Basic ingredients for mathematical modeling of tumor growth in vitro: Cooperative effects and search for space

Based on the literature data from HT-29 cell monolayers, we develop a model for its growth, analogous to an epidemic model, mixing local and global interactions. First, we propose and solve a deterministic equation for the progress of these colonies. Thus, we add a stochastic (local) interaction and simulate the evolution of an Eden-like aggregate by using dynamical Monte Carlo methods. The growth curves of both deterministic and stochastic models are in excellent agreement with the experimental observations. The waiting times distributions, generated via our stochastic model, allowed us to analyze the role of mesoscopic events. We obtain log-normal distributions in the initial stages of the growth and Gaussians at long times. We interpret these outcomes in the light of cellular division events: in the early stages, the phenomena are dependent each other in a multiplicative geometric-based process, and they are independent at long times. We conclude that the main ingredients for a good minimalist model of tumor growth, at mesoscopic level, are intrinsic cooperative mechanisms and competitive search for space. © 2013 Elsevier Ltd.

Modeling the growth rate and lag time of different strains of Salmonella enterica and Listeria monocytogenes in ready-to-eat lettuce

The growth parameters (growth rate, mu and lag time, lambda) of three different strains each of Salmonella enterica and Listeria monocytogenes in minimally processed lettuce (MPL) and their changes as a function of temperature were modeled. MPL were packed under modified atmosphere (5% O-2, 15% CO2 and 80% N-2), stored at 7-30 degrees C and samples collected at different time intervals were enumerated for S. enterica and L monocytogenes. Growth curves and equations describing the relationship between mu and lambda as a function of temperature were constructed using the DMFit Excel add-in and through linear regression, respectively. The predicted growth parameters for the pathogens observed in this study were compared to ComBase, Pathogen modeling program (PMP) and data from the literature. High R-2 values (0.97 and 0.93) were observed for average growth curves of different strains of pathogens grown on MPL Secondary models of mu and lambda for both pathogens followed a linear trend with high R2 values (>0.90). Root mean square error (RMSE) showed that the models obtained are accurate and suitable for modeling the growth of S. enterica and L monocytogenes in MP lettuce. The current study provides growth models for these foodborne pathogens that can be used in microbial risk assessment. (C) 2011 Elsevier Ltd. All rights reserved.

Detection and Modeling of Boundary Layer Height

This thesis tackles the problem of the automated detection of the atmospheric boundary layer (BL) height, h, from aerosol lidar/ceilometer observations. A new method, the Bayesian Selective Method (BSM), is presented. It implements a Bayesian statistical inference procedure which combines in an statistically optimal way different sources of information. Firstly atmospheric stratification boundaries are located from discontinuities in the ceilometer back-scattered signal. The BSM then identifies the discontinuity edge that has the highest probability to effectively mark the BL height. Information from the contemporaneus physical boundary layer model simulations and a climatological dataset of BL height evolution are combined in the assimilation framework to assist this choice. The BSM algorithm has been tested for four months of continuous ceilometer measurements collected during the BASE:ALFA project and is shown to realistically diagnose the BL depth evolution in many different weather conditions. Then the BASE:ALFA dataset is used to investigate the boundary layer structure in stable conditions. Functions from the Obukhov similarity theory are used as regression curves to fit observed velocity and temperature profiles in the lower half of the stable boundary layer. Surface fluxes of heat and momentum are best-fitting parameters in this exercise and are compared with what measured by a sonic anemometer. The comparison shows remarkable discrepancies, more evident in cases for which the bulk Richardson number turns out to be quite large. This analysis supports earlier results, that surface turbulent fluxes are not the appropriate scaling parameters for profiles of mean quantities in very stable conditions. One of the practical consequences is that boundary layer height diagnostic formulations which mainly rely on surface fluxes are in disagreement to what obtained by inspecting co-located radiosounding profiles.

Topologically correct intersection curves of tori and natural quadrics

This thesis provides efficient and robust algorithms for the computation of the intersection curve between a torus and a simple surface (e.g. a plane, a natural quadric or another torus), based on algebraic and numeric methods. The algebraic part includes the classification of the topological type of the intersection curve and the detection of degenerate situations like embedded conic sections and singularities. Moreover, reference points for each connected intersection curve component are determined. The required computations are realised efficiently by solving quartic polynomials at most and exactly by using exact arithmetic. The numeric part includes algorithms for the tracing of each intersection curve component, starting from the previously computed reference points. Using interval arithmetic, accidental incorrectness like jumping between branches or the skipping of parts are prevented. Furthermore, the environments of singularities are correctly treated. Our algorithms are complete in the sense that any kind of input can be handled including degenerate and singular configurations. They are verified, since the results are topologically correct and approximate the real intersection curve up to any arbitrary given error bound. The algorithms are robust, since no human intervention is required and they are efficient in the way that the treatment of algebraic equations of high degree is avoided.

Measurement and modeling of cloud condensation nuclei in continental air

Atmospheric aerosol particles serving as cloud condensation nuclei (CCN) are key elements of the hydrological cycle and climate. Knowledge of the spatial and temporal distribution of CCN in the atmosphere is essential to understand and describe the effects of aerosols in meteorological models. In this study, CCN properties were measured in polluted and pristine air of different continental regions, and the results were parameterized for efficient prediction of CCN concentrations.The continuous-flow CCN counter used for size-resolved measurements of CCN efficiency spectra (activation curves) was calibrated with ammonium sulfate and sodium chloride aerosols for a wide range of water vapor supersaturations (S=0.068% to 1.27%). A comprehensive uncertainty analysis showed that the instrument calibration depends strongly on the applied particle generation techniques, Köhler model calculations, and water activity parameterizations (relative deviations in S up to 25%). Laboratory experiments and a comparison with other CCN instruments confirmed the high accuracy and precision of the calibration and measurement procedures developed and applied in this study.The mean CCN number concentrations (NCCN,S) observed in polluted mega-city air and biomass burning smoke (Beijing and Pearl River Delta, China) ranged from 1000 cm−3 at S=0.068% to 16 000 cm−3 at S=1.27%, which is about two orders of magnitude higher than in pristine air at remote continental sites (Swiss Alps, Amazonian rainforest). Effective average hygroscopicity parameters, κ, describing the influence of chemical composition on the CCN activity of aerosol particles were derived from the measurement data. They varied in the range of 0.3±0.2, were size-dependent, and could be parameterized as a function of organic and inorganic aerosol mass fraction. At low S (≤0.27%), substantial portions of externally mixed CCN-inactive particles with much lower hygroscopicity were observed in polluted air (fresh soot particles with κ≈0.01). Thus, the aerosol particle mixing state needs to be known for highly accurate predictions of NCCN,S. Nevertheless, the observed CCN number concentrations could be efficiently approximated using measured aerosol particle number size distributions and a simple κ-Köhler model with a single proxy for the effective average particle hygroscopicity. The relative deviations between observations and model predictions were on average less than 20% when a constant average value of κ=0.3 was used in conjunction with variable size distribution data. With a constant average size distribution, however, the deviations increased up to 100% and more. The measurement and model results demonstrate that the aerosol particle number and size are the major predictors for the variability of the CCN concentration in continental boundary layer air, followed by particle composition and hygroscopicity as relatively minor modulators. Depending on the required and applicable level of detail, the measurement results and parameterizations presented in this study can be directly implemented in detailed process models as well as in large-scale atmospheric and climate models for efficient description of the CCN activity of atmospheric aerosols.

Kinematics of local and high-z galaxies through 3D modeling of emission-line datacubes

The kinematics is a fundamental tool to infer the dynamical structure of galaxies and to understand their formation and evolution. Spectroscopic observations of gas emission lines are often used to derive rotation curves and velocity dispersions. It is however difficult to disentangle these two quantities in low spatial-resolution data because of beam smearing. In this thesis, we present 3D-Barolo, a new software to derive the gas kinematics of disk galaxies from emission-line data-cubes. The code builds tilted-ring models in the 3D observational space and compares them with the actual data-cubes. 3D-Barolo works with data at a wide range of spatial resolutions without being affected by instrumental biases. We use 3D-Barolo to derive rotation curves and velocity dispersions of several galaxies in both the local and the high-redshift Universe. We run our code on HI observations of nearby galaxies and we compare our results with 2D traditional approaches. We show that a 3D approach to the derivation of the gas kinematics has to be preferred to a 2D approach whenever a galaxy is resolved with less than about 20 elements across the disk. We moreover analyze a sample of galaxies at z~1, observed in the H-alpha line with the KMOS/VLT spectrograph. Our 3D modeling reveals that the kinematics of these high-z systems is comparable to that of local disk galaxies, with steeply-rising rotation curves followed by a flat part and H-alpha velocity dispersions of 15-40 km/s over the whole disks. This evidence suggests that disk galaxies were already fully settled about 7-8 billion years ago. In summary, 3D-Barolo is a powerful and robust tool to separate physical and instrumental effects and to derive a reliable kinematics. The analysis of large samples of galaxies at different redshifts with 3D-Barolo will provide new insights on how galaxies assemble and evolve throughout cosmic time.

Functional error modeling for uncertainty quantification in hydrogeology

Approximate models (proxies) can be employed to reduce the computational costs of estimating uncertainty. The price to pay is that the approximations introduced by the proxy model can lead to a biased estimation. To avoid this problem and ensure a reliable uncertainty quantification, we propose to combine functional data analysis and machine learning to build error models that allow us to obtain an accurate prediction of the exact response without solving the exact model for all realizations. We build the relationship between proxy and exact model on a learning set of geostatistical realizations for which both exact and approximate solvers are run. Functional principal components analysis (FPCA) is used to investigate the variability in the two sets of curves and reduce the dimensionality of the problem while maximizing the retained information. Once obtained, the error model can be used to predict the exact response of any realization on the basis of the sole proxy response. This methodology is purpose-oriented as the error model is constructed directly for the quantity of interest, rather than for the state of the system. Also, the dimensionality reduction performed by FPCA allows a diagnostic of the quality of the error model to assess the informativeness of the learning set and the fidelity of the proxy to the exact model. The possibility of obtaining a prediction of the exact response for any newly generated realization suggests that the methodology can be effectively used beyond the context of uncertainty quantification, in particular for Bayesian inference and optimization.

Preclinical modeling of multi-drug cancer therapies

Anticancer drugs typically are administered in the clinic in the form of mixtures, sometimes called combinations. Only in rare cases, however, are mixtures approved as drugs. Rather, research on mixtures tends to occur after single drugs have been approved. The goal of this research project was to develop modeling approaches that would encourage rational preclinical mixture design. To this end, a series of models were developed. First, several QSAR classification models were constructed to predict the cytotoxicity, oral clearance, and acute systemic toxicity of drugs. The QSAR models were applied to a set of over 115,000 natural compounds in order to identify promising ones for testing in mixtures. Second, an improved method was developed to assess synergistic, antagonistic, and additive effects between drugs in a mixture. This method, dubbed the MixLow method, is similar to the Median-Effect method, the de facto standard for assessing drug interactions. The primary difference between the two is that the MixLow method uses a nonlinear mixed-effects model to estimate parameters of concentration-effect curves, rather than an ordinary least squares procedure. Parameter estimators produced by the MixLow method were more precise than those produced by the Median-Effect Method, and coverage of Loewe index confidence intervals was superior. Third, a model was developed to predict drug interactions based on scores obtained from virtual docking experiments. This represents a novel approach for modeling drug mixtures and was more useful for the data modeled here than competing approaches. The model was applied to cytotoxicity data for 45 mixtures, each composed of up to 10 selected drugs. One drug, doxorubicin, was a standard chemotherapy agent and the others were well-known natural compounds including curcumin, EGCG, quercetin, and rhein. Predictions of synergism/antagonism were made for all possible fixed-ratio mixtures, cytotoxicities of the 10 best-scoring mixtures were tested, and drug interactions were assessed. Predicted and observed responses were highly correlated (r2 = 0.83). Results suggested that some mixtures allowed up to an 11-fold reduction of doxorubicin concentrations without sacrificing efficacy. Taken together, the models developed in this project present a general approach to rational design of mixtures during preclinical drug development. ^

Advances in the modeling, characterization and reliability of concentrator multijunction solar cells

Los sistemas de concentración fotovoltaica (CPV) parecen ser una de las vías más prometedoras para generar electricidad a gran escala a precios competitivos. La investigación actual se centra en aumentar la eficiencia y la concentración de los sistemas para abaratar costes. Al mismo tiempo se investiga sobre la fiabilidad de los diferentes componentes que integran un sistema de concentración, ya que para que los sistemas de concentración sean competitivos es necesario que tengan una fiabilidad al menos similar a los sistemas basados en células de silicio. En la presente tesis doctoral se ha llevado a cabo el estudio de aspectos avanzados de células solares multi-unión diseñadas para trabajar a concentraciones ultra-altas. Para ello, se ha desarrollado un modelo circuital tridimensional distribuido con el que simular el comportamiento de las células solares triple-unión bajo distintas condiciones de funcionamiento, así mismo se ha realizado una caracterización avanzada de este tipo de células para comprender mejor su modo de operación y así poder contribuir a mejorar su eficiencia. Finalmente, se han llevado a cabo ensayos de vida acelerados en células multiunión comerciales para conocer la fiabilidad de este tipo de células solares. Para la simulación de células solares triple-unión se ha desarrollado en la presente tesis doctoral un modelo circuital tridimensinal distribuido el cuál integra una descripción completa de la unión túnel. De este modo, con el modelo desarrollado, hemos podido simular perfiles de luz sobre la célula solar que hacen que la densidad de corriente fotogenerada sea mayor a la densidad de corriente pico de la unión túnel. El modelo desarrollado también contempla la distribución lateral de corriente en las capas semiconductoras que componen y rodean la unión túnel. Por tanto, se ha podido simular y analizar el efecto que tiene sobre el funcionamiento de la célula solar que los concentradores ópticos produzcan perfiles de luz desuniformes, tanto en nivel de irradiancia como en el contenido espectral de la luz (aberración cromática). Con el objetivo de determinar cuáles son los mecanismos de recombinación que están limitando el funcionamiento de cada subcélula que integra una triple-unión, y así intentar reducirlos, se ha llevado a cabo la caracterización eléctrica de células solares monouni ón idénticas a las subcelulas de una triple-unión. También se ha determinado la curva corriente-tensión en oscuridad de las subcélulas de GaInP y GaAs de una célula dobleunión mediante la utilización de un teorema de reciprocidad electro-óptico. Finalmente, se ha analizado el impacto de los diferentes mecanismos de recombinación en el funcionamiento de la célula solar triple-unión en concentración. Por último, para determinar la fiabilidad de este tipo de células, se ha llevado a cabo un ensayo de vida acelerada en temperatura en células solares triple-unión comerciales. En la presente tesis doctoral se describe el diseño del ensayo, el progreso del mismo y los datos obtenidos tras el análisis de los resultados preliminares. Abstract Concentrator photovoltaic systems (CPV) seem to be one of the most promising ways to generate electricity at competitive prices. Nowadays, the research is focused on increasing the efficiency and the concentration of the systems in order to reduce costs. At the same time, another important area of research is the study of the reliability of the different components which make up a CPV system. In fact, in order for a CPV to be cost-effective, it should have a warranty at least similar to that of the systems based on Si solar cells. In the present thesis, we will study in depth the behavior of multijunction solar cells under ultra-high concentration. With this purpose in mind, a three-dimensional circuital distributed model which is able to simulate the behavior of triple-junction solar cells under different working conditions has been developed. Also, an advanced characterization of these solar cells has been carried out in order to better understand their behavior and thus contribute to improving efficiency. Finally, accelerated life tests have been carried out on commercial lattice-matched triple-junction solar cells in order to determine their reliability. In order to simulate triple-junction solar cells, a 3D circuital distributed model which integrates a full description of the tunnel junction has been developed. We have analyzed the behavior of the multijunction solar cell under light profiles which cause the current density photo-generated in the solar cell to be higher than the tunnel junction’s peak current density. The advanced model developed also takes into account the lateral current spreading through the semiconductor layers which constitute and surround the tunnel junction. Therefore, the effects of non-uniform light profiles, in both irradiance and the spectral content produced by the concentrators on the solar cell, have been simulated and analyzed. In order to determine which recombination mechanisms are limiting the behavior of each subcell in a triple-junction stack, and to try to reduce them when possible, an electrical characterization of single-junction solar cells that resemble the subcells in a triplejunction stack has been carried out. Also, the dark I-V curves of the GaInP and GaAs subcells in a dual-junction solar cell have been determined by using an electro-optical reciprocity theorem. Finally, the impact of the different recombination mechanisms on the behavior of the triple-junction solar cell under concentration has been analyzed. In order to determine the reliability of these solar cells, a temperature accelerated life test has been carried out on commercial triple-junction solar cells. In the present thesis, the design and the evolution of the test, as well as the data obtained from the analysis of the preliminary results, are presented.

HVOSM studies of cross-slope breaks on highway curves. Final report.

Federal Highway Administration, Office of Research and Development, Washington, D.C.

Analysis of truck safety on crest vertical curves. Final report.

Federal Highway Administration, Washington, D.C.

Review of tropospheric bomb C-14 data for carbon cycle modeling and age calibration purposes

Comprehensive published radiocarbon data from selected atmospheric records, tree rings, and recent organic matter were analyzed and grouped into 4 different zones (three for the Northern Hemisphere and one for the whole Southern Hemisphere). These C-14 data for the summer season of each hemisphere were employed to construct zonal, hemispheric, and global data sets for use in regional and global carbon model calculations including calibrating and comparing carbon cycle models. In addition, extended monthly atmospheric C-14 data sets for 4 different zones were compiled for age calibration purposes. This is the first time these data sets were constructed to facilitate the dating of recent organic material using the bomb C-14 curves. The distribution of bomb C-14 reflects the major zones of atmospheric circulation.

Development and Implementation of NURBS Models of Quadratic Curves and Surfaces

This article goes into the development of NURBS models of quadratic curves and surfaces. Curves and surfaces which could be represented by one general equation (one for the curves and one for the surfaces) are addressed. The research examines the curves: ellipse, parabola and hyperbola, the surfaces: ellipsoid, paraboloid, hyperboloid, double hyperboloid, hyperbolic paraboloid and cone, and the cylinders: elliptic, parabolic and hyperbolic. Many real objects which have to be modeled in 3D applications possess specific features. Because of this these geometric objects have been chosen. Using the NURBS models presented here, specialized software modules (plug-ins) have been developed for a 3D graphic system. An analysis of their implementation and the primitives they create has been performed.

Weak form equation–based finite-element modeling of viscoelastic asphalt mixtures

The objective of this study is to demonstrate using weak form partial differential equation (PDE) method for a finite-element (FE) modeling of a new constitutive relation without the need of user subroutine programming. The viscoelastic asphalt mixtures were modeled by the weak form PDE-based FE method as the examples in the paper. A solid-like generalized Maxwell model was used to represent the deforming mechanism of a viscoelastic material, the constitutive relations of which were derived and implemented in the weak form PDE module of Comsol Multiphysics, a commercial FE program. The weak form PDE modeling of viscoelasticity was verified by comparing Comsol and Abaqus simulations, which employed the same loading configurations and material property inputs in virtual laboratory test simulations. Both produced identical results in terms of axial and radial strain responses. The weak form PDE modeling of viscoelasticity was further validated by comparing the weak form PDE predictions with real laboratory test results of six types of asphalt mixtures with two air void contents and three aging periods. The viscoelastic material properties such as the coefficients of a Prony series model for the relaxation modulus were obtained by converting from the master curves of dynamic modulus and phase angle. Strain responses of compressive creep tests at three temperatures and cyclic load tests were predicted using the weak form PDE modeling and found to be comparable with the measurements of the real laboratory tests. It was demonstrated that the weak form PDE-based FE modeling can serve as an efficient method to implement new constitutive models and can free engineers from user subroutine programming.

On precise three-dimensional environment modeling via UAV-based photogrammetric systems

Abstract : Images acquired from unmanned aerial vehicles (UAVs) can provide data with unprecedented spatial and temporal resolution for three-dimensional (3D) modeling. Solutions developed for this purpose are mainly operating based on photogrammetry concepts, namely UAV-Photogrammetry Systems (UAV-PS). Such systems are used in applications where both geospatial and visual information of the environment is required. These applications include, but are not limited to, natural resource management such as precision agriculture, military and police-related services such as traffic-law enforcement, precision engineering such as infrastructure inspection, and health services such as epidemic emergency management. UAV-photogrammetry systems can be differentiated based on their spatial characteristics in terms of accuracy and resolution. That is some applications, such as precision engineering, require high-resolution and high-accuracy information of the environment (e.g. 3D modeling with less than one centimeter accuracy and resolution). In other applications, lower levels of accuracy might be sufficient, (e.g. wildlife management needing few decimeters of resolution). However, even in those applications, the specific characteristics of UAV-PSs should be well considered in the steps of both system development and application in order to yield satisfying results. In this regard, this thesis presents a comprehensive review of the applications of unmanned aerial imagery, where the objective was to determine the challenges that remote-sensing applications of UAV systems currently face. This review also allowed recognizing the specific characteristics and requirements of UAV-PSs, which are mostly ignored or not thoroughly assessed in recent studies. Accordingly, the focus of the first part of this thesis is on exploring the methodological and experimental aspects of implementing a UAV-PS. The developed system was extensively evaluated for precise modeling of an open-pit gravel mine and performing volumetric-change measurements. This application was selected for two main reasons. Firstly, this case study provided a challenging environment for 3D modeling, in terms of scale changes, terrain relief variations as well as structure and texture diversities. Secondly, open-pit-mine monitoring demands high levels of accuracy, which justifies our efforts to improve the developed UAV-PS to its maximum capacities. The hardware of the system consisted of an electric-powered helicopter, a high-resolution digital camera, and an inertial navigation system. The software of the system included the in-house programs specifically designed for camera calibration, platform calibration, system integration, onboard data acquisition, flight planning and ground control point (GCP) detection. The detailed features of the system are discussed in the thesis, and solutions are proposed in order to enhance the system and its photogrammetric outputs. The accuracy of the results was evaluated under various mapping conditions, including direct georeferencing and indirect georeferencing with different numbers, distributions and types of ground control points. Additionally, the effects of imaging configuration and network stability on modeling accuracy were assessed. The second part of this thesis concentrates on improving the techniques of sparse and dense reconstruction. The proposed solutions are alternatives to traditional aerial photogrammetry techniques, properly adapted to specific characteristics of unmanned, low-altitude imagery. Firstly, a method was developed for robust sparse matching and epipolar-geometry estimation. The main achievement of this method was its capacity to handle a very high percentage of outliers (errors among corresponding points) with remarkable computational efficiency (compared to the state-of-the-art techniques). Secondly, a block bundle adjustment (BBA) strategy was proposed based on the integration of intrinsic camera calibration parameters as pseudo-observations to Gauss-Helmert model. The principal advantage of this strategy was controlling the adverse effect of unstable imaging networks and noisy image observations on the accuracy of self-calibration. The sparse implementation of this strategy was also performed, which allowed its application to data sets containing a lot of tie points. Finally, the concepts of intrinsic curves were revisited for dense stereo matching. The proposed technique could achieve a high level of accuracy and efficiency by searching only through a small fraction of the whole disparity search space as well as internally handling occlusions and matching ambiguities. These photogrammetric solutions were extensively tested using synthetic data, close-range images and the images acquired from the gravel-pit mine. Achieving absolute 3D mapping accuracy of 11±7 mm illustrated the success of this system for high-precision modeling of the environment.