[Elbow dysplasia in the dog: finite element analysis]

For young active dogs of large, fast-growing breeds, diseases of the elbow represent an increasing important disorder. Genetic predisposition, overweight and joint overload have been proposed as possible causes of elbow dysplasia. In this study, the influence of various biomechanical parameters on load transfer in healthy and pathological dog elbows has been analysed by means of a two-dimensional finite element model. Pathological changes in the elbow structure, such as altered material properties or asynchronous bone growth, have a distinct influence on the contact pressure in the joint articulation, internal bone deformation and stresses in the bones. The results obtained support empirical observations made during years of experience and offer explanations for clinical findings that are not yet well understood.

Dosimetric impact of geometric errors due to respiratory motion prediction on dynamic multileaf collimator-based four-dimensional radiation delivery

The synchronization of dynamic multileaf collimator (DMLC) response with respiratory motion is critical to ensure the accuracy of DMLC-based four dimensional (4D) radiation delivery. In practice, however, a finite time delay (response time) between the acquisition of tumor position and multileaf collimator response necessitates predictive models of respiratory tumor motion to synchronize radiation delivery. Predicting a complex process such as respiratory motion introduces geometric errors, which have been reported in several publications. However, the dosimetric effect of such errors on 4D radiation delivery has not yet been investigated. Thus, our aim in this work was to quantify the dosimetric effects of geometric error due to prediction under several different conditions. Conformal and intensity modulated radiation therapy (IMRT) plans for a lung patient were generated for anterior-posterior/posterior-anterior (AP/PA) beam arrangements at 6 and 18 MV energies to provide planned dose distributions. Respiratory motion data was obtained from 60 diaphragm-motion fluoroscopy recordings from five patients. A linear adaptive filter was employed to predict the tumor position. The geometric error of prediction was defined as the absolute difference between predicted and actual positions at each diaphragm position. Distributions of geometric error of prediction were obtained for all of the respiratory motion data. Planned dose distributions were then convolved with distributions for the geometric error of prediction to obtain convolved dose distributions. The dosimetric effect of such geometric errors was determined as a function of several variables: response time (0-0.6 s), beam energy (6/18 MV), treatment delivery (3D/4D), treatment type (conformal/IMRT), beam direction (AP/PA), and breathing training type (free breathing/audio instruction/visual feedback). Dose difference and distance-to-agreement analysis was employed to quantify results. Based on our data, the dosimetric impact of prediction (a) increased with response time, (b) was larger for 3D radiation therapy as compared with 4D radiation therapy, (c) was relatively insensitive to change in beam energy and beam direction, (d) was greater for IMRT distributions as compared with conformal distributions, (e) was smaller than the dosimetric impact of latency, and (f) was greatest for respiration motion with audio instructions, followed by visual feedback and free breathing. Geometric errors of prediction that occur during 4D radiation delivery introduce dosimetric errors that are dependent on several factors, such as response time, treatment-delivery type, and beam energy. Even for relatively small response times of 0.6 s into the future, dosimetric errors due to prediction could approach delivery errors when respiratory motion is not accounted for at all. To reduce the dosimetric impact, better predictive models and/or shorter response times are required.

Finite element 3D reconstruction of the pulmonary acinus imaged by synchrotron X-ray tomography

The alveolated structure of the pulmonary acinus plays a vital role in gas exchange function. Three-dimensional (3D) analysis of the parenchymal region is fundamental to understanding this structure-function relationship, but only a limited number of attempts have been conducted in the past because of technical limitations. In this study, we developed a new image processing methodology based on finite element (FE) analysis for accurate 3D structural reconstruction of the gas exchange regions of the lung. Stereologically well characterized rat lung samples (Pediatr Res 53: 72-80, 2003) were imaged using high-resolution synchrotron radiation-based X-ray tomographic microscopy. A stack of 1,024 images (each slice: 1024 x 1024 pixels) with resolution of 1.4 mum(3) per voxel were generated. For the development of FE algorithm, regions of interest (ROI), containing approximately 7.5 million voxels, were further extracted as a working subunit. 3D FEs were created overlaying the voxel map using a grid-based hexahedral algorithm. A proper threshold value for appropriate segmentation was iteratively determined to match the calculated volume density of tissue to the stereologically determined value (Pediatr Res 53: 72-80, 2003). The resulting 3D FEs are ready to be used for 3D structural analysis as well as for subsequent FE computational analyses like fluid dynamics and skeletonization.

Modeling mechanical response of heterogeneous materials

Heterogeneous materials are ubiquitous in nature and as synthetic materials. These materials provide unique combination of desirable mechanical properties emerging from its heterogeneities at different length scales. Future structural and technological applications will require the development of advanced light weight materials with superior strength and toughness. Cost effective design of the advanced high performance synthetic materials by tailoring their microstructure is the challenge facing the materials design community. Prior knowledge of structure-property relationships for these materials is imperative for optimal design. Thus, understanding such relationships for heterogeneous materials is of primary interest. Furthermore, computational burden is becoming critical concern in several areas of heterogeneous materials design. Therefore, computationally efficient and accurate predictive tools are highly essential. In the present study, we mainly focus on mechanical behavior of soft cellular materials and tough biological material such as mussel byssus thread. Cellular materials exhibit microstructural heterogeneity by interconnected network of same material phase. However, mussel byssus thread comprises of two distinct material phases. A robust numerical framework is developed to investigate the micromechanisms behind the macroscopic response of both of these materials. Using this framework, effect of microstuctural parameters has been addressed on the stress state of cellular specimens during split Hopkinson pressure bar test. A voronoi tessellation based algorithm has been developed to simulate the cellular microstructure. Micromechanisms (microinertia, microbuckling and microbending) governing macroscopic behavior of cellular solids are investigated thoroughly with respect to various microstructural and loading parameters. To understand the origin of high toughness of mussel byssus thread, a Genetic Algorithm (GA) based optimization framework has been developed. It is found that two different material phases (collagens) of mussel byssus thread are optimally distributed along the thread. These applications demonstrate that the presence of heterogeneity in the system demands high computational resources for simulation and modeling. Thus, Higher Dimensional Model Representation (HDMR) based surrogate modeling concept has been proposed to reduce computational complexity. The applicability of such methodology has been demonstrated in failure envelope construction and in multiscale finite element techniques. It is observed that surrogate based model can capture the behavior of complex material systems with sufficient accuracy. The computational algorithms presented in this thesis will further pave the way for accurate prediction of macroscopic deformation behavior of various class of advanced materials from their measurable microstructural features at a reasonable computational cost.

Integration of computational models and experimental characterization to study internal frost damage in cementitious materials

The objective of this doctoral research is to investigate the internal frost damage due to crystallization pore pressure in porous cement-based materials by developing computational and experimental characterization tools. As an essential component of the U.S. infrastructure system, the durability of concrete has significant impact on maintenance costs. In cold climates, freeze-thaw damage is a major issue affecting the durability of concrete. The deleterious effects of the freeze-thaw cycle depend on the microscale characteristics of concrete such as the pore sizes and the pore distribution, as well as the environmental conditions. Recent theories attribute internal frost damage of concrete is caused by crystallization pore pressure in the cold environment. The pore structures have significant impact on freeze-thaw durability of cement/concrete samples. The scanning electron microscope (SEM) and transmission X-ray microscopy (TXM) techniques were applied to characterize freeze-thaw damage within pore structure. In the microscale pore system, the crystallization pressures at sub-cooling temperatures were calculated using interface energy balance with thermodynamic analysis. The multi-phase Extended Finite Element Modeling (XFEM) and bilinear Cohesive Zone Modeling (CZM) were developed to simulate the internal frost damage of heterogeneous cement-based material samples. The fracture simulation with these two techniques were validated by comparing the predicted fracture behavior with the captured damage from compact tension (CT) and single-edge notched beam (SEB) bending tests. The study applied the developed computational tools to simulate the internal frost damage caused by ice crystallization with the two dimensional (2-D) SEM and three dimensional (3-D) reconstructed SEM and TXM digital samples. The pore pressure calculated from thermodynamic analysis was input for model simulation. The 2-D and 3-D bilinear CZM predicted the crack initiation and propagation within cement paste microstructure. The favorably predicted crack paths in concrete/cement samples indicate the developed bilinear CZM techniques have the ability to capture crack nucleation and propagation in cement-based material samples with multiphase and associated interface. By comparing the computational prediction with the actual damaged samples, it also indicates that the ice crystallization pressure is the main mechanism for the internal frost damage in cementitious materials.

Two dimensional Lattice Boltzmann simulation of fluid flow through an idealized micro-structure of disordered media

This technical report discusses the application of Lattice Boltzmann Method (LBM) in the fluid flow simulation through porous filter-wall of disordered media. The diesel particulate filter (DPF) is an example of disordered media. DPF is developed as a cutting edge technology to reduce harmful particulate matter in the engine exhaust. Porous filter-wall of DPF traps these soot particles in the after-treatment of the exhaust gas. To examine the phenomena inside the DPF, researchers are looking forward to use the Lattice Boltzmann Method as a promising alternative simulation tool. The lattice Boltzmann method is comparatively a newer numerical scheme and can be used to simulate fluid flow for single-component single-phase, single-component multi-phase. It is also an excellent method for modelling flow through disordered media. The current work focuses on a single-phase fluid flow simulation inside the porous micro-structure using LBM. Firstly, the theory concerning the development of LBM is discussed. LBM evolution is always related to Lattice gas Cellular Automata (LGCA), but it is also shown that this method is a special discretized form of the continuous Boltzmann equation. Since all the simulations are conducted in two-dimensions, the equations developed are in reference with D2Q9 (two-dimensional 9-velocity) model. The artificially created porous micro-structure is used in this study. The flow simulations are conducted by considering air and CO2 gas as fluids. The numerical model used in this study is explained with a flowchart and the coding steps. The numerical code is constructed in MATLAB. Different types of boundary conditions and their importance is discussed separately. Also the equations specific to boundary conditions are derived. The pressure and velocity contours over the porous domain are studied and recorded. The results are compared with the published work. The permeability values obtained in this study can be fitted to the relation proposed by Nabovati [8], and the results are in excellent agreement within porosity range of 0.4 to 0.8.

Two-dimensional assembly and local redox-activity of molecular hybrid structures in an electrochemical environment

The self-assembly and redox-properties of two viologen derivatives, N-hexyl-N-(6-thiohexyl)-4,4-bipyridinium bromide (HS-6V6-H) and N,N-bis(6-thiohexyl)-4,4-bipyridinium bromide (HS-6V6-SH), immobilized on Au(111)-(1x1) macro-electrodes were investigated by cyclic voltammetry, surface enhanced infrared spectroscopy (SEIRAS) and in situ scanning tunneling microscopy (STM). Depending on the assembly conditions one could distinguish three different types of adlayers for both viologens: a low coverage disordered and an ordered striped phase of flat oriented molecules as well as a high coverage monolayer composed of tilted viologen moieties. Both molecules, HS-6V6-H and HS-6V6-SH, were successfully immobilized on Au(poly) nano-electrodes, which gave a well-defined redox-response in the lower pA–current range. An in situ STM configuration was employed to explore electron transport properties of single molecule junctions Au(T)|HS-6V6-SH(HS-6V6-H)|Au(S). The observed sigmoidal potential dependence, measured at variable substrate potential ES and at constant bias voltage (ET–ES), was attributed to electronic structure changes of the viologen moiety during the one-electron reduction/re-oxidation process V2+ V+. Tunneling experiments in asymmetric, STM-based junctions Au(T)-S-6V6-H|Au(S) revealed current (iT)–voltage (ET) curves with a maximum located at the equilibrium potential of the redox-process V2+ V+. The experimental iT–ET characteristics of the HS-6V6-H–modified tunneling junction were tentatively attributed to a sequential two-step electron transfer mechanism.

The Role of Online Platforms for Media Markets – Two‐Dimensional Spatial Competition in a Two‐Sided Market

We analyze the market for online and offline media in a model of two-dimensional spatial competition where media outlets sell content and advertising space. Consumer preferences are distributed along the style and type of news coverage where the distance costs may vary across dimensions. For integrated provision of online and offline platforms we show that entering the online market reduces average profits and may even constitute a prisoner's dilemma. Specialized provision may yield polarization in the style and type dimensions. This is in contrast to the maximum–minimum differentiation result previously established in the literature on multidimensional horizontal competition. We show that maximal differentiation in both dimensions occurs due to the discrete nature of the type dimension and asymmetric advertising markets.

Action crisis and cost–benefit thinking: A cognitive analysis of a goal-disengagement phase

The present research is based on the notion that disengagement from goals is not a discrete event but a process (Klinger, 1975). A critical phase in this process is when difficulties and setbacks in striving for a goal accumulate. This critical phase is termed here as an action crisis. Given the profound effects that people's thoughts have on their self-regulatory efficiency, it is essential to understand the cognitive correlates of an action crisis. In two experimental lab and two correlational field studies, the hypothesis that goal-related costs and benefits become cognitively highly accessible during an action crisis was tested and supported. Participants who were experiencing an action crisis in such diverse goal areas as intimate relationships, sports, and university studies, thought about goal-related costs and benefits more intensively and frequently in comparison to participants who were not in an action crisis. In an incidental learning task they recognized more of cost–benefit-items and less of implementation-items than the control group. Results are interpreted in terms of action phase specific mindsets (Gollwitzer, 1990, 2012).

Two-dimensional supramolecular polymers: controlled formation and visualization on the surface

Self – assembly is a powerful tool for the construction of highly organized nanostructures. Therefore, the possibility to control and predict pathways of molecular ordering on the nanoscale level is a critical issue for the production of materials with tunable and adaptive macroscopic properties. 2D polymers are attractive objects for the field of material sciences due to their exceptional properties. [1] As shown before, amphiphilic oligopyrenotides (produced via automated solid-phase synthesis) form rod–like supramolecular polymers in water. [2] These assemblies form 1D objects. [3] By applying certain changes to the design of the oligopyrenotide units the dimensionality of the formed assemblies can be influenced. Herein, we demonstrate that Py3 (see Figure 1) forms defined supramolecular assemblies under thermodynamic conditions in water. To study Py3 self-assembly, we carried out whole set of spectroscopic (UV/vis, fluorescence, DLS) and microscopic experiments (AFM). The obtained results suggest that oligopyrenotides with the present type of geometry and linker length leads to formation of 2D supramolecular assemblies.

Two-dimensional supramolecular polymers

One of the biggest issues of modern materials science is developing of strategies to create large and ordered assemblies in the form of discrete nanoscale objects. Oligopyrenotides (OPs) represent novel class of amphiphilic molecules which tend to self-assemble forming highly ordered structures. As has been already shown OPs are able to form 1D («rod-like») supramolecular polymer [1]. Since programmed arraying of polyaromatic hydrocarbons in structurally defined objects could offer enhanced performance over the individual components, prediction and controlling of their spatial arrangement remains challenging. Herein we demonstrate that certain changes to design of pyrene’s molecular core allow Py3 form 2D supramolecular assemblies («nanosheets») instead of 1D. Two dimensional supramolecular polymers are attractive objects due to their exceptional properties which originate from in-plan alignment of molecular units in the sheets with constant thickness ~ 2 nm [2]. These assemblies have high degree of internal order: the interior consists of hydrophobic pyrenes and alkyl chains, whereas the exterior exists as a net of hydrophilic, negatively charged phosphates. The Py3 units are hold up by non-covalent interactions what makes these assemblies totally reversible. Moreover the polymerization occurs via nucleation-elongation mechanism. To study Py3 self-assembly, we carried out whole set of spectroscopic (UV/vis, fluorescence, DLS) and microscopic experiments (AFM)

Two-dimensional supramolecular polymers

One of the biggest issues of modern materials science is developing of strategies to create large and ordered assemblies in the form of discrete nanoscale objects. Oligopyrenotides (OPs) represent novel class of amphiphilic molecules which tend to self-assemble forming highly ordered structures. As has been already shown OPs are able to form 1D («rod-like») supramolecular polymer [1]. Since programmed arraying of polyaromatic hydrocarbons in structurally defined objects could offer enhanced performance over the individual components, prediction and controlling of their spatial arrangement remains challenging. Herein we demonstrate that certain changes to design of pyrene’s molecular core allow Py3 form 2D supramolecular assemblies («nanosheets») instead of 1D. Two dimensional supramolecular polymers are attractive objects due to their exceptional properties which originate from in-plan alignment of molecular units in the sheets with constant thickness ~ 2 nm [2]. These assemblies have high degree of internal order: the interior consists of hydrophobic pyrenes and alkyl chains, whereas the exterior exists as a net of hydrophilic, negatively charged phosphates. The Py3 units are hold up by non-covalent interactions what makes these assemblies totally reversible. Moreover the polymerization occurs via nucleation-elongation mechanism. To study Py3 self-assembly, we carried out whole set of spectroscopic (UV/vis, fluorescence, DLS) and microscopic experiments (AFM)

Thermal 2-loop master spectral function at finite momentum

When considering NLO corrections to thermal particle production in the “relativistic” regime, in which the invariant mass squared of the produced particle is K2 ~ (πT)2, then the production rate can be expressed as a sum of a few universal “master” spectral functions. Taking the most complicated 2-loop master as an example, a general strategy for obtaining a convergent 2-dimensional integral representation is suggested. The analysis applies both to bosonic and fermionic statistics, and shows that for this master the non-relativistic approximation is only accurate for K2 ~(8πT)2, whereas the zero-momentum approximation works surprisingly well. Once the simpler masters have been similarly resolved, NLO results for quantities such as the right-handed neutrino production rate from a Standard Model plasma or the dilepton production rate from a QCD plasma can be assembled for K2 ~ (πT)2.

BAYESIAN PHASE I DOSE FINDING IN CANCER TRIALS

This dissertation explores phase I dose-finding designs in cancer trials from three perspectives: the alternative Bayesian dose-escalation rules, a design based on a time-to-dose-limiting toxicity (DLT) model, and a design based on a discrete-time multi-state (DTMS) model. We list alternative Bayesian dose-escalation rules and perform a simulation study for the intra-rule and inter-rule comparisons based on two statistical models to identify the most appropriate rule under certain scenarios. We provide evidence that all the Bayesian rules outperform the traditional ``3+3'' design in the allocation of patients and selection of the maximum tolerated dose. The design based on a time-to-DLT model uses patients' DLT information over multiple treatment cycles in estimating the probability of DLT at the end of treatment cycle 1. Dose-escalation decisions are made whenever a cycle-1 DLT occurs, or two months after the previous check point. Compared to the design based on a logistic regression model, the new design shows more safety benefits for trials in which more late-onset toxicities are expected. As a trade-off, the new design requires more patients on average. The design based on a discrete-time multi-state (DTMS) model has three important attributes: (1) Toxicities are categorized over a distribution of severity levels, (2) Early toxicity may inform dose escalation, and (3) No suspension is required between accrual cohorts. The proposed model accounts for the difference in the importance of the toxicity severity levels and for transitions between toxicity levels. We compare the operating characteristics of the proposed design with those from a similar design based on a fully-evaluated model that directly models the maximum observed toxicity level within the patients' entire assessment window. We describe settings in which, under comparable power, the proposed design shortens the trial. The proposed design offers more benefit compared to the alternative design as patient accrual becomes slower.

Estimation of aortic pressure waveforms from 4D phase-contrast MRI

Several approaches for the non-invasive MRI-based measurement of the aortic pressure waveform over the heart cycle have been proposed in the last years. These methods are normally based on time-resolved, two-dimensional phase-contrast sequences with uni-directionally encoded velocities (2D PC-MRI). In contrast, three-dimensional acquisitions with tridirectional velocity encoding (4D PC-MRI) have been shown to be a suitable data source for detailed investigations of blood flow and spatial blood pressure maps. In order to avoid additional MR acquisitions, it would be advantageous if the aortic pressure waveform could also be computed from this particular form of MRI. Therefore, we propose an approach for the computation of the aortic pressure waveform which can be completely performed using 4D PC-MRI. After the application of a segmentation algorithm, the approach automatically computes the aortic pressure waveform without any manual steps. We show that our method agrees well with catheter measurements in an experimental phantom setup and produces physiologically realistic results in three healthy volunteers.