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Collation Model for Oversize Ms. Codex 987: Recognoyssenssas et fieux novels...
Full text linkA collection of notarial documents from the southern edge of the departement of Tarn-et-Garonne, France. The original set all mention Joham de Vernoils (Zacour-Hirsch propose the alternate spelling Jean de Verneuil), and are all written in the same hand with the same notarial signet and date between 1467 and 1472. These were often separated by blank pages into which later documents (through 1567) were copied by other notaries, and these almost all mention the village or family of Pompignan (near the village of Grisolles, also mentioned in the title), which relates them to the original set. A table of names appearing in the documents was added later at the end (f. 91-[92]).https://repository.upenn.edu/sims_models/1083/thumbnail.jp
Brain Metabolic Responses To Alzheimer Pathologies With Molecular Imaging And Machine Learning
No full textAlzheimer Disease (AD) is defined by amyloid (A) and tau (T) pathologies, with T better correlated to neurodegeneration (N) than is A. However, T and N have complex regional relationships in part related to non-AD factors that may influence N. Using machine learning, we assessed heterogeneity in 18F-Flortaucipir vs. 18F-Fluorodeoxyglucose positron emission tomography as markers of T and neuronal hypometabolism (NM) in 289 symptomatic patients from the Alzheimer Disease Neuroimaging Initiative (ADNI) and 115 cognitively normal older adults from the Harvard Aging Brain Study (HABS). Fromboth cohorts, we identified six T/NM clusters with differing limbic and cortical patterns. The canonical group was defined as the T/NM pattern with the lowest regression model residuals, while non-canonical groups reflected either resilience or susceptibility, with either less or greater hypometabolism than expected relative to T. Resilient groups displayed better cognition and less copathology-related factors than the canonical group. Susceptible groups exhibited worse cognitive decline and had imaging and clinical measures consistent with the presence of copathologies, including factors associated with vascular, α-synuclein and TDP-43 pathologies. Mismatch analyses were applied with a loglinear model and compared to a generative adversarial network with dual contrastive learning objectives. We performed theoretical and empirical investigations to optimize this contrastive learning model. Our proof-of-concept experiments demonstrate the advantage of multi-domain contrastive losses, the utility of training set and contrastive sampling diversity and the ability of image-to-image translation models to accurately map between T and NM domains. These findings provide the basis for further biological and statistical inquiries into the translation accuracy and reconstruction error of models that map between types of images in AD. Together, T/NM mismatch in AD reveals distinct imaging signatures with pathobiological and prognostic consequences that may improve clinical trial design, diagnosis and management of patients living with neurodegenerative diseases
Gray Dating: How Age And Gender Impact The Experiences Of Singlehood, Dating, And Partnering For Older Adults
No full textDating and family formation have been prominent topics in family sociology, but research has narrowly focused on younger adults, meaning little is known about how older adults experience and approach these processes. Single older adults are in a different life stage, often having experienced divorce, widowhood, or both, and having more extensive families, but not seeking a partner with whom to have children. Older singles often became single again more recently, meaning they are relatively new to dating. This research investigates how age and gender structure and influence the process of finding a romantic partner in older age. How do older adults navigate finding a partner? How do older adults utilize online dating websites? Is this process different between men and women? This research is based on in-depth interviews with 100 heterosexual older singles, 50 men and 50 women ages 60-83, who have experienced singlehood, dating, and (re)partnering in older age. They vary by gender, race, education, marital history and family structure, location, and other demographics, but all have sought a romantic partner through online dating websites. I find that single older adults have learn how to date and adopt egalitarian dating scripts unevenly. Older singles are also pursing romantic relationships during a pandemic and justifying this decision through loneliness and, particularly for women, planning COVID-safe dates. Lastly, I find carework responsibilities alter one’s desirability on the dating market, with women becoming less desirable and men becoming more desirable because of their ties to family. I argue that the process of finding a romantic partner is unique because of their age, as they weave together modern and traditional behaviors and attitudes, and gender differentiates the experience, with men and women adhering to and rejecting traditional gender roles in unequal measures. This study not only illustrates the impact of age and gender but shifts our conceptualization of dating and marriage market theory and highlights the steadfast and deep desire to find a romantic partner
Etf Primary Market Structure And Its Efficiency
Full text linkThe primary market of many US registered ETFs exhibits an oligopolistic structure, which is shown to have relevant implications for the pricing efficiency of those financial products. I show that the entry of an additional Authorized Participant (AP) corresponds to a decrease in the magnitude of ETF price deviations from Net Asset Value (NAV) of at least one basis point in ETFs with high primary market concentration. I build a dynamic equilibrium model of ETF primary market arbitrage that describes the trade-off faced by monopolistically competitive APs between waiting for mispricing to widen and pre-empting competitors from eliminating it. In the model, the creation unit size is shown to be an important friction driving the entry decision and, therefore, the magnitude of mispricing. Indeed, in the data, around one-third of all primary market transactions amount to one creation unit, suggesting that it is often a binding constraint. ETF split events and the creation unit size changes help to identify shocks to the dollar value of creation unit size empirically. I show that by cutting the creation unit size in half, mispricing decreases by almost two basis points, a magnitude consistent with that implied by my quantitative model
Dynamic Control Of Behavior By Hypothalamic Hunger Neurons
No full textSurvival requires neural circuits regulating behavior to rapidly adapt to an animal’s needs. Energy homeostasis is a basic need that drives feeding behavior. The ability to manipulate access to food in the laboratory allows us to assess how the brain responds to dynamic environmental challenges. The brain must properly gauge energy needs and coordinate behavior to find and consume food. There are three main components to this process that are addressed in this dissertation. First, circuits in the brain that coordinate feeding behavior must be well tuned to both external and internal cues signaling energy need and food availability. Second, when hunger circuits are active and food is not available, competing needs that impair food seeking are devalued. Third, hunger circuits promote food consumption by modulating motivation and reward. Hypothalamic agouti-related protein (AgRP)-expressing neurons are active during food deprivation and their activity drives food seeking and consumption. Precisely how AgRP neuron activity is regulated, however, is not completely understood. We used in vivo calcium imaging and gut-brain manipulations to identify multiple pathways that are utilized by nutrients along the gastrointestinal tract to inhibit AgRP neuron activity. When AgRP neurons are active in the absence of food, they suppress persistent inflammatory pain to promote feeding. We show here, using neural activity recordings, that peptidergic signaling blunts the activation of a population of glutamatergic neurons in a hindbrain hub that is a critical relay point for pain information. This work significantly advances our understanding of a relatively unexplored endogenous analgesic circuit. Finally, we demonstrate that AgRP neuron activity is sufficient to increase dopamine release in the striatum following food intake and that tonic elevations of striatal dopamine by drugs or input from a novel satiation center in the cerebellum suppress food intake by attenuating further release in response to food. Together, our findings reveal that hypothalamic neurons are regulated by rapid neural signals from the gut in order to properly enhance reward circuit activation and suppress activity in pain-responsive neurons to ensure survival
Investigating The Thermal And Kinetic Stability Of Thin Films Of Molecular Glasses
Full text linkStable Glasses (SGs) are very dense glasses with remarkable thermodynamic and kinetic stability, that are made by the process of Physical Vapor Deposition (PVD). These glasses are made directly into a low-energy state via surface-mediated equilibration (SME), during PVD. In this work, we are investigating the kinetic and thermodynamic stability of vapor-deposited films of N,N’-Bis(3-methylphenyl)-N,N’-diphenylbenzidine (TPD) of different thicknesses and substrate temperatures. We produced SGs of bulk (\u3e200nm) TPD films with a broad range of stability and measured the density change of the films, which is a measure of the thermodynamic stability, upon thermal annealing. To study the kinetics of as-deposited glasses, we have optimized the process of solvent vapor annealing (SVA). When the as-deposited films of TPD are solvent annealed with toluene under the right conditions, a solvent front, analogous to a propagating thermal front, can be produced and measured by in-situ spectroscopic ellipsometry. The speed of the solvent front, limited by the relaxation of the medium, gave an indirect estimate of the kinetics of the film. For bulk films of TPD SGs, we observed the strong dependence of the thermodynamic stability on substrate temperatures. The kinetics of the bulk SG films on the other hand, depend not only on the substrate temperature but also on other factors such as the birefrigence of the films and mobility of the solvent front. The thermodynamics and kinetic stability of as-deposited SG films point towards the existence of two regimes in the formation of the SGs. In very thin films (\u3c60nm), the density of the as-deposited films exceeds that of the supercooled liquid (SCL) line and follows a new SCL line, at lower temperatures. The transition from the high temperature SCL, to the low temperature SCL happens within a narrow range of substrate temperatures, where the kinetics of the films changes drastically by almost to an order of magnitude. This suggests the existence of a distinct phase that exists in very thin as-deposited films, with a liquid-liquid phase transition, below the glass transition, to the low temperature SCL
Machine Learning As Tool And Theory For Computational Neuroscience
Full text linkComputational neuroscience is in the midst of constructing a new framework for understanding the brain based on the ideas and methods of machine learning. This is effort has been encouraged, in part, by recent advances in neural network models. It is also driven by a recognition of the complexity of neural computation and the challenges that this poses for neuroscience’s methods. In this dissertation, I first work to describe these problems of complexity that have prompted a shift in focus. In particular, I develop machine learning tools for neurophysiology that help test whether tuning curves and other statistical models in fact capture the meaning of neural activity. Then, taking up a machine learning framework for understanding, I consider theories about how neural computation emerges from experience. Specifically, I develop hypotheses about the potential learning objectives of sensory plasticity, the potential learning algorithms in the brain, and finally the consequences for sensory representations of learning with such algorithms. These hypotheses pull from advances in several areas of machine learning, including optimization, representation learning, and deep learning theory. Each of these subfields has insights for neuroscience, offering up links for a chain of knowledge about how we learn and think. Together, this dissertation helps to further an understanding of the brain in the lens of machine learning
Intrinsically And Extrinsically Modulated Polymer Mechanical Behaviors For Engineered Advantages In Adhesion, Topological Mechanics And Energy Storage
No full textThis thesis covers three parts of my doctoral research and describes an evolution of intrinsic and extrinsic strategies to manipulate elastic energy and manage stress in functional polymers for various engineering applications. Chapter 2 focuses on tuning bulk and near-surface mechanical properties of hydrogels to foster strong yet reversible adhesion to arbitrary target surfaces, analogous to the naturally observed action of snail epiphragm. At the outset, I synthesize hydrogel precursors and develop conditions for polymerization to tune the material’s intrinsic modulus, especially at the adhesive interface, for sufficient compliance to conformally map rough target surfaces. Whereas intrinsic modulus increases by three orders of magnitude, minimal shrinkage upon dehydration preserves conformal contact with the target surface and stores very little residual stress. This engenders strong shear adhesion courtesy dispersive interactions and mechanical interlocking with a target topography. I design experiments to extract maximal shear adhesion performances and understand underlying adhesion mechanisms and phenomena. Finally, I leverage microscale fabrication techniques to pattern the hydrogel with various surface and bulk geometries for various extrinsic advantages. In Chapter 3, I extend this strategy to other functional polymers with dynamic covalent bonds and shape memory and leverage intrinsic polymer phase transitions to protect topological behavior in mechanical metamaterials. Maxwell lattices can exist in multiple distinct topological states featuring polar elasticity and strongly asymmetric acoustic behavior. However, prior demonstrations of Maxwell lattice-based metamaterials with non-trivial topological mechanical behavior have been limited to either static monoliths or mechanical linkages. I develop a transformable topological mechanical metamaterial (TTMM) made from a shape memory polymer, capable of reversibly exploring its phase space. I propose a kinematic strategy that cascades single uniaxial mechanical inputs at free edge pairs into a biaxial global transformation to reversibly switch between different topological states. I expose the vulnerability of a topologically polarized elastic response to stresses stored during a prior kinematic transformation and proceed to show how intrinsic polymer phase transitions can \u27quench\u27 polymer chain mobility and thereby \u27cache\u27 these stresses to safeguard a metamaterial’s topological behavior against its kinematic stress history. Finally, in Chapter 4, I pivot towards a predominantly extrinsic strategy of minimizing and managing stress by structuring a functionalized polyelectrolyte polymer into triply periodic minimal surfaces (TPMS) for external-pressure-free high capacity lithium metal anodes. Sheet-based gyroid architectures offer exceptional strength, porosity and surface area per unit volume coupled with excellent manufacturability. Using a highly optimized polymer precursor and μ-scale digital light processing (μ-DLP) additive manufacturing techniques, I create microporous scaffolds that can stabilize and guide lithium metal deposition into dense, dendrite-free morphologies even at high current capacities, without the need for any externally applied pressure
The Black Worker and the Knowledge Economy in Philadelphia: University-Led Displacement vs. Homeowner Democracy
No full textThis dissertation investigates the consequences of university-driven development in Philadelphia, especially for the African American communities that surround the University of Pennsylvania, Temple University, and Drexel University. It uses the theoretical contributions of W.E.B. Du Bois and David Harvey to conceptualize Philadelphia’s high rate of low-income homeownership as a product of the struggle of black workers and communities for democracy and the Right to the City. Thirty-three qualitative interviews with long-time residents, political activists, university administrators, and community institutions were conducted. Quantitative analysis including logistic regression analysis of Home Mortgage Disclosure Act (HMDA) data comparing outcomes in gentrifying and non-gentrifying neighborhoods and spatial K-cluster analysis were also conducted. Results show that university-driven development is leading to the conversion of single-family homes into apartment buildings and multifamily rentals, and a vision of the city in which developers, city officials, and university administrators wish to (in the words of one interviewee) “bring Manhattan to Philadelphia”. For homeowners, density is a shorthand for social, economic, and political displacement of the black working class and the disappearance of affordable homeownership opportunities. Density and affordable housing—and an ideology of urbanism—as conceptualized by city planners, university officials, developers, and new residents, clash with communities’ definitions of what the urban fabric of Philadelphia should be, as well as what truly affordable housing looks like. Furthermore, the influx of a student and professional population and its definition of progressivism has led to the political displacement of constituencies that have been shaped by black liberation movements. Resistance to university-driven development, whether it is the movement against the building of Temple’s Stadium, or the drive to “save-zone” neighborhoods by rezoning them from mixed residential to single family, are led by black homeowners to preserve homeownership and black electorates. They are rooted in the historic struggles of the black worker in Philadelphia. I conclude with a discussion of the context of decreasing rates of homeownership in the country as a threat to a truly democratic society
Teaching Teachers: Classroom Teachers\u27 Roles in the Third Space of Student Teaching
No full textThis study explores how public-school teachers who host student teachers in urban, grade 7—12 classrooms (referred to as cooperating teachers or classroom mentors in this study) define their role in preparing pre-service teachers. This study is particularly interested in yielding insight into how participants describe the “practice” of preparing teachers and how this compares with university-based notions of practice-based teacher education (Grossman, 2018). Through the use of qualitative methodologies this study will explore mentor interactions with their student teachers, as well as whether these interactions reshape their practice and classrooms. Additionally, this study will explore the extent to which mentor teachers’ past experiences influence their mentoring practices as well as how university-provided guidance such as communications, handbooks, and professional development shape mentors’ conceptions of what it means to be a teacher educator. Knowledge about how in-service teachers define themselves as teacher educators could provide valuable insight into how school districts can build structures for effective field-based teacher education and where they might engage Universities to fill gaps