Calibration of Predictor Models Using Multiple Validation Experiments

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.

2015-01-01

This paper presents a framework for calibrating computational models using data from several and possibly dissimilar validation experiments. The offset between model predictions and observations, which might be caused by measurement noise, model-form uncertainty, and numerical error, drives the process by which uncertainty in the models parameters is characterized. The resulting description of uncertainty along with the computational model constitute a predictor model. Two types of predictor models are studied: Interval Predictor Models (IPMs) and Random Predictor Models (RPMs). IPMs use sets to characterize uncertainty, whereas RPMs use random vectors. The propagation of a set through a model makes the response an interval valued function of the state, whereas the propagation of a random vector yields a random process. Optimization-based strategies for calculating both types of predictor models are proposed. Whereas the formulations used to calculate IPMs target solutions leading to the interval value function of minimal spread containing all observations, those for RPMs seek to maximize the models' ability to reproduce the distribution of observations. Regarding RPMs, we choose a structure for the random vector (i.e., the assignment of probability to points in the parameter space) solely dependent on the prediction error. As such, the probabilistic description of uncertainty is not a subjective assignment of belief, nor is it expected to asymptotically converge to a fixed value, but instead it casts the model's ability to reproduce the experimental data. This framework enables evaluating the spread and distribution of the predicted response of target applications depending on the same parameters beyond the validation domain.

Trait complexes and academic achievement: old and new ways of examining personality in educational contexts.

PubMed

Ackerman, Phillip L; Chamorro-Premuzic, Tomas; Furnham, Adrian

2011-03-01

BACKGROUND. Although recent research has provided evidence for the predictive validity of personality traits in academic settings, the path to an improved understanding of the nature of personality influences on academic achievement involves a reconceptualization of both criterion and predictor construct spaces. AIMS. For the criterion space, one needs to consider student behaviours beyond grades and level of educational attainment, and include what the student does among other things outside of the classroom. For the predictor space, it is possible to bring some order to the myriad personality constructs that have been developed over the last century, by focusing on common variance among personality and other non-ability traits. METHODS. We review these conceptual issues and several empirical studies. CONCLUSIONS. We demonstrate the possible increments in understanding non-ability determinants of academic achievement that may be obtained by focusing on areas where there is a theoretical convergence between predictor and criterion spaces. 2010 The British Psychological Society.

A Canonical Ensemble Correlation Prediction Model for Seasonal Precipitation Anomaly

NASA Technical Reports Server (NTRS)

Shen, Samuel S. P.; Lau, William K. M.; Kim, Kyu-Myong; Li, Guilong

2001-01-01

This report describes an optimal ensemble forecasting model for seasonal precipitation and its error estimation. Each individual forecast is based on the canonical correlation analysis (CCA) in the spectral spaces whose bases are empirical orthogonal functions (EOF). The optimal weights in the ensemble forecasting crucially depend on the mean square error of each individual forecast. An estimate of the mean square error of a CCA prediction is made also using the spectral method. The error is decomposed onto EOFs of the predictand and decreases linearly according to the correlation between the predictor and predictand. This new CCA model includes the following features: (1) the use of area-factor, (2) the estimation of prediction error, and (3) the optimal ensemble of multiple forecasts. The new CCA model is applied to the seasonal forecasting of the United States precipitation field. The predictor is the sea surface temperature.

Optimization techniques applied to passive measures for in-orbit spacecraft survivability

NASA Technical Reports Server (NTRS)

Mog, Robert A.; Price, D. Marvin

1991-01-01

Spacecraft designers have always been concerned about the effects of meteoroid impacts on mission safety. The engineering solution to this problem has generally been to erect a bumper or shield placed outboard from the spacecraft wall to disrupt/deflect the incoming projectiles. Spacecraft designers have a number of tools at their disposal to aid in the design process. These include hypervelocity impact testing, analytic impact predictors, and hydrodynamic codes. Analytic impact predictors generally provide the best quick-look estimate of design tradeoffs. The most complete way to determine the characteristics of an analytic impact predictor is through optimization of the protective structures design problem formulated with the predictor of interest. Space Station Freedom protective structures design insight is provided through the coupling of design/material requirements, hypervelocity impact phenomenology, meteoroid and space debris environment sensitivities, optimization techniques and operations research strategies, and mission scenarios. Major results are presented.

Student-directed retrieval practice is a predictor of medical licensing examination performance.

PubMed

Deng, Francis; Gluckstein, Jeffrey A; Larsen, Douglas P

2015-12-01

A large body of evidence indicates that retrieval practice (test-enhanced learning) and spaced repetition increase long-term information retention. Implementation of these strategies in medical curricula is unfortunately limited. However, students may choose to apply them autonomously when preparing for high-stakes, cumulative assessments, such as the United States Medical Licensing Examination Step 1. We examined the prevalence of specific self-directed methods of testing, with or without spaced repetition, among preclinical students and assessed the relationship between these methods and licensing examination performance. Seventy-two medical students at one institution completed a survey concerning their use of user-generated (Anki) or commercially-available (Firecracker) flashcards intended for spaced repetition and of boards-style multiple-choice questions (MCQs). Other information collected included Step 1 score, past academic performance (Medical College Admission Test [MCAT] score, preclinical grades), and psychological factors that may have affected exam preparation or performance (feelings of depression, burnout, and test anxiety). All students reported using practice MCQs (mean 3870, SD 1472). Anki and Firecracker users comprised 31 and 49 % of respondents, respectively. In a multivariate regression model, significant independent predictors of Step 1 score included MCQs completed (unstandardized beta coefficient [B] = 2.2 × 10 - 3 , p < 0.001), unique Anki flashcards seen (B = 5.9 × 10 - 4 , p = 0.024), second-year honours (B = 1.198, p = 0.002), and MCAT score (B = 1.078, p = 0.003). Test anxiety was a significant negative predictor (B= - 1.986, p < 0.001). Unique Firecracker flashcards seen did not predict Step 1 score. Each additional 445 boards-style practice questions or 1700 unique Anki flashcards was associated with an additional point on Step 1 when controlling for other academic and psychological factors. Medical students engage extensively in self-initiated retrieval practice, often with spaced repetition. These practices are associated with superior performance on a medical licensing examination and should be considered for formal support by educators.

NASA-Ames workload research program

NASA Technical Reports Server (NTRS)

Hart, Sandra

1988-01-01

Research has been underway for several years to develop valid and reliable measures and predictors of workload as a function of operator state, task requirements, and system resources. Although the initial focus of this research was on aeronautics, the underlying principles and methodologies are equally applicable to space, and provide a set of tools that NASA and its contractors can use to evaluate design alternatives from the perspective of the astronauts. Objectives and approach of the research program are described, as well as the resources used in conducting research and the conceptual framework around which the program evolved. Next, standardized tasks are described, in addition to predictive models and assessment techniques and their application to the space program. Finally, some of the operational applications of these tasks and measures are reviewed.

Cross-cultural generality and specificity in self-regulation: avoidance personal goals and multiple aspects of well-being in the United States and Japan.

PubMed

Elliot, Andrew J; Sedikides, Constantine; Murayama, Kou; Tanaka, Ayumi; Thrash, Todd M; Mapes, Rachel R

2012-10-01

The authors examined avoidance personal goals as concurrent (Study 1) and longitudinal (Study 2) predictors of multiple aspects of well-being in the United States and Japan. In both studies, participants adopted more avoidance personal goals in Japan relative to the United States. Both studies also demonstrated that avoidance personal goals were significant negative predictors of the most relevant aspects of well-being in each culture. Specifically, avoidance personal goals were negative predictors of intrapersonal and eudaimonic well-being in the United States and were negative predictors of interpersonal and eudaimonic well-being in Japan. The findings clarify and extend puzzling findings from prior empirical work in this area, and raise provocative possibilities about the nature of avoidance goal pursuit.

Does school suspension affect subsequent youth nonviolent antisocial behavior? A longitudinal study of students in Victoria, Australia and Washington State, United States

PubMed Central

Hemphill, Sheryl A.; Kotevski, Aneta; Herrenkohl, Todd I.; Smith, Rachel; Toumbourou, John W.; Catalano, Richard F.

2013-01-01

School suspension has been not only associated with negative behaviours but is predictive of future poor outcomes. The current study investigates a) whether school suspension is a unique predictor of youth nonviolent antisocial behaviour (NVAB) relative to other established predictors, and b) whether the predictors of NVAB are similar in Australia and the United States (U.S.). The data analysed here draws on two state-wide representative samples of Grade 7 and 9 students in Victoria, Australia and Washington State, U.S., resurveyed at 12-month follow-up (N = 3,677, 99% retention). School suspension did not uniquely predict NVAB in the final model. The predictors of NVAB, similar across states, included previous student NVAB; current alcohol and tobacco use; poor family management; association with antisocial friends; and low commitment to school. An implication of the findings is that U.S. evidence-based prevention programs targeting the influences investigated here could be trialled in Australia. PMID:24860192

Tumour front inflammation and necrosis are independent prognostic predictors in high-grade urothelial carcinoma of the bladder.

PubMed

Hodgson, Anjelica; Xu, Bin; Satkunasivam, Raj; Downes, Michelle R

2018-02-01

Inflammation and necrosis have been associated with prognosis in multiple epithelial malignancies. Our objective was to evaluate inflammation and necrosis in a cohort of patients with high-grade urothelial carcinomas of the bladder to determine their association with pathological parameters and their prognostic effect on relapse-free and disease-specific survival. A retrospective cohort that underwent radical cystectomy for urothelial carcinomas (n=235) was evaluated for invasive front and central inflammation using the Klintrup-Makinen assessment method. Necrosis was scored using a four-point scale. The relationship of inflammation and necrosis with stage, nodal status, carcinoma in situ, tumour size, margin status and vascular space invasion and the impact on relapse-free and disease-specific survival were calculated using appropriate statistical tests. On multivariate analysis, invasive front inflammation (p=0.003) and necrosis (p=0.000) were independent predictors of relapse-free survival. Both invasive front inflammation (p=0.009) and necrosis (p=0.002) again were independent predictors of disease-specific survival. For pathological features, low invasive front inflammation was associated with lymphovascular space invasion (p=0.008), a positive soft tissue margin (p=0.028) and carcinoma in situ (p=0.042). Necrosis was statistically associated with tumours >3 cm in size (p=0.013) and carcinoma in situ (p<0.001). Necrosis and invasive front inflammation are additional histological variables with independent prognostic relevance in high-grade urothelial carcinoma of the bladder. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

CWD prevalence, perceived human health risks, and state influences on deer hunting participation.

PubMed

Vaske, Jerry J; Lyon, Katie M

2011-03-01

This study examined factors predicted by previous research to influence hunters' decisions to stop hunting deer in a state. Data were obtained from mail surveys of resident and nonresident deer hunters in Arizona, North Dakota, South Dakota, and Wisconsin (n = 3,518). Hunters were presented with six scenarios depicting hypothetical CWD prevalence levels and human health risks from the disease (e.g., death), and asked if they would continue or stop hunting deer in the state. Bivariate analyses examined the influence of five predictor variables: (a) CWD prevalence, (b) hypothetical human death from CWD, (c) perceived human health risks from CWD, (d) state, and (e) residency. In the bivariate analyses, prevalence was the strongest predictor of quitting hunting in the state followed by hypothetical human death and perceived risk. The presence of CWD in a state and residency were weak, but statistically significant, predictors. Interactions among these predictors increased the potential for stopping hunting in the state. Multivariate analyses suggested that 64% of our respondents would quit hunting in the worst-case scenario. © 2010 Society for Risk Analysis.

Predictor laws for pictorial flight displays

NASA Technical Reports Server (NTRS)

Grunwald, A. J.

1985-01-01

Two predictor laws are formulated and analyzed: (1) a circular path law based on constant accelerations perpendicular to the path and (2) a predictor law based on state transition matrix computations. It is shown that for both methods the predictor provides the essential lead zeros for the path-following task. However, in contrast to the circular path law, the state transition matrix law furnishes the system with additional zeros that entirely cancel out the higher-frequency poles of the vehicle dynamics. On the other hand, the circular path law yields a zero steady-state error in following a curved trajectory with a constant radius. A combined predictor law is suggested that utilizes the advantages of both methods. A simple analysis shows that the optimal prediction time mainly depends on the level of precision required in the path-following task, and guidelines for determining the optimal prediction time are given.

Predictors of Academic Success in Language Arts Literacy and Math on State Assessments in New Jersey Charter Schools

ERIC Educational Resources Information Center

Jerue, Gary A.

2013-01-01

There are a limited number of studies that examine the predictors of academic success in charter schools (Lawton, 2009). This study utilized a multiple regression analysis to identify the best predictors of academic success in language arts literacy (LAL) and math on state assessments in New Jersey charter schools. This study included four student…

Comparing Dropout Predictors for Two State-Level Panels Using Grade 6 and Grade 8 Data

ERIC Educational Resources Information Center

Franklin, Bobby J.; Trouard, Stephen B.

2016-01-01

The purpose of this study was to examine the effectiveness of dropout predictors across time. Two state-level high school graduation panels were selected to begin with the seventh and ninth grades but end at the same time. The first panel (seventh grade) contained 29,554 students and used sixth grade predictors. The second panel (ninth grade)…

Urban Green Space Perception and Its Contribution to Well-Being.

PubMed

Kothencz, Gyula; Kolcsár, Ronald; Cabrera-Barona, Pablo; Szilassi, Péter

2017-07-12

Individual perceptions are essential when evaluating the well-being benefits from urban green spaces. This study predicted the influence of perceived green space characteristics in the city of Szeged, Hungary, on two well-being variables: the green space visitors' level of satisfaction and the self-reported quality of life. The applied logistic regression analysis used nine predictors: seven perceived green space characteristics from a questionnaire survey among visitors of five urban green spaces of Szeged; and the frequency of green space visitors' crowd-sourced recreational running paths and photographs picturing green space aesthetics. Results revealed that perceived green space characteristics with direct well-being benefits were strong predictors of both dependent variables. Perceived green space characteristics with indirect, yet fundamental, well-being benefits, namely, regulating ecosystem services had minor influence on the dependent variables. The crowd-sourced geo-tagged data predicted only the perceived quality of life contributions; but revealed spatial patterns of recreational green space use and aesthetics. This study recommends that regulating ecosystem services should be planned with a focus on residents' aesthetic and recreational needs. Further research on the combination of green space visitors´ perceptions and crowd-sourced geo-tagged data is suggested to promote planning for well-being and health benefits of urban green spaces.

Urban Green Space Perception and Its Contribution to Well-Being

PubMed Central

Kolcsár, Ronald; Cabrera-Barona, Pablo; Szilassi, Péter

2017-01-01

Individual perceptions are essential when evaluating the well-being benefits from urban green spaces. This study predicted the influence of perceived green space characteristics in the city of Szeged, Hungary, on two well-being variables: the green space visitors’ level of satisfaction and the self-reported quality of life. The applied logistic regression analysis used nine predictors: seven perceived green space characteristics from a questionnaire survey among visitors of five urban green spaces of Szeged; and the frequency of green space visitors’ crowd-sourced recreational running paths and photographs picturing green space aesthetics. Results revealed that perceived green space characteristics with direct well-being benefits were strong predictors of both dependent variables. Perceived green space characteristics with indirect, yet fundamental, well-being benefits, namely, regulating ecosystem services had minor influence on the dependent variables. The crowd-sourced geo-tagged data predicted only the perceived quality of life contributions; but revealed spatial patterns of recreational green space use and aesthetics. This study recommends that regulating ecosystem services should be planned with a focus on residents’ aesthetic and recreational needs. Further research on the combination of green space visitors´ perceptions and crowd-sourced geo-tagged data is suggested to promote planning for well-being and health benefits of urban green spaces. PMID:28704969

Error Estimation of An Ensemble Statistical Seasonal Precipitation Prediction Model

NASA Technical Reports Server (NTRS)

Shen, Samuel S. P.; Lau, William K. M.; Kim, Kyu-Myong; Li, Gui-Long

2001-01-01

This NASA Technical Memorandum describes an optimal ensemble canonical correlation forecasting model for seasonal precipitation. Each individual forecast is based on the canonical correlation analysis (CCA) in the spectral spaces whose bases are empirical orthogonal functions (EOF). The optimal weights in the ensemble forecasting crucially depend on the mean square error of each individual forecast. An estimate of the mean square error of a CCA prediction is made also using the spectral method. The error is decomposed onto EOFs of the predictand and decreases linearly according to the correlation between the predictor and predictand. Since new CCA scheme is derived for continuous fields of predictor and predictand, an area-factor is automatically included. Thus our model is an improvement of the spectral CCA scheme of Barnett and Preisendorfer. The improvements include (1) the use of area-factor, (2) the estimation of prediction error, and (3) the optimal ensemble of multiple forecasts. The new CCA model is applied to the seasonal forecasting of the United States (US) precipitation field. The predictor is the sea surface temperature (SST). The US Climate Prediction Center's reconstructed SST is used as the predictor's historical data. The US National Center for Environmental Prediction's optimally interpolated precipitation (1951-2000) is used as the predictand's historical data. Our forecast experiments show that the new ensemble canonical correlation scheme renders a reasonable forecasting skill. For example, when using September-October-November SST to predict the next season December-January-February precipitation, the spatial pattern correlation between the observed and predicted are positive in 46 years among the 50 years of experiments. The positive correlations are close to or greater than 0.4 in 29 years, which indicates excellent performance of the forecasting model. The forecasting skill can be further enhanced when several predictors are used.

Kickoff to Conflict: A Sequence Analysis of Intra-State Conflict-Preceding Event Structures

PubMed Central

D'Orazio, Vito; Yonamine, James E.

2015-01-01

While many studies have suggested or assumed that the periods preceding the onset of intra-state conflict are similar across time and space, few have empirically tested this proposition. Using the Integrated Crisis Early Warning System's domestic event data in Asia from 1998–2010, we subject this proposition to empirical analysis. We code the similarity of government-rebel interactions in sequences preceding the onset of intra-state conflict to those preceding further periods of peace using three different metrics: Euclidean, Levenshtein, and mutual information. These scores are then used as predictors in a bivariate logistic regression to forecast whether we are likely to observe conflict in neither, one, or both of the states. We find that our model accurately classifies cases where both sequences precede peace, but struggles to distinguish between cases in which one sequence escalates to conflict and where both sequences escalate to conflict. These findings empirically suggest that generalizable patterns exist between event sequences that precede peace. PMID:25951105

New Predictive Filters for Compensating the Transport Delay on a Flight Simulator

NASA Technical Reports Server (NTRS)

Guo, Liwen; Cardullo, Frank M.; Houck, Jacob A.; Kelly, Lon C.; Wolters, Thomas E.

2004-01-01

The problems of transport delay in a flight simulator, such as its sources and effects, are reviewed. Then their effects on a pilot-in-the-loop control system are investigated with simulations. Three current prominent delay compensators the lead/lag filter, McFarland filter, and the Sobiski/Cardullo filter were analyzed and compared. This paper introduces two novel delay compensation techniques an adaptive predictor using the Kalman estimator and a state space predictive filter using a reference aerodynamic model. Applications of these two new compensators on recorded data from the NASA Langley Research Center Visual Motion Simulator show that they achieve better compensation over the current ones.

National Identity and Group Narcissism as Predictors of Intergroup Attitudes toward Undocumented Latino Immigrants in the United States

ERIC Educational Resources Information Center

Lyons, Patricia A.; Coursey, Lauren E.; Kenworthy, Jared B.

2013-01-01

The debate surrounding immigration reform to address undocumented Latino immigrants in the United States has been emotionally charged and polarizing. This study's goal was to better understand some of the psychological predictors of attitudes toward undocumented Latino immigrants in the United States, namely, collective identity as an…

Regional Distribution Models with Lack of Proximate Predictors: Africanized Honeybees Expanding North

NASA Technical Reports Server (NTRS)

Jarnevich, Catherine S.; Esaias, Wayne E.; Ma, Peter L. A.; Morisette, Jeffery T.; Nickeson, Jaime E.; Stohlgren, Thomas J.; Holcombe, Tracy R.; Nightingale, Joanne M.; Wolfe, Robert E.; Tan, Bin

2014-01-01

Species distribution models have often been hampered by poor local species data, reliance on coarse-scale climate predictors and the assumption that species-environment relationships, even with non-proximate predictors, are consistent across geographical space. Yet locally accurate maps of invasive species, such as the Africanized honeybee (AHB) in North America, are needed to support conservation efforts. Current AHB range maps are relatively coarse and are inconsistent with observed data. Our aim was to improve distribution maps using more proximate predictors (phenology) and using regional models rather than one across the entire range of interest to explore potential differences in drivers.

Regional distribution models with lack of proximate predictors: Africanized honeybees expanding north

USGS Publications Warehouse

Jarnevich, Catherine S.; Esaias, Wayne E.; Ma, Peter L.A.; Morisette, Jeffery T.; Nickeson, Jaime E.; Stohlgren, Thomas J.; Holcombe, Tracy R.; Nightingale, Joanne M.; Wolfe, Robert E.; Tan, Bin

2014-01-01

Species distribution models have often been hampered by poor local species data, reliance on coarse-scale climate predictors and the assumption that species–environment relationships, even with non-proximate predictors, are consistent across geographical space. Yet locally accurate maps of invasive species, such as the Africanized honeybee (AHB) in North America, are needed to support conservation efforts. Current AHB range maps are relatively coarse and are inconsistent with observed data. Our aim was to improve distribution maps using more proximate predictors (phenology) and using regional models rather than one across the entire range of interest to explore potential differences in drivers.

Supervised embedding of textual predictors with applications in clinical diagnostics for pediatric cardiology.

PubMed

Perry, Thomas Ernest; Zha, Hongyuan; Zhou, Ke; Frias, Patricio; Zeng, Dadan; Braunstein, Mark

2014-02-01

Electronic health records possess critical predictive information for machine-learning-based diagnostic aids. However, many traditional machine learning methods fail to simultaneously integrate textual data into the prediction process because of its high dimensionality. In this paper, we present a supervised method using Laplacian Eigenmaps to enable existing machine learning methods to estimate both low-dimensional representations of textual data and accurate predictors based on these low-dimensional representations at the same time. We present a supervised Laplacian Eigenmap method to enhance predictive models by embedding textual predictors into a low-dimensional latent space, which preserves the local similarities among textual data in high-dimensional space. The proposed implementation performs alternating optimization using gradient descent. For the evaluation, we applied our method to over 2000 patient records from a large single-center pediatric cardiology practice to predict if patients were diagnosed with cardiac disease. In our experiments, we consider relatively short textual descriptions because of data availability. We compared our method with latent semantic indexing, latent Dirichlet allocation, and local Fisher discriminant analysis. The results were assessed using four metrics: the area under the receiver operating characteristic curve (AUC), Matthews correlation coefficient (MCC), specificity, and sensitivity. The results indicate that supervised Laplacian Eigenmaps was the highest performing method in our study, achieving 0.782 and 0.374 for AUC and MCC, respectively. Supervised Laplacian Eigenmaps showed an increase of 8.16% in AUC and 20.6% in MCC over the baseline that excluded textual data and a 2.69% and 5.35% increase in AUC and MCC, respectively, over unsupervised Laplacian Eigenmaps. As a solution, we present a supervised Laplacian Eigenmap method to embed textual predictors into a low-dimensional Euclidean space. This method allows many existing machine learning predictors to effectively and efficiently capture the potential of textual predictors, especially those based on short texts.

Predicting Efficiency of Travel in Young, Visually Impaired Children from Their Other Spatial Skills.

ERIC Educational Resources Information Center

Hill, Anita; And Others

1985-01-01

To test ways of predicting how efficiently visually impaired children learn travel skills, a criteria checklist of spatial skills was developed for close-body space, local space, and geographical/travel space. Comparison was made between predictors of efficient learning including subjective ratings of teachers, personal qualities and factors of…

Development of equations to predict the influence of floor space on average daily gain, average daily feed intake and gain : feed ratio of finishing pigs.

PubMed

Flohr, J R; Dritz, S S; Tokach, M D; Woodworth, J C; DeRouchey, J M; Goodband, R D

2018-05-01

Floor space allowance for pigs has substantial effects on pig growth and welfare. Data from 30 papers examining the influence of floor space allowance on the growth of finishing pigs was used in a meta-analysis to develop alternative prediction equations for average daily gain (ADG), average daily feed intake (ADFI) and gain : feed ratio (G : F). Treatment means were compiled in a database that contained 30 papers for ADG and 28 papers for ADFI and G : F. The predictor variables evaluated were floor space (m2/pig), k (floor space/final BW0.67), Initial BW, Final BW, feed space (pigs per feeder hole), water space (pigs per waterer), group size (pigs per pen), gender, floor type and study length (d). Multivariable general linear mixed model regression equations were used. Floor space treatments within each experiment were the observational and experimental unit. The optimum equations to predict ADG, ADFI and G : F were: ADG, g=337.57+(16 468×k)-(237 350×k 2)-(3.1209×initial BW (kg))+(2.569×final BW (kg))+(71.6918×k×initial BW (kg)); ADFI, g=833.41+(24 785×k)-(388 998×k 2)-(3.0027×initial BW (kg))+(11.246×final BW (kg))+(187.61×k×initial BW (kg)); G : F=predicted ADG/predicted ADFI. Overall, the meta-analysis indicates that BW is an important predictor of ADG and ADFI even after computing the constant coefficient k, which utilizes final BW in its calculation. This suggests including initial and final BW improves the prediction over using k as a predictor alone. In addition, the analysis also indicated that G : F of finishing pigs is influenced by floor space allowance, whereas individual studies have concluded variable results.

Diffusion of Impaired Driving Laws Among US States.

PubMed

Macinko, James; Silver, Diana

2015-09-01

We examined internal and external determinants of state's adoption of impaired driving laws. Data included 7 state-level, evidence-based public health laws collected from 1980 to 2010. We used event history analyses to identify predictors of first-time law adoption and subsequent adoption between state pairs. The independent variables were internal state factors, including the political environment, legislative professionalism, government capacity, state resources, legislative history, and policy-specific risk factors. The external factors were neighboring states' history of law adoption and changes in federal law. We found a strong secular trend toward an increased number of laws over time. The proportion of younger drivers and the presence of a neighboring state with similar laws were the strongest predictors of first-time law adoption. The predictors of subsequent law adoption included neighbor state adoption and previous legislative action. Alcohol laws were negatively associated with first-time adoption of impaired driving laws, suggesting substitution effects among policy choices. Organizations seeking to stimulate state policy changes may need to craft strategies that engage external actors, such as neighboring states, in addition to mobilizing within-state constituencies.

Co-Clustering by Bipartite Spectral Graph Partitioning for Out-of-Tutor Prediction

ERIC Educational Resources Information Center

Trivedi, Shubhendu; Pardos, Zachary A.; Sarkozy, Gabor N.; Heffernan, Neil T.

2012-01-01

Learning a more distributed representation of the input feature space is a powerful method to boost the performance of a given predictor. Often this is accomplished by partitioning the data into homogeneous groups by clustering so that separate models could be trained on each cluster. Intuitively each such predictor is a better representative of…

Predictors of HIV Testing and Intention to Test Among Hispanic Farmworkers in South Florida

ERIC Educational Resources Information Center

Fernandez, M. Isabel; Collazo, Jose B.; Bowen, G. Stephen; Varga, Leah M.; Hernandez, Nilda; Perrino, Tatiana

2005-01-01

Context and Purpose: This study examined the predictors of HIV testing and factors associated with intention to accept a free HIV test among 244 Hispanic migrant/seasonal farmworkers in South Florida. Methods: Time and space sampling procedures were used to recruit participants in public venues. Bilingual staff interviewed eligible respondents in…

Measures for Predictors of Innovation Adoption

PubMed Central

Chor, Ka Ho Brian; Wisdom, Jennifer P.; Olin, Su-Chin Serene; Hoagwood, Kimberly E.; Horwitz, Sarah M.

2014-01-01

Building on a narrative synthesis of adoption theories by Wisdom et al. (2013), this review identifies 118 measures associated with the 27 adoption predictors in the synthesis. The distribution of measures is uneven across the predictors and predictors vary in modifiability. Multiple dimensions and definitions of predictors further complicate measurement efforts. For state policymakers and researchers, more effective and integrated measurement can advance the adoption of complex innovations such as evidence-based practices. PMID:24740175

Multi-Disciplinary Knowledge Synthesis for Human Health Assessment on Earth and in Space

NASA Astrophysics Data System (ADS)

Christakos, G.

We discuss methodological developments in multi-disciplinary knowledge synthesis (KS) of human health assessment. A theoretical KS framework can provide the rational means for the assimilation of various information bases (general, site-specific etc.) that are relevant to the life system of interest. KS-based techniques produce a realistic representation of the system, provide a rigorous assessment of the uncertainty sources, and generate informative health state predictions across space-time. The underlying epistemic cognition methodology is based on teleologic criteria and stochastic logic principles. The mathematics of KS involves a powerful and versatile spatiotemporal random field model that accounts rigorously for the uncertainty features of the life system and imposes no restriction on the shape of the probability distributions or the form of the predictors. KS theory is instrumental in understanding natural heterogeneities, assessing crucial human exposure correlations and laws of physical change, and explaining toxicokinetic mechanisms and dependencies in a spatiotemporal life system domain. It is hoped that a better understanding of KS fundamentals would generate multi-disciplinary models that are useful for the maintenance of human health on Earth and in Space.

Learning Parsimonious Classification Rules from Gene Expression Data Using Bayesian Networks with Local Structure.

PubMed

Lustgarten, Jonathan Lyle; Balasubramanian, Jeya Balaji; Visweswaran, Shyam; Gopalakrishnan, Vanathi

2017-03-01

The comprehensibility of good predictive models learned from high-dimensional gene expression data is attractive because it can lead to biomarker discovery. Several good classifiers provide comparable predictive performance but differ in their abilities to summarize the observed data. We extend a Bayesian Rule Learning (BRL-GSS) algorithm, previously shown to be a significantly better predictor than other classical approaches in this domain. It searches a space of Bayesian networks using a decision tree representation of its parameters with global constraints, and infers a set of IF-THEN rules. The number of parameters and therefore the number of rules are combinatorial to the number of predictor variables in the model. We relax these global constraints to a more generalizable local structure (BRL-LSS). BRL-LSS entails more parsimonious set of rules because it does not have to generate all combinatorial rules. The search space of local structures is much richer than the space of global structures. We design the BRL-LSS with the same worst-case time-complexity as BRL-GSS while exploring a richer and more complex model space. We measure predictive performance using Area Under the ROC curve (AUC) and Accuracy. We measure model parsimony performance by noting the average number of rules and variables needed to describe the observed data. We evaluate the predictive and parsimony performance of BRL-GSS, BRL-LSS and the state-of-the-art C4.5 decision tree algorithm, across 10-fold cross-validation using ten microarray gene-expression diagnostic datasets. In these experiments, we observe that BRL-LSS is similar to BRL-GSS in terms of predictive performance, while generating a much more parsimonious set of rules to explain the same observed data. BRL-LSS also needs fewer variables than C4.5 to explain the data with similar predictive performance. We also conduct a feasibility study to demonstrate the general applicability of our BRL methods on the newer RNA sequencing gene-expression data.

Effective Teaching Factors and Student Reading Strategies as Predictors of Student Achievement in PISA 2009: The Case of China and the United States

ERIC Educational Resources Information Center

Meng, Lingqi; Muñoz, Marco; King Hess, Kristin; Liu, Shujie

2017-01-01

This study investigated effective teaching factors and student reading strategies as predictors of student reading achievement in the United States and China. Participants were 10,348 students in the 2009 Program for International Student Assessment (PISA) study, 5115 from China and 5233 from the United States. Exploratory factor analysis (EFA)…

Diffusion of Impaired Driving Laws Among US States

PubMed Central

Silver, Diana

2015-01-01

Objectives. We examined internal and external determinants of state’s adoption of impaired driving laws. Methods. Data included 7 state-level, evidence-based public health laws collected from 1980 to 2010. We used event history analyses to identify predictors of first-time law adoption and subsequent adoption between state pairs. The independent variables were internal state factors, including the political environment, legislative professionalism, government capacity, state resources, legislative history, and policy-specific risk factors. The external factors were neighboring states’ history of law adoption and changes in federal law. Results. We found a strong secular trend toward an increased number of laws over time. The proportion of younger drivers and the presence of a neighboring state with similar laws were the strongest predictors of first-time law adoption. The predictors of subsequent law adoption included neighbor state adoption and previous legislative action. Alcohol laws were negatively associated with first-time adoption of impaired driving laws, suggesting substitution effects among policy choices. Conclusions. Organizations seeking to stimulate state policy changes may need to craft strategies that engage external actors, such as neighboring states, in addition to mobilizing within-state constituencies. PMID:26180969

Real-time validation of the Dst Predictor model

USGS Publications Warehouse

McCollough, James P.; Young, Shawn L.; Rigler, E. Joshua; Simpson, Hal A.

2015-01-01

The Dst Predictor model, which has been running real-time in the Space Weather Analysis and Forecast System (SWAFS), provides 1-hour and 4-hour forecasts of the Dst index. This is useful for awareness of impending geomagnetic activity, as well as driving other real-time models that use Dst as an input. In this report, we examine the performance of this forecast model in detail. When validating indices it should be noted that performance is only with respect to a reference index as they are derived quantities assumed to reflect a state of the magnetosphere that cannot be directly measured. In this case U.S. Geological Survey (USGS) Definitive Dst is the reference index (Section 3). Whether or not the model better reflects the actual activity level is nearly impossible to discern and is outside the scope of this report. We evaluate the performance of the model by computing continuous predictant skill scores against USGS Definitive Dst values as “observations” (Section 4.2). The two sets of data are not well-correlated for both 1-hour and 4-hour forecasts. The Dst Predictor Prediction Efficiency for both the 1- and 4-hour forecasts suggests poor performance versus the climatological mean. However, the skill score against a nowcast persistence model is positive, suggesting value added by the Dst Predictor model. We further examine statistics for storm times (Section 4.3) with similar results: nowcast persistence performs worse than Dst Predictor.  Dst Predictor is superior to the nowcast persistence model for the metric used in this study. We recommend continued use of the DstPredictor model for 1-and4-hour Dst predictions along with active study of other Dst forecast models that do not rely on nowcast inputs (Section 6). The lack of certified requirements makes further recommendations difficult. A study of how the error in Dst translates to error in models and a better understanding of operational needs for magnetic storm warning are needed to determine such requirements. Nowcast persistence is often hard to beat for short term forecasts and specification and Dst Predictor clearly performs well against that standard (with 1-hour and 4-hour skill-scores of 0.233 and 0.485 respectively), although poor in absolute terms (with1-hourand4-hour prediction efficiencies of-64.6and-43.1, respectively).

Geospatial Indicators of Space and Place: A Review of Multilevel Studies of HIV Prevention and Care Outcomes Among Young Men Who Have Sex With Men in the United States.

PubMed

Bauermeister, José A; Connochie, Daniel; Eaton, Lisa; Demers, Michele; Stephenson, Rob

Young men who have sex with men (YMSM), particularly YMSM who are racial/ethnic minorities, are disproportionately affected by the human immunodeficiency virus (HIV) epidemic in the United States. These HIV disparities have been linked to demographic, social, and physical geospatial characteristics. The objective of this scoping review was to summarize the existing evidence from multilevel studies examining how geospatial characteristics are associated with HIV prevention and care outcomes among YMSM populations. Our literature search uncovered 126 peer-reviewed articles, of which 17 were eligible for inclusion based on our review criteria. Nine studies examined geospatial characteristics as predictors of HIV prevention outcomes. Nine of the 17 studies reported HIV care outcomes. From the synthesis regarding the current state of research around geospatial correlates of behavioral and biological HIV risk, we propose strategies to move the field forward in order to inform the design of future multilevel research and intervention studies for this population.

Response to Early AED Therapy and Its Prognostic Implications

PubMed Central

French, Jacqueline A.

2002-01-01

Determining the prognosis of patients when they first present with epilepsy is a difficult task. Several clinical studies have shed light on this very important topic. Potential predictors of the refractory state, including seizure etiology, duration of epilepsy before treatment, and epilepsy type, have not been successful indicators of long-term outcome. One predictor of the refractory state appears to be early response to AED therapy. Inadequate seizure control after initial treatment is a poor prognostic sign. Recent research into genetic causes of the refractory state has included investigation of the multiple drug resistance gene, and polymorphisms at drug targets. More work is needed to determine the causes and predictors of drug resistance. PMID:15309146

Relative importance and utility of positive worker states: a review and empirical examination.

PubMed

Steele, John P; Rupayana, Disha D; Mills, Maura J; Smith, Michael R; Wefald, Andrew; Downey, Ronald G

2012-01-01

Our purpose was to identity the unique contribution, relative importance, and utility of positive worker states. Using Luthans et al.'s (2007) five positive organizational behavior criteria, a variety of positive worker states were reviewed and then empirically tested to establish if they met these criteria. Data were collected from 724 restaurant employees. Positive worker states included: job involvement, perceived organizational support, engagement, and vigor. Criteria were self-reported performance, customer service, turnover intention, satisfaction, and quality of life. Our review indicated consistency between predictor adequacy of meeting the criteria and their empirical relationship with key outcomes. This research found the positive worker states to be independent constructs that had differential effects depending on the focused outcome. Regression and relative weights analyses showed involvement was a weak predictor of outcomes, while perceived organizational support was the most consistent predictor. Vigor was most useful when predicting job performance. Quality of life was poorly explained.

Combining climatic and soil properties better predicts covers of Brazilian biomes.

PubMed

Arruda, Daniel M; Fernandes-Filho, Elpídio I; Solar, Ricardo R C; Schaefer, Carlos E G R

2017-04-01

Several techniques have been used to model the area covered by biomes or species. However, most models allow little freedom of choice of response variables and are conditioned to the use of climate predictors. This major restriction of the models has generated distributions of low accuracy or inconsistent with the actual cover. Our objective was to characterize the environmental space of the most representative biomes of Brazil and predict their cover, using climate and soil-related predictors. As sample units, we used 500 cells of 100 km 2 for ten biomes, derived from the official vegetation map of Brazil (IBGE 2004). With a total of 38 (climatic and soil-related) predictors, an a priori model was run with the random forest classifier. Each biome was calibrated with 75% of the samples. The final model was based on four climate and six soil-related predictors, the most important variables for the a priori model, without collinearity. The model reached a kappa value of 0.82, generating a highly consistent prediction with the actual cover of the country. We showed here that the richness of biomes should not be underestimated, and that in spite of the complex relationship, highly accurate modeling based on climatic and soil-related predictors is possible. These predictors are complementary, for covering different parts of the multidimensional niche. Thus, a single biome can cover a wide range of climatic space, versus a narrow range of soil types, so that its prediction is best adjusted by soil-related variables, or vice versa.

Combining climatic and soil properties better predicts covers of Brazilian biomes

NASA Astrophysics Data System (ADS)

Arruda, Daniel M.; Fernandes-Filho, Elpídio I.; Solar, Ricardo R. C.; Schaefer, Carlos E. G. R.

2017-04-01

Several techniques have been used to model the area covered by biomes or species. However, most models allow little freedom of choice of response variables and are conditioned to the use of climate predictors. This major restriction of the models has generated distributions of low accuracy or inconsistent with the actual cover. Our objective was to characterize the environmental space of the most representative biomes of Brazil and predict their cover, using climate and soil-related predictors. As sample units, we used 500 cells of 100 km2 for ten biomes, derived from the official vegetation map of Brazil (IBGE 2004). With a total of 38 (climatic and soil-related) predictors, an a priori model was run with the random forest classifier. Each biome was calibrated with 75% of the samples. The final model was based on four climate and six soil-related predictors, the most important variables for the a priori model, without collinearity. The model reached a kappa value of 0.82, generating a highly consistent prediction with the actual cover of the country. We showed here that the richness of biomes should not be underestimated, and that in spite of the complex relationship, highly accurate modeling based on climatic and soil-related predictors is possible. These predictors are complementary, for covering different parts of the multidimensional niche. Thus, a single biome can cover a wide range of climatic space, versus a narrow range of soil types, so that its prediction is best adjusted by soil-related variables, or vice versa.

Community measures of low-fat milk consumption: comparing store shelves with households.

PubMed

Fisher, B D; Strogatz, D S

1999-02-01

This study examined the relationship between the proportion of milk in food stores that is low-fat and consumption of low-fat milk in the community. Data were gathered from 503 stores across 53 New York State zip codes. In 19 zip codes, a telephone survey measured household low-fat milk use. Census data were obtained to examine sociodemographic predictors of the percentage of low-fat milk in stores. The proportion of low-fat milk in stores was directly related to low-fat milk consumption in households and to the median income and urban level of the zip code. These results support using food store shelf-space observations to estimate low-fat milk consumption.

Automated Knowledge Discovery From Simulators

NASA Technical Reports Server (NTRS)

Burl, Michael; DeCoste, Dennis; Mazzoni, Dominic; Scharenbroich, Lucas; Enke, Brian; Merline, William

2007-01-01

A computational method, SimLearn, has been devised to facilitate efficient knowledge discovery from simulators. Simulators are complex computer programs used in science and engineering to model diverse phenomena such as fluid flow, gravitational interactions, coupled mechanical systems, and nuclear, chemical, and biological processes. SimLearn uses active-learning techniques to efficiently address the "landscape characterization problem." In particular, SimLearn tries to determine which regions in "input space" lead to a given output from the simulator, where "input space" refers to an abstraction of all the variables going into the simulator, e.g., initial conditions, parameters, and interaction equations. Landscape characterization can be viewed as an attempt to invert the forward mapping of the simulator and recover the inputs that produce a particular output. Given that a single simulation run can take days or weeks to complete even on a large computing cluster, SimLearn attempts to reduce costs by reducing the number of simulations needed to effect discoveries. Unlike conventional data-mining methods that are applied to static predefined datasets, SimLearn involves an iterative process in which a most informative dataset is constructed dynamically by using the simulator as an oracle. On each iteration, the algorithm models the knowledge it has gained through previous simulation trials and then chooses which simulation trials to run next. Running these trials through the simulator produces new data in the form of input-output pairs. The overall process is embodied in an algorithm that combines support vector machines (SVMs) with active learning. SVMs use learning from examples (the examples are the input-output pairs generated by running the simulator) and a principle called maximum margin to derive predictors that generalize well to new inputs. In SimLearn, the SVM plays the role of modeling the knowledge that has been gained through previous simulation trials. Active learning is used to determine which new input points would be most informative if their output were known. The selected input points are run through the simulator to generate new information that can be used to refine the SVM. The process is then repeated. SimLearn carefully balances exploration (semi-randomly searching around the input space) versus exploitation (using the current state of knowledge to conduct a tightly focused search). During each iteration, SimLearn uses not one, but an ensemble of SVMs. Each SVM in the ensemble is characterized by different hyper-parameters that control various aspects of the learned predictor - for example, whether the predictor is constrained to be very smooth (nearby points in input space lead to similar output predictions) or whether the predictor is allowed to be "bumpy." The various SVMs will have different preferences about which input points they would like to run through the simulator next. SimLearn includes a formal mechanism for balancing the ensemble SVM preferences so that a single choice can be made for the next set of trials.

Identifying Predictors of Social Functioning in College Students: A Meta-Analysis

ERIC Educational Resources Information Center

Beard, Jennifer Blair

2011-01-01

This meta-analysis draws studies from the literature on college student persistence, need theories, and positive psychology in investigating the strongest predictors of social functioning in college students in the United States and Canada. The predictor categories included background characteristics, measures of personality, mental health…

Posterior consistency in conditional distribution estimation

PubMed Central

Pati, Debdeep; Dunson, David B.; Tokdar, Surya T.

2014-01-01

A wide variety of priors have been proposed for nonparametric Bayesian estimation of conditional distributions, and there is a clear need for theorems providing conditions on the prior for large support, as well as posterior consistency. Estimation of an uncountable collection of conditional distributions across different regions of the predictor space is a challenging problem, which differs in some important ways from density and mean regression estimation problems. Defining various topologies on the space of conditional distributions, we provide sufficient conditions for posterior consistency focusing on a broad class of priors formulated as predictor-dependent mixtures of Gaussian kernels. This theory is illustrated by showing that the conditions are satisfied for a class of generalized stick-breaking process mixtures in which the stick-breaking lengths are monotone, differentiable functions of a continuous stochastic process. We also provide a set of sufficient conditions for the case where stick-breaking lengths are predictor independent, such as those arising from a fixed Dirichlet process prior. PMID:25067858

Immigration, acculturation, and risk factors for obesity and cardiovascular disease: a comparison between Latinos of Peruvian descent in Peru and in the United States.

PubMed

Lizarzaburu, Jesus L; Palinkas, Lawrence A

2002-01-01

To determine whether migration and acculturation was associated with risk factors for obesity and cardiovascular disease, whether this association is linear or curvilinear, and whether the socio-cultural context alters the association between obesity and cardiovascular disease and individual-level variables. Lima, Peru, San Diego and San Francisco, California. Ninety-two Peruvian residents of Lima and 83 Peruvian immigrant residents of California. total cholesterol, blood pressure, body mass index, waist-to-hip ratio. A significant linear association was found between migration and acculturation and alcohol consumption and total cholesterol in men and women, systolic (SBP) and diastolic (DBP) blood pressure and body mass index in men, and physical activity in women. Immigration/acculturation level was a significant independent predictor of total cholesterol. Age and body mass index were independent predictors of total cholesterol only in Peru. Sex was an independent predictor of DBP only in the United States. Body mass index was an in dependent predictor of DBP only in Peru. Household income was an independent predictor of SBP and DBP only in Peru and body mass index only in the United States, while level of education was inversely associated with body mass index only in Peru. Regular strenuous physical activity was an independent predictor of obesity measures only in the United States. The socio-cultural context alters the risk of obesity and cardiovascular disease associated with individual-level variables and accounts for gender and cross-national differences in the migration-illness association.

Nurse staffing levels and Medicaid reimbursement rates in nursing facilities.

PubMed

Harrington, Charlene; Swan, James H; Carrillo, Helen

2007-06-01

To examine the relationship between nursing staffing levels in U.S. nursing homes and state Medicaid reimbursement rates. Facility staffing, characteristics, and case-mix data were from the federal On-Line Survey Certification and Reporting (OSCAR) system and other data were from public sources. Ordinary least squares and two-stage least squares regression analyses were used to separately examine the relationship between registered nurse (RN) and total nursing hours in all U.S. nursing homes in 2002, with two endogenous variables: Medicaid reimbursement rates and resident case mix. RN hours and total nursing hours were endogenous with Medicaid reimbursement rates and resident case mix. As expected, Medicaid nursing home reimbursement rates were positively related to both RN and total nursing hours. Resident case mix was a positive predictor of RN hours and a negative predictor of total nursing hours. Higher state minimum RN staffing standards was a positive predictor of RN and total nursing hours while for-profit facilities and the percent of Medicaid residents were negative predictors. To increase staffing levels, average Medicaid reimbursement rates would need to be substantially increased while higher state minimum RN staffing standards is a stronger positive predictor of RN and total nursing hours.

Radiographic assessment of lower third molar eruption in different anteroposterior skeletal patterns and age-related groups.

PubMed

Jakovljevic, Aleksandar; Lazic, Emira; Soldatovic, Ivan; Nedeljkovic, Nenad; Andric, Miroslav

2015-07-01

To analyze radiographic predictors for lower third molar eruption among subjects with different anteroposterior skeletal relations and of different age groups. In total, 300 lower third molars were recorded on diagnostic digital orthopantomograms (DPTs) and lateral cephalograms (LCs). The radiographs were grouped according to sagittal intermaxillary angle (ANB), subject age, and level of lower third molar eruption. The DPT was used to analyze retromolar space, mesiodistal crown width, space/width ratio, third and second molar angulation (α, γ), third molar inclination (β), and gonion angle. The LC was used to determine ANB, angles of maxillar and mandibular prognathism (SNA, SNB), mandibular plane angle (SN/MP), and mandibular lengths. A logistic regression model was created using the statistically significant predictors. The logistic regression analysis revealed a statistically significant impact of β angle and distance between gonion and gnathion (Go-Gn) on the level of lower third molar eruption (P < .001 and P < .015, respectively). The retromolar space was significantly increased in the adult subgroup for all skeletal classes. The lower third molar impaction rate was significantly higher in the adult subgroup with the Class II (62.3%) compared with Class III subjects (31.7%; P < .013). The most favorable values of linear and angular predictors of mandibular third molar eruption were measured in Class III subjects. For valid estimation of mandibular third molar eruption, certain linear and angular measures (β angle, Go-Gn), as well as the size of the retromolar space, need to be considered.

Pre-Veterinary Medical Grade Point Averages as Predictors of Academic Success in Veterinary College.

ERIC Educational Resources Information Center

Julius, Marcia F.; Kaiser, Herbert E.

1978-01-01

A five-year longitudinal study was designed to find the best predictors of academic success in veterinary school at Kansas State University and to set up a multiple regression formula to be used in selecting students. The preveterinary grade point average was found to be the best predictor. (JMD)

Driving Competence in Mild Dementia with Lewy Bodies: In Search of Cognitive Predictors Using Driving Simulation

PubMed Central

Yamin, Stephanie; Stinchcombe, Arne; Gagnon, Sylvain

2015-01-01

Driving is a multifactorial behaviour drawing on multiple cognitive, sensory, and physical systems. Dementia is a progressive and degenerative neurological condition that impacts the cognitive processes necessary for safe driving. While a number of studies have examined driving among individuals with Alzheimer's disease, less is known about the impact of Dementia with Lewy Bodies (DLB) on driving safety. The present study compared simulated driving performance of 15 older drivers with mild DLB with that of 21 neurologically healthy control drivers. DLB drivers showed poorer performance on all indicators of simulated driving including an increased number of collisions in the simulator and poorer composite indicators of overall driving performance. A measure of global cognitive function (i.e., the Mini Mental State Exam) was found to be related to the overall driving performance. In addition, measures of attention (i.e., Useful Field of View, UFOV) and space processing (Visual Object and Space Perception, VOSP, Test) correlated significantly with a rater's assessment of driving performance. PMID:26713169

MIT research in telerobotics

NASA Technical Reports Server (NTRS)

Sheridan, T. B.

1987-01-01

Ongoing MIT research in telerobotics (vehicles capable of some autonomous sensing and manipulating, having some remote supervisory control by people) and teleoperation (vehicles for sensing and manipulating which are fully controlled remotely by people) is discussed. The current efforts mix human and artificial intelligence/control. The idea of adjustable impedance at either end of pure master-slave teleoperation, and simultaneous coordinated control of teleoperator/telerobotic systems which have more than six degrees of freedom (e.g., a combined vehicle and arm, each with five or six DOF) are discussed. A new cable-controlled parallel link arm which offers many advantages over conventional arms for space is briefly described. Predictor displays to compensate for time delay in teleoperator loops, the use of state estimation to help human control decisions in space, and ongoing research in supervisory command language are covered. Finally, efforts to build a human flyable real-time dynamic computer-graphic telerobot simulator are described. These projects represent most, but not all, of the telerobotics research in our laboratory, supported by JPL, NASA Ames and NOAA.

Investigating the Performance of Alternate Regression Weights by Studying All Possible Criteria in Regression Models with a Fixed Set of Predictors

ERIC Educational Resources Information Center

Waller, Niels; Jones, Jeff

2011-01-01

We describe methods for assessing all possible criteria (i.e., dependent variables) and subsets of criteria for regression models with a fixed set of predictors, x (where x is an n x 1 vector of independent variables). Our methods build upon the geometry of regression coefficients (hereafter called regression weights) in n-dimensional space. For a…

Predictors of Outcomes for African Americans in a Rehabilitation State Agency: Implications for National Policy and Practice

ERIC Educational Resources Information Center

Balcazar, Fabricio E.; Oberoi, Ashmeet K.; Suarez-Balcazar, Yolanda; Alvarado, Francisco

2012-01-01

A review of vocational rehabilitation (VR) data from a Midwestern state was conducted to identify predictors of rehabilitation outcomes for African American consumers. The database included 37,404 African Americans who were referred or self-referred over a period of five years. Logistic regression analysis indicated that except for age and…

Cancer of the Colorectum in Maine, 1995-1998: Determinants of Stage at Diagnosis in a Rural State

ERIC Educational Resources Information Center

Parsons, Margaret A.; Askland, Kathleen D.

2007-01-01

Context: Despite screening for colorectal cancer, mortality in the United States remains substantial. In northern New England, little is known about predictors of stage at diagnosis, an important determinant of survival and mortality. Purpose: The objective of this study was to identify predictors of late stage at diagnosis for colorectal cancer…

A State-Trait Model of Negative Life Event Occurrence in Adolescence: Predictors of Stability in the Occurrence of Stressors

ERIC Educational Resources Information Center

King, Kevin M.; Molina, Brooke S. G.; Chassin, Laurie

2008-01-01

Stressful life events are an important risk factor for psychopathology among children and adolescents. However, variation in life stress may be both stable and time-varying with associated differences in the antecedents. We tested, using latent variable modeling, a state-trait model of stressful life events in adolescence, and predictors of…

Motivational Factors and Predictors for Attending a Continuing Education Program for Older Adults

ERIC Educational Resources Information Center

Cachioni, Meire; Nascimento Ordonez, Tiago; Lima da Silva, Thais Bento; Tavares Batistoni, Samila Sathler; Sanches Yassuda, Mônica; Caldeira Melo, Ruth; Rodrigues da Costa Domingues, Marisa Accioly; Lopes, Andrea

2014-01-01

The objectives were to describe the stated motives of participants who enrolled in a program at the Open University for the Elderly (UnATI, in Portuguese), identify correlations between the stated motives and sociodemographic data, and find a set of predictors related to the listed motives. A total of 306 middle-aged and elderly adults aged 50 or…

A new finite element formulation for computational fluid dynamics. IX - Fourier analysis of space-time Galerkin/least-squares algorithms

NASA Technical Reports Server (NTRS)

Shakib, Farzin; Hughes, Thomas J. R.

1991-01-01

A Fourier stability and accuracy analysis of the space-time Galerkin/least-squares method as applied to a time-dependent advective-diffusive model problem is presented. Two time discretizations are studied: a constant-in-time approximation and a linear-in-time approximation. Corresponding space-time predictor multi-corrector algorithms are also derived and studied. The behavior of the space-time algorithms is compared to algorithms based on semidiscrete formulations.

Community measures of low-fat milk consumption: comparing store shelves with households.

PubMed Central

Fisher, B D; Strogatz, D S

1999-01-01

OBJECTIVES: This study examined the relationship between the proportion of milk in food stores that is low-fat and consumption of low-fat milk in the community. METHODS: Data were gathered from 503 stores across 53 New York State zip codes. In 19 zip codes, a telephone survey measured household low-fat milk use. Census data were obtained to examine sociodemographic predictors of the percentage of low-fat milk in stores. RESULTS: The proportion of low-fat milk in stores was directly related to low-fat milk consumption in households and to the median income and urban level of the zip code. CONCLUSIONS: These results support using food store shelf-space observations to estimate low-fat milk consumption. PMID:9949755

Predictor-based multivariable closed-loop system identification of the EXTRAP T2R reversed field pinch external plasma response

NASA Astrophysics Data System (ADS)

Olofsson, K. Erik J.; Brunsell, Per R.; Rojas, Cristian R.; Drake, James R.; Hjalmarsson, Håkan

2011-08-01

The usage of computationally feasible overparametrized and nonregularized system identification signal processing methods is assessed for automated determination of the full reversed-field pinch external plasma response spectrum for the experiment EXTRAP T2R. No assumptions on the geometry of eigenmodes are imposed. The attempted approach consists of high-order autoregressive exogenous estimation followed by Markov block coefficient construction and Hankel matrix singular value decomposition. It is seen that the obtained 'black-box' state-space models indeed can be compared with the commonplace ideal magnetohydrodynamics (MHD) resistive thin-shell model in cylindrical geometry. It is possible to directly map the most unstable autodetected empirical system pole to the corresponding theoretical resistive shell MHD eigenmode.

On neural networks in identification and control of dynamic systems

NASA Technical Reports Server (NTRS)

Phan, Minh; Juang, Jer-Nan; Hyland, David C.

1993-01-01

This paper presents a discussion of the applicability of neural networks in the identification and control of dynamic systems. Emphasis is placed on the understanding of how the neural networks handle linear systems and how the new approach is related to conventional system identification and control methods. Extensions of the approach to nonlinear systems are then made. The paper explains the fundamental concepts of neural networks in their simplest terms. Among the topics discussed are feed forward and recurrent networks in relation to the standard state-space and observer models, linear and nonlinear auto-regressive models, linear, predictors, one-step ahead control, and model reference adaptive control for linear and nonlinear systems. Numerical examples are presented to illustrate the application of these important concepts.

The influence of high school academics on freshman college mathematics and science courses at SUNY Oswego

NASA Astrophysics Data System (ADS)

Hayali, Tolga

This study examined the relationship between 2011 freshman college mathematics and science grades and freshman students' high school academics and demographic data, exploring the factors that contribute to the success of first-year STEM majoring freshman students at State University of New York at Oswego. The variables were Gender, Race, SES, School Size, Parent with College Education, High School Grade Point Average (HSGPA), Transfer Credit, SAT Composite Score, and New York State Regents Exam results, based on data from 237 freshman students entering college immediately following high school. The findings show HSGPA as a significant predictor of success in freshman College Mathematics and Sciences, Transfer Credit as a significant predictor in College Mathematics and College Chemistry, SES as a significant predictor in College Biology and College Chemistry, Parent with College Education as a significant predictor in College Biology and New York State Chemistry Regents Exam as a significant predictor in College Chemistry. Based on these findings, guidance counselors, science educators, and education institutions can develop a framework to determine which measurements are meaningful and advise students to focus on excellent performance in the Chemistry Regents Exams, take more college courses during high school, and maintain a high grade point average.

Self Efficacy and Some Demographic Variables as Predictors of Occupational Stress among Primary School Teachers in Delta State of Nigeria

ERIC Educational Resources Information Center

Akpochafo, G. O.

2014-01-01

This study investigated self efficacy and some demographic variables as predictors of occupational stress among primary school teachers in Delta State. Three hypotheses were formulated to guide the study. The study adopted a descriptive survey design that utilized an expost-facto research type. A sample of one hundred and twenty primary school…

Evaluation of the Freshman Class To Determine Predictors for Academic Success at Panhandle State University. Emergence of Higher Education in America Seminar.

ERIC Educational Resources Information Center

Manning, Wayne

A study was done at Panhandle State University (Oklahoma) examining whether high school grade point averages or ACT (American College Testing) scores provided a better predictor of freshman academic success. Study procedures included a review of the literature, meetings with the academic vice president and five deans, as well as examination of…

Ensemble Canonical Correlation Prediction of Seasonal Precipitation Over the United States: Raising the Bar for Dynamical Model Forecasts

NASA Technical Reports Server (NTRS)

Lau, William K. M.; Kim, Kyu-Myong; Shen, S. P.

2001-01-01

This paper presents preliminary results of an ensemble canonical correlation (ECC) prediction scheme developed at the Climate and Radiation Branch, NASA/Goddard Space Flight Center for determining the potential predictability of regional precipitation, and for climate downscaling studies. The scheme is tested on seasonal hindcasts of anomalous precipitation over the continental United States using global sea surface temperature (SST) for 1951-2000. To maximize the forecast skill derived from SST, the world ocean is divided into non-overlapping sectors. The canonical SST modes for each sector are used as the predictor for the ensemble hindcasts. Results show that the ECC yields a substantial (10-25%) increase in prediction skills for all the regions of the US in every season compared to traditional CCA prediction schemes. For the boreal winter, the tropical Pacific contributes the largest potential predictability to precipitation in the southwestern and southeastern regions, while the North Pacific and the North Atlantic are responsible to the enhanced forecast skills in the Pacific Northwest, the northern Great Plains and Ohio Valley. Most importantly, the ECC increases skill for summertime precipitation prediction and substantially reduces the spring predictability barrier over all the regions of the US continent. Besides SST, the ECC is designed with the flexibility to include any number of predictor fields, such as soil moisture, snow cover and additional local observations. The enhanced ECC forecast skill provides a new benchmark for evaluating dynamical model forecasts.

Life-Space Mobility Change Predicts 6-Month Mortality.

PubMed

Kennedy, Richard E; Sawyer, Patricia; Williams, Courtney P; Lo, Alexander X; Ritchie, Christine S; Roth, David L; Allman, Richard M; Brown, Cynthia J

2017-04-01

To examine 6-month change in life-space mobility as a predictor of subsequent 6-month mortality in community-dwelling older adults. Prospective cohort study. Community-dwelling older adults from five Alabama counties in the University of Alabama at Birmingham (UAB) Study of Aging. A random sample of 1,000 Medicare beneficiaries, stratified according to sex, race, and rural or urban residence, recruited between November 1999 and February 2001, followed by a telephone interview every 6 months for the subsequent 8.5 years. Mortality data were determined from informant contacts and confirmed using the National Death Index and Social Security Death Index. Life-space was measured at each interview using the UAB Life-Space Assessment, a validated instrument for assessing community mobility. Eleven thousand eight hundred seventeen 6-month life-space change scores were calculated over 8.5 years of follow-up. Generalized linear mixed models were used to test predictors of mortality at subsequent 6-month intervals. Three hundred fifty-four deaths occurred within 6 months of two sequential life-space assessments. Controlling for age, sex, race, rural or urban residence, and comorbidity, life-space score and life-space decline over the preceding 6-month interval predicted mortality. A 10-point decrease in life-space resulted in a 72% increase in odds of dying over the subsequent 6 months (odds ratio = 1.723, P < .001). Life-space score at the beginning of a 6-month interval and change in life-space over 6 months were each associated with significant differences in subsequent 6-month mortality. Life-space assessment may assist clinicians in identifying older adults at risk of short-term mortality. © 2017, Copyright the Authors Journal compilation © 2017, The American Geriatrics Society.

Predicting In-State Workforce Retention After Graduate Medical Education Training.

PubMed

Koehler, Tracy J; Goodfellow, Jaclyn; Davis, Alan T; Spybrook, Jessaca; vanSchagen, John E; Schuh, Lori

2017-02-01

There is a paucity of literature when it comes to identifying predictors of in-state retention of graduate medical education (GME) graduates, such as the demographic and educational characteristics of these physicians. The purpose was to use demographic and educational predictors to identify graduates from a single Michigan GME sponsoring institution, who are also likely to practice medicine in Michigan post-GME training. We included all residents and fellows who graduated between 2000 and 2014 from 1 of 18 GME programs at a Michigan-based sponsoring institution. Predictor variables identified by logistic regression with cross-validation were used to create a scoring tool to determine the likelihood of a GME graduate to practice medicine in the same state post-GME training. A 6-variable model, which included 714 observations, was identified. The predictor variables were birth state, program type (primary care versus non-primary care), undergraduate degree location, medical school location, state in which GME training was completed, and marital status. The positive likelihood ratio (+LR) for the scoring tool was 5.31, while the negative likelihood ratio (-LR) was 0.46, with an accuracy of 74%. The +LR indicates that the scoring tool was useful in predicting whether graduates who trained in a Michigan-based GME sponsoring institution were likely to practice medicine in Michigan following training. Other institutions could use these techniques to identify key information that could help pinpoint matriculating residents/fellows likely to practice medicine within the state in which they completed their training.

Statistical Evaluation of Causal Factors Associated with Astronaut Shoulder Injury in Space Suits.

PubMed

Anderson, Allison P; Newman, Dava J; Welsch, Roy E

2015-07-01

Shoulder injuries due to working inside the space suit are some of the most serious and debilitating injuries astronauts encounter. Space suit injuries occur primarily in the Neutral Buoyancy Laboratory (NBL) underwater training facility due to accumulated musculoskeletal stress. We quantitatively explored the underlying causal mechanisms of injury. Logistic regression was used to identify relevant space suit components, training environment variables, and anthropometric dimensions related to an increased propensity for space-suited injury. Two groups of subjects were analyzed: those whose reported shoulder incident is attributable to the NBL or working in the space suit, and those whose shoulder incidence began in active duty, meaning working in the suit could be a contributing factor. For both groups, percent of training performed in the space suit planar hard upper torso (HUT) was the most important predictor variable for injury. Frequency of training and recovery between training were also significant metrics. The most relevant anthropometric dimensions were bideltoid breadth, expanded chest depth, and shoulder circumference. Finally, record of previous injury was found to be a relevant predictor for subsequent injury. The first statistical model correctly identifies 39% of injured subjects, while the second model correctly identifies 68% of injured subjects. A review of the literature suggests this is the first work to quantitatively evaluate the hypothesized causal mechanisms of all space-suited shoulder injuries. Although limited in predictive capability, each of the identified variables can be monitored and modified operationally to reduce future impacts on an astronaut's health.

Predictors of vulnerability to reduced body image satisfaction and psychological wellbeing in response to exposure to idealized female media images in adolescent girls.

PubMed

Durkin, Sarah J; Paxton, Susan J

2002-11-01

Predictors of change in body satisfaction, depressed mood, anxiety and anger, were examined following exposure to idealized female advertising images in Grades 7 and 10 girls. Stable body dissatisfaction, physical appearance comparison tendency, internalization of thin ideal, self-esteem, depression, identity confusion and body mass index (BMI) were assessed. One week later, participants viewed magazine images, before and after which they completed assessments of state body satisfaction, state depression, state anxiety and state anger. Participants were randomly allocated to view either images of idealized females (experimental condition) or fashion accessories (control condition). For both grades, there was a significant decrease in state body satisfaction and a significant increase in state depression attributable to viewing the female images. In Grade 7 girls in the experimental condition, decrease in state body satisfaction was predicted by stable body dissatisfaction and BMI, while significant predictors of decreases in the measures of negative affect included internalization of the thin-ideal and appearance comparison. In Grade 10 girls, reduction in state body satisfaction and increase in state depression was predicted by internalization of the thin-ideal, appearance comparison and stable body dissatisfaction. These findings indicate the importance of individual differences in short-term reaction to viewing idealized media images. Copyright 2002 Elsevier Science Inc.

A Deep Machine Learning Algorithm to Optimize the Forecast of Atmospherics

NASA Astrophysics Data System (ADS)

Russell, A. M.; Alliss, R. J.; Felton, B. D.

Space-based applications from imaging to optical communications are significantly impacted by the atmosphere. Specifically, the occurrence of clouds and optical turbulence can determine whether a mission is a success or a failure. In the case of space-based imaging applications, clouds produce atmospheric transmission losses that can make it impossible for an electro-optical platform to image its target. Hence, accurate predictions of negative atmospheric effects are a high priority in order to facilitate the efficient scheduling of resources. This study seeks to revolutionize our understanding of and our ability to predict such atmospheric events through the mining of data from a high-resolution Numerical Weather Prediction (NWP) model. Specifically, output from the Weather Research and Forecasting (WRF) model is mined using a Random Forest (RF) ensemble classification and regression approach in order to improve the prediction of low cloud cover over the Haleakala summit of the Hawaiian island of Maui. RF techniques have a number of advantages including the ability to capture non-linear associations between the predictors (in this case physical variables from WRF such as temperature, relative humidity, wind speed and pressure) and the predictand (clouds), which becomes critical when dealing with the complex non-linear occurrence of clouds. In addition, RF techniques are capable of representing complex spatial-temporal dynamics to some extent. Input predictors to the WRF-based RF model are strategically selected based on expert knowledge and a series of sensitivity tests. Ultimately, three types of WRF predictors are chosen: local surface predictors, regional 3D moisture predictors and regional inversion predictors. A suite of RF experiments is performed using these predictors in order to evaluate the performance of the hybrid RF-WRF technique. The RF model is trained and tuned on approximately half of the input dataset and evaluated on the other half. The RF approach is validated using in-situ observations of clouds. All of the hybrid RF-WRF experiments demonstrated here significantly outperform the base WRF local low cloud cover forecasts in terms of the probability of detection and the overall bias. In particular, RF experiments that use only regional three-dimensional moisture predictors from the WRF model produce the highest accuracy when compared to RF experiments that use local surface predictors only or regional inversion predictors only. Furthermore, adding multiple types of WRF predictors and additional WRF predictors to the RF algorithm does not necessarily add more value in the resulting forecasts, indicating that it is better to have a small set of meaningful predictors than to have a vast set of indiscriminately-chosen predictors. This work also reveals that the WRF-based RF approach is highly sensitive to the time period over which the algorithm is trained and evaluated. Future work will focus on developing a similar WRF-based RF model for high cloud prediction and expanding the algorithm to two-dimensions horizontally.

Predictors of Payer Mix and Financial Performance Among Safety Net Hospitals Prior to the Affordable Care Act.

PubMed

Sommers, Benjamin D; Stone, Juliana; Kane, Nancy

2016-01-01

The objective of this study was to use audited hospital financial statements to identify predictors of payer mix and financial performance in safety net hospitals prior to the Affordable Care Act. We analyzed the 2010 financial statements of 98 large, urban safety net hospital systems in 34 states, supplemented with data on population demographics, hospital features, and state policies. We used multivariate regression to identify independent predictors of three outcomes: 1) Medicaid-reliant payer mix (hospitals for which at least 25% of hospital days are paid for by Medicaid); 2) safety net revenue-to-cost ratio (Medicaid and Medicare Disproportionate Share Hospital payments and local government transfers, divided by charity care costs and Medicaid payment shortfall); and 3) operating margin. Medicaid-reliant payer mix was positively associated with more inclusive state Medicaid eligibility criteria and more minority patients. More inclusive Medicaid eligibility and higher Medicaid reimbursement rates positively predicted safety net revenue-to-cost ratio. University governance was the strongest positive predictor of operating margin. Safety net hospital financial performance varied considerably. Academic hospitals had higher operating margins, while more generous Medicaid eligibility and reimbursement policies improved hospitals' ability to recoup costs. Institutional and state policies may outweigh patient demographics in the financial health of safety net hospitals. © The Author(s) 2015.

Child Physical Abuse Prevalence, Characteristics, Predictors, and Beliefs about Parent-Child Violence in South Asian, Middle Eastern, East Asian, and Latina Women in the United States

ERIC Educational Resources Information Center

Maker, Azmaira H.; Shah, Priti V.; Agha, Zia

2005-01-01

The present study examined the prevalence, characteristics, beliefs, and demographic predictors of parent-child physical violence among South Asian, Middle Eastern, East Asian, and Latina women in the United States. Two hundred fifty-one college-educated women from a middle to high SES (South Asian/Middle Eastern, n = 93; East Asian, n = 72;…

Mode of Entry as a Predictor of Success in Final Year Bachelor of Education Degree Examinations in Universities in Ekiti and Ondo States, Nigeria

ERIC Educational Resources Information Center

Adeyemi, T. O.

2009-01-01

This paper investigates the mode of entry as a predictor of success in final year bachelor of education degree examinations in universities in Ekiti and Ondo States, Nigeria. As an ex-post facto and correlational research, the study population comprised all the 1810 final year 400 level students in the two universities offering education courses,…

Telerobotic Surgery: An Intelligent Systems Approach to Mitigate the Adverse Effects of Communication Delay. Chapter 4

NASA Technical Reports Server (NTRS)

Cardullo, Frank M.; Lewis, Harold W., III; Panfilov, Peter B.

2007-01-01

An extremely innovative approach has been presented, which is to have the surgeon operate through a simulator running in real-time enhanced with an intelligent controller component to enhance the safety and efficiency of a remotely conducted operation. The use of a simulator enables the surgeon to operate in a virtual environment free from the impediments of telecommunication delay. The simulator functions as a predictor and periodically the simulator state is corrected with truth data. Three major research areas must be explored in order to ensure achieving the objectives. They are: simulator as predictor, image processing, and intelligent control. Each is equally necessary for success of the project and each of these involves a significant intelligent component in it. These are diverse, interdisciplinary areas of investigation, thereby requiring a highly coordinated effort by all the members of our team, to ensure an integrated system. The following is a brief discussion of those areas. Simulator as a predictor: The delays encountered in remote robotic surgery will be greater than any encountered in human-machine systems analysis, with the possible exception of remote operations in space. Therefore, novel compensation techniques will be developed. Included will be the development of the real-time simulator, which is at the heart of our approach. The simulator will present real-time, stereoscopic images and artificial haptic stimuli to the surgeon. Image processing: Because of the delay and the possibility of insufficient bandwidth a high level of novel image processing is necessary. This image processing will include several innovative aspects, including image interpretation, video to graphical conversion, texture extraction, geometric processing, image compression and image generation at the surgeon station. Intelligent control: Since the approach we propose is in a sense predictor based, albeit a very sophisticated predictor, a controller, which not only optimizes end effector trajectory but also avoids error, is essential. We propose to investigate two different approaches to the controller design. One approach employs an optimal controller based on modern control theory; the other one involves soft computing techniques, i.e. fuzzy logic, neural networks, genetic algorithms and hybrids of these.

Vestibular response to pseudorandom angular velocity input: progress report.

PubMed

Lessard, C S; Wong, W C

1987-09-01

Space motion sickness was not reported during the first Apollo missions; however, since Apollo 8 through the current Shuttle and Skylab missions, approximately 50% of the crewmembers have experienced instances of space motion sickness. One of NASA's efforts to resolve the space adaptation syndrome is to model the vestibular response for both basic knowledge and as a possible predictor of an individual's susceptibility to the disorder. This report describes a method to analyze the vestibular system when subjected to a pseudorandom angular velocity input.

The Influence of Urbanism and Information Consumption on Political Dimensions of Social Capital: Exploratory Study of the Localities Adjacent to the Core City from Brașov Metropolitan Area, Romania.

PubMed

Rezeanu, Cătălina-Ionela; Briciu, Arabela; Briciu, Victor; Repanovici, Angela; Coman, Claudiu

2016-01-01

The last two decades have seen a growing trend towards the research of voting behavior in post-communist countries. Urban sociology theorists state that not only space structures influence political participation, but also space structures are changing under the influence of global, local, and individual factors. The growing role played by information in the globalised world has accelerated the paradigm shift in urban sociology: from central place model (based on urban-rural distinction and on monocentric metropolitan areas) to network society (based on space of flows and polycentric metropolitan areas). However, recent studies have mainly focused on countries with solid democracies, rather than on former communist countries. The present study aims to analyze the extent to which a new emerging spatial structure can be envisaged within a metropolitan area of Romania and its consequences for the political dimensions of social capital. The Transilvania University Ethics Commission approved this study (S1 Aprouval). The research is based upon individual and aggregate empirical data, collected from the areas adjacent to the core city in Brașov metropolitan area. Individual data has been collected during October 2012, using the oral survey technique (S1 Survey), based on a standardized questionnaire (stratified simple random sample, N = 600). The National Institute of Statistics and the Electoral Register provided the aggregate data per locality. Unvaried and multivariate analyses (hierarchical regression method) were conducted based on these data. Some dimensions of urbanism, identified as predictors of the political dimensions of social capital, suggest that the area under analysis has a predominantly monocentric character, where the rural-urban distinction continues to remain relevant. There are also arguments favoring the dissolution of the rural-urban distinction and the emergence of polycentric spatial structures. The presence of some influences related to the information consumption on all six indicators of the political dimensions of social capital under analysis suggests the occurrence of emerging forms of a space of flows. The identified effects of social problems associated with transport infrastructure and of migration experience on the political dimensions of social capital, also support the emergence of space of flows. We recommend that, in the urban studies in former communist countries, conceptualization of urbanism as predictor of the political dimensions of social capital should consider both the material dimensions of space, as well as the dimensions of information consumption and migration experience.

The Influence of Urbanism and Information Consumption on Political Dimensions of Social Capital: Exploratory Study of the Localities Adjacent to the Core City from Brașov Metropolitan Area, Romania

PubMed Central

Rezeanu, Cătălina-Ionela; Briciu, Arabela; Briciu, Victor; Repanovici, Angela; Coman, Claudiu

2016-01-01

Background The last two decades have seen a growing trend towards the research of voting behavior in post-communist countries. Urban sociology theorists state that not only space structures influence political participation, but also space structures are changing under the influence of global, local, and individual factors. The growing role played by information in the globalised world has accelerated the paradigm shift in urban sociology: from central place model (based on urban-rural distinction and on monocentric metropolitan areas) to network society (based on space of flows and polycentric metropolitan areas). However, recent studies have mainly focused on countries with solid democracies, rather than on former communist countries. The present study aims to analyze the extent to which a new emerging spatial structure can be envisaged within a metropolitan area of Romania and its consequences for the political dimensions of social capital. Methods The Transilvania University Ethics Commission approved this study (S1 Aprouval). The research is based upon individual and aggregate empirical data, collected from the areas adjacent to the core city in Brașov metropolitan area. Individual data has been collected during October 2012, using the oral survey technique (S1 Survey), based on a standardized questionnaire (stratified simple random sample, N = 600). The National Institute of Statistics and the Electoral Register provided the aggregate data per locality. Unvaried and multivariate analyses (hierarchical regression method) were conducted based on these data. Results Some dimensions of urbanism, identified as predictors of the political dimensions of social capital, suggest that the area under analysis has a predominantly monocentric character, where the rural-urban distinction continues to remain relevant. There are also arguments favoring the dissolution of the rural-urban distinction and the emergence of polycentric spatial structures. The presence of some influences related to the information consumption on all six indicators of the political dimensions of social capital under analysis suggests the occurrence of emerging forms of a space of flows. The identified effects of social problems associated with transport infrastructure and of migration experience on the political dimensions of social capital, also support the emergence of space of flows. Conclusions We recommend that, in the urban studies in former communist countries, conceptualization of urbanism as predictor of the political dimensions of social capital should consider both the material dimensions of space, as well as the dimensions of information consumption and migration experience. PMID:26807882

Difficulties with Regression Analysis of Age-Adjusted Rates.

DTIC Science & Technology

1982-09-01

variables used in those analyses, such as death rates in various states, have been age adjusted, whereas the predictor variables have not been age adjusted...The use of crude state death rates as the outcome variable with crude covariates and age as predictors can avoid the problem, at least under some...should be regressed on age-adjusted exposure Z+B+ Although age-specific death rates , Yas+’ may be available, it is often difficult to obtain age

A neuroanatomical model of space-based and object-centered processing in spatial neglect.

PubMed

Pedrazzini, Elena; Schnider, Armin; Ptak, Radek

2017-11-01

Visual attention can be deployed in space-based or object-centered reference frames. Right-hemisphere damage may lead to distinct deficits of space- or object-based processing, and such dissociations are thought to underlie the heterogeneous nature of spatial neglect. Previous studies have suggested that object-centered processing deficits (such as in copying, reading or line bisection) result from damage to retro-rolandic regions while impaired spatial exploration reflects damage to more anterior regions. However, this evidence is based on small samples and heterogeneous tasks. Here, we tested a theoretical model of neglect that takes in account the space- and object-based processing and relates them to neuroanatomical predictors. One hundred and one right-hemisphere-damaged patients were examined with classic neuropsychological tests and structural brain imaging. Relations between neglect measures and damage to the temporal-parietal junction, intraparietal cortex, insula and middle frontal gyrus were examined with two structural equation models by assuming that object-centered processing (involved in line bisection and single-word reading) and space-based processing (involved in cancelation tasks) either represented a unique latent variable or two distinct variables. Of these two models the latter had better explanatory power. Damage to the intraparietal sulcus was a significant predictor of object-centered, but not space-based processing, while damage to the temporal-parietal junction predicted space-based, but not object-centered processing. Space-based processing and object-centered processing were strongly intercorrelated, indicating that they rely on similar, albeit partly dissociated processes. These findings indicate that object-centered and space-based deficits in neglect are partly independent and result from superior parietal and inferior parietal damage, respectively.

Mature Driver Laws and State Predictors of Motor Vehicle Crash Fatality Rates Among the Elderly: A Cross-sectional Ecological Study.

PubMed

Bell, Teresa M; Qiao, Nan; Zarzaur, Ben L

2015-01-01

State-level data have indicated that motor vehicle crash (MVC) fatality rates among the elderly vary widely across states. To date, the majority of states have implemented mature driver laws, which often require more frequent license renewals, in-person renewal, and vision testing for drivers above a certain age. We sought to evaluate the impact of mature driver laws on states' MVC fatality rates among the elderly while examining other state-level determinants of MVC-related deaths. We performed a cross-sectional ecological study and modeled state MVC fatality rates for the population over age 65 as a function of state transportation policies and demographic, health system, population health, travel, and climate characteristics using a general linear model. Principal component analysis was used to reduce dimensionality of the data and overcome multicollinearity of state predictor variables. Higher average temperature, higher gas prices, and a greater number of emergency medicine physicians to population size were significantly associated with lower MVC fatality rates. Positive predictors of MVC fatality rates were percentage of population overweight or obese and percentage with college degree over the age of 65. Having any restriction on elderly drivers was associated with a higher MVC fatality rate and no individual component of mature driver laws (shortened renewal cycle, in-person renewal, and vision testing) was significantly associated with lower fatality MVC rates for adults over 65. Mature driver laws are not associated with lower state MVC fatality rates among the elderly.

Sampled-data chain-observer design for a class of delayed nonlinear systems

NASA Astrophysics Data System (ADS)

Kahelras, M.; Ahmed-Ali, T.; Giri, F.; Lamnabhi-Lagarrigue, F.

2018-05-01

The problem of observer design is addressed for a class of triangular nonlinear systems with not-necessarily small delay and sampled output measurements. One more difficulty is that the system state matrix is dependent on the un-delayed output signal which is not accessible to measurement, making existing observers inapplicable. A new chain observer, composed of m elementary observers in series, is designed to compensate for output sampling and arbitrary large delays. The larger the time-delay the larger the number m. Each elementary observer includes an output predictor that is conceived to compensate for the effects of output sampling and a fractional delay. The predictors are defined by first-order ordinary differential equations (ODEs) much simpler than those of existing predictors which involve both output and state predictors. Using a small gain type analysis, sufficient conditions for the observer to be exponentially convergent are established in terms of the minimal number m of elementary observers and the maximum sampling interval.

The impact of subjective memory complaints on quality of life in community-dwelling older adults.

PubMed

Maki, Yohko; Yamaguchi, Tomoharu; Yamagami, Tetsuya; Murai, Tatsuhiko; Hachisuka, Kenji; Miyamae, Fumiko; Ito, Kae; Awata, Shuichi; Ura, Chiaki; Takahashi, Ryutaro; Yamaguchi, Haruyasu

2014-09-01

The aim of this study was to evaluate the impact of memory complaints on quality of life (QOL) in elderly community dwellers with or without mild cognitive impairment (MCI). Participants included 120 normal controls (NC) and 37 with MCI aged 65 and over. QOL was measured using the Japanese version of Satisfaction in Daily Life, and memory complaints were measured using a questionnaire consisting of four items. The relevance of QOL was evaluated with psychological factors of personality traits, sense of self-efficacy, depressive mood, self-evaluation of daily functioning, range of social activities (Life-Space Assessment), social network size, and cognitive functions including memory. The predictors of QOL were analyzed by multiple linear regression analysis. QOL was not significantly different between the NC and MCI groups. In both groups, QOL was positively correlated with self-efficacy, daily functioning, social network size, Life-Space Assessment, and the personality traits of extraversion and agreeableness; QOL was negatively correlated with memory complaints, depressive mood, and the personality trait of neuroticism. In regression analysis, memory complaints were a negative predictor of QOL in the MCI group, but not in the NC group. The partial correlation coefficient between QOL and memory complaints was -0.623 (P < 0.05), after scores of depressive mood and self-efficacy were controlled. Depressive mood was a common negative predictor in both groups. Positive predictors were Life-Space Assessment in the NC group and sense of self-efficacy in the MCI group. Memory complaints exerted a negative impact on self-rated QOL in the MCI group, whereas a negative correlation was weak in the NC group. Memory training has been widely practised in individuals with MCI to prevent the development of dementia. However, such approaches inevitably identify their memory deficits and could aggravate their awareness of memory decline. Thus, it is critical to give sufficient consideration not to reduce QOL in the intervention for those with MCI. © 2014 The Authors. Psychogeriatrics © 2014 Japanese Psychogeriatric Society.

A homotopy method based on WENO schemes for solving steady state problems of hyperbolic conservation laws

DTIC Science & Technology

2012-09-03

prac- tice to solve these initial value problems. Additionally, the predictor / corrector methods are combined with adaptive stepsize and adaptive ...for implementing a numerical path tracking algorithm is to decide which predictor / corrector method to employ, how large to take the step ∆t, and what...the endgame algorithm . Output: A steady state solution Set ǫ = 1 while ǫ >= ǫend do set the stepsize ∆ǫ by using adaptive stepsize control algorithm

Predictors of Secondary Traumatic Stress among Children's Advocacy Center Forensic Interviewers

ERIC Educational Resources Information Center

Bonach, Kathryn; Heckert, Alex

2012-01-01

This study examined various predictor variables that were hypothesized to impact secondary traumatic stress in forensic interviewers (n = 257) from children's advocacy centers across the United States. Data were examined to investigate the relationship between organizational satisfaction, organizational buffers, and job support with secondary…

Predictors of Academic Procrastination in Asian International College Students

ERIC Educational Resources Information Center

Lowinger, Robert Jay; Kuo, Ben C. H.; Song, Hyun-A.; Mahadevan, Lakshmi; Kim, Eunyoung; Liao, Kelly Yu-Hsin; Chang, Catherine Y.; Kwon, Kyong-Ah; Han, Suejung

2016-01-01

This study examined the relationships among acculturative stress, coping styles, self-efficacy, English language proficiency, and various demographic characteristics as predictors of procrastination behavior in Asian International students (N = 255) studying in the United States. Results of multiple logistic regression indicated that a collective…

Predicting risk for disciplinary action by a state medical board.

PubMed

Cardarelli, Roberto; Licciardone, John C; Ramirez, Gilbert

2004-01-01

Disciplinary actions taken against physicians in the United States have been increasing over the last decade, yet the factors that place physicians at risk have not been well identified. The objective of this study is to identify predictors of physician disciplinary action. This case-control study used data from the Texas State Board of Medical Examiners from January 1989 through December 1998. Characteristics of disciplined physicians and predictors of disciplinary action for all violations and by type of violation were the main outcome descriptors. Years in practice, black physicians, and osteopathic graduates were positive predictors for disciplinary action. In contrast, female physicians, international medical graduates, and Hispanic and Asian physicians were less likely to receive disciplinary action compared with male, US allopathic, and white physicians, respectively. Most specialists, except psychiatrists and obstetrician-gynecologists, were less likely to be disciplined than were family practitioners, whereas general practitioners were more likely to be disciplined. More studies are needed to corroborate these findings.

National Trends and Predictors of Locally Advanced Penile Cancer in the United States (1998-2012).

PubMed

Chipollini, Juan; Chaing, Sharon; Peyton, Charles C; Sharma, Pranav; Kidd, Laura C; Giuliano, Anna R; Johnstone, Peter A; Spiess, Philippe E

2017-08-12

We analyzed the trends in presentation of squamous cell carcinoma (SCC) of the penis and determined the socioeconomic predictors for locally advanced (cT3-cT4) disease in the United States. The National Cancer Database was queried for patients with clinically nonmetastatic penile SCC and staging available from 1998 to 2012. Temporal trends per tumor stage were evaluated, and a multivariable logistic regression model was used to identify predictors for advanced presentation during the study period. A total of 5767 patients with stage ≤ T1-T2 (n = 5423) and T3-T4 (n = 344) disease were identified. Increasing trends were noted in all stages of penile SCC with a greater proportion of advanced cases over time (P = .001). Significant predictors of advanced presentation were age > 55 years, the presence of comorbidities, and Medicaid or no insurance (P < .05 for all). More penile SCC is being detected in the United States. Our results have demonstrated older age, presence of comorbidities, and Medicaid or no insurance as potential barriers to early access of care in the male population. Understanding the current socioeconomic gaps could help guide targeted interventions in vulnerable populations. Copyright © 2017 Elsevier Inc. All rights reserved.

Neural Predictors of Visuomotor Adaptation Rate and Multi-Day Savings

NASA Technical Reports Server (NTRS)

Cassady, Kaitlin; Ruitenberg, Marit; Koppelmans, Vincent; Reuter-Lorenz, Patricia; De Dios, Yiri; Gadd, Nichole; Wood, Scott; Riascos Castenada, Roy; Kofman, Igor; Bloomberg, Jacob;

DRREP: deep ridge regressed epitope predictor.

PubMed

Sher, Gene; Zhi, Degui; Zhang, Shaojie

2017-10-03

The ability to predict epitopes plays an enormous role in vaccine development in terms of our ability to zero in on where to do a more thorough in-vivo analysis of the protein in question. Though for the past decade there have been numerous advancements and improvements in epitope prediction, on average the best benchmark prediction accuracies are still only around 60%. New machine learning algorithms have arisen within the domain of deep learning, text mining, and convolutional networks. This paper presents a novel analytically trained and string kernel using deep neural network, which is tailored for continuous epitope prediction, called: Deep Ridge Regressed Epitope Predictor (DRREP). DRREP was tested on long protein sequences from the following datasets: SARS, Pellequer, HIV, AntiJen, and SEQ194. DRREP was compared to numerous state of the art epitope predictors, including the most recently published predictors called LBtope and DMNLBE. Using area under ROC curve (AUC), DRREP achieved a performance improvement over the best performing predictors on SARS (13.7%), HIV (8.9%), Pellequer (1.5%), and SEQ194 (3.1%), with its performance being matched only on the AntiJen dataset, by the LBtope predictor, where both DRREP and LBtope achieved an AUC of 0.702. DRREP is an analytically trained deep neural network, thus capable of learning in a single step through regression. By combining the features of deep learning, string kernels, and convolutional networks, the system is able to perform residue-by-residue prediction of continues epitopes with higher accuracy than the current state of the art predictors.

Predictor Development and Pilot Testing of a Prototype Selection Instrument for Army Flight Training

DTIC Science & Technology

2007-02-01

called the Automated Pilot Examination System, or "APEX") during the preliminary validation reserach . The current version of the ASTB includes subtests...of objects in three-dimensional space . Aviation & Nautical Information: items assess an examinee’s familiarity with aviation history, nautical...proficiency. Aviation, Space and Environmental Medicine, 46, 309-311. Daryanian, B. (1980). Subjective scaling of mental workload in a multi-task environment

Penalized Ordinal Regression Methods for Predicting Stage of Cancer in High-Dimensional Covariate Spaces.

PubMed

Gentry, Amanda Elswick; Jackson-Cook, Colleen K; Lyon, Debra E; Archer, Kellie J

2015-01-01

The pathological description of the stage of a tumor is an important clinical designation and is considered, like many other forms of biomedical data, an ordinal outcome. Currently, statistical methods for predicting an ordinal outcome using clinical, demographic, and high-dimensional correlated features are lacking. In this paper, we propose a method that fits an ordinal response model to predict an ordinal outcome for high-dimensional covariate spaces. Our method penalizes some covariates (high-throughput genomic features) without penalizing others (such as demographic and/or clinical covariates). We demonstrate the application of our method to predict the stage of breast cancer. In our model, breast cancer subtype is a nonpenalized predictor, and CpG site methylation values from the Illumina Human Methylation 450K assay are penalized predictors. The method has been made available in the ordinalgmifs package in the R programming environment.

Predictors of Employment Outcomes for State-Federal Vocational Rehabilitation Consumers with HIV/AIDS

ERIC Educational Resources Information Center

Jung, Youngoh; Schaller, James; Bellini, James

2010-01-01

In this study, the authors investigated the effects of demographic, medical, and vocational rehabilitation service variables on employment outcomes of persons living with HIV/AIDS. Binary logistic regression analyses were conducted to determine predictors of employment outcomes using two groups drawn from Rehabilitation Services Administration…

Planning in subsumption architectures

NASA Technical Reports Server (NTRS)

Chalfant, Eugene C.

1994-01-01

A subsumption planner using a parallel distributed computational paradigm based on the subsumption architecture for control of real-world capable robots is described. Virtual sensor state space is used as a planning tool to visualize the robot's anticipated effect on its environment. Decision sequences are generated based on the environmental situation expected at the time the robot must commit to a decision. Between decision points, the robot performs in a preprogrammed manner. A rudimentary, domain-specific partial world model contains enough information to extrapolate the end results of the rote behavior between decision points. A collective network of predictors operates in parallel with the reactive network forming a recurrrent network which generates plans as a hierarchy. Details of a plan segment are generated only when its execution is imminent. The use of the subsumption planner is demonstrated by a simple maze navigation problem.

A State-Space Approach to Optimal Level-Crossing Prediction for Linear Gaussian Processes

NASA Technical Reports Server (NTRS)

Martin, Rodney Alexander

2009-01-01

In many complex engineered systems, the ability to give an alarm prior to impending critical events is of great importance. These critical events may have varying degrees of severity, and in fact they may occur during normal system operation. In this article, we investigate approximations to theoretically optimal methods of designing alarm systems for the prediction of level-crossings by a zero-mean stationary linear dynamic system driven by Gaussian noise. An optimal alarm system is designed to elicit the fewest false alarms for a fixed detection probability. This work introduces the use of Kalman filtering in tandem with the optimal level-crossing problem. It is shown that there is a negligible loss in overall accuracy when using approximations to the theoretically optimal predictor, at the advantage of greatly reduced computational complexity. I

Hybrid Smith predictor and phase lead based divergence compensation for hardware-in-the-loop contact simulation with measurement delay

NASA Astrophysics Data System (ADS)

Qi, Chenkun; Gao, Feng; Zhao, Xianchao; Wang, Qian; Ren, Anye

2018-06-01

On the ground the hardware-in-the-loop (HIL) simulation is a good approach to test the contact dynamics of spacecraft docking process in space. Unfortunately, due to the time delay in the system the HIL contact simulation becomes divergent. However, the traditional first-order phase lead compensation approach still result in a small divergence for the pure time delay. The serial Smith predictor and phase lead compensation approach proposed by the authors recently will lead to an over-compensation and an obvious convergence. In this study, a hybrid Smith predictor and phase lead compensation approach is proposed. The hybrid Smith predictor and phase lead compensation can achieve a higher simulation fidelity with a little convergence. The phase angle of the compensator is analyzed and the stability condition of the HIL simulation system is given. The effectiveness of the proposed compensation approach is tested by simulations on an undamped elastic contact process.

Predictors of negotiated NIH indirect rates at US institutions.

PubMed

Johnston, S Claiborne; Desmond-Hellmann, Susan; Hauser, Stewart; Vermillion, Eric; Mia, Nilo

2015-01-01

The United States (US) Department of Health and Human Services and the Office of Naval Research negotiate institutional rates for payments of overhead costs associated with administration and space usage, commonly known as indirect rates. Such payments account for a large proportion of spending by the National Institutes of Health (NIH). Little has been published about differences in rates and their predictors. Negotiated indirect rates for on-campus research grants were requested from the Council on Governmental Relations for the 100 institutions with greatest NIH funding in 2010. NIH funding, cost of living (ACCRA Index for 2008), public vs. private status, negotiating governmental organization (Department of Health and Human Services or Office of Naval Research), US Census Region, and year were assessed as predictors of institutional indirect rates using generalized estimating equations with all variables included in the model. Overall, 72 institutions participated, with 207 reported indirect rates for the years 2006, 2008, and 2010. Indirect rates ranged from 36.3% to 78%, with an average of 54.5%. Mean rates increased from 53.6% in 2006 to 55.4% in 2010 (p<0.001). In multivariable models, private institutions had 6.2% (95% CI 3.7%-8.7%; p<0.001) higher indirect rates than public institutions. Rates in the Northeast were highest (Midwest 4.0% lower; West 4.9% lower; South 5.2% lower). Greater NIH funding (p = 0.025) and cost of living (p = 0.034) also predicted indirect rates while negotiating governmental organization did not (p = 0.414). Negotiated indirect rates for governmental research grants to academic centers vary widely. Although the association between indirect rates and cost of living may be justified, the cause of variation in rates by region, public-private status, and NIH funding levels is unclear.

Altitude, gun ownership, rural areas, and suicide.

PubMed

Kim, Namkug; Mickelson, Jennie B; Brenner, Barry E; Haws, Charlotte A; Yurgelun-Todd, Deborah A; Renshaw, Perry F

2011-01-01

The authors recently observed a correlation between state altitude and suicide rate in the United States, which could be explained by higher rates of gun ownership and lower population density in the intermountain West. The present study evaluated the relationship between mean county and state altitude in the United States and total age-adjusted suicide rates, firearm-related suicide rates, and non-firearm-related suicide rates. The authors hypothesized that altitude would be significantly associated with suicide rate. Elevation data were calculated with an approximate spatial resolution of 0.5 km, using zonal statistics on data sets compiled from the National Geospatial-Intelligence Agency and the National Aeronautics and Space Administration. Suicide and population density data were obtained through the Centers for Disease Control and Prevention (CDC) WONDER database. Gun ownership data were obtained through the CDC's Behavioral Risk Factor Surveillance System. A significant positive correlation was observed between age-adjusted suicide rate and county elevation (r=0.51). Firearm (r=0.41) and non-firearm suicide rates (r=0.32) were also positively correlated with mean county elevation. When altitude, gun ownership, and population density are considered as predictor variables for suicide rates on a state basis, altitude appears to be a significant independent risk factor. This association may be related to the effects of metabolic stress associated with mild hypoxia in individuals with mood disorders.

Altitude, Gun Ownership, Rural Areas, and Suicide

PubMed Central

Kim, Namkug; Mickelson, Jennie B.; Brenner, Barry E.; Haws, Charlotte A.; Yurgelun-Todd, Deborah A.; Renshaw, Perry F.

2015-01-01

Objective The authors recently observed a correlation between state altitude and suicide rate in the United States, which could be explained by higher rates of gun ownership and lower population density in the intermountain West. The present study evaluated the relationship between mean county and state altitude in the United States and total age-adjusted suicide rates, firearm-related suicide rates, and non-firearm-related suicide rates. The authors hypothesized that altitude would be significantly associated with suicide rate. Method Elevation data were calculated with an approximate spatial resolution of 0.5 km, using zonal statistics on data sets compiled from the National Geospatial-Intelligence Agency and the National Aeronautics and Space Administration. Suicide and population density data were obtained through the Centers for Disease Control and Prevention (CDC) WONDER database. Gun ownership data were obtained through the CDC’s Behavioral Risk Factor Surveillance System. Results A significant positive correlation was observed between age-adjusted suicide rate and county elevation (r=0.51). Firearm (r=0.41) and non-firearm suicide rates (r=0.32) were also positively correlated with mean county elevation. Conclusions When altitude, gun ownership, and population density are considered as predictor variables for suicide rates on a state basis, altitude appears to be a significant independent risk factor. This association may be related to the effects of metabolic stress associated with mild hypoxia in individuals with mood disorders. PMID:20843869

Improved Survival Endpoints With Adjuvant Radiation Treatment in Patients With High-Risk Early-Stage Endometrial Carcinoma

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

Elshaikh, Mohamed A., E-mail: melshai1@hfhs.org; Vance, Sean; Suri, Jaipreet S.

2014-02-01

Purpose/Objective(s): To determine the impact of adjuvant radiation treatment (RT) on recurrence-free survival (RFS), disease-specific survival (DSS), and overall survival (OS) in patients with high-risk 2009 International Federation of Gynecology and Obstetrics stage I-II endometrial carcinoma. Methods and Materials: We identified 382 patients with high-risk EC who underwent hysterectomy. RFS, DSS, and OS were calculated from the date of hysterectomy by use of the Kaplan-Meier method. Cox regression modeling was used to explore the risks associated with various factors on survival endpoints. Results: The median follow-up time for the study cohort was 5.4 years. The median age was 71 years.more » All patients underwent hysterectomy and salpingo-oophorectomy, 93% had peritoneal cytology, and 85% underwent lymphadenectomy. Patients with endometrioid histology constituted 72% of the study cohort, serous in 16%, clear cell in 7%, and mixed histology in 4%. Twenty-three percent of patients had stage II disease. Adjuvant management included RT alone in 220 patients (57%), chemotherapy alone in 25 patients (7%), and chemoradiation therapy in 27 patients (7%); 110 patients (29%) were treated with close surveillance. The 5-year RFS, DSS, and OS were 76%, 88%, and 73%, respectively. On multivariate analysis, adjuvant RT was a significant predictor of RFS (P<.001) DSS (P<.001), and OS (P=.017). Lymphovascular space involvement was a significant predictor of RFS and DSS (P<.001). High tumor grade was a significant predictor for RFS (P=.038) and DSS (P=.025). Involvement of the lower uterine segment was also a predictor of RFS (P=.049). Age at diagnosis and lymphovascular space involvement were significant predictors of OS: P<.001 and P=.002, respectively. Conclusion: In the treatment of patients with high-risk features, our study suggests that adjuvant RT significantly improves recurrence-free, disease-specific, and overall survival in patients with early-stage endometrial carcinoma. Furthermore, adjuvant RT is an independent predictor for RFS, DSS, and OS in this group of patients. These findings need validation from a prospective randomized study.« less

Does initial spacing influence crown and hydraulic architecture of Eucalyptus marginata?

PubMed

Grigg, A H; Macfarlane, C; Evangelista, C; Eamus, D; Adams, M A

2008-05-01

Long-term declines in rainfall in south-western Australia have resulted in increased interest in the hydraulic characteristics of jarrah (Eucalyptus marginata Donn ex Smith) forest established in the region's drinking water catchments on rehabilitated bauxite mining sites. We hypothesized that in jarrah forest established on rehabilitated mine sites: (1) leaf area index (L) is independent of initial tree spacing; and (2) more densely planted trees have less leaf area for the same leaf mass, or the same sapwood area, and have denser sapwood. Initial stand densities ranged from about 600 to 9000 stems ha(-1), and trees were 18 years old at the time of sampling. Leaf area index was unaffected by initial stand density, except in the most sparsely stocked stands where L was 1.2 compared with 2.0-2.5 in stands at other spacings. The ratio of leaf area to sapwood area (A(l):A(s)) was unaffected by tree spacing or tree size and was 0.2 at 1.3 m height and 0.25 at the crown base. There were small increases in sapwood density and decreases in leaf specific area with increased spacing. Tree diameter or basal area was a better predictor of leaf area than sapwood area. At the stand scale, basal area was a good predictor of L (r(2) = 0.98, n = 15) except in the densest stands. We conclude that the hydraulic attributes of this forest type are largely independent of initial tree spacing, thus simplifying parameterization of stand and catchment water balance models.

Complaints against Nursing Homes: Comparing Two Sources of Complaint Information and Predictors of Complaints

ERIC Educational Resources Information Center

Troyer, Jennifer L.; Sause, Wendy L.

2011-01-01

Purpose of the Study: Two consumer-derived measures of nursing home quality that have been underutilized by researchers are consumer complaints to the state certification agency between inspections and complaints to the Long-Term Care Ombudsman Program. This article describes these complaints, considers facility-level predictors of complaints, and…

Predictors of Retention in Smoking Cessation Treatment among Latino Smokers in the Northeast United States

ERIC Educational Resources Information Center

Lee, Christina S.; Hayes, Rashelle B.; McQuaid, Elizabeth L.; Borrelli, Belinda

2010-01-01

Introduction. Only one previous study on minority retention in smoking cessation treatment has been conducted (Nevid JS, Javier RA, Moulton JL III. "Factors predicting participant attrition in a community-based, culturally specific smoking cessation program for Hispanic smokers." "Health Psychol" 1996; 15: 226-29). We investigated predictors of…

Predictors, spatial distribution, and occurrence of woody invasive plants in subtropical urban ecosystems

Treesearch

Christina L. Staudhammer; Francisco J. Escobedo; Nathan Holt; Linda J. Young; Thomas J. Brandeis; Wayne Zipperer; Other

2015-01-01

We examined the spatial distribution, occurrence, and socioecological predictors of woody invasive plants (WIP) in two subtropical, coastal urban ecosystems: San Juan, Puerto Rico and Miami-Dade, United States. These two cities have similar climates and ecosystems typical of subtropical regions but differ in socioeconomics, topography, and urbanization processes. Using...

Motivational state controls the prediction error in Pavlovian appetitive-aversive interactions.

PubMed

Laurent, Vincent; Balleine, Bernard W; Westbrook, R Frederick

2018-01-01

Contemporary theories of learning emphasize the role of a prediction error signal in driving learning, but the nature of this signal remains hotly debated. Here, we used Pavlovian conditioning in rats to investigate whether primary motivational and emotional states interact to control prediction error. We initially generated cues that positively or negatively predicted an appetitive food outcome. We then assessed how these cues modulated aversive conditioning when a novel cue was paired with a foot shock. We found that a positive predictor of food enhances, whereas a negative predictor of that same food impairs, aversive conditioning. Critically, we also showed that the enhancement produced by the positive predictor is removed by reducing the value of its associated food. In contrast, the impairment triggered by the negative predictor remains insensitive to devaluation of its associated food. These findings provide compelling evidence that the motivational value attributed to a predicted food outcome can directly control appetitive-aversive interactions and, therefore, that motivational processes can modulate emotional processes to generate the final error term on which subsequent learning is based. Copyright © 2017 Elsevier Inc. All rights reserved.

Examining gender salary disparities: an analysis of the 2003 multistate salary survey.

PubMed

Brown, Lawrence M; Schommer, Jon C; Mott, Dave; Gaither, Caroline A; Doucette, William R; Zgarrick, Dave P; Droege, Marcus

2006-09-01

Pharmacist salary and wage surveys have been conducted at the state and national level for more than 20 years; however, it is not known to what extent, if any, wage disparities due to gender still exist. The overall objective of this study was to determine if wage disparities exist among male and female pharmacists at the multistate and individual state level for each of 6 states studied. A secondary objective was to explore the effect of various demographic variables on the hourly wages of pharmacists. Data were collected from 1,688 pharmacists in 6 states during 2003 using a cross-sectional descriptive survey design. A multiple regression analysis on hourly wage testing the effects of state of practice, practice setting, position, terminal degree, and years in practice was conducted. Subsequent multiple regression analyses were conducted individually for each of the 6 states to test the effects of the above variables on hourly wage for both male and female pharmacists, followed by state-level analyses for male and female pharmacists, respectively. For the pooled data, all variables were found to be significant predictors of hourly wage, except for earning a PharmD degree without a residency or graduate degree. Gender was not a significant predictor of wage disparities in the state-level analyses. Position was the only significant predictor of wage disparities in all states (except Tennessee) such that pharmacists in management positions make significantly higher salaries than those in staff positions. The results of these analyses suggest that wage disparities due to gender do not exist at the state level for the 6 states surveyed, when controlling for practice setting, position, terminal degree, and years in practice. The larger number of men in management positions may explain lower wages for female pharmacists.

A finite difference solution for the propagation of sound in near sonic flows

NASA Technical Reports Server (NTRS)

Hariharan, S. I.; Lester, H. C.

1983-01-01

An explicit time/space finite difference procedure is used to model the propagation of sound in a quasi one-dimensional duct containing high Mach number subsonic flow. Nonlinear acoustic equations are derived by perturbing the time-dependent Euler equations about a steady, compressible mean flow. The governing difference relations are based on a fourth-order, two-step (predictor-corrector) MacCormack scheme. The solution algorithm functions by switching on a time harmonic source and allowing the difference equations to iterate to a steady state. The principal effect of the non-linearities was to shift acoustical energy to higher harmonics. With increased source strengths, wave steepening was observed. This phenomenon suggests that the acoustical response may approach a shock behavior at at higher sound pressure level as the throat Mach number aproaches unity. On a peak level basis, good agreement between the nonlinear finite difference and linear finite element solutions was observed, even through a peak sound pressure level of about 150 dB occurred in the throat region. Nonlinear steady state waveform solutions are shown to be in excellent agreement with a nonlinear asymptotic theory.

The impact of homophobia, poverty, and racism on the mental health of gay and bisexual Latino men: findings from 3 US cities.

PubMed

Díaz, R M; Ayala, G; Bein, E; Henne, J; Marin, B V

2001-06-01

This study assessed the relation between experiences of social discrimination (homophobia, racism, and financial hardship) and symptoms of psychologic distress (anxiety, depression, and suicidal ideation) among self-identified gay and bisexual Latino men in the United States. Data were collected from a probability sample of 912 men (self-identified as both Latino and nonheterosexual) recruited from the venues and public social spaces identified as both Latino and gay in the cities of Miami, Los Angeles, and New York. The study showed high prevalence rates of psychologic symptoms of distress in the population of gay Latino men during the 6 months before the interview, including suicidal ideation (17% prevalence), anxiety (44%), and depressed mood (80%). In both univariate and multivariate analyses, experiences of social discrimination were strong predictors of psychologic symptoms. The mental health difficulties experienced by many gay and bisexual Latino men in the United States are directly related to a social context of oppression that leads to social alienation, low self-esteem, and symptoms of psychologic distress.

The impact of homophobia, poverty, and racism on the mental health of gay and bisexual Latino men: findings from 3 US cities.

PubMed Central

Díaz, R M; Ayala, G; Bein, E; Henne, J; Marin, B V

2001-01-01

OBJECTIVES: This study assessed the relation between experiences of social discrimination (homophobia, racism, and financial hardship) and symptoms of psychologic distress (anxiety, depression, and suicidal ideation) among self-identified gay and bisexual Latino men in the United States. METHODS: Data were collected from a probability sample of 912 men (self-identified as both Latino and nonheterosexual) recruited from the venues and public social spaces identified as both Latino and gay in the cities of Miami, Los Angeles, and New York. RESULTS: The study showed high prevalence rates of psychologic symptoms of distress in the population of gay Latino men during the 6 months before the interview, including suicidal ideation (17% prevalence), anxiety (44%), and depressed mood (80%). In both univariate and multivariate analyses, experiences of social discrimination were strong predictors of psychologic symptoms. CONCLUSIONS: The mental health difficulties experienced by many gay and bisexual Latino men in the United States are directly related to a social context of oppression that leads to social alienation, low self-esteem, and symptoms of psychologic distress. PMID:11392936

Cougar space use and movements in the wildland-urban landscape of western Washington

USGS Publications Warehouse

Kertson, B.N.; Spencer, R.D.; Marzluff, J.M.; Hepinstall-Cymerman, Jeffrey; Grue, C.E.

2011-01-01

The wildland-urban interface lies at the confluence of human-dominated and wild landscapes, creating a number of management and conservation challenges. Because wildlife ecology, behavior, and evolution at this interface are shaped by both natural and human phenomena, this requires greater understanding of how diverse factors affect ecosystem and population processes. We illustrate the challenge of understanding and managing a frequent and often undesired inhabitant of the wildland-urban landscape, the cougar (Puma concolor). In wildland and residential areas of western Washington State, USA, we captured and radiotracked 27 cougars to model space use and understand the role of landscape features in interactions (sightings, encounters, and depredations) between cougars and humans. Resource utilization functions (RUFs) identified cougar use of areas with features that were probably attractive to prey, influential on prey vulnerability, and associated with limited or no residential development. Early-successional forest (+), conifer forest (+), distance to road (-), residential density (-), and elevation (-) were significant positive and negative predictors of use for the population, whereas use of other landscape features was highly variable. Space use and movement rates in wildland and residential areas were similar because cougars used wildland-like forest patches, reserves, and corridors in residential portions of their home range. The population RUF was a good predictor of confirmed cougar interactions, with 72% of confirmed reports occurring in the 50% of the landscape predicted to be medium-high and high cougar use areas. We believe that there is a threshold residential density at which the level of development modifies the habitat but maintains enough wildland characteristics to encourage moderate levels of cougar use and maximize the probability of interaction. Wildlife managers trying to reduce interactions between cougars and people should incorporate information on spatial ecology and landscape characteristics to identify areas with the highest overlap of human and cougar use to focus management, education, and landscape planning. Resource utilization functions provide a proactive tool to guide these activities for improved coexistence with wildlife using both wildland and residential portions of the landscape. ??2011 by the Ecological Society of America.

ReactionPredictor: prediction of complex chemical reactions at the mechanistic level using machine learning.

PubMed

Kayala, Matthew A; Baldi, Pierre

2012-10-22

Proposing reasonable mechanisms and predicting the course of chemical reactions is important to the practice of organic chemistry. Approaches to reaction prediction have historically used obfuscating representations and manually encoded patterns or rules. Here we present ReactionPredictor, a machine learning approach to reaction prediction that models elementary, mechanistic reactions as interactions between approximate molecular orbitals (MOs). A training data set of productive reactions known to occur at reasonable rates and yields and verified by inclusion in the literature or textbooks is derived from an existing rule-based system and expanded upon with manual curation from graduate level textbooks. Using this training data set of complex polar, hypervalent, radical, and pericyclic reactions, a two-stage machine learning prediction framework is trained and validated. In the first stage, filtering models trained at the level of individual MOs are used to reduce the space of possible reactions to consider. In the second stage, ranking models over the filtered space of possible reactions are used to order the reactions such that the productive reactions are the top ranked. The resulting model, ReactionPredictor, perfectly ranks polar reactions 78.1% of the time and recovers all productive reactions 95.7% of the time when allowing for small numbers of errors. Pericyclic and radical reactions are perfectly ranked 85.8% and 77.0% of the time, respectively, rising to >93% recovery for both reaction types with a small number of allowed errors. Decisions about which of the polar, pericyclic, or radical reaction type ranking models to use can be made with >99% accuracy. Finally, for multistep reaction pathways, we implement the first mechanistic pathway predictor using constrained tree-search to discover a set of reasonable mechanistic steps from given reactants to given products. Webserver implementations of both the single step and pathway versions of ReactionPredictor are available via the chemoinformatics portal http://cdb.ics.uci.edu/.

The complex roles of space and environment in structuring functional, taxonomic and phylogenetic beta diversity of frogs in the Atlantic Forest

PubMed Central

Luiz, Amom Mendes; Sawaya, Ricardo J.

2018-01-01

Ecological communities are complex entities that can be maintained and structured by niche-based processes such as environmental conditions, and spatial processes such as dispersal. Thus, diversity patterns may be shaped simultaneously at different spatial scales by very distinct processes. Herein we assess whether and how functional, taxonomic, and phylogenetic beta diversities of frog tadpoles are explained by environmental and/or spatial predictors. We implemented a distance–based redundancy analysis to explore variation in components of beta diversity explained by pure environmental and pure spatial predictors, as well as their interactions, at both fine and broad spatial scales. Our results indicated important but complex roles of spatial and environmental predictors in structuring phylogenetic, taxonomic and functional beta diversities. The pure fine-scales spatial fraction was more important in structuring all beta diversity components, especially to functional and taxonomical spatial turnover. Environmental variables such as canopy cover and vegetation structure were important predictors of all components, but especially to functional and taxonomic beta diversity. We emphasize that distinct factors related to environment and space are affecting distinct components of beta diversity in different ways. Although weaker, phylogenetic beta diversity, which is structured more on biogeographical scales, and thus can be represented by spatially structured processes, was more related to broad spatial processes than other components. However, selected fine-scale spatial predictors denoted negative autocorrelation, which may be revealing the existence of differences in unmeasured habitat variables among samples. Although overall important, local environmental-based processes explained better functional and taxonomic beta diversity, as these diversity components carry an important ecological value. We highlight the importance of assessing different components of diversity patterns at different scales by spatially explicit models in order to improve our understanding of community structure and help to unravel the complex nature of biodiversity. PMID:29672575

Bayesian isotonic density regression

PubMed Central

Wang, Lianming; Dunson, David B.

2011-01-01

Density regression models allow the conditional distribution of the response given predictors to change flexibly over the predictor space. Such models are much more flexible than nonparametric mean regression models with nonparametric residual distributions, and are well supported in many applications. A rich variety of Bayesian methods have been proposed for density regression, but it is not clear whether such priors have full support so that any true data-generating model can be accurately approximated. This article develops a new class of density regression models that incorporate stochastic-ordering constraints which are natural when a response tends to increase or decrease monotonely with a predictor. Theory is developed showing large support. Methods are developed for hypothesis testing, with posterior computation relying on a simple Gibbs sampler. Frequentist properties are illustrated in a simulation study, and an epidemiology application is considered. PMID:22822259

Computational Approaches to Predict Indices of Cyanobacteria Toxicity.

EPA Science Inventory

As nutrient inputs increase, productivity increases and lakes transition from low trophic state (e.g., oligotrophic) to higher trophic states (e.g., eutrophic). These broad trophic state classifications are good predictors of ecosystem health and the potential for ecosystem serv...

Computational Approaches to Predict Indices of Cyanobacteria Toxicity

EPA Science Inventory

As nutrient inputs increase, productivity increases and lakes transition from low trophic state (e.g. oligotrophic) to higher trophic states (e.g. eutrophic). These broad trophic state classifications are good predictors of ecosystem health and the potential for ecosystem servic...

Ethnic/Racial, Religious, and Demographic Predictors of Organ Donor Registration Status Among Young Adults in the Southwestern United States.

PubMed

Ginossar, Tamar; Benavidez, Julian; Gillooly, Zachary D; Kanwal Attreya, Aarti; Nguyen, Hieu; Bentley, Joshua

2017-03-01

Context and Setting: New Mexico (NM) is a minority-majority state. Despite its unique cultural characteristics and documented ethnic/racial disparities in deceased organ donation (DOD), past studies did not explore predictors of organ donor registration status (ODRS) in this state. This study aimed at identifying demographic, cultural, and religious predictors of ODRS among a diverse sample of young adults in NM. This study focused on recruitment of American Indian, Hispanic, and Asian American participants through online social network sites and university listservs. Participants (N = 602) answered an online survey. The largest racial/ethnic group included American Indians (n = 200). Main outcome measures included ODRS, demographics, religious affiliation, and open-ended question on reasons for objections to DOD. Race/ethnicity, religion, and educational attainment were significant predictors of ODRS. Non-Hispanic whites (NHWs) were most likely to be registered as donors, with no significant difference between NHWs and Asians or Pacific Islanders. Non-Catholic Christians were most likely to be registered donors, followed by Catholics, practitioners of American Indian/Native American traditional religions, and Hindus, with Buddhists the least likely to register. This pattern was consistent with the propensity of individuals from these religious groups to cite religious objections to DOD. Finally, respondents who had graduated from high schools in NM were 2.3 times less likely to be registered as organ donors compared to those who had graduated in other states. This study provides evidence for the need for culturally tailored interventions targeting diverse communities in NM.

Organized music instruction as a predictor of nursing student success.

PubMed

Cesario, Sandra K; Cesario, Robert J; Cesario, Anthony R

2013-01-01

Stringent admission criteria exist for nursing programs in the United States, but better predictors of success are needed to reduce student attrition. Research indicates that organized music experiences are associated with greater academic success. This exploratory study examined the association between early music experiences and undergraduate nursing student success. Findings suggest that students with a music background were more likely to graduate, have higher grade point averages, and pass the licensure examination. Previous music education might be considered as an additional predictor of nursing student success.

The Impact of State Legislation and Model Policies on Bullying in Schools.

PubMed

Terry, Amanda

2018-04-01

The purpose of this study was to determine the impact of the coverage of state legislation and the expansiveness ratings of state model policies on the state-level prevalence of bullying in schools. The state-level prevalence of bullying in schools was based on cross-sectional data from the 2013 High School Youth Risk Behavior Survey. Multiple regression was conducted to determine whether the coverage of state legislation and the expansiveness rating of a state model policy affected the state-level prevalence of bullying in schools. The purpose and definition category of components in state legislation and the expansiveness rating of a state model policy were statistically significant predictors of the state-level prevalence of bullying in schools. The other 3 categories of components in state legislation-District Policy Development and Review, District Policy Components, and Additional Components-were not statistically significant predictors in the model. Extensive coverage in the purpose and definition category of components in state legislation and a high expansiveness rating of a state model policy may be important in efforts to reduce bullying in schools. Improving these areas may reduce the state-level prevalence of bullying in schools. © 2018, American School Health Association.

Intergroup conflict: Ecological predictors of winning and consequences of defeat in a wild primate population

PubMed Central

MARKHAM, A. CATHERINE; ALBERTS, SUSAN C.; ALTMANN, JEANNE

2012-01-01

In many social species, competition between groups is a major factor proximately affecting group-level movement patterns and space use and ultimately shaping the evolution of group living and complex sociality. Here we evaluated the factors influencing group-level dominance among 5 social groups of wild baboons (Papio cynocephalus), in particular focusing on the spatial determinants of dominance and the consequences of defeat. When direct conflict occurred between conspecific baboon groups, the winning group was predicted by differences in the number of adult males in each group and/or groups that had used the areas surrounding the encounter location more intensively than their opponent in the preceding 9 or 12 months. Relative intensity of space use over shorter timescales examined (3 and 6 months) was a poor predictor of the interaction’s outcome. Losing groups but not winning groups experienced clear short-term costs. Losing groups used the area surrounding the interaction less following an agonistic encounter (relative to their intensity of use of the area prior to the interaction). These findings offer insight into the influences and consequences of intergroup competition on group-level patterns of space use. PMID:22837555

Cluster-based control of a separating flow over a smoothly contoured ramp

NASA Astrophysics Data System (ADS)

Kaiser, Eurika; Noack, Bernd R.; Spohn, Andreas; Cattafesta, Louis N.; Morzyński, Marek

2017-12-01

The ability to manipulate and control fluid flows is of great importance in many scientific and engineering applications. The proposed closed-loop control framework addresses a key issue of model-based control: The actuation effect often results from slow dynamics of strongly nonlinear interactions which the flow reveals at timescales much longer than the prediction horizon of any model. Hence, we employ a probabilistic approach based on a cluster-based discretization of the Liouville equation for the evolution of the probability distribution. The proposed methodology frames high-dimensional, nonlinear dynamics into low-dimensional, probabilistic, linear dynamics which considerably simplifies the optimal control problem while preserving nonlinear actuation mechanisms. The data-driven approach builds upon a state space discretization using a clustering algorithm which groups kinematically similar flow states into a low number of clusters. The temporal evolution of the probability distribution on this set of clusters is then described by a control-dependent Markov model. This Markov model can be used as predictor for the ergodic probability distribution for a particular control law. This probability distribution approximates the long-term behavior of the original system on which basis the optimal control law is determined. We examine how the approach can be used to improve the open-loop actuation in a separating flow dominated by Kelvin-Helmholtz shedding. For this purpose, the feature space, in which the model is learned, and the admissible control inputs are tailored to strongly oscillatory flows.

S(he) Loves Me, S(he) Loves Me Not: Predictors of Relational Information-Seeking in Courtship and Beyond.

ERIC Educational Resources Information Center

Bell, Robert A.; Buerkel-Rothfuss, Nancy L.

1990-01-01

Examines the secret tests that couples use to acquire information about the state of their relationships. Examines predictors of when individuals are most likely to seek such information: commitment, perceptions of the partner's commitment, jealousy, and courtship progress. Explicates the associations among various dimensions of testing episodes.…

Perceived Support as a Predictor of Acculturative Stress among International Students in the United States

ERIC Educational Resources Information Center

Bai, Jieru

2016-01-01

A quantitative study was conducted to measure the acculturative stress of international students and investigate the predictors of acculturative stress. A total of 186 students participated in the survey. Results showed that 22.4% of the students in this study exceeded the normal stress level and might need counseling or psychological…

Latino and Caucasian Students' Academic and Non-Academic Characteristics as Predictors of Educational Outcomes, High School and Beyond

ERIC Educational Resources Information Center

Sanchez, Jafeth Evelyn

2010-01-01

The pathway to a postsecondary education is challenging for many students, including students from the growing Latino population in the United States. This research project focused on Latino and Caucasian students' academic and non-academic characteristics as predictors of educational outcomes, high school and beyond. The introduction to the…

Predictors of Student Success in Online Courses: Quantitative versus Qualitative Subject Matter

ERIC Educational Resources Information Center

Guidry, Krisandra

2013-01-01

This study seeks to examine whether the predictors of success for students in an online quantitative course are different than those for an online qualitative course. Data were collected from students taking online courses offered by an AACSB accredited College of Business at a medium sized state university (total student population 7,000) in…

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

ERIC Educational Resources Information Center

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

2017-01-01

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

A Comparison of Transition Predictors between Students Following Different Diploma Pathways

ERIC Educational Resources Information Center

Vierno, Peter Joseph

2013-01-01

The purpose of this study was to determine the extent to which evidence of two secondary transition predictors, paid employment and independent living, exist in the Individualized Education Plans (IEPs) of students on two pathways to a high school diploma in a southeastern state. The IEPs of 538 students were examined from one urban district in…

Attitudes towards Computer and Computer Self-Efficacy as Predictors of Preservice Mathematics Teachers' Computer Anxiety

ERIC Educational Resources Information Center

Awofala, Adeneye O. A.; Akinoso, Sabainah O.; Fatade, Alfred O.

2017-01-01

The study investigated attitudes towards computer and computer self-efficacy as predictors of computer anxiety among 310 preservice mathematics teachers from five higher institutions of learning in Lagos and Ogun States of Nigeria using the quantitative research method within the blueprint of the descriptive survey design. Data collected were…

Predictors of HIV/AIDS Programming in African American Churches: Implications for HIV Prevention, Testing, and Care

ERIC Educational Resources Information Center

Stewart, Jennifer M.; Hanlon, Alexandra; Brawner, Bridgette M.

2017-01-01

Using data from the National Congregational Study, we examined predictors of having an HIV/AIDS program in predominately African American churches across the United States. We conducted regression analyses of Wave II data (N = 1,506) isolating the sample to churches with a predominately African American membership. The dependent variable asked…

Psychosocial Variables as Predictors of School Adjustment of Gifted Students with Learning Disabilities in Nigeria

ERIC Educational Resources Information Center

Fakolade, O. A.; Oyedokun, S. O.

2015-01-01

The paper considered several psychosocial variables as predictors of school adjustment of 40 gifted students with learning disabilities in Junior Secondary School in Ikenne Local Government Council Area of Ogun State, Nigeria. Purposeful random sampling was employed to select four schools from 13 junior secondary schools in the area, six…

Rate and predictors of human papillomavirus vaccine uptake among women who have sex with women in the United States, the National Health and Nutrition Examination Survey, 2009-2012.

PubMed

Makris, Nicole; Vena, Catherine; Paul, Sudeshna

2016-12-01

To examine rates and associated correlates of human papilloma virus vaccine uptake in women who have sex with women in the United States, and to determine whether they differ from those in women who do not have sex with women. Women who have sex with women are at risk for human papilloma virus infection but are less likely to receive preventive gynaecological services. Little research has been carried out to evaluate human papilloma virus vaccination rates and associated predictors of vaccination uptake in this population. Cross-sectional descriptive study. Data from two consecutive cohorts of the National Health and Nutrition Examination Survey conducted by the United States' Centers for Disease Control were analysed. The sample (N = 1105) consisted of women aged 18-26 years. There was no difference in human papilloma virus vaccine uptake between women who have sex with women and women who do not have sex with women. Overall, the vaccination rate was low (32·5%). Having health insurance and more education were significant predictors of vaccine uptake in women who have sex with women. Higher education and younger age were predictors in women who do not have sex with women. Vaccination rates of women are far lower than the national target of 80%. The predictors of vaccine uptake were different in women who have sex with women than for women who do not have sex with women. Women in their 20s (regardless of their sexual orientation) should be recognised as an undervaccinated population and require targeted interventions to improve vaccination uptake. © 2016 John Wiley & Sons Ltd.

An evolution-based DNA-binding residue predictor using a dynamic query-driven learning scheme.

PubMed

Chai, H; Zhang, J; Yang, G; Ma, Z

2016-11-15

DNA-binding proteins play a pivotal role in various biological activities. Identification of DNA-binding residues (DBRs) is of great importance for understanding the mechanism of gene regulations and chromatin remodeling. Most traditional computational methods usually construct their predictors on static non-redundant datasets. They excluded many homologous DNA-binding proteins so as to guarantee the generalization capability of their models. However, those ignored samples may potentially provide useful clues when studying protein-DNA interactions, which have not obtained enough attention. In view of this, we propose a novel method, namely DQPred-DBR, to fill the gap of DBR predictions. First, a large-scale extensible sample pool was compiled. Second, evolution-based features in the form of a relative position specific score matrix and covariant evolutionary conservation descriptors were used to encode the feature space. Third, a dynamic query-driven learning scheme was designed to make more use of proteins with known structure and functions. In comparison with a traditional static model, the introduction of dynamic models could obviously improve the prediction performance. Experimental results from the benchmark and independent datasets proved that our DQPred-DBR had promising generalization capability. It was capable of producing decent predictions and outperforms many state-of-the-art methods. For the convenience of academic use, our proposed method was also implemented as a web server at .

Accurate prediction of hot spot residues through physicochemical characteristics of amino acid sequences.

PubMed

Chen, Peng; Li, Jinyan; Wong, Limsoon; Kuwahara, Hiroyuki; Huang, Jianhua Z; Gao, Xin

2013-08-01

Hot spot residues of proteins are fundamental interface residues that help proteins perform their functions. Detecting hot spots by experimental methods is costly and time-consuming. Sequential and structural information has been widely used in the computational prediction of hot spots. However, structural information is not always available. In this article, we investigated the problem of identifying hot spots using only physicochemical characteristics extracted from amino acid sequences. We first extracted 132 relatively independent physicochemical features from a set of the 544 properties in AAindex1, an amino acid index database. Each feature was utilized to train a classification model with a novel encoding schema for hot spot prediction by the IBk algorithm, an extension of the K-nearest neighbor algorithm. The combinations of the individual classifiers were explored and the classifiers that appeared frequently in the top performing combinations were selected. The hot spot predictor was built based on an ensemble of these classifiers and to work in a voting manner. Experimental results demonstrated that our method effectively exploited the feature space and allowed flexible weights of features for different queries. On the commonly used hot spot benchmark sets, our method significantly outperformed other machine learning algorithms and state-of-the-art hot spot predictors. The program is available at http://sfb.kaust.edu.sa/pages/software.aspx. Copyright © 2013 Wiley Periodicals, Inc.

The impact of conventional surface data upon VAS regression retrievals in the lower troposphere

NASA Technical Reports Server (NTRS)

Lee, T. H.; Chesters, D.; Mostek, A.

1983-01-01

Surface temperature and dewpoint reports are added to the infrared radiances from the VISSR Atmospheric Sounder (VAS) in order to improve the retrieval of temperature and moisture profiles in the lower troposphere. The conventional (airways) surface data are combined with the twelve VAS channels as additional predictors in a ridge regression retrieval scheme, with the aim of using all available data to make high resolution space-time interpolations of the radiosonde network. For one day of VAS observations, retrievals using only VAS radiances are compared with retrievals using VAS radiances plus surface data. Temperature retrieval accuracy evaluated at coincident radiosonde sites shows a significant impact within the boundary layer. Dewpoint retrieval accuracy shows a broader improvement within the lowest tropospheric layers. The most dramatic impact of surface data is observed in the improved relative spatial and temporal continuity of low-level fields retrieved over the Midwestern United States.

Landscape capability predicts upland game bird abundance and occurrence

USGS Publications Warehouse

Loman, Zachary G.; Blomberg, Erik J.; DeLuca, William; Harrison, Daniel J.; Loftin, Cyndy; Wood, Petra B.

2017-01-01

Landscape capability (LC) models are a spatial tool with potential applications in conservation planning. We used survey data to validate LC models as predictors of occurrence and abundance at broad and fine scales for American woodcock (Scolopax minor) and ruffed grouse (Bonasa umbellus). Landscape capability models were reliable predictors of occurrence but were less indicative of relative abundance at route (11.5–14.6 km) and point scales (0.5–1 km). As predictors of occurrence, LC models had high sensitivity (0.71–0.93) and were accurate (0.71–0.88) and precise (0.88 and 0.92 for woodcock and grouse, respectively). Models did not predict point-scale abundance independent of the ability to predict occurrence of either species. The LC models are useful predictors of patterns of occurrences in the northeastern United States, but they have limited utility as predictors of fine-scale or route-specific abundances. 

Factors Associated with Research Wrongdoing in Nigeria

PubMed Central

Adeleye, Omokhoa A.; Adebamowo, Clement A.

2013-01-01

Concerns about research wrongdoing in biomedical research are growing in developing countries, where research ethics training and research regulatory systems are just emerging. In a first-time study in Africa, medical/dental researchers (N = 132) in two states in Nigeria were interviewed on a wide range of research wrongdoings and potential predictors. Using multivariate logistic regression, significant predictors of research wrongdoing were identified. Some 22.0% admitted to at least one of fabrication, falsification, and plagiarism, the predictors of which were knowledge gaps in research ethics and pressure to publish enough papers for promotion. Acknowledging inadequate knowledge of research ethics was a predictor of admitting a wrongdoing. Systems that support ethical research, including skilled training and funding, are recommended. PMID:23324199

Predictors of the transition from experimental to daily smoking among adolescents in the United States.

PubMed

Park, Sunhee; Weaver, Terri E; Romer, Daniel

2009-04-01

This study examined factors affecting the transition from experimental smoking at baseline to two types of daily smoking, temporary daily smoking, and continued daily smoking, at 1-year follow-up. This study analyzed data from the National Longitudinal Study of Adolescent Health (n = 4,903 U.S. adolescents). Baseline predictors were selected based on Problem Behavior Theory. Important problem behavior theory-related predictors of smoking were the number of friends who smoke, academic performance, and alcohol, marijuana, and other illicit drug use. Other significant predictors were age, gender, race, depression, perceived general health, and cigarette availability at home. To prevent teens from progressing to daily smoking, nursing professionals should consider multifaceted factors based on multiple theories.

Global salinity predictors of western United States precipitation

NASA Astrophysics Data System (ADS)

Liu, T.; Schmitt, R. W.; Li, L.

2016-12-01

Moisture transport from the excess of evaporation over precipitation in the global ocean drives terrestrial precipitation patterns. Sea surface salinity (SSS) is sensitive to changes in ocean evaporation and precipitation, and therefore, to changes in the global water cycle. We use the Met Office Hadley Centre EN4.2.0 SSS dataset to search for teleconnections between autumn-lead seasonal salinity signals and winter precipitation over the western United States. NOAA CPC Unified observational US precipitation in winter months is extracted from bounding boxes over the northwest and southwest and averaged. Lead autumn SON SSS in ocean areas that are relatively highly correlated with winter DJF terrestrial precipitation are filtered by a size threshold and treated as individual predictors. After removing linear trends from the response and explanatory variables and accounting for multiple collinearity, we use best subsets regression and the Bayesian information criterion (BIC) to objectively select the best model to predict terrestrial precipitation using SSS and SST predictors. The combination of autumn SSS and SST predictors can skillfully predict western US winter terrestrial precipitation (R2 = 0.51 for the US Northwest and R2 = 0.7 for the US Southwest). In both cases, SSS is a better predictor than SST. Thus, incorporating SSS can greatly enhance the accuracy of existing precipitation prediction frameworks that use SST-based climate indices and by extension improve watershed management.

Predictors in Internet-delivered cognitive behavior therapy and behavioral stress management for severe health anxiety.

PubMed

Hedman, Erik; Andersson, Erik; Lekander, Mats; Ljótsson, Brjánn

2015-01-01

Severe health anxiety can be effectively treated with exposure-based Internet-delivered cognitive behavior therapy (ICBT), but information about which factors that predict outcome is scarce. Using data from a recently conducted RCT comparing ICBT (n = 79) with Internet-delivered behavioral stress management (IBSM) (n = 79) the presented study investigated predictors of treatment outcome. Analyses were conducted using a two-step linear regression approach and the dependent variable was operationalized both as end state health anxiety at post-treatment and as baseline-to post-treatment improvement. A hypothesis driven approach was used where predictors expected to influence outcome were based on a previous predictor study by our research group. As hypothesized, the results showed that baseline health anxiety and treatment adherence predicted both end state health anxiety and improvement. In addition, anxiety sensitivity, treatment credibility, and working alliance were significant predictors of health anxiety improvement. Demographic variables, i.e. age, gender, marital status, computer skills, educational level, and having children, had no significant predictive value. We conclude that it is possible to predict a substantial proportion of the outcome variance in ICBT and IBSM for severe health anxiety. The findings of the present study can be of high clinical value as they provide information about factors of importance for outcome in the treatment of severe health anxiety. Copyright © 2014 Elsevier Ltd. All rights reserved.

Assessing range-wide habitat suitability for the Lesser Prairie-Chicken

USGS Publications Warehouse

Jarnevich, Catherine S.; Holcombe, Tracy R.; Grisham, Blake A.; Timmer, Jennifer M.; Boal, Clint W.; Butler, Matthew; Pitman, James C.; Kyle, Sean; Klute, David; Beauprez, Grant M.; Janus, Allan; Van Pelt, William E.

2016-01-01

Population declines of many wildlife species have been linked to habitat loss incurred through land-use change. Incorporation of conservation planning into development planning may mitigate these impacts. The threatened Lesser Prairie-Chicken (Tympanuchus pallidicinctus) is experiencing loss of native habitat and high levels of energy development across its multijurisdictional range. Our goal was to explore relationships of the species occurrence with landscape characteristics and anthropogenic effects influencing its distribution through evaluation of habitat suitability associated with one particular habitat usage, lekking. Lekking has been relatively well-surveyed, though not consistently, in all jurisdictions. All five states in which Lesser Prairie-Chickens occur cooperated in development of a Maxent habitat suitability model. We created two models, one with state as a factor and one without state. When state was included it was the most important predictor, followed by percent of land cover consisting of known or suspected used vegetation classes within a 5000 m area around a lek. Without state, land cover was the most important predictor of relative habitat suitability for leks. Among the anthropogenic predictors, landscape condition, a measure of human impact integrated across several factors, was most important, ranking third in importance without state. These results quantify the relative suitability of the landscape within the current occupied range of Lesser Prairie-Chickens. These models, combined with other landscape information, form the basis of a habitat assessment tool that can be used to guide siting of development projects and targeting of areas for conservation.

Mandibular bone structure, bone mineral density, and clinical variables as fracture predictors: a 15-year follow-up of female patients in a dental clinic.

PubMed

Jonasson, Grethe; Billhult, Annika

2013-09-01

To compare three mandibular trabeculation evaluation methods, clinical variables, and osteoporosis as fracture predictors in women. One hundred and thirty-six female dental patients (35-94 years) answered a questionnaire in 1996 and 2011. Using intra-oral radiographs from 1996, five methods were compared as fracture predictors: (1) mandibular bone structure evaluated with a visual radiographic index, (2) bone texture, (3) size and number of intertrabecular spaces calculated with Jaw-X software, (4) fracture probability calculated with a fracture risk assessment tool (FRAX), and (5) osteoporosis diagnosis based on dual-energy-X-ray absorptiometry. Differences were assessed with the Mann-Whitney test and relative risk calculated. Previous fracture, gluco-corticoid medication, and bone texture were significant indicators of future and total (previous plus future) fracture. Osteoporosis diagnosis, sparse trabeculation, Jaw-X, and FRAX were significant predictors of total but not future fracture. Clinical and oral bone variables may identify individuals at greatest risk of fracture. Copyright © 2013 Elsevier Inc. All rights reserved.

Predictors of Homonegativity in the United States and the Netherlands Using the Fifth Wave of the World Values Survey.

PubMed

Haney, Jolynn L

2016-10-01

Using data from the fifth wave of the World Values Survey (WVS), I investigated negative attitude toward homosexual individuals in two countries-the United States and the Netherlands-to determine how factors associated with homonegativity in the United States compare with factors associated with homonegativity in the Netherlands. Logistic regression of survey responses from 2,299 participants from the United States (n = 1,249) and the Netherlands (n = 1,050) supported findings from previous research suggesting that homonegativity is more likely to occur in the United States than in the Netherlands, and that negative attitudes toward persons with AIDS and immigrants predicted homonegativity in both countries. Predictors of homonegativity in the United States included being male and being unemployed; in the Netherlands, being unhappy predicted homonegativity. How these findings inform social work policy and practice related to the lesbian, gay, bisexual, and transgender (LGBT) population, as well as suggestions for future research, are discussed.

Micro-CT evaluation of bone defects: applications to osteolytic bone metastases, bone cysts, and fracture.

PubMed

Buie, Helen R; Bosma, Nick A; Downey, Charlene M; Jirik, Frank R; Boyd, Steven K

2013-11-01

Bone defects can occur in various forms and present challenges to performing a standard micro-CT evaluation of bone quality because most measures are suited to homogeneous structures rather than ones with spatially focal abnormalities. Such defects are commonly associated with pain and fragility. Research involving bone defects requires quantitative approaches to be developed if micro-CT is to be employed. In this study, we demonstrate that measures of inter-microarchitectural bone spacing are sensitive to the presence of focal defects in the proximal tibia of two distinctly different mouse models: a burr-hole model for fracture healing research, and a model of osteolytic bone metastases. In these models, the cortical and trabecular bone compartments were both affected by the defect and were, therefore, evaluated as a single unit to avoid splitting the defects into multiple analysis regions. The burr-hole defect increased mean spacing (Sp) by 27.6%, spacing standard deviation (SpSD) by 113%, and maximum spacing (Spmax) by 72.8%. Regression modeling revealed SpSD (β=0.974, p<0.0001) to be a significant predictor of the defect volume (R(2)=0.949) and Spmax (β=0.712, p<0.0001) and SpSD (β=0.271, p=0.022) to be significant predictors of the defect diameter (R(2)=0.954). In the mice with osteolytic bone metastases, spacing parameters followed similar patterns of change as reflected by other imaging technologies, specifically bioluminescence data which is indicative of tumor burden. These data highlight the sensitivity of spacing measurements to bone architectural abnormalities from 3D micro-CT data and provide a tool for quantitative evaluation of defects within a bone. Copyright © 2013 IPEM. Published by Elsevier Ltd. All rights reserved.

Improving national-scale invasion maps: Tamarisk in the western United States

USGS Publications Warehouse

Jarnevich, C.S.; Evangelista, P.; Stohlgren, T.J.; Morisette, J.

2011-01-01

New invasions, better field data, and novel spatial-modeling techniques often drive the need to revisit previous maps and models of invasive species. Such is the case with the at least 10 species of Tamarix, which are invading riparian systems in the western United States and expanding their range throughout North America. In 2006, we developed a National Tamarisk Map by using a compilation of presence and absence locations with remotely sensed data and statistical modeling techniques. Since the publication of that work, our database of Tamarix distributions has grown significantly. Using the updated database of species occurrence, new predictor variables, and the maximum entropy (Maxent) model, we have revised our potential Tamarix distribution map for the western United States. Distance-to-water was the strongest predictor in the model (58.1%), while mean temperature of the warmest quarter was the second best predictor (18.4%). Model validation, averaged from 25 model iterations, indicated that our analysis had strong predictive performance (AUC = 0.93) and that the extent of Tamarix distributions is much greater than previously thought. The southwestern United States had the greatest suitable habitat, and this result differed from the 2006 model. Our work highlights the utility of iterative modeling for invasive species habitat modeling as new information becomes available. ?? 2011.

Predictors of School Garden Integration: Factors Critical to Gardening Success in New York City.

PubMed

Burt, Kate Gardner; Burgermaster, Marissa; Jacquez, Raquel

2018-03-01

The purpose of this study was to determine the level of integration of school gardens and identify factors that predict integration. 211 New York City schools completed a survey that collected demographic information and utilized the School Garden Integration Scale. A mean garden integration score was calculated, and multiple regression analysis was conducted to determine independent predictors of integration and assess relationships between individual integration characteristics and budget. The average integration score was 34.1 (of 57 points) and ranged from 8 to 53. Operating budget had significant influence on integration score, controlling for all other factors ( p < .0001). Partner organizations, evaluation/feedback, planning the physical space, and characteristics of the physical space were positively and significantly related to budget. The results of this study indicate that any garden can become well integrated, as budget is a modifiable factor. When adequate funding is secured, a well-integrated garden may be established with proper planning and sound implementation.

Dietary and Urinary Sulfur can Predict Changes in Bone Metabolism During Space Flight

NASA Technical Reports Server (NTRS)

Zwart, Sara R.; Heer, Martina; Shackelford, Linda; Smith, Scott M.

2015-01-01

Mitigating space flight-induced bone loss is critical for space exploration, and diet can play a major role in this effort. Previous ground-based studies provide evidence that dietary composition can influence bone resorption during bed rest. In this study we examined the role of dietary intake patterns as one factor that can influence bone mineral loss in astronauts during space flight. Crew members were asked to consume, for 4 days at a time, prescribed menus with either a low (0.3-0.6 g/mEq) or high (1.0-1.3 g/mEq) ratio of animal protein to potassium (APro:K). Menus were developed for each crewmember, and were designed to meet both crew preferences and study constraints. Intakes of energy, total protein, calcium, and sodium were held relatively constant between the two diets. The order of the menus was randomized, and crews completed each set (low and high) once before and twice during space flight, for a total of 6 controlled diet sessions. One inflight session and three postflight sessions (R+30, R+180, R+365) monitored typical dietary intake. As of this writing, data are available from 14 crew members. The final three subjects' inflight samples are awaiting return from the International Space Station via Space-X. On the last day of each of the 4-d controlled diet sessions, 24-h urine samples were collected, along with a fasting blood sample on the morning of the 5th day. Preliminary analyses show that urinary excretion of sulfate (normalized to lean body mass) is a significant predictor of urinary n-telopeptide (NTX). Dietary sulfate (normalized to lean body mass) is also a significant predictor of urinary NTX. The results from this study, will be important to better understand diet and bone interrelationships during space flight as well as on Earth. This study was funded by the Human Health Countermeasures Element of the NASA Human Research Program.

Expanding Downward: Innovation, Diffusion, and State Policy Adoptions of Universal Preschool

ERIC Educational Resources Information Center

Curran, F. Chris

2015-01-01

Framed within the theoretical framework of policy innovation and diffusion, this study explores both interstate (diffusion) and intrastate predictors of adoption of state universal preschool policies. Event history analysis methodology is applied to a state level dataset drawn from the Census, the NCES Common Core, the Book of the States, and…

Short communication: Analysis of genomic predictor population for Holstein dairy cattle in the United States – Effects of sex and age

USDA-ARS?s Scientific Manuscript database

The number of females genotyped in the US has increased to 12,650 per month, comprising 74% of the total genotypes received in 2013. Concerns of increased computing time of the ever-growing predictor population set and linkage decay between the ancestral population and the current animals have arise...

Predictors of Close Family Relationships over One Year among Homeless Young People

ERIC Educational Resources Information Center

Milburn, N.G.; Jane Rotheram-Borus, M.; Batterham, P.; Brumback, B.; Rosenthal, D.; Mallett, S.

2005-01-01

Predictors of perceived family bonds were examined among homeless young people who initially left home one year earlier. Newly homeless young people aged 12-20 years who had recently left home were recruited in Los Angeles County, United States (n=201) and Melbourne, Australia (n=124) and followed longitudinally at 3, 6, and 12 months (follow-up…

Attitude and Motivation as Predictors of Academic Achievement of Students in Clothing and Textiles

ERIC Educational Resources Information Center

Uwameiye, B. E.; Osho, L. E.

2011-01-01

This study investigated attitude and motivation as predictors of academic achievement of students in clothing and textiles. Three colleges of education in Edo and Delta States were randomly selected for use in this study. From each school, 40 students were selected from Year III using simple random technique yielding a total of 240 students. The…

Fuzzy neural network technique for system state forecasting.

PubMed

Li, Dezhi; Wang, Wilson; Ismail, Fathy

2013-10-01

In many system state forecasting applications, the prediction is performed based on multiple datasets, each corresponding to a distinct system condition. The traditional methods dealing with multiple datasets (e.g., vector autoregressive moving average models and neural networks) have some shortcomings, such as limited modeling capability and opaque reasoning operations. To tackle these problems, a novel fuzzy neural network (FNN) is proposed in this paper to effectively extract information from multiple datasets, so as to improve forecasting accuracy. The proposed predictor consists of both autoregressive (AR) nodes modeling and nonlinear nodes modeling; AR models/nodes are used to capture the linear correlation of the datasets, and the nonlinear correlation of the datasets are modeled with nonlinear neuron nodes. A novel particle swarm technique [i.e., Laplace particle swarm (LPS) method] is proposed to facilitate parameters estimation of the predictor and improve modeling accuracy. The effectiveness of the developed FNN predictor and the associated LPS method is verified by a series of tests related to Mackey-Glass data forecast, exchange rate data prediction, and gear system prognosis. Test results show that the developed FNN predictor and the LPS method can capture the dynamics of multiple datasets effectively and track system characteristics accurately.

Measurement error and timing of predictor values for multivariable risk prediction models are poorly reported.

PubMed

Whittle, Rebecca; Peat, George; Belcher, John; Collins, Gary S; Riley, Richard D

2018-05-18

Measurement error in predictor variables may threaten the validity of clinical prediction models. We sought to evaluate the possible extent of the problem. A secondary objective was to examine whether predictors are measured at the intended moment of model use. A systematic search of Medline was used to identify a sample of articles reporting the development of a clinical prediction model published in 2015. After screening according to a predefined inclusion criteria, information on predictors, strategies to control for measurement error and intended moment of model use were extracted. Susceptibility to measurement error for each predictor was classified into low and high risk. Thirty-three studies were reviewed, including 151 different predictors in the final prediction models. Fifty-one (33.7%) predictors were categorised as high risk of error, however this was not accounted for in the model development. Only 8 (24.2%) studies explicitly stated the intended moment of model use and when the predictors were measured. Reporting of measurement error and intended moment of model use is poor in prediction model studies. There is a need to identify circumstances where ignoring measurement error in prediction models is consequential and whether accounting for the error will improve the predictions. Copyright © 2018. Published by Elsevier Inc.

Impact of work pressure, work stress and work-family conflict on firefighter burnout.

PubMed

Smith, Todd D; DeJoy, David M; Dyal, Mari-Amanda Aimee; Huang, Gaojian

2017-10-25

Little research has explored burnout and its causes in the American fire service. Data were collected from career firefighters in the southeastern United States (n = 208) to explore these relationships. A hierarchical regression model was tested to examine predictors of burnout including sociodemographic characteristics (model 1), work pressure (model 2), work stress and work-family conflict (model 3) and interaction terms (model 4). The main findings suggest that perceived work stress and work-family conflict emerged as the significant predictors of burnout (both p < .001). Interventions and programs aimed at these predictors could potentially curtail burnout among firefighters.

Predictor-Based Model Reference Adaptive Control

NASA Technical Reports Server (NTRS)

Lavretsky, Eugene; Gadient, Ross; Gregory, Irene M.

2009-01-01

This paper is devoted to robust, Predictor-based Model Reference Adaptive Control (PMRAC) design. The proposed adaptive system is compared with the now-classical Model Reference Adaptive Control (MRAC) architecture. Simulation examples are presented. Numerical evidence indicates that the proposed PMRAC tracking architecture has better than MRAC transient characteristics. In this paper, we presented a state-predictor based direct adaptive tracking design methodology for multi-input dynamical systems, with partially known dynamics. Efficiency of the design was demonstrated using short period dynamics of an aircraft. Formal proof of the reported PMRAC benefits constitute future research and will be reported elsewhere.

Change in joint space width: hyaline articular cartilage loss or alteration in meniscus?

PubMed

Hunter, D J; Zhang, Y Q; Tu, X; Lavalley, M; Niu, J B; Amin, S; Guermazi, A; Genant, H; Gale, D; Felson, D T

2006-08-01

To explore the relative contribution of hyaline cartilage morphologic features and the meniscus to the radiographic joint space. The Boston Osteoarthritis of the Knee Study is a natural history study of symptomatic knee osteoarthritis (OA). Baseline and 30-month followup assessments included knee magnetic resonance imaging (MRI) and fluoroscopically positioned weight-bearing knee radiographs. Cartilage and meniscal degeneration were scored on MRI in the medial and lateral tibiofemoral joints using a semiquantitative grading system. Meniscal position was measured to the nearest millimeter. The dependent variable was joint space narrowing (JSN) on the plain radiograph (possible range 0-3). The predictor variables were MRI cartilage score, meniscal degeneration, and meniscal position measures. We first conducted a cross-sectional analysis using multivariate regression to determine the relative contribution of meniscal factors and cartilage morphologic features to JSN, adjusting for body mass index (BMI), age, and sex. The same approach was used for change in JSN and change in predictor variables. We evaluated 264 study participants with knee OA (mean age 66.7 years, 59% men, mean BMI 31.4 kg/m(2)). The results from the models demonstrated that meniscal position and meniscal degeneration each contributed to prediction of JSN, in addition to the contribution by cartilage morphologic features. For change in medial joint space, both change in meniscal position and change in articular cartilage score contributed substantially to narrowing of the joint space. The meniscus (both its position and degeneration) accounts for a substantial proportion of the variance explained in JSN, and the change in meniscal position accounts for a substantial proportion of change in JSN.

Developing a Statewide Childhood Body Mass Index Surveillance Program

ERIC Educational Resources Information Center

Paul, David R.; Scruggs, Philip W.; Goc Karp, Grace; Ransdell, Lynda B.; Robinson, Clay; Lester, Michael J.; Gao, Yong; Petranek, Laura J.; Brown, Helen; Shimon, Jane M.

2014-01-01

Background: Several states have implemented childhood obesity surveillance programs supported by legislation. Representatives from Idaho wished to develop a model for childhood obesity surveillance without the support of state legislation, and subsequently report predictors of overweight and obesity in the state. Methods: A coalition comprised of…

The State Sets the Rate: The Relationship Among State-Specific College Binge Drinking, State Binge Drinking Rates, and Selected State Alcohol Control Policies

PubMed Central

Nelson, Toben F.; Naimi, Timothy S.; Brewer, Robert D.; Wechsler, Henry

2005-01-01

Objectives. We assessed the relationship between college binge drinking, binge drinking in the general population, and selected alcohol control policies. Methods. We analyzed binge drinking rates from 2 national surveys, the Har-vard School of Public Health College Alcohol Study and the Centers for Disease Control and Prevention’s Behavioral Risk Factor Surveillance System. Binge drinking data were linked to a summary measure of 7 salient alcohol control policies and a rating of resources devoted to law enforcement. Results. State-level college and adult binge drinking rates were strongly correlated (Pearson correlation coefficient=0.43; P<.01). Attending college in states with the lowest binge drinking rates (adjusted odds ratio [OR]=0.63; 95% confidence interval [CI]=0.41, 0.97) and presence of more stringent alcohol control policies (adjusted OR=0.57; 95% CI=0.33, 0.97) were independent predictors of student binge drinking, after adjusting for state law enforcement and individual-, college-, and state-level covariates. Conclusions. State of residence is a predictor of binge drinking by college students. State-level alcohol control policies may help reduce binge drinking among college students and in the general population. PMID:15727974

State-Level Predictors of Food Insecurity among Households with Children

ERIC Educational Resources Information Center

Bartfeld, Judi; Dunifon, Rachel

2006-01-01

This article examines interstate variation in household food security. Using hierarchical modeling, we identify several kinds of state characteristics that appear linked to household food security: the availability and accessibility of federal nutrition assistance programs, policies affecting economic wellbeing of low income families, and states'…

Is State Anxiety, Trait Anxiety, or Anxiety Sensitivity a Clinical Predictor of Symptoms in Those Presenting With Mild Traumatic Brain Injury or Concussion?

PubMed

Hixson, Krista M; Allen, Alex N; Williams, Andrew S; McLeod, Tamara C Valovich

2017-11-01

Clinical Scenario: Mild traumatic brain injury, or concussion, has been associated with physical, cognitive, and emotional sequelae. Little is understood in regard to many characteristics, such as anxiety, and their effect on post-concussion symptoms. Is state anxiety, trait anxiety, or anxiety sensitivity a clinical predictor of symptoms in those presenting with mild traumatic brain injury or concussion? Summary of Key Findings: A literature search returned 3 possible studies; 3 studies met inclusion criteria and included. One study reported in athletes that greater social support was associated with decreased state-anxiety, lower state anxiety post-concussion was associated with increased social support, and that those with greater social support may experience reduced anxiety, regardless of injury type sustained. One study reported baseline trait anxiety in athletes was not significantly associated with post-concussion state anxiety, but that symptoms of depression at baseline was the strongest predictor for post-concussion state anxiety. Three studies reported that state and trait anxiety are not related to increased post-concussion symptom scores. One study reported that greater anxiety sensitivity is related to higher reported post-concussion symptom scores, which may manifest as somatic symptoms following concussion, and revealed that anxiety sensitivity may be a risk factor symptom development. Clinical Bottom Line: There is low-level to moderate evidence to support that anxiety sensitivity is linked to post-concussion symptoms. State and trait anxiety do not appear to be related to post-concussion symptoms alone. Post-concussion state anxiety may occur if post-concussion symptoms of depression are present or if baseline symptoms of depression are present. Better social support may improve state anxiety post-concussion. Strength of Recommendation: There is grade B evidence to support that state and trait anxiety are not risk factors for post-concussion symptom development. There is grade C evidence to support anxiety sensitivity as a risk factor for developing post-concussion symptoms.

The Relational-Behavior Survey as a Predictor of HIV-Related Parental Miscommunication: Implications for HIV, Prevention and Education at Primary Healthcare Service Facilities

ERIC Educational Resources Information Center

Chandler, Michele Denise; Chandler, Donald S.; Chandler, Donald S., Jr.; Race, James

2012-01-01

The study examined the relational-behavior survey (RBS) as a predictor of HIV-related parental miscommunication (HPM) among a voluntary sample 75 African American parents at a private healthcare facility located in the southwest region of the United States. A multiple regression analysis indicated that there was significant marginal prediction of…

Assessment of Critical Thinking as a Predictor of Success in Completion of an Associate Degree Respiratory Care Program

ERIC Educational Resources Information Center

Campbell, Fiona B.

2017-01-01

The purpose of this study was to explore the relationship between assessment of critical thinking as admission criteria as a predictor of success in the completion of an associate degree respiratory care program. The research site was a community college located in the southern United States. The sample included 176 students who completed Health…

Alabama's Education Report Card, 2000: Significant Predictors of Student Achievement at the District and School Level. Research Brief.

ERIC Educational Resources Information Center

Miller-Whitehead, Marie

This paper examines Alabama's State Education Report Card for the year 2000. It identifies predictors for student academic achievement at both the district and school levels for 128 public school systems and 1,272 public schools. Separate analyses were conducted for 61 city and 67 county school systems. The variables included number of students,…

A Project Manager’s Personal Attributes as Predictors for Success

DTIC Science & Technology

2007-03-01

Northouse (2004) explains that leadership is highly a researched topic with much written. Yet, a definitive description of this phenomenon is difficult to...express because of its complexity. Even though leadership has varied descriptions and conceptualizations, Northouse states that the concept of...characteristic of leadership is not an accurate predictor of performance. Leadership is a complex, multi-faceted attribute ( Northouse , 2004) and specific

Predictors of English Reading Comprehension: Cantonese-Speaking English Language Learners in the U.S.

ERIC Educational Resources Information Center

Uchikoshi, Yuuko

2013-01-01

In this paper, first language (L1) and second language (L2) oral language and word reading skills were used as predictors to devise a model of reading comprehension in young Cantonese-speaking English language learners (ELLs) in the United States. L1 and L2 language and literacy measures were collected from a total of 101 Cantonese-speaking ELLs…

Predicting Psychotic-Like Experiences during Sensory Deprivation

PubMed Central

Daniel, Christina; Mason, Oliver J.

2015-01-01

Aims. This study aimed to establish the contribution of hallucination proneness, anxiety, suggestibility, and fantasy proneness to psychotic-like experiences (PLEs) reported during brief sensory deprivation. Method. Twenty-four high and 22 low hallucination-prone participants reported on PLEs occurring during brief sensory deprivation and at baseline. State/trait anxiety, suggestibility, and fantasy proneness were also measured. Results. Both groups experienced a significant increase in PLEs in sensory deprivation. The high hallucination prone group reported more PLEs both at baseline and in sensory deprivation. They also scored significantly higher on measures of state/trait anxiety, suggestibility, and fantasy proneness, though these did not explain the effects of group or condition. Regression analysis found hallucination proneness to be the best predictor of the increase in PLEs, with state anxiety also being a significant predictor. Fantasy proneness and suggestibility were not significant predictors. Conclusion. This study suggests the increase in PLEs reported during sensory deprivation reflects a genuine aberration in perceptual experience, as opposed to increased tendency to make false reports due to suggestibility of fantasy proneness. The study provides further support for the use of sensory deprivation as a safe and effective nonpharmacological model of psychosis. PMID:25811027

Space versus Place in Complex Human-Natural Systems: Spatial and Multi-level Models of Tropical Land Use and Cover Change (LUCC) in Guatemala

PubMed Central

López-Carr, David; Davis, Jason; Jankowska, Marta; Grant, Laura; López-Carr, Anna Carla; Clark, Matthew

2013-01-01

The relative role of space and place has long been debated in geography. Yet modeling efforts applied to coupled human-natural systems seemingly favor models assuming continuous spatial relationships. We examine the relative importance of placebased hierarchical versus spatial clustering influences in tropical land use/cover change (LUCC). Guatemala was chosen as our study site given its high rural population growth and deforestation in recent decades. We test predictors of 2009 forest cover and forest cover change from 2001-2009 across Guatemala's 331 municipalities and 22 departments using spatial and multi-level statistical models. Our results indicate the emergence of several socio-economic predictors of LUCC regardless of model choice. Hierarchical model results suggest that significant differences exist at the municipal and departmental levels but largely maintain the magnitude and direction of single-level model coefficient estimates. They are also intervention-relevant since policies tend to be applicable to distinct political units rather than to continuous space. Spatial models complement hierarchical approaches by indicating where and to what magnitude significant negative and positive clustering associations emerge. Appreciating the comparative advantages and limitations of spatial and nested models enhances a holistic approach to geographical analysis of tropical LUCC and human-environment interactions. PMID:24013908

[Hepatobiliary System Diseases as the Predictors of Psoriasis Progression].

PubMed

Smirnova, S V; Barilo, A A; Smolnikova, M V

2016-01-01

To assess the state of the hepatobiliary system in psoriasis andpsoriatic arthritis in order to establish a causal relationship and to identify clinical and functional predictors of psoriatic disease progression. The study includedpatients with extensive psoriasis vulgaris (n = 175) aged 18 to 66 years old and healthy donors (n = 30), matched by sex and age: Group 1--patients with psoriasis (PS, n = 77), group 2--patients with psoriatic arthritis (PsA, n = 98), group 3--control. The evaluation of functional state of the hepatobiliary system was performed by the analysis of the clinical and anamnestic data and by the laboratory-instrumental methods. We identified predictors of psoriasis: triggers (stress and nutritionalfactor), increased total bilirubin, aspartate aminotransferase, alkaline phosphatase, gamma-glutamyl transferase, eosinophilia, giardiasis, carriers of hepatitis C virus, ductal changes andfocal leisons in the liver, thickening of the walls of the gallbladder detected by ultrasound. Predictors ofpsoriatic arthritis: age over 50 years, dyspeptic complaints, the presence of hepatobiliary system diseases, the positive right hypochondrium syndrome, the clinical symptoms of chronic cholecystitis, excess body weight, high levels of bilirubin, cholesterol and low density lipoprotein, hepatomegaly, non-alcoholic fatty liver disease. High activity of hepatocytes cytolysis, cholestasis, inflammation, metabolic disorders let us considerpsoriatic arthritis as a severe clinical stage psoriatic disease when the hepatobiliary system, in turn, is one of the main target organs in systemic psoriatic process. Non-alcoholic fatty liver disease and chronic cholecystitis are predictors of psoriatic disease progression.

The relationship between performance and flow state in tennis competition.

PubMed

Koehn, S; Morris, T

2012-08-01

The study aimed to examine 1) the validity of the nine-factor flow model in tennis competition; 2) differences in flow state between athletes who won or lost their competition match; 3) the link between flow and subjective performance; and 4) flow dimensions as predictors of performance outcome The sample consisted of 188 junior tennis players (115 male, 73 female) between 12 and 18 years of age. Participants' performance was recorded during junior ranking-list tournaments. Following the completion of a tennis competition match, participants completed the Flow State Scale-2 and a subjective performance outcome measure. Acceptable flow model fit indices of CFI, TLI, SRMR, and RMSEA were only found for winning athletes. The group of winning athletes scored significantly higher on all nine flow dimensions, except time transformation, than losing athletes, showing statistically significant differences for challenge-skills balance, clear goals, sense of control, and autotelic experience. Significant correlation coefficients were found between flow state and subjective performance assessments. The binary logistic regression revealed concentration on the task and sense of control to be significant predictors of performance outcome. The predictor variables explained 13% of the variance in games won. The study showed that athletes who win or lose perceived flow state differently. Studies using retrospective assessments need to be aware that subjective experience could be biased by performance outcomes. Pinpointing psychological variables and their impact on ecologically valid measures, such as performance results, would support the development of effective intervention studies to increase performance in sport competition.

The Campus Spiritual Climate: Predictors of Satisfaction among Students with Diverse Worldviews

ERIC Educational Resources Information Center

Rockenbach, Alyssa Bryant; Mayhew, Matthew J.

2014-01-01

Using data collected via the Campus Religious and Spiritual Climate Survey (CRSCS), we examined how dimensions of the campus spiritual climate shape student satisfaction. The findings reveal that structural worldview diversity, space for support and spiritual expression, and provocative experiences with worldview diversity positively relate to…

In vivo perfusion assessment of an anastomosis surgery on porcine intestinal model (Conference Presentation)

NASA Astrophysics Data System (ADS)

Le, Hanh N. D.; Opferman, Justin; Decker, Ryan; Cheon, Gyeong W.; Kim, Peter C. W.; Kang, Jin U.; Krieger, Axel

2016-04-01

Anastomosis, the connection of two structures, is a critical procedure for reconstructive surgery with over 1 million cases/year for visceral indication alone. However, complication rates such as strictures and leakage affect up to 19% of cases for colorectal anastomoses and up to 30% for visceral transplantation anastomoses. Local ischemia plays a critical role in anastomotic complications, making blood perfusion an important indicator for tissue health and predictor for healing following anastomosis. In this work, we apply a real time multispectral imaging technique to monitor impact on tissue perfusion due to varying interrupted suture spacing and suture tensions. Multispectral tissue images at 470, 540, 560, 580, 670 and 760 nm are analyzed in conjunction with an empirical model based on diffuse reflectance process to quantify the hemoglobin oxygen saturation within the suture site. The investigated tissues for anastomoses include porcine small (jejunum and ileum) and large (transverse colon) intestines. Two experiments using interrupted suturing with suture spacing of 1, 2, and 3 mm and tension levels from 0 N to 2.5 N are conducted. Tissue perfusion at 5, 10, 20 and 30 min after suturing are recorded and compared with the initial normal state. The result indicates the contrast between healthy and ischemic tissue areas and assists the determination of suturing spacing and tension. Therefore, the assessment of tissue perfusion will permit the development and intra-surgical monitoring of an optimal suture protocol during anastomosis with less complications and improved functional outcome.

Unique and related predictors of major depressive disorder, posttraumatic stress disorder, and their comorbidity after Hurricane Katrina.

PubMed

Nillni, Yael I; Nosen, Elizabeth; Williams, Patrick A; Tracy, Melissa; Coffey, Scott F; Galea, Sandro

2013-10-01

The current study examined demographic and psychosocial factors that predict major depressive disorder (MDD) and comorbid MDD/posttraumatic stress disorder (MDD/PTSD) diagnostic status after Hurricane Katrina, one of the deadliest and costliest hurricanes in the history of the United States. This study expanded on the findings published in the article by Galea, Tracy, Norris, and Coffey (J Trauma Stress 21:357-368, 2008), which examined the same predictors for PTSD, to better understand related and unique predictors of MDD, PTSD, and MDD/PTSD comorbidity. A total of 810 individuals representative of adult residents living in the 23 southernmost counties of Mississippi before Hurricane Katrina were interviewed. Ongoing hurricane-related stressors, low social support, and hurricane-related financial loss were common predictors of MDD, PTSD, and MDD/PTSD, whereas educational and marital status emerged as unique predictors of MDD. Implications for postdisaster relief efforts that address the risk for both MDD and PTSD are discussed.

Childhood maltreatment history as a risk factor for sexual harassment among U.S. Army soldiers.

PubMed

Rosen, L N; Martin, L

1998-01-01

Four different types of childhood maltreatment were examined as predictors of unwanted sexual experiences and acknowledged sexual harassment among male and female active duty soldiers in the United States Army. Predictor variables included childhood sexual abuse, physical-emotional abuse, physical neglect, and emotional neglect. Three types of unwanted sexual experiences in the workplace were examined as outcome variables: gender harassment, unwanted sexual attention, and coercion. Both sexual and physical-emotional abuse during childhood were found to be predictors of unwanted sexual experiences and of acknowledged sexual harassment in the workplace. Among female soldiers, the most severe type of unwanted experience-coercion-was predicted only by childhood physical-emotional abuse. Among male soldiers childhood sexual abuse was the strongest predictor of coercion. A greater variety of types of childhood maltreatment predicted sexual harassment outcomes for male soldiers. Childhood maltreatment and adult sexual harassment were predictors of psychological well-being for soldiers of both genders.

[The clinical predictors of heteroaggressive behaviour of the women serving sentence in penitentiary].

PubMed

Shaklein, K N; Bardenshtein, L M; Demcheva, N K

To identify clinical predictors of heteroaggressive behavior. Three hundreds and three women serving sentence in a penal colony were examined using clinical, neurologic and statistical methods. The main group consisted of 225 women with heteroaggressive behavior, the control group included 78 women without aggressive behavior. Differences between the main and control groups in the structure of mental disorders and key syndromes were revealed. The authors conclude that the states with elements of dysphoria, dysthymia, decompensation of personality disorders, which are defined in the various forms of mental pathology, are the most significant predictors of heteroaggressive behavior in women in the penal colony.

Racial/Ethnic Differences in Cigarette Smoking Initiation and Progression to Daily Smoking: A Multilevel Analysis

PubMed Central

Kandel, Denise B.; Kiros, Gebre-Egziabher; Schaffran, Christine; Hu, Mei-Chen

2004-01-01

Objectives. We sought to identify individual and contextual predictors of adolescent smoking initiation and progression to daily smoking by race/ethnicity. Methods. We used data from the National Longitudinal Study of Adolescent Health to estimate the effects of individual (adolescent, family, peer) and contextual (school and state) factors on smoking onset among nonsmokers (n = 5374) and progression to daily smoking among smokers (n = 4474) with multilevel regression models. Results. Individual factors were more important predictors of smoking behaviors than were contextual factors. Predictors of smoking behaviors were mostly common across racial/ethnic groups. Conclusions. The few identified racial/ethnic differences in predictors of smoking behavior suggest that universal prevention and intervention efforts could reach most adolescents regardless of race/ethnicity. With 2 exceptions, important contextual factors remain to be identified. PMID:14713710

Probabilistic streamflow forecasting for hydroelectricity production: A comparison of two non-parametric system identification algorithms

NASA Astrophysics Data System (ADS)

Pande, Saket; Sharma, Ashish

2014-05-01

This study is motivated by the need to robustly specify, identify, and forecast runoff generation processes for hydroelectricity production. It atleast requires the identification of significant predictors of runoff generation and the influence of each such significant predictor on runoff response. To this end, we compare two non-parametric algorithms of predictor subset selection. One is based on information theory that assesses predictor significance (and hence selection) based on Partial Information (PI) rationale of Sharma and Mehrotra (2014). The other algorithm is based on a frequentist approach that uses bounds on probability of error concept of Pande (2005), assesses all possible predictor subsets on-the-go and converges to a predictor subset in an computationally efficient manner. Both the algorithms approximate the underlying system by locally constant functions and select predictor subsets corresponding to these functions. The performance of the two algorithms is compared on a set of synthetic case studies as well as a real world case study of inflow forecasting. References: Sharma, A., and R. Mehrotra (2014), An information theoretic alternative to model a natural system using observational information alone, Water Resources Research, 49, doi:10.1002/2013WR013845. Pande, S. (2005), Generalized local learning in water resource management, PhD dissertation, Utah State University, UT-USA, 148p.

Predictors of Complications in Patients Receiving Head and Neck Free Flap Reconstructive Procedures.

PubMed

Eskander, Antoine; Kang, Stephen; Tweel, Ben; Sitapara, Jigar; Old, Matthew; Ozer, Enver; Agrawal, Amit; Carrau, Ricardo; Rocco, James W; Teknos, Theodoros N

2018-05-01

Objective To (1) determine the overall complication rate, wound healing, and wound infection complications and (2) identify preoperative, intraoperative, and postoperative predictors of these complications. Study Design Case series with chart review. Setting Tertiary academic cancer hospital. Subjects and Methods All head and neck free flap patients at The Ohio State University (2006-2012) were assessed. Multivariable logistic regression assessed the impact of patient factors, flap and wound factors, and intraoperative factors on the aforementioned quality metric outcomes. Results Of the 515 patients identified, 54% had a complication predicted by longer operating room (OR) time, higher comorbidity index, and oral cavity and pharyngeal tumor sites. Predictors of wound-healing complications (15%) were longer OR time, volume of crystalloid given intraoperatively, and oral cavity and pharyngeal tumor sites. Predictors of wound infection (12%) were younger age, diabetes mellitus, and malnutrition. Conclusions Wound healing and infectious complications account for most complications in patients with head and neck cancer undergoing free flap reconstruction. Clean contaminated wounds are a significant predictor of wound complications. Advanced OR time, advanced age, and comorbidity status, including diabetes mellitus and malnutrition, are other important predictors. Crystalloid administration is also an important predictor of wound-healing complications, and this warrants further study.

Cigarette Smoking among Korean International College Students in the United States

ERIC Educational Resources Information Center

Sa, Jaesin; Seo, Dong-Chul; Nelson, Toben F.; Lohrmann, David K.

2013-01-01

Objective and Participants: This study explored (1) the prevalence of cigarette smoking among South Korean international college students in the United States, (2) differences in smoking between on- and off-campus living arrangements, and (3) predictors of an increase in smoking over time in the United States Methods: An online survey was…

Factors associated with local public health agency participation in obesity prevention in southern States.

PubMed

Hatala, Jeffrey J; Fields, Tina T

2015-05-01

Obesity rates in the southern US states are higher than in other states. Historically, large-scale community-based interventions in the United States have not proven successful. With local public health agencies (LPHAs) tasked with prevention, their role in obesity prevention is important, yet little research exists regarding what predicts the participation of LPHAs. Cross-sectional data from the 2008 National Association of City and County Health Officials profile study and two public health conceptual frameworks were used to assess structural and environmental predictors of LPHA participation in obesity prevention. The predictors were compared between southern and nonsouthern states. Univariate and weighted logistic regressions were performed. Analysis revealed that more LPHAs in southern states were engaged in nearly all of the 10 essential public health functions related to obesity prevention compared with nonsouthern states. Presence of community-based organizations and staffing levels were the only significant variables in two of the six logistic regression models. This study provides insights into the success rates of the obesity prevention efforts of LPHAs in southern and nonsouthern states. Future research is needed to understand why and how certain structural elements and any additional factors influence LPHA participation in obesity prevention.

Truck drivers' traffic accidents in the State of São Paulo: prevalence and predictors.

PubMed

Oliveira, Lucio Garcia de; Almeida, Carlos Vinícius Dias de; Barroso, Lucia Pereira; Gouvea, Marcela Julio Cesar; Muñoz, Daniel Romero; Leyton, Vilma

2016-12-01

Abstract The mortality rate of traffic accidents (TA) is high in Brazil. Trucks are the second category of motor vehicles most often involved in TA. However, few studies have addressed the issue of TA among these professionals. The study aimed to estimate the prevalence of TA and their predictors in a sample of 684 truck drivers recruited in the state of São Paulo during 2012 and 2013. We requested participants to answer a research instrument on their personal and occupational data and their involvement in TA and traffic violations. A logistic regression model was developed to identify TA predictors. Almost 11% of the respondents suffered at least one TA in that timeframe. We identified the following TA predictors: having few years of experience as professional drivers (OR = 1.86; CI 95% = 1.05-3.38; p = 0.036); receiving some traffic tickets (OR = 1.91; CI 95% = 1.04-3.66; p = 0.043) and working more than 12 hours daily (OR = 1.84; CI 95% = 1.04-3.24; p = 0.034). Given those results, we suggest the development of a joint action among all the involved social stakeholders in order to negotiate truck drivers' work organization aiming at reducing behaviors that may lead to traffic accidents.

Risk For Postpartum Depression Among Immigrant Arabic Women in the United States: A Feasibility Study.

PubMed

Alhasanat, Dalia; Fry-McComish, Judith; Yarandi, Hossein N

2017-07-01

Postpartum depression (PPD) affects approximately 14% of women in the United States and 10% to 37% of Arabic women in the Middle East. Evidence suggests that immigrant women experience higher rates, but information on PPD among immigrant women of Arabic descent in the United States is nonexistent. A cross-sectional descriptive feasibility study was conducted to assess the practicality of implementing a larger proposed research study to examine predictors of PPD in US immigrant women of Arabic descent residing in Dearborn, Michigan. Fifty women were recruited from an Arab community center and completed demographic data, the Arabic version of the Edinburgh Postpartum Depression Scale (EPDS), and the Postpartum Depression Predictors Inventory-Revised (PDPI-R). Among participants, 36% were considered at high risk for developing PPD. Lack of social support, antenatal anxiety, antenatal depression, maternity blues (feeling depressed during the first 4 weeks postpartum), and life stress were significantly related to risk for PPD. Multiple regression analysis revealed that social support (t = -3.77, P < .0001) and maternity blues (t = 2.19, P = .03) were the only significant predictors for postpartum depressive symptoms. Findings of this study describe the prevalence of PPD in a sample of US immigrant women of Arabic descent and support the feasibility of a larger and more in-depth understanding of their immigration and acculturation experiences. Study participants reported high risk for PPD. Maternity blues and lack of social support were significant predictors to the risk for PPD. Future research tailored to this minority group is recommended. © 2017 by the American College of Nurse-Midwives.

Long-term distribution and habitat changes of protected wildlife: giant pandas in Wolong Nature Reserve, China.

PubMed

Bai, Wenke; Connor, Thomas; Zhang, Jindong; Yang, Hongbo; Dong, Xin; Gu, Xiaodong; Zhou, Caiquan

2018-04-01

Changes in wildlife habitat across space and time, and corresponding changes in wildlife space use, are increasingly common phenomenon. It is critical to study and understand these spatio-temporal changes to accurately inform conservation strategy and manage wildlife populations. These changes can be particularly large and complex in areas that face pressure from human development and disturbance but are also under protection and/or restoration regimes. We analyzed changes in space use and habitat suitability of giant pandas in Wolong Nature Reserve, China, over three decades using kernel density, spatio-temporal analysis of moving polygons (STAMP), and MaxEnt methods, and data from three national censuses. Between 2001 and 2012, there was a slight retraction in total range, and more area of significant space use decreases than increases. Habitat suitability varied spatially and temporally, with a 4.1% decrease in average suitability between 1987 and 2001 and a 3.5% increase in average suitability in between 2001 and 2012. Elevation and bamboo were the most important habitat predictors across the three censuses. Human and natural disturbance variables such as distance to household and the distance to landslide variable in the 4th census were also important predictors, and likely also negatively influenced important habitat variables such as bamboo and forest cover. We were able to measure changes in space utilization and habitat suitability over a large time scale, highlighting the achievements and challenges of giant panda conservation. Long-term monitoring of the changes in distribution and habitat of threatened species, and an analysis of the drivers behind these changes such as undergone here, are important to inform the management and conservation of the world's remaining wildlife populations.

The Ratio of Angiopoietin-2 to Angiopoietin-1 as a Predictor of Mortality in Acute Lung Injury Patients

PubMed Central

Ong, Thida; McClintock, Dana E.; Kallet, Richard H.; Ware, Lorraine B.; Matthay, Michael A.; Liu, Kathleen D.

2014-01-01

Objective To test the hypothesis that the concentration of angiopoietin-2 relative to angiopoietin-1 (Ang-2/Ang-1) may be a useful biologic marker of mortality in acute lung injury (ALI) patients. We also tested the association of Ang-2/Ang-1 with physiologic and biologic markers of activated endothelium. Design Prospective observational cohort study. Setting Intensive care units in a tertiary care university hospital and a university-affiliated city hospital. Patients Fifty-six mechanically ventilated patients with ALI. Interventions Baseline plasma samples and pulmonary dead space fraction measurements were collected within 48 hours of ALI diagnosis. Measurements and Main Results Plasma levels of Ang-1 and Ang-2 and of biomarkers of endothelial activation were measured by ELISA. Baseline Ang-2/Ang-1 was significantly higher in patients who died [median 58 (IQR 17–117) vs. 14 (IQR 6–35), p=0.01]. In a multivariable analysis stratified by dead space fraction, Ang-2/Ang-1 was an independent predictor of death with an adjusted odds ratio of 4.3 (95% CI 1.3–13.5, p=0.01) in those with an elevated pulmonary dead space fraction (p=0.03 for interaction between pulmonary dead space fraction and Ang-2/Ang-1). Moderate to weak correlation was found with biologic markers of endothelial activation. Conclusions The ratio of Ang-2/Ang-1 may be a prognostic biomarker of endothelial activation in ALI patients and, along with pulmonary dead space fraction, may be useful for risk stratification of ALI patients, particularly in identifying subgroups for future research and therapeutic trials. PMID:20581666

Continuation of studies on thermoregulation of fish and turtles in thermally stressed habitats. Summary progress report, 1 October 1977-30 September 1980

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

Spotila, J.R.

1980-05-01

Biophysical-behavioral-ecological models have been completed to explain the behavioral thermoregulation of largemouth bass (Micropterus salmoides) and turtles (Chrysemys scripta). Steady state and time dependent mathematical models accurately predict the body temperatures of largemouth bass. Field experiments using multichannel radio transmitters have provided temperatures of several body compartments of free ranging bass in their natural habitat. Initial studies have been completed to describe the behavioral thermoregulation of bass in a reactor cooling reservoir. Energy budgets, fundamental climate spaces, and realized climate spaces have been completed for the turtle, C. scripta. We have described the behavioral thermoregulation of C. scripta in Parmore » Pond, S.C. and have measured its movements, home ranges and population levels in heated and unheated arms of the reservoir. Operative environmental temperature is a good predictor of the basking behavior of this turtle. A new synthesis explained the evolution of thermoregulatory strategies among animals. Laboratory experiments clarified the effects of movement, diving and temperature on the blood flow of alligators. Other experiments defined the role of boundary layers in controlling the evaporation of water from the surfaces of turtles and alligators in still and moving air. Nutritional status may be an important factor affecting the thermoregulatory behavior of turtles.« less

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

PubMed

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

2014-02-10

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

A Cross-Language Study of Acoustic Predictors of Speech Intelligibility in Individuals With Parkinson's Disease

PubMed Central

Choi, Yaelin

2017-01-01

Purpose The present study aimed to compare acoustic models of speech intelligibility in individuals with the same disease (Parkinson's disease [PD]) and presumably similar underlying neuropathologies but with different native languages (American English [AE] and Korean). Method A total of 48 speakers from the 4 speaker groups (AE speakers with PD, Korean speakers with PD, healthy English speakers, and healthy Korean speakers) were asked to read a paragraph in their native languages. Four acoustic variables were analyzed: acoustic vowel space, voice onset time contrast scores, normalized pairwise variability index, and articulation rate. Speech intelligibility scores were obtained from scaled estimates of sentences extracted from the paragraph. Results The findings indicated that the multiple regression models of speech intelligibility were different in Korean and AE, even with the same set of predictor variables and with speakers matched on speech intelligibility across languages. Analysis of the descriptive data for the acoustic variables showed the expected compression of the vowel space in speakers with PD in both languages, lower normalized pairwise variability index scores in Korean compared with AE, and no differences within or across language in articulation rate. Conclusions The results indicate that the basis of an intelligibility deficit in dysarthria is likely to depend on the native language of the speaker and listener. Additional research is required to explore other potential predictor variables, as well as additional language comparisons to pursue cross-linguistic considerations in classification and diagnosis of dysarthria types. PMID:28821018

Average State IQ, State Wealth and Racial Composition as Predictors of State Health Statistics: Partial Support for "g" as a Fundamental Cause of Health Disparities

ERIC Educational Resources Information Center

Reeve, Charlie L.; Basalik, Debra

2010-01-01

This study examined the degree to which differences in average IQ across the 50 states was associated with differences in health statistics independent of differences in wealth, health care expenditures and racial composition. Results show that even after controlling for differences in state wealth and health care expenditures, average IQ had…

Bioclimatic predictors for supporting ecological applications in the conterminous United States

USGS Publications Warehouse

O'Donnel, Michael S.; Ignizio, Drew A.

2012-01-01

The U.S. Geological Survey (USGS) has developed climate indices, referred to as bioclimatic predictors, which highlight climate conditions best related to species physiology. A set of 20 bioclimatic predictors were developed as Geographic Information Systems (GIS) continuous raster surfaces for each year between 1895 and 2009. The Parameter-elevation Regression on Independent Slopes Model (PRISM) and down-scaled PRISM data, which included both averaged multi-year and averaged monthly climate summaries, was used to develop these multi-scale bioclimatic predictors. Bioclimatic predictors capture information about annual conditions (annual mean temperature, annual precipitation, annual range in temperature and precipitation), as well as seasonal mean climate conditions and intra-year seasonality (temperature of the coldest and warmest months, precipitation of the wettest and driest quarters). Examining climate over time is useful when quantifying the effects of climate changes on species' distributions for past, current, and forecasted scenarios. These data, which have not been readily available to scientists, can provide biologists and ecologists with relevant and multi-scaled climate data to augment research on the responses of species to changing climate conditions. The relationships established between species demographics and distributions with bioclimatic predictors can inform land managers of climatic effects on species during decisionmaking processes.

Assessing Lake Trophic Status: A Proportional Odds Logistic Regression Model

EPA Science Inventory

Lake trophic state classifications are good predictors of ecosystem condition and are indicative of both ecosystem services (e.g., recreation and aesthetics), and disservices (e.g., harmful algal blooms). Methods for classifying trophic state are based off the foundational work o...

[Influential factors on psychosocial health of the migrant workers in Guangzhou].

PubMed

Lin, Qiu-hong; Liu, Yi-min; Zhou, Jing-dong; Cao, Nai-qiong; Fang, Yuan-yu

2012-03-01

To study the influential factors on psychosocial health of the migrant workers in Guangzhou. The Symptom Checklist 90 (SCL-90) and Eysenck Personality Questionnaire (EPQ) were used to investigate 518 migrant workers in Guangzhou. The rate of migrant workers with psychosocial problems was 36.5%. The scores of SCL-90 and positive rates in migrant workers with the different personality types had significant difference (P < 0.01). The results of binary logistic regression analysis indicated that the working years, drinking, sex, P scores, E scores and N scores of EPQ were main predictors of the poor physical fitness status. The vocations, working years, P scores and N scores of EPQ were strong predictors of the somatization. he vocations, P scores and N scores of EPQ were strong predictors of the obsessive compulsive symptom. The smoking, P scores and N scores of EPQ were strong predictors of the interpersonal sensitivity. The working years, P scores of EPQ were strong predictors of the depression. P scores of EPQ was strong predictors of the anxiety. P scores, E scores and N scores of EPQ were strong predictors of the hostility. The working years, smoking, P scores, E scores and N scores of EPQ were strong predictors of the phobic anxiety. The working years, P scores of EPQ were strong predictors of the paranoid ideation. The working years, P scores and N scores of EPQ were strong predictors of the psychosis. The level of mental health of the migrant workers was significantly associated with the personality. The results of present study indicated that different vocation, sex, working years, smoking and drinking might interfere with the psychological states. The migrant workers with the personality of psychoticism, neuroticism and introversion may have unhealthy mental reaction.

An Occupational Performance Test Validation Program for Fire Fighters at the Kennedy Space Center

NASA Technical Reports Server (NTRS)

Schonfeld, Brian R.; Doerr, Donald F.; Convertino, Victor A.

1990-01-01

We evaluated performance of a modified Combat Task Test (CTT) and of standard fitness tests in 20 male subjects to assess the prediction of occupational performance standards for Kennedy Space Center fire fighters. The CTT consisted of stair-climbing, a chopping simulation, and a victim rescue simulation. Average CTT performance time was 3.61 +/- 0.25 min (SEM) and all CTT tasks required 93% to 97% maximal heart rate. By using scores from the standard fitness tests, a multiple linear regression model was fitted to each parameter: the stairclimb (r(exp 2) = .905, P less than .05), the chopping performance time (r(exp 2) = .582, P less than .05), the victim rescue time (r(exp 2) = .218, P = not significant), and the total performance time (r(exp 2) = .769, P less than .05). Treadmill time was the predominant variable, being the major predictor in two of four models. These results indicated that standardized fitness tests can predict performance on some CTT tasks and that test predictors were amenable to exercise training.

Development Roadmap of an Evolvable and Extensible Multi-Mission Telecom Planning and Analysis Framework

NASA Technical Reports Server (NTRS)

Cheung, Kar-Ming; Tung, Ramona H.; Lee, Charles H.

2003-01-01

In this paper, we describe the development roadmap and discuss the various challenges of an evolvable and extensible multi-mission telecom planning and analysis framework. Our long-term goal is to develop a set of powerful flexible telecommunications analysis tools that can be easily adapted to different missions while maintain the common Deep Space Communication requirements. The ability of re-using the DSN ground models and the common software utilities in our adaptations has contributed significantly to our development efforts measured in terms of consistency, accuracy, and minimal effort redundancy, which can translate into shorter development time and major cost savings for the individual missions. In our roadmap, we will address the design principles, technical achievements and the associated challenges for following telecom analysis tools (i) Telecom Forecaster Predictor - TFP (ii) Unified Telecom Predictor - UTP (iii) Generalized Telecom Predictor - GTP (iv) Generic TFP (v) Web-based TFP (vi) Application Program Interface - API (vii) Mars Relay Network Planning Tool - MRNPT.

The Effectiveness of a Cohort Model as a Predictor of Grade Point Average and Graduation Status of Pre-Health Sciences Students in a Public Community College

ERIC Educational Resources Information Center

Brandon, Elvis Nash

2017-01-01

There is a college completion crisis in the United States. In today's competitive job market, health sciences students cannot afford to fail in their educational attainment. The purpose of this study was to determine if participation in the cohort model is a predictor of the success of public community college pre-health sciences students.…

Leaders' Communication Pattern: A Predictor of Lecturers' Job Performance in Nigeria

ERIC Educational Resources Information Center

Oluwatoyin, Fashiku Christopher

2016-01-01

The study investigated the influence leaders' communication pattern has on lecturers' job performance in Kwara State Colleges of Education, Nigeria. Using the descriptive survey method, the population of the study was made up of all lecturers and students of the existing three state government owned Colleges of Education in the state. Five hundred…

Justifying the Ivory Tower: Higher Education and State Economic Growth

ERIC Educational Resources Information Center

Baldwin, J. Norman; McCracken, William A., III

2013-01-01

As the U.S. continues to embrace a comprehensive plan for economic recovery, this article investigates the validity of the claim that investing in higher education will help restore state economic growth and prosperity. It presents the findings from a study that indicates that the most consistent predictors of state economic growth related to…

Parents' Socio-Economic Status as Predictor of Secondary School Students' Academic Performance in Ekiti State, Nigeria

ERIC Educational Resources Information Center

Abdu-Raheem, B. O.

2015-01-01

This paper investigated parents' socio-economic status on secondary school students' academic performance in Ekiti State. Descriptive research design of the survey type was adopted. The population for the study comprised all Junior Secondary School students in Ekiti State. The sample consisted of 960 students from 20 secondary schools randomly…

A direct Arbitrary-Lagrangian-Eulerian ADER-WENO finite volume scheme on unstructured tetrahedral meshes for conservative and non-conservative hyperbolic systems in 3D

NASA Astrophysics Data System (ADS)

Boscheri, Walter; Dumbser, Michael

2014-10-01

In this paper we present a new family of high order accurate Arbitrary-Lagrangian-Eulerian (ALE) one-step ADER-WENO finite volume schemes for the solution of nonlinear systems of conservative and non-conservative hyperbolic partial differential equations with stiff source terms on moving tetrahedral meshes in three space dimensions. A WENO reconstruction technique is used to achieve high order of accuracy in space, while an element-local space-time Discontinuous Galerkin finite element predictor on moving curved meshes is used to obtain a high order accurate one-step time discretization. Within the space-time predictor the physical element is mapped onto a reference element using a high order isoparametric approach, where the space-time basis and test functions are given by the Lagrange interpolation polynomials passing through a predefined set of space-time nodes. Since our algorithm is cell-centered, the final mesh motion is computed by using a suitable node solver algorithm. A rezoning step as well as a flattener strategy are used in some of the test problems to avoid mesh tangling or excessive element deformations that may occur when the computation involves strong shocks or shear waves. The ALE algorithm presented in this article belongs to the so-called direct ALE methods because the final Lagrangian finite volume scheme is based directly on a space-time conservation formulation of the governing PDE system, with the rezoned geometry taken already into account during the computation of the fluxes. We apply our new high order unstructured ALE schemes to the 3D Euler equations of compressible gas dynamics, for which a set of classical numerical test problems has been solved and for which convergence rates up to sixth order of accuracy in space and time have been obtained. We furthermore consider the equations of classical ideal magnetohydrodynamics (MHD) as well as the non-conservative seven-equation Baer-Nunziato model of compressible multi-phase flows with stiff relaxation source terms.

Predictors of women's exercise maintenance after cardiac rehabilitation.

PubMed

Moore, Shirley M; Dolansky, Mary A; Ruland, Cornelia M; Pashkow, Fredric J; Blackburn, Gordon G

2003-01-01

Less than 50% of persons who participate in cardiac rehabilitation (CR) programs maintain an exercise regimen for as long as 6 months after completion. This study was conducted to identify factors that predict women's exercise following completion of a CR program. In this prospective, descriptive study, a convenience sample of 60 women were recruited at completion of a phase II CR program. Exercise was measured using a heart rate wristwatch monitor over 3 months. Predictor variables collected at the time of the subjects' enrollment were age, body mass index, cardiac functional status, comorbidity, muscle or joint pain, motivation, mood state, social support, self-efficacy, perceived benefits or barriers, and prior exercise. Of women, 25% did not exercise at all following completion of a CR program and only 48% of the subjects were exercising at 3 months. Different predictors were found of the various dimensions of exercise maintenance. Predictors of exercise frequency were comorbidity and instrumental social support. Instrumental social support was the only predictor of exercise persistence. Comorbidity was the only predictor of exercise intensity. The only predictor of the total amount of exercise was benefits or barriers. Interventions aimed at increasing women's exercise should focus on increasing their problem-solving abilities to reduce barriers to exercise and increase social support by family and friends. Because comorbidity was a significant predictor of exercise, women should be encouraged to use exercise techniques that reduce impact on muscles and joints (eg, swimming) or exercising for short periods several times a day.

Predicting athletes' functional and dysfunctional emotions: The role of the motivational climate and motivation regulations.

PubMed

Ruiz, Montse C; Haapanen, Saara; Tolvanen, Asko; Robazza, Claudio; Duda, Joan L

2017-08-01

This study examined the relationships between perceptions of the motivational climate, motivation regulations, and the intensity and functionality levels of athletes' pleasant and unpleasant emotional states. Specifically, we examined the hypothesised mediational role of motivation regulations in the climate-emotion relationship. We also tested a sequence in which emotions were assumed to be predicted by the motivational climate dimensions and then served as antecedents to variability in motivation regulations. Participants (N = 494) completed a multi-section questionnaire assessing targeted variables. Structural equation modelling (SEM) revealed that a perceived task-involving climate was a positive predictor of autonomous motivation and of the impact of functional anger, and a negative predictor of the intensity of anxiety and dysfunctional anger. Autonomous motivation was a partial mediator of perceptions of a task-involving climate and the impact of functional anger. An ego-involving climate was a positive predictor of controlled motivation, and of the intensity and impact of functional anger and the intensity of dysfunctional anger. Controlled motivation partially mediated the relationship between an ego-involving climate and the intensity of dysfunctional anger. Good fit to the data also emerged for the motivational climate, emotional states, and motivation regulations sequence. Findings provide support for the consideration of hedonic tone and functionality distinctions in the assessment of athletes' emotional states.

Predictors of Desire for Involvement in a State Rehabilitation Association.

ERIC Educational Resources Information Center

Heinemann, Allen W.; And Others

1986-01-01

Surveyed state rehabilitation association members to test a path model predicting desire for organizational involvement on the basis of breadth of expectations of the organization, professional identity, professional education, training satisfaction, and years in rehabilitation. Broader expectations predicted greater desire for organizational…

Predicting Abandonment of School-Wide Behavior Support Interventions

ERIC Educational Resources Information Center

Nese, Rhonda N. T.; McIntosh, Kent; Nese, Joseph F. T.; Ghemraoui, Adam; Bloom, Jerry; Johnson, Nanci W.; Phillips, Danielle; Richter, Mary F.; Hoselton, Robert

2016-01-01

This study examines predictors of abandonment of evidence-based practices through descriptive analyses of extant state-level training data, fidelity of implementation data, and nationally reported school demographic data across 915 schools in 3 states implementing school-wide positive behavioral interventions and supports (SWPBIS). Schools…

[Anxiety and polymorphism Val66Met of BDNF gene--predictors of depression severity in ischemic heart disease].

PubMed

Golimbet, V E; Volel', B A; Kopylov, F Iu; Dolzhikov, A V; Korovaitseva, G I; Kasparov, S V; Isaeva, M I

2015-01-01

In a framework of search for early predictors of depression in patients with ischemic heart disease (IHD) we studied effect of molecular-genetic factors (polymorphism of brain-derived neirotrophic factor--BDNF), personality traits (anxiety, neuroticism), IHD severity, and psychosocial stressors on manifestations of depression in men with verified diagnosis of IHD. Severity of depression was assessed by Hamilton Depression Rating Scale 21-item (HAMD 21), anxiety and neuroticism were evaluated by the Spielberger State-Trait Anxiety Inventory and "Big Five" questionnaire, respectively. It wa shown that personal anxiety and ValVal genotype of BDNF gene appeared to be predictors of moderate and severe depression.

Improved disturbance rejection for predictor-based control of MIMO linear systems with input delay

NASA Astrophysics Data System (ADS)

Shi, Shang; Liu, Wenhui; Lu, Junwei; Chu, Yuming

2018-02-01

In this paper, we are concerned with the predictor-based control of multi-input multi-output (MIMO) linear systems with input delay and disturbances. By taking the future values of disturbances into consideration, a new improved predictive scheme is proposed. Compared with the existing predictive schemes, our proposed predictive scheme can achieve a finite-time exact state prediction for some smooth disturbances including the constant disturbances, and a better disturbance attenuation can also be achieved for a large class of other time-varying disturbances. The attenuation of mismatched disturbances for second-order linear systems with input delay is also investigated by using our proposed predictor-based controller.

A field examination of two measures of work motivation as predictors of leaders' influence tactics.

PubMed

Barbuto, John E; Fritz, Susan M; Marx, David

2002-10-01

The authors tested 2 motivation measures, the Motivation Sources Inventory (MSI; J. E. Barbuto & R. W. Scholl, 1998) and the Job Choice Decision-Making Exercise (A. M. Harrell & M. J. Stahl, 1981) as predictors of leaders' influence tactics. The authors sampled 219 leader-member dyads from a variety of organizations and communities throughout the central United States. Results strongly favored the MSI as a predictor of influence tactics. Limitations of the study include low power of relationships, sample size as limited by the research design, and education levels of participants. Future researchers should use larger and more diverse samples and test other relevant antecedents of leaders' behaviors.

Non-predictor control of a class of feedforward nonlinear systems with unknown time-varying delays

NASA Astrophysics Data System (ADS)

Koo, Min-Sung; Choi, Ho-Lim

2016-08-01

This paper generalises the several recent results on the control of feedforward time-delay nonlinear systems. First, in view of system formulation, there are unknown time-varying delays in both states and main control input. Also, the considered nonlinear system has extended feedforward nonlinearities. Second, in view of control solution, our proposed controller is a non-predictor feedback controller whereas smith-predictor type controllers are used in the several existing results. Moreover, our controller does not need any information on the unknown delays except their upper bounds. Thus, our result has certain merits in both system formulation and control solution perspective. The analysis and example are given for clear illustration.

Trajectories of affective states in adolescent hockey players: turning point and motivational antecedents.

PubMed

Gaudreau, Patrick; Amiot, Catherine E; Vallerand, Robert J

2009-03-01

This study examined longitudinal trajectories of positive and negative affective states with a sample of 265 adolescent elite hockey players followed across 3 measurement points during the 1st 11 weeks of a season. Latent class growth modeling, incorporating a time-varying covariate and a series of predictors assessed at the onset of the season, was used to chart out distinct longitudinal trajectories of affective states. Results provided evidence for 3 trajectories of positive affect and 3 trajectories of negative affect. Two of these trajectories were deflected by team selection, a seasonal turning point occurring after the 1st measurement point. Furthermore, the trajectories of positive and negative affective states were predicted by theoretically driven predictors assessed at the start of the season (i.e., self-determination, need satisfaction, athletic identity, and school identity). These results contribute to a better understanding of the motivational, social, and identity-related processes associated with the distinct affective trajectories of athletes participating in elite sport during adolescence.

Patterns and predictors of enactment of state childhood obesity legislation in the United States: 2006-2009.

PubMed

Eyler, Amy A; Nguyen, Leah; Kong, Jooyoung; Yan, Yan; Brownson, Ross

2012-12-01

We developed a content review for state policies related to childhood obesity, and we have quantitatively described the predictors of enactment. We collected an inventory of 2006 through 2009 state legislation on 27 childhood obesity topics from legislative databases. We coded each bill for general information, topic content, and other appropriate components. We conducted a general descriptive analysis and 3 multilevel analyses using bill- and state-level characteristics to predict bill enactment. Common topics in the 27% of the bills that were enacted were community physical activity access, physical education, and school food policy. Committee and bipartisan sponsorship and having term limits significantly predicted enactment in at least 1 model. Bills with safe routes to school or health and nutrition content were twice as likely to be enacted. Bills containing product and menu labeling or soda and snack taxes were significantly less likely to be enacted. Bipartisan and committee support and term limits are important in bill enactment. Advocacy efforts can be tailored to increase awareness and sense of priority among policymakers.

Patterns and Predictors of Enactment of State Childhood Obesity Legislation in the United States: 2006–2009

PubMed Central

Nguyen, Leah; Kong, Jooyoung; Yan, Yan; Brownson, Ross

2012-01-01

Objectives. We developed a content review for state policies related to childhood obesity, and we have quantitatively described the predictors of enactment. Methods. We collected an inventory of 2006 through 2009 state legislation on 27 childhood obesity topics from legislative databases. We coded each bill for general information, topic content, and other appropriate components. We conducted a general descriptive analysis and 3 multilevel analyses using bill- and state-level characteristics to predict bill enactment. Results. Common topics in the 27% of the bills that were enacted were community physical activity access, physical education, and school food policy. Committee and bipartisan sponsorship and having term limits significantly predicted enactment in at least 1 model. Bills with safe routes to school or health and nutrition content were twice as likely to be enacted. Bills containing product and menu labeling or soda and snack taxes were significantly less likely to be enacted. Conclusions. Bipartisan and committee support and term limits are important in bill enactment. Advocacy efforts can be tailored to increase awareness and sense of priority among policymakers. PMID:23078482

The impact of school suspension on student tobacco use: A longitudinal study in Victoria, Australia and Washington State, United States

PubMed Central

Hemphill, Sheryl A.; Heerde, Jessica A.; Herrenkohl, Todd I.; Toumbourou, John W.; Catalano, Richard F.

2011-01-01

Context School suspension may have unintended consequences in contributing to problem behaviors including school drop-out, substance use, and antisocial behavior. Tobacco use is an early-onset problem behavior, but prospective studies of the effects of suspension on tobacco use are lacking. Method Longitudinal school-based survey of students drawn as a 2-stage cluster sample, administered in 2002 and 2003 in Washington State, United States and Victoria, Australia. The study uses statewide representative samples of students in Grades 7 and 9 (N = 3,599). Results Rates of tobacco use were higher for Victorian than Washington State students. School suspension remained a predictor of current tobacco use at 12-month follow-up, after controlling for established risk factors including prior tobacco and other drug use for Grade 7 but not Grade 9 students. Conclusions School suspension is associated with tobacco use in early adolescence, itself an established predictor of adverse outcomes in young people. Findings suggest the need to explore process mechanisms and alternatives to school suspensions as a response to challenging student behavior in early adolescence. PMID:21586667

Improved prediction of residue flexibility by embedding optimized amino acid grouping into RSA-based linear models.

PubMed

Zhang, Hua; Kurgan, Lukasz

2014-12-01

Knowledge of protein flexibility is vital for deciphering the corresponding functional mechanisms. This knowledge would help, for instance, in improving computational drug design and refinement in homology-based modeling. We propose a new predictor of the residue flexibility, which is expressed by B-factors, from protein chains that use local (in the chain) predicted (or native) relative solvent accessibility (RSA) and custom-derived amino acid (AA) alphabets. Our predictor is implemented as a two-stage linear regression model that uses RSA-based space in a local sequence window in the first stage and a reduced AA pair-based space in the second stage as the inputs. This method is easy to comprehend explicit linear form in both stages. Particle swarm optimization was used to find an optimal reduced AA alphabet to simplify the input space and improve the prediction performance. The average correlation coefficients between the native and predicted B-factors measured on a large benchmark dataset are improved from 0.65 to 0.67 when using the native RSA values and from 0.55 to 0.57 when using the predicted RSA values. Blind tests that were performed on two independent datasets show consistent improvements in the average correlation coefficients by a modest value of 0.02 for both native and predicted RSA-based predictions.

Predictors of immune function in space flight

NASA Astrophysics Data System (ADS)

Shearer, William T.; Zhang, Shaojie; Reuben, James M.; Lee, Bang-Ning; Butel, Janet S.

2007-02-01

Of all of the environmental conditions of space flight that might have an adverse effect upon human immunity and the incidence of infection, space radiation stands out as the single-most important threat. As important as this would be on humans engaged in long and deep space flight, it obviously is not possible to plan Earth-bound radiation and infection studies in humans. Therefore, we propose to develop a murine model that could predict the adverse effects of space flight radiation and reactivation of latent virus infection for humans. Recent observations on the effects of gamma and latent virus infection demonstrate latent virus reactivation and loss of T cell mediated immune responses in a murine model. We conclude that using this small animal method of quantitating the amounts of radiation and latent virus infection and resulting alterations in immune responses, it may be possible to predict the degree of immunosuppression in interplanetary space travel for humans. Moreover, this model could be extended to include other space flight conditions, such as microgravity, sleep deprivation, and isolation, to obtain a more complete assessment of space flight risks for humans.

The changing suicide pattern in Canadian adolescents and youth, compared to their American counterparts.

PubMed

Leenaars, A A; Lester, D

1995-01-01

Canada has a high rate of suicide among adolescents and youth--higher than the rate in the United States. The study of variation in societal suicide rates is still guided primarily by Durkheim's (1897) theory which proposed a primarily social integration/regulation theory of suicide. There is evidence that social and economic predictors of suicide vary depending upon the particular subgroup--women or men, and young or old. Rates of birth, divorce, marriage, and unemployment were analyzed and compared to rates of suicide from 1965-1985 in Canada and the United States for particular subgroups. In Canada, measures of domestic integration (divorce and birth rates) and the economy (unemployment rate) predicted youth suicide rates more successfully than they did adult suicide rates. In the United States for the same period, there was less variation in the predictors of suicide by age. Further research as well as caution about overgeneralizing the results are warranted.

Shame as a predictor of post-event rumination in social anxiety.

PubMed

Cândea, Diana-Mirela; Szentágotai-Tătar, Aurora

2017-12-01

Evidence shows that people with high social anxiety levels ruminate about distressing social events, which contributes to the maintenance of social anxiety symptoms. The present study aimed to explore the role of shame in maintaining post-event rumination (PER) following a negative social event (an impromptu speech with negative feedback) in a student sample (N = 104). Participants reported negative rumination related to the event one day and one week after the speech. PER measured one day after the speech was not associated with social anxiety symptoms and state anxiety. One week later, participants with clinically relevant social anxiety symptoms experienced greater PER. State shame was the only significant predictor of PER in a regression equation that also included social anxiety symptoms, state anxiety and self-evaluation of performance. Possible explanations and implications are discussed in light of cognitive models of social anxiety.

Frequency and clinical predictors of coronary artery disease in chronic renal failure renal transplant candidates.

PubMed

de Albuquerque Seixas, Emerson; Carmello, Beatriz Leone; Kojima, Christiane Akemi; Contti, Mariana Moraes; Modeli de Andrade, Luiz Gustavo; Maiello, José Roberto; Almeida, Fernando Antonio; Martin, Luis Cuadrado

2015-05-01

Cardiovascular diseases are major causes of mortality in chronic renal failure patients before and after renal transplantation. Among them, coronary disease presents a particular risk; however, risk predictors have been used to diagnose coronary heart disease. This study evaluated the frequency and importance of clinical predictors of coronary artery disease in chronic renal failure patients undergoing dialysis who were renal transplant candidates, and assessed a previously developed scoring system. Coronary angiographies conducted between March 2008 and April 2013 from 99 candidates for renal transplantation from two transplant centers in São Paulo state were analyzed for associations between significant coronary artery diseases (≥70% stenosis in one or more epicardial coronary arteries or ≥50% in the left main coronary artery) and clinical parameters. Univariate logistic regression analysis identified diabetes, angina, and/or previous infarction, clinical peripheral arterial disease and dyslipidemia as predictors of coronary artery disease. Multiple logistic regression analysis identified only diabetes and angina and/or previous infarction as independent predictors. The results corroborate previous studies demonstrating the importance of these factors when selecting patients for coronary angiography in clinical pretransplant evaluation.

Predictors of mammography screening among ethnically diverse low-income women.

PubMed

Cronan, Terry A; Villalta, Ian; Gottfried, Emily; Vaden, Yavette; Ribas, Mabel; Conway, Terry L

2008-05-01

Breast cancer is the second leading cause of cancer deaths among women in the United States. Minority women are less likely to be screened and more likely to die from breast cancer than are Caucasian women. Although some studies have examined ethnic disparities in mammography screening, no study has examined whether there are ethnic disparities among low-income, ethnically diverse women. The present study was designed to determine whether there are ethnic disparities in mammography screening and predictors of screening among low-income African American, Mexican American, and Caucasian women, and to determine whether the disparities and predictors vary across ethnic groups. The participants were 146 low-income women who were Mexican American (32%), African American (31%), or Caucasian (37%). Statistical analyses were performed to assess the relationships between mammography screening during the past 2 years and potential predictors of screening, both within ethnic groups and for the combined sample. The results varied depending on whether analyses combined ethnic groups or were performed within each of the three ethnic groups. It is, therefore, important to examine within-group differences when examining ethnic disparities in predictors of mammography.

Predictors of Exceptional Longevity: Effects of Early-Life and Midlife Conditions, and Familial Longevity.

PubMed

Gavrilov, Leonid A; Gavrilova, Natalia S

Knowledge of strong predictors of mortality and longevity is very important for actuarial science and practice. Earlier studies found that parental characteristics as well as early-life conditions and midlife environment play a significant role in survival to advanced ages. However, little is known about the simultaneous effects of these three factors on longevity. This ongoing study attempts to fill this gap by comparing centenarians born in the United States in 1890-1891 with peers born in the same years who died at age 65. The records for centenarians and controls were taken from computerized family histories, which were then linked to 1900 and 1930 U.S. censuses. As a result of this linkage procedure, 765 records of confirmed centenarians and 783 records of controls were obtained. Analysis with multivariate logistic regression found the existence of both general and gender-specific predictors of human longevity. General predictors common for men and women are paternal and maternal longevity. Gender-specific predictors of male longevity are occupation as a farmer at age 40, Northeastern region of birth in the United States, and birth in the second half of year. A gender-specific predictor of female longevity is the availability of radio in the household according to the 1930 U.S. census. Given the importance of familial longevity as an independent predictor of survival to advanced ages, we conducted a comparative study of biological and nonbiological relatives of centenarians using a larger sample of 1,945 validated U.S. centenarians born in 1880-1895. We found that male gender of centenarian has a significant positive effect on survival of adult male relatives (brothers and fathers) but not female blood relatives. Life span of centenarian siblings-in-law is lower compared to life span of centenarian siblings and does not depend on centenarian gender. Wives of male centenarians (who share lifestyle and living conditions) have a significantly better survival compared to wives of centenarians' brothers. This finding demonstrates an important role of shared familial environment and lifestyle in human longevity. The results of this study suggest that familial background, some early-life conditions and midlife characteristics play an important role in longevity.

Nonlinguistic vocalizations from online amateur videos for emotion research: A validated corpus.

PubMed

Anikin, Andrey; Persson, Tomas

2017-04-01

This study introduces a corpus of 260 naturalistic human nonlinguistic vocalizations representing nine emotions: amusement, anger, disgust, effort, fear, joy, pain, pleasure, and sadness. The recognition accuracy in a rating task varied greatly per emotion, from <40% for joy and pain, to >70% for amusement, pleasure, fear, and sadness. In contrast, the raters' linguistic-cultural group had no effect on recognition accuracy: The predominantly English-language corpus was classified with similar accuracies by participants from Brazil, Russia, Sweden, and the UK/USA. Supervised random forest models classified the sounds as accurately as the human raters. The best acoustic predictors of emotion were pitch, harmonicity, and the spacing and regularity of syllables. This corpus of ecologically valid emotional vocalizations can be filtered to include only sounds with high recognition rates, in order to study reactions to emotional stimuli of known perceptual types (reception side), or can be used in its entirety to study the association between affective states and vocal expressions (production side).

An analysis of region-of-influence methods for flood regionalization in the Gulf-Atlantic Rolling Plains

USGS Publications Warehouse

Eng, K.; Tasker, Gary D.; Milly, P.C.D.

2005-01-01

Region-of-influence (RoI) approaches for estimating streamflow characteristics at ungaged sites were applied and evaluated in a case study of the 50-year peak discharge in the Gulf-Atlantic Rolling Plains of the southeastern United States. Linear regression against basin characteristics was performed for each ungaged site considered based on data from a region of influence containing the n closest gages in predictor variable (PRoI) or geographic (GRoI) space. Augmentation of this count based cutoff by a distance based cutoff also was considered. Prediction errors were evaluated for an independent (split-sampled) dataset. For the dataset and metrics considered here: (1) for either PRoI or GRoI, optimal results were found when the simpler count based cutoff, rather than the distance augmented cutoff, was used; (2) GRoI produced lower error than PRoI when applied indiscriminately over the entire study region; (3) PRoI performance improved considerably when RoI was restricted to predefined geographic subregions.

Predictors of self-reported negative mood following a depressive mood induction procedure across previously depressed, currently anxious, and control individuals.

PubMed

Scherrer, Martin C; Dobson, Keith S; Quigley, Leanne

2014-09-01

This study identified and examined a set of potential predictors of self-reported negative mood following a depressive mood induction procedure (MIP) in a sample of previously depressed, clinically anxious, and control participants. The examined predictor variables were selected on the basis of previous research and theories of depression, and included symptoms of depression and anxiety, negative and positive affect, negative and positive automatic thoughts, dysfunctional beliefs, rumination, self-concept, and occurrence and perceived unpleasantness of recent negative events. The sample consisted of 33 previously depressed, 22 currently anxious, and 26 non-clinical control participants, recruited from community sources. Participant group status was confirmed through structured diagnostic interviews. Participants completed the Velten negative self-statement MIP as well as self-report questionnaires of affective, cognitive, and psychosocial variables selected as potential predictors of mood change. Symptoms of anxiety were associated with increased self-reported negative mood shift following the MIP in previously depressed participants, but not clinically anxious or control participants. Increased occurrence of recent negative events was a marginally significant predictor of negative mood shift for the previously depressed participants only. None of the other examined variables was significant predictors of MIP response for any of the participant groups. These results identify factors that may increase susceptibility to negative mood states in previously depressed individuals, with implications for theory and prevention of relapse to depression. The findings also identify a number of affective, cognitive, and psychosocial variables that do not appear to influence mood change following a depressive MIP in previously depressed, currently anxious, and control individuals. Limitations of the study and directions for future research are discussed. Current anxiety symptomatology was a significant predictor and occurrence of recent negative events was a marginally significant predictor of greater negative mood shift following the depressive mood induction for previously depressed individuals. None of the examined variables predicted change in mood following the depressive mood induction for currently anxious or control individuals. These results suggest that anxiety symptoms and experience with negative events may increase risk for experiencing depressive mood states among individuals with a vulnerability to depression. The generalizability of the present results to individuals with comorbid depression and anxiety is limited. Future research employing appropriate statistical approaches for confirmatory research is needed to test and confirm the present results. © 2014 The British Psychological Society.

Mathematical modeling of a Ti:sapphire solid-state laser

NASA Technical Reports Server (NTRS)

Swetits, John J.

1987-01-01

The project initiated a study of a mathematical model of a tunable Ti:sapphire solid-state laser. A general mathematical model was developed for the purpose of identifying design parameters which will optimize the system, and serve as a useful predictor of the system's behavior.

Predicting Abandonment of School-Wide Positive Behavioral Interventions and Supports

ERIC Educational Resources Information Center

Nese, Rhonda; McIntosh, Kent; Nese, Joseph; Hoselton, Robert; Bloom, Jerry; Johnson, Nanci; Richter, Mary; Phillips, Danielle; Ghemraoui, Adam

2016-01-01

This study examines predictors of abandonment of evidence-based practices through descriptive analyses of extant state-level training data, fidelity of implementation data, and nationally reported school demographic data across 915 schools in three states implementing school-wide positive behavioral interventions and supports (SWPBIS). Schools…

Reference right atrial dimensions and volume estimation by steady state free precession cardiovascular magnetic resonance

PubMed Central

2013-01-01

Background Cardiovascular magnetic resonance (CMR) steady state free precession (SSFP) cine sequences with high temporal resolution and improved post-processing can accurately measure RA dimensions. We used this technique to define ranges for normal RA volumes and dimensions normalized, when necessary, to the influence of gender, body surface area (BSA) and age, and also to define the best 2D images-derived predictors of RA enlargement. Methods For definition of normal ranges of RA volume we studied 120 healthy subjects (60 men, 60 women; 20 subjects per age decile from 20 to 80 years), after careful exclusion of cardiovascular abnormality. We also studied 120 patients (60 men, 60 women; age range 20 to 80 years) with a clinical indication for CMR in order to define the best 1D and 2D predictors of RA enlargement. Data were generated from SSFP cine CMR, with 3-dimensional modeling, including tracking of the atrioventricular ring motion and time-volume curves analysis. Results In the group of healthy individuals, age influenced RA 2-chamber area and transverse diameter. Gender influenced most absolute RA dimensions and volume. Interestingly, right atrial volumes did not change with age and gender when indexed to body surface area. New CMR normal ranges for RA dimensions were modeled and displayed for clinical use with normalization for BSA and gender and display of parameter variation with age. Finally, the best 2D images-derived independent predictors of RA enlargement were indexed area and indexed longitudinal diameter in the 2-chamber view. Conclusion Reference RA dimensions and predictors of RA enlargement are provided using state-of-the-art CMR techniques. PMID:23566426

Mapping the determinants of health inequalities in social space: can Bourdieu help us?

PubMed

Gatrell, Anthony C; Popay, Jennie; Thomas, Carol

2004-09-01

Considerable research effort has been devoted to describing and explaining, at a variety of spatial scales, geographical inequalities in health outcomes within the developed world. Following Bourdieu, we argue that structures of the social world may be revealed in different kinds of 'social' space. We outline the relational thinking that underlies these ideas. We then 'map', using correspondence analysis (on which Bourdieu himself drew), the structure of social space according to the differential availability of some forms of capital, across four study areas in north-west England. We use logistic regression analysis to explain variation in psychological morbidity (GHQ-score) and then portray the significant predictors of morbidity using multiple correspondence analysis. The area of residence of the survey respondents is used to associate them with particular locations in these social spaces.

The Musculoskeletal Readiness Screening Tool-Injury Predictor for United States Military Academy Preparatory Cadets

DTIC Science & Technology

2015-10-30

predictors of ACL injury.25 189 Several studies investigate the effects of faulty movement and injury 190 prediction for the lower extremity. In 2006...at 40% and 39% of the total injuries, respectively.16 In 2012, 83 193 NCAA Division I football players participated in a survey to assess low back...recent study , firefighters performed the FMS™ and firefighter-specific testing. Two 218 of the musculoskeletal movement variables were predictive of

Predictors of matching in an ophthalmology residency program.

PubMed

Loh, Allison R; Joseph, Damien; Keenan, Jeremy D; Lietman, Thomas M; Naseri, Ayman

2013-04-01

To examine the characteristics of US medical students applying for ophthalmology residency and to determine the predictors of matching. A retrospective case series. A total of 3435 medical students from the United States who applied to an ophthalmology residency program from 2003 to 2008 were included. Matched and unmatched applicants were compared and stratified by predictor variables, including United States Medical Licensing Examination (USMLE) Step 1 score, Alpha Omega Alpha (AOA) status, medical school reputation, and medical school geographic region. Differences in proportions were analyzed using the Fisher exact test. Logistic regression was used to determine the predictors of successful matching. Successful matching to an ophthalmology program. The majority of applicants (72%, 2486/3435) matched in ophthalmology. In multivariate analysis, AOA membership (odds ratio [OR], 2.6, P<0.0001), USMLE score (OR, 1.6; P<0.0001), presence of an ophthalmology residency at medical school (OR, 1.4; P = 0.01), top 25 medical school (OR, 1.4; P<0.03), top 10 medical school (OR, 1.6; P<0.02), and allopathic degree (OR, 4.0; P<0.0001) were statistically significant predictors of matching. Approximately 60% (1442/2486) of applicants matched to the same geographic region as their medical school. Applicants were more likely to match at a program in the same geographic region as their medical school than would be predicted by chance alone (P<0.0001). In multivariate analysis, higher USMLE score (OR, 0.9; P<0.0001) and top 10 medical school (OR, 0.7; P = 0.027) were statistically significant predictors of matching to outside the geographic region as one's medical school. The majority of applicants applying for an ophthalmology residency position match successfully. Higher performance on quantitative metrics seems to confer an advantage for matching. The majority of applicants match at a residency program within the same geographic region as one's medical school. Copyright © 2013 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Self-consistent predictor/corrector algorithms for stable and efficient integration of the time-dependent Kohn-Sham equation

NASA Astrophysics Data System (ADS)

Zhu, Ying; Herbert, John M.

2018-01-01

The "real time" formulation of time-dependent density functional theory (TDDFT) involves integration of the time-dependent Kohn-Sham (TDKS) equation in order to describe the time evolution of the electron density following a perturbation. This approach, which is complementary to the more traditional linear-response formulation of TDDFT, is more efficient for computation of broad-band spectra (including core-excited states) and for systems where the density of states is large. Integration of the TDKS equation is complicated by the time-dependent nature of the effective Hamiltonian, and we introduce several predictor/corrector algorithms to propagate the density matrix, one of which can be viewed as a self-consistent extension of the widely used modified-midpoint algorithm. The predictor/corrector algorithms facilitate larger time steps and are shown to be more efficient despite requiring more than one Fock build per time step, and furthermore can be used to detect a divergent simulation on-the-fly, which can then be halted or else the time step modified.

Child physical abuse: prevalence, characteristics, predictors, and beliefs about parent-child violence in South Asian, Middle Eastern, East Asian, and Latina women in the United States.

PubMed

Maker, Azmaira H; Shah, Priti V; Agha, Zia

2005-11-01

The present study examined the prevalence, characteristics, beliefs, and demographic predictors of parent-child physical violence among South Asian, Middle Eastern, East Asian, and Latina women in the United States. Two hundred fifty-one college-educated women from a middle to high SES (South Asian/Middle Eastern, n = 93; East Asian,n = 72; Latina,n = 86) completed a self-report survey on childhood experiences and beliefs regarding physical abuse. Seventy-three percent of the South Asian and Middle Eastern sample, 65% of the East Asian sample, and 78% of the Latina sample reported experiencing at least one type of physical abuse. Significant differences in characteristics and perpetrators of abuse were found across groups. Demographic factors did not predict physical abuse. Experiencing physical abuse was the only predictor for acceptance of physical discipline and as a parental privilege or right across groups. Implications of alternate cultural models of family violence based on beliefs and exposure to violence are discussed.

Condom use among Hispanic men with secondary female sexual partners.

PubMed Central

Marin, B V; Gomez, C A; Tschann, J M

1993-01-01

Greater understanding of psychosocial predictors of the use of condoms among Hispanics is needed in prevention efforts related to the human immunodeficiency virus and sexually transmitted disease epidemics among Hispanics in the United States. A telephone survey was carried out in nine States that have large populations of Hispanics, using a stratified clustered random digit dialing sampling strategy. The survey yielded interviews with 968 Hispanic men ages 18-49 years. Of them, 361 (37.8 percent) reported at least one secondary female sexual partner in the 12 months prior to the interview. Predictors were identified of condom use by those men with their secondary sex partners. Key predictors of the subjects' condom use with secondary partners included carrying condoms; self-efficacy, or a measure of the subject's perceived ability to use condoms under difficult circumstances; positive attitude toward condom use; having friends who used condoms; and lack of symptoms of depression in the week before the interview (R2 = 0.35). Significant predictors of condom carrying were being comfortable in sexual situations, positive attitude toward condom use, and self-efficacy to use condoms. Less acculturated men had more positive attitudes toward condom use and carried them more than did more acculturated men. The researchers found encouraging levels of condom use with secondary sexual partners among Hispanic men with multiple partners.(ABSTRACT TRUNCATED AT 250 WORDS) PMID:8265759

Regionally Implicit Discontinuous Galerkin Methods for Solving the Relativistic Vlasov-Maxwell System Submitted to Iowa State University

NASA Astrophysics Data System (ADS)

Guthrey, Pierson Tyler

The relativistic Vlasov-Maxwell system (RVM) models the behavior of collisionless plasma, where electrons and ions interact via the electromagnetic fields they generate. In the RVM system, electrons could accelerate to significant fractions of the speed of light. An idea that is actively being pursued by several research groups around the globe is to accelerate electrons to relativistic speeds by hitting a plasma with an intense laser beam. As the laser beam passes through the plasma it creates plasma wakes, much like a ship passing through water, which can trap electrons and push them to relativistic speeds. Such setups are known as laser wakefield accelerators, and have the potential to yield particle accelerators that are significantly smaller than those currently in use. Ultimately, the goal of such research is to harness the resulting electron beams to generate electromagnetic waves that can be used in medical imaging applications. High-order accurate numerical discretizations of kinetic Vlasov plasma models are very effective at yielding low-noise plasma simulations, but are computationally expensive to solve because of the high dimensionality. In addition to the general difficulties inherent to numerically simulating Vlasov models, the relativistic Vlasov-Maxwell system has unique challenges not present in the non-relativistic case. One such issue is that operator splitting of the phase gradient leads to potential instabilities, thus we require an alternative to operator splitting of the phase. The goal of the current work is to develop a new class of high-order accurate numerical methods for solving kinetic Vlasov models of plasma. The main discretization in configuration space is handled via a high-order finite element method called the discontinuous Galerkin method (DG). One difficulty is that standard explicit time-stepping methods for DG suffer from time-step restrictions that are significantly worse than what a simple Courant-Friedrichs-Lewy (CFL) argument requires. The maximum stable time-step scales inversely with the highest degree in the DG polynomial approximation space and becomes progressively smaller with each added spatial dimension. In this work, we overcome this difficulty by introducing a novel time-stepping strategy: the regionally-implicit discontinuous Galerkin (RIDG) method. The RIDG is method is based on an extension of the Lax-Wendroff DG (LxW-DG) method, which previously had been shown to be equivalent (for linear constant coefficient problems) to a predictor-corrector approach, where the prediction is computed by a space-time DG method (STDG). The corrector is an explicit method that uses the space-time reconstructed solution from the predictor step. In this work, we modify the predictor to include not just local information, but also neighboring information. With this modification, we show that the stability is greatly enhanced; we show that we can remove the polynomial degree dependence of the maximum time-step and show vastly improved time-steps in multiple spatial dimensions. Upon the development of the general RIDG method, we apply it to the non-relativistic 1D1V Vlasov-Poisson equations and the relativistic 1D2V Vlasov-Maxwell equations. For each we validate the high-order method on several test cases. In the final test case, we demonstrate the ability of the method to simulate the acceleration of electrons to relativistic speeds in a simplified test case.

State Machine Modeling of the Space Launch System Solid Rocket Boosters

NASA Technical Reports Server (NTRS)

Harris, Joshua A.; Patterson-Hine, Ann

2013-01-01

The Space Launch System is a Shuttle-derived heavy-lift vehicle currently in development to serve as NASA's premiere launch vehicle for space exploration. The Space Launch System is a multistage rocket with two Solid Rocket Boosters and multiple payloads, including the Multi-Purpose Crew Vehicle. Planned Space Launch System destinations include near-Earth asteroids, the Moon, Mars, and Lagrange points. The Space Launch System is a complex system with many subsystems, requiring considerable systems engineering and integration. To this end, state machine analysis offers a method to support engineering and operational e orts, identify and avert undesirable or potentially hazardous system states, and evaluate system requirements. Finite State Machines model a system as a finite number of states, with transitions between states controlled by state-based and event-based logic. State machines are a useful tool for understanding complex system behaviors and evaluating "what-if" scenarios. This work contributes to a state machine model of the Space Launch System developed at NASA Ames Research Center. The Space Launch System Solid Rocket Booster avionics and ignition subsystems are modeled using MATLAB/Stateflow software. This model is integrated into a larger model of Space Launch System avionics used for verification and validation of Space Launch System operating procedures and design requirements. This includes testing both nominal and o -nominal system states and command sequences.

Stay out of My Space! Territoriality and Nonverbal Immediacy as Predictors of Roommate Satisfaction

ERIC Educational Resources Information Center

Erlandson, Karen

2012-01-01

This study utilize d direct observation to explore the relationship between nonverbal communication variables (immediacy and territoriality) and roommate satisfaction. Data were collected from 51 roommate pairs (N = 102) at a small liberal arts college. Participants were asked to engage in a discussion about a time they had to negotiate activities…

A comparison of mangrove canopy height using multiple independent measurements from land, air, and space

Treesearch

David Lagomasino; Temilola Fatoyinbo; SeungKuk Lee; Emanuelle Feliciano; Carl Trettin; Marc Simard

2016-01-01

Canopy height is one of the strongest predictors of biomass and carbon in forested ecosystems. Additionally, mangrove ecosystems represent one of the most concentrated carbon reservoirs that are rapidly degrading as a result of deforestation, development, and hydrologic manipulation. Therefore, the accuracy of Canopy Height Models (CHM) over mangrove forest...

Lessons on Leadership: A Study of Distributed Leadership in Washington State. Research Report #10

ERIC Educational Resources Information Center

Washington School Research Center, 2007

2007-01-01

As traditionally structured, American schools, in general, have found it more difficult to educate some students than others. In Washington State, as in most other states, the single best predictor of student achievement at the school level is the percentage of students on free or reduced (f/r) lunch status (Abbott & Joireman, 2001). This fact…

Cognitive components of a mathematical processing network in 9-year-old children.

PubMed

Szűcs, Dénes; Devine, Amy; Soltesz, Fruzsina; Nobes, Alison; Gabriel, Florence

2014-07-01

We determined how various cognitive abilities, including several measures of a proposed domain-specific number sense, relate to mathematical competence in nearly 100 9-year-old children with normal reading skill. Results are consistent with an extended number processing network and suggest that important processing nodes of this network are phonological processing, verbal knowledge, visuo-spatial short-term and working memory, spatial ability and general executive functioning. The model was highly specific to predicting arithmetic performance. There were no strong relations between mathematical achievement and verbal short-term and working memory, sustained attention, response inhibition, finger knowledge and symbolic number comparison performance. Non-verbal intelligence measures were also non-significant predictors when added to our model. Number sense variables were non-significant predictors in the model and they were also non-significant predictors when entered into regression analysis with only a single visuo-spatial WM measure. Number sense variables were predicted by sustained attention. Results support a network theory of mathematical competence in primary school children and falsify the importance of a proposed modular 'number sense'. We suggest an 'executive memory function centric' model of mathematical processing. Mapping a complex processing network requires that studies consider the complex predictor space of mathematics rather than just focusing on a single or a few explanatory factors.

The Geography of Mental Health and General Wellness in Galveston Bay After Hurricane Ike: A Spatial Epidemiologic Study With Longitudinal Data.

PubMed

Gruebner, Oliver; Lowe, Sarah R; Tracy, Melissa; Cerdá, Magdalena; Joshi, Spruha; Norris, Fran H; Galea, Sandro

2016-04-01

To demonstrate a spatial epidemiologic approach that could be used in the aftermath of disasters to (1) detect spatial clusters and (2) explore geographic heterogeneity in predictors for mental health and general wellness. We used a cohort study of Hurricane Ike survivors (n=508) to assess the spatial distribution of postdisaster mental health wellness (most likely resilience trajectory for posttraumatic stress symptoms [PTSS] and depression) and general wellness (most likely resilience trajectory for PTSS, depression, functional impairment, and days of poor health) in Galveston, Texas. We applied the spatial scan statistic (SaTScan) and geographically weighted regression. We found spatial clusters of high likelihood wellness in areas north of Texas City and spatial concentrations of low likelihood wellness in Galveston Island. Geographic variation was found in predictors of wellness, showing increasing associations with both forms of wellness the closer respondents were located to Galveston City in Galveston Island. Predictors for postdisaster wellness may manifest differently across geographic space with concentrations of lower likelihood wellness and increased associations with predictors in areas of higher exposure. Our approach could be used to inform geographically targeted interventions to promote mental health and general wellness in disaster-affected communities.

Cognitive components of a mathematical processing network in 9-year-old children

PubMed Central

Szűcs, Dénes; Devine, Amy; Soltesz, Fruzsina; Nobes, Alison; Gabriel, Florence

2014-01-01

We determined how various cognitive abilities, including several measures of a proposed domain-specific number sense, relate to mathematical competence in nearly 100 9-year-old children with normal reading skill. Results are consistent with an extended number processing network and suggest that important processing nodes of this network are phonological processing, verbal knowledge, visuo-spatial short-term and working memory, spatial ability and general executive functioning. The model was highly specific to predicting arithmetic performance. There were no strong relations between mathematical achievement and verbal short-term and working memory, sustained attention, response inhibition, finger knowledge and symbolic number comparison performance. Non-verbal intelligence measures were also non-significant predictors when added to our model. Number sense variables were non-significant predictors in the model and they were also non-significant predictors when entered into regression analysis with only a single visuo-spatial WM measure. Number sense variables were predicted by sustained attention. Results support a network theory of mathematical competence in primary school children and falsify the importance of a proposed modular ‘number sense’. We suggest an ‘executive memory function centric’ model of mathematical processing. Mapping a complex processing network requires that studies consider the complex predictor space of mathematics rather than just focusing on a single or a few explanatory factors. PMID:25089322

14 CFR 1217.106 - Articles brought into the United States by NASA from space.

Code of Federal Regulations, 2010 CFR

2010-01-01

... NASA from space. 1217.106 Section 1217.106 Aeronautics and Space NATIONAL AERONAUTICS AND SPACE ADMINISTRATION DUTY-FREE ENTRY OF SPACE ARTICLES § 1217.106 Articles brought into the United States by NASA from... territory of the United States by NASA from space shall not be considered an importation, and no...

14 CFR 1217.106 - Articles brought into the United States by NASA from space.

Code of Federal Regulations, 2012 CFR

2012-01-01

... NASA from space. 1217.106 Section 1217.106 Aeronautics and Space NATIONAL AERONAUTICS AND SPACE ADMINISTRATION DUTY-FREE ENTRY OF SPACE ARTICLES § 1217.106 Articles brought into the United States by NASA from... territory of the United States by NASA from space shall not be considered an importation, and no...

14 CFR 1217.106 - Articles brought into the United States by NASA from space.

Code of Federal Regulations, 2011 CFR

2011-01-01

... NASA from space. 1217.106 Section 1217.106 Aeronautics and Space NATIONAL AERONAUTICS AND SPACE ADMINISTRATION DUTY-FREE ENTRY OF SPACE ARTICLES § 1217.106 Articles brought into the United States by NASA from... territory of the United States by NASA from space shall not be considered an importation, and no...

Predictive displays for a process-control schematic interface.

PubMed

Yin, Shanqing; Wickens, Christopher D; Helander, Martin; Laberge, Jason C

2015-02-01

Our objective was to examine the extent to which increasing precision of predictive (rate of change) information in process control will improve performance on a simulated process-control task. Predictive displays have been found to be useful in process control (as well as aviation and maritime industries). However, authors of prior research have not examined the extent to which predictive value is increased by increasing predictor resolution, nor has such research tied potential improvements to changes in process control strategy. Fifty nonprofessional participants each controlled a simulated chemical mixture process (honey mixer simulation) that simulated the operations found in process control. Participants in each of five groups controlled with either no predictor or a predictor ranging in the resolution of prediction of the process. Increasing detail resolution generally increased the benefit of prediction over the control condition although not monotonically so. The best overall performance, combining quality and predictive ability, was obtained by the display of intermediate resolution. The two displays with the lowest resolution were clearly inferior. Predictors with higher resolution are of value but may trade off enhanced sensitivity to variable change (lower-resolution discrete state predictor) with smoother control action (higher-resolution continuous predictors). The research provides guidelines to the process-control industry regarding displays that can most improve operator performance.

Predictors of the Perception of Smoking Health Risks in Smokers With or Without Schizophrenia.

PubMed

Kowalczyk, William J; Wehring, Heidi J; Burton, George; Raley, Heather; Feldman, Stephanie; Heishman, Stephen J; Kelly, Deanna L

2017-01-01

This study sought to examine the predictors of health risk perception in smokers with or without schizophrenia. The health risk subscale from the Smoking Consequences Questionnaire was dichotomized and used to measure health risk perception in smokers with (n = 67) and without schizophrenia (n = 100). A backward stepwise logistic regression was conducted using variables associated at the bivariate level to determine multivariate predictors. Overall, 62.5% of smokers without schizophrenia and 40.3% of smokers with schizophrenia completely recognize the health risks of smoking (p ≤ .01). Multivariate predictors for smokers without schizophrenia included: sex (Exp (B) = .3; p < .05), Smoking Consequences Questionnaire state enhancement (Exp (B) = .69; p < .01), and craving relief (Exp (B) = 1.8; p < .01). Among smokers with schizophrenia, predictors were education (Exp (B) = .7; p < .05), nicotine dependence (Exp (B) = .5; p < .01), motivation to quit (Exp (B) = 1.8; p < .01), and Smoking Consequences Questionnaire craving relief (Exp (B) = 1.8; p < .01). There was overlap and differences between predictors in smokers with and without schizophrenia. Commonly used techniques for education on the health consequences of cigarettes may work in smokers with schizophrenia, but intervention efforts specifically tailored to smokers with schizophrenia might be more efficacious.

Predictors of the Perception of Smoking Health Risks in Smokers With or Without Schizophrenia

PubMed Central

Kowalczyk, William J.; Wehring, Heidi J.; Burton, George; Raley, Heather; Feldman, Stephanie; Heishman, Stephen J.; Kelly, Deanna L.

2017-01-01

Objective This study sought to examine the predictors of health risk perception in smokers with or without schizophrenia. Methods The health risk subscale from the Smoking Consequences Questionnaire was dichotomized and used to measure health risk perception in smokers with (n = 67) and without schizophrenia (n = 100). A backward stepwise logistic regression was conducted using variables associated at the bivariate level to determine multivariate predictors. Results Overall, 62.5% of smokers without schizophrenia and 40.3% of smokers with schizophrenia completely recognize the health risks of smoking (p ≤ .01). Multivariate predictors for smokers without schizophrenia included: sex (Exp (B) = .3; p < .05), Smoking Consequences Questionnaire state enhancement (Exp (B) = .69; p < .01), and craving relief (Exp (B) = 1.8; p < .01). Among smokers with schizophrenia, predictors were education (Exp (B) = .7; p < .05), nicotine dependence (Exp (B) = .5; p < .01), motivation to quit (Exp (B) = 1.8; p < .01), and Smoking Consequences Questionnaire craving relief (Exp (B) = 1.8; p < .01). Conclusions There was overlap and differences between predictors in smokers with and without schizophrenia. Commonly used techniques for education on the health consequences of cigarettes may work in smokers with schizophrenia, but intervention efforts specifically tailored to smokers with schizophrenia might be more efficacious. PMID:27858591

Spatially Explicit Predictors of Indicators of Water Quality: Example from Wadeable Streams in the U.S

EPA Science Inventory

The Environmental Protection Agency (USEPA) in collaboration with the States is assessing and reporting on the condition of surface waters in the United States using synoptic surveys and consistent field collections of water quality indicators (WQI). The survey is a probability-b...

Predictors of Postsecondary Success

ERIC Educational Resources Information Center

Hein, Vanessa; Smerdon, Becky; Sambolt, Megan

2013-01-01

The purpose of this brief is to provide information to state, district, and school personnel seeking support to determine whether their students are on a path to postsecondary success. The College and Career Readiness and Success Center (CCRS Center) has received technical assistance requests from a number of states regarding factors that predict…

Effective dimension reduction for sparse functional data

PubMed Central

YAO, F.; LEI, E.; WU, Y.

2015-01-01

Summary We propose a method of effective dimension reduction for functional data, emphasizing the sparse design where one observes only a few noisy and irregular measurements for some or all of the subjects. The proposed method borrows strength across the entire sample and provides a way to characterize the effective dimension reduction space, via functional cumulative slicing. Our theoretical study reveals a bias-variance trade-off associated with the regularizing truncation and decaying structures of the predictor process and the effective dimension reduction space. A simulation study and an application illustrate the superior finite-sample performance of the method. PMID:26566293

Efficient conservative ADER schemes based on WENO reconstruction and space-time predictor in primitive variables

NASA Astrophysics Data System (ADS)

Zanotti, Olindo; Dumbser, Michael

2016-01-01

We present a new version of conservative ADER-WENO finite volume schemes, in which both the high order spatial reconstruction as well as the time evolution of the reconstruction polynomials in the local space-time predictor stage are performed in primitive variables, rather than in conserved ones. To obtain a conservative method, the underlying finite volume scheme is still written in terms of the cell averages of the conserved quantities. Therefore, our new approach performs the spatial WENO reconstruction twice: the first WENO reconstruction is carried out on the known cell averages of the conservative variables. The WENO polynomials are then used at the cell centers to compute point values of the conserved variables, which are subsequently converted into point values of the primitive variables. This is the only place where the conversion from conservative to primitive variables is needed in the new scheme. Then, a second WENO reconstruction is performed on the point values of the primitive variables to obtain piecewise high order reconstruction polynomials of the primitive variables. The reconstruction polynomials are subsequently evolved in time with a novel space-time finite element predictor that is directly applied to the governing PDE written in primitive form. The resulting space-time polynomials of the primitive variables can then be directly used as input for the numerical fluxes at the cell boundaries in the underlying conservative finite volume scheme. Hence, the number of necessary conversions from the conserved to the primitive variables is reduced to just one single conversion at each cell center. We have verified the validity of the new approach over a wide range of hyperbolic systems, including the classical Euler equations of gas dynamics, the special relativistic hydrodynamics (RHD) and ideal magnetohydrodynamics (RMHD) equations, as well as the Baer-Nunziato model for compressible two-phase flows. In all cases we have noticed that the new ADER schemes provide less oscillatory solutions when compared to ADER finite volume schemes based on the reconstruction in conserved variables, especially for the RMHD and the Baer-Nunziato equations. For the RHD and RMHD equations, the overall accuracy is improved and the CPU time is reduced by about 25 %. Because of its increased accuracy and due to the reduced computational cost, we recommend to use this version of ADER as the standard one in the relativistic framework. At the end of the paper, the new approach has also been extended to ADER-DG schemes on space-time adaptive grids (AMR).

Trajectories and predictors of state and trait anxiety in patients receiving chemotherapy for breast and colorectal cancer: Results from a longitudinal study.

PubMed

Schneider, Annegret; Kotronoulas, Grigorios; Papadopoulou, Constantina; McCann, Lisa; Miller, Morven; McBride, Jackie; Polly, Zoe; Bettles, Simon; Whitehouse, Alison; Kearney, Nora; Maguire, Roma

2016-10-01

To examine the trajectories and predictors of state and trait anxiety in patients undergoing chemotherapy for breast or colorectal cancer. Secondary analysis of data collected as part of a large multi-site longitudinal study. Patients with breast or colorectal cancer completed validated scales assessing their state and trait anxiety levels (State-Trait Anxiety Inventory) and symptom burden (Rotterdam Symptom Checklist) at the beginning of each chemotherapy cycle. Longitudinal mixed model analyses were performed to test changes of trait and state anxiety over time and the predictive value of symptom burden and patients' demographic (age, gender) and clinical characteristics (cancer type, stage, comorbidities, ECOG performance status). Data from 137 patients with breast (60%) or colorectal cancer (40%) were analysed. Linear time effects were found for both state (χ 2  = 46.3 [df = 3]; p < 0.001) and trait anxiety (χ 2  = 17.708 [df = 3]; p = 0.001), with anxiety levels being higher at baseline and gradually decreasing over the course of chemotherapy. Symptom burden (β = 0.21; SD = 0.06; p = 0.001) predicted state anxiety throughout treatment, but this effect disappeared when accounting for trait anxiety scores before the start of chemotherapy (β = 0.85; SD = 0.05; p < 0.001). Patients' baseline trait anxiety was the only significant predictor of anxiety throughout treatment. Changes in the generally stable characteristic of trait anxiety indicate the profoundly life-altering nature of chemotherapy. The time point before the start of chemotherapy was identified as the most anxiety-provoking, calling for interventions to be delivered as early as possible in the treatment trajectory. Patients with high trait anxiety and symptom burden may benefit from additional support. Copyright © 2016 Elsevier Ltd. All rights reserved.

Recurrence patterns and survival endpoints in women with stage II uterine endometrioid carcinoma: a multi-institution study.

PubMed

Elshaikh, Mohamed A; Al-Wahab, Zaid; Mahdi, Haider; Albuquerque, Kevin; Mahan, Meredith; Kehoe, Siobhan M; Ali-Fehmi, Rouba; Rose, Peter G; Munkarah, Adnan R

2015-02-01

There is paucity of data in regard to prognostic factors and outcome of women with 2009 FIGO stage II disease. The objective of this study was to investigate prognostic factors, recurrence patterns and survival endpoints in this group of patients. Data from four academic institutions were analyzed. 130 women were identified with 2009 FIGO stage II. All patients underwent hysterectomy, oophorectomy and lymph node evaluation with or without pelvic and paraaortic lymph node dissections and peritoneal cytology. The Kaplan-Meier approach and Cox regression analysis were used to estimate recurrence-free (RFS), disease-specific (DSS) and overall survival (OS). Median follow-up was 44months. 120 patients (92%) underwent simple hysterectomy, 78% had lymph node dissection and 95% had peritoneal cytology examination. 99 patients (76%) received adjuvant radiation treatment (RT). 5-year RFS, DSS and OS were 77%, 90%, and 72%, respectively. On multivariate analysis of RFS, adjuvant RT, the presence of lymphovascular space invasion (LVSI) and high tumor grades were significant predictors. For DSS, LVSI and high tumor grades were significant predictors while older age and high tumor grade were the only predictors of OS. In this multi-institutional study, disease-specific survival for women with FIGO stage II uterine endometrioid carcinoma is excellent. High tumor grade, lymphovascular space invasion, adjuvant radiation treatment and old age are important prognostic factors. There was no significant difference in the outcome between patients who received vaginal cuff brachytherapy compared to those who received pelvic external beam radiation treatment. Copyright © 2014 Elsevier Inc. All rights reserved.

Predictors for Perioperative Outcomes following Total Laryngectomy: A University HealthSystem Consortium Discharge Database Study.

PubMed

Rutledge, Jonathan W; Spencer, Horace; Moreno, Mauricio A

2014-07-01

The University HealthSystem Consortium (UHC) database collects discharge information on patients treated at academic health centers throughout the United States. We sought to use this database to identify outcome predictors for patients undergoing total laryngectomy. A secondary end point was to assess the validity of the UHC's predictive risk mortality model in this cohort of patients. Retrospective review. Academic medical centers (tertiary referral centers) and their affiliate hospitals in the United States. Using the UHC discharge database, we retrieved and analyzed data for 4648 patients undergoing total laryngectomy who were discharged between October 2007 and January 2011 from all of the member institutions. Demographics, comorbidities, institutional data, and outcomes were retrieved. The length of stay and overall costs were significantly higher among female patients (P < .0001), while age was a predictor of intensive care unit stay (P = .014). The overall complication rate was higher among Asians (P = .019) and in patients with anemia and diabetes compared with other comorbidities. The average institutional case load was 1.92 cases/mo; we found an inverse correlation (R = -0.47) between the institutional case load and length of stay (P < .0001). The UHC admit mortality risk estimator was found to be an accurate predictor not only of mortality (P < .0002) but also of intensive care unit admission and complication rate (P < .0001). This study provides an overview of laryngectomy outcomes in a contemporary cohort of patients treated at academic health centers. UHC admit mortality risk is an excellent outcome predictor and a valuable tool for risk stratification in these patients. © American Academy of Otolaryngology—Head and Neck Surgery Foundation 2014.

Why do patients discontinue fertility treatment? A systematic review of reasons and predictors of discontinuation in fertility treatment.

PubMed

Gameiro, S; Boivin, J; Peronace, L; Verhaak, C M

2012-01-01

BACKGROUND Chances of achieving parenthood are high for couples who undergo fertility treatment. However, many choose to discontinue before conceiving. A systematic review was conducted to investigate patients' stated reasons for and predictors of discontinuation at five fertility treatment stages. METHODS Six databases were systematically searched. Search-terms referred to fertility treatment and discontinuation. Studies reporting on patients' stated reasons for or predictors of treatment discontinuation were included. A list of all reasons for discontinuation presented in each study was made, different categories of reasons were defined and the percentage of selections of each category was calculated. For each predictor, it was noted how many studies investigated it and how many found a positive and/or negative association with discontinuation. RESULTS The review included 22 studies that sampled 21 453 patients from eight countries. The most selected reasons for discontinuation were: postponement of treatment (39.18%, postponement of treatment or unknown 19.17%), physical and psychological burden (19.07%, psychological burden 14%, physical burden 6.32%), relational and personal problems (16.67%, personal reasons 9.27%, relational problems 8.83%), treatment rejection (13.23%) and organizational (11.68%) and clinic (7.71%) problems. Some reasons were common across stages (e.g. psychological burden). Others were stage-specific (e.g. treatment rejection during workup). None of the predictors reported were consistently associated with discontinuation. CONCLUSIONS Much longitudinal and theory led research is required to explain discontinuation. Meanwhile, treatment burden should be addressed by better care organization and support for patients. Patients should be well informed, have the opportunity to discuss values and worries about treatment and receive advice to decide about continuing treatment.

Why do patients discontinue fertility treatment? A systematic review of reasons and predictors of discontinuation in fertility treatment

PubMed Central

Gameiro, S.; Boivin, J.; Peronace, L.; Verhaak, C.M.

2012-01-01

BACKGROUND Chances of achieving parenthood are high for couples who undergo fertility treatment. However, many choose to discontinue before conceiving. A systematic review was conducted to investigate patients' stated reasons for and predictors of discontinuation at five fertility treatment stages. METHODS Six databases were systematically searched. Search-terms referred to fertility treatment and discontinuation. Studies reporting on patients' stated reasons for or predictors of treatment discontinuation were included. A list of all reasons for discontinuation presented in each study was made, different categories of reasons were defined and the percentage of selections of each category was calculated. For each predictor, it was noted how many studies investigated it and how many found a positive and/or negative association with discontinuation. RESULTS The review included 22 studies that sampled 21 453 patients from eight countries. The most selected reasons for discontinuation were: postponement of treatment (39.18%, postponement of treatment or unknown 19.17%), physical and psychological burden (19.07%, psychological burden 14%, physical burden 6.32%), relational and personal problems (16.67%, personal reasons 9.27%, relational problems 8.83%), treatment rejection (13.23%) and organizational (11.68%) and clinic (7.71%) problems. Some reasons were common across stages (e.g. psychological burden). Others were stage-specific (e.g. treatment rejection during workup). None of the predictors reported were consistently associated with discontinuation. CONCLUSIONS Much longitudinal and theory led research is required to explain discontinuation. Meanwhile, treatment burden should be addressed by better care organization and support for patients. Patients should be well informed, have the opportunity to discuss values and worries about treatment and receive advice to decide about continuing treatment. PMID:22869759

Priorities in national space strategies and governance of the member states of the European Space Agency

NASA Astrophysics Data System (ADS)

Adriaensen, Maarten; Giannopapa, Christina; Sagath, Daniel; Papastefanou, Anastasia

2015-12-01

The European Space Agency (ESA) has twenty Member States with a variety of strategic priorities and governance structures regarding their space activities. A number of countries engage in space activities exclusively though ESA, while others have also their own national space programme. Some consider ESA as their prime space agency and others have additionally their own national agency with respective programmes. The main objective of this paper is to provide an up-to date overview and a holistic assessment of strategic priorities and the national space governance structures in 20 ESA Member States. This analysis and assessment has been conducted by analysing the Member States public documents, information provided at ESA workshop on this topic and though unstructured interviews. The paper is structured to include two main elements: priorities and trends in national space strategies and space governance in ESA Member States. The first part of this paper focuses on the content and analysis of the national space strategies and indicates the main priorities and trends in Member States. The priorities are categorised with regards to technology domains, the role of space in the areas of sustainability and the motivators that boost engagement in space. These vary from one Member State to another and include with different levels of engagement in technology domains amongst others: science and exploration, navigation, Earth observation, human space flight, launchers, telecommunications, and integrated applications. Member States allocate a different role of space as enabling tool adding to the advancement of sustainability areas including: security, resources, environment and climate change, transport and communication, energy, and knowledge and education. The motivators motivating reasoning which enhances or hinders space engagement also differs. The motivators identified are industrial competitiveness, job creation, technology development and transfer, social benefits, international cooperation, and European non-dependence. The second part of the paper provides a categorisation of national space governance structures in ESA Member States. Different governance models are identified depending on the responsible ministries for space for a number of space related organisations and ESA. In the case of ESA, these can typically vary from the more traditional ministry of science and/or education, the ministry of industry and/or innovation to the more recent ones being the ministry of economy and the ministry of transport. Recognising the transverse nature of space and its potential as a tool for a number of policies like agriculture, environment, maritime, disaster management, etc., other ministries are more and more getting involved in space activities. The development and implementation of the space strategy and policy of a Member State is realised though the engagement of an implementing entity. The type, role and activity vary from Member State to Member State.

Bridging glycated hemoglobin with quality of life and health state; a randomized case-control study among type 2 diabetes patients.

PubMed

Gillani, Syed Wasif; Ansari, Irfan Altaf; Zaghloul, Hisham A; Abdul, Mohi Iqbal Mohammad; Sulaiman, Syed Azhar Syed; Baig, Mirza R

2018-01-01

The aim of this study was to explore the predictors of QOL and health state and examine the relationship with glycemic control among type 2 diabetes mellitus (T2DM) patients. A randomized cross-sectional case-control study was conducted among n = 600 T2DM patients of Malaysia. Study population was distributed into three groups as: controls: patients with HbA1c ≤ 7 (n = 199), cases arm 1: with HbA1c 7-7.9 (n = 204) and cases arm 2 (n = 197): with HbA1c ≥ 8 consecutively last 3 times. Participants with diabetes history > 10 years exhibits higher mean QOL score among all the three groups. In contrast mean health status score significantly ( p  < 0.001) reduced with the exposure duration of diabetes both within and intergroup assessment that participants with poor glycemic control (arm 2) had significantly higher mean QOL score with knowledge and self-care dimensions as compared to others, however mean health state scores were significantly ( p  < 0.001) lower in all assessment dimensions as compared to controls. The F test of significance showed that demographic and clinical parameters were strong predictors of QOL, whereas self-care activities, comorbidities, ability of positive management and BMI were significant predictors to health state for consistent glycemic control (controls) as compared to poor glycemic control (arm 2) participants. This study suggested that poor glycemic index reported low self-care behavior, increase barriers to daily living activities and poor ability to manage diabetes positively, which cause poor QOL and decrease health state.

Space sickness predictors suggest fluid shift involvement and possible countermeasures

NASA Technical Reports Server (NTRS)

Simanonok, K. E.; Moseley, E. C.; Charles, J. B.

1992-01-01

Preflight data from 64 first time Shuttle crew members were examined retrospectively to predict space sickness severity (NONE, MILD, MODERATE, or SEVERE) by discriminant analysis. From 9 input variables relating to fluid, electrolyte, and cardiovascular status, 8 variables were chosen by discriminant analysis that correctly predicted space sickness severity with 59 pct. success by one method of cross validation on the original sample and 67 pct. by another method. The 8 variables in order of their importance for predicting space sickness severity are sitting systolic blood pressure, serum uric acid, calculated blood volume, serum phosphate, urine osmolality, environmental temperature at the launch site, red cell count, and serum chloride. These results suggest the presence of predisposing physiologic factors to space sickness that implicate a fluid shift etiology. Addition of a 10th input variable, hours spent in the Weightless Environment Training Facility (WETF), improved the prediction of space sickness severity to 66 pct. success by the first method of cross validation on the original sample and to 71 pct. by the second method. The data suggest that WETF training may reduce space sickness severity.

Factors affecting female space use in ten populations of prairie chickens

USGS Publications Warehouse

Winder, Virginia L.; Carrlson, Kaylan M.; Gregory, Andrew J.; Hagen, Christian A.; Haukos, David A.; Kesler, Dylan C.; Larsson, Lena C.; Matthews, Ty W.; McNew, Lance B.; Patten, Michael; Pitman, Jim C.; Powell, Larkin A.; Smith, Jennifer A.; Thompson, Tom; Wolfe, Donald H.; Sandercock, Brett K.

2015-01-01

Conservation of wildlife depends on an understanding of the interactions between animal movements and key landscape factors. Habitat requirements of wide-ranging species often vary spatially, but quantitative assessment of variation among replicated studies at multiple sites is rare. We investigated patterns of space use for 10 populations of two closely related species of prairie grouse: Greater Prairie-Chickens (Tympanuchus cupido) and Lesser Prairie-Chickens (T. pallidicinctus). Prairie chickens require large, intact tracts of native grasslands, and are umbrella species for conservation of prairie ecosystems in North America. We used resource utilization functions to investigate space use by female prairie chickens during the 6-month breeding season from March through August in relation to lek sites, habitat conditions, and anthropogenic development. Our analysis included data from 382 radio-marked individuals across a major portion of the extant range. Our project is a unique opportunity to study comparative space use of prairie chickens, and we employed standardized methods that facilitated direct comparisons across an ecological gradient of study sites. Median home range size of females varied ~10-fold across 10 sites (3.6–36.7 km2), and home ranges tended to be larger at sites with higher annual precipitation. Proximity to lek sites was a strong and consistent predictor of space use for female prairie chickens at all 10 sites. The relative importance of other predictors of space use varied among sites, indicating that generalized habitat management guidelines may not be appropriate for these two species. Prairie chickens actively selected for prairie habitats, even at sites where ~90% of the land cover within the study area was prairie. A majority of the females monitored in our study (>95%) had activity centers within 5 km of leks, suggesting that conservation efforts can be effectively concentrated near active lek sites. Our data on female space use suggest that lek surveys of male prairie chickens can indirectly assess habitat suitability for females during the breeding season. Lek monitoring and surveys for new leks provide information on population trends, but can also guide management actions aimed at improving nesting and brood-rearing habitats.

14 CFR § 1217.106 - Articles brought into the United States by NASA from space.

Code of Federal Regulations, 2014 CFR

2014-01-01

... NASA from space. § 1217.106 Section § 1217.106 Aeronautics and Space NATIONAL AERONAUTICS AND SPACE ADMINISTRATION DUTY-FREE ENTRY OF SPACE ARTICLES § 1217.106 Articles brought into the United States by NASA from... territory of the United States by NASA from space shall not be considered an importation, and no...

Space strategy and governance of ESA small member states

NASA Astrophysics Data System (ADS)

Sagath, Daniel; Papadimitriou, Angeliki; Adriaensen, Maarten; Giannopapa, Christina

2018-01-01

The European Space Agency (ESA) has twenty-two Member States with a variety of governance structures and strategic priorities regarding their space activities. The objective of this paper is to provide an up-to date overview and a holistic assessment of the national space governance structures and strategic priorities of the eleven smaller Member States (based on annual ESA contributions). A link is made between the governance structure and the main strategic objectives. The specific needs and interests of small and new Member States in the frame of European Space Integration are addressed. The first part of the paper focuses on the national space governance structures in the eleven smaller ESA Member States. The governance models of these Member States are identified including the responsible ministries and the entities entrusted with the implementation of space strategy/policy and programmes of the country. The second part of this paper focuses on the content and analysis of the national space strategies and indicates the main priorities and trends in the eleven smaller ESA Member States. The priorities are categorised with regards to technology domains, the role of space in the areas of sustainability and the motivators for space investments. In a third and final part, attention is given to the specific needs and interests of the smaller Member States in the frame of European space integration. ESA instruments are tailored to facilitate the needs and interests of the eleven smaller and/or new Member States.

Arc-Length Continuation and Multi-Grid Techniques for Nonlinear Elliptic Eigenvalue Problems,

DTIC Science & Technology

1981-03-19

size of the finest grid. We use the (AM) adaptive version of the Cycle C algorithm , unless otherwise stated. The first modified algorithm is the...by computing the derivative, uk, at a known solution and use it to get a better initial guess for the next value of X in a predictor - corrector fashion...factorization of the Jacobian Gu computed already in the Newton step. Using such a predictor - corrector method will often allow us to take a much bigger step

Explicit finite difference predictor and convex corrector with applications to hyperbolic partial differential equations

NASA Technical Reports Server (NTRS)

Dey, C.; Dey, S. K.

1983-01-01

An explicit finite difference scheme consisting of a predictor and a corrector has been developed and applied to solve some hyperbolic partial differential equations (PDEs). The corrector is a convex-type function which is applied at each time level and at each mesh point. It consists of a parameter which may be estimated such that for larger time steps the algorithm should remain stable and generate a fast speed of convergence to the steady-state solution. Some examples have been given.

Early Predictors of Lumbar Spine Surgery after Occupational Back Injury: Results from a Prospective Study of Workers in Washington State

PubMed Central

Keeney, Benjamin J.; Fulton-Kehoe, Deborah; Turner, Judith A.; Wickizer, Thomas M.; Chan, Kwun Chuen Gary; Franklin, Gary M.

2014-01-01

Study Design Prospective population-based cohort study Objective To identify early predictors of lumbar spine surgery within 3 years after occupational back injury Summary of Background Data Back injuries are the most prevalent occupational injury in the United States. Little is known about predictors of lumbar spine surgery following occupational back injury. Methods Using Disability Risk Identification Study Cohort (D-RISC) data, we examined the early predictors of lumbar spine surgery within 3 years among Washington State workers with new worker’s compensation temporary total disability claims for back injuries. Baseline measures included worker-reported measures obtained approximately 3 weeks after claim submission. We used medical bill data to determine whether participants underwent surgery, covered by the claim, within 3 years. Baseline predictors (P < 0.10) of surgery in bivariate analyses were included in a multivariate logistic regression model predicting lumbar spine surgery. The model’s area under the receiver operating characteristic curve (AUC) was used to determine the model’s ability to identify correctly workers who underwent surgery. Results In the D-RISC sample of 1,885 workers, 174 (9.2%) had a lumbar spine surgery within 3 years. Baseline variables associated with surgery (P < 0.05) in the multivariate model included higher Roland Disability Questionnaire scores, greater injury severity, and surgeon as first provider seen for the injury. Reduced odds of surgery were observed for those under age 35, women, Hispanics, and those whose first provider was a chiropractor. 42.7% of workers who first saw a surgeon had surgery, in contrast to only 1.5% of those who saw a chiropractor. The multivariate model’s AUC was 0.93 (95% CI 0.92–0.95), indicating excellent ability to discriminate between workers who would versus would not have surgery. Conclusion Baseline variables in multiple domains predicted lumbar spine surgery. There was a very strong association between surgery and first provider seen for the injury, even after adjustment for other important variables. PMID:23238486

Early predictors of lumbar spine surgery after occupational back injury: results from a prospective study of workers in Washington State.

PubMed

Keeney, Benjamin J; Fulton-Kehoe, Deborah; Turner, Judith A; Wickizer, Thomas M; Chan, Kwun Chuen Gary; Franklin, Gary M

2013-05-15

Prospective population-based cohort study. To identify early predictors of lumbar spine surgery within 3 years after occupational back injury. Back injuries are the most prevalent occupational injury in the United States. Few prospective studies have examined early predictors of spine surgery after work-related back injury. Using Disability Risk Identification Study Cohort (D-RISC) data, we examined the early predictors of lumbar spine surgery within 3 years among Washington State workers, with new workers compensation temporary total disability claims for back injuries. Baseline measures included worker-reported measures obtained approximately 3 weeks after claim submission. We used medical bill data to determine whether participants underwent surgery, covered by the claim, within 3 years. Baseline predictors (P < 0.10) of surgery in bivariate analyses were included in a multivariate logistic regression model predicting lumbar spine surgery. The area under the receiver operating characteristic curve of the model was used to determine the model's ability to identify correctly workers who underwent surgery. In the D-RISC sample of 1885 workers, 174 (9.2%) had a lumbar spine surgery within 3 years. Baseline variables associated with surgery (P < 0.05) in the multivariate model included higher Roland-Morris Disability Questionnaire scores, greater injury severity, and surgeon as first provider seen for the injury. Reduced odds of surgery were observed for those younger than 35 years, females, Hispanics, and those whose first provider was a chiropractor. Approximately 42.7% of workers who first saw a surgeon had surgery, in contrast to only 1.5% of those who saw a chiropractor. The area under the receiver operating characteristic curve of the multivariate model was 0.93 (95% confidence interval, 0.92-0.95), indicating excellent ability to discriminate between workers who would versus would not have surgery. Baseline variables in multiple domains predicted lumbar spine surgery. There was a very strong association between surgery and first provider seen for the injury even after adjustment for other important variables.

The Relationship Between Structural Racism and Black-White Disparities in Fatal Police Shootings at the State Level.

PubMed

Mesic, Aldina; Franklin, Lydia; Cansever, Alev; Potter, Fiona; Sharma, Anika; Knopov, Anita; Siegel, Michael

2018-04-01

The objective of this study was to discern the relationship between state-level structural racism and Black-White disparities in police shootings of victims not known to be armed. Using a Poisson regression, we evaluated the effect of structural racism on differences between states in Black-White disparities in fatal police shootings involving victims not known to be armed during the period from January 1, 2013 through June 30, 2017. We created a state racism index, which was comprised of five dimensions: (1) residential segregation; and gaps in (2) incarceration rates; (3) educational attainment; (4) economic indicators; and (5) employment status. After controlling for numerous state-level factors and for the underlying rate of fatal shootings of black victims in each state, the state racism index was a significant predictor of the Black-White disparity in police shooting rates of victims not known to be armed (incidence rate ratio: 1.24; 95% confidence interval, 1.02-1.50). For every 10-point increase in the state racism index, the Black-White disparity ratio of police shooting rates of people not known to be armed increased by 24%. These findings suggest that structural racism is an important predictor of the Black-White disparity in rates of police shootings of unarmed victims across states. Copyright © 2018 National Medical Association. Published by Elsevier Inc. All rights reserved.

Real-time prediction of respiratory motion based on a local dynamic model in an augmented space

NASA Astrophysics Data System (ADS)

Hong, S.-M.; Jung, B.-H.; Ruan, D.

2011-03-01

Motion-adaptive radiotherapy aims to deliver ablative radiation dose to the tumor target with minimal normal tissue exposure, by accounting for real-time target movement. In practice, prediction is usually necessary to compensate for system latency induced by measurement, communication and control. This work focuses on predicting respiratory motion, which is most dominant for thoracic and abdominal tumors. We develop and investigate the use of a local dynamic model in an augmented space, motivated by the observation that respiratory movement exhibits a locally circular pattern in a plane augmented with a delayed axis. By including the angular velocity as part of the system state, the proposed dynamic model effectively captures the natural evolution of respiratory motion. The first-order extended Kalman filter is used to propagate and update the state estimate. The target location is predicted by evaluating the local dynamic model equations at the required prediction length. This method is complementary to existing work in that (1) the local circular motion model characterizes 'turning', overcoming the limitation of linear motion models; (2) it uses a natural state representation including the local angular velocity and updates the state estimate systematically, offering explicit physical interpretations; (3) it relies on a parametric model and is much less data-satiate than the typical adaptive semiparametric or nonparametric method. We tested the performance of the proposed method with ten RPM traces, using the normalized root mean squared difference between the predicted value and the retrospective observation as the error metric. Its performance was compared with predictors based on the linear model, the interacting multiple linear models and the kernel density estimator for various combinations of prediction lengths and observation rates. The local dynamic model based approach provides the best performance for short to medium prediction lengths under relatively low observation rate. Sensitivity analysis indicates its robustness toward the choice of parameters. Its simplicity, robustness and low computation cost makes the proposed local dynamic model an attractive tool for real-time prediction with system latencies below 0.4 s.

Real-time prediction of respiratory motion based on a local dynamic model in an augmented space.

PubMed

Hong, S-M; Jung, B-H; Ruan, D

2011-03-21

Motion-adaptive radiotherapy aims to deliver ablative radiation dose to the tumor target with minimal normal tissue exposure, by accounting for real-time target movement. In practice, prediction is usually necessary to compensate for system latency induced by measurement, communication and control. This work focuses on predicting respiratory motion, which is most dominant for thoracic and abdominal tumors. We develop and investigate the use of a local dynamic model in an augmented space, motivated by the observation that respiratory movement exhibits a locally circular pattern in a plane augmented with a delayed axis. By including the angular velocity as part of the system state, the proposed dynamic model effectively captures the natural evolution of respiratory motion. The first-order extended Kalman filter is used to propagate and update the state estimate. The target location is predicted by evaluating the local dynamic model equations at the required prediction length. This method is complementary to existing work in that (1) the local circular motion model characterizes 'turning', overcoming the limitation of linear motion models; (2) it uses a natural state representation including the local angular velocity and updates the state estimate systematically, offering explicit physical interpretations; (3) it relies on a parametric model and is much less data-satiate than the typical adaptive semiparametric or nonparametric method. We tested the performance of the proposed method with ten RPM traces, using the normalized root mean squared difference between the predicted value and the retrospective observation as the error metric. Its performance was compared with predictors based on the linear model, the interacting multiple linear models and the kernel density estimator for various combinations of prediction lengths and observation rates. The local dynamic model based approach provides the best performance for short to medium prediction lengths under relatively low observation rate. Sensitivity analysis indicates its robustness toward the choice of parameters. Its simplicity, robustness and low computation cost makes the proposed local dynamic model an attractive tool for real-time prediction with system latencies below 0.4 s.

Predictors of success for Saudi Arabian students enrolled in an accelerated baccalaureate degree program in nursing in the United States.

PubMed

Carty, Rita M; Moss, Margaret M; Al-Zayyer, Wael; Kowitlawakul, Yanika; Arietti, Lesley

2007-01-01

In the mid 1980s, a professional nursing education program was initiated between the Kingdom of Saudi Arabia and the United States. Based on a perceived and documented need, a collaborative education and research program was established with George Mason University in Fairfax, Virginia, to begin building a community of new scholars to assist in the advancement of professional nursing in the Kingdom of Saudi Arabia. Four cohorts of Saudi citizens from three institutions (King Faisal Specialist Hospital and Research Center, Saudi Arabia National Guard Hospital, and Ministry of Aviation and Defense Hospital), who held a degree in science or a related field, were enrolled in an accelerated baccalaureate program leading to a bachelor of science in nursing degree. This project was funded by Saudi Arabian sources. A descriptive research study was conducted to identify predictors of success in the program. Results indicated a rate of program completion that was higher than expected. Some of the first graduates went on for a doctor of philosophy degree, but not all enrolled completed the program. Many countries around the world are seeking ways to upgrade and increase the supply of qualified nurses within their own borders. This study identified those factors that were predictors of success for Saudi Arabian students who completed a baccalaureate degree in nursing program in the United States.

Gravitons as Embroidery on the Weave

NASA Astrophysics Data System (ADS)

Iwasaki, Junichi; Rovelli, Carlo

We investigate the physical interpretation of the loop states that appear in the loop representation of quantum gravity. By utilizing the “weave” state, which has been recently introduced as a quantum description of the microstructure of flat space, we analyze the relation between loop states and graviton states. This relation determines a linear map M from the state-space of the nonperturbative theory (loop space) into the state-space of the linearized theory (Fock space). We present an explicit form of this map, and a preliminary investigation of its properties. The existence of such a map indicates that the full nonperturbative quantum theory includes a sector that describes the same physics as (the low energy regimes of) the linearized theory, namely gravitons on flat space.

Temporal BYY encoding, Markovian state spaces, and space dimension determination.

PubMed

Xu, Lei

2004-09-01

As a complementary to those temporal coding approaches of the current major stream, this paper aims at the Markovian state space temporal models from the perspective of the temporal Bayesian Ying-Yang (BYY) learning with both new insights and new results on not only the discrete state featured Hidden Markov model and extensions but also the continuous state featured linear state spaces and extensions, especially with a new learning mechanism that makes selection of the state number or the dimension of state space either automatically during adaptive learning or subsequently after learning via model selection criteria obtained from this mechanism. Experiments are demonstrated to show how the proposed approach works.

Ensemble Cannonical Correlation Prediction of Seasonal Precipitation Over the US

NASA Technical Reports Server (NTRS)

Lau, William K. M.; Kim, Kyu-Myong; Shen, Samuel; Einaudi, Franco (Technical Monitor)

2001-01-01

This paper presents preliminary results of an ensemble cannonical correlation (ECC) prediction scheme developed at the Climate and Radiation Branch, NASA/Goddard Space Flight Center for determining the potential predictability of regional precipitation, and for climate downscaling studies. The scheme is tested on seasonal hindcasts of anomalous precipitation over the continental United States using global sea surface temperature (SST) for 1951-2000. To maximize the forecast skill derived from SST, the world ocean is divided into nonoverlapping sectors. The cannonical SST modes for each sector are used as the predictor for the ensemble hindcasts. Results show that the ECC yields a substantial (10-25%) increase in prediction skills for all regions of the US and for all seasonal compared to traditional CCA prediction schemes. For the boreal winter, the tropical Pacific contributes the largest potential predictability to precipitation in the southwestern and southeastern regions, while the North Pacific and the North Atlantic are responsible for enhanced forecast skills in the Pacific Northwest, the northern Great Plains and Ohio Valley. Most importantly, the ECC increases skill for summertime precipitation prediction and substantially reduced the spring predictability barrier over all regions of the US continent. Besides SST, the ECC is designed with the flexibility to include any number of predictor fields, such as soil moisture, snow cover and regional regional data. Moreover, the ECC forecasts can be applied to other climate subsystems and, in conjunction with further diagnostic or model studies will enables a better understanding of the dynamic links between climate variations and precipitation, not only for the US, but also for other regions of the world.

Path Dependency and the Politics of Socialized Health Care.

PubMed

Brady, David; Marquardt, Susanne; Gauchat, Gordon; Reynolds, Megan M

2016-06-01

Rich democracies exhibit vast cross-national and historical variation in the socialization of health care. Yet, cross-national analyses remain relatively rare in the health policy literature, and health care remains relatively neglected in the welfare state literature. We analyze pooled time series models of the public share of total health spending for eighteen rich democracies from 1960 to 2010. Building on path dependency theory, we present a strategy for modeling the relationship between the initial 1960 public share and the current public share. We also examine two contrasting accounts for how the 1960 public share interacts with conventional welfare state predictors: the self-reinforcing hypothesis expecting positive feedbacks and the counteracting hypothesis expecting negative feedbacks. We demonstrate that most of the variation from 1960 to 2010 in the public share can be explained by a country's initial value in 1960. This 1960 value has a large significant effect in models of 1961-2010, and including the 1960 value alters the coefficients of conventional welfare state predictors. To investigate the mechanism whereby prior social policy influences public opinion about current social policy, we use the 2006 International Social Survey Programme (ISSP). This analysis confirms that the 1960 values predict individual preferences for government spending on health. Returning to the pooled time series, we demonstrate that the 1960 values interact significantly with several conventional welfare state predictors. Some interactions support the self-reinforcing hypothesis, while others support the counteracting hypothesis. Ultimately, this study illustrates how historical legacies of social policy exert substantial influence on the subsequent politics of social policy. Copyright © 2016 by Duke University Press.

Evaluating a Space-Based Indicator of Surface Ozone-NOx-VOC Sensitivity Over Midlatitude Source Regions and Application to Decadal Trends

NASA Astrophysics Data System (ADS)

Jin, Xiaomeng; Fiore, Arlene M.; Murray, Lee T.; Valin, Lukas C.; Lamsal, Lok N.; Duncan, Bryan; Folkert Boersma, K.; De Smedt, Isabelle; Abad, Gonzalo Gonzalez; Chance, Kelly; Tonnesen, Gail S.

2017-10-01

Determining effective strategies for mitigating surface ozone (O3) pollution requires knowledge of the relative ambient concentrations of its precursors, NOx, and VOCs. The space-based tropospheric column ratio of formaldehyde to NO2 (FNR) has been used as an indicator to identify NOx-limited versus NOx-saturated O3 formation regimes. Quantitative use of this indicator ratio is subject to three major uncertainties: (1) the split between NOx-limited and NOx-saturated conditions may shift in space and time, (2) the ratio of the vertically integrated column may not represent the near-surface environment, and (3) satellite products contain errors. We use the GEOS-Chem global chemical transport model to evaluate the quantitative utility of FNR observed from the Ozone Monitoring Instrument over three northern midlatitude source regions. We find that FNR in the model surface layer is a robust predictor of the simulated near-surface O3 production regime. Extending this surface-based predictor to a column-based FNR requires accounting for differences in the HCHO and NO2 vertical profiles. We compare four combinations of two OMI HCHO and NO2 retrievals with modeled FNR. The spatial and temporal correlations between the modeled and satellite-derived FNR vary with the choice of NO2 product, while the mean offset depends on the choice of HCHO product. Space-based FNR indicates that the spring transition to NOx-limited regimes has shifted at least a month earlier over major cities (e.g., New York, London, and Seoul) between 2005 and 2015. This increase in NOx sensitivity implies that NOx emission controls will improve O3 air quality more now than it would have a decade ago.

Evaluating a Space-Based Indicator of Surface Ozone-NO x -VOC Sensitivity Over Midlatitude Source Regions and Application to Decadal Trends.

PubMed

Jin, Xiaomeng; Fiore, Arlene M; Murray, Lee T; Valin, Lukas C; Lamsal, Lok N; Duncan, Bryan; Boersma, K Folkert; De Smedt, Isabelle; Abad, Gonzalo Gonzalez; Chance, Kelly; Tonnesen, Gail S

2017-10-16

Determining effective strategies for mitigating surface ozone (O 3 ) pollution requires knowledge of the relative ambient concentrations of its precursors, NO x , and VOCs. The space-based tropospheric column ratio of formaldehyde to NO 2 (FNR) has been used as an indicator to identify NO x -limited versus NO x -saturated O 3 formation regimes. Quantitative use of this indicator ratio is subject to three major uncertainties: (1) the split between NO x -limited and NO x -saturated conditions may shift in space and time, (2) the ratio of the vertically integrated column may not represent the near-surface environment, and (3) satellite products contain errors. We use the GEOS-Chem global chemical transport model to evaluate the quantitative utility of FNR observed from the Ozone Monitoring Instrument over three northern midlatitude source regions. We find that FNR in the model surface layer is a robust predictor of the simulated near-surface O 3 production regime. Extending this surface-based predictor to a column-based FNR requires accounting for differences in the HCHO and NO 2 vertical profiles. We compare four combinations of two OMI HCHO and NO 2 retrievals with modeled FNR. The spatial and temporal correlations between the modeled and satellite-derived FNR vary with the choice of NO 2 product, while the mean offset depends on the choice of HCHO product. Space-based FNR indicates that the spring transition to NO x -limited regimes has shifted at least a month earlier over major cities (e.g., New York, London, and Seoul) between 2005 and 2015. This increase in NO x sensitivity implies that NO x emission controls will improve O 3 air quality more now than it would have a decade ago.

Time diary and questionnaire assessment of factors associated with academic and personal success among university undergraduates.

PubMed

George, Darren; Dixon, Sinikka; Stansal, Emory; Gelb, Shannon Lund; Pheri, Tabitha

2008-01-01

A sample of 231 students attending a private liberal arts university in central Alberta, Canada, completed a 5-day time diary and a 71-item questionnaire assessing the influence of personal, cognitive, and attitudinal factors on success. The authors used 3 success measures: cumulative grade point average (GPA), Personal Success--each participant's rating of congruence between stated goals and progress toward those goals--and Total Success--a measure that weighted GPA and Personal Success equally. The greatest predictors of GPA were time-management skills, intelligence, time spent studying, computer ownership, less time spent in passive leisure, and a healthy diet. Predictors of Personal Success scores were clearly defined goals, overall health, personal spirituality, and time-management skills. Predictors of Total Success scores were clearly defined goals, time-management skills, less time spent in passive leisure, healthy diet, waking up early, computer ownership, and less time spent sleeping. Results suggest alternatives to traditional predictors of academic success.

Predicting driving performance in older adults: we are not there yet!

PubMed

Bédard, Michel; Weaver, Bruce; Darzins, Peteris; Porter, Michelle M

2008-08-01

We set up this study to determine the predictive value of approaches for which a statistical association with driving performance has been documented. We determined the statistical association (magnitude of association and probability of occurrence by chance alone) between four different predictors (the Mini-Mental State Examination, Trails A test, Useful Field of View [UFOV], and a composite measure of past driving incidents) and driving performance. We then explored the predictive value of these measures with receiver operating characteristic (ROC) curves and various cutoff values. We identified associations between the predictors and driving performance well beyond the play of chance (p < .01). Nonetheless, the predictors had limited predictive value with areas under the curve ranging from .51 to .82. Statistical associations are not sufficient to infer adequate predictive value, especially when crucial decisions such as whether one can continue driving are at stake. The predictors we examined have limited predictive value if used as stand-alone screening tests.

A Longitudinal Study of Work After Retirement: Examining Predictors of Bridge Employment, Continued Career Employment, and Retirement.

PubMed

Bennett, Misty M; Beehr, Terry A; Lepisto, Lawrence R

2016-09-01

Older employees are increasingly accepting bridge employment, which occurs when older workers take employment for pay after they retire from their main career. This study examined predictors of workers' decisions to engage in bridge employment versus full retirement and career employment. A national sample of 482 older people in the United States was surveyed regarding various work-related and nonwork related predictors of retirement decisions, and their retirement status was measured 5 years later. In bivariate analyses, both work-related variables (career goal achievement and experienced pressure to retire) and nonwork-related variables (psychological distress and traditional gender role orientation) predicted taking bridge employment, but in multinomial logistic regression, only nonwork variables had unique effects. Few predictors differentiated the bridge employed and fully retired groups. Nonwork variables were salient in making the decision to retire, and bridge employment may be conceptually more similar to full retirement than to career employment. © The Author(s) 2016.

Personality Traits and Socio-Demographic Variables as Correlates of Counselling Effectiveness of Counsellors in Enugu State, Nigeria

ERIC Educational Resources Information Center

Onyekuru, Bruno U.; Ibegbunam, Josephat

2015-01-01

Quality personality traits and socio-demographic variables are essential elements of effective counselling. This correlational study investigated personality traits and socio-demographic variables as predictors of counselling effectiveness of counsellors in Enugu State. The instruments for data collection were Personality Traits Assessment Scale…

Mood States as Predictors of Characteristics and Precipitants of Suicidality among College Students

ERIC Educational Resources Information Center

Hess, Elaine A.; Becker, Martin A.; Pituch, Keenan A.; Saathoff, Andrea K.

2011-01-01

This article examines college students' self-reported mood states during a suicidal crisis and the relationship between mood and indicators of suicidality. Multilevel modeling demonstrated that the moods of hopelessness and anger predicted stronger intent; anxiety/worry predicted weaker thoughts of suicide; hopelessness increased the odds of…

Assessment and Mapping of Forest Parcel Sizes

Treesearch

Brett J. Butler; Susan L. King

2005-01-01

A method for analyzing and mapping forest parcel sizes in the Northeastern United States is presented. A decision tree model was created that predicts forest parcel size from spatially explicit predictor variables: population density, State, percentage forest land cover, and road density. The model correctly predicted parcel size for 60 percent of the observations in a...

Estimating Cause: Teacher Turnover and School Effectiveness in Michigan

ERIC Educational Resources Information Center

Keesler, Venessa; Schneider, Barbara

2010-01-01

The purpose of this paper is investigate issues related to within-school teacher supply and school-specific teacher turnover within the state of Michigan using state administrative data on Michigan's teaching force. This paper 1) investigates the key predictors of teacher turnover and mobility, 2) develops a profile of schools that are likely to…

Predictors of Placement Stability at the State Level: The Use of Logistic Regression to Inform Practice

ERIC Educational Resources Information Center

Courtney, Jon R.; Prophet, Retta

2011-01-01

Placement instability is often associated with a number of negative outcomes for children. To gain state level contextual knowledge of factors associated with placement stability/instability, logistic regression was applied to selected variables from the New Mexico Adoption and Foster Care Administrative Reporting System dataset. Predictors…

Predictors of Success on the Prosthetics Certification Examination

ERIC Educational Resources Information Center

Miro, Rebecca Maria

2014-01-01

Students who graduate from a practitioner program in prosthetics & orthotics must achieve certification in order to obtain licensure and practice independently in 16 states. In states where licensure is not mandatory, graduates may choose to pursue certification in order assure patients that they are practicing at the highest level as well as…

Analysis of nystagmus response to a pseudorandom velocity input

NASA Technical Reports Server (NTRS)

Lessard, C. S.

1986-01-01

Space motion sickness was not reported during the first Apollo missions; however, since Apollo 8 through the current Shuttle and Skylab missions, approximately 50% of the crewmembers have experienced instances of space motion sickness. Space motion sickness, renamed space adaptation syndrome, occurs primarily during the initial period of a mission until habilation takes place. One of NASA's efforts to resolve the space adaptation syndrome is to model the individual's vestibular response for basis knowledge and as a possible predictor of an individual's susceptibility to the disorder. This report describes a method to analyse the vestibular system when subjected to a pseudorandom angular velocity input. A sum of sinusoids (pseudorandom) input lends itself to analysis by linear frequency methods. Resultant horizontal ocular movements were digitized, filtered and transformed into the frequency domain. Programs were developed and evaluated to obtain the (1) auto spectra of input stimulus and resultant ocular resonse, (2) cross spectra, (3) the estimated vestibular-ocular system transfer function gain and phase, and (4) coherence function between stimulus and response functions.

Will they stay or will they go? The role of job embeddedness in predicting turnover in individualistic and collectivistic cultures.

PubMed

Ramesh, Anuradha; Gelfand, Michele J

2010-09-01

Although turnover is an issue of global concern, paradoxically there have been few studies of turnover across cultures. We investigated the cross-cultural generalizability of the job embeddedness model (Mitchell & Lee, 2001) by examining turnover in an individualistic country (United States) and a collectivistic country (India). Using cross-cultural data from call centers (N = 797), we demonstrated that although organization job embeddedness predicted turnover in both countries, different dimensions of job embeddedness predicted turnover in the United States and India. As hypothesized, on the basis of individualism-collectivism theory, person-job fit was a significant predictor of lower turnover in the United States, whereas person-organization fit, organization links, and community links were significant predictors of lower turnover in India. We also explored whether a newly developed construct of embeddedness-family embeddedness-predicts turnover above and beyond job embeddedness and found initial support for its utility in both the United States and India. Theoretical and practical implications are discussed. Copyright 2010 APA, all rights reserved

Evaluating physical habitat and water chemistry data from statewide stream monitoring programs to establish least-impacted conditions in Washington State

USGS Publications Warehouse

Wilmoth, Siri K.; Irvine, Kathryn M.; Larson, Chad

2015-01-01

Various GIS-generated land-use predictor variables, physical habitat metrics, and water chemistry variables from 75 reference streams and 351 randomly sampled sites throughout Washington State were evaluated for effectiveness at discriminating reference from random sites within level III ecoregions. A combination of multivariate clustering and ordination techniques were used. We describe average observed conditions for a subset of predictor variables as well as proposing statistical criteria for establishing reference conditions for stream habitat in Washington. Using these criteria, we determined whether any of the random sites met expectations for reference condition and whether any of the established reference sites failed to meet expectations for reference condition. Establishing these criteria will set a benchmark from which future data will be compared.

An evaluation of behavior inferences from Bayesian state-space models: A case study with the Pacific walrus

USGS Publications Warehouse

Beatty, William; Jay, Chadwick V.; Fischbach, Anthony S.

2016-01-01

State-space models offer researchers an objective approach to modeling complex animal location data sets, and state-space model behavior classifications are often assumed to have a link to animal behavior. In this study, we evaluated the behavioral classification accuracy of a Bayesian state-space model in Pacific walruses using Argos satellite tags with sensors to detect animal behavior in real time. We fit a two-state discrete-time continuous-space Bayesian state-space model to data from 306 Pacific walruses tagged in the Chukchi Sea. We matched predicted locations and behaviors from the state-space model (resident, transient behavior) to true animal behavior (foraging, swimming, hauled out) and evaluated classification accuracy with kappa statistics (κ) and root mean square error (RMSE). In addition, we compared biased random bridge utilization distributions generated with resident behavior locations to true foraging behavior locations to evaluate differences in space use patterns. Results indicated that the two-state model fairly classified true animal behavior (0.06 ≤ κ ≤ 0.26, 0.49 ≤ RMSE ≤ 0.59). Kernel overlap metrics indicated utilization distributions generated with resident behavior locations were generally smaller than utilization distributions generated with true foraging behavior locations. Consequently, we encourage researchers to carefully examine parameters and priors associated with behaviors in state-space models, and reconcile these parameters with the study species and its expected behaviors.

Pre-performance Physiological State: Heart Rate Variability as a Predictor of Shooting Performance.

PubMed

Ortega, E; Wang, C J K

2018-03-01

Heart rate variability (HRV) is commonly used in sport science for monitoring the physiology of athletes but not as an indicator of physiological state from a psychological perspective. Since HRV is established to be an indicator of emotional responding, it could be an objective means of quantifying an athlete's subjective physiological state before competition. A total of 61 sport shooters participated in this study, of which 21 were novice shooters, 19 were intermediate shooters, and 21 were advanced level shooters. HRV, self-efficacy, and use of mental skills were assessed before they completed a standard shooting performance task of 40 shots, as in a competition qualifying round. The results showed that HRV was significantly positively correlated with self-efficacy and performance and was a significant predictor of shooting performance. In addition, advanced shooters were found to have significantly lower average heart rate before shooting and used more self-talk, relaxation, imagery, and automaticity compared to novice and intermediate shooters. HRV was found to be useful in identifying the physiological state of an athlete before competing, and as such, coaches and athletes can adopt practical strategies to improve the pre-performance physiological state as a means to optimize performance.

State-space reduction and equivalence class sampling for a molecular self-assembly model.

PubMed

Packwood, Daniel M; Han, Patrick; Hitosugi, Taro

2016-07-01

Direct simulation of a model with a large state space will generate enormous volumes of data, much of which is not relevant to the questions under study. In this paper, we consider a molecular self-assembly model as a typical example of a large state-space model, and present a method for selectively retrieving 'target information' from this model. This method partitions the state space into equivalence classes, as identified by an appropriate equivalence relation. The set of equivalence classes H, which serves as a reduced state space, contains none of the superfluous information of the original model. After construction and characterization of a Markov chain with state space H, the target information is efficiently retrieved via Markov chain Monte Carlo sampling. This approach represents a new breed of simulation techniques which are highly optimized for studying molecular self-assembly and, moreover, serves as a valuable guideline for analysis of other large state-space models.

Predictors of health care provider anticipatory guidance provision for older drivers.

PubMed

Huseth-Zosel, Andrea L; Sanders, Gregory; O'Connor, Melissa

2016-11-16

The objective of this study was to determine the frequency of health care provider (HCP) driving safety/cessation-related anticipatory guidance provision and predictors of driving safety-related anticipatory guidance provision by HCPs. HCPs in several central/upper Midwest states were surveyed about frequency of anticipatory guidance provision (n = 265). More than half of HCPs stated that they frequently or always provide driving safety/cessation-related anticipatory guidance to patients aged 85 or older, 38.7% provided this guidance to patients aged 75 to 84, and 13.7% to patients aged 65 to 74. Predictors of driving safety/cessation-related anticipatory guidance provision differed by patient age. For patients aged 65-74, HCP personal experience with a motor vehicle crash (either the HCP themselves or a friend/family member) was significant in predicting anticipatory guidance provision. However, for patients aged 75 and older, significant predictors included HCP rural practice, HCP age, and percentage of HCP patients who were older adults. HCP counseling provision related to driving issues differs by patient age and several HCP characteristics, including HCP rurality, age, and personal experience with motor vehicle crashes. Because aging results in physical and mental changes that affect driving and can be identified by HCPs, HCPs are in a position to counsel patients on the potential impacts of aging on the act of driving. Future research should examine the reasons for the differences in anticipatory guidance provision found in this study.

Ecology of Vibrio parahaemolyticus and Vibrio vulnificus in the Coastal and Estuarine Waters of Louisiana, Maryland, Mississippi, and Washington (United States)

PubMed Central

Bowers, John C.; Griffitt, Kimberly J.; Molina, Vanessa; Clostio, Rachel W.; Pei, Shaofeng; Laws, Edward; Paranjpye, Rohinee N.; Strom, Mark S.; Chen, Arlene; Hasan, Nur A.; Huq, Anwar; Noriea, Nicholas F.; Grimes, D. Jay; Colwell, Rita R.

2012-01-01

Vibrio parahaemolyticus and Vibrio vulnificus, which are native to estuaries globally, are agents of seafood-borne or wound infections, both potentially fatal. Like all vibrios autochthonous to coastal regions, their abundance varies with changes in environmental parameters. Sea surface temperature (SST), sea surface height (SSH), and chlorophyll have been shown to be predictors of zooplankton and thus factors linked to vibrio populations. The contribution of salinity, conductivity, turbidity, and dissolved organic carbon to the incidence and distribution of Vibrio spp. has also been reported. Here, a multicoastal, 21-month study was conducted to determine relationships between environmental parameters and V. parahaemolyticus and V. vulnificus populations in water, oysters, and sediment in three coastal areas of the United States. Because ecologically unique sites were included in the study, it was possible to analyze individual parameters over wide ranges. Molecular methods were used to detect genes for thermolabile hemolysin (tlh), thermostable direct hemolysin (tdh), and tdh-related hemolysin (trh) as indicators of V. parahaemolyticus and the hemolysin gene vvhA for V. vulnificus. SST and suspended particulate matter were found to be strong predictors of total and potentially pathogenic V. parahaemolyticus and V. vulnificus. Other predictors included chlorophyll a, salinity, and dissolved organic carbon. For the ecologically unique sites included in the study, SST was confirmed as an effective predictor of annual variation in vibrio abundance, with other parameters explaining a portion of the variation not attributable to SST. PMID:22865080

Geometry of matrix product states: Metric, parallel transport, and curvature

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

Haegeman, Jutho, E-mail: jutho.haegeman@gmail.com; Verstraete, Frank; Faculty of Physics and Astronomy, University of Ghent, Krijgslaan 281 S9, 9000 Gent

2014-02-15

We study the geometric properties of the manifold of states described as (uniform) matrix product states. Due to the parameter redundancy in the matrix product state representation, matrix product states have the mathematical structure of a (principal) fiber bundle. The total space or bundle space corresponds to the parameter space, i.e., the space of tensors associated to every physical site. The base manifold is embedded in Hilbert space and can be given the structure of a Kähler manifold by inducing the Hilbert space metric. Our main interest is in the states living in the tangent space to the base manifold,more » which have recently been shown to be interesting in relation to time dependence and elementary excitations. By lifting these tangent vectors to the (tangent space) of the bundle space using a well-chosen prescription (a principal bundle connection), we can define and efficiently compute an inverse metric, and introduce differential geometric concepts such as parallel transport (related to the Levi-Civita connection) and the Riemann curvature tensor.« less

RNA-protein binding motifs mining with a new hybrid deep learning based cross-domain knowledge integration approach.

PubMed

Pan, Xiaoyong; Shen, Hong-Bin

2017-02-28

RNAs play key roles in cells through the interactions with proteins known as the RNA-binding proteins (RBP) and their binding motifs enable crucial understanding of the post-transcriptional regulation of RNAs. How the RBPs correctly recognize the target RNAs and why they bind specific positions is still far from clear. Machine learning-based algorithms are widely acknowledged to be capable of speeding up this process. Although many automatic tools have been developed to predict the RNA-protein binding sites from the rapidly growing multi-resource data, e.g. sequence, structure, their domain specific features and formats have posed significant computational challenges. One of current difficulties is that the cross-source shared common knowledge is at a higher abstraction level beyond the observed data, resulting in a low efficiency of direct integration of observed data across domains. The other difficulty is how to interpret the prediction results. Existing approaches tend to terminate after outputting the potential discrete binding sites on the sequences, but how to assemble them into the meaningful binding motifs is a topic worth of further investigation. In viewing of these challenges, we propose a deep learning-based framework (iDeep) by using a novel hybrid convolutional neural network and deep belief network to predict the RBP interaction sites and motifs on RNAs. This new protocol is featured by transforming the original observed data into a high-level abstraction feature space using multiple layers of learning blocks, where the shared representations across different domains are integrated. To validate our iDeep method, we performed experiments on 31 large-scale CLIP-seq datasets, and our results show that by integrating multiple sources of data, the average AUC can be improved by 8% compared to the best single-source-based predictor; and through cross-domain knowledge integration at an abstraction level, it outperforms the state-of-the-art predictors by 6%. Besides the overall enhanced prediction performance, the convolutional neural network module embedded in iDeep is also able to automatically capture the interpretable binding motifs for RBPs. Large-scale experiments demonstrate that these mined binding motifs agree well with the experimentally verified results, suggesting iDeep is a promising approach in the real-world applications. The iDeep framework not only can achieve promising performance than the state-of-the-art predictors, but also easily capture interpretable binding motifs. iDeep is available at http://www.csbio.sjtu.edu.cn/bioinf/iDeep.

Predictors of nurse manager stress: a dominance analysis of potential work environment stressors.

PubMed

Kath, Lisa M; Stichler, Jaynelle F; Ehrhart, Mark G; Sievers, Andree

2013-11-01

Nurse managers have important but stressful jobs. Clinical or bedside nurse predictors of stress have been studied more frequently, but less has been done on work environment predictors for those in this first-line leadership role. Understanding the relative importance of those work environment predictors could be used to help identify the most fruitful areas for intervention, potentially improving recruitment and retention for nurse managers. Using Role Stress Theory and the Job Demands-Resources Theory, a model was tested examining the relative importance of five potential predictors of nurse manager stress (i.e., stressors). The work environment stressors included role ambiguity, role overload, role conflict, organizational constraints, and interpersonal conflict. A quantitative, cross-sectional survey study was conducted with a convenience sample of 36 hospitals in the Southwestern United States. All nurse managers working in these 36 hospitals were invited to participate. Of the 636 nurse managers invited, 480 responded, for a response rate of 75.5%. Questionnaires were distributed during nursing leadership meetings and were returned in person (in sealed envelopes) or by mail. Because work environment stressors were correlated, dominance analysis was conducted to examine which stressors were the most important predictors of nurse manager stress. Role overload was the most important predictor of stress, with an average of 13% increase in variance explained. The second- and third-most important predictors were organizational constraints and role conflict, with an average of 7% and 6% increase in variance explained, respectively. Because other research has shown deleterious effects of nurse manager stress, organizational leaders are encouraged to help nurse managers reduce their actual and/or perceived role overload and organizational constraints. Copyright © 2013 Elsevier Ltd. All rights reserved.

Context dependent prediction and category encoding for DPCM image compression

NASA Technical Reports Server (NTRS)

Beaudet, Paul R.

1989-01-01

Efficient compression of image data requires the understanding of the noise characteristics of sensors as well as the redundancy expected in imagery. Herein, the techniques of Differential Pulse Code Modulation (DPCM) are reviewed and modified for information-preserving data compression. The modifications include: mapping from intensity to an equal variance space; context dependent one and two dimensional predictors; rationale for nonlinear DPCM encoding based upon an image quality model; context dependent variable length encoding of 2x2 data blocks; and feedback control for constant output rate systems. Examples are presented at compression rates between 1.3 and 2.8 bits per pixel. The need for larger block sizes, 2D context dependent predictors, and the hope for sub-bits-per-pixel compression which maintains spacial resolution (information preserving) are discussed.

Analysis and prediction of aperiodic hydrodynamic oscillatory time series by feed-forward neural networks, fuzzy logic, and a local nonlinear predictor

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

Gentili, Pier Luigi, E-mail: pierluigi.gentili@unipg.it; Gotoda, Hiroshi; Dolnik, Milos

Forecasting of aperiodic time series is a compelling challenge for science. In this work, we analyze aperiodic spectrophotometric data, proportional to the concentrations of two forms of a thermoreversible photochromic spiro-oxazine, that are generated when a cuvette containing a solution of the spiro-oxazine undergoes photoreaction and convection due to localized ultraviolet illumination. We construct the phase space for the system using Takens' theorem and we calculate the Lyapunov exponents and the correlation dimensions to ascertain the chaotic character of the time series. Finally, we predict the time series using three distinct methods: a feed-forward neural network, fuzzy logic, and amore » local nonlinear predictor. We compare the performances of these three methods.« less

Hierarchical Adaptive Regression Kernels for Regression with Functional Predictors.

PubMed

Woodard, Dawn B; Crainiceanu, Ciprian; Ruppert, David

2013-01-01

We propose a new method for regression using a parsimonious and scientifically interpretable representation of functional predictors. Our approach is designed for data that exhibit features such as spikes, dips, and plateaus whose frequency, location, size, and shape varies stochastically across subjects. We propose Bayesian inference of the joint functional and exposure models, and give a method for efficient computation. We contrast our approach with existing state-of-the-art methods for regression with functional predictors, and show that our method is more effective and efficient for data that include features occurring at varying locations. We apply our methodology to a large and complex dataset from the Sleep Heart Health Study, to quantify the association between sleep characteristics and health outcomes. Software and technical appendices are provided in online supplemental materials.

Prevalence and Predictors of Depressive Symptoms in Pregnant African American Women.

PubMed

Jallo, Nancy; Elswick, R K; Kinser, Patricia; Masho, Saba; Price, Sarah Kye; Svikis, Dace S

2015-01-01

African American women may be especially vulnerable to antepartum depression, a major health concern during pregnancy. This study investigated the prevalence and predictors of depressive symptoms in a sample of African American women who were between 14-17 weeks pregnant, a timeframe that is typically thought to be a time of general well-being. Two-thirds reported a CES-D score ≥ 16 indicative of depressive symptomatology. Age, perceived stress (as measured by the Perceived Stress Scale [PSS]), and anxiety (as measured by the State Trait Anxiety Inventory [STAI]) predicted depressive symptoms; the interaction between PSS and STAI scores was also a significant predictor. Our study findings suggest that early identification of stress and anxiety, in addition to depressive symptoms, is vital for intervention with this group.

Predictors of Exceptional Longevity: Effects of Early-Life Childhood Conditions, Midlife Environment and Parental Characteristics.

PubMed

Gavrilov, Leonid A; Gavrilova, Natalia S

Knowledge of strong predictors of mortality and longevity is very important for actuarial science and practice. Earlier studies found that parental characteristics as well as early-life conditions and midlife environment play a significant role in survival to advanced ages. However, little is known about the simultaneous effects of these three factors on longevity. This ongoing study attempts to fill this gap by comparing centenarians born in the United States in 1890-91 with peers born in the same years who died at age 65. The records for centenarians and controls were taken from computerized family histories, which were then linked to 1900 and 1930 U.S. censuses. As a result of this linkage procedure, 765 records of confirmed centenarians and 783 records of controls were obtained. Analysis with multivariate logistic regression found that parental longevity and some midlife characteristics proved to be significant predictors of longevity while the role of childhood conditions was less important. More centenarians were born in the second half of the year compared to controls, suggesting early origins of longevity. We found the existence of both general and gender-specific predictors of human longevity. General predictors common for men and women are paternal and maternal longevity. Gender-specific predictors of male longevity are the farmer occupation at age 40, Northeastern region of birth in the United States and birth in the second half of year. A gender-specific predictor of female longevity is surprisingly the availability of radio in the household according to the 1930 U.S. census. Given the importance of familial longevity as an independent predictor of survival to advanced ages, we conducted a comparative study of biological and nonbiological relatives of centenarians using a larger sample of 1,945 validated U.S. centenarians born in 1880-95. We found that male gender of centenarian has significant positive effect on survival of adult male relatives (brothers and fathers) but not female blood relatives. Life span of centenarian siblings-in-law is lower compared to life span of centenarian siblings and does not depend on centenarian gender. Wives of male centenarians (who share lifestyle and living conditions) have a significantly better survival compared to wives of centenarians' brothers. This finding demonstrates an important role of shared familial environment and lifestyle in human longevity. The results of this study suggest that familial background, early-life conditions and midlife characteristics play an important role in longevity.

Predictors of Exceptional Longevity: Effects of Early-Life Childhood Conditions, Midlife Environment and Parental Characteristics

PubMed Central

Gavrilov, Leonid A.; Gavrilova, Natalia S.

2014-01-01

Knowledge of strong predictors of mortality and longevity is very important for actuarial science and practice. Earlier studies found that parental characteristics as well as early-life conditions and midlife environment play a significant role in survival to advanced ages. However, little is known about the simultaneous effects of these three factors on longevity. This ongoing study attempts to fill this gap by comparing centenarians born in the United States in 1890–91 with peers born in the same years who died at age 65. The records for centenarians and controls were taken from computerized family histories, which were then linked to 1900 and 1930 U.S. censuses. As a result of this linkage procedure, 765 records of confirmed centenarians and 783 records of controls were obtained. Analysis with multivariate logistic regression found that parental longevity and some midlife characteristics proved to be significant predictors of longevity while the role of childhood conditions was less important. More centenarians were born in the second half of the year compared to controls, suggesting early origins of longevity. We found the existence of both general and gender-specific predictors of human longevity. General predictors common for men and women are paternal and maternal longevity. Gender-specific predictors of male longevity are the farmer occupation at age 40, Northeastern region of birth in the United States and birth in the second half of year. A gender-specific predictor of female longevity is surprisingly the availability of radio in the household according to the 1930 U.S. census. Given the importance of familial longevity as an independent predictor of survival to advanced ages, we conducted a comparative study of biological and nonbiological relatives of centenarians using a larger sample of 1,945 validated U.S. centenarians born in 1880–95. We found that male gender of centenarian has significant positive effect on survival of adult male relatives (brothers and fathers) but not female blood relatives. Life span of centenarian siblings-in-law is lower compared to life span of centenarian siblings and does not depend on centenarian gender. Wives of male centenarians (who share lifestyle and living conditions) have a significantly better survival compared to wives of centenarians' brothers. This finding demonstrates an important role of shared familial environment and lifestyle in human longevity. The results of this study suggest that familial background, early-life conditions and midlife characteristics play an important role in longevity. PMID:25664346

A model of head-related transfer functions based on a state-space analysis

NASA Astrophysics Data System (ADS)

Adams, Norman Herkamp

This dissertation develops and validates a novel state-space method for binaural auditory display. Binaural displays seek to immerse a listener in a 3D virtual auditory scene with a pair of headphones. The challenge for any binaural display is to compute the two signals to supply to the headphones. The present work considers a general framework capable of synthesizing a wide variety of auditory scenes. The framework models collections of head-related transfer functions (HRTFs) simultaneously. This framework improves the flexibility of contemporary displays, but it also compounds the steep computational cost of the display. The cost is reduced dramatically by formulating the collection of HRTFs in the state-space and employing order-reduction techniques to design efficient approximants. Order-reduction techniques based on the Hankel-operator are found to yield accurate low-cost approximants. However, the inter-aural time difference (ITD) of the HRTFs degrades the time-domain response of the approximants. Fortunately, this problem can be circumvented by employing a state-space architecture that allows the ITD to be modeled outside of the state-space. Accordingly, three state-space architectures are considered. Overall, a multiple-input, single-output (MISO) architecture yields the best compromise between performance and flexibility. The state-space approximants are evaluated both empirically and psychoacoustically. An array of truncated FIR filters is used as a pragmatic reference system for comparison. For a fixed cost bound, the state-space systems yield lower approximation error than FIR arrays for D>10, where D is the number of directions in the HRTF collection. A series of headphone listening tests are also performed to validate the state-space approach, and to estimate the minimum order N of indiscriminable approximants. For D = 50, the state-space systems yield order thresholds less than half those of the FIR arrays. Depending upon the stimulus uncertainty, a minimum state-space order of 7≤N≤23 appears to be adequate. In conclusion, the proposed state-space method enables a more flexible and immersive binaural display with low computational cost.

Saturation: An efficient iteration strategy for symbolic state-space generation

NASA Technical Reports Server (NTRS)

Ciardo, Gianfranco; Luettgen, Gerald; Siminiceanu, Radu; Bushnell, Dennis M. (Technical Monitor)

2001-01-01

This paper presents a novel algorithm for generating state spaces of asynchronous systems using Multi-valued Decision Diagrams. In contrast to related work, the next-state function of a system is not encoded as a single Boolean function, but as cross-products of integer functions. This permits the application of various iteration strategies to build a system's state space. In particular, this paper introduces a new elegant strategy, called saturation, and implements it in the tool SMART. On top of usually performing several orders of magnitude faster than existing BDD-based state-space generators, the algorithm's required peak memory is often close to the nal memory needed for storing the overall state spaces.

Mental health indicator interaction in predicting substance abuse treatment outcomes in nevada.

PubMed

Greenfield, Lawrence; Wolf-Branigin, Michael

2009-01-01

Indicators of co-occurring mental health and substance abuse problems routinely collected at treatment admission in 19 State substance abuse treatment systems include a dual diagnosis and a State mental health (cognitive impairment) agency referral. These indicators have yet to be compared as predictors of treatment outcomes. 1. Compare both indices as outcomes predictors individually and interactively. 2. Assess relationship of both indices to other client risk factors, e.g., physical/sexual abuse. Client admission and discharge records from the Nevada substance abuse treatment program, spanning 1995-2001 were reviewed (n = 17,591). Logistic regression analyses predicted treatment completion with significant improvement (33%) and treatment readmission following discharge (21%). Using Cox regression, the number of days from discharge to treatment readmission was predicted. Examined as predictors were two mental health indicators and their interaction with other admission and treatment variables controlled. Neither mental health indicator alone significantly predicted any of the three outcomes; however, the interaction between the two indicators significantly predicted each outcome (p < .05). Having both indices was highly associated with physical/sexual abuse, domestic violence, homelessness, out of labor force and prior treatment. Indicator interactions may help improve substance abuse treatment outcomes prediction.

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

Smith, Braeton J.; Shaneyfelt, Calvin R.

A NISAC study on the economic effects of a hypothetical H1N1 pandemic was done in order to assess the differential impacts at the state and industry levels given changes in absenteeism, mortality, and consumer spending rates. Part of the analysis was to determine if there were any direct relationships between pandemic impacts and gross domestic product (GDP) losses. Multiple regression analysis was used because it shows very clearly which predictors are significant in their impact on GDP. GDP impact data taken from the REMI PI+ (Regional Economic Models, Inc., Policy Insight +) model was used to serve as the responsemore » variable. NISAC economists selected the average absenteeism rate, mortality rate, and consumer spending categories as the predictor variables. Two outliers were found in the data: Nevada and Washington, DC. The analysis was done twice, with the outliers removed for the second analysis. The second set of regressions yielded a cleaner model, but for the purposes of this study, the analysts deemed it not as useful because particular interest was placed on determining the differential impacts to states. Hospitals and accommodation were found to be the most important predictors of percentage change in GDP among the consumer spending variables.« less

Exploring resilience in Chinese nurses: a cross-sectional study.

PubMed

Guo, Yu-Fang; Cross, Wendy; Plummer, Virginia; Lam, Louisa; Luo, Yuan-Hui; Zhang, Jing-Ping

2017-04-01

To explore the state of resilience and its predictors among nurses in mainland China. Resilience is considered as an important ability to influence the prevention of job dissatisfaction and burnout. There are few studies on resilience in Chinese nurses, particularly investigating the predictors of resilience. A cross-sectional survey was employed and 1061 nurses from six three-level hospitals in Hunan responded to participate in the study. Data were collected using self-reported questionnaires. Nurses experienced moderate levels of resilience and self-efficacy and tended to use a positive coping style. Multiple linear regression showed that a high level of self-efficacy and education, having a positive coping style rather than a negative coping style, exercising regularly and not using cigarettes predicted a high level of resilience (P < 0.01). This study shows a moderate level of resilience among nurses and suggests that a high level of self-efficacy and education, as well as having a positive coping style and choosing a healthy lifestyle may increase nurses' resilience. Hospital administrators and nursing managers need to explore the resilience state among nurses and understand the predictors of resilience. Then, scientific and evidence-based interventions for improving resilience should be adopted. © 2017 John Wiley & Sons Ltd.

Influence of preoperative emotional state on postoperative pain following orthopedic and trauma surgery.

PubMed

Robleda, Gemma; Sillero-Sillero, Amalia; Puig, Teresa; Gich, Ignasi; Baños, Josep-E

2014-10-01

To analyze the relationship between preoperative emotional state and the prevalence and intensity of postoperative pain and to explore predictors of postoperative pain. Observational retrospective study undertaken among 127 adult patients of orthopedic and trauma surgery. Postoperative pain was assessed with the verbal numeric scale and with five variables of emotional state: anxiety, sweating, stress, fear, and crying. The Chi-squared test, Student's t test or ANOVA and a multivariate logistic regression analysis were used for the statistical analysis. The prevalence of immediate postoperative pain was 28%. Anxiety was the most common emotional factor (72%) and a predictive risk factor for moderate to severe postoperative pain (OR: 4.60, 95% CI 1.38 to 15.3, p<0.05, AUC: 0.72, 95% CI: 0.62 to 0.83). Age exerted a protective effect (OR 0.96, 95% CI: 0.94-0.99, p<0.01). Preoperative anxiety and age are predictors of postoperative pain in patients undergoing orthopedic and trauma surgery.

Resting State and Diffusion Neuroimaging Predictors of Clinical Improvements Following Constraint-Induced Movement Therapy in Children With Hemiplegic Cerebral Palsy.

PubMed

Manning, Kathryn Y; Fehlings, Darcy; Mesterman, Ronit; Gorter, Jan Willem; Switzer, Lauren; Campbell, Craig; Menon, Ravi S

2015-10-01

The aim was to identify neuroimaging predictors of clinical improvements following constraint-induced movement therapy. Resting state functional magnetic resonance and diffusion tensor imaging data was acquired in 7 children with hemiplegic cerebral palsy. Clinical and magnetic resonance imaging (MRI) data were acquired at baseline and 1 month later following a 3-week constraint therapy regimen. A more negative baseline laterality index characterizing an atypical unilateral sensorimotor resting state network significantly correlated with an improvement in the Canadian Occupational Performance Measure score (r = -0.81, P = .03). A more unilateral network with decreased activity in the affected hemisphere was associated with greater improvements in clinical scores. Higher mean diffusivity in the posterior limb of the internal capsule of the affect tract correlated significantly with improvements in the Jebsen-Taylor score (r = -0.83, P = .02). Children with more compromised networks and tracts improved the most following constraint therapy. © The Author(s) 2015.

Predictors of Exceptional Longevity: Effects of Early-Life and Midlife Conditions, and Familial Longevity

PubMed Central

Gavrilov, Leonid A.; Gavrilova, Natalia S.

2015-01-01

Knowledge of strong predictors of mortality and longevity is very important for actuarial science and practice. Earlier studies found that parental characteristics as well as early-life conditions and midlife environment play a significant role in survival to advanced ages. However, little is known about the simultaneous effects of these three factors on longevity. This ongoing study attempts to fill this gap by comparing centenarians born in the United States in 1890–1891 with peers born in the same years who died at age 65. The records for centenarians and controls were taken from computerized family histories, which were then linked to 1900 and 1930 U.S. censuses. As a result of this linkage procedure, 765 records of confirmed centenarians and 783 records of controls were obtained. Analysis with multivariate logistic regression found the existence of both general and gender-specific predictors of human longevity. General predictors common for men and women are paternal and maternal longevity. Gender-specific predictors of male longevity are occupation as a farmer at age 40, Northeastern region of birth in the United States, and birth in the second half of year. A gender-specific predictor of female longevity is the availability of radio in the household according to the 1930 U.S. census. Given the importance of familial longevity as an independent predictor of survival to advanced ages, we conducted a comparative study of biological and nonbiological relatives of centenarians using a larger sample of 1,945 validated U.S. centenarians born in 1880–1895. We found that male gender of centenarian has a significant positive effect on survival of adult male relatives (brothers and fathers) but not female blood relatives. Life span of centenarian siblings-in-law is lower compared to life span of centenarian siblings and does not depend on centenarian gender. Wives of male centenarians (who share lifestyle and living conditions) have a significantly better survival compared to wives of centenarians’ brothers. This finding demonstrates an important role of shared familial environment and lifestyle in human longevity. The results of this study suggest that familial background, some early-life conditions and midlife characteristics play an important role in longevity. PMID:26412963

State-space receptive fields of semicircular canal afferent neurons in the bullfrog

NASA Technical Reports Server (NTRS)

Paulin, M. G.; Hoffman, L. F.

2001-01-01

Receptive fields are commonly used to describe spatial characteristics of sensory neuron responses. They can be extended to characterize temporal or dynamical aspects by mapping neural responses in dynamical state spaces. The state-space receptive field of a neuron is the probability distribution of the dynamical state of the stimulus-generating system conditioned upon the occurrence of a spike. We have computed state-space receptive fields for semicircular canal afferent neurons in the bullfrog (Rana catesbeiana). We recorded spike times during broad-band Gaussian noise rotational velocity stimuli, computed the frequency distribution of head states at spike times, and normalized these to obtain conditional pdfs for the state. These state-space receptive fields quantify what the brain can deduce about the dynamical state of the head when a single spike arrives from the periphery. c2001 Elsevier Science B.V. All rights reserved.

The Modern Space Domain: On the Eve of Weaponization

DTIC Science & Technology

2018-04-09

in space has existed since the opening of the space domain, yet the trend has been for space-faring states to respect the historic norms of a free ...commons and declares all states have free access for the peaceful use of space. It forbids any state from placing weapons of mass destruction (WMD...will remain neutral and free from hostile threat. For the strategist, the logical conclusion is that the US space architecture is a vital national

Adaptive predictors based on probabilistic SVM for real time disruption mitigation on JET

NASA Astrophysics Data System (ADS)

Murari, A.; Lungaroni, M.; Peluso, E.; Gaudio, P.; Vega, J.; Dormido-Canto, S.; Baruzzo, M.; Gelfusa, M.; Contributors, JET

2018-05-01

Detecting disruptions with sufficient anticipation time is essential to undertake any form of remedial strategy, mitigation or avoidance. Traditional predictors based on machine learning techniques can be very performing, if properly optimised, but do not provide a natural estimate of the quality of their outputs and they typically age very quickly. In this paper a new set of tools, based on probabilistic extensions of support vector machines (SVM), are introduced and applied for the first time to JET data. The probabilistic output constitutes a natural qualification of the prediction quality and provides additional flexibility. An adaptive training strategy ‘from scratch’ has also been devised, which allows preserving the performance even when the experimental conditions change significantly. Large JET databases of disruptions, covering entire campaigns and thousands of discharges, have been analysed, both for the case of the graphite and the ITER Like Wall. Performance significantly better than any previous predictor using adaptive training has been achieved, satisfying even the requirements of the next generation of devices. The adaptive approach to the training has also provided unique information about the evolution of the operational space. The fact that the developed tools give the probability of disruption improves the interpretability of the results, provides an estimate of the predictor quality and gives new insights into the physics. Moreover, the probabilistic treatment permits to insert more easily these classifiers into general decision support and control systems.

(3 + 1)-dimensional topological phases and self-dual quantum geometries encoded on Heegaard surfaces

NASA Astrophysics Data System (ADS)

Dittrich, Bianca

2017-05-01

We apply the recently suggested strategy to lift state spaces and operators for (2 + 1)-dimensional topological quantum field theories to state spaces and operators for a (3 + 1)-dimensional TQFT with defects. We start from the (2 + 1)-dimensional TuraevViro theory and obtain a state space, consistent with the state space expected from the Crane-Yetter model with line defects.

Valuation of financial models with non-linear state spaces

NASA Astrophysics Data System (ADS)

Webber, Nick

2001-02-01

A common assumption in valuation models for derivative securities is that the underlying state variables take values in a linear state space. We discuss numerical implementation issues in an interest rate model with a simple non-linear state space, formulating and comparing Monte Carlo, finite difference and lattice numerical solution methods. We conclude that, at least in low dimensional spaces, non-linear interest rate models may be viable.

Sensitivity to Punishment and Explanatory Style as Predictors of Public Speaking State Anxiety. Brief Reports

ERIC Educational Resources Information Center

Kopecky, Courtney; Sawyer, Chris; Behnke, Ralph

2004-01-01

Recent biological theories of state anxiety have focused on temperament and neurophysiology as factors that predispose some people to be particularly at risk of debilitating levels of performance anxiety. The present study extends Gray's (1982; Gray & McNaughton, 2000) reinforcement sensitivity theory by proposing a linkage between sensitivity to…

Bio-Social Variables as Predictors of Teacher Union Leaders' Adherence to Democratic Principles in Ogun State, Nigeria

ERIC Educational Resources Information Center

Fejoh, Johnson

2016-01-01

This study investigated the influence of bio-social variables - educational status, age and family socio-economic background on teacher union leaders' adherence to democratic principles in Ogun State of Nigeria. The study employed the ex-post-facto research design. Five hypotheses were generated and tested using an instrument titled "union…

Variation by Disability in State Predictors of Medicaid 1915C Waiver Use and Expenditures

ERIC Educational Resources Information Center

Miller, Nancy A.; Kitchener, Martin; Elder, Keith T.; Kang, Yu; Rubin, Andrea; Harrington, Charlene

2005-01-01

Purpose: States are increasingly using the Medicaid 1915c waiver program to provide community-based long-term care. A substantially greater share of long-term-care dollars supports community-based care for individuals with intellectual and developmental disabilities, relative to older and working-age persons with primarily physical disabilities.…

Joining the Conversation: Predictors of Success on the United States Medical Licensing Examinations (USMLE)

ERIC Educational Resources Information Center

Gohara, Sabry; Shapiro, Joseph I.; Jacob, Adam N.; Khuder, Sadik A.; Gandy, Robyn A.; Metting, Patricia J.; Gold, Jeffrey; Kleshinski, James; and James Kleshinski

2011-01-01

The purpose of this study was to evaluate whether models based on pre-admission testing, including performance on the Medical College Admission Test (MCAT), performance on required courses in the medical school curriculum, or a combination of both could accurately predict performance of medical students on the United States Medical Licensing…

The Effectiveness of Six Personality Variables in Predicting Success on the Nursing State Board Examination.

ERIC Educational Resources Information Center

Cusick, Patricia; Harckham, Laura D.

A study was conducted to determine whether six personality variables, presently used in admissions decisions by a nursing school, were effective predictors of success on the State Board Examination (SBE), the nursing licensing examination. The personality variables were measured by subtests of the Personal Preference Schedule of the Psychological…

Co-Occurring Severe Mental Illnesses and Substance Abuse Disorders as Predictors of State Prison Inmate Assaults

ERIC Educational Resources Information Center

Wood, Steven R.; Buttaro, Anthony, Jr.

2013-01-01

Using hierarchical logistic regression with a nationally representative sample of state prisoners ("n" = 12,504), we found inmates with dual severe psychiatric and substance abuse disorders to be at higher risk of being assaulted and to assault others in prison than nonmentally ill inmates. Dually disordered inmates may be "importing"…

Forecasting Nursing Student Success and Failure on the NCLEX-RN Using Predictor Tests

ERIC Educational Resources Information Center

Santiago, Lawrence A.

2013-01-01

A severe and worsening nursing shortage exists in the United States. Increasing numbers of new graduate nurses are necessary to meet this demand. To address the concerns of increased nursing demand, leaders of nursing schools must ensure larger numbers of nursing students graduate. Prior to practicing as registered nurses in the United States,…

Are Teachers Prepared? Predictors of Teachers' Readiness to Serve as Mandated Reporters of Child Abuse

ERIC Educational Resources Information Center

Greytak, Emily A.

2009-01-01

The Child Abuse Prevention and Treatment Act (1974) requires that states receiving U.S. federal funds directed at child abuse implement mandated reporting laws. As a result, all states have adopted legislation requiring teachers and other professionals who deal with children to report suspicions of child abuse. The federal mandate for such…

Evaluating the Effectiveness of Various Blast Loading Descriptors as Occupant Injury Predictors for Underbody Blast Events

DTIC Science & Technology

2013-08-22

expressed herein do not necessarily state or reflect those of the United States Government or the DoD, and shall not be used for advertising or...Trembelay, J., “Validation of a Loading Model for Simulating Blast Mine Effects on Armoured Vehicles,” 7th International LS-DYNA Users Conference

Interest, Enjoyment and Pride after Failure Experiences? Predictors of Students' State-Emotions after Success and Failure during Learning in Mathematics

ERIC Educational Resources Information Center

Tulis, Maria; Ainley, Mary

2011-01-01

The current investigation was designed to identify emotion states students experience during mathematics activities, and in particular to distinguish emotions contingent on experiences of success and experiences of failure. Students' task-related emotional responses were recorded following experiences of success and failure while working with an…

Predictors of Postschool Education/Training and Employment Outcomes for Youth with Disabilities

ERIC Educational Resources Information Center

Prince, Angela M. T.; Hodge, Janie; Bridges, William C.; Katsiyannis, Antonis

2018-01-01

Youth with disabilities have consistently poor postschool engagement outcomes in employment and postsecondary education and training. At least once every 6 years, states are required to submit a State Performance Plan in which they report performance on the progress of students with disabilities (20 U.S.C. 1416(b)(1)). Indicator 14 requires states…

The Impact of Socioeconomic Status on Elementary Student Achievement in Rural South Texas Schools

ERIC Educational Resources Information Center

Martinez-Perez, Frances A.

2013-01-01

Educational inequalities that exist due to socioeconomic status impact the academic achievement of students and contribute to the achievement gap. This study attempted to examine how the predictors of grade level and socioeconomic status impact the passing of state standardized reading and mathematics exams. The 2012-2013 State of Texas Academic…

Effects of Using Dynamic Mathematics Software on Preservice Mathematics Teachers' Spatial Visualization Skills: The Case of Spatial Analytic Geometry

ERIC Educational Resources Information Center

Kösa, Temel

2016-01-01

The purpose of this study was to investigate the effects of using dynamic geometry software on preservice mathematics teachers' spatial visualization skills and to determine whether spatial visualization skills can be a predictor of success in learning analytic geometry of space. The study used a quasi-experimental design with a control group.…

Predictors of cerebral venous thrombosis and arterial ischemic stroke in young Asian women.

PubMed

Wasay, Mohammad; Saadatnia, Mohammad; Venketasubramanian, Narayanaswamy; Kaul, Subhash; Menon, Bindu; Gunaratne, Padma; Malik, Abdul; Mehmood, Kauser; Ahmed, Shahzad; Awan, Safia; Mehndiratta, M M

2012-11-01

The management and outcome of cerebral venous thrombosis (CVT) may be different from that of arterial ischemic stroke (AIS). Clinically differentiating the 2 diseases on clinical grounds may be difficult. The main objective of this study was to identify predictors differentiating CVT from AIS in a large cohort of young Asian women, based on risk factors and investigations. Twelve centers in 8 Asian countries participated. Women aged 15-45 years were included if they had a diagnosis of first-ever symptomatic AIS or CVT confirmed by brain computed tomography scan or magnetic resonance imaging/magnetic resonance venography. Patients with head trauma, cerebral contusions, intracranial hemorrhage, and subarachnoid or subdural hemorrhage were excluded. Data, including demographic data, risk factor assessment, neuroimaging studies, blood tests, and cardiac studies, were collected by retrospective and then prospective chart review between January 2001 and July 2008. Outcome was based on the modified Rankin Scale (mRS) score at admission, discharge, and latest follow-up. A total of 958 patients (204 with CVT and 754 with AIS) were included in the study. Age under 36 years, anemia, pregnancy or postpartum state, and presence of hemorrhagic infarcts on computed tomography scan or magnetic resonance imaging were significant predictors of CVT on univariate analysis. Age over 36 years, diabetes, hypertension, dyslipidemia, recent myocardial infarction, electrocardiogram abnormalities, and blood glucose level >150 mg/dL were strong predictors of AIS. On multivariate analysis, postpartum state and hemorrhagic infarct were the strongest predictors of CVT (P < .001). Mortality was comparable in the 2 patient groups. Prognosis was significantly better for patients with CVT than for those with AIS (mRS score 0-2, 74% v 46%; P < .001). There was no difference in outcome between patients with obstetric and nonobstetric CVT. Our data indicate that in young Asian women, predictors of CVT differ from those for AIS. These findings could be useful in the early identification and diagnosis of patients with CVT. Copyright © 2012 National Stroke Association. Published by Elsevier Inc. All rights reserved.

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.

Field Study of Stress: Psychophysiological Measures During Project Supex.

DTIC Science & Technology

1978-10-01

recordings proved to be unreliable utilizing the current procedures. The perceived scales evaluated the current state of the individual, but they were not good predictors of performance or heart rate activity. (Author)

A Steady-State Kalman Predictor-Based Filtering Strategy for Non-Overlapping Sub-Band Spectral Estimation

PubMed Central

Li, Zenghui; Xu, Bin; Yang, Jian; Song, Jianshe

2015-01-01

This paper focuses on suppressing spectral overlap for sub-band spectral estimation, with which we can greatly decrease the computational complexity of existing spectral estimation algorithms, such as nonlinear least squares spectral analysis and non-quadratic regularized sparse representation. Firstly, our study shows that the nominal ability of the high-order analysis filter to suppress spectral overlap is greatly weakened when filtering a finite-length sequence, because many meaningless zeros are used as samples in convolution operations. Next, an extrapolation-based filtering strategy is proposed to produce a series of estimates as the substitutions of the zeros and to recover the suppression ability. Meanwhile, a steady-state Kalman predictor is applied to perform a linearly-optimal extrapolation. Finally, several typical methods for spectral analysis are applied to demonstrate the effectiveness of the proposed strategy. PMID:25609038

Prevalence and predictors of posttraumatic stress disorder among victims of violence applying for state compensation.

PubMed

Kunst, Maarten; Winkel, Frans Willem; Bogaerts, Stefan

2010-09-01

Many studies have focused on the predictive value of victims' emotions experienced shortly after violence exposure to identify those vulnerable for development of posttraumatic stress disorder (PTSD). However, many victims remain unidentified during the initial recovery phase, yet may still be highly in need of psychological help after substantial time since victimization has passed. Professionals involved in the settlement of civil damage claims filed by victims of violence may play an important role in referring victims with current psychological problems to appropriate treatment services, as they are likely to maintain relations with victims until all compensation possibilities have been exhausted. As an exploratory examination of this topic, the current study investigates the potential utility of file characteristics as predictors of chronic PTSD among 686 victims of violence who had applied for state compensation with the Dutch Victim Compensation Fund (DVCF) in 2006. Identification of significant predictors is preceded by estimating prevalence rates of PTSD. Results indicate that approximately 1 of 2 victims applying for state compensation in the Netherlands still have PTSD many years after victimization and claim settlement. Age, female sex, time since victimization, acquaintance with the perpetrator, violence-related hospitalization, and compensation for immaterial damage prove to be predictive of PTSD, although female sex and immaterial damage compensation fail to reach significance after adjusting for recalled peritraumatic distress severity. Implications for policy practice as well as strengths and limitations of the study are discussed.

Determinants of severe anemia among laboring mothers in Mekelle city public hospitals, Tigray region, Ethiopia

PubMed Central

Alemayehu, Mussie; Mitiku, Mengistu; Goba, Gelila K.

2017-01-01

Introduction Anemia is a global public health problem that has affected a significant number of pregnant mothers worldwide. The World Health Organization has estimated the prevalence of anemia in pregnant women at 18% and 56% in developed and developing countries, respectively. This study aimed to identify factors associated with severe anemia among laboring women in Mekelle city public hospitals, Tigray, Ethiopia. Methods This unmatched case–control study involved 264 (88 = cases and 176 = controls) pregnant women who were recruited when they came for delivery service in Mekelle city public hospitals. The data was collected from July to August, 2016. In this study, a systematic sampling technique was used inselecting controls, but the cases were enrolled until the required sample size was reached. Bivariate and multivariate analyses were conducted to find predictors of severe anemia. Statistically significant predictors of severe anemia were identified at P-value <0.05 and 95% confidence interval. Results A total of 264 pregnant women who came for delivery services were enrolled in this study. The major predicting variables for the occurrence of severe anemia among laboring women were residency (AOR = 3.28, 95% CI: 1.26–8.48), number of pregnancies (AOR = 2.46, 95% CI: 1.14–5.29), iron folate supplementation (AOR = 3.29, 95% CI: 1.27–8.49), dietary diversification score (AOR = 3.23, 95% CI: 1.19–8.71) and duration of menstrual cycle (AOR = 2.37, 95% CI: 1.10–5.10). The variable ‘blood loss during pregnancy’ (AOR = 6.63 95% CI: 2.96–14.86) was identified as a strong predictor of the outcome variable, severe anemia. Conclusion This study identified determinants of severe anemia among laboring women in Mekelle city public hospitals, Northern Ethiopia. To reduce anemia, strengthening health education provision related to the importance of birth spacing and consuming diversified and iron-enriched food should be considered. Moreover, screening of pregnant women for state of anemia during their visits to health facilities, as well as de-worming for intestinal parasites infection are needed. PMID:29099850

Determinants of severe anemia among laboring mothers in Mekelle city public hospitals, Tigray region, Ethiopia.

PubMed

Ebuy, Yirga; Alemayehu, Mussie; Mitiku, Mengistu; Goba, Gelila K

2017-01-01

Anemia is a global public health problem that has affected a significant number of pregnant mothers worldwide. The World Health Organization has estimated the prevalence of anemia in pregnant women at 18% and 56% in developed and developing countries, respectively. This study aimed to identify factors associated with severe anemia among laboring women in Mekelle city public hospitals, Tigray, Ethiopia. This unmatched case-control study involved 264 (88 = cases and 176 = controls) pregnant women who were recruited when they came for delivery service in Mekelle city public hospitals. The data was collected from July to August, 2016. In this study, a systematic sampling technique was used inselecting controls, but the cases were enrolled until the required sample size was reached. Bivariate and multivariate analyses were conducted to find predictors of severe anemia. Statistically significant predictors of severe anemia were identified at P-value <0.05 and 95% confidence interval. A total of 264 pregnant women who came for delivery services were enrolled in this study. The major predicting variables for the occurrence of severe anemia among laboring women were residency (AOR = 3.28, 95% CI: 1.26-8.48), number of pregnancies (AOR = 2.46, 95% CI: 1.14-5.29), iron folate supplementation (AOR = 3.29, 95% CI: 1.27-8.49), dietary diversification score (AOR = 3.23, 95% CI: 1.19-8.71) and duration of menstrual cycle (AOR = 2.37, 95% CI: 1.10-5.10). The variable 'blood loss during pregnancy' (AOR = 6.63 95% CI: 2.96-14.86) was identified as a strong predictor of the outcome variable, severe anemia. This study identified determinants of severe anemia among laboring women in Mekelle city public hospitals, Northern Ethiopia. To reduce anemia, strengthening health education provision related to the importance of birth spacing and consuming diversified and iron-enriched food should be considered. Moreover, screening of pregnant women for state of anemia during their visits to health facilities, as well as de-worming for intestinal parasites infection are needed.

Mental state and its psychophysical conditions in patients with acute leukaemia treated with bone marrow transplantation.

PubMed

Warchala, Anna; Wojtyna, Ewa; Krysta, Krzysztof

2015-09-01

Acute leukaemia and bone marrow transplantation (BMT) as a method of its treatment are great psychological stressors, which are responsible for anxiety and depression in the group of patients. The aim of the study was to assess the patients' mental state and its psychophysical predictors before and after BMT. The study was of a longitudinal and self-descriptive character. The questionnaires: LOT-R, AIS, Mini-Mac, CECS, RSCL and HADS were filled by 60 patients with acute leukaemia before and after BMT. There were no essential statistical differences between the severity of anxiety and depression before and after BMT but the pattern and the power of various mental state predictors changed in the course of the hospitalization. Anxiety before transplantation was greater when the psychological stress and the strategy of "anxious preoccupation" were stronger and the strategy of "fighting spirit" and the level of generalized optimism were weaker. The factors explained 51% variations of anxiety before transplantation. After BMT 77% variations of anxiety were explained, which were associated with a high level of distress at the end of the hospitalization, higher level of anxiety before transplantation, weaker strategy of "fighting spirit" before transplantation and stronger strategy of "anxious preoccupation" after BMT. Before transplantation 36% variations of depression were explained and estimated as weaker "fighting spirit" and worse "global life quality". The essential predictors of depressive symptoms after transplantation, explained by 81% variations of depression, were weaker "fighting spirit" before transplantation, stronger "anxious preoccupation" after transplantation, worse "global life quality" after transplantation and higher level of anxious and depressive symptoms on admission to hospital. The psychological and pharmacological interventions, which reduce anxiety, depression and "anxious preoccupation" as well as enhance "fighting spirit", should be introduced before BMT to improve the patients' mental state.

Weaponizing the Final Frontier: The United States and the New Space Race

DTIC Science & Technology

2017-06-09

42 CHAPTER 3 RESEARCH METHODOLOGY ................................................................43 Documentary Analysis...Commission to Assess United States National Security Space Management and Organization, Executive Summary. The report concluded that to avoid a “Space Pearl...2010), 36. 10 Report of the Commission to Assess United States National Security Space Management and Organization pursuant to Public Law 106-65

A Hierarchical Framework for State-Space Matrix Inference and Clustering.

PubMed

Zuo, Chandler; Chen, Kailei; Hewitt, Kyle J; Bresnick, Emery H; Keleş, Sündüz

2016-09-01

In recent years, a large number of genomic and epigenomic studies have been focusing on the integrative analysis of multiple experimental datasets measured over a large number of observational units. The objectives of such studies include not only inferring a hidden state of activity for each unit over individual experiments, but also detecting highly associated clusters of units based on their inferred states. Although there are a number of methods tailored for specific datasets, there is currently no state-of-the-art modeling framework for this general class of problems. In this paper, we develop the MBASIC ( M atrix B ased A nalysis for S tate-space I nference and C lustering) framework. MBASIC consists of two parts: state-space mapping and state-space clustering. In state-space mapping, it maps observations onto a finite state-space, representing the activation states of units across conditions. In state-space clustering, MBASIC incorporates a finite mixture model to cluster the units based on their inferred state-space profiles across all conditions. Both the state-space mapping and clustering can be simultaneously estimated through an Expectation-Maximization algorithm. MBASIC flexibly adapts to a large number of parametric distributions for the observed data, as well as the heterogeneity in replicate experiments. It allows for imposing structural assumptions on each cluster, and enables model selection using information criterion. In our data-driven simulation studies, MBASIC showed significant accuracy in recovering both the underlying state-space variables and clustering structures. We applied MBASIC to two genome research problems using large numbers of datasets from the ENCODE project. The first application grouped genes based on transcription factor occupancy profiles of their promoter regions in two different cell types. The second application focused on identifying groups of loci that are similar to a GATA2 binding site that is functional at its endogenous locus by utilizing transcription factor occupancy data and illustrated applicability of MBASIC in a wide variety of problems. In both studies, MBASIC showed higher levels of raw data fidelity than analyzing these data with a two-step approach using ENCODE results on transcription factor occupancy data.

Limitations Of The Current State Space Modelling Approach In Multistage Machining Processes Due To Operation Variations

NASA Astrophysics Data System (ADS)

Abellán-Nebot, J. V.; Liu, J.; Romero, F.

2009-11-01

The State Space modelling approach has been recently proposed as an engineering-driven technique for part quality prediction in Multistage Machining Processes (MMP). Current State Space models incorporate fixture and datum variations in the multi-stage variation propagation, without explicitly considering common operation variations such as machine-tool thermal distortions, cutting-tool wear, cutting-tool deflections, etc. This paper shows the limitations of the current State Space model through an experimental case study where the effect of the spindle thermal expansion, cutting-tool flank wear and locator errors are introduced. The paper also discusses the extension of the current State Space model to include operation variations and its potential benefits.

Hypothesized predictors of patient–physician trust and distrust in the elderly: implications for health and disease management

PubMed Central

Mascarenhas, Oswald AJ; Cardozo, Lavoisier J; Afonso, Nelia M; Siddique, Mohamed; Steinberg, Joel; Lepczyk, Marybeth; Aranha, Anil NF

2006-01-01

This study notes the differences between trust and distrust perceptions by the elderly as compared with younger populations. Given the importance of trust and distrust in compliance, changing behaviors, and forming partnerships for both health and disease management, it is necessary to be able to measure patient–doctor trust and distrust (PDTD). Following recent conceptualizations on trust and distrust as coexistent states, this study hypothesizes predictors of PDTD. We are proposing that these predictors form the basis for designing, developing and validating a PDTD scale (PDTDS). It is important to capture the trust–distrust perceptions of older patients as they confront the complexities and vulnerabilities of the modern healthcare delivery system. This is necessary if we are to design interventions to change behaviors of both the healthcare provider and the older patient. PMID:18044114

Projective loop quantum gravity. I. State space

NASA Astrophysics Data System (ADS)

Lanéry, Suzanne; Thiemann, Thomas

2016-12-01

Instead of formulating the state space of a quantum field theory over one big Hilbert space, it has been proposed by Kijowski to describe quantum states as projective families of density matrices over a collection of smaller, simpler Hilbert spaces. Beside the physical motivations for this approach, it could help designing a quantum state space holding the states we need. In a latter work by Okolów, the description of a theory of Abelian connections within this framework was developed, an important insight being to use building blocks labeled by combinations of edges and surfaces. The present work generalizes this construction to an arbitrary gauge group G (in particular, G is neither assumed to be Abelian nor compact). This involves refining the definition of the label set, as well as deriving explicit formulas to relate the Hilbert spaces attached to different labels. If the gauge group happens to be compact, we also have at our disposal the well-established Ashtekar-Lewandowski Hilbert space, which is defined as an inductive limit using building blocks labeled by edges only. We then show that the quantum state space presented here can be thought as a natural extension of the space of density matrices over this Hilbert space. In addition, it is manifest from the classical counterparts of both formalisms that the projective approach allows for a more balanced treatment of the holonomy and flux variables, so it might pave the way for the development of more satisfactory coherent states.

Risk of Adverse Cognitive or Behavioral Conditions and Psychiatric Disorders: Evidence Report

NASA Technical Reports Server (NTRS)

Slack, Kelley J.; Williams, Thomas J.; Schneiderman, Jason S.; Whitmire, Alexandra M.; Picano, James J.; Leveton, Lauren B.; Schmidt, Lacey L.; Shea, Camille

2016-01-01

In April 2010, President Obama declared a space pioneering goal for the United States in general and NASA in particular. "Fifty years after the creation of NASA, our goal is no longer just a destination to reach. Our goal is the capacity for people to work and learn and operate and live safely beyond the Earth for extended periods of time, ultimately in ways that are more sustainable and even indefinite." Thus NASA's Strategic Objective 1.1 emerged as "expand human presence into the solar system and to the surface of Mars to advance exploration, science, innovation, benefits to humanity, and international collaboration" (NASA 2015b). Any space flight, be it of long or short duration, occurs in an extreme environment that has unique stressors. Even with excellent selection methods, the potential for behavioral problems among space flight crews remain a threat to mission success. Assessment of factors that are related to behavioral health can help minimize the chances of distress and, thus, reduce the likelihood of adverse cognitive or behavioral conditions and psychiatric disorders arising within a crew. Similarly, countermeasures that focus on prevention and treatment can mitigate the cognitive or behavioral conditions that, should they arise, would impact mission success. Given the general consensus that longer duration, isolation, and confined missions have a greater risk for behavioral health ensuring crew behavioral health over the long term is essential. Risk, which within the context of this report is assessed with respect to behavioral health and performance, is addressed to deter development of cognitive and behavioral degradations or psychiatric conditions in space flight and analog populations, and to monitor, detect, and treat early risk factors, predictors and other contributing factors. Based on space flight and analog evidence, the average incidence rate of an adverse behavioral health event occurring during a space mission is relatively low for the current conditions. While mood and anxiety disturbances have occurred, no behavioral emergencies have been reported to date in space flight. Anecdotal and empirical evidence indicate that the likelihood of an adverse cognitive or behavioral condition or psychiatric disorder occurring greatly increases with the length of a mission. Further, while cognitive, behavioral, or psychiatric conditions might not immediately and directly threaten mission success, such conditions can, and do, adversely impact individual and crew health, welfare, and performance.

Environmental Temperature and Thermal Indices: What Is the Most Effective Predictor of Heat-Related Mortality in Different Geographical Contexts?

PubMed Central

Morabito, Marco; Crisci, Alfonso; Messeri, Alessandro; Capecchi, Valerio; Modesti, Pietro Amedeo; Gensini, Gian Franco; Orlandini, Simone

2014-01-01

The aim of this study is to identify the most effective thermal predictor of heat-related very-elderly mortality in two cities located in different geographical contexts of central Italy. We tested the hypothesis that use of the state-of-the-art rational thermal indices, the Universal Thermal Climate Index (UTCI), might provide an improvement in predicting heat-related mortality with respect to other predictors. Data regarding very elderly people (≥75 years) who died in inland and coastal cities from 2006 to 2008 (May–October) and meteorological and air pollution were obtained from the regional mortality and environmental archives. Rational (UTCI) and direct thermal indices represented by a set of bivariate/multivariate apparent temperature indices were assessed. Correlation analyses and generalized additive models were applied. The Akaike weights were used for the best model selection. Direct multivariate indices showed the highest correlations with UTCI and were also selected as the best thermal predictors of heat-related mortality for both inland and coastal cities. Conversely, the UTCI was never identified as the best thermal predictor. The use of direct multivariate indices, which also account for the extra effect of wind speed and/or solar radiation, revealed the best fitting with all-cause, very-elderly mortality attributable to heat stress. PMID:24523657

Environmental temperature and thermal indices: what is the most effective predictor of heat-related mortality in different geographical contexts?

PubMed

Morabito, Marco; Crisci, Alfonso; Messeri, Alessandro; Capecchi, Valerio; Modesti, Pietro Amedeo; Gensini, Gian Franco; Orlandini, Simone

2014-01-01

The aim of this study is to identify the most effective thermal predictor of heat-related very-elderly mortality in two cities located in different geographical contexts of central Italy. We tested the hypothesis that use of the state-of-the-art rational thermal indices, the Universal Thermal Climate Index (UTCI), might provide an improvement in predicting heat-related mortality with respect to other predictors. Data regarding very elderly people (≥ 75 years) who died in inland and coastal cities from 2006 to 2008 (May-October) and meteorological and air pollution were obtained from the regional mortality and environmental archives. Rational (UTCI) and direct thermal indices represented by a set of bivariate/multivariate apparent temperature indices were assessed. Correlation analyses and generalized additive models were applied. The Akaike weights were used for the best model selection. Direct multivariate indices showed the highest correlations with UTCI and were also selected as the best thermal predictors of heat-related mortality for both inland and coastal cities. Conversely, the UTCI was never identified as the best thermal predictor. The use of direct multivariate indices, which also account for the extra effect of wind speed and/or solar radiation, revealed the best fitting with all-cause, very-elderly mortality attributable to heat stress.

ProQ3: Improved model quality assessments using Rosetta energy terms

PubMed Central

Uziela, Karolis; Shu, Nanjiang; Wallner, Björn; Elofsson, Arne

2016-01-01

Quality assessment of protein models using no other information than the structure of the model itself has been shown to be useful for structure prediction. Here, we introduce two novel methods, ProQRosFA and ProQRosCen, inspired by the state-of-art method ProQ2, but using a completely different description of a protein model. ProQ2 uses contacts and other features calculated from a model, while the new predictors are based on Rosetta energies: ProQRosFA uses the full-atom energy function that takes into account all atoms, while ProQRosCen uses the coarse-grained centroid energy function. The two new predictors also include residue conservation and terms corresponding to the agreement of a model with predicted secondary structure and surface area, as in ProQ2. We show that the performance of these predictors is on par with ProQ2 and significantly better than all other model quality assessment programs. Furthermore, we show that combining the input features from all three predictors, the resulting predictor ProQ3 performs better than any of the individual methods. ProQ3, ProQRosFA and ProQRosCen are freely available both as a webserver and stand-alone programs at http://proq3.bioinfo.se/. PMID:27698390

Environmental and social-demographic predictors of the southern house mosquito Culex quinquefasciatus in New Orleans, Louisiana.

PubMed

Moise, Imelda K; Riegel, Claudia; Muturi, Ephantus J

2018-04-17

Understanding the major predictors of disease vectors such as mosquitoes can guide the development of effective and timely strategies for mitigating vector-borne disease outbreaks. This study examined the influence of selected environmental, weather and sociodemographic factors on the spatial and temporal distribution of the southern house mosquito Culex quinquefasciatus Say in New Orleans, Louisiana, USA. Adult mosquitoes were collected over a 4-year period (2006, 2008, 2009 and 2010) using CDC gravid traps. Socio-demographic predictors were obtained from the United States Census Bureau, 2005-2009 American Community Survey and the City of New Orleans Department of Code Enforcement. Linear mixed effects models and ERDAS image processing software were used for statistical analysis and image processing. Only two of the 22 predictors examined were significant predictors of Cx. quinquefasciatus abundance. Mean temperature during the week of mosquito collection was positively associated with Cx. quinquefasciatus abundance while developed high intensity areas were negatively associated with Cx. quinquefasciatus abundance. The findings of this study illustrate the power and utility of integrating biophysical and sociodemographic data using GIS analysis to identify the biophysical and sociodemographic processes that increase the risk of vector mosquito abundance. This knowledge can inform development of accurate predictive models that ensure timely implementation of mosquito control interventions.

On the interest of combining an analog model to a regression model for the adaptation of the downscaling link. Application to probabilistic prediction of precipitation over France.

NASA Astrophysics Data System (ADS)

Chardon, Jérémy; Hingray, Benoit; Favre, Anne-Catherine

2016-04-01

Scenarios of surface weather required for the impact studies have to be unbiased and adapted to the space and time scales of the considered hydro-systems. Hence, surface weather scenarios obtained from global climate models and/or numerical weather prediction models are not really appropriated. Outputs of these models have to be post-processed, which is often carried out thanks to Statistical Downscaling Methods (SDMs). Among those SDMs, approaches based on regression are often applied. For a given station, a regression link can be established between a set of large scale atmospheric predictors and the surface weather variable. These links are then used for the prediction of the latter. However, physical processes generating surface weather vary in time. This is well known for precipitation for instance. The most relevant predictors and the regression link are also likely to vary in time. A better prediction skill is thus classically obtained with a seasonal stratification of the data. Another strategy is to identify the most relevant predictor set and establish the regression link from dates that are similar - or analog - to the target date. In practice, these dates can be selected thanks to an analog model. In this study, we explore the possibility of improving the local performance of an analog model - where the analogy is applied to the geopotential heights 1000 and 500 hPa - using additional local scale predictors for the probabilistic prediction of the Safran precipitation over France. For each prediction day, the prediction is obtained from two GLM regression models - for both the occurrence and the quantity of precipitation - for which predictors and parameters are estimated from the analog dates. Firstly, the resulting combined model noticeably allows increasing the prediction performance by adapting the downscaling link for each prediction day. Secondly, the selected predictors for a given prediction depend on the large scale situation and on the considered region. Finally, even with such an adaptive predictor identification, the downscaling link appears to be robust: for a same prediction day, predictors selected for different locations of a given region are similar and the regression parameters are consistent within the region of interest.

Predictors of initial levels and trajectories of anxiety in women before and for 6 months after breast cancer surgery.

PubMed

Kyranou, Marianna; Puntillo, Kathleen; Dunn, Laura B; Aouizerat, Bradley E; Paul, Steven M; Cooper, Bruce A; Neuhaus, John; West, Claudia; Dodd, Marylin; Miaskowski, Christine

2014-01-01

The diagnosis of breast cancer, in combination with the anticipation of surgery, evokes fear, uncertainty, and anxiety in most women. Study purposes were to examine in patients who underwent breast cancer surgery how ratings of state anxiety changed from the time of the preoperative assessment to 6 months after surgery and to investigate whether specific demographic, clinical, symptom, and psychosocial adjustment characteristics predicted the preoperative levels of state anxiety and/or characteristics of the trajectories of state anxiety. Patients (n = 396) were enrolled preoperatively and completed the Spielberger State Anxiety inventory monthly for 6 months. Using hierarchical linear modeling, demographic, clinical, symptom, and psychosocial adjustment characteristics were evaluated as predictors of initial levels and trajectories of state anxiety. Patients experienced moderate levels of anxiety before surgery. Higher levels of depressive symptoms and uncertainty about the future, as well as lower levels of life satisfaction, less sense of control, and greater difficulty coping, predicted higher preoperative levels of state anxiety. Higher preoperative state anxiety, poorer physical health, decreased sense of control, and more feelings of isolation predicted higher state anxiety scores over time. Moderate levels of anxiety persist in women for 6 months after breast cancer surgery. Clinicians need to implement systematic assessments of anxiety to identify high-risk women who warrant more targeted interventions. In addition, ongoing follow-up is needed to prevent adverse postoperative outcomes and to support women to return to their preoperative levels of function.

Positive and negative affect dimensions in chronic knee osteoarthritis: effects on clinical and laboratory pain.

PubMed

Finan, Patrick H; Quartana, Phillip J; Smith, Michael T

2013-06-01

This study investigated whether daily and laboratory assessed pain differs as a function of the temporal stability and valence of affect in individuals with chronic knee osteoarthritis (KOA). One hundred fifty-one men and women with KOA completed 14 days of electronic diaries assessing positive affect (PA), negative affect (NA), and clinical pain. A subset of participants (n =79) engaged in quantitative sensory testing (QST). State PA and NA were assessed prior to administration of stimuli that induced suprathreshold pain and temporal summation. Multilevel modeling and multiple regression evaluated associations of affect and pain as a function of valence (i.e., positive versus negative) and stability (i.e., stable versus state). In the diary, stable NA (B = -.63, standard error [SE] = .13, p < .001) was a stronger predictor of clinical KOA pain than stable PA (B = -.18, SE = .11, p = .091), and state PA (B = -.09, p < .001) was a stronger predictor of concurrent daily clinical pain than state NA (B = .04, SE = .02, p = .068). In the laboratory, state PA (B = -.05, SE = .02, p = .042), but not state NA (p = .46), predicted diminished temporal summation of mechanical pain. Stable NA is more predictive of clinical pain than stable PA, whereas state PA is more predictive of both clinical and laboratory pain than state NA. The findings suggest that dynamic affect-pain processes in the field may reflect individual differences in central pain facilitation.

Episode forecasting in bipolar disorder: Is energy better than mood?

PubMed

Ortiz, Abigail; Bradler, Kamil; Hintze, Arend

2018-01-22

Bipolar disorder is a severe mood disorder characterized by alternating episodes of mania and depression. Several interventions have been developed to decrease high admission rates and high suicides rates associated with the illness, including psychoeducation and early episode detection, with mixed results. More recently, machine learning approaches have been used to aid clinical diagnosis or to detect a particular clinical state; however, contradictory results arise from confusion around which of the several automatically generated data are the most contributory and useful to detect a particular clinical state. Our aim for this study was to apply machine learning techniques and nonlinear analyses to a physiological time series dataset in order to find the best predictor for forecasting episodes in mood disorders. We employed three different techniques: entropy calculations and two different machine learning approaches (genetic programming and Markov Brains as classifiers) to determine whether mood, energy or sleep was the best predictor to forecast a mood episode in a physiological time series. Evening energy was the best predictor for both manic and depressive episodes in each of the three aforementioned techniques. This suggests that energy might be a better predictor than mood for forecasting mood episodes in bipolar disorder and that these particular machine learning approaches are valuable tools to be used clinically. Energy should be considered as an important factor for episode prediction. Machine learning approaches provide better tools to forecast episodes and to increase our understanding of the processes that underlie mood regulation. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Presence and consequence of tooth periapical radiolucency in patients with cirrhosis

PubMed Central

Grønkjær, Lea Ladegaard; Holmstrup, Palle; Schou, Søren; Schwartz, Kristoffer; Kongstad, Johanne; Jepsen, Peter; Vilstrup, Hendrik

2016-01-01

Background Periapical radiolucency is the radiographic sign of inflammatory bone lesions around the apex of the tooth. We determined the prevalence and predictors of periapical radiolucency in patients with cirrhosis and the association with systemic inflammation status and cirrhosis-related complications. Methods A total of 110 cirrhosis patients were consecutively enrolled. Periapical radiolucency was defined as the presence of radiolucency or widening of the periapical periodontal ligament space to more than twice the normal width. Predictors of periapical radiolucency and the association with systemic inflammation markers and cirrhosis-related complications were explored by univariable and multivariable logistic regression analyses. Results Periapical radiolucency was present in one or more teeth in 46% of the patients. Strong predictors were gross caries (odds ratio [OR] 3.12, 95% confidence interval [CI] 1.43–6.79) and severe periodontitis (OR 3.98, 95% CI 1.04–15.20). Also old age (OR 1.10, 95% CI 1.01–1.19) and smoking (OR 3.24, 95% CI 1.02–17.62) were predictors. However, cirrhosis etiology (alcoholic vs nonalcoholic) or severity (Model of End-Stage Liver Disease score) were not predictors. The patients with periapical radiolucency had higher C-reactive protein (15.8 mg/L vs 8.1 mg/L, P=0.02) and lower albumin contents (25 g/L vs 28 g/L, P=0.04) than those without. Furthermore, the patients with periapical radiolucency had a higher prevalence of cirrhosis-related complications such as ascites, hepatic encephalopathy, and/or variceal bleeding (46% vs 27%, P=0.05). Conclusion Periapical radiolucency is often present as an element of poor oral health status and likely has an adverse clinical significance, which should motivate diagnostic and clinical attention to the findings. PMID:27695370

Predictors of stroke associated with coronary artery bypass grafting in patients with diabetes mellitus and multivessel coronary artery disease.

PubMed

Domanski, Michael J; Farkouh, Michael E; Zak, Victor; Feske, Steven; Easton, Donald; Weinberger, Jesse; Hamon, Martial; Escobedo, Jorge; Shrader, Peter; Siami, Flora S; Fuster, Valentin

2015-05-15

This study assesses demographic and clinical variables associated with perioperative and late stroke in diabetes mellitus patients after multivessel coronary artery bypass grafting (CABG). Future Revascularization Evaluation in Patients with Diabetes Mellitus: Optimal Management of Multivessel Disease (FREEDOM) is the largest randomized trial of diabetic patients undergoing multivessel CABG. FREEDOM patients had improved survival free of death, myocardial infarction, or stroke and increased overall survival after CABG compared to percutaneous intervention. However, the stroke rate was greater following CABG than percutaneous intervention. We studied predictors of stroke in CABG-treated patients analyzing separately overall, perioperative (≤30 days after surgery), and late (>30 days after surgery) stroke. For long-term outcomes (overall stroke and late stroke), Cox proportional hazards regression was used, accounting for time to event, and logistic regression was used for perioperative stroke. Independent perioperative stroke predictors were previous stroke (odds ratio [OR] 6.96, 95% confidence interval [CI] 1.43 to 33.96; p = 0.02), warfarin use (OR 10.26, 95% CI 1.10 to 96.03; p = 0.02), and surgery outside the United States or Canada (OR 9.81, 95% CI 1.28 to 75.40; p = 0.03). Independent late stroke predictors: renal insufficiency (hazard ratio [HR] 3.57, 95% CI 1.01 to 12.64; p = 0.048), baseline low-density lipoprotein ≥105 mg/dl (HR 3.28, 95% CI 1.19 to 9.02; p = 0.02), and baseline diastolic blood pressure (each 1 mm Hg increase reduces stroke hazard by 5%; HR 0.95, 95% CI 0.91 to 0.99; p = 0.03). There was no overlap between predictors of perioperative versus late stroke. In conclusion, late post-CABG strokes were associated with well-described risk factors. Nearly half of the strokes were perioperative. Independent risk factors for perioperative stroke: previous stroke, previous warfarin use, and CABG performed outside the United States or Canada. Copyright © 2015 Elsevier Inc. All rights reserved.

An Adaptive Prediction-Based Approach to Lossless Compression of Floating-Point Volume Data.

PubMed

Fout, N; Ma, Kwan-Liu

2012-12-01

In this work, we address the problem of lossless compression of scientific and medical floating-point volume data. We propose two prediction-based compression methods that share a common framework, which consists of a switched prediction scheme wherein the best predictor out of a preset group of linear predictors is selected. Such a scheme is able to adapt to different datasets as well as to varying statistics within the data. The first method, called APE (Adaptive Polynomial Encoder), uses a family of structured interpolating polynomials for prediction, while the second method, which we refer to as ACE (Adaptive Combined Encoder), combines predictors from previous work with the polynomial predictors to yield a more flexible, powerful encoder that is able to effectively decorrelate a wide range of data. In addition, in order to facilitate efficient visualization of compressed data, our scheme provides an option to partition floating-point values in such a way as to provide a progressive representation. We compare our two compressors to existing state-of-the-art lossless floating-point compressors for scientific data, with our data suite including both computer simulations and observational measurements. The results demonstrate that our polynomial predictor, APE, is comparable to previous approaches in terms of speed but achieves better compression rates on average. ACE, our combined predictor, while somewhat slower, is able to achieve the best compression rate on all datasets, with significantly better rates on most of the datasets.

Incidence and Predictors of Incontinence Associated Skin Damage in Nursing Home Residents with New Onset Incontinence

PubMed Central

Bliss, Donna Z.; Mathiason, Michelle A.; Gurvich, Olga; Savik, Kay; Eberly, Lynn E.; Fisher, Jessica; Wiltzen, Kjerstie R.; Akermark, Haley; Hildebrandt, Amanda; Jacobson, Megan; Funk, Taylor; Beckman, Amanda; Larson, Reed

2016-01-01

Purpose The purpose of this study was to determine the incidence and predictors of incontinence associated dermatitis (IAD) in nursing home residents. Methods Records of a cohort of 10,713 elderly (aged 65+) newly incontinent nursing home residents in 448 nursing homes in 28 states free of IAD were followed for IAD development. Potential multi-level predictors of IAD were identified in four national datasets containing information about the characteristics of individual nursing home residents, nursing home care environment, and communities in which the nursing homes were located. A unique set of health practitioner orders provided information about IAD and the predictors of IAD prevention and pressure injuries in the extended perineal area. Analysis was based on hierarchical logistical regression. Results The incidence of IAD was 5.5%. Significant predictors of IAD were not receiving preventive interventions for IAD, presence of a perineal pressure injury, having greater functional limitations in activities of daily living, more perfusion problems, and lesser cognitive deficits. Conclusion Findings highlight the importance of prevention of IAD and treatment/prevention of pressure injuries. A Wound Ostomy and Continence (WOC) nurse offers expertise in these interventions and can educate staff about IAD predictors which can improve resident outcomes. Other recommendations include implementing plans of care to improve functional status, treat perfusion problems, and provide assistance with incontinence and skin care to residents with milder as well as greater cognitive deficits. PMID:28267124

Predictors of acculturative hassles among Vietnamese refugees in Norway: Results from a long-term longitudinal study.

PubMed

Tingvold, Laila; Vaage, Aina Basilier; Allen, James; Wentzel-Larsen, Tore; van Ta, Thong; Hauff, Edvard

2015-10-01

We investigated acculturative hassles in a community cohort of Vietnamese refugees in Norway (n = 61), exploring cross-sectional data and longitudinal predictors of acculturative hassles using data from their arrival in Norway in 1982 (T1), with follow up in 1985 (T2) and in 2005-2006 (T3). To our knowledge, this is the first longitudinal study of predictors of acculturative hassles in a refugee population. Results indicated that more communication problems and less Norwegian language competence were related to most hassles at T3. Higher psychological distress, lower quality of life, lower self-reported state of health, and less education at T3 were associated with higher levels of hassles at T3. More psychological distress at T2 and less education at arrival (T1) were significant predictors for more acculturative hassles at T3. These data suggest that addressing psychological distress during the early phase in a resettlement country may promote long-term refugee adjustment and, in particular, reduce exposure to acculturative hassles. © The Author(s) 2015.

Predictors of food decision making: A systematic interdisciplinary mapping (SIM) review.

PubMed

Symmank, Claudia; Mai, Robert; Hoffmann, Stefan; Stok, F Marijn; Renner, Britta; Lien, Nanna; Rohm, Harald

2017-03-01

The number of publications on consumer food decision making and its predictors and correlates has been steadily increasing over the last three decades. Given that different scientific disciplines illuminate this topic from different perspectives, it is necessary to develop an interdisciplinary overview. The aim of this study is to conduct a systematic interdisciplinary mapping (SIM) review by using rapid review techniques to explore the state-of-the-art, and to identify hot topics and research gaps in this field. This interdisciplinary review includes 1,820 publications in 485 different journals and other types of publications from more than ten disciplines (including nutritional science, medicine/health science, psychology, food science and technology, business research, etc.) across a period of 60 years. The identified predictors of food decision making were categorized in line with the recently proposed DONE (Determinants Of Nutrition and Eating behavior) framework. After applying qualitative and quantitative analyses, this study reveals that most of the research emphasizes biological, psychological, and product-related predictors, whereas policy-related influences on food choice are scarcely considered. Copyright © 2016 Elsevier Ltd. All rights reserved.

Predicting dropout using student- and school-level factors: An ecological perspective.

PubMed

Wood, Laura; Kiperman, Sarah; Esch, Rachel C; Leroux, Audrey J; Truscott, Stephen D

2017-03-01

High school dropout has been associated with negative outcomes, including increased rates of unemployment, incarceration, and mortality. Dropout rates vary significantly depending on individual and environmental factors. The purpose of our study was to use an ecological perspective to concurrently explore student- and school-level predictors associated with dropout for the purpose of better understanding how to prevent it. We used the Education Longitudinal Study of 2002 dataset. Participants included 14,106 sophomores across 684 public and private schools. We identified variables of interest based on previous research on dropout and implemented hierarchical generalized linear modeling. In the final model, significant student-level predictors included academic achievement, retention, sex, family socioeconomic status (SES), and extracurricular involvement. Significant school-level predictors included school SES and school size. Race/ethnicity, special education status, born in the United States, English as first language, school urbanicity, and school region did not significantly predict dropout after controlling for the aforementioned predictors. Implications for prevention and intervention efforts within a multitiered intervention model are discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Predictors of nursing home residents' time to hospitalization.

PubMed

O'Malley, A James; Caudry, Daryl J; Grabowski, David C

2011-02-01

To model the predictors of the time to first acute hospitalization for nursing home residents, and accounting for previous hospitalizations, model the predictors of time between subsequent hospitalizations. Merged file from New York State for the period 1998-2004 consisting of nursing home information from the minimum dataset and hospitalization information from the Statewide Planning and Research Cooperative System. Accelerated failure time models were used to estimate the model parameters and predict survival times. The models were fit to observations from 50 percent of the nursing homes and validated on the remaining observations. Pressure ulcers and facility-level deficiencies were associated with a decreased time to first hospitalization, while the presence of advance directives and facility staffing was associated with an increased time. These predictors of the time to first hospitalization model had effects of similar magnitude in predicting the time between subsequent hospitalizations. This study provides novel evidence suggesting modifiable patient and nursing home characteristics are associated with the time to first hospitalization and time to subsequent hospitalizations for nursing home residents. © Health Research and Educational Trust.

Update on Performance in Tobacco Control: A Longitudinal Analysis of the Impact of Tobacco Control Policy and the US Adult Smoking Rate, 2011-2013.

PubMed

Mader, Emily M; Lapin, Brittany; Cameron, Brianna J; Carr, Thomas A; Morley, Christopher P

2016-01-01

Tobacco use remains the leading cause of preventable death in the United States. States and municipalities have instituted a variety of tobacco control measures (TCMs) to address the significant impact tobacco use has on population health. The American Lung Association annually grades state performance of tobacco control using the State of Tobacco Control grading framework. To gain an updated understanding of how recent efforts in tobacco control have impacted tobacco use across the United States, using yearly State of Tobacco Control TCM assessments. The independent TCM variables of smoke-free air score, cessation score, excise tax, and percentage of recommended funding were selected from the American Lung Association State of Tobacco Control reports. Predictors of adult smoking rates were determined by a mixed-effects model. The 50 US states and District of Columbia. Adult smoking rate in each state from 2011 to 2013. The average adult smoking rate decreased significantly from 2011 to 2013 (21.3% [SD: 3.5] to 19.3% [SD: 3.5], P = .016). All forms of TCMs varied widely in implementation levels across states. Excise taxes (β = -.812, P = .006) and smoke-free air regulations (β = -.057, P = .008) were significant, negative predictors of adult smoking. Cessation services (β = .015, P = .46) did not have a measurable effect on adult smoking. Tobacco control measures with the strongest influence on adult smoking include the state excise tax and state smoke-free air regulations. The lack of robust funding for tobacco cessation services across the majority of US states highlights an important shortfall in current tobacco control policy.

CAPITAL IMPROVEMENTS PROGRAM FOR THE OKLAHOMA STATE SYSTEM OF HIGHER EDUCATION, 1965-75. PHASE TWO.

ERIC Educational Resources Information Center

CLEEK, JOHN E.; COFFELT, JOHN J.

THIS STUDY UPDATES THE 1963 TEN-YEAR PROJECTION OF CAPITAL IMPROVEMENTS FOR THE INSTITUTIONS OF THE OKLAHOMA STATE SYSTEM OF HIGHER EDUCATION. SPACE NEEDS OF THE STATE SYSTEM WERE DETERMINED BY A COMPARISON OF FACILITY INVENTORIES FOR CURRENT SPACE NEEDS AND PROJECTED SPACE NEEDS. THE SPACE NEEDS WERE TABULATED FOR CLASSROOMS, FACULTY OFFICES,…

Spatio-temporal patterns of gun violence in Syracuse, New York 2009-2015.

PubMed

Larsen, David A; Lane, Sandra; Jennings-Bey, Timothy; Haygood-El, Arnett; Brundage, Kim; Rubinstein, Robert A

2017-01-01

Gun violence in the United States of America is a large public health problem that disproportionately affects urban areas. The epidemiology of gun violence reflects various aspects of an infectious disease including spatial and temporal clustering. We examined the spatial and temporal trends of gun violence in Syracuse, New York, a city of 145,000. We used a spatial scan statistic to reveal spatio-temporal clusters of gunshots investigated and corroborated by Syracuse City Police Department for the years 2009-2015. We also examined predictors of areas with increased gun violence using a multi-level zero-inflated Poisson regression with data from the 2010 census. Two space-time clusters of gun violence were revealed in the city. Higher rates of segregation, poverty and the summer months were all associated with increased risk of gun violence. Previous gunshots in the area were associated with a 26.8% increase in the risk of gun violence. Gun violence in Syracuse, NY is both spatially and temporally stable, with some neighborhoods of the city greatly afflicted.

Spatio-temporal patterns of gun violence in Syracuse, New York 2009-2015

PubMed Central

Lane, Sandra; Jennings-Bey, Timothy; Haygood-El, Arnett; Brundage, Kim; Rubinstein, Robert A.

2017-01-01

Gun violence in the United States of America is a large public health problem that disproportionately affects urban areas. The epidemiology of gun violence reflects various aspects of an infectious disease including spatial and temporal clustering. We examined the spatial and temporal trends of gun violence in Syracuse, New York, a city of 145,000. We used a spatial scan statistic to reveal spatio-temporal clusters of gunshots investigated and corroborated by Syracuse City Police Department for the years 2009–2015. We also examined predictors of areas with increased gun violence using a multi-level zero-inflated Poisson regression with data from the 2010 census. Two space-time clusters of gun violence were revealed in the city. Higher rates of segregation, poverty and the summer months were all associated with increased risk of gun violence. Previous gunshots in the area were associated with a 26.8% increase in the risk of gun violence. Gun violence in Syracuse, NY is both spatially and temporally stable, with some neighborhoods of the city greatly afflicted. PMID:28319125

Data-driven modeling and predictive control for boiler-turbine unit using fuzzy clustering and subspace methods.

PubMed

Wu, Xiao; Shen, Jiong; Li, Yiguo; Lee, Kwang Y

2014-05-01

This paper develops a novel data-driven fuzzy modeling strategy and predictive controller for boiler-turbine unit using fuzzy clustering and subspace identification (SID) methods. To deal with the nonlinear behavior of boiler-turbine unit, fuzzy clustering is used to provide an appropriate division of the operation region and develop the structure of the fuzzy model. Then by combining the input data with the corresponding fuzzy membership functions, the SID method is extended to extract the local state-space model parameters. Owing to the advantages of the both methods, the resulting fuzzy model can represent the boiler-turbine unit very closely, and a fuzzy model predictive controller is designed based on this model. As an alternative approach, a direct data-driven fuzzy predictive control is also developed following the same clustering and subspace methods, where intermediate subspace matrices developed during the identification procedure are utilized directly as the predictor. Simulation results show the advantages and effectiveness of the proposed approach. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

International Cooperation and Competition in Civilian Space Activities.

ERIC Educational Resources Information Center

Congress of the U.S., Washington, DC. Office of Technology Assessment.

This report assesses the state of international competition in civilian space activities, explores United States civilian objectives in space, and suggests alternative options for enhancing the overall U.S. position in space technologies. It also investigated past, present, and projected international cooperative arrangements for space activities…

Trajectories of Affective States in Adolescent Hockey Players: Turning Point and Motivational Antecedents

ERIC Educational Resources Information Center

Gaudreau, Patrick; Amiot, Catherine E.; Vallerand, Robert J.

2009-01-01

This study examined longitudinal trajectories of positive and negative affective states with a sample of 265 adolescent elite hockey players followed across 3 measurement points during the 1st 11 weeks of a season. Latent class growth modeling, incorporating a time-varying covariate and a series of predictors assessed at the onset of the season,…

Minority Adolescents and Substance Use Risk-Protective Factors: A Focus on Inhalant Use

ERIC Educational Resources Information Center

Mosher, Clayton; Rotolo, Thomas; Phillips, Dretha; Krupski, Antoinette; Stark, Kenneth D.

2004-01-01

Despite the fact that inhalant use is a growing problem among youth in the United States, relatively little attention has been paid to the demographic and social factors related to its use. This study used data from a household survey of adolescents in Washington state, and found that race/ethnicity was a strong predictor of lifetime prevalence of…

Brazil soybean yield covariance model

NASA Technical Reports Server (NTRS)

Callis, S. L.; Sakamoto, C.

1984-01-01

A model based on multiple regression was developed to estimate soybean yields for the seven soybean-growing states of Brazil. The meteorological data of these seven states were pooled and the years 1975 to 1980 were used to model since there was no technological trend in the yields during these years. Predictor variables were derived from monthly total precipitation and monthly average temperature.

Predictors of restraint use among child occupants.

PubMed

Benedetti, Marco; Klinich, Kathleen D; Manary, Miriam A; Flannagan, Carol A

2017-11-17

The objective of this study was to identify factors that predict restraint use and optimal restraint use among children aged 0 to 13 years. The data set is a national sample of police-reported crashes for years 2010-2014 in which type of child restraint is recorded. The data set was supplemented with demographic census data linked by driver ZIP code, as well as a score for the state child restraint law during the year of the crash relative to best practice recommendations for protecting child occupants. Analysis used linear regression techniques. The main predictor of unrestrained child occupants was the presence of an unrestrained driver. Among restrained children, children had 1.66 (95% confidence interval, 1.27, 2.17) times higher odds of using the recommended type of restraint system if the state law at the time of the crash included requirements based on best practice recommendations. Children are more likely to ride in the recommended type of child restraint when their state's child restraint law includes wording that follows best practice recommendations for child occupant protection. However, state child restraint law requirements do not influence when caregivers fail to use an occupant restraint for their child passengers.

The Effect of Three Cognitive Variables on Students' Understanding of the Particulate Nature of Matter and its Changes of State

NASA Astrophysics Data System (ADS)

Tsitsipis, Georgios; Stamovlasis, Dimitrios; Papageorgiou, George

2010-05-01

In this study, students' understanding of the structure of matter and its changes of state such as melting, evaporation, boiling, and condensation was investigated in relation to three cognitive variables: logical thinking (LTh), field dependence/independence, and convergence/divergence dimension. The study took place in Greece with the participation of 329 ninth-grade junior high school pupils (age 14-15). A stepwise multiple regression analysis revealed that all of the above-mentioned cognitive variables were statistically significant predictors of the students' achievement. Among the three predictors, LTh was found to be the most dominant. In addition, students' understanding of the structure of matter, along with the cognitive variables, was shown to have an effect on their understanding of the changes of states and on their competence to interpret these physical changes. Path analyses were implemented to depict these effects. Moreover, a theoretical analysis is provided that associates LTh and cognitive styles with the nature of mental tasks involved when learning the material concerning the particulate nature of matter and its changes of state. Implications for science education are also discussed.

The morphological state space revisited: what do phylogenetic patterns in homoplasy tell us about the number of possible character states?

PubMed Central

Hoyal Cuthill, Jennifer F.

2015-01-01

Biological variety and major evolutionary transitions suggest that the space of possible morphologies may have varied among lineages and through time. However, most models of phylogenetic character evolution assume that the potential state space is finite. Here, I explore what the morphological state space might be like, by analysing trends in homoplasy (repeated derivation of the same character state). Analyses of ten published character matrices are compared against computer simulations with different state space models: infinite states, finite states, ordered states and an ‘inertial' model, simulating phylogenetic constraints. Of these, only the infinite states model results in evolution without homoplasy, a prediction which is not generally met by real phylogenies. Many authors have interpreted the ubiquity of homoplasy as evidence that the number of evolutionary alternatives is finite. However, homoplasy is also predicted by phylogenetic constraints on the morphological distance that can be traversed between ancestor and descendent. Phylogenetic rarefaction (sub-sampling) shows that finite and inertial state spaces do produce contrasting trends in the distribution of homoplasy. Two clades show trends characteristic of phylogenetic inertia, with decreasing homoplasy (increasing consistency index) as we sub-sample more distantly related taxa. One clade shows increasing homoplasy, suggesting exhaustion of finite states. Different clades may, therefore, show different patterns of character evolution. However, when parsimony uninformative characters are excluded (which may occur without documentation in cladistic studies), it may no longer be possible to distinguish inertial and finite state spaces. Interestingly, inertial models predict that homoplasy should be clustered among comparatively close relatives (parallel evolution), whereas finite state models do not. If morphological evolution is often inertial in nature, then homoplasy (false homology) may primarily occur between close relatives, perhaps being replaced by functional analogy at higher taxonomic scales. PMID:26640650

The relationship between unmet needs and distress amongst young people with cancer.

PubMed

Dyson, Gavin J; Thompson, Kate; Palmer, Susan; Thomas, David M; Schofield, Penelope

2012-01-01

Most psychosocial research in cancer has been restricted to paediatric or older adult populations. This study aimed to explore psychological distress and unmet needs in adolescents and young adults (AYA) with cancer and identify predictors of distress among demographic and illness characteristics and supportive care needs. Fifty-three patients between 16 and 30 years completed a cross-sectional survey, administered shortly after presentation to an AYA oncology service and within 4 months of diagnosis. Measures included the Beck Depression Inventory-Fast Screen (BDI-FS), State-Trait Anxiety Inventory-State Form (STAI-S) and the Supportive Care Needs Survey. Level of distress-related sypmtomatology in this population was based on previous work, whereby a cut-off score of 4 or greater was used for the BDI-FS, and one standard deviation above the sample population mean was used for the STAI-S. Prevalence of distress (25%) was lower than that found previously in AYA with cancer. Physical and daily living needs were the most frequently unmet needs overall, followed by psychological needs, health system and information needs and care and support needs. Lastly, being pre-treatment predicted increased depression and state anxiety, while having treatment post-surgery predicted reduced state anxiety. After controlling for treatment status, however, the main predictors of depression and state anxiety were physical and daily living needs and health system and information needs, respectively. Lower levels of distress and unmet psychological needs were related to the few participants (17%) in this study who were pre-treatment, when distress was most likely. However, physical needs and information needs, which are almost inevitable throughout treatment and beyond, were more important predictors of distress. Further exploration must consider the psychosocial difficulties underlying this association and the needs of AYA at transitions between critical periods in their cancer journey (i.e., upon diagnosis, during treatment, etc.).

Loving and Leaving Public Health: Predictors of Intentions to Quit Among State Health Agency Workers.

PubMed

Liss-Levinson, Rivka; Bharthapudi, Kiran; Leider, Jonathon P; Sellers, Katie

2015-01-01

State health agencies play a critical role in protecting and promoting the health and well-being of the people they serve. To be effective, they must maintain a highly skilled, diverse workforce of sufficient size and with proper training. The goal of this study was to examine demographics, job and workplace environment characteristics, job satisfaction, and reasons for initially joining the public health workforce as predictors of an employee's intentions to leave an organization within the next year. This study used a cross-sectional design. Respondents were selected on the basis of a stratified sampling approach, with 5 geographic (paired Health and Human Services [HHS] regions) as the primary strata. Balanced repeated replication was used as a resampling method for variance estimation. A logistic regression model was used to examine the correlates of intentions to leave one's organization within the next year. The independent variables included several measures of satisfaction, perceptions about the workplace environment, initial reasons for joining public health, gender, age, education, salary, supervisory status, program area, and paired HHS region. The sample for this study consisted of 10,246 permanently employed state health agency central office employees who responded to the Public Health Workforce Interests and Needs Survey (PH WINS). Considering leaving one's organization within the next year. Being a person of color, living in the West (HHS regions 9 and 10), and shorter tenure in one's current position were all associated with higher odds of intentions to leave an organization within the next year. Conversely, greater employee engagement, organizational support, job satisfaction, organization satisfaction, and pay satisfaction were all significant predictors of lower intentions to leave one's organization within the next year. Results from this study suggest several variables related to demographics, job characteristics, workplace environment, and job satisfaction that are predictive of intentions to leave. Future researchers and state health agencies should explore how these findings can be used to help with retention of employees in the state health agency workforce.

Identified state-space prediction model for aero-optical wavefronts

NASA Astrophysics Data System (ADS)

Faghihi, Azin; Tesch, Jonathan; Gibson, Steve

2013-07-01

A state-space disturbance model and associated prediction filter for aero-optical wavefronts are described. The model is computed by system identification from a sequence of wavefronts measured in an airborne laboratory. Estimates of the statistics and flow velocity of the wavefront data are shown and can be computed from the matrices in the state-space model without returning to the original data. Numerical results compare velocity values and power spectra computed from the identified state-space model with those computed from the aero-optical data.

Space Mission Human Reliability Analysis (HRA) Project

NASA Technical Reports Server (NTRS)

Boyer, Roger

2014-01-01

The purpose of the Space Mission Human Reliability Analysis (HRA) Project is to extend current ground-based HRA risk prediction techniques to a long-duration, space-based tool. Ground-based HRA methodology has been shown to be a reasonable tool for short-duration space missions, such as Space Shuttle and lunar fly-bys. However, longer-duration deep-space missions, such as asteroid and Mars missions, will require the crew to be in space for as long as 400 to 900 day missions with periods of extended autonomy and self-sufficiency. Current indications show higher risk due to fatigue, physiological effects due to extended low gravity environments, and others, may impact HRA predictions. For this project, Safety & Mission Assurance (S&MA) will work with Human Health & Performance (HH&P) to establish what is currently used to assess human reliabiilty for human space programs, identify human performance factors that may be sensitive to long duration space flight, collect available historical data, and update current tools to account for performance shaping factors believed to be important to such missions. This effort will also contribute data to the Human Performance Data Repository and influence the Space Human Factors Engineering research risks and gaps (part of the HRP Program). An accurate risk predictor mitigates Loss of Crew (LOC) and Loss of Mission (LOM).The end result will be an updated HRA model that can effectively predict risk on long-duration missions.

Predictors of Daily Mobility of Adults in Peri-Urban South India.

PubMed

Sanchez, Margaux; Ambros, Albert; Salmon, Maëlle; Bhogadi, Santhi; Wilson, Robin T; Kinra, Sanjay; Marshall, Julian D; Tonne, Cathryn

2017-07-14

Daily mobility, an important aspect of environmental exposures and health behavior, has mainly been investigated in high-income countries. We aimed to identify the main dimensions of mobility and investigate their individual, contextual, and external predictors among men and women living in a peri-urban area of South India. We used 192 global positioning system (GPS)-recorded mobility tracks from 47 participants (24 women, 23 men) from the Cardiovascular Health effects of Air pollution in Telangana, India (CHAI) project (mean: 4.1 days/person). The mean age was 44 (standard deviation: 14) years. Half of the population was illiterate and 55% was in unskilled manual employment, mostly agriculture-related. Sex was the largest determinant of mobility. During daytime, time spent at home averaged 13.4 (3.7) h for women and 9.4 (4.2) h for men. Women's activity spaces were smaller and more circular than men's. A principal component analysis identified three main mobility dimensions related to the size of the activity space, the mobility in/around the residence, and mobility inside the village, explaining 86% (women) and 61% (men) of the total variability in mobility. Age, socioeconomic status, and urbanicity were associated with all three dimensions. Our results have multiple potential applications for improved assessment of environmental exposures and their effects on health.

Application of Interval Predictor Models to Space Radiation Shielding

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.; Giesy,Daniel P.; Norman, Ryan B.; Blattnig, Steve R.

2016-01-01

This paper develops techniques for predicting the uncertainty range of an output variable given input-output data. These models are called Interval Predictor Models (IPM) because they yield an interval valued function of the input. This paper develops IPMs having a radial basis structure. This structure enables the formal description of (i) the uncertainty in the models parameters, (ii) the predicted output interval, and (iii) the probability that a future observation would fall in such an interval. In contrast to other metamodeling techniques, this probabilistic certi cate of correctness does not require making any assumptions on the structure of the mechanism from which data are drawn. Optimization-based strategies for calculating IPMs having minimal spread while containing all the data are developed. Constraints for bounding the minimum interval spread over the continuum of inputs, regulating the IPMs variation/oscillation, and centering its spread about a target point, are used to prevent data over tting. Furthermore, we develop an approach for using expert opinion during extrapolation. This metamodeling technique is illustrated using a radiation shielding application for space exploration. In this application, we use IPMs to describe the error incurred in predicting the ux of particles resulting from the interaction between a high-energy incident beam and a target.

Bayesian Analysis of High Dimensional Classification

NASA Astrophysics Data System (ADS)

Mukhopadhyay, Subhadeep; Liang, Faming

2009-12-01

Modern data mining and bioinformatics have presented an important playground for statistical learning techniques, where the number of input variables is possibly much larger than the sample size of the training data. In supervised learning, logistic regression or probit regression can be used to model a binary output and form perceptron classification rules based on Bayesian inference. In these cases , there is a lot of interest in searching for sparse model in High Dimensional regression(/classification) setup. we first discuss two common challenges for analyzing high dimensional data. The first one is the curse of dimensionality. The complexity of many existing algorithms scale exponentially with the dimensionality of the space and by virtue of that algorithms soon become computationally intractable and therefore inapplicable in many real applications. secondly, multicollinearities among the predictors which severely slowdown the algorithm. In order to make Bayesian analysis operational in high dimension we propose a novel 'Hierarchical stochastic approximation monte carlo algorithm' (HSAMC), which overcomes the curse of dimensionality, multicollinearity of predictors in high dimension and also it possesses the self-adjusting mechanism to avoid the local minima separated by high energy barriers. Models and methods are illustrated by simulation inspired from from the feild of genomics. Numerical results indicate that HSAMC can work as a general model selection sampler in high dimensional complex model space.

Predictors of Daily Mobility of Adults in Peri-Urban South India

PubMed Central

Kinra, Sanjay; Marshall, Julian D.; Tonne, Cathryn

2017-01-01

Daily mobility, an important aspect of environmental exposures and health behavior, has mainly been investigated in high-income countries. We aimed to identify the main dimensions of mobility and investigate their individual, contextual, and external predictors among men and women living in a peri-urban area of South India. We used 192 global positioning system (GPS)-recorded mobility tracks from 47 participants (24 women, 23 men) from the Cardiovascular Health effects of Air pollution in Telangana, India (CHAI) project (mean: 4.1 days/person). The mean age was 44 (standard deviation: 14) years. Half of the population was illiterate and 55% was in unskilled manual employment, mostly agriculture-related. Sex was the largest determinant of mobility. During daytime, time spent at home averaged 13.4 (3.7) h for women and 9.4 (4.2) h for men. Women’s activity spaces were smaller and more circular than men’s. A principal component analysis identified three main mobility dimensions related to the size of the activity space, the mobility in/around the residence, and mobility inside the village, explaining 86% (women) and 61% (men) of the total variability in mobility. Age, socioeconomic status, and urbanicity were associated with all three dimensions. Our results have multiple potential applications for improved assessment of environmental exposures and their effects on health. PMID:28708095

Predictors of vitamin D status in subjects that consume a vitamin D supplement.

PubMed

Levy, M A; McKinnon, T; Barker, T; Dern, A; Helland, T; Robertson, J; Cuomo, J; Wood, T; Dixon, B M

2015-01-01

Although dietary supplement use has increased significantly among the general population, the interplay between vitamin D supplementation and other factors that influence vitamin D status remains unclear. The objective of this study was to identify predictor variables of vitamin D status in free-living subjects to determine the extent to which vitamin D supplements and other factors influence vitamin D status. This was a retrospective, cross-sectional study involving 743 volunteers. Serum 25-hydroxy-vitamin D (25(OH)D) level and the variables diet, supplement usage, latitude of residence, ethnicity, age and body mass index (BMI) were used to predict vitamin D status in a summer and winter cohort. Supplemental vitamin D3 consumption was the most significant positive predictor, whereas BMI was the most significant negative predictor, of vitamin D status in each cohort. Other positive predictors were fortified beverage and dairy consumption in the summer and winter cohort, respectively. Negative predictors were: African American, Asian and Hispanic race in the summer; latitude of residence >36°N, Asian and Hispanic ethnicity in the winter. Mean(± s.d.) 25(OH)D levels were 101.1 (± 42.1) and 92.6 (± 39.0) nmol/l in summer and winter, respectively. Comparing non-supplement vs supplement users, approximately 38 vs 2.5% in the winter and 18 vs 1.4% in the summer had vitamin D levels <50 nmol/l. Vitamin D supplementation was the most significant positive predictor of vitamin D status. Collectively, these data point to the practicality of utilizing vitamin D supplements to reduce hypovitaminosis D in adults throughout the United States.

00pp0065

NASA Image and Video Library

2000-01-14

Before the start of the First Florida Space Summit, participants gather around the poster. From left are Center Director Roy Bridges, Representative Jim Davis, Representative Dave Weldon, NASA Administrator Dan Goldin, Senator Connie Mack, Governor Jeb Bush, Senator Bob Graham and 45th Space Wing Commander Brig. Gen. Donald Pettit. The summit, which was held at the Kennedy Space Center Visitor Complex, featured key state officials and aerospace companies to discuss the future of space as it relates to the State of Florida. Moderated by Bridges, the event also included State Senator Patsy Kurth, State Senator Charlie Bronson, and State Representative Randy Ball

KSC-00pp0065

NASA Image and Video Library

2000-01-14

Before the start of the First Florida Space Summit, participants gather around the poster. From left are Center Director Roy Bridges, Representative Jim Davis, Representative Dave Weldon, NASA Administrator Dan Goldin, Senator Connie Mack, Governor Jeb Bush, Senator Bob Graham and 45th Space Wing Commander Brig. Gen. Donald Pettit. The summit, which was held at the Kennedy Space Center Visitor Complex, featured key state officials and aerospace companies to discuss the future of space as it relates to the State of Florida. Moderated by Bridges, the event also included State Senator Patsy Kurth, State Senator Charlie Bronson, and State Representative Randy Ball

Occams Quantum Strop: Synchronizing and Compressing Classical Cryptic Processes via a Quantum Channel (Open Source)

DTIC Science & Technology

2016-02-15

do not quote them here. A sequel details a yet more efficient analytic technique based on holomorphic functions of the internal - state Markov chain...required, though, when synchronizing over a quantum channel? Recent work demonstrated that representing causal similarity as quantum state ...minimal, unifilar predictor4. The -machine’s causal states σ ∈ are defined by the equivalence relation that groups all histories = −∞ ←x x :0 that

Segmentation of the glottal space from laryngeal images using the watershed transform.

PubMed

Osma-Ruiz, Víctor; Godino-Llorente, Juan I; Sáenz-Lechón, Nicolás; Fraile, Rubén

2008-04-01

The present work describes a new method for the automatic detection of the glottal space from laryngeal images obtained either with high speed or with conventional video cameras attached to a laryngoscope. The detection is based on the combination of several relevant techniques in the field of digital image processing. The image is segmented with a watershed transform followed by a region merging, while the final decision is taken using a simple linear predictor. This scheme has successfully segmented the glottal space in all the test images used. The method presented can be considered a generalist approach for the segmentation of the glottal space because, in contrast with other methods found in literature, this approach does not need either initialization or finding strict environmental conditions extracted from the images to be processed. Therefore, the main advantage is that the user does not have to outline the region of interest with a mouse click. In any case, some a priori knowledge about the glottal space is needed, but this a priori knowledge can be considered weak compared to the environmental conditions fixed in former works.

A Sensitivity Study of the Aircraft Vortex Spacing System (AVOSS) Wake Predictor Algorithm to the Resolution of Input Meteorological Profiles

NASA Technical Reports Server (NTRS)

Rutishauser, David K.; Butler, Patrick; Riggins, Jamie

2004-01-01

The AVOSS project demonstrated the feasibility of applying aircraft wake vortex sensing and prediction technologies to safe aircraft spacing for single runway arrivals. On average, AVOSS provided spacing recommendations that were less than the current FAA prescribed spacing rules, resulting in a potential airport efficiency gain. Subsequent efforts have included quantifying the operational specifications for future Wake Vortex Advisory Systems (WakeVAS). In support of these efforts, each of the candidate subsystems for a WakeVAS must be specified. The specifications represent a consensus between the high-level requirements and the capabilities of the candidate technologies. This report documents the beginnings of an effort to quantify the capabilities of the AVOSS Prediction Algorithm (APA). Specifically, the APA horizontal position and circulation strength output sensitivity to the resolution of its wind and turbulence inputs is examined. The results of this analysis have implications for the requirements of the meteorological sensing and prediction systems comprising a WakeVAS implementation.

Using experienced activity spaces to measure foodscape exposure.

PubMed

Kestens, Yan; Lebel, Alexandre; Daniel, Mark; Thériault, Marius; Pampalon, Robert

2010-11-01

Researchers are increasingly interested in understanding how food environments influence eating behavior and weight-related health outcomes. Little is known about the dose-response relationship between foodscapes and behavior or weight, with measures of food exposure having mainly focused on fixed anchor points including residential neighborhoods, schools, or workplaces. Recent calls have been made to extend the consideration of environmental influences beyond local neighborhoods and also to shift away from place-based, to people-based, measures of exposure. This report presents analyses of novel activity-space measures of exposure to foodscapes, combining travel survey data with food store locations in Montreal and Quebec City, Canada. The resulting individual activity-space experienced foodscape exposure measures differ from traditional residential-based measures, and show variations by age and income levels. Furthermore, these activity-space exposure measures once modeled, can be used as predictors of health outcomes. Hence, travel surveys can be used to estimate environmental exposure for health survey participants. Copyright © 2010 Elsevier Ltd. All rights reserved.

Objective Lightning Probability Forecasting for Kennedy Space Center and Cape Canaveral Air Force Station, Phase II

NASA Technical Reports Server (NTRS)

Lambert, Winifred; Wheeler, Mark

2007-01-01

This report describes the work done by the Applied Meteorology Unit (AMU) to update the lightning probability forecast equations developed in Phase I. In the time since the Phase I equations were developed, new ideas regarding certain predictors were formulated and a desire to make the tool more automated was expressed by 45 WS forecasters. Five modifications were made to the data: 1) increased the period of record from 15 to 17 years, 2) modified the valid area to match the lighting warning areas, 3) added the 1000 UTC CCAFS sounding to the other soundings in determining the flow regime, 4) used a different smoothing function for the daily climatology, and 5) determined the optimal relative humidity (RH) layer to use as a predictor. The new equations outperformed the Phase I equations in several tests, and improved the skill of the forecast over the Phase I equations by 8%. A graphical user interface (GUI) was created in the Meteorological Interactive Data Display System (MIDDS) that gathers the predictor values for the equations automatically. The GUI was transitioned to operations in May 2007 for the 2007 warm season.

Fluid reasoning predicts future mathematics among children and adolescents

PubMed Central

Green, Chloe T.; Bunge, Silvia A.; Chiongbian, Victoria Briones; Barrow, Maia; Ferrer, Emilio

2017-01-01

The aim of this longitudinal study was to determine whether fluid reasoning (FR) plays a significant role in the acquisition of mathematics skills, above and beyond the effects of other cognitive and numerical abilities. Using a longitudinal cohort sequential design, we examined how FR measured at three assessment occasions, spaced approximately 1.5 years apart, predicted math outcomes for a group of 69 participants between ages 6 and 21 across all three assessment occasions. We used structural equation modeling (SEM) to examine the direct and indirect relations between children's prior cognitive abilities and their future math achievement. A model including age, FR, vocabulary, and spatial skills accounted for 90% of the variance in future math achievement. In this model, FR was the only significant predictor of future math achievement; neither age, vocabulary, nor spatial skills were significant predictors. Thus, FR was the only predictor of future math achievement across a wide age range that spanned primary and secondary school. These findings build on Cattell's conceptualization of FR (Cattell, 1987) as a scaffold for learning, showing that this domain-general ability supports the acquisition of rudimentary math skills as well as the ability to solve more complex mathematical problems. PMID:28152390

Demographic Predictors of Event-Level Associations between Alcohol Consumption and Sexual Behavior.

PubMed

Wells, Brooke E; Rendina, H Jonathon; Kelly, Brian C; Golub, Sarit A; Parsons, Jeffrey T

2016-02-01

Alcohol consumption is associated with sexual behavior and outcomes, though research indicates a variety of moderating factors, including demographic characteristics. To better target interventions aimed at alcohol-related sexual risk behavior, our analyses simultaneously examine demographic predictors of both day- and event-level associations between alcohol consumption and sexual behavior in a sample of young adults (N = 301) who are sexually active and consume alcohol. Young adults (aged 18-29) recruited using time-space sampling and incentivized snowball sampling completed a survey and a timeline follow-back calendar reporting alcohol consumption and sexual behavior in the past 30 days. On a given day, a greater number of drinks consumed was associated with higher likelihood of sex occurring, particularly for women and single participants. During a given sexual event, number of drinks consumed was not associated with condom use, nor did any demographic predictors predict that association. Findings highlight associations between alcohol and sexual behavior, though not between alcohol and sexual risk behavior, highlighting the need for additional research exploring the complex role of alcohol in sexual risk behavior and the need to develop prevention efforts to minimize the role of alcohol in the initiation of sexual encounters.

Unsupervised classification of operator workload from brain signals.

PubMed

Schultze-Kraft, Matthias; Dähne, Sven; Gugler, Manfred; Curio, Gabriel; Blankertz, Benjamin

2016-06-01

In this study we aimed for the classification of operator workload as it is expected in many real-life workplace environments. We explored brain-signal based workload predictors that differ with respect to the level of label information required for training, including entirely unsupervised approaches. Subjects executed a task on a touch screen that required continuous effort of visual and motor processing with alternating difficulty. We first employed classical approaches for workload state classification that operate on the sensor space of EEG and compared those to the performance of three state-of-the-art spatial filtering methods: common spatial patterns (CSPs) analysis, which requires binary label information; source power co-modulation (SPoC) analysis, which uses the subjects' error rate as a target function; and canonical SPoC (cSPoC) analysis, which solely makes use of cross-frequency power correlations induced by different states of workload and thus represents an unsupervised approach. Finally, we investigated the effects of fusing brain signals and peripheral physiological measures (PPMs) and examined the added value for improving classification performance. Mean classification accuracies of 94%, 92% and 82% were achieved with CSP, SPoC, cSPoC, respectively. These methods outperformed the approaches that did not use spatial filtering and they extracted physiologically plausible components. The performance of the unsupervised cSPoC is significantly increased by augmenting it with PPM features. Our analyses ensured that the signal sources used for classification were of cortical origin and not contaminated with artifacts. Our findings show that workload states can be successfully differentiated from brain signals, even when less and less information from the experimental paradigm is used, thus paving the way for real-world applications in which label information may be noisy or entirely unavailable.

Unsupervised classification of operator workload from brain signals

NASA Astrophysics Data System (ADS)

Schultze-Kraft, Matthias; Dähne, Sven; Gugler, Manfred; Curio, Gabriel; Blankertz, Benjamin

2016-06-01

Objective. In this study we aimed for the classification of operator workload as it is expected in many real-life workplace environments. We explored brain-signal based workload predictors that differ with respect to the level of label information required for training, including entirely unsupervised approaches. Approach. Subjects executed a task on a touch screen that required continuous effort of visual and motor processing with alternating difficulty. We first employed classical approaches for workload state classification that operate on the sensor space of EEG and compared those to the performance of three state-of-the-art spatial filtering methods: common spatial patterns (CSPs) analysis, which requires binary label information; source power co-modulation (SPoC) analysis, which uses the subjects’ error rate as a target function; and canonical SPoC (cSPoC) analysis, which solely makes use of cross-frequency power correlations induced by different states of workload and thus represents an unsupervised approach. Finally, we investigated the effects of fusing brain signals and peripheral physiological measures (PPMs) and examined the added value for improving classification performance. Main results. Mean classification accuracies of 94%, 92% and 82% were achieved with CSP, SPoC, cSPoC, respectively. These methods outperformed the approaches that did not use spatial filtering and they extracted physiologically plausible components. The performance of the unsupervised cSPoC is significantly increased by augmenting it with PPM features. Significance. Our analyses ensured that the signal sources used for classification were of cortical origin and not contaminated with artifacts. Our findings show that workload states can be successfully differentiated from brain signals, even when less and less information from the experimental paradigm is used, thus paving the way for real-world applications in which label information may be noisy or entirely unavailable.

Study of multiple unfolding trajectories and unfolded states of the protein GB1 under the physical property space.

PubMed

Wang, Jihua; Zhao, Liling; Dou, Xianghua; Zhang, Zhiyong

2008-06-01

Forty nine molecular dynamics simulations of unfolding trajectories of the segment B1 of streptococcal protein G (GB1) provide a direct demonstration of the diversity of unfolding pathway and give a statistically utmost unfolding pathway under the physical property space. Twelve physical properties of the protein were chosen to construct a 12-dimensional property space. Then the 12-dimensional property space was reduced to a 3-dimensional principle component property space. Under the property space, the multiple unfolding trajectories look like "trees", which have some common characters. The "root of the tree" corresponds to the native state, the "bole" homologizes the partially unfolded conformations, and the "crown" is in correspondence to the unfolded state. These unfolding trajectories can be divided into three types. The first one has the characters of straight "bole" and "crown" corresponding to a fast two-state unfolding pathway of GB1. The second one has the character of "the standstill in the middle tree bole", which may correspond to a three-state unfolding pathway. The third one has the character of "the circuitous bole" corresponding to a slow two-state unfolding pathway. The fast two-state unfolding pathway is a statistically utmost unfolding pathway or preferred pathway of GB1, which occupies 53% of 49 unfolding trajectories. In the property space all the unfolding trajectories construct a thermal unfolding pathway ensemble of GB1. The unfolding pathway ensemble resembles a funnel that is gradually emanative from the native state ensemble to the unfolded state ensemble. In the property space, the thermal unfolded state distribution looks like electronic cloud in quantum mechanics. The unfolded states of the independent unfolding simulation trajectories have substantial overlaps, indicating that the thermal unfolded states are confined by the physical property values, and the number of protein unfolded state are much less than that was believed before.

Determinants of individual and group performance

NASA Technical Reports Server (NTRS)

Helmreich, Robert L.

1986-01-01

A broad exploration of individual and group/organizational factors that influence performance in demanding environments such as space and air transport was undertaken. Primary efforts were directed toward defining critical issues, developing new methodologies for the assessment of performance in such environments, and developing new measures of personality and attitudes as predictors of performance. Substantial clarification of relevant issues for research and validation was achieved. A reliable instrument to assess crewmembers' attitudes regarding crew coordination and flightdeck management was validated. Major efforts in data collection to validate concepts were initiated. The results suggest that substantial improvements can be made in the prediction of performance and in the selection of crewmembers for aviation and space.

Correction of defective pixels for medical and space imagers based on Ising Theory

NASA Astrophysics Data System (ADS)

Cohen, Eliahu; Shnitser, Moriel; Avraham, Tsvika; Hadar, Ofer

2014-09-01

We propose novel models for image restoration based on statistical physics. We investigate the affinity between these fields and describe a framework from which interesting denoising algorithms can be derived: Ising-like models and simulated annealing techniques. When combined with known predictors such as Median and LOCO-I, these models become even more effective. In order to further examine the proposed models we apply them to two important problems: (i) Digital Cameras in space damaged from cosmic radiation. (ii) Ultrasonic medical devices damaged from speckle noise. The results, as well as benchmark and comparisons, suggest in most of the cases a significant gain in PSNR and SSIM in comparison to other filters.

The effects of natural disturbances, reef state, and herbivorous fish densities on ciguatera poisoning in Rarotonga, southern Cook Islands.

PubMed

Rongo, Teina; van Woesik, Robert

2013-03-15

Ciguatera poisoning is a critical public-health issue among Pacific island nations. Accurately predicting ciguatera outbreaks has become a priority, particularly in Rarotonga in the southern Cook Islands, which has reported the highest incidence of ciguatera poisoning globally. Since 2006, however, cases of ciguatera poisoning have declined, and in 2011 ciguatera cases were the lowest in nearly 20 years. Here we examined the relationships between cases of ciguatera poisoning, from 1994 to 2011, and: (i) coral cover, used as a proxy of reef state, (ii) the densities of herbivorous fishes, and (iii) reef disturbances. We found that coral cover was not a good predictor of cases of ciguatera poisoning, but high densities of the herbivorous fish Ctenochaetus striatus and reef disturbances were both strong predictors of ciguatera poisoning. Yet these two predictors were correlated, because the densities of C. striatus increased only after major cyclones had disturbed the reefs. Since 2006, the number of cyclones has decreased considerably in Rarotonga, because of the climatic shift toward the negative phase of the Pacific Decadal Oscillation. We suggest that fewer cyclones have led to decreases in both the densities of C. striatus and of the number of reported cases of ciguatera poisoning in Rarotonga. Copyright © 2013 Elsevier Ltd. All rights reserved.

Catchment-scale determinants of nonindigenous minnow richness in the eastern United States

USGS Publications Warehouse

Peoples, Brandon K.; Midway, Stephen R.; DeWeber, Jefferson T.; Wagner, Tyler

2018-01-01

Understanding the drivers of biological invasions is critical for preserving aquatic biodiversity. Stream fishes make excellent model taxa for examining mechanisms driving species introduction success because their distributions are naturally limited by catchment boundaries. In this study, we compared the relative importance of catchment-scale abiotic and biotic predictors of native and nonindigenous minnow (Cyprinidae) richness in 170 catchments throughout the eastern United States. We compared historic and contemporary cyprinid distributional data to determine catchment-wise native/nonindigenous status for 152 species. Catchment-scale model predictor variables described natural (elevation, precipitation, flow accumulation) and anthropogenic (developed land cover, number of dams) abiotic features, as well as native congener richness. Native congener richness may represent either biotic resistance via interspecific competition, or trait preadaptation according to Darwin's naturalisation hypothesis. We used generalised linear mixed models to examine evidence supporting the relative roles of abiotic and biotic predictors of cyprinid introduction success. Native congener richness was positively correlated with nonindigenous cyprinid richness and was the most important variable predicting nonindigenous cyprinid richness. Mean elevation had a weak positive effect, and effects of other abiotic factors were insignificant and less important. Our results suggest that at this spatial scale, trait preadaptation may be more important than intrageneric competition for determining richness of nonindigenous fishes.

Relationship between college success and employer competency ratings for graduates of a baccalaureate nursing program.

PubMed

Bolin, S E; Hogle, E L

1984-01-01

This expost facto correlational study sought to determine which measures of academic success in one class of BSN graduates predicted their competence as employees one year after graduation, as judged by their employers. The relationship between pre-entrance test scores, clinical experience grades, GPA, State Board Test Pool examination scores, and employer competency ratings were also determined. In keeping with the literature in fields other than nursing, the findings suggest that there may be little relationship between academic performance in a nursing program and subsequent job performance as a nurse, even though verbal ability may be predictive of success in school. While significant positive correlations were found between pre-entrance test data and final grade point averages, as well as pre-entrance test scores and State Board Test Pool examination scores, there was little evidence that pre-entrance test scores were predictive of nursing abilities. Isolated correlations were found between the clinical components of some nursing courses and specific nursing abilities. Using multiple regression analysis, no clinical course grade was found to be a significant predictor of the mean employer competency rating. Significant predictors were found for only four of the individual nursing abilities, with the clinical component of Leadership in Nursing being the most frequent and best predictor.

DHSpred: support-vector-machine-based human DNase I hypersensitive sites prediction using the optimal features selected by random forest.

PubMed

Manavalan, Balachandran; Shin, Tae Hwan; Lee, Gwang

2018-01-05

DNase I hypersensitive sites (DHSs) are genomic regions that provide important information regarding the presence of transcriptional regulatory elements and the state of chromatin. Therefore, identifying DHSs in uncharacterized DNA sequences is crucial for understanding their biological functions and mechanisms. Although many experimental methods have been proposed to identify DHSs, they have proven to be expensive for genome-wide application. Therefore, it is necessary to develop computational methods for DHS prediction. In this study, we proposed a support vector machine (SVM)-based method for predicting DHSs, called DHSpred (DNase I Hypersensitive Site predictor in human DNA sequences), which was trained with 174 optimal features. The optimal combination of features was identified from a large set that included nucleotide composition and di- and trinucleotide physicochemical properties, using a random forest algorithm. DHSpred achieved a Matthews correlation coefficient and accuracy of 0.660 and 0.871, respectively, which were 3% higher than those of control SVM predictors trained with non-optimized features, indicating the efficiency of the feature selection method. Furthermore, the performance of DHSpred was superior to that of state-of-the-art predictors. An online prediction server has been developed to assist the scientific community, and is freely available at: http://www.thegleelab.org/DHSpred.html.

Climate drives inter-annual variability in probability of high severity fire occurrence in the western United States

NASA Astrophysics Data System (ADS)

Keyser, Alisa; Westerling, Anthony LeRoy

2017-05-01

A long history of fire suppression in the western United States has significantly changed forest structure and ecological function, leading to increasingly uncharacteristic fires in terms of size and severity. Prior analyses of fire severity in California forests showed that time since last fire and fire weather conditions predicted fire severity very well, while a larger regional analysis showed that topography and climate were important predictors of high severity fire. There has not yet been a large-scale study that incorporates topography, vegetation and fire-year climate to determine regional scale high severity fire occurrence. We developed models to predict the probability of high severity fire occurrence for the western US. We predict high severity fire occurrence with some accuracy, and identify the relative importance of predictor classes in determining the probability of high severity fire. The inclusion of both vegetation and fire-year climate predictors was critical for model skill in identifying fires with high fractional fire severity. The inclusion of fire-year climate variables allows this model to forecast inter-annual variability in areas at future risk of high severity fire, beyond what slower-changing fuel conditions alone can accomplish. This allows for more targeted land management, including resource allocation for fuels reduction treatments to decrease the risk of high severity fire.

DHSpred: support-vector-machine-based human DNase I hypersensitive sites prediction using the optimal features selected by random forest

PubMed Central

Manavalan, Balachandran; Shin, Tae Hwan; Lee, Gwang

2018-01-01

DNase I hypersensitive sites (DHSs) are genomic regions that provide important information regarding the presence of transcriptional regulatory elements and the state of chromatin. Therefore, identifying DHSs in uncharacterized DNA sequences is crucial for understanding their biological functions and mechanisms. Although many experimental methods have been proposed to identify DHSs, they have proven to be expensive for genome-wide application. Therefore, it is necessary to develop computational methods for DHS prediction. In this study, we proposed a support vector machine (SVM)-based method for predicting DHSs, called DHSpred (DNase I Hypersensitive Site predictor in human DNA sequences), which was trained with 174 optimal features. The optimal combination of features was identified from a large set that included nucleotide composition and di- and trinucleotide physicochemical properties, using a random forest algorithm. DHSpred achieved a Matthews correlation coefficient and accuracy of 0.660 and 0.871, respectively, which were 3% higher than those of control SVM predictors trained with non-optimized features, indicating the efficiency of the feature selection method. Furthermore, the performance of DHSpred was superior to that of state-of-the-art predictors. An online prediction server has been developed to assist the scientific community, and is freely available at: http://www.thegleelab.org/DHSpred.html PMID:29416743

Optimism predicts positive health in repatriated prisoners of war.

PubMed

Segovia, Francine; Moore, Jeffrey L; Linnville, Steven E; Hoyt, Robert E

2015-05-01

"Positive health," defined as a state beyond the mere absence of disease, was used as a model to examine factors for enhancing health despite extreme trauma. The study examined the United States' longest detained American prisoners of war, those held in Vietnam in the 1960s through early 1970s. Positive health was measured using a physical and a psychological composite score for each individual, based on 9 physical and 9 psychological variables. Physical and psychological health was correlated with optimism obtained postrepatriation (circa 1973). Linear regressions were employed to determine which variables contributed most to health ratings. Optimism was the strongest predictor of physical health (β = -.33, t = -2.73, p = .008), followed by fewer sleep complaints (β = -.29, t = -2.52, p = .01). This model accounted for 25% of the variance. Optimism was also the strongest predictor of psychological health (β = -.41, t = -2.87, p = .006), followed by Minnesota Multiphasic Personality Inventory-Psychopathic Deviate (MMPI-PD; McKinley & Hathaway, 1944) scores (β = -.23, t = -1.88, p = .07). This model strongly suggests that optimism is a significant predictor of positive physical and psychological health, and optimism also provides long-term protective benefits. These findings and the utility of this model suggest a promising area for future research and intervention. (c) 2015 APA, all rights reserved).

Stochastic state-space temperature regulation of biochar production. Part I: Theoretical development.

PubMed

Cantrell, Keri B; Martin, Jerry H

2012-02-01

The concept of a designer biochar that targets the improvement of a specific soil property imposes the need for production processes to generate biochars with both high consistency and quality. These important production parameters can be affected by variations in process temperature that must be taken into account when controlling the pyrolysis of agricultural residues such as manures and other feedstocks. A novel stochastic state-space temperature regulator was developed to accurately match biochar batch production to a defined temperature input schedule. This was accomplished by describing the system's state-space with five temperature variables--four directly measured and one change in temperature. Relationships were derived between the observed state and the desired, controlled state. When testing the unit at two different temperatures, the actual pyrolytic temperature was within 3 °C of the control with no overshoot. This state-space regulator simultaneously controlled the indirect heat source and sample temperature by employing difficult-to-measure variables such as temperature stability in the description of the pyrolysis system's state-space. These attributes make a state-space controller an optimum control scheme for the production of a predictable, repeatable designer biochar. Published 2011 by John Wiley & Sons, Ltd.

Guarded self-disclosure predicts psychological distress and willingness to use psychological services among East Asian immigrants in the United States.

PubMed

Barry, Declan T; Mizrahi, Trina C

2005-08-01

This study examined the relationship between guarded self-disclosure, psychological distress, and willingness to use psychological services if distressed among 170 (88 male, 82 female) East Asian immigrants in the United States. Participants were administered a battery of psychometrically established measures. Participants who endorsed overall guarded self-disclosure, self-concealment (i.e., unwillingness to reveal affect to others), or conflict avoidance (i.e., maintenance of harmony via suppression of feelings) were significantly more likely to report psychological distress and were significantly less likely to report willingness to use psychological services. While conflict avoidance was a significant independent predictor of psychological distress, self-concealment was a significant independent predictor of willingness to use psychological services. These findings point to the importance of assessing multiple facets of guarded self-disclosure, which appear to be differentially associated with psychological distress and willingness to use psychological services.

Predictive factors of excessive online poker playing.

PubMed

Hopley, Anthony A B; Nicki, Richard M

2010-08-01

Despite the widespread rise of online poker playing, there is a paucity of research examining potential predictors for excessive poker playing. The aim of this study was to build on recent research examining motives for Texas Hold'em play in students by determining whether predictors of other kinds of excessive gambling apply to Texas Hold'em. Impulsivity, negative mood states, dissociation, and boredom proneness have been linked to general problem gambling and may play a role in online poker. Participants of this study were self-selected online poker players (N = 179) who completed an online survey. Results revealed that participants played an average of 20 hours of online poker a week and approximately 9% of the sample was classified as a problem gambler according to the Canadian Problem Gambling Index. Problem gambling, in this sample, was uniquely predicted by time played, dissociation, boredom proneness, impulsivity, and negative affective states, namely depression, anxiety, and stress.

Predictors of treatment use among foster mothers in an attachment-based intervention program.

PubMed

Bick, Johanna; Dozier, Mary; Moore, Shannon

2012-01-01

The current study examined predictors of treatment use among 56 foster mothers who participated in an attachment-based intervention program for foster infants. Foster mothers' levels of treatment use were coded at early, middle, and late phases of the intervention program. Foster mothers' states of mind with regard to attachment predicted their understanding of the intervention session concepts. Specifically, autonomous foster mothers showed higher levels of understanding at the start of the intervention program, when compared with non-autonomous foster mothers. State of mind with regard to attachment also predicted foster mothers' levels of reflective functioning during the intervention sessions. Autonomous foster mothers showed higher levels of reflective functioning at early, middle, and late stages of the intervention program, when compared with non-autonomous foster mothers. The relevance of these findings for both treatment effectiveness and treatment delivery is discussed.

State-by-state variations in cardiac rehabilitation participation are associated with educational attainment, income, and program availability.

PubMed

Gaalema, Diann E; Higgins, Stephen T; Shepard, Donald S; Suaya, Jose A; Savage, Patrick D; Ades, Philip A

2014-01-01

Wide geographic variations in cardiac rehabilitation (CR) participation in the United States have been demonstrated but are not well understood. Socioeconomic factors such as educational attainment are robust predictors of many health-related behaviors, including smoking, obesity, physical activity, substance abuse, and cardiovascular disease. We investigated potential associations between state-level differences in educational attainment, other socioeconomic factors, CR program availability, and variations in CR participation. A retrospective database analysis was conducted using data from the US Census Bureau, the Centers for Disease Control and Prevention, and the 1997 Medicare database. The outcome of interest was CR participation rates by state, and predictors included state-level high school (HS) graduation rates (in 2001 and 1970), median household income, smoking rates, density of CR program (programs per square mile and per state population), sex and race ratios, and median age. The relationship between HS graduation rates and CR participation by state was significant for both 2001 and 1970 (r = 0.64 and 0.44, respectively, P < .01). Adding the density of CR programs (per population) and income contributed significantly with a cumulative r value of 0.74 and 0.71 for the models using 2001 and 1970, respectively (Ps < .01). The amount of variance accounted for by each of the 3 variables differed between the 2000 and 1970 graduation rates, but both models were unaltered by including additional variables. State-level HS graduation rates, CR programs expressed as programs per population, and median income were strongly associated with geographic variations in CR participation rates.

Violence exposure and teen dating violence among African American youth.

PubMed

Black, Beverly M; Chido, Lisa M; Preble, Kathleen M; Weisz, Arlene N; Yoon, Jina S; Delaney-Black, Virginia; Kernsmith, Poco; Lewandowski, Linda

2015-07-01

This study examines the relationships between exposure to violence in the community, school, and family with dating violence attitudes and behaviors among 175 urban African American youth. Age, gender, state support and experiences with neglect, school violence, and community violence were the most significant predictors of acceptance of dating violence. Experiences with community violence and age were important predictors of dating violence perpetration and victimization. Findings highlight the importance of planning prevention programs that address variables affecting attitudes and behaviors of high-risk youth who have already been exposed to multiple types of violence. © The Author(s) 2014.

On the importance of an accurate representation of the initial state of the system in classical dynamics simulations

NASA Astrophysics Data System (ADS)

García-Vela, A.

2000-05-01

A definition of a quantum-type phase-space distribution is proposed in order to represent the initial state of the system in a classical dynamics simulation. The central idea is to define an initial quantum phase-space state of the system as the direct product of the coordinate and momentum representations of the quantum initial state. The phase-space distribution is then obtained as the square modulus of this phase-space state. The resulting phase-space distribution closely resembles the quantum nature of the system initial state. The initial conditions are sampled with the distribution, using a grid technique in phase space. With this type of sampling the distribution of initial conditions reproduces more faithfully the shape of the original phase-space distribution. The method is applied to generate initial conditions describing the three-dimensional state of the Ar-HCl cluster prepared by ultraviolet excitation. The photodissociation dynamics is simulated by classical trajectories, and the results are compared with those of a wave packet calculation. The classical and quantum descriptions are found in good agreement for those dynamical events less subject to quantum effects. The classical result fails to reproduce the quantum mechanical one for the more strongly quantum features of the dynamics. The properties and applicability of the phase-space distribution and the sampling technique proposed are discussed.

State-Space Formulation for Circuit Analysis

ERIC Educational Resources Information Center

Martinez-Marin, T.

2010-01-01

This paper presents a new state-space approach for temporal analysis of electrical circuits. The method systematically obtains the state-space formulation of nondegenerate linear networks without using concepts of topology. It employs nodal/mesh systematic analysis to reduce the number of undesired variables. This approach helps students to…

Geometric state space uncertainty as a new type of uncertainty addressing disparity in ';emergent properties' between real and modeled systems

NASA Astrophysics Data System (ADS)

Montero, J. T.; Lintz, H. E.; Sharp, D.

2013-12-01

Do emergent properties that result from models of complex systems match emergent properties from real systems? This question targets a type of uncertainty that we argue requires more attention in system modeling and validation efforts. We define an ';emergent property' to be an attribute or behavior of a modeled or real system that can be surprising or unpredictable and result from complex interactions among the components of a system. For example, thresholds are common across diverse systems and scales and can represent emergent system behavior that is difficult to predict. Thresholds or other types of emergent system behavior can be characterized by their geometry in state space (where state space is the space containing the set of all states of a dynamic system). One way to expedite our growing mechanistic understanding of how emergent properties emerge from complex systems is to compare the geometry of surfaces in state space between real and modeled systems. Here, we present an index (threshold strength) that can quantify a geometric attribute of a surface in state space. We operationally define threshold strength as how strongly a surface in state space resembles a step or an abrupt transition between two system states. First, we validated the index for application in greater than three dimensions of state space using simulated data. Then, we demonstrated application of the index in measuring geometric state space uncertainty between a real system and a deterministic, modeled system. In particular, we looked at geometric space uncertainty between climate behavior in 20th century and modeled climate behavior simulated by global climate models (GCMs) in the Coupled Model Intercomparison Project phase 5 (CMIP5). Surfaces from the climate models came from running the models over the same domain as the real data. We also created response surfaces from a real, climate data based on an empirical model that produces a geometric surface of predicted values in state space. We used a kernel regression method designed to capture the geometry of real data pattern without imposing shape assumptions a priori on the data; this kernel regression method is known as Non-parametric Multiplicative Regression (NPMR). We found that quantifying and comparing a geometric attribute in more than three dimensions of state space can discern whether the emergent nature of complex interactions in modeled systems matches that of real systems. Further, this method has potentially wider application in contexts where searching for abrupt change or ';action' in any hyperspace is desired.

Statistical Models for Tornado Climatology: Long and Short-Term Views.

PubMed

Elsner, James B; Jagger, Thomas H; Fricker, Tyler

2016-01-01

This paper estimates regional tornado risk from records of past events using statistical models. First, a spatial model is fit to the tornado counts aggregated in counties with terms that control for changes in observational practices over time. Results provide a long-term view of risk that delineates the main tornado corridors in the United States where the expected annual rate exceeds two tornadoes per 10,000 square km. A few counties in the Texas Panhandle and central Kansas have annual rates that exceed four tornadoes per 10,000 square km. Refitting the model after removing the least damaging tornadoes from the data (EF0) produces a similar map but with the greatest tornado risk shifted south and eastward. Second, a space-time model is fit to the counts aggregated in raster cells with terms that control for changes in climate factors. Results provide a short-term view of risk. The short-term view identifies a shift of tornado activity away from the Ohio Valley under El Niño conditions and away from the Southeast under positive North Atlantic oscillation conditions. The combined predictor effects on the local rates is quantified by fitting the model after leaving out the year to be predicted from the data. The models provide state-of-the-art views of tornado risk that can be used by government agencies, the insurance industry, and the general public.

Statistical Models for Tornado Climatology: Long and Short-Term Views

PubMed Central

Jagger, Thomas H.; Fricker, Tyler

2016-01-01

This paper estimates regional tornado risk from records of past events using statistical models. First, a spatial model is fit to the tornado counts aggregated in counties with terms that control for changes in observational practices over time. Results provide a long-term view of risk that delineates the main tornado corridors in the United States where the expected annual rate exceeds two tornadoes per 10,000 square km. A few counties in the Texas Panhandle and central Kansas have annual rates that exceed four tornadoes per 10,000 square km. Refitting the model after removing the least damaging tornadoes from the data (EF0) produces a similar map but with the greatest tornado risk shifted south and eastward. Second, a space-time model is fit to the counts aggregated in raster cells with terms that control for changes in climate factors. Results provide a short-term view of risk. The short-term view identifies a shift of tornado activity away from the Ohio Valley under El Niño conditions and away from the Southeast under positive North Atlantic oscillation conditions. The combined predictor effects on the local rates is quantified by fitting the model after leaving out the year to be predicted from the data. The models provide state-of-the-art views of tornado risk that can be used by government agencies, the insurance industry, and the general public. PMID:27875581

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.

Non-neutralized Electric Currents in Solar Active Regions and Flare Productivity

NASA Astrophysics Data System (ADS)

Kontogiannis, Ioannis; Georgoulis, Manolis K.; Park, Sung-Hong; Guerra, Jordan A.

2017-11-01

We explore the association of non-neutralized currents with solar flare occurrence in a sizable sample of observations, aiming to show the potential of such currents in solar flare prediction. We used the high-quality vector magnetograms that are regularly produced by the Helioseismic Magnetic Imager, and more specifically, the Space weather HMI Active Region Patches (SHARP). Through a newly established method that incorporates detailed error analysis, we calculated the non-neutralized currents contained in active regions (AR). Two predictors were produced, namely the total and the maximum unsigned non-neutralized current. Both were tested in AR time-series and a representative sample of point-in-time observations during the interval 2012 - 2016. The average values of non-neutralized currents in flaring active regions are higher by more than an order of magnitude than in non-flaring regions and correlate very well with the corresponding flare index. The temporal evolution of these parameters appears to be connected to physical processes, such as flux emergence and/or magnetic polarity inversion line formation, that are associated with increased solar flare activity. Using Bayesian inference of flaring probabilities, we show that the total unsigned non-neutralized current significantly outperforms the total unsigned magnetic flux and other well-established current-related predictors. It therefore shows good prospects for inclusion in an operational flare-forecasting service. We plan to use the new predictor in the framework of the FLARECAST project along with other highly performing predictors.

Fact Sheet: National Space Policy. Appendix F-2

NASA Technical Reports Server (NTRS)

1996-01-01

For over three decades, the United States has led the world in the exploration and use of outer space. Our achievements in space have inspired a generation of Americans and people throughout the world. We will maintain this leadership role by supporting a strong, stable, and balanced national space program that serves our goals in national security, foreign policy, economic growth, environmental stewardship, and scientific and technical excellence. Access to and use of space are central for preserving peace and protecting US national security as well as civil and commercial interests. The United States will pursue greater levels of partnership and cooperation in national and international space activities and work with other nations to ensure the continued exploration and use of outer space for peaceful purposes. The goals of the US space program are to: (a) Enhance knowledge of the Earth, the solar system, and the universe through human and robotic exploration; (b) Strengthen and maintain the national security of the United States; (c) Enhance the economic competitiveness and scientific and technical capabilities of the United States; (d) Encourage State, local, and private sector investment in, and use of, space technologies; (e) Promote international cooperation to further US domestic, national security, and foreign policies. The United States is committed to the exploration and use of outer space by all nations for peaceful purposes and for the benefit of all humanity. "Peaceful purposes" allow defense and intelligence-related activities in pursuit of national security and other goals. The United States rejects any claims to sovereignty by any nation over outer space or celestial bodies, or any portion thereof, and rejects any limitations on the fundamental right of sovereign nations to acquire data from space. The United States considers the space systems of any nation to be national property with the right of passage through and operations in space without interference. Purposeful interference with space systems shall be viewed as an infringement on sovereign rights. The US Government will maintain and coordinate separate national security and civil space systems where differing needs dictate. All actions undertaken by agencies and departments in implementing the national space policy shall be consistent with US law, regulations, national security requirements, foreign policy, international obligations, and nonproliferation policy. The National Science and Technology Council (NSTC) is the principal forum for resolving issues related to national space policy. As appropriate, the NSTC and NSC will co-chair policy process. This policy will be implemented within the overall resource and policy guidance provided by the President.

Network influences on dissemination of evidence-based guidelines in state tobacco control programs.

PubMed

Luke, Douglas A; Wald, Lana M; Carothers, Bobbi J; Bach, Laura E; Harris, Jenine K

2013-10-01

Little is known regarding the social network relationships that influence dissemination of evidence-based public health practices and policies. In public health, it is critical that evidence-based guidelines, such as the Centers for Disease Control and Prevention's Best Practices for Comprehensive Tobacco Control Programs, are effectively and efficiently disseminated to intended stakeholders. To determine the organizational and network predictors of dissemination among state tobacco control programs, interviews with members of tobacco control networks across eight states were conducted between August 2009 and September 2010. Measures included partner attributes (e.g., agency type) and relationships among network members (frequency of contact, extent of collaboration, and dissemination of Best Practices). Exponential random graph modeling was used to examine attribute and structural predictors of collaboration and dissemination among partners in each network. Although density and centralization of dissemination ties varied across states, network analyses revealed a consistent prediction pattern across all eight states. State tobacco control dissemination networks were less dense but more centralized compared with organizational contact and collaboration networks. Tobacco control partners in each state were more likely to disseminate the Best Practices guidelines if they also had existing contact and collaboration relationships with one another. Evidence-based guidelines in public health need to be efficiently and broadly disseminated if we hope to translate science into practice. This study suggests that funders, advocacy groups, and public health agencies can take advantage of existing public health organizational relationships to support the communication and dissemination of evidence-based practices and policies.

A structural equation model of turnover for a longitudinal survey among early career registered nurses.

PubMed

Brewer, Carol S; Chao, Ying-Yu; Colder, Craig R; Kovner, Christine T; Chacko, Thomas P

2015-11-01

Key predictors of early career nurses' turnover are job satisfaction, organizational commitment, job search, intent to stay, and shock (back injuries) based on the literature review and our previous research. Existing research has often omitted one of these key predictors. The purpose of this study in a sample of early career nurses was to compare predictors of turnover to nurses' actual turnover at two time points in their careers. A multi-state longitudinal panel survey of early career nurses was used to compare a turnover model across two time periods. The sample has been surveyed five times. The sample was selected using a two-stage sample of registered nurses nested in 51 metropolitan areas and nine non-metropolitan, rural areas in 34 states and the District of Columbia. The associations between key predictors of turnover were tested using structural equation modeling and data from the earliest and latest panels in our study. We used predictors from the respondents who replied to the Wave-1 survey in 2006 and their turnover status from Wave 2 in 2007 (N=2386). We compared these results to the remaining respondents' predictors from Wave 4 in 2011 and their turnover status in Wave 5 in 2013 (N=1073). We tested and found no effect for missingness from Wave 1-5 and little evidence of attrition bias. Strong support was found for the relationships hypothesized among job satisfaction, organizational commitment, intent to stay, and turnover, with some support for shock and search in the Wave 1-2 sample. However, for Wave 4-5 sample (n=1073), none of the paths through search were significant, nor was the path from shock to turnover. Nurses in the second analysis who had matured longer in their career did not have a significant response to search or shock (back injuries), which may indicate how easily experienced registered nurses find new jobs and/or accommodation to jobs requiring significant physicality. Nurse turnover is a major concern for healthcare organizations because of its costs and related outcomes. The relevant strength and relationships of these key turnover predictors will be informative to employers for prioritizing strategies to retain their registered nurse workforce. We need more research on programs that implement changes in the work environment that impact these two outcomes, as well as research that focuses on the relevant strength or impact to help administrators prioritize translation of results. Copyright © 2015 Elsevier Ltd. All rights reserved.

KENNEDY SPACE CENTER, FLA. - The Space Life Sciences Lab (SLSL), formerly known as the Space Experiment Research and Processing Laboratory (SERPL), is nearing completion. The new lab is a state-of-the-art facility being built for ISS biotechnology research. Developed as a partnership between NASA-KSC and the State of Florida, NASA’s life sciences contractor will be the primary tenant of the facility, leasing space to conduct flight experiment processing and NASA-sponsored research. About 20 percent of the facility will be available for use by Florida’s university researchers through the Florida Space Research Institute.

NASA Image and Video Library

2003-09-10

KENNEDY SPACE CENTER, FLA. - The Space Life Sciences Lab (SLSL), formerly known as the Space Experiment Research and Processing Laboratory (SERPL), is nearing completion. The new lab is a state-of-the-art facility being built for ISS biotechnology research. Developed as a partnership between NASA-KSC and the State of Florida, NASA’s life sciences contractor will be the primary tenant of the facility, leasing space to conduct flight experiment processing and NASA-sponsored research. About 20 percent of the facility will be available for use by Florida’s university researchers through the Florida Space Research Institute.

Health Care Reform: Understanding Individuals' Attitudes and Information Sources

PubMed Central

Shue, Carolyn K.; McGeary, Kerry Anne; Reid, Ian; Fan, Maoyong

2014-01-01

Since passage of the Affordable Care Act (ACA) was signed into law by President Barrack Obama, little is known about state-level perceptions of residents on the ACA. Perceptions about the act could potentially affect implementation of the law to the fullest extent. This 3-year survey study explored attitudes about the ACA, the types of information sources that individuals rely on when creating those attitudes, and the predictors of these attitudes among state of Indiana residents. The respondents were split between favorable and unfavorable views of the ACA, yet the majority of respondents strongly supported individual components of the act. National TV news, websites, family members, and individuals' own reading of the ACA legislation were identified as the most influential information sources. After controlling for potential confounders, the respondent's political affiliation, age, sex, and obtaining ACA information from watching national television news were the most important predictors of attitudes about the ACA and its components. These results mirror national-level findings. Implications for implementing health care reform at the state-level are discussed. PMID:25045705

Race, deprivation, and immigrant isolation: The spatial demography of air-toxic clusters in the continental United States.

PubMed

Liévanos, Raoul S

2015-11-01

This article contributes to environmental inequality outcomes research on the spatial and demographic factors associated with cumulative air-toxic health risks at multiple geographic scales across the United States. It employs a rigorous spatial cluster analysis of census tract-level 2005 estimated lifetime cancer risk (LCR) of ambient air-toxic emissions from stationary (e.g., facility) and mobile (e.g., vehicular) sources to locate spatial clusters of air-toxic LCR risk in the continental United States. It then tests intersectional environmental inequality hypotheses on the predictors of tract presence in air-toxic LCR clusters with tract-level principal component factor measures of economic deprivation by race and immigrant status. Logistic regression analyses show that net of controls, isolated Latino immigrant-economic deprivation is the strongest positive demographic predictor of tract presence in air-toxic LCR clusters, followed by black-economic deprivation and isolated Asian/Pacific Islander immigrant-economic deprivation. Findings suggest scholarly and practical implications for future research, advocacy, and policy. Copyright © 2015 Elsevier Inc. All rights reserved.

Work engagement and its predictors in registered nurses: A cross-sectional design.

PubMed

Wan, Qiaoqin; Zhou, Weijiao; Li, Zhaoyang; Shang, Shaomei; Yu, Fang

2018-04-23

Nurses are key staff members of health-care organizations. Nurse engagement directly influences quality of care and organizational performance. The purpose of the present study was to understand the state of work engagement and explore its predictors among registered nurses in China by using a descriptive, cross-sectional survey design (n = 1065). Work engagement was measured with the Chinese version of the Utrecht Work Engagement Scale. The results showed that the average work engagement of Chinese nurses was 3.54 (standard deviation = 1.49), and that nurses' age (β = .16, t = 5.32), job characteristics (β = .33, t = 9.43), and practice environment (β = .23, t = 6.59) were significant predictors of work engagement. Thus, nurse leaders should be encouraged to shape motivational job characteristics and create supportive practice environment so as to increase nurses' work engagement. © 2018 John Wiley & Sons Australia, Ltd.

Illicit substance use among adolescents: a matrix of prospective predictors.

PubMed

Petraitis, J; Flay, B R; Miller, T Q; Torpy, E J; Greiner, B

1998-11-01

This paper reviews findings from 58 prospective studies of illicit substance use (ISU) among adolescents. It arranges 384 findings according to three types of influence (viz., social, attitudinal, and intrapersonal) and four levels of influence (viz., ultimate, distal, proximal, and immediate). The bulk of evidence reconfirms the importance of several predictors of ISU (e.g., intentions and prior substance-related behavior, friendship patterns and peer behaviors, absence of supportive parents, psychological temperament), reveals that a few variables thought to be well-established predictors may not be (e.g., parental behaviors, parental permissiveness, depression, low self-esteem), and uncovers several variables where findings were either sparse or inconsistent (e.g., the role of public policies concerning ISU, mass media depictions of ISU, certain parenting styles, affective states, perceptions of parental disapproval for ISU, and substance-specific refusal skills). Directions for future research are discussed.

Space Commercialization

NASA Technical Reports Server (NTRS)

Martin, Gary L.

2011-01-01

A robust and competitive commercial space sector is vital to continued progress in space. The United States is committed to encouraging and facilitating the growth of a U.S. commercial space sector that supports U.S. needs, is globally competitive, and advances U.S. leadership in the generation of new markets and innovation-driven entrepreneurship. Energize competitive domestic industries to participate in global markets and advance the development of: satellite manufacturing; satellite-based services; space launch; terrestrial applications; and increased entrepreneurship. Purchase and use commercial space capabilities and services to the maximum practical extent Actively explore the use of inventive, nontraditional arrangements for acquiring commercial space goods and services to meet United States Government requirements, including measures such as public-private partnerships, . Refrain from conducting United States Government space activities that preclude, discourage, or compete with U.S. commercial space activities. Pursue potential opportunities for transferring routine, operational space functions to the commercial space sector where beneficial and cost-effective.

Neural correlates of establishing, maintaining, and switching brain states

PubMed Central

Tang, Yi-Yuan; Rothbart, Mary K.; Posner, Michael I.

2012-01-01

Although the study of brain states is an old one in neuroscience, there has been growing interest in brain state specification owing to MRI studies tracing brain connectivity at rest. In this review, we summarize recent research on three relatively well-described brain states: the resting, alert, and meditation states. We explore the neural correlates of maintaining a state or switching between states, and argue that the anterior cingulate cortex and striatum play a critical role in state maintenance, whereas the insula has a major role in switching between states. Brain state may serve as a predictor of performance in a variety of perceptual, memory, and problem solving tasks. Thus, understanding brain states is critical for understanding human performance. PMID:22613871

Handy elementary algebraic properties of the geometry of entanglement

NASA Astrophysics Data System (ADS)

Blair, Howard A.; Alsing, Paul M.

2013-05-01

The space of separable states of a quantum system is a hyperbolic surface in a high dimensional linear space, which we call the separation surface, within the exponentially high dimensional linear space containing the quantum states of an n component multipartite quantum system. A vector in the linear space is representable as an n-dimensional hypermatrix with respect to bases of the component linear spaces. A vector will be on the separation surface iff every determinant of every 2-dimensional, 2-by-2 submatrix of the hypermatrix vanishes. This highly rigid constraint can be tested merely in time asymptotically proportional to d, where d is the dimension of the state space of the system due to the extreme interdependence of the 2-by-2 submatrices. The constraint on 2-by-2 determinants entails an elementary closed formformula for a parametric characterization of the entire separation surface with d-1 parameters in the char- acterization. The state of a factor of a partially separable state can be calculated in time asymptotically proportional to the dimension of the state space of the component. If all components of the system have approximately the same dimension, the time complexity of calculating a component state as a function of the parameters is asymptotically pro- portional to the time required to sort the basis. Metric-based entanglement measures of pure states are characterized in terms of the separation hypersurface.

Quantization of Space-like States in Lorentz-Violating Theories

NASA Astrophysics Data System (ADS)

Colladay, Don

2018-01-01

Lorentz violation frequently induces modified dispersion relations that can yield space-like states that impede the standard quantization procedures. In certain cases, an extended Hamiltonian formalism can be used to define observer-covariant normalization factors for field expansions and phase space integrals. These factors extend the theory to include non-concordant frames in which there are negative-energy states. This formalism provides a rigorous way to quantize certain theories containing space-like states and allows for the consistent computation of Cherenkov radiation rates in arbitrary frames and avoids singular expressions.

National directory of space grant contacts

NASA Technical Reports Server (NTRS)

1995-01-01

In this directory of space grant contacts of the NASA Space Grant College and Fellowship Program a listing of participating universities and other institutions are shown from all 50 states and from the District of Columbia and Puerto Rico. These 52 Space Grant State consortia currently consist of 395 institutions of higher learning, 66 industry affiliates, 26 state/local government offices, 40 nonprofit organizations, and 25 other educational entities. This directory is organized alphabetically by state and the contacts, addresses, phone numbers, and internet email addresses (where available) are included.

Comparison of ground-based and space flight energy expenditure and water turnover in middle-aged healthy male US astronauts

NASA Technical Reports Server (NTRS)

Lane, H. W.; Gretebeck, R. J.; Schoeller, D. A.; Davis-Street, J.; Socki, R. A.; Gibson, E. K.

1997-01-01

Energy requirements during space flight are poorly defined because they depend on metabolic-balance studies, food disappearance, and dietary records. Water turnover has been estimated by balance methods only. The purpose of this study was to determine energy requirements and water turnover for short-term space flights (8-14 d). Subjects were 13 male astronauts aged 36-51 y with normal body mass indexes (BMIs). Total energy expenditure (TEE) was determined during both a ground-based period and space flight and compared with the World Health Organization (WHO) calculations of energy requirements and dietary intake. TEE was not different for the ground-based and the space-flight periods (12.40 +/- 2.83 and 11.70 +/- 1.89 MJ/d, respectively), and the WHO calculation using the moderate activity correction was a good predictor of TEE during space flight. During the ground-based period, energy intake and TEE did not differ, but during space flight energy intake was significantly lower than TEE; body weight was also less at landing than before flight. Water turnover was lower during space flight than during the ground-based period (2.7 +/- 0.6 compared with 3.8 +/- 0.5 L/d), probably because of lower fluid intakes and perspiration loss during flight. This study confirmed that the WHO calculation can be used for male crew members' energy requirements during short space flights.

Content and Alignment of State Writing Standards and Assessments as Predictors of Student Writing Achievement: An Analysis of 2007 National Assessment of Educational Progress Data

ERIC Educational Resources Information Center

Troia, Gary A.; Olinghouse, Natalie G.; Zhang, Mingcai; Wilson, Joshua; Stewart, Kelly A.; Mo, Ya; Hawkins, Lisa

2018-01-01

We examined the degree to which content of states' writing standards and assessments (using measures of content range, frequency, balance, and cognitive complexity) and their alignment were related to student writing achievement on the 2007 National Assessment of Educational Progress (NAEP), while controlling for student, school, and state…

Estimating watershed evapotranspiration across the United States using multiple methods

Treesearch

Ge Sun; Shanlei Sun; Jingfeng Xiao; Peter Caldwell; Devendra Amatya; Suat Irmak; Prasanna H. Gowda; Sudhanshu Panda; Steve McNulty; Yang Zhang

2016-01-01

Evapotranspiration (ET) is the largest watershed water balance component only next to precipitation in the United States. ET is closely coupled with ecosystem carbon and energy fluxes, affects flooding or drought magnitude, and is also a good predictor for biodiversity at a regional scale.Thus, accurately estimating ET is of paramount importance to quantify the effects...

RISK FACTORS FOR AND SPATIAL DISTRIBUTION OF LYMPHOPROLIFERATIVE DISEASE VIRUS (LPDV) IN WILD TURKEYS (MELEAGRIS GALLOPAVO) IN NEW YORK STATE, USA.

PubMed

Alger, Katrina; Bunting, Elizabeth; Schuler, Krysten; Whipps, Christopher M

2017-07-01

Lymphoproliferative disease virus (LPDV) is an oncogenic avian retrovirus that was previously thought to exclusively infect domestic turkeys but was recently shown to be widespread in Wild Turkeys ( Meleagris gallopavo ) throughout most of the eastern US. In commercial flocks, the virus spreads between birds housed in close quarters, but there is little information about potential risk factors for infection in wild birds. Initial studies focused on distribution of LPDV nationally, but investigation of state-level data is necessary to assess potential predictors of infection and detect patterns in disease prevalence and distribution. We tested wild turkey bone marrow samples (n=2,538) obtained from hunter-harvested birds in New York State from 2012 to 2014 for LPDV infection. Statewide prevalence for those 3 yr was 55% with a 95% confidence interval (CI) of 53-57%. We evaluated a suite of demographic, anthropogenic, and land cover characteristics with logistic regression to identify potential predictors for infection based on odds ratio (OR). Age (OR=0.16, 95% CI=0.13-0.19) and sex (OR=1.3, 95% CI=1.03-1.24) were strong predictors of LPDV infection, with juveniles less likely to test positive than adults, and females more likely to test positive than males. The number of birds released during the state's 40-yr translocation program (OR=0.993, 95% CI=0.990-0.997) and the ratio of agriculture to forest cover (OR=1.13, 95% CI=1.03-1.19) were also predictive of LPDV infection. Prevalence distribution was analyzed using dual kernel density smoothing to produce a risk surface map, combined with Kulldorff's spatial scan statistic and the Anselin Local Moran's I to identify statistically significant geographic clusters of high or low prevalence. These methods revealed the prevalence of LPDV was high (>50%) throughout New York State, with regions of variation and several significant clusters. We revealed new information about the risk factors and distribution of LPDV in New York State, which may be beneficial to game bird managers and producers of organic or pasture-raised poultry.

Common Risk Criteria Standards for National Test Ranges

DTIC Science & Technology

2016-08-01

mitigation is a national policy goal. The most recent National Space Policy of the United States (dated June 28, 2010) states that “the United States will...pursue the following goals in its national space programs …strengthening measures to mitigate orbital debris.”5 While DoD Directive (DoDD) 3100.106... United States of America. National Space Policy of the United States of America. 28 June, 2010. May be superseded by update. Retrieved 7 April 2016

Registration of Space Objects

NASA Astrophysics Data System (ADS)

Schmidt-Tedd, Bernhard

2017-07-01

Space objects are subject to registration in order to allocate "jurisdiction and control" over those objects in the sovereign-free environment of outer space. This approach is similar to the registration of ships in view of the high sea and for aircrafts with respect to the international airspace. Registration is one of the basic principles of space law, starting with UN General Assembly Resolution 1721 B (XVI) of December 20, 1961, followed by Resolution 1962 (XVIII) of December 13, 1963, then formulated in Article VIII of the Outer Space Treaty of 1967 and as specified in the Registration Convention of 1975. Registration of space objects can be seen today as a principle of customary international law, relevant for each spacefaring state. Registration is divided into a national and an international level. The State Party establishes a national registry for its space objects, and those registrations have to be communicated via diplomatic channel to the UN Register of space objects. This UN Register is handled by the UN Office for Outer Space Affairs (UNOOSA) and is an open source of information for space objects worldwide. Registration is linked to the so-called launching state of the relevant space object. There might be more than one launching state for the specific launch event, but only one state actor can register a specific space object. The state of registry gains "jurisdiction and control" over the space object and therefore no double registration is permissible. Based on the established UN Space Law, registration practice was subject to some adaptions due to technical developments and legal challenges. After the privatization of the major international satellite organizations, a number of non-registrations had to be faced. The state actors reacted with the UN Registration Practice Resolution of 2007 as elaborated in the Legal Subcommittee of UNCOPUOS, the Committee for the Peaceful Use of Outer Space. In this context an UNOOSA Registration Information Submission Form had been developed. Today the complexity of launch activities and the concepts of mega-constellations lead to new challenges to the registration system. The Registration Practice Resolution already recommends that in cases of joint launches, each space object should be registered separately. Registration of space objects is a legal instrument in the context of state responsibility; it is not an instrument of traffic management. The orbit information of the registration system is indicative for identification purposes but not real-time positioning information. Such traffic management information follows different rules.

Spatiotemporal predictions of soil properties and states in variably saturated landscapes

NASA Astrophysics Data System (ADS)

Franz, Trenton E.; Loecke, Terrance D.; Burgin, Amy J.; Zhou, Yuzhen; Le, Tri; Moscicki, David

2017-07-01

Understanding greenhouse gas (GHG) fluxes from landscapes with variably saturated soil conditions is challenging given the highly dynamic nature of GHG fluxes in both space and time, dubbed hot spots, and hot moments. On one hand, our ability to directly monitor these processes is limited by sparse in situ and surface chamber observational networks. On the other hand, remote sensing approaches provide spatial data sets but are limited by infrequent imaging over time. We use a robust statistical framework to merge sparse sensor network observations with reconnaissance style hydrogeophysical mapping at a well-characterized site in Ohio. We find that combining time-lapse electromagnetic induction surveys with empirical orthogonal functions provides additional environmental covariates related to soil properties and states at high spatial resolutions ( 5 m). A cross-validation experiment using eight different spatial interpolation methods versus 120 in situ soil cores indicated an 30% reduction in root-mean-square error for soil properties (clay weight percent and total soil carbon weight percent) using hydrogeophysical derived environmental covariates with regression kriging. In addition, the hydrogeophysical derived environmental covariates were found to be good predictors of soil states (soil temperature, soil water content, and soil oxygen). The presented framework allows for temporal gap filling of individual sensor data sets as well as provides flexible geometric interpolation to complex areas/volumes. We anticipate that the framework, with its flexible temporal and spatial monitoring options, will be useful in designing future monitoring networks as well as support the next generation of hyper-resolution hydrologic and biogeochemical models.

Ghettoizing outdoor advertising: disadvantage and ad panel density in black neighborhoods.

PubMed

Kwate, Naa Oyo A; Lee, Tammy H

2007-01-01

This study investigated correlates of outdoor advertising panel density in predominantly African American neighborhoods in New York City. Research shows that black neighborhoods have more outdoor advertising space than white neighborhoods, and these spaces disproportionately market alcohol and tobacco advertisements. Thus, understanding the factors associated with outdoor advertising panel density has important implications for public health. We linked 2000 census data with property data at the census block group level to investigate two neighborhood-level determinants of ad density: income level and physical decay. Results showed that block groups were exposed to an average of four ad spaces per 1,000 residents and that vacant lot square footage was a significant positive predictor of ad density. An inverse relationship between median household income and ad density did not reach significance, suggesting that relative affluence did not protect black neighborhoods from being targeted for outdoor advertisements.

Ghettoizing Outdoor Advertising: Disadvantage and Ad Panel Density in Black Neighborhoods

PubMed Central

Lee, Tammy H.

2006-01-01

This study investigated correlates of outdoor advertising panel density in predominantly African American neighborhoods in New York City. Research shows that black neighborhoods have more outdoor advertising space than white neighborhoods, and these spaces disproportionately market alcohol and tobacco advertisements. Thus, understanding the factors associated with outdoor advertising panel density has important implications for public health. We linked 2000 census data with property data at the census block group level to investigate two neighborhood-level determinants of ad density: income level and physical decay. Results showed that block groups were exposed to an average of four ad spaces per 1,000 residents and that vacant lot square footage was a significant positive predictor of ad density. An inverse relationship between median household income and ad density did not reach significance, suggesting that relative affluence did not protect black neighborhoods from being targeted for outdoor advertisements. PMID:17146710

Building the database for introduced plants in the United States

Treesearch

Qinfeng Guo; Josephine Falcone; Joe Brownsmith

2009-01-01

More than 4000 nonnative plant species have been introduced to the U.S. and Canada. Identifying potentially invasive species is an important goal. Ecologists have generally agreed that there is no simple biological predictor of invasion...

The importance of lake-specific characteristics for water quality across the continental United States.

PubMed

Read, Emily K; Patil, Vijay P; Oliver, Samantha K; Hetherington, Amy L; Brentrup, Jennifer A; Zwart, Jacob A; Winters, Kirsten M; Corman, Jessica R; Nodine, Emily R; Woolway, R Iestyn; Dugan, Hilary A; Jaimes, Aline; Santoso, Arianto B; Hong, Grace S; Winslow, Luke A; Hanson, Paul C; Weathers, Kathleen C

2015-06-01

Lake water quality is affected by local and regional drivers, including lake physical characteristics, hydrology, landscape position, land cover, land use, geology, and climate. Here, we demonstrate the utility of hypothesis testing within the landscape limnology framework using a random forest algorithm on a national-scale, spatially explicit data set, the United States Environmental Protection Agency's 2007 National Lakes Assessment. For 1026 lakes, we tested the relative importance of water quality drivers across spatial scales, the importance of hydrologic connectivity in mediating water quality drivers, and how the importance of both spatial scale and connectivity differ across response variables for five important in-lake water quality metrics (total phosphorus, total nitrogen, dissolved organic carbon, turbidity, and conductivity). By modeling the effect of water quality predictors at different spatial scales, we found that lake-specific characteristics (e.g., depth, sediment area-to-volume ratio) were important for explaining water quality (54-60% variance explained), and that regionalization schemes were much less effective than lake specific metrics (28-39% variance explained). Basin-scale land use and land cover explained between 45-62% of variance, and forest cover and agricultural land uses were among the most important basin-scale predictors. Water quality drivers did not operate independently; in some cases, hydrologic connectivity (the presence of upstream surface water features) mediated the effect of regional-scale drivers. For example, for water quality in lakes with upstream lakes, regional classification schemes were much less effective predictors than lake-specific variables, in contrast to lakes with no upstream lakes or with no surface inflows. At the scale of the continental United States, conductivity was explained by drivers operating at larger spatial scales than for other water quality responses. The current regulatory practice of using regionalization schemes to guide water quality criteria could be improved by consideration of lake-specific characteristics, which were the most important predictors of water quality at the scale of the continental United States. The spatial extent and high quality of contextual data available for this analysis makes this work an unprecedented application of landscape limnology theory to water quality data. Further, the demonstrated importance of lake morphology over other controls on water quality is relevant to both aquatic scientists and managers.

Association between activity space exposure to food establishments and individual risk of overweight.

PubMed

Kestens, Yan; Lebel, Alexandre; Chaix, Basile; Clary, Christelle; Daniel, Mark; Pampalon, Robert; Theriault, Marius; P Subramanian, S V

2012-01-01

Environmental exposure to food sources may underpin area level differences in individual risk for overweight. Place of residence is generally used to assess neighbourhood exposure. Yet, because people are mobile, multiple exposures should be accounted for to assess the relation between food environments and overweight. Unfortunately, mobility data is often missing from health surveys. We hereby test the feasibility of linking travel survey data with food listings to derive food store exposure predictors of overweight among health survey participants. Food environment exposure measures accounting for non-residential activity places (activity spaces) were computed and modelled in Montreal and Quebec City, Canada, using travel surveys and food store listings. Models were then used to predict activity space food exposures for 5,578 participants of the Canadian Community Health Survey. These food exposure estimates, accounting for daily mobility, were used to model self-reported overweight in a multilevel framework. Median Odd Ratios were used to assess the proportion of between-neighborhood variance explained by such food exposure predictors. Estimates of food environment exposure accounting for both residential and non-residential destinations were significantly and more strongly associated with overweight than residential-only measures of exposure for men. For women, residential exposures were more strongly associated with overweight than non-residential exposures. In Montreal, adjusted models showed men in the highest quartile of exposure to food stores were at lesser risk of being overweight considering exposure to restaurants (OR = 0.36 [0.21-0.62]), fast food outlets (0.48 [0.30-0.79]), or corner stores (0.52 [0.35-0.78]). Conversely, men experiencing the highest proportion of restaurants being fast-food outlets were at higher risk of being overweight (2.07 [1.25-3.42]). Women experiencing higher residential exposures were at lower risk of overweight. Using residential neighbourhood food exposure measures may underestimate true exposure and observed associations. Using mobility data offers potential for deriving activity space exposure estimates in epidemiological models.

Remote preparation of a qudit using maximally entangled states of qubits

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

Yu Changshui; Song Heshan; Wang Yahong

2006-02-15

Known quantum pure states of a qudit can be remotely prepared onto a group of particles of qubits exactly or probabilistically with the aid of two-level Einstein-Podolsky-Rosen states. We present a protocol for such kind of remote state preparation. We are mainly focused on the remote preparation of the ensembles of equatorial states and those of states in real Hilbert space. In particular, a kind of states of qudits in real Hilbert space have been shown to be remotely prepared in faith without the limitation of the input space dimension.

Prevalence and Predictors of Thyroid Dysfunction in Patients with HIV Infection and Acquired Immunodeficiency Syndrome: An Indian Perspective.

PubMed

Sharma, Neera; Sharma, Lokesh Kumar; Dutta, Deep; Gadpayle, Adesh Kisanji; Anand, Atul; Gaurav, Kumar; Mukherjee, Sabyasachi; Bansal, Rahul

2015-01-01

Background. Predictors of thyroid dysfunction in HIV are not well determined. This study aimed to determine the prevalence and predictors of thyroid dysfunction in HIV infected Indians. Methods. Consecutive HIV patients, 18-70 years of age, without any severe comorbid state, having at least 1-year follow-up at the antiretroviral therapy clinic, underwent clinical assessment and hormone assays. Results. From initially screened 527 patients, 359 patients (61.44 ± 39.42 months' disease duration), having good immune function [CD4 count >200 cell/mm(3): 90.25%; highly active antiretroviral therapy (HAART): 88.58%], were analyzed. Subclinical hypothyroidism (ScH) was the commonest thyroid dysfunction (14.76%) followed by sick euthyroid syndrome (SES) (5.29%) and isolated low TSH (3.1%). Anti-TPO antibody (TPOAb) was positive in 3.90%. Baseline CD4 count had inverse correlation with TPOAb after adjusting for age and body mass index. Stepwise linear regression revealed baseline CD4 count, TPOAb, and tuberculosis to be best predictors of ScH after adjusting for age, weight, duration of HIV, and history of opportunistic fungal and viral infections. Conclusion. Burden of thyroid dysfunction in chronic HIV infection with stable immune function is lower compared to pre-HAART era. Thyroid dysfunction is primarily of nonautoimmune origin, predominantly ScH. Severe immunodeficiency at disease onset, TPOAb positivity, and tuberculosis were best predictors of ScH.

Predictors of academic performance for applicants to an international dental studies program in the United States.

PubMed

Pitigoi-Aron, Gabriela; King, Patricia A; Chambers, David W

2011-12-01

The number of U.S. and Canadian dental schools offering programs for dentists with degrees from other countries leading to the D.D.S. or D.M.D. degree has increased recently. This fact, along with the diversity of educational systems represented by candidates for these programs, increases the importance of identifying valid admissions predictors of success in international dental student programs. Data from 148 students accepted into the international dental studies program at the University of the Pacific from 1994 through 2004 were analyzed. Dependent variables were comprehensive cumulative GPA at the end of both the first and second years of the two-year program. The Test of English as a Foreign Language (TOEFL) and both Parts I and II of the National Board Dental Examination (NBDE) were significant positive predictors of success. Performance on laboratory tests of clinical skill in operative dentistry and in fixed prosthodontics and ratings from interviewers were not predictive of overall success in the program. Although this study confirms the predictive value of written tests such as the TOEFL and NBDE, it also contributes to the literature documenting inconsistent results regarding other types of predictors. It may be the case that characteristics of individual programs or features of the applicant pools for each may require use of admissions predictors that are unique to schools.

Predictors of Initial Levels and Trajectories of Anxiety in Women Prior to and For Six Months Following Breast Cancer Surgery

PubMed Central

Kyranou, Marianna; Puntillo, Kathleen; Dunn, Laura B.; Aouizerat, Bradley E.; Paul, Steven M.; Cooper, Bruce A.; Neuhaus, John; West, Claudia; Dodd, Marylin; Miaskowski, Christine

2014-01-01

Background The diagnosis of breast cancer in combination with the anticipation of surgery evokes fear, uncertainty, and anxiety in most women. Objective In patients who underwent breast cancer surgery, study purposes were to examine how ratings of state anxiety changed from the time of the preoperative assessment to 6 months after surgery and to investigate whether specific demographic, clinical, symptom, and psychosocial adjustment characteristics predicted the preoperative levels of state anxiety and/or characteristics of the trajectories of state anxiety. Interventions/Methods Patients (n=396) were enrolled preoperatively and completed the Spielberger State Anxiety inventory monthly for six months. Using hierarchical linear modeling, demographic, clinical, symptom, and psychosocial adjustment characteristics were evaluated as predictors of initial levels and trajectories of state anxiety. Results Patients experienced moderate levels of anxiety prior to surgery. Higher levels of depressive symptoms and uncertainty about the future, as well as lower levels of life satisfaction, less sense of control, and greater difficulty coping predicted higher preoperative levels of state anxiety. Higher preoperative state anxiety, poorer physical health, decreased sense of control, and more feelings of isolation predicted higher state anxiety scores over time. Conclusions Moderate levels of anxiety persist in women for six months following breast cancer surgery. Implications for Practice Clinicians need to implement systematic assessments of anxiety to identify high risk women who warrant more targeted interventions. In addition, ongoing follow-up is needed in order to prevent adverse postoperative outcomes and to support women to return to their preoperative levels of function. PMID:24633334

Value for the money spent? Exploring the relationship between expenditures, insurance adequacy, and access to care for publicly insured children.

PubMed

Colby, Margaret S; Lipson, Debra J; Turchin, Sarah R

2012-04-01

This study examines the relationship between total state Medicaid spending per child and measures of insurance adequacy and access to care for publicly insured children. Using the 2007 National Survey of Children's Health, seven measures of insurance adequacy and health care access were examined for publicly insured children (n = 19,715). Aggregate state-level measures were constructed, adjusting for differences in demographic, health status, and household characteristics. Per member per month (PMPM) state Medicaid spending on children ages 0-17 was calculated from capitated, fee-for-service, and administrative expenses. Adjusted measures were compared with PMPM state Medicaid spending in scatter plots, and multilevel logistic regression models tested how well state-level expenditures predicted individual adequacy and access measures. Medicaid spending PMPM was a significant predictor of both insurance adequacy and receipt of mental health services. An increase of $50 PMPM was associated with a 6-7 % increase in the likelihood that insurance would always cover needed services and allow access to providers (p = 0.04) and a 19 % increase in the likelihood of receiving mental health services (p < 0.01). For the remaining four measures, PMPM was a consistent (though not statistically significant) positive predictor. States with higher total spending per child appear to assure better access to care for Medicaid children. The policies or incentives used by the few states that get the greatest value--lower-than-median spending and higher-than-median adequacy and access--should be examined for potential best practices that other states could adapt to improve value for their Medicaid spending.

KENNEDY SPACE CENTER, FLA. - The Honorable Toni Jennings (left), lieutenant governor of the state of Florida, and Frank T. Brogan, president of Florida Atlantic University, receive a briefing on the research that will be conducted in the Space Life Sciences Lab from Dr. Robert J. Ferl (right), director of Space Agriculture Biotechnology Research and Education (SABRE), University of Florida. Jennings and Brogan are speaking at a dedication and ribbon-cutting ceremony for the lab hosted by NASA-Kennedy Space Center and the state of Florida at the new lab. Completed in August, the facility encompasses more than 100,000 square feet and was formerly known as the Space Experiment Research and Processing Laboratory or SERPL. The state, through the Florida Space Authority, built the research lab which is host to NASA, NASA’s Life Sciences Services contractor Dynamac Corp., Bionetics Corp., and researchers from the University of Florida. Dynamac Corp. leases the facility. The Florida Space Research Institute is responsible for gaining additional tenants from outside the NASA community.

NASA Image and Video Library

2003-11-19

KENNEDY SPACE CENTER, FLA. - The Honorable Toni Jennings (left), lieutenant governor of the state of Florida, and Frank T. Brogan, president of Florida Atlantic University, receive a briefing on the research that will be conducted in the Space Life Sciences Lab from Dr. Robert J. Ferl (right), director of Space Agriculture Biotechnology Research and Education (SABRE), University of Florida. Jennings and Brogan are speaking at a dedication and ribbon-cutting ceremony for the lab hosted by NASA-Kennedy Space Center and the state of Florida at the new lab. Completed in August, the facility encompasses more than 100,000 square feet and was formerly known as the Space Experiment Research and Processing Laboratory or SERPL. The state, through the Florida Space Authority, built the research lab which is host to NASA, NASA’s Life Sciences Services contractor Dynamac Corp., Bionetics Corp., and researchers from the University of Florida. Dynamac Corp. leases the facility. The Florida Space Research Institute is responsible for gaining additional tenants from outside the NASA community.

Quantum decimation in Hilbert space: Coarse graining without structure

NASA Astrophysics Data System (ADS)

Singh, Ashmeet; Carroll, Sean M.

2018-03-01

We present a technique to coarse grain quantum states in a finite-dimensional Hilbert space. Our method is distinguished from other approaches by not relying on structures such as a preferred factorization of Hilbert space or a preferred set of operators (local or otherwise) in an associated algebra. Rather, we use the data corresponding to a given set of states, either specified independently or constructed from a single state evolving in time. Our technique is based on principle component analysis (PCA), and the resulting coarse-grained quantum states live in a lower-dimensional Hilbert space whose basis is defined using the underlying (isometric embedding) transformation of the set of fine-grained states we wish to coarse grain. Physically, the transformation can be interpreted to be an "entanglement coarse-graining" scheme that retains most of the global, useful entanglement structure of each state, while needing fewer degrees of freedom for its reconstruction. This scheme could be useful for efficiently describing collections of states whose number is much smaller than the dimension of Hilbert space, or a single state evolving over time.

Interval Predictor Models for Data with Measurement Uncertainty

NASA Technical Reports Server (NTRS)

Lacerda, Marcio J.; Crespo, Luis G.

2017-01-01

An interval predictor model (IPM) is a computational model that predicts the range of an output variable given input-output data. This paper proposes strategies for constructing IPMs based on semidefinite programming and sum of squares (SOS). The models are optimal in the sense that they yield an interval valued function of minimal spread containing all the observations. Two different scenarios are considered. The first one is applicable to situations where the data is measured precisely whereas the second one is applicable to data subject to known biases and measurement error. In the latter case, the IPMs are designed to fully contain regions in the input-output space where the data is expected to fall. Moreover, we propose a strategy for reducing the computational cost associated with generating IPMs as well as means to simulate them. Numerical examples illustrate the usage and performance of the proposed formulations.

Different slopes for different folks: alpha and delta EEG power predict subsequent video game learning rate and improvements in cognitive control tasks.

PubMed

Mathewson, Kyle E; Basak, Chandramallika; Maclin, Edward L; Low, Kathy A; Boot, Walter R; Kramer, Arthur F; Fabiani, Monica; Gratton, Gabriele

2012-12-01

We hypothesized that control processes, as measured using electrophysiological (EEG) variables, influence the rate of learning of complex tasks. Specifically, we measured alpha power, event-related spectral perturbations (ERSPs), and event-related brain potentials during early training of the Space Fortress task, and correlated these measures with subsequent learning rate and performance in transfer tasks. Once initial score was partialled out, the best predictors were frontal alpha power and alpha and delta ERSPs, but not P300. By combining these predictors, we could explain about 50% of the learning rate variance and 10%-20% of the variance in transfer to other tasks using only pretraining EEG measures. Thus, control processes, as indexed by alpha and delta EEG oscillations, can predict learning and skill improvements. The results are of potential use to optimize training regimes. Copyright © 2012 Society for Psychophysiological Research.

Theoretical predictor for candidate structure assignment from IMS data of biomolecule-related conformational space.

PubMed

Schenk, Emily R; Nau, Frederic; Fernandez-Lima, Francisco

2015-06-01

The ability to correlate experimental ion mobility data with candidate structures from theoretical modeling provides a powerful analytical and structural tool for the characterization of biomolecules. In the present paper, a theoretical workflow is described to generate and assign candidate structures for experimental trapped ion mobility and H/D exchange (HDX-TIMS-MS) data following molecular dynamics simulations and statistical filtering. The applicability of the theoretical predictor is illustrated for a peptide and protein example with multiple conformations and kinetic intermediates. The described methodology yields a low computational cost and a simple workflow by incorporating statistical filtering and molecular dynamics simulations. The workflow can be adapted to different IMS scenarios and CCS calculators for a more accurate description of the IMS experimental conditions. For the case of the HDX-TIMS-MS experiments, molecular dynamics in the "TIMS box" accounts for a better sampling of the molecular intermediates and local energy minima.

Physical frailty predicts incident depressive symptoms in elderly people: prospective findings from the Obu Study of Health Promotion for the Elderly.

PubMed

Makizako, Hyuma; Shimada, Hiroyuki; Doi, Takehiko; Yoshida, Daisuke; Anan, Yuya; Tsutsumimoto, Kota; Uemura, Kazuki; Liu-Ambrose, Teresa; Park, Hyuntae; Lee, Sanyoon; Suzuki, Takao

2015-03-01

The purpose of this study was to determine whether frailty is an important and independent predictor of incident depressive symptoms in elderly people without depressive symptoms at baseline. Fifteen-month prospective study. General community in Japan. A total of 3025 community-dwelling elderly people aged 65 years or over without depressive symptoms at baseline. The self-rated 15-item Geriatric Depression Scale was used to assess symptoms of depression with a score of 6 or more at baseline and 15-month follow-up. Participants underwent a structural interview designed to obtain demographic factors and frailty status, and completed cognitive testing with the Mini-Mental State Examination and physical performance testing with the Short Physical Performance Battery as potential predictors. At a 15-month follow-up survey, 226 participants (7.5%) reported the development of depressive symptoms. We found that frailty and poor self-rated general health (adjusted odds ratio 1.86, 95% confidence interval 1.30-2.66, P < .01) were independent predictors of incident depressive symptoms. The odds ratio for depressive symptoms in participants with frailty compared with robust participants was 1.86 (95% confidence interval 1.05-3.28, P = .03) after adjusting for demographic factors, self-rated general health, behavior, living arrangements, Mini-Mental State Examination, Short Physical Performance Battery, and Geriatric Depression Scale scores at baseline. Our findings suggested that frailty and poor self-rated general health were independent predictors of depressive symptoms in community-dwelling elderly people. Copyright © 2015 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.

Determinants of Clostridium difficile Infection Incidence Across Diverse United States Geographic Locations

PubMed Central

Lessa, Fernanda C.; Mu, Yi; Winston, Lisa G.; Dumyati, Ghinwa K.; Farley, Monica M.; Beldavs, Zintars G.; Kast, Kelly; Holzbauer, Stacy M.; Meek, James I.; Cohen, Jessica; McDonald, L. Clifford; Fridkin, Scott K.

2014-01-01

Background  Clostridium difficile infection (CDI) is no longer restricted to hospital settings, and population-based incidence measures are needed. Understanding the determinants of CDI incidence will allow for more meaningful comparisons of rates and accurate national estimates. Methods  Data from active population- and laboratory-based CDI surveillance in 7 US states were used to identify CDI cases (ie, residents with positive C difficile stool specimen without a positive test in the prior 8 weeks). Cases were classified as community-associated (CA) if stool was collected as outpatients or ≤3 days of admission and no overnight healthcare facility stay in the past 12 weeks; otherwise, cases were classified as healthcare-associated (HA). Two regression models, one for CA-CDI and another for HA-CDI, were built to evaluate predictors of high CDI incidence. Site-specific incidence was adjusted based on the regression models. Results  Of 10 062 cases identified, 32% were CA. Crude incidence varied by geographic area; CA-CDI ranged from 28.2 to 79.1/100 000 and HA-CDI ranged from 45.7 to 155.9/100 000. Independent predictors of higher CA-CDI incidence were older age, white race, female gender, and nucleic acid amplification test (NAAT) use. For HA-CDI, older age and a greater number of inpatient-days were predictors. After adjusting for relevant predictors, the range of incidence narrowed greatly; CA-CDI rates ranged from 30.7 to 41.3/100 000 and HA-CDI rates ranged from 58.5 to 94.8/100 000. Conclusions  Differences in CDI incidence across geographic areas can be partially explained by differences in NAAT use, age, race, sex, and inpatient-days. Variation in antimicrobial use may contribute to the remaining differences in incidence. PMID:25734120

Predictors of cognitive impairment assessed by Mini Mental State Examination in community-dwelling older adults: relevance of the step test.

PubMed

Muscari, Antonio; Spiller, Ilaria; Bianchi, Giampaolo; Fabbri, Elisa; Forti, Paola; Magalotti, Donatella; Pandolfi, Paolo; Zoli, Marco

2018-07-15

Several predictors of cognitive impairment assessed by Mini Mental State Examination (MMSE) have previously been identified. However, which predictors are the most relevant and what is their effect on MMSE categories remains unclear. Cross-sectional and longitudinal study using data from 1116 older adults (72.6 ± 5.6 years, 579 female), 350 of whom were followed for 7 years. At baseline, the following variables were collected: personal data, marital status, occupation, anthropometric measures, risk factors, previous cardiovascular events, self-rated health and physical activity during the last week. Furthermore, routine laboratory tests, abdominal echography and a step test (with measurement of the time needed to ascend and descend two steps 20 times) were performed. The associations of these variables with cross-sectional cognitive deficit (MMSE < 24) and longitudinal cognitive decline (decrease of MMSE score over 7 years of follow-up) were investigated using logistic regression models. Cross-sectional cognitive deficit was independently associated with school education ≤ 5 years, prolonged step test duration, having been blue collar or housewife (P ≤ 0.0001 for all) and, with lower significance, with advanced age, previous stroke and poor recent physical activity (P < 0.05). Longitudinal cognitive decline was mainly associated with step test duration (P = 0.0001) and diastolic blood pressure (P = 0.0002). The MMSE categories mostly associated with step test duration were orientation, attention, calculation and language, while memory appeared to be poorly or not affected. In our cohort of older adults, step test duration was the most relevant predictor of cognitive impairment. Copyright © 2018 Elsevier Inc. All rights reserved.

Lower urinary tract symptoms in men with Parkinson disease.

PubMed

Robinson, Joanne P; Bradway, Christine W; Bunting-Perry, Lisette; Avi-Itzhak, Tamara; Mangino, Marie; Chittams, Jesse; Duda, John E

2013-12-01

The aim of this study was to examine the prevalence, presentation, and predictors of lower urinary tract symptoms (LUTS) in men with idiopathic Parkinson disease (PD). Guided by the Theory of Unpleasant Symptoms, this retrospective exploratory study used data abstracted from admission clinical records of 271 male patients with idiopathic PD enrolled in a movement disorders clinic at a large metropolitan Veterans Affairs Medical Center in the eastern region of the United States. Data from the admission questionnaire, Unified Parkinson's Disease Rating Scale, and Mini Mental State Examination were abstracted by trained research assistants. Interrater reliability for the abstraction process was 0.99 in a randomly selected 10% sample of records. Descriptive statistics were used to determine the prevalence of LUTS. Logistic regression was used to determine LUTS risk factors and predictors. At least one LUTS was reported by 40.2% of participants. Incontinence was the most prevalent symptom, affecting almost 25% of participants, followed by nocturia (14.8%) and frequency (13.7%). Of the 10 identified risk factors for LUTS, four significant predictors were discovered: number of non-PD medications (p < .05), PD duration (p < .05), number of comorbidities (p < .05), and history of a hernia diagnosis (p < .05). Assessment for LUTS should be a component of every evaluation of a patient with PD. Our findings offer a preliminary profile of the male PD patient with LUTS, which is an important step toward effective screening, detection, and access to care and treatment. Next steps in research include further work to identify predictors of LUTS in both male and female PD populations, explore patient perspectives, begin trials of interventions for LUTS in the PD population, and analyze the economic impact.

Determinants of Clostridium difficile Infection Incidence Across Diverse United States Geographic Locations.

PubMed

Lessa, Fernanda C; Mu, Yi; Winston, Lisa G; Dumyati, Ghinwa K; Farley, Monica M; Beldavs, Zintars G; Kast, Kelly; Holzbauer, Stacy M; Meek, James I; Cohen, Jessica; McDonald, L Clifford; Fridkin, Scott K

2014-09-01

Clostridium difficile infection (CDI) is no longer restricted to hospital settings, and population-based incidence measures are needed. Understanding the determinants of CDI incidence will allow for more meaningful comparisons of rates and accurate national estimates. Data from active population- and laboratory-based CDI surveillance in 7 US states were used to identify CDI cases (ie, residents with positive C difficile stool specimen without a positive test in the prior 8 weeks). Cases were classified as community-associated (CA) if stool was collected as outpatients or ≤3 days of admission and no overnight healthcare facility stay in the past 12 weeks; otherwise, cases were classified as healthcare-associated (HA). Two regression models, one for CA-CDI and another for HA-CDI, were built to evaluate predictors of high CDI incidence. Site-specific incidence was adjusted based on the regression models. Of 10 062 cases identified, 32% were CA. Crude incidence varied by geographic area; CA-CDI ranged from 28.2 to 79.1/100 000 and HA-CDI ranged from 45.7 to 155.9/100 000. Independent predictors of higher CA-CDI incidence were older age, white race, female gender, and nucleic acid amplification test (NAAT) use. For HA-CDI, older age and a greater number of inpatient-days were predictors. After adjusting for relevant predictors, the range of incidence narrowed greatly; CA-CDI rates ranged from 30.7 to 41.3/100 000 and HA-CDI rates ranged from 58.5 to 94.8/100 000. Differences in CDI incidence across geographic areas can be partially explained by differences in NAAT use, age, race, sex, and inpatient-days. Variation in antimicrobial use may contribute to the remaining differences in incidence.

Space Utilization and Comparison Report. A SCHEV Report.

ERIC Educational Resources Information Center

Virginia State Council of Higher Education, 2004

2004-01-01

This report has been created to provide information on how public institutions of higher education in Virginia utilize their Educational and General space as well as compare the State Council of Higher Education for Virginia's (SCHEV) space utilization guidelines with those used in other State Higher Education Executive Offices. The State Council…

Experimental Issues in Coherent Quantum-State Manipulation of Trapped Atomic Ions

DTIC Science & Technology

1998-05-01

in Hilbert space and almost always precludes the exis- tence of “large” Schrödinger-cat-like states except on extremely short time scales. A...Hamiltonian Hideal operate on the Hilbert space formed by the ↓l and ↑l states of the L qubits. In practice, for the case of trapped ions, the...auxiliary state (Sec. 3.3). If decoherence mechanisms cause other states to be populated, the Hilbert space must be expanded. Although more streamlined

KENNEDY SPACE CENTER, FLA. - Dignitaries, invited guests, space center employees, and the media gather for a dedication and ribbon-cutting ceremony for the Space Life Sciences Lab hosted by NASA-Kennedy Space Center and the state of Florida at the new lab. Completed in August, the facility encompasses more than 100,000 square feet and was formerly known as the Space Experiment Research and Processing Laboratory or SERPL. The state, through the Florida Space Authority, built the research lab which is host to NASA, NASA’s Life Sciences Services contractor Dynamac Corp., Bionetics Corp., and researchers from the University of Florida. Dynamac Corp. leases the facility. The Florida Space Research Institute is responsible for gaining additional tenants from outside the NASA community.

NASA Image and Video Library

2003-11-19

KENNEDY SPACE CENTER, FLA. - Dignitaries, invited guests, space center employees, and the media gather for a dedication and ribbon-cutting ceremony for the Space Life Sciences Lab hosted by NASA-Kennedy Space Center and the state of Florida at the new lab. Completed in August, the facility encompasses more than 100,000 square feet and was formerly known as the Space Experiment Research and Processing Laboratory or SERPL. The state, through the Florida Space Authority, built the research lab which is host to NASA, NASA’s Life Sciences Services contractor Dynamac Corp., Bionetics Corp., and researchers from the University of Florida. Dynamac Corp. leases the facility. The Florida Space Research Institute is responsible for gaining additional tenants from outside the NASA community.

KENNEDY SPACE CENTER, FLA. - Capt. Winston Scott, executive director of the Florida Space Authority, speaks at a dedication and ribbon-cutting ceremony for the Space Life Sciences Lab hosted by NASA-Kennedy Space Center and the state of Florida at the new lab. Completed in August, the facility encompasses more than 100,000 square feet and was formerly known as the Space Experiment Research and Processing Laboratory or SERPL. The state, through the Florida Space Authority, built the research lab which is host to NASA, NASA’s Life Sciences Services contractor Dynamac Corp., Bionetics Corp., and researchers from the University of Florida. Dynamac Corp. leases the facility. The Florida Space Research Institute is responsible for gaining additional tenants from outside the NASA community.

NASA Image and Video Library

2003-11-19

KENNEDY SPACE CENTER, FLA. - Capt. Winston Scott, executive director of the Florida Space Authority, speaks at a dedication and ribbon-cutting ceremony for the Space Life Sciences Lab hosted by NASA-Kennedy Space Center and the state of Florida at the new lab. Completed in August, the facility encompasses more than 100,000 square feet and was formerly known as the Space Experiment Research and Processing Laboratory or SERPL. The state, through the Florida Space Authority, built the research lab which is host to NASA, NASA’s Life Sciences Services contractor Dynamac Corp., Bionetics Corp., and researchers from the University of Florida. Dynamac Corp. leases the facility. The Florida Space Research Institute is responsible for gaining additional tenants from outside the NASA community.

National Directory of NASA Space Grant Contacts

NASA Technical Reports Server (NTRS)

2002-01-01

Congress enacted the National Space Grant College and Fellowship Program (also known as Space Grant). NASA's Space Grant Program funds education, research, and public service programs in all 50 States, the District of Columbia, and the Commonwealth of Puerto Rico through 52 university-based Space Grant consortia. These consortia form a network of colleges and universities, industry partners, State and local Government agencies, other Federal agencies, museum and science centers, and nonprofit organizations, all with interests in aerospace education, research, and training. Space Grant programs emphasize the diversity of human resources, the participation of students in research, and the communication of the benefits of science and technology to the general public. Each year approximately one-third of the NASA Space Grant funds support scholarships and fellowships for United States students at the undergraduate and graduate levels. Typically, at least 20 percent of these awards go to students from underrepresented groups, and at least 40 percent go to women. Most Space Grant student awards include a mentored research experience with university faculty or NASA scientists or engineers. Space Grant consortia also fund curriculum enhancement and faculty development programs. Consortia members administer precollege and public service education programs in their States. The 52 consortia typically leverage NASA funds with matching contributions from State, local, and other university sources, which more than double the NASA funding. For more information, consult the Space Grant Web site at http://education.nasa.gov/spacegrant/

Physiological Observations and Omics to Develop Personalized Sensormotor Adaptability Countermeasures Using Bed Rest and Space Flight Data

NASA Technical Reports Server (NTRS)

Mulavara, A. P.; Seidler, R. D.; Feiveson, A.; Oddsson, L.; Zanello, S.; Oman, C. M.; Ploutz-Snyder, L.; Peters, B.; Cohen, H. S.; Reschke, M.;

KENNEDY SPACE CENTER, FLA. - Officials of the NASA-Kennedy Space Center and the state of Florida pose for a group portrait at a dedication and ribbon-cutting ceremony for the Space Life Sciences Lab at the new lab. From left are Capt. Winston Scott, executive director of the Florida Space Authority; Dr. Robert J. Ferl, director of Space Agriculture Biotechnology Research and Education (SABRE), University of Florida; Charlie Quincy, chief of the Biological Sciences Office, Kennedy Space Center; Jose Perez-Morales, NASA Project Manager for the Space Life Sciences Lab; Jim Kennedy, director of the Kennedy Space Center; The Honorable Toni Jennings, lieutenant governor of the state of Florida; Frank T. Brogan, president of the Florida Atlantic University; and Dr. Samuel Durrance, executive director of the Florida Space Research Institute. Completed in August, the facility encompasses more than 100,000 square feet and was formerly known as the Space Experiment Research and Processing Laboratory or SERPL. The state, through the Florida Space Authority, built the research lab which is host to NASA, NASA’s Life Sciences Services contractor Dynamac Corp., Bionetics Corp., and researchers from the University of Florida. Dynamac Corp. leases the facility. The Florida Space Research Institute is responsible for gaining additional tenants from outside the NASA community.

NASA Image and Video Library

2003-11-19

KENNEDY SPACE CENTER, FLA. - Officials of the NASA-Kennedy Space Center and the state of Florida pose for a group portrait at a dedication and ribbon-cutting ceremony for the Space Life Sciences Lab at the new lab. From left are Capt. Winston Scott, executive director of the Florida Space Authority; Dr. Robert J. Ferl, director of Space Agriculture Biotechnology Research and Education (SABRE), University of Florida; Charlie Quincy, chief of the Biological Sciences Office, Kennedy Space Center; Jose Perez-Morales, NASA Project Manager for the Space Life Sciences Lab; Jim Kennedy, director of the Kennedy Space Center; The Honorable Toni Jennings, lieutenant governor of the state of Florida; Frank T. Brogan, president of the Florida Atlantic University; and Dr. Samuel Durrance, executive director of the Florida Space Research Institute. Completed in August, the facility encompasses more than 100,000 square feet and was formerly known as the Space Experiment Research and Processing Laboratory or SERPL. The state, through the Florida Space Authority, built the research lab which is host to NASA, NASA’s Life Sciences Services contractor Dynamac Corp., Bionetics Corp., and researchers from the University of Florida. Dynamac Corp. leases the facility. The Florida Space Research Institute is responsible for gaining additional tenants from outside the NASA community.

Educational Choice and Educational Space

ERIC Educational Resources Information Center

Thomson, Kathleen Sonia

2016-01-01

This dissertation entitled "Educational choice and educational space" aims to explore the confluence of constructed space and geographic space using a supply-side context for New Zealand's public school system of quasi-open enrollment. In Part I, New Zealand's state and state-integrated school system across four urban areas is analyzed…

The effect of charge mutations on the stability and aggregation of a human single chain Fv fragment.

PubMed

Austerberry, James I; Dajani, Rana; Panova, Stanislava; Roberts, Dorota; Golovanov, Alexander P; Pluen, Alain; van der Walle, Christopher F; Uddin, Shahid; Warwicker, Jim; Derrick, Jeremy P; Curtis, Robin

2017-06-01

The aggregation propensities for a series of single-chain variable fragment (scFv) mutant proteins containing supercharged sequences, salt bridges and lysine/arginine-enriched motifs were characterised as a function of pH and ionic strength to isolate the electrostatic contributions. Recent improvements in aggregation predictors rely on using knowledge of native-state protein-protein interactions. Consistent with previous findings, electrostatic contributions to native protein-protein interactions correlate with aggregate growth pathway and rates. However, strong reversible self-association observed for selected mutants under native conditions did not correlate with aggregate growth, indicating 'sticky' surfaces that are exposed in the native monomeric state are inaccessible when aggregates grow. We find that even though similar native-state protein-protein interactions occur for the arginine and lysine-enriched mutants, aggregation propensity is increased for the former and decreased for the latter, providing evidence that lysine suppresses interactions between partially folded states under these conditions. The supercharged mutants follow the behaviour observed for basic proteins under acidic conditions; where excess net charge decreases conformational stability and increases nucleation rates, but conversely reduces aggregate growth rates due to increased intermolecular electrostatic repulsion. The results highlight the limitations of using conformational stability and native-state protein-protein interactions as predictors for aggregation propensity and provide guidance on how to engineer stabilizing charged mutations. Copyright © 2017. Published by Elsevier B.V.

Predictors of employment status among adults with Autism Spectrum Disorder.

PubMed

Ohl, Alisha; Grice Sheff, Mira; Small, Sarah; Nguyen, Jamie; Paskor, Kelly; Zanjirian, Aliza

2017-01-01

In the United States, adults with Autism Spectrum Disorder (ASD) experience high rates of unemployment and underemployment in relation to adults with other disabilities and the general population. Yet there is little research examining their employment experiences and the predictors of employment status. The purpose of this study was to examine the employment characteristics and histories of both employed and unemployed adults with ASD, and the factors that contributed to their employment status. This cross-sectional study used an online survey and the Short Effort Reward Imbalance (ERI) Scale to gather data. Multivariate logistic regression analyses were used to examine predictors of employment status and self-reported health. Of the 254 adults with ASD who participated in this study, 61.42% were employed and 38.58% were unemployed. Over half of the participants reported job imbalance on the Short ERI Scale and the vast majority did not receive any job assistance. Participants who disclosed their ASD diagnosis to their employer were more than three times as likely to be employed than those who did not disclose. Education level was also a significant predictor of employment status. This study suggests disability disclosure and education level are factors that contribute to employment status.

Healthcare employees' progression through disability benefits.

PubMed

Hawley, Carolyn E; Diaz, Sebastian; Reid, Christine

2009-01-01

Progression of Disability Benefits (PODB) refers to the migration of workers with work-limiting disabilities through a system of economic disability benefits that result in their ultimate placement into the Social Security Disability Insurance (SSDI) system [16]. Specifically, this migration involves a "progression" from short-term disability (STD) to long-term disability (LTD) to SSDI income. This project uses Chi-squared Automatic Interaction (CHAID) Technique to study the Healthcare industry, the largest industry in the United States, and its PODB experience. The first part of the study analyzes if claimant demographic (age, gender, disability type) and PODB data (movement from STD to LTD to SSDI) can be used to predict employer industry (dependent variable). Gender was the most significant predictor, while men working outside of Healthcare had the greatest amount of progression to advanced disability levels. The second part of the study assesses if the PODB experience could be predicted through claimant demographics and the sub-set industry within Healthcare in which claimants' were employed. The resulting dendogram reveals that disability type was the strongest predictor of claimant movement through disability benefits levels. Age was the second strongest predictor for all but 1 category of disability type, in which the Healthcare sector was the strongest predictor.

Stability of Predictors of Mortality after Spinal Cord Injury

PubMed Central

Krause, James S.; Saunders, Lee L.; Zhai, Yusheng

2011-01-01

Objective To identify the stability of socio-environmental, behavioral, and health predictors of mortality over an eight year time frame. Study Design Cohort study. Setting Data were analyzed at a large medical university in the Southeast United States of America (USA). Methods Adults with residual impairment from a spinal cord injury (SCI) who were at least one year post-injury at assessment were recruited through a large specialty hospital in the Southeast USA. 1209 participants were included in the final analysis. A piecewise exponential model with 2 equal time intervals (eight years total) was used to assess the stability of the hazard and the predictors over time. Results The hazard did significantly change over time, where the hazard in the first time interval was significantly lower than the second. There were no interactions between the socio-environmental, behavior, or health factors and time, although there was a significant interaction between age at injury (a demographic variable) and time. Conclusion These results suggest there is stability in the association between the predictors and mortality, even over an eight year time period. Results reinforce the use of historic variables for prediction of mortality in persons with SCI. PMID:22231541

A systematic review of studies identifying predictors of poor return to work outcomes following workplace injury.

PubMed

Street, Tamara D; Lacey, Sarah J

2015-06-05

Injuries occurring in the workplace can have serious implications for the health of the individual, the productivity of the employer and the overall economic community. The objective of this paper is to increase the current state of understanding of individual demographic and psychosocial characteristics associated with extended absenteeism from the workforce due to a workplace injury. Studies included in this systematic literature review tracked participants' return to work status over a minimum of three months, identified either demographic, psychosocial or general injury predictors of poor return to work outcomes and included a heterogeneous sample of workplace injuries. Identified predictors of poor return to work outcomes included older age, female gender, divorced marital status, two or more dependent family members, lower education levels, employment variables associated with reduced labour market desirability, severity or sensitive injury locations, negative attitudes and outcome perceptions of the participant. There is a need for clear and consistent definition and measurement of return to work outcomes and a holistic theoretical model integrating injury, psychosocial and demographic predictors of return to work. Through greater understanding of the nature of factors affecting return to work, improved outcomes could be achieved.

Entanglement and the three-dimensionality of the Bloch ball

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

Masanes, Ll., E-mail: ll.masanes@gmail.com; Müller, M. P.; Pérez-García, D.

2014-12-15

We consider a very natural generalization of quantum theory by letting the dimension of the Bloch ball be not necessarily three. We analyze bipartite state spaces where each of the components has a d-dimensional Euclidean ball as state space. In addition to this, we impose two very natural assumptions: the continuity and reversibility of dynamics and the possibility of characterizing bipartite states by local measurements. We classify all these bipartite state spaces and prove that, except for the quantum two-qubit state space, none of them contains entangled states. Equivalently, in any of these non-quantum theories, interacting dynamics is impossible. Thismore » result reveals that “existence of entanglement” is the requirement with minimal logical content which singles out quantum theory from our family of theories.« less

Framing research for state policymakers who place a priority on cancer.

PubMed

Brownson, Ross C; Dodson, Elizabeth A; Kerner, Jon F; Moreland-Russell, Sarah

2016-08-01

Despite the potential for reducing the cancer burden via state policy change, few data exist on how best to disseminate research information to influence state legislators' policy choices. We explored: (1) the relative importance of core framing issues (source, presentation, timeliness) among policymakers who prioritize cancer and those who do not prioritize cancer and (2) the predictors of use of research in policymaking. Cross-sectional data were collected from US state policymakers (i.e., legislators elected to state houses or senates) from January through October 2012 (n = 862). One-way analysis of variance was performed to investigate the association of the priority of cancer variable with outcome variables. Multivariate logistic regression models examined predictors of the influence of research information. Legislators who prioritized cancer tended to rate characteristics that make research information useful higher than those who did not prioritize cancer. Among differences that were statistically significant were three items in the "source" domain (relevance, delivered by someone respected, supports one's own position), one item in the "presentation" domain (telling a story related to constituents) and two items in the "timeliness" domain (high current state priority, feasible when information is received). Participants who prioritized cancer risk factors were 80 % more likely to rate research information as one of their top reasons for choosing an issue on which to work. Our results suggest the importance of narrative forms of communication and that research information needs to be relevant to the policymakers' constituents in a brief, concise format.

Predictors of Alumni Donor Behavior in Graduates of the Traditional MBA and iMBA Programs at The Pennsylvania State University

ERIC Educational Resources Information Center

Ketter, Jason W.

2013-01-01

The affordability of a degree from a public university is the subject of much heated debate in the halls of many state governments. The taxpayer, as well as the individual paying tuition, is asking the question: What is the return on investment for the millions of dollars used to support public higher education? The taxpayer views public…

How Are Previous Physical Activity and Self-Efficacy Related to Future Physical Activity and Self-Efficacy?

ERIC Educational Resources Information Center

David, Prabu; Pennell, Michael L.; Foraker, Randi E.; Katz, Mira L.; Buckworth, Janet; Paskett, Electra D.

2014-01-01

Self-efficacy (SE) has been found to be a robust predictor of success in achieving physical activity (PA) goals. While much of the current research has focused on SE as a trait, SE as a state has received less attention. Using day-to-day measurements obtained over 84 days, we examined the relationship between state SE and PA. Postmenopausal women…

Use of Curricular and Extracurricular Assessments to Predict Performance on the United States Medical Licensing Examination (USMLE) Step 1: A Multi-Year Study

ERIC Educational Resources Information Center

Gandy, Robyn A.; Herial, Nabeel A.; Khuder, Sadik A.; Metting, Patricia J.

2008-01-01

This paper studies student performance predictions based on the United States Medical Licensure Exam (USMLE) Step 1. Subjects were second-year medical students from academic years of 2002 through 2006 (n = 711). Three measures of basic science knowledge (two curricular and one extracurricular) were evaluated as predictors of USMLE Step 1 scores.…

Integrating fine-scale soil data into species distribution models: preparing Soil Survey Geographic (SSURGO) data from multiple counties

Treesearch

Matthew P. Peters; Louis R. Iverson; Anantha M. Prasad; Steve N. Matthews

2013-01-01

Fine-scale soil (SSURGO) data were processed at the county level for 37 states within the eastern United States, initially for use as predictor variables in a species distribution model called DISTRIB II. Values from county polygon files converted into a continuous 30-m raster grid were aggregated to 4-km cells and integrated with other environmental and site condition...

Internet Searches for Affect-Related Terms: An Indicator of Subjective Well-Being and Predictor of Health Outcomes across US States and Metro Areas.

PubMed

Ford, Michael T; Jebb, Andrew T; Tay, Louis; Diener, Ed

2018-03-01

The present study explored the potential for internet search data to serve as indicators of subjective well-being (SWB) and predictors of health at the state and metro area levels. We propose that searches for positive and negative affect-related terms represent information-seeking behavior of individuals who are experiencing emotions and seeking information about them. Data on the frequency of Google searches for 15 affect terms were collected from Google's Trends website (trends.google.com). These were paired with data on health, self-reported emotions, psychological well-being, personality, and Twitter postings at the state and metro area levels. Several internet search scores correlated with indicators of cardiovascular health and depression. Some search term scores also correlated strongly with self-reported emotions, well-being metrics, neuroticism, per capita income, and Twitter postings at the state or metro area level. Multiple regression analyses suggest that affect searches predict depression rates at the metro area level beyond the effects of income and other well-being measures. The results highlight the promise and challenges of using internet search data at the aggregate level for physical and mental health assessment and surveillance. © 2018 The International Association of Applied Psychology.

Effects of life-state on detectability in a demographic study of the terrestrial orchid Cleistes bifaria

USGS Publications Warehouse

Kery, M.; Gregg, K.B.

2003-01-01

1. Most plant demographic studies follow marked individuals in permanent plots. Plots tend to be small, so detectability is assumed to be one for every individual. However, detectability could be affected by factors such as plant traits, time, space, observer, previous detection, biotic interactions, and especially by life-state. 2. We used a double-observer survey and closed population capture-recapture modelling to estimate state-specific detectability of the orchid Cleistes bifaria in a long-term study plot of 41.2 m2. Based on AICc model selection, detectability was different for each life-state and for tagged vs. previously untagged plants. There were no differences in detectability between the two observers. 3. Detectability estimates (SE) for one-leaf vegetative, two-leaf vegetative, and flowering/fruiting states correlated with mean size of these states and were 0.76 (0.05), 0.92 (0.06), and 1 (0.00), respectively, for previously tagged plants, and 0.84 (0.08), 0.75 (0.22), and 0 (0.00), respectively, for previously untagged plants. (We had insufficient data to obtain a satisfactory estimate of previously untagged flowering plants). 4. Our estimates are for a medium-sized plant in a small and intensively surveyed plot. It is possible that detectability is even lower for larger plots and smaller plants or smaller life-states (e.g. seedlings) and that detectabilities < 1 are widespread in plant demographic studies. 5. State-dependent detectabilities are especially worrying since they will lead to a size- or state-biased sample from the study plot. Failure to incorporate detectability into demographic estimation methods introduces a bias into most estimates of population parameters such as fecundity, recruitment, mortality, and transition rates between life-states. We illustrate this by a simple example using a matrix model, where a hypothetical population was stable but, due to imperfect detection, wrongly projected to be declining at a rate of 8% per year. 6. Almost all plant demographic studies are based on models for discrete states. State and size are important predictors both for demographic rates and detectability. We suggest that even in studies based on small plots, state- or size-specific detectability should be estimated at least at some point to avoid biased inference about the dynamics of the population sampled.

Lossless compression algorithm for multispectral imagers

NASA Astrophysics Data System (ADS)

Gladkova, Irina; Grossberg, Michael; Gottipati, Srikanth

2008-08-01

Multispectral imaging is becoming an increasingly important tool for monitoring the earth and its environment from space borne and airborne platforms. Multispectral imaging data consists of visible and IR measurements from a scene across space and spectrum. Growing data rates resulting from faster scanning and finer spatial and spectral resolution makes compression an increasingly critical tool to reduce data volume for transmission and archiving. Research for NOAA NESDIS has been directed to finding for the characteristics of satellite atmospheric Earth science Imager sensor data what level of Lossless compression ratio can be obtained as well as appropriate types of mathematics and approaches that can lead to approaching this data's entropy level. Conventional lossless do not achieve the theoretical limits for lossless compression on imager data as estimated from the Shannon entropy. In a previous paper, the authors introduce a lossless compression algorithm developed for MODIS as a proxy for future NOAA-NESDIS satellite based Earth science multispectral imagers such as GOES-R. The algorithm is based on capturing spectral correlations using spectral prediction, and spatial correlations with a linear transform encoder. In decompression, the algorithm uses a statistically computed look up table to iteratively predict each channel from a channel decompressed in the previous iteration. In this paper we present a new approach which fundamentally differs from our prior work. In this new approach, instead of having a single predictor for each pair of bands we introduce a piecewise spatially varying predictor which significantly improves the compression results. Our new algorithm also now optimizes the sequence of channels we use for prediction. Our results are evaluated by comparison with a state of the art wavelet based image compression scheme, Jpeg2000. We present results on the 14 channel subset of the MODIS imager, which serves as a proxy for the GOES-R imager. We will also show results of the algorithm for on NOAA AVHRR data and data from SEVIRI. The algorithm is designed to be adapted to the wide range of multispectral imagers and should facilitate distribution of data throughout globally. This compression research is managed by Roger Heymann, PE of OSD NOAA NESDIS Engineering, in collaboration with the NOAA NESDIS STAR Research Office through Mitch Goldberg, Tim Schmit, Walter Wolf.

K-12 Aerospace Education Programs

NASA Technical Reports Server (NTRS)

1999-01-01

NASA, the United States Air Force Academy, the Air Force Space Command, the University of Colorado at Colorado Springs (UCCS), and the United States Space Foundation teamed to produce a dynamic and successful graduate course and in-service program for K-12 educators that has a positive impact on education trends across the nation. Since 1986, more than 10,000 educators from across the United States have participated in Space Discovery and Teaching with Space affecting nearly a million students in grades K-12. The programs are designed to prepare educators to use the excitement of space to motivate students in all curriculum subjects.

Early predictors of occupational back reinjury: results from a prospective study of workers in Washington State.

PubMed

Keeney, Benjamin J; Turner, Judith A; Fulton-Kehoe, Deborah; Wickizer, Thomas M; Chan, Kwun Chuen Gary; Franklin, Gary M

2013-01-15

Prospective population-based cohort study. To identify early predictors of self-reported occupational back reinjury within 1 year after work-related back injury. Back injuries are the costliest and most prevalent disabling occupational injuries in the United States. A substantial proportion of workers with back injuries have reinjuries after returning to work, yet there are few studies of risk factors for occupational back reinjuries. We aimed to identify the incidence and early (in the claim) predictors of self-reported back reinjury by approximately 1 year after the index injury among Washington State workers with new work disability claims for back injuries. The Washington Workers' Compensation Disability Risk Identification Study Cohort provided a large, population-based sample with information on variables in 7 domains: sociodemographic, employment-related, pain and function, clinical status, health care, health behavior, and psychological. We conducted telephone interviews with workers 3 weeks and 1 year after submission of a time-loss claim for the injury. We first identified predictors (P < 0.10) of self-reported reinjury within 1 year in bivariate analyses. Those variables were then included in a multivariate logistic regression model predicting occupational back reinjury. A total of 290 (25.8%) of 1123 (70.0% response rate) workers who completed the 1-year follow-up interview and had returned to work reported having reinjured their back at work. Baseline variables significantly associated with reinjury (P < 0.05) in the multivariate model included male sex, constant whole-body vibration at work, previous similar injury, 4 or more previous claims of any type, possessing health insurance, and high fear-avoidance scores. Baseline obesity was associated with reduced odds of reinjury. No other employment-related or psychological variables were significant. One-fourth of the workers who received work disability compensation for a back injury self-reported reinjury after returning to work. Baseline variables in multiple domains predicted occupational back reinjury. Increased knowledge of early risk factors for reinjury may help to lead to interventions, such as efforts to reduce fear avoidance and graded activity to promote recovery, effective in lowering the risk of reinjury.

Space-time patterns in ignimbrite compositions revealed by GIS and R based statistical analysis

NASA Astrophysics Data System (ADS)

Brandmeier, Melanie; Wörner, Gerhard

2017-04-01

GIS-based multivariate statistical and geospatial analysis of a compilation of 890 geochemical and ca. 1,200 geochronological data for 194 mapped ignimbrites from Central Andes documents the compositional and temporal pattern of large volume ignimbrites (so-called "ignimbrite flare-ups") during Neogene times. Rapid advances in computational sciences during the past decade lead to a growing pool of algorithms for multivariate statistics on big datasets with many predictor variables. This study uses the potential of R and ArcGIS and applies cluster (CA) and linear discriminant analysis (LDA) on log-ratio transformed spatial data. CA on major and trace element data allows to group ignimbrites according to their geochemical characteristics into rhyolitic and a dacitic "end-members" and differentiates characteristic trace element signatures with respect to Eu anomaly, depletion of MREEs and variable enrichment in LREE. To highlight these distinct compositional signatures, we applied LDA to selected ignimbrites for which comprehensive data sets were available. The most important predictors for discriminating ignimbrites are La (LREE), Yb (HREE), Eu, Al2O3, K2O, P2O5, MgO, FeOt and TiO2. However, other REEs such as Gd, Pr, Tm, Sm and Er also contribute to the discrimination functions. Significant compositional differences were found between the older (>14 Ma) large-volume plateau-forming ignimbrites in northernmost Chile and southern Peru and the younger (< 10 Ma) Altiplano-Puna-Volcanic-Complex ignimbrites that are of similar volumes. Older ignimbrites are less depleted in HREEs and less radiogenic in Sr isotopes, indicating smaller crustal contributions during evolution in thinner and thermally less evolved crust. These compositional variations indicate a relation to crustal thickening with a "transition" from plagioclase to amphibole and garnet residual mineralogy between 13 to 9 Ma. We correlate compositional and volumetric variations to the N-S passage of the Juan-Fernandéz ridge and crustal shortening and thickening during the past 26 Ma. The value of GIS and multivariate statistics in comparison to traditional geochemical parameters are highlighted working with large datasets with many predictors in a spatial and temporal context. Algorithms implemented in R allow taking advantage of an n-dimensional space and, thus, of subtle compositional differences contained in the data, while space-time patterns can be analyzed easily in GIS.

Factors Associated with Pediatric Mortality from Motor Vehicle Crashes in the United States: A State-Based Analysis.

PubMed

Wolf, Lindsey L; Chowdhury, Ritam; Tweed, Jefferson; Vinson, Lori; Losina, Elena; Haider, Adil H; Qureshi, Faisal G

2017-08-01

To examine geographic variation in motor vehicle crash (MVC)-related pediatric mortality and identify state-level predictors of mortality. Using the 2010-2014 Fatality Analysis Reporting System, we identified passengers <15 years of age involved in fatal MVCs, defined as crashes on US public roads with ≥1 death (adult or pediatric) within 30 days. We assessed passenger, driver, vehicle, crash, and state policy characteristics as factors potentially associated with MVC-related pediatric mortality. Our outcomes were age-adjusted, MVC-related mortality rate per 100 000 children and percentage of children who died of those in fatal MVCs. Unit of analysis was US state. We used multivariable linear regression to define state characteristics associated with higher levels of each outcome. Of 18 116 children in fatal MVCs, 15.9% died. The age-adjusted, MVC-related mortality rate per 100 000 children varied from 0.25 in Massachusetts to 3.23 in Mississippi (mean national rate of 0.94). Predictors of greater age-adjusted, MVC-related mortality rate per 100 000 children included greater percentage of children who were unrestrained or inappropriately restrained (P < .001) and greater percentage of crashes on rural roads (P = .016). Additionally, greater percentages of children died in states without red light camera legislation (P < .001). For 10% absolute improvement in appropriate child restraint use nationally, our risk-adjusted model predicted >1100 pediatric deaths averted over 5 years. MVC-related pediatric mortality varied by state and was associated with restraint nonuse or misuse, rural roads, vehicle type, and red light camera policy. Revising state regulations and improving enforcement around these factors may prevent substantial pediatric mortality. Copyright © 2017 Elsevier Inc. All rights reserved.

Distributed state-space generation of discrete-state stochastic models

NASA Technical Reports Server (NTRS)

Ciardo, Gianfranco; Gluckman, Joshua; Nicol, David

1995-01-01

High-level formalisms such as stochastic Petri nets can be used to model complex systems. Analysis of logical and numerical properties of these models of ten requires the generation and storage of the entire underlying state space. This imposes practical limitations on the types of systems which can be modeled. Because of the vast amount of memory consumed, we investigate distributed algorithms for the generation of state space graphs. The distributed construction allows us to take advantage of the combined memory readily available on a network of workstations. The key technical problem is to find effective methods for on-the-fly partitioning, so that the state space is evenly distributed among processors. In this paper we report on the implementation of a distributed state-space generator that may be linked to a number of existing system modeling tools. We discuss partitioning strategies in the context of Petri net models, and report on performance observed on a network of workstations, as well as on a distributed memory multi-computer.

KSC-03PD-3139

NASA Technical Reports Server (NTRS)

2003-01-01

KENNEDY SPACE CENTER, FLA. The Honorable Toni Jennings, lieutenant governor of the state of Florida, speaks at a dedication and ribbon-cutting ceremony for the Space Life Sciences Lab hosted by NASA-Kennedy Space Center and the state of Florida at the new lab. Completed in August, the facility encompasses more than 100,000 square feet and was formerly known as the Space Experiment Research and Processing Laboratory or SERPL. The state, through the Florida Space Authority, built the research lab which is host to NASA, NASAs Life Sciences Services contractor Dynamac Corp., Bionetics Corp., and researchers from the University of Florida. Dynamac Corp. leases the facility. The Florida Space Research Institute is responsible for gaining additional tenants from outside the NASA community.

Social network and census tract-level influences on substance use among emerging adult males: An activity spaces approach

PubMed Central

Gibson, Crystal; Perley, Lauren; Bailey, Jonathan; Barbour, Russell; Kershaw, Trace

2015-01-01

Social network and area level characteristics have been linked to substance use. We used snowball sampling to recruit 90 predominantly African American emerging adult men who provided typical locations visited (n=510). We used generalized estimating equations to examine social network and area level predictors of substance use. Lower social network quality was associated with days of marijuana use (B=-0.0037, p<0.0001) and problem alcohol use (B=-0.0050, p=0.0181). The influence of area characteristics on substance use differed between risky and non-risky spaces. Peer and area influences are important for substance use among men, and may differ for high and low risk places. PMID:26176810

Risk factors for suicidal behaviors among Filipino Americans: a data mining approach.

PubMed

Kuroki, Yusuke

2015-01-01

Filipino Americans have lower suicide rates than other Asian ethnic groups. The present study examined risk factors for suicide ideation and attempt among Filipino Americans with random forest. The data were from the Filipino American Community Epidemiological Study (Takeuchi, 2011). The results showed that the important predictors for suicide ideation were depressive disorder, substance use disorder, and years in the United States. The important predictors for suicide attempt were the number of family relatives and family conflict. Clinicians are advised to investigate familial and cultural factors among Filipino Americans. How family and cultural factors may affect suicidal behaviors were further discussed.

State-by-state Variation in Prostate-specific Antigen Screening Trends Following the 2011 United States Preventive Services Task Force Panel Update.

PubMed

Vetterlein, Malte W; Dalela, Deepansh; Sammon, Jesse D; Karabon, Patrick; Sood, Akshay; Jindal, Tarun; Meyer, Christian P; Löppenberg, Björn; Sun, Maxine; Trinh, Quoc-Dien; Menon, Mani; Abdollah, Firas

2018-02-01

To evaluate state-by-state trends in prostate-specific antigen (PSA) screening prevalence after the 2011 United States Preventive Services Task Force (USPSTF) recommendation against this practice. We included 222,475 men who responded to the Behavioral Risk Factor Surveillance System 2012 and 2014 surveys, corresponding to early and late post-USPSTF populations. Logistic regression was used to identify predictors of PSA screening and to calculate the adjusted and weighted state-by-state PSA screening prevalence and respective relative percent changes between 2012 and 2014. To account for unmeasured factors, the correlation between changes in PSA screening over time and changes in screening for colorectal and breast cancer were assessed. All analyses were conducted in 2016. Overall, 38.9% (95% confidence interval [CI] = 38.6%-39.2%) reported receiving PSA screening in 2012 vs 35.8% (95% CI = 35.1%-36.2%) in 2014. State of residence, age, race, education, income, insurance, access to care, marital status, and smoking status were independent predictors of PSA screening in both years (all P <.001). In adjusted analyses, the nationwide PSA screening prevalence decreased by a relative 8.5% (95% CI = 6.4%-10.5%; P <.001) between 2012 and 2014. There was a vast state-by-state heterogeneity, ranging from a relative 26.6% decrease in Vermont to 10.2% increase in Hawaii. Overall, 81.5% and 84.0% of the observed changes were not accompanied by matching changes in respective colorectal and breast cancer screening utilization, for which there were no updates in USPSTF recommendations. There is a significant state-by-state variation in PSA screening trends following the 2011 USPSTF recommendation. Further research is needed to elucidate the reasons for this heterogeneity in screening behavior among the states. Copyright © 2017 Elsevier Inc. All rights reserved.

State space truncation with quantified errors for accurate solutions to discrete Chemical Master Equation

PubMed Central

Cao, Youfang; Terebus, Anna; Liang, Jie

2016-01-01

The discrete chemical master equation (dCME) provides a general framework for studying stochasticity in mesoscopic reaction networks. Since its direct solution rapidly becomes intractable due to the increasing size of the state space, truncation of the state space is necessary for solving most dCMEs. It is therefore important to assess the consequences of state space truncations so errors can be quantified and minimized. Here we describe a novel method for state space truncation. By partitioning a reaction network into multiple molecular equivalence groups (MEG), we truncate the state space by limiting the total molecular copy numbers in each MEG. We further describe a theoretical framework for analysis of the truncation error in the steady state probability landscape using reflecting boundaries. By aggregating the state space based on the usage of a MEG and constructing an aggregated Markov process, we show that the truncation error of a MEG can be asymptotically bounded by the probability of states on the reflecting boundary of the MEG. Furthermore, truncating states of an arbitrary MEG will not undermine the estimated error of truncating any other MEGs. We then provide an overall error estimate for networks with multiple MEGs. To rapidly determine the appropriate size of an arbitrary MEG, we also introduce an a priori method to estimate the upper bound of its truncation error. This a priori estimate can be rapidly computed from reaction rates of the network, without the need of costly trial solutions of the dCME. As examples, we show results of applying our methods to the four stochastic networks of 1) the birth and death model, 2) the single gene expression model, 3) the genetic toggle switch model, and 4) the phage lambda bistable epigenetic switch model. We demonstrate how truncation errors and steady state probability landscapes can be computed using different sizes of the MEG(s) and how the results validate out theories. Overall, the novel state space truncation and error analysis methods developed here can be used to ensure accurate direct solutions to the dCME for a large number of stochastic networks. PMID:27105653

State Space Truncation with Quantified Errors for Accurate Solutions to Discrete Chemical Master Equation

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

Cao, Youfang; Terebus, Anna; Liang, Jie

The discrete chemical master equation (dCME) provides a general framework for studying stochasticity in mesoscopic reaction networks. Since its direct solution rapidly becomes intractable due to the increasing size of the state space, truncation of the state space is necessary for solving most dCMEs. It is therefore important to assess the consequences of state space truncations so errors can be quantified and minimized. Here we describe a novel method for state space truncation. By partitioning a reaction network into multiple molecular equivalence groups (MEGs), we truncate the state space by limiting the total molecular copy numbers in each MEG. Wemore » further describe a theoretical framework for analysis of the truncation error in the steady-state probability landscape using reflecting boundaries. By aggregating the state space based on the usage of a MEG and constructing an aggregated Markov process, we show that the truncation error of a MEG can be asymptotically bounded by the probability of states on the reflecting boundary of the MEG. Furthermore, truncating states of an arbitrary MEG will not undermine the estimated error of truncating any other MEGs. We then provide an overall error estimate for networks with multiple MEGs. To rapidly determine the appropriate size of an arbitrary MEG, we also introduce an a priori method to estimate the upper bound of its truncation error. This a priori estimate can be rapidly computed from reaction rates of the network, without the need of costly trial solutions of the dCME. As examples, we show results of applying our methods to the four stochastic networks of (1) the birth and death model, (2) the single gene expression model, (3) the genetic toggle switch model, and (4) the phage lambda bistable epigenetic switch model. We demonstrate how truncation errors and steady-state probability landscapes can be computed using different sizes of the MEG(s) and how the results validate our theories. Overall, the novel state space truncation and error analysis methods developed here can be used to ensure accurate direct solutions to the dCME for a large number of stochastic networks.« less

State Space Truncation with Quantified Errors for Accurate Solutions to Discrete Chemical Master Equation

DOE PAGES

Cao, Youfang; Terebus, Anna; Liang, Jie

2016-04-22

The discrete chemical master equation (dCME) provides a general framework for studying stochasticity in mesoscopic reaction networks. Since its direct solution rapidly becomes intractable due to the increasing size of the state space, truncation of the state space is necessary for solving most dCMEs. It is therefore important to assess the consequences of state space truncations so errors can be quantified and minimized. Here we describe a novel method for state space truncation. By partitioning a reaction network into multiple molecular equivalence groups (MEGs), we truncate the state space by limiting the total molecular copy numbers in each MEG. Wemore » further describe a theoretical framework for analysis of the truncation error in the steady-state probability landscape using reflecting boundaries. By aggregating the state space based on the usage of a MEG and constructing an aggregated Markov process, we show that the truncation error of a MEG can be asymptotically bounded by the probability of states on the reflecting boundary of the MEG. Furthermore, truncating states of an arbitrary MEG will not undermine the estimated error of truncating any other MEGs. We then provide an overall error estimate for networks with multiple MEGs. To rapidly determine the appropriate size of an arbitrary MEG, we also introduce an a priori method to estimate the upper bound of its truncation error. This a priori estimate can be rapidly computed from reaction rates of the network, without the need of costly trial solutions of the dCME. As examples, we show results of applying our methods to the four stochastic networks of (1) the birth and death model, (2) the single gene expression model, (3) the genetic toggle switch model, and (4) the phage lambda bistable epigenetic switch model. We demonstrate how truncation errors and steady-state probability landscapes can be computed using different sizes of the MEG(s) and how the results validate our theories. Overall, the novel state space truncation and error analysis methods developed here can be used to ensure accurate direct solutions to the dCME for a large number of stochastic networks.« less

State-of-the-art of photorefractive holographic interferometry and potentialities for space applications

NASA Astrophysics Data System (ADS)

Georges, Marc; Lemaire, Philippe; Pauliat, Gilles; Launay, Jean-Claude; Roosen, Gérald

2018-04-01

This paper, "State-of-the-art of photorefractive holographic interferometry and potentialities for space applications," was presented as part of International Conference on Space Optics—ICSO 1997, held in Toulouse, France.

KENNEDY SPACE CENTER, FLA. - Dignitaries, invited guests, space center employees, and the media show their appreciation for the speakers at a dedication and ribbon-cutting ceremony for the Space Life Sciences Lab hosted by NASA-Kennedy Space Center and the state of Florida at the new lab. Completed in August, the facility encompasses more than 100,000 square feet and was formerly known as the Space Experiment Research and Processing Laboratory or SERPL. The state, through the Florida Space Authority, built the research lab which is host to NASA, NASA’s Life Sciences Services contractor Dynamac Corp., Bionetics Corp., and researchers from the University of Florida. Dynamac Corp. leases the facility. The Florida Space Research Institute is responsible for gaining additional tenants from outside the NASA community.

NASA Image and Video Library

2003-11-19

KENNEDY SPACE CENTER, FLA. - Dignitaries, invited guests, space center employees, and the media show their appreciation for the speakers at a dedication and ribbon-cutting ceremony for the Space Life Sciences Lab hosted by NASA-Kennedy Space Center and the state of Florida at the new lab. Completed in August, the facility encompasses more than 100,000 square feet and was formerly known as the Space Experiment Research and Processing Laboratory or SERPL. The state, through the Florida Space Authority, built the research lab which is host to NASA, NASA’s Life Sciences Services contractor Dynamac Corp., Bionetics Corp., and researchers from the University of Florida. Dynamac Corp. leases the facility. The Florida Space Research Institute is responsible for gaining additional tenants from outside the NASA community.

Spirituality moderates the relationship of psychosocial stress to metabolic risk factors among Afro-Caribbean immigrants in the US Virgin Islands.

PubMed

Tull, Eugene S; Doswell, Willa M; Cort, Malcolm A

2015-03-01

Spirituality may contribute to the health advantage of foreign-born blacks compared to United States (US)-born blacks. The objective of this study was to test the hypothesis that spirituality attenuates the association of psychosocial stress to stress-associated metabolic risk factors among foreign-born Caribbean blacks living in a US jurisdiction. Data on demographic factors, anthropometric measurements (height, weight and waist), fasting glucose and insulin, lifestyle behaviors (smoking and alcohol use), psychosocial stress and spirituality were collected from a population-based sample of 319 Afro-Caribbean immigrants, ages 20 and older, who were recruited between 1995 and 2000 in the Virgin Islands of the United States (USVI). Glucose and insulin measurements were used to estimate insulin resistance by the homeostasis model assessment (HOMA-IR) method. Participants were classified into three levels of spirituality, "low", "medium" and "high" based on the distribution of spirituality scores. Stepwise regression analyses were used to identify the significant predictors of waist circumference and HOMA-IR within each level of spirituality. The predictors of waist circumference and HOMA-IR varied across the levels of spirituality. Psychosocial stress was an independent predictor of waist and HOMA-IR only among participants with a low level of spirituality. Spirituality appears to attenuate the association of psychosocial stress to waist circumference and insulin resistance among Afro-Caribbean immigrants in the USVI.

Prevalence and Predictors of Herbal Medicine Use Among Adults in the United States.

PubMed

Rashrash, Mohamed; Schommer, Jon C; Brown, Lawrence M

2017-09-01

To describe the prevalence of herbal medicine use among US adults and to assess factors associated with and predictors of herbal use. The data for herbal products use were collected from the 2015 National Consumer Survey on the Medication Experience and Pharmacists' Roles. Chi-square test was used to analyz factors associated with herbal use, and predictors of herbal use were assessed with logistic regression analysis. Factors associated with herbal supplement use include age older than 70, having a higher than high school education, using prescription medications or over-the-counter (OTC) medications, and using a mail-order pharmacy." All Disease state associated significantly with herbal use. Approximately thirty-eight percent of those who used herbals used prescription medications and 42% of those who used herbals also used an OTC medication. The most frequent conditions associated with herbal supplement use were a stroke (48.7%), cancer (43.1%), and arthritis (43.0%). Among herbal product users, factors that predicted use included having higher than school education, using OTC medications, using mail-order pharmacy, stroke, obesity, arthritis, and breathing problems. More than one-third of respondents reported using herbal supplements. Older age and higher education were associated with a higher use of herbal supplements. People with chronic diseases are more likely to use herbal medicines than others. OTC drug users and patients with stroke are more likely to use herbal medicines than others.

Using "Big Data" Versus Alternative Measures of Aggregate Data to Predict the U.S. 2016 Presidential Election.

PubMed

Ma-Kellams, Christine; Bishop, Brianna; Zhang, Mei Fong; Villagrana, Brian

2017-01-01

To what extent could "Big Data" predict the results of the 2016 U.S. presidential election better than more conventional sources of aggregate measures? To test this idea, the present research used Google search trends versus other forms of state-level data (i.e., both behavioral measures like the incidence of hate crimes, hate groups, and police brutality and implicit measures like Implicit Association Test (IAT) data) to predict each state's popular vote for the 2016 presidential election. Results demonstrate that, when taken in isolation, zero-order correlations reveal that prevalence of hate groups, prevalence of hate crimes, Google searches for racially charged terms (i.e., related to White supremacy groups, racial slurs, and the Nazi movement), and political conservatism were all significant predictors of popular support for Trump. However, subsequent hierarchical regression analyses show that when these predictors are considered simultaneously, only Google search data for historical White supremacy terms (e.g., "Adolf Hitler") uniquely predicted election outcomes earlier and beyond political conservatism. Thus, Big Data, in the form of Google search, emerged as a more potent predictor of political behavior than other aggregate measures, including implicit attitudes and behavioral measures of racial bias. Implications for the role of racial bias in the 2016 presidential election in particular and the utility of Google search data more generally are discussed.