Bivariate gamma-geometric law and its induced Levy process

In this article we introduce a three-parameter extension of the bivariate exponential-geometric (BEG) law (Kozubowski and Panorska, 2005) [4]. We refer to this new distribution as the bivariate gamma-geometric (BGG) law. A bivariate random vector (X, N) follows the BGG law if N has geometric distribution and X may be represented (in law) as a sum of N independent and identically distributed gamma variables, where these variables are independent of N. Statistical properties such as moment generation and characteristic functions, moments and a variance-covariance matrix are provided. The marginal and conditional laws are also studied. We show that BBG distribution is infinitely divisible, just as the BEG model is. Further, we provide alternative representations for the BGG distribution and show that it enjoys a geometric stability property. Maximum likelihood estimation and inference are discussed and a reparametrization is proposed in order to obtain orthogonality of the parameters. We present an application to a real data set where our model provides a better fit than the BEG model. Our bivariate distribution induces a bivariate Levy process with correlated gamma and negative binomial processes, which extends the bivariate Levy motion proposed by Kozubowski et al. (2008) [6]. The marginals of our Levy motion are a mixture of gamma and negative binomial processes and we named it BMixGNB motion. Basic properties such as stochastic self-similarity and the covariance matrix of the process are presented. The bivariate distribution at fixed time of our BMixGNB process is also studied and some results are derived, including a discussion about maximum likelihood estimation and inference. (C) 2012 Elsevier Inc. All rights reserved.

Quantum critical scaling at a Bose-glass/superfluid transition: Theory and experiment for a model quantum magnet

In this paper we investigate the quantum phase transition from magnetic Bose Glass to magnetic Bose-Einstein condensation induced by amagnetic field in NiCl2 center dot 4SC(NH2)(2) (dichloro-tetrakis-thiourea-nickel, or DTN), doped with Br (Br-DTN) or site diluted. Quantum Monte Carlo simulations for the quantum phase transition of the model Hamiltonian for Br-DTN, as well as for site-diluted DTN, are consistent with conventional scaling at the quantum critical point and with a critical exponent z verifying the prediction z = d; moreover the correlation length exponent is found to be nu = 0.75(10), and the order parameter exponent to be beta = 0.95(10). We investigate the low-temperature thermodynamics at the quantum critical field of Br-DTN both numerically and experimentally, and extract the power-law behavior of the magnetization and of the specific heat. Our results for the exponents of the power laws, as well as previous results for the scaling of the critical temperature to magnetic ordering with the applied field, are incompatible with the conventional crossover-scaling Ansatz proposed by Fisher et al. [Phys. Rev. B 40, 546 (1989)]. However they can all be reconciled within a phenomenological Ansatz in the presence of a dangerously irrelevant operator.

Protective Effects of Human Amniotic Fluid Stem Cells in a Model of Aorta Allograft Vasculopathy in Rats

Background. Chronic allograft vasculopathy (CAV) is an important cause of graft loss. Considering the immune inflammatory events involved in the development of CAV, therapeutic approaches to target this process are of relevance. Human amniotic fluid derived stem cells (hAFSCs), a class of fetal, pluripotent stem cells with intermediate characteristics between embryonic and adult stem cells, display immunomodulatory properties. hAFSCs express mesenchymal and embryonic markers, show high proliferation rates; however, they do not induce tumor formation, and their use does not raise ethical issues. Thus, we sought to investigate the effect of hAFSC on CAV in a model of aorta transplantation. Methods. Orthotopic aorta transplantation was performed using Fisher (F344) rats as donors and Lewis rats as recipients. Rats were divided into three groups: syngeneic (SYNG), untreated F344 receiving aorta from F344 (n = 8); allogeneic (ALLO), Lewis rats receiving allogeneic aorta from F344 (n = 8); and ALLO + hAFSC, ALLO rats treated with hAFSC (10(6) cells; n = 8). Histological analysis and immunohistochemistry were performed 30 days posttransplantation. Results. The ALLO group developed a robust aortic neointimal formation (208.7 +/- 25.4 gm) accompanied by a significant high number of ED1(+) (4845 +/- 841 cells/mm(2)) and CD43(+) cells (4064 +/- 563 cells/mm(2)), and enhanced expression of a-smooth muscle actin in the neointima (25 +/- 6%). Treatment with hAFSC diminished neointimal thickness (180.7 +/- 23.7 mu m) and induced a significant decrease of ED1(+) (1100 +/- 276 cells/mm(2)), CD43(+) cells (1080 +/- 309 cells/mu m(2)), and alpha-smooth muscle actin expression 8 +/- 3% in the neointima. Conclusions. These preliminary results showed that hAFSC suppressed inflammation and myofibroblast migration to the intima, which may contribute to ameliorate vascular changes in CAV.

Dynamic identification of structures: experimental assessment of modal parameteres through methods in frequency domain, in time-frequency domain and model updating

Among the experimental methods commonly used to define the behaviour of a full scale system, dynamic tests are the most complete and efficient procedures. A dynamic test is an experimental process, which would define a set of characteristic parameters of the dynamic behaviour of the system, such as natural frequencies of the structure, mode shapes and the corresponding modal damping values associated. An assessment of these modal characteristics can be used both to verify the theoretical assumptions of the project, to monitor the performance of the structural system during its operational use. The thesis is structured in the following chapters: The first introductive chapter recalls some basic notions of dynamics of structure, focusing the discussion on the problem of systems with multiply degrees of freedom (MDOF), which can represent a generic real system under study, when it is excited with harmonic force or in free vibration. The second chapter is entirely centred on to the problem of dynamic identification process of a structure, if it is subjected to an experimental test in forced vibrations. It first describes the construction of FRF through classical FFT of the recorded signal. A different method, also in the frequency domain, is subsequently introduced; it allows accurately to compute the FRF using the geometric characteristics of the ellipse that represents the direct input-output comparison. The two methods are compared and then the attention is focused on some advantages of the proposed methodology. The third chapter focuses on the study of real structures when they are subjected to experimental test, where the force is not known, like in an ambient or impact test. In this analysis we decided to use the CWT, which allows a simultaneous investigation in the time and frequency domain of a generic signal x(t). The CWT is first introduced to process free oscillations, with excellent results both in terms of frequencies, dampings and vibration modes. The application in the case of ambient vibrations defines accurate modal parameters of the system, although on the damping some important observations should be made. The fourth chapter is still on the problem of post processing data acquired after a vibration test, but this time through the application of discrete wavelet transform (DWT). In the first part the results obtained by the DWT are compared with those obtained by the application of CWT. Particular attention is given to the use of DWT as a tool for filtering the recorded signal, in fact in case of ambient vibrations the signals are often affected by the presence of a significant level of noise. The fifth chapter focuses on another important aspect of the identification process: the model updating. In this chapter, starting from the modal parameters obtained from some environmental vibration tests, performed by the University of Porto in 2008 and the University of Sheffild on the Humber Bridge in England, a FE model of the bridge is defined, in order to define what type of model is able to capture more accurately the real dynamic behaviour of the bridge. The sixth chapter outlines the necessary conclusions of the presented research. They concern the application of a method in the frequency domain in order to evaluate the modal parameters of a structure and its advantages, the advantages in applying a procedure based on the use of wavelet transforms in the process of identification in tests with unknown input and finally the problem of 3D modeling of systems with many degrees of freedom and with different types of uncertainty.

Geometric and Combinatorial Aspects of NonEquilibrium Statistical Mechanics

Non-Equilibrium Statistical Mechanics is a broad subject. Grossly speaking, it deals with systems which have not yet relaxed to an equilibrium state, or else with systems which are in a steady non-equilibrium state, or with more general situations. They are characterized by external forcing and internal fluxes, resulting in a net production of entropy which quantifies dissipation and the extent by which, by the Second Law of Thermodynamics, time-reversal invariance is broken. In this thesis we discuss some of the mathematical structures involved with generic discrete-state-space non-equilibrium systems, that we depict with networks in all analogous to electrical networks. We define suitable observables and derive their linear regime relationships, we discuss a duality between external and internal observables that reverses the role of the system and of the environment, we show that network observables serve as constraints for a derivation of the minimum entropy production principle. We dwell on deep combinatorial aspects regarding linear response determinants, which are related to spanning tree polynomials in graph theory, and we give a geometrical interpretation of observables in terms of Wilson loops of a connection and gauge degrees of freedom. We specialize the formalism to continuous-time Markov chains, we give a physical interpretation for observables in terms of locally detailed balanced rates, we prove many variants of the fluctuation theorem, and show that a well-known expression for the entropy production due to Schnakenberg descends from considerations of gauge invariance, where the gauge symmetry is related to the freedom in the choice of a prior probability distribution. As an additional topic of geometrical flavor related to continuous-time Markov chains, we discuss the Fisher-Rao geometry of nonequilibrium decay modes, showing that the Fisher matrix contains information about many aspects of non-equilibrium behavior, including non-equilibrium phase transitions and superposition of modes. We establish a sort of statistical equivalence principle and discuss the behavior of the Fisher matrix under time-reversal. To conclude, we propose that geometry and combinatorics might greatly increase our understanding of nonequilibrium phenomena.

DESIGN OF A LIQUID FUEL INJECTOR FOR ALTERNATIVE FUEL STUDIES IN AN ATMOSPHERIC MODEL GAS TURBINE COMBUSTOR

A new liquid-fuel injector was designed for use in the atmospheric-pressure, model gas turbine combustor in Bucknell University’s Combustion Research Laboratory during alternative fuel testing. The current liquid-fuel injector requires a higher-than-desired pressure drop and volumetric flow rate to provide proper atomization of liquid fuels. An air-blast atomizer type of fuel injector was chosen and an experiment utilizing water as the working fluid was performed on a variable-geometry prototype. Visualization of the spray pattern was achieved through photography and the pressure drop was measured as a function of the required operating parameters. Experimental correlations were used to estimate droplet sizes over flow conditions similar to that which would be experienced in the actual combustor. The results of this experiment were used to select the desired geometric parameters for the proposed final injector design and a CAD model was generated. Eventually, the new injector will be fabricated and tested to provide final validation of the design prior to use in the combustion test apparatus.

A prediction model for assessing residential radon concentration in Switzerland

Indoor radon is regularly measured in Switzerland. However, a nationwide model to predict residential radon levels has not been developed. The aim of this study was to develop a prediction model to assess indoor radon concentrations in Switzerland. The model was based on 44,631 measurements from the nationwide Swiss radon database collected between 1994 and 2004. Of these, 80% randomly selected measurements were used for model development and the remaining 20% for an independent model validation. A multivariable log-linear regression model was fitted and relevant predictors selected according to evidence from the literature, the adjusted R², the Akaike's information criterion (AIC), and the Bayesian information criterion (BIC). The prediction model was evaluated by calculating Spearman rank correlation between measured and predicted values. Additionally, the predicted values were categorised into three categories (50th, 50th-90th and 90th percentile) and compared with measured categories using a weighted Kappa statistic. The most relevant predictors for indoor radon levels were tectonic units and year of construction of the building, followed by soil texture, degree of urbanisation, floor of the building where the measurement was taken and housing type (P-values <0.001 for all). Mean predicted radon values (geometric mean) were 66 Bq/m³ (interquartile range 40-111 Bq/m³) in the lowest exposure category, 126 Bq/m³ (69-215 Bq/m³) in the medium category, and 219 Bq/m³ (108-427 Bq/m³) in the highest category. Spearman correlation between predictions and measurements was 0.45 (95%-CI: 0.44; 0.46) for the development dataset and 0.44 (95%-CI: 0.42; 0.46) for the validation dataset. Kappa coefficients were 0.31 for the development and 0.30 for the validation dataset, respectively. The model explained 20% overall variability (adjusted R²). In conclusion, this residential radon prediction model, based on a large number of measurements, was demonstrated to be robust through validation with an independent dataset. The model is appropriate for predicting radon level exposure of the Swiss population in epidemiological research. Nevertheless, some exposure misclassification and regression to the mean is unavoidable and should be taken into account in future applications of the model.

A Cox Model for Biostatistics of the Future

Professor Sir David R. Cox (DRC) is widely acknowledged as among the most important scientists of the second half of the twentieth century. He inherited the mantle of statistical science from Pearson and Fisher, advanced their ideas, and translated statistical theory into practice so as to forever change the application of statistics in many fields, but especially biology and medicine. The logistic and proportional hazards models he substantially developed, are arguably among the most influential biostatistical methods in current practice. This paper looks forward over the period from DRC's 80th to 90th birthdays, to speculate about the future of biostatistics, drawing lessons from DRC's contributions along the way. We consider "Cox's model" of biostatistics, an approach to statistical science that: formulates scientific questions or quantities in terms of parameters gamma in probability models f(y; gamma) that represent in a parsimonious fashion, the underlying scientific mechanisms (Cox, 1997); partition the parameters gamma = theta, eta into a subset of interest theta and other "nuisance parameters" eta necessary to complete the probability distribution (Cox and Hinkley, 1974); develops methods of inference about the scientific quantities that depend as little as possible upon the nuisance parameters (Barndorff-Nielsen and Cox, 1989); and thinks critically about the appropriate conditional distribution on which to base infrences. We briefly review exciting biomedical and public health challenges that are capable of driving statistical developments in the next decade. We discuss the statistical models and model-based inferences central to the CM approach, contrasting them with computationally-intensive strategies for prediction and inference advocated by Breiman and others (e.g. Breiman, 2001) and to more traditional design-based methods of inference (Fisher, 1935). We discuss the hierarchical (multi-level) model as an example of the future challanges and opportunities for model-based inference. We then consider the role of conditional inference, a second key element of the CM. Recent examples from genetics are used to illustrate these ideas. Finally, the paper examines causal inference and statistical computing, two other topics we believe will be central to biostatistics research and practice in the coming decade. Throughout the paper, we attempt to indicate how DRC's work and the "Cox Model" have set a standard of excellence to which all can aspire in the future.

Development of a novel material flow simulation model for the integration of spatial and process relevant information

Simulation techniques are almost indispensable in the analysis of complex systems. Materials- and related information flow processes in logistics often possess such complexity. Further problem arise as the processes change over time and pose a Big Data problem as well. To cope with these issues adaptive simulations are more and more frequently used. This paper presents a few relevant advanced simulation models and intro-duces a novel model structure, which unifies modelling of geometrical relations and time processes. This way the process structure and their geometric relations can be handled in a well understandable and transparent way. Capabilities and applicability of the model is also presented via a demonstrational example.

Geometric properties of the lung parenchyma after postnatal glucocorticoid treatment in rats

While glucocorticoid (GC) administration appears to be beneficial during the acute phase of treatment of neonates at risk of developing chronic lung disease, it is still not clear whether steroid application has an adverse long-term effect on the lung maturation. Thus, the goal of the present work was to analyze GC effects on the pulmonary structure in a rat model where dosage and timing of drug administration were adapted to the therapeutic situation in human neonatology. The animals received daily a maximum of 0.1 mg dexamethasone phosphate per kilogram body weight during the first 4 postnatal days. Investigations were performed at the light microscopic level by means of a digital image analysis system. While there were no differences in the lung architecture between experimental animals and controls on day 4, the earliest time point of observation, we found a widening of airspaces with a concomitant decrease in the alveolar surface area density, representing a loss of parenchymal complexity, on days 10 and 21 in treated rats. On days 36 and 60, however, no alterations in the pulmonary parenchyma could be detected in experimental animals. We conclude from these findings that the GC-induced initial inhibition of development (days 10 and 21) was completely reversed, so that a normal parenchymal architecture and also a normal alveolar surface area density were found in adult rats (days 36 and 60). From the results obtained using the regimen of GC administration described, mimicking more closely the steroid treatment in human neonatology, we conclude that the observed short-term adverse effects on lung development can be fully compensated until adult age.

Characterization of the 9L gliosarcoma implanted in the Fischer rat: an orthotopic model for a grade IV brain tumor.

Among rodent models for brain tumors, the 9L gliosarcoma is one of the most widely used. Our 9L-European Synchrotron Radiation Facility (ESRF) model was developed from cells acquired at the Brookhaven National Laboratory (NY, USA) in 1997 and implanted in the right caudate nucleus of syngeneic Fisher rats. It has been largely used by the user community of the ESRF during the last decade, for imaging, radiotherapy, and chemotherapy, including innovative treatments based on particular irradiation techniques and/or use of new drugs. This work presents a detailed study of its characteristics, assessed by magnetic resonance imaging (MRI), histology, immunohistochemistry, and cytogenetic analysis. The data used for this work were from rats sampled in six experiments carried out over a 3-year period in our lab (total number of rats = 142). The 9L-ESRF tumors were induced by a stereotactic inoculation of 10(4) 9L cells in the right caudate nucleus of the brain. The assessment of vascular parameters was performed by MRI (blood volume fraction and vascular size index) and by immunostaining of vessels (rat endothelial cell antigen-1 and type IV collagen). Immunohistochemistry and regular histology were used to describe features such as tumor cell infiltration, necrosis area, nuclear pleomorphism, cellularity, mitotic characteristics, leukocytic infiltration, proliferation, and inflammation. Moreover, for each of the six experiments, the survival of the animals was assessed and related to the tumor growth observed by MRI or histology. Additionally, the cytogenetic status of the 9L cells used at ESRF lab was investigated by comparative genomics hybridization analysis. Finally, the response of the 9L-ESRF tumor to radiotherapy was estimated by plotting the survival curves after irradiation. The median survival time of 9L-ESRF tumor-bearing rats was highly reproducible (19-20 days). The 9L-ESRF tumors presented a quasi-exponential growth, were highly vascularized with a high cellular density and a high proliferative index, accompanied by signs of inflammatory responses. We also report an infiltrative pattern which is poorly observed on conventional 9 L tumor. The 9L-ESRF cells presented some cytogenetic specificities such as altered regions including CDK4, CDKN2A, CDKN2B, and MDM2 genes. Finally, the lifespan of 9L-ESRF tumor-bearing rats was enhanced up to 28, 35, and 45 days for single doses of 10, 20, and 2 × 20 Gy, respectively. First, this report describes an animal model that is used worldwide. Second, we describe few features typical of our model if compared to other 9L models worldwide. Altogether, the 9L-ESRF tumor model presents characteristics close to the human high-grade gliomas such as high proliferative capability, high vascularization and a high infiltrative pattern. Its response to radiotherapy demonstrates its potential as a tool for innovative radiotherapy protocols.

Digital surface model, hillshade and Lambertian reflectance model of the rock glaciers Oelgrube and Aeusseres Hochebenkar (Oetztal Alps, Tyrol, Austria)

With full-waveform (FWF) lidar systems becoming increasingly available from different commercial manufacturers, the possibility for extracting physical parameters of the scanned surfaces in an area-wide sense, as addendum to their geometric representation, has risen as well. The mentioned FWF systems digitize the temporal profiles of the transmitted laser pulse and of its backscattered echoes, allowing for a reliable determination of the target distance to the instrument and of physical target quantities by means of radiometric calibration, one of such quantities being the diffuse Lambertian reflectance. The delineation of glaciers is a time-consuming task, commonly performed manually by experts and involving field trips as well as image interpretation of orthophotos, digital terrain models and shaded reliefs. In this study, the diffuse Lambertian reflectance was compared to the glacier outlines mapped by experts. We start the presentation with the workflow for analysis of FWF data, their direct georeferencing and the calculation of the diffuse Lambertian reflectance by radiometric calibration; this workflow is illustrated for a large FWF lidar campaign in the Ötztal Alps (Tyrol, Austria), operated with an Optech ALTM 3100 system. The geometric performance of the presented procedure was evaluated by means of a relative and an absolute accuracy assessment using strip differences and orthophotos, resp. The diffuse Lambertian reflectance was evaluated at two rock glaciers within the mentioned lidar campaign. This feature showed good performance for the delineation of the rock glacier boundaries, especially at their lower parts.

Atmospheric, oceanic and hydrological polar motion excitation mechanisms based on a combination of geometric and gravimetric space observations

The goal of our study is to determine accurate time series of geophysical Earth rotation excitations to learn more about global dynamic processes in the Earth system. For this purpose, we developed an adjustment model which allows to combine precise observations from space geodetic observation systems, such as Satellite Laser Ranging (SLR), Global Navigation Satellite Systems (GNSS), Very Long Baseline Interferometry (VLBI), Doppler Orbit determination and Radiopositioning Integrated on Satellite (DORIS), satellite altimetry and satellite gravimetry in order to separate geophysical excitation mechanisms of Earth rotation. Three polar motion time series are applied to derive the polar motion excitation functions (integral effect). Furthermore we use five time variable gravity field solutions from Gravity Recovery and Climate Experiment (GRACE) to determine not only the integral mass effect but also the oceanic and hydrological mass effects by applying suitable filter techniques and a land-ocean mask. For comparison the integral mass effect is also derived from degree 2 potential coefficients that are estimated from SLR observations. The oceanic mass effect is also determined from sea level anomalies observed by satellite altimetry by reducing the steric sea level anomalies derived from temperature and salinity fields of the oceans. Due to the combination of all geodetic estimated excitations the weaknesses of the individual processing strategies can be reduced and the technique-specific strengths can be accounted for. The formal errors of the adjusted geodetic solutions are smaller than the RMS differences of the geophysical model solutions. The improved excitation time series can be used to improve the geophysical modeling.