VictorJuiz/thesis huggingface dataset:
The Intersection of Renewable Energy Finance and Governance: Solutions to the Multi-trillion Dollar Challenges
Keywords: Climate change
Finance
GCC
Renewable energy

The International Finance Corporation (IFC) estimated in 2016 that the 2015 Paris Agreement could drive demand for tens of trillions of dollars of new climate-related investment between 2016 and 2030. Assessments suggest that at least some percentage of these funds will need to be mobilized from private investment sources. Renewable energy, the primary supply-side decarbonization tool, stands poised to capture a significant portion of this number, yet numerous technical, economic, and governance questions loom large in any discussion of renewable energy sector deployment. This thesis focuses on the question of financing all stages of renewables, as well as the ability of finance-linked entities to implement energy governance structures designed to drive a substantial level of renewables integration. We start by presenting case studies on both the United States and the Gulf Cooperation Council (GCC) countries. This study of contrasts is followed by a synthesis of insights on key renewable energy governance challenges from one perspective; specifically, the perspective of individuals with connections to the private finance sector that will be responsible for some of the financial flows for renewables deployment. Derived from extensive time in the field (including unstructured interviews, semi-structured interviews, and ethnographic work), this thesis critically examines the perspectives of leading renewable energy financiers (as well as academics and other knowledgeable market observers from around the world) on how best to improve the financial flows to, and governance of, renewable energy finance. Given the difficulty of offering definitive prescriptions in the inherently idiosyncratic political, economic, social, and environmental context guiding each nation, the thesis starts by offering region-specific prescriptions, followed by general directions. In the final substantial chapter, it draws on a geographically diverse set of key stakeholder interviews to tease out common lessons that can be shared across borders. These lessons include the importance of a carbon tax, the criticality of appropriate policy structure and market design, the urgency of pursuing low-cost options (such as applied research), and the need for encouraging new capital sources into the space. Further research on the role of private sector and public sector capital in the renewable energy space is encouraged.
1H NMR-Based Metabolomics of Daphnia magna Sub-lethal Exposure to Organic Contaminants in the Absence and Presence of Dissolved Organic Matter
Keywords: Daphnia magna
Metabolomics
NMR spectroscopy
Organic contaminants

Ecotoxicity tests which monitor observable endpoints such as mortality, growth and reproduction do not assess the molecular mode of action of contaminants in target organisms. Also, aquatic toxicity tests often do not include dissolved organic matter (DOM), which is ubiquitously found in natural waters. Hydrophobic organic contaminants sorb to DOM which may alter the bioavailability and toxicity of these contaminants. To assess this hypothesis, proton (1H) nuclear magnetic resonance (NMR)-based metabolomics was used to analyze the metabolome of Daphnia magna after acute sub-lethal exposure to organic contaminants in the absence or presence of DOM. Triclosan, carbamazepine and ibuprofen exposure resulted in different metabolic responses in D. magna. DOM at 5 mg dissolved organic carbon/L (DOC/L) did not change the D. magna metabolome from carbamazepine, imidacloprid or tris(2-chloroethyl) phosphate exposure, perhaps because these weakly hydrophobic contaminants do not sorb to DOM. The metabolic response of D. magna from 17α-ethynylestradiol (EE2) exposure was suppressed by 1, 2, 3, 4 and 5 mg DOC/L, likely from decreased EE2 bioavailability with DOM. The metabolic response in D. magna from perfluorooctane sulfonate (PFOS) exposure was not altered with 1 mg DOC/L. However, PFOS exposure with 2, 3, 4 and 5 mg DOC/L resulted in a unique metabolic response in D. magna, which may be due to enhanced PFOS bioavailability or combined action of PFOS and DOM on the metabolome. The metabolic response of D. magna from tris(2-butoxyethyl) phosphate (TBOEP) exposure was unaltered with 5 mg DOC/L, perhaps from the high potency of TBOEP. D. magna exposure to triphenyl phosphate (TPhP) with 5 mg DOC/L resulted in a unique metabolic response compared to TPhP exposure, possibly from combined stress of TPhP and DOM on the metabolome or altered TPhP bioavailability. The mode of action of mixtures of the hydrophobic contaminants triclosan, TPhP and diazinon in D. magna was not altered by 1 and 5 mg DOC/L. Overall, DOM may enhance or suppress the metabolic perturbations in aquatic organisms that originate from sub-lethal exposure to organic contaminants. Therefore, DOM should be included when evaluating molecular-level responses from sub-lethal ecotoxicity tests and during risk assessment of environmental mixtures.
Chemistry in Action: Making Molecular Movies with Ultrafast Electron Diffraction and Data Science
Keywords: Crystallography
Data science
Femtochemistry
Spin crossover
Structural dynamics
Ultrafast electron diffraction

A long-held thought experiment of science is the direct observation of the motions of atoms and molecules as they undergo chemical reactions and phase transitions. The advent of microscopy and diffraction beyond the visible spectrum of light ⁠— using X-rays, electrons, and neutrons ⁠— has since enabled such atomic-level elucidation of the structure of matter in the steady state. Recently, time-resolved techniques have finally enabled the making of the titular `molecular movie' on the time scale of chemical physics. In this thesis, I report on my works which further this quest by using ultrafast electron diffraction and data science to fully resolve the photoinduced structural dynamics of five large, low-symmetry, and weakly scattering molecular systems: two Bechgaard-Fabre salts of 4,5-ethylenedioxy-tetrathiafulvalene, a ring-closing diarylethene derivative, and two iron(II)-based spin-crossover complexes. Leveraging the ultrabright femtosecond electron source presently available, large overdetermining time-series maps of reciprocal space were measured and structurally refined to track the individual atomic motions that lead to each photoproduct: two transient metallic phases, a ring-closed isomer, and two expanded high-spin states. In all cases, a dramatic and heretofore unknown reduction in dimensionality was found, whereby the photoinduced structural dynamics is governed by key reaction modes that are much fewer in number than the degrees of freedom expected of the respective molecular systems. This insight — along with the experiments and methods presented herein — should find application in uncovering the physics of reduced dimensionality as a solution to the problem of how chemistry scales with complexity.This work lays the foundation to recast chemistry in terms of reduced reaction modes, unifying structure and dynamics as a new conceptual basis for chemistry.
The Ecological Validity of Traditional Pen-and-paper, Ecologically Oriented, and Virtual Reality Neuropsychological Test Measures to Cognitive Impairment and Real-World Function after Mild Traumatic Brain Injury
Keywords: assessment
ecological validity
mild traumatic brain injury
neuropsychology
return to work
virtual reality

A growing concern in neuropsychology is whether neuropsychological test measures (NTMs) can predict functional outcome (i.e., ecological validity). Ecological validity can be understood in two ways: veridicality (i.e., prediction of functional outcome is independent of how the test reflects the outcome being measured) and verisimilitude (i.e., tests resemble the functional outcome they are predicting). Historically, the veridicality approach has been utilized (i.e., by way of traditional, pen-and-paper NTMs), but there has been a movement to employ verisimilitude approaches (e.g., Behavioural Assessment for Dysexecutive Syndrome; BADS). These approaches were examined in patients experiencing ongoing cognitive complaints in the post-acute period of recovery (> 3 months) following a mild traumatic brain injury (mTBI). This was the principal inclusion criteria for the studies described here. A meta-analytic study was conducted and found that traditional NTMs were not sensitive to persistent cognitive complaints in this population across all domains. Studies 2 and 3 utilized archival data to determine whether NTMs could predict return to work (RTW) status. The BADS predicted employment status by way of medium-to-large effects, while traditional NTMs did not. Overall, these findings suggest the verisimilitude approach is more ecologically valid than the veridicality approach. As such, two virtual reality tests (VRTs) evaluating attention and executive function were developed to investigate their ability to predict RTW. Tests of attention (VR and traditional tests) significantly predicted group membership at 82% accuracy, with 82.6% sensitivity and 81.5% specificity. The attention shift trial of the VRT and to a lesser degree the total speed score of the Ruff 2 7 were predictive of employment status. Overall, this research provides empirical evidence for the verisimilitude approach when evaluating RTW status in patients who are in the post-acute period of recovery following mTBI. Moreover, it provides initial evidence for the clinical utility of VRTs to evaluate real-world functioning.
Low-frequency Piezoelectric Energy Harvesting
Keywords: battery-free electronics
energy conversion
low-frequency
piezoelectric energy harvesting
self-powered sensing system
vibration

In this work, a novel approach to reduce the resonant frequency of current piezoelectric energy harvesters is proposed to harness energy from low-frequency vibrations. The approach is to embed revolute joint mechanism(s) into the structure of harvesters. This approach is applied onto two typical configurations. The modeling, simulation and experimental results demonstrate that joints can effectively lower linear stiffness of the structures and further decrease the resonant frequencies of the harvesters. Besides, additional advantageous influences are found in widened operating bandwidth and higher voltage outputs. The voltage output enhancement results in a power output with matched impedance 440% or 730% as high as those of the two counterpart cases. As the joint mechanism embedment does not lead to increase in volume or mass of the harvesters, the power density is enhanced by the same magnitude. Also a truss-based compressive-mode piezoelectric energy harvester is proposed for ultra-low-frequency vibrations. Several techniques are employed: separated piezoelectric transduction element from the mechanically-excited system so that the resonant frequency is designed to be ultra-low; the truss mechanism for force amplification; an amplitude limiter causing impacts between the mass and limiter for frequency up conversion. Experimental results indicate that an open-circuit voltage reaches 83.3 V and a peak-peak power of 32 mW is generated with matched impedance. The harvester also demonstrates excellent charging performance to capacitors with a rapid charging rate and high saturation voltages. The harvester is able to charge a 47μF capacitor to over 2V in 50s, which powered a thermometer for 10s. Also two hybridization schemes with triboelectric and electromagnetic transductions are proposed. Both schemes demonstrate output power improvement. In the latter scheme, the harvester can generate a 1/3W peak power under excitation of 0.7g at resonance. A self-powered sensing system and a battery-free systems were developed so that not only can the sensor and electronic device be powered real-time, but also when excitation stops, residual charges can power them for a 20.38 and 8.33 minutes, respectively. This work can be greatly significant for high-performance energy harvesting and for development of self-power sensing and battery-free electronic systems.
Working Together: Indigenous Knowledges, Urban Youth, and Mental Health for Career Development
Keywords: Employment solutions
Indigenous
Indigenous youth
Mental Health
Traditional Knowledges

Indigenous people in Canada have endured and survived many traumas as a result of the legacy of colonization, which have negatively impacted their social determinants of health. Employment, especially for Indigenous youth, has been identified as an area in need of urgent attention. Despite the fact that Indigenous youth are the fast growing population in Canada, they continue to be underemployed despite programs that were designed to increase Indigenous youth employment rates. This study explores the intersections of employment policies and practices, traditional and cultural knowledges, and mental health by interviewing ten Indigenous key community informants and five Indigenous Elders/Traditional Knowledge keepers in the Greater Toronto Area. The results revealed that decolonizing and Indigenizing current employment policies and practices and is integral to supporting Indigenous youth employment. The results of this study highlight the importance of modifying services so that they emphasize the strengths of Indigenous knowledges and cultures to promote healing and mental wellness. Implications were identified that policies, practices, and vocational psychology models can be enhanced in their application with Indigenous youth by integrating Indigenous worldviews related to health and wellness to promote healing from trauma and mental health.
Association of Obesity with Breast Cancer
Keywords: Breast Cancer
Circulating Tumor Cells
Inflammation
Meta-analysis
Obesity
Outcome

In a literature-based meta-analysis, we reported on the association of obesity at breast cancer (BC) diagnosis with disease-free (DFS) and overall survival (OS) in BC subtypes. We included 26 studies (108,793 patients) and the results showed pooled hazard ratios, HRs, for DFS and OS in obese vs non-obese were worse in all subgroups studied (ER/PgR+ve and HER2-ve; HER2+ve and any ER/PgR; and triple negative, TN), with larger prognostic effects in the ER/PgR and HER2-ve subtype. HRs for OS (but not DFS) were somewhat higher in observational vs interventional studies in ER/PgR+ve/HER2-ve and HER2+ve/ any ER/PgR but not in TN. This differential effect was statistically significant only in the HER2+ve subgroup and it may reflect the selection of healthier patients for intervention trials; obese patients in these studies may not have the same degree of obese physiology as the broader population. We evaluated the association of BMI, metabolic, inflammatory and tumor markers with CTCs in women with metastatic BC prior to a new systemic therapy. 96 patients with metastatic BC were recruited. ≥5 CTCs/7.5mL was detected in 43.8% of patients and those with liver metastases (vs. not) more frequently had an elevated CTC count. Some inflammatory markers were significantly associated with PAI-1, IL6, IL8, hs-CRP. CEA and CA15-3 were significantly higher in the CTC high (≥5 CTCs/7.5mL) versus in the CTC low group (
Positron Emission Tomography (PET) of Breast Cancer Heterogeneous for HER2 and EGFR using Bispecific Radioimmunoconjugates
Keywords: Bispecific Radioimmunoconjugate
Breast Cancer
Copper-64
Human Epidermal Growth Factor Receptor 2
Molecular Imaging
Positron Emission Tomography

The human epidermal growth factor receptor-2 (HER2) is overexpressed in 15-20% of breast cancer (BC) and is the target for immunotherapy with trastuzumab, pertuzumab, and trastuzumab-emtansine (T-DM1). Despite improvements in survival, resistance to HER2-targeted therapies remains a major problem. One resistance mechanism is loss of HER2 and increased EGFR. Additionally, intratumoral HER2 heterogeneity is correlated with a poor response to trastuzumab. The hypothesis was that novel bispecific radioimmunoconjugates (bsRICs) are capable of permit molecular imaging of both EGFR and HER2 receptors simultaneously with positron emission tomography (PET) and deliver more radioactivity to the tumor especially in the presence of receptor heterogeneity. BsRICs was developed by chemically linking trastuzumab Fab (anti-HER2) to human EGF through a 24-mer polyethylene glycol (PEG24) spacer, and radiolabeled with 64Cu. 64Cu-NOTA-Fab-PEG24-EGF demonstrated the ability to specifically bind to EGFR or HER2 both in vitro and in vivo, and exhibited prolonged blood circulation than monospecific agents in mice. PET imaging was performed on NOD-SCID mice bearing tumor xenografts expressing EGFR, HER2, or both receptors. Tumors were clearly visualized by microPET/CT imaging, and biodistribution studies showed significantly better tumor uptake for bsRICs in tumor xenograft expressing both receptors. Human cancer xenograft mouse models with heterogeneous levels of HER2 and EGFR was established by subcutaneous inoculation of mixtures of SK-OV-3 cells and MDA-MB-468 cells. These BC xenografts were more clearly visualized by microPET/CT, and bsRICs exhibited higher tumor uptake and lower degree of heterogeneous uptake than monospecific agents. These results suggest that bsRICs may be useful for imaging of HER2-positive heterogeneous BC consisting of EGFR-positive subpopulations. Thus, bsRICs will be able to address the challenge of HER2 intratumoral heterogeneity in BC.
A Wearable Computer Vision System for Monitoring Hand Use at Home
Keywords: Community-based rehabilitation
Egocentric vision
Outcome measure
Rehabilitation engineering
Tetraplegia
Upper extremity

Impairments in hand function lead to reduced independence and quality of life after cervical spinal cord injury (SCI). In order to develop effective rehabilitation interventions for individuals with cervical SCI, it is important to assess hand function throughout the rehabilitation process. Currently, the efficacy of new treatments is measured by assessments limited to a controlled setting or based on self-report; there is currently no viable method to collect quantitative information once the patient has returned to the community. This thesis attempts to solve this gap by developing a computer vision-based wearable camera system for monitoring hand use. Our research involved (1) the collection of egocentric video that represents activities of daily living, (2) the development of an algorithm that captures interactions between the hand and objects in the environment, and (3) the evaluation of the system in both laboratory and home settings. Four studies were executed, involving three video datasets (20 able-bodied participants and 17 participants with SCI in a home simulation laboratory, as well as 3 participants with SCI in their home). We introduced the concept of hand-object interaction detection, defined as a binary decision about whether or not the hand is manipulating an object for a functional purpose. The datasets were used in the development and evaluation of an algorithmic pipeline consisting of hand detection and segmentation, followed by hand-object interaction detection. For this step, a random forest classifier was trained on hand motion, hand shape and scene colour features. The frame-by-frame binary output data over time was further analysed to extract three functional hand-use metrics: (1) the amount of total interaction as a percentage of testing time, (2) the average duration of interactions in seconds, and (3) the number of interactions per hour. The final study investigated the views of participants with SCI on the use of wearable cameras. With appropriate strategies determined by input from individuals with SCI, this thesis demonstrates the potential of a wearable egocentric camera as a unique tool to allow researchers and clinicians to gauge the user's level of independence at home in activities involving upper limb function.
Conditional Copula Inference and Efficient Approximate MCMC
Keywords: Approximate Bayesian Computation
Conditional copula
Perturbed MCMC
Simplifying assumption
Single index model
Synthetic Likelihood

This thesis consists of two main parts. The first part focuses on parametric conditional copula models that allow the copula parameters to vary with a set of covariates according to an unknown calibration function. Flexible Bayesian inference for the calibration function of a bivariate conditional copula is introduced. The prior distribution over the set of smooth calibration functions is built using a sparse Gaussian Process prior for the Single Index Model. The estimation of parameters from the marginal distributions and the calibration function is done jointly via Markov Chain Monte Carlo sampling from the full posterior distribution. A new Conditional Cross Validated Pseudo-Marginal criterion is used to perform copula selection and is modified using a permutation-based procedure to assess data support for the simplifying assumption. The first part concludes with methods for establishing data support for the simplifying assumption in a bivariate conditional copula model. After splitting the observed data into training and test sets, the method proposed will use a flexible Bayesian model fit to the training data to define tests based on randomization and standard asymptotic theory. I discuss theoretical justification for the method and implementations in alternative models of interest: Gaussian, Logistic and Quantile regressions. The performance is studied via simulated data. The second part of the thesis focuses on approximate Bayesian methods. Approximate Bayesian Computation (ABC) and Bayesian Synthetic Likelihood (BSL) are popular simulation based methods for sampling from the posterior distribution when the likelihood is not tractable but simulations for each parameter are easily available. However these methods can be computationally inefficient since a large number of pseudo-data simulations is required. I propose to use perturbed MCMC versions of ABC and BSL algorithms and attempt to significantly accelerate these samplers. The main idea of the proposed strategy is to utilize past samples with k-Nearest-Neighbor approach for likelihood approximation. This general method works for ABC and BSL and greatly reduces computational cost and number of required simulations for these samplers. Performance and computational advantage are examined via series of simulation examples. The second part concludes with theoretical justifications and convergence properties of the proposed strategies.