Quantitative analysis of crystalline pharmaceuticals in tablets by pattern-fitting procedure using X-ray diffraction pattern.

PubMed

Takehira, Rieko; Momose, Yasunori; Yamamura, Shigeo

2010-10-15

A pattern-fitting procedure using an X-ray diffraction pattern was applied to the quantitative analysis of binary system of crystalline pharmaceuticals in tablets. Orthorhombic crystals of isoniazid (INH) and mannitol (MAN) were used for the analysis. Tablets were prepared under various compression pressures using a direct compression method with various compositions of INH and MAN. Assuming that X-ray diffraction pattern of INH-MAN system consists of diffraction intensities from respective crystals, observed diffraction intensities were fitted to analytic expression based on X-ray diffraction theory and separated into two intensities from INH and MAN crystals by a nonlinear least-squares procedure. After separation, the contents of INH were determined by using the optimized normalization constants for INH and MAN. The correction parameter including all the factors that are beyond experimental control was required for quantitative analysis without calibration curve. The pattern-fitting procedure made it possible to determine crystalline phases in the range of 10-90% (w/w) of the INH contents. Further, certain characteristics of the crystals in the tablets, such as the preferred orientation, size of crystallite, and lattice disorder were determined simultaneously. This method can be adopted to analyze compounds whose crystal structures are known. It is a potentially powerful tool for the quantitative phase analysis and characterization of crystals in tablets and powders using X-ray diffraction patterns. Copyright 2010 Elsevier B.V. All rights reserved.

A hidden Markov model approach to neuron firing patterns.

PubMed

Camproux, A C; Saunier, F; Chouvet, G; Thalabard, J C; Thomas, G

1996-11-01

Analysis and characterization of neuronal discharge patterns are of interest to neurophysiologists and neuropharmacologists. In this paper we present a hidden Markov model approach to modeling single neuron electrical activity. Basically the model assumes that each interspike interval corresponds to one of several possible states of the neuron. Fitting the model to experimental series of interspike intervals by maximum likelihood allows estimation of the number of possible underlying neuron states, the probability density functions of interspike intervals corresponding to each state, and the transition probabilities between states. We present an application to the analysis of recordings of a locus coeruleus neuron under three pharmacological conditions. The model distinguishes two states during halothane anesthesia and during recovery from halothane anesthesia, and four states after administration of clonidine. The transition probabilities yield additional insights into the mechanisms of neuron firing.

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

PubMed

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

2018-01-01

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

Gap Gene Regulatory Dynamics Evolve along a Genotype Network

PubMed Central

Crombach, Anton; Wotton, Karl R.; Jiménez-Guri, Eva; Jaeger, Johannes

2016-01-01

Developmental gene networks implement the dynamic regulatory mechanisms that pattern and shape the organism. Over evolutionary time, the wiring of these networks changes, yet the patterning outcome is often preserved, a phenomenon known as “system drift.” System drift is illustrated by the gap gene network—involved in segmental patterning—in dipteran insects. In the classic model organism Drosophila melanogaster and the nonmodel scuttle fly Megaselia abdita, early activation and placement of gap gene expression domains show significant quantitative differences, yet the final patterning output of the system is essentially identical in both species. In this detailed modeling analysis of system drift, we use gene circuits which are fit to quantitative gap gene expression data in M. abdita and compare them with an equivalent set of models from D. melanogaster. The results of this comparative analysis show precisely how compensatory regulatory mechanisms achieve equivalent final patterns in both species. We discuss the larger implications of the work in terms of “genotype networks” and the ways in which the structure of regulatory networks can influence patterns of evolutionary change (evolvability). PMID:26796549

Characterization and Measurements from the Infrared Grazing Angle Reflectometer

DTIC Science & Technology

2012-06-14

18 3. List of sample scatter pattern fitting values. All values were taken from Ngan’s paper ”Experimental Analysis of BRDF Models - Supplemental” [1...using a BRDF model , and the absorptance can be modeled using a Fresnel absorptance. After defining both of these values, we can calculate the power seen... BRDF model of the face of the detector. This paper will examine the case of a flat detector with some index of refraction n. This air-detector

The Effects of industrial workers' food choice attribute on sugar intake pattern and job satisfaction with Structural Equcation Model

PubMed Central

Park, Young Il

2016-01-01

BACKGROUND/OBJECTIVES This research analyzes the effects of the food choices of industrial workers according to their sugar intake pattern on their job satisfaction through the construction of a model on the relationship between sugar intake pattern and job satisfaction. SUBJECTS/METHODS Surveys were collected from May to July 2015. A statistical analysis of the 775 surveys from Kyungsangnam-do was conducted using SPSS13.0 for Windows and SEM was performed using the AMOS 5.0 statistics package. RESULTS The reliability of the data was confirmed by an exploratory factor analysis through a Cronbach's alpha coefficient, and the measurement model was proven to be appropriate by a confirmatory factor analysis in conjunction with AMOS. The results of factor analysis on food choice, sugar intake pattern and job satisfaction were categorized into five categories. The reliability of these findings was supported by a Cronbach's alpha coefficient of 0.6 and higher for all factors except confection (0.516) and dairy products (0.570). The multicollinearity results did not indicate a problem between the variables since the highest correlation coefficient was 0.494 (P < 0.01). In an attempt to study the sugar intake pattern in accordance with the food choices and job satisfaction of industrial workers, a structural equation model was constructed and analyzed. CONCLUSIONS All tests confirmed that the model satisfied the recommended levels for the goodness of fit index, and thus, the overall research model was proven to be appropriate. PMID:27478555

A methodological approach to short-term tracking of youth physical fitness: the Oporto Growth, Health and Performance Study.

PubMed

Souza, Michele; Eisenmann, Joey; Chaves, Raquel; Santos, Daniel; Pereira, Sara; Forjaz, Cláudia; Maia, José

2016-10-01

In this paper, three different statistical approaches were used to investigate short-term tracking of cardiorespiratory and performance-related physical fitness among adolescents. Data were obtained from the Oporto Growth, Health and Performance Study and comprised 1203 adolescents (549 girls) divided into two age cohorts (10-12 and 12-14 years) followed for three consecutive years, with annual assessment. Cardiorespiratory fitness was assessed with 1-mile run/walk test; 50-yard dash, standing long jump, handgrip, and shuttle run test were used to rate performance-related physical fitness. Tracking was expressed in three different ways: auto-correlations, multilevel modelling with crude and adjusted model (for biological maturation, body mass index, and physical activity), and Cohen's Kappa (κ) computed in IBM SPSS 20.0, HLM 7.01 and Longitudinal Data Analysis software, respectively. Tracking of physical fitness components was (1) moderate-to-high when described by auto-correlations; (2) low-to-moderate when crude and adjusted models were used; and (3) low according to Cohen's Kappa (κ). These results demonstrate that when describing tracking, different methods should be considered since they provide distinct and more comprehensive views about physical fitness stability patterns.

A hidden Markov model approach to neuron firing patterns.

PubMed Central

Camproux, A C; Saunier, F; Chouvet, G; Thalabard, J C; Thomas, G

1996-01-01

Analysis and characterization of neuronal discharge patterns are of interest to neurophysiologists and neuropharmacologists. In this paper we present a hidden Markov model approach to modeling single neuron electrical activity. Basically the model assumes that each interspike interval corresponds to one of several possible states of the neuron. Fitting the model to experimental series of interspike intervals by maximum likelihood allows estimation of the number of possible underlying neuron states, the probability density functions of interspike intervals corresponding to each state, and the transition probabilities between states. We present an application to the analysis of recordings of a locus coeruleus neuron under three pharmacological conditions. The model distinguishes two states during halothane anesthesia and during recovery from halothane anesthesia, and four states after administration of clonidine. The transition probabilities yield additional insights into the mechanisms of neuron firing. Images FIGURE 3 PMID:8913581

Factor Covariance Analysis in Subgroups.

ERIC Educational Resources Information Center

Pennell, Roger

The problem considered is that of an investigator sampling two or more correlation matrices and desiring to fit a model where a factor pattern matrix is assumed to be identical across samples and we need to estimate only the factor covariance matrix and the unique variance for each sample. A flexible, least squares solution is worked out and…

Person-Fit Statistics for Joint Models for Accuracy and Speed

ERIC Educational Resources Information Center

Fox, Jean-Paul; Marianti, Sukaesi

2017-01-01

Response accuracy and response time data can be analyzed with a joint model to measure ability and speed of working, while accounting for relationships between item and person characteristics. In this study, person-fit statistics are proposed for joint models to detect aberrant response accuracy and/or response time patterns. The person-fit tests…

Selective sweeps in growing microbial colonies

NASA Astrophysics Data System (ADS)

Korolev, Kirill S.; Müller, Melanie J. I.; Karahan, Nilay; Murray, Andrew W.; Hallatschek, Oskar; Nelson, David R.

2012-04-01

Evolutionary experiments with microbes are a powerful tool to study mutations and natural selection. These experiments, however, are often limited to the well-mixed environments of a test tube or a chemostat. Since spatial organization can significantly affect evolutionary dynamics, the need is growing for evolutionary experiments in spatially structured environments. The surface of a Petri dish provides such an environment, but a more detailed understanding of microbial growth on Petri dishes is necessary to interpret such experiments. We formulate a simple deterministic reaction-diffusion model, which successfully predicts the spatial patterns created by two competing species during colony expansion. We also derive the shape of these patterns analytically without relying on microscopic details of the model. In particular, we find that the relative fitness of two microbial strains can be estimated from the logarithmic spirals created by selective sweeps. The theory is tested with strains of the budding yeast Saccharomyces cerevisiae for spatial competitions with different initial conditions and for a range of relative fitnesses. The reaction-diffusion model also connects the microscopic parameters like growth rates and diffusion constants with macroscopic spatial patterns and predicts the relationship between fitness in liquid cultures and on Petri dishes, which we confirmed experimentally. Spatial sector patterns therefore provide an alternative fitness assay to the commonly used liquid culture fitness assays.

Bayesian Computation for Log-Gaussian Cox Processes: A Comparative Analysis of Methods

PubMed Central

Teng, Ming; Nathoo, Farouk S.; Johnson, Timothy D.

2017-01-01

The Log-Gaussian Cox Process is a commonly used model for the analysis of spatial point pattern data. Fitting this model is difficult because of its doubly-stochastic property, i.e., it is an hierarchical combination of a Poisson process at the first level and a Gaussian Process at the second level. Various methods have been proposed to estimate such a process, including traditional likelihood-based approaches as well as Bayesian methods. We focus here on Bayesian methods and several approaches that have been considered for model fitting within this framework, including Hamiltonian Monte Carlo, the Integrated nested Laplace approximation, and Variational Bayes. We consider these approaches and make comparisons with respect to statistical and computational efficiency. These comparisons are made through several simulation studies as well as through two applications, the first examining ecological data and the second involving neuroimaging data. PMID:29200537

Analysis of dynamics and fit of diving suits

NASA Astrophysics Data System (ADS)

Mahnic Naglic, M.; Petrak, S.; Gersak, J.; Rolich, T.

2017-10-01

Paper presents research on dynamical behaviour and fit analysis of customised diving suits. Diving suits models are developed using the 3D flattening method, which enables the construction of a garment model directly on the 3D computer body model and separation of discrete 3D surfaces as well as transformation into 2D cutting parts. 3D body scanning of male and female test subjects was performed with the purpose of body measurements analysis in static and dynamic postures and processed body models were used for construction and simulation of diving suits prototypes. All necessary parameters, for 3D simulation were applied on obtained cutting parts, as well as parameters values for mechanical properties of neoprene material. Developed computer diving suits prototypes were used for stretch analysis on areas relevant for body dimensional changes according to dynamic anthropometrics. Garment pressures against the body in static and dynamic conditions was also analysed. Garments patterns for which the computer prototype verification was conducted were used for real prototype production. Real prototypes were also used for stretch and pressure analysis in static and dynamic conditions. Based on the obtained results, correlation analysis between body changes in dynamic positions and dynamic stress, determined on computer and real prototypes, was performed.

Patterns of medicinal plant use: an examination of the Ecuadorian Shuar medicinal flora using contingency table and binomial analyses.

PubMed

Bennett, Bradley C; Husby, Chad E

2008-03-28

Botanical pharmacopoeias are non-random subsets of floras, with some taxonomic groups over- or under-represented. Moerman [Moerman, D.E., 1979. Symbols and selectivity: a statistical analysis of Native American medical ethnobotany, Journal of Ethnopharmacology 1, 111-119] introduced linear regression/residual analysis to examine these patterns. However, regression, the commonly-employed analysis, suffers from several statistical flaws. We use contingency table and binomial analyses to examine patterns of Shuar medicinal plant use (from Amazonian Ecuador). We first analyzed the Shuar data using Moerman's approach, modified to better meet requirements of linear regression analysis. Second, we assessed the exact randomization contingency table test for goodness of fit. Third, we developed a binomial model to test for non-random selection of plants in individual families. Modified regression models (which accommodated assumptions of linear regression) reduced R(2) to from 0.59 to 0.38, but did not eliminate all problems associated with regression analyses. Contingency table analyses revealed that the entire flora departs from the null model of equal proportions of medicinal plants in all families. In the binomial analysis, only 10 angiosperm families (of 115) differed significantly from the null model. These 10 families are largely responsible for patterns seen at higher taxonomic levels. Contingency table and binomial analyses offer an easy and statistically valid alternative to the regression approach.

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

PubMed Central

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

2018-01-01

Background Among combat sports, Judo and Brazilian Jiu-Jitsu (BJJ) present elevated physical fitness demands from the high-intensity intermittent efforts. However, information regarding how metabolic and neuromuscular physical fitness is associated with technical-tactical performance in Judo and BJJ fights is not available. This study aimed to relate indicators of physical fitness with combat performance variables in Judo and BJJ. Methods The sample consisted of Judo (n = 16) and BJJ (n = 24) male athletes. At the first meeting, the physical tests were applied and, in the second, simulated fights were performed for later notational analysis. Results The main findings indicate: (i) high reproducibility of the proposed instrument and protocol used for notational analysis in a mobile device; (ii) differences in the technical-tactical and time-motion patterns between modalities; (iii) performance-related variables are different in Judo and BJJ; and (iv) regression models based on metabolic fitness variables may account for up to 53% of the variances in technical-tactical and/or time-motion variables in Judo and up to 31% in BJJ, whereas neuromuscular fitness models can reach values up to 44 and 73% of prediction in Judo and BJJ, respectively. When all components are combined, they can explain up to 90% of high intensity actions in Judo. Discussion In conclusion, performance prediction models in simulated combat indicate that anaerobic, aerobic and neuromuscular fitness variables contribute to explain time-motion variables associated with high intensity and technical-tactical variables in Judo and BJJ fights. PMID:29844991

Patterns of Dating Violence Perpetration and Victimization in U.S. Young Adult Males and Females.

PubMed

Spencer, Rachael A; Renner, Lynette M; Clark, Cari Jo

2016-09-01

Dating violence (DV) is frequently reported by young adults in intimate relationships in the United States, but little is known about patterns of DV perpetration and victimization. In this study, we examined sexual and physical violence perpetration and victimization reported by young adults to determine how the violence patterns differ by sex and race/ethnicity. Data from non-Hispanic White, non-Hispanic Black, and Hispanic participants in Wave 3 of the National Longitudinal Study of Adolescent to Adult Health were analyzed. DV was assessed using responses to four questions focused on perpetration and four questions focused on victimization. The information on DV was taken from the most violent relationship reported by participants prior to Wave 3. Latent class analysis was first conducted separately by sex, adjusting for age, race/ethnicity, and financial stress, then by race/ethnicity, adjusting for age and financial stress. Relative model fit was established by comparing Bayesian Information Criteria (BIC), adjusted BIC, entropy, interpretability of latent classes, and certainty of latent class assignment for covariate-adjusted models. The results indicate that patterns of violence differed by sex and for females, by race/ethnicity. A three-class model was the best fit for males. For females, separate four-class models were parsimonious for White, Black, and Hispanic females. Financial stress was a significant predictor of violence classification for males and females and age predicted membership in White and Black female models. Variations in DV patterns by sex and race/ethnicity suggest the need for a more nuanced understanding of differences in DV. © The Author(s) 2015.

The Role of River Morphodynamic Disturbance and Groundwater Hydrology As Driving Factors of Riparian Landscape Patterns in Mediterranean Rivers.

PubMed

Rivaes, Rui; Pinheiro, António N; Egger, Gregory; Ferreira, Teresa

2017-01-01

Fluvial disturbances, especially floods and droughts, are the main drivers of the successional patterns of riparian vegetation. Those disturbances control the riparian landscape dynamics through the direct interaction between flow and vegetation. The main aim of this work is to investigate the specific paths by which fluvial disturbances, distributed by its components of groundwater hydrology (grndh) and morphodynamic disturbance (mrphd), drive riparian landscape patterns as characterized by the location (position in the river corridor) and shape (physical form of the patch) of vegetation patches in Mediterranean rivers. Specifically, this work assesses how the different components of fluvial disturbances affect these features in general and particularly in each succession phase of riparian vegetation. grndh and mrphd were defined by time and intensity weighted indexes calculated, respectively, from the mean annual water table elevations and the annual maximum instantaneous discharge shear stresses of the previous decade. The interactions between riparian landscape features and fluvial disturbances were assessed by confirmatory factor analysis using structural equation modeling. Two hypothetical models for patch location and shape were conceptualized and tested against empirical data collected from 220 patches at four different study sites. Both models were successfully fitted, meaning that they adequately depicted the relationships between the variables. Furthermore, the models achieved a good adjustment for the observed data, based on the evaluation of several approximate fit indexes. The patch location model explained approximately 80% of the patch location variability, demonstrating that the location of the riparian patches is primarily driven by grndh, while the mrphd had very little effect on this feature. In a multigroup analysis regarding the succession phases of riparian vegetation, the fitted model explained more than 68% of the variance of the data, confirming the results of the general model. The patch shape model explained nearly 13% of the patch shape variability, in which the disturbances came to have less influence on driving this feature. However, grndh continues to be the primary driver of riparian vegetation between the two disturbance factors, despite the proportional increase of the mrphd effect to approximately a third of the grndh effect.

The Role of River Morphodynamic Disturbance and Groundwater Hydrology As Driving Factors of Riparian Landscape Patterns in Mediterranean Rivers

PubMed Central

Rivaes, Rui; Pinheiro, António N.; Egger, Gregory; Ferreira, Teresa

2017-01-01

Fluvial disturbances, especially floods and droughts, are the main drivers of the successional patterns of riparian vegetation. Those disturbances control the riparian landscape dynamics through the direct interaction between flow and vegetation. The main aim of this work is to investigate the specific paths by which fluvial disturbances, distributed by its components of groundwater hydrology (grndh) and morphodynamic disturbance (mrphd), drive riparian landscape patterns as characterized by the location (position in the river corridor) and shape (physical form of the patch) of vegetation patches in Mediterranean rivers. Specifically, this work assesses how the different components of fluvial disturbances affect these features in general and particularly in each succession phase of riparian vegetation. grndh and mrphd were defined by time and intensity weighted indexes calculated, respectively, from the mean annual water table elevations and the annual maximum instantaneous discharge shear stresses of the previous decade. The interactions between riparian landscape features and fluvial disturbances were assessed by confirmatory factor analysis using structural equation modeling. Two hypothetical models for patch location and shape were conceptualized and tested against empirical data collected from 220 patches at four different study sites. Both models were successfully fitted, meaning that they adequately depicted the relationships between the variables. Furthermore, the models achieved a good adjustment for the observed data, based on the evaluation of several approximate fit indexes. The patch location model explained approximately 80% of the patch location variability, demonstrating that the location of the riparian patches is primarily driven by grndh, while the mrphd had very little effect on this feature. In a multigroup analysis regarding the succession phases of riparian vegetation, the fitted model explained more than 68% of the variance of the data, confirming the results of the general model. The patch shape model explained nearly 13% of the patch shape variability, in which the disturbances came to have less influence on driving this feature. However, grndh continues to be the primary driver of riparian vegetation between the two disturbance factors, despite the proportional increase of the mrphd effect to approximately a third of the grndh effect. PMID:28979278

Detailed temporal structure of communication networks in groups of songbirds.

PubMed

Stowell, Dan; Gill, Lisa; Clayton, David

2016-06-01

Animals in groups often exchange calls, in patterns whose temporal structure may be influenced by contextual factors such as physical location and the social network structure of the group. We introduce a model-based analysis for temporal patterns of animal call timing, originally developed for networks of firing neurons. This has advantages over cross-correlation analysis in that it can correctly handle common-cause confounds and provides a generative model of call patterns with explicit parameters for the influences between individuals. It also has advantages over standard Markovian analysis in that it incorporates detailed temporal interactions which affect timing as well as sequencing of calls. Further, a fitted model can be used to generate novel synthetic call sequences. We apply the method to calls recorded from groups of domesticated zebra finch (Taeniopygia guttata) individuals. We find that the communication network in these groups has stable structure that persists from one day to the next, and that 'kernels' reflecting the temporal range of influence have a characteristic structure for a calling individual's effect on itself, its partner and on others in the group. We further find characteristic patterns of influences by call type as well as by individual. © 2016 The Authors.

Statistical approaches to account for missing values in accelerometer data: Applications to modeling physical activity.

PubMed

Yue Xu, Selene; Nelson, Sandahl; Kerr, Jacqueline; Godbole, Suneeta; Patterson, Ruth; Merchant, Gina; Abramson, Ian; Staudenmayer, John; Natarajan, Loki

2018-04-01

Physical inactivity is a recognized risk factor for many chronic diseases. Accelerometers are increasingly used as an objective means to measure daily physical activity. One challenge in using these devices is missing data due to device nonwear. We used a well-characterized cohort of 333 overweight postmenopausal breast cancer survivors to examine missing data patterns of accelerometer outputs over the day. Based on these observed missingness patterns, we created psuedo-simulated datasets with realistic missing data patterns. We developed statistical methods to design imputation and variance weighting algorithms to account for missing data effects when fitting regression models. Bias and precision of each method were evaluated and compared. Our results indicated that not accounting for missing data in the analysis yielded unstable estimates in the regression analysis. Incorporating variance weights and/or subject-level imputation improved precision by >50%, compared to ignoring missing data. We recommend that these simple easy-to-implement statistical tools be used to improve analysis of accelerometer data.

Cardiorespiratory fitness is positively associated with a healthy dietary pattern in New Zealand adolescents.

PubMed

Howe, Anna S; Skidmore, Paula M L; Parnell, Winsome R; Wong, Jyh Eiin; Lubransky, Alexandra C; Black, Katherine E

2016-05-01

To examine the association between cardiorespiratory fitness and dietary patterns in adolescents. Food choice was assessed using the validated New Zealand Adolescent FFQ. Principal components analysis was used to determine dietary patterns. Trained research assistants measured participants' height and body mass. Cardiorespiratory fitness was assessed in a subset of participants using the multistage 20 m shuttle run. The level and stage were recorded, and the corresponding VO2max was calculated. Differences in mean VO2max according to sex and BMI were assessed using t tests, while associations between cardiorespiratory fitness and dietary patterns were examined using linear regression analyses adjusted for age, sex, school attended, socio-economic deprivation and BMI. Secondary schools in Otago, New Zealand. Students (n 279) aged 14-18 years who completed an online lifestyle survey during a class period. Principal components analysis produced three dietary patterns: 'Treat Foods', 'Fruits and Vegetables' and 'Basic Foods'. The 279 participants who provided questionnaire data and completed cardiorespiratory fitness testing had a mean age of 15·7 (sd 0·9) years. Mean VO2max was 45·8 (sd 6·9) ml/kg per min. The 'Fruits and Vegetables' pattern was positively associated with VO2max in the total sample (β=0·04; 95%CI 0·02, 0·07), girls (β=0·06; 95% CI 0·03, 0·10) and boys (β=0·03; 95% CI 0·01, 0·05). These results indicate that increase in cardiorespiratory fitness was associated with a healthier dietary pattern, suggesting both should be targeted as part of a global lifestyle approach. Longitudinal studies are needed to confirm this association in relation to health outcomes in New Zealand adolescents.

Estimated landmark calibration of biomechanical models for inverse kinematics.

PubMed

Trinler, Ursula; Baker, Richard

2018-01-01

Inverse kinematics is emerging as the optimal method in movement analysis to fit a multi-segment biomechanical model to experimental marker positions. A key part of this process is calibrating the model to the dimensions of the individual being analysed which requires scaling of the model, pose estimation and localisation of tracking markers within the relevant segment coordinate systems. The aim of this study is to propose a generic technique for this process and test a specific application to the OpenSim model Gait2392. Kinematic data from 10 healthy adult participants were captured in static position and normal walking. Results showed good average static and dynamic fitting errors between virtual and experimental markers of 0.8 cm and 0.9 cm, respectively. Highest fitting errors were found on the epicondyle (static), feet (static, dynamic) and on the thigh (dynamic). These result from inconsistencies between the model geometry and degrees of freedom and the anatomy and movement pattern of the individual participants. A particular limitation is in estimating anatomical landmarks from the bone meshes supplied with Gait2392 which do not conform with the bone morphology of the participants studied. Soft tissue artefact will also affect fitting the model to walking trials. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

Confirmatory factor analysis of the Eating Disorder Examination-Questionnaire: A comparison of five factor solutions across vegan and omnivore participants.

PubMed

Heiss, Sydney; Boswell, James F; Hormes, Julia M

2018-05-01

The Eating Disorder Examination-Questionnaire (EDE-Q) is a valid and reliable measure of eating-related pathology, but its factor structure has proven difficult to replicate. Given differences in dietary patterns in vegans compared to omnivores, proper measurement of eating disorder symptoms is especially important in studies of animal product avoiders. This study compared goodness-of-fit of five alternative models of the EDE-Q in vegans (i.e., individuals refraining from all animal products, n = 318) and omnivores (i.e., individuals not restricting intake of animal products, n = 200). Confirmatory factor analyses were used to compare fit indices of the original four-factor model of the EDE-Q, along with alternative three-, two-, full one-, and brief one-factor models. No model provided adequate fit of the data in either sample of respondents. The fit of the brief one-factor model was the closest to acceptable in omnivores, but did not perform as well in vegans. Indicators of fit were comparable in vegans and omnivores across all other models. Our data confirm difficulties in replicating the proposed factor structure of the EDE-Q, including in vegans. More research is needed to determine the suitability of the EDE-Q for quantifying eating behaviors, including in those abstaining from animal products. © 2018 Wiley Periodicals, Inc.

Genome-wide heterogeneity of nucleotide substitution model fit.

PubMed

Arbiza, Leonardo; Patricio, Mateus; Dopazo, Hernán; Posada, David

2011-01-01

At a genomic scale, the patterns that have shaped molecular evolution are believed to be largely heterogeneous. Consequently, comparative analyses should use appropriate probabilistic substitution models that capture the main features under which different genomic regions have evolved. While efforts have concentrated in the development and understanding of model selection techniques, no descriptions of overall relative substitution model fit at the genome level have been reported. Here, we provide a characterization of best-fit substitution models across three genomic data sets including coding regions from mammals, vertebrates, and Drosophila (24,000 alignments). According to the Akaike Information Criterion (AIC), 82 of 88 models considered were selected as best-fit models at least in one occasion, although with very different frequencies. Most parameter estimates also varied broadly among genes. Patterns found for vertebrates and Drosophila were quite similar and often more complex than those found in mammals. Phylogenetic trees derived from models in the 95% confidence interval set showed much less variance and were significantly closer to the tree estimated under the best-fit model than trees derived from models outside this interval. Although alternative criteria selected simpler models than the AIC, they suggested similar patterns. All together our results show that at a genomic scale, different gene alignments for the same set of taxa are best explained by a large variety of different substitution models and that model choice has implications on different parameter estimates including the inferred phylogenetic trees. After taking into account the differences related to sample size, our results suggest a noticeable diversity in the underlying evolutionary process. All together, we conclude that the use of model selection techniques is important to obtain consistent phylogenetic estimates from real data at a genomic scale.

Low dose aerosol fitness at the innate phase of murine infection better predicts virulence amongst clinical strains of Mycobacterium tuberculosis.

PubMed

Caceres, Neus; Llopis, Isaac; Marzo, Elena; Prats, Clara; Vilaplana, Cristina; de Viedma, Dario Garcia; Samper, Sofía; Lopez, Daniel; Cardona, Pere-Joan

2012-01-01

Evaluation of a quick and easy model to determine the intrinsic ability of clinical strains to generate active TB has been set by assuming that this is linked to the fitness of Mycobacterium tuberculosis strain at the innate phase of the infection. Thus, the higher the bacillary load, the greater the possibility of inducting liquefaction, and thus active TB, once the adaptive response is set. The virulence of seven clinical Mycobacterium tuberculosis strains isolated in Spain was tested by determining the bacillary concentration in the spleen and lung of mice at weeks 0, 1 and 2 after intravenous (IV) inoculation of 10⁴ CFU, and by determining the growth in vitro until the stationary phase had been reached. Cord distribution automated analysis showed two clear patterns related to the high and low fitness in the lung after IV infection. This pattern was not seen in the in vitro fitness tests, which clearly favored the reference strain (H37Rv). Subsequent determination using a more physiological low-dose aerosol (AER) inoculation with 10² CFU showed a third pattern in which the three best values coincided with the highest dissemination capacity according to epidemiological data. The fitness obtained after low dose aerosol administration in the presence of the innate immune response is the most predictive factor for determining the virulence of clinical strains. This gives support to a mechanism of the induction of active TB derived from the dynamic hypothesis of latent tuberculosis infection.

The Many Null Distributions of Person Fit Indices.

ERIC Educational Resources Information Center

Molenaar, Ivo W.; Hoijtink, Herbert

1990-01-01

Statistical properties of person fit indices are reviewed as indicators of the extent to which a person's score pattern is in agreement with a measurement model. Distribution of a fit index and ability-free fit evaluation are discussed. The null distribution was simulated for a test of 20 items. (SLD)

High-Dimensional Sparse Factor Modeling: Applications in Gene Expression Genomics

PubMed Central

Carvalho, Carlos M.; Chang, Jeffrey; Lucas, Joseph E.; Nevins, Joseph R.; Wang, Quanli; West, Mike

2010-01-01

We describe studies in molecular profiling and biological pathway analysis that use sparse latent factor and regression models for microarray gene expression data. We discuss breast cancer applications and key aspects of the modeling and computational methodology. Our case studies aim to investigate and characterize heterogeneity of structure related to specific oncogenic pathways, as well as links between aggregate patterns in gene expression profiles and clinical biomarkers. Based on the metaphor of statistically derived “factors” as representing biological “subpathway” structure, we explore the decomposition of fitted sparse factor models into pathway subcomponents and investigate how these components overlay multiple aspects of known biological activity. Our methodology is based on sparsity modeling of multivariate regression, ANOVA, and latent factor models, as well as a class of models that combines all components. Hierarchical sparsity priors address questions of dimension reduction and multiple comparisons, as well as scalability of the methodology. The models include practically relevant non-Gaussian/nonparametric components for latent structure, underlying often quite complex non-Gaussianity in multivariate expression patterns. Model search and fitting are addressed through stochastic simulation and evolutionary stochastic search methods that are exemplified in the oncogenic pathway studies. Supplementary supporting material provides more details of the applications, as well as examples of the use of freely available software tools for implementing the methodology. PMID:21218139

EVALUATING EFFECTS OF LOW QUALITY HABITATS ON REGIONAL GROWTH IN PEOMYCUS LEUCOPUS: INSIGHTS FROM FIELD-PARAMETERIZED SPATIAL MATRIX MODELS.

EPA Science Inventory

Due to complex population dynamics and source-sink metapopulation processes, animal fitness sometimes varies across landscapes in ways that cannot be deduced from simple density patterns. In this study, we examine spatial patterns in fitness using a combination of intensive fiel...

Multi-scale analysis of a household level agent-based model of landcover change.

PubMed

Evans, Tom P; Kelley, Hugh

2004-08-01

Scale issues have significant implications for the analysis of social and biophysical processes in complex systems. These same scale implications are likewise considerations for the design and application of models of landcover change. Scale issues have wide-ranging effects from the representativeness of data used to validate models to aggregation errors introduced in the model structure. This paper presents an analysis of how scale issues affect an agent-based model (ABM) of landcover change developed for a research area in the Midwest, USA. The research presented here explores how scale factors affect the design and application of agent-based landcover change models. The ABM is composed of a series of heterogeneous agents who make landuse decisions on a portfolio of cells in a raster-based programming environment. The model is calibrated using measures of fit derived from both spatial composition and spatial pattern metrics from multi-temporal landcover data interpreted from historical aerial photography. A model calibration process is used to find a best-fit set of parameter weights assigned to agents' preferences for different landuses (agriculture, pasture, timber production, and non-harvested forest). Previous research using this model has shown how a heterogeneous set of agents with differing preferences for a portfolio of landuses produces the best fit to landcover changes observed in the study area. The scale dependence of the model is explored by varying the resolution of the input data used to calibrate the model (observed landcover), ancillary datasets that affect land suitability (topography), and the resolution of the model landscape on which agents make decisions. To explore the impact of these scale relationships the model is run with input datasets constructed at the following spatial resolutions: 60, 90, 120, 150, 240, 300 and 480 m. The results show that the distribution of landuse-preference weights differs as a function of scale. In addition, with the gradient descent model fitting method used in this analysis the model was not able to converge to an acceptable fit at the 300 and 480 m spatial resolutions. This is a product of the ratio of the input cell resolution to the average parcel size in the landscape. This paper uses these findings to identify scale considerations in the design, development, validation and application of ABMs of landcover change.

Looking Past Primary Productivity: Benchmarking System Processes that Drive Ecosystem Level Responses in Models

NASA Astrophysics Data System (ADS)

Cowdery, E.; Dietze, M.

2017-12-01

As atmospheric levels of carbon dioxide levels continue to increase, it is critical that terrestrial ecosystem models can accurately predict ecological responses to the changing environment. Current predictions of net primary productivity (NPP) in response to elevated atmospheric CO2 concentration are highly variable and contain a considerable amount of uncertainty. Benchmarking model predictions against data are necessary to assess their ability to replicate observed patterns, but also to identify and evaluate the assumptions causing inter-model differences. We have implemented a novel benchmarking workflow as part of the Predictive Ecosystem Analyzer (PEcAn) that is automated, repeatable, and generalized to incorporate different sites and ecological models. Building on the recent Free-Air CO2 Enrichment Model Data Synthesis (FACE-MDS) project, we used observational data from the FACE experiments to test this flexible, extensible benchmarking approach aimed at providing repeatable tests of model process representation that can be performed quickly and frequently. Model performance assessments are often limited to traditional residual error analysis; however, this can result in a loss of critical information. Models that fail tests of relative measures of fit may still perform well under measures of absolute fit and mathematical similarity. This implies that models that are discounted as poor predictors of ecological productivity may still be capturing important patterns. Conversely, models that have been found to be good predictors of productivity may be hiding error in their sub-process that result in the right answers for the wrong reasons. Our suite of tests have not only highlighted process based sources of uncertainty in model productivity calculations, they have also quantified the patterns and scale of this error. Combining these findings with PEcAn's model sensitivity analysis and variance decomposition strengthen our ability to identify which processes need further study and additional data constraints. This can be used to inform future experimental design and in turn can provide an informative starting point for data assimilation.

Turkish version of the Academic Motivation Scale.

PubMed

Can, Gürhan

2015-04-01

The purpose of this study was to adapt the college version of the Academic Motivation Scale (AMS) into Turkish. The participants were 797 college students (437 men, 360 women) with a mean age of 20.1 yr. A seven-factor model of the scale, as well as alternative models (five-, three-, two-, and one-factor models) were investigated and compared through confirmatory factor analysis. The seven-factor model demonstrated adequate fit to the data. The fit indices obtained from the five-factor model were acceptable also. Hancock's coefficient H values and test-retest correlation coefficients of the subscales indicated that reliability of the scale was adequate except for the identified regulation subscale. The CFA conducted for the groups of men and women produced more acceptable fit indices values for men than women, but women obtained significantly higher scores from the AMS subscales. Correlations among the seven subscales partially supported the simplex pattern which claims that the neighboring subscales should have stronger positive correlations than the non-neighboring subscales and that the subscales which are the farthest apart should have the strongest negative relationships.

Proceedings of the Second Annual Symposium on Mathematical Pattern Recognition and Image Analysis Program

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr. (Principal Investigator)

1984-01-01

Several papers addressing image analysis and pattern recognition techniques for satellite imagery are presented. Texture classification, image rectification and registration, spatial parameter estimation, and surface fitting are discussed.

qFeature

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

2015-09-14

This package contains statistical routines for extracting features from multivariate time-series data which can then be used for subsequent multivariate statistical analysis to identify patterns and anomalous behavior. It calculates local linear or quadratic regression model fits to moving windows for each series and then summarizes the model coefficients across user-defined time intervals for each series. These methods are domain agnostic-but they have been successfully applied to a variety of domains, including commercial aviation and electric power grid data.

The Neuronal Transition Probability (NTP) Model for the Dynamic Progression of Non-REM Sleep EEG: The Role of the Suprachiasmatic Nucleus

PubMed Central

Merica, Helli; Fortune, Ronald D.

2011-01-01

Little attention has gone into linking to its neuronal substrates the dynamic structure of non-rapid-eye-movement (NREM) sleep, defined as the pattern of time-course power in all frequency bands across an entire episode. Using the spectral power time-courses in the sleep electroencephalogram (EEG), we showed in the typical first episode, several moves towards-and-away from deep sleep, each having an identical pattern linking the major frequency bands beta, sigma and delta. The neuronal transition probability model (NTP) – in fitting the data well – successfully explained the pattern as resulting from stochastic transitions of the firing-rates of the thalamically-projecting brainstem-activating neurons, alternating between two steady dynamic-states (towards-and-away from deep sleep) each initiated by a so-far unidentified flip-flop. The aims here are to identify this flip-flop and to demonstrate that the model fits well all NREM episodes, not just the first. Using published data on suprachiasmatic nucleus (SCN) activity we show that the SCN has the information required to provide a threshold-triggered flip-flop for timing the towards-and-away alternations, information provided by sleep-relevant feedback to the SCN. NTP then determines the pattern of spectral power within each dynamic-state. NTP was fitted to individual NREM episodes 1–4, using data from 30 healthy subjects aged 20–30 years, and the quality of fit for each NREM measured. We show that the model fits well all NREM episodes and the best-fit probability-set is found to be effectively the same in fitting all subject data. The significant model-data agreement, the constant probability parameter and the proposed role of the SCN add considerable strength to the model. With it we link for the first time findings at cellular level and detailed time-course data at EEG level, to give a coherent picture of NREM dynamics over the entire night and over hierarchic brain levels all the way from the SCN to the EEG. PMID:21886801

Evaluation of two models for predicting elemental accumulation by arthropods

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

Webster, J.R.; Crossley, D.A. Jr.

1978-06-15

Two different models have been proposed for predicting elemental accumulation by arthropods. Parameters of both models can be quantified from radioisotope elimination experiments. Our analysis of the 2 models shows that both predict identical elemental accumulation for a whole organism, though differing in the accumulation in body and gut. We quantified both models with experimental data from /sup 134/Cs and /sup 85/Sr elimination by crickets. Computer simulations of radioisotope accumulation were then compared with actual accumulation experiments. Neither model showed exact fit to the experimental data, though both showed the general pattern of elemental accumulation.

A statistical model of diurnal variation in human growth hormone

NASA Technical Reports Server (NTRS)

Klerman, Elizabeth B.; Adler, Gail K.; Jin, Moonsoo; Maliszewski, Anne M.; Brown, Emery N.

2003-01-01

The diurnal pattern of growth hormone (GH) serum levels depends on the frequency and amplitude of GH secretory events, the kinetics of GH infusion into and clearance from the circulation, and the feedback of GH on its secretion. We present a two-dimensional linear differential equation model based on these physiological principles to describe GH diurnal patterns. The model characterizes the onset times of the secretory events, the secretory event amplitudes, as well as the infusion, clearance, and feedback half-lives of GH. We illustrate the model by using maximum likelihood methods to fit it to GH measurements collected in 12 normal, healthy women during 8 h of scheduled sleep and a 16-h circadian constant-routine protocol. We assess the importance of the model components by using parameter standard error estimates and Akaike's Information Criterion. During sleep, both the median infusion and clearance half-life estimates were 13.8 min, and the median number of secretory events was 2. During the constant routine, the median infusion half-life estimate was 12.6 min, the median clearance half-life estimate was 11.7 min, and the median number of secretory events was 5. The infusion and clearance half-life estimates and the number of secretory events are consistent with current published reports. Our model gave an excellent fit to each GH data series. Our analysis paradigm suggests an approach to decomposing GH diurnal patterns that can be used to characterize the physiological properties of this hormone under normal and pathological conditions.

Confirmatory factor analysis of the PTSD Checklist and the Clinician-Administered PTSD Scale in disaster workers exposed to the World Trade Center Ground Zero.

PubMed

Palmieri, Patrick A; Weathers, Frank W; Difede, JoAnn; King, Dainel W

2007-05-01

Although posttraumatic stress disorder (PTSD) factor analytic research has yielded little support for the DSM-IV 3-factor model of reexperiencing, avoidance, and hyperarousal symptoms, no clear consensus regarding alternative models has emerged. One possible explanation is differential instrumentation across studies. In the present study, the authors used confirmatory factor analysis to compare a self-report measure, the PTSD Checklist (PCL), and a structured clinical interview, the Clinician-Administered PTSD Scale (CAPS), in 2,960 utility workers exposed to the World Trade Center Ground Zero site. Although two 4-factor models fit adequately for each measure, the latent structure of the PCL was slightly better represented by correlated reexperiencing, avoidance, dysphoria, and hyperarousal factors, whereas that of the CAPS was slightly better represented by correlated reexperiencing, avoidance, emotional numbing, and hyperarousal factors. After accounting for method variance, the model specifying dysphoria as a distinct factor achieved slightly better fit. Patterns of correlations with external variables provided additional support for the dysphoria model. Implications regarding the underlying structure of PTSD are discussed.

Monte Carlo analysis of neutron diffuse scattering data

NASA Astrophysics Data System (ADS)

Goossens, D. J.; Heerdegen, A. P.; Welberry, T. R.; Gutmann, M. J.

2006-11-01

This paper presents a discussion of a technique developed for the analysis of neutron diffuse scattering data. The technique involves processing the data into reciprocal space sections and modelling the diffuse scattering in these sections. A Monte Carlo modelling approach is used in which the crystal energy is a function of interatomic distances between molecules and torsional rotations within molecules. The parameters of the model are the spring constants governing the interactions, as they determine the correlations which evolve when the model crystal structure is relaxed at finite temperature. When the model crystal has reached equilibrium its diffraction pattern is calculated and a χ2 goodness-of-fit test between observed and calculated data slices is performed. This allows a least-squares refinement of the fit parameters and so automated refinement can proceed. The first application of this methodology to neutron, rather than X-ray, data is outlined. The sample studied was deuterated benzil, d-benzil, C14D10O2, for which data was collected using time-of-flight Laue diffraction on SXD at ISIS.

Genetic analysis of partial egg production records in Japanese quail using random regression models.

PubMed

Abou Khadiga, G; Mahmoud, B Y F; Farahat, G S; Emam, A M; El-Full, E A

2017-08-01

The main objectives of this study were to detect the most appropriate random regression model (RRM) to fit the data of monthly egg production in 2 lines (selected and control) of Japanese quail and to test the consistency of different criteria of model choice. Data from 1,200 female Japanese quails for the first 5 months of egg production from 4 consecutive generations of an egg line selected for egg production in the first month (EP1) was analyzed. Eight RRMs with different orders of Legendre polynomials were compared to determine the proper model for analysis. All criteria of model choice suggested that the adequate model included the second-order Legendre polynomials for fixed effects, and the third-order for additive genetic effects and permanent environmental effects. Predictive ability of the best model was the highest among all models (ρ = 0.987). According to the best model fitted to the data, estimates of heritability were relatively low to moderate (0.10 to 0.17) showed a descending pattern from the first to the fifth month of production. A similar pattern was observed for permanent environmental effects with greater estimates in the first (0.36) and second (0.23) months of production than heritability estimates. Genetic correlations between separate production periods were higher (0.18 to 0.93) than their phenotypic counterparts (0.15 to 0.87). The superiority of the selected line over the control was observed through significant (P < 0.05) linear contrast estimates. Significant (P < 0.05) estimates of covariate effect (age at sexual maturity) showed a decreased pattern with greater impact on egg production in earlier ages (first and second months) than later ones. A methodology based on random regression animal models can be recommended for genetic evaluation of egg production in Japanese quail. © 2017 Poultry Science Association Inc.

Longitudinal Model Building Using Latent Transition Analysis: An Example Using School Bullying Data.

PubMed

Ryoo, Ji Hoon; Wang, Cixin; Swearer, Susan M; Hull, Michael; Shi, Dingjing

2018-01-01

Applications of latent transition analysis (LTA) have emerged since the early 1990s, with numerous scientific findings being published in many areas, including social and behavioral sciences, education, and public health. Although LTA is effective as a statistical analytic tool for a person-centered model using longitudinal data, model building in LTA has often been subjective and confusing for applied researchers. To fill this gap in the literature, we review the components of LTA, recommend a framework of fitting LTA, and summarize what acceptable model evaluation tools should be used in practice. The proposed framework of fitting LTA consists of six steps depicted in Figure 1 from step 0 (exploring data) to step 5 (fitting distal variables). We also illustrate the framework of fitting LTA with data on concerns about school bullying from a sample of 1,180 students ranging from 5th to 9th grade (mean age = 12.2 years, SD = 1.29 years at Time 1) over three semesters. We identified four groups of students with distinct patterns of bullying concerns, and found that their concerns about bullying decreased and narrowed to specific concerns about rumors, gossip, and social exclusion over time. The data and command (syntax) files needed for reproducing the results using SAS PROC LCA and PROC LTA (Version 1.3.2) (2015) and Mplus 7.4 (Muthén and Muthén, 1998-2015) are provided as online supplementary materials.

Spatial diffusion of raccoon rabies in Pennsylvania, USA.

PubMed

Moore, D A

1999-05-14

Identification of the geographic pattern of diffusion of a wildlife disease could lead to information regarding its control. The objective of this study was to model raccoon-rabies diffusion in Pennsylvania to identify geographic constraints on the diffusion pattern for potential use in bait-vaccination strategies. A trend-surface analysis (TSA) was used as a spatial filter for month to first report by county location. A cubic polynomial model was fitted (R2 = 0.80). Velocity vectors were calculated from the partial derivatives of the model and mapped to demonstrate the instantaneous speed of diffusion at each location. A main corridor of diffusion through the ridge and valley section of the state was evident early in the outbreak. Once the disease reached the northern counties, the disease moved west toward Ohio. I believe that TSA was useful in identifying the pattern of raccoon-rabies diffusion across the stage from the inherent noise of disease-reporting data.

Effects of Heterogeniety on Spatial Pattern Analysis of Wild Pistachio Trees in Zagros Woodlands, Iran

NASA Astrophysics Data System (ADS)

Erfanifard, Y.; Rezayan, F.

2014-10-01

Vegetation heterogeneity biases second-order summary statistics, e.g., Ripley's K-function, applied for spatial pattern analysis in ecology. Second-order investigation based on Ripley's K-function and related statistics (i.e., L- and pair correlation function g) is widely used in ecology to develop hypothesis on underlying processes by characterizing spatial patterns of vegetation. The aim of this study was to demonstrate effects of underlying heterogeneity of wild pistachio (Pistacia atlantica Desf.) trees on the second-order summary statistics of point pattern analysis in a part of Zagros woodlands, Iran. The spatial distribution of 431 wild pistachio trees was accurately mapped in a 40 ha stand in the Wild Pistachio & Almond Research Site, Fars province, Iran. Three commonly used second-order summary statistics (i.e., K-, L-, and g-functions) were applied to analyse their spatial pattern. The two-sample Kolmogorov-Smirnov goodness-of-fit test showed that the observed pattern significantly followed an inhomogeneous Poisson process null model in the study region. The results also showed that heterogeneous pattern of wild pistachio trees biased the homogeneous form of K-, L-, and g-functions, demonstrating a stronger aggregation of the trees at the scales of 0-50 m than actually existed and an aggregation at scales of 150-200 m, while regularly distributed. Consequently, we showed that heterogeneity of point patterns may bias the results of homogeneous second-order summary statistics and we also suggested applying inhomogeneous summary statistics with related null models for spatial pattern analysis of heterogeneous vegetations.

Large Occurrence Patterns of New Zealand Deep Earthquakes: Characterization by Use of a Switching Poisson Model

NASA Astrophysics Data System (ADS)

Shaochuan, Lu; Vere-Jones, David

2011-10-01

The paper studies the statistical properties of deep earthquakes around North Island, New Zealand. We first evaluate the catalogue coverage and completeness of deep events according to cusum (cumulative sum) statistics and earlier literature. The epicentral, depth, and magnitude distributions of deep earthquakes are then discussed. It is worth noting that strong grouping effects are observed in the epicentral distribution of these deep earthquakes. Also, although the spatial distribution of deep earthquakes does not change, their occurrence frequencies vary from time to time, active in one period, relatively quiescent in another. The depth distribution of deep earthquakes also hardly changes except for events with focal depth less than 100 km. On the basis of spatial concentration we partition deep earthquakes into several groups—the Taupo-Bay of Plenty group, the Taranaki group, and the Cook Strait group. Second-order moment analysis via the two-point correlation function reveals only very small-scale clustering of deep earthquakes, presumably limited to some hot spots only. We also suggest that some models usually used for shallow earthquakes fit deep earthquakes unsatisfactorily. Instead, we propose a switching Poisson model for the occurrence patterns of deep earthquakes. The goodness-of-fit test suggests that the time-varying activity is well characterized by a switching Poisson model. Furthermore, detailed analysis carried out on each deep group by use of switching Poisson models reveals similar time-varying behavior in occurrence frequencies in each group.

A dynamical pattern recognition model of gamma activity in auditory cortex

PubMed Central

Zavaglia, M.; Canolty, R.T.; Schofield, T.M.; Leff, A.P.; Ursino, M.; Knight, R.T.; Penny, W.D.

2012-01-01

This paper describes a dynamical process which serves both as a model of temporal pattern recognition in the brain and as a forward model of neuroimaging data. This process is considered at two separate levels of analysis: the algorithmic and implementation levels. At an algorithmic level, recognition is based on the use of Occurrence Time features. Using a speech digit database we show that for noisy recognition environments, these features rival standard cepstral coefficient features. At an implementation level, the model is defined using a Weakly Coupled Oscillator (WCO) framework and uses a transient synchronization mechanism to signal a recognition event. In a second set of experiments, we use the strength of the synchronization event to predict the high gamma (75–150 Hz) activity produced by the brain in response to word versus non-word stimuli. Quantitative model fits allow us to make inferences about parameters governing pattern recognition dynamics in the brain. PMID:22327049

Low Dose Aerosol Fitness at the Innate Phase of Murine Infection Better Predicts Virulence amongst Clinical Strains of Mycobacterium tuberculosis

PubMed Central

Caceres, Neus; Llopis, Isaac; Marzo, Elena; Prats, Clara; Vilaplana, Cristina; de Viedma, Dario Garcia; Samper, Sofía; Lopez, Daniel; Cardona, Pere-Joan

2012-01-01

Background Evaluation of a quick and easy model to determine the intrinsic ability of clinical strains to generate active TB has been set by assuming that this is linked to the fitness of Mycobacterium tuberculosis strain at the innate phase of the infection. Thus, the higher the bacillary load, the greater the possibility of inducting liquefaction, and thus active TB, once the adaptive response is set. Methodology/Principal Findings The virulence of seven clinical Mycobacterium tuberculosis strains isolated in Spain was tested by determining the bacillary concentration in the spleen and lung of mice at weeks 0, 1 and 2 after intravenous (IV) inoculation of 104 CFU, and by determining the growth in vitro until the stationary phase had been reached. Cord distribution automated analysis showed two clear patterns related to the high and low fitness in the lung after IV infection. This pattern was not seen in the in vitro fitness tests, which clearly favored the reference strain (H37Rv). Subsequent determination using a more physiological low-dose aerosol (AER) inoculation with 102 CFU showed a third pattern in which the three best values coincided with the highest dissemination capacity according to epidemiological data. Conclusions/Significance The fitness obtained after low dose aerosol administration in the presence of the innate immune response is the most predictive factor for determining the virulence of clinical strains. This gives support to a mechanism of the induction of active TB derived from the dynamic hypothesis of latent tuberculosis infection. PMID:22235258

Resistance of virus to extinction on bottleneck passages: study of a decaying and fluctuating pattern of fitness loss

NASA Technical Reports Server (NTRS)

Lazaro, Ester; Escarmis, Cristina; Perez-Mercader, Juan; Manrubia, Susanna C.; Domingo, Esteban

2003-01-01

RNA viruses display high mutation rates and their populations replicate as dynamic and complex mutant distributions, termed viral quasispecies. Repeated genetic bottlenecks, which experimentally are carried out through serial plaque-to-plaque transfers of the virus, lead to fitness decrease (measured here as diminished capacity to produce infectious progeny). Here we report an analysis of fitness evolution of several low fitness foot-and-mouth disease virus clones subjected to 50 plaque-to-plaque transfers. Unexpectedly, fitness decrease, rather than being continuous and monotonic, displayed a fluctuating pattern, which was influenced by both the virus and the state of the host cell as shown by effects of recent cell passage history. The amplitude of the fluctuations increased as fitness decreased, resulting in a remarkable resistance of virus to extinction. Whereas the frequency distribution of fitness in control (independent) experiments follows a log-normal distribution, the probability of fitness values in the evolving bottlenecked populations fitted a Weibull distribution. We suggest that multiple functions of viral genomic RNA and its encoded proteins, subjected to high mutational pressure, interact with cellular components to produce this nontrivial, fluctuating pattern.

Quantifying traditional Chinese medicine patterns using modern test theory: an example of functional constipation.

PubMed

Shen, Minxue; Cui, Yuanwu; Hu, Ming; Xu, Linyong

2017-01-13

The study aimed to validate a scale to assess the severity of "Yin deficiency, intestine heat" pattern of functional constipation based on the modern test theory. Pooled longitudinal data of 237 patients with "Yin deficiency, intestine heat" pattern of constipation from a prospective cohort study were used to validate the scale. Exploratory factor analysis was used to examine the common factors of items. A multidimensional item response model was used to assess the scale with the presence of multidimensionality. The Cronbach's alpha ranged from 0.79 to 0.89, and the split-half reliability ranged from 0.67 to 0.79 at different measurements. Exploratory factor analysis identified two common factors, and all items had cross factor loadings. Bidimensional model had better goodness of fit than the unidimensional model. Multidimensional item response model showed that the all items had moderate to high discrimination parameters. Parameters indicated that the first latent trait signified intestine heat, while the second trait characterized Yin deficiency. Information function showed that items demonstrated highest discrimination power among patients with moderate to high level of disease severity. Multidimensional item response theory provides a useful and rational approach in validating scales for assessing the severity of patterns in traditional Chinese medicine.

The effect of road network patterns on pedestrian safety: A zone-based Bayesian spatial modeling approach.

PubMed

Guo, Qiang; Xu, Pengpeng; Pei, Xin; Wong, S C; Yao, Danya

2017-02-01

Pedestrian safety is increasingly recognized as a major public health concern. Extensive safety studies have been conducted to examine the influence of multiple variables on the occurrence of pedestrian-vehicle crashes. However, the explicit relationship between pedestrian safety and road network characteristics remains unknown. This study particularly focused on the role of different road network patterns on the occurrence of crashes involving pedestrians. A global integration index via space syntax was introduced to quantify the topological structures of road networks. The Bayesian Poisson-lognormal (PLN) models with conditional autoregressive (CAR) prior were then developed via three different proximity structures: contiguity, geometry-centroid distance, and road network connectivity. The models were also compared with the PLN counterpart without spatial correlation effects. The analysis was based on a comprehensive crash dataset from 131 selected traffic analysis zones in Hong Kong. The results indicated that higher global integration was associated with more pedestrian-vehicle crashes; the irregular pattern network was proved to be safest in terms of pedestrian crash occurrences, whereas the grid pattern was the least safe; the CAR model with a neighborhood structure based on road network connectivity was found to outperform in model goodness-of-fit, implying the importance of accurately accounting for spatial correlation when modeling spatially aggregated crash data. Copyright © 2016 Elsevier Ltd. All rights reserved.

Sexual and reproductive behaviour of Drosophila melanogaster from a microclimatically interslope differentiated population of "Evolution Canyon" (Mount Carmel, Israel).

PubMed

Iliadi, K; Iliadi, N; Rashkovetsky, E; Minkov, I; Nevo, E; Korol, A

2001-11-22

The strong microscale interslope environmental differences in "Evolution Canyon" provide an excellent natural model for sympatric speciation. Our previous studies revealed significant slope-specific differences for a fitness complex of Drosophila. This complex involved either adaptation traits (tolerance to high temperature, different viability and longevity pattern) or behavioural differentiation, manifested in habitat choice and non-random mating. This remarkable differentiation has evolved despite a very small interslope distance (a few hundred metres only). Our hypothesis is that strong interslope microclimatic contrast caused differential selection for fitness-related traits accompanied by behavioural differentiation and reinforced by some sexual isolation, which started incipient speciation. Here we describe the results of a systematic analysis of sexual behaviour in a non-choice situation and several reproductive parameters of D. melanogaster populations from the opposite slopes of "Evolution Canyon". The evidence indicates that: (i) mate choice derives from differences in mating propensity and discrimination; (ii) females from the milder north-facing slope discriminate strongly against males of the opposite slope; (iii) both sexes of the south-facing slope display distinct reproductive and behavioural patterns with females showing increased fecundity, shorter time before remating and relatively higher receptivity, and males showing higher mating propensity. These patterns represent adaptive life strategies contributing to higher fitness.

Runoff potentiality of a watershed through SCS and functional data analysis technique.

PubMed

Adham, M I; Shirazi, S M; Othman, F; Rahman, S; Yusop, Z; Ismail, Z

2014-01-01

Runoff potentiality of a watershed was assessed based on identifying curve number (CN), soil conservation service (SCS), and functional data analysis (FDA) techniques. Daily discrete rainfall data were collected from weather stations in the study area and analyzed through lowess method for smoothing curve. As runoff data represents a periodic pattern in each watershed, Fourier series was introduced to fit the smooth curve of eight watersheds. Seven terms of Fourier series were introduced for the watersheds 5 and 8, while 8 terms of Fourier series were used for the rest of the watersheds for the best fit of data. Bootstrapping smooth curve analysis reveals that watersheds 1, 2, 3, 6, 7, and 8 are with monthly mean runoffs of 29, 24, 22, 23, 26, and 27 mm, respectively, and these watersheds would likely contribute to surface runoff in the study area. The purpose of this study was to transform runoff data into a smooth curve for representing the surface runoff pattern and mean runoff of each watershed through statistical method. This study provides information of runoff potentiality of each watershed and also provides input data for hydrological modeling.

Runoff Potentiality of a Watershed through SCS and Functional Data Analysis Technique

PubMed Central

Adham, M. I.; Shirazi, S. M.; Othman, F.; Rahman, S.; Yusop, Z.; Ismail, Z.

2014-01-01

Runoff potentiality of a watershed was assessed based on identifying curve number (CN), soil conservation service (SCS), and functional data analysis (FDA) techniques. Daily discrete rainfall data were collected from weather stations in the study area and analyzed through lowess method for smoothing curve. As runoff data represents a periodic pattern in each watershed, Fourier series was introduced to fit the smooth curve of eight watersheds. Seven terms of Fourier series were introduced for the watersheds 5 and 8, while 8 terms of Fourier series were used for the rest of the watersheds for the best fit of data. Bootstrapping smooth curve analysis reveals that watersheds 1, 2, 3, 6, 7, and 8 are with monthly mean runoffs of 29, 24, 22, 23, 26, and 27 mm, respectively, and these watersheds would likely contribute to surface runoff in the study area. The purpose of this study was to transform runoff data into a smooth curve for representing the surface runoff pattern and mean runoff of each watershed through statistical method. This study provides information of runoff potentiality of each watershed and also provides input data for hydrological modeling. PMID:25152911

Multivariate Autoregressive Modeling and Granger Causality Analysis of Multiple Spike Trains

PubMed Central

Krumin, Michael; Shoham, Shy

2010-01-01

Recent years have seen the emergence of microelectrode arrays and optical methods allowing simultaneous recording of spiking activity from populations of neurons in various parts of the nervous system. The analysis of multiple neural spike train data could benefit significantly from existing methods for multivariate time-series analysis which have proven to be very powerful in the modeling and analysis of continuous neural signals like EEG signals. However, those methods have not generally been well adapted to point processes. Here, we use our recent results on correlation distortions in multivariate Linear-Nonlinear-Poisson spiking neuron models to derive generalized Yule-Walker-type equations for fitting ‘‘hidden” Multivariate Autoregressive models. We use this new framework to perform Granger causality analysis in order to extract the directed information flow pattern in networks of simulated spiking neurons. We discuss the relative merits and limitations of the new method. PMID:20454705

Goodness of Fit of Skills Assessment Approaches: Insights from Patterns of Real vs. Synthetic Data Sets

ERIC Educational Resources Information Center

Beheshti, Behzad; Desmarais, Michel C.

2015-01-01

This study investigates the issue of the goodness of fit of different skills assessment models using both synthetic and real data. Synthetic data is generated from the different skills assessment models. The results show wide differences of performances between the skills assessment models over synthetic data sets. The set of relative performances…

Characterising the reproducibility and reliability of dietary patterns among Yup'ik Alaska Native people.

PubMed

Ryman, Tove K; Boyer, Bert B; Hopkins, Scarlett; Philip, Jacques; O'Brien, Diane; Thummel, Kenneth; Austin, Melissa A

2015-02-28

FFQ data can be used to characterise dietary patterns for diet-disease association studies. In the present study, we evaluated three previously defined dietary patterns--'subsistence foods', market-based 'processed foods' and 'fruits and vegetables'--among a sample of Yup'ik people from Southwest Alaska. We tested the reproducibility and reliability of the dietary patterns, as well as the associations of these patterns with dietary biomarkers and participant characteristics. We analysed data from adult study participants who completed at least one FFQ with the Center for Alaska Native Health Research 9/2009-5/2013. To test the reproducibility of the dietary patterns, we conducted a confirmatory factor analysis (CFA) of a hypothesised model using eighteen food items to measure the dietary patterns (n 272). To test the reliability of the dietary patterns, we used the CFA to measure composite reliability (n 272) and intra-class correlation coefficients for test-retest reliability (n 113). Finally, to test the associations, we used linear regression (n 637). All factor loadings, except one, in CFA indicated acceptable correlations between foods and dietary patterns (r>0·40), and model-fit criteria were >0·90. Composite and test-retest reliability of the dietary patterns were, respectively, 0·56 and 0·34 for 'subsistence foods', 0·73 and 0·66 for 'processed foods', and 0·72 and 0·54 for 'fruits and vegetables'. In the multi-predictor analysis, the dietary patterns were significantly associated with dietary biomarkers, community location, age, sex and self-reported lifestyle. This analysis confirmed the reproducibility and reliability of the dietary patterns in the present study population. These dietary patterns can be used for future research and development of dietary interventions in this underserved population.

Development of a program to fit data to a new logistic model for microbial growth.

PubMed

Fujikawa, Hiroshi; Kano, Yoshihiro

2009-06-01

Recently we developed a mathematical model for microbial growth in food. The model successfully predicted microbial growth at various patterns of temperature. In this study, we developed a program to fit data to the model with a spread sheet program, Microsoft Excel. Users can instantly get curves fitted to the model by inputting growth data and choosing the slope portion of a curve. The program also could estimate growth parameters including the rate constant of growth and the lag period. This program would be a useful tool for analyzing growth data and further predicting microbial growth.

Mathematical models of human mobility of relevance to malaria transmission in Africa.

PubMed

Marshall, John M; Wu, Sean L; Sanchez C, Hector M; Kiware, Samson S; Ndhlovu, Micky; Ouédraogo, André Lin; Touré, Mahamoudou B; Sturrock, Hugh J; Ghani, Azra C; Ferguson, Neil M

2018-05-16

As Africa-wide malaria prevalence declines, an understanding of human movement patterns is essential to inform how best to target interventions. We fitted movement models to trip data from surveys conducted at 3-5 sites throughout each of Mali, Burkina Faso, Zambia and Tanzania. Two models were compared in terms of their ability to predict the observed movement patterns - a gravity model, in which movement rates between pairs of locations increase with population size and decrease with distance, and a radiation model, in which travelers are cumulatively "absorbed" as they move outwards from their origin of travel. The gravity model provided a better fit to the data overall and for travel to large populations, while the radiation model provided a better fit for nearby populations. One strength of the data set was that trips could be categorized according to traveler group - namely, women traveling with children in all survey countries and youth workers in Mali. For gravity models fitted to data specific to these groups, youth workers were found to have a higher travel frequency to large population centers, and women traveling with children a lower frequency. These models may help predict the spatial transmission of malaria parasites and inform strategies to control their spread.

Time-Resolved Transposon Insertion Sequencing Reveals Genome-Wide Fitness Dynamics during Infection.

PubMed

Yang, Guanhua; Billings, Gabriel; Hubbard, Troy P; Park, Joseph S; Yin Leung, Ka; Liu, Qin; Davis, Brigid M; Zhang, Yuanxing; Wang, Qiyao; Waldor, Matthew K

2017-10-03

Transposon insertion sequencing (TIS) is a powerful high-throughput genetic technique that is transforming functional genomics in prokaryotes, because it enables genome-wide mapping of the determinants of fitness. However, current approaches for analyzing TIS data assume that selective pressures are constant over time and thus do not yield information regarding changes in the genetic requirements for growth in dynamic environments (e.g., during infection). Here, we describe structured analysis of TIS data collected as a time series, termed pattern analysis of conditional essentiality (PACE). From a temporal series of TIS data, PACE derives a quantitative assessment of each mutant's fitness over the course of an experiment and identifies mutants with related fitness profiles. In so doing, PACE circumvents major limitations of existing methodologies, specifically the need for artificial effect size thresholds and enumeration of bacterial population expansion. We used PACE to analyze TIS samples of Edwardsiella piscicida (a fish pathogen) collected over a 2-week infection period from a natural host (the flatfish turbot). PACE uncovered more genes that affect E. piscicida 's fitness in vivo than were detected using a cutoff at a terminal sampling point, and it identified subpopulations of mutants with distinct fitness profiles, one of which informed the design of new live vaccine candidates. Overall, PACE enables efficient mining of time series TIS data and enhances the power and sensitivity of TIS-based analyses. IMPORTANCE Transposon insertion sequencing (TIS) enables genome-wide mapping of the genetic determinants of fitness, typically based on observations at a single sampling point. Here, we move beyond analysis of endpoint TIS data to create a framework for analysis of time series TIS data, termed pattern analysis of conditional essentiality (PACE). We applied PACE to identify genes that contribute to colonization of a natural host by the fish pathogen Edwardsiella piscicida. PACE uncovered more genes that affect E. piscicida 's fitness in vivo than were detected using a terminal sampling point, and its clustering of mutants with related fitness profiles informed design of new live vaccine candidates. PACE yields insights into patterns of fitness dynamics and circumvents major limitations of existing methodologies. Finally, the PACE method should be applicable to additional "omic" time series data, including screens based on clustered regularly interspaced short palindromic repeats with Cas9 (CRISPR/Cas9). Copyright © 2017 Yang et al.

Statistical ecology comes of age.

PubMed

Gimenez, Olivier; Buckland, Stephen T; Morgan, Byron J T; Bez, Nicolas; Bertrand, Sophie; Choquet, Rémi; Dray, Stéphane; Etienne, Marie-Pierre; Fewster, Rachel; Gosselin, Frédéric; Mérigot, Bastien; Monestiez, Pascal; Morales, Juan M; Mortier, Frédéric; Munoz, François; Ovaskainen, Otso; Pavoine, Sandrine; Pradel, Roger; Schurr, Frank M; Thomas, Len; Thuiller, Wilfried; Trenkel, Verena; de Valpine, Perry; Rexstad, Eric

2014-12-01

The desire to predict the consequences of global environmental change has been the driver towards more realistic models embracing the variability and uncertainties inherent in ecology. Statistical ecology has gelled over the past decade as a discipline that moves away from describing patterns towards modelling the ecological processes that generate these patterns. Following the fourth International Statistical Ecology Conference (1-4 July 2014) in Montpellier, France, we analyse current trends in statistical ecology. Important advances in the analysis of individual movement, and in the modelling of population dynamics and species distributions, are made possible by the increasing use of hierarchical and hidden process models. Exciting research perspectives include the development of methods to interpret citizen science data and of efficient, flexible computational algorithms for model fitting. Statistical ecology has come of age: it now provides a general and mathematically rigorous framework linking ecological theory and empirical data.

Statistical ecology comes of age

PubMed Central

Gimenez, Olivier; Buckland, Stephen T.; Morgan, Byron J. T.; Bez, Nicolas; Bertrand, Sophie; Choquet, Rémi; Dray, Stéphane; Etienne, Marie-Pierre; Fewster, Rachel; Gosselin, Frédéric; Mérigot, Bastien; Monestiez, Pascal; Morales, Juan M.; Mortier, Frédéric; Munoz, François; Ovaskainen, Otso; Pavoine, Sandrine; Pradel, Roger; Schurr, Frank M.; Thomas, Len; Thuiller, Wilfried; Trenkel, Verena; de Valpine, Perry; Rexstad, Eric

2014-01-01

The desire to predict the consequences of global environmental change has been the driver towards more realistic models embracing the variability and uncertainties inherent in ecology. Statistical ecology has gelled over the past decade as a discipline that moves away from describing patterns towards modelling the ecological processes that generate these patterns. Following the fourth International Statistical Ecology Conference (1–4 July 2014) in Montpellier, France, we analyse current trends in statistical ecology. Important advances in the analysis of individual movement, and in the modelling of population dynamics and species distributions, are made possible by the increasing use of hierarchical and hidden process models. Exciting research perspectives include the development of methods to interpret citizen science data and of efficient, flexible computational algorithms for model fitting. Statistical ecology has come of age: it now provides a general and mathematically rigorous framework linking ecological theory and empirical data. PMID:25540151

Characterizing the Reproducibility and Reliability of Dietary Patterns among Yup’ik Alaska Native People

PubMed Central

Ryman, Tove K.; Boyer, Bert B.; Hopkins, Scarlett; Philip, Jacques; O’Brien, Diane; Thummel, Kenneth; Austin, Melissa A.

2015-01-01

Food frequency questionnaire (FFQ) data can be used to characterize dietary patterns for diet-disease association studies. Among a sample of Yup’ik people from Southwest Alaska, we evaluated three previously defined dietary patterns: “subsistence foods” and market-based “processed foods” and “fruits and vegetables”. We tested the reproducibility and reliability of the dietary patterns and tested associations of the patterns with dietary biomarkers and participant characteristics. We analyzed data from adult study participants who completed at least one FFQ with the Center for Alaska Native Health Research 9/2009–5/2013. To test reproducibility we conducted a confirmatory factor analysis (CFA) of a hypothesized model using 18 foods to measure the dietary patterns (n=272). To test the reliability of the dietary patterns, we used CFA to measure the composite reliability (n=272) and intraclass correlation coefficients for test-retest reliability (n=113). Finally, to test associations we used linear regression (n=637). All CFA factor loadings, except one, indicated acceptable correlations between foods and dietary patterns (r > 0.40) and model fit criteria were greater than 0.90. Composite and test-retest reliability of dietary patterns were respectively 0.56 and 0.34 for subsistence foods, 0.73 and 0.66 for processed foods, and 0.72 and 0.54 for fruits and vegetables. In the multi-predictor analysis, dietary patterns were significantly associated with dietary biomarkers, community location, age, sex, and self-reported lifestyle. This analysis confirmed the reproducibility and reliability of the dietary patterns in this study population. These dietary patterns can be used for future research and development of dietary interventions in this underserved population. PMID:25656871

Regional Cultures and the Psychological Geography of Switzerland: Person–Environment–Fit in Personality Predicts Subjective Wellbeing

PubMed Central

Götz, Friedrich M.; Ebert, Tobias; Rentfrow, Peter J.

2018-01-01

The present study extended traditional nation-based research on person–culture–fit to the regional level. First, we examined the geographical distribution of Big Five personality traits in Switzerland. Across the 26 Swiss cantons, unique patterns were observed for all traits. For Extraversion and Neuroticism clear language divides emerged between the French- and Italian-speaking South-West vs. the German-speaking North-East. Second, multilevel modeling demonstrated that person–environment–fit in Big Five, composed of elevation (i.e., mean differences between individual profile and cantonal profile), scatter (differences in mean variances) and shape (Pearson correlations between individual and cantonal profiles across all traits; Furr, 2008, 2010), predicted the development of subjective wellbeing (i.e., life satisfaction, satisfaction with personal relationships, positive affect, negative affect) over a period of 4 years. Unexpectedly, while the effects of shape were in line with the person–environment–fit hypothesis (better fit predicted higher subjective wellbeing), the effects of scatter showed the opposite pattern, while null findings were observed for elevation. Across a series of robustness checks, the patterns for shape and elevation were consistently replicated. While that was mostly the case for scatter as well, the effects of scatter appeared to be somewhat less robust and more sensitive to the specific way fit was modeled when predicting certain outcomes (negative affect, positive affect). Distinguishing between supplementary and complementary fit may help to reconcile these findings and future research should explore whether and if so under which conditions these concepts may be applicable to the respective facets of person–culture–fit. PMID:29713299

Regional Cultures and the Psychological Geography of Switzerland: Person-Environment-Fit in Personality Predicts Subjective Wellbeing.

PubMed

Götz, Friedrich M; Ebert, Tobias; Rentfrow, Peter J

2018-01-01

The present study extended traditional nation-based research on person-culture-fit to the regional level. First, we examined the geographical distribution of Big Five personality traits in Switzerland. Across the 26 Swiss cantons, unique patterns were observed for all traits. For Extraversion and Neuroticism clear language divides emerged between the French- and Italian-speaking South-West vs. the German-speaking North-East. Second, multilevel modeling demonstrated that person-environment-fit in Big Five, composed of elevation (i.e., mean differences between individual profile and cantonal profile), scatter (differences in mean variances) and shape (Pearson correlations between individual and cantonal profiles across all traits; Furr, 2008, 2010), predicted the development of subjective wellbeing (i.e., life satisfaction, satisfaction with personal relationships, positive affect, negative affect) over a period of 4 years. Unexpectedly, while the effects of shape were in line with the person-environment-fit hypothesis (better fit predicted higher subjective wellbeing), the effects of scatter showed the opposite pattern, while null findings were observed for elevation. Across a series of robustness checks, the patterns for shape and elevation were consistently replicated. While that was mostly the case for scatter as well, the effects of scatter appeared to be somewhat less robust and more sensitive to the specific way fit was modeled when predicting certain outcomes (negative affect, positive affect). Distinguishing between supplementary and complementary fit may help to reconcile these findings and future research should explore whether and if so under which conditions these concepts may be applicable to the respective facets of person-culture-fit.

On the Complexity of Item Response Theory Models.

PubMed

Bonifay, Wes; Cai, Li

2017-01-01

Complexity in item response theory (IRT) has traditionally been quantified by simply counting the number of freely estimated parameters in the model. However, complexity is also contingent upon the functional form of the model. We examined four popular IRT models-exploratory factor analytic, bifactor, DINA, and DINO-with different functional forms but the same number of free parameters. In comparison, a simpler (unidimensional 3PL) model was specified such that it had 1 more parameter than the previous models. All models were then evaluated according to the minimum description length principle. Specifically, each model was fit to 1,000 data sets that were randomly and uniformly sampled from the complete data space and then assessed using global and item-level fit and diagnostic measures. The findings revealed that the factor analytic and bifactor models possess a strong tendency to fit any possible data. The unidimensional 3PL model displayed minimal fitting propensity, despite the fact that it included an additional free parameter. The DINA and DINO models did not demonstrate a proclivity to fit any possible data, but they did fit well to distinct data patterns. Applied researchers and psychometricians should therefore consider functional form-and not goodness-of-fit alone-when selecting an IRT model.

Contrasting Patterns in Mammal–Bacteria Coevolution: Bartonella and Leptospira in Bats and Rodents

PubMed Central

Lei, Bonnie R.; Olival, Kevin J.

2014-01-01

Background Emerging bacterial zoonoses in bats and rodents remain relatively understudied. We conduct the first comparative host–pathogen coevolutionary analyses of bacterial pathogens in these hosts, using Bartonella spp. and Leptospira spp. as a model. Methodology/Principal Findings We used published genetic data for 51 Bartonella genotypes from 24 bat species, 129 Bartonella from 38 rodents, and 26 Leptospira from 20 bats. We generated maximum likelihood and Bayesian phylogenies for hosts and bacteria, and tested for coevoutionary congruence using programs ParaFit, PACO, and Jane. Bartonella spp. and their bat hosts had a significant coevolutionary fit (ParaFitGlobal = 1.9703, P≤0.001; m2 global value = 7.3320, P≤0.0001). Bartonella spp. and rodent hosts also indicated strong overall patterns of cospeciation (ParaFitGlobal = 102.4409, P≤0.001; m2 global value = 86.532, P≤0.0001). In contrast, we were unable to reject independence of speciation events in Leptospira and bats (ParaFitGlobal = 0.0042, P = 0.84; m2 global value = 4.6310, P = 0.5629). Separate analyses of New World and Old World data subsets yielded results congruent with analysis from entire datasets. We also conducted event-based cophylogeny analyses to reconstruct likely evolutionary histories for each group of pathogens and hosts. Leptospira and bats had the greatest number of host switches per parasite (0.731), while Bartonella and rodents had the fewest (0.264). Conclusions/Significance In both bat and rodent hosts, Bartonella exhibits significant coevolution with minimal host switching, while Leptospira in bats lacks evolutionary congruence with its host and has high number of host switches. Reasons underlying these variable coevolutionary patterns in host range are likely due to differences in disease-specific transmission and host ecology. Understanding the coevolutionary patterns and frequency of host-switching events between bacterial pathogens and their hosts will allow better prediction of spillover between mammal reservoirs, and ultimately to humans. PMID:24651646

Coma Recovery Scale-Revised: evidentiary support for hierarchical grading of level of consciousness.

PubMed

Gerrard, Paul; Zafonte, Ross; Giacino, Joseph T

2014-12-01

To investigate the neurobehavioral pattern of recovery of consciousness as reflected by performance on the subscales of the Coma Recovery Scale-Revised (CRS-R). Retrospective item response theory (IRT) and factor analysis. Inpatient rehabilitation facilities. Rehabilitation inpatients (N=180) with posttraumatic disturbance in consciousness who participated in a double-blinded, randomized, controlled drug trial. Not applicable. Scores on CRS-R subscales. The CRS-R was found to fit factor analytic models adhering to the assumptions of unidimensionality and monotonicity. In addition, subscales were mutually independent based on residual correlations. Nonparametric IRT reaffirmed the finding of monotonicity. A highly constrained confirmatory factor analysis model, which imposed equal factor loadings on all items, was found to fit the data well and was used to estimate a 1-parameter IRT model. This study provides evidence of the unidimensionality of the CRS-R and supports the hierarchical structure of the CRS-R subscales, suggesting that it is an effective tool for establishing diagnosis and monitoring recovery of consciousness after severe traumatic brain injury. Copyright © 2014 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Preliminary Examination of Pulse Shapes From GLAS Ocean Returns

NASA Astrophysics Data System (ADS)

Swift, T. P.; Minster, B.

2003-12-01

We have examined GLAS data collected over the Pacific ocean during the commission phase of the ICESat mission, in an area where sea state is well documented. The data used for this preliminary analysis were acquired during two passes along track 95, on March 18 and 26 of 2003, along the stretch offshore southern California. These dates were chosen for their lack of cloud cover; large (4.0 m) and small (0.7 m) significant wave heights, respectively; and the presence of waves emanating from single distant Pacific storms. Cloud cover may be investigated using MODIS images (http://acdisx.gsfc.nasa.gov/data/dataset/MODIS/), while models of significant wave heights and wave vectors for offshore California are archived by the Coastal Data Information Program (http://cdip.ucsd.edu/cdip_htmls/models.shtml). We find that the shape of deep-ocean GLAS pulse returns is diagnostic of the state of the ocean surface. A calm surface produces near-Gaussian, single-peaked shot returns. In contrast, a rough surface produces blurred shot returns which often feature multiple peaks; these peaks are typically separated by total path lengths on the order of one meter. Gaussian curves fit to rough-water returns are therefore less reliable and lead to greater measurement error; outliers in the ocean surface elevation product are mostly the result of poorly fit low-energy shot returns. Additionally, beat patterns and aliasing artifacts may arise from the sampling of deep-ocean wave trains by GLAS footprints separated by 140m. The apparent wavelength of such patterns depends not only on the wave frequency, but also on the angle between the ICESat ground track and the azimuth of the wave crests. We present a preliminary analysis of such patterns which appears to be consistent with a simple geometrical model.

A laboratory-calibrated model of coho salmon growth with utility for ecological analyses

USGS Publications Warehouse

Manhard, Christopher V.; Som, Nicholas A.; Perry, Russell W.; Plumb, John M.

2018-01-01

We conducted a meta-analysis of laboratory- and hatchery-based growth data to estimate broadly applicable parameters of mass- and temperature-dependent growth of juvenile coho salmon (Oncorhynchus kisutch). Following studies of other salmonid species, we incorporated the Ratkowsky growth model into an allometric model and fit this model to growth observations from eight studies spanning ten different populations. To account for changes in growth patterns with food availability, we reparameterized the Ratkowsky model to scale several of its parameters relative to ration. The resulting model was robust across a wide range of ration allocations and experimental conditions, accounting for 99% of the variation in final body mass. We fit this model to growth data from coho salmon inhabiting tributaries and constructed ponds in the Klamath Basin by estimating habitat-specific indices of food availability. The model produced evidence that constructed ponds provided higher food availability than natural tributaries. Because of their simplicity (only mass and temperature are required as inputs) and robustness, ration-varying Ratkowsky models have utility as an ecological tool for capturing growth in freshwater fish populations.

Self-concept in fairness and rule establishment during a competitive game: a computational approach

PubMed Central

Lee, Sang Ho; Kim, Sung-Phil; Cho, Yang Seok

2015-01-01

People consider fairness as well as their own interest when making decisions in economic games. The present study proposes a model that encompasses the self-concept determined by one's own kindness as a factor of fairness. To observe behavioral patterns that reflect self-concept and fairness, a chicken game experiment was conducted. Behavioral data demonstrates four distinct patterns; “switching,” “mutual rush,” “mutual avoidance,” and “unfair” patterns. Model estimation of chicken game data shows that a model with self-concept predicts those behaviors better than previous models of fairness, suggesting that self-concept indeed affects human behavior in competitive economic games. Moreover, a non-stationary parameter analysis revealed the process of reaching consensus between the players in a game. When the models were fitted to a continuous time window, the parameters of the players in a pair with “switching” and “mutual avoidance” patterns became similar as the game proceeded, suggesting that the players gradually formed a shared rule during the game. In contrast, the difference of parameters between the players in the “unfair” and “mutual rush” patterns did not become stable. The outcomes of the present study showed that people are likely to change their strategy until they reach a mutually beneficial status. PMID:26441707

Model of visual contrast gain control and pattern masking

NASA Technical Reports Server (NTRS)

Watson, A. B.; Solomon, J. A.

1997-01-01

We have implemented a model of contrast gain and control in human vision that incorporates a number of key features, including a contrast sensitivity function, multiple oriented bandpass channels, accelerating nonlinearities, and a devisive inhibitory gain control pool. The parameters of this model have been optimized through a fit to the recent data that describe masking of a Gabor function by cosine and Gabor masks [J. M. Foley, "Human luminance pattern mechanisms: masking experiments require a new model," J. Opt. Soc. Am. A 11, 1710 (1994)]. The model achieves a good fit to the data. We also demonstrate how the concept of recruitment may accommodate a variant of this model in which excitatory and inhibitory paths have a common accelerating nonlinearity, but which include multiple channels tuned to different levels of contrast.

Māori identity signatures: A latent profile analysis of the types of Māori identity.

PubMed

Greaves, Lara M; Houkamau, Carla; Sibley, Chris G

2015-10-01

Māori are the indigenous peoples of New Zealand. However, the term 'Māori' can refer to a wide range of people of varying ethnic compositions and cultural identity. We present a statistical model identifying 6 distinct types, or 'Māori Identity Signatures,' and estimate their proportion in the Māori population. The model is tested using a Latent Profile Analysis of a national probability sample of 686 Māori drawn from the New Zealand Attitudes and Values Study. We identify 6 distinct signatures: Traditional Essentialists (22.6%), Traditional Inclusives (16%), High Moderates (31.7%), Low Moderates (18.7%), Spiritually Orientated (4.1%), and Disassociated (6.9%). These distinct Identity Signatures predicted variation in deprivation, age, mixed-ethnic affiliation, and religion. This research presents the first formal statistical model assessing how people's identity as Māori is psychologically structured, documents the relative proportion of these different patterns of structures, and shows that these patterns reliably predict differences in core demographics. We identify a range of patterns of Māori identity far more diverse than has been previously proposed based on qualitative data, and also show that the majority of Māori fit a moderate or traditional identity pattern. The application of our model for studying Māori health and identity development is discussed. (c) 2015 APA, all rights reserved).

Hierarchical Bayesian spatial models for multispecies conservation planning and monitoring.

PubMed

Carroll, Carlos; Johnson, Devin S; Dunk, Jeffrey R; Zielinski, William J

2010-12-01

Biologists who develop and apply habitat models are often familiar with the statistical challenges posed by their data's spatial structure but are unsure of whether the use of complex spatial models will increase the utility of model results in planning. We compared the relative performance of nonspatial and hierarchical Bayesian spatial models for three vertebrate and invertebrate taxa of conservation concern (Church's sideband snails [Monadenia churchi], red tree voles [Arborimus longicaudus], and Pacific fishers [Martes pennanti pacifica]) that provide examples of a range of distributional extents and dispersal abilities. We used presence-absence data derived from regional monitoring programs to develop models with both landscape and site-level environmental covariates. We used Markov chain Monte Carlo algorithms and a conditional autoregressive or intrinsic conditional autoregressive model framework to fit spatial models. The fit of Bayesian spatial models was between 35 and 55% better than the fit of nonspatial analogue models. Bayesian spatial models outperformed analogous models developed with maximum entropy (Maxent) methods. Although the best spatial and nonspatial models included similar environmental variables, spatial models provided estimates of residual spatial effects that suggested how ecological processes might structure distribution patterns. Spatial models built from presence-absence data improved fit most for localized endemic species with ranges constrained by poorly known biogeographic factors and for widely distributed species suspected to be strongly affected by unmeasured environmental variables or population processes. By treating spatial effects as a variable of interest rather than a nuisance, hierarchical Bayesian spatial models, especially when they are based on a common broad-scale spatial lattice (here the national Forest Inventory and Analysis grid of 24 km(2) hexagons), can increase the relevance of habitat models to multispecies conservation planning. Journal compilation © 2010 Society for Conservation Biology. No claim to original US government works.

Detecting Aberrant Response Patterns in the Rasch Model. Rapport 87-3.

ERIC Educational Resources Information Center

Kogut, Jan

In this paper, the detection of response patterns aberrant from the Rasch model is considered. For this purpose, a new person fit index, recently developed by I. W. Molenaar (1987) and an iterative estimation procedure are used in a simulation study of Rasch model data mixed with aberrant data. Three kinds of aberrant response behavior are…

Genome-wide profiling of 24 hr diel rhythmicity in the water flea, Daphnia pulex: network analysis reveals rhythmic gene expression and enhances functional gene annotation.

PubMed

Rund, Samuel S C; Yoo, Boyoung; Alam, Camille; Green, Taryn; Stephens, Melissa T; Zeng, Erliang; George, Gary F; Sheppard, Aaron D; Duffield, Giles E; Milenković, Tijana; Pfrender, Michael E

2016-08-18

Marine and freshwater zooplankton exhibit daily rhythmic patterns of behavior and physiology which may be regulated directly by the light:dark (LD) cycle and/or a molecular circadian clock. One of the best-studied zooplankton taxa, the freshwater crustacean Daphnia, has a 24 h diel vertical migration (DVM) behavior whereby the organism travels up and down through the water column daily. DVM plays a critical role in resource tracking and the behavioral avoidance of predators and damaging ultraviolet radiation. However, there is little information at the transcriptional level linking the expression patterns of genes to the rhythmic physiology/behavior of Daphnia. Here we analyzed genome-wide temporal transcriptional patterns from Daphnia pulex collected over a 44 h time period under a 12:12 LD cycle (diel) conditions using a cosine-fitting algorithm. We used a comprehensive network modeling and analysis approach to identify novel co-regulated rhythmic genes that have similar network topological properties and functional annotations as rhythmic genes identified by the cosine-fitting analyses. Furthermore, we used the network approach to predict with high accuracy novel gene-function associations, thus enhancing current functional annotations available for genes in this ecologically relevant model species. Our results reveal that genes in many functional groupings exhibit 24 h rhythms in their expression patterns under diel conditions. We highlight the rhythmic expression of immunity, oxidative detoxification, and sensory process genes. We discuss differences in the chronobiology of D. pulex from other well-characterized terrestrial arthropods. This research adds to a growing body of literature suggesting the genetic mechanisms governing rhythmicity in crustaceans may be divergent from other arthropod lineages including insects. Lastly, these results highlight the power of using a network analysis approach to identify differential gene expression and provide novel functional annotation.

Morphology and phase behavior of ethanol nanodrops condensed on chemically patterned surfaces

NASA Astrophysics Data System (ADS)

Checco, Antonio; Ocko, Benjamin M.

2008-06-01

Equilibrium wetting of ethanol onto chemically patterned nanostripes has been investigated using environmental atomic force microscopy (AFM) in noncontact mode. The chemical patterns are composed of COOH-terminated “wetting” regions and CH3 -terminated “nonwetting” regions. A specially designed environmental AFM chamber allowed for accurate measurements of droplet height as a function of the temperature offset between the substrate and a macroscopic ethanol reservoir. At saturation, the height dependence scales with droplet width according to w1/2 , in excellent agreement with the augmented Young equation (AYE) modeled with dispersive, nonretarded surface potentials. At small under- and oversaturations, the AYE model accurately fits the data if an effective ΔT is used as a fitting parameter. There is a systematic difference between the measured ΔT and the values extracted from the fits to the data. In addition to static measurements, we present time-resolved measurements of the droplet height which enable the study of condensation-evaporation dynamics of nanometer-scale drops.

Adaptive and non-adaptive models of depression: A comparison using register data on antidepressant medication during divorce

PubMed Central

Fawcett, Tim W.; Higginson, Andrew D.; Metsä-Simola, Niina; Hagen, Edward H.; Houston, Alasdair I.; Martikainen, Pekka

2017-01-01

Divorce is associated with an increased probability of a depressive episode, but the causation of events remains unclear. Adaptive models of depression propose that depression is a social strategy in part, whereas non-adaptive models tend to propose a diathesis-stress mechanism. We compare an adaptive evolutionary model of depression to three alternative non-adaptive models with respect to their ability to explain the temporal pattern of depression around the time of divorce. Register-based data (304,112 individuals drawn from a random sample of 11% of Finnish people) on antidepressant purchases is used as a proxy for depression. This proxy affords an unprecedented temporal resolution (a 3-monthly prevalence estimates over 10 years) without any bias from non-compliance, and it can be linked with underlying episodes via a statistical model. The evolutionary-adaptation model (all time periods with risk of divorce are depressogenic) was the best quantitative description of the data. The non-adaptive stress-relief model (period before divorce is depressogenic and period afterwards is not) provided the second best quantitative description of the data. The peak-stress model (periods before and after divorce can be depressogenic) fit the data less well, and the stress-induction model (period following divorce is depressogenic and the preceding period is not) did not fit the data at all. The evolutionary model was the most detailed mechanistic description of the divorce-depression link among the models, and the best fit in terms of predicted curvature; thus, it offers most rigorous hypotheses for further study. The stress-relief model also fit very well and was the best model in a sensitivity analysis, encouraging development of more mechanistic models for that hypothesis. PMID:28614385

Adaptive and non-adaptive models of depression: A comparison using register data on antidepressant medication during divorce.

PubMed

Rosenström, Tom; Fawcett, Tim W; Higginson, Andrew D; Metsä-Simola, Niina; Hagen, Edward H; Houston, Alasdair I; Martikainen, Pekka

2017-01-01

Divorce is associated with an increased probability of a depressive episode, but the causation of events remains unclear. Adaptive models of depression propose that depression is a social strategy in part, whereas non-adaptive models tend to propose a diathesis-stress mechanism. We compare an adaptive evolutionary model of depression to three alternative non-adaptive models with respect to their ability to explain the temporal pattern of depression around the time of divorce. Register-based data (304,112 individuals drawn from a random sample of 11% of Finnish people) on antidepressant purchases is used as a proxy for depression. This proxy affords an unprecedented temporal resolution (a 3-monthly prevalence estimates over 10 years) without any bias from non-compliance, and it can be linked with underlying episodes via a statistical model. The evolutionary-adaptation model (all time periods with risk of divorce are depressogenic) was the best quantitative description of the data. The non-adaptive stress-relief model (period before divorce is depressogenic and period afterwards is not) provided the second best quantitative description of the data. The peak-stress model (periods before and after divorce can be depressogenic) fit the data less well, and the stress-induction model (period following divorce is depressogenic and the preceding period is not) did not fit the data at all. The evolutionary model was the most detailed mechanistic description of the divorce-depression link among the models, and the best fit in terms of predicted curvature; thus, it offers most rigorous hypotheses for further study. The stress-relief model also fit very well and was the best model in a sensitivity analysis, encouraging development of more mechanistic models for that hypothesis.

Investigating the effect of invasion characteristics on onion thrips (Thysanoptera: Thripidae) populations in onions with a temperature-driven process model.

PubMed

Mo, Jianhua; Stevens, Mark; Liu, De Li; Herron, Grant

2009-12-01

A temperature-driven process model was developed to describe the seasonal patterns of populations of onion thrips, Thrips tabaci Lindeman, in onions. The model used daily cohorts (individuals of the same developmental stage and daily age) as the population unit. Stage transitions were modeled as a logistic function of accumulated degree-days to account for variability in development rate among individuals. Daily survival was modeled as a logistic function of daily mean temperature. Parameters for development, survival, and fecundity were estimated from published data. A single invasion event was used to initiate the population process, starting at 1-100 d after onion emergence (DAE) for 10-100 d at the daily rate of 0.001-0.9 adults/plant/d. The model was validated against five observed seasonal patterns of onion thrips populations from two unsprayed sites in the Riverina, New South Wales, Australia, during 2003-2006. Performance of the model was measured by a fit index based on the proportion of variations in observed data explained by the model (R (2)) and the differences in total thrips-days between observed and predicted populations. Satisfactory matching between simulated and observed seasonal patterns was obtained within the ranges of invasion parameters tested. Model best-fit was obtained at invasion starting dates of 6-98 DAE with a daily invasion rate of 0.002-0.2 adults/plant/d and an invasion duration of 30-100 d. Under the best-fit invasion scenarios, the model closely reproduced the observed seasonal patterns, explaining 73-95% of variability in adult and larval densities during population increase periods. The results showed that small invasions of adult thrips followed by a gradual population build-up of thrips within onion crops were sufficient to bring about the observed seasonal patterns of onion thrips populations in onion. Implications of the model on timing of chemical controls are discussed.

Meta-analysis of Gaussian individual patient data: Two-stage or not two-stage?

PubMed

Morris, Tim P; Fisher, David J; Kenward, Michael G; Carpenter, James R

2018-04-30

Quantitative evidence synthesis through meta-analysis is central to evidence-based medicine. For well-documented reasons, the meta-analysis of individual patient data is held in higher regard than aggregate data. With access to individual patient data, the analysis is not restricted to a "two-stage" approach (combining estimates and standard errors) but can estimate parameters of interest by fitting a single model to all of the data, a so-called "one-stage" analysis. There has been debate about the merits of one- and two-stage analysis. Arguments for one-stage analysis have typically noted that a wider range of models can be fitted and overall estimates may be more precise. The two-stage side has emphasised that the models that can be fitted in two stages are sufficient to answer the relevant questions, with less scope for mistakes because there are fewer modelling choices to be made in the two-stage approach. For Gaussian data, we consider the statistical arguments for flexibility and precision in small-sample settings. Regarding flexibility, several of the models that can be fitted only in one stage may not be of serious interest to most meta-analysis practitioners. Regarding precision, we consider fixed- and random-effects meta-analysis and see that, for a model making certain assumptions, the number of stages used to fit this model is irrelevant; the precision will be approximately equal. Meta-analysts should choose modelling assumptions carefully. Sometimes relevant models can only be fitted in one stage. Otherwise, meta-analysts are free to use whichever procedure is most convenient to fit the identified model. © 2018 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Is the Bifactor Model a Better Model or Is It Just Better at Modeling Implausible Responses? Application of Iteratively Reweighted Least Squares to the Rosenberg Self-Esteem Scale.

PubMed

Reise, Steven P; Kim, Dale S; Mansolf, Maxwell; Widaman, Keith F

2016-01-01

Although the structure of the Rosenberg Self-Esteem Scale (RSES) has been exhaustively evaluated, questions regarding dimensionality and direction of wording effects continue to be debated. To shed new light on these issues, we ask (a) for what percentage of individuals is a unidimensional model adequate, (b) what additional percentage of individuals can be modeled with multidimensional specifications, and (c) what percentage of individuals respond so inconsistently that they cannot be well modeled? To estimate these percentages, we applied iteratively reweighted least squares (IRLS) to examine the structure of the RSES in a large, publicly available data set. A distance measure, d s , reflecting a distance between a response pattern and an estimated model, was used for case weighting. We found that a bifactor model provided the best overall model fit, with one general factor and two wording-related group factors. However, on the basis of d r  values, a distance measure based on individual residuals, we concluded that approximately 86% of cases were adequately modeled through a unidimensional structure, and only an additional 3% required a bifactor model. Roughly 11% of cases were judged as "unmodelable" due to their significant residuals in all models considered. Finally, analysis of d s revealed that some, but not all, of the superior fit of the bifactor model is owed to that model's ability to better accommodate implausible and possibly invalid response patterns, and not necessarily because it better accounts for the effects of direction of wording.

Spatial Analysis of “Crazy Quilts”, a Class of Potentially Random Aesthetic Artefacts

PubMed Central

Westphal-Fitch, Gesche; Fitch, W. Tecumseh

2013-01-01

Human artefacts in general are highly structured and often display ordering principles such as translational, reflectional or rotational symmetry. In contrast, human artefacts that are intended to appear random and non symmetrical are very rare. Furthermore, many studies show that humans find it extremely difficult to recognize or reproduce truly random patterns or sequences. Here, we attempt to model two-dimensional decorative spatial patterns produced by humans that show no obvious order. “Crazy quilts” represent a historically important style of quilt making that became popular in the 1870s, and lasted about 50 years. Crazy quilts are unusual because unlike most human artefacts, they are specifically intended to appear haphazard and unstructured. We evaluate the degree to which this intention was achieved by using statistical techniques of spatial point pattern analysis to compare crazy quilts with regular quilts from the same region and era and to evaluate the fit of various random distributions to these two quilt classes. We found that the two quilt categories exhibit fundamentally different spatial characteristics: The patch areas of crazy quilts derive from a continuous random distribution, while area distributions of regular quilts consist of Gaussian mixtures. These Gaussian mixtures derive from regular pattern motifs that are repeated and we suggest that such a mixture is a distinctive signature of human-made visual patterns. In contrast, the distribution found in crazy quilts is shared with many other naturally occurring spatial patterns. Centroids of patches in the two quilt classes are spaced differently and in general, crazy quilts but not regular quilts are well-fitted by a random Strauss process. These results indicate that, within the constraints of the quilt format, Victorian quilters indeed achieved their goal of generating random structures. PMID:24066095

Spatial analysis of "crazy quilts", a class of potentially random aesthetic artefacts.

PubMed

Westphal-Fitch, Gesche; Fitch, W Tecumseh

2013-01-01

Human artefacts in general are highly structured and often display ordering principles such as translational, reflectional or rotational symmetry. In contrast, human artefacts that are intended to appear random and non symmetrical are very rare. Furthermore, many studies show that humans find it extremely difficult to recognize or reproduce truly random patterns or sequences. Here, we attempt to model two-dimensional decorative spatial patterns produced by humans that show no obvious order. "Crazy quilts" represent a historically important style of quilt making that became popular in the 1870s, and lasted about 50 years. Crazy quilts are unusual because unlike most human artefacts, they are specifically intended to appear haphazard and unstructured. We evaluate the degree to which this intention was achieved by using statistical techniques of spatial point pattern analysis to compare crazy quilts with regular quilts from the same region and era and to evaluate the fit of various random distributions to these two quilt classes. We found that the two quilt categories exhibit fundamentally different spatial characteristics: The patch areas of crazy quilts derive from a continuous random distribution, while area distributions of regular quilts consist of Gaussian mixtures. These Gaussian mixtures derive from regular pattern motifs that are repeated and we suggest that such a mixture is a distinctive signature of human-made visual patterns. In contrast, the distribution found in crazy quilts is shared with many other naturally occurring spatial patterns. Centroids of patches in the two quilt classes are spaced differently and in general, crazy quilts but not regular quilts are well-fitted by a random Strauss process. These results indicate that, within the constraints of the quilt format, Victorian quilters indeed achieved their goal of generating random structures.

Rotated balance in humans due to repetitive rotational movement.

PubMed

Zakynthinaki, M S; Milla, J Madera; De Durana, A López Diaz; Martínez, C A Cordente; Romo, G Rodríguez; Quintana, M Sillero; Molinuevo, J Sampedro

2010-03-01

We show how asymmetries in the movement patterns during the process of regaining balance after perturbation from quiet stance can be modeled by a set of coupled vector fields for the derivative with respect to time of the angles between the resultant ground reaction forces and the vertical in the anteroposterior and mediolateral directions. In our model, which is an adaption of the model of Stirling and Zakynthinaki (2004), the critical curve, defining the set of maximum angles one can lean to and still correct to regain balance, can be rotated and skewed so as to model the effects of a repetitive training of a rotational movement pattern. For the purposes of our study a rotation and a skew matrix is applied to the critical curve of the model. We present here a linear stability analysis of the modified model, as well as a fit of the model to experimental data of two characteristic "asymmetric" elite athletes and to a "symmetric" elite athlete for comparison. The new adapted model has many uses not just in sport but also in rehabilitation, as many work place injuries are caused by excessive repetition of unaligned and rotational movement patterns.

Empirical evidence for multi-scaled controls on wildfire size distributions in California

NASA Astrophysics Data System (ADS)

Povak, N.; Hessburg, P. F., Sr.; Salter, R. B.

2014-12-01

Ecological theory asserts that regional wildfire size distributions are examples of self-organized critical (SOC) systems. Controls on SOC event-size distributions by virtue are purely endogenous to the system and include the (1) frequency and pattern of ignitions, (2) distribution and size of prior fires, and (3) lagged successional patterns after fires. However, recent work has shown that the largest wildfires often result from extreme climatic events, and that patterns of vegetation and topography may help constrain local fire spread, calling into question the SOC model's simplicity. Using an atlas of >12,000 California wildfires (1950-2012) and maximum likelihood estimation (MLE), we fit four different power-law models and broken-stick regressions to fire-size distributions across 16 Bailey's ecoregions. Comparisons among empirical fire size distributions across ecoregions indicated that most ecoregion's fire-size distributions were significantly different, suggesting that broad-scale top-down controls differed among ecoregions. One-parameter power-law models consistently fit a middle range of fire sizes (~100 to 10000 ha) across most ecoregions, but did not fit to larger and smaller fire sizes. We fit the same four power-law models to patch size distributions of aspect, slope, and curvature topographies and found that the power-law models fit to a similar middle range of topography patch sizes. These results suggested that empirical evidence may exist for topographic controls on fire sizes. To test this, we used neutral landscape modeling techniques to determine if observed fire edges corresponded with aspect breaks more often than expected by random. We found significant differences between the empirical and neutral models for some ecoregions, particularly within the middle range of fire sizes. Our results, combined with other recent work, suggest that controls on ecoregional fire size distributions are multi-scaled and likely are not purely SOC. California wildfire ecosystems appear to be adaptive, governed by stationary and non-stationary controls, which may be either exogenous or endogenous to the system.

Non-linear Growth Models in Mplus and SAS

PubMed Central

Grimm, Kevin J.; Ram, Nilam

2013-01-01

Non-linear growth curves or growth curves that follow a specified non-linear function in time enable researchers to model complex developmental patterns with parameters that are easily interpretable. In this paper we describe how a variety of sigmoid curves can be fit using the Mplus structural modeling program and the non-linear mixed-effects modeling procedure NLMIXED in SAS. Using longitudinal achievement data collected as part of a study examining the effects of preschool instruction on academic gain we illustrate the procedures for fitting growth models of logistic, Gompertz, and Richards functions. Brief notes regarding the practical benefits, limitations, and choices faced in the fitting and estimation of such models are included. PMID:23882134

Emergent neutrality drives phytoplankton species coexistence

PubMed Central

Segura, Angel M.; Calliari, Danilo; Kruk, Carla; Conde, Daniel; Bonilla, Sylvia; Fort, Hugo

2011-01-01

The mechanisms that drive species coexistence and community dynamics have long puzzled ecologists. Here, we explain species coexistence, size structure and diversity patterns in a phytoplankton community using a combination of four fundamental factors: organism traits, size-based constraints, hydrology and species competition. Using a ‘microscopic’ Lotka–Volterra competition (MLVC) model (i.e. with explicit recipes to compute its parameters), we provide a mechanistic explanation of species coexistence along a niche axis (i.e. organismic volume). We based our model on empirically measured quantities, minimal ecological assumptions and stochastic processes. In nature, we found aggregated patterns of species biovolume (i.e. clumps) along the volume axis and a peak in species richness. Both patterns were reproduced by the MLVC model. Observed clumps corresponded to niche zones (volumes) where species fitness was highest, or where fitness was equal among competing species. The latter implies the action of equalizing processes, which would suggest emergent neutrality as a plausible mechanism to explain community patterns. PMID:21177680

Investigating Convergence Patterns for Numerical Methods Using Data Analysis

ERIC Educational Resources Information Center

Gordon, Sheldon P.

2013-01-01

The article investigates the patterns that arise in the convergence of numerical methods, particularly those in the errors involved in successive iterations, using data analysis and curve fitting methods. In particular, the results obtained are used to convey a deeper level of understanding of the concepts of linear, quadratic, and cubic…

Amorphous Analogs of Martian Global Soil: Pair Distribution Function Analyses and Implications for Scattering Models of Chemin X-ray Diffraction Data

NASA Technical Reports Server (NTRS)

Achilles, C. N.; Bish, D. L.; Rampe, E. B.; Morris, R. V.

2015-01-01

Soils on Mars have been analyzed by the Mars Exploration Rovers (MER) and most recently by the Mars Science Laboratory (MSL) rover. Chemical analyses from a majority of soil samples suggest that there is a relatively uniform global soil composition across much of the planet. A soil site, Rocknest, was sampled by the MSL science payload including the CheMin X-ray diffractometer and the Alpha Particle X-ray Spectrometer (APXS). Che- Min X-ray diffraction (XRD) data revealed crystalline phases and a broad, elevated background, indicating the presence of amorphous or poorly ordered materials (Fig 1). Based on the chemical composition of the bulk soil measured by APXS and the composition of crystalline phases derived from unit-cell parameters determined with CheMin data, the percentages of crystalline and amorphous phases were calculated at 51% and 49%, respectively. Attempts to model the amorphous contribution to CheMin XRD patterns were made using amorphous standards and full-pattern fitting methods and show that the broad, elevated background region can be fitted by basaltic glass, allophane, and palagonite. However, the modeling shows only that these phases have scattering patterns similar to that for the soil, not that they represent unique solutions. Here, we use pair distribution function (PDF) analysis to determine the short-range order of amorphous analogs in martian soils and better constrain the amorphous material detected by CheMin.

Is the Bifactor Model a Better Model or is it Just Better at Modeling Implausible Responses? Application of Iteratively Reweighted Least Squares to the Rosenberg Self-Esteem Scale

PubMed Central

Reise, Steven P.; Kim, Dale S.; Mansolf, Maxwell; Widaman, Keith F.

2017-01-01

Although the structure of the Rosenberg Self-Esteem Scale (RSES; Rosenberg, 1965) has been exhaustively evaluated, questions regarding dimensionality and direction of wording effects continue to be debated. To shed new light on these issues, we ask: (1) for what percentage of individuals is a unidimensional model adequate, (2) what additional percentage of individuals can be modeled with multidimensional specifications, and (3) what percentage of individuals respond so inconsistently that they cannot be well modeled? To estimate these percentages, we applied iteratively reweighted least squares (IRLS; Yuan & Bentler, 2000) to examine the structure of the RSES in a large, publicly available dataset. A distance measure, ds, reflecting a distance between a response pattern and an estimated model, was used for case weighting. We found that a bifactor model provided the best overall model fit, with one general factor and two wording-related group factors. But, based on dr values, a distance measure based on individual residuals, we concluded that approximately 86% of cases were adequately modeled through a unidimensional structure, and only an additional 3% required a bifactor model. Roughly 11% of cases were judged as “unmodelable” due to their significant residuals in all models considered. Finally, analysis of ds revealed that some, but not all, of the superior fit of the bifactor model is owed to that model’s ability to better accommodate implausible and possibly invalid response patterns, and not necessarily because it better accounts for the effects of direction of wording. PMID:27834509

Astigmatism correction of a non-imaging double spectrometer fitted with a 2D array detector

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

Yaney, P.P.; Ernst, S.L.; Blackshire, J.

1992-12-01

A SPEX 1401 double spectrometer was adapted for a liquid nitrogen cooled CCD detector to permit both spectral and spatial analysis of ceramic specimens in a laser Raman microprobe system. The exit image of the spectrometer suffers from astigmatism due to off-axis spherical mirrors. A cylindrical lens was added before the CCD to correct for the astigmatism. The spectrometer and several lenses were modeled using an optical ray tracing program to characterize the astigmatism and to optimize the locations of the lens and the detector. The astigmatism and the spot pattern sizes determined by the model were in good agreementmore » with he observed performance of the modified spectrometer-detector system. Typical spot patterns fell within the 23 {mu}m square pixel size.« less

AIDS-related health behavior: coping, protection motivation, and previous behavior.

PubMed

Van der Velde, F W; Van der Pligt, J

1991-10-01

The purpose of this study was to examine Rogers' protection motivation theory and aspects of Janis and Mann's conflict theory in the context of AIDS-related health behavior. Subjects were 84 heterosexual men and women and 147 homosexual men with multiple sexual partners; LISREL's path-analysis techniques were used to evaluate the goodness of fit of the structural equation models. Protection motivation theory did fit the data but had considerably more explanatory power for heterosexual than for homosexual subjects (49 vs. 22%, respectively). When coping styles were added, different patterns of findings were found among both groups. Adding variables such as social norms and previous behavior increased the explained variance to 73% for heterosexual subjects and to 44% for homosexual subjects. It was concluded that although protection motivation theory did fit the data fairly adequately, expanding the theory with other variables--especially those related to previous behavior--could improve our understanding of AIDS-related health behavior.

A Comparison of Four Estimators of a Population Measure of Model Fit in Covariance Structure Analysis

ERIC Educational Resources Information Center

Zhang, Wei

2008-01-01

A major issue in the utilization of covariance structure analysis is model fit evaluation. Recent years have witnessed increasing interest in various test statistics and so-called fit indexes, most of which are actually based on or closely related to F[subscript 0], a measure of model fit in the population. This study aims to provide a systematic…

Semivarying coefficient models for capture-recapture data: colony size estimation for the little penguin Eudyptula minor.

PubMed

Stoklosa, Jakub; Dann, Peter; Huggins, Richard

2014-09-01

To accommodate seasonal effects that change from year to year into models for the size of an open population we consider a time-varying coefficient model. We fit this model to a capture-recapture data set collected on the little penguin Eudyptula minor in south-eastern Australia over a 25 year period using Jolly-Seber type estimators and nonparametric P-spline techniques. The time-varying coefficient model identified strong changes in the seasonal pattern across the years which we further examined using functional data analysis techniques. To evaluate the methodology we also conducted several simulation studies that incorporate seasonal variation. Copyright © 2014 Elsevier Inc. All rights reserved.

Apparent power-law distributions in animal movements can arise from intraspecific interactions

PubMed Central

Breed, Greg A.; Severns, Paul M.; Edwards, Andrew M.

2015-01-01

Lévy flights have gained prominence for analysis of animal movement. In a Lévy flight, step-lengths are drawn from a heavy-tailed distribution such as a power law (PL), and a large number of empirical demonstrations have been published. Others, however, have suggested that animal movement is ill fit by PL distributions or contend a state-switching process better explains apparent Lévy flight movement patterns. We used a mix of direct behavioural observations and GPS tracking to understand step-length patterns in females of two related butterflies. We initially found movement in one species (Euphydryas editha taylori) was best fit by a bounded PL, evidence of a Lévy flight, while the other (Euphydryas phaeton) was best fit by an exponential distribution. Subsequent analyses introduced additional candidate models and used behavioural observations to sort steps based on intraspecific interactions (interactions were rare in E. phaeton but common in E. e. taylori). These analyses showed a mixed-exponential is favoured over the bounded PL for E. e. taylori and that when step-lengths were sorted into states based on the influence of harassing conspecific males, both states were best fit by simple exponential distributions. The direct behavioural observations allowed us to infer the underlying behavioural mechanism is a state-switching process driven by intraspecific interactions rather than a Lévy flight. PMID:25519992

Kinetics of mineralization of organic compounds at low concentrations in soil.

PubMed Central

Scow, K M; Simkins, S; Alexander, M

1986-01-01

The kinetics of mineralization of 14C-labeled phenol and aniline were measured at initial concentrations ranging from 0.32 to 5,000 ng and 0.30 ng to 500 micrograms/g of soil, respectively. Mineralization of phenol at concentrations less than or equal to 32 ng/g of soil and of aniline at all concentrations began immediately, and the curves for the evolution of labeled CO2 were biphasic. The patterns of mineralization of 4.0 ng of 2,4-dichlorophenol per g of soil and 20 ng of nitrilotriacetic acid per g of soil were similar to the patterns for phenol and aniline. The patterns of mineralization of 1.0 to 100 ng of p-nitrophenol and 6.0 ng of benzylamine per g of soil were also biphasic but after a short apparent lag period. The curves of CO2 evolution from higher concentrations of phenol and p-nitrophenol had increasing apparent lag phases and were S-shaped or linear. Cumulative plots of the percentage of substrate converted to CO2 were fit by nonlinear regression to first-order, integrated Monod, logistic, logarithmic, zero-order, three-half-order, and two-compartment models. None of the models of the Monod family provided the curve of best fit to any of the patterns of mineralization. The linear growth form of the three-half-order model provided the best fit for the mineralization of p-nitrophenol, with the exception of the lowest concentrations, and of benzylamine. The two-compartment model provided the best fit for the mineralization of concentrations of phenol below 100 ng/g, of several concentrations of aniline, and of nitrilotriacetic acid. It is concluded that models derived from the Monod equation, including the first-order model, do not adequately describe the kinetics of mineralization of low concentrations of chemicals added to soil. PMID:3729388

Patterns of productive activity engagement among older adults in urban China.

PubMed

Liu, Huiying; Lou, Wei Qun

2016-12-01

This study aims to identify patterns of productive activity engagement among older adults in urban China. Once patterns are identified, we further explore how a set of individual characteristics is associated with these patterns. Using data from the 2011 baseline survey of the China Health and Retirement Longitudinal Study (CHARLS), we performed a latent class analysis (LCA) on a national representative sample of adults aged 60 years and over ( N  = 3019). A specified range of productive activity indicators that fit the context of urban China was used for performing LCA (including working, grandchildren's care, parental care, spousal care, informal helping, and formal volunteering). A multinomial logistic regression was used to assess whether individual characteristics are associated with the identified patterns. The results indicated that a four-class model fit the data well, with the interpretable set of classes: spouse carer (51.2 %), working grandparents (21.7 %), multifaceted contributor (16.6 %), and light-engaged volunteer (10.5 %). Age, gender, education, number of children, proximity with the nearest child, household composition and functional status contributed to differentiating these classes. This study captured the reality of productive engagement among older adults by drawing attention to how multiple productive activities intersect in later-life stages. Our findings have implications for policy-makers, health care practitioners, and community advocates to develop programs that facilitate this aging population in assuming meaningful productive activities.

[Analysis of genetic models and gene effects on main agronomy characters in rapeseed].

PubMed

Li, J; Qiu, J; Tang, Z; Shen, L

1992-01-01

According to four different genetic models, the genetic patterns of 8 agronomy traits were analysed by using the data of 24 generations which included positive and negative cross of 81008 x Tower, both of the varieties are of good quality. The results showed that none of 8 characters could fit in with additive-dominance models. Epistasis was found in all of these characters, and it has significant effect on generation means. Seed weight/plant and some other main yield characters are controlled by duplicate interaction genes. The interaction between triple genes or multiple genes needs to be utilized in yield heterosis.

The Kunming CalFit study: modeling dietary behavioral patterns using smartphone data.

PubMed

Seto, Edmund; Hua, Jenna; Wu, Lemuel; Bestick, Aaron; Shia, Victor; Eom, Sue; Han, Jay; Wang, May; Li, Yan

2014-01-01

Human behavioral interventions aimed at improving health can benefit from objective wearable sensor data and mathematical models. Smartphone-based sensing is particularly practical for monitoring behavioral patterns because smartphones are fairly common, are carried by individuals throughout their daily lives, offer a variety of sensing modalities, and can facilitate various forms of user feedback for intervention studies. We describe our findings from a smartphone-based study, in which an Android-based application we developed called CalFit was used to collect information related to young adults' dietary behaviors. In addition to monitoring dietary patterns, we were interested in understanding contextual factors related to when and where an individual eats, as well as how their dietary intake relates to physical activity (which creates energy demand) and psychosocial stress. 12 participants were asked to use CalFit to record videos of their meals over two 1-week periods, which were translated into nutrient intake by trained dietitians. During this same period, triaxial accelerometry was used to assess each subject's energy expenditure, and GPS was used to record time-location patterns. Ecological momentary assessment was also used to prompt subjects to respond to questions on their phone about their psychological state. The GPS data were processed through a web service we developed called Foodscoremap that is based on the Google Places API to characterize food environments that subjects were exposed to, which may explain and influence dietary patterns. Furthermore, we describe a modeling framework that incorporates all of these information to dynamically infer behavioral patterns that may be used for future intervention studies.

Spatio-temporal water quality mapping from satellite images using geographically and temporally weighted regression

NASA Astrophysics Data System (ADS)

Chu, Hone-Jay; Kong, Shish-Jeng; Chang, Chih-Hua

2018-03-01

The turbidity (TB) of a water body varies with time and space. Water quality is traditionally estimated via linear regression based on satellite images. However, estimating and mapping water quality require a spatio-temporal nonstationary model, while TB mapping necessitates the use of geographically and temporally weighted regression (GTWR) and geographically weighted regression (GWR) models, both of which are more precise than linear regression. Given the temporal nonstationary models for mapping water quality, GTWR offers the best option for estimating regional water quality. Compared with GWR, GTWR provides highly reliable information for water quality mapping, boasts a relatively high goodness of fit, improves the explanation of variance from 44% to 87%, and shows a sufficient space-time explanatory power. The seasonal patterns of TB and the main spatial patterns of TB variability can be identified using the estimated TB maps from GTWR and by conducting an empirical orthogonal function (EOF) analysis.

Comparing the Fit of Item Response Theory and Factor Analysis Models

ERIC Educational Resources Information Center

Maydeu-Olivares, Alberto; Cai, Li; Hernandez, Adolfo

2011-01-01

Linear factor analysis (FA) models can be reliably tested using test statistics based on residual covariances. We show that the same statistics can be used to reliably test the fit of item response theory (IRT) models for ordinal data (under some conditions). Hence, the fit of an FA model and of an IRT model to the same data set can now be…

Local and average structures of BaTiO 3-Bi(Zn 1/2Ti 1/2)O 3

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

Usher, Tedi-Marie; Iamsasri, Thanakorn; Forrester, Jennifer S.

The complex crystallographic structures of (1-x)BaTiO 3-xBi(Zn 1/2Ti 1/2)O 3 (BT-xBZT) are examined using high resolution synchrotron X-ray diffraction, neutron diffraction, and neutron pair distribution function (PDF) analyses. The short-range structures are characterized from the PDFs, and a combined analysis of the X-ray and neutron diffraction patterns is used to determine the long-range structures. Our results demonstrate that the structure appears different when averaged over different length scales. In all compositions, the local structures determined from the PDFs show local tetragonal distortions (i.e., c/a > 1). But, a box-car fitting analysis of the PDFs reveals variations at different length scales.more » For 0.80BT-0.20BZT and 0.90BT-0.10BZT, the tetragonal distortions decrease at longer atom-atom distances (e.g., 30 vs. 5 ). When the longest distances are evaluated (r > 40 ), the lattice parameters approach cubic. Neutron and X-ray diffraction yield further information about the long-range structure. Compositions 0.80BT-0.20BZT and 0.90BT-0.10BZT appear cubic by Bragg diffraction (no peak splitting), consistent with the PDFs at long distances. However, these patterns cannot be adequately fit using a cubic lattice model; modeling their structures with the P4mm space group allows for a better fit to the patterns because the space group allows for c-axis atomic displacements that occur at the local scale. Furthermore, for the compositions 0.92BT-0.08BZT and 0.94BT-0.06BZT, strong tetragonal distortions are observed at the local scale and a less-distorted tetragonal structure is observed at longer length scales. In Rietveld refinements, the latter is modeled using a tetragonal phase. Since the peak overlap in these two-phase compositions limits the ability to model the local-scale structures as tetragonal, it is approximated in the refinements as a cubic phase. These results demonstrate that alloying BT with BZT results in increased disorder and disrupts the long-range ferroelectric symmetry present in BT, while the large tetragonal distortion present in BZT persists at the local scale.« less

Local and average structures of BaTiO 3-Bi(Zn 1/2Ti 1/2)O 3

DOE PAGES

Usher, Tedi-Marie; Iamsasri, Thanakorn; Forrester, Jennifer S.; ...

2016-11-11

The complex crystallographic structures of (1-x)BaTiO 3-xBi(Zn 1/2Ti 1/2)O 3 (BT-xBZT) are examined using high resolution synchrotron X-ray diffraction, neutron diffraction, and neutron pair distribution function (PDF) analyses. The short-range structures are characterized from the PDFs, and a combined analysis of the X-ray and neutron diffraction patterns is used to determine the long-range structures. Our results demonstrate that the structure appears different when averaged over different length scales. In all compositions, the local structures determined from the PDFs show local tetragonal distortions (i.e., c/a > 1). But, a box-car fitting analysis of the PDFs reveals variations at different length scales.more » For 0.80BT-0.20BZT and 0.90BT-0.10BZT, the tetragonal distortions decrease at longer atom-atom distances (e.g., 30 vs. 5 ). When the longest distances are evaluated (r > 40 ), the lattice parameters approach cubic. Neutron and X-ray diffraction yield further information about the long-range structure. Compositions 0.80BT-0.20BZT and 0.90BT-0.10BZT appear cubic by Bragg diffraction (no peak splitting), consistent with the PDFs at long distances. However, these patterns cannot be adequately fit using a cubic lattice model; modeling their structures with the P4mm space group allows for a better fit to the patterns because the space group allows for c-axis atomic displacements that occur at the local scale. Furthermore, for the compositions 0.92BT-0.08BZT and 0.94BT-0.06BZT, strong tetragonal distortions are observed at the local scale and a less-distorted tetragonal structure is observed at longer length scales. In Rietveld refinements, the latter is modeled using a tetragonal phase. Since the peak overlap in these two-phase compositions limits the ability to model the local-scale structures as tetragonal, it is approximated in the refinements as a cubic phase. These results demonstrate that alloying BT with BZT results in increased disorder and disrupts the long-range ferroelectric symmetry present in BT, while the large tetragonal distortion present in BZT persists at the local scale.« less

A Note on Procrustean Rotation in Exploratory Factor Analysis: A Computer Intensive Approach to Goodness-of-Fit Evaluation.

ERIC Educational Resources Information Center

Raykov, Tenko; Little, Todd D.

1999-01-01

Describes a method for evaluating results of Procrustean rotation to a target factor pattern matrix in exploratory factor analysis. The approach, based on the bootstrap method, yields empirical approximations of the sampling distributions of: (1) differences between target elements and rotated factor pattern matrices; and (2) the overall…

Using Latent Class Analysis to Model Temperament Types.

PubMed

Loken, Eric

2004-10-01

Mixture models are appropriate for data that arise from a set of qualitatively different subpopulations. In this study, latent class analysis was applied to observational data from a laboratory assessment of infant temperament at four months of age. The EM algorithm was used to fit the models, and the Bayesian method of posterior predictive checks was used for model selection. Results show at least three types of infant temperament, with patterns consistent with those identified by previous researchers who classified the infants using a theoretically based system. Multiple imputation of group memberships is proposed as an alternative to assigning subjects to the latent class with maximum posterior probability in order to reflect variance due to uncertainty in the parameter estimation. Latent class membership at four months of age predicted longitudinal outcomes at four years of age. The example illustrates issues relevant to all mixture models, including estimation, multi-modality, model selection, and comparisons based on the latent group indicators.

The use of MAGSAT data to determine secular variation.

USGS Publications Warehouse

Cain, J.C.; Frayser, J.; Muth, L.; Schmitz, D.

1983-01-01

A combined spatial and secular variation model of the geomagnetic field, labeled M061581, is derived from a selection of MAGSAT data. Secular variation (SV) data computed from linear fits to midnight hourly values from 19 magnetic observatories were also included in the analysis but were seen to have little effect on the model. The SV patterns from this new model are compared with those from the 1980 IGRF and with those for 1970 computed by the DGRF and with the 1960 patterns computed using the GSFC(12/66) model. Most of the features of the M061581 are identical in location and level with those of the 1980 IGRF. Together they confirm that the reversals in sign of field change seen over Asia and North America between 1965 and 1975 are reverting to the pre-1965 states. The M061581 model gives -32 nT/yr for the dipole decay rate, larger than the 70% increase already reported since 1965. -Authors

Patterns of Change in Children's Loneliness: Trajectories from Third through Fifth Grades

ERIC Educational Resources Information Center

Jobe-Shields, Lisa; Cohen, Robert; Parra, Gilbert R.

2011-01-01

Latent growth-mixture modeling was used to investigate patterns of change in loneliness for 170 children from third through fifth grades. A three-class model representing unique trajectories of loneliness provided the best overall fit to the data, including a Stable Low group (65%), as well as groups of Increasers (23%) and Decreasers (12%).…

User Guide to RockJock - A Program for Determining Quantitative Mineralogy from X-Ray Diffraction Data

USGS Publications Warehouse

Eberl, D.D.

2003-01-01

RockJock is a computer program that determines quantitative mineralogy in powdered samples by comparing the integrated X-ray diffraction (XRD) intensities of individual minerals in complex mixtures to the intensities of an internal standard. Analysis without an internal standard (standardless analysis) also is an option. This manual discusses how to prepare and X-ray samples and mineral standards for these types of analyses and describes the operation of the program. Carefully weighed samples containing an internal standard (zincite) are ground in a McCrone mill. Randomly oriented preparations then are X-rayed, and the X-ray data are entered into the RockJock program. Minerals likely to be present in the sample are chosen from a list of standards, and the calculation is begun. The program then automatically fits the sum of stored XRD patterns of pure standard minerals (the calculated pattern) to the measured pattern by varying the fraction of each mineral standard pattern, using the Solver function in Microsoft Excel to minimize a degree of fit parameter between the calculated and measured pattern. The calculation analyzes the pattern (usually 20 to 65 degrees two-theta) to find integrated intensities for the minerals. Integrated intensities for each mineral then are determined from the proportion of each mineral standard pattern required to give the best fit. These integrated intensities then are compared to the integrated intensity of the internal standard, and the weight percentages of the minerals are calculated. The results are presented as a list of minerals with their corresponding weight percent. To some extent, the quality of the analysis can be checked because each mineral is analyzed independently, and, therefore, the sum of the analysis should approach 100 percent. Also, the method has been shown to give good results with artificial mixtures. The program is easy to use, but does require an understanding of mineralogy, of X-ray diffraction practice, and an elementary knowledge of the Excel program.

Response Surface Methodology Using a Fullest Balanced Model: A Re-Analysis of a Dataset in the Korean Journal for Food Science of Animal Resources.

PubMed

Rheem, Sungsue; Rheem, Insoo; Oh, Sejong

2017-01-01

Response surface methodology (RSM) is a useful set of statistical techniques for modeling and optimizing responses in research studies of food science. In the analysis of response surface data, a second-order polynomial regression model is usually used. However, sometimes we encounter situations where the fit of the second-order model is poor. If the model fitted to the data has a poor fit including a lack of fit, the modeling and optimization results might not be accurate. In such a case, using a fullest balanced model, which has no lack of fit, can fix such problem, enhancing the accuracy of the response surface modeling and optimization. This article presents how to develop and use such a model for the better modeling and optimizing of the response through an illustrative re-analysis of a dataset in Park et al. (2014) published in the Korean Journal for Food Science of Animal Resources .

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

PubMed

Chatterji, Madhabi

2002-01-01

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

Growth Patterns of Neuropsychological Functions in Indian Children

PubMed Central

Kar, Bhoomika R.; Rao, Shobini L.; Chandramouli, B. A.; Thennarasu, K.

2011-01-01

We investigated age-related differences in neuropsychological performance in 400 Indian school children (5–15 years of age). Functions of motor speed, attention, executive functions, visuospatial functions, comprehension, learning, and memory were examined. Growth curve analysis was performed. Different growth models fitted different cognitive functions. Neuropsychological task performance improved slowly between 5 and 7 years, moderately between 8 and 12 years and slowly between 13 and 15 years of age. The overall growth patterns of neuropsychological functions in Indian children have been discussed with the findings reported on American children. The present work describes non-linear, heterogeneous, and protracted age trends of neuropsychological functions in Indian children and adolescents. PMID:22053158

Right-Sizing Statistical Models for Longitudinal Data

PubMed Central

Wood, Phillip K.; Steinley, Douglas; Jackson, Kristina M.

2015-01-01

Arguments are proposed that researchers using longitudinal data should consider more and less complex statistical model alternatives to their initially chosen techniques in an effort to “right-size” the model to the data at hand. Such model comparisons may alert researchers who use poorly fitting overly parsimonious models to more complex better fitting alternatives, and, alternatively, may identify more parsimonious alternatives to overly complex (and perhaps empirically under-identified and/or less powerful) statistical models. A general framework is proposed for considering (often nested) relationships between a variety of psychometric and growth curve models. A three-step approach is proposed in which models are evaluated based on the number and patterning of variance components prior to selection of better-fitting growth models that explain both mean and variation/covariation patterns. The orthogonal, free-curve slope-intercept (FCSI) growth model is considered as a general model which includes, as special cases, many models including the Factor Mean model (FM, McArdle & Epstein, 1987), McDonald's (1967) linearly constrained factor model, Hierarchical Linear Models (HLM), Repeated Measures MANOVA, and the Linear Slope Intercept (LinearSI) Growth Model. The FCSI model, in turn, is nested within the Tuckerized factor model. The approach is illustrated by comparing alternative models in a longitudinal study of children's vocabulary and by comparison of several candidate parametric growth and chronometric models in a Monte Carlo study. PMID:26237507

Modelling the firing pattern of bullfrog vestibular neurons responding to naturalistic stimuli

NASA Technical Reports Server (NTRS)

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

1999-01-01

We have developed a neural system identification method for fitting models to stimulus-response data, where the response is a spike train. The method involves using a general nonlinear optimisation procedure to fit models in the time domain. We have applied the method to model bullfrog semicircular canal afferent neuron responses during naturalistic, broad-band head rotations. These neurons respond in diverse ways, but a simple four parameter class of models elegantly accounts for the various types of responses observed. c1999 Elsevier Science B.V. All rights reserved.

Student Background, School Climate, School Disorder, and Student Achievement: An Empirical Study of New York City's Middle Schools

ERIC Educational Resources Information Center

Chen, Greg; Weikart, Lynne A.

2008-01-01

This study develops and tests a school disorder and student achievement model based upon the school climate framework. The model was fitted to 212 New York City middle schools using the Structural Equations Modeling Analysis method. The analysis shows that the model fits the data well based upon test statistics and goodness of fit indices. The…

The extended Lennard-Jones potential energy function: A simpler model for direct-potential-fit analysis

NASA Astrophysics Data System (ADS)

Hajigeorgiou, Photos G.

2016-12-01

An analytical model for the diatomic potential energy function that was recently tested as a universal function (Hajigeorgiou, 2010) has been further modified and tested as a suitable model for direct-potential-fit analysis. Applications are presented for the ground electronic states of three diatomic molecules: oxygen, carbon monoxide, and hydrogen fluoride. The adjustable parameters of the extended Lennard-Jones potential model are determined through nonlinear regression by fits to calculated rovibrational energy term values or experimental spectroscopic line positions. The model is shown to lead to reliable, compact and simple representations for the potential energy functions of these systems and could therefore be classified as a suitable and attractive model for direct-potential-fit analysis.

The hitchhiker's guide to altruism: gene-culture coevolution, and the internalization of norms.

PubMed

Gintis, Herbert

2003-02-21

An internal norm is a pattern of behavior enforced in part by internal sanctions, such as shame, guilt and loss of self-esteem, as opposed to purely external sanctions, such as material rewards and punishment. The ability to internalize norms is widespread among humans, although in some so-called "sociopaths", this capacity is diminished or lacking. Suppose there is one genetic locus that controls the capacity to internalize norms. This model shows that if an internal norm is fitness enhancing, then for plausible patterns of socialization, the allele for internalization of norms is evolutionarily stable. This framework can be used to model Herbert Simon's (1990) explanation of altruism, showing that altruistic norms can "hitchhike" on the general tendency of internal norms to be personally fitness-enhancing. A multi-level selection, gene-culture coevolution argument then explains why individually fitness-reducing internal norms are likely to be prosocial as opposed to socially harmful.

Evaluation of bacterial run and tumble motility parameters through trajectory analysis

NASA Astrophysics Data System (ADS)

Liang, Xiaomeng; Lu, Nanxi; Chang, Lin-Ching; Nguyen, Thanh H.; Massoudieh, Arash

2018-04-01

In this paper, a method for extraction of the behavior parameters of bacterial migration based on the run and tumble conceptual model is described. The methodology is applied to the microscopic images representing the motile movement of flagellated Azotobacter vinelandii. The bacterial cells are considered to change direction during both runs and tumbles as is evident from the movement trajectories. An unsupervised cluster analysis was performed to fractionate each bacterial trajectory into run and tumble segments, and then the distribution of parameters for each mode were extracted by fitting mathematical distributions best representing the data. A Gaussian copula was used to model the autocorrelation in swimming velocity. For both run and tumble modes, Gamma distribution was found to fit the marginal velocity best, and Logistic distribution was found to represent better the deviation angle than other distributions considered. For the transition rate distribution, log-logistic distribution and log-normal distribution, respectively, was found to do a better job than the traditionally agreed exponential distribution. A model was then developed to mimic the motility behavior of bacteria at the presence of flow. The model was applied to evaluate its ability to describe observed patterns of bacterial deposition on surfaces in a micro-model experiment with an approach velocity of 200 μm/s. It was found that the model can qualitatively reproduce the attachment results of the micro-model setting.

Model Fit and Item Factor Analysis: Overfactoring, Underfactoring, and a Program to Guide Interpretation.

PubMed

Clark, D Angus; Bowles, Ryan P

2018-04-23

In exploratory item factor analysis (IFA), researchers may use model fit statistics and commonly invoked fit thresholds to help determine the dimensionality of an assessment. However, these indices and thresholds may mislead as they were developed in a confirmatory framework for models with continuous, not categorical, indicators. The present study used Monte Carlo simulation methods to investigate the ability of popular model fit statistics (chi-square, root mean square error of approximation, the comparative fit index, and the Tucker-Lewis index) and their standard cutoff values to detect the optimal number of latent dimensions underlying sets of dichotomous items. Models were fit to data generated from three-factor population structures that varied in factor loading magnitude, factor intercorrelation magnitude, number of indicators, and whether cross loadings or minor factors were included. The effectiveness of the thresholds varied across fit statistics, and was conditional on many features of the underlying model. Together, results suggest that conventional fit thresholds offer questionable utility in the context of IFA.

RATES OF FITNESS DECLINE AND REBOUND SUGGEST PERVASIVE EPISTASIS

PubMed Central

Perfeito, L; Sousa, A; Bataillon, T; Gordo, I

2014-01-01

Unraveling the factors that determine the rate of adaptation is a major question in evolutionary biology. One key parameter is the effect of a new mutation on fitness, which invariably depends on the environment and genetic background. The fate of a mutation also depends on population size, which determines the amount of drift it will experience. Here, we manipulate both population size and genotype composition and follow adaptation of 23 distinct Escherichia coli genotypes. These have previously accumulated mutations under intense genetic drift and encompass a substantial fitness variation. A simple rule is uncovered: the net fitness change is negatively correlated with the fitness of the genotype in which new mutations appear—a signature of epistasis. We find that Fisher's geometrical model can account for the observed patterns of fitness change and infer the parameters of this model that best fit the data, using Approximate Bayesian Computation. We estimate a genomic mutation rate of 0.01 per generation for fitness altering mutations, albeit with a large confidence interval, a mean fitness effect of mutations of −0.01, and an effective number of traits nine in mutS− E. coli. This framework can be extended to confront a broader range of models with data and test different classes of fitness landscape models. PMID:24372601

Global-constrained hidden Markov model applied on wireless capsule endoscopy video segmentation

NASA Astrophysics Data System (ADS)

Wan, Yiwen; Duraisamy, Prakash; Alam, Mohammad S.; Buckles, Bill

2012-06-01

Accurate analysis of wireless capsule endoscopy (WCE) videos is vital but tedious. Automatic image analysis can expedite this task. Video segmentation of WCE into the four parts of the gastrointestinal tract is one way to assist a physician. The segmentation approach described in this paper integrates pattern recognition with statiscal analysis. Iniatially, a support vector machine is applied to classify video frames into four classes using a combination of multiple color and texture features as the feature vector. A Poisson cumulative distribution, for which the parameter depends on the length of segments, models a prior knowledge. A priori knowledge together with inter-frame difference serves as the global constraints driven by the underlying observation of each WCE video, which is fitted by Gaussian distribution to constrain the transition probability of hidden Markov model.Experimental results demonstrated effectiveness of the approach.

New database for improving virtual system “body-dress”

NASA Astrophysics Data System (ADS)

Yan, J. Q.; Zhang, S. C.; Kuzmichev, V. E.; Adolphe, D. C.

2017-10-01

The aim of this exploration is to develop a new database of solid algorithms and relations between the dress fit and the fabric mechanical properties, the pattern block construction for improving the reality of virtual system “body-dress”. In virtual simulation, the system “body-clothing” sometimes shown distinct results with reality, especially when important changes in pattern block and fabrics were involved. In this research, to enhance the simulation process, diverse fit parameters were proposed: bottom height of dress, angle of front center contours, air volume and its distribution between dress and dummy. Measurements were done and optimized by ruler, camera, 3D body scanner image processing software and 3D modeling software. In the meantime, pattern block indexes were measured and fabric properties were tested by KES. Finally, the correlation and linear regression equations between indexes of fabric properties, pattern blocks and fit parameters were investigated. In this manner, new database could be extended in programming modules of virtual design for more realistic results.

Statistical model to perform error analysis of curve fits of wind tunnel test data using the techniques of analysis of variance and regression analysis

NASA Technical Reports Server (NTRS)

Alston, D. W.

1981-01-01

The considered research had the objective to design a statistical model that could perform an error analysis of curve fits of wind tunnel test data using analysis of variance and regression analysis techniques. Four related subproblems were defined, and by solving each of these a solution to the general research problem was obtained. The capabilities of the evolved true statistical model are considered. The least squares fit is used to determine the nature of the force, moment, and pressure data. The order of the curve fit is increased in order to delete the quadratic effect in the residuals. The analysis of variance is used to determine the magnitude and effect of the error factor associated with the experimental data.

Variations in motor unit recruitment patterns occur within and between muscles in the running rat (Rattus norvegicus).

PubMed

Hodson-Tole, E F; Wakeling, J M

2007-07-01

Motor units are generally considered to follow a set, orderly pattern of recruitment within each muscle with activation occurring in the slowest through to the fastest units. A growing body of evidence, however, suggests that recruitment patterns may not always follow such an orderly sequence. Here we investigate whether motor unit recruitment patterns vary within and between the ankle extensor muscles of the rat running at 40 cm s(-1) on a level treadmill. In the past it has been difficult to quantify motor unit recruitment patterns during locomotion; however, recent application of wavelet analysis techniques has made such detailed analysis of motor unit recruitment possible. Here we present methods for quantifying the interplay of fast and slow motor unit recruitment based on their myoelectric signals. Myoelectric data were collected from soleus, plantaris and medial gastrocnemius muscles representing populations of slow, mixed and fast fibres, respectively, and providing a good opportunity to relate myoelectric frequency content to motor unit recruitment patterns. Following wavelet transformation, principal component analysis quantified signal intensity and relative frequency content. Significant differences in signal frequency content occurred between different time points within a stride (P<0.001). We optimised high- and low-frequency wavelets to the major signals from the fast and slow motor units. The goodness-of-fit of the optimised wavelets to the signal intensity was high for all three muscles (r2>0.98). The low-frequency band had a significantly better fit to signals from the soleus muscle (P<0.001), while the high-frequency band had a significantly better fit to the medial gastrocnemius (P<0.001).

Understanding the persistence of measles: reconciling theory, simulation and observation.

PubMed Central

Keeling, Matt J; Grenfell, Bryan T

2002-01-01

Ever since the pattern of localized extinction associated with measles was discovered by Bartlett in 1957, many models have been developed in an attempt to reproduce this phenomenon. Recently, the use of constant infectious and incubation periods, rather than the more convenient exponential forms, has been presented as a simple means of obtaining realistic persistence levels. However, this result appears at odds with rigorous mathematical theory; here we reconcile these differences. Using a deterministic approach, we parameterize a variety of models to fit the observed biennial attractor, thus determining the level of seasonality by the choice of model. We can then compare fairly the persistence of the stochastic versions of these models, using the 'best-fit' parameters. Finally, we consider the differences between the observed fade-out pattern and the more theoretically appealing 'first passage time'. PMID:11886620

Modeling of Phenoxy Acid Herbicide Mineralization and Growth of Microbial Degraders in 15 Soils Monitored by Quantitative Real-Time PCR of the Functional tfdA Gene

PubMed Central

Bælum, Jacob; Prestat, Emmanuel; David, Maude M.; Strobel, Bjarne W.

2012-01-01

Mineralization potentials, rates, and kinetics of the three phenoxy acid (PA) herbicides, 2,4-dichlorophenoxyacetic acid (2,4-D), 4-chloro-2-methylphenoxyacetic acid (MCPA), and 2-(4-chloro-2-methylphenoxy)propanoic acid (MCPP), were investigated and compared in 15 soils collected from five continents. The mineralization patterns were fitted by zero/linear or exponential growth forms of the three-half-order models and by logarithmic (log), first-order, or zero-order kinetic models. Prior and subsequent to the mineralization event, tfdA genes were quantified using real-time PCR to estimate the genetic potential for degrading PA in the soils. In 25 of the 45 mineralization scenarios, ∼60% mineralization was observed within 118 days. Elevated concentrations of tfdA in the range 1 × 105 to 5 × 107 gene copies g−1 of soil were observed in soils where mineralization could be described by using growth-linked kinetic models. A clear trend was observed that the mineralization rates of the three PAs occurred in the order 2,4-D > MCPA > MCPP, and a correlation was observed between rapid mineralization and soils exposed to PA previously. Finally, for 2,4-D mineralization, all seven mineralization patterns which were best fitted by the exponential model yielded a higher tfdA gene potential after mineralization had occurred than the three mineralization patterns best fitted by the Lin model. PMID:22635998

Using multiple group modeling to test moderators in meta-analysis.

PubMed

Schoemann, Alexander M

2016-12-01

Meta-analysis is a popular and flexible analysis that can be fit in many modeling frameworks. Two methods of fitting meta-analyses that are growing in popularity are structural equation modeling (SEM) and multilevel modeling (MLM). By using SEM or MLM to fit a meta-analysis researchers have access to powerful techniques associated with SEM and MLM. This paper details how to use one such technique, multiple group analysis, to test categorical moderators in meta-analysis. In a multiple group meta-analysis a model is fit to each level of the moderator simultaneously. By constraining parameters across groups any model parameter can be tested for equality. Using multiple groups to test for moderators is especially relevant in random-effects meta-analysis where both the mean and the between studies variance of the effect size may be compared across groups. A simulation study and the analysis of a real data set are used to illustrate multiple group modeling with both SEM and MLM. Issues related to multiple group meta-analysis and future directions for research are discussed. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Individual differences in long-range time representation.

PubMed

Agostino, Camila S; Caetano, Marcelo S; Balci, Fuat; Claessens, Peter M E; Zana, Yossi

2017-04-01

On the basis of experimental data, long-range time representation has been proposed to follow a highly compressed power function, which has been hypothesized to explain the time inconsistency found in financial discount rate preferences. The aim of this study was to evaluate how well linear and power function models explain empirical data from individual participants tested in different procedural settings. The line paradigm was used in five different procedural variations with 35 adult participants. Data aggregated over the participants showed that fitted linear functions explained more than 98% of the variance in all procedures. A linear regression fit also outperformed a power model fit for the aggregated data. An individual-participant-based analysis showed better fits of a linear model to the data of 14 participants; better fits of a power function with an exponent β > 1 to the data of 12 participants; and better fits of a power function with β < 1 to the data of the remaining nine participants. Of the 35 volunteers, the null hypothesis β = 1 was rejected for 20. The dispersion of the individual β values was approximated well by a normal distribution. These results suggest that, on average, humans perceive long-range time intervals not in a highly compressed, biased manner, but rather in a linear pattern. However, individuals differ considerably in their subjective time scales. This contribution sheds new light on the average and individual psychophysical functions of long-range time representation, and suggests that any attribution of deviation from exponential discount rates in intertemporal choice to the compressed nature of subjective time must entail the characterization of subjective time on an individual-participant basis.

Statistical Emulation of Climate Model Projections Based on Precomputed GCM Runs*

DOE PAGES

Castruccio, Stefano; McInerney, David J.; Stein, Michael L.; ...

2014-02-24

The authors describe a new approach for emulating the output of a fully coupled climate model under arbitrary forcing scenarios that is based on a small set of precomputed runs from the model. Temperature and precipitation are expressed as simple functions of the past trajectory of atmospheric CO 2 concentrations, and a statistical model is fit using a limited set of training runs. The approach is demonstrated to be a useful and computationally efficient alternative to pattern scaling and captures the nonlinear evolution of spatial patterns of climate anomalies inherent in transient climates. The approach does as well as patternmore » scaling in all circumstances and substantially better in many; it is not computationally demanding; and, once the statistical model is fit, it produces emulated climate output effectively instantaneously. In conclusion, it may therefore find wide application in climate impacts assessments and other policy analyses requiring rapid climate projections.« less

The Relationship Between Pain Characteristics, Peer Difficulties, and Emotional Functioning Among Adolescents Seeking Treatment for Chronic Pain: A Test of Mediational Models.

PubMed

Chan, Sherilynn F; Connelly, Mark; Wallace, Dustin P

2017-10-01

To evaluate patterns of relationships between pain characteristics, peer difficulties, and emotional functioning in a sample of adolescents seeking treatment for chronic pain. Participants were 172 adolescents (age M = 14.88 years; 76% female, 88% White) with heterogeneous chronic pain disorders who completed measures of pain characteristics, peer difficulties, and emotional functioning before their new patient appointment in a pain management clinic. Direct and indirect relationships between variables were tested using path analysis. Adequate model fit was found for models that specified emotional functioning (anxiety and depression) as a mediator of the relationship between pain interference and peer difficulties. Conversely, poor fit was found for all models specifying peer difficulties as a mediator of the relationship between pain characteristics and emotional functioning. Assessing and targeting depression and anxiety among youth with high pain interference may help prevent or improve peer difficulties. © The Author 2017. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Modeling seasonal leptospirosis transmission and its association with rainfall and temperature in Thailand using time-series and ARIMAX analyses.

PubMed

Chadsuthi, Sudarat; Modchang, Charin; Lenbury, Yongwimon; Iamsirithaworn, Sopon; Triampo, Wannapong

2012-07-01

To study the number of leptospirosis cases in relations to the seasonal pattern, and its association with climate factors. Time series analysis was used to study the time variations in the number of leptospirosis cases. The Autoregressive Integrated Moving Average (ARIMA) model was used in data curve fitting and predicting the next leptospirosis cases. We found that the amount of rainfall was correlated to leptospirosis cases in both regions of interest, namely the northern and northeastern region of Thailand, while the temperature played a role in the northeastern region only. The use of multivariate ARIMA (ARIMAX) model showed that factoring in rainfall (with an 8 months lag) yields the best model for the northern region while the model, which factors in rainfall (with a 10 months lag) and temperature (with an 8 months lag) was the best for the northeastern region. The models are able to show the trend in leptospirosis cases and closely fit the recorded data in both regions. The models can also be used to predict the next seasonal peak quite accurately. Copyright © 2012 Hainan Medical College. Published by Elsevier B.V. All rights reserved.

Wetlands explain most in the genetic divergence pattern of Oncomelania hupensis.

PubMed

Liang, Lu; Liu, Yang; Liao, Jishan; Gong, Peng

2014-10-01

Understanding the divergence patterns of hosts could shed lights on the prediction of their parasite transmission. No effort has been devoted to understand the drivers of genetic divergence pattern of Oncomelania hupensis, the only intermediate host of Schistosoma japonicum. Based on a compilation of two O. hupensis gene datasets covering a wide geographic range in China and an array of geographical distance and environmental dissimilarity metrics built from earth observation data and ecological niche modeling, we conducted causal modeling analysis via simple, partial Mantel test and local polynomial fitting to understand the interactions among isolation-by-distance, isolation-by-environment, and genetic divergence. We found that geography contributes more to genetic divergence than environmental isolation, and among all variables involved, wetland showed the strongest correlation with the genetic pairwise distances. These results suggested that in China, O. hupensis dispersal is strongly linked to the distribution of wetlands, and the current divergence pattern of both O. hupensis and schistosomiasis might be altered due to the changed wetland pattern with the accomplishment of the Three Gorges Dam and the South-to-North water transfer project. Copyright © 2014 Elsevier B.V. All rights reserved.

A general model to explore complex dominance patterns in plant sporophytic self-incompatibility systems.

PubMed

Billiard, Sylvain; Castric, Vincent; Vekemans, Xavier

2007-03-01

We developed a general model of sporophytic self-incompatibility under negative frequency-dependent selection allowing complex patterns of dominance among alleles. We used this model deterministically to investigate the effects on equilibrium allelic frequencies of the number of dominance classes, the number of alleles per dominance class, the asymmetry in dominance expression between pollen and pistil, and whether selection acts on male fitness only or both on male and on female fitnesses. We show that the so-called "recessive effect" occurs under a wide variety of situations. We found emerging properties of finite population models with several alleles per dominance class such as that higher numbers of alleles are maintained in more dominant classes and that the number of dominance classes can evolve. We also investigated the occurrence of homozygous genotypes and found that substantial proportions of those can occur for the most recessive alleles. We used the model for two species with complex dominance patterns to test whether allelic frequencies in natural populations are in agreement with the distribution predicted by our model. We suggest that the model can be used to test explicitly for additional, allele-specific, selective forces.

X-ray peak broadening analysis of AA 6061{sub 100-x} - x wt.% Al{sub 2}O{sub 3} nanocomposite prepared by mechanical alloying

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

Sivasankaran, S., E-mail: sivasankarangs1979@gmail.com; Sivaprasad, K., E-mail: ksp@nitt.edu; Narayanasamy, R., E-mail: narayan@nitt.edu

2011-07-15

Nanocrystalline AA 6061 alloy reinforced with alumina (0, 4, 8, and 12 wt.%) in amorphized state composite powder was synthesized by mechanical alloying and consolidated by conventional powder metallurgy route. The as-milled and as-sintered (573 K and 673 K) nanocomposites were characterized by X-ray diffraction (XRD) and transmission electron microscopy (TEM). The peaks corresponding to fine alumina was not observed by XRD patterns due to amorphization. Using high-resolution transmission electron microscope, it is confirmed that the presence of amorphized alumina observed in Al lattice fringes. The crystallite size, lattice strain, deformation stress, and strain energy density of AA 6061 matrixmore » were determined precisely from the first five most intensive reflection of XRD using simple Williamson-Hall models; uniform deformation model, uniform stress deformation model, and uniform energy density deformation model. Among the developed models, uniform energy density deformation model was observed to be the best fit and realistic model for mechanically alloyed powders. This model evidenced the more anisotropic nature of the ball milled powders. The XRD peaks of as-milled powder samples demonstrated a considerable broadening with percentage of reinforcement due to grain refinement and lattice distortions during same milling time (40 h). The as-sintered (673 K) unreinforced AA 6061 matrix crystallite size from well fitted uniform energy density deformation model was 98 nm. The as-milled and as-sintered (673 K) nanocrystallite matrix sizes for 12 wt.% Al{sub 2}O{sub 3} well fitted by uniform energy density deformation model were 38 nm and 77 nm respectively, which indicate that the fine Al{sub 2}O{sub 3} pinned the matrix grain boundary and prevented the grain growth during sintering. Finally, the lattice parameter of Al matrix in as-milled and as-sintered conditions was also investigated in this paper. Research highlights: {yields} Integral breadth methods using various Williamson-Hall models were investigated for line profile analysis. {yields} Uniform energy density deformation model is observed to the best realistic model. {yields} The present analysis is used for understanding the stress and the strain present in the nanocomposites.« less

Soil Moisture (SMAP) and Vapor Pressure Deficit Controls on Evaporative Fraction over the Continental U.S.

NASA Astrophysics Data System (ADS)

Salvucci, G.; Rigden, A. J.; Gianotti, D.; Entekhabi, D.

2017-12-01

We analyze the control over evapotranspiration (ET) imposed by soil moisture limitations and stomatal closure due to vapor pressure deficit (VPD) across the United States using estimates of satellite-derived soil moisture from SMAP and a meteorological, data-driven ET estimate over a two year period at over 1000 locations. The ET data are developed independent of soil moisture using the emergent relationship between the diurnal cycle of the relative humidity profile and ET based on ETRHEQ (Salvucci and Gentine (2013), PNAS, 110(16): 6287-6291, Rigden and Salvucci, 2015, WRR, 51(4): 2951-2973; Rigden and Salvucci, 2017, GCB, 23(3) 1140-1151). The key advantage of using this approach to estimate ET is that no measurements of surface limiting factors (soil moisture, leaf area, canopy conductance) are required; instead, ET is estimated from only meteorological data. The combination of these two independent datasets allows for a unique spatial analysis of the control on ET imposed by the availability of soil moisture vs. VPD. Spatial patterns of limitations are inferred by fitting the ETRHEQ-inferred surface conductance to a weighted sum of a Jarvis type stomatal conductance model and bare soil evaporation conductance model, with separate moisture-dependent evaporation efficiency relations for bare soil and vegetation. Spatial patterns are visualized by mapping the optimal curve fitting coefficients and by conducting sensitivity analyses of the resulting fitted model across the Unites States. Results indicate regional variations in rate-limiting factors, and suggest that in some areas the VPD effect on stomatal closure is strong enough to induce a decrease in ET under projected climate change, despite an increase in atmospheric drying (and thus evaporative demand).

Confirmatory factor analysis of posttraumatic stress symptoms in sexually harassed women.

PubMed

Palmieri, Patrick A; Fitzgerald, Louise F

2005-12-01

Posttraumatic stress disorder (PTSD) factor analytic research to date has not provided a clear consensus on the structure of posttraumatic stress symptoms. Seven hypothesized factor structures were evaluated using confirmatory factor analysis of the Posttraumatic Stress Disorder Checklist, a paper-and-pencil measure of posttraumatic stress symptom severity, in a sample of 1,218 women who experienced a broad range of workplace sexual harassment. The model specifying correlated re-experiencing, effortful avoidance, emotional numbing, and hyperarousal factors provided the best fit to the data. Virtually no support was obtained for the Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV; American Psychiatric Association, 1994) three-factor model of re-experiencing, avoidance, and hyperarousal factors. Different patterns of correlations with external variables were found for the avoidance and emotional numbing factors, providing further validation of the supported model.

Damage classification and estimation in experimental structures using time series analysis and pattern recognition

NASA Astrophysics Data System (ADS)

de Lautour, Oliver R.; Omenzetter, Piotr

2010-07-01

Developed for studying long sequences of regularly sampled data, time series analysis methods are being increasingly investigated for the use of Structural Health Monitoring (SHM). In this research, Autoregressive (AR) models were used to fit the acceleration time histories obtained from two experimental structures: a 3-storey bookshelf structure and the ASCE Phase II Experimental SHM Benchmark Structure, in undamaged and limited number of damaged states. The coefficients of the AR models were considered to be damage-sensitive features and used as input into an Artificial Neural Network (ANN). The ANN was trained to classify damage cases or estimate remaining structural stiffness. The results showed that the combination of AR models and ANNs are efficient tools for damage classification and estimation, and perform well using small number of damage-sensitive features and limited sensors.

Understanding interannual, decadal level variability in paralytic shellfish poisoning toxicity in the Gulf of Maine: The HAB Index

NASA Astrophysics Data System (ADS)

Anderson, Donald M.; Couture, Darcie A.; Kleindinst, Judith L.; Keafer, Bruce A.; McGillicuddy, Dennis J., Jr.; Martin, Jennifer L.; Richlen, Mindy L.; Hickey, J. Michael; Solow, Andrew R.

2014-05-01

A major goal in harmful algal bloom (HAB) research has been to identify mechanisms underlying interannual variability in bloom magnitude and impact. Here the focus is on variability in Alexandrium fundyense blooms and paralytic shellfish poisoning (PSP) toxicity in Maine, USA, over 34 years (1978-2011). The Maine coastline was divided into two regions - eastern and western Maine, and within those two regions, three measures of PSP toxicity (the percent of stations showing detectable toxicity over the year, the cumulative amount of toxicity per station measured in all shellfish (mussel) samples during that year, and the duration of measurable toxicity) were examined for each year in the time series. These metrics were combined into a simple HAB Index that provides a single measure of annual toxin severity across each region. The three toxin metrics, as well as the HAB Index that integrates them, reveal significant variability in overall toxicity between individual years as well as long-term, decadal patterns or regimes. Based on different conceptual models of the system, we considered three trend formulations to characterize the long-term patterns in the Index - a three-phase (mean-shift) model, a linear two-phase model, and a pulse-decline model. The first represents a “regime shift” or multiple equilibria formulation as might occur with alternating periods of sustained high and low cyst abundance or favorable and unfavorable growth conditions, the second depicts a scenario of more gradual transitions in cyst abundance or growth conditions of vegetative cells, and the third characterizes a ”sawtooth” pattern in which upward shifts in toxicity are associated with major cyst recruitment events, followed by a gradual but continuous decline until the next pulse. The fitted models were compared using both residual sum of squares and Akaike's Information Criterion. There were some differences between model fits, but none consistently gave a better fit than the others. This statistical underpinning can guide efforts to identify physical and/or biological mechanisms underlying the patterns revealed by the HAB Index. Although A. fundyense cyst survey data (limited to 9 years) do not span the entire interval of the shellfish toxicity records, this analysis leads us to hypothesize that major changes in the abundance of A. fundyense cysts may be a primary factor contributing to the decadal trends in shellfish toxicity in this region. The HAB Index approach taken here is simple but represents a novel and potentially useful tool for resource managers in many areas of the world subject to toxic HABs.

Understanding interannual, decadal level variability in paralytic shellfish poisoning toxicity in the Gulf of Maine: the HAB Index

PubMed Central

Anderson, Donald M.; Couture, Darcie A.; Kleindinst, Judith L.; Keafer, Bruce A.; McGillicuddy, Dennis J.; Martin, Jennifer L.; Richlen, Mindy L.; Hickey, J. Michael; Solow, Andrew R.

2013-01-01

A major goal in harmful algal bloom (HAB) research has been to identify mechanisms underlying interannual variability in bloom magnitude and impact. Here the focus is on variability in Alexandrium fundyense blooms and paralytic shellfish poisoning (PSP) toxicity in Maine, USA, over 34 years (1978 – 2011). The Maine coastline was divided into two regions -eastern and western Maine, and within those two regions, three measures of PSP toxicity (the percent of stations showing detectable toxicity over the year, the cumulative amount of toxicity per station measured in all shellfish (mussel) samples during that year, and the duration of measurable toxicity) were examined for each year in the time series. These metrics were combined into a simple HAB Index that provides a single measure of annual toxin severity across each region. The three toxin metrics, as well as the HAB Index that integrates them, reveal significant variability in overall toxicity between individual years as well as long-term, decadal patterns or regimes. Based on different conceptual models of the system, we considered three trend formulations to characterize the long-term patterns in the Index – a three-phase (mean-shift) model, a linear two-phase model, and a pulse-decline model. The first represents a “regime shift” or multiple equilibria formulation as might occur with alternating periods of sustained high and low cyst abundance or favorable and unfavorable growth conditions, the second depicts a scenario of more gradual transitions in cyst abundance or growth conditions of vegetative cells, and the third characterizes a ”sawtooth” pattern in which upward shifts in toxicity are associated with major cyst recruitment events, followed by a gradual but continuous decline until the next pulse. The fitted models were compared using both residual sum of squares and Akaike's Information Criterion. There were some differences between model fits, but none consistently gave a better fit than the others. This statistical underpinning can guide efforts to identify physical and/or biological mechanisms underlying the patterns revealed by the HAB Index. Although A. fundyense cyst survey data (limited to 9 years) do not span the entire interval of the shellfish toxicity records, this analysis leads us to hypothesize that major changes in the abundance of A. fundyense cysts may be a primary factor contributing to the decadal trends in shellfish toxicity in this region. The HAB Index approach taken here is simple but represents a novel and potentially useful tool for resource managers in many areas of the world subject to toxic HABs. PMID:24948849

Patterns of functional vision loss in glaucoma determined with archetypal analysis

PubMed Central

Elze, Tobias; Pasquale, Louis R.; Shen, Lucy Q.; Chen, Teresa C.; Wiggs, Janey L.; Bex, Peter J.

2015-01-01

Glaucoma is an optic neuropathy accompanied by vision loss which can be mapped by visual field (VF) testing revealing characteristic patterns related to the retinal nerve fibre layer anatomy. While detailed knowledge about these patterns is important to understand the anatomic and genetic aspects of glaucoma, current classification schemes are typically predominantly derived qualitatively. Here, we classify glaucomatous vision loss quantitatively by statistically learning prototypical patterns on the convex hull of the data space. In contrast to component-based approaches, this method emphasizes distinct aspects of the data and provides patterns that are easier to interpret for clinicians. Based on 13 231 reliable Humphrey VFs from a large clinical glaucoma practice, we identify an optimal solution with 17 glaucomatous vision loss prototypes which fit well with previously described qualitative patterns from a large clinical study. We illustrate relations of our patterns to retinal structure by a previously developed mathematical model. In contrast to the qualitative clinical approaches, our results can serve as a framework to quantify the various subtypes of glaucomatous visual field loss. PMID:25505132

Multifractality of laser beam spatial intensity in a turbulent medium

NASA Astrophysics Data System (ADS)

Barille, Régis; Lapenna, Paolo

2006-05-01

We present the results of a laser beam passing through a turbulent medium. First we measure the geometric parameters and the spatial coherence of the beam as a function of wind velocities. A multifractal detrended fluctuation analysis algorithm is applied to determine the multifractal scaling behavior of the intensity patterns. The measurements are fitted with models used in the analysis of river runoff records. We show the surprising result that the multifractality decreases when the spatial coherence of the laser is decreased. Universal scaling properties could be applied to the spatial characterization of a laser propagating in a turbulent medium or random medium.

Fitness trade-offs of group formation and movement by Thomson's gazelles in the Serengeti ecosystem.

PubMed

Fryxell, John M; Berdahl, Andrew M

2018-05-19

Collective behaviours contributing to patterns of group formation and coordinated movement are common across many ecosystems and taxa. Their ubiquity is presumably due to altering interactions between individuals and their predators, resources and physical environment in ways that enhance individual fitness. On the other hand, fitness costs are also often associated with group formation. Modifications to these interactions have the potential to dramatically impact population-level processes, such as trophic interactions or patterns of space use in relation to abiotic environmental variation. In a wide variety of empirical systems and models, collective behaviour has been shown to enhance access to ephemeral patches of resources, reduce the risk of predation and reduce vulnerability to environmental fluctuation. Evolution of collective behaviour should accordingly depend on the advantages of collective behaviour weighed against the costs experienced at the individual level. As an illustrative case study, we consider the potential trade-offs on Malthusian fitness associated with patterns of group formation and movement by migratory Thomson's gazelles in the Serengeti ecosystem.This article is part of the theme issue 'Collective movement ecology'. © 2018 The Authors.

The spatial impact of neighbouring on the exports activities of COMESA countries by using spatial panel models

NASA Astrophysics Data System (ADS)

Hamzalouh, L.; Ismail, M. T.; Rahman, R. A.

2017-09-01

In this paper, spatial panel models were used and the method for selecting the best model amongst the spatial fixed effects model and the spatial random effects model to estimate the fitting model by using the robust Hausman test for analysis of the exports pattern of the Common Market for Eastern and Southern African (COMESA) countries. And examine the effects of the interactions of the economic statistic of explanatory variables on the exports of the COMESA. Results indicated that the spatial Durbin model with fixed effects specification should be tested and considered in most cases of this study. After that, the direct and indirect effects among COMESA regions were assessed, and the role of indirect spatial effects in estimating exports was empirically demonstrated. Regarding originality and research value, and to the best of the authors’ knowledge, this is the first attempt to examine exports between COMESA and its member countries through spatial panel models using XSMLE, which is a new command for spatial analysis using STATA.

An evaluation of the structural validity of the shoulder pain and disability index (SPADI) using the Rasch model.

PubMed

Jerosch-Herold, Christina; Chester, Rachel; Shepstone, Lee; Vincent, Joshua I; MacDermid, Joy C

2018-02-01

The shoulder pain and disability index (SPADI) has been extensively evaluated for its psychometric properties using classical test theory (CTT). The purpose of this study was to evaluate its structural validity using Rasch model analysis. Responses to the SPADI from 1030 patients referred for physiotherapy with shoulder pain and enrolled in a prospective cohort study were available for Rasch model analysis. Overall fit, individual person and item fit, response format, dependence, unidimensionality, targeting, reliability and differential item functioning (DIF) were examined. The SPADI pain subscale initially demonstrated a misfit due to DIF by age and gender. After iterative analysis it showed good fit to the Rasch model with acceptable targeting and unidimensionality (overall fit Chi-square statistic 57.2, p = 0.1; mean item fit residual 0.19 (1.5) and mean person fit residual 0.44 (1.1); person separation index (PSI) of 0.83. The disability subscale however shows significant misfit due to uniform DIF even after iterative analyses were used to explore different solutions to the sources of misfit (overall fit (Chi-square statistic 57.2, p = 0.1); mean item fit residual 0.54 (1.26) and mean person fit residual 0.38 (1.0); PSI 0.84). Rasch Model analysis of the SPADI has identified some strengths and limitations not previously observed using CTT methods. The SPADI should be treated as two separate subscales. The SPADI is a widely used outcome measure in clinical practice and research; however, the scores derived from it must be interpreted with caution. The pain subscale fits the Rasch model expectations well. The disability subscale does not fit the Rasch model and its current format does not meet the criteria for true interval-level measurement required for use as a primary endpoint in clinical trials. Clinicians should therefore exercise caution when interpreting score changes on the disability subscale and attempt to compare their scores to age- and sex-stratified data.

Validation of the Spanish version of the Amsterdam Preoperative Anxiety and Information Scale (APAIS).

PubMed

Vergara-Romero, Manuel; Morales-Asencio, José Miguel; Morales-Fernández, Angelines; Canca-Sanchez, Jose Carlos; Rivas-Ruiz, Francisco; Reinaldo-Lapuerta, Jose Antonio

2017-06-07

Preoperative anxiety is a frequent and challenging problem with deleterious effects on the development of surgical procedures and postoperative outcomes. To prevent and treat preoperative anxiety effectively, the level of anxiety of patients needs to be assessed through valid and reliable measuring instruments. One such measurement tool is the Amsterdam Preoperative Anxiety and Information Scale (APAIS), of which a Spanish version has not been validated yet. To perform a Spanish cultural adaptation and empirical validation of the APAIS for assessing preoperative anxiety in the Spanish population. A two-step forward/back translation of the APAIS scale was performed to ensure a reliable Spanish cultural adaptation. The final Spanish version of the APAIS questionnaire was administered to 529 patients between the ages of 18 to 70 undergoing elective surgery at hospitals of the Agencia Sanitaria Costa del Sol (Spain). Cronbach's alpha, homogeneity index, intra-class correlation coefficient, and confirmatory factor analysis were calculated to assess internal consistency and criteria and construct validity. Confirmatory factor analysis showed that a one-factor model was better fitted than a two-factor model, with good fitting patterns (root mean square error of approximation: 0.05, normed-fit index: 0.99, goodness-of-fit statistic: 0.99). The questionnaire showed high internal consistency (Cronbach's alpha: 0.84) and a good correlation with the Goldberg Anxiety Scale (CCI: 0.62 (95% CI: 0.55 to 0.68). The Spanish version of the APAIS is a valid and reliable preoperative anxiety measurement tool and shows psychometric properties similar to those obtained by similar previous studies.

Search query data to monitor interest in behavior change: application for public health.

PubMed

Carr, Lucas J; Dunsiger, Shira I

2012-01-01

There is a need for effective interventions and policies that target the leading preventable causes of death in the U.S. (e.g., smoking, overweight/obesity, physical inactivity). Such efforts could be aided by the use of publicly available, real-time search query data that illustrate times and locations of high and low public interest in behaviors related to preventable causes of death. This study explored patterns of search query activity for the terms 'weight', 'diet', 'fitness', and 'smoking' using Google Insights for Search. Search activity for 'weight', 'diet', 'fitness', and 'smoking' conducted within the United States via Google between January 4(th), 2004 (first date data was available) and November 28(th), 2011 (date of data download and analysis) were analyzed. Using a generalized linear model, we explored the effects of time (month) on mean relative search volume for all four terms. Models suggest a significant effect of month on mean search volume for all four terms. Search activity for all four terms was highest in January with observable declines throughout the remainder of the year. These findings demonstrate discernable temporal patterns of search activity for four areas of behavior change. These findings could be used to inform the timing, location and messaging of interventions, campaigns and policies targeting these behaviors.

Snijders's correction of Infit and Outfit indexes with estimated ability level: an analysis with the Rasch model.

PubMed

Magis, David; Beland, Sebastien; Raiche, Gilles

2014-01-01

The Infit mean square W and the Outfit mean square U are commonly used person fit indexes under Rasch measurement. However, they suffer from two major weaknesses. First, their asymptotic distribution is usually derived by assuming that the true ability levels are known. Second, such distributions are even not clearly stated for indexes U and W. Both issues can seriously affect the selection of an appropriate cut-score for person fit identification. Snijders (2001) proposed a general approach to correct some person fit indexes when specific ability estimators are used. The purpose of this paper is to adapt this approach to U and W indexes. First, a brief sketch of the methodology and its application to U and W is proposed. Then, the corrected indexes are compared to their classical versions through a simulation study. The suggested correction yields controlled Type I errors against both conservatism and inflation, while the power to detect specific misfitting response patterns gets significantly increased.

Controlled comparison of species- and community-level models across novel climates and communities

PubMed Central

Maguire, Kaitlin C.; Blois, Jessica L.; Fitzpatrick, Matthew C.; Williams, John W.; Ferrier, Simon; Lorenz, David J.

2016-01-01

Species distribution models (SDMs) assume species exist in isolation and do not influence one another's distributions, thus potentially limiting their ability to predict biodiversity patterns. Community-level models (CLMs) capitalize on species co-occurrences to fit shared environmental responses of species and communities, and therefore may result in more robust and transferable models. Here, we conduct a controlled comparison of five paired SDMs and CLMs across changing climates, using palaeoclimatic simulations and fossil-pollen records of eastern North America for the past 21 000 years. Both SDMs and CLMs performed poorly when projected to time periods that are temporally distant and climatically dissimilar from those in which they were fit; however, CLMs generally outperformed SDMs in these instances, especially when models were fit with sparse calibration datasets. Additionally, CLMs did not over-fit training data, unlike SDMs. The expected emergence of novel climates presents a major forecasting challenge for all models, but CLMs may better rise to this challenge by borrowing information from co-occurring taxa. PMID:26962143

A gravity model for the spread of a pollinator-borne plant pathogen.

PubMed

Ferrari, Matthew J; Bjørnstad, Ottar N; Partain, Jessica L; Antonovics, Janis

2006-09-01

Many pathogens of plants are transmitted by arthropod vectors whose movement between individual hosts is influenced by foraging behavior. Insect foraging has been shown to depend on both the quality of hosts and the distances between hosts. Given the spatial distribution of host plants and individual variation in quality, vector foraging patterns may therefore produce predictable variation in exposure to pathogens. We develop a "gravity" model to describe the spatial spread of a vector-borne plant pathogen from underlying models of insect foraging in response to host quality using the pollinator-borne smut fungus Microbotryum violaceum as a case study. We fit the model to spatially explicit time series of M. violaceum transmission in replicate experimental plots of the white campion Silene latifolia. The gravity model provides a better fit than a mean field model or a model with only distance-dependent transmission. The results highlight the importance of active vector foraging in generating spatial patterns of disease incidence and for pathogen-mediated selection for floral traits.

Assessing prescription drug abuse using functional principal component analysis (FPCA) of wastewater data.

PubMed

Salvatore, Stefania; Røislien, Jo; Baz-Lomba, Jose A; Bramness, Jørgen G

2017-03-01

Wastewater-based epidemiology is an alternative method for estimating the collective drug use in a community. We applied functional data analysis, a statistical framework developed for analysing curve data, to investigate weekly temporal patterns in wastewater measurements of three prescription drugs with known abuse potential: methadone, oxazepam and methylphenidate, comparing them to positive and negative control drugs. Sewage samples were collected in February 2014 from a wastewater treatment plant in Oslo, Norway. The weekly pattern of each drug was extracted by fitting of generalized additive models, using trigonometric functions to model the cyclic behaviour. From the weekly component, the main temporal features were then extracted using functional principal component analysis. Results are presented through the functional principal components (FPCs) and corresponding FPC scores. Clinically, the most important weekly feature of the wastewater-based epidemiology data was the second FPC, representing the difference between average midweek level and a peak during the weekend, representing possible recreational use of a drug in the weekend. Estimated scores on this FPC indicated recreational use of methylphenidate, with a high weekend peak, but not for methadone and oxazepam. The functional principal component analysis uncovered clinically important temporal features of the weekly patterns of the use of prescription drugs detected from wastewater analysis. This may be used as a post-marketing surveillance method to monitor prescription drugs with abuse potential. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

If the skull fits: magnetic resonance imaging and microcomputed tomography for combined analysis of brain and skull phenotypes in the mouse

PubMed Central

Blank, Marissa C.; Roman, Brian B.; Henkelman, R. Mark; Millen, Kathleen J.

2012-01-01

The mammalian brain and skull develop concurrently in a coordinated manner, consistently producing a brain and skull that fit tightly together. It is common that abnormalities in one are associated with related abnormalities in the other. However, this is not always the case. A complete characterization of the relationship between brain and skull phenotypes is necessary to understand the mechanisms that cause them to be coordinated or divergent and to provide perspective on the potential diagnostic or prognostic significance of brain and skull phenotypes. We demonstrate the combined use of magnetic resonance imaging and microcomputed tomography for analysis of brain and skull phenotypes in the mouse. Co-registration of brain and skull images allows comparison of the relationship between phenotypes in the brain and those in the skull. We observe a close fit between the brain and skull of two genetic mouse models that both show abnormal brain and skull phenotypes. Application of these three-dimensional image analyses in a broader range of mouse mutants will provide a map of the relationships between brain and skull phenotypes generally and allow characterization of patterns of similarities and differences. PMID:22947655

Neutrality and Robustness in Evo-Devo: Emergence of Lateral Inhibition

PubMed Central

Munteanu, Andreea; Solé, Ricard V.

2008-01-01

Embryonic development is defined by the hierarchical dynamical process that translates genetic information (genotype) into a spatial gene expression pattern (phenotype) providing the positional information for the correct unfolding of the organism. The nature and evolutionary implications of genotype–phenotype mapping still remain key topics in evolutionary developmental biology (evo-devo). We have explored here issues of neutrality, robustness, and diversity in evo-devo by means of a simple model of gene regulatory networks. The small size of the system allowed an exhaustive analysis of the entire fitness landscape and the extent of its neutrality. This analysis shows that evolution leads to a class of robust genetic networks with an expression pattern characteristic of lateral inhibition. This class is a repertoire of distinct implementations of this key developmental process, the diversity of which provides valuable clues about its underlying causal principles. PMID:19023404

[How to fit and interpret multilevel models using SPSS].

PubMed

Pardo, Antonio; Ruiz, Miguel A; San Martín, Rafael

2007-05-01

Hierarchic or multilevel models are used to analyse data when cases belong to known groups and sample units are selected both from the individual level and from the group level. In this work, the multilevel models most commonly discussed in the statistic literature are described, explaining how to fit these models using the SPSS program (any version as of the 11 th ) and how to interpret the outcomes of the analysis. Five particular models are described, fitted, and interpreted: (1) one-way analysis of variance with random effects, (2) regression analysis with means-as-outcomes, (3) one-way analysis of covariance with random effects, (4) regression analysis with random coefficients, and (5) regression analysis with means- and slopes-as-outcomes. All models are explained, trying to make them understandable to researchers in health and behaviour sciences.

A lattice model for influenza spreading.

PubMed

Liccardo, Antonella; Fierro, Annalisa

2013-01-01

We construct a stochastic SIR model for influenza spreading on a D-dimensional lattice, which represents the dynamic contact network of individuals. An age distributed population is placed on the lattice and moves on it. The displacement from a site to a nearest neighbor empty site, allows individuals to change the number and identities of their contacts. The dynamics on the lattice is governed by an attractive interaction between individuals belonging to the same age-class. The parameters, which regulate the pattern dynamics, are fixed fitting the data on the age-dependent daily contact numbers, furnished by the Polymod survey. A simple SIR transmission model with a nearest neighbors interaction and some very basic adaptive mobility restrictions complete the model. The model is validated against the age-distributed Italian epidemiological data for the influenza A(H1N1) during the [Formula: see text] season, with sensible predictions for the epidemiological parameters. For an appropriate topology of the lattice, we find that, whenever the accordance between the contact patterns of the model and the Polymod data is satisfactory, there is a good agreement between the numerical and the experimental epidemiological data. This result shows how rich is the information encoded in the average contact patterns of individuals, with respect to the analysis of the epidemic spreading of an infectious disease.

A new metric of inclusive fitness predicts the human mortality profile.

PubMed

Newman, Saul J; Easteal, Simon

2015-01-01

Biological species have evolved characteristic patterns of age-specific mortality across their life spans. If these mortality profiles are shaped by natural selection they should reflect underlying variation in the fitness effect of mortality with age. Direct fitness models, however, do not accurately predict the mortality profiles of many species. For several species, including humans, mortality rates vary considerably before and after reproductive ages, during life-stages when no variation in direct fitness is possible. Variation in mortality rates at these ages may reflect indirect effects of natural selection acting through kin. To test this possibility we developed a new two-variable measure of inclusive fitness, which we term the extended genomic output or EGO. Using EGO, we estimate the inclusive fitness effect of mortality at different ages in a small hunter-gatherer population with a typical human mortality profile. EGO in this population predicts 90% of the variation in age-specific mortality. This result represents the first empirical measurement of inclusive fitness of a trait in any species. It shows that the pattern of human survival can largely be explained by variation in the inclusive fitness cost of mortality at different ages. More generally, our approach can be used to estimate the inclusive fitness of any trait or genotype from population data on birth dates and relatedness.

Using the PLUM procedure of SPSS to fit unequal variance and generalized signal detection models.

PubMed

DeCarlo, Lawrence T

2003-02-01

The recent addition of aprocedure in SPSS for the analysis of ordinal regression models offers a simple means for researchers to fit the unequal variance normal signal detection model and other extended signal detection models. The present article shows how to implement the analysis and how to interpret the SPSS output. Examples of fitting the unequal variance normal model and other generalized signal detection models are given. The approach offers a convenient means for applying signal detection theory to a variety of research.

Usability and potential of geostatistics for spatial discrimination of multiple sclerosis lesion patterns.

PubMed

Marschallinger, Robert; Golaszewski, Stefan M; Kunz, Alexander B; Kronbichler, Martin; Ladurner, Gunther; Hofmann, Peter; Trinka, Eugen; McCoy, Mark; Kraus, Jörg

2014-01-01

In multiple sclerosis (MS) the individual disease courses are very heterogeneous among patients and biomarkers for setting the diagnosis and the estimation of the prognosis for individual patients would be very helpful. For this purpose, we are developing a multidisciplinary method and workflow for the quantitative, spatial, and spatiotemporal analysis and characterization of MS lesion patterns from MRI with geostatistics. We worked on a small data set involving three synthetic and three real-world MS lesion patterns, covering a wide range of possible MS lesion configurations. After brain normalization, MS lesions were extracted and the resulting binary 3-dimensional models of MS lesion patterns were subject to geostatistical indicator variography in three orthogonal directions. By applying geostatistical indicator variography, we were able to describe the 3-dimensional spatial structure of MS lesion patterns in a standardized manner. Fitting a model function to the empirical variograms, spatial characteristics of the MS lesion patterns could be expressed and quantified by two parameters. An orthogonal plot of these parameters enabled a well-arranged comparison of the involved MS lesion patterns. This method in development is a promising candidate to complement standard image-based statistics by incorporating spatial quantification. The work flow is generic and not limited to analyzing MS lesion patterns. It can be completely automated for the screening of radiological archives. Copyright © 2013 by the American Society of Neuroimaging.

Spatial self-organization in hybrid models of multicellular adhesion

NASA Astrophysics Data System (ADS)

Bonforti, Adriano; Duran-Nebreda, Salva; Montañez, Raúl; Solé, Ricard

2016-10-01

Spatial self-organization emerges in distributed systems exhibiting local interactions when nonlinearities and the appropriate propagation of signals are at work. These kinds of phenomena can be modeled with different frameworks, typically cellular automata or reaction-diffusion systems. A different class of dynamical processes involves the correlated movement of agents over space, which can be mediated through chemotactic movement or minimization of cell-cell interaction energy. A classic example of the latter is given by the formation of spatially segregated assemblies when cells display differential adhesion. Here, we consider a new class of dynamical models, involving cell adhesion among two stochastically exchangeable cell states as a minimal model capable of exhibiting well-defined, ordered spatial patterns. Our results suggest that a whole space of pattern-forming rules is hosted by the combination of physical differential adhesion and the value of probabilities modulating cell phenotypic switching, showing that Turing-like patterns can be obtained without resorting to reaction-diffusion processes. If the model is expanded allowing cells to proliferate and die in an environment where diffusible nutrient and toxic waste are at play, different phases are observed, characterized by regularly spaced patterns. The analysis of the parameter space reveals that certain phases reach higher population levels than other modes of organization. A detailed exploration of the mean-field theory is also presented. Finally, we let populations of cells with different adhesion matrices compete for reproduction, showing that, in our model, structural organization can improve the fitness of a given cell population. The implications of these results for ecological and evolutionary models of pattern formation and the emergence of multicellularity are outlined.

Links between physical fitness and cardiovascular reactivity and recovery to psychological stressors: A meta-analysis.

PubMed

Forcier, Kathleen; Stroud, Laura R; Papandonatos, George D; Hitsman, Brian; Reiches, Meredith; Krishnamoorthy, Jenelle; Niaura, Raymond

2006-11-01

A meta-analysis of published studies with adult human participants was conducted to evaluate whether physical fitness attenuates cardiovascular reactivity and improves recovery from acute psychological stressors. Thirty-three studies met selection criteria; 18 were included in recovery analyses. Effect sizes and moderator influences were calculated by using meta-analysis software. A fixed effects model was fit initially; however, between-studies heterogeneity could not be explained even after inclusion of moderators. Therefore, to account for residual heterogeneity, a random effects model was estimated. Under this model, fit individuals showed significantly attenuated heart rate and systolic blood pressure reactivity and a trend toward attenuated diastolic blood pressure reactivity. Fit individuals also showed faster heart rate recovery, but there were no significant differences in systolic blood pressure or diastolic blood pressure recovery. No significant moderators emerged. Results have important implications for elucidating mechanisms underlying effects of fitness on cardiovascular disease and suggest that fitness may be an important confound in studies of stress reactivity. Copyright 2006 APA, all rights reserved.

Domain Engineered Magnetoelectric Thin Films for High Sensitivity Resonant Magnetic Field Sensors

DTIC Science & Technology

2012-02-28

texture E analysis w cated by poo re accounted n measurem 8 sol-gel samp d PZT sol-g as utilized t r fit between in the mo ent spot). les shown i el...nsformer str nted by aero ure. ure 34: Un were grow as varied in D) as show texturing in . D pattern of the films d ucture. Figu sol jet depo ipoled PZT ...the detailed characterization was the development of prediction models for texturing of PZT sol-gel thin films, an understanding of the analytical

PREdator: a python based GUI for data analysis, evaluation and fitting

PubMed Central

2014-01-01

The analysis of a series of experimental data is an essential procedure in virtually every field of research. The information contained in the data is extracted by fitting the experimental data to a mathematical model. The type of the mathematical model (linear, exponential, logarithmic, etc.) reflects the physical laws that underlie the experimental data. Here, we aim to provide a readily accessible, user-friendly python script for data analysis, evaluation and fitting. PREdator is presented at the example of NMR paramagnetic relaxation enhancement analysis.

Environmental Factors Can Influence Mitochondrial Inheritance in the Saccharomyces Yeast Hybrids.

PubMed

Hsu, Yu-Yi; Chou, Jui-Yu

2017-01-01

Mitochondria play a critical role in the generation of metabolic energy and are crucial for eukaryotic cell survival and proliferation. In most sexual eukaryotes, mitochondrial DNA (mtDNA) is inherited from only one parent in non-Mendelian inheritance in contrast to the inheritance of nuclear DNA. The model organism Saccharomyces cerevisiae is commonly used to study mitochondrial biology. It has two mating types: MATa and MATα. Previous studies have suggested that the mtDNA inheritance patterns in hybrid diploid cells depend on the genetic background of parental strains. However, the underlying mechanisms remain unclear. To elucidate the mechanisms, we examined the effects of environmental factors on the mtDNA inheritance patterns in hybrids obtained by crossing S. cerevisiae with its close relative S. paradoxus. The results demonstrated that environmental factors can influence mtDNA transmission in hybrid diploids, and that the inheritance patterns are strain dependent. The fitness competition assay results showed that the fitness differences can explain the mtDNA inheritance patterns under specific conditions. However, in this study, we found that fitness differences cannot fully be explained by mitochondrial activity in hybrids under stress conditions.

Assessing item fit for unidimensional item response theory models using residuals from estimated item response functions.

PubMed

Haberman, Shelby J; Sinharay, Sandip; Chon, Kyong Hee

2013-07-01

Residual analysis (e.g. Hambleton & Swaminathan, Item response theory: principles and applications, Kluwer Academic, Boston, 1985; Hambleton, Swaminathan, & Rogers, Fundamentals of item response theory, Sage, Newbury Park, 1991) is a popular method to assess fit of item response theory (IRT) models. We suggest a form of residual analysis that may be applied to assess item fit for unidimensional IRT models. The residual analysis consists of a comparison of the maximum-likelihood estimate of the item characteristic curve with an alternative ratio estimate of the item characteristic curve. The large sample distribution of the residual is proved to be standardized normal when the IRT model fits the data. We compare the performance of our suggested residual to the standardized residual of Hambleton et al. (Fundamentals of item response theory, Sage, Newbury Park, 1991) in a detailed simulation study. We then calculate our suggested residuals using data from an operational test. The residuals appear to be useful in assessing the item fit for unidimensional IRT models.

Descriptive analysis of the type and design of contact lenses fitted according to keratoconus severity and morphology.

PubMed

Lunardi, Letícia Helena; Arroyo, Danielle; Andrade Sobrinho, Marcelo Vicente de; Lipener, César; Rosa, Juliana Maria da Silva

2016-04-01

Keratoconus is characterized by bilateral asymmetrical corneal ectasia that leads to inferior stromal thinning and corneal protrusion. There is currently a lack of consensus regarding the most efficacious method for fitting contact lenses in patients with keratoconus, given the various topographical patterns and evolution grades observed in affected populations. The purpose of the present study was to evaluate the association between keratoconus evolution grade and topography pattern and the type and design of fitted contact lens. We performed a retrospective analysis of contact lenses fitted in a total of 185 patients with keratoconus (325 eyes). Keratoconus was classified as either grade I, II, III, or IV based on keratometry and cone morphology (nipple, oval, globus, or indeterminate) results. A total of 325 eyes were evaluated in the present study. Of the 62 eyes classified as grade I, 66.1% were fitted with monocurve contact lenses. Of the 162 eyes classified as grade I and II, 51%, 30%, and 19% were fitted with adapted monocurve rigid gas-permeable contact lenses (RGPCL), bicurve lenses, and others lens types, respectively. Bicurve lenses were fitted in 52.1% and 62.2% of eyes classified as grade III and IV, respectively. Of the eyes classified as grade III and IV, monocurve and bicurve RGPCL were fitted in 26% and 55%, respectively. In eyes with oval keratoconus, 45%, 35%, and 20% were fitted with monocurve lenses, bicurve lenses, and other lens types, respectively. In eyes with round cones (nipple morphology), 55%, 30%, and 15% were fitted with bicurve lenses, monocurve lenses, and other lens types, respectively. Monocurve RGPCL were most frequently fitted in patients with mild to moderate keratoconus and oval cones morphology, while bicurve lenses were more frequently fitted in patients with severe and advanced keratoconus. This was probably because bicurve lenses are more appropriate for round cones due to increased corneal asphericity.

Spatiotemporal patterns of severe fever with thrombocytopenia syndrome in China, 2011-2016.

PubMed

Sun, Jimin; Lu, Liang; Wu, Haixia; Yang, Jun; Liu, Keke; Liu, Qiyong

2018-05-01

Severe fever with thrombocytopenia syndrome (SFTS) is emerging and the number of SFTS cases have increased year by year in China. However, spatiotemporal patterns and trends of SFTS are less clear up to date. In order to explore spatiotemporal patterns and predict SFTS incidences, we analyzed temporal trends of SFTS using autoregressive integrated moving average (ARIMA) model, spatial patterns, and spatiotemporal clusters of SFTS cases at the county level based on SFTS data in China during 2011-2016. We determined the optimal time series model was ARIMA (2, 0, 1) × (0, 0, 1) 12 which fitted the SFTS cases reasonably well during the training process and forecast process. In the spatial clustering analysis, the global autocorrelation suggested that SFTS cases were not of random distribution. Local spatial autocorrelation analysis of SFTS identified foci mainly concentrated in Hubei Province, Henan Province, Anhui Province, Shandong Province, Liaoning Province, and Zhejiang Province. A most likely cluster including 21 counties in Henan Province and Hubei Province was observed in the central region of China from April 2015 to August 2016. Our results will provide a sound evidence base for future prevention and control programs of SFTS such as allocation of the health resources, surveillance in high-risk regions, health education, improvement of diagnosis and so on. Copyright © 2018 Elsevier GmbH. All rights reserved.

MISFITS: evaluating the goodness of fit between a phylogenetic model and an alignment.

PubMed

Nguyen, Minh Anh Thi; Klaere, Steffen; von Haeseler, Arndt

2011-01-01

As models of sequence evolution become more and more complicated, many criteria for model selection have been proposed, and tools are available to select the best model for an alignment under a particular criterion. However, in many instances the selected model fails to explain the data adequately as reflected by large deviations between observed pattern frequencies and the corresponding expectation. We present MISFITS, an approach to evaluate the goodness of fit (http://www.cibiv.at/software/misfits). MISFITS introduces a minimum number of "extra substitutions" on the inferred tree to provide a biologically motivated explanation why the alignment may deviate from expectation. These extra substitutions plus the evolutionary model then fully explain the alignment. We illustrate the method on several examples and then give a survey about the goodness of fit of the selected models to the alignments in the PANDIT database.

Motion patterns in acupuncture needle manipulation.

PubMed

Seo, Yoonjeong; Lee, In-Seon; Jung, Won-Mo; Ryu, Ho-Sun; Lim, Jinwoong; Ryu, Yeon-Hee; Kang, Jung-Won; Chae, Younbyoung

2014-10-01

In clinical practice, acupuncture manipulation is highly individualised for each practitioner. Before we establish a standard for acupuncture manipulation, it is important to understand completely the manifestations of acupuncture manipulation in the actual clinic. To examine motion patterns during acupuncture manipulation, we generated a fitted model of practitioners' motion patterns and evaluated their consistencies in acupuncture manipulation. Using a motion sensor, we obtained real-time motion data from eight experienced practitioners while they conducted acupuncture manipulation using their own techniques. We calculated the average amplitude and duration of a sampled motion unit for each practitioner and, after normalisation, we generated a true regression curve of motion patterns for each practitioner using a generalised additive mixed modelling (GAMM). We observed significant differences in rotation amplitude and duration in motion samples among practitioners. GAMM showed marked variations in average regression curves of motion patterns among practitioners but there was strong consistency in motion parameters for individual practitioners. The fitted regression model showed that the true regression curve accounted for an average of 50.2% of variance in the motion pattern for each practitioner. Our findings suggest that there is great inter-individual variability between practitioners, but remarkable intra-individual consistency within each practitioner. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Modeling the near-ultraviolet band of GK stars. III. Dependence on abundance pattern

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

Short, C. Ian; Campbell, Eamonn A., E-mail: ishort@ap.smu.ca

2013-06-01

We extend the grid of non-LTE (NLTE) models presented in Paper II to explore variations in abundance pattern in two ways: (1) the adoption of the Asplund et al. (GASS10) abundances, (2) for stars of metallicity, [M/H], of –0.5, the adoption of a non-solar enhancement of α-elements by +0.3 dex. Moreover, our grid of synthetic spectral energy distributions (SEDs) is interpolated to a finer numerical resolution in both T {sub eff} (ΔT {sub eff} = 25 K) and log g (Δlog g = 0.25). We compare the values of T {sub eff} and log g inferred from fitting LTE andmore » NLTE SEDs to observed SEDs throughout the entire visible band, and in an ad hoc 'blue' band. We compare our spectrophotometrically derived T {sub eff} values to a variety of T {sub eff} calibrations, including more empirical ones, drawn from the literature. For stars of solar metallicity, we find that the adoption of the GASS10 abundances lowers the inferred T {sub eff} value by 25-50 K for late-type giants, and NLTE models computed with the GASS10 abundances give T {sub eff} results that are marginally in better agreement with other T {sub eff} calibrations. For stars of [M/H] = –0.5 there is marginal evidence that adoption of α-enhancement further lowers the derived T {sub eff} value by 50 K. Stellar parameters inferred from fitting NLTE models to SEDs are more dependent than LTE models on the wavelength region being fitted, and we find that the effect depends on how heavily line blanketed the fitting region is, whether the fitting region is to the blue of the Wien peak of the star's SED, or both.« less

Pattern Recognition Analysis of Age-Related Retinal Ganglion Cell Signatures in the Human Eye

PubMed Central

Yoshioka, Nayuta; Zangerl, Barbara; Nivison-Smith, Lisa; Khuu, Sieu K.; Jones, Bryan W.; Pfeiffer, Rebecca L.; Marc, Robert E.; Kalloniatis, Michael

2017-01-01

Purpose To characterize macular ganglion cell layer (GCL) changes with age and provide a framework to assess changes in ocular disease. This study used data clustering to analyze macular GCL patterns from optical coherence tomography (OCT) in a large cohort of subjects without ocular disease. Methods Single eyes of 201 patients evaluated at the Centre for Eye Health (Sydney, Australia) were retrospectively enrolled (age range, 20–85); 8 × 8 grid locations obtained from Spectralis OCT macular scans were analyzed with unsupervised classification into statistically separable classes sharing common GCL thickness and change with age. The resulting classes and gridwise data were fitted with linear and segmented linear regression curves. Additionally, normalized data were analyzed to determine regression as a percentage. Accuracy of each model was examined through comparison of predicted 50-year-old equivalent macular GCL thickness for the entire cohort to a true 50-year-old reference cohort. Results Pattern recognition clustered GCL thickness across the macula into five to eight spatially concentric classes. F-test demonstrated segmented linear regression to be the most appropriate model for macular GCL change. The pattern recognition–derived and normalized model revealed less difference between the predicted macular GCL thickness and the reference cohort (average ± SD 0.19 ± 0.92 and −0.30 ± 0.61 μm) than a gridwise model (average ± SD 0.62 ± 1.43 μm). Conclusions Pattern recognition successfully identified statistically separable macular areas that undergo a segmented linear reduction with age. This regression model better predicted macular GCL thickness. The various unique spatial patterns revealed by pattern recognition combined with core GCL thickness data provide a framework to analyze GCL loss in ocular disease. PMID:28632847

The policy effects of feed-in tariff and renewable portfolio standard: A case study of China's waste incineration power industry.

PubMed

Xin-Gang, Zhao; Yu-Zhuo, Zhang; Ling-Zhi, Ren; Yi, Zuo; Zhi-Gong, Wu

2017-10-01

Among the regulatory policies, feed-in tariffs (FIT) and renewable portfolio standards (RPS) are the most popular to promote the development of renewable energy power industry. They can significantly contribute to the expansion of domestic industrial activities in terms of sustainable energy. This paper uses system dynamics (SD) to establish models of long-term development of China's waste incineration power industry under FIT and RPS schemes, and provides a case study by using scenario analysis method. The model, on the one hand, not only clearly shows the complex logical relationship between the factors but also assesses policy effects of the two policy tools in the development of the industry. On the other hand, it provides a reference for scholars to study similar problems in different countries, thereby facilitating an understanding of waste incineration power's long-term sustainable development pattern under FIT and RPS schemes, and helping to provide references for policy-making institutions. The results show that in the perfect competitive market, the implementation of RPS can promote long-term and rapid development of China's waste incineration power industry given the constraints and actions of the mechanisms of RPS quota proportion, the TGC valid period, and fines, compared with FIT. At the end of the paper, policy implications are offered as references for the government. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparing rainfall patterns between regions in Peninsular Malaysia via a functional data analysis technique

NASA Astrophysics Data System (ADS)

Suhaila, Jamaludin; Jemain, Abdul Aziz; Hamdan, Muhammad Fauzee; Wan Zin, Wan Zawiah

2011-12-01

SummaryNormally, rainfall data is collected on a daily, monthly or annual basis in the form of discrete observations. The aim of this study is to convert these rainfall values into a smooth curve or function which could be used to represent the continuous rainfall process at each region via a technique known as functional data analysis. Since rainfall data shows a periodic pattern in each region, the Fourier basis is introduced to capture these variations. Eleven basis functions with five harmonics are used to describe the unimodal rainfall pattern for stations in the East while five basis functions which represent two harmonics are needed to describe the rainfall pattern in the West. Based on the fitted smooth curve, the wet and dry periods as well as the maximum and minimum rainfall values could be determined. Different rainfall patterns are observed among the studied regions based on the smooth curve. Using the functional analysis of variance, the test results indicated that there exist significant differences in the functional means between each region. The largest differences in the functional means are found between the East and Northwest regions and these differences may probably be due to the effect of topography and, geographical location and are mostly influenced by the monsoons. Therefore, the same inputs or approaches might not be useful in modeling the hydrological process for different regions.

An application of a Hill-based response surface model for a drug combination experiment on lung cancer.

PubMed

Ning, Shaoyang; Xu, Hongquan; Al-Shyoukh, Ibrahim; Feng, Jiaying; Sun, Ren

2014-10-30

Combination chemotherapy with multiple drugs has been widely applied to cancer treatment owing to enhanced efficacy and reduced drug resistance. For drug combination experiment analysis, response surface modeling has been commonly adopted. In this paper, we introduce a Hill-based global response surface model and provide an application of the model to a 512-run drug combination experiment with three chemicals, namely AG490, U0126, and indirubin-3  ' -monoxime (I-3-M), on lung cancer cells. The results demonstrate generally improved goodness of fit of our model from the traditional polynomial model, as well as the original Hill model on the basis of fixed-ratio drug combinations. We identify different dose-effect patterns between normal and cancer cells on the basis of our model, which indicates the potential effectiveness of the drug combination in cancer treatment. Meanwhile, drug interactions are analyzed both qualitatively and quantitatively. The distinct interaction patterns between U0126 and I-3-M on two types of cells uncovered by the model could be a further indicator of the efficacy of the drug combination. Copyright © 2014 John Wiley & Sons, Ltd.

Preschool Psychopathology Reported by Parents in 23 Societies: Testing the Seven-Syndrome Model of the Child Behavior Checklist for Ages 1.5–5

PubMed Central

Ivanova, Masha Y.; Achenbach, Thomas M.; Rescorla, Leslie A.; Harder, Valerie S.; Ang, Rebecca P.; Bilenberg, Niels; Bjarnadottir, Gudrun; Capron, Christiane; De Pauw, Sarah S.W.; Dias, Pedro; Dobrean, Anca; Doepfner, Manfred; Duyme, Michele; Eapen, Valsamma; Erol, Nese; Esmaeili, Elaheh Mohammad; Ezpeleta, Lourdes; Frigerio, Alessandra; Gonçalves, Miguel M.; Gudmundsson, Halldor S.; Jeng, Suh-Fang; Jetishi, Pranvera; Jusiene, Roma; Kim, Young-Ah; Kristensen, Solvejg; Lecannelier, Felipe; Leung, Patrick W.L.; Liu, Jianghong; Montirosso, Rosario; Oh, Kyung Ja; Plueck, Julia; Pomalima, Rolando; Shahini, Mimoza; Silva, Jaime R.; Simsek, Zynep; Sourander, Andre; Valverde, Jose; Van Leeuwen, Karla G.; Woo, Bernardine S.C.; Wu, Yen-Tzu; Zubrick, Stephen R.; Verhulst, Frank C.

2014-01-01

Objective To test the fit of a seven-syndrome model to ratings of preschoolers' problems by parents in very diverse societies. Method Parents of 19,106 children 18 to 71 months of age from 23 societies in Asia, Australasia, Europe, the Middle East, and South America completed the Child Behavior Checklist for Ages 1.5–5 (CBCL/1.5–5). Confirmatory factor analyses were used to test the seven-syndrome model separately for each society. Results The primary model fit index, the root mean square error of approximation (RMSEA), indicated acceptable to good fit for each society. Although a six-syndrome model combining the Emotionally Reactive and Anxious/Depressed syndromes also fit the data for nine societies, it fit less well than the seven-syndrome model for seven of the nine societies. Other fit indices yielded less consistent results than the RMSEA. Conclusions The seven-syndrome model provides one way to capture patterns of children's problems that are manifested in ratings by parents from many societies. Clinicians working with preschoolers from these societies can thus assess and describe parents' ratings of behavioral, emotional, and social problems in terms of the seven syndromes. The results illustrate possibilities for culture–general taxonomic constructs of preschool psychopathology. Problems not captured by the CBCL/1.5–5 may form additional syndromes, and other syndrome models may also fit the data. PMID:21093771

Preschool psychopathology reported by parents in 23 societies: testing the seven-syndrome model of the child behavior checklist for ages 1.5-5.

PubMed

Ivanova, Masha Y; Achenbach, Thomas M; Rescorla, Leslie A; Harder, Valerie S; Ang, Rebecca P; Bilenberg, Niels; Bjarnadottir, Gudrun; Capron, Christiane; De Pauw, Sarah S W; Dias, Pedro; Dobrean, Anca; Doepfner, Manfred; Duyme, Michele; Eapen, Valsamma; Erol, Nese; Esmaeili, Elaheh Mohammad; Ezpeleta, Lourdes; Frigerio, Alessandra; Gonçalves, Miguel M; Gudmundsson, Halldor S; Jeng, Suh-Fang; Jetishi, Pranvera; Jusiene, Roma; Kim, Young-Ah; Kristensen, Solvejg; Lecannelier, Felipe; Leung, Patrick W L; Liu, Jianghong; Montirosso, Rosario; Oh, Kyung Ja; Plueck, Julia; Pomalima, Rolando; Shahini, Mimoza; Silva, Jaime R; Simsek, Zynep; Sourander, Andre; Valverde, Jose; Van Leeuwen, Karla G; Woo, Bernardine S C; Wu, Yen-Tzu; Zubrick, Stephen R; Verhulst, Frank C

2010-12-01

To test the fit of a seven-syndrome model to ratings of preschoolers' problems by parents in very diverse societies. Parents of 19,106 children 18 to 71 months of age from 23 societies in Asia, Australasia, Europe, the Middle East, and South America completed the Child Behavior Checklist for Ages 1.5-5 (CBCL/1.5-5). Confirmatory factor analyses were used to test the seven-syndrome model separately for each society. The primary model fit index, the root mean square error of approximation (RMSEA), indicated acceptable to good fit for each society. Although a six-syndrome model combining the Emotionally Reactive and Anxious/Depressed syndromes also fit the data for nine societies, it fit less well than the seven-syndrome model for seven of the nine societies. Other fit indices yielded less consistent results than the RMSEA. The seven-syndrome model provides one way to capture patterns of children's problems that are manifested in ratings by parents from many societies. Clinicians working with preschoolers from these societies can thus assess and describe parents' ratings of behavioral, emotional, and social problems in terms of the seven syndromes. The results illustrate possibilities for culture-general taxonomic constructs of preschool psychopathology. Problems not captured by the CBCL/1.5-5 may form additional syndromes, and other syndrome models may also fit the data. Copyright © 2010 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

Microenvironmental influence on microtumour infiltration patterns: 3D-mathematical modelling supported by in vitro studies.

PubMed

Luján, Emmanuel; Soto, Daniela; Rosito, María S; Soba, Alejandro; Guerra, Liliana N; Calvo, Juan C; Marshall, Guillermo; Suárez, Cecilia

2018-05-09

Mathematical modelling approaches have become increasingly abundant in cancer research. Tumour infiltration extent and its spatial organization depend both on the tumour type and stage and on the bio-physicochemical characteristics of the microenvironment. This sets a complex scenario that often requires a multidisciplinary and individually adjusted approach. The ultimate goal of this work is to present an experimental/numerical combined method for the development of a three-dimensional mathematical model with the ability to reproduce the growth and infiltration patterns of a given avascular microtumour in response to different microenvironmental conditions. The model is based on a diffusion-convection reaction equation that considers logistic proliferation, volumetric growth, a rim of proliferative cells at the tumour surface, and invasion with diffusive and convective components. The parameter values of the model were fitted to experimental results while radial velocity and diffusion coefficients were made spatially variable in a case-specific way through the introduction of a shape function and a diffusion-limited-aggregation (DLA)-derived fractal matrix, respectively, according to the infiltration pattern observed. The in vitro model consists of multicellular tumour spheroids (MTSs) of an epithelial mammary tumour cell line (LM3) immersed in a collagen I gel matrix with a standard culture medium ("naive" matrix) or a conditioned medium from adipocytes or preadipocytes ("conditioned" matrix). It was experimentally determined that both adipocyte and preadipocyte conditioned media had the ability to change the MTS infiltration pattern from collective and laminar to an individual and atomized one. Numerical simulations were able to adequately reproduce qualitatively and quantitatively both kinds of infiltration patterns, which were determined by area quantification, analysis of fractal dimensions and lacunarity, and Bland-Altman analysis. These results suggest that the combined approach presented here could be established as a new framework with interesting potential applications at both the basic and clinical levels in the oncology area.

Testability of evolutionary game dynamics based on experimental economics data

NASA Astrophysics Data System (ADS)

Wang, Yijia; Chen, Xiaojie; Wang, Zhijian

2017-11-01

Understanding the dynamic processes of a real game system requires an appropriate dynamics model, and rigorously testing a dynamics model is nontrivial. In our methodological research, we develop an approach to testing the validity of game dynamics models that considers the dynamic patterns of angular momentum and speed as measurement variables. Using Rock-Paper-Scissors (RPS) games as an example, we illustrate the geometric patterns in the experiment data. We then derive the related theoretical patterns from a series of typical dynamics models. By testing the goodness-of-fit between the experimental and theoretical patterns, we show that the validity of these models can be evaluated quantitatively. Our approach establishes a link between dynamics models and experimental systems, which is, to the best of our knowledge, the most effective and rigorous strategy for ascertaining the testability of evolutionary game dynamics models.

Association of Physical Activity or Fitness With Incident Heart Failure: A Systematic Review and Meta-Analysis.

PubMed

Echouffo-Tcheugui, Justin B; Butler, Javed; Yancy, Clyde W; Fonarow, Gregg C

2015-09-01

Previous studies have shown that high levels of physical activity are associated with lower risk of risk factors for heart failure (HF), such as coronary heart disease, hypertension, and diabetes mellitus. However, the effects of physical activity or fitness on the incidence of HF remain unclear. MEDLINE and EMBASE were systematically searched until November 30, 2014. Prospective cohort studies reporting measures of the association of physical activity (n=10) or fitness (n=2) with incident HF were included. Extracted effect estimates from the eligible studies were pooled using a random-effects model meta-analysis, with heterogeneity assessed with the I(2) statistic. Ten cohort studies on physical activity eligible for meta-analysis included a total of 282 889 participants followed for 7 to 30 years. For the physical activity studies, maximum versus minimal amount of physical activity groups were used for analyses; with a total number of participants (n=165 695). The pooled relative risk (95% confidence interval [CI]) for HF among those with a regular exercise pattern was 0.72 (95% CI, 0.67-0.79). Findings were similar for men (0.71 [95% CI, 0.61-0.83]) and women (0.72 [95% CI, 0.67-0.77]) and by type of exercise. There was no evidence of publication bias (P value for Egger test=0.34). The pooled associated effect of physical fitness on incident HF was 0.79 (95% CI, 0.75-0.83) for each unit increase in metabolic equivalent of oxygen consumption. Published literature support a significant association between increased physical activity or fitness and decreased incidence of HF. © 2015 American Heart Association, Inc.

A critique of Rasch residual fit statistics.

PubMed

Karabatsos, G

2000-01-01

In test analysis involving the Rasch model, a large degree of importance is placed on the "objective" measurement of individual abilities and item difficulties. The degree to which the objectivity properties are attained, of course, depends on the degree to which the data fit the Rasch model. It is therefore important to utilize fit statistics that accurately and reliably detect the person-item response inconsistencies that threaten the measurement objectivity of persons and items. Given this argument, it is somewhat surprising that there is far more emphasis placed in the objective measurement of person and items than there is in the measurement quality of Rasch fit statistics. This paper provides a critical analysis of the residual fit statistics of the Rasch model, arguably the most often used fit statistics, in an effort to illustrate that the task of Rasch fit analysis is not as simple and straightforward as it appears to be. The faulty statistical properties of the residual fit statistics do not allow either a convenient or a straightforward approach to Rasch fit analysis. For instance, given a residual fit statistic, the use of a single minimum critical value for misfit diagnosis across different testing situations, where the situations vary in sample and test properties, leads to both the overdetection and underdetection of misfit. To improve this situation, it is argued that psychometricians need to implement residual-free Rasch fit statistics that are based on the number of Guttman response errors, or use indices that are statistically optimal in detecting measurement disturbances.

3D Product Development for Loose-Fitting Garments Based on Parametric Human Models

NASA Astrophysics Data System (ADS)

Krzywinski, S.; Siegmund, J.

2017-10-01

Researchers and commercial suppliers worldwide pursue the objective of achieving a more transparent garment construction process that is computationally linked to a virtual body, in order to save development costs over the long term. The current aim is not to transfer the complete pattern making step to a 3D design environment but to work out basic constructions in 3D that provide excellent fit due to their accurate construction and morphological pattern grading (automatic change of sizes in 3D) in respect of sizes and body types. After a computer-aided derivation of 2D pattern parts, these can be made available to the industry as a basis on which to create more fashionable variations.

Examining evolving performance on the Force Concept Inventory using factor analysis

NASA Astrophysics Data System (ADS)

Semak, M. R.; Dietz, R. D.; Pearson, R. H.; Willis, C. W.

2017-06-01

The application of factor analysis to the Force Concept Inventory (FCI) has proven to be problematic. Some studies have suggested that factor analysis of test results serves as a helpful tool in assessing the recognition of Newtonian concepts by students. Other work has produced at best ambiguous results. For the FCI administered as a pre- and post-test, we see factor analysis as a tool by which the changes in conceptual associations made by our students may be gauged given the evolution of their response patterns. This analysis allows us to identify and track conceptual linkages, affording us insight as to how our students have matured due to instruction. We report on our analysis of 427 pre- and post-tests. The factor models for the pre- and post-tests are explored and compared along with the methodology by which these models were fit to the data. The post-test factor pattern is more aligned with an expert's interpretation of the questions' content, as it allows for a more readily identifiable relationship between factors and physical concepts. We discuss this evolution in the context of approaching the characteristics of an expert with force concepts. Also, we find that certain test items do not significantly contribute to the pre- or post-test factor models and attempt explanations as to why this is so. This may suggest that such questions may not be effective in probing the conceptual understanding of our students.

Relationships between attitudes toward and achievement in science for rural middle school students: Patterns across gender

NASA Astrophysics Data System (ADS)

Mattern, Nancy Page Garland

Four causal models describing the relationships between attitudes and achievement have been proposed in the literature. The cross-effects, or reciprocal effects, model highlights the effects of prior attitudes on later achievement (over and above the effect of previous achievement) and of prior achievement on later attitudes (above the effect of previous attitudes). In the achievement predominant model, the effect of prior achievement on later attitudes is emphasized, controlling for the effect of previous attitudes. The effect of prior attitudes on later achievement, controlling for the effect of previous achievement, is emphasized in the attitudes predominant model. In the no cross-effects model there are no significant cross paths from prior attitudes to later achievement or from prior achievement to later attitudes. To determine the best-fitting model for rural seventh and eighth grade science girls and boys, the causal relationships over time between attitudes toward science and achievement in science were examined by gender using structural equation modeling. Data were collected in two waves, over one school year. A baseline measurement model was estimated in simultaneous two-group solutions and was a good fit to the data. Next, the four structural models were estimated and model fits compared. The three models nested within the structural cross-effects model showed significant decay of fit when compared to the fit of the cross-effects model. The cross-effects model was the best fit overall for middle school girls and boys. The cross-effects model was then tested for invariance across gender. There was significant decay of fit when model form, factor path loadings, and structural paths were constrained to be equal for girls and boys. Two structural paths, the path from prior achievement to later attitudes, and the path from prior attitudes to later attitudes, were the sources of gender non-invariance. Separate models were estimated for girls and boys, and the fits of nested models were compared. The no cross-effects model was the best-fitting model for rural middle school girls. The new no attitudes-path model was the best-fitting model for boys. Implications of these findings for teaching middle school students were discussed.

Resource competition model predicts zonation and increasing nutrient use efficiency along a wetland salinity gradient

USGS Publications Warehouse

Schoolmaster, Donald; Stagg, Camille L.

2018-01-01

A trade-off between competitive ability and stress tolerance has been hypothesized and empirically supported to explain the zonation of species across stress gradients for a number of systems. Since stress often reduces plant productivity, one might expect a pattern of decreasing productivity across the zones of the stress gradient. However, this pattern is often not observed in coastal wetlands that show patterns of zonation along a salinity gradient. To address the potentially complex relationship between stress, zonation, and productivity in coastal wetlands, we developed a model of plant biomass as a function of resource competition and salinity stress. Analysis of the model confirms the conventional wisdom that a trade-off between competitive ability and stress tolerance is a necessary condition for zonation. It also suggests that a negative relationship between salinity and production can be overcome if (1) the supply of the limiting resource increases with greater salinity stress or (2) nutrient use efficiency increases with increasing salinity. We fit the equilibrium solution of the dynamic model to data from Louisiana coastal wetlands to test its ability to explain patterns of production across the landscape gradient and derive predictions that could be tested with independent data. We found support for a number of the model predictions, including patterns of decreasing competitive ability and increasing nutrient use efficiency across a gradient from freshwater to saline wetlands. In addition to providing a quantitative framework to support the mechanistic hypotheses of zonation, these results suggest that this simple model is a useful platform to further build upon, simulate and test mechanistic hypotheses of more complex patterns and phenomena in coastal wetlands.

Modeling vertebrate diversity in Oregon using satellite imagery

NASA Astrophysics Data System (ADS)

Cablk, Mary Elizabeth

Vertebrate diversity was modeled for the state of Oregon using a parametric approach to regression tree analysis. This exploratory data analysis effectively modeled the non-linear relationships between vertebrate richness and phenology, terrain, and climate. Phenology was derived from time-series NOAA-AVHRR satellite imagery for the year 1992 using two methods: principal component analysis and derivation of EROS data center greenness metrics. These two measures of spatial and temporal vegetation condition incorporated the critical temporal element in this analysis. The first three principal components were shown to contain spatial and temporal information about the landscape and discriminated phenologically distinct regions in Oregon. Principal components 2 and 3, 6 greenness metrics, elevation, slope, aspect, annual precipitation, and annual seasonal temperature difference were investigated as correlates to amphibians, birds, all vertebrates, reptiles, and mammals. Variation explained for each regression tree by taxa were: amphibians (91%), birds (67%), all vertebrates (66%), reptiles (57%), and mammals (55%). Spatial statistics were used to quantify the pattern of each taxa and assess validity of resulting predictions from regression tree models. Regression tree analysis was relatively robust against spatial autocorrelation in the response data and graphical results indicated models were well fit to the data.

Comparative analysis through probability distributions of a data set

NASA Astrophysics Data System (ADS)

Cristea, Gabriel; Constantinescu, Dan Mihai

2018-02-01

In practice, probability distributions are applied in such diverse fields as risk analysis, reliability engineering, chemical engineering, hydrology, image processing, physics, market research, business and economic research, customer support, medicine, sociology, demography etc. This article highlights important aspects of fitting probability distributions to data and applying the analysis results to make informed decisions. There are a number of statistical methods available which can help us to select the best fitting model. Some of the graphs display both input data and fitted distributions at the same time, as probability density and cumulative distribution. The goodness of fit tests can be used to determine whether a certain distribution is a good fit. The main used idea is to measure the "distance" between the data and the tested distribution, and compare that distance to some threshold values. Calculating the goodness of fit statistics also enables us to order the fitted distributions accordingly to how good they fit to data. This particular feature is very helpful for comparing the fitted models. The paper presents a comparison of most commonly used goodness of fit tests as: Kolmogorov-Smirnov, Anderson-Darling, and Chi-Squared. A large set of data is analyzed and conclusions are drawn by visualizing the data, comparing multiple fitted distributions and selecting the best model. These graphs should be viewed as an addition to the goodness of fit tests.

Evaluating the Number of Stages in Development of Squamous Cell and Adenocarcinomas across Cancer Sites Using Human Population-Based Cancer Modeling

PubMed Central

Kravchenko, Julia; Akushevich, Igor; Abernethy, Amy P.; Lyerly, H. Kim

2012-01-01

Background Adenocarcinomas (ACs) and squamous cell carcinomas (SCCs) differ by clinical and molecular characteristics. We evaluated the characteristics of carcinogenesis by modeling the age patterns of incidence rates of ACs and SCCs of various organs to test whether these characteristics differed between cancer subtypes. Methodology/Principal Findings Histotype-specific incidence rates of 14 ACs and 12 SCCs from the SEER Registry (1973–2003) were analyzed by fitting several biologically motivated models to observed age patterns. A frailty model with the Weibull baseline was applied to each age pattern to provide the best fit for the majority of cancers. For each cancer, model parameters describing the underlying mechanisms of carcinogenesis including the number of stages occurring during an individual’s life and leading to cancer (m-stages) were estimated. For sensitivity analysis, the age-period-cohort model was incorporated into the carcinogenesis model to test the stability of the estimates. For the majority of studied cancers, the numbers of m-stages were similar within each group (i.e., AC and SCC). When cancers of the same organs were compared (i.e., lung, esophagus, and cervix uteri), the number of m-stages were more strongly associated with the AC/SCC subtype than with the organ: 9.79±0.09, 9.93±0.19 and 8.80±0.10 for lung, esophagus, and cervical ACs, compared to 11.41±0.10, 12.86±0.34 and 12.01±0.51 for SCCs of the respective organs (p<0.05 between subtypes). Most SCCs had more than ten m-stages while ACs had fewer than ten m-stages. The sensitivity analyses of the model parameters demonstrated the stability of the obtained estimates. Conclusions/Significance A model containing parameters capable of representing the number of stages of cancer development occurring during individual’s life was applied to the large population data on incidence of ACs and SCCs. The model revealed that the number of m-stages differed by cancer subtype being more strongly associated with ACs/SCCs histotype than with organ/site. PMID:22629394

Patterning nanowire and micro-nanoparticle array on micropillar-structured surface: Experiment and modeling.

PubMed

Lin, Chung Hsun; Guan, Jingjiao; Chau, Shiu Wu; Chen, Shia Chung; Lee, L James

2010-08-04

DNA molecules in a solution can be immobilized and stretched into a highly ordered array on a solid surface containing micropillars by molecular combing technique. However, the mechanism of this process is not well understood. In this study, we demonstrated the generation of DNA nanostrand array with linear, zigzag, and fork-zigzag patterns and the microfluidic processes are modeled based on a deforming body-fitted grid approach. The simulation results provide insights for explaining the stretching, immobilizing, and patterning of DNA molecules observed in the experiments.

Detecting consistent patterns of directional adaptation using differential selection codon models.

PubMed

Parto, Sahar; Lartillot, Nicolas

2017-06-23

Phylogenetic codon models are often used to characterize the selective regimes acting on protein-coding sequences. Recent methodological developments have led to models explicitly accounting for the interplay between mutation and selection, by modeling the amino acid fitness landscape along the sequence. However, thus far, most of these models have assumed that the fitness landscape is constant over time. Fluctuations of the fitness landscape may often be random or depend on complex and unknown factors. However, some organisms may be subject to systematic changes in selective pressure, resulting in reproducible molecular adaptations across independent lineages subject to similar conditions. Here, we introduce a codon-based differential selection model, which aims to detect and quantify the fine-grained consistent patterns of adaptation at the protein-coding level, as a function of external conditions experienced by the organism under investigation. The model parameterizes the global mutational pressure, as well as the site- and condition-specific amino acid selective preferences. This phylogenetic model is implemented in a Bayesian MCMC framework. After validation with simulations, we applied our method to a dataset of HIV sequences from patients with known HLA genetic background. Our differential selection model detects and characterizes differentially selected coding positions specifically associated with two different HLA alleles. Our differential selection model is able to identify consistent molecular adaptations as a function of repeated changes in the environment of the organism. These models can be applied to many other problems, ranging from viral adaptation to evolution of life-history strategies in plants or animals.

Twitter classification model: the ABC of two million fitness tweets.

PubMed

Vickey, Theodore A; Ginis, Kathleen Martin; Dabrowski, Maciej

2013-09-01

The purpose of this project was to design and test data collection and management tools that can be used to study the use of mobile fitness applications and social networking within the context of physical activity. This project was conducted over a 6-month period and involved collecting publically shared Twitter data from five mobile fitness apps (Nike+, RunKeeper, MyFitnessPal, Endomondo, and dailymile). During that time, over 2.8 million tweets were collected, processed, and categorized using an online tweet collection application and a customized JavaScript. Using the grounded theory, a classification model was developed to categorize and understand the types of information being shared by application users. Our data show that by tracking mobile fitness app hashtags, a wealth of information can be gathered to include but not limited to daily use patterns, exercise frequency, location-based workouts, and overall workout sentiment.

Performance of the Generalized S-X[squared] Item Fit Index for the Graded Response Model

ERIC Educational Resources Information Center

Kang, Taehoon; Chen, Troy T.

2011-01-01

The utility of Orlando and Thissen's ("2000", "2003") S-X[squared] fit index was extended to the model-fit analysis of the graded response model (GRM). The performance of a modified S-X[squared] in assessing item-fit of the GRM was investigated in light of empirical Type I error rates and power with a simulation study having…

Nonlinear Structured Growth Mixture Models in M"plus" and OpenMx

ERIC Educational Resources Information Center

Grimm, Kevin J.; Ram, Nilam; Estabrook, Ryne

2010-01-01

Growth mixture models (GMMs; B. O. Muthen & Muthen, 2000; B. O. Muthen & Shedden, 1999) are a combination of latent curve models (LCMs) and finite mixture models to examine the existence of latent classes that follow distinct developmental patterns. GMMs are often fit with linear, latent basis, multiphase, or polynomial change models…

The Population Tracking Model: A Simple, Scalable Statistical Model for Neural Population Data

PubMed Central

O'Donnell, Cian; alves, J. Tiago Gonç; Whiteley, Nick; Portera-Cailliau, Carlos; Sejnowski, Terrence J.

2017-01-01

Our understanding of neural population coding has been limited by a lack of analysis methods to characterize spiking data from large populations. The biggest challenge comes from the fact that the number of possible network activity patterns scales exponentially with the number of neurons recorded (∼2Neurons). Here we introduce a new statistical method for characterizing neural population activity that requires semi-independent fitting of only as many parameters as the square of the number of neurons, requiring drastically smaller data sets and minimal computation time. The model works by matching the population rate (the number of neurons synchronously active) and the probability that each individual neuron fires given the population rate. We found that this model can accurately fit synthetic data from up to 1000 neurons. We also found that the model could rapidly decode visual stimuli from neural population data from macaque primary visual cortex about 65 ms after stimulus onset. Finally, we used the model to estimate the entropy of neural population activity in developing mouse somatosensory cortex and, surprisingly, found that it first increases, and then decreases during development. This statistical model opens new options for interrogating neural population data and can bolster the use of modern large-scale in vivo Ca2+ and voltage imaging tools. PMID:27870612

Self-efficacy for healthy eating and peer support for unhealthy eating are associated with adolescents' food intake patterns.

PubMed

Fitzgerald, Amanda; Heary, Caroline; Kelly, Colette; Nixon, Elizabeth; Shevlin, Mark

2013-04-01

Adolescence, with its change in dietary habits, is likely to be a vulnerable period in the onset of obesity. It is considered that peers have an important role to play on adolescents' diet, however, limited research has examined the role of peers in this context. This study examined the relationship between self-efficacy for healthy eating, parent and peer support for healthy and unhealthy eating and food intake patterns. Participants were 264 boys and 219 girls (N=483), aged 13-18years, recruited from post-primary schools in Ireland. Self-report measures assessed self-efficacy, parent and peer support for healthy eating, and for unhealthy eating. Dietary pattern analysis, a popular alternative to traditional methods used in nutritional research, was conducted on a FFQ to derive food intake patterns. Two patterns were identified labelled 'healthy food intake' and 'unhealthy food intake'. Multi-group modelling was used to evaluate whether the hypothesized model of factors related to dietary patterns differed by gender. The multi-group model fit the data well, with only one path shown to differ by gender. Lower self-efficacy for healthy eating and higher peer support for unhealthy eating were associated with 'unhealthy food intake'. Higher self-efficacy was associated with 'healthy food intake'. Prevention programs that target self-efficacy for eating and peer support for unhealthy eating may be beneficial in improving dietary choices among adolescents. Copyright © 2012 Elsevier Ltd. All rights reserved.

Nonlinear Growth Models in M"plus" and SAS

ERIC Educational Resources Information Center

Grimm, Kevin J.; Ram, Nilam

2009-01-01

Nonlinear growth curves or growth curves that follow a specified nonlinear function in time enable researchers to model complex developmental patterns with parameters that are easily interpretable. In this article we describe how a variety of sigmoid curves can be fit using the M"plus" structural modeling program and the nonlinear…

Application of seasonal auto-regressive integrated moving average model in forecasting the incidence of hand-foot-mouth disease in Wuhan, China.

PubMed

Peng, Ying; Yu, Bin; Wang, Peng; Kong, De-Guang; Chen, Bang-Hua; Yang, Xiao-Bing

2017-12-01

Outbreaks of hand-foot-mouth disease (HFMD) have occurred many times and caused serious health burden in China since 2008. Application of modern information technology to prediction and early response can be helpful for efficient HFMD prevention and control. A seasonal auto-regressive integrated moving average (ARIMA) model for time series analysis was designed in this study. Eighty-four-month (from January 2009 to December 2015) retrospective data obtained from the Chinese Information System for Disease Prevention and Control were subjected to ARIMA modeling. The coefficient of determination (R 2 ), normalized Bayesian Information Criterion (BIC) and Q-test P value were used to evaluate the goodness-of-fit of constructed models. Subsequently, the best-fitted ARIMA model was applied to predict the expected incidence of HFMD from January 2016 to December 2016. The best-fitted seasonal ARIMA model was identified as (1,0,1)(0,1,1) 12 , with the largest coefficient of determination (R 2 =0.743) and lowest normalized BIC (BIC=3.645) value. The residuals of the model also showed non-significant autocorrelations (P Box-Ljung (Q) =0.299). The predictions by the optimum ARIMA model adequately captured the pattern in the data and exhibited two peaks of activity over the forecast interval, including a major peak during April to June, and again a light peak for September to November. The ARIMA model proposed in this study can forecast HFMD incidence trend effectively, which could provide useful support for future HFMD prevention and control in the study area. Besides, further observations should be added continually into the modeling data set, and parameters of the models should be adjusted accordingly.

Modeling and forecasting of the under-five mortality rate in Kermanshah province in Iran: a time series analysis.

PubMed

Rostami, Mehran; Jalilian, Abdollah; Hamzeh, Behrooz; Laghaei, Zahra

2015-01-01

The target of the Fourth Millennium Development Goal (MDG-4) is to reduce the rate of under-five mortality by two-thirds between 1990 and 2015. Despite substantial progress towards achieving the target of the MDG-4 in Iran at the national level, differences at the sub-national levels should be taken into consideration. The under-five mortality data available from the Deputy of Public Health, Kermanshah University of Medical Sciences, was used in order to perform a time series analysis of the monthly under-five mortality rate (U5MR) from 2005 to 2012 in Kermanshah province in the west of Iran. After primary analysis, a seasonal auto-regressive integrated moving average model was chosen as the best fitting model based on model selection criteria. The model was assessed and proved to be adequate in describing variations in the data. However, the unexpected presence of a stochastic increasing trend and a seasonal component with a periodicity of six months in the fitted model are very likely to be consequences of poor quality of data collection and reporting systems. The present work is the first attempt at time series modeling of the U5MR in Iran, and reveals that improvement of under-five mortality data collection in health facilities and their corresponding systems is a major challenge to fully achieving the MGD-4 in Iran. Studies similar to the present work can enhance the understanding of the invisible patterns in U5MR, monitor progress towards the MGD-4, and predict the impact of future variations on the U5MR.

A comment on priors for Bayesian occupancy models.

PubMed

Northrup, Joseph M; Gerber, Brian D

2018-01-01

Understanding patterns of species occurrence and the processes underlying these patterns is fundamental to the study of ecology. One of the more commonly used approaches to investigate species occurrence patterns is occupancy modeling, which can account for imperfect detection of a species during surveys. In recent years, there has been a proliferation of Bayesian modeling in ecology, which includes fitting Bayesian occupancy models. The Bayesian framework is appealing to ecologists for many reasons, including the ability to incorporate prior information through the specification of prior distributions on parameters. While ecologists almost exclusively intend to choose priors so that they are "uninformative" or "vague", such priors can easily be unintentionally highly informative. Here we report on how the specification of a "vague" normally distributed (i.e., Gaussian) prior on coefficients in Bayesian occupancy models can unintentionally influence parameter estimation. Using both simulated data and empirical examples, we illustrate how this issue likely compromises inference about species-habitat relationships. While the extent to which these informative priors influence inference depends on the data set, researchers fitting Bayesian occupancy models should conduct sensitivity analyses to ensure intended inference, or employ less commonly used priors that are less informative (e.g., logistic or t prior distributions). We provide suggestions for addressing this issue in occupancy studies, and an online tool for exploring this issue under different contexts.

On the dangers of model complexity without ecological justification in species distribution modeling

Treesearch

David M. Bell; Daniel R. Schlaepfer

2016-01-01

Although biogeographic patterns are the product of complex ecological processes, the increasing com-plexity of correlative species distribution models (SDMs) is not always motivated by ecological theory,but by model fit. The validity of model projections, such as shifts in a species’ climatic niche, becomesquestionable particularly during extrapolations, such as for...

Evaluation of marginal and internal gaps of metal ceramic crowns obtained from conventional impressions and casting techniques with those obtained from digital techniques.

PubMed

Rai, Rathika; Kumar, S Arun; Prabhu, R; Govindan, Ranjani Thillai; Tanveer, Faiz Mohamed

2017-01-01

Accuracy in fit of cast metal restoration has always remained as one of the primary factors in determining the success of the restoration. A well-fitting restoration needs to be accurate both along its margin and with regard to its internal surface. The aim of the study is to evaluate the marginal fit of metal ceramic crowns obtained by conventional inlay casting wax pattern using conventional impression with the metal ceramic crowns obtained by computer-aided design and computer-aided manufacturing (CAD/CAM) technique using direct and indirect optical scanning. This in vitro study on preformed custom-made stainless steel models with former assembly that resembles prepared tooth surfaces of standardized dimensions comprised three groups: the first group included ten samples of metal ceramic crowns fabricated with conventional technique, the second group included CAD/CAM-milled direct metal laser sintering (DMLS) crowns using indirect scanning, and the third group included DMLS crowns fabricated by direct scanning of the stainless steel model. The vertical marginal gap and the internal gap were evaluated with the stereomicroscope (Zoomstar 4); post hoc Turkey's test was used for statistical analysis. One-way analysis of variance method was used to compare the mean values. Metal ceramic crowns obtained from direct optical scanning showed the least marginal and internal gap when compared to the castings obtained from inlay casting wax and indirect optical scanning. Indirect and direct optical scanning had yielded results within clinically acceptable range.

Structural differences within negative and depressive syndrome dimensions in schizophrenia, organic brain disease, and major depression: A confirmatory factor analysis of the positive and negative syndrome scale.

PubMed

Eisenberg, Daniel P; Aniskin, Dmitry B; White, Leonard; Stein, Judith A; Harvey, Philip D; Galynker, Igor I

2009-01-01

The emerging dimensional approach to classification and treatment of psychiatric disorders calls for better understanding of diagnosis-related variations in psychiatric syndromes and for proper validation of psychometric scales used for the evaluation of those syndromes. This study tested the hypothesis that negative and depressive syndromes as measured by the Positive and Negative Syndrome Scale (PANSS) are consistent across different diagnoses. We administered the PANSS to subjects with schizophrenia (n = 305), organic brain disease (OBD, n = 66) and major depressive disorder (MDD, n = 75). Confirmatory factor analysis (CFA) was used to establish if the PANSS items for negative symptoms and for depression fit the hypothesized factor structure and if the item factor loadings were similar among the diagnostic groups. The negative and depressive symptom subscales fit well according to a variety of fit indexes for all groups individually after some modest model modification. However, multisample modeling procedures indicated that the pattern of factor loadings was significantly different among the groups in most cases. The results of this study indicate diagnosis-related variations in the negative and depressive syndrome dimensions in schizophrenia, OBD and MDD. These results also validate limited use of the PANSS for evaluation of negative and depressive syndromes in disorders other than schizophrenia. Larger studies are warranted to further evaluate clinical and nosologic significance of diagnostic categories, dimensions and structures of psychiatric syndromes. 2009 S. Karger AG, Basel.

Determining the hydraulic and fracture properties of the Coal Seam Gas well by numerical modelling and GLUE analysis

NASA Astrophysics Data System (ADS)

Askarimarnani, Sara; Willgoose, Garry; Fityus, Stephen

2017-04-01

Coal seam gas (CSG) is a form of natural gas that occurs in some coal seams. Coal seams have natural fractures with dual-porosity systems and low permeability. In the CSG industry, hydraulic fracturing is applied to increase the permeability and extract the gas more efficiently from the coal seam. The industry claims that it can design fracking patterns. Whether this is true or not, the public (and regulators) requires assurance that once a well has been fracked that the fracking has occurred according to plan and that the fracked well is safe. Thus defensible post-fracking testing methodologies for gas generating wells are required. In 2009 a fracked well HB02, owned by AGL, near Broke, NSW, Australia was subjected to "traditional" water pump-testing as part of this assurance process. Interpretation with well Type Curves and simple single phase (i.e. only water, no gas) highlighted deficiencies in traditional water well approaches with a systemic deviation from the qualitative characteristic of well drawdown curves (e.g. concavity versus convexity of drawdown with time). Accordingly a multiphase (i.e. water and methane) model of the well was developed and compared with the observed data. This paper will discuss the results of this multiphase testing using the TOUGH2 model and its EOS7C constitutive model. A key objective was to test a methodology, based on GLUE monte-carlo calibration technique, to calibrate the characteristics of the frack using the well test drawdown curve. GLUE involves a sensitivity analysis of how changes in the fracture properties change the well hydraulics through and analysis of the drawdown curve and changes in the cone of depression. This was undertaken by changing the native coal, fracture, and gas parameters to see how changing those parameters changed the match between simulations and the observed well drawdown. Results from the GLUE analysis show how much information is contained in the well drawdown curve for estimating field scale coal and gas generation properties, the fracture geometry, and the proponent characteristics. The results with the multiphase model show a better match to the drawdown than using a single phase model but the differences between the best fit drawdowns were small, and smaller than the difference between the best fit and field data. However, the parameters derived to generate these best fits for each model were very different. We conclude that while satisfactory fits with single phase groundwater models (e.g. MODFLOW, FEFLOW) can be achieved the parameters derived will not be realistic, with potential implications for drawdowns and water yields for gas field modelling. Multiphase models are thus required and we will discuss some of the limitations of TOUGH2 for the CSG problem.

In silico evolution of biochemical networks

NASA Astrophysics Data System (ADS)

Francois, Paul

2010-03-01

We use computational evolution to select models of genetic networks that can be built from a predefined set of parts to achieve a certain behavior. Selection is made with the help of a fitness defining biological functions in a quantitative way. This fitness has to be specific to a process, but general enough to find processes common to many species. Computational evolution favors models that can be built by incremental improvements in fitness rather than via multiple neutral steps or transitions through less fit intermediates. With the help of these simulations, we propose a kinetic view of evolution, where networks are rapidly selected along a fitness gradient. This mathematics recapitulates Darwin's original insight that small changes in fitness can rapidly lead to the evolution of complex structures such as the eye, and explain the phenomenon of convergent/parallel evolution of similar structures in independent lineages. We will illustrate these ideas with networks implicated in embryonic development and patterning of vertebrates and primitive insects.

Species area relationships in mediterranean-climate plant communities

USGS Publications Warehouse

Keeley, Jon E.; Fotheringham, C.J.

2003-01-01

Aim To determine the best-fit model of species–area relationships for Mediterranean-type plant communities and evaluate how community structure affects these species–area models.Location Data were collected from California shrublands and woodlands and compared with literature reports for other Mediterranean-climate regions.Methods The number of species was recorded from 1, 100 and 1000 m2 nested plots. Best fit to the power model or exponential model was determined by comparing adjusted r2 values from the least squares regression, pattern of residuals, homoscedasticity across scales, and semi-log slopes at 1–100 m2 and 100–1000 m2. Dominance–diversity curves were tested for fit to the lognormal model, MacArthur's broken stick model, and the geometric and harmonic series.Results Early successional Western Australia and California shrublands represented the extremes and provide an interesting contrast as the exponential model was the best fit for the former, and the power model for the latter, despite similar total species richness. We hypothesize that structural differences in these communities account for the different species–area curves and are tied to patterns of dominance, equitability and life form distribution. Dominance–diversity relationships for Western Australian heathlands exhibited a close fit to MacArthur's broken stick model, indicating more equitable distribution of species. In contrast, Californian shrublands, both postfire and mature stands, were best fit by the geometric model indicating strong dominance and many minor subordinate species. These regions differ in life form distribution, with annuals being a major component of diversity in early successional Californian shrublands although they are largely lacking in mature stands. Both young and old Australian heathlands are dominated by perennials, and annuals are largely absent. Inherent in all of these ecosystems is cyclical disequilibrium caused by periodic fires. The potential for community reassembly is greater in Californian shrublands where only a quarter of the flora resprout, whereas three quarters resprout in Australian heathlands.Other Californian vegetation types sampled include coniferous forests, oak savannas and desert scrub, and demonstrate that different community structures may lead to a similar species–area relationship. Dominance–diversity relationships for coniferous forests closely follow a geometric model whereas associated oak savannas show a close fit to the lognormal model. However, for both communities, species–area curves fit a power model. The primary driver appears to be the presence of annuals. Desert scrub communities illustrate dramatic changes in both species diversity and dominance–diversity relationships in high and low rainfall years, because of the disappearance of annuals in drought years.Main conclusions Species–area curves for immature shrublands in California and the majority of Mediterranean plant communities fit a power function model. Exceptions that fit the exponential model are not because of sampling error or scaling effects, rather structural differences in these communities provide plausible explanations. The exponential species–area model may arise in more than one way. In the highly diverse Australian heathlands it results from a rapid increase in species richness at small scales. In mature California shrublands it results from very depauperate richness at the community scale. In both instances the exponential model is tied to a preponderance of perennials and paucity of annuals. For communities fit by a power model, coefficients z and log c exhibit a number of significant correlations with other diversity parameters, suggesting that they have some predictive value in ecological communities.

Empirical Profiles of Alcohol and Marijuana Use, Drugged Driving, and Risk Perceptions.

PubMed

Arterberry, Brooke J; Treloar, Hayley; McCarthy, Denis M

2017-11-01

The present study sought to inform models of risk for drugged driving through empirically identifying patterns of marijuana use, alcohol use, and related driving behaviors. Perceived dangerousness and consequences of drugged driving were evaluated as putative influences on risk patterns. We used latent profile analysis of survey responses from 897 college students to identify patterns of substance use and drugged driving. We tested the hypotheses that low perceived danger and low perceived likelihood of negative consequences of drugged driving would identify individuals with higher-risk patterns. Findings from the latent profile analysis indicated that a four-profile model provided the best model fit. Low-level engagers had low rates of substance use and drugged driving. Alcohol-centric engagers had higher rates of alcohol use but low rates of marijuana/simultaneous use and low rates of driving after substance use. Concurrent engagers had higher rates of marijuana and alcohol use, simultaneous use, and related driving behaviors, but marijuana-centric/simultaneous engagers had the highest rates of marijuana use, co-use, and related driving behaviors. Those with higher perceived danger of driving while high were more likely to be in the low-level, alcohol-centric, or concurrent engagers' profiles; individuals with higher perceived likelihood of consequences of driving while high were more likely to be in the low-level engagers group. Findings suggested that college students' perceived dangerousness of driving after using marijuana had greater influence on drugged driving behaviors than alcohol-related driving risk perceptions. These results support targeting marijuana-impaired driving risk perceptions in young adult intervention programs.

Marginal fit and photoelastic stress analysis of CAD-CAM and overcast 3-unit implant-supported frameworks.

PubMed

Presotto, Anna Gabriella Camacho; Bhering, Cláudia Lopes Brilhante; Mesquita, Marcelo Ferraz; Barão, Valentim Adelino Ricardo

2017-03-01

Several studies have shown the superiority of computer-assisted design and computer-assisted manufacturing (CAD-CAM) technology compared with conventional casting. However, an advanced technology exists for casting procedures (the overcasting technique), which may serve as an acceptable and affordable alternative to CAD-CAM technology for fabricating 3-unit implant-supported fixed dental prostheses (FDPs). The purpose of this in vitro study was to evaluate, using quantitative photoelastic analysis, the effect of the prosthetic framework fabrication method (CAD-CAM and overcasting) on the marginal fit and stress transmitted to implants. The correlation between marginal fit and stress was also investigated. Three-unit implant-supported FDP frameworks were made using the CAD-CAM (n=10) and overcasting (n=10) methods. The frameworks were waxed to simulate a mandibular first premolar (PM region) to first molar (M region) FDP using overcast mini-abutment cylinders. The wax patterns were overcast (overcast experimental group) or scanned to obtain the frameworks (CAD-CAM control group). All frameworks were fabricated from cobalt-chromium (CoCr) alloy. The marginal fit was analyzed according to the single-screw test protocol, obtaining an average value for each region (M and PM) and each framework. The frameworks were tightened for the photoelastic model with standardized 10-Ncm torque. Stress was measured by quantitative photoelastic analysis. The results were submitted to the Student t test, 2-way ANOVA, and Pearson correlation test (α=.05). The framework fabrication method (FM) and evaluation site (ES; M and PM regions) did not affect the marginal fit values (P=.559 for FM and P=.065 for ES) and stress (P=.685 for FM and P=.468 for ES) in the implant-supported system. Positive correlations between marginal fit and stress were observed (CAD-CAM: r=0.922; P<.001; overcast: r=0.908; P<.001). CAD-CAM and overcasting methods present similar marginal fit and stress values for 3-unit FDP frameworks. The decreased marginal fit of frameworks induces greater stress in the implant-supported system. Copyright © 2016 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

Premium analysis for copula model: A case study for Malaysian motor insurance claims

NASA Astrophysics Data System (ADS)

Resti, Yulia; Ismail, Noriszura; Jaaman, Saiful Hafizah

2014-06-01

This study performs premium analysis for copula models with regression marginals. For illustration purpose, the copula models are fitted to the Malaysian motor insurance claims data. In this study, we consider copula models from Archimedean and Elliptical families, and marginal distributions of Gamma and Inverse Gaussian regression models. The simulated results from independent model, which is obtained from fitting regression models separately to each claim category, and dependent model, which is obtained from fitting copula models to all claim categories, are compared. The results show that the dependent model using Frank copula is the best model since the risk premiums estimated under this model are closely approximate to the actual claims experience relative to the other copula models.

Conservation success as a function of good alignment of social and ecological structures and processes.

PubMed

Bodin, Orjan; Crona, Beatrice; Thyresson, Matilda; Golz, Anna-Lea; Tengö, Maria

2014-10-01

How to create and adjust governing institutions so that they align (fit) with complex ecosystem processes and structures across scales is an issue of increasing concern in conservation. It is argued that lack of such social-ecological fit makes governance and conservation difficult, yet progress in explicitly defining and rigorously testing what constitutes a good fit has been limited. We used a novel modeling approach and data from case studies of fishery and forest conservation to empirically test presumed relationships between conservation outcomes and certain patterns of alignment of social-ecological interdependences. Our approach made it possible to analyze conservation outcome on a systems level while also providing information on how individual actors are positioned in the complex web of social-ecological interdependencies. We found that when actors who shared resources were also socially linked, conservation at the level of the whole social-ecological system was positively affected. When the scales at which individual actors used resources and the scale at which ecological resources were interconnected to other ecological resources were aligned through tightened feedback loops, conservation outcome was better than when they were not aligned. The analysis of individual actors' positions in the web of social-ecological interdependencies was helpful in understanding why a system has a certain level of social-ecological fit. Results of analysis of positions showed that different actors contributed in very different ways to achieve a certain fit and revealed some underlying difference between the actors, for example in terms of actors' varying rights to access and use different ecological resources. © 2014 Society for Conservation Biology.

Risk factors and short-term projections for serotype-1 poliomyelitis incidence in Pakistan: A spatiotemporal analysis.

PubMed

Molodecky, Natalie A; Blake, Isobel M; O'Reilly, Kathleen M; Wadood, Mufti Zubair; Safdar, Rana M; Wesolowski, Amy; Buckee, Caroline O; Bandyopadhyay, Ananda S; Okayasu, Hiromasa; Grassly, Nicholas C

2017-06-01

Pakistan currently provides a substantial challenge to global polio eradication, having contributed to 73% of reported poliomyelitis in 2015 and 54% in 2016. A better understanding of the risk factors and movement patterns that contribute to poliovirus transmission across Pakistan would support evidence-based planning for mass vaccination campaigns. We fit mixed-effects logistic regression models to routine surveillance data recording the presence of poliomyelitis associated with wild-type 1 poliovirus in districts of Pakistan over 6-month intervals between 2010 to 2016. To accurately capture the force of infection (FOI) between districts, we compared 6 models of population movement (adjacency, gravity, radiation, radiation based on population density, radiation based on travel times, and mobile-phone based). We used the best-fitting model (based on the Akaike Information Criterion [AIC]) to produce 6-month forecasts of poliomyelitis incidence. The odds of observing poliomyelitis decreased with improved routine or supplementary (campaign) immunisation coverage (multivariable odds ratio [OR] = 0.75, 95% confidence interval [CI] 0.67-0.84; and OR = 0.75, 95% CI 0.66-0.85, respectively, for each 10% increase in coverage) and increased with a higher rate of reporting non-polio acute flaccid paralysis (AFP) (OR = 1.13, 95% CI 1.02-1.26 for a 1-unit increase in non-polio AFP per 100,000 persons aged <15 years). Estimated movement of poliovirus-infected individuals was associated with the incidence of poliomyelitis, with the radiation model of movement providing the best fit to the data. Six-month forecasts of poliomyelitis incidence by district for 2013-2016 showed good predictive ability (area under the curve range: 0.76-0.98). However, although the best-fitting movement model (radiation) was a significant determinant of poliomyelitis incidence, it did not improve the predictive ability of the multivariable model. Overall, in Pakistan the risk of polio cases was predicted to reduce between July-December 2016 and January-June 2017. The accuracy of the model may be limited by the small number of AFP cases in some districts. Spatiotemporal variation in immunization performance and population movement patterns are important determinants of historical poliomyelitis incidence in Pakistan; however, movement dynamics were less influential in predicting future cases, at a time when the polio map is shrinking. Results from the regression models we present are being used to help plan vaccination campaigns and transit vaccination strategies in Pakistan.

Risk factors and short-term projections for serotype-1 poliomyelitis incidence in Pakistan: A spatiotemporal analysis

PubMed Central

Molodecky, Natalie A.; Buckee, Caroline O.; Okayasu, Hiromasa; Grassly, Nicholas C.

2017-01-01

Background Pakistan currently provides a substantial challenge to global polio eradication, having contributed to 73% of reported poliomyelitis in 2015 and 54% in 2016. A better understanding of the risk factors and movement patterns that contribute to poliovirus transmission across Pakistan would support evidence-based planning for mass vaccination campaigns. Methods and findings We fit mixed-effects logistic regression models to routine surveillance data recording the presence of poliomyelitis associated with wild-type 1 poliovirus in districts of Pakistan over 6-month intervals between 2010 to 2016. To accurately capture the force of infection (FOI) between districts, we compared 6 models of population movement (adjacency, gravity, radiation, radiation based on population density, radiation based on travel times, and mobile-phone based). We used the best-fitting model (based on the Akaike Information Criterion [AIC]) to produce 6-month forecasts of poliomyelitis incidence. The odds of observing poliomyelitis decreased with improved routine or supplementary (campaign) immunisation coverage (multivariable odds ratio [OR] = 0.75, 95% confidence interval [CI] 0.67–0.84; and OR = 0.75, 95% CI 0.66–0.85, respectively, for each 10% increase in coverage) and increased with a higher rate of reporting non-polio acute flaccid paralysis (AFP) (OR = 1.13, 95% CI 1.02–1.26 for a 1-unit increase in non-polio AFP per 100,000 persons aged <15 years). Estimated movement of poliovirus-infected individuals was associated with the incidence of poliomyelitis, with the radiation model of movement providing the best fit to the data. Six-month forecasts of poliomyelitis incidence by district for 2013–2016 showed good predictive ability (area under the curve range: 0.76–0.98). However, although the best-fitting movement model (radiation) was a significant determinant of poliomyelitis incidence, it did not improve the predictive ability of the multivariable model. Overall, in Pakistan the risk of polio cases was predicted to reduce between July–December 2016 and January–June 2017. The accuracy of the model may be limited by the small number of AFP cases in some districts. Conclusions Spatiotemporal variation in immunization performance and population movement patterns are important determinants of historical poliomyelitis incidence in Pakistan; however, movement dynamics were less influential in predicting future cases, at a time when the polio map is shrinking. Results from the regression models we present are being used to help plan vaccination campaigns and transit vaccination strategies in Pakistan. PMID:28604777

Pattern formation in individual-based systems with time-varying parameters

NASA Astrophysics Data System (ADS)

Ashcroft, Peter; Galla, Tobias

2013-12-01

We study the patterns generated in finite-time sweeps across symmetry-breaking bifurcations in individual-based models. Similar to the well-known Kibble-Zurek scenario of defect formation, large-scale patterns are generated when model parameters are varied slowly, whereas fast sweeps produce a large number of small domains. The symmetry breaking is triggered by intrinsic noise, originating from the discrete dynamics at the microlevel. Based on a linear-noise approximation, we calculate the characteristic length scale of these patterns. We demonstrate the applicability of this approach in a simple model of opinion dynamics, a model in evolutionary game theory with a time-dependent fitness structure, and a model of cell differentiation. Our theoretical estimates are confirmed in simulations. In further numerical work, we observe a similar phenomenon when the symmetry-breaking bifurcation is triggered by population growth.

Western and Mediterranean Dietary Patterns and Physical Activity and Fitness among Spanish Older Adults.

PubMed

Bibiloni, Maria Del Mar; Julibert, Alicia; Argelich, Emma; Aparicio-Ugarriza, Raquel; Palacios, Gonzalo; Pons, Antoni; Gonzalez-Gross, Marcela; Tur, Josep A

2017-07-06

Objectives: To assess prevailing food patterns, and its association with physical activity and fitness among Spanish older adults. Methods: Cross-sectional study in Spain, collecting data from a sample ( n = 380; 54% female) aged 55-80 years (men) and 60-80 years (women) with no previously documented cardiovascular disease. Body weight, body fat and waist circumference were assessed. Physical activity performed was measured using the Minnesota Leisure-time Physical Activity Questionnaire (LTPA). Physical fitness was assessed using a validated physical fitness test battery. Food consumption was assessed by a validated semi-quantitative food-frequency questionnaire. Factor analysis identified two major dietary food patterns: "Western" (WDP) and "Mediterranean" (MDP) dietary patterns. Results: Participants in MDP's fourth quartile were classified in the second (men) and third (men and women) tertile of LTPA. After adjusting for age, body fat, waist-to-height ratio, and METs, in both sexes, a negative significant association was found between 30-s Chair stand and 6-min walking test, a positive significant association was found between 30-m Gait speed and 8-foot Time Up-and-Go (except in men) tests with WDP. The 30-m Gait speed test was negatively associated with MDP in men. Conclusions: MDP is associated with more time spent on LTPA, and this association was independent of body composition and a fast gait speed in men. WDP is associated with slower gait speed and lower body strength, agility and aerobic endurance. MDP has protective effect on healthy physical fitness, and WDP may be a contributor to frailty.

Application of x-ray absorption fine structure (XAFS) to local-order analysis in Fe-Cr maghemite-like materials

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

Montero-Cabrera, M. E., E-mail: elena.montero@cimav.edu.mx; Fuentes-Cobas, L. E.; Macías-Ríos, E.

2015-07-23

The maghemite-like oxide system γ-Fe{sub 2-x}Cr{sub x}O{sub 3} (x=0.75, 1 and 1.25) was studied by X-ray absorption fine structure (XAFS) and by synchrotron radiation X-ray diffraction (XRD). Measurements were performed at the Stanford Synchrotron Radiation Lightsource at room temperature, at beamlines 2-1, 2-3 and 4-3. High-resolution XRD patterns were processed by means of the Rietveld method. In cases of atoms being neighbors in the Periodic Table, the order/disorder degree of the considered solutions is indiscernible by “normal” (absence of “anomalous scattering”) diffraction experiments. Thus, maghemite-like materials were investigated by XAFS in both Fe and Cr K-edges to clarify, via short-rangemore » structure characterization, the local ordering of the investigated system. Athena and Artemis graphic user interfaces for IFEFFIT and FEFF8.4 codes were employed for XAFS spectra interpretation. Pre-edge decomposition and theoretical modeling of X-ray absorption near edge structure (XANES) transitions were performed. By analysis of the Cr K-edge XANES, it has been confirmed that Cr is located in an octahedral environment. Fitting of the extended X-ray absorption fine structure (EXAFS) spectra was performed under the consideration that the central atom of Fe is allowed to occupy octa- and tetrahedral positions, while Cr occupies only octahedral ones. Coordination number of neighboring atoms, interatomic distances and their quadratic deviation average were determined for x=1, by fitting simultaneously the EXAFS spectra of both Fe and Cr K-edges. The results of fitting the experimental spectra with theoretical standards showed that the cation vacancies tend to follow a regular pattern within the structure of the iron-chromium maghemite (FeCrO{sub 3})« less

Patterns of Weight Change in Black Americans: Pooled Analysis from Three Behavioral Weight Loss Trials

PubMed Central

Morales, Knashawn H.; Kumanyika, Shiriki K.; Fassbender, Jennifer E.; Good, Jerene; Localio, A. Russell; Wadden, Thomas A.

2014-01-01

Objective Differentiating trajectories of weight change and identifying associated baseline predictors can provide insights for improving behavioral obesity treatment outcomes. Design and Methods Secondary, observational analyses using growth mixture models were conducted in pooled data for 604 black American, primarily female adults in three completed clinical trials. Covariates of identified patterns were evaluated. Results The best fitting model identified three patterns over 2 years: 1) mean weight loss of approximately 2 kg (n=519); 2) mean weight loss of approximately 3 kg at 1 year, followed by ~ 4 kg regain (n=61); and 3) mean weight loss of approximately 20 kg at 1 year followed by ~ 4 kg regain (n=24, with 23 from one study). In final multivariate analyses, higher BMI predicted having pattern 2 (OR[95% CI]) 1.10[1.03, 1.17]) or 3 (OR[95% CI] 1.42[1.25, 1.63]), and higher dietary fat score was predictive of a lower odds of having patterns 2 (OR[95% CI] 0.37[0.15, 0.94]) or 3 (OR[95% CI] 0.23[0.07, 0.79]). Conclusions Findings were consistent with moderate, clinically non-significant weight loss as the predominant pattern across all studies. Results underscore the need to develop novel and more carefully targeted and tailored approaches to facilitating weight loss in black American adults. PMID:25251464

Association between dietary patterns and mental disorders in pregnant women in Southern Brazil.

PubMed

Paskulin, Jéssica T A; Drehmer, Michele; Olinto, Maria T; Hoffmann, Juliana F; Pinheiro, Andréa P; Schmidt, Maria I; Nunes, Maria A

2017-01-01

To evaluate the association between dietary patterns and mental disorders among pregnant women in southern Brazil. Cross-sectional study with 712 pregnant women recruited from the Study of Food Intake and Eating Behaviors in Pregnancy (ECCAGe). Food intake assessment was performed using the Food Frequency Questionnaire. Dietary patterns were identified by cluster analysis. The Primary Care Evaluation of Mental Disorders (PRIME-MD) was used to evaluate participants' mental health. Poisson regression models with robust variance were fitted to estimate prevalence ratios (PR). In the adjusted models, there was a high prevalence of major depressive disorder among women with low fruit intake (43%, PR 1.43, 95%CI 1.04-1.95) and high sweets and sugars intake (91%, PR 1.91, 95%CI 1.19-3.07). Women with a common-Brazilian dietary pattern had higher prevalence of major depressive disorder compared to those with a varied consumption pattern (PR 1.43, 95%CI 1.01-2.02). Low intake of beans was significantly associated with generalized anxiety disorder (PR 1.40, 95%CI 1.01-1.93). Low consumption of fruits and beans and intake of the common-Brazilian dietary pattern during pregnancy were associated with higher prevalence of mental disorders. These results reinforce the importance of an adequate dietary intake to ensure better mental health in pregnancy.

Some considerations on the use of ecological models to predict species' geographic distributions

USGS Publications Warehouse

Peterjohn, B.G.

2001-01-01

Peterson (2001) used Genetic Algorithm for Rule-set Prediction (GARP) models to predict distribution patterns from Breeding Bird Survey (BBS) data. Evaluations of these models should consider inherent limitations of BBS data: (1) BBS methods may not sample species and habitats equally; (2) using BBS data for both model development and testing may overlook poor fit of some models; and (3) BBS data may not provide the desired spatial resolution or capture temporal changes in species distributions. The predictive value of GARP models requires additional study, especially comparisons with distribution patterns from independent data sets. When employed at appropriate temporal and geographic scales, GARP models show considerable promise for conservation biology applications but provide limited inferences concerning processes responsible for the observed patterns.

Television Content Viewing Patterns: Some Clues from Societal Norms.

ERIC Educational Resources Information Center

McDonald, Daniel G.; Glynn, Carroll J.

Focusing on how television viewing fits into a general model of consumer consumption patterns, a study examined (1) the extent to which the viewing of certain television content can be considered a "norm" of society, (2) similarities and differences between the norms for adults and those for children, and (3) some of the antecedents of…

Analysis of fMRI data using noise-diffusion network models: a new covariance-coding perspective.

PubMed

Gilson, Matthieu

2018-04-01

Since the middle of the 1990s, studies of resting-state fMRI/BOLD data have explored the correlation patterns of activity across the whole brain, which is referred to as functional connectivity (FC). Among the many methods that have been developed to interpret FC, a recently proposed model-based approach describes the propagation of fluctuating BOLD activity within the recurrently connected brain network by inferring the effective connectivity (EC). In this model, EC quantifies the strengths of directional interactions between brain regions, viewed from the proxy of BOLD activity. In addition, the tuning procedure for the model provides estimates for the local variability (input variances) to explain how the observed FC is generated. Generalizing, the network dynamics can be studied in the context of an input-output mapping-determined by EC-for the second-order statistics of fluctuating nodal activities. The present paper focuses on the following detection paradigm: observing output covariances, how discriminative is the (estimated) network model with respect to various input covariance patterns? An application with the model fitted to experimental fMRI data-movie viewing versus resting state-illustrates that changes in local variability and changes in brain coordination go hand in hand.

Trial-dependent psychometric functions accounting for perceptual learning in 2-AFC discrimination tasks.

PubMed

Kattner, Florian; Cochrane, Aaron; Green, C Shawn

2017-09-01

The majority of theoretical models of learning consider learning to be a continuous function of experience. However, most perceptual learning studies use thresholds estimated by fitting psychometric functions to independent blocks, sometimes then fitting a parametric function to these block-wise estimated thresholds. Critically, such approaches tend to violate the basic principle that learning is continuous through time (e.g., by aggregating trials into large "blocks" for analysis that each assume stationarity, then fitting learning functions to these aggregated blocks). To address this discrepancy between base theory and analysis practice, here we instead propose fitting a parametric function to thresholds from each individual trial. In particular, we implemented a dynamic psychometric function whose parameters were allowed to change continuously with each trial, thus parameterizing nonstationarity. We fit the resulting continuous time parametric model to data from two different perceptual learning tasks. In nearly every case, the quality of the fits derived from the continuous time parametric model outperformed the fits derived from a nonparametric approach wherein separate psychometric functions were fit to blocks of trials. Because such a continuous trial-dependent model of perceptual learning also offers a number of additional advantages (e.g., the ability to extrapolate beyond the observed data; the ability to estimate performance on individual critical trials), we suggest that this technique would be a useful addition to each psychophysicist's analysis toolkit.

Analysis of randomly shaped puzzle-fragment-particles via their chord length distribution

NASA Astrophysics Data System (ADS)

Gille, Wilfried

2012-12-01

The chord length distribution (CLD) of an ensemble (E) of homogeneous, hard, compact, randomly shaped fragment particles Fi is studied. The practical problem whether such Fi can fit together like the pieces of a puzzle can be solved, based on the experimental information involved in a small-angle scattering (SAS) experiment. The sample material of such an experiment is the isotropic particle ensemble E, consisting of many separate Fi. Let L0 be the maximum diameter of the largest piece (of the largest Fi). The one by one investigation of F1, F2, F3 ... in a quasi-diluted arrangement (or in the separate state) yields the characteristic scattering pattern of E. This pattern fixes the mean CLD of the Fi. The approach is based on the construction of a 50 % volume fraction model from the Fi given. A fitting function Φ1/2(r,L0),(0≤r≪L0), has been introduced (limiting case r→0+). If Φ1/2(0+,2ṡL0) = 1, the origin of the Fi is a destroyed mosaic. 'Dead Leaves' mosaics are a special case of the approach. Hereby, Φ1/2(r)⇒Φ(r,L0).

A General Population Genetic Framework for Antagonistic Selection That Accounts for Demography and Recurrent Mutation

PubMed Central

Connallon, Tim; Clark, Andrew G.

2012-01-01

Antagonistic selection—where alleles at a locus have opposing effects on male and female fitness (“sexual antagonism”) or between components of fitness (“antagonistic pleiotropy”)—might play an important role in maintaining population genetic variation and in driving phylogenetic and genomic patterns of sexual dimorphism and life-history evolution. While prior theory has thoroughly characterized the conditions necessary for antagonistic balancing selection to operate, we currently know little about the evolutionary interactions between antagonistic selection, recurrent mutation, and genetic drift, which should collectively shape empirical patterns of genetic variation. To fill this void, we developed and analyzed a series of population genetic models that simultaneously incorporate these processes. Our models identify two general properties of antagonistically selected loci. First, antagonistic selection inflates heterozygosity and fitness variance across a broad parameter range—a result that applies to alleles maintained by balancing selection and by recurrent mutation. Second, effective population size and genetic drift profoundly affect the statistical frequency distributions of antagonistically selected alleles. The “efficacy” of antagonistic selection (i.e., its tendency to dominate over genetic drift) is extremely weak relative to classical models, such as directional selection and overdominance. Alleles meeting traditional criteria for strong selection (Nes >> 1, where Ne is the effective population size, and s is a selection coefficient for a given sex or fitness component) may nevertheless evolve as if neutral. The effects of mutation and demography may generate population differences in overall levels of antagonistic fitness variation, as well as molecular population genetic signatures of balancing selection. PMID:22298707

A general population genetic framework for antagonistic selection that accounts for demography and recurrent mutation.

PubMed

Connallon, Tim; Clark, Andrew G

2012-04-01

Antagonistic selection--where alleles at a locus have opposing effects on male and female fitness ("sexual antagonism") or between components of fitness ("antagonistic pleiotropy")--might play an important role in maintaining population genetic variation and in driving phylogenetic and genomic patterns of sexual dimorphism and life-history evolution. While prior theory has thoroughly characterized the conditions necessary for antagonistic balancing selection to operate, we currently know little about the evolutionary interactions between antagonistic selection, recurrent mutation, and genetic drift, which should collectively shape empirical patterns of genetic variation. To fill this void, we developed and analyzed a series of population genetic models that simultaneously incorporate these processes. Our models identify two general properties of antagonistically selected loci. First, antagonistic selection inflates heterozygosity and fitness variance across a broad parameter range--a result that applies to alleles maintained by balancing selection and by recurrent mutation. Second, effective population size and genetic drift profoundly affect the statistical frequency distributions of antagonistically selected alleles. The "efficacy" of antagonistic selection (i.e., its tendency to dominate over genetic drift) is extremely weak relative to classical models, such as directional selection and overdominance. Alleles meeting traditional criteria for strong selection (N(e)s > 1, where N(e) is the effective population size, and s is a selection coefficient for a given sex or fitness component) may nevertheless evolve as if neutral. The effects of mutation and demography may generate population differences in overall levels of antagonistic fitness variation, as well as molecular population genetic signatures of balancing selection.

Environmental Factors Can Influence Mitochondrial Inheritance in the Saccharomyces Yeast Hybrids

PubMed Central

Hsu, Yu-Yi; Chou, Jui-Yu

2017-01-01

Mitochondria play a critical role in the generation of metabolic energy and are crucial for eukaryotic cell survival and proliferation. In most sexual eukaryotes, mitochondrial DNA (mtDNA) is inherited from only one parent in non-Mendelian inheritance in contrast to the inheritance of nuclear DNA. The model organism Saccharomyces cerevisiae is commonly used to study mitochondrial biology. It has two mating types: MATa and MATα. Previous studies have suggested that the mtDNA inheritance patterns in hybrid diploid cells depend on the genetic background of parental strains. However, the underlying mechanisms remain unclear. To elucidate the mechanisms, we examined the effects of environmental factors on the mtDNA inheritance patterns in hybrids obtained by crossing S. cerevisiae with its close relative S. paradoxus. The results demonstrated that environmental factors can influence mtDNA transmission in hybrid diploids, and that the inheritance patterns are strain dependent. The fitness competition assay results showed that the fitness differences can explain the mtDNA inheritance patterns under specific conditions. However, in this study, we found that fitness differences cannot fully be explained by mitochondrial activity in hybrids under stress conditions. PMID:28081193

Identifying seasonal and temporal trends in the pressures experienced by hospitals related to unscheduled care.

PubMed

Walker, N J; Van Woerden, H C; Kiparoglou, V; Yang, Y

2016-07-26

As part of an electronic dashboard operated by Public Health Wales, senior managers at hospitals in Wales report daily "escalation" scores which reflect management opinion on the pressure a hospital is experiencing and ability to meet ongoing demand with respect to unscheduled care. An analysis was undertaken of escalation scores returned for 18 hospitals in Wales between the years 2006 and 2014 inclusive, with a view to identifying systematic temporal patterns in pressure experienced by hospitals in relation to unscheduled care. Exploratory data analysis indicated the presence of within-year cyclicity in average daily scores over all hospitals. In order to quantify this cyclicity, a Generalised Linear Mixed Model was fitted which incorporated a trigonometric function (sine and cosine) to capture within-year change in escalation. In addition, a 7-level categorical day of the week effect was fitted as well as a 3-level categorical Christmas holiday variable based on patterns observed in exploration of the raw data. All of the main effects investigated were found to be statistically significant. Firstly, significant differences emerged in terms of overall pressure reported by individual hospitals. Furthermore, escalation scores were found to vary systematically within-year in a wave-like fashion for all hospitals (but not between hospitals) with the period of highest pressure consistently observed to occur in winter and lowest pressure in summer. In addition to this annual variation, pressure reported by hospitals was also found to be influenced by day of the week (low at weekends, high early in the working week) and especially low over the Christmas period but high immediately afterwards. Whilst unpredictable to a degree, quantifiable pressure experienced by hospitals can be anticipated according to models incorporating systematic temporal patterns. In the context of finite resources for healthcare services, these findings could optimise staffing schedules and inform resource utilisation.

Music in film and animation: experimental semiotics applied to visual, sound and musical structures

NASA Astrophysics Data System (ADS)

Kendall, Roger A.

2010-02-01

The relationship of music to film has only recently received the attention of experimental psychologists and quantificational musicologists. This paper outlines theory, semiotical analysis, and experimental results using relations among variables of temporally organized visuals and music. 1. A comparison and contrast is developed among the ideas in semiotics and experimental research, including historical and recent developments. 2. Musicological Exploration: The resulting multidimensional structures of associative meanings, iconic meanings, and embodied meanings are applied to the analysis and interpretation of a range of film with music. 3. Experimental Verification: A series of experiments testing the perceptual fit of musical and visual patterns layered together in animations determined goodness of fit between all pattern combinations, results of which confirmed aspects of the theory. However, exceptions were found when the complexity of the stratified stimuli resulted in cognitive overload.

Trajectories of premorbid childhood and adolescent functioning in schizophrenia-spectrum psychoses: A first-episode study.

PubMed

Horton, Leslie E; Tarbox, Sarah I; Olino, Thomas M; Haas, Gretchen L

2015-06-30

Evidence of social and behavioral problems preceding the onset of schizophrenia-spectrum psychoses is consistent with a neurodevelopmental model of these disorders. Here we predict that individuals with a first episode of schizophrenia-spectrum psychoses will evidence one of three patterns of premorbid adjustment: an early deficit, a deteriorating pattern, or adequate or good social adjustment. Participants were 164 (38% female; 31% black) individuals ages 15-50 with a first episode of schizophrenia-spectrum psychoses. Premorbid adjustment was assessed using the Cannon-Spoor Premorbid Adjustment Scale. We compared the fit of a series of growth mixture models to examine premorbid adjustment trajectories, and found the following 3-class model provided the best fit with: a "stable-poor" adjustment class (54%), a "stable-good" adjustment class (39%), and a "deteriorating" adjustment class (7%). Relative to the "stable-good" class, the "stable-poor" class experienced worse negative symptoms at 1-year follow-up, particularly in the social amotivation domain. This represents the first known growth mixture modeling study to examine premorbid functioning patterns in first-episode schizophrenia-spectrum psychoses. Given that the stable-poor adjustment pattern was most prevalent, detection of social and academic maladjustment as early as childhood may help identify people at increased risk for schizophrenia-spectrum psychoses, potentially increasing feasibility of early interventions. Published by Elsevier Ireland Ltd.

Assessment of spatial discordance of primary and effective seed dispersal of European beech (Fagus sylvatica L.) by ecological and genetic methods.

PubMed

Millerón, M; López de Heredia, U; Lorenzo, Z; Alonso, J; Dounavi, A; Gil, L; Nanos, N

2013-03-01

Spatial discordance between primary and effective dispersal in plant populations indicates that postdispersal processes erase the seed rain signal in recruitment patterns. Five different models were used to test the spatial concordance of the primary and effective dispersal patterns in a European beech (Fagus sylvatica) population from central Spain. An ecological method was based on classical inverse modelling (SSS), using the number of seed/seedlings as input data. Genetic models were based on direct kernel fitting of mother-to-offspring distances estimated by a parentage analysis or were spatially explicit models based on the genotype frequencies of offspring (competing sources model and Moran-Clark's Model). A fully integrated mixed model was based on inverse modelling, but used the number of genotypes as input data (gene shadow model). The potential sources of error and limitations of each seed dispersal estimation method are discussed. The mean dispersal distances for seeds and saplings estimated with these five methods were higher than those obtained by previous estimations for European beech forests. All the methods show strong discordance between primary and effective dispersal kernel parameters, and for dispersal directionality. While seed rain was released mostly under the canopy, saplings were established far from mother trees. This discordant pattern may be the result of the action of secondary dispersal by animals or density-dependent effects; that is, the Janzen-Connell effect. © 2013 Blackwell Publishing Ltd.

Modeling of boldine alkaloid adsorption onto pure and propyl-sulfonic acid-modified mesoporous silicas. A comparative study.

PubMed

Geszke-Moritz, Małgorzata; Moritz, Michał

2016-12-01

The present study deals with the adsorption of boldine onto pure and propyl-sulfonic acid-functionalized SBA-15, SBA-16 and mesocellular foam (MCF) materials. Siliceous adsorbents were characterized by nitrogen sorption analysis, transmission electron microscopy (TEM), scanning electron microscopy (SEM), Fourier-transform infrared (FT-IR) spectroscopy and thermogravimetric analysis. The equilibrium adsorption data were analyzed using the Langmuir, Freundlich, Redlich-Peterson, and Temkin isotherms. Moreover, the Dubinin-Radushkevich and Dubinin-Astakhov isotherm models based on the Polanyi adsorption potential were employed. The latter was calculated using two alternative formulas including solubility-normalized (S-model) and empirical C-model. In order to find the best-fit isotherm, both linear regression and nonlinear fitting analysis were carried out. The Dubinin-Astakhov (S-model) isotherm revealed the best fit to the experimental points for adsorption of boldine onto pure mesoporous materials using both linear and nonlinear fitting analysis. Meanwhile, the process of boldine sorption onto modified silicas was described the best by the Langmuir and Temkin isotherms using linear regression and nonlinear fitting analysis, respectively. The values of adsorption energy (below 8kJ/mol) indicate the physical nature of boldine adsorption onto unmodified silicas whereas the ionic interactions seem to be the main force of alkaloid adsorption onto functionalized sorbents (energy of adsorption above 8kJ/mol). Copyright © 2016 Elsevier B.V. All rights reserved.

Filler Network Model of Filled Rubber Materials to Estimate System Size Dependence of Two-Dimensional Small-Angle Scattering Patterns

NASA Astrophysics Data System (ADS)

Hagita, Katsumi; Tominaga, Tetsuo; Hatazoe, Takumi; Sone, Takuo; Takano, Hiroshi

2018-01-01

We proposed a filler network toy (FN-toy) model in order to approximately forecast changes in two-dimensional scattering patterns (2DSPs) of nanoparticles (NPs) in crosslinked polymer networks in ultrasmall-angle X-ray scattering (USAXS) experiments under uniaxial elongation. It enables us to estimate the system size dependence of the 2DSP of the NPs. In the FN-toy model, we considered NPs connected by harmonic springs with excluded-volume interactions among the NPs. In this study, we used the NP configurations estimated by reverse Monte Carlo (RMC) analysis for USAXS data observed in SPring-8 experiments on filler-filled styrene butadiene rubber (SBR). In the FN-toy model, we set a bond between every pair of NPs whose distance is less than Cd, where d is the diameter of an NP and C is a parameter that characterizes network properties. We determined the optimal value of C by comparison with 2DSPs of the NPs at 200% elongation for end-modified and unmodified SBR. These 2DSPs are obtained from the results of a large-scale coarse-grained molecular dynamics (CGMD) simulation with 8,192 NPs and 160 million Lennard-Jones (LJ) particles in previous works. For the end-modified SBR, the fitted value is C = 1.367 and for the unmodified SBR, C = 1.258. The difference in C can be regarded as originating from the difference in polymer-NP interactions. We found that the harmonic potential used in the current FN-toy model is not sufficient to reproduce stress-strain curves and local structures of NPs obtained in the previous CGMD simulations, although the FN-toy model can reproduce the 2DSPs. Using the FN-toy model with the fitted value of C, we calculated the 2DSPs of 65,536 and 524,288 NPs, whose initial positions were estimated by RMC analysis for the same USAXS data. It was found that CGMD simulations with 10 billion LJ particles and 524,288 NPs can provide a high-resolution 2DSP that is comparable to the 2DSP observed in USAXS experiments.

The Probability of Exceedance as a Nonparametric Person-Fit Statistic for Tests of Moderate Length

ERIC Educational Resources Information Center

Tendeiro, Jorge N.; Meijer, Rob R.

2013-01-01

To classify an item score pattern as not fitting a nonparametric item response theory (NIRT) model, the probability of exceedance (PE) of an observed response vector x can be determined as the sum of the probabilities of all response vectors that are, at most, as likely as x, conditional on the test's total score. Vector x is to be considered…

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

USGS Publications Warehouse

Hoos, A.B.; McMahon, G.

2009-01-01

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

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

USGS Publications Warehouse

Hoos, Anne B.; McMahon, Gerard

2009-01-01

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

Human X-chromosome inactivation pattern distributions fit a model of genetically influenced choice better than models of completely random choice

PubMed Central

Renault, Nisa K E; Pritchett, Sonja M; Howell, Robin E; Greer, Wenda L; Sapienza, Carmen; Ørstavik, Karen Helene; Hamilton, David C

2013-01-01

In eutherian mammals, one X-chromosome in every XX somatic cell is transcriptionally silenced through the process of X-chromosome inactivation (XCI). Females are thus functional mosaics, where some cells express genes from the paternal X, and the others from the maternal X. The relative abundance of the two cell populations (X-inactivation pattern, XIP) can have significant medical implications for some females. In mice, the ‘choice' of which X to inactivate, maternal or paternal, in each cell of the early embryo is genetically influenced. In humans, the timing of XCI choice and whether choice occurs completely randomly or under a genetic influence is debated. Here, we explore these questions by analysing the distribution of XIPs in large populations of normal females. Models were generated to predict XIP distributions resulting from completely random or genetically influenced choice. Each model describes the discrete primary distribution at the onset of XCI, and the continuous secondary distribution accounting for changes to the XIP as a result of development and ageing. Statistical methods are used to compare models with empirical data from Danish and Utah populations. A rigorous data treatment strategy maximises information content and allows for unbiased use of unphased XIP data. The Anderson–Darling goodness-of-fit statistics and likelihood ratio tests indicate that a model of genetically influenced XCI choice better fits the empirical data than models of completely random choice. PMID:23652377

Structural equation modeling in environmental risk assessment.

PubMed

Buncher, C R; Succop, P A; Dietrich, K N

1991-01-01

Environmental epidemiology requires effective models that take individual observations of environmental factors and connect them into meaningful patterns. Single-factor relationships have given way to multivariable analyses; simple additive models have been augmented by multiplicative (logistic) models. Each of these steps has produced greater enlightenment and understanding. Models that allow for factors causing outputs that can affect later outputs with putative causation working at several different time points (e.g., linkage) are not commonly used in the environmental literature. Structural equation models are a class of covariance structure models that have been used extensively in economics/business and social science but are still little used in the realm of biostatistics. Path analysis in genetic studies is one simplified form of this class of models. We have been using these models in a study of the health and development of infants who have been exposed to lead in utero and in the postnatal home environment. These models require as input the directionality of the relationship and then produce fitted models for multiple inputs causing each factor and the opportunity to have outputs serve as input variables into the next phase of the simultaneously fitted model. Some examples of these models from our research are presented to increase familiarity with this class of models. Use of these models can provide insight into the effect of changing an environmental factor when assessing risk. The usual cautions concerning believing a model, believing causation has been proven, and the assumptions that are required for each model are operative.

Discrete subgroups of adolescents diagnosed with borderline personality disorder: a latent class analysis of personality features.

PubMed

Ramos, Vera; Canta, Guilherme; de Castro, Filipa; Leal, Isabel

2014-08-01

Research suggests that borderline personality disorder (BPD) can be diagnosed in adolescents and is marked by considerable heterogeneity. This study aimed to identify personality features characterizing adolescents with BPD and possible meaningful patterns of heterogeneity that could lead to personality subgroups. The authors analyzed data on 60 adolescents, ages 15 to 18 years, who met DSM criteria for a BPD diagnosis. The authors used latent class analysis (LCA) to identify subgroups based on the personality pattern scales from the Millon Adolescent Clinical Inventory (MACI). LCA indicated that the best-fitting solution was a two-class model, identifying two discrete subgroups of BPD adolescents that were described as internalizing and externalizing. The subgroups were then compared on clinical and sociodemographic variables, measures of personality dimensions, DSM BPD criteria, and perception of attachment styles. Adolescents with a BPD diagnosis constitute a heterogeneous group and vary meaningfully on personality features that can have clinical implications for treatment.

Unveiling the physics of AGN through X-ray variability

NASA Astrophysics Data System (ADS)

Hernández-García, L.; González-Martín, O.; Masegosa, J.; Márquez, I.

2017-03-01

Although variability is a general property characterizing active galactic nuclei (AGN), it is not well established whether the changes occur in the same way in every nuclei. The main purpose of this work is to study the X-ray variability pattern(s) in AGN selected at optical wavelengths in a large sample, including low ionization nuclear emission line regions (LINERs) and type 1.8, 1.9, and 2 Seyferts, using the public archives in Chandra and/or XMM-Newton. Spectra of the same source gathered at different epochs were simultaneously fitted to study long term variations; the variability patterns were studied allowing different parameters to vary during the spectral fit. Whenever possible, short term variations from the analysis of the light curves and long term UV flux variability were studied. Variations at X-rays in timescales of months/years are very common in all AGN families but short term variations are only found in type 1.8 and 1.9 Seyferts. The main driver of the long term X-ray variations seems to be related to changes in the nuclear power. Other variability patterns cannot be discarded in a few cases. We discuss the geometry and physics of AGN through the X-ray variability analysis.

Strike-slip tectonics during rift linkage

NASA Astrophysics Data System (ADS)

Pagli, C.; Yun, S. H.; Ebinger, C.; Keir, D.; Wang, H.

2017-12-01

The kinematics of triple junction linkage and the initiation of transforms in magmatic rifts remain debated. Strain patterns from the Afar triple junction provide tests of current models of how rifts grow to link in area of incipient oceanic spreading. Here we present a combined analysis of seismicity, InSAR and GPS derived strain rate maps to reveal that the plate boundary deformation in Afar is accommodated primarily by extensional tectonics in the Red Sea and Gulf of Aden rifts, and does not require large rotations about vertical axes (bookshelf faulting). Additionally, models of stress changes and seismicity induced by recent dykes in one sector of the Afar triple junction provide poor fit to the observed strike-slip earthquakes. Instead we explain these patterns as rift-perpendicular shearing at the tips of spreading rifts where extensional strains terminate against less stretched lithosphere. Our results demonstrate that rift-perpendicular strike-slip faulting between rift segments achieves plate boundary linkage during incipient seafloor spreading.

Divergence in plant and microbial allocation strategies explains continental patterns in microbial allocation and biogeochemical fluxes.

PubMed

Averill, Colin

2014-10-01

Allocation trade-offs shape ecological and biogeochemical phenomena at local to global scale. Plant allocation strategies drive major changes in ecosystem carbon cycling. Microbial allocation to enzymes that decompose carbon vs. organic nutrients may similarly affect ecosystem carbon cycling. Current solutions to this allocation problem prioritise stoichiometric tradeoffs implemented in plant ecology. These solutions may not maximise microbial growth and fitness under all conditions, because organic nutrients are also a significant carbon resource for microbes. I created multiple allocation frameworks and simulated microbial growth using a microbial explicit biogeochemical model. I demonstrate that prioritising stoichiometric trade-offs does not optimise microbial allocation, while exploiting organic nutrients as carbon resources does. Analysis of continental-scale enzyme data supports the allocation patterns predicted by this framework, and modelling suggests large deviations in soil C loss based on which strategy is implemented. Therefore, understanding microbial allocation strategies will likely improve our understanding of carbon cycling and climate. © 2014 John Wiley & Sons Ltd/CNRS.

Establishing Factor Validity Using Variable Reduction in Confirmatory Factor Analysis.

ERIC Educational Resources Information Center

Hofmann, Rich

1995-01-01

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

Cooked Food Waste-An Efficient and Less Expensive Precursor for the Generation of Activated Carbon.

PubMed

Krithiga, Thangavelu; Sabina, Xavier Janet; Rajesh, Baskaran; Ilbeygi, Hamid; Shetty, Adka Nityananda; Reddy, Ramanjaneya; Karthikeyan, Jayabalan

2018-06-01

Activated carbon was synthesized from cooked food waste, especially dehydrated rice kernels, by chemical activation method using NaOH and KOH as activating agents. It was then characterized by ultimate and proximate analysis, BET surface analysis, XRD, FTIR, Raman and SEM. The XRD patterns and Raman spectra confirmed the amorphous nature of the prepared activated carbons. Ultimate analysis showed an increase in the carbon content after activation of the raw carbon samples. Upon activation with NaOH and KOH, the surface area of the carbon sample was found to have increased from 0.3424 to 539.78 and 306.83 m2g-1 respectively. The SEM images revealed the formation of heterogeneous pores on the surface of the activated samples. The samples were then tested for their adsorption activity using acetic acid and methylene blue. Based on the regression coefficients, the adsorption kinetics of methylene blue dye were fitted with pseudo-second order model for both samples. Similarly, the Freundlich isotherm was found to be a better fit than Langmuir isotherm for both samples. The activity of thus prepared activated carbons was found to be comparable with the commercial carbon.

Surface modeling method for aircraft engine blades by using speckle patterns based on the virtual stereo vision system

NASA Astrophysics Data System (ADS)

Yu, Zhijing; Ma, Kai; Wang, Zhijun; Wu, Jun; Wang, Tao; Zhuge, Jingchang

2018-03-01

A blade is one of the most important components of an aircraft engine. Due to its high manufacturing costs, it is indispensable to come up with methods for repairing damaged blades. In order to obtain a surface model of the blades, this paper proposes a modeling method by using speckle patterns based on the virtual stereo vision system. Firstly, blades are sprayed evenly creating random speckle patterns and point clouds from blade surfaces can be calculated by using speckle patterns based on the virtual stereo vision system. Secondly, boundary points are obtained in the way of varied step lengths according to curvature and are fitted to get a blade surface envelope with a cubic B-spline curve. Finally, the surface model of blades is established with the envelope curves and the point clouds. Experimental results show that the surface model of aircraft engine blades is fair and accurate.

Intra-Urban Human Mobility and Activity Transition: Evidence from Social Media Check-In Data

PubMed Central

Wu, Lun; Zhi, Ye; Sui, Zhengwei; Liu, Yu

2014-01-01

Most existing human mobility literature focuses on exterior characteristics of movements but neglects activities, the driving force that underlies human movements. In this research, we combine activity-based analysis with a movement-based approach to model the intra-urban human mobility observed from about 15 million check-in records during a yearlong period in Shanghai, China. The proposed model is activity-based and includes two parts: the transition of travel demands during a specific time period and the movement between locations. For the first part, we find the transition probability between activities varies over time, and then we construct a temporal transition probability matrix to represent the transition probability of travel demands during a time interval. For the second part, we suggest that the travel demands can be divided into two classes, locationally mandatory activity (LMA) and locationally stochastic activity (LSA), according to whether the demand is associated with fixed location or not. By judging the combination of predecessor activity type and successor activity type we determine three trip patterns, each associated with a different decay parameter. To validate the model, we adopt the mechanism of an agent-based model and compare the simulated results with the observed pattern from the displacement distance distribution, the spatio-temporal distribution of activities, and the temporal distribution of travel demand transitions. The results show that the simulated patterns fit the observed data well, indicating that these findings open new directions for combining activity-based analysis with a movement-based approach using social media check-in data. PMID:24824892

Comparison of yellow poplar growth models on the basis of derived growth analysis variables

Treesearch

Keith F. Jensen; Daniel A. Yaussy

1986-01-01

Quadratic and cubic polynomials, and Gompertz and Richards asymptotic models were fitted to yellow poplar growth data. These data included height, leaf area, leaf weight and new shoot height for 23 weeks. Seven growth analysis variables were estimated from each function. The Gompertz and Richards models fitted the data best and provided the most accurate derived...

Psychometric properties of the NEPSY-II affect recognition subtest in a preschool sample: a Rasch modeling approach.

PubMed

Yao, Shih-Ying; Bull, Rebecca; Khng, Kiat Hui; Rahim, Anisa

2018-01-01

Understanding a child's ability to decode emotion expressions is important to allow early interventions for potential difficulties in social and emotional functioning. This study applied the Rasch model to investigate the psychometric properties of the NEPSY-II Affect Recognition subtest, a U.S. normed measure for 3-16 year olds which assesses the ability to recognize facial expressions of emotion. Data were collected from 1222 children attending preschools in Singapore. We first performed the Rasch analysis with the raw item data, and examined the technical qualities and difficulty pattern of the studied items. We subsequently investigated the relation of the estimated affect recognition ability from the Rasch analysis to a teacher-reported measure of a child's behaviors, emotions, and relationships. Potential gender differences were also examined. The Rasch model fits our data well. Also, the NEPSY-II Affect Recognition subtest was found to have reasonable technical qualities, expected item difficulty pattern, and desired association with the external measure of children's behaviors, emotions, and relationships for both boys and girls. Overall, findings from this study suggest that the NEPSY-II Affect Recognition subtest is a promising measure of young children's affect recognition ability. Suggestions for future test improvement and research were discussed.

Bayesian spatiotemporal crash frequency models with mixture components for space-time interactions.

PubMed

Cheng, Wen; Gill, Gurdiljot Singh; Zhang, Yongping; Cao, Zhong

2018-03-01

The traffic safety research has developed spatiotemporal models to explore the variations in the spatial pattern of crash risk over time. Many studies observed notable benefits associated with the inclusion of spatial and temporal correlation and their interactions. However, the safety literature lacks sufficient research for the comparison of different temporal treatments and their interaction with spatial component. This study developed four spatiotemporal models with varying complexity due to the different temporal treatments such as (I) linear time trend; (II) quadratic time trend; (III) Autoregressive-1 (AR-1); and (IV) time adjacency. Moreover, the study introduced a flexible two-component mixture for the space-time interaction which allows greater flexibility compared to the traditional linear space-time interaction. The mixture component allows the accommodation of global space-time interaction as well as the departures from the overall spatial and temporal risk patterns. This study performed a comprehensive assessment of mixture models based on the diverse criteria pertaining to goodness-of-fit, cross-validation and evaluation based on in-sample data for predictive accuracy of crash estimates. The assessment of model performance in terms of goodness-of-fit clearly established the superiority of the time-adjacency specification which was evidently more complex due to the addition of information borrowed from neighboring years, but this addition of parameters allowed significant advantage at posterior deviance which subsequently benefited overall fit to crash data. The Base models were also developed to study the comparison between the proposed mixture and traditional space-time components for each temporal model. The mixture models consistently outperformed the corresponding Base models due to the advantages of much lower deviance. For cross-validation comparison of predictive accuracy, linear time trend model was adjudged the best as it recorded the highest value of log pseudo marginal likelihood (LPML). Four other evaluation criteria were considered for typical validation using the same data for model development. Under each criterion, observed crash counts were compared with three types of data containing Bayesian estimated, normal predicted, and model replicated ones. The linear model again performed the best in most scenarios except one case of using model replicated data and two cases involving prediction without including random effects. These phenomena indicated the mediocre performance of linear trend when random effects were excluded for evaluation. This might be due to the flexible mixture space-time interaction which can efficiently absorb the residual variability escaping from the predictable part of the model. The comparison of Base and mixture models in terms of prediction accuracy further bolstered the superiority of the mixture models as the mixture ones generated more precise estimated crash counts across all four models, suggesting that the advantages associated with mixture component at model fit were transferable to prediction accuracy. Finally, the residual analysis demonstrated the consistently superior performance of random effect models which validates the importance of incorporating the correlation structures to account for unobserved heterogeneity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Glassy dynamics in three-dimensional embryonic tissues

PubMed Central

Schötz, Eva-Maria; Lanio, Marcos; Talbot, Jared A.; Manning, M. Lisa

2013-01-01

Many biological tissues are viscoelastic, behaving as elastic solids on short timescales and fluids on long timescales. This collective mechanical behaviour enables and helps to guide pattern formation and tissue layering. Here, we investigate the mechanical properties of three-dimensional tissue explants from zebrafish embryos by analysing individual cell tracks and macroscopic mechanical response. We find that the cell dynamics inside the tissue exhibit features of supercooled fluids, including subdiffusive trajectories and signatures of caging behaviour. We develop a minimal, three-parameter mechanical model for these dynamics, which we calibrate using only information about cell tracks. This model generates predictions about the macroscopic bulk response of the tissue (with no fit parameters) that are verified experimentally, providing a strong validation of the model. The best-fit model parameters indicate that although the tissue is fluid-like, it is close to a glass transition, suggesting that small changes to single-cell parameters could generate a significant change in the viscoelastic properties of the tissue. These results provide a robust framework for quantifying and modelling mechanically driven pattern formation in tissues. PMID:24068179

Temporal Stability, Correlates, and Longitudinal Outcomes of Career Indecision Factors

ERIC Educational Resources Information Center

Nauta, Margaret M.

2012-01-01

A confirmatory factor analysis (CFA) tested the fit of Kelly and Lee's six-factor model of career decision problems among 188 college students. The six-factor model did not fit the data well, but a five-factor (Lack of Information, Need for Information, Trait Indecision, Disagreement with Others, and Choice Anxiety) model did provide a good fit.…

Modeling the Spatial Distribution and Fruiting Pattern of a Key Tree Species in a Neotropical Forest: Methodology and Potential Applications

PubMed Central

Scarpino, Samuel V.; Jansen, Patrick A.; Garzon-Lopez, Carol X.; Winkelhagen, Annemarie J. S.; Bohlman, Stephanie A.; Walsh, Peter D.

2010-01-01

Background The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most attempts to model this relationship were forced to rely on simplified assumptions about the spatiotemporal distribution of food resources. Here we demonstrate how advances in statistics permit the combination of sparse ground sampling with remote sensing imagery to generate biological relevant, spatially and temporally explicit distributions of food resources. We illustrate our procedure by creating a detailed simulation model of fruit production patterns for Dipteryx oleifera, a keystone tree species, on Barro Colorado Island (BCI), Panama. Methodology and Principal Findings Aerial photographs providing GPS positions for large, canopy trees, the complete census of a 50-ha and 25-ha area, diameter at breast height data from haphazardly sampled trees and long-term phenology data from six trees were used to fit 1) a point process model of tree spatial distribution and 2) a generalized linear mixed-effect model of temporal variation of fruit production. The fitted parameters from these models are then used to create a stochastic simulation model which incorporates spatio-temporal variations of D. oleifera fruit availability on BCI. Conclusions and Significance We present a framework that can provide a statistical characterization of the habitat that can be included in agent-based models of animal movements. When environmental heterogeneity cannot be exhaustively mapped, this approach can be a powerful alternative. The results of our model on the spatio-temporal variation in D. oleifera fruit availability will be used to understand behavioral and movement patterns of several species on BCI. PMID:21124927

Correlations between environmental factors and wild bee behavior on alfalfa (Medicago sativa) in northwestern China.

PubMed

Wang, Xiaojuan; Liu, Hongping; Li, Xiaoxia; Song, Yu; Chen, Li; Jin, Liang

2009-10-01

To discover the effect of environmental factors on pollinator visitation to flowering Medicago sativa, several field experiments were designed to examine the diurnal movement patterns of wild bee species in the Hexi Corridor of northwestern China. Our study results showed that Megachile abluta, M. spissula, and Xylocopa valga showed unimodal diurnal foraging behavior, whereas Andrena parvula and Anthophora melanognatha showed bimodal diurnal foraging behavior. Correlation analysis indicated that diurnal foraging activities of pollinators were significantly correlated with environmental factors. Correlations of foraging activities versus environmental factors for M. abluta, M. spissula, and X. valga best fit a linear model, whereas those of A. parvula and A. melanognatha best fit a parallel quadratic model. Results of this study indicated that solitary wild bees such as M. abluta, M. spissula, X. valga, A. parvula, and A. melanognatha are potential alfalfa pollinators in the Hexi Corridor. An understanding of the environmental factors that affect the behaviors of different wild bees foraging in alfalfa are basic to the utilization of solitary wild bees in a practical way for increased, or more consistent, pollination of alfalfa for seed production.

Ocean wavenumber estimation from wave-resolving time series imagery

USGS Publications Warehouse

Plant, N.G.; Holland, K.T.; Haller, M.C.

2008-01-01

We review several approaches that have been used to estimate ocean surface gravity wavenumbers from wave-resolving remotely sensed image sequences. Two fundamentally different approaches that utilize these data exist. A power spectral density approach identifies wavenumbers where image intensity variance is maximized. Alternatively, a cross-spectral correlation approach identifies wavenumbers where intensity coherence is maximized. We develop a solution to the latter approach based on a tomographic analysis that utilizes a nonlinear inverse method. The solution is tolerant to noise and other forms of sampling deficiency and can be applied to arbitrary sampling patterns, as well as to full-frame imagery. The solution includes error predictions that can be used for data retrieval quality control and for evaluating sample designs. A quantitative analysis of the intrinsic resolution of the method indicates that the cross-spectral correlation fitting improves resolution by a factor of about ten times as compared to the power spectral density fitting approach. The resolution analysis also provides a rule of thumb for nearshore bathymetry retrievals-short-scale cross-shore patterns may be resolved if they are about ten times longer than the average water depth over the pattern. This guidance can be applied to sample design to constrain both the sensor array (image resolution) and the analysis array (tomographic resolution). ?? 2008 IEEE.

Atmospheric Properties Of T Dwarfs Inferred From Model Fits At Low Spectral Resolution

NASA Astrophysics Data System (ADS)

Giorla Godfrey, Paige A.; Rice, Emily L.; Filippazzo, Joseph C.; Douglas, Stephanie E.

2016-09-01

Brown dwarf spectral types (M, L, T, Y) correlate with spectral morphology, and generally appear to correspond with decreasing mass and effective temperature (Teff). Model fits to observed spectra suggest, however, that spectral subclasses do not share this monotonic temperature correlation, indicating that secondary parameters (gravity, metallicity, dust) significantly influence spectral morphology. We seekto disentangle the fundamental parameters that underlie the spectral type sequence of the coolest fully populated spectral class of brown dwarfs using atmosphere models. We investigate the relationship between spectral type and best fit model parameters for a sample of over 150 T dwarfs with low resolution (R 75-100) near-infrared ( 0.8-2.5 micron) SpeX Prism spectra. We use synthetic spectra from four model grids (Saumon & Marley 2008, Morley+ 2012, Saumon+ 2012, BT Settl 2013) and a Markov-Chain Monte Carlo (MCMC) analysis to determine robust best fit parameters and their uncertainties. We compare the consistency of each model grid by performing our analysis on the full spectrum and also on individual wavelength bands (Y,J,H,K). We find more consistent results between the J band and full spectrum fits and that our best fit spectral type-Teff results agree with the polynomial relationships of Stephens+2009 and Filippazzo+ 2015 using bolometric luminosities. Our analysis consists of the most extensive low resolution T dwarf model comparison to date, and lays the foundation for interpretation of cool brown dwarf and exoplanet spectra.

An Application of M[subscript 2] Statistic to Evaluate the Fit of Cognitive Diagnostic Models

ERIC Educational Resources Information Center

Liu, Yanlou; Tian, Wei; Xin, Tao

2016-01-01

The fit of cognitive diagnostic models (CDMs) to response data needs to be evaluated, since CDMs might yield misleading results when they do not fit the data well. Limited-information statistic M[subscript 2] and the associated root mean square error of approximation (RMSEA[subscript 2]) in item factor analysis were extended to evaluate the fit of…

Stronger tests of mechanisms underlying geographic gradients of biodiversity: insights from the dimensionality of biodiversity.

PubMed

Stevens, Richard D; Tello, J Sebastián; Gavilanez, María Mercedes

2013-01-01

Inference involving diversity gradients typically is gathered by mechanistic tests involving single dimensions of biodiversity such as species richness. Nonetheless, because traits such as geographic range size, trophic status or phenotypic characteristics are tied to a particular species, mechanistic effects driving broad diversity patterns should manifest across numerous dimensions of biodiversity. We develop an approach of stronger inference based on numerous dimensions of biodiversity and apply it to evaluate one such putative mechanism: the mid-domain effect (MDE). Species composition of 10,000-km(2) grid cells was determined by overlaying geographic range maps of 133 noctilionoid bat taxa. We determined empirical diversity gradients in the Neotropics by calculating species richness and three indices each of phylogenetic, functional and phenetic diversity for each grid cell. We also created 1,000 simulated gradients of each examined metric of biodiversity based on a MDE model to estimate patterns expected if species distributions were randomly placed within the Neotropics. For each simulation run, we regressed the observed gradient onto the MDE-expected gradient. If a MDE drives empirical gradients, then coefficients of determination from such an analysis should be high, the intercept no different from zero and the slope no different than unity. Species richness gradients predicted by the MDE fit empirical patterns. The MDE produced strong spatially structured gradients of taxonomic, phylogenetic, functional and phenetic diversity. Nonetheless, expected values generated from the MDE for most dimensions of biodiversity exhibited poor fit to most empirical patterns. The MDE cannot account for most empirical patterns of biodiversity. Fuller understanding of latitudinal gradients will come from simultaneous examination of relative effects of random, environmental and historical mechanisms to better understand distribution and abundance of the current biota.

Stronger Tests of Mechanisms Underlying Geographic Gradients of Biodiversity: Insights from the Dimensionality of Biodiversity

PubMed Central

Stevens, Richard D.; Tello, J. Sebastián; Gavilanez, María Mercedes

2013-01-01

Inference involving diversity gradients typically is gathered by mechanistic tests involving single dimensions of biodiversity such as species richness. Nonetheless, because traits such as geographic range size, trophic status or phenotypic characteristics are tied to a particular species, mechanistic effects driving broad diversity patterns should manifest across numerous dimensions of biodiversity. We develop an approach of stronger inference based on numerous dimensions of biodiversity and apply it to evaluate one such putative mechanism: the mid-domain effect (MDE). Species composition of 10,000-km2 grid cells was determined by overlaying geographic range maps of 133 noctilionoid bat taxa. We determined empirical diversity gradients in the Neotropics by calculating species richness and three indices each of phylogenetic, functional and phenetic diversity for each grid cell. We also created 1,000 simulated gradients of each examined metric of biodiversity based on a MDE model to estimate patterns expected if species distributions were randomly placed within the Neotropics. For each simulation run, we regressed the observed gradient onto the MDE-expected gradient. If a MDE drives empirical gradients, then coefficients of determination from such an analysis should be high, the intercept no different from zero and the slope no different than unity. Species richness gradients predicted by the MDE fit empirical patterns. The MDE produced strong spatially structured gradients of taxonomic, phylogenetic, functional and phenetic diversity. Nonetheless, expected values generated from the MDE for most dimensions of biodiversity exhibited poor fit to most empirical patterns. The MDE cannot account for most empirical patterns of biodiversity. Fuller understanding of latitudinal gradients will come from simultaneous examination of relative effects of random, environmental and historical mechanisms to better understand distribution and abundance of the current biota. PMID:23451099

Climate Cycles and Forecasts of Cutaneous Leishmaniasis, a Nonstationary Vector-Borne Disease

PubMed Central

Chaves, Luis Fernando; Pascual, Mercedes

2006-01-01

Background Cutaneous leishmaniasis (CL) is one of the main emergent diseases in the Americas. As in other vector-transmitted diseases, its transmission is sensitive to the physical environment, but no study has addressed the nonstationary nature of such relationships or the interannual patterns of cycling of the disease. Methods and Findings We studied monthly data, spanning from 1991 to 2001, of CL incidence in Costa Rica using several approaches for nonstationary time series analysis in order to ensure robustness in the description of CL's cycles. Interannual cycles of the disease and the association of these cycles to climate variables were described using frequency and time-frequency techniques for time series analysis. We fitted linear models to the data using climatic predictors, and tested forecasting accuracy for several intervals of time. Forecasts were evaluated using “out of fit” data (i.e., data not used to fit the models). We showed that CL has cycles of approximately 3 y that are coherent with those of temperature and El Niño Southern Oscillation indices (Sea Surface Temperature 4 and Multivariate ENSO Index). Conclusions Linear models using temperature and MEI can predict satisfactorily CL incidence dynamics up to 12 mo ahead, with an accuracy that varies from 72% to 77% depending on prediction time. They clearly outperform simpler models with no climate predictors, a finding that further supports a dynamical link between the disease and climate. PMID:16903778

A comment on priors for Bayesian occupancy models

PubMed Central

Gerber, Brian D.

2018-01-01

Understanding patterns of species occurrence and the processes underlying these patterns is fundamental to the study of ecology. One of the more commonly used approaches to investigate species occurrence patterns is occupancy modeling, which can account for imperfect detection of a species during surveys. In recent years, there has been a proliferation of Bayesian modeling in ecology, which includes fitting Bayesian occupancy models. The Bayesian framework is appealing to ecologists for many reasons, including the ability to incorporate prior information through the specification of prior distributions on parameters. While ecologists almost exclusively intend to choose priors so that they are “uninformative” or “vague”, such priors can easily be unintentionally highly informative. Here we report on how the specification of a “vague” normally distributed (i.e., Gaussian) prior on coefficients in Bayesian occupancy models can unintentionally influence parameter estimation. Using both simulated data and empirical examples, we illustrate how this issue likely compromises inference about species-habitat relationships. While the extent to which these informative priors influence inference depends on the data set, researchers fitting Bayesian occupancy models should conduct sensitivity analyses to ensure intended inference, or employ less commonly used priors that are less informative (e.g., logistic or t prior distributions). We provide suggestions for addressing this issue in occupancy studies, and an online tool for exploring this issue under different contexts. PMID:29481554

Tolerance adaptation and precipitation changes complicate latitudinal patterns of climate change impacts.

PubMed

Bonebrake, Timothy C; Mastrandrea, Michael D

2010-07-13

Global patterns of biodiversity and comparisons between tropical and temperate ecosystems have pervaded ecology from its inception. However, the urgency in understanding these global patterns has been accentuated by the threat of rapid climate change. We apply an adaptive model of environmental tolerance evolution to global climate data and climate change model projections to examine the relative impacts of climate change on different regions of the globe. Our results project more adverse impacts of warming on tropical populations due to environmental tolerance adaptation to conditions of low interannual variability in temperature. When applied to present variability and future forecasts of precipitation data, the tolerance adaptation model found large reductions in fitness predicted for populations in high-latitude northern hemisphere regions, although some tropical regions had comparable reductions in fitness. We formulated an evolutionary regional climate change index (ERCCI) to additionally incorporate the predicted changes in the interannual variability of temperature and precipitation. Based on this index, we suggest that the magnitude of climate change impacts could be much more heterogeneous across latitude than previously thought. Specifically, tropical regions are likely to be just as affected as temperate regions and, in some regions under some circumstances, possibly more so.

Deriving the pattern speed using dynamical modelling of gas flows in barred galaxies .

NASA Astrophysics Data System (ADS)

Pérez, I.; Freeman, K. C.; Fux, R.; Zurita, A.

In this paper we analyse the methodology to derive the bar pattern speed from dynamical simulations. The results are robust to the changes in the vertical-scale height and in the mass-to-light (M/L) ratios. There is a small range of parameters for which the kinematics can be fitted. We have also taken into account the use of different type of dynamical modelling and the effect of using 2-D vs 1-D models in deriving the pattern speeds. We conclude that the derivation of the bar streaming motions and strength and position of shocks is not greatly affected by the fluid dynamical model used. We show new results on the derivation of the pattern speed for NGC 1530. The best fit pattern speed is around 10 km s-1 kpc-1 , which corresponds to a R_cor/R_bar = 1.4, implying a slower bar than previously derived from more indirect assumptions. With this pattern speed, the global and most local kinematic features are beautifully reproduced. However, the simulations fail to reproduce the velocity gradients close to some bright HII regions in the bar. We have shown from the study of the H{alpha } equivalent widths that the HII regions that are located further away from the bar dust-lane in its leading side, downstream from the main bar dust-lane, are older than the rest by 1.5-2.5 Myr. In addition, a clear spatial correlation was found between the location of HII regions, dust spurs on the trailing side of the bar dust-lane, and the loci of maximum velocity gradients parallel to the bar major axis.

Are running speeds maximized with simple-spring stance mechanics?

PubMed

Clark, Kenneth P; Weyand, Peter G

2014-09-15

Are the fastest running speeds achieved using the simple-spring stance mechanics predicted by the classic spring-mass model? We hypothesized that a passive, linear-spring model would not account for the running mechanics that maximize ground force application and speed. We tested this hypothesis by comparing patterns of ground force application across athletic specialization (competitive sprinters vs. athlete nonsprinters, n = 7 each) and running speed (top speeds vs. slower ones). Vertical ground reaction forces at 5.0 and 7.0 m/s, and individual top speeds (n = 797 total footfalls) were acquired while subjects ran on a custom, high-speed force treadmill. The goodness of fit between measured vertical force vs. time waveform patterns and the patterns predicted by the spring-mass model were assessed using the R(2) statistic (where an R(2) of 1.00 = perfect fit). As hypothesized, the force application patterns of the competitive sprinters deviated significantly more from the simple-spring pattern than those of the athlete, nonsprinters across the three test speeds (R(2) <0.85 vs. R(2) ≥ 0.91, respectively), and deviated most at top speed (R(2) = 0.78 ± 0.02). Sprinters attained faster top speeds than nonsprinters (10.4 ± 0.3 vs. 8.7 ± 0.3 m/s) by applying greater vertical forces during the first half (2.65 ± 0.05 vs. 2.21 ± 0.05 body wt), but not the second half (1.71 ± 0.04 vs. 1.73 ± 0.04 body wt) of the stance phase. We conclude that a passive, simple-spring model has limited application to sprint running performance because the swiftest runners use an asymmetrical pattern of force application to maximize ground reaction forces and attain faster speeds. Copyright © 2014 the American Physiological Society.

Advanced Concepts for Composite Structure Joints and Attachment Fittings. Volume I. Design and Evaluation.

DTIC Science & Technology

1981-11-01

interlaminar tension). The analysis is also influenced by other factors such as bolt location, washer/bolt size, fastener pattern, laminate thickness, corner...to reduce the cost of tooling were also studied. These include: * Pultrusion dies for under $5, 000 * Stable, accurate, low-cost chopped-fiber phenolic ...fittings were state-of- the-art methods developed for laminated composite plates, shells, beams, and columns as used in analyses of discontinuities, edge

A comparison of multivariate and univariate time series approaches to modelling and forecasting emergency department demand in Western Australia.

PubMed

Aboagye-Sarfo, Patrick; Mai, Qun; Sanfilippo, Frank M; Preen, David B; Stewart, Louise M; Fatovich, Daniel M

2015-10-01

To develop multivariate vector-ARMA (VARMA) forecast models for predicting emergency department (ED) demand in Western Australia (WA) and compare them to the benchmark univariate autoregressive moving average (ARMA) and Winters' models. Seven-year monthly WA state-wide public hospital ED presentation data from 2006/07 to 2012/13 were modelled. Graphical and VARMA modelling methods were used for descriptive analysis and model fitting. The VARMA models were compared to the benchmark univariate ARMA and Winters' models to determine their accuracy to predict ED demand. The best models were evaluated by using error correction methods for accuracy. Descriptive analysis of all the dependent variables showed an increasing pattern of ED use with seasonal trends over time. The VARMA models provided a more precise and accurate forecast with smaller confidence intervals and better measures of accuracy in predicting ED demand in WA than the ARMA and Winters' method. VARMA models are a reliable forecasting method to predict ED demand for strategic planning and resource allocation. While the ARMA models are a closely competing alternative, they under-estimated future ED demand. Copyright © 2015 Elsevier Inc. All rights reserved.

Linearised and non-linearised isotherm models optimization analysis by error functions and statistical means

PubMed Central

2014-01-01

In adsorption study, to describe sorption process and evaluation of best-fitting isotherm model is a key analysis to investigate the theoretical hypothesis. Hence, numerous statistically analysis have been extensively used to estimate validity of the experimental equilibrium adsorption values with the predicted equilibrium values. Several statistical error analysis were carried out. In the present study, the following statistical analysis were carried out to evaluate the adsorption isotherm model fitness, like the Pearson correlation, the coefficient of determination and the Chi-square test, have been used. The ANOVA test was carried out for evaluating significance of various error functions and also coefficient of dispersion were evaluated for linearised and non-linearised models. The adsorption of phenol onto natural soil (Local name Kalathur soil) was carried out, in batch mode at 30 ± 20 C. For estimating the isotherm parameters, to get a holistic view of the analysis the models were compared between linear and non-linear isotherm models. The result reveled that, among above mentioned error functions and statistical functions were designed to determine the best fitting isotherm. PMID:25018878

The Specific Analysis of Structural Equation Models

ERIC Educational Resources Information Center

McDonald, Roderick P.

2004-01-01

Conventional structural equation modeling fits a covariance structure implied by the equations of the model. This treatment of the model often gives misleading results because overall goodness of fit tests do not focus on the specific constraints implied by the model. An alternative treatment arising from Pearl's directed acyclic graph theory…

Clarifications regarding the use of model-fitting methods of kinetic analysis for determining the activation energy from a single non-isothermal curve.

PubMed

Sánchez-Jiménez, Pedro E; Pérez-Maqueda, Luis A; Perejón, Antonio; Criado, José M

2013-02-05

This paper provides some clarifications regarding the use of model-fitting methods of kinetic analysis for estimating the activation energy of a process, in response to some results recently published in Chemistry Central journal. The model fitting methods of Arrhenius and Savata are used to determine the activation energy of a single simulated curve. It is shown that most kinetic models correctly fit the data, each providing a different value for the activation energy. Therefore it is not really possible to determine the correct activation energy from a single non-isothermal curve. On the other hand, when a set of curves are recorded under different heating schedules are used, the correct kinetic parameters can be clearly discerned. Here, it is shown that the activation energy and the kinetic model cannot be unambiguously determined from a single experimental curve recorded under non isothermal conditions. Thus, the use of a set of curves recorded under different heating schedules is mandatory if model-fitting methods are employed.

Environmental heterogeneity blurs the signature of dispersal syndromes on spatial patterns of woody species in a moist tropical forest

PubMed Central

Velázquez, Eduardo; Escudero, Adrián; de la Cruz, Marcelino

2018-01-01

We assessed the relative importance of dispersal limitation, environmental heterogeneity and their joint effects as determinants of the spatial patterns of 229 species in the moist tropical forest of Barro Colorado Island (Panama). We differentiated five types of species according to their dispersal syndrome; autochorous, anemochorous, and zoochorous species with small, medium-size and large fruits. We characterized the spatial patterns of each species and we checked whether they were best fitted by Inhomogeneous Poisson (IPP), Homogeneous Poisson cluster (HPCP) and Inhomogeneous Poisson cluster processes (IPCP) by means of the Akaike Information Criterion. We also assessed the influence of species’ dispersal mode in the average cluster size. We found that 63% of the species were best fitted by IPCP regardless of their dispersal syndrome, although anemochorous species were best described by HPCP. Our results indicate that spatial patterns of tree species in this forest cannot be explained only by dispersal limitation, but by the joint effects of dispersal limitation and environmental heterogeneity. The absence of relationships between dispersal mode and degree of clustering suggests that several processes modify the original spatial pattern generated by seed dispersal. These findings emphasize the importance of fitting point process models with a different biological meaning when studying the main determinants of spatial structure in plant communities. PMID:29451871

Geospatial Analysis of Atmospheric Haze Effect by Source and Sink Landscape

NASA Astrophysics Data System (ADS)

Yu, T.; Xu, K.; Yuan, Z.

2017-09-01

Based on geospatial analysis model, this paper analyzes the relationship between the landscape patterns of source and sink in urban areas and atmospheric haze pollution. Firstly, the classification result and aerosol optical thickness (AOD) of Wuhan are divided into a number of square grids with the side length of 6 km, and the category level landscape indices (PLAND, PD, COHESION, LPI, FRAC_MN) and AOD of each grid are calculated. Then the source and sink landscapes of atmospheric haze pollution are selected based on the analysis of the correlation between landscape indices and AOD. Next, to make the following analysis more efficient, the indices selected before should be determined through the correlation coefficient between them. Finally, due to the spatial dependency and spatial heterogeneity of the data used in this paper, spatial autoregressive model and geo-weighted regression model are used to analyze atmospheric haze effect by source and sink landscape from the global and local level. The results show that the source landscape of atmospheric haze pollution is the building, and the sink landscapes are shrub and woodland. PLAND, PD and COHESION are suitable for describing the atmospheric haze effect by source and sink landscape. Comparing these models, the fitting effect of SLM, SEM and GWR is significantly better than that of OLS model. The SLM model is superior to the SEM model in this paper. Although the fitting effect of GWR model is more unsuited than that of SLM, the influence degree of influencing factors on atmospheric haze of different geography can be expressed clearer. Through the analysis results of these models, following conclusions can be summarized: Reducing the proportion of source landscape area and increasing the degree of fragmentation could cut down aerosol optical thickness; And distributing the source and sink landscape evenly and interspersedly could effectively reduce aerosol optical thickness which represents atmospheric haze pollution; For Wuhan City, the method of adjusting the built-up area slightly and planning the non-built-up areas reasonably can be taken to reduce atmospheric haze pollution.

A comparative analysis of sex change in Labridae supports the size advantage hypothesis.

PubMed

Kazancioğlu, Erem; Alonzo, Suzanne H

2010-08-01

The size advantage hypothesis (SAH) predicts that the rate of increase in male and female fitness with size (the size advantage) drives the evolution of sequential hermaphroditism or sex change. Despite qualitative agreement between empirical patterns and SAH, only one comparative study tested SAH quantitatively. Here, we perform the first comparative analysis of sex change in Labridae, a group of hermaphroditic and dioecious (non-sex changer) fish with several model sex-changing species. We also estimate, for the first time, rates of evolutionary transitions between sex change and dioecy. Our analyses support SAH and indicate that the evolution of hermaphroditism is correlated to the size advantage. Furthermore, we find that transitions from sex change to dioecy are less likely under stronger size advantage. We cannot determine, however, how the size advantage affects transitions from dioecy to sex change. Finally, contrary to what is generally expected, we find that transitions from dioecy to sex change are more likely than transitions from sex change to dioecy. The similarity of sexual differentiation in hermaphroditic and dioecious labrids might underlie this pattern. We suggest that elucidating the developmental basis of sex change is critical to predict and explain patterns of the evolutionary history of sequential hermaphroditism.

Logistic regression analysis of conventional ultrasonography, strain elastosonography, and contrast-enhanced ultrasound characteristics for the differentiation of benign and malignant thyroid nodules

PubMed Central

Deng, Yingyuan; Wang, Tianfu; Chen, Siping; Liu, Weixiang

2017-01-01

The aim of the study is to screen the significant sonographic features by logistic regression analysis and fit a model to diagnose thyroid nodules. A total of 525 pathological thyroid nodules were retrospectively analyzed. All the nodules underwent conventional ultrasonography (US), strain elastosonography (SE), and contrast -enhanced ultrasound (CEUS). Those nodules’ 12 suspicious sonographic features were used to assess thyroid nodules. The significant features of diagnosing thyroid nodules were picked out by logistic regression analysis. All variables that were statistically related to diagnosis of thyroid nodules, at a level of p < 0.05 were embodied in a logistic regression analysis model. The significant features in the logistic regression model of diagnosing thyroid nodules were calcification, suspected cervical lymph node metastasis, hypoenhancement pattern, margin, shape, vascularity, posterior acoustic, echogenicity, and elastography score. According to the results of logistic regression analysis, the formula that could predict whether or not thyroid nodules are malignant was established. The area under the receiver operating curve (ROC) was 0.930 and the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 83.77%, 89.56%, 87.05%, 86.04%, and 87.79% respectively. PMID:29228030

Logistic regression analysis of conventional ultrasonography, strain elastosonography, and contrast-enhanced ultrasound characteristics for the differentiation of benign and malignant thyroid nodules.

PubMed

Pang, Tiantian; Huang, Leidan; Deng, Yingyuan; Wang, Tianfu; Chen, Siping; Gong, Xuehao; Liu, Weixiang

2017-01-01

The aim of the study is to screen the significant sonographic features by logistic regression analysis and fit a model to diagnose thyroid nodules. A total of 525 pathological thyroid nodules were retrospectively analyzed. All the nodules underwent conventional ultrasonography (US), strain elastosonography (SE), and contrast -enhanced ultrasound (CEUS). Those nodules' 12 suspicious sonographic features were used to assess thyroid nodules. The significant features of diagnosing thyroid nodules were picked out by logistic regression analysis. All variables that were statistically related to diagnosis of thyroid nodules, at a level of p < 0.05 were embodied in a logistic regression analysis model. The significant features in the logistic regression model of diagnosing thyroid nodules were calcification, suspected cervical lymph node metastasis, hypoenhancement pattern, margin, shape, vascularity, posterior acoustic, echogenicity, and elastography score. According to the results of logistic regression analysis, the formula that could predict whether or not thyroid nodules are malignant was established. The area under the receiver operating curve (ROC) was 0.930 and the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 83.77%, 89.56%, 87.05%, 86.04%, and 87.79% respectively.

Detecting Adaptation in Protein-Coding Genes Using a Bayesian Site-Heterogeneous Mutation-Selection Codon Substitution Model.

PubMed

Rodrigue, Nicolas; Lartillot, Nicolas

2017-01-01

Codon substitution models have traditionally attempted to uncover signatures of adaptation within protein-coding genes by contrasting the rates of synonymous and non-synonymous substitutions. Another modeling approach, known as the mutation-selection framework, attempts to explicitly account for selective patterns at the amino acid level, with some approaches allowing for heterogeneity in these patterns across codon sites. Under such a model, substitutions at a given position occur at the neutral or nearly neutral rate when they are synonymous, or when they correspond to replacements between amino acids of similar fitness; substitutions from high to low (low to high) fitness amino acids have comparatively low (high) rates. Here, we study the use of such a mutation-selection framework as a null model for the detection of adaptation. Following previous works in this direction, we include a deviation parameter that has the effect of capturing the surplus, or deficit, in non-synonymous rates, relative to what would be expected under a mutation-selection modeling framework that includes a Dirichlet process approach to account for across-codon-site variation in amino acid fitness profiles. We use simulations, along with a few real data sets, to study the behavior of the approach, and find it to have good power with a low false-positive rate. Altogether, we emphasize the potential of recent mutation-selection models in the detection of adaptation, calling for further model refinements as well as large-scale applications. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

A global goodness-of-fit statistic for Cox regression models.

PubMed

Parzen, M; Lipsitz, S R

1999-06-01

In this paper, a global goodness-of-fit test statistic for a Cox regression model, which has an approximate chi-squared distribution when the model has been correctly specified, is proposed. Our goodness-of-fit statistic is global and has power to detect if interactions or higher order powers of covariates in the model are needed. The proposed statistic is similar to the Hosmer and Lemeshow (1980, Communications in Statistics A10, 1043-1069) goodness-of-fit statistic for binary data as well as Schoenfeld's (1980, Biometrika 67, 145-153) statistic for the Cox model. The methods are illustrated using data from a Mayo Clinic trial in primary billiary cirrhosis of the liver (Fleming and Harrington, 1991, Counting Processes and Survival Analysis), in which the outcome is the time until liver transplantation or death. The are 17 possible covariates. Two Cox proportional hazards models are fit to the data, and the proposed goodness-of-fit statistic is applied to the fitted models.

Sexual dimorphism is associated with population fitness in the seed beetle Callosobruchus maculatus.

PubMed

Rankin, Daniel J; Arnqvist, Göran

2008-03-01

The population consequences of sexual selection remain empirically unexplored. Comparative studies, involving extinction risk, have yielded different results as to the effect of sexual selection on population densities make contrasting predictions. Here, we investigate the relationship between sexual dimorphism (SD) and population productivity in the seed beetle Callosobruchus maculatus, using 13 populations that have evolved in isolation. Geometric morphometric methods and image analysis are employed to form integrative measures of sexual dimorphism, composed of variation in weight, size, body shape, and pigmentation. We found a positive relationship between SD and adult fitness (net adult offspring production) across our study populations, but failed to find any association between SD and juvenile fitness (egg-to-adult survival). Several mechanisms may have contributed to the pattern found, and variance in sexual selection regimes across populations, either in female choice for "good genes" or in the magnitude of direct benefits provided by their mates, would tend to produce the pattern seen. However, our results suggest that evolutionary constraints in the form of intralocus sexual conflict may have been the major generator of the relationship seen between SD and population fitness.

A comparative analysis of three vector-borne diseases across Australia using seasonal and meteorological models

PubMed Central

Stratton, Margaret D.; Ehrlich, Hanna Y.; Mor, Siobhan M.; Naumova, Elena N.

2017-01-01

Ross River virus (RRV), Barmah Forest virus (BFV), and dengue are three common mosquito-borne diseases in Australia that display notable seasonal patterns. Although all three diseases have been modeled on localized scales, no previous study has used harmonic models to compare seasonality of mosquito-borne diseases on a continent-wide scale. We fit Poisson harmonic regression models to surveillance data on RRV, BFV, and dengue (from 1993, 1995 and 1991, respectively, through 2015) incorporating seasonal, trend, and climate (temperature and rainfall) parameters. The models captured an average of 50–65% variability of the data. Disease incidence for all three diseases generally peaked in January or February, but peak timing was most variable for dengue. The most significant predictor parameters were trend and inter-annual periodicity for BFV, intra-annual periodicity for RRV, and trend for dengue. We found that a Temperature Suitability Index (TSI), designed to reclassify climate data relative to optimal conditions for vector establishment, could be applied to this context. Finally, we extrapolated our models to estimate the impact of a false-positive BFV epidemic in 2013. Creating these models and comparing variations in periodicities may provide insight into historical outbreaks as well as future patterns of mosquito-borne diseases. PMID:28071683

A comparative analysis of three vector-borne diseases across Australia using seasonal and meteorological models.

PubMed

Stratton, Margaret D; Ehrlich, Hanna Y; Mor, Siobhan M; Naumova, Elena N

2017-01-10

Ross River virus (RRV), Barmah Forest virus (BFV), and dengue are three common mosquito-borne diseases in Australia that display notable seasonal patterns. Although all three diseases have been modeled on localized scales, no previous study has used harmonic models to compare seasonality of mosquito-borne diseases on a continent-wide scale. We fit Poisson harmonic regression models to surveillance data on RRV, BFV, and dengue (from 1993, 1995 and 1991, respectively, through 2015) incorporating seasonal, trend, and climate (temperature and rainfall) parameters. The models captured an average of 50-65% variability of the data. Disease incidence for all three diseases generally peaked in January or February, but peak timing was most variable for dengue. The most significant predictor parameters were trend and inter-annual periodicity for BFV, intra-annual periodicity for RRV, and trend for dengue. We found that a Temperature Suitability Index (TSI), designed to reclassify climate data relative to optimal conditions for vector establishment, could be applied to this context. Finally, we extrapolated our models to estimate the impact of a false-positive BFV epidemic in 2013. Creating these models and comparing variations in periodicities may provide insight into historical outbreaks as well as future patterns of mosquito-borne diseases.

A comparative analysis of three vector-borne diseases across Australia using seasonal and meteorological models

NASA Astrophysics Data System (ADS)

Stratton, Margaret D.; Ehrlich, Hanna Y.; Mor, Siobhan M.; Naumova, Elena N.

2017-01-01

Ross River virus (RRV), Barmah Forest virus (BFV), and dengue are three common mosquito-borne diseases in Australia that display notable seasonal patterns. Although all three diseases have been modeled on localized scales, no previous study has used harmonic models to compare seasonality of mosquito-borne diseases on a continent-wide scale. We fit Poisson harmonic regression models to surveillance data on RRV, BFV, and dengue (from 1993, 1995 and 1991, respectively, through 2015) incorporating seasonal, trend, and climate (temperature and rainfall) parameters. The models captured an average of 50-65% variability of the data. Disease incidence for all three diseases generally peaked in January or February, but peak timing was most variable for dengue. The most significant predictor parameters were trend and inter-annual periodicity for BFV, intra-annual periodicity for RRV, and trend for dengue. We found that a Temperature Suitability Index (TSI), designed to reclassify climate data relative to optimal conditions for vector establishment, could be applied to this context. Finally, we extrapolated our models to estimate the impact of a false-positive BFV epidemic in 2013. Creating these models and comparing variations in periodicities may provide insight into historical outbreaks as well as future patterns of mosquito-borne diseases.

A multivariate spatial mixture model for areal data: examining regional differences in standardized test scores

PubMed Central

Neelon, Brian; Gelfand, Alan E.; Miranda, Marie Lynn

2013-01-01

Summary Researchers in the health and social sciences often wish to examine joint spatial patterns for two or more related outcomes. Examples include infant birth weight and gestational length, psychosocial and behavioral indices, and educational test scores from different cognitive domains. We propose a multivariate spatial mixture model for the joint analysis of continuous individual-level outcomes that are referenced to areal units. The responses are modeled as a finite mixture of multivariate normals, which accommodates a wide range of marginal response distributions and allows investigators to examine covariate effects within subpopulations of interest. The model has a hierarchical structure built at the individual level (i.e., individuals are nested within areal units), and thus incorporates both individual- and areal-level predictors as well as spatial random effects for each mixture component. Conditional autoregressive (CAR) priors on the random effects provide spatial smoothing and allow the shape of the multivariate distribution to vary flexibly across geographic regions. We adopt a Bayesian modeling approach and develop an efficient Markov chain Monte Carlo model fitting algorithm that relies primarily on closed-form full conditionals. We use the model to explore geographic patterns in end-of-grade math and reading test scores among school-age children in North Carolina. PMID:26401059

Corynebacterium glutamicum MTCC 2745 immobilized on granular activated carbon/MnFe2O4 composite: A novel biosorbent for removal of As(III) and As(V) ions

NASA Astrophysics Data System (ADS)

Podder, M. S.; Majumder, C. B.

2016-11-01

The optimization of biosorption/bioaccumulation process of both As(III) and As(V) has been investigated by using the biosorbent; biofilm of Corynebacterium glutamicum MTCC 2745 supported on granular activated carbon/MnFe2O4 composite (MGAC). The presence of functional groups on the cell wall surface of the biomass that may interact with the metal ions was proved by FT-IR. To determine the most appropriate correlation for the equilibrium curves employing the procedure of the non-linear regression for curve fitting analysis, isotherm studies were performed for As(III) and As(V) using 30 isotherm models. The pattern of biosorption/bioaccumulation fitted well with Vieth-Sladek isotherm model for As(III) and Brouers-Sotolongo and Fritz-Schlunder-V isotherm models for As(V). The maximum biosorption/bioaccumulation capacity estimated using Langmuir model were 2584.668 mg/g for As(III) and 2651.675 mg/g for As(V) at 30 °C temperature and 220 min contact time. The results showed that As(III) and As(V) removal was strongly pH-dependent with an optimum pH value of 7.0. D-R isotherm studies specified that ion exchange might play a prominent role.

Modeling and Classification of Kinetic Patterns of Dynamic Metabolic Biomarkers in Physical Activity

PubMed Central

Breit, Marc; Netzer, Michael

2015-01-01

The objectives of this work were the classification of dynamic metabolic biomarker candidates and the modeling and characterization of kinetic regulatory mechanisms in human metabolism with response to external perturbations by physical activity. Longitudinal metabolic concentration data of 47 individuals from 4 different groups were examined, obtained from a cycle ergometry cohort study. In total, 110 metabolites (within the classes of acylcarnitines, amino acids, and sugars) were measured through a targeted metabolomics approach, combining tandem mass spectrometry (MS/MS) with the concept of stable isotope dilution (SID) for metabolite quantitation. Biomarker candidates were selected by combined analysis of maximum fold changes (MFCs) in concentrations and P-values resulting from statistical hypothesis testing. Characteristic kinetic signatures were identified through a mathematical modeling approach utilizing polynomial fitting. Modeled kinetic signatures were analyzed for groups with similar behavior by applying hierarchical cluster analysis. Kinetic shape templates were characterized, defining different forms of basic kinetic response patterns, such as sustained, early, late, and other forms, that can be used for metabolite classification. Acetylcarnitine (C2), showing a late response pattern and having the highest values in MFC and statistical significance, was classified as late marker and ranked as strong predictor (MFC = 1.97, P < 0.001). In the class of amino acids, highest values were shown for alanine (MFC = 1.42, P < 0.001), classified as late marker and strong predictor. Glucose yields a delayed response pattern, similar to a hockey stick function, being classified as delayed marker and ranked as moderate predictor (MFC = 1.32, P < 0.001). These findings coincide with existing knowledge on central metabolic pathways affected in exercise physiology, such as β-oxidation of fatty acids, glycolysis, and glycogenolysis. The presented modeling approach demonstrates high potential for dynamic biomarker identification and the investigation of kinetic mechanisms in disease or pharmacodynamics studies using MS data from longitudinal cohort studies. PMID:26317529

A Parametric Model of Shoulder Articulation for Virtual Assessment of Space Suit Fit

NASA Technical Reports Server (NTRS)

Kim, K. Han; Young, Karen S.; Bernal, Yaritza; Boppana, Abhishektha; Vu, Linh Q.; Benson, Elizabeth A.; Jarvis, Sarah; Rajulu, Sudhakar L.

2016-01-01

Shoulder injury is one of the most severe risks that have the potential to impair crewmembers' performance and health in long duration space flight. Overall, 64% of crewmembers experience shoulder pain after extra-vehicular training in a space suit, and 14% of symptomatic crewmembers require surgical repair (Williams & Johnson, 2003). Suboptimal suit fit, in particular at the shoulder region, has been identified as one of the predominant risk factors. However, traditional suit fit assessments and laser scans represent only a single person's data, and thus may not be generalized across wide variations of body shapes and poses. The aim of this work is to develop a software tool based on a statistical analysis of a large dataset of crewmember body shapes. This tool can accurately predict the skin deformation and shape variations for any body size and shoulder pose for a target population, from which the geometry can be exported and evaluated against suit models in commercial CAD software. A preliminary software tool was developed by statistically analyzing 150 body shapes matched with body dimension ranges specified in the Human-Systems Integration Requirements of NASA ("baseline model"). Further, the baseline model was incorporated with shoulder joint articulation ("articulation model"), using additional subjects scanned in a variety of shoulder poses across a pre-specified range of motion. Scan data was cleaned and aligned using body landmarks. The skin deformation patterns were dimensionally reduced and the co-variation with shoulder angles was analyzed. A software tool is currently in development and will be presented in the final proceeding. This tool would allow suit engineers to parametrically generate body shapes in strategically targeted anthropometry dimensions and shoulder poses. This would also enable virtual fit assessments, with which the contact volume and clearance between the suit and body surface can be predictively quantified at reduced time and cost.

Condensation and fractionation of rare earths in the solar nebula

NASA Technical Reports Server (NTRS)

Davis, A. M.; Grossman, L.

1979-01-01

The condensation behavior of the rare earth elements in the solar nebula is calculated on the basis of the most recent thermodynamic data in order to construct a model explaining group II rare earth element patterns in Allende inclusions. Models considered all involve the removal of large fractions of the more refractory heavy rare earth elements in an early condensate, followed by the condensation of the remainder at a lower temperature. It is shown that the model of Boynton (1975) in which one rare earth element component is dissolved nonideally in perovskite according to relative activity coefficients can not reasonably be made to fit the observed group II patterns. A model in which two rare earth components control the patterns and dissolve ideally in perovskite is proposed and shown to be able to account for the 20 patterns by variations of the perovskite removal temperature and the relative proportions of the two components.

Comparison the Marginal and Internal Fit of Metal Copings Cast from Wax Patterns Fabricated by CAD/CAM and Conventional Wax up Techniques.

PubMed

Vojdani, M; Torabi, K; Farjood, E; Khaledi, Aar

2013-09-01

Metal-ceramic crowns are most commonly used as the complete coverage restorations in clinical daily use. Disadvantages of conventional hand-made wax-patterns introduce some alternative ways by means of CAD/CAM technologies. This study compares the marginal and internal fit of copings cast from CAD/CAM and conventional fabricated wax-patterns. Twenty-four standardized brass dies were prepared and randomly divided into 2 groups according to the wax-patterns fabrication method (CAD/CAM technique and conventional method) (n=12). All the wax-patterns were fabricated in a standard fashion by means of contour, thickness and internal relief (M1-M12: representative of CAD/CAM group, C1-C12: representative of conventional group). CAD/CAM milling machine (Cori TEC 340i; imes-icore GmbH, Eiterfeld, Germany) was used to fabricate the CAD/CAM group wax-patterns. The copings cast from 24 wax-patterns were cemented to the corresponding dies. For all the coping-die assemblies cross-sectional technique was used to evaluate the marginal and internal fit at 15 points. The Student's t- test was used for statistical analysis (α=0.05). The overall mean (SD) for absolute marginal discrepancy (AMD) was 254.46 (25.10) um for CAD/CAM group and 88.08(10.67) um for conventional group (control). The overall mean of internal gap total (IGT) was 110.77(5.92) um for CAD/CAM group and 76.90 (10.17) um for conventional group. The Student's t-test revealed significant differences between 2 groups. Marginal and internal gaps were found to be significantly higher at all measured areas in CAD/CAM group than conventional group (p< 0.001). Within limitations of this study, conventional method of wax-pattern fabrication produced copings with significantly better marginal and internal fit than CAD/CAM (machine-milled) technique. All the factors for 2 groups were standardized except wax pattern fabrication technique, therefore, only the conventional group results in copings with clinically acceptable margins of less than 120um.

Comparison the Marginal and Internal Fit of Metal Copings Cast from Wax Patterns Fabricated by CAD/CAM and Conventional Wax up Techniques

PubMed Central

Vojdani, M; Torabi, K; Farjood, E; Khaledi, AAR

2013-01-01

Statement of Problem: Metal-ceramic crowns are most commonly used as the complete coverage restorations in clinical daily use. Disadvantages of conventional hand-made wax-patterns introduce some alternative ways by means of CAD/CAM technologies. Purpose: This study compares the marginal and internal fit of copings cast from CAD/CAM and conventional fabricated wax-patterns. Materials and Method: Twenty-four standardized brass dies were prepared and randomly divided into 2 groups according to the wax-patterns fabrication method (CAD/CAM technique and conventional method) (n=12). All the wax-patterns were fabricated in a standard fashion by means of contour, thickness and internal relief (M1-M12: representative of CAD/CAM group, C1-C12: representative of conventional group). CAD/CAM milling machine (Cori TEC 340i; imes-icore GmbH, Eiterfeld, Germany) was used to fabricate the CAD/CAM group wax-patterns. The copings cast from 24 wax-patterns were cemented to the corresponding dies. For all the coping-die assemblies cross-sectional technique was used to evaluate the marginal and internal fit at 15 points. The Student’s t- test was used for statistical analysis (α=0.05). Results: The overall mean (SD) for absolute marginal discrepancy (AMD) was 254.46 (25.10) um for CAD/CAM group and 88.08(10.67) um for conventional group (control). The overall mean of internal gap total (IGT) was 110.77(5.92) um for CAD/CAM group and 76.90 (10.17) um for conventional group. The Student’s t-test revealed significant differences between 2 groups. Marginal and internal gaps were found to be significantly higher at all measured areas in CAD/CAM group than conventional group (p< 0.001). Conclusion: Within limitations of this study, conventional method of wax-pattern fabrication produced copings with significantly better marginal and internal fit than CAD/CAM (machine-milled) technique. All the factors for 2 groups were standardized except wax pattern fabrication technique, therefore, only the conventional group results in copings with clinically acceptable margins of less than 120um. PMID:24724133

A MODEL TO EVALUATE PAST EXPOSURE TO 2,3,7,8 ...

EPA Pesticide Factsheets

Data from several studies suggest that concentrations of dioxins rose in the environment from the 1930s to about the 1960s/70s and have been declining over the last decade or two. The most direct evidence of this trend comes from lake core sediments, which can be used to estimate past atmospheric depositions of dioxins. The primary source of human exposure to dioxins is through the food supply. The pathway relating atmospheric depositions to concentrations in food is quite complex, and accordingly, it is not known to what extent the trend in human exposure mirrors the trend in atmospheric depositions. This paper describes an attempt to statistically reconstruct the pattern of past human exposure to the most toxic dioxin congener, 2,3,7,8-TCDD (abbreviated TCDD), through use of a simple pharmacokinetic (PK) model which included a time-varying TCDD exposure dose. This PK model was fit to TCDD body burden data (i.e., TCDD concentrations in lipid) from five U.S. studies dating from 1972 to 1987 and covering a wide age range. A Bayesian statistical approach was used to fit TCDD exposure; model parameters other than exposure were all previously known or estimated from other data sources. The primary results of the analysis are as follows: 1.) use of a time-varying exposure dose provided a far better fit to the TCDD body burden data than did using a dose that was constant over time; this is strong evidence that exposure to TCDD has, in fact, varied during the

Interrelationship of Knowledge, Interest, and Recall: Assessing a Model of Domain Learning.

ERIC Educational Resources Information Center

Alexander, Patricia A.; And Others

1995-01-01

Two experiments involving 125 college and graduate students examined the interrelationship of subject-matter knowledge, interest, and recall in the field of human immunology and biology and assessed cross-domain performance in physics. Patterns of knowledge, interest, and performance fit well with the premises of the Model of Domain Learning. (SLD)

Whole School English Learner Reform: A Heuristic Approach to Professional Learning in Middle Schools

ERIC Educational Resources Information Center

Plough, Bobbie; Garcia, Ray

2015-01-01

This work highlights a heuristic model for professional learning while examining the implementation of a reform initiative. The researchers used longitudinal data collected from surveys to develop and fit a model of professional learning where patterns of interaction among teachers changed the discussion about English learner instruction. Data…

A comparative study between nonlinear regression and artificial neural network approaches for modelling wild oat (Avena fatua) field emergence

USDA-ARS?s Scientific Manuscript database

Non-linear regression techniques are used widely to fit weed field emergence patterns to soil microclimatic indices using S-type functions. Artificial neural networks present interesting and alternative features for such modeling purposes. In this work, a univariate hydrothermal-time based Weibull m...

Extreme deconstruction supports niche conservatism driving New World bird diversity

NASA Astrophysics Data System (ADS)

Diniz-Filho, José Alexandre Felizola; Rangel, Thiago Fernando; dos Santos, Mariana Rocha

2012-08-01

It is expected that if environment fully establishes the borders of species geographic distribution, then richness patterns will arise simple by changing parameters on how environment affect each of the species. However, if other mechanisms (i.e., non-equilibrium of species' distributions with climate and historical contingency, shifts in adaptive peaks or biotic interactions) are driving species geographic distribution, models for species distribution and richness will not entirely match. Here we used the extreme deconstruction principle to test how niche conservatism keeping species geographic distributions in certain parts of environmental space drives richness patterns in New World birds, under tropical niche conservatism. Eight environmental variables were used to model the geographic distribution of 2790 species within 28 bird families using a GLM. Spatial patterns in richness for each of these families were also modeled as a function of these same variables using a standard OLS regression. Fit of these two types of models (mean MacFadden's ρ2 for GLM and R2 of OLS) across families and the match between GLM and OLS standardized slopes within and among bird families were then compared. We found a positive and significant correlation between GLM and OLS model fit (r = 0.601; P < 0.01), indicating that when environment strongly determine richness of a family, it also explains its species geographic distributions. The match between GLM and OLS slopes is significantly correlated with families' phylogenetic root distance (r = -0.467; P = 0.012), so that more basal families tend to have a better match between environmental drivers of richness and geographic distribution models. This is expected under tropical niche conservatism model and provides an integrated explanation on how processes at a lower hierarchical level (species' geographic distribution) drive diversity patterns.

Fitting monthly Peninsula Malaysian rainfall using Tweedie distribution

NASA Astrophysics Data System (ADS)

Yunus, R. M.; Hasan, M. M.; Zubairi, Y. Z.

2017-09-01

In this study, the Tweedie distribution was used to fit the monthly rainfall data from 24 monitoring stations of Peninsula Malaysia for the period from January, 2008 to April, 2015. The aim of the study is to determine whether the distributions within the Tweedie family fit well the monthly Malaysian rainfall data. Within the Tweedie family, the gamma distribution is generally used for fitting the rainfall totals, however the Poisson-gamma distribution is more useful to describe two important features of rainfall pattern, which are the occurrences (dry months) and the amount (wet months). First, the appropriate distribution of the monthly rainfall was identified within the Tweedie family for each station. Then, the Tweedie Generalised Linear Model (GLM) with no explanatory variable was used to model the monthly rainfall data. Graphical representation was used to assess model appropriateness. The QQ plots of quantile residuals show that the Tweedie models fit the monthly rainfall data better for majority of the stations in the west coast and mid land than those in the east coast of Peninsula. This significant finding suggests that the best fitted distribution depends on the geographical location of the monitoring station. In this paper, a simple model is developed for generating synthetic rainfall data for use in various areas, including agriculture and irrigation. We have showed that the data that were simulated using the Tweedie distribution have fairly similar frequency histogram to that of the actual data. Both the mean number of rainfall events and mean amount of rain for a month were estimated simultaneously for the case that the Poisson gamma distribution fits the data reasonably well. Thus, this work complements previous studies that fit the rainfall amount and the occurrence of rainfall events separately, each to a different distribution.

Adaptive Evolution under Extreme Genetic Drift in Oxidatively Stressed Caenorhabditis elegans

PubMed Central

Christy, Stephen F; Wernick, Riana I; Lue, Michael J; Velasco, Griselda; Howe, Dana K; Denver, Dee R

2017-01-01

Abstract A mutation-accumulation (MA) experiment with Caenorhabditis elegans nematodes was conducted in which replicate, independently evolving lines were initiated from a low-fitness mitochondrial electron transport chain mutant, gas-1. The original intent of the study was to assess the effect of electron transport chain dysfunction involving elevated reactive oxygen species production on patterns of spontaneous germline mutation. In contrast to results of standard MA experiments, gas-1 MA lines evolved slightly higher mean fitness alongside reduced among-line genetic variance compared with their ancestor. Likewise, the gas-1 MA lines experienced partial recovery to wildtype reactive oxygen species levels. Whole-genome sequencing and analysis revealed that the molecular spectrum but not the overall rate of nuclear DNA mutation differed from wildtype patterns. Further analysis revealed an enrichment of mutations in loci that occur in a gas-1-centric region of the C. elegans interactome, and could be classified into a small number of functional-genomic categories. Characterization of a backcrossed four-mutation set isolated from one gas-1 MA line revealed this combination to be beneficial on both gas-1 mutant and wildtype genetic backgrounds. Our combined results suggest that selection favoring beneficial mutations can be powerful even under unfavorable population genetic conditions, and agree with fitness landscape theory predicting an inverse relationship between population fitness and the likelihood of adaptation. PMID:29069345

Two Aspects of the Simplex Model: Goodness of Fit to Linear Growth Curve Structures and the Analysis of Mean Trends.

ERIC Educational Resources Information Center

Mandys, Frantisek; Dolan, Conor V.; Molenaar, Peter C. M.

1994-01-01

Studied the conditions under which the quasi-Markov simplex model fits a linear growth curve covariance structure and determined when the model is rejected. Presents a quasi-Markov simplex model with structured means and gives an example. (SLD)

Some Statistics for Assessing Person-Fit Based on Continuous-Response Models

ERIC Educational Resources Information Center

Ferrando, Pere Joan

2010-01-01

This article proposes several statistics for assessing individual fit based on two unidimensional models for continuous responses: linear factor analysis and Samejima's continuous response model. Both models are approached using a common framework based on underlying response variables and are formulated at the individual level as fixed regression…

Analysis technique for controlling system wavefront error with active/adaptive optics

NASA Astrophysics Data System (ADS)

Genberg, Victor L.; Michels, Gregory J.

2017-08-01

The ultimate goal of an active mirror system is to control system level wavefront error (WFE). In the past, the use of this technique was limited by the difficulty of obtaining a linear optics model. In this paper, an automated method for controlling system level WFE using a linear optics model is presented. An error estimate is included in the analysis output for both surface error disturbance fitting and actuator influence function fitting. To control adaptive optics, the technique has been extended to write system WFE in state space matrix form. The technique is demonstrated by example with SigFit, a commercially available tool integrating mechanical analysis with optical analysis.

Graphical modeling of gene expression in monocytes suggests molecular mechanisms explaining increased atherosclerosis in smokers.

PubMed

Verdugo, Ricardo A; Zeller, Tanja; Rotival, Maxime; Wild, Philipp S; Münzel, Thomas; Lackner, Karl J; Weidmann, Henri; Ninio, Ewa; Trégouët, David-Alexandre; Cambien, François; Blankenberg, Stefan; Tiret, Laurence

2013-01-01

Smoking is a risk factor for atherosclerosis with reported widespread effects on gene expression in circulating blood cells. We hypothesized that a molecular signature mediating the relation between smoking and atherosclerosis may be found in the transcriptome of circulating monocytes. Genome-wide expression profiles and counts of atherosclerotic plaques in carotid arteries were collected in 248 smokers and 688 non-smokers from the general population. Patterns of co-expressed genes were identified by Independent Component Analysis (ICA) and network structure of the pattern-specific gene modules was inferred by the PC-algorithm. A likelihood-based causality test was implemented to select patterns that fit models containing a path "smoking→gene expression→plaques". Robustness of the causal inference was assessed by bootstrapping. At a FDR ≤0.10, 3,368 genes were associated to smoking or plaques, of which 93% were associated to smoking only. SASH1 showed the strongest association to smoking and PPARG the strongest association to plaques. Twenty-nine gene patterns were identified by ICA. Modules containing SASH1 and PPARG did not show evidence for the "smoking→gene expression→plaques" causality model. Conversely, three modules had good support for causal effects and exhibited a network topology consistent with gene expression mediating the relation between smoking and plaques. The network with the strongest support for causal effects was connected to plaques through SLC39A8, a gene with known association to HDL-cholesterol and cellular uptake of cadmium from tobacco, while smoking was directly connected to GAS6, a gene reported to have anti-inflammatory effects in atherosclerosis and to be up-regulated in the placenta of women smoking during pregnancy. Our analysis of the transcriptome of monocytes recovered genes relevant for association to smoking and atherosclerosis, and connected genes that before, were only studied in separate contexts. Inspection of correlation structure revealed candidates that would be missed by expression-phenotype association analysis alone.

Graphical Modeling of Gene Expression in Monocytes Suggests Molecular Mechanisms Explaining Increased Atherosclerosis in Smokers

PubMed Central

Verdugo, Ricardo A.; Zeller, Tanja; Rotival, Maxime; Wild, Philipp S.; Münzel, Thomas; Lackner, Karl J.; Weidmann, Henri; Ninio, Ewa; Trégouët, David-Alexandre; Cambien, François; Blankenberg, Stefan; Tiret, Laurence

2013-01-01

Smoking is a risk factor for atherosclerosis with reported widespread effects on gene expression in circulating blood cells. We hypothesized that a molecular signature mediating the relation between smoking and atherosclerosis may be found in the transcriptome of circulating monocytes. Genome-wide expression profiles and counts of atherosclerotic plaques in carotid arteries were collected in 248 smokers and 688 non-smokers from the general population. Patterns of co-expressed genes were identified by Independent Component Analysis (ICA) and network structure of the pattern-specific gene modules was inferred by the PC-algorithm. A likelihood-based causality test was implemented to select patterns that fit models containing a path “smoking→gene expression→plaques”. Robustness of the causal inference was assessed by bootstrapping. At a FDR ≤0.10, 3,368 genes were associated to smoking or plaques, of which 93% were associated to smoking only. SASH1 showed the strongest association to smoking and PPARG the strongest association to plaques. Twenty-nine gene patterns were identified by ICA. Modules containing SASH1 and PPARG did not show evidence for the “smoking→gene expression→plaques” causality model. Conversely, three modules had good support for causal effects and exhibited a network topology consistent with gene expression mediating the relation between smoking and plaques. The network with the strongest support for causal effects was connected to plaques through SLC39A8, a gene with known association to HDL-cholesterol and cellular uptake of cadmium from tobacco, while smoking was directly connected to GAS6, a gene reported to have anti-inflammatory effects in atherosclerosis and to be up-regulated in the placenta of women smoking during pregnancy. Our analysis of the transcriptome of monocytes recovered genes relevant for association to smoking and atherosclerosis, and connected genes that before, were only studied in separate contexts. Inspection of correlation structure revealed candidates that would be missed by expression-phenotype association analysis alone. PMID:23372645

Anxiety as a context for understanding associations between hypochondriasis, obsessive-compulsive, and panic attack symptoms.

PubMed

Longley, Susan L; Calamari, John E; Wu, Kevin; Wade, Michael

2010-12-01

In the context of the integrative model of anxiety and depression, we examined whether the essential problem of hypochondriasis is one of anxiety. When analyzed, data from a large nonclinical sample corresponded to the integrative model's characterization of anxiety as composed of both broad, shared and specific, unique symptom factors. The unique hypochondriasis, obsessive-compulsive, and panic attack symptom factors all had correlational patterns expected of anxiety with the shared, broad factors of negative emotionality and positive emotionality. A confirmatory factor analysis showed a higher-order, bifactor model was the best fit to our data; the shared and the unique hypochondriasis and anxiety symptom factors both contributed substantial variance. This study provides refinements to an empirically based taxonomy and clarifies what hypochondriasis is and, importantly, what it is not. Copyright © 2010. Published by Elsevier Ltd.

TransFit: Finite element analysis data fitting software

NASA Technical Reports Server (NTRS)

Freeman, Mark

1993-01-01

The Advanced X-Ray Astrophysics Facility (AXAF) mission support team has made extensive use of geometric ray tracing to analyze the performance of AXAF developmental and flight optics. One important aspect of this performance modeling is the incorporation of finite element analysis (FEA) data into the surface deformations of the optical elements. TransFit is software designed for the fitting of FEA data of Wolter I optical surface distortions with a continuous surface description which can then be used by SAO's analytic ray tracing software, currently OSAC (Optical Surface Analysis Code). The improved capabilities of Transfit over previous methods include bicubic spline fitting of FEA data to accommodate higher spatial frequency distortions, fitted data visualization for assessing the quality of fit, the ability to accommodate input data from three FEA codes plus other standard formats, and options for alignment of the model coordinate system with the ray trace coordinate system. TransFit uses the AnswerGarden graphical user interface (GUI) to edit input parameters and then access routines written in PV-WAVE, C, and FORTRAN to allow the user to interactively create, evaluate, and modify the fit. The topics covered include an introduction to TransFit: requirements, designs philosophy, and implementation; design specifics: modules, parameters, fitting algorithms, and data displays; a procedural example; verification of performance; future work; and appendices on online help and ray trace results of the verification section.

Simultaneous overlay and CD measurement for double patterning: scatterometry and RCWA approach

NASA Astrophysics Data System (ADS)

Li, Jie; Liu, Zhuan; Rabello, Silvio; Dasari, Prasad; Kritsun, Oleg; Volkman, Catherine; Park, Jungchul; Singh, Lovejeet

2009-03-01

As optical lithography advances to 32 nm technology node and beyond, double patterning technology (DPT) has emerged as an attractive solution to circumvent the fundamental optical limitations. DPT poses unique demands on critical dimension (CD) uniformity and overlay control, making the tolerance decrease much faster than the rate at which critical dimension shrinks. This, in turn, makes metrology even more challenging. In the past, multi-pad diffractionbased overlay (DBO) using empirical approach has been shown to be an effective approach to measure overlay error associated with double patterning [1]. In this method, registration errors for double patterning were extracted from specially designed diffraction targets (three or four pads for each direction); CD variation is assumed negligible within each group of adjacent pads and not addressed in the measurement. In another paper, encouraging results were reported with a first attempt at simultaneously extracting overlay and CD parameters using scatterometry [2]. In this work, we apply scatterometry with a rigorous coupled wave analysis (RCWA) approach to characterize two double-patterning processes: litho-etch-litho-etch (LELE) and litho-freeze-litho-etch (LFLE). The advantage of performing rigorous modeling is to reduce the number of pads within each measurement target, thus reducing space requirement and improving throughput, and simultaneously extract CD and overlay information. This method measures overlay errors and CDs by fitting the optical signals with spectra calculated from a model of the targets. Good correlation is obtained between the results from this method and that of several reference techniques, including empirical multi-pad DBO, CD-SEM, and IBO. We also perform total measurement uncertainty (TMU) analysis to evaluate the overall performance. We demonstrate that scatterometry provides a promising solution to meet the challenging overlay metrology requirement in DPT.

Global, Local, and Graphical Person-Fit Analysis Using Person-Response Functions

ERIC Educational Resources Information Center

Emons, Wilco H. M.; Sijtsma, Klaas; Meijer, Rob R.

2005-01-01

Person-fit statistics test whether the likelihood of a respondent's complete vector of item scores on a test is low given the hypothesized item response theory model. This binary information may be insufficient for diagnosing the cause of a misfitting item-score vector. The authors propose a comprehensive methodology for person-fit analysis in the…

A necessarily complex model to explain the biogeography of the amphibians and reptiles of Madagascar.

PubMed

Brown, Jason L; Cameron, Alison; Yoder, Anne D; Vences, Miguel

2014-10-09

Pattern and process are inextricably linked in biogeographic analyses, though we can observe pattern, we must infer process. Inferences of process are often based on ad hoc comparisons using a single spatial predictor. Here, we present an alternative approach that uses mixed-spatial models to measure the predictive potential of combinations of hypotheses. Biodiversity patterns are estimated from 8,362 occurrence records from 745 species of Malagasy amphibians and reptiles. By incorporating 18 spatially explicit predictions of 12 major biogeographic hypotheses, we show that mixed models greatly improve our ability to explain the observed biodiversity patterns. We conclude that patterns are influenced by a combination of diversification processes rather than by a single predominant mechanism. A 'one-size-fits-all' model does not exist. By developing a novel method for examining and synthesizing spatial parameters such as species richness, endemism and community similarity, we demonstrate the potential of these analyses for understanding the diversification history of Madagascar's biota.

Masking Misfit in Confirmatory Factor Analysis by Increasing Unique Variances: A Cautionary Note on the Usefulness of Cutoff Values of Fit Indices

ERIC Educational Resources Information Center

Heene, Moritz; Hilbert, Sven; Draxler, Clemens; Ziegler, Matthias; Buhner, Markus

2011-01-01

Fit indices are widely used in order to test the model fit for structural equation models. In a highly influential study, Hu and Bentler (1999) showed that certain cutoff values for these indices could be derived, which, over time, has led to the reification of these suggested thresholds as "golden rules" for establishing the fit or other aspects…

An integrated model-driven method for in-treatment upper airway motion tracking using cine MRI in head and neck radiation therapy

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

Li, Hua, E-mail: huli@radonc.wustl.edu; Chen, Hsin

Purpose: For the first time, MRI-guided radiation therapy systems can acquire cine images to dynamically monitor in-treatment internal organ motion. However, the complex head and neck (H&N) structures and low-contrast/resolution of on-board cine MRI images make automatic motion tracking a very challenging task. In this study, the authors proposed an integrated model-driven method to automatically track the in-treatment motion of the H&N upper airway, a complex and highly deformable region wherein internal motion often occurs in an either voluntary or involuntary manner, from cine MRI images for the analysis of H&N motion patterns. Methods: Considering the complex H&N structures andmore » ensuring automatic and robust upper airway motion tracking, the authors firstly built a set of linked statistical shapes (including face, face-jaw, and face-jaw-palate) using principal component analysis from clinically approved contours delineated on a set of training data. The linked statistical shapes integrate explicit landmarks and implicit shape representation. Then, a hierarchical model-fitting algorithm was developed to align the linked shapes on the first image frame of a to-be-tracked cine sequence and to localize the upper airway region. Finally, a multifeature level set contour propagation scheme was performed to identify the upper airway shape change, frame-by-frame, on the entire image sequence. The multifeature fitting energy, including the information of intensity variations, edge saliency, curve geometry, and temporal shape continuity, was minimized to capture the details of moving airway boundaries. Sagittal cine MR image sequences acquired from three H&N cancer patients were utilized to demonstrate the performance of the proposed motion tracking method. Results: The tracking accuracy was validated by comparing the results to the average of two manual delineations in 50 randomly selected cine image frames from each patient. The resulting average dice similarity coefficient (93.28%  ±  1.46%) and margin error (0.49  ±  0.12 mm) showed good agreement between the automatic and manual results. The comparison with three other deformable model-based segmentation methods illustrated the superior shape tracking performance of the proposed method. Large interpatient variations of swallowing frequency, swallowing duration, and upper airway cross-sectional area were observed from the testing cine image sequences. Conclusions: The proposed motion tracking method can provide accurate upper airway motion tracking results, and enable automatic and quantitative identification and analysis of in-treatment H&N upper airway motion. By integrating explicit and implicit linked-shape representations within a hierarchical model-fitting process, the proposed tracking method can process complex H&N structures and low-contrast/resolution cine MRI images. Future research will focus on the improvement of method reliability, patient motion pattern analysis for providing more information on patient-specific prediction of structure displacements, and motion effects on dosimetry for better H&N motion management in radiation therapy.« less

An integrated model-driven method for in-treatment upper airway motion tracking using cine MRI in head and neck radiation therapy.

PubMed

Li, Hua; Chen, Hsin-Chen; Dolly, Steven; Li, Harold; Fischer-Valuck, Benjamin; Victoria, James; Dempsey, James; Ruan, Su; Anastasio, Mark; Mazur, Thomas; Gach, Michael; Kashani, Rojano; Green, Olga; Rodriguez, Vivian; Gay, Hiram; Thorstad, Wade; Mutic, Sasa

2016-08-01

For the first time, MRI-guided radiation therapy systems can acquire cine images to dynamically monitor in-treatment internal organ motion. However, the complex head and neck (H&N) structures and low-contrast/resolution of on-board cine MRI images make automatic motion tracking a very challenging task. In this study, the authors proposed an integrated model-driven method to automatically track the in-treatment motion of the H&N upper airway, a complex and highly deformable region wherein internal motion often occurs in an either voluntary or involuntary manner, from cine MRI images for the analysis of H&N motion patterns. Considering the complex H&N structures and ensuring automatic and robust upper airway motion tracking, the authors firstly built a set of linked statistical shapes (including face, face-jaw, and face-jaw-palate) using principal component analysis from clinically approved contours delineated on a set of training data. The linked statistical shapes integrate explicit landmarks and implicit shape representation. Then, a hierarchical model-fitting algorithm was developed to align the linked shapes on the first image frame of a to-be-tracked cine sequence and to localize the upper airway region. Finally, a multifeature level set contour propagation scheme was performed to identify the upper airway shape change, frame-by-frame, on the entire image sequence. The multifeature fitting energy, including the information of intensity variations, edge saliency, curve geometry, and temporal shape continuity, was minimized to capture the details of moving airway boundaries. Sagittal cine MR image sequences acquired from three H&N cancer patients were utilized to demonstrate the performance of the proposed motion tracking method. The tracking accuracy was validated by comparing the results to the average of two manual delineations in 50 randomly selected cine image frames from each patient. The resulting average dice similarity coefficient (93.28%  ±  1.46%) and margin error (0.49  ±  0.12 mm) showed good agreement between the automatic and manual results. The comparison with three other deformable model-based segmentation methods illustrated the superior shape tracking performance of the proposed method. Large interpatient variations of swallowing frequency, swallowing duration, and upper airway cross-sectional area were observed from the testing cine image sequences. The proposed motion tracking method can provide accurate upper airway motion tracking results, and enable automatic and quantitative identification and analysis of in-treatment H&N upper airway motion. By integrating explicit and implicit linked-shape representations within a hierarchical model-fitting process, the proposed tracking method can process complex H&N structures and low-contrast/resolution cine MRI images. Future research will focus on the improvement of method reliability, patient motion pattern analysis for providing more information on patient-specific prediction of structure displacements, and motion effects on dosimetry for better H&N motion management in radiation therapy.

Model-Free Estimation of Tuning Curves and Their Attentional Modulation, Based on Sparse and Noisy Data.

PubMed

Helmer, Markus; Kozyrev, Vladislav; Stephan, Valeska; Treue, Stefan; Geisel, Theo; Battaglia, Demian

2016-01-01

Tuning curves are the functions that relate the responses of sensory neurons to various values within one continuous stimulus dimension (such as the orientation of a bar in the visual domain or the frequency of a tone in the auditory domain). They are commonly determined by fitting a model e.g. a Gaussian or other bell-shaped curves to the measured responses to a small subset of discrete stimuli in the relevant dimension. However, as neuronal responses are irregular and experimental measurements noisy, it is often difficult to determine reliably the appropriate model from the data. We illustrate this general problem by fitting diverse models to representative recordings from area MT in rhesus monkey visual cortex during multiple attentional tasks involving complex composite stimuli. We find that all models can be well-fitted, that the best model generally varies between neurons and that statistical comparisons between neuronal responses across different experimental conditions are affected quantitatively and qualitatively by specific model choices. As a robust alternative to an often arbitrary model selection, we introduce a model-free approach, in which features of interest are extracted directly from the measured response data without the need of fitting any model. In our attentional datasets, we demonstrate that data-driven methods provide descriptions of tuning curve features such as preferred stimulus direction or attentional gain modulations which are in agreement with fit-based approaches when a good fit exists. Furthermore, these methods naturally extend to the frequent cases of uncertain model selection. We show that model-free approaches can identify attentional modulation patterns, such as general alterations of the irregular shape of tuning curves, which cannot be captured by fitting stereotyped conventional models. Finally, by comparing datasets across different conditions, we demonstrate effects of attention that are cell- and even stimulus-specific. Based on these proofs-of-concept, we conclude that our data-driven methods can reliably extract relevant tuning information from neuronal recordings, including cells whose seemingly haphazard response curves defy conventional fitting approaches.

Accounting for non-independent detection when estimating abundance of organisms with a Bayesian approach

USGS Publications Warehouse

Martin, Julien; Royle, J. Andrew; MacKenzie, Darryl I.; Edwards, Holly H.; Kery, Marc; Gardner, Beth

2011-01-01

Summary 1. Binomial mixture models use repeated count data to estimate abundance. They are becoming increasingly popular because they provide a simple and cost-effective way to account for imperfect detection. However, these models assume that individuals are detected independently of each other. This assumption may often be violated in the field. For instance, manatees (Trichechus manatus latirostris) may surface in turbid water (i.e. become available for detection during aerial surveys) in a correlated manner (i.e. in groups). However, correlated behaviour, affecting the non-independence of individual detections, may also be relevant in other systems (e.g. correlated patterns of singing in birds and amphibians). 2. We extend binomial mixture models to account for correlated behaviour and therefore to account for non-independent detection of individuals. We simulated correlated behaviour using beta-binomial random variables. Our approach can be used to simultaneously estimate abundance, detection probability and a correlation parameter. 3. Fitting binomial mixture models to data that followed a beta-binomial distribution resulted in an overestimation of abundance even for moderate levels of correlation. In contrast, the beta-binomial mixture model performed considerably better in our simulation scenarios. We also present a goodness-of-fit procedure to evaluate the fit of beta-binomial mixture models. 4. We illustrate our approach by fitting both binomial and beta-binomial mixture models to aerial survey data of manatees in Florida. We found that the binomial mixture model did not fit the data, whereas there was no evidence of lack of fit for the beta-binomial mixture model. This example helps illustrate the importance of using simulations and assessing goodness-of-fit when analysing ecological data with N-mixture models. Indeed, both the simulations and the goodness-of-fit procedure highlighted the limitations of the standard binomial mixture model for aerial manatee surveys. 5. Overestimation of abundance by binomial mixture models owing to non-independent detections is problematic for ecological studies, but also for conservation. For example, in the case of endangered species, it could lead to inappropriate management decisions, such as downlisting. These issues will be increasingly relevant as more ecologists apply flexible N-mixture models to ecological data.

Model-Free Estimation of Tuning Curves and Their Attentional Modulation, Based on Sparse and Noisy Data

PubMed Central

Helmer, Markus; Kozyrev, Vladislav; Stephan, Valeska; Treue, Stefan; Geisel, Theo; Battaglia, Demian

2016-01-01

Tuning curves are the functions that relate the responses of sensory neurons to various values within one continuous stimulus dimension (such as the orientation of a bar in the visual domain or the frequency of a tone in the auditory domain). They are commonly determined by fitting a model e.g. a Gaussian or other bell-shaped curves to the measured responses to a small subset of discrete stimuli in the relevant dimension. However, as neuronal responses are irregular and experimental measurements noisy, it is often difficult to determine reliably the appropriate model from the data. We illustrate this general problem by fitting diverse models to representative recordings from area MT in rhesus monkey visual cortex during multiple attentional tasks involving complex composite stimuli. We find that all models can be well-fitted, that the best model generally varies between neurons and that statistical comparisons between neuronal responses across different experimental conditions are affected quantitatively and qualitatively by specific model choices. As a robust alternative to an often arbitrary model selection, we introduce a model-free approach, in which features of interest are extracted directly from the measured response data without the need of fitting any model. In our attentional datasets, we demonstrate that data-driven methods provide descriptions of tuning curve features such as preferred stimulus direction or attentional gain modulations which are in agreement with fit-based approaches when a good fit exists. Furthermore, these methods naturally extend to the frequent cases of uncertain model selection. We show that model-free approaches can identify attentional modulation patterns, such as general alterations of the irregular shape of tuning curves, which cannot be captured by fitting stereotyped conventional models. Finally, by comparing datasets across different conditions, we demonstrate effects of attention that are cell- and even stimulus-specific. Based on these proofs-of-concept, we conclude that our data-driven methods can reliably extract relevant tuning information from neuronal recordings, including cells whose seemingly haphazard response curves defy conventional fitting approaches. PMID:26785378

Combining optimization methods with response spectra curve-fitting toward improved damping ratio estimation

NASA Astrophysics Data System (ADS)

Brewick, Patrick T.; Smyth, Andrew W.

2016-12-01

The authors have previously shown that many traditional approaches to operational modal analysis (OMA) struggle to properly identify the modal damping ratios for bridges under traffic loading due to the interference caused by the driving frequencies of the traffic loads. This paper presents a novel methodology for modal parameter estimation in OMA that overcomes the problems presented by driving frequencies and significantly improves the damping estimates. This methodology is based on finding the power spectral density (PSD) of a given modal coordinate, and then dividing the modal PSD into separate regions, left- and right-side spectra. The modal coordinates were found using a blind source separation (BSS) algorithm and a curve-fitting technique was developed that uses optimization to find the modal parameters that best fit each side spectra of the PSD. Specifically, a pattern-search optimization method was combined with a clustering analysis algorithm and together they were employed in a series of stages in order to improve the estimates of the modal damping ratios. This method was used to estimate the damping ratios from a simulated bridge model subjected to moving traffic loads. The results of this method were compared to other established OMA methods, such as Frequency Domain Decomposition (FDD) and BSS methods, and they were found to be more accurate and more reliable, even for modes that had their PSDs distorted or altered by driving frequencies.

SensibleSleep: A Bayesian Model for Learning Sleep Patterns from Smartphone Events

PubMed Central

Sekara, Vedran; Jonsson, Håkan; Larsen, Jakob Eg; Lehmann, Sune

2017-01-01

We propose a Bayesian model for extracting sleep patterns from smartphone events. Our method is able to identify individuals’ daily sleep periods and their evolution over time, and provides an estimation of the probability of sleep and wake transitions. The model is fitted to more than 400 participants from two different datasets, and we verify the results against ground truth from dedicated armband sleep trackers. We show that the model is able to produce reliable sleep estimates with an accuracy of 0.89, both at the individual and at the collective level. Moreover the Bayesian model is able to quantify uncertainty and encode prior knowledge about sleep patterns. Compared with existing smartphone-based systems, our method requires only screen on/off events, and is therefore much less intrusive in terms of privacy and more battery-efficient. PMID:28076375

SensibleSleep: A Bayesian Model for Learning Sleep Patterns from Smartphone Events.

PubMed

Cuttone, Andrea; Bækgaard, Per; Sekara, Vedran; Jonsson, Håkan; Larsen, Jakob Eg; Lehmann, Sune

2017-01-01

We propose a Bayesian model for extracting sleep patterns from smartphone events. Our method is able to identify individuals' daily sleep periods and their evolution over time, and provides an estimation of the probability of sleep and wake transitions. The model is fitted to more than 400 participants from two different datasets, and we verify the results against ground truth from dedicated armband sleep trackers. We show that the model is able to produce reliable sleep estimates with an accuracy of 0.89, both at the individual and at the collective level. Moreover the Bayesian model is able to quantify uncertainty and encode prior knowledge about sleep patterns. Compared with existing smartphone-based systems, our method requires only screen on/off events, and is therefore much less intrusive in terms of privacy and more battery-efficient.

Correlation of Respirator Fit Measured on Human Subjects and a Static Advanced Headform

PubMed Central

Bergman, Michael S.; He, Xinjian; Joseph, Michael E.; Zhuang, Ziqing; Heimbuch, Brian K.; Shaffer, Ronald E.; Choe, Melanie; Wander, Joseph D.

2015-01-01

This study assessed the correlation of N95 filtering face-piece respirator (FFR) fit between a Static Advanced Headform (StAH) and 10 human test subjects. Quantitative fit evaluations were performed on test subjects who made three visits to the laboratory. On each visit, one fit evaluation was performed on eight different FFRs of various model/size variations. Additionally, subject breathing patterns were recorded. Each fit evaluation comprised three two-minute exercises: “Normal Breathing,” “Deep Breathing,” and again “Normal Breathing.” The overall test fit factors (FF) for human tests were recorded. The same respirator samples were later mounted on the StAH and the overall test manikin fit factors (MFF) were assessed utilizing the recorded human breathing patterns. Linear regression was performed on the mean log10-transformed FF and MFF values to assess the relationship between the values obtained from humans and the StAH. This is the first study to report a positive correlation of respirator fit between a headform and test subjects. The linear regression by respirator resulted in R2 = 0.95, indicating a strong linear correlation between FF and MFF. For all respirators the geometric mean (GM) FF values were consistently higher than those of the GM MFF. For 50% of respirators, GM FF and GM MFF values were significantly different between humans and the StAH. For data grouped by subject/respirator combinations, the linear regression resulted in R2 = 0.49. A weaker correlation (R2 = 0.11) was found using only data paired by subject/respirator combination where both the test subject and StAH had passed a real-time leak check before performing the fit evaluation. For six respirators, the difference in passing rates between the StAH and humans was < 20%, while two respirators showed a difference of 29% and 43%. For data by test subject, GM FF and GM MFF values were significantly different for 40% of the subjects. Overall, the advanced headform system has potential for assessing fit for some N95 FFR model/sizes. PMID:25265037

Type A and B behavior patterns and self-reported health symptoms and stress: examining individual and organizational fit.

PubMed

Matteson, M T; Ivancevich, J M

1982-08-01

This article describes a preliminary investigation of the proposition that organizations, as well as people, can be classified along a Type A and B behavior pattern dimension and that the resulting match or lack thereof between individual and organizational behavior patterns is related to various health indices. A sample of 315 medical technologists were classified as either Type As or Bs and as working in either Type A or B environments. Results supported the hypotheses that (1) Type Bs in B organizations report the fewest negative health symptoms; (2) Type As in A organizations report the most; and (3) Type Bs in A organizations and Type As in B organizations report an intermediate level of symptoms. The results are treated within the framework of a person-environment fit model and the implications of the findings are discussed.

Rasch analysis of the Chedoke-McMaster Attitudes towards Children with Handicaps scale.

PubMed

Armstrong, Megan; Morris, Christopher; Tarrant, Mark; Abraham, Charles; Horton, Mike C

2017-02-01

Aim To assess whether the Chedoke-McMaster Attitudes towards Children with Handicaps (CATCH) 36-item total scale and subscales fit the unidimensional Rasch model. Method The CATCH was administered to 1881 children, aged 7-16 years in a cross-sectional survey. Data were used from a random sample of 416 for the initial Rasch analysis. The analysis was performed on the 36-item scale and then separately for each subscale. The analysis explored fit to the Rasch model in terms of overall scale fit, individual item fit, item response categories, and unidimensionality. Item bias for gender and school level was also assessed. Revised scales were then tested on an independent second random sample of 415 children. Results Analyses indicated that the 36-item overall scale was not unidimensional and did not fit the Rasch model. Two scales of affective attitudes and behavioural intention were retained after four items were removed from each due to misfit to the Rasch model. Additionally, the scaling was improved when the two most negative response categories were aggregated. There was no item bias by gender or school level on the revised scales. Items assessing cognitive attitudes did not fit the Rasch model and had low internal consistency as a scale. Conclusion Affective attitudes and behavioural intention CATCH sub-scales should be treated separately. Caution should be exercised when using the cognitive subscale. Implications for Rehabilitation The 36-item Chedoke-McMaster Attitudes towards Children with Handicaps (CATCH) scale as a whole did not fit the Rasch model; thus indicating a multi-dimensional scale. Researchers should use two revised eight-item subscales of affective attitudes and behavioural intentions when exploring interventions aiming to improve children's attitudes towards disabled people or factors associated with those attitudes. Researchers should use the cognitive subscale with caution, as it did not create a unidimensional and internally consistent scale. Therefore, conclusions drawn from this scale may not accurately reflect children's attitudes.

Forecasting selected specific age mortality rate of Malaysia by using Lee-Carter model

NASA Astrophysics Data System (ADS)

Shukri Kamaruddin, Halim; Ismail, Noriszura

2018-03-01

Observing mortality pattern and trend is an important subject for any country to maintain a good social-economy in the next projection years. The declining in mortality trend gives a good impression of what a government has done towards macro citizen in one nation. Selecting a particular mortality model can be a tricky based on the approached method adapting. Lee-Carter model is adapted because of its simplicity and reliability of the outcome results with approach of regression. Implementation of Lee-Carter in finding a fitted model and hence its projection has been used worldwide in most of mortality research in developed countries. This paper studies the mortality pattern of Malaysia in the past by using original model of Lee-Carter (1992) and hence its cross-sectional observation for a single age. The data is indexed by age of death and year of death from 1984 to 2012, in which are supplied by Department of Statistics Malaysia. The results are modelled by using RStudio and the keen analysis will focus on the trend and projection of mortality rate and age specific mortality rate in the future. This paper can be extended to different variants extensions of Lee-Carter or any stochastic mortality tool by using Malaysia mortality experience as a centre of the main issue.

Boundary curves of individual items in the distribution of total depressive symptom scores approximate an exponential pattern in a general population.

PubMed

Tomitaka, Shinichiro; Kawasaki, Yohei; Ide, Kazuki; Akutagawa, Maiko; Yamada, Hiroshi; Furukawa, Toshiaki A; Ono, Yutaka

2016-01-01

Previously, we proposed a model for ordinal scale scoring in which individual thresholds for each item constitute a distribution by each item. This lead us to hypothesize that the boundary curves of each depressive symptom score in the distribution of total depressive symptom scores follow a common mathematical model, which is expressed as the product of the frequency of the total depressive symptom scores and the probability of the cumulative distribution function of each item threshold. To verify this hypothesis, we investigated the boundary curves of the distribution of total depressive symptom scores in a general population. Data collected from 21,040 subjects who had completed the Center for Epidemiologic Studies Depression Scale (CES-D) questionnaire as part of a national Japanese survey were analyzed. The CES-D consists of 20 items (16 negative items and four positive items). The boundary curves of adjacent item scores in the distribution of total depressive symptom scores for the 16 negative items were analyzed using log-normal scales and curve fitting. The boundary curves of adjacent item scores for a given symptom approximated a common linear pattern on a log normal scale. Curve fitting showed that an exponential fit had a markedly higher coefficient of determination than either linear or quadratic fits. With negative affect items, the gap between the total score curve and boundary curve continuously increased with increasing total depressive symptom scores on a log-normal scale, whereas the boundary curves of positive affect items, which are not considered manifest variables of the latent trait, did not exhibit such increases in this gap. The results of the present study support the hypothesis that the boundary curves of each depressive symptom score in the distribution of total depressive symptom scores commonly follow the predicted mathematical model, which was verified to approximate an exponential mathematical pattern.

Boundary curves of individual items in the distribution of total depressive symptom scores approximate an exponential pattern in a general population

PubMed Central

Kawasaki, Yohei; Akutagawa, Maiko; Yamada, Hiroshi; Furukawa, Toshiaki A.; Ono, Yutaka

2016-01-01

Background Previously, we proposed a model for ordinal scale scoring in which individual thresholds for each item constitute a distribution by each item. This lead us to hypothesize that the boundary curves of each depressive symptom score in the distribution of total depressive symptom scores follow a common mathematical model, which is expressed as the product of the frequency of the total depressive symptom scores and the probability of the cumulative distribution function of each item threshold. To verify this hypothesis, we investigated the boundary curves of the distribution of total depressive symptom scores in a general population. Methods Data collected from 21,040 subjects who had completed the Center for Epidemiologic Studies Depression Scale (CES-D) questionnaire as part of a national Japanese survey were analyzed. The CES-D consists of 20 items (16 negative items and four positive items). The boundary curves of adjacent item scores in the distribution of total depressive symptom scores for the 16 negative items were analyzed using log-normal scales and curve fitting. Results The boundary curves of adjacent item scores for a given symptom approximated a common linear pattern on a log normal scale. Curve fitting showed that an exponential fit had a markedly higher coefficient of determination than either linear or quadratic fits. With negative affect items, the gap between the total score curve and boundary curve continuously increased with increasing total depressive symptom scores on a log-normal scale, whereas the boundary curves of positive affect items, which are not considered manifest variables of the latent trait, did not exhibit such increases in this gap. Discussion The results of the present study support the hypothesis that the boundary curves of each depressive symptom score in the distribution of total depressive symptom scores commonly follow the predicted mathematical model, which was verified to approximate an exponential mathematical pattern. PMID:27761346

A new approach to aid the characterisation and identification of metabolites of a model drug; partial isotope enrichment combined with novel formula elucidation software.

PubMed

Hobby, Kirsten; Gallagher, Richard T; Caldwell, Patrick; Wilson, Ian D

2009-01-01

This work describes the identification of 'isotopically enriched' metabolites of 4-cyanoaniline using the unique features of the software package 'Spectral Simplicity'. The software is capable of creating the theoretical mass spectra for partially isotope-enriched compounds, and subsequently performing an elemental composition analysis to give the elemental formula for the 'isotopically enriched' metabolite. A novel mass spectral correlation method, called 'FuzzyFit', was employed. 'FuzzyFit' utilises the expected experimental distribution of errors in both mass accuracy and isotope pattern and enables discrimination between statistically probable and improbable candidate formulae. The software correctly determined the molecular formulae of ten previously described metabolites of 4-cyanoaniline confirming the technique of partial isotope enrichment can produce results analogous to standard methodologies. Six previously unknown species were also identified, based on the presence of the unique 'designer' isotope ratio. Three of the unknowns were tentatively identified as N-acetylglutamine, O-methyl-N acetylglucuronide and a putative fatty acid conjugate. The discovery of a significant number of unknown species of a model drug with a comprehensive history of investigation highlights the potential for enhancement to the analytical process by the use of 'designer' isotope ratio compounds. The 'FuzzyFit' methodology significantly aided the elucidation of candidate formulae, by provision of a vastly simplified candidate formula data set. Copyright (c) 2008 John Wiley & Sons, Ltd.

Applying the LANL Statistical Pattern Recognition Paradigm for Structural Health Monitoring to Data from a Surface-Effect Fast Patrol Boat

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

Hoon Sohn; Charles Farrar; Norman Hunter

2001-01-01

This report summarizes the analysis of fiber-optic strain gauge data obtained from a surface-effect fast patrol boat being studied by the staff at the Norwegian Defense Research Establishment (NDRE) in Norway and the Naval Research Laboratory (NRL) in Washington D.C. Data from two different structural conditions were provided to the staff at Los Alamos National Laboratory. The problem was then approached from a statistical pattern recognition paradigm. This paradigm can be described as a four-part process: (1) operational evaluation, (2) data acquisition & cleansing, (3) feature extraction and data reduction, and (4) statistical model development for feature discrimination. Given thatmore » the first two portions of this paradigm were mostly completed by the NDRE and NRL staff, this study focused on data normalization, feature extraction, and statistical modeling for feature discrimination. The feature extraction process began by looking at relatively simple statistics of the signals and progressed to using the residual errors from auto-regressive (AR) models fit to the measured data as the damage-sensitive features. Data normalization proved to be the most challenging portion of this investigation. A novel approach to data normalization, where the residual errors in the AR model are considered to be an unmeasured input and an auto-regressive model with exogenous inputs (ARX) is then fit to portions of the data exhibiting similar waveforms, was successfully applied to this problem. With this normalization procedure, a clear distinction between the two different structural conditions was obtained. A false-positive study was also run, and the procedure developed herein did not yield any false-positive indications of damage. Finally, the results must be qualified by the fact that this procedure has only been applied to very limited data samples. A more complete analysis of additional data taken under various operational and environmental conditions as well as other structural conditions is necessary before one can definitively state that the procedure is robust enough to be used in practice.« less

The Regular Interaction Pattern among Odorants of the Same Type and Its Application in Odor Intensity Assessment.

PubMed

Yan, Luchun; Liu, Jiemin; Jiang, Shen; Wu, Chuandong; Gao, Kewei

2017-07-13

The olfactory evaluation function (e.g., odor intensity rating) of e-nose is always one of the most challenging issues in researches about odor pollution monitoring. But odor is normally produced by a set of stimuli, and odor interactions among constituents significantly influenced their mixture's odor intensity. This study investigated the odor interaction principle in odor mixtures of aldehydes and esters, respectively. Then, a modified vector model (MVM) was proposed and it successfully demonstrated the similarity of the odor interaction pattern among odorants of the same type. Based on the regular interaction pattern, unlike a determined empirical model only fit for a specific odor mixture in conventional approaches, the MVM distinctly simplified the odor intensity prediction of odor mixtures. Furthermore, the MVM also provided a way of directly converting constituents' chemical concentrations to their mixture's odor intensity. By combining the MVM with usual data-processing algorithm of e-nose, a new e-nose system was established for an odor intensity rating. Compared with instrumental analysis and human assessor, it exhibited accuracy well in both quantitative analysis (Pearson correlation coefficient was 0.999 for individual aldehydes ( n = 12), 0.996 for their binary mixtures ( n = 36) and 0.990 for their ternary mixtures ( n = 60)) and odor intensity assessment (Pearson correlation coefficient was 0.980 for individual aldehydes ( n = 15), 0.973 for their binary mixtures ( n = 24), and 0.888 for their ternary mixtures ( n = 25)). Thus, the observed regular interaction pattern is considered an important foundation for accelerating extensive application of olfactory evaluation in odor pollution monitoring.

Spatial gender-age-period-cohort analysis of pancreatic cancer mortality in Spain (1990–2013)

PubMed Central

Etxeberria, Jaione; Goicoa, Tomás; López-Abente, Gonzalo; Riebler, Andrea

2017-01-01

Recently, the interest in studying pancreatic cancer mortality has increased due to its high lethality. In this work a detailed analysis of pancreatic cancer mortality in Spanish provinces was performed using recent data. A set of multivariate spatial gender-age-period-cohort models was considered to look for potential candidates to analyze pancreatic cancer mortality rates. The selected model combines features of APC (age-period-cohort) models with disease mapping approaches. To ensure model identifiability sum-to-zero constraints were applied. A fully Bayesian approach based on integrated nested Laplace approximations (INLA) was considered for model fitting and inference. Sensitivity analyses were also conducted. In general, estimated average rates by age, cohort, and period are higher in males than in females. The higher differences according to age between males and females correspond to the age groups [65, 70), [70, 75), and [75, 80). Regarding the cohort, the greatest difference between men and women is observed for those born between the forties and the sixties. From there on, the younger the birth cohort is, the smaller the difference becomes. Some cohort differences are also identified by regions and age-groups. The spatial pattern indicates a North-South gradient of pancreatic cancer mortality in Spain, the provinces in the North being the ones with the highest effects on mortality during the studied period. Finally, the space-time evolution shows that the space pattern has changed little over time. PMID:28199327

Seasonality of Influenza and Respiratory Syncytial Viruses and the Effect of Climate Factors in Subtropical-Tropical Asia Using Influenza-Like Illness Surveillance Data, 2010 -2012.

PubMed

Kamigaki, Taro; Chaw, Liling; Tan, Alvin G; Tamaki, Raita; Alday, Portia P; Javier, Jenaline B; Olveda, Remigio M; Oshitani, Hitoshi; Tallo, Veronica L

2016-01-01

The seasonality of influenza and respiratory syncytial virus (RSV) is well known, and many analyses have been conducted in temperate countries; however, this is still not well understood in tropical countries. Previous studies suggest that climate factors are involved in the seasonality of these viruses. However, the extent of the effect of each climate variable is yet to be defined. We investigated the pattern of seasonality and the effect of climate variables on influenza and RSV at three sites of different latitudes: the Eastern Visayas region and Baguio City in the Philippines, and Okinawa Prefecture in Japan. Wavelet analysis and the dynamic linear regression model were applied. Climate variables used in the analysis included mean temperature, relative and specific humidity, precipitation, and number of rainy days. The Akaike Information Criterion estimated in each model was used to test the improvement of fit in comparison with the baseline model. At all three study sites, annual seasonal peaks were observed in influenza A and RSV; peaks were unclear for influenza B. Ranges of climate variables at the two Philippine sites were narrower and mean variables were significantly different among the three sites. Whereas all climate variables except the number of rainy days improved model fit to the local trend model, their contributions were modest. Mean temperature and specific humidity were positively associated with influenza and RSV at the Philippine sites and negatively associated with influenza A in Okinawa. Precipitation also improved model fit for influenza and RSV at both Philippine sites, except for the influenza A model in the Eastern Visayas. Annual seasonal peaks were observed for influenza A and RSV but were less clear for influenza B at all three study sites. Including additional data from subsequent more years would help to ascertain these findings. Annual amplitude and variation in climate variables are more important than their absolute values for determining their effect on the seasonality of influenza and RSV.

Model fit evaluation in multilevel structural equation models

PubMed Central

Ryu, Ehri

2014-01-01

Assessing goodness of model fit is one of the key questions in structural equation modeling (SEM). Goodness of fit is the extent to which the hypothesized model reproduces the multivariate structure underlying the set of variables. During the earlier development of multilevel structural equation models, the “standard” approach was to evaluate the goodness of fit for the entire model across all levels simultaneously. The model fit statistics produced by the standard approach have a potential problem in detecting lack of fit in the higher-level model for which the effective sample size is much smaller. Also when the standard approach results in poor model fit, it is not clear at which level the model does not fit well. This article reviews two alternative approaches that have been proposed to overcome the limitations of the standard approach. One is a two-step procedure which first produces estimates of saturated covariance matrices at each level and then performs single-level analysis at each level with the estimated covariance matrices as input (Yuan and Bentler, 2007). The other level-specific approach utilizes partially saturated models to obtain test statistics and fit indices for each level separately (Ryu and West, 2009). Simulation studies (e.g., Yuan and Bentler, 2007; Ryu and West, 2009) have consistently shown that both alternative approaches performed well in detecting lack of fit at any level, whereas the standard approach failed to detect lack of fit at the higher level. It is recommended that the alternative approaches are used to assess the model fit in multilevel structural equation model. Advantages and disadvantages of the two alternative approaches are discussed. The alternative approaches are demonstrated in an empirical example. PMID:24550882

Testability of evolutionary game dynamics based on experimental economics data

NASA Astrophysics Data System (ADS)

Wang, Yijia; Chen, Xiaojie; Wang, Zhijian

In order to better understand the dynamic processes of a real game system, we need an appropriate dynamics model, so to evaluate the validity of a model is not a trivial task. Here, we demonstrate an approach, considering the dynamical macroscope patterns of angular momentum and speed as the measurement variables, to evaluate the validity of various dynamics models. Using the data in real time Rock-Paper-Scissors (RPS) games experiments, we obtain the experimental dynamic patterns, and then derive the related theoretical dynamic patterns from a series of typical dynamics models respectively. By testing the goodness-of-fit between the experimental and theoretical patterns, the validity of the models can be evaluated. One of the results in our study case is that, among all the nonparametric models tested, the best-known Replicator dynamics model performs almost worst, while the Projection dynamics model performs best. Besides providing new empirical macroscope patterns of social dynamics, we demonstrate that the approach can be an effective and rigorous tool to test game dynamics models. Fundamental Research Funds for the Central Universities (SSEYI2014Z) and the National Natural Science Foundation of China (Grants No. 61503062).

Interference pattern period measurement at picometer level

NASA Astrophysics Data System (ADS)

Xiang, Xiansong; Wei, Chunlong; Jia, Wei; Zhou, Changhe; Li, Minkang; Lu, Yancong

2016-10-01

To produce large scale gratings by Scanning Beam Interference Lithography (SBIL), a light spot containing grating pattern is generated by two beams interfering, and a scanning stage is used to drive the substrate moving under the light spot. In order to locate the stage at the proper exposure positions, the period of the Interference pattern must be measured accurately. We developed a set of process to obtain the period value of two interfering beams at picometer level. The process includes data acquisition and data analysis. The data is received from a photodiode and a laser interferometer with sub-nanometer resolution. Data analysis differs from conventional analyzing methods like counting wave peaks or using Fourier transform to get the signal period, after a preprocess of filtering and envelope removing, the mean square error is calculated between the received signal and ideal sinusoid waves to find the best-fit frequency, thus an accuracy period value is acquired, this method has a low sensitivity to amplitude noise and a high resolution of frequency. With 405nm laser beams interfering, a pattern period value around 562nm is acquired by employing this process, fitting diagram of the result shows the accuracy of the period value reaches picometer level, which is much higher than the results of conventional methods.

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

PubMed

Tsubakita, Takashi; Shimazaki, Kazuyo

2016-01-01

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

A User's Version View of a Robustified, Bayesian Weighted Least-Squares Recursive Algorithm for Interpolating AVHRR-NDVI Data: Applications to an Animated Visualization of the Phenology of a Semi-Arid Study Area

NASA Astrophysics Data System (ADS)

Hermance, J. F.; Jacob, R. W.; Bradley, B. A.; Mustard, J. F.

2005-12-01

In studying vegetation patterns remotely, the objective is to draw inferences on the development of specific or general land surface phenology (LSP) as a function of space and time by determining the behavior of a parameter (in our case NDVI), when the parameter estimate may be biased by noise, data dropouts and obfuscations from atmospheric and other effects. We describe the underpinning concepts of a procedure for a robust interpolation of NDVI data that does not have the limitations of other mathematical approaches which require orthonormal basis functions (e.g. Fourier analysis). In this approach, data need not be uniformly sampled in time, nor do we expect noise to be Gaussian-distributed. Our approach is intuitive and straightforward, and is applied here to the refined modeling of LSP using 7 years of weekly and biweekly AVHRR NDVI data for a 150 x 150 km study area in central Nevada. This site is a microcosm of a broad range of vegetation classes, from irrigated agriculture with annual NDVIvalues of up to 0.7 to playas and alkali salt flats with annual NDVI values of only 0.07. Our procedure involves a form of parameter estimation employing Bayesian statistics. In utilitarian terms, the latter procedure is a method of statistical analysis (in our case, robustified, weighted least-squares recursive curve-fitting) that incorporates a variety of prior knowledge when forming current estimates of a particular process or parameter. In addition to the standard Bayesian approach, we account for outliers due to data dropouts or obfuscations because of clouds and snow cover. An initial "starting model" for the average annual cycle and long term (7 year) trend is determined by jointly fitting a common set of complex annual harmonics and a low order polynomial to an entire multi-year time series in one step. This is not a formal Fourier series in the conventional sense, but rather a set of 4 cosine and 4 sine coefficients with fundamental periods of 12, 6, 3 and 1.5 months. Instabilities during large time gaps in the data are suppressed by introducing an expectation of minimum roughness on the fitted time series. Our next significant computational step involves a constrained least squares fit to the observed NDVI data. Residuals between the observed NDVI value and the predicted starting model are computed, and the inverse of these residuals provide the weights for a weighted least squares analysis whereby a set of annual eighth-order splines are fit to the 7 years of NDVI data. Although a series of independent 8-th order annual functionals over a period of 7 years is intrinsically unstable when there are significant data gaps, the splined versions for this specific application are quite stable due to explicit continuity conditions on the values and derivatives of the functionals across contiguous years, as well as a priori constraints on the predicted values vis-a-vis the assumed initial model. Our procedure allows us to robustly interpolate original unequally-spaced NDVI data with a new time series having the most-appropriate, user-defined time base. We apply this approach to the temporal behavior of vegetation in our 150 x 150 km study area. Such a small area, being so rich in vegetation diversity, is particularly useful to view in map form and by animated annual and multi-year time sequences, since the interrelation between phenology, topography and specific usage patterns becomes clear.

Disentangling early language development: modeling lexical and grammatical acquisition using an extension of case-study methodology.

PubMed

Robinson, B F; Mervis, C B

1998-03-01

The early lexical and grammatical development of 1 male child is examined with growth curves and dynamic-systems modeling procedures. Lexical-development described a pattern of logistic growth (R2 = .98). Lexical and plural development shared the following characteristics: Plural growth began only after a threshold was reached in vocabulary size; lexical growth slowed as plural growth increased. As plural use reached full mastery, lexical growth began again to increase. It was hypothesized that a precursor model (P. van Geert, 1991) would fit these data. Subsequent testing indicated that the precursor model, modified to incorporate brief yet intensive plural growth, provided a suitable fit. The value of the modified precursor model for the explication of processes implicated in language development is discussed.

Boltzmann Energy-based Image Analysis Demonstrates that Extracellular Domain Size Differences Explain Protein Segregation at Immune Synapses

PubMed Central

Burroughs, Nigel J.; Köhler, Karsten; Miloserdov, Vladimir; Dustin, Michael L.; van der Merwe, P. Anton; Davis, Daniel M.

2011-01-01

Immune synapses formed by T and NK cells both show segregation of the integrin ICAM1 from other proteins such as CD2 (T cell) or KIR (NK cell). However, the mechanism by which these proteins segregate remains unclear; one key hypothesis is a redistribution based on protein size. Simulations of this mechanism qualitatively reproduce observed segregation patterns, but only in certain parameter regimes. Verifying that these parameter constraints in fact hold has not been possible to date, this requiring a quantitative coupling of theory to experimental data. Here, we address this challenge, developing a new methodology for analysing and quantifying image data and its integration with biophysical models. Specifically we fit a binding kinetics model to 2 colour fluorescence data for cytoskeleton independent synapses (2 and 3D) and test whether the observed inverse correlation between fluorophores conforms to size dependent exclusion, and further, whether patterned states are predicted when model parameters are estimated on individual synapses. All synapses analysed satisfy these conditions demonstrating that the mechanisms of protein redistribution have identifiable signatures in their spatial patterns. We conclude that energy processes implicit in protein size based segregation can drive the patternation observed in individual synapses, at least for the specific examples tested, such that no additional processes need to be invoked. This implies that biophysical processes within the membrane interface have a crucial impact on cell∶cell communication and cell signalling, governing protein interactions and protein aggregation. PMID:21829338

Contingent capture and inhibition of return: a comparison of mechanisms.

PubMed

Prinzmetal, William; Taylor, Jordan A; Myers, Loretta Barry; Nguyen-Espino, Jacqueline

2011-09-01

We investigated the cause(s) of two effects associated with involuntary attention in the spatial cueing task: contingent capture and inhibition of return (IOR). Previously, we found that there were two mechanisms of involuntary attention in this task: (1) a (serial) search mechanism that predicts a larger cueing effect in reaction time with more display locations and (2) a decision (threshold) mechanism that predicts a smaller cueing effect with more display locations (Prinzmetal et al. 2010). In the present study, contingent capture and IOR had completely different patterns of results when we manipulated the number of display locations and the presence of distractors. Contingent capture was best described by a search model, whereas the inhibition of return was best described by a decision model. Furthermore, we fit a linear ballistic accumulator model to the results and IOR was accounted for by a change of threshold, whereas the results from contingent capture experiments could not be fit with a change of threshold and were better fit by a search model.

Modeling short duration extreme precipitation patterns using copula and generalized maximum pseudo-likelihood estimation with censoring

NASA Astrophysics Data System (ADS)

Bargaoui, Zoubeida Kebaili; Bardossy, Andràs

2015-10-01

The paper aims to develop researches on the spatial variability of heavy rainfall events estimation using spatial copula analysis. To demonstrate the methodology, short time resolution rainfall time series from Stuttgart region are analyzed. They are constituted by rainfall observations on continuous 30 min time scale recorded over a network composed by 17 raingages for the period July 1989-July 2004. The analysis is performed aggregating the observations from 30 min up to 24 h. Two parametric bivariate extreme copula models, the Husler-Reiss model and the Gumbel model are investigated. Both involve a single parameter to be estimated. Thus, model fitting is operated for every pair of stations for a giving time resolution. A rainfall threshold value representing a fixed rainfall quantile is adopted for model inference. Generalized maximum pseudo-likelihood estimation is adopted with censoring by analogy with methods of univariate estimation combining historical and paleoflood information with systematic data. Only pairs of observations greater than the threshold are assumed as systematic data. Using the estimated copula parameter, a synthetic copula field is randomly generated and helps evaluating model adequacy which is achieved using Kolmogorov Smirnov distance test. In order to assess dependence or independence in the upper tail, the extremal coefficient which characterises the tail of the joint bivariate distribution is adopted. Hence, the extremal coefficient is reported as a function of the interdistance between stations. If it is less than 1.7, stations are interpreted as dependent in the extremes. The analysis of the fitted extremal coefficients with respect to stations inter distance highlights two regimes with different dependence structures: a short spatial extent regime linked to short duration intervals (from 30 min to 6 h) with an extent of about 8 km and a large spatial extent regime related to longer rainfall intervals (from 12 h to 24 h) with an extent of 34 to 38 km.

Precision of Fit of Titanium and Cast Implant Frameworks Using a New Matching Formula

PubMed Central

Sierraalta, Marianella; Vivas, Jose L.; Razzoog, Michael E.; Wang, Rui-Feng

2012-01-01

Statement of the Problem. Fit of prosthodontic frameworks is linked to the lifetime survival of dental implants and maintenance of surrounding bone. Purpose. The purpose of this study was to evaluate and compare the precision of fit of milled one-piece Titanium fixed complete denture frameworks to that of conventional cast frameworks. Material and Methods. Fifteen casts fabricated from a single edentulous CAD/CAM surgical guide were separated in two groups and resin patterns simulating the framework for a fixed complete denture developed. Five casts were sent to dental laboratories to invest, cast in a Palladium-Gold alloy and fit the framework. Ten casts had the resin pattern scanned for fabrication of milled bars in Titanium. Using measuring software, positions of implant replicas in the definitive model were recorded. The three dimensional spatial orientation of each implant replica was matched to the implant replica. Results. Results demonstrated the mean vertical gap of the Cast framework was 0.021 (+0.004) mm and 0.012 (0.002) mm determined by fixed and unfixed best-fit matching coordinate system. For Titanium frameworks they were 0.0037 (+0.0028) mm and 0.0024 (+0.0005) mm, respectively. Conclusions. Milled one-piece Titanium fixed complete denture frameworks provided a more accurate precision of fit then traditional cast frameworks. PMID:22550486

A Two-Factor Model Better Explains Heterogeneity in Negative Symptoms: Evidence from the Positive and Negative Syndrome Scale.

PubMed

Jang, Seon-Kyeong; Choi, Hye-Im; Park, Soohyun; Jaekal, Eunju; Lee, Ga-Young; Cho, Young Il; Choi, Kee-Hong

2016-01-01

Acknowledging separable factors underlying negative symptoms may lead to better understanding and treatment of negative symptoms in individuals with schizophrenia. The current study aimed to test whether the negative symptoms factor (NSF) of the Positive and Negative Syndrome Scale (PANSS) would be better represented by expressive and experiential deficit factors, rather than by a single factor model, using confirmatory factor analysis (CFA). Two hundred and twenty individuals with schizophrenia spectrum disorders completed the PANSS; subsamples additionally completed the Brief Negative Symptom Scale (BNSS) and the Motivation and Pleasure Scale-Self-Report (MAP-SR). CFA results indicated that the two-factor model fit the data better than the one-factor model; however, latent variables were closely correlated. The two-factor model's fit was significantly improved by accounting for correlated residuals between N2 (emotional withdrawal) and N6 (lack of spontaneity and flow of conversation), and between N4 (passive social withdrawal) and G16 (active social avoidance), possibly reflecting common method variance. The two NSF factors exhibited differential patterns of correlation with subdomains of the BNSS and MAP-SR. These results suggest that the PANSS NSF would be better represented by a two-factor model than by a single-factor one, and support the two-factor model's adequate criterion-related validity. Common method variance among several items may be a potential source of measurement error under a two-factor model of the PANSS NSF.

Fitness in animals correlates with proximity to discontinuities in body mass distributions.

USGS Publications Warehouse

Angeler, David G.; Allen, Craig R.; Vila-Gispert, Anna; Almeida, David

2014-01-01

Discontinuous structure in landscapes may cause discontinuous, aggregated species body-mass patterns, reflecting the scales of structure available to animal communities within a landscape. Empirical analyses have shown that the location of species within body mass aggregations, which reflect this scale-specific organization, is non-random with regard to several ecological phenomena, including species extinctions. The propensity of declining species to have body masses proximate to discontinuities suggests that transition zones between scaling regimes ultimately decreases the ecological fitness for some species. We test this proposition using vulnerable and unthreatened fish species in Mediterranean streams with differing levels of human impact. We show that the proximity to discontinuities in body mass aggregations (“distance-to-edge”) of more vs. less fit individuals within vulnerable and unthreatened populations differs. Specifically, regression analysis between the scaled mass index, a proxy of animal fitness, and distance-to-edge reveals negative and positive relationships for vulnerable and unthreatened species, respectively. That is, fitness is higher close to discontinuities in vulnerable populations and toward the center of body mass aggregation groups in unthreatened populations. Our results demonstrate the suitability of the discontinuity framework for scrutinizing non-random patterns of environmental impact in populations. Further exploration of the usefulness of this method across other ecosystems and organism groups is warranted.

Child-mother and child-father attachment security: links to internalizing adjustment among children with learning disabilities.

PubMed

Al-Yagon, Michal

2014-02-01

The study examined the unique role of children's attachment with the father and with the mother, in explaining differences in internalizing features (i.e., loneliness, sense of coherence, hope and effort, and internalizing behavior syndrome) among 107 children with learning disabilities (LD) versus 98 children with typical development ages 8-12. Preliminary analyses yielded significant group differences on most measures. SEM analysis indicated high fit between the theoretical model and empirical findings, and different patterns of relations among the model's components for the two populations. As hypothesized, child-father and child-mother attachment contributed differently to children's internalizing features for the two subgroups. Discussion focused on understanding unique and complementary roles of attachment relations with fathers versus mothers among children with and without LD.

Predictive model for convective flows induced by surface reactivity contrast

NASA Astrophysics Data System (ADS)

Davidson, Scott M.; Lammertink, Rob G. H.; Mani, Ali

2018-05-01

Concentration gradients in a fluid adjacent to a reactive surface due to contrast in surface reactivity generate convective flows. These flows result from contributions by electro- and diffusio-osmotic phenomena. In this study, we have analyzed reactive patterns that release and consume protons, analogous to bimetallic catalytic conversion of peroxide. Similar systems have typically been studied using either scaling analysis to predict trends or costly numerical simulation. Here, we present a simple analytical model, bridging the gap in quantitative understanding between scaling relations and simulations, to predict the induced potentials and consequent velocities in such systems without the use of any fitting parameters. Our model is tested against direct numerical solutions to the coupled Poisson, Nernst-Planck, and Stokes equations. Predicted slip velocities from the model and simulations agree to within a factor of ≈2 over a multiple order-of-magnitude change in the input parameters. Our analysis can be used to predict enhancement of mass transport and the resulting impact on overall catalytic conversion, and is also applicable to predicting the speed of catalytic nanomotors.

Robustness of fit indices to outliers and leverage observations in structural equation modeling.

PubMed

Yuan, Ke-Hai; Zhong, Xiaoling

2013-06-01

Normal-distribution-based maximum likelihood (NML) is the most widely used method in structural equation modeling (SEM), although practical data tend to be nonnormally distributed. The effect of nonnormally distributed data or data contamination on the normal-distribution-based likelihood ratio (LR) statistic is well understood due to many analytical and empirical studies. In SEM, fit indices are used as widely as the LR statistic. In addition to NML, robust procedures have been developed for more efficient and less biased parameter estimates with practical data. This article studies the effect of outliers and leverage observations on fit indices following NML and two robust methods. Analysis and empirical results indicate that good leverage observations following NML and one of the robust methods lead most fit indices to give more support to the substantive model. While outliers tend to make a good model superficially bad according to many fit indices following NML, they have little effect on those following the two robust procedures. Implications of the results to data analysis are discussed, and recommendations are provided regarding the use of estimation methods and interpretation of fit indices. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

Fitness Profiles and Activity Patterns of Entering College Students.

ERIC Educational Resources Information Center

Pierce, Edgar F.; And Others

1992-01-01

Entering college students were evaluated for performance on maximal oxygen consumption, body composition, muscle endurance, muscle strength, and joint flexibility tests to determine the relationship of physical activity patterns to fitness levels. Results supported previous research indicating reduced fitness levels in young adults. (SM)

Linking big models to big data: efficient ecosystem model calibration through Bayesian model emulation

NASA Astrophysics Data System (ADS)

Fer, I.; Kelly, R.; Andrews, T.; Dietze, M.; Richardson, A. D.

2016-12-01

Our ability to forecast ecosystems is limited by how well we parameterize ecosystem models. Direct measurements for all model parameters are not always possible and inverse estimation of these parameters through Bayesian methods is computationally costly. A solution to computational challenges of Bayesian calibration is to approximate the posterior probability surface using a Gaussian Process that emulates the complex process-based model. Here we report the integration of this method within an ecoinformatics toolbox, Predictive Ecosystem Analyzer (PEcAn), and its application with two ecosystem models: SIPNET and ED2.1. SIPNET is a simple model, allowing application of MCMC methods both to the model itself and to its emulator. We used both approaches to assimilate flux (CO2 and latent heat), soil respiration, and soil carbon data from Bartlett Experimental Forest. This comparison showed that emulator is reliable in terms of convergence to the posterior distribution. A 10000-iteration MCMC analysis with SIPNET itself required more than two orders of magnitude greater computation time than an MCMC run of same length with its emulator. This difference would be greater for a more computationally demanding model. Validation of the emulator-calibrated SIPNET against both the assimilated data and out-of-sample data showed improved fit and reduced uncertainty around model predictions. We next applied the validated emulator method to the ED2, whose complexity precludes standard Bayesian data assimilation. We used the ED2 emulator to assimilate demographic data from a network of inventory plots. For validation of the calibrated ED2, we compared the model to results from Empirical Succession Mapping (ESM), a novel synthesis of successional patterns in Forest Inventory and Analysis data. Our results revealed that while the pre-assimilation ED2 formulation cannot capture the emergent demographic patterns from ESM analysis, constrained model parameters controlling demographic processes increased their agreement considerably.

Meta-Analytic Methods of Pooling Correlation Matrices for Structural Equation Modeling under Different Patterns of Missing Data

ERIC Educational Resources Information Center

Furlow, Carolyn F.; Beretvas, S. Natasha

2005-01-01

Three methods of synthesizing correlations for meta-analytic structural equation modeling (SEM) under different degrees and mechanisms of missingness were compared for the estimation of correlation and SEM parameters and goodness-of-fit indices by using Monte Carlo simulation techniques. A revised generalized least squares (GLS) method for…

The Black-White-Other Test Score Gap: Academic Achievement among Mixed Race Adolescents. Institute for Policy Research Working Paper.

ERIC Educational Resources Information Center

Herman, Melissa R.

This paper describes the achievement patterns of a sample of 1,492 multiracial high school students and examines how their achievement fits into existing theoretical models that explain monoracial differences in achievement. These theoretical models include status attainment, parenting style, oppositional culture, and educational attitudes. The…

Cross-national health comparisons using the Rasch model: findings from the 2012 US Health and Retirement Study and the 2012 Mexican Health and Aging Study.

PubMed

Hong, Ickpyo; Reistetter, Timothy A; Díaz-Venegas, Carlos; Michaels-Obregon, Alejandra; Wong, Rebeca

2018-05-10

Cross-national comparisons of patterns of population aging have emerged as comparable national micro-data have become available. This study creates a metric using Rasch analysis and determines the health of American and Mexican older adult populations. Secondary data analysis using representative samples aged 50 and older from 2012 U.S. Health and Retirement Study (n = 20,554); 2012 Mexican Health and Aging Study (n = 14,448). We developed a function measurement scale using Rasch analysis of 22 daily tasks and physical function questions. We tested psychometrics of the scale including factor analysis, fit statistics, internal consistency, and item difficulty. We investigated differences in function using multiple linear regression controlling for demographics. Lastly, we conducted subgroup analyses for chronic conditions. The created common metric demonstrated a unidimensional structure with good item fit, an acceptable precision (person reliability = 0.78), and an item difficulty hierarchy. The American adults appeared less functional than adults in Mexico (β = - 0.26, p < 0.0001) and across two chronic conditions (arthritis, β = - 0.36; lung problems, β = - 0.62; all p < 0.05). However, American adults with stroke were more functional than Mexican adults (β = 0.46, p = 0.047). The Rasch model indicates that Mexican adults were more functional than Americans at the population level and across two chronic conditions (arthritis and lung problems). Future studies would need to elucidate other factors affecting the function differences between the two countries.

Rejecting probability summation for radial frequency patterns, not so Quick!

PubMed

Baldwin, Alex S; Schmidtmann, Gunnar; Kingdom, Frederick A A; Hess, Robert F

2016-05-01

Radial frequency (RF) patterns are used to assess how the visual system processes shape. They are thought to be detected globally. This is supported by studies that have found summation for RF patterns to be greater than what is possible if the parts were being independently detected and performance only then improved with an increasing number of cycles by probability summation between them. However, the model of probability summation employed in these previous studies was based on High Threshold Theory (HTT), rather than Signal Detection Theory (SDT). We conducted rating scale experiments to investigate the receiver operating characteristics. We find these are of the curved form predicted by SDT, rather than the straight lines predicted by HTT. This means that to test probability summation we must use a model based on SDT. We conducted a set of summation experiments finding that thresholds decrease as the number of modulated cycles increases at approximately the same rate as previously found. As this could be consistent with either additive or probability summation, we performed maximum-likelihood fitting of a set of summation models (Matlab code provided in our Supplementary material) and assessed the fits using cross validation. We find we are not able to distinguish whether the responses to the parts of an RF pattern are combined by additive or probability summation, because the predictions are too similar. We present similar results for summation between separate RF patterns, suggesting that the summation process there may be the same as that within a single RF. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Dynamics of Power laws: Fitness and Aging in Preferential Attachment Trees

NASA Astrophysics Data System (ADS)

Garavaglia, Alessandro; van der Hofstad, Remco; Woeginger, Gerhard

2017-09-01

Continuous-time branching processes describe the evolution of a population whose individuals generate a random number of children according to a birth process. Such branching processes can be used to understand preferential attachment models in which the birth rates are linear functions. We are motivated by citation networks, where power-law citation counts are observed as well as aging in the citation patterns. To model this, we introduce fitness and age-dependence in these birth processes. The multiplicative fitness moderates the rate at which children are born, while the aging is integrable, so that individuals receives a finite number of children in their lifetime. We show the existence of a limiting degree distribution for such processes. In the preferential attachment case, where fitness and aging are absent, this limiting degree distribution is known to have power-law tails. We show that the limiting degree distribution has exponential tails for bounded fitnesses in the presence of integrable aging, while the power-law tail is restored when integrable aging is combined with fitness with unbounded support with at most exponential tails. In the absence of integrable aging, such processes are explosive.

Forecasting mortality of road traffic injuries in China using seasonal autoregressive integrated moving average model.

PubMed

Zhang, Xujun; Pang, Yuanyuan; Cui, Mengjing; Stallones, Lorann; Xiang, Huiyun

2015-02-01

Road traffic injuries have become a major public health problem in China. This study aimed to develop statistical models for predicting road traffic deaths and to analyze seasonality of deaths in China. A seasonal autoregressive integrated moving average (SARIMA) model was used to fit the data from 2000 to 2011. Akaike Information Criterion, Bayesian Information Criterion, and mean absolute percentage error were used to evaluate the constructed models. Autocorrelation function and partial autocorrelation function of residuals and Ljung-Box test were used to compare the goodness-of-fit between the different models. The SARIMA model was used to forecast monthly road traffic deaths in 2012. The seasonal pattern of road traffic mortality data was statistically significant in China. SARIMA (1, 1, 1) (0, 1, 1)12 model was the best fitting model among various candidate models; the Akaike Information Criterion, Bayesian Information Criterion, and mean absolute percentage error were -483.679, -475.053, and 4.937, respectively. Goodness-of-fit testing showed nonautocorrelations in the residuals of the model (Ljung-Box test, Q = 4.86, P = .993). The fitted deaths using the SARIMA (1, 1, 1) (0, 1, 1)12 model for years 2000 to 2011 closely followed the observed number of road traffic deaths for the same years. The predicted and observed deaths were also very close for 2012. This study suggests that accurate forecasting of road traffic death incidence is possible using SARIMA model. The SARIMA model applied to historical road traffic deaths data could provide important evidence of burden of road traffic injuries in China. Copyright © 2015 Elsevier Inc. All rights reserved.

Analysis and fit of stellar spectra using a mega-database of CMFGEN models

NASA Astrophysics Data System (ADS)

Fierro-Santillán, Celia; Zsargó, Janos; Klapp, Jaime; Díaz-Azuara, Santiago Alfredo; Arrieta, Anabel; Arias, Lorena

2017-11-01

We present a tool for analysis and fit of stellar spectra using a mega database of 15,000 atmosphere models for OB stars. We have developed software tools, which allow us to find the model that best fits to an observed spectrum, comparing equivalent widths and line ratios in the observed spectrum with all models of the database. We use the Hα, Hβ, Hγ, and Hδ lines as criterion of stellar gravity and ratios of He II λ4541/He I λ4471, He II λ4200/(He I+He II λ4026), He II λ4541/He I λ4387, and He II λ4200/He I λ4144 as criterion of T eff.

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

Lee, Jaesun; Cho, Younho; Park, Jun-Pil

Guided wave was widely studied for plate and pipe due to the great application area. Guided wave has advantage on long distance inspection for an inaccessible area and apart from transducer. Quite often shrink fit structures were found in nuclear power facilities. In this paper, two pipes were designed with perfect shrink fit condition for Stainless Steel 316. The displacement distribution was calculated with boundary condition. The interface wave propagation pattern was analyzed by the numerical modeling. The experimental results show a possibility of weld delamination and defect detection.

Protein Dynamics from NMR: The Slowly Relaxing Local Structure Analysis Compared with Model-Free Analysis

PubMed Central

Meirovitch, Eva; Shapiro, Yury E.; Polimeno, Antonino; Freed, Jack H.

2009-01-01

15N-1H spin relaxation is a powerful method for deriving information on protein dynamics. The traditional method of data analysis is model-free (MF), where the global and local N-H motions are independent and the local geometry is simplified. The common MF analysis consists of fitting single-field data. The results are typically field-dependent, and multi-field data cannot be fit with standard fitting schemes. Cases where known functional dynamics has not been detected by MF were identified by us and others. Recently we applied to spin relaxation in proteins the Slowly Relaxing Local Structure (SRLS) approach which accounts rigorously for mode-mixing and general features of local geometry. SRLS was shown to yield MF in appropriate asymptotic limits. We found that the experimental spectral density corresponds quite well to the SRLS spectral density. The MF formulae are often used outside of their validity ranges, allowing small data sets to be force-fitted with good statistics but inaccurate best-fit parameters. This paper focuses on the mechanism of force-fitting and its implications. It is shown that MF force-fits the experimental data because mode-mixing, the rhombic symmetry of the local ordering and general features of local geometry are not accounted for. Combined multi-field multi-temperature data analyzed by MF may lead to the detection of incorrect phenomena, while conformational entropy derived from MF order parameters may be highly inaccurate. On the other hand, fitting to more appropriate models can yield consistent physically insightful information. This requires that the complexity of the theoretical spectral densities matches the integrity of the experimental data. As shown herein, the SRLS densities comply with this requirement. PMID:16821820

Bivariate at-site frequency analysis of simulated flood peak-volume data using copulas

NASA Astrophysics Data System (ADS)

Gaál, Ladislav; Viglione, Alberto; Szolgay, Ján.; Blöschl, Günter; Bacigál, Tomáå.¡

2010-05-01

In frequency analysis of joint hydro-climatological extremes (flood peaks and volumes, low flows and durations, etc.), usually, bivariate distribution functions are fitted to the observed data in order to estimate the probability of their occurrence. Bivariate models, however, have a number of limitations; therefore, in the recent past, dependence models based on copulas have gained increased attention to represent the joint probabilities of hydrological characteristics. Regardless of whether standard or copula based bivariate frequency analysis is carried out, one is generally interested in the extremes corresponding to low probabilities of the fitted joint cumulative distribution functions (CDFs). However, usually there is not enough flood data in the right tail of the empirical CDFs to derive reliable statistical inferences on the behaviour of the extremes. Therefore, different techniques are used to extend the amount of information for the statistical inference, i.e., temporal extension methods that allow for making use of historical data or spatial extension methods such as regional approaches. In this study, a different approach was adopted which uses simulated flood data by rainfall-runoff modelling, to increase the amount of data in the right tail of the CDFs. In order to generate artificial runoff data (i.e. to simulate flood records of lengths of approximately 106 years), a two-step procedure was used. (i) First, the stochastic rainfall generator proposed by Sivapalan et al. (2005) was modified for our purpose. This model is based on the assumption of discrete rainfall events whose arrival times, durations, mean rainfall intensity and the within-storm intensity patterns are all random, and can be described by specified distributions. The mean storm rainfall intensity is disaggregated further to hourly intensity patterns. (ii) Secondly, the simulated rainfall data entered a semi-distributed conceptual rainfall-runoff model that consisted of a snow routine, a soil moisture routine and a flow routing routine (Parajka et al., 2007). The applicability of the proposed method was demonstrated on selected sites in Slovakia and Austria. The pairs of simulated flood volumes and flood peaks were analysed in terms of their dependence structure and different families of copulas (Archimedean, extreme value, Gumbel-Hougaard, etc.) were fitted to the observed and simulated data. The question to what extent measured data can be used to find the right copula was discussed. The study is supported by the Austrian Academy of Sciences and the Austrian-Slovak Co-operation in Science and Education "Aktion". Parajka, J., Merz, R., Blöschl, G., 2007: Uncertainty and multiple objective calibration in regional water balance modeling - Case study in 320 Austrian catchments. Hydrological Processes, 21, 435-446. Sivapalan, M., Blöschl, G., Merz, R., Gutknecht, D., 2005: Linking flood frequency to long-term water balance: incorporating effects of seasonality. Water Resources Research, 41, W06012, doi:10.1029/2004WR003439.

Self-Control Constructs Related to Measures of Dietary Intake and Physical Activity in Adolescents

PubMed Central

Wills, Thomas A.; Isasi, Carmen R.; Mendoza, Don; Ainette, Michael G.

2007-01-01

Purpose To test self-regulation concepts in relation to dietary intake and physical activity patterns in adolescence, which we predicted to be influenced by components of a self-control model. Methods A survey was conducted with a multiethnic sample of 9th grade public school students in a metropolitan area (N = 539). Confirmatory analysis tested the measurement structure of self-control. Structural equation modeling tested the association of self-control constructs with measures of fruit and vegetable intake, saturated-fat intake, physical activity, and sedentary behavior. Results Confirmatory analysis of 14 indicators of self-control showed best fit for a two-factor structure, with latent constructs of good self-control (planfulness) and poor self-control (impulsiveness). Good self-control was related to more fruit and vegetable intake, more participation in sports, and less sedentary behavior. Poor self-control was related to more saturated-fat intake and less vigorous exercise. These effects were independent of gender, ethnicity, and parental education, which themselves had relations to diet and exercise measures. Multiple-group modeling indicated that effects of self-control were comparable across gender and ethnicity subgroups. Conclusions Self-control concepts are relevant for patterns of dietary intake and physical activity among adolescents. Attention to self-control processes may be warranted for prevention programs to improve health behaviors in childhood and adolescence. PMID:18023783

Beyond Serial Founder Effects: The Impact of Admixture and Localized Gene Flow on Patterns of Regional Genetic Diversity.

PubMed

Hunley, Keith L; Cabana, Graciela S

2016-07-01

Geneticists have argued that the linear decay in within-population genetic diversity with increasing geographic distance from East Africa is best explained by a phylogenetic process of repeated founder effects, growth, and isolation. However, this serial founder effect (SFE) process has not yet been adequately vetted against other evolutionary processes that may also affect geospatial patterns of diversity. Additionally, studies of the SFE process have been largely based on a limited 52-population sample. Here, we assess the effects of founder effect, admixture, and localized gene flow processes on patterns of global and regional diversity using a published data set of 645 autosomal microsatellite genotypes from 5,415 individuals in 248 widespread populations. We used a formal tree-fitting approach to explore the role of founder effects. The approach involved fitting global and regional population trees to extant patterns of gene diversity and then systematically examining the deviations in fit. We also informally tested the SFE process using linear models of gene diversity versus waypoint geographic distances from Africa. We tested the role of localized gene flow using partial Mantel correlograms of gene diversity versus geographic distance controlling for the confounding effects of treelike genetic structure. We corroborate previous findings that global patterns of diversity, both within and between populations, are the product of an out-of-Africa SFE process. Within regions, however, diversity within populations is uncorrelated with geographic distance from Africa. Here, patterns of diversity have been largely shaped by recent interregional admixture and secondary range expansions. Our detailed analyses of the pattern of diversity within and between populations reveal that the signatures of different evolutionary processes dominate at different geographic scales. These findings have important implications for recent publications on the biology of race.

Model-based analysis of multi-shell diffusion MR data for tractography: How to get over fitting problems

PubMed Central

Jbabdi, Saad; Sotiropoulos, Stamatios N; Savio, Alexander M; Graña, Manuel; Behrens, Timothy EJ

2012-01-01

In this article, we highlight an issue that arises when using multiple b-values in a model-based analysis of diffusion MR data for tractography. The non-mono-exponential decay, commonly observed in experimental data, is shown to induce over-fitting in the distribution of fibre orientations when not considered in the model. Extra fibre orientations perpendicular to the main orientation arise to compensate for the slower apparent signal decay at higher b-values. We propose a simple extension to the ball and stick model based on a continuous Gamma distribution of diffusivities, which significantly improves the fitting and reduces the over-fitting. Using in-vivo experimental data, we show that this model outperforms a simpler, noise floor model, especially at the interfaces between brain tissues, suggesting that partial volume effects are a major cause of the observed non-mono-exponential decay. This model may be helpful for future data acquisition strategies that may attempt to combine multiple shells to improve estimates of fibre orientations in white matter and near the cortex. PMID:22334356

Curvature, metric and parametrization of origami tessellations: theory and application to the eggbox pattern.

PubMed

Nassar, H; Lebée, A; Monasse, L

2017-01-01

Origami tessellations are particular textured morphing shell structures. Their unique folding and unfolding mechanisms on a local scale aggregate and bring on large changes in shape, curvature and elongation on a global scale. The existence of these global deformation modes allows for origami tessellations to fit non-trivial surfaces thus inspiring applications across a wide range of domains including structural engineering, architectural design and aerospace engineering. The present paper suggests a homogenization-type two-scale asymptotic method which, combined with standard tools from differential geometry of surfaces, yields a macroscopic continuous characterization of the global deformation modes of origami tessellations and other similar periodic pin-jointed trusses. The outcome of the method is a set of nonlinear differential equations governing the parametrization, metric and curvature of surfaces that the initially discrete structure can fit. The theory is presented through a case study of a fairly generic example: the eggbox pattern. The proposed continuous model predicts correctly the existence of various fittings that are subsequently constructed and illustrated.

Curvature, metric and parametrization of origami tessellations: theory and application to the eggbox pattern

NASA Astrophysics Data System (ADS)

Nassar, H.; Lebée, A.; Monasse, L.

2017-01-01

Origami tessellations are particular textured morphing shell structures. Their unique folding and unfolding mechanisms on a local scale aggregate and bring on large changes in shape, curvature and elongation on a global scale. The existence of these global deformation modes allows for origami tessellations to fit non-trivial surfaces thus inspiring applications across a wide range of domains including structural engineering, architectural design and aerospace engineering. The present paper suggests a homogenization-type two-scale asymptotic method which, combined with standard tools from differential geometry of surfaces, yields a macroscopic continuous characterization of the global deformation modes of origami tessellations and other similar periodic pin-jointed trusses. The outcome of the method is a set of nonlinear differential equations governing the parametrization, metric and curvature of surfaces that the initially discrete structure can fit. The theory is presented through a case study of a fairly generic example: the eggbox pattern. The proposed continuous model predicts correctly the existence of various fittings that are subsequently constructed and illustrated.

PyFolding: Open-Source Graphing, Simulation, and Analysis of the Biophysical Properties of Proteins.

PubMed

Lowe, Alan R; Perez-Riba, Albert; Itzhaki, Laura S; Main, Ewan R G

2018-02-06

For many years, curve-fitting software has been heavily utilized to fit simple models to various types of biophysical data. Although such software packages are easy to use for simple functions, they are often expensive and present substantial impediments to applying more complex models or for the analysis of large data sets. One field that is reliant on such data analysis is the thermodynamics and kinetics of protein folding. Over the past decade, increasingly sophisticated analytical models have been generated, but without simple tools to enable routine analysis. Consequently, users have needed to generate their own tools or otherwise find willing collaborators. Here we present PyFolding, a free, open-source, and extensible Python framework for graphing, analysis, and simulation of the biophysical properties of proteins. To demonstrate the utility of PyFolding, we have used it to analyze and model experimental protein folding and thermodynamic data. Examples include: 1) multiphase kinetic folding fitted to linked equations, 2) global fitting of multiple data sets, and 3) analysis of repeat protein thermodynamics with Ising model variants. Moreover, we demonstrate how PyFolding is easily extensible to novel functionality beyond applications in protein folding via the addition of new models. Example scripts to perform these and other operations are supplied with the software, and we encourage users to contribute notebooks and models to create a community resource. Finally, we show that PyFolding can be used in conjunction with Jupyter notebooks as an easy way to share methods and analysis for publication and among research teams. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Erroneous Arrhenius: Modified Arrhenius model best explains the temperature dependence of ectotherm fitness

PubMed Central

Knies, Jennifer L.; Kingsolver, Joel G.

2013-01-01

The initial rise of fitness that occurs with increasing temperature is attributed to Arrhenius kinetics, in which rates of reaction increase exponentially with increasing temperature. Models based on Arrhenius typically assume single rate-limiting reaction(s) over some physiological temperature range for which all the rate-limiting enzymes are in 100% active conformation. We test this assumption using datasets for microbes that have measurements of fitness (intrinsic rate of population growth) at many temperatures and over a broad temperature range, and for diverse ectotherms that have measurements at fewer temperatures. When measurements are available at many temperatures, strictly Arrhenius kinetics is rejected over the physiological temperature range. However, over a narrower temperature range, we cannot reject strictly Arrhenius kinetics. The temperature range also affects estimates of the temperature dependence of fitness. These results indicate that Arrhenius kinetics only apply over a narrow range of temperatures for ectotherms, complicating attempts to identify general patterns of temperature dependence. PMID:20528477

Erroneous Arrhenius: modified arrhenius model best explains the temperature dependence of ectotherm fitness.

PubMed

Knies, Jennifer L; Kingsolver, Joel G

2010-08-01

The initial rise of fitness that occurs with increasing temperature is attributed to Arrhenius kinetics, in which rates of reaction increase exponentially with increasing temperature. Models based on Arrhenius typically assume single rate-limiting reactions over some physiological temperature range for which all the rate-limiting enzymes are in 100% active conformation. We test this assumption using data sets for microbes that have measurements of fitness (intrinsic rate of population growth) at many temperatures and over a broad temperature range and for diverse ectotherms that have measurements at fewer temperatures. When measurements are available at many temperatures, strictly Arrhenius kinetics are rejected over the physiological temperature range. However, over a narrower temperature range, we cannot reject strictly Arrhenius kinetics. The temperature range also affects estimates of the temperature dependence of fitness. These results indicate that Arrhenius kinetics only apply over a narrow range of temperatures for ectotherms, complicating attempts to identify general patterns of temperature dependence.

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

Takahashi, Koh; Umeda, Hideyuki; Yoshida, Takashi, E-mail: ktakahashi@astron.s.u-tokyo.ac.jp

We perform a stellar evolution simulation of first stars and calculate stellar yields from the first supernovae. The initial masses are taken from 12 to 140 M {sub ☉} to cover the whole range of core-collapse supernova progenitors, and stellar rotation is included, which results in efficient internal mixing. A weak explosion is assumed in supernova yield calculations, thus only outer distributed matter, which is not affected by the explosive nucleosynthesis, is ejected in the models. We show that the initial mass and the rotation affect the explosion yield. All the weak explosion models have abundances of [C/O] larger thanmore » unity. Stellar yields from massive progenitors of >40-60 M {sub ☉} show enhancement of Mg and Si. Rotating models yield abundant Na and Al, and Ca is synthesized in nonrotating heavy massive models of >80 M {sub ☉}. We fit the stellar yields to the three most iron-deficient stars and constrain the initial parameters of the mother progenitor stars. The abundance pattern in SMSS 0313–6708 is well explained by 50-80 M {sub ☉} nonrotating models, rotating 30-40 M {sub ☉} models well fit the abundance of HE 0107-5240, and both nonrotating and rotating 15-40 M {sub ☉} models explain HE 1327-2326. The presented analysis will be applicable to other carbon-enhanced hyper-metal-poor stars observed in the future. The abundance analyses will give valuable information about the characteristics of the first stars.« less

Decomposition of mineral absorption bands using nonlinear least squares curve fitting: Application to Martian meteorites and CRISM data

NASA Astrophysics Data System (ADS)

Parente, Mario; Makarewicz, Heather D.; Bishop, Janice L.

2011-04-01

This study advances curve-fitting modeling of absorption bands of reflectance spectra and applies this new model to spectra of Martian meteorites ALH 84001 and EETA 79001 and data from the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM). This study also details a recently introduced automated parameter initialization technique. We assess the performance of this automated procedure by comparing it to the currently available initialization method and perform a sensitivity analysis of the fit results to variation in initial guesses. We explore the issues related to the removal of the continuum, offer guidelines for continuum removal when modeling the absorptions and explore different continuum-removal techniques. We further evaluate the suitability of curve fitting techniques using Gaussians/Modified Gaussians to decompose spectra into individual end-member bands. We show that nonlinear least squares techniques such as the Levenberg-Marquardt algorithm achieve comparable results to the MGM model ( Sunshine and Pieters, 1993; Sunshine et al., 1990) for meteorite spectra. Finally we use Gaussian modeling to fit CRISM spectra of pyroxene and olivine-rich terrains on Mars. Analysis of CRISM spectra of two regions show that the pyroxene-dominated rock spectra measured at Juventae Chasma were modeled well with low Ca pyroxene, while the pyroxene-rich spectra acquired at Libya Montes required both low-Ca and high-Ca pyroxene for a good fit.

Anomaly Detection in Dynamic Networks

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

Turcotte, Melissa

2014-10-14

Anomaly detection in dynamic communication networks has many important security applications. These networks can be extremely large and so detecting any changes in their structure can be computationally challenging; hence, computationally fast, parallelisable methods for monitoring the network are paramount. For this reason the methods presented here use independent node and edge based models to detect locally anomalous substructures within communication networks. As a first stage, the aim is to detect changes in the data streams arising from node or edge communications. Throughout the thesis simple, conjugate Bayesian models for counting processes are used to model these data streams. Amore » second stage of analysis can then be performed on a much reduced subset of the network comprising nodes and edges which have been identified as potentially anomalous in the first stage. The first method assumes communications in a network arise from an inhomogeneous Poisson process with piecewise constant intensity. Anomaly detection is then treated as a changepoint problem on the intensities. The changepoint model is extended to incorporate seasonal behavior inherent in communication networks. This seasonal behavior is also viewed as a changepoint problem acting on a piecewise constant Poisson process. In a static time frame, inference is made on this extended model via a Gibbs sampling strategy. In a sequential time frame, where the data arrive as a stream, a novel, fast Sequential Monte Carlo (SMC) algorithm is introduced to sample from the sequence of posterior distributions of the change points over time. A second method is considered for monitoring communications in a large scale computer network. The usage patterns in these types of networks are very bursty in nature and don’t fit a Poisson process model. For tractable inference, discrete time models are considered, where the data are aggregated into discrete time periods and probability models are fitted to the communication counts. In a sequential analysis, anomalous behavior is then identified from outlying behavior with respect to the fitted predictive probability models. Seasonality is again incorporated into the model and is treated as a changepoint model on the transition probabilities of a discrete time Markov process. Second stage analytics are then developed which combine anomalous edges to identify anomalous substructures in the network.« less

Patterns and scaling properties of surface soil moisture in an agricultural landscape: An ecohydrological modeling study

NASA Astrophysics Data System (ADS)

Korres, W.; Reichenau, T. G.; Schneider, K.

2013-08-01

Soil moisture is a key variable in hydrology, meteorology and agriculture. Soil moisture, and surface soil moisture in particular, is highly variable in space and time. Its spatial and temporal patterns in agricultural landscapes are affected by multiple natural (precipitation, soil, topography, etc.) and agro-economic (soil management, fertilization, etc.) factors, making it difficult to identify unequivocal cause and effect relationships between soil moisture and its driving variables. The goal of this study is to characterize and analyze the spatial and temporal patterns of surface soil moisture (top 20 cm) in an intensively used agricultural landscape (1100 km2 northern part of the Rur catchment, Western Germany) and to determine the dominant factors and underlying processes controlling these patterns. A second goal is to analyze the scaling behavior of surface soil moisture patterns in order to investigate how spatial scale affects spatial patterns. To achieve these goals, a dynamically coupled, process-based and spatially distributed ecohydrological model was used to analyze the key processes as well as their interactions and feedbacks. The model was validated for two growing seasons for the three main crops in the investigation area: Winter wheat, sugar beet, and maize. This yielded RMSE values for surface soil moisture between 1.8 and 7.8 vol.% and average RMSE values for all three crops of 0.27 kg m-2 for total aboveground biomass and 0.93 for green LAI. Large deviations of measured and modeled soil moisture can be explained by a change of the infiltration properties towards the end of the growing season, especially in maize fields. The validated model was used to generate daily surface soil moisture maps, serving as a basis for an autocorrelation analysis of spatial patterns and scale. Outside of the growing season, surface soil moisture patterns at all spatial scales depend mainly upon soil properties. Within the main growing season, larger scale patterns that are induced by soil properties are superimposed by the small scale land use pattern and the resulting small scale variability of evapotranspiration. However, this influence decreases at larger spatial scales. Most precipitation events cause temporarily higher surface soil moisture autocorrelation lengths at all spatial scales for a short time even beyond the autocorrelation lengths induced by soil properties. The relation of daily spatial variance to the spatial scale of the analysis fits a power law scaling function, with negative values of the scaling exponent, indicating a decrease in spatial variability with increasing spatial resolution. High evapotranspiration rates cause an increase in the small scale soil moisture variability, thus leading to large negative values of the scaling exponent. Utilizing a multiple regression analysis, we found that 53% of the variance of the scaling exponent can be explained by a combination of an independent LAI parameter and the antecedent precipitation.

A Practical Guide to Check the Consistency of Item Response Patterns in Clinical Research Through Person-Fit Statistics: Examples and a Computer Program.

PubMed

Meijer, Rob R; Niessen, A Susan M; Tendeiro, Jorge N

2016-02-01

Although there are many studies devoted to person-fit statistics to detect inconsistent item score patterns, most studies are difficult to understand for nonspecialists. The aim of this tutorial is to explain the principles of these statistics for researchers and clinicians who are interested in applying these statistics. In particular, we first explain how invalid test scores can be detected using person-fit statistics; second, we provide the reader practical examples of existing studies that used person-fit statistics to detect and to interpret inconsistent item score patterns; and third, we discuss a new R-package that can be used to identify and interpret inconsistent score patterns. © The Author(s) 2015.

Bioenergetics-based modeling of individual PCB congeners in nestling tree swallows from two contaminated sites on the Upper Hudson River, New York

USGS Publications Warehouse

Nichols, John W.; Echols, Kathy R.; Tillitt, Donald E.; Secord, Anne L.; McCarty, John P.

2004-01-01

A bioenergetics-based model was used to simulate the accumulation of total PCBs and 20 PCB congeners by nestling tree swallows at two contaminated sites on the Upper Hudson River, New York. PCB concentrations in birds were calculated as the sum of inherited residues and those acquired through consumption of contaminated insects. Close agreement between simulations and measured residues in 5-, 10-, and 15-day-old nestlings was obtained when PCB concentrations in the diet were set equal to those in food boli taken from adult birds. These simulations were further optimized by fitting the value of a dietary assimilation efficiency constant. Fitted constants for both sites were similar and averaged about 0.7. An evaluation of model performance for individual congeners provided no evidence of metabolic biotransformation. The results of this study are consistent with a companion effort in which principal components analysis was used to compare PCB congener patterns in insects and in tree swallow eggs, nestlings, and adults. Together, these studies establish a quantitative linkage between nestling tree swallows and the insects that they consume and provide strong support for the use of nestling swallows as a biomonitoring species for exposure assessment.

Particle size distributions by transmission electron microscopy: an interlaboratory comparison case study

PubMed Central

Rice, Stephen B; Chan, Christopher; Brown, Scott C; Eschbach, Peter; Han, Li; Ensor, David S; Stefaniak, Aleksandr B; Bonevich, John; Vladár, András E; Hight Walker, Angela R; Zheng, Jiwen; Starnes, Catherine; Stromberg, Arnold; Ye, Jia; Grulke, Eric A

2015-01-01

This paper reports an interlaboratory comparison that evaluated a protocol for measuring and analysing the particle size distribution of discrete, metallic, spheroidal nanoparticles using transmission electron microscopy (TEM). The study was focused on automated image capture and automated particle analysis. NIST RM8012 gold nanoparticles (30 nm nominal diameter) were measured for area-equivalent diameter distributions by eight laboratories. Statistical analysis was used to (1) assess the data quality without using size distribution reference models, (2) determine reference model parameters for different size distribution reference models and non-linear regression fitting methods and (3) assess the measurement uncertainty of a size distribution parameter by using its coefficient of variation. The interlaboratory area-equivalent diameter mean, 27.6 nm ± 2.4 nm (computed based on a normal distribution), was quite similar to the area-equivalent diameter, 27.6 nm, assigned to NIST RM8012. The lognormal reference model was the preferred choice for these particle size distributions as, for all laboratories, its parameters had lower relative standard errors (RSEs) than the other size distribution reference models tested (normal, Weibull and Rosin–Rammler–Bennett). The RSEs for the fitted standard deviations were two orders of magnitude higher than those for the fitted means, suggesting that most of the parameter estimate errors were associated with estimating the breadth of the distributions. The coefficients of variation for the interlaboratory statistics also confirmed the lognormal reference model as the preferred choice. From quasi-linear plots, the typical range for good fits between the model and cumulative number-based distributions was 1.9 fitted standard deviations less than the mean to 2.3 fitted standard deviations above the mean. Automated image capture, automated particle analysis and statistical evaluation of the data and fitting coefficients provide a framework for assessing nanoparticle size distributions using TEM for image acquisition. PMID:26361398

Spectral Study of Measles Epidemics: The Dependence of Spectral Gradient on the Population Size of the Community

NASA Astrophysics Data System (ADS)

Sumi, Ayako; Olsen, Lars Folke; Ohtomo, Norio; Tanaka, Yukio; Sawamura, Sadashi

2003-02-01

We have carried out spectral analysis of measles notifications in several communities in Denmark, UK and USA. The results confirm that each power spectral density (PSD) shows exponential characteristics, which are universally observed in the PSD for time series generated from nonlinear dynamical system. The exponential gradient increases with the population size. For almost all communities, many spectral lines observed in each PSD can be fully assigned to linear combinations of several fundamental periods, suggesting that the measles data are substantially noise-free. The optimum least squares fitting curve calculated using these fundamental periods essentially reproduces an underlying variation of the measles data, and an extension of the curve can be used to predict measles epidemics. For the communities with large population sizes, some PSD patterns obtained from segment time series analysis show a close resemblance to the PSD patterns at the initial stages of a period-doubling bifurcation process for the so-called susceptible/exposed/infectious/recovered (SEIR) model with seasonal forcing. The meaning of the relationship between the exponential gradient and the population size is discussed.

Exact computation of the maximum-entropy potential of spiking neural-network models.

PubMed

Cofré, R; Cessac, B

2014-05-01

Understanding how stimuli and synaptic connectivity influence the statistics of spike patterns in neural networks is a central question in computational neuroscience. The maximum-entropy approach has been successfully used to characterize the statistical response of simultaneously recorded spiking neurons responding to stimuli. However, in spite of good performance in terms of prediction, the fitting parameters do not explain the underlying mechanistic causes of the observed correlations. On the other hand, mathematical models of spiking neurons (neuromimetic models) provide a probabilistic mapping between the stimulus, network architecture, and spike patterns in terms of conditional probabilities. In this paper we build an exact analytical mapping between neuromimetic and maximum-entropy models.

Are all models created equal? A content analysis of women in advertisements of fitness versus fashion magazines.

PubMed

Wasylkiw, L; Emms, A A; Meuse, R; Poirier, K F

2009-03-01

The current study is a content analysis of women appearing in advertisements in two types of magazines: fitness/health versus fashion/beauty chosen because of their large and predominantly female readerships. Women appearing in advertisements of the June 2007 issue of five fitness/health magazines were compared to women appearing in advertisements of the June 2007 issue of five beauty/fashion magazines. Female models appearing in advertisements of both types of magazines were primarily young, thin Caucasians; however, images of models were more likely to emphasize appearance over performance when they appeared in fashion magazines. This difference in emphasis has implications for future research.

Experimental study of canvas characterization for paintings

NASA Astrophysics Data System (ADS)

Cornelis, Bruno; Dooms, Ann; Munteanu, Adrian; Cornelis, Jan; Schelkens, Peter

2010-02-01

The work described here fits in the context of a larger project on the objective and relevant characterization of paintings and painting canvas through the analysis of multimodal digital images. We captured, amongst others, X-ray images of different canvas types, characterized by a variety of textures and weave patterns (fine and rougher texture; single thread and multiple threads per weave), including raw canvas as well as canvas processed with different primers. In this paper, we study how to characterize the canvas by extracting global features such as average thread width, average distance between successive threads (i.e. thread density) and the spatial distribution of primers. These features are then used to construct a generic model of the canvas structure. Secondly, we investigate whether we can identify different pieces of canvas coming from the same bolt. This is an important element for dating, authentication and identification of restorations. Both the global characteristics mentioned earlier and some local properties (such as deviations from the average pattern model) are used to compare the "fingerprint" of different pieces of cloth coming from the same or different bolts.

Decomposition Analyses Applied to a Complex Ultradian Biorhythm: The Oscillating NADH Oxidase Activity of Plasma Membranes Having a Potential Time-Keeping (Clock) Function

PubMed Central

Foster, Ken; Anwar, Nasim; Pogue, Rhea; Morré, Dorothy M.; Keenan, T. W.; Morré, D. James

2003-01-01

Seasonal decomposition analyses were applied to the statistical evaluation of an oscillating activity for a plasma membrane NADH oxidase activity with a temperature compensated period of 24 min. The decomposition fits were used to validate the cyclic oscillatory pattern. Three measured values, average percentage error (MAPE), a measure of the periodic oscillation, mean average deviation (MAD), a measure of the absolute average deviations from the fitted values, and mean standard deviation (MSD), the measure of standard deviation from the fitted values plus R-squared and the Henriksson-Merton p value were used to evaluate accuracy. Decomposition was carried out by fitting a trend line to the data, then detrending the data if necessary, by subtracting the trend component. The data, with or without detrending, were then smoothed by subtracting a centered moving average of length equal to the period length determined by Fourier analysis. Finally, the time series were decomposed into cyclic and error components. The findings not only validate the periodic nature of the major oscillations but suggest, as well, that the minor intervening fluctuations also recur within each period with a reproducible pattern of recurrence. PMID:19330112

A single factor underlies the metabolic syndrome: a confirmatory factor analysis.

PubMed

Pladevall, Manel; Singal, Bonita; Williams, L Keoki; Brotons, Carlos; Guyer, Heidi; Sadurni, Josep; Falces, Carles; Serrano-Rios, Manuel; Gabriel, Rafael; Shaw, Jonathan E; Zimmet, Paul Z; Haffner, Steven

2006-01-01

Confirmatory factor analysis (CFA) was used to test the hypothesis that the components of the metabolic syndrome are manifestations of a single common factor. Three different datasets were used to test and validate the model. The Spanish and Mauritian studies included 207 men and 203 women and 1,411 men and 1,650 women, respectively. A third analytical dataset including 847 men was obtained from a previously published CFA of a U.S. population. The one-factor model included the metabolic syndrome core components (central obesity, insulin resistance, blood pressure, and lipid measurements). We also tested an expanded one-factor model that included uric acid and leptin levels. Finally, we used CFA to compare the goodness of fit of one-factor models with the fit of two previously published four-factor models. The simplest one-factor model showed the best goodness-of-fit indexes (comparative fit index 1, root mean-square error of approximation 0.00). Comparisons of one-factor with four-factor models in the three datasets favored the one-factor model structure. The selection of variables to represent the different metabolic syndrome components and model specification explained why previous exploratory and confirmatory factor analysis, respectively, failed to identify a single factor for the metabolic syndrome. These analyses support the current clinical definition of the metabolic syndrome, as well as the existence of a single factor that links all of the core components.

Spatial and temporal uplift history of South America from calibrated drainage analysis

NASA Astrophysics Data System (ADS)

Rodríguez Tribaldos, V.; White, N. J.; Roberts, G. G.; Hoggard, M. J.

2017-06-01

A multidisciplinary approach is used to analyze the Cenozoic uplift history of South America. Residual depth anomalies of oceanic crust abutting this continent help to determine the pattern of present-day dynamic topography. Admittance analysis and crustal thickness measurements indicate that the elastic thickness of the Borborema and Altiplano regions is ≤10 km with evidence for sub-plate support at longer wavelengths. A drainage inventory of 1827 river profiles is assembled and used to investigate landscape development. Linear inverse modeling enables river profiles to be fitted as a function of the spatial and temporal history of regional uplift. Erosional parameters are calibrated using observations from the Borborema Plateau and tested against continent-wide stratigraphic and thermochronologic constraints. Our results predict that two phases of regional uplift of the Altiplano plateau occurred in Neogene times. Regional uplift of the southern Patagonian Andes also appears to have occurred in Early Miocene times. The consistency between observed and predicted histories for the Borborema, Altiplano, and Patagonian plateaux implies that drainage networks record coherent signals that are amenable to simple modeling strategies. Finally, the predicted pattern of incision across the Amazon catchment constrains solid sedimentary flux at the Foz do Amazonas. Observed and calculated flux estimates match, suggesting that erosion and deposition were triggered by regional Andean uplift during Miocene times.

Assessing spatial inequalities in accessing community pharmacies: a mixed geographically weighted approach.

PubMed

Domnich, Alexander; Arata, Lucia; Amicizia, Daniela; Signori, Alessio; Gasparini, Roberto; Panatto, Donatella

2016-11-16

Geographical accessibility is an important determinant for the utilisation of community pharmacies. The present study explored patterns of spatial accessibility with respect to pharmacies in Liguria, Italy, a region with particular geographical and demographic features. Municipal density of pharmacies was proxied as the number of pharmacies per capita and per km2, and spatial autocorrelation analysis was performed to identify spatial clusters. Both non-spatial and spatial models were constructed to predict the study outcome. Spatial autocorrelation analysis showed a highly significant clustered pattern in the density of pharmacies per capita (I=0.082) and per km2 (I=0.295). Potentially under-supplied areas were mostly located in the mountainous hinterland. Ordinary least-squares (OLS) regressions established a significant positive relationship between the density of pharmacies and income among municipalities located at high altitudes, while no such association was observed in lower-lying areas. However, residuals of the OLS models were spatially auto-correlated. The best-fitting mixed geographically weighted regression (GWR) models outperformed the corresponding OLS models. Pharmacies per capita were best predicted by two local predictors (altitude and proportion of immigrants) and two global ones (proportion of elderly residents and income), while the local terms population, mean altitude and rural status and the global term income functioned as independent variables predicting pharmacies per km2. The density of pharmacies in Liguria was found to be associated with both socio-economic and landscape factors. Mapping of mixed GWR results would be helpful to policy-makers.

An autoregressive integrated moving average model for short-term prediction of hepatitis C virus seropositivity among male volunteer blood donors in Karachi, Pakistan

PubMed Central

Akhtar, Saeed; Rozi, Shafquat

2009-01-01

AIM: To identify the stochastic autoregressive integrated moving average (ARIMA) model for short term forecasting of hepatitis C virus (HCV) seropositivity among volunteer blood donors in Karachi, Pakistan. METHODS: Ninety-six months (1998-2005) data on HCV seropositive cases (1000-1 × month-1) among male volunteer blood donors tested at four major blood banks in Karachi, Pakistan were subjected to ARIMA modeling. Subsequently, a fitted ARIMA model was used to forecast HCV seropositive donors for 91-96 mo to contrast with observed series of the same months. To assess the forecast accuracy, the mean absolute error rate (%) between the observed and predicted HCV seroprevalence was calculated. Finally, a fitted ARIMA model was used for short-term forecasts beyond the observed series. RESULTS: The goodness-of-fit test of the optimum ARIMA (2,1,7) model showed non-significant autocorrelations in the residuals of the model. The forecasts by ARIMA for 91-96 mo closely followed the pattern of observed series for the same months, with mean monthly absolute forecast errors (%) over 6 mo of 6.5%. The short-term forecasts beyond the observed series adequately captured the pattern in the data and showed increasing tendency of HCV seropositivity with a mean ± SD HCV seroprevalence (1000-1 × month-1) of 24.3 ± 1.4 over the forecast interval. CONCLUSION: To curtail HCV spread, public health authorities need to educate communities and health care providers about HCV transmission routes based on known HCV epidemiology in Pakistan and its neighboring countries. Future research may focus on factors associated with hyperendemic levels of HCV infection. PMID:19340903

Population patterns in World’s administrative units

PubMed Central

Miramontes, Pedro; Cocho, Germinal

2017-01-01

Whereas there has been an extended discussion concerning city population distribution, little has been said about that of administrative divisions. In this work, we investigate the population distribution of second-level administrative units of 150 countries and territories and propose the discrete generalized beta distribution (DGBD) rank-size function to describe the data. After testing the balance between the goodness of fit and number of parameters of this function compared with a power law, which is the most common model for city population, the DGBD is a good statistical model for 96% of our datasets and preferred over a power law in almost every case. Moreover, the DGBD is preferred over a power law for fitting country population data, which can be seen as the zeroth-level administrative unit. We present a computational toy model to simulate the formation of administrative divisions in one dimension and give numerical evidence that the DGBD arises from a particular case of this model. This model, along with the fitting of the DGBD, proves adequate in reproducing and describing local unit evolution and its effect on the population distribution. PMID:28791153

Evaluating WAIS-IV structure through a different psychometric lens: structural causal model discovery as an alternative to confirmatory factor analysis.

PubMed

van Dijk, Marjolein J A M; Claassen, Tom; Suwartono, Christiany; van der Veld, William M; van der Heijden, Paul T; Hendriks, Marc P H

Since the publication of the WAIS-IV in the U.S. in 2008, efforts have been made to explore the structural validity by applying factor analysis to various samples. This study aims to achieve a more fine-grained understanding of the structure of the Dutch language version of the WAIS-IV (WAIS-IV-NL) by applying an alternative analysis based on causal modeling in addition to confirmatory factor analysis (CFA). The Bayesian Constraint-based Causal Discovery (BCCD) algorithm learns underlying network structures directly from data and assesses more complex structures than is possible with factor analysis. WAIS-IV-NL profiles of two clinical samples of 202 patients (i.e. patients with temporal lobe epilepsy and a mixed psychiatric outpatient group) were analyzed and contrasted with a matched control group (N = 202) selected from the Dutch standardization sample of the WAIS-IV-NL to investigate internal structure by means of CFA and BCCD. With CFA, the four-factor structure as proposed by Wechsler demonstrates acceptable fit in all three subsamples. However, BCCD revealed three consistent clusters (verbal comprehension, visual processing, and processing speed) in all three subsamples. The combination of Arithmetic and Digit Span as a coherent working memory factor could not be verified, and Matrix Reasoning appeared to be isolated. With BCCD, some discrepancies from the proposed four-factor structure are exemplified. Furthermore, these results fit CHC theory of intelligence more clearly. Consistent clustering patterns indicate these results are robust. The structural causal discovery approach may be helpful in better interpreting existing tests, the development of new tests, and aid in diagnostic instruments.

A gamma variate model that includes stretched exponential is a better fit for gastric emptying data from mice

PubMed Central

Bajzer, Željko; Gibbons, Simon J.; Coleman, Heidi D.; Linden, David R.

2015-01-01

Noninvasive breath tests for gastric emptying are important techniques for understanding the changes in gastric motility that occur in disease or in response to drugs. Mice are often used as an animal model; however, the gamma variate model currently used for data analysis does not always fit the data appropriately. The aim of this study was to determine appropriate mathematical models to better fit mouse gastric emptying data including when two peaks are present in the gastric emptying curve. We fitted 175 gastric emptying data sets with two standard models (gamma variate and power exponential), with a gamma variate model that includes stretched exponential and with a proposed two-component model. The appropriateness of the fit was assessed by the Akaike Information Criterion. We found that extension of the gamma variate model to include a stretched exponential improves the fit, which allows for a better estimation of T1/2 and Tlag. When two distinct peaks in gastric emptying are present, a two-component model is required for the most appropriate fit. We conclude that use of a stretched exponential gamma variate model and when appropriate a two-component model will result in a better estimate of physiologically relevant parameters when analyzing mouse gastric emptying data. PMID:26045615

Non-proportional odds multivariate logistic regression of ordinal family data.

PubMed

Zaloumis, Sophie G; Scurrah, Katrina J; Harrap, Stephen B; Ellis, Justine A; Gurrin, Lyle C

2015-03-01

Methods to examine whether genetic and/or environmental sources can account for the residual variation in ordinal family data usually assume proportional odds. However, standard software to fit the non-proportional odds model to ordinal family data is limited because the correlation structure of family data is more complex than for other types of clustered data. To perform these analyses we propose the non-proportional odds multivariate logistic regression model and take a simulation-based approach to model fitting using Markov chain Monte Carlo methods, such as partially collapsed Gibbs sampling and the Metropolis algorithm. We applied the proposed methodology to male pattern baldness data from the Victorian Family Heart Study. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A New Global Regression Analysis Method for the Prediction of Wind Tunnel Model Weight Corrections

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert Manfred; Bridge, Thomas M.; Amaya, Max A.

2014-01-01

A new global regression analysis method is discussed that predicts wind tunnel model weight corrections for strain-gage balance loads during a wind tunnel test. The method determines corrections by combining "wind-on" model attitude measurements with least squares estimates of the model weight and center of gravity coordinates that are obtained from "wind-off" data points. The method treats the least squares fit of the model weight separate from the fit of the center of gravity coordinates. Therefore, it performs two fits of "wind- off" data points and uses the least squares estimator of the model weight as an input for the fit of the center of gravity coordinates. Explicit equations for the least squares estimators of the weight and center of gravity coordinates are derived that simplify the implementation of the method in the data system software of a wind tunnel. In addition, recommendations for sets of "wind-off" data points are made that take typical model support system constraints into account. Explicit equations of the confidence intervals on the model weight and center of gravity coordinates and two different error analyses of the model weight prediction are also discussed in the appendices of the paper.

LONGITUDINAL PATTERNS OF CARDIORESPIRATORY FITNESS PREDICT THE DEVELOPMENT OF HYPERTENSION AMONG MEN AND WOMEN

PubMed Central

Sui, Xuemei; Sarzynski, Mark A.; Lee, Duck-chul; Lavie, Carl J.; Zhang, Jiajia; Kokkinos, Peter F.; Payne, Jonathan; Blair, Steven N.

2016-01-01

Background Most of the existing literature has linked either a baseline cardiorespiratory fitness, or change between baseline and one follow-up measurement of cardiorespiratory fitness, to hypertension. The purpose of the study is to assess the association between longitudinal patterns of cardiorespiratory fitness changes with time and incident hypertension in adult men and women. Patients and Methods Participants were aged from 20 to 82 years, free of hypertension during the first three examinations, and received at least four preventive medical examinations at the Cooper Clinic in Dallas, TX, during 1971 – 2006. They were classified into one of five groups based on all of the measured cardiorespiratory fitness values (in metabolic equivalents) during maximal treadmill tests. Logistic regression was used to compute odds ratios and 95% confidence intervals. Results Among a total of 4,932 participants (13% women), 1,954 developed hypertension. After controlling for baseline potential confounders, follow-up duration, and number of follow-up visits, odds ratios (95% confidence intervals) for hypertension were: 1.00 for decreasing group (referent), 0.64 (0.52–0.80) for increasing, 0.89 (0.70–1.12) for Bell-shape, 0.78 (0.62–0.98) for U-shape, and 0.83 (0.69–1.00) for inconsistent group. The general pattern of the association was consistent regardless of participants’ baseline cardiorespiratory fitness or body mass index levels. Conclusion An increasing pattern of cardiorespiratory fitness provides the lowest risk of hypertension in this middle-aged relatively healthy population. Identifying specific pattern(s) of cardiorespiratory fitness change may be important for determining associations with comorbidity such as hypertension. PMID:27986522

Characterizing longitudinal health state transitions among heroin, cocaine, and methamphetamine users

PubMed Central

Nosyk, B; Li, L; Evans, E; Huang, D; Min, J; Kerr, T; Brecht, ML; Hser, YI

2014-01-01

Aims Characterize longitudinal patterns of drug use careers and identify determinants of drug use frequency across cohorts of primary heroin, methamphetamine (MA) and cocaine users. Design Pooled analysis of prospective cohort studies. Settings Illicit drug users recruited from community, criminal justice and drug treatment settings in California, USA. Participants We used longitudinal data on from five observational cohort studies featuring primary users of heroin (N=629), cocaine (N=694) and methamphetamine (N=474). The mean duration of follow-up was 20.9 years. Measurements Monthly longitudinal data was arranged according to five health states (incarceration, drug treatment, abstinence, non-daily and daily use). We fitted proportional hazards (PH) frailty models to determine independent differences in successive episode durations. We then executed multi-state Markov (MSM) models to estimate probabilities of transitioning between health states, and the determinants of these transitions. Findings Across primary drug use types, PH frailty models demonstrated durations of daily use diminished in successive episodes over time. MSM models revealed primary stimulant users had more erratic longitudinal patterns of drug use, transitioning more rapidly between periods of treatment, abstinence, non-daily and daily use. MA users exhibited relatively longer durations of high-frequency use. Criminal engagement had a destabilizing effect on health state durations across drug types. Longer incarceration histories were associated with delayed transitions towards cessation. Conclusions PH frailty and MSM modeling techniques provided complementary information on longitudinal patterns of drug abuse. This information can inform clinical practice and policy, and otherwise be used in health economic simulation models, designed to inform resource allocation decisions. PMID:24837584

Fitting and Modeling in the ASC Data Analysis Environment

NASA Astrophysics Data System (ADS)

Doe, S.; Siemiginowska, A.; Joye, W.; McDowell, J.

As part of the AXAF Science Center (ASC) Data Analysis Environment, we will provide to the astronomical community a Fitting Application. We present a design of the application in this paper. Our design goal is to give the user the flexibility to use a variety of optimization techniques (Levenberg-Marquardt, maximum entropy, Monte Carlo, Powell, downhill simplex, CERN-Minuit, and simulated annealing) and fit statistics (chi (2) , Cash, variance, and maximum likelihood); our modular design allows the user easily to add their own optimization techniques and/or fit statistics. We also present a comparison of the optimization techniques to be provided by the Application. The high spatial and spectral resolutions that will be obtained with AXAF instruments require a sophisticated data modeling capability. We will provide not only a suite of astronomical spatial and spectral source models, but also the capability of combining these models into source models of up to four data dimensions (i.e., into source functions f(E,x,y,t)). We will also provide tools to create instrument response models appropriate for each observation.

A goodness-of-fit test for occupancy models with correlated within-season revisits

USGS Publications Warehouse

Wright, Wilson; Irvine, Kathryn M.; Rodhouse, Thomas J.

2016-01-01

Occupancy modeling is important for exploring species distribution patterns and for conservation monitoring. Within this framework, explicit attention is given to species detection probabilities estimated from replicate surveys to sample units. A central assumption is that replicate surveys are independent Bernoulli trials, but this assumption becomes untenable when ecologists serially deploy remote cameras and acoustic recording devices over days and weeks to survey rare and elusive animals. Proposed solutions involve modifying the detection-level component of the model (e.g., first-order Markov covariate). Evaluating whether a model sufficiently accounts for correlation is imperative, but clear guidance for practitioners is lacking. Currently, an omnibus goodnessof- fit test using a chi-square discrepancy measure on unique detection histories is available for occupancy models (MacKenzie and Bailey, Journal of Agricultural, Biological, and Environmental Statistics, 9, 2004, 300; hereafter, MacKenzie– Bailey test). We propose a join count summary measure adapted from spatial statistics to directly assess correlation after fitting a model. We motivate our work with a dataset of multinight bat call recordings from a pilot study for the North American Bat Monitoring Program. We found in simulations that our join count test was more reliable than the MacKenzie–Bailey test for detecting inadequacy of a model that assumed independence, particularly when serial correlation was low to moderate. A model that included a Markov-structured detection-level covariate produced unbiased occupancy estimates except in the presence of strong serial correlation and a revisit design consisting only of temporal replicates. When applied to two common bat species, our approach illustrates that sophisticated models do not guarantee adequate fit to real data, underscoring the importance of model assessment. Our join count test provides a widely applicable goodness-of-fit test and specifically evaluates occupancy model lack of fit related to correlation among detections within a sample unit. Our diagnostic tool is available for practitioners that serially deploy survey equipment as a way to achieve cost savings.

Spatio-temporal modelling of rainfall in the Murray-Darling Basin

NASA Astrophysics Data System (ADS)

Nowak, Gen; Welsh, A. H.; O'Neill, T. J.; Feng, Lingbing

2018-02-01

The Murray-Darling Basin (MDB) is a large geographical region in southeastern Australia that contains many rivers and creeks, including Australia's three longest rivers, the Murray, the Murrumbidgee and the Darling. Understanding rainfall patterns in the MDB is very important due to the significant impact major events such as droughts and floods have on agricultural and resource productivity. We propose a model for modelling a set of monthly rainfall data obtained from stations in the MDB and for producing predictions in both the spatial and temporal dimensions. The model is a hierarchical spatio-temporal model fitted to geographical data that utilises both deterministic and data-derived components. Specifically, rainfall data at a given location are modelled as a linear combination of these deterministic and data-derived components. A key advantage of the model is that it is fitted in a step-by-step fashion, enabling appropriate empirical choices to be made at each step.

Description Of Scoliotic Deformity Pattern By Harmonic Functions

NASA Astrophysics Data System (ADS)

Drerup, Burkhard; Hierholzer, Eberhard

1989-04-01

Frontal radiographs of scoliotic deformity of the spine reveal a characteristic pattern of lateral deviation, lateral tilt and axial rotation of vertebrae. In order to study interrelations between deformation parameters 478 radiographs of idiopathic scolioses, 23 of scolioses after Wilms-tumor treatment and 18 of scolioses following poliomyelitis were digitized. From these the curves of lateral deviation, tilt and rotation are calculated and fitted by Fourier series. By restriction to the first harmonic, analysis reduces to the analysis of a single phase and amplitude for each curve. Justification of this simplification will be discussed. Results provide a general geometric description of scoliotic deformity.

Using Gamma and Quantile Regressions to Explore the Association between Job Strain and Adiposity in the ELSA-Brasil Study: Does Gender Matter?

PubMed

Fonseca, Maria de Jesus Mendes da; Juvanhol, Leidjaira Lopes; Rotenberg, Lúcia; Nobre, Aline Araújo; Griep, Rosane Härter; Alves, Márcia Guimarães de Mello; Cardoso, Letícia de Oliveira; Giatti, Luana; Nunes, Maria Angélica; Aquino, Estela M L; Chor, Dóra

2017-11-17

This paper explores the association between job strain and adiposity, using two statistical analysis approaches and considering the role of gender. The research evaluated 11,960 active baseline participants (2008-2010) in the ELSA-Brasil study. Job strain was evaluated through a demand-control questionnaire, while body mass index (BMI) and waist circumference (WC) were evaluated in continuous form. The associations were estimated using gamma regression models with an identity link function. Quantile regression models were also estimated from the final set of co-variables established by gamma regression. The relationship that was found varied by analytical approach and gender. Among the women, no association was observed between job strain and adiposity in the fitted gamma models. In the quantile models, a pattern of increasing effects of high strain was observed at higher BMI and WC distribution quantiles. Among the men, high strain was associated with adiposity in the gamma regression models. However, when quantile regression was used, that association was found not to be homogeneous across outcome distributions. In addition, in the quantile models an association was observed between active jobs and BMI. Our results point to an association between job strain and adiposity, which follows a heterogeneous pattern. Modelling strategies can produce different results and should, accordingly, be used to complement one another.

Fixed versus mixed RSA: Explaining visual representations by fixed and mixed feature sets from shallow and deep computational models.

PubMed

Khaligh-Razavi, Seyed-Mahdi; Henriksson, Linda; Kay, Kendrick; Kriegeskorte, Nikolaus

2017-02-01

Studies of the primate visual system have begun to test a wide range of complex computational object-vision models. Realistic models have many parameters, which in practice cannot be fitted using the limited amounts of brain-activity data typically available. Task performance optimization (e.g. using backpropagation to train neural networks) provides major constraints for fitting parameters and discovering nonlinear representational features appropriate for the task (e.g. object classification). Model representations can be compared to brain representations in terms of the representational dissimilarities they predict for an image set. This method, called representational similarity analysis (RSA), enables us to test the representational feature space as is (fixed RSA) or to fit a linear transformation that mixes the nonlinear model features so as to best explain a cortical area's representational space (mixed RSA). Like voxel/population-receptive-field modelling, mixed RSA uses a training set (different stimuli) to fit one weight per model feature and response channel (voxels here), so as to best predict the response profile across images for each response channel. We analysed response patterns elicited by natural images, which were measured with functional magnetic resonance imaging (fMRI). We found that early visual areas were best accounted for by shallow models, such as a Gabor wavelet pyramid (GWP). The GWP model performed similarly with and without mixing, suggesting that the original features already approximated the representational space, obviating the need for mixing. However, a higher ventral-stream visual representation (lateral occipital region) was best explained by the higher layers of a deep convolutional network and mixing of its feature set was essential for this model to explain the representation. We suspect that mixing was essential because the convolutional network had been trained to discriminate a set of 1000 categories, whose frequencies in the training set did not match their frequencies in natural experience or their behavioural importance. The latter factors might determine the representational prominence of semantic dimensions in higher-level ventral-stream areas. Our results demonstrate the benefits of testing both the specific representational hypothesis expressed by a model's original feature space and the hypothesis space generated by linear transformations of that feature space.

When growth models are not universal: evidence from marine invertebrates

PubMed Central

Hirst, Andrew G.; Forster, Jack

2013-01-01

The accumulation of body mass, as growth, is fundamental to all organisms. Being able to understand which model(s) best describe this growth trajectory, both empirically and ultimately mechanistically, is an important challenge. A variety of equations have been proposed to describe growth during ontogeny. Recently, the West Brown Enquist (WBE) equation, formulated as part of the metabolic theory of ecology, has been proposed as a universal model of growth. This equation has the advantage of having a biological basis, but its ability to describe invertebrate growth patterns has not been well tested against other, more simple models. In this study, we collected data for 58 species of marine invertebrate from 15 different taxa. The data were fitted to three growth models (power, exponential and WBE), and their abilities were examined using an information theoretic approach. Using Akaike information criteria, we found changes in mass through time to fit an exponential equation form best (in approx. 73% of cases). The WBE model predominantly overestimates body size in early ontogeny and underestimates it in later ontogeny; it was the best fit in approximately 14% of cases. The exponential model described growth well in nine taxa, whereas the WBE described growth well in one of the 15 taxa, the Amphipoda. Although the WBE has the advantage of being developed with an underlying proximate mechanism, it provides a poor fit to the majority of marine invertebrates examined here, including species with determinate and indeterminate growth types. In the original formulation of the WBE model, it was tested almost exclusively against vertebrates, to which it fitted well; the model does not however appear to be universal given its poor ability to describe growth in benthic or pelagic marine invertebrates. PMID:23945691

Developmental Inter-Relationships Among Concrete Operational Tasks: An Investigation of Piaget's Stage Concept

ERIC Educational Resources Information Center

Jamison, Wesley

1977-01-01

Two models of intertask relations, Wohlwill's divergent-decalage and reciprocal-interaction patterns, were evaluated for their fit to cross-classification tables which showed the joint classification of 101 children's performance on all possible pairs of eight concrete operational tasks. (SB)

Gender differences in depressive symptom profiles and patterns of psychotropic drug usage in Asian patients with depression: Findings from the Research on Asian Psychotropic Prescription Patterns for Antidepressants study.

PubMed

Park, Seon-Cheol; Lee, Min-Soo; Shinfuku, Naotaka; Sartorius, Norman; Park, Yong Chon

2015-09-01

The purpose of this study was to investigate whether there were gender-specific depressive symptom profiles or gender-specific patterns of psychotropic agent usage in Asian patients with depression. Clinical data from the Research on Asian Psychotropic Prescription Patterns for Antidepressant study (1171 depressed patients) were used to determine gender differences by analysis of covariates for continuous variables and by logistic regression analysis for discrete variables. In addition, a binary logistic regression model was fitted to identify independent clinical correlates of the gender-specific pattern on psychotropic drug usage. Men were more likely than women to have loss of interest (adjusted odds ratio = 1.379, p = 0.009), fatigue (adjusted odds ratio = 1.298, p = 0.033) and concurrent substance abuse (adjusted odds ratio = 3.793, p = 0.008), but gender differences in other symptom profiles and clinical features were not significant. Men were also more likely than women to be prescribed adjunctive therapy with a second-generation antipsychotic (adjusted odds ratio = 1.320, p = 0.044). However, men were less likely than women to have suicidal thoughts/acts (adjusted odds ratio = 0.724, p = 0.028). Binary logistic regression models revealed that lower age (odds ratio = 0.986, p = 0.027) and current hospitalization (odds ratio = 3.348, p < 0.0001) were independent clinical correlates of use of second-generation antipsychotics as adjunctive therapy for treating depressed Asian men. Unique gender-specific symptom profiles and gender-specific patterns of psychotropic drug usage can be identified in Asian patients with depression. Hence, ethnic and cultural influences on the gender preponderance of depression should be considered in the clinical psychiatry of Asian patients. © The Royal Australian and New Zealand College of Psychiatrists 2015.

Unusual Configurations of Personality Traits Indicate Multiple Patterns of Their Coalescence

PubMed Central

Allik, Jüri; Hřebíčková, Martina; Realo, Anu

2018-01-01

It is widely accepted that the Five Factor Model (FFM) is a satisfactory description of the pattern of covariations among personality traits, which supposedly fits, more or less adequately, every individual. As an amendment to the FFM, we propose that the customary five-factor structure is only a near-universal, because it does not fit all individuals but only a large majority of them. Evidences reveal a small minority of participants who have an unusual configuration of personality traits, which is clearly recognizable, both in self- and observer-ratings. We identified three types of atypical configurations of personality traits, characterized mainly by a scatter of subscale scores within each of the FFM factors. How different configurations of personality traits are formed, persist, and function needs further investigation. PMID:29515499

Tree Height and DBH Growth Model Establishment of Main Tree Species in Wuling Mountain Small Watershed

NASA Astrophysics Data System (ADS)

Luo, Jia; Zhang, Min; Zhou, Xiaoling; Chen, Jianhua; Tian, Yuxin

2018-01-01

Taken 4 main tree species in the Wuling mountain small watershed as research objects, 57 typical sample plots were set up according to the stand type, site conditions and community structure. 311 goal diameter-class sample trees were selected according to diameter-class groups of different tree-height grades, and the optimal fitting models of tree height and DBH growth of main tree species were obtained by stem analysis using Richard, Logistic, Korf, Mitscherlich, Schumacher, Weibull theoretical growth equations, and the correlation coefficient of all optimal fitting models reached above 0.9. Through the evaluation and test, the optimal fitting models possessed rather good fitting precision and forecast dependability.

Corynebacterium glutamicum MTCC 2745 immobilized on granular activated carbon/MnFe2O4 composite: A novel biosorbent for removal of As(III) and As(V) ions.

PubMed

Podder, M S; Majumder, C B

2016-11-05

The optimization of biosorption/bioaccumulation process of both As(III) and As(V) has been investigated by using the biosorbent; biofilm of Corynebacterium glutamicum MTCC 2745 supported on granular activated carbon/MnFe2O4 composite (MGAC). The presence of functional groups on the cell wall surface of the biomass that may interact with the metal ions was proved by FT-IR. To determine the most appropriate correlation for the equilibrium curves employing the procedure of the non-linear regression for curve fitting analysis, isotherm studies were performed for As(III) and As(V) using 30 isotherm models. The pattern of biosorption/bioaccumulation fitted well with Vieth-Sladek isotherm model for As(III) and Brouers-Sotolongo and Fritz-Schlunder-V isotherm models for As(V). The maximum biosorption/bioaccumulation capacity estimated using Langmuir model were 2584.668mg/g for As(III) and 2651.675mg/g for As(V) at 30°C temperature and 220min contact time. The results showed that As(III) and As(V) removal was strongly pH-dependent with an optimum pH value of 7.0. D-R isotherm studies specified that ion exchange might play a prominent role. Copyright © 2016 Elsevier B.V. All rights reserved.

Factor Structure of the Hare Psychopathy Checklist: Youth Version in German Female and Male Detainees and Community Adolescents

ERIC Educational Resources Information Center

Sevecke, Kathrin; Pukrop, Ralf; Kosson, David S.; Krischer, Maya K.

2009-01-01

Substantial evidence exists for 3- and 4-factor models of psychopathy underlying patterns of covariation among the items of the Psychopathy Checklist-Revised (PCL-R) in diverse adult samples. Although initial studies conducted with the Psychopathy Checklist: Youth Version (PCL:YV) indicated reasonable fit for these models in incarcerated male…

Model-independent partial wave analysis using a massively-parallel fitting framework

NASA Astrophysics Data System (ADS)

Sun, L.; Aoude, R.; dos Reis, A. C.; Sokoloff, M.

2017-10-01

The functionality of GooFit, a GPU-friendly framework for doing maximum-likelihood fits, has been extended to extract model-independent {\\mathscr{S}}-wave amplitudes in three-body decays such as D + → h + h + h -. A full amplitude analysis is done where the magnitudes and phases of the {\\mathscr{S}}-wave amplitudes are anchored at a finite number of m 2(h + h -) control points, and a cubic spline is used to interpolate between these points. The amplitudes for {\\mathscr{P}}-wave and {\\mathscr{D}}-wave intermediate states are modeled as spin-dependent Breit-Wigner resonances. GooFit uses the Thrust library, with a CUDA backend for NVIDIA GPUs and an OpenMP backend for threads with conventional CPUs. Performance on a variety of platforms is compared. Executing on systems with GPUs is typically a few hundred times faster than executing the same algorithm on a single CPU.

Using integrated models to minimize environmentally induced wavefront error in optomechanical design and analysis

NASA Astrophysics Data System (ADS)

Genberg, Victor L.; Michels, Gregory J.

2017-08-01

The ultimate design goal of an optical system subjected to dynamic loads is to minimize system level wavefront error (WFE). In random response analysis, system WFE is difficult to predict from finite element results due to the loss of phase information. In the past, the use of ystem WFE was limited by the difficulty of obtaining a linear optics model. In this paper, an automated method for determining system level WFE using a linear optics model is presented. An error estimate is included in the analysis output based on fitting errors of mode shapes. The technique is demonstrated by example with SigFit, a commercially available tool integrating mechanical analysis with optical analysis.

Evaluating abundance and trends in a Hawaiian avian community using state-space analysis

USGS Publications Warehouse

Camp, Richard J.; Brinck, Kevin W.; Gorresen, P.M.; Paxton, Eben H.

2016-01-01

Estimating population abundances and patterns of change over time are important in both ecology and conservation. Trend assessment typically entails fitting a regression to a time series of abundances to estimate population trajectory. However, changes in abundance estimates from year-to-year across time are due to both true variation in population size (process variation) and variation due to imperfect sampling and model fit. State-space models are a relatively new method that can be used to partition the error components and quantify trends based only on process variation. We compare a state-space modelling approach with a more traditional linear regression approach to assess trends in uncorrected raw counts and detection-corrected abundance estimates of forest birds at Hakalau Forest National Wildlife Refuge, Hawai‘i. Most species demonstrated similar trends using either method. In general, evidence for trends using state-space models was less strong than for linear regression, as measured by estimates of precision. However, while the state-space models may sacrifice precision, the expectation is that these estimates provide a better representation of the real world biological processes of interest because they are partitioning process variation (environmental and demographic variation) and observation variation (sampling and model variation). The state-space approach also provides annual estimates of abundance which can be used by managers to set conservation strategies, and can be linked to factors that vary by year, such as climate, to better understand processes that drive population trends.

Model Performance Evaluation and Scenario Analysis (MPESA) Tutorial

EPA Science Inventory

This tool consists of two parts: model performance evaluation and scenario analysis (MPESA). The model performance evaluation consists of two components: model performance evaluation metrics and model diagnostics. These metrics provides modelers with statistical goodness-of-fit m...

Marginal and internal fit of pressed lithium disilicate inlays fabricated with milling, 3D printing, and conventional technologies.

PubMed

Homsy, Foudda R; Özcan, Mutlu; Khoury, Marwan; Majzoub, Zeina A K

2018-05-01

The subtractive and additive computer-aided design and computer-aided manufacturing (CAD-CAM) of lithium disilicate partial coverage restorations is poorly documented. The purpose of this in vitro study was to compare the marginal and internal fit accuracy of lithium disilicate glass-ceramic inlays fabricated with conventional, milled, and 3-dimensional (3D) printed wax patterns. A dentoform mandibular first molar was prepared for a mesio-occlusal ceramic inlay. Five groups of 15 inlays were obtained through conventional impression and manual wax pattern (group CICW); conventional impression, laboratory scanning of the stone die, CAD-CAM milled wax blanks (group CIDW) or 3D printed wax patterns (group CI3DW); and scanning of the master preparation with intraoral scanner and CAD-CAM milled (group DSDW) or 3D printed wax patterns (group DS3DW). The same design was used to produce the wax patterns in the last 4 groups. The replica technique was used to measure marginal and internal adaptation by using stereomicroscopy. Mixed-model ANOVA was used to assess differences according to the groups and discrepancy location (α=.05). Group DSDW showed the smallest marginal discrepancy (24.3 μm) compared with those of groups CICW (45.1 μm), CIDW (33.7 μm), CI3DW (39.8 μm), and DS3DW (39.7 μm) (P<.001). No statistically significant differences were detected among groups CICW, CIDW, CI3DW, and DS3DW relative to the marginal discrepancy. The internal discrepancy was significantly larger than the marginal discrepancy within all groups (P<.001). Lithium disilicate glass-ceramic inlays produced from digital scans and subtractive milling of wax patterns resulted in better marginal and internal fit accuracy than either conventional impression/fabrication or additive 3D manufacturing. Three-dimensional printed wax patterns yielded fit values similar to those of the conventionally waxed inlays. Copyright © 2017 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

Applicability of TOPMODEL in the mountainous catchments in the upper Nysa Kłodzka river basin (SW Poland)

NASA Astrophysics Data System (ADS)

Jeziorska, Justyna; Niedzielski, Tomasz

2018-03-01

River basins located in the Central Sudetes (SW Poland) demonstrate a high vulnerability to flooding. Four mountainous basins and the corresponding outlets have been chosen for modeling the streamflow dynamics using TOPMODEL, a physically based semi-distributed topohydrological model. The model has been calibrated using the Monte Carlo approach—with discharge, rainfall, and evapotranspiration data used to estimate the parameters. The overall performance of the model was judged by interpreting the efficiency measures. TOPMODEL was able to reproduce the main pattern of the hydrograph with acceptable accuracy for two of the investigated catchments. However, it failed to simulate the hydrological response in the remaining two catchments. The best performing data set obtained Nash-Sutcliffe efficiency of 0.78. This data set was chosen to conduct a detailed analysis aiming to estimate the optimal timespan of input data for which TOPMODEL performs best. The best fit was attained for the half-year time span. The model was validated and found to reveal good skills.

Gene Circuit Analysis of the Terminal Gap Gene huckebein

PubMed Central

Ashyraliyev, Maksat; Siggens, Ken; Janssens, Hilde; Blom, Joke; Akam, Michael; Jaeger, Johannes

2009-01-01

The early embryo of Drosophila melanogaster provides a powerful model system to study the role of genes in pattern formation. The gap gene network constitutes the first zygotic regulatory tier in the hierarchy of the segmentation genes involved in specifying the position of body segments. Here, we use an integrative, systems-level approach to investigate the regulatory effect of the terminal gap gene huckebein (hkb) on gap gene expression. We present quantitative expression data for the Hkb protein, which enable us to include hkb in gap gene circuit models. Gap gene circuits are mathematical models of gene networks used as computational tools to extract regulatory information from spatial expression data. This is achieved by fitting the model to gap gene expression patterns, in order to obtain estimates for regulatory parameters which predict a specific network topology. We show how considering variability in the data combined with analysis of parameter determinability significantly improves the biological relevance and consistency of the approach. Our models are in agreement with earlier results, which they extend in two important respects: First, we show that Hkb is involved in the regulation of the posterior hunchback (hb) domain, but does not have any other essential function. Specifically, Hkb is required for the anterior shift in the posterior border of this domain, which is now reproduced correctly in our models. Second, gap gene circuits presented here are able to reproduce mutants of terminal gap genes, while previously published models were unable to reproduce any null mutants correctly. As a consequence, our models now capture the expression dynamics of all posterior gap genes and some variational properties of the system correctly. This is an important step towards a better, quantitative understanding of the developmental and evolutionary dynamics of the gap gene network. PMID:19876378

Gene circuit analysis of the terminal gap gene huckebein.

PubMed

Ashyraliyev, Maksat; Siggens, Ken; Janssens, Hilde; Blom, Joke; Akam, Michael; Jaeger, Johannes

2009-10-01

The early embryo of Drosophila melanogaster provides a powerful model system to study the role of genes in pattern formation. The gap gene network constitutes the first zygotic regulatory tier in the hierarchy of the segmentation genes involved in specifying the position of body segments. Here, we use an integrative, systems-level approach to investigate the regulatory effect of the terminal gap gene huckebein (hkb) on gap gene expression. We present quantitative expression data for the Hkb protein, which enable us to include hkb in gap gene circuit models. Gap gene circuits are mathematical models of gene networks used as computational tools to extract regulatory information from spatial expression data. This is achieved by fitting the model to gap gene expression patterns, in order to obtain estimates for regulatory parameters which predict a specific network topology. We show how considering variability in the data combined with analysis of parameter determinability significantly improves the biological relevance and consistency of the approach. Our models are in agreement with earlier results, which they extend in two important respects: First, we show that Hkb is involved in the regulation of the posterior hunchback (hb) domain, but does not have any other essential function. Specifically, Hkb is required for the anterior shift in the posterior border of this domain, which is now reproduced correctly in our models. Second, gap gene circuits presented here are able to reproduce mutants of terminal gap genes, while previously published models were unable to reproduce any null mutants correctly. As a consequence, our models now capture the expression dynamics of all posterior gap genes and some variational properties of the system correctly. This is an important step towards a better, quantitative understanding of the developmental and evolutionary dynamics of the gap gene network.

Combined approaches to flexible fitting and assessment in virus capsids undergoing conformational change☆

PubMed Central

Pandurangan, Arun Prasad; Shakeel, Shabih; Butcher, Sarah Jane; Topf, Maya

2014-01-01

Fitting of atomic components into electron cryo-microscopy (cryoEM) density maps is routinely used to understand the structure and function of macromolecular machines. Many fitting methods have been developed, but a standard protocol for successful fitting and assessment of fitted models has yet to be agreed upon among the experts in the field. Here, we created and tested a protocol that highlights important issues related to homology modelling, density map segmentation, rigid and flexible fitting, as well as the assessment of fits. As part of it, we use two different flexible fitting methods (Flex-EM and iMODfit) and demonstrate how combining the analysis of multiple fits and model assessment could result in an improved model. The protocol is applied to the case of the mature and empty capsids of Coxsackievirus A7 (CAV7) by flexibly fitting homology models into the corresponding cryoEM density maps at 8.2 and 6.1 Å resolution. As a result, and due to the improved homology models (derived from recently solved crystal structures of a close homolog – EV71 capsid – in mature and empty forms), the final models present an improvement over previously published models. In close agreement with the capsid expansion observed in the EV71 structures, the new CAV7 models reveal that the expansion is accompanied by ∼5° counterclockwise rotation of the asymmetric unit, predominantly contributed by the capsid protein VP1. The protocol could be applied not only to viral capsids but also to many other complexes characterised by a combination of atomic structure modelling and cryoEM density fitting. PMID:24333899

Analysis of the DFP/AFCS Systems for Compensating Gravity Distortions on the 70-Meter Antenna

NASA Technical Reports Server (NTRS)

Imbriale, William A.; Hoppe, Daniel J.; Rochblatt, David

2000-01-01

This paper presents the theoretical computations showing the expected performances for both systems. The basic analysis tool is a Physical Optics reflector analysis code that was ported to a parallel computer for faster execution times. There are several steps involved in computing the RF performance of the various systems. 1 . A model of the RF distortions of the main reflector is required. This model is based upon measured holography maps of the 70-meter antenna obtained at 3 elevation angles. The holography maps are then processed (using an appropriate gravity mechanical model of the dish) to provide surface distortion maps at all elevation angles. 2. From the surface distortion maps, ray optics is used to determine the theoretical shape of the DFP that will exactly phase compensate the distortions. 3. From the theoretical shape and a NASTRAN mechanical model of the plate, the actuator positions that generate a surface that provides the best RMS fit to the theoretical model are selected. Using the actuator positions and the NASTRAN model provides an accurate description of the actual mirror shape. 4. Starting from the mechanical drawings of the feed, a computed RF feed pattern is generated. This pattern is expanded into a set of spherical wave modes so that a complete near field analysis of the reflector system can be obtained. 5. For the array feed, the excitation coefficients that provide the maximum gain are computed using a phase conjugate technique. The basic experimental geometry consisted of a dual shaped 70-meter antenna system; a refocusing ellipse, a DFP and an array feed system. To provide physical insight to the systems performance, focal plane field plots are presented at several elevations. Curves of predicted performance are shown for the DFP system, monopulse tracking system, AFCS and combined DFP/AFCS system. The calculated results show that the combined DFP/AFCS system is capable of recovering the majority of the gain lost due to gravity distortion.

A Complex Story: Universal Preference vs. Individual Differences Shaping Aesthetic Response to Fractals Patterns.

PubMed

Street, Nichola; Forsythe, Alexandra M; Reilly, Ronan; Taylor, Richard; Helmy, Mai S

2016-01-01

Fractal patterns offer one way to represent the rough complexity of the natural world. Whilst they dominate many of our visual experiences in nature, little large-scale perceptual research has been done to explore how we respond aesthetically to these patterns. Previous research (Taylor et al., 2011) suggests that the fractal patterns with mid-range fractal dimensions (FDs) have universal aesthetic appeal. Perceptual and aesthetic responses to visual complexity have been more varied with findings suggesting both linear (Forsythe et al., 2011) and curvilinear (Berlyne, 1970) relationships. Individual differences have been found to account for many of the differences we see in aesthetic responses but some, such as culture, have received little attention within the fractal and complexity research fields. This two-study article aims to test preference responses to FD and visual complexity, using a large cohort (N = 443) of participants from around the world to allow universality claims to be tested. It explores the extent to which age, culture and gender can predict our preferences for fractally complex patterns. Following exploratory analysis that found strong correlations between FD and visual complexity, a series of linear mixed-effect models were implemented to explore if each of the individual variables could predict preference. The first tested a linear complexity model (likelihood of selecting the more complex image from the pair of images) and the second a mid-range FD model (likelihood of selecting an image within mid-range). Results show that individual differences can reliably predict preferences for complexity across culture, gender and age. However, in fitting with current findings the mid-range models show greater consistency in preference not mediated by gender, age or culture. This article supports the established theory that the mid-range fractal patterns appear to be a universal construct underlying preference but also highlights the fragility of universal claims by demonstrating individual differences in preference for the interrelated concept of visual complexity. This highlights a current stalemate in the field of empirical aesthetics.

Typology of club drug use among young adults recruited using time-space sampling

PubMed Central

Ramo, Danielle E.; Grov, Christian; Delucchi, Kevin; Kelly, Brian C.; Parsons, Jeffrey T.

2009-01-01

The present study examined patterns of recent club drug use among 400 young adults (18–29) recruited using time-space sampling in NYC. Subjects had used at least one of six club drugs (MDMA, Ketamine, GHB, Cocaine, Methamphetamine, and LSD) within the prior 3 months. We used latent class analysis (LCA) to estimate latent groups based on patterns of recent club drug use and examined differences in demographic and psychological variables by class. A 3-class model fit the data best. Patterns were: Primary cocaine users (42% of sample), Mainstream users (44% of sample), and Wide-range users (14% of sample). Those most likely to be Primary cocaine users were significantly less likely to be heterosexual males and had higher educational attainment than the other two classes. Those most likely to be Wide-range users were less likely to be heterosexual females, more likely to be gay/bisexual males, dependent on club drugs, had significantly greater drug and sexual sensation-seeking, and were more likely to use when experiencing physical discomfort or pleasant times with others compared to the other two groups. Findings highlight the utility of using person-centered approaches to understand patterns of substance use, as well as highlight several patterns of club drug use among young adults. PMID:19939585

Isochrone Fitting of Hubble Photometry in UV-Vis Bands

NASA Astrophysics Data System (ADS)

Barker, Hallie; Paust, Nathaniel

2017-01-01

We present the results of isochrone fitting of color-magnitude diagrams from Hubble Space Telescope Wide Field Camera 3 (WFC3) and Advanced Camera for Surveys (ACS) photometry of the globular clusters M13 and M80 in five bands from the ultraviolet to near infrared. Fits from both the Dartmouth Stellar Evolution Program (DSEP) and the PAdova and TRieste Stellar Evolution Code (PARSEC) are examined. Ages, extinctions, and distances are found from the isochrone fitting, and metallicities are confirmed. We conduct careful qualitative analysis on the inconsistencies of the fits across all of the color combinations possible with the five observed bands, and find that the (F606W-F814W) color generally produces very good fits, but that there are large discrepancies when the data is fit using colors including UV bands for both models. Finally, we directly compare the two models by performing isochrone-isochrone fitting, and find that the age in PARSEC is on average 1.5 Gyr younger than DSEP for similar-appearing models at the same metallicity, and that the two models become less discrepant at lower metallicities.

River catchment rainfall series analysis using additive Holt-Winters method

NASA Astrophysics Data System (ADS)

Puah, Yan Jun; Huang, Yuk Feng; Chua, Kuan Chin; Lee, Teang Shui

2016-03-01

Climate change is receiving more attention from researchers as the frequency of occurrence of severe natural disasters is getting higher. Tropical countries like Malaysia have no distinct four seasons; rainfall has become the popular parameter to assess climate change. Conventional ways that determine rainfall trends can only provide a general result in single direction for the whole study period. In this study, rainfall series were modelled using additive Holt-Winters method to examine the rainfall pattern in Langat River Basin, Malaysia. Nine homogeneous series of more than 25 years data and less than 10% missing data were selected. Goodness of fit of the forecasted models was measured. It was found that seasonal rainfall model forecasts are generally better than the monthly rainfall model forecasts. Three stations in the western region exhibited increasing trend. Rainfall in southern region showed fluctuation. Increasing trends were discovered at stations in the south-eastern region except the seasonal analysis at station 45253. Decreasing trend was found at station 2818110 in the east, while increasing trend was shown at station 44320 that represents the north-eastern region. The accuracies of both rainfall model forecasts were tested using the recorded data of years 2010-2012. Most of the forecasts are acceptable.

Ten years in the library: new data confirm paleontological patterns

NASA Technical Reports Server (NTRS)

Sepkoski, J. J. Jr; Sepkoski JJ, J. r. (Principal Investigator)

1993-01-01

A comparison is made between compilations of times of origination and extinction of fossil marine animal families published in 1982 and 1992. As a result of ten years of library research, half of the information in the compendia has changed: families have been added and deleted, low-resolution stratigraphic data been improved, and intervals of origination and extinction have been altered. Despite these changes, apparent macroevolutionary patterns for the entire marine fauna have remained constant. Diversity curves compiled from the two data bases are very similar, with a goodness-of-fit of 99%; the principal difference is that the 1992 curve averages 13% higher than the older curve. Both numbers and percentages of origination and extinction also match well, with fits ranging from 83% to 95%. All major events of radiation and extinction are identical. Therefore, errors in large paleontological data bases and arbitrariness of included taxa are not necessarily impediments to the analysis of pattern in the fossil record, so long as the data are sufficiently numerous.

The self-transcendence scale: an investigation of the factor structure among nursing home patients.

PubMed

Haugan, Gørill; Rannestad, Toril; Garåsen, Helge; Hammervold, Randi; Espnes, Geir Arild

2012-09-01

Self-transcendence, the ability to expand personal boundaries in multiple ways, has been found to provide well-being. The purpose of this study was to examine the dimensionality of the Norwegian version of the Self-Transcendence Scale, which comprises 15 items. Reed's empirical nursing theory of self-transcendence provided the theoretical framework; self-transcendence includes an interpersonal, intrapersonal, transpersonal, and temporal dimension. Cross-sectional data were obtained from a sample of 202 cognitively intact elderly patients in 44 Norwegian nursing homes. Exploratory factor analysis revealed two and four internally consistent dimensions of self-transcendence, explaining 35.3% (two factors) and 50.7% (four factors) of the variance, respectively. Confirmatory factor analysis indicated that the hypothesized two- and four-factor models fitted better than the one-factor model (cx (2), root mean square error of approximation, standardized root mean square residual, normed fit index, nonnormed fit index, comparative fit index, goodness-of-fit index, and adjusted goodness-of-fit index). The findings indicate self-transcendence as a multifactorial construct; at present, we conclude that the two-factor model might be the most accurate and reasonable measure of self-transcendence. This research generates insights in the application of the widely used Self-Transcendence Scale by investigating its psychometric properties by applying a confirmatory factor analysis. It also generates new research-questions on the associations between self-transcendence and well-being.

Identifying model error in metabolic flux analysis - a generalized least squares approach.

PubMed

Sokolenko, Stanislav; Quattrociocchi, Marco; Aucoin, Marc G

2016-09-13

The estimation of intracellular flux through traditional metabolic flux analysis (MFA) using an overdetermined system of equations is a well established practice in metabolic engineering. Despite the continued evolution of the methodology since its introduction, there has been little focus on validation and identification of poor model fit outside of identifying "gross measurement error". The growing complexity of metabolic models, which are increasingly generated from genome-level data, has necessitated robust validation that can directly assess model fit. In this work, MFA calculation is framed as a generalized least squares (GLS) problem, highlighting the applicability of the common t-test for model validation. To differentiate between measurement and model error, we simulate ideal flux profiles directly from the model, perturb them with estimated measurement error, and compare their validation to real data. Application of this strategy to an established Chinese Hamster Ovary (CHO) cell model shows how fluxes validated by traditional means may be largely non-significant due to a lack of model fit. With further simulation, we explore how t-test significance relates to calculation error and show that fluxes found to be non-significant have 2-4 fold larger error (if measurement uncertainty is in the 5-10 % range). The proposed validation method goes beyond traditional detection of "gross measurement error" to identify lack of fit between model and data. Although the focus of this work is on t-test validation and traditional MFA, the presented framework is readily applicable to other regression analysis methods and MFA formulations.

Visualisation of Lines of Best Fit

ERIC Educational Resources Information Center

Rudziewicz, Michael; Bossé, Michael J.; Marland, Eric S.; Rhoads, Gregory S.

2017-01-01

Humans possess a remarkable ability to recognise both simple patterns such as shapes and handwriting and very complex patterns such as faces and landscapes. To investigate one small aspect of human pattern recognition, in this study participants position lines of "best fit" to two-dimensional scatter plots of data. The study investigates…

MIA analysis of FPGA BPMs and beam optics at APS

NASA Astrophysics Data System (ADS)

Ji, Da-Heng; Wang, Chun-Xi; Qin, Qing

2012-11-01

Model independent analysis, which was developed for high precision and fast beam dynamics analysis, is a promising diagnostic tool for modern accelerators. We implemented a series of methods to analyze the turn-by-turn BPM data. Green's functions corresponding to the local transfer matrix elements R12 or R34 are extracted from BPM data and fitted with the model lattice using least-square fitting. Here, we report experimental results obtained from analyzing the transverse motion of a beam in the storage ring at the Advanced Photon Source. BPM gains and uncoupled optics parameters are successfully determined. Quadrupole strengths are adjusted for fitting but can not be uniquely determined in general due to an insufficient number of BPMs.

Sedentary patterns, physical activity and health-related physical fitness in youth: a cross-sectional study.

PubMed

Júdice, Pedro B; Silva, Analiza M; Berria, Juliane; Petroski, Edio L; Ekelund, Ulf; Sardinha, Luís B

2017-03-04

Strong evidence indicates that moderate-vigorous physical activity (MVPA) is positively associated with fitness in youth, independent of total sedentary-time. Sedentary-time appears negatively associated with fitness only when it replaces MVPA. However, whether different sedentary-patterns affect health-related fitness is unknown. The associations between MVPA and sedentary-patterns with physical fitness were examined in 2698 youths (1262 boys) aged 13.4 ± 2.28 years. Sedentary-time (counts · minute -1  < 100) and PA were objectively measured by accelerometry. Each break (≥100 counts · min -1  < 2295) in sedentary-time and the frequency of daily bouts in non-prolonged (<30 min) and prolonged (≥30 min) sedentary-time were determined. The FITNESSGRAM® test battery was used to assess fitness. A standardized fitness composite-score (z-score) was calculated by summing the individual z-scores of the five tests adjusted to age and sex. Positive associations between MVPA and fitness were observed in both boys (β = 0.013, 95% CI: 0.005; 0.021) and girls (β = 0.014, 95% CI: 0.006; 0.022), independent of sedentary-patterns. Modest associations were found for the breaks in sedentary-time with fitness (β = 0.026, 95% CI: 0.009; 0.042), independent of total sedentary-time and MVPA in boys. In girls, non-prolonged sedentary bouts were positively associated with fitness (β = 0.014, 95% CI: 0.003; 0.024), independent of total sedentary-time and MVPA. These results reinforce that, independent of the time and patterns of sedentary behavior, MVPA is consistently associated with fitness in youth. Modest and inconsistent associations were found for sedentary behaviors. Breaking-up sedentary-time in boys and non-prolonged sedentary bouts in girls were positively associated with fitness, independent of total sedentary-time and MVPA. In order to enhance youth's fitness, public health recommendations should primarily target MVPA, still, suggestion to reduce and break-up sedentary-time may also be considered.

The relationship between cost estimates reliability and BIM adoption: SEM analysis

NASA Astrophysics Data System (ADS)

Ismail, N. A. A.; Idris, N. H.; Ramli, H.; Rooshdi, R. R. Raja Muhammad; Sahamir, S. R.

2018-02-01

This paper presents the usage of Structural Equation Modelling (SEM) approach in analysing the effects of Building Information Modelling (BIM) technology adoption in improving the reliability of cost estimates. Based on the questionnaire survey results, SEM analysis using SPSS-AMOS application examined the relationships between BIM-improved information and cost estimates reliability factors, leading to BIM technology adoption. Six hypotheses were established prior to SEM analysis employing two types of SEM models, namely the Confirmatory Factor Analysis (CFA) model and full structural model. The SEM models were then validated through the assessment on their uni-dimensionality, validity, reliability, and fitness index, in line with the hypotheses tested. The final SEM model fit measures are: P-value=0.000, RMSEA=0.079<0.08, GFI=0.824, CFI=0.962>0.90, TLI=0.956>0.90, NFI=0.935>0.90 and ChiSq/df=2.259; indicating that the overall index values achieved the required level of model fitness. The model supports all the hypotheses evaluated, confirming that all relationship exists amongst the constructs are positive and significant. Ultimately, the analysis verified that most of the respondents foresee better understanding of project input information through BIM visualization, its reliable database and coordinated data, in developing more reliable cost estimates. They also perceive to accelerate their cost estimating task through BIM adoption.

Perceptron Genetic to Recognize Openning Strategy Ruy Lopez

NASA Astrophysics Data System (ADS)

Azmi, Zulfian; Mawengkang, Herman

2018-01-01

The application of Perceptron method is not effective for coding on hardware based systems because it is not real time learning. With Genetic algorithm approach in calculating and searching the best weight (fitness value) system will do learning only one iteration. And the results of this analysis were tested in the case of the introduction of the opening pattern of chess Ruy Lopez. The Analysis with Perceptron Model with Algorithm Approach Genetics from group Artificial Neural Network for open Ruy Lopez. The data is processed with base open chess, with step eight a position white Pion from end open chess. Using perceptron method have many input and one output process many weight and refraction until output equal goal. Data trained and test with software Matlab and system can recognize the chess opening Ruy Lopez or Not open Ruy Lopez with Real time.

GALFIT-CORSAIR: Implementing the Core-Sérsic Model Into GALFIT

NASA Astrophysics Data System (ADS)

Bonfini, Paolo

2014-10-01

We introduce GALFIT-CORSAIR: a publicly available, fully retro-compatible modification of the 2D fitting software GALFIT (v.3) which adds an implementation of the core-Sersic model. We demonstrate the software by fitting the images of NGC 5557 and NGC 5813, which have been previously identified as core-Sersic galaxies by their 1D radial light profiles. These two examples are representative of different dust obscuration conditions, and of bulge/disk decomposition. To perform the analysis, we obtained deep Hubble Legacy Archive (HLA) mosaics in the F555W filter (~V-band). We successfully reproduce the results of the previous 1D analysis, modulo the intrinsic differences between the 1D and the 2D fitting procedures. The code and the analysis procedure described here have been developed for the first coherent 2D analysis of a sample of core-Sersic galaxies, which will be presented in a forth-coming paper. As the 2D analysis provides better constraining on multi-component fitting, and is fully seeing-corrected, it will yield complementary constraints on the missing mass in depleted galaxy cores.

Location of coating defects and assessment of level of cathodic protection on underground pipelines using AC impedance, deterministic and non-deterministic models

NASA Astrophysics Data System (ADS)

Castaneda-Lopez, Homero

A methodology for detecting and locating defects or discontinuities on the outside covering of coated metal underground pipelines subjected to cathodic protection has been addressed. On the basis of wide range AC impedance signals for various frequencies applied to a steel-coated pipeline system and by measuring its corresponding transfer function under several laboratory simulation scenarios, a physical laboratory setup of an underground cathodic-protected, coated pipeline was built. This model included different variables and elements that exist under real conditions, such as soil resistivity, soil chemical composition, defect (holiday) location in the pipeline covering, defect area and geometry, and level of cathodic protection. The AC impedance data obtained under different working conditions were used to fit an electrical transmission line model. This model was then used as a tool to fit the impedance signal for different experimental conditions and to establish trends in the impedance behavior without the necessity of further experimental work. However, due to the chaotic nature of the transfer function response of this system under several conditions, it is believed that non-deterministic models based on pattern recognition algorithms are suitable for field condition analysis. A non-deterministic approach was used for experimental analysis by applying an artificial neural network (ANN) algorithm based on classification analysis capable of studying the pipeline system and differentiating the variables that can change impedance conditions. These variables include level of cathodic protection, location of discontinuities (holidays), and severity of corrosion. This work demonstrated a proof-of-concept for a well-known technique and a novel algorithm capable of classifying impedance data for experimental results to predict the exact location of the active holidays and defects on the buried pipelines. Laboratory findings from this procedure are promising, and efforts to develop it for field conditions should continue.

Detecting Growth Shape Misspecifications in Latent Growth Models: An Evaluation of Fit Indexes

ERIC Educational Resources Information Center

Leite, Walter L.; Stapleton, Laura M.

2011-01-01

In this study, the authors compared the likelihood ratio test and fit indexes for detection of misspecifications of growth shape in latent growth models through a simulation study and a graphical analysis. They found that the likelihood ratio test, MFI, and root mean square error of approximation performed best for detecting model misspecification…

IPMP Global Fit - A one-step direct data analysis tool for predictive microbiology.

PubMed

Huang, Lihan

2017-12-04

The objective of this work is to develop and validate a unified optimization algorithm for performing one-step global regression analysis of isothermal growth and survival curves for determination of kinetic parameters in predictive microbiology. The algorithm is incorporated with user-friendly graphical interfaces (GUIs) to develop a data analysis tool, the USDA IPMP-Global Fit. The GUIs are designed to guide the users to easily navigate through the data analysis process and properly select the initial parameters for different combinations of mathematical models. The software is developed for one-step kinetic analysis to directly construct tertiary models by minimizing the global error between the experimental observations and mathematical models. The current version of the software is specifically designed for constructing tertiary models with time and temperature as the independent model parameters in the package. The software is tested with a total of 9 different combinations of primary and secondary models for growth and survival of various microorganisms. The results of data analysis show that this software provides accurate estimates of kinetic parameters. In addition, it can be used to improve the experimental design and data collection for more accurate estimation of kinetic parameters. IPMP-Global Fit can be used in combination with the regular USDA-IPMP for solving the inverse problems and developing tertiary models in predictive microbiology. Published by Elsevier B.V.

A systematical rheological study of polysaccharide from Sophora alopecuroides L. seeds.

PubMed

Wu, Yan; Guo, Rui; Cao, Nannan; Sun, Xiangjun; Sui, Zhongquan; Guo, Qingbin

2018-01-15

The rheological properties of polysaccharide (SAP) from Sophora alopecuroides L. seeds were systematically investigated by fitting different models. The steady flow testing indicated that SAP exhibited shear-thinning behaviors, which were enhanced with increasing concentration and decreasing temperature. This was demonstrated quantitatively by Williamson and Arrhenius models. According to the generalized Morris equation, SAP exhibited random coil conformation with the potential to form weak gel-like network. On the other hand, multiple results of dynamic tests confirmed the viscoelastic properties of SAP, showing oscillatory behaviors between a dilute solution and an elastic gel. Furthermore, SAP solutions were thermorheologically stable without remarkable energetic interactions or structural heterogeneity, since their rheological patterns were successfully applied to Time-temperature superposition (TTS) principle, modified Cole-Cole analysis and Cox-Merz rule. Copyright © 2017 Elsevier Ltd. All rights reserved.

Self-organized pattern formation at organic-inorganic interfaces during deposition: Experiment versus modeling

NASA Astrophysics Data System (ADS)

Szillat, F.; Mayr, S. G.

2011-09-01

Self-organized pattern formation during physical vapor deposition of organic materials onto rough inorganic substrates is characterized by a complex morphological evolution as a function of film thickness. We employ a combined experimental-theoretical study using atomic force microscopy and numerically solved continuum rate equations to address morphological evolution in the model system: poly(bisphenol A carbonate) on polycrystalline Cu. As the key ingredients for pattern formation, (i) curvature and interface potential driven surface diffusion, (ii) deposition noise, and (iii) interface boundary effects are identified. Good agreement of experiments and theory, fitting only the Hamaker constant and diffusivity within narrow physical parameter windows, corroborates the underlying physics and paves the way for computer-assisted interface engineering.

Fluctuation-controlled front propagation

NASA Astrophysics Data System (ADS)

Ridgway, Douglas Thacher

1997-09-01

A number of fundamental pattern-forming systems are controlled by fluctuations at the front. These problems involve the interaction of an infinite dimensional probability distribution with a strongly nonlinear, spatially extended pattern-forming system. We have examined fluctuation-controlled growth in the context of the specific problems of diffusion-limited growth and biological evolution. Mean field theory of diffusion-limited growth exhibits a finite time singularity. Near the leading edge of a diffusion-limited front, this leads to acceleration and blowup. This may be resolved, in an ad hoc manner, by introducing a cutoff below which growth is weakened or eliminated (8). This model, referred to as the BLT model, captures a number of qualitative features of global pattern formation in diffusion-limited aggregation: contours of the mean field match contours of averaged particle density in simulation, and the modified mean field theory can form dendritic features not possible in the naive mean field theory. The morphology transition between dendritic and non-dendritic global patterns requires that BLT fronts have a Mullins-Sekerka instability of the wavefront shape, in order to form concave patterns. We compute the stability of BLT fronts numerically, and compare the results to fronts without a cutoff. A significant morphological instability of the BLT fronts exists, with a dominant wavenumber on the scale of the front width. For standard mean field fronts, no instability is found. The naive and ad hoc mean field theories are continuum-deterministic models intended to capture the behavior of a discrete stochastic system. A transformation which maps discrete systems into a continuum model with a singular multiplicative noise is known, however numerical simulations of the continuum stochastic system often give mean field behavior instead of the critical behavior of the discrete system. We have found a new interpretation of the singular noise, based on maintaining the symmetry of the absorbing state, but which is unsuccessful at capturing the behavior of diffusion-limited growth. In an effort to find a simpler model system, we turned to modelling fitness increases in evolution. The work was motivated by an experiment on vesicular stomatitis virus, a short (˜9600bp) single-stranded RNA virus. A highly bottlenecked viral population increases in fitness rapidly until a certain point, after which the fitness increases at a slower rate. This is well modeled by a constant population reproducing and mutating on a smooth fitness landscape. Mean field theory of this system displays the same infinite propagation velocity blowup as mean field diffusion-limited aggregation. However, we have been able to make progress on a number of fronts. One is solving systems of moment equations, where a hierarchy of moments is truncated arbitrarily at some level. Good results for front propagation velocity are found with just two moments, corresponding to inclusion of the basic finite population clustering effect ignored by mean field theory. In addition, for small mutation rates, most of the population will be entirely on a single site or two adjacent sites, and the density of these cases can be described and solved. (Abstract shortened by UMI.)

Modeling dust emission in the Magellanic Clouds with Spitzer and Herschel

NASA Astrophysics Data System (ADS)

Chastenet, Jérémy; Bot, Caroline; Gordon, Karl D.; Bocchio, Marco; Roman-Duval, Julia; Jones, Anthony P.; Ysard, Nathalie

2017-05-01

Context. Dust modeling is crucial to infer dust properties and budget for galaxy studies. However, there are systematic disparities between dust grain models that result in corresponding systematic differences in the inferred dust properties of galaxies. Quantifying these systematics requires a consistent fitting analysis. Aims: We compare the output dust parameters and assess the differences between two dust grain models, the DustEM model and THEMIS. In this study, we use a single fitting method applied to all the models to extract a coherent and unique statistical analysis. Methods: We fit the models to the dust emission seen by Spitzer and Herschel in the Small and Large Magellanic Clouds (SMC and LMC). The observations cover the infrared (IR) spectrum from a few microns to the sub-millimeter range. For each fitted pixel, we calculate the full n-D likelihood based on a previously described method. The free parameters are both environmental (U, the interstellar radiation field strength; αISRF, power-law coefficient for a multi-U environment; Ω∗, the starlight strength) and intrinsic to the model (YI: abundances of the grain species I; αsCM20, coefficient in the small carbon grain size distribution). Results: Fractional residuals of five different sets of parameters show that fitting THEMIS brings a more accurate reproduction of the observations than the DustEM model. However, independent variations of the dust species show strong model-dependencies. We find that the abundance of silicates can only be constrained to an upper-limit and that the silicate/carbon ratio is different than that seen in our Galaxy. In the LMC, our fits result in dust masses slightly lower than those found in the literature, by a factor lower than 2. In the SMC, we find dust masses in agreement with previous studies.

Reflection Patterns Generated by Condensed-Phase Oblique Detonation Interaction with a Rigid Wall

NASA Astrophysics Data System (ADS)

Short, Mark; Chiquete, Carlos; Bdzil, John; Meyer, Chad

2017-11-01

We examine numerically the wave reflection patterns generated by a detonation in a condensed phase explosive inclined obliquely but traveling parallel to a rigid wall as a function of incident angle. The problem is motivated by the characterization of detonation-material confiner interactions. We compare the reflection patterns for two detonation models, one where the reaction zone is spatially distributed, and the other where the reaction is instantaneous (a Chapman-Jouguet detonation). For the Chapman-Jouguet model, we compare the results of the computations with an asymptotic study recently conducted by Bdzil and Short for small detonation incident angles. We show that the ability of a spatially distributed reaction energy release to turn flow streamlines has a significant impact on the nature of the observed reflection patterns. The computational approach uses a shock-fit methodology.

Development of Evaluation Indicators for Hospice and Palliative Care Professionals Training Programs in Korea.

PubMed

Kang, Jina; Park, Kyoung-Ok

2017-01-01

The importance of training for Hospice and Palliative Care (HPC) professionals has been increasing with the systemization of HPC in Korea. Hence, the need and importance of training quality for HPC professionals are growing. This study evaluated the construct validity and reliability of the Evaluation Indicators for standard Hospice and Palliative Care Training (EIHPCT) program. As a framework to develop evaluation indicators, an invented theoretical model combining Stufflebeam's CIPP (Context-Input-Process-Product) evaluation model with PRECEDE-PROCEED model was used. To verify the construct validity of the EIHPCT program, a structured survey was performed with 169 professionals who were the HPC training program administrators, trainers, and trainees. To examine the validity of the areas of the EIHPCT program, exploratory factor analysis and confirmatory factor analysis were conducted. First, in the exploratory factor analysis, the indicators with factor loadings above 0.4 were chosen as desirable items, and some cross-loaded items that loaded at 0.4 or higher on two or more factors were adjusted as the higher factor. Second, the model fit of the modified EIHPCT program was quite good in the confirmatory factor analysis (Goodness-of-Fit Index > 0.70, Comparative Fit Index > 0.80, Normed Fit Index > 0.80, Root Mean square of Residuals < 0.05). The modified model of the EIHPCT comprised 4 areas, 13 subdomains, and 61 indicators. The evaluation indicators of the modified model will be valuable references for improving the HPC professional training program.

Comparison of Approaches to the Prediction of Surface Wave Phase Velocity

NASA Astrophysics Data System (ADS)

Godfrey, K. E.; Dalton, C. A.; Hjorleifsdottir, V.; Ekstrom, G.

2017-12-01

Global seismic models provide crucial information about the state, composition, and dynamics of the Earth's interior, and in the shallow mantle these models are primarily constrained by observations of surface waves. Models developed by different groups have been constructed using different data sets and different techniques. While these models exhibit good agreement on the long-wavelength features, there is less consistency in the patterns and amplitude of smaller-scale heterogeneity. Here we investigate how approximations in the theoretical treatment of wave propagation and excitation influence the interpretation of measured phase delays and the tomographic images that result from inverting them. Synthetic seismograms were generated using SPECFEM3D_GLOBE for 42 earthquakes, 134 receiver locations, and two 3-D models of elastic Earth structure: S362ANI (Kustowski et al., 2008) and a rougher model constructed by adding realistic small-scale structure to S362ANI. Fundamental-mode Rayleigh and Love wave phase delays in the period range 35-250 seconds were measured using the approach of Ekström et al. (1997), for which PREM is the assumed reference Earth model. These measurements were compared to phase-delay predictions generated for the great-circle ray approximation, exact ray theory, and finite-frequency theory. We find that for both 3-D earth models exact ray theory provides the best fit to the measurements at short periods. At longer periods finite frequency theory provides the best fit. For the smooth earth model, the differences in fit for the various predictions are less significant at long periods than at shorter periods. The differences at long periods become more significant with increasing model roughness. In all cases, the agreement between predictions and measurements is best for paths located away from nodes in the source radiation pattern. The ability of the measured phase delays to recover the input Earth models is assessed through tests that explore the influence of parameterization, regularization, and crustal corrections.

Detection and correction of laser induced breakdown spectroscopy spectral background based on spline interpolation method

NASA Astrophysics Data System (ADS)

Tan, Bing; Huang, Min; Zhu, Qibing; Guo, Ya; Qin, Jianwei

2017-12-01

Laser-induced breakdown spectroscopy (LIBS) is an analytical technique that has gained increasing attention because of many applications. The production of continuous background in LIBS is inevitable because of factors associated with laser energy, gate width, time delay, and experimental environment. The continuous background significantly influences the analysis of the spectrum. Researchers have proposed several background correction methods, such as polynomial fitting, Lorenz fitting and model-free methods. However, less of them apply these methods in the field of LIBS Technology, particularly in qualitative and quantitative analyses. This study proposes a method based on spline interpolation for detecting and estimating the continuous background spectrum according to its smooth property characteristic. Experiment on the background correction simulation indicated that, the spline interpolation method acquired the largest signal-to-background ratio (SBR) over polynomial fitting, Lorenz fitting and model-free method after background correction. These background correction methods all acquire larger SBR values than that acquired before background correction (The SBR value before background correction is 10.0992, whereas the SBR values after background correction by spline interpolation, polynomial fitting, Lorentz fitting, and model-free methods are 26.9576, 24.6828, 18.9770, and 25.6273 respectively). After adding random noise with different kinds of signal-to-noise ratio to the spectrum, spline interpolation method acquires large SBR value, whereas polynomial fitting and model-free method obtain low SBR values. All of the background correction methods exhibit improved quantitative results of Cu than those acquired before background correction (The linear correlation coefficient value before background correction is 0.9776. Moreover, the linear correlation coefficient values after background correction using spline interpolation, polynomial fitting, Lorentz fitting, and model-free methods are 0.9998, 0.9915, 0.9895, and 0.9940 respectively). The proposed spline interpolation method exhibits better linear correlation and smaller error in the results of the quantitative analysis of Cu compared with polynomial fitting, Lorentz fitting and model-free methods, The simulation and quantitative experimental results show that the spline interpolation method can effectively detect and correct the continuous background.

Using the MWC model to describe heterotropic interactions in hemoglobin

PubMed Central

Rapp, Olga

2017-01-01

Hemoglobin is a classical model allosteric protein. Research on hemoglobin parallels the development of key cooperativity and allostery concepts, such as the ‘all-or-none’ Hill formalism, the stepwise Adair binding formulation and the concerted Monod-Wymann-Changuex (MWC) allosteric model. While it is clear that the MWC model adequately describes the cooperative binding of oxygen to hemoglobin, rationalizing the effects of H+, CO2 or organophosphate ligands on hemoglobin-oxygen saturation using the same model remains controversial. According to the MWC model, allosteric ligands exert their effect on protein function by modulating the quaternary conformational transition of the protein. However, data fitting analysis of hemoglobin oxygen saturation curves in the presence or absence of inhibitory ligands persistently revealed effects on both relative oxygen affinity (c) and conformational changes (L), elementary MWC parameters. The recent realization that data fitting analysis using the traditional MWC model equation may not provide reliable estimates for L and c thus calls for a re-examination of previous data using alternative fitting strategies. In the current manuscript, we present two simple strategies for obtaining reliable estimates for MWC mechanistic parameters of hemoglobin steady-state saturation curves in cases of both evolutionary and physiological variations. Our results suggest that the simple MWC model provides a reasonable description that can also account for heterotropic interactions in hemoglobin. The results, moreover, offer a general roadmap for successful data fitting analysis using the MWC model. PMID:28793329

Multi-scale comparison of source parameter estimation using empirical Green's function approach

NASA Astrophysics Data System (ADS)

Chen, X.; Cheng, Y.

2015-12-01

Analysis of earthquake source parameters requires correction of path effect, site response, and instrument responses. Empirical Green's function (EGF) method is one of the most effective methods in removing path effects and station responses by taking the spectral ratio between a larger and smaller event. Traditional EGF method requires identifying suitable event pairs, and analyze each event individually. This allows high quality estimations for strictly selected events, however, the quantity of resolvable source parameters is limited, which challenges the interpretation of spatial-temporal coherency. On the other hand, methods that exploit the redundancy of event-station pairs are proposed, which utilize the stacking technique to obtain systematic source parameter estimations for a large quantity of events at the same time. This allows us to examine large quantity of events systematically, facilitating analysis of spatial-temporal patterns, and scaling relationship. However, it is unclear how much resolution is scarified during this process. In addition to the empirical Green's function calculation, choice of model parameters and fitting methods also lead to biases. Here, using two regional focused arrays, the OBS array in the Mendocino region, and the borehole array in the Salton Sea geothermal field, I compare the results from the large scale stacking analysis, small-scale cluster analysis, and single event-pair analysis with different fitting methods to systematically compare the results within completely different tectonic environment, in order to quantify the consistency and inconsistency in source parameter estimations, and the associated problems.

Goodness-Of-Fit Test for Nonparametric Regression Models: Smoothing Spline ANOVA Models as Example.

PubMed

Teran Hidalgo, Sebastian J; Wu, Michael C; Engel, Stephanie M; Kosorok, Michael R

2018-06-01

Nonparametric regression models do not require the specification of the functional form between the outcome and the covariates. Despite their popularity, the amount of diagnostic statistics, in comparison to their parametric counter-parts, is small. We propose a goodness-of-fit test for nonparametric regression models with linear smoother form. In particular, we apply this testing framework to smoothing spline ANOVA models. The test can consider two sources of lack-of-fit: whether covariates that are not currently in the model need to be included, and whether the current model fits the data well. The proposed method derives estimated residuals from the model. Then, statistical dependence is assessed between the estimated residuals and the covariates using the HSIC. If dependence exists, the model does not capture all the variability in the outcome associated with the covariates, otherwise the model fits the data well. The bootstrap is used to obtain p-values. Application of the method is demonstrated with a neonatal mental development data analysis. We demonstrate correct type I error as well as power performance through simulations.

How do the effects of mutations add up?

NASA Astrophysics Data System (ADS)

Velenich, Andrea; Dai, Mingjie; Gore, Jeff

2011-03-01

Genetic mutations affect the fitness of any organism and provide the variability necessary for natural selection to occur. Given the fitness of a wild type organism and the fitness of mutants A and B which differ from the wild type by a single mutation, predicting the fitness of the double mutant AB is a fundamental problem with broad implications in many fields, from evolutionary theory to medicine. Analysis of millions of double gene knockouts in yeast reveals that, on average, the fitness of AB is the product of the fitness of A and the fitness of B. However, most pairs of mutations deviate from this mean behavior in a way that challenges existing theoretical models. We propose a natural generalization of the geometric Fisher's model which accommodates the experimentally observed features and allows us to characterize the fitness landscape of yeast.

Statistical aspects of modeling the labor curve.

PubMed

Zhang, Jun; Troendle, James; Grantz, Katherine L; Reddy, Uma M

2015-06-01

In a recent review by Cohen and Friedman, several statistical questions on modeling labor curves were raised. This article illustrates that asking data to fit a preconceived model or letting a sufficiently flexible model fit observed data is the main difference in principles of statistical modeling between the original Friedman curve and our average labor curve. An evidence-based approach to construct a labor curve and establish normal values should allow the statistical model to fit observed data. In addition, the presence of the deceleration phase in the active phase of an average labor curve was questioned. Forcing a deceleration phase to be part of the labor curve may have artificially raised the speed of progression in the active phase with a particularly large impact on earlier labor between 4 and 6 cm. Finally, any labor curve is illustrative and may not be instructive in managing labor because of variations in individual labor pattern and large errors in measuring cervical dilation. With the tools commonly available, it may be more productive to establish a new partogram that takes the physiology of labor and contemporary obstetric population into account. Copyright © 2015 Elsevier Inc. All rights reserved.

Sensitivity analysis of respiratory parameter uncertainties: impact of criterion function form and constraints.

PubMed

Lutchen, K R

1990-08-01

A sensitivity analysis based on weighted least-squares regression is presented to evaluate alternative methods for fitting lumped-parameter models to respiratory impedance data. The goal is to maintain parameter accuracy simultaneously with practical experiment design. The analysis focuses on predicting parameter uncertainties using a linearized approximation for joint confidence regions. Applications are with four-element parallel and viscoelastic models for 0.125- to 4-Hz data and a six-element model with separate tissue and airway properties for input and transfer impedance data from 2-64 Hz. The criterion function form was evaluated by comparing parameter uncertainties when data are fit as magnitude and phase, dynamic resistance and compliance, or real and imaginary parts of input impedance. The proper choice of weighting can make all three criterion variables comparable. For the six-element model, parameter uncertainties were predicted when both input impedance and transfer impedance are acquired and fit simultaneously. A fit to both data sets from 4 to 64 Hz could reduce parameter estimate uncertainties considerably from those achievable by fitting either alone. For the four-element models, use of an independent, but noisy, measure of static compliance was assessed as a constraint on model parameters. This may allow acceptable parameter uncertainties for a minimum frequency of 0.275-0.375 Hz rather than 0.125 Hz. This reduces data acquisition requirements from a 16- to a 5.33- to 8-s breath holding period. These results are approximations, and the impact of using the linearized approximation for the confidence regions is discussed.

Combinatorics of the Breakage-Fusion-Bridge Mechanism

PubMed Central

Bafna, Vineet

2012-01-01

Abstract The breakage-fusion-bridge (BFB) mechanism was proposed over seven decades ago and is a source of genomic variability and gene amplification in cancer. Here we formally model and analyze the BFB mechanism, to our knowledge the first time this has been undertaken. We show that BFB can be modeled as successive inverted prefix duplications of a string. Using this model, we show that BFB can achieve a surprisingly broad range of amplification patterns. We find that a sequence of BFB operations can be found that nearly fits most patterns of copy number increases along a chromosome. We conclude that this limits the usefulness of methods like array CGH for detecting BFB. PMID:22506505

MPTinR: analysis of multinomial processing tree models in R.

PubMed

Singmann, Henrik; Kellen, David

2013-06-01

We introduce MPTinR, a software package developed for the analysis of multinomial processing tree (MPT) models. MPT models represent a prominent class of cognitive measurement models for categorical data with applications in a wide variety of fields. MPTinR is the first software for the analysis of MPT models in the statistical programming language R, providing a modeling framework that is more flexible than standalone software packages. MPTinR also introduces important features such as (1) the ability to calculate the Fisher information approximation measure of model complexity for MPT models, (2) the ability to fit models for categorical data outside the MPT model class, such as signal detection models, (3) a function for model selection across a set of nested and nonnested candidate models (using several model selection indices), and (4) multicore fitting. MPTinR is available from the Comprehensive R Archive Network at http://cran.r-project.org/web/packages/MPTinR/ .

A mechanical model for deformable and mesh pattern wheel of lunar roving vehicle

NASA Astrophysics Data System (ADS)

Liang, Zhongchao; Wang, Yongfu; Chen, Gang (Sheng); Gao, Haibo

2015-12-01

As an indispensable tool for astronauts on lunar surface, the lunar roving vehicle (LRV) is of great significance for manned lunar exploration. An LRV moves on loose and soft lunar soil, so the mechanical property of its wheels directly affects the mobility performance. The wheels used for LRV have deformable and mesh pattern, therefore, the existing mechanical theory of vehicle wheel cannot be used directly for analyzing the property of LRV wheels. In this paper, a new mechanical model for LRV wheel is proposed. At first, a mechanical model for a rigid normal wheel is presented, which involves in multiple conventional parameters such as vertical load, tangential traction force, lateral force, and slip ratio. Secondly, six equivalent coefficients are introduced to amend the rigid normal wheel model to fit for the wheels with deformable and mesh-pattern in LRV application. Thirdly, the values of the six equivalent coefficients are identified by using experimental data obtained in an LRV's single wheel testing. Finally, the identified mechanical model for LRV's wheel with deformable and mesh pattern are further verified and validated by using additional experimental results.

The housing, geography, and mobility of Latin American urban poor: the prevailing model and the case of Quito, Ecuador.

PubMed

Klak, T; Holtzclaw, M

1993-01-01

In this study of the constraints of low-income migrants in securing decent housing in Quito, Ecuador (a rapidly growing city), there is a literature review of Latin American intraurban mobility and housing, the development of a theoretical model, and a bivariate analysis. John Turner's model of the three stages in the life cycle of migrants and the three concentric zones of urbanization provides the initial framework for examining Quito migration. Quito differs from other Third World and Latin American cities in that its origins are pre-Colombian, and physical barriers surround the city. Data were obtained from housing data collected independently in 1990 and 1991 and survey data on households living in 1000 inadequate housing units in 1989. 35.5% of Quito's population live in inadequate housing (poor building materials, poor construction, deterioration, or lack of basic services). Three concentric and elongated zones are constructed based on distance from the center city and periphery and are representative of shelter types (rented rooms, shanty, house, and apartment). Shelter improves with type of ownership status. The attitudes of local officials influences the proportion of the poor living in rental or self-help housing. 36% of Quito's low-income residents live in rented rooms, and 38% live in shanties and houses. Bridgeheaders (new migrants who are usually young single males) tend to live in rented rooms for under five years and to move over time to shanties and then houses. Colonial preservation in central Quito and landlords' incentives for encouraging migrants to stay in rental housing interferes with the third phase of the model. Mixed housing throughout the city fits the third phase. Local laws prevent squatters and self-help housing. Rented rooms are primarily in the central city. Occupant income increases with shifts from rented rooms, to shanties, to houses. Shelter, geographic, and mobility patterns that do not fit the model are identified. Urban circumstance may not be linear and evolutionary as predicted, but the pattern is not diverse enough to warrant abandoning the model. The recommendation is for a flexible model for adapting a universal model to local and global conditions.

HIV-1 Env C2-V4 Diversification in a Slow-Progressor Infant Reveals a Flat but Rugged Fitness Landscape

PubMed Central

Smith, S. Abigail; Wood, Charles; West, John T.

2013-01-01

Human immunodeficiency virus type-1 (HIV-1) fitness has been associated with virus entry, a process mediated by the envelope glycoprotein (Env). We previously described Env genetic diversification in a Zambian, subtype C infected, slow-progressor child (1157i) in parallel with an evolving neutralizing antibody response. Because of the role the Variable-3 loop (V3) plays in transmission, cell tropism, neutralization sensitivity, and fitness, longitudinally isolated 1157i C2-V4 alleles were cloned into HIV-1NL4-3-eGFP and -DsRed2 infectious molecular clones. The fluorescent reporters allowed for dual-infection competitions between all patient-derived C2-V4 chimeras to quantify the effect of V3 diversification and selection on fitness. ‘Winners’ and ‘losers’ were readily discriminated among the C2-V4 alleles. Exceptional sensitivity for detection of subtle fitness differences was revealed through analysis of two alleles differing in a single synonymous amino acid. However, when the outcomes of N = 33 competitions were averaged for each chimera, the aggregate analysis showed that despite increasing diversification and divergence with time, natural selection of C2-V4 sequences in this individual did not appear to be producing a ‘survival of the fittest’ evolutionary pattern. Rather, we detected a relatively flat fitness landscape consistent with mutational robustness. Fitness outcomes were then correlated with individual components of the entry process. Env incorporation into particles correlated best with fitness, suggesting a role for Env avidity, as opposed to receptor/coreceptor affinity, in defining fitness. Nevertheless, biochemical analyses did not identify any step in HIV-1 entry as a dominant determinant of fitness. Our results lead us to conclude that multiple aspects of entry contribute to maintaining adequate HIV-1 fitness, and there is no surrogate analysis for determining fitness. The capacity for subtle polymorphisms in Env to nevertheless significantly impact viral fitness suggests fitness is best defined by head-to-head competition. PMID:23638182

Forecasting the incidence of tuberculosis in China using the seasonal auto-regressive integrated moving average (SARIMA) model.

PubMed

Mao, Qiang; Zhang, Kai; Yan, Wu; Cheng, Chaonan

2018-05-02

The aims of this study were to develop a forecasting model for the incidence of tuberculosis (TB) and analyze the seasonality of infections in China; and to provide a useful tool for formulating intervention programs and allocating medical resources. Data for the monthly incidence of TB from January 2004 to December 2015 were obtained from the National Scientific Data Sharing Platform for Population and Health (China). The Box-Jenkins method was applied to fit a seasonal auto-regressive integrated moving average (SARIMA) model to forecast the incidence of TB over the subsequent six months. During the study period of 144 months, 12,321,559 TB cases were reported in China, with an average monthly incidence of 6.4426 per 100,000 of the population. The monthly incidence of TB showed a clear 12-month cycle, and a seasonality with two peaks occurring in January and March and a trough in December. The best-fit model was SARIMA (1,0,0)(0,1,1) 12 , which demonstrated adequate information extraction (white noise test, p>0.05). Based on the analysis, the incidence of TB from January to June 2016 were 6.6335, 4.7208, 5.8193, 5.5474, 5.2202 and 4.9156 per 100,000 of the population, respectively. According to the seasonal pattern of TB incidence in China, the SARIMA model was proposed as a useful tool for monitoring epidemics. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

CalFitter: a web server for analysis of protein thermal denaturation data.

PubMed

Mazurenko, Stanislav; Stourac, Jan; Kunka, Antonin; Nedeljkovic, Sava; Bednar, David; Prokop, Zbynek; Damborsky, Jiri

2018-05-14

Despite significant advances in the understanding of protein structure-function relationships, revealing protein folding pathways still poses a challenge due to a limited number of relevant experimental tools. Widely-used experimental techniques, such as calorimetry or spectroscopy, critically depend on a proper data analysis. Currently, there are only separate data analysis tools available for each type of experiment with a limited model selection. To address this problem, we have developed the CalFitter web server to be a unified platform for comprehensive data fitting and analysis of protein thermal denaturation data. The server allows simultaneous global data fitting using any combination of input data types and offers 12 protein unfolding pathway models for selection, including irreversible transitions often missing from other tools. The data fitting produces optimal parameter values, their confidence intervals, and statistical information to define unfolding pathways. The server provides an interactive and easy-to-use interface that allows users to directly analyse input datasets and simulate modelled output based on the model parameters. CalFitter web server is available free at https://loschmidt.chemi.muni.cz/calfitter/.

Psychometric evaluation of the revised Illness Perception Questionnaire (IPQ-R) in cancer patients: confirmatory factor analysis and Rasch analysis.

PubMed

Ashley, Laura; Smith, Adam B; Keding, Ada; Jones, Helen; Velikova, Galina; Wright, Penny

2013-12-01

To provide new insights into the psychometrics of the revised Illness Perception Questionnaire (IPQ-R) in cancer patients. To undertake, for the first time using data from breast, colorectal and prostate cancer patients, a confirmatory factor analysis (CFA) to assess the validity of the IPQ-R's core seven-factor structure. Also, for the first time in any illness group, to undertake Rasch analysis to explore the extent to which the IPQ-R factors form unidimensional scales, with linear measurement properties and no Differential Item Functioning (DIF). Patients with potentially curable breast, colorectal or prostate cancer, within 6months post-diagnosis, completed the IPQ-R online (N=531). CFA was conducted, including multi-sample analysis, and for each IPQ-R factor fit to the Rasch model was assessed by examining, amongst other things, item fit, DIF and unidimensionality. The CFA showed a moderate fit of the data to the IPQ-R model, and stability across diagnosis, although fit was significantly improved following the removal of selected items. All seven factors achieved fit to the Rasch model, and exhibited unidimensionality and minimal DIF, although in most cases this was after some item rescoring and/or deletion. In both analyses, IPQ-R items 12, 18 and 24 were indicated as misfitting and removed. Given the rigorous standard of Rasch measurement, and the generic nature of the IPQ-R, it stood up well to the demands of the Rasch model in this study. Importantly, the results show that with some relatively minor, pragmatic modifications the IPQ-R could possess Rasch-standard measurement in cancer patients. © 2013.

PVA/NaCl/MgO nanocomposites-microstructural analysis by whole pattern fitting method

NASA Astrophysics Data System (ADS)

Prashanth, K. S.; Mahesh, S. S.; Prakash, M. B. Nanda; Somashekar, R.; Nagabhushana, B. M.

2018-04-01

The nanofillers in the macromolecular matrix have displayed noteworthy changes in the structure and reactivity of the polymer nanocomposites. Novel functional materials usually consist of defects and are largely disordered. The intriguing properties of these materials are often attributed to defects. X-ray line profiles from powder diffraction reveal the quantitative information about size distribution and shape of diffracting domains which governs the contribution from small conventional X-ray diffraction (XRD) techniques to enumerate the microstructural information. In this study the MgO nanoparticles were prepared by solution combustion method and PVA/NaCl/MgO nanocomposite films were synthesized by the solvent cast method. Microstructural parameters viz crystal defects like stacking faults and twin faults, compositional inhomogeneity, crystallite size and lattice strain (g in %), were extracted using whole pattern fitting method.

Insight into model mechanisms through automatic parameter fitting: a new methodological framework for model development

PubMed Central

2014-01-01

Background Striking a balance between the degree of model complexity and parameter identifiability, while still producing biologically feasible simulations using modelling is a major challenge in computational biology. While these two elements of model development are closely coupled, parameter fitting from measured data and analysis of model mechanisms have traditionally been performed separately and sequentially. This process produces potential mismatches between model and data complexities that can compromise the ability of computational frameworks to reveal mechanistic insights or predict new behaviour. In this study we address this issue by presenting a generic framework for combined model parameterisation, comparison of model alternatives and analysis of model mechanisms. Results The presented methodology is based on a combination of multivariate metamodelling (statistical approximation of the input–output relationships of deterministic models) and a systematic zooming into biologically feasible regions of the parameter space by iterative generation of new experimental designs and look-up of simulations in the proximity of the measured data. The parameter fitting pipeline includes an implicit sensitivity analysis and analysis of parameter identifiability, making it suitable for testing hypotheses for model reduction. Using this approach, under-constrained model parameters, as well as the coupling between parameters within the model are identified. The methodology is demonstrated by refitting the parameters of a published model of cardiac cellular mechanics using a combination of measured data and synthetic data from an alternative model of the same system. Using this approach, reduced models with simplified expressions for the tropomyosin/crossbridge kinetics were found by identification of model components that can be omitted without affecting the fit to the parameterising data. Our analysis revealed that model parameters could be constrained to a standard deviation of on average 15% of the mean values over the succeeding parameter sets. Conclusions Our results indicate that the presented approach is effective for comparing model alternatives and reducing models to the minimum complexity replicating measured data. We therefore believe that this approach has significant potential for reparameterising existing frameworks, for identification of redundant model components of large biophysical models and to increase their predictive capacity. PMID:24886522

Evaluating the MSCEIT V2.0 via CFA: comment on Mayer et al. (2003).

PubMed

Gignac, Gilles E

2005-06-01

This investigation uncovered several substantial errors in the confirmatory factor analysis results reported by J. D. Mayer, P. Salovey, D. R. Caruso, and G. Sitarenios (see record 2003-02341-015). Specifically, the values associated with the close-fit indices (normed fit index, Tucker-Lewis Index, and root-mean-square error of approximation) are inaccurate. A reanalysis of the Mayer et al. subscale intercorrelation matrix provided accurate values of the close-fit indices, which resulted in different evaluations of the models tested by J. D. Mayer et al. Contrary to J. D. Mayer et al., the 1-factor model and the 2-factor model did not provide good fit. Although the 4-factor model was still considered good fitting, the non-constrained 4-factor model yielded a non-positive definite matrix, which was interpreted to be due to the fact that two of the branch-level factors (Perceiving and Facilitating) were collinear, suggesting that a model with 4 factors was implausible.

Diffuse X-ray scattering from benzil, C(14)H(10)O(2): analysis via automatic refinement of a Monte Carlo model.

PubMed

Welberry, T R; Goossens, D J; Edwards, A J; David, W I

2001-01-01

A recently developed method for fitting a Monte Carlo computer-simulation model to observed single-crystal diffuse X-ray scattering has been used to study the diffuse scattering in benzil, diphenylethanedione, C(6)H(5)-CO-CO-C(6)H(5). A model involving 13 parameters consisting of 11 intermolecular force constants, a single intramolecular torsional force constant and a local Debye-Waller factor was refined to give an agreement factor, R = [summation operator omega(Delta I)(2)/summation operator omega I(obs)(2)](1/2), of 14.5% for 101,324 data points. The model was purely thermal in nature. The analysis has shown that the diffuse lines, which feature so prominently in the observed diffraction patterns, are due to strong longitudinal displacement correlations. These are transmitted from molecule to molecule via a network of contacts involving hydrogen bonding of an O atom on one molecule and the para H atom of the phenyl ring of a neighbouring molecule. The analysis also allowed the determination of a torsional force constant for rotations about the single bonds in the molecule. This is the first diffuse scattering study in which measurement of such internal molecular torsion forces has been attempted.

Supporting cognition in systems biology analysis: findings on users' processes and design implications.

PubMed

Mirel, Barbara

2009-02-13

Current usability studies of bioinformatics tools suggest that tools for exploratory analysis support some tasks related to finding relationships of interest but not the deep causal insights necessary for formulating plausible and credible hypotheses. To better understand design requirements for gaining these causal insights in systems biology analyses a longitudinal field study of 15 biomedical researchers was conducted. Researchers interacted with the same protein-protein interaction tools to discover possible disease mechanisms for further experimentation. Findings reveal patterns in scientists' exploratory and explanatory analysis and reveal that tools positively supported a number of well-structured query and analysis tasks. But for several of scientists' more complex, higher order ways of knowing and reasoning the tools did not offer adequate support. Results show that for a better fit with scientists' cognition for exploratory analysis systems biology tools need to better match scientists' processes for validating, for making a transition from classification to model-based reasoning, and for engaging in causal mental modelling. As the next great frontier in bioinformatics usability, tool designs for exploratory systems biology analysis need to move beyond the successes already achieved in supporting formulaic query and analysis tasks and now reduce current mismatches with several of scientists' higher order analytical practices. The implications of results for tool designs are discussed.

Temporal patterns and forecast of dengue infection in Northeastern Thailand.

PubMed

Silawan, Tassanee; Singhasivanon, Pratap; Kaewkungwal, Jaranit; Nimmanitya, Suchitra; Suwonkerd, Wanapa

2008-01-01

This study aimed to determine temporal patterns and develop a forecasting model for dengue incidence in northeastern Thailand. Reported cases were obtained from the Thailand national surveillance system. The temporal patterns were displayed by plotting monthly rates, the seasonal-trend decomposition procedure based on loess (STL) was performed using R 2.2.1 software, and the trend was assessed using Poisson regression. The forecasting model for dengue incidence was performed in R 2.2.1 and Intercooled Stata 9.2 using the seasonal Autoregressive Integrated Moving Average (ARIMA) model. The model was evaluated by comparing predicted versus actual rates of dengue for 1996 to 2005 and used to forecast monthly rates during January to December 2006. The results reveal that epidemics occurred every two years, with approximately three years per epidemic, and that the next epidemic will take place in 2006 to 2008. It was found that if a month increased, the rate ratio for dengue infection decreased by a factor 0.9919 for overall region and 0.9776 to 0.9984 for individual provinces. The amplitude of the peak, which was evident in June or July, was 11.32 to 88.08 times greater than the rest of the year. The seasonal ARIMA (2, 1, 0) (0, 1, 1)12 model was model with the best fit for regionwide data of total dengue incidence whereas the models with the best fit varied by province. The forecasted regional monthly rates during January to December 2006 should range from 0.27 to 17.89 per 100,000 population. The peak for 2006 should be much higher than the peak for 2005. The highest peaks in 2006 should be in Loei, Buri Ram, Surin, Nakhon Phanom, and Ubon Ratchathani Provinces.

Occam's shadow: levels of analysis in evolutionary ecology - where to next?

USGS Publications Warehouse

Cooch, E.G.; Cam, E.; Link, W.A.

2002-01-01

Evolutionary ecology is the study of evolutionary processes, and the ecological conditions that influence them. A fundamental paradigm underlying the study of evolution is natural selection. Although there are a variety of operational definitions for natural selection in the literature, perhaps the most general one is that which characterizes selection as the process whereby heritable variation in fitness associated with variation in one or more phenotypic traits leads to intergenerational change in the frequency distribution of those traits. The past 20 years have witnessed a marked increase in the precision and reliability of our ability to estimate one or more components of fitness and characterize natural selection in wild populations, owing particularly to significant advances in methods for analysis of data from marked individuals. In this paper, we focus on several issues that we believe are important considerations for the application and development of these methods in the context of addressing questions in evolutionary ecology. First, our traditional approach to estimation often rests upon analysis of aggregates of individuals, which in the wild may reflect increasingly non-random (selected) samples with respect to the trait(s) of interest. In some cases, analysis at the aggregate level, rather than the individual level, may obscure important patterns. While there are a growing number of analytical tools available to estimate parameters at the individual level, and which can cope (to varying degrees) with progressive selection of the sample, the advent of new methods does not reduce the need to consider carefully the appropriate level of analysis in the first place. Estimation should be motivated a priori by strong theoretical analysis. Doing so provides clear guidance, in terms of both (i) assisting in the identification of realistic and meaningful models to include in the candidate model set, and (ii) providing the appropriate context under which the results are interpreted. Second, while it is true that selection (as defined) operates at the level of the individual, the selection gradient is often (if not generally) conditional on the abundance of the population. As such, it may be important to consider estimating transition rates conditional on both the parameter values of the other individuals in the population (or at least their distribution), and population abundance. This will undoubtedly pose a considerable challenge, for both single- and multi-strata applications. It will also require renewed consideration of the estimation of abundance, especially for open populations. Thirdly, selection typically operates on dynamic, individually varying traits. Such estimation may require characterizing fitness in terms of individual plasticity in one or more state variables, constituting analysis of the norms of reaction of individuals to variable environments. This can be quite complex, especially for traits that are under facultative control. Recent work has indicated that the pattern of selection on such traits is conditional on the relative rates of movement among and frequency of spatially heterogeneous habitats, suggesting analyses of evolution of life histories in open populations can be misleading in some cases.

Event-scale power law recession analysis: quantifying methodological uncertainty

NASA Astrophysics Data System (ADS)

Dralle, David N.; Karst, Nathaniel J.; Charalampous, Kyriakos; Veenstra, Andrew; Thompson, Sally E.

2017-01-01

The study of single streamflow recession events is receiving increasing attention following the presentation of novel theoretical explanations for the emergence of power law forms of the recession relationship, and drivers of its variability. Individually characterizing streamflow recessions often involves describing the similarities and differences between model parameters fitted to each recession time series. Significant methodological sensitivity has been identified in the fitting and parameterization of models that describe populations of many recessions, but the dependence of estimated model parameters on methodological choices has not been evaluated for event-by-event forms of analysis. Here, we use daily streamflow data from 16 catchments in northern California and southern Oregon to investigate how combinations of commonly used streamflow recession definitions and fitting techniques impact parameter estimates of a widely used power law recession model. Results are relevant to watersheds that are relatively steep, forested, and rain-dominated. The highly seasonal mediterranean climate of northern California and southern Oregon ensures study catchments explore a wide range of recession behaviors and wetness states, ideal for a sensitivity analysis. In such catchments, we show the following: (i) methodological decisions, including ones that have received little attention in the literature, can impact parameter value estimates and model goodness of fit; (ii) the central tendencies of event-scale recession parameter probability distributions are largely robust to methodological choices, in the sense that differing methods rank catchments similarly according to the medians of these distributions; (iii) recession parameter distributions are method-dependent, but roughly catchment-independent, such that changing the choices made about a particular method affects a given parameter in similar ways across most catchments; and (iv) the observed correlative relationship between the power-law recession scale parameter and catchment antecedent wetness varies depending on recession definition and fitting choices. Considering study results, we recommend a combination of four key methodological decisions to maximize the quality of fitted recession curves, and to minimize bias in the related populations of fitted recession parameters.

Social comparison and perceived breach of psychological contract: their effects on burnout in a multigroup analysis.

PubMed

Cantisano, Gabriela Topa; Domínguez, J Francisco Morales; García, J Luis Caeiro

2007-05-01

This study focuses on the mediator role of social comparison in the relationship between perceived breach of psychological contract and burnout. A previous model showing the hypothesized effects of perceived breach on burnout, both direct and mediated, is proposed. The final model reached an optimal fit to the data and was confirmed through multigroup analysis using a sample of Spanish teachers (N = 401) belonging to preprimary, primary, and secondary schools. Multigroup analyses showed that the model fit all groups adequately.

On the Usefulness of a Multilevel Logistic Regression Approach to Person-Fit Analysis

ERIC Educational Resources Information Center

Conijn, Judith M.; Emons, Wilco H. M.; van Assen, Marcel A. L. M.; Sijtsma, Klaas

2011-01-01

The logistic person response function (PRF) models the probability of a correct response as a function of the item locations. Reise (2000) proposed to use the slope parameter of the logistic PRF as a person-fit measure. He reformulated the logistic PRF model as a multilevel logistic regression model and estimated the PRF parameters from this…

Stochastic approach to data analysis in fluorescence correlation spectroscopy.

PubMed

Rao, Ramachandra; Langoju, Rajesh; Gösch, Michael; Rigler, Per; Serov, Alexandre; Lasser, Theo

2006-09-21

Fluorescence correlation spectroscopy (FCS) has emerged as a powerful technique for measuring low concentrations of fluorescent molecules and their diffusion constants. In FCS, the experimental data is conventionally fit using standard local search techniques, for example, the Marquardt-Levenberg (ML) algorithm. A prerequisite for these categories of algorithms is the sound knowledge of the behavior of fit parameters and in most cases good initial guesses for accurate fitting, otherwise leading to fitting artifacts. For known fit models and with user experience about the behavior of fit parameters, these local search algorithms work extremely well. However, for heterogeneous systems or where automated data analysis is a prerequisite, there is a need to apply a procedure, which treats FCS data fitting as a black box and generates reliable fit parameters with accuracy for the chosen model in hand. We present a computational approach to analyze FCS data by means of a stochastic algorithm for global search called PGSL, an acronym for Probabilistic Global Search Lausanne. This algorithm does not require any initial guesses and does the fitting in terms of searching for solutions by global sampling. It is flexible as well as computationally faster at the same time for multiparameter evaluations. We present the performance study of PGSL for two-component with triplet fits. The statistical study and the goodness of fit criterion for PGSL are also presented. The robustness of PGSL on noisy experimental data for parameter estimation is also verified. We further extend the scope of PGSL by a hybrid analysis wherein the output of PGSL is fed as initial guesses to ML. Reliability studies show that PGSL and the hybrid combination of both perform better than ML for various thresholds of the mean-squared error (MSE).

Sequence-based model of gap gene regulatory network.

PubMed

Kozlov, Konstantin; Gursky, Vitaly; Kulakovskiy, Ivan; Samsonova, Maria

2014-01-01

The detailed analysis of transcriptional regulation is crucially important for understanding biological processes. The gap gene network in Drosophila attracts large interest among researches studying mechanisms of transcriptional regulation. It implements the most upstream regulatory layer of the segmentation gene network. The knowledge of molecular mechanisms involved in gap gene regulation is far less complete than that of genetics of the system. Mathematical modeling goes beyond insights gained by genetics and molecular approaches. It allows us to reconstruct wild-type gene expression patterns in silico, infer underlying regulatory mechanism and prove its sufficiency. We developed a new model that provides a dynamical description of gap gene regulatory systems, using detailed DNA-based information, as well as spatial transcription factor concentration data at varying time points. We showed that this model correctly reproduces gap gene expression patterns in wild type embryos and is able to predict gap expression patterns in Kr mutants and four reporter constructs. We used four-fold cross validation test and fitting to random dataset to validate the model and proof its sufficiency in data description. The identifiability analysis showed that most model parameters are well identifiable. We reconstructed the gap gene network topology and studied the impact of individual transcription factor binding sites on the model output. We measured this impact by calculating the site regulatory weight as a normalized difference between the residual sum of squares error for the set of all annotated sites and for the set with the site of interest excluded. The reconstructed topology of the gap gene network is in agreement with previous modeling results and data from literature. We showed that 1) the regulatory weights of transcription factor binding sites show very weak correlation with their PWM score; 2) sites with low regulatory weight are important for the model output; 3) functional important sites are not exclusively located in cis-regulatory elements, but are rather dispersed through regulatory region. It is of importance that some of the sites with high functional impact in hb, Kr and kni regulatory regions coincide with strong sites annotated and verified in Dnase I footprint assays.

Spectral optical coherence tomography vs. fluorescein pattern for rigid gas-permeable lens fit.

PubMed

Piotrowiak, Ilona; Kaluzny, Bartłomiej Jan; Danek, Beata; Chwiędacz, Adam; Sikorski, Bartosz Lukasz; Malukiewicz, Grażyna

2014-07-04

This study aimed to evaluate anterior segment spectral optical coherence tomography (AS SOCT) for assessing the lens-to-cornea fit of rigid gas-permeable (RGP) lenses. The results were verified with the fluorescein pattern method, considered the criterion standard for RGP lens alignment evaluations. Twenty-six eyes of 14 patients were enrolled in the study. Initial base curve radius (BCR) of each RGP lens was determined on the basis of keratometry readings. The fluorescein pattern and AS SOCT tomograms were evaluated, starting with an alignment fit, and subsequently, with BCR reductions in increments of 0.1 mm, up to 3 consecutive changes. AS SOCT examination was performed with the use of RTVue (Optovue, California, USA). The average BCR for alignment fits, defined according to the fluorescein pattern, was 7.8 mm (SD=0.26). Repeatability of the measurements was 18.2%. BCR reductions of 0.1, 0.2, and 0.3 mm resulted in average apical clearances detected with AS SOCT of 12.38 (SD=9.91, p<0.05), 28.79 (SD=15.39, p<0.05), and 33.25 (SD=10.60, p>0.05), respectively. BCR steepening of 0.1 mm or more led to measurable changes in lens-to-cornea fits. Although AS SOCT represents a new method of assessing lens-to-cornea fit, apical clearance detection with current commercial technology showed lower sensitivity than the fluorescein pattern assessment.

Climate and Human Pressure Constraints Co-Explain Regional Plant Invasion at Different Spatial Scales

PubMed Central

García-Baquero, Gonzalo; Caño, Lidia; Biurrun, Idoia; García-Mijangos, Itziar; Loidi, Javier; Herrera, Mercedes

2016-01-01

Alien species invasion represents a global threat to biodiversity and ecosystems. Explaining invasion patterns in terms of environmental constraints will help us to assess invasion risks and plan control strategies. We aim to identify plant invasion patterns in the Basque Country (Spain), and to determine the effects of climate and human pressure on that pattern. We modeled the regional distribution of 89 invasive plant species using two approaches. First, distance-based Moran’s eigenvector maps were used to partition variation in the invasive species richness, S, into spatial components at broad and fine scales; redundancy analysis was then used to explain those components on the basis of climate and human pressure descriptors. Second, we used generalized additive mixed modeling to fit species-specific responses to the same descriptors. Climate and human pressure descriptors have different effects on S at different spatial scales. Broad-scale spatially structured temperature and precipitation, and fine-scale spatially structured human population density and percentage of natural and semi-natural areas, explained altogether 38.7% of the total variance. The distribution of 84% of the individually tested species was related to either temperature, precipitation or both, and 68% was related to either population density or natural and semi-natural areas, displaying similar responses. The spatial pattern of the invasive species richness is strongly environmentally forced, mainly by climate factors. Since individual species responses were proved to be both similarly constrained in shape and explained variance by the same environmental factors, we conclude that the pattern of invasive species richness results from individual species’ environmental preferences. PMID:27741276

Genetic diversity in the interference selection limit.

PubMed

Good, Benjamin H; Walczak, Aleksandra M; Neher, Richard A; Desai, Michael M

2014-03-01

Pervasive natural selection can strongly influence observed patterns of genetic variation, but these effects remain poorly understood when multiple selected variants segregate in nearby regions of the genome. Classical population genetics fails to account for interference between linked mutations, which grows increasingly severe as the density of selected polymorphisms increases. Here, we describe a simple limit that emerges when interference is common, in which the fitness effects of individual mutations play a relatively minor role. Instead, similar to models of quantitative genetics, molecular evolution is determined by the variance in fitness within the population, defined over an effectively asexual segment of the genome (a "linkage block"). We exploit this insensitivity in a new "coarse-grained" coalescent framework, which approximates the effects of many weakly selected mutations with a smaller number of strongly selected mutations that create the same variance in fitness. This approximation generates accurate and efficient predictions for silent site variability when interference is common. However, these results suggest that there is reduced power to resolve individual selection pressures when interference is sufficiently widespread, since a broad range of parameters possess nearly identical patterns of silent site variability.

Using a second‐order differential model to fit data without baselines in protein isothermal chemical denaturation

PubMed Central

Tang, Chuanning; Lew, Scott

2016-01-01

Abstract In vitro protein stability studies are commonly conducted via thermal or chemical denaturation/renaturation of protein. Conventional data analyses on the protein unfolding/(re)folding require well‐defined pre‐ and post‐transition baselines to evaluate Gibbs free‐energy change associated with the protein unfolding/(re)folding. This evaluation becomes problematic when there is insufficient data for determining the pre‐ or post‐transition baselines. In this study, fitting on such partial data obtained in protein chemical denaturation is established by introducing second‐order differential (SOD) analysis to overcome the limitations that the conventional fitting method has. By reducing numbers of the baseline‐related fitting parameters, the SOD analysis can successfully fit incomplete chemical denaturation data sets with high agreement to the conventional evaluation on the equivalent completed data, where the conventional fitting fails in analyzing them. This SOD fitting for the abbreviated isothermal chemical denaturation further fulfills data analysis methods on the insufficient data sets conducted in the two prevalent protein stability studies. PMID:26757366

Quantitative model analysis with diverse biological data: applications in developmental pattern formation.

PubMed

Pargett, Michael; Umulis, David M

2013-07-15

Mathematical modeling of transcription factor and signaling networks is widely used to understand if and how a mechanism works, and to infer regulatory interactions that produce a model consistent with the observed data. Both of these approaches to modeling are informed by experimental data, however, much of the data available or even acquirable are not quantitative. Data that is not strictly quantitative cannot be used by classical, quantitative, model-based analyses that measure a difference between the measured observation and the model prediction for that observation. To bridge the model-to-data gap, a variety of techniques have been developed to measure model "fitness" and provide numerical values that can subsequently be used in model optimization or model inference studies. Here, we discuss a selection of traditional and novel techniques to transform data of varied quality and enable quantitative comparison with mathematical models. This review is intended to both inform the use of these model analysis methods, focused on parameter estimation, and to help guide the choice of method to use for a given study based on the type of data available. Applying techniques such as normalization or optimal scaling may significantly improve the utility of current biological data in model-based study and allow greater integration between disparate types of data. Copyright © 2013 Elsevier Inc. All rights reserved.

Are infant mortality rate declines exponential? The general pattern of 20th century infant mortality rate decline

PubMed Central

Bishai, David; Opuni, Marjorie

2009-01-01

Background Time trends in infant mortality for the 20th century show a curvilinear pattern that most demographers have assumed to be approximately exponential. Virtually all cross-country comparisons and time series analyses of infant mortality have studied the logarithm of infant mortality to account for the curvilinear time trend. However, there is no evidence that the log transform is the best fit for infant mortality time trends. Methods We use maximum likelihood methods to determine the best transformation to fit time trends in infant mortality reduction in the 20th century and to assess the importance of the proper transformation in identifying the relationship between infant mortality and gross domestic product (GDP) per capita. We apply the Box Cox transform to infant mortality rate (IMR) time series from 18 countries to identify the best fitting value of lambda for each country and for the pooled sample. For each country, we test the value of λ against the null that λ = 0 (logarithmic model) and against the null that λ = 1 (linear model). We then demonstrate the importance of selecting the proper transformation by comparing regressions of ln(IMR) on same year GDP per capita against Box Cox transformed models. Results Based on chi-squared test statistics, infant mortality decline is best described as an exponential decline only for the United States. For the remaining 17 countries we study, IMR decline is neither best modelled as logarithmic nor as a linear process. Imposing a logarithmic transform on IMR can lead to bias in fitting the relationship between IMR and GDP per capita. Conclusion The assumption that IMR declines are exponential is enshrined in the Preston curve and in nearly all cross-country as well as time series analyses of IMR data since Preston's 1975 paper, but this assumption is seldom correct. Statistical analyses of IMR trends should assess the robustness of findings to transformations other than the log transform. PMID:19698144

THE FERTILITY MOTIVATIONS OF YOUTH PREDICT LATER FERTILITY OUTCOMES: A PROSPECTIVE ANALYSIS OF NLSY DATA*

PubMed Central

Miller, Warren B.; Rodgers, Joseph Lee; Pasta, David J.

2010-01-01

We examine how the motivational sequence that leads to childbearing predicts fertility outcomes across reproductive careers. Using a motivational traits-desires-intentions theoretical framework, we test a structural equation model using prospective male and female data from the National Longitudinal Survey of Youth. Specifically, we take motivational data collected during the 1979–1982 period, when the youths were in their teens and early twenties, to predict the timing of the next child born after 1982 and the total number of children born by 2002. Separate models were estimated for males and females but with equality constraints imposed unless relaxing these constraints improved the overall model fit. The results indicate substantial explanatory power of fertility motivations for both short-term and long-term fertility outcomes. They also reveal the effects of both gender role attitude and educational intentions on these outcomes. Although some sex differences in model pathways occurred, the primary hypothesized pathways were essentially the same across the sexes. Two validity substudies support the soundness of the results. A third substudy comparing the male and female models across the sample split on the basis of previous childbearing revealed a number of pattern differences within the four sex-by-previous childbearing groups. Several of the more robust of these pattern differences offer interesting insights and support the validity and usefulness of our theoretical framework. PMID:20463915

History, Epidemic Evolution, and Model Burn-In for a Network of Annual Invasion: Soybean Rust.

PubMed

Sanatkar, M R; Scoglio, C; Natarajan, B; Isard, S A; Garrett, K A

2015-07-01

Ecological history may be an important driver of epidemics and disease emergence. We evaluated the role of history and two related concepts, the evolution of epidemics and the burn-in period required for fitting a model to epidemic observations, for the U.S. soybean rust epidemic (caused by Phakopsora pachyrhizi). This disease allows evaluation of replicate epidemics because the pathogen reinvades the United States each year. We used a new maximum likelihood estimation approach for fitting the network model based on observed U.S. epidemics. We evaluated the model burn-in period by comparing model fit based on each combination of other years of observation. When the miss error rates were weighted by 0.9 and false alarm error rates by 0.1, the mean error rate did decline, for most years, as more years were used to construct models. Models based on observations in years closer in time to the season being estimated gave lower miss error rates for later epidemic years. The weighted mean error rate was lower in backcasting than in forecasting, reflecting how the epidemic had evolved. Ongoing epidemic evolution, and potential model failure, can occur because of changes in climate, host resistance and spatial patterns, or pathogen evolution.

Assessment of family functioning in Caucasian and Hispanic Americans: reliability, validity, and factor structure of the Family Assessment Device.

PubMed

Aarons, Gregory A; McDonald, Elizabeth J; Connelly, Cynthia D; Newton, Rae R

2007-12-01

The purpose of this study was to examine the factor structure, reliability, and validity of the Family Assessment Device (FAD) among a national sample of Caucasian and Hispanic American families receiving public sector mental health services. A confirmatory factor analysis conducted to test model fit yielded equivocal findings. With few exceptions, indices of model fit, reliability, and validity were poorer for Hispanic Americans compared with Caucasian Americans. Contrary to our expectation, an exploratory factor analysis did not result in a better fitting model of family functioning. Without stronger evidence supporting a reformulation of the FAD, we recommend against such a course of action. Findings highlight the need for additional research on the role of culture in measurement of family functioning.

A quantitative validated model reveals two phases of transcriptional regulation for the gap gene giant in Drosophila.

PubMed

Hoermann, Astrid; Cicin-Sain, Damjan; Jaeger, Johannes

2016-03-15

Understanding eukaryotic transcriptional regulation and its role in development and pattern formation is one of the big challenges in biology today. Most attempts at tackling this problem either focus on the molecular details of transcription factor binding, or aim at genome-wide prediction of expression patterns from sequence through bioinformatics and mathematical modelling. Here we bridge the gap between these two complementary approaches by providing an integrative model of cis-regulatory elements governing the expression of the gap gene giant (gt) in the blastoderm embryo of Drosophila melanogaster. We use a reverse-engineering method, where mathematical models are fit to quantitative spatio-temporal reporter gene expression data to infer the regulatory mechanisms underlying gt expression in its anterior and posterior domains. These models are validated through prediction of gene expression in mutant backgrounds. A detailed analysis of our data and models reveals that gt is regulated by domain-specific CREs at early stages, while a late element drives expression in both the anterior and the posterior domains. Initial gt expression depends exclusively on inputs from maternal factors. Later, gap gene cross-repression and gt auto-activation become increasingly important. We show that auto-regulation creates a positive feedback, which mediates the transition from early to late stages of regulation. We confirm the existence and role of gt auto-activation through targeted mutagenesis of Gt transcription factor binding sites. In summary, our analysis provides a comprehensive picture of spatio-temporal gene regulation by different interacting enhancer elements for an important developmental regulator. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Three-dimensional whole-brain perfusion quantification using pseudo-continuous arterial spin labeling MRI at multiple post-labeling delays: accounting for both arterial transit time and impulse response function.

PubMed

Qin, Qin; Huang, Alan J; Hua, Jun; Desmond, John E; Stevens, Robert D; van Zijl, Peter C M

2014-02-01

Measurement of the cerebral blood flow (CBF) with whole-brain coverage is challenging in terms of both acquisition and quantitative analysis. In order to fit arterial spin labeling-based perfusion kinetic curves, an empirical three-parameter model which characterizes the effective impulse response function (IRF) is introduced, which allows the determination of CBF, the arterial transit time (ATT) and T(1,eff). The accuracy and precision of the proposed model were compared with those of more complicated models with four or five parameters through Monte Carlo simulations. Pseudo-continuous arterial spin labeling images were acquired on a clinical 3-T scanner in 10 normal volunteers using a three-dimensional multi-shot gradient and spin echo scheme at multiple post-labeling delays to sample the kinetic curves. Voxel-wise fitting was performed using the three-parameter model and other models that contain two, four or five unknown parameters. For the two-parameter model, T(1,eff) values close to tissue and blood were assumed separately. Standard statistical analysis was conducted to compare these fitting models in various brain regions. The fitted results indicated that: (i) the estimated CBF values using the two-parameter model show appreciable dependence on the assumed T(1,eff) values; (ii) the proposed three-parameter model achieves the optimal balance between the goodness of fit and model complexity when compared among the models with explicit IRF fitting; (iii) both the two-parameter model using fixed blood T1 values for T(1,eff) and the three-parameter model provide reasonable fitting results. Using the proposed three-parameter model, the estimated CBF (46 ± 14 mL/100 g/min) and ATT (1.4 ± 0.3 s) values averaged from different brain regions are close to the literature reports; the estimated T(1,eff) values (1.9 ± 0.4 s) are higher than the tissue T1 values, possibly reflecting a contribution from the microvascular arterial blood compartment. Copyright © 2013 John Wiley & Sons, Ltd.

Injury Rate and Patterns Among CrossFit Athletes.

PubMed

Weisenthal, Benjamin M; Beck, Christopher A; Maloney, Michael D; DeHaven, Kenneth E; Giordano, Brian D

2014-04-01

CrossFit is a type of competitive exercise program that has gained widespread recognition. To date, there have been no studies that have formally examined injury rates among CrossFit participants or factors that may contribute to injury rates. To establish an injury rate among CrossFit participants and to identify trends and associations between injury rates and demographic categories, gym characteristics, and athletic abilities among CrossFit participants. Descriptive epidemiology study. A survey was conducted, based on validated epidemiologic injury surveillance methods, to identify patterns of injury among CrossFit participants. It was sent to CrossFit gyms in Rochester, New York; New York City, New York; and Philadelphia, Pennsylvania, and made available via a posting on the main CrossFit website. Participants were encouraged to distribute it further, and as such, there were responses from a wide geographical location. Inclusion criteria included participating in CrossFit training at a CrossFit gym in the United States. Data were collected from October 2012 to February 2013. Data analysis was performed using Fisher exact tests and chi-square tests. A total of 486 CrossFit participants completed the survey, and 386 met the inclusion criteria. The overall injury rate was determined to be 19.4% (75/386). Males (53/231) were injured more frequently than females (21/150; P = .03). Across all exercises, injury rates were significantly different (P < .001), with shoulder (21/84), low back (12/84), and knee (11/84) being the most commonly injured overall. The shoulder was most commonly injured in gymnastic movements, and the low back was most commonly injured in power lifting movements. Most participants did not report prior injury (72/89; P < .001) or discomfort in the area (58/88; P < .001). Last, the injury rate was significantly decreased with trainer involvement (P = .028). The injury rate in CrossFit was approximately 20%. Males were more likely to sustain an injury than females. The involvement of trainers in coaching participants on their form and guiding them through the workout correlates with a decreased injury rate. The shoulder and lower back were the most commonly injured in gymnastic and power lifting movements, respectively. Participants reported primarily acute and fairly mild injuries.

The X-ray spectra of blazars: Analysis of the complete EXOSAT archive

NASA Technical Reports Server (NTRS)

Sambruna, Rita M.; Barr, Paul; Giommi, Paolo; Maraschi, Laura; Tagliaferri, Gianpiero; Treves, Aldo

1994-01-01

We analyzed the 0.1-10 keV spectra of 26 blazars (21 BL Lac objects and 5 highly polarized quasars), on the basis of 93 exposures taken from the EXOSAT archives. Fits were performed first with a single power-law model. Indications are found that better fits can be obtained with models where the slope steepens at higher energies. We therefore considered a broken power law and found that in a large fraction of the spectra the fit is significantly improved. Fits with a power law + oxygen edge at 0.6 keV are also explored.

The Common Patterns of Nature

PubMed Central

Frank, Steven A.

2010-01-01

We typically observe large-scale outcomes that arise from the interactions of many hidden, small-scale processes. Examples include age of disease onset, rates of amino acid substitutions, and composition of ecological communities. The macroscopic patterns in each problem often vary around a characteristic shape that can be generated by neutral processes. A neutral generative model assumes that each microscopic process follows unbiased or random stochastic fluctuations: random connections of network nodes; amino acid substitutions with no effect on fitness; species that arise or disappear from communities randomly. These neutral generative models often match common patterns of nature. In this paper, I present the theoretical background by which we can understand why these neutral generative models are so successful. I show where the classic patterns come from, such as the Poisson pattern, the normal or Gaussian pattern, and many others. Each classic pattern was often discovered by a simple neutral generative model. The neutral patterns share a special characteristic: they describe the patterns of nature that follow from simple constraints on information. For example, any aggregation of processes that preserves information only about the mean and variance attracts to the Gaussian pattern; any aggregation that preserves information only about the mean attracts to the exponential pattern; any aggregation that preserves information only about the geometric mean attracts to the power law pattern. I present a simple and consistent informational framework of the common patterns of nature based on the method of maximum entropy. This framework shows that each neutral generative model is a special case that helps to discover a particular set of informational constraints; those informational constraints define a much wider domain of non-neutral generative processes that attract to the same neutral pattern. PMID:19538344

Model error in covariance structure models: Some implications for power and Type I error

PubMed Central

Coffman, Donna L.

2010-01-01

The present study investigated the degree to which violation of the parameter drift assumption affects the Type I error rate for the test of close fit and power analysis procedures proposed by MacCallum, Browne, and Sugawara (1996) for both the test of close fit and the test of exact fit. The parameter drift assumption states that as sample size increases both sampling error and model error (i.e. the degree to which the model is an approximation in the population) decrease. Model error was introduced using a procedure proposed by Cudeck and Browne (1992). The empirical power for both the test of close fit, in which the null hypothesis specifies that the Root Mean Square Error of Approximation (RMSEA) ≤ .05, and the test of exact fit, in which the null hypothesis specifies that RMSEA = 0, is compared with the theoretical power computed using the MacCallum et al. (1996) procedure. The empirical power and theoretical power for both the test of close fit and the test of exact fit are nearly identical under violations of the assumption. The results also indicated that the test of close fit maintains the nominal Type I error rate under violations of the assumption. PMID:21331302

Measuring Adjustment to College: Construct Validity of the Student Adaptation to College Questionnaire

ERIC Educational Resources Information Center

Feldt, Ronald C.; Graham, Melody; Dew, Dennis

2011-01-01

This study employed confirmatory factor analysis to examine the quality of fit of two measurement models of the Student Adaptation to College Questionnaire (N = 305). Following the observation of poor fit, exploratory factor analysis was used. Results indicated six factors that account for the variance in Student Adaptation to College…

Calibration data Analysis Package (CAP): An IDL based widget application for analysis of X-ray calibration data

NASA Astrophysics Data System (ADS)

Vaishali, S.; Narendranath, S.; Sreekumar, P.

An IDL (interactive data language) based widget application developed for the calibration of C1XS (Narendranath et al., 2010) instrument on Chandrayaan-1 is modified to provide a generic package for the analysis of data from x-ray detectors. The package supports files in ascii as well as FITS format. Data can be fitted with a list of inbuilt functions to derive the spectral redistribution function (SRF). We have incorporated functions such as `HYPERMET' (Philips & Marlow 1976) including non Gaussian components in the SRF such as low energy tail, low energy shelf and escape peak. In addition users can incorporate additional models which may be required to model detector specific features. Spectral fits use a routine `mpfit' which uses Leven-Marquardt least squares fitting method. The SRF derived from this tool can be fed into an accompanying program to generate a redistribution matrix file (RMF) compatible with the X-ray spectral analysis package XSPEC. The tool provides a user friendly interface of help to beginners and also provides transparency and advanced features for experts.

3D spherical-cap fitting procedure for (truncated) sessile nano- and micro-droplets & -bubbles.

PubMed

Tan, Huanshu; Peng, Shuhua; Sun, Chao; Zhang, Xuehua; Lohse, Detlef

2016-11-01

In the study of nanobubbles, nanodroplets or nanolenses immobilised on a substrate, a cross-section of a spherical cap is widely applied to extract geometrical information from atomic force microscopy (AFM) topographic images. In this paper, we have developed a comprehensive 3D spherical-cap fitting procedure (3D-SCFP) to extract morphologic characteristics of complete or truncated spherical caps from AFM images. Our procedure integrates several advanced digital image analysis techniques to construct a 3D spherical-cap model, from which the geometrical parameters of the nanostructures are extracted automatically by a simple algorithm. The procedure takes into account all valid data points in the construction of the 3D spherical-cap model to achieve high fidelity in morphology analysis. We compare our 3D fitting procedure with the commonly used 2D cross-sectional profile fitting method to determine the contact angle of a complete spherical cap and a truncated spherical cap. The results from 3D-SCFP are consistent and accurate, while 2D fitting is unavoidably arbitrary in the selection of the cross-section and has a much lower number of data points on which the fitting can be based, which in addition is biased to the top of the spherical cap. We expect that the developed 3D spherical-cap fitting procedure will find many applications in imaging analysis.

Effect of X-ray Line Spectra Profile Fitting with Pearson VII, Pseudo-Voigt and Generalized Fermi Functions on Asphalt Binder Aromaticity and Crystallite Parameters

NASA Astrophysics Data System (ADS)

Gebresellasie, K.; Shirokoff, J.; Lewis, J. C.

2012-12-01

X-ray line spectra profile fitting using Pearson VII, pseudo-Voigt and generalized Fermi functions was performed on asphalt binders prior to the calculation of aromaticity and crystallite size parameters. The effects of these functions on the results are presented and discussed in terms of the peak profile fit parameters, the uncertainties in calculated values that can arise owing to peak shape, peak features in the pattern and crystallite size according to the asphalt models (Yen, modified Yen or Yen-Mullins) and theories. Interpretation of these results is important in terms of evaluating the performance of asphalt binders widely used in the application of transportation systems (roads, highways, airports).

The rotation and fracture history of Europa from modeling of tidal-tectonic processes

NASA Astrophysics Data System (ADS)

Rhoden, Alyssa Rose

Europa's surface displays a complex history of tectonic activity, much of which has been linked to tidal stress caused by Europa's eccentric orbit and possibly non-synchronous rotation of the ice shell. Cycloids are arcuate features thought to have formed in response to tidal normal stress while strike-slip motion along preexisting faults has been attributed to tidal shear stress. Tectonic features thus provide constraints on the rotational parameters that govern tidal stress, and can help us develop an understanding of the tidal-tectonic processes operating on ice covered ocean moons. In the first part of this work (Chapter 3), I test tidal models that include obliquity, fast precession, stress due to non-synchronous rotation (NSR), and physical libration by comparing how well each model reproduces observed cycloids. To do this, I have designed and implemented an automated parameter-searching algorithm that relies on a quantitative measure of fit quality to identify the best fits to observed cycloids. I apply statistical techniques to determine the tidal model best supported by the data and constrain the values of Europa's rotational parameters. Cycloids indicate a time-varying obliquity of about 1° and a physical libration in phase with the eccentricity libration, with amplitude >1°. To obtain good fits, cycloids must be translated in longitude, which implies non-synchronous rotation of the icy shell. However, stress from NSR is not well-supported, indicating that the rotation rate is slow enough that these stresses relax. I build upon the results of cycloid modeling in the second section by applying calculations of tidal stress that include obliquity to the formation of strike-slip faults. I predict the slip directions of faults with the standard formation model---tidal walking (Chapter 5)---and with a new mechanical model I have developed, called shell tectonics (Chapter 6). The shell tectonics model incorporates linear elasticity to determine slip and stress release on faults and uses a Coulomb failure criterion. Both of these models can be used to predict the direction of net displacement along faults. Until now, the tidal walking model has been the only model that reproduces the observed global pattern of strike-slip displacement; the shell tectonics model incorporates a more physical treatment of fault mechanics and reproduces this global pattern. Both models fit the regional patterns of observed strike-slip faults better when a small obliquity is incorporated into calculations of tidal stresses. Shell tectonics is also distinct from tidal walking in that it calculates the relative growth rates of displacements in addition to net slip direction. Examining these growth rates, I find that certain azimuths and locations develop offsets more quickly than others. Because faults with larger offsets are easier to identify, this may explain why observed faults cluster in azimuth in many regions. The growth rates also allow for a more sophisticated statistical comparison between the predictions and observations. Although the slip directions of >75% of faults are correctly predicted using shell tectonics and 1° of obliquity, a portion of these faults could be fit equally well with a random model. Examining these faults in more detail has revealed a region of Europa in which strike-slip faults likely formed through local extensional and compressional deformation rather than as a result of tidal shear stress. This approach enables a better understanding of the tectonic record, which has implications on Europa's rotation history.

Exploring the measurement properties of the osteopathy clinical teaching questionnaire using Rasch analysis.

PubMed

Vaughan, Brett

2018-01-01

Clinical teaching evaluations are common in health profession education programs to ensure students are receiving a quality clinical education experience. Questionnaires students use to evaluate their clinical teachers have been developed in professions such as medicine and nursing. The development of a questionnaire that is specifically for the osteopathy on-campus, student-led clinic environment is warranted. Previous work developed the 30-item Osteopathy Clinical Teaching Questionnaire. The current study utilised Rasch analysis to investigate the construct validity of the Osteopathy Clinical Teaching Questionnaire and provide evidence for the validity argument through fit to the Rasch model. Senior osteopathy students at four institutions in Australia, New Zealand and the United Kingdom rated their clinical teachers using the Osteopathy Clinical Teaching Questionnaire. Three hundred and ninety-nine valid responses were received and the data were evaluated for fit to the Rasch model. Reliability estimations (Cronbach's alpha and McDonald's omega) were also evaluated for the final model. The initial analysis demonstrated the data did not fit the Rasch model. Accordingly, modifications to the questionnaire were made including removing items, removing person responses, and rescoring one item. The final model contained 12 items and fit to the Rasch model was adequate. Support for unidimensionality was demonstrated through both the Principal Components Analysis/t-test, and the Cronbach's alpha and McDonald's omega reliability estimates. Analysis of the questionnaire using McDonald's omega hierarchical supported a general factor (quality of clinical teaching in osteopathy). The evidence for unidimensionality and the presence of a general factor support the calculation of a total score for the questionnaire as a sufficient statistic. Further work is now required to investigate the reliability of the 12-item Osteopathy Clinical Teaching Questionnaire to provide evidence for the validity argument.

Kinetics of antigen binding to arrays of antibodies in different sized spots

NASA Technical Reports Server (NTRS)

Sapsford, K. E.; Liron, Z.; Shubin, Y. S.; Ligler, F. S.

2001-01-01

A fluorescence-based array biosensor has been developed which can measure the binding kinetics of an antigen to an immobilized antibody in real time. A patterned array of antibodies immobilized on the surface of a planar waveguide was used to capture a Cy5-labeled antigen present in a solution that was continuously flowed over the surface. The CCD image of the waveguide was monitored continuously for 25 min. The resulting exponential rise in fluorescence signal was determined by image analysis software and fitted to a reaction-limited kinetics model, giving a kf of 3.6 x 10(5) M(-1) s(-1). Different spot sizes were then patterned on the surface of the waveguide using either a PDMS flow cell or laser exposure, producing width sizes ranging from 80 to 1145 microm. It was demonstrated that under flow conditions, the reduction of spot size did not alter the association rate of the antigen with immobilized antibody; however, as the spot width decreased to < 200 nm, the signal intensity also decreased.

Extrapolation of the dna fragment-size distribution after high-dose irradiation to predict effects at low doses

NASA Technical Reports Server (NTRS)

Ponomarev, A. L.; Cucinotta, F. A.; Sachs, R. K.; Brenner, D. J.; Peterson, L. E.

2001-01-01

The patterns of DSBs induced in the genome are different for sparsely and densely ionizing radiations: In the former case, the patterns are well described by a random-breakage model; in the latter, a more sophisticated tool is needed. We used a Monte Carlo algorithm with a random-walk geometry of chromatin, and a track structure defined by the radial distribution of energy deposition from an incident ion, to fit the PFGE data for fragment-size distribution after high-dose irradiation. These fits determined the unknown parameters of the model, enabling the extrapolation of data for high-dose irradiation to the low doses that are relevant for NASA space radiation research. The randomly-located-clusters formalism was used to speed the simulations. It was shown that only one adjustable parameter, Q, the track efficiency parameter, was necessary to predict DNA fragment sizes for wide ranges of doses. This parameter was determined for a variety of radiations and LETs and was used to predict the DSB patterns at the HPRT locus of the human X chromosome after low-dose irradiation. It was found that high-LET radiation would be more likely than low-LET radiation to induce additional DSBs within the HPRT gene if this gene already contained one DSB.

Auditory development in early amplified children: factors influencing auditory-based communication outcomes in children with hearing loss.

PubMed

Sininger, Yvonne S; Grimes, Alison; Christensen, Elizabeth

2010-04-01

The purpose of this study was to determine the influence of selected predictive factors, primarily age at fitting of amplification and degree of hearing loss, on auditory-based outcomes in young children with bilateral sensorineural hearing loss. Forty-four infants and toddlers, first identified with mild to profound bilateral hearing loss, who were being fitted with amplification were enrolled in the study and followed longitudinally. Subjects were otherwise typically developing with no evidence of cognitive, motor, or visual impairment. A variety of subject factors were measured or documented and used as predictor variables, including age at fitting of amplification, degree of hearing loss in the better hearing ear, cochlear implant status, intensity of oral education, parent-child interaction, and the number of languages spoken in the home. These factors were used in a linear multiple regression analysis to assess their contribution to auditory-based communication outcomes. Five outcome measures, evaluated at regular intervals in children starting at age 3, included measures of speech perception (Pediatric Speech Intelligibility and Online Imitative Test of Speech Pattern Contrast Perception), speech production (Arizona-3), and spoken language (Reynell Expressive and Receptive Language). The age at fitting of amplification ranged from 1 to 72 mo, and the degree of hearing loss ranged from mild to profound. Age at fitting of amplification showed the largest influence and was a significant factor in all outcome models. The degree of hearing loss was an important factor in the modeling of speech production and spoken language outcomes. Cochlear implant use was the other factor that contributed significantly to speech perception, speech production, and language outcomes. Other factors contributed sparsely to the models. Prospective longitudinal studies of children are important to establish relationships between subject factors and outcomes. This study clearly demonstrated the importance of early amplification on communication outcomes. This demonstration required a participant pool that included children who have been fit at very early ages and who represent all degrees of hearing loss. Limitations of longitudinal studies include selection biases. Families who enroll tend to have high levels of education and rate highly on cooperation and compliance measures. Although valuable information can be extracted from prospective studies, not all factors can be evaluated because of enrollment constraints.

The Cross-Cultural Validity of the MMPI-2-RF Higher-Order Scales in a Sample of North Korean Female Refugees.

PubMed

Kim, Seong-Hyeon; Goodman, Grace M; Toruno, Joseph A; Sherry, Alissa R; Kim, Hee Kyung

2015-10-01

We investigated the cross-cultural factorial validity of the three Higher-Order (H-O) scales in the Minnesota Multiphasic Personality Inventory-2 Restructured Form (MMPI-2-RF) among a sample of North Korean female refugees (N = 2,732). Given the importance of the H-O scales in the overall structure of the MMPI-2-RF scales and in interpretation, we were interested in exploring their cross-cultural validity. We conducted an exploratory factor analysis (EFA) on the nine Restructured Clinical (RC) scale raw scores and fitted and compared one- to three-factor models. The three-factor model, akin to the model in Tellegen and Ben-Porath, demonstrated the best fit to the data. Furthermore, the pattern matrices of loadings across the current sample and the U.S. samples were comparable despite some differences, such as the RC2 scale's salient, negative loading on a factor analogous to the Behavioral/Externalizing Dysfunction scale. We also investigated the unique psychological characteristics of the refugees, possibly resulting from the arduous, perilous journeys out of North Korea taken by this group of female refugees and discussed the results of EFA in light of those singular psychological traits and experiences. Overall, the three H-O scales of the Korean MMPI-2-RF evidenced reasonable cross-cultural factorial validity among the sample of North Korean female refugees. © The Author(s) 2014.

A minimum stochastic model evaluating the interplay between population density and drift for species coexistence

NASA Astrophysics Data System (ADS)

Guariento, Rafael Dettogni; Caliman, Adriano

2017-02-01

Despite the general acknowledgment of the role of niche and stochastic process in community dynamics, the role of species relative abundances according to both perspectives may have different effects regarding coexistence patterns. In this study, we explore a minimum probabilistic stochastic model to determine the relationship of populations relative and total abundances with species chances to outcompete each other and their persistence in time (i.e., unstable coexistence). Our model is focused on the effects drift (i.e., random sampling of recruitment) under different scenarios of selection (i.e., fitness differences between species). Our results show that taking into account the stochasticity in demographic properties and conservation of individuals in closed communities (zero-sum assumption), initial population abundance can strongly influence species chances to outcompete each other, despite fitness inequalities between populations, and also, influence the period of coexistence of these species in a particular time interval. Systems carrying capacity can have an important role in species coexistence by exacerbating fitness inequalities and affecting the size of the period of coexistence. Overall, the simple stochastic formulation used in this study demonstrated that populations initial abundances could act as an equalizing mechanism, reducing fitness inequalities, which can favor species coexistence and even make less fitted species to be more likely to outcompete better-fitted species, and thus to dominate ecological communities in the absence of niche mechanisms. Although our model is restricted to a pair of interacting species, and overall conclusions are already predicted by the Neutral Theory of Biodiversity, our main objective was to derive a model that can explicitly show the functional relationship between population densities and community mono-dominance odds. Overall, our study provides a straightforward understanding of how a stochastic process (i.e., drift) may affect the expected outcome based on species selection (i.e., fitness inequalities among species) and the resulting outcome regarding unstable coexistence among species.

CrossFit Overview: Systematic Review and Meta-analysis.

PubMed

Claudino, João Gustavo; Gabbett, Tim J; Bourgeois, Frank; Souza, Helton de Sá; Miranda, Rafael Chagas; Mezêncio, Bruno; Soncin, Rafael; Cardoso Filho, Carlos Alberto; Bottaro, Martim; Hernandez, Arnaldo Jose; Amadio, Alberto Carlos; Serrão, Julio Cerca

2018-02-26

CrossFit is recognized as one of the fastest growing high-intensity functional training modes in the world. However, scientific data regarding the practice of CrossFit is sparse. Therefore, the objective of this study is to analyze the findings of scientific literature related to CrossFit via systematic review and meta-analysis. Systematic searches of the PubMed, Web of Science, Scopus, Bireme/MedLine, and SciELO online databases were conducted for articles reporting the effects of CrossFit training. The systematic review followed the PRISMA guidelines. The Oxford Levels of Evidence was used for all included articles, and only studies that investigated the effects of CrossFit as a training program were included in the meta-analysis. For the meta-analysis, effect sizes (ESs) with 95% confidence interval (CI) were calculated and heterogeneity was assessed using a random-effects model. Thirty-one articles were included in the systematic review and four were included in the meta-analysis. However, only two studies had a high level of evidence at low risk of bias. Scientific literature related to CrossFit has reported on body composition, psycho-physiological parameters, musculoskeletal injury risk, life and health aspects, and psycho-social behavior. In the meta-analysis, significant results were not found for any variables. The current scientific literature related to CrossFit has few studies with high level of evidence at low risk of bias. However, preliminary data has suggested that CrossFit practice is associated with higher levels of sense of community, satisfaction, and motivation.

Using the Mixed Rasch Model to analyze data from the beliefs and attitudes about memory survey.

PubMed

Smith, Everett V; Ying, Yuping; Brown, Scott W

2012-01-01

In this study, we used the Mixed Rasch Model (MRM) to analyze data from the Beliefs and Attitudes About Memory Survey (BAMS; Brown, Garry, Silver, and Loftus, 1997). We used the original 5-point BAMS data to investigate the functioning of the "Neutral" category via threshold analysis under a 2-class MRM solution. The "Neutral" category was identified as not eliciting the model expected responses and observations in the "Neutral" category were subsequently treated as missing data. For the BAMS data without the "Neutral" category, exploratory MRM analyses specifying up to 5 latent classes were conducted to evaluate data-model fit using the consistent Akaike information criterion (CAIC). For each of three BAMS subscales, a two latent class solution was identified as fitting the mixed Rasch rating scale model the best. Results regarding threshold analysis, person parameters, and item fit based on the final models are presented and discussed as well as the implications of this study.

Evolution of flowering strategies in Oenothera glazioviana: an integral projection model approach.

PubMed Central

Rees, Mark; Rose, Karen E

2002-01-01

The timing of reproduction is a key determinant of fitness. Here, we develop parameterized integral projection models of size-related flowering for the monocarpic perennial Oenothera glazioviana and use these to predict the evolutionarily stable strategy (ESS) for flowering. For the most part there is excellent agreement between the model predictions and the results of quantitative field studies. However, the model predicts a much steeper relationship between plant size and the probability of flowering than observed in the field, indicating selection for a 'threshold size' flowering function. Elasticity and sensitivity analysis of population growth rate lambda and net reproductive rate R(0) are used to identify the critical traits that determine fitness and control the ESS for flowering. Using the fitted model we calculate the fitness landscape for invading genotypes and show that this is characterized by a ridge of approximately equal fitness. The implications of these results for the maintenance of genetic variation are discussed. PMID:12137582

Evolution of flowering strategies in Oenothera glazioviana: an integral projection model approach.

PubMed

Rees, Mark; Rose, Karen E

2002-07-22

The timing of reproduction is a key determinant of fitness. Here, we develop parameterized integral projection models of size-related flowering for the monocarpic perennial Oenothera glazioviana and use these to predict the evolutionarily stable strategy (ESS) for flowering. For the most part there is excellent agreement between the model predictions and the results of quantitative field studies. However, the model predicts a much steeper relationship between plant size and the probability of flowering than observed in the field, indicating selection for a 'threshold size' flowering function. Elasticity and sensitivity analysis of population growth rate lambda and net reproductive rate R(0) are used to identify the critical traits that determine fitness and control the ESS for flowering. Using the fitted model we calculate the fitness landscape for invading genotypes and show that this is characterized by a ridge of approximately equal fitness. The implications of these results for the maintenance of genetic variation are discussed.

Rapid Global Fitting of Large Fluorescence Lifetime Imaging Microscopy Datasets

PubMed Central

Warren, Sean C.; Margineanu, Anca; Alibhai, Dominic; Kelly, Douglas J.; Talbot, Clifford; Alexandrov, Yuriy; Munro, Ian; Katan, Matilda

2013-01-01

Fluorescence lifetime imaging (FLIM) is widely applied to obtain quantitative information from fluorescence signals, particularly using Förster Resonant Energy Transfer (FRET) measurements to map, for example, protein-protein interactions. Extracting FRET efficiencies or population fractions typically entails fitting data to complex fluorescence decay models but such experiments are frequently photon constrained, particularly for live cell or in vivo imaging, and this leads to unacceptable errors when analysing data on a pixel-wise basis. Lifetimes and population fractions may, however, be more robustly extracted using global analysis to simultaneously fit the fluorescence decay data of all pixels in an image or dataset to a multi-exponential model under the assumption that the lifetime components are invariant across the image (dataset). This approach is often considered to be prohibitively slow and/or computationally expensive but we present here a computationally efficient global analysis algorithm for the analysis of time-correlated single photon counting (TCSPC) or time-gated FLIM data based on variable projection. It makes efficient use of both computer processor and memory resources, requiring less than a minute to analyse time series and multiwell plate datasets with hundreds of FLIM images on standard personal computers. This lifetime analysis takes account of repetitive excitation, including fluorescence photons excited by earlier pulses contributing to the fit, and is able to accommodate time-varying backgrounds and instrument response functions. We demonstrate that this global approach allows us to readily fit time-resolved fluorescence data to complex models including a four-exponential model of a FRET system, for which the FRET efficiencies of the two species of a bi-exponential donor are linked, and polarisation-resolved lifetime data, where a fluorescence intensity and bi-exponential anisotropy decay model is applied to the analysis of live cell homo-FRET data. A software package implementing this algorithm, FLIMfit, is available under an open source licence through the Open Microscopy Environment. PMID:23940626

Compensation for Lithography Induced Process Variations during Physical Design

NASA Astrophysics Data System (ADS)

Chin, Eric Yiow-Bing

This dissertation addresses the challenge of designing robust integrated circuits in the deep sub micron regime in the presence of lithography process variability. By extending and combining existing process and circuit analysis techniques, flexible software frameworks are developed to provide detailed studies of circuit performance in the presence of lithography variations such as focus and exposure. Applications of these software frameworks to select circuits demonstrate the electrical impact of these variations and provide insight into variability aware compact models that capture the process dependent circuit behavior. These variability aware timing models abstract lithography variability from the process level to the circuit level and are used to estimate path level circuit performance with high accuracy with very little overhead in runtime. The Interconnect Variability Characterization (IVC) framework maps lithography induced geometrical variations at the interconnect level to electrical delay variations. This framework is applied to one dimensional repeater circuits patterned with both 90nm single patterning and 32nm double patterning technologies, under the presence of focus, exposure, and overlay variability. Studies indicate that single and double patterning layouts generally exhibit small variations in delay (between 1--3%) due to self compensating RC effects associated with dense layouts and overlay errors for layouts without self-compensating RC effects. The delay response of each double patterned interconnect structure is fit with a second order polynomial model with focus, exposure, and misalignment parameters with 12 coefficients and residuals of less than 0.1ps. The IVC framework is also applied to a repeater circuit with cascaded interconnect structures to emulate more complex layout scenarios, and it is observed that the variations on each segment average out to reduce the overall delay variation. The Standard Cell Variability Characterization (SCVC) framework advances existing layout-level lithography aware circuit analysis by extending it to cell-level applications utilizing a physically accurate approach that integrates process simulation, compact transistor models, and circuit simulation to characterize electrical cell behavior. This framework is applied to combinational and sequential cells in the Nangate 45nm Open Cell Library, and the timing response of these cells to lithography focus and exposure variations demonstrate Bossung like behavior. This behavior permits the process parameter dependent response to be captured in a nine term variability aware compact model based on Bossung fitting equations. For a two input NAND gate, the variability aware compact model captures the simulated response to an accuracy of 0.3%. The SCVC framework is also applied to investigate advanced process effects including misalignment and layout proximity. The abstraction of process variability from the layout level to the cell level opens up an entire new realm of circuit analysis and optimization and provides a foundation for path level variability analysis without the computationally expensive costs associated with joint process and circuit simulation. The SCVC framework is used with slight modification to illustrate the speedup and accuracy tradeoffs of using compact models. With variability aware compact models, the process dependent performance of a three stage logic circuit can be estimated to an accuracy of 0.7% with a speedup of over 50,000. Path level variability analysis also provides an accurate estimate (within 1%) of ring oscillator period in well under a second. Another significant advantage of variability aware compact models is that they can be easily incorporated into existing design methodologies for design optimization. This is demonstrated by applying cell swapping on a logic circuit to reduce the overall delay variability along a circuit path. By including these variability aware compact models in cell characterization libraries, design metrics such as circuit timing, power, area, and delay variability can be quickly assessed to optimize for the correct balance of all design metrics, including delay variability. Deterministic lithography variations can be easily captured using the variability aware compact models described in this dissertation. However, another prominent source of variability is random dopant fluctuations, which affect transistor threshold voltage and in turn circuit performance. The SCVC framework is utilized to investigate the interactions between deterministic lithography variations and random dopant fluctuations. Monte Carlo studies show that the output delay distribution in the presence of random dopant fluctuations is dependent on lithography focus and exposure conditions, with a 3.6 ps change in standard deviation across the focus exposure process window. This indicates that the electrical impact of random variations is dependent on systematic lithography variations, and this dependency should be included for precise analysis.

A study of the relationship between parental bonding, self-concept and eating disturbances in Norwegian and American college populations.

PubMed

Perry, Judith A; Silvera, David H; Neilands, Torsten B; Rosenvinge, Jan H; Hanssen, Tina

2008-01-01

This study investigated the relationship between bonding patterns and self-concept, and the influence of these constructs on a measure of sub-clinical eating disturbances. Undergraduate students from the United States (N=166) and Norway (N=233) were given self-report questionnaires that included measures of parental bonding, locus of control, self-concept clarity, self-esteem, and disturbed cognitions associated with eating. A structural equation model showed the expected pattern, with bonding predicting self-concept and self-concept predicting eating disturbances. The model fit equally well for samples from both countries and for both genders. This model links the pattern of low care and overprotective parental bonding indicators mediated through a self-concept defined by a lack of self-understanding, low self-esteem, and external locus of control to increased risk of eating disturbances for college aged men and women.

Optimization of isotherm models for pesticide sorption on biopolymer-nanoclay composite by error analysis.

PubMed

Narayanan, Neethu; Gupta, Suman; Gajbhiye, V T; Manjaiah, K M

2017-04-01

A carboxy methyl cellulose-nano organoclay (nano montmorillonite modified with 35-45 wt % dimethyl dialkyl (C 14 -C 18 ) amine (DMDA)) composite was prepared by solution intercalation method. The prepared composite was characterized by infrared spectroscopy (FTIR), X-Ray diffraction spectroscopy (XRD) and scanning electron microscopy (SEM). The composite was utilized for its pesticide sorption efficiency for atrazine, imidacloprid and thiamethoxam. The sorption data was fitted into Langmuir and Freundlich isotherms using linear and non linear methods. The linear regression method suggested best fitting of sorption data into Type II Langmuir and Freundlich isotherms. In order to avoid the bias resulting from linearization, seven different error parameters were also analyzed by non linear regression method. The non linear error analysis suggested that the sorption data fitted well into Langmuir model rather than in Freundlich model. The maximum sorption capacity, Q 0 (μg/g) was given by imidacloprid (2000) followed by thiamethoxam (1667) and atrazine (1429). The study suggests that the degree of determination of linear regression alone cannot be used for comparing the best fitting of Langmuir and Freundlich models and non-linear error analysis needs to be done to avoid inaccurate results. Copyright © 2017 Elsevier Ltd. All rights reserved.

Predictability of a Coupled Model of ENSO Using Singular Vector Analysis: Optimal Growth and Forecast Skill.

NASA Astrophysics Data System (ADS)

Xue, Yan

The optimal growth and its relationship with the forecast skill of the Zebiak and Cane model are studied using a simple statistical model best fit to the original nonlinear model and local linear tangent models about idealized climatic states (the mean background and ENSO cycles in a long model run), and the actual forecast states, including two sets of runs using two different initialization procedures. The seasonally varying Markov model best fit to a suite of 3-year forecasts in a reduced EOF space (18 EOFs) fits the original nonlinear model reasonably well and has comparable or better forecast skill. The initial error growth in a linear evolution operator A is governed by the eigenvalues of A^{T}A, and the square roots of eigenvalues and eigenvectors of A^{T}A are named singular values and singular vectors. One dominant growing singular vector is found, and the optimal 6 month growth rate is largest for a (boreal) spring start and smallest for a fall start. Most of the variation in the optimal growth rate of the two forecasts is seasonal, attributable to the seasonal variations in the mean background, except that in the cold events it is substantially suppressed. It is found that the mean background (zero anomaly) is the most unstable state, and the "forecast IC states" are more unstable than the "coupled model states". One dominant growing singular vector is found, characterized by north-south and east -west dipoles, convergent winds on the equator in the eastern Pacific and a deepened thermocline in the whole equatorial belt. This singular vector is insensitive to initial time and optimization time, but its final pattern is a strong function of initial states. The ENSO system is inherently unpredictable for the dominant singular vector can amplify 5-fold to 24-fold in 6 months and evolve into the large scales characteristic of ENSO. However, the inherent ENSO predictability is only a secondary factor, while the mismatches between the model and data is a primary factor controlling the current forecast skill.