether FCE test was prematurely ended were associated with lift. Patient's height, Body Mass Index, post-test heart-rate, reported pain intensity and effort during FCE, days off work, and whether FCE test was prematurely ended were associated with walk. Patient's age, sex, height, affected body area, reported pain intensity and catastrophizing, and physical work demands were associated with handgrip. Final regression models explained 38‒65% of total variance. Clinician and country random effects composed 1-39% of total residual variance in these models. Conclusion Biopsychosocial factors were associated with every FCE result across multiple countries; specifically, patients' height, reported pain intensity, clinician, and measurement country. Social factors, which had been under-researched, were consistently associated with FCE performances. Patients' FCE results should be considered from a biopsychosocial perspective, including different social contexts.

Predictors of psychological distress in low-income populations of Montreal.

PubMed

Caron, Jean; Latimer, Eric; Tousignant, Michel

2007-01-01

THEORETICAL PERSPECTIVE: Many epidemiologic studies agree that low-income populations are the groups most vulnerable to mental health problems. However, not all people in economic difficulty show symptoms, and it appears that having a social support network plays a role in protecting against the chronic stress resulting from conditions such as poverty. The aim of the study is to clarify the relative contribution of social support to the mental health of low-income populations in two neighbourhoods in the southwest of Montreal: Pointe-Saint Charles and Saint-Henri. A random sample of 416 social assistance recipients in southwest Montreal and another sample of 112 people, drawn at random from the general population, were interviewed. The psychological distress scale used was the Indice de détresse psychologique--Enquête Santê Quêbec (IDPESQ). The availability of social support components was assessed by using the Social Provisions Scale. Data were collected during interviews in the respondents' homes. Social support measures were entered into a multidimensional model including many variables identified as being associated with mental health. Multiple regression analysis identified the best predictors of psychological distress for the low-income population. Among the 30 variables included in a multiple regression analysis, emotional support and the presence of persons perceived as stressful together accounted for most of the variance in distress predicted by the model. Although younger people, people experiencing food insecurity and people with poorer numeracy show a higher level of distress, these variables make a fairly marginal contribution compared with that of social relations.

The Canadian Hydrological Model (CHM): A multi-scale, variable-complexity hydrological model for cold regions

NASA Astrophysics Data System (ADS)

Marsh, C.; Pomeroy, J. W.; Wheater, H. S.

2016-12-01

There is a need for hydrological land surface schemes that can link to atmospheric models, provide hydrological prediction at multiple scales and guide the development of multiple objective water predictive systems. Distributed raster-based models suffer from an overrepresentation of topography, leading to wasted computational effort that increases uncertainty due to greater numbers of parameters and initial conditions. The Canadian Hydrological Model (CHM) is a modular, multiphysics, spatially distributed modelling framework designed for representing hydrological processes, including those that operate in cold-regions. Unstructured meshes permit variable spatial resolution, allowing coarse resolutions at low spatial variability and fine resolutions as required. Model uncertainty is reduced by lessening the necessary computational elements relative to high-resolution rasters. CHM uses a novel multi-objective approach for unstructured triangular mesh generation that fulfills hydrologically important constraints (e.g., basin boundaries, water bodies, soil classification, land cover, elevation, and slope/aspect). This provides an efficient spatial representation of parameters and initial conditions, as well as well-formed and well-graded triangles that are suitable for numerical discretization. CHM uses high-quality open source libraries and high performance computing paradigms to provide a framework that allows for integrating current state-of-the-art process algorithms. The impact of changes to model structure, including individual algorithms, parameters, initial conditions, driving meteorology, and spatial/temporal discretization can be easily tested. Initial testing of CHM compared spatial scales and model complexity for a spring melt period at a sub-arctic mountain basin. The meshing algorithm reduced the total number of computational elements and preserved the spatial heterogeneity of predictions.

Roles of increased glycaemic variability, GLP-1 and glucagon in hypoglycaemia after Roux-en-Y gastric bypass

PubMed Central

Tharakan, George; Behary, Preeshila; Wewer Albrechtsen, Nicolai J; Chahal, Harvinder; Kenkre, Julia; Miras, Alexander D; Ahmed, Ahmed R; Holst, Jens J; Bloom, Stephen R

2017-01-01

Objective Roux-en-Y gastric bypass (RYGB) surgery is currently the most effective treatment for diabetes and obesity. An increasingly recognized and highly disabling complication of RYGB is postprandial hypoglycaemia (PPH). The pathophysiology of PPH remains unclear with multiple mechanisms suggested including nesidioblastosis, altered insulin clearance and increased glucagon-like peptide-1 (GLP-1) secretion. Whilst many PPH patients respond to dietary modification, some have severely disabling symptoms. Multiple treatments are proposed, including dietary modification, GLP-1 antagonism, GLP-1 analogues and even surgical reversal, with none showing a more decided advantage over the others. A greater understanding of the pathophysiology of PPH could guide the development of new therapeutic strategies. Methods We studied a cohort of PPH patients at the Imperial Weight Center. We performed continuous glucose monitoring to characterize their altered glycaemic variability. We also performed a mixed meal test (MMT) and measured gut hormone concentrations. Results We found increased glycaemic variability in our cohort of PPH patients, specifically a higher mean amplitude glucose excursion (MAGE) score of 4.9. We observed significantly greater and earlier increases in insulin, GLP-1 and glucagon in patients who had hypoglycaemia in response to an MMT (MMT Hypo) relative to those that did not (MMT Non-Hypo). No significant differences in oxyntomodulin, GIP or peptide YY secretion were seen between these two groups. Conclusion An early peak in GLP-1 and glucagon may together trigger an exaggerated insulinotropic response to eating and consequent hypoglycaemia in patients with PPH. PMID:28855269

Importance of Urinary Drug Screening in the Multiple Sleep Latency Test and Maintenance of Wakefulness Test.

PubMed

Anniss, Angela M; Young, Alan; O'Driscoll, Denise M

2016-12-15

Multiple sleep latency testing (MSLT) and the maintenance of wakefulness test (MWT) are gold-standard objective tests of daytime sleepiness and alertness; however, there is marked variability in their interpretation and practice. This study aimed to determine the incidence of positive drug screens and their influence on MSLT, MWT, and polysomnographic variables. All patients attending Eastern Health Sleep Laboratory for MSLT or MWT over a 21-mo period were included in the study. Urinary drug screening for amphetamines, barbiturates, benzodiazepines, cannabinoids, cocaine, methadone, and opiates was performed following overnight polysomnography (PSG). Demographics and PSG variables were compared. Of 69 studies, MSLT (43) and MWT (26), 16% of patients had positive urinary drug screening (7 MSLT; 4 MWT). Drugs detected included amphetamines, cannabinoids, opiates, and benzodiazepines. No patient self-reported use of these medications prior to testing. No demographic, MSLT or MWT PSG data or overnight PSG data showed any statistical differences between positive and negative drug screen groups. Of seven MSLT patients testing positive for drug use, one met criteria for the diagnosis of narcolepsy and five for idiopathic hypersomnia. On MWT, three of the four drug-positive patients had a history of a motor vehicle accident and two patients were occupational drivers. These findings indicate drug use is present in patients attending for daytime testing of objective sleepiness and wakefulness. These data support routine urinary drug screening in all patients undergoing MSLT or MWT studies to ensure accurate interpretation in the context of illicit and prescription drug use. © 2016 American Academy of Sleep Medicine

The chi-square test of independence.

PubMed

McHugh, Mary L

2013-01-01

The Chi-square statistic is a non-parametric (distribution free) tool designed to analyze group differences when the dependent variable is measured at a nominal level. Like all non-parametric statistics, the Chi-square is robust with respect to the distribution of the data. Specifically, it does not require equality of variances among the study groups or homoscedasticity in the data. It permits evaluation of both dichotomous independent variables, and of multiple group studies. Unlike many other non-parametric and some parametric statistics, the calculations needed to compute the Chi-square provide considerable information about how each of the groups performed in the study. This richness of detail allows the researcher to understand the results and thus to derive more detailed information from this statistic than from many others. The Chi-square is a significance statistic, and should be followed with a strength statistic. The Cramer's V is the most common strength test used to test the data when a significant Chi-square result has been obtained. Advantages of the Chi-square include its robustness with respect to distribution of the data, its ease of computation, the detailed information that can be derived from the test, its use in studies for which parametric assumptions cannot be met, and its flexibility in handling data from both two group and multiple group studies. Limitations include its sample size requirements, difficulty of interpretation when there are large numbers of categories (20 or more) in the independent or dependent variables, and tendency of the Cramer's V to produce relative low correlation measures, even for highly significant results.

A multidisciplinary-based conceptual model of a fractured sedimentary bedrock aquitard: improved prediction of aquitard integrity

NASA Astrophysics Data System (ADS)

Runkel, Anthony C.; Tipping, Robert G.; Meyer, Jessica R.; Steenberg, Julia R.; Retzler, Andrew J.; Parker, Beth L.; Green, Jeff A.; Barry, John D.; Jones, Perry M.

2018-06-01

A hydrogeologic conceptual model that improves understanding of variability in aquitard integrity is presented for a fractured sedimentary bedrock unit in the Cambrian-Ordovician aquifer system of midcontinent North America. The model is derived from multiple studies on the siliciclastic St. Lawrence Formation and adjacent strata across a range of scales and geologic conditions. These studies employed multidisciplinary techniques including borehole flowmeter logging, high-resolution depth-discrete multilevel well monitoring, fracture stratigraphy, fluorescent dye tracing, and three-dimensional (3D) distribution of anthropogenic tracers regionally. The paper documents a bulk aquitard that is highly anisotropic because of poor connectivity of vertical fractures across matrix with low permeability, but with ubiquitous bed parallel partings. The partings provide high bulk horizontal hydraulic conductivity, analogous to aquifers in the system, while multiple preferential termination horizons of vertical fractures serve as discrete low vertical hydraulic conductivity intervals inhibiting vertical flow. The aquitard has substantial variability in its ability to protect underlying groundwater from contamination. Across widespread areas where the aquitard is deeply buried by younger bedrock, preferential termination horizons provide for high aquitard integrity (i.e. protection). Protection is diminished close to incised valleys where stress release and weathering has enhanced secondary pore development, including better connection of fractures across these horizons. These conditions, along with higher hydraulic head gradients in the same areas and more complex 3D flow where the aquitard is variably incised, allow for more substantial transport to deeper aquifers. The conceptual model likely applies to other fractured sedimentary bedrock aquitards within and outside of this region.

A Bayesian joint probability modeling approach for seasonal forecasting of streamflows at multiple sites

NASA Astrophysics Data System (ADS)

Wang, Q. J.; Robertson, D. E.; Chiew, F. H. S.

2009-05-01

Seasonal forecasting of streamflows can be highly valuable for water resources management. In this paper, a Bayesian joint probability (BJP) modeling approach for seasonal forecasting of streamflows at multiple sites is presented. A Box-Cox transformed multivariate normal distribution is proposed to model the joint distribution of future streamflows and their predictors such as antecedent streamflows and El Niño-Southern Oscillation indices and other climate indicators. Bayesian inference of model parameters and uncertainties is implemented using Markov chain Monte Carlo sampling, leading to joint probabilistic forecasts of streamflows at multiple sites. The model provides a parametric structure for quantifying relationships between variables, including intersite correlations. The Box-Cox transformed multivariate normal distribution has considerable flexibility for modeling a wide range of predictors and predictands. The Bayesian inference formulated allows the use of data that contain nonconcurrent and missing records. The model flexibility and data-handling ability means that the BJP modeling approach is potentially of wide practical application. The paper also presents a number of statistical measures and graphical methods for verification of probabilistic forecasts of continuous variables. Results for streamflows at three river gauges in the Murrumbidgee River catchment in southeast Australia show that the BJP modeling approach has good forecast quality and that the fitted model is consistent with observed data.

Responsiveness-informed multiple imputation and inverse probability-weighting in cohort studies with missing data that are non-monotone or not missing at random.

PubMed

Doidge, James C

2018-02-01

Population-based cohort studies are invaluable to health research because of the breadth of data collection over time, and the representativeness of their samples. However, they are especially prone to missing data, which can compromise the validity of analyses when data are not missing at random. Having many waves of data collection presents opportunity for participants' responsiveness to be observed over time, which may be informative about missing data mechanisms and thus useful as an auxiliary variable. Modern approaches to handling missing data such as multiple imputation and maximum likelihood can be difficult to implement with the large numbers of auxiliary variables and large amounts of non-monotone missing data that occur in cohort studies. Inverse probability-weighting can be easier to implement but conventional wisdom has stated that it cannot be applied to non-monotone missing data. This paper describes two methods of applying inverse probability-weighting to non-monotone missing data, and explores the potential value of including measures of responsiveness in either inverse probability-weighting or multiple imputation. Simulation studies are used to compare methods and demonstrate that responsiveness in longitudinal studies can be used to mitigate bias induced by missing data, even when data are not missing at random.

Missing data and multiple imputation in clinical epidemiological research.

PubMed

Pedersen, Alma B; Mikkelsen, Ellen M; Cronin-Fenton, Deirdre; Kristensen, Nickolaj R; Pham, Tra My; Pedersen, Lars; Petersen, Irene

2017-01-01

Missing data are ubiquitous in clinical epidemiological research. Individuals with missing data may differ from those with no missing data in terms of the outcome of interest and prognosis in general. Missing data are often categorized into the following three types: missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR). In clinical epidemiological research, missing data are seldom MCAR. Missing data can constitute considerable challenges in the analyses and interpretation of results and can potentially weaken the validity of results and conclusions. A number of methods have been developed for dealing with missing data. These include complete-case analyses, missing indicator method, single value imputation, and sensitivity analyses incorporating worst-case and best-case scenarios. If applied under the MCAR assumption, some of these methods can provide unbiased but often less precise estimates. Multiple imputation is an alternative method to deal with missing data, which accounts for the uncertainty associated with missing data. Multiple imputation is implemented in most statistical software under the MAR assumption and provides unbiased and valid estimates of associations based on information from the available data. The method affects not only the coefficient estimates for variables with missing data but also the estimates for other variables with no missing data.

Missing data and multiple imputation in clinical epidemiological research

PubMed Central

Pedersen, Alma B; Mikkelsen, Ellen M; Cronin-Fenton, Deirdre; Kristensen, Nickolaj R; Pham, Tra My; Pedersen, Lars; Petersen, Irene

2017-01-01

Missing data are ubiquitous in clinical epidemiological research. Individuals with missing data may differ from those with no missing data in terms of the outcome of interest and prognosis in general. Missing data are often categorized into the following three types: missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR). In clinical epidemiological research, missing data are seldom MCAR. Missing data can constitute considerable challenges in the analyses and interpretation of results and can potentially weaken the validity of results and conclusions. A number of methods have been developed for dealing with missing data. These include complete-case analyses, missing indicator method, single value imputation, and sensitivity analyses incorporating worst-case and best-case scenarios. If applied under the MCAR assumption, some of these methods can provide unbiased but often less precise estimates. Multiple imputation is an alternative method to deal with missing data, which accounts for the uncertainty associated with missing data. Multiple imputation is implemented in most statistical software under the MAR assumption and provides unbiased and valid estimates of associations based on information from the available data. The method affects not only the coefficient estimates for variables with missing data but also the estimates for other variables with no missing data. PMID:28352203

Multiple sclerosis and employment: Associations of psychological factors and work instability.

PubMed

Wicks, Charlotte Rose; Ward, Karl; Stroud, Amanda; Tennant, Alan; Ford, Helen L

2016-10-12

People with multiple sclerosis often stop working earlier than expected. Psychological factors may have an impact on job retention. Investigation may inform interventions to help people stay in work. To investigate the associations between psychological factors and work instability in people with multiple sclerosis. A multi-method, 2-phased study. Focus groups were held to identify key themes. Questionnaire packs using validated scales of the key themes were completed at baseline and at 8-month follow-up. Four key psychological themes emerged. Out of 208 study subjects 57.2% reported medium/high risk of job loss, with marginal changes at 8 months. Some psychological variables fluctuated significantly, e.g. depression fell from 24.6% to 14.5%. Work instability and anxiety and depression were strongly correlated (χ2 p < 0.001). Those with probable depression at baseline had 7.1 times increased odds of medium/high work instability, and baseline depression levels also predicted later work instability (Hosmer-Lemeshow test 0.899; Nagelkerke R Square 0.579). Psychological factors fluctuated over the 8-month follow-up period. Some psychological variables, including anxiety and depression, were significantly associated with, and predictive of, work instability. Longitudinal analysis should further identify how these psychological attributes impact on work instability and potential job loss in the longer term.

Elastic-net regularization approaches for genome-wide association studies of rheumatoid arthritis.

PubMed

Cho, Seoae; Kim, Haseong; Oh, Sohee; Kim, Kyunga; Park, Taesung

2009-12-15

The current trend in genome-wide association studies is to identify regions where the true disease-causing genes may lie by evaluating thousands of single-nucleotide polymorphisms (SNPs) across the whole genome. However, many challenges exist in detecting disease-causing genes among the thousands of SNPs. Examples include multicollinearity and multiple testing issues, especially when a large number of correlated SNPs are simultaneously tested. Multicollinearity can often occur when predictor variables in a multiple regression model are highly correlated, and can cause imprecise estimation of association. In this study, we propose a simple stepwise procedure that identifies disease-causing SNPs simultaneously by employing elastic-net regularization, a variable selection method that allows one to address multicollinearity. At Step 1, the single-marker association analysis was conducted to screen SNPs. At Step 2, the multiple-marker association was scanned based on the elastic-net regularization. The proposed approach was applied to the rheumatoid arthritis (RA) case-control data set of Genetic Analysis Workshop 16. While the selected SNPs at the screening step are located mostly on chromosome 6, the elastic-net approach identified putative RA-related SNPs on other chromosomes in an increased proportion. For some of those putative RA-related SNPs, we identified the interactions with sex, a well known factor affecting RA susceptibility.

Cumulative risk effects for the development of behaviour difficulties in children and adolescents with special educational needs and disabilities.

PubMed

Oldfield, Jeremy; Humphrey, Neil; Hebron, Judith

2015-01-01

Research has identified multiple risk factors for the development of behaviour difficulties. What have been less explored are the cumulative effects of exposure to multiple risks on behavioural outcomes, with no study specifically investigating these effects within a population of young people with special educational needs and disabilities (SEND). Furthermore, it is unclear whether a threshold or linear risk model better fits the data for this population. The sample included 2660 children and 1628 adolescents with SEND. Risk factors associated with increases in behaviour difficulties over an 18-month period were summed to create a cumulative risk score, with this explanatory variable being added into a multi-level model. A quadratic term was then added to test the threshold model. There was evidence of a cumulative risk effect, suggesting that exposure to higher numbers of risk factors, regardless of their exact nature, resulted in increased behaviour difficulties. The relationship between risk and behaviour difficulties was non-linear, with exposure to increasing risk having a disproportionate and detrimental impact on behaviour difficulties in child and adolescent models. Interventions aimed at reducing behaviour difficulties need to consider the impact of multiple risk variables. Tailoring interventions towards those exposed to large numbers of risks would be advantageous. Copyright © 2015 Elsevier Ltd. All rights reserved.

Most Likely to Succeed: Exploring Predictor Variables for the Counselor Preparation Comprehensive Examination

ERIC Educational Resources Information Center

Hartwig, Elizabeth Kjellstrand; Van Overschelde, James P.

2016-01-01

The authors investigated predictor variables for the Counselor Preparation Comprehensive Examination (CPCE) to examine whether academic variables, demographic variables, and test version were associated with graduate counseling students' CPCE scores. Multiple regression analyses revealed all 3 variables were statistically significant predictors of…

Multichannel microformulators for massively parallel machine learning and automated design of biological experiments

NASA Astrophysics Data System (ADS)

Wikswo, John; Kolli, Aditya; Shankaran, Harish; Wagoner, Matthew; Mettetal, Jerome; Reiserer, Ronald; Gerken, Gregory; Britt, Clayton; Schaffer, David

Genetic, proteomic, and metabolic networks describing biological signaling can have 102 to 103 nodes. Transcriptomics and mass spectrometry can quantify 104 different dynamical experimental variables recorded from in vitro experiments with a time resolution approaching 1 s. It is difficult to infer metabolic and signaling models from such massive data sets, and it is unlikely that causality can be determined simply from observed temporal correlations. There is a need to design and apply specific system perturbations, which will be difficult to perform manually with 10 to 102 externally controlled variables. Machine learning and optimal experimental design can select an experiment that best discriminates between multiple conflicting models, but a remaining problem is to control in real time multiple variables in the form of concentrations of growth factors, toxins, nutrients and other signaling molecules. With time-division multiplexing, a microfluidic MicroFormulator (μF) can create in real time complex mixtures of reagents in volumes suitable for biological experiments. Initial 96-channel μF implementations control the exposure profile of cells in a 96-well plate to different temporal profiles of drugs; future experiments will include challenge compounds. Funded in part by AstraZeneca, NIH/NCATS HHSN271201600009C and UH3TR000491, and VIIBRE.

Prediction system of hydroponic plant growth and development using algorithm Fuzzy Mamdani method

NASA Astrophysics Data System (ADS)

Sudana, I. Made; Purnawirawan, Okta; Arief, Ulfa Mediaty

2017-03-01

Hydroponics is a method of farming without soil. One of the Hydroponic plants is Watercress (Nasturtium Officinale). The development and growth process of hydroponic Watercress was influenced by levels of nutrients, acidity and temperature. The independent variables can be used as input variable system to predict the value level of plants growth and development. The prediction system is using Fuzzy Algorithm Mamdani method. This system was built to implement the function of Fuzzy Inference System (Fuzzy Inference System/FIS) as a part of the Fuzzy Logic Toolbox (FLT) by using MATLAB R2007b. FIS is a computing system that works on the principle of fuzzy reasoning which is similar to humans' reasoning. Basically FIS consists of four units which are fuzzification unit, fuzzy logic reasoning unit, base knowledge unit and defuzzification unit. In addition to know the effect of independent variables on the plants growth and development that can be visualized with the function diagram of FIS output surface that is shaped three-dimensional, and statistical tests based on the data from the prediction system using multiple linear regression method, which includes multiple linear regression analysis, T test, F test, the coefficient of determination and donations predictor that are calculated using SPSS (Statistical Product and Service Solutions) software applications.

Deglacial variability of Antarctic Intermediate Water penetration into the North Atlantic from authigenic neodymium isotope ratios

NASA Astrophysics Data System (ADS)

Xie, Ruifang C.; Marcantonio, Franco; Schmidt, Matthew W.

2012-09-01

Understanding intermediate water circulation across the last deglacial is critical in assessing the role of oceanic heat transport associated with Atlantic Meridional Overturning Circulation variability across abrupt climate events. However, the links between intermediate water circulation and abrupt climate events such as the Younger Dryas (YD) and Heinrich Event 1 (H1) are still poorly constrained. Here, we reconstruct changes in Antarctic Intermediate Water (AAIW) circulation in the subtropical North Atlantic over the past 25 kyr by measuring authigenic neodymium isotope ratios in sediments from two sites in the Florida Straits. Our authigenic Nd isotope records suggest that there was little to no penetration of AAIW into the subtropical North Atlantic during the YD and H1. Variations in the northward penetration of AAIW into the Florida Straits documented in our authigenic Nd isotope record are synchronous with multiple climatic archives, including the Greenland ice core δ18O record, the Cariaco Basin atmosphere Δ14C reconstruction, the Bermuda Rise sedimentary Pa/Th record, and nutrient and stable isotope data from the tropical North Atlantic. The synchroneity of our Nd records with multiple climatic archives suggests a tight connection between AAIW variability and high-latitude North Atlantic climate change.

Accelerometry in persons with multiple sclerosis: measurement of physical activity or walking mobility?

PubMed

Weikert, Madeline; Motl, Robert W; Suh, Yoojin; McAuley, Edward; Wynn, Daniel

2010-03-15

Motion sensors such as accelerometers have been recognized as an ideal measure of physical activity in persons with MS. This study examined the hypothesis that accelerometer movement counts represent a measure of both physical activity and walking mobility in individuals with MS. The sample included 269 individuals with a definite diagnosis of relapsing-remitting MS who completed the Godin Leisure-Time Exercise Questionnaire (GLTEQ), International Physical Activity Questionnaire (IPAQ), Multiple Sclerosis Walking Scale-12 (MSWS-12), Patient Determined Disease Steps (PDDS), and then wore an ActiGraph accelerometer for 7days. The data were analyzed using bivariate correlation and confirmatory factor analysis. The results indicated that (a) the GLTEQ and IPAQ scores were strongly correlated and loaded significantly on a physical activity latent variable, (b) the MSWS-12 and PDDS scores strongly correlated and loaded significantly on a walking mobility latent variable, and (c) the accelerometer movement counts correlated similarly with the scores from the four self-report questionnaires and cross-loaded on both physical activity and walking mobility latent variables. Our data suggest that accelerometers are measuring both physical activity and walking mobility in persons with MS, whereas self-report instruments are measuring either physical activity or walking mobility in this population.

Use of the partial farm budget technique to predict the economic impact of the flock management decision to use B-mode ultrasonographic pregnancy diagnosis.

PubMed

Sprecher, D J; Ley, W B; Whittier, W D; Bowen, J M; Thatcher, C D; Pelzer, K D; Moore, J M

1989-07-15

A computer spreadsheet was developed to predict the economic impact of a management decision to use B-mode ultrasonographic ovine pregnancy diagnosis. The spreadsheet design and spreadsheet cell formulas are provided. The program used the partial farm budget technique to calculate net return (NR) or cash flow changes that resulted from the decision to use ultrasonography. Using the program, either simple pregnancy diagnosis or pregnancy diagnosis with the ability to determine singleton or multiple pregnancies may be compared with no flock ultrasonographic pregnancy diagnosis. A wide range of user-selected regional variables are used to calculate the cash flow changes associated with the ultrasonography decisions. A variable may be altered through a range of values to conduct a sensitivity analysis of predicted NR. Example sensitivity analyses are included for flock conception rate, veterinary ultrasound fee, and the price of corn. Variables that influence the number of cull animals and the cost of ultrasonography have the greatest impact on predicted NR. Because the determination of singleton or multiple pregnancies is more time consuming, its economic practicality in comparison with simple pregnancy diagnosis is questionable. The value of feed saved by identifying and separately feeding ewes with singleton pregnancies is not offset by the increased ultrasonography cost.

Predictors of psychological resilience amongst medical students following major earthquakes.

PubMed

Carter, Frances; Bell, Caroline; Ali, Anthony; McKenzie, Janice; Boden, Joseph M; Wilkinson, Timothy; Bell, Caroline

2016-05-06

To identify predictors of self-reported psychological resilience amongst medical students following major earthquakes in Canterbury in 2010 and 2011. Two hundred and fifty-three medical students from the Christchurch campus, University of Otago, were invited to participate in an electronic survey seven months following the most severe earthquake. Students completed the Connor-Davidson Resilience Scale, the Depression, Anxiety and Stress Scale, the Post-traumatic Disorder Checklist, the Work and Adjustment Scale, and the Eysenck Personality Questionnaire. Likert scales and other questions were also used to assess a range of variables including demographic and historical variables (eg, self-rated resilience prior to the earthquakes), plus the impacts of the earthquakes. The response rate was 78%. Univariate analyses identified multiple variables that were significantly associated with higher resilience. Multiple linear regression analyses produced a fitted model that was able to explain 35% of the variance in resilience scores. The best predictors of higher resilience were: retrospectively-rated personality prior to the earthquakes (higher extroversion and lower neuroticism); higher self-rated resilience prior to the earthquakes; not being exposed to the most severe earthquake; and less psychological distress following the earthquakes. Psychological resilience amongst medical students following major earthquakes was able to be predicted to a moderate extent.

Detection of bifurcations in noisy coupled systems from multiple time series

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

Williamson, Mark S., E-mail: m.s.williamson@exeter.ac.uk; Lenton, Timothy M.

We generalize a method of detecting an approaching bifurcation in a time series of a noisy system from the special case of one dynamical variable to multiple dynamical variables. For a system described by a stochastic differential equation consisting of an autonomous deterministic part with one dynamical variable and an additive white noise term, small perturbations away from the system's fixed point will decay slower the closer the system is to a bifurcation. This phenomenon is known as critical slowing down and all such systems exhibit this decay-type behaviour. However, when the deterministic part has multiple coupled dynamical variables, themore » possible dynamics can be much richer, exhibiting oscillatory and chaotic behaviour. In our generalization to the multi-variable case, we find additional indicators to decay rate, such as frequency of oscillation. In the case of approaching a homoclinic bifurcation, there is no change in decay rate but there is a decrease in frequency of oscillations. The expanded method therefore adds extra tools to help detect and classify approaching bifurcations given multiple time series, where the underlying dynamics are not fully known. Our generalisation also allows bifurcation detection to be applied spatially if one treats each spatial location as a new dynamical variable. One may then determine the unstable spatial mode(s). This is also something that has not been possible with the single variable method. The method is applicable to any set of time series regardless of its origin, but may be particularly useful when anticipating abrupt changes in the multi-dimensional climate system.« less

Detection of bifurcations in noisy coupled systems from multiple time series

NASA Astrophysics Data System (ADS)

Williamson, Mark S.; Lenton, Timothy M.

2015-03-01

We generalize a method of detecting an approaching bifurcation in a time series of a noisy system from the special case of one dynamical variable to multiple dynamical variables. For a system described by a stochastic differential equation consisting of an autonomous deterministic part with one dynamical variable and an additive white noise term, small perturbations away from the system's fixed point will decay slower the closer the system is to a bifurcation. This phenomenon is known as critical slowing down and all such systems exhibit this decay-type behaviour. However, when the deterministic part has multiple coupled dynamical variables, the possible dynamics can be much richer, exhibiting oscillatory and chaotic behaviour. In our generalization to the multi-variable case, we find additional indicators to decay rate, such as frequency of oscillation. In the case of approaching a homoclinic bifurcation, there is no change in decay rate but there is a decrease in frequency of oscillations. The expanded method therefore adds extra tools to help detect and classify approaching bifurcations given multiple time series, where the underlying dynamics are not fully known. Our generalisation also allows bifurcation detection to be applied spatially if one treats each spatial location as a new dynamical variable. One may then determine the unstable spatial mode(s). This is also something that has not been possible with the single variable method. The method is applicable to any set of time series regardless of its origin, but may be particularly useful when anticipating abrupt changes in the multi-dimensional climate system.

The Enduring Challenge of Determining Pneumonia Etiology in Children: Considerations for Future Research Priorities.

PubMed

Feikin, Daniel R; Hammitt, Laura L; Murdoch, David R; O'Brien, Katherine L; Scott, J Anthony G

2017-06-15

Pneumonia kills more children each year worldwide than any other disease. Nonetheless, accurately determining the causes of childhood pneumonia has remained elusive. Over the past century, the focus of pneumonia etiology research has shifted from studies of lung aspirates and postmortem specimens intent on identifying pneumococcal disease to studies of multiple specimen types distant from the lung that are tested for multiple pathogens. Some major challenges facing modern pneumonia etiology studies include the use of nonspecific and variable case definitions, poor access to pathologic lung tissue and to specimens from fatal cases, poor diagnostic accuracy of assays (especially when testing nonpulmonary specimens), and the interpretation of results when multiple pathogens are detected in a given individual. The future of childhood pneumonia etiology research will likely require integrating data from complementary approaches, including applications of advanced molecular diagnostics and vaccine probe studies, as well as a renewed emphasis on lung aspirates from radiologically confirmed pneumonia and postmortem examinations. © The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America.

Rural-urban analyses of health-related quality of life among people with multiple sclerosis.

PubMed

Buchanan, Robert J; Zhu, Li; Schiffer, Randolph; Radin, Dagmar; James, Wesley

2008-01-01

Health-related quality of life (HRQOL) is a multi-dimensional construct including aspects of life quality or function that are affected by physical health and symptoms, psychosocial factors, and psychiatric conditions. HRQOL gives a broader measure of the burden of disease than physical impairment or disability levels. To identify factors associated with HRQOL among people with multiple sclerosis (MS) utilizing the SF-8 Health Survey. Data presented in this study were collected in a survey of 1,518 people with MS living in all 50 states. The survey sample was randomly selected from the database of the National Multiple Sclerosis Society, using ZIP codes to recruit the survey sample. A multiple linear regression model was employed to analyze the survey data, with the Physical Component Summary and the Mental Component Summary of the SF-8 the dependent variables. Independent variables were demographic characteristics, MS-disease characteristics, and health services utilized. People with MS in rural areas tended to report lower physically related HRQOL. Worsening MS symptoms were associated with reduced physical and mental dimensions of HRQOL. In addition, people with MS who received a diagnosis of depression tended to have reduced physical and mental dimensions of HRQOL. Receiving MS care at an MS clinic was associated with better physically related HRQOL, while having a neurologist as principal care physician was associated with better mental-related HRQOL. The challenge is to increase the access that people living with MS in rural areas have to MS-focused specialty care.

Informative graphing of continuous safety variables relative to normal reference limits.

PubMed

Breder, Christopher D

2018-05-16

Interpreting graphs of continuous safety variables can be complicated because differences in age, gender, and testing site methodologies data may give rise to multiple reference limits. Furthermore, data below the lower limit of normal are compressed relative to those points above the upper limit of normal. The objective of this study is to develop a graphing technique that addresses these issues and is visually intuitive. A mock dataset with multiple reference ranges is initially used to develop the graphing technique. Formulas are developed for conditions where data are above the upper limit of normal, normal, below the lower limit of normal, and below the lower limit of normal when the data value equals zero. After the formulae are developed, an anonymized dataset from an actual set of trials for an approved drug is evaluated comparing the technique developed in this study to standard graphical methods. Formulas are derived for the novel graphing method based on multiples of the normal limits. The formula for values scaled between the upper and lower limits of normal is a novel application of a readily available scaling formula. The formula for the lower limit of normal is novel and addresses the issue of this value potentially being indeterminate when the result to be scaled as a multiple is zero. The formulae and graphing method described in this study provides a visually intuitive method to graph continuous safety data including laboratory values, vital sign data.

Prognostic factors versus markers of response to treatment versus surrogate endpoints: Three different concepts.

PubMed

Sormani, Maria Pia

2017-03-01

Multiple sclerosis is a highly heterogeneous disease; the quantitative assessment of disease progression is problematic for many reasons, including the lack of objective methods to measure disability and the long follow-up times needed to detect relevant and stable changes. For these reasons, the importance of prognostic markers, markers of response to treatments and of surrogate endpoints, is crucial in multiple sclerosis research. Aim of this report is to clarify some basic definitions and methodological issues about baseline factors to be considered prognostic markers or markers of response to treatment; to define the dynamic role that variables must have to be considered surrogate markers in relation to specific treatments.

Global methane and nitrous oxide emissions from terrestrial ecosystems due to multiple environmental changes

DOE PAGES

Tian, Hanqin; Chen, Guangsheng; Lu, Chaoqun; ...

2015-03-16

Greenhouse gas (GHG)-induced climate change is among the most pressing sustainability challenges facing humanity today, posing serious risks for ecosystem health. Methane (CH 4) and nitrous oxide (N 2O) are the two most important GHGs after carbon dioxide (CO 2), but their regional and global budgets are not well known. In this paper, we applied a process-based coupled biogeochemical model to concurrently estimate the magnitude and spatial and temporal patterns of CH 4 and N 2O fluxes as driven by multiple environmental changes, including climate variability, rising atmospheric CO 2, increasing nitrogen deposition, tropospheric ozone pollution, land use change, andmore » nitrogen fertilizer use.« less

Dynamic modal estimation using instrumental variables

NASA Technical Reports Server (NTRS)

Salzwedel, H.

1980-01-01

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

Nonparametric Bayesian Multiple Imputation for Incomplete Categorical Variables in Large-Scale Assessment Surveys

ERIC Educational Resources Information Center

Si, Yajuan; Reiter, Jerome P.

2013-01-01

In many surveys, the data comprise a large number of categorical variables that suffer from item nonresponse. Standard methods for multiple imputation, like log-linear models or sequential regression imputation, can fail to capture complex dependencies and can be difficult to implement effectively in high dimensions. We present a fully Bayesian,…

Predicting probability of occurrence and factors affecting distribution and abundance of three Ozark endemic crayfish species at multiple spatial scales

USGS Publications Warehouse

Nolen, Matthew S.; Magoulick, Daniel D.; DiStefano, Robert J.; Imhoff, Emily M.; Wagner, Brian K.

2014-01-01

We found that a range of environmental variables were important in predicting crayfish distribution and abundance at multiple spatial scales and their importance was species-, response variable- and scale dependent. We would encourage others to examine the influence of spatial scale on species distribution and abundance patterns.

Latent Variable Regression 4-Level Hierarchical Model Using Multisite Multiple-Cohorts Longitudinal Data. CRESST Report 801

ERIC Educational Resources Information Center

Choi, Kilchan

2011-01-01

This report explores a new latent variable regression 4-level hierarchical model for monitoring school performance over time using multisite multiple-cohorts longitudinal data. This kind of data set has a 4-level hierarchical structure: time-series observation nested within students who are nested within different cohorts of students. These…

Stable carbon isotope fractionation of chlorinated ethenes by a microbial consortium containing multiple dechlorinating genes.

PubMed

Liu, Na; Ding, Longzhen; Li, Haijun; Zhang, Pengpeng; Zheng, Jixing; Weng, Chih-Huang

2018-08-01

The study aimed to determine the possible contribution of specific growth conditions and community structures to variable carbon enrichment factors (Ɛ- carbon ) values for the degradation of chlorinated ethenes (CEs) by a bacterial consortium with multiple dechlorinating genes. Ɛ- carbon values for trichloroethylene, cis-1,2-dichloroethylene, and vinyl chloride were -7.24% ± 0.59%, -14.6% ± 1.71%, and -21.1% ± 1.14%, respectively, during their degradation by a microbial consortium containing multiple dechlorinating genes including tceA and vcrA. The Ɛ- carbon values of all CEs were not greatly affected by changes in growth conditions and community structures, which directly or indirectly affected reductive dechlorination of CEs by this consortium. Stability analysis provided evidence that the presence of multiple dechlorinating genes within a microbial consortium had little effect on carbon isotope fractionation, as long as the genes have definite, non-overlapping functions. Copyright © 2018 Elsevier Ltd. All rights reserved.

Multiple balance tests improve the assessment of postural stability in subjects with Parkinson's disease

PubMed Central

Jacobs, J V; Horak, F B; Tran, V K; Nutt, J G

2006-01-01

Objectives Clinicians often base the implementation of therapies on the presence of postural instability in subjects with Parkinson's disease (PD). These decisions are frequently based on the pull test from the Unified Parkinson's Disease Rating Scale (UPDRS). We sought to determine whether combining the pull test, the one‐leg stance test, the functional reach test, and UPDRS items 27–29 (arise from chair, posture, and gait) predicts balance confidence and falling better than any test alone. Methods The study included 67 subjects with PD. Subjects performed the one‐leg stance test, the functional reach test, and the UPDRS motor exam. Subjects also responded to the Activities‐specific Balance Confidence (ABC) scale and reported how many times they fell during the previous year. Regression models determined the combination of tests that optimally predicted mean ABC scores or categorised fall frequency. Results When all tests were included in a stepwise linear regression, only gait (UPDRS item 29), the pull test (UPDRS item 30), and the one‐leg stance test, in combination, represented significant predictor variables for mean ABC scores (r2 = 0.51). A multinomial logistic regression model including the one‐leg stance test and gait represented the model with the fewest significant predictor variables that correctly identified the most subjects as fallers or non‐fallers (85% of subjects were correctly identified). Conclusions Multiple balance tests (including the one‐leg stance test, and the gait and pull test items of the UPDRS) that assess different types of postural stress provide an optimal assessment of postural stability in subjects with PD. PMID:16484639

The impact of 14-nm photomask uncertainties on computational lithography solutions

NASA Astrophysics Data System (ADS)

Sturtevant, John; Tejnil, Edita; Lin, Tim; Schultze, Steffen; Buck, Peter; Kalk, Franklin; Nakagawa, Kent; Ning, Guoxiang; Ackmann, Paul; Gans, Fritz; Buergel, Christian

2013-04-01

Computational lithography solutions rely upon accurate process models to faithfully represent the imaging system output for a defined set of process and design inputs. These models, which must balance accuracy demands with simulation runtime boundary conditions, rely upon the accurate representation of multiple parameters associated with the scanner and the photomask. While certain system input variables, such as scanner numerical aperture, can be empirically tuned to wafer CD data over a small range around the presumed set point, it can be dangerous to do so since CD errors can alias across multiple input variables. Therefore, many input variables for simulation are based upon designed or recipe-requested values or independent measurements. It is known, however, that certain measurement methodologies, while precise, can have significant inaccuracies. Additionally, there are known errors associated with the representation of certain system parameters. With shrinking total CD control budgets, appropriate accounting for all sources of error becomes more important, and the cumulative consequence of input errors to the computational lithography model can become significant. In this work, we examine with a simulation sensitivity study, the impact of errors in the representation of photomask properties including CD bias, corner rounding, refractive index, thickness, and sidewall angle. The factors that are most critical to be accurately represented in the model are cataloged. CD Bias values are based on state of the art mask manufacturing data and other variables changes are speculated, highlighting the need for improved metrology and awareness.

MHC variability in heritage breeds of chickens.

PubMed

Fulton, J E; Lund, A R; McCarron, A M; Pinegar, K N; Korver, D R; Classen, H L; Aggrey, S; Utterbach, C; Anthony, N B; Berres, M E

2016-02-01

The chicken Major Histocompatibility Complex (MHC) is very strongly associated with disease resistance and thus is a very important region of the chicken genome. Historically, MHC (B locus) has been identified by the use of serology with haplotype specific alloantisera. These antisera can be difficult to produce and frequently cross-react with multiple haplotypes and hence their application is generally limited to inbred and MHC-defined lines. As a consequence, very little information about MHC variability in heritage chicken breeds is available. DNA-based methods are now available for examining MHC variability in these previously uncharacterized populations. A high density SNP panel consisting of 101 SNP that span a 230,000 bp region of the chicken MHC was used to examine MHC variability in 17 heritage populations of chickens from five universities from Canada and the United States. The breeds included 6 heritage broiler lines, 3 Barred Plymouth Rock, 2 New Hampshire and one each of Rhode Island Red, Light Sussex, White Leghorn, Dark Brown Leghorn, and 2 synthetic lines. These heritage breeds contained from one to 11 haplotypes per line. A total of 52 unique MHC haplotypes were found with only 10 of them identical to serologically defined haplotypes. Furthermore, nine MHC recombinants with their respective parental haplotypes were identified. This survey confirms the value of these non-commercially utilized lines in maintaining genetic diversity. The identification of multiple MHC haplotypes and novel MHC recombinants indicates that diversity is being generated and maintained within these heritage populations. © 2016 Poultry Science Association Inc.

Differentiating incest survivors who self-mutilate.

PubMed

Turell, S C; Armsworth, M W

2000-02-01

This study was an exploratory analysis of the variables which differentiated incest survivors who self-mutilate from those who do not. A sample of women incest survivors (N = 84) were divided into two groups based on the presence or absence of self-mutilation. Participants included both community and clinical populations. A packet consisting of a demographic questionnaire, Sexual Attitudes Survey, Diagnostic Inventory of Personality and Symptoms, Dissociative Events Scale and the Beck Depression Inventory was completed by each participant. Demographic, incest, and family of origin variables distinguished the self-mutilating women from those who did not. These include ethnicity and educational experiences; duration, frequency, and perpetrator characteristics regarding the incest; and multiple abuses, instability, birth order, and loss of mother in one's family of origin. Psychological and physical health concerns also differentiated between the two groups. Many variables may differentiate between women incest survivors who self-mutilate from those who do not. A rudimentary checklist to describe the lives of incest survivors who self-mutilate resulted from these findings. The importance of the concept of embodiment is also discussed.

Multi-Constraint Multi-Variable Optimization of Source-Driven Nuclear Systems

NASA Astrophysics Data System (ADS)

Watkins, Edward Francis

1995-01-01

A novel approach to the search for optimal designs of source-driven nuclear systems is investigated. Such systems include radiation shields, fusion reactor blankets and various neutron spectrum-shaping assemblies. The novel approach involves the replacement of the steepest-descents optimization algorithm incorporated in the code SWAN by a significantly more general and efficient sequential quadratic programming optimization algorithm provided by the code NPSOL. The resulting SWAN/NPSOL code system can be applied to more general, multi-variable, multi-constraint shield optimization problems. The constraints it accounts for may include simple bounds on variables, linear constraints, and smooth nonlinear constraints. It may also be applied to unconstrained, bound-constrained and linearly constrained optimization. The shield optimization capabilities of the SWAN/NPSOL code system is tested and verified in a variety of optimization problems: dose minimization at constant cost, cost minimization at constant dose, and multiple-nonlinear constraint optimization. The replacement of the optimization part of SWAN with NPSOL is found feasible and leads to a very substantial improvement in the complexity of optimization problems which can be efficiently handled.

Overview of Key Results from SDO Extreme ultraviolet Variability Experiment (EVE)

NASA Astrophysics Data System (ADS)

Woods, Tom; Eparvier, Frank; Jones, Andrew; Mason, James; Didkovsky, Leonid; Chamberlin, Phil

2016-10-01

The SDO Extreme ultraviolet Variability Experiment (EVE) includes several channels to observe the solar extreme ultraviolet (EUV) spectral irradiance from 1 to 106 nm. These channels include the Multiple EUV Grating Spectrograph (MEGS) A, B, and P channels from the University of Colorado (CU) and the EUV SpectroPhometer (ESP) channels from the University of Southern California (USC). The solar EUV spectrum is rich in many different emission lines from the corona, transition region, and chromosphere. The EVE full-disk irradiance spectra are important for studying the solar impacts in Earth's ionosphere and thermosphere and are useful for space weather operations. In addition, the EVE observations, with its high spectral resolution of 0.1 nm and in collaboration with AIA solar EUV images, have proven valuable for studying active region evolution and explosive energy release during flares and coronal eruptions. These SDO measurements have revealed interesting results such as understanding the flare variability over all wavelengths, discovering and classifying different flare phases, using coronal dimming measurements to predict CME properties of mass and velocity, and exploring the role of nano-flares in continual heating of active regions.

A Noachian/Hesperian Hiatus and Erosive Reactivation of Martian Valley Networks

NASA Technical Reports Server (NTRS)

Irwin, R. P., III.; Maxwell, T. A.; Howard, A. D.; Craddock, R. A.; Moore, J. M.

2005-01-01

Despite new evidence for persistent flow and sedimentation on early Mars, it remains unclear whether valley networks were active over long geologic timescales (10(exp 5)-10(exp 8) yr), or if flows were persistent only during multiple discrete episodes of moderate (approx. 10(exp 4) yr) to short (<10 yr) duration. Understanding the long-term stability/variability of valley network hydrology would provide an important control on paleoclimate and groundwater models. Here we describe geologic evidence for a hiatus in highland valley network activity while the fretted terrain formed, followed by a discrete reactivation of persistent (but possibly variable) erosive flows. Additional information is included in the original extended abstract.

Datasets on hub-height wind speed comparisons for wind farms in California.

PubMed

Wang, Meina; Ullrich, Paul; Millstein, Dev

2018-08-01

This article includes the description of data information related to the research article entitled "The future of wind energy in California: Future projections with the Variable-Resolution CESM"[1], with reference number RENE_RENE-D-17-03392. Datasets from the Variable-Resolution CESM, Det Norske Veritas Germanischer Lloyd Virtual Met, MERRA-2, CFSR, NARR, ISD surface observations, and upper air sounding observations were used for calculating and comparing hub-height wind speed at multiple major wind farms across California. Information on hub-height wind speed interpolation and power curves at each wind farm sites are also presented. All datasets, except Det Norske Veritas Germanischer Lloyd Virtual Met, are publicly available for future analysis.

Replicates in high dimensions, with applications to latent variable graphical models.

PubMed

Tan, Kean Ming; Ning, Yang; Witten, Daniela M; Liu, Han

2016-12-01

In classical statistics, much thought has been put into experimental design and data collection. In the high-dimensional setting, however, experimental design has been less of a focus. In this paper, we stress the importance of collecting multiple replicates for each subject in this setting. We consider learning the structure of a graphical model with latent variables, under the assumption that these variables take a constant value across replicates within each subject. By collecting multiple replicates for each subject, we are able to estimate the conditional dependence relationships among the observed variables given the latent variables. To test the null hypothesis of conditional independence between two observed variables, we propose a pairwise decorrelated score test. Theoretical guarantees are established for parameter estimation and for this test. We show that our proposal is able to estimate latent variable graphical models more accurately than some existing proposals, and apply the proposed method to a brain imaging dataset.

Associations between period 3 gene polymorphisms and sleep- /chronotype-related variables in patients with late-life insomnia.

PubMed

Mansour, Hader A; Wood, Joel; Chowdari, Kodavali V; Tumuluru, Divya; Bamne, Mikhil; Monk, Timothy H; Hall, Martica H; Buysse, Daniel J; Nimgaonkar, Vishwajit L

2017-01-01

A variable number tandem repeat polymorphism (VNTR) in the period 3 (PER3) gene has been associated with heritable sleep and circadian variables, including self-rated chronotypes, polysomnographic (PSG) variables, insomnia and circadian sleep-wake disorders. This report describes novel molecular and clinical analyses of PER3 VNTR polymorphisms to better define their functional consequences. As the PER3 VNTR is located in the exonic (protein coding) region of PER3, we initially investigated whether both alleles (variants) are transcribed into messenger RNA in human fibroblasts. The VNTR showed bi-allelic gene expression. We next investigated genetic associations in relation to clinical variables in 274 older adult Caucasian individuals. Independent variables included genotypes for the PER3 VNTR as well as a representative set of single nucleotide polymorphisms (SNPs) that tag common variants at the PER3 locus (linkage disequilibrium (LD) between genetic variants < 0.5). In order to comprehensively evaluate variables analyzed individually in prior analyses, dependent measures included PSG total sleep time and sleep latency, self-rated chronotype, estimated with the Composite Scale (CS), and lifestyle regularity, estimated using the social rhythm metric (SRM). Initially, genetic polymorphisms were individually analyzed in relation to each outcome variable using analysis of variance (ANOVA). Nominally significant associations were further tested using regression analyses that incorporated individual ANOVA-associated DNA variants as potential predictors and each of the selected sleep/circadian variables as outcomes. The covariates included age, gender, body mass index and an index of medical co-morbidity. Significant genetic associations with the VNTR were not detected with the sleep or circadian variables. Nominally significant associations were detected between SNP rs1012477 and CS scores (p = 0.003) and between rs10462021 and SRM (p = 0.047); rs11579477 and average delta power (p = 0.043) (analyses uncorrected for multiple comparisons). In conclusion, alleles of the VNTR are expressed at the transcript level and may have a functional effect in cells expressing the PER3 gene. PER3 polymorphisms had a modest impact on selected sleep/circadian variables in our sample, suggesting that PER3 is associated with sleep and circadian function beyond VNTR polymorphisms. Further replicate analyses in larger, independent samples are recommended.

A supramolecular biomimetic skin combining a wide spectrum of mechanical properties and multiple sensory capabilities.

PubMed

Lei, Zhouyue; Wu, Peiyi

2018-03-19

Biomimetic skin-like materials, capable of adapting shapes to variable environments and sensing external stimuli, are of great significance in a wide range of applications, including artificial intelligence, soft robotics, and smart wearable devices. However, such highly sophisticated intelligence has been mainly found in natural creatures while rarely realized in artificial materials. Herein, we fabricate a type of biomimetic iontronics to imitate natural skins using supramolecular polyelectrolyte hydrogels. The dynamic viscoelastic networks provide the biomimetic skin with a wide spectrum of mechanical properties, including flexible reconfiguration ability, robust elasticity, extremely large stretchability, autonomous self-healability, and recyclability. Meanwhile, polyelectrolytes' ionic conductivity allows multiple sensory capabilities toward temperature, strain, and stress. This work provides not only insights into dynamic interactions and sensing mechanism of supramolecular iontronics, but may also promote the development of biomimetic skins with sophisticated intelligence similar to natural skins.

Cardiovascular Disease Death Before Age 65 in 168 Countries Correlated Statistically with Biometrics, Socioeconomic Status, Tobacco, Gender, Exercise, Macronutrients, and Vitamin K

PubMed Central

Agutter, Paul S

2016-01-01

Background Nutrition researchers recently recognized that deficiency of vitamin K2 (menaquinone: MK-4–MK-13) is widespread and contributes to cardiovascular disease (CVD). The deficiency of vitamin K2 or vitamin K inhibition with warfarin leads to calcium deposition in the arterial blood vessels. Methods Using publicly available sources, we collected food commodity availability data and derived nutrient profiles including vitamin K2 for people from 168 countries. We also collected female and male cohort data on early death from CVD (ages 15–64 years), insufficient physical activity, tobacco, biometric CVD risk markers, socioeconomic risk factors for CVD, and gender. The outcome measures included (1) univariate correlations of early death from CVD with each risk factor, (2) a multiple regression-derived formula relating early death from CVD (dependent variable) to macronutrient profile, vitamin K1 and K2 and other risk factors (independent variables), (3) for each risk factor appearing in the multiple regression formula, the portion of CVD risk attributable to that factor, and (4) similar univariate and multivariate analyses of body mass index (BMI), fasting blood sugar (FBS) (simulated from diabetes prevalence), systolic blood pressure (SBP), and cholesterol/ HDL-C ratio (simulated from serum cholesterol) (dependent variables) and dietary and other risk factors (independent variables). Results Female and male cohorts in countries that have vitamin K2 < 5µg per 2000 kcal/day per capita (n = 70) had about 2.2 times the rate of early CVD deaths as people in countries with > 24 µg/day of vitamin K2 per 2000 kcal/day (n = 72). A multiple regression-derived formula relating early death from CVD to dietary nutrients and other risk factors accounted for about 50% of the variance between cohorts in early CVD death. The attributable risks of the variables in the CVD early death formula were: too much alcohol (0.38%), too little vitamin K2 (6.95%), tobacco (6.87%), high blood pressure (9.01%), air pollution (9.15%), early childhood death (3.64%), poverty (7.66%), and male gender (6.13%). Conclusions Worldwide dietary vitamin K2 data derived from food commodities add much understanding to the analysis of CVD risk factors and the etiology of CVD. Vitamin K2 in food products should be systematically quantified. Public health programs should be considered to increase the intake of vitamin K2-containing fermented plant foods such as sauerkraut, miso, and natto. PMID:27688985

Cardiovascular Disease Death Before Age 65 in 168 Countries Correlated Statistically with Biometrics, Socioeconomic Status, Tobacco, Gender, Exercise, Macronutrients, and Vitamin K.

PubMed

Cundiff, David K; Agutter, Paul S

2016-08-24

Nutrition researchers recently recognized that deficiency of vitamin K2 (menaquinone: MK-4-MK-13) is widespread and contributes to cardiovascular disease (CVD). The deficiency of vitamin K2 or vitamin K inhibition with warfarin leads to calcium deposition in the arterial blood vessels. Using publicly available sources, we collected food commodity availability data and derived nutrient profiles including vitamin K2 for people from 168 countries. We also collected female and male cohort data on early death from CVD (ages 15-64 years), insufficient physical activity, tobacco, biometric CVD risk markers, socioeconomic risk factors for CVD, and gender. The outcome measures included (1) univariate correlations of early death from CVD with each risk factor, (2) a multiple regression-derived formula relating early death from CVD (dependent variable) to macronutrient profile, vitamin K1 and K2 and other risk factors (independent variables), (3) for each risk factor appearing in the multiple regression formula, the portion of CVD risk attributable to that factor, and (4) similar univariate and multivariate analyses of body mass index (BMI), fasting blood sugar (FBS) (simulated from diabetes prevalence), systolic blood pressure (SBP), and cholesterol/ HDL-C ratio (simulated from serum cholesterol) (dependent variables) and dietary and other risk factors (independent variables). Female and male cohorts in countries that have vitamin K2 < 5µg per 2000 kcal/day per capita (n = 70) had about 2.2 times the rate of early CVD deaths as people in countries with > 24 µg/day of vitamin K2 per 2000 kcal/day (n = 72). A multiple regression-derived formula relating early death from CVD to dietary nutrients and other risk factors accounted for about 50% of the variance between cohorts in early CVD death. The attributable risks of the variables in the CVD early death formula were: too much alcohol (0.38%), too little vitamin K2 (6.95%), tobacco (6.87%), high blood pressure (9.01%), air pollution (9.15%), early childhood death (3.64%), poverty (7.66%), and male gender (6.13%). Worldwide dietary vitamin K2 data derived from food commodities add much understanding to the analysis of CVD risk factors and the etiology of CVD. Vitamin K2 in food products should be systematically quantified. Public health programs should be considered to increase the intake of vitamin K2-containing fermented plant foods such as sauerkraut, miso, and natto.

Depression and literacy are important factors for missed appointments.

PubMed

Miller-Matero, Lisa Renee; Clark, Kalin Burkhardt; Brescacin, Carly; Dubaybo, Hala; Willens, David E

2016-09-01

Multiple variables are related to missed clinic appointments. However, the prevalence of missed appointments is still high suggesting other factors may play a role. The purpose of this study was to investigate the relationship between missed appointments and multiple variables simultaneously across a health care system, including patient demographics, psychiatric symptoms, cognitive functioning and literacy status. Chart reviews were conducted on 147 consecutive patients who were seen by a primary care psychologist over a six month period and completed measures to determine levels of depression, anxiety, sleep, cognitive functioning and health literacy. Demographic information and rates of missed appointments were also collected from charts. The average rate of missed appointments was 15.38%. In univariate analyses, factors related to higher rates of missed appointments included younger age (p = .03), lower income (p = .05), probable depression (p = .05), sleep difficulty (p = .05) and limited reading ability (p = .003). There were trends for a higher rate of missed appointments for patients identifying as black (p = .06), government insurance (p = .06) and limited math ability (p = .06). In a multivariate model, probable depression (p = .02) and limited reading ability (p = .003) were the only independent predictors. Depression and literacy status may be the most important factors associated with missed appointments. Implications are discussed including regular screening for depression and literacy status as well as interventions that can be utilized to help improve the rate of missed appointments.

Treatment integrity of school-based interventions with children in the journal of applied behavior analysis 1991-2005.

PubMed

McIntyre, Laura Lee; Gresham, Frank M; DiGennaro, Florence D; Reed, Derek D

2007-01-01

We reviewed all school-based experimental studies with individuals 0 to 18 years published in the Journal of Applied Behavior Analysis (JABA) between 1991 and 2005. A total of 142 articles (152 studies) that met review criteria were included. Nearly all (95%) of these experiments provided an operational definition of the independent variable, but only 30% of the studies provided treatment integrity data. Nearly half of studies (45%) were judged to be at high risk for treatment inaccuracies. Treatment integrity data were more likely to be included in studies that used teachers, multiple treatment agents, or both. Although there was a substantial increase in reporting operational definitions of independent variables, results suggest that there was only a modest improvement in reported integrity over the past 30 years of JABA studies. Recommendations for research and practice are discussed.

Cardiorespiratory interaction with continuous positive airway pressure

PubMed Central

Bonafini, Sara; Fava, Cristiano; Steier, Joerg

2018-01-01

The treatment of choice for obstructive sleep apnoea (OSA) is continuous positive airway pressure therapy (CPAP). Since its introduction in clinical practice, CPAP has been used in various clinical conditions with variable and heterogeneous outcomes. In addition to the well-known effects on the upper airway CPAP impacts on intrathoracic pressures, haemodynamics and blood pressure (BP) control. However, short- and long-term effects of CPAP therapy depend on multiple variables which include symptoms, underlying condition, pressure used, treatment acceptance, compliance and usage. CPAP can alter long-term cardiovascular risk in patients with cardiorespiratory conditions. Furthermore, the effect of CPAP on the awake patient differs from the effect on the patients while asleep, and this might contribute to discomfort and removal of the use interface. The purpose of this review is to highlight the physiological impact of CPAP on the cardiorespiratory system, including short-term benefits and long-term outcomes. PMID:29445529

Apparatus and method for variable angle slant hole collimator

DOEpatents

Lee, Seung Joon; Kross, Brian J.; McKisson, John E.

2017-07-18

A variable angle slant hole (VASH) collimator for providing collimation of high energy photons such as gamma rays during radiological imaging of humans. The VASH collimator includes a stack of multiple collimator leaves and a means of quickly aligning each leaf to provide various projection angles. Rather than rotate the detector around the subject, the VASH collimator enables the detector to remain stationary while the projection angle of the collimator is varied for tomographic acquisition. High collimator efficiency is achieved by maintaining the leaves in accurate alignment through the various projection angles. Individual leaves include unique angled cuts to maintain a precise target collimation angle. Matching wedge blocks driven by two actuators with twin-lead screws accurately position each leaf in the stack resulting in the precise target collimation angle. A computer interface with the actuators enables precise control of the projection angle of the collimator.

Intrauterine Linear Echogenicities in the Gravid Uterus: What Radiologists Should Know.

PubMed

Jensen, Kyle K; Oh, Karen Y; Kennedy, Anne M; Sohaey, Roya

2018-01-01

Intrauterine linear echogenicity (ILE) is a common ultrasonographic finding in the gravid uterus and has variable causes and variable maternal and fetal outcomes. Correctly categorizing ILE during pregnancy is crucial for guiding surveillance and advanced imaging strategies. Common causes of ILE include membranes in multiple gestations, uterine synechiae with amniotic sheets, and uterine duplication anomalies. Less common causes include circumvallate placenta, chorioamniotic separation, and hemorrhage between membranes. Amniotic band syndrome is a rare but important diagnosis to consider, as it causes severe fetal defects. Imaging findings enable body stalk anomaly, a lethal defect, to be distinguished from amniotic bands, which although destructive are not necessarily lethal. This review describes the key imaging findings used to differentiate the various types of ILE in pregnancy, thus enabling accurate diagnosis and appropriate patient counseling. Online supplemental material is available for this article. © RSNA, 2018.

Multi-hazard Assessment and Scenario Toolbox (MhAST): A Framework for Analyzing Compounding Effects of Multiple Hazards

NASA Astrophysics Data System (ADS)

Sadegh, M.; Moftakhari, H.; AghaKouchak, A.

2017-12-01

Many natural hazards are driven by multiple forcing variables, and concurrence/consecutive extreme events significantly increases risk of infrastructure/system failure. It is a common practice to use univariate analysis based upon a perceived ruling driver to estimate design quantiles and/or return periods of extreme events. A multivariate analysis, however, permits modeling simultaneous occurrence of multiple forcing variables. In this presentation, we introduce the Multi-hazard Assessment and Scenario Toolbox (MhAST) that comprehensively analyzes marginal and joint probability distributions of natural hazards. MhAST also offers a wide range of scenarios of return period and design levels and their likelihoods. Contribution of this study is four-fold: 1. comprehensive analysis of marginal and joint probability of multiple drivers through 17 continuous distributions and 26 copulas, 2. multiple scenario analysis of concurrent extremes based upon the most likely joint occurrence, one ruling variable, and weighted random sampling of joint occurrences with similar exceedance probabilities, 3. weighted average scenario analysis based on a expected event, and 4. uncertainty analysis of the most likely joint occurrence scenario using a Bayesian framework.

A Population-Based Study on Alcohol and High-Risk Sexual Behaviors in Botswana

PubMed Central

Weiser, Sheri D; Leiter, Karen; Heisler, Michele; McFarland, Willi; Korte, Fiona Percy-de; DeMonner, Sonya M; Tlou, Sheila; Phaladze, Nthabiseng; Iacopino, Vincent; Bangsberg, David R

2006-01-01

Background In Botswana, an estimated 24% of adults ages 15–49 years are infected with HIV. While alcohol use is strongly associated with HIV infection in Africa, few population-based studies have characterized the association of alcohol use with specific high-risk sexual behaviors. Methods and Findings We conducted a cross-sectional, population-based study of 1,268 adults from five districts in Botswana using a stratified two-stage probability sample design. Multivariate logistic regression was used to assess correlates of heavy alcohol consumption (>14 drinks/week for women, and >21 drinks/week for men) as a dependent variable. We also assessed gender-specific associations between alcohol use as a primary independent variable (categorized as none, moderate, problem and heavy drinking) and several risky sex outcomes including: (a) having unprotected sex with a nonmonogamous partner; (b) having multiple sexual partners; and (c) paying for or selling sex in exchange for money or other resources. Criteria for heavy drinking were met by 31% of men and 17% of women. Adjusted correlates of heavy alcohol use included male gender, intergenerational relationships (age gap ≥10 y), higher education, and living with a sexual partner. Among men, heavy alcohol use was associated with higher odds of all risky sex outcomes examined, including unprotected sex (AOR = 3.48; 95% confidence interval [CI], 1.65 to 7.32), multiple partners (AOR = 3.08; 95% CI, 1.95 to 4.87), and paying for sex (AOR = 3.65; 95% CI, 2.58 to 12.37). Similarly, among women, heavy alcohol consumption was associated with higher odds of unprotected sex (AOR = 3.28; 95% CI, 1.71 to 6.28), multiple partners (AOR = 3.05; 95% CI, 1.83 to 5.07), and selling sex (AOR = 8.50; 95% CI, 3.41 to 21.18). A dose-response relationship was seen between alcohol use and risky sexual behaviors, with moderate drinkers at lower risk than both problem and heavy drinkers. Conclusions Alcohol use is associated with multiple risks for HIV transmission among both men and women. The findings of this study underscore the need to integrate alcohol abuse and HIV prevention efforts in Botswana and elsewhere. PMID:17032060

Visual analytics of large multidimensional data using variable binned scatter plots

NASA Astrophysics Data System (ADS)

Hao, Ming C.; Dayal, Umeshwar; Sharma, Ratnesh K.; Keim, Daniel A.; Janetzko, Halldór

2010-01-01

The scatter plot is a well-known method of visualizing pairs of two-dimensional continuous variables. Multidimensional data can be depicted in a scatter plot matrix. They are intuitive and easy-to-use, but often have a high degree of overlap which may occlude a significant portion of data. In this paper, we propose variable binned scatter plots to allow the visualization of large amounts of data without overlapping. The basic idea is to use a non-uniform (variable) binning of the x and y dimensions and plots all the data points that fall within each bin into corresponding squares. Further, we map a third attribute to color for visualizing clusters. Analysts are able to interact with individual data points for record level information. We have applied these techniques to solve real-world problems on credit card fraud and data center energy consumption to visualize their data distribution and cause-effect among multiple attributes. A comparison of our methods with two recent well-known variants of scatter plots is included.

The annual cycles of phytoplankton biomass

USGS Publications Warehouse

Winder, M.; Cloern, J.E.

2010-01-01

Terrestrial plants are powerful climate sentinels because their annual cycles of growth, reproduction and senescence are finely tuned to the annual climate cycle having a period of one year. Consistency in the seasonal phasing of terrestrial plant activity provides a relatively low-noise background from which phenological shifts can be detected and attributed to climate change. Here, we ask whether phytoplankton biomass also fluctuates over a consistent annual cycle in lake, estuarine-coastal and ocean ecosystems and whether there is a characteristic phenology of phytoplankton as a consistent phase and amplitude of variability. We compiled 125 time series of phytoplankton biomass (chloro-phyll a concentration) from temperate and subtropical zones and used wavelet analysis to extract their dominant periods of variability and the recurrence strength at those periods. Fewer than half (48%) of the series had a dominant 12-month period of variability, commonly expressed as the canonical spring-bloom pattern. About 20 per cent had a dominant six-month period of variability, commonly expressed as the spring and autumn or winter and summer blooms of temperate lakes and oceans. These annual patterns varied in recurrence strength across sites, and did not persist over the full series duration at some sites. About a third of the series had no component of variability at either the six-or 12-month period, reflecting a series of irregular pulses of biomass. These findings show that there is high variability of annual phytoplankton cycles across ecosystems, and that climate-driven annual cycles can be obscured by other drivers of population variability, including human disturbance, aperiodic weather events and strong trophic coupling between phytoplankton and their consumers. Regulation of phytoplankton biomass by multiple processes operating at multiple time scales adds complexity to the challenge of detecting climate-driven trends in aquatic ecosystems where the noise to signal ratio is high. ?? 2010 The Royal Society.

Prediction of rectal temperature using non-invasive physiologic variable measurements in hair pregnant ewes subjected to natural conditions of heat stress.

PubMed

Vicente-Pérez, Ricardo; Avendaño-Reyes, Leonel; Mejía-Vázquez, Ángel; Álvarez-Valenzuela, F Daniel; Correa-Calderón, Abelardo; Mellado, Miguel; Meza-Herrera, Cesar A; Guerra-Liera, Juan E; Robinson, P H; Macías-Cruz, Ulises

2016-01-01

Rectal temperature (RT) is the foremost physiological variable indicating if an animal is suffering hyperthermia. However, this variable is traditionally measured by invasive methods, which may compromise animal welfare. Models to predict RT have been developed for growing pigs and lactating dairy cows, but not for pregnant heat-stressed ewes. Our aim was to develop a prediction equation for RT using non-invasive physiological variables in pregnant ewes under heat stress. A total of 192 records of respiratory frequency (RF) and hair coat temperature in various body regions (i.e., head, rump, flank, shoulder, and belly) obtained from 24 Katahdin × Pelibuey pregnant multiparous ewes were collected during the last third of gestation (i.e., d 100 to lambing) with a 15 d sampling interval. Hair coat temperatures were taken using infrared thermal imaging technology. Initially, a Pearson correlation analysis examined the relationship among variables, and then multiple linear regression analysis was used to develop the prediction equations. All predictor variables were positively correlated (P<0.01; r=0.59-0.67) with RT. The adjusted equation which best predicted RT (P<0.01; Radj(2)=56.15%; CV=0.65%) included as predictors RF and head and belly temperatures. Comparison of predicted and observed values for RT indicates a suitable agreement (P<0.01) between them with moderate accuracy (Radj(2)=56.15%) when RT was calculated with the adjusted equation. In general, the final equation does not violate any assumption of multiple regression analysis. The RT in heat-stressed pregnant ewes can be predicted with an adequate accuracy using non-invasive physiologic variables, and the final equation was: RT=35.57+0.004 (RF)+0.067 (heat temperature)+0.028 (belly temperature). Copyright © 2015 Elsevier Ltd. All rights reserved.

BIOPHYSICAL CHARACTERISATION OF THE UNDER-APPRECIATED AND IMPORTANT RELATIONSHIP BETWEEN HEART RATE VARIABILITY AND HEART RATE

PubMed Central

Monfredi, Oliver; Lyashkov, Alexey E; Johnsen, Anne-Berit; Inada, Shin; Schneider, Heiko; Wang, Ruoxi; Nirmalan, Mahesh; Wisloff, Ulrik; Maltsev, Victor A; Lakatta, Edward G; Zhang, Henggui; Boyett, Mark R

2014-01-01

Heart rate variability (beat-to-beat changes in the RR interval) has attracted considerable attention over the last 30+ years (PubMed currently lists >17,000 publications). Clinically, a decrease in heart rate variability is correlated to higher morbidity and mortality in diverse conditions, from heart disease to foetal distress. It is usually attributed to fluctuation in cardiac autonomic nerve activity. We calculated heart rate variability parameters from a variety of cardiac preparations (including humans, living animals, Langendorff-perfused heart and single sinoatrial nodal cell) in diverse species, combining this with data from previously published papers. We show that regardless of conditions, there is a universal exponential decay-like relationship between heart rate variability and heart rate. Using two biophysical models, we develop a theory for this, and confirm that heart rate variability is primarily dependent on heart rate and cannot be used in any simple way to assess autonomic nerve activity to the heart. We suggest that the correlation between a change in heart rate variability and altered morbidity and mortality is substantially attributable to the concurrent change in heart rate. This calls for re-evaluation of the findings from many papers that have not adjusted properly or at all for heart rate differences when comparing heart rate variability in multiple circumstances. PMID:25225208

The Effects of Sexual Partnerships and Relationship Characteristics on Three Sexual Risk Variables in Young Men Who Have Sex with Men

PubMed Central

Newcomb, Michael E.; Ryan, Daniel T.; Garofalo, Robert; Mustanski, Brian

2014-01-01

Young men who have sex with men (YMSM) in the United States are experiencing an alarming increase in HIV incidence. Recent evidence suggests that the majority of new HIV infections in YMSM occur in the context of serious relationships, which underscores the importance of examining predictors of sexual risk behavior in the context of sexual partnerships, including relationship type, sexual partner characteristics, and relationship dynamics. The current study aimed to evaluate relationship and sexual partnership influences on sexual risk behavior in YMSM, including differentiating between multiple sexual risk variables (i.e., any unprotected anal or vaginal intercourse, unprotected insertive anal or vaginal intercourse, and unprotected receptive anal intercourse). More serious/familiar partnerships were associated with more sexual risk across all three risk variables, while wanting a relationship to last was protective against risk across all three risk variables. Some variables were differentially linked to unprotected insertive sex (partner gender) or unprotected receptive sex (partner age, partner race, believing a partner was having sex with others, and partners repeated across waves). Sexual risk behavior in YMSM is inconsistent across sexual partnerships and appears to be determined in no small part by sexual partner characteristics, relationship dynamics, and sexual role (i.e., insertive or receptive partner). These influences are critical in understanding sexual risk in YMSM and provide important targets for intervention. PMID:24217953

Effects of gestational length, gender, postnatal age, and birth order on visual contrast sensitivity in infants.

PubMed

Dobkins, Karen R; Bosworth, Rain G; McCleery, Joseph P

2009-09-30

To investigate effects of visual experience versus preprogrammed mechanisms on visual development, we used multiple regression analysis to determine the extent to which a variety of variables (that differ in the extent to which they are tied to visual experience) predict luminance and chromatic (red/green) contrast sensitivity (CS), which are mediated by the magnocellular (M) and parvocellular (P) subcortical pathways, respectively. Our variables included gestational length (GL), birth weight (BW), gender, postnatal age (PNA), and birth order (BO). Two-month-olds (n = 60) and 6-month-olds (n = 122) were tested. Results revealed that (1) at 2 months, infants with longer GL have higher luminance CS; (2) at both ages, CS significantly increases over a approximately 21-day range of PNA, but this effect is stronger in 2- than 6-month-olds and stronger for chromatic than luminance CS; (3) at 2 months, boys have higher luminance CS than girls; and (4) at 2 months, firstborn infants have higher CS, while at 6 months, non-firstborn infants have higher CS. The results for PNA/GL are consistent with the possibility that P pathway development is more influenced by variables tied to visual experience (PNA), while M pathway development is more influenced by variables unrelated to visual experience (GL). Other variables, including prenatal environment, are also discussed.

The effects of sexual partnership and relationship characteristics on three sexual risk variables in young men who have sex with men.

PubMed

Newcomb, Michael E; Ryan, Daniel T; Garofalo, Robert; Mustanski, Brian

2014-01-01

Young men who have sex with men (YMSM) in the United States are experiencing an alarming increase in HIV incidence. Recent evidence suggests that the majority of new HIV infections in YMSM occur in the context of serious relationships, which underscores the importance of examining predictors of sexual risk behavior in the context of sexual partnerships, including relationship type, sexual partner characteristics, and relationship dynamics. The current study aimed to evaluate relationship and sexual partnership influences on sexual risk behavior in YMSM, including differentiating between multiple sexual risk variables (i.e., any unprotected anal or vaginal intercourse, unprotected insertive anal or vaginal intercourse, and unprotected receptive anal intercourse). More serious/familiar partnerships were associated with more sexual risk across all three risk variables, while wanting a relationship to last was protective against risk across all three risk variables. Some variables were differentially linked to unprotected insertive sex (partner gender) or unprotected receptive sex (partner age, partner race, believing a partner was having sex with others, and partners repeated across waves). Sexual risk behavior in YMSM is inconsistent across sexual partnerships and appears to be determined in no small part by sexual partner characteristics, relationship dynamics, and sexual role (i.e., insertive or receptive partner). These influences are critical in understanding sexual risk in YMSM and provide important targets for intervention.

Effects of gestational length, gender, postnatal age, and birth order on visual contrast sensitivity in infants

PubMed Central

Dobkins, Karen R.; Bosworth, Rain G.; McCleery, Joseph P.

2010-01-01

To investigate effects of visual experience versus preprogrammed mechanisms on visual development, we used multiple regression analysis to determine the extent to which a variety of variables (that differ in the extent to which they are tied to visual experience) predict luminance and chromatic (red/green) contrast sensitivity (CS), which are mediated by the magnocellular (M) and parvocellular (P) subcortical pathways, respectively. Our variables included gestational length (GL), birth weight (BW), gender, postnatal age (PNA), and birth order (BO). Two-month-olds (n = 60) and 6-month-olds (n = 122) were tested. Results revealed that (1) at 2 months, infants with longer GL have higher luminance CS; (2) at both ages, CS significantly increases over a ~21-day range of PNA, but this effect is stronger in 2- than 6-month-olds and stronger for chromatic than luminance CS; (3) at 2 months, boys have higher luminance CS than girls; and (4) at 2 months, firstborn infants have higher CS, while at 6 months, non-firstborn infants have higher CS. The results for PNA/GL are consistent with the possibility that P pathway development is more influenced by variables tied to visual experience (PNA), while M pathway development is more influenced by variables unrelated to visual experience (GL). Other variables, including prenatal environment, are also discussed. PMID:19810800

Blaming the helpers: the marginalization of teachers and parents of the urban poor.

PubMed

Farber, B A; Azar, S T

1999-10-01

The nature and origins of the current tendency toward disparaging parents and teachers of the urban poor are examined. It is suggested that the influence of parents and teachers must be understood in the context of multiple intervening variables. Several explanations are offered for the phenomenon of blame, including the fact that women constitute the great majority of teachers and are often the primary agents of parenting.

Results of the 2008 AORN Salary Survey.

PubMed

Bacon, Donald

2008-12-01

AORN conducted its sixth annual compensation survey for perioperative nurses in August of 2008. A multiple regression model was used to examine how a variety of variables including job title, education level, certification, experience, and geographic region affect nursing compensation. Comparisons between the 2008 and previous years' data are presented. The effects of other forms of compensation, such as on-call compensation, overtime, bonuses, and shift differentials on average base compensation rates also are examined.

Collaborative Research: Process-resolving Decomposition of the Global Temperature Response to Modes of Low Frequency Variability in a Changing Climate

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

Cai, Ming; Deng, Yi

2015-02-06

El Niño-Southern Oscillation (ENSO) and Annular Modes (AMs) represent respectively the most important modes of low frequency variability in the tropical and extratropical circulations. The future projection of the ENSO and AM variability, however, remains highly uncertain with the state-of-the-art coupled general circulation models. A comprehensive understanding of the factors responsible for the inter-model discrepancies in projecting future changes in the ENSO and AM variability, in terms of multiple feedback processes involved, has yet to be achieved. The proposed research aims to identify sources of such uncertainty and establish a set of process-resolving quantitative evaluations of the existing predictions ofmore » the future ENSO and AM variability. The proposed process-resolving evaluations are based on a feedback analysis method formulated in Lu and Cai (2009), which is capable of partitioning 3D temperature anomalies/perturbations into components linked to 1) radiation-related thermodynamic processes such as cloud and water vapor feedbacks, 2) local dynamical processes including convection and turbulent/diffusive energy transfer and 3) non-local dynamical processes such as the horizontal energy transport in the oceans and atmosphere. Taking advantage of the high-resolution, multi-model ensemble products from the Coupled Model Intercomparison Project Phase 5 (CMIP5) soon to be available at the Lawrence Livermore National Lab, we will conduct a process-resolving decomposition of the global three-dimensional (3D) temperature (including SST) response to the ENSO and AM variability in the preindustrial, historical and future climate simulated by these models. Specific research tasks include 1) identifying the model-observation discrepancies in the global temperature response to ENSO and AM variability and attributing such discrepancies to specific feedback processes, 2) delineating the influence of anthropogenic radiative forcing on the key feedback processes operating on ENSO and AM variability and quantifying their relative contributions to the changes in the temperature anomalies associated with different phases of ENSO and AMs, and 3) investigating the linkages between model feedback processes that lead to inter-model differences in time-mean temperature projection and model feedback processes that cause inter-model differences in the simulated ENSO and AM temperature response. Through a thorough model-observation and inter-model comparison of the multiple energetic processes associated with ENSO and AM variability, the proposed research serves to identify key uncertainties in model representation of ENSO and AM variability, and investigate how the model uncertainty in predicting time-mean response is related to the uncertainty in predicting response of the low-frequency modes. The proposal is thus a direct response to the first topical area of the solicitation: Interaction of Climate Change and Low Frequency Modes of Natural Climate Variability. It ultimately supports the accomplishment of the BER climate science activity Long Term Measure (LTM): "Deliver improved scientific data and models about the potential response of the Earth's climate and terrestrial biosphere to increased greenhouse gas levels for policy makers to determine safe levels of greenhouse gases in the atmosphere."« less

Climate, soil or both? Which variables are better predictors of the distributions of Australian shrub species?

PubMed Central

Esperón-Rodríguez, Manuel; Baumgartner, John B.; Beaumont, Linda J.

2017-01-01

Background Shrubs play a key role in biogeochemical cycles, prevent soil and water erosion, provide forage for livestock, and are a source of food, wood and non-wood products. However, despite their ecological and societal importance, the influence of different environmental variables on shrub distributions remains unclear. We evaluated the influence of climate and soil characteristics, and whether including soil variables improved the performance of a species distribution model (SDM), Maxent. Methods This study assessed variation in predictions of environmental suitability for 29 Australian shrub species (representing dominant members of six shrubland classes) due to the use of alternative sets of predictor variables. Models were calibrated with (1) climate variables only, (2) climate and soil variables, and (3) soil variables only. Results The predictive power of SDMs differed substantially across species, but generally models calibrated with both climate and soil data performed better than those calibrated only with climate variables. Models calibrated solely with soil variables were the least accurate. We found regional differences in potential shrub species richness across Australia due to the use of different sets of variables. Conclusions Our study provides evidence that predicted patterns of species richness may be sensitive to the choice of predictor set when multiple, plausible alternatives exist, and demonstrates the importance of considering soil properties when modeling availability of habitat for plants. PMID:28652933

The Effect of Feedback Delay and Feedback Type on Perceptual Category Learning: The Limits of Multiple Systems

ERIC Educational Resources Information Center

Dunn, John C.; Newell, Ben R.; Kalish, Michael L.

2012-01-01

Evidence that learning rule-based (RB) and information-integration (II) category structures can be dissociated across different experimental variables has been used to support the view that such learning is supported by multiple learning systems. Across 4 experiments, we examined the effects of 2 variables, the delay between response and feedback…

The Log-Linear Cognitive Diagnostic Model (LCDM) as a Special Case of The General Diagnostic Model (GDM). Research Report. ETS RR-14-40

ERIC Educational Resources Information Center

von Davier, Matthias

2014-01-01

Diagnostic models combine multiple binary latent variables in an attempt to produce a latent structure that provides more information about test takers' performance than do unidimensional latent variable models. Recent developments in diagnostic modeling emphasize the possibility that multiple skills may interact in a conjunctive way within the…

Concept and implementation of the Globalstar mobile satellite system

NASA Technical Reports Server (NTRS)

Schindall, Joel

1995-01-01

Globalstar is a satellite-based mobile communications system which provides quality wireless communications (voice and/or data) anywhere in the world except the polar regions. The Globalstar system concept is based upon technological advancements in Low Earth Orbit (LEO) satellite technology and in cellular telephone technology, including the commercial application of Code Division Multiple Access (CDMA) technologies. The Globalstar system uses elements of CDMA and Frequency Division Multiple Access (FDMA), combined with satellite Multiple Beam Antenna (MBA) technology and advanced variable-rate vocoder technology to arrive at one of the most efficient modulation and multiple access systems ever proposed for a satellite communications system. The technology used in Globalstar includes the following techniques in obtaining high spectral efficiency and affordable cost per channel: (1) CDMA modulation with efficient power control; (2) high efficiency vocoder with voice activity factor; (3) spot beam antenna for increased gain and frequency reuse; (4) weighted satellite antenna gain for broad geographic coverage; (5) multisatellite user links (diversity) to enhance communications reliability; and (6) soft hand-off between beams and satellites. Initial launch is scheduled in 1997 and the system is scheduled to be operational in 1998. The Globalstar system utilizes frequencies in L-, S- and C-bands which have the potential to offer worldwide availability with authorization by the appropriate regulatory agencies.

Estimating basin lagtime and hydrograph-timing indexes used to characterize stormflows for runoff-quality analysis

USGS Publications Warehouse

Granato, Gregory E.

2012-01-01

A nationwide study to better define triangular-hydrograph statistics for use with runoff-quality and flood-flow studies was done by the U.S. Geological Survey (USGS) in cooperation with the Federal Highway Administration. Although the triangular hydrograph is a simple linear approximation, the cumulative distribution of stormflow with a triangular hydrograph is a curvilinear S-curve that closely approximates the cumulative distribution of stormflows from measured data. The temporal distribution of flow within a runoff event can be estimated using the basin lagtime, (which is the time from the centroid of rainfall excess to the centroid of the corresponding runoff hydrograph) and the hydrograph recession ratio (which is the ratio of the duration of the falling limb to the rising limb of the hydrograph). This report documents results of the study, methods used to estimate the variables, and electronic files that facilitate calculation of variables. Ten viable multiple-linear regression equations were developed to estimate basin lagtimes from readily determined drainage basin properties using data published in 37 stormflow studies. Regression equations using the basin lag factor (BLF, which is a variable calculated as the main-channel length, in miles, divided by the square root of the main-channel slope in feet per mile) and two variables describing development in the drainage basin were selected as the best candidates, because each equation explains about 70 percent of the variability in the data. The variables describing development are the USGS basin development factor (BDF, which is a function of the amount of channel modifications, storm sewers, and curb-and-gutter streets in a basin) and the total impervious area variable (IMPERV) in the basin. Two datasets were used to develop regression equations. The primary dataset included data from 493 sites that have values for the BLF, BDF, and IMPERV variables. This dataset was used to develop the best-fit regression equation using the BLF and BDF variables. The secondary dataset included data from 896 sites that have values for the BLF and IMPERV variables. This dataset was used to develop the best-fit regression equation using the BLF and IMPERV variables. Analysis of hydrograph recession ratios and basin characteristics for 41 sites indicated that recession ratios are random variables. Thus, recession ratios cannot be estimated quantitatively using multiple linear regression equations developed using the data available for these sites. The minimums of recession ratios for different streamgages are well characterized by a value of one. The most probable values and maximum values of recession ratios for different streamgages are, however, more variable than the minimums. The most probable values of recession ratios for the 41 streamgages analyzed ranged from 1.0 to 3.52 and had a median of 1.85. The maximum values ranged from 2.66 to 11.3 and had a median of 4.36.

Modeling a historical mountain pine beetle outbreak using Landsat MSS and multiple lines of evidence

USGS Publications Warehouse

Assal, Timothy J.; Sibold, Jason; Reich, Robin M.

2014-01-01

Mountain pine beetles are significant forest disturbance agents, capable of inducing widespread mortality in coniferous forests in western North America. Various remote sensing approaches have assessed the impacts of beetle outbreaks over the last two decades. However, few studies have addressed the impacts of historical mountain pine beetle outbreaks, including the 1970s event that impacted Glacier National Park. The lack of spatially explicit data on this disturbance represents both a major data gap and a critical research challenge in that wildfire has removed some of the evidence from the landscape. We utilized multiple lines of evidence to model forest canopy mortality as a proxy for outbreak severity. We incorporate historical aerial and landscape photos, aerial detection survey data, a nine-year collection of satellite imagery and abiotic data. This study presents a remote sensing based framework to (1) relate measurements of canopy mortality from fine-scale aerial photography to coarse-scale multispectral imagery and (2) classify the severity of mountain pine beetle affected areas using a temporal sequence of Landsat data and other landscape variables. We sampled canopy mortality in 261 plots from aerial photos and found that insect effects on mortality were evident in changes to the Normalized Difference Vegetation Index (NDVI) over time. We tested multiple spectral indices and found that a combination of NDVI and the green band resulted in the strongest model. We report a two-step process where we utilize a generalized least squares model to account for the large-scale variability in the data and a binary regression tree to describe the small-scale variability. The final model had a root mean square error estimate of 9.8% canopy mortality, a mean absolute error of 7.6% and an R2 of 0.82. The results demonstrate that a model of percent canopy mortality as a continuous variable can be developed to identify a gradient of mountain pine beetle severity on the landscape.

The performance of integrated transconductance amplifiers as variable current sources for bio-electric impedance measurements.

PubMed

Smith, D N

1992-01-01

Multiple applied current impedance measurement systems require numbers of current sources which operate simultaneously at the same frequency and within the same phase but at variable amplitudes. Investigations into the performance of some integrated operational transconductance amplifiers as variable current sources are described. Measurements of breakthrough, non-linearity and common-mode output levels for LM13600, NE5517 and CA3280 were carried out. The effects of such errors on the overall performance and stability of multiple current systems when driving floating loads are considered.

Use of Variable Pressure Suits, Intermittent Recompression and Nitrox Breathing Mixtures during Lunar Extravehicular Activities

NASA Technical Reports Server (NTRS)

Gernhardt, Michael L.; Abercromby, Andrew F.

2009-01-01

This slide presentation reviews the use of variable pressure suits, intermittent recompression and Nitrox breathing mixtures to allow for multiple short extravehicular activities (EVAs) at different locations in a day. This new operational concept of multiple short EVAs requires short purge times and shorter prebreathes to assure rapid egress with a minimal loss of the vehicular air. Preliminary analysis has begun to evaluate the potential benefits of the intermittent recompression, and Nitrox breathing mixtures when used with variable pressure suits to enable reduce purges and prebreathe durations.

Interpret with caution: multicollinearity in multiple regression of cognitive data.

PubMed

Morrison, Catriona M

2003-08-01

Shibihara and Kondo in 2002 reported a reanalysis of the 1997 Kanji picture-naming data of Yamazaki, Ellis, Morrison, and Lambon-Ralph in which independent variables were highly correlated. Their addition of the variable visual familiarity altered the previously reported pattern of results, indicating that visual familiarity, but not age of acquisition, was important in predicting Kanji naming speed. The present paper argues that caution should be taken when drawing conclusions from multiple regression analyses in which the independent variables are so highly correlated, as such multicollinearity can lead to unreliable output.

The Impact of Specific and Complex Trauma on the Mental Health of Homeless Youth.

PubMed

Wong, Carolyn F; Clark, Leslie F; Marlotte, Lauren

2016-03-01

This study investigates the relative impact of trauma experiences that occurred prior to and since becoming homeless on depressive symptoms, posttraumatic stress disorder (PTSD) symptoms, and self-injurious behaviors among a sample of homeless youth (N = 389). Youth (aged 13 to 25) who had been homeless or precariously housed in the past year completed a survey about housing history, experiences of violence and victimization, mental health, and service utilization. In addition to examining the impact associated with specific trauma types, we also considered the effect of "early-on" poly-victimization (i.e., cumulative number of reported traumas prior to homelessness) and the influence of a compound sexual trauma variable created to represent earlier complex trauma. This created-variable has values ranging from no reported trauma, single trauma, multiple non-sexual traumas, and multiple traumas that co-occurred with sexual abuse. Multivariate analyses revealed that specific traumatic experiences prior to homelessness, including sexual abuse, emotional abuse/neglect, and adverse home environment, predicted greater mental health symptoms. Poly-victimization did not add to the prediction of mental health symptoms after the inclusion of specific traumas. Results with early compound sexual trauma revealed significant differences between lower-order trauma exposures and multiple-trauma exposures. Specifically, experience of multiple traumas that co-occurred with sexual trauma was significantly more detrimental in predicting PTSD symptoms than multiple traumas of non-sexual nature. Findings support the utility of an alternate/novel conceptualization of complex trauma, and support the need to carefully evaluate complex traumatic experiences that occurred prior to homelessness, which can impact the design and implementation of mental health care and services for homeless youth. © The Author(s) 2014.

Lower extremity kinematics during walking and elliptical training in individuals with and without traumatic brain injury.

PubMed

Buster, Thad; Burnfield, Judith; Taylor, Adam P; Stergiou, Nicholas

2013-12-01

Elliptical training may be an option for practicing walking-like activity for individuals with traumatic brain injuries (TBI). Understanding similarities and differences between participants with TBI and neurologically healthy individuals during elliptical trainer use and walking may help guide clinical applications incorporating elliptical trainers. Ten participants with TBI and a comparison group of 10 neurologically healthy participants underwent 2 familiarization sessions and 1 data collection session. Kinematic data were collected as participants walked on a treadmill or on an elliptical trainer. Gait-related measures, including coefficient of multiple correlations (a measure of similarity between ensemble joint movement profiles; coefficient of multiple correlations [CMCs]), critical event joint angles, variability of peak critical event joint angles (standard deviations [SDs]) of peak critical event joint angles, and maximum Lyapunov exponents (a measure of the organization of the variability [LyEs]) were compared between groups and conditions. Coefficient of multiple correlations values comparing the similarity in ensemble motion profiles between the TBI and comparison participants exceeded 0.85 for the hip, knee, and ankle joints. The only critical event joint angle that differed significantly between participants with TBI and comparison participants was the ankle during terminal stance. Variability was higher for the TBI group (6 of 11 comparisons significant) compared with comparison participants. Hip and knee joint movement patterns of both participants with TBI and comparison participants on the elliptical trainer were similar to walking (CMCs ≥ 0.87). Variability was higher during elliptical trainer usage compared with walking (5 of 11 comparisons significant). Hip LyEs were higher during treadmill walking. Ankle LyEs were greater during elliptical trainer usage. Movement patterns of participants with TBI were similar to, but more variable than, those of comparison participants while using both the treadmill and the elliptical trainer. If incorporation of complex movements similar to walking is a goal of rehabilitation, elliptical training is a reasonable alternative to treadmill-based training.Video Abstract available (see Video, Supplemental Digital Content 1, http://links.lww.com/JNPT/A65) for more insights from the authors.

A comparison of multiple imputation methods for handling missing values in longitudinal data in the presence of a time-varying covariate with a non-linear association with time: a simulation study.

PubMed

De Silva, Anurika Priyanjali; Moreno-Betancur, Margarita; De Livera, Alysha Madhu; Lee, Katherine Jane; Simpson, Julie Anne

2017-07-25

Missing data is a common problem in epidemiological studies, and is particularly prominent in longitudinal data, which involve multiple waves of data collection. Traditional multiple imputation (MI) methods (fully conditional specification (FCS) and multivariate normal imputation (MVNI)) treat repeated measurements of the same time-dependent variable as just another 'distinct' variable for imputation and therefore do not make the most of the longitudinal structure of the data. Only a few studies have explored extensions to the standard approaches to account for the temporal structure of longitudinal data. One suggestion is the two-fold fully conditional specification (two-fold FCS) algorithm, which restricts the imputation of a time-dependent variable to time blocks where the imputation model includes measurements taken at the specified and adjacent times. To date, no study has investigated the performance of two-fold FCS and standard MI methods for handling missing data in a time-varying covariate with a non-linear trajectory over time - a commonly encountered scenario in epidemiological studies. We simulated 1000 datasets of 5000 individuals based on the Longitudinal Study of Australian Children (LSAC). Three missing data mechanisms: missing completely at random (MCAR), and a weak and a strong missing at random (MAR) scenarios were used to impose missingness on body mass index (BMI) for age z-scores; a continuous time-varying exposure variable with a non-linear trajectory over time. We evaluated the performance of FCS, MVNI, and two-fold FCS for handling up to 50% of missing data when assessing the association between childhood obesity and sleep problems. The standard two-fold FCS produced slightly more biased and less precise estimates than FCS and MVNI. We observed slight improvements in bias and precision when using a time window width of two for the two-fold FCS algorithm compared to the standard width of one. We recommend the use of FCS or MVNI in a similar longitudinal setting, and when encountering convergence issues due to a large number of time points or variables with missing values, the two-fold FCS with exploration of a suitable time window.

Solving the problem of comparing whole bacterial genomes across different sequencing platforms.

PubMed

Kaas, Rolf S; Leekitcharoenphon, Pimlapas; Aarestrup, Frank M; Lund, Ole

2014-01-01

Whole genome sequencing (WGS) shows great potential for real-time monitoring and identification of infectious disease outbreaks. However, rapid and reliable comparison of data generated in multiple laboratories and using multiple technologies is essential. So far studies have focused on using one technology because each technology has a systematic bias making integration of data generated from different platforms difficult. We developed two different procedures for identifying variable sites and inferring phylogenies in WGS data across multiple platforms. The methods were evaluated on three bacterial data sets and sequenced on three different platforms (Illumina, 454, Ion Torrent). We show that the methods are able to overcome the systematic biases caused by the sequencers and infer the expected phylogenies. It is concluded that the cause of the success of these new procedures is due to a validation of all informative sites that are included in the analysis. The procedures are available as web tools.

Multiple or familial café-au-lait spots is neurofibromatosis type 6: clarification of a diagnosis.

PubMed

Madson, Justin G

2012-05-15

A café-au-lait macule (CALM) is an evenly pigmented macule or patch of variable size. Solitary CALMs are common birthmarks in up to 2.5 percent of normal neonates and their incidence rises to up to 25 percent in preschool-aged children. Two or more CALMs occur much less frequently. Multiple lesions may warrant investigation to identify an underlying disease including neurofibromatosis types 1 (NF1), neurofibromatosis type 2, McCune-Albright syndrome, and neurofibromatosis type 1-like syndrome. Considered a hallmark and diagnostic criteria for NF1 is the presence of 6 or more CALMs greater than 0.5 cm in prepubertal individuals. Rare reports describe families which demonstrate the phenomenon of multiple CALMs without other stigmata of NF1 or evidence of other systemic disease. Herein is a description of the condition and justification for this entity to be named Neurofibromatosis type 6.

Multiple endocrine diseases in cats: 15 cases (1997-2008).

PubMed

Blois, Shauna L; Dickie, Erica L; Kruth, Stephen A; Allen, Dana G

2010-08-01

The objective of this retrospective study was to characterize a population of cats from a tertiary care center diagnosed with multiple endocrine disorders, including the specific disorders and time intervals between diagnosis of each disorder. Medical records of 15 cats diagnosed with more than one endocrine disorder were reviewed. The majority of cats were domestic shorthairs, and the mean age at the time of diagnosis of the first disorder was 10.3 years. The most common combination of disorders was diabetes mellitus and hyperthyroidism. Two cats had concurrent diabetes mellitus and hyperadrenocorticism, one cat had concurrent central diabetes insipidus and diabetes mellitus. A mean of 25.7 months elapsed between diagnoses of the first and second endocrine disorder, but this was variable. This study suggests the occurrence of multiple endocrine disorders is uncommon in cats. Copyright 2010 ISFM and AAFP. Published by Elsevier Ltd. All rights reserved.

Multiscale Framework for Assessing Critical Loads of Atmospheric Nitrogen Deposition for Aquatic Ecosystems in Wilderness Areas of the Western United States

NASA Astrophysics Data System (ADS)

Nanus, Leora; Clow, David; Saros, Jasmine; McMurray, Jill; Blett, Tamara; Sickman, James

2017-04-01

High-elevation aquatic ecosystems in Wilderness areas of the western United States are impacted by current and historic atmospheric nitrogen (N) deposition associated with local and regional air pollution. Documented effects include elevated surface water nitrate concentrations, increased algal productivity, and changes in diatom species assemblages. A predictive framework was developed for sensitive high-elevation basins across the western United States at multiple spatial scales including the Rocky Mountain Region (Rockies), the Greater Yellowstone Area (GYA), and Yosemite (YOSE) and Sequoia & Kings Canyon (SEKI) National Parks. Spatial trends in critical loads of N deposition for nutrient enrichment of aquatic ecosystems were quantified and mapped using a geostatistical approach, with modeled N deposition, topography, vegetation, geology, and climate as potential explanatory variables. Multiple predictive models were created using various combinations of explanatory variables; this approach allowed for better quantification of uncertainty and identification of areas most sensitive to high atmospheric N deposition (> 3 kg N ha-1 yr-1). For multiple spatial scales, the lowest critical loads estimates (<1.5 + 1 kg N ha-1 yr-1) occurred in high-elevation basins with steep slopes, sparse vegetation, and exposed bedrock and talus. Based on a nitrate threshold of 1 μmol L-1, estimated critical load exceedances (>1.5 + 1 kg N ha-1 yr-1) correspond with areas of high N deposition and vary spatially ranging from less than 20% to over 40% of the study area for the Rockies, GYA, YOSE, and SEKI. These predictive models and maps identify sensitive aquatic ecosystems that may be impacted by excess atmospheric N deposition and can be used to help protect against future anthropogenic disturbance. The approach presented here may be transferable to other remote and protected high-elevation ecosystems at multiple spatial scales that are sensitive to adverse effects of pollutant loading in the US and around the world.

Hyperspectral remote sensing of plant biochemistry using Bayesian model averaging with variable and band selection

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

Zhao, Kaiguang; Valle, Denis; Popescu, Sorin

2013-05-15

Model specification remains challenging in spectroscopy of plant biochemistry, as exemplified by the availability of various spectral indices or band combinations for estimating the same biochemical. This lack of consensus in model choice across applications argues for a paradigm shift in hyperspectral methods to address model uncertainty and misspecification. We demonstrated one such method using Bayesian model averaging (BMA), which performs variable/band selection and quantifies the relative merits of many candidate models to synthesize a weighted average model with improved predictive performances. The utility of BMA was examined using a portfolio of 27 foliage spectral–chemical datasets representing over 80 speciesmore » across the globe to estimate multiple biochemical properties, including nitrogen, hydrogen, carbon, cellulose, lignin, chlorophyll (a or b), carotenoid, polar and nonpolar extractives, leaf mass per area, and equivalent water thickness. We also compared BMA with partial least squares (PLS) and stepwise multiple regression (SMR). Results showed that all the biochemicals except carotenoid were accurately estimated from hyerspectral data with R2 values > 0.80.« less

[Keys to preventing accidents in children in the school context].

PubMed

Gabari Gambarte, M Inés; Sáenz Mendía, Raquel

2016-11-02

To learn about children's perception of the causes and prevention strategies involved in school accidents. The sample included 584 school children aged 8-9 years from Navarra. A mixed design was chosen by questionnaire with three open-response questions and one multiple-choice assessment. Analysis was performed in two phases: 1) qualitative development of categories and dimensions of the responses of narrative content, and 2) quantitative variables for recoding correlational analysis. 22 categories emerged, which make up three perceptual dimensions: 1) attribution of causality (5), 2) identification of mechanisms of avoidance (11), and 3) development of coping strategies (6). The correlation intra-variables portray varying degrees: on the one hand, moderate positive numbers (r>0.5) in allocating and identifying causality avoidance mechanisms and, on the other hand, high positive correlation values (r>0.7) referred to developing coping strategies. Children are able to identify accidents as a health problem. They question the multiplicity of elements involved and relate the origin and kind of accident to prevention and support mechanisms. Copyright © 2016 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

On Latent Growth Models for Composites and Their Constituents.

PubMed

Hancock, Gregory R; Mao, Xiulin; Kher, Hemant

2013-09-01

Over the last decade and a half, latent growth modeling has become an extremely popular and versatile technique for evaluating longitudinal change and its determinants. Most common among the models applied are those for a single measured variable over time. This model has been extended in a variety of ways, most relevant for the current work being the multidomain and the second-order latent growth models. Whereas the former allows for growth function characteristics to be modeled for multiple outcomes simultaneously, with the degree of growth characteristics' relations assessed within the model (e.g., cross-domain slope factor correlations), the latter models growth in latent outcomes, each of which has effect indicators repeated over time. But what if one has an outcome that is believed to be formative relative to its indicator variables rather than latent? In this case, where the outcome is a composite of multiple constituents, modeling change over time is less straightforward. This article provides analytical and applied details for simultaneously modeling growth in composites and their constituent elements, including a real data example using a general computer self-efficacy questionnaire.

MULTIPLE-LOCUS VARIABLE-NUMBER TANDEM REPEAT ANALYSIS OF BRUCELLA ISOLATES FROM THAILAND.

PubMed

Kumkrong, Khurawan; Chankate, Phanita; Tonyoung, Wittawat; Intarapuk, Apiradee; Kerdsin, Anusak; Kalambaheti, Thareerat

2017-01-01

Brucellosis-induced abortion can result in significant economic loss to farm animals. Brucellosis can be transmitted to humans during slaughter of infected animals or via consumption of contaminated food products. Strain identification of Brucella isolates can reveal the route of transmission. Brucella strains were isolated from vaginal swabs of farm animal, cow milk and from human blood cultures. Multiplex PCR was used to identify Brucella species, and owing to high DNA homology among Brucella isolates, multiple-locus variable-number tandem repeat analysis (MLVA) based on the number of tandem repeats at 16 different genomic loci was used for strain identification. Multiplex PCR categorized the isolates into B. abortus (n = 7), B. melitensis (n = 37), B. suis (n = 3), and 5 of unknown Brucella spp. MLVA-16 clustering analysis differentiated the strains into various genotypes, with Brucella isolates from the same geographic region being closely related, and revealed that the Thai isolates were phylogenetically distinct from those in other countries, including within the Southeast Asian region. Thus, MLVA-16 typing has utility in epidemiological studies.

Design of Experiments with Multiple Independent Variables: A Resource Management Perspective on Complete and Reduced Factorial Designs

PubMed Central

Collins, Linda M.; Dziak, John J.; Li, Runze

2009-01-01

An investigator who plans to conduct experiments with multiple independent variables must decide whether to use a complete or reduced factorial design. This article advocates a resource management perspective on making this decision, in which the investigator seeks a strategic balance between service to scientific objectives and economy. Considerations in making design decisions include whether research questions are framed as main effects or simple effects; whether and which effects are aliased (confounded) in a particular design; the number of experimental conditions that must be implemented in a particular design and the number of experimental subjects the design requires to maintain the desired level of statistical power; and the costs associated with implementing experimental conditions and obtaining experimental subjects. In this article four design options are compared: complete factorial, individual experiments, single factor, and fractional factorial designs. Complete and fractional factorial designs and single factor designs are generally more economical than conducting individual experiments on each factor. Although relatively unfamiliar to behavioral scientists, fractional factorial designs merit serious consideration because of their economy and versatility. PMID:19719358

Shedding subspecies: The influence of genetics on reptile subspecies taxonomy.

PubMed

Torstrom, Shannon M; Pangle, Kevin L; Swanson, Bradley J

2014-07-01

The subspecies concept influences multiple aspects of biology and management. The 'molecular revolution' altered traditional methods (morphological traits) of subspecies classification by applying genetic analyses resulting in alternative or contradictory classifications. We evaluated recent reptile literature for bias in the recommendations regarding subspecies status when genetic data were included. Reviewing characteristics of the study, genetic variables, genetic distance values and noting the species concepts, we found that subspecies were more likely elevated to species when using genetic analysis. However, there was no predictive relationship between variables used and taxonomic recommendation. There was a significant difference between the median genetic distance values when researchers elevated or collapsed a subspecies. Our review found nine different concepts of species used when recommending taxonomic change, and studies incorporating multiple species concepts were more likely to recommend a taxonomic change. Since using genetic techniques significantly alter reptile taxonomy there is a need to establish a standard method to determine the species-subspecies boundary in order to effectively use the subspecies classification for research and conservation purposes. Copyright © 2014 Elsevier Inc. All rights reserved.

Input Variability Facilitates Unguided Subcategory Learning in Adults

PubMed Central

Eidsvåg, Sunniva Sørhus; Austad, Margit; Asbjørnsen, Arve E.

2015-01-01

Purpose This experiment investigated whether input variability would affect initial learning of noun gender subcategories in an unfamiliar, natural language (Russian), as it is known to assist learning of other grammatical forms. Method Forty adults (20 men, 20 women) were familiarized with examples of masculine and feminine Russian words. Half of the participants were familiarized with 32 different root words in a high-variability condition. The other half were familiarized with 16 different root words, each repeated twice for a total of 32 presentations in a high-repetition condition. Participants were tested on untrained members of the category to assess generalization. Familiarization and testing was completed 2 additional times. Results Only participants in the high-variability group showed evidence of learning after an initial period of familiarization. Participants in the high-repetition group were able to learn after additional input. Both groups benefited when words included 2 cues to gender compared to a single cue. Conclusions The results demonstrate that the degree of input variability can influence learners' ability to generalize a grammatical subcategory (noun gender) from a natural language. In addition, the presence of multiple cues to linguistic subcategory facilitated learning independent of variability condition. PMID:25680081

Input Variability Facilitates Unguided Subcategory Learning in Adults.

PubMed

Eidsvåg, Sunniva Sørhus; Austad, Margit; Plante, Elena; Asbjørnsen, Arve E

2015-06-01

This experiment investigated whether input variability would affect initial learning of noun gender subcategories in an unfamiliar, natural language (Russian), as it is known to assist learning of other grammatical forms. Forty adults (20 men, 20 women) were familiarized with examples of masculine and feminine Russian words. Half of the participants were familiarized with 32 different root words in a high-variability condition. The other half were familiarized with 16 different root words, each repeated twice for a total of 32 presentations in a high-repetition condition. Participants were tested on untrained members of the category to assess generalization. Familiarization and testing was completed 2 additional times. Only participants in the high-variability group showed evidence of learning after an initial period of familiarization. Participants in the high-repetition group were able to learn after additional input. Both groups benefited when words included 2 cues to gender compared to a single cue. The results demonstrate that the degree of input variability can influence learners' ability to generalize a grammatical subcategory (noun gender) from a natural language. In addition, the presence of multiple cues to linguistic subcategory facilitated learning independent of variability condition.

A data-driven multiplicative fault diagnosis approach for automation processes.

PubMed

Hao, Haiyang; Zhang, Kai; Ding, Steven X; Chen, Zhiwen; Lei, Yaguo

2014-09-01

This paper presents a new data-driven method for diagnosing multiplicative key performance degradation in automation processes. Different from the well-established additive fault diagnosis approaches, the proposed method aims at identifying those low-level components which increase the variability of process variables and cause performance degradation. Based on process data, features of multiplicative fault are extracted. To identify the root cause, the impact of fault on each process variable is evaluated in the sense of contribution to performance degradation. Then, a numerical example is used to illustrate the functionalities of the method and Monte-Carlo simulation is performed to demonstrate the effectiveness from the statistical viewpoint. Finally, to show the practical applicability, a case study on the Tennessee Eastman process is presented. Copyright © 2013. Published by Elsevier Ltd.

Multiple-variable neighbourhood search for the single-machine total weighted tardiness problem

NASA Astrophysics Data System (ADS)

Chung, Tsui-Ping; Fu, Qunjie; Liao, Ching-Jong; Liu, Yi-Ting

2017-07-01

The single-machine total weighted tardiness (SMTWT) problem is a typical discrete combinatorial optimization problem in the scheduling literature. This problem has been proved to be NP hard and thus provides a challenging area for metaheuristics, especially the variable neighbourhood search algorithm. In this article, a multiple variable neighbourhood search (m-VNS) algorithm with multiple neighbourhood structures is proposed to solve the problem. Special mechanisms named matching and strengthening operations are employed in the algorithm, which has an auto-revising local search procedure to explore the solution space beyond local optimality. Two aspects, searching direction and searching depth, are considered, and neighbourhood structures are systematically exchanged. Experimental results show that the proposed m-VNS algorithm outperforms all the compared algorithms in solving the SMTWT problem.

Fall Risk Assessment Tools for Elderly Living in the Community: Can We Do Better?

PubMed

Palumbo, Pierpaolo; Palmerini, Luca; Bandinelli, Stefania; Chiari, Lorenzo

2015-01-01

Falls are a common, serious threat to the health and self-confidence of the elderly. Assessment of fall risk is an important aspect of effective fall prevention programs. In order to test whether it is possible to outperform current prognostic tools for falls, we analyzed 1010 variables pertaining to mobility collected from 976 elderly subjects (InCHIANTI study). We trained and validated a data-driven model that issues probabilistic predictions about future falls. We benchmarked the model against other fall risk indicators: history of falls, gait speed, Short Physical Performance Battery (Guralnik et al. 1994), and the literature-based fall risk assessment tool FRAT-up (Cattelani et al. 2015). Parsimony in the number of variables included in a tool is often considered a proxy for ease of administration. We studied how constraints on the number of variables affect predictive accuracy. The proposed model and FRAT-up both attained the same discriminative ability; the area under the Receiver Operating Characteristic (ROC) curve (AUC) for multiple falls was 0.71. They outperformed the other risk scores, which reported AUCs for multiple falls between 0.64 and 0.65. Thus, it appears that both data-driven and literature-based approaches are better at estimating fall risk than commonly used fall risk indicators. The accuracy-parsimony analysis revealed that tools with a small number of predictors (~1-5) were suboptimal. Increasing the number of variables improved the predictive accuracy, reaching a plateau at ~20-30, which we can consider as the best trade-off between accuracy and parsimony. Obtaining the values of these ~20-30 variables does not compromise usability, since they are usually available in comprehensive geriatric assessments.

Modelling Spatial Dependence Structures Between Climate Variables by Combining Mixture Models with Copula Models

NASA Astrophysics Data System (ADS)

Khan, F.; Pilz, J.; Spöck, G.

2017-12-01

Spatio-temporal dependence structures play a pivotal role in understanding the meteorological characteristics of a basin or sub-basin. This further affects the hydrological conditions and consequently will provide misleading results if these structures are not taken into account properly. In this study we modeled the spatial dependence structure between climate variables including maximum, minimum temperature and precipitation in the Monsoon dominated region of Pakistan. For temperature, six, and for precipitation four meteorological stations have been considered. For modelling the dependence structure between temperature and precipitation at multiple sites, we utilized C-Vine, D-Vine and Student t-copula models. For temperature, multivariate mixture normal distributions and for precipitation gamma distributions have been used as marginals under the copula models. A comparison was made between C-Vine, D-Vine and Student t-copula by observational and simulated spatial dependence structure to choose an appropriate model for the climate data. The results show that all copula models performed well, however, there are subtle differences in their performances. The copula models captured the patterns of spatial dependence structures between climate variables at multiple meteorological sites, however, the t-copula showed poor performance in reproducing the dependence structure with respect to magnitude. It was observed that important statistics of observed data have been closely approximated except of maximum values for temperature and minimum values for minimum temperature. Probability density functions of simulated data closely follow the probability density functions of observational data for all variables. C and D-Vines are better tools when it comes to modelling the dependence between variables, however, Student t-copulas compete closely for precipitation. Keywords: Copula model, C-Vine, D-Vine, Spatial dependence structure, Monsoon dominated region of Pakistan, Mixture models, EM algorithm.

Poor sleep quality and nightmares are associated with non-suicidal self-injury in adolescents.

PubMed

Liu, Xianchen; Chen, Hua; Bo, Qi-Gui; Fan, Fang; Jia, Cun-Xian

2017-03-01

Non-suicidal self-injury (NSSI) is prevalent and is associated with increased risk of suicidal behavior in adolescents. This study examined which sleep variables are associated with NSSI, independently from demographics and mental health problems in Chinese adolescents. Participants consisted of 2090 students sampled from three high schools in Shandong, China and had a mean age of 15.49 years. Participants completed a sleep and health questionnaire to report their demographic and family information, sleep duration and sleep problems, impulsiveness, hopelessness, internalizing and externalizing problems, and NSSI. A series of regression analyses were conducted to examine the associations between sleep variables and NSSI. Of the sample, 12.6 % reported having ever engaged in NSSI and 8.8 % engaged during the last year. Univariate logistic analyses demonstrated that multiple sleep variables including short sleep duration, insomnia symptoms, poor sleep quality, sleep insufficiency, unrefreshed sleep, sleep dissatisfaction, daytime sleepiness, fatigue, snoring, and nightmares were associated with increased risk of NSSI. After adjusting for demographic and mental health variables, NSSI was significantly associated with sleeping <6 h per night, poor sleep quality, sleep dissatisfaction, daytime sleepiness, and frequent nightmares. Stepwise logistic regression model demonstrated that poor sleep quality (OR = 2.18, 95 % CI = 1.37-3.47) and frequent nightmares (OR = 2.88, 95 % CI = 1.45-5.70) were significantly independently associated with NSSI. In conclusion, while multiple sleep variables are associated with NSSI, poor sleep quality and frequent nightmares are independent risk factors of NSSI. These findings may have important implications for further research of sleep self-harm mechanisms and early detection and prevention of NSSI in adolescents.

Post-cracking characteristics of high performance fiber reinforced cementitious composites

NASA Astrophysics Data System (ADS)

Suwannakarn, Supat W.

The application of high performance fiber reinforced cement composites (HPFRCC) in structural systems depends primarily on the material's tensile response, which is a direct function of fiber and matrix characteristics, the bond between them, and the fiber content or volume fraction. The objective of this dissertation is to evaluate and model the post-cracking behavior of HPFRCC. In particular, it focused on the influential parameters controlling tensile behavior and the variability associated with them. The key parameters considered include: the stress and strain at first cracking, the stress and strain at maximum post-cracking, the shape of the stress-strain or stress-elongation response, the multiple cracking process, the shape of the resistance curve after crack localization, the energy associated with the multiple cracking process, and the stress versus crack opening response of a single crack. Both steel fibers and polymeric fibers, perceived to have the greatest potential for current commercial applications, are considered. The main variables covered include fiber type (Torex, Hooked, PVA, and Spectra) and fiber volume fraction (ranging from 0.75% to 2.0%). An extensive experimental program is carried out using direct tensile tests and stress-versus crack opening displacement tests on notched tensile prisms. The key experimental results were analysed and modeled using simple prediction equations which, combined with a composite mechanics approach, allowed for predicting schematic simplified stress-strain and stress-displacement response curves for use in structural modeling. The experimental data show that specimens reinforced with Torex fibers performs best, follows by Hooked and Spectra fibers, then PVA fibers. Significant variability in key parameters was observed througout suggesting that variability must be studied further. The new information obtained can be used as input for material models for finite element analysis and can provide greater confidence in using the HPFRC composites in structural applications. It also provides a good foundation to integrate these composites in conventional structural analysis and design.

Breast cancer - one term, many entities?

PubMed

Bertos, Nicholas R; Park, Morag

2011-10-01

Breast cancer, rather than constituting a monolithic entity, comprises heterogeneous tumors with different clinical characteristics, disease courses, and responses to specific treatments. Tumor-intrinsic features, including classical histological and immunopathological classifications as well as more recently described molecular subtypes, separate breast tumors into multiple groups. Tumor-extrinsic features, including microenvironmental configuration, also have prognostic significance and further expand the list of tumor-defining variables. A better understanding of the features underlying heterogeneity, as well as of the mechanisms and consequences of their interactions, is essential to improve targeting of existing therapies and to develop novel agents addressing specific combinations of features.

Predicting Satisfaction for Unicompartmental Knee Arthroplasty Patients in an Asian Population.

PubMed

Lee, Merrill; Huang, Yilun; Chong, Hwei Chi; Ning, Yilin; Lo, Ngai Nung; Yeo, Seng Jin

2016-08-01

Despite renewed interest in unicompartmental knee arthroplasty (UKA), there is a paucity of published literature with regard to patient satisfaction after UKA within Asian populations. The purpose of this study is to identify characteristics and factors which may contribute to patient dissatisfaction after UKA in a multiracial Asian population. Seven hundred twenty-four UKAs were performed between January 2007 and April 2013. Preoperative and postoperative variables were prospectively captured, such as standardized knee scores, knee range of motion, and patient satisfaction scores. These variables were then analyzed with a multiple logistic regression model to determine statistically significant factors contributing to patients' satisfaction. Minimum duration of follow-up was 2 years, with an overall patient satisfaction rate of 92.2%. There was improvement in mean knee range of motion and across various standardized knee scores. Preoperative variables associated with patient dissatisfaction included a poorer preoperative Mental Component Summary, better preoperative knee extension, and better preoperative Oxford Knee Scores. Significant postoperative variables included better Oxford Knee Score at 6 months and Mental Component Summary at 2 years. Despite the impressive patient satisfaction rate of UKA in this Asian population, these findings suggest that there is a targeted group of patients with select preoperative factors who would benefit from preoperative counseling. Copyright © 2016 Elsevier Inc. All rights reserved.

How to induce multiple delays in coupled chaotic oscillators?

NASA Astrophysics Data System (ADS)

Bhowmick, Sourav K.; Ghosh, Dibakar; Roy, Prodyot K.; Kurths, Jürgen; Dana, Syamal K.

2013-12-01

Lag synchronization is a basic phenomenon in mismatched coupled systems, delay coupled systems, and time-delayed systems. It is characterized by a lag configuration that identifies a unique time shift between all pairs of similar state variables of the coupled systems. In this report, an attempt is made how to induce multiple lag configurations in coupled systems when different pairs of state variables attain different time shift. A design of coupling is presented to realize this multiple lag synchronization. Numerical illustration is given using examples of the Rössler system and the slow-fast Hindmarsh-Rose neuron model. The multiple lag scenario is physically realized in an electronic circuit of two Sprott systems.

The cumulative effects of life event, personal and social resources on subjective well-being of elderly widowers.

PubMed

Balaswamy, S; Richardson, V E

2001-01-01

A multidimensional Life Stress Model was used to test the independent contributions of background characteristics, personal resources, life event, and environmental influences on 200 widowers' levels of well-being, measured by the Affect Balance Scale. Stepwise regression analyses revealed that environmental resources were unrelated to negative affect which is influenced more by the life event and personal resource variables. The environmental resource variables, particularly interactions with friends and neighbors, mostly influenced positive affect. The explanatory model for well-being included multiple variables and explained 33 percent of the variance. Although background characteristics had the greatest impact, absence of hospitalization, higher mastery, higher self-esteem, contacts with friends, and interaction with neighbors enhanced well-being. The results support previous speculations on the importance of positive exchanges for positive affect. African-American widowers showed higher levels of well-being than Caucasian widowers did. The results advance knowledge about differences among elderly men.

Overtone Mobility Spectrometry (Part 2): Theoretical Considerations of Resolving Power

PubMed Central

Valentine, Stephen J.; Stokes, Sarah T.; Kurulugama, Ruwan T.; Nachtigall, Fabiane M.; Clemmer, David E.

2009-01-01

The transport of ions through multiple drift regions is modeled in order to develop an equation that is useful for an understanding of the resolving power of an overtone mobility spectrometry (OMS) technique. It is found that resolving power is influenced by a number of experimental variables, including those that define ion mobility spectrometry (IMS) resolving power: drift field (E), drift region length (L), and buffer gas temperature (T). However, unlike IMS, the resolving power of OMS is also influenced by the number of drift regions (n), harmonic frequency value (m), and the phase number (ϕ) of the applied drift field. The OMS resolving power dependence upon the new OMS variables (n, m, and ϕ) scales differently than the square root dependence of the E, L, and T variables in IMS. The results provide insight about optimal instrumental design and operation. PMID:19230705

Servant teaching: the power and promise for nursing education.

PubMed

Robinson, F Patrick

2009-01-01

The best theoretical or practical approaches to achieving learning outcomes in nursing likely depend on multiple variables, including instructor-related variables. This paper explores one such variable and its potential impact on learning. Application of the principles inherent in servant leadership to teaching/learning in nursing education is suggested as a way to produce professional nurses who are willing and able to transform the health care environment to achieve higher levels of quality and safety. Thus, the concept of servant teaching is introduced with discussion of the following principles and their application to teaching in nursing: judicious use of power, listening and empathy, willingness to change, reflection and contemplation, collaboration and consensus, service learning, healing, conceptualization, stewardship, building community, and commitment to the growth of people. Faculty colleagues are invited to explore the use of servant teaching and its potential for nursing education.

Housing Satisfaction of Older (55+) Single-Person Householders in U.S. Rural Communities.

PubMed

Ahn, Mira; Lee, Sung-Jin

2016-08-01

This study aims to understand the housing satisfaction of older (55+) single-person householders in U.S. rural communities using the available variables from a secondary data set, the 2011 American Housing Survey (AHS). In this study, housing satisfaction was considered to be an indicator of quality of life. Based on previous studies, we developed a model to test a hypothesized relationship between older (55+) single-person householders' (N = 1,017) housing satisfaction and their personal, physical, financial, and environmental characteristics. Multiple regression results showed that the model was supported, indicating that significant variables in housing satisfaction include age, gender, health status, age of house, structure type, and unit location. Among the significant variables, health status was revealed to be the strongest factor in housing satisfaction. Housing satisfaction was discussed as potential indicators of quality of life. © The Author(s) 2015.

Multiplication factor versus regression analysis in stature estimation from hand and foot dimensions.

PubMed

Krishan, Kewal; Kanchan, Tanuj; Sharma, Abhilasha

2012-05-01

Estimation of stature is an important parameter in identification of human remains in forensic examinations. The present study is aimed to compare the reliability and accuracy of stature estimation and to demonstrate the variability in estimated stature and actual stature using multiplication factor and regression analysis methods. The study is based on a sample of 246 subjects (123 males and 123 females) from North India aged between 17 and 20 years. Four anthropometric measurements; hand length, hand breadth, foot length and foot breadth taken on the left side in each subject were included in the study. Stature was measured using standard anthropometric techniques. Multiplication factors were calculated and linear regression models were derived for estimation of stature from hand and foot dimensions. Derived multiplication factors and regression formula were applied to the hand and foot measurements in the study sample. The estimated stature from the multiplication factors and regression analysis was compared with the actual stature to find the error in estimated stature. The results indicate that the range of error in estimation of stature from regression analysis method is less than that of multiplication factor method thus, confirming that the regression analysis method is better than multiplication factor analysis in stature estimation. Copyright © 2012 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Multiple-input multiple-output causal strategies for gene selection.

PubMed

Bontempi, Gianluca; Haibe-Kains, Benjamin; Desmedt, Christine; Sotiriou, Christos; Quackenbush, John

2011-11-25

Traditional strategies for selecting variables in high dimensional classification problems aim to find sets of maximally relevant variables able to explain the target variations. If these techniques may be effective in generalization accuracy they often do not reveal direct causes. The latter is essentially related to the fact that high correlation (or relevance) does not imply causation. In this study, we show how to efficiently incorporate causal information into gene selection by moving from a single-input single-output to a multiple-input multiple-output setting. We show in synthetic case study that a better prioritization of causal variables can be obtained by considering a relevance score which incorporates a causal term. In addition we show, in a meta-analysis study of six publicly available breast cancer microarray datasets, that the improvement occurs also in terms of accuracy. The biological interpretation of the results confirms the potential of a causal approach to gene selection. Integrating causal information into gene selection algorithms is effective both in terms of prediction accuracy and biological interpretation.

Modelling multiple cycles of static and dynamic recrystallisation using a fully implicit isotropic material model based on dislocation density

NASA Astrophysics Data System (ADS)

Jansen van Rensburg, Gerhardus J.; Kok, Schalk; Wilke, Daniel N.

2018-03-01

This paper presents the development and numerical implementation of a state variable based thermomechanical material model, intended for use within a fully implicit finite element formulation. Plastic hardening, thermal recovery and multiple cycles of recrystallisation can be tracked for single peak as well as multiple peak recrystallisation response. The numerical implementation of the state variable model extends on a J2 isotropic hypo-elastoplastic modelling framework. The complete numerical implementation is presented as an Abaqus UMAT and linked subroutines. Implementation is discussed with detailed explanation of the derivation and use of various sensitivities, internal state variable management and multiple recrystallisation cycle contributions. A flow chart explaining the proposed numerical implementation is provided as well as verification on the convergence of the material subroutine. The material model is characterised using two high temperature data sets for cobalt and copper. The results of finite element analyses using the material parameter values characterised on the copper data set are also presented.

Estimating Interaction Effects With Incomplete Predictor Variables

PubMed Central

Enders, Craig K.; Baraldi, Amanda N.; Cham, Heining

2014-01-01

The existing missing data literature does not provide a clear prescription for estimating interaction effects with missing data, particularly when the interaction involves a pair of continuous variables. In this article, we describe maximum likelihood and multiple imputation procedures for this common analysis problem. We outline 3 latent variable model specifications for interaction analyses with missing data. These models apply procedures from the latent variable interaction literature to analyses with a single indicator per construct (e.g., a regression analysis with scale scores). We also discuss multiple imputation for interaction effects, emphasizing an approach that applies standard imputation procedures to the product of 2 raw score predictors. We thoroughly describe the process of probing interaction effects with maximum likelihood and multiple imputation. For both missing data handling techniques, we outline centering and transformation strategies that researchers can implement in popular software packages, and we use a series of real data analyses to illustrate these methods. Finally, we use computer simulations to evaluate the performance of the proposed techniques. PMID:24707955

Heart rate variability is differentially altered in multiple sclerosis: implications for acute, worsening and progressive disability.

PubMed

Studer, Valeria; Rocchi, Camilla; Motta, Caterina; Lauretti, Benedetta; Perugini, Jacopo; Brambilla, Laura; Pareja-Gutierrez, Lorena; Camera, Giorgia; Barbieri, Francesca Romana; Marfia, Girolama A; Centonze, Diego; Rossi, Silvia

2017-01-01

Sympathovagal imbalance has been associated with poor prognosis in chronic diseases, but there is conflicting evidence in multiple sclerosis. The objective of this study was to investigate the autonomic nervous system dysfunction correlation with inflammation and progression in multiple sclerosis. Heart rate variability was analysed in 120 multiple sclerosis patients and 60 healthy controls during supine rest and head-up tilt test; the normalised units of low frequency and high frequency power were considered to assess sympathetic and vagal components, respectively. Correlation analyses with clinical and radiological markers of disease activity and progression were performed. Sympathetic dysfunction was closely related to the progression of disability in multiple sclerosis: progressive patients showed altered heart rate variability with respect to healthy controls and relapsing-remitting patients, with higher rest low frequency power and lacking the expected low frequency power increase during the head-up tilt test. In relapsing-remitting patients, disease activity, even subclinical, was associated with lower rest low frequency power, whereas stable relapsing-remitting patients did not differ from healthy controls. Less sympathetic reactivity and higher low frequency power at rest were associated with incomplete recovery from relapse. Autonomic balance appears to be intimately linked with both the inflammatory activity of multiple sclerosis, which is featured by an overall hypoactivity of the sympathetic nervous system, and its compensatory plastic processes, which appear inefficient in case of worsening and progressive multiple sclerosis.

White matter microstructural alterations in clinically isolated syndrome and multiple sclerosis.

PubMed

Huang, Jing; Liu, Yaou; Zhao, Tengda; Shu, Ni; Duan, Yunyun; Ren, Zhuoqiong; Sun, Zheng; Liu, Zheng; Chen, Hai; Dong, Huiqing; Li, Kuncheng

2018-07-01

This study aims to determine whether and how diffusion alteration occurs in the earliest stage of multiple sclerosis (MS) and the differences in diffusion metrics between CIS and MS by using the tract-based spatial statistics (TBSS) method based on diffusion tensor imaging (DTI). Thirty-six CIS patients (mean age ± SD: 34.0 years ± 12.6), 36 relapsing-remitting multiple sclerosis (RRMS) patients (mean age ± SD: 35.0 years ± 9.4) and 36 age- and gender-matched normal controls (NCs) were included in this study. Voxel-wise analyses were performed with TBSS using multiple diffusion metrics, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (λ 1 ) and radial diffusivity (λ 23 ). In the CIS patients, TBSS analyses revealed diffusion alterations in a few white matter (WM) regions including the anterior thalamic radiation, corticospinal tract, inferior fronto-occipital fasciculus, superior longitudinal fasciculus, body and splenium of the corpus callosum, internal capsule, external capsule, and cerebral peduncle. MS patients showed more widespread diffusion changes (decreased FA, increased λ 1 , λ 23 and MD) than CIS. Exploratory analyses also revealed the possible associations between WM diffusion metrics and clinical variables (Expanded Disability Status Scale and disease duration) in the patients. This study provided imaging evidence for DTI abnormalities in CIS and MS and suggested that DTI can improve our knowledge of the path physiology of CIS and MS and clinical progression. Copyright © 2018 Elsevier Ltd. All rights reserved.

Motor control differs for increasing and releasing force

PubMed Central

Park, Seoung Hoon; Kwon, MinHyuk; Solis, Danielle; Lodha, Neha

2016-01-01

Control of the motor output depends on our ability to precisely increase and release force. However, the influence of aging on force increase and release remains unknown. The purpose of this study, therefore, was to determine whether force control differs while increasing and releasing force in young and older adults. Sixteen young adults (22.5 ± 4 yr, 8 females) and 16 older adults (75.7 ± 6.4 yr, 8 females) increased and released force at a constant rate (10% maximum voluntary contraction force/s) during an ankle dorsiflexion isometric task. We recorded the force output and multiple motor unit activity from the tibialis anterior (TA) muscle and quantified the following outcomes: 1) variability of force using the SD of force; 2) mean discharge rate and variability of discharge rate of multiple motor units; and 3) power spectrum of the multiple motor units from 0–4, 4–10, 10–35, and 35–60 Hz. Participants exhibited greater force variability while releasing force, independent of age (P < 0.001). Increased force variability during force release was associated with decreased modulation of multiple motor units from 35 to 60 Hz (R2 = 0.38). Modulation of multiple motor units from 35 to 60 Hz was further correlated to the change in mean discharge rate of multiple motor units (r = 0.66) and modulation from 0 to 4 Hz (r = −0.64). In conclusion, these findings suggest that force control is altered while releasing due to an altered modulation of the motor units. PMID:26961104