Advanced Visualization Techniques for Laparoscopic Liver Surgery

Laparoscopic liver surgery is mainly preferred over the traditional open liver surgery due to its unquestionable benefits. This type of surgery is executed by inserting an endoscope camera and the surgical tools inside the patient’s body through small incisions. The surgeons perform the operation by watching the video transmitted from the endoscope camera to high-resolution monitors. The location of the tumors and cysts is examined before and during the operation by the surgeons from the pre-operative CT scans displayed on a different monitor or on printed copies making the operation more difficult to perform. In order to make it easier for the surgeons to locate the tumors and cysts and have an insight for the rest of the inner structures of the liver, the 3D models of the liver’s inner structures are extracted from the preoperative CT scans and are overlaid on to the live video stream transmitted from the endoscope camera during the operation, a technique known as virtual X-ray. In that way the surgeons can virtually look into the liver and locate the tumors and cysts (focus objects) and also have a basic understanding of their spatial relation with other critical structures. The current master thesis focuses on enhancing the depth and spatial perception between the focus objects and their surrounding areas when they are overlaid on to the live endoscope video stream. That is achieved by placing a cone on the position of each focus object facing the camera. The cone creates an intersection surface (cut volume) that cuts the structures that lay in it, visualizing the depth of the cut and the spatial relation between the focus object and the intersected structures. The positioning of the cones is calculated automatically according to the center points of the focus objects but the sizes of the cones are user defined with bigger sizes revealing more of the surrounding area. The rest of the structures that are not part of any cut volume are not discarded but handled in such way that still depict their spatial relation with the rest of the structures. Different rendering results are presented for a laparoscopic liver test surgery in which a plastic liver model was used. The results include different presets of the cut volumes’ characteristics. Additionally, the same technique can be applied on the 3D liver’s surface instead of the live endoscope image and provide depth and spatial information. Results from that case are also presented

Effects of Energetic Disorder on the Optoelectronic Properties of Organic Solar Cells

Organic photovoltaics (OPVs) is a promising low-cost and environmental-friendly technology currently achieving 12-14% power conversion efficiency. Despite the extensive focus of the research community over the last years, critical mechanisms defining the performance of OPVs are still topics of debate. While energetic disorder is known to be characteristic of organic semiconductors in general, its potential role in OPV has received surprisingly little attention. In this thesis we investigate some aspects of the relation between energetic disorder and several optoelectronic properties of OPV. Charge carrier mobility is a key parameter in characterizing the performance of organic semiconductors. Analyzing the temperature dependence of the mobility is also an oftenused method to obtain (estimates for) the energetic disorder in the HOMO and LUMO levels of an organic semiconductor material. Different formalisms to extract and analyze mobilities from space charge limited conductivity (SCLC) experiments are reviewed. Surprisingly, the Murgatroyd-Gill analytical model in combination with the Gaussian disorder model in the Boltzmann limit yields similar mobilities and energetic disorders as a more elaborate drift-diffusion model with parametrized mobility functionals. Common analysis and measurement errors are discussed. All the models are incorporated in an automated analysis freeware tool. The open circuit voltage (Voc) has attracted considerable interest as the large difference between Voc and the bandgap is the main loss mechanism in bulk heterojunction OPVs. Surprisingly, in ternary devices composed of two donors and one acceptor, the Voc is not pinned to the shallowest HOMO but demonstrates a continuous tunability between the binary extremities. We show that this phenomenon can be explained with an equilibrium model where Voc is defined as the splitting of the quasi-Fermi levels of the photo-created holes and electrons in a common density of states accounting for the stoichiometry, i.e. the ratio of the donor materials and the broadening by Gaussian disorder. Evaluating the PCE, it is found that ternary devices do not offer advantages over binary unless the fill factor (FF) is increased at intermediate compositions, as a result of improved transport/recombination upon material blending. Stressing the importance of material intermixing to improve the performance, we found that the presence of an acceptor may drastically alter the mobility and energetic disorder of the donor and vice versa. The effect of different acceptors was studied in a ternary onedonor- two-acceptors system, where the unpredictable variability with composition of the energetic disorder in the HOMO and the LUMO explained the almost linear tunability of Voc. Designing binary OPVs based on the design rule that the energetic disorder can be reduced upon material blending, as we observed, can yield a relative PCE improvement of at least 20%. CT states currently play a key role in evaluating the performance of OPVs and CTelectroluminescence (CT-EL) is assumed to stem from the recombination of thermalized electron-hole pairs. The varying width of the CT-EL peak for different material combinations is intuitively expected to reflect the energetic disorder of the effective HOMO and LUMO. We employ kinetic Monte Carlo (kMC) CT-EL simulations, using independently measured disorder parameters as input, to calculate the ground-to-ground state (0-0) transition spectrum. Including the vibronic broadening according to the Franck Condon principle, we reproduce the width and current dependence of the measured CT-EL peak for a large number of donor-acceptor combinations. The fitted dominant phonon modes compare well with the values measured using the spectral line narrowing technique. Importantly, the calculations show that CT-EL originates from a narrow, non-thermalized subset of all available CT states, which can be understood by considering the kinetic microscopic process with which electron-hole pairs meet and recombine. Despite electron-hole pairs being strongly bound in organic materials, the charge separation process following photo-excitation is found to be extremely efficient and independent of the excitation energy. However, at low photon energies where the charges are excited deep in the tail of the DOS, it is intuitively expected for the extraction yield to be quenched. Internal Quantum Efficiency (IQE) experiments for different material systems show both inefficient and efficient charge dissociation for excitation close to the CT energy. This finding is explained by kinetic Monte Carlo simulations accounting for a varying degree of e-h delocalization, where strongly bound localized CT pairs (< 2nm distance) are doomed to recombine at low excitation energies while extended delocalization over 3-5nm yields an increased and energy-independent IQE. Using a single material parameter set, the experimental CT electroluminescence and absorption spectra are reproduced by the same kMC model by accounting for the vibronic progression of the calculated 0-0 transition. In contrast to CT-EL, CT-absorption probes the complete CT manifold. Charge transport in organic solar cells is currently modelled as either an equilibrium or a non-equilibrium process. The former is described by drift-diffusion (DD) equations, which can be calculated quickly but assume local thermal equilibrium of the charge carriers with the lattice. The latter is described by kMC models, that are time-consuming but treat the charge carriers individually and can probe all relevant time and energy scales. A hybrid model that makes use of the multiple trap and release (MTR) concept in combination with the DD equations is shown to describe both steady-state space charge limited conductivity experiments and non-equilibrium time-resolved transport experiments using a single parameter set. For the investigated simulations, the DD-MTR model is in good agreement with kMC and ~10 times faster. Steady-state mobilities from DD equations have been argued to be exclusively relevant for operating OPVs while charge carrier thermalization and non-equilibrium time-dependent mobilities (although acknowledged) can be disregarded. This conclusion, based on transient photocurrent experiments with μs time resolution, is not complete. We show that non-equilibrium kMC simulations can describe the extraction of charge carriers from subps to 100 μs timescales with a single parameter set. The majority of the fast charge carriers, mostly non-thermalized electrons, are extracted at time scales below the resolution of the experiment. In other words, the experiment resolves only the slower fraction of the charges, predominantly holes

EMPIRICAL ANALYSIS OF FACTORS AFFECTING THE EXPECTED RATE OF RETURN FOR ALL-ELECTRIC-VEHICLE MAKERS : USING REGRESSION ANALYSIS TO TEST THE SIGNIFICANCE OF THE CAPM AND FAMA FRENCH FACTORS ON THE CALCULATION OF THE EXPECTED RATE OF RETURN FOR 9 OF THE BIGGEST ALL-ELECTRIC VEHICLE MAKERS.

The All-Electric Vehicle (AEV) industry development has intensified and is connected to governmentefforts to minimize greenhouse gas emissions and encourage people to buy electric vehicles. This hasled to all the lights turning on newly established all-electric vehicle makers and some older players. Thegrowth of these companies is depicted in their market capitalization, which has seen an unprecedentedrun. However, one can notice a knowledge gap in the analysis of factors affecting such companies'expected rate of return. This research focuses on analyzing the factors from three of the most knownasset pricing models - CAPM, Fama-French 3 Factor, and Fama-French 5 Factor models. It shows whichof these factors are significant in estimating the expected return rate for nine chosen companies and theimpact of each considerable factor on the return rate.Additionally, we calculate the expected return rate using the beforementioned models to verify whetherthere is an uptrend or not in the electric vehicle market. The current research is limited to companieslisted on the US stock market, with only all-electric vehicle production lines. We make an introductionto the AEV theoretical aspects and related market structure. We also present theoretical concepts behindthe expected rate of return perception.The analysis showed that the market risk premium impacts 100% of the companies. The SMB factorinfluences 55% of the companies while the HML factor only 11%. Finally, RMW affects 66% of thechosen dataset and CMA 77%. For all companies, there is a positive expected return rate. Looking atthe significant coefficients for each model, the results are the following: we can observe that for CAPMand all the companies, 100% of the coefficients are positive. For FF3FM, 93% of the significant factorsare positive, while only 7% are negative. Finally, for FF5FM, out of the 28 significant factors, 65% ofthe coefficients are positive, and 35% are negative

EMPIRICAL ANALYSIS OF FACTORS AFFECTING THE EXPECTED RATE OF RETURN FOR ALL-ELECTRIC-VEHICLE MAKERS : USING REGRESSION ANALYSIS TO TEST THE SIGNIFICANCE OF THE CAPM AND FAMA FRENCH FACTORS ON THE CALCULATION OF THE EXPECTED RATE OF RETURN FOR 9 OF THE BIGGEST ALL-ELECTRIC VEHICLE MAKERS.

The All-Electric Vehicle (AEV) industry development has intensified and is connected to governmentefforts to minimize greenhouse gas emissions and encourage people to buy electric vehicles. This hasled to all the lights turning on newly established all-electric vehicle makers and some older players. Thegrowth of these companies is depicted in their market capitalization, which has seen an unprecedentedrun. However, one can notice a knowledge gap in the analysis of factors affecting such companies'expected rate of return. This research focuses on analyzing the factors from three of the most knownasset pricing models - CAPM, Fama-French 3 Factor, and Fama-French 5 Factor models. It shows whichof these factors are significant in estimating the expected return rate for nine chosen companies and theimpact of each considerable factor on the return rate.Additionally, we calculate the expected return rate using the beforementioned models to verify whetherthere is an uptrend or not in the electric vehicle market. The current research is limited to companieslisted on the US stock market, with only all-electric vehicle production lines. We make an introductionto the AEV theoretical aspects and related market structure. We also present theoretical concepts behindthe expected rate of return perception.The analysis showed that the market risk premium impacts 100% of the companies. The SMB factorinfluences 55% of the companies while the HML factor only 11%. Finally, RMW affects 66% of thechosen dataset and CMA 77%. For all companies, there is a positive expected return rate. Looking atthe significant coefficients for each model, the results are the following: we can observe that for CAPMand all the companies, 100% of the coefficients are positive. For FF3FM, 93% of the significant factorsare positive, while only 7% are negative. Finally, for FF5FM, out of the 28 significant factors, 65% ofthe coefficients are positive, and 35% are negative

Open circuit voltage and efficiency in ternary organic photovoltaic blends

Organic bulk heterojunction solar cells based on ternary blends of two donor absorbers and one acceptor are investigated by experiments and modeling. The commonly observed continuous tunability of the open circuit voltage VOC with the donor1: donor2 ratio can quantitatively be explained as quasi-Fermi level splitting due to photocreated charges filling a joint density of states that is broadened by Gaussian disorder. On this basis, a predictive model for the power conversion efficiency that accounts for the composition-dependent absorption and the shape of the current-voltage characteristic curve is developed. When all other parameters, most notably the fill factor, are constant, we find that for state-of-the-art absorbers, having a broad and strong absorption spectrum, ternary blends offer no advantage over binary ones. For absorbers with a more narrow absorption spectrum ternary blends of donors with complementary absorption spectra, offer modest improvements over binary ones. In contrast, when, upon blending, transport and/or recombination kinetics are improved, leading to an increased fill factor, ternaries may offer significant advantages over binaries

Nonequilibrium drift-diffusion model for organic semiconductor devices

Two prevailing formalisms are currently used to model charge transport in organic semiconductor devices. Drift-diffusion calculations, on the one hand, are time effective but assume local thermodynamic equilibrium, which is not always realistic. Kinetic Monte Carlo models, on the other hand, do not require this assumption but are computationally expensive. Here, we present a nonequilibrium drift-diffusion model that bridges this gap by fusing the established multiple trap and release formalism with the drift-diffusion transport equation. For a prototypical photovoltaic system the model is shown to quantitatively describe, with a single set of parameters, experiments probing (1) temperature-dependent steady-state charge transport-space-charge limited currents, and (2) time-resolved charge transport and relaxation of nonequilibrated photocreated charges. Moreover, the outputs of the developed kinetic drift-diffusion model are an order of magnitude, or more, faster to compute and in good agreement with kinetic Monte Carlo calculations