Constraining the GRB-Magnetar Model by Means of the Galactic Pulsar Population

A large fraction of Gamma-ray bursts (GRBs) displays an X-ray plateau phase within <105 s from the prompt emission, proposed to be powered by the spin-down energy of a rapidly spinning newly born magnetar. In this work we use the properties of the Galactic neutron star population to constrain the GRB-magnetar scenario. We re-analyze the X-ray plateaus of all Swift GRBs with known redshift, between 2005 January and 2014 August. From the derived initial magnetic field distribution for the possible magnetars left behind by the GRBs, we study the evolution and properties of a simulated GRB-magnetar population using numerical simulations of magnetic field evolution, coupled with Monte Carlo simulations of Pulsar Population Synthesis in our Galaxy. We find that if the GRB X-ray plateaus are powered by the rotational energy of a newly formed magnetar, the current observational properties of the Galactic magnetar population are not compatible with being formed within the GRB scenario (regardless of the GRB type or rate at z = 0). Direct consequences would be that we should allow the existence of magnetars and "super-magnetars" having different progenitors, and that Type Ib/c SNe related to Long GRBs form systematically neutron stars with higher initial magnetic fields. We put an upper limit of ≤16 "super-magnetars" formed by a GRB in our Galaxy in the past Myr (at 99% c.l.). This limit is somewhat smaller than what is roughly expected from Long GRB rates, although the very large uncertainties do not allow us to draw strong conclusion in this respect.

A population balance model for high shear granulation

In a previous paper, Hoornaert et al. (Powder Technol. 96 (1998); 116-128) presented data from granulation experiments performed in a 50 L Lodige high shear mixer. In this study that same data was simulated with a population balance model. Based on an analysis of the experimental data, the granulation process was divided into three separate stages: nucleation, induction, and coalescence growth. These three stages were then simulated separately, with promising results. it is possible to derive a kernel that fit both the induction and the coalescence growth stage. Modeling the nucleation stage proved to be more challenging due to the complex mechanism of nucleus formation. From this work some recommendations are made for the improvement of this type of model.

An investigation into effects of long-distance seed dispersal on organelle population genetic structure and colonization rate: a model analysis

A simulation-based modelling approach is used to examine the effects of stratified seed dispersal (representing the distribution of the majority of dispersal around the maternal parent and also rare long-distance dispersal) on the genetic structure of maternally inherited genomes and the colonization rate of expanding plant populations. The model is parameterized to approximate postglacial oak colonization in the UK, but is relevant to plant populations that exhibit stratified seed dispersal. The modelling approach considers the colonization of individual plants over a large area (three 500 km x 10 km rolled transects are used to approximate a 500 km x 300 km area). Our approach shows how the interaction of plant population dynamics with stratified dispersal can result in a spatially patchy haplotype structure. We show that while both colonization speeds and the resulting genetic structure are influenced by the characteristics of the dispersal kernel, they are robust to changes in the periodicity of long-distance events, provided the average number of long-distance dispersal events remains constant. We also consider the effects of additional physical and environmental mechanisms on plant colonization. Results show significant changes in genetic structure when the initial colonization of different haplotypes is staggered over time and when a barrier to colonization is introduced. Environmental influences on survivorship and fecundity affect both the genetic structure and the speed of colonization. The importance of these mechanisms in relation to the postglacial spread and genetic structure of oak in the UK is discussed.

Optimal design for model discrimination and parameter estimation for itraconazole population pharmacokinetics in cystic fibrosis patients

Optimal sampling times are found for a study in which one of the primary purposes is to develop a model of the pharmacokinetics of itraconazole in patients with cystic fibrosis for both capsule and solution doses. The optimal design is expected to produce reliable estimates of population parameters for two different structural PK models. Data collected at these sampling times are also expected to provide the researchers with sufficient information to reasonably discriminate between the two competing structural models.

Customised birthweight: Coefficients for an Australian population and validation of the model

Background: Published birthweight references in Australia do not fully take into account constitutional factors that influence birthweight and therefore may not provide an accurate reference to identify the infant with abnormal growth. Furthermore, studies in other regions that have derived adjusted (customised) birthweight references have applied untested assumptions in the statistical modelling. Aims: To validate the customised birthweight model and to produce a reference set of coefficients for estimating a customised birthweight that may be useful for maternity care in Australia and for future research. Methods: De-identified data were extracted from the clinical database for all births at the Mater Mother's Hospital, Brisbane, Australia, between January 1997 and June 2005. Births with missing data for the variables under study were excluded. In addition the following were excluded: multiple pregnancies, births less than 37 completed week's gestation, stillbirths, and major congenital abnormalities. Multivariate analysis was undertaken. A double cross-validation procedure was used to validate the model. Results: The study of 42 206 births demonstrated that, for statistical purposes, birthweight is normally distributed. Coefficients for the derivation of customised birthweight in an Australian population were developed and the statistical model is demonstrably robust. Conclusions: This study provides empirical data as to the robustness of the model to determine customised birthweight. Further research is required to define where normal physiology ends and pathology begins, and which segments of the population should be included in the construction of a customised birthweight standard.

Subjective indicators of health held by the lay population:eudaimanistic model

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Population pharmacokinetic model of canrenone after intravenous administration of potassium canrenoate to paediatric patients

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT • Little is known about the pharmacokinetics of potassium canrenoate/canrenone in paediatric patients WHAT THIS STUDY ADDS • A population pharmacokinetic model has been developed to evaluate the pharmacokinetics of canrenone in paediatric patients who received potassium canrenoate as part of their therapy in the intensive care unit. AIMS To characterize the population pharmacokinetics of canrenone following administration of potassium canrenoate to paediatric patients. METHODS Data were collected prospectively from 23 paediatric patients (2 days to 10 years of age; median weight 4 kg, range 2.16–28.0 kg) who received intravenous potassium canrenoate (K-canrenoate) as part of their intensive care therapy for removal of retained fluids, e.g. in pulmonary oedema due to chronic lung disease and for the management of congestive heart failure. Plasma samples were analyzed by HPLC for determination of canrenone (the major metabolite and pharmacologically active moiety) and the data subjected to pharmacokinetic analysis using NONMEM. RESULTS A one compartment model best described the data. The only significant covariate was weight (WT). The final population models for canrenone clearance (CL/F) and volume of distribution (V/F) were CL/F (l h−1) = 11.4 × (WT/70.0)0.75 and V/F (l) = 374.2 × (WT/70) where WT is in kg. The values of CL/F and V/F in a 4 kg child would be 1.33 l h−1 and 21.4 l, respectively, resulting in an elimination half-life of 11.2 h. CONCLUSIONS The range of estimated CL/F in the study population was 0.67–7.38 l h−1. The data suggest that adjustment of K-canrenoate dosage according to body weight is appropriate in paediatric patients.

The effect of climate change on the population of sycamore lace bug (Corythuca ciliata, Say) based on a simulation model with phenological response

Climate change affects on insect populations in many ways: it can cause a shift in geographical spread, abundance, or diversity, it can change the location, the timing and the magnitude of outbreaks of pests and it can define the phenological or even the genetic properties of the species. Long-time investigations of special insect populations, simulation models and scenario studies give us very important information about the response of the insects far away and near to our century. Getting to know the potential responses of insect populations to climate change makes us possible to evaluate the adaptation of pest management alternatives as well as to formulate our future management policy. In this paper we apply two simple models, in order to introduce a complex case study for a Sycamore lace bug population. We test how the model works in case the whether conditions are very different from those in our days. Thus, besides we can understand the processes that happen in present, we can analyze the effects of a possible climate change, as well.

A population dynamical model of Operophtera brumata, L. extended by climatic factors

Setting out from the database of Operophtera brumata, L. in between 1973 and 2000 due to the Light Trap Network in Hungary, we introduce a simple theta-logistic population dynamical model based on endogenous and exogenous factors, only. We create an indicator set from which we can choose some elements with which we can improve the fitting results the most effectively. Than we extend the basic simple model with additive climatic factors. The parameter optimization is based on the minimized root mean square error. The best model is chosen according to the Akaike Information Criterion. Finally we run the calibrated extended model with daily outputs of the regional climate model RegCM3.1, regarding 1961-1990 as reference period and 2021-2050 with 2071-2100 as future predictions. The results of the three time intervals are fitted with Beta distributions and compared statistically. The expected changes are discussed.