Identification of adequate neurally adjusted ventilatory assist (NAVA) during systematic increases in the NAVA level

Neurally adjusted ventilatory assist (NAVA) delivers airway pressure (P(aw)) in proportion to the electrical activity of the diaphragm (EAdi) using an adjustable proportionality constant (NAVA level, cm·H(2)O/μV). During systematic increases in the NAVA level, feedback-controlled down-regulation of the EAdi results in a characteristic two-phased response in P(aw) and tidal volume (Vt). The transition from the 1st to the 2nd response phase allows identification of adequate unloading of the respiratory muscles with NAVA (NAVA(AL)). We aimed to develop and validate a mathematical algorithm to identify NAVA(AL). P(aw), Vt, and EAdi were recorded while systematically increasing the NAVA level in 19 adult patients. In a multistep approach, inspiratory P(aw) peaks were first identified by dividing the EAdi into inspiratory portions using Gaussian mixture modeling. Two polynomials were then fitted onto the curves of both P(aw) peaks and Vt. The beginning of the P(aw) and Vt plateaus, and thus NAVA(AL), was identified at the minimum of squared polynomial derivative and polynomial fitting errors. A graphical user interface was developed in the Matlab computing environment. Median NAVA(AL) visually estimated by 18 independent physicians was 2.7 (range 0.4 to 5.8) cm·H(2)O/μV and identified by our model was 2.6 (range 0.6 to 5.0) cm·H(2)O/μV. NAVA(AL) identified by our model was below the range of visually estimated NAVA(AL) in two instances and was above in one instance. We conclude that our model identifies NAVA(AL) in most instances with acceptable accuracy for application in clinical routine and research.

Multi-Scale Modeling for Image Analysis of Brain Tumor Studies

Image-based modeling of tumor growth combines methods from cancer simulation and medical imaging. In this context, we present a novel approach to adapt a healthy brain atlas to MR images of tumor patients. In order to establish correspondence between a healthy atlas and a pathologic patient image, tumor growth modeling in combination with registration algorithms is employed. In a first step, the tumor is grown in the atlas based on a new multi-scale, multi-physics model including growth simulation from the cellular level up to the biomechanical level, accounting for cell proliferation and tissue deformations. Large-scale deformations are handled with an Eulerian approach for finite element computations, which can operate directly on the image voxel mesh. Subsequently, dense correspondence between the modified atlas and patient image is established using nonrigid registration. The method offers opportunities in atlasbased segmentation of tumor-bearing brain images as well as for improved patient-specific simulation and prognosis of tumor progression.

Coupling biomechanics to a cellular level model: An approach to patient-specific image driven multi-scale and multi-physics tumor simulation

Modeling of tumor growth has been performed according to various approaches addressing different biocomplexity levels and spatiotemporal scales. Mathematical treatments range from partial differential equation based diffusion models to rule-based cellular level simulators, aiming at both improving our quantitative understanding of the underlying biological processes and, in the mid- and long term, constructing reliable multi-scale predictive platforms to support patient-individualized treatment planning and optimization. The aim of this paper is to establish a multi-scale and multi-physics approach to tumor modeling taking into account both the cellular and the macroscopic mechanical level. Therefore, an already developed biomodel of clinical tumor growth and response to treatment is self-consistently coupled with a biomechanical model. Results are presented for the free growth case of the imageable component of an initially point-like glioblastoma multiforme tumor. The composite model leads to significant tumor shape corrections that are achieved through the utilization of environmental pressure information and the application of biomechanical principles. Using the ratio of smallest to largest moment of inertia of the tumor material to quantify the effect of our coupled approach, we have found a tumor shape correction of 20\% by coupling biomechanics to the cellular simulator as compared to a cellular simulation without preferred growth directions. We conclude that the integration of the two models provides additional morphological insight into realistic tumor growth behavior. Therefore, it might be used for the development of an advanced oncosimulator focusing on tumor types for which morphology plays an important role in surgical and/or radio-therapeutic treatment planning.

Modeling Features at Runtime

A feature represents a functional requirement fulfilled by a system. Since many maintenance tasks are expressed in terms of features, it is important to establish the correspondence between a feature and its implementation in source code. Traditional approaches to establish this correspondence exercise features to generate a trace of runtime events, which is then processed by post-mortem analysis. These approaches typically generate large amounts of data to analyze. Due to their static nature, these approaches do not support incremental and interactive analysis of features. We propose a radically different approach called live feature analysis, which provides a model at runtime of features. Our approach analyzes features on a running system and also makes it possible to grow feature representations by exercising different scenarios of the same feature, and identifies execution elements even to the sub-method level. We describe how live feature analysis is implemented effectively by annotating structural representations of code based on abstract syntax trees. We illustrate our live analysis with a case study where we achieve a more complete feature representation by exercising and merging variants of feature behavior and demonstrate the efficiency or our technique with benchmarks.

A Computationally Efficient Procedure for Modeling the First Step in the Alkaline Hydrolysis of Esters

A computationally efficient procedure for modeling the alkaline hydrolysis of esters is proposed based on calculations performed on methyl acetate and methyl benzoate systems. Extensive geometry and energy comparisons were performed on the simple ester methyl acetate. The effectiveness of performing high level single point ab initio energy calculations on the geometries obtained from semiempirical and ab initio methods was determined. The AM1 and PM3 semiempirical methods are evaluated for their ability to model the transition states and intermediates for ester hydrolysis. The Cramer/Truhlar SM3 solvation method was used to determine activation energies. The most computationally efficient way to model the transition states of large esters is to use the PM3 method. The PM3 transition structure can then be used as a template for the design of haptens capable of inducing catalytic antibodies.

Block of the hERG channel by bupivacaine: Electrophysiological and modeling insights towards stereochemical optimization

The hERG voltage-gated potassium channel mediates the cardiac I(Kr) current, which is crucial for the duration of the cardiac action potential. Undesired block of the channel by certain drugs may prolong the QT interval and increase the risk of malignant ventricular arrhythmias. Although the molecular determinants of hERG block have been intensively studied, not much is known about its stereoselectivity. Levo-(S)-bupivacaine was the first drug reported to have a higher affinity to block hERG than its enantiomer. This study strives to understand the principles underlying the stereoselectivity of bupivacaine block with the help of mutagenesis analyses and molecular modeling simulations. Electrophysiological measurements of mutated hERG channels allowed for the identification of residues involved in bupivacaine binding and stereoselectivity. Docking and molecular mechanics simulations for both enantiomers of bupivacaine and terfenadine (a non-stereoselective blocker) were performed inside an open-state model of the hERG channel. The predicted binding modes enabled a clear depiction of ligand-protein interactions. Estimated binding affinities for both enantiomers were consistent with electrophysiological measurements. A similar computational procedure was applied to bupivacaine enantiomers towards two mutated hERG channels (Tyr652Ala and Phe656Ala). This study confirmed, at the molecular level, that bupivacaine stereoselectively binds the hERG channel. These results help to lay the foundation for structural guidelines to optimize the cardiotoxic profile of drug candidates in silico.

Individual and population level effects of partner notification for Chlamydia trachomatis

Partner notification (PN or contact tracing) is an important aspect of treating bacterial sexually transmitted infections (STIs), such as Chlamydia trachomatis. It facilitates the identification of new infected cases that can be treated through individual case management. PN also acts indirectly by limiting onward transmission in the general population. However, the impact of PN, both at the level of individuals and the population, remains unclear. Since it is difficult to study the effects of PN empirically, mathematical and computational models are useful tools for investigating its potential as a public health intervention. To this end, we developed an individual-based modeling framework called Rstisim. It allows the implementation of different models of STI transmission with various levels of complexity and the reconstruction of the complete dynamic sexual partnership network over any time period. A key feature of this framework is that we can trace an individual's partnership history in detail and investigate the outcome of different PN strategies for C. trachomatis. For individual case management, the results suggest that notifying three or more partners from the preceding 18 months yields substantial numbers of new cases. In contrast, the successful treatment of current partners is most important for preventing re-infection of index cases and reducing further transmission of C. trachomatis at the population level. The findings of this study demonstrate the difference between individual and population level outcomes of public health interventions for STIs.

A BAYESIAN HIERARCHICAL FRAMEWORK FOR SPATIAL MODELING OF fMRI DATA

Functional neuroimaging techniques enable investigations into the neural basis of human cognition, emotions, and behaviors. In practice, applications of functional magnetic resonance imaging (fMRI) have provided novel insights into the neuropathophysiology of major psychiatric,neurological, and substance abuse disorders, as well as into the neural responses to their treatments. Modern activation studies often compare localized task-induced changes in brain activity between experimental groups. One may also extend voxel-level analyses by simultaneously considering the ensemble of voxels constituting an anatomically defined region of interest (ROI) or by considering means or quantiles of the ROI. In this work we present a Bayesian extension of voxel-level analyses that offers several notable benefits. First, it combines whole-brain voxel-by-voxel modeling and ROI analyses within a unified framework. Secondly, an unstructured variance/covariance for regional mean parameters allows for the study of inter-regional functional connectivity, provided enough subjects are available to allow for accurate estimation. Finally, an exchangeable correlation structure within regions allows for the consideration of intra-regional functional connectivity. We perform estimation for our model using Markov Chain Monte Carlo (MCMC) techniques implemented via Gibbs sampling which, despite the high throughput nature of the data, can be executed quickly (less than 30 minutes). We apply our Bayesian hierarchical model to two novel fMRI data sets: one considering inhibitory control in cocaine-dependent men and the second considering verbal memory in subjects at high risk for Alzheimer’s disease. The unifying hierarchical model presented in this manuscript is shown to enhance the interpretation content of these data sets.

ATP modeling of internal transformer faults for relay performance testing

Transformers are very important elements of any power system. Unfortunately, they are subjected to through-faults and abnormal operating conditions which can affect not only the transformer itself but also other equipment connected to the transformer. Thus, it is essential to provide sufficient protection for transformers as well as the best possible selectivity and sensitivity of the protection. Nowadays microprocessor-based relays are widely used to protect power equipment. Current differential and voltage protection strategies are used in transformer protection applications and provide fast and sensitive multi-level protection and monitoring. The elements responsible for detecting turn-to-turn and turn-to-ground faults are the negative-sequence percentage differential element and restricted earth-fault (REF) element, respectively. During severe internal faults current transformers can saturate and slow down the speed of relay operation which affects the degree of equipment damage. The scope of this work is to develop a modeling methodology to perform simulations and laboratory tests for internal faults such as turn-to-turn and turn-to-ground for two step-down power transformers with capacity ratings of 11.2 MVA and 290 MVA. The simulated current waveforms are injected to a microprocessor relay to check its sensitivity for these internal faults. Saturation of current transformers is also studied in this work. All simulations are performed with the Alternative Transients Program (ATP) utilizing the internal fault model for three-phase two-winding transformers. The tested microprocessor relay is the SEL-487E current differential and voltage protection relay. The results showed that the ATP internal fault model can be used for testing microprocessor relays for any percentage of turns involved in an internal fault. An interesting observation from the experiments was that the SEL-487E relay is more sensitive to turn-to-turn faults than advertized for the transformers studied. The sensitivity of the restricted earth-fault element was confirmed. CT saturation cases showed that low accuracy CTs can be saturated with a high percentage of turn-to-turn faults, where the CT burden will affect the extent of saturation. Recommendations for future work include more accurate simulation of internal faults, transformer energization inrush, and other scenarios involving core saturation, using the newest version of the internal fault model. The SEL-487E relay or other microprocessor relays should again be tested for performance. Also, application of a grounding bank to the delta-connected side of a transformer will increase the zone of protection and relay performance can be tested for internal ground faults on both sides of a transformer.

Car ownership modeling and forecasts for China

A great increase of private car ownership took place in China from 1980 to 2009 with the development of the economy. To explain the relationship between car ownership and economic and social changes, an ordinary least squares linear regression model is developed using car ownership per capita as the dependent variable with GDP, savings deposits and highway mileages per capita as the independent variables. The model is tested and corrected for econometric problems such as spurious correlation and cointegration. Finally, the regression model is used to project oil consumption by the Chinese transportation sector through 2015. The result shows that about 2.0 million barrels of oil will be consumed by private cars in conservative scenario, and about 2.6 million barrels of oil per day in high case scenario in 2015. Both of them are much higher than the consumption level of 2009, which is 1.9 million barrels per day. It also shows that the annual growth rate of oil demand by transportation is 2.7% - 3.1% per year in the conservative scenario, and 6.9% - 7.3% per year in the high case forecast scenario from 2010 to 2015. As a result, actions like increasing oil efficiency need to be taken to deal with challenges of the increasing demand for oil.

Multiscale constitutive modeling of polymer materials

Materials are inherently multi-scale in nature consisting of distinct characteristics at various length scales from atoms to bulk material. There are no widely accepted predictive multi-scale modeling techniques that span from atomic level to bulk relating the effects of the structure at the nanometer (10-9 meter) on macro-scale properties. Traditional engineering deals with treating matter as continuous with no internal structure. In contrast to engineers, physicists have dealt with matter in its discrete structure at small length scales to understand fundamental behavior of materials. Multiscale modeling is of great scientific and technical importance as it can aid in designing novel materials that will enable us to tailor properties specific to an application like multi-functional materials. Polymer nanocomposite materials have the potential to provide significant increases in mechanical properties relative to current polymers used for structural applications. The nanoscale reinforcements have the potential to increase the effective interface between the reinforcement and the matrix by orders of magnitude for a given reinforcement volume fraction as relative to traditional micro- or macro-scale reinforcements. To facilitate the development of polymer nanocomposite materials, constitutive relationships must be established that predict the bulk mechanical properties of the materials as a function of the molecular structure. A computational hierarchical multiscale modeling technique is developed to study the bulk-level constitutive behavior of polymeric materials as a function of its molecular chemistry. Various parameters and modeling techniques from computational chemistry to continuum mechanics are utilized for the current modeling method. The cause and effect relationship of the parameters are studied to establish an efficient modeling framework. The proposed methodology is applied to three different polymers and validated using experimental data available in literature.

RF-sputter fabrication of magnetic garnet thin films and simulation modeling for 1-D magnetic photonic crystal waveguide devices

One dimensional magnetic photonic crystals (1D-MPC) are promising structures for integrated optical isolator applications. Rare earth substituted garnet thin films with proper Faraday rotation are required to fabricate planar 1D-MPCs. In this thesis, flat-top response 1D-MPC was proposed and spectral responses and Faraday rotation were modeled. Bismuth substituted iron garnet films were fabricated by RF magnetron sputtering and structures, compositions, birefringence and magnetooptical properties were studied. Double layer structures for single mode propagation were also fabricated by sputtering for the first time. Multilayer stacks with multiple defects (phase shift) composed of Ce-YIG and GGG quarter-wave plates were simulated by the transfer matrix method. The transmission and Faraday rotation characteristics were theoretically studied. It is found that flat-top response, with 100% transmission and near 45o rotation is achievable by adjusting the inter-defect spacing, for film structures as thin as 30 to 35 μm. This is better than 3-fold reduction in length compared to the best Ce-YIG films for comparable rotations, thus allows a considerable reduction in size in manufactured optical isolators. Transmission bands as wide as 7nm were predicted, which is considerable improvement over 2 defects structure. Effect of repetition number and ratio factor on transmission and Faraday rotation ripple factors for the case of 3 and 4 defects structure has been discussed. Diffraction across the structure corresponds to a longer optical path length. Thus the use of guided optics is required to minimize the insertion losses in integrated devices. This part is discussed in chapter 2 in this thesis. Bismuth substituted iron garnet thin films were prepared by RF magnetron sputtering. We investigated or measured the deposition parameters optimization, crystallinity, surface morphologies, composition, magnetic and magnetooptical properties. A very high crystalline quality garnet film with smooth surface has been heteroepitaxially grown on (111) GGG substrate for films less than 1μm. Dual layer structures with two distinct XRD peaks (within a single sputtered film) start to develop when films exceed this thickness. The development of dual layer structure was explained by compositional gradient across film thickness, rather than strain gradient proposed by other authors. Lower DC self bias or higher substrate temperature is found to help to delay the appearance of the 2nd layer. The deposited films show in-plane magnetization, which is advantageous for waveguide devices application. Propagation losses of fabricated waveguides can be decreased by annealing in an oxygen atmosphere from 25dB/cm to 10dB/cm. The Faraday rotation at λ=1.55μm were also measured for the waveguides. FR is small (10° for a 3mm long waveguide), due to the presence of linear birefringence. This part is covered in chapter 4. We also investigated the elimination of linear birefringence by thickness tuning method for our sputtered films. We examined the compressively and tensilely strained films and analyze the photoelastic response of the sputter deposited garnet films. It has been found that the net birefringence can be eliminated under planar compressive strain conditions by sputtering. Bi-layer GGG on garnet thin film yields a reduced birefringence. Temperature control during the sputter deposition of GGG cover layer is critical and strongly influences the magnetization and birefringence level in the waveguide. High temperature deposition lowers the magnetization and increases the linear birefringence in the garnet films. Double layer single mode structures fabricated by sputtering were also studied. The double layer, which shows an in-plane magnetization, has an increased RMS roughness upon upper layer deposition. The single mode characteristic was confirmed by prism coupler measurement. This part is discussed in chapter 5.

Proteins in silico-modeling and sampling

Proteins are linear chain molecules made out of amino acids. Only when they fold to their native states, they become functional. This dissertation aims to model the solvent (environment) effect and to develop & implement enhanced sampling methods that enable a reliable study of the protein folding problem in silico. We have developed an enhanced solvation model based on the solution to the Poisson-Boltzmann equation in order to describe the solvent effect. Following the quantum mechanical Polarizable Continuum Model (PCM), we decomposed net solvation free energy into three physical terms– Polarization, Dispersion and Cavitation. All the terms were implemented, analyzed and parametrized individually to obtain a high level of accuracy. In order to describe the thermodynamics of proteins, their conformational space needs to be sampled thoroughly. Simulations of proteins are hampered by slow relaxation due to their rugged free-energy landscape, with the barriers between minima being higher than the thermal energy at physiological temperatures. In order to overcome this problem a number of approaches have been proposed of which replica exchange method (REM) is the most popular. In this dissertation we describe a new variant of canonical replica exchange method in the context of molecular dynamic simulation. The advantage of this new method is the easily tunable high acceptance rate for the replica exchange. We call our method Microcanonical Replica Exchange Molecular Dynamic (MREMD). We have described the theoretical frame work, comment on its actual implementation, and its application to Trp-cage mini-protein in implicit solvent. We have been able to correctly predict the folding thermodynamics of this protein using our approach.

Physical modeling of air injection as a scour remediation technique near gated weir stilling basins

The South Florida Water Management District (SFWMD) manages and operates numerous water control structures that are subject to scour. In an effort to reduce scour downstream of these gated structures, laboratory experiments were performed to investigate the effect of active air-injection downstream of the terminal structure of a gated spillway on the depth of the scour hole. A literature review involving similar research revealed significant variables such as the ratio of headwater-to-tailwater depths, the diffuser angle, sediment uniformity, and the ratio of air-to-water volumetric discharge values. The experimental design was based on the analysis of several of these non-dimensional parameters. Bed scouring at stilling basins downstream of gated spillways has been identified as posing a serious risk to the spillway’s structural stability. Although this type of scour has been studied in the past, it continues to represent a real threat to water control structures and requires additional attention. A hydraulic scour channel comprised of a head tank, flow straightening section, gated spillway, stilling basin, scour section, sediment trap, and tail-tank was used to further this analysis. Experiments were performed in a laboratory channel consisting of a 1:30 scale model of the SFWMD S65E spillway structure. To ascertain the feasibility of air injection for scour reduction a proof-of-concept study was performed. Experiments were conducted without air entrainment and with high, medium, and low air entrainment rates for high and low headwater conditions. For the cases with no air entrainment it was found that there was excessive scour downstream of the structure due to a downward roller formed upon exiting the downstream sill of the stilling basin. When air was introduced vertically just downstream of, and at the same level as, the stilling basin sill, it was found that air entrainment does reduce scour depth by up to 58% depending on the air flow rate, but shifts the deepest scour location to the sides of the channel bed instead of the center. Various hydraulic flow conditions were tested without air injection to verify which scenario caused more scour. That scenario, uncontrolled free, in which water does not contact the gate and the water elevation in the stilling basin is lower than the spillway crest, would be used for the remainder of experiments testing air injection. Various air flow rates, diffuser elevations, air hole diameters, air hole spacings, diffuser angles and widths were tested in over 120 experiments. Optimal parameters include air injection at a rate that results in a water-to-air ratio of 0.28, air holes 1.016mm in diameter the entire width of the stilling basin, and a vertically orientated injection pattern. Detailed flow measurements were collected for one case using air injection and one without. An identical flow scenario was used for each experiment, namely that of a high flow rate and upstream headwater depth and a low tailwater depth. Equilibrium bed scour and velocity measurements were taken using an Acoustic Doppler Velocimeter at nearly 3000 points. Velocity data was used to construct a vector plot in order to identify which flow components contribute to the scour hole. Additionally, turbulence parameters were calculated in an effort to help understand why air-injection reduced bed scour. Turbulence intensities, normalized mean flow, normalized kinetic energy, and anisotropy of turbulence plots were constructed. A clear trend emerged that showed air-injection reduces turbulence near the bed and therefore reduces scour potential.