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Middle East respiratory syndrome coronavirus (MERS-CoV) remains a notable disease and poses a significant threat to global public health. The Arabian Peninsula is considered a major global epicentre for the disease and the virus has crossed regional and continental boundaries since 2012. In this study, we focused on exploring the temporal dynamics of MERS-CoV in human populations in the Arabian Peninsula between 2012 and 2017, using publicly available data on case counts and combining two analytical methods. Disease progression was assessed by quantifying the time-dependent reproductive number (TD-Rs), while case series temporal pattern was modelled using the AutoRegressive Integrated Moving Average (ARIMA). We accounted for geographical variability between three major affected regions in Saudi Arabia including Eastern Province, Riyadh and Makkah. In Saudi Arabia, the epidemic size was large with TD-Rs >1, indicating significant spread until 2017. In both Makkah and Riyadh regions, the epidemic progression reached its peak in April 2014 (TD-Rs > 7), during the highest incidence period of MERS-CoV cases. In Eastern Province, one unique super-spreading event (TD-R > 10) was identified in May 2013, which comprised of the most notable cases of human-to-human transmission. Best-fitting ARIMA model inferred statistically significant biannual seasonality in Riyadh region, a region characterised by heavy seasonal camel-related activities. However, no statistical evidence of seasonality was identified in Eastern Province and Makkah. Instead, both areas were marked by an endemic pattern of cases with sporadic outbreaks. Our study suggested new insights into the epidemiology of the virus, including inferences about epidemic progression and evidence for seasonality. Despite the inherent limitations of the available data, our conclusions provide further guidance to currently implement risk-based surveillance in high-risk populations and, subsequently, improve related interventions strategies against the epidemic at country and regional levels.

Within the field of cytogenetic biodosimetry, Poisson regression is the classical approach for modeling the number of chromosome aberrations as a function of radiation dose. However, it is common to find data that exhibit overdispersion. In practice, the assumption of equidispersion may be violated due to unobserved heterogeneity in the cell population, which will render the variance of observed aberration counts larger than their mean, and/or the frequency of zero counts greater than expected for the Poisson distribution. This phenomenon is observable for both full- and partial-body exposure, but more pronounced for the latter. In this work, different methodologies for analyzing cytogenetic chromosomal aberrations datasets are compared, with special focus on zero-inflated Poisson and zero-inflated negative binomial models. A score test for testing for zero inflation in Poisson regression models under the identity link is also developed.

The Bayesian framework has been shown to be very useful in cytogenetic dose estimation. This approach allows description of the probability of an event in terms of previous knowledge, e.g. its expectation and/or its uncertainty. A new R package entitled radir (radiation inverse regression) has been implemented with the aim of reproducing a recent Bayesian-type dose estimation methodology. radir adopts the method of dose estimation under the Poisson assumption of the responses (the chromosomal aberrations counts) for the required dose-response curve (typically linear or quadratic). The individual commands are described in detail and relevant examples of the use of the methods and the corresponding radir software tools are given. The suitability of this methodology is highlighted and its application encouraged by providing a user-friendly command-type software interface within the R statistical software (version 3.1.1 or higher), which includes a complete manual.

Influenza is a costly disease for pig producers and understanding its epidemiology is critical to control it. In this study, we aimed to estimate the herd-level prevalence and seasonality of influenza in breed-to-wean pig farms, evaluate the correlation between influenza herd-level prevalence and meteorological conditions, and characterize influenza genetic diversity over time. A cohort of 34 breed-to-wean farms with monthly influenza status obtained over a 5-year period in piglets prior to wean was selected. A farm was considered positive in a given month if at least one oral fluid tested influenza positive by reverse transcriptase polymerase chain reaction. Influenza seasonality was assessed combining autoregressive integrated moving average (ARIMA) models with trigonometric functions as covariates. Meteorological conditions were gathered from local land-based weather stations, monthly aggregated and correlated with influenza herd-level prevalence. Influenza herd-level prevalence had a median of 28% with a range from 7 to 57% and followed a cyclical pattern with levels increasing during fall, peaking in both early winter (December) and late spring (May), and decreasing in summer. Influenza herd-level prevalence was correlated with mean outdoor air absolute humidity (AH) and temperature. Influenza genetic diversity was substantial over time with influenza isolates belonging to 10 distinct clades from which H1 delta 1 and H1 gamma 1 were the most common. Twenty-one percent of farms had three different clades co-circulating over time, 18% of farms had two clades, and 41% of farms had one clade. In summary, our study showed that influenza had a cyclical pattern explained in part by air AH and temperature changes over time, and highlighted the importance of active surveillance to identify high-risk periods when strategic control measures for influenza could be implemented.

This article is about how to improve the positional dispensing accuracy of low-volume (microliters) drops and to understand the factors affecting them. These same parameters can be investigated to reduce deleterious effects on dispensing performance. Many applications, such as those in immunoassay diagnostics, require accurate volumetric dispensing and are also less tolerant of other phenomena that cause the reagent to be located outside the target area of interest. In this article, we work with liquid inertia. This phenomenon is present in positional dispensing and affects its accuracy. The negative effect of liquid inertia is reduced by changing parameters such as pressure and the diameter of the involved conducts.

We present a model for under-reported time series count data in which the underlying process satisfy an INAR(1) structure. Parameters are estimated through a naive method based on the theoretical expression of the autocorrelation function of the underlying process, and also by means of the forward algorithm. The hidden process is reconstructed using the Viterbi algorithm, and a real data example is discussed.

One of the key clues to consider rainfall as a self-organized critical phenomenon is the existence of power-law distributions for rain-event sizes. We have studied the problem of universality in the exponents of these distributions by means of a suitable statistic whose distribution is inferred by several variations of a permutational test. In contrast to more common approaches, our procedure does not suffer from the difficulties of multiple testing and does not require the precise knowledge of the uncertainties associated to the power-law exponents. When applied to seven sites monitored by the Atmospheric Radiation Measurement Program the tests lead to the rejection of the universality hypothesis, despite the fact that the exponents are rather close to each other. We discuss the reasons of the rejection.

In this paper we introduce the one-inflated bivariate Beta distribution as a new approach to analyze matching scores related to retinal image identification in lambs. These kind of data sets present many values equal to one, the perfect matching, and this justifies the introduction of one-inflation patterns. In addition, matching scores are correlated according to several bivariate patterns: left and right eye, 3 and 12 months of age, etc. Some examples of applications are given.

Newborn Ripollesa lambs (n = 143) were used to assess the optimal age at which the vascular pattern of the retina can be used as a reference for identification and traceability. Retinal images from both eyes were recorded from birth to yearling (d 1, 8, 30, 82, 180, and 388 of age) in duplicate (2,534 images) using a digital camera specially designed for livestock (Optibrand, Fort Collins, CO). Intra- and inter-age image comparisons (9,316 pairs of images) were carried out, and matching score (MS) was used as the exclusion criterion of lamb identity (MS 12 mo of age and ~50 kg of BW, n = 25). Values of MS were treated with a model based on the 1-inflated bivariate beta distribution, and treated data were compared by using a likelihood ratio test. Intra-age image comparisons showed that average MS and percentage of images with MS ≥70 increased (P 0.05); no differences were detected for 30-d images (97.4 and 98.0%, respectively, for RR and YR lambs; P > 0.05). Total percentage of matching was achieved when images were obtained from older lambs (180 and 388 d). In conclusion, retinal imaging was a useful tool for verifying the identity and auditing the traceability of live lambs from suckling to yearling. Matching scores were satisfactory when the reference retinal images were obtained from 1-mo-old or older lambs.

With the objective of verifying the presumed identity of sheep in a traceability study based on visual ear tags and electronic boluses, retinal image recognition was used as an auditing biomarker on 152 lambs of 2 dairy breeds (Manchega, n=82; Lacaune, n=70). Lambs were identified with temporary ear tags (birth to weaning), and with official ear tags and electronic mini-boluses (weaning to yearling). At 3 mo of age, 58 lambs were recruited for flock replacement, and the rest were transported to a slaughterhouse. Retinal images (RI) and capturing times (CT) were recorded from the left and right eyes of each lamb in duplicate and by the same operator using an OptiReader device (Optibrand, Fort Collins, CO) at 3, 6, and 12 mo of age in 152, 58, and 58 lambs, respectively. The 3-mo RI were used as reference images and to assess operator training and accuracy of the technique. Intra- and inter-age comparisons were made to obtain the matching score (MS; 0 to 100) of pairs of RI from the same eye, using Optibrand's software. Operator skill improved with training sessions, but MS reached a plateau after the sixth session (264 images; MS=93.2 ± 1.5). Values of CT also decreased in trained compared with untrained operators (63 ± 5 vs. 144 ± 15 s, respectively; P 70, which supported 100% lamb traceability. In conclusion, retinal imaging was an accurate technique for auditing the identity of living lambs from weaning to yearling.

In this paper, the r th-order univariate Hermite distributions are proposed to model the number of dicentrics in biological dosimetry. These families of distributions are introduced from compound Poisson process modelling. Regression models appropriate for analysing the number of dicentrics as a function of doses of radiation are presented, and an example of application is also given.

Consider two-parameter statistical models for positive continuous observations. Suppose that these models are closed under change of scale and under reciprocals, properties that are very appropriate when the observations are ratios of positive magnitudes. Additionally, suppose that the maximum likelihood estimator of the population mean is the sample mean (Gauss's principle). Surprisingly, only one statistical model satisfies these three properties and this is a special case of the generalized inverse gaussian family of distributions known as Harmonic Law.

In this work, we deal with correlated under-reported data through INAR(1)-hidden Markov chain models. These models are very flexible and can be identified through its autocorrelation function, which has a very simple form. A naïve method of parameter estimation is proposed, jointly with the maximum likelihood method based on a revised version of the forward algorithm. The most-probable unobserved time series is reconstructed by means of the Viterbi algorithm. Several examples of application in the field of public health are discussed illustrating the utility of the models. Copyright © 2016 John WileySons, Ltd.

Rural environment, due to its specific characteristics, requires an adjustment of the pedagogical approach in education. This environment is characterized by: 1) life at work, family life, social life, life in leisure time, all focused and running according to the rhythm of the profession; 2) attaching no importance to discussions and speeches – facts and deeds are of the greatest importance; 3) relative difficulty in articulating and sharing thoughts; 4) possible inferiority complex towards the people of the city; 5) professed prejudgments can lead to doubts about the right to education and development; 6) established belief that one should not change habits; 7) lack of trust in the novelty and the unknown; 8) mentality inducing the situation when innovations are introduced by influential people or leaders; 9) independence of character and activity; 10) importance of cultural transmission; 11) and predominance of the oral tradition over the written one. Some countries have successfully adapted education to the reality of rural life. Others are trying to do so, also being quite successful in that. “Despite different cultures, all peasants react in the same way!” (Blois, interview). Le milieu rural présente quelques caractéristiques induisant une pédagogie de formation adaptée. Parmi ces caractéristiques, on peut relever : 1) la vie de travail, la vie de famille, la vie sociale, la vie de loisirs, orientées et rythmées par les exigences de la profession ; 2) le poids faible des discussions ou des discours : seuls les faits et les actes ont de la valeur ; 3) la difficulté relative à s’exprimer et à faire connaître sa pensée ; 4) un éventuel complexe d’infériorité face au citadin ; 5) des préjugés ténus qui peuvent faire douter d’avoir le droit de se cultiver et de s’épanouir ; 6) l’idée prégnante qu’il ne faut surtout rien changer aux habitudes ; 7) une certaine méfiance face à la nouveauté et à l’inconnu ; 8) la mentalité qui oblige à faire passer l’innovation par des personnes influentes ou par des leaders ; 9) une indépendance de caractère et une autonomie d’entreprise ; 10) le poids de la transmission ; 11) et de la tradition orale par rapport à l’écrit. Certains pays ont innové pour adapter la formation à cette réalité, avec des succès incontestables. D’autres pays s’y essaient avec des succès non négligeables, car « même si la culture n’est pas la même, tous les paysans réagissent de la même façon ! » (Blois, entretiens).

In this article, tests are developed which can be used to investigate the goodness-of-fit of the skew-normal distribution in the context most relevant to the data analyst, namely that in which the parameter values are unknown and are estimated from the data. We consider five test statistics chosen from the broad Cramer–von Mises and Kolmogorov–Smirnov families, based on measures of disparity between the distribution function of a fitted skew-normal population and the empirical distribution function. The sampling distributions of the proposed test statistics are approximated using Monte Carlo techniques and summarized in easy to use tabular form. We also present results obtained from simulation studies designed to explore the true size of the tests and their power against various asymmetric alternative distributions.

It is well known that the Hodges–Lehmann estimator is asymptotically efficient for the location parameter of the logistic distribution. In this article we give a simple and direct proof that this property also characterizes the logistic between all the symmetric location distributions under mild conditions. Using pseudolikelihood, we also show how to find from the Hodges–Lehmann estimator an asymptotically efficient estimator of the scale parameter of the logistic distribution.

In this article we characterize all two-parameter count distributions (satisfying very general conditions) that are partially closed under addition. We also find those for which the maximum likelihood estimator of the population mean is the sample mean. Mixed Poisson models satisfying these properties are completely determined. Among these models are the negative binomial, Poisson-inverse Gaussian, and other known distributions. New count distributions can also be constructed using these characterizations. Three examples of application are given.

We characterize all symmetric location models for which a linear combination of the median and the sample mean is an asymptotically efficient estimator of the location parameter. The resulting model can be understood as a symmetrized or double truncated normal distribution. A simple algorithm to estimate the parameters is given and an application is presented.

An analysis of the length of productive life in the Bruna dels Pirineus beef breed was performed with a non-parametric approach giving an average value of 9 years of productive life, and a corresponding replacement rate of 11%. Using a proportional hazards model stratified by herd, the influence of calf birth weight and weight gain until weaning, calving difficulty, calving interval and age at first calving on length of productive life were studied. Two models were explored: the first one included time-dependent variables taking the current value of the covariate at each calving date, while the second one also comprised time-dependent interactions between the value of the covariate of the current calving and its mean value during the last (up to) three previous calvings. Results from the first model showed that the risk of culling increases with very high ages at first calving, increasing calving difficulties, very large calf birth weights, very small weight gains until weaning and very long calving intervals. Furthermore, results from the second model showed that these increases also depend upon a sequence of values for the same covariate in previous calvings. Finally, these higher risks of culling implied lower survival functions that increased replacement rates but only slightly decreased average performances.

This article reports on two-parameter count distributions (satisfying very general conditions) that are closed under addition so that their maximum likelihood estimator (MLE) of the population mean is the sample mean. The most important of these in practice, the generalized Hermite distribution, is analyzed, and a necessary and sufficient condition is given to ensure that the MLE is the solution of likelihood equations. Score test to contrast the Poisson assumption is studied, and two examples of applications are given.

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A new zero-inflated Poisson model is introduced for the estimation of partial body irradiation dose and fraction of body irradiated. The Bayes factors are introduced as tools to help determine whether a data set of chromosomal aberrations obtained from a blood sample reflects partial or whole body irradiation. Two examples of simulated cytogenetic radiation exposure data are presented to demonstrate the usefulness of this methodology in cytogenetic biological dosimetry.

“The final publication is available at Springer via http://dx.doi.org/10.1007/s00184-014-0497-5" Suppose that follows a simple AR(1) model, that is, it can be expressed as , where is a white noise with mean equal to and variance . There are many examples in practice where these assumptions hold very well. Consider . We shall show that the autocorrelation function of characterizes the distribution of W-t.

A compound Poisson distribution is a natural choice for the innovations of an INAR(1) model. If the support of the compounding distribution is finite (Hermite-type distributions), the observations’ marginal distribution belongs to the same family and it can be computed exactly. In the infinite case, however, which includes the popular choice of negative binomial innovations, this is not so simple. We propose two types of Hermite approximations for this case and investigate their quality in a numerical study.

[This corrects the article DOI: 10.1371/journal.pone.0114137.].

For Location and Scale models with Type I Censored Data the estimation of the parameters based on likelihood is analyzed. When the sample size is very small the usual procedures for inference based on the asymptotic distribution of the statistics do not function properly. We develop higher-order asymptotic methods and their performance is investigated by Monte Carlo experiments.

Within the field of cytogenetic biodosimetry, Poisson regression is the classical approach for modeling the number of chromosome aberrations as a function of radiation dose. However, it is common to find data that exhibit overdispersion. In practice, the assumption of equidispersion may be violated due to unobserved heterogeneity in the cell population, which will render the variance of observed aberration counts larger than their mean, and/or the frequency of zero counts greater than expected for the Poisson distribution. This phenomenon is observable for both full- and partial-body exposure, but more pronounced for the latter. In this work, different methodologies for analyzing cytogenetic chromosomal aberrations datasets are compared, with special focus on zero-inflated Poisson and zero-inflated negative binomial models. A score test for testing for zero inflation in Poisson regression models under the identity link is also developed.

The authors give tests of fit for the hyperbolic distribution, based on the Cramer-von Mises statistic W2. They consider the general case with four parameters unknown, and some specific cases where one or two parameters are fixed. They give two examples using stock price data.

We show that the likelihood ratio test of exponentiality against singly truncated normal alternatives is the uniformly most powerful unbiased test and can be expressed in terms of the sampling coefficient of variation. This test is closely related to Greenwood's statistic for testing departures from the uniform distribution. We provide a way to approximate the critical points of the test, using saddlepoint methods, that gives a high degree of accuracy.

Classical methods of assessing the uncertainty associated with radiation doses estimated using cytogenetic techniques are now extremely well defined. However, several authors have suggested that a Bayesian approach to uncertainty estimation may be more suitable for cytogenetic data, which are inherently stochastic in nature. The Bayesian analysis framework focuses on identification of probability distributions (for yield of aberrations or estimated dose), which also means that uncertainty is an intrinsic part of the analysis, rather than an 'afterthought'. In this paper Bayesian, as well as some more advanced classical, data analysis methods for radiation cytogenetics are reviewed that have been proposed in the literature. A practical overview of Bayesian cytogenetic dose estimation is also presented, with worked examples from the literature.

A number of authors have suggested that a Bayesian approach may be most appropriate for analysis of cytogenetic radiation dosimetry data. In the Bayesian framework, probability of an event is described in terms of previous expectations and uncertainty. Previously existing, or prior, information is used in combination with experimental results to infer probabilities or the likelihood that a hypothesis is true. It has been shown that the Bayesian approach increases both the accuracy and quality assurance of radiation dose estimates. New software entitled CytoBayesJ has been developed with the aim of bringing Bayesian analysis to cytogenetic biodosimetry laboratory practice. CytoBayesJ takes a number of Bayesian or ‘Bayesian like’ methods that have been proposed in the literature and presents them to the user in the form of simple user-friendly tools, including testing for the most appropriate model for distribution of chromosome aberrations and calculations of posterior probability distributions. The individual tools are described in detail and relevant examples of the use of the methods and the corresponding CytoBayesJ software tools are given. In this way, the suitability of the Bayesian approach to biological radiation dosimetry is highlighted and its wider application encouraged by providing a user-friendly software interface and manual in English and Russian.

Background High-throughput RNA sequencing (RNA-seq) offers unprecedented power to capture the real dynamics of gene expression. Experimental designs with extensive biological replication present a unique opportunity to exploit this feature and distinguish expression profiles with higher resolution. RNA-seq data analysis methods so far have been mostly applied to data sets with few replicates and their default settings try to provide the best performance under this constraint. These methods are based on two well-known count data distributions: the Poisson and the negative binomial. The way to properly calibrate them with large RNA-seq data sets is not trivial for the non-expert bioinformatics user. Results Here we show that expression profiles produced by extensively-replicated RNA-seq experiments lead to a rich diversity of count data distributions beyond the Poisson and the negative binomial, such as Poisson-Inverse Gaussian or Pólya-Aeppli, which can be captured by a more general family of count data distributions called the Poisson-Tweedie. The flexibility of the Poisson-Tweedie family enables a direct fitting of emerging features of large expression profiles, such as heavy-tails or zero-inflation, without the need to alter a single configuration parameter. We provide a software package for R called implementing a new test for differential expression based on the Poisson-Tweedie family. Using simulations on synthetic and real RNA-seq data we show that yields P-values that are equally or more accurate than competing methods under different configuration parameters. By surveying the tiny fraction of sex-specific gene expression changes in human lymphoblastoid cell lines, we also show that accurately detects differentially expressed genes in a real large RNA-seq data set with improved performance and reproducibility over the previously compared methodologies. Finally, we compared the results with those obtained from microarrays in order to check for reproducibility. Conclusions RNA-seq data with many replicates leads to a handful of count data distributions which can be accurately estimated with the statistical model illustrated in this paper. This method provides a better fit to the underlying biological variability; this may be critical when comparing groups of RNA-seq samples with markedly different count data distributions. The package forms part of the Bioconductor project and it is available for download at http://www.bioconductor.org.

The aim of this prospective study is to evaluate prostanoid (prostacyclin and thromboxane) and lipid peroxide levels at the portal and hepatic veins, and their relation to immediate postoperative liver function. Nineteen patients with liver cirrhosis undergoing orthotopic liver transplantation were prospectively studied. Blood samples were obtained within 5 min and 1 and 2 hr after reperfusion of the new liver, through a catheter placed at the portal vein in the recipient and another at the left hepatic vein in the donor liver. Plasma prostacyclin and thromboxane were analyzed by HPLC and RIA. The formation of lipid peroxides was determined and expressed in terms of thiobarbituric acid-reacting substances. Immediate postoperative liver function was evaluated using the transaminase levels within the first 48 hr and the early postoperative graft function score, as described previously. After reperfusion, only determinations at 5 min were related with liver function. Either prostacyclin (R = -0.61, P = 0.004) levels at the hepatic vein or prostacyclin production (subtraction between hepatic and portal vein levels) (R = -0.47, P = 0.04) correlated significantly with the early postoperative graft function score. Besides, there was a significant relationship between lipid peroxide production as measured by thiobarbituric acid-reacting substances and a worse early postoperative graft function score (R = 0.61, P = .005). These results suggest that prostacyclin released after liver grafting attenuates preservation and reperfusion damage of the liver, supporting the hypothesis that there is an imbalance of prostanoids within the microvasculature in patients with a compromised postoperative liver function. Our results agree with the involvement of some degree of lipid peroxidation products in the damage of hepatocytes during anoxia and reperfusion.

Due to the great number of congeners, the use of the correct nomenclature for PCBs is a difficult task, and unfortunately errors in the assignment of chemical denominations are not unusual. We suggest in this paper to correctly apply the rules initially introduced by Ballschmiter and Zell in 1980, which differ from those of the IUPAC. A simple algorithm in BASIC was created to help researchers in this field to denominate all the 209 congeners by their correct Ballschmiter and Zell and/or IUPAC systematic names.

The genetic structure and relationships among 10 Spanish dog breeds have been studied by using F statistics. Data came from 21 structural genic loci that codify for blood-soluble proteins and enzymes detected by electrophoresis. Of the 21 loci, 11 were found to be polymorphic. The study was done at three levels of hierarchical differentiation: ancestral trunks, breeds, and subpopulations. The deficit of heterozygotes was estimated at the subpopulation, breed, and ancestral trunk levels, with values of 4.0%, 6.5%, and 11.2%, respectively. In the whole population, the deficit of heterozygotes was about 17%. The proportion of genetic variability attributable to differences between subpopulations, breeds, and ancestral trunks was estimated to be 14.2%, 9.9%, and 6.9%, respectively. The dendrogram, obtained by using values of genic differentiation (FST) as a measure of the genetic distance among populations, is topologically identical to the one obtained using Nei's index of distance, which indicates a high correlation (r = .99) between both distances. These racial groupings, however, differ from the grouping obtained from historical, archeological, and morphological data.

The objective of the study was to evaluate epidemiological data derived from 2735 canine uroliths received by Hill's Pet Nutrition from Spain and Portugal between January 2004 and December 2006. The results of quantitative analysis from Minnesota Urolith Center (MUC) were compared with that from other countries and interrelations of mineral composition, age, breed, and gender were determined. The most frequent calculus was calcium oxalate (38.1%) followed by struvite (32.9%). Eighty-three breeds plus crossbreeds (25%) were identified. In all of them, but Dalmatians, calcium oxalate and struvite accounted for 71-78%. The mean age of urolith appearance was 7.6 years. There was a significant difference in the frequency of different uroliths composition among the six most common breeds presenting urolithiasis in Spain and Portugal (Yorkshire terrier, Miniature Schnauzer, Cocker Spaniel, Poodle, Shih Tzu and Dalmatian). This is the first report on xanthine urolithiasis found in Spain. Prevalence of cystine calculi was significantly lower (3.2%) than that reported previously in parts of Spain (26%).

In biological dosimetry by dicentric analysis, an exposure to radiation is considered non-homogeneous if the dicentric cell distribution shows overdispersion with respect to Poisson distribution. Traditionally, when this occurs, all non-homogeneous exposures are considered as partial-body exposures, assuming that there is only a mixture of irradiated and nonirradiated cells. The methods to estimate the dose in the irradiated fraction and the initial fraction of irradiated cells are based on separating which part of the cells without aberrations comes from the nonirradiated or irradiated fractions. In this study we show a new approach based on a mixed Poisson model, which allows for a distinction to be made between partial and heterogeneous exposures. To validate this approach blood samples from two donors, a male and a female, irradiated at different doses, were mixed at a 1:1 proportion to simulate partial and heterogeneous exposures. The results show a good agreement between the observed proportion of male and female cells and the proportion estimated by the model. Additionally, a good agreement was observed between the delivered doses, the initial fraction of cells and the ones estimated by the model. This good agreement was also observed after very high-dose irradiation (up to 17 Gy), when the lymphocyte cultures were treated with caffeine. Based on these results, we propose the use of this mixed Poisson model for a more accurate assessment of non-homogeneous exposures.

In this paper we characterize all the $r$-parameter families of count distributions (satisfying mild conditions) that are closed under addition and under binomial subsampling. Surprisingly, few families satisfy both properties and the resulting models consist of the $r$th-order univariate Hermite distributions. Among these, we find the Poisson ($r=1$) and the ordinary Hermite distributions ($r=2$)., Published at http://dx.doi.org/10.3150/07-BEJ6021 in the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm)

The skew-Laplace distribution is frequently used to fit the logarithm of particle sizes and it is also used in Economics, Engineering, Finance and Biology. We show the Anderson-Darling and Cram´ er-von Mises goodness of fit tests for this distribution.

The effect of atropine (1 μM) and N G -nitro- l -arginine ( l -NOARG, 10 μM) on electrical field stimulation induced relaxation in proximal and distal segments of guinea-pig taenia caeci in the presence of guanethidine (4 μM) was studied. The frequency-dependent relaxations were lower in proximal than in distal segments both in the presence and in the absence of atropine. The effect of l -NOARG (an inhibitor of nitric oxide (NO) synthase) on relaxation in the presence of atropine depended on the frequency of electrical stimulation and the segment used; the effect of l -NOARG was greater in proximal segments than in distal segments. In the absence of atropine, the inhibitory effect of l -NOARG was the same in both segments at all frequencies tested. This study demonstrates differences between the opposite extremes of guinea-pig taenia caeci in relaxations induced by electrical stimulation. Our data also show a role of NO that is dependent on the integrity of cholinergic transmission.

For a two-parameter exponential model with increasing failure rate (IFR) or decreasing failure rate (DFR) distributions necessary and sufficient conditions of the existence of a solution of the likelihood equations are given. Also, all of the scale-invariant two-parameter statistical models closed by raising to a power and by exponential tilting are introduced. The conditions of existence of a solution of the likelihood equations are studied for these invariant models, and the models are applied to obtain some uniformly most powerful unbiased tests of exponentially against alternatives in these models.