VictorJuiz/thesis huggingface dataset:
Investigating Distribution of Talk During Day-Long Naturalistic Recordings in English- and Spanish-Speaking Children
Keywords: language learning
language processing
distribution of talk
Thesis

Children vary substantially in their rates of language growth (Fenson et al., 2007). Numerous studies in Western societies have shown that at least some of this variation is attributable to the overall amount of talk that children hear. Caregivers who verbally engage more with their children have children who demonstrate stronger later language skills (Hart & Risley, 1995; Weisleder & Fernald, 2013). However, studies conducted with children living in non-Western societies (e.g.,Casillas et al., 2019) have questioned the universal nature of this relation, showing normative language development even when children hear very little talk. This suggests that features of the language environments that extend beyond the overall amount of talk are also relevant for learning. This study directly contrasts mean overall talk (i.e., Adult Word Count, AWC) with two new measures that sought to capture variation in the moment-to-moment distribution of talk across the day: (1) consistency (i.e., degree of difference between higher and lower periods of talk) and (2) density (i.e., number of consecutive periods of dense talk). Participants were children in English- (n=56) and Spanish-speaking (n=49) families with 18-24-month-old children. Caregiver talk was estimated using day-long naturalistic audio recordings in the home using LENA technology (Xu et al., 2009). Outcome measures were real-time language processing and vocabulary size. Results revealed striking variability among families in all three measures of talk. Children in English-speaking families who experienced higher overall AWC and more consistent talk were more efficient in real-time language processing. However, AWC was the only unique predictor. Surprisingly, in the Spanish-speaking families, no links were observed to vocabulary. However, the number of dense periods of talk predicted later processing skills in Spanish-speaking families. Similar results were obtained after filtering the audio recordings for likely periods of child-directed speech. Future analyses should continue to explore measures of consistency and density by listening to all-day recordings.
Investigating fracture network creation during hydraulic stimulation in enhanced geothermal systems
Keywords: Energy Resources Engineering.

During hydraulic stimulation treatment in an enhanced geothermal (EGS) reservoir, it has been suggested that a complex fracture network including both preexisting natural fractures and newly formed fractures is created. In this stimulation mechanism, a fracture propagating from a preexisting natural fracture and the interaction of newly formed fractures and preexisting natural fractures play an important role in the creation of a fracture network. Analyzing the interaction between preexisting fractures and newly formed fractures during hydraulic stimulation is thus necessary to understand the creation of a fracture network. We approached to this research question with laboratory and numerical experiments for an EGS reservoir where large preexisting fractures dominate. Laboratory scale hydraulic fracturing experiments were conducted to investigate how a fracture network is created when a propagating hydraulic fracture and a preexisting fracture interact. The physics-based numerical model developed in this work was used to investigate fracture network creation from a small scale area including a small number of fractures to a reservoir scale with tens of fractures. We analyzed the geological factors that affect the fracture network patterns through the laboratory and numerical experiments. We observed that the stress state and preexisting fracture orientation affect the fracture propagation pattern in the laboratory experiments. The numerical analysis shows that the stress field induced by an upstream hydraulic fracture causes asymmetric distributions of normal and shear stresses along the preexisting fracture when they intersect, which resulted in initiation of a wing crack from the fracture tip on the side with larger angles. The numerical results also showed that the complexity of the created fracture network is affected by the fracture intersection angle, stress state, and injection rates. We reviewed past EGS projects and analyzed the stimulation mechanism during their hydraulic stimulation treatment. This study implies that stimulating a reservoir with poorly oriented preexisting fractures may result a complex and broad shaped fracture network, which would be beneficial for energy recovery
Investigating the use of NMR to estimate hydraulic conductivity in near-surface materials
Keywords: Geophysics.

Nuclear magnetic resonance (NMR) is a useful tool for characterizing groundwater resources. NMR measures the total amount of water and gives an estimate of the pore size in water containing geological materials. In the last several decades, NMR has been used more often to characterize groundwater resources, but most of these methods are based on relationships developed by the petroleum industry. This thesis studies how NMR can be used to estimate how easily water flows through porous materials. At the field scale, this thesis investigates how NMR can estimate the hydraulic conductivity (K). At the lab scale, this thesis investigates the use of NMR to study fluid flow at the pore scale. At the field scale, borehole NMR logging data was collected at two sites in a glacial aquifer in Wisconsin to investigate how well NMR data can estimate K. This study established NMR as a method for estimating K in a glacial aquifer in Wisconsin. Estimating K with NMR requires empirical calibration to estimate K accurately. How well other NMR calibrations and methods for estimating K is determined, and an optimal calibration is presented. At the laboratory scale, different NMR experiments are used to study how easily water flows through a porous material. Computational simulations are used to interpret the laboratory NMR data. The work done in this study demonstrates that certain NMR experiments can estimate parameters related to fluid flow useful for groundwater management. The research presented in this thesis focused on how to best estimate K with NMR, and how to characterize fluid flow at the pore scale. The research done investigating how well NMR estimates K at the field scale will improve how K is estimated with NMR in the future. This thesis also shows that different NMR experiments at the laboratory scale can estimate parameters relevant for groundwater management. This thesis demonstrates that NMR is a valuable tool for characterizing groundwater resources in the near surface.
Investigation of cell-cycle entry and DNA replication termination using single-cell microscopy
Keywords: Chemical and Systems Biology.

The cell cycle is a highly orchestrated series of cellular events that results in the duplication of DNA and division into two daughter cells. As a critical process during tissue development and homeostasis, the cell cycle is tightly regulated at the cellular, tissue, and organismal levels. In this thesis, we study two cellular processes that are key to cell-cycle regulation: the decision to enter the cell cycle in response to extracellular signals, and the multi-step process that replicates DNA. In the first study, we find that the decision of a newborn cell to proliferate or become quiescent is controlled by the memory of local cell density that is inherited from its mother cell. This memory regulates the expression of the cell-cycle activator cyclin D1 and inhibitor p27. Cyclin D1 and p27 form an activator-inhibitor balance in newborn cells that regulates the proliferation-quiescence decision in a sharp, ultrasensitive manner. We further show that competing cell density and mitogen signals are funneled into the cyclin D1-p27 balance through ERK signaling. We propose that memory of cell density, coupled to tight regulation of proliferation by the activator- inhibitor balance, may contribute to robust control of cell density and tissue homeostasis. In the second study, we demonstrate that replisome disassembly, a final step during DNA replication that is generally thought to be functionally downstream of nascent DNA synthesis, is continuously required for efficient DNA synthesis. Failure to disassemble replisomes traps essential replisome components on chromatin, which prevents their recycling into the soluble pool and blocks replication initiation. Cells with defects in replisome disassembly experience slow and incomplete DNA replication, G2/M checkpoint activation, and cell-cycle arrest. We also show that LRR1, which encodes a key component of the E3 ligase CRL2-LRR1 that initiates replisome disassembly, is an essential gene in actively dividing human cells. Thus we propose that inhibiting CRL2-LRR1 activity may be a potential target for cancer therapy, which acts by blocking the recycling of key replication factors that are in high demand in cancer cells due to the higher replicative activity in many cancers
Investigation of condensed matter systems with resonant inelastic X-ray scattering
Keywords: Physics.

One of the key ideas in the condensed matter physics at a low energy scale is to treat an interacting many-body electron system in terms of weakly interacting emergent particles, namely elementary excitations. Resonant inelastic X-ray scattering (RIXS) has emerged as a powerful tool to study elementary excitations, thanks to the exciting instrumentation improvement and the advent of X-ray synchrotron radiation facilities. By tuning the incident X-ray photon energy to the resonance condition of a specific element, RIXS can resonantly enhance the scattering cross section between the incident photon and the elementary excitation in the material, enabling element-specific measurements. In this dissertation, we investigated magnetic excitations in the recently discovered superconducting infinite-layer nickelate thin films. Besides a similar crystal structure, the infinite-layer nickelate is nominally isoelectronic to the high temperature cuprate superconductors. At this early stage, it is important to experimentally study the similarities and differences between cuprates and nickelates, particularly the respective electronic and magnetic structures. Here, by utilizing the high-resolution RIXS, we found that the parent compound of the infinite-layer nickelate is not a charge-transfer material, like cuprates. Instead, it is probably closer to a Mott compound with an additional coupling with rare-earth metallic states. Furthermore, we also found a branch of dispersive magnetic excitations with a bandwidth of approximately 200 meV in the parent compound nickelates. Although these modes are significantly damped, they are reminiscent of the spin-wave of strongly coupled, anti-ferromagnetically aligned spins on a square lattice. Upon doping, the spectral weight and energy decrease slightly, while the modes become overdamped. The dispersion, doping dependence, damping effect of the magnetic excitation, and the added complexity due to the presence of the rare-earth metallic pockets, together with its comparison with the magnetic excitation in cuprates, will be discussed
Investigations in emissions-constrained, integrated gas-electric energy systems
Keywords: Energy Resources Engineering.

To mitigate risk of climate disaster, net atmospheric release of greenhouse gases (GHGs) from energy systems must decline to zero by mid-century. Electricity and natural gas are the most widely used end-use energy carriers in existing infrastructure systems that serve hundreds of millions of consumers in the United States and billions globally. Electricity and natural gas suppliers are also subject to unique regulatory oversight given their status as a public utility. While the electric power system has a reasonably clear path towards net-zero emissions, the natural gas system lacks a diverse set of low-carbon supply options. As energy utilities implement climate change mitigation policies, system planners require strategies for achieving affordable emissions reductions. Coordinated planning of electric power and natural gas delivery systems will allow synergistic investment plans to address cross-sector operational constraints, competing uses for net-zero emissions fuels, and shifts in final energy demands across energy carriers. The industrial sector accounts for a large share of natural gas demands and nearly a quarter of global greenhouse gas emissions. These energy demands can be difficult to transition to electric-powered alternatives. Methane pyrolysis could be used to produce low-carbon hydrogen for industrial processes while generating a solid carbon product that can be permanently sequestered or sold as a manufacturing feedstock. Accurate quantification and attribution of GHG emissions liabilities is essential for climate policy but challenging in the case of energy transfers across regulatory jurisdictions. Regulating emissions associated with delivered electricity is further complicated by contractual arrangements for dynamic electricity transfer that confound emissions accounting approaches rooted in the physics of grid operations. As such, the transition to net-zero emissions natural gas and electric power systems must accommodate three parallel trends: increasing integration across gas and electric energy systems, the challenge of difficult-to-decarbonize industrial energy demands, and the regulatory and accounting structures which track and assess their emissions liabilities or promote the development of low-carbon resources. Here, we present new modeling frameworks that help elucidate features of cost-effective transitions to deeply-decarbonized, integrated gas-electric energy systems. We develop and implement three model formulations that enable design and simulation of low-carbon energy systems, providing insight for the policy and economic decisions that will shape the transition
Investigations of carbon-based materials for electrocatalytic carbon dioxide reduction
Keywords: Chemical Engineering.

There is an urgent need for renewable and sustainable technologies to help abate the consequences of climate change originating from anthropogenic CO2 emissions. Electrochemical CO2 reduction (CO2R) can covert CO2 to useful chemicals like carbon monoxide (CO) or ethanol under ambient conditions and could be a route towards storing renewable electricity and producing carbon-based consumer products. CO2R kinetics are tied to the structure of the catalytic active site and the surrounding chemical environment but precisely describing this interface is challenging which is an impediment for future industrial applications of CO2R. This dissertation describes efforts to determine the effect of carbon-based materials on CO2R rates in two areas: 1) Ni, N co-doped carbon electrocatalysts (Ni-N-C), and 2) Imidazolium-ionomer coatings on Ag. Ni-N-C materials have been shown to have high selectivity for CO but knowledge of the catalytic active site is limited. In this dissertation, the origin of this activity was investigated by a wide variety of techniques including kinetic testing and physiochemical characterization (electron microscopy (STEM), X-ray absorption spectroscopy (XAS), secondary ion mass spectrometry (SIMS), electron energy loss spectroscopy (EELS), X-ray diffraction (XRD), and 61-Ni Mossbauer spectroscopy). By combining insights from these diverse methods, atomically dispersed, nitrogen-coordinated sites in a distorted square planar geometry were identified as likely CO2R active sites. As these sites are expected to be both thermally and electrochemically stable, the activity of Ni-N-C was extended beyond electrochemical catalysis by demonstrating that the same Ni-N-C catalyst could also selectively facilitate thermal CO2 to CO conversion. This study provides a framework for studying the same active site under very different reaction conditions and driving forces and suggested that the electrochemical environment plays a strong role in reducing transition state barriers relative to the thermal gas-phase environment. Similarly, the effect of ionomers on the intrinsic reaction rates of CO2R catalysts has been hypothesized but rarely quantitatively studied. Here, a series of imidazolium-containing ionomers with different substituents were synthesized and coated on silver foil revealing that imidazolium-ionomers promoted hydrogen evolution and left CO2R rates unchanged. This effect was found to originate from enhanced bicarbonate reduction rates which was dependent on the steric bulk of the imidazolium substituent. This dissertation demonstrates the power of multimodal characterization and kinetic modeling towards identifying atomistic information about CO2R electrocatalytic interfaces. Further work in this area is necessary to expand our understanding of CO2 reduction which can guide materials design efforts to achieve optimized catalytic activity
Is It Language or Is It Culture? Re-examining Cross-Cultural Similarity Judgments Using Lexical Co-Occurrence
Keywords:  Symbolic Systems Program
similarity
culture
language
semantics
lexical co-occurrence
variation
Symbolic Systems Program
Language and Cognition Lab
Thesis

Is “cow” more closely related to “grass” or “chicken”? Speakers of different languages judge similarity in this context differently, but why? One possibility is that cultures co-varying with these languages induce variation in conceptualizations of similarity. Specifically, East Asian cultures may promote reasoning about thematic similarity, by which cow and grass are more related whereas Western cultures may bias similarity judgments toward taxonomic relations, like cow-chicken. This difference in notions of similarity is the consensus interpretation for cross-cultural variation in this paradigm. We consider, and provide evidence for, an alternative possibility, by which notions of similarity are equivalent across contexts, but the statistics of the environment vary. On this account, similarity judgments are guided by co-occurrence in experience, and observing or hearing about cows and grass or cows and chickens more often could induce preferences for the relevant grouping and account for apparent differences in notions of similarity across contexts.
Is less always more? What PISA 2015 can actually tell us about inquiry-based science teaching practices
Keywords: Education.

International large-scale assessments, including the International Program for Student Assessment (PISA), influence both educational policy and practice. Studies based on results from the 2015 survey described a negative relationship the frequency of inquiry-based science instruction and student scientific literacy scores. Based on this correlation, PISA's parent organization, the Organisation for Economic Co-operation and Development (OECD), recommended that inquiry-based instructional practices be approached with caution. PISA's recommendation conflicts with numerous classroom-based studies, which have found that inquiry-based instruction improves student learning. Furthermore, due to PISA's influence, articles for science teachers claiming that inquiry-based instruction is ineffective now cite PISA results as supporting evidence. This dissertation uses data from PISA 2015 and student interviews to better understand the nature of this relationship. By closely examining the assumptions inherent in the primary analysis of PISA 2015 data using both quantitative and qualitative methodologies, this set of studies challenges PISA's claim about inquiry-based instructional practices. The analyses indicate at least four areas in which threats to validity warrant wariness about the PISA recommendation that inquiry-based practice may not be effective. First, analyses should account for the multidimensionality of the PISA enquiry-driven instruction index. Second, linear models may not accurately describe the relationship between student-reported frequencies of inquiry-based instruction and scientific literacy scores, so other models should be explored. Third, measurement invariance for students from different SES quartiles suggests that either the items or the efficacy of inquiry-based instruction vary for students from different groups and a more nuanced perspective is needed before developing recommendations. Finally, student interpretations of the items and response space require more study if we are to use the questionnaire responses to describe the activities students have in mind and their frequencies. Together, these findings suggest that the OCED recommendations about science instructional practices should be reconsidered. Alternative interpretive models and recommendations for practice are discussed
Is this Actual Self-Actualization? Edtech’s Push to Move Beyond Traditional Measurement Pitfalls When Assessing Non-Cognitive Skills in Online Environments
Keywords: edtech
non-cognitive skills
measurement
accountability
technologists
founders
self-efficacy
Graduate School of Education
Thesis

The increased technologization of education and the increased emphasis placed on developing and assessing non-cognitive skills has led to a need for measurement of non-cognitive skills in online environments. Questions remain about the possible benefits of these measurements, as well as the challenges to their adoption. This thesis takes a qualitative outlook, and investigates these questions from the perspectives of the people who build such education technology (edtech). I interviewed 10 technologists, including founders, CEOs, and software engineers, who are building these tools, to understand the impacts they want their tools to have, and the factors that stand in their way. In the technical realm, they identified three main perceived technical benefits: the ability to utilize more valid data sources, the ability to measure more frequently, and the ability to experiment. They also described one main contextual desire, the hope that the ability to measure would increase overall emphasis on non-cognitive skills. The technical barriers were twofold: that the technologies had difficulties extrapolating from context to context; and that technology was often the wrong solution for a problem. However, while these technical barriers were surmountable, contextual ones were harder to overcome. This is due to a Catch-22: increased emphasis on non-cognitive skills is hard to drive without accountability measures to incentivize it, and accountability measures often come with the types of high-stakes testing that are antithetical to many non-cognitive skills. Because of that, some founders are forced to use the effects that non-cognitive skills can have on cognitive skills as the basis for their adoption, rather than non-cognitive skills’ standalone value. These findings suggest that policy and contextual education factors, not just technical capabilities, must be a focus in research on edtech tools measuring and developing non-cognitive skills.