Mean-Field critical behavior and ergodicity break in a nonequilibrium one-dimensional RSOS growth model

We investigate the nonequilibrium roughening transition of a one-dimensional restricted solid-on-solid model by directly sampling the stationary probability density of a suitable order parameter as the surface adsorption rate varies. The shapes of the probability density histograms suggest a typical Ginzburg-Landau scenario for the phase transition of the model, and estimates of the "magnetic" exponent seem to confirm its mean-field critical behavior. We also found that the flipping times between the metastable phases of the model scale exponentially with the system size, signaling the breaking of ergodicity in the thermodynamic limit. Incidentally, we discovered that a closely related model not considered before also displays a phase transition with the same critical behavior as the original model. Our results support the usefulness of off-critical histogram techniques in the investigation of nonequilibrium phase transitions. We also briefly discuss in the appendix a good and simple pseudo-random number generator used in our simulations.

On Equilibrium Distribution of a Reversible Growth Model

We study a probabilistic model of interacting spins indexed by elements of a finite subset of the d-dimensional integer lattice, da parts per thousand yen1. Conditions of time reversibility are examined. It is shown that the model equilibrium distribution converges to a limit distribution as the indexing set expands to the whole lattice. The occupied site percolation problem is solved for the limit distribution. Two models with similar dynamics are also discussed.

Parameter estimation in a growth model for a biological population

The motivating problem concerns the estimation of the growth curve of solitary corals that follow the nonlinear Von Bertalanffy Growth Function (VBGF). The most common parameterization of the VBGF for corals is based on two parameters: the ultimate length L∞ and the growth rate k. One aim was to find a more reliable method for estimating these parameters, which can capture the influence of environmental covariates. The main issue with current methods is that they force the linearization of VBGF and neglect intra-individual variability. The idea was to use the hierarchical nonlinear model which has the appealing features of taking into account the influence of collection sites, possible intra-site measurement correlation and variance heterogeneity, and that can handle the influence of environmental factors and all the reliable information that might influence coral growth. This method was used on two databases of different solitary corals i.e. Balanophyllia europaea and Leptopsammia pruvoti, collected in six different sites in different environmental conditions, which introduced a decisive improvement in the results. Nevertheless, the theory of the energy balance in growth ascertains the linear correlation of the two parameters and the independence of the ultimate length L∞ from the influence of environmental covariates, so a further aim of the thesis was to propose a new parameterization based on the ultimate length and parameter c which explicitly describes the part of growth ascribable to site-specific conditions such as environmental factors. We explored the possibility of estimating these parameters characterizing the VBGF new parameterization via the nonlinear hierarchical model. Again there was a general improvement with respect to traditional methods. The results of the two parameterizations were similar, although a very slight improvement was observed in the new one. This is, nevertheless, more suitable from a theoretical point of view when considering environmental covariates.

Atlas-Based Segmentation of Brain Tumor Images Using a Markov Random Field-Based Tumor Growth Model and Non-Rigid Registration

We propose a new and clinically oriented approach to perform atlas-based segmentation of brain tumor images. A mesh-free method is used to model tumor-induced soft tissue deformations in a healthy brain atlas image with subsequent registration of the modified atlas to a pathologic patient image. The atlas is seeded with a tumor position prior and tumor growth simulating the tumor mass effect is performed with the aim of improving the registration accuracy in case of patients with space-occupying lesions. We perform tests on 2D axial slices of five different patient data sets and show that the approach gives good results for the segmentation of white matter, grey matter, cerebrospinal fluid and the tumor.

Effects of probiotic bacteria in dogs with food responsive diarrhoea treated with an elimination diet

We evaluated whether a probiotic supplementation in dogs with food responsive diarrhoea (FRD) has beneficial effects on intestinal cytokine patterns and on microbiota. Twenty-one client-owned dogs with FRD were presented for clinically needed duodeno- and colonoscopy and were enrolled in a prospective placebo (PL)-controlled probiotic trial. Intestinal tissue samples and faeces were collected during endoscopy. Intestinal mRNA abundance of interleukin (IL)-5, -10, -12p40 and -13, tumour necrosis factor-alpha, transforming growth factor-beta1 and interferon (IFN)-gamma were analysed and numbers of Lactobacillus spp., Bifidobacterium spp., Enterococcus spp. and Enterobacteriaceae and supplemented probiotic bacteria were determined in faeces. The Canine Inflammatory Bowel Disease Activity Index, a scoring system comprising general attitude, appetite, faecal consistency, defecation frequency, and vomitus, decreased in all dogs (p < 0.0001). Duodenal IL-10 mRNA levels decreased (p = 0.1) and colonic IFN-gamma mRNA levels increased (p = 0.08) after probiotic treatment. Numbers of Enterobacteriaceae decreased in FRD dogs receiving probiotic cocktail (FRD(PC)) and FRD dogs fed PL (FRD(PL)) during treatment (p < 0.05), numbers of Lactobacillus spp. increased in FRD(PC after) when compared with FRD(PC before) (p < 0.1). One strain of PC was detected in five of eight FRD(PC) dogs after probiotic supplementation. In conclusion, all dogs clinically improved after treatment, but cytokine patterns were not associated with the clinical features irrespective of the dietary supplementation.

Robust effect sizes and their confidence intervals for group difference between trajectories in hierarchical linear growth model

Hierarchical linear growth model (HLGM), as a flexible and powerful analytic method, has played an increased important role in psychology, public health and medical sciences in recent decades. Mostly, researchers who conduct HLGM are interested in the treatment effect on individual trajectories, which can be indicated by the cross-level interaction effects. However, the statistical hypothesis test for the effect of cross-level interaction in HLGM only show us whether there is a significant group difference in the average rate of change, rate of acceleration or higher polynomial effect; it fails to convey information about the magnitude of the difference between the group trajectories at specific time point. Thus, reporting and interpreting effect sizes have been increased emphases in HLGM in recent years, due to the limitations and increased criticisms for statistical hypothesis testing. However, most researchers fail to report these model-implied effect sizes for group trajectories comparison and their corresponding confidence intervals in HLGM analysis, since lack of appropriate and standard functions to estimate effect sizes associated with the model-implied difference between grouping trajectories in HLGM, and also lack of computing packages in the popular statistical software to automatically calculate them. ^ The present project is the first to establish the appropriate computing functions to assess the standard difference between grouping trajectories in HLGM. We proposed the two functions to estimate effect sizes on model-based grouping trajectories difference at specific time, we also suggested the robust effect sizes to reduce the bias of estimated effect sizes. Then, we applied the proposed functions to estimate the population effect sizes (d ) and robust effect sizes (du) on the cross-level interaction in HLGM by using the three simulated datasets, and also we compared the three methods of constructing confidence intervals around d and du recommended the best one for application. At the end, we constructed 95% confidence intervals with the suitable method for the effect sizes what we obtained with the three simulated datasets. ^ The effect sizes between grouping trajectories for the three simulated longitudinal datasets indicated that even though the statistical hypothesis test shows no significant difference between grouping trajectories, effect sizes between these grouping trajectories can still be large at some time points. Therefore, effect sizes between grouping trajectories in HLGM analysis provide us additional and meaningful information to assess group effect on individual trajectories. In addition, we also compared the three methods to construct 95% confident intervals around corresponding effect sizes in this project, which handled with the uncertainty of effect sizes to population parameter. We suggested the noncentral t-distribution based method when the assumptions held, and the bootstrap bias-corrected and accelerated method when the assumptions are not met.^

Compression, gain, and nonlinear distortion in an active cochlear model with subpartitions

The propagation of inhomogeneous, weakly nonlinear waves is considered in a cochlear model having two degrees of freedom that represent the transverse motions of the tectorial and basilar membranes within the organ of Corti. It is assumed that nonlinearity arises from the saturation of outer hair cell active force generation. I use multiple scale asymptotics and treat nonlinearity as a correction to a linear hydroelastic wave. The resulting theory is used to explain experimentally observed features of the response of the cochlear partition to a pure tone, including: the amplification of the response in a healthy cochlea vs a dead one; the less than linear growth rate of the response to increasing sound pressure level; and the amount of distortion to be expected at high and low frequencies at basal and apical locations, respectively. I also show that the outer hair cell nonlinearity generates retrograde waves.

Establishment of a confluent monolayer model with human primary trophoblast cells: novel insights into placental glucose transport

STUDY HYPOTHESIS Using optimized conditions, primary trophoblast cells isolated from human term placenta can develop a confluent monolayer in vitro, which morphologically and functionally resembles the microvilli structure found in vivo. STUDY FINDING We report the successful establishment of a confluent human primary trophoblast monolayer using pre-coated polycarbonate inserts, where the integrity and functionality was validated by cell morphology, biophysical features, cellular marker expression and secretion, and asymmetric glucose transport. WHAT IS KNOWN ALREADY Human trophoblast cells form the initial barrier between maternal and fetal blood to regulate materno-fetal exchange processes. Although the method for isolating pure human cytotrophoblast cells was developed almost 30 years ago, a functional in vitro model with primary trophoblasts forming a confluent monolayer is still lacking. STUDY DESIGN, SAMPLES/MATERIALS, METHODS Human term cytotrophoblasts were isolated by enzymatic digestion and density gradient separation. The purity of the primary cells was evaluated by flow cytometry using the trophoblast-specific marker cytokeratin 7, and vimentin as an indicator for potentially contaminating cells. We screened different coating matrices for high cell viability to optimize the growth conditions for primary trophoblasts on polycarbonate inserts. During culture, cell confluency and polarity were monitored daily by determining transepithelial electrical resistance (TEER) and permeability properties of florescent dyes. The time course of syncytia-related gene expression and hCG secretion during syncytialization were assessed by quantitative RT-PCR and enzyme-linked immunosorbent assay, respectively. The morphology of cultured trophoblasts after 5 days was determined by light microscopy, scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Membrane makers were visualized using confocal microscopy. Additionally, glucose transport studies were performed on the polarized trophoblasts in the same system. MAIN RESULTS AND THE ROLE OF CHANCE During 5-day culture, the highly pure trophoblasts were cultured on inserts coated with reconstituted basement membrane matrix . They exhibited a confluent polarized monolayer, with a modest TEER and a size-dependent apparent permeability coefficient (Papp) to fluorescently labeled compounds (MW ∼400-70 000 Da). The syncytialization progress was characterized by gradually increasing mRNA levels of fusogen genes and elevating hCG secretion. SEM analyses confirmed a confluent trophoblast layer with numerous microvilli, and TEM revealed a monolayer with tight junctions. Immunocytochemistry on the confluent trophoblasts showed positivity for the cell-cell adhesion molecule E-cadherin, the tight junction protein 1 (ZO-1) and the membrane proteins ATP-binding cassette transporter A1 (ABCA1) and glucose transporter 1 (GLUT1). Applying this model to study the bidirectional transport of a non-metabolizable glucose derivative indicated a carrier-mediated placental glucose transport mechanism with asymmetric kinetics. LIMITATIONS, REASONS FOR CAUTION The current study is only focused on primary trophoblast cells isolated from healthy placentas delivered at term. It remains to be evaluated whether this system can be extended to pathological trophoblasts isolated from diverse gestational diseases. WIDER IMPLICATIONS OF THE FINDINGS These findings confirmed the physiological properties of the newly developed human trophoblast barrier, which can be applied to study the exchange of endobiotics and xenobiotics between the maternal and fetal compartment, as well as intracellular metabolism, paracellular contributions and regulatory mechanisms influencing the vectorial transport of molecules. LARGE-SCALE DATA Not applicable. STUDY FUNDING AND COMPETING INTERESTS This study was supported by the Swiss National Center of Competence in Research, NCCR TransCure, University of Bern, Switzerland, and the Swiss National Science Foundation (grant no. 310030_149958, C.A.). All authors declare that their participation in the study did not involve factual or potential conflicts of interests.

Optimal debt, endogenous fertility, and human capital externalities in a model with altruistic bequests

and human capital externalities. Because of such externalities, education investment is too low and fertility is too high. While education subsidies are the conventional means to deal with these problems, we show that the optimal policy also comprises debt even when distortionary taxes are used. The reason is that debt tips the usual trade-off between children's quantity and quality in favor of the latter by increasing the bequest cost of children. The optimal debt-output ratio exceeds 10% for plausible parameterization. (C) 2002 Elsevier B.V. All rights reserved.

Memory effects in a non-equilibrium growth model

We study memory effects in a kinetic roughening model. For d=1, a different dynamic scaling is uncovered in the memory dominated phases; the Kardar-Parisi-Zhang scaling is restored in the absence of noise. dc=2 represents the critical dimension where memory is shown to smoothen the roughening front (a=0). Studies on a discrete atomistic model in the same universality class reconfirm the analytical results in the large time limit, while a different scaling behavior shows up for twith t being the memory characteristic of the atomistic model. Results can be generalized for other nonconservative systems.

Language independent on-off voice over IP source model with lognormal transitions

The recent explosive growth of voice over IP (VoIP) solutions calls for accurate modelling of VoIP traffic. This study presents measurements of ON and OFF periods of VoIP activity from a significantly large database of VoIP call recordings consisting of native speakers speaking in some of the world's most widely spoken languages. The impact of the languages and the varying dynamics of caller interaction on the ON and OFF period statistics are assessed. It is observed that speaker interactions dominate over language dependence which makes monologue-based data unreliable for traffic modelling. The authors derive a semi-Markov model which accurately reproduces the statistics of composite dialogue measurements. © The Institution of Engineering and Technology 2013.

A Dynamic Input-Output Model with Renewable Resources

The paper studies a generalisation of the dynamic Leontief input-output model. The standard dynamic Leontief model will be extended with the balance equation of renewable resources. The renewable stocks will increase regenerating and decrease exploiting primary natural resources. In this study the controllability of this extended model is examined by taking the consumption as the control parameter. Assuming balanced growth for both consumption and production, we investigate the exhaustion of renewable resources in dependence on the balanced growth rate and on the rate of natural regeneration. In doing so, classic results from control theory and on eigenvalue problems in linear algebra are applied.

A Dynamic Input-Output Model with Renewable Resources

The paper studies a generalisation of the dynamic Leontief input-output model. The standard dynamic Leontief model will be extended with the balance equation of renewable resources. The renewable stocks will increase regenerating and decrease exploiting primary natural resources. In this study the controllability of this extended model is examined by taking the consumption as the control parameter. Assuming balanced growth for both consumption and production, we investigate the exhaustion of renewable resources in dependence on the balanced growth rate and on the rate of natural regeneration. In doing so, classic results from control theory and on eigenvalue problems in linear algebra are applied.

Simulation modeling of phytoplankton dynamics in a large eutrophic river, Hungary – Danubian Phytoplankton Growth Model (DPGM)

Ecological models have often been used in order to answer questions that are in the limelight of recent researches such as the possible effects of climate change. The methodology of tactical models is a very useful tool comparison to those complex models requiring relatively large set of input parameters. In this study, a theoretical strategic model (TEGM ) was adapted to the field data on the basis of a 24-year long monitoring database of phytoplankton in the Danube River at the station of G¨od, Hungary (at 1669 river kilometer – hereafter referred to as “rkm”). The Danubian Phytoplankton Growth Model (DPGM) is able to describe the seasonal dynamics of phytoplankton biomass (mg L−1) based on daily temperature, but takes the availability of light into consideration as well. In order to improve fitting, the 24-year long database was split in two parts in accordance with environmental sustainability. The period of 1979–1990 has a higher level of nutrient excess compared with that of the 1991–2002. The authors assume that, in the above-mentioned periods, phytoplankton responded to temperature in two different ways, thus two submodels were developed, DPGM-sA and DPGMsB. Observed and simulated data correlated quite well. Findings suggest that linear temperature rise brings drastic change to phytoplankton only in case of high nutrient load and it is mostly realized through the increase of yearly total biomass.

The inclusion of differentially assessed lands in urban growth model calibration: a comparison of two approaches using SLEUTH

This research sought to understand the role that differentially assessed lands (lands in the United States given tax breaks in return for their guarantee to remain in agriculture) play in influencing urban growth. Our method was to calibrate the SLEUTH urban growth model under two different conditions. The first used an excluded layer that ignored such lands, effectively rendering them available for development. The second treated those lands as totally excluded from development. Our hypothesis was that excluding those lands would yield better metrics of fit with past data. Our results validate our hypothesis since two different metrics that evaluate goodness of fit both yielded higher values when differentially assessed lands are treated as excluded. This suggests that, at least in our study area, differential assessment, which protects farm and ranch lands for tenuous periods of time, has indeed allowed farmland to resist urban development. Including differentially assessed lands also yielded very different calibrated coefficients of growth as the model tried to account for the same growth patterns over two very different excluded areas. Excluded layer design can greatly affect model behavior. Since differentially assessed lands are quite common through the United States and are often ignored in urban growth modeling, the findings of this research can assist other urban growth modelers in designing excluded layers that result in more accurate model calibration and thus forecasting.