In defence of modeling simultaneity for a correct approximation of cultural aspects: implications for food consumers studies with latent variables

Dealing with latent constructs (loaded by reflective and congeneric measures) cross-culturally compared means studying how these unobserved variables vary, and/or covary each other, after controlling for possibly disturbing cultural forces. This yields to the so-called ‘measurement invariance’ matter that refers to the extent to which data collected by the same multi-item measurement instrument (i.e., self-reported questionnaire of items underlying common latent constructs) are comparable across different cultural environments. As a matter of fact, it would be unthinkable exploring latent variables heterogeneity (e.g., latent means; latent levels of deviations from the means (i.e., latent variances), latent levels of shared variation from the respective means (i.e., latent covariances), levels of magnitude of structural path coefficients with regard to causal relations among latent variables) across different populations without controlling for cultural bias in the underlying measures. Furthermore, it would be unrealistic to assess this latter correction without using a framework that is able to take into account all these potential cultural biases across populations simultaneously. Since the real world ‘acts’ in a simultaneous way as well. As a consequence, I, as researcher, may want to control for cultural forces hypothesizing they are all acting at the same time throughout groups of comparison and therefore examining if they are inflating or suppressing my new estimations with hierarchical nested constraints on the original estimated parameters. Multi Sample Structural Equation Modeling-based Confirmatory Factor Analysis (MS-SEM-based CFA) still represents a dominant and flexible statistical framework to work out this potential cultural bias in a simultaneous way. With this dissertation I wanted to make an attempt to introduce new viewpoints on measurement invariance handled under covariance-based SEM framework by means of a consumer behavior modeling application on functional food choices.

Computer aided design and finite element modeling to predict bulk mechanical properties of bone scaffolds using triply periodic minimal surfaces (progettazione assistita al calcolatore ed analisi con il metodo degli elementi finiti per predire il comportamento meccanico di scaffolds ossei creati con l'uso di superfici minime periodiche in tre direzioni)

The aim of Tissue Engineering is to develop biological substitutes that will restore lost morphological and functional features of diseased or damaged portions of organs. Recently computer-aided technology has received considerable attention in the area of tissue engineering and the advance of additive manufacture (AM) techniques has significantly improved control over the pore network architecture of tissue engineering scaffolds. To regenerate tissues more efficiently, an ideal scaffold should have appropriate porosity and pore structure. More sophisticated porous configurations with higher architectures of the pore network and scaffolding structures that mimic the intricate architecture and complexity of native organs and tissues are then required. This study adopts a macro-structural shape design approach to the production of open porous materials (Titanium foams), which utilizes spatial periodicity as a simple way to generate the models. From among various pore architectures which have been studied, this work simulated pore structure by triply-periodic minimal surfaces (TPMS) for the construction of tissue engineering scaffolds. TPMS are shown to be a versatile source of biomorphic scaffold design. A set of tissue scaffolds using the TPMS-based unit cell libraries was designed. TPMS-based Titanium foams were meant to be printed three dimensional with the relative predicted geometry, microstructure and consequently mechanical properties. Trough a finite element analysis (FEA) the mechanical properties of the designed scaffolds were determined in compression and analyzed in terms of their porosity and assemblies of unit cells. The purpose of this work was to investigate the mechanical performance of TPMS models trying to understand the best compromise between mechanical and geometrical requirements of the scaffolds. The intention was to predict the structural modulus in open porous materials via structural design of interconnected three-dimensional lattices, hence optimising geometrical properties. With the aid of FEA results, it is expected that the effective mechanical properties for the TPMS-based scaffold units can be used to design optimized scaffolds for tissue engineering applications. Regardless of the influence of fabrication method, it is desirable to calculate scaffold properties so that the effect of these properties on tissue regeneration may be better understood.

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.

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.

Assessment Of Dynamic Properties Of A Crowd Model For Human-Structure Interaction Modeling

As lightweight and slender structural elements are more frequently used in the design, large scale structures become more flexible and susceptible to excessive vibrations. To ensure the functionality of the structure, dynamic properties of the occupied structure need to be estimated during the design phase. Traditional analysis method models occupants simply as an additional mass; however, research has shown that human occupants could be better modeled as an additional degree-of- freedom. In the United Kingdom, active and passive crowd models are proposed by the Joint Working Group as a result of a series of analytical and experimental research. It is expected that the crowd models would yield a more accurate estimation to the dynamic response of the occupied structure. However, experimental testing recently conducted through a graduate student project at Bucknell University indicated that the proposed passive crowd model might be inaccurate in representing the impact on the structure from the occupants. The objective of this study is to provide an assessment of the validity of the crowd models proposed by JWG through comparing the dynamic properties obtained from experimental testing data and analytical modeling results. The experimental data used in this study was collected by Firman in 2010. The analytical results were obtained by performing a time-history analysis on a finite element model of the occupied structure. The crowd models were created based on the recommendations from the JWG combined with the physical properties of the occupants during the experimental study. During this study, SAP2000 was used to create the finite element models and to implement the analysis; Matlab and ME¿scope were used to obtain the dynamic properties of the structure through processing the time-history analysis results from SAP2000. The result of this study indicates that the active crowd model could quite accurately represent the impact on the structure from occupants standing with bent knees while the passive crowd model could not properly simulate the dynamic response of the structure when occupants were standing straight or sitting on the structure. Future work related to this study involves improving the passive crowd model and evaluating the crowd models with full-scale structure models and operating data.

Monitoring and Modeling of the Hydraulic and Sediment Processes at In-Stream Restoration Structures in the Vicinity of a Bridge Crossing

The long-term performance of infrastructure depends on reliable and sustainable designs. Many of Pennsylvania’s streams experience sediment transport problems that increase maintenance costs and lower structural integrity of bridge crossings. A stream restoration project is one common mitigation measure used to correct such problems at bridge crossings. Specifically, in an attempt to alleviate aggradation problems with the Old Route 15 Bridge crossing on White Deer Creek, in White Deer, PA, two in-stream structures (rock cross vanes) and several bank stabilization features were installed along with a complete channel redevelopment. The objectives of this research were to characterize the hydraulic and sediment transport processes occurring at the White Deer Creek site, and to investigate, through physical and mathematical modeling, the use of instream restoration structures. The goal is to be able to use the results of this study to prevent aggradation or other sediment related problems in the vicinity of bridges through improved design considerations. Monitoring and modeling indicate that the study site on White Deer Creek is currently unstable, experiencing general channel down-cutting, bank erosion, and several local areas of increased aggradation and degradation of the channel bed. An in-stream structure installed upstream of the Old Route 15 Bridge failed by sediment burial caused by the high sediment load that White Deer Creek is transporting as well as the backwater effects caused by the bridge crossing. The in-stream structure installed downstream of the Old Route 15 Bridge is beginning to fail because of the alignment of the structure with the approach direction of flow from upstream of the restoration structure.

MODELING FUNCTIONAL DATA WITH SPATIALLY HETEROGENEOUS SHAPE CHARACTERISTICS

We propose a novel class of models for functional data exhibiting skewness or other shape characteristics that vary with spatial or temporal location. We use copulas so that the marginal distributions and the dependence structure can be modeled independently. Dependence is modeled with a Gaussian or t-copula, so that there is an underlying latent Gaussian process. We model the marginal distributions using the skew t family. The mean, variance, and shape parameters are modeled nonparametrically as functions of location. A computationally tractable inferential framework for estimating heterogeneous asymmetric or heavy-tailed marginal distributions is introduced. This framework provides a new set of tools for increasingly complex data collected in medical and public health studies. Our methods were motivated by and are illustrated with a state-of-the-art study of neuronal tracts in multiple sclerosis patients and healthy controls. Using the tools we have developed, we were able to find those locations along the tract most affected by the disease. However, our methods are general and highly relevant to many functional data sets. In addition to the application to one-dimensional tract profiles illustrated here, higher-dimensional extensions of the methodology could have direct applications to other biological data including functional and structural MRI.

Structural response and dynamics of fluid-structure-control interaction in wind turbine blades

Reducing the uncertainties related to blade dynamics by the improvement of the quality of numerical simulations of the fluid structure interaction process is a key for a breakthrough in wind-turbine technology. A fundamental step in that direction is the implementation of aeroelastic models capable of capturing the complex features of innovative prototype blades, so they can be tested at realistic full-scale conditions with a reasonable computational cost. We make use of a code based on a combination of two advanced numerical models implemented in a parallel HPC supercomputer platform: First, a model of the structural response of heterogeneous composite blades, based on a variation of the dimensional reduction technique proposed by Hodges and Yu. This technique has the capacity of reducing the geometrical complexity of the blade section into a stiffness matrix for an equivalent beam. The reduced 1-D strain energy is equivalent to the actual 3-D strain energy in an asymptotic sense, allowing accurate modeling of the blade structure as a 1-D finite-element problem. This substantially reduces the computational effort required to model the structural dynamics at each time step. Second, a novel aerodynamic model based on an advanced implementation of the BEM(Blade ElementMomentum) Theory; where all velocities and forces are re-projected through orthogonal matrices into the instantaneous deformed configuration to fully include the effects of large displacements and rotation of the airfoil sections into the computation of aerodynamic forces. This allows the aerodynamic model to take into account the effects of the complex flexo-torsional deformation that can be captured by the more sophisticated structural model mentioned above. In this thesis we have successfully developed a powerful computational tool for the aeroelastic analysis of wind-turbine blades. Due to the particular features mentioned above in terms of a full representation of the combined modes of deformation of the blade as a complex structural part and their effects on the aerodynamic loads, it constitutes a substantial advancement ahead the state-of-the-art aeroelastic models currently available, like the FAST-Aerodyn suite. In this thesis, we also include the results of several experiments on the NREL-5MW blade, which is widely accepted today as a benchmark blade, together with some modifications intended to explore the capacities of the new code in terms of capturing features on blade-dynamic behavior, which are normally overlooked by the existing aeroelastic models.

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.

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.

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.

MODEL UPDATING AND STRUCTURAL HEALTH MONITORING OF HORIZONTAL AXIS WIND TURBINES VIA ADVANCED SPINNING FINITE ELEMENTS AND STOCHASTIC SUBSPACE IDENTIFICATION METHODS

Wind energy has been one of the most growing sectors of the nation’s renewable energy portfolio for the past decade, and the same tendency is being projected for the upcoming years given the aggressive governmental policies for the reduction of fossil fuel dependency. Great technological expectation and outstanding commercial penetration has shown the so called Horizontal Axis Wind Turbines (HAWT) technologies. Given its great acceptance, size evolution of wind turbines over time has increased exponentially. However, safety and economical concerns have emerged as a result of the newly design tendencies for massive scale wind turbine structures presenting high slenderness ratios and complex shapes, typically located in remote areas (e.g. offshore wind farms). In this regard, safety operation requires not only having first-hand information regarding actual structural dynamic conditions under aerodynamic action, but also a deep understanding of the environmental factors in which these multibody rotating structures operate. Given the cyclo-stochastic patterns of the wind loading exerting pressure on a HAWT, a probabilistic framework is appropriate to characterize the risk of failure in terms of resistance and serviceability conditions, at any given time. Furthermore, sources of uncertainty such as material imperfections, buffeting and flutter, aeroelastic damping, gyroscopic effects, turbulence, among others, have pleaded for the use of a more sophisticated mathematical framework that could properly handle all these sources of indetermination. The attainable modeling complexity that arises as a result of these characterizations demands a data-driven experimental validation methodology to calibrate and corroborate the model. For this aim, System Identification (SI) techniques offer a spectrum of well-established numerical methods appropriated for stationary, deterministic, and data-driven numerical schemes, capable of predicting actual dynamic states (eigenrealizations) of traditional time-invariant dynamic systems. As a consequence, it is proposed a modified data-driven SI metric based on the so called Subspace Realization Theory, now adapted for stochastic non-stationary and timevarying systems, as is the case of HAWT’s complex aerodynamics. Simultaneously, this investigation explores the characterization of the turbine loading and response envelopes for critical failure modes of the structural components the wind turbine is made of. In the long run, both aerodynamic framework (theoretical model) and system identification (experimental model) will be merged in a numerical engine formulated as a search algorithm for model updating, also known as Adaptive Simulated Annealing (ASA) process. This iterative engine is based on a set of function minimizations computed by a metric called Modal Assurance Criterion (MAC). In summary, the Thesis is composed of four major parts: (1) development of an analytical aerodynamic framework that predicts interacted wind-structure stochastic loads on wind turbine components; (2) development of a novel tapered-swept-corved Spinning Finite Element (SFE) that includes dampedgyroscopic effects and axial-flexural-torsional coupling; (3) a novel data-driven structural health monitoring (SHM) algorithm via stochastic subspace identification methods; and (4) a numerical search (optimization) engine based on ASA and MAC capable of updating the SFE aerodynamic model.

Structural model of the CopA copper ATPase of Enterococcus hirae based on chemical cross-linking

The CopA copper ATPase of Enterococcus hirae belongs to the family of heavy metal pumping CPx-type ATPases and shares 43% sequence similarity with the human Menkes and Wilson copper ATPases. Due to a lack of suitable protein crystals, only partial three-dimensional structures have so far been obtained for this family of ion pumps. We present a structural model of CopA derived by combining topological information obtained by intramolecular cross-linking with molecular modeling. Purified CopA was cross-linked with different bivalent reagents, followed by tryptic digestion and identification of cross-linked peptides by mass spectrometry. The structural proximity of tryptic fragments provided information about the structural arrangement of the hydrophilic protein domains, which was integrated into a three-dimensional model of CopA. Comparative modeling of CopA was guided by the sequence similarity to the calcium ATPase of the sarcoplasmic reticulum, Serca1, for which detailed structures are available. In addition, known partial structures of CPx-ATPase homologous to CopA were used as modeling templates. A docking approach was used to predict the orientation of the heavy metal binding domain of CopA relative to the core structure, which was verified by distance constraints derived from cross-links. The overall structural model of CopA resembles the Serca1 structure, but reveals distinctive features of CPx-type ATPases. A prominent feature is the positioning of the heavy metal binding domain. It features an orientation of the Cu binding ligands which is appropriate for the interaction with Cu-loaded metallochaperones in solution. Moreover, a novel model of the architecture of the intramembranous Cu binding sites could be derived.

Modeling of human P450 oxidoreductase structure by in silico mutagenesis and MD simulation

P450 oxidoreductase (POR) is the obligate electron donor for microsomal cytochrome P450s and mutations in POR cause several metabolic disorders. We have modeled the structure of human P450 oxidoreductase by in silico amino acid replacements in the rat POR crystal structure. The rat POR has 94% homology with human POR and 38 amino acids were replaced to make its sequence identical to human POR. Several rounds of molecular dynamic simulations refined the model and removed structural clashes from side chain alterations of replaced amino acids. This approach has the advantage of keeping the cofactor contacts and structural features of the core enzyme intact which could not be achieved by homology based approaches. The final model from our approach was of high quality and compared well with experimentally determined structures of other PORs. This model will be used for analyzing the structural implications of mutations and polymorphisms in human POR.

Molecular Surface Features in Modeling the HIV-1 RT Inhibitory Activity of 2-(2,6-Disubstituted phenyl)-3-(substituted pyrimidin-2-yl)-thiazolidin-4-ones

The human immunodeficiency virus-1 reverse transcriptase inhibitory activity of 2-(2,6-disubstituted phenyl)-3-(substituted pyrimidin-2-yl)-thiazolidin-4-ones have been analyzed using combinatorial protocol in multiple linear regression (CP-MLR) with several electronic and molecular surface area features of the compounds obtained from Molecular Operating Environment (MOE) software. The study has indicated the role of different charged molecular surface areas in modeling the inhibitory activity of the compounds. The derived models collectively suggested that the compounds should be compact without bulky substitutions on its peripheries for better HIV-1 RT inhibitory activity. It also emphasized the necessity of hydrophobicity and compact structural features for their activity. The scope of the descriptors identified for these analogues have been verified by extending the dataset with different 2-(disubstituted phenyl)-3-(substituted pyridin-2-yl)-thiazolidin-4-ones. The joint analysis of extended dataset highlighted the information content of identified descriptors in modeling the HIV-1 RT inhibitory activity of the compounds.