This thesis focuses on the spread of organisms in both ecological and epidemiological contexts. In most of the studies presented, displacement is modeled with a spatial kernel function, which is characterized by scale and shape. These are measured by the net squared displacement (or kernel variance) and kurtosis, respectively. If organisms disperse by the assumptions of a random walk or correlated random walk, a Gaussian shaped kernel is expected. Empirical studies often report deviations from this, and commonly leptokurtic distributions are found, often as a result of heterogeneity in the dispersal process. In the studies presented in two of the included papers, the importance of the kernel shape is tested, by using a family of kernels where the shape and scale can be separated effectively. Both studies utilize spectral density approaches for modeling the spatial environment. It is concluded that the shape is not important when studying the population distribution in a habitat/matrix context. The shape is however important when looking at the invasion of organisms in a patchy environment, when the arrangement of patches deviates from randomly distributed. The introduced method for generating patch distribution is also compared to empirical distributions of patches (farms and old trees). Here it is concluded that the assumptions used for modeling of the spatial environment are consistent with the observed patterns. These assumptions include fractal properties such that the same aggregational patterns are found at different scales. In a series of papers, movements of animals are considered as vectors for between-herd disease spread. The studies are based on data found in databases held by the Swedish Board of Agricultural (SJV), consisting of reported movements, as well as farm location and characteristics. The first study focuses on the distance related probability of contacts between herds. In the following papers, the analysis is expanded to include production type and herd size. Movement data of pigs (and cattle in Paper I) are analyzed with Bayesian models, implemented with Markov Chain Monte Carlo (MCMC). This is a flexible approach that allows for parameter estimations of complex models, and at the same time includes parameter uncertainty. In Paper IV, the effects of the included factors are investigated. It is shown that all three factors (herd size, production type structure and distance related probability of contacts) are expected to influence disease spread dynamics, however the production type structure is found to be the most important factor. This emphasizes the value of keeping such information in central databases. The models presented can be used as support for risk analysis and disease tracing. However, data reliability is always a problem, and implementation may be improved with better quality data. The thesis also shows that utilizing spatial kernels for description of the spatial spread of organisms is an appropriate approach. However, these kernels must be flexible and flawed assumptions about the shape may lead to erroneous conclusions. Hence, the joint distribution of kernel shape and scale should be estimated. The flexibility of Bayesian analysis, implemented with MCMC techniques, is a good approach for this, and further allows for implementation of more complex models where other factors may be included.

This study measures the effect of a model of explicit instruction (EMIT) on the: 1) physics graduate teaching assistants’ adherence to reformed teaching methods, 2) impact of the instructional model on GTAs’ beliefs about the nature of physics and physics problem solving and 3) undergraduate physics students’ understanding and performance in an introductory calculus-based physics course. Methods included explicit modeling for the treatment group GTAs of the Reformed Teaching Observation Protocol (RTOP) and assessment of treatment and control GTAs and their students throughout the semester. Students’ understanding was measured using the Force Concept Inventory (FCI) and Flash-mediated Force and Motion Concept Inventory (FM2CA). Students were surveyed about performance of GTAs using the Student Survey (SS). Results indicated changes were tied to individual GTAs’ beliefs about the nature of physics. Student conceptual understanding reflected a two-fold Hake gain compared to the control group. General application of the EMIT model presupposes explicit instruction of the model for GTAs.

This study measures the effect of a model of explicit instruction (EMIT) on the: 1) physics graduate teaching assistants’ adherence to reformed teaching methods, 2) impact of the instructional model on GTAs’ beliefs about the nature of physics and physics problem solving and 3) undergraduate physics students’ understanding and performance in an introductory calculus-based physics course. Methods included explicit modeling for the treatment group GTAs of the Reformed Teaching Observation Protocol (RTOP) and assessment of treatment and control GTAs and their students throughout the semester. Students’ understanding was measured using the Force Concept Inventory (FCI) and Flash-mediated Force and Motion Concept Inventory (FM2CA). Students were surveyed about performance of GTAs using the Student Survey (SS). Results indicated changes were tied to individual GTAs’ beliefs about the nature of physics. Student conceptual understanding reflected a two-fold Hake gain compared to the control group. General application of the EMIT model presupposes explicit instruction of the model for GTAs.

Les aérosols organiques secondaires (AOS) représentent une fraction significative de l'aérosol fin, et contribuent donc fortement à leurs impacts sur la santé, l'environnement et le climat. Connaitre les sources, l’évolution et les propriétés des AOS constitue actuellement un véritable enjeu pour la communauté scientifique. Ces AOS sont formés par condensation sur des aérosols préexistants des espèces de faible volatilité produites au cours de l’oxydation progressive de la matière organique gazeuse. L'objectif de ce travail de thèse vise à évaluer nos connaissances sur les processus de formation de l’AOS. La méthodologie mise en place consiste à (i) représenter les processus dans un modèle déterministe et explicite, (ii) confronter le modèle à des expériences de formation d’AOS effectuées dans des environnements contrôlés et (iii) examiner la sensibilité des évolutions simulées aux paramètres peu contraints. Le modèle GECKO-A (Generator for Explicit Chemistry and Kinetics of Organics in the Atmosphere) développé au LISA permet de générer des schémas chimiques explicites sur la base de principes fondamentaux et de renseigner les grandeurs cinétiques et thermodynamiques associées. Sa capacité à représenter la formation des AOS a été évaluée par comparaison avec des expériences en chambres de simulation atmosphérique (CSA). Les comparaisons modèle/mesures des rendements finaux en AOS montrent que l’outil GECKO-A restitue correctement l’influence de la structure moléculaire sur la formation d’AOS. Cependant l’analyse quantitative montre que ces rendements sont systématiquement surestimés. Ceci suggère que des processus sont manquants ou mal représentés dans le modèle, en particulier la perte de composés organiques gazeux aux parois des CSA. L’intégration de ce processus dans le modèle conduit à (i) une diminution des rendements finaux simulés pouvant atteindre un facteur 2, (ii) une modification de la composition de l’AOS avec une sensibilité importante pour les espèces de premières générations (nitrates, hydroxynitrates et carbonylesters) et (iii) une vitesse de production de l’AOS plus faible lorsque la vitesse de transfert vers les parois augmente. La dynamique de formation des AOS n'est cependant pas correctement reproduite par le modèle. Les résultats montrent que les incertitudes sur les paramètres d’accommodation à la surface des particules et de pertes gazeuses aux parois permettent d’encadrer les données expérimentales. Aucune configuration unique de ces deux paramètres ne permet, toutefois, de représenter l’ensemble des expériences / Secondary organic aerosols (SOAs) represent a large fraction of fine particle matter, and contribute therefore to their impacts on human health, environment and climate. Understanding the sources, the evolution and the properties of SOAs is a challenge for the scientific community. These SOAs are produced by condensation onto preexisting aerosols of low volatility compounds formed during the progressive oxidation of gaseous organic matter. The objective of this thesis is to assess our knowledge of SOA formation processes. The methodology aims at (i) representing the processes in a deterministic and explicit model, (ii) comparing the modeling results with SOA measurements performed in controlled environments and (iii) examining the sensitivity of simulated results to poorly constrained parameters. The GECKO-A model (Generator for Explicit Chemistry and Kinetics of Organics in the Atmosphere) developed at LISA generates explicit chemical schemes on the basis of fundamental principles and provides the related kinetic and thermodynamic constants. Its ability to represent SOA formation was evaluated by comparisons with experiments performed in environmental chambers. The comparisons between modeled and measured final SOA yields show that the GECKO-A tool accurately reproduces the influence of molecular structure on the SOA formation. However, quantitative analysis shows that these yields are systematically overestimated. This suggests that processes are missing or misrepresented in the model, in particular the loss of gaseous organic compounds on the chamber walls. The implementation of this process into the model leads to (i) a decrease of the simulated final yields up to a factor 2, (ii) a change on SOA composition with a high sensitivity for the first generation species (nitrates, hydroxynitrates and carbonylesters) and (iii) a decrease in the SOA production rate when the mass transfer rate to the wall is increased. The model fails however to reproduce the dynamic of SOA formation. The results show that the uncertainties on particle surface accommodation and wall losses allow to encompass the experimental data. However, no unique configuration of these two parameters can be selected for all of the experiments

The behavior of jointed rock mass is very complex and is influenced by many factors such as location of joints, joint frequency, joint orientation and joint strength. A thorough review of literature on different aspects of jointed rock mass indicate that the discontinuities or planes of weakness present in rock mass significantly influence its behavior. Numerous experimental tests were conducted to study the behavior of natural as well as artificial joints in rocks. Laboratory tests are time consuming and give results applicable to specific joint fabric and confining pressure. Numerical methods are the best alternative to laboratory tests to study the behavior of jointed rock mass. With the advent of computers numerical methods of analysis have become very popular, as they are highly flexible and can represent all complex geometries and material behavior. The accuracy of a numerical model depends upon the how well constitutive relations for the jointed rock mass are defined in the analysis. Empirical relationships for describing the mechanical behavior of discontinuities obtained from scaling the laboratory data is crucial unresolved problem, which will affect the quality of results obtained. One more important aspect in the numerical model is strength criteria used for jointed rock mass. The applicability of existing strength criteria to a particular jointed rock has to be carefully examined before they are used. Equivalent continuum approach simplifies the modeling of jointed rock mass as the joints are not modeled separately. Instead in equivalent continuum approach the jointed rock mass is represented by an equivalent continuum whose properties are defined by a combination of intact rock properties and joint properties. The accuracy of this kind of modeling depends upon the relationships used to define the jointed rock mass properties as a function of intact rock properties and joint properties. In the present study, an effort has been made (i) to establish empirical relations to define the properties of jointed rock mass as a function of intact rock properties and joint factor (ii) to develop a numerical model based on equivalent continuum approach using the empirical relations derived above, for easy and efficient modeling of jointed rock mass (iii) comparison of existing strength criteria for jointed rock masses using the equivalent continuum model developed above (iv) Modeling of joints explicitly and comparing these results with the equivalent continuum model results. Empirical relationships expressing the uniaxial compressive strength and elastic modulus of jointed rock as a function of corresponding intact rock properties and joint factor have been derived based on the statistical analysis of large amount of experimental data of uniaxial and triaxial tests collected from the literature. The effect of joints in the jointed rock is taken in to account by the joint factor. A comparative study of the empirical relationships arrived by the above analysis has been made to choose the best relation for the numerical analysis. Empirical relationships thus arrived for jointed rock mass are used in the equivalent continuum approach to represent the jointed rock properties as a combination of intact rock properties and joint factor. Equivalent continuum model developed is thoroughly tested, validated and applied for single, multiple and block jointed rocks. The equivalent continuum model developed has been applied for analysis of the power cavern for Shiobara power station. Different strength criteria available for jointed rock namely Mohr-Coulomb, Hoek and Drown, Yudhbir et al. and Rarnamurthy are incorporated in the equivalent continuum model to evaluate their applicability for jointed rock masses. Ramarnurthy's strength criterion gives the best values of failure stress for almost all the test cases and hence used in the equivalent continuum model. Alternatively, the joints in jointed rock mass are represented explicitly using interface element in the nonlinear finite element analysis. The explicit finite element model has been tested and validated using the experimental stress strain curves and failure stress values. Comparison of results obtained using equivalent continuum analysis and explicit modeling of joints has been given in the form of stress strain curves and failure stress plots for jointed rock masses along with the experimental results. Some of the major conclusions from the present study are as follows. Statistical relationships arrived to express the properties of the jointed rock as a function of intact rock and joint factor give a fair estimate of jointed rock in the absence of experimental data. Equivalent continuum model developed using statistical relations arrived above simplifies the numerical modeling of jointed rock to a large extent and also gives a fair estimate of jointed rock behavior with minimum input data. From the equivalent continuum analysis of Shiobara power cavern, it can be concluded that this approach is very advantageous for modeling highly discontinuous systems provided the joint factor is estimated properly so that it represents the real fabric of the joints present in the system. Comparison of different strength criteria shows that Ramamurthy's strength criterion is the best for jointed rocks. When the rock mass has one or two major joints it is advantageous to model it explicitly so that the behavior of the joint can be studied in detail. Explicit representation of the joints in the finite element analysis gives a lair estimate of the zones most susceptible to failure in a jointed rock. From comparison of experimental values, equivalent continuum model results and the explicit joint model results, it can be concluded that results obtained using equivalent continuum model are nearest to the experimental results in almost all the cases.