Optimal transformations leading to normal distributions of positron emission tomography standardized uptake values

NASA Astrophysics Data System (ADS)

Scarpelli, Matthew; Eickhoff, Jens; Cuna, Enrique; Perlman, Scott; Jeraj, Robert

2018-02-01

The statistical analysis of positron emission tomography (PET) standardized uptake value (SUV) measurements is challenging due to the skewed nature of SUV distributions. This limits utilization of powerful parametric statistical models for analyzing SUV measurements. An ad-hoc approach, which is frequently used in practice, is to blindly use a log transformation, which may or may not result in normal SUV distributions. This study sought to identify optimal transformations leading to normally distributed PET SUVs extracted from tumors and assess the effects of therapy on the optimal transformations. Methods. The optimal transformation for producing normal distributions of tumor SUVs was identified by iterating the Box-Cox transformation parameter (λ) and selecting the parameter that maximized the Shapiro-Wilk P-value. Optimal transformations were identified for tumor SUVmax distributions at both pre and post treatment. This study included 57 patients that underwent 18F-fluorodeoxyglucose (18F-FDG) PET scans (publically available dataset). In addition, to test the generality of our transformation methodology, we included analysis of 27 patients that underwent 18F-Fluorothymidine (18F-FLT) PET scans at our institution. Results. After applying the optimal Box-Cox transformations, neither the pre nor the post treatment 18F-FDG SUV distributions deviated significantly from normality (P  >  0.10). Similar results were found for 18F-FLT PET SUV distributions (P  >  0.10). For both 18F-FDG and 18F-FLT SUV distributions, the skewness and kurtosis increased from pre to post treatment, leading to a decrease in the optimal Box-Cox transformation parameter from pre to post treatment. There were types of distributions encountered for both 18F-FDG and 18F-FLT where a log transformation was not optimal for providing normal SUV distributions. Conclusion. Optimization of the Box-Cox transformation, offers a solution for identifying normal SUV transformations for when the log transformation is insufficient. The log transformation is not always the appropriate transformation for producing normally distributed PET SUVs.

Computation of distribution of minimum resolution for log-normal distribution of chromatographic peak heights.

PubMed

Davis, Joe M

2011-10-28

General equations are derived for the distribution of minimum resolution between two chromatographic peaks, when peak heights in a multi-component chromatogram follow a continuous statistical distribution. The derivation draws on published theory by relating the area under the distribution of minimum resolution to the area under the distribution of the ratio of peak heights, which in turn is derived from the peak-height distribution. Two procedures are proposed for the equations' numerical solution. The procedures are applied to the log-normal distribution, which recently was reported to describe the distribution of component concentrations in three complex natural mixtures. For published statistical parameters of these mixtures, the distribution of minimum resolution is similar to that for the commonly assumed exponential distribution of peak heights used in statistical-overlap theory. However, these two distributions of minimum resolution can differ markedly, depending on the scale parameter of the log-normal distribution. Theory for the computation of the distribution of minimum resolution is extended to other cases of interest. With the log-normal distribution of peak heights as an example, the distribution of minimum resolution is computed when small peaks are lost due to noise or detection limits, and when the height of at least one peak is less than an upper limit. The distribution of minimum resolution shifts slightly to lower resolution values in the first case and to markedly larger resolution values in the second one. The theory and numerical procedure are confirmed by Monte Carlo simulation. Copyright © 2011 Elsevier B.V. All rights reserved.

On generalisations of the log-Normal distribution by means of a new product definition in the Kapteyn process

NASA Astrophysics Data System (ADS)

Duarte Queirós, Sílvio M.

2012-07-01

We discuss the modification of the Kapteyn multiplicative process using the q-product of Borges [E.P. Borges, A possible deformed algebra and calculus inspired in nonextensive thermostatistics, Physica A 340 (2004) 95]. Depending on the value of the index q a generalisation of the log-Normal distribution is yielded. Namely, the distribution increases the tail for small (when q<1) or large (when q>1) values of the variable upon analysis. The usual log-Normal distribution is retrieved when q=1, which corresponds to the traditional Kapteyn multiplicative process. The main statistical features of this distribution as well as related random number generators and tables of quantiles of the Kolmogorov-Smirnov distance are presented. Finally, we illustrate the validity of this scenario by describing a set of variables of biological and financial origin.

Log-normal distribution of the trace element data results from a mixture of stocahstic input and deterministic internal dynamics.

PubMed

Usuda, Kan; Kono, Koichi; Dote, Tomotaro; Shimizu, Hiroyasu; Tominaga, Mika; Koizumi, Chisato; Nakase, Emiko; Toshina, Yumi; Iwai, Junko; Kawasaki, Takashi; Akashi, Mitsuya

2002-04-01

In previous article, we showed a log-normal distribution of boron and lithium in human urine. This type of distribution is common in both biological and nonbiological applications. It can be observed when the effects of many independent variables are combined, each of which having any underlying distribution. Although elemental excretion depends on many variables, the one-compartment open model following a first-order process can be used to explain the elimination of elements. The rate of excretion is proportional to the amount present of any given element; that is, the same percentage of an existing element is eliminated per unit time, and the element concentration is represented by a deterministic negative power function of time in the elimination time-course. Sampling is of a stochastic nature, so the dataset of time variables in the elimination phase when the sample was obtained is expected to show Normal distribution. The time variable appears as an exponent of the power function, so a concentration histogram is that of an exponential transformation of Normally distributed time. This is the reason why the element concentration shows a log-normal distribution. The distribution is determined not by the element concentration itself, but by the time variable that defines the pharmacokinetic equation.

Scoring in genetically modified organism proficiency tests based on log-transformed results.

PubMed

Thompson, Michael; Ellison, Stephen L R; Owen, Linda; Mathieson, Kenneth; Powell, Joanne; Key, Pauline; Wood, Roger; Damant, Andrew P

2006-01-01

The study considers data from 2 UK-based proficiency schemes and includes data from a total of 29 rounds and 43 test materials over a period of 3 years. The results from the 2 schemes are similar and reinforce each other. The amplification process used in quantitative polymerase chain reaction determinations predicts a mixture of normal, binomial, and lognormal distributions dominated by the latter 2. As predicted, the study results consistently follow a positively skewed distribution. Log-transformation prior to calculating z-scores is effective in establishing near-symmetric distributions that are sufficiently close to normal to justify interpretation on the basis of the normal distribution.

[Distribution of individuals by spontaneous frequencies of lymphocytes with micronuclei. Particularity and consequences].

PubMed

Serebrianyĭ, A M; Akleev, A V; Aleshchenko, A V; Antoshchina, M M; Kudriashova, O V; Riabchenko, N I; Semenova, L P; Pelevina, I I

2011-01-01

By micronucleus (MN) assay with cytokinetic cytochalasin B block, the mean frequency of blood lymphocytes with MN has been determined in 76 Moscow inhabitants, 35 people from Obninsk and 122 from Chelyabinsk region. In contrast to the distribution of individuals on spontaneous frequency of cells with aberrations, which was shown to be binomial (Kusnetzov et al., 1980), the distribution of individuals on the spontaneous frequency of cells with MN in all three massif can be acknowledged as log-normal (chi2 test). Distribution of individuals in the joined massifs (Moscow and Obninsk inhabitants) and in the unique massif of all inspected with great reliability must be acknowledged as log-normal (0.70 and 0.86 correspondingly), but it cannot be regarded as Poisson, binomial or normal. Taking into account that log-normal distribution of children by spontaneous frequency of lymphocytes with MN has been observed by the inspection of 473 children from different kindergartens in Moscow we can make the conclusion that log-normal is regularity inherent in this type of damage of lymphocytes genome. On the contrary the distribution of individuals on induced by irradiation in vitro lymphocytes with MN frequency in most cases must be acknowledged as normal. This distribution character points out that damage appearance in the individual (genomic instability) in a single lymphocytes increases the probability of the damage appearance in another lymphocytes. We can propose that damaged stem cells lymphocyte progenitor's exchange by information with undamaged cells--the type of the bystander effect process. It can also be supposed that transmission of damage to daughter cells occurs in the time of stem cells division.

Performance analysis of MIMO wireless optical communication system with Q-ary PPM over correlated log-normal fading channel

NASA Astrophysics Data System (ADS)

Wang, Huiqin; Wang, Xue; Lynette, Kibe; Cao, Minghua

2018-06-01

The performance of multiple-input multiple-output wireless optical communication systems that adopt Q-ary pulse position modulation over spatial correlated log-normal fading channel is analyzed in terms of its un-coded bit error rate and ergodic channel capacity. The analysis is based on the Wilkinson's method which approximates the distribution of a sum of correlated log-normal random variables to a log-normal random variable. The analytical and simulation results corroborate the increment of correlation coefficients among sub-channels lead to system performance degradation. Moreover, the receiver diversity has better performance in resistance of spatial correlation caused channel fading.

Ventilation-perfusion distribution in normal subjects.

PubMed

Beck, Kenneth C; Johnson, Bruce D; Olson, Thomas P; Wilson, Theodore A

2012-09-01

Functional values of LogSD of the ventilation distribution (σ(V)) have been reported previously, but functional values of LogSD of the perfusion distribution (σ(q)) and the coefficient of correlation between ventilation and perfusion (ρ) have not been measured in humans. Here, we report values for σ(V), σ(q), and ρ obtained from wash-in data for three gases, helium and two soluble gases, acetylene and dimethyl ether. Normal subjects inspired gas containing the test gases, and the concentrations of the gases at end-expiration during the first 10 breaths were measured with the subjects at rest and at increasing levels of exercise. The regional distribution of ventilation and perfusion was described by a bivariate log-normal distribution with parameters σ(V), σ(q), and ρ, and these parameters were evaluated by matching the values of expired gas concentrations calculated for this distribution to the measured values. Values of cardiac output and LogSD ventilation/perfusion (Va/Q) were obtained. At rest, σ(q) is high (1.08 ± 0.12). With the onset of ventilation, σ(q) decreases to 0.85 ± 0.09 but remains higher than σ(V) (0.43 ± 0.09) at all exercise levels. Rho increases to 0.87 ± 0.07, and the value of LogSD Va/Q for light and moderate exercise is primarily the result of the difference between the magnitudes of σ(q) and σ(V). With known values for the parameters, the bivariate distribution describes the comprehensive distribution of ventilation and perfusion that underlies the distribution of the Va/Q ratio.

[Quantitative study of diesel/CNG buses exhaust particulate size distribution in a road tunnel].

PubMed

Zhu, Chun; Zhang, Xu

2010-10-01

Vehicle emission is one of main sources of fine/ultra-fine particles in many cities. This study firstly presents daily mean particle size distributions of mixed diesel/CNG buses traffic flow by 4 days consecutive real world measurement in an Australia road tunnel. Emission factors (EFs) of particle size distribution of diesel buses and CNG buses are obtained by MLR methods, particle distributions of diesel buses and CNG buses are observed as single accumulation mode and nuclei-mode separately. Particle size distributions of mixed traffic flow are decomposed by two log-normal fitting curves for each 30 min interval mean scans, the degrees of fitting between combined fitting curves and corresponding in-situ scans for totally 90 fitting scans are from 0.972 to 0.998. Finally particle size distributions of diesel buses and CNG buses are quantified by statistical whisker-box charts. For log-normal particle size distribution of diesel buses, accumulation mode diameters are 74.5-86.5 nm, geometric standard deviations are 1.88-2.05. As to log-normal particle size distribution of CNG buses, nuclei-mode diameters are 19.9-22.9 nm, geometric standard deviations are 1.27-1.3.

Distribution of transvascular pathway sizes through the pulmonary microvascular barrier.

PubMed

McNamee, J E

1987-01-01

Mathematical models of solute and water exchange in the lung have been helpful in understanding factors governing the volume flow rate and composition of pulmonary lymph. As experimental data and models become more encompassing, parameter identification becomes more difficult. Pore sizes in these models should approach and eventually become equivalent to actual physiological pathway sizes as more complex and accurate models are tried. However, pore sizes and numbers vary from model to model as new pathway sizes are added. This apparent inconsistency of pore sizes can be explained if it is assumed that the pulmonary blood-lymph barrier is widely heteroporous, for example, being composed of a continuous distribution of pathway sizes. The sieving characteristics of the pulmonary barrier are reproduced by a log normal distribution of pathway sizes (log mean = -0.20, log s.d. = 1.05). A log normal distribution of pathways in the microvascular barrier is shown to follow from a rather general assumption about the nature of the pulmonary endothelial junction.

Stick-slip behavior in a continuum-granular experiment.

PubMed

Geller, Drew A; Ecke, Robert E; Dahmen, Karin A; Backhaus, Scott

2015-12-01

We report moment distribution results from a laboratory experiment, similar in character to an isolated strike-slip earthquake fault, consisting of sheared elastic plates separated by a narrow gap filled with a two-dimensional granular medium. Local measurement of strain displacements of the plates at 203 spatial points located adjacent to the gap allows direct determination of the event moments and their spatial and temporal distributions. We show that events consist of spatially coherent, larger motions and spatially extended (noncoherent), smaller events. The noncoherent events have a probability distribution of event moment consistent with an M(-3/2) power law scaling with Poisson-distributed recurrence times. Coherent events have a log-normal moment distribution and mean temporal recurrence. As the applied normal pressure increases, there are more coherent events and their log-normal distribution broadens and shifts to larger average moment.

Comparison of parametric and bootstrap method in bioequivalence test.

PubMed

Ahn, Byung-Jin; Yim, Dong-Seok

2009-10-01

The estimation of 90% parametric confidence intervals (CIs) of mean AUC and Cmax ratios in bioequivalence (BE) tests are based upon the assumption that formulation effects in log-transformed data are normally distributed. To compare the parametric CIs with those obtained from nonparametric methods we performed repeated estimation of bootstrap-resampled datasets. The AUC and Cmax values from 3 archived datasets were used. BE tests on 1,000 resampled datasets from each archived dataset were performed using SAS (Enterprise Guide Ver.3). Bootstrap nonparametric 90% CIs of formulation effects were then compared with the parametric 90% CIs of the original datasets. The 90% CIs of formulation effects estimated from the 3 archived datasets were slightly different from nonparametric 90% CIs obtained from BE tests on resampled datasets. Histograms and density curves of formulation effects obtained from resampled datasets were similar to those of normal distribution. However, in 2 of 3 resampled log (AUC) datasets, the estimates of formulation effects did not follow the Gaussian distribution. Bias-corrected and accelerated (BCa) CIs, one of the nonparametric CIs of formulation effects, shifted outside the parametric 90% CIs of the archived datasets in these 2 non-normally distributed resampled log (AUC) datasets. Currently, the 80~125% rule based upon the parametric 90% CIs is widely accepted under the assumption of normally distributed formulation effects in log-transformed data. However, nonparametric CIs may be a better choice when data do not follow this assumption.

Comparison of Parametric and Bootstrap Method in Bioequivalence Test

PubMed Central

Ahn, Byung-Jin

2009-01-01

The estimation of 90% parametric confidence intervals (CIs) of mean AUC and Cmax ratios in bioequivalence (BE) tests are based upon the assumption that formulation effects in log-transformed data are normally distributed. To compare the parametric CIs with those obtained from nonparametric methods we performed repeated estimation of bootstrap-resampled datasets. The AUC and Cmax values from 3 archived datasets were used. BE tests on 1,000 resampled datasets from each archived dataset were performed using SAS (Enterprise Guide Ver.3). Bootstrap nonparametric 90% CIs of formulation effects were then compared with the parametric 90% CIs of the original datasets. The 90% CIs of formulation effects estimated from the 3 archived datasets were slightly different from nonparametric 90% CIs obtained from BE tests on resampled datasets. Histograms and density curves of formulation effects obtained from resampled datasets were similar to those of normal distribution. However, in 2 of 3 resampled log (AUC) datasets, the estimates of formulation effects did not follow the Gaussian distribution. Bias-corrected and accelerated (BCa) CIs, one of the nonparametric CIs of formulation effects, shifted outside the parametric 90% CIs of the archived datasets in these 2 non-normally distributed resampled log (AUC) datasets. Currently, the 80~125% rule based upon the parametric 90% CIs is widely accepted under the assumption of normally distributed formulation effects in log-transformed data. However, nonparametric CIs may be a better choice when data do not follow this assumption. PMID:19915699

Interpreting the concordance statistic of a logistic regression model: relation to the variance and odds ratio of a continuous explanatory variable.

PubMed

Austin, Peter C; Steyerberg, Ewout W

2012-06-20

When outcomes are binary, the c-statistic (equivalent to the area under the Receiver Operating Characteristic curve) is a standard measure of the predictive accuracy of a logistic regression model. An analytical expression was derived under the assumption that a continuous explanatory variable follows a normal distribution in those with and without the condition. We then conducted an extensive set of Monte Carlo simulations to examine whether the expressions derived under the assumption of binormality allowed for accurate prediction of the empirical c-statistic when the explanatory variable followed a normal distribution in the combined sample of those with and without the condition. We also examine the accuracy of the predicted c-statistic when the explanatory variable followed a gamma, log-normal or uniform distribution in combined sample of those with and without the condition. Under the assumption of binormality with equality of variances, the c-statistic follows a standard normal cumulative distribution function with dependence on the product of the standard deviation of the normal components (reflecting more heterogeneity) and the log-odds ratio (reflecting larger effects). Under the assumption of binormality with unequal variances, the c-statistic follows a standard normal cumulative distribution function with dependence on the standardized difference of the explanatory variable in those with and without the condition. In our Monte Carlo simulations, we found that these expressions allowed for reasonably accurate prediction of the empirical c-statistic when the distribution of the explanatory variable was normal, gamma, log-normal, and uniform in the entire sample of those with and without the condition. The discriminative ability of a continuous explanatory variable cannot be judged by its odds ratio alone, but always needs to be considered in relation to the heterogeneity of the population.

Log-amplitude statistics for Beck-Cohen superstatistics

NASA Astrophysics Data System (ADS)

Kiyono, Ken; Konno, Hidetoshi

2013-05-01

As a possible generalization of Beck-Cohen superstatistical processes, we study non-Gaussian processes with temporal heterogeneity of local variance. To characterize the variance heterogeneity, we define log-amplitude cumulants and log-amplitude autocovariance and derive closed-form expressions of the log-amplitude cumulants for χ2, inverse χ2, and log-normal superstatistical distributions. Furthermore, we show that χ2 and inverse χ2 superstatistics with degree 2 are closely related to an extreme value distribution, called the Gumbel distribution. In these cases, the corresponding superstatistical distributions result in the q-Gaussian distribution with q=5/3 and the bilateral exponential distribution, respectively. Thus, our finding provides a hypothesis that the asymptotic appearance of these two special distributions may be explained by a link with the asymptotic limit distributions involving extreme values. In addition, as an application of our approach, we demonstrated that non-Gaussian fluctuations observed in a stock index futures market can be well approximated by the χ2 superstatistical distribution with degree 2.

Fluctuations in email size

NASA Astrophysics Data System (ADS)

Matsubara, Yoshitsugu; Musashi, Yasuo

2017-12-01

The purpose of this study is to explain fluctuations in email size. We have previously investigated the long-term correlations between email send requests and data flow in the system log of the primary staff email server at a university campus, finding that email size frequency follows a power-law distribution with two inflection points, and that the power-law property weakens the correlation of the data flow. However, the mechanism underlying this fluctuation is not completely understood. We collected new log data from both staff and students over six academic years and analyzed the frequency distribution thereof, focusing on the type of content contained in the emails. Furthermore, we obtained permission to collect "Content-Type" log data from the email headers. We therefore collected the staff log data from May 1, 2015 to July 31, 2015, creating two subdistributions. In this paper, we propose a model to explain these subdistributions, which follow log-normal-like distributions. In the log-normal-like model, email senders -consciously or unconsciously- regulate the size of new email sentences according to a normal distribution. The fitting of the model is acceptable for these subdistributions, and the model demonstrates power-law properties for large email sizes. An analysis of the length of new email sentences would be required for further discussion of our model; however, to protect user privacy at the participating organization, we left this analysis for future work. This study provides new knowledge on the properties of email sizes, and our model is expected to contribute to the decision on whether to establish upper size limits in the design of email services.

Size distribution of submarine landslides along the U.S. Atlantic margin

USGS Publications Warehouse

Chaytor, J.D.; ten Brink, Uri S.; Solow, A.R.; Andrews, B.D.

2009-01-01

Assessment of the probability for destructive landslide-generated tsunamis depends on the knowledge of the number, size, and frequency of large submarine landslides. This paper investigates the size distribution of submarine landslides along the U.S. Atlantic continental slope and rise using the size of the landslide source regions (landslide failure scars). Landslide scars along the margin identified in a detailed bathymetric Digital Elevation Model (DEM) have areas that range between 0.89??km2 and 2410??km2 and volumes between 0.002??km3 and 179??km3. The area to volume relationship of these failure scars is almost linear (inverse power-law exponent close to 1), suggesting a fairly uniform failure thickness of a few 10s of meters in each event, with only rare, deep excavating landslides. The cumulative volume distribution of the failure scars is very well described by a log-normal distribution rather than by an inverse power-law, the most commonly used distribution for both subaerial and submarine landslides. A log-normal distribution centered on a volume of 0.86??km3 may indicate that landslides preferentially mobilize a moderate amount of material (on the order of 1??km3), rather than large landslides or very small ones. Alternatively, the log-normal distribution may reflect an inverse power law distribution modified by a size-dependent probability of observing landslide scars in the bathymetry data. If the latter is the case, an inverse power-law distribution with an exponent of 1.3 ?? 0.3, modified by a size-dependent conditional probability of identifying more failure scars with increasing landslide size, fits the observed size distribution. This exponent value is similar to the predicted exponent of 1.2 ?? 0.3 for subaerial landslides in unconsolidated material. Both the log-normal and modified inverse power-law distributions of the observed failure scar volumes suggest that large landslides, which have the greatest potential to generate damaging tsunamis, occur infrequently along the margin. ?? 2008 Elsevier B.V.

Stochastic modelling of non-stationary financial assets

NASA Astrophysics Data System (ADS)

Estevens, Joana; Rocha, Paulo; Boto, João P.; Lind, Pedro G.

2017-11-01

We model non-stationary volume-price distributions with a log-normal distribution and collect the time series of its two parameters. The time series of the two parameters are shown to be stationary and Markov-like and consequently can be modelled with Langevin equations, which are derived directly from their series of values. Having the evolution equations of the log-normal parameters, we reconstruct the statistics of the first moments of volume-price distributions which fit well the empirical data. Finally, the proposed framework is general enough to study other non-stationary stochastic variables in other research fields, namely, biology, medicine, and geology.

Determining prescription durations based on the parametric waiting time distribution.

PubMed

Støvring, Henrik; Pottegård, Anton; Hallas, Jesper

2016-12-01

The purpose of the study is to develop a method to estimate the duration of single prescriptions in pharmacoepidemiological studies when the single prescription duration is not available. We developed an estimation algorithm based on maximum likelihood estimation of a parametric two-component mixture model for the waiting time distribution (WTD). The distribution component for prevalent users estimates the forward recurrence density (FRD), which is related to the distribution of time between subsequent prescription redemptions, the inter-arrival density (IAD), for users in continued treatment. We exploited this to estimate percentiles of the IAD by inversion of the estimated FRD and defined the duration of a prescription as the time within which 80% of current users will have presented themselves again. Statistical properties were examined in simulation studies, and the method was applied to empirical data for four model drugs: non-steroidal anti-inflammatory drugs (NSAIDs), warfarin, bendroflumethiazide, and levothyroxine. Simulation studies found negligible bias when the data-generating model for the IAD coincided with the FRD used in the WTD estimation (Log-Normal). When the IAD consisted of a mixture of two Log-Normal distributions, but was analyzed with a single Log-Normal distribution, relative bias did not exceed 9%. Using a Log-Normal FRD, we estimated prescription durations of 117, 91, 137, and 118 days for NSAIDs, warfarin, bendroflumethiazide, and levothyroxine, respectively. Similar results were found with a Weibull FRD. The algorithm allows valid estimation of single prescription durations, especially when the WTD reliably separates current users from incident users, and may replace ad-hoc decision rules in automated implementations. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Technical note: An improved approach to determining background aerosol concentrations with PILS sampling on aircraft

NASA Astrophysics Data System (ADS)

Fukami, Christine S.; Sullivan, Amy P.; Ryan Fulgham, S.; Murschell, Trey; Borch, Thomas; Smith, James N.; Farmer, Delphine K.

2016-07-01

Particle-into-Liquid Samplers (PILS) have become a standard aerosol collection technique, and are widely used in both ground and aircraft measurements in conjunction with off-line ion chromatography (IC) measurements. Accurate and precise background samples are essential to account for gas-phase components not efficiently removed and any interference in the instrument lines, collection vials or off-line analysis procedures. For aircraft sampling with PILS, backgrounds are typically taken with in-line filters to remove particles prior to sample collection once or twice per flight with more numerous backgrounds taken on the ground. Here, we use data collected during the Front Range Air Pollution and Photochemistry Éxperiment (FRAPPÉ) to demonstrate that not only are multiple background filter samples are essential to attain a representative background, but that the chemical background signals do not follow the Gaussian statistics typically assumed. Instead, the background signals for all chemical components analyzed from 137 background samples (taken from ∼78 total sampling hours over 18 flights) follow a log-normal distribution, meaning that the typical approaches of averaging background samples and/or assuming a Gaussian distribution cause an over-estimation of background samples - and thus an underestimation of sample concentrations. Our approach of deriving backgrounds from the peak of the log-normal distribution results in detection limits of 0.25, 0.32, 3.9, 0.17, 0.75 and 0.57 μg m-3 for sub-micron aerosol nitrate (NO3-), nitrite (NO2-), ammonium (NH4+), sulfate (SO42-), potassium (K+) and calcium (Ca2+), respectively. The difference in backgrounds calculated from assuming a Gaussian distribution versus a log-normal distribution were most extreme for NH4+, resulting in a background that was 1.58× that determined from fitting a log-normal distribution.

Optical and physical properties of stratospheric aerosols from balloon measurements in the visible and near-infrared domains. I. Analysis of aerosol extinction spectra from the AMON and SALOMON balloonborne spectrometers

NASA Astrophysics Data System (ADS)

Berthet, Gwenaël; Renard, Jean-Baptiste; Brogniez, Colette; Robert, Claude; Chartier, Michel; Pirre, Michel

2002-12-01

Aerosol extinction coefficients have been derived in the 375-700-nm spectral domain from measurements in the stratosphere since 1992, at night, at mid- and high latitudes from 15 to 40 km, by two balloonborne spectrometers, Absorption par les Minoritaires Ozone et NOx (AMON) and Spectroscopie d'Absorption Lunaire pour l'Observation des Minoritaires Ozone et NOx (SALOMON). Log-normal size distributions associated with the Mie-computed extinction spectra that best fit the measurements permit calculation of integrated properties of the distributions. Although measured extinction spectra that correspond to background aerosols can be reproduced by the Mie scattering model by use of monomodal log-normal size distributions, each flight reveals some large discrepancies between measurement and theory at several altitudes. The agreement between measured and Mie-calculated extinction spectra is significantly improved by use of bimodal log-normal distributions. Nevertheless, neither monomodal nor bimodal distributions permit correct reproduction of some of the measured extinction shapes, especially for the 26 February 1997 AMON flight, which exhibited spectral behavior attributed to particles from a polar stratospheric cloud event.

Inferring local competition intensity from patch size distributions: a test using biological soil crusts

USGS Publications Warehouse

Bowker, Matthew A.; Maestre, Fernando T.

2012-01-01

Dryland vegetation is inherently patchy. This patchiness goes on to impact ecology, hydrology, and biogeochemistry. Recently, researchers have proposed that dryland vegetation patch sizes follow a power law which is due to local plant facilitation. It is unknown what patch size distribution prevails when competition predominates over facilitation, or if such a pattern could be used to detect competition. We investigated this question in an alternative vegetation type, mosses and lichens of biological soil crusts, which exhibit a smaller scale patch-interpatch configuration. This micro-vegetation is characterized by competition for space. We proposed that multiplicative effects of genetics, environment and competition should result in a log-normal patch size distribution. When testing the prevalence of log-normal versus power law patch size distributions, we found that the log-normal was the better distribution in 53% of cases and a reasonable fit in 83%. In contrast, the power law was better in 39% of cases, and in 8% of instances both distributions fit equally well. We further hypothesized that the log-normal distribution parameters would be predictably influenced by competition strength. There was qualitative agreement between one of the distribution's parameters (μ) and a novel intransitive (lacking a 'best' competitor) competition index, suggesting that as intransitivity increases, patch sizes decrease. The correlation of μ with other competition indicators based on spatial segregation of species (the C-score) depended on aridity. In less arid sites, μ was negatively correlated with the C-score (suggesting smaller patches under stronger competition), while positive correlations (suggesting larger patches under stronger competition) were observed at more arid sites. We propose that this is due to an increasing prevalence of competition transitivity as aridity increases. These findings broaden the emerging theory surrounding dryland patch size distributions and, with refinement, may help us infer cryptic ecological processes from easily observed spatial patterns in the field.

Assessment of the hygienic performances of hamburger patty production processes.

PubMed

Gill, C O; Rahn, K; Sloan, K; McMullen, L M

1997-05-20

The hygienic conditions of the hamburger patties collected from three patty manufacturing plants and six retail outlets were examined. At each manufacturing plant a sample from newly formed, chilled patties and one from frozen patties were collected from each of 25 batches of patties selected at random. At three, two or one retail outlet, respectively, 25 samples from frozen, chilled or both frozen and chilled patties were collected at random. Each sample consisted of 30 g of meat obtained from five or six patties. Total aerobic, coliform and Escherichia coli counts per gram were enumerated for each sample. The mean log (x) and standard deviation (s) were calculated for the log10 values for each set of 25 counts, on the assumption that the distribution of counts approximated the log normal. A value for the log10 of the arithmetic mean (log A) was calculated for each set from the values of x and s. A chi2 statistic was calculated for each set as a test of the assumption of the log normal distribution. The chi2 statistic was calculable for 32 of the 39 sets. Four of the sets gave chi2 values indicative of gross deviation from log normality. On inspection of those sets, distributions obviously differing from the log normal were apparent in two. Log A values for total, coliform and E. coli counts for chilled patties from manufacturing plants ranged from 4.4 to 5.1, 1.7 to 2.3 and 0.9 to 1.5, respectively. Log A values for frozen patties from manufacturing plants were between < 0.1 and 0.5 log10 units less than the equivalent values for chilled patties. Log A values for total, coliform and E. coli counts for frozen patties on retail sale ranged from 3.8 to 8.5, < 0.5 to 3.6 and < 0 to 1.9, respectively. The equivalent ranges for chilled patties on retail sale were 4.8 to 8.5, 1.8 to 3.7 and 1.4 to 2.7, respectively. The findings indicate that the general hygienic condition of hamburgers patties could be improved by their being manufactured from only manufacturing beef of superior hygienic quality, and by the better management of chilled patties at retail outlets.

Effects of a primordial magnetic field with log-normal distribution on the cosmic microwave background

NASA Astrophysics Data System (ADS)

Yamazaki, Dai G.; Ichiki, Kiyotomo; Takahashi, Keitaro

2011-12-01

We study the effect of primordial magnetic fields (PMFs) on the anisotropies of the cosmic microwave background (CMB). We assume the spectrum of PMFs is described by log-normal distribution which has a characteristic scale, rather than power-law spectrum. This scale is expected to reflect the generation mechanisms and our analysis is complementary to previous studies with power-law spectrum. We calculate power spectra of energy density and Lorentz force of the log-normal PMFs, and then calculate CMB temperature and polarization angular power spectra from scalar, vector, and tensor modes of perturbations generated from such PMFs. By comparing these spectra with WMAP7, QUaD, CBI, Boomerang, and ACBAR data sets, we find that the current CMB data set places the strongest constraint at k≃10-2.5Mpc-1 with the upper limit B≲3nG.

Standardized likelihood ratio test for comparing several log-normal means and confidence interval for the common mean.

PubMed

Krishnamoorthy, K; Oral, Evrim

2017-12-01

Standardized likelihood ratio test (SLRT) for testing the equality of means of several log-normal distributions is proposed. The properties of the SLRT and an available modified likelihood ratio test (MLRT) and a generalized variable (GV) test are evaluated by Monte Carlo simulation and compared. Evaluation studies indicate that the SLRT is accurate even for small samples, whereas the MLRT could be quite liberal for some parameter values, and the GV test is in general conservative and less powerful than the SLRT. Furthermore, a closed-form approximate confidence interval for the common mean of several log-normal distributions is developed using the method of variance estimate recovery, and compared with the generalized confidence interval with respect to coverage probabilities and precision. Simulation studies indicate that the proposed confidence interval is accurate and better than the generalized confidence interval in terms of coverage probabilities. The methods are illustrated using two examples.

Explorations in statistics: the log transformation.

PubMed

Curran-Everett, Douglas

2018-06-01

Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This thirteenth installment of Explorations in Statistics explores the log transformation, an established technique that rescales the actual observations from an experiment so that the assumptions of some statistical analysis are better met. A general assumption in statistics is that the variability of some response Y is homogeneous across groups or across some predictor variable X. If the variability-the standard deviation-varies in rough proportion to the mean value of Y, a log transformation can equalize the standard deviations. Moreover, if the actual observations from an experiment conform to a skewed distribution, then a log transformation can make the theoretical distribution of the sample mean more consistent with a normal distribution. This is important: the results of a one-sample t test are meaningful only if the theoretical distribution of the sample mean is roughly normal. If we log-transform our observations, then we want to confirm the transformation was useful. We can do this if we use the Box-Cox method, if we bootstrap the sample mean and the statistic t itself, and if we assess the residual plots from the statistical model of the actual and transformed sample observations.

Stochastic Growth Theory of Spatially-Averaged Distributions of Langmuir Fields in Earth's Foreshock

NASA Technical Reports Server (NTRS)

Boshuizen, Christopher R.; Cairns, Iver H.; Robinson, P. A.

2001-01-01

Langmuir-like waves in the foreshock of Earth are characteristically bursty and irregular, and are the subject of a number of recent studies. Averaged over the foreshock, it is observed that the probability distribution is power-law P(bar)(log E) in the wave field E with the bar denoting this averaging over position, In this paper it is shown that stochastic growth theory (SGT) can explain a power-law spatially-averaged distributions P(bar)(log E), when the observed power-law variations of the mean and standard deviation of log E with position are combined with the log normal statistics predicted by SGT at each location.

Universal Distribution of Litter Decay Rates

NASA Astrophysics Data System (ADS)

Forney, D. C.; Rothman, D. H.

2008-12-01

Degradation of litter is the result of many physical, chemical and biological processes. The high variability of these processes likely accounts for the progressive slowdown of decay with litter age. This age dependence is commonly thought to result from the superposition of processes with different decay rates k. Here we assume an underlying continuous yet unknown distribution p(k) of decay rates [1]. To seek its form, we analyze the mass-time history of 70 LIDET [2] litter data sets obtained under widely varying conditions. We construct a regularized inversion procedure to find the best fitting distribution p(k) with the least degrees of freedom. We find that the resulting p(k) is universally consistent with a lognormal distribution, i.e.~a Gaussian distribution of log k, characterized by a dataset-dependent mean and variance of log k. This result is supported by a recurring observation that microbial populations on leaves are log-normally distributed [3]. Simple biological processes cause the frequent appearance of the log-normal distribution in ecology [4]. Environmental factors, such as soil nitrate, soil aggregate size, soil hydraulic conductivity, total soil nitrogen, soil denitrification, soil respiration have been all observed to be log-normally distributed [5]. Litter degradation rates depend on many coupled, multiplicative factors, which provides a fundamental basis for the lognormal distribution. Using this insight, we systematically estimated the mean and variance of log k for 512 data sets from the LIDET study. We find the mean strongly correlates with temperature and precipitation, while the variance appears to be uncorrelated with main environmental factors and is thus likely more correlated with chemical composition and/or ecology. Results indicate the possibility that the distribution in rates reflects, at least in part, the distribution of microbial niches. [1] B. P. Boudreau, B.~R. Ruddick, American Journal of Science,291, 507, (1991). [2] M. Harmon, Forest Science Data Bank: TD023 [Database]. LTER Intersite Fine Litter Decomposition Experiment (LIDET): Long-Term Ecological Research, (2007). [3] G.~A. Beattie, S.~E. Lindow, Phytopathology 89, 353 (1999). [4] R.~A. May, Ecology and Evolution of Communities/, A pattern of Species Abundance and Diversity, 81 (1975). [5] T.~B. Parkin, J.~A. Robinson, Advances in Soil Science 20, Analysis of Lognormal Data, 194 (1992).

Interpreting the concordance statistic of a logistic regression model: relation to the variance and odds ratio of a continuous explanatory variable

PubMed Central

2012-01-01

Background When outcomes are binary, the c-statistic (equivalent to the area under the Receiver Operating Characteristic curve) is a standard measure of the predictive accuracy of a logistic regression model. Methods An analytical expression was derived under the assumption that a continuous explanatory variable follows a normal distribution in those with and without the condition. We then conducted an extensive set of Monte Carlo simulations to examine whether the expressions derived under the assumption of binormality allowed for accurate prediction of the empirical c-statistic when the explanatory variable followed a normal distribution in the combined sample of those with and without the condition. We also examine the accuracy of the predicted c-statistic when the explanatory variable followed a gamma, log-normal or uniform distribution in combined sample of those with and without the condition. Results Under the assumption of binormality with equality of variances, the c-statistic follows a standard normal cumulative distribution function with dependence on the product of the standard deviation of the normal components (reflecting more heterogeneity) and the log-odds ratio (reflecting larger effects). Under the assumption of binormality with unequal variances, the c-statistic follows a standard normal cumulative distribution function with dependence on the standardized difference of the explanatory variable in those with and without the condition. In our Monte Carlo simulations, we found that these expressions allowed for reasonably accurate prediction of the empirical c-statistic when the distribution of the explanatory variable was normal, gamma, log-normal, and uniform in the entire sample of those with and without the condition. Conclusions The discriminative ability of a continuous explanatory variable cannot be judged by its odds ratio alone, but always needs to be considered in relation to the heterogeneity of the population. PMID:22716998

Best Statistical Distribution of flood variables for Johor River in Malaysia

NASA Astrophysics Data System (ADS)

Salarpour Goodarzi, M.; Yusop, Z.; Yusof, F.

2012-12-01

A complex flood event is always characterized by a few characteristics such as flood peak, flood volume, and flood duration, which might be mutually correlated. This study explored the statistical distribution of peakflow, flood duration and flood volume at Rantau Panjang gauging station on the Johor River in Malaysia. Hourly data were recorded for 45 years. The data were analysed based on water year (July - June). Five distributions namely, Log Normal, Generalize Pareto, Log Pearson, Normal and Generalize Extreme Value (GEV) were used to model the distribution of all the three variables. Anderson-Darling and Kolmogorov-Smirnov goodness-of-fit tests were used to evaluate the best fit. Goodness-of-fit tests at 5% level of significance indicate that all the models can be used to model the distribution of peakflow, flood duration and flood volume. However, Generalize Pareto distribution is found to be the most suitable model when tested with the Anderson-Darling test and the, Kolmogorov-Smirnov suggested that GEV is the best for peakflow. The result of this research can be used to improve flood frequency analysis. Comparison between Generalized Extreme Value, Generalized Pareto and Log Pearson distributions in the Cumulative Distribution Function of peakflow

Box-Cox transformation of firm size data in statistical analysis

NASA Astrophysics Data System (ADS)

Chen, Ting Ting; Takaishi, Tetsuya

2014-03-01

Firm size data usually do not show the normality that is often assumed in statistical analysis such as regression analysis. In this study we focus on two firm size data: the number of employees and sale. Those data deviate considerably from a normal distribution. To improve the normality of those data we transform them by the Box-Cox transformation with appropriate parameters. The Box-Cox transformation parameters are determined so that the transformed data best show the kurtosis of a normal distribution. It is found that the two firm size data transformed by the Box-Cox transformation show strong linearity. This indicates that the number of employees and sale have the similar property as a firm size indicator. The Box-Cox parameters obtained for the firm size data are found to be very close to zero. In this case the Box-Cox transformations are approximately a log-transformation. This suggests that the firm size data we used are approximately log-normal distributions.

A Feasibility Study of Expanding the F404 Aircraft Engine Repair Capability at the Aircraft Intermediate Maintenance Department

DTIC Science & Technology

1993-06-01

1 A. OBJECTIVES ............. .... .................. 1 B. HISTORY ................... .................... 2 C...utilization, and any additional manpower requirements at the "selected" AIMD’s. B. HISTORY Until late 1991 both NADEP JAX and NADEP North Island (NORIS...TRIANGULAR OR ALL LOG NORMAL DISTRIBUTIONS FOR SERVICE TIMES AT AIND CECIL FIELD maintenance/ Triangular Log Normal MAZDA Difference Differe•ce Supply

Erosion associated with cable and tractor logging in northwestern California

Treesearch

R. M. Rice; P. A. Datzman

1981-01-01

Abstract - Erosion and site conditions were measured at 102 logged plots in northwestern California. Erosion averaged 26.8 m 3 /ha. A log-normal distribution was a better fit to the data. The antilog of the mean of the logarithms of erosion was 3.2 m 3 /ha. The Coast District Erosion Hazard Rating was a poor predictor of erosion related to logging. In a new equation...

Double stars with wide separations in the AGK3 - II. The wide binaries and the multiple systems*

NASA Astrophysics Data System (ADS)

Halbwachs, J.-L.; Mayor, M.; Udry, S.

2017-02-01

A large observation programme was carried out to measure the radial velocities of the components of a selection of common proper motion (CPM) stars to select the physical binaries. 80 wide binaries (WBs) were detected, and 39 optical pairs were identified. By adding CPM stars with separations close enough to be almost certain that they are physical, a bias-controlled sample of 116 WBs was obtained, and used to derive the distribution of separations from 100 to 30 000 au. The distribution obtained does not match the log-constant distribution, but agrees with the log-normal distribution. The spectroscopic binaries detected among the WB components were used to derive statistical information about the multiple systems. The close binaries in WBs seem to be like those detected in other field stars. As for the WBs, they seem to obey the log-normal distribution of periods. The number of quadruple systems agrees with the no correlation hypothesis; this indicates that an environment conducive to the formation of WBs does not favour the formation of subsystems with periods shorter than 10 yr.

An iterative procedure for obtaining maximum-likelihood estimates of the parameters for a mixture of normal distributions

NASA Technical Reports Server (NTRS)

Peters, B. C., Jr.; Walker, H. F.

1975-01-01

A general iterative procedure is given for determining the consistent maximum likelihood estimates of normal distributions. In addition, a local maximum of the log-likelihood function, Newtons's method, a method of scoring, and modifications of these procedures are discussed.

Energetics and Birth Rates of Supernova Remnants in the Large Magellanic Cloud

NASA Astrophysics Data System (ADS)

Leahy, D. A.

2017-03-01

Published X-ray emission properties for a sample of 50 supernova remnants (SNRs) in the Large Magellanic Cloud (LMC) are used as input for SNR evolution modeling calculations. The forward shock emission is modeled to obtain the initial explosion energy, age, and circumstellar medium density for each SNR in the sample. The resulting age distribution yields a SNR birthrate of 1/(500 yr) for the LMC. The explosion energy distribution is well fit by a log-normal distribution, with a most-probable explosion energy of 0.5× {10}51 erg, with a 1σ dispersion by a factor of 3 in energy. The circumstellar medium density distribution is broader than the explosion energy distribution, with a most-probable density of ˜0.1 cm-3. The shape of the density distribution can be fit with a log-normal distribution, with incompleteness at high density caused by the shorter evolution times of SNRs.

Distribution of runup heights of the December 26, 2004 tsunami in the Indian Ocean

NASA Astrophysics Data System (ADS)

Choi, Byung Ho; Hong, Sung Jin; Pelinovsky, Efim

2006-07-01

A massive earthquake with magnitude 9.3 occurred on December 26, 2004 off the northern Sumatra generated huge tsunami waves affected many coastal countries in the Indian Ocean. A number of field surveys have been performed after this tsunami event; in particular, several surveys in the south/east coast of India, Andaman and Nicobar Islands, Sri Lanka, Sumatra, Malaysia, and Thailand have been organized by the Korean Society of Coastal and Ocean Engineers from January to August 2005. Spatial distribution of the tsunami runup is used to analyze the distribution function of the wave heights on different coasts. Theoretical interpretation of this distribution is associated with random coastal bathymetry and coastline led to the log-normal functions. Observed data also are in a very good agreement with log-normal distribution confirming the important role of the variable ocean bathymetry in the formation of the irregular wave height distribution along the coasts.

An estimate of field size distributions for selected sites in the major grain producing countries

NASA Technical Reports Server (NTRS)

Podwysocki, M. H.

1977-01-01

The field size distributions for the major grain producing countries of the World were estimated. LANDSAT-1 and 2 images were evaluated for two areas each in the United States, People's Republic of China, and the USSR. One scene each was evaluated for France, Canada, and India. Grid sampling was done for representative sub-samples of each image, measuring the long and short axes of each field; area was then calculated. Each of the resulting data sets was computer analyzed for their frequency distributions. Nearly all frequency distributions were highly peaked and skewed (shifted) towards small values, approaching that of either a Poisson or log-normal distribution. The data were normalized by a log transformation, creating a Gaussian distribution which has moments readily interpretable and useful for estimating the total population of fields. Resultant predictors of the field size estimates are discussed.

The missing impact craters on Venus

NASA Technical Reports Server (NTRS)

Speidel, D. H.

1993-01-01

The size-frequency pattern of the 842 impact craters on Venus measured to date can be well described (across four standard deviation units) as a single log normal distribution with a mean crater diameter of 14.5 km. This result was predicted in 1991 on examination of the initial Magellan analysis. If this observed distribution is close to the real distribution, the 'missing' 90 percent of the small craters and the 'anomalous' lack of surface splotches may thus be neither missing nor anomalous. I think that the missing craters and missing splotches can be satisfactorily explained by accepting that the observed distribution approximates the real one, that it is not craters that are missing but the impactors. What you see is what you got. The implication that Venus crossing impactors would have the same type of log normal distribution is consistent with recently described distribution for terrestrial craters and Earth crossing asteroids.

A New Closed Form Approximation for BER for Optical Wireless Systems in Weak Atmospheric Turbulence

NASA Astrophysics Data System (ADS)

Kaushik, Rahul; Khandelwal, Vineet; Jain, R. C.

2018-04-01

Weak atmospheric turbulence condition in an optical wireless communication (OWC) is captured by log-normal distribution. The analytical evaluation of average bit error rate (BER) of an OWC system under weak turbulence is intractable as it involves the statistical averaging of Gaussian Q-function over log-normal distribution. In this paper, a simple closed form approximation for BER of OWC system under weak turbulence is given. Computation of BER for various modulation schemes is carried out using proposed expression. The results obtained using proposed expression compare favorably with those obtained using Gauss-Hermite quadrature approximation and Monte Carlo Simulations.

Log-Normality and Multifractal Analysis of Flame Surface Statistics

NASA Astrophysics Data System (ADS)

Saha, Abhishek; Chaudhuri, Swetaprovo; Law, Chung K.

2013-11-01

The turbulent flame surface is typically highly wrinkled and folded at a multitude of scales controlled by various flame properties. It is useful if the information contained in this complex geometry can be projected onto a simpler regular geometry for the use of spectral, wavelet or multifractal analyses. Here we investigate local flame surface statistics of turbulent flame expanding under constant pressure. First the statistics of local length ratio is experimentally obtained from high-speed Mie scattering images. For spherically expanding flame, length ratio on the measurement plane, at predefined equiangular sectors is defined as the ratio of the actual flame length to the length of a circular-arc of radius equal to the average radius of the flame. Assuming isotropic distribution of such flame segments we convolute suitable forms of the length-ratio probability distribution functions (pdfs) to arrive at corresponding area-ratio pdfs. Both the pdfs are found to be near log-normally distributed and shows self-similar behavior with increasing radius. Near log-normality and rather intermittent behavior of the flame-length ratio suggests similarity with dissipation rate quantities which stimulates multifractal analysis. Currently at Indian Institute of Science, India.

A log-sinh transformation for data normalization and variance stabilization

NASA Astrophysics Data System (ADS)

Wang, Q. J.; Shrestha, D. L.; Robertson, D. E.; Pokhrel, P.

2012-05-01

When quantifying model prediction uncertainty, it is statistically convenient to represent model errors that are normally distributed with a constant variance. The Box-Cox transformation is the most widely used technique to normalize data and stabilize variance, but it is not without limitations. In this paper, a log-sinh transformation is derived based on a pattern of errors commonly seen in hydrological model predictions. It is suited to applications where prediction variables are positively skewed and the spread of errors is seen to first increase rapidly, then slowly, and eventually approach a constant as the prediction variable becomes greater. The log-sinh transformation is applied in two case studies, and the results are compared with one- and two-parameter Box-Cox transformations.

Estimation of Microbial Contamination of Food from Prevalence and Concentration Data: Application to Listeria monocytogenes in Fresh Vegetables▿

PubMed Central

Crépet, Amélie; Albert, Isabelle; Dervin, Catherine; Carlin, Frédéric

2007-01-01

A normal distribution and a mixture model of two normal distributions in a Bayesian approach using prevalence and concentration data were used to establish the distribution of contamination of the food-borne pathogenic bacteria Listeria monocytogenes in unprocessed and minimally processed fresh vegetables. A total of 165 prevalence studies, including 15 studies with concentration data, were taken from the scientific literature and from technical reports and used for statistical analysis. The predicted mean of the normal distribution of the logarithms of viable L. monocytogenes per gram of fresh vegetables was −2.63 log viable L. monocytogenes organisms/g, and its standard deviation was 1.48 log viable L. monocytogenes organisms/g. These values were determined by considering one contaminated sample in prevalence studies in which samples are in fact negative. This deliberate overestimation is necessary to complete calculations. With the mixture model, the predicted mean of the distribution of the logarithm of viable L. monocytogenes per gram of fresh vegetables was −3.38 log viable L. monocytogenes organisms/g and its standard deviation was 1.46 log viable L. monocytogenes organisms/g. The probabilities of fresh unprocessed and minimally processed vegetables being contaminated with concentrations higher than 1, 2, and 3 log viable L. monocytogenes organisms/g were 1.44, 0.63, and 0.17%, respectively. Introducing a sensitivity rate of 80 or 95% in the mixture model had a small effect on the estimation of the contamination. In contrast, introducing a low sensitivity rate (40%) resulted in marked differences, especially for high percentiles. There was a significantly lower estimation of contamination in the papers and reports of 2000 to 2005 than in those of 1988 to 1999 and a lower estimation of contamination of leafy salads than that of sprouts and other vegetables. The interest of the mixture model for the estimation of microbial contamination is discussed. PMID:17098926

Statistical characteristics of the spatial distribution of territorial contamination by radionuclides from the Chernobyl accident

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

Arutyunyan, R.V.; Bol`shov, L.A.; Vasil`ev, S.K.

1994-06-01

The objective of this study was to clarify a number of issues related to the spatial distribution of contaminants from the Chernobyl accident. The effects of local statistics were addressed by collecting and analyzing (for Cesium 137) soil samples from a number of regions, and it was found that sample activity differed by a factor of 3-5. The effect of local non-uniformity was estimated by modeling the distribution of the average activity of a set of five samples for each of the regions, with the spread in the activities for a {+-}2 range being equal to 25%. The statistical characteristicsmore » of the distribution of contamination were then analyzed and found to be a log-normal distribution with the standard deviation being a function of test area. All data for the Bryanskaya Oblast area were analyzed statistically and were adequately described by a log-normal function.« less

Stochastic Modeling Approach to the Incubation Time of Prionic Diseases

NASA Astrophysics Data System (ADS)

Ferreira, A. S.; da Silva, M. A.; Cressoni, J. C.

2003-05-01

Transmissible spongiform encephalopathies are neurodegenerative diseases for which prions are the attributed pathogenic agents. A widely accepted theory assumes that prion replication is due to a direct interaction between the pathologic (PrPSc) form and the host-encoded (PrPC) conformation, in a kind of autocatalytic process. Here we show that the overall features of the incubation time of prion diseases are readily obtained if the prion reaction is described by a simple mean-field model. An analytical expression for the incubation time distribution then follows by associating the rate constant to a stochastic variable log normally distributed. The incubation time distribution is then also shown to be log normal and fits the observed BSE (bovine spongiform encephalopathy) data very well. Computer simulation results also yield the correct BSE incubation time distribution at low PrPC densities.

Statistical Characterization of the Mechanical Parameters of Intact Rock Under Triaxial Compression: An Experimental Proof of the Jinping Marble

NASA Astrophysics Data System (ADS)

Jiang, Quan; Zhong, Shan; Cui, Jie; Feng, Xia-Ting; Song, Leibo

2016-12-01

We investigated the statistical characteristics and probability distribution of the mechanical parameters of natural rock using triaxial compression tests. Twenty cores of Jinping marble were tested under each different levels of confining stress (i.e., 5, 10, 20, 30, and 40 MPa). From these full stress-strain data, we summarized the numerical characteristics and determined the probability distribution form of several important mechanical parameters, including deformational parameters, characteristic strength, characteristic strains, and failure angle. The statistical proofs relating to the mechanical parameters of rock presented new information about the marble's probabilistic distribution characteristics. The normal and log-normal distributions were appropriate for describing random strengths of rock; the coefficients of variation of the peak strengths had no relationship to the confining stress; the only acceptable random distribution for both Young's elastic modulus and Poisson's ratio was the log-normal function; and the cohesive strength had a different probability distribution pattern than the frictional angle. The triaxial tests and statistical analysis also provided experimental evidence for deciding the minimum reliable number of experimental sample and for picking appropriate parameter distributions to use in reliability calculations for rock engineering.

Improvement of Reynolds-Stress and Triple-Product Lag Models

NASA Technical Reports Server (NTRS)

Olsen, Michael E.; Lillard, Randolph P.

2017-01-01

The Reynolds-stress and triple product Lag models were created with a normal stress distribution which was denied by a 4:3:2 distribution of streamwise, spanwise and wall normal stresses, and a ratio of r(sub w) = 0.3k in the log layer region of high Reynolds number flat plate flow, which implies R11(+)= [4/(9/2)*.3] approximately 2.96. More recent measurements show a more complex picture of the log layer region at high Reynolds numbers. The first cut at improving these models along with the direction for future refinements is described. Comparison with recent high Reynolds number data shows areas where further work is needed, but also shows inclusion of the modeled turbulent transport terms improve the prediction where they influence the solution. Additional work is needed to make the model better match experiment, but there is significant improvement in many of the details of the log layer behavior.

210Po Log-normal distribution in human urines: Survey from Central Italy people

PubMed Central

Sisti, D.; Rocchi, M. B. L.; Meli, M. A.; Desideri, D.

2009-01-01

The death in London of the former secret service agent Alexander Livtinenko on 23 November 2006 generally attracted the attention of the public to the rather unknown radionuclide 210Po. This paper presents the results of a monitoring programme of 210Po background levels in the urines of noncontaminated people living in Central Italy (near the Republic of S. Marino). The relationship between age, sex, years of smoking, number of cigarettes per day, and 210Po concentration was also studied. The results indicated that the urinary 210Po concentration follows a surprisingly perfect Log-normal distribution. Log 210Po concentrations were positively correlated to age (p < 0.0001), number of daily smoked cigarettes (p = 0.006), and years of smoking (p = 0.021), and associated to sex (p = 0.019). Consequently, this study provides upper reference limits for each sub-group identified by significantly predictive variables. PMID:19750019

Probability density function of non-reactive solute concentration in heterogeneous porous formations.

PubMed

Bellin, Alberto; Tonina, Daniele

2007-10-30

Available models of solute transport in heterogeneous formations lack in providing complete characterization of the predicted concentration. This is a serious drawback especially in risk analysis where confidence intervals and probability of exceeding threshold values are required. Our contribution to fill this gap of knowledge is a probability distribution model for the local concentration of conservative tracers migrating in heterogeneous aquifers. Our model accounts for dilution, mechanical mixing within the sampling volume and spreading due to formation heterogeneity. It is developed by modeling local concentration dynamics with an Ito Stochastic Differential Equation (SDE) that under the hypothesis of statistical stationarity leads to the Beta probability distribution function (pdf) for the solute concentration. This model shows large flexibility in capturing the smoothing effect of the sampling volume and the associated reduction of the probability of exceeding large concentrations. Furthermore, it is fully characterized by the first two moments of the solute concentration, and these are the same pieces of information required for standard geostatistical techniques employing Normal or Log-Normal distributions. Additionally, we show that in the absence of pore-scale dispersion and for point concentrations the pdf model converges to the binary distribution of [Dagan, G., 1982. Stochastic modeling of groundwater flow by unconditional and conditional probabilities, 2, The solute transport. Water Resour. Res. 18 (4), 835-848.], while it approaches the Normal distribution for sampling volumes much larger than the characteristic scale of the aquifer heterogeneity. Furthermore, we demonstrate that the same model with the spatial moments replacing the statistical moments can be applied to estimate the proportion of the plume volume where solute concentrations are above or below critical thresholds. Application of this model to point and vertically averaged bromide concentrations from the first Cape Cod tracer test and to a set of numerical simulations confirms the above findings and for the first time it shows the superiority of the Beta model to both Normal and Log-Normal models in interpreting field data. Furthermore, we show that assuming a-priori that local concentrations are normally or log-normally distributed may result in a severe underestimate of the probability of exceeding large concentrations.

Empirical study of the tails of mutual fund size

NASA Astrophysics Data System (ADS)

Schwarzkopf, Yonathan; Farmer, J. Doyne

2010-06-01

The mutual fund industry manages about a quarter of the assets in the U.S. stock market and thus plays an important role in the U.S. economy. The question of how much control is concentrated in the hands of the largest players is best quantitatively discussed in terms of the tail behavior of the mutual fund size distribution. We study the distribution empirically and show that the tail is much better described by a log-normal than a power law, indicating less concentration than, for example, personal income. The results are highly statistically significant and are consistent across fifteen years. This contradicts a recent theory concerning the origin of the power law tails of the trading volume distribution. Based on the analysis in a companion paper, the log-normality is to be expected, and indicates that the distribution of mutual funds remains perpetually out of equilibrium.

Statistical distributions of ultra-low dose CT sinograms and their fundamental limits

NASA Astrophysics Data System (ADS)

Lee, Tzu-Cheng; Zhang, Ruoqiao; Alessio, Adam M.; Fu, Lin; De Man, Bruno; Kinahan, Paul E.

2017-03-01

Low dose CT imaging is typically constrained to be diagnostic. However, there are applications for even lowerdose CT imaging, including image registration across multi-frame CT images and attenuation correction for PET/CT imaging. We define this as the ultra-low-dose (ULD) CT regime where the exposure level is a factor of 10 lower than current low-dose CT technique levels. In the ULD regime it is possible to use statistically-principled image reconstruction methods that make full use of the raw data information. Since most statistical based iterative reconstruction methods are based on the assumption of that post-log noise distribution is close to Poisson or Gaussian, our goal is to understand the statistical distribution of ULD CT data with different non-positivity correction methods, and to understand when iterative reconstruction methods may be effective in producing images that are useful for image registration or attenuation correction in PET/CT imaging. We first used phantom measurement and calibrated simulation to reveal how the noise distribution deviate from normal assumption under the ULD CT flux environment. In summary, our results indicate that there are three general regimes: (1) Diagnostic CT, where post-log data are well modeled by normal distribution. (2) Lowdose CT, where normal distribution remains a reasonable approximation and statistically-principled (post-log) methods that assume a normal distribution have an advantage. (3) An ULD regime that is photon-starved and the quadratic approximation is no longer effective. For instance, a total integral density of 4.8 (ideal pi for 24 cm of water) for 120kVp, 0.5mAs of radiation source is the maximum pi value where a definitive maximum likelihood value could be found. This leads to fundamental limits in the estimation of ULD CT data when using a standard data processing stream

Analyzing repeated measures semi-continuous data, with application to an alcohol dependence study.

PubMed

Liu, Lei; Strawderman, Robert L; Johnson, Bankole A; O'Quigley, John M

2016-02-01

Two-part random effects models (Olsen and Schafer,(1) Tooze et al.(2)) have been applied to repeated measures of semi-continuous data, characterized by a mixture of a substantial proportion of zero values and a skewed distribution of positive values. In the original formulation of this model, the natural logarithm of the positive values is assumed to follow a normal distribution with a constant variance parameter. In this article, we review and consider three extensions of this model, allowing the positive values to follow (a) a generalized gamma distribution, (b) a log-skew-normal distribution, and (c) a normal distribution after the Box-Cox transformation. We allow for the possibility of heteroscedasticity. Maximum likelihood estimation is shown to be conveniently implemented in SAS Proc NLMIXED. The performance of the methods is compared through applications to daily drinking records in a secondary data analysis from a randomized controlled trial of topiramate for alcohol dependence treatment. We find that all three models provide a significantly better fit than the log-normal model, and there exists strong evidence for heteroscedasticity. We also compare the three models by the likelihood ratio tests for non-nested hypotheses (Vuong(3)). The results suggest that the generalized gamma distribution provides the best fit, though no statistically significant differences are found in pairwise model comparisons. © The Author(s) 2012.

Possible Statistics of Two Coupled Random Fields: Application to Passive Scalar

NASA Technical Reports Server (NTRS)

Dubrulle, B.; He, Guo-Wei; Bushnell, Dennis M. (Technical Monitor)

2000-01-01

We use the relativity postulate of scale invariance to derive the similarity transformations between two coupled scale-invariant random elds at different scales. We nd the equations leading to the scaling exponents. This formulation is applied to the case of passive scalars advected i) by a random Gaussian velocity field; and ii) by a turbulent velocity field. In the Gaussian case, we show that the passive scalar increments follow a log-Levy distribution generalizing Kraichnan's solution and, in an appropriate limit, a log-normal distribution. In the turbulent case, we show that when the velocity increments follow a log-Poisson statistics, the passive scalar increments follow a statistics close to log-Poisson. This result explains the experimental observations of Ruiz et al. about the temperature increments.

Simulations of large acoustic scintillations in the straits of Florida.

PubMed

Tang, Xin; Tappert, F D; Creamer, Dennis B

2006-12-01

Using a full-wave acoustic model, Monte Carlo numerical studies of intensity fluctuations in a realistic shallow water environment that simulates the Straits of Florida, including internal wave fluctuations and bottom roughness, have been performed. Results show that the sound intensity at distant receivers scintillates dramatically. The acoustic scintillation index SI increases rapidly with propagation range and is significantly greater than unity at ranges beyond about 10 km. This result supports a theoretical prediction by one of the authors. Statistical analyses show that the distribution of intensity of the random wave field saturates to the expected Rayleigh distribution with SI= 1 at short range due to multipath interference effects, and then SI continues to increase to large values. This effect, which is denoted supersaturation, is universal at long ranges in waveguides having lossy boundaries (where there is differential mode attenuation). The intensity distribution approaches a log-normal distribution to an excellent approximation; it may not be a universal distribution and comparison is also made to a K distribution. The long tails of the log-normal distribution cause "acoustic intermittency" in which very high, but rare, intensities occur.

Lognormal Distribution of Cellular Uptake of Radioactivity: Statistical Analysis of α-Particle Track Autoradiography

PubMed Central

Neti, Prasad V.S.V.; Howell, Roger W.

2010-01-01

Recently, the distribution of radioactivity among a population of cells labeled with 210Po was shown to be well described by a log-normal (LN) distribution function (J Nucl Med. 2006;47:1049–1058) with the aid of autoradiography. To ascertain the influence of Poisson statistics on the interpretation of the autoradiographic data, the present work reports on a detailed statistical analysis of these earlier data. Methods The measured distributions of α-particle tracks per cell were subjected to statistical tests with Poisson, LN, and Poisson-lognormal (P-LN) models. Results The LN distribution function best describes the distribution of radioactivity among cell populations exposed to 0.52 and 3.8 kBq/mL of 210Po-citrate. When cells were exposed to 67 kBq/mL, the P-LN distribution function gave a better fit; however, the underlying activity distribution remained log-normal. Conclusion The present analysis generally provides further support for the use of LN distributions to describe the cellular uptake of radioactivity. Care should be exercised when analyzing autoradiographic data on activity distributions to ensure that Poisson processes do not distort the underlying LN distribution. PMID:18483086

The stochastic distribution of available coefficient of friction for human locomotion of five different floor surfaces.

PubMed

Chang, Wen-Ruey; Matz, Simon; Chang, Chien-Chi

2014-05-01

The maximum coefficient of friction that can be supported at the shoe and floor interface without a slip is usually called the available coefficient of friction (ACOF) for human locomotion. The probability of a slip could be estimated using a statistical model by comparing the ACOF with the required coefficient of friction (RCOF), assuming that both coefficients have stochastic distributions. An investigation of the stochastic distributions of the ACOF of five different floor surfaces under dry, water and glycerol conditions is presented in this paper. One hundred friction measurements were performed on each floor surface under each surface condition. The Kolmogorov-Smirnov goodness-of-fit test was used to determine if the distribution of the ACOF was a good fit with the normal, log-normal and Weibull distributions. The results indicated that the ACOF distributions had a slightly better match with the normal and log-normal distributions than with the Weibull in only three out of 15 cases with a statistical significance. The results are far more complex than what had heretofore been published and different scenarios could emerge. Since the ACOF is compared with the RCOF for the estimate of slip probability, the distribution of the ACOF in seven cases could be considered a constant for this purpose when the ACOF is much lower or higher than the RCOF. A few cases could be represented by a normal distribution for practical reasons based on their skewness and kurtosis values without a statistical significance. No representation could be found in three cases out of 15. Copyright © 2013 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Probability distribution functions for unit hydrographs with optimization using genetic algorithm

NASA Astrophysics Data System (ADS)

Ghorbani, Mohammad Ali; Singh, Vijay P.; Sivakumar, Bellie; H. Kashani, Mahsa; Atre, Atul Arvind; Asadi, Hakimeh

2017-05-01

A unit hydrograph (UH) of a watershed may be viewed as the unit pulse response function of a linear system. In recent years, the use of probability distribution functions (pdfs) for determining a UH has received much attention. In this study, a nonlinear optimization model is developed to transmute a UH into a pdf. The potential of six popular pdfs, namely two-parameter gamma, two-parameter Gumbel, two-parameter log-normal, two-parameter normal, three-parameter Pearson distribution, and two-parameter Weibull is tested on data from the Lighvan catchment in Iran. The probability distribution parameters are determined using the nonlinear least squares optimization method in two ways: (1) optimization by programming in Mathematica; and (2) optimization by applying genetic algorithm. The results are compared with those obtained by the traditional linear least squares method. The results show comparable capability and performance of two nonlinear methods. The gamma and Pearson distributions are the most successful models in preserving the rising and recession limbs of the unit hydographs. The log-normal distribution has a high ability in predicting both the peak flow and time to peak of the unit hydrograph. The nonlinear optimization method does not outperform the linear least squares method in determining the UH (especially for excess rainfall of one pulse), but is comparable.

M-dwarf exoplanet surface density distribution. A log-normal fit from 0.07 to 400 AU

NASA Astrophysics Data System (ADS)

Meyer, Michael R.; Amara, Adam; Reggiani, Maddalena; Quanz, Sascha P.

2018-04-01

Aims: We fit a log-normal function to the M-dwarf orbital surface density distribution of gas giant planets, over the mass range 1-10 times that of Jupiter, from 0.07 to 400 AU. Methods: We used a Markov chain Monte Carlo approach to explore the likelihoods of various parameter values consistent with point estimates of the data given our assumed functional form. Results: This fit is consistent with radial velocity, microlensing, and direct-imaging observations, is well-motivated from theoretical and phenomenological points of view, and predicts results of future surveys. We present probability distributions for each parameter and a maximum likelihood estimate solution. Conclusions: We suggest that this function makes more physical sense than other widely used functions, and we explore the implications of our results on the design of future exoplanet surveys.

Flame surface statistics of constant-pressure turbulent expanding premixed flames

NASA Astrophysics Data System (ADS)

Saha, Abhishek; Chaudhuri, Swetaprovo; Law, Chung K.

2014-04-01

In this paper we investigate the local flame surface statistics of constant-pressure turbulent expanding flames. First the statistics of local length ratio is experimentally determined from high-speed planar Mie scattering images of spherically expanding flames, with the length ratio on the measurement plane, at predefined equiangular sectors, defined as the ratio of the actual flame length to the length of a circular-arc of radius equal to the average radius of the flame. Assuming isotropic distribution of such flame segments we then convolute suitable forms of the length-ratio probability distribution functions (pdfs) to arrive at the corresponding area-ratio pdfs. It is found that both the length ratio and area ratio pdfs are near log-normally distributed and shows self-similar behavior with increasing radius. Near log-normality and rather intermittent behavior of the flame-length ratio suggests similarity with dissipation rate quantities which stimulates multifractal analysis.

Detection of Person Misfit in Computerized Adaptive Tests with Polytomous Items.

ERIC Educational Resources Information Center

van Krimpen-Stoop, Edith M. L. A.; Meijer, Rob R.

2002-01-01

Compared the nominal and empirical null distributions of the standardized log-likelihood statistic for polytomous items for paper-and-pencil (P&P) and computerized adaptive tests (CATs). Results show that the empirical distribution of the statistic differed from the assumed standard normal distribution for both P&P tests and CATs. Also…

A Bayesian Surrogate for Regional Skew in Flood Frequency Analysis

NASA Astrophysics Data System (ADS)

Kuczera, George

1983-06-01

The problem of how to best utilize site and regional flood data to infer the shape parameter of a flood distribution is considered. One approach to this problem is given in Bulletin 17B of the U.S. Water Resources Council (1981) for the log-Pearson distribution. Here a lesser known distribution is considered, namely, the power normal which fits flood data as well as the log-Pearson and has a shape parameter denoted by λ derived from a Box-Cox power transformation. The problem of regionalizing λ is considered from an empirical Bayes perspective where site and regional flood data are used to infer λ. The distortive effects of spatial correlation and heterogeneity of site sampling variance of λ are explicitly studied with spatial correlation being found to be of secondary importance. The end product of this analysis is the posterior distribution of the power normal parameters expressing, in probabilistic terms, what is known about the parameters given site flood data and regional information on λ. This distribution can be used to provide the designer with several types of information. The posterior distribution of the T-year flood is derived. The effect of nonlinearity in λ on inference is illustrated. Because uncertainty in λ is explicitly allowed for, the understatement in confidence limits due to fixing λ (analogous to fixing log skew) is avoided. Finally, it is shown how to obtain the marginal flood distribution which can be used to select a design flood with specified exceedance probability.

Evaluation of the best fit distribution for partial duration series of daily rainfall in Madinah, western Saudi Arabia

NASA Astrophysics Data System (ADS)

Alahmadi, F.; Rahman, N. A.; Abdulrazzak, M.

2014-09-01

Rainfall frequency analysis is an essential tool for the design of water related infrastructure. It can be used to predict future flood magnitudes for a given magnitude and frequency of extreme rainfall events. This study analyses the application of rainfall partial duration series (PDS) in the vast growing urban Madinah city located in the western part of Saudi Arabia. Different statistical distributions were applied (i.e. Normal, Log Normal, Extreme Value type I, Generalized Extreme Value, Pearson Type III, Log Pearson Type III) and their distribution parameters were estimated using L-moments methods. Also, different selection criteria models are applied, e.g. Akaike Information Criterion (AIC), Corrected Akaike Information Criterion (AICc), Bayesian Information Criterion (BIC) and Anderson-Darling Criterion (ADC). The analysis indicated the advantage of Generalized Extreme Value as the best fit statistical distribution for Madinah partial duration daily rainfall series. The outcome of such an evaluation can contribute toward better design criteria for flood management, especially flood protection measures.

Gaussian Quadrature is an efficient method for the back-transformation in estimating the usual intake distribution when assessing dietary exposure.

PubMed

Dekkers, A L M; Slob, W

2012-10-01

In dietary exposure assessment, statistical methods exist for estimating the usual intake distribution from daily intake data. These methods transform the dietary intake data to normal observations, eliminate the within-person variance, and then back-transform the data to the original scale. We propose Gaussian Quadrature (GQ), a numerical integration method, as an efficient way of back-transformation. We compare GQ with six published methods. One method uses a log-transformation, while the other methods, including GQ, use a Box-Cox transformation. This study shows that, for various parameter choices, the methods with a Box-Cox transformation estimate the theoretical usual intake distributions quite well, although one method, a Taylor approximation, is less accurate. Two applications--on folate intake and fruit consumption--confirmed these results. In one extreme case, some methods, including GQ, could not be applied for low percentiles. We solved this problem by modifying GQ. One method is based on the assumption that the daily intakes are log-normally distributed. Even if this condition is not fulfilled, the log-transformation performs well as long as the within-individual variance is small compared to the mean. We conclude that the modified GQ is an efficient, fast and accurate method for estimating the usual intake distribution. Copyright © 2012 Elsevier Ltd. All rights reserved.

Money-center structures in dynamic banking systems

NASA Astrophysics Data System (ADS)

Li, Shouwei; Zhang, Minghui

2016-10-01

In this paper, we propose a dynamic model for banking systems based on the description of balance sheets. It generates some features identified through empirical analysis. Through simulation analysis of the model, we find that banking systems have the feature of money-center structures, that bank asset distributions are power-law distributions, and that contract size distributions are log-normal distributions.

Variance stabilization and normalization for one-color microarray data using a data-driven multiscale approach.

PubMed

Motakis, E S; Nason, G P; Fryzlewicz, P; Rutter, G A

2006-10-15

Many standard statistical techniques are effective on data that are normally distributed with constant variance. Microarray data typically violate these assumptions since they come from non-Gaussian distributions with a non-trivial mean-variance relationship. Several methods have been proposed that transform microarray data to stabilize variance and draw its distribution towards the Gaussian. Some methods, such as log or generalized log, rely on an underlying model for the data. Others, such as the spread-versus-level plot, do not. We propose an alternative data-driven multiscale approach, called the Data-Driven Haar-Fisz for microarrays (DDHFm) with replicates. DDHFm has the advantage of being 'distribution-free' in the sense that no parametric model for the underlying microarray data is required to be specified or estimated; hence, DDHFm can be applied very generally, not just to microarray data. DDHFm achieves very good variance stabilization of microarray data with replicates and produces transformed intensities that are approximately normally distributed. Simulation studies show that it performs better than other existing methods. Application of DDHFm to real one-color cDNA data validates these results. The R package of the Data-Driven Haar-Fisz transform (DDHFm) for microarrays is available in Bioconductor and CRAN.

Single-trial log transformation is optimal in frequency analysis of resting EEG alpha.

PubMed

Smulders, Fren T Y; Ten Oever, Sanne; Donkers, Franc C L; Quaedflieg, Conny W E M; van de Ven, Vincent

2018-02-01

The appropriate definition and scaling of the magnitude of electroencephalogram (EEG) oscillations is an underdeveloped area. The aim of this study was to optimize the analysis of resting EEG alpha magnitude, focusing on alpha peak frequency and nonlinear transformation of alpha power. A family of nonlinear transforms, Box-Cox transforms, were applied to find the transform that (a) maximized a non-disputed effect: the increase in alpha magnitude when the eyes are closed (Berger effect), and (b) made the distribution of alpha magnitude closest to normal across epochs within each participant, or across participants. The transformations were performed either at the single epoch level or at the epoch-average level. Alpha peak frequency showed large individual differences, yet good correspondence between various ways to estimate it in 2 min of eyes-closed and 2 min of eyes-open resting EEG data. Both alpha magnitude and the Berger effect were larger for individual alpha than for a generic (8-12 Hz) alpha band. The log-transform on single epochs (a) maximized the t-value of the contrast between the eyes-open and eyes-closed conditions when tested within each participant, and (b) rendered near-normally distributed alpha power across epochs and participants, thereby making further transformation of epoch averages superfluous. The results suggest that the log-normal distribution is a fundamental property of variations in alpha power across time in the order of seconds. Moreover, effects on alpha power appear to be multiplicative rather than additive. These findings support the use of the log-transform on single epochs to achieve appropriate scaling of alpha magnitude. © 2018 The Authors. European Journal of Neuroscience published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Shape of growth-rate distribution determines the type of Non-Gibrat’s Property

NASA Astrophysics Data System (ADS)

Ishikawa, Atushi; Fujimoto, Shouji; Mizuno, Takayuki

2011-11-01

In this study, the authors examine exhaustive business data on Japanese firms, which cover nearly all companies in the mid- and large-scale ranges in terms of firm size, to reach several key findings on profits/sales distribution and business growth trends. Here, profits denote net profits. First, detailed balance is observed not only in profits data but also in sales data. Furthermore, the growth-rate distribution of sales has wider tails than the linear growth-rate distribution of profits in log-log scale. On the one hand, in the mid-scale range of profits, the probability of positive growth decreases and the probability of negative growth increases symmetrically as the initial value increases. This is called Non-Gibrat’s First Property. On the other hand, in the mid-scale range of sales, the probability of positive growth decreases as the initial value increases, while the probability of negative growth hardly changes. This is called Non-Gibrat’s Second Property. Under detailed balance, Non-Gibrat’s First and Second Properties are analytically derived from the linear and quadratic growth-rate distributions in log-log scale, respectively. In both cases, the log-normal distribution is inferred from Non-Gibrat’s Properties and detailed balance. These analytic results are verified by empirical data. Consequently, this clarifies the notion that the difference in shapes between growth-rate distributions of sales and profits is closely related to the difference between the two Non-Gibrat’s Properties in the mid-scale range.

A spatial scan statistic for survival data based on Weibull distribution.

PubMed

Bhatt, Vijaya; Tiwari, Neeraj

2014-05-20

The spatial scan statistic has been developed as a geographical cluster detection analysis tool for different types of data sets such as Bernoulli, Poisson, ordinal, normal and exponential. We propose a scan statistic for survival data based on Weibull distribution. It may also be used for other survival distributions, such as exponential, gamma, and log normal. The proposed method is applied on the survival data of tuberculosis patients for the years 2004-2005 in Nainital district of Uttarakhand, India. Simulation studies reveal that the proposed method performs well for different survival distribution functions. Copyright © 2013 John Wiley & Sons, Ltd.

Parametric modelling of cost data in medical studies.

PubMed

Nixon, R M; Thompson, S G

2004-04-30

The cost of medical resources used is often recorded for each patient in clinical studies in order to inform decision-making. Although cost data are generally skewed to the right, interest is in making inferences about the population mean cost. Common methods for non-normal data, such as data transformation, assuming asymptotic normality of the sample mean or non-parametric bootstrapping, are not ideal. This paper describes possible parametric models for analysing cost data. Four example data sets are considered, which have different sample sizes and degrees of skewness. Normal, gamma, log-normal, and log-logistic distributions are fitted, together with three-parameter versions of the latter three distributions. Maximum likelihood estimates of the population mean are found; confidence intervals are derived by a parametric BC(a) bootstrap and checked by MCMC methods. Differences between model fits and inferences are explored.Skewed parametric distributions fit cost data better than the normal distribution, and should in principle be preferred for estimating the population mean cost. However for some data sets, we find that models that fit badly can give similar inferences to those that fit well. Conversely, particularly when sample sizes are not large, different parametric models that fit the data equally well can lead to substantially different inferences. We conclude that inferences are sensitive to choice of statistical model, which itself can remain uncertain unless there is enough data to model the tail of the distribution accurately. Investigating the sensitivity of conclusions to choice of model should thus be an essential component of analysing cost data in practice. Copyright 2004 John Wiley & Sons, Ltd.

Bidisperse and polydisperse suspension rheology at large solid fraction

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

Pednekar, Sidhant; Chun, Jaehun; Morris, Jeffrey F.

At the same solid volume fraction, bidisperse and polydisperse suspensions display lower viscosities, and weaker normal stress response, compared to monodisperse suspensions. The reduction of viscosity associated with size distribution can be explained by an increase of the maximum flowable, or jamming, solid fraction. In this work, concentrated or "dense" suspensions are simulated under strong shearing, where thermal motion and repulsive forces are negligible, but we allow for particle contact with a mild frictional interaction with interparticle friction coefficient of 0.2. Aspects of bidisperse suspension rheology are first revisited to establish that the approach reproduces established trends; the study ofmore » bidisperse suspensions at size ratios of large to small particle radii (2 to 4) shows that a minimum in the viscosity occurs for zeta slightly above 0.5, where zeta=phi_{large}/phi is the fraction of the total solid volume occupied by the large particles. The simple shear flows of polydisperse suspensions with truncated normal and log normal size distributions, and bidisperse suspensions which are statistically equivalent with these polydisperse cases up to third moment of the size distribution, are simulated and the rheologies are extracted. Prior work shows that such distributions with equivalent low-order moments have similar phi_{m}, and the rheological behaviors of normal, log normal and bidisperse cases are shown to be in close agreement for a wide range of standard deviation in particle size, with standard correlations which are functionally dependent on phi/phi_{m} providing excellent agreement with the rheology found in simulation. The close agreement of both viscosity and normal stress response between bi- and polydisperse suspensions demonstrates the controlling in influence of the maximum packing fraction in noncolloidal suspensions. Microstructural investigations and the stress distribution according to particle size are also presented.« less

Channel characterization and empirical model for ergodic capacity of free-space optical communication link

NASA Astrophysics Data System (ADS)

Alimi, Isiaka; Shahpari, Ali; Ribeiro, Vítor; Sousa, Artur; Monteiro, Paulo; Teixeira, António

2017-05-01

In this paper, we present experimental results on channel characterization of single input single output (SISO) free-space optical (FSO) communication link that is based on channel measurements. The histograms of the FSO channel samples and the log-normal distribution fittings are presented along with the measured scintillation index. Furthermore, we extend our studies to diversity schemes and propose a closed-form expression for determining ergodic channel capacity of multiple input multiple output (MIMO) FSO communication systems over atmospheric turbulence fading channels. The proposed empirical model is based on SISO FSO channel characterization. Also, the scintillation effects on the system performance are analyzed and results for different turbulence conditions are presented. Moreover, we observed that the histograms of the FSO channel samples that we collected from a 1548.51 nm link have good fits with log-normal distributions and the proposed model for MIMO FSO channel capacity is in conformity with the simulation results in terms of normalized mean-square error (NMSE).

On the scaling of the distribution of daily price fluctuations in the Mexican financial market index

NASA Astrophysics Data System (ADS)

Alfonso, Léster; Mansilla, Ricardo; Terrero-Escalante, César A.

2012-05-01

In this paper, a statistical analysis of log-return fluctuations of the IPC, the Mexican Stock Market Index is presented. A sample of daily data covering the period from 04/09/2000-04/09/2010 was analyzed, and fitted to different distributions. Tests of the goodness of fit were performed in order to quantitatively asses the quality of the estimation. Special attention was paid to the impact of the size of the sample on the estimated decay of the distributions tail. In this study a forceful rejection of normality was obtained. On the other hand, the null hypothesis that the log-fluctuations are fitted to a α-stable Lévy distribution cannot be rejected at the 5% significance level.

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

PubMed

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

2016-01-01

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

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

PubMed Central

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

2016-01-01

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

Growth models and the expected distribution of fluctuating asymmetry

USGS Publications Warehouse

Graham, John H.; Shimizu, Kunio; Emlen, John M.; Freeman, D. Carl; Merkel, John

2003-01-01

Multiplicative error accounts for much of the size-scaling and leptokurtosis in fluctuating asymmetry. It arises when growth involves the addition of tissue to that which is already present. Such errors are lognormally distributed. The distribution of the difference between two lognormal variates is leptokurtic. If those two variates are correlated, then the asymmetry variance will scale with size. Inert tissues typically exhibit additive error and have a gamma distribution. Although their asymmetry variance does not exhibit size-scaling, the distribution of the difference between two gamma variates is nevertheless leptokurtic. Measurement error is also additive, but has a normal distribution. Thus, the measurement of fluctuating asymmetry may involve the mixing of additive and multiplicative error. When errors are multiplicative, we recommend computing log E(l) − log E(r), the difference between the logarithms of the expected values of left and right sides, even when size-scaling is not obvious. If l and r are lognormally distributed, and measurement error is nil, the resulting distribution will be normal, and multiplicative error will not confound size-related changes in asymmetry. When errors are additive, such a transformation to remove size-scaling is unnecessary. Nevertheless, the distribution of l − r may still be leptokurtic.

Generalised Extreme Value Distributions Provide a Natural Hypothesis for the Shape of Seed Mass Distributions

PubMed Central

2015-01-01

Among co-occurring species, values for functionally important plant traits span orders of magnitude, are uni-modal, and generally positively skewed. Such data are usually log-transformed “for normality” but no convincing mechanistic explanation for a log-normal expectation exists. Here we propose a hypothesis for the distribution of seed masses based on generalised extreme value distributions (GEVs), a class of probability distributions used in climatology to characterise the impact of event magnitudes and frequencies; events that impose strong directional selection on biological traits. In tests involving datasets from 34 locations across the globe, GEVs described log10 seed mass distributions as well or better than conventional normalising statistics in 79% of cases, and revealed a systematic tendency for an overabundance of small seed sizes associated with low latitudes. GEVs characterise disturbance events experienced in a location to which individual species’ life histories could respond, providing a natural, biological explanation for trait expression that is lacking from all previous hypotheses attempting to describe trait distributions in multispecies assemblages. We suggest that GEVs could provide a mechanistic explanation for plant trait distributions and potentially link biology and climatology under a single paradigm. PMID:25830773

Statistical analysis of variability properties of the Kepler blazar W2R 1926+42

NASA Astrophysics Data System (ADS)

Li, Yutong; Hu, Shaoming; Wiita, Paul J.; Gupta, Alok C.

2018-04-01

We analyzed Kepler light curves of the blazar W2R 1926+42 that provided nearly continuous coverage from quarter 11 through quarter 17 (589 days between 2011 and 2013) and examined some of their flux variability properties. We investigate the possibility that the light curve is dominated by a large number of individual flares and adopt exponential rise and decay models to investigate the symmetry properties of flares. We found that those variations of W2R 1926+42 are predominantly asymmetric with weak tendencies toward positive asymmetry (rapid rise and slow decay). The durations (D) and the amplitudes (F0) of flares can be fit with log-normal distributions. The energy (E) of each flare is also estimated for the first time. There are positive correlations between logD and logE with a slope of 1.36, and between logF0 and logE with a slope of 1.12. Lomb-Scargle periodograms are used to estimate the power spectral density (PSD) shape. It is well described by a power law with an index ranging between -1.1 and -1.5. The sizes of the emission regions, R, are estimated to be in the range of 1.1 × 1015cm - 6.6 × 1016cm. The flare asymmetry is difficult to explain by a light travel time effect but may be caused by differences between the timescales for acceleration and dissipation of high-energy particles in the relativistic jet. A jet-in-jet model also could produce the observed log-normal distributions.

On the null distribution of Bayes factors in linear regression

USDA-ARS?s Scientific Manuscript database

We show that under the null, the 2 log (Bayes factor) is asymptotically distributed as a weighted sum of chi-squared random variables with a shifted mean. This claim holds for Bayesian multi-linear regression with a family of conjugate priors, namely, the normal-inverse-gamma prior, the g-prior, and...

Species-abundance distribution patterns of soil fungi: contribution to the ecological understanding of their response to experimental fire in Mediterranean maquis (southern Italy).

PubMed

Persiani, Anna Maria; Maggi, Oriana

2013-01-01

Experimental fires, of both low and high intensity, were lit during summer 2000 and the following 2 y in the Castel Volturno Nature Reserve, southern Italy. Soil samples were collected Jul 2000-Jul 2002 to analyze the soil fungal community dynamics. Species abundance distribution patterns (geometric, logarithmic, log normal, broken-stick) were compared. We plotted datasets with information both on species richness and abundance for total, xerotolerant and heat-stimulated soil microfungi. The xerotolerant fungi conformed to a broken-stick model for both the low- and high intensity fires at 7 and 84 d after the fire; their distribution subsequently followed logarithmic models in the 2 y following the fire. The distribution of the heat-stimulated fungi changed from broken-stick to logarithmic models and eventually to a log-normal model during the post-fire recovery. Xerotolerant and, to a far greater extent, heat-stimulated soil fungi acquire an important functional role following soil water stress and/or fire disturbance; these disturbances let them occupy unsaturated habitats and become increasingly abundant over time.

Thermal and log-normal distributions of plasma in laser driven Coulomb explosions of deuterium clusters

NASA Astrophysics Data System (ADS)

Barbarino, M.; Warrens, M.; Bonasera, A.; Lattuada, D.; Bang, W.; Quevedo, H. J.; Consoli, F.; de Angelis, R.; Andreoli, P.; Kimura, S.; Dyer, G.; Bernstein, A. C.; Hagel, K.; Barbui, M.; Schmidt, K.; Gaul, E.; Donovan, M. E.; Natowitz, J. B.; Ditmire, T.

2016-08-01

In this work, we explore the possibility that the motion of the deuterium ions emitted from Coulomb cluster explosions is highly disordered enough to resemble thermalization. We analyze the process of nuclear fusion reactions driven by laser-cluster interactions in experiments conducted at the Texas Petawatt laser facility using a mixture of D2+3He and CD4+3He cluster targets. When clusters explode by Coulomb repulsion, the emission of the energetic ions is “nearly” isotropic. In the framework of cluster Coulomb explosions, we analyze the energy distributions of the ions using a Maxwell-Boltzmann (MB) distribution, a shifted MB distribution (sMB), and the energy distribution derived from a log-normal (LN) size distribution of clusters. We show that the first two distributions reproduce well the experimentally measured ion energy distributions and the number of fusions from d-d and d-3He reactions. The LN distribution is a good representation of the ion kinetic energy distribution well up to high momenta where the noise becomes dominant, but overestimates both the neutron and the proton yields. If the parameters of the LN distributions are chosen to reproduce the fusion yields correctly, the experimentally measured high energy ion spectrum is not well represented. We conclude that the ion kinetic energy distribution is highly disordered and practically not distinguishable from a thermalized one.

Analysis of field size distributions, LACIE test sites 5029, 5033, and 5039, Anhwei Province, People's Republic of China

NASA Technical Reports Server (NTRS)

Podwysocki, M. H.

1976-01-01

A study was made of the field size distributions for LACIE test sites 5029, 5033, and 5039, People's Republic of China. Field lengths and widths were measured from LANDSAT imagery, and field area was statistically modeled. Field size parameters have log-normal or Poisson frequency distributions. These were normalized to the Gaussian distribution and theoretical population curves were made. When compared to fields in other areas of the same country measured in the previous study, field lengths and widths in the three LACIE test sites were 2 to 3 times smaller and areas were smaller by an order of magnitude.

Problems with Using the Normal Distribution – and Ways to Improve Quality and Efficiency of Data Analysis

PubMed Central

Limpert, Eckhard; Stahel, Werner A.

2011-01-01

Background The Gaussian or normal distribution is the most established model to characterize quantitative variation of original data. Accordingly, data are summarized using the arithmetic mean and the standard deviation, by ± SD, or with the standard error of the mean, ± SEM. This, together with corresponding bars in graphical displays has become the standard to characterize variation. Methodology/Principal Findings Here we question the adequacy of this characterization, and of the model. The published literature provides numerous examples for which such descriptions appear inappropriate because, based on the “95% range check”, their distributions are obviously skewed. In these cases, the symmetric characterization is a poor description and may trigger wrong conclusions. To solve the problem, it is enlightening to regard causes of variation. Multiplicative causes are by far more important than additive ones, in general, and benefit from a multiplicative (or log-) normal approach. Fortunately, quite similar to the normal, the log-normal distribution can now be handled easily and characterized at the level of the original data with the help of both, a new sign, x/, times-divide, and notation. Analogous to ± SD, it connects the multiplicative (or geometric) mean * and the multiplicative standard deviation s* in the form * x/s*, that is advantageous and recommended. Conclusions/Significance The corresponding shift from the symmetric to the asymmetric view will substantially increase both, recognition of data distributions, and interpretation quality. It will allow for savings in sample size that can be considerable. Moreover, this is in line with ethical responsibility. Adequate models will improve concepts and theories, and provide deeper insight into science and life. PMID:21779325

Problems with using the normal distribution--and ways to improve quality and efficiency of data analysis.

PubMed

Limpert, Eckhard; Stahel, Werner A

2011-01-01

The gaussian or normal distribution is the most established model to characterize quantitative variation of original data. Accordingly, data are summarized using the arithmetic mean and the standard deviation, by mean ± SD, or with the standard error of the mean, mean ± SEM. This, together with corresponding bars in graphical displays has become the standard to characterize variation. Here we question the adequacy of this characterization, and of the model. The published literature provides numerous examples for which such descriptions appear inappropriate because, based on the "95% range check", their distributions are obviously skewed. In these cases, the symmetric characterization is a poor description and may trigger wrong conclusions. To solve the problem, it is enlightening to regard causes of variation. Multiplicative causes are by far more important than additive ones, in general, and benefit from a multiplicative (or log-) normal approach. Fortunately, quite similar to the normal, the log-normal distribution can now be handled easily and characterized at the level of the original data with the help of both, a new sign, x/, times-divide, and notation. Analogous to mean ± SD, it connects the multiplicative (or geometric) mean mean * and the multiplicative standard deviation s* in the form mean * x/s*, that is advantageous and recommended. The corresponding shift from the symmetric to the asymmetric view will substantially increase both, recognition of data distributions, and interpretation quality. It will allow for savings in sample size that can be considerable. Moreover, this is in line with ethical responsibility. Adequate models will improve concepts and theories, and provide deeper insight into science and life.

Diameter distribution in a Brazilian tropical dry forest domain: predictions for the stand and species.

PubMed

Lima, Robson B DE; Bufalino, Lina; Alves, Francisco T; Silva, José A A DA; Ferreira, Rinaldo L C

2017-01-01

Currently, there is a lack of studies on the correct utilization of continuous distributions for dry tropical forests. Therefore, this work aims to investigate the diameter structure of a brazilian tropical dry forest and to select suitable continuous distributions by means of statistic tools for the stand and the main species. Two subsets were randomly selected from 40 plots. Diameter at base height was obtained. The following functions were tested: log-normal; gamma; Weibull 2P and Burr. The best fits were selected by Akaike's information validation criterion. Overall, the diameter distribution of the dry tropical forest was better described by negative exponential curves and positive skewness. The forest studied showed diameter distributions with decreasing probability for larger trees. This behavior was observed for both the main species and the stand. The generalization of the function fitted for the main species show that the development of individual models is needed. The Burr function showed good flexibility to describe the diameter structure of the stand and the behavior of Mimosa ophthalmocentra and Bauhinia cheilantha species. For Poincianella bracteosa, Aspidosperma pyrifolium and Myracrodum urundeuva better fitting was obtained with the log-normal function.

Beyond the power law: Uncovering stylized facts in interbank networks

NASA Astrophysics Data System (ADS)

Vandermarliere, Benjamin; Karas, Alexei; Ryckebusch, Jan; Schoors, Koen

2015-06-01

We use daily data on bilateral interbank exposures and monthly bank balance sheets to study network characteristics of the Russian interbank market over August 1998-October 2004. Specifically, we examine the distributions of (un)directed (un)weighted degree, nodal attributes (bank assets, capital and capital-to-assets ratio) and edge weights (loan size and counterparty exposure). We search for the theoretical distribution that fits the data best and report the "best" fit parameters. We observe that all studied distributions are heavy tailed. The fat tail typically contains 20% of the data and can be mostly described well by a truncated power law. Also the power law, stretched exponential and log-normal provide reasonably good fits to the tails of the data. In most cases, however, separating the bulk and tail parts of the data is hard, so we proceed to study the full range of the events. We find that the stretched exponential and the log-normal distributions fit the full range of the data best. These conclusions are robust to (1) whether we aggregate the data over a week, month, quarter or year; (2) whether we look at the "growth" versus "maturity" phases of interbank market development; and (3) with minor exceptions, whether we look at the "normal" versus "crisis" operation periods. In line with prior research, we find that the network topology changes greatly as the interbank market moves from a "normal" to a "crisis" operation period.

Transient Properties of Probability Distribution for a Markov Process with Size-dependent Additive Noise

NASA Astrophysics Data System (ADS)

Yamada, Yuhei; Yamazaki, Yoshihiro

2018-04-01

This study considered a stochastic model for cluster growth in a Markov process with a cluster size dependent additive noise. According to this model, the probability distribution of the cluster size transiently becomes an exponential or a log-normal distribution depending on the initial condition of the growth. In this letter, a master equation is obtained for this model, and derivation of the distributions is discussed.

Including operational data in QMRA model: development and impact of model inputs.

PubMed

Jaidi, Kenza; Barbeau, Benoit; Carrière, Annie; Desjardins, Raymond; Prévost, Michèle

2009-03-01

A Monte Carlo model, based on the Quantitative Microbial Risk Analysis approach (QMRA), has been developed to assess the relative risks of infection associated with the presence of Cryptosporidium and Giardia in drinking water. The impact of various approaches for modelling the initial parameters of the model on the final risk assessments is evaluated. The Monte Carlo simulations that we performed showed that the occurrence of parasites in raw water was best described by a mixed distribution: log-Normal for concentrations > detection limit (DL), and a uniform distribution for concentrations < DL. The selection of process performance distributions for modelling the performance of treatment (filtration and ozonation) influences the estimated risks significantly. The mean annual risks for conventional treatment are: 1.97E-03 (removal credit adjusted by log parasite = log spores), 1.58E-05 (log parasite = 1.7 x log spores) or 9.33E-03 (regulatory credits based on the turbidity measurement in filtered water). Using full scale validated SCADA data, the simplified calculation of CT performed at the plant was shown to largely underestimate the risk relative to a more detailed CT calculation, which takes into consideration the downtime and system failure events identified at the plant (1.46E-03 vs. 3.93E-02 for the mean risk).

Performance of statistical models to predict mental health and substance abuse cost.

PubMed

Montez-Rath, Maria; Christiansen, Cindy L; Ettner, Susan L; Loveland, Susan; Rosen, Amy K

2006-10-26

Providers use risk-adjustment systems to help manage healthcare costs. Typically, ordinary least squares (OLS) models on either untransformed or log-transformed cost are used. We examine the predictive ability of several statistical models, demonstrate how model choice depends on the goal for the predictive model, and examine whether building models on samples of the data affects model choice. Our sample consisted of 525,620 Veterans Health Administration patients with mental health (MH) or substance abuse (SA) diagnoses who incurred costs during fiscal year 1999. We tested two models on a transformation of cost: a Log Normal model and a Square-root Normal model, and three generalized linear models on untransformed cost, defined by distributional assumption and link function: Normal with identity link (OLS); Gamma with log link; and Gamma with square-root link. Risk-adjusters included age, sex, and 12 MH/SA categories. To determine the best model among the entire dataset, predictive ability was evaluated using root mean square error (RMSE), mean absolute prediction error (MAPE), and predictive ratios of predicted to observed cost (PR) among deciles of predicted cost, by comparing point estimates and 95% bias-corrected bootstrap confidence intervals. To study the effect of analyzing a random sample of the population on model choice, we re-computed these statistics using random samples beginning with 5,000 patients and ending with the entire sample. The Square-root Normal model had the lowest estimates of the RMSE and MAPE, with bootstrap confidence intervals that were always lower than those for the other models. The Gamma with square-root link was best as measured by the PRs. The choice of best model could vary if smaller samples were used and the Gamma with square-root link model had convergence problems with small samples. Models with square-root transformation or link fit the data best. This function (whether used as transformation or as a link) seems to help deal with the high comorbidity of this population by introducing a form of interaction. The Gamma distribution helps with the long tail of the distribution. However, the Normal distribution is suitable if the correct transformation of the outcome is used.

Income distribution dependence of poverty measure: A theoretical analysis

NASA Astrophysics Data System (ADS)

Chattopadhyay, Amit K.; Mallick, Sushanta K.

2007-04-01

Using a modified deprivation (or poverty) function, in this paper, we theoretically study the changes in poverty with respect to the ‘global’ mean and variance of the income distribution using Indian survey data. We show that when the income obeys a log-normal distribution, a rising mean income generally indicates a reduction in poverty while an increase in the variance of the income distribution increases poverty. This altruistic view for a developing economy, however, is not tenable anymore once the poverty index is found to follow a pareto distribution. Here although a rising mean income indicates a reduction in poverty, due to the presence of an inflexion point in the poverty function, there is a critical value of the variance below which poverty decreases with increasing variance while beyond this value, poverty undergoes a steep increase followed by a decrease with respect to higher variance. Identifying this inflexion point as the poverty line, we show that the pareto poverty function satisfies all three standard axioms of a poverty index [N.C. Kakwani, Econometrica 43 (1980) 437; A.K. Sen, Econometrica 44 (1976) 219] whereas the log-normal distribution falls short of this requisite. Following these results, we make quantitative predictions to correlate a developing with a developed economy.

Comparison of hypertabastic survival model with other unimodal hazard rate functions using a goodness-of-fit test.

PubMed

Tahir, M Ramzan; Tran, Quang X; Nikulin, Mikhail S

2017-05-30

We studied the problem of testing a hypothesized distribution in survival regression models when the data is right censored and survival times are influenced by covariates. A modified chi-squared type test, known as Nikulin-Rao-Robson statistic, is applied for the comparison of accelerated failure time models. This statistic is used to test the goodness-of-fit for hypertabastic survival model and four other unimodal hazard rate functions. The results of simulation study showed that the hypertabastic distribution can be used as an alternative to log-logistic and log-normal distribution. In statistical modeling, because of its flexible shape of hazard functions, this distribution can also be used as a competitor of Birnbaum-Saunders and inverse Gaussian distributions. The results for the real data application are shown. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

SMALL-SCALE AND GLOBAL DYNAMOS AND THE AREA AND FLUX DISTRIBUTIONS OF ACTIVE REGIONS, SUNSPOT GROUPS, AND SUNSPOTS: A MULTI-DATABASE STUDY

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

Muñoz-Jaramillo, Andrés; Windmueller, John C.; Amouzou, Ernest C.

2015-02-10

In this work, we take advantage of 11 different sunspot group, sunspot, and active region databases to characterize the area and flux distributions of photospheric magnetic structures. We find that, when taken separately, different databases are better fitted by different distributions (as has been reported previously in the literature). However, we find that all our databases can be reconciled by the simple application of a proportionality constant, and that, in reality, different databases are sampling different parts of a composite distribution. This composite distribution is made up by linear combination of Weibull and log-normal distributions—where a pure Weibull (log-normal) characterizesmore » the distribution of structures with fluxes below (above) 10{sup 21}Mx (10{sup 22}Mx). Additionally, we demonstrate that the Weibull distribution shows the expected linear behavior of a power-law distribution (when extended to smaller fluxes), making our results compatible with the results of Parnell et al. We propose that this is evidence of two separate mechanisms giving rise to visible structures on the photosphere: one directly connected to the global component of the dynamo (and the generation of bipolar active regions), and the other with the small-scale component of the dynamo (and the fragmentation of magnetic structures due to their interaction with turbulent convection)« less

Ordinal probability effect measures for group comparisons in multinomial cumulative link models.

PubMed

Agresti, Alan; Kateri, Maria

2017-03-01

We consider simple ordinal model-based probability effect measures for comparing distributions of two groups, adjusted for explanatory variables. An "ordinal superiority" measure summarizes the probability that an observation from one distribution falls above an independent observation from the other distribution, adjusted for explanatory variables in a model. The measure applies directly to normal linear models and to a normal latent variable model for ordinal response variables. It equals Φ(β/2) for the corresponding ordinal model that applies a probit link function to cumulative multinomial probabilities, for standard normal cdf Φ and effect β that is the coefficient of the group indicator variable. For the more general latent variable model for ordinal responses that corresponds to a linear model with other possible error distributions and corresponding link functions for cumulative multinomial probabilities, the ordinal superiority measure equals exp(β)/[1+exp(β)] with the log-log link and equals approximately exp(β/2)/[1+exp(β/2)] with the logit link, where β is the group effect. Another ordinal superiority measure generalizes the difference of proportions from binary to ordinal responses. We also present related measures directly for ordinal models for the observed response that need not assume corresponding latent response models. We present confidence intervals for the measures and illustrate with an example. © 2016, The International Biometric Society.

Probabilistic structural analysis of a truss typical for space station

NASA Technical Reports Server (NTRS)

Pai, Shantaram S.

1990-01-01

A three-bay, space, cantilever truss is probabilistically evaluated using the computer code NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) to identify and quantify the uncertainties and respective sensitivities associated with corresponding uncertainties in the primitive variables (structural, material, and loads parameters) that defines the truss. The distribution of each of these primitive variables is described in terms of one of several available distributions such as the Weibull, exponential, normal, log-normal, etc. The cumulative distribution function (CDF's) for the response functions considered and sensitivities associated with the primitive variables for given response are investigated. These sensitivities help in determining the dominating primitive variables for that response.

Probabilistic properties of wavelets in kinetic surface roughening

NASA Astrophysics Data System (ADS)

Bershadskii, A.

2001-08-01

Using the data of a recent numerical simulation [M. Ahr and M. Biehl, Phys. Rev. E 62, 1773 (2000)] of homoepitaxial growth it is shown that the observed probability distribution of a wavelet based measure of the growing surface roughness is consistent with a stretched log-normal distribution and the corresponding branching dimension depends on the level of particle desorption.

A model for the flux-r.m.s. correlation in blazar variability or the minijets-in-a-jet statistical model

NASA Astrophysics Data System (ADS)

Biteau, J.; Giebels, B.

2012-12-01

Very high energy gamma-ray variability of blazar emission remains of puzzling origin. Fast flux variations down to the minute time scale, as observed with H.E.S.S. during flares of the blazar PKS 2155-304, suggests that variability originates from the jet, where Doppler boosting can be invoked to relax causal constraints on the size of the emission region. The observation of log-normality in the flux distributions should rule out additive processes, such as those resulting from uncorrelated multiple-zone emission models, and favour an origin of the variability from multiplicative processes not unlike those observed in a broad class of accreting systems. We show, using a simple kinematic model, that Doppler boosting of randomly oriented emitting regions generates flux distributions following a Pareto law, that the linear flux-r.m.s. relation found for a single zone holds for a large number of emitting regions, and that the skewed distribution of the total flux is close to a log-normal, despite arising from an additive process.

Coverage dependent molecular assembly of anthraquinone on Au(111)

NASA Astrophysics Data System (ADS)

DeLoach, Andrew S.; Conrad, Brad R.; Einstein, T. L.; Dougherty, Daniel B.

2017-11-01

A scanning tunneling microscopy study of anthraquinone (AQ) on the Au(111) surface shows that the molecules self-assemble into several structures depending on the local surface coverage. At high coverages, a close-packed saturated monolayer is observed, while at low coverages, mobile surface molecules coexist with stable chiral hexamer clusters. At intermediate coverages, a disordered 2D porous network interlinking close-packed islands is observed in contrast to the giant honeycomb networks observed for the same molecule on Cu(111). This difference verifies the predicted extreme sensitivity [J. Wyrick et al., Nano Lett. 11, 2944 (2011)] of the pore network to small changes in the surface electronic structure. Quantitative analysis of the 2D pore network reveals that the areas of the vacancy islands are distributed log-normally. Log-normal distributions are typically associated with the product of random variables (multiplicative noise), and we propose that the distribution of pore sizes for AQ on Au(111) originates from random linear rate constants for molecules to either desorb from the surface or detach from the region of a nucleated pore.

Coverage dependent molecular assembly of anthraquinone on Au(111).

PubMed

DeLoach, Andrew S; Conrad, Brad R; Einstein, T L; Dougherty, Daniel B

2017-11-14

A scanning tunneling microscopy study of anthraquinone (AQ) on the Au(111) surface shows that the molecules self-assemble into several structures depending on the local surface coverage. At high coverages, a close-packed saturated monolayer is observed, while at low coverages, mobile surface molecules coexist with stable chiral hexamer clusters. At intermediate coverages, a disordered 2D porous network interlinking close-packed islands is observed in contrast to the giant honeycomb networks observed for the same molecule on Cu(111). This difference verifies the predicted extreme sensitivity [J. Wyrick et al., Nano Lett. 11, 2944 (2011)] of the pore network to small changes in the surface electronic structure. Quantitative analysis of the 2D pore network reveals that the areas of the vacancy islands are distributed log-normally. Log-normal distributions are typically associated with the product of random variables (multiplicative noise), and we propose that the distribution of pore sizes for AQ on Au(111) originates from random linear rate constants for molecules to either desorb from the surface or detach from the region of a nucleated pore.

Ejected Particle Size Distributions from Shocked Metal Surfaces

DOE PAGES

Schauer, M. M.; Buttler, W. T.; Frayer, D. K.; ...

2017-04-12

Here, we present size distributions for particles ejected from features machined onto the surface of shocked Sn targets. The functional form of the size distributions is assumed to be log-normal, and the characteristic parameters of the distribution are extracted from the measured angular distribution of light scattered from a laser beam incident on the ejected particles. We also found strong evidence for a bimodal distribution of particle sizes with smaller particles evolved from features machined into the target surface and larger particles being produced at the edges of these features.

Ejected Particle Size Distributions from Shocked Metal Surfaces

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

Schauer, M. M.; Buttler, W. T.; Frayer, D. K.

Here, we present size distributions for particles ejected from features machined onto the surface of shocked Sn targets. The functional form of the size distributions is assumed to be log-normal, and the characteristic parameters of the distribution are extracted from the measured angular distribution of light scattered from a laser beam incident on the ejected particles. We also found strong evidence for a bimodal distribution of particle sizes with smaller particles evolved from features machined into the target surface and larger particles being produced at the edges of these features.

Methane Leaks from Natural Gas Systems Follow Extreme Distributions.

PubMed

Brandt, Adam R; Heath, Garvin A; Cooley, Daniel

2016-11-15

Future energy systems may rely on natural gas as a low-cost fuel to support variable renewable power. However, leaking natural gas causes climate damage because methane (CH 4 ) has a high global warming potential. In this study, we use extreme-value theory to explore the distribution of natural gas leak sizes. By analyzing ∼15 000 measurements from 18 prior studies, we show that all available natural gas leakage data sets are statistically heavy-tailed, and that gas leaks are more extremely distributed than other natural and social phenomena. A unifying result is that the largest 5% of leaks typically contribute over 50% of the total leakage volume. While prior studies used log-normal model distributions, we show that log-normal functions poorly represent tail behavior. Our results suggest that published uncertainty ranges of CH 4 emissions are too narrow, and that larger sample sizes are required in future studies to achieve targeted confidence intervals. Additionally, we find that cross-study aggregation of data sets to increase sample size is not recommended due to apparent deviation between sampled populations. Understanding the nature of leak distributions can improve emission estimates, better illustrate their uncertainty, allow prioritization of source categories, and improve sampling design. Also, these data can be used for more effective design of leak detection technologies.

Predicting clicks of PubMed articles.

PubMed

Mao, Yuqing; Lu, Zhiyong

2013-01-01

Predicting the popularity or access usage of an article has the potential to improve the quality of PubMed searches. We can model the click trend of each article as its access changes over time by mining the PubMed query logs, which contain the previous access history for all articles. In this article, we examine the access patterns produced by PubMed users in two years (July 2009 to July 2011). We explore the time series of accesses for each article in the query logs, model the trends with regression approaches, and subsequently use the models for prediction. We show that the click trends of PubMed articles are best fitted with a log-normal regression model. This model allows the number of accesses an article receives and the time since it first becomes available in PubMed to be related via quadratic and logistic functions, with the model parameters to be estimated via maximum likelihood. Our experiments predicting the number of accesses for an article based on its past usage demonstrate that the mean absolute error and mean absolute percentage error of our model are 4.0% and 8.1% lower than the power-law regression model, respectively. The log-normal distribution is also shown to perform significantly better than a previous prediction method based on a human memory theory in cognitive science. This work warrants further investigation on the utility of such a log-normal regression approach towards improving information access in PubMed.

Predicting clicks of PubMed articles

PubMed Central

Mao, Yuqing; Lu, Zhiyong

2013-01-01

Predicting the popularity or access usage of an article has the potential to improve the quality of PubMed searches. We can model the click trend of each article as its access changes over time by mining the PubMed query logs, which contain the previous access history for all articles. In this article, we examine the access patterns produced by PubMed users in two years (July 2009 to July 2011). We explore the time series of accesses for each article in the query logs, model the trends with regression approaches, and subsequently use the models for prediction. We show that the click trends of PubMed articles are best fitted with a log-normal regression model. This model allows the number of accesses an article receives and the time since it first becomes available in PubMed to be related via quadratic and logistic functions, with the model parameters to be estimated via maximum likelihood. Our experiments predicting the number of accesses for an article based on its past usage demonstrate that the mean absolute error and mean absolute percentage error of our model are 4.0% and 8.1% lower than the power-law regression model, respectively. The log-normal distribution is also shown to perform significantly better than a previous prediction method based on a human memory theory in cognitive science. This work warrants further investigation on the utility of such a log-normal regression approach towards improving information access in PubMed. PMID:24551386

Statistical distribution of building lot frontage: application for Tokyo downtown districts

NASA Astrophysics Data System (ADS)

Usui, Hiroyuki

2018-03-01

The frontage of a building lot is the determinant factor of the residential environment. The statistical distribution of building lot frontages shows how the perimeters of urban blocks are shared by building lots for a given density of buildings and roads. For practitioners in urban planning, this is indispensable to identify potential districts which comprise a high percentage of building lots with narrow frontage after subdivision and to reconsider the appropriate criteria for the density of buildings and roads as residential environment indices. In the literature, however, the statistical distribution of building lot frontages and the density of buildings and roads has not been fully researched. In this paper, based on the empirical study in the downtown districts of Tokyo, it is found that (1) a log-normal distribution fits the observed distribution of building lot frontages better than a gamma distribution, which is the model of the size distribution of Poisson Voronoi cells on closed curves; (2) the statistical distribution of building lot frontages statistically follows a log-normal distribution, whose parameters are the gross building density, road density, average road width, the coefficient of variation of building lot frontage, and the ratio of the number of building lot frontages to the number of buildings; and (3) the values of the coefficient of variation of building lot frontages, and that of the ratio of the number of building lot frontages to that of buildings are approximately equal to 0.60 and 1.19, respectively.

Fatigue shifts and scatters heart rate variability in elite endurance athletes.

PubMed

Schmitt, Laurent; Regnard, Jacques; Desmarets, Maxime; Mauny, Fréderic; Mourot, Laurent; Fouillot, Jean-Pierre; Coulmy, Nicolas; Millet, Grégoire

2013-01-01

This longitudinal study aimed at comparing heart rate variability (HRV) in elite athletes identified either in 'fatigue' or in 'no-fatigue' state in 'real life' conditions. 57 elite Nordic-skiers were surveyed over 4 years. R-R intervals were recorded supine (SU) and standing (ST). A fatigue state was quoted with a validated questionnaire. A multilevel linear regression model was used to analyze relationships between heart rate (HR) and HRV descriptors [total spectral power (TP), power in low (LF) and high frequency (HF) ranges expressed in ms(2) and normalized units (nu)] and the status without and with fatigue. The variables not distributed normally were transformed by taking their common logarithm (log10). 172 trials were identified as in a 'fatigue' and 891 as in 'no-fatigue' state. All supine HR and HRV parameters (Beta±SE) were significantly different (P<0.0001) between 'fatigue' and 'no-fatigue': HRSU (+6.27±0.61 bpm), logTPSU (-0.36±0.04), logLFSU (-0.27±0.04), logHFSU (-0.46±0.05), logLF/HFSU (+0.19±0.03), HFSU(nu) (-9.55±1.33). Differences were also significant (P<0.0001) in standing: HRST (+8.83±0.89), logTPST (-0.28±0.03), logLFST (-0.29±0.03), logHFST (-0.32±0.04). Also, intra-individual variance of HRV parameters was larger (P<0.05) in the 'fatigue' state (logTPSU: 0.26 vs. 0.07, logLFSU: 0.28 vs. 0.11, logHFSU: 0.32 vs. 0.08, logTPST: 0.13 vs. 0.07, logLFST: 0.16 vs. 0.07, logHFST: 0.25 vs. 0.14). HRV was significantly lower in 'fatigue' vs. 'no-fatigue' but accompanied with larger intra-individual variance of HRV parameters in 'fatigue'. The broader intra-individual variance of HRV parameters might encompass different changes from no-fatigue state, possibly reflecting different fatigue-induced alterations of HRV pattern.

Log-normal spray drop distribution...analyzed by two new computer programs

Treesearch

Gerald S. Walton

1968-01-01

Results of U.S. Forest Service research on chemical insecticides suggest that large drops are not as effective as small drops in carrying insecticides to target insects. Two new computer programs have been written to analyze size distribution properties of drops from spray nozzles. Coded in Fortran IV, the programs have been tested on both the CDC 6400 and the IBM 7094...

Radium-226 content of beverages

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

Kiefer, J.

Radium contents of commercially obtained beer, wine, milk and mineral waters were measured. All distributions were log-normal with the following geometrical mean values: beer: 2.1 X 10(-2) Bq L-1; wine: 3.4 X 10(-2) Bq L-1; milk: 3 X 10(-3) Bq L-1; normal mineral water: 4.3 X 10(-2) L-1; medical mineral water: 9.4 X 10(-2) Bq L-1.

Investigation into the performance of different models for predicting stutter.

PubMed

Bright, Jo-Anne; Curran, James M; Buckleton, John S

2013-07-01

In this paper we have examined five possible models for the behaviour of the stutter ratio, SR. These were two log-normal models, two gamma models, and a two-component normal mixture model. A two-component normal mixture model was chosen with different behaviours of variance; at each locus SR was described with two distributions, both with the same mean. The distributions have difference variances: one for the majority of the observations and a second for the less well-behaved ones. We apply each model to a set of known single source Identifiler™, NGM SElect™ and PowerPlex(®) 21 DNA profiles to show the applicability of our findings to different data sets. SR determined from the single source profiles were compared to the calculated SR after application of the models. The model performance was tested by calculating the log-likelihoods and comparing the difference in Akaike information criterion (AIC). The two-component normal mixture model systematically outperformed all others, despite the increase in the number of parameters. This model, as well as performing well statistically, has intuitive appeal for forensic biologists and could be implemented in an expert system with a continuous method for DNA interpretation. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

PERFLUORINATED COMPOUNDS IN ARCHIVED HOUSE-DUST SAMPLES

EPA Science Inventory

Archived house-dust samples were analyzed for 13 perfluorinated compounds (PFCs). Results show that PFCs are found in house-dust samples, and the data are log-normally distributed. PFOS/PFOA were present in 94.6% and 96.4% of the samples respectively. Concentrations ranged fro...

Simulation of flight maneuver-load distributions by utilizing stationary, non-Gaussian random load histories

NASA Technical Reports Server (NTRS)

Leybold, H. A.

1971-01-01

Random numbers were generated with the aid of a digital computer and transformed such that the probability density function of a discrete random load history composed of these random numbers had one of the following non-Gaussian distributions: Poisson, binomial, log-normal, Weibull, and exponential. The resulting random load histories were analyzed to determine their peak statistics and were compared with cumulative peak maneuver-load distributions for fighter and transport aircraft in flight.

Statistical Considerations of Data Processing in Giovanni Online Tool

NASA Technical Reports Server (NTRS)

Suhung, Shen; Leptoukh, G.; Acker, J.; Berrick, S.

2005-01-01

The GES DISC Interactive Online Visualization and Analysis Infrastructure (Giovanni) is a web-based interface for the rapid visualization and analysis of gridded data from a number of remote sensing instruments. The GES DISC currently employs several Giovanni instances to analyze various products, such as Ocean-Giovanni for ocean products from SeaWiFS and MODIS-Aqua; TOMS & OM1 Giovanni for atmospheric chemical trace gases from TOMS and OMI, and MOVAS for aerosols from MODIS, etc. (http://giovanni.gsfc.nasa.gov) Foremost among the Giovanni statistical functions is data averaging. Two aspects of this function are addressed here. The first deals with the accuracy of averaging gridded mapped products vs. averaging from the ungridded Level 2 data. Some mapped products contain mean values only; others contain additional statistics, such as number of pixels (NP) for each grid, standard deviation, etc. Since NP varies spatially and temporally, averaging with or without weighting by NP will be different. In this paper, we address differences of various weighting algorithms for some datasets utilized in Giovanni. The second aspect is related to different averaging methods affecting data quality and interpretation for data with non-normal distribution. The present study demonstrates results of different spatial averaging methods using gridded SeaWiFS Level 3 mapped monthly chlorophyll a data. Spatial averages were calculated using three different methods: arithmetic mean (AVG), geometric mean (GEO), and maximum likelihood estimator (MLE). Biogeochemical data, such as chlorophyll a, are usually considered to have a log-normal distribution. The study determined that differences between methods tend to increase with increasing size of a selected coastal area, with no significant differences in most open oceans. The GEO method consistently produces values lower than AVG and MLE. The AVG method produces values larger than MLE in some cases, but smaller in other cases. Further studies indicated that significant differences between AVG and MLE methods occurred in coastal areas where data have large spatial variations and a log-bimodal distribution instead of log-normal distribution.

A novel gamma-fitting statistical method for anti-drug antibody assays to establish assay cut points for data with non-normal distribution.

PubMed

Schlain, Brian; Amaravadi, Lakshmi; Donley, Jean; Wickramasekera, Ananda; Bennett, Donald; Subramanyam, Meena

2010-01-31

In recent years there has been growing recognition of the impact of anti-drug or anti-therapeutic antibodies (ADAs, ATAs) on the pharmacokinetic and pharmacodynamic behavior of the drug, which ultimately affects drug exposure and activity. These anti-drug antibodies can also impact safety of the therapeutic by inducing a range of reactions from hypersensitivity to neutralization of the activity of an endogenous protein. Assessments of immunogenicity, therefore, are critically dependent on the bioanalytical method used to test samples, in which a positive versus negative reactivity is determined by a statistically derived cut point based on the distribution of drug naïve samples. For non-normally distributed data, a novel gamma-fitting method for obtaining assay cut points is presented. Non-normal immunogenicity data distributions, which tend to be unimodal and positively skewed, can often be modeled by 3-parameter gamma fits. Under a gamma regime, gamma based cut points were found to be more accurate (closer to their targeted false positive rates) compared to normal or log-normal methods and more precise (smaller standard errors of cut point estimators) compared with the nonparametric percentile method. Under a gamma regime, normal theory based methods for estimating cut points targeting a 5% false positive rate were found in computer simulation experiments to have, on average, false positive rates ranging from 6.2 to 8.3% (or positive biases between +1.2 and +3.3%) with bias decreasing with the magnitude of the gamma shape parameter. The log-normal fits tended, on average, to underestimate false positive rates with negative biases as large a -2.3% with absolute bias decreasing with the shape parameter. These results were consistent with the well known fact that gamma distributions become less skewed and closer to a normal distribution as their shape parameters increase. Inflated false positive rates, especially in a screening assay, shifts the emphasis to confirm test results in a subsequent test (confirmatory assay). On the other hand, deflated false positive rates in the case of screening immunogenicity assays will not meet the minimum 5% false positive target as proposed in the immunogenicity assay guidance white papers. Copyright 2009 Elsevier B.V. All rights reserved.

A comparison of methods to handle skew distributed cost variables in the analysis of the resource consumption in schizophrenia treatment.

PubMed

Kilian, Reinhold; Matschinger, Herbert; Löeffler, Walter; Roick, Christiane; Angermeyer, Matthias C

2002-03-01

Transformation of the dependent cost variable is often used to solve the problems of heteroscedasticity and skewness in linear ordinary least square regression of health service cost data. However, transformation may cause difficulties in the interpretation of regression coefficients and the retransformation of predicted values. The study compares the advantages and disadvantages of different methods to estimate regression based cost functions using data on the annual costs of schizophrenia treatment. Annual costs of psychiatric service use and clinical and socio-demographic characteristics of the patients were assessed for a sample of 254 patients with a diagnosis of schizophrenia (ICD-10 F 20.0) living in Leipzig. The clinical characteristics of the participants were assessed by means of the BPRS 4.0, the GAF, and the CAN for service needs. Quality of life was measured by WHOQOL-BREF. A linear OLS regression model with non-parametric standard errors, a log-transformed OLS model and a generalized linear model with a log-link and a gamma distribution were used to estimate service costs. For the estimation of robust non-parametric standard errors, the variance estimator by White and a bootstrap estimator based on 2000 replications were employed. Models were evaluated by the comparison of the R2 and the root mean squared error (RMSE). RMSE of the log-transformed OLS model was computed with three different methods of bias-correction. The 95% confidence intervals for the differences between the RMSE were computed by means of bootstrapping. A split-sample-cross-validation procedure was used to forecast the costs for the one half of the sample on the basis of a regression equation computed for the other half of the sample. All three methods showed significant positive influences of psychiatric symptoms and met psychiatric service needs on service costs. Only the log- transformed OLS model showed a significant negative impact of age, and only the GLM shows a significant negative influences of employment status and partnership on costs. All three models provided a R2 of about.31. The Residuals of the linear OLS model revealed significant deviances from normality and homoscedasticity. The residuals of the log-transformed model are normally distributed but still heteroscedastic. The linear OLS model provided the lowest prediction error and the best forecast of the dependent cost variable. The log-transformed model provided the lowest RMSE if the heteroscedastic bias correction was used. The RMSE of the GLM with a log link and a gamma distribution was higher than those of the linear OLS model and the log-transformed OLS model. The difference between the RMSE of the linear OLS model and that of the log-transformed OLS model without bias correction was significant at the 95% level. As result of the cross-validation procedure, the linear OLS model provided the lowest RMSE followed by the log-transformed OLS model with a heteroscedastic bias correction. The GLM showed the weakest model fit again. None of the differences between the RMSE resulting form the cross- validation procedure were found to be significant. The comparison of the fit indices of the different regression models revealed that the linear OLS model provided a better fit than the log-transformed model and the GLM, but the differences between the models RMSE were not significant. Due to the small number of cases in the study the lack of significance does not sufficiently proof that the differences between the RSME for the different models are zero and the superiority of the linear OLS model can not be generalized. The lack of significant differences among the alternative estimators may reflect a lack of sample size adequate to detect important differences among the estimators employed. Further studies with larger case number are necessary to confirm the results. Specification of an adequate regression models requires a careful examination of the characteristics of the data. Estimation of standard errors and confidence intervals by nonparametric methods which are robust against deviations from the normal distribution and the homoscedasticity of residuals are suitable alternatives to the transformation of the skew distributed dependent variable. Further studies with more adequate case numbers are needed to confirm the results.

THE DEPENDENCE OF PRESTELLAR CORE MASS DISTRIBUTIONS ON THE STRUCTURE OF THE PARENTAL CLOUD

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

Parravano, Antonio; Sanchez, Nestor; Alfaro, Emilio J.

2012-08-01

The mass distribution of prestellar cores is obtained for clouds with arbitrary internal mass distributions using a selection criterion based on the thermal and turbulent Jeans mass and applied hierarchically from small to large scales. We have checked this methodology by comparing our results for a log-normal density probability distribution function with the theoretical core mass function (CMF) derived by Hennebelle and Chabrier, namely a power law at large scales and a log-normal cutoff at low scales, but our method can be applied to any mass distributions representing a star-forming cloud. This methodology enables us to connect the parental cloudmore » structure with the mass distribution of the cores and their spatial distribution, providing an efficient tool for investigating the physical properties of the molecular clouds that give rise to the prestellar core distributions observed. Simulated fractional Brownian motion (fBm) clouds with the Hurst exponent close to the value H = 1/3 give the best agreement with the theoretical CMF derived by Hennebelle and Chabrier and Chabrier's system initial mass function. Likewise, the spatial distribution of the cores derived from our methodology shows a surface density of companions compatible with those observed in Trapezium and Ophiucus star-forming regions. This method also allows us to analyze the properties of the mass distribution of cores for different realizations. We found that the variations in the number of cores formed in different realizations of fBm clouds (with the same Hurst exponent) are much larger than the expected root N statistical fluctuations, increasing with H.« less

The Universal Statistical Distributions of the Affinity, Equilibrium Constants, Kinetics and Specificity in Biomolecular Recognition

PubMed Central

Zheng, Xiliang; Wang, Jin

2015-01-01

We uncovered the universal statistical laws for the biomolecular recognition/binding process. We quantified the statistical energy landscapes for binding, from which we can characterize the distributions of the binding free energy (affinity), the equilibrium constants, the kinetics and the specificity by exploring the different ligands binding with a particular receptor. The results of the analytical studies are confirmed by the microscopic flexible docking simulations. The distribution of binding affinity is Gaussian around the mean and becomes exponential near the tail. The equilibrium constants of the binding follow a log-normal distribution around the mean and a power law distribution in the tail. The intrinsic specificity for biomolecular recognition measures the degree of discrimination of native versus non-native binding and the optimization of which becomes the maximization of the ratio of the free energy gap between the native state and the average of non-native states versus the roughness measured by the variance of the free energy landscape around its mean. The intrinsic specificity obeys a Gaussian distribution near the mean and an exponential distribution near the tail. Furthermore, the kinetics of binding follows a log-normal distribution near the mean and a power law distribution at the tail. Our study provides new insights into the statistical nature of thermodynamics, kinetics and function from different ligands binding with a specific receptor or equivalently specific ligand binding with different receptors. The elucidation of distributions of the kinetics and free energy has guiding roles in studying biomolecular recognition and function through small-molecule evolution and chemical genetics. PMID:25885453

The Dependence of Prestellar Core Mass Distributions on the Structure of the Parental Cloud

NASA Astrophysics Data System (ADS)

Parravano, Antonio; Sánchez, Néstor; Alfaro, Emilio J.

2012-08-01

The mass distribution of prestellar cores is obtained for clouds with arbitrary internal mass distributions using a selection criterion based on the thermal and turbulent Jeans mass and applied hierarchically from small to large scales. We have checked this methodology by comparing our results for a log-normal density probability distribution function with the theoretical core mass function (CMF) derived by Hennebelle & Chabrier, namely a power law at large scales and a log-normal cutoff at low scales, but our method can be applied to any mass distributions representing a star-forming cloud. This methodology enables us to connect the parental cloud structure with the mass distribution of the cores and their spatial distribution, providing an efficient tool for investigating the physical properties of the molecular clouds that give rise to the prestellar core distributions observed. Simulated fractional Brownian motion (fBm) clouds with the Hurst exponent close to the value H = 1/3 give the best agreement with the theoretical CMF derived by Hennebelle & Chabrier and Chabrier's system initial mass function. Likewise, the spatial distribution of the cores derived from our methodology shows a surface density of companions compatible with those observed in Trapezium and Ophiucus star-forming regions. This method also allows us to analyze the properties of the mass distribution of cores for different realizations. We found that the variations in the number of cores formed in different realizations of fBm clouds (with the same Hurst exponent) are much larger than the expected root {\\cal N} statistical fluctuations, increasing with H.

ELISPOTs Produced by CD8 and CD4 Cells Follow Log Normal Size Distribution Permitting Objective Counting

PubMed Central

Karulin, Alexey Y.; Karacsony, Kinga; Zhang, Wenji; Targoni, Oleg S.; Moldovan, Ioana; Dittrich, Marcus; Sundararaman, Srividya; Lehmann, Paul V.

2015-01-01

Each positive well in ELISPOT assays contains spots of variable sizes that can range from tens of micrometers up to a millimeter in diameter. Therefore, when it comes to counting these spots the decision on setting the lower and the upper spot size thresholds to discriminate between non-specific background noise, spots produced by individual T cells, and spots formed by T cell clusters is critical. If the spot sizes follow a known statistical distribution, precise predictions on minimal and maximal spot sizes, belonging to a given T cell population, can be made. We studied the size distributional properties of IFN-γ, IL-2, IL-4, IL-5 and IL-17 spots elicited in ELISPOT assays with PBMC from 172 healthy donors, upon stimulation with 32 individual viral peptides representing defined HLA Class I-restricted epitopes for CD8 cells, and with protein antigens of CMV and EBV activating CD4 cells. A total of 334 CD8 and 80 CD4 positive T cell responses were analyzed. In 99.7% of the test cases, spot size distributions followed Log Normal function. These data formally demonstrate that it is possible to establish objective, statistically validated parameters for counting T cell ELISPOTs. PMID:25612115

A cross-site comparison of methods used for hydrogeologic characterization of the Galena-Platteville aquifer in Illinois and Wisconsin, with examples from selected Superfund sites

USGS Publications Warehouse

Kay, Robert T.; Mills, Patrick C.; Dunning, Charles P.; Yeskis, Douglas J.; Ursic, James R.; Vendl, Mark

2004-01-01

The effectiveness of 28 methods used to characterize the fractured Galena-Platteville aquifer at eight sites in northern Illinois and Wisconsin is evaluated. Analysis of government databases, previous investigations, topographic maps, aerial photographs, and outcrops was essential to understanding the hydrogeology in the area to be investigated. The effectiveness of surface-geophysical methods depended on site geology. Lithologic logging provided essential information for site characterization. Cores were used for stratigraphy and geotechnical analysis. Natural-gamma logging helped identify the effect of lithology on the location of secondary- permeability features. Caliper logging identified large secondary-permeability features. Neutron logs identified trends in matrix porosity. Acoustic-televiewer logs identified numerous secondary-permeability features and their orientation. Borehole-camera logs also identified a number of secondary-permeability features. Borehole ground-penetrating radar identified lithologic and secondary-permeability features. However, the accuracy and completeness of this method is uncertain. Single-point-resistance, density, and normal resistivity logs were of limited use. Water-level and water-quality data identified flow directions and indicated the horizontal and vertical distribution of aquifer permeability and the depth of the permeable features. Temperature, spontaneous potential, and fluid-resistivity logging identified few secondary-permeability features at some sites and several features at others. Flowmeter logging was the most effective geophysical method for characterizing secondary-permeability features. Aquifer tests provided insight into the permeability distribution, identified hydraulically interconnected features, the presence of heterogeneity and anisotropy, and determined effective porosity. Aquifer heterogeneity prevented calculation of accurate hydraulic properties from some tests. Different methods, such as flowmeter logging and slug testing, occasionally produced different interpretations. Aquifer characterization improved with an increase in the number of data points, the period of data collection, and the number of methods used.

Universal noise and Efimov physics

NASA Astrophysics Data System (ADS)

Nicholson, Amy N.

2016-03-01

Probability distributions for correlation functions of particles interacting via random-valued fields are discussed as a novel tool for determining the spectrum of a theory. In particular, this method is used to determine the energies of universal N-body clusters tied to Efimov trimers, for even N, by investigating the distribution of a correlation function of two particles at unitarity. Using numerical evidence that this distribution is log-normal, an analytical prediction for the N-dependence of the N-body binding energies is made.

Transmitting Information by Propagation in an Ocean Waveguide: Computation of Acoustic Field Capacity

DTIC Science & Technology

2015-06-17

progress, Eq. (4) is evaluated in terms of the differential entropy h. The integrals can be identified as differential entropy terms by expanding the log...all ran- dom vectors p with a given covariance matrix, the entropy of p is maximized when p is ZMCSCG since a normal distribution maximizes the... entropy over all distributions with the same covariance [9, 18], implying that this is the optimal distribution on s as well. In addition, of all the

Assessment of Methane Emissions from Oil and Gas Production Pads using Mobile Measurements

EPA Science Inventory

Journal Article Abstract --- "A mobile source inspection approach called OTM 33A was used to quantify short-term methane emission rates from 218 oil and gas production pads in Texas, Colorado, and Wyoming from 2010 to 2013. The emission rates were log-normally distributed with ...

Evaluation of waste mushroom logs as a potential biomass resource for the production of bioethanol.

PubMed

Lee, Jae-Won; Koo, Bon-Wook; Choi, Joon-Weon; Choi, Don-Ha; Choi, In-Gyu

2008-05-01

In order to investigate the possibility of using waste mushroom logs as a biomass resource for alternative energy production, the chemical and physical characteristics of normal wood and waste mushroom logs were examined. Size reduction of normal wood (145 kW h/tone) required significantly higher energy consumption than waste mushroom logs (70 kW h/tone). The crystallinity value of waste mushroom logs was dramatically lower (33%) than normal wood (49%) after cultivation by Lentinus edodes as spawn. Lignin, an enzymatic hydrolysis inhibitor in sugar production, decreased from 21.07% to 18.78% after inoculation of L. edodes. Total sugar yields obtained by enzyme and acid hydrolysis were higher in waste mushroom logs than in normal wood. After 24h fermentation, 12 g/L ethanol was produced on waste mushroom logs, while normal wood produced 8 g/L ethanol. These results indicate that waste mushroom logs are economically suitable lignocellulosic material for the production of fermentable sugars related to bioethanol production.

Modelling of PM10 concentration for industrialized area in Malaysia: A case study in Shah Alam

NASA Astrophysics Data System (ADS)

N, Norazian Mohamed; Abdullah, M. M. A.; Tan, Cheng-yau; Ramli, N. A.; Yahaya, A. S.; Fitri, N. F. M. Y.

In Malaysia, the predominant air pollutants are suspended particulate matter (SPM) and nitrogen dioxide (NO2). This research is on PM10 as they may trigger harm to human health as well as environment. Six distributions, namely Weibull, log-normal, gamma, Rayleigh, Gumbel and Frechet were chosen to model the PM10 observations at the chosen industrial area i.e. Shah Alam. One-year period hourly average data for 2006 and 2007 were used for this research. For parameters estimation, method of maximum likelihood estimation (MLE) was selected. Four performance indicators that are mean absolute error (MAE), root mean squared error (RMSE), coefficient of determination (R2) and prediction accuracy (PA), were applied to determine the goodness-of-fit criteria of the distributions. The best distribution that fits with the PM10 observations in Shah Alamwas found to be log-normal distribution. The probabilities of the exceedences concentration were calculated and the return period for the coming year was predicted from the cumulative density function (cdf) obtained from the best-fit distributions. For the 2006 data, Shah Alam was predicted to exceed 150 μg/m3 for 5.9 days in 2007 with a return period of one occurrence per 62 days. For 2007, the studied area does not exceed the MAAQG of 150 μg/m3

The distribution of the intervals between neural impulses in the maintained discharges of retinal ganglion cells.

PubMed

Levine, M W

1991-01-01

Simulated neural impulse trains were generated by a digital realization of the integrate-and-fire model. The variability in these impulse trains had as its origin a random noise of specified distribution. Three different distributions were used: the normal (Gaussian) distribution (no skew, normokurtic), a first-order gamma distribution (positive skew, leptokurtic), and a uniform distribution (no skew, platykurtic). Despite these differences in the distribution of the variability, the distributions of the intervals between impulses were nearly indistinguishable. These inter-impulse distributions were better fit with a hyperbolic gamma distribution than a hyperbolic normal distribution, although one might expect a better approximation for normally distributed inverse intervals. Consideration of why the inter-impulse distribution is independent of the distribution of the causative noise suggests two putative interval distributions that do not depend on the assumed noise distribution: the log normal distribution, which is predicated on the assumption that long intervals occur with the joint probability of small input values, and the random walk equation, which is the diffusion equation applied to a random walk model of the impulse generating process. Either of these equations provides a more satisfactory fit to the simulated impulse trains than the hyperbolic normal or hyperbolic gamma distributions. These equations also provide better fits to impulse trains derived from the maintained discharges of ganglion cells in the retinae of cats or goldfish. It is noted that both equations are free from the constraint that the coefficient of variation (CV) have a maximum of unity.(ABSTRACT TRUNCATED AT 250 WORDS)

On the use of log-transformation vs. nonlinear regression for analyzing biological power laws.

PubMed

Xiao, Xiao; White, Ethan P; Hooten, Mevin B; Durham, Susan L

2011-10-01

Power-law relationships are among the most well-studied functional relationships in biology. Recently the common practice of fitting power laws using linear regression (LR) on log-transformed data has been criticized, calling into question the conclusions of hundreds of studies. It has been suggested that nonlinear regression (NLR) is preferable, but no rigorous comparison of these two methods has been conducted. Using Monte Carlo simulations, we demonstrate that the error distribution determines which method performs better, with NLR better characterizing data with additive, homoscedastic, normal error and LR better characterizing data with multiplicative, heteroscedastic, lognormal error. Analysis of 471 biological power laws shows that both forms of error occur in nature. While previous analyses based on log-transformation appear to be generally valid, future analyses should choose methods based on a combination of biological plausibility and analysis of the error distribution. We provide detailed guidelines and associated computer code for doing so, including a model averaging approach for cases where the error structure is uncertain.

A log-normal distribution model for the molecular weight of aquatic fulvic acids

USGS Publications Warehouse

Cabaniss, S.E.; Zhou, Q.; Maurice, P.A.; Chin, Y.-P.; Aiken, G.R.

2000-01-01

The molecular weight of humic substances influences their proton and metal binding, organic pollutant partitioning, adsorption onto minerals and activated carbon, and behavior during water treatment. We propose a lognormal model for the molecular weight distribution in aquatic fulvic acids to provide a conceptual framework for studying these size effects. The normal curve mean and standard deviation are readily calculated from measured M(n) and M(w) and vary from 2.7 to 3 for the means and from 0.28 to 0.37 for the standard deviations for typical aquatic fulvic acids. The model is consistent with several types of molecular weight data, including the shapes of high- pressure size-exclusion chromatography (HP-SEC) peaks. Applications of the model to electrostatic interactions, pollutant solubilization, and adsorption are explored in illustrative calculations.The molecular weight of humic substances influences their proton and metal binding, organic pollutant partitioning, adsorption onto minerals and activated carbon, and behavior during water treatment. We propose a log-normal model for the molecular weight distribution in aquatic fulvic acids to provide a conceptual framework for studying these size effects. The normal curve mean and standard deviation are readily calculated from measured Mn and Mw and vary from 2.7 to 3 for the means and from 0.28 to 0.37 for the standard deviations for typical aquatic fulvic acids. The model is consistent with several type's of molecular weight data, including the shapes of high-pressure size-exclusion chromatography (HP-SEC) peaks. Applications of the model to electrostatic interactions, pollutant solubilization, and adsorption are explored in illustrative calculations.

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.

Role of Demographic Dynamics and Conflict in the Population-Area Relationship for Human Languages

PubMed Central

Manrubia, Susanna C.; Axelsen, Jacob B.; Zanette, Damián H.

2012-01-01

Many patterns displayed by the distribution of human linguistic groups are similar to the ecological organization described for biological species. It remains a challenge to identify simple and meaningful processes that describe these patterns. The population size distribution of human linguistic groups, for example, is well fitted by a log-normal distribution that may arise from stochastic demographic processes. As we show in this contribution, the distribution of the area size of home ranges of those groups also agrees with a log-normal function. Further, size and area are significantly correlated: the number of speakers and the area spanned by linguistic groups follow the allometric relation , with an exponent varying accross different world regions. The empirical evidence presented leads to the hypothesis that the distributions of and , and their mutual dependence, rely on demographic dynamics and on the result of conflicts over territory due to group growth. To substantiate this point, we introduce a two-variable stochastic multiplicative model whose analytical solution recovers the empirical observations. Applied to different world regions, the model reveals that the retreat in home range is sublinear with respect to the decrease in population size, and that the population-area exponent grows with the typical strength of conflicts. While the shape of the population size and area distributions, and their allometric relation, seem unavoidable outcomes of demography and inter-group contact, the precise value of could give insight on the cultural organization of those human groups in the last thousand years. PMID:22815726

Fatigue Shifts and Scatters Heart Rate Variability in Elite Endurance Athletes

PubMed Central

Schmitt, Laurent; Regnard, Jacques; Desmarets, Maxime; Mauny, Fréderic; Mourot, Laurent; Fouillot, Jean-Pierre; Coulmy, Nicolas; Millet, Grégoire

2013-01-01

Purpose This longitudinal study aimed at comparing heart rate variability (HRV) in elite athletes identified either in ‘fatigue’ or in ‘no-fatigue’ state in ‘real life’ conditions. Methods 57 elite Nordic-skiers were surveyed over 4 years. R-R intervals were recorded supine (SU) and standing (ST). A fatigue state was quoted with a validated questionnaire. A multilevel linear regression model was used to analyze relationships between heart rate (HR) and HRV descriptors [total spectral power (TP), power in low (LF) and high frequency (HF) ranges expressed in ms2 and normalized units (nu)] and the status without and with fatigue. The variables not distributed normally were transformed by taking their common logarithm (log10). Results 172 trials were identified as in a ‘fatigue’ and 891 as in ‘no-fatigue’ state. All supine HR and HRV parameters (Beta±SE) were significantly different (P<0.0001) between ‘fatigue’ and ‘no-fatigue’: HRSU (+6.27±0.61 bpm), logTPSU (−0.36±0.04), logLFSU (−0.27±0.04), logHFSU (−0.46±0.05), logLF/HFSU (+0.19±0.03), HFSU(nu) (−9.55±1.33). Differences were also significant (P<0.0001) in standing: HRST (+8.83±0.89), logTPST (−0.28±0.03), logLFST (−0.29±0.03), logHFST (−0.32±0.04). Also, intra-individual variance of HRV parameters was larger (P<0.05) in the ‘fatigue’ state (logTPSU: 0.26 vs. 0.07, logLFSU: 0.28 vs. 0.11, logHFSU: 0.32 vs. 0.08, logTPST: 0.13 vs. 0.07, logLFST: 0.16 vs. 0.07, logHFST: 0.25 vs. 0.14). Conclusion HRV was significantly lower in 'fatigue' vs. 'no-fatigue' but accompanied with larger intra-individual variance of HRV parameters in 'fatigue'. The broader intra-individual variance of HRV parameters might encompass different changes from no-fatigue state, possibly reflecting different fatigue-induced alterations of HRV pattern. PMID:23951198

A new stochastic algorithm for inversion of dust aerosol size distribution

NASA Astrophysics Data System (ADS)

Wang, Li; Li, Feng; Yang, Ma-ying

2015-08-01

Dust aerosol size distribution is an important source of information about atmospheric aerosols, and it can be determined from multiwavelength extinction measurements. This paper describes a stochastic inverse technique based on artificial bee colony (ABC) algorithm to invert the dust aerosol size distribution by light extinction method. The direct problems for the size distribution of water drop and dust particle, which are the main elements of atmospheric aerosols, are solved by the Mie theory and the Lambert-Beer Law in multispectral region. And then, the parameters of three widely used functions, i.e. the log normal distribution (L-N), the Junge distribution (J-J), and the normal distribution (N-N), which can provide the most useful representation of aerosol size distributions, are inversed by the ABC algorithm in the dependent model. Numerical results show that the ABC algorithm can be successfully applied to recover the aerosol size distribution with high feasibility and reliability even in the presence of random noise.

Prediction of the filtrate particle size distribution from the pore size distribution in membrane filtration: Numerical correlations from computer simulations

NASA Astrophysics Data System (ADS)

Marrufo-Hernández, Norma Alejandra; Hernández-Guerrero, Maribel; Nápoles-Duarte, José Manuel; Palomares-Báez, Juan Pedro; Chávez-Rojo, Marco Antonio

2018-03-01

We present a computational model that describes the diffusion of a hard spheres colloidal fluid through a membrane. The membrane matrix is modeled as a series of flat parallel planes with circular pores of different sizes and random spatial distribution. This model was employed to determine how the size distribution of the colloidal filtrate depends on the size distributions of both, the particles in the feed and the pores of the membrane, as well as to describe the filtration kinetics. A Brownian dynamics simulation study considering normal distributions was developed in order to determine empirical correlations between the parameters that characterize these distributions. The model can also be extended to other distributions such as log-normal. This study could, therefore, facilitate the selection of membranes for industrial or scientific filtration processes once the size distribution of the feed is known and the expected characteristics in the filtrate have been defined.

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.

Computer routines for probability distributions, random numbers, and related functions

USGS Publications Warehouse

Kirby, W.

1983-01-01

Use of previously coded and tested subroutines simplifies and speeds up program development and testing. This report presents routines that can be used to calculate various probability distributions and other functions of importance in statistical hydrology. The routines are designed as general-purpose Fortran subroutines and functions to be called from user-written main progress. The probability distributions provided include the beta, chi-square, gamma, Gaussian (normal), Pearson Type III (tables and approximation), and Weibull. Also provided are the distributions of the Grubbs-Beck outlier test, Kolmogorov 's and Smirnov 's D, Student 's t, noncentral t (approximate), and Snedecor F. Other mathematical functions include the Bessel function, I sub o, gamma and log-gamma functions, error functions, and exponential integral. Auxiliary services include sorting and printer-plotting. Random number generators for uniform and normal numbers are provided and may be used with some of the above routines to generate numbers from other distributions. (USGS)

Computer routines for probability distributions, random numbers, and related functions

USGS Publications Warehouse

Kirby, W.H.

1980-01-01

Use of previously codes and tested subroutines simplifies and speeds up program development and testing. This report presents routines that can be used to calculate various probability distributions and other functions of importance in statistical hydrology. The routines are designed as general-purpose Fortran subroutines and functions to be called from user-written main programs. The probability distributions provided include the beta, chisquare, gamma, Gaussian (normal), Pearson Type III (tables and approximation), and Weibull. Also provided are the distributions of the Grubbs-Beck outlier test, Kolmogorov 's and Smirnov 's D, Student 's t, noncentral t (approximate), and Snedecor F tests. Other mathematical functions include the Bessel function I (subzero), gamma and log-gamma functions, error functions and exponential integral. Auxiliary services include sorting and printer plotting. Random number generators for uniform and normal numbers are provided and may be used with some of the above routines to generate numbers from other distributions. (USGS)

Wealth of the world's richest publicly traded companies per industry and per employee: Gamma, Log-normal and Pareto power-law as universal distributions?

NASA Astrophysics Data System (ADS)

Soriano-Hernández, P.; del Castillo-Mussot, M.; Campirán-Chávez, I.; Montemayor-Aldrete, J. A.

2017-04-01

Forbes Magazine published its list of leading or strongest publicly-traded two thousand companies in the world (G-2000) based on four independent metrics: sales or revenues, profits, assets and market value. Every one of these wealth metrics yields particular information on the corporate size or wealth size of each firm. The G-2000 cumulative probability wealth distribution per employee (per capita) for all four metrics exhibits a two-class structure: quasi-exponential in the lower part, and a Pareto power-law in the higher part. These two-class structure per capita distributions are qualitatively similar to income and wealth distributions in many countries of the world, but the fraction of firms per employee within the high-class Pareto is about 49% in sales per employee, and 33% after averaging on the four metrics, whereas in countries the fraction of rich agents in the Pareto zone is less than 10%. The quasi-exponential zone can be adjusted by Gamma or Log-normal distributions. On the other hand, Forbes classifies the G-2000 firms in 82 different industries or economic activities. Within each industry, the wealth distribution per employee also follows a two-class structure, but when the aggregate wealth of firms in each industry for the four metrics is divided by the total number of employees in that industry, then the 82 points of the aggregate wealth distribution by industry per employee can be well adjusted by quasi-exponential curves for the four metrics.

Power laws in citation distributions: evidence from Scopus.

PubMed

Brzezinski, Michal

Modeling distributions of citations to scientific papers is crucial for understanding how science develops. However, there is a considerable empirical controversy on which statistical model fits the citation distributions best. This paper is concerned with rigorous empirical detection of power-law behaviour in the distribution of citations received by the most highly cited scientific papers. We have used a large, novel data set on citations to scientific papers published between 1998 and 2002 drawn from Scopus. The power-law model is compared with a number of alternative models using a likelihood ratio test. We have found that the power-law hypothesis is rejected for around half of the Scopus fields of science. For these fields of science, the Yule, power-law with exponential cut-off and log-normal distributions seem to fit the data better than the pure power-law model. On the other hand, when the power-law hypothesis is not rejected, it is usually empirically indistinguishable from most of the alternative models. The pure power-law model seems to be the best model only for the most highly cited papers in "Physics and Astronomy". Overall, our results seem to support theories implying that the most highly cited scientific papers follow the Yule, power-law with exponential cut-off or log-normal distribution. Our findings suggest also that power laws in citation distributions, when present, account only for a very small fraction of the published papers (less than 1 % for most of science fields) and that the power-law scaling parameter (exponent) is substantially higher (from around 3.2 to around 4.7) than found in the older literature.

Grain coarsening in two-dimensional phase-field models with an orientation field

NASA Astrophysics Data System (ADS)

Korbuly, Bálint; Pusztai, Tamás; Henry, Hervé; Plapp, Mathis; Apel, Markus; Gránásy, László

2017-05-01

In the literature, contradictory results have been published regarding the form of the limiting (long-time) grain size distribution (LGSD) that characterizes the late stage grain coarsening in two-dimensional and quasi-two-dimensional polycrystalline systems. While experiments and the phase-field crystal (PFC) model (a simple dynamical density functional theory) indicate a log-normal distribution, other works including theoretical studies based on conventional phase-field simulations that rely on coarse grained fields, like the multi-phase-field (MPF) and orientation field (OF) models, yield significantly different distributions. In a recent work, we have shown that the coarse grained phase-field models (whether MPF or OF) yield very similar limiting size distributions that seem to differ from the theoretical predictions. Herein, we revisit this problem, and demonstrate in the case of OF models [R. Kobayashi, J. A. Warren, and W. C. Carter, Physica D 140, 141 (2000), 10.1016/S0167-2789(00)00023-3; H. Henry, J. Mellenthin, and M. Plapp, Phys. Rev. B 86, 054117 (2012), 10.1103/PhysRevB.86.054117] that an insufficient resolution of the small angle grain boundaries leads to a log-normal distribution close to those seen in the experiments and the molecular scale PFC simulations. Our paper indicates, furthermore, that the LGSD is critically sensitive to the details of the evaluation process, and raises the possibility that the differences among the LGSD results from different sources may originate from differences in the detection of small angle grain boundaries.

A Maximum Likelihood Ensemble Data Assimilation Method Tailored to the Inner Radiation Belt

NASA Astrophysics Data System (ADS)

Guild, T. B.; O'Brien, T. P., III; Mazur, J. E.

2014-12-01

The Earth's radiation belts are composed of energetic protons and electrons whose fluxes span many orders of magnitude, whose distributions are log-normal, and where data-model differences can be large and also log-normal. This physical system thus challenges standard data assimilation methods relying on underlying assumptions of Gaussian distributions of measurements and data-model differences, where innovations to the model are small. We have therefore developed a data assimilation method tailored to these properties of the inner radiation belt, analogous to the ensemble Kalman filter but for the unique cases of non-Gaussian model and measurement errors, and non-linear model and measurement distributions. We apply this method to the inner radiation belt proton populations, using the SIZM inner belt model [Selesnick et al., 2007] and SAMPEX/PET and HEO proton observations to select the most likely ensemble members contributing to the state of the inner belt. We will describe the algorithm, the method of generating ensemble members, our choice of minimizing the difference between instrument counts not phase space densities, and demonstrate the method with our reanalysis of the inner radiation belt throughout solar cycle 23. We will report on progress to continue our assimilation into solar cycle 24 using the Van Allen Probes/RPS observations.

LEVELS OF EXTREMELY LOW-FREQUENCY ELECTRIC AND MAGNETIC FIELDS FROM OVERHEAD POWER LINES IN THE OUTDOOR ENVIRONMENT OF RAMALLAH CITY-PALESTINE.

PubMed

Abuasbi, Falastine; Lahham, Adnan; Abdel-Raziq, Issam Rashid

2018-05-01

In this study, levels of extremely low-frequency electric and magnetic fields originated from overhead power lines were investigated in the outdoor environment in Ramallah city, Palestine. Spot measurements were applied to record fields intensities over 6-min period. The Spectrum Analyzer NF-5035 was used to perform measurements at 1 m above ground level and directly underneath 40 randomly selected power lines distributed fairly within the city. Levels of electric fields varied depending on the line's category (power line, transformer or distributor), a minimum mean electric field of 3.9 V/m was found under a distributor line, and a maximum of 769.4 V/m under a high-voltage power line (66 kV). However, results of electric fields showed a log-normal distribution with the geometric mean and the geometric standard deviation of 35.9 and 2.8 V/m, respectively. Magnetic fields measured at power lines, on contrast, were not log-normally distributed; the minimum and maximum mean magnetic fields under power lines were 0.89 and 3.5 μT, respectively. As a result, none of the measured fields exceeded the ICNIRP's guidelines recommended for general public exposures to extremely low-frequency fields.

Predicting durations of online collective actions based on Peaks' heights

NASA Astrophysics Data System (ADS)

Lu, Peng; Nie, Shizhao; Wang, Zheng; Jing, Ziwei; Yang, Jianwu; Qi, Zhongxiang; Pujia, Wangmo

2018-02-01

Capturing the whole process of collective actions, the peak model contains four stages, including Prepare, Outbreak, Peak, and Vanish. Based on the peak model, one of the key variables, factors and parameters are further investigated in this paper, which is the rate between peaks and spans. Although the durations or spans and peaks' heights are highly diversified, it seems that the ratio between them is quite stable. If the rate's regularity is discovered, we can predict how long the collective action lasts and when it ends based on the peak's height. In this work, we combined mathematical simulations and empirical big data of 148 cases to explore the regularity of ratio's distribution. It is indicated by results of simulations that the rate has some regularities of distribution, which is not normal distribution. The big data has been collected from the 148 online collective actions and the whole processes of participation are recorded. The outcomes of empirical big data indicate that the rate seems to be closer to being log-normally distributed. This rule holds true for both the total cases and subgroups of 148 online collective actions. The Q-Q plot is applied to check the normal distribution of the rate's logarithm, and the rate's logarithm does follow the normal distribution.

Measurement of the distribution of ventilation-perfusion ratios in the human lung with proton MRI: comparison with the multiple inert-gas elimination technique.

PubMed

Sá, Rui Carlos; Henderson, A Cortney; Simonson, Tatum; Arai, Tatsuya J; Wagner, Harrieth; Theilmann, Rebecca J; Wagner, Peter D; Prisk, G Kim; Hopkins, Susan R

2017-07-01

We have developed a novel functional proton magnetic resonance imaging (MRI) technique to measure regional ventilation-perfusion (V̇ A /Q̇) ratio in the lung. We conducted a comparison study of this technique in healthy subjects ( n = 7, age = 42 ± 16 yr, Forced expiratory volume in 1 s = 94% predicted), by comparing data measured using MRI to that obtained from the multiple inert gas elimination technique (MIGET). Regional ventilation measured in a sagittal lung slice using Specific Ventilation Imaging was combined with proton density measured using a fast gradient-echo sequence to calculate regional alveolar ventilation, registered with perfusion images acquired using arterial spin labeling, and divided on a voxel-by-voxel basis to obtain regional V̇ A /Q̇ ratio. LogSDV̇ and LogSDQ̇, measures of heterogeneity derived from the standard deviation (log scale) of the ventilation and perfusion vs. V̇ A /Q̇ ratio histograms respectively, were calculated. On a separate day, subjects underwent study with MIGET and LogSDV̇ and LogSDQ̇ were calculated from MIGET data using the 50-compartment model. MIGET LogSDV̇ and LogSDQ̇ were normal in all subjects. LogSDQ̇ was highly correlated between MRI and MIGET (R = 0.89, P = 0.007); the intercept was not significantly different from zero (-0.062, P = 0.65) and the slope did not significantly differ from identity (1.29, P = 0.34). MIGET and MRI measures of LogSDV̇ were well correlated (R = 0.83, P = 0.02); the intercept differed from zero (0.20, P = 0.04) and the slope deviated from the line of identity (0.52, P = 0.01). We conclude that in normal subjects, there is a reasonable agreement between MIGET measures of heterogeneity and those from proton MRI measured in a single slice of lung. NEW & NOTEWORTHY We report a comparison of a new proton MRI technique to measure regional V̇ A /Q̇ ratio against the multiple inert gas elimination technique (MIGET). The study reports good relationships between measures of heterogeneity derived from MIGET and those derived from MRI. Although currently limited to a single slice acquisition, these data suggest that single sagittal slice measures of V̇ A /Q̇ ratio provide an adequate means to assess heterogeneity in the normal lung. Copyright © 2017 the American Physiological Society.

A model for the spatial distribution of snow water equivalent parameterized from the spatial variability of precipitation

NASA Astrophysics Data System (ADS)

Skaugen, Thomas; Weltzien, Ingunn H.

2016-09-01

Snow is an important and complicated element in hydrological modelling. The traditional catchment hydrological model with its many free calibration parameters, also in snow sub-models, is not a well-suited tool for predicting conditions for which it has not been calibrated. Such conditions include prediction in ungauged basins and assessing hydrological effects of climate change. In this study, a new model for the spatial distribution of snow water equivalent (SWE), parameterized solely from observed spatial variability of precipitation, is compared with the current snow distribution model used in the operational flood forecasting models in Norway. The former model uses a dynamic gamma distribution and is called Snow Distribution_Gamma, (SD_G), whereas the latter model has a fixed, calibrated coefficient of variation, which parameterizes a log-normal model for snow distribution and is called Snow Distribution_Log-Normal (SD_LN). The two models are implemented in the parameter parsimonious rainfall-runoff model Distance Distribution Dynamics (DDD), and their capability for predicting runoff, SWE and snow-covered area (SCA) is tested and compared for 71 Norwegian catchments. The calibration period is 1985-2000 and validation period is 2000-2014. Results show that SDG better simulates SCA when compared with MODIS satellite-derived snow cover. In addition, SWE is simulated more realistically in that seasonal snow is melted out and the building up of "snow towers" and giving spurious positive trends in SWE, typical for SD_LN, is prevented. The precision of runoff simulations using SDG is slightly inferior, with a reduction in Nash-Sutcliffe and Kling-Gupta efficiency criterion of 0.01, but it is shown that the high precision in runoff prediction using SD_LN is accompanied with erroneous simulations of SWE.

Pan-European comparison of candidate distributions for climatological drought indices, SPI and SPEI

NASA Astrophysics Data System (ADS)

Stagge, James; Tallaksen, Lena; Gudmundsson, Lukas; Van Loon, Anne; Stahl, Kerstin

2013-04-01

Drought indices are vital to objectively quantify and compare drought severity, duration, and extent across regions with varied climatic and hydrologic regimes. The Standardized Precipitation Index (SPI), a well-reviewed meterological drought index recommended by the WMO, and its more recent water balance variant, the Standardized Precipitation-Evapotranspiration Index (SPEI) both rely on selection of univariate probability distributions to normalize the index, allowing for comparisons across climates. The SPI, considered a universal meteorological drought index, measures anomalies in precipitation, whereas the SPEI measures anomalies in climatic water balance (precipitation minus potential evapotranspiration), a more comprehensive measure of water availability that incorporates temperature. Many reviewers recommend use of the gamma (Pearson Type III) distribution for SPI normalization, while developers of the SPEI recommend use of the three parameter log-logistic distribution, based on point observation validation. Before the SPEI can be implemented at the pan-European scale, it is necessary to further validate the index using a range of candidate distributions to determine sensitivity to distribution selection, identify recommended distributions, and highlight those instances where a given distribution may not be valid. This study rigorously compares a suite of candidate probability distributions using WATCH Forcing Data, a global, historical (1958-2001) climate dataset based on ERA40 reanalysis with 0.5 x 0.5 degree resolution and bias-correction based on CRU-TS2.1 observations. Using maximum likelihood estimation, alternative candidate distributions are fit for the SPI and SPEI across the range of European climate zones. When evaluated at this scale, the gamma distribution for the SPI results in negatively skewed values, exaggerating the index severity of extreme dry conditions, while decreasing the index severity of extreme high precipitation. This bias is particularly notable for shorter aggregation periods (1-6 months) during the summer months in southern Europe (below 45° latitude), and can partially be attributed to distribution fitting difficulties in semi-arid regions where monthly precipitation totals cluster near zero. By contrast, the SPEI has potential for avoiding this fitting difficulty because it is not bounded by zero. However, the recommended log-logistic distribution produces index values with less variation than the standard normal distribution. Among the alternative candidate distributions, the best fit distribution and the distribution parameters vary in space and time, suggesting regional commonalities within hydroclimatic regimes, as discussed further in the presentation.

Proton Straggling in Thick Silicon Detectors

NASA Technical Reports Server (NTRS)

Selesnick, R. S.; Baker, D. N.; Kanekal, S. G.

2017-01-01

Straggling functions for protons in thick silicon radiation detectors are computed by Monte Carlo simulation. Mean energy loss is constrained by the silicon stopping power, providing higher straggling at low energy and probabilities for stopping within the detector volume. By matching the first four moments of simulated energy-loss distributions, straggling functions are approximated by a log-normal distribution that is accurate for Vavilov k is greater than or equal to 0:3. They are verified by comparison to experimental proton data from a charged particle telescope.

On the Use of the Log-Normal Particle Size Distribution to Characterize Global Rain

NASA Technical Reports Server (NTRS)

Meneghini, Robert; Rincon, Rafael; Liao, Liang

2003-01-01

Although most parameterizations of the drop size distributions (DSD) use the gamma function, there are several advantages to the log-normal form, particularly if we want to characterize the large scale space-time variability of the DSD and rain rate. The advantages of the distribution are twofold: the logarithm of any moment can be expressed as a linear combination of the individual parameters of the distribution; the parameters of the distribution are approximately normally distributed. Since all radar and rainfall-related parameters can be written approximately as a moment of the DSD, the first property allows us to express the logarithm of any radar/rainfall variable as a linear combination of the individual DSD parameters. Another consequence is that any power law relationship between rain rate, reflectivity factor, specific attenuation or water content can be expressed in terms of the covariance matrix of the DSD parameters. The joint-normal property of the DSD parameters has applications to the description of the space-time variation of rainfall in the sense that any radar-rainfall quantity can be specified by the covariance matrix associated with the DSD parameters at two arbitrary space-time points. As such, the parameterization provides a means by which we can use the spaceborne radar-derived DSD parameters to specify in part the covariance matrices globally. However, since satellite observations have coarse temporal sampling, the specification of the temporal covariance must be derived from ancillary measurements and models. Work is presently underway to determine whether the use of instantaneous rain rate data from the TRMM Precipitation Radar can provide good estimates of the spatial correlation in rain rate from data collected in 5(sup 0)x 5(sup 0) x 1 month space-time boxes. To characterize the temporal characteristics of the DSD parameters, disdrometer data are being used from the Wallops Flight Facility site where as many as 4 disdrometers have been used to acquire data over a 2 km path. These data should help quantify the temporal form of the covariance matrix at this site.

Integrating models that depend on variable data

NASA Astrophysics Data System (ADS)

Banks, A. T.; Hill, M. C.

2016-12-01

Models of human-Earth systems are often developed with the goal of predicting the behavior of one or more dependent variables from multiple independent variables, processes, and parameters. Often dependent variable values range over many orders of magnitude, which complicates evaluation of the fit of the dependent variable values to observations. Many metrics and optimization methods have been proposed to address dependent variable variability, with little consensus being achieved. In this work, we evaluate two such methods: log transformation (based on the dependent variable being log-normally distributed with a constant variance) and error-based weighting (based on a multi-normal distribution with variances that tend to increase as the dependent variable value increases). Error-based weighting has the advantage of encouraging model users to carefully consider data errors, such as measurement and epistemic errors, while log-transformations can be a black box for typical users. Placing the log-transformation into the statistical perspective of error-based weighting has not formerly been considered, to the best of our knowledge. To make the evaluation as clear and reproducible as possible, we use multiple linear regression (MLR). Simulations are conducted with MatLab. The example represents stream transport of nitrogen with up to eight independent variables. The single dependent variable in our example has values that range over 4 orders of magnitude. Results are applicable to any problem for which individual or multiple data types produce a large range of dependent variable values. For this problem, the log transformation produced good model fit, while some formulations of error-based weighting worked poorly. Results support previous suggestions fthat error-based weighting derived from a constant coefficient of variation overemphasizes low values and degrades model fit to high values. Applying larger weights to the high values is inconsistent with the log-transformation. Greater consistency is obtained by imposing smaller (by up to a factor of 1/35) weights on the smaller dependent-variable values. From an error-based perspective, the small weights are consistent with large standard deviations. This work considers the consequences of these two common ways of addressing variable data.

On the use of log-transformation vs. nonlinear regression for analyzing biological power laws

USGS Publications Warehouse

Xiao, X.; White, E.P.; Hooten, M.B.; Durham, S.L.

2011-01-01

Power-law relationships are among the most well-studied functional relationships in biology. Recently the common practice of fitting power laws using linear regression (LR) on log-transformed data has been criticized, calling into question the conclusions of hundreds of studies. It has been suggested that nonlinear regression (NLR) is preferable, but no rigorous comparison of these two methods has been conducted. Using Monte Carlo simulations, we demonstrate that the error distribution determines which method performs better, with NLR better characterizing data with additive, homoscedastic, normal error and LR better characterizing data with multiplicative, heteroscedastic, lognormal error. Analysis of 471 biological power laws shows that both forms of error occur in nature. While previous analyses based on log-transformation appear to be generally valid, future analyses should choose methods based on a combination of biological plausibility and analysis of the error distribution. We provide detailed guidelines and associated computer code for doing so, including a model averaging approach for cases where the error structure is uncertain. ?? 2011 by the Ecological Society of America.

Bladder cancer mapping in Libya based on standardized morbidity ratio and log-normal model

NASA Astrophysics Data System (ADS)

Alhdiri, Maryam Ahmed; Samat, Nor Azah; Mohamed, Zulkifley

2017-05-01

Disease mapping contains a set of statistical techniques that detail maps of rates based on estimated mortality, morbidity, and prevalence. A traditional approach to measure the relative risk of the disease is called Standardized Morbidity Ratio (SMR). It is the ratio of an observed and expected number of accounts in an area, which has the greatest uncertainty if the disease is rare or if geographical area is small. Therefore, Bayesian models or statistical smoothing based on Log-normal model are introduced which might solve SMR problem. This study estimates the relative risk for bladder cancer incidence in Libya from 2006 to 2007 based on the SMR and log-normal model, which were fitted to data using WinBUGS software. This study starts with a brief review of these models, starting with the SMR method and followed by the log-normal model, which is then applied to bladder cancer incidence in Libya. All results are compared using maps and tables. The study concludes that the log-normal model gives better relative risk estimates compared to the classical method. The log-normal model has can overcome the SMR problem when there is no observed bladder cancer in an area.

RESIDENTIAL EXPOSURE TO EXTREMELY LOW FREQUENCY ELECTRIC AND MAGNETIC FIELDS IN THE CITY OF RAMALLAH-PALESTINE.

PubMed

Abuasbi, Falastine; Lahham, Adnan; Abdel-Raziq, Issam Rashid

2018-04-01

This study was focused on the measurement of residential exposure to power frequency (50-Hz) electric and magnetic fields in the city of Ramallah-Palestine. A group of 32 semi-randomly selected residences distributed amongst the city were under investigations of fields variations. Measurements were performed with the Spectrum Analyzer NF-5035 and were carried out at one meter above ground level in the residence's bedroom or living room under both zero and normal-power conditions. Fields' variations were recorded over 6-min and some times over few hours. Electric fields under normal-power use were relatively low; ~59% of residences experienced mean electric fields <10 V/m. The highest mean electric field of 66.9 V/m was found at residence R27. However, electric field values were log-normally distributed with geometric mean and geometric standard deviation of 9.6 and 3.5 V/m, respectively. Background electric fields measured under zero-power use, were very low; ~80% of residences experienced background electric fields <1 V/m. Under normal-power use, the highest mean magnetic field (0.45 μT) was found at residence R26 where an indoor power substation exists. However, ~81% of residences experienced mean magnetic fields <0.1 μT. Magnetic fields measured inside the 32 residences showed also a log-normal distribution with geometric mean and geometric standard deviation of 0.04 and 3.14 μT, respectively. Under zero-power conditions, ~7% of residences experienced average background magnetic field >0.1 μT. Fields from appliances showed a maximum mean electric field of 67.4 V/m from hair dryer, and maximum mean magnetic field of 13.7 μT from microwave oven. However, no single result surpassed the ICNIRP limits for general public exposures to ELF fields, but still, the interval 0.3-0.4 μT for possible non-thermal health impacts of exposure to ELF magnetic fields, was experienced in 13% of the residences.

ROBUST: an interactive FORTRAN-77 package for exploratory data analysis using parametric, ROBUST and nonparametric location and scale estimates, data transformations, normality tests, and outlier assessment

NASA Astrophysics Data System (ADS)

Rock, N. M. S.

ROBUST calculates 53 statistics, plus significance levels for 6 hypothesis tests, on each of up to 52 variables. These together allow the following properties of the data distribution for each variable to be examined in detail: (1) Location. Three means (arithmetic, geometric, harmonic) are calculated, together with the midrange and 19 high-performance robust L-, M-, and W-estimates of location (combined, adaptive, trimmed estimates, etc.) (2) Scale. The standard deviation is calculated along with the H-spread/2 (≈ semi-interquartile range), the mean and median absolute deviations from both mean and median, and a biweight scale estimator. The 23 location and 6 scale estimators programmed cover all possible degrees of robustness. (3) Normality: Distributions are tested against the null hypothesis that they are normal, using the 3rd (√ h1) and 4th ( b 2) moments, Geary's ratio (mean deviation/standard deviation), Filliben's probability plot correlation coefficient, and a more robust test based on the biweight scale estimator. These statistics collectively are sensitive to most usual departures from normality. (4) Presence of outliers. The maximum and minimum values are assessed individually or jointly using Grubbs' maximum Studentized residuals, Harvey's and Dixon's criteria, and the Studentized range. For a single input variable, outliers can be either winsorized or eliminated and all estimates recalculated iteratively as desired. The following data-transformations also can be applied: linear, log 10, generalized Box Cox power (including log, reciprocal, and square root), exponentiation, and standardization. For more than one variable, all results are tabulated in a single run of ROBUST. Further options are incorporated to assess ratios (of two variables) as well as discrete variables, and be concerned with missing data. Cumulative S-plots (for assessing normality graphically) also can be generated. The mutual consistency or inconsistency of all these measures helps to detect errors in data as well as to assess data-distributions themselves.

Transformation techniques for cross-sectional and longitudinal endocrine data: application to salivary cortisol concentrations.

PubMed

Miller, Robert; Plessow, Franziska

2013-06-01

Endocrine time series often lack normality and homoscedasticity most likely due to the non-linear dynamics of their natural determinants and the immanent characteristics of the biochemical analysis tools, respectively. As a consequence, data transformation (e.g., log-transformation) is frequently applied to enable general linear model-based analyses. However, to date, data transformation techniques substantially vary across studies and the question of which is the optimum power transformation remains to be addressed. The present report aims to provide a common solution for the analysis of endocrine time series by systematically comparing different power transformations with regard to their impact on data normality and homoscedasticity. For this, a variety of power transformations of the Box-Cox family were applied to salivary cortisol data of 309 healthy participants sampled in temporal proximity to a psychosocial stressor (the Trier Social Stress Test). Whereas our analyses show that un- as well as log-transformed data are inferior in terms of meeting normality and homoscedasticity, they also provide optimum transformations for both, cross-sectional cortisol samples reflecting the distributional concentration equilibrium and longitudinal cortisol time series comprising systematically altered hormone distributions that result from simultaneously elicited pulsatile change and continuous elimination processes. Considering these dynamics of endocrine oscillations, data transformation prior to testing GLMs seems mandatory to minimize biased results. Copyright © 2012 Elsevier Ltd. All rights reserved.

Distribution of Total Depressive Symptoms Scores and Each Depressive Symptom Item in a Sample of Japanese Employees.

PubMed

Tomitaka, Shinichiro; Kawasaki, Yohei; Ide, Kazuki; Yamada, Hiroshi; Miyake, Hirotsugu; Furukawa, Toshiaki A; Furukaw, Toshiaki A

2016-01-01

In a previous study, we reported that the distribution of total depressive symptoms scores according to the Center for Epidemiologic Studies Depression Scale (CES-D) in a general population is stable throughout middle adulthood and follows an exponential pattern except for at the lowest end of the symptom score. Furthermore, the individual distributions of 16 negative symptom items of the CES-D exhibit a common mathematical pattern. To confirm the reproducibility of these findings, we investigated the distribution of total depressive symptoms scores and 16 negative symptom items in a sample of Japanese employees. We analyzed 7624 employees aged 20-59 years who had participated in the Northern Japan Occupational Health Promotion Centers Collaboration Study for Mental Health. Depressive symptoms were assessed using the CES-D. The CES-D contains 20 items, each of which is scored in four grades: "rarely," "some," "much," and "most of the time." The descriptive statistics and frequency curves of the distributions were then compared according to age group. The distribution of total depressive symptoms scores appeared to be stable from 30-59 years. The right tail of the distribution for ages 30-59 years exhibited a linear pattern with a log-normal scale. The distributions of the 16 individual negative symptom items of the CES-D exhibited a common mathematical pattern which displayed different distributions with a boundary at "some." The distributions of the 16 negative symptom items from "some" to "most" followed a linear pattern with a log-normal scale. The distributions of the total depressive symptoms scores and individual negative symptom items in a Japanese occupational setting show the same patterns as those observed in a general population. These results show that the specific mathematical patterns of the distributions of total depressive symptoms scores and individual negative symptom items can be reproduced in an occupational population.

Characterization of airborne particles in an open pit mining region.

PubMed

Huertas, José I; Huertas, María E; Solís, Dora A

2012-04-15

We characterized airborne particle samples collected from 15 stations in operation since 2007 in one of the world's largest opencast coal mining regions. Using gravimetric, scanning electron microscopy (SEM-EDS), and X-ray photoelectron spectroscopy (XPS) analysis the samples were characterized in terms of concentration, morphology, particle size distribution (PSD), and elemental composition. All of the total suspended particulate (TSP) samples exhibited a log-normal PSD with a mean of d=5.46 ± 0.32 μm and σ(ln d)=0.61 ± 0.03. Similarly, all particles with an equivalent aerodynamic diameter less than 10 μm (PM(10)) exhibited a log-normal type distribution with a mean of d=3.6 ± 0.38 μm and σ(ln d)=0.55 ± 0.03. XPS analysis indicated that the main elements present in the particles were carbon, oxygen, potassium, and silicon with average mass concentrations of 41.5%, 34.7%, 11.6%, and 5.7% respectively. In SEM micrographs the particles appeared smooth-surfaced and irregular in shape, and tended to agglomerate. The particles were typically clay minerals, including limestone, calcite, quartz, and potassium feldspar. Copyright © 2012 Elsevier B.V. All rights reserved.

Exponential blocking-temperature distribution in ferritin extracted from magnetization measurements

NASA Astrophysics Data System (ADS)

Lee, T. H.; Choi, K.-Y.; Kim, G.-H.; Suh, B. J.; Jang, Z. H.

2014-11-01

We developed a direct method to extract the zero-field zero-temperature anisotropy energy barrier distribution of magnetic particles in the form of a blocking-temperature distribution. The key idea is to modify measurement procedures slightly to make nonequilibrium magnetization calculations (including the time evolution of magnetization) easier. We applied this method to the biomagnetic molecule ferritin and successfully reproduced field-cool magnetization by using the extracted distribution. We find that the resulting distribution is more like an exponential type and that the distribution cannot be correlated simply to the widely known log-normal particle-size distribution. The method also allows us to determine the values of the zero-temperature coercivity and Bloch coefficient, which are in good agreement with those determined from other techniques.

Evaluation and validity of a LORETA normative EEG database.

PubMed

Thatcher, R W; North, D; Biver, C

2005-04-01

To evaluate the reliability and validity of a Z-score normative EEG database for Low Resolution Electromagnetic Tomography (LORETA), EEG digital samples (2 second intervals sampled 128 Hz, 1 to 2 minutes eyes closed) were acquired from 106 normal subjects, and the cross-spectrum was computed and multiplied by the Key Institute's LORETA 2,394 gray matter pixel T Matrix. After a log10 transform or a Box-Cox transform the mean and standard deviation of the *.lor files were computed for each of the 2394 gray matter pixels, from 1 to 30 Hz, for each of the subjects. Tests of Gaussianity were computed in order to best approximate a normal distribution for each frequency and gray matter pixel. The relative sensitivity of a Z-score database was computed by measuring the approximation to a Gaussian distribution. The validity of the LORETA normative database was evaluated by the degree to which confirmed brain pathologies were localized using the LORETA normative database. Log10 and Box-Cox transforms approximated Gaussian distribution in the range of 95.64% to 99.75% accuracy. The percentage of normative Z-score values at 2 standard deviations ranged from 1.21% to 3.54%, and the percentage of Z-scores at 3 standard deviations ranged from 0% to 0.83%. Left temporal lobe epilepsy, right sensory motor hematoma and a right hemisphere stroke exhibited maximum Z-score deviations in the same locations as the pathologies. We conclude: (1) Adequate approximation to a Gaussian distribution can be achieved using LORETA by using a log10 transform or a Box-Cox transform and parametric statistics, (2) a Z-Score normative database is valid with adequate sensitivity when using LORETA, and (3) the Z-score LORETA normative database also consistently localized known pathologies to the expected Brodmann areas as an hypothesis test based on the surface EEG before computing LORETA.

Combining counts and incidence data: an efficient approach for estimating the log-normal species abundance distribution and diversity indices.

PubMed

Bellier, Edwige; Grøtan, Vidar; Engen, Steinar; Schartau, Ann Kristin; Diserud, Ola H; Finstad, Anders G

2012-10-01

Obtaining accurate estimates of diversity indices is difficult because the number of species encountered in a sample increases with sampling intensity. We introduce a novel method that requires that the presence of species in a sample to be assessed while the counts of the number of individuals per species are only required for just a small part of the sample. To account for species included as incidence data in the species abundance distribution, we modify the likelihood function of the classical Poisson log-normal distribution. Using simulated community assemblages, we contrast diversity estimates based on a community sample, a subsample randomly extracted from the community sample, and a mixture sample where incidence data are added to a subsample. We show that the mixture sampling approach provides more accurate estimates than the subsample and at little extra cost. Diversity indices estimated from a freshwater zooplankton community sampled using the mixture approach show the same pattern of results as the simulation study. Our method efficiently increases the accuracy of diversity estimates and comprehension of the left tail of the species abundance distribution. We show how to choose the scale of sample size needed for a compromise between information gained, accuracy of the estimates and cost expended when assessing biological diversity. The sample size estimates are obtained from key community characteristics, such as the expected number of species in the community, the expected number of individuals in a sample and the evenness of the community.

Management of Listeria monocytogenes in fermented sausages using the Food Safety Objective concept underpinned by stochastic modeling and meta-analysis.

PubMed

Mataragas, M; Alessandria, V; Rantsiou, K; Cocolin, L

2015-08-01

In the present work, a demonstration is made on how the risk from the presence of Listeria monocytogenes in fermented sausages can be managed using the concept of Food Safety Objective (FSO) aided by stochastic modeling (Bayesian analysis and Monte Carlo simulation) and meta-analysis. For this purpose, the ICMSF equation was used, which combines the initial level (H0) of the hazard and its subsequent reduction (ΣR) and/or increase (ΣI) along the production chain. Each element of the equation was described by a distribution to investigate the effect not only of the level of the hazard, but also the effect of the accompanying variability. The distribution of each element was determined by Bayesian modeling (H0) and meta-analysis (ΣR and ΣI). The output was a normal distribution N(-5.36, 2.56) (log cfu/g) from which the percentage of the non-conforming products, i.e. the fraction above the FSO of 2 log cfu/g, was estimated at 0.202%. Different control measures were examined such as lowering initial L. monocytogenes level and inclusion of an additional killing step along the process resulting in reduction of the non-conforming products from 0.195% to 0.003% based on the mean and/or square-root change of the normal distribution, and 0.001%, respectively. Copyright © 2015 Elsevier Ltd. All rights reserved.

Parameter estimation and forecasting for multiplicative log-normal cascades.

PubMed

Leövey, Andrés E; Lux, Thomas

2012-04-01

We study the well-known multiplicative log-normal cascade process in which the multiplication of Gaussian and log normally distributed random variables yields time series with intermittent bursts of activity. Due to the nonstationarity of this process and the combinatorial nature of such a formalism, its parameters have been estimated mostly by fitting the numerical approximation of the associated non-Gaussian probability density function to empirical data, cf. Castaing et al. [Physica D 46, 177 (1990)]. More recently, alternative estimators based upon various moments have been proposed by Beck [Physica D 193, 195 (2004)] and Kiyono et al. [Phys. Rev. E 76, 041113 (2007)]. In this paper, we pursue this moment-based approach further and develop a more rigorous generalized method of moments (GMM) estimation procedure to cope with the documented difficulties of previous methodologies. We show that even under uncertainty about the actual number of cascade steps, our methodology yields very reliable results for the estimated intermittency parameter. Employing the Levinson-Durbin algorithm for best linear forecasts, we also show that estimated parameters can be used for forecasting the evolution of the turbulent flow. We compare forecasting results from the GMM and Kiyono et al.'s procedure via Monte Carlo simulations. We finally test the applicability of our approach by estimating the intermittency parameter and forecasting of volatility for a sample of financial data from stock and foreign exchange markets.

Comparative analysis of background EEG activity in childhood absence epilepsy during valproate treatment: a standardized, low-resolution, brain electromagnetic tomography (sLORETA) study.

PubMed

Shin, Jung-Hyun; Eom, Tae-Hoon; Kim, Young-Hoon; Chung, Seung-Yun; Lee, In-Goo; Kim, Jung-Min

2017-07-01

Valproate (VPA) is an antiepileptic drug (AED) used for initial monotherapy in treating childhood absence epilepsy (CAE). EEG might be an alternative approach to explore the effects of AEDs on the central nervous system. We performed a comparative analysis of background EEG activity during VPA treatment by using standardized, low-resolution, brain electromagnetic tomography (sLORETA) to explore the effect of VPA in patients with CAE. In 17 children with CAE, non-parametric statistical analyses using sLORETA were performed to compare the current density distribution of four frequency bands (delta, theta, alpha, and beta) between the untreated and treated condition. Maximum differences in current density were found in the left inferior frontal gyrus for the delta frequency band (log-F-ratio = -1.390, P > 0.05), the left medial frontal gyrus for the theta frequency band (log-F-ratio = -0.940, P > 0.05), the left inferior frontal gyrus for the alpha frequency band (log-F-ratio = -0.590, P > 0.05), and the left anterior cingulate for the beta frequency band (log-F-ratio = -1.318, P > 0.05). However, none of these differences were significant (threshold log-F-ratio = ±1.888, P < 0.01; threshold log-F-ratio = ±1.722, P < 0.05). Because EEG background is accepted as normal in CAE, VPA would not be expected to significantly change abnormal thalamocortical oscillations on a normal EEG background. Therefore, our results agree with currently accepted concepts but are not consistent with findings in some previous studies.

Bayesian methods for uncertainty factor application for derivation of reference values.

PubMed

Simon, Ted W; Zhu, Yiliang; Dourson, Michael L; Beck, Nancy B

2016-10-01

In 2014, the National Research Council (NRC) published Review of EPA's Integrated Risk Information System (IRIS) Process that considers methods EPA uses for developing toxicity criteria for non-carcinogens. These criteria are the Reference Dose (RfD) for oral exposure and Reference Concentration (RfC) for inhalation exposure. The NRC Review suggested using Bayesian methods for application of uncertainty factors (UFs) to adjust the point of departure dose or concentration to a level considered to be without adverse effects for the human population. The NRC foresaw Bayesian methods would be potentially useful for combining toxicity data from disparate sources-high throughput assays, animal testing, and observational epidemiology. UFs represent five distinct areas for which both adjustment and consideration of uncertainty may be needed. NRC suggested UFs could be represented as Bayesian prior distributions, illustrated the use of a log-normal distribution to represent the composite UF, and combined this distribution with a log-normal distribution representing uncertainty in the point of departure (POD) to reflect the overall uncertainty. Here, we explore these suggestions and present a refinement of the methodology suggested by NRC that considers each individual UF as a distribution. From an examination of 24 evaluations from EPA's IRIS program, when individual UFs were represented using this approach, the geometric mean fold change in the value of the RfD or RfC increased from 3 to over 30, depending on the number of individual UFs used and the sophistication of the assessment. We present example calculations and recommendations for implementing the refined NRC methodology. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Thorium normalization as a hydrocarbon accumulation indicator for Lower Miocene rocks in Ras Ghara area, Gulf of Suez, Egypt

NASA Astrophysics Data System (ADS)

El-Khadragy, A. A.; Shazly, T. F.; AlAlfy, I. M.; Ramadan, M.; El-Sawy, M. Z.

2018-06-01

An exploration method has been developed using surface and aerial gamma-ray spectral measurements in prospecting petroleum in stratigraphic and structural traps. The Gulf of Suez is an important region for studying hydrocarbon potentiality in Egypt. Thorium normalization technique was applied on the sandstone reservoirs in the region to determine the hydrocarbon potentialities zones using the three spectrometric radioactive gamma ray-logs (eU, eTh and K% logs). This method was applied on the recorded gamma-ray spectrometric logs for Rudeis and Kareem Formations in Ras Ghara oil Field, Gulf of Suez, Egypt. The conventional well logs (gamma-ray, resistivity, neutron, density and sonic logs) were analyzed to determine the net pay zones in the study area. The agreement ratios between the thorium normalization technique and the results of the well log analyses are high, so the application of thorium normalization technique can be used as a guide for hydrocarbon accumulation in the study reservoir rocks.

Polynomial probability distribution estimation using the method of moments

PubMed Central

Mattsson, Lars; Rydén, Jesper

2017-01-01

We suggest a procedure for estimating Nth degree polynomial approximations to unknown (or known) probability density functions (PDFs) based on N statistical moments from each distribution. The procedure is based on the method of moments and is setup algorithmically to aid applicability and to ensure rigor in use. In order to show applicability, polynomial PDF approximations are obtained for the distribution families Normal, Log-Normal, Weibull as well as for a bimodal Weibull distribution and a data set of anonymized household electricity use. The results are compared with results for traditional PDF series expansion methods of Gram–Charlier type. It is concluded that this procedure is a comparatively simple procedure that could be used when traditional distribution families are not applicable or when polynomial expansions of probability distributions might be considered useful approximations. In particular this approach is practical for calculating convolutions of distributions, since such operations become integrals of polynomial expressions. Finally, in order to show an advanced applicability of the method, it is shown to be useful for approximating solutions to the Smoluchowski equation. PMID:28394949

Polynomial probability distribution estimation using the method of moments.

PubMed

Munkhammar, Joakim; Mattsson, Lars; Rydén, Jesper

2017-01-01

We suggest a procedure for estimating Nth degree polynomial approximations to unknown (or known) probability density functions (PDFs) based on N statistical moments from each distribution. The procedure is based on the method of moments and is setup algorithmically to aid applicability and to ensure rigor in use. In order to show applicability, polynomial PDF approximations are obtained for the distribution families Normal, Log-Normal, Weibull as well as for a bimodal Weibull distribution and a data set of anonymized household electricity use. The results are compared with results for traditional PDF series expansion methods of Gram-Charlier type. It is concluded that this procedure is a comparatively simple procedure that could be used when traditional distribution families are not applicable or when polynomial expansions of probability distributions might be considered useful approximations. In particular this approach is practical for calculating convolutions of distributions, since such operations become integrals of polynomial expressions. Finally, in order to show an advanced applicability of the method, it is shown to be useful for approximating solutions to the Smoluchowski equation.

Wavefront-Guided Scleral Lens Correction in Keratoconus

PubMed Central

Marsack, Jason D.; Ravikumar, Ayeswarya; Nguyen, Chi; Ticak, Anita; Koenig, Darren E.; Elswick, James D.; Applegate, Raymond A.

2014-01-01

Purpose To examine the performance of state-of-the-art wavefront-guided scleral contact lenses (wfgSCLs) on a sample of keratoconic eyes, with emphasis on performance quantified with visual quality metrics; and to provide a detailed discussion of the process used to design, manufacture and evaluate wfgSCLs. Methods Fourteen eyes of 7 subjects with keratoconus were enrolled and a wfgSCL was designed for each eye. High-contrast visual acuity and visual quality metrics were used to assess the on-eye performance of the lenses. Results The wfgSCL provided statistically lower levels of both lower-order RMS (p < 0.001) and higher-order RMS (p < 0.02) than an intermediate spherical equivalent scleral contact lens. The wfgSCL provided lower levels of lower-order RMS than a normal group of well-corrected observers (p < < 0.001). However, the wfgSCL does not provide less higher-order RMS than the normal group (p = 0.41). Of the 14 eyes studied, 10 successfully reached the exit criteria, achieving residual higher-order root mean square wavefront error (HORMS) less than or within 1 SD of the levels experienced by normal, age-matched subjects. In addition, measures of visual image quality (logVSX, logNS and logLIB) for the 10 eyes were well distributed within the range of values seen in normal eyes. However, visual performance as measured by high contrast acuity did not reach normal, age-matched levels, which is in agreement with prior results associated with the acute application of wavefront correction to KC eyes. Conclusions Wavefront-guided scleral contact lenses are capable of optically compensating for the deleterious effects of higher-order aberration concomitant with the disease, and can provide visual image quality equivalent to that seen in normal eyes. Longer duration studies are needed to assess whether the visual system of the highly aberrated eye wearing a wfgSCL is capable of producing visual performance levels typical of the normal population. PMID:24830371

Bayesian analysis of stochastic volatility-in-mean model with leverage and asymmetrically heavy-tailed error using generalized hyperbolic skew Student’s t-distribution*

PubMed Central

Leão, William L.; Chen, Ming-Hui

2017-01-01

A stochastic volatility-in-mean model with correlated errors using the generalized hyperbolic skew Student-t (GHST) distribution provides a robust alternative to the parameter estimation for daily stock returns in the absence of normality. An efficient Markov chain Monte Carlo (MCMC) sampling algorithm is developed for parameter estimation. The deviance information, the Bayesian predictive information and the log-predictive score criterion are used to assess the fit of the proposed model. The proposed method is applied to an analysis of the daily stock return data from the Standard & Poor’s 500 index (S&P 500). The empirical results reveal that the stochastic volatility-in-mean model with correlated errors and GH-ST distribution leads to a significant improvement in the goodness-of-fit for the S&P 500 index returns dataset over the usual normal model. PMID:29333210

Bayesian analysis of stochastic volatility-in-mean model with leverage and asymmetrically heavy-tailed error using generalized hyperbolic skew Student's t-distribution.

PubMed

Leão, William L; Abanto-Valle, Carlos A; Chen, Ming-Hui

2017-01-01

A stochastic volatility-in-mean model with correlated errors using the generalized hyperbolic skew Student-t (GHST) distribution provides a robust alternative to the parameter estimation for daily stock returns in the absence of normality. An efficient Markov chain Monte Carlo (MCMC) sampling algorithm is developed for parameter estimation. The deviance information, the Bayesian predictive information and the log-predictive score criterion are used to assess the fit of the proposed model. The proposed method is applied to an analysis of the daily stock return data from the Standard & Poor's 500 index (S&P 500). The empirical results reveal that the stochastic volatility-in-mean model with correlated errors and GH-ST distribution leads to a significant improvement in the goodness-of-fit for the S&P 500 index returns dataset over the usual normal model.

Evaluation of bacterial run and tumble motility parameters through trajectory analysis

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Correlation between size distribution and luminescence properties of spool-shaped InAs quantum dots

NASA Astrophysics Data System (ADS)

Xie, H.; Prioli, R.; Torelly, G.; Liu, H.; Fischer, A. M.; Jakomin, R.; Mourão, R.; Kawabata, R.; Pires, M. P.; Souza, P. L.; Ponce, F. A.

2017-05-01

InAs QDs embedded in an AlGaAs matrix have been produced by MOVPE with a partial capping and annealing technique to achieve controllable QD energy levels that could be useful for solar cell applications. The resulted spool-shaped QDs are around 5 nm in height and have a log-normal diameter distribution, which is observed by TEM to range from 5 to 15 nm. Two photoluminescence peaks associated with QD emission are attributed to the ground and the first excited states transitions. The luminescence peak width is correlated with the distribution of QD diameters through the diameter dependent QD energy levels.

Bubble-chip analysis of human origin distributions demonstrates on a genomic scale significant clustering into zones and significant association with transcription

PubMed Central

Mesner, Larry D.; Valsakumar, Veena; Karnani, Neerja; Dutta, Anindya; Hamlin, Joyce L.; Bekiranov, Stefan

2011-01-01

We have used a novel bubble-trapping procedure to construct nearly pure and comprehensive human origin libraries from early S- and log-phase HeLa cells, and from log-phase GM06990, a karyotypically normal lymphoblastoid cell line. When hybridized to ENCODE tiling arrays, these libraries illuminated 15.3%, 16.4%, and 21.8% of the genome in the ENCODE regions, respectively. Approximately half of the origin fragments cluster into zones, and their signals are generally higher than those of isolated fragments. Interestingly, initiation events are distributed about equally between genic and intergenic template sequences. While only 13.2% and 14.0% of genes within the ENCODE regions are actually transcribed in HeLa and GM06990 cells, 54.5% and 25.6% of zonal origin fragments overlap transcribed genes, most with activating chromatin marks in their promoters. Our data suggest that cell synchronization activates a significant number of inchoate origins. In addition, HeLa and GM06990 cells activate remarkably different origin populations. Finally, there is only moderate concordance between the log-phase HeLa bubble map and published maps of small nascent strands for this cell line. PMID:21173031

Log-gamma linear-mixed effects models for multiple outcomes with application to a longitudinal glaucoma study

PubMed Central

Zhang, Peng; Luo, Dandan; Li, Pengfei; Sharpsten, Lucie; Medeiros, Felipe A.

2015-01-01

Glaucoma is a progressive disease due to damage in the optic nerve with associated functional losses. Although the relationship between structural and functional progression in glaucoma is well established, there is disagreement on how this association evolves over time. In addressing this issue, we propose a new class of non-Gaussian linear-mixed models to estimate the correlations among subject-specific effects in multivariate longitudinal studies with a skewed distribution of random effects, to be used in a study of glaucoma. This class provides an efficient estimation of subject-specific effects by modeling the skewed random effects through the log-gamma distribution. It also provides more reliable estimates of the correlations between the random effects. To validate the log-gamma assumption against the usual normality assumption of the random effects, we propose a lack-of-fit test using the profile likelihood function of the shape parameter. We apply this method to data from a prospective observation study, the Diagnostic Innovations in Glaucoma Study, to present a statistically significant association between structural and functional change rates that leads to a better understanding of the progression of glaucoma over time. PMID:26075565

Superstatistical generalised Langevin equation: non-Gaussian viscoelastic anomalous diffusion

NASA Astrophysics Data System (ADS)

Ślęzak, Jakub; Metzler, Ralf; Magdziarz, Marcin

2018-02-01

Recent advances in single particle tracking and supercomputing techniques demonstrate the emergence of normal or anomalous, viscoelastic diffusion in conjunction with non-Gaussian distributions in soft, biological, and active matter systems. We here formulate a stochastic model based on a generalised Langevin equation in which non-Gaussian shapes of the probability density function and normal or anomalous diffusion have a common origin, namely a random parametrisation of the stochastic force. We perform a detailed analysis demonstrating how various types of parameter distributions for the memory kernel result in exponential, power law, or power-log law tails of the memory functions. The studied system is also shown to exhibit a further unusual property: the velocity has a Gaussian one point probability density but non-Gaussian joint distributions. This behaviour is reflected in the relaxation from a Gaussian to a non-Gaussian distribution observed for the position variable. We show that our theoretical results are in excellent agreement with stochastic simulations.

Power law versus exponential state transition dynamics: application to sleep-wake architecture.

PubMed

Chu-Shore, Jesse; Westover, M Brandon; Bianchi, Matt T

2010-12-02

Despite the common experience that interrupted sleep has a negative impact on waking function, the features of human sleep-wake architecture that best distinguish sleep continuity versus fragmentation remain elusive. In this regard, there is growing interest in characterizing sleep architecture using models of the temporal dynamics of sleep-wake stage transitions. In humans and other mammals, the state transitions defining sleep and wake bout durations have been described with exponential and power law models, respectively. However, sleep-wake stage distributions are often complex, and distinguishing between exponential and power law processes is not always straightforward. Although mono-exponential distributions are distinct from power law distributions, multi-exponential distributions may in fact resemble power laws by appearing linear on a log-log plot. To characterize the parameters that may allow these distributions to mimic one another, we systematically fitted multi-exponential-generated distributions with a power law model, and power law-generated distributions with multi-exponential models. We used the Kolmogorov-Smirnov method to investigate goodness of fit for the "incorrect" model over a range of parameters. The "zone of mimicry" of parameters that increased the risk of mistakenly accepting power law fitting resembled empiric time constants obtained in human sleep and wake bout distributions. Recognizing this uncertainty in model distinction impacts interpretation of transition dynamics (self-organizing versus probabilistic), and the generation of predictive models for clinical classification of normal and pathological sleep architecture.

A Statistical Method for Estimating Missing GHG Emissions in Bottom-Up Inventories: The Case of Fossil Fuel Combustion in Industry in the Bogota Region, Colombia

NASA Astrophysics Data System (ADS)

Jimenez-Pizarro, R.; Rojas, A. M.; Pulido-Guio, A. D.

2012-12-01

The development of environmentally, socially and financially suitable greenhouse gas (GHG) mitigation portfolios requires detailed disaggregation of emissions by activity sector, preferably at the regional level. Bottom-up (BU) emission inventories are intrinsically disaggregated, but although detailed, they are frequently incomplete. Missing and erroneous activity data are rather common in emission inventories of GHG, criteria and toxic pollutants, even in developed countries. The fraction of missing and erroneous data can be rather large in developing country inventories. In addition, the cost and time for obtaining or correcting this information can be prohibitive or can delay the inventory development. This is particularly true for regional BU inventories in the developing world. Moreover, a rather common practice is to disregard or to arbitrarily impute low default activity or emission values to missing data, which typically leads to significant underestimation of the total emissions. Our investigation focuses on GHG emissions by fossil fuel combustion in industry in the Bogota Region, composed by Bogota and its adjacent, semi-rural area of influence, the Province of Cundinamarca. We found that the BU inventories for this sub-category substantially underestimate emissions when compared to top-down (TD) estimations based on sub-sector specific national fuel consumption data and regional energy intensities. Although both BU inventories have a substantial number of missing and evidently erroneous entries, i.e. information on fuel consumption per combustion unit per company, the validated energy use and emission data display clear and smooth frequency distributions, which can be adequately fitted to bimodal log-normal distributions. This is not unexpected as industrial plant sizes are typically log-normally distributed. Moreover, our statistical tests suggest that industrial sub-sectors, as classified by the International Standard Industrial Classification (ISIC), are also well represented by log-normal distributions. Using the validated data, we tested several missing data estimation procedures, including Montecarlo sampling of the real and fitted distributions, and a per ISIC estimation based on bootstrap-calculated mean values. These results will be presented and discussed in detail. Our results suggest that the accuracy of sub-sector BU emission inventories, particularly in developing regions, could be significantly improved if they are designed and carried out to be representative sub-samples (surveys) of the actual universe of emitters. A large fraction the missing data could be subsequently estimated by robust statistical procedures provided that most of the emitters were accounted by number and ISIC.

Simple display system of mechanical properties of cells and their dispersion.

PubMed

Shimizu, Yuji; Kihara, Takanori; Haghparast, Seyed Mohammad Ali; Yuba, Shunsuke; Miyake, Jun

2012-01-01

The mechanical properties of cells are unique indicators of their states and functions. Though, it is difficult to recognize the degrees of mechanical properties, due to small size of the cell and broad distribution of the mechanical properties. Here, we developed a simple virtual reality system for presenting the mechanical properties of cells and their dispersion using a haptic device and a PC. This system simulates atomic force microscopy (AFM) nanoindentation experiments for floating cells in virtual environments. An operator can virtually position the AFM spherical probe over a round cell with the haptic handle on the PC monitor and feel the force interaction. The Young's modulus of mesenchymal stem cells and HEK293 cells in the floating state was measured by AFM. The distribution of the Young's modulus of these cells was broad, and the distribution complied with a log-normal pattern. To represent the mechanical properties together with the cell variance, we used log-normal distribution-dependent random number determined by the mode and variance values of the Young's modulus of these cells. The represented Young's modulus was determined for each touching event of the probe surface and the cell object, and the haptic device-generating force was calculated using a Hertz model corresponding to the indentation depth and the fixed Young's modulus value. Using this system, we can feel the mechanical properties and their dispersion in each cell type in real time. This system will help us not only recognize the degrees of mechanical properties of diverse cells but also share them with others.

Simple Display System of Mechanical Properties of Cells and Their Dispersion

PubMed Central

Shimizu, Yuji; Kihara, Takanori; Haghparast, Seyed Mohammad Ali; Yuba, Shunsuke; Miyake, Jun

2012-01-01

The mechanical properties of cells are unique indicators of their states and functions. Though, it is difficult to recognize the degrees of mechanical properties, due to small size of the cell and broad distribution of the mechanical properties. Here, we developed a simple virtual reality system for presenting the mechanical properties of cells and their dispersion using a haptic device and a PC. This system simulates atomic force microscopy (AFM) nanoindentation experiments for floating cells in virtual environments. An operator can virtually position the AFM spherical probe over a round cell with the haptic handle on the PC monitor and feel the force interaction. The Young's modulus of mesenchymal stem cells and HEK293 cells in the floating state was measured by AFM. The distribution of the Young's modulus of these cells was broad, and the distribution complied with a log-normal pattern. To represent the mechanical properties together with the cell variance, we used log-normal distribution-dependent random number determined by the mode and variance values of the Young's modulus of these cells. The represented Young's modulus was determined for each touching event of the probe surface and the cell object, and the haptic device-generating force was calculated using a Hertz model corresponding to the indentation depth and the fixed Young's modulus value. Using this system, we can feel the mechanical properties and their dispersion in each cell type in real time. This system will help us not only recognize the degrees of mechanical properties of diverse cells but also share them with others. PMID:22479595

Potential source identification for aerosol concentrations over a site in Northwestern India

NASA Astrophysics Data System (ADS)

Payra, Swagata; Kumar, Pramod; Verma, Sunita; Prakash, Divya; Soni, Manish

2016-03-01

The collocated measurements of aerosols size distribution (ASD) and aerosol optical thickness (AOT) are analyzed simultaneously using Grimm aerosol spectrometer and MICROTOP II Sunphotometer over Jaipur, capital of Rajasthan in India. The contrast temperature characteristics during winter and summer seasons of year 2011 are investigated in the present study. The total aerosol number concentration (TANC, 0.3-20 μm) during winter season was observed higher than in summer time and it was dominated by fine aerosol number concentration (FANC < 2 μm). Particles smaller than 0.8 μm (at aerodynamic size) constitute ~ 99% of all particles in winter and ~ 90% of particles in summer season. However, particles greater than 2 μm contribute ~ 3% and ~ 0.2% in summer and winter seasons respectively. The aerosols optical thickness shows nearly similar AOT values during summer and winter but corresponding low Angstrom Exponent (AE) values during summer than winter, respectively. In this work, Potential Source Contribution Function (PSCF) analysis is applied to identify locations of sources that influenced concentrations of aerosols over study area in two different seasons. PSCF analysis shows that the dust particles from Thar Desert contribute significantly to the coarse aerosol number concentration (CANC). Higher values of the PSCF in north from Jaipur showed the industrial areas in northern India to be the likely sources of fine particles. The variation in size distribution of aerosols during two seasons is clearly reflected in the log normal size distribution curves. The log normal size distribution curves reveals that the particle size less than 0.8 μm is the key contributor in winter for higher ANC.

Parameter estimation and forecasting for multiplicative log-normal cascades

NASA Astrophysics Data System (ADS)

Leövey, Andrés E.; Lux, Thomas

2012-04-01

We study the well-known multiplicative log-normal cascade process in which the multiplication of Gaussian and log normally distributed random variables yields time series with intermittent bursts of activity. Due to the nonstationarity of this process and the combinatorial nature of such a formalism, its parameters have been estimated mostly by fitting the numerical approximation of the associated non-Gaussian probability density function to empirical data, cf. Castaing [Physica DPDNPDT0167-278910.1016/0167-2789(90)90035-N 46, 177 (1990)]. More recently, alternative estimators based upon various moments have been proposed by Beck [Physica DPDNPDT0167-278910.1016/j.physd.2004.01.020 193, 195 (2004)] and Kiyono [Phys. Rev. EPLEEE81539-375510.1103/PhysRevE.76.041113 76, 041113 (2007)]. In this paper, we pursue this moment-based approach further and develop a more rigorous generalized method of moments (GMM) estimation procedure to cope with the documented difficulties of previous methodologies. We show that even under uncertainty about the actual number of cascade steps, our methodology yields very reliable results for the estimated intermittency parameter. Employing the Levinson-Durbin algorithm for best linear forecasts, we also show that estimated parameters can be used for forecasting the evolution of the turbulent flow. We compare forecasting results from the GMM and Kiyono 's procedure via Monte Carlo simulations. We finally test the applicability of our approach by estimating the intermittency parameter and forecasting of volatility for a sample of financial data from stock and foreign exchange markets.

Posterior propriety for hierarchical models with log-likelihoods that have norm bounds

DOE PAGES

Michalak, Sarah E.; Morris, Carl N.

2015-07-17

Statisticians often use improper priors to express ignorance or to provide good frequency properties, requiring that posterior propriety be verified. Our paper addresses generalized linear mixed models, GLMMs, when Level I parameters have Normal distributions, with many commonly-used hyperpriors. It provides easy-to-verify sufficient posterior propriety conditions based on dimensions, matrix ranks, and exponentiated norm bounds, ENBs, for the Level I likelihood. Since many familiar likelihoods have ENBs, which is often verifiable via log-concavity and MLE finiteness, our novel use of ENBs permits unification of posterior propriety results and posterior MGF/moment results for many useful Level I distributions, including those commonlymore » used with multilevel generalized linear models, e.g., GLMMs and hierarchical generalized linear models, HGLMs. Furthermore, those who need to verify existence of posterior distributions or of posterior MGFs/moments for a multilevel generalized linear model given a proper or improper multivariate F prior as in Section 1 should find the required results in Sections 1 and 2 and Theorem 3 (GLMMs), Theorem 4 (HGLMs), or Theorem 5 (posterior MGFs/moments).« less

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.

Rescaled earthquake recurrence time statistics: application to microrepeaters

NASA Astrophysics Data System (ADS)

Goltz, Christian; Turcotte, Donald L.; Abaimov, Sergey G.; Nadeau, Robert M.; Uchida, Naoki; Matsuzawa, Toru

2009-01-01

Slip on major faults primarily occurs during `characteristic' earthquakes. The recurrence statistics of characteristic earthquakes play an important role in seismic hazard assessment. A major problem in determining applicable statistics is the short sequences of characteristic earthquakes that are available worldwide. In this paper, we introduce a rescaling technique in which sequences can be superimposed to establish larger numbers of data points. We consider the Weibull and log-normal distributions, in both cases we rescale the data using means and standard deviations. We test our approach utilizing sequences of microrepeaters, micro-earthquakes which recur in the same location on a fault. It seems plausible to regard these earthquakes as a miniature version of the classic characteristic earthquakes. Microrepeaters are much more frequent than major earthquakes, leading to longer sequences for analysis. In this paper, we present results for the analysis of recurrence times for several microrepeater sequences from Parkfield, CA as well as NE Japan. We find that, once the respective sequence can be considered to be of sufficient stationarity, the statistics can be well fitted by either a Weibull or a log-normal distribution. We clearly demonstrate this fact by our technique of rescaled combination. We conclude that the recurrence statistics of the microrepeater sequences we consider are similar to the recurrence statistics of characteristic earthquakes on major faults.

3D modeling of effects of increased oxygenation and activity concentration in tumors treated with radionuclides and antiangiogenic drugs

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

Lagerloef, Jakob H.; Kindblom, Jon; Bernhardt, Peter

Purpose: Formation of new blood vessels (angiogenesis) in response to hypoxia is a fundamental event in the process of tumor growth and metastatic dissemination. However, abnormalities in tumor neovasculature often induce increased interstitial pressure (IP) and further reduce oxygenation (pO{sub 2}) of tumor cells. In radiotherapy, well-oxygenated tumors favor treatment. Antiangiogenic drugs may lower IP in the tumor, improving perfusion, pO{sub 2} and drug uptake, by reducing the number of malfunctioning vessels in the tissue. This study aims to create a model for quantifying the effects of altered pO{sub 2}-distribution due to antiangiogenic treatment in combination with radionuclide therapy. Methods:more » Based on experimental data, describing the effects of antiangiogenic agents on oxygenation of GlioblastomaMultiforme (GBM), a single cell based 3D model, including 10{sup 10} tumor cells, was developed, showing how radionuclide therapy response improves as tumor oxygenation approaches normal tissue levels. The nuclides studied were {sup 90}Y, {sup 131}I, {sup 177}Lu, and {sup 211}At. The absorbed dose levels required for a tumor control probability (TCP) of 0.990 are compared for three different log-normal pO{sub 2}-distributions: {mu}{sub 1} = 2.483, {sigma}{sub 1} = 0.711; {mu}{sub 2} = 2.946, {sigma}{sub 2} = 0.689; {mu}{sub 3} = 3.689, and {sigma}{sub 3} = 0.330. The normal tissue absorbed doses will, in turn, depend on this. These distributions were chosen to represent the expected oxygen levels in an untreated hypoxic tumor, a hypoxic tumor treated with an anti-VEGF agent, and in normal, fully-oxygenated tissue, respectively. The former two are fitted to experimental data. The geometric oxygen distributions are simulated using two different patterns: one Monte Carlo based and one radially increasing, while keeping the log-normal volumetric distributions intact. Oxygen and activity are distributed, according to the same pattern. Results: As tumor pO{sub 2} approaches normal tissue levels, the therapeutic effect is improved so that the normal tissue absorbed doses can be decreased by more than 95%, while retaining TCP, in the most favorable scenario and by up to about 80% with oxygen levels previously achieved in vivo, when the least favourable oxygenation case is used as starting point. The major difference occurs in poorly oxygenated cells. This is also where the pO{sub 2}-dependence of the oxygen enhancement ratio is maximal. Conclusions: Improved tumor oxygenation together with increased radionuclide uptake show great potential for optimising treatment strategies, leaving room for successive treatments, or lowering absorbed dose to normal tissues, due to increased tumor response. Further studies of the concomitant use of antiangiogenic drugs and radionuclide therapy therefore appear merited.« less

Multilevel mixed effects parametric survival models using adaptive Gauss-Hermite quadrature with application to recurrent events and individual participant data meta-analysis.

PubMed

Crowther, Michael J; Look, Maxime P; Riley, Richard D

2014-09-28

Multilevel mixed effects survival models are used in the analysis of clustered survival data, such as repeated events, multicenter clinical trials, and individual participant data (IPD) meta-analyses, to investigate heterogeneity in baseline risk and covariate effects. In this paper, we extend parametric frailty models including the exponential, Weibull and Gompertz proportional hazards (PH) models and the log logistic, log normal, and generalized gamma accelerated failure time models to allow any number of normally distributed random effects. Furthermore, we extend the flexible parametric survival model of Royston and Parmar, modeled on the log-cumulative hazard scale using restricted cubic splines, to include random effects while also allowing for non-PH (time-dependent effects). Maximum likelihood is used to estimate the models utilizing adaptive or nonadaptive Gauss-Hermite quadrature. The methods are evaluated through simulation studies representing clinically plausible scenarios of a multicenter trial and IPD meta-analysis, showing good performance of the estimation method. The flexible parametric mixed effects model is illustrated using a dataset of patients with kidney disease and repeated times to infection and an IPD meta-analysis of prognostic factor studies in patients with breast cancer. User-friendly Stata software is provided to implement the methods. Copyright © 2014 John Wiley & Sons, Ltd.

Studies of Isolated and Non-isolated Photospheric Bright Points in an Active Region Observed by the New Vacuum Solar Telescope

NASA Astrophysics Data System (ADS)

Liu, Yanxiao; Xiang, Yongyuan; Erdélyi, Robertus; Liu, Zhong; Li, Dong; Ning, Zongjun; Bi, Yi; Wu, Ning; Lin, Jun

2018-03-01

Properties of photospheric bright points (BPs) near an active region have been studied in TiO λ 7058 Å images observed by the New Vacuum Solar Telescope of the Yunnan Observatories. We developed a novel recognition method that was used to identify and track 2010 BPs. The observed evolving BPs are classified into isolated (individual) and non-isolated (where multiple BPs are observed to display splitting and merging behaviors) sets. About 35.1% of BPs are non-isolated. For both isolated and non-isolated BPs, the brightness varies from 0.8 to 1.3 times the average background intensity and follows a Gaussian distribution. The lifetimes of BPs follow a log-normal distribution, with characteristic lifetimes of (267 ± 140) s and (421 ± 255) s, respectively. Their size also follows log-normal distribution, with an average size of about (2.15 ± 0.74) × 104 km2 and (3.00 ± 1.31) × 104 km2 for area, and (163 ± 27) km and (191 ± 40) km for diameter, respectively. Our results indicate that regions with strong background magnetic field have higher BP number density and higher BP area coverage than regions with weak background field. Apparently, the brightness/size of BPs does not depend on the background field. Lifetimes in regions with strong background magnetic field are shorter than those in regions with weak background field, on average.

Statistical Analysis of Hubble /WFC3 Transit Spectroscopy of Extrasolar Planets

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

Fu, Guangwei; Deming, Drake; Knutson, Heather

2017-10-01

Transmission spectroscopy provides a window to study exoplanetary atmospheres, but that window is fogged by clouds and hazes. Clouds and haze introduce a degeneracy between the strength of gaseous absorption features and planetary physical parameters such as abundances. One way to break that degeneracy is via statistical studies. We collect all published HST /WFC3 transit spectra for 1.1–1.65 μ m water vapor absorption and perform a statistical study on potential correlations between the water absorption feature and planetary parameters. We fit the observed spectra with a template calculated for each planet using the Exo-transmit code. We express the magnitude ofmore » the water absorption in scale heights, thereby removing the known dependence on temperature, surface gravity, and mean molecular weight. We find that the absorption in scale heights has a positive baseline correlation with planetary equilibrium temperature; our hypothesis is that decreasing cloud condensation with increasing temperature is responsible for this baseline slope. However, the observed sample is also intrinsically degenerate in the sense that equilibrium temperature correlates with planetary mass. We compile the distribution of absorption in scale heights, and we find that this distribution is closer to log-normal than Gaussian. However, we also find that the distribution of equilibrium temperatures for the observed planets is similarly log-normal. This indicates that the absorption values are affected by observational bias, whereby observers have not yet targeted a sufficient sample of the hottest planets.« less

In-residence, multiple route exposures to chlorpyrifos and diazinon estimated by indirect method models

NASA Astrophysics Data System (ADS)

Moschandreas, D. J.; Kim, Y.; Karuchit, S.; Ari, H.; Lebowitz, M. D.; O'Rourke, M. K.; Gordon, S.; Robertson, G.

One of the objectives of the National Human Exposure Assessment Survey (NHEXAS) is to estimate exposures to several pollutants in multiple media and determine their distributions for the population of Arizona. This paper presents modeling methods used to estimate exposure distributions of chlorpyrifos and diazinon in the residential microenvironment using the database generated in Arizona (NHEXAS-AZ). A four-stage probability sampling design was used for sample selection. Exposures to pesticides were estimated using the indirect method of exposure calculation by combining measured concentrations of the two pesticides in multiple media with questionnaire information such as time subjects spent indoors, dietary and non-dietary items they consumed, and areas they touched. Most distributions of in-residence exposure to chlorpyrifos and diazinon were log-normal or nearly log-normal. Exposures to chlorpyrifos and diazinon vary by pesticide and route as well as by various demographic characteristics of the subjects. Comparisons of exposure to pesticides were investigated among subgroups of demographic categories, including gender, age, minority status, education, family income, household dwelling type, year the dwelling was built, pesticide use, and carpeted areas within dwellings. Residents with large carpeted areas within their dwellings have higher exposures to both pesticides for all routes than those in less carpet-covered areas. Depending on the route, several other determinants of exposure to pesticides were identified, but a clear pattern could not be established regarding the exposure differences between several subpopulation groups.

Statistical Analysis of Hubble/WFC3 Transit Spectroscopy of Extrasolar Planets

NASA Astrophysics Data System (ADS)

Fu, Guangwei; Deming, Drake; Knutson, Heather; Madhusudhan, Nikku; Mandell, Avi; Fraine, Jonathan

2018-01-01

Transmission spectroscopy provides a window to study exoplanetary atmospheres, but that window is fogged by clouds and hazes. Clouds and haze introduce a degeneracy between the strength of gaseous absorption features and planetary physical parameters such as abundances. One way to break that degeneracy is via statistical studies. We collect all published HST/WFC3 transit spectra for 1.1-1.65 micron water vapor absorption, and perform a statistical study on potential correlations between the water absorption feature and planetary parameters. We fit the observed spectra with a template calculated for each planet using the Exo-Transmit code. We express the magnitude of the water absorption in scale heights, thereby removing the known dependence on temperature, surface gravity, and mean molecular weight. We find that the absorption in scale heights has a positive baseline correlation with planetary equilibrium temperature; our hypothesis is that decreasing cloud condensation with increasing temperature is responsible for this baseline slope. However, the observed sample is also intrinsically degenerate in the sense that equilibrium temperature correlates with planetary mass. We compile the distribution of absorption in scale heights, and we find that this distribution is closer to log-normal than Gaussian. However, we also find that the distribution of equilibrium temperatures for the observed planets is similarly log-normal. This indicates that the absorption values are affected by observational bias, whereby observers have not yet targeted a sufficient sample of the hottest planets.

Statistical Analysis of Hubble/WFC3 Transit Spectroscopy of Extrasolar Planets

NASA Astrophysics Data System (ADS)

Fu, Guangwei; Deming, Drake; Knutson, Heather; Madhusudhan, Nikku; Mandell, Avi; Fraine, Jonathan

2017-10-01

Transmission spectroscopy provides a window to study exoplanetary atmospheres, but that window is fogged by clouds and hazes. Clouds and haze introduce a degeneracy between the strength of gaseous absorption features and planetary physical parameters such as abundances. One way to break that degeneracy is via statistical studies. We collect all published HST/WFC3 transit spectra for 1.1-1.65 μm water vapor absorption and perform a statistical study on potential correlations between the water absorption feature and planetary parameters. We fit the observed spectra with a template calculated for each planet using the Exo-transmit code. We express the magnitude of the water absorption in scale heights, thereby removing the known dependence on temperature, surface gravity, and mean molecular weight. We find that the absorption in scale heights has a positive baseline correlation with planetary equilibrium temperature; our hypothesis is that decreasing cloud condensation with increasing temperature is responsible for this baseline slope. However, the observed sample is also intrinsically degenerate in the sense that equilibrium temperature correlates with planetary mass. We compile the distribution of absorption in scale heights, and we find that this distribution is closer to log-normal than Gaussian. However, we also find that the distribution of equilibrium temperatures for the observed planets is similarly log-normal. This indicates that the absorption values are affected by observational bias, whereby observers have not yet targeted a sufficient sample of the hottest planets.

On the intrinsic shape of the gamma-ray spectrum for Fermi blazars

NASA Astrophysics Data System (ADS)

Kang, Shi-Ju; Wu, Qingwen; Zheng, Yong-Gang; Yin, Yue; Song, Jia-Li; Zou, Hang; Feng, Jian-Chao; Dong, Ai-Jun; Wu, Zhong-Zu; Zhang, Zhi-Bin; Wu, Lin-Hui

2018-05-01

The curvature of the γ-ray spectrumin blazarsmay reflect the intrinsic distribution of emitting electrons, which will further give some information on the possible acceleration and cooling processes in the emitting region. The γ-ray spectra of Fermi blazars are normally fitted either by a single power-law (PL) or a log-normal (call Logarithmic Parabola, LP) form. The possible reason for this difference is not clear. We statistically explore this issue based on the different observational properties of 1419 Fermi blazars in the 3LAC Clean Sample.We find that the γ-ray flux (100MeV–100GeV) and variability index follow bimodal distributions for PL and LP blazars, where the γ-ray flux and variability index show a positive correlation. However, the distributions of γ-ray luminosity and redshift follow a unimodal distribution. Our results suggest that the bimodal distribution of γ-ray fluxes for LP and PL blazars may not be intrinsic and all blazars may have an intrinsically curved γ-ray spectrum, and the PL spectrum is just caused by the fitting effect due to less photons.

Scaling laws and properties of compositional data

NASA Astrophysics Data System (ADS)

Buccianti, Antonella; Albanese, Stefano; Lima, AnnaMaria; Minolfi, Giulia; De Vivo, Benedetto

2016-04-01

Many random processes occur in geochemistry. Accurate predictions of the manner in which elements or chemical species interact each other are needed to construct models able to treat presence of random components. Geochemical variables actually observed are the consequence of several events, some of which may be poorly defined or imperfectly understood. Variables tend to change with time/space but, despite their complexity, may share specific common traits and it is possible to model them stochastically. Description of the frequency distribution of the geochemical abundances has been an important target of research, attracting attention for at least 100 years, starting with CLARKE (1889) and continued by GOLDSCHMIDT (1933) and WEDEPOHL (1955). However, it was AHRENS (1954a,b) who focussed on the effect of skewness distributions, for example the log-normal distribution, regarded by him as a fundamental law of geochemistry. Although modeling of frequency distributions with some probabilistic models (for example Gaussian, log-normal, Pareto) has been well discussed in several fields of application, little attention has been devoted to the features of compositional data. When compositional nature of data is taken into account, the most typical distribution models for compositions are the Dirichlet and the additive logistic normal (or normal on the simplex) (AITCHISON et al. 2003; MATEU-FIGUERAS et al. 2005; MATEU-FIGUERAS and PAWLOWSKY-GLAHN 2008; MATEU-FIGUERAS et al. 2013). As an alternative, because compositional data have to be transformed from simplex space to real space, coordinates obtained by the ilr transformation or by application of the concept of balance can be analyzed by classical methods (EGOZCUE et al. 2003). In this contribution an approach coherent with the properties of compositional information is proposed and used to investigate the shape of the frequency distribution of compositional data. The purpose is to understand data-generation processes from the perspective of compositional theory. The approach is based on the use of the isometric log-ratio transformation, characterized by theoretical and practical advantages, but requiring a more complex geochemical interpretation compared with the investigation of single variables. The proposed methodology directs attention to model the frequency distributions of more complex indices, linking all the terms of the composition to better represent the dynamics of geochemical processes. An example of its application is presented and discussed by considering topsoil geochemistry of Campania Region (southern Italy). The investigated multi-element data archive contains, among others, Al, As, B, Ba, Ca, Co, Cr, Cu, Fe, K, La, Mg, Mn, Mo, Na, Ni, P, Pb, Sr, Th, Ti, V and Zn (mg/kg) contents determined in 3535 new topsoils as well as information on coordinates, geology, land cover. (BUCCIANTI et al., 2015). AHRENS, L. ,1954a. Geochim. Cosm. Acta 6, 121-131. AHRENS, L., 1954b. Geochim. Cosm. Acta 5, 49-73. AITCHISON, J., et al., 2003. Math Geol 35(6), 667-680. BUCCIANTI et al., 2015. Jour. Geoch. Explor., 159, 302-316. CLARKE, F., 1889. Phil. Society of Washington Bull. 11, 131-142. EGOZCUE, J.J. et al., 2003. Math Geol 35(3), 279-300. MATEU-FIGUERAS, G. et al, (2005), Stoch. Environ. Res. Risk Ass. 19(3), 205-214.

Measuring firm size distribution with semi-nonparametric densities

NASA Astrophysics Data System (ADS)

Cortés, Lina M.; Mora-Valencia, Andrés; Perote, Javier

2017-11-01

In this article, we propose a new methodology based on a (log) semi-nonparametric (log-SNP) distribution that nests the lognormal and enables better fits in the upper tail of the distribution through the introduction of new parameters. We test the performance of the lognormal and log-SNP distributions capturing firm size, measured through a sample of US firms in 2004-2015. Taking different levels of aggregation by type of economic activity, our study shows that the log-SNP provides a better fit of the firm size distribution. We also formally introduce the multivariate log-SNP distribution, which encompasses the multivariate lognormal, to analyze the estimation of the joint distribution of the value of the firm's assets and sales. The results suggest that sales are a better firm size measure, as indicated by other studies in the literature.

Football goal distributions and extremal statistics

NASA Astrophysics Data System (ADS)

Greenhough, J.; Birch, P. C.; Chapman, S. C.; Rowlands, G.

2002-12-01

We analyse the distributions of the number of goals scored by home teams, away teams, and the total scored in the match, in domestic football games from 169 countries between 1999 and 2001. The probability density functions (PDFs) of goals scored are too heavy-tailed to be fitted over their entire ranges by Poisson or negative binomial distributions which would be expected for uncorrelated processes. Log-normal distributions cannot include zero scores and here we find that the PDFs are consistent with those arising from extremal statistics. In addition, we show that it is sufficient to model English top division and FA Cup matches in the seasons of 1970/71-2000/01 on Poisson or negative binomial distributions, as reported in analyses of earlier seasons, and that these are not consistent with extremal statistics.

Algae Tile Data: 2004-2007, BPA-51; Preliminary Report, October 28, 2008.

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

Holderman, Charles

Multiple files containing 2004 through 2007 Tile Chlorophyll data for the Kootenai River sites designated as: KR1, KR2, KR3, KR4 (Downriver) and KR6, KR7, KR9, KR9.1, KR10, KR11, KR12, KR13, KR14 (Upriver) were received by SCS. For a complete description of the sites covered, please refer to http://ktoi.scsnetw.com. To maintain consistency with the previous SCS algae reports, all analyses were carried out separately for the Upriver and Downriver categories, as defined in the aforementioned paragraph. The Upriver designation, however, now includes three additional sites, KR11, KR12, and the nutrient addition site, KR9.1. Summary statistics and information on the four responses,more » chlorophyll a, chlorophyll a Accrual Rate, Total Chlorophyll, and Total Chlorophyll Accrual Rate are presented in Print Out 2. Computations were carried out separately for each river position (Upriver and Downriver) and year. For example, the Downriver position in 2004 showed an average Chlorophyll a level of 25.5 mg with a standard deviation of 21.4 and minimum and maximum values of 3.1 and 196 mg, respectively. The Upriver data in 2004 showed a lower overall average chlorophyll a level at 2.23 mg with a lower standard deviation (3.6) and minimum and maximum values of (0.13 and 28.7, respectively). A more comprehensive summary of each variable and position is given in Print Out 3. This lists the information above as well as other summary information such as the variance, standard error, various percentiles and extreme values. Using the 2004 Downriver Chlorophyll a as an example again, the variance of this data was 459.3 and the standard error of the mean was 1.55. The median value or 50th percentile was 21.3, meaning 50% of the data fell above and below this value. It should be noted that this value is somewhat different than the mean of 25.5. This is an indication that the frequency distribution of the data is not symmetrical (skewed). The skewness statistic, listed as part of the first section of each analysis, quantifies this. In a symmetric distribution, such as a Normal distribution, the skewness value would be 0. The tile chlorophyll data, however, shows larger values. Chlorophyll a, in the 2004 Downriver example, has a skewness statistic of 3.54, which is quite high. In the last section of the summary analysis, the stem and leaf plot graphically demonstrates the asymmetry, showing most of the data centered around 25 with a large value at 196. The final plot is referred to as a normal probability plot and graphically compares the data to a theoretical normal distribution. For chlorophyll a, the data (asterisks) deviate substantially from the theoretical normal distribution (diagonal reference line of pluses), indicating that the data is non-normal. Other response variables in both the Downriver and Upriver categories also indicated skewed distributions. Because the sample size and mean comparison procedures below require symmetrical, normally distributed data, each response in the data set was logarithmically transformed. The logarithmic transformation, in this case, can help mitigate skewness problems. The summary statistics for the four transformed responses (log-ChlorA, log-TotChlor, and log-accrual ) are given in Print Out 4. For the 2004 Downriver Chlorophyll a data, the logarithmic transformation reduced the skewness value to -0.36 and produced a more bell-shaped symmetric frequency distribution. Similar improvements are shown for the remaining variables and river categories. Hence, all subsequent analyses given below are based on logarithmic transformations of the original responses.« less

Normality of raw data in general linear models: The most widespread myth in statistics

USGS Publications Warehouse

Kery, Marc; Hatfield, Jeff S.

2003-01-01

In years of statistical consulting for ecologists and wildlife biologists, by far the most common misconception we have come across has been the one about normality in general linear models. These comprise a very large part of the statistical models used in ecology and include t tests, simple and multiple linear regression, polynomial regression, and analysis of variance (ANOVA) and covariance (ANCOVA). There is a widely held belief that the normality assumption pertains to the raw data rather than to the model residuals. We suspect that this error may also occur in countless published studies, whenever the normality assumption is tested prior to analysis. This may lead to the use of nonparametric alternatives (if there are any), when parametric tests would indeed be appropriate, or to use of transformations of raw data, which may introduce hidden assumptions such as multiplicative effects on the natural scale in the case of log-transformed data. Our aim here is to dispel this myth. We very briefly describe relevant theory for two cases of general linear models to show that the residuals need to be normally distributed if tests requiring normality are to be used, such as t and F tests. We then give two examples demonstrating that the distribution of the response variable may be nonnormal, and yet the residuals are well behaved. We do not go into the issue of how to test normality; instead we display the distributions of response variables and residuals graphically.

Meta-analysis of prediction model performance across multiple studies: Which scale helps ensure between-study normality for the C-statistic and calibration measures?

PubMed

Snell, Kym Ie; Ensor, Joie; Debray, Thomas Pa; Moons, Karel Gm; Riley, Richard D

2017-01-01

If individual participant data are available from multiple studies or clusters, then a prediction model can be externally validated multiple times. This allows the model's discrimination and calibration performance to be examined across different settings. Random-effects meta-analysis can then be used to quantify overall (average) performance and heterogeneity in performance. This typically assumes a normal distribution of 'true' performance across studies. We conducted a simulation study to examine this normality assumption for various performance measures relating to a logistic regression prediction model. We simulated data across multiple studies with varying degrees of variability in baseline risk or predictor effects and then evaluated the shape of the between-study distribution in the C-statistic, calibration slope, calibration-in-the-large, and E/O statistic, and possible transformations thereof. We found that a normal between-study distribution was usually reasonable for the calibration slope and calibration-in-the-large; however, the distributions of the C-statistic and E/O were often skewed across studies, particularly in settings with large variability in the predictor effects. Normality was vastly improved when using the logit transformation for the C-statistic and the log transformation for E/O, and therefore we recommend these scales to be used for meta-analysis. An illustrated example is given using a random-effects meta-analysis of the performance of QRISK2 across 25 general practices.

heterogeneous mixture distributions for multi-source extreme rainfall

NASA Astrophysics Data System (ADS)

Ouarda, T.; Shin, J.; Lee, T. S.

2013-12-01

Mixture distributions have been used to model hydro-meteorological variables showing mixture distributional characteristics, e.g. bimodality. Homogeneous mixture (HOM) distributions (e.g. Normal-Normal and Gumbel-Gumbel) have been traditionally applied to hydro-meteorological variables. However, there is no reason to restrict the mixture distribution as the combination of one identical type. It might be beneficial to characterize the statistical behavior of hydro-meteorological variables from the application of heterogeneous mixture (HTM) distributions such as Normal-Gamma. In the present work, we focus on assessing the suitability of HTM distributions for the frequency analysis of hydro-meteorological variables. In the present work, in order to estimate the parameters of HTM distributions, the meta-heuristic algorithm (Genetic Algorithm) is employed to maximize the likelihood function. In the present study, a number of distributions are compared, including the Gamma-Extreme value type-one (EV1) HTM distribution, the EV1-EV1 HOM distribution, and EV1 distribution. The proposed distribution models are applied to the annual maximum precipitation data in South Korea. The Akaike Information Criterion (AIC), the root mean squared errors (RMSE) and the log-likelihood are used as measures of goodness-of-fit of the tested distributions. Results indicate that the HTM distribution (Gamma-EV1) presents the best fitness. The HTM distribution shows significant improvement in the estimation of quantiles corresponding to the 20-year return period. It is shown that extreme rainfall in the coastal region of South Korea presents strong heterogeneous mixture distributional characteristics. Results indicate that HTM distributions are a good alternative for the frequency analysis of hydro-meteorological variables when disparate statistical characteristics are presented.

The probability distribution model of air pollution index and its dominants in Kuala Lumpur

NASA Astrophysics Data System (ADS)

AL-Dhurafi, Nasr Ahmed; Razali, Ahmad Mahir; Masseran, Nurulkamal; Zamzuri, Zamira Hasanah

2016-11-01

This paper focuses on the statistical modeling for the distributions of air pollution index (API) and its sub-indexes data observed at Kuala Lumpur in Malaysia. Five pollutants or sub-indexes are measured including, carbon monoxide (CO); sulphur dioxide (SO2); nitrogen dioxide (NO2), and; particulate matter (PM10). Four probability distributions are considered, namely log-normal, exponential, Gamma and Weibull in search for the best fit distribution to the Malaysian air pollutants data. In order to determine the best distribution for describing the air pollutants data, five goodness-of-fit criteria's are applied. This will help in minimizing the uncertainty in pollution resource estimates and improving the assessment phase of planning. The conflict in criterion results for selecting the best distribution was overcome by using the weight of ranks method. We found that the Gamma distribution is the best distribution for the majority of air pollutants data in Kuala Lumpur.

Methodological study of affine transformations of gene expression data with proposed robust non-parametric multi-dimensional normalization method.

PubMed

Bengtsson, Henrik; Hössjer, Ola

2006-03-01

Low-level processing and normalization of microarray data are most important steps in microarray analysis, which have profound impact on downstream analysis. Multiple methods have been suggested to date, but it is not clear which is the best. It is therefore important to further study the different normalization methods in detail and the nature of microarray data in general. A methodological study of affine models for gene expression data is carried out. Focus is on two-channel comparative studies, but the findings generalize also to single- and multi-channel data. The discussion applies to spotted as well as in-situ synthesized microarray data. Existing normalization methods such as curve-fit ("lowess") normalization, parallel and perpendicular translation normalization, and quantile normalization, but also dye-swap normalization are revisited in the light of the affine model and their strengths and weaknesses are investigated in this context. As a direct result from this study, we propose a robust non-parametric multi-dimensional affine normalization method, which can be applied to any number of microarrays with any number of channels either individually or all at once. A high-quality cDNA microarray data set with spike-in controls is used to demonstrate the power of the affine model and the proposed normalization method. We find that an affine model can explain non-linear intensity-dependent systematic effects in observed log-ratios. Affine normalization removes such artifacts for non-differentially expressed genes and assures that symmetry between negative and positive log-ratios is obtained, which is fundamental when identifying differentially expressed genes. In addition, affine normalization makes the empirical distributions in different channels more equal, which is the purpose of quantile normalization, and may also explain why dye-swap normalization works or fails. All methods are made available in the aroma package, which is a platform-independent package for R.

Workload Characterization and Performance Implications of Large-Scale Blog Servers

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

Jeon, Myeongjae; Kim, Youngjae; Hwang, Jeaho

With the ever-increasing popularity of social network services (SNSs), an understanding of the characteristics of these services and their effects on the behavior of their host servers is critical. However, there has been a lack of research on the workload characterization of servers running SNS applications such as blog services. To fill this void, we empirically characterized real-world web server logs collected from one of the largest South Korean blog hosting sites for 12 consecutive days. The logs consist of more than 96 million HTTP requests and 4.7 TB of network traffic. Our analysis reveals the followings: (i) The transfermore » size of non-multimedia files and blog articles can be modeled using a truncated Pareto distribution and a log-normal distribution, respectively; (ii) User access for blog articles does not show temporal locality, but is strongly biased towards those posted with image or audio files. We additionally discuss the potential performance improvement through clustering of small files on a blog page into contiguous disk blocks, which benefits from the observed file access patterns. Trace-driven simulations show that, on average, the suggested approach achieves 60.6% better system throughput and reduces the processing time for file access by 30.8% compared to the best performance of the Ext4 file system.« less

IMPLEMENTING A NOVEL CYCLIC CO2 FLOOD IN PALEOZOIC REEFS

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

James R. Wood; W. Quinlan; A. Wylie

2003-07-01

Recycled CO2 will be used in this demonstration project to produce bypassed oil from the Silurian Charlton 6 pinnacle reef (Otsego County) in the Michigan Basin. Contract negotiations by our industry partner to gain access to this CO2 that would otherwise be vented to the atmosphere are near completion. A new method of subsurface characterization, log curve amplitude slicing, is being used to map facies distributions and reservoir properties in two reefs, the Belle River Mills and Chester 18 Fields. The Belle River Mills and Chester18 fields are being used as typefields because they have excellent log-curve and core datamore » coverage. Amplitude slicing of the normalized gamma ray curves is showing trends that may indicate significant heterogeneity and compartmentalization in these reservoirs. Digital and hard copy data continues to be compiled for the Niagaran reefs in the Michigan Basin. Technology transfer took place through technical presentations regarding the log curve amplitude slicing technique and a booth at the Midwest PTTC meeting.« less

A branching process model for the analysis of abortive colony size distributions in carbon ion-irradiated normal human fibroblasts.

PubMed

Sakashita, Tetsuya; Hamada, Nobuyuki; Kawaguchi, Isao; Hara, Takamitsu; Kobayashi, Yasuhiko; Saito, Kimiaki

2014-05-01

A single cell can form a colony, and ionizing irradiation has long been known to reduce such a cellular clonogenic potential. Analysis of abortive colonies unable to continue to grow should provide important information on the reproductive cell death (RCD) following irradiation. Our previous analysis with a branching process model showed that the RCD in normal human fibroblasts can persist over 16 generations following irradiation with low linear energy transfer (LET) γ-rays. Here we further set out to evaluate the RCD persistency in abortive colonies arising from normal human fibroblasts exposed to high-LET carbon ions (18.3 MeV/u, 108 keV/µm). We found that the abortive colony size distribution determined by biological experiments follows a linear relationship on the log-log plot, and that the Monte Carlo simulation using the RCD probability estimated from such a linear relationship well simulates the experimentally determined surviving fraction and the relative biological effectiveness (RBE). We identified the short-term phase and long-term phase for the persistent RCD following carbon-ion irradiation, which were similar to those previously identified following γ-irradiation. Taken together, our results suggest that subsequent secondary or tertiary colony formation would be invaluable for understanding the long-lasting RCD. All together, our framework for analysis with a branching process model and a colony formation assay is applicable to determination of cellular responses to low- and high-LET radiation, and suggests that the long-lasting RCD is a pivotal determinant of the surviving fraction and the RBE.

Daily magnesium intake and serum magnesium concentration among Japanese people.

PubMed

Akizawa, Yoriko; Koizumi, Sadayuki; Itokawa, Yoshinori; Ojima, Toshiyuki; Nakamura, Yosikazu; Tamura, Tarou; Kusaka, Yukinori

2008-01-01

The vitamins and minerals that are deficient in the daily diet of a normal adult remain unknown. To answer this question, we conducted a population survey focusing on the relationship between dietary magnesium intake and serum magnesium level. The subjects were 62 individuals from Fukui Prefecture who participated in the 1998 National Nutrition Survey. The survey investigated the physical status, nutritional status, and dietary data of the subjects. Holidays and special occasions were avoided, and a day when people are most likely to be on an ordinary diet was selected as the survey date. The mean (+/-standard deviation) daily magnesium intake was 322 (+/-132), 323 (+/-163), and 322 (+/-147) mg/day for men, women, and the entire group, respectively. The mean (+/-standard deviation) serum magnesium concentration was 20.69 (+/-2.83), 20.69 (+/-2.88), and 20.69 (+/-2.83) ppm for men, women, and the entire group, respectively. The distribution of serum magnesium concentration was normal. Dietary magnesium intake showed a log-normal distribution, which was then transformed by logarithmic conversion for examining the regression coefficients. The slope of the regression line between the serum magnesium concentration (Y ppm) and daily magnesium intake (X mg) was determined using the formula Y = 4.93 (log(10)X) + 8.49. The coefficient of correlation (r) was 0.29. A regression line (Y = 14.65X + 19.31) was observed between the daily intake of magnesium (Y mg) and serum magnesium concentration (X ppm). The coefficient of correlation was 0.28. The daily magnesium intake correlated with serum magnesium concentration, and a linear regression model between them was proposed.

A Bayesian Hybrid Adaptive Randomisation Design for Clinical Trials with Survival Outcomes.

PubMed

Moatti, M; Chevret, S; Zohar, S; Rosenberger, W F

2016-01-01

Response-adaptive randomisation designs have been proposed to improve the efficiency of phase III randomised clinical trials and improve the outcomes of the clinical trial population. In the setting of failure time outcomes, Zhang and Rosenberger (2007) developed a response-adaptive randomisation approach that targets an optimal allocation, based on a fixed sample size. The aim of this research is to propose a response-adaptive randomisation procedure for survival trials with an interim monitoring plan, based on the following optimal criterion: for fixed variance of the estimated log hazard ratio, what allocation minimizes the expected hazard of failure? We demonstrate the utility of the design by redesigning a clinical trial on multiple myeloma. To handle continuous monitoring of data, we propose a Bayesian response-adaptive randomisation procedure, where the log hazard ratio is the effect measure of interest. Combining the prior with the normal likelihood, the mean posterior estimate of the log hazard ratio allows derivation of the optimal target allocation. We perform a simulation study to assess and compare the performance of this proposed Bayesian hybrid adaptive design to those of fixed, sequential or adaptive - either frequentist or fully Bayesian - designs. Non informative normal priors of the log hazard ratio were used, as well as mixture of enthusiastic and skeptical priors. Stopping rules based on the posterior distribution of the log hazard ratio were computed. The method is then illustrated by redesigning a phase III randomised clinical trial of chemotherapy in patients with multiple myeloma, with mixture of normal priors elicited from experts. As expected, there was a reduction in the proportion of observed deaths in the adaptive vs. non-adaptive designs; this reduction was maximized using a Bayes mixture prior, with no clear-cut improvement by using a fully Bayesian procedure. The use of stopping rules allows a slight decrease in the observed proportion of deaths under the alternate hypothesis compared with the adaptive designs with no stopping rules. Such Bayesian hybrid adaptive survival trials may be promising alternatives to traditional designs, reducing the duration of survival trials, as well as optimizing the ethical concerns for patients enrolled in the trial.

Analysis of the Factors Affecting the Interval between Blood Donations Using Log-Normal Hazard Model with Gamma Correlated Frailties.

PubMed

Tavakol, Najmeh; Kheiri, Soleiman; Sedehi, Morteza

2016-01-01

Time to donating blood plays a major role in a regular donor to becoming continues one. The aim of this study was to determine the effective factors on the interval between the blood donations. In a longitudinal study in 2008, 864 samples of first-time donors in Shahrekord Blood Transfusion Center,  capital city of Chaharmahal and Bakhtiari Province, Iran were selected by a systematic sampling and were followed up for five years. Among these samples, a subset of 424 donors who had at least two successful blood donations were chosen for this study and the time intervals between their donations were measured as response variable. Sex, body weight, age, marital status, education, stay and job were recorded as independent variables. Data analysis was performed based on log-normal hazard model with gamma correlated frailty. In this model, the frailties are sum of two independent components assumed a gamma distribution. The analysis was done via Bayesian approach using Markov Chain Monte Carlo algorithm by OpenBUGS. Convergence was checked via Gelman-Rubin criteria using BOA program in R. Age, job and education were significant on chance to donate blood (P<0.05). The chances of blood donation for the higher-aged donors, clericals, workers, free job, students and educated donors were higher and in return, time intervals between their blood donations were shorter. Due to the significance effect of some variables in the log-normal correlated frailty model, it is necessary to plan educational and cultural program to encourage the people with longer inter-donation intervals to donate more frequently.

Analytical approximations for effective relative permeability in the capillary limit

NASA Astrophysics Data System (ADS)

Rabinovich, Avinoam; Li, Boxiao; Durlofsky, Louis J.

2016-10-01

We present an analytical method for calculating two-phase effective relative permeability, krjeff, where j designates phase (here CO2 and water), under steady state and capillary-limit assumptions. These effective relative permeabilities may be applied in experimental settings and for upscaling in the context of numerical flow simulations, e.g., for CO2 storage. An exact solution for effective absolute permeability, keff, in two-dimensional log-normally distributed isotropic permeability (k) fields is the geometric mean. We show that this does not hold for krjeff since log normality is not maintained in the capillary-limit phase permeability field (Kj=k·krj) when capillary pressure, and thus the saturation field, is varied. Nevertheless, the geometric mean is still shown to be suitable for approximating krjeff when the variance of ln⁡k is low. For high-variance cases, we apply a correction to the geometric average gas effective relative permeability using a Winsorized mean, which neglects large and small Kj values symmetrically. The analytical method is extended to anisotropically correlated log-normal permeability fields using power law averaging. In these cases, the Winsorized mean treatment is applied to the gas curves for cases described by negative power law exponents (flow across incomplete layers). The accuracy of our analytical expressions for krjeff is demonstrated through extensive numerical tests, using low-variance and high-variance permeability realizations with a range of correlation structures. We also present integral expressions for geometric-mean and power law average krjeff for the systems considered, which enable derivation of closed-form series solutions for krjeff without generating permeability realizations.

Quality of the log-geometric distribution extrapolation for smaller undiscovered oil and gas pool size

USGS Publications Warehouse

Chenglin, L.; Charpentier, R.R.

2010-01-01

The U.S. Geological Survey procedure for the estimation of the general form of the parent distribution requires that the parameters of the log-geometric distribution be calculated and analyzed for the sensitivity of these parameters to different conditions. In this study, we derive the shape factor of a log-geometric distribution from the ratio of frequencies between adjacent bins. The shape factor has a log straight-line relationship with the ratio of frequencies. Additionally, the calculation equations of a ratio of the mean size to the lower size-class boundary are deduced. For a specific log-geometric distribution, we find that the ratio of the mean size to the lower size-class boundary is the same. We apply our analysis to simulations based on oil and gas pool distributions from four petroleum systems of Alberta, Canada and four generated distributions. Each petroleum system in Alberta has a different shape factor. Generally, the shape factors in the four petroleum systems stabilize with the increase of discovered pool numbers. For a log-geometric distribution, the shape factor becomes stable when discovered pool numbers exceed 50 and the shape factor is influenced by the exploration efficiency when the exploration efficiency is less than 1. The simulation results show that calculated shape factors increase with those of the parent distributions, and undiscovered oil and gas resources estimated through the log-geometric distribution extrapolation are smaller than the actual values. ?? 2010 International Association for Mathematical Geology.

Geostatistics and Bayesian updating for transmissivity estimation in a multiaquifer system in Manitoba, Canada.

PubMed

Kennedy, Paula L; Woodbury, Allan D

2002-01-01

In ground water flow and transport modeling, the heterogeneous nature of porous media has a considerable effect on the resulting flow and solute transport. Some method of generating the heterogeneous field from a limited dataset of uncertain measurements is required. Bayesian updating is one method that interpolates from an uncertain dataset using the statistics of the underlying probability distribution function. In this paper, Bayesian updating was used to determine the heterogeneous natural log transmissivity field for a carbonate and a sandstone aquifer in southern Manitoba. It was determined that the transmissivity in m2/sec followed a natural log normal distribution for both aquifers with a mean of -7.2 and - 8.0 for the carbonate and sandstone aquifers, respectively. The variograms were calculated using an estimator developed by Li and Lake (1994). Fractal nature was not evident in the variogram from either aquifer. The Bayesian updating heterogeneous field provided good results even in cases where little data was available. A large transmissivity zone in the sandstone aquifer was created by the Bayesian procedure, which is not a reflection of any deterministic consideration, but is a natural outcome of updating a prior probability distribution function with observations. The statistical model returns a result that is very reasonable; that is homogeneous in regions where little or no information is available to alter an initial state. No long range correlation trends or fractal behavior of the log-transmissivity field was observed in either aquifer over a distance of about 300 km.

A new macroseismic intensity prediction equation and magnitude estimates of the 1811-1812 New Madrid and 1886 Charleston, South Carolina, earthquakes

NASA Astrophysics Data System (ADS)

Boyd, O. S.; Cramer, C. H.

2013-12-01

We develop an intensity prediction equation (IPE) for the Central and Eastern United States, explore differences between modified Mercalli intensities (MMI) and community internet intensities (CII) and the propensity for reporting, and estimate the moment magnitudes of the 1811-1812 New Madrid, MO, and 1886 Charleston, SC, earthquakes. We constrain the study with North American census data, the National Oceanic and Atmospheric Administration MMI dataset (responses between 1924 and 1985), and the USGS ';Did You Feel It?' CII dataset (responses between June, 2000 and August, 2012). The combined intensity dataset has more than 500,000 felt reports for 517 earthquakes with magnitudes between 2.5 and 7.2. The IPE has the basic form, MMI=c1+c2M+c3exp(λ)+c4λ. where M is moment magnitude and λ is mean log hypocentral distance. Previous IPEs use a limited dataset of MMI, do not differentiate between MMI and CII data in the CEUS, nor account for spatial variations in population. These factors can have an impact at all magnitudes, especially the last factor at large magnitudes and small intensities where the population drops to zero in the Atlantic Ocean and Gulf of Mexico. We assume that the number of reports of a given intensity have hypocentral distances that are log-normally distributed, the distribution of which is modulated by population and the propensity for individuals to report their experience. We do not account for variations in stress drop, regional variations in Q, or distance-dependent geometrical spreading. We simulate the distribution of reports of a given intensity accounting for population and use a grid search method to solve for the fraction of population to report the intensity, the standard deviation of the log-normal distribution and the mean log hypocentral distance, which appears in the above equation. We find that lower intensities, both CII and MMI, are less likely to be reported than greater intensities. Further, there are strong spatial variations in the level of CII reporting. For example, large metropolitan areas appear to have a lower level of reporting relative to rural areas. In general, we find that intensities decrease with increasing distance and decreasing magnitude, as expected. Coefficients for the IPE are c1=1.98×0.13 c2=1.76×0.02 c3=-0.0027×0.0004, and c4=-1.26×0.03. We find significant differences in mean log hypocentral distance between MMI- and CII-based reporting, particularly at smaller mean log distance and higher intensity. Values of mean log distance for CII at high intensity tend to be smaller than for MMI at the same value of intensity. The new IPE leads to magnitude estimates for the 1811-1812 New Madrid earthquakes that are within the broad range of those determined previously. Using three MMI datasets for the New Madrid mainshocks, the new relation results in estimates for the moment magnitudes of the December 16th, 1811, January 23rd, 1812, and February 7th, 1812 mainshocks and December 16th dawn aftershock of 7.1¬¬-7.4, 7.2, 7.5-7.7, and 6.7-7.2, respectively, with a magnitude uncertainty of about ×0.4 units. We estimate a magnitude of 7.0×0.3 for the 1886 Charleston, SC earthquake.

Detrital illite crystals identified from crystallite thickness measurements in siliciclastic sediments

USGS Publications Warehouse

Aldega, L.; Eberl, D.D.

2005-01-01

Illite crystals in siliciclastic sediments are heterogeneous assemblages of detrital material coming from various source rocks and, at paleotemperatures >70 ??C, of superimposed diagenetic modification in the parent sediment. We distinguished the relative proportions of 2M1 detrital illite and possible diagenetic 1Md + 1M illite by a combined analysis of crystal-size distribution and illite polytype quantification. We found that the proportions of 1Md + 1M and 2M1 illite could be determined from crystallite thickness measurements (BWA method, using the MudMaster program) by unmixing measured crystallite thickness distributions using theoretical and calculated log-normal and/or asymptotic distributions. The end-member components that we used to unmix the measured distributions were three asymptotic-shaped distributions (assumed to be the diagenetic component of the mixture, the 1Md + 1M polytypes) calculated using the Galoper program (Phase A was simulated using 500 crystals per cycle of nucleation and growth, Phase B = 333/cycle, and Phase C = 250/ cycle), and one theoretical log-normal distribution (Phase D, assumed to approximate the detrital 2M1 component of the mixture). In addition, quantitative polytype analysis was carried out using the RockJock software for comparison. The two techniques gave comparable results (r2 = 0.93), which indicates that the unmixing method permits one to calculate the proportion of illite polytypes and, therefore, the proportion of 2M1 detrital illite, from crystallite thickness measurements. The overall illite crystallite thicknesses in the samples were found to be a function of the relative proportions of thick 2M1 and thin 1Md + 1M illite. The percentage of illite layers in I-S mixed layers correlates with the mean crystallite thickness of the 1Md + 1M polytypes, indicating that these polytypes, rather than the 2M1 polytype, participate in I-S mixed layering.

Parametric vs. non-parametric statistics of low resolution electromagnetic tomography (LORETA).

PubMed

Thatcher, R W; North, D; Biver, C

2005-01-01

This study compared the relative statistical sensitivity of non-parametric and parametric statistics of 3-dimensional current sources as estimated by the EEG inverse solution Low Resolution Electromagnetic Tomography (LORETA). One would expect approximately 5% false positives (classification of a normal as abnormal) at the P < .025 level of probability (two tailed test) and approximately 1% false positives at the P < .005 level. EEG digital samples (2 second intervals sampled 128 Hz, 1 to 2 minutes eyes closed) from 43 normal adult subjects were imported into the Key Institute's LORETA program. We then used the Key Institute's cross-spectrum and the Key Institute's LORETA output files (*.lor) as the 2,394 gray matter pixel representation of 3-dimensional currents at different frequencies. The mean and standard deviation *.lor files were computed for each of the 2,394 gray matter pixels for each of the 43 subjects. Tests of Gaussianity and different transforms were computed in order to best approximate a normal distribution for each frequency and gray matter pixel. The relative sensitivity of parametric vs. non-parametric statistics were compared using a "leave-one-out" cross validation method in which individual normal subjects were withdrawn and then statistically classified as being either normal or abnormal based on the remaining subjects. Log10 transforms approximated Gaussian distribution in the range of 95% to 99% accuracy. Parametric Z score tests at P < .05 cross-validation demonstrated an average misclassification rate of approximately 4.25%, and range over the 2,394 gray matter pixels was 27.66% to 0.11%. At P < .01 parametric Z score cross-validation false positives were 0.26% and ranged from 6.65% to 0% false positives. The non-parametric Key Institute's t-max statistic at P < .05 had an average misclassification error rate of 7.64% and ranged from 43.37% to 0.04% false positives. The nonparametric t-max at P < .01 had an average misclassification rate of 6.67% and ranged from 41.34% to 0% false positives of the 2,394 gray matter pixels for any cross-validated normal subject. In conclusion, adequate approximation to Gaussian distribution and high cross-validation can be achieved by the Key Institute's LORETA programs by using a log10 transform and parametric statistics, and parametric normative comparisons had lower false positive rates than the non-parametric tests.

The Italian primary school-size distribution and the city-size: a complex nexus

NASA Astrophysics Data System (ADS)

Belmonte, Alessandro; di Clemente, Riccardo; Buldyrev, Sergey V.

2014-06-01

We characterize the statistical law according to which Italian primary school-size distributes. We find that the school-size can be approximated by a log-normal distribution, with a fat lower tail that collects a large number of very small schools. The upper tail of the school-size distribution decreases exponentially and the growth rates are distributed with a Laplace PDF. These distributions are similar to those observed for firms and are consistent with a Bose-Einstein preferential attachment process. The body of the distribution features a bimodal shape suggesting some source of heterogeneity in the school organization that we uncover by an in-depth analysis of the relation between schools-size and city-size. We propose a novel cluster methodology and a new spatial interaction approach among schools which outline the variety of policies implemented in Italy. Different regional policies are also discussed shedding lights on the relation between policy and geographical features.

VizieR Online Data Catalog: Double stars with wide separations in the AGK3 (Halbwachs+, 2016)

NASA Astrophysics Data System (ADS)

Halbwachs, J. L.; Mayor, M.; Udry, S.

2016-10-01

A large list of common proper motion stars selected from the third Astronomischen Gesellschaft Katalog (AGK3) was monitored with the CORAVEL (for COrrelation RAdial VELocities) spectrovelocimeter, in order to prepare a sample of physical binaries with very wide separations. In paper I,66 stars received special attention, since their radial velocities (RV) seemed to be variable. These stars were monitored over several years in order to derive the elements of their spectroscopic orbits. In addition, 10 of them received accurate RV measurements from the SOPHIE spectrograph of the T193 telescope at the Observatory of Haute-Provence. For deriving the orbital elements of double-lined spectroscopic binaries (SB2s), a new method was applied, which assumed that the RV of blended measurements are linear combinations of the RV of the components. 13 SB2 orbits were thus calculated. The orbital elements were eventually obtained for 52 spectroscopic binaries (SBs), two of them making a triple system. 40 SBs received their first orbit and the orbital elements were improved for 10 others. In addition, 11 SBs were discovered with very long periods for which the orbital parameters were not found. It appeared that HD 153252 has a close companion, which is a candidate brown dwarf with a minimum mass of 50 Jupiter masses. In paper II, 80 wide binaries (WBs) were detected, and 39 optical pairs were identified. Adding CPM stars with separations close enough to be almost certain they are physical, a "bias-controlled" sample of 116 wide binaries was obtained, and used to derive the distribution of separations from 100 to 30,000 au. The distribution obtained doesn't match the log-constant distribution, but is in agreement with the log-normal distribution. The spectroscopic binaries detected among the WB components were used to derive statistical informations about the multiple systems. The close binaries in WBs seem to be similar to those detected in other field stars. As for the WBs, they seem to obey the log-normal distribution of periods. The number of quadruple systems is in agreement with the "no correlation" hypothesis; this indicates that an environment conducive to the formation of WBs doesn't favor the formation of subsystems with periods shorter than 10 years. (9 data files).

Likelihood-based confidence intervals for estimating floods with given return periods

NASA Astrophysics Data System (ADS)

Martins, Eduardo Sávio P. R.; Clarke, Robin T.

1993-06-01

This paper discusses aspects of the calculation of likelihood-based confidence intervals for T-year floods, with particular reference to (1) the two-parameter gamma distribution; (2) the Gumbel distribution; (3) the two-parameter log-normal distribution, and other distributions related to the normal by Box-Cox transformations. Calculation of the confidence limits is straightforward using the Nelder-Mead algorithm with a constraint incorporated, although care is necessary to ensure convergence either of the Nelder-Mead algorithm, or of the Newton-Raphson calculation of maximum-likelihood estimates. Methods are illustrated using records from 18 gauging stations in the basin of the River Itajai-Acu, State of Santa Catarina, southern Brazil. A small and restricted simulation compared likelihood-based confidence limits with those given by use of the central limit theorem; for the same confidence probability, the confidence limits of the simulation were wider than those of the central limit theorem, which failed more frequently to contain the true quantile being estimated. The paper discusses possible applications of likelihood-based confidence intervals in other areas of hydrological analysis.

Determining the best population-level alcohol consumption model and its impact on estimates of alcohol-attributable harms

PubMed Central

2012-01-01

Background The goals of our study are to determine the most appropriate model for alcohol consumption as an exposure for burden of disease, to analyze the effect of the chosen alcohol consumption distribution on the estimation of the alcohol Population- Attributable Fractions (PAFs), and to characterize the chosen alcohol consumption distribution by exploring if there is a global relationship within the distribution. Methods To identify the best model, the Log-Normal, Gamma, and Weibull prevalence distributions were examined using data from 41 surveys from Gender, Alcohol and Culture: An International Study (GENACIS) and from the European Comparative Alcohol Study. To assess the effect of these distributions on the estimated alcohol PAFs, we calculated the alcohol PAF for diabetes, breast cancer, and pancreatitis using the three above-named distributions and using the more traditional approach based on categories. The relationship between the mean and the standard deviation from the Gamma distribution was estimated using data from 851 datasets for 66 countries from GENACIS and from the STEPwise approach to Surveillance from the World Health Organization. Results The Log-Normal distribution provided a poor fit for the survey data, with Gamma and Weibull distributions providing better fits. Additionally, our analyses showed that there were no marked differences for the alcohol PAF estimates based on the Gamma or Weibull distributions compared to PAFs based on categorical alcohol consumption estimates. The standard deviation of the alcohol distribution was highly dependent on the mean, with a unit increase in alcohol consumption associated with a unit increase in the mean of 1.258 (95% CI: 1.223 to 1.293) (R2 = 0.9207) for women and 1.171 (95% CI: 1.144 to 1.197) (R2 = 0. 9474) for men. Conclusions Although the Gamma distribution and the Weibull distribution provided similar results, the Gamma distribution is recommended to model alcohol consumption from population surveys due to its fit, flexibility, and the ease with which it can be modified. The results showed that a large degree of variance of the standard deviation of the alcohol consumption Gamma distribution was explained by the mean alcohol consumption, allowing for alcohol consumption to be modeled through a Gamma distribution using only average consumption. PMID:22490226

An analysis of fracture trace patterns in areas of flat-lying sedimentary rocks for the detection of buried geologic structure. [Kansas and Texas

NASA Technical Reports Server (NTRS)

Podwysocki, M. H.

1974-01-01

Two study areas in a cratonic platform underlain by flat-lying sedimentary rocks were analyzed to determine if a quantitative relationship exists between fracture trace patterns and their frequency distributions and subsurface structural closures which might contain petroleum. Fracture trace lengths and frequency (number of fracture traces per unit area) were analyzed by trend surface analysis and length frequency distributions also were compared to a standard Gaussian distribution. Composite rose diagrams of fracture traces were analyzed using a multivariate analysis method which grouped or clustered the rose diagrams and their respective areas on the basis of the behavior of the rays of the rose diagram. Analysis indicates that the lengths of fracture traces are log-normally distributed according to the mapping technique used. Fracture trace frequency appeared higher on the flanks of active structures and lower around passive reef structures. Fracture trace log-mean lengths were shorter over several types of structures, perhaps due to increased fracturing and subsequent erosion. Analysis of rose diagrams using a multivariate technique indicated lithology as the primary control for the lower grouping levels. Groupings at higher levels indicated that areas overlying active structures may be isolated from their neighbors by this technique while passive structures showed no differences which could be isolated.

The Statistical Nature of Fatigue Crack Propagation

DTIC Science & Technology

1977-03-01

LEVEL x - V AFFDL-TRt-T843 r THE STATISTICAL NATURE OF b FATIGUE CRACK PROPAGATION D. A. VIRKLER B. M. HILLBERR Y LL= P. K. GOEL C* SCHOOL...function of crack length was best represented by the three-parameter log-normal distribution. Six growth rate calculation methods were investigated and the...dN, which varied moderately as a function of crack length, replicate a vs. N data were predicted This predicted data reproduced the mean behavior but

Application of survival analysis methodology to the quantitative analysis of LC-MS proteomics data.

PubMed

Tekwe, Carmen D; Carroll, Raymond J; Dabney, Alan R

2012-08-01

Protein abundance in quantitative proteomics is often based on observed spectral features derived from liquid chromatography mass spectrometry (LC-MS) or LC-MS/MS experiments. Peak intensities are largely non-normal in distribution. Furthermore, LC-MS-based proteomics data frequently have large proportions of missing peak intensities due to censoring mechanisms on low-abundance spectral features. Recognizing that the observed peak intensities detected with the LC-MS method are all positive, skewed and often left-censored, we propose using survival methodology to carry out differential expression analysis of proteins. Various standard statistical techniques including non-parametric tests such as the Kolmogorov-Smirnov and Wilcoxon-Mann-Whitney rank sum tests, and the parametric survival model and accelerated failure time-model with log-normal, log-logistic and Weibull distributions were used to detect any differentially expressed proteins. The statistical operating characteristics of each method are explored using both real and simulated datasets. Survival methods generally have greater statistical power than standard differential expression methods when the proportion of missing protein level data is 5% or more. In particular, the AFT models we consider consistently achieve greater statistical power than standard testing procedures, with the discrepancy widening with increasing missingness in the proportions. The testing procedures discussed in this article can all be performed using readily available software such as R. The R codes are provided as supplemental materials. ctekwe@stat.tamu.edu.

Relationship between the column density distribution and evolutionary class of molecular clouds as viewed by ATLASGAL

NASA Astrophysics Data System (ADS)

Abreu-Vicente, J.; Kainulainen, J.; Stutz, A.; Henning, Th.; Beuther, H.

2015-09-01

We present the first study of the relationship between the column density distribution of molecular clouds within nearby Galactic spiral arms and their evolutionary status as measured from their stellar content. We analyze a sample of 195 molecular clouds located at distances below 5.5 kpc, identified from the ATLASGAL 870 μm data. We define three evolutionary classes within this sample: starless clumps, star-forming clouds with associated young stellar objects, and clouds associated with H ii regions. We find that the N(H2) probability density functions (N-PDFs) of these three classes of objects are clearly different: the N-PDFs of starless clumps are narrowest and close to log-normal in shape, while star-forming clouds and H ii regions exhibit a power-law shape over a wide range of column densities and log-normal-like components only at low column densities. We use the N-PDFs to estimate the evolutionary time-scales of the three classes of objects based on a simple analytic model from literature. Finally, we show that the integral of the N-PDFs, the dense gas mass fraction, depends on the total mass of the regions as measured by ATLASGAL: more massive clouds contain greater relative amounts of dense gas across all evolutionary classes. Appendices are available in electronic form at http://www.aanda.org

Uncertainty analysis of the radiological characteristics of radioactive waste using a method based on log-normal distributions

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

Gigase, Yves

2007-07-01

Available in abstract form only. Full text of publication follows: The uncertainty on characteristics of radioactive LILW waste packages is difficult to determine and often very large. This results from a lack of knowledge of the constitution of the waste package and of the composition of the radioactive sources inside. To calculate a quantitative estimate of the uncertainty on a characteristic of a waste package one has to combine these various uncertainties. This paper discusses an approach to this problem, based on the use of the log-normal distribution, which is both elegant and easy to use. It can provide asmore » example quantitative estimates of uncertainty intervals that 'make sense'. The purpose is to develop a pragmatic approach that can be integrated into existing characterization methods. In this paper we show how our method can be applied to the scaling factor method. We also explain how it can be used when estimating other more complex characteristics such as the total uncertainty of a collection of waste packages. This method could have applications in radioactive waste management, more in particular in those decision processes where the uncertainty on the amount of activity is considered to be important such as in probability risk assessment or the definition of criteria for acceptance or categorization. (author)« less

Methodological uncertainty in quantitative prediction of human hepatic clearance from in vitro experimental systems.

PubMed

Hallifax, D; Houston, J B

2009-03-01

Mechanistic prediction of unbound drug clearance from human hepatic microsomes and hepatocytes correlates with in vivo clearance but is both systematically low (10 - 20 % of in vivo clearance) and highly variable, based on detailed assessments of published studies. Metabolic capacity (Vmax) of commercially available human hepatic microsomes and cryopreserved hepatocytes is log-normally distributed within wide (30 - 150-fold) ranges; Km is also log-normally distributed and effectively independent of Vmax, implying considerable variability in intrinsic clearance. Despite wide overlap, average capacity is 2 - 20-fold (dependent on P450 enzyme) greater in microsomes than hepatocytes, when both are normalised (scaled to whole liver). The in vitro ranges contrast with relatively narrow ranges of clearance among clinical studies. The high in vitro variation probably reflects unresolved phenotypical variability among liver donors and practicalities in processing of human liver into in vitro systems. A significant contribution from the latter is supported by evidence of low reproducibility (several fold) of activity in cryopreserved hepatocytes and microsomes prepared from the same cells, between separate occasions of thawing of cells from the same liver. The large uncertainty which exists in human hepatic in vitro systems appears to dominate the overall uncertainty of in vitro-in vivo extrapolation, including uncertainties within scaling, modelling and drug dependent effects. As such, any notion of quantitative prediction of clearance appears severely challenged.

Evaluation of portfolio credit risk based on survival analysis for progressive censored data

NASA Astrophysics Data System (ADS)

Jaber, Jamil J.; Ismail, Noriszura; Ramli, Siti Norafidah Mohd

2017-04-01

In credit risk management, the Basel committee provides a choice of three approaches to the financial institutions for calculating the required capital: the standardized approach, the Internal Ratings-Based (IRB) approach, and the Advanced IRB approach. The IRB approach is usually preferred compared to the standard approach due to its higher accuracy and lower capital charges. This paper use several parametric models (Exponential, log-normal, Gamma, Weibull, Log-logistic, Gompertz) to evaluate the credit risk of the corporate portfolio in the Jordanian banks based on the monthly sample collected from January 2010 to December 2015. The best model is selected using several goodness-of-fit criteria (MSE, AIC, BIC). The results indicate that the Gompertz distribution is the best model parametric model for the data.

A New Bond Albedo for Performing Orbital Debris Brightness to Size Transformations

NASA Technical Reports Server (NTRS)

Mulrooney, Mark K.; Matney, Mark J.

2008-01-01

We have developed a technique for estimating the intrinsic size distribution of orbital debris objects via optical measurements alone. The process is predicated on the empirically observed power-law size distribution of debris (as indicated by radar RCS measurements) and the log-normal probability distribution of optical albedos as ascertained from phase (Lambertian) and range-corrected telescopic brightness measurements. Since the observed distribution of optical brightness is the product integral of the size distribution of the parent [debris] population with the albedo probability distribution, it is a straightforward matter to transform a given distribution of optical brightness back to a size distribution by the appropriate choice of a single albedo value. This is true because the integration of a powerlaw with a log-normal distribution (Fredholm Integral of the First Kind) yields a Gaussian-blurred power-law distribution with identical power-law exponent. Application of a single albedo to this distribution recovers a simple power-law [in size] which is linearly offset from the original distribution by a constant whose value depends on the choice of the albedo. Significantly, there exists a unique Bond albedo which, when applied to an observed brightness distribution, yields zero offset and therefore recovers the original size distribution. For physically realistic powerlaws of negative slope, the proper choice of albedo recovers the parent size distribution by compensating for the observational bias caused by the large number of small objects that appear anomalously large (bright) - and thereby skew the small population upward by rising above the detection threshold - and the lower number of large objects that appear anomalously small (dim). Based on this comprehensive analysis, a value of 0.13 should be applied to all orbital debris albedo-based brightness-to-size transformations regardless of data source. Its prima fascia genesis, derived and constructed from the current RCS to size conversion methodology (SiBAM Size-Based Estimation Model) and optical data reduction standards, assures consistency in application with the prior canonical value of 0.1. Herein we present the empirical and mathematical arguments for this approach and by example apply it to a comprehensive set of photometric data acquired via NASA's Liquid Mirror Telescopes during the 2000-2001 observing season.

TESTING THE PROPAGATING FLUCTUATIONS MODEL WITH A LONG, GLOBAL ACCRETION DISK SIMULATION

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

Hogg, J Drew; Reynolds, Christopher S.

2016-07-20

The broadband variability of many accreting systems displays characteristic structures; log-normal flux distributions, root-mean square (rms)-flux relations, and long inter-band lags. These characteristics are usually interpreted as inward propagating fluctuations of the mass accretion rate in an accretion disk driven by stochasticity of the angular momentum transport mechanism. We present the first analysis of propagating fluctuations in a long-duration, high-resolution, global three-dimensional magnetohydrodynamic (MHD) simulation of a geometrically thin ( h / r ≈ 0.1) accretion disk around a black hole. While the dynamical-timescale turbulent fluctuations in the Maxwell stresses are too rapid to drive radially coherent fluctuations in themore » accretion rate, we find that the low-frequency quasi-periodic dynamo action introduces low-frequency fluctuations in the Maxwell stresses, which then drive the propagating fluctuations. Examining both the mass accretion rate and emission proxies, we recover log-normality, linear rms-flux relations, and radial coherence that would produce inter-band lags. Hence, we successfully relate and connect the phenomenology of propagating fluctuations to modern MHD accretion disk theory.« less

A Poisson Log-Normal Model for Constructing Gene Covariation Network Using RNA-seq Data.

PubMed

Choi, Yoonha; Coram, Marc; Peng, Jie; Tang, Hua

2017-07-01

Constructing expression networks using transcriptomic data is an effective approach for studying gene regulation. A popular approach for constructing such a network is based on the Gaussian graphical model (GGM), in which an edge between a pair of genes indicates that the expression levels of these two genes are conditionally dependent, given the expression levels of all other genes. However, GGMs are not appropriate for non-Gaussian data, such as those generated in RNA-seq experiments. We propose a novel statistical framework that maximizes a penalized likelihood, in which the observed count data follow a Poisson log-normal distribution. To overcome the computational challenges, we use Laplace's method to approximate the likelihood and its gradients, and apply the alternating directions method of multipliers to find the penalized maximum likelihood estimates. The proposed method is evaluated and compared with GGMs using both simulated and real RNA-seq data. The proposed method shows improved performance in detecting edges that represent covarying pairs of genes, particularly for edges connecting low-abundant genes and edges around regulatory hubs.

Introducing high performance distributed logging service for ACS

NASA Astrophysics Data System (ADS)

Avarias, Jorge A.; López, Joao S.; Maureira, Cristián; Sommer, Heiko; Chiozzi, Gianluca

2010-07-01

The ALMA Common Software (ACS) is a software framework that provides the infrastructure for the Atacama Large Millimeter Array and other projects. ACS, based on CORBA, offers basic services and common design patterns for distributed software. Every properly built system needs to be able to log status and error information. Logging in a single computer scenario can be as easy as using fprintf statements. However, in a distributed system, it must provide a way to centralize all logging data in a single place without overloading the network nor complicating the applications. ACS provides a complete logging service infrastructure in which every log has an associated priority and timestamp, allowing filtering at different levels of the system (application, service and clients). Currently the ACS logging service uses an implementation of the CORBA Telecom Log Service in a customized way, using only a minimal subset of the features provided by the standard. The most relevant feature used by ACS is the ability to treat the logs as event data that gets distributed over the network in a publisher-subscriber paradigm. For this purpose the CORBA Notification Service, which is resource intensive, is used. On the other hand, the Data Distribution Service (DDS) provides an alternative standard for publisher-subscriber communication for real-time systems, offering better performance and featuring decentralized message processing. The current document describes how the new high performance logging service of ACS has been modeled and developed using DDS, replacing the Telecom Log Service. Benefits and drawbacks are analyzed. A benchmark is presented comparing the differences between the implementations.

Pulse height response of an optical particle counter to monodisperse aerosols

NASA Technical Reports Server (NTRS)

Wilmoth, R. G.; Grice, S. S.; Cuda, V.

1976-01-01

The pulse height response of a right angle scattering optical particle counter has been investigated using monodisperse aerosols of polystyrene latex spheres, di-octyl phthalate and methylene blue. The results confirm previous measurements for the variation of mean pulse height as a function of particle diameter and show good agreement with the relative response predicted by Mie scattering theory. Measured cumulative pulse height distributions were found to fit reasonably well to a log normal distribution with a minimum geometric standard deviation of about 1.4 for particle diameters greater than about 2 micrometers. The geometric standard deviation was found to increase significantly with decreasing particle diameter.

Quantifying nonstationary radioactivity concentration fluctuations near Chernobyl: A complete statistical description

NASA Astrophysics Data System (ADS)

Viswanathan, G. M.; Buldyrev, S. V.; Garger, E. K.; Kashpur, V. A.; Lucena, L. S.; Shlyakhter, A.; Stanley, H. E.; Tschiersch, J.

2000-09-01

We analyze nonstationary 137Cs atmospheric activity concentration fluctuations measured near Chernobyl after the 1986 disaster and find three new results: (i) the histogram of fluctuations is well described by a log-normal distribution; (ii) there is a pronounced spectral component with period T=1yr, and (iii) the fluctuations are long-range correlated. These findings allow us to quantify two fundamental statistical properties of the data: the probability distribution and the correlation properties of the time series. We interpret our findings as evidence that the atmospheric radionuclide resuspension processes are tightly coupled to the surrounding ecosystems and to large time scale weather patterns.

Complexity of viscous dissipation in turbulent thermal convection

NASA Astrophysics Data System (ADS)

Bhattacharya, Shashwat; Pandey, Ambrish; Kumar, Abhishek; Verma, Mahendra K.

2018-03-01

Using direct numerical simulations of turbulent thermal convection for the Rayleigh number between 106 and 108 and unit Prandtl number, we derive scaling relations for viscous dissipation in the bulk and in the boundary layers. We show that contrary to the general belief, the total viscous dissipation in the bulk is larger, albeit marginally, than that in the boundary layers. The bulk dissipation rate is similar to that in hydrodynamic turbulence with log-normal distribution, but it differs from (U3/d) by a factor of Ra-0.18. Viscous dissipation in the boundary layers is rarer but more intense with a stretched-exponential distribution.

A common mode of origin of power laws in models of market and earthquake

NASA Astrophysics Data System (ADS)

Bhattacharyya, Pratip; Chatterjee, Arnab; Chakrabarti, Bikas K.

2007-07-01

We show that there is a common mode of origin for the power laws observed in two different models: (i) the Pareto law for the distribution of money among the agents with random-saving propensities in an ideal gas-like market model and (ii) the Gutenberg-Richter law for the distribution of overlaps in a fractal-overlap model for earthquakes. We find that the power laws appear as the asymptotic forms of ever-widening log-normal distributions for the agents’ money and the overlap magnitude, respectively. The identification of the generic origin of the power laws helps in better understanding and in developing generalized views of phenomena in such diverse areas as economics and geophysics.

Chaos-assisted tunneling in the presence of Anderson localization.

PubMed

Doggen, Elmer V H; Georgeot, Bertrand; Lemarié, Gabriel

2017-10-01

Tunneling between two classically disconnected regular regions can be strongly affected by the presence of a chaotic sea in between. This phenomenon, known as chaos-assisted tunneling, gives rise to large fluctuations of the tunneling rate. Here we study chaos-assisted tunneling in the presence of Anderson localization effects in the chaotic sea. Our results show that the standard tunneling rate distribution is strongly modified by localization, going from the Cauchy distribution in the ergodic regime to a log-normal distribution in the strongly localized case, for both a deterministic and a disordered model. We develop a single-parameter scaling description which accurately describes the numerical data. Several possible experimental implementations using cold atoms, photonic lattices, or microwave billiards are discussed.

Universal statistics of selected values

NASA Astrophysics Data System (ADS)

Smerlak, Matteo; Youssef, Ahmed

2017-03-01

Selection, the tendency of some traits to become more frequent than others under the influence of some (natural or artificial) agency, is a key component of Darwinian evolution and countless other natural and social phenomena. Yet a general theory of selection, analogous to the Fisher-Tippett-Gnedenko theory of extreme events, is lacking. Here we introduce a probabilistic definition of selection and show that selected values are attracted to a universal family of limiting distributions which generalize the log-normal distribution. The universality classes and scaling exponents are determined by the tail thickness of the random variable under selection. Our results provide a possible explanation for skewed distributions observed in diverse contexts where selection plays a key role, from molecular biology to agriculture and sport.

Field size, length, and width distributions based on LACIE ground truth data. [large area crop inventory experiment

NASA Technical Reports Server (NTRS)

Pitts, D. E.; Badhwar, G.

1980-01-01

The development of agricultural remote sensing systems requires knowledge of agricultural field size distributions so that the sensors, sampling frames, image interpretation schemes, registration systems, and classification systems can be properly designed. Malila et al. (1976) studied the field size distribution for wheat and all other crops in two Kansas LACIE (Large Area Crop Inventory Experiment) intensive test sites using ground observations of the crops and measurements of their field areas based on current year rectified aerial photomaps. The field area and size distributions reported in the present investigation are derived from a representative subset of a stratified random sample of LACIE sample segments. In contrast to previous work, the obtained results indicate that most field-size distributions are not log-normally distributed. The most common field size observed in this study was 10 acres for most crops studied.

Relationships between log N-log S and celestial distribution of gamma-ray bursts

NASA Technical Reports Server (NTRS)

Nishimura, J.; Yamagami, T.

1985-01-01

The apparent conflict between log N-log S curve and isotropic celestial distribution of the gamma ray bursts is discussed. A possible selection effect due to the time profile of each burst is examined. It is shown that the contradiction is due to this selection effect of the gamma ray bursts.

Multiwavelength Studies of Rotating Radio Transients

NASA Astrophysics Data System (ADS)

Miller, Joshua J.

Seven years ago, a new class of pulsars called the Rotating Radio Transients (RRATs) was discovered with the Parkes radio telescope in Australia (McLaughlin et al., 2006). These neutron stars are characterized by strong radio bursts at repeatable dispersion measures, but not detectable using standard periodicity-search algorithms. We now know of roughly 100 of these objects, discovered in new surveys and re-analysis of archival survey data. They generally have longer periods than those of the normal pulsar population, and several have high magnetic fields, similar to those other neutron star populations like the X-ray bright magnetars. However, some of the RRATs have spin-down properties very similar to those of normal pulsars, making it difficult to determine the cause of their unusual emission and possible evolutionary relationships between them and other classes of neutron stars. We have calculated single-pulse flux densities for eight RRAT sources observed using the Parkes radio telescope. Like normal pulsars, the pulse amplitude distributions are well described by log-normal probability distribution functions, though two show evidence for an additional power-law tail. Spectral indices are calculated for the seven RRATs which were detected at multiple frequencies. These RRATs have a mean spectral index of = -3.2(7), or = -3.1(1) when using mean flux densities derived from fitting log-normal probability distribution functions to the pulse amplitude distributions, suggesting that the RRATs have steeper spectra than normal pulsars. When only considering the three RRATs for which we have a wide range of observing frequencies, however, and become --1.7(1) and --2.0(1), respectively, and are roughly consistent with those measured for normal pulsars. In all cases, these spectral indices exclude magnetar-like flat spectra. For PSR J1819--1458, the RRAT with the highest bursting rate, pulses were detected at 685 and 3029 MHz in simultaneous observations and have a spectral index consistent with our other analysis. We also present the results of simultaneous radio and X-ray observations of PSR J1819--1458. Our 94-ks XMM-Newton observation of the high magnetic field (~5x109 T) pulsar reveals a blackbody spectrum ( kT~130 eV) with a broad absorption feature, possibly composed of two lines at ~1.0 and ~1.3 keV. We performed a correlation analysis of the X-ray photons with radio pulses detected in 16.2 hours of simultaneous observations at 1--2 GHz with the Green Bank, Effelsberg, and Parkes telescopes, respectively. Both the detected X-ray photons and radio pulses appear to be randomly distributed in time. We find tentative evidence for a correlation between the detected radio pulses and X-ray photons on timescales of less than 10 pulsar spin periods, with the probability of this occurring by chance being 0.46%. This suggests that the physical process producing the radio pulses may also heat the polar cap.

[Data distribution and transformation in population based sampling survey of viral load in HIV positive men who have sex with men in China].

PubMed

Dou, Z; Chen, J; Jiang, Z; Song, W L; Xu, J; Wu, Z Y

2017-11-10

Objective: To understand the distribution of population viral load (PVL) data in HIV infected men who have sex with men (MSM), fit distribution function and explore the appropriate estimating parameter of PVL. Methods: The detection limit of viral load (VL) was ≤ 50 copies/ml. Box-Cox transformation and normal distribution tests were used to describe the general distribution characteristics of the original and transformed data of PVL, then the stable distribution function was fitted with test of goodness of fit. Results: The original PVL data fitted a skewed distribution with the variation coefficient of 622.24%, and had a multimodal distribution after Box-Cox transformation with optimal parameter ( λ ) of-0.11. The distribution of PVL data over the detection limit was skewed and heavy tailed when transformed by Box-Cox with optimal λ =0. By fitting the distribution function of the transformed data over the detection limit, it matched the stable distribution (SD) function ( α =1.70, β =-1.00, γ =0.78, δ =4.03). Conclusions: The original PVL data had some censored data below the detection limit, and the data over the detection limit had abnormal distribution with large degree of variation. When proportion of the censored data was large, it was inappropriate to use half-value of detection limit to replace the censored ones. The log-transformed data over the detection limit fitted the SD. The median ( M ) and inter-quartile ranger ( IQR ) of log-transformed data can be used to describe the centralized tendency and dispersion tendency of the data over the detection limit.

Comparison of Survival Models for Analyzing Prognostic Factors in Gastric Cancer Patients

PubMed

Habibi, Danial; Rafiei, Mohammad; Chehrei, Ali; Shayan, Zahra; Tafaqodi, Soheil

2018-03-27

Objective: There are a number of models for determining risk factors for survival of patients with gastric cancer. This study was conducted to select the model showing the best fit with available data. Methods: Cox regression and parametric models (Exponential, Weibull, Gompertz, Log normal, Log logistic and Generalized Gamma) were utilized in unadjusted and adjusted forms to detect factors influencing mortality of patients. Comparisons were made with Akaike Information Criterion (AIC) by using STATA 13 and R 3.1.3 softwares. Results: The results of this study indicated that all parametric models outperform the Cox regression model. The Log normal, Log logistic and Generalized Gamma provided the best performance in terms of AIC values (179.2, 179.4 and 181.1, respectively). On unadjusted analysis, the results of the Cox regression and parametric models indicated stage, grade, largest diameter of metastatic nest, largest diameter of LM, number of involved lymph nodes and the largest ratio of metastatic nests to lymph nodes, to be variables influencing the survival of patients with gastric cancer. On adjusted analysis, according to the best model (log normal), grade was found as the significant variable. Conclusion: The results suggested that all parametric models outperform the Cox model. The log normal model provides the best fit and is a good substitute for Cox regression. Creative Commons Attribution License

Geophysical evaluation of sandstone aquifers in the Reconcavo-Tucano Basin, Bahia -- Brazil

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

Lima, O.A.L. de

1993-11-01

The upper clastic sediments in the Reconcavo-Tucano basin comprise a multilayer aquifer system of Jurassic age. Its groundwater is normally fresh down to depths of more than 1,000 m. Locally, however, there are zones producing high salinity or sulfur geothermal water. Analysis of electrical logs of more than 150 wells enabled the identification of the most typical sedimentary structures and the gross geometries for the sandstone units in selected areas of the basin. Based on this information, the thick sands are interpreted as coalescent point bars and the shales as flood plain deposits of a large fluvial environment. The resistivitymore » logs and core laboratory data are combined to develop empirical equations relating aquifer porosity and permeability to log-derived parameters such as formation factor and cementation exponent. Temperature logs of 15 wells were useful to quantify the water leakage through semiconfining shales. The groundwater quality was inferred from spontaneous potential (SP) log deflections under control of chemical analysis of water samples. An empirical chart is developed that relates the SP-derived water resistivity to the true water resistivity within the formations. The patterns of salinity variation with depth inferred from SP logs were helpful in identifying subsurface flows along major fault zones, where extensive mixing of water is taking place. A total of 49 vertical Schlumberger resistivity soundings aid in defining aquifer structures and in extrapolating the log derived results. Transition zones between fresh and saline waters have also been detected based on a combination of logging and surface sounding data. Ionic filtering by water leakage across regional shales, local convection and mixing along major faults and hydrodynamic dispersion away from lateral permeability contrasts are the main mechanisms controlling the observed distributions of salinity and temperature within the basin.« less

Assessing cadmium exposure risks of vegetables with plant uptake factor and soil property.

PubMed

Yang, Yang; Chang, Andrew C; Wang, Meie; Chen, Weiping; Peng, Chi

2018-07-01

Plant uptake factors (PUFs) are of great importance in human cadmium (Cd) exposure risk assessment while it has been often treated in a generic way. We collected 1077 pairs of vegetable-soil samples from production fields to characterize Cd PUFs and demonstrated their utility in assessing Cd exposure risks to consumers of locally grown vegetables. The Cd PUFs varied with plant species and pH and organic matter content of soils. Once normalized PUFs against soil parameters, the PUFs distributions were log-normal in nature. In this manner, the PUFs were represented by definable probability distributions instead of a deterministic figure. The Cd exposure risks were then assessed using the normalized PUF based on the Monte Carlo simulation algorithm. Factors affecting the extent of Cd exposures were isolated through sensitivity analyses. Normalized PUF would illustrate the outcomes for uncontaminated and slightly contaminated soils. Among the vegetables, lettuce was potentially hazardous for residents due to its high Cd accumulation but low Zn concentration. To protect 95% of the lettuce production from causing excessive Cd exposure risks, pH of soils needed to be 5.9 and above. Copyright © 2018 Elsevier Ltd. All rights reserved.

Mesh size selectivity of the gillnet in East China Sea

NASA Astrophysics Data System (ADS)

Li, L. Z.; Tang, J. H.; Xiong, Y.; Huang, H. L.; Wu, L.; Shi, J. J.; Gao, Y. S.; Wu, F. Q.

2017-07-01

A production test using several gillnets with various mesh sizes was carried out to discover the selectivity of gillnets in the East China Sea. The result showed that the composition of the catch species was synthetically affected by panel height and mesh size. The bycatch species of the 10-m nets were more than those of the 6-m nets. For target species, the effect of panel height on juvenile fish was ambiguous, but the number of juvenile fish declined quickly with the increase in mesh size. According to model deviance (D) and Akaike’s information criterion, the bi-normal model provided the best fit for small yellow croaker (Larimichthy polyactis), and the relative retention was 0.2 and 1, respectively. For Chelidonichthys spinosus, the log-normal was the best model; the right tilt of the selectivity curve was obvious and well coincided with the original data. The contact population of small yellow croaker showed a bi-normal distribution, and body lengths ranged from 95 to 215 mm. The contact population of C. spinosus showed a normal distribution, and the body lengths ranged from 95 to 205 mm. These results can provide references for coastal fishery management.

Collective purchase behavior toward retail price changes

NASA Astrophysics Data System (ADS)

Ueno, Hiromichi; Watanabe, Tsutomu; Takayasu, Hideki; Takayasu, Misako

2011-02-01

By analyzing a huge amount of point-of-sale data collected from Japanese supermarkets, we find power law relationships between price and sales numbers. The estimated values of the exponents of these power laws depend on the category of products; however, they are independent of the stores, thereby implying the existence of universal human purchase behavior. The rate of sales numbers around these power laws are generally approximated by log-normal distributions implying that there are hidden random parameters, which might proportionally affect the purchase activity.

The comparison of proportional hazards and accelerated failure time models in analyzing the first birth interval survival data

NASA Astrophysics Data System (ADS)

Faruk, Alfensi

2018-03-01

Survival analysis is a branch of statistics, which is focussed on the analysis of time- to-event data. In multivariate survival analysis, the proportional hazards (PH) is the most popular model in order to analyze the effects of several covariates on the survival time. However, the assumption of constant hazards in PH model is not always satisfied by the data. The violation of the PH assumption leads to the misinterpretation of the estimation results and decreasing the power of the related statistical tests. On the other hand, the accelerated failure time (AFT) models do not assume the constant hazards in the survival data as in PH model. The AFT models, moreover, can be used as the alternative to PH model if the constant hazards assumption is violated. The objective of this research was to compare the performance of PH model and the AFT models in analyzing the significant factors affecting the first birth interval (FBI) data in Indonesia. In this work, the discussion was limited to three AFT models which were based on Weibull, exponential, and log-normal distribution. The analysis by using graphical approach and a statistical test showed that the non-proportional hazards exist in the FBI data set. Based on the Akaike information criterion (AIC), the log-normal AFT model was the most appropriate model among the other considered models. Results of the best fitted model (log-normal AFT model) showed that the covariates such as women’s educational level, husband’s educational level, contraceptive knowledge, access to mass media, wealth index, and employment status were among factors affecting the FBI in Indonesia.

Alternate methods for FAAT S-curve generation

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

Kaufman, A.M.

The FAAT (Foreign Asset Assessment Team) assessment methodology attempts to derive a probability of effect as a function of incident field strength. The probability of effect is the likelihood that the stress put on a system exceeds its strength. In the FAAT methodology, both the stress and strength are random variables whose statistical properties are estimated by experts. Each random variable has two components of uncertainty: systematic and random. The systematic uncertainty drives the confidence bounds in the FAAT assessment. Its variance can be reduced by improved information. The variance of the random uncertainty is not reducible. The FAAT methodologymore » uses an assessment code called ARES to generate probability of effect curves (S-curves) at various confidence levels. ARES assumes log normal distributions for all random variables. The S-curves themselves are log normal cumulants associated with the random portion of the uncertainty. The placement of the S-curves depends on confidence bounds. The systematic uncertainty in both stress and strength is usually described by a mode and an upper and lower variance. Such a description is not consistent with the log normal assumption of ARES and an unsatisfactory work around solution is used to obtain the required placement of the S-curves at each confidence level. We have looked into this situation and have found that significant errors are introduced by this work around. These errors are at least several dB-W/cm{sup 2} at all confidence levels, but they are especially bad in the estimate of the median. In this paper, we suggest two alternate solutions for the placement of S-curves. To compare these calculational methods, we have tabulated the common combinations of upper and lower variances and generated the relevant S-curves offsets from the mode difference of stress and strength.« less

Daily Magnesium Intake and Serum Magnesium Concentration among Japanese People

PubMed Central

Akizawa, Yoriko; Koizumi, Sadayuki; Itokawa, Yoshinori; Ojima, Toshiyuki; Nakamura, Yosikazu; Tamura, Tarou; Kusaka, Yukinori

2008-01-01

Background The vitamins and minerals that are deficient in the daily diet of a normal adult remain unknown. To answer this question, we conducted a population survey focusing on the relationship between dietary magnesium intake and serum magnesium level. Methods The subjects were 62 individuals from Fukui Prefecture who participated in the 1998 National Nutrition Survey. The survey investigated the physical status, nutritional status, and dietary data of the subjects. Holidays and special occasions were avoided, and a day when people are most likely to be on an ordinary diet was selected as the survey date. Results The mean (±standard deviation) daily magnesium intake was 322 (±132), 323 (±163), and 322 (±147) mg/day for men, women, and the entire group, respectively. The mean (±standard deviation) serum magnesium concentration was 20.69 (±2.83), 20.69 (±2.88), and 20.69 (±2.83) ppm for men, women, and the entire group, respectively. The distribution of serum magnesium concentration was normal. Dietary magnesium intake showed a log-normal distribution, which was then transformed by logarithmic conversion for examining the regression coefficients. The slope of the regression line between the serum magnesium concentration (Y ppm) and daily magnesium intake (X mg) was determined using the formula Y = 4.93 (log10X) + 8.49. The coefficient of correlation (r) was 0.29. A regression line (Y = 14.65X + 19.31) was observed between the daily intake of magnesium (Y mg) and serum magnesium concentration (X ppm). The coefficient of correlation was 0.28. Conclusion The daily magnesium intake correlated with serum magnesium concentration, and a linear regression model between them was proposed. PMID:18635902

Jimsphere wind and turbulence exceedance statistic

NASA Technical Reports Server (NTRS)

Adelfang, S. I.; Court, A.

1972-01-01

Exceedance statistics of winds and gusts observed over Cape Kennedy with Jimsphere balloon sensors are described. Gust profiles containing positive and negative departures, from smoothed profiles, in the wavelength ranges 100-2500, 100-1900, 100-860, and 100-460 meters were computed from 1578 profiles with four 41 weight digital high pass filters. Extreme values of the square root of gust speed are normally distributed. Monthly and annual exceedance probability distributions of normalized rms gust speeds in three altitude bands (2-7, 6-11, and 9-14 km) are log-normal. The rms gust speeds are largest in the 100-2500 wavelength band between 9 and 14 km in late winter and early spring. A study of monthly and annual exceedance probabilities and the number of occurrences per kilometer of level crossings with positive slope indicates significant variability with season, altitude, and filter configuration. A decile sampling scheme is tested and an optimum approach is suggested for drawing a relatively small random sample that represents the characteristic extreme wind speeds and shears of a large parent population of Jimsphere wind profiles.

Results of APL rain gauge network measurements in mid-Atlantic coast region and comparisons of distributions with CCIR models

NASA Technical Reports Server (NTRS)

Goldhirsh, Julius; Gebo, Norman; Rowland, John

1988-01-01

In this effort are described cumulative rain rate distributions for a network of nine tipping bucket rain gauge systems located in the mid-Atlantic coast region in the vicinity of the NASA Wallops Flight Facility, Wallops Island, Virginia. The rain gauges are situated within a gridded region of dimensions of 47 km east-west by 70 km north-south. Distributions are presented for the individual site measurements and the network average for the year period June 1, 1986 through May 31, 1987. A previous six year average distribution derived from measurements at one of the site locations is also presented. Comparisons are given of the network average, the CCIR (International Radio Consultative Committee) climatic zone, and the CCIR functional model distributions, the latter of which approximates a log normal at the lower rain rate and a gamma function at the higher rates.

SU-E-T-664: Radiobiological Modeling of Prophylactic Cranial Irradiation in Mice

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

Smith, D; Debeb, B; Woodward, W

Purpose: Prophylactic cranial irradiation (PCI) is a clinical technique used to reduce the incidence of brain metastasis and improve overall survival in select patients with ALL and SCLC, and we have shown the potential of PCI in select breast cancer patients through a mouse model (manuscript in preparation). We developed a computational model using our experimental results to demonstrate the advantage of treating brain micro-metastases early. Methods: MATLAB was used to develop the computational model of brain metastasis and PCI in mice. The number of metastases per mouse and the volume of metastases from four- and eight-week endpoints were fitmore » to normal and log-normal distributions, respectively. Model input parameters were optimized so that model output would match the experimental number of metastases per mouse. A limiting dilution assay was performed to validate the model. The effect of radiation at different time points was computationally evaluated through the endpoints of incidence, number of metastases, and tumor burden. Results: The correlation between experimental number of metastases per mouse and the Gaussian fit was 87% and 66% at the two endpoints. The experimental volumes and the log-normal fit had correlations of 99% and 97%. In the optimized model, the correlation between number of metastases per mouse and the Gaussian fit was 96% and 98%. The log-normal volume fit and the model agree 100%. The model was validated by a limiting dilution assay, where the correlation was 100%. The model demonstrates that cells are very sensitive to radiation at early time points, and delaying treatment introduces a threshold dose at which point the incidence and number of metastases decline. Conclusion: We have developed a computational model of brain metastasis and PCI in mice that is highly correlated to our experimental data. The model shows that early treatment of subclinical disease is highly advantageous.« less

Statistical characterization of a large geochemical database and effect of sample size

USGS Publications Warehouse

Zhang, C.; Manheim, F.T.; Hinde, J.; Grossman, J.N.

2005-01-01

The authors investigated statistical distributions for concentrations of chemical elements from the National Geochemical Survey (NGS) database of the U.S. Geological Survey. At the time of this study, the NGS data set encompasses 48,544 stream sediment and soil samples from the conterminous United States analyzed by ICP-AES following a 4-acid near-total digestion. This report includes 27 elements: Al, Ca, Fe, K, Mg, Na, P, Ti, Ba, Ce, Co, Cr, Cu, Ga, La, Li, Mn, Nb, Nd, Ni, Pb, Sc, Sr, Th, V, Y and Zn. The goal and challenge for the statistical overview was to delineate chemical distributions in a complex, heterogeneous data set spanning a large geographic range (the conterminous United States), and many different geological provinces and rock types. After declustering to create a uniform spatial sample distribution with 16,511 samples, histograms and quantile-quantile (Q-Q) plots were employed to delineate subpopulations that have coherent chemical and mineral affinities. Probability groupings are discerned by changes in slope (kinks) on the plots. Major rock-forming elements, e.g., Al, Ca, K and Na, tend to display linear segments on normal Q-Q plots. These segments can commonly be linked to petrologic or mineralogical associations. For example, linear segments on K and Na plots reflect dilution of clay minerals by quartz sand (low in K and Na). Minor and trace element relationships are best displayed on lognormal Q-Q plots. These sensitively reflect discrete relationships in subpopulations within the wide range of the data. For example, small but distinctly log-linear subpopulations for Pb, Cu, Zn and Ag are interpreted to represent ore-grade enrichment of naturally occurring minerals such as sulfides. None of the 27 chemical elements could pass the test for either normal or lognormal distribution on the declustered data set. Part of the reasons relate to the presence of mixtures of subpopulations and outliers. Random samples of the data set with successively smaller numbers of data points showed that few elements passed standard statistical tests for normality or log-normality until sample size decreased to a few hundred data points. Large sample size enhances the power of statistical tests, and leads to rejection of most statistical hypotheses for real data sets. For large sample sizes (e.g., n > 1000), graphical methods such as histogram, stem-and-leaf, and probability plots are recommended for rough judgement of probability distribution if needed. ?? 2005 Elsevier Ltd. All rights reserved.

A Box-Cox normal model for response times.

PubMed

Klein Entink, R H; van der Linden, W J; Fox, J-P

2009-11-01

The log-transform has been a convenient choice in response time modelling on test items. However, motivated by a dataset of the Medical College Admission Test where the lognormal model violated the normality assumption, the possibilities of the broader class of Box-Cox transformations for response time modelling are investigated. After an introduction and an outline of a broader framework for analysing responses and response times simultaneously, the performance of a Box-Cox normal model for describing response times is investigated using simulation studies and a real data example. A transformation-invariant implementation of the deviance information criterium (DIC) is developed that allows for comparing model fit between models with different transformation parameters. Showing an enhanced description of the shape of the response time distributions, its application in an educational measurement context is discussed at length.

Measuring Resistance to Change at the Within-Session Level

ERIC Educational Resources Information Center

Tonneau, Francois; Rios, Americo; Cabrera, Felipe

2006-01-01

Resistance to change is often studied by measuring response rate in various components of a multiple schedule. Response rate in each component is normalized (that is, divided by its baseline level) and then log-transformed. Differential resistance to change is demonstrated if the normalized, log-transformed response rate in one component decreases…

Phenomenology of wall-bounded Newtonian turbulence.

PubMed

L'vov, Victor S; Pomyalov, Anna; Procaccia, Itamar; Zilitinkevich, Sergej S

2006-01-01

We construct a simple analytic model for wall-bounded turbulence, containing only four adjustable parameters. Two of these parameters are responsible for the viscous dissipation of the components of the Reynolds stress tensor. The other two parameters control the nonlinear relaxation of these objects. The model offers an analytic description of the profiles of the mean velocity and the correlation functions of velocity fluctuations in the entire boundary region, from the viscous sublayer, through the buffer layer, and further into the log-law turbulent region. In particular, the model predicts a very simple distribution of the turbulent kinetic energy in the log-law region between the velocity components: the streamwise component contains a half of the total energy whereas the wall-normal and cross-stream components contain a quarter each. In addition, the model predicts a very simple relation between the von Kármán slope k and the turbulent velocity in the log-law region v+ (in wall units): v+=6k. These predictions are in excellent agreement with direct numerical simulation data and with recent laboratory experiments.

Evaluation of sewage sludge and slow pyrolyzed sewage sludge-derived biochar for adsorption of phenanthrene and pyrene.

PubMed

Zielińska, Anna; Oleszczuk, Patryk

2015-09-01

The present study investigated the sorption of phenanthrene (PHE) and pyrene (PYR) by sewage sludges and sewage sludge-derived biochars. The organic carbon normalized distribution coefficient (log K(OC) for C(w) = 0.01 S(w)) for the sewage sludges ranged from 5.62 L kg(-1) to 5.64 L kg(-1) for PHE and from 5.72 L kg(-1) to 5.75 L kg(-1) for PYR. The conversion of sewage sludges into biochar significantly increased their sorption capacity. The value of log K(OC) for the biochars ranged from 5.54 L kg(-1) to 6.23 L kg(-1) for PHE and from 5.95 L kg(-1) to 6.52 L kg(-1) for PYR depending on temperature of pyrolysis. The dominant process was monolayer adsorption in the micropores and/or multilayer surface adsorption (in the mesopores), which was indicated by the significant correlations between log K(OC) and surface properties of biochars. PYR was sorbed better on the tested materials than PHE. Copyright © 2015 Elsevier Ltd. All rights reserved.

Spatial organization of surface nanobubbles and its implications in their formation process.

PubMed

Lhuissier, Henri; Lohse, Detlef; Zhang, Xuehua

2014-02-21

We study the size and spatial distribution of surface nanobubbles formed by the solvent exchange method to gain insight into the mechanism of their formation. The analysis of Atomic Force Microscopy (AFM) images of nanobubbles formed on a hydrophobic surface reveals that the nanobubbles are not randomly located, which we attribute to the role of the history of nucleation during the formation. Moreover, the size of each nanobubble is found to be strongly correlated with the area of the bubble-depleted zone around it. The precise correlation suggests that the nanobubbles grow by diffusion of the gas from the bulk rather than by diffusion of the gas adsorbed on the surface. Lastly, the size distribution of the nanobubbles is found to be well described by a log-normal distribution.

Microscopic understanding of the complex polymer dynamics in a blend —A molecular-dynamics simulation study

NASA Astrophysics Data System (ADS)

Diddens, D.; Brodeck, M.; Heuer, A.

2011-09-01

Within polymer blends composed of two species with largely different glass transition temperatures like PEO/PMMA, the dynamics of the fast PEO component is severely affected by the rather immobile PMMA, reflected by a breakdown of the typical Rouse scaling. The phenomenological random Rouse model (RRM), in which each monomer has an individual mobility obeying a broad log-normal distribution, has been applied to these blends. Using a newly developed method, we extract the distribution of friction coefficients from MD simulations of a PEO/PMMA blend, thereby testing the RRM explicitly. In our simulations we observe that the distribution is much narrower than expected from the RRM. Here, rather, the presence of additional forward-backward correlations of intermolecular origin is responsible for the anomalous PEO behavior.

CYP1A2 in a smoking and a non-smoking population; correlation of urinary and salivary phenotypic ratios.

PubMed

Woolridge, Helen; Williams, John; Cronin, Anna; Evans, Nicola; Steventon, Glyn B

2004-01-01

The use of caffeine as a probe for CYP1A2 phenotyping has been extensively investigated over the last 25 years. Numerous metabolic ratios have been employed and various biological fluids analysed for caffeine and its metabolites. These investigations have used non-smoking, smoking and numerous disease populations to investigate the role of CYP1A2 in possible disease aetiology and for induction and inhibition studies in vivo using dietary, environmental and pharmaceutical compounds. This investigation found that the 17X/137X CYP1A2 metabolic ratio in a 5 h saliva sample and 0-5 h urine collection was not normally distributed in both a non-smoking and a smoking population. The urinary and salivary CYP1A2 metabolic ratio was log normally distributed in the non-smoking population but the smoking population showed a bi- (or tri-)modal distribution on log transformation of both the urinary and salivary CYP1A2 metabolic ratios. The CYP1A2 metabolic ratios were significantly higher in the smoking population compared to the non-smoking population when both the urinary and salivary CYP1A2 metabolic ratios were analysed. These results indicate that urinary flow rate was not a factor in the variation in CYP1A2 phenotype in the non-smoking and smoking populations studied here. The increased CYP1A2 activity in the smoking population was probably due to induction of the CYP1A2 gene via the Ah receptor causing an increase in the concentration of CYP1A2 protein.

Twitter-Based Analysis of the Dynamics of Collective Attention to Political Parties

PubMed Central

Eom, Young-Ho; Puliga, Michelangelo; Smailović, Jasmina; Mozetič, Igor; Caldarelli, Guido

2015-01-01

Large-scale data from social media have a significant potential to describe complex phenomena in the real world and to anticipate collective behaviors such as information spreading and social trends. One specific case of study is represented by the collective attention to the action of political parties. Not surprisingly, researchers and stakeholders tried to correlate parties' presence on social media with their performances in elections. Despite the many efforts, results are still inconclusive since this kind of data is often very noisy and significant signals could be covered by (largely unknown) statistical fluctuations. In this paper we consider the number of tweets (tweet volume) of a party as a proxy of collective attention to the party, identify the dynamics of the volume, and show that this quantity has some information on the election outcome. We find that the distribution of the tweet volume for each party follows a log-normal distribution with a positive autocorrelation of the volume over short terms, which indicates the volume has large fluctuations of the log-normal distribution yet with a short-term tendency. Furthermore, by measuring the ratio of two consecutive daily tweet volumes, we find that the evolution of the daily volume of a party can be described by means of a geometric Brownian motion (i.e., the logarithm of the volume moves randomly with a trend). Finally, we determine the optimal period of averaging tweet volume for reducing fluctuations and extracting short-term tendencies. We conclude that the tweet volume is a good indicator of parties' success in the elections when considered over an optimal time window. Our study identifies the statistical nature of collective attention to political issues and sheds light on how to model the dynamics of collective attention in social media. PMID:26161795

Twitter-Based Analysis of the Dynamics of Collective Attention to Political Parties.

PubMed

Eom, Young-Ho; Puliga, Michelangelo; Smailović, Jasmina; Mozetič, Igor; Caldarelli, Guido

2015-01-01

Large-scale data from social media have a significant potential to describe complex phenomena in the real world and to anticipate collective behaviors such as information spreading and social trends. One specific case of study is represented by the collective attention to the action of political parties. Not surprisingly, researchers and stakeholders tried to correlate parties' presence on social media with their performances in elections. Despite the many efforts, results are still inconclusive since this kind of data is often very noisy and significant signals could be covered by (largely unknown) statistical fluctuations. In this paper we consider the number of tweets (tweet volume) of a party as a proxy of collective attention to the party, identify the dynamics of the volume, and show that this quantity has some information on the election outcome. We find that the distribution of the tweet volume for each party follows a log-normal distribution with a positive autocorrelation of the volume over short terms, which indicates the volume has large fluctuations of the log-normal distribution yet with a short-term tendency. Furthermore, by measuring the ratio of two consecutive daily tweet volumes, we find that the evolution of the daily volume of a party can be described by means of a geometric Brownian motion (i.e., the logarithm of the volume moves randomly with a trend). Finally, we determine the optimal period of averaging tweet volume for reducing fluctuations and extracting short-term tendencies. We conclude that the tweet volume is a good indicator of parties' success in the elections when considered over an optimal time window. Our study identifies the statistical nature of collective attention to political issues and sheds light on how to model the dynamics of collective attention in social media.

Estimation of the incubation period of invasive aspergillosis by survival models in acute myeloid leukemia patients.

PubMed

Bénet, Thomas; Voirin, Nicolas; Nicolle, Marie-Christine; Picot, Stephane; Michallet, Mauricette; Vanhems, Philippe

2013-02-01

The duration of the incubation of invasive aspergillosis (IA) remains unknown. The objective of this investigation was to estimate the time interval between aplasia onset and that of IA symptoms in acute myeloid leukemia (AML) patients. A single-centre prospective survey (2004-2009) included all patients with AML and probable/proven IA. Parametric survival models were fitted to the distribution of the time intervals between aplasia onset and IA. Overall, 53 patients had IA after aplasia, with the median observed time interval between the two being 15 days. Based on log-normal distribution, the median estimated IA incubation period was 14.6 days (95% CI; 12.8-16.5 days).

Detection of anomalous events

DOEpatents

Ferragut, Erik M.; Laska, Jason A.; Bridges, Robert A.

2016-06-07

A system is described for receiving a stream of events and scoring the events based on anomalousness and maliciousness (or other classification). The system can include a plurality of anomaly detectors that together implement an algorithm to identify low-probability events and detect atypical traffic patterns. The anomaly detector provides for comparability of disparate sources of data (e.g., network flow data and firewall logs.) Additionally, the anomaly detector allows for regulatability, meaning that the algorithm can be user configurable to adjust a number of false alerts. The anomaly detector can be used for a variety of probability density functions, including normal Gaussian distributions, irregular distributions, as well as functions associated with continuous or discrete variables.

Far-infrared properties of cluster galaxies

NASA Technical Reports Server (NTRS)

Bicay, M. D.; Giovanelli, R.

1987-01-01

Far-infrared properties are derived for a sample of over 200 galaxies in seven clusters: A262, Cancer, A1367, A1656 (Coma), A2147, A2151 (Hercules), and Pegasus. The IR-selected sample consists almost entirely of IR normal galaxies, with Log of L(FIR) = 9.79 solar luminosities, Log of L(FIR)/L(B) = 0,79, and Log of S(100 microns)/S(60 microns) = 0.42. None of the sample galaxies has Log of L(FIR) greater than 11.0 solar luminosities, and only one has a FIR-to-blue luminosity ratio greater than 10. No significant differences are found in the FIR properties of HI-deficient and HI-normal cluster galaxies.

The Italian primary school-size distribution and the city-size: a complex nexus

PubMed Central

Belmonte, Alessandro; Di Clemente, Riccardo; Buldyrev, Sergey V.

2014-01-01

We characterize the statistical law according to which Italian primary school-size distributes. We find that the school-size can be approximated by a log-normal distribution, with a fat lower tail that collects a large number of very small schools. The upper tail of the school-size distribution decreases exponentially and the growth rates are distributed with a Laplace PDF. These distributions are similar to those observed for firms and are consistent with a Bose-Einstein preferential attachment process. The body of the distribution features a bimodal shape suggesting some source of heterogeneity in the school organization that we uncover by an in-depth analysis of the relation between schools-size and city-size. We propose a novel cluster methodology and a new spatial interaction approach among schools which outline the variety of policies implemented in Italy. Different regional policies are also discussed shedding lights on the relation between policy and geographical features. PMID:24954714

Localized massive halo properties in BAHAMAS and MACSIS simulations: scalings, log-normality, and covariance

NASA Astrophysics Data System (ADS)

Farahi, Arya; Evrard, August E.; McCarthy, Ian; Barnes, David J.; Kay, Scott T.

2018-05-01

Using tens of thousands of halos realized in the BAHAMAS and MACSIS simulations produced with a consistent astrophysics treatment that includes AGN feedback, we validate a multi-property statistical model for the stellar and hot gas mass behavior in halos hosting groups and clusters of galaxies. The large sample size allows us to extract fine-scale mass-property relations (MPRs) by performing local linear regression (LLR) on individual halo stellar mass (Mstar) and hot gas mass (Mgas) as a function of total halo mass (Mhalo). We find that: 1) both the local slope and variance of the MPRs run with mass (primarily) and redshift (secondarily); 2) the conditional likelihood, p(Mstar, Mgas| Mhalo, z) is accurately described by a multivariate, log-normal distribution, and; 3) the covariance of Mstar and Mgas at fixed Mhalo is generally negative, reflecting a partially closed baryon box model for high mass halos. We validate the analytical population model of Evrard et al. (2014), finding sub-percent accuracy in the log-mean halo mass selected at fixed property, ⟨ln Mhalo|Mgas⟩ or ⟨ln Mhalo|Mstar⟩, when scale-dependent MPR parameters are employed. This work highlights the potential importance of allowing for running in the slope and scatter of MPRs when modeling cluster counts for cosmological studies. We tabulate LLR fit parameters as a function of halo mass at z = 0, 0.5 and 1 for two popular mass conventions.

Analyzing coastal environments by means of functional data analysis

NASA Astrophysics Data System (ADS)

Sierra, Carlos; Flor-Blanco, Germán; Ordoñez, Celestino; Flor, Germán; Gallego, José R.

2017-07-01

Here we used Functional Data Analysis (FDA) to examine particle-size distributions (PSDs) in a beach/shallow marine sedimentary environment in Gijón Bay (NW Spain). The work involved both Functional Principal Components Analysis (FPCA) and Functional Cluster Analysis (FCA). The grainsize of the sand samples was characterized by means of laser dispersion spectroscopy. Within this framework, FPCA was used as a dimension reduction technique to explore and uncover patterns in grain-size frequency curves. This procedure proved useful to describe variability in the structure of the data set. Moreover, an alternative approach, FCA, was applied to identify clusters and to interpret their spatial distribution. Results obtained with this latter technique were compared with those obtained by means of two vector approaches that combine PCA with CA (Cluster Analysis). The first method, the point density function (PDF), was employed after adapting a log-normal distribution to each PSD and resuming each of the density functions by its mean, sorting, skewness and kurtosis. The second applied a centered-log-ratio (clr) to the original data. PCA was then applied to the transformed data, and finally CA to the retained principal component scores. The study revealed functional data analysis, specifically FPCA and FCA, as a suitable alternative with considerable advantages over traditional vector analysis techniques in sedimentary geology studies.

Accuracy for detection of simulated lesions: comparison of fluid-attenuated inversion-recovery, proton density--weighted, and T2-weighted synthetic brain MR imaging

NASA Technical Reports Server (NTRS)

Herskovits, E. H.; Itoh, R.; Melhem, E. R.

2001-01-01

OBJECTIVE: The objective of our study was to determine the effects of MR sequence (fluid-attenuated inversion-recovery [FLAIR], proton density--weighted, and T2-weighted) and of lesion location on sensitivity and specificity of lesion detection. MATERIALS AND METHODS: We generated FLAIR, proton density-weighted, and T2-weighted brain images with 3-mm lesions using published parameters for acute multiple sclerosis plaques. Each image contained from zero to five lesions that were distributed among cortical-subcortical, periventricular, and deep white matter regions; on either side; and anterior or posterior in position. We presented images of 540 lesions, distributed among 2592 image regions, to six neuroradiologists. We constructed a contingency table for image regions with lesions and another for image regions without lesions (normal). Each table included the following: the reviewer's number (1--6); the MR sequence; the side, position, and region of the lesion; and the reviewer's response (lesion present or absent [normal]). We performed chi-square and log-linear analyses. RESULTS: The FLAIR sequence yielded the highest true-positive rates (p < 0.001) and the highest true-negative rates (p < 0.001). Regions also differed in reviewers' true-positive rates (p < 0.001) and true-negative rates (p = 0.002). The true-positive rate model generated by log-linear analysis contained an additional sequence-location interaction. The true-negative rate model generated by log-linear analysis confirmed these associations, but no higher order interactions were added. CONCLUSION: We developed software with which we can generate brain images of a wide range of pulse sequences and that allows us to specify the location, size, shape, and intrinsic characteristics of simulated lesions. We found that the use of FLAIR sequences increases detection accuracy for cortical-subcortical and periventricular lesions over that associated with proton density- and T2-weighted sequences.

Application of Tryptophan Fluorescence Bandwidth-Maximum Plot in Analysis of Monoclonal Antibody Structure.

PubMed

Huang, Cheng-Yen; Hsieh, Ming-Ching; Zhou, Qinwei

2017-04-01

Monoclonal antibodies have become the fastest growing protein therapeutics in recent years. The stability and heterogeneity pertaining to its physical and chemical structures remain a big challenge. Tryptophan fluorescence has been proven to be a versatile tool to monitor protein tertiary structure. By modeling the tryptophan fluorescence emission envelope with log-normal distribution curves, the quantitative measure can be exercised for the routine characterization of monoclonal antibody overall tertiary structure. Furthermore, the log-normal deconvolution results can be presented as a two-dimensional plot with tryptophan emission bandwidth vs. emission maximum to enhance the resolution when comparing samples or as a function of applied perturbations. We demonstrate this by studying four different monoclonal antibodies, which show the distinction on emission bandwidth-maximum plot despite their similarity in overall amino acid sequences and tertiary structures. This strategy is also used to demonstrate the tertiary structure comparability between different lots manufactured for one of the monoclonal antibodies (mAb2). In addition, in the unfolding transition studies of mAb2 as a function of guanidine hydrochloride concentration, the evolution of the tertiary structure can be clearly traced in the emission bandwidth-maximum plot.

Studies of the Ability to Hold the Eye in Eccentric Gaze: Measurements in Normal Subjects with the Head Erect

NASA Technical Reports Server (NTRS)

Reschke, Millard F.; Somers, Jeffrey T.; Feiveson, Alan H.; Leigh, R. John; Wood, Scott J.; Paloski, William H.; Kornilova, Ludmila

2006-01-01

We studied the ability to hold the eyes in eccentric horizontal or vertical gaze angles in 68 normal humans, age range 19-56. Subjects attempted to sustain visual fixation of a briefly flashed target located 30 in the horizontal plane and 15 in the vertical plane in a dark environment. Conventionally, the ability to hold eccentric gaze is estimated by fitting centripetal eye drifts by exponential curves and calculating the time constant (t(sub c)) of these slow phases of gazeevoked nystagmus. Although the distribution of time-constant measurements (t(sub c)) in our normal subjects was extremely skewed due to occasional test runs that exhibited near-perfect stability (large t(sub c) values), we found that log10(tc) was approximately normally distributed within classes of target direction. Therefore, statistical estimation and inference on the effect of target direction was performed on values of z identical with log10t(sub c). Subjects showed considerable variation in their eyedrift performance over repeated trials; nonetheless, statistically significant differences emerged: values of tc were significantly higher for gaze elicited to targets in the horizontal plane than for the vertical plane (P less than 10(exp -5), suggesting eccentric gazeholding is more stable in the horizontal than in the vertical plane. Furthermore, centrifugal eye drifts were observed in 13.3, 16.0 and 55.6% of cases for horizontal, upgaze and downgaze tests, respectively. Fifth percentile values of the time constant were estimated to be 10.2 sec, 3.3 sec and 3.8 sec for horizontal, upward and downward gaze, respectively. The difference between horizontal and vertical gazeholding may be ascribed to separate components of the velocity position neural integrator for eye movements, and to differences in orbital mechanics. Our statistical method for representing the range of normal eccentric gaze stability can be readily applied in a clinical setting to patients who were exposed to environments that may have modified their central integrators and thus require monitoring. Patients with gaze-evoked nystagmus can be flagged by comparing to the above established normative criteria.

Retention for Stoploss reinsurance to minimize VaR in compound Poisson-Lognormal distribution

NASA Astrophysics Data System (ADS)

Soleh, Achmad Zanbar; Noviyanti, Lienda; Nurrahmawati, Irma

2015-12-01

Automobile insurance is one of the emerging general insurance's product in Indonesia. Fluctuation in total premium revenues and total claim expenses leads to a risk that insurance company can not be able to pay consumer's claims, thus reinsurance is needeed. Reinsurance is a risk transfer mechanism from the insurance company to another company called reinsurer, one of the reinsurance type is Stoploss. Because reinsurer charges premium to the insurance company, it is important to determine the retention or the total claims to be retain solely by the insurance company. Thus, retention is determined using Value at Risk (VaR) which minimize the total risk of the insurance company in the presence of Stoploss reinsurance. Retention depends only on the distribution of total claims and reinsurance loading factor. We use the compound Poisson distribution and the Log-Normal Distribution to illustrate the retention value in a collective risk model.

Do wealth distributions follow power laws? Evidence from ‘rich lists’

NASA Astrophysics Data System (ADS)

Brzezinski, Michal

2014-07-01

We use data on the wealth of the richest persons taken from the 'rich lists' provided by business magazines like Forbes to verify if the upper tails of wealth distributions follow, as often claimed, a power-law behaviour. The data sets used cover the world's richest persons over 1996-2012, the richest Americans over 1988-2012, the richest Chinese over 2006-2012, and the richest Russians over 2004-2011. Using a recently introduced comprehensive empirical methodology for detecting power laws, which allows for testing the goodness of fit as well as for comparing the power-law model with rival distributions, we find that a power-law model is consistent with data only in 35% of the analysed data sets. Moreover, even if wealth data are consistent with the power-law model, they are usually also consistent with some rivals like the log-normal or stretched exponential distributions.

Statistics of backscatter radar return from vegetation

NASA Technical Reports Server (NTRS)

Karam, M. A.; Chen, K. S.; Fung, A. K.

1992-01-01

The statistical characteristics of radar return from vegetation targets are investigated through a simulation study based upon the first-order scattered field. For simulation purposes, the vegetation targets are modeled as a layer of randomly oriented and spaced finite cylinders, needles, or discs, or a combination of them. The finite cylinder is used to represent a branch or a trunk, the needle for a stem or a coniferous leaf, and the disc for a decidous leaf. For a plane wave illuminating a vegetation canopy, simulation results show that the signal returned from a layer of disc- or needle-shaped leaves follows the Gamma distribution, and that the signal returned from a layer of branches resembles the log normal distribution. The Gamma distribution also represents the signal returned from a layer of a mixture of branches and leaves regardless of the leaf shapes. Results also indicate that the polarization state does not have a significant impact on signal distribution.

Predictive distributions for between-study heterogeneity and simple methods for their application in Bayesian meta-analysis

PubMed Central

Turner, Rebecca M; Jackson, Dan; Wei, Yinghui; Thompson, Simon G; Higgins, Julian P T

2015-01-01

Numerous meta-analyses in healthcare research combine results from only a small number of studies, for which the variance representing between-study heterogeneity is estimated imprecisely. A Bayesian approach to estimation allows external evidence on the expected magnitude of heterogeneity to be incorporated. The aim of this paper is to provide tools that improve the accessibility of Bayesian meta-analysis. We present two methods for implementing Bayesian meta-analysis, using numerical integration and importance sampling techniques. Based on 14 886 binary outcome meta-analyses in the Cochrane Database of Systematic Reviews, we derive a novel set of predictive distributions for the degree of heterogeneity expected in 80 settings depending on the outcomes assessed and comparisons made. These can be used as prior distributions for heterogeneity in future meta-analyses. The two methods are implemented in R, for which code is provided. Both methods produce equivalent results to standard but more complex Markov chain Monte Carlo approaches. The priors are derived as log-normal distributions for the between-study variance, applicable to meta-analyses of binary outcomes on the log odds-ratio scale. The methods are applied to two example meta-analyses, incorporating the relevant predictive distributions as prior distributions for between-study heterogeneity. We have provided resources to facilitate Bayesian meta-analysis, in a form accessible to applied researchers, which allow relevant prior information on the degree of heterogeneity to be incorporated. © 2014 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. PMID:25475839

Are CO Observations of Interstellar Clouds Tracing the H2?

NASA Astrophysics Data System (ADS)

Federrath, Christoph; Glover, S. C. O.; Klessen, R. S.; Mac Low, M.

2010-01-01

Interstellar clouds are commonly observed through the emission of rotational transitions from carbon monoxide (CO). However, the abundance ratio of CO to molecular hydrogen (H2), which is the most abundant molecule in molecular clouds is only about 10-4. This raises the important question of whether the observed CO emission is actually tracing the bulk of the gas in these clouds, and whether it can be used to derive quantities like the total mass of the cloud, the gas density distribution function, the fractal dimension, and the velocity dispersion--size relation. To evaluate the usability and accuracy of CO as a tracer for H2 gas, we generate synthetic observations of hydrodynamical models that include a detailed chemical network to follow the formation and photo-dissociation of H2 and CO. These three-dimensional models of turbulent interstellar cloud formation self-consistently follow the coupled thermal, dynamical and chemical evolution of 32 species, with a particular focus on H2 and CO (Glover et al. 2009). We find that CO primarily traces the dense gas in the clouds, however, with a significant scatter due to turbulent mixing and self-shielding of H2 and CO. The H2 probability distribution function (PDF) is well-described by a log-normal distribution. In contrast, the CO column density PDF has a strongly non-Gaussian low-density wing, not at all consistent with a log-normal distribution. Centroid velocity statistics show that CO is more intermittent than H2, leading to an overestimate of the velocity scaling exponent in the velocity dispersion--size relation. With our systematic comparison of H2 and CO data from the numerical models, we hope to provide a statistical formula to correct for the bias of CO observations. CF acknowledges financial support from a Kade Fellowship of the American Museum of Natural History.

Log-Linear Models for Gene Association

PubMed Central

Hu, Jianhua; Joshi, Adarsh; Johnson, Valen E.

2009-01-01

We describe a class of log-linear models for the detection of interactions in high-dimensional genomic data. This class of models leads to a Bayesian model selection algorithm that can be applied to data that have been reduced to contingency tables using ranks of observations within subjects, and discretization of these ranks within gene/network components. Many normalization issues associated with the analysis of genomic data are thereby avoided. A prior density based on Ewens’ sampling distribution is used to restrict the number of interacting components assigned high posterior probability, and the calculation of posterior model probabilities is expedited by approximations based on the likelihood ratio statistic. Simulation studies are used to evaluate the efficiency of the resulting algorithm for known interaction structures. Finally, the algorithm is validated in a microarray study for which it was possible to obtain biological confirmation of detected interactions. PMID:19655032

Scaling of global input-output networks

NASA Astrophysics Data System (ADS)

Liang, Sai; Qi, Zhengling; Qu, Shen; Zhu, Ji; Chiu, Anthony S. F.; Jia, Xiaoping; Xu, Ming

2016-06-01

Examining scaling patterns of networks can help understand how structural features relate to the behavior of the networks. Input-output networks consist of industries as nodes and inter-industrial exchanges of products as links. Previous studies consider limited measures for node strengths and link weights, and also ignore the impact of dataset choice. We consider a comprehensive set of indicators in this study that are important in economic analysis, and also examine the impact of dataset choice, by studying input-output networks in individual countries and the entire world. Results show that Burr, Log-Logistic, Log-normal, and Weibull distributions can better describe scaling patterns of global input-output networks. We also find that dataset choice has limited impacts on the observed scaling patterns. Our findings can help examine the quality of economic statistics, estimate missing data in economic statistics, and identify key nodes and links in input-output networks to support economic policymaking.

Demonstration of a Low Cost, High-Speed Fiber Optic Transceiver

DTIC Science & Technology

2002-09-01

200 610 (2) 800 600 (3) Diameter of cable(s) (mm) 0.125 3 7 (4) 100×10 (5) Weight (5 m cable, kg) (6) 0.008 0.1 0.51 0.5 Reliability ( MTTF hrs...Based on 1E7 hour MTTF number from Honeywell preliminary data sheet (8) Based on 12 VCSELs, log-normal distribution, σ = 0.225 Technical...A009 on Form DD 1423-1 Optical Link for Radar Digital Processor Andrew Davidson, Terri L. Dooley, Grant R. Emmel, Robert A. Marsland, and

Binary data corruption due to a Brownian agent

NASA Astrophysics Data System (ADS)

Newman, T. J.; Triampo, Wannapong

1999-05-01

We introduce a model of binary data corruption induced by a Brownian agent (active random walker) on a d-dimensional lattice. A continuum formulation allows the exact calculation of several quantities related to the density of corrupted bits ρ, for example, the mean of ρ and the density-density correlation function. Excellent agreement is found with the results from numerical simulations. We also calculate the probability distribution of ρ in d=1, which is found to be log normal, indicating that the system is governed by extreme fluctuations.

Statistical methods of fracture characterization using acoustic borehole televiewer log interpretation

NASA Astrophysics Data System (ADS)

Massiot, Cécile; Townend, John; Nicol, Andrew; McNamara, David D.

2017-08-01

Acoustic borehole televiewer (BHTV) logs provide measurements of fracture attributes (orientations, thickness, and spacing) at depth. Orientation, censoring, and truncation sampling biases similar to those described for one-dimensional outcrop scanlines, and other logging or drilling artifacts specific to BHTV logs, can affect the interpretation of fracture attributes from BHTV logs. K-means, fuzzy K-means, and agglomerative clustering methods provide transparent means of separating fracture groups on the basis of their orientation. Fracture spacing is calculated for each of these fracture sets. Maximum likelihood estimation using truncated distributions permits the fitting of several probability distributions to the fracture attribute data sets within truncation limits, which can then be extrapolated over the entire range where they naturally occur. Akaike Information Criterion (AIC) and Schwartz Bayesian Criterion (SBC) statistical information criteria rank the distributions by how well they fit the data. We demonstrate these attribute analysis methods with a data set derived from three BHTV logs acquired from the high-temperature Rotokawa geothermal field, New Zealand. Varying BHTV log quality reduces the number of input data points, but careful selection of the quality levels where fractures are deemed fully sampled increases the reliability of the analysis. Spacing data analysis comprising up to 300 data points and spanning three orders of magnitude can be approximated similarly well (similar AIC rankings) with several distributions. Several clustering configurations and probability distributions can often characterize the data at similar levels of statistical criteria. Thus, several scenarios should be considered when using BHTV log data to constrain numerical fracture models.

[Quantification of the gnostic sensitivity via measurement of the vibration threshold and of finger tip sensation].

PubMed

Oosterhuis, H J; Bouwsma, C; van Halsema, B; Hollander, R A; Kros, C J; Tombroek, I

1992-10-03

Quantification of vibration perception and fingertip sensation in routine neurological examination. Neurological Clinic, University Hospital, Groningen, the Netherlands. Prospective, controlled investigation. Vibration perception and fingertip sensation were quantified in a large group of normal control persons of various ages and in neurological patients and compared with the usual sensory tests at routine neurological examination. The vibration perception limit was measured with a biothesiometer without accelerometer, the fingertip sensation with a device for two-point discrimination slightly modified according to Renfrew ('Renfrew meter'). Concordance of the tests was studied by calculating kappa values. The normal values of both sensory qualities had a log-normal distribution and increased with age. The values obtained with the Renfrew meter correlated well with those of the two-point discrimination and stereognosis but were systematically higher than those indicated by Renfrew. Both methods appear useful at routine neurological examination if certain measuring precautions are taken.

Estimation of design floods in ungauged catchments using a regional index flood method. A case study of Lake Victoria Basin in Kenya

NASA Astrophysics Data System (ADS)

Nobert, Joel; Mugo, Margaret; Gadain, Hussein

Reliable estimation of flood magnitudes corresponding to required return periods, vital for structural design purposes, is impacted by lack of hydrological data in the study area of Lake Victoria Basin in Kenya. Use of regional information, derived from data at gauged sites and regionalized for use at any location within a homogenous region, would improve the reliability of the design flood estimation. Therefore, the regional index flood method has been applied. Based on data from 14 gauged sites, a delineation of the basin into two homogenous regions was achieved using elevation variation (90-m DEM), spatial annual rainfall pattern and Principal Component Analysis of seasonal rainfall patterns (from 94 rainfall stations). At site annual maximum series were modelled using the Log normal (LN) (3P), Log Logistic Distribution (LLG), Generalized Extreme Value (GEV) and Log Pearson Type 3 (LP3) distributions. The parameters of the distributions were estimated using the method of probability weighted moments. Goodness of fit tests were applied and the GEV was identified as the most appropriate model for each site. Based on the GEV model, flood quantiles were estimated and regional frequency curves derived from the averaged at site growth curves. Using the least squares regression method, relationships were developed between the index flood, which is defined as the Mean Annual Flood (MAF) and catchment characteristics. The relationships indicated area, mean annual rainfall and altitude were the three significant variables that greatly influence the index flood. Thereafter, estimates of flood magnitudes in ungauged catchments within a homogenous region were estimated from the derived equations for index flood and quantiles from the regional curves. These estimates will improve flood risk estimation and to support water management and engineering decisions and actions.

A log-Weibull spatial scan statistic for time to event data.

PubMed

Usman, Iram; Rosychuk, Rhonda J

2018-06-13

Spatial scan statistics have been used for the identification of geographic clusters of elevated numbers of cases of a condition such as disease outbreaks. These statistics accompanied by the appropriate distribution can also identify geographic areas with either longer or shorter time to events. Other authors have proposed the spatial scan statistics based on the exponential and Weibull distributions. We propose the log-Weibull as an alternative distribution for the spatial scan statistic for time to events data and compare and contrast the log-Weibull and Weibull distributions through simulation studies. The effect of type I differential censoring and power have been investigated through simulated data. Methods are also illustrated on time to specialist visit data for discharged patients presenting to emergency departments for atrial fibrillation and flutter in Alberta during 2010-2011. We found northern regions of Alberta had longer times to specialist visit than other areas. We proposed the spatial scan statistic for the log-Weibull distribution as a new approach for detecting spatial clusters for time to event data. The simulation studies suggest that the test performs well for log-Weibull data.

Structural changes of casein micelles in a calcium gradient film.

PubMed

Gebhardt, Ronald; Burghammer, Manfred; Riekel, Christian; Roth, Stephan Volkher; Müller-Buschbaum, Peter

2008-04-09

Calcium gradients are prepared by sequentially filling a micropipette with casein solutions of varying calcium concentration and spreading them on glass slides. The casein film is formed by a solution casting process, which results in a macroscopically rough surface. Microbeam grazing incidence small-angle X-ray scattering (microGISAXS) is used to investigate the lateral size distribution of three main components in casein films: casein micelles, casein mini-micelles, and micellar calcium phosphate. At length scales within the beam size the film surface is flat and detection of size distribution in a macroscopic casein gradient becomes accessible. The model used to analyze the data is based on a set of three log-normal distributed particle sizes. Increasing calcium concentration causes a decrease in casein micelle diameter while the size of casein mini-micelles increases and micellar calcium phosphate particles remain unchanged.

Neuropsychological constraints to human data production on a global scale

NASA Astrophysics Data System (ADS)

Gros, C.; Kaczor, G.; Marković, D.

2012-01-01

Which are the factors underlying human information production on a global level? In order to gain an insight into this question we study a corpus of 252-633 mil. publicly available data files on the Internet corresponding to an overall storage volume of 284-675 Terabytes. Analyzing the file size distribution for several distinct data types we find indications that the neuropsychological capacity of the human brain to process and record information may constitute the dominant limiting factor for the overall growth of globally stored information, with real-world economic constraints having only a negligible influence. This supposition draws support from the observation that the files size distributions follow a power law for data without a time component, like images, and a log-normal distribution for multimedia files, for which time is a defining qualia.

The Ghost in the Machine: Fracking in the Earth's Complex Brittle Crust

NASA Astrophysics Data System (ADS)

Malin, P. E.

2015-12-01

This paper discusses in the impact of complex rock properties on practical applications like fracking and its associated seismic emissions. A variety of borehole measurements show that the complex physical properties of the upper crust cannot be characterized by averages on any scale. Instead they appear to follow 3 empirical rule: a power law distribution in physical scales, a lognormal distribution in populations, and a direct relation between changes in porosity and log(permeability). These rules can be directly related to the presence of fluid rich and seismically active fractures - from mineral grains to fault segments. (These are the "ghosts" referred to in the title.) In other physical systems, such behaviors arise on the boundaries of phase changes, and are studied as "critical state physics". In analogy to the 4 phases of water, crustal rocks progress upward from a un-fractured, ductile lower crust to nearly cohesionless surface alluvium. The crust in between is in an unstable transition. It is in this layer methods such as hydrofracking operate - be they in Oil and Gas, geothermal, or mining. As a result, nothing is predictable in these systems. Crustal models have conventionally been constructed assuming that in situ permeability and related properties are normally distributed. This approach is consistent with the use of short scale-length cores and logs to estimate properties. However, reservoir-scale flow data show that they are better fit to lognormal distributions. Such "long tail" distributions are observed for well productivity, ore vein grades, and induced seismic signals. Outcrop and well-log data show that many rock properties also show a power-law-type variation in scale lengths. In terms of Fourier power spectra, if peaks per km is k, then their power is proportional to 1/k. The source of this variation is related to pore-space connectivity, beginning with grain-fractures. We then show that a passive seismic method, Tomographic Fracture ImagingTM (TFI), can observe the distribution of this connectivity. Combined with TFI data, our fracture-connectivity model reveals the most significant crustal features and account for their range of passive and stimulated behaviors.

Detection of vapor nanobubbles by small angle neutron scattering (SANS)

NASA Astrophysics Data System (ADS)

Popov, Emilian; He, Lilin; Dominguez-Ontiveros, Elvis; Melnichenko, Yuri

2018-04-01

Experiments using boiling water on untreated (roughness 100-300 nm) metal surfaces using small-angle neutron scattering (SANS) show the appearance of structures that are 50-70 nm in size when boiling is present. The scattering signal disappears when the boiling ceases, and no change in the signal is detected at any surface temperature condition below saturation. This confirms that the signal is caused by vapor nanobubbles. Two boiling regimes are evaluated herein that differ by the degree of subcooling (3-10 °C). A polydisperse spherical model with a log-normal distribution fits the SANS data well. The size distribution indicates that a large number of nanobubbles exist on the surface during boiling, and some of them grow into large bubbles.

Plasmodial vein networks of the slime mold Physarum polycephalum form regular graphs

NASA Astrophysics Data System (ADS)

Baumgarten, Werner; Ueda, Tetsuo; Hauser, Marcus J. B.

2010-10-01

The morphology of a typical developing biological transportation network, the vein network of the plasmodium of the myxomycete Physarum polycephalum is analyzed during its free extension. The network forms a classical, regular graph, and has exclusively nodes of degree 3. This contrasts to most real-world transportation networks which show small-world or scale-free properties. The complexity of the vein network arises from the weighting of the lengths, widths, and areas of the vein segments. The lengths and areas follow exponential distributions, while the widths are distributed log-normally. These functional dependencies are robust during the entire evolution of the network, even though the exponents change with time due to the coarsening of the vein network.

Plasmodial vein networks of the slime mold Physarum polycephalum form regular graphs.

PubMed

Baumgarten, Werner; Ueda, Tetsuo; Hauser, Marcus J B

2010-10-01

The morphology of a typical developing biological transportation network, the vein network of the plasmodium of the myxomycete Physarum polycephalum is analyzed during its free extension. The network forms a classical, regular graph, and has exclusively nodes of degree 3. This contrasts to most real-world transportation networks which show small-world or scale-free properties. The complexity of the vein network arises from the weighting of the lengths, widths, and areas of the vein segments. The lengths and areas follow exponential distributions, while the widths are distributed log-normally. These functional dependencies are robust during the entire evolution of the network, even though the exponents change with time due to the coarsening of the vein network.

Population Synthesis of Radio and Y-ray Normal, Isolated Pulsars Using Markov Chain Monte Carlo

NASA Astrophysics Data System (ADS)

Billman, Caleb; Gonthier, P. L.; Harding, A. K.

2013-04-01

We present preliminary results of a population statistics study of normal pulsars (NP) from the Galactic disk using Markov Chain Monte Carlo techniques optimized according to two different methods. The first method compares the detected and simulated cumulative distributions of series of pulsar characteristics, varying the model parameters to maximize the overall agreement. The advantage of this method is that the distributions do not have to be binned. The other method varies the model parameters to maximize the log of the maximum likelihood obtained from the comparisons of four-two dimensional distributions of radio and γ-ray pulsar characteristics. The advantage of this method is that it provides a confidence region of the model parameter space. The computer code simulates neutron stars at birth using Monte Carlo procedures and evolves them to the present assuming initial spatial, kick velocity, magnetic field, and period distributions. Pulsars are spun down to the present and given radio and γ-ray emission characteristics, implementing an empirical γ-ray luminosity model. A comparison group of radio NPs detected in ten-radio surveys is used to normalize the simulation, adjusting the model radio luminosity to match a birth rate. We include the Fermi pulsars in the forthcoming second pulsar catalog. We present preliminary results comparing the simulated and detected distributions of radio and γ-ray NPs along with a confidence region in the parameter space of the assumed models. We express our gratitude for the generous support of the National Science Foundation (REU and RUI), Fermi Guest Investigator Program and the NASA Astrophysics Theory and Fundamental Program.

Butt-log grade distributions for five Appalachian hardwood species

Treesearch

John R. Myers; Gary W. Miller; Harry V., Jr. Wiant; Joseph E. Barnard; Joseph E. Barnard

1986-01-01

Tree quality is an important factor in determining the market value of hardwood timber stands, but many forest inventories do not include estimates of tree quality. Butt-log grade distributions were developed for northern red oak, black oak, white oak, chestnut oak, and yellow-poplar using USDA Forest Service log grades on more than 4,700 trees in West Virginia. Butt-...

The modelling of carbon-based supercapacitors: Distributions of time constants and Pascal Equivalent Circuits

NASA Astrophysics Data System (ADS)

Fletcher, Stephen; Kirkpatrick, Iain; Dring, Roderick; Puttock, Robert; Thring, Rob; Howroyd, Simon

2017-03-01

Supercapacitors are an emerging technology with applications in pulse power, motive power, and energy storage. However, their carbon electrodes show a variety of non-ideal behaviours that have so far eluded explanation. These include Voltage Decay after charging, Voltage Rebound after discharging, and Dispersed Kinetics at long times. In the present work, we establish that a vertical ladder network of RC components can reproduce all these puzzling phenomena. Both software and hardware realizations of the network are described. In general, porous carbon electrodes contain random distributions of resistance R and capacitance C, with a wider spread of log R values than log C values. To understand what this implies, a simplified model is developed in which log R is treated as a Gaussian random variable while log C is treated as a constant. From this model, a new family of equivalent circuits is developed in which the continuous distribution of log R values is replaced by a discrete set of log R values drawn from a geometric series. We call these Pascal Equivalent Circuits. Their behaviour is shown to resemble closely that of real supercapacitors. The results confirm that distributions of RC time constants dominate the behaviour of real supercapacitors.

Phylogenetic analyses suggest that diversification and body size evolution are independent in insects.

PubMed

Rainford, James L; Hofreiter, Michael; Mayhew, Peter J

2016-01-08

Skewed body size distributions and the high relative richness of small-bodied taxa are a fundamental property of a wide range of animal clades. The evolutionary processes responsible for generating these distributions are well described in vertebrate model systems but have yet to be explored in detail for other major terrestrial clades. In this study, we explore the macro-evolutionary patterns of body size variation across families of Hexapoda (insects and their close relatives), using recent advances in phylogenetic understanding, with an aim to investigate the link between size and diversity within this ancient and highly diverse lineage. The maximum, minimum and mean-log body lengths of hexapod families are all approximately log-normally distributed, consistent with previous studies at lower taxonomic levels, and contrasting with skewed distributions typical of vertebrate groups. After taking phylogeny and within-tip variation into account, we find no evidence for a negative relationship between diversification rate and body size, suggesting decoupling of the forces controlling these two traits. Likelihood-based modeling of the log-mean body size identifies distinct processes operating within Holometabola and Diptera compared with other hexapod groups, consistent with accelerating rates of size evolution within these clades, while as a whole, hexapod body size evolution is found to be dominated by neutral processes including significant phylogenetic conservatism. Based on our findings we suggest that the use of models derived from well-studied but atypical clades, such as vertebrates may lead to misleading conclusions when applied to other major terrestrial lineages. Our results indicate that within hexapods, and within the limits of current systematic and phylogenetic knowledge, insect diversification is generally unfettered by size-biased macro-evolutionary processes, and that these processes over large timescales tend to converge on apparently neutral evolutionary processes. We also identify limitations on available data within the clade and modeling approaches for the resolution of trees of higher taxa, the resolution of which may collectively enhance our understanding of this key component of terrestrial ecosystems.

Inverse Gaussian gamma distribution model for turbulence-induced fading in free-space optical communication.

PubMed

Cheng, Mingjian; Guo, Ya; Li, Jiangting; Zheng, Xiaotong; Guo, Lixin

2018-04-20

We introduce an alternative distribution to the gamma-gamma (GG) distribution, called inverse Gaussian gamma (IGG) distribution, which can efficiently describe moderate-to-strong irradiance fluctuations. The proposed stochastic model is based on a modulation process between small- and large-scale irradiance fluctuations, which are modeled by gamma and inverse Gaussian distributions, respectively. The model parameters of the IGG distribution are directly related to atmospheric parameters. The accuracy of the fit among the IGG, log-normal, and GG distributions with the experimental probability density functions in moderate-to-strong turbulence are compared, and results indicate that the newly proposed IGG model provides an excellent fit to the experimental data. As the receiving diameter is comparable with the atmospheric coherence radius, the proposed IGG model can reproduce the shape of the experimental data, whereas the GG and LN models fail to match the experimental data. The fundamental channel statistics of a free-space optical communication system are also investigated in an IGG-distributed turbulent atmosphere, and a closed-form expression for the outage probability of the system is derived with Meijer's G-function.

SU-E-T-142: Automatic Linac Log File: Analysis and Reporting

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

Gainey, M; Rothe, T

Purpose: End to end QA for IMRT/VMAT is time consuming. Automated linac log file analysis and recalculation of daily recorded fluence, and hence dose, distribution bring this closer. Methods: Matlab (R2014b, Mathworks) software was written to read in and analyse IMRT/VMAT trajectory log files (TrueBeam 1.5, Varian Medical Systems) overnight, and are archived on a backed-up network drive (figure). A summary report (PDF) is sent by email to the duty linac physicist. A structured summary report (PDF) for each patient is automatically updated for embedding into the R&V system (Mosaiq 2.5, Elekta AG). The report contains cross-referenced hyperlinks to easemore » navigation between treatment fractions. Gamma analysis can be performed on planned (DICOM RTPlan) and treated (trajectory log) fluence distributions. Trajectory log files can be converted into RTPlan files for dose distribution calculation (Eclipse, AAA10.0.28, VMS). Results: All leaf positions are within +/−0.10mm: 57% within +/−0.01mm; 89% within 0.05mm. Mean leaf position deviation is 0.02mm. Gantry angle variations lie in the range −0.1 to 0.3 degrees, mean 0.04 degrees. Fluence verification shows excellent agreement between planned and treated fluence. Agreement between planned and treated dose distribution, the derived from log files, is very good. Conclusion: Automated log file analysis is a valuable tool for the busy physicist, enabling potential treated fluence distribution errors to be quickly identified. In the near future we will correlate trajectory log analysis with routine IMRT/VMAT QA analysis. This has the potential to reduce, but not eliminate, the QA workload.« less

Empirical analysis on the connection between power-law distributions and allometries for urban indicators

NASA Astrophysics Data System (ADS)

Alves, L. G. A.; Ribeiro, H. V.; Lenzi, E. K.; Mendes, R. S.

2014-09-01

We report on the existing connection between power-law distributions and allometries. As it was first reported in Gomez-Lievano et al. (2012) for the relationship between homicides and population, when these urban indicators present asymptotic power-law distributions, they can also display specific allometries among themselves. Here, we present an extensive characterization of this connection when considering all possible pairs of relationships from twelve urban indicators of Brazilian cities (such as child labor, illiteracy, income, sanitation and unemployment). Our analysis reveals that all our urban indicators are asymptotically distributed as power laws and that the proposed connection also holds for our data when the allometric relationship displays enough correlations. We have also found that not all allometric relationships are independent and that they can be understood as a consequence of the allometric relationship between the urban indicator and the population size. We further show that the residuals fluctuations surrounding the allometries are characterized by an almost constant variance and log-normal distributions.

At what scale should microarray data be analyzed?

PubMed

Huang, Shuguang; Yeo, Adeline A; Gelbert, Lawrence; Lin, Xi; Nisenbaum, Laura; Bemis, Kerry G

2004-01-01

The hybridization intensities derived from microarray experiments, for example Affymetrix's MAS5 signals, are very often transformed in one way or another before statistical models are fitted. The motivation for performing transformation is usually to satisfy the model assumptions such as normality and homogeneity in variance. Generally speaking, two types of strategies are often applied to microarray data depending on the analysis need: correlation analysis where all the gene intensities on the array are considered simultaneously, and gene-by-gene ANOVA where each gene is analyzed individually. We investigate the distributional properties of the Affymetrix GeneChip signal data under the two scenarios, focusing on the impact of analyzing the data at an inappropriate scale. The Box-Cox type of transformation is first investigated for the strategy of pooling genes. The commonly used log-transformation is particularly applied for comparison purposes. For the scenario where analysis is on a gene-by-gene basis, the model assumptions such as normality are explored. The impact of using a wrong scale is illustrated by log-transformation and quartic-root transformation. When all the genes on the array are considered together, the dependent relationship between the expression and its variation level can be satisfactorily removed by Box-Cox transformation. When genes are analyzed individually, the distributional properties of the intensities are shown to be gene dependent. Derivation and simulation show that some loss of power is incurred when a wrong scale is used, but due to the robustness of the t-test, the loss is acceptable when the fold-change is not very large.

Detecting trends in raptor counts: power and type I error rates of various statistical tests

USGS Publications Warehouse

Hatfield, J.S.; Gould, W.R.; Hoover, B.A.; Fuller, M.R.; Lindquist, E.L.

1996-01-01

We conducted simulations that estimated power and type I error rates of statistical tests for detecting trends in raptor population count data collected from a single monitoring site. Results of the simulations were used to help analyze count data of bald eagles (Haliaeetus leucocephalus) from 7 national forests in Michigan, Minnesota, and Wisconsin during 1980-1989. Seven statistical tests were evaluated, including simple linear regression on the log scale and linear regression with a permutation test. Using 1,000 replications each, we simulated n = 10 and n = 50 years of count data and trends ranging from -5 to 5% change/year. We evaluated the tests at 3 critical levels (alpha = 0.01, 0.05, and 0.10) for both upper- and lower-tailed tests. Exponential count data were simulated by adding sampling error with a coefficient of variation of 40% from either a log-normal or autocorrelated log-normal distribution. Not surprisingly, tests performed with 50 years of data were much more powerful than tests with 10 years of data. Positive autocorrelation inflated alpha-levels upward from their nominal levels, making the tests less conservative and more likely to reject the null hypothesis of no trend. Of the tests studied, Cox and Stuart's test and Pollard's test clearly had lower power than the others. Surprisingly, the linear regression t-test, Collins' linear regression permutation test, and the nonparametric Lehmann's and Mann's tests all had similar power in our simulations. Analyses of the count data suggested that bald eagles had increasing trends on at least 2 of the 7 national forests during 1980-1989.

Effect of particle size distribution on permeability in the randomly packed porous media

NASA Astrophysics Data System (ADS)

Markicevic, Bojan

2017-11-01

An answer of how porous medium heterogeneity influences the medium permeability is still inconclusive, where both increase and decrease in the permeability value are reported. A numerical procedure is used to generate a randomly packed porous material consisting of spherical particles. Six different particle size distributions are used including mono-, bi- and three-disperse particles, as well as uniform, normal and log-normal particle size distribution with the maximum to minimum particle size ratio ranging from three to eight for different distributions. In all six cases, the average particle size is kept the same. For all media generated, the stochastic homogeneity is checked from distribution of three coordinates of particle centers, where uniform distribution of x-, y- and z- positions is found. The medium surface area remains essentially constant except for bi-modal distribution in which medium area decreases, while no changes in the porosity are observed (around 0.36). The fluid flow is solved in such domain, and after checking for the pressure axial linearity, the permeability is calculated from the Darcy law. The permeability comparison reveals that the permeability of the mono-disperse medium is smallest, and the permeability of all poly-disperse samples is less than ten percent higher. For bi-modal particles, the permeability is for a quarter higher compared to the other media which can be explained by volumetric contribution of larger particles and larger passages for fluid flow to take place.

Spatiotemporal stick-slip phenomena in a coupled continuum-granular system

NASA Astrophysics Data System (ADS)

Ecke, Robert

In sheared granular media, stick-slip behavior is ubiquitous, especially at very small shear rates and weak drive coupling. The resulting slips are characteristic of natural phenomena such as earthquakes and well as being a delicate probe of the collective dynamics of the granular system. In that spirit, we developed a laboratory experiment consisting of sheared elastic plates separated by a narrow gap filled with quasi-two-dimensional granular material (bi-dispersed nylon rods) . We directly determine the spatial and temporal distributions of strain displacements of the elastic continuum over 200 spatial points located adjacent to the gap. Slip events can be divided into large system-spanning events and spatially distributed smaller events. The small events have a probability distribution of event moment consistent with an M - 3 / 2 power law scaling and a Poisson distributed recurrence time distribution. Large events have a broad, log-normal moment distribution and a mean repetition time. As the applied normal force increases, there are fractionally more (less) large (small) events, and the large-event moment distribution broadens. The magnitude of the slip motion of the plates is well correlated with the root-mean-square displacements of the granular matter. Our results are consistent with mean field descriptions of statistical models of earthquakes and avalanches. We further explore the high-speed dynamics of system events and also discuss the effective granular friction of the sheared layer. We find that large events result from stored elastic energy in the plates in this coupled granular-continuum system.

Community Structure of Tintinnid Ciliates of the Microzooplankton in the South West Pacific Ocean: Comparison of a High Primary Productivity with a Typical Oligotrophic Site.

PubMed

Dolan, John R; Gimenez, Audrey; Cornet-Barthaux, Veronique; de Verneil, Alain

2016-11-01

Transient 'hot spots' of phytoplankton productivity occur in the generally oligotrophic Southern Pacific Ocean and we hypothesized that the population structure of tintinnid ciliates, planktonic grazers, would differ from that of a typical oligotrophic sites. Samples were collected over a 1-wk period at each of two sites between Fiji and Tahiti: one of elevated chlorophyll a concentrations and primary productivity with an abundance of N-fixing cyanobacteria Trichodesmium, and a distant oligotrophic site. Tintinnid abundance differed between the sites by a factor of 2. A single species (Favella sp.), absent from the oligotrophic site, highly dominated the 'hot spot' site. However, total species richness was identical (71 spp.) as well as short-term temporal variability (2-4 d). At both sites, species abundance distributions most closely fit a log-series or log-normal distribution and the abundance distributions of ecological types, forms of distinct lorica oral diameter, were the typical geometric. Morphological diversity was only slightly lower at the high productivity site. We found that communities of these plankton grazers in 'hot spots' of phytoplankton productivity in oligotrophic systems, although harboring different species, differ little from surrounding oligotrophic areas in community structure. © 2016 The Author(s) Journal of Eukaryotic Microbiology © 2016 International Society of Protistologists.

Distribution and Bioconcentration of Polycyclic Aromatic Hydrocarbons in Surface Water and Fishes

PubMed Central

Li, Haiyan; Ran, Yong

2012-01-01

To examine spatial distribution and bioconcentration of PAHs, water and fish samples were collected from Pearl River Delta in summer and spring, respectively. Particulate organic carbon, dissolved organic carbon, biodegradable DOC (BDOC), and chlorophyll a were measured. PAHs were dominated by 2- and 3-ring compounds in the water and SPM samples. Aqueous and solid-phase PAHs, respectively, showed significant correlations with total organic matter (TOC) in SPM or dissolved organic matter (DOC) in the water. The in-situ partitioning coefficients (logK oc, mL/g) for the samples were observed to be related to logK ow, implying that the hydrophobicity of PAHs is a critical factor in their distribution. It was also observed that BCF increased with the increasing K ow in the viscera of tilapia (logBCF = 0.507logK ow − 1.368, r = 0.883). However, most of the observed log BCF values in other different fish tissues at first increased with the increasing of log K ow, then reached a maximum value when logK ow is between 5 and 7, and then decreased when logK ow is higher than 7, indicating that the value of BCF may vary due to the diversity of fish species. PMID:23365526

Permutational distribution of the log-rank statistic under random censorship with applications to carcinogenicity assays.

PubMed

Heimann, G; Neuhaus, G

1998-03-01

In the random censorship model, the log-rank test is often used for comparing a control group with different dose groups. If the number of tumors is small, so-called exact methods are often applied for computing critical values from a permutational distribution. Two of these exact methods are discussed and shown to be incorrect. The correct permutational distribution is derived and studied with respect to its behavior under unequal censoring in the light of recent results proving that the permutational version and the unconditional version of the log-rank test are asymptotically equivalent even under unequal censoring. The log-rank test is studied by simulations of a realistic scenario from a bioassay with small numbers of tumors.

Is a data set distributed as a power law? A test, with application to gamma-ray burst brightnesses

NASA Technical Reports Server (NTRS)

Wijers, Ralph A. M. J.; Lubin, Lori M.

1994-01-01

We present a method to determine whether an observed sample of data is drawn from a parent distribution that is pure power law. The method starts from a class of statistics which have zero expectation value under the null hypothesis, H(sub 0), that the distribution is a pure power law: F(x) varies as x(exp -alpha). We study one simple member of the class, named the `bending statistic' B, in detail. It is most effective for detection a type of deviation from a power law where the power-law slope varies slowly and monotonically as a function of x. Our estimator of B has a distribution under H(sub 0) that depends only on the size of the sample, not on the parameters of the parent population, and is approximated well by a normal distribution even for modest sample sizes. The bending statistic can therefore be used to test a set of numbers is drawn from any power-law parent population. Since many measurable quantities in astrophysics have distriibutions that are approximately power laws, and since deviations from the ideal power law often provide interesting information about the object of study (e.g., a `bend' or `break' in a luminosity function, a line in an X- or gamma-ray spectrum), we believe that a test of this type will be useful in many different contexts. In the present paper, we apply our test to various subsamples of gamma-ray burst brightness from the first-year Burst and Transient Source Experiment (BATSE) catalog and show that we can only marginally detect the expected steepening of the log (N (greater than C(sub max))) - log (C(sub max)) distribution.

Cell-free fetal DNA (SRY locus) concentration in maternal plasma is directly correlated to the time elapsed from the onset of preeclampsia to the collection of blood.

PubMed

Farina, Antonio; Sekizawa, Akihiko; Rizzo, Nicola; Concu, Manuela; Banzola, Irina; Carinci, Paolo; Simonazzi, Giuliana; Okai, Takashi

2004-04-01

To determine (1) if fetal DNA (fDNA) in the maternal circulation in women affected by preeclampsia correlates with the time elapsed from the onset of symptoms to the time of blood collection, and (2) if the inclusion of this variable improves the discrimination between affected and unaffected patients by using fDNA distributions. Plasma were collected from 34 women at 33.7 +/- 3.9 weeks' gestation, affected by preeclampsia, and bearing a single male fetus. fDNA was extracted from 1.5-mL plasma samples, and the SRY and beta-globin gene were analyzed by real-time quantitative PCR. MoMs (multiple of the control median) were calculated by using a log equation of 102 normal cases. Log MoMs were then plotted against the time elapsed from onset of symptoms to blood collection (expressed in days) by means of a log-linear regression. Adjusted MoMs were then calculated. ROC curves were used to test the discrimination obtained by using adjusted MoMs. The median MoMs of controls and preeclamptic patients were 1.00 +/- 1.53 and 2.62 +/- 2.70 respectively. By plotting log MoM fDNA against the time elapsed from onset of symptoms to blood collection, we found a significant positive correlation, (p-value < 0.001, R2 = 0.55, F = 38.97, from 1 to 50 days). The adjusted median fDNA MoM was 2.66 +/- 2.50. Areas under the curves, as estimated by ROC curves, were 76.7 for unadjusted and 85.5 for adjusted MoMs respectively (p-value = 0.02). The effect of a further covariate showed that (1) fDNA passage from trophoblasts to maternal circulation for unit of time is proportional to the duration of the damage and that (2) increased discrimination can be obtained in comparison to normal subjects. Copyright 2004 John Wiley & Sons, Ltd.

Carrier Mediated Distribution System (CAMDIS): a new approach for the measurement of octanol/water distribution coefficients.

PubMed

Wagner, Bjoern; Fischer, Holger; Kansy, Manfred; Seelig, Anna; Assmus, Frauke

2015-02-20

Here we present a miniaturized assay, referred to as Carrier-Mediated Distribution System (CAMDIS) for fast and reliable measurement of octanol/water distribution coefficients, log D(oct). By introducing a filter support for octanol, phase separation from water is facilitated and the tendency of emulsion formation (emulsification) at the interface is reduced. A guideline for the best practice of CAMDIS is given, describing a strategy to manage drug adsorption at the filter-supported octanol/buffer interface. We validated the assay on a set of 52 structurally diverse drugs with known shake flask log D(oct) values. Excellent agreement with literature data (r(2) = 0.996, standard error of estimate, SEE = 0.111), high reproducibility (standard deviation, SD < 0.1 log D(oct) units), minimal sample consumption (10 μL of 100 μM DMSO stock solution) and a broad analytical range (log D(oct) range = -0.5 to 4.2) make CAMDIS a valuable tool for the high-throughput assessment of log D(oc)t. Copyright © 2014 Elsevier B.V. All rights reserved.

The integration of elastic wave properties and machine learning for the distribution of petrophysical properties in reservoir modeling

NASA Astrophysics Data System (ADS)

Ratnam, T. C.; Ghosh, D. P.; Negash, B. M.

2018-05-01

Conventional reservoir modeling employs variograms to predict the spatial distribution of petrophysical properties. This study aims to improve property distribution by incorporating elastic wave properties. In this study, elastic wave properties obtained from seismic inversion are used as input for an artificial neural network to predict neutron porosity in between well locations. The method employed in this study is supervised learning based on available well logs. This method converts every seismic trace into a pseudo-well log, hence reducing the uncertainty between well locations. By incorporating the seismic response, the reliance on geostatistical methods such as variograms for the distribution of petrophysical properties is reduced drastically. The results of the artificial neural network show good correlation with the neutron porosity log which gives confidence for spatial prediction in areas where well logs are not available.

A flow-through aqueous standard generation system for thin film microextraction investigations of UV filters and biocides partitioning to different environmental compartments.

PubMed

Ahmadi, Fardin; Sparham, Chris; Pawliszyn, Janusz

2017-11-01

In this paper problems associated with preparation of aqueous standard of highly hydrophobic compounds such as partial precipitation, being lost on the surfaces, low solubility in water and limited sample volume for accurate determination of their distribution coefficients are addressed. The following work presents two approaches that utilize blade thin film microextraction (TFME) to investigate partitioning of UV filters and biocides to humic acid (dissolved organic carbon) and sediment. A steady-state concentration of target analytes in water was generated using a flow-through aqueous standard generation (ASG) system. Dialysis membranes, a polytetrafluoroethylene permeation tube, and a frit porous (0.5 μm) coated by epoxy glue were basic elements used for preparation of the ASG system. In the currently presented study, negligible depletion TFME using hydrophilic-lipophilic balance (HLB) and octadecyl silica-based (C18) sorbents was employed towards the attainment of free concentration values of target analytes in the studied matrices. Thin film geometry provided a large volume of extraction phase, which improved the sensitivity of the method towards highly matrix-bound analytes. Extractions were performed in the equilibrium regime so as to prevent matrix effects and with aims to reach maximum method sensitivity for all analytes under study. Partitioning of analytes on dissolved organic carbon (DOC) was investigated in ASG to facilitate large sample volume conditions. Binding percentages and DOC distribution coefficients (Log K DOC ) ranged from 20 to 98% and 3.71-6.72, respectively. Furthermore, sediment-water partition coefficients (K d ), organic-carbon normalized partition coefficients (Log K OC ), and DOC distribution coefficients (Log K DOC ) were investigated in slurry sediment, and ranged from 33 to 2860, 3.31-5.24 and 4.52-5.75 Lkg -1 , respectively. The obtained results demonstrated that investigations utilizing ASG and TFME can yield reliable binding information for compounds with high log K OW values. This information is useful for study of fate, transport, and ecotoxicological effects of UV filters and biocides in aquatic environment. Copyright © 2017 Elsevier Ltd. All rights reserved.

Size distribution of radon daughter particles in uranium mine atmospheres.

PubMed

George, A C; Hinchliffe, L; Sladowski, R

1975-06-01

The size distribution of radon daughters was measured in several uranium mines using four compact diffusion batteries and a round jet cascade impactor. Simultaneously, measurements were made of uncombined fractions of radon daughters, radon concentration, working level and particle concentration. The size distributions found for radon daughters were log normal. The activity median diameters ranged from 0.09 mum to 0.3 mum with a mean value of 0.17 mum. Geometric standard deviations were in the range from 1.3 to 4 with a mean value of 2.7. Uncombined fractions expressed in accordance with the ICRP definition ranged from 0.004 to 0.16 with a mean value of 0.04. The radon daughter sizes in these mines are greater than the sizes assumed by various authors in calculating respiratory tract dose. The disparity may reflect the widening use of diesel-powered equipment in large uranium mines.

Resistance distribution in the hopping percolation model.

PubMed

Strelniker, Yakov M; Havlin, Shlomo; Berkovits, Richard; Frydman, Aviad

2005-07-01

We study the distribution function P (rho) of the effective resistance rho in two- and three-dimensional random resistor networks of linear size L in the hopping percolation model. In this model each bond has a conductivity taken from an exponential form sigma proportional to exp (-kappar) , where kappa is a measure of disorder and r is a random number, 0< or = r < or =1 . We find that in both the usual strong-disorder regime L/ kappa(nu) >1 (not sensitive to removal of any single bond) and the extreme-disorder regime L/ kappa(nu) <1 (very sensitive to such a removal) the distribution depends only on L/kappa(nu) and can be well approximated by a log-normal function with dispersion b kappa(nu) /L , where b is a coefficient which depends on the type of lattice, and nu is the correlation critical exponent.

Distributions of tunnel splittings in quantum tunneling of magnetization in the single-molecule magnet, manganese12-acetate

NASA Astrophysics Data System (ADS)

Mertes, Kevin Mathias

I present the results of an experimental investigation of quantum tunneling of magnetization in the single molecule magnet, Mn12-acetate, for magnetic fields applied along the easy c-axis of the crystal. Magnetization measurements for temperatures below 2 Kelvin reveal new properties of the nature of tunneling in Mn12-acetate: an abrupt cross-over from thermally-assisted tunneling to pure ground state tunneling, strong suppression of ground state tunneling for temperatures corresponding to the thermally activated regime and the unexpected dependence of the tunnel splitting determined from the Landau-Zener-Stueckelberg formalism on the magnetic field sweep rate. It is shown that the measured data is inconsistent with a system of identical molecules. The data is shown to be consistent with the presence of a broad log-normal distribution of second order transverse anisotropy which drives the tunneling process. A general method of determining the distribution is developed.

Casein micelles: size distribution in milks from individual cows.

PubMed

de Kruif, C G Kees; Huppertz, Thom

2012-05-09

The size distribution and protein composition of casein micelles in the milk of Holstein-Friesian cows was determined as a function of stage and number of lactations. Protein composition did not vary significantly between the milks of different cows or as a function of lactation stage. Differences in the size and polydispersity of the casein micelles were observed between the milks of different cows, but not as a function of stage of milking or stage of lactation and not even over successive lactations periods. Modal radii varied from 55 to 70 nm, whereas hydrodynamic radii at a scattering angle of 73° (Q² = 350 μm⁻²) varied from 77 to 115 nm and polydispersity varied from 0.27 to 0.41, in a log-normal distribution. Casein micelle size in the milks of individual cows was not correlated with age, milk production, or lactation stage of the cows or fat or protein content of the milk.

Combining uncertainty factors in deriving human exposure levels of noncarcinogenic toxicants.

PubMed

Kodell, R L; Gaylor, D W

1999-01-01

Acceptable levels of human exposure to noncarcinogenic toxicants in environmental and occupational settings generally are derived by reducing experimental no-observed-adverse-effect levels (NOAELs) or benchmark doses (BDs) by a product of uncertainty factors (Barnes and Dourson, Ref. 1). These factors are presumed to ensure safety by accounting for uncertainty in dose extrapolation, uncertainty in duration extrapolation, differential sensitivity between humans and animals, and differential sensitivity among humans. The common default value for each uncertainty factor is 10. This paper shows how estimates of means and standard deviations of the approximately log-normal distributions of individual uncertainty factors can be used to estimate percentiles of the distribution of the product of uncertainty factors. An appropriately selected upper percentile, for example, 95th or 99th, of the distribution of the product can be used as a combined uncertainty factor to replace the conventional product of default factors.

Rockfall travel distances theoretical distributions

NASA Astrophysics Data System (ADS)

Jaboyedoff, Michel; Derron, Marc-Henri; Pedrazzini, Andrea

2017-04-01

The probability of propagation of rockfalls is a key part of hazard assessment, because it permits to extrapolate the probability of propagation of rockfall either based on partial data or simply theoretically. The propagation can be assumed frictional which permits to describe on average the propagation by a line of kinetic energy which corresponds to the loss of energy along the path. But loss of energy can also be assumed as a multiplicative process or a purely random process. The distributions of the rockfall block stop points can be deduced from such simple models, they lead to Gaussian, Inverse-Gaussian, Log-normal or exponential negative distributions. The theoretical background is presented, and the comparisons of some of these models with existing data indicate that these assumptions are relevant. The results are either based on theoretical considerations or by fitting results. They are potentially very useful for rockfall hazard zoning and risk assessment. This approach will need further investigations.

Retrieval of phytoplankton cell size from chlorophyll a specific absorption and scattering spectra of phytoplankton.

PubMed

Zhou, Wen; Wang, Guifen; Li, Cai; Xu, Zhantang; Cao, Wenxi; Shen, Fang

2017-10-20

Phytoplankton cell size is an important property that affects diverse ecological and biogeochemical processes, and analysis of the absorption and scattering spectra of phytoplankton can provide important information about phytoplankton size. In this study, an inversion method for extracting quantitative phytoplankton cell size data from these spectra was developed. This inversion method requires two inputs: chlorophyll a specific absorption and scattering spectra of phytoplankton. The average equivalent-volume spherical diameter (ESD v ) was calculated as the single size approximation for the log-normal particle size distribution (PSD) of the algal suspension. The performance of this method for retrieving cell size was assessed using the datasets from cultures of 12 phytoplankton species. The estimations of a(λ) and b(λ) for the phytoplankton population using ESD v had mean error values of 5.8%-6.9% and 7.0%-10.6%, respectively, compared to the a(λ) and b(λ) for the phytoplankton populations using the log-normal PSD. The estimated values of C i ESD v were in good agreement with the measurements, with r 2 =0.88 and relative root mean square error (NRMSE)=25.3%, and relatively good performances were also found for the retrieval of ESD v with r 2 =0.78 and NRMSE=23.9%.

Infuence of Averaging Method on the Evaluation of a Coastal Ocean Color Event on the U.S. Northeast Coast

NASA Technical Reports Server (NTRS)

Acker, James G.; Uz, Stephanie Schollaert; Shen, Suhung; Leptoukh, Gregory G.

2010-01-01

Application of appropriate spatial averaging techniques is crucial to correct evaluation of ocean color radiometric data, due to the common log-normal or mixed log-normal distribution of these data. Averaging method is particularly crucial for data acquired in coastal regions. The effect of averaging method was markedly demonstrated for a precipitation-driven event on the U.S. Northeast coast in October-November 2005, which resulted in export of high concentrations of riverine colored dissolved organic matter (CDOM) to New York and New Jersey coastal waters over a period of several days. Use of the arithmetic mean averaging method created an inaccurate representation of the magnitude of this event in SeaWiFS global mapped chl a data, causing it to be visualized as a very large chl a anomaly. The apparent chl a anomaly was enhanced by the known incomplete discrimination of CDOM and phytoplankton chlorophyll in SeaWiFS data; other data sources enable an improved characterization. Analysis using the geometric mean averaging method did not indicate this event to be statistically anomalous. Our results predicate the necessity of providing the geometric mean averaging method for ocean color radiometric data in the Goddard Earth Sciences DISC Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni).

Reprographics Career Ladder AFSC 703X0.

DTIC Science & Technology

1988-02-01

paper by hand adjust stitchers pack printed materials manually wax drill bit ends VI. PRODUCTION CONTROL PERSONNEL CLUSTER (STG033, N=38). Comprising...work requests notify customer of completed work verify duplicating requests maintain job logs manually 16 Two jobs were identified within this...E146 MAINTAIN LOGS OF JOBS PROCESSED 47 E138 DISTRIBUTE COMPLETED PRODUCTS 47 N441 MAINTAIN JOB LOGS MANUALLY 43 E169 PROCESS INCOMING DISTRIBUTION 6.l

Timing Solution and Single-pulse Properties for Eight Rotating Radio Transients

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

Cui, B.-Y.; McLaughlin, M. A.; Boyles, J.

Rotating radio transients (RRATs), loosely defined as objects that are discovered through only their single pulses, are sporadic pulsars that have a wide range of emission properties. For many of them, we must measure their periods and determine timing solutions relying on the timing of their individual pulses, while some of the less sporadic RRATs can be timed by using folding techniques as we do for other pulsars. Here, based on Parkes and Green Bank Telescope (GBT) observations, we introduce our results on eight RRATs including their timing-derived rotation parameters, positions, and dispersion measures (DMs), along with a comparison ofmore » the spin-down properties of RRATs and normal pulsars. Using data for 24 RRATs, we find that their period derivatives are generally larger than those of normal pulsars, independent of any intrinsic correlation with period, indicating that RRATs’ highly sporadic emission may be associated with intrinsically larger magnetic fields. We carry out Lomb–Scargle tests to search for periodicities in RRATs’ pulse detection times with long timescales. Periodicities are detected for all targets, with significant candidates of roughly 3.4 hr for PSR J1623−0841 and 0.7 hr for PSR J1839−0141. We also analyze their single-pulse amplitude distributions, finding that log-normal distributions provide the best fits, as is the case for most pulsars. However, several RRATs exhibit power-law tails, as seen for pulsars emitting giant pulses. This, along with consideration of the selection effects against the detection of weak pulses, imply that RRAT pulses generally represent the tail of a normal intensity distribution.« less

Finite-size effects in transcript sequencing count distribution: its power-law correction necessarily precedes downstream normalization and comparative analysis.

PubMed

Wong, Wing-Cheong; Ng, Hong-Kiat; Tantoso, Erwin; Soong, Richie; Eisenhaber, Frank

2018-02-12

Though earlier works on modelling transcript abundance from vertebrates to lower eukaroytes have specifically singled out the Zip's law, the observed distributions often deviate from a single power-law slope. In hindsight, while power-laws of critical phenomena are derived asymptotically under the conditions of infinite observations, real world observations are finite where the finite-size effects will set in to force a power-law distribution into an exponential decay and consequently, manifests as a curvature (i.e., varying exponent values) in a log-log plot. If transcript abundance is truly power-law distributed, the varying exponent signifies changing mathematical moments (e.g., mean, variance) and creates heteroskedasticity which compromises statistical rigor in analysis. The impact of this deviation from the asymptotic power-law on sequencing count data has never truly been examined and quantified. The anecdotal description of transcript abundance being almost Zipf's law-like distributed can be conceptualized as the imperfect mathematical rendition of the Pareto power-law distribution when subjected to the finite-size effects in the real world; This is regardless of the advancement in sequencing technology since sampling is finite in practice. Our conceptualization agrees well with our empirical analysis of two modern day NGS (Next-generation sequencing) datasets: an in-house generated dilution miRNA study of two gastric cancer cell lines (NUGC3 and AGS) and a publicly available spike-in miRNA data; Firstly, the finite-size effects causes the deviations of sequencing count data from Zipf's law and issues of reproducibility in sequencing experiments. Secondly, it manifests as heteroskedasticity among experimental replicates to bring about statistical woes. Surprisingly, a straightforward power-law correction that restores the distribution distortion to a single exponent value can dramatically reduce data heteroskedasticity to invoke an instant increase in signal-to-noise ratio by 50% and the statistical/detection sensitivity by as high as 30% regardless of the downstream mapping and normalization methods. Most importantly, the power-law correction improves concordance in significant calls among different normalization methods of a data series averagely by 22%. When presented with a higher sequence depth (4 times difference), the improvement in concordance is asymmetrical (32% for the higher sequencing depth instance versus 13% for the lower instance) and demonstrates that the simple power-law correction can increase significant detection with higher sequencing depths. Finally, the correction dramatically enhances the statistical conclusions and eludes the metastasis potential of the NUGC3 cell line against AGS of our dilution analysis. The finite-size effects due to undersampling generally plagues transcript count data with reproducibility issues but can be minimized through a simple power-law correction of the count distribution. This distribution correction has direct implication on the biological interpretation of the study and the rigor of the scientific findings. This article was reviewed by Oliviero Carugo, Thomas Dandekar and Sandor Pongor.

A modified weighted function method for parameter estimation of Pearson type three distribution

NASA Astrophysics Data System (ADS)

Liang, Zhongmin; Hu, Yiming; Li, Binquan; Yu, Zhongbo

2014-04-01

In this paper, an unconventional method called Modified Weighted Function (MWF) is presented for the conventional moment estimation of a probability distribution function. The aim of MWF is to estimate the coefficient of variation (CV) and coefficient of skewness (CS) from the original higher moment computations to the first-order moment calculations. The estimators for CV and CS of Pearson type three distribution function (PE3) were derived by weighting the moments of the distribution with two weight functions, which were constructed by combining two negative exponential-type functions. The selection of these weight functions was based on two considerations: (1) to relate weight functions to sample size in order to reflect the relationship between the quantity of sample information and the role of weight function and (2) to allocate more weights to data close to medium-tail positions in a sample series ranked in an ascending order. A Monte-Carlo experiment was conducted to simulate a large number of samples upon which statistical properties of MWF were investigated. For the PE3 parent distribution, results of MWF were compared to those of the original Weighted Function (WF) and Linear Moments (L-M). The results indicate that MWF was superior to WF and slightly better than L-M, in terms of statistical unbiasness and effectiveness. In addition, the robustness of MWF, WF, and L-M were compared by designing the Monte-Carlo experiment that samples are obtained from Log-Pearson type three distribution (LPE3), three parameter Log-Normal distribution (LN3), and Generalized Extreme Value distribution (GEV), respectively, but all used as samples from the PE3 distribution. The results show that in terms of statistical unbiasness, no one method possesses the absolutely overwhelming advantage among MWF, WF, and L-M, while in terms of statistical effectiveness, the MWF is superior to WF and L-M.

Distribution of Animal Drugs between Skim Milk and Milk Fat Fractions in Spiked Whole Milk: Understanding the Potential Impact on Commercial Milk Products.

PubMed

Hakk, Heldur; Shappell, Nancy W; Lupton, Sara J; Shelver, Weilin L; Fanaselle, Wendy; Oryang, David; Yeung, Chi Yuen; Hoelzer, Karin; Ma, Yinqing; Gaalswyk, Dennis; Pouillot, Régis; Van Doren, Jane M

2016-01-13

Seven animal drugs [penicillin G (PENG), sulfadimethoxine (SDMX), oxytetracycline (OTET), erythromycin (ERY), ketoprofen (KETO), thiabendazole (THIA), and ivermectin (IVR)] were used to evaluate the drug distribution between milk fat and skim milk fractions of cow milk. More than 90% of the radioactivity was distributed into the skim milk fraction for ERY, KETO, OTET, PENG, and SDMX, approximately 80% for THIA, and 13% for IVR. The distribution of drug between milk fat and skim milk fractions was significantly correlated to the drug's lipophilicity (partition coefficient, log P, or distribution coefficient, log D, which includes ionization). Data were fit with linear mixed effects models; the best fit was obtained within this data set with log D versus observed drug distribution ratios. These candidate empirical models serve for assisting to predict the distribution and concentration of these drugs in a variety of milk and milk products.

Atomic force microscope observation of branching in single transcript molecules derived from human cardiac muscle

NASA Astrophysics Data System (ADS)

Reed, Jason; Hsueh, Carlin; Mishra, Bud; Gimzewski, James K.

2008-09-01

We have used an atomic force microscope to examine a clinically derived sample of single-molecule gene transcripts, in the form of double-stranded cDNA, (c: complementary) obtained from human cardiac muscle without the use of polymerase chain reaction (PCR) amplification. We observed a log-normal distribution of transcript sizes, with most molecules being in the range of 0.4-7.0 kilobase pairs (kb) or 130-2300 nm in contour length, in accordance with the expected distribution of mRNA (m: messenger) sizes in mammalian cells. We observed novel branching structures not previously known to exist in cDNA, and which could have profound negative effects on traditional analysis of cDNA samples through cloning, PCR and DNA sequencing.

Influence of particle size distribution on nanopowder cold compaction processes

NASA Astrophysics Data System (ADS)

Boltachev, G.; Volkov, N.; Lukyashin, K.; Markov, V.; Chingina, E.

2017-06-01

Nanopowder uniform and uniaxial cold compaction processes are simulated by 2D granular dynamics method. The interaction of particles in addition to wide-known contact laws involves the dispersion forces of attraction and possibility of interparticle solid bridges formation, which have a large importance for nanopowders. Different model systems are investigated: monosized systems with particle diameter of 10, 20 and 30 nm; bidisperse systems with different content of small (diameter is 10 nm) and large (30 nm) particles; polydisperse systems corresponding to the log-normal size distribution law with different width. Non-monotone dependence of compact density on powder content is revealed in bidisperse systems. The deviations of compact density in polydisperse systems from the density of corresponding monosized system are found to be minor, less than 1 per cent.

Grain size distribution in sheared polycrystals

NASA Astrophysics Data System (ADS)

Sarkar, Tanmoy; Biswas, Santidan; Chaudhuri, Pinaki; Sain, Anirban

2017-12-01

Plastic deformation in solids induced by external stresses is of both fundamental and practical interest. Using both phase field crystal modeling and molecular dynamics simulations, we study the shear response of monocomponent polycrystalline solids. We subject mesocale polycrystalline samples to constant strain rates in a planar Couette flow geometry for studying its plastic flow, in particular its grain deformation dynamics. As opposed to equilibrium solids where grain dynamics is mainly driven by thermal diffusion, external stress/strain induce a much higher level of grain deformation activity in the form of grain rotation, coalescence, and breakage, mediated by dislocations. Despite this, the grain size distribution of this driven system shows only a weak power-law correction to its equilibrium log-normal behavior. We interpret the grain reorganization dynamics using a stochastic model.

Use of the Box-Cox Transformation in Detecting Changepoints in Daily Precipitation Data Series

NASA Astrophysics Data System (ADS)

Wang, X. L.; Chen, H.; Wu, Y.; Pu, Q.

2009-04-01

This study integrates a Box-Cox power transformation procedure into two statistical tests for detecting changepoints in Gaussian data series, to make the changepoint detection methods applicable to non-Gaussian data series, such as daily precipitation amounts. The detection power aspects of transformed methods in a common trend two-phase regression setting are assessed by Monte Carlo simulations for data of a log-normal or Gamma distribution. The results show that the transformed methods have increased the power of detection, in comparison with the corresponding original (untransformed) methods. The transformed data much better approximate to a Gaussian distribution. As an example of application, the new methods are applied to a series of daily precipitation amounts recorded at a station in Canada, showing satisfactory detection power.

Comparable Analysis of the Distribution Functions of Runup Heights of the 1896, 1933 and 2011 Japanese Tsunamis in the Sanriku Area

NASA Astrophysics Data System (ADS)

Choi, B. H.; Min, B. I.; Yoshinobu, T.; Kim, K. O.; Pelinovsky, E.

2012-04-01

Data from a field survey of the 2011 tsunami in the Sanriku area of Japan is presented and used to plot the distribution function of runup heights along the coast. It is shown that the distribution function can be approximated using a theoretical log-normal curve [Choi et al, 2002]. The characteristics of the distribution functions derived from the runup-heights data obtained during the 2011 event are compared with data from two previous gigantic tsunamis (1896 and 1933) that occurred in almost the same region. The number of observations during the last tsunami is very large (more than 5,247), which provides an opportunity to revise the conception of the distribution of tsunami wave heights and the relationship between statistical characteristics and number of observations suggested by Kajiura [1983]. The distribution function of the 2011 event demonstrates the sensitivity to the number of observation points (many of them cannot be considered independent measurements) and can be used to determine the characteristic scale of the coast, which corresponds to the statistical independence of observed wave heights.

Analysis of in vitro evolution reveals the underlying distribution of catalytic activity among random sequences.

PubMed

Pressman, Abe; Moretti, Janina E; Campbell, Gregory W; Müller, Ulrich F; Chen, Irene A

2017-08-21

The emergence of catalytic RNA is believed to have been a key event during the origin of life. Understanding how catalytic activity is distributed across random sequences is fundamental to estimating the probability that catalytic sequences would emerge. Here, we analyze the in vitro evolution of triphosphorylating ribozymes and translate their fitnesses into absolute estimates of catalytic activity for hundreds of ribozyme families. The analysis efficiently identified highly active ribozymes and estimated catalytic activity with good accuracy. The evolutionary dynamics follow Fisher's Fundamental Theorem of Natural Selection and a corollary, permitting retrospective inference of the distribution of fitness and activity in the random sequence pool for the first time. The frequency distribution of rate constants appears to be log-normal, with a surprisingly steep dropoff at higher activity, consistent with a mechanism for the emergence of activity as the product of many independent contributions. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Cumulative slant path rain attenuation associated with COMSTAR beacon at 28.56 GHz for Wallops Island, Virginia

NASA Technical Reports Server (NTRS)

Goldhirsh, J.

1978-01-01

Yearly, monthly, and time of day fade statistics are presented and characterized. A 19.04 GHz yearly fade distribution, corresponding to a second COMSTAR beacon frequency, is predicted using the concept of effective path length, disdrometer, and rain rate results. The yearly attenuation and rain rate distributions follow with good approximation log normal variations for most fade and rain rate levels. Attenuations were exceeded for the longest and shortest periods of times for all fades in August and February, respectively. The eight hour time period showing the maximum and minimum number of minutes over the year for which fades exceeded 12 db were approximately between 1600 to 2400, and 0400 to 1200 hours, respectively. In employing the predictive method for obtaining the 19.04 GHz fade distribution, it is demonstrated theoretically that the ratio of attenuations at two frequencies is minimally dependent of raindrop size distribution providing these frequencies are not widely separated.

Application of bimodal distribution to the detection of changes in uranium concentration in drinking water collected by random daytime sampling method from a large water supply zone.

PubMed

Garboś, Sławomir; Święcicka, Dorota

2015-11-01

The random daytime (RDT) sampling method was used for the first time in the assessment of average weekly exposure to uranium through drinking water in a large water supply zone. Data set of uranium concentrations determined in 106 RDT samples collected in three runs from the water supply zone in Wroclaw (Poland), cannot be simply described by normal or log-normal distributions. Therefore, a numerical method designed for the detection and calculation of bimodal distribution was applied. The extracted two distributions containing data from the summer season of 2011 and the winter season of 2012 (nI=72) and from the summer season of 2013 (nII=34) allowed to estimate means of U concentrations in drinking water: 0.947 μg/L and 1.23 μg/L, respectively. As the removal efficiency of uranium during applied treatment process is negligible, the effect of increase in uranium concentration can be explained by higher U concentration in the surface-infiltration water used for the production of drinking water. During the summer season of 2013, heavy rains were observed in Lower Silesia region, causing floods over the territory of the entire region. Fluctuations in uranium concentrations in surface-infiltration water can be attributed to releases of uranium from specific sources - migration from phosphate fertilizers and leaching from mineral deposits. Thus, exposure to uranium through drinking water may increase during extreme rainfall events. The average chronic weekly intakes of uranium through drinking water, estimated on the basis of central values of the extracted normal distributions, accounted for 3.2% and 4.1% of tolerable weekly intake. Copyright © 2015 Elsevier Ltd. All rights reserved.

Estimation of optical properties of aerosols and bidirectional reflectance from PARASOL/POLDER data over land

NASA Astrophysics Data System (ADS)

Kusaka, Takashi; Miyazaki, Go

2014-10-01

When monitoring target areas covered with vegetation from a satellite, it is very useful to estimate the vegetation index using the surface anisotropic reflectance, which is dependent on both solar and viewing geometries, from satellite data. In this study, the algorithm for estimating optical properties of atmospheric aerosols such as the optical thickness (τ), the refractive index (Nr), the mixing ratio of small particles in the bimodal log-normal distribution function (C) and the bidirectional reflectance (R) from only the radiance and polarization at the 865nm channel received by the PARASOL/POLDER is described. Parameters of the bimodal log-normal distribution function: mean radius, r1, standard deviation, σ1, of fine aerosols, and r2, σ2 of coarse aerosols were fixed, and these values were estimated from monthly averaged size distribution at AERONET sites managed by NASA near the target area. Moreover, it is assumed that the contribution of the surface reflectance with directional anisotropy to the polarized radiance received by the satellite is small because it is shown from our ground-based polarization measurements of light ray reflected by the grassland that degrees of polarization of the reflected light by the grassland are very low values at the 865nm channel. First aerosol properties were estimated from only the polarized radiance and then the bidirectional reflectance given by the Ross-Li BRDF model was estimated from only the total radiance at target areas in PARASOL/POLDER data over the Japanese islands taken on April 28, 2012 and April 25, 2010. The estimated optical thickness of aerosols was checked with those given in AERONET sites and the estimated parameters of BRDF were compared with those of vegetation measured from the radio-controlled helicopter. Consequently, it is shown that the algorithm described in the present study provides reasonable values for aerosol properties and surface bidirectional reflectance.

Compacting biomass waste materials for use as fuel

NASA Astrophysics Data System (ADS)

Zhang, Ou

Every year, biomass waste materials are produced in large quantity. The combustibles in biomass waste materials make up over 70% of the total waste. How to utilize these waste materials is important to the nation and the world. The purpose of this study is to test optimum processes and conditions of compacting a number of biomass waste materials to form a densified solid fuel for use at coal-fired power plants or ordinary commercial furnaces. Successful use of such fuel as a substitute for or in cofiring with coal not only solves a solid waste disposal problem but also reduces the release of some gases from burning coal which cause health problem, acid rain and global warming. The unique punch-and-die process developed at the Capsule Pipeline Research Center, University of Missouri-Columbia was used for compacting the solid wastes, including waste paper, plastics (both film and hard products), textiles, leaves, and wood. The compaction was performed to produce strong compacts (biomass logs) under room temperature without binder and without preheating. The compaction conditions important to the commercial production of densified biomass fuel logs, including compaction pressure, pressure holding time, back pressure, moisture content, particle size, binder effects, and mold conditions were studied and optimized. The properties of the biomass logs were evaluated in terms of physical, mechanical, and combustion characteristics. It was found that the compaction pressure and the initial moisture content of the biomass material play critical roles in producing high-quality biomass logs. Under optimized compaction conditions, biomass waste materials can be compacted into high-quality logs with a density of 0.8 to 1.2 g/cm3. The logs made from the combustible wastes have a heating value in the range 6,000 to 8,000 Btu/lb which is only slightly (10 to 30%) less than that of subbituminous coal. To evaluate the feasibility of cofiring biomass logs with coal, burn tests were conducted in a stoke boiler. A separate burning test was also carried out by burning biomass logs alone in an outdoor hot-water furnace for heating a building. Based on a previous coal compaction study, the process of biomass compaction was studied numerically by use of a non-linear finite element code. A constitutive model with sufficient generality was adapted for biomass material to deal with pore contraction during compaction. A contact node algorithm was applied to implement the effect of mold wall friction into the finite element program. Numerical analyses were made to investigate the pressure distribution in a die normal to the axis of compaction, and to investigate the density distribution in a biomass log after compaction. The results of the analyses gave generally good agreement with theoretical analysis of coal log compaction, although assumptions had to be made about the variation in the elastic modulus of the material and the Poisson's ratio during the compaction cycle.

Temperature dependence of electron magnetic resonance spectra of iron oxide nanoparticles mineralized in Listeria innocua protein cages

NASA Astrophysics Data System (ADS)

Usselman, Robert J.; Russek, Stephen E.; Klem, Michael T.; Allen, Mark A.; Douglas, Trevor; Young, Mark; Idzerda, Yves U.; Singel, David J.

2012-10-01

Electron magnetic resonance (EMR) spectroscopy was used to determine the magnetic properties of maghemite (γ-Fe2O3) nanoparticles formed within size-constraining Listeria innocua (LDps)-(DNA-binding protein from starved cells) protein cages that have an inner diameter of 5 nm. Variable-temperature X-band EMR spectra exhibited broad asymmetric resonances with a superimposed narrow peak at a gyromagnetic factor of g ≈ 2. The resonance structure, which depends on both superparamagnetic fluctuations and inhomogeneous broadening, changes dramatically as a function of temperature, and the overall linewidth becomes narrower with increasing temperature. Here, we compare two different models to simulate temperature-dependent lineshape trends. The temperature dependence for both models is derived from a Langevin behavior of the linewidth resulting from "anisotropy melting." The first uses either a truncated log-normal distribution of particle sizes or a bi-modal distribution and then a Landau-Liftshitz lineshape to describe the nanoparticle resonances. The essential feature of this model is that small particles have narrow linewidths and account for the g ≈ 2 feature with a constant resonance field, whereas larger particles have broad linewidths and undergo a shift in resonance field. The second model assumes uniform particles with a diameter around 4 nm and a random distribution of uniaxial anisotropy axes. This model uses a more precise calculation of the linewidth due to superparamagnetic fluctuations and a random distribution of anisotropies. Sharp features in the spectrum near g ≈ 2 are qualitatively predicted at high temperatures. Both models can account for many features of the observed spectra, although each has deficiencies. The first model leads to a nonphysical increase in magnetic moment as the temperature is increased if a log normal distribution of particles sizes is used. Introducing a bi-modal distribution of particle sizes resolves the unphysical increase in moment with temperature. The second model predicts low-temperature spectra that differ significantly from the observed spectra. The anisotropy energy density K1, determined by fitting the temperature-dependent linewidths, was ˜50 kJ/m3, which is considerably larger than that of bulk maghemite. The work presented here indicates that the magnetic properties of these size-constrained nanoparticles and more generally metal oxide nanoparticles with diameters d < 5 nm are complex and that currently existing models are not sufficient for determining their magnetic resonance signatures.

Seroprevalence of Toxocara canis infection in tropical Venezuela.

PubMed

Lynch, N R; Eddy, K; Hodgen, A N; Lopez, R I; Turner, K J

1988-01-01

An enzyme-linked immunosorbent assay (ELISA) was used to determine the seroprevalence of Toxocara canis infection in different socio-economic groups of the tropical population of Venezuela. The lack of definitive independent diagnostic criteria for toxocariasis required the establishment of operational upper limits of normality for Toxocara ELISA values, based upon their log-normalized distribution in a presumptive "non-toxocariasis" sub-population. Only 1.8% of urban subjects of medium-high socio-economic level were considered to be clearly positive in Toxocara ELISA, compared to 20.0% of urban slum dwellers, 25.6% rural subsistence farmers and 34.9% Amazon Indians. As the test was performed using excretory-secretory antigen, and under conditions of competitive inhibition by soluble extracts of non-homologous parasites, co-infection by common intestinal helminths, protozoa or other organisms did not give rise to false positive results. However, strong cross-reactivity with Onchocerca volvulus may have influenced the prevalence figure obtained for the Amazon Indians. These results indicate that T. canis is yet another parasite that is widely distributed in economically underprivileged tropical populations.

R/S analysis of reaction time in Neuron Type Test for human activity in civil aviation

NASA Astrophysics Data System (ADS)

Zhang, Hong-Yan; Kang, Ming-Cui; Li, Jing-Qiang; Liu, Hai-Tao

2017-03-01

Human factors become the most serious problem leading to accidents of civil aviation, which stimulates the design and analysis of Neuron Type Test (NTT) system to explore the intrinsic properties and patterns behind the behaviors of professionals and students in civil aviation. In the experiment, normal practitioners' reaction time sequences, collected from NTT, exhibit log-normal distribution approximately. We apply the χ2 test to compute the goodness-of-fit by transforming the time sequence with Box-Cox transformation to cluster practitioners. The long-term correlation of different individual practitioner's time sequence is represented by the Hurst exponent via Rescaled Range Analysis, also named by Range/Standard deviation (R/S) Analysis. The different Hurst exponent suggests the existence of different collective behavior and different intrinsic patterns of human factors in civil aviation.

Cooperation evolution in random multiplicative environments

NASA Astrophysics Data System (ADS)

Yaari, G.; Solomon, S.

2010-02-01

Most real life systems have a random component: the multitude of endogenous and exogenous factors influencing them result in stochastic fluctuations of the parameters determining their dynamics. These empirical systems are in many cases subject to noise of multiplicative nature. The special properties of multiplicative noise as opposed to additive noise have been noticed for a long while. Even though apparently and formally the difference between free additive vs. multiplicative random walks consists in just a move from normal to log-normal distributions, in practice the implications are much more far reaching. While in an additive context the emergence and survival of cooperation requires special conditions (especially some level of reward, punishment, reciprocity), we find that in the multiplicative random context the emergence of cooperation is much more natural and effective. We study the various implications of this observation and its applications in various contexts.

Body mass index, immune status, and virological control in HIV-infected men who have sex with men.

PubMed

Blashill, Aaron J; Mayer, Kenneth H; Crane, Heidi M; Grasso, Chris; Safren, Steven A

2013-01-01

Prior cross-sectional studies have found inconsistent relationships between body mass index (BMI) and disease progression in HIV-infected individuals. Cross-sectional and longitudinal analyses were conducted on data from a sample of 864 HIV-infected men who have sex with men (MSM) obtained from a large, nationally distributed HIV clinical cohort. Of the 864 HIV-infected MSM, 394 (46%) were of normal weight, 363 (42%) were overweight, and 107 (12%) were obese at baseline. The baseline CD4 count was 493 (standard error [SE] = 9), with viral load (log10) = 2.4 (SE = .04), and 561 (65%) were virologically suppressed. Over time, controlling for viral load, highly active antiretroviral therapy (HAART) adherence, age, and race/ethnicity, overweight and obese HIV-infected men possessed higher CD4 counts than that of normal weight HIV-infected men. Further, overweight and obese men possessed lower viral loads than that of normal weight HIV-infected men. For HIV-infected MSM, in this longitudinal cohort study, possessing a heavier than normal BMI is longitudinally associated with improved immunological health.

Cross-platform normalization of microarray and RNA-seq data for machine learning applications

PubMed Central

Thompson, Jeffrey A.; Tan, Jie

2016-01-01

Large, publicly available gene expression datasets are often analyzed with the aid of machine learning algorithms. Although RNA-seq is increasingly the technology of choice, a wealth of expression data already exist in the form of microarray data. If machine learning models built from legacy data can be applied to RNA-seq data, larger, more diverse training datasets can be created and validation can be performed on newly generated data. We developed Training Distribution Matching (TDM), which transforms RNA-seq data for use with models constructed from legacy platforms. We evaluated TDM, as well as quantile normalization, nonparanormal transformation, and a simple log2 transformation, on both simulated and biological datasets of gene expression. Our evaluation included both supervised and unsupervised machine learning approaches. We found that TDM exhibited consistently strong performance across settings and that quantile normalization also performed well in many circumstances. We also provide a TDM package for the R programming language. PMID:26844019

Refinement of the timing-based estimator of pulsar magnetic fields

NASA Astrophysics Data System (ADS)

Biryukov, Anton; Astashenok, Artyom; Beskin, Gregory

2017-04-01

Numerical simulations of realistic non-vacuum magnetospheres of isolated neutron stars have shown that pulsar spin-down luminosities depend weakly on the magnetic obliquity α. In particular, L ∝ B2(1 + sin 2α), where B is the magnetic field strength at the star surface. Being the most accurate expression to date, this result provides the opportunity to estimate B for a given radiopulsar with quite a high accuracy. In the current work, we present a refinement of the classical 'magneto-dipolar' formula for pulsar magnetic fields B_md = (3.2× 10^{19} G)√{P\\dot{P}}, where P is the neutron star spin period. The new, robust timing-based estimator is introduced as log B = log Bmd + ΔB(M, α), where the correction ΔB depends on the equation of state (EOS) of dense matter, the individual pulsar obliquity α and the mass M. Adopting state-of-the-art statistics for M and α we calculate the distributions of ΔB for a representative subset of 22 EOSs that do not contradict observations. It has been found that ΔB is distributed nearly normally, with the average in the range -0.5 to -0.25 dex and standard deviation σ[ΔB] ≈ 0.06 to 0.09 dex, depending on the adopted EOS. The latter quantity represents a formal uncertainty of the corrected estimation of log B because ΔB is weakly correlated with log Bmd. At the same time, if it is assumed that every considered EOS has the same chance of occurring in nature, then another, more generalized, estimator B* ≈ 3Bmd/7 can be introduced providing an unbiased value of the pulsar surface magnetic field with ˜30 per cent uncertainty with 68 per cent confidence. Finally, we discuss the possible impact of pulsar timing irregularities on the timing-based estimation of B and review the astrophysical applications of the obtained results.

Intracellular activity of antibiotics in a model of human THP-1 macrophages infected by a Staphylococcus aureus small-colony variant strain isolated from a cystic fibrosis patient: pharmacodynamic evaluation and comparison with isogenic normal-phenotype and revertant strains.

PubMed

Nguyen, Hoang Anh; Denis, Olivier; Vergison, Anne; Theunis, Anne; Tulkens, Paul M; Struelens, Marc J; Van Bambeke, Françoise

2009-04-01

Small-colony variant (SCV) strains of Staphylococcus aureus show reduced antibiotic susceptibility and intracellular persistence, potentially explaining therapeutic failures. The activities of oxacillin, fusidic acid, clindamycin, gentamicin, rifampin, vancomycin, linezolid, quinupristin-dalfopristin, daptomycin, tigecycline, moxifloxacin, telavancin, and oritavancin have been examined in THP-1 macrophages infected by a stable thymidine-dependent SCV strain in comparison with normal-phenotype and revertant isogenic strains isolated from the same cystic fibrosis patient. The SCV strain grew slowly extracellularly and intracellularly (1- and 0.2-log CFU increase in 24 h, respectively). In confocal and electron microscopy, SCV and the normal-phenotype bacteria remain confined in acid vacuoles. All antibiotics tested, except tigecycline, caused a net reduction in bacterial counts that was both time and concentration dependent. At an extracellular concentration corresponding to the maximum concentration in human serum (total drug), oritavancin caused a 2-log CFU reduction at 24 h; rifampin, moxifloxacin, and quinupristin-dalfopristin caused a similar reduction at 72 h; and all other antibiotics had only a static effect at 24 h and a 1-log CFU reduction at 72 h. In concentration dependence experiments, response to oritavancin was bimodal (two successive plateaus of -0.4 and -3.1 log CFU); tigecycline, moxifloxacin, and rifampin showed maximal effects of -1.1 to -1.7 log CFU; and the other antibiotics produced results of -0.6 log CFU or less. Addition of thymidine restored intracellular growth of the SCV strain but did not modify the activity of antibiotics (except quinupristin-dalfopristin). All drugs (except tigecycline and oritavancin) showed higher intracellular activity against normal or revertant phenotypes than against SCV strains. The data may help rationalizing the design of further studies with intracellular SCV strains.

Portable acuity screening for any school: validation of patched HOTV with amblyopic patients and Bangerter normals.

PubMed

Tsao Wu, Maya; Armitage, M Diane; Trujillo, Claire; Trujillo, Anna; Arnold, Laura E; Tsao Wu, Lauren; Arnold, Robert W

2017-12-04

We needed to validate and calibrate our portable acuity screening tools so amblyopia could be detected quickly and effectively at school entry. Spiral-bound flip cards and download pdf surround HOTV acuity test box with critical lines were combined with a matching card. Amblyopic patients performed critical line, then threshold acuity which was then compared to patched E-ETDRS acuity. 5 normal subjects wore Bangerter foil goggles to simulate blur for comparative validation. The 31 treated amblyopic eyes showed: logMAR HOTV = 0.97(logMAR E-ETDRS)-0.04 r2 = 0.88. All but two (6%) fell less than 2 lines difference. The five showed logMAR HOTV = 1.09 ((logMAR E-ETDRS) + .15 r2 = 0.63. The critical-line, test box was 98% efficient at screening within one line of 20/40. These tools reliably detected acuity in treated amblyopic patients and Bangerter blurred normal subjects. These free and affordable tools provide sensitive screening for amblyopia in children from public, private and home schools. Changing "pass" criteria to 4 out of 5 would improve sensitivity with somewhat slower testing for all students.

Fermi/GBM Observations of SGRJ0501 + 4516 Bursts

NASA Technical Reports Server (NTRS)

Lin, Lin; Kouveliotou, Chryssa; Baring, Matthew G.; van der Horst, Alexander J.; Guiriec, Sylvain; Woods, Peter M.; Goegues, Ersin; Kaneko, Yuki; Scargle, Jeffrey; Granot, Jonathan;

Human Target Attainment Probabilities for Delafloxacin against Escherichia coli and Pseudomonas aeruginosa

PubMed Central

Hoover, Randall; Marra, Andrea; Duffy, Erin; Cammarata, Sue K

2017-01-01

Abstract Background Delafloxacin (DLX) is a broad-spectrum fluoroquinolone antibiotic under FDA review for the treatment of ABSSSI. Previous studies determined DLX bacterial stasis and 1-log10 bacterial reduction free AUC0-24 / MIC (fAUC0-24/MIC) targets for Escherichia coli (EC) and Pseudomonas aeruginosa (PA) in a mouse thigh infection model. The resulting PK/PD targets were used to predict DLX target attainment probabilities (TAP) in humans. Methods Monte Carlo simulations were used to estimate TAP with DLX 300 mg IV, q12hr. Human DLX plasma pharmacokinetics were determined in patients with ABSSSI in a Phase 3 clinical trial. Individual AUC values were analyzed and determined to be log-normally distributed. The parameters of the AUC distribution were used to simulate random values for fAUC24, which then were combined with random MIC values based on 2014–2015 US distributions of skin and soft tissue isolates of EC (n = 108) and PA (n = 40), to calculate PK/PD TAPs. Results DLX fAUC0-24/MIC targets for bacterial stasis and 1-log10 bacterial reduction for EC were 14.5 and 26.2, and for PA were 3.81 and 5.02, respectively. The Monte Carlo simulations for EC predicted TAPs of 98.7% for stasis at an MIC of 0.25 μg/mL, and 99.3% for 1-log10 bacterial reduction at an MIC of 0.12 μg/mL. The simulations for PA predicted TAPs of 97.3% for stasis and 86.5% for 1-log10 bacterial reduction at an MIC of 1 μg/mL. E. coli MIC (ug/mL) Target 0.008 0.015 0.03 0.06 0.12 0.25 0.5 1 Stasis 100 100 100 100 100 97.8 50.4 2.0 1-Log Kill 100 100 100 100 99.3 60.4 5.8 0.0 P. aeruginosa MIC (ug/mL) Target 0.03 0.06 0.12 0.25 0.5 1 2 4 5 Stasis 100 100 100 100 100 97.3 45.9 1.7 0.5 1-Log Kill 100 100 100 100 100 86.5 17.8 0.3 0.1 Conclusion DLX 300 mg IV, q12hr, should achieve fAUC24/MIC ratios that are adequate to treat ABSSSI caused by most contemporary isolates of EC and PA. For EC, isolates with DLX MICs ≤0.25 μg/mL comprised 73% of all isolates. For PA, isolates with DLX MICs ≤1 μg/mL comprised 88% of all isolates. Similar results would be expected for TAP with oral DLX 450 mg, q12hr. Disclosures R. Hoover, Melinta Therapeutics: Consultant, Consulting fee; A. Marra, Melinta Therapeutics: Employee, Salary; E. Duffy, Melinta Therapeutics: Employee, Salary; S. K. Cammarata, Melinta Therapeutics: Employee, Salary

A comparison of Probability Of Detection (POD) data determined using different statistical methods

NASA Astrophysics Data System (ADS)

Fahr, A.; Forsyth, D.; Bullock, M.

1993-12-01

Different statistical methods have been suggested for determining probability of detection (POD) data for nondestructive inspection (NDI) techniques. A comparative assessment of various methods of determining POD was conducted using results of three NDI methods obtained by inspecting actual aircraft engine compressor disks which contained service induced cracks. The study found that the POD and 95 percent confidence curves as a function of crack size as well as the 90/95 percent crack length vary depending on the statistical method used and the type of data. The distribution function as well as the parameter estimation procedure used for determining POD and the confidence bound must be included when referencing information such as the 90/95 percent crack length. The POD curves and confidence bounds determined using the range interval method are very dependent on information that is not from the inspection data. The maximum likelihood estimators (MLE) method does not require such information and the POD results are more reasonable. The log-logistic function appears to model POD of hit/miss data relatively well and is easy to implement. The log-normal distribution using MLE provides more realistic POD results and is the preferred method. Although it is more complicated and slower to calculate, it can be implemented on a common spreadsheet program.

Precipitation scavenging of polychlorinated biphenyl congeners in the great lakes region

NASA Astrophysics Data System (ADS)

Murray, Michael W.; Andren, Anders W.

Ten precipitation events were sampled in the fall of 1986 in Madison, WI and analyzed for individual congener and total polychlorinated biphenyl (PCB) levels in both the dissolved and particulate phases. Total PCB concentrations were generally at the lower end of ranges recently reported for precipitation. Operationally defined dissolved and particulate phase congener distribution patterns for the two events of highest concentration were qualitatively similar to gas-phase and particle-bound patterns for northern Wisconsin air samples. Higher than predicted dissolved-phase concentrations may indicate non-equilibrium processes during scavenging and/or sample processing, the presence of colloids and micro-particulates, and/or more efficient gas-phase transfer to hydrometeors with organic coatings. Observed organic carbon-normalized distribution coefficients increased slightly with increasing octanol-water partition coefficient, giving the relationship log Koc = 0.22 log Kow + 4.64. The data indicate that a third organic-rich colloidal phase could be influencing partitioning, and could explain the higher than expected apparent gas scavenging efficiency for PCBs from the atmosphere. Precipitation-weighted mean fluxes of PCBs in the dissolved and particulate phases were 1.2 and 1.4 μg m -2 year -1, respectively, indicating that precipitation remains a significant source of PCBs to the upper Great Lakes.

The Tail Exponent for Stock Returns in Bursa Malaysia for 2003-2008

NASA Astrophysics Data System (ADS)

Rusli, N. H.; Gopir, G.; Usang, M. D.

2010-07-01

A developed discipline of econophysics that has been introduced is exhibiting the application of mathematical tools that are usually applied to the physical models for the study of financial models. In this study, an analysis of the time series behavior of several blue chip and penny stock companies in Main Market of Bursa Malaysia has been performed. Generally, the basic quantity being used is the relative price changes or is called the stock price returns, contains daily-sampled data from the beginning of 2003 until the end of 2008, containing 1555 trading days recorded. The aim of this paper is to investigate the tail exponent in tails of the distribution for blue chip stocks and penny stocks financial returns in six years period. By using a standard regression method, it is found that the distribution performed double scaling on the log-log plot of the cumulative probability of the normalized returns. Thus we calculate α for a small scale return as well as large scale return. Based on the result obtained, it is found that the power-law behavior for the probability density functions of the stock price absolute returns P(z)˜z-α with values lying inside and outside the Lévy stable regime with values α>2. All the results were discussed in detail.

Superposition of Polytropes in the Inner Heliosheath

NASA Astrophysics Data System (ADS)

Livadiotis, G.

2016-03-01

This paper presents a possible generalization of the equation of state and Bernoulli's integral when a superposition of polytropic processes applies in space and astrophysical plasmas. The theory of polytropic thermodynamic processes for a fixed polytropic index is extended for a superposition of polytropic indices. In general, the superposition may be described by any distribution of polytropic indices, but emphasis is placed on a Gaussian distribution. The polytropic density-temperature relation has been used in numerous analyses of space plasma data. This linear relation on a log-log scale is now generalized to a concave-downward parabola that is able to describe the observations better. The model of the Gaussian superposition of polytropes is successfully applied in the proton plasma of the inner heliosheath. The estimated mean polytropic index is near zero, indicating the dominance of isobaric thermodynamic processes in the sheath, similar to other previously published analyses. By computing Bernoulli's integral and applying its conservation along the equator of the inner heliosheath, the magnetic field in the inner heliosheath is estimated, B ˜ 2.29 ± 0.16 μG. The constructed normalized histogram of the values of the magnetic field is similar to that derived from a different method that uses the concept of large-scale quantization, bringing incredible insights to this novel theory.

Uniwavelength lidar sensitivity to spherical aerosol microphysical properties for the interpretation of Lagrangian stratospheric observations

NASA Astrophysics Data System (ADS)

Jumelet, Julien; David, Christine; Bekki, Slimane; Keckhut, Philippe

2009-01-01

The determination of stratospheric particle microphysical properties from multiwavelength lidar, including Rayleigh and/or Raman detection, has been widely investigated. However, most lidar systems are uniwavelength operating at 532 nm. Although the information content of such lidar data is too limited to allow the retrieval of the full size distribution, the coupling of two or more uniwavelength lidar measurements probing the same moving air parcel may provide some meaningful size information. Within the ORACLE-O3 IPY project, the coordination of several ground-based lidars and the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) space-borne lidar is planned during measurement campaigns called MATCH-PSC (Polar Stratospheric Clouds). While probing the same moving air masses, the evolution of the measured backscatter coefficient (BC) should reflect the variation of particles microphysical properties. A sensitivity study of 532 nm lidar particle backscatter to variations of particles size distribution parameters is carried out. For simplicity, the particles are assumed to be spherical (liquid) particles and the size distribution is represented with a unimodal log-normal distribution. Each of the four microphysical parameters (i.e. log-normal size distribution parameters, refractive index) are analysed separately, while the three others are remained set to constant reference values. Overall, the BC behaviour is not affected by the initial values taken as references. The total concentration (N0) is the parameter to which BC is least sensitive, whereas it is most sensitive to the refractive index (m). A 2% variation of m induces a 15% variation of the lidar BC, while the uncertainty on the BC retrieval can also reach 15%. This result underlines the importance of having both an accurate lidar inversion method and a good knowledge of the temperature for size distribution retrieval techniques. The standard deviation ([sigma]) is the second parameter to which BC is most sensitive to. Yet, the impact of m and [sigma] on BC variations is limited by the realistic range of their variations. The mean radius (rm) of the size distribution is thus the key parameter for BC, as it can vary several-fold. BC is most sensitive to the presence of large particles. The sensitivity of BC to rm and [sigma] variations increases when the initial size distributions are characterized by low rm and large [sigma]. This makes lidar more suitable to detect particles growing on background aerosols than on volcanic aerosols.

Investigating uplift in the South-Western Barents Sea using sonic and density well log measurements

NASA Astrophysics Data System (ADS)

Yang, Y.; Ellis, M.

2014-12-01

Sediments in the Barents Sea have undergone large amounts of uplift due to Plio-Pleistoncene deglaciation as well as Palaeocene-Eocene Atlantic rifting. Uplift affects the reservoir quality, seal capacity and fluid migration. Therefore, it is important to gain reliable uplift estimates in order to evaluate the petroleum prospectivity properly. To this end, a number of quantification methods have been proposed, such as Apatite Fission Track Analysis (AFTA), and integration of seismic surveys with well log data. AFTA usually provides accurate uplift estimates, but the data is limited due to its high cost. While the seismic survey can provide good uplift estimate when well data is available for calibration, the uncertainty can be large in areas where there is little to no well data. We estimated South-Western Barents Sea uplift based on well data from the Norwegian Petroleum Directorate. Primary assumptions include time-irreversible shale compaction trends and a universal normal compaction trend for a specified formation. Sonic and density logs from two Cenozoic shale formation intervals, Kolmule and Kolje, were used for the study. For each formation, we studied logs of all released wells, and established exponential normal compaction trends based on a single well. That well was then deemed the reference well, and relative uplift can be calculated at other well locations based on the offset from the normal compaction trend. We found that the amount of uplift increases along the SW to NE direction, with a maximum difference of 1,447 m from the Kolje FM estimate, and 699 m from the Kolmule FM estimate. The average standard deviation of the estimated uplift is 130 m for the Kolje FM, and 160 m for the Kolmule FM using the density log. While results from density logs and sonic logs have good agreement in general, the density log provides slightly better results in terms of higher consistency and lower standard deviation. Our results agree with published papers qualitatively with some differences in the actual amount of uplifts. The results are considered to be more accurate due to the higher resolution of the log scale data that was used.

Microfracture spacing distributions and the evolution of fracture patterns in sandstones

NASA Astrophysics Data System (ADS)

Hooker, J. N.; Laubach, S. E.; Marrett, R.

2018-03-01

Natural fracture patterns in sandstone were sampled using scanning electron microscope-based cathodoluminescence (SEM-CL) imaging. All fractures are opening-mode and are fully or partially sealed by quartz cement. Most sampled fractures are too small to be height-restricted by sedimentary layers. At very low strains (<∼0.001), fracture spatial distributions are indistinguishable from random, whereas at higher strains, fractures are generally statistically clustered. All 12 large (N > 100) datasets show spacings that are best fit by log-normal size distributions, compared to exponential, power law, or normal distributions. The clustering of fractures suggests that the locations of natural factures are not determined by a random process. To investigate natural fracture localization, we reconstructed the opening history of a cluster of fractures within the Huizachal Group in northeastern Mexico, using fluid inclusions from synkinematic cements and thermal-history constraints. The largest fracture, which is the only fracture in the cluster visible to the naked eye, among 101 present, opened relatively late in the sequence. This result suggests that the growth of sets of fractures is a self-organized process, in which small, initially isolated fractures grow and progressively interact, with preferential growth of a subset of fractures developing at the expense of growth of the rest. Size-dependent sealing of fractures within sets suggests that synkinematic cementation may contribute to fracture clustering.

Seismic velocity deviation log: An effective method for evaluating spatial distribution of reservoir pore types

NASA Astrophysics Data System (ADS)

Shirmohamadi, Mohamad; Kadkhodaie, Ali; Rahimpour-Bonab, Hossain; Faraji, Mohammad Ali

2017-04-01

Velocity deviation log (VDL) is a synthetic log used to determine pore types in reservoir rocks based on a combination of the sonic log with neutron-density logs. The current study proposes a two step approach to create a map of porosity and pore types by integrating the results of petrographic studies, well logs and seismic data. In the first step, velocity deviation log was created from the combination of the sonic log with the neutron-density log. The results allowed identifying negative, zero and positive deviations based on the created synthetic velocity log. Negative velocity deviations (below - 500 m/s) indicate connected or interconnected pores and fractures, while positive deviations (above + 500 m/s) are related to isolated pores. Zero deviations in the range of [- 500 m/s, + 500 m/s] are in good agreement with intercrystalline and microporosities. The results of petrographic studies were used to validate the main pore type derived from velocity deviation log. In the next step, velocity deviation log was estimated from seismic data by using a probabilistic neural network model. For this purpose, the inverted acoustic impedance along with the amplitude based seismic attributes were formulated to VDL. The methodology is illustrated by performing a case study from the Hendijan oilfield, northwestern Persian Gulf. The results of this study show that integration of petrographic, well logs and seismic attributes is an instrumental way for understanding the spatial distribution of main reservoir pore types.

C-reactive protein, waist circumference, and family history of heart attack are independent predictors of body iron stores in apparently healthy premenopausal women.

PubMed

Suárez-Ortegón, M F; Arbeláez, A; Mosquera, M; Méndez, F; Aguilar-de Plata, C

2012-08-01

Ferritin levels have been associated with metabolic syndrome and insulin resistance. The aim of the present study was to evaluate the prediction of ferritin levels by variables related to cardiometabolic disease risk in a multivariate analysis. For this aim, 123 healthy women (72 premenopausal and 51 posmenopausal) were recruited. Data were collected through procedures of anthropometric measurements, questionnaires for personal/familial antecedents, and dietary intake (24-h recall), and biochemical determinations (ferritin, C reactive protein (CRP), glucose, insulin, and lipid profile) in blood serum samples obtained. Multiple linear regression analysis was used and variables with no normal distribution were log-transformed for this analysis. In premenopausal women, a model to explain log-ferritin levels was found with log-CRP levels, heart attack familial history, and waist circumference as independent predictors. Ferritin behaves as other cardiovascular markers in terms of prediction of its levels by documented predictors of cardiometabolic disease and related disorders. This is the first report of a relationship between heart attack familial history and ferritin levels. Further research is required to evaluate the mechanism to explain the relationship of central body fat and heart attack familial history with body iron stores values.

Survey of Large Methane Emitters in North America

NASA Astrophysics Data System (ADS)

Deiker, S.

2017-12-01

It has been theorized that methane emissions in the oil and gas industry follow log normal or "fat tail" distributions, with large numbers of small sources for every very large source. Such distributions would have significant policy and operational implications. Unfortunately, by their very nature such distributions would require large sample sizes to verify. Until recently, such large-scale studies would be prohibitively expensive. The largest public study to date sampled 450 wells, an order of magnitude too low to effectively constrain these models. During 2016 and 2017, Kairos Aerospace conducted a series of surveys the LeakSurveyor imaging spectrometer, mounted on light aircraft. This small, lightweight instrument was designed to rapidly locate large emission sources. The resulting survey covers over three million acres of oil and gas production. This includes over 100,000 wells, thousands of storage tanks and over 7,500 miles of gathering lines. This data set allows us to now probe the distribution of large methane emitters. Results of this survey, and implications for methane emission distribution, methane policy and LDAR will be discussed.

Agnostic stacking of intergalactic doublet absorption: measuring the Ne VIII population

NASA Astrophysics Data System (ADS)

Frank, Stephan; Pieri, Matthew M.; Mathur, Smita; Danforth, Charles W.; Shull, J. Michael

2018-05-01

We present a blind search for doublet intergalactic metal absorption with a method dubbed `agnostic stacking'. Using a forward-modelling framework, we combine this with direct detections in the literature to measure the overall metal population. We apply this novel approach to the search for Ne VIII absorption in a set of 26 high-quality COS spectra. We probe to an unprecedented low limit of log N>12.3 at 0.47≤z ≤1.34 over a path-length Δz = 7.36. This method selects apparent absorption without requiring knowledge of its source. Stacking this mixed population dilutes doublet features in composite spectra in a deterministic manner, allowing us to measure the proportion corresponding to Ne VIII absorption. We stack potential Ne VIII absorption in two regimes: absorption too weak to be significant in direct line studies (12.3 < log N < 13.7), and strong absorbers (log N > 13.7). We do not detect Ne VIII absorption in either regime. Combining our measurements with direct detections, we find that the Ne VIII population is reproduced with a power-law column density distribution function with slope β = -1.86 ^{+0.18 }_{ -0.26} and normalization log f_{13.7} = -13.99 ^{+0.20 }_{ -0.23}, leading to an incidence rate of strong Ne VIII absorbers dn/dz =1.38 ^{+0.97 }_{ -0.82}. We infer a cosmic mass density for Ne VIII gas with 12.3 < log N < 15.0 of Ω _{{{Ne {VIII}}}} = 2.2 ^{+1.6 }_{ _-1.2} × 10^{-8}, a value significantly lower that than predicted by recent simulations. We translate this density into an estimate of the baryon density Ωb ≈ 1.8 × 10-3, constituting 4 per cent of the total baryonic mass.

On the identification of Dragon Kings among extreme-valued outliers

NASA Astrophysics Data System (ADS)

Riva, M.; Neuman, S. P.; Guadagnini, A.

2013-07-01

Extreme values of earth, environmental, ecological, physical, biological, financial and other variables often form outliers to heavy tails of empirical frequency distributions. Quite commonly such tails are approximated by stretched exponential, log-normal or power functions. Recently there has been an interest in distinguishing between extreme-valued outliers that belong to the parent population of most data in a sample and those that do not. The first type, called Gray Swans by Nassim Nicholas Taleb (often confused in the literature with Taleb's totally unknowable Black Swans), is drawn from a known distribution of the tails which can thus be extrapolated beyond the range of sampled values. However, the magnitudes and/or space-time locations of unsampled Gray Swans cannot be foretold. The second type of extreme-valued outliers, termed Dragon Kings by Didier Sornette, may in his view be sometimes predicted based on how other data in the sample behave. This intriguing prospect has recently motivated some authors to propose statistical tests capable of identifying Dragon Kings in a given random sample. Here we apply three such tests to log air permeability data measured on the faces of a Berea sandstone block and to synthetic data generated in a manner statistically consistent with these measurements. We interpret the measurements to be, and generate synthetic data that are, samples from α-stable sub-Gaussian random fields subordinated to truncated fractional Gaussian noise (tfGn). All these data have frequency distributions characterized by power-law tails with extreme-valued outliers about the tail edges.

Genotype-Specific Minimal Residual Disease Interpretation Improves Stratification in Pediatric Acute Lymphoblastic Leukemia

PubMed Central

O’Connor, David; Enshaei, Amir; Bartram, Jack; Hancock, Jeremy; Harrison, Christine J.; Hough, Rachael; Samarasinghe, Sujith; Schwab, Claire; Vora, Ajay; Wade, Rachel; Moppett, John; Moorman, Anthony V.; Goulden, Nick

2018-01-01

Purpose Minimal residual disease (MRD) and genetic abnormalities are important risk factors for outcome in acute lymphoblastic leukemia. Current risk algorithms dichotomize MRD data and do not assimilate genetics when assigning MRD risk, which reduces predictive accuracy. The aim of our study was to exploit the full power of MRD by examining it as a continuous variable and to integrate it with genetics. Patients and Methods We used a population-based cohort of 3,113 patients who were treated in UKALL2003, with a median follow-up of 7 years. MRD was evaluated by polymerase chain reaction analysis of Ig/TCR gene rearrangements, and patients were assigned to a genetic subtype on the basis of immunophenotype, cytogenetics, and fluorescence in situ hybridization. To examine response kinetics at the end of induction, we log-transformed the absolute MRD value and examined its distribution across subgroups. Results MRD was log normally distributed at the end of induction. MRD distributions of patients with distinct genetic subtypes were different (P < .001). Patients with good-risk cytogenetics demonstrated the fastest disease clearance, whereas patients with high-risk genetics and T-cell acute lymphoblastic leukemia responded more slowly. The risk of relapse was correlated with MRD kinetics, and each log reduction in disease level reduced the risk by 20% (hazard ratio, 0.80; 95% CI, 0.77 to 0.83; P < .001). Although the risk of relapse was directly proportional to the MRD level within each genetic risk group, absolute relapse rate that was associated with a specific MRD value or category varied significantly by genetic subtype. Integration of genetic subtype–specific MRD values allowed more refined risk group stratification. Conclusion A single threshold for assigning patients to an MRD risk group does not reflect the response kinetics of the different genetic subtypes. Future risk algorithms should integrate genetics with MRD to accurately identify patients with the lowest and highest risk of relapse. PMID:29131699

Stretched exponential distributions in nature and economy: ``fat tails'' with characteristic scales

NASA Astrophysics Data System (ADS)

Laherrère, J.; Sornette, D.

1998-04-01

To account quantitatively for many reported "natural" fat tail distributions in Nature and Economy, we propose the stretched exponential family as a complement to the often used power law distributions. It has many advantages, among which to be economical with only two adjustable parameters with clear physical interpretation. Furthermore, it derives from a simple and generic mechanism in terms of multiplicative processes. We show that stretched exponentials describe very well the distributions of radio and light emissions from galaxies, of US GOM OCS oilfield reserve sizes, of World, US and French agglomeration sizes, of country population sizes, of daily Forex US-Mark and Franc-Mark price variations, of Vostok (near the south pole) temperature variations over the last 400 000 years, of the Raup-Sepkoski's kill curve and of citations of the most cited physicists in the world. We also discuss its potential for the distribution of earthquake sizes and fault displacements. We suggest physical interpretations of the parameters and provide a short toolkit of the statistical properties of the stretched exponentials. We also provide a comparison with other distributions, such as the shifted linear fractal, the log-normal and the recently introduced parabolic fractal distributions.

A point hailfall classification based on hailpad measurements: The ANELFA scale

NASA Astrophysics Data System (ADS)

Dessens, J.; Berthet, C.; Sanchez, J. L.

2007-02-01

The ANELFA scale for hailfall intensity is proposed on the model of the 6-class Fujita scale for tornadoes. It is based on more than three thousand point hailfalls measured by hailpads over a 16-year period in France. The class number of a hailfall is determined by the integer value of the largest measured hailstone diameter in cm, or by equivalence with current objects: A0 to A5 for pea, grape, pigeon's egg, walnut, hen's egg, orange. The class number is followed by a plus or minus sign if the ground is significantly more or less than half-covered by hailstones respectively. When the scale is applied to the ANELFA data, a log-normal distribution is found for the class distribution, allowing the frequency determination of the upper class ever observed until now at the hailpad stations.

A detailed heterogeneous agent model for a single asset financial market with trading via an order book.

PubMed

Mota Navarro, Roberto; Larralde, Hernán

2017-01-01

We present an agent based model of a single asset financial market that is capable of replicating most of the non-trivial statistical properties observed in real financial markets, generically referred to as stylized facts. In our model agents employ strategies inspired on those used in real markets, and a realistic trade mechanism based on a double auction order book. We study the role of the distinct types of trader on the return statistics: specifically, correlation properties (or lack thereof), volatility clustering, heavy tails, and the degree to which the distribution can be described by a log-normal. Further, by introducing the practice of "profit taking", our model is also capable of replicating the stylized fact related to an asymmetry in the distribution of losses and gains.

A detailed heterogeneous agent model for a single asset financial market with trading via an order book

PubMed Central

2017-01-01

We present an agent based model of a single asset financial market that is capable of replicating most of the non-trivial statistical properties observed in real financial markets, generically referred to as stylized facts. In our model agents employ strategies inspired on those used in real markets, and a realistic trade mechanism based on a double auction order book. We study the role of the distinct types of trader on the return statistics: specifically, correlation properties (or lack thereof), volatility clustering, heavy tails, and the degree to which the distribution can be described by a log-normal. Further, by introducing the practice of “profit taking”, our model is also capable of replicating the stylized fact related to an asymmetry in the distribution of losses and gains. PMID:28245251

Observational constraints on the multiphase ISM

NASA Astrophysics Data System (ADS)

Wolfire, Mark G.

2015-03-01

In recent years we have seen a wealth of new observations and analysis that sheds light on the distribution and physical properties of various ISM phases. In particular the thermal pressure from C I (Jenkins & Tripp 2011) shows the bulk of the CNM phase with a log normal pressure distribution. It appears that thermal instability is important for phase separation, but with with a thermal pressure variation about the mean driven by turbulence. In additional, there is evidence from C I, H2, and complex molecules, of both higher and lower pressure environments. An additional ``phase`` that is of increasing interest for high z, low metallicity galaxies is the C+/H2 gas that is not traced by H I or CO. This review presents the observational evidence for the existence and physical properties of these various ISM phases.

Empirical analysis and modeling of manual turnpike tollbooths in China

NASA Astrophysics Data System (ADS)

Zhang, Hao

2017-03-01

To deal with low-level of service satisfaction at tollbooths of many turnpikes in China, we conduct an empirical study and use a queueing model to investigate performance measures. In this paper, we collect archived data from six tollbooths of a turnpike in China. Empirical analysis on vehicle's time-dependent arrival process and collector's time-dependent service time is conducted. It shows that the vehicle arrival process follows a non-homogeneous Poisson process while the collector service time follows a log-normal distribution. Further, we model the process of collecting tolls at tollbooths with MAP / PH / 1 / FCFS queue for mathematical tractability and present some numerical examples.

First Test of Stochastic Growth Theory for Langmuir Waves in Earth's Foreshock

NASA Technical Reports Server (NTRS)

Cairns, Iver H.; Robinson, P. A.

1997-01-01

This paper presents the first test of whether stochastic growth theory (SGT) can explain the detailed characteristics of Langmuir-like waves in Earth's foreshock. A period with unusually constant solar wind magnetic field is analyzed. The observed distributions P(logE) of wave fields E for two intervals with relatively constant spacecraft location (DIFF) are shown to agree well with the fundamental prediction of SGT, that P(logE) is Gaussian in log E. This stochastic growth can be accounted for semi-quantitatively in terms of standard foreshock beam parameters and a model developed for interplanetary type III bursts. Averaged over the entire period with large variations in DIFF, the P(logE) distribution is a power-law with index approximately -1; this is interpreted in terms of convolution of intrinsic, spatially varying P(logE) distributions with a probability function describing ISEE's residence time at a given DIFF. Wave data from this interval thus provide good observational evidence that SGT can sometimes explain the clumping, burstiness, persistence, and highly variable fields of the foreshock Langmuir-like waves.

First test of stochastic growth theory for Langmuir waves in Earth's foreshock

NASA Astrophysics Data System (ADS)

Cairns, Iver H.; Robinson, P. A.

This paper presents the first test of whether stochastic growth theory (SGT) can explain the detailed characteristics of Langmuir-like waves in Earth's foreshock. A period with unusually constant solar wind magnetic field is analyzed. The observed distributions P(log E) of wave fields E for two intervals with relatively constant spacecraft location (DIFF) are shown to agree well with the fundamental prediction of SGT, that P(log E) is Gaussian in log E. This stochastic growth can be accounted for semi-quantitatively in terms of standard foreshock beam parameters and a model developed for interplanetary type III bursts. Averaged over the entire period with large variations in DIFF, the P(log E) distribution is a power-law with index ˜ -1 this is interpreted in terms of convolution of intrinsic, spatially varying P(log E) distributions with a probability function describing ISEE's residence time at a given DIFF. Wave data from this interval thus provide good observational evidence that SGT can sometimes explain the clumping, burstiness, persistence, and highly variable fields of the foreshock Langmuir-like waves.

Analytical performance specifications for changes in assay bias (Δbias) for data with logarithmic distributions as assessed by effects on reference change values.

PubMed

Petersen, Per H; Lund, Flemming; Fraser, Callum G; Sölétormos, György

2016-11-01

Background The distributions of within-subject biological variation are usually described as coefficients of variation, as are analytical performance specifications for bias, imprecision and other characteristics. Estimation of specifications required for reference change values is traditionally done using relationship between the batch-related changes during routine performance, described as Δbias, and the coefficients of variation for analytical imprecision (CV A ): the original theory is based on standard deviations or coefficients of variation calculated as if distributions were Gaussian. Methods The distribution of between-subject biological variation can generally be described as log-Gaussian. Moreover, recent analyses of within-subject biological variation suggest that many measurands have log-Gaussian distributions. In consequence, we generated a model for the estimation of analytical performance specifications for reference change value, with combination of Δbias and CV A based on log-Gaussian distributions of CV I as natural logarithms. The model was tested using plasma prolactin and glucose as examples. Results Analytical performance specifications for reference change value generated using the new model based on log-Gaussian distributions were practically identical with the traditional model based on Gaussian distributions. Conclusion The traditional and simple to apply model used to generate analytical performance specifications for reference change value, based on the use of coefficients of variation and assuming Gaussian distributions for both CV I and CV A , is generally useful.

Influence of the Magnitude and Spatial Distribution of Water Storage in Aquifers on the Character of Baseflow Recessions

NASA Astrophysics Data System (ADS)

Nieber, J. L.; Li, W.

2017-12-01

The instantaneous groundwater discharge (Qgw) from a watershed is related to volume of drainable water stored (Sgw) within the watershed aquifer(s). The relation is hysteretic and the magnitude of the hysteresis is completely scale-dependent. In the research reported here we apply a previously calibrated (USGS) GSFLOW model to the simulation of surface and subsurface runoff for the Sagehen Creek watershed. This 29.3 km2 watershed is located in the eastern range of the Sierra Nevada Mountains, and most of the precipitation falls in the form of snow. The GSFLOW model is composed of a surface water and shallow subsurface flow hydrology model, PRMS, and a groundwater flow component based on MODFLOW. PRMS is a semi-distributed watershed model, very similar in character to the well-known SWAT model. The PRMS model is coupled with the MODFLOW model in that deep percolation generated within the PRMS model feeds into the MODFLOW model. The simulated baseflow recessions, plotted as -dQ/dt vs Q, show a strong dependence to watershed topography and plot concave downward. These plots show a somewhat weaker dependence on the hydrologic fluxes of evapotranspiration and recharge, with the concave downward shape maintained but somewhat modified by these hydrologic fluxes. As expected the Qgw vs Sgw relation is markedly hysteretic. The cause for this hysteresis is related to the magnitude of water stored, and also the spatial distribution of water stored in the watershed, with the antecedent storage in upland areas controlling the recession flow in late time, while the valley area dominates the recession flow in the early time. Both the minimum streamflow (Qmin ; the flow at the transition between early time and late time uninterrupted recession) and the intercept (intercept of the regression line fit to the recession data on a log-log scale) show a strong relationship with antecedent streamflows. The minimum streamflow, Qmin, is found to be a valid normalizing parameter for producing a unique normalized -dQ/dt vs. Q relation from data manifesting the effects of hysteresis. It is proposed that this normalized relation can be used to improve the performance of low-dimension dynamic models of watershed hydrology that would otherwise not account for hysteresis in Qgw vs Sgw.

The snake geothermal drilling project. Innovative approaches to geothermal exploration

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

Shervais, John W.; Evans, James P.; Liberty, Lee M.

2014-02-21

The goal of our project was to test innovative technologies using existing and new data, and to ground-truth these technologies using slim-hole core technology. The slim-hole core allowed us to understand subsurface stratigraphy and alteration in detail, and to correlate lithologies observed in core with surface based geophysical studies. Compiled data included geologic maps, volcanic vent distribution, structural maps, existing well logs and temperature gradient logs, groundwater temperatures, and geophysical surveys (resistivity, magnetics, gravity). New data included high-resolution gravity and magnetic surveys, high-resolution seismic surveys, three slimhole test wells, borehole wireline logs, lithology logs, water chemistry, alteration mineralogy, fracture distribution,more » and new thermal gradient measurements.« less

Load-Based Lower Neck Injury Criteria for Females from Rear Impact from Cadaver Experiments.

PubMed

Yoganandan, Narayan; Pintar, Frank A; Banerjee, Anjishnu

2017-05-01

The objectives of this study were to derive lower neck injury metrics/criteria and injury risk curves for the force, moment, and interaction criterion in rear impacts for females. Biomechanical data were obtained from previous intact and isolated post mortem human subjects and head-neck complexes subjected to posteroanterior accelerative loading. Censored data were used in the survival analysis model. The primary shear force, sagittal bending moment, and interaction (lower neck injury criterion, LN ic ) metrics were significant predictors of injury. The most optimal distribution was selected (Weibulll, log normal, or log logistic) using the Akaike information criterion according to the latest ISO recommendations for deriving risk curves. The Kolmogorov-Smirnov test was used to quantify robustness of the assumed parametric model. The intercepts for the interaction index were extracted from the primary risk curves. Normalized confidence interval sizes (NCIS) were reported at discrete probability levels, along with the risk curves and 95% confidence intervals. The mean force of 214 N, moment of 54 Nm, and 0.89 LN ic were associated with a five percent probability of injury. The NCIS for these metrics were 0.90, 0.95, and 0.85. These preliminary results can be used as a first step in the definition of lower neck injury criteria for women under posteroanterior accelerative loading in crashworthiness evaluations.

PHAGE FORMATION IN STAPHYLOCOCCUS MUSCAE CULTURES

PubMed Central

Price, Winston H.

1949-01-01

1. The total nucleic acid synthesized by normal and by infected S. muscae suspensions is approximately the same. This is true for either lag phase cells or log phase cells. 2. The amount of nucleic acid synthesized per cell in normal cultures increases during the lag period and remains fairly constant during log growth. 3. The amount of nucleic acid synthesized per cell by infected cells increases during the whole course of the infection. 4. Infected cells synthesize less RNA and more DNA than normal cells. The ratio of RNA/DNA is larger in lag phase cells than in log phase cells. 5. Normal cells release neither ribonucleic acid nor desoxyribonucleic acid into the medium. 6. Infected cells release both ribonucleic acid and desoxyribonucleic acid into the medium. The time and extent of release depend upon the physiological state of the cells. 7. Infected lag phase cells may or may not show an increased RNA content. They release RNA, but not DNA, into the medium well before observable cellular lysis and before any virus is liberated. At virus liberation, the cell RNA content falls to a value below that initially present, while DNA, which increased during infection falls to approximately the original value. 8. Infected log cells show a continuous loss of cell RNA and a loss of DNA a short time after infection. At the time of virus liberation the cell RNA value is well below that initially present and the cells begin to lyse. PMID:18139006

Generating log-normal mock catalog of galaxies in redshift space

NASA Astrophysics Data System (ADS)

Agrawal, Aniket; Makiya, Ryu; Chiang, Chi-Ting; Jeong, Donghui; Saito, Shun; Komatsu, Eiichiro

2017-10-01

We present a public code to generate a mock galaxy catalog in redshift space assuming a log-normal probability density function (PDF) of galaxy and matter density fields. We draw galaxies by Poisson-sampling the log-normal field, and calculate the velocity field from the linearised continuity equation of matter fields, assuming zero vorticity. This procedure yields a PDF of the pairwise velocity fields that is qualitatively similar to that of N-body simulations. We check fidelity of the catalog, showing that the measured two-point correlation function and power spectrum in real space agree with the input precisely. We find that a linear bias relation in the power spectrum does not guarantee a linear bias relation in the density contrasts, leading to a cross-correlation coefficient of matter and galaxies deviating from unity on small scales. We also find that linearising the Jacobian of the real-to-redshift space mapping provides a poor model for the two-point statistics in redshift space. That is, non-linear redshift-space distortion is dominated by non-linearity in the Jacobian. The power spectrum in redshift space shows a damping on small scales that is qualitatively similar to that of the well-known Fingers-of-God (FoG) effect due to random velocities, except that the log-normal mock does not include random velocities. This damping is a consequence of non-linearity in the Jacobian, and thus attributing the damping of the power spectrum solely to FoG, as commonly done in the literature, is misleading.

Exponential series approaches for nonparametric graphical models

NASA Astrophysics Data System (ADS)

Janofsky, Eric

Markov Random Fields (MRFs) or undirected graphical models are parsimonious representations of joint probability distributions. This thesis studies high-dimensional, continuous-valued pairwise Markov Random Fields. We are particularly interested in approximating pairwise densities whose logarithm belongs to a Sobolev space. For this problem we propose the method of exponential series which approximates the log density by a finite-dimensional exponential family with the number of sufficient statistics increasing with the sample size. We consider two approaches to estimating these models. The first is regularized maximum likelihood. This involves optimizing the sum of the log-likelihood of the data and a sparsity-inducing regularizer. We then propose a variational approximation to the likelihood based on tree-reweighted, nonparametric message passing. This approximation allows for upper bounds on risk estimates, leverages parallelization and is scalable to densities on hundreds of nodes. We show how the regularized variational MLE may be estimated using a proximal gradient algorithm. We then consider estimation using regularized score matching. This approach uses an alternative scoring rule to the log-likelihood, which obviates the need to compute the normalizing constant of the distribution. For general continuous-valued exponential families, we provide parameter and edge consistency results. As a special case we detail a new approach to sparse precision matrix estimation which has statistical performance competitive with the graphical lasso and computational performance competitive with the state-of-the-art glasso algorithm. We then describe results for model selection in the nonparametric pairwise model using exponential series. The regularized score matching problem is shown to be a convex program; we provide scalable algorithms based on consensus alternating direction method of multipliers (ADMM) and coordinate-wise descent. We use simulations to compare our method to others in the literature as well as the aforementioned TRW estimator.

Novel bayes factors that capture expert uncertainty in prior density specification in genetic association studies.

PubMed

Spencer, Amy V; Cox, Angela; Lin, Wei-Yu; Easton, Douglas F; Michailidou, Kyriaki; Walters, Kevin

2015-05-01

Bayes factors (BFs) are becoming increasingly important tools in genetic association studies, partly because they provide a natural framework for including prior information. The Wakefield BF (WBF) approximation is easy to calculate and assumes a normal prior on the log odds ratio (logOR) with a mean of zero. However, the prior variance (W) must be specified. Because of the potentially high sensitivity of the WBF to the choice of W, we propose several new BF approximations with logOR ∼N(0,W), but allow W to take a probability distribution rather than a fixed value. We provide several prior distributions for W which lead to BFs that can be calculated easily in freely available software packages. These priors allow a wide range of densities for W and provide considerable flexibility. We examine some properties of the priors and BFs and show how to determine the most appropriate prior based on elicited quantiles of the prior odds ratio (OR). We show by simulation that our novel BFs have superior true-positive rates at low false-positive rates compared to those from both P-value and WBF analyses across a range of sample sizes and ORs. We give an example of utilizing our BFs to fine-map the CASP8 region using genotype data on approximately 46,000 breast cancer case and 43,000 healthy control samples from the Collaborative Oncological Gene-environment Study (COGS) Consortium, and compare the single-nucleotide polymorphism ranks to those obtained using WBFs and P-values from univariate logistic regression. © 2015 The Authors. *Genetic Epidemiology published by Wiley Periodicals, Inc.

Statistical characterization of thermal plumes in turbulent thermal convection

NASA Astrophysics Data System (ADS)

Zhou, Sheng-Qi; Xie, Yi-Chao; Sun, Chao; Xia, Ke-Qing

2016-09-01

We report an experimental study on the statistical properties of the thermal plumes in turbulent thermal convection. A method has been proposed to extract the basic characteristics of thermal plumes from temporal temperature measurement inside the convection cell. It has been found that both plume amplitude A and cap width w , in a time domain, are approximately in the log-normal distribution. In particular, the normalized most probable front width is found to be a characteristic scale of thermal plumes, which is much larger than the thermal boundary layer thickness. Over a wide range of the Rayleigh number, the statistical characterizations of the thermal fluctuations of plumes, and the turbulent background, the plume front width and plume spacing have been discussed and compared with the theoretical predictions and morphological observations. For the most part good agreements have been found with the direct observations.

Body Fat Distribution Ratios and Obstructive Sleep Apnea Severity in Youth With Obesity.

PubMed

Glicksman, Amy; Hadjiyannakis, Stasia; Barrowman, Nicholas; Walker, Scott; Hoey, Lynda; Katz, Sherri Lynne

2017-04-15

Obesity and regional fat distribution, measured by neck fat mass percentage using dual-energy X-ray absorptiometry (DXA), correlate with obstructive sleep apnea (OSA) severity in adults. In obese children, neck-to-waist-circumference ratio predicts OSA. This study examined associations between body fat percentage and distribution and sleep-disordered breathing (SDB) severity in obese youth, measured with DXA. Cross-sectional retrospective study conducted at a tertiary children's hospital. Participants were aged 6 to 18 years with obesity (body mass index [BMI] > 99th percentile [BMI z-score 2.35] or > 95th percentile with comorbidity). They underwent polysomnography and DXA to quantify body fat percentage and distribution ratios (neck-to-abdominal fat percentage [NAF % ratio]). SDB was defined as apnea-hypopnea index (AHI) > 5 and OSA as obstructive AHI (OAHI) > 1 event/h. Relationships of BMI z-score and NAF % ratio to log AHI and log OAHI were evaluated. Thirty individuals participated; 18 male; median age 14.1 years. Twenty-four individuals had BMI z-scores > 2.35. Ten had AHI > 5 events/h. NAF % ratio was significantly associated with log AHI in males and with log OAHI in all, whereas total fat mass percent was not. The association between log OAHI and NAF % ratio was significant in males, but not females. NAF % ratio was significantly associated with log OAHI in those with BMI z-score above 2.35. NAF % ratio was associated with OSA severity in males and youth with BMI > 99th percentile; however, total fat mass percentage was not, suggesting that body fat distribution is associated with OSA risk in youth. © 2017 American Academy of Sleep Medicine

Multiple imputation in the presence of non-normal data.

PubMed

Lee, Katherine J; Carlin, John B

2017-02-20

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

Chapter 9:Red maple lumber resources for glued-laminated timber beams

Treesearch

John J. Janowiak; Harvey B. Manbeck; Roland Hernandez; Russell C. Moody

2005-01-01

This chapter evaluates the performance of red maple glulam beams made from two distinctly different lumber resources: 1. logs sawn using practices normally used for hardwood appearance lumber recovery; and 2. lower-grade, smaller-dimension lumber primarily obtained from residual log cants.

Actual distribution of Cronobacter spp. in industrial batches of powdered infant formula and consequences for performance of sampling strategies.

PubMed

Jongenburger, I; Reij, M W; Boer, E P J; Gorris, L G M; Zwietering, M H

2011-11-15

The actual spatial distribution of microorganisms within a batch of food influences the results of sampling for microbiological testing when this distribution is non-homogeneous. In the case of pathogens being non-homogeneously distributed, it markedly influences public health risk. This study investigated the spatial distribution of Cronobacter spp. in powdered infant formula (PIF) on industrial batch-scale for both a recalled batch as well a reference batch. Additionally, local spatial occurrence of clusters of Cronobacter cells was assessed, as well as the performance of typical sampling strategies to determine the presence of the microorganisms. The concentration of Cronobacter spp. was assessed in the course of the filling time of each batch, by taking samples of 333 g using the most probable number (MPN) enrichment technique. The occurrence of clusters of Cronobacter spp. cells was investigated by plate counting. From the recalled batch, 415 MPN samples were drawn. The expected heterogeneous distribution of Cronobacter spp. could be quantified from these samples, which showed no detectable level (detection limit of -2.52 log CFU/g) in 58% of samples, whilst in the remainder concentrations were found to be between -2.52 and 2.75 log CFU/g. The estimated average concentration in the recalled batch was -2.78 log CFU/g and a standard deviation of 1.10 log CFU/g. The estimated average concentration in the reference batch was -4.41 log CFU/g, with 99% of the 93 samples being below the detection limit. In the recalled batch, clusters of cells occurred sporadically in 8 out of 2290 samples of 1g taken. The two largest clusters contained 123 (2.09 log CFU/g) and 560 (2.75 log CFU/g) cells. Various sampling strategies were evaluated for the recalled batch. Taking more and smaller samples and keeping the total sampling weight constant, considerably improved the performance of the sampling plans to detect such a type of contaminated batch. Compared to random sampling, stratified random sampling improved the probability to detect the heterogeneous contamination. Copyright © 2011 Elsevier B.V. All rights reserved.

Baseline MNREAD Measures for Normally Sighted Subjects From Childhood to Old Age

PubMed Central

Calabrèse, Aurélie; Cheong, Allen M. Y.; Cheung, Sing-Hang; He, Yingchen; Kwon, MiYoung; Mansfield, J. Stephen; Subramanian, Ahalya; Yu, Deyue; Legge, Gordon E.

2016-01-01

Purpose The continuous-text reading-acuity test MNREAD is designed to measure the reading performance of people with normal and low vision. This test is used to estimate maximum reading speed (MRS), critical print size (CPS), reading acuity (RA), and the reading accessibility index (ACC). Here we report the age dependence of these measures for normally sighted individuals, providing baseline data for MNREAD testing. Methods We analyzed MNREAD data from 645 normally sighted participants ranging in age from 8 to 81 years. The data were collected in several studies conducted by different testers and at different sites in our research program, enabling evaluation of robustness of the test. Results Maximum reading speed and reading accessibility index showed a trilinear dependence on age: first increasing from 8 to 16 years (MRS: 140–200 words per minute [wpm]; ACC: 0.7–1.0); then stabilizing in the range of 16 to 40 years (MRS: 200 ± 25 wpm; ACC: 1.0 ± 0.14); and decreasing to 175 wpm and 0.88 by 81 years. Critical print size was constant from 8 to 23 years (0.08 logMAR), increased slowly until 68 years (0.21 logMAR), and then more rapidly until 81 years (0.34 logMAR). logMAR reading acuity improved from −0.1 at 8 years to −0.18 at 16 years, then gradually worsened to −0.05 at 81 years. Conclusions We found a weak dependence of the MNREAD parameters on age in normal vision. In broad terms, MNREAD performance exhibits differences between three age groups: children 8 to 16 years, young adults 16 to 40 years, and middle-aged to older adults >40 years. PMID:27442222

The distribution of dry matter growth between shoot and roots in loblolly pine

Treesearch

F. Thomas Ledig; F. Herbert Bormann; Karl F. Wenger

1970-01-01

The allometric relationship, log (y) = a + k•log (x)-where x is one plant organ (e g., dry weight of roots) and y is another (e.g., dry weight of shoot)-was used to study the relative distribution of growth within loblolly pine seedlings. The relative...

A CORRELATION BETWEEN RADIATION TOLERANCE AND NUCLEAR SURFACE AREA

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

Iversen, S.

1962-09-22

Sparrow and Miksche (Science, 134:282) determined the dose (r/day) required to produce severe growth inhibition in 23 species of plants and found a linear relationship between log nuclear volume and log dose. The following equations hold for 6 species: log nuclear volume - 4.42 -0.82 log dose and log nuclear volume = 1.66 + 0.66 log (DNA content). If all the nuclear DNA is distributed in two peripheral zones, the equations also hold: 2(log nuclear surface area) - 1.33(log nuclear volume) - 2.21 + 0.88 log(DNA content) and 5.88-- 1.09 log dose. For the 23 species, the equation was obtained:more » 2(log nuclear surface area) = 5.41 -- 0.97 log dose. All the slopes are close to the expected value of 1.00. (D.L.C.)« less

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%.

Stylized facts in internal rates of return on stock index and its derivative transactions

NASA Astrophysics Data System (ADS)

Pichl, Lukáš; Kaizoji, Taisei; Yamano, Takuya

2007-08-01

Universal features in stock markets and their derivative markets are studied by means of probability distributions in internal rates of return on buy and sell transaction pairs. Unlike the stylized facts in normalized log returns, the probability distributions for such single asset encounters incorporate the time factor by means of the internal rate of return, defined as the continuous compound interest. Resulting stylized facts are shown in the probability distributions derived from the daily series of TOPIX, S & P 500 and FTSE 100 index close values. The application of the above analysis to minute-tick data of NIKKEI 225 and its futures market, respectively, reveals an interesting difference in the behavior of the two probability distributions, in case a threshold on the minimal duration of the long position is imposed. It is therefore suggested that the probability distributions of the internal rates of return could be used for causality mining between the underlying and derivative stock markets. The highly specific discrete spectrum, which results from noise trader strategies as opposed to the smooth distributions observed for fundamentalist strategies in single encounter transactions may be useful in deducing the type of investment strategy from trading revenues of small portfolio investors.

Distribution of Plasmoids in Post-Coronal Mass Ejection Current Sheets

NASA Astrophysics Data System (ADS)

Bhattacharjee, A.; Guo, L.; Huang, Y.

2013-12-01

Recently, the fragmentation of a current sheet in the high-Lundquist-number regime caused by the plasmoid instability has been proposed as a possible mechanism for fast reconnection. In this work, we investigate this scenario by comparing the distribution of plasmoids obtained from Large Angle and Spectrometric Coronagraph (LASCO) observational data of a coronal mass ejection event with a resistive magnetohydrodynamic simulation of a similar event. The LASCO/C2 data are analyzed using visual inspection, whereas the numerical data are analyzed using both visual inspection and a more precise topological method. Contrasting the observational data with numerical data analyzed with both methods, we identify a major limitation of the visual inspection method, due to the difficulty in resolving smaller plasmoids. This result raises questions about reports of log-normal distributions of plasmoids and other coherent features in the recent literature. Based on nonlinear scaling relations of the plasmoid instability, we infer a lower bound on the current sheet width, assuming the underlying mechanism of current sheet broadening is resistive diffusion.

Photoballistics of volcanic jet activity at Stromboli, Italy

NASA Technical Reports Server (NTRS)

Chouet, B.; Hamisevicz, N.; Mcgetchin, T. R.

1974-01-01

Two night eruptions of the volcano Stromboli were studied through 70-mm photography. Single-camera techniques were used. Particle sphericity, constant velocity in the frame, and radial symmetry were assumed. Properties of the particulate phase found through analysis include: particle size, velocity, total number of particles ejected, angular dispersion and distribution in the jet, time variation of particle size and apparent velocity distribution, averaged volume flux, and kinetic energy carried by the condensed phase. The frequency distributions of particle size and apparent velocities are found to be approximately log normal. The properties of the gas phase were inferred from the fact that it was the transporting medium for the condensed phase. Gas velocity and time variation, volume flux of gas, dynamic pressure, mass erupted, and density were estimated. A CO2-H2O mixture is possible for the observed eruptions. The flow was subsonic. Velocity variations may be explained by an organ pipe resonance. Particle collimation may be produced by a Magnus effect.

Radiation exposure assessment for portsmouth naval shipyard health studies.

PubMed

Daniels, R D; Taulbee, T D; Chen, P

2004-01-01

Occupational radiation exposures of 13,475 civilian nuclear shipyard workers were investigated as part of a retrospective mortality study. Estimates of annual, cumulative and collective doses were tabulated for future dose-response analysis. Record sets were assembled and amended through range checks, examination of distributions and inspection. Methods were developed to adjust for administrative overestimates and dose from previous employment. Uncertainties from doses below the recording threshold were estimated. Low-dose protracted radiation exposures from submarine overhaul and repair predominated. Cumulative doses are best approximated by a hybrid log-normal distribution with arithmetic mean and median values of 20.59 and 3.24 mSv, respectively. The distribution is highly skewed with more than half the workers having cumulative doses <10 mSv and >95% having doses <100 mSv. The maximum cumulative dose is estimated at 649.39 mSv from 15 person-years of exposure. The collective dose was 277.42 person-Sv with 96.8% attributed to employment at Portsmouth Naval Shipyard.

Rank Dynamics

NASA Astrophysics Data System (ADS)

Gershenson, Carlos

Studies of rank distributions have been popular for decades, especially since the work of Zipf. For example, if we rank words of a given language by use frequency (most used word in English is 'the', rank 1; second most common word is 'of', rank 2), the distribution can be approximated roughly with a power law. The same applies for cities (most populated city in a country ranks first), earthquakes, metabolism, the Internet, and dozens of other phenomena. We recently proposed ``rank diversity'' to measure how ranks change in time, using the Google Books Ngram dataset. Studying six languages between 1800 and 2009, we found that the rank diversity curves of languages are universal, adjusted with a sigmoid on log-normal scale. We are studying several other datasets (sports, economies, social systems, urban systems, earthquakes, artificial life). Rank diversity seems to be universal, independently of the shape of the rank distribution. I will present our work in progress towards a general description of the features of rank change in time, along with simple models which reproduce it

Relationship between neighbourhood socioeconomic position and neighbourhood public green space availability: An environmental inequality analysis in a large German city applying generalized linear models.

PubMed

Schüle, Steffen Andreas; Gabriel, Katharina M A; Bolte, Gabriele

2017-06-01

The environmental justice framework states that besides environmental burdens also resources may be social unequally distributed both on the individual and on the neighbourhood level. This ecological study investigated whether neighbourhood socioeconomic position (SEP) was associated with neighbourhood public green space availability in a large German city with more than 1 million inhabitants. Two different measures were defined for green space availability. Firstly, percentage of green space within neighbourhoods was calculated with the additional consideration of various buffers around the boundaries. Secondly, percentage of green space was calculated based on various radii around the neighbourhood centroid. An index of neighbourhood SEP was calculated with principal component analysis. Log-gamma regression from the group of generalized linear models was applied in order to consider the non-normal distribution of the response variable. All models were adjusted for population density. Low neighbourhood SEP was associated with decreasing neighbourhood green space availability including 200m up to 1000m buffers around the neighbourhood boundaries. Low neighbourhood SEP was also associated with decreasing green space availability based on catchment areas measured from neighbourhood centroids with different radii (1000m up to 3000 m). With an increasing radius the strength of the associations decreased. Social unequally distributed green space may amplify environmental health inequalities in an urban context. Thus, the identification of vulnerable neighbourhoods and population groups plays an important role for epidemiological research and healthy city planning. As a methodical aspect, log-gamma regression offers an adequate parametric modelling strategy for positively distributed environmental variables. Copyright © 2017 Elsevier GmbH. All rights reserved.

Log N-log S in inconclusive

NASA Technical Reports Server (NTRS)

Klebesadel, R. W.; Fenimore, E. E.; Laros, J.

1983-01-01

The log N-log S data acquired by the Pioneer Venus Orbiter Gamma Burst Detector (PVO) are presented and compared to similar data from the Soviet KONUS experiment. Although the PVO data are consistent with and suggestive of a -3/2 power law distribution, the results are not adequate at this state of observations to differentiate between a -3/2 and a -1 power law slope.

Lumber yield from sitka spruce in southeastern Alaska.

Treesearch

Paul H. Lane; Richard O. Jr. Woodfin; John W. Henley; Marlin E. Plank

1972-01-01

A representative sample of 400 mature, Sitka spruce, sawtimber trees from throughout southeastern Alaska produced 1,009 commercial saw logs that were sawn at Wrangell, Alaska. The distribution of these saw logs by log grade was: 3 percent Select, 7 percent No. 1, 43 percent No. 2, and 47 percent No. 3. The total net log scale (Scribner) was 774,000 board feet. A total...

Body fat assessed from body density and estimated from skinfold thickness in normal children and children with cystic fibrosis.

PubMed

Johnston, J L; Leong, M S; Checkland, E G; Zuberbuhler, P C; Conger, P R; Quinney, H A

1988-12-01

Body density and skinfold thickness at four sites were measured in 140 normal boys, 168 normal girls, and 6 boys and 7 girls with cystic fibrosis, all aged 8-14 y. Prediction equations for the normal boys and girls for the estimation of body-fat content from skinfold measurements were derived from linear regression of body density vs the log of the sum of the skinfold thickness. The relationship between body density and the log of the sum of the skinfold measurements differed from normal for the boys and girls with cystic fibrosis because of their high body density even though their large residual volume was corrected for. However the sum of skinfold measurements in the children with cystic fibrosis did not differ from normal. Thus body fat percent of these children with cystic fibrosis was underestimated when calculated from body density and invalid when calculated from skinfold thickness.

Narrow log-periodic modulations in non-Markovian random walks

NASA Astrophysics Data System (ADS)

Diniz, R. M. B.; Cressoni, J. C.; da Silva, M. A. A.; Mariz, A. M.; de Araújo, J. M.

2017-12-01

What are the necessary ingredients for log-periodicity to appear in the dynamics of a random walk model? Can they be subtle enough to be overlooked? Previous studies suggest that long-range damaged memory and negative feedback together are necessary conditions for the emergence of log-periodic oscillations. The role of negative feedback would then be crucial, forcing the system to change direction. In this paper we show that small-amplitude log-periodic oscillations can emerge when the system is driven by positive feedback. Due to their very small amplitude, these oscillations can easily be mistaken for numerical finite-size effects. The models we use consist of discrete-time random walks with strong memory correlations where the decision process is taken from memory profiles based either on a binomial distribution or on a delta distribution. Anomalous superdiffusive behavior and log-periodic modulations are shown to arise in the large time limit for convenient choices of the models parameters.

Well log characterization of natural gas-hydrates

USGS Publications Warehouse

Collett, Timothy S.; Lee, Myung W.

2012-01-01

In the last 25 years there have been significant advancements in the use of well-logging tools to acquire detailed information on the occurrence of gas hydrates in nature: whereas wireline electrical resistivity and acoustic logs were formerly used to identify gas-hydrate occurrences in wells drilled in Arctic permafrost environments, more advanced wireline and logging-while-drilling (LWD) tools are now routinely used to examine the petrophysical nature of gas-hydrate reservoirs and the distribution and concentration of gas hydrates within various complex reservoir systems. Resistivity- and acoustic-logging tools are the most widely used for estimating the gas-hydrate content (i.e., reservoir saturations) in various sediment types and geologic settings. Recent integrated sediment coring and well-log studies have confirmed that electrical-resistivity and acoustic-velocity data can yield accurate gas-hydrate saturations in sediment grain-supported (isotropic) systems such as sand reservoirs, but more advanced log-analysis models are required to characterize gas hydrate in fractured (anisotropic) reservoir systems. New well-logging tools designed to make directionally oriented acoustic and propagation-resistivity log measurements provide the data needed to analyze the acoustic and electrical anisotropic properties of both highly interbedded and fracture-dominated gas-hydrate reservoirs. Advancements in nuclear magnetic resonance (NMR) logging and wireline formation testing (WFT) also allow for the characterization of gas hydrate at the pore scale. Integrated NMR and formation testing studies from northern Canada and Alaska have yielded valuable insight into how gas hydrates are physically distributed in sediments and the occurrence and nature of pore fluids(i.e., free water along with clay- and capillary-bound water) in gas-hydrate-bearing reservoirs. Information on the distribution of gas hydrate at the pore scale has provided invaluable insight on the mechanisms controlling the formation and occurrence of gas hydrate in nature along with data on gas-hydrate reservoir properties (i.e., porosities and permeabilities) needed to accurately predict gas production rates for various gas-hydrate production schemes.

Evaluating the performance of the quick CSF method in detecting contrast sensitivity function changes

PubMed Central

Hou, Fang; Lesmes, Luis Andres; Kim, Woojae; Gu, Hairong; Pitt, Mark A.; Myung, Jay I.; Lu, Zhong-Lin

2016-01-01

The contrast sensitivity function (CSF) has shown promise as a functional vision endpoint for monitoring the changes in functional vision that accompany eye disease or its treatment. However, detecting CSF changes with precision and efficiency at both the individual and group levels is very challenging. By exploiting the Bayesian foundation of the quick CSF method (Lesmes, Lu, Baek, & Albright, 2010), we developed and evaluated metrics for detecting CSF changes at both the individual and group levels. A 10-letter identification task was used to assess the systematic changes in the CSF measured in three luminance conditions in 112 naïve normal observers. The data from the large sample allowed us to estimate the test–retest reliability of the quick CSF procedure and evaluate its performance in detecting CSF changes at both the individual and group levels. The test–retest reliability reached 0.974 with 50 trials. In 50 trials, the quick CSF method can detect a medium 0.30 log unit area under log CSF change with 94.0% accuracy at the individual observer level. At the group level, a power analysis based on the empirical distribution of CSF changes from the large sample showed that a very small area under log CSF change (0.025 log unit) could be detected by the quick CSF method with 112 observers and 50 trials. These results make it plausible to apply the method to monitor the progression of visual diseases or treatment effects on individual patients and greatly reduce the time, sample size, and costs in clinical trials at the group level. PMID:27120074

Application of ozonated dry ice (ALIGAL™ Blue Ice) for packaging and transport in the food industry.

PubMed

Fratamico, Pina M; Juneja, Vijay; Annous, Bassam A; Rasanayagam, Vasuhi; Sundar, M; Braithwaite, David; Fisher, Steven

2012-05-01

Dry ice is used by meat and poultry processors for temperature reduction during processing and for temperature maintenance during transportation. ALIGAL™ Blue Ice (ABI), which combines the antimicrobial effect of ozone (O(3)) along with the high cooling capacity of dry ice, was investigated for its effect on bacterial reduction in air, in liquid, and on food and glass surfaces. Through proprietary means, O(3) was introduced to produce dry ice pellets to a concentration of 20 parts per million (ppm) by total weight. The ABI sublimation rate was similar to that of dry ice pellets under identical conditions, and ABI was able to hold the O(3) concentration throughout the normal shelf life of the product. Challenge studies were performed using different microorganisms, including E. coli, Campylobacter jejuni, Salmonella, and Listeria, that are critical to food safety. ABI showed significant (P < 0.05) microbial reduction during bioaerosol contamination (up to 5-log reduction of E. coli and Listeria), on chicken breast (approximately 1.3-log reduction of C. jejuni), on contact surfaces (approximately 3.9 log reduction of C. jejuni), and in liquid (2-log reduction of C. jejuni). Considering the stability of O(3), ease of use, and antimicrobial efficacy against foodborne pathogens, our results suggest that ABI is a better alternative, especially for meat and poultry processors, as compared to dry ice. Further, ABI can potentially serve as an additional processing hurdle to guard against pathogens during processing, transportation, distribution, and/or storage. © 2012 Institute of Food Technologists®

Correlation of serum cartilage oligomeric matrix protein (COMP) and interleukin-16 (IL-16) levels with disease severity in primary knee osteoarthritis: A pilot study in a Malaysian population.

PubMed

Das Gupta, Esha; Ng, Wei Ren; Wong, Shew Fung; Bhurhanudeen, Abdul Kareem; Yeap, Swan Sim

2017-01-01

The aim of this study was to investigate the correlations between serum cartilage oligomeric matrix protein (COMP), interleukin-16 (IL-16) and different grades of knee osteoarthritis (KOA) in Malaysian subjects. Ninety subjects were recruited comprising 30 with Kellgren-Lawrence (K-L) grade 2 KOA, 27 with K-L grade 3 KOA, 7 with grade 4 KOA, and 30 healthy controls. All subjects completed the Western Ontario and McMaster Universities Arthritis Index (WOMAC) questionnaire. Serum COMP and IL-16 levels were measured using ELISA and their values log transformed to ensure a normal distribution. There was no significant differences in levels of log serum COMP and IL-16 between healthy controls and KOA patients. There were no significant differences in the log serum COMP and IL-16 levels within the different K-L grades in the KOA patients. In KOA patients, log serum IL-16 levels significantly correlated with the WOMAC score (p = 0.001) and its subscales, pain (p = 0.005), stiffness (p = 0.019) and physical function (p<0.0001). Serum IL-16 levels were significantly higher in Malaysian Indians compared to Malays and Chinese (p = 0.024). In this multi-ethnic Malaysian population, there was no difference in serum COMP and IL-16 levels between healthy controls and patients with KOA, nor was there any difference in serum COMP or IL-16 levels across the various K-L grades of KOA. However, there were significant inter-racial differences in serum IL-16 levels.

Proliferation and apoptosis in malignant and normal cells in B-cell non-Hodgkin's lymphomas.

PubMed Central

Stokke, T.; Holte, H.; Smedshammer, L.; Smeland, E. B.; Kaalhus, O.; Steen, H. B.

1998-01-01

We have examined apoptosis and proliferation in lymph node cell suspensions from patients with B-cell non-Hodgkin's lymphoma using flow cytometry. A method was developed which allowed estimation of the fractions of apoptotic cells and cells in the S-phase of the cell cycle simultaneously with tumour-characteristic light chain expression. Analysis of the tumour S-phase fraction and the tumour apoptotic fraction in lymph node cell suspensions from 95 B-cell non-Hodgkin's lymphoma (NHL) patients revealed a non-normal distribution for both parameters. The median fraction of apoptotic tumour cells was 1.1% (25 percentiles 0.5%, 2.7%). In the same samples, the median fraction of apoptotic normal cells was higher than for the tumour cells (1.9%; 25 percentiles 0.7%, 4.0%; P = 0.03). The median fraction of tumour cells in S-phase was 1.4% (25 percentiles 0.8%, 4.8%), the median fraction of normal cells in S-phase was significantly lower than for the tumour cells (1.0%; 25 percentiles 0.6%, 1.9%; P = 0.004). When the number of cases was plotted against the logarithm of the S-phase fraction of the tumour cells, a distribution with two Gaussian peaks was needed to fit the data. One peak was centred around an S-phase fraction of 0.9%; the other was centred around 7%. These peaks were separated by a valley at approximately 3%, indicating that the S-phase fraction in NHL can be classified as 'low' (< 3%) or 'high' (> 3%), independent of the median S-phase fraction. The apoptotic fractions were log-normally distributed. The median apoptotic fraction was higher (1.5%) in the 'high' S-phase group than in the 'low' S-phase group (0.8%; P = 0.02). However, there was no significant correlation between the two parameters (P > 0.05). PMID:9667654

Demography-based adaptive network model reproduces the spatial organization of human linguistic groups

NASA Astrophysics Data System (ADS)

Capitán, José A.; Manrubia, Susanna

2015-12-01

The distribution of human linguistic groups presents a number of interesting and nontrivial patterns. The distributions of the number of speakers per language and the area each group covers follow log-normal distributions, while population and area fulfill an allometric relationship. The topology of networks of spatial contacts between different linguistic groups has been recently characterized, showing atypical properties of the degree distribution and clustering, among others. Human demography, spatial conflicts, and the construction of networks of contacts between linguistic groups are mutually dependent processes. Here we introduce an adaptive network model that takes all of them into account and successfully reproduces, using only four model parameters, not only those features of linguistic groups already described in the literature, but also correlations between demographic and topological properties uncovered in this work. Besides their relevance when modeling and understanding processes related to human biogeography, our adaptive network model admits a number of generalizations that broaden its scope and make it suitable to represent interactions between agents based on population dynamics and competition for space.

Demography-based adaptive network model reproduces the spatial organization of human linguistic groups.

PubMed

Capitán, José A; Manrubia, Susanna

2015-12-01

The distribution of human linguistic groups presents a number of interesting and nontrivial patterns. The distributions of the number of speakers per language and the area each group covers follow log-normal distributions, while population and area fulfill an allometric relationship. The topology of networks of spatial contacts between different linguistic groups has been recently characterized, showing atypical properties of the degree distribution and clustering, among others. Human demography, spatial conflicts, and the construction of networks of contacts between linguistic groups are mutually dependent processes. Here we introduce an adaptive network model that takes all of them into account and successfully reproduces, using only four model parameters, not only those features of linguistic groups already described in the literature, but also correlations between demographic and topological properties uncovered in this work. Besides their relevance when modeling and understanding processes related to human biogeography, our adaptive network model admits a number of generalizations that broaden its scope and make it suitable to represent interactions between agents based on population dynamics and competition for space.

Effect of rapid thermal annealing temperature on the dispersion of Si nanocrystals in SiO2 matrix

NASA Astrophysics Data System (ADS)

Saxena, Nupur; Kumar, Pragati; Gupta, Vinay

2015-05-01

Effect of rapid thermal annealing temperature on the dispersion of silicon nanocrystals (Si-NC's) embedded in SiO2 matrix grown by atom beam sputtering (ABS) method is reported. The dispersion of Si NCs in SiO2 is an important issue to fabricate high efficiency devices based on Si-NC's. The transmission electron microscopy studies reveal that the precipitation of excess silicon is almost uniform and the particles grow in almost uniform size upto 850 °C. The size distribution of the particles broadens and becomes bimodal as the temperature is increased to 950 °C. This suggests that by controlling the annealing temperature, the dispersion of Si-NC's can be controlled. The results are supported by selected area diffraction (SAED) studies and micro photoluminescence (PL) spectroscopy. The discussion of effect of particle size distribution on PL spectrum is presented based on tight binding approximation (TBA) method using Gaussian and log-normal distribution of particles. The study suggests that the dispersion and consequently emission energy varies as a function of particle size distribution and that can be controlled by annealing parameters.

Application of the LSQR algorithm in non-parametric estimation of aerosol size distribution

NASA Astrophysics Data System (ADS)

He, Zhenzong; Qi, Hong; Lew, Zhongyuan; Ruan, Liming; Tan, Heping; Luo, Kun

2016-05-01

Based on the Least Squares QR decomposition (LSQR) algorithm, the aerosol size distribution (ASD) is retrieved in non-parametric approach. The direct problem is solved by the Anomalous Diffraction Approximation (ADA) and the Lambert-Beer Law. An optimal wavelength selection method is developed to improve the retrieval accuracy of the ASD. The proposed optimal wavelength set is selected by the method which can make the measurement signals sensitive to wavelength and decrease the degree of the ill-condition of coefficient matrix of linear systems effectively to enhance the anti-interference ability of retrieval results. Two common kinds of monomodal and bimodal ASDs, log-normal (L-N) and Gamma distributions, are estimated, respectively. Numerical tests show that the LSQR algorithm can be successfully applied to retrieve the ASD with high stability in the presence of random noise and low susceptibility to the shape of distributions. Finally, the experimental measurement ASD over Harbin in China is recovered reasonably. All the results confirm that the LSQR algorithm combined with the optimal wavelength selection method is an effective and reliable technique in non-parametric estimation of ASD.

Multiplicative processes in visual cognition

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

A review of statistical estimators for risk-adjusted length of stay: analysis of the Australian and new Zealand Intensive Care Adult Patient Data-Base, 2008-2009.

PubMed

Moran, John L; Solomon, Patricia J

2012-05-16

For the analysis of length-of-stay (LOS) data, which is characteristically right-skewed, a number of statistical estimators have been proposed as alternatives to the traditional ordinary least squares (OLS) regression with log dependent variable. Using a cohort of patients identified in the Australian and New Zealand Intensive Care Society Adult Patient Database, 2008-2009, 12 different methods were used for estimation of intensive care (ICU) length of stay. These encompassed risk-adjusted regression analysis of firstly: log LOS using OLS, linear mixed model [LMM], treatment effects, skew-normal and skew-t models; and secondly: unmodified (raw) LOS via OLS, generalised linear models [GLMs] with log-link and 4 different distributions [Poisson, gamma, negative binomial and inverse-Gaussian], extended estimating equations [EEE] and a finite mixture model including a gamma distribution. A fixed covariate list and ICU-site clustering with robust variance were utilised for model fitting with split-sample determination (80%) and validation (20%) data sets, and model simulation was undertaken to establish over-fitting (Copas test). Indices of model specification using Bayesian information criterion [BIC: lower values preferred] and residual analysis as well as predictive performance (R2, concordance correlation coefficient (CCC), mean absolute error [MAE]) were established for each estimator. The data-set consisted of 111663 patients from 131 ICUs; with mean(SD) age 60.6(18.8) years, 43.0% were female, 40.7% were mechanically ventilated and ICU mortality was 7.8%. ICU length-of-stay was 3.4(5.1) (median 1.8, range (0.17-60)) days and demonstrated marked kurtosis and right skew (29.4 and 4.4 respectively). BIC showed considerable spread, from a maximum of 509801 (OLS-raw scale) to a minimum of 210286 (LMM). R2 ranged from 0.22 (LMM) to 0.17 and the CCC from 0.334 (LMM) to 0.149, with MAE 2.2-2.4. Superior residual behaviour was established for the log-scale estimators. There was a general tendency for over-prediction (negative residuals) and for over-fitting, the exception being the GLM negative binomial estimator. The mean-variance function was best approximated by a quadratic function, consistent with log-scale estimation; the link function was estimated (EEE) as 0.152(0.019, 0.285), consistent with a fractional-root function. For ICU length of stay, log-scale estimation, in particular the LMM, appeared to be the most consistently performing estimator(s). Neither the GLM variants nor the skew-regression estimators dominated.

Mathematical model of a smoldering log.

Treesearch

Fernando de Souza Costa; David Sandberg

2004-01-01

A mathematical model is developed describing the natural smoldering of logs. It is considered the steady one dimensional propagation of infinitesimally thin fronts of drying, pyrolysis, and char oxidation in a horizontal semi-infinite log. Expressions for the burn rates, distribution profiles of temperature, and positions of the drying, pyrolysis, and smoldering fronts...

Interannual consistency in fractal snow depth patterns at two Colorado mountain sites

Treesearch

Jeffrey S. Deems; Steven R. Fassnacht; Kelly J. Elder

2008-01-01

Fractal dimensions derived from log-log variograms are useful for characterizing spatial structure and scaling behavior in snow depth distributions. This study examines the temporal consistency of snow depth scaling features at two sites using snow depth distributions derived from lidar datasets collected in 2003 and 2005. The temporal snow accumulation patterns in...

Hardwood supply chain and the role of log brokers in 2012

Treesearch

Iris Montague; Adrienn Andersch; Jan Wiedenbeck; Urs Buehlmann

2013-01-01

The recent economic crisis has greatly affected how companies conduct business. To be competitive, companies had to make changes to their product lines, distribution channels, marketing, and overall business strategies. This study was conducted to describe and analyze the log supply component of the hardwood forest products distribution chain and to investigate changes...

A Language-Independent Approach to Automatic Text Difficulty Assessment for Second-Language Learners

DTIC Science & Technology

2013-08-01

best-suited for regression. Our baseline uses z-normalized shallow length features and TF -LOG weighted vectors on bag-of-words for Arabic, Dari...length features and TF -LOG weighted vectors on bag-of-words for Arabic, Dari, English and Pashto. We compare Support Vector Machines and the Margin...football, whereas they are much less common in documents about opera). We used TF -LOG weighted word frequencies on bag-of-words for each document

Classification of epileptic seizures using wavelet packet log energy and norm entropies with recurrent Elman neural network classifier.

PubMed

Raghu, S; Sriraam, N; Kumar, G Pradeep

2017-02-01

Electroencephalogram shortly termed as EEG is considered as the fundamental segment for the assessment of the neural activities in the brain. In cognitive neuroscience domain, EEG-based assessment method is found to be superior due to its non-invasive ability to detect deep brain structure while exhibiting superior spatial resolutions. Especially for studying the neurodynamic behavior of epileptic seizures, EEG recordings reflect the neuronal activity of the brain and thus provide required clinical diagnostic information for the neurologist. This specific proposed study makes use of wavelet packet based log and norm entropies with a recurrent Elman neural network (REN) for the automated detection of epileptic seizures. Three conditions, normal, pre-ictal and epileptic EEG recordings were considered for the proposed study. An adaptive Weiner filter was initially applied to remove the power line noise of 50 Hz from raw EEG recordings. Raw EEGs were segmented into 1 s patterns to ensure stationarity of the signal. Then wavelet packet using Haar wavelet with a five level decomposition was introduced and two entropies, log and norm were estimated and were applied to REN classifier to perform binary classification. The non-linear Wilcoxon statistical test was applied to observe the variation in the features under these conditions. The effect of log energy entropy (without wavelets) was also studied. It was found from the simulation results that the wavelet packet log entropy with REN classifier yielded a classification accuracy of 99.70 % for normal-pre-ictal, 99.70 % for normal-epileptic and 99.85 % for pre-ictal-epileptic.

Foraging patterns in online searches.

PubMed

Wang, Xiangwen; Pleimling, Michel

2017-03-01

Nowadays online searches are undeniably the most common form of information gathering, as witnessed by billions of clicks generated each day on search engines. In this work we describe online searches as foraging processes that take place on the semi-infinite line. Using a variety of quantities like probability distributions and complementary cumulative distribution functions of step length and waiting time as well as mean square displacements and entropies, we analyze three different click-through logs that contain the detailed information of millions of queries submitted to search engines. Notable differences between the different logs reveal an increased efficiency of the search engines. In the language of foraging, the newer logs indicate that online searches overwhelmingly yield local searches (i.e., on one page of links provided by the search engines), whereas for the older logs the foraging processes are a combination of local searches and relocation phases that are power law distributed. Our investigation of click logs of search engines therefore highlights the presence of intermittent search processes (where phases of local explorations are separated by power law distributed relocation jumps) in online searches. It follows that good search engines enable the users to find the information they are looking for through a local exploration of a single page with search results, whereas for poor search engine users are often forced to do a broader exploration of different pages.

Foraging patterns in online searches

NASA Astrophysics Data System (ADS)

Wang, Xiangwen; Pleimling, Michel

2017-03-01

Nowadays online searches are undeniably the most common form of information gathering, as witnessed by billions of clicks generated each day on search engines. In this work we describe online searches as foraging processes that take place on the semi-infinite line. Using a variety of quantities like probability distributions and complementary cumulative distribution functions of step length and waiting time as well as mean square displacements and entropies, we analyze three different click-through logs that contain the detailed information of millions of queries submitted to search engines. Notable differences between the different logs reveal an increased efficiency of the search engines. In the language of foraging, the newer logs indicate that online searches overwhelmingly yield local searches (i.e., on one page of links provided by the search engines), whereas for the older logs the foraging processes are a combination of local searches and relocation phases that are power law distributed. Our investigation of click logs of search engines therefore highlights the presence of intermittent search processes (where phases of local explorations are separated by power law distributed relocation jumps) in online searches. It follows that good search engines enable the users to find the information they are looking for through a local exploration of a single page with search results, whereas for poor search engine users are often forced to do a broader exploration of different pages.

SIMULATED HUMAN ERROR PROBABILITY AND ITS APPLICATION TO DYNAMIC HUMAN FAILURE EVENTS

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

Herberger, Sarah M.; Boring, Ronald L.

Abstract Objectives: Human reliability analysis (HRA) methods typically analyze human failure events (HFEs) at the overall task level. For dynamic HRA, it is important to model human activities at the subtask level. There exists a disconnect between dynamic subtask level and static task level that presents issues when modeling dynamic scenarios. For example, the SPAR-H method is typically used to calculate the human error probability (HEP) at the task level. As demonstrated in this paper, quantification in SPAR-H does not translate to the subtask level. Methods: Two different discrete distributions were generated for each SPAR-H Performance Shaping Factor (PSF) tomore » define the frequency of PSF levels. The first distribution was a uniform, or uninformed distribution that assumed the frequency of each PSF level was equally likely. The second non-continuous distribution took the frequency of PSF level as identified from an assessment of the HERA database. These two different approaches were created to identify the resulting distribution of the HEP. The resulting HEP that appears closer to the known distribution, a log-normal centered on 1E-3, is the more desirable. Each approach then has median, average and maximum HFE calculations applied. To calculate these three values, three events, A, B and C are generated from the PSF level frequencies comprised of subtasks. The median HFE selects the median PSF level from each PSF and calculates HEP. The average HFE takes the mean PSF level, and the maximum takes the maximum PSF level. The same data set of subtask HEPs yields starkly different HEPs when aggregated to the HFE level in SPAR-H. Results: Assuming that each PSF level in each HFE is equally likely creates an unrealistic distribution of the HEP that is centered at 1. Next the observed frequency of PSF levels was applied with the resulting HEP behaving log-normally with a majority of the values under 2.5% HEP. The median, average and maximum HFE calculations did yield different answers for the HFE. The HFE maximum grossly over estimates the HFE, while the HFE distribution occurs less than HFE median, and greater than HFE average. Conclusions: Dynamic task modeling can be perused through the framework of SPAR-H. Identification of distributions associated with each PSF needs to be defined, and may change depending upon the scenario. However it is very unlikely that each PSF level is equally likely as the resulting HEP distribution is strongly centered at 100%, which is unrealistic. Other distributions may need to be identified for PSFs, to facilitate the transition to dynamic task modeling. Additionally discrete distributions need to be exchanged for continuous so that simulations for the HFE can further advance. This paper provides a method to explore dynamic subtask to task translation and provides examples of the process using the SPAR-H method.« less

Groundwater contaminant plume maps and volumes, 100-K and 100-N Areas, Hanford Site, Washington

USGS Publications Warehouse

Johnson, Kenneth H.

2016-09-27

This study provides an independent estimate of the areal and volumetric extent of groundwater contaminant plumes which are affected by waste disposal in the 100-K and 100-N Areas (study area) along the Columbia River Corridor of the Hanford Site. The Hanford Natural Resource Trustee Council requested that the U.S. Geological Survey perform this interpolation to assess the accuracy of delineations previously conducted by the U.S. Department of Energy and its contractors, in order to assure that the Natural Resource Damage Assessment could rely on these analyses. This study is based on previously existing chemical (or radionuclide) sampling and analysis data downloaded from publicly available Hanford Site Internet sources, geostatistically selected and interpreted as representative of current (from 2009 through part of 2012) but average conditions for groundwater contamination in the study area. The study is limited in scope to five contaminants—hexavalent chromium, tritium, nitrate, strontium-90, and carbon-14, all detected at concentrations greater than regulatory limits in the past.All recent analytical concentrations (or activities) for each contaminant, adjusted for radioactive decay, non-detections, and co-located wells, were converted to log-normal distributions and these transformed values were averaged for each well location. The log-normally linearized well averages were spatially interpolated on a 50 × 50-meter (m) grid extending across the combined 100-N and 100-K Areas study area but limited to avoid unrepresentative extrapolation, using the minimum curvature geostatistical interpolation method provided by SURFER®data analysis software. Plume extents were interpreted by interpolating the log-normally transformed data, again using SURFER®, along lines of equal contaminant concentration at an appropriate established regulatory concentration . Total areas for each plume were calculated as an indicator of relative environmental damage. These plume extents are shown graphically and in tabular form for comparison to previous estimates. Plume data also were interpolated to a finer grid (10 × 10 m) for some processing, particularly to estimate volumes of contaminated groundwater. However, hydrogeologic transport modeling was not considered for the interpolation. The compilation of plume extents for each contaminant also allowed estimates of overlap of the plumes or areas with more than one contaminant above regulatory standards.A mapping of saturated aquifer thickness also was derived across the 100-K and 100–N study area, based on the vertical difference between the groundwater level (water table) at the top and the altitude of the top of the Ringold Upper Mud geologic unit, considered the bottom of the uppermost unconfined aquifer. Saturated thickness was calculated for each cell in the finer (10 × 10 m) grid. The summation of the cells’ saturated thickness values within each polygon of plume regulatory exceedance provided an estimate of the total volume of contaminated aquifer, and the results also were checked using a SURFER® volumetric integration procedure. The total volume of contaminated groundwater in each plume was derived by multiplying the aquifer saturated thickness volume by a locally representative value of porosity (0.3).Estimates of the uncertainty of the plume delineation also are presented. “Upper limit” plume delineations were calculated for each contaminant using the same procedure as the “average” plume extent except with values at each well that are set at a 95-percent upper confidence limit around the log-normally transformed mean concentrations, based on the standard error for the distribution of the mean value in that well; “lower limit” plumes are calculated at a 5-percent confidence limit around the geometric mean. These upper- and lower-limit estimates are considered unrealistic because the statistics were increased or decreased at each well simultaneously and were not adjusted for correlation among the well distributions (i.e., it is not realistic that all wells would be high simultaneously). Sources of the variability in the distributions used in the upper- and lower-extent maps include time varying concentrations and analytical errors.The plume delineations developed in this study are similar to the previous plume descriptions developed by U.S. Department of Energy and its contractors. The differences are primarily due to data selection and interpolation methodology. The differences in delineated plumes are not sufficient to result in the Hanford Natural Resource Trustee Council adjusting its understandings of contaminant impact or remediation.

An analytical approach to reduce between-plate variation in multiplex assays that measure antibodies to Plasmodium falciparum antigens.

PubMed

Fang, Rui; Wey, Andrew; Bobbili, Naveen K; Leke, Rose F G; Taylor, Diane Wallace; Chen, John J

2017-07-17

Antibodies play an important role in immunity to malaria. Recent studies show that antibodies to multiple antigens, as well as, the overall breadth of the response are associated with protection from malaria. Yet, the variability and reliability of antibody measurements against a combination of malarial antigens using multiplex assays have not been well characterized. A normalization procedure for reducing between-plate variation using replicates of pooled positive and negative controls was investigated. Sixty test samples (30 from malaria-positive and 30 malaria-negative individuals), together with five pooled positive-controls and two pooled negative-controls, were screened for antibody levels to 9 malarial antigens, including merozoite antigens (AMA1, EBA175, MSP1, MSP2, MSP3, MSP11, Pf41), sporozoite CSP, and pregnancy-associated VAR2CSA. The antibody levels were measured in triplicate on each of 3 plates, and the experiments were replicated on two different days by the same technician. The performance of the proposed normalization procedure was evaluated with the pooled controls for the test samples on both the linear and natural-log scales. Compared with data on the linear scale, the natural-log transformed data were less skewed and reduced the mean-variance relationship. The proposed normalization procedure using pooled controls on the natural-log scale significantly reduced between-plate variation. For malaria-related research that measure antibodies to multiple antigens with multiplex assays, the natural-log transformation is recommended for data analysis and use of the normalization procedure with multiple pooled controls can improve the precision of antibody measurements.

Generating log-normal mock catalog of galaxies in redshift space

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

Agrawal, Aniket; Makiya, Ryu; Saito, Shun

We present a public code to generate a mock galaxy catalog in redshift space assuming a log-normal probability density function (PDF) of galaxy and matter density fields. We draw galaxies by Poisson-sampling the log-normal field, and calculate the velocity field from the linearised continuity equation of matter fields, assuming zero vorticity. This procedure yields a PDF of the pairwise velocity fields that is qualitatively similar to that of N-body simulations. We check fidelity of the catalog, showing that the measured two-point correlation function and power spectrum in real space agree with the input precisely. We find that a linear biasmore » relation in the power spectrum does not guarantee a linear bias relation in the density contrasts, leading to a cross-correlation coefficient of matter and galaxies deviating from unity on small scales. We also find that linearising the Jacobian of the real-to-redshift space mapping provides a poor model for the two-point statistics in redshift space. That is, non-linear redshift-space distortion is dominated by non-linearity in the Jacobian. The power spectrum in redshift space shows a damping on small scales that is qualitatively similar to that of the well-known Fingers-of-God (FoG) effect due to random velocities, except that the log-normal mock does not include random velocities. This damping is a consequence of non-linearity in the Jacobian, and thus attributing the damping of the power spectrum solely to FoG, as commonly done in the literature, is misleading.« less

Assessment of visual disability using visual evoked potentials.

PubMed

Jeon, Jihoon; Oh, Seiyul; Kyung, Sungeun

2012-08-06

The purpose of this study is to validate the use of visual evoked potential (VEP) to objectively quantify visual acuity in normal and amblyopic patients, and determine if it is possible to predict visual acuity in disability assessment to register visual pathway lesions. A retrospective chart review was conducted of patients diagnosed with normal vision, unilateral amblyopia, optic neuritis, and visual disability who visited the university medical center for registration from March 2007 to October 2009. The study included 20 normal subjects (20 right eyes: 10 females, 10 males, ages 9-42 years), 18 unilateral amblyopic patients (18 amblyopic eyes, ages 19-36 years), 19 optic neuritis patients (19 eyes: ages 9-71 years), and 10 patients with visual disability having visual pathway lesions. Amplitude and latencies were analyzed and correlations with visual acuity (logMAR) were derived from 20 normal and 18 amblyopic subjects. Correlation of VEP amplitude and visual acuity (logMAR) of 19 optic neuritis patients confirmed relationships between visual acuity and amplitude. We calculated the objective visual acuity (logMAR) of 16 eyes from 10 patients to diagnose the presence or absence of visual disability using relations derived from 20 normal and 18 amblyopic eyes. Linear regression analyses between amplitude of pattern visual evoked potentials and visual acuity (logMAR) of 38 eyes from normal (right eyes) and amblyopic (amblyopic eyes) subjects were significant [y = -0.072x + 1.22, x: VEP amplitude, y: visual acuity (logMAR)]. There were no significant differences between visual acuity prediction values, which substituted amplitude values of 19 eyes with optic neuritis into function. We calculated the objective visual acuity of 16 eyes of 10 patients to diagnose the presence or absence of visual disability using relations of y = -0.072x + 1.22 (-0.072). This resulted in a prediction reference of visual acuity associated with malingering vs. real disability in a range >5.77 μV. The results could be useful, especially in cases of no obvious pale disc with trauma. Visual acuity quantification using absolute value of amplitude in pattern visual evoked potentials was useful in confirming subjective visual acuity for cutoff values >5.77 μV in disability evaluation to discriminate the malingering from real disability.

Assessment of visual disability using visual evoked potentials

PubMed Central

2012-01-01

Background The purpose of this study is to validate the use of visual evoked potential (VEP) to objectively quantify visual acuity in normal and amblyopic patients, and determine if it is possible to predict visual acuity in disability assessment to register visual pathway lesions. Methods A retrospective chart review was conducted of patients diagnosed with normal vision, unilateral amblyopia, optic neuritis, and visual disability who visited the university medical center for registration from March 2007 to October 2009. The study included 20 normal subjects (20 right eyes: 10 females, 10 males, ages 9–42 years), 18 unilateral amblyopic patients (18 amblyopic eyes, ages 19–36 years), 19 optic neuritis patients (19 eyes: ages 9–71 years), and 10 patients with visual disability having visual pathway lesions. Amplitude and latencies were analyzed and correlations with visual acuity (logMAR) were derived from 20 normal and 18 amblyopic subjects. Correlation of VEP amplitude and visual acuity (logMAR) of 19 optic neuritis patients confirmed relationships between visual acuity and amplitude. We calculated the objective visual acuity (logMAR) of 16 eyes from 10 patients to diagnose the presence or absence of visual disability using relations derived from 20 normal and 18 amblyopic eyes. Results Linear regression analyses between amplitude of pattern visual evoked potentials and visual acuity (logMAR) of 38 eyes from normal (right eyes) and amblyopic (amblyopic eyes) subjects were significant [y = −0.072x + 1.22, x: VEP amplitude, y: visual acuity (logMAR)]. There were no significant differences between visual acuity prediction values, which substituted amplitude values of 19 eyes with optic neuritis into function. We calculated the objective visual acuity of 16 eyes of 10 patients to diagnose the presence or absence of visual disability using relations of y = −0.072x + 1.22 (−0.072). This resulted in a prediction reference of visual acuity associated with malingering vs. real disability in a range >5.77 μV. The results could be useful, especially in cases of no obvious pale disc with trauma. Conclusions Visual acuity quantification using absolute value of amplitude in pattern visual evoked potentials was useful in confirming subjective visual acuity for cutoff values >5.77 μV in disability evaluation to discriminate the malingering from real disability. PMID:22866948

Characterization of the spatial variability of channel morphology

USGS Publications Warehouse

Moody, J.A.; Troutman, B.M.

2002-01-01

The spatial variability of two fundamental morphological variables is investigated for rivers having a wide range of discharge (five orders of magnitude). The variables, water-surface width and average depth, were measured at 58 to 888 equally spaced cross-sections in channel links (river reaches between major tributaries). These measurements provide data to characterize the two-dimensional structure of a channel link which is the fundamental unit of a channel network. The morphological variables have nearly log-normal probability distributions. A general relation was determined which relates the means of the log-transformed variables to the logarithm of discharge similar to previously published downstream hydraulic geometry relations. The spatial variability of the variables is described by two properties: (1) the coefficient of variation which was nearly constant (0.13-0.42) over a wide range of discharge; and (2) the integral length scale in the downstream direction which was approximately equal to one to two mean channel widths. The joint probability distribution of the morphological variables in the downstream direction was modelled as a first-order, bivariate autoregressive process. This model accounted for up to 76 per cent of the total variance. The two-dimensional morphological variables can be scaled such that the channel width-depth process is independent of discharge. The scaling properties will be valuable to modellers of both basin and channel dynamics. Published in 2002 John Wiley and Sons, Ltd.

A Comparison Study of Summer Season Raindrop Size Distribution Between Palau and Taiwan, Two Islands in Western Pacific

NASA Astrophysics Data System (ADS)

Seela, Balaji Kumar; Janapati, Jayalakshmi; Lin, Pay-Liam; Reddy, K. Krishna; Shirooka, Ryuichi; Wang, Pao K.

2017-11-01

Raindrop size distribution (RSD) characteristics in summer season rainfall of two observational sites (Taiwan (24°58'N, 121°10'E) and Palau (7°20'N, 134°28'E)) in western Pacific are studied by using five years of impact type disdrometer data. In addition to disdrometer data, Tropical Rainfall Measuring Mission, Moderate Resolution Imaging Spectroradiometer, and ERA-Interim data sets are used to illustrate the dynamical and microphysical characteristics associated with summer season rainfall of Taiwan and Palau. Taiwan and Palau's raindrop spectra showed a significant difference, with a higher concentration of middle and large drops in Taiwan than Palau rainfall. RSD stratified on the basis of rain rate showed a higher mass-weighted mean diameter (Dm) and a lower normalized intercept parameter (log10Nw) in Taiwan than Palau rainfall. Precipitation classification into stratiform and convective regimes showed higher Dm values in Taiwan than Palau. Furthermore, for both the locations, the convective precipitation has a higher Dm value than stratiform precipitation. The radar reflectivity-rain rate relations (Z = A*Rb) of Taiwan and Palau showed a clear variation in the coefficient and a less variation in exponent values. Terrain-influenced clouds extended to higher altitudes over Taiwan resulted with higher Dm and lower log10Nw values as compared to Palau.

Well log characterization of natural gas hydrates

USGS Publications Warehouse

Collett, Timothy S.; Lee, Myung W.

2011-01-01

In the last 25 years we have seen significant advancements in the use of downhole well logging tools to acquire detailed information on the occurrence of gas hydrate in nature: From an early start of using wireline electrical resistivity and acoustic logs to identify gas hydrate occurrences in wells drilled in Arctic permafrost environments to today where wireline and advanced logging-while-drilling tools are routinely used to examine the petrophysical nature of gas hydrate reservoirs and the distribution and concentration of gas hydrates within various complex reservoir systems. The most established and well known use of downhole log data in gas hydrate research is the use of electrical resistivity and acoustic velocity data (both compressional- and shear-wave data) to make estimates of gas hydrate content (i.e., reservoir saturations) in various sediment types and geologic settings. New downhole logging tools designed to make directionally oriented acoustic and propagation resistivity log measurements have provided the data needed to analyze the acoustic and electrical anisotropic properties of both highly inter-bedded and fracture dominated gas hydrate reservoirs. Advancements in nuclear-magnetic-resonance (NMR) logging and wireline formation testing have also allowed for the characterization of gas hydrate at the pore scale. Integrated NMR and formation testing studies from northern Canada and Alaska have yielded valuable insight into how gas hydrates are physically distributed in sediments and the occurrence and nature of pore fluids (i.e., free-water along with clay and capillary bound water) in gas-hydrate-bearing reservoirs. Information on the distribution of gas hydrate at the pore scale has provided invaluable insight on the mechanisms controlling the formation and occurrence of gas hydrate in nature along with data on gas hydrate reservoir properties (i.e., permeabilities) needed to accurately predict gas production rates for various gas hydrate production schemes.

Structural characterization of the packings of granular regular polygons.

PubMed

Wang, Chuncheng; Dong, Kejun; Yu, Aibing

2015-12-01

By using a recently developed method for discrete modeling of nonspherical particles, we simulate the random packings of granular regular polygons with three to 11 edges under gravity. The effects of shape and friction on the packing structures are investigated by various structural parameters, including packing fraction, the radial distribution function, coordination number, Voronoi tessellation, and bond-orientational order. We find that packing fraction is generally higher for geometrically nonfrustrated regular polygons, and can be increased by the increase of edge number and decrease of friction. The changes of packing fraction are linked with those of the microstructures, such as the variations of the translational and orientational orders and local configurations. In particular, the free areas of Voronoi tessellations (which are related to local packing fractions) can be described by log-normal distributions for all polygons. The quantitative analyses establish a clearer picture for the packings of regular polygons.

Concentrations of organic contaminants in mollusks and sediments at NOAA National Status and Trend sites in the coastal and estuarine United States.

PubMed

O'Connor, T P

1991-01-01

Mean concentrations of PAHs, PCBs, and DDT in mollusks and sediments at sites in the National Status and Trends Program (NST) are distributed in log-normal fashion. The dry weight-based chlorinated organic concentrations in mollusks generally exceed those in nearby sediments by an order of magnitude. PAHs are found at similar concentrations in sediments and mollusks. Highest concentrations of PCBs and DDT in mollusks are in the ranges of 1000 to 4000 ng/g (dry) and 400 to 1000 ng/g (dry), respectively. The highest PAH concentrations in sediments are in the 10,000 to 50,000 ng/g (dry) range. While higher concentrations of contaminants can be found by sampling localized hot spots, the NST data represent the distribution of concentrations over general areas of the coastal United States.

Viscosity and transient electric birefringence study of clay colloidal aggregation.

PubMed

Bakk, Audun; Fossum, Jon O; da Silva, Geraldo J; Adland, Hans M; Mikkelsen, Arne; Elgsaeter, Arnljot

2002-02-01

We study a synthetic clay suspension of laponite at different particle and NaCl concentrations by measuring stationary shear viscosity and transient electrically induced birefringence (TEB). On one hand the viscosity data are consistent with the particles being spheres and the particles being associated with large amount bound water. On the other hand the viscosity data are also consistent with the particles being asymmetric, consistent with single laponite platelets associated with a very few monolayers of water. We analyze the TEB data by employing two different models of aggregate size (effective hydrodynamic radius) distribution: (1) bidisperse model and (2) log-normal distributed model. Both models fit, in the same manner, fairly well to the experimental TEB data and they indicate that the suspension consists of polydisperse particles. The models also appear to confirm that the aggregates increase in size vs increasing ionic strength. The smallest particles at low salt concentrations seem to be monomers and oligomers.

Measurement, Modeling, and Analysis of a Large-scale Blog Sever Workload

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

Jeon, Myeongjae; Hwang, Jeaho; Kim, Youngjae

2010-01-01

Despite the growing popularity of Online Social Networks (OSNs), the workload characteristics of OSN servers, such as those hosting blog services, are not well understood. Understanding workload characteristics is important for opti- mizing and improving the performance of current systems and software based on observed trends. Thus, in this paper, we characterize the system workload of the largest blog hosting servers in South Korea, Tistory1. In addition to understanding the system workload of the blog hosting server, we have developed synthesized workloads and obtained the following major findings: (i) the transfer size of non-multimedia files and blog articles can bemore » modeled by a truncated Pareto distribution and a log-normal distribution respectively, and (ii) users accesses to blog articles do not show temporal locality, but they are strongly biased toward those posted along with images or audio.« less

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

Murase, Kenya, E-mail: murase@sahs.med.osaka-u.ac.jp; Song, Ruixiao; Hiratsuka, Samu

We investigated the feasibility of visualizing blood coagulation using a system for magnetic particle imaging (MPI). A magnetic field-free line is generated using two opposing neodymium magnets and transverse images are reconstructed from the third-harmonic signals received by a gradiometer coil, using the maximum likelihood-expectation maximization algorithm. Our MPI system was used to image the blood coagulation induced by adding CaCl{sub 2} to whole sheep blood mixed with magnetic nanoparticles (MNPs). The “MPI value” was defined as the pixel value of the transverse image reconstructed from the third-harmonic signals. MPI values were significantly smaller for coagulated blood samples than thosemore » without coagulation. We confirmed the rationale of these results by calculating the third-harmonic signals for the measured viscosities of samples, with an assumption that the magnetization and particle size distribution of MNPs obey the Langevin equation and log-normal distribution, respectively. We concluded that MPI can be useful for visualizing blood coagulation.« less

Dynamic design of ecological monitoring networks for non-Gaussian spatio-temporal data

USGS Publications Warehouse

Wikle, C.K.; Royle, J. Andrew

2005-01-01

Many ecological processes exhibit spatial structure that changes over time in a coherent, dynamical fashion. This dynamical component is often ignored in the design of spatial monitoring networks. Furthermore, ecological variables related to processes such as habitat are often non-Gaussian (e.g. Poisson or log-normal). We demonstrate that a simulation-based design approach can be used in settings where the data distribution is from a spatio-temporal exponential family. The key random component in the conditional mean function from this distribution is then a spatio-temporal dynamic process. Given the computational burden of estimating the expected utility of various designs in this setting, we utilize an extended Kalman filter approximation to facilitate implementation. The approach is motivated by, and demonstrated on, the problem of selecting sampling locations to estimate July brood counts in the prairie pothole region of the U.S.

Globular cluster seeding by primordial black hole population

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

Dolgov, A.; Postnov, K., E-mail: dolgov@fe.infn.it, E-mail: kpostnov@gmail.com

Primordial black holes (PBHs) that form in the early Universe in the modified Affleck-Dine (AD) mechanism of baryogenesis should have intrinsic log-normal mass distribution of PBHs. We show that the parameters of this distribution adjusted to provide the required spatial density of massive seeds (≥ 10{sup 4} M {sub ⊙}) for early galaxy formation and not violating the dark matter density constraints, predict the existence of the population of intermediate-mass PBHs with a number density of 0∼ 100 Mpc{sup −3}. We argue that the population of intermediate-mass AD PBHs can also seed the formation of globular clusters in galaxies. Inmore » this scenario, each globular cluster should host an intermediate-mass black hole with a mass of a few thousand solar masses, and should not obligatorily be immersed in a massive dark matter halo.« less

Shielding Effectiveness in a Two-Dimensional Reverberation Chamber Using Finite-Element Techniques

NASA Technical Reports Server (NTRS)

Bunting, Charles F.

2006-01-01

Reverberation chambers are attaining an increased importance in determination of electromagnetic susceptibility of avionics equipment. Given the nature of the variable boundary condition, the ability of a given source to couple energy into certain modes and the passband characteristic due the chamber Q, the fields are typically characterized by statistical means. The emphasis of this work is to apply finite-element techniques at cutoff to the analysis of a two-dimensional structure to examine the notion of shielding-effectiveness issues in a reverberating environment. Simulated mechanical stirring will be used to obtain the appropriate statistical field distribution. The shielding effectiveness (SE) in a simulated reverberating environment is compared to measurements in a reverberation chamber. A log-normal distribution for the SE is observed with implications for system designers. The work is intended to provide further refinement in the consideration of SE in a complex electromagnetic environment.

Solving puzzles of GW150914 by primordial black holes

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

Blinnikov, S.; Dolgov, A.; Porayko, N.K.

The black hole binary properties inferred from the LIGO gravitational wave signal GW150914 posed several serious problems. The high masses and low effective spin of black hole binary can be explained if they are primordial (PBH) rather than the products of the stellar binary evolution. Such PBH properties are postulated ad hoc but not derived from fundamental theory. We show that the necessary features of PBHs naturally follow from the slightly modified Affleck-Dine (AD) mechanism of baryogenesis. The log-normal distribution of PBHs, predicted within the AD paradigm, is adjusted to provide an abundant population of low-spin stellar mass black holes.more » The same distribution gives a sufficient number of quickly growing seeds of supermassive black holes observed at high redshifts and may comprise an appreciable fraction of Dark Matter which does not contradict any existing observational limits. Testable predictions of this scenario are discussed.« less

Statistical patterns of visual search for hidden objects

PubMed Central

Credidio, Heitor F.; Teixeira, Elisângela N.; Reis, Saulo D. S.; Moreira, André A.; Andrade Jr, José S.

2012-01-01

The movement of the eyes has been the subject of intensive research as a way to elucidate inner mechanisms of cognitive processes. A cognitive task that is rather frequent in our daily life is the visual search for hidden objects. Here we investigate through eye-tracking experiments the statistical properties associated with the search of target images embedded in a landscape of distractors. Specifically, our results show that the twofold process of eye movement, composed of sequences of fixations (small steps) intercalated by saccades (longer jumps), displays characteristic statistical signatures. While the saccadic jumps follow a log-normal distribution of distances, which is typical of multiplicative processes, the lengths of the smaller steps in the fixation trajectories are consistent with a power-law distribution. Moreover, the present analysis reveals a clear transition between a directional serial search to an isotropic random movement as the difficulty level of the searching task is increased. PMID:23226829

Generating porosity spectrum of carbonate reservoirs using ultrasonic imaging log

NASA Astrophysics Data System (ADS)

Zhang, Jie; Nie, Xin; Xiao, Suyun; Zhang, Chong; Zhang, Chaomo; Zhang, Zhansong

2018-03-01

Imaging logging tools can provide us the borehole wall image. The micro-resistivity imaging logging has been used to obtain borehole porosity spectrum. However, the resistivity imaging logging cannot cover the whole borehole wall. In this paper, we propose a method to calculate the porosity spectrum using ultrasonic imaging logging data. Based on the amplitude attenuation equation, we analyze the factors affecting the propagation of wave in drilling fluid and formation and based on the bulk-volume rock model, Wyllie equation and Raymer equation, we establish various conversion models between the reflection coefficient β and porosity ϕ. Then we use the ultrasonic imaging logging and conventional wireline logging data to calculate the near-borehole formation porosity distribution spectrum. The porosity spectrum result obtained from ultrasonic imaging data is compared with the one from the micro-resistivity imaging data, and they turn out to be similar, but with discrepancy, which is caused by the borehole coverage and data input difference. We separate the porosity types by performing threshold value segmentation and generate porosity-depth distribution curves by counting with equal depth spacing on the porosity image. The practice result is good and reveals the efficiency of our method.

On the log-normality of historical magnetic-storm intensity statistics: implications for extreme-event probabilities

USGS Publications Warehouse

Love, Jeffrey J.; Rigler, E. Joshua; Pulkkinen, Antti; Riley, Pete

2015-01-01

An examination is made of the hypothesis that the statistics of magnetic-storm-maximum intensities are the realization of a log-normal stochastic process. Weighted least-squares and maximum-likelihood methods are used to fit log-normal functions to −Dst storm-time maxima for years 1957-2012; bootstrap analysis is used to established confidence limits on forecasts. Both methods provide fits that are reasonably consistent with the data; both methods also provide fits that are superior to those that can be made with a power-law function. In general, the maximum-likelihood method provides forecasts having tighter confidence intervals than those provided by weighted least-squares. From extrapolation of maximum-likelihood fits: a magnetic storm with intensity exceeding that of the 1859 Carrington event, −Dst≥850 nT, occurs about 1.13 times per century and a wide 95% confidence interval of [0.42,2.41] times per century; a 100-yr magnetic storm is identified as having a −Dst≥880 nT (greater than Carrington) but a wide 95% confidence interval of [490,1187] nT.

Determination of reversed-phase high performance liquid chromatography based octanol-water partition coefficients for neutral and ionizable compounds: Methodology evaluation.

PubMed

Liang, Chao; Qiao, Jun-Qin; Lian, Hong-Zhen

2017-12-15

Reversed-phase liquid chromatography (RPLC) based octanol-water partition coefficient (logP) or distribution coefficient (logD) determination methods were revisited and assessed comprehensively. Classic isocratic and some gradient RPLC methods were conducted and evaluated for neutral, weak acid and basic compounds. Different lipophilicity indexes in logP or logD determination were discussed in detail, including the retention factor logk w corresponding to neat water as mobile phase extrapolated via linear solvent strength (LSS) model from isocratic runs and calculated with software from gradient runs, the chromatographic hydrophobicity index (CHI), apparent gradient capacity factor (k g ') and gradient retention time (t g ). Among the lipophilicity indexes discussed, logk w from whether isocratic or gradient elution methods best correlated with logP or logD. Therefore logk w is recommended as the preferred lipophilicity index for logP or logD determination. logk w easily calculated from methanol gradient runs might be the main candidate to replace logk w calculated from classic isocratic run as the ideal lipophilicity index. These revisited RPLC methods were not applicable for strongly ionized compounds that are hardly ion-suppressed. A previously reported imperfect ion-pair RPLC method was attempted and further explored for studying distribution coefficients (logD) of sulfonic acids that totally ionized in the mobile phase. Notably, experimental logD values of sulfonic acids were given for the first time. The IP-RPLC method provided a distinct way to explore logD values of ionized compounds. Copyright © 2017 Elsevier B.V. All rights reserved.

Antral follicle counts are strongly associated with live-birth rates after assisted reproduction, with superior treatment outcome in women with polycystic ovaries.

PubMed

Holte, Jan; Brodin, Thomas; Berglund, Lars; Hadziosmanovic, Nermin; Olovsson, Matts; Bergh, Torbjörn

2011-09-01

To evaluate the association of antral follicle count (AFC) with in vitro fertilization/intracytoplasmic sperm injection (IVF-ICSI) outcome in a large unselected cohort of patients covering the entire range of AFC. Prospective observational study. University-affiliated private infertility center. 2,092 women undergoing 4,308 IVF-ICSI cycles. AFC analyzed for associations with treatment outcome and statistically adjusted for repeated treatments and age. Pregnancy rate, live-birth rate, and stimulation outcome parameters. The AFC was log-normally distributed. Pregnancy rates and live-birth rates were positively associated with AFC in a log-linear way, leveling out above AFC ∼30. Treatment outcome was superior among women with polycystic ovaries, independent from ovulatory status. The findings were significant also after adjustment for age and number of oocytes retrieved. Pregnancy and live-birth rates are log-linearly related to AFC. Polycystic ovaries, most often excluded from studies on ovarian reserve, fit as one extreme in the spectrum of AFC; a low count constitutes the other extreme, with the lowest ovarian reserve and poor treatment outcome. The findings remained statistically significant also after adjustment for the number of oocytes retrieved, suggesting this measure of ovarian reserve comprises information on oocyte quality and not only quantity. Copyright © 2011 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

IMPLEMENTING A NOVEL CYCLIC CO2 FLOOD IN PALEOZOIC REEFS

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

James R. Wood; W. Quinlan; A. Wylie

2004-07-01

Recycled CO2 will be used in this demonstration project to produce bypassed oil from the Silurian Dover 35 pinnacle reef (Otsego County) in the Michigan Basin. We began injecting CO2 in the Dover 35 field into the Salling-Hansen 4-35A well on May 6, 2004. Subsurface characterization is being completed using well log tomography animations and 3D visualizations to map facies distributions and reservoir properties in three reefs, the Belle River Mills, Chester 18, and Dover 35 Fields. The Belle River Mills and Chester 18 fields are being used as type-fields because they have excellent log and/or core data coverage. Amplitudemore » slicing of the log porosity, normalized gamma ray, core permeability, and core porosity curves is showing trends that indicate significant heterogeneity and compartmentalization in these reservoirs associated with the original depositional fabric of the rocks. Digital and hard copy data continues to be compiled for the Niagaran reefs in the Michigan Basin. Technology transfer took place through technical presentations regarding visualization of the heterogeneity of the Niagaran reefs. Oral presentations were given at the Petroleum Technology Transfer Council workshop, Michigan Oil and Gas Association Conference, and Michigan Basin Geological Society meeting. A technical paper was submitted to the Bulletin of the American Association of Petroleum Geologists on the characterization of the Belle River Mills Field.« less

Structural control of coalbed methane production in Alabama

USGS Publications Warehouse

Pashin, J.C.; Groshong, R.H.

1998-01-01

Thin-skinned structures are distributed throughout the Alabama coalbed methane fields, and these structures affect the production of gas and water from coal-bearing strata. Extensional structures in Deerlick Creek and Cedar Cove fields include normal faults and hanging-wall rollovers, and area balancing indicates that these structures are detached in the Pottsville Formation. Compressional folds in Gurnee and Oak Grove fields, by comparison, are interpreted to be detachment folds formed above decollements at different stratigraphic levels. Patterns of gas and water production reflect the structural style of each field and further indicate that folding and faulting have affected the distribution of permeability and the overall success of coalbed methane operations. Area balancing can be an effective way to characterize coalbed methane reservoirs in structurally complex regions because it constrains structural geometry and can be used to determine the distribution of layer-parallel strain. Comparison of calculated requisite strain and borehole expansion data from calliper logs suggests that strain in coalbed methane reservoirs is predictable and can be expressed as fracturing and small-scale faulting. However, refined methodology is needed to analyze heterogeneous strain distributions in discrete bed segments. Understanding temporal variation of production patterns in areas where gas and water production are influenced by map-scale structure will further facilitate effective management of coalbed methane fields.Thin-skinned structures are distributed throughout the Alabama coalbed methane fields, and these structures affect the production of gas and water from coal-bearing strata. Extensional structures in Deerlick Creek and Cedar Cove fields include normal faults and hanging-wall rollovers, and area balancing indicates that these structures are detached in the Pottsville Formation. Compressional folds in Gurnee and Oak Grove fields, by comparison, are interpreted to be detachment folds formed above decollements at different stratigraphic levels. Patterns of gas and water production reflect the structural style of each field and further indicate that folding and faulting have affected the distribution of permeability and the overall success of coalbed methane operations. Area balancing can be an effective way to characterize coalbed methane reservoirs in structurally complex regions because it constrains structural geometry and can be used to determine the distribution of layer-parallel strain. Comparison of calculated requisite strain and borehole expansion data from calliper logs suggests that strain in coalbed methane reservoirs is predictable and can be expressed as fracturing and small-scale faulting. However, refined methodology is needed to analyze heterogeneous strain distributions in discrete bed segments. Understanding temporal variation of production patterns in areas where gas and water production are influenced by map-scale structure will further facilitate effective management of coalbed methane fields.

Landslides after clearcut logging in a coast redwood forest

Treesearch

Leslie M. Reid; Elizabeth T. Keppeler

2012-01-01

Landslides have been mapped at least annually in the 473 ha North Fork Caspar Creek watershed since 1985, allowing evaluation of landslide distribution, characteristics, and rates associated with second-entry partial clearcut logging of 1989 to 1992. Comparison of sliding rates in logged and forested areas shows no appreciable difference for streamside slides (size...

Advanced information processing system

NASA Technical Reports Server (NTRS)

Lala, J. H.

1984-01-01

Design and performance details of the advanced information processing system (AIPS) for fault and damage tolerant data processing on aircraft and spacecraft are presented. AIPS comprises several computers distributed throughout the vehicle and linked by a damage tolerant data bus. Most I/O functions are available to all the computers, which run in a TDMA mode. Each computer performs separate specific tasks in normal operation and assumes other tasks in degraded modes. Redundant software assures that all fault monitoring, logging and reporting are automated, together with control functions. Redundant duplex links and damage-spread limitation provide the fault tolerance. Details of an advanced design of a laboratory-scale proof-of-concept system are described, including functional operations.

Two-component mixture model: Application to palm oil and exchange rate

NASA Astrophysics Data System (ADS)

Phoong, Seuk-Yen; Ismail, Mohd Tahir; Hamzah, Firdaus Mohamad

2014-12-01

Palm oil is a seed crop which is widely adopt for food and non-food products such as cookie, vegetable oil, cosmetics, household products and others. Palm oil is majority growth in Malaysia and Indonesia. However, the demand for palm oil is getting growth and rapidly running out over the years. This phenomenal cause illegal logging of trees and destroy the natural habitat. Hence, the present paper investigates the relationship between exchange rate and palm oil price in Malaysia by using Maximum Likelihood Estimation via Newton-Raphson algorithm to fit a two components mixture model. Besides, this paper proposes a mixture of normal distribution to accommodate with asymmetry characteristics and platykurtic time series data.

Consequence of reputation in the Sznajd consensus model

NASA Astrophysics Data System (ADS)

Crokidakis, Nuno; Forgerini, Fabricio L.

2010-07-01

In this work we study a modified version of the Sznajd sociophysics model. In particular we introduce reputation, a mechanism that limits the capacity of persuasion of the agents. The reputation is introduced as a score which is time-dependent, and its introduction avoid dictatorship (all spins parallel) for a wide range of parameters. The relaxation time follows a log-normal-like distribution. In addition, we show that the usual phase transition also occurs, as in the standard model, and it depends on the initial concentration of individuals following an opinion, occurring at a initial density of up spins greater than 1/2. The transition point is determined by means of a finite-size scaling analysis.

Effects of composition of grains of debris flow on its impact force

NASA Astrophysics Data System (ADS)

Tang, jinbo; Hu, Kaiheng; Cui, Peng

2017-04-01

Debris flows compose of solid material with broad size distribution from fine sand to boulders. Impact force imposed by debris flows is a very important issue for protection engineering design and strongly influenced by their grain composition. However, this issue has not been studied in depth and the effects of grain composition not been considered in the calculation of the impact force. In this present study, the small-scale flume experiments with five kinds of compositions of grains for debris flow were carried out to study the effect of the composition of grains of debris flow on its impact force. The results show that the impact force of debris flow increases with the grain size, the hydrodynamic pressure of debris flow is calibrated based on the normalization parameter dmax/d50, in which dmax is the maximum size and d50 is the median size. Furthermore, a log-logistic statistic distribution could be used to describe the distribution of magnitude of impact force of debris flow, where the mean and the variance of the present distribution increase with grain size. This distribution proposed in the present study could be used to the reliability analysis of structures impacted by debris flow.

Design and characterization of a cough simulator.

PubMed

Zhang, Bo; Zhu, Chao; Ji, Zhiming; Lin, Chao-Hsin

2017-02-23

Expiratory droplets from human coughing have always been considered as potential carriers of pathogens, responsible for respiratory infectious disease transmission. To study the transmission of disease by human coughing, a transient repeatable cough simulator has been designed and built. Cough droplets are generated by different mechanisms, such as the breaking of mucus, condensation and high-speed atomization from different depths of the respiratory tract. These mechanisms in coughing produce droplets of different sizes, represented by a bimodal distribution of 'fine' and 'coarse' droplets. A cough simulator is hence designed to generate transient sprays with such bimodal characteristics. It consists of a pressurized gas tank, a nebulizer and an ejector, connected in series, which are controlled by computerized solenoid valves. The bimodal droplet size distribution is characterized for the coarse droplets and fine droplets, by fibrous collection and laser diffraction, respectively. The measured size distributions of coarse and fine droplets are reasonably represented by the Rosin-Rammler and log-normal distributions in probability density function, which leads to a bimodal distribution. To assess the hydrodynamic consequences of coughing including droplet vaporization and polydispersion, a Lagrangian model of droplet trajectories is established, with its ambient flow field predetermined from a computational fluid dynamics simulation.

Characterizing Topology of Probabilistic Biological Networks.

PubMed

Todor, Andrei; Dobra, Alin; Kahveci, Tamer

2013-09-06

Biological interactions are often uncertain events, that may or may not take place with some probability. Existing studies analyze the degree distribution of biological networks by assuming that all the given interactions take place under all circumstances. This strong and often incorrect assumption can lead to misleading results. Here, we address this problem and develop a sound mathematical basis to characterize networks in the presence of uncertain interactions. We develop a method that accurately describes the degree distribution of such networks. We also extend our method to accurately compute the joint degree distributions of node pairs connected by edges. The number of possible network topologies grows exponentially with the number of uncertain interactions. However, the mathematical model we develop allows us to compute these degree distributions in polynomial time in the number of interactions. It also helps us find an adequate mathematical model using maximum likelihood estimation. Our results demonstrate that power law and log-normal models best describe degree distributions for probabilistic networks. The inverse correlation of degrees of neighboring nodes shows that, in probabilistic networks, nodes with large number of interactions prefer to interact with those with small number of interactions more frequently than expected.

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.

Atomisation and droplet formation mechanisms in a model two-phase mixing layer

NASA Astrophysics Data System (ADS)

Zaleski, Stephane; Ling, Yue; Fuster, Daniel; Tryggvason, Gretar

2017-11-01

We study atomization in a turbulent two-phase mixing layer inspired by the Grenoble air-water experiments. A planar gas jet of large velocity is emitted on top of a planar liquid jet of smaller velocity. The density ratio and momentum ratios are both set at 20 in the numerical simulation in order to ease the simulation. We use a Volume-Of-Fluid method with good parallelisation properties, implemented in our code http://parissimulator.sf.net. Our simulations show two distinct droplet formation mechanisms, one in which thin liquid sheets are punctured to form rapidly expanding holes and the other in which ligaments of irregular shape form and breakup in a manner similar but not identical to jets in Rayleigh-Plateau-Savart instabilities. Observed distributions of particle sizes are extracted for a sequence of ever more refined grids, the largest grid containing approximately eight billion points. Although their accuracy is limited at small sizes by the grid resolution and at large size by statistical effects, the distributions overlap in the central region. The observed distributions are much closer to log normal distributions than to gamma distributions as is also the case for experiments.

A Hierarchical Poisson Log-Normal Model for Network Inference from RNA Sequencing Data

PubMed Central

Gallopin, Mélina; Rau, Andrea; Jaffrézic, Florence

2013-01-01

Gene network inference from transcriptomic data is an important methodological challenge and a key aspect of systems biology. Although several methods have been proposed to infer networks from microarray data, there is a need for inference methods able to model RNA-seq data, which are count-based and highly variable. In this work we propose a hierarchical Poisson log-normal model with a Lasso penalty to infer gene networks from RNA-seq data; this model has the advantage of directly modelling discrete data and accounting for inter-sample variance larger than the sample mean. Using real microRNA-seq data from breast cancer tumors and simulations, we compare this method to a regularized Gaussian graphical model on log-transformed data, and a Poisson log-linear graphical model with a Lasso penalty on power-transformed data. For data simulated with large inter-sample dispersion, the proposed model performs better than the other methods in terms of sensitivity, specificity and area under the ROC curve. These results show the necessity of methods specifically designed for gene network inference from RNA-seq data. PMID:24147011

Probing star formation relations of mergers and normal galaxies across the CO ladder

NASA Astrophysics Data System (ADS)

Greve, Thomas R.

We examine integrated luminosity relations between the IR continuum and the CO rotational ladder observed for local (ultra) luminous infra-red galaxies ((U)LIRGs, L IR >= 1011 M⊙) and normal star forming galaxies in the context of radiation pressure regulated star formation proposed by Andrews & Thompson (2011). This can account for the normalization and linear slopes of the luminosity relations (log L IR = α log L'CO + β) of both low- and high-J CO lines observed for normal galaxies. Super-linear slopes occur for galaxy samples with significantly different dense gas fractions. Local (U)LIRGs are observed to have sub-linear high-J (J up > 6) slopes or, equivalently, increasing L COhigh-J /L IR with L IR. In the extreme ISM conditions of local (U)LIRGs, the high-J CO lines no longer trace individual hot spots of star formation (which gave rise to the linear slopes for normal galaxies) but a more widespread warm and dense gas phase mechanically heated by powerful supernovae-driven turbulence and shocks.

Contributions of Optical and Non-Optical Blur to Variation in Visual Acuity

PubMed Central

McAnany, J. Jason; Shahidi, Mahnaz; Applegate, Raymond A.; Zelkha, Ruth; Alexander, Kenneth R.

2011-01-01

Purpose To determine the relative contributions of optical and non-optical sources of intrinsic blur to variations in visual acuity (VA) among normally sighted subjects. Methods Best-corrected VA of sixteen normally sighted subjects was measured using briefly presented (59 ms) tumbling E optotypes that were either unblurred or blurred through convolution with Gaussian functions of different widths. A standard model of intrinsic blur was used to estimate each subject’s equivalent intrinsic blur (σint) and VA for the unblurred tumbling E (MAR0). For 14 subjects, a radially averaged optical point spread function due to higher-order aberrations was derived by Shack-Hartmann aberrometry and fit with a Gaussian function. The standard deviation of the best-fit Gaussian function defined optical blur (σopt). An index of non-optical blur (η) was defined as: 1-σopt/σint. A control experiment was conducted on 5 subjects to evaluate the effect of stimulus duration on MAR0 and σint. Results Log MAR0 for the briefly presented E was correlated significantly with log σint (r = 0.95, p < 0.01), consistent with previous work. However, log MAR0 was not correlated significantly with log σopt (r = 0.46, p = 0.11). For subjects with log MAR0 equivalent to approximately 20/20 or better, log MAR0 was independent of log η, whereas for subjects with larger log MAR0 values, log MAR0 was proportional to log η. The control experiment showed a statistically significant effect of stimulus duration on log MAR0 (p < 0.01) but a non-significant effect on σint (p = 0.13). Conclusions The relative contributions of optical and non-optical blur to VA varied among the subjects, and were related to the subject’s VA. Evaluating optical and non-optical blur may be useful for predicting changes in VA following procedures that improve the optics of the eye in patients with both optical and non-optical sources of VA loss. PMID:21460756

Using the ovarian sensitivity index to define poor, normal, and high response after controlled ovarian hyperstimulation in the long gonadotropin-releasing hormone-agonist protocol: suggestions for a new principle to solve an old problem.

PubMed

Huber, Malin; Hadziosmanovic, Nermin; Berglund, Lars; Holte, Jan

2013-11-01

To explore the utility of using the ratio between oocyte yield and total dose of FSH, i.e., the ovarian sensitivity index (OSI), to define ovarian response patterns. Retrospective cross-sectional study. University-affiliated private center. The entire unselected cohort of 7,520 IVF/intracytoplasmic sperm injection treatments (oocyte pick-ups [OPUs]) during an 8-year period (long GnRH agonist-recombinant FSH protocol). None. The distribution of the OSI (oocytes recovered × 1,000/total dose of FSH), the cutoff levels for poor and high response, set at ±1 SD, and the relationship between OSI and treatment outcome. OSI showed a log-normal distribution with cutoff levels for poor and high response at 1.697/IU and 10.07/IU, respectively. A nomogram is presented. Live-birth rates per OPU were 10.5 ± 0.1%, 26.9 ± 0.6%, and 36.0 ± 1.4% for poor, normal, and high response treatments, respectively. The predictive power (C-statistic) for OSI to predict live birth was superior to that of oocyte yield. The OSI improves the definition of ovarian response patterns because it takes into account the degree of stimulation. The nomogram presents evidence-based cutoff levels for poor, normal, and high response and could be used for unifying study designs involving ovarian response patterns. Copyright © 2013 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Analysis of DNS Cache Effects on Query Distribution

PubMed Central

2013-01-01

This paper studies the DNS cache effects that occur on query distribution at the CN top-level domain (TLD) server. We first filter out the malformed DNS queries to purify the log data pollution according to six categories. A model for DNS resolution, more specifically DNS caching, is presented. We demonstrate the presence and magnitude of DNS cache effects and the cache sharing effects on the request distribution through analytic model and simulation. CN TLD log data results are provided and analyzed based on the cache model. The approximate TTL distribution for domain name is inferred quantificationally. PMID:24396313

Analysis of DNS cache effects on query distribution.

PubMed

Wang, Zheng

2013-01-01

This paper studies the DNS cache effects that occur on query distribution at the CN top-level domain (TLD) server. We first filter out the malformed DNS queries to purify the log data pollution according to six categories. A model for DNS resolution, more specifically DNS caching, is presented. We demonstrate the presence and magnitude of DNS cache effects and the cache sharing effects on the request distribution through analytic model and simulation. CN TLD log data results are provided and analyzed based on the cache model. The approximate TTL distribution for domain name is inferred quantificationally.

Modifications of exposure to ambient particulate matter: Tackling bias in using ambient concentration as surrogate with particle infiltration factor and ambient exposure factor.

PubMed

Shi, Shanshan; Chen, Chen; Zhao, Bin

2017-01-01

Numerous epidemiological studies explored health risks attributed to outdoor particle pollution. However, a number of these studies routinely utilized ambient concentration as a surrogate for personal exposure to ambient particles. This simplification ignored the difference between indoor and outdoor concentrations of outdoor originated particles and may bias the estimate of particle-health associations. Intending to avoid the bias, particle infiltration factor (F inf ), which describes the penetration of outdoor particles in indoor environment, and ambient exposure factor (α), which represents the fraction of outdoor particles people are truly exposed to, are utilized as modification factors to modify outdoor particle concentration. In this study, the probabilistic distributions of annually-averaged and seasonally-averaged F inf and α were assessed for residences and residents in Beijing. F inf of a single residence and α of an individual was estimated based on the mechanisms governing particle outdoor-to-indoor migration and human time-activity pattern. With this as the core deterministic model, probabilistic distributions of F inf and α were estimated via Monte Carlo Simulation. Annually-averaged F inf of PM 2.5 and PM 10 for residences in Beijing tended to be log-normally distributed as lnN(-0.74,0.14) and lnN(-0.94,0.15) with geometric mean value as 0.47 and 0.39, respectively. Annually-averaged α of PM 2.5 and PM 10 for Beijing residents also tended to be log-normally distributed as lnN(-0.59,0.12) and lnN(-0.73,0.13) with geometric mean value as 0.55 and 0.48, respectively. As for seasonally-averaged results, F inf and α of PM 2.5 and PM 10 were largest in summer and smallest in winter. The obvious difference between these modification factors and unity suggested that modifications of ambient particle concentration need to be considered in epidemiological studies to avoid misclassifications of personal exposure to ambient particles. Moreover, considering the inter-individual difference of F inf and α may lead to a brand new perspective of particle-health associations in further epidemiological study. Copyright © 2016 Elsevier Ltd. All rights reserved.

Influence of forest roads standards and networks on water yield as predicted by the distributed hydrology-soil-vegetation model

Treesearch

Salli F. Dymond; W. Michael Aust; Steven P. Prisley; Mark H. Eisenbies; James M. Vose

2013-01-01

Throughout the country, foresters are continually looking at the effects of logging and forest roads on stream discharge and overall stream health. In the Pacific Northwest, a distributed hydrology-soil-vegetation model (DHSVM) has been used to predict the effects of logging on peak discharge in mountainous regions. DHSVM uses elevation, meteorological, vegetation, and...

Statistical Analysis of the Exchange Rate of Bitcoin.

PubMed

Chu, Jeffrey; Nadarajah, Saralees; Chan, Stephen

2015-01-01

Bitcoin, the first electronic payment system, is becoming a popular currency. We provide a statistical analysis of the log-returns of the exchange rate of Bitcoin versus the United States Dollar. Fifteen of the most popular parametric distributions in finance are fitted to the log-returns. The generalized hyperbolic distribution is shown to give the best fit. Predictions are given for future values of the exchange rate.

Heterogeneity of Chlorinity distribution within gas hydrate reservoir at Daini-Atsumi knoll, based on logging data analysis

NASA Astrophysics Data System (ADS)

Suzuki, K.; Takayama, T.; Fujii, T.

2016-12-01

We will present possible heterogeneity of pore-water salinity within methane hydrate reservoir of Daini-Atsumi knoll, on the basis of Logging-while-drilling (LWD) data and several kind of wire-line logging dataset. The LWD and the wire-line logging had been carried out during 2012 to 2013, before/after the first offshore gas-production-test from marine-methane-hydrate reservoir at Daini-Atsumi Knoll along the northeast Nankai trough. Several data from the logging, especially data from the reservoir saturation tool; RST, gave us some possible interpretation for heterogeneity distribution of chlorinity within the methane-hydrate reservoir. The computed pore-water chlorinity could be interpreted as condense of chlorinity at gas-hydrate formation. This year, we drilled several number of wells at Daini-Atsumi Knoll, again for next gas production test, and we have also found out possibility of chlorinity heterogeneity from LWD data of Neutron-capture cross section; i.e. Sigma. The distribution of chlorinity within gas-hydrate reservoir may help our understanding of gas hydrate-crystallization and/or dissociation in turbidite reservoir at Daini-Atsumi Knoll. This research is conducted as a part of the Research Consortium for Methane Hydrate Resource in Japan (MH21 Research consortium).

Separate-channel analysis of two-channel microarrays: recovering inter-spot information.

PubMed

Smyth, Gordon K; Altman, Naomi S

2013-05-26

Two-channel (or two-color) microarrays are cost-effective platforms for comparative analysis of gene expression. They are traditionally analysed in terms of the log-ratios (M-values) of the two channel intensities at each spot, but this analysis does not use all the information available in the separate channel observations. Mixed models have been proposed to analyse intensities from the two channels as separate observations, but such models can be complex to use and the gain in efficiency over the log-ratio analysis is difficult to quantify. Mixed models yield test statistics for the null distributions can be specified only approximately, and some approaches do not borrow strength between genes. This article reformulates the mixed model to clarify the relationship with the traditional log-ratio analysis, to facilitate information borrowing between genes, and to obtain an exact distributional theory for the resulting test statistics. The mixed model is transformed to operate on the M-values and A-values (average log-expression for each spot) instead of on the log-expression values. The log-ratio analysis is shown to ignore information contained in the A-values. The relative efficiency of the log-ratio analysis is shown to depend on the size of the intraspot correlation. A new separate channel analysis method is proposed that assumes a constant intra-spot correlation coefficient across all genes. This approach permits the mixed model to be transformed into an ordinary linear model, allowing the data analysis to use a well-understood empirical Bayes analysis pipeline for linear modeling of microarray data. This yields statistically powerful test statistics that have an exact distributional theory. The log-ratio, mixed model and common correlation methods are compared using three case studies. The results show that separate channel analyses that borrow strength between genes are more powerful than log-ratio analyses. The common correlation analysis is the most powerful of all. The common correlation method proposed in this article for separate-channel analysis of two-channel microarray data is no more difficult to apply in practice than the traditional log-ratio analysis. It provides an intuitive and powerful means to conduct analyses and make comparisons that might otherwise not be possible.

Application of a continuous distribution model for proton binding by humic acids extracted from acidic lake sediments

NASA Astrophysics Data System (ADS)

Rhea, James R.; Young, Thomas C.

1987-10-01

The proton binding characteristics of humic acids extracted from the sediments of Cranberry Pond, an acidic water body located in the Adirondack Mountain region of New York State, were explored by the application of a multiligand distribution model. The model characterizes a class of proton binding sites by mean log K values and the standard deviations of log K values about the mean. Mean log K values and their relative abundances were determined directly from experimental titration data. The model accurately predicts the binding of protons by the humic acids for pH values in the range 3.5 to 10.0.

Application of a continuous distribution model for proton binding by humic acids extracted from acidic lake sediments

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

Rhea, J.R.; Young, T.C.

1987-01-01

The proton binding characteristics of humic acids extracted from the sediments of Cranberry Pond, an acidic water body located in the Adirondack Mountain region of New York State, were explored by the application of a nultiligand distribution model. The model characterizes a class of proton binding sites by mean log K values and the standard deviations of log K values and the mean. Mean log K values and their relative abundances were determined directly from experimental titration data. The model accurately predicts the binding of protons by the humic acids for pH values in the range 3.5 to 10.0.

Application of Statistically Derived CPAS Parachute Parameters

NASA Technical Reports Server (NTRS)

Romero, Leah M.; Ray, Eric S.

2013-01-01

The Capsule Parachute Assembly System (CPAS) Analysis Team is responsible for determining parachute inflation parameters and dispersions that are ultimately used in verifying system requirements. A model memo is internally released semi-annually documenting parachute inflation and other key parameters reconstructed from flight test data. Dispersion probability distributions published in previous versions of the model memo were uniform because insufficient data were available for determination of statistical based distributions. Uniform distributions do not accurately represent the expected distributions since extreme parameter values are just as likely to occur as the nominal value. CPAS has taken incremental steps to move away from uniform distributions. Model Memo version 9 (MMv9) made the first use of non-uniform dispersions, but only for the reefing cutter timing, for which a large number of sample was available. In order to maximize the utility of the available flight test data, clusters of parachutes were reconstructed individually starting with Model Memo version 10. This allowed for statistical assessment for steady-state drag area (CDS) and parachute inflation parameters such as the canopy fill distance (n), profile shape exponent (expopen), over-inflation factor (C(sub k)), and ramp-down time (t(sub k)) distributions. Built-in MATLAB distributions were applied to the histograms, and parameters such as scale (sigma) and location (mu) were output. Engineering judgment was used to determine the "best fit" distribution based on the test data. Results include normal, log normal, and uniform (where available data remains insufficient) fits of nominal and failure (loss of parachute and skipped stage) cases for all CPAS parachutes. This paper discusses the uniform methodology that was previously used, the process and result of the statistical assessment, how the dispersions were incorporated into Monte Carlo analyses, and the application of the distributions in trajectory benchmark testing assessments with parachute inflation parameters, drag area, and reefing cutter timing used by CPAS.

Human respiratory syncytial virus load normalized by cell quantification as predictor of acute respiratory tract infection.

PubMed

Gómez-Novo, Miriam; Boga, José A; Álvarez-Argüelles, Marta E; Rojo-Alba, Susana; Fernández, Ana; Menéndez, María J; de Oña, María; Melón, Santiago

2018-05-01

Human respiratory syncytial virus (HRSV) is a common cause of respiratory infections. The main objective is to analyze the prediction ability of viral load of HRSV normalized by cell number in respiratory symptoms. A prospective, descriptive, and analytical study was performed. From 7307 respiratory samples processed between December 2014 to April 2016, 1019 HRSV-positive samples, were included in this study. Low respiratory tract infection was present in 729 patients (71.54%). Normalized HRSV load was calculated by quantification of HRSV genome and human β-globin gene and expressed as log10 copies/1000 cells. HRSV mean loads were 4.09 ± 2.08 and 4.82 ± 2.09 log10 copies/1000 cells in the 549 pharyngeal and 470 nasopharyngeal samples, respectively (P < 0.001). The viral mean load was 4.81 ± 1.98 log10 copies/1000 cells for patients under the age of 4-year-old (P < 0.001). The viral mean loads were 4.51 ± 2.04 cells in patients with low respiratory tract infection and 4.22 ± 2.28 log10 copies/1000 cells with upper respiratory tract infection or febrile syndrome (P < 0.05). A possible cut off value to predict LRTI evolution was tentatively established. Normalization of viral load by cell number in the samples is essential to ensure an optimal virological molecular diagnosis avoiding that the quality of samples affects the results. A high viral load can be a useful marker to predict disease progression. © 2018 Wiley Periodicals, Inc.

Blind prediction of cyclohexane-water distribution coefficients from the SAMPL5 challenge.

PubMed

Bannan, Caitlin C; Burley, Kalistyn H; Chiu, Michael; Shirts, Michael R; Gilson, Michael K; Mobley, David L

2016-11-01

In the recent SAMPL5 challenge, participants submitted predictions for cyclohexane/water distribution coefficients for a set of 53 small molecules. Distribution coefficients (log D) replace the hydration free energies that were a central part of the past five SAMPL challenges. A wide variety of computational methods were represented by the 76 submissions from 18 participating groups. Here, we analyze submissions by a variety of error metrics and provide details for a number of reference calculations we performed. As in the SAMPL4 challenge, we assessed the ability of participants to evaluate not just their statistical uncertainty, but their model uncertainty-how well they can predict the magnitude of their model or force field error for specific predictions. Unfortunately, this remains an area where prediction and analysis need improvement. In SAMPL4 the top performing submissions achieved a root-mean-squared error (RMSE) around 1.5 kcal/mol. If we anticipate accuracy in log D predictions to be similar to the hydration free energy predictions in SAMPL4, the expected error here would be around 1.54 log units. Only a few submissions had an RMSE below 2.5 log units in their predicted log D values. However, distribution coefficients introduced complexities not present in past SAMPL challenges, including tautomer enumeration, that are likely to be important in predicting biomolecular properties of interest to drug discovery, therefore some decrease in accuracy would be expected. Overall, the SAMPL5 distribution coefficient challenge provided great insight into the importance of modeling a variety of physical effects. We believe these types of measurements will be a promising source of data for future blind challenges, especially in view of the relatively straightforward nature of the experiments and the level of insight provided.

Blind prediction of cyclohexane-water distribution coefficients from the SAMPL5 challenge

PubMed Central

Bannan, Caitlin C.; Burley, Kalistyn H.; Chiu, Michael; Shirts, Michael R.; Gilson, Michael K.; Mobley, David L.

2016-01-01

In the recent SAMPL5 challenge, participants submitted predictions for cyclohexane/water distribution coefficients for a set of 53 small molecules. Distribution coefficients (log D) replace the hydration free energies that were a central part of the past five SAMPL challenges. A wide variety of computational methods were represented by the 76 submissions from 18 participating groups. Here, we analyze submissions by a variety of error metrics and provide details for a number of reference calculations we performed. As in the SAMPL4 challenge, we assessed the ability of participants to evaluate not just their statistical uncertainty, but their model uncertainty – how well they can predict the magnitude of their model or force field error for specific predictions. Unfortunately, this remains an area where prediction and analysis need improvement. In SAMPL4 the top performing submissions achieved a root-mean-squared error (RMSE) around 1.5 kcal/mol. If we anticipate accuracy in log D predictions to be similar to the hydration free energy predictions in SAMPL4, the expected error here would be around 1.54 log units. Only a few submissions had an RMSE below 2.5 log units in their predicted log D values. However, distribution coefficients introduced complexities not present in past SAMPL challenges, including tautomer enumeration, that are likely to be important in predicting biomolecular properties of interest to drug discovery, therefore some decrease in accuracy would be expected. Overall, the SAMPL5 distribution coefficient challenge provided great insight into the importance of modeling a variety of physical effects. We believe these types of measurements will be a promising source of data for future blind challenges, especially in view of the relatively straightforward nature of the experiments and the level of insight provided. PMID:27677750

Chronic Kidney Disease Is Associated With White Matter Hyperintensity Volume

PubMed Central

Khatri, Minesh; Wright, Clinton B.; Nickolas, Thomas L.; Yoshita, Mitsuhiro; Paik, Myunghee C.; Kranwinkel, Grace; Sacco, Ralph L.; DeCarli, Charles

2010-01-01

Background and Purpose White matter hyperintensities have been associated with increased risk of stroke, cognitive decline, and dementia. Chronic kidney disease is a risk factor for vascular disease and has been associated with inflammation and endothelial dysfunction, which have been implicated in the pathogenesis of white matter hyperintensities. Few studies have explored the relationship between chronic kidney disease and white matter hyperintensities. Methods The Northern Manhattan Study is a prospective, community-based cohort of which a subset of stroke-free participants underwent MRIs. MRIs were analyzed quantitatively for white matter hyperintensities volume, which was log-transformed to yield a normal distribution (log-white matter hyperintensity volume). Kidney function was modeled using serum creatinine, the Cockcroft-Gault formula for creatinine clearance, and the Modification of Diet in Renal Disease formula for estimated glomerular filtration rate. Creatinine clearance and estimated glomerular filtration rate were trichotomized to 15 to 60 mL/min, 60 to 90 mL/min, and >90 mL/min (reference). Linear regression was used to measure the association between kidney function and log-white matter hyperintensity volume adjusting for age, gender, race–ethnicity, education, cardiac disease, diabetes, homocysteine, and hypertension. Results Baseline data were available on 615 subjects (mean age 70 years, 60% women, 18% whites, 21% blacks, 62% Hispanics). In multivariate analysis, creatinine clearance 15 to 60 mL/min was associated with increased log-white matter hyperintensity volume (β 0.322; 95% CI, 0.095 to 0.550) as was estimated glomerular filtration rate 15 to 60 mL/min (β 0.322; 95% CI, 0.080 to 0.564). Serum creatinine, per 1-mg/dL increase, was also positively associated with log-white matter hyperintensity volume (β 1.479; 95% CI, 1.067 to 2.050). Conclusions The association between moderate–severe chronic kidney disease and white matter hyperintensity volume highlights the growing importance of kidney disease as a possible determinant of cerebrovascular disease and/or as a marker of microangiopathy. PMID:17962588

Index map of cross sections through parts of the Appalachian basin (Kentucky, New York, Ohio, Pennsylvania, Tennessee, Virginia, West Virginia): Chapter E.1 in Coal and petroleum resources in the Appalachian basin: distribution, geologic framework, and geochemical character

USGS Publications Warehouse

Ryder, Robert T.; Trippi, Michael H.; Ruppert, Leslie F.; Ryder, Robert T.

2014-01-01

The appendixes in chapters E.4.1 and E.4.2 include (1) Log ASCII Standard (LAS) files, which encode gamma-ray, neutron, density, and other logs in text files that can be used by most well-logging software programs; and (2) graphic well-log traces. In the appendix to chapter E.4.1, the well-log traces are accompanied by lithologic descriptions with formation tops.

Analysis of geophysical logs from six boreholes at Lariat Gulch, former U.S. Air Force site PJKS, Jefferson County, Colorado

USGS Publications Warehouse

Paillet, Frederick L.; Hodges, Richard E.; Corland, Barbara S.

2002-01-01

This report presents and describes geophysical logs for six boreholes in Lariat Gulch, a topographic gulch at the former U.S. Air Force site PJKS in Jefferson County near Denver, Colorado. Geophysical logs include gamma, normal resistivity, fluid-column temperature and resistivity, caliper, televiewer, and heat-pulse flowmeter. These logs were run in two boreholes penetrating only the Fountain Formation of Pennsylvanian and Permian age (logged to depths of about 65 and 570 feet) and in four boreholes (logged to depths of about 342 to 742 feet) penetrating mostly the Fountain Formation and terminating in Precambrian crystalline rock, which underlies the Fountain Formation. Data from the logs were used to identify fractures and bedding planes and to locate the contact between the two formations. The logs indicated few fractures in the boreholes and gave no indication of higher transmissivity in the contact zone between the two formations. Transmissivities for all fractures in each borehole were estimated to be less than 2 feet squared per day.

Well logging evaluation of water-flooded layers and distribution rule of remaining oil in marine sandstone reservoirs of the M oilfield in the Pearl River Mouth basin

NASA Astrophysics Data System (ADS)

Li, Xiongyan; Qin, Ruibao; Gao, Yunfeng; Fan, Hongjun

2017-03-01

In the marine sandstone reservoirs of the M oilfield the water cut is up to 98%, while the recovery factor is only 35%. Additionally, the distribution of the remaining oil is very scattered. In order to effectively assess the potential of the remaining oil, the logging evaluation of the water-flooded layers and the distribution rule of the remaining oil are studied. Based on the log response characteristics, the water-flooded layers can be qualitatively identified. On the basis of the mercury injection experimental data of the evaluation wells, the calculation model of the initial oil saturation is built. Based on conventional logging data, the evaluation model of oil saturation is established. The difference between the initial oil saturation and the residual oil saturation can be used to quantitatively evaluate the water-flooded layers. The evaluation result of the water-flooded layers is combined with the ratio of the water-flooded wells in the marine sandstone reservoirs. As a result, the degree of water flooding in the marine sandstone reservoirs can be assessed. On the basis of structural characteristics and sedimentary environments, the horizontal and vertical water-flooding rules of the different types of reservoirs are elaborated upon, and the distribution rule of the remaining oil is disclosed. The remaining oil is mainly distributed in the high parts of the structure. The remaining oil exists in the top of the reservoirs with good physical properties while the thickness of the remaining oil ranges from 2-5 m. However, the thickness of the remaining oil of the reservoirs with poor physical properties ranges from 5-8 m. The high production of some of the drilled horizontal wells shows that the above distribution rule of the remaining oil is accurate. In the marine sandstone reservoirs of the M oilfield, the research on the well logging evaluation of the water-flooded layers and the distribution rule of the remaining oil has great practical significance to the prediction of the distribution of the remaining oil and the optimization of well locations.

The incidence and role of gullies after logging in a coastal redwood forest

Treesearch

Leslie Reid; N. Dewey; Tom Lisle; Susan Hilton

2010-01-01

The distribution and morphological characteristics of channels were mapped in a redwood forest at Caspar Creek, California, USA, to evaluate the extent to which recent logging has influenced channel conditions in the area. In the North Fork Caspar Creek watershed, second-cycle logging of the early 1990s appears to have triggered increased coalescence of discontinuous...

Statistical Analysis of the Exchange Rate of Bitcoin

PubMed Central

Chu, Jeffrey; Nadarajah, Saralees; Chan, Stephen

2015-01-01

Bitcoin, the first electronic payment system, is becoming a popular currency. We provide a statistical analysis of the log-returns of the exchange rate of Bitcoin versus the United States Dollar. Fifteen of the most popular parametric distributions in finance are fitted to the log-returns. The generalized hyperbolic distribution is shown to give the best fit. Predictions are given for future values of the exchange rate. PMID:26222702

An "ASYMPTOTIC FRACTAL" Approach to the Morphology of Malignant Cell Nuclei

NASA Astrophysics Data System (ADS)

Landini, Gabriel; Rippin, John W.

To investigate quantitatively nuclear membrane irregularity, 672 nuclei from 10 cases of oral cancer (squamous cell carcinoma) and normal cells from oral mucosa were studied in transmission electron micrographs. The nuclei were photographed at ×1400 magnification and transferred to computer memory (1 pixel = 35 nm). The perimeter of the profiles was analysed using the "yardstick method" of fractal dimension estimation, and the log-log plot of ruler size vs. boundary length demonstrated that there exists a significant effect of resolution on length measurement. However, this effect seems to disappear at higher resolutions. As this observation is compatible with the concept of asymptotic fractal, we estimated the parameters c, L and Bm from the asymptotic fractal formula Br = Bm {1 + (r / L)c}-1 , where Br is the boundary length measured with a ruler of size r, Bm is the maximum boundary for r → 0, L is a constant, and c = asymptotic fractal dimension minus topological dimension (D - Dt) for r → ∞. Analyses of variance showed c to be significantly higher in the normal than malignant cases (P < 0.001), but log(L) and Bm to be significantly higher in the malignant cases (P < 0.001). A multivariate linear discrimination analysis on c, log(L) and Bm re-classified 76.6% of the cells correctly (84.8% of the normal and 67.5% of the tumor). Furthermore, this shows that asymptotic fractal analysis applied to nuclear profiles has great potential for shape quantification in diagnosis of oral cancer.

Estimating macroporosity in a forest watershed by use of a tension infiltrometer

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

Watson, K.W.; Luxmoore, R.J.

The ability to obtain sufficient field hydrologic data at reasonable cost can be an important limiting factor in applying transport models. A procedure is described for using ponded-flow- and tension-infiltration measurements to calculate transport parameters in a forest watershed. Thirty infiltration measurements were taken under ponded-flow conditions and at 3, 6, and 15 cm (H/sub 2/O) tension. It was assumed from capillarity theory that pores > 0.1-, 0.05-, and 0.02-cm diam, respectively, were excluded from the transport process during the tension infiltration measurements. Under ponded flow, 73% of the flux was conducted through macropores (i.e., pores > 0.1-cm diam.). Anmore » estimated 96% of the water flux was transmitted through only 0.32% of the soil volume. In general the larger the total water flux the larger the macropore contribution to total water flux. The Shapiro-Wilk normality test indicated that water flux through both matrix pore space and macropores was log-normally distributed in space.« less

Assessment of variations in thermal cycle life data of thermal barrier coated rods

NASA Astrophysics Data System (ADS)

Hendricks, R. C.; McDonald, G.

An analysis of thermal cycle life data for 22 thermal barrier coated (TBC) specimens was conducted. The Zr02-8Y203/NiCrAlY plasma spray coated Rene 41 rods were tested in a Mach 0.3 Jet A/air burner flame. All specimens were subjected to the same coating and subsequent test procedures in an effort to control three parametric groups; material properties, geometry and heat flux. Statistically, the data sample space had a mean of 1330 cycles with a standard deviation of 520 cycles. The data were described by normal or log-normal distributions, but other models could also apply; the sample size must be increased to clearly delineate a statistical failure model. The statistical methods were also applied to adhesive/cohesive strength data for 20 TBC discs of the same composition, with similar results. The sample space had a mean of 9 MPa with a standard deviation of 4.2 MPa.

Assessment of variations in thermal cycle life data of thermal barrier coated rods

NASA Technical Reports Server (NTRS)

Hendricks, R. C.; Mcdonald, G.

1981-01-01

An analysis of thermal cycle life data for 22 thermal barrier coated (TBC) specimens was conducted. The Zr02-8Y203/NiCrAlY plasma spray coated Rene 41 rods were tested in a Mach 0.3 Jet A/air burner flame. All specimens were subjected to the same coating and subsequent test procedures in an effort to control three parametric groups; material properties, geometry and heat flux. Statistically, the data sample space had a mean of 1330 cycles with a standard deviation of 520 cycles. The data were described by normal or log-normal distributions, but other models could also apply; the sample size must be increased to clearly delineate a statistical failure model. The statistical methods were also applied to adhesive/cohesive strength data for 20 TBC discs of the same composition, with similar results. The sample space had a mean of 9 MPa with a standard deviation of 4.2 MPa.

Analytical Fingerprint of Wolframite Ore Concentrates.

PubMed

Gäbler, Hans-Eike; Schink, Wilhelm; Goldmann, Simon; Bahr, Andreas; Gawronski, Timo

2017-07-01

Ongoing violent conflicts in Central Africa are fueled by illegal mining and trading of tantalum, tin, and tungsten ores. The credibility of document-based traceability systems can be improved by an analytical fingerprint applied as an independent method to confirm or doubt the documented origin of ore minerals. Wolframite (Fe,Mn)WO 4 is the most important ore mineral for tungsten and is subject to artisanal mining in Central Africa. Element concentrations of wolframite grains analyzed by laser ablation-inductively coupled plasma-mass spectrometry are used to establish the analytical fingerprint. The data from ore concentrate samples are multivariate, not normal or log-normal distributed. The samples cannot be regarded as representative aliquots of a population. Based on the Kolmogorov-Smirnov distance, a measure of similarity between a sample in question and reference samples from a database is determined. A decision criterion is deduced to recognize samples which do not originate from the declared mine site. © 2017 American Academy of Forensic Sciences.

LogCauchy, log-sech and lognormal distributions of species abundances in forest communities

USGS Publications Warehouse

Yin, Z.-Y.; Peng, S.-L.; Ren, H.; Guo, Q.; Chen, Z.-H.

2005-01-01

Species-abundance (SA) pattern is one of the most fundamental aspects of biological community structure, providing important information regarding species richness, species-area relation and succession. To better describe the SA distribution (SAD) in a community, based on the widely used lognormal (LN) distribution model with exp(-x2) roll-off on Preston's octave scale, this study proposed two additional models, logCauchy (LC) and log-sech (LS), respectively with roll-offs of simple x-2 and e-x. The estimation of the theoretical total number of species in the whole community, S*, including very rare species not yet collected in sample, was derived from the left-truncation of each distribution. We fitted these three models by Levenberg-Marquardt nonlinear regression and measured the model fit to the data using coefficient of determination of regression, parameters' t-test and distribution's Kolmogorov-Smirnov (KS) test. Examining the SA data from six forest communities (five in lower subtropics and one in tropics), we found that: (1) on a log scale, all three models that are bell-shaped and left-truncated statistically adequately fitted the observed SADs, and the LC and LS did better than the LN; (2) from each model and for each community the S* values estimated by the integral and summation methods were almost equal, allowing us to estimate S* using a simple integral formula and to estimate its asymptotic confidence internals by regression of a transformed model containing it; (3) following the order of LC, LS, and LN, the fitted distributions became lower in the peak, less concave in the side, and shorter in the tail, and overall the LC tended to overestimate, the LN tended to underestimate, while the LS was intermediate but slightly tended to underestimate, the observed SADs (particularly the number of common species in the right tail); (4) the six communities had some similar structural properties such as following similar distribution models, having a common modal octave and a similar proportion of common species. We suggested that what follows the LN distribution should follow (or better follow) the LC and LS, and that the LC, LS and LN distributions represent a "sequential distribution set" in which one can find a best fit to the observed SAD. ?? 2004 Elsevier B.V. All rights reserved.

Statistical approaches for the determination of cut points in anti-drug antibody bioassays.

PubMed

Schaarschmidt, Frank; Hofmann, Matthias; Jaki, Thomas; Grün, Bettina; Hothorn, Ludwig A

2015-03-01

Cut points in immunogenicity assays are used to classify future specimens into anti-drug antibody (ADA) positive or negative. To determine a cut point during pre-study validation, drug-naive specimens are often analyzed on multiple microtiter plates taking sources of future variability into account, such as runs, days, analysts, gender, drug-spiked and the biological variability of un-spiked specimens themselves. Five phenomena may complicate the statistical cut point estimation: i) drug-naive specimens may contain already ADA-positives or lead to signals that erroneously appear to be ADA-positive, ii) mean differences between plates may remain after normalization of observations by negative control means, iii) experimental designs may contain several factors in a crossed or hierarchical structure, iv) low sample sizes in such complex designs lead to low power for pre-tests on distribution, outliers and variance structure, and v) the choice between normal and log-normal distribution has a serious impact on the cut point. We discuss statistical approaches to account for these complex data: i) mixture models, which can be used to analyze sets of specimens containing an unknown, possibly larger proportion of ADA-positive specimens, ii) random effects models, followed by the estimation of prediction intervals, which provide cut points while accounting for several factors, and iii) diagnostic plots, which allow the post hoc assessment of model assumptions. All methods discussed are available in the corresponding R add-on package mixADA. Copyright © 2015 Elsevier B.V. All rights reserved.

Spatial distribution of pH and organic matter in urban soils and its implications on site-specific land uses in Xuzhou, China.

PubMed

Mao, Yingming; Sang, Shuxun; Liu, Shiqi; Jia, Jinlong

2014-05-01

The spatial variation of soil pH and soil organic matter (SOM) in the urban area of Xuzhou, China, was investigated in this study. Conventional statistics, geostatistics, and a geographical information system (GIS) were used to produce spatial distribution maps and to provide information about land use types. A total of 172 soil samples were collected based on grid method in the study area. Soil pH ranged from 6.47 to 8.48, with an average of 7.62. SOM content was very variable, ranging from 3.51 g/kg to 17.12 g/kg, with an average of 8.26 g/kg. Soil pH followed a normal distribution, while SOM followed a log-normal distribution. The results of semi-variograms indicated that soil pH and SOM had strong (21%) and moderate (44%) spatial dependence, respectively. The variogram model was spherical for soil pH and exponential for SOM. The spatial distribution maps were achieved using kriging interpolation. The high pH and high SOM tended to occur in the mixed forest land cover areas such as those in the southwestern part of the urban area, while the low values were found in the eastern and the northern parts, probably due to the effect of industrial and human activities. In the central urban area, the soil pH was low, but the SOM content was high, which is mainly attributed to the disturbance of regional resident activities and urban transportation. Furthermore, anthropogenic organic particles are possible sources of organic matter after entering the soil ecosystem in urban areas. These maps provide useful information for urban planning and environmental management. Copyright © 2014 Académie des sciences. Published by Elsevier SAS. All rights reserved.

Statistical models for RNA-seq data derived from a two-condition 48-replicate experiment.

PubMed

Gierliński, Marek; Cole, Christian; Schofield, Pietà; Schurch, Nicholas J; Sherstnev, Alexander; Singh, Vijender; Wrobel, Nicola; Gharbi, Karim; Simpson, Gordon; Owen-Hughes, Tom; Blaxter, Mark; Barton, Geoffrey J

2015-11-15

High-throughput RNA sequencing (RNA-seq) is now the standard method to determine differential gene expression. Identifying differentially expressed genes crucially depends on estimates of read-count variability. These estimates are typically based on statistical models such as the negative binomial distribution, which is employed by the tools edgeR, DESeq and cuffdiff. Until now, the validity of these models has usually been tested on either low-replicate RNA-seq data or simulations. A 48-replicate RNA-seq experiment in yeast was performed and data tested against theoretical models. The observed gene read counts were consistent with both log-normal and negative binomial distributions, while the mean-variance relation followed the line of constant dispersion parameter of ∼0.01. The high-replicate data also allowed for strict quality control and screening of 'bad' replicates, which can drastically affect the gene read-count distribution. RNA-seq data have been submitted to ENA archive with project ID PRJEB5348. g.j.barton@dundee.ac.uk. © The Author 2015. Published by Oxford University Press.

Statistical models for RNA-seq data derived from a two-condition 48-replicate experiment

PubMed Central

Cole, Christian; Schofield, Pietà; Schurch, Nicholas J.; Sherstnev, Alexander; Singh, Vijender; Wrobel, Nicola; Gharbi, Karim; Simpson, Gordon; Owen-Hughes, Tom; Blaxter, Mark; Barton, Geoffrey J.

2015-01-01

Motivation: High-throughput RNA sequencing (RNA-seq) is now the standard method to determine differential gene expression. Identifying differentially expressed genes crucially depends on estimates of read-count variability. These estimates are typically based on statistical models such as the negative binomial distribution, which is employed by the tools edgeR, DESeq and cuffdiff. Until now, the validity of these models has usually been tested on either low-replicate RNA-seq data or simulations. Results: A 48-replicate RNA-seq experiment in yeast was performed and data tested against theoretical models. The observed gene read counts were consistent with both log-normal and negative binomial distributions, while the mean-variance relation followed the line of constant dispersion parameter of ∼0.01. The high-replicate data also allowed for strict quality control and screening of ‘bad’ replicates, which can drastically affect the gene read-count distribution. Availability and implementation: RNA-seq data have been submitted to ENA archive with project ID PRJEB5348. Contact: g.j.barton@dundee.ac.uk PMID:26206307

Polybrominated diphenyl ethers in indoor air in Kuwait: Implications for human exposure

NASA Astrophysics Data System (ADS)

Gevao, Bondi; Al-Bahloul, Majed; Al-Ghadban, Abdul Nabi; Ali, Lulwa; Al-Omair, Ali; Helaleh, Murad; Al-Matrouk, Khaled; Zafar, Jamal

Polyurethane foam plug passive samplers were used to concurrently measure air concentrations of polybrominated diphenyl ethers (PBDEs) in 70 indoor environments. PBDEs were detected in all homes and offices investigated with patterns similar to the distribution in the commercial penta technical formulation (Bromkal 70-5DE). The ubiquitous distribution of these compounds in indoor environments may be due to the volatilization of these chemicals from foam (e.g. mattresses, foam padded furniture), electronic equipments (e.g. TVs, printers, computers) and other consumer products to which they are added as flame retardants. Mean ΣPBDEs concentration in air was log-normally distributed and ranged from ˜2-385 pg m -3. Using an inhalation rate of 8 and 20 m 3 day -1 for children and adults respectively, exposure via inhalation is estimated to be 173 and 399 pg day -1 for children and adults respectively. This study supports the growing body of evidence for the ubiquitous presence of these compounds in indoor air and the potential for continuous, low-level exposure both at work and home.

Binary Star Fractions from the LAMOST DR4

NASA Astrophysics Data System (ADS)

Tian, Zhi-Jia; Liu, Xiao-Wei; Yuan, Hai-Bo; Chen, Bing-Qiu; Xiang, Mao-Sheng; Huang, Yang; Wang, Chun; Zhang, Hua-Wei; Guo, Jin-Cheng; Ren, Juan-Juan; Huo, Zhi-Ying; Yang, Yong; Zhang, Meng; Bi, Shao-Lan; Yang, Wu-Ming; Liu, Kang; Zhang, Xian-Fei; Li, Tan-Da; Wu, Ya-Qian; Zhang, Jing-Hua

2018-05-01

Stellar systems composed of single, double, triple or higher-order systems are rightfully regarded as the fundamental building blocks of the Milky Way. Binary stars play an important role in formation and evolution of the Galaxy. Through comparing the radial velocity variations from multi-epoch observations, we analyze the binary fraction of dwarf stars observed with LAMOST. Effects of different model assumptions, such as orbital period distributions on the estimate of binary fractions, are investigated. The results based on log-normal distribution of orbital periods reproduce the previous complete analyses better than the power-law distribution. We find that the binary fraction increases with T eff and decreases with [Fe/H]. We first investigate the relation between α-elements and binary fraction in such a large sample as provided by LAMOST. The old stars with high [α/Fe] dominate with a higher binary fraction than young stars with low [α/Fe]. At the same mass, earlier forming stars possess a higher binary fraction than newly forming ones, which may be related with evolution of the Galaxy.

The VMC Survey. XXIX. Turbulence-controlled Hierarchical Star Formation in the Small Magellanic Cloud

NASA Astrophysics Data System (ADS)

Sun, Ning-Chen; de Grijs, Richard; Cioni, Maria-Rosa L.; Rubele, Stefano; Subramanian, Smitha; van Loon, Jacco Th.; Bekki, Kenji; Bell, Cameron P. M.; Ivanov, Valentin D.; Marconi, Marcella; Muraveva, Tatiana; Oliveira, Joana M.; Ripepi, Vincenzo

2018-05-01

In this paper we report a clustering analysis of upper main-sequence stars in the Small Magellanic Cloud, using data from the VMC survey (the VISTA near-infrared YJK s survey of the Magellanic system). Young stellar structures are identified as surface overdensities on a range of significance levels. They are found to be organized in a hierarchical pattern, such that larger structures at lower significance levels contain smaller ones at higher significance levels. They have very irregular morphologies, with a perimeter–area dimension of 1.44 ± 0.02 for their projected boundaries. They have a power-law mass–size relation, power-law size/mass distributions, and a log-normal surface density distribution. We derive a projected fractal dimension of 1.48 ± 0.03 from the mass–size relation, or of 1.4 ± 0.1 from the size distribution, reflecting significant lumpiness of the young stellar structures. These properties are remarkably similar to those of a turbulent interstellar medium, supporting a scenario of hierarchical star formation regulated by supersonic turbulence.

A preliminary analysis of quantifying computer security vulnerability data in "the wild"

NASA Astrophysics Data System (ADS)

Farris, Katheryn A.; McNamara, Sean R.; Goldstein, Adam; Cybenko, George

2016-05-01

A system of computers, networks and software has some level of vulnerability exposure that puts it at risk to criminal hackers. Presently, most vulnerability research uses data from software vendors, and the National Vulnerability Database (NVD). We propose an alternative path forward through grounding our analysis in data from the operational information security community, i.e. vulnerability data from "the wild". In this paper, we propose a vulnerability data parsing algorithm and an in-depth univariate and multivariate analysis of the vulnerability arrival and deletion process (also referred to as the vulnerability birth-death process). We find that vulnerability arrivals are best characterized by the log-normal distribution and vulnerability deletions are best characterized by the exponential distribution. These distributions can serve as prior probabilities for future Bayesian analysis. We also find that over 22% of the deleted vulnerability data have a rate of zero, and that the arrival vulnerability data is always greater than zero. Finally, we quantify and visualize the dependencies between vulnerability arrivals and deletions through a bivariate scatterplot and statistical observations.

Determining inert content in coal dust/rock dust mixture

DOEpatents

Sapko, Michael J.; Ward, Jr., Jack A.

1989-01-01

A method and apparatus for determining the inert content of a coal dust and rock dust mixture uses a transparent window pressed against the mixture. An infrared light beam is directed through the window such that a portion of the infrared light beam is reflected from the mixture. The concentration of the reflected light is detected and a signal indicative of the reflected light is generated. A normalized value for the generated signal is determined according to the relationship .phi.=(log i.sub.c `log i.sub.co) / (log i.sub.c100 -log i.sub.co) where i.sub.co =measured signal at 0% rock dust i.sub.c100 =measured signal at 100% rock dust i.sub.c =measured signal of the mixture. This normalized value is then correlated to a predetermined relationship of .phi. to rock dust percentage to determine the rock dust content of the mixture. The rock dust content is displayed where the percentage is between 30 and 100%, and an indication of out-of-range is displayed where the rock dust percent is less than 30%. Preferably, the rock dust percentage (RD%) is calculated from the predetermined relationship RD%=100+30 log .phi.. where the dust mixture initially includes moisture, the dust mixture is dried before measuring by use of 8 to 12 mesh molecular-sieves which are shaken with the dust mixture and subsequently screened from the dust mixture.

The relevance of the slope for concentration-effect relations

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

Schobben, H.P.M.; Smit, M.; Schobben, J.H.M.

1995-12-31

Risk analysis is mostly based on a comparison of one value for the exposure to a chemical (PEC) and one value for the sensitivity of biota (NEC). This method enables the determination of an effect to be expected, but it is not possible to quantify the magnitude of that effect. Moreover, it is impossible to estimate the effect of a combination of chemicals. Therefore, it is necessary to use a mathematical function to describe the relation between a concentration and the subsequent effect. These relations are typically based on a log normal or log logistic distribution of the sensitivity ofmore » individuals of a species. This distribution is characterized by the median sensitivity (EC{sub 50}) and the variation between the sensitivity of individuals (being a measure for the slope of the relation). Presently the attention is focused on the median, while the slope might be even more important. Relevant exposure concentrations are typically in the range which are found in the left tail of the sensitivity distribution. In this study the slope was determined for 250 chemical-species combinations. The data were derived from original experiments and from literature. The slope is highly dependent on the exposure time; the shorter the exposure time the steeper the slope. If data for a standard exposure time [96 hours] are considered, the total variation in slope can partly be explained by the groups of organisms and chemicals. The slope for heavy metals tends to be less steep as compared to the slope of narcotic organic compounds. The slope for fish and molluscs is steeper than for crustaceans. The results of this study are presently applied in a number of risk analysis studies.« less

The evolution of high summit metabolism and cold tolerance in birds and its impact on present-day distributions.

PubMed

Swanson, David L; Garland, Theodore

2009-01-01

Summit metabolic rate (M(sum), maximum cold-induced metabolic rate) is positively correlated with cold tolerance in birds, suggesting that high M(sum) is important for residency in cold climates. However, the phylogenetic distribution of high M(sum) among birds and the impact of its evolution on current distributions are not well understood. Two potential adaptive hypotheses might explain the phylogenetic distribution of high M(sum) among birds. The cold adaptation hypothesis contends that species wintering in cold climates should have higher M(sum) than species wintering in warmer climates. The flight adaptation hypothesis suggests that volant birds might be capable of generating high M(sum) as a byproduct of their muscular capacity for flight; thus, variation in M(sum) should be associated with capacity for sustained flight, one indicator of which is migration. We collected M(sum) data from the literature for 44 bird species and conducted both conventional and phylogenetically informed statistical analyses to examine the predictors of M(sum) variation. Significant phylogenetic signal was present for log body mass, log mass-adjusted M(sum), and average temperature in the winter range. In multiple regression models, log body mass, winter temperature, and clade were significant predictors of log M(sum). These results are consistent with a role for climate in determining M(sum) in birds, but also indicate that phylogenetic signal remains even after accounting for associations indicative of adaptation to winter temperature. Migratory strategy was never a significant predictor of log M(sum) in multiple regressions, a result that is not consistent with the flight adaptation hypothesis.

Labeling Defects in CT Images of Hardwood Logs with Species-Dependent and Species-Independent Classifiers

Treesearch

Pei Li; Jing He; A. Lynn Abbott; Daniel L. Schmoldt

1996-01-01

This paper analyses computed tomography (CT) images of hardwood logs, with the goal of locating internal defects. The ability to detect and identify defects automatically is a critical component of efficiency improvements for future sawmills and veneer mills. This paper describes an approach in which 1) histogram equalization is used during preprocessing to normalize...

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

NASA Technical Reports Server (NTRS)

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

2003-01-01

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

Suppression of nucleation mode particles by biomass burning in an urban environment: a case study.

PubMed

Agus, Emily L; Lingard, Justin J N; Tomlin, Alison S

2008-08-01

Measurements of concentrations and size distributions of particles 4.7 to 160 nm were taken using an SMPS during the bonfire and firework celebrations on Bonfire Night in Leeds, UK, 2006. These celebrations provided an opportunity to study size distributions in a unique atmospheric pollution situation during and following a significant emission event due to open biomass burning. A log-normal fitting program was used to determine the characteristics of the modal groups present within hourly averaged size distributions. Results from the modal fitting showed that on bonfire night the smallest nucleation mode, which was present before and after the bonfire event and on comparison weekends, was not detected within the size distribution. In addition, there was a significant shift in the modal diameters of the remaining modes during the peak of the pollution event. Using the concept of a coagulation sink, the atmospheric lifetimes of smaller particles were significantly reduced during the pollution event, and thus were used to explain the disappearance of the smallest nucleation mode as well as changes in particle count mean diameters. The significance for particle mixing state is discussed.

Bimodal Distributions of Ozone in Relation to Water Vapor, Cloud Hydrometeors, and Other Chemical Tracers Over the Tropical Western Pacific

NASA Astrophysics Data System (ADS)

Steinmann, K. M.; Diao, M.

2017-12-01

The main objective of this work is to use the in-situ observations from the 2014 NSF Convective Transport of Active Species in the Tropics (CONTRAST) campaign to analyze the relationships among the distributions of ozone, water vapor, relative humidity, cloud hydrometers, and other chemical tracers in the Tropical Western Pacific. Previous analysis by Pan et al.(2015) observed a bimodal distribution of ozone: The first mode was observed around 20 ppbv and the second mode was observed around 60 ppbv. When RH was restricted to between 45% and 100%, the second mode was no longer observed, leaving only the first mode. Based on those results, this study looks at the distributions of different chemical tracers, RH, and water vapor. Preliminary analysis shows an increased concentration of ozone around a pressure of 150 hPa for "clear-sky" conditions, while the ozone concentration at the same pressure level for "in-cloud" conditions was around 40 ppbv lower. The differences between "clear-sky" and "in-cloud" average ozone concentrations become much smaller when restricting the analyzing RH to above 45%, indicating that ozone distributions have a stronger relationship with the magnitudes of RH than with the existence of clouds. The contrast between "clear-sky" and "in-cloud" conditions was not clearly observed for carbon monoxide (CO), CH3CN, or HCN. An anti-correlation is clearly observed in a ΔO3 vs. ΔLog10Q plot (where Q stands for water vapor mixing ratio), where larger ΔO3 values are observed at lower ΔLog10Q values. In addition, a weak anti-correlation is also observed in plots for ozone vs. Log10Q. When analyzing CO concentrations, only a weak anti-correlation is observed in a CO vs. Log10Q, while no strong correlation was observed in ΔCO vs. ΔLog10Q. For two biomass burning tracers, CH3CN and HCN, a positive correlation is observed between CH3CN and Log10Q, but an anti-correlation is observed between HCN and Log10Q. Analysis of vertical velocity, updraft frequency, and potential temperature will also be examined.

Valid analytical performance specifications for combined analytical bias and imprecision for the use of common reference intervals.

PubMed

Hyltoft Petersen, Per; Lund, Flemming; Fraser, Callum G; Sandberg, Sverre; Sölétormos, György

2018-01-01

Background Many clinical decisions are based on comparison of patient results with reference intervals. Therefore, an estimation of the analytical performance specifications for the quality that would be required to allow sharing common reference intervals is needed. The International Federation of Clinical Chemistry (IFCC) recommended a minimum of 120 reference individuals to establish reference intervals. This number implies a certain level of quality, which could then be used for defining analytical performance specifications as the maximum combination of analytical bias and imprecision required for sharing common reference intervals, the aim of this investigation. Methods Two methods were investigated for defining the maximum combination of analytical bias and imprecision that would give the same quality of common reference intervals as the IFCC recommendation. Method 1 is based on a formula for the combination of analytical bias and imprecision and Method 2 is based on the Microsoft Excel formula NORMINV including the fractional probability of reference individuals outside each limit and the Gaussian variables of mean and standard deviation. The combinations of normalized bias and imprecision are illustrated for both methods. The formulae are identical for Gaussian and log-Gaussian distributions. Results Method 2 gives the correct results with a constant percentage of 4.4% for all combinations of bias and imprecision. Conclusion The Microsoft Excel formula NORMINV is useful for the estimation of analytical performance specifications for both Gaussian and log-Gaussian distributions of reference intervals.