VictorJuiz/thesis huggingface dataset:
Beyond Consent: A Relational Model of Community Authorization for Genetically Modified Mosquito Trials in Developing Countries
Keywords: Bioethics
Community
Consent
Engagement
Global Health
Research Ethics

This thesis provides the first empirical explanatory theory for community authorization for Genetically Modified Mosquito (GMM) trials. Although this theory was developed in the context of GMM trials, it can apply to other endeavors, research or not, where whole communities might be affected. As GMM make their way from laboratories to villages of developing countries to test their effectiveness in controlling vector-borne diseases, community authorization emerges as a critical and urgent, yet undefined, mechanism of protection and respect for communities who might be affected by research and its outcomes.Following a constructivist Grounded Theory approach, I analyzed three prominent GMM trials from Mexico, the Cayman Islands, and Malaysia. Nineteen (19) interviews and two hundred and forty nine (249) documents were analyzed in order to uncover the substantive and procedural aspects of authentic and sufficient community authorization for research, as well as the factors that affect such authorization.This interdisciplinary bioethics thesis supports a relational notion of community authorization, as a continuous state of ongoing, maintenance-dependent, approval for research from inception through all stages. Enabled by successful relationships between researchers and community groups and individuals, this state manifests in formal and informal ways at all levels of the community; institutional, national, regional, local, and even individual, and involves authorities, both official and traditional, and publics alike. The state of authorization manifests in reciprocity, or the fulfillment of commitment to promote mutual interests. The findings challenge current conceptions of research participants as well as consent, and consequently current practices of research appraisal. Future research is needed to provide researchers, research ethics boards, and regulatory agencies with standardized tools to gauge the conduct of research in relationship to the community. The elements of this theory, as well as its reliability, applicability and generalizability, need to be tested and refined in future empirical work in multiple contexts and different fields.
An Examination of Productive Processing Activities in the Expressive Writing Intervention
Keywords: emotion
expression
processing
therapy
trauma
writing

Expressive Writing (EW) is a therapeutic intervention that involves writing about stressful experiences over several sessions using as much detail and references to emotion as possible. For individuals experiencing a wide range of psychological and physical symptoms, in response to an array of stressors, EW has been repeatedly shown to lead to positive outcomes. Not all participants experience these positive outcomes, however, and the questions of how EW works and why it can lead to disparate outcomes across participants remain. In an effort to address these questions, the present study turned to psychotherapy process research, which has revealed several in-session client cognitive and affective processes that are consistently linked with positive therapeutic change. The purpose of the present study was to examine whether these processes are also relevant to EW and can provide insight into how and why EW works. Twenty-eight individuals who experienced psychological trauma participated in an EW intervention. Measures of psychological and physical health were administered at baseline and one month follow-up. The Measure of Clients' Productive Processing (MCPP; Watson McMullen, 2008), an observer-rated measure, was used to assess participants' engagement in several processing activities believed to be productive. The Linguistic Inquiry and Word Count (LIWC; Pennebaker, Booth, Francis, 2007) was also used to examine word use related to affective processes and cognitive mechanisms. Partial correlations calculated between the MCPP, LIWC and outcome provided some support for the notion that the expression of emotions at a moderate level of arousal, as well as actively exploring and developing new understanding, are productive processes in EW. These processes were most prominently linked with improvements in depressive symptoms, though some improvements in other psychological and physical symptoms were also revealed. Phase of the intervention emerged as important, with the most notable effects occurring in the mid and late phases. Productive descriptions of external experience, expressions of need, and evaluations were not found to be related to positive outcome following EW. Results are discussed in the context of the previous research, with consideration given to limitations, future directions and clinical implications.
Lost in Translation: Exposure Misclassification when Relying on Days Supply in Pharmacy Claims Data
Keywords: Claims Data
Exposure Misclassification
Health Services Research
Osteoporosis
Pharmacy

Administrative pharmacy claims data are frequently utilized in pharmacoepidemiology. Days supply values are the most commonly used to estimate drug exposure. This research investigated the potential for exposure misclassification when relying on days supply values to quantify drug adherence and estimate drug effectiveness. With scheduled long-dose intervals, osteoporosis drugs provided a unique case example to examine the potential for misclassified days supply values. Using Ontario administrative claims data, three independent, yet related studies were completed. First, a cross-sectional study of all osteoporosis medications dispensed in Ontario identified potential inaccuracies in days supply values, particularly in long-term care (LTC), where only 59% of days supply values matched pre-defined expected values. In comparison, 90% of community prescriptions matched the expected. Next, two cohort studies were completed to investigate the potential impact of the noted variation in days supply reporting on measures of medication adherence (Study Two) and drug effectiveness (Study Three). To adjust for misclassification, dose-specific cleaning algorithms were developed based on the identification of logical typos and refill patterns, resulting in two values that could be compared; the observed and cleaned days supply. Measures of compliance and persistence were used to identify patient adherence, and were calculated using the observed and cleaned days supply. Results in Study Two identified that data cleaning significantly increased estimates of drug adherence, particularly among LTC residents, where mean compliance increased from 59% to 83% and proportion persisting with therapy increased from 62% to 78%. In the third study, Cox proportional hazard models were used to estimate the relationship between compliance and hip fractures. Results identified important differences in effect estimates following data cleaning, particularly in LTC, where a significant 35% (HRobserved=0.99 to HRcleaned=0.65) change in hazard ratio estimates was observed for the effect of high compliance on fracture risk. Overall, results identified larger differences in LTC settings where exposure was most likely to be misclassified; however, important differences were identified when all patients were combined. Cumulatively, the findings of this thesis have important methodological implications for pharmacoepidemiologic research, and will inform best practices when using days supply values.
Elucidating the Role of Protein Misfolding in Neurodegenrative Disease Using Multiphoton Microscopy
Keywords: Alzheimer's disease
neurodegenerative disease
protein misfolding
proteomics
two-photon microscopy

This work develops a two-pronged approach to using multiphoton microscopy for the study of protein folding and misfolding in neurodegenerative disease. First, we present the use of 1,8-anilinonaphthalene sulfonate (ANS) in two-photon excitation (TPE) microsopy as a probe for protein misfolding in living cells and tissues. By using TPE microscopy, we are able to generate high-resolution images with confocal-like optical sectioning, while avoiding the phototoxicity and photobleaching effects that would otherwise be associated with the ultraviolet-excited ANS. ANS fluorescence is compatible with live-cell imaging, and ANS binding occurs principally in the endoplasmic reticulum (ER), the Golgi apparatus, and the lysosomes. ANS fluorescence responds to an array of stressors, including ER stress, hyperthermia, and proteasome inhibition. Strikingly, ANS fluorescence highlights the nucleolus as a structure exquisitely sensitive to protein-damaging stress. ANS fluorescence microscopy is also possible in transparent organisms - including Caenorhabditis elegans and larval Drosophila melanogaster. Second, we develop a new photo-tag reagent (6HisBP) which couples a benzophenone-derived photo-crosslinker to a hexahistidine affinity tag. Exposure to UV light covalently couples the 6HisBP tag to whatever protein molecules are nearby. At the microscope, TPE confines the photo-tag crosslinking to a single-micron-scale volume at the focus of the microscope objective. Using this precision TPE photo-tagging, we can selectively tag volumes of interest associated with microscopic pathological features. Photo-tagged proteins can subsequently be recovered from the tissue (after homogenization and solubilization) with affinity chromatography; proteins can be identified using liquid chromatography and tandem mass spectrometry (LC/MS/MS proteomic analysis). With this method (which we call spatially targeted optical microproteomics, or STOMP), we have inventoried the components of cortical plaques in the TgCRND8 mouse model of Alzheimer's disease. Strongly represented are proteins associated with presynaptic vesicle formation, transport, and fusion. Together, these two methods are tools that allow the identification of cells or tissues which are experiencing aberrant protein folding or misfolding and aggregation as part of a disease process; and then subsequently to photo-tag, isolate, and identify specific proteins involved in the disease.
Influence of Selected Diets on Neural Insulin Activity and Cognitive Function
Keywords: aging
Alzheimer's disease
cognition
diet quality
insulin

Diets high in saturated fat are related to worse cognitive function while those high in fish, vegetables and fruit have been associated with better cognitive function and lower dementia risk. While the precise physiological mechanisms underlying these dietary influences are not completely understood, modulation of brain-insulin activity and neuroinflammation were speculated to contribute. The results of this thesis suggest that the associations of fish, fruit, vegetables and saturated fat with cognitive function reflect adherence to a broader set of dietary patterns in older adults whose own relationship with cognition may be dependent on individual differences in environmental conditions, innate metabolism, and/or genetics. Although markers of brain insulin signaling were related to optimal cognitive function in rodent studies, diet-induced modulation of the hippocampal insulin signaling pathway was, at best, indirect. Diet-induced, peripheral insulin resistance and metabolic dysfunction were closely related to cognitive deficits.
Using Lanthanide Nanoparticles as Isotopic Tags for Biomarker Detection by Mass Cytometry
Keywords: Biochemistry
Biomarker
Cancer
Chemistry
Mass Cytometry
Nanoparticles

The development of robust, versatile, and high-throughput biosensing techniques has widespread implications for early disease detection and accurate diagnosis. An innovative technology, mass cytometry, has been developed to use isotopically-labelled antibodies to simultaneously study multiple parameters of single cells. The current detection sensitivity of mass cytometry is limited by the number of copies of a given isotope that can be attached to a given antibody. This thesis describes research on the synthesis, characterization, and bioconjugation of a new class of nanoparticle-based labelling agents to be employed for the detection of low-abundance biomarkers by mass cytometry. Hydrophobic lanthanide nanoparticles (Ln NPs) have been prepared by the Winnik group. To render the NPs water-soluble for biological applications, we coated the NP surface with a first generation of multidentate poly(ethylene glycol) (PEG)-based ligands via ligand exchange. We measured the size, morphology, and polydispersity of these hydrophilic NPs by transmission electron microscopy (TEM) and dynamic light scattering (DLS). The colloidal stability of the NPs was determined at various pH and in phosphate buffered saline (PBS) solutions. Tetradentate-PEG-coated NPs (Tetra-NPs) exhibited the best stability at pH 3 to 9, and in PBS. However, when cells were treated with Tetra-NPs in preliminary in vitro studies, significant undesirable non-specific binding (NSB) was observed. In order to tackle the NSB issue presented in the Tetra-NPs, we prepared a second generation of polymer-based ligands using ring-opening metathesis polymerization (ROMP). A small library of ROMP polymers was synthesized, characterized, and used to stabilize NPs in aqueous solutions. The ROMP-NPs were found to have significantly reduced NSB to cells by inductively coupled plasma-mass spectrometry (ICP-MS). To further modify the NPs, amine groups were introduced as functional handles to both the tetradentate-PEG and ROMP polymer ligands. These amine groups on the NP surface were used to conjugate to the antibodies via maleimide-thiol chemistry. The antigen-recognizing abilities of the antibody-NP conjugates were assessed using two cell lines (CD34-positive KG1a and CD34-negative HL60 cells) by ICP-MS and mass cytometry. It is hoped that the lessons learned from these studies will ultimately support the development of a new biosensing technique for early disease detection..
Structural Dynamic Modeling, Dynamic Stiffness, and Active Vibration Control of Parallel Kinematic Mechanisms with Flexible Linkages
Keywords: Active Vibration Control
CNC Machine Tool
meso-Milling
Parallel Kinematic Mechanisms
Piezoelectric Actuators
Structural Dynamic

This thesis is concerned with modeling of structural dynamics, dynamic stiffness, and active control of unwanted vibrations in Parallel Kinematic Mechanisms (PKMs) as a result of flexibility of the PKM linkages. Using energy-based approaches, the structural dynamics of the PKMs with flexible links is derived. Subsequently, a new set of admissible shape functions is proposed for the flexible links that incorporate the dynamic effects of the adjacent structural components. The resulting mode frequencies obtained from the proposed shape functions are compared with the resonance frequencies of the entire PKM obtained via Finite Element (FE) analysis for a set of moving platform/payload masses. Next, an FE-based methodology is presented for the estimation of the configuration-dependent dynamic stiffness of the redundant 6-dof PKMs utilized as 5-axis CNC machine tools at the Tool Center Point (TCP). The proposed FE model is validated via experimental modal tests conducted on two PKM-based meso-Milling Machine Tool (mMT) prototypes built in the CIMLab.For active vibration control of the PKM linkages, a set of PZT transducers are designed, and bonded to the flexible linkage of the PKM to form a "smart link". An electromechanical model is developed that takes into account the effects of the added mass and stiffness of the PZT transducers to those of the PKM links. The electromechanical model is subsequently utilized in a controllability analysis where it is shown that the desired controllability of PKMs can be simply achieved by adjusting the mass of the moving platform. Finally, a new vibration controller based on a modified Integral Resonant Control (IRC) scheme is designed and synthesized with the "smart link" model. Knowing that the structural dynamics of the PKM link undergoes configuration-dependent variations within the workspace, the controller must be robust with respect to the plant uncertainties. To this end, the modified IRC approach is shown via a Quantitative Feedback Theory (QFT) methodology to have improved robustness against plant variations while maintaining its vibration attenuation capability. Using LabVIEW Real-Time module, the active vibration control system is experimentally implemented on the smart link of the PKM to verify the proposed vibration control methodology.
Violin Pedagogy and the Physics of the Bowed String
Keywords: flesch
galamian
pedagogy
physics
string
violin

The paper describes the mechanics of violin tone production using non-specialist language, in order to present a scientific understanding of tone production accessible to a broad readership. As well as offering an objective understanding of tone production, this model provides a powerful tool for analyzing the technique of string playing.The interaction between the bow and the string is quite complex. Literature reviewed for this study reveals that scientific investigations have provided important insights into the mechanics of string playing, offering explanations for factors which both contribute to and limit the range of tone colours and dynamics that stringed instruments can produce. Also examined in the literature review are significant works of twentieth century violin pedagogy exploring tone production on the violin, based on the practical experience of generations of teachers and performers.Hermann von Helmholtz described the stick-slip cycle which drives the string in 1863, which replaced earlier ideas about the vibration of violin strings. Later, scientists such as John Schelleng and Lothar Cremer were able to demonstrate how the mechanics of the bow-string interaction can create different tone colours. Recent research by Anders Askenfelt, Knut Guettler, and Erwin Schoonderwaldt have continued to refine earlier research in this area.The writings of Lucien Capet, Leopold Auer, Carl Flesch, Paul Rolland, Kat贸 Havas, Ivan Galamian, and Simon Fischer are examined and analyzed. Each author describes a different approach to tone production on the violin, representing a different understanding of the underlying mechanism. Analyzing these writings within the context of a scientific understanding of tone production makes it possible to compare these approaches more consistently, and to synthesize different concepts drawn from the diverse sources evaluated.
A Fermi Gas Microscope Apparatus
Keywords: Cold atoms
Condensed matter
Quantum mechanics

This thesis reports on the design, construction, and performance of a new ultracold atoms apparatus with the capability of resolving individual fermionic potassium atoms trapped in an optical lattice for the purpose of investigating locally ordered quantum states. Our apparatus incorporates a high numerical aperture imaging objective to imge the fluorescence from the 405nm excited state transition while atoms are simultaneously cooled on the 770nm transition.
Early Fault Detection and Optimal Maintenance Control for Partially Observable Systems Subject to Vibration Monitoring
Keywords: condition-based maintenance
EM algorithm
hidden semi-Markov model
multivariate Bayesian control
Partially observable system
Vibration Monitoring

Due to the advancements in data measurement and computer technology, automated data collection from multiple sensors has become common in recent years. However, very few published papers have dealt with the cost-optimal early fault detection of gearboxes, condition based maintenance policy, and remaining useful life prediction when multiple sensors are used for data collection under both fixed load and varying load.This research has focused on several new developments. An early fault detection scheme has been firstly developed using real multivariate vibration data under varying load. A multivariate Hotelling's T-squared control chart has been applied to detect the early fault occurrence of a gearbox. Furthermore, to investigate maintenance policies triggered by the early fault detection, we have considered the combination of continuous time hidden Markov modeling (HMM) and the optimal Bayesian control technique using vector time series model residuals. Model parameters have been obtained using the Expectation-Maximization (EM) algorithm. An optimal Bayesian maintenance policy represented by a Bayesian control chart has been developed by minimizing the long-run expected average cost per unit time. Prediction of mean residual life using a posterior probability has also been developed in this research. For vibration systems without historical failure data, a hidden semi-Markov model (HSMM), has also been developed for maintenance planning. The evolution of the unknown state process has been described by a hidden, two-state semi-Markov process with a generally distributed sojourn time in the healthy state. The model parameter estimation procedure based on the EM algorithm has been developed. The optimal maintenance scheme in a two-state HSMM framework has also been constructed. We have developed this model considering three different state sojourn time distributions using the same set of real helical gearboxes multivariate data: exponential distribution, phase-type Erlang distribution, and Weibull distribution. The numerical results of parameter estimates and optimal control limits have been compared for these three distributions. Lastly, we present the proposed HSMM models to monitor the health condition of a planetary gearbox degradation system using vibration data from multiple sensors.
Erlang-based Methods in Modeling Losses in Insurance and Applications
Keywords: EM algorithm
Erlang-based methods
Multidimensional risk process
Operational risk modeling
Optimal capital allocation
Recursive method

This thesis studies several insurance/loss models and development tools for modeling, quantifying and predicting aggregate losses and/or evaluating ruin probabilities and related risk measures.The thesis can be structurally viewed as tackling problems in two different inter-connected areas. The first area deals with the aggregate loss modeling problems that occur in non-life insurance or operational risk areas. We first propose a modified expectation-maximization algorithm to fit incomplete (truncated and/or censored) loss data. Furthermore we propose a multivariate frequency model with a direct application to the estimation of the operational riskencountered by a financial institution. Further modified expectation-maximization algorithms are derived for fitting such a multivariate frequency distribution.In the second part of the thesis we deal with multidimensional risk modeling from a ruin theoretical viewpoint. More specifically, we are interested in determining certain risk measures and optimal capital allocations for insurance companies that manage multiple dependent lines of business.