Determinants of The Grade A Embryos in Infertile Women; Zero-Inflated Regression Model.

PubMed

Almasi-Hashiani, Amir; Ghaheri, Azadeh; Omani Samani, Reza

2017-10-01

In assisted reproductive technology, it is important to choose high quality embryos for embryo transfer. The aim of the present study was to determine the grade A embryo count and factors related to it in infertile women. This historical cohort study included 996 infertile women. The main outcome was the number of grade A embryos. Zero-Inflated Poisson (ZIP) regression and Zero-Inflated Negative Binomial (ZINB) regression were used to model the count data as it contained excessive zeros. Stata software, version 13 (Stata Corp, College Station, TX, USA) was used for all statistical analyses. After adjusting for potential confounders, results from the ZINB model show that for each unit increase in the number 2 pronuclear (2PN) zygotes, we get an increase of 1.45 times as incidence rate ratio (95% confidence interval (CI): 1.23-1.69, P=0.001) in the expected grade A embryo count number, and for each increase in the cleavage day we get a decrease 0.35 times (95% CI: 0.20-0.61, P=0.001) in expected grade A embryo count. There is a significant association between both the number of 2PN zygotes and cleavage day with the number of grade A embryos in both ZINB and ZIP regression models. The estimated coefficients are more plausible than values found in earlier studies using less relevant models. Copyright© by Royan Institute. All rights reserved.

Classifying next-generation sequencing data using a zero-inflated Poisson model.

PubMed

Zhou, Yan; Wan, Xiang; Zhang, Baoxue; Tong, Tiejun

2018-04-15

With the development of high-throughput techniques, RNA-sequencing (RNA-seq) is becoming increasingly popular as an alternative for gene expression analysis, such as RNAs profiling and classification. Identifying which type of diseases a new patient belongs to with RNA-seq data has been recognized as a vital problem in medical research. As RNA-seq data are discrete, statistical methods developed for classifying microarray data cannot be readily applied for RNA-seq data classification. Witten proposed a Poisson linear discriminant analysis (PLDA) to classify the RNA-seq data in 2011. Note, however, that the count datasets are frequently characterized by excess zeros in real RNA-seq or microRNA sequence data (i.e. when the sequence depth is not enough or small RNAs with the length of 18-30 nucleotides). Therefore, it is desired to develop a new model to analyze RNA-seq data with an excess of zeros. In this paper, we propose a Zero-Inflated Poisson Logistic Discriminant Analysis (ZIPLDA) for RNA-seq data with an excess of zeros. The new method assumes that the data are from a mixture of two distributions: one is a point mass at zero, and the other follows a Poisson distribution. We then consider a logistic relation between the probability of observing zeros and the mean of the genes and the sequencing depth in the model. Simulation studies show that the proposed method performs better than, or at least as well as, the existing methods in a wide range of settings. Two real datasets including a breast cancer RNA-seq dataset and a microRNA-seq dataset are also analyzed, and they coincide with the simulation results that our proposed method outperforms the existing competitors. The software is available at http://www.math.hkbu.edu.hk/∼tongt. xwan@comp.hkbu.edu.hk or tongt@hkbu.edu.hk. Supplementary data are available at Bioinformatics online.

Zero-Inflated Poisson Modeling of Fall Risk Factors in Community-Dwelling Older Adults.

PubMed

Jung, Dukyoo; Kang, Younhee; Kim, Mi Young; Ma, Rye-Won; Bhandari, Pratibha

2016-02-01

The aim of this study was to identify risk factors for falls among community-dwelling older adults. The study used a cross-sectional descriptive design. Self-report questionnaires were used to collect data from 658 community-dwelling older adults and were analyzed using logistic and zero-inflated Poisson (ZIP) regression. Perceived health status was a significant factor in the count model, and fall efficacy emerged as a significant predictor in the logistic models. The findings suggest that fall efficacy is important for predicting not only faller and nonfaller status but also fall counts in older adults who may or may not have experienced a previous fall. The fall predictors identified in this study--perceived health status and fall efficacy--indicate the need for fall-prevention programs tailored to address both the physical and psychological issues unique to older adults. © The Author(s) 2014.

IRT-ZIP Modeling for Multivariate Zero-Inflated Count Data

ERIC Educational Resources Information Center

Wang, Lijuan

2010-01-01

This study introduces an item response theory-zero-inflated Poisson (IRT-ZIP) model to investigate psychometric properties of multiple items and predict individuals' latent trait scores for multivariate zero-inflated count data. In the model, two link functions are used to capture two processes of the zero-inflated count data. Item parameters are…

Modeling health survey data with excessive zero and K responses.

PubMed

Lin, Ting Hsiang; Tsai, Min-Hsiao

2013-04-30

Zero-inflated Poisson regression is a popular tool used to analyze data with excessive zeros. Although much work has already been performed to fit zero-inflated data, most models heavily depend on special features of the individual data. To be specific, this means that there is a sizable group of respondents who endorse the same answers making the data have peaks. In this paper, we propose a new model with the flexibility to model excessive counts other than zero, and the model is a mixture of multinomial logistic and Poisson regression, in which the multinomial logistic component models the occurrence of excessive counts, including zeros, K (where K is a positive integer) and all other values. The Poisson regression component models the counts that are assumed to follow a Poisson distribution. Two examples are provided to illustrate our models when the data have counts containing many ones and sixes. As a result, the zero-inflated and K-inflated models exhibit a better fit than the zero-inflated Poisson and standard Poisson regressions. Copyright © 2012 John Wiley & Sons, Ltd.

Growth Curve Models for Zero-Inflated Count Data: An Application to Smoking Behavior

ERIC Educational Resources Information Center

Liu, Hui; Powers, Daniel A.

2007-01-01

This article applies growth curve models to longitudinal count data characterized by an excess of zero counts. We discuss a zero-inflated Poisson regression model for longitudinal data in which the impact of covariates on the initial counts and the rate of change in counts over time is the focus of inference. Basic growth curve models using a…

Semiparametric bivariate zero-inflated Poisson models with application to studies of abundance for multiple species

USGS Publications Warehouse

Arab, Ali; Holan, Scott H.; Wikle, Christopher K.; Wildhaber, Mark L.

2012-01-01

Ecological studies involving counts of abundance, presence–absence or occupancy rates often produce data having a substantial proportion of zeros. Furthermore, these types of processes are typically multivariate and only adequately described by complex nonlinear relationships involving externally measured covariates. Ignoring these aspects of the data and implementing standard approaches can lead to models that fail to provide adequate scientific understanding of the underlying ecological processes, possibly resulting in a loss of inferential power. One method of dealing with data having excess zeros is to consider the class of univariate zero-inflated generalized linear models. However, this class of models fails to address the multivariate and nonlinear aspects associated with the data usually encountered in practice. Therefore, we propose a semiparametric bivariate zero-inflated Poisson model that takes into account both of these data attributes. The general modeling framework is hierarchical Bayes and is suitable for a broad range of applications. We demonstrate the effectiveness of our model through a motivating example on modeling catch per unit area for multiple species using data from the Missouri River Benthic Fishes Study, implemented by the United States Geological Survey.

Mapping species abundance by a spatial zero-inflated Poisson model: a case study in the Wadden Sea, the Netherlands.

PubMed

Lyashevska, Olga; Brus, Dick J; van der Meer, Jaap

2016-01-01

The objective of the study was to provide a general procedure for mapping species abundance when data are zero-inflated and spatially correlated counts. The bivalve species Macoma balthica was observed on a 500×500 m grid in the Dutch part of the Wadden Sea. In total, 66% of the 3451 counts were zeros. A zero-inflated Poisson mixture model was used to relate counts to environmental covariates. Two models were considered, one with relatively fewer covariates (model "small") than the other (model "large"). The models contained two processes: a Bernoulli (species prevalence) and a Poisson (species intensity, when the Bernoulli process predicts presence). The model was used to make predictions for sites where only environmental data are available. Predicted prevalences and intensities show that the model "small" predicts lower mean prevalence and higher mean intensity, than the model "large". Yet, the product of prevalence and intensity, which might be called the unconditional intensity, is very similar. Cross-validation showed that the model "small" performed slightly better, but the difference was small. The proposed methodology might be generally applicable, but is computer intensive.

A review and comparison of Bayesian and likelihood-based inferences in beta regression and zero-or-one-inflated beta regression.

PubMed

Liu, Fang; Eugenio, Evercita C

2018-04-01

Beta regression is an increasingly popular statistical technique in medical research for modeling of outcomes that assume values in (0, 1), such as proportions and patient reported outcomes. When outcomes take values in the intervals [0,1), (0,1], or [0,1], zero-or-one-inflated beta (zoib) regression can be used. We provide a thorough review on beta regression and zoib regression in the modeling, inferential, and computational aspects via the likelihood-based and Bayesian approaches. We demonstrate the statistical and practical importance of correctly modeling the inflation at zero/one rather than ad hoc replacing them with values close to zero/one via simulation studies; the latter approach can lead to biased estimates and invalid inferences. We show via simulation studies that the likelihood-based approach is computationally faster in general than MCMC algorithms used in the Bayesian inferences, but runs the risk of non-convergence, large biases, and sensitivity to starting values in the optimization algorithm especially with clustered/correlated data, data with sparse inflation at zero and one, and data that warrant regularization of the likelihood. The disadvantages of the regular likelihood-based approach make the Bayesian approach an attractive alternative in these cases. Software packages and tools for fitting beta and zoib regressions in both the likelihood-based and Bayesian frameworks are also reviewed.

New variable selection methods for zero-inflated count data with applications to the substance abuse field

PubMed Central

Buu, Anne; Johnson, Norman J.; Li, Runze; Tan, Xianming

2011-01-01

Zero-inflated count data are very common in health surveys. This study develops new variable selection methods for the zero-inflated Poisson regression model. Our simulations demonstrate the negative consequences which arise from the ignorance of zero-inflation. Among the competing methods, the one-step SCAD method is recommended because it has the highest specificity, sensitivity, exact fit, and lowest estimation error. The design of the simulations is based on the special features of two large national databases commonly used in the alcoholism and substance abuse field so that our findings can be easily generalized to the real settings. Applications of the methodology are demonstrated by empirical analyses on the data from a well-known alcohol study. PMID:21563207

Variable selection for distribution-free models for longitudinal zero-inflated count responses.

PubMed

Chen, Tian; Wu, Pan; Tang, Wan; Zhang, Hui; Feng, Changyong; Kowalski, Jeanne; Tu, Xin M

2016-07-20

Zero-inflated count outcomes arise quite often in research and practice. Parametric models such as the zero-inflated Poisson and zero-inflated negative binomial are widely used to model such responses. Like most parametric models, they are quite sensitive to departures from assumed distributions. Recently, new approaches have been proposed to provide distribution-free, or semi-parametric, alternatives. These methods extend the generalized estimating equations to provide robust inference for population mixtures defined by zero-inflated count outcomes. In this paper, we propose methods to extend smoothly clipped absolute deviation (SCAD)-based variable selection methods to these new models. Variable selection has been gaining popularity in modern clinical research studies, as determining differential treatment effects of interventions for different subgroups has become the norm, rather the exception, in the era of patent-centered outcome research. Such moderation analysis in general creates many explanatory variables in regression analysis, and the advantages of SCAD-based methods over their traditional counterparts render them a great choice for addressing this important and timely issues in clinical research. We illustrate the proposed approach with both simulated and real study data. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Functional linear models for zero-inflated count data with application to modeling hospitalizations in patients on dialysis.

PubMed

Sentürk, Damla; Dalrymple, Lorien S; Nguyen, Danh V

2014-11-30

We propose functional linear models for zero-inflated count data with a focus on the functional hurdle and functional zero-inflated Poisson (ZIP) models. Although the hurdle model assumes the counts come from a mixture of a degenerate distribution at zero and a zero-truncated Poisson distribution, the ZIP model considers a mixture of a degenerate distribution at zero and a standard Poisson distribution. We extend the generalized functional linear model framework with a functional predictor and multiple cross-sectional predictors to model counts generated by a mixture distribution. We propose an estimation procedure for functional hurdle and ZIP models, called penalized reconstruction, geared towards error-prone and sparsely observed longitudinal functional predictors. The approach relies on dimension reduction and pooling of information across subjects involving basis expansions and penalized maximum likelihood techniques. The developed functional hurdle model is applied to modeling hospitalizations within the first 2 years from initiation of dialysis, with a high percentage of zeros, in the Comprehensive Dialysis Study participants. Hospitalization counts are modeled as a function of sparse longitudinal measurements of serum albumin concentrations, patient demographics, and comorbidities. Simulation studies are used to study finite sample properties of the proposed method and include comparisons with an adaptation of standard principal components regression. Copyright © 2014 John Wiley & Sons, Ltd.

Full Bayes Poisson gamma, Poisson lognormal, and zero inflated random effects models: Comparing the precision of crash frequency estimates.

PubMed

Aguero-Valverde, Jonathan

2013-01-01

In recent years, complex statistical modeling approaches have being proposed to handle the unobserved heterogeneity and the excess of zeros frequently found in crash data, including random effects and zero inflated models. This research compares random effects, zero inflated, and zero inflated random effects models using a full Bayes hierarchical approach. The models are compared not just in terms of goodness-of-fit measures but also in terms of precision of posterior crash frequency estimates since the precision of these estimates is vital for ranking of sites for engineering improvement. Fixed-over-time random effects models are also compared to independent-over-time random effects models. For the crash dataset being analyzed, it was found that once the random effects are included in the zero inflated models, the probability of being in the zero state is drastically reduced, and the zero inflated models degenerate to their non zero inflated counterparts. Also by fixing the random effects over time the fit of the models and the precision of the crash frequency estimates are significantly increased. It was found that the rankings of the fixed-over-time random effects models are very consistent among them. In addition, the results show that by fixing the random effects over time, the standard errors of the crash frequency estimates are significantly reduced for the majority of the segments on the top of the ranking. Copyright © 2012 Elsevier Ltd. All rights reserved.

Zero-inflated count models for longitudinal measurements with heterogeneous random effects.

PubMed

Zhu, Huirong; Luo, Sheng; DeSantis, Stacia M

2017-08-01

Longitudinal zero-inflated count data arise frequently in substance use research when assessing the effects of behavioral and pharmacological interventions. Zero-inflated count models (e.g. zero-inflated Poisson or zero-inflated negative binomial) with random effects have been developed to analyze this type of data. In random effects zero-inflated count models, the random effects covariance matrix is typically assumed to be homogeneous (constant across subjects). However, in many situations this matrix may be heterogeneous (differ by measured covariates). In this paper, we extend zero-inflated count models to account for random effects heterogeneity by modeling their variance as a function of covariates. We show via simulation that ignoring intervention and covariate-specific heterogeneity can produce biased estimates of covariate and random effect estimates. Moreover, those biased estimates can be rectified by correctly modeling the random effects covariance structure. The methodological development is motivated by and applied to the Combined Pharmacotherapies and Behavioral Interventions for Alcohol Dependence (COMBINE) study, the largest clinical trial of alcohol dependence performed in United States with 1383 individuals.

EM Adaptive LASSO—A Multilocus Modeling Strategy for Detecting SNPs Associated with Zero-inflated Count Phenotypes

PubMed Central

Mallick, Himel; Tiwari, Hemant K.

2016-01-01

Count data are increasingly ubiquitous in genetic association studies, where it is possible to observe excess zero counts as compared to what is expected based on standard assumptions. For instance, in rheumatology, data are usually collected in multiple joints within a person or multiple sub-regions of a joint, and it is not uncommon that the phenotypes contain enormous number of zeroes due to the presence of excessive zero counts in majority of patients. Most existing statistical methods assume that the count phenotypes follow one of these four distributions with appropriate dispersion-handling mechanisms: Poisson, Zero-inflated Poisson (ZIP), Negative Binomial, and Zero-inflated Negative Binomial (ZINB). However, little is known about their implications in genetic association studies. Also, there is a relative paucity of literature on their usefulness with respect to model misspecification and variable selection. In this article, we have investigated the performance of several state-of-the-art approaches for handling zero-inflated count data along with a novel penalized regression approach with an adaptive LASSO penalty, by simulating data under a variety of disease models and linkage disequilibrium patterns. By taking into account data-adaptive weights in the estimation procedure, the proposed method provides greater flexibility in multi-SNP modeling of zero-inflated count phenotypes. A fast coordinate descent algorithm nested within an EM (expectation-maximization) algorithm is implemented for estimating the model parameters and conducting variable selection simultaneously. Results show that the proposed method has optimal performance in the presence of multicollinearity, as measured by both prediction accuracy and empirical power, which is especially apparent as the sample size increases. Moreover, the Type I error rates become more or less uncontrollable for the competing methods when a model is misspecified, a phenomenon routinely encountered in practice

EM Adaptive LASSO-A Multilocus Modeling Strategy for Detecting SNPs Associated with Zero-inflated Count Phenotypes.

PubMed

Mallick, Himel; Tiwari, Hemant K

2016-01-01

Count data are increasingly ubiquitous in genetic association studies, where it is possible to observe excess zero counts as compared to what is expected based on standard assumptions. For instance, in rheumatology, data are usually collected in multiple joints within a person or multiple sub-regions of a joint, and it is not uncommon that the phenotypes contain enormous number of zeroes due to the presence of excessive zero counts in majority of patients. Most existing statistical methods assume that the count phenotypes follow one of these four distributions with appropriate dispersion-handling mechanisms: Poisson, Zero-inflated Poisson (ZIP), Negative Binomial, and Zero-inflated Negative Binomial (ZINB). However, little is known about their implications in genetic association studies. Also, there is a relative paucity of literature on their usefulness with respect to model misspecification and variable selection. In this article, we have investigated the performance of several state-of-the-art approaches for handling zero-inflated count data along with a novel penalized regression approach with an adaptive LASSO penalty, by simulating data under a variety of disease models and linkage disequilibrium patterns. By taking into account data-adaptive weights in the estimation procedure, the proposed method provides greater flexibility in multi-SNP modeling of zero-inflated count phenotypes. A fast coordinate descent algorithm nested within an EM (expectation-maximization) algorithm is implemented for estimating the model parameters and conducting variable selection simultaneously. Results show that the proposed method has optimal performance in the presence of multicollinearity, as measured by both prediction accuracy and empirical power, which is especially apparent as the sample size increases. Moreover, the Type I error rates become more or less uncontrollable for the competing methods when a model is misspecified, a phenomenon routinely encountered in practice.

Modeling Zero-Inflated and Overdispersed Count Data: An Empirical Study of School Suspensions

ERIC Educational Resources Information Center

Desjardins, Christopher David

2016-01-01

The purpose of this article is to develop a statistical model that best explains variability in the number of school days suspended. Number of school days suspended is a count variable that may be zero-inflated and overdispersed relative to a Poisson model. Four models were examined: Poisson, negative binomial, Poisson hurdle, and negative…

A new multivariate zero-adjusted Poisson model with applications to biomedicine.

PubMed

Liu, Yin; Tian, Guo-Liang; Tang, Man-Lai; Yuen, Kam Chuen

2018-05-25

Recently, although advances were made on modeling multivariate count data, existing models really has several limitations: (i) The multivariate Poisson log-normal model (Aitchison and Ho, ) cannot be used to fit multivariate count data with excess zero-vectors; (ii) The multivariate zero-inflated Poisson (ZIP) distribution (Li et al., 1999) cannot be used to model zero-truncated/deflated count data and it is difficult to apply to high-dimensional cases; (iii) The Type I multivariate zero-adjusted Poisson (ZAP) distribution (Tian et al., 2017) could only model multivariate count data with a special correlation structure for random components that are all positive or negative. In this paper, we first introduce a new multivariate ZAP distribution, based on a multivariate Poisson distribution, which allows the correlations between components with a more flexible dependency structure, that is some of the correlation coefficients could be positive while others could be negative. We then develop its important distributional properties, and provide efficient statistical inference methods for multivariate ZAP model with or without covariates. Two real data examples in biomedicine are used to illustrate the proposed methods. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Cumulative sum control charts for monitoring geometrically inflated Poisson processes: An application to infectious disease counts data.

PubMed

Rakitzis, Athanasios C; Castagliola, Philippe; Maravelakis, Petros E

2018-02-01

In this work, we study upper-sided cumulative sum control charts that are suitable for monitoring geometrically inflated Poisson processes. We assume that a process is properly described by a two-parameter extension of the zero-inflated Poisson distribution, which can be used for modeling count data with an excessive number of zero and non-zero values. Two different upper-sided cumulative sum-type schemes are considered, both suitable for the detection of increasing shifts in the average of the process. Aspects of their statistical design are discussed and their performance is compared under various out-of-control situations. Changes in both parameters of the process are considered. Finally, the monitoring of the monthly cases of poliomyelitis in the USA is given as an illustrative example.

Conditional modeling of antibody titers using a zero-inflated poisson random effects model: application to Fabrazyme.

PubMed

Bonate, Peter L; Sung, Crystal; Welch, Karen; Richards, Susan

2009-10-01

Patients that are exposed to biotechnology-derived therapeutics often develop antibodies to the therapeutic, the magnitude of which is assessed by measuring antibody titers. A statistical approach for analyzing antibody titer data conditional on seroconversion is presented. The proposed method is to first transform the antibody titer data based on a geometric series using a common ratio of 2 and a scale factor of 50 and then analyze the exponent using a zero-inflated or hurdle model assuming a Poisson or negative binomial distribution with random effects to account for patient heterogeneity. Patient specific covariates can be used to model the probability of developing an antibody response, i.e., seroconversion, as well as the magnitude of the antibody titer itself. The method was illustrated using antibody titer data from 87 male seroconverted Fabry patients receiving Fabrazyme. Titers from five clinical trials were collected over 276 weeks of therapy with anti-Fabrazyme IgG titers ranging from 100 to 409,600 after exclusion of seronegative patients. The best model to explain seroconversion was a zero-inflated Poisson (ZIP) model where cumulative dose (under a constant dose regimen of dosing every 2 weeks) influenced the probability of seroconversion. There was an 80% chance of seroconversion when the cumulative dose reached 210 mg (90% confidence interval: 194-226 mg). No difference in antibody titers was noted between Japanese or Western patients. Once seroconverted, antibody titers did not remain constant but decreased in an exponential manner from an initial magnitude to a new lower steady-state value. The expected titer after the new steady-state titer had been achieved was 870 (90% CI: 630-1109). The half-life to the new steady-state value after seroconversion was 44 weeks (90% CI: 17-70 weeks). Time to seroconversion did not appear to be correlated with titer at the time of seroconversion. The method can be adequately used to model antibody titer data.

Some findings on zero-inflated and hurdle poisson models for disease mapping.

PubMed

Corpas-Burgos, Francisca; García-Donato, Gonzalo; Martinez-Beneito, Miguel A

2018-05-27

Zero excess in the study of geographically referenced mortality data sets has been the focus of considerable attention in the literature, with zero-inflation being the most common procedure to handle this lack of fit. Although hurdle models have also been used in disease mapping studies, their use is more rare. We show in this paper that models using particular treatments of zero excesses are often required for achieving appropriate fits in regular mortality studies since, otherwise, geographical units with low expected counts are oversmoothed. However, as also shown, an indiscriminate treatment of zero excess may be unnecessary and has a problematic implementation. In this regard, we find that naive zero-inflation and hurdle models, without an explicit modeling of the probabilities of zeroes, do not fix zero excesses problems well enough and are clearly unsatisfactory. Results sharply suggest the need for an explicit modeling of the probabilities that should vary across areal units. Unfortunately, these more flexible modeling strategies can easily lead to improper posterior distributions as we prove in several theoretical results. Those procedures have been repeatedly used in the disease mapping literature, and one should bear these issues in mind in order to propose valid models. We finally propose several valid modeling alternatives according to the results mentioned that are suitable for fitting zero excesses. We show that those proposals fix zero excesses problems and correct the mentioned oversmoothing of risks in low populated units depicting geographic patterns more suited to the data. Copyright © 2018 John Wiley & Sons, Ltd.

Applying the zero-inflated Poisson model with random effects to detect abnormal rises in school absenteeism indicating infectious diseases outbreak.

PubMed

Song, X X; Zhao, Q; Tao, T; Zhou, C M; Diwan, V K; Xu, B

2018-05-30

Records of absenteeism from primary schools are valuable data for infectious diseases surveillance. However, the analysis of the absenteeism is complicated by the data features of clustering at zero, non-independence and overdispersion. This study aimed to generate an appropriate model to handle the absenteeism data collected in a European Commission granted project for infectious disease surveillance in rural China and to evaluate the validity and timeliness of the resulting model for early warnings of infectious disease outbreak. Four steps were taken: (1) building a 'well-fitting' model by the zero-inflated Poisson model with random effects (ZIP-RE) using the absenteeism data from the first implementation year; (2) applying the resulting model to predict the 'expected' number of absenteeism events in the second implementation year; (3) computing the differences between the observations and the expected values (O-E values) to generate an alternative series of data; (4) evaluating the early warning validity and timeliness of the observational data and model-based O-E values via the EARS-3C algorithms with regard to the detection of real cluster events. The results indicate that ZIP-RE and its corresponding O-E values could improve the detection of aberrations, reduce the false-positive signals and are applicable to the zero-inflated data.

Hurdle models for multilevel zero-inflated data via h-likelihood.

PubMed

Molas, Marek; Lesaffre, Emmanuel

2010-12-30

Count data often exhibit overdispersion. One type of overdispersion arises when there is an excess of zeros in comparison with the standard Poisson distribution. Zero-inflated Poisson and hurdle models have been proposed to perform a valid likelihood-based analysis to account for the surplus of zeros. Further, data often arise in clustered, longitudinal or multiple-membership settings. The proper analysis needs to reflect the design of a study. Typically random effects are used to account for dependencies in the data. We examine the h-likelihood estimation and inference framework for hurdle models with random effects for complex designs. We extend the h-likelihood procedures to fit hurdle models, thereby extending h-likelihood to truncated distributions. Two applications of the methodology are presented. Copyright © 2010 John Wiley & Sons, Ltd.

Understanding poisson regression.

PubMed

Hayat, Matthew J; Higgins, Melinda

2014-04-01

Nurse investigators often collect study data in the form of counts. Traditional methods of data analysis have historically approached analysis of count data either as if the count data were continuous and normally distributed or with dichotomization of the counts into the categories of occurred or did not occur. These outdated methods for analyzing count data have been replaced with more appropriate statistical methods that make use of the Poisson probability distribution, which is useful for analyzing count data. The purpose of this article is to provide an overview of the Poisson distribution and its use in Poisson regression. Assumption violations for the standard Poisson regression model are addressed with alternative approaches, including addition of an overdispersion parameter or negative binomial regression. An illustrative example is presented with an application from the ENSPIRE study, and regression modeling of comorbidity data is included for illustrative purposes. Copyright 2014, SLACK Incorporated.

On performance of parametric and distribution-free models for zero-inflated and over-dispersed count responses.

PubMed

Tang, Wan; Lu, Naiji; Chen, Tian; Wang, Wenjuan; Gunzler, Douglas David; Han, Yu; Tu, Xin M

2015-10-30

Zero-inflated Poisson (ZIP) and negative binomial (ZINB) models are widely used to model zero-inflated count responses. These models extend the Poisson and negative binomial (NB) to address excessive zeros in the count response. By adding a degenerate distribution centered at 0 and interpreting it as describing a non-risk group in the population, the ZIP (ZINB) models a two-component population mixture. As in applications of Poisson and NB, the key difference between ZIP and ZINB is the allowance for overdispersion by the ZINB in its NB component in modeling the count response for the at-risk group. Overdispersion arising in practice too often does not follow the NB, and applications of ZINB to such data yield invalid inference. If sources of overdispersion are known, other parametric models may be used to directly model the overdispersion. Such models too are subject to assumed distributions. Further, this approach may not be applicable if information about the sources of overdispersion is unavailable. In this paper, we propose a distribution-free alternative and compare its performance with these popular parametric models as well as a moment-based approach proposed by Yu et al. [Statistics in Medicine 2013; 32: 2390-2405]. Like the generalized estimating equations, the proposed approach requires no elaborate distribution assumptions. Compared with the approach of Yu et al., it is more robust to overdispersed zero-inflated responses. We illustrate our approach with both simulated and real study data. Copyright © 2015 John Wiley & Sons, Ltd.

Analyzing Propensity Matched Zero-Inflated Count Outcomes in Observational Studies

PubMed Central

DeSantis, Stacia M.; Lazaridis, Christos; Ji, Shuang; Spinale, Francis G.

2013-01-01

Determining the effectiveness of different treatments from observational data, which are characterized by imbalance between groups due to lack of randomization, is challenging. Propensity matching is often used to rectify imbalances among prognostic variables. However, there are no guidelines on how appropriately to analyze group matched data when the outcome is a zero inflated count. In addition, there is debate over whether to account for correlation of responses induced by matching, and/or whether to adjust for variables used in generating the propensity score in the final analysis. The aim of this research is to compare covariate unadjusted and adjusted zero-inflated Poisson models that do and do not account for the correlation. A simulation study is conducted, demonstrating that it is necessary to adjust for potential residual confounding, but that accounting for correlation is less important. The methods are applied to a biomedical research data set. PMID:24298197

Spatiotemporal hurdle models for zero-inflated count data: Exploring trends in emergency department visits.

PubMed

Neelon, Brian; Chang, Howard H; Ling, Qiang; Hastings, Nicole S

2016-12-01

Motivated by a study exploring spatiotemporal trends in emergency department use, we develop a class of two-part hurdle models for the analysis of zero-inflated areal count data. The models consist of two components-one for the probability of any emergency department use and one for the number of emergency department visits given use. Through a hierarchical structure, the models incorporate both patient- and region-level predictors, as well as spatially and temporally correlated random effects for each model component. The random effects are assigned multivariate conditionally autoregressive priors, which induce dependence between the components and provide spatial and temporal smoothing across adjacent spatial units and time periods, resulting in improved inferences. To accommodate potential overdispersion, we consider a range of parametric specifications for the positive counts, including truncated negative binomial and generalized Poisson distributions. We adopt a Bayesian inferential approach, and posterior computation is handled conveniently within standard Bayesian software. Our results indicate that the negative binomial and generalized Poisson hurdle models vastly outperform the Poisson hurdle model, demonstrating that overdispersed hurdle models provide a useful approach to analyzing zero-inflated spatiotemporal data. © The Author(s) 2014.

Marginalized multilevel hurdle and zero-inflated models for overdispersed and correlated count data with excess zeros.

PubMed

Kassahun, Wondwosen; Neyens, Thomas; Molenberghs, Geert; Faes, Christel; Verbeke, Geert

2014-11-10

Count data are collected repeatedly over time in many applications, such as biology, epidemiology, and public health. Such data are often characterized by the following three features. First, correlation due to the repeated measures is usually accounted for using subject-specific random effects, which are assumed to be normally distributed. Second, the sample variance may exceed the mean, and hence, the theoretical mean-variance relationship is violated, leading to overdispersion. This is usually allowed for based on a hierarchical approach, combining a Poisson model with gamma distributed random effects. Third, an excess of zeros beyond what standard count distributions can predict is often handled by either the hurdle or the zero-inflated model. A zero-inflated model assumes two processes as sources of zeros and combines a count distribution with a discrete point mass as a mixture, while the hurdle model separately handles zero observations and positive counts, where then a truncated-at-zero count distribution is used for the non-zero state. In practice, however, all these three features can appear simultaneously. Hence, a modeling framework that incorporates all three is necessary, and this presents challenges for the data analysis. Such models, when conditionally specified, will naturally have a subject-specific interpretation. However, adopting their purposefully modified marginalized versions leads to a direct marginal or population-averaged interpretation for parameter estimates of covariate effects, which is the primary interest in many applications. In this paper, we present a marginalized hurdle model and a marginalized zero-inflated model for correlated and overdispersed count data with excess zero observations and then illustrate these further with two case studies. The first dataset focuses on the Anopheles mosquito density around a hydroelectric dam, while adolescents' involvement in work, to earn money and support their families or themselves, is

Marginalized zero-altered models for longitudinal count data.

PubMed

Tabb, Loni Philip; Tchetgen, Eric J Tchetgen; Wellenius, Greg A; Coull, Brent A

2016-10-01

Count data often exhibit more zeros than predicted by common count distributions like the Poisson or negative binomial. In recent years, there has been considerable interest in methods for analyzing zero-inflated count data in longitudinal or other correlated data settings. A common approach has been to extend zero-inflated Poisson models to include random effects that account for correlation among observations. However, these models have been shown to have a few drawbacks, including interpretability of regression coefficients and numerical instability of fitting algorithms even when the data arise from the assumed model. To address these issues, we propose a model that parameterizes the marginal associations between the count outcome and the covariates as easily interpretable log relative rates, while including random effects to account for correlation among observations. One of the main advantages of this marginal model is that it allows a basis upon which we can directly compare the performance of standard methods that ignore zero inflation with that of a method that explicitly takes zero inflation into account. We present simulations of these various model formulations in terms of bias and variance estimation. Finally, we apply the proposed approach to analyze toxicological data of the effect of emissions on cardiac arrhythmias.

Marginalized zero-altered models for longitudinal count data

PubMed Central

Tabb, Loni Philip; Tchetgen, Eric J. Tchetgen; Wellenius, Greg A.; Coull, Brent A.

2015-01-01

Count data often exhibit more zeros than predicted by common count distributions like the Poisson or negative binomial. In recent years, there has been considerable interest in methods for analyzing zero-inflated count data in longitudinal or other correlated data settings. A common approach has been to extend zero-inflated Poisson models to include random effects that account for correlation among observations. However, these models have been shown to have a few drawbacks, including interpretability of regression coefficients and numerical instability of fitting algorithms even when the data arise from the assumed model. To address these issues, we propose a model that parameterizes the marginal associations between the count outcome and the covariates as easily interpretable log relative rates, while including random effects to account for correlation among observations. One of the main advantages of this marginal model is that it allows a basis upon which we can directly compare the performance of standard methods that ignore zero inflation with that of a method that explicitly takes zero inflation into account. We present simulations of these various model formulations in terms of bias and variance estimation. Finally, we apply the proposed approach to analyze toxicological data of the effect of emissions on cardiac arrhythmias. PMID:27867423

Distribution-free Inference of Zero-inated Binomial Data for Longitudinal Studies.

PubMed

He, H; Wang, W J; Hu, J; Gallop, R; Crits-Christoph, P; Xia, Y L

2015-10-01

Count reponses with structural zeros are very common in medical and psychosocial research, especially in alcohol and HIV research, and the zero-inflated poisson (ZIP) and zero-inflated negative binomial (ZINB) models are widely used for modeling such outcomes. However, as alcohol drinking outcomes such as days of drinkings are counts within a given period, their distributions are bounded above by an upper limit (total days in the period) and thus inherently follow a binomial or zero-inflated binomial (ZIB) distribution, rather than a Poisson or zero-inflated Poisson (ZIP) distribution, in the presence of structural zeros. In this paper, we develop a new semiparametric approach for modeling zero-inflated binomial (ZIB)-like count responses for cross-sectional as well as longitudinal data. We illustrate this approach with both simulated and real study data.

Modified Regression Correlation Coefficient for Poisson Regression Model

NASA Astrophysics Data System (ADS)

Kaengthong, Nattacha; Domthong, Uthumporn

2017-09-01

This study gives attention to indicators in predictive power of the Generalized Linear Model (GLM) which are widely used; however, often having some restrictions. We are interested in regression correlation coefficient for a Poisson regression model. This is a measure of predictive power, and defined by the relationship between the dependent variable (Y) and the expected value of the dependent variable given the independent variables [E(Y|X)] for the Poisson regression model. The dependent variable is distributed as Poisson. The purpose of this research was modifying regression correlation coefficient for Poisson regression model. We also compare the proposed modified regression correlation coefficient with the traditional regression correlation coefficient in the case of two or more independent variables, and having multicollinearity in independent variables. The result shows that the proposed regression correlation coefficient is better than the traditional regression correlation coefficient based on Bias and the Root Mean Square Error (RMSE).

Zero-inflated spatio-temporal models for disease mapping.

PubMed

Torabi, Mahmoud

2017-05-01

In this paper, our aim is to analyze geographical and temporal variability of disease incidence when spatio-temporal count data have excess zeros. To that end, we consider random effects in zero-inflated Poisson models to investigate geographical and temporal patterns of disease incidence. Spatio-temporal models that employ conditionally autoregressive smoothing across the spatial dimension and B-spline smoothing over the temporal dimension are proposed. The analysis of these complex models is computationally difficult from the frequentist perspective. On the other hand, the advent of the Markov chain Monte Carlo algorithm has made the Bayesian analysis of complex models computationally convenient. Recently developed data cloning method provides a frequentist approach to mixed models that is also computationally convenient. We propose to use data cloning, which yields to maximum likelihood estimation, to conduct frequentist analysis of zero-inflated spatio-temporal modeling of disease incidence. One of the advantages of the data cloning approach is that the prediction and corresponding standard errors (or prediction intervals) of smoothing disease incidence over space and time is easily obtained. We illustrate our approach using a real dataset of monthly children asthma visits to hospital in the province of Manitoba, Canada, during the period April 2006 to March 2010. Performance of our approach is also evaluated through a simulation study. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Statistical Models for the Analysis of Zero-Inflated Pain Intensity Numeric Rating Scale Data.

PubMed

Goulet, Joseph L; Buta, Eugenia; Bathulapalli, Harini; Gueorguieva, Ralitza; Brandt, Cynthia A

2017-03-01

Pain intensity is often measured in clinical and research settings using the 0 to 10 numeric rating scale (NRS). NRS scores are recorded as discrete values, and in some samples they may display a high proportion of zeroes and a right-skewed distribution. Despite this, statistical methods for normally distributed data are frequently used in the analysis of NRS data. We present results from an observational cross-sectional study examining the association of NRS scores with patient characteristics using data collected from a large cohort of 18,935 veterans in Department of Veterans Affairs care diagnosed with a potentially painful musculoskeletal disorder. The mean (variance) NRS pain was 3.0 (7.5), and 34% of patients reported no pain (NRS = 0). We compared the following statistical models for analyzing NRS scores: linear regression, generalized linear models (Poisson and negative binomial), zero-inflated and hurdle models for data with an excess of zeroes, and a cumulative logit model for ordinal data. We examined model fit, interpretability of results, and whether conclusions about the predictor effects changed across models. In this study, models that accommodate zero inflation provided a better fit than the other models. These models should be considered for the analysis of NRS data with a large proportion of zeroes. We examined and analyzed pain data from a large cohort of veterans with musculoskeletal disorders. We found that many reported no current pain on the NRS on the diagnosis date. We present several alternative statistical methods for the analysis of pain intensity data with a large proportion of zeroes. Published by Elsevier Inc.

SEMIPARAMETRIC ZERO-INFLATED MODELING IN MULTI-ETHNIC STUDY OF ATHEROSCLEROSIS (MESA)

PubMed Central

Liu, Hai; Ma, Shuangge; Kronmal, Richard; Chan, Kung-Sik

2013-01-01

We analyze the Agatston score of coronary artery calcium (CAC) from the Multi-Ethnic Study of Atherosclerosis (MESA) using semi-parametric zero-inflated modeling approach, where the observed CAC scores from this cohort consist of high frequency of zeroes and continuously distributed positive values. Both partially constrained and unconstrained models are considered to investigate the underlying biological processes of CAC development from zero to positive, and from small amount to large amount. Different from existing studies, a model selection procedure based on likelihood cross-validation is adopted to identify the optimal model, which is justified by comparative Monte Carlo studies. A shrinkaged version of cubic regression spline is used for model estimation and variable selection simultaneously. When applying the proposed methods to the MESA data analysis, we show that the two biological mechanisms influencing the initiation of CAC and the magnitude of CAC when it is positive are better characterized by an unconstrained zero-inflated normal model. Our results are significantly different from those in published studies, and may provide further insights into the biological mechanisms underlying CAC development in human. This highly flexible statistical framework can be applied to zero-inflated data analyses in other areas. PMID:23805172

A new approach for handling longitudinal count data with zero-inflation and overdispersion: poisson geometric process model.

PubMed

Wan, Wai-Yin; Chan, Jennifer S K

2009-08-01

For time series of count data, correlated measurements, clustering as well as excessive zeros occur simultaneously in biomedical applications. Ignoring such effects might contribute to misleading treatment outcomes. A generalized mixture Poisson geometric process (GMPGP) model and a zero-altered mixture Poisson geometric process (ZMPGP) model are developed from the geometric process model, which was originally developed for modelling positive continuous data and was extended to handle count data. These models are motivated by evaluating the trend development of new tumour counts for bladder cancer patients as well as by identifying useful covariates which affect the count level. The models are implemented using Bayesian method with Markov chain Monte Carlo (MCMC) algorithms and are assessed using deviance information criterion (DIC).

A Three-dimensional Polymer Scaffolding Material Exhibiting a Zero Poisson's Ratio.

PubMed

Soman, Pranav; Fozdar, David Y; Lee, Jin Woo; Phadke, Ameya; Varghese, Shyni; Chen, Shaochen

2012-05-14

Poisson's ratio describes the degree to which a material contracts (expands) transversally when axially strained. A material with a zero Poisson's ratio does not transversally deform in response to an axial strain (stretching). In tissue engineering applications, scaffolding having a zero Poisson's ratio (ZPR) may be more suitable for emulating the behavior of native tissues and accommodating and transmitting forces to the host tissue site during wound healing (or tissue regrowth). For example, scaffolding with a zero Poisson's ratio may be beneficial in the engineering of cartilage, ligament, corneal, and brain tissues, which are known to possess Poisson's ratios of nearly zero. Here, we report a 3D biomaterial constructed from polyethylene glycol (PEG) exhibiting in-plane Poisson's ratios of zero for large values of axial strain. We use digital micro-mirror device projection printing (DMD-PP) to create single- and double-layer scaffolds composed of semi re-entrant pores whose arrangement and deformation mechanisms contribute the zero Poisson's ratio. Strain experiments prove the zero Poisson's behavior of the scaffolds and that the addition of layers does not change the Poisson's ratio. Human mesenchymal stem cells (hMSCs) cultured on biomaterials with zero Poisson's ratio demonstrate the feasibility of utilizing these novel materials for biological applications which require little to no transverse deformations resulting from axial strains. Techniques used in this work allow Poisson's ratio to be both scale-independent and independent of the choice of strut material for strains in the elastic regime, and therefore ZPR behavior can be imparted to a variety of photocurable biomaterial.

Zero adjusted models with applications to analysing helminths count data.

PubMed

Chipeta, Michael G; Ngwira, Bagrey M; Simoonga, Christopher; Kazembe, Lawrence N

2014-11-27

It is common in public health and epidemiology that the outcome of interest is counts of events occurrence. Analysing these data using classical linear models is mostly inappropriate, even after transformation of outcome variables due to overdispersion. Zero-adjusted mixture count models such as zero-inflated and hurdle count models are applied to count data when over-dispersion and excess zeros exist. Main objective of the current paper is to apply such models to analyse risk factors associated with human helminths (S. haematobium) particularly in a case where there's a high proportion of zero counts. The data were collected during a community-based randomised control trial assessing the impact of mass drug administration (MDA) with praziquantel in Malawi, and a school-based cross sectional epidemiology survey in Zambia. Count data models including traditional (Poisson and negative binomial) models, zero modified models (zero inflated Poisson and zero inflated negative binomial) and hurdle models (Poisson logit hurdle and negative binomial logit hurdle) were fitted and compared. Using Akaike information criteria (AIC), the negative binomial logit hurdle (NBLH) and zero inflated negative binomial (ZINB) showed best performance in both datasets. With regards to zero count capturing, these models performed better than other models. This paper showed that zero modified NBLH and ZINB models are more appropriate methods for the analysis of data with excess zeros. The choice between the hurdle and zero-inflated models should be based on the aim and endpoints of the study.

A time-varying effect model for examining group differences in trajectories of zero-inflated count outcomes with applications in substance abuse research.

PubMed

Yang, Songshan; Cranford, James A; Jester, Jennifer M; Li, Runze; Zucker, Robert A; Buu, Anne

2017-02-28

This study proposes a time-varying effect model for examining group differences in trajectories of zero-inflated count outcomes. The motivating example demonstrates that this zero-inflated Poisson model allows investigators to study group differences in different aspects of substance use (e.g., the probability of abstinence and the quantity of alcohol use) simultaneously. The simulation study shows that the accuracy of estimation of trajectory functions improves as the sample size increases; the accuracy under equal group sizes is only higher when the sample size is small (100). In terms of the performance of the hypothesis testing, the type I error rates are close to their corresponding significance levels under all settings. Furthermore, the power increases as the alternative hypothesis deviates more from the null hypothesis, and the rate of this increasing trend is higher when the sample size is larger. Moreover, the hypothesis test for the group difference in the zero component tends to be less powerful than the test for the group difference in the Poisson component. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Assessment and Selection of Competing Models for Zero-Inflated Microbiome Data

PubMed Central

Xu, Lizhen; Paterson, Andrew D.; Turpin, Williams; Xu, Wei

2015-01-01

Typical data in a microbiome study consist of the operational taxonomic unit (OTU) counts that have the characteristic of excess zeros, which are often ignored by investigators. In this paper, we compare the performance of different competing methods to model data with zero inflated features through extensive simulations and application to a microbiome study. These methods include standard parametric and non-parametric models, hurdle models, and zero inflated models. We examine varying degrees of zero inflation, with or without dispersion in the count component, as well as different magnitude and direction of the covariate effect on structural zeros and the count components. We focus on the assessment of type I error, power to detect the overall covariate effect, measures of model fit, and bias and effectiveness of parameter estimations. We also evaluate the abilities of model selection strategies using Akaike information criterion (AIC) or Vuong test to identify the correct model. The simulation studies show that hurdle and zero inflated models have well controlled type I errors, higher power, better goodness of fit measures, and are more accurate and efficient in the parameter estimation. Besides that, the hurdle models have similar goodness of fit and parameter estimation for the count component as their corresponding zero inflated models. However, the estimation and interpretation of the parameters for the zero components differs, and hurdle models are more stable when structural zeros are absent. We then discuss the model selection strategy for zero inflated data and implement it in a gut microbiome study of > 400 independent subjects. PMID:26148172

Assessment and Selection of Competing Models for Zero-Inflated Microbiome Data.

PubMed

Xu, Lizhen; Paterson, Andrew D; Turpin, Williams; Xu, Wei

2015-01-01

Typical data in a microbiome study consist of the operational taxonomic unit (OTU) counts that have the characteristic of excess zeros, which are often ignored by investigators. In this paper, we compare the performance of different competing methods to model data with zero inflated features through extensive simulations and application to a microbiome study. These methods include standard parametric and non-parametric models, hurdle models, and zero inflated models. We examine varying degrees of zero inflation, with or without dispersion in the count component, as well as different magnitude and direction of the covariate effect on structural zeros and the count components. We focus on the assessment of type I error, power to detect the overall covariate effect, measures of model fit, and bias and effectiveness of parameter estimations. We also evaluate the abilities of model selection strategies using Akaike information criterion (AIC) or Vuong test to identify the correct model. The simulation studies show that hurdle and zero inflated models have well controlled type I errors, higher power, better goodness of fit measures, and are more accurate and efficient in the parameter estimation. Besides that, the hurdle models have similar goodness of fit and parameter estimation for the count component as their corresponding zero inflated models. However, the estimation and interpretation of the parameters for the zero components differs, and hurdle models are more stable when structural zeros are absent. We then discuss the model selection strategy for zero inflated data and implement it in a gut microbiome study of > 400 independent subjects.

Background stratified Poisson regression analysis of cohort data.

PubMed

Richardson, David B; Langholz, Bryan

2012-03-01

Background stratified Poisson regression is an approach that has been used in the analysis of data derived from a variety of epidemiologically important studies of radiation-exposed populations, including uranium miners, nuclear industry workers, and atomic bomb survivors. We describe a novel approach to fit Poisson regression models that adjust for a set of covariates through background stratification while directly estimating the radiation-disease association of primary interest. The approach makes use of an expression for the Poisson likelihood that treats the coefficients for stratum-specific indicator variables as 'nuisance' variables and avoids the need to explicitly estimate the coefficients for these stratum-specific parameters. Log-linear models, as well as other general relative rate models, are accommodated. This approach is illustrated using data from the Life Span Study of Japanese atomic bomb survivors and data from a study of underground uranium miners. The point estimate and confidence interval obtained from this 'conditional' regression approach are identical to the values obtained using unconditional Poisson regression with model terms for each background stratum. Moreover, it is shown that the proposed approach allows estimation of background stratified Poisson regression models of non-standard form, such as models that parameterize latency effects, as well as regression models in which the number of strata is large, thereby overcoming the limitations of previously available statistical software for fitting background stratified Poisson regression models.

Unified Computational Methods for Regression Analysis of Zero-Inflated and Bound-Inflated Data

PubMed Central

Yang, Yan; Simpson, Douglas

2010-01-01

Bounded data with excess observations at the boundary are common in many areas of application. Various individual cases of inflated mixture models have been studied in the literature for bound-inflated data, yet the computational methods have been developed separately for each type of model. In this article we use a common framework for computing these models, and expand the range of models for both discrete and semi-continuous data with point inflation at the lower boundary. The quasi-Newton and EM algorithms are adapted and compared for estimation of model parameters. The numerical Hessian and generalized Louis method are investigated as means for computing standard errors after optimization. Correlated data are included in this framework via generalized estimating equations. The estimation of parameters and effectiveness of standard errors are demonstrated through simulation and in the analysis of data from an ultrasound bioeffect study. The unified approach enables reliable computation for a wide class of inflated mixture models and comparison of competing models. PMID:20228950

A review on models for count data with extra zeros

NASA Astrophysics Data System (ADS)

Zamri, Nik Sarah Nik; Zamzuri, Zamira Hasanah

2017-04-01

Typically, the zero inflated models are usually used in modelling count data with excess zeros. The existence of the extra zeros could be structural zeros or random which occur by chance. These types of data are commonly found in various disciplines such as finance, insurance, biomedical, econometrical, ecology, and health sciences. As found in the literature, the most popular zero inflated models used are zero inflated Poisson and zero inflated negative binomial. Recently, more complex models have been developed to account for overdispersion and unobserved heterogeneity. In addition, more extended distributions are also considered in modelling data with this feature. In this paper, we review related literature, provide a recent development and summary on models for count data with extra zeros.

Zero-Inflated Models for Identifying Relationships Between Body Mass Index and Gastroesophageal Reflux Symptoms: A Nationwide Population-Based Study in China.

PubMed

Xu, Qin; Zhang, Wei; Zhang, Tianyi; Zhang, Ruijie; Zhao, Yanfang; Zhang, Yuan; Guo, Yibin; Wang, Rui; Ma, Xiuqiang; He, Jia

2016-07-01

That obesity leads to gastroesophageal reflux is a widespread notion. However, scientific evidence for this association is limited, with no rigorous epidemiological approach conducted to address this question. This study examined the relationship between body mass index (BMI) and gastroesophageal reflux symptoms in a large population-representative sample from China. We performed a cross-sectional study in an age- and gender-stratified random sample of the population of five central regions in China. Participants aged 18-80 years completed a general information questionnaire and a Chinese version of the Reflux Disease Questionnaire. The zero-inflated Poisson regression model estimated the relationship between body mass index and gastroesophageal reflux symptoms. Overall, 16,091 (89.4 %) of the 18,000 eligible participants responded. 638 (3.97 %) and 1738 (10.81 %) experienced at least weekly heartburn and weekly acid regurgitation, respectively. After adjusting for potential risk factors in the zero-inflated part, the frequency [odds ratio (OR) 0.66, 95 % confidence interval (95 % CI) 0.50-0.86, p = 0.002] and severity (OR 0.66, 95 % CI 0.50-088, p = 0.004) of heartburn in obese participants were statistically significant compared to those in normal participants. In the Poisson part, the frequency of acid regurgitation, overweight (OR 1.10, 95 % CI 1.01-1.21, p = 0.038) and obesity (OR 1.19, 95 % CI 1.04-1.37, p = 0.013) were statistically significant. BMI was strongly and positively related to the frequency and severity of gastroesophageal reflux symptoms. Additionally, gender exerted strong specific effects on the relationship between BMI and gastroesophageal reflux symptoms. The severity and frequency of heartburn were positively correlated with obesity. This relationship was presented distinct in male participants only.

Item Response Modeling of Multivariate Count Data with Zero Inflation, Maximum Inflation, and Heaping

ERIC Educational Resources Information Center

Magnus, Brooke E.; Thissen, David

2017-01-01

Questionnaires that include items eliciting count responses are becoming increasingly common in psychology. This study proposes methodological techniques to overcome some of the challenges associated with analyzing multivariate item response data that exhibit zero inflation, maximum inflation, and heaping at preferred digits. The modeling…

Multivariate random-parameters zero-inflated negative binomial regression model: an application to estimate crash frequencies at intersections.

PubMed

Dong, Chunjiao; Clarke, David B; Yan, Xuedong; Khattak, Asad; Huang, Baoshan

2014-09-01

Crash data are collected through police reports and integrated with road inventory data for further analysis. Integrated police reports and inventory data yield correlated multivariate data for roadway entities (e.g., segments or intersections). Analysis of such data reveals important relationships that can help focus on high-risk situations and coming up with safety countermeasures. To understand relationships between crash frequencies and associated variables, while taking full advantage of the available data, multivariate random-parameters models are appropriate since they can simultaneously consider the correlation among the specific crash types and account for unobserved heterogeneity. However, a key issue that arises with correlated multivariate data is the number of crash-free samples increases, as crash counts have many categories. In this paper, we describe a multivariate random-parameters zero-inflated negative binomial (MRZINB) regression model for jointly modeling crash counts. The full Bayesian method is employed to estimate the model parameters. Crash frequencies at urban signalized intersections in Tennessee are analyzed. The paper investigates the performance of MZINB and MRZINB regression models in establishing the relationship between crash frequencies, pavement conditions, traffic factors, and geometric design features of roadway intersections. Compared to the MZINB model, the MRZINB model identifies additional statistically significant factors and provides better goodness of fit in developing the relationships. The empirical results show that MRZINB model possesses most of the desirable statistical properties in terms of its ability to accommodate unobserved heterogeneity and excess zero counts in correlated data. Notably, in the random-parameters MZINB model, the estimated parameters vary significantly across intersections for different crash types. Copyright © 2014 Elsevier Ltd. All rights reserved.

Evaluation of the Use of Zero-Augmented Regression Techniques to Model Incidence of Campylobacter Infections in FoodNet.

PubMed

Tremblay, Marlène; Crim, Stacy M; Cole, Dana J; Hoekstra, Robert M; Henao, Olga L; Döpfer, Dörte

2017-10-01

The Foodborne Diseases Active Surveillance Network (FoodNet) is currently using a negative binomial (NB) regression model to estimate temporal changes in the incidence of Campylobacter infection. FoodNet active surveillance in 483 counties collected data on 40,212 Campylobacter cases between years 2004 and 2011. We explored models that disaggregated these data to allow us to account for demographic, geographic, and seasonal factors when examining changes in incidence of Campylobacter infection. We hypothesized that modeling structural zeros and including demographic variables would increase the fit of FoodNet's Campylobacter incidence regression models. Five different models were compared: NB without demographic covariates, NB with demographic covariates, hurdle NB with covariates in the count component only, hurdle NB with covariates in both zero and count components, and zero-inflated NB with covariates in the count component only. Of the models evaluated, the nonzero-augmented NB model with demographic variables provided the best fit. Results suggest that even though zero inflation was not present at this level, individualizing the level of aggregation and using different model structures and predictors per site might be required to correctly distinguish between structural and observational zeros and account for risk factors that vary geographically.

Observation weights unlock bulk RNA-seq tools for zero inflation and single-cell applications.

PubMed

Van den Berge, Koen; Perraudeau, Fanny; Soneson, Charlotte; Love, Michael I; Risso, Davide; Vert, Jean-Philippe; Robinson, Mark D; Dudoit, Sandrine; Clement, Lieven

2018-02-26

Dropout events in single-cell RNA sequencing (scRNA-seq) cause many transcripts to go undetected and induce an excess of zero read counts, leading to power issues in differential expression (DE) analysis. This has triggered the development of bespoke scRNA-seq DE methods to cope with zero inflation. Recent evaluations, however, have shown that dedicated scRNA-seq tools provide no advantage compared to traditional bulk RNA-seq tools. We introduce a weighting strategy, based on a zero-inflated negative binomial model, that identifies excess zero counts and generates gene- and cell-specific weights to unlock bulk RNA-seq DE pipelines for zero-inflated data, boosting performance for scRNA-seq.

[Application of negative binomial regression and modified Poisson regression in the research of risk factors for injury frequency].

PubMed

Cao, Qingqing; Wu, Zhenqiang; Sun, Ying; Wang, Tiezhu; Han, Tengwei; Gu, Chaomei; Sun, Yehuan

2011-11-01

To Eexplore the application of negative binomial regression and modified Poisson regression analysis in analyzing the influential factors for injury frequency and the risk factors leading to the increase of injury frequency. 2917 primary and secondary school students were selected from Hefei by cluster random sampling method and surveyed by questionnaire. The data on the count event-based injuries used to fitted modified Poisson regression and negative binomial regression model. The risk factors incurring the increase of unintentional injury frequency for juvenile students was explored, so as to probe the efficiency of these two models in studying the influential factors for injury frequency. The Poisson model existed over-dispersion (P < 0.0001) based on testing by the Lagrangemultiplier. Therefore, the over-dispersion dispersed data using a modified Poisson regression and negative binomial regression model, was fitted better. respectively. Both showed that male gender, younger age, father working outside of the hometown, the level of the guardian being above junior high school and smoking might be the results of higher injury frequencies. On a tendency of clustered frequency data on injury event, both the modified Poisson regression analysis and negative binomial regression analysis can be used. However, based on our data, the modified Poisson regression fitted better and this model could give a more accurate interpretation of relevant factors affecting the frequency of injury.

Empirical null estimation using zero-inflated discrete mixture distributions and its application to protein domain data.

PubMed

Gauran, Iris Ivy M; Park, Junyong; Lim, Johan; Park, DoHwan; Zylstra, John; Peterson, Thomas; Kann, Maricel; Spouge, John L

2017-09-22

In recent mutation studies, analyses based on protein domain positions are gaining popularity over gene-centric approaches since the latter have limitations in considering the functional context that the position of the mutation provides. This presents a large-scale simultaneous inference problem, with hundreds of hypothesis tests to consider at the same time. This article aims to select significant mutation counts while controlling a given level of Type I error via False Discovery Rate (FDR) procedures. One main assumption is that the mutation counts follow a zero-inflated model in order to account for the true zeros in the count model and the excess zeros. The class of models considered is the Zero-inflated Generalized Poisson (ZIGP) distribution. Furthermore, we assumed that there exists a cut-off value such that smaller counts than this value are generated from the null distribution. We present several data-dependent methods to determine the cut-off value. We also consider a two-stage procedure based on screening process so that the number of mutations exceeding a certain value should be considered as significant mutations. Simulated and protein domain data sets are used to illustrate this procedure in estimation of the empirical null using a mixture of discrete distributions. Overall, while maintaining control of the FDR, the proposed two-stage testing procedure has superior empirical power. 2017 The Authors. Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

A tutorial on count regression and zero-altered count models for longitudinal substance use data

PubMed Central

Atkins, David C.; Baldwin, Scott A.; Zheng, Cheng; Gallop, Robert J.; Neighbors, Clayton

2012-01-01

Critical research questions in the study of addictive behaviors concern how these behaviors change over time - either as the result of intervention or in naturalistic settings. The combination of count outcomes that are often strongly skewed with many zeroes (e.g., days using, number of total drinks, number of drinking consequences) with repeated assessments (e.g., longitudinal follow-up after intervention or daily diary data) present challenges for data analyses. The current article provides a tutorial on methods for analyzing longitudinal substance use data, focusing on Poisson, zero-inflated, and hurdle mixed models, which are types of hierarchical or multilevel models. Two example datasets are used throughout, focusing on drinking-related consequences following an intervention and daily drinking over the past 30 days, respectively. Both datasets as well as R, SAS, Mplus, Stata, and SPSS code showing how to fit the models are available on a supplemental website. PMID:22905895

Poisson Regression Analysis of Illness and Injury Surveillance Data

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

Frome E.L., Watkins J.P., Ellis E.D.

2012-12-12

The Department of Energy (DOE) uses illness and injury surveillance to monitor morbidity and assess the overall health of the work force. Data collected from each participating site include health events and a roster file with demographic information. The source data files are maintained in a relational data base, and are used to obtain stratified tables of health event counts and person time at risk that serve as the starting point for Poisson regression analysis. The explanatory variables that define these tables are age, gender, occupational group, and time. Typical response variables of interest are the number of absences duemore » to illness or injury, i.e., the response variable is a count. Poisson regression methods are used to describe the effect of the explanatory variables on the health event rates using a log-linear main effects model. Results of fitting the main effects model are summarized in a tabular and graphical form and interpretation of model parameters is provided. An analysis of deviance table is used to evaluate the importance of each of the explanatory variables on the event rate of interest and to determine if interaction terms should be considered in the analysis. Although Poisson regression methods are widely used in the analysis of count data, there are situations in which over-dispersion occurs. This could be due to lack-of-fit of the regression model, extra-Poisson variation, or both. A score test statistic and regression diagnostics are used to identify over-dispersion. A quasi-likelihood method of moments procedure is used to evaluate and adjust for extra-Poisson variation when necessary. Two examples are presented using respiratory disease absence rates at two DOE sites to illustrate the methods and interpretation of the results. In the first example the Poisson main effects model is adequate. In the second example the score test indicates considerable over-dispersion and a more detailed analysis attributes the over-dispersion to

Performance of the modified Poisson regression approach for estimating relative risks from clustered prospective data.

PubMed

Yelland, Lisa N; Salter, Amy B; Ryan, Philip

2011-10-15

Modified Poisson regression, which combines a log Poisson regression model with robust variance estimation, is a useful alternative to log binomial regression for estimating relative risks. Previous studies have shown both analytically and by simulation that modified Poisson regression is appropriate for independent prospective data. This method is often applied to clustered prospective data, despite a lack of evidence to support its use in this setting. The purpose of this article is to evaluate the performance of the modified Poisson regression approach for estimating relative risks from clustered prospective data, by using generalized estimating equations to account for clustering. A simulation study is conducted to compare log binomial regression and modified Poisson regression for analyzing clustered data from intervention and observational studies. Both methods generally perform well in terms of bias, type I error, and coverage. Unlike log binomial regression, modified Poisson regression is not prone to convergence problems. The methods are contrasted by using example data sets from 2 large studies. The results presented in this article support the use of modified Poisson regression as an alternative to log binomial regression for analyzing clustered prospective data when clustering is taken into account by using generalized estimating equations.

Modelling infant mortality rate in Central Java, Indonesia use generalized poisson regression method

NASA Astrophysics Data System (ADS)

Prahutama, Alan; Sudarno

2018-05-01

The infant mortality rate is the number of deaths under one year of age occurring among the live births in a given geographical area during a given year, per 1,000 live births occurring among the population of the given geographical area during the same year. This problem needs to be addressed because it is an important element of a country’s economic development. High infant mortality rate will disrupt the stability of a country as it relates to the sustainability of the population in the country. One of regression model that can be used to analyze the relationship between dependent variable Y in the form of discrete data and independent variable X is Poisson regression model. Recently The regression modeling used for data with dependent variable is discrete, among others, poisson regression, negative binomial regression and generalized poisson regression. In this research, generalized poisson regression modeling gives better AIC value than poisson regression. The most significant variable is the Number of health facilities (X1), while the variable that gives the most influence to infant mortality rate is the average breastfeeding (X9).

Zero-state Markov switching count-data models: an empirical assessment.

PubMed

Malyshkina, Nataliya V; Mannering, Fred L

2010-01-01

In this study, a two-state Markov switching count-data model is proposed as an alternative to zero-inflated models to account for the preponderance of zeros sometimes observed in transportation count data, such as the number of accidents occurring on a roadway segment over some period of time. For this accident-frequency case, zero-inflated models assume the existence of two states: one of the states is a zero-accident count state, which has accident probabilities that are so low that they cannot be statistically distinguished from zero, and the other state is a normal-count state, in which counts can be non-negative integers that are generated by some counting process, for example, a Poisson or negative binomial. While zero-inflated models have come under some criticism with regard to accident-frequency applications - one fact is undeniable - in many applications they provide a statistically superior fit to the data. The Markov switching approach we propose seeks to overcome some of the criticism associated with the zero-accident state of the zero-inflated model by allowing individual roadway segments to switch between zero and normal-count states over time. An important advantage of this Markov switching approach is that it allows for the direct statistical estimation of the specific roadway-segment state (i.e., zero-accident or normal-count state) whereas traditional zero-inflated models do not. To demonstrate the applicability of this approach, a two-state Markov switching negative binomial model (estimated with Bayesian inference) and standard zero-inflated negative binomial models are estimated using five-year accident frequencies on Indiana interstate highway segments. It is shown that the Markov switching model is a viable alternative and results in a superior statistical fit relative to the zero-inflated models.

A generalized right truncated bivariate Poisson regression model with applications to health data.

PubMed

Islam, M Ataharul; Chowdhury, Rafiqul I

2017-01-01

A generalized right truncated bivariate Poisson regression model is proposed in this paper. Estimation and tests for goodness of fit and over or under dispersion are illustrated for both untruncated and right truncated bivariate Poisson regression models using marginal-conditional approach. Estimation and test procedures are illustrated for bivariate Poisson regression models with applications to Health and Retirement Study data on number of health conditions and the number of health care services utilized. The proposed test statistics are easy to compute and it is evident from the results that the models fit the data very well. A comparison between the right truncated and untruncated bivariate Poisson regression models using the test for nonnested models clearly shows that the truncated model performs significantly better than the untruncated model.

Non-Poisson Processes: Regression to Equilibrium Versus Equilibrium Correlation Functions

DTIC Science & Technology

2004-07-07

ARTICLE IN PRESSPhysica A 347 (2005) 268–2880378-4371/$ - doi:10.1016/j Correspo E-mail adwww.elsevier.com/locate/physaNon- Poisson processes : regression...05.40.a; 89.75.k; 02.50.Ey Keywords: Stochastic processes; Non- Poisson processes ; Liouville and Liouville-like equations; Correlation function...which is not legitimate with renewal non- Poisson processes , is a correct property if the deviation from the exponential relaxation is obtained by time

A generalized right truncated bivariate Poisson regression model with applications to health data

PubMed Central

Islam, M. Ataharul; Chowdhury, Rafiqul I.

2017-01-01

A generalized right truncated bivariate Poisson regression model is proposed in this paper. Estimation and tests for goodness of fit and over or under dispersion are illustrated for both untruncated and right truncated bivariate Poisson regression models using marginal-conditional approach. Estimation and test procedures are illustrated for bivariate Poisson regression models with applications to Health and Retirement Study data on number of health conditions and the number of health care services utilized. The proposed test statistics are easy to compute and it is evident from the results that the models fit the data very well. A comparison between the right truncated and untruncated bivariate Poisson regression models using the test for nonnested models clearly shows that the truncated model performs significantly better than the untruncated model. PMID:28586344

Poisson's ratio from polarization of acoustic zero-group velocity Lamb mode.

PubMed

Baggens, Oskar; Ryden, Nils

2015-07-01

Poisson's ratio of an isotropic and free elastic plate is estimated from the polarization of the first symmetric acoustic zero-group velocity Lamb mode. This polarization is interpreted as the ratio of the absolute amplitudes of the surface normal and surface in-plane components of the acoustic mode. Results from the evaluation of simulated datasets indicate that the presented relation, which links the polarization and Poisson's ratio, can be extended to incorporate plates with material damping. Furthermore, the proposed application of the polarization is demonstrated in a practical field case, where an increased accuracy of estimated nominal thickness is obtained.

Comparing statistical methods for analyzing skewed longitudinal count data with many zeros: an example of smoking cessation.

PubMed

Xie, Haiyi; Tao, Jill; McHugo, Gregory J; Drake, Robert E

2013-07-01

Count data with skewness and many zeros are common in substance abuse and addiction research. Zero-adjusting models, especially zero-inflated models, have become increasingly popular in analyzing this type of data. This paper reviews and compares five mixed-effects Poisson family models commonly used to analyze count data with a high proportion of zeros by analyzing a longitudinal outcome: number of smoking quit attempts from the New Hampshire Dual Disorders Study. The findings of our study indicated that count data with many zeros do not necessarily require zero-inflated or other zero-adjusting models. For rare event counts or count data with small means, a simpler model such as the negative binomial model may provide a better fit. Copyright © 2013 Elsevier Inc. All rights reserved.

Some considerations for excess zeroes in substance abuse research.

PubMed

Bandyopadhyay, Dipankar; DeSantis, Stacia M; Korte, Jeffrey E; Brady, Kathleen T

2011-09-01

Count data collected in substance abuse research often come with an excess of "zeroes," which are typically handled using zero-inflated regression models. However, there is a need to consider the design aspects of those studies before using such a statistical model to ascertain the sources of zeroes. We sought to illustrate hurdle models as alternatives to zero-inflated models to validate a two-stage decision-making process in situations of "excess zeroes." We use data from a study of 45 cocaine-dependent subjects where the primary scientific question was to evaluate whether study participation influences drug-seeking behavior. The outcome, "the frequency (count) of cocaine use days per week," is bounded (ranging from 0 to 7). We fit and compare binomial, Poisson, negative binomial, and the hurdle version of these models to study the effect of gender, age, time, and study participation on cocaine use. The hurdle binomial model provides the best fit. Gender and time are not predictive of use. Higher odds of use versus no use are associated with age; however once use is experienced, odds of further use decrease with increase in age. Participation was associated with higher odds of no-cocaine use; once there is use, participation reduced the odds of further use. Age and study participation are significantly predictive of cocaine-use behavior. The two-stage decision process as modeled by a hurdle binomial model (appropriate for bounded count data with excess zeroes) provides interesting insights into the study of covariate effects on count responses of substance use, when all enrolled subjects are believed to be "at-risk" of use.

Trending in Probability of Collision Measurements via a Bayesian Zero-Inflated Beta Mixed Model

NASA Technical Reports Server (NTRS)

Vallejo, Jonathon; Hejduk, Matt; Stamey, James

2015-01-01

We investigate the performance of a generalized linear mixed model in predicting the Probabilities of Collision (Pc) for conjunction events. Specifically, we apply this model to the log(sub 10) transformation of these probabilities and argue that this transformation yields values that can be considered bounded in practice. Additionally, this bounded random variable, after scaling, is zero-inflated. Consequently, we model these values using the zero-inflated Beta distribution, and utilize the Bayesian paradigm and the mixed model framework to borrow information from past and current events. This provides a natural way to model the data and provides a basis for answering questions of interest, such as what is the likelihood of observing a probability of collision equal to the effective value of zero on a subsequent observation.

A Zero- and K-Inflated Mixture Model for Health Questionnaire Data

PubMed Central

Finkelman, Matthew D.; Green, Jennifer Greif; Gruber, Michael J.; Zaslavsky, Alan M.

2011-01-01

In psychiatric assessment, Item Response Theory (IRT) is a popular tool to formalize the relation between the severity of a disorder and associated responses to questionnaire items. Practitioners of IRT sometimes make the assumption of normally distributed severities within a population; while convenient, this assumption is often violated when measuring psychiatric disorders. Specifically, there may be a sizable group of respondents whose answers place them at an extreme of the latent trait spectrum. In this article, a zero- and K-inflated mixture model is developed to account for the presence of such respondents. The model is fitted using an expectation-maximization (E-M) algorithm to estimate the percentage of the population at each end of the continuum, concurrently analyzing the remaining “graded component” via IRT. A method to perform factor analysis for only the graded component is introduced. In assessments of oppositional defiant disorder and conduct disorder, the zero- and K-inflated model exhibited better fit than the standard IRT model. PMID:21365673

Disease Mapping of Zero-excessive Mesothelioma Data in Flanders

PubMed Central

Neyens, Thomas; Lawson, Andrew B.; Kirby, Russell S.; Nuyts, Valerie; Watjou, Kevin; Aregay, Mehreteab; Carroll, Rachel; Nawrot, Tim S.; Faes, Christel

2016-01-01

Purpose To investigate the distribution of mesothelioma in Flanders using Bayesian disease mapping models that account for both an excess of zeros and overdispersion. Methods The numbers of newly diagnosed mesothelioma cases within all Flemish municipalities between 1999 and 2008 were obtained from the Belgian Cancer Registry. To deal with overdispersion, zero-inflation and geographical association, the hurdle combined model was proposed, which has three components: a Bernoulli zero-inflation mixture component to account for excess zeros, a gamma random effect to adjust for overdispersion and a normal conditional autoregressive random effect to attribute spatial association. This model was compared with other existing methods in literature. Results The results indicate that hurdle models with a random effects term accounting for extra-variance in the Bernoulli zero-inflation component fit the data better than hurdle models that do not take overdispersion in the occurrence of zeros into account. Furthermore, traditional models that do not take into account excessive zeros but contain at least one random effects term that models extra-variance in the counts have better fits compared to their hurdle counterparts. In other words, the extra-variability, due to an excess of zeros, can be accommodated by spatially structured and/or unstructured random effects in a Poisson model such that the hurdle mixture model is not necessary. Conclusions Models taking into account zero-inflation do not always provide better fits to data with excessive zeros than less complex models. In this study, a simple conditional autoregressive model identified a cluster in mesothelioma cases near a former asbestos processing plant (Kapelle-op-den-Bos). This observation is likely linked with historical local asbestos exposures. Future research will clarify this. PMID:27908590

Disease mapping of zero-excessive mesothelioma data in Flanders.

PubMed

Neyens, Thomas; Lawson, Andrew B; Kirby, Russell S; Nuyts, Valerie; Watjou, Kevin; Aregay, Mehreteab; Carroll, Rachel; Nawrot, Tim S; Faes, Christel

2017-01-01

To investigate the distribution of mesothelioma in Flanders using Bayesian disease mapping models that account for both an excess of zeros and overdispersion. The numbers of newly diagnosed mesothelioma cases within all Flemish municipalities between 1999 and 2008 were obtained from the Belgian Cancer Registry. To deal with overdispersion, zero inflation, and geographical association, the hurdle combined model was proposed, which has three components: a Bernoulli zero-inflation mixture component to account for excess zeros, a gamma random effect to adjust for overdispersion, and a normal conditional autoregressive random effect to attribute spatial association. This model was compared with other existing methods in literature. The results indicate that hurdle models with a random effects term accounting for extra variance in the Bernoulli zero-inflation component fit the data better than hurdle models that do not take overdispersion in the occurrence of zeros into account. Furthermore, traditional models that do not take into account excessive zeros but contain at least one random effects term that models extra variance in the counts have better fits compared to their hurdle counterparts. In other words, the extra variability, due to an excess of zeros, can be accommodated by spatially structured and/or unstructured random effects in a Poisson model such that the hurdle mixture model is not necessary. Models taking into account zero inflation do not always provide better fits to data with excessive zeros than less complex models. In this study, a simple conditional autoregressive model identified a cluster in mesothelioma cases near a former asbestos processing plant (Kapelle-op-den-Bos). This observation is likely linked with historical local asbestos exposures. Future research will clarify this. Copyright © 2016 Elsevier Inc. All rights reserved.

Fuzzy classifier based support vector regression framework for Poisson ratio determination

NASA Astrophysics Data System (ADS)

Asoodeh, Mojtaba; Bagheripour, Parisa

2013-09-01

Poisson ratio is considered as one of the most important rock mechanical properties of hydrocarbon reservoirs. Determination of this parameter through laboratory measurement is time, cost, and labor intensive. Furthermore, laboratory measurements do not provide continuous data along the reservoir intervals. Hence, a fast, accurate, and inexpensive way of determining Poisson ratio which produces continuous data over the whole reservoir interval is desirable. For this purpose, support vector regression (SVR) method based on statistical learning theory (SLT) was employed as a supervised learning algorithm to estimate Poisson ratio from conventional well log data. SVR is capable of accurately extracting the implicit knowledge contained in conventional well logs and converting the gained knowledge into Poisson ratio data. Structural risk minimization (SRM) principle which is embedded in the SVR structure in addition to empirical risk minimization (EMR) principle provides a robust model for finding quantitative formulation between conventional well log data and Poisson ratio. Although satisfying results were obtained from an individual SVR model, it had flaws of overestimation in low Poisson ratios and underestimation in high Poisson ratios. These errors were eliminated through implementation of fuzzy classifier based SVR (FCBSVR). The FCBSVR significantly improved accuracy of the final prediction. This strategy was successfully applied to data from carbonate reservoir rocks of an Iranian Oil Field. Results indicated that SVR predicted Poisson ratio values are in good agreement with measured values.

Weather variability and the incidence of cryptosporidiosis: comparison of time series poisson regression and SARIMA models.

PubMed

Hu, Wenbiao; Tong, Shilu; Mengersen, Kerrie; Connell, Des

2007-09-01

Few studies have examined the relationship between weather variables and cryptosporidiosis in Australia. This paper examines the potential impact of weather variability on the transmission of cryptosporidiosis and explores the possibility of developing an empirical forecast system. Data on weather variables, notified cryptosporidiosis cases, and population size in Brisbane were supplied by the Australian Bureau of Meteorology, Queensland Department of Health, and Australian Bureau of Statistics for the period of January 1, 1996-December 31, 2004, respectively. Time series Poisson regression and seasonal auto-regression integrated moving average (SARIMA) models were performed to examine the potential impact of weather variability on the transmission of cryptosporidiosis. Both the time series Poisson regression and SARIMA models show that seasonal and monthly maximum temperature at a prior moving average of 1 and 3 months were significantly associated with cryptosporidiosis disease. It suggests that there may be 50 more cases a year for an increase of 1 degrees C maximum temperature on average in Brisbane. Model assessments indicated that the SARIMA model had better predictive ability than the Poisson regression model (SARIMA: root mean square error (RMSE): 0.40, Akaike information criterion (AIC): -12.53; Poisson regression: RMSE: 0.54, AIC: -2.84). Furthermore, the analysis of residuals shows that the time series Poisson regression appeared to violate a modeling assumption, in that residual autocorrelation persisted. The results of this study suggest that weather variability (particularly maximum temperature) may have played a significant role in the transmission of cryptosporidiosis. A SARIMA model may be a better predictive model than a Poisson regression model in the assessment of the relationship between weather variability and the incidence of cryptosporidiosis.

GMPR: A robust normalization method for zero-inflated count data with application to microbiome sequencing data.

PubMed

Chen, Li; Reeve, James; Zhang, Lujun; Huang, Shengbing; Wang, Xuefeng; Chen, Jun

2018-01-01

Normalization is the first critical step in microbiome sequencing data analysis used to account for variable library sizes. Current RNA-Seq based normalization methods that have been adapted for microbiome data fail to consider the unique characteristics of microbiome data, which contain a vast number of zeros due to the physical absence or under-sampling of the microbes. Normalization methods that specifically address the zero-inflation remain largely undeveloped. Here we propose geometric mean of pairwise ratios-a simple but effective normalization method-for zero-inflated sequencing data such as microbiome data. Simulation studies and real datasets analyses demonstrate that the proposed method is more robust than competing methods, leading to more powerful detection of differentially abundant taxa and higher reproducibility of the relative abundances of taxa.

Simulation on Poisson and negative binomial models of count road accident modeling

NASA Astrophysics Data System (ADS)

Sapuan, M. S.; Razali, A. M.; Zamzuri, Z. H.; Ibrahim, K.

2016-11-01

Accident count data have often been shown to have overdispersion. On the other hand, the data might contain zero count (excess zeros). The simulation study was conducted to create a scenarios which an accident happen in T-junction with the assumption the dependent variables of generated data follows certain distribution namely Poisson and negative binomial distribution with different sample size of n=30 to n=500. The study objective was accomplished by fitting Poisson regression, negative binomial regression and Hurdle negative binomial model to the simulated data. The model validation was compared and the simulation result shows for each different sample size, not all model fit the data nicely even though the data generated from its own distribution especially when the sample size is larger. Furthermore, the larger sample size indicates that more zeros accident count in the dataset.

Zero-inflated modeling of fish catch per unit area resulting from multiple gears: Application to channel catfish and shovelnose sturgeon in the Missouri River

USGS Publications Warehouse

Arab, A.; Wildhaber, M.L.; Wikle, C.K.; Gentry, C.N.

2008-01-01

Fisheries studies often employ multiple gears that result in large percentages of zero values. We considered a zero-inflated Poisson (ZIP) model with random effects to address these excessive zeros. By employing a Bayesian ZIP model that simultaneously incorporates data from multiple gears to analyze data from the Missouri River, we were able to compare gears and make more year, segment, and macrohabitat comparisons than did the original data analysis. For channel catfish Ictalurus punctatus, our results rank (highest to lowest) the mean catch per unit area (CPUA) for gears (beach seine, benthic trawl, electrofishing, and drifting trammel net); years (1998 and 1997); macrohabitats (tributary mouth, connected secondary channel, nonconnected secondary channel, and bend); and river segment zones (channelized, inter-reservoir, and least-altered). For shovelnose sturgeon Scaphirhynchus platorynchus, the mean CPUA was significantly higher for benthic trawls and drifting trammel nets; 1998 and 1997; tributary mouths, bends, and connected secondary channels; and some channelized or least-altered inter-reservoir segments. One important advantage of our approach is the ability to reliably infer patterns of relative abundance by means of multiple gears without using gear efficiencies. ?? Copyright by the American Fisheries Society 2008.

Three-dimensionally bonded spongy graphene material with super compressive elasticity and near-zero Poisson's ratio.

PubMed

Wu, Yingpeng; Yi, Ningbo; Huang, Lu; Zhang, Tengfei; Fang, Shaoli; Chang, Huicong; Li, Na; Oh, Jiyoung; Lee, Jae Ah; Kozlov, Mikhail; Chipara, Alin C; Terrones, Humberto; Xiao, Peishuang; Long, Guankui; Huang, Yi; Zhang, Fan; Zhang, Long; Lepró, Xavier; Haines, Carter; Lima, Márcio Dias; Lopez, Nestor Perea; Rajukumar, Lakshmy P; Elias, Ana L; Feng, Simin; Kim, Seon Jeong; Narayanan, N T; Ajayan, Pulickel M; Terrones, Mauricio; Aliev, Ali; Chu, Pengfei; Zhang, Zhong; Baughman, Ray H; Chen, Yongsheng

2015-01-20

It is a challenge to fabricate graphene bulk materials with properties arising from the nature of individual graphene sheets, and which assemble into monolithic three-dimensional structures. Here we report the scalable self-assembly of randomly oriented graphene sheets into additive-free, essentially homogenous graphene sponge materials that provide a combination of both cork-like and rubber-like properties. These graphene sponges, with densities similar to air, display Poisson's ratios in all directions that are near-zero and largely strain-independent during reversible compression to giant strains. And at the same time, they function as enthalpic rubbers, which can recover up to 98% compression in air and 90% in liquids, and operate between -196 and 900 °C. Furthermore, these sponges provide reversible liquid absorption for hundreds of cycles and then discharge it within seconds, while still providing an effective near-zero Poisson's ratio.

Variable selection for zero-inflated and overdispersed data with application to health care demand in Germany

PubMed Central

Wang, Zhu; Shuangge, Ma; Wang, Ching-Yun

2017-01-01

In health services and outcome research, count outcomes are frequently encountered and often have a large proportion of zeros. The zero-inflated negative binomial (ZINB) regression model has important applications for this type of data. With many possible candidate risk factors, this paper proposes new variable selection methods for the ZINB model. We consider maximum likelihood function plus a penalty including the least absolute shrinkage and selection operator (LASSO), smoothly clipped absolute deviation (SCAD) and minimax concave penalty (MCP). An EM (expectation-maximization) algorithm is proposed for estimating the model parameters and conducting variable selection simultaneously. This algorithm consists of estimating penalized weighted negative binomial models and penalized logistic models via the coordinated descent algorithm. Furthermore, statistical properties including the standard error formulae are provided. A simulation study shows that the new algorithm not only has more accurate or at least comparable estimation, also is more robust than the traditional stepwise variable selection. The proposed methods are applied to analyze the health care demand in Germany using an open-source R package mpath. PMID:26059498

Persistently Auxetic Materials: Engineering the Poisson Ratio of 2D Self-Avoiding Membranes under Conditions of Non-Zero Anisotropic Strain.

PubMed

Ulissi, Zachary W; Govind Rajan, Ananth; Strano, Michael S

2016-08-23

Entropic surfaces represented by fluctuating two-dimensional (2D) membranes are predicted to have desirable mechanical properties when unstressed, including a negative Poisson's ratio ("auxetic" behavior). Herein, we present calculations of the strain-dependent Poisson ratio of self-avoiding 2D membranes demonstrating desirable auxetic properties over a range of mechanical strain. Finite-size membranes with unclamped boundary conditions have positive Poisson's ratio due to spontaneous non-zero mean curvature, which can be suppressed with an explicit bending rigidity in agreement with prior findings. Applying longitudinal strain along a singular axis to this system suppresses this mean curvature and the entropic out-of-plane fluctuations, resulting in a molecular-scale mechanism for realizing a negative Poisson's ratio above a critical strain, with values significantly more negative than the previously observed zero-strain limit for infinite sheets. We find that auxetic behavior persists over surprisingly high strains of more than 20% for the smallest surfaces, with desirable finite-size scaling producing surfaces with negative Poisson's ratio over a wide range of strains. These results promise the design of surfaces and composite materials with tunable Poisson's ratio by prestressing platelet inclusions or controlling the surface rigidity of a matrix of 2D materials.

Bayesian spatiotemporal analysis of zero-inflated biological population density data by a delta-normal spatiotemporal additive model.

PubMed

Arcuti, Simona; Pollice, Alessio; Ribecco, Nunziata; D'Onghia, Gianfranco

2016-03-01

We evaluate the spatiotemporal changes in the density of a particular species of crustacean known as deep-water rose shrimp, Parapenaeus longirostris, based on biological sample data collected during trawl surveys carried out from 1995 to 2006 as part of the international project MEDITS (MEDiterranean International Trawl Surveys). As is the case for many biological variables, density data are continuous and characterized by unusually large amounts of zeros, accompanied by a skewed distribution of the remaining values. Here we analyze the normalized density data by a Bayesian delta-normal semiparametric additive model including the effects of covariates, using penalized regression with low-rank thin-plate splines for nonlinear spatial and temporal effects. Modeling the zero and nonzero values by two joint processes, as we propose in this work, allows to obtain great flexibility and easily handling of complex likelihood functions, avoiding inaccurate statistical inferences due to misclassification of the high proportion of exact zeros in the model. Bayesian model estimation is obtained by Markov chain Monte Carlo simulations, suitably specifying the complex likelihood function of the zero-inflated density data. The study highlights relevant nonlinear spatial and temporal effects and the influence of the annual Mediterranean oscillations index and of the sea surface temperature on the distribution of the deep-water rose shrimp density. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Extending the Applicability of the Generalized Likelihood Function for Zero-Inflated Data Series

NASA Astrophysics Data System (ADS)

Oliveira, Debora Y.; Chaffe, Pedro L. B.; Sá, João. H. M.

2018-03-01

Proper uncertainty estimation for data series with a high proportion of zero and near zero observations has been a challenge in hydrologic studies. This technical note proposes a modification to the Generalized Likelihood function that accounts for zero inflation of the error distribution (ZI-GL). We compare the performance of the proposed ZI-GL with the original Generalized Likelihood function using the entire data series (GL) and by simply suppressing zero observations (GLy>0). These approaches were applied to two interception modeling examples characterized by data series with a significant number of zeros. The ZI-GL produced better uncertainty ranges than the GL as measured by the precision, reliability and volumetric bias metrics. The comparison between ZI-GL and GLy>0 highlights the need for further improvement in the treatment of residuals from near zero simulations when a linear heteroscedastic error model is considered. Aside from the interception modeling examples illustrated herein, the proposed ZI-GL may be useful for other hydrologic studies, such as for the modeling of the runoff generation in hillslopes and ephemeral catchments.

Variable selection for zero-inflated and overdispersed data with application to health care demand in Germany.

PubMed

Wang, Zhu; Ma, Shuangge; Wang, Ching-Yun

2015-09-01

In health services and outcome research, count outcomes are frequently encountered and often have a large proportion of zeros. The zero-inflated negative binomial (ZINB) regression model has important applications for this type of data. With many possible candidate risk factors, this paper proposes new variable selection methods for the ZINB model. We consider maximum likelihood function plus a penalty including the least absolute shrinkage and selection operator (LASSO), smoothly clipped absolute deviation (SCAD), and minimax concave penalty (MCP). An EM (expectation-maximization) algorithm is proposed for estimating the model parameters and conducting variable selection simultaneously. This algorithm consists of estimating penalized weighted negative binomial models and penalized logistic models via the coordinated descent algorithm. Furthermore, statistical properties including the standard error formulae are provided. A simulation study shows that the new algorithm not only has more accurate or at least comparable estimation, but also is more robust than the traditional stepwise variable selection. The proposed methods are applied to analyze the health care demand in Germany using the open-source R package mpath. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Matching the Statistical Model to the Research Question for Dental Caries Indices with Many Zero Counts.

PubMed

Preisser, John S; Long, D Leann; Stamm, John W

2017-01-01

Marginalized zero-inflated count regression models have recently been introduced for the statistical analysis of dental caries indices and other zero-inflated count data as alternatives to traditional zero-inflated and hurdle models. Unlike the standard approaches, the marginalized models directly estimate overall exposure or treatment effects by relating covariates to the marginal mean count. This article discusses model interpretation and model class choice according to the research question being addressed in caries research. Two data sets, one consisting of fictional dmft counts in 2 groups and the other on DMFS among schoolchildren from a randomized clinical trial comparing 3 toothpaste formulations to prevent incident dental caries, are analyzed with negative binomial hurdle, zero-inflated negative binomial, and marginalized zero-inflated negative binomial models. In the first example, estimates of treatment effects vary according to the type of incidence rate ratio (IRR) estimated by the model. Estimates of IRRs in the analysis of the randomized clinical trial were similar despite their distinctive interpretations. The choice of statistical model class should match the study's purpose, while accounting for the broad decline in children's caries experience, such that dmft and DMFS indices more frequently generate zero counts. Marginalized (marginal mean) models for zero-inflated count data should be considered for direct assessment of exposure effects on the marginal mean dental caries count in the presence of high frequencies of zero counts. © 2017 S. Karger AG, Basel.

Matching the Statistical Model to the Research Question for Dental Caries Indices with Many Zero Counts

PubMed Central

Preisser, John S.; Long, D. Leann; Stamm, John W.

2017-01-01

Marginalized zero-inflated count regression models have recently been introduced for the statistical analysis of dental caries indices and other zero-inflated count data as alternatives to traditional zero-inflated and hurdle models. Unlike the standard approaches, the marginalized models directly estimate overall exposure or treatment effects by relating covariates to the marginal mean count. This article discusses model interpretation and model class choice according to the research question being addressed in caries research. Two datasets, one consisting of fictional dmft counts in two groups and the other on DMFS among schoolchildren from a randomized clinical trial (RCT) comparing three toothpaste formulations to prevent incident dental caries, are analysed with negative binomial hurdle (NBH), zero-inflated negative binomial (ZINB), and marginalized zero-inflated negative binomial (MZINB) models. In the first example, estimates of treatment effects vary according to the type of incidence rate ratio (IRR) estimated by the model. Estimates of IRRs in the analysis of the RCT were similar despite their distinctive interpretations. Choice of statistical model class should match the study’s purpose, while accounting for the broad decline in children’s caries experience, such that dmft and DMFS indices more frequently generate zero counts. Marginalized (marginal mean) models for zero-inflated count data should be considered for direct assessment of exposure effects on the marginal mean dental caries count in the presence of high frequencies of zero counts. PMID:28291962

On the Singularity of the Vlasov-Poisson System

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

and Hong Qin, Jian Zheng

2013-04-26

The Vlasov-Poisson system can be viewed as the collisionless limit of the corresponding Fokker- Planck-Poisson system. It is reasonable to expect that the result of Landau damping can also be obtained from the Fokker-Planck-Poisson system when the collision frequency v approaches zero. However, we show that the colllisionless Vlasov-Poisson system is a singular limit of the collisional Fokker-Planck-Poisson system, and Landau's result can be recovered only as the approaching zero from the positive side.

On the singularity of the Vlasov-Poisson system

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

Zheng, Jian; Qin, Hong; Plasma Physics Laboratory, Princeton University, Princeton, New Jersey 08550

2013-09-15

The Vlasov-Poisson system can be viewed as the collisionless limit of the corresponding Fokker-Planck-Poisson system. It is reasonable to expect that the result of Landau damping can also be obtained from the Fokker-Planck-Poisson system when the collision frequency ν approaches zero. However, we show that the collisionless Vlasov-Poisson system is a singular limit of the collisional Fokker-Planck-Poisson system, and Landau's result can be recovered only as the ν approaches zero from the positive side.

An application of a zero-inflated lifetime distribution with multiple and incomplete data sources

DOE PAGES

Hamada, M. S.; Margevicius, K. J.

2016-02-11

In this study, we analyze data sampled from a population of parts in which an associated anomaly can occur at assembly or after assembly. Using a zero-inflated lifetime distribution to fit left-censored and right-censored data as well data from a supplementary sample, we make predictions about the proportion of the population with anomalies today and in the future. Goodness-of-fit is also addressed.

Modeling the number of car theft using Poisson regression

NASA Astrophysics Data System (ADS)

Zulkifli, Malina; Ling, Agnes Beh Yen; Kasim, Maznah Mat; Ismail, Noriszura

2016-10-01

Regression analysis is the most popular statistical methods used to express the relationship between the variables of response with the covariates. The aim of this paper is to evaluate the factors that influence the number of car theft using Poisson regression model. This paper will focus on the number of car thefts that occurred in districts in Peninsular Malaysia. There are two groups of factor that have been considered, namely district descriptive factors and socio and demographic factors. The result of the study showed that Bumiputera composition, Chinese composition, Other ethnic composition, foreign migration, number of residence with the age between 25 to 64, number of employed person and number of unemployed person are the most influence factors that affect the car theft cases. These information are very useful for the law enforcement department, insurance company and car owners in order to reduce and limiting the car theft cases in Peninsular Malaysia.

Poisson regression models outperform the geometrical model in estimating the peak-to-trough ratio of seasonal variation: a simulation study.

PubMed

Christensen, A L; Lundbye-Christensen, S; Dethlefsen, C

2011-12-01

Several statistical methods of assessing seasonal variation are available. Brookhart and Rothman [3] proposed a second-order moment-based estimator based on the geometrical model derived by Edwards [1], and reported that this estimator is superior in estimating the peak-to-trough ratio of seasonal variation compared with Edwards' estimator with respect to bias and mean squared error. Alternatively, seasonal variation may be modelled using a Poisson regression model, which provides flexibility in modelling the pattern of seasonal variation and adjustments for covariates. Based on a Monte Carlo simulation study three estimators, one based on the geometrical model, and two based on log-linear Poisson regression models, were evaluated in regards to bias and standard deviation (SD). We evaluated the estimators on data simulated according to schemes varying in seasonal variation and presence of a secular trend. All methods and analyses in this paper are available in the R package Peak2Trough[13]. Applying a Poisson regression model resulted in lower absolute bias and SD for data simulated according to the corresponding model assumptions. Poisson regression models had lower bias and SD for data simulated to deviate from the corresponding model assumptions than the geometrical model. This simulation study encourages the use of Poisson regression models in estimating the peak-to-trough ratio of seasonal variation as opposed to the geometrical model. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

The Role of Depressive Symptoms, Family Invalidation and Behavioral Impulsivity in the Occurrence and Repetition of Non-Suicidal Self-Injury in Chinese Adolescents: A 2-Year Follow-Up Study

ERIC Educational Resources Information Center

You, Jianing; Leung, Freedom

2012-01-01

This study used zero-inflated poisson regression analysis to examine the role of depressive symptoms, family invalidation, and behavioral impulsivity in the occurrence and repetition of non-suicidal self-injury among Chinese community adolescents over a 2-year period. Participants, 4782 high school students, were assessed twice during the…

Zero-truncated panel Poisson mixture models: Estimating the impact on tourism benefits in Fukushima Prefecture.

PubMed

Narukawa, Masaki; Nohara, Katsuhito

2018-04-01

This study proposes an estimation approach to panel count data, truncated at zero, in order to apply a contingent behavior travel cost method to revealed and stated preference data collected via a web-based survey. We develop zero-truncated panel Poisson mixture models by focusing on respondents who visited a site. In addition, we introduce an inverse Gaussian distribution to unobserved individual heterogeneity as an alternative to a popular gamma distribution, making it possible to capture effectively the long tail typically observed in trip data. We apply the proposed method to estimate the impact on tourism benefits in Fukushima Prefecture as a result of the Fukushima Nuclear Power Plant No. 1 accident. Copyright © 2018 Elsevier Ltd. All rights reserved.

Zero inflation in ordinal data: Incorporating susceptibility to response through the use of a mixture model

PubMed Central

Kelley, Mary E.; Anderson, Stewart J.

2008-01-01

Summary The aim of the paper is to produce a methodology that will allow users of ordinal scale data to more accurately model the distribution of ordinal outcomes in which some subjects are susceptible to exhibiting the response and some are not (i.e., the dependent variable exhibits zero inflation). This situation occurs with ordinal scales in which there is an anchor that represents the absence of the symptom or activity, such as “none”, “never” or “normal”, and is particularly common when measuring abnormal behavior, symptoms, and side effects. Due to the unusually large number of zeros, traditional statistical tests of association can be non-informative. We propose a mixture model for ordinal data with a built-in probability of non-response that allows modeling of the range (e.g., severity) of the scale, while simultaneously modeling the presence/absence of the symptom. Simulations show that the model is well behaved and a likelihood ratio test can be used to choose between the zero-inflated and the traditional proportional odds model. The model, however, does have minor restrictions on the nature of the covariates that must be satisfied in order for the model to be identifiable. The method is particularly relevant for public health research such as large epidemiological surveys where more careful documentation of the reasons for response may be difficult. PMID:18351711

A semi-nonparametric Poisson regression model for analyzing motor vehicle crash data.

PubMed

Ye, Xin; Wang, Ke; Zou, Yajie; Lord, Dominique

2018-01-01

This paper develops a semi-nonparametric Poisson regression model to analyze motor vehicle crash frequency data collected from rural multilane highway segments in California, US. Motor vehicle crash frequency on rural highway is a topic of interest in the area of transportation safety due to higher driving speeds and the resultant severity level. Unlike the traditional Negative Binomial (NB) model, the semi-nonparametric Poisson regression model can accommodate an unobserved heterogeneity following a highly flexible semi-nonparametric (SNP) distribution. Simulation experiments are conducted to demonstrate that the SNP distribution can well mimic a large family of distributions, including normal distributions, log-gamma distributions, bimodal and trimodal distributions. Empirical estimation results show that such flexibility offered by the SNP distribution can greatly improve model precision and the overall goodness-of-fit. The semi-nonparametric distribution can provide a better understanding of crash data structure through its ability to capture potential multimodality in the distribution of unobserved heterogeneity. When estimated coefficients in empirical models are compared, SNP and NB models are found to have a substantially different coefficient for the dummy variable indicating the lane width. The SNP model with better statistical performance suggests that the NB model overestimates the effect of lane width on crash frequency reduction by 83.1%.

Protection from annual flooding is correlated with increased cholera prevalence in Bangladesh: a zero-inflated regression analysis.

PubMed

Carrel, Margaret; Voss, Paul; Streatfield, Peter K; Yunus, Mohammad; Emch, Michael

2010-03-22

Alteration of natural or historical aquatic flows can have unintended consequences for regions where waterborne diseases are endemic and where the epidemiologic implications of such change are poorly understood. The implementation of flood protection measures for a portion of an intensely monitored population in Matlab, Bangladesh, allows us to examine whether cholera outcomes respond positively or negatively to measures designed to control river flooding. Using a zero inflated negative binomial model, we examine how selected covariates can simultaneously account for household clusters reporting no cholera from those with positive counts as well as distinguishing residential areas with low counts from areas with high cholera counts. Our goal is to examine how residence within or outside a flood protected area interacts with the probability of cholera presence and the effect of flood protection on the magnitude of cholera prevalence. In Matlab, living in a household that is protected from annual monsoon flooding appears to have no significant effect on whether the household experiences cholera, net of other covariates. However, counter-intuitively, among households where cholera is reported, living within the flood protected region significantly increases the number of cholera cases. The construction of dams or other water impoundment strategies for economic or social motives can have profound and unanticipated consequences for waterborne disease. Our results indicate that the construction of a flood control structure in rural Bangladesh is correlated with an increase in cholera cases for residents protected from annual monsoon flooding. Such a finding requires attention from both the health community and from governments and non-governmental organizations involved in ongoing water management schemes.

Multinomial model and zero-inflated gamma model to study time spent on leisure time physical activity: an example of ELSA-Brasil.

PubMed

Nobre, Aline Araújo; Carvalho, Marilia Sá; Griep, Rosane Härter; Fonseca, Maria de Jesus Mendes da; Melo, Enirtes Caetano Prates; Santos, Itamar de Souza; Chor, Dora

2017-08-17

To compare two methodological approaches: the multinomial model and the zero-inflated gamma model, evaluating the factors associated with the practice and amount of time spent on leisure time physical activity. Data collected from 14,823 baseline participants in the Longitudinal Study of Adult Health (ELSA-Brasil - Estudo Longitudinal de Saúde do Adulto ) have been analysed. Regular leisure time physical activity has been measured using the leisure time physical activity module of the International Physical Activity Questionnaire. The explanatory variables considered were gender, age, education level, and annual per capita family income. The main advantage of the zero-inflated gamma model over the multinomial model is that it estimates mean time (minutes per week) spent on leisure time physical activity. For example, on average, men spent 28 minutes/week longer on leisure time physical activity than women did. The most sedentary groups were young women with low education level and income. The zero-inflated gamma model, which is rarely used in epidemiological studies, can give more appropriate answers in several situations. In our case, we have obtained important information on the main determinants of the duration of leisure time physical activity. This information can help guide efforts towards the most vulnerable groups since physical inactivity is associated with different diseases and even premature death.

A Spatial Poisson Hurdle Model for Exploring Geographic Variation in Emergency Department Visits

PubMed Central

Neelon, Brian; Ghosh, Pulak; Loebs, Patrick F.

2012-01-01

Summary We develop a spatial Poisson hurdle model to explore geographic variation in emergency department (ED) visits while accounting for zero inflation. The model consists of two components: a Bernoulli component that models the probability of any ED use (i.e., at least one ED visit per year), and a truncated Poisson component that models the number of ED visits given use. Together, these components address both the abundance of zeros and the right-skewed nature of the nonzero counts. The model has a hierarchical structure that incorporates patient- and area-level covariates, as well as spatially correlated random effects for each areal unit. Because regions with high rates of ED use are likely to have high expected counts among users, we model the spatial random effects via a bivariate conditionally autoregressive (CAR) prior, which introduces dependence between the components and provides spatial smoothing and sharing of information across neighboring regions. Using a simulation study, we show that modeling the between-component correlation reduces bias in parameter estimates. We adopt a Bayesian estimation approach, and the model can be fit using standard Bayesian software. We apply the model to a study of patient and neighborhood factors influencing emergency department use in Durham County, North Carolina. PMID:23543242

Estimating cavity tree and snag abundance using negative binomial regression models and nearest neighbor imputation methods

Treesearch

Bianca N.I. Eskelson; Hailemariam Temesgen; Tara M. Barrett

2009-01-01

Cavity tree and snag abundance data are highly variable and contain many zero observations. We predict cavity tree and snag abundance from variables that are readily available from forest cover maps or remotely sensed data using negative binomial (NB), zero-inflated NB, and zero-altered NB (ZANB) regression models as well as nearest neighbor (NN) imputation methods....

A quantile count model of water depth constraints on Cape Sable seaside sparrows

USGS Publications Warehouse

Cade, B.S.; Dong, Q.

2008-01-01

1. A quantile regression model for counts of breeding Cape Sable seaside sparrows Ammodramus maritimus mirabilis (L.) as a function of water depth and previous year abundance was developed based on extensive surveys, 1992-2005, in the Florida Everglades. The quantile count model extends linear quantile regression methods to discrete response variables, providing a flexible alternative to discrete parametric distributional models, e.g. Poisson, negative binomial and their zero-inflated counterparts. 2. Estimates from our multiplicative model demonstrated that negative effects of increasing water depth in breeding habitat on sparrow numbers were dependent on recent occupation history. Upper 10th percentiles of counts (one to three sparrows) decreased with increasing water depth from 0 to 30 cm when sites were not occupied in previous years. However, upper 40th percentiles of counts (one to six sparrows) decreased with increasing water depth for sites occupied in previous years. 3. Greatest decreases (-50% to -83%) in upper quantiles of sparrow counts occurred as water depths increased from 0 to 15 cm when previous year counts were 1, but a small proportion of sites (5-10%) held at least one sparrow even as water depths increased to 20 or 30 cm. 4. A zero-inflated Poisson regression model provided estimates of conditional means that also decreased with increasing water depth but rates of change were lower and decreased with increasing previous year counts compared to the quantile count model. Quantiles computed for the zero-inflated Poisson model enhanced interpretation of this model but had greater lack-of-fit for water depths > 0 cm and previous year counts 1, conditions where the negative effect of water depths were readily apparent and fitted better with the quantile count model.

Selecting the right statistical model for analysis of insect count data by using information theoretic measures.

PubMed

Sileshi, G

2006-10-01

Researchers and regulatory agencies often make statistical inferences from insect count data using modelling approaches that assume homogeneous variance. Such models do not allow for formal appraisal of variability which in its different forms is the subject of interest in ecology. Therefore, the objectives of this paper were to (i) compare models suitable for handling variance heterogeneity and (ii) select optimal models to ensure valid statistical inferences from insect count data. The log-normal, standard Poisson, Poisson corrected for overdispersion, zero-inflated Poisson, the negative binomial distribution and zero-inflated negative binomial models were compared using six count datasets on foliage-dwelling insects and five families of soil-dwelling insects. Akaike's and Schwarz Bayesian information criteria were used for comparing the various models. Over 50% of the counts were zeros even in locally abundant species such as Ootheca bennigseni Weise, Mesoplatys ochroptera Stål and Diaecoderus spp. The Poisson model after correction for overdispersion and the standard negative binomial distribution model provided better description of the probability distribution of seven out of the 11 insects than the log-normal, standard Poisson, zero-inflated Poisson or zero-inflated negative binomial models. It is concluded that excess zeros and variance heterogeneity are common data phenomena in insect counts. If not properly modelled, these properties can invalidate the normal distribution assumptions resulting in biased estimation of ecological effects and jeopardizing the integrity of the scientific inferences. Therefore, it is recommended that statistical models appropriate for handling these data properties be selected using objective criteria to ensure efficient statistical inference.

Regular exercise and related factors in patients with Parkinson's disease: Applying zero-inflated negative binomial modeling of exercise count data.

PubMed

Lee, JuHee; Park, Chang Gi; Choi, Moonki

2016-05-01

This study was conducted to identify risk factors that influence regular exercise among patients with Parkinson's disease in Korea. Parkinson's disease is prevalent in the elderly, and may lead to a sedentary lifestyle. Exercise can enhance physical and psychological health. However, patients with Parkinson's disease are less likely to exercise than are other populations due to physical disability. A secondary data analysis and cross-sectional descriptive study were conducted. A convenience sample of 106 patients with Parkinson's disease was recruited at an outpatient neurology clinic of a tertiary hospital in Korea. Demographic characteristics, disease-related characteristics (including disease duration and motor symptoms), self-efficacy for exercise, balance, and exercise level were investigated. Negative binomial regression and zero-inflated negative binomial regression for exercise count data were utilized to determine factors involved in exercise. The mean age of participants was 65.85 ± 8.77 years, and the mean duration of Parkinson's disease was 7.23 ± 6.02 years. Most participants indicated that they engaged in regular exercise (80.19%). Approximately half of participants exercised at least 5 days per week for 30 min, as recommended (51.9%). Motor symptoms were a significant predictor of exercise in the count model, and self-efficacy for exercise was a significant predictor of exercise in the zero model. Severity of motor symptoms was related to frequency of exercise. Self-efficacy contributed to the probability of exercise. Symptom management and improvement of self-efficacy for exercise are important to encourage regular exercise in patients with Parkinson's disease. Copyright © 2015 Elsevier Inc. All rights reserved.

Logistic regression for dichotomized counts.

PubMed

Preisser, John S; Das, Kalyan; Benecha, Habtamu; Stamm, John W

2016-12-01

Sometimes there is interest in a dichotomized outcome indicating whether a count variable is positive or zero. Under this scenario, the application of ordinary logistic regression may result in efficiency loss, which is quantifiable under an assumed model for the counts. In such situations, a shared-parameter hurdle model is investigated for more efficient estimation of regression parameters relating to overall effects of covariates on the dichotomous outcome, while handling count data with many zeroes. One model part provides a logistic regression containing marginal log odds ratio effects of primary interest, while an ancillary model part describes the mean count of a Poisson or negative binomial process in terms of nuisance regression parameters. Asymptotic efficiency of the logistic model parameter estimators of the two-part models is evaluated with respect to ordinary logistic regression. Simulations are used to assess the properties of the models with respect to power and Type I error, the latter investigated under both misspecified and correctly specified models. The methods are applied to data from a randomized clinical trial of three toothpaste formulations to prevent incident dental caries in a large population of Scottish schoolchildren. © The Author(s) 2014.

Zero-truncated negative binomial - Erlang distribution

NASA Astrophysics Data System (ADS)

Bodhisuwan, Winai; Pudprommarat, Chookait; Bodhisuwan, Rujira; Saothayanun, Luckhana

2017-11-01

The zero-truncated negative binomial-Erlang distribution is introduced. It is developed from negative binomial-Erlang distribution. In this work, the probability mass function is derived and some properties are included. The parameters of the zero-truncated negative binomial-Erlang distribution are estimated by using the maximum likelihood estimation. Finally, the proposed distribution is applied to real data, the number of methamphetamine in the Bangkok, Thailand. Based on the results, it shows that the zero-truncated negative binomial-Erlang distribution provided a better fit than the zero-truncated Poisson, zero-truncated negative binomial, zero-truncated generalized negative-binomial and zero-truncated Poisson-Lindley distributions for this data.

Antibiotic Resistances in Livestock: A Comparative Approach to Identify an Appropriate Regression Model for Count Data

PubMed Central

Hüls, Anke; Frömke, Cornelia; Ickstadt, Katja; Hille, Katja; Hering, Johanna; von Münchhausen, Christiane; Hartmann, Maria; Kreienbrock, Lothar

2017-01-01

Antimicrobial resistance in livestock is a matter of general concern. To develop hygiene measures and methods for resistance prevention and control, epidemiological studies on a population level are needed to detect factors associated with antimicrobial resistance in livestock holdings. In general, regression models are used to describe these relationships between environmental factors and resistance outcome. Besides the study design, the correlation structures of the different outcomes of antibiotic resistance and structural zero measurements on the resistance outcome as well as on the exposure side are challenges for the epidemiological model building process. The use of appropriate regression models that acknowledge these complexities is essential to assure valid epidemiological interpretations. The aims of this paper are (i) to explain the model building process comparing several competing models for count data (negative binomial model, quasi-Poisson model, zero-inflated model, and hurdle model) and (ii) to compare these models using data from a cross-sectional study on antibiotic resistance in animal husbandry. These goals are essential to evaluate which model is most suitable to identify potential prevention measures. The dataset used as an example in our analyses was generated initially to study the prevalence and associated factors for the appearance of cefotaxime-resistant Escherichia coli in 48 German fattening pig farms. For each farm, the outcome was the count of samples with resistant bacteria. There was almost no overdispersion and only moderate evidence of excess zeros in the data. Our analyses show that it is essential to evaluate regression models in studies analyzing the relationship between environmental factors and antibiotic resistances in livestock. After model comparison based on evaluation of model predictions, Akaike information criterion, and Pearson residuals, here the hurdle model was judged to be the most appropriate model. PMID

Bayesian semi-parametric analysis of Poisson change-point regression models: application to policy making in Cali, Colombia.

PubMed

Park, Taeyoung; Krafty, Robert T; Sánchez, Alvaro I

2012-07-27

A Poisson regression model with an offset assumes a constant baseline rate after accounting for measured covariates, which may lead to biased estimates of coefficients in an inhomogeneous Poisson process. To correctly estimate the effect of time-dependent covariates, we propose a Poisson change-point regression model with an offset that allows a time-varying baseline rate. When the nonconstant pattern of a log baseline rate is modeled with a nonparametric step function, the resulting semi-parametric model involves a model component of varying dimension and thus requires a sophisticated varying-dimensional inference to obtain correct estimates of model parameters of fixed dimension. To fit the proposed varying-dimensional model, we devise a state-of-the-art MCMC-type algorithm based on partial collapse. The proposed model and methods are used to investigate an association between daily homicide rates in Cali, Colombia and policies that restrict the hours during which the legal sale of alcoholic beverages is permitted. While simultaneously identifying the latent changes in the baseline homicide rate which correspond to the incidence of sociopolitical events, we explore the effect of policies governing the sale of alcohol on homicide rates and seek a policy that balances the economic and cultural dependencies on alcohol sales to the health of the public.

A comparison of different statistical methods analyzing hypoglycemia data using bootstrap simulations.

PubMed

Jiang, Honghua; Ni, Xiao; Huster, William; Heilmann, Cory

2015-01-01

Hypoglycemia has long been recognized as a major barrier to achieving normoglycemia with intensive diabetic therapies. It is a common safety concern for the diabetes patients. Therefore, it is important to apply appropriate statistical methods when analyzing hypoglycemia data. Here, we carried out bootstrap simulations to investigate the performance of the four commonly used statistical models (Poisson, negative binomial, analysis of covariance [ANCOVA], and rank ANCOVA) based on the data from a diabetes clinical trial. Zero-inflated Poisson (ZIP) model and zero-inflated negative binomial (ZINB) model were also evaluated. Simulation results showed that Poisson model inflated type I error, while negative binomial model was overly conservative. However, after adjusting for dispersion, both Poisson and negative binomial models yielded slightly inflated type I errors, which were close to the nominal level and reasonable power. Reasonable control of type I error was associated with ANCOVA model. Rank ANCOVA model was associated with the greatest power and with reasonable control of type I error. Inflated type I error was observed with ZIP and ZINB models.

Three-part joint modeling methods for complex functional data mixed with zero-and-one-inflated proportions and zero-inflated continuous outcomes with skewness.

PubMed

Li, Haocheng; Staudenmayer, John; Wang, Tianying; Keadle, Sarah Kozey; Carroll, Raymond J

2018-02-20

We take a functional data approach to longitudinal studies with complex bivariate outcomes. This work is motivated by data from a physical activity study that measured 2 responses over time in 5-minute intervals. One response is the proportion of time active in each interval, a continuous proportions with excess zeros and ones. The other response, energy expenditure rate in the interval, is a continuous variable with excess zeros and skewness. This outcome is complex because there are 3 possible activity patterns in each interval (inactive, partially active, and completely active), and those patterns, which are observed, induce both nonrandom and random associations between the responses. More specifically, the inactive pattern requires a zero value in both the proportion for active behavior and the energy expenditure rate; a partially active pattern means that the proportion of activity is strictly between zero and one and that the energy expenditure rate is greater than zero and likely to be moderate, and the completely active pattern means that the proportion of activity is exactly one, and the energy expenditure rate is greater than zero and likely to be higher. To address these challenges, we propose a 3-part functional data joint modeling approach. The first part is a continuation-ratio model to reorder the ordinal valued 3 activity patterns. The second part models the proportions when they are in interval (0,1). The last component specifies the skewed continuous energy expenditure rate with Box-Cox transformations when they are greater than zero. In this 3-part model, the regression structures are specified as smooth curves measured at various time points with random effects that have a correlation structure. The smoothed random curves for each variable are summarized using a few important principal components, and the association of the 3 longitudinal components is modeled through the association of the principal component scores. The difficulties in

MIXED MODEL AND ESTIMATING EQUATION APPROACHES FOR ZERO INFLATION IN CLUSTERED BINARY RESPONSE DATA WITH APPLICATION TO A DATING VIOLENCE STUDY1

PubMed Central

Fulton, Kara A.; Liu, Danping; Haynie, Denise L.; Albert, Paul S.

2016-01-01

The NEXT Generation Health study investigates the dating violence of adolescents using a survey questionnaire. Each student is asked to affirm or deny multiple instances of violence in his/her dating relationship. There is, however, evidence suggesting that students not in a relationship responded to the survey, resulting in excessive zeros in the responses. This paper proposes likelihood-based and estimating equation approaches to analyze the zero-inflated clustered binary response data. We adopt a mixed model method to account for the cluster effect, and the model parameters are estimated using a maximum-likelihood (ML) approach that requires a Gaussian–Hermite quadrature (GHQ) approximation for implementation. Since an incorrect assumption on the random effects distribution may bias the results, we construct generalized estimating equations (GEE) that do not require the correct specification of within-cluster correlation. In a series of simulation studies, we examine the performance of ML and GEE methods in terms of their bias, efficiency and robustness. We illustrate the importance of properly accounting for this zero inflation by reanalyzing the NEXT data where this issue has previously been ignored. PMID:26937263

Modeling number of claims and prediction of total claim amount

NASA Astrophysics Data System (ADS)

Acar, Aslıhan Şentürk; Karabey, Uǧur

2017-07-01

In this study we focus on annual number of claims of a private health insurance data set which belongs to a local insurance company in Turkey. In addition to Poisson model and negative binomial model, zero-inflated Poisson model and zero-inflated negative binomial model are used to model the number of claims in order to take into account excess zeros. To investigate the impact of different distributional assumptions for the number of claims on the prediction of total claim amount, predictive performances of candidate models are compared by using root mean square error (RMSE) and mean absolute error (MAE) criteria.

Analysis of overdispersed count data: application to the Human Papillomavirus Infection in Men (HIM) Study.

PubMed

Lee, J-H; Han, G; Fulp, W J; Giuliano, A R

2012-06-01

The Poisson model can be applied to the count of events occurring within a specific time period. The main feature of the Poisson model is the assumption that the mean and variance of the count data are equal. However, this equal mean-variance relationship rarely occurs in observational data. In most cases, the observed variance is larger than the assumed variance, which is called overdispersion. Further, when the observed data involve excessive zero counts, the problem of overdispersion results in underestimating the variance of the estimated parameter, and thus produces a misleading conclusion. We illustrated the use of four models for overdispersed count data that may be attributed to excessive zeros. These are Poisson, negative binomial, zero-inflated Poisson and zero-inflated negative binomial models. The example data in this article deal with the number of incidents involving human papillomavirus infection. The four models resulted in differing statistical inferences. The Poisson model, which is widely used in epidemiology research, underestimated the standard errors and overstated the significance of some covariates.

Tobit analysis of vehicle accident rates on interstate highways.

PubMed

Anastasopoulos, Panagiotis Ch; Tarko, Andrew P; Mannering, Fred L

2008-03-01

There has been an abundance of research that has used Poisson models and its variants (negative binomial and zero-inflated models) to improve our understanding of the factors that affect accident frequencies on roadway segments. This study explores the application of an alternate method, tobit regression, by viewing vehicle accident rates directly (instead of frequencies) as a continuous variable that is left-censored at zero. Using data from vehicle accidents on Indiana interstates, the estimation results show that many factors relating to pavement condition, roadway geometrics and traffic characteristics significantly affect vehicle accident rates.

Geographically weighted poisson regression semiparametric on modeling of the number of tuberculosis cases (Case study: Bandung city)

NASA Astrophysics Data System (ADS)

Octavianty, Toharudin, Toni; Jaya, I. G. N. Mindra

2017-03-01

Tuberculosis (TB) is a disease caused by a bacterium, called Mycobacterium tuberculosis, which typically attacks the lungs but can also affect the kidney, spine, and brain (Centers for Disease Control and Prevention). Indonesia had the largest number of TB cases after India (Global Tuberculosis Report 2015 by WHO). The distribution of Mycobacterium tuberculosis genotypes in Indonesia showed the high genetic diversity and tended to vary by geographic regions. For instance, in Bandung city, the prevalence rate of TB morbidity is quite high. A number of TB patients belong to the counted data. To determine the factors that significantly influence the number of tuberculosis patients in each location of the observations can be used statistical analysis tool that is Geographically Weighted Poisson Regression Semiparametric (GWPRS). GWPRS is an extension of the Poisson regression and GWPR that is influenced by geographical factors, and there is also variables that influence globally and locally. Using the TB Data in Bandung city (in 2015), the results show that the global and local variables that influence the number of tuberculosis patients in every sub-district.

Systematic review of treatment modalities for gingival depigmentation: a random-effects poisson regression analysis.

PubMed

Lin, Yi Hung; Tu, Yu Kang; Lu, Chun Tai; Chung, Wen Chen; Huang, Chiung Fang; Huang, Mao Suan; Lu, Hsein Kun

2014-01-01

Repigmentation variably occurs with different treatment methods in patients with gingival pigmentation. A systemic review was conducted of various treatment modalities for eliminating melanin pigmentation of the gingiva, comprising bur abrasion, scalpel surgery, cryosurgery, electrosurgery, gingival grafts, and laser techniques, to compare the recurrence rates (Rrs) of these treatment procedures. Electronic databases, including PubMed, Web of Science, Google, and Medline were comprehensively searched, and manual searches were conducted for studies published from January 1951 to June 2013. After applying inclusion and exclusion criteria, the final list of articles was reviewed in depth to achieve the objectives of this review. A Poisson regression was used to analyze the outcome of depigmentation using the various treatment methods. The systematic review was based on case reports mainly. In total, 61 eligible publications met the defined criteria. The various therapeutic procedures showed variable clinical results with a wide range of Rrs. A random-effects Poisson regression showed that cryosurgery (Rr = 0.32%), electrosurgery (Rr = 0.74%), and laser depigmentation (Rr = 1.16%) yielded superior result, whereas bur abrasion yielded the highest Rr (8.89%). Within the limit of the sampling level, the present evidence-based results show that cryosurgery exhibits the optimal predictability for depigmentation of the gingiva among all procedures examined, followed by electrosurgery and laser techniques. It is possible to treat melanin pigmentation of the gingiva with various methods and prevent repigmentation. Among those treatment modalities, cryosurgery, electrosurgery, and laser surgery appear to be the best choices for treating gingival pigmentation. © 2014 Wiley Periodicals, Inc.

A smooth exit from eternal inflation?

NASA Astrophysics Data System (ADS)

Hawking, S. W.; Hertog, Thomas

2018-04-01

The usual theory of inflation breaks down in eternal inflation. We derive a dual description of eternal inflation in terms of a deformed Euclidean CFT located at the threshold of eternal inflation. The partition function gives the amplitude of different geometries of the threshold surface in the no-boundary state. Its local and global behavior in dual toy models shows that the amplitude is low for surfaces which are not nearly conformal to the round three-sphere and essentially zero for surfaces with negative curvature. Based on this we conjecture that the exit from eternal inflation does not produce an infinite fractal-like multiverse, but is finite and reasonably smooth.

The effect of a major cigarette price change on smoking behavior in california: a zero-inflated negative binomial model.

PubMed

Sheu, Mei-Ling; Hu, Teh-Wei; Keeler, Theodore E; Ong, Michael; Sung, Hai-Yen

2004-08-01

The objective of this paper is to determine the price sensitivity of smokers in their consumption of cigarettes, using evidence from a major increase in California cigarette prices due to Proposition 10 and the Tobacco Settlement. The study sample consists of individual survey data from Behavioral Risk Factor Survey (BRFS) and price data from the Bureau of Labor Statistics between 1996 and 1999. A zero-inflated negative binomial (ZINB) regression model was applied for the statistical analysis. The statistical model showed that price did not have an effect on reducing the estimated prevalence of smoking. However, it indicated that among smokers the price elasticity was at the level of -0.46 and statistically significant. Since smoking prevalence is significantly lower than it was a decade ago, price increases are becoming less effective as an inducement for hard-core smokers to quit, although they may respond by decreasing consumption. For those who only smoke occasionally (many of them being young adults) price increases alone may not be an effective inducement to quit smoking. Additional underlying behavioral factors need to be identified so that more effective anti-smoking strategies can be developed.

Effects of categorization method, regression type, and variable distribution on the inflation of Type-I error rate when categorizing a confounding variable.

PubMed

Barnwell-Ménard, Jean-Louis; Li, Qing; Cohen, Alan A

2015-03-15

The loss of signal associated with categorizing a continuous variable is well known, and previous studies have demonstrated that this can lead to an inflation of Type-I error when the categorized variable is a confounder in a regression analysis estimating the effect of an exposure on an outcome. However, it is not known how the Type-I error may vary under different circumstances, including logistic versus linear regression, different distributions of the confounder, and different categorization methods. Here, we analytically quantified the effect of categorization and then performed a series of 9600 Monte Carlo simulations to estimate the Type-I error inflation associated with categorization of a confounder under different regression scenarios. We show that Type-I error is unacceptably high (>10% in most scenarios and often 100%). The only exception was when the variable categorized was a continuous mixture proxy for a genuinely dichotomous latent variable, where both the continuous proxy and the categorized variable are error-ridden proxies for the dichotomous latent variable. As expected, error inflation was also higher with larger sample size, fewer categories, and stronger associations between the confounder and the exposure or outcome. We provide online tools that can help researchers estimate the potential error inflation and understand how serious a problem this is. Copyright © 2014 John Wiley & Sons, Ltd.

Modeling urban coastal flood severity from crowd-sourced flood reports using Poisson regression and Random Forest

NASA Astrophysics Data System (ADS)

Sadler, J. M.; Goodall, J. L.; Morsy, M. M.; Spencer, K.

2018-04-01

Sea level rise has already caused more frequent and severe coastal flooding and this trend will likely continue. Flood prediction is an essential part of a coastal city's capacity to adapt to and mitigate this growing problem. Complex coastal urban hydrological systems however, do not always lend themselves easily to physically-based flood prediction approaches. This paper presents a method for using a data-driven approach to estimate flood severity in an urban coastal setting using crowd-sourced data, a non-traditional but growing data source, along with environmental observation data. Two data-driven models, Poisson regression and Random Forest regression, are trained to predict the number of flood reports per storm event as a proxy for flood severity, given extensive environmental data (i.e., rainfall, tide, groundwater table level, and wind conditions) as input. The method is demonstrated using data from Norfolk, Virginia USA from September 2010 to October 2016. Quality-controlled, crowd-sourced street flooding reports ranging from 1 to 159 per storm event for 45 storm events are used to train and evaluate the models. Random Forest performed better than Poisson regression at predicting the number of flood reports and had a lower false negative rate. From the Random Forest model, total cumulative rainfall was by far the most dominant input variable in predicting flood severity, followed by low tide and lower low tide. These methods serve as a first step toward using data-driven methods for spatially and temporally detailed coastal urban flood prediction.

Dark energy from gravitoelectromagnetic inflation?

NASA Astrophysics Data System (ADS)

Membiela, F. A.; Bellini, M.

2008-02-01

Gravitoectromagnetic Inflation (GI) was introduced to describe in an unified manner, electromagnetic, gravitatory and inflaton fields from a 5D vacuum state. On the other hand, the primordial origin and evolution of dark energy is today unknown. In this letter we show using GI that the zero modes of some redefined vector fields $B_i=A_i/a$ produced during inflation, could be the source of dark energy in the universe.

Computation of solar perturbations with Poisson series

NASA Technical Reports Server (NTRS)

Broucke, R.

1974-01-01

Description of a project for computing first-order perturbations of natural or artificial satellites by integrating the equations of motion on a computer with automatic Poisson series expansions. A basic feature of the method of solution is that the classical variation-of-parameters formulation is used rather than rectangular coordinates. However, the variation-of-parameters formulation uses the three rectangular components of the disturbing force rather than the classical disturbing function, so that there is no problem in expanding the disturbing function in series. Another characteristic of the variation-of-parameters formulation employed is that six rather unusual variables are used in order to avoid singularities at the zero eccentricity and zero (or 90 deg) inclination. The integration process starts by assuming that all the orbit elements present on the right-hand sides of the equations of motion are constants. These right-hand sides are then simple Poisson series which can be obtained with the use of the Bessel expansions of the two-body problem in conjunction with certain interation methods. These Poisson series can then be integrated term by term, and a first-order solution is obtained.

Predictors of the number of under-five malnourished children in Bangladesh: application of the generalized poisson regression model

PubMed Central

2013-01-01

Background Malnutrition is one of the principal causes of child mortality in developing countries including Bangladesh. According to our knowledge, most of the available studies, that addressed the issue of malnutrition among under-five children, considered the categorical (dichotomous/polychotomous) outcome variables and applied logistic regression (binary/multinomial) to find their predictors. In this study malnutrition variable (i.e. outcome) is defined as the number of under-five malnourished children in a family, which is a non-negative count variable. The purposes of the study are (i) to demonstrate the applicability of the generalized Poisson regression (GPR) model as an alternative of other statistical methods and (ii) to find some predictors of this outcome variable. Methods The data is extracted from the Bangladesh Demographic and Health Survey (BDHS) 2007. Briefly, this survey employs a nationally representative sample which is based on a two-stage stratified sample of households. A total of 4,460 under-five children is analysed using various statistical techniques namely Chi-square test and GPR model. Results The GPR model (as compared to the standard Poisson regression and negative Binomial regression) is found to be justified to study the above-mentioned outcome variable because of its under-dispersion (variance < mean) property. Our study also identify several significant predictors of the outcome variable namely mother’s education, father’s education, wealth index, sanitation status, source of drinking water, and total number of children ever born to a woman. Conclusions Consistencies of our findings in light of many other studies suggest that the GPR model is an ideal alternative of other statistical models to analyse the number of under-five malnourished children in a family. Strategies based on significant predictors may improve the nutritional status of children in Bangladesh. PMID:23297699

Modelling fourier regression for time series data- a case study: modelling inflation in foods sector in Indonesia

NASA Astrophysics Data System (ADS)

Prahutama, Alan; Suparti; Wahyu Utami, Tiani

2018-03-01

Regression analysis is an analysis to model the relationship between response variables and predictor variables. The parametric approach to the regression model is very strict with the assumption, but nonparametric regression model isn’t need assumption of model. Time series data is the data of a variable that is observed based on a certain time, so if the time series data wanted to be modeled by regression, then we should determined the response and predictor variables first. Determination of the response variable in time series is variable in t-th (yt), while the predictor variable is a significant lag. In nonparametric regression modeling, one developing approach is to use the Fourier series approach. One of the advantages of nonparametric regression approach using Fourier series is able to overcome data having trigonometric distribution. In modeling using Fourier series needs parameter of K. To determine the number of K can be used Generalized Cross Validation method. In inflation modeling for the transportation sector, communication and financial services using Fourier series yields an optimal K of 120 parameters with R-square 99%. Whereas if it was modeled by multiple linear regression yield R-square 90%.

Weibull mixture regression for marginal inference in zero-heavy continuous outcomes.

PubMed

Gebregziabher, Mulugeta; Voronca, Delia; Teklehaimanot, Abeba; Santa Ana, Elizabeth J

2017-06-01

Continuous outcomes with preponderance of zero values are ubiquitous in data that arise from biomedical studies, for example studies of addictive disorders. This is known to lead to violation of standard assumptions in parametric inference and enhances the risk of misleading conclusions unless managed properly. Two-part models are commonly used to deal with this problem. However, standard two-part models have limitations with respect to obtaining parameter estimates that have marginal interpretation of covariate effects which are important in many biomedical applications. Recently marginalized two-part models are proposed but their development is limited to log-normal and log-skew-normal distributions. Thus, in this paper, we propose a finite mixture approach, with Weibull mixture regression as a special case, to deal with the problem. We use extensive simulation study to assess the performance of the proposed model in finite samples and to make comparisons with other family of models via statistical information and mean squared error criteria. We demonstrate its application on real data from a randomized controlled trial of addictive disorders. Our results show that a two-component Weibull mixture model is preferred for modeling zero-heavy continuous data when the non-zero part are simulated from Weibull or similar distributions such as Gamma or truncated Gauss.

Decoding and modelling of time series count data using Poisson hidden Markov model and Markov ordinal logistic regression models.

PubMed

Sebastian, Tunny; Jeyaseelan, Visalakshi; Jeyaseelan, Lakshmanan; Anandan, Shalini; George, Sebastian; Bangdiwala, Shrikant I

2018-01-01

Hidden Markov models are stochastic models in which the observations are assumed to follow a mixture distribution, but the parameters of the components are governed by a Markov chain which is unobservable. The issues related to the estimation of Poisson-hidden Markov models in which the observations are coming from mixture of Poisson distributions and the parameters of the component Poisson distributions are governed by an m-state Markov chain with an unknown transition probability matrix are explained here. These methods were applied to the data on Vibrio cholerae counts reported every month for 11-year span at Christian Medical College, Vellore, India. Using Viterbi algorithm, the best estimate of the state sequence was obtained and hence the transition probability matrix. The mean passage time between the states were estimated. The 95% confidence interval for the mean passage time was estimated via Monte Carlo simulation. The three hidden states of the estimated Markov chain are labelled as 'Low', 'Moderate' and 'High' with the mean counts of 1.4, 6.6 and 20.2 and the estimated average duration of stay of 3, 3 and 4 months, respectively. Environmental risk factors were studied using Markov ordinal logistic regression analysis. No significant association was found between disease severity levels and climate components.

Statistical procedures for analyzing mental health services data.

PubMed

Elhai, Jon D; Calhoun, Patrick S; Ford, Julian D

2008-08-15

In mental health services research, analyzing service utilization data often poses serious problems, given the presence of substantially skewed data distributions. This article presents a non-technical introduction to statistical methods specifically designed to handle the complexly distributed datasets that represent mental health service use, including Poisson, negative binomial, zero-inflated, and zero-truncated regression models. A flowchart is provided to assist the investigator in selecting the most appropriate method. Finally, a dataset of mental health service use reported by medical patients is described, and a comparison of results across several different statistical methods is presented. Implications of matching data analytic techniques appropriately with the often complexly distributed datasets of mental health services utilization variables are discussed.

Quasiopen inflation

NASA Astrophysics Data System (ADS)

García-Bellido, Juan; Garriga, Jaume; Montes, Xavier

1998-04-01

We show that a large class of two-field models of single-bubble open inflation does not lead to infinite open universes, as was previously thought, but to an ensemble of very large but finite inflating ``islands.'' The reason is that the quantum tunneling responsible for the nucleation of the bubble does not occur simultaneously along both field directions and equal-time hypersurfaces in the open universe are not synchronized with equal-density or fixed-field hypersurfaces. The most probable tunneling trajectory corresponds to a zero value of the inflaton field; large values, necessary for the second period of inflation inside the bubble, only arise as localized fluctuations. The interior of each nucleated bubble will contain an infinite number of such inflating regions of comoving size of order γ-1, where γ is the supercurvature eigenvalue, which depends on the parameters of the model. Each one of these islands will be a quasi-open universe. Since the volume of the hyperboloid is infinite, inflating islands with all possible values of the field at their center will be realized inside of a single bubble. We may happen to live in one of those patches of comoving size d<~γ-1, where the universe appears to be open. In particular, we consider the ``supernatural'' model proposed by Linde and Mezhlumian. There, an approximate U(1) symmetry is broken by a tunneling field in a first order phase transition, and slow-roll inflation inside the nucleated bubble is driven by the pseudo Goldstone field. We find that the excitations of the pseudo Goldstone field produced by the nucleation and subsequent expansion of the bubble place severe constraints on this model. We also discuss the coupled and uncoupled two-field models.

Logistic quantile regression provides improved estimates for bounded avian counts: a case study of California Spotted Owl fledgling production

Treesearch

Brian S. Cade; Barry R. Noon; Rick D. Scherer; John J. Keane

2017-01-01

Counts of avian fledglings, nestlings, or clutch size that are bounded below by zero and above by some small integer form a discrete random variable distribution that is not approximated well by conventional parametric count distributions such as the Poisson or negative binomial. We developed a logistic quantile regression model to provide estimates of the empirical...

Conditional Poisson models: a flexible alternative to conditional logistic case cross-over analysis.

PubMed

Armstrong, Ben G; Gasparrini, Antonio; Tobias, Aurelio

2014-11-24

The time stratified case cross-over approach is a popular alternative to conventional time series regression for analysing associations between time series of environmental exposures (air pollution, weather) and counts of health outcomes. These are almost always analyzed using conditional logistic regression on data expanded to case-control (case crossover) format, but this has some limitations. In particular adjusting for overdispersion and auto-correlation in the counts is not possible. It has been established that a Poisson model for counts with stratum indicators gives identical estimates to those from conditional logistic regression and does not have these limitations, but it is little used, probably because of the overheads in estimating many stratum parameters. The conditional Poisson model avoids estimating stratum parameters by conditioning on the total event count in each stratum, thus simplifying the computing and increasing the number of strata for which fitting is feasible compared with the standard unconditional Poisson model. Unlike the conditional logistic model, the conditional Poisson model does not require expanding the data, and can adjust for overdispersion and auto-correlation. It is available in Stata, R, and other packages. By applying to some real data and using simulations, we demonstrate that conditional Poisson models were simpler to code and shorter to run than are conditional logistic analyses and can be fitted to larger data sets than possible with standard Poisson models. Allowing for overdispersion or autocorrelation was possible with the conditional Poisson model but when not required this model gave identical estimates to those from conditional logistic regression. Conditional Poisson regression models provide an alternative to case crossover analysis of stratified time series data with some advantages. The conditional Poisson model can also be used in other contexts in which primary control for confounding is by fine

Non-linear properties of metallic cellular materials with a negative Poisson's ratio

NASA Technical Reports Server (NTRS)

Choi, J. B.; Lakes, R. S.

1992-01-01

Negative Poisson's ratio copper foam was prepared and characterized experimentally. The transformation into re-entrant foam was accomplished by applying sequential permanent compressions above the yield point to achieve a triaxial compression. The Poisson's ratio of the re-entrant foam depended on strain and attained a relative minimum at strains near zero. Poisson's ratio as small as -0.8 was achieved. The strain dependence of properties occurred over a narrower range of strain than in the polymer foams studied earlier. Annealing of the foam resulted in a slightly greater magnitude of negative Poisson's ratio and greater toughness at the expense of a decrease in the Young's modulus.

Efficiency optimization of a fast Poisson solver in beam dynamics simulation

NASA Astrophysics Data System (ADS)

Zheng, Dawei; Pöplau, Gisela; van Rienen, Ursula

2016-01-01

Calculating the solution of Poisson's equation relating to space charge force is still the major time consumption in beam dynamics simulations and calls for further improvement. In this paper, we summarize a classical fast Poisson solver in beam dynamics simulations: the integrated Green's function method. We introduce three optimization steps of the classical Poisson solver routine: using the reduced integrated Green's function instead of the integrated Green's function; using the discrete cosine transform instead of discrete Fourier transform for the Green's function; using a novel fast convolution routine instead of an explicitly zero-padded convolution. The new Poisson solver routine preserves the advantages of fast computation and high accuracy. This provides a fast routine for high performance calculation of the space charge effect in accelerators.

Analyzing Seasonal Variations in Suicide With Fourier Poisson Time-Series Regression: A Registry-Based Study From Norway, 1969-2007.

PubMed

Bramness, Jørgen G; Walby, Fredrik A; Morken, Gunnar; Røislien, Jo

2015-08-01

Seasonal variation in the number of suicides has long been acknowledged. It has been suggested that this seasonality has declined in recent years, but studies have generally used statistical methods incapable of confirming this. We examined all suicides occurring in Norway during 1969-2007 (more than 20,000 suicides in total) to establish whether seasonality decreased over time. Fitting of additive Fourier Poisson time-series regression models allowed for formal testing of a possible linear decrease in seasonality, or a reduction at a specific point in time, while adjusting for a possible smooth nonlinear long-term change without having to categorize time into discrete yearly units. The models were compared using Akaike's Information Criterion and analysis of variance. A model with a seasonal pattern was significantly superior to a model without one. There was a reduction in seasonality during the period. Both the model assuming a linear decrease in seasonality and the model assuming a change at a specific point in time were both superior to a model assuming constant seasonality, thus confirming by formal statistical testing that the magnitude of the seasonality in suicides has diminished. The additive Fourier Poisson time-series regression model would also be useful for studying other temporal phenomena with seasonal components. © The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

The Use of a Poisson Regression to Evaluate Antihistamines and Fatal Aircraft Mishaps in Instrument Meteorological Conditions.

PubMed

Gildea, Kevin M; Hileman, Christy R; Rogers, Paul; Salazar, Guillermo J; Paskoff, Lawrence N

2018-04-01

Research indicates that first-generation antihistamine usage may impair pilot performance by increasing the likelihood of vestibular illusions, spatial disorientation, and/or cognitive impairment. Second- and third-generation antihistamines generally have fewer impairing side effects and are approved for pilot use. We hypothesized that toxicological findings positive for second- and third-generation antihistamines are less likely to be associated with pilots involved in fatal mishaps than first-generation antihistamines. The evaluated population consisted of 1475 U.S. civil pilots fatally injured between September 30, 2008, and October 1, 2014. Mishap factors evaluated included year, weather conditions, airman rating, recent airman flight time, quarter of year, and time of day. Due to the low prevalence of positive antihistamine findings, a count-based model was selected, which can account for rare outcomes. The means and variances were close for both regression models supporting the assumption that the data follow a Poisson distribution; first-generation antihistamine mishap airmen (N = 582, M = 0.17, S2 = 0.17) with second- and third-generation antihistamine mishap airmen (N = 116, M = 0.20, S2 = 0.18). The data indicate fewer airmen with second- and third-generation antihistamines than first-generation antihistamines in their system are fatally injured while flying in IMC conditions. Whether the lower incidence is a factor of greater usage of first-generation antihistamines versus second- and third-generation antihistamines by the pilot population or fewer deleterious side effects with second- and third-generation antihistamines is unclear. These results engender cautious optimism, but additional research is necessary to determine why these differences exist.Gildea KM, Hileman CR, Rogers P, Salazar GJ, Paskoff LN. The use of a Poisson regression to evaluate antihistamines and fatal aircraft mishaps in instrument meteorological conditions. Aerosp Med Hum Perform

The BRST complex of homological Poisson reduction

NASA Astrophysics Data System (ADS)

Müller-Lennert, Martin

2017-02-01

BRST complexes are differential graded Poisson algebras. They are associated with a coisotropic ideal J of a Poisson algebra P and provide a description of the Poisson algebra (P/J)^J as their cohomology in degree zero. Using the notion of stable equivalence introduced in Felder and Kazhdan (Contemporary Mathematics 610, Perspectives in representation theory, 2014), we prove that any two BRST complexes associated with the same coisotropic ideal are quasi-isomorphic in the case P = R[V] where V is a finite-dimensional symplectic vector space and the bracket on P is induced by the symplectic structure on V. As a corollary, the cohomology of the BRST complexes is canonically associated with the coisotropic ideal J in the symplectic case. We do not require any regularity assumptions on the constraints generating the ideal J. We finally quantize the BRST complex rigorously in the presence of infinitely many ghost variables and discuss the uniqueness of the quantization procedure.

Horizon feedback inflation

NASA Astrophysics Data System (ADS)

Fairbairn, Malcolm; Markkanen, Tommi; Rodriguez Roman, David

2018-04-01

We consider the effect of the Gibbons-Hawking radiation on the inflaton in the situation where it is coupled to a large number of spectator fields. We argue that this will lead to two important effects - a thermal contribution to the potential and a gradual change in parameters in the Lagrangian which results from thermodynamic and energy conservation arguments. We present a scenario of hilltop inflation where the field starts trapped at the origin before slowly experiencing a phase transition during which the field extremely slowly moves towards its zero temperature expectation value. We show that it is possible to obtain enough e-folds of expansion as well as the correct spectrum of perturbations without hugely fine-tuned parameters in the potential (albeit with many spectator fields). We also comment on how initial conditions for inflation can arise naturally in this situation.

Measures of clustering and heterogeneity in multilevel Poisson regression analyses of rates/count data

PubMed Central

Austin, Peter C.; Stryhn, Henrik; Leckie, George; Merlo, Juan

2017-01-01

Multilevel data occur frequently in many research areas like health services research and epidemiology. A suitable way to analyze such data is through the use of multilevel regression models. These models incorporate cluster‐specific random effects that allow one to partition the total variation in the outcome into between‐cluster variation and between‐individual variation. The magnitude of the effect of clustering provides a measure of the general contextual effect. When outcomes are binary or time‐to‐event in nature, the general contextual effect can be quantified by measures of heterogeneity like the median odds ratio or the median hazard ratio, respectively, which can be calculated from a multilevel regression model. Outcomes that are integer counts denoting the number of times that an event occurred are common in epidemiological and medical research. The median (incidence) rate ratio in multilevel Poisson regression for counts that corresponds to the median odds ratio or median hazard ratio for binary or time‐to‐event outcomes respectively is relatively unknown and is rarely used. The median rate ratio is the median relative change in the rate of the occurrence of the event when comparing identical subjects from 2 randomly selected different clusters that are ordered by rate. We also describe how the variance partition coefficient, which denotes the proportion of the variation in the outcome that is attributable to between‐cluster differences, can be computed with count outcomes. We illustrate the application and interpretation of these measures in a case study analyzing the rate of hospital readmission in patients discharged from hospital with a diagnosis of heart failure. PMID:29114926

Genericness of inflation in isotropic loop quantum cosmology.

PubMed

Date, Ghanashyam; Hossain, Golam Mortuza

2005-01-14

Nonperturbative corrections from loop quantum cosmology (LQC) to the scalar matter sector are already known to imply inflation. We prove that the LQC modified scalar field generates exponential inflation in the small scale factor regime, for all positive definite potentials, independent of initial conditions and independent of ambiguity parameters. For positive semidefinite potentials it is always possible to choose, without fine-tuning, a value of one of the ambiguity parameters such that exponential inflation results, provided zeros of the potential are approached at most as a power law in the scale factor. In conjunction with the generic occurrence of bounce at small volumes, particle horizon is absent, thus eliminating the horizon problem of the standard big bang model.

Association between large strongyle genera in larval cultures--using rare-event poisson regression.

PubMed

Cao, X; Vidyashankar, A N; Nielsen, M K

2013-09-01

Decades of intensive anthelmintic treatment has caused equine large strongyles to become quite rare, while the cyathostomins have developed resistance to several drug classes. The larval culture has been associated with low to moderate negative predictive values for detecting Strongylus vulgaris infection. It is unknown whether detection of other large strongyle species can be statistically associated with presence of S. vulgaris. This remains a statistical challenge because of the rare occurrence of large strongyle species. This study used a modified Poisson regression to analyse a dataset for associations between S. vulgaris infection and simultaneous occurrence of Strongylus edentatus and Triodontophorus spp. In 663 horses on 42 Danish farms, the individual prevalences of S. vulgaris, S. edentatus and Triodontophorus spp. were 12%, 3% and 12%, respectively. Both S. edentatus and Triodontophorus spp. were significantly associated with S. vulgaris infection with relative risks above 1. Further, S. edentatus was associated with use of selective therapy on the farms, as well as negatively associated with anthelmintic treatment carried out within 6 months prior to the study. The findings illustrate that occurrence of S. vulgaris in larval cultures can be interpreted as indicative of other large strongyles being likely to be present.

Accident prediction model for public highway-rail grade crossings.

PubMed

Lu, Pan; Tolliver, Denver

2016-05-01

Considerable research has focused on roadway accident frequency analysis, but relatively little research has examined safety evaluation at highway-rail grade crossings. Highway-rail grade crossings are critical spatial locations of utmost importance for transportation safety because traffic crashes at highway-rail grade crossings are often catastrophic with serious consequences. The Poisson regression model has been employed to analyze vehicle accident frequency as a good starting point for many years. The most commonly applied variations of Poisson including negative binomial, and zero-inflated Poisson. These models are used to deal with common crash data issues such as over-dispersion (sample variance is larger than the sample mean) and preponderance of zeros (low sample mean and small sample size). On rare occasions traffic crash data have been shown to be under-dispersed (sample variance is smaller than the sample mean) and traditional distributions such as Poisson or negative binomial cannot handle under-dispersion well. The objective of this study is to investigate and compare various alternate highway-rail grade crossing accident frequency models that can handle the under-dispersion issue. The contributions of the paper are two-fold: (1) application of probability models to deal with under-dispersion issues and (2) obtain insights regarding to vehicle crashes at public highway-rail grade crossings. Copyright © 2016 Elsevier Ltd. All rights reserved.

Poisson-Like Spiking in Circuits with Probabilistic Synapses

PubMed Central

Moreno-Bote, Rubén

2014-01-01

Neuronal activity in cortex is variable both spontaneously and during stimulation, and it has the remarkable property that it is Poisson-like over broad ranges of firing rates covering from virtually zero to hundreds of spikes per second. The mechanisms underlying cortical-like spiking variability over such a broad continuum of rates are currently unknown. We show that neuronal networks endowed with probabilistic synaptic transmission, a well-documented source of variability in cortex, robustly generate Poisson-like variability over several orders of magnitude in their firing rate without fine-tuning of the network parameters. Other sources of variability, such as random synaptic delays or spike generation jittering, do not lead to Poisson-like variability at high rates because they cannot be sufficiently amplified by recurrent neuronal networks. We also show that probabilistic synapses predict Fano factor constancy of synaptic conductances. Our results suggest that synaptic noise is a robust and sufficient mechanism for the type of variability found in cortex. PMID:25032705

Impact of a New Law to Reduce the Legal Blood Alcohol Concentration Limit - A Poisson Regression Analysis and Descriptive Approach.

PubMed

Nistal-Nuño, Beatriz

2017-03-31

In Chile, a new law introduced in March 2012 lowered the blood alcohol concentration (BAC) limit for impaired drivers from 0.1% to 0.08% and the BAC limit for driving under the influence of alcohol from 0.05% to 0.03%, but its effectiveness remains uncertain. The goal of this investigation was to evaluate the effects of this enactment on road traffic injuries and fatalities in Chile. A retrospective cohort study. Data were analyzed using a descriptive and a Generalized Linear Models approach, type of Poisson regression, to analyze deaths and injuries in a series of additive Log-Linear Models accounting for the effects of law implementation, month influence, a linear time trend and population exposure. A review of national databases in Chile was conducted from 2003 to 2014 to evaluate the monthly rates of traffic fatalities and injuries associated to alcohol and in total. It was observed a decrease by 28.1 percent in the monthly rate of traffic fatalities related to alcohol as compared to before the law (P<0.001). Adding a linear time trend as a predictor, the decrease was by 20.9 percent (P<0.001).There was a reduction in the monthly rate of traffic injuries related to alcohol by 10.5 percent as compared to before the law (P<0.001). Adding a linear time trend as a predictor, the decrease was by 24.8 percent (P<0.001). Positive results followed from this new 'zero-tolerance' law implemented in 2012 in Chile. Chile experienced a significant reduction in alcohol-related traffic fatalities and injuries, being a successful public health intervention.

Characterizing the performance of the Conway-Maxwell Poisson generalized linear model.

PubMed

Francis, Royce A; Geedipally, Srinivas Reddy; Guikema, Seth D; Dhavala, Soma Sekhar; Lord, Dominique; LaRocca, Sarah

2012-01-01

Count data are pervasive in many areas of risk analysis; deaths, adverse health outcomes, infrastructure system failures, and traffic accidents are all recorded as count events, for example. Risk analysts often wish to estimate the probability distribution for the number of discrete events as part of doing a risk assessment. Traditional count data regression models of the type often used in risk assessment for this problem suffer from limitations due to the assumed variance structure. A more flexible model based on the Conway-Maxwell Poisson (COM-Poisson) distribution was recently proposed, a model that has the potential to overcome the limitations of the traditional model. However, the statistical performance of this new model has not yet been fully characterized. This article assesses the performance of a maximum likelihood estimation method for fitting the COM-Poisson generalized linear model (GLM). The objectives of this article are to (1) characterize the parameter estimation accuracy of the MLE implementation of the COM-Poisson GLM, and (2) estimate the prediction accuracy of the COM-Poisson GLM using simulated data sets. The results of the study indicate that the COM-Poisson GLM is flexible enough to model under-, equi-, and overdispersed data sets with different sample mean values. The results also show that the COM-Poisson GLM yields accurate parameter estimates. The COM-Poisson GLM provides a promising and flexible approach for performing count data regression. © 2011 Society for Risk Analysis.

Zeroth Poisson Homology, Foliated Cohomology and Perfect Poisson Manifolds

NASA Astrophysics Data System (ADS)

Martínez-Torres, David; Miranda, Eva

2018-01-01

We prove that, for compact regular Poisson manifolds, the zeroth homology group is isomorphic to the top foliated cohomology group, and we give some applications. In particular, we show that, for regular unimodular Poisson manifolds, top Poisson and foliated cohomology groups are isomorphic. Inspired by the symplectic setting, we define what a perfect Poisson manifold is. We use these Poisson homology computations to provide families of perfect Poisson manifolds.

The transverse Poisson's ratio of composites.

NASA Technical Reports Server (NTRS)

Foye, R. L.

1972-01-01

An expression is developed that makes possible the prediction of Poisson's ratio for unidirectional composites with reference to any pair of orthogonal axes that are normal to the direction of the reinforcing fibers. This prediction appears to be a reasonable one in that it follows the trends of the finite element analysis and the bounding estimates, and has the correct limiting value for zero fiber content. It can only be expected to apply to composites containing stiff, circular, isotropic fibers bonded to a soft matrix material.

Analysis of aggregate impact factor inflation in ophthalmology.

PubMed

Caramoy, Albert; Korwitz, Ulrich; Eppelin, Anita; Kirchhof, Bernd; Fauser, Sascha

2013-01-01

To analyze the aggregate impact factor (AIF) in ophthalmology, its inflation rate, and its relation to other subject fields. A retrospective, database review of all subject fields in the Journal Citation Reports (JCR), Science edition. Citation data, AIF, number of journals and citations from the years 2003-2011 were analyzed. Data were retrieved from JCR. Future trends were calculated using a linear regression method. The AIF varies considerably between subjects. It shows also an inflation rate, which varies annually. The AIF inflation rate in ophthalmology was not as high as the background AIF inflation rate. The AIF inflation rate caused the AIF to increase annually. Not considering these variations in the AIF between years and between fields will make the AIF as a bibliometric tool inappropriate. Copyright © 2012 S. Karger AG, Basel.

46 CFR 131.580 - Servicing of inflatable liferafts, inflatable lifejackets, inflatable buoyant apparatus, and...

Code of Federal Regulations, 2011 CFR

2011-10-01

... lifejackets, inflatable buoyant apparatus, and inflated rescue boats. 131.580 Section 131.580 Shipping COAST... Inspections § 131.580 Servicing of inflatable liferafts, inflatable lifejackets, inflatable buoyant apparatus, and inflated rescue boats. (a) An inflatable liferaft or inflatable buoyant apparatus must be serviced...

46 CFR 131.580 - Servicing of inflatable liferafts, inflatable lifejackets, inflatable buoyant apparatus, and...

Code of Federal Regulations, 2010 CFR

2010-10-01

... lifejackets, inflatable buoyant apparatus, and inflated rescue boats. 131.580 Section 131.580 Shipping COAST... Inspections § 131.580 Servicing of inflatable liferafts, inflatable lifejackets, inflatable buoyant apparatus, and inflated rescue boats. (a) An inflatable liferaft or inflatable buoyant apparatus must be serviced...

Universality of the Volume Bound in Slow-Roll Eternal Inflation

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

Dubovsky, Sergei; Senatore, Leonardo; Villadoro, Giovanni

2012-03-28

It has recently been shown that in single field slow-roll inflation the total volume cannot grow by a factor larger than e{sup S{sub dS}/2} without becoming infinite. The bound is saturated exactly at the phase transition to eternal inflation where the probability to produce infinite volume becomes non zero. We show that the bound holds sharply also in any space-time dimensions, when arbitrary higher-dimensional operators are included and in the multi-field inflationary case. The relation with the entropy of de Sitter and the universality of the bound strengthen the case for a deeper holographic interpretation. As a spin-off we providemore » the formalism to compute the probability distribution of the volume after inflation for generic multi-field models, which might help to address questions about the population of vacua of the landscape during slow-roll inflation.« less

Normal forms for Poisson maps and symplectic groupoids around Poisson transversals

NASA Astrophysics Data System (ADS)

Frejlich, Pedro; Mărcuț, Ioan

2018-03-01

Poisson transversals are submanifolds in a Poisson manifold which intersect all symplectic leaves transversally and symplectically. In this communication, we prove a normal form theorem for Poisson maps around Poisson transversals. A Poisson map pulls a Poisson transversal back to a Poisson transversal, and our first main result states that simultaneous normal forms exist around such transversals, for which the Poisson map becomes transversally linear, and intertwines the normal form data of the transversals. Our second result concerns symplectic integrations. We prove that a neighborhood of a Poisson transversal is integrable exactly when the Poisson transversal itself is integrable, and in that case we prove a normal form theorem for the symplectic groupoid around its restriction to the Poisson transversal, which puts all structure maps in normal form. We conclude by illustrating our results with examples arising from Lie algebras.

Normal forms for Poisson maps and symplectic groupoids around Poisson transversals.

PubMed

Frejlich, Pedro; Mărcuț, Ioan

2018-01-01

Poisson transversals are submanifolds in a Poisson manifold which intersect all symplectic leaves transversally and symplectically. In this communication, we prove a normal form theorem for Poisson maps around Poisson transversals. A Poisson map pulls a Poisson transversal back to a Poisson transversal, and our first main result states that simultaneous normal forms exist around such transversals, for which the Poisson map becomes transversally linear, and intertwines the normal form data of the transversals. Our second result concerns symplectic integrations. We prove that a neighborhood of a Poisson transversal is integrable exactly when the Poisson transversal itself is integrable, and in that case we prove a normal form theorem for the symplectic groupoid around its restriction to the Poisson transversal, which puts all structure maps in normal form. We conclude by illustrating our results with examples arising from Lie algebras.

The analysis of incontinence episodes and other count data in patients with overactive bladder by Poisson and negative binomial regression.

PubMed

Martina, R; Kay, R; van Maanen, R; Ridder, A

2015-01-01

Clinical studies in overactive bladder have traditionally used analysis of covariance or nonparametric methods to analyse the number of incontinence episodes and other count data. It is known that if the underlying distributional assumptions of a particular parametric method do not hold, an alternative parametric method may be more efficient than a nonparametric one, which makes no assumptions regarding the underlying distribution of the data. Therefore, there are advantages in using methods based on the Poisson distribution or extensions of that method, which incorporate specific features that provide a modelling framework for count data. One challenge with count data is overdispersion, but methods are available that can account for this through the introduction of random effect terms in the modelling, and it is this modelling framework that leads to the negative binomial distribution. These models can also provide clinicians with a clearer and more appropriate interpretation of treatment effects in terms of rate ratios. In this paper, the previously used parametric and non-parametric approaches are contrasted with those based on Poisson regression and various extensions in trials evaluating solifenacin and mirabegron in patients with overactive bladder. In these applications, negative binomial models are seen to fit the data well. Copyright © 2014 John Wiley & Sons, Ltd.

Does money matter in inflation forecasting?

NASA Astrophysics Data System (ADS)

Binner, J. M.; Tino, P.; Tepper, J.; Anderson, R.; Jones, B.; Kendall, G.

2010-11-01

This paper provides the most fully comprehensive evidence to date on whether or not monetary aggregates are valuable for forecasting US inflation in the early to mid 2000s. We explore a wide range of different definitions of money, including different methods of aggregation and different collections of included monetary assets. In our forecasting experiment we use two nonlinear techniques, namely, recurrent neural networks and kernel recursive least squares regression-techniques that are new to macroeconomics. Recurrent neural networks operate with potentially unbounded input memory, while the kernel regression technique is a finite memory predictor. The two methodologies compete to find the best fitting US inflation forecasting models and are then compared to forecasts from a naïve random walk model. The best models were nonlinear autoregressive models based on kernel methods. Our findings do not provide much support for the usefulness of monetary aggregates in forecasting inflation. Beyond its economic findings, our study is in the tradition of physicists’ long-standing interest in the interconnections among statistical mechanics, neural networks, and related nonparametric statistical methods, and suggests potential avenues of extension for such studies.

Mixed effect Poisson log-linear models for clinical and epidemiological sleep hypnogram data

PubMed Central

Swihart, Bruce J.; Caffo, Brian S.; Crainiceanu, Ciprian; Punjabi, Naresh M.

2013-01-01

Bayesian Poisson log-linear multilevel models scalable to epidemiological studies are proposed to investigate population variability in sleep state transition rates. Hierarchical random effects are used to account for pairings of subjects and repeated measures within those subjects, as comparing diseased to non-diseased subjects while minimizing bias is of importance. Essentially, non-parametric piecewise constant hazards are estimated and smoothed, allowing for time-varying covariates and segment of the night comparisons. The Bayesian Poisson regression is justified through a re-derivation of a classical algebraic likelihood equivalence of Poisson regression with a log(time) offset and survival regression assuming exponentially distributed survival times. Such re-derivation allows synthesis of two methods currently used to analyze sleep transition phenomena: stratified multi-state proportional hazards models and log-linear models with GEE for transition counts. An example data set from the Sleep Heart Health Study is analyzed. Supplementary material includes the analyzed data set as well as the code for a reproducible analysis. PMID:22241689

Modeling both of the number of pausibacillary and multibacillary leprosy patients by using bivariate poisson regression

NASA Astrophysics Data System (ADS)

Winahju, W. S.; Mukarromah, A.; Putri, S.

2015-03-01

Leprosy is a chronic infectious disease caused by bacteria of leprosy (Mycobacterium leprae). Leprosy has become an important thing in Indonesia because its morbidity is quite high. Based on WHO data in 2014, in 2012 Indonesia has the highest number of new leprosy patients after India and Brazil with a contribution of 18.994 people (8.7% of the world). This number makes Indonesia automatically placed as the country with the highest number of leprosy morbidity of ASEAN countries. The province that most contributes to the number of leprosy patients in Indonesia is East Java. There are two kind of leprosy. They consist of pausibacillary and multibacillary. The morbidity of multibacillary leprosy is higher than pausibacillary leprosy. This paper will discuss modeling both of the number of multibacillary and pausibacillary leprosy patients as responses variables. These responses are count variables, so modeling will be conducted by using bivariate poisson regression method. Unit experiment used is in East Java, and predictors involved are: environment, demography, and poverty. The model uses data in 2012, and the result indicates that all predictors influence significantly.

The impact of state safe routes to school-related laws on active travel to school policies and practices in U.S. elementary schools.

PubMed

Chriqui, Jamie F; Taber, Daniel R; Slater, Sandy J; Turner, Lindsey; Lowrey, Kerri McGowan; Chaloupka, Frank J

2012-01-01

This study examined the relationship between state laws requiring minimum bussing distances, hazardous route exemptions, sidewalks, crossing guards, speed zones, and traffic control measures around schools and active travel to school (ATS) policies/practices in nationally representative samples of U.S. public elementary schools between 2007-2009. The state laws and school data were compiled through primary legal research and annual mail-back surveys of principals, respectively. Multivariate logistic and zero-inflated poisson regression indicated that all state law categories (except for sidewalks) relate to ATS. These laws should be considered in addition to formal safe routes to school programs as possible influences on ATS. Copyright © 2011 Elsevier Ltd. All rights reserved.

46 CFR 131.580 - Servicing of inflatable liferafts, inflatable lifejackets, inflatable buoyant apparatus, and...

Code of Federal Regulations, 2012 CFR

2012-10-01

... lifejackets, inflatable buoyant apparatus, and inflated rescue boats. 131.580 Section 131.580 Shipping COAST..., and inflated rescue boats. (a) An inflatable liferaft or inflatable buoyant apparatus must be serviced... maintenance of inflatable rescue boats must follow the manufacturers' instructions. Each repair, except an...

46 CFR 131.580 - Servicing of inflatable liferafts, inflatable lifejackets, inflatable buoyant apparatus, and...

Code of Federal Regulations, 2013 CFR

2013-10-01

... lifejackets, inflatable buoyant apparatus, and inflated rescue boats. 131.580 Section 131.580 Shipping COAST..., and inflated rescue boats. (a) An inflatable liferaft or inflatable buoyant apparatus must be serviced... maintenance of inflatable rescue boats must follow the manufacturers' instructions. Each repair, except an...

46 CFR 131.580 - Servicing of inflatable liferafts, inflatable lifejackets, inflatable buoyant apparatus, and...

Code of Federal Regulations, 2014 CFR

2014-10-01

... lifejackets, inflatable buoyant apparatus, and inflated rescue boats. 131.580 Section 131.580 Shipping COAST..., and inflated rescue boats. (a) An inflatable liferaft or inflatable buoyant apparatus must be serviced... maintenance of inflatable rescue boats must follow the manufacturers' instructions. Each repair, except an...

46 CFR 122.730 - Servicing of inflatable liferafts, inflatable buoyant apparatus, inflatable life jackets, and...

Code of Federal Regulations, 2013 CFR

2013-10-01

... apparatus, inflatable life jackets, and inflated rescue boats. 122.730 Section 122.730 Shipping COAST GUARD..., inflatable life jackets, and inflated rescue boats. (a) An inflatable liferaft or inflatable buoyant... other standard specified by the Commandant. (e) Repair and maintenance of inflated rescue boats must be...

46 CFR 122.730 - Servicing of inflatable liferafts, inflatable buoyant apparatus, inflatable life jackets, and...

Code of Federal Regulations, 2012 CFR

2012-10-01

... apparatus, inflatable life jackets, and inflated rescue boats. 122.730 Section 122.730 Shipping COAST GUARD..., inflatable life jackets, and inflated rescue boats. (a) An inflatable liferaft or inflatable buoyant... other standard specified by the Commandant. (e) Repair and maintenance of inflated rescue boats must be...

46 CFR 122.730 - Servicing of inflatable liferafts, inflatable buoyant apparatus, inflatable life jackets, and...

Code of Federal Regulations, 2014 CFR

2014-10-01

... apparatus, inflatable life jackets, and inflated rescue boats. 122.730 Section 122.730 Shipping COAST GUARD..., inflatable life jackets, and inflated rescue boats. (a) An inflatable liferaft or inflatable buoyant... other standard specified by the Commandant. (e) Repair and maintenance of inflated rescue boats must be...

Inflatable Re-Entry Vehicle Experiment (IRVE) Design Overview

NASA Technical Reports Server (NTRS)

Hughes, Stephen J.; Dillman, Robert A.; Starr, Brett R.; Stephan, Ryan A.; Lindell, Michael C.; Player, Charles J.; Cheatwood, F. McNeil

2005-01-01

integrity when exposed to a relevant dynamic pressure and aerodynamic stability of the inflatable system. Structural integrity and structural response of the inflatable will be verified with photogrammetric measurements of the back side of the aeroshell in flight. Aerodynamic stability as well as drag performance will be verified with on board inertial measurements and radar tracking from multiple ground radar stations. The experiment will yield valuable information about zero-g vacuum deployment dynamics of the flexible inflatable structure with both inertial and photographic measurements. In addition to demonstrating inflatable technology, IRVE will validate structural, aerothermal, and trajectory modeling techniques for the inflatable. Structural response determined from photogrammetrics will validate structural models, skin temperature measurements and additional in-depth temperature measurements will validate material thermal performance models, and on board inertial measurements along with radar tracking from multiple ground radar stations will validate trajectory simulation models.

46 CFR 185.730 - Servicing of inflatable liferafts, inflatable buoyant apparatus, inflatable life jackets, and...

Code of Federal Regulations, 2014 CFR

2014-10-01

... apparatus, inflatable life jackets, and inflated rescue boats. 185.730 Section 185.730 Shipping COAST GUARD... liferafts, inflatable buoyant apparatus, inflatable life jackets, and inflated rescue boats. (a) An... inflated rescue boats must be in accordance with the manufacturer's instructions. All repairs must be made...

46 CFR 185.730 - Servicing of inflatable liferafts, inflatable buoyant apparatus, inflatable life jackets, and...

Code of Federal Regulations, 2013 CFR

2013-10-01

... apparatus, inflatable life jackets, and inflated rescue boats. 185.730 Section 185.730 Shipping COAST GUARD... liferafts, inflatable buoyant apparatus, inflatable life jackets, and inflated rescue boats. (a) An... inflated rescue boats must be in accordance with the manufacturer's instructions. All repairs must be made...

46 CFR 185.730 - Servicing of inflatable liferafts, inflatable buoyant apparatus, inflatable life jackets, and...

Code of Federal Regulations, 2012 CFR

2012-10-01

... apparatus, inflatable life jackets, and inflated rescue boats. 185.730 Section 185.730 Shipping COAST GUARD... liferafts, inflatable buoyant apparatus, inflatable life jackets, and inflated rescue boats. (a) An... inflated rescue boats must be in accordance with the manufacturer's instructions. All repairs must be made...

DISCRETE COMPOUND POISSON PROCESSES AND TABLES OF THE GEOMETRIC POISSON DISTRIBUTION.

DTIC Science & Technology

A concise summary of the salient properties of discrete Poisson processes , with emphasis on comparing the geometric and logarithmic Poisson processes . The...the geometric Poisson process are given for 176 sets of parameter values. New discrete compound Poisson processes are also introduced. These...processes have properties that are particularly relevant when the summation of several different Poisson processes is to be analyzed. This study provides the

Poisson Coordinates.

PubMed

Li, Xian-Ying; Hu, Shi-Min

2013-02-01

Harmonic functions are the critical points of a Dirichlet energy functional, the linear projections of conformal maps. They play an important role in computer graphics, particularly for gradient-domain image processing and shape-preserving geometric computation. We propose Poisson coordinates, a novel transfinite interpolation scheme based on the Poisson integral formula, as a rapid way to estimate a harmonic function on a certain domain with desired boundary values. Poisson coordinates are an extension of the Mean Value coordinates (MVCs) which inherit their linear precision, smoothness, and kernel positivity. We give explicit formulas for Poisson coordinates in both continuous and 2D discrete forms. Superior to MVCs, Poisson coordinates are proved to be pseudoharmonic (i.e., they reproduce harmonic functions on n-dimensional balls). Our experimental results show that Poisson coordinates have lower Dirichlet energies than MVCs on a number of typical 2D domains (particularly convex domains). As well as presenting a formula, our approach provides useful insights for further studies on coordinates-based interpolation and fast estimation of harmonic functions.

Bayesian analysis of zero inflated spatiotemporal HIV/TB child mortality data through the INLA and SPDE approaches: Applied to data observed between 1992 and 2010 in rural North East South Africa

NASA Astrophysics Data System (ADS)

Musenge, Eustasius; Chirwa, Tobias Freeman; Kahn, Kathleen; Vounatsou, Penelope

2013-06-01

Longitudinal mortality data with few deaths usually have problems of zero-inflation. This paper presents and applies two Bayesian models which cater for zero-inflation, spatial and temporal random effects. To reduce the computational burden experienced when a large number of geo-locations are treated as a Gaussian field (GF) we transformed the field to a Gaussian Markov Random Fields (GMRF) by triangulation. We then modelled the spatial random effects using the Stochastic Partial Differential Equations (SPDEs). Inference was done using a computationally efficient alternative to Markov chain Monte Carlo (MCMC) called Integrated Nested Laplace Approximation (INLA) suited for GMRF. The models were applied to data from 71,057 children aged 0 to under 10 years from rural north-east South Africa living in 15,703 households over the years 1992-2010. We found protective effects on HIV/TB mortality due to greater birth weight, older age and more antenatal clinic visits during pregnancy (adjusted RR (95% CI)): 0.73(0.53;0.99), 0.18(0.14;0.22) and 0.96(0.94;0.97) respectively. Therefore childhood HIV/TB mortality could be reduced if mothers are better catered for during pregnancy as this can reduce mother-to-child transmissions and contribute to improved birth weights. The INLA and SPDE approaches are computationally good alternatives in modelling large multilevel spatiotemporal GMRF data structures.

Variable- and Person-Centered Approaches to the Analysis of Early Adolescent Substance Use: Linking Peer, Family, and Intervention Effects with Developmental Trajectories

ERIC Educational Resources Information Center

Connell, Arin M.; Dishion, Thomas J.; Deater-Deckard, Kirby

2006-01-01

This 4-year study of 698 young adolescents examined the covariates of early onset substance use from Grade 6 through Grade 9. The youth were randomly assigned to a family-centered Adolescent Transitions Program (ATP) condition. Variable-centered (zero-inflated Poisson growth model) and person-centered (latent growth mixture model) approaches were…

46 CFR 185.730 - Servicing of inflatable liferafts, inflatable buoyant apparatus, inflatable life jackets, and...

Code of Federal Regulations, 2011 CFR

2011-10-01

... inflatable liferaft or inflatable buoyant apparatus must be serviced at a facility specifically approved by... apparatus, inflatable life jackets, and inflated rescue boats. 185.730 Section 185.730 Shipping COAST GUARD... Operational Readiness, Maintenance, and Inspection of Lifesaving Equipment § 185.730 Servicing of inflatable...

46 CFR 185.730 - Servicing of inflatable liferafts, inflatable buoyant apparatus, inflatable life jackets, and...

Code of Federal Regulations, 2010 CFR

2010-10-01

... inflatable liferaft or inflatable buoyant apparatus must be serviced at a facility specifically approved by... apparatus, inflatable life jackets, and inflated rescue boats. 185.730 Section 185.730 Shipping COAST GUARD... Operational Readiness, Maintenance, and Inspection of Lifesaving Equipment § 185.730 Servicing of inflatable...

Inverse Jacobi multiplier as a link between conservative systems and Poisson structures

NASA Astrophysics Data System (ADS)

García, Isaac A.; Hernández-Bermejo, Benito

2017-08-01

Some aspects of the relationship between conservativeness of a dynamical system (namely the preservation of a finite measure) and the existence of a Poisson structure for that system are analyzed. From the local point of view, due to the flow-box theorem we restrict ourselves to neighborhoods of singularities. In this sense, we characterize Poisson structures around the typical zero-Hopf singularity in dimension 3 under the assumption of having a local analytic first integral with non-vanishing first jet by connecting with the classical Poincaré center problem. From the global point of view, we connect the property of being strictly conservative (the invariant measure must be positive) with the existence of a Poisson structure depending on the phase space dimension. Finally, weak conservativeness in dimension two is introduced by the extension of inverse Jacobi multipliers as weak solutions of its defining partial differential equation and some of its applications are developed. Examples including Lotka-Volterra systems, quadratic isochronous centers, and non-smooth oscillators are provided.

Type I error rates of rare single nucleotide variants are inflated in tests of association with non-normally distributed traits using simple linear regression methods.

PubMed

Schwantes-An, Tae-Hwi; Sung, Heejong; Sabourin, Jeremy A; Justice, Cristina M; Sorant, Alexa J M; Wilson, Alexander F

2016-01-01

In this study, the effects of (a) the minor allele frequency of the single nucleotide variant (SNV), (b) the degree of departure from normality of the trait, and (c) the position of the SNVs on type I error rates were investigated in the Genetic Analysis Workshop (GAW) 19 whole exome sequence data. To test the distribution of the type I error rate, 5 simulated traits were considered: standard normal and gamma distributed traits; 2 transformed versions of the gamma trait (log 10 and rank-based inverse normal transformations); and trait Q1 provided by GAW 19. Each trait was tested with 313,340 SNVs. Tests of association were performed with simple linear regression and average type I error rates were determined for minor allele frequency classes. Rare SNVs (minor allele frequency < 0.05) showed inflated type I error rates for non-normally distributed traits that increased as the minor allele frequency decreased. The inflation of average type I error rates increased as the significance threshold decreased. Normally distributed traits did not show inflated type I error rates with respect to the minor allele frequency for rare SNVs. There was no consistent effect of transformation on the uniformity of the distribution of the location of SNVs with a type I error.

A novel stent inflation protocol improves long-term outcomes compared with rapid inflation/deflation deployment method.

PubMed

Vallurupalli, Srikanth; Kasula, Srikanth; Kumar Agarwal, Shiv; Pothineni, Naga Venkata K; Abualsuod, Amjad; Hakeem, Abdul; Ahmed, Zubair; Uretsky, Barry F

2017-08-01

High-pressure inflation for coronary stent deployment is universally performed. However, the duration of inflation is variable and does not take into account differences in lesion compliance. We developed a standardized "pressure optimization protocol" (POP) using inflation pressure stability rather than an arbitrary inflation time or angiographic balloon appearance for stent deployment. Whether this approach improves long-term outcomes is unknown. 792 patients who underwent PCI using either rapid inflation/deflation (n = 376) or POP (n = 416) between January 2009 and March 2014 were included. Exclusion criteria included PCI for acute myocardial infarction, in-stent restenosis, chronic total occlusion, left main, and saphenous vein graft lesions. Primary endpoint was target vessel failure [TVF = combined end point of target vessel revascularization (TVR), myocardial infarction, and cardiac death]. Outcomes were analyzed in the entire cohort and in a propensity analysis. Stent implantation using POP with a median follow-up of 1317 days was associated with lower TVF compared with rapid inflation/deflation (10.1 vs. 17.8%, P < 0.0001). This difference was driven by a decrease in TVR (7 vs. 10.6%, P = 0.0016) and cardiac death (2.9 vs. 5.8%, P = 0.017) while there was no difference in myocardial infarction (1 vs. 1.9%, P = 0.19). In the Cox regression model, deployment using POP was the only independent predictor of reduced TVF (HR 0.43; 0.29-0.64; P < 0.0001). In the propensity analysis (330 patients per group) TVF remained lower with POP vs. rapid inflation/deflation (10 vs. 18%, P < 0.0001). Stent deployment using POP led to reduced TVF compared to rapid I/D. These results recommend this method to improve long-term outcomes. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Efficacy of a Savings-Led Microfinance Intervention to Reduce Sexual Risk for HIV Among Women Engaged in Sex Work: A Randomized Clinical Trial

PubMed Central

Aira, Toivgoo; Tsai, Laura Cordisco; Riedel, Marion; Offringa, Reid; Chang, Mingway; El-Bassel, Nabila; Ssewamala, Fred

2015-01-01

Objectives. We tested whether a structural intervention combining savings-led microfinance and HIV prevention components would achieve enhanced reductions in sexual risk among women engaging in street-based sex work in Ulaanbaatar, Mongolia, compared with an HIV prevention intervention alone. Methods. Between November 2011 and August 2012, we randomized 107 eligible women who completed baseline assessments to either a 4-session HIV sexual risk reduction intervention (HIVSRR) alone (n = 50) or a 34-session HIVSRR plus a savings-led microfinance intervention (n = 57). At 3- and 6-month follow-up assessments, participants reported unprotected acts of vaginal intercourse with paying partners and number of paying partners with whom they engaged in sexual intercourse in the previous 90 days. Using Poisson and zero-inflated Poisson model regressions, we examined the effects of assignment to treatment versus control condition on outcomes. Results. At 6-month follow-up, the HIVSRR plus microfinance participants reported significantly fewer paying sexual partners and were more likely to report zero unprotected vaginal sex acts with paying sexual partners. Conclusions. Findings advance the HIV prevention repertoire for women, demonstrating that risk reduction may be achieved through a structural intervention that relies on asset building, including savings, and alternatives to income from sex work. PMID:25602889

Efficacy of a savings-led microfinance intervention to reduce sexual risk for HIV among women engaged in sex work: a randomized clinical trial.

PubMed

Witte, Susan S; Aira, Toivgoo; Tsai, Laura Cordisco; Riedel, Marion; Offringa, Reid; Chang, Mingway; El-Bassel, Nabila; Ssewamala, Fred

2015-03-01

We tested whether a structural intervention combining savings-led microfinance and HIV prevention components would achieve enhanced reductions in sexual risk among women engaging in street-based sex work in Ulaanbaatar, Mongolia, compared with an HIV prevention intervention alone. Between November 2011 and August 2012, we randomized 107 eligible women who completed baseline assessments to either a 4-session HIV sexual risk reduction intervention (HIVSRR) alone (n=50) or a 34-session HIVSRR plus a savings-led microfinance intervention (n=57). At 3- and 6-month follow-up assessments, participants reported unprotected acts of vaginal intercourse with paying partners and number of paying partners with whom they engaged in sexual intercourse in the previous 90 days. Using Poisson and zero-inflated Poisson model regressions, we examined the effects of assignment to treatment versus control condition on outcomes. At 6-month follow-up, the HIVSRR plus microfinance participants reported significantly fewer paying sexual partners and were more likely to report zero unprotected vaginal sex acts with paying sexual partners. Findings advance the HIV prevention repertoire for women, demonstrating that risk reduction may be achieved through a structural intervention that relies on asset building, including savings, and alternatives to income from sex work.

46 CFR 131.865 - Inflatable liferafts and inflatable buoyant apparatus.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 4 2010-10-01 2010-10-01 false Inflatable liferafts and inflatable buoyant apparatus... SUPPLY VESSELS OPERATIONS Markings for Fire Equipment and Emergency Equipment § 131.865 Inflatable liferafts and inflatable buoyant apparatus. The number of the inflatable liferaft or inflatable buoyant...

46 CFR 131.865 - Inflatable liferafts and inflatable buoyant apparatus.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 4 2011-10-01 2011-10-01 false Inflatable liferafts and inflatable buoyant apparatus... SUPPLY VESSELS OPERATIONS Markings for Fire Equipment and Emergency Equipment § 131.865 Inflatable liferafts and inflatable buoyant apparatus. The number of the inflatable liferaft or inflatable buoyant...

Selecting a distributional assumption for modelling relative densities of benthic macroinvertebrates

USGS Publications Warehouse

Gray, B.R.

2005-01-01

The selection of a distributional assumption suitable for modelling macroinvertebrate density data is typically challenging. Macroinvertebrate data often exhibit substantially larger variances than expected under a standard count assumption, that of the Poisson distribution. Such overdispersion may derive from multiple sources, including heterogeneity of habitat (historically and spatially), differing life histories for organisms collected within a single collection in space and time, and autocorrelation. Taken to extreme, heterogeneity of habitat may be argued to explain the frequent large proportions of zero observations in macroinvertebrate data. Sampling locations may consist of habitats defined qualitatively as either suitable or unsuitable. The former category may yield random or stochastic zeroes and the latter structural zeroes. Heterogeneity among counts may be accommodated by treating the count mean itself as a random variable, while extra zeroes may be accommodated using zero-modified count assumptions, including zero-inflated and two-stage (or hurdle) approaches. These and linear assumptions (following log- and square root-transformations) were evaluated using 9 years of mayfly density data from a 52 km, ninth-order reach of the Upper Mississippi River (n = 959). The data exhibited substantial overdispersion relative to that expected under a Poisson assumption (i.e. variance:mean ratio = 23 ??? 1), and 43% of the sampling locations yielded zero mayflies. Based on the Akaike Information Criterion (AIC), count models were improved most by treating the count mean as a random variable (via a Poisson-gamma distributional assumption) and secondarily by zero modification (i.e. improvements in AIC values = 9184 units and 47-48 units, respectively). Zeroes were underestimated by the Poisson, log-transform and square root-transform models, slightly by the standard negative binomial model but not by the zero-modified models (61%, 24%, 32%, 7%, and 0%, respectively

46 CFR 122.730 - Servicing of inflatable liferafts, inflatable buoyant apparatus, inflatable life jackets, and...

Code of Federal Regulations, 2011 CFR

2011-10-01

... Inspection of Lifesaving Equipment § 122.730 Servicing of inflatable liferafts, inflatable buoyant apparatus... apparatus must be serviced at a facility specifically approved by the Commandant for the particular brand... apparatus, inflatable life jackets, and inflated rescue boats. 122.730 Section 122.730 Shipping COAST GUARD...

46 CFR 122.730 - Servicing of inflatable liferafts, inflatable buoyant apparatus, inflatable life jackets, and...

Code of Federal Regulations, 2010 CFR

2010-10-01

... Inspection of Lifesaving Equipment § 122.730 Servicing of inflatable liferafts, inflatable buoyant apparatus... apparatus must be serviced at a facility specifically approved by the Commandant for the particular brand... apparatus, inflatable life jackets, and inflated rescue boats. 122.730 Section 122.730 Shipping COAST GUARD...

INFLATE: INFlate Landing Apparatus Technology

NASA Astrophysics Data System (ADS)

Koryanov, V. V. K.; Da-Poian, V. D. P.

2018-02-01

Our project, named INFLATE (INFlatable Landing Apparatus Technology), aims at reducing space landing risks and constraints and so optimizing space missions (reducing cost, mass, and risk and in the same time improving performance).

False Positives in Multiple Regression: Unanticipated Consequences of Measurement Error in the Predictor Variables

ERIC Educational Resources Information Center

Shear, Benjamin R.; Zumbo, Bruno D.

2013-01-01

Type I error rates in multiple regression, and hence the chance for false positive research findings, can be drastically inflated when multiple regression models are used to analyze data that contain random measurement error. This article shows the potential for inflated Type I error rates in commonly encountered scenarios and provides new…

Bayesian hierarchical modelling of continuous non‐negative longitudinal data with a spike at zero: An application to a study of birds visiting gardens in winter

PubMed Central

Buckland, Stephen T.; King, Ruth; Toms, Mike P.

2015-01-01

The development of methods for dealing with continuous data with a spike at zero has lagged behind those for overdispersed or zero‐inflated count data. We consider longitudinal ecological data corresponding to an annual average of 26 weekly maximum counts of birds, and are hence effectively continuous, bounded below by zero but also with a discrete mass at zero. We develop a Bayesian hierarchical Tweedie regression model that can directly accommodate the excess number of zeros common to this type of data, whilst accounting for both spatial and temporal correlation. Implementation of the model is conducted in a Markov chain Monte Carlo (MCMC) framework, using reversible jump MCMC to explore uncertainty across both parameter and model spaces. This regression modelling framework is very flexible and removes the need to make strong assumptions about mean‐variance relationships a priori. It can also directly account for the spike at zero, whilst being easily applicable to other types of data and other model formulations. Whilst a correlative study such as this cannot prove causation, our results suggest that an increase in an avian predator may have led to an overall decrease in the number of one of its prey species visiting garden feeding stations in the United Kingdom. This may reflect a change in behaviour of house sparrows to avoid feeding stations frequented by sparrowhawks, or a reduction in house sparrow population size as a result of sparrowhawk increase. PMID:25737026

A generalized Poisson and Poisson-Boltzmann solver for electrostatic environments

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

Fisicaro, G., E-mail: giuseppe.fisicaro@unibas.ch; Goedecker, S.; Genovese, L.

2016-01-07

The computational study of chemical reactions in complex, wet environments is critical for applications in many fields. It is often essential to study chemical reactions in the presence of applied electrochemical potentials, taking into account the non-trivial electrostatic screening coming from the solvent and the electrolytes. As a consequence, the electrostatic potential has to be found by solving the generalized Poisson and the Poisson-Boltzmann equations for neutral and ionic solutions, respectively. In the present work, solvers for both problems have been developed. A preconditioned conjugate gradient method has been implemented for the solution of the generalized Poisson equation and themore » linear regime of the Poisson-Boltzmann, allowing to solve iteratively the minimization problem with some ten iterations of the ordinary Poisson equation solver. In addition, a self-consistent procedure enables us to solve the non-linear Poisson-Boltzmann problem. Both solvers exhibit very high accuracy and parallel efficiency and allow for the treatment of periodic, free, and slab boundary conditions. The solver has been integrated into the BigDFT and Quantum-ESPRESSO electronic-structure packages and will be released as an independent program, suitable for integration in other codes.« less

A generalized Poisson and Poisson-Boltzmann solver for electrostatic environments.

PubMed

Fisicaro, G; Genovese, L; Andreussi, O; Marzari, N; Goedecker, S

2016-01-07

The computational study of chemical reactions in complex, wet environments is critical for applications in many fields. It is often essential to study chemical reactions in the presence of applied electrochemical potentials, taking into account the non-trivial electrostatic screening coming from the solvent and the electrolytes. As a consequence, the electrostatic potential has to be found by solving the generalized Poisson and the Poisson-Boltzmann equations for neutral and ionic solutions, respectively. In the present work, solvers for both problems have been developed. A preconditioned conjugate gradient method has been implemented for the solution of the generalized Poisson equation and the linear regime of the Poisson-Boltzmann, allowing to solve iteratively the minimization problem with some ten iterations of the ordinary Poisson equation solver. In addition, a self-consistent procedure enables us to solve the non-linear Poisson-Boltzmann problem. Both solvers exhibit very high accuracy and parallel efficiency and allow for the treatment of periodic, free, and slab boundary conditions. The solver has been integrated into the BigDFT and Quantum-ESPRESSO electronic-structure packages and will be released as an independent program, suitable for integration in other codes.

Schrödinger-Poisson-Vlasov-Poisson correspondence

NASA Astrophysics Data System (ADS)

Mocz, Philip; Lancaster, Lachlan; Fialkov, Anastasia; Becerra, Fernando; Chavanis, Pierre-Henri

2018-04-01

The Schrödinger-Poisson equations describe the behavior of a superfluid Bose-Einstein condensate under self-gravity with a 3D wave function. As ℏ/m →0 , m being the boson mass, the equations have been postulated to approximate the collisionless Vlasov-Poisson equations also known as the collisionless Boltzmann-Poisson equations. The latter describe collisionless matter with a 6D classical distribution function. We investigate the nature of this correspondence with a suite of numerical test problems in 1D, 2D, and 3D along with analytic treatments when possible. We demonstrate that, while the density field of the superfluid always shows order unity oscillations as ℏ/m →0 due to interference and the uncertainty principle, the potential field converges to the classical answer as (ℏ/m )2. Thus, any dynamics coupled to the superfluid potential is expected to recover the classical collisionless limit as ℏ/m →0 . The quantum superfluid is able to capture rich phenomena such as multiple phase-sheets, shell-crossings, and warm distributions. Additionally, the quantum pressure tensor acts as a regularizer of caustics and singularities in classical solutions. This suggests the exciting prospect of using the Schrödinger-Poisson equations as a low-memory method for approximating the high-dimensional evolution of the Vlasov-Poisson equations. As a particular example we consider dark matter composed of ultralight axions, which in the classical limit (ℏ/m →0 ) is expected to manifest itself as collisionless cold dark matter.

Is there scale-dependent bias in single-field inflation?

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

De Putter, Roland; Doré, Olivier; Green, Daniel, E-mail: rdputter@caltech.edu, E-mail: Olivier.P.Dore@jpl.nasa.gov, E-mail: drgreen@cita.utoronto.ca

2015-10-01

Scale-dependent halo bias due to local primordial non-Gaussianity provides a strong test of single-field inflation. While it is universally understood that single-field inflation predicts negligible scale-dependent bias compared to current observational uncertainties, there is still disagreement on the exact level of scale-dependent bias at a level that could strongly impact inferences made from future surveys. In this paper, we clarify this confusion and derive in various ways that there is exactly zero scale-dependent bias in single-field inflation. Much of the current confusion follows from the fact that single-field inflation does predict a mode coupling of matter perturbations at the levelmore » of f{sub NL}{sup local}; ≈ −5/3, which naively would lead to scale-dependent bias. However, we show explicitly that this mode coupling cancels out when perturbations are evaluated at a fixed physical scale rather than fixed coordinate scale. Furthermore, we show how the absence of scale-dependent bias can be derived easily in any gauge. This result can then be incorporated into a complete description of the observed galaxy clustering, including the previously studied general relativistic terms, which are important at the same level as scale-dependent bias of order f{sub NL}{sup local} ∼ 1. This description will allow us to draw unbiased conclusions about inflation from future galaxy clustering data.« less

Herd-level risk factors for Campylobacter fetus infection, Brucella seropositivity and within-herd seroprevalence of brucellosis in cattle in northern Nigeria.

PubMed

Mai, H M; Irons, P C; Kabir, J; Thompson, P N

2013-09-01

Brucellosis and campylobacteriosis are economically important diseases affecting bovine reproductive efficiency in Nigeria. A questionnaire-based survey was conducted in 271 cattle herds in Adamawa, Kaduna and Kano states of northern Nigeria using multistage cluster sampling. Serum from 4745 mature animals was tested for Brucella antibodies using the Rose-Bengal plate test and positives were confirmed in series-testing protocol using competitive enzyme-linked immunosorbent assay. Preputial scrapings from 602 bulls were tested using culture and identification for Campylobacter fetus. For each disease, a herd was classified as positive if one or more animals tested positive. For each herd, information on potential managemental and environmental risk factors was collected through a questionnaire administered during an interview with the manager, owner or herdsman. Multiple logistic regression models were used to model the odds of herd infection for each disease. A zero-inflated Poisson model was used to model the count of Brucella-positive animals within herds, with the number tested as an exposure variable. The presence of small ruminants (sheep and/or goats) on the same farm, and buying-in of >3 new animals in the previous year or failure to practice quarantine were associated with increased odds of herd-level campylobacteriosis and brucellosis, as well as increased within-herd counts of Brucella-positive animals. In addition, high rainfall, initial acquisition of animals from markets, practice of gynaecological examination and failure to practice herd prophylactic measures were positively associated with the odds of C. fetus infection in the herd. Herd size of >15, pastoral management system and presence of handling facility on the farm were associated with increased odds, and gynaecological examination with reduced odds of herd-level Brucella seropositivity. Furthermore, the zero-inflated Poisson model showed that borrowing or sharing of bulls was associated with

Bayesian hierarchical modelling of continuous non-negative longitudinal data with a spike at zero: An application to a study of birds visiting gardens in winter.

PubMed

Swallow, Ben; Buckland, Stephen T; King, Ruth; Toms, Mike P

2016-03-01

The development of methods for dealing with continuous data with a spike at zero has lagged behind those for overdispersed or zero-inflated count data. We consider longitudinal ecological data corresponding to an annual average of 26 weekly maximum counts of birds, and are hence effectively continuous, bounded below by zero but also with a discrete mass at zero. We develop a Bayesian hierarchical Tweedie regression model that can directly accommodate the excess number of zeros common to this type of data, whilst accounting for both spatial and temporal correlation. Implementation of the model is conducted in a Markov chain Monte Carlo (MCMC) framework, using reversible jump MCMC to explore uncertainty across both parameter and model spaces. This regression modelling framework is very flexible and removes the need to make strong assumptions about mean-variance relationships a priori. It can also directly account for the spike at zero, whilst being easily applicable to other types of data and other model formulations. Whilst a correlative study such as this cannot prove causation, our results suggest that an increase in an avian predator may have led to an overall decrease in the number of one of its prey species visiting garden feeding stations in the United Kingdom. This may reflect a change in behaviour of house sparrows to avoid feeding stations frequented by sparrowhawks, or a reduction in house sparrow population size as a result of sparrowhawk increase. © 2015 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Using multi-year national survey cohorts for period estimates: an application of weighted discrete Poisson regression for assessing annual national mortality in US adults with and without diabetes, 2000-2006.

PubMed

Cheng, Yiling J; Gregg, Edward W; Rolka, Deborah B; Thompson, Theodore J

2016-12-15

Monitoring national mortality among persons with a disease is important to guide and evaluate progress in disease control and prevention. However, a method to estimate nationally representative annual mortality among persons with and without diabetes in the United States does not currently exist. The aim of this study is to demonstrate use of weighted discrete Poisson regression on national survey mortality follow-up data to estimate annual mortality rates among adults with diabetes. To estimate mortality among US adults with diabetes, we applied a weighted discrete time-to-event Poisson regression approach with post-stratification adjustment to national survey data. Adult participants aged 18 or older with and without diabetes in the National Health Interview Survey 1997-2004 were followed up through 2006 for mortality status. We estimated mortality among all US adults, and by self-reported diabetes status at baseline. The time-varying covariates used were age and calendar year. Mortality among all US adults was validated using direct estimates from the National Vital Statistics System (NVSS). Using our approach, annual all-cause mortality among all US adults ranged from 8.8 deaths per 1,000 person-years (95% confidence interval [CI]: 8.0, 9.6) in year 2000 to 7.9 (95% CI: 7.6, 8.3) in year 2006. By comparison, the NVSS estimates ranged from 8.6 to 7.9 (correlation = 0.94). All-cause mortality among persons with diabetes decreased from 35.7 (95% CI: 28.4, 42.9) in 2000 to 31.8 (95% CI: 28.5, 35.1) in 2006. After adjusting for age, sex, and race/ethnicity, persons with diabetes had 2.1 (95% CI: 2.01, 2.26) times the risk of death of those without diabetes. Period-specific national mortality can be estimated for people with and without a chronic condition using national surveys with mortality follow-up and a discrete time-to-event Poisson regression approach with post-stratification adjustment.

The Inflatable Poster

NASA Astrophysics Data System (ADS)

Tackley, P. J.

2004-12-01

Inflatable devices are frequently used in advertising in order to grab the attention of consumers: one sees, for example, 20 foot tall inflatable drink containers, inflatable cell phones, inflatable bubble gum packets, as well as blimps wafting majestically over major sports events. More usefully, inflatable representations of scientifically-interesting items are widely available, including astronauts, space shuttles, dinosaurs and globes and can help to build and inspire the interest of the general public, and in particular children, in such ideas. How can such concepts be adapted to improve poster presentations? Possibility one is to use relevant existing commercially-available inflatables to dress the poster: skeletons, astronauts, globes and so forth. More exciting is to develop custom inflatables that represent three-dimensional renderings of objects that the poster is describing. Examples of individual objects might be an inflatable slab, inflatable avalanche, inflatable plume, or it's larger cousin, the 10 foot high inflatable superplume or 20 foot high inflatable megaplume. More elaborately, inflatables might represent isosurfaces in three-dimensional spherical convection, although other fabrication methods may be more suitable. More simply, inflatable spheres could be imprinted with the planform of convection, geoid, or other spherical fields of geophysical interest. Finally, it should be possible to put an entire poster on an inflatable object, possibly small ones (balloons) to hand out. A major concern, however, is that the presenter may use such techniques to inflate their scientific findings, or to present overblown ideas.

Multi-material Additive Manufacturing of Metamaterials with Giant, Tailorable Negative Poisson's Ratios.

PubMed

Chen, Da; Zheng, Xiaoyu

2018-06-14

Nature has evolved with a recurring strategy to achieve unusual mechanical properties through coupling variable elastic moduli from a few GPa to below KPa within a single tissue. The ability to produce multi-material, three-dimensional (3D) micro-architectures with high fidelity incorporating dissimilar components has been a major challenge in man-made materials. Here we show multi-modulus metamaterials whose architectural element is comprised of encoded elasticity ranging from rigid to soft. We found that, in contrast to ordinary architected materials whose negative Poisson's ratio is dictated by their geometry, these type of metamaterials are capable of displaying Poisson's ratios from extreme negative to zero, independent of their 3D micro-architecture. The resulting low density metamaterials is capable of achieving functionally graded, distributed strain amplification capabilities within the metamaterial with uniform micro-architectures. Simultaneous tuning of Poisson's ratio and moduli within the 3D multi-materials could open up a broad array of material by design applications ranging from flexible armor, artificial muscles, to actuators and bio-mimetic materials.

Inflation and dark energy from f(R) gravity

NASA Astrophysics Data System (ADS)

Artymowski, Michał; Lalak, Zygmunt

2014-09-01

The standard Starobinsky inflation has been extended to the R + α Rn - β R2-n model to obtain a stable minimum of the Einstein frame scalar potential of the auxiliary field. As a result we have obtained obtain a scalar potential with non-zero value of residual vacuum energy, which may be a source of Dark Energy. Our results can be easily consistent with PLANCK or BICEP2 data for appropriate choices of the value of n.

Are all quantitative postmarketing signal detection methods equal? Performance characteristics of logistic regression and Multi-item Gamma Poisson Shrinker.

PubMed

Berlin, Conny; Blanch, Carles; Lewis, David J; Maladorno, Dionigi D; Michel, Christiane; Petrin, Michael; Sarp, Severine; Close, Philippe

2012-06-01

The detection of safety signals with medicines is an essential activity to protect public health. Despite widespread acceptance, it is unclear whether recently applied statistical algorithms provide enhanced performance characteristics when compared with traditional systems. Novartis has adopted a novel system for automated signal detection on the basis of disproportionality methods within a safety data mining application (Empirica™ Signal System [ESS]). ESS uses two algorithms for routine analyses: empirical Bayes Multi-item Gamma Poisson Shrinker and logistic regression (LR). A model was developed comprising 14 medicines, categorized as "new" or "established." A standard was prepared on the basis of safety findings selected from traditional sources. ESS results were compared with the standard to calculate the positive predictive value (PPV), specificity, and sensitivity. PPVs of the lower one-sided 5% and 0.05% confidence limits of the Bayes geometric mean (EB05) and of the LR odds ratio (LR0005) almost coincided for all the drug-event combinations studied. There was no obvious difference comparing the PPV of the leading Medical Dictionary for Regulatory Activities (MedDRA) terms to the PPV for all terms. The PPV of narrow MedDRA query searches was higher than that for broad searches. The widely used threshold value of EB05 = 2.0 or LR0005 = 2.0 together with more than three spontaneous reports of the drug-event combination produced balanced results for PPV, sensitivity, and specificity. Consequently, performance characteristics were best for leading terms with narrow MedDRA query searches irrespective of applying Multi-item Gamma Poisson Shrinker or LR at a threshold value of 2.0. This research formed the basis for the configuration of ESS for signal detection at Novartis. Copyright © 2011 John Wiley & Sons, Ltd.

Soft inflation

NASA Technical Reports Server (NTRS)

Berkin, Andrew L.; Maeda, Kei-Ichi; Yokoyama, Junichi

1990-01-01

The cosmology resulting from two coupled scalar fields was studied, one which is either a new inflation or chaotic type inflation, and the other which has an exponentially decaying potential. Such a potential may appear in the conformally transformed frame of generalized Einstein theories like the Jordan-Brans-Dicke theory. The constraints necessary for successful inflation are examined. Conventional GUT models such as SU(5) were found to be compatible with new inflation, while restrictions on the self-coupling constant are significantly loosened for chaotic inflation.

Nambu-Poisson gauge theory

NASA Astrophysics Data System (ADS)

Jurčo, Branislav; Schupp, Peter; Vysoký, Jan

2014-06-01

We generalize noncommutative gauge theory using Nambu-Poisson structures to obtain a new type of gauge theory with higher brackets and gauge fields. The approach is based on covariant coordinates and higher versions of the Seiberg-Witten map. We construct a covariant Nambu-Poisson gauge theory action, give its first order expansion in the Nambu-Poisson tensor and relate it to a Nambu-Poisson matrix model.

Low-Mass Inflation Systems for Inflatable Structures

NASA Technical Reports Server (NTRS)

Thunnissen, Daniel P.; Webster, Mark S.; Engelbrecht, Carl S.

1995-01-01

The use of inflatable space structures has often been proposed for aerospace and planetary applications. Communication, power generation, and very-long-baseline interferometry are just three potential applications of inflatable technology. The success of inflatable structures depends on the development of an applications of inflatable technology. This paper describes two design studies performed to develop a low mass inflation system. The first study takes advantage of existing onboard propulsion gases to reduce the overall system mass. The second study assumes that there is no onboard propulsion system. Both studies employ advanced components developed for the Pluto fast flyby spacecraft to further reduce mass. The study examined four different types of systems: hydrazine, nitrogen and water, nitrogen, and xenon. This study shows that all of these systems can be built for a small space structure with masses lower than 0.5 kilograms.

LD Score Regression Distinguishes Confounding from Polygenicity in Genome-Wide Association Studies

PubMed Central

Bulik-Sullivan, Brendan K.; Loh, Po-Ru; Finucane, Hilary; Ripke, Stephan; Yang, Jian; Patterson, Nick; Daly, Mark J.; Price, Alkes L.; Neale, Benjamin M.

2015-01-01

Both polygenicity (i.e., many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield an inflated distribution of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from true polygenic signal and bias. We have developed an approach, LD Score regression, that quantifies the contribution of each by examining the relationship between test statistics and linkage disequilibrium (LD). The LD Score regression intercept can be used to estimate a more powerful and accurate correction factor than genomic control. We find strong evidence that polygenicity accounts for the majority of test statistic inflation in many GWAS of large sample size. PMID:25642630

First-order inflation

NASA Technical Reports Server (NTRS)

Kolb, Edward W.

1991-01-01

In the original proposal, inflation occurred in the process of a strongly first-order phase transition. This model was soon demonstrated to be fatally flawed. Subsequent models for inflation involved phase transitions that were second-order, or perhaps weakly first-order; some even involved no phase transition at all. Recently the possibility of inflation during a strongly first-order phase transition has been revived. In this talk I will discuss some models for first-order inflation, and emphasize unique signatures that result if inflation is realized in a first-order transition. Before discussing first-order inflation, I will briefly review some of the history of inflation to demonstrate how first-order inflation differs from other models.

Poisson-Based Inference for Perturbation Models in Adaptive Spelling Training

ERIC Educational Resources Information Center

Baschera, Gian-Marco; Gross, Markus

2010-01-01

We present an inference algorithm for perturbation models based on Poisson regression. The algorithm is designed to handle unclassified input with multiple errors described by independent mal-rules. This knowledge representation provides an intelligent tutoring system with local and global information about a student, such as error classification…

Species abundance in a forest community in South China: A case of poisson lognormal distribution

USGS Publications Warehouse

Yin, Z.-Y.; Ren, H.; Zhang, Q.-M.; Peng, S.-L.; Guo, Q.-F.; Zhou, G.-Y.

2005-01-01

Case studies on Poisson lognormal distribution of species abundance have been rare, especially in forest communities. We propose a numerical method to fit the Poisson lognormal to the species abundance data at an evergreen mixed forest in the Dinghushan Biosphere Reserve, South China. Plants in the tree, shrub and herb layers in 25 quadrats of 20 m??20 m, 5 m??5 m, and 1 m??1 m were surveyed. Results indicated that: (i) for each layer, the observed species abundance with a similarly small median, mode, and a variance larger than the mean was reverse J-shaped and followed well the zero-truncated Poisson lognormal; (ii) the coefficient of variation, skewness and kurtosis of abundance, and two Poisson lognormal parameters (?? and ??) for shrub layer were closer to those for the herb layer than those for the tree layer; and (iii) from the tree to the shrub to the herb layer, the ?? and the coefficient of variation decreased, whereas diversity increased. We suggest that: (i) the species abundance distributions in the three layers reflects the overall community characteristics; (ii) the Poisson lognormal can describe the species abundance distribution in diverse communities with a few abundant species but many rare species; and (iii) 1/?? should be an alternative measure of diversity.

Prediction of Short-Distance Aerial Movement of Phakopsora pachyrhizi Urediniospores Using Machine Learning.

PubMed

Wen, L; Bowen, C R; Hartman, G L

2017-10-01

Dispersal of urediniospores by wind is the primary means of spread for Phakopsora pachyrhizi, the cause of soybean rust. Our research focused on the short-distance movement of urediniospores from within the soybean canopy and up to 61 m from field-grown rust-infected soybean plants. Environmental variables were used to develop and compare models including the least absolute shrinkage and selection operator regression, zero-inflated Poisson/regular Poisson regression, random forest, and neural network to describe deposition of urediniospores collected in passive and active traps. All four models identified distance of trap from source, humidity, temperature, wind direction, and wind speed as the five most important variables influencing short-distance movement of urediniospores. The random forest model provided the best predictions, explaining 76.1 and 86.8% of the total variation in the passive- and active-trap datasets, respectively. The prediction accuracy based on the correlation coefficient (r) between predicted values and the true values were 0.83 (P < 0.0001) and 0.94 (P < 0.0001) for the passive and active trap datasets, respectively. Overall, multiple machine learning techniques identified the most important variables to make the most accurate predictions of movement of P. pachyrhizi urediniospores short-distance.

Predictors for the Number of Warning Information Sources During Tornadoes.

PubMed

Cong, Zhen; Luo, Jianjun; Liang, Daan; Nejat, Ali

2017-04-01

People may receive tornado warnings from multiple information sources, but little is known about factors that affect the number of warning information sources (WISs). This study examined predictors for the number of WISs with a telephone survey on randomly sampled residents in Tuscaloosa, Alabama, and Joplin, Missouri, approximately 1 year after both cities were struck by violent tornadoes (EF4 and EF5) in 2011. The survey included 1006 finished interviews and the working sample included 903 respondents. Poisson regression and Zero-Inflated Poisson regression showed that older age and having an emergency plan predicted more WISs in both cities. Education, marital status, and gender affected the possibilities of receiving warnings and the number of WISs either in Joplin or in Tuscaloosa. The findings suggest that social disparity affects the access to warnings not only with respect to the likelihood of receiving any warnings but also with respect to the number of WISs. In addition, historical and social contexts are important for examining predictors for the number of WISs. We recommend that the number of WISs should be regarded as an important measure to evaluate access to warnings in addition to the likelihood of receiving warnings. (Disaster Med Public Health Preparedness. 2017;11:168-172).

Estimation of inflation parameters for Perturbed Power Law model using recent CMB measurements

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

Mukherjee, Suvodip; Das, Santanu; Souradeep, Tarun

2015-01-01

Cosmic Microwave Background (CMB) is an important probe for understanding the inflationary era of the Universe. We consider the Perturbed Power Law (PPL) model of inflation which is a soft deviation from Power Law (PL) inflationary model. This model captures the effect of higher order derivative of Hubble parameter during inflation, which in turn leads to a non-zero effective mass m{sub eff} for the inflaton field. The higher order derivatives of Hubble parameter at leading order sources constant difference in the spectral index for scalar and tensor perturbation going beyond PL model of inflation. PPL model have two observable independentmore » parameters, namely spectral index for tensor perturbation ν{sub t} and change in spectral index for scalar perturbation ν{sub st} to explain the observed features in the scalar and tensor power spectrum of perturbation. From the recent measurements of CMB power spectra by WMAP, Planck and BICEP-2 for temperature and polarization, we estimate the feasibility of PPL model with standard ΛCDM model. Although BICEP-2 claimed a detection of r=0.2, estimates of dust contamination provided by Planck have left open the possibility that only upper bound on r will be expected in a joint analysis. As a result we consider different upper bounds on the value of r and show that PPL model can explain a lower value of tensor to scalar ratio (r<0.1 or r<0.01) for a scalar spectral index of n{sub s}=0.96 by having a non-zero value of effective mass of the inflaton field m{sup 2}{sub eff}/H{sup 2}. The analysis with WP + Planck likelihood shows a non-zero detection of m{sup 2}{sub eff}/H{sup 2} with 5.7 σ and 8.1 σ respectively for r<0.1 and r<0.01. Whereas, with BICEP-2 likelihood m{sup 2}{sub eff}/H{sup 2} = −0.0237 ± 0.0135 which is consistent with zero.« less

Estimation of inflation parameters for Perturbed Power Law model using recent CMB measurements

NASA Astrophysics Data System (ADS)

Mukherjee, Suvodip; Das, Santanu; Joy, Minu; Souradeep, Tarun

2015-01-01

Cosmic Microwave Background (CMB) is an important probe for understanding the inflationary era of the Universe. We consider the Perturbed Power Law (PPL) model of inflation which is a soft deviation from Power Law (PL) inflationary model. This model captures the effect of higher order derivative of Hubble parameter during inflation, which in turn leads to a non-zero effective mass meff for the inflaton field. The higher order derivatives of Hubble parameter at leading order sources constant difference in the spectral index for scalar and tensor perturbation going beyond PL model of inflation. PPL model have two observable independent parameters, namely spectral index for tensor perturbation νt and change in spectral index for scalar perturbation νst to explain the observed features in the scalar and tensor power spectrum of perturbation. From the recent measurements of CMB power spectra by WMAP, Planck and BICEP-2 for temperature and polarization, we estimate the feasibility of PPL model with standard ΛCDM model. Although BICEP-2 claimed a detection of r=0.2, estimates of dust contamination provided by Planck have left open the possibility that only upper bound on r will be expected in a joint analysis. As a result we consider different upper bounds on the value of r and show that PPL model can explain a lower value of tensor to scalar ratio (r<0.1 or r<0.01) for a scalar spectral index of ns=0.96 by having a non-zero value of effective mass of the inflaton field m2eff/H2. The analysis with WP + Planck likelihood shows a non-zero detection of m2eff/H2 with 5.7 σ and 8.1 σ respectively for r<0.1 and r<0.01. Whereas, with BICEP-2 likelihood m2eff/H2 = -0.0237 ± 0.0135 which is consistent with zero.

Maximum Entropy Discrimination Poisson Regression for Software Reliability Modeling.

PubMed

Chatzis, Sotirios P; Andreou, Andreas S

2015-11-01

Reliably predicting software defects is one of the most significant tasks in software engineering. Two of the major components of modern software reliability modeling approaches are: 1) extraction of salient features for software system representation, based on appropriately designed software metrics and 2) development of intricate regression models for count data, to allow effective software reliability data modeling and prediction. Surprisingly, research in the latter frontier of count data regression modeling has been rather limited. More specifically, a lack of simple and efficient algorithms for posterior computation has made the Bayesian approaches appear unattractive, and thus underdeveloped in the context of software reliability modeling. In this paper, we try to address these issues by introducing a novel Bayesian regression model for count data, based on the concept of max-margin data modeling, effected in the context of a fully Bayesian model treatment with simple and efficient posterior distribution updates. Our novel approach yields a more discriminative learning technique, making more effective use of our training data during model inference. In addition, it allows of better handling uncertainty in the modeled data, which can be a significant problem when the training data are limited. We derive elegant inference algorithms for our model under the mean-field paradigm and exhibit its effectiveness using the publicly available benchmark data sets.

Inflatable Structures Technology Handbook. Chapter 21; Inflatable Habitats

NASA Technical Reports Server (NTRS)

Kennedy, Kriss J.; Raboin, Jasen; Spexarth, Gary; Valle, Gerard

2000-01-01

The technologies required to design, fabricate, and utilize an inflatable module for space applications has been demonstrated and proven by the TransHab team during the development phase of the program. Through testing and hands-on development several issues about inflatable space structures have been addressed , such as: ease of manufacturing, structural integrity, micrometeorite protection, folding , and vacuum deployment. The TransHab inflatable technology development program has proven that not only are inflatable structures a viable option, but they also offer significant advantages over conventional metallic structures.

Cosmic Inflation

ScienceCinema

Lincoln, Don

2018-01-16

In 1964, scientists discovered a faint radio hiss coming from the heavens and realized that the hiss wasn’t just noise. It was a message from eons ago; specifically the remnants of the primordial fireball, cooled to about 3 degrees above absolute zero. Subsequent research revealed that the radio hiss was the same in every direction. The temperature of the early universe was uniform to at better than a part in a hundred thousand. And this was weird. According to the prevailing theory, the two sides of the universe have never been in contact. So how could two places that had never been in contact be so similar? One possible explanation was proposed in 1979. Called inflation, the theory required that early in the history of the universe, the universe expanded faster than the speed of light. Confused? Watch this video as Fermilab’s Dr. Don Lincoln makes sense of this mind-bending idea.

Cosmic Inflation

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

Lincoln, Don

In 1964, scientists discovered a faint radio hiss coming from the heavens and realized that the hiss wasn’t just noise. It was a message from eons ago; specifically the remnants of the primordial fireball, cooled to about 3 degrees above absolute zero. Subsequent research revealed that the radio hiss was the same in every direction. The temperature of the early universe was uniform to at better than a part in a hundred thousand. And this was weird. According to the prevailing theory, the two sides of the universe have never been in contact. So how could two places that hadmore » never been in contact be so similar? One possible explanation was proposed in 1979. Called inflation, the theory required that early in the history of the universe, the universe expanded faster than the speed of light. Confused? Watch this video as Fermilab’s Dr. Don Lincoln makes sense of this mind-bending idea.« less

Population heterogeneity in the salience of multiple risk factors for adolescent delinquency.

PubMed

Lanza, Stephanie T; Cooper, Brittany R; Bray, Bethany C

2014-03-01

To present mixture regression analysis as an alternative to more standard regression analysis for predicting adolescent delinquency. We demonstrate how mixture regression analysis allows for the identification of population subgroups defined by the salience of multiple risk factors. We identified population subgroups (i.e., latent classes) of individuals based on their coefficients in a regression model predicting adolescent delinquency from eight previously established risk indices drawn from the community, school, family, peer, and individual levels. The study included N = 37,763 10th-grade adolescents who participated in the Communities That Care Youth Survey. Standard, zero-inflated, and mixture Poisson and negative binomial regression models were considered. Standard and mixture negative binomial regression models were selected as optimal. The five-class regression model was interpreted based on the class-specific regression coefficients, indicating that risk factors had varying salience across classes of adolescents. Standard regression showed that all risk factors were significantly associated with delinquency. Mixture regression provided more nuanced information, suggesting a unique set of risk factors that were salient for different subgroups of adolescents. Implications for the design of subgroup-specific interventions are discussed. Copyright © 2014 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Anisotropic inflation with a non-minimally coupled electromagnetic field to gravity

NASA Astrophysics Data System (ADS)

Adak, Muzaffer; Akarsu, Özgür; Dereli, Tekin; Sert, Özcan

2017-11-01

We consider the non-minimal model of gravity in Y(R) F2-form. We investigate a particular case of the model, for which the higher order derivatives are eliminated but the scalar curvature R is kept to be dynamical via the constraint YRFmnFmn =-2/κ2. The effective fluid obtained can be represented by interacting electromagnetic field and vacuum depending on Y(R), namely, the energy density of the vacuum tracks R while energy density of the conventional electromagnetic field is dynamically scaled with the factor Y(R)/2. We give exact solutions for anisotropic inflation by assuming the volume scale factor of the Universe exhibits a power-law expansion. The directional scale factors do not necessarily exhibit power-law expansion, which would give rise to a constant expansion anisotropy, but expand non-trivially and give rise to a non-monotonically evolving expansion anisotropy that eventually converges to a non-zero constant. Relying on this fact, we discuss the anisotropic e-fold during the inflation by considering observed scale invariance in CMB and demanding the Universe to undergo the same amount of e-folds in all directions. We calculate the residual expansion anisotropy at the end of inflation, though as a result of non-monotonic behaviour of expansion anisotropy all the axes of the Universe undergo the same of amount of e-folds by the end of inflation. We also discuss the generation of the modified electromagnetic field during the first few e-folds of the inflation and its persistence against to the vacuum till end of inflation.

Fractional Poisson Fields and Martingales

NASA Astrophysics Data System (ADS)

Aletti, Giacomo; Leonenko, Nikolai; Merzbach, Ely

2018-02-01

We present new properties for the Fractional Poisson process (FPP) and the Fractional Poisson field on the plane. A martingale characterization for FPPs is given. We extend this result to Fractional Poisson fields, obtaining some other characterizations. The fractional differential equations are studied. We consider a more general Mixed-Fractional Poisson process and show that this process is the stochastic solution of a system of fractional differential-difference equations. Finally, we give some simulations of the Fractional Poisson field on the plane.

Seasonally adjusted birth frequencies follow the Poisson distribution.

PubMed

Barra, Mathias; Lindstrøm, Jonas C; Adams, Samantha S; Augestad, Liv A

2015-12-15

Variations in birth frequencies have an impact on activity planning in maternity wards. Previous studies of this phenomenon have commonly included elective births. A Danish study of spontaneous births found that birth frequencies were well modelled by a Poisson process. Somewhat unexpectedly, there were also weekly variations in the frequency of spontaneous births. Another study claimed that birth frequencies follow the Benford distribution. Our objective was to test these results. We analysed 50,017 spontaneous births at Akershus University Hospital in the period 1999-2014. To investigate the Poisson distribution of these births, we plotted their variance over a sliding average. We specified various Poisson regression models, with the number of births on a given day as the outcome variable. The explanatory variables included various combinations of years, months, days of the week and the digit sum of the date. The relationship between the variance and the average fits well with an underlying Poisson process. A Benford distribution was disproved by a goodness-of-fit test (p < 0.01). The fundamental model with year and month as explanatory variables is significantly improved (p < 0.001) by adding day of the week as an explanatory variable. Altogether 7.5% more children are born on Tuesdays than on Sundays. The digit sum of the date is non-significant as an explanatory variable (p = 0.23), nor does it increase the explained variance. INERPRETATION: Spontaneous births are well modelled by a time-dependent Poisson process when monthly and day-of-the-week variation is included. The frequency is highest in summer towards June and July, Friday and Tuesday stand out as particularly busy days, and the activity level is at its lowest during weekends.

Fitting statistical distributions to sea duck count data: implications for survey design and abundance estimation

USGS Publications Warehouse

Zipkin, Elise F.; Leirness, Jeffery B.; Kinlan, Brian P.; O'Connell, Allan F.; Silverman, Emily D.

2014-01-01

Determining appropriate statistical distributions for modeling animal count data is important for accurate estimation of abundance, distribution, and trends. In the case of sea ducks along the U.S. Atlantic coast, managers want to estimate local and regional abundance to detect and track population declines, to define areas of high and low use, and to predict the impact of future habitat change on populations. In this paper, we used a modified marked point process to model survey data that recorded flock sizes of Common eiders, Long-tailed ducks, and Black, Surf, and White-winged scoters. The data come from an experimental aerial survey, conducted by the United States Fish & Wildlife Service (USFWS) Division of Migratory Bird Management, during which east-west transects were flown along the Atlantic Coast from Maine to Florida during the winters of 2009–2011. To model the number of flocks per transect (the points), we compared the fit of four statistical distributions (zero-inflated Poisson, zero-inflated geometric, zero-inflated negative binomial and negative binomial) to data on the number of species-specific sea duck flocks that were recorded for each transect flown. To model the flock sizes (the marks), we compared the fit of flock size data for each species to seven statistical distributions: positive Poisson, positive negative binomial, positive geometric, logarithmic, discretized lognormal, zeta and Yule–Simon. Akaike’s Information Criterion and Vuong’s closeness tests indicated that the negative binomial and discretized lognormal were the best distributions for all species for the points and marks, respectively. These findings have important implications for estimating sea duck abundances as the discretized lognormal is a more skewed distribution than the Poisson and negative binomial, which are frequently used to model avian counts; the lognormal is also less heavy-tailed than the power law distributions (e.g., zeta and Yule–Simon), which are

Unemployment and inflation dynamics prior to the economic downturn of 2007-2008.

PubMed

Guastello, Stephen J; Myers, Adam

2009-10-01

This article revisits a long-standing theoretical issue as to whether a "natural rate" of unemployment exists in the sense of an exogenously driven fixed-point Walrasian equilibrium or attractor, or whether more complex dynamics such as hysteresis or chaos characterize an endogenous dynamical process instead. The same questions are posed regarding a possible natural rate of inflation along with an investigation of the actual relationship between inflation and unemployment for which extent theories differ. Time series of unemployment and inflation for US data - were analyzed using the exponential model series and nonlinear regression for capturing Lyapunov exponents and transfer effects from other variables. The best explanation for unemployment was that it is a chaotic variable that is driven in part by inflation. The best explanation for inflation is that it is also a chaotic variable driven in part by unemployment and the prices of treasury bills. Estimates of attractors' epicenters were calculated in lieu of classical natural rates.

On a Poisson homogeneous space of bilinear forms with a Poisson-Lie action

NASA Astrophysics Data System (ADS)

Chekhov, L. O.; Mazzocco, M.

2017-12-01

Let \\mathscr A be the space of bilinear forms on C^N with defining matrices A endowed with a quadratic Poisson structure of reflection equation type. The paper begins with a short description of previous studies of the structure, and then this structure is extended to systems of bilinear forms whose dynamics is governed by the natural action A\\mapsto B ABT} of the {GL}_N Poisson-Lie group on \\mathscr A. A classification is given of all possible quadratic brackets on (B, A)\\in {GL}_N× \\mathscr A preserving the Poisson property of the action, thus endowing \\mathscr A with the structure of a Poisson homogeneous space. Besides the product Poisson structure on {GL}_N× \\mathscr A, there are two other (mutually dual) structures, which (unlike the product Poisson structure) admit reductions by the Dirac procedure to a space of bilinear forms with block upper triangular defining matrices. Further generalisations of this construction are considered, to triples (B,C, A)\\in {GL}_N× {GL}_N× \\mathscr A with the Poisson action A\\mapsto B ACT}, and it is shown that \\mathscr A then acquires the structure of a Poisson symmetric space. Generalisations to chains of transformations and to the quantum and quantum affine algebras are investigated, as well as the relations between constructions of Poisson symmetric spaces and the Poisson groupoid. Bibliography: 30 titles.

Prediction of forest fires occurrences with area-level Poisson mixed models.

PubMed

Boubeta, Miguel; Lombardía, María José; Marey-Pérez, Manuel Francisco; Morales, Domingo

2015-05-01

The number of fires in forest areas of Galicia (north-west of Spain) during the summer period is quite high. Local authorities are interested in analyzing the factors that explain this phenomenon. Poisson regression models are good tools for describing and predicting the number of fires per forest areas. This work employs area-level Poisson mixed models for treating real data about fires in forest areas. A parametric bootstrap method is applied for estimating the mean squared errors of fires predictors. The developed methodology and software are applied to a real data set of fires in forest areas of Galicia. Copyright © 2015 Elsevier Ltd. All rights reserved.

Adiabatic elimination for systems with inertia driven by compound Poisson colored noise.

PubMed

Li, Tiejun; Min, Bin; Wang, Zhiming

2014-02-01

We consider the dynamics of systems driven by compound Poisson colored noise in the presence of inertia. We study the limit when the frictional relaxation time and the noise autocorrelation time both tend to zero. We show that the Itô and Marcus stochastic calculuses naturally arise depending on these two time scales, and an extra intermediate type occurs when the two time scales are comparable. This leads to three different limiting regimes which are supported by numerical simulations. Furthermore, we establish that when the resulting compound Poisson process tends to the Wiener process in the frequent jump limit the Itô and Marcus calculuses, respectively, tend to the classical Itô and Stratonovich calculuses for Gaussian white noise, and the crossover type calculus tends to a crossover between the Itô and Stratonovich calculuses. Our results would be very helpful for understanding relevant experiments when jump type noise is involved.

Temperature of the inflaton and duration of inflation from Wilkinson microwave anisotropy probe data.

PubMed

Bhattacharya, Kaushik; Mohanty, Subhendra; Rangarajan, Raghavan

2006-03-31

If the initial state of the inflaton field is taken to have a thermal distribution instead of the conventional zero particle vacuum state then the curvature power spectrum gets modified by a temperature dependent factor such that the fluctuation spectrum of the microwave background radiation is enhanced at larger angles. We compare this modified cosmic microwave background spectrum with Wilkinson microwave anisotropy probe data to obtain an upper bound on the temperature of the inflaton at the time our current horizon crossed the horizon during inflation. We further conclude that there must be additional -foldings of inflation beyond what is needed to solve the horizon problem.

Pseudosmooth tribrid inflation

NASA Astrophysics Data System (ADS)

Antusch, Stefan; Nolde, David; Rehman, Mansoor Ur

2012-08-01

We explore a new class of supersymmetric models of inflation where the inflaton is realised as a combination of a Higgs field and (gauge non-singlet) matter fields, using a ``tribrid'' structure of the superpotential. Inflation is associated with a phase transition around GUT scale energies. The inflationary trajectory already preselects the later vacuum after inflation, which has the advantage of automatically avoiding the production of dangerous topological defects at the end of inflation. While at first sight the models look similar to smooth inflation, they feature a waterfall and are therefore only pseudosmooth. The new class of models offers novel possibilities for realising inflation in close contact with particle physics, for instance with supersymmetric GUTs or with supersymmetric flavour models based on family symmetries.

What is the cause of confidence inflation in the Life Events Inventory (LEI) paradigm?

PubMed

Von Glahn, Nicholas R; Otani, Hajime; Migita, Mai; Langford, Sara J; Hillard, Erin E

2012-01-01

Briefly imagining, paraphrasing, or explaining an event causes people to increase their confidence that this event occurred during childhood-the imagination inflation effect. The mechanisms responsible for the effect were investigated with a new paradigm. In Experiment 1, event familiarity (defined as processing fluency) was varied by asking participants to rate each event once, three times, or five times. No inflation was found, indicating that familiarity does not account for the effect. In Experiment 2, richness of memory representation was manipulated by asking participants to generate zero, three, or six details. Confidence increased from the initial to the final rating in the three- and six-detail conditions, indicating that the effect is based on reality-monitoring errors. However, greater inflation in the three-detail condition than in the six-detail condition indicated that there is a boundary condition. These results were also consistent with an alternative hypothesis, the mental workload hypothesis.

A zero-augmented generalized gamma regression calibration to adjust for covariate measurement error: A case of an episodically consumed dietary intake

PubMed Central

Agogo, George O.

2017-01-01

Measurement error in exposure variables is a serious impediment in epidemiological studies that relate exposures to health outcomes. In nutritional studies, interest could be in the association between long-term dietary intake and disease occurrence. Long-term intake is usually assessed with food frequency questionnaire (FFQ), which is prone to recall bias. Measurement error in FFQ-reported intakes leads to bias in parameter estimate that quantifies the association. To adjust for bias in the association, a calibration study is required to obtain unbiased intake measurements using a short-term instrument such as 24-hour recall (24HR). The 24HR intakes are used as response in regression calibration to adjust for bias in the association. For foods not consumed daily, 24HR-reported intakes are usually characterized by excess zeroes, right skewness, and heteroscedasticity posing serious challenge in regression calibration modeling. We proposed a zero-augmented calibration model to adjust for measurement error in reported intake, while handling excess zeroes, skewness, and heteroscedasticity simultaneously without transforming 24HR intake values. We compared the proposed calibration method with the standard method and with methods that ignore measurement error by estimating long-term intake with 24HR and FFQ-reported intakes. The comparison was done in real and simulated datasets. With the 24HR, the mean increase in mercury level per ounce fish intake was about 0.4; with the FFQ intake, the increase was about 1.2. With both calibration methods, the mean increase was about 2.0. Similar trend was observed in the simulation study. In conclusion, the proposed calibration method performs at least as good as the standard method. PMID:27704599

The Effect of the "Zero Tolerance for Head Contact" Rule Change on the Risk of Concussions in Youth Ice Hockey Players.

PubMed

Krolikowski, Maciej P; Black, Amanda M; Palacios-Derflingher, Luz; Blake, Tracy A; Schneider, Kathryn J; Emery, Carolyn A

2017-02-01

Ice hockey is a popular winter sport in Canada. Concussions account for the greatest proportion of all injuries in youth ice hockey. In 2011, a policy change enforcing "zero tolerance for head contact" was implemented in all leagues in Canada. To determine if the risk of game-related concussions and more severe concussions (ie, resulting in >10 days of time loss) and the mechanisms of a concussion differed for Pee Wee class (ages 11-12 years) and Bantam class (ages 13-14 years) players after the 2011 "zero tolerance for head contact" policy change compared with players in similar divisions before the policy change. Cohort study; Level of evidence, 3. The retrospective cohort included Pee Wee (most elite 70%, 2007-2008; n = 891) and Bantam (most elite 30%, 2008-2009; n = 378) players before the rule change and Pee Wee (2011-2012; n = 588) and Bantam (2011-2012; n = 242) players in the same levels of play after the policy change. Suspected concussions were identified by a team designate and referred to a sport medicine physician for diagnosis. Incidence rate ratios (IRRs) were estimated based on multiple Poisson regression analysis, controlling for clustering by team and other important covariates and offset by game-exposure hours. Incidence rates based on the mechanisms of a concussion were estimated based on univariate Poisson regression analysis. The risk of game-related concussions increased after the head contact rule in Pee Wee (IRR, 1.85; 95% CI, 1.20-2.86) and Bantam (IRR, 2.48; 95% CI, 1.17-5.24) players. The risk of more severe concussions increased after the head contact rule in Pee Wee (IRR, 4.12; 95% CI, 2.00-8.50) and Bantam (IRR, 7.91; 95% CI, 3.13-19.94) players. The rates of concussions due to body checking and direct head contact increased after the rule change. The "zero tolerance for head contact" policy change did not reduce the risk of game-related concussions in Pee Wee or Bantam class ice hockey players. Increased concussion awareness and

Modification of the Mantel-Haenszel and Logistic Regression DIF Procedures to Incorporate the SIBTEST Regression Correction

ERIC Educational Resources Information Center

DeMars, Christine E.

2009-01-01

The Mantel-Haenszel (MH) and logistic regression (LR) differential item functioning (DIF) procedures have inflated Type I error rates when there are large mean group differences, short tests, and large sample sizes.When there are large group differences in mean score, groups matched on the observed number-correct score differ on true score,…

Distinguishing between extra natural inflation and natural inflation after BICEP2

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

Kohri, Kazunori; Lim, C.S.; Lin, Chia-Min, E-mail: kohri@post.kek.jp, E-mail: lim@lab.twcu.ac.jp, E-mail: lin@chuo-u.ac.jp

2014-08-01

In this paper, we carefully calculated the tensor-to-scalar ratio, the running spectral index, and the running of running spectrum for (extra) natural inflation in order to compare with recent BICEP2 data, PLANCK satellite data and future 21 cm data. We discovered that the prediction for running spectral index and the running of running spectrum in natural inflation is different from that in the case of extra natural inflation. Near future observation for the running spectral index can only provide marginal accuracy which may not allow us distinguishing between extra natural inflation from natural inflation clearly unless the experimental accuracy canmore » be further improved.« less

The Other Inflation

ERIC Educational Resources Information Center

Aristides

1976-01-01

The other inflation is grade inflation, the label affixed to the indisputable rise in the grade-point averages of undergraduates at public and private, elite and community colleges and universities across the country. The effects of grade inflation upon academic performance were assessed. (Author/RK)

Inflatable Vessel and Method

NASA Technical Reports Server (NTRS)

Raboin, Jasen L. (Inventor); Valle, Gerard D. (Inventor); Edeen, Gregg A. (Inventor); delaFuente, Horacio M. (Inventor); Schneider, William C. (Inventor); Spexarth, Gary R. (Inventor); Pandya, Shalini Gupta (Inventor); Johnson, Christopher J. (Inventor)

2003-01-01

An inflatable module comprising a structural core and an inflatable shell, wherein the inflatable shell is sealingly attached to the structural core. In its launch or pre-deployed configuration, the wall thickness of the inflatable shell is collapsed by vacuum. Also in this configuration, the inflatable shell is collapsed and efficiently folded around the structural core. Upon deployment, the wall thickness of the inflatable shell is inflated; whereby the inflatable shell itself, is thereby inflated around the structural core, defining therein a large enclosed volume. A plurality of removable shelves are arranged interior to the structural core in the launch configuration. The structural core also includes at least one longeron that, in conjunction with the shelves, primarily constitute the rigid, strong, and lightweight load-bearing structure of the module during launch. The removable shelves are detachable from their arrangement in the launch configuration so that, when the module is in its deployed configuration and launch loads no longer exist, the shelves can be rearranged to provide a module interior arrangement suitable for human habitation and work. In the preferred embodiment, to provide efficiency in structural load paths and attachments, the shape of the inflatable shell is a cylinder with semi-toroidal ends.

Compositions, Random Sums and Continued Random Fractions of Poisson and Fractional Poisson Processes

NASA Astrophysics Data System (ADS)

Orsingher, Enzo; Polito, Federico

2012-08-01

In this paper we consider the relation between random sums and compositions of different processes. In particular, for independent Poisson processes N α ( t), N β ( t), t>0, we have that N_{α}(N_{β}(t)) stackrel{d}{=} sum_{j=1}^{N_{β}(t)} Xj, where the X j s are Poisson random variables. We present a series of similar cases, where the outer process is Poisson with different inner processes. We highlight generalisations of these results where the external process is infinitely divisible. A section of the paper concerns compositions of the form N_{α}(tauk^{ν}), ν∈(0,1], where tauk^{ν} is the inverse of the fractional Poisson process, and we show how these compositions can be represented as random sums. Furthermore we study compositions of the form Θ( N( t)), t>0, which can be represented as random products. The last section is devoted to studying continued fractions of Cauchy random variables with a Poisson number of levels. We evaluate the exact distribution and derive the scale parameter in terms of ratios of Fibonacci numbers.

The Application of Censored Regression Models in Low Streamflow Analyses

NASA Astrophysics Data System (ADS)

Kroll, C.; Luz, J.

2003-12-01

Estimation of low streamflow statistics at gauged and ungauged river sites is often a daunting task. This process is further confounded by the presence of intermittent streamflows, where streamflow is sometimes reported as zero, within a region. Streamflows recorded as zero may be zero, or may be less than the measurement detection limit. Such data is often referred to as censored data. Numerous methods have been developed to characterize intermittent streamflow series. Logit regression has been proposed to develop regional models of the probability annual lowflows series (such as 7-day lowflows) are zero. In addition, Tobit regression, a method of regression that allows for censored dependent variables, has been proposed for lowflow regional regression models in regions where the lowflow statistic of interest estimated as zero at some sites in the region. While these methods have been proposed, their use in practice has been limited. Here a delete-one jackknife simulation is presented to examine the performance of Logit and Tobit models of 7-day annual minimum flows in 6 USGS water resource regions in the United States. For the Logit model, an assessment is made of whether sites are correctly classified as having at least 10% of 7-day annual lowflows equal to zero. In such a situation, the 7-day, 10-year lowflow (Q710), a commonly employed low streamflow statistic, would be reported as zero. For the Tobit model, a comparison is made between results from the Tobit model, and from performing either ordinary least squares (OLS) or principal component regression (PCR) after the zero sites are dropped from the analysis. Initial results for the Logit model indicate this method to have a high probability of correctly classifying sites into groups with Q710s as zero and non-zero. Initial results also indicate the Tobit model produces better results than PCR and OLS when more than 5% of the sites in the region have Q710 values calculated as zero.

Inflation from Minkowski space

DOE PAGES

Pirtskhalava, David; Santoni, Luca; Trincherini, Enrico; ...

2014-12-23

Here, we propose a class of scalar models that, once coupled to gravity, lead to cosmologies that smoothly and stably connect an inflationary quasi-de Sitter universe to a low, or even zero-curvature, maximally symmetric spacetime in the asymptotic past, strongly violating the null energy condition (H • >>H2) at intermediate times. The models are deformations of the conformal galileon lagrangian and are therefore based on symmetries, both exact and approximate, that ensure the quantum robustness of the whole picture. The resulting cosmological backgrounds can be viewed as regularized extensions of the galilean genesis scenario, or, equivalently, as ‘early-time-complete’ realizations ofmore » inflation. The late-time inflationary dynamics possesses phenomenologically interesting properties: it can produce a large tensor-to-scalar ratio within the regime of validity of the effective field theory and can lead to sizeable equilateral nongaussianities.« less

Cumulative Poisson Distribution Program

NASA Technical Reports Server (NTRS)

Bowerman, Paul N.; Scheuer, Ernest M.; Nolty, Robert

1990-01-01

Overflow and underflow in sums prevented. Cumulative Poisson Distribution Program, CUMPOIS, one of two computer programs that make calculations involving cumulative Poisson distributions. Both programs, CUMPOIS (NPO-17714) and NEWTPOIS (NPO-17715), used independently of one another. CUMPOIS determines cumulative Poisson distribution, used to evaluate cumulative distribution function (cdf) for gamma distributions with integer shape parameters and cdf for X (sup2) distributions with even degrees of freedom. Used by statisticians and others concerned with probabilities of independent events occurring over specific units of time, area, or volume. Written in C.

Supernatural inflation: inflation from supersymmetry with no (very) small parameters

NASA Astrophysics Data System (ADS)

Randall, Lisa; SoljačiĆ, Marin; Guth, Alan H.

1996-02-01

Most models of inflation have small parameters, either to guarantee sufficient inflation or the correct magnitude of the density perturbations. In this paper we show that, in supersymmetric theories with weak-scale supersymmetry breaking, one can construct viable inflationary models in which the requisite parameters appear naturally in the form of the ratio of mass scales that are already present in the theory. Successful inflationary models can be constructed from the flat-direction fields of a renormalizable supersymmetric potential, and such models can be realized even in the context of a simple GUT extension of the MSSM. We evade naive ``naturalness'' arguments by allowing for more than one field to be relevant to inflation, as in ``hybrid inflation'' models, and we argue that this is the most natural possibility if inflation fields are to be associated with flat direction fields of a supersymmetric theory. Such models predict a very low Hubble constant during inflation, of order 103-104 GeV, a scalar density perturbation index n which is very close to or greater than unity, and negligible tensor perturbations. In addition, these models lead to a large spike in the density perturbation spectrum at short wavelengths.

Nonlinear Poisson Equation for Heterogeneous Media

PubMed Central

Hu, Langhua; Wei, Guo-Wei

2012-01-01

The Poisson equation is a widely accepted model for electrostatic analysis. However, the Poisson equation is derived based on electric polarizations in a linear, isotropic, and homogeneous dielectric medium. This article introduces a nonlinear Poisson equation to take into consideration of hyperpolarization effects due to intensive charges and possible nonlinear, anisotropic, and heterogeneous media. Variational principle is utilized to derive the nonlinear Poisson model from an electrostatic energy functional. To apply the proposed nonlinear Poisson equation for the solvation analysis, we also construct a nonpolar solvation energy functional based on the nonlinear Poisson equation by using the geometric measure theory. At a fixed temperature, the proposed nonlinear Poisson theory is extensively validated by the electrostatic analysis of the Kirkwood model and a set of 20 proteins, and the solvation analysis of a set of 17 small molecules whose experimental measurements are also available for a comparison. Moreover, the nonlinear Poisson equation is further applied to the solvation analysis of 21 compounds at different temperatures. Numerical results are compared to theoretical prediction, experimental measurements, and those obtained from other theoretical methods in the literature. A good agreement between our results and experimental data as well as theoretical results suggests that the proposed nonlinear Poisson model is a potentially useful model for electrostatic analysis involving hyperpolarization effects. PMID:22947937

Nonlinear Poisson equation for heterogeneous media.

PubMed

Hu, Langhua; Wei, Guo-Wei

2012-08-22

The Poisson equation is a widely accepted model for electrostatic analysis. However, the Poisson equation is derived based on electric polarizations in a linear, isotropic, and homogeneous dielectric medium. This article introduces a nonlinear Poisson equation to take into consideration of hyperpolarization effects due to intensive charges and possible nonlinear, anisotropic, and heterogeneous media. Variational principle is utilized to derive the nonlinear Poisson model from an electrostatic energy functional. To apply the proposed nonlinear Poisson equation for the solvation analysis, we also construct a nonpolar solvation energy functional based on the nonlinear Poisson equation by using the geometric measure theory. At a fixed temperature, the proposed nonlinear Poisson theory is extensively validated by the electrostatic analysis of the Kirkwood model and a set of 20 proteins, and the solvation analysis of a set of 17 small molecules whose experimental measurements are also available for a comparison. Moreover, the nonlinear Poisson equation is further applied to the solvation analysis of 21 compounds at different temperatures. Numerical results are compared to theoretical prediction, experimental measurements, and those obtained from other theoretical methods in the literature. A good agreement between our results and experimental data as well as theoretical results suggests that the proposed nonlinear Poisson model is a potentially useful model for electrostatic analysis involving hyperpolarization effects. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Soft inflation. [in cosmology

NASA Technical Reports Server (NTRS)

Berkin, Andrew L.; Maeda, Kei-Ichi; Yokoyama, Jun'ichi

1990-01-01

The cosmology resulting from two coupled scalar fields was studied, one which is either a new inflation or chaotic type inflation, and the other which has an exponentially decaying potential. Such a potential may appear in the conformally transformed frame of generalized Einstein theories like the Jordan-Brans-Dicke theory. The constraints necessary for successful inflation are examined. Conventional GUT models such as SU(5) were found to be compatible with new inflation, while restrictions on the self-coupling constant are significantly loosened for chaotic inflation.

The emergence of gravity as a retro-causal post-inflation macro-quantum-coherent holographic vacuum Higgs-Goldstone field

NASA Astrophysics Data System (ADS)

Sarfatti, Jack; Levit, Creon

2009-06-01

We present a model for the origin of gravity, dark energy and dark matter: Dark energy and dark matter are residual pre-inflation false vacuum random zero point energy (w = - 1) of large-scale negative, and short-scale positive pressure, respectively, corresponding to the "zero point" (incoherent) component of a superfluid (supersolid) ground state. Gravity, in contrast, arises from the 2nd order topological defects in the post-inflation virtual "condensate" (coherent) component. We predict, as a consequence, that the LHC will never detect exotic real on-mass-shell particles that can explain dark matter ΩMDM approx 0.23. We also point out that the future holographic dark energy de Sitter horizon is a total absorber (in the sense of retro-causal Wheeler-Feynman action-at-a-distance electrodynamics) because it is an infinite redshift surface for static detectors. Therefore, the advanced Hawking-Unruh thermal radiation from the future de Sitter horizon is a candidate for the negative pressure dark vacuum energy.

Poisson's ratio of fiber-reinforced composites

NASA Astrophysics Data System (ADS)

Christiansson, Henrik; Helsing, Johan

1996-05-01

Poisson's ratio flow diagrams, that is, the Poisson's ratio versus the fiber fraction, are obtained numerically for hexagonal arrays of elastic circular fibers in an elastic matrix. High numerical accuracy is achieved through the use of an interface integral equation method. Questions concerning fixed point theorems and the validity of existing asymptotic relations are investigated and partially resolved. Our findings for the transverse effective Poisson's ratio, together with earlier results for random systems by other authors, make it possible to formulate a general statement for Poisson's ratio flow diagrams: For composites with circular fibers and where the phase Poisson's ratios are equal to 1/3, the system with the lowest stiffness ratio has the highest Poisson's ratio. For other choices of the elastic moduli for the phases, no simple statement can be made.

Properties of the Bivariate Delayed Poisson Process

DTIC Science & Technology

1974-07-01

and Lewis (1972) in their Berkeley Symposium paper and here their analysis of the bivariate Poisson processes (without Poisson noise) is carried... Poisson processes . They cannot, however, be independent Poisson processes because their events are associated in pairs by the displace- ment centres...process because its marginal processes for events of each type are themselves (univariate) Poisson processes . Cox and Lewis (1972) assumed a

Seasonal prediction of the typhoon genesis frequency over the Western North Pacific with a Poisson regression model

NASA Astrophysics Data System (ADS)

Zhang, Xinchang; Zhong, Shanshan; Wu, Zhiwei; Li, Yun

2017-06-01

This study investigates the typhoon genesis frequency (TGF) in the dominant season (July to October) in Western North Pacific (WNP) using observed data in 1965-2015. Of particular interest is the predictability of the TGF and associated preseason sea surface temperature (SST) in the Pacific. It is found that, the TGF is positively related to a tri-polar pattern of April SST anomalies in North Pacific (NP{T}_{Apr}), while it is negatively related to SST anomalies over the Coral Sea (CSS{T}_{Apr}) off east coast of Australia. The NP{T}_{Apr} leads to large anomalous cyclonic circulation over North Pacific. The anomalous southwesterly weakens the northeast trade wind, decreases evaporation, and induces warm water in central tropical North Pacific. As such, the warming effect amplifies the temperature gradient in central tropical North Pacific, which in turn maintains the cyclonic wind anomaly in the west tropical Pacific, which favors the typhoon genesis in WNP. In the South Pacific, the CSS{T}_{Apr} supports the typhoon formation over the WNP by (a) strengthening the cross-equatorial flows and enhancing the Inter-tropical Convergence Zone; (b) weakening southeast and northeast trade wind, and keeping continuous warming in the center of tropical Pacific. The influence of both NP{T}_{Apr} and CSS{T}_{Apr} can persistently affect the zonal wind in the tropical Pacific and induce conditions favorable for the typhoon genesis in the typhoon season. A Poisson regression model using NP{T}_{Apr} and CSS}{T}_{Apr} is developed to predict the TGF and a promising skill is achieved.

From Loss of Memory to Poisson.

ERIC Educational Resources Information Center

Johnson, Bruce R.

1983-01-01

A way of presenting the Poisson process and deriving the Poisson distribution for upper-division courses in probability or mathematical statistics is presented. The main feature of the approach lies in the formulation of Poisson postulates with immediate intuitive appeal. (MNS)

First-order inflation. [in cosmology

NASA Technical Reports Server (NTRS)

Kolb, Edward W.

1991-01-01

In the original proposal, inflation occurred in the process of a strongly first-order phase transition. This model was soon demonstrated to be fatally flawed. Subsequent models for inflation involved phase transitions that were second-order, or perhaps weakly first-order; some even involved no phase transition at all. Recently the possibility of inflation during a strongly first-order phase transition has been revived. In this paper, some models for first-order inflation are discussed, and unique signatures that result if inflation is realized in a first-order transition are emphasized. Some of the history of inflation is reviewed to demonstrate how first-order inflation differs from other models.

How thermal inflation can save minimal hybrid inflation in supergravity

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

Dimopoulos, Konstantinos; Owen, Charlotte

2016-10-12

Minimal hybrid inflation in supergravity has been ruled out by the 2015 Planck observations because the spectral index of the produced curvature perturbation falls outside observational bounds. To resurrect the model, a number of modifications have been put forward but many of them spoil the accidental cancellation that resolves the η-problem and require complicated Kähler constructions to counterbalance the lost cancellation. In contrast, in this paper the model is rendered viable by supplementing the scenario with a brief period of thermal inflation, which follows the reheating of primordial inflation. The scalar field responsible for thermal inflation requires a large non-zeromore » vacuum expectation value (VEV) and a flat potential. We investigate the VEV of such a flaton field and its subsequent effect on the inflationary observables. We find that, for large VEV, minimal hybrid inflation in supergravity produces a spectral index within the 1-σ Planck bound and a tensor-to-scalar ratio which may be observable in the near future. The mechanism is applicable to other inflationary models.« less

Longitudinal Poisson Regression To Evaluate the Epidemiology of Cryptosporidium, Giardia, and Fecal Indicator Bacteria in Coastal California Wetlands

PubMed Central

Hogan, Jennifer N.; Daniels, Miles E.; Watson, Fred G.; Conrad, Patricia A.; Oates, Stori C.; Miller, Melissa A.; Hardin, Dane; Byrne, Barbara A.; Dominik, Clare; Melli, Ann; Jessup, David A.

2012-01-01

Fecal pathogen contamination of watersheds worldwide is increasingly recognized, and natural wetlands may have an important role in mitigating fecal pathogen pollution flowing downstream. Given that waterborne protozoa, such as Cryptosporidium and Giardia, are transported within surface waters, this study evaluated associations between fecal protozoa and various wetland-specific and environmental risk factors. This study focused on three distinct coastal California wetlands: (i) a tidally influenced slough bordered by urban and agricultural areas, (ii) a seasonal wetland adjacent to a dairy, and (iii) a constructed wetland that receives agricultural runoff. Wetland type, seasonality, rainfall, and various water quality parameters were evaluated using longitudinal Poisson regression to model effects on concentrations of protozoa and indicator bacteria (Escherichia coli and total coliform). Among wetland types, the dairy wetland exhibited the highest protozoal and bacterial concentrations, and despite significant reductions in microbe concentrations, the wetland could still be seen to influence water quality in the downstream tidal wetland. Additionally, recent rainfall events were associated with higher protozoal and bacterial counts in wetland water samples across all wetland types. Notably, detection of E. coli concentrations greater than a 400 most probable number (MPN) per 100 ml was associated with higher Cryptosporidium oocyst and Giardia cyst concentrations. These findings show that natural wetlands draining agricultural and livestock operation runoff into human-utilized waterways should be considered potential sources of pathogens and that wetlands can be instrumental in reducing pathogen loads to downstream waters. PMID:22427504

Inflatable wing

DOEpatents

Priddy, Tommy G.

1988-01-01

An inflatable wing is formed from a pair of tapered, conical inflatable tubes in bonded tangential contact with each other. The tubes are further connected together by means of top and bottom reinforcement boards having corresponding longitudinal edges lying in the same central diametral plane passing through the associated tube. The reinforcement boards are made of a stiff reinforcement material, such as Kevlar, collapsible in a direction parallel to the spanwise wing axis upon deflation of the tubes. The stiff reinforcement material cooperates with the inflated tubes to impart structural I-beam characteristics to the composite structure for transferring inflation pressure-induced tensile stress from the tubes to the reinforcement boards. A plurality of rigid hoops shaped to provide airfoil definition are spaced from each other along the spanwise axis and are connected to the top and bottom reinforcement boards. Tension lines are employed for stabilizing the hoops along the trailing and leading edges thereof.

Inflatable nested toroid structure

NASA Technical Reports Server (NTRS)

Johnson, Christopher J. (Inventor); Raboin, Jasen L. (Inventor); Spexarth, Gary R. (Inventor)

2011-01-01

An inflatable structure comprises at least two generally toroidal, inflatable modules. When in a deployed mode, the first, inner module has a major diameter less than that of a second, outer module and is positioned within the inner circumference of the outer module such that the first module is nested circumferentially alongside the second module. The inflatable structure, in a non-deployed, non-inflated mode, is of compact configuration and adapted to be transported to a site of deployment. When deployed, the inflatable structure is of substantially increased interior volume. In one embodiment, access between the interior of the first module and the second module is provided by at least one port or structural pass-through. In another embodiment, the inflatable structure includes at least one additional generally toroidal module external of and circumferentially surrounding the second module.

Attractors, universality, and inflation

NASA Astrophysics Data System (ADS)

Downes, Sean; Dutta, Bhaskar; Sinha, Kuver

2012-11-01

Studies of the initial conditions for inflation have conflicting predictions from exponential suppression to inevitability. At the level of phase space, this conflict arises from the competing intuitions of CPT invariance and thermodynamics. After reviewing this conflict, we enlarge the ensemble beyond phase space to include scalar potential data. We show how this leads to an important contribution from inflection point inflation, enhancing the likelihood of inflation to a power law, 1/Ne3. In the process, we emphasize the attractor dynamics of the gravity-scalar system and the existence of universality classes from inflection point inflation. Finally, we comment on the predictivity of inflation in light of these results.

Prediction of vehicle crashes by drivers' characteristics and past traffic violations in Korea using a zero-inflated negative binomial model.

PubMed

Kim, Dae-Hwan; Ramjan, Lucie M; Mak, Kwok-Kei

2016-01-01

Traffic safety is a significant public health challenge, and vehicle crashes account for the majority of injuries. This study aims to identify whether drivers' characteristics and past traffic violations may predict vehicle crashes in Korea. A total of 500,000 drivers were randomly selected from the 11.6 million driver records of the Ministry of Land, Transport and Maritime Affairs in Korea. Records of traffic crashes were obtained from the archives of the Korea Insurance Development Institute. After matching the past violation history for the period 2004-2005 with the number of crashes in year 2006, a total of 488,139 observations were used for the analysis. Zero-inflated negative binomial model was used to determine the incident risk ratio (IRR) of vehicle crashes by past violations of individual drivers. The included covariates were driver's age, gender, district of residence, vehicle choice, and driving experience. Drivers violating (1) a hit-and-run or drunk driving regulation at least once and (2) a signal, central line, or speed regulation more than once had a higher risk of a vehicle crash with respective IRRs of 1.06 and 1.15. Furthermore, female gender, a younger age, fewer years of driving experience, and middle-sized vehicles were all significantly associated with a higher likelihood of vehicle crashes. Drivers' demographic characteristics and past traffic violations could predict vehicle crashes in Korea. Greater resources should be assigned to the provision of traffic safety education programs for the high-risk driver groups.

Household Implementation of Smoke-Free Rules in Homes and Cars: A Focus on Adolescent Smoking Behavior and Secondhand Smoke Exposure.

PubMed

Parks, Michael J; Kingsbury, John H; Boyle, Raymond G; Evered, Sharrilyn

2018-01-01

This study addresses the dearth of population-based research on how comprehensive household smoke-free rules (ie, in the home and car) relate to tobacco use and secondhand smoke (SHS) exposure among adolescents. Analysis of 2014 Minnesota Youth Tobacco Survey. Representative sample of Minnesota youth. A total of 1287 youth who lived with a smoker. Measures included household smoke-free rules (no rules, partial rules-home or car, but not both-and comprehensive rules), lifetime and 30-day cigarette use, 30-day cigarette and other product use, and SHS exposure in past 7 days in home and car. Weighted multivariate logistic, zero-inflated Poisson, and zero-inflated negative binomial regressions were used. Compared to comprehensive rules, partial and no smoke-free rules were significantly and positively related to lifetime cigarette use (respectively, adjusted odds ratio [AOR] = 1.80, 95% confidence interval [CI] = 1.24-2.61; AOR = 2.87, 95% CI = 1.93-4.25), and a similar significant pattern was found for 30-day cigarette use (respectively, AOR = 2.20, 95% CI = 1.21-4.02; AOR = 2.45, 95% CI = 1.34-4.50). No smoke-free rules significantly predicted using cigarettes and other tobacco products compared to comprehensive rules. In both descriptive and regression analyses, we found SHS exposure rates in both the home and car were significantly lower among youth whose household implemented comprehensive smoke-free rules. Comprehensive smoke-free rules protect youth from the harms of caregiver tobacco use. Relative to both partial and no smoke-free rules, comprehensive smoke-free rules have a marked impact on tobacco use and SHS exposure among youth who live with a smoker. Health promotion efforts should promote comprehensive smoke-free rules among all households and particularly households with children and adolescents.

Impact of multicollinearity on small sample hydrologic regression models

NASA Astrophysics Data System (ADS)

Kroll, Charles N.; Song, Peter

2013-06-01

Often hydrologic regression models are developed with ordinary least squares (OLS) procedures. The use of OLS with highly correlated explanatory variables produces multicollinearity, which creates highly sensitive parameter estimators with inflated variances and improper model selection. It is not clear how to best address multicollinearity in hydrologic regression models. Here a Monte Carlo simulation is developed to compare four techniques to address multicollinearity: OLS, OLS with variance inflation factor screening (VIF), principal component regression (PCR), and partial least squares regression (PLS). The performance of these four techniques was observed for varying sample sizes, correlation coefficients between the explanatory variables, and model error variances consistent with hydrologic regional regression models. The negative effects of multicollinearity are magnified at smaller sample sizes, higher correlations between the variables, and larger model error variances (smaller R2). The Monte Carlo simulation indicates that if the true model is known, multicollinearity is present, and the estimation and statistical testing of regression parameters are of interest, then PCR or PLS should be employed. If the model is unknown, or if the interest is solely on model predictions, is it recommended that OLS be employed since using more complicated techniques did not produce any improvement in model performance. A leave-one-out cross-validation case study was also performed using low-streamflow data sets from the eastern United States. Results indicate that OLS with stepwise selection generally produces models across study regions with varying levels of multicollinearity that are as good as biased regression techniques such as PCR and PLS.

Constructions and classifications of projective Poisson varieties

NASA Astrophysics Data System (ADS)

Pym, Brent

2018-03-01

This paper is intended both as an introduction to the algebraic geometry of holomorphic Poisson brackets, and as a survey of results on the classification of projective Poisson manifolds that have been obtained in the past 20 years. It is based on the lecture series delivered by the author at the Poisson 2016 Summer School in Geneva. The paper begins with a detailed treatment of Poisson surfaces, including adjunction, ruled surfaces and blowups, and leading to a statement of the full birational classification. We then describe several constructions of Poisson threefolds, outlining the classification in the regular case, and the case of rank-one Fano threefolds (such as projective space). Following a brief introduction to the notion of Poisson subspaces, we discuss Bondal's conjecture on the dimensions of degeneracy loci on Poisson Fano manifolds. We close with a discussion of log symplectic manifolds with simple normal crossings degeneracy divisor, including a new proof of the classification in the case of rank-one Fano manifolds.

Constructions and classifications of projective Poisson varieties.

PubMed

Pym, Brent

2018-01-01

This paper is intended both as an introduction to the algebraic geometry of holomorphic Poisson brackets, and as a survey of results on the classification of projective Poisson manifolds that have been obtained in the past 20 years. It is based on the lecture series delivered by the author at the Poisson 2016 Summer School in Geneva. The paper begins with a detailed treatment of Poisson surfaces, including adjunction, ruled surfaces and blowups, and leading to a statement of the full birational classification. We then describe several constructions of Poisson threefolds, outlining the classification in the regular case, and the case of rank-one Fano threefolds (such as projective space). Following a brief introduction to the notion of Poisson subspaces, we discuss Bondal's conjecture on the dimensions of degeneracy loci on Poisson Fano manifolds. We close with a discussion of log symplectic manifolds with simple normal crossings degeneracy divisor, including a new proof of the classification in the case of rank-one Fano manifolds.

Modulus D-term inflation

NASA Astrophysics Data System (ADS)

Kadota, Kenji; Kobayashi, Tatsuo; Saga, Ikumi; Sumita, Keigo

2018-04-01

We propose a new model of single-field D-term inflation in supergravity, where the inflation is driven by a single modulus field which transforms non-linearly under the U(1) gauge symmetry. One of the notable features of our modulus D-term inflation scenario is that the global U(1) remains unbroken in the vacuum and hence our model is not plagued by the cosmic string problem which can exclude most of the conventional D-term inflation models proposed so far due to the CMB observations.

Kähler-driven tribrid inflation

NASA Astrophysics Data System (ADS)

Antusch, Stefan; Nolde, David

2012-11-01

We discuss a new class of tribrid inflation models in supergravity, where the shape of the inflaton potential is dominated by effects from the Kähler potential. Tribrid inflation is a variant of hybrid inflation which is particularly suited for connecting inflation with particle physics, since the inflaton can be a D-flat combination of charged fields from the matter sector. In models of tribrid inflation studied so far, the inflaton potential was dominated by either loop corrections or by mixing effects with the waterfall field (as in "pseudosmooth" tribrid inflation). Here we investigate the third possibility, namely that tribrid inflation is dominantly driven by effects from higher-dimensional operators of the Kähler potential. We specify for which superpotential parameters the new regime is realized and show how it can be experimentally distinguished from the other two (loop-driven and "pseudosmooth") regimes.

Nonlocal Poisson-Fermi model for ionic solvent.

PubMed

Xie, Dexuan; Liu, Jinn-Liang; Eisenberg, Bob

2016-07-01

We propose a nonlocal Poisson-Fermi model for ionic solvent that includes ion size effects and polarization correlations among water molecules in the calculation of electrostatic potential. It includes the previous Poisson-Fermi models as special cases, and its solution is the convolution of a solution of the corresponding nonlocal Poisson dielectric model with a Yukawa-like kernel function. The Fermi distribution is shown to be a set of optimal ionic concentration functions in the sense of minimizing an electrostatic potential free energy. Numerical results are reported to show the difference between a Poisson-Fermi solution and a corresponding Poisson solution.

Climate variations and salmonellosis transmission in Adelaide, South Australia: a comparison between regression models

NASA Astrophysics Data System (ADS)

Zhang, Ying; Bi, Peng; Hiller, Janet

2008-01-01

This is the first study to identify appropriate regression models for the association between climate variation and salmonellosis transmission. A comparison between different regression models was conducted using surveillance data in Adelaide, South Australia. By using notified salmonellosis cases and climatic variables from the Adelaide metropolitan area over the period 1990-2003, four regression methods were examined: standard Poisson regression, autoregressive adjusted Poisson regression, multiple linear regression, and a seasonal autoregressive integrated moving average (SARIMA) model. Notified salmonellosis cases in 2004 were used to test the forecasting ability of the four models. Parameter estimation, goodness-of-fit and forecasting ability of the four regression models were compared. Temperatures occurring 2 weeks prior to cases were positively associated with cases of salmonellosis. Rainfall was also inversely related to the number of cases. The comparison of the goodness-of-fit and forecasting ability suggest that the SARIMA model is better than the other three regression models. Temperature and rainfall may be used as climatic predictors of salmonellosis cases in regions with climatic characteristics similar to those of Adelaide. The SARIMA model could, thus, be adopted to quantify the relationship between climate variations and salmonellosis transmission.

No-scale inflation

NASA Astrophysics Data System (ADS)

Ellis, John; Garcia, Marcos A. G.; Nanopoulos, Dimitri V.; Olive, Keith A.

2016-05-01

Supersymmetry is the most natural framework for physics above the TeV scale, and the corresponding framework for early-Universe cosmology, including inflation, is supergravity. No-scale supergravity emerges from generic string compactifications and yields a non-negative potential, and is therefore a plausible framework for constructing models of inflation. No-scale inflation yields naturally predictions similar to those of the Starobinsky model based on R+{R}2 gravity, with a tilted spectrum of scalar perturbations: {n}s∼ 0.96, and small values of the tensor-to-scalar perturbation ratio r\\lt 0.1, as favoured by Planck and other data on the cosmic microwave background (CMB). Detailed measurements of the CMB may provide insights into the embedding of inflation within string theory as well as its links to collider physics.

Gravitational waves from warm inflation

NASA Astrophysics Data System (ADS)

Li, Xi-Bin; Wang, He; Zhu, Jian-Yang

2018-03-01

A fundamental prediction of inflation is a nearly scale-invariant spectrum of gravitational wave. The features of such a signal provide extremely important information about the physics of the early universe. In this paper, we focus on several topics about warm inflation. First, we discuss the stability property about warm inflation based on nonequilibrium statistical mechanics, which gives more fundamental physical illustrations to thermal property of such model. Then, we calculate the power spectrum of gravitational waves generated during warm inflation, in which there are three components contributing to such spectrum: thermal term, quantum term, and cross term combining the both. We also discuss some interesting properties about these terms and illustrate them in different panels. As a model different from cold inflation, warm inflation model has its individual properties in observational practice, so we finally give a discussion about the observational effect to distinguish it from cold inflation.

STS-45 crewmembers during zero gravity activities onboard KC-135 NASA 930

NASA Image and Video Library

1991-08-21

S91-44453 (21 Aug 1991) --- The crew of STS-45 is already training for its March 1992 mission, including stints on the KC-135 zero-gravity-simulating aircraft. Shown with an inflatable globe are, clockwise from the top, C. Michael Foale, mission specialist; Dirk Frimout, payload specialist; Brian Duffy, pilot; Charles R. (Rick) Chappell, backup payload specialist; Charles F. Bolden, mission commander; Byron K. Lichtenberg, payload specialist; and Kathryn D. Sullivan, payload commander.

Quasi-neutral limit of Euler–Poisson system of compressible fluids coupled to a magnetic field

NASA Astrophysics Data System (ADS)

Yang, Jianwei

2018-06-01

In this paper, we consider the quasi-neutral limit of a three-dimensional Euler-Poisson system of compressible fluids coupled to a magnetic field. We prove that, as Debye length tends to zero, periodic initial-value problems of the model have unique smooth solutions existing in the time interval where the ideal incompressible magnetohydrodynamic equations has smooth solution. Meanwhile, it is proved that smooth solutions converge to solutions of incompressible magnetohydrodynamic equations with a sharp convergence rate in the process of quasi-neutral limit.

Descriptive Analysis on the Impacts of Universal Zero-Markup Drug Policy on a Chinese Urban Tertiary Hospital

PubMed Central

Yang, Dong

2016-01-01

Background Universal Zero-Markup Drug Policy (UZMDP) mandates no price mark-ups on any drug dispensed by a healthcare institution, and covers the medicines not included in the China’s National Essential Medicine System. Five tertiary hospitals in Beijing, China implemented UZMDP in 2012. Its impacts on these hospitals are unknown. We described the effects of UZMDP on a participating hospital, Jishuitan Hospital, Beijing, China (JST). Methods This retrospective longitudinal study examined the hospital-level data of JST and city-level data of tertiary hospitals of Beijing, China (BJT) 2009–2015. Rank-sum tests and join-point regression analyses were used to assess absolute changes and differences in trends, respectively. Results In absolute terms, after the UZDMP implementation, there were increased annual patient-visits and decreased ratios of medicine-to-healthcare-charges (RMOH) in JST outpatient and inpatient services; however, in outpatient service, physician work-days decreased and physician-workload and inflation-adjusted per-visit healthcare charges increased, while the inpatient physician work-days increased and inpatient mortality-rate reduced. Interestingly, the decreasing trend in inpatient mortality-rate was neutralized after UZDMP implementation. Compared with BJT and under influence of UZDMP, JST outpatient and inpatient services both had increasing trends in annual patient-visits (annual percentage changes[APC] = 8.1% and 6.5%, respectively) and decreasing trends in RMOH (APC = -4.3% and -5.4%, respectively), while JST outpatient services had increasing trend in inflation-adjusted per-visit healthcare charges (APC = 3.4%) and JST inpatient service had decreasing trend in inflation-adjusted per-visit medicine-charges (APC = -5.2%). Conclusion Implementation of UZMDP seems to increase annual patient-visits, reduce RMOH and have different impacts on outpatient and inpatient services in a Chinese urban tertiary hospital. PMID:27627811

Descriptive Analysis on the Impacts of Universal Zero-Markup Drug Policy on a Chinese Urban Tertiary Hospital.

PubMed

Tian, Wei; Yuan, Jiangfan; Yang, Dong; Zhang, Lanjing

2016-01-01

Universal Zero-Markup Drug Policy (UZMDP) mandates no price mark-ups on any drug dispensed by a healthcare institution, and covers the medicines not included in the China's National Essential Medicine System. Five tertiary hospitals in Beijing, China implemented UZMDP in 2012. Its impacts on these hospitals are unknown. We described the effects of UZMDP on a participating hospital, Jishuitan Hospital, Beijing, China (JST). This retrospective longitudinal study examined the hospital-level data of JST and city-level data of tertiary hospitals of Beijing, China (BJT) 2009-2015. Rank-sum tests and join-point regression analyses were used to assess absolute changes and differences in trends, respectively. In absolute terms, after the UZDMP implementation, there were increased annual patient-visits and decreased ratios of medicine-to-healthcare-charges (RMOH) in JST outpatient and inpatient services; however, in outpatient service, physician work-days decreased and physician-workload and inflation-adjusted per-visit healthcare charges increased, while the inpatient physician work-days increased and inpatient mortality-rate reduced. Interestingly, the decreasing trend in inpatient mortality-rate was neutralized after UZDMP implementation. Compared with BJT and under influence of UZDMP, JST outpatient and inpatient services both had increasing trends in annual patient-visits (annual percentage changes[APC] = 8.1% and 6.5%, respectively) and decreasing trends in RMOH (APC = -4.3% and -5.4%, respectively), while JST outpatient services had increasing trend in inflation-adjusted per-visit healthcare charges (APC = 3.4%) and JST inpatient service had decreasing trend in inflation-adjusted per-visit medicine-charges (APC = -5.2%). Implementation of UZMDP seems to increase annual patient-visits, reduce RMOH and have different impacts on outpatient and inpatient services in a Chinese urban tertiary hospital.

A Linear Regression Model Identifying the Primary Factors Contributing to Maintenance Man Hours for the C-17 Globemaster III in the Air National Guard

DTIC Science & Technology

2012-06-15

Maintenance AFSCs ................................................................................................. 14 2. Variation Inflation Factors...total variability in the data. It is an indication of how much of the   20    variation in the data can be accounted for in the regression model. In... Variation Inflation Factors for each independent variable (predictor) as regressed against all of the other independent variables in the model. The

Family size and old-age wellbeing: effects of the fertility transition in Mexico

PubMed Central

DÍAZ-VENEGAS, CARLOS; SÁENZ, JOSEPH L.; WONG, REBECA

2016-01-01

The present study aims to determine how family size affects psycho-social, economic and health wellbeing in old age differently across two cohorts with declining fertility. The data are from the 2012 Mexican Health and Ageing Study (MHAS) including respondents aged 50+ (N = 13,102). Poisson (standard and zero-inflated) and logistic regressions are used to model determinants of wellbeing in old age: psycho-social (depressive symptoms), economic (consumer durables and insurance) and health (chronic conditions). In the younger cohort, having fewer children is associated with fewer depressive symptoms and chronic conditions, and better economic well-being. For the older cohort, having fewer children is associated with lower economic wellbeing and higher odds of being uninsured. Lower fertility benefited the younger cohort (born after 1937), whereas the older cohort (born in 1937 or earlier) benefited from lower fertility only in chronic conditions. Further research is needed to continue exploring the old-age effects of the fertility transition. PMID:28239210

Health care usage among immigrants and native-born elderly populations in eleven European countries: results from SHARE

PubMed Central

Guillén, Montserrat; Crimmins, Eileen M.

2013-01-01

Differences in health care utilization of immigrants 50 years of age and older relative to the native-born populations in eleven European countries are investigated. Negative binomial and zero-inflated Poisson regression are used to examine differences between immigrants and native-borns in number of doctor visits, visits to general practitioners, and hospital stays using the 2004 Survey of Health, Ageing, and Retirement in Europe database. In the pooled European sample and in some individual countries, older immigrants use from 13 to 20% more health services than native-borns after demographic characteristics are controlled. After controlling for the need for health care, differences between immigrants and native-borns in the use of physicians, but not hospitals, are reduced by about half. These are not changed much with the incorporation of indicators of socioeconomic status and extra insurance coverage. Higher country-level relative expenditures on health, paying physicians a fee-for-service, and physician density are associated with higher usage of physician services among immigrants. PMID:21660564

Examining psychosocial and physical hazards in the Ghanaian mining industry and their implications for employees' safety experience.

PubMed

Amponsah-Tawiah, Kwesi; Jain, Aditya; Leka, Stavroula; Hollis, David; Cox, Tom

2013-06-01

In addition to hazardous conditions that are prevalent in mines, there are various physical and psychosocial risk factors that can affect mine workers' safety and health. Without due diligence to mine safety, these risk factors can affect workers' safety experience, in terms of near misses, disabling injuries and accidents experienced or witnessed by workers. This study sets out to examine the effects of physical and psychosocial risk factors on workers' safety experience in a sample of Ghanaian miners. 307 participants from five mining companies responded to a cross sectional survey examining physical and psychosocial hazards and their implications for employees' safety experience. Zero-inflated Poisson regression models indicated that mining conditions, equipment, ambient conditions, support and security, and work demands and control are significant predictors of near misses, disabling injuries, and accidents experienced or witnessed by workers. The type of mine had important implications for workers' safety experience. Copyright © 2013 Elsevier Ltd and National Safety Council. All rights reserved.

Can a supersonically expanding Bose-Einstein Condensates be used to study cosmological inflation?

NASA Astrophysics Data System (ADS)

Banik, Swarnav; Eckel, Stephen; Kumar, Avinash; Jacobson, Ted; Spielman, Ian; Campbell, Gretchen

2017-04-01

The massive scale of the universe makes the experimental study of cosmological inflation difficult. This has led to an interest in developing analogous systems using table top experiments. Here, we present the basic features of an expanding universe by drawing parallels with an expanding toroidal Bose Einstein Condensate (BEC) of 23Na atoms. The toroidal BEC serves as the background vacuum and phonons are the analogue to photons in the expanding universe. We study the dynamics of phonons in both non-expanding and expanding condensates and measure dissipation using the structure factor. We demonstrate red shifting of phonons and quasi-particle production similar to pre-heating after the inflation of universe. At the end of expansion, we also observe spontaneous non-zero winding numbers in the ring. Using Monte-Carlo simulations, we predict the widths of the resulting winding number distribution, which agree well with our experimental findings.

Alchemical inflation: inflaton turns into Higgs

NASA Astrophysics Data System (ADS)

Nakayama, Kazunori; Takahashi, Fuminobu

2012-11-01

We propose a new inflation model in which a gauge singlet inflaton turns into the Higgs condensate after inflation. The inflationary path is characterized by a moduli space of supersymmetric vacua spanned by the inflaton and Higgs field. The inflation energy scale is related to the soft supersymmetry breaking, and the Hubble parameter during inflation is smaller than the gravitino mass. The initial condition for the successful inflation is naturally realized by the pre-inflation in which the Higgs plays a role of the waterfall field.

Multilevel poisson regression modelling for determining factors of dengue fever cases in bandung

NASA Astrophysics Data System (ADS)

Arundina, Davila Rubianti; Tantular, Bertho; Pontoh, Resa Septiani

2017-03-01

Scralatina or Dengue Fever is a kind of fever caused by serotype virus which Flavivirus genus and be known as Dengue Virus. Dengue Fever caused by Aedes Aegipty Mosquito bites who infected by a dengue virus. The study was conducted in 151 villages in Bandung. Health Analysts believes that there are two factors that affect the dengue cases, Internal factor (individual) and external factor (environment). The data who used in this research is hierarchical data. The method is used for hierarchical data modelling is multilevel method. Which is, the level 1 is village and level 2 is sub-district. According exploration data analysis, the suitable Multilevel Method is Random Intercept Model. Penalized Quasi Likelihood (PQL) approach on multilevel Poisson is a proper analysis to determine factors that affecting dengue cases in the city of Bandung. Clean and Healthy Behavior factor from the village level have an effect on the number of cases of dengue fever in the city of Bandung. Factor from the sub-district level has no effect.

Comparison of robustness to outliers between robust poisson models and log-binomial models when estimating relative risks for common binary outcomes: a simulation study.

PubMed

Chen, Wansu; Shi, Jiaxiao; Qian, Lei; Azen, Stanley P

2014-06-26

To estimate relative risks or risk ratios for common binary outcomes, the most popular model-based methods are the robust (also known as modified) Poisson and the log-binomial regression. Of the two methods, it is believed that the log-binomial regression yields more efficient estimators because it is maximum likelihood based, while the robust Poisson model may be less affected by outliers. Evidence to support the robustness of robust Poisson models in comparison with log-binomial models is very limited. In this study a simulation was conducted to evaluate the performance of the two methods in several scenarios where outliers existed. The findings indicate that for data coming from a population where the relationship between the outcome and the covariate was in a simple form (e.g. log-linear), the two models yielded comparable biases and mean square errors. However, if the true relationship contained a higher order term, the robust Poisson models consistently outperformed the log-binomial models even when the level of contamination is low. The robust Poisson models are more robust (or less sensitive) to outliers compared to the log-binomial models when estimating relative risks or risk ratios for common binary outcomes. Users should be aware of the limitations when choosing appropriate models to estimate relative risks or risk ratios.

Sharp predictions from eternal inflation patches in D-brane inflation

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

Hertog, Thomas; Janssen, Oliver, E-mail: thomas.hertog@fys.kuleuven.be, E-mail: opj202@nyu.edu

We numerically generate the six-dimensional landscape of D3-brane inflation and identify patches of eternal inflation near sufficiently flat inflection points of the potential. We show that reasonable measures that select patches of eternal inflation in the landscape yield sharp predictions for the spectral properties of primordial perturbations on observable scales. These include a scalar tilt of .936, a running of the scalar tilt −.00103, undetectably small tensors and non-Gaussianity, and no observable spatial curvature. Our results explicitly demonstrate that precision cosmology probes the combination of the statistical properties of the string landscape and the measure implied by the universe's quantummore » state.« less

Modeling zero-modified count and semicontinuous data in health services research part 2: case studies.

PubMed

Neelon, Brian; O'Malley, A James; Smith, Valerie A

2016-11-30

This article is the second installment of a two-part tutorial on the analysis of zero-modified count and semicontinuous data. Part 1, which appears as a companion piece in this issue of Statistics in Medicine, provides a general background and overview of the topic, with particular emphasis on applications to health services research. Here, we present three case studies highlighting various approaches for the analysis of zero-modified data. The first case study describes methods for analyzing zero-inflated longitudinal count data. Case study 2 considers the use of hurdle models for the analysis of spatiotemporal count data. The third case study discusses an application of marginalized two-part models to the analysis of semicontinuous health expenditure data. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Two-Part and Related Regression Models for Longitudinal Data

PubMed Central

Farewell, V.T.; Long, D.L.; Tom, B.D.M.; Yiu, S.; Su, L.

2017-01-01

Statistical models that involve a two-part mixture distribution are applicable in a variety of situations. Frequently, the two parts are a model for the binary response variable and a model for the outcome variable that is conditioned on the binary response. Two common examples are zero-inflated or hurdle models for count data and two-part models for semicontinuous data. Recently, there has been particular interest in the use of these models for the analysis of repeated measures of an outcome variable over time. The aim of this review is to consider motivations for the use of such models in this context and to highlight the central issues that arise with their use. We examine two-part models for semicontinuous and zero-heavy count data, and we also consider models for count data with a two-part random effects distribution. PMID:28890906

On the fractal characterization of Paretian Poisson processes

NASA Astrophysics Data System (ADS)

Eliazar, Iddo I.; Sokolov, Igor M.

2012-06-01

Paretian Poisson processes are Poisson processes which are defined on the positive half-line, have maximal points, and are quantified by power-law intensities. Paretian Poisson processes are elemental in statistical physics, and are the bedrock of a host of power-law statistics ranging from Pareto's law to anomalous diffusion. In this paper we establish evenness-based fractal characterizations of Paretian Poisson processes. Considering an array of socioeconomic evenness-based measures of statistical heterogeneity, we show that: amongst the realm of Poisson processes which are defined on the positive half-line, and have maximal points, Paretian Poisson processes are the unique class of 'fractal processes' exhibiting scale-invariance. The results established in this paper are diametric to previous results asserting that the scale-invariance of Poisson processes-with respect to physical randomness-based measures of statistical heterogeneity-is characterized by exponential Poissonian intensities.

Topological inflation with graceful exit

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

Marunović, Anja; Prokopec, Tomislav, E-mail: a.marunovic@uu.nl, E-mail: t.prokopec@uu.nl

We investigate a class of models of topological inflation in which a super-Hubble-sized global monopole seeds inflation. These models are attractive since inflation starts from rather generic initial conditions, but their not so attractive feature is that, unless symmetry is again restored, inflation never ends. In this work we show that, in presence of another nonminimally coupled scalar field, that is both quadratically and quartically coupled to the Ricci scalar, inflation naturally ends, representing an elegant solution to the graceful exit problem of topological inflation. While the monopole core grows during inflation, the growth stops after inflation, such that themore » monopole eventually enters the Hubble radius, and shrinks to its Minkowski space size, rendering it immaterial for the subsequent Universe's dynamics. Furthermore, we find that our model can produce cosmological perturbations that source CMB temperature fluctuations and seed large scale structure statistically consistent (within one standard deviation) with all available data. In particular, for small and (in our convention) negative nonminimal couplings, the scalar spectral index can be as large as n {sub s} ≅ 0.955, which is about one standard deviation lower than the central value quoted by the most recent Planck Collaboration.« less

Phenomenology of fermion production during axion inflation

NASA Astrophysics Data System (ADS)

Adshead, Peter; Pearce, Lauren; Peloso, Marco; Roberts, Michael A.; Sorbo, Lorenzo

2018-06-01

We study the production of fermions through a derivative coupling with a pseudoscalar inflaton and the effects of the produced fermions on the scalar primordial perturbations. We present analytic results for the modification of the scalar power spectrum due to the produced fermions, and we estimate the amplitude of the non-Gaussianities in the equilateral regime. Remarkably, we find a regime where the effect of the fermions gives the dominant contribution to the scalar spectrum while the amplitude of the bispectrum is small and in agreement with observation. We also note the existence of a regime in which the backreaction of the fermions on the evolution of the zero-mode of the inflaton can lead to inflation even if the potential of the inflaton is steep and does not satisfy the slow-roll conditions.

Observing the inflation potential. [in models of cosmological inflation

NASA Technical Reports Server (NTRS)

Copeland, Edmund J.; Kolb, Edward W.; Liddle, Andrew R.; Lidsey, James E.

1993-01-01

We show how observations of the density perturbation (scalar) spectrum and the gravitational wave (tensor) spectrum allow a reconstruction of the potential responsible for cosmological inflation. A complete functional reconstruction or a perturbative approximation about a single scale are possible; the suitability of each approach depends on the data available. Consistency equations between the scalar and tensor spectra are derived, which provide a powerful signal of inflation.

NEWTPOIS- NEWTON POISSON DISTRIBUTION PROGRAM

NASA Technical Reports Server (NTRS)

Bowerman, P. N.

1994-01-01

The cumulative poisson distribution program, NEWTPOIS, is one of two programs which make calculations involving cumulative poisson distributions. Both programs, NEWTPOIS (NPO-17715) and CUMPOIS (NPO-17714), can be used independently of one another. NEWTPOIS determines percentiles for gamma distributions with integer shape parameters and calculates percentiles for chi-square distributions with even degrees of freedom. It can be used by statisticians and others concerned with probabilities of independent events occurring over specific units of time, area, or volume. NEWTPOIS determines the Poisson parameter (lambda), that is; the mean (or expected) number of events occurring in a given unit of time, area, or space. Given that the user already knows the cumulative probability for a specific number of occurrences (n) it is usually a simple matter of substitution into the Poisson distribution summation to arrive at lambda. However, direct calculation of the Poisson parameter becomes difficult for small positive values of n and unmanageable for large values. NEWTPOIS uses Newton's iteration method to extract lambda from the initial value condition of the Poisson distribution where n=0, taking successive estimations until some user specified error term (epsilon) is reached. The NEWTPOIS program is written in C. It was developed on an IBM AT with a numeric co-processor using Microsoft C 5.0. Because the source code is written using standard C structures and functions, it should compile correctly on most C compilers. The program format is interactive, accepting epsilon, n, and the cumulative probability of the occurrence of n as inputs. It has been implemented under DOS 3.2 and has a memory requirement of 30K. NEWTPOIS was developed in 1988.

Censored Hurdle Negative Binomial Regression (Case Study: Neonatorum Tetanus Case in Indonesia)

NASA Astrophysics Data System (ADS)

Yuli Rusdiana, Riza; Zain, Ismaini; Wulan Purnami, Santi

2017-06-01

Hurdle negative binomial model regression is a method that can be used for discreate dependent variable, excess zero and under- and overdispersion. It uses two parts approach. The first part estimates zero elements from dependent variable is zero hurdle model and the second part estimates not zero elements (non-negative integer) from dependent variable is called truncated negative binomial models. The discrete dependent variable in such cases is censored for some values. The type of censor that will be studied in this research is right censored. This study aims to obtain the parameter estimator hurdle negative binomial regression for right censored dependent variable. In the assessment of parameter estimation methods used Maximum Likelihood Estimator (MLE). Hurdle negative binomial model regression for right censored dependent variable is applied on the number of neonatorum tetanus cases in Indonesia. The type data is count data which contains zero values in some observations and other variety value. This study also aims to obtain the parameter estimator and test statistic censored hurdle negative binomial model. Based on the regression results, the factors that influence neonatorum tetanus case in Indonesia is the percentage of baby health care coverage and neonatal visits.

Algorithm Calculates Cumulative Poisson Distribution

NASA Technical Reports Server (NTRS)

Bowerman, Paul N.; Nolty, Robert C.; Scheuer, Ernest M.

1992-01-01

Algorithm calculates accurate values of cumulative Poisson distribution under conditions where other algorithms fail because numbers are so small (underflow) or so large (overflow) that computer cannot process them. Factors inserted temporarily to prevent underflow and overflow. Implemented in CUMPOIS computer program described in "Cumulative Poisson Distribution Program" (NPO-17714).

Bayesian Poisson hierarchical models for crash data analysis: Investigating the impact of model choice on site-specific predictions.

PubMed

Khazraee, S Hadi; Johnson, Valen; Lord, Dominique

2018-08-01

The Poisson-gamma (PG) and Poisson-lognormal (PLN) regression models are among the most popular means for motor vehicle crash data analysis. Both models belong to the Poisson-hierarchical family of models. While numerous studies have compared the overall performance of alternative Bayesian Poisson-hierarchical models, little research has addressed the impact of model choice on the expected crash frequency prediction at individual sites. This paper sought to examine whether there are any trends among candidate models predictions e.g., that an alternative model's prediction for sites with certain conditions tends to be higher (or lower) than that from another model. In addition to the PG and PLN models, this research formulated a new member of the Poisson-hierarchical family of models: the Poisson-inverse gamma (PIGam). Three field datasets (from Texas, Michigan and Indiana) covering a wide range of over-dispersion characteristics were selected for analysis. This study demonstrated that the model choice can be critical when the calibrated models are used for prediction at new sites, especially when the data are highly over-dispersed. For all three datasets, the PIGam model would predict higher expected crash frequencies than would the PLN and PG models, in order, indicating a clear link between the models predictions and the shape of their mixing distributions (i.e., gamma, lognormal, and inverse gamma, respectively). The thicker tail of the PIGam and PLN models (in order) may provide an advantage when the data are highly over-dispersed. The analysis results also illustrated a major deficiency of the Deviance Information Criterion (DIC) in comparing the goodness-of-fit of hierarchical models; models with drastically different set of coefficients (and thus predictions for new sites) may yield similar DIC values, because the DIC only accounts for the parameters in the lowest (observation) level of the hierarchy and ignores the higher levels (regression coefficients

Modeling zero-modified count and semicontinuous data in health services research Part 1: background and overview.

PubMed

Neelon, Brian; O'Malley, A James; Smith, Valerie A

2016-11-30

Health services data often contain a high proportion of zeros. In studies examining patient hospitalization rates, for instance, many patients will have no hospitalizations, resulting in a count of zero. When the number of zeros is greater or less than expected under a standard count model, the data are said to be zero modified relative to the standard model. A similar phenomenon arises with semicontinuous data, which are characterized by a spike at zero followed by a continuous distribution with positive support. When analyzing zero-modified count and semicontinuous data, flexible mixture distributions are often needed to accommodate both the excess zeros and the typically skewed distribution of nonzero values. Various models have been introduced over the past three decades to accommodate such data, including hurdle models, zero-inflated models, and two-part semicontinuous models. This tutorial describes recent modeling strategies for zero-modified count and semicontinuous data and highlights their role in health services research studies. Part 1 of the tutorial, presented here, provides a general overview of the topic. Part 2, appearing as a companion piece in this issue of Statistics in Medicine, discusses three case studies illustrating applications of the methods to health services research. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Topological defects in extended inflation

NASA Technical Reports Server (NTRS)

Copeland, Edmund J.; Kolb, Edward W.; Liddle, Andrew R.

1990-01-01

The production of topological defects, especially cosmic strings, in extended inflation models was considered. In extended inflation, the Universe passes through a first-order phase transition via bubble percolation, which naturally allows defects to form at the end of inflation. The correlation length, which determines the number density of the defects, is related to the mean size of bubbles when they collide. This mechanism allows a natural combination of inflation and large scale structure via cosmic strings.

Tribrid Inflation in Supergravity

NASA Astrophysics Data System (ADS)

Antusch, Stefan; Dutta, Koushik; Kostka, Philipp M.

We propose a novel class of F-term hybrid inflation models in supergravity (SUGRA) where the η-problem is resolved using either a Heisenberg symmetry or a shift symmetry of the Kähler potential. In addition to the inflaton and the waterfall field, this class (referred to as tribrid inflation) contains a third "driving" field which contributes the large vacuum energy during inflation by its F-term. In contrast to the "standard" hybrid scenario, it has several attractive features due to the property of vanishing inflationary superpotential (Winf = 0) during inflation. Quantum corrections induced by symmetry breaking terms in the superpotential generate a slope of the potential and lead to a spectral tilt consistent with recent WMAP observations.

Stochastic effects in hybrid inflation

NASA Astrophysics Data System (ADS)

Martin, Jérôme; Vennin, Vincent

2012-02-01

Hybrid inflation is a two-field model where inflation ends due to an instability. In the neighborhood of the instability point, the potential is very flat and the quantum fluctuations dominate over the classical motion of the inflaton and waterfall fields. In this article, we study this regime in the framework of stochastic inflation. We numerically solve the two coupled Langevin equations controlling the evolution of the fields and compute the probability distributions of the total number of e-folds and of the inflation exit point. Then, we discuss the physical consequences of our results, in particular, the question of how the quantum diffusion can affect the observable predictions of hybrid inflation.

Calculation of the Poisson cumulative distribution function

NASA Technical Reports Server (NTRS)

Bowerman, Paul N.; Nolty, Robert G.; Scheuer, Ernest M.

1990-01-01

A method for calculating the Poisson cdf (cumulative distribution function) is presented. The method avoids computer underflow and overflow during the process. The computer program uses this technique to calculate the Poisson cdf for arbitrary inputs. An algorithm that determines the Poisson parameter required to yield a specified value of the cdf is presented.

Graphic Simulations of the Poisson Process.

DTIC Science & Technology

1982-10-01

RANDOM NUMBERS AND TRANSFORMATIONS..o......... 11 Go THE RANDOM NUMBERGENERATOR....... .oo..... 15 III. POISSON PROCESSES USER GUIDE....oo.ooo ......... o...again. In the superimposed mode, two Poisson processes are active, each with a different rate parameter, (call them Type I and Type II with respective...occur. The value ’p’ is generated by the following equation where ’Li’ and ’L2’ are the rates of the two Poisson processes ; p = Li / (Li + L2) The value

Inflatable robotics for planetary applications

NASA Technical Reports Server (NTRS)

Jones, Jack A.

2001-01-01

Space Inflatable vehicles have been finding popularity in recent years for applications as varied as spacecraft antennas, space-based telescopes, solar sails, and manned habitats [1]. Another branch of space inflatable technology has also considered developing ambient gasfilled, solar balloons for Mars as well as ambient gasfilled inflatable rovers [2]. More recently, some other intriguing space-inflatable vehicles have been proposed for the gas planets and Pluto, as well as for Saturn's moon, Titan, Neptune's moon, Triton, and Jupiter's moon, Io [3].

Poisson Spot with Magnetic Levitation

ERIC Educational Resources Information Center

Hoover, Matthew; Everhart, Michael; D'Arruda, Jose

2010-01-01

In this paper we describe a unique method for obtaining the famous Poisson spot without adding obstacles to the light path, which could interfere with the effect. A Poisson spot is the interference effect from parallel rays of light diffracting around a solid spherical object, creating a bright spot in the center of the shadow.

Degravitation, inflation and the cosmological constant as an afterglow

NASA Astrophysics Data System (ADS)

Patil, Subodh P.

2009-01-01

In this report, we adopt the phenomenological approach of taking the degravitation paradigm seriously as a consistent modification of gravity in the IR, and investigate its consequences for various cosmological situations. We motivate degravitation — where Netwon's constant is promoted to a scale dependent filter function — as arising from either a small (resonant) mass for the graviton, or as an effect in semi-classical gravity. After addressing how the Bianchi identities are to be satisfied in such a set up, we turn our attention towards the cosmological consequences of degravitation. By considering the example filter function corresponding to a resonantly massive graviton (with a filter scale larger than the present horizon scale), we show that slow roll inflation, hybrid inflation and old inflation remain quantitatively unchanged. We also find that the degravitation mechanism inherits a memory of past energy densities in the present epoch in such a way that is likely significant for present cosmological evolution. For example, if the universe underwent inflation in the past due to it having tunneled out of some false vacuum, we find that degravitation implies a remnant `afterglow' cosmological constant, whose scale immediately afterwards is parametrically suppressed by the filter scale (L) in Planck units Λ ~ l2pl/L2. We discuss circumstances through which this scenario reasonably yields the presently observed value for Λ ~ O(10-120). We also find that in a universe still currently trapped in some false vacuum state, resonance graviton models of degravitation only degravitate initially Planck or GUT scale energy densities down to the presently observed value over timescales comparable to the filter scale. We argue that different functional forms for the filter function will yield similar conclusions. In this way, we argue that although the degravitation models we study have the potential to explain why the cosmological constant is not large in addition to

Map scale effects on estimating the number of undiscovered mineral deposits

USGS Publications Warehouse

Singer, D.A.; Menzie, W.D.

2008-01-01

Estimates of numbers of undiscovered mineral deposits, fundamental to assessing mineral resources, are affected by map scale. Where consistently defined deposits of a particular type are estimated, spatial and frequency distributions of deposits are linked in that some frequency distributions can be generated by processes randomly in space whereas others are generated by processes suggesting clustering in space. Possible spatial distributions of mineral deposits and their related frequency distributions are affected by map scale and associated inclusions of non-permissive or covered geological settings. More generalized map scales are more likely to cause inclusion of geologic settings that are not really permissive for the deposit type, or that include unreported cover over permissive areas, resulting in the appearance of deposit clustering. Thus, overly generalized map scales can cause deposits to appear clustered. We propose a model that captures the effects of map scale and the related inclusion of non-permissive geologic settings on numbers of deposits estimates, the zero-inflated Poisson distribution. Effects of map scale as represented by the zero-inflated Poisson distribution suggest that the appearance of deposit clustering should diminish as mapping becomes more detailed because the number of inflated zeros would decrease with more detailed maps. Based on observed worldwide relationships between map scale and areas permissive for deposit types, mapping at a scale with twice the detail should cut permissive area size of a porphyry copper tract to 29% and a volcanic-hosted massive sulfide tract to 50% of their original sizes. Thus some direct benefits of mapping an area at a more detailed scale are indicated by significant reductions in areas permissive for deposit types, increased deposit density and, as a consequence, reduced uncertainty in the estimate of number of undiscovered deposits. Exploration enterprises benefit from reduced areas requiring

Log-normal frailty models fitted as Poisson generalized linear mixed models.

PubMed

Hirsch, Katharina; Wienke, Andreas; Kuss, Oliver

2016-12-01

The equivalence of a survival model with a piecewise constant baseline hazard function and a Poisson regression model has been known since decades. As shown in recent studies, this equivalence carries over to clustered survival data: A frailty model with a log-normal frailty term can be interpreted and estimated as a generalized linear mixed model with a binary response, a Poisson likelihood, and a specific offset. Proceeding this way, statistical theory and software for generalized linear mixed models are readily available for fitting frailty models. This gain in flexibility comes at the small price of (1) having to fix the number of pieces for the baseline hazard in advance and (2) having to "explode" the data set by the number of pieces. In this paper we extend the simulations of former studies by using a more realistic baseline hazard (Gompertz) and by comparing the model under consideration with competing models. Furthermore, the SAS macro %PCFrailty is introduced to apply the Poisson generalized linear mixed approach to frailty models. The simulations show good results for the shared frailty model. Our new %PCFrailty macro provides proper estimates, especially in case of 4 events per piece. The suggested Poisson generalized linear mixed approach for log-normal frailty models based on the %PCFrailty macro provides several advantages in the analysis of clustered survival data with respect to more flexible modelling of fixed and random effects, exact (in the sense of non-approximate) maximum likelihood estimation, and standard errors and different types of confidence intervals for all variance parameters. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Newton/Poisson-Distribution Program

NASA Technical Reports Server (NTRS)

Bowerman, Paul N.; Scheuer, Ernest M.

1990-01-01

NEWTPOIS, one of two computer programs making calculations involving cumulative Poisson distributions. NEWTPOIS (NPO-17715) and CUMPOIS (NPO-17714) used independently of one another. NEWTPOIS determines Poisson parameter for given cumulative probability, from which one obtains percentiles for gamma distributions with integer shape parameters and percentiles for X(sup2) distributions with even degrees of freedom. Used by statisticians and others concerned with probabilities of independent events occurring over specific units of time, area, or volume. Program written in C.

Introduction to the use of regression models in epidemiology.

PubMed

Bender, Ralf

2009-01-01

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

12 CFR 19.240 - Inflation adjustments.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 1 2010-01-01 2010-01-01 false Inflation adjustments. 19.240 Section 19.240... PROCEDURE Civil Money Penalty Inflation Adjustments § 19.240 Inflation adjustments. (a) The maximum amount... Civil Penalties Inflation Adjustment Act of 1990 (28 U.S.C. 2461 note) as follows: ER10NO08.001 (b) The...

Aerocapture Inflatable Decelerator (AID)

NASA Technical Reports Server (NTRS)

Reza, Sajjad

2007-01-01

Forward Attached Inflatable Decelerators, more commonly known as inflatable aeroshells, provide an effective, cost efficient means of decelerating spacecrafts by using atmospheric drag for aerocapture or planetary entry instead of conventional liquid propulsion deceleration systems. Entry into planetary atmospheres results in significant heating and aerodynamic pressures which stress aeroshell systems to their useful limits. Incorporation of lightweight inflatable decelerator surfaces with increased surface-area footprints provides the opportunity to reduce heat flux and induced temperatures, while increasing the payload mass fraction. Furthermore, inflatable aeroshell decelerators provide the needed deceleration at considerably higher altitudes and Mach numbers when compared with conventional rigid aeroshell entry systems. Inflatable aeroshells also provide for stowage in a compact space, with subsequent deployment of a large-area, lightweight heatshield to survive entry heating. Use of a deployable heatshield decelerator not only enables an increase in the spacecraft payload mass fraction and but may also eliminate the need for a spacecraft backshell and cruise stage. This document is the viewgraph slides for the paper's presentation.

Mutated hilltop inflation revisited

NASA Astrophysics Data System (ADS)

Pal, Barun Kumar

2018-05-01

In this work we re-investigate pros and cons of mutated hilltop inflation. Applying Hamilton-Jacobi formalism we solve inflationary dynamics and find that inflation goes on along the {W}_{-1} branch of the Lambert function. Depending on the model parameter mutated hilltop model renders two types of inflationary solutions: one corresponds to small inflaton excursion during observable inflation and the other describes large field inflation. The inflationary observables from curvature perturbation are in tune with the current data for a wide range of the model parameter. The small field branch predicts negligible amount of tensor to scalar ratio r˜ O(10^{-4}), while the large field sector is capable of generating high amplitude for tensor perturbations, r˜ O(10^{-1}). Also, the spectral index is almost independent of the model parameter along with a very small negative amount of scalar running. Finally we find that the mutated hilltop inflation closely resembles the α -attractor class of inflationary models in the limit of α φ ≫ 1.

A Martingale Characterization of Mixed Poisson Processes.

DTIC Science & Technology

1985-10-01

03LA A 11. TITLE (Inciuae Security Clanafication, ",A martingale characterization of mixed Poisson processes " ________________ 12. PERSONAL AUTHOR... POISSON PROCESSES Jostification .......... . ... . . Di.;t ib,,jtion by Availability Codes Dietmar Pfeifer* Technical University Aachen Dist Special and...Mixed Poisson processes play an important role in many branches of applied probability, for instance in insurance mathematics and physics (see Albrecht

General methodology for nonlinear modeling of neural systems with Poisson point-process inputs.

PubMed

Marmarelis, V Z; Berger, T W

2005-07-01

This paper presents a general methodological framework for the practical modeling of neural systems with point-process inputs (sequences of action potentials or, more broadly, identical events) based on the Volterra and Wiener theories of functional expansions and system identification. The paper clarifies the distinctions between Volterra and Wiener kernels obtained from Poisson point-process inputs. It shows that only the Wiener kernels can be estimated via cross-correlation, but must be defined as zero along the diagonals. The Volterra kernels can be estimated far more accurately (and from shorter data-records) by use of the Laguerre expansion technique adapted to point-process inputs, and they are independent of the mean rate of stimulation (unlike their P-W counterparts that depend on it). The Volterra kernels can also be estimated for broadband point-process inputs that are not Poisson. Useful applications of this modeling approach include cases where we seek to determine (model) the transfer characteristics between one neuronal axon (a point-process 'input') and another axon (a point-process 'output') or some other measure of neuronal activity (a continuous 'output', such as population activity) with which a causal link exists.

Dark zone in the centre of the Arago-Poisson diffraction spot of a helical laser beam

NASA Astrophysics Data System (ADS)

Emile, O.; Voisin, A.; Niemiec, R.; Viaris de Lesegno, B.; Pruvost, L.; Ropars, G.; Emile, J.; Brousseau, C.

2013-03-01

We report on the diffraction of non-zero Laguerre Gaussian laser beams by an opaque disk. We observe a tiny circular dark zone at the centre of the usual Arago-Poisson diffraction bright spot. For such non-diffracting dark hollow beams, we have measured diameters as small as 20 μm on distances of the order of ten metres, without focalization. Diameters depend on the diffracting object size and on the topological charge of the input Laguerre Gaussian beam. These results are in good agreement with theoretical considerations. Potential applications are then discussed.

No-scale ripple inflation revisited

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

Li, Tianjun; Li, Zhijin; Nanopoulos, Dimitri V., E-mail: tli@itp.ac.cn, E-mail: lizhijin@physics.tamu.edu, E-mail: dimitri@physics.tamu.edu

We revisit the no-scale ripple inflation model, where no-scale supergravity is modified by an additional term for the inflaton field in the Kähler potential. This term not only breaks one SU(N,1) symmetry explicitly, but also plays an important role for inflation. We generalize the superpotential in the no-scale ripple inflation model slightly. There exists a discrete Z{sub 2} symmetry/parity in the scalar potential in general, which can be preserved or violated by the non-canonical nomalized inflaton kinetic term. Thus, there are three inflation paths: one parity invariant path, and the left and right paths for parity violating scenario. We showmore » that the inflations along the parity invariant path and right path are consistent with the Planck results. However, the gavitino mass for the parity invariant path is so large that the inflation results will be invalid if we consider the inflaton supersymmetry breaking soft mass term. Thus, only the inflation along the right path gives the correct and consistent results. Notably, the tensor-to-scalar ratio in such case can be large, with a value around 0.05, which may be probed by the future Planck experiment.« less

Paretian Poisson Processes

NASA Astrophysics Data System (ADS)

Eliazar, Iddo; Klafter, Joseph

2008-05-01

Many random populations can be modeled as a countable set of points scattered randomly on the positive half-line. The points may represent magnitudes of earthquakes and tornados, masses of stars, market values of public companies, etc. In this article we explore a specific class of random such populations we coin ` Paretian Poisson processes'. This class is elemental in statistical physics—connecting together, in a deep and fundamental way, diverse issues including: the Poisson distribution of the Law of Small Numbers; Paretian tail statistics; the Fréchet distribution of Extreme Value Theory; the one-sided Lévy distribution of the Central Limit Theorem; scale-invariance, renormalization and fractality; resilience to random perturbations.

Testing Cosmic Inflation

NASA Technical Reports Server (NTRS)

Chuss, David

2010-01-01

The Cosmic Microwave Background (CMB) has provided a wealth of information about the history and physics of the early Universe. Much progress has been made on uncovering the emerging Standard Model of Cosmology by such experiments as COBE and WMAP, and ESA's Planck Surveyor will likely increase our knowledge even more. Despite the success of this model, mysteries remain. Currently understood physics does not offer a compelling explanation for the homogeneity, flatness, and the origin of structure in the Universe. Cosmic Inflation, a brief epoch of exponential expansion, has been posted to explain these observations. If inflation is a reality, it is expected to produce a background spectrum of gravitational waves that will leave a small polarized imprint on the CMB. Discovery of this signal would give the first direct evidence for inflation and provide a window into physics at scales beyond those accessible to terrestrial particle accelerators. I will briefly review aspects of the Standard Model of Cosmology and discuss our current efforts to design and deploy experiments to measure the polarization of the CMB with the precision required to test inflation.

First-order inflation. [in cosmology

NASA Technical Reports Server (NTRS)

Turner, Michael S.

1992-01-01

I discuss the most recent model of inflation. In first-order inflation the inflationary epoch is associated with a first-order phase transition, with the most likely candidate being GUT symmetry breaking. The transition from the false-vacuum inflationary phase to the true-vacuum radiation-dominated phase proceeds through the nucleation and percolation of true-vacuum bubbles. The first successful and simplest model of first-order inflation, extended inflation, is discussed in some detail: evolution of the cosmic-scale factor, reheating, density perturbations, and the production of gravitational waves both from quantum fluctuations and bubble collisions. Particular attention is paid to the most critical issue in any model of first-order inflation: the requirements on the nucleation rate to ensure a graceful transition from the inflationary phase to the radiation-dominated phase.

Poisson's spot and Gouy phase

NASA Astrophysics Data System (ADS)

da Paz, I. G.; Soldati, Rodolfo; Cabral, L. A.; de Oliveira, J. G. G.; Sampaio, Marcos

2016-12-01

Recently there have been experimental results on Poisson spot matter-wave interferometry followed by theoretical models describing the relative importance of the wave and particle behaviors for the phenomenon. We propose an analytical theoretical model for Poisson's spot with matter waves based on the Babinet principle, in which we use the results for free propagation and single-slit diffraction. We take into account effects of loss of coherence and finite detection area using the propagator for a quantum particle interacting with an environment. We observe that the matter-wave Gouy phase plays a role in the existence of the central peak and thus corroborates the predominantly wavelike character of the Poisson's spot. Our model shows remarkable agreement with the experimental data for deuterium (D2) molecules.

[Analysis on risk factors of endotracheal cuff under inflation in mechanically ventilated patients].

PubMed

Fu, You; Xi, Xiuming

2014-12-01

To investigate the prevalent condition of endotracheal cuff pressure and risk factors for under inflation. A prospective cohort study was conducted. Patients admitted to the Department of Critical Care Medicine of Fuxing Hospital Affiliated to Capital Medical University, who were intubated with a high-volume low-pressure endotracheal tube, and had undergone mechanical ventilation for at least 48 hours, were enrolled. The endotracheal cuff pressure was determined every 8 hours by a manual manometer connected to the distal edge of the valve cuff at 07 : 00, 15 : 00, and 23 : 00. Measurement of the endotracheal cuff pressure was continued until the extubation of endotracheal or tracheostomy tube, or death of the patient. According to the incidence of under inflation of endotracheal cuff, patients were divided into the incidence of under inflation lower than 25% group (lower low cuff pressure group) and higher than 25% group (higher low cuff pressure group). The possible influencing factors were evaluated in the two groups, including body mass index (BMI), size of endotracheal tube, duration of intubation, use of sedative or analgesic, number of leaving from intensive care unit (ICU), the number of turning over the patients, and aspiration of sputum. Logistic regression analysis was used to determine risk factors for under-inflation of the endotracheal cuff. During the study period, 53 patients were enrolled. There were 812 measurements, and 46.3% of them was abnormal, and 204 times (25.1%) of under inflation of endotracheal cuff were found. There were 24 patients (45.3%) in whom the incidence of under inflation rate was higher than 25%. The average of under inflation was 7 (4, 10) times. Compared with the group with lower rate of low cuff pressure, a longer time for intubation was found in group with higher rate of low cuff pressure [hours: 162 (113, 225) vs. 118 (97, 168), Z=-2.034, P=0.042]. There were no differences between the two groups in other factors

Microwave background anisotropies in quasiopen inflation

NASA Astrophysics Data System (ADS)

García-Bellido, Juan; Garriga, Jaume; Montes, Xavier

1999-10-01

Quasiopenness seems to be generic to multifield models of single-bubble open inflation. Instead of producing infinite open universes, these models actually produce an ensemble of very large but finite inflating islands. In this paper we study the possible constraints from CMB anisotropies on existing models of open inflation. The effect of supercurvature anisotropies combined with the quasiopenness of the inflating regions make some models incompatible with observations, and severely reduces the parameter space of others. Supernatural open inflation and the uncoupled two-field model seem to be ruled out due to these constraints for values of Ω0<~0.98. Others, such as the open hybrid inflation model with suitable parameters for the slow roll potential can be made compatible with observations.

IAE - Inflatable Antenna Experiment

NASA Image and Video Library

1996-06-10

STS077-705-051 (20 May 1996) --- Following its deployment from the Space Shuttle Endeavour and its subsequent inflation process, the Spartan 207/Inflatable Antenna Experiment (IAE) payload is backdropped over mountains. The view was photographed with a handheld 70mm camera during the first full day of orbital operations by the six-member crew. Managed by Goddard Space Flight Center (GSFC), Spartan is designed to provide short-duration, free-flight opportunities for a variety of scientific studies. The Spartan configuration on this flight is unique in that the IAE is part of an additional separate unit which is ejected once the experiment is completed. The IAE experiment will lay the groundwork for future technology development in inflatable space structures, which will be launched and then inflated like a balloon on-orbit.

IAE - Inflatable Antenna Experiment

NASA Image and Video Library

1996-05-20

STS077-150-010 (20 May 1996) --- Soon after leaving the cargo bay of the Space Shuttle Endeavour, the Spartan 207/Inflatable Antenna Experiment (IAE) payload goes through its inflation process, backdropped over clouds. The view was photographed with a large format still camera on the first full day of in-space operations by the six-member crew. Managed by Goddard Space Flight Center (GSFC), Spartan is designed to provide short-duration, free-flight opportunities for a variety of scientific studies. The Spartan configuration on this flight is unique in that the IAE is part of an additional separate unit which is ejected once the experiment is completed. The IAE experiment will lay the groundwork for future technology development in inflatable space structures, which will be launched and then inflated like a balloon on-orbit.

Cosmological perturbations and noncommutative tachyon inflation

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

Liu Daojun; Li Xinzhou

2004-12-15

The motivation for studying the rolling tachyon and noncommutative inflation comes from string theory. In the tachyon inflation scenario, metric perturbations are created by tachyon field fluctuations during inflation. We drive the exact mode equation for scalar perturbations of the metric and investigate the cosmological perturbations in the commutative and noncommutative inflationary spacetime driven by the tachyon field which have a Born-Infeld Lagrangian. Although at lowest order the predictions of tachyon inflation are no different than those from standard slow-roll inflation, due to the modified inflationary dynamics there exists modifications to the power spectra of fluctuations generated during inflation. Inmore » the noncommutative tachyon inflation scenario, the stringy noncommutativity of spacetime results in corrections to the primordial power spectrum that lead to a spectral index that is greater than 1 on large scales and less than 1 on small scales as the first-year results of the Wilkinson Microwave Anisotropy Probe indicate.« less

Attachment device for an inflatable protective cushion

DOEpatents

Nelsen, J.M.; Luna, D.A.; Gwinn, K.W.

1997-11-18

An inflatable cushion assembly for use with an inflator comprises an inflatable cushion having an inner surface, outer surface, and at least one protrusion extending from one of the inner or outer surfaces. The inflatable cushion defines an opening between the inner surface and the outer surface for receiving the inflator. An attachment member contacts the one of the inner or outer surfaces adjacent the opening and includes a groove for receiving the protrusion, the attachment member securing the inflator within the opening. 22 figs.

Attachment device for an inflatable protective cushion

DOEpatents

Nelsen, J.M.; Luna, D.A.; Gwinn, K.W.

1998-12-08

An inflatable cushion assembly for use with an inflator comprises an inflatable cushion having an inner surface, outer surface, and at least one protrusion extending from one of the inner or outer surfaces. The inflatable cushion defines an opening between the inner surface and the outer surface for receiving the inflator. An attachment member contacts the one of the inner or outer surfaces adjacent the opening and includes a groove for receiving the protrusion, the attachment member securing the inflator within the opening. 22 figs.

Unimodularity criteria for Poisson structures on foliated manifolds

NASA Astrophysics Data System (ADS)

Pedroza, Andrés; Velasco-Barreras, Eduardo; Vorobiev, Yury

2018-03-01

We study the behavior of the modular class of an orientable Poisson manifold and formulate some unimodularity criteria in the semilocal context, around a (singular) symplectic leaf. Our results generalize some known unimodularity criteria for regular Poisson manifolds related to the notion of the Reeb class. In particular, we show that the unimodularity of the transverse Poisson structure of the leaf is a necessary condition for the semilocal unimodular property. Our main tool is an explicit formula for a bigraded decomposition of modular vector fields of a coupling Poisson structure on a foliated manifold. Moreover, we also exploit the notion of the modular class of a Poisson foliation and its relationship with the Reeb class.

Inflation at the electroweak scale

NASA Technical Reports Server (NTRS)

Knox, Lloyd; Turner, Michael S.

1993-01-01

We present a model for slow-rollover inflation where the vacuum energy that drives inflation is of the order of G(F) exp -2; unlike most models, the conversion of vacuum energy to radiation ('reheating') is moderately efficient. The scalar field responsible for inflation is a standard-model singlet, develops a vacuum expectation value of 4 x 10 exp 6 GeV, has a mass of about 1 GeV, and can play a role in electroweak phenomena. We also discuss models where the energy scale of inflation is somewhat larger, but still well below the unification scale.

Equivalence of MAXENT and Poisson point process models for species distribution modeling in ecology.

PubMed

Renner, Ian W; Warton, David I

2013-03-01

Modeling the spatial distribution of a species is a fundamental problem in ecology. A number of modeling methods have been developed, an extremely popular one being MAXENT, a maximum entropy modeling approach. In this article, we show that MAXENT is equivalent to a Poisson regression model and hence is related to a Poisson point process model, differing only in the intercept term, which is scale-dependent in MAXENT. We illustrate a number of improvements to MAXENT that follow from these relations. In particular, a point process model approach facilitates methods for choosing the appropriate spatial resolution, assessing model adequacy, and choosing the LASSO penalty parameter, all currently unavailable to MAXENT. The equivalence result represents a significant step in the unification of the species distribution modeling literature. Copyright © 2013, The International Biometric Society.

Characterization of Nonhomogeneous Poisson Processes Via Moment Conditions.

DTIC Science & Technology

1986-08-01

Poisson processes play an important role in many fields. The Poisson process is one of the simplest counting processes and is a building block for...place of independent increments. This provides a somewhat different viewpoint for examining Poisson processes . In addition, new characterizations for

Advanced Structural and Inflatable Hybrid Spacecraft Module

NASA Technical Reports Server (NTRS)

Schneider, William C. (Inventor); delaFuente, Horacio M. (Inventor); Edeen, Gregg A. (Inventor); Kennedy, Kriss J. (Inventor); Lester, James D. (Inventor); Gupta, Shalini (Inventor); Hess, Linda F. (Inventor); Lin, Chin H. (Inventor); Malecki, Richard H. (Inventor); Raboin, Jasen L. (Inventor)

2001-01-01

An inflatable module comprising a structural core and an inflatable shell, wherein the inflatable shell is sealingly attached to the structural core. In its launch configuration, the wall thickness of the inflatable shell is collapsed by vacuum. Also in this configuration, the inflatable shell is collapsed and efficiently folded around the structural core. Upon deployment, the wall thickness of the inflatable shell is inflated; whereby the inflatable shell itself, is thereby inflated around the structural core, defining therein a large enclosed volume. A plurality of removable shelves are arranged interior to the structural core in the launch configuration. The structural core also includes at least one longeron that, in conjunction with the shelves, primarily constitute the rigid, strong, and lightweight load-bearing structure of the module during launch. The removable shelves are detachable from their arrangement in the launch configuration so that, when the module is in its deployed configuration and launch loads no longer exist, the shelves can be rearranged to provide a module interior arrangement suitable for human habitation and work. In the preferred embodiment, to provide efficiency in structural load paths and attachments, the shape of the inflatable shell is a cylinder with semi-toroidal ends.

Quantile regression applied to spectral distance decay

USGS Publications Warehouse

Rocchini, D.; Cade, B.S.

2008-01-01

Remotely sensed imagery has long been recognized as a powerful support for characterizing and estimating biodiversity. Spectral distance among sites has proven to be a powerful approach for detecting species composition variability. Regression analysis of species similarity versus spectral distance allows us to quantitatively estimate the amount of turnover in species composition with respect to spectral and ecological variability. In classical regression analysis, the residual sum of squares is minimized for the mean of the dependent variable distribution. However, many ecological data sets are characterized by a high number of zeroes that add noise to the regression model. Quantile regressions can be used to evaluate trend in the upper quantiles rather than a mean trend across the whole distribution of the dependent variable. In this letter, we used ordinary least squares (OLS) and quantile regressions to estimate the decay of species similarity versus spectral distance. The achieved decay rates were statistically nonzero (p < 0.01), considering both OLS and quantile regressions. Nonetheless, the OLS regression estimate of the mean decay rate was only half the decay rate indicated by the upper quantiles. Moreover, the intercept value, representing the similarity reached when the spectral distance approaches zero, was very low compared with the intercepts of the upper quantiles, which detected high species similarity when habitats are more similar. In this letter, we demonstrated the power of using quantile regressions applied to spectral distance decay to reveal species diversity patterns otherwise lost or underestimated by OLS regression. ?? 2008 IEEE.

Poisson geometry from a Dirac perspective

NASA Astrophysics Data System (ADS)

Meinrenken, Eckhard

2018-03-01

We present proofs of classical results in Poisson geometry using techniques from Dirac geometry. This article is based on mini-courses at the Poisson summer school in Geneva, June 2016, and at the workshop Quantum Groups and Gravity at the University of Waterloo, April 2016.

Information transmission using non-poisson regular firing.

PubMed

Koyama, Shinsuke; Omi, Takahiro; Kass, Robert E; Shinomoto, Shigeru

2013-04-01

In many cortical areas, neural spike trains do not follow a Poisson process. In this study, we investigate a possible benefit of non-Poisson spiking for information transmission by studying the minimal rate fluctuation that can be detected by a Bayesian estimator. The idea is that an inhomogeneous Poisson process may make it difficult for downstream decoders to resolve subtle changes in rate fluctuation, but by using a more regular non-Poisson process, the nervous system can make rate fluctuations easier to detect. We evaluate the degree to which regular firing reduces the rate fluctuation detection threshold. We find that the threshold for detection is reduced in proportion to the coefficient of variation of interspike intervals.

The relationship between inflation and inflation uncertainty. Empirical evidence for the newest EU countries.

PubMed

Viorica, Daniela; Jemna, Danut; Pintilescu, Carmen; Asandului, Mircea

2014-01-01

The objective of this paper is to verify the hypotheses presented in the literature on the causal relationship between inflation and its uncertainty, for the newest EU countries. To ensure the robustness of the results, in the study four models for inflation uncertainty are estimated in parallel: ARCH (1), GARCH (1,1), EGARCH (1,1,1) and PARCH (1,1,1). The Granger method is used to test the causality between two variables. The working hypothesis is that groups of countries with a similar political and economic background in 1990 and are likely to be characterized by the same causal relationship between inflation and inflation uncertainty. Empirical results partially confirm this hypothesis. C22, E31, E37.

IAE - Inflatable Antenna Experiment

NASA Image and Video Library

1996-06-10

STS077-705-012 (20 May 1996) --- Following its deployment from the Space Shuttle Endeavour, the Inflatable Antenna Experiment (IAE) portion of the Spartan 207 payload is backdropped over Earth as it continues its inflation process. The view was photographed with a handheld 70mm camera during the first full day of orbital operations by the six-member crew. Managed by Goddard Space Flight Center (GSFC), Spartan is designed to provide short-duration, free-flight opportunities for a variety of scientific studies. The Spartan configuration on this flight is unique in that the IAE is part of an additional separate unit which is ejected once the experiment is completed. The IAE experiment will lay the groundwork for future technology development in inflatable space structures, which will be launched and then inflated like a balloon on-orbit.

IAE - Inflatable Antenna Experiment

NASA Image and Video Library

1996-06-10

STS077-705-016 (20 May 1996) --- Following its deployment from the Space Shuttle Endeavour, the Inflatable Antenna Experiment (IAE) part of the Spartan 207 payload nears completion of its inflation process over California?s Pacific Coast near Santa Barbara and Point Conception. The view was photographed with a handheld 70mm camera during the first full day of orbital operations by the six-member crew. Managed by Goddard Space Flight Center (GSFC), Spartan is designed to provide short-duration, free-flight opportunities for a variety of scientific studies. The Spartan configuration on this flight is unique in that the IAE is part of an additional separate unit which is ejected once the experiment is completed. The IAE experiment will lay the groundwork for future technology development in inflatable space structures, which will be launched and then inflated like a balloon on-orbit.

IAE - Inflatable Antenna Experiment

NASA Image and Video Library

1996-05-20

STS077-150-044 (20 May 1996) --- Following its deployment from the Space Shuttle Endeavour, the Spartan 207/Inflatable Antenna Experiment (IAE) payload is backdropped over the Grand Canyon. After the IAE completed its inflation process in free-flight, this view was photographed with a large format still camera. The activity came on the first full day of in-space operations by the six-member crew. Managed by Goddard Space Flight Center (GSFC), Spartan is designed to provide short-duration, free-flight opportunities for a variety of scientific studies. The Spartan configuration on this flight is unique in that the IAE is part of an additional separate unit which is ejected once the experiment is completed. The IAE experiment will lay the groundwork for future technology development in inflatable space structures, which will be launched and then inflated like a balloon on-orbit.

IAE - Inflatable Antenna Experiment

NASA Image and Video Library

1996-06-10

STS077-705-004 (20 May 1996) --- Following its deployment from the Space Shuttle Endeavour, the Inflatable Antenna Experiment (IAE) portion of the Spartan 207 payload begins to inflate, backdropped against clouds over the Pacific Ocean. The view was photographed with a handheld 70mm camera during the first full day of orbital operations by the six-member crew. Managed by Goddard Space Flight Center (GSFC), Spartan is designed to provide short-duration, free-flight opportunities for a variety of scientific studies. The Spartan configuration on this flight is unique in that the IAE is part of an additional separate unit which is ejected once the experiment is completed. The IAE experiment will lay the groundwork for future technology development in inflatable space structures, which will be launched and then inflated like a balloon on-orbit.

IAE - Inflatable Antenna Experiment

NASA Image and Video Library

1996-05-20

STS077-150-022 (20 May 1996) --- After leaving the cargo bay of the Space Shuttle Endeavour, the Spartan 207/Inflatable Antenna Experiment (IAE) payload goes through the final stages its inflation process, backdropped over clouds and blue water. The view was photographed with a large format still camera on the first full day of in-space operations by the six-member crew. Managed by Goddard Space Flight Center (GSFC), Spartan is designed to provide short-duration, free-flight opportunities for a variety of scientific studies. The Spartan configuration on this flight is unique in that the IAE is part of an additional separate unit which is ejected once the experiment is completed. The IAE experiment will lay the groundwork for future technology development in inflatable space structures, which will be launched and then inflated like a balloon on-orbit.

Tribrid Inflation in Supergravity

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

Antusch, Stefan; Dutta, Koushik; Kostka, Philipp M.

2010-02-10

We propose a novel class of F-term hybrid inflation models in supergravity (SUGRA) where the eta-problem is resolved using either a Heisenberg symmetry or a shift symmetry of the Kaehler potential. In addition to the inflaton and the waterfall field, this class (referred to as tribrid inflation) contains a third 'driving' field which contributes the large vacuum energy during inflation by its F-term. In contrast to the 'standard' hybrid scenario, it has several attractive features due to the property of vanishing inflationary superpotential (W{sub inf} = 0) during inflation. While the symmetries of the Kaehler potential ensure a flat inflatonmore » potential at tree-level, quantum corrections induced by symmetry breaking terms in the superpotential generate a slope of the potential and lead to a spectral tilt consistent with recent WMAP observations.« less

Thermalized axion inflation: Natural and monomial inflation with small r

NASA Astrophysics Data System (ADS)

Ferreira, Ricardo Z.; Notari, Alessio

2018-03-01

A safe way to reheat the Universe, in models of natural and quadratic inflation, is through shift symmetric couplings between the inflaton ϕ and the Standard Model (SM), since they do not generate loop corrections to the potential V (ϕ ). We consider such a coupling to SM gauge fields, of the form ϕ F F ˜/f , with sub-Planckian f . In this case, gauge fields can be exponentially produced already during inflation and thermalize via interactions with charged particles, as pointed out in previous work. This can lead to a plasma of temperature T during inflation, and the thermal masses g T of the gauge bosons can equilibrate the system. In addition, inflaton perturbations δ ϕ can also have a thermal spectrum if they have sufficiently large cross sections with the plasma. In this case, inflationary predictions are strongly modified: (1) scalar perturbations are thermal, and so enhanced over the vacuum, leading to a generic way to suppress the tensor-to-scalar ratio r ; (2) the spectral index is ns-1 =η -4 ɛ . After presenting the relevant conditions for thermalization, we show that thermalized natural and monomial models of inflation agree with present observations and have r ≈10-3-10-2, which is within reach of next generation CMB experiments.

Negative running can prevent eternal inflation

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

Kinney, William H.; Freese, Katherine, E-mail: whkinney@buffalo.edu, E-mail: ktfreese@umich.edu

Current data from the Planck satellite and the BICEP2 telescope favor, at around the 2 σ level, negative running of the spectral index of curvature perturbations from inflation. We show that for negative running α < 0, the curvature perturbation amplitude has a maximum on scales larger than our current horizon size. A condition for the absence of eternal inflation is that the curvature perturbation amplitude always remain below unity on superhorizon scales. For current bounds on n{sub S} from Planck, this corresponds to an upper bound of the running α < −9 × 10{sup −5}, so that even tiny running of the scalar spectral index ismore » sufficient to prevent eternal inflation from occurring, as long as the running remains negative on scales outside the horizon. In single-field inflation models, negative running is associated with a finite duration of inflation: we show that eternal inflation may not occur even in cases where inflation lasts as long as 10{sup 4} e-folds.« less

Primordial anisotropies in gauged hybrid inflation

NASA Astrophysics Data System (ADS)

Akbar Abolhasani, Ali; Emami, Razieh; Firouzjahi, Hassan

2014-05-01

We study primordial anisotropies generated in the model of gauged hybrid inflation in which the complex waterfall field is charged under a U(1)gauge field. Primordial anisotropies are generated either actively during inflation or from inhomogeneities modulating the surface of end of inflation during waterfall transition. We present a consistent δN mechanism to calculate the anisotropic power spectrum and bispectrum. We show that the primordial anisotropies generated at the surface of end of inflation do not depend on the number of e-folds and therefore do not produce dangerously large anisotropies associated with the IR modes. Furthermore, one can find the parameter space that the anisotropies generated from the surface of end of inflation cancel the anisotropies generated during inflation, therefore relaxing the constrains on model parameters imposed from IR anisotropies. We also show that the gauge field fluctuations induce a red-tilted power spectrum so the averaged power spectrum from the gauge field can change the total power spectrum from blue to red. Therefore, hybrid inflation, once gauged under a U(1) field, can be consistent with the cosmological observations.

Nonthermal gravitino production in tribrid inflation

NASA Astrophysics Data System (ADS)

Antusch, Stefan; Dutta, Koushik

2015-10-01

We investigate nonthermal gravitino production after tribrid inflation in supergravity, which is a variant of supersymmetric hybrid inflation where three fields are involved in the inflationary model and where the inflaton field resides in the matter sector of the theory. In contrast to conventional supersymmetric hybrid inflation, where nonthermal gravitino production imposes severe constraints on the inflationary model, we find that the "nonthermal gravitino problem" is generically absent in models of tribrid inflation, mainly due to two effects: (i) With the inflaton in tribrid inflation (after inflation) being lighter than the waterfall field, the latter has a second decay channel with a much larger rate than for the decay into gravitinos. This reduces the branching ratio for the decay of the waterfall field into gravitinos. (ii) The inflaton generically decays later than the waterfall field, and it does not produce gravitinos when it decays. This leads to a dilution of the gravitino population from the decays of the waterfall field. The combination of both effects generically leads to a strongly reduced gravitino production in tribrid inflation.

Structurally efficient inflatable protective device

DOEpatents

Nelsen, James M.; Whinery, Larry D.; Gwinn, Kenneth W.; McBride, Donald D.; Luna, Daniel A.; Holder, Joseph P.; Bliton, Richard J.

1997-01-01

An apparatus and method for making a low cost, self-venting, inflatable protective cushion of simple and structurally efficient design with a shape and construction that optimizes the cushion's ability to withstand inflation pressures and impact when deployed which includes a sheet defined by at least one fold line and a plurality of flap portions, each flap portion having a base edge corresponding to a fold line and at least two side edges each extending outwardly from a base edge and ultimately converging to meet each other, the flap portions being folded at the fold line(s) and being joined at corresponding side edges to define an inflatable chamber. The inflatable protective cushion and method for making same may further include a lightweight, low permeability, fabric that optimizes the cushion's ability to withstand inflation pressures and impact when deployed and minimizes the packed volume of the cushion when stored.

Structurally efficient inflatable protective device

DOEpatents

Nelsen, James M.; Whinery, Larry D.; Gwinn, Kenneth W.; McBride, Donald D.; Luna, Daniel A.; Holder, Joseph P.; Bliton, Richard J.

1996-01-01

An apparatus and method for making a low cost, self-venting, inflatable protective cushion of simple and structurally efficient design with a shape and construction that optimizes the cushion's ability to withstand inflation pressures and impact when deployed which includes a sheet defined by at least one fold line and a plurality of flap portions, each flap portion having a base edge corresponding to a fold line and at least two side edges each extending outwardly from a base edge and ultimately converging to meet each other, the flap portions being folded at the fold line(s) and being Joined at corresponding side edges to define an inflatable chamber. The inflatable protective cushion and method for making same may further include a lightweight, low permeability, fabric that optimizes the cushion's ability to withstand inflation pressures and impact when deployed and minimizes the packed volume of the cushion when stored.

Structurally efficient inflatable protective device

DOEpatents

Nelsen, James M.; Whinery, Larry D.; Gwinn, Kenneth W.; McBride, Donald D.; Luna, Daniel A.; Holder, Joseph P.; Bliton, Richard J.

1996-01-01

An apparatus and method for making a low cost, self-venting, inflatable protective cushion of simple and structurally efficient design with a shape and construction that optimizes the cushion's ability to withstand inflation pressures and impact when deployed which includes a sheet defined by at least one fold line and a plurality of flap portions, each flap portion having a base edge corresponding to a fold line and at least two side edges each extending outwardly from a base edge and ultimately converging to meet each other, the flap portions being folded at the fold line(s) and being joined at corresponding side edges to define an inflatable chamber. The inflatable protective cushion and method for making same may further include a lightweight, low permeability, fabric that optimizes the cushion's ability to withstand inflation pressures and impact when deployed and minimizes the packed volume of the cushion when stored.

Modular invariant inflation

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

Kobayashi, Tatsuo; Nitta, Daisuke; Urakawa, Yuko

2016-08-08

Modular invariance is a striking symmetry in string theory, which may keep stringy corrections under control. In this paper, we investigate a phenomenological consequence of the modular invariance, assuming that this symmetry is preserved as well as in a four dimensional (4D) low energy effective field theory. As a concrete setup, we consider a modulus field T whose contribution in the 4D effective field theory remains invariant under the modular transformation and study inflation drived by T. The modular invariance restricts a possible form of the scalar potenntial. As a result, large field models of inflation are hardly realized. Meanwhile,more » a small field model of inflation can be still accomodated in this restricted setup. The scalar potential traced during the slow-roll inflation mimics the hilltop potential V{sub ht}, but it also has a non-negligible deviation from V{sub ht}. Detecting the primordial gravitational waves predicted in this model is rather challenging. Yet, we argue that it may be still possible to falsify this model by combining the information in the reheating process which can be determined self-completely in this setup.« less

Inflatable antennas for microwave pwoer transmission

NASA Technical Reports Server (NTRS)

Williams, Geoff

1989-01-01

Operational phase of the inflatable radiator; inflatable space structures; advantages; inflated thin-film satellites; antenna configuration; 3 meter diameter test paraboloid (HAIR program); and weight breakdown for the 100 meter diameter reflector are outlined. This presentation is represented by viewgraphs only.

Oscillatory Reduction in Option Pricing Formula Using Shifted Poisson and Linear Approximation

NASA Astrophysics Data System (ADS)

Nur Rachmawati, Ro'fah; Irene; Budiharto, Widodo

2014-03-01

Option is one of derivative instruments that can help investors improve their expected return and minimize the risks. However, the Black-Scholes formula is generally used in determining the price of the option does not involve skewness factor and it is difficult to apply in computing process because it produces oscillation for the skewness values close to zero. In this paper, we construct option pricing formula that involve skewness by modified Black-Scholes formula using Shifted Poisson model and transformed it into the form of a Linear Approximation in the complete market to reduce the oscillation. The results are Linear Approximation formula can predict the price of an option with very accurate and successfully reduce the oscillations in the calculation processes.

Inspiratory capacity at inflation hold in ventilated newborns: a surrogate measure for static compliance of the respiratory system.

PubMed

Hentschel, Roland; Semar, Nicole; Guttmann, Josef

2012-09-01

To study appropriateness of respiratory system compliance calculation using an inflation hold and compare it with ventilator readouts of pressure and tidal volume as well as with measurement of compliance of the respiratory system with the single-breath-single-occlusion technique gained with a standard lung function measurement. Prospective clinical trial. Level III neonatal unit of a university hospital. Sixty-seven newborns, born prematurely or at term, ventilated for a variety of pathologic conditions. A standardized sigh maneuver with a predefined peak inspiratory pressure of 30 cm H2O, termed inspiratory capacity at inflation hold, was applied. Using tidal volume, exhaled from inspiratory pause down to ambient pressure, as displayed by the ventilator, and predefined peak inspiratory pressure, compliance at inspiratory capacity at inflation hold conditions could be calculated as well as ratio of tidal volume and ventilator pressure using tidal volume and differential pressure at baseline ventilator settings: peak inspiratory pressure minus positive end-expiratory pressure. For the whole cohort, the equation for the regression between tidal volume at inspiratory capacity at inflation hold and compliance of the respiratory system was: compliance of the respiratory system = 0.052 * tidal volume at inspiratory capacity at inflation hold - 0.113, and compliance at inspiratory capacity at inflation hold conditions was closely related to the standard lung function measurement method of compliance of the respiratory system (R = 0.958). In contrast, ratio of tidal volume and ventilator pressure per kilogram calculated from the ventilator readouts and displayed against compliance of the respiratory system per kilogram yielded a broad scatter throughout the whole range of compliance; both were only weakly correlated (R = 0.309) and also the regression line was significantly different from the line of identity (p < .05). Peak inspiratory pressure at study entry did not

46 CFR 169.849 - Posting placards containing instructions for launching and inflating inflatable liferafts.

Code of Federal Regulations, 2012 CFR

2012-10-01

... accessible to the ship's company and guests approved placards containing instructions for launching and inflating inflatable liferafts. The number and location of such placards for a particular vessel shall be...

46 CFR 169.849 - Posting placards containing instructions for launching and inflating inflatable liferafts.

Code of Federal Regulations, 2014 CFR

2014-10-01

... accessible to the ship's company and guests approved placards containing instructions for launching and inflating inflatable liferafts. The number and location of such placards for a particular vessel shall be...

46 CFR 169.849 - Posting placards containing instructions for launching and inflating inflatable liferafts.

Code of Federal Regulations, 2011 CFR

2011-10-01

... accessible to the ship's company and guests approved placards containing instructions for launching and inflating inflatable liferafts. The number and location of such placards for a particular vessel shall be...

46 CFR 169.849 - Posting placards containing instructions for launching and inflating inflatable liferafts.

Code of Federal Regulations, 2013 CFR

2013-10-01

... accessible to the ship's company and guests approved placards containing instructions for launching and inflating inflatable liferafts. The number and location of such placards for a particular vessel shall be...

The Relationship between Inflation and Inflation Uncertainty. Empirical Evidence for the Newest EU Countries

PubMed Central

Viorica, Daniela; Jemna, Danut; Pintilescu, Carmen; Asandului, Mircea

2014-01-01

The objective of this paper is to verify the hypotheses presented in the literature on the causal relationship between inflation and its uncertainty, for the newest EU countries. To ensure the robustness of the results, in the study four models for inflation uncertainty are estimated in parallel: ARCH (1), GARCH (1,1), EGARCH (1,1,1) and PARCH (1,1,1). The Granger method is used to test the causality between two variables. The working hypothesis is that groups of countries with a similar political and economic background in 1990 and are likely to be characterized by the same causal relationship between inflation and inflation uncertainty. Empirical results partially confirm this hypothesis. Jel Classification C22, E31, E37. PMID:24633073

Structurally efficient inflatable protective device

DOEpatents

Nelsen, J.M.; Whinery, L.D.; Gwinn, K.W.; McBride, D.D.; Luna, D.A.; Holder, J.P.; Bliton, R.J.

1997-03-04

An apparatus and method are disclosed for making a low cost, self-venting, inflatable protective cushion of simple and structurally efficient design with a shape and construction that optimizes the cushion`s ability to withstand inflation pressures and impact when deployed which includes a sheet defined by at least one fold line and a plurality of flap portions, each flap portion having a base edge corresponding to a fold line and at least two side edges each extending outwardly from a base edge and ultimately converging to meet each other, the flap portions being folded at the fold line(s) and being joined at corresponding side edges to define an inflatable chamber. The inflatable protective cushion and method for making same may further include a lightweight, low permeability, fabric that optimizes the cushion`s ability to withstand inflation pressures and impact when deployed and minimizes the packed volume of the cushion when stored. 22 figs.

Structurally efficient inflatable protective device

DOEpatents

Nelsen, J.M.; Whinery, L.D.; Gwinn, K.W.; McBride, D.D.; Luna, D.A.; Holder, J.P.; Bliton, R.J.

1996-01-09

An apparatus and method are disclosed for making a low cost, self-venting, inflatable protective cushion of simple and structurally efficient design with a shape and construction that optimizes the cushion`s ability to withstand inflation pressures and impact when deployed which includes a sheet defined by at least one fold line and a plurality of flap portions, each flap portion having a base edge corresponding to a fold line and at least two side edges each extending outwardly from a base edge and ultimately converging to meet each other, the flap portions being folded at the fold line(s) and being joined at corresponding side edges to define an inflatable chamber. The inflatable protective cushion and method for making same may further include a lightweight, low permeability, fabric that optimizes the cushion`s ability to withstand inflation pressures and impact when deployed and minimizes the packed volume of the cushion when stored. 22 figs.

Sustained inflation during neonatal resuscitation.

PubMed

Keszler, Martin

2015-04-01

Sustained inflation performed shortly after birth to help clear lung fluid and establish functional residual capacity in preterm infants is gaining popularity, but definitive evidence for its effectiveness is lacking. Although there is a sound physiologic basis for this approach, and much preclinical experimental evidence of effectiveness, the results of recent animal studies and clinical trials have been inconsistent. The most recent data from a multicenter randomized trial suggest a modest benefit of sustained inflation in reducing the need for mechanical ventilation in extremely-low-birth-weight infants. However, the impact may be more modest than earlier retrospective cohort comparisons suggested. The trend toward more airleak and a higher rate of intraventricular hemorrhage is worrisome. Sustained inflation may be ineffective unless some spontaneous respiratory effort is present. Several on-going trials should further clarify the putative benefits of sustained inflation. Delivery room sustained inflation is an attractive concept that holds much promise, but widespread clinical application should await definitive evidence from on-going clinical trials.

Goldstone inflation

NASA Astrophysics Data System (ADS)

Croon, Djuna; Sanz, Verónica; Setford, Jack

2015-10-01

Identifying the inflaton with a pseudo-Goldstone boson explains the flatness of its potential. Successful Goldstone Inflation should also be robust against UV corrections, such as from quantum gravity: in the language of the effective field theory this implies that all scales are sub-Planckian. In this paper we present scenarios which realise both requirements by examining the structure of Goldstone potentials arising from Coleman-Weinberg contributions. We focus on single-field models, for which we notice that both bosonic and fermionic contributions are required and that spinorial fermion representations can generate the right potential shape. We then evaluate the constraints on non-Gaussianity from higher-derivative interactions, finding that axiomatic constraints on Goldstone boson scattering prevail over the current CMB measurements. The fit to CMB data can be connected to the UV completions for Goldstone Inflation, finding relations in the spectrum of new resonances. Finally, we show how hybrid inflation can be realised in the same context, where both the inflaton and the waterfall fields share a common origin as Goldstones.

Inflation from extra dimensions

NASA Astrophysics Data System (ADS)

Levin, Janna J.

1995-02-01

A gravity-driven inflation is shown to arise from a simple higher-dimensional universe. In vacuum, the shear of n > 1 contracting dimensions is able to inflate the remaining three spatial dimensions. Said another way, the expansion of the 3-volume is accelerated by the contraction of the n-volume. Upon dimensional reduction, the theory is equivalent to a four-dimensional cosmology with a dynamical Planck mass. A connection can therefore be made to recent examples of inflation powered by a dilaton kinetic energy. Unfortunately, the graceful exit problem encountered in dilaton cosmologies will haunt this cosmology as well.

Study of non-Hodgkin's lymphoma mortality associated with industrial pollution in Spain, using Poisson models

PubMed Central

Ramis, Rebeca; Vidal, Enrique; García-Pérez, Javier; Lope, Virginia; Aragonés, Nuria; Pérez-Gómez, Beatriz; Pollán, Marina; López-Abente, Gonzalo

2009-01-01

Background Non-Hodgkin's lymphomas (NHLs) have been linked to proximity to industrial areas, but evidence regarding the health risk posed by residence near pollutant industries is very limited. The European Pollutant Emission Register (EPER) is a public register that furnishes valuable information on industries that release pollutants to air and water, along with their geographical location. This study sought to explore the relationship between NHL mortality in small areas in Spain and environmental exposure to pollutant emissions from EPER-registered industries, using three Poisson-regression-based mathematical models. Methods Observed cases were drawn from mortality registries in Spain for the period 1994–2003. Industries were grouped into the following sectors: energy; metal; mineral; organic chemicals; waste; paper; food; and use of solvents. Populations having an industry within a radius of 1, 1.5, or 2 kilometres from the municipal centroid were deemed to be exposed. Municipalities outside those radii were considered as reference populations. The relative risks (RRs) associated with proximity to pollutant industries were estimated using the following methods: Poisson Regression; mixed Poisson model with random provincial effect; and spatial autoregressive modelling (BYM model). Results Only proximity of paper industries to population centres (>2 km) could be associated with a greater risk of NHL mortality (mixed model: RR:1.24, 95% CI:1.09–1.42; BYM model: RR:1.21, 95% CI:1.01–1.45; Poisson model: RR:1.16, 95% CI:1.06–1.27). Spatial models yielded higher estimates. Conclusion The reported association between exposure to air pollution from the paper, pulp and board industry and NHL mortality is independent of the model used. Inclusion of spatial random effects terms in the risk estimate improves the study of associations between environmental exposures and mortality. The EPER could be of great utility when studying the effects of industrial pollution

Plausible double inflation

NASA Technical Reports Server (NTRS)

Holman, Richard; Kolb, Edward W.; Vadas, Sharon L.; Wang, Yun

1991-01-01

It is likely that extended inflation is followed by an epoch of slowroll inflation. Such a sequence of events may lead to a very interesting perturbation spectrum with significant power on the scale of the transition between the extended and slowroll phase, superimposed upon a power-law spectrum with deviations from the Harrison-Zeldovich slope. Normalization of the spectra above and below the transition scale is expected to differ.

Bayesian Estimation of Multivariate Latent Regression Models: Gauss versus Laplace

ERIC Educational Resources Information Center

Culpepper, Steven Andrew; Park, Trevor

2017-01-01

A latent multivariate regression model is developed that employs a generalized asymmetric Laplace (GAL) prior distribution for regression coefficients. The model is designed for high-dimensional applications where an approximate sparsity condition is satisfied, such that many regression coefficients are near zero after accounting for all the model…

Accidental inflation from Kähler uplifting

NASA Astrophysics Data System (ADS)

Ben-Dayan, Ido; Jing, Shenglin; Westphal, Alexander; Wieck, Clemens

2014-03-01

We analyze the possibility of realizing inflation with a subsequent dS vacuum in the Käahler uplifting scenario. The inclusion of several quantum corrections to the 4d effective action evades previous no-go theorems and allows for construction of simple and successful models of string inflation. The predictions of several benchmark models are in accord with current observations, i.e., a red spectral index, negligible non-gaussianity, and spectral distortions similar to the simplest models of inflation. A particularly interesting subclass of models are ``left-rolling" ones, where the overall volume of the compactified dimensions shrinks during inflation. We call this phenomenon ``inflation by deflation" (IBD), where deflation refers to the internal manifold. This subclass has the appealing features of being insensitive to initial conditions, avoiding the overshooting problem, and allowing for observable running α ~ 0.012 and enhanced tensor-to-scalar ratio r ~ 10-5. The latter results differ significantly from many string inflation models.

Mass inflation followed by Belinskii-Khalatnikov-Lifshitz collapse inside accreting, rotating black holes

NASA Astrophysics Data System (ADS)

Hamilton, Andrew J. S.

2017-10-01

Numerical evidence is presented that the Poisson-Israel mass inflation instability at the inner horizon of an accreting, rotating black hole is generically followed by Belinskii-Khalatnikov-Lifshitz oscillatory collapse to a spacelike singularity. The computation involves following all 6 degrees of freedom of the gravitational field. To simplify the problem, the computation takes as initial conditions the conformally separable solutions of Andrew J. S. Hamilton and Gavin Polhemus [Interior structure of rotating black holes. I. Concise derivation, Phys. Rev. D 84, 124055 (2011), 10.1103/PhysRevD.84.124055] and Andrew J. S. Hamilton [Interior structure of rotating black holes. II. Uncharged black holes, Phys. Rev. D 84, 124056 (2011), 10.1103/PhysRevD.84.124056] just above the inner horizon of a slowly accreting, rotating black hole and integrates the equations inward along single latitudes.

Bispectrum from open inflation

NASA Astrophysics Data System (ADS)

Sugimura, Kazuyuki; Komatsu, Eiichiro

2013-11-01

We calculate the bispectrum of primordial curvature perturbations, ζ, generated during ``open inflation.'' Inflation occurs inside a bubble nucleated via quantum tunneling from the background false vacuum state. Our universe lives inside the bubble, which can be described as a Friedmann-Lemaȋtre-Robertson-Walker (FLRW) universe with negative spatial curvature, undergoing slow-roll inflation. We pay special attention to the issue of an initial state for quantum fluctuations. A ``vacuum state'' defined by a positive-frequency mode in de Sitter space charted by open coordinates is different from the Euclidean vacuum (which is equivalent to the so-called ``Bunch-Davies vacuum'' defined by a positive-frequency mode in de Sitter space charted by flat coordinates). Quantum tunneling (bubble nucleation) then modifies the initial state away from the original Euclidean vacuum. While most of the previous study on modifications of the initial quantum state introduces, by hand, an initial time at which the quantum state is modified as well as the form of the modification, an effective initial time naturally emerges and the form is fixed by quantum tunneling in open inflation models. Therefore, open inflation enables a self-consistent computation of the effect of a modified initial state on the bispectrum. We find a term which goes as langleζk1ζk2ζk3ranglepropto1/k12k34 in the so-called squeezed configurations, k3 << k1 ≈ k2, in agreement with the previous study on modifications of the initial state. The bispectrum in the exact folded limit, e.g., k1 = k2+k3, is also enhanced and remains finite. However, these terms are exponentially suppressed when the wavelength of ζ is smaller than the curvature radius of the universe. The leading-order bispectrum is equal to the usual one from single-field slow-roll inflation; the terms specific for open inflation arise only in the sub-leading order when the wavelength of ζ is smaller than the curvature radius.

Gauge fields and inflation

NASA Astrophysics Data System (ADS)

Maleknejad, A.; Sheikh-Jabbari, M. M.; Soda, J.

2013-07-01

The isotropy and homogeneity of the cosmic microwave background (CMB) favors “scalar driven” early Universe inflationary models. However, gauge fields and other non-scalar fields are far more common at all energy scales, in particular at high energies seemingly relevant to inflation models. Hence, in this review we consider the role and consequences, theoretical and observational, that gauge fields can have during the inflationary era. Gauge fields may be turned on in the background during inflation, or may become relevant at the level of cosmic perturbations. There have been two main classes of models with gauge fields in the background, models which show violation of the cosmic no-hair theorem and those which lead to isotropic FLRW cosmology, respecting the cosmic no-hair theorem. Models in which gauge fields are only turned on at the cosmic perturbation level, may source primordial magnetic fields. We also review specific observational features of these models on the CMB and/or the primordial cosmic magnetic fields. Our discussions will be mainly focused on the inflation period, with only a brief discussion on the post inflationary (p)reheating era. Large field models: The initial value of the inflaton field is large, generically super-Planckian, and it rolls slowly down toward the potential minimum at smaller φ values. For instance, chaotic inflation is one of the representative models of this class. The typical potential of large-field models has a monomial form as V(φ)=V0φn. A simple analysis using the dynamical equations reveals that for number of e-folds Ne larger than 60, we require super-Planckian initial field values,5φ0>3M. For these models typically ɛ˜η˜Ne-1. Small field models: Inflaton field is initially small and slowly evolves toward the potential minimum at larger φ values. The small field models are characterized by the following potential V(φ)=V0(1-(), which corresponds to a Taylor expansion about the origin, but more realistic

46 CFR 169.849 - Posting placards containing instructions for launching and inflating inflatable liferafts.

Code of Federal Regulations, 2010 CFR

2010-10-01

... Inspections § 169.849 Posting placards containing instructions for launching and inflating inflatable... accessible to the ship's company and guests approved placards containing instructions for launching and... determined by the Officer in Charge, Marine Inspection. ...

Sparse Poisson noisy image deblurring.

PubMed

Carlavan, Mikael; Blanc-Féraud, Laure

2012-04-01

Deblurring noisy Poisson images has recently been a subject of an increasing amount of works in many areas such as astronomy and biological imaging. In this paper, we focus on confocal microscopy, which is a very popular technique for 3-D imaging of biological living specimens that gives images with a very good resolution (several hundreds of nanometers), although degraded by both blur and Poisson noise. Deconvolution methods have been proposed to reduce these degradations, and in this paper, we focus on techniques that promote the introduction of an explicit prior on the solution. One difficulty of these techniques is to set the value of the parameter, which weights the tradeoff between the data term and the regularizing term. Only few works have been devoted to the research of an automatic selection of this regularizing parameter when considering Poisson noise; therefore, it is often set manually such that it gives the best visual results. We present here two recent methods to estimate this regularizing parameter, and we first propose an improvement of these estimators, which takes advantage of confocal images. Following these estimators, we secondly propose to express the problem of the deconvolution of Poisson noisy images as the minimization of a new constrained problem. The proposed constrained formulation is well suited to this application domain since it is directly expressed using the antilog likelihood of the Poisson distribution and therefore does not require any approximation. We show how to solve the unconstrained and constrained problems using the recent alternating-direction technique, and we present results on synthetic and real data using well-known priors, such as total variation and wavelet transforms. Among these wavelet transforms, we specially focus on the dual-tree complex wavelet transform and on the dictionary composed of curvelets and an undecimated wavelet transform.

Poly-symplectic Groupoids and Poly-Poisson Structures

NASA Astrophysics Data System (ADS)

Martinez, Nicolas

2015-05-01

We introduce poly-symplectic groupoids, which are natural extensions of symplectic groupoids to the context of poly-symplectic geometry, and define poly-Poisson structures as their infinitesimal counterparts. We present equivalent descriptions of poly-Poisson structures, including one related with AV-Dirac structures. We also discuss symmetries and reduction in the setting of poly-symplectic groupoids and poly-Poisson structures, and use our viewpoint to revisit results and develop new aspects of the theory initiated in Iglesias et al. (Lett Math Phys 103:1103-1133, 2013).

12 CFR 1780.80 - Inflation adjustments.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 7 2010-01-01 2010-01-01 false Inflation adjustments. 1780.80 Section 1780.80... DEVELOPMENT RULES OF PRACTICE AND PROCEDURE RULES OF PRACTICE AND PROCEDURE Civil Money Penalty Inflation Adjustments § 1780.80 Inflation adjustments. The maximum amount of each civil money penalty within OFHEO's...

Retargeted Least Squares Regression Algorithm.

PubMed

Zhang, Xu-Yao; Wang, Lingfeng; Xiang, Shiming; Liu, Cheng-Lin

2015-09-01

This brief presents a framework of retargeted least squares regression (ReLSR) for multicategory classification. The core idea is to directly learn the regression targets from data other than using the traditional zero-one matrix as regression targets. The learned target matrix can guarantee a large margin constraint for the requirement of correct classification for each data point. Compared with the traditional least squares regression (LSR) and a recently proposed discriminative LSR models, ReLSR is much more accurate in measuring the classification error of the regression model. Furthermore, ReLSR is a single and compact model, hence there is no need to train two-class (binary) machines that are independent of each other. The convex optimization problem of ReLSR is solved elegantly and efficiently with an alternating procedure including regression and retargeting as substeps. The experimental evaluation over a range of databases identifies the validity of our method.

Comments on SUSY Inflation Models on the Brane

NASA Astrophysics Data System (ADS)

Lee, Lu-Yun; Cheung, Kingman; Lin, Chia-Min

In this paper we consider a class of inflation models on the brane where the dominant part of the inflaton scalar potential does not depend on the inflaton field value during inflation. In particular, we consider supernatural inflation, its hilltop version, A-term inflation, and supersymmetric (SUSY) D- and F-term hybrid inflation on the brane. We show that the parameter space can be broadened, the inflation scale generally can be lowered, and still possible to have the spectral index ns = 0.96.

An INAR(1) Negative Multinomial Regression Model for Longitudinal Count Data.

ERIC Educational Resources Information Center

Bockenholt, Ulf

1999-01-01

Discusses a regression model for the analysis of longitudinal count data in a panel study by adapting an integer-valued first-order autoregressive (INAR(1)) Poisson process to represent time-dependent correlation between counts. Derives a new negative multinomial distribution by combining INAR(1) representation with a random effects approach.…

Inflation and Rural Society.

ERIC Educational Resources Information Center

Pitt, David

Inflation is both a cause and consequence of changes in power and status. Competitive status activities create spiral situations which have an economic correlate. Ultimately, inflation leads to the creation of economically deprived and depressed social groups. Deflation can be achieved to some extent by redistribution of wealth dictated from…

Evaluating the double Poisson generalized linear model.

PubMed

Zou, Yaotian; Geedipally, Srinivas Reddy; Lord, Dominique

2013-10-01

The objectives of this study are to: (1) examine the applicability of the double Poisson (DP) generalized linear model (GLM) for analyzing motor vehicle crash data characterized by over- and under-dispersion and (2) compare the performance of the DP GLM with the Conway-Maxwell-Poisson (COM-Poisson) GLM in terms of goodness-of-fit and theoretical soundness. The DP distribution has seldom been investigated and applied since its first introduction two decades ago. The hurdle for applying the DP is related to its normalizing constant (or multiplicative constant) which is not available in closed form. This study proposed a new method to approximate the normalizing constant of the DP with high accuracy and reliability. The DP GLM and COM-Poisson GLM were developed using two observed over-dispersed datasets and one observed under-dispersed dataset. The modeling results indicate that the DP GLM with its normalizing constant approximated by the new method can handle crash data characterized by over- and under-dispersion. Its performance is comparable to the COM-Poisson GLM in terms of goodness-of-fit (GOF), although COM-Poisson GLM provides a slightly better fit. For the over-dispersed data, the DP GLM performs similar to the NB GLM. Considering the fact that the DP GLM can be easily estimated with inexpensive computation and that it is simpler to interpret coefficients, it offers a flexible and efficient alternative for researchers to model count data. Copyright © 2013 Elsevier Ltd. All rights reserved.

Inflation model selection meets dark radiation

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

Tram, Thomas; Vallance, Robert; Vennin, Vincent, E-mail: thomas.tram@port.ac.uk, E-mail: robert.vallance@student.manchester.ac.uk, E-mail: vincent.vennin@port.ac.uk

2017-01-01

We investigate how inflation model selection is affected by the presence of additional free-streaming relativistic degrees of freedom, i.e. dark radiation. We perform a full Bayesian analysis of both inflation parameters and cosmological parameters taking reheating into account self-consistently. We compute the Bayesian evidence for a few representative inflation scenarios in both the standard ΛCDM model and an extension including dark radiation parametrised by its effective number of relativistic species N {sub eff}. Using a minimal dataset (Planck low-ℓ polarisation, temperature power spectrum and lensing reconstruction), we find that the observational status of most inflationary models is unchanged. The exceptionsmore » are potentials such as power-law inflation that predict large values for the scalar spectral index that can only be realised when N {sub eff} is allowed to vary. Adding baryon acoustic oscillations data and the B-mode data from BICEP2/Keck makes power-law inflation disfavoured, while adding local measurements of the Hubble constant H {sub 0} makes power-law inflation slightly favoured compared to the best single-field plateau potentials. This illustrates how the dark radiation solution to the H {sub 0} tension would have deep consequences for inflation model selection.« less

The development of inflatable array antennas

NASA Technical Reports Server (NTRS)

Huang, J.

2001-01-01

Inflatable array antennas are being developed to significantly reduce the mass, the launch vehicle's stowage volume, and the cost of future spacecraft systems. Three inflatable array antennas, recently developed for spacecraft applications, are a 3.3 m x 1.0 m L-band synthetic-aperture radar (SAR) array, a 1.0 m-diameter X-band telecom reflectarray, and a 3 m-diameter Ka-band telecom reflectarray. All three antennas are similar in construction, and each consists of an inflatable tubular frame that supports and tensions a multi-layer thin-membrane RF radiating surface with printed microstrip patches. The L-band SAR array achieved a bandwidth of 80 MHz, an aperture efficiency of 74%, and a total mass of 15 kg. The X-band reflectarray achieved an aperture efficiency of 37%, good radiation patterns, and a total mass of 1.2 kg (excluding the inflation system). The 3 m Ka-band reflectarray achieved a surface flatness of 0.1 mm RMS, good radiation patterns, and a total mass of 12.8 kg (excluding the inflation system). These antennas demonstrated that inflatable arrays are feasible across the microwave and millimeter-wave spectrums. Further developments of these antennas are deemed necessary, in particular, in the area of qualifying the inflatable structures for space-environment usage.

The inflation sector of extended inflation

NASA Technical Reports Server (NTRS)

Kolb, Edward W.

1991-01-01

In extended inflation, the inflationary era is brought to a close by the process of percolation of true vacuum bubbles produced in a first-order phase transition. This paper discusses several effects that might obtain if the universe undergoes an inflationary first-order phase transition.

Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses.

PubMed

Faul, Franz; Erdfelder, Edgar; Buchner, Axel; Lang, Albert-Georg

2009-11-01

G*Power is a free power analysis program for a variety of statistical tests. We present extensions and improvements of the version introduced by Faul, Erdfelder, Lang, and Buchner (2007) in the domain of correlation and regression analyses. In the new version, we have added procedures to analyze the power of tests based on (1) single-sample tetrachoric correlations, (2) comparisons of dependent correlations, (3) bivariate linear regression, (4) multiple linear regression based on the random predictor model, (5) logistic regression, and (6) Poisson regression. We describe these new features and provide a brief introduction to their scope and handling.

Seeing Double with K2: Testing Re-inflation with Two Remarkably Similar Planets around Red Giant Branch Stars

NASA Astrophysics Data System (ADS)

Grunblatt, Samuel K.; Huber, Daniel; Gaidos, Eric; Lopez, Eric D.; Howard, Andrew W.; Isaacson, Howard T.; Sinukoff, Evan; Vanderburg, Andrew; Nofi, Larissa; Yu, Jie; North, Thomas S. H.; Chaplin, William; Foreman-Mackey, Daniel; Petigura, Erik; Ansdell, Megan; Weiss, Lauren; Fulton, Benjamin; Lin, Douglas N. C.

2017-12-01

Despite more than 20 years since the discovery of the first gas giant planet with an anomalously large radius, the mechanism for planet inflation remains unknown. Here, we report the discovery of K2-132b, an inflated gas giant planet found with the NASA K2 Mission, and a revised mass for another inflated planet, K2-97b. These planets orbit on ≈9 day orbits around host stars that recently evolved into red giants. We constrain the irradiation history of these planets using models constrained by asteroseismology and Keck/High Resolution Echelle Spectrometer spectroscopy and radial velocity measurements. We measure planet radii of 1.31 ± 0.11 R J and 1.30 ± 0.07 R J, respectively. These radii are typical for planets receiving the current irradiation, but not the former, zero age main-sequence irradiation of these planets. This suggests that the current sizes of these planets are directly correlated to their current irradiation. Our precise constraints of the masses and radii of the stars and planets in these systems allow us to constrain the planetary heating efficiency of both systems as 0.03{ % }-0.02 % +0.03 % . These results are consistent with a planet re-inflation scenario, but suggest that the efficiency of planet re-inflation may be lower than previously theorized. Finally, we discuss the agreement within 10% of the stellar masses and radii, and the planet masses, radii, and orbital periods of both systems, and speculate that this may be due to selection bias in searching for planets around evolved stars.

[Use of multiple regression models in observational studies (1970-2013) and requirements of the STROBE guidelines in Spanish scientific journals].

PubMed

Real, J; Cleries, R; Forné, C; Roso-Llorach, A; Martínez-Sánchez, J M

In medicine and biomedical research, statistical techniques like logistic, linear, Cox and Poisson regression are widely known. The main objective is to describe the evolution of multivariate techniques used in observational studies indexed in PubMed (1970-2013), and to check the requirements of the STROBE guidelines in the author guidelines in Spanish journals indexed in PubMed. A targeted PubMed search was performed to identify papers that used logistic linear Cox and Poisson models. Furthermore, a review was also made of the author guidelines of journals published in Spain and indexed in PubMed and Web of Science. Only 6.1% of the indexed manuscripts included a term related to multivariate analysis, increasing from 0.14% in 1980 to 12.3% in 2013. In 2013, 6.7, 2.5, 3.5, and 0.31% of the manuscripts contained terms related to logistic, linear, Cox and Poisson regression, respectively. On the other hand, 12.8% of journals author guidelines explicitly recommend to follow the STROBE guidelines, and 35.9% recommend the CONSORT guideline. A low percentage of Spanish scientific journals indexed in PubMed include the STROBE statement requirement in the author guidelines. Multivariate regression models in published observational studies such as logistic regression, linear, Cox and Poisson are increasingly used both at international level, as well as in journals published in Spanish. Copyright © 2015 Sociedad Española de Médicos de Atención Primaria (SEMERGEN). Publicado por Elsevier España, S.L.U. All rights reserved.

Grade Inflation: Metaphor and Reality

ERIC Educational Resources Information Center

Kamber, Richard; Biggs, Mary

2003-01-01

Grade inflation has become a general term for teachers and administrators in recent times and is an ambiguous denomination which needs to be identified. The allegory and reality of grade inflation is discussed.

Developing an Inflatable Solar Array

NASA Technical Reports Server (NTRS)

Malone, Patrick K.; Jankowski, Francis J.; Williams, Geoffery T.; Vendura, George J., Jr.

1992-01-01

Viewgraphs describing the development of an inflatable solar array as part of the Inflatable Torus Solar Array Technology (ITSAT) program are presented. Program phases, overall and subsystem designs, and array deployment are addressed.

Accidental inflation from Kähler uplifting

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

Ben-Dayan, Ido; Westphal, Alexander; Wieck, Clemens

2014-03-01

We analyze the possibility of realizing inflation with a subsequent dS vacuum in the Käahler uplifting scenario. The inclusion of several quantum corrections to the 4d effective action evades previous no-go theorems and allows for construction of simple and successful models of string inflation. The predictions of several benchmark models are in accord with current observations, i.e., a red spectral index, negligible non-gaussianity, and spectral distortions similar to the simplest models of inflation. A particularly interesting subclass of models are ''left-rolling'' ones, where the overall volume of the compactified dimensions shrinks during inflation. We call this phenomenon ''inflation by deflation''more » (IBD), where deflation refers to the internal manifold. This subclass has the appealing features of being insensitive to initial conditions, avoiding the overshooting problem, and allowing for observable running α ∼ 0.012 and enhanced tensor-to-scalar ratio r ∼ 10{sup −5}. The latter results differ significantly from many string inflation models.« less

Development of Inflatable Entry Systems Technologies

NASA Technical Reports Server (NTRS)

Player, Charles J.; Cheatwood, F. McNeil; Corliss, James

2005-01-01

Achieving the objectives of NASA s Vision for Space Exploration will require the development of new technologies, which will in turn require higher fidelity modeling and analysis techniques, and innovative testing capabilities. Development of entry systems technologies can be especially difficult due to the lack of facilities and resources available to test these new technologies in mission relevant environments. This paper discusses the technology development process to bring inflatable aeroshell technology from Technology Readiness Level 2 (TRL-2) to TRL-7. This paper focuses mainly on two projects: Inflatable Reentry Vehicle Experiment (IRVE), and Inflatable Aeroshell and Thermal Protection System Development (IATD). The objectives of IRVE are to conduct an inflatable aeroshell flight test that demonstrates exoatmospheric deployment and inflation, reentry survivability and stability, and predictable drag performance. IATD will continue the development of the technology by conducting exploration specific trade studies and feeding forward those results into three more flight tests. Through an examination of these projects, and other potential projects, this paper discusses some of the risks, issues, and unexpected benefits associated with the development of inflatable entry systems technology.

When Parents' Praise Inflates, Children's Self-Esteem Deflates.

PubMed

Brummelman, Eddie; Nelemans, Stefanie A; Thomaes, Sander; Orobio de Castro, Bram

2017-11-01

Western parents often give children overly positive, inflated praise. One perspective holds that inflated praise sets unattainable standards for children, eventually lowering children's self-esteem (self-deflation hypothesis). Another perspective holds that children internalize inflated praise to form narcissistic self-views (self-inflation hypothesis). These perspectives were tested in an observational-longitudinal study (120 parent-child dyads from the Netherlands) in late childhood (ages 7-11), when narcissism and self-esteem first emerge. Supporting the self-deflation hypothesis, parents' inflated praise predicted lower self-esteem in children. Partly supporting the self-inflation hypothesis, parents' inflated praise predicted higher narcissism-but only in children with high self-esteem. Noninflated praise predicted neither self-esteem nor narcissism. Thus, inflated praise may foster the self-views it seeks to prevent. © 2017 The Authors. Child Development © 2017 Society for Research in Child Development, Inc.

Analysis of overdispersed count data by mixtures of Poisson variables and Poisson processes.

PubMed

Hougaard, P; Lee, M L; Whitmore, G A

1997-12-01

Count data often show overdispersion compared to the Poisson distribution. Overdispersion is typically modeled by a random effect for the mean, based on the gamma distribution, leading to the negative binomial distribution for the count. This paper considers a larger family of mixture distributions, including the inverse Gaussian mixture distribution. It is demonstrated that it gives a significantly better fit for a data set on the frequency of epileptic seizures. The same approach can be used to generate counting processes from Poisson processes, where the rate or the time is random. A random rate corresponds to variation between patients, whereas a random time corresponds to variation within patients.

Poisson denoising on the sphere

NASA Astrophysics Data System (ADS)

Schmitt, J.; Starck, J. L.; Fadili, J.; Grenier, I.; Casandjian, J. M.

2009-08-01

In the scope of the Fermi mission, Poisson noise removal should improve data quality and make source detection easier. This paper presents a method for Poisson data denoising on sphere, called Multi-Scale Variance Stabilizing Transform on Sphere (MS-VSTS). This method is based on a Variance Stabilizing Transform (VST), a transform which aims to stabilize a Poisson data set such that each stabilized sample has an (asymptotically) constant variance. In addition, for the VST used in the method, the transformed data are asymptotically Gaussian. Thus, MS-VSTS consists in decomposing the data into a sparse multi-scale dictionary (wavelets, curvelets, ridgelets...), and then applying a VST on the coefficients in order to get quasi-Gaussian stabilized coefficients. In this present article, the used multi-scale transform is the Isotropic Undecimated Wavelet Transform. Then, hypothesis tests are made to detect significant coefficients, and the denoised image is reconstructed with an iterative method based on Hybrid Steepest Descent (HST). The method is tested on simulated Fermi data.

Relaxed Poisson cure rate models.

PubMed

Rodrigues, Josemar; Cordeiro, Gauss M; Cancho, Vicente G; Balakrishnan, N

2016-03-01

The purpose of this article is to make the standard promotion cure rate model (Yakovlev and Tsodikov, ) more flexible by assuming that the number of lesions or altered cells after a treatment follows a fractional Poisson distribution (Laskin, ). It is proved that the well-known Mittag-Leffler relaxation function (Berberan-Santos, ) is a simple way to obtain a new cure rate model that is a compromise between the promotion and geometric cure rate models allowing for superdispersion. So, the relaxed cure rate model developed here can be considered as a natural and less restrictive extension of the popular Poisson cure rate model at the cost of an additional parameter, but a competitor to negative-binomial cure rate models (Rodrigues et al., ). Some mathematical properties of a proper relaxed Poisson density are explored. A simulation study and an illustration of the proposed cure rate model from the Bayesian point of view are finally presented. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Biases and Standard Errors of Standardized Regression Coefficients

ERIC Educational Resources Information Center

Yuan, Ke-Hai; Chan, Wai

2011-01-01

The paper obtains consistent standard errors (SE) and biases of order O(1/n) for the sample standardized regression coefficients with both random and given predictors. Analytical results indicate that the formulas for SEs given in popular text books are consistent only when the population value of the regression coefficient is zero. The sample…

Constant-roll tachyon inflation and observational constraints

NASA Astrophysics Data System (ADS)

Gao, Qing; Gong, Yungui; Fei, Qin

2018-05-01

For the constant-roll tachyon inflation, we derive the analytical expressions for the scalar and tensor power spectra, the scalar and tensor spectral tilts and the tensor to scalar ratio to the first order of epsilon1 by using the method of Bessel function approximation. The derived ns-r results are compared with the observations, we find that only the constant-roll inflation with ηH being a constant is consistent with the observations and observations constrain the constant-roll inflation to be slow-roll inflation. The tachyon potential is also reconstructed for the constant-roll inflation which is consistent with the observations.

Inflation data clustering of some cities in Indonesia

NASA Astrophysics Data System (ADS)

Setiawan, Adi; Susanto, Bambang; Mahatma, Tundjung

2017-06-01

In this paper, it is presented how to cluster inflation data of cities in Indonesia by using k-means cluster method and fuzzy c-means method. The data that are used is limited to the monthly inflation data from 15 cities across Indonesia which have highest weight of donations and is supplemented with 5 cities used in the calculation of inflation in Indonesia. When they are applied into two clusters with k = 2 for k-means cluster method and c = 2, w = 1.25 for fuzzy c-means cluster method, Ambon, Manado and Jayapura tend to become one cluster (high inflation) meanwhile other cities tend to become members of other cluster (low inflation). However, if they are applied into two clusters with c=2, w=1.5, Surabaya, Medan, Makasar, Samarinda, Makasar, Manado, Ambon dan Jayapura tend to become one cluster (high inflation) meanwhile other cities tend to become members of other cluster (low inflation). Furthermore, when we use two clusters with k=3 for k-means cluster method and c=3, w = 1.25 for fuzzy c-means cluster method, Ambon tends to become member of first cluster (high inflation), Manado and Jayapura tend to become member of second cluster (moderate inflation), other cities tend to become members of third cluster (low inflation). If it is applied c=3, w = 1.5, Ambon, Manado and Jayapura tend to become member of first cluster (high inflation), Surabaya, Bandung, Medan, Makasar, Banyuwangi, Denpasar, Samarinda dan Mataram tend to become members of second cluster (moderate inflation), meanwhile other cities tend to become members of third cluster (low inflation). Similarly, interpretation can be made to the results of applying 5 clusters.

DL_MG: A Parallel Multigrid Poisson and Poisson-Boltzmann Solver for Electronic Structure Calculations in Vacuum and Solution.

PubMed

Womack, James C; Anton, Lucian; Dziedzic, Jacek; Hasnip, Phil J; Probert, Matt I J; Skylaris, Chris-Kriton

2018-03-13

The solution of the Poisson equation is a crucial step in electronic structure calculations, yielding the electrostatic potential-a key component of the quantum mechanical Hamiltonian. In recent decades, theoretical advances and increases in computer performance have made it possible to simulate the electronic structure of extended systems in complex environments. This requires the solution of more complicated variants of the Poisson equation, featuring nonhomogeneous dielectric permittivities, ionic concentrations with nonlinear dependencies, and diverse boundary conditions. The analytic solutions generally used to solve the Poisson equation in vacuum (or with homogeneous permittivity) are not applicable in these circumstances, and numerical methods must be used. In this work, we present DL_MG, a flexible, scalable, and accurate solver library, developed specifically to tackle the challenges of solving the Poisson equation in modern large-scale electronic structure calculations on parallel computers. Our solver is based on the multigrid approach and uses an iterative high-order defect correction method to improve the accuracy of solutions. Using two chemically relevant model systems, we tested the accuracy and computational performance of DL_MG when solving the generalized Poisson and Poisson-Boltzmann equations, demonstrating excellent agreement with analytic solutions and efficient scaling to ∼10 9 unknowns and 100s of CPU cores. We also applied DL_MG in actual large-scale electronic structure calculations, using the ONETEP linear-scaling electronic structure package to study a 2615 atom protein-ligand complex with routinely available computational resources. In these calculations, the overall execution time with DL_MG was not significantly greater than the time required for calculations using a conventional FFT-based solver.

An analysis of input errors in precipitation-runoff models using regression with errors in the independent variables

USGS Publications Warehouse

Troutman, Brent M.

1982-01-01

Errors in runoff prediction caused by input data errors are analyzed by treating precipitation-runoff models as regression (conditional expectation) models. Independent variables of the regression consist of precipitation and other input measurements; the dependent variable is runoff. In models using erroneous input data, prediction errors are inflated and estimates of expected storm runoff for given observed input variables are biased. This bias in expected runoff estimation results in biased parameter estimates if these parameter estimates are obtained by a least squares fit of predicted to observed runoff values. The problems of error inflation and bias are examined in detail for a simple linear regression of runoff on rainfall and for a nonlinear U.S. Geological Survey precipitation-runoff model. Some implications for flood frequency analysis are considered. A case study using a set of data from Turtle Creek near Dallas, Texas illustrates the problems of model input errors.

A Note on the Relationship between the Number of Indicators and Their Reliability in Detecting Regression Coefficients in Latent Regression Analysis

ERIC Educational Resources Information Center

Dolan, Conor V.; Wicherts, Jelte M.; Molenaar, Peter C. M.

2004-01-01

We consider the question of how variation in the number and reliability of indicators affects the power to reject the hypothesis that the regression coefficients are zero in latent linear regression analysis. We show that power remains constant as long as the coefficient of determination remains unchanged. Any increase in the number of indicators…

Scalar-tensor linear inflation

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

Artymowski, Michał; Racioppi, Antonio, E-mail: Michal.Artymowski@uj.edu.pl, E-mail: Antonio.Racioppi@kbfi.ee

2017-04-01

We investigate two approaches to non-minimally coupled gravity theories which present linear inflation as attractor solution: a) the scalar-tensor theory approach, where we look for a scalar-tensor theory that would restore results of linear inflation in the strong coupling limit for a non-minimal coupling to gravity of the form of f (φ) R /2; b) the particle physics approach, where we motivate the form of the Jordan frame potential by loop corrections to the inflaton field. In both cases the Jordan frame potentials are modifications of the induced gravity inflationary scenario, but instead of the Starobinsky attractor they lead tomore » linear inflation in the strong coupling limit.« less

Mars inflatable greenhouse analog.

PubMed

Sadler, Philip D; Giacomelli, Gene A

2002-01-01

Light intensities on the Martian surface can possibly support a bioregenerative life support system (BLSS) utilizing natural sunlight for hydroponic crop production, if a suitable controlled environment can be provided. Inflatable clear membrane structures offer low mass, are more easily transported than a rigid structure, and are good candidates for providing a suitable controlled environment for crop production. Cable culture is one hydroponic growing system that can take advantage of the beneficial attributes of the inflatable structure. An analog of a Mars inflatable greenhouse can provide researchers data on issues such as crew time requirements for operation, productivity for BLSS, human factors, and much more at a reasonable cost. This is a description of one such design.

Beyond Inflation:. A Cyclic Universe Scenario

NASA Astrophysics Data System (ADS)

Turok, Neil; Steinhardt, Paul J.

2005-08-01

Inflation has been the leading early universe scenario for two decades, and has become an accepted element of the successful 'cosmic concordance' model. However, there are many puzzling features of the resulting theory. It requires both high energy and low energy inflation, with energy densities differing by a hundred orders of magnitude. The questions of why the universe started out undergoing high energy inflation, and why it will end up in low energy inflation, are unanswered. Rather than resort to anthropic arguments, we have developed an alternative cosmology, the cyclic universe [1], in which the universe exists in a very long-lived attractor state determined by the laws of physics. The model shares inflation's phenomenological successes without requiring an epoch of high energy inflation. Instead, the universe is made homogeneous and flat, and scale-invariant adiabatic perturbations are generated during an epoch of low energy acceleration like that seen today, but preceding the last big bang. Unlike inflation, the model requires low energy acceleration in order for a periodic attractor state to exist. The key challenge facing the scenario is that of passing through the cosmic singularity at t = 0. Substantial progress has been made at the level of linearised gravity, which is reviewed here. The challenge of extending this to nonlinear gravity and string theory remains.

Beyond Inflation: A Cyclic Universe Scenario

NASA Astrophysics Data System (ADS)

Turok, Neil; Steinhardt, Paul J.

2005-01-01

Inflation has been the leading early universe scenario for two decades, and has become an accepted element of the successful `cosmic concordance' model. However, there are many puzzling features of the resulting theory. It requires both high energy and low energy inflation, with energy densities differing by a hundred orders of magnitude. The questions of why the universe started out undergoing high energy inflation, and why it will end up in low energy inflation, are unanswered. Rather than resort to anthropic arguments, we have developed an alternative cosmology, the cyclic universe, in which the universe exists in a very long-lived attractor state determined by the laws of physics. The model shares inflation's phenomenological successes without requiring an epoch of high energy inflation. Instead, the universe is made homogeneous and flat, and scale-invariant adiabatic perturbations are generated during an epoch of low energy acceleration like that seen today, but preceding the last big bang. Unlike inflation, the model requires low energy acceleration in order for a periodic attractor state to exist. The key challenge facing the scenario is that of passing through the cosmic singularity at t = 0. Substantial progress has been made at the level of linearised gravity, which is reviewed here. The challenge of extending this to nonlinear gravity and string theory remains.

Deformation mechanisms in negative Poisson's ratio materials - Structural aspects

NASA Technical Reports Server (NTRS)

Lakes, R.

1991-01-01

Poisson's ratio in materials is governed by the following aspects of the microstructure: the presence of rotational degrees of freedom, non-affine deformation kinematics, or anisotropic structure. Several structural models are examined. The non-affine kinematics are seen to be essential for the production of negative Poisson's ratios for isotropic materials containing central force linkages of positive stiffness. Non-central forces combined with pre-load can also give rise to a negative Poisson's ratio in isotropic materials. A chiral microstructure with non-central force interaction or non-affine deformation can also exhibit a negative Poisson's ratio. Toughness and damage resistance in these materials may be affected by the Poisson's ratio itself, as well as by generalized continuum aspects associated with the microstructure.

Robustness of inflation to inhomogeneous initial conditions

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

Clough, Katy; Lim, Eugene A.; DiNunno, Brandon S.

We consider the effects of inhomogeneous initial conditions in both the scalar field profile and the extrinsic curvature on different inflationary models. In particular, we compare the robustness of small field inflation to that of large field inflation, using numerical simulations with Einstein gravity in 3+1 dimensions. We find that small field inflation can fail in the presence of subdominant gradient energies, suggesting that it is much less robust to inhomogeneities than large field inflation, which withstands dominant gradient energies. However, we also show that small field inflation can be successful even if some regions of spacetime start out inmore » the region of the potential that does not support inflation. In the large field case, we confirm previous results that inflation is robust if the inflaton occupies the inflationary part of the potential. Furthermore, we show that increasing initial scalar gradients will not form sufficiently massive inflation-ending black holes if the initial hypersurface is approximately flat. Finally, we consider the large field case with a varying extrinsic curvature K , such that some regions are initially collapsing. We find that this may again lead to local black holes, but overall the spacetime remains inflationary if the spacetime is open, which confirms previous theoretical studies.« less

Robustness of inflation to inhomogeneous initial conditions

NASA Astrophysics Data System (ADS)

Clough, Katy; Lim, Eugene A.; DiNunno, Brandon S.; Fischler, Willy; Flauger, Raphael; Paban, Sonia

2017-09-01

We consider the effects of inhomogeneous initial conditions in both the scalar field profile and the extrinsic curvature on different inflationary models. In particular, we compare the robustness of small field inflation to that of large field inflation, using numerical simulations with Einstein gravity in 3+1 dimensions. We find that small field inflation can fail in the presence of subdominant gradient energies, suggesting that it is much less robust to inhomogeneities than large field inflation, which withstands dominant gradient energies. However, we also show that small field inflation can be successful even if some regions of spacetime start out in the region of the potential that does not support inflation. In the large field case, we confirm previous results that inflation is robust if the inflaton occupies the inflationary part of the potential. Furthermore, we show that increasing initial scalar gradients will not form sufficiently massive inflation-ending black holes if the initial hypersurface is approximately flat. Finally, we consider the large field case with a varying extrinsic curvature K, such that some regions are initially collapsing. We find that this may again lead to local black holes, but overall the spacetime remains inflationary if the spacetime is open, which confirms previous theoretical studies.

Spatio-temporal patterns of gun violence in Syracuse, New York 2009-2015.

PubMed

Larsen, David A; Lane, Sandra; Jennings-Bey, Timothy; Haygood-El, Arnett; Brundage, Kim; Rubinstein, Robert A

2017-01-01

Gun violence in the United States of America is a large public health problem that disproportionately affects urban areas. The epidemiology of gun violence reflects various aspects of an infectious disease including spatial and temporal clustering. We examined the spatial and temporal trends of gun violence in Syracuse, New York, a city of 145,000. We used a spatial scan statistic to reveal spatio-temporal clusters of gunshots investigated and corroborated by Syracuse City Police Department for the years 2009-2015. We also examined predictors of areas with increased gun violence using a multi-level zero-inflated Poisson regression with data from the 2010 census. Two space-time clusters of gun violence were revealed in the city. Higher rates of segregation, poverty and the summer months were all associated with increased risk of gun violence. Previous gunshots in the area were associated with a 26.8% increase in the risk of gun violence. Gun violence in Syracuse, NY is both spatially and temporally stable, with some neighborhoods of the city greatly afflicted.

Novel Phenotype Issues Raised in Cross-National Epidemiological Research on Drug Dependence

PubMed Central

Anthony, James C.

2010-01-01

Stage-transition models based on the American Diagnostic and Statistical Manual (DSM) generally are applied in epidemiology and genetics research on drug dependence syndromes associated with cannabis, cocaine, and other internationally regulated drugs (IRD). Difficulties with DSM stage-transition models have surfaced during cross-national research intended to provide a truly global perspective, such as the work of the World Mental Health Surveys (WMHS) Consortium. Alternative simpler dependence-related phenotypes are possible, including population-level count process models for steps early and before coalescence of clinical features into a coherent syndrome (e.g., zero-inflated Poisson regression). Selected findings are reviewed, based on ZIP modeling of alcohol, tobacco, and IRD count processes, with an illustration that may stimulate new research on genetic susceptibility traits. The annual National Surveys on Drug Use and Health can be readily modified for this purpose, along the lines of a truly anonymous research approach that can help make NSDUH-type cross-national epidemiological surveys more useful in the context of subsequent genome wide association (GWAS) research and post-GWAS investigations with a truly global health perspective. PMID:20201862

Spatio-temporal patterns of gun violence in Syracuse, New York 2009-2015

PubMed Central

Lane, Sandra; Jennings-Bey, Timothy; Haygood-El, Arnett; Brundage, Kim; Rubinstein, Robert A.

2017-01-01

Gun violence in the United States of America is a large public health problem that disproportionately affects urban areas. The epidemiology of gun violence reflects various aspects of an infectious disease including spatial and temporal clustering. We examined the spatial and temporal trends of gun violence in Syracuse, New York, a city of 145,000. We used a spatial scan statistic to reveal spatio-temporal clusters of gunshots investigated and corroborated by Syracuse City Police Department for the years 2009–2015. We also examined predictors of areas with increased gun violence using a multi-level zero-inflated Poisson regression with data from the 2010 census. Two space-time clusters of gun violence were revealed in the city. Higher rates of segregation, poverty and the summer months were all associated with increased risk of gun violence. Previous gunshots in the area were associated with a 26.8% increase in the risk of gun violence. Gun violence in Syracuse, NY is both spatially and temporally stable, with some neighborhoods of the city greatly afflicted. PMID:28319125

Noncommutative gauge theory for Poisson manifolds

NASA Astrophysics Data System (ADS)

Jurčo, Branislav; Schupp, Peter; Wess, Julius

2000-09-01

A noncommutative gauge theory is associated to every Abelian gauge theory on a Poisson manifold. The semi-classical and full quantum version of the map from the ordinary gauge theory to the noncommutative gauge theory (Seiberg-Witten map) is given explicitly to all orders for any Poisson manifold in the Abelian case. In the quantum case the construction is based on Kontsevich's formality theorem.

Self-reproduction in k-inflation

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

Helmer, Ferdinand; Winitzki, Sergei

2006-09-15

We study cosmological self-reproduction in models of inflation driven by a scalar field {phi} with a noncanonical kinetic term (k-inflation). We develop a general criterion for the existence of attractors and establish conditions selecting a class of k-inflation models that admit a unique attractor solution. We then consider quantum fluctuations on the attractor background. We show that the correlation length of the fluctuations is of order c{sub s}H{sup -1}, where c{sub s} is the speed of sound. By computing the magnitude of field fluctuations, we determine the coefficients of Fokker-Planck equations describing the probability distribution of the spatially averaged fieldmore » {phi}. The field fluctuations are generally large in the inflationary attractor regime; hence, eternal self-reproduction is a generic feature of k-inflation. This is established more formally by demonstrating the existence of stationary solutions of the relevant Fokker-Planck equations. We also show that there exists a (model-dependent) range {phi}{sub R}<{phi}<{phi}{sub max} within which large fluctuations are likely to drive the field towards the upper boundary {phi}={phi}{sub max}, where the semiclassical consideration breaks down. An exit from inflation into reheating without reaching {phi}{sub max} will occur almost surely (with probability 1) only if the initial value of {phi} is below {phi}{sub R}. In this way, strong self-reproduction effects constrain models of k-inflation.« less

The comparison of robust partial least squares regression with robust principal component regression on a real

NASA Astrophysics Data System (ADS)

Polat, Esra; Gunay, Suleyman

2013-10-01

One of the problems encountered in Multiple Linear Regression (MLR) is multicollinearity, which causes the overestimation of the regression parameters and increase of the variance of these parameters. Hence, in case of multicollinearity presents, biased estimation procedures such as classical Principal Component Regression (CPCR) and Partial Least Squares Regression (PLSR) are then performed. SIMPLS algorithm is the leading PLSR algorithm because of its speed, efficiency and results are easier to interpret. However, both of the CPCR and SIMPLS yield very unreliable results when the data set contains outlying observations. Therefore, Hubert and Vanden Branden (2003) have been presented a robust PCR (RPCR) method and a robust PLSR (RPLSR) method called RSIMPLS. In RPCR, firstly, a robust Principal Component Analysis (PCA) method for high-dimensional data on the independent variables is applied, then, the dependent variables are regressed on the scores using a robust regression method. RSIMPLS has been constructed from a robust covariance matrix for high-dimensional data and robust linear regression. The purpose of this study is to show the usage of RPCR and RSIMPLS methods on an econometric data set, hence, making a comparison of two methods on an inflation model of Turkey. The considered methods have been compared in terms of predictive ability and goodness of fit by using a robust Root Mean Squared Error of Cross-validation (R-RMSECV), a robust R2 value and Robust Component Selection (RCS) statistic.

Inflatable Dark Matter.

PubMed

Davoudiasl, Hooman; Hooper, Dan; McDermott, Samuel D

2016-01-22

We describe a general scenario, dubbed "inflatable dark matter," in which the density of dark matter particles can be reduced through a short period of late-time inflation in the early Universe. The overproduction of dark matter that is predicted within many, otherwise, well-motivated models of new physics can be elegantly remedied within this context. Thermal relics that would, otherwise, be disfavored can easily be accommodated within this class of scenarios, including dark matter candidates that are very heavy or very light. Furthermore, the nonthermal abundance of grand unified theory or Planck scale axions can be brought to acceptable levels without invoking anthropic tuning of initial conditions. A period of late-time inflation could have occurred over a wide range of scales from ∼MeV to the weak scale or above, and could have been triggered by physics within a hidden sector, with small but not necessarily negligible couplings to the standard model.

Model with two periods of inflation

NASA Astrophysics Data System (ADS)

Schettler, Simon; Schaffner-Bielich, Jürgen

2016-01-01

A scenario with two subsequent periods of inflationary expansion in the very early Universe is examined. The model is based on a potential motivated by symmetries being found in field theory at high energy. For various parameter sets of the potential, the spectra of scalar and tensor perturbations that are expected to originate from this scenario are calculated. Also the beginning of the reheating epoch connecting the second inflation with thermal equilibrium is studied. Perturbations with wavelengths leaving the horizon around the transition between the two inflations are special: It is demonstrated that the power spectrum at such scales deviates significantly from expectations based on measurements of the cosmic microwave background. This supports the conclusion that parameters for which this part of the spectrum leaves observable traces in the cosmic microwave background must be excluded. Parameters entailing a very efficient second inflation correspond to standard small-field inflation and can meet observational constraints. Particular attention is paid to the case where the second inflation leads solely to a shift of the observable spectrum from the first inflation. A viable scenario requires this shift to be small.

Inflatable Personal Flotation Device Study.

DTIC Science & Technology

1981-02-01

late. t, h Iw . No cood (1) - CVider would not Ipu, tore 1t) - ( I\\ inder d idn ’t punk t n- t . Tried several times. Lost belt in lake, Lr ic - caIIt...dii not respond as expected (1) 6. (C) - When C02 cylinder is used to inflate, all the snaps do not pop open (1) - No event (1) - When inflated it is...Upon inflation, the snap closest to my face popped , striking my hand and face (1) - Device rode up over back of head in rough water (1) - None (1

Accidental Kähler moduli inflation

NASA Astrophysics Data System (ADS)

Maharana, Anshuman; Rummel, Markus; Sumitomo, Yoske

2015-09-01

We study a model of accidental inflation in type IIB string theory where inflation occurs near the inflection point of a small Kähler modulus. A racetrack structure helps to alleviate the known concern that string-loop corrections may spoil Kähler Moduli Inflation unless having a significant suppression via the string coupling or a special brane setup. Also, the hierarchy of gauge group ranks required for the separation between moduli stabilization and inflationary dynamics is relaxed. The relaxation becomes more significant when we use the recently proposed D-term generated racetrack model.

Aerocapture Inflatable Decelerator for Planetary Entry

NASA Technical Reports Server (NTRS)

Reza, Sajjad; Hund, Richard; Kustas, Frank; Willcockson, William; Songer, Jarvis; Brown, Glen

2007-01-01

Forward Attached Inflatable Decelerators, more commonly known as inflatable aeroshells, provide an effective, cost efficient means of decelerating spacecrafts by using atmospheric drag for aerocapture or planetary entry instead of conventional liquid propulsion deceleration systems. Entry into planetary atmospheres results in significant heating and aerodynamic pressures which stress aeroshell systems to their useful limits. Incorporation of lightweight inflatable decelerator surfaces with increased surface-area footprints provides the opportunity to reduce heat flux and induced temperatures, while increasing the payload mass fraction. Furthermore, inflatable aeroshell decelerators provide the needed deceleration at considerably higher altitudes and Mach numbers when compared with conventional rigid aeroshell entry systems. Inflatable aeroshells also provide for stowage in a compact space, with subsequent deployment of a large-area, lightweight heatshield to survive entry heating. Use of a deployable heatshield decelerator enables an increase in the spacecraft payload mass fraction and may eliminate the need for a spacecraft backshell.

Primordial perturbations in multi-scalar inflation

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

Abedi, Habib; Abbassi, Amir M., E-mail: h.abedi@ut.ac.ir, E-mail: amabasi@khayam.ut.ac.ir

2017-07-01

Multiple field models of inflation exhibit new features than single field models. In this work, we study the hierarchy of parameters based on Hubble expansion rate in curved field space and derive the system of flow equations that describe their evolutions. Then we focus on obtaining derivatives of number of e-folds with respect to scalar fields during inflation and at hypersurface of the end of inflation.

Inflation of Unreefed and Reefed Extraction Parachutes

NASA Technical Reports Server (NTRS)

Ray, Eric S.; Varela, Jose G.

2015-01-01

Data from the Orion and several other test programs have been used to reconstruct inflation parameters for 28 ft Do extraction parachutes as well as the parent aircraft pitch response during extraction. The inflation force generated by extraction parachutes is recorded directly during tow tests but is usually inferred from the payload accelerometer during Low Velocity Airdrop Delivery (LVAD) flight test extractions. Inflation parameters are dependent on the type of parent aircraft, number of canopies, and standard vs. high altitude extraction conditions. For standard altitudes, single canopy inflations are modeled as infinite mass, but the non-symmetric inflations in a cluster are modeled as finite mass. High altitude extractions have necessitated reefing the extraction parachutes, which are best modeled as infinite mass for those conditions. Distributions of aircraft pitch profiles and inflation parameters have been generated for use in Monte Carlo simulations of payload extractions.

STS-45 crewmembers during zero gravity activities onboard KC-135 NASA 930

NASA Technical Reports Server (NTRS)

1991-01-01

STS-45 Atlantis, Orbiter Vehicle (OV) 104, crewmembers and backup payload specialist participate in zero gravity activities onboard KC-135 NASA 930. The crewmembers, wearing flight suits, float and tumble around an inflated globe during the few seconds of microgravity created by parabolic flight. With his hand on the fuselage ceiling is Payload Specialist Dirk D. Frimout. Clockwise from his position are Mission Specialist (MS) C. Michael Foale, Pilot Brian Duffy, backup Payload Specialist Charles R. Chappell, MS and Payload Commander (PLC) Kathryn D. Sullivan (with eye glasses), Commander Charles F. Bolden, and Payload Specialist Byron K. Lichtenberg.

Clockwork inflation

NASA Astrophysics Data System (ADS)

Kehagias, Alex; Riotto, Antonio

2017-04-01

We investigate the recently proposed clockwork mechanism delivering light degrees of freedom with suppressed interactions and show, with various examples, that it can be efficiently implemented in inflationary scenarios to generate flat inflaton potentials and small density perturbations without fine-tunings. We also study the clockwork graviton in de Sitter and, interestingly, we find that the corresponding clockwork charge is site-dependent. As a consequence, the amount of tensor modes is generically suppressed with respect to the standard cases where the clockwork set-up is not adopted. This point can be made a virtue in resurrecting models of inflation which were supposed to be ruled out because of the excessive amount of tensor modes from inflation.

Trapped Inflation

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

Green, Daniel; Horn, Bart; /SLAC /Stanford U., Phys. Dept.

2009-06-19

We analyze a distinctive mechanism for inflation in which particle production slows down a scalar field on a steep potential, and show how it descends from angular moduli in string compactifications. The analysis of density perturbations - taking into account the integrated effect of the produced particles and their quantum fluctuations - requires somewhat new techniques that we develop. We then determine the conditions for this effect to produce sixty e-foldings of inflation with the correct amplitude of density perturbations at the Gaussian level, and show that these requirements can be straightforwardly satisfied. Finally, we estimate the amplitude of themore » non-Gaussianity in the power spectrum and find a significant equilateral contribution.« less

Saint-Venant end effects for materials with negative Poisson's ratios

NASA Technical Reports Server (NTRS)

Lakes, R. S.

1992-01-01

Results are presented from an analysis of Saint-Venant end effects for materials with negative Poisson's ratio. Examples are presented showing that slow decay of end stress occurs in circular cylinders of negative Poisson's ratio, whereas a sandwich panel containing rigid face sheets and a compliant core exhibits no anomalous effects for negative Poisson's ratio (but exhibits slow stress decay for core Poisson's ratios approaching 0.5). In sand panels with stiff but not perfectly rigid face sheets, a negative Poisson's ratio results in end stress decay, which is faster than it would be otherwise. It is suggested that the slow decay previously predicted for sandwich strips in plane deformation as a result of the geometry can be mitigated by the use of a negative Poisson's ratio material for the core.

Coronary artery calcium distributions in older persons in the AGES-Reykjavik study

PubMed Central

Gudmundsson, Elias Freyr; Gudnason, Vilmundur; Sigurdsson, Sigurdur; Launer, Lenore J.; Harris, Tamara B.; Aspelund, Thor

2013-01-01

Coronary Artery Calcium (CAC) is a sign of advanced atherosclerosis and an independent risk factor for cardiac events. Here, we describe CAC-distributions in an unselected aged population and compare modelling methods to characterize CAC-distribution. CAC is difficult to model because it has a skewed and zero inflated distribution with over-dispersion. Data are from the AGES-Reykjavik sample, a large population based study [2002-2006] in Iceland of 5,764 persons aged 66-96 years. Linear regressions using logarithmic- and Box-Cox transformations on CAC+1, quantile regression and a Zero-Inflated Negative Binomial model (ZINB) were applied. Methods were compared visually and with the PRESS-statistic, R2 and number of detected associations with concurrently measured variables. There were pronounced differences in CAC according to sex, age, history of coronary events and presence of plaque in the carotid artery. Associations with conventional coronary artery disease (CAD) risk factors varied between the sexes. The ZINB model provided the best results with respect to the PRESS-statistic, R2, and predicted proportion of zero scores. The ZINB model detected similar numbers of associations as the linear regression on ln(CAC+1) and usually with the same risk factors. PMID:22990371

Open inflation in the landscape

NASA Astrophysics Data System (ADS)

Yamauchi, Daisuke; Linde, Andrei; Naruko, Atsushi; Sasaki, Misao; Tanaka, Takahiro

2011-08-01

The open inflation scenario is attracting a renewed interest in the context of the string landscape. Since there are a large number of metastable de Sitter vacua in the string landscape, tunneling transitions to lower metastable vacua through the bubble nucleation occur quite naturally, which leads to a natural realization of open inflation. Although the deviation of Ω0 from unity is small by the observational bound, we argue that the effect of this small deviation on the large-angle CMB anisotropies can be significant for tensor-type perturbation in the open inflation scenario. We consider the situation in which there is a large hierarchy between the energy scale of the quantum tunneling and that of the slow-roll inflation in the nucleated bubble. If the potential just after tunneling is steep enough, a rapid-roll phase appears before the slow-roll inflation. In this case the power spectrum is basically determined by the Hubble rate during the slow-roll inflation. On the other hand, if such a rapid-roll phase is absent, the power spectrum keeps the memory of the high energy density there in the large angular components. Furthermore, the amplitude of large angular components can be enhanced due to the effects of the wall fluctuation mode if the bubble wall tension is small. Therefore, although even the dominant quadrupole component is suppressed by the factor (1-Ω0)2, one can construct some models in which the deviation of Ω0 from unity is large enough to produce measurable effects. We also consider a more general class of models, where the false vacuum decay may occur due to Hawking-Moss tunneling, as well as the models involving more than one scalar field. We discuss scalar perturbations in these models and point out that a large set of such models is already ruled out by observational data, unless there was a very long stage of slow-roll inflation after the tunneling. These results show that observational data allow us to test various assumptions concerning

Scaling the Poisson Distribution

ERIC Educational Resources Information Center

Farnsworth, David L.

2014-01-01

We derive the additive property of Poisson random variables directly from the probability mass function. An important application of the additive property to quality testing of computer chips is presented.

Symmetry breaking patterns for inflation

NASA Astrophysics Data System (ADS)

Klein, Remko; Roest, Diederik; Stefanyszyn, David

2018-06-01

We study inflationary models where the kinetic sector of the theory has a non-linearly realised symmetry which is broken by the inflationary potential. We distinguish between kinetic symmetries which non-linearly realise an internal or space-time group, and which yield a flat or curved scalar manifold. This classification leads to well-known inflationary models such as monomial inflation and α-attractors, as well as a new model based on fixed couplings between a dilaton and many axions which non-linearly realises higher-dimensional conformal symmetries. In this model, inflation can be realised along the dilatonic direction, leading to a tensor-to-scalar ratio r ˜ 0 .01 and a spectral index n s ˜ 0 .975. We refer to the new model as ambient inflation since inflation proceeds along an isometry of an anti-de Sitter ambient space-time, which fully determines the kinetic sector.

Reprint of "Modelling the influence of temperature and rainfall on malaria incidence in four endemic provinces of Zambia using semiparametric Poisson regression".

PubMed

Shimaponda-Mataa, Nzooma M; Tembo-Mwase, Enala; Gebreslasie, Michael; Achia, Thomas N O; Mukaratirwa, Samson

2017-11-01

Although malaria morbidity and mortality are greatly reduced globally owing to great control efforts, the disease remains the main contributor. In Zambia, all provinces are malaria endemic. However, the transmission intensities vary mainly depending on environmental factors as they interact with the vectors. Generally in Africa, possibly due to the varying perspectives and methods used, there is variation on the relative importance of malaria risk determinants. In Zambia, the role climatic factors play on malaria case rates has not been determined in combination of space and time using robust methods in modelling. This is critical considering the reversal in malaria reduction after the year 2010 and the variation by transmission zones. Using a geoadditive or structured additive semiparametric Poisson regression model, we determined the influence of climatic factors on malaria incidence in four endemic provinces of Zambia. We demonstrate a strong positive association between malaria incidence and precipitation as well as minimum temperature. The risk of malaria was 95% lower in Lusaka (ARR=0.05, 95% CI=0.04-0.06) and 68% lower in the Western Province (ARR=0.31, 95% CI=0.25-0.41) compared to Luapula Province. North-western Province did not vary from Luapula Province. The effects of geographical region are clearly demonstrated by the unique behaviour and effects of minimum and maximum temperatures in the four provinces. Environmental factors such as landscape in urbanised places may also be playing a role. Copyright © 2017 Elsevier B.V. All rights reserved.

Identification of a Class of Filtered Poisson Processes.

DTIC Science & Technology

1981-01-01

LD-A135 371 IDENTIFICATION OF A CLASS OF FILERED POISSON PROCESSES I AU) NORTH CAROLINA UNIV AT CHAPEL HIL DEPT 0F STATISTICS D DE RRUC ET AL 1981...STNO&IO$ !tt ~ 4.s " . , ".7" -L N ~ TITLE :IDENTIFICATION OF A CLASS OF FILTERED POISSON PROCESSES Authors : DE BRUCQ Denis - GUALTIEROTTI Antonio...filtered Poisson processes is intro- duced : the amplitude has a law which is spherically invariant and the filter is real, linear and causal. It is shown

Gravitational waves and large field inflation

NASA Astrophysics Data System (ADS)

Linde, Andrei

2017-02-01

According to the famous Lyth bound, one can confirm large field inflation by finding tensor modes with sufficiently large tensor-to-scalar ratio r. Here we will try to answer two related questions: is it possible to rule out all large field inflationary models by not finding tensor modes with r above some critical value, and what can we say about the scale of inflation by measuring r? However, in order to answer these questions one should distinguish between two different definitions of the large field inflation and three different definitions of the scale of inflation. We will examine these issues using the theory of cosmological α-attractors as a convenient testing ground.

[Prediction and spatial distribution of recruitment trees of natural secondary forest based on geographically weighted Poisson model].

PubMed

Zhang, Ling Yu; Liu, Zhao Gang

2017-12-01

Based on the data collected from 108 permanent plots of the forest resources survey in Maoershan Experimental Forest Farm during 2004-2016, this study investigated the spatial distribution of recruitment trees in natural secondary forest by global Poisson regression and geographically weighted Poisson regression (GWPR) with four bandwidths of 2.5, 5, 10 and 15 km. The simulation effects of the 5 regressions and the factors influencing the recruitment trees in stands were analyzed, a description was given to the spatial autocorrelation of the regression residuals on global and local levels using Moran's I. The results showed that the spatial distribution of the number of natural secondary forest recruitment was significantly influenced by stands and topographic factors, especially average DBH. The GWPR model with small scale (2.5 km) had high accuracy of model fitting, a large range of model parameter estimates was generated, and the localized spatial distribution effect of the model parameters was obtained. The GWPR model at small scale (2.5 and 5 km) had produced a small range of model residuals, and the stability of the model was improved. The global spatial auto-correlation of the GWPR model residual at the small scale (2.5 km) was the lowe-st, and the local spatial auto-correlation was significantly reduced, in which an ideal spatial distribution pattern of small clusters with different observations was formed. The local model at small scale (2.5 km) was much better than the global model in the simulation effect on the spatial distribution of recruitment tree number.

A Methane Balloon Inflation Chamber

ERIC Educational Resources Information Center

Czerwinski, Curtis J.; Cordes, Tanya J.; Franek, Joe

2005-01-01

The various equipments, procedure and hazards in constructing the device for inflating a methane balloon using a standard methane outlet in a laboratory are described. This device is fast, safe, inexpensive, and easy to use as compared to a hydrogen gas cylinder for inflating balloons.

Natural inflation and quantum gravity.

PubMed

de la Fuente, Anton; Saraswat, Prashant; Sundrum, Raman

2015-04-17

Cosmic inflation provides an attractive framework for understanding the early Universe and the cosmic microwave background. It can readily involve energies close to the scale at which quantum gravity effects become important. General considerations of black hole quantum mechanics suggest nontrivial constraints on any effective field theory model of inflation that emerges as a low-energy limit of quantum gravity, in particular, the constraint of the weak gravity conjecture. We show that higher-dimensional gauge and gravitational dynamics can elegantly satisfy these constraints and lead to a viable, theoretically controlled and predictive class of natural inflation models.

Inflatable Antenna Experiment (IAE)

NASA Image and Video Library

1996-05-20

S77-E-5022 (20 May 1996)--- Following its deployment from the Space Shuttle Endeavour, the Spartan 207/Inflatable Antenna Experiment (IAE) payload is backdropped over clouds and water. The view was photographed with an Electronic Still Camera (ESC) and downlinked to flight controllers on the first full day of orbital operations by the six-member crew. Managed by Goddard Space Flight Center (GSFC), Spartan is designed to provide short-duration, free-flight opportunities for a variety of scientific studies. The Spartan configuration on this flight is unique in that the IAE is part of an additional separate unit which is ejected once the experiment is completed. The IAE experiment will lay the groundwork for future technology development in inflatable space structures, which will be launched and then inflated like a balloon on-orbit.

Inflatable Antenna Experiment (IAE)

NASA Image and Video Library

1996-05-20

S77-E-5027 (20 May 1996)--- Following its deployment from the Space Shuttle Endeavour, the Spartan 207/Inflatable Antenna Experiment (IAE) payload is backdropped over clouds and water. The view was photographed with an Electronic Still Camera (ESC) and downlinked to flight controllers on the first full day of orbital operations by the six-member crew. Managed by Goddard Space Flight Center (GSFC), Spartan is designed to provide short-duration, free-flight opportunities for a variety of scientific studies. The Spartan configuration on this flight is unique in that the IAE is part of an additional separate unit which is ejected once the experiment is completed. The IAE experiment will lay the groundwork for future technology development in inflatable space structures, which will be launched and then inflated like a balloon on-orbit.

Fast-food exposure around schools in urban Adelaide.

PubMed

Coffee, Neil T; Kennedy, Hannah P; Niyonsenga, Theo

2016-12-01

To assess whether exposure to fast-food outlets around schools differed depending on socio-economic status (SES). Binary logistic regression was used to investigate the presence and zero-inflated Poisson regression was used for the count (due to the excess of zeroes) of fast food within 1000 m and 15000 m road network buffers around schools. The low and middle SES tertiles were combined due to a lack of significant variation as the 'disadvantaged' group and compared with the high SES tertile as the 'advantaged' group. School SES was expressed using the 2011 Australian Bureau of Statistics, socio-economic indices for areas, index of relative socio-economic disadvantage. Fast-food data included independent takeaway food outlets and major fast-food chains. Metropolitan Adelaide, South Australia. A total of 459 schools were geocoded to the street address and 1000 m and 1500 m road network distance buffers calculated. There was a 1·6 times greater risk of exposure to fast food within 1000 m (OR=1·634; 95 % 1·017, 2·625) and a 9·5 times greater risk of exposure to a fast food within 1500 m (OR=9·524; 95 % CI 3·497, 25·641) around disadvantaged schools compared with advantaged schools. Disadvantaged schools were exposed to more fast food, with more than twice the number of disadvantaged schools exposed to fast food. The higher exposure to fast food near more disadvantaged schools may reflect lower commercial land cost in low-SES areas, potentially creating more financially desirable investments for fast-food developers.

Poisson-Boltzmann versus Size-Modified Poisson-Boltzmann Electrostatics Applied to Lipid Bilayers.

PubMed

Wang, Nuo; Zhou, Shenggao; Kekenes-Huskey, Peter M; Li, Bo; McCammon, J Andrew

2014-12-26

Mean-field methods, such as the Poisson-Boltzmann equation (PBE), are often used to calculate the electrostatic properties of molecular systems. In the past two decades, an enhancement of the PBE, the size-modified Poisson-Boltzmann equation (SMPBE), has been reported. Here, the PBE and the SMPBE are reevaluated for realistic molecular systems, namely, lipid bilayers, under eight different sets of input parameters. The SMPBE appears to reproduce the molecular dynamics simulation results better than the PBE only under specific parameter sets, but in general, it performs no better than the Stern layer correction of the PBE. These results emphasize the need for careful discussions of the accuracy of mean-field calculations on realistic systems with respect to the choice of parameters and call for reconsideration of the cost-efficiency and the significance of the current SMPBE formulation.

Inflatable stretcher to transport patients

NASA Technical Reports Server (NTRS)

Clark, C. C.; Gordon, F. T., Jr.; Schmidt, C. B.

1970-01-01

Inflatable plastic bag inside strong, inflexible outer bag facilitates emergency transport of seriously burned or disabled patients. When the bag is inflated the patient is completely immobilized and cushioned from external shock. Air for breathing, temperature controls and communications may be provided by appropriate plug-in connections.

Fibre inflation and α-attractors

NASA Astrophysics Data System (ADS)

Kallosh, Renata; Linde, Andrei; Roest, Diederik; Westphal, Alexander; Yamada, Yusuke

2018-02-01

Fibre inflation is a specific string theory construction based on the Large Volume Scenario that produces an inflationary plateau. We outline its relation to α-attractor models for inflation, with the cosmological sector originating from certain string theory corrections leading to α = 2 and α = 1/2. Above a certain field range, the steepening effect of higher-order corrections leads first to the breakdown of single-field slow-roll and after that to the onset of 2-field dynamics: the overall volume of the extra dimensions starts to participate in the effective dynamics. Finally, we propose effective supergravity models of fibre inflation based on an \\overline{D3} uplift term with a nilpotent superfield. Specific moduli dependent \\overline{D3} induced geometries lead to cosmological fibre models but have in addition a de Sitter minimum exit. These supergravity models motivated by fibre inflation are relatively simple, stabilize the axions and disentangle the Hubble parameter from supersymmetry breaking.

Poisson mixture model for measurements using counting.

PubMed

Miller, Guthrie; Justus, Alan; Vostrotin, Vadim; Dry, Donald; Bertelli, Luiz

2010-03-01

Starting with the basic Poisson statistical model of a counting measurement process, 'extraPoisson' variance or 'overdispersion' are included by assuming that the Poisson parameter representing the mean number of counts itself comes from another distribution. The Poisson parameter is assumed to be given by the quantity of interest in the inference process multiplied by a lognormally distributed normalising coefficient plus an additional lognormal background that might be correlated with the normalising coefficient (shared uncertainty). The example of lognormal environmental background in uranium urine data is discussed. An additional uncorrelated background is also included. The uncorrelated background is estimated from a background count measurement using Bayesian arguments. The rather complex formulas are validated using Monte Carlo. An analytical expression is obtained for the probability distribution of gross counts coming from the uncorrelated background, which allows straightforward calculation of a classical decision level in the form of a gross-count alarm point with a desired false-positive rate. The main purpose of this paper is to derive formulas for exact likelihood calculations in the case of various kinds of backgrounds.

Understanding the Determinants of Debt Burden among College Graduates

ERIC Educational Resources Information Center

Chen, Rong; Wiederspan, Mark

2014-01-01

This article examines debt burden among college graduates and contributes to previous research by incorporating institutional and state characteristics. Utilizing a combination of national datasets and zero-one inflated beta regression, we find several major themes. First, family income and college experiences are strongly associated with the…

Inflatable Dark Matter

DOE PAGES

Davoudiasl, Hooman; Hooper, Dan; McDermott, Samuel D.

2016-01-22

We describe a general scenario, dubbed “Inflatable Dark Matter”, in which the density of dark matter particles can be reduced through a short period of late-time inflation in the early universe. The overproduction of dark matter that is predicted within many otherwise well-motivated models of new physics can be elegantly remedied within this context, without the need to tune underlying parameters or to appeal to anthropic considerations. Thermal relics that would otherwise be disfavored can easily be accommodated within this class of scenarios, including dark matter candidates that are very heavy or very light. Furthermore, the non-thermal abundance of GUTmore » or Planck scale axions can be brought to acceptable levels, without invoking anthropic tuning of initial conditions. Additionally, a period of late-time inflation could have occurred over a wide range of scales from ~ MeV to the weak scale or above, and could have been triggered by physics within a hidden sector, with small but not necessarily negligible couplings to the Standard Model.« less

Seven lessons from manyfield inflation in random potentials

NASA Astrophysics Data System (ADS)

Dias, Mafalda; Frazer, Jonathan; Marsh, M. C. David

2018-01-01

We study inflation in models with many interacting fields subject to randomly generated scalar potentials. We use methods from non-equilibrium random matrix theory to construct the potentials and an adaption of the `transport method' to evolve the two-point correlators during inflation. This construction allows, for the first time, for an explicit study of models with up to 100 interacting fields supporting a period of `approximately saddle-point' inflation. We determine the statistical predictions for observables by generating over 30,000 models with 2–100 fields supporting at least 60 efolds of inflation. These studies lead us to seven lessons: i) Manyfield inflation is not single-field inflation, ii) The larger the number of fields, the simpler and sharper the predictions, iii) Planck compatibility is not rare, but future experiments may rule out this class of models, iv) The smoother the potentials, the sharper the predictions, v) Hyperparameters can transition from stiff to sloppy, vi) Despite tachyons, isocurvature can decay, vii) Eigenvalue repulsion drives the predictions. We conclude that many of the `generic predictions' of single-field inflation can be emergent features of complex inflation models.

Does Education Corrupt? Theories of Grade Inflation

ERIC Educational Resources Information Center

Oleinik, Anton

2009-01-01

Several theories of grade inflation are discussed in this review article. It is argued that grade inflation results from the substitution of criteria specific to the search for truth by criteria of quality control generated outside of academia. Particular mechanisms of the grade inflation that occurs when a university is transformed into a…

Alternative Derivations for the Poisson Integral Formula

ERIC Educational Resources Information Center

Chen, J. T.; Wu, C. S.

2006-01-01

Poisson integral formula is revisited. The kernel in the Poisson integral formula can be derived in a series form through the direct BEM free of the concept of image point by using the null-field integral equation in conjunction with the degenerate kernels. The degenerate kernels for the closed-form Green's function and the series form of Poisson…

A horizontal inflatable habitat for SEI