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The Relationship between Moral Thought-Action Fusion and Scrupulosity across Judaism, Christianity, and Islam
Get PDFScrupulosity is a subtype of obsessive-compulsive disorder (OCD) where individuals are upset by intrusive thoughts related to religious or moral issues. Current research suggests that scrupulosity occurs across the major world religions—including the Abrahamic religions (i.e., Judaism, Christianity, and Islam). Some research suggests that moral thought-action fusion (moral TAF), a dysfunctional belief that thinking something is equal to doing it, may only be pathological under certain circumstances (e.g., if it is not culturally normative). If this is true, the current cognitive model of scrupulosity may need to be amended to reflect how cultural differences impact the role of moral TAF as a risk-factor in the development of scrupulosity. The current study included participants (N=207) identifying as Jewish (n=73), Muslim (n=66), and Christian (n=68) residing in the United States who were at least 18 and could read English. Participants were recruited through CloudResearch and the community. Participants completed a series of questionnaires online assessing scrupulosity, moral TAF, religiosity, etc. in a randomized order. They then completed a thought-induction task. This is the first study to explore how the relationship between moral TAF and scrupulosity symptoms may differ across the Abrahamic religions. Results suggest that moral TAF most strongly predicted scrupulosity symptoms for those identifying as Jewish and least strongly predicted scrupulosity symptoms for those identifying as Christian. Moral TAF may thus only pose as a risk-factor if it is not culturally normative, and the current cognitive model of scrupulosity may need to be modified to reflect greater cultural sensitivity. Exploratory analyses also suggest that the moral domain of purity/sanctity may be an important, culturally dependent variable to include within the cognitive model of scrupulosity
A Tradition of Turbulence: Personal and Political Chaos in Francisco Goya’s Two Old Ones Eating Soup
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Development of Probabilistic Dynamic Model Building and Bayesian Machine Learning Approaches
No full textAbstract
Development of Probabilistic Dynamic Model Building and Bayesian Machine Learning Approaches
Samuel Adeyemo
The recent years have seen a tremendous increase in the use of artificial intelligence (AI) and machine learning (ML) for the development of data-driven mathematical models needed for performing real-time optimization, model-based control, performance optimization, dynamic data reconciliation, and process performance monitoring. However, the development of data-driven models is faced with some challenges including lack of model interpretability, sensitivity of algorithm to noise in training data, limited extrapolation capabilities and violation of conservation laws. Drawing motivation from these existing gaps, this work aims to develop robust algorithms for constructing interpretable predictive data-driven models from noisy process data. Novel strategies are developed to enhance model extrapolation capabilities by guaranteeing the satisfaction of conservation laws for both steady state and dynamic models.
By carrying out Bayesian inferencing in the Expectation-Maximization framework, a data-driven approach that simultaneously estimates the noise in training data and their possible correlation while estimating the posterior probability distribution of model parameters conditioned on the available data is developed. An algorithm for model selection is proposed using branch and bound seeking a parsimonious model structure by promoting sparsity and penalizing redundancy in model parameters. The resulting Bayesian Identification of Dynamic Sparse Algebraic Model (BIDSAM) algorithm incorporates model parameter estimability measures in the model selection criterion minimizing the computational cost of the algorithm.
To guarantee the conservation of mass by model predictions, two novel algorithms are developed for both static and dynamic models. The first algorithm involves a sequential approach for solving for model parameters and carrying out data reconciliation while the second approach exploits the model structure in the proposed BIDSAM algorithm to enforce equality constraints on the model parameters such that model predictions are guaranteed to satisfy mass and energy balances.
Finally, this work draws cue from the computational neuroscience literature where predictive coding (PC) is used in the training of networks modeling the Bayesian brain. In this work, sparse hierarchical models are constructed for systems with (spatio)temporal distributions and local computations are engaged for parameter estimation. This results in hierarchical BIDSAM (H-BIDSAM) algorithm which automatically detects unknown input delays and is robust to presence of noise with cross- and autocorrelations, in the training data
“Population, Proximity, and Promise: A Study of College Choice and the Competition for Students in Higher Education”
Get PDFThis dissertation is an empirical investigation of the relationship between institution and state characteristics and college choice for students enrolling out-of-state, as well as the relationship between Promise programs and college choice. The theoretical framework used in this study draws on both an economic model of human capital investment and sociological concepts of habitus, cultural, and social capital, and organizational context and assumes that an individual’s college choice is shaped by four contextual layers: the individual’s habitus, school and community context, the higher education context, and broader social, economic, and policy context. Public data from the Integrated Postsecondary Education Data System (IPEDS) and the United States Census were used to analyze out-of-state enrollment of first-time, first-year undergraduate students by state and public four-year doctoral institutions between 2005-2020. These associations were investigated by using Poisson regression models that analyzed a set of variables for each institution and each state. Results were included for four different models that varied by reporting years, whether a Promise indicator was included in the model, time-periods, and region. Factors including tuition costs, race and ethnicity, and proximity were found to be statistically significantly related to students\u27 choice of enrolling at a public doctoral university in another stat
Testing a Conceptual Model of Age, Gender, Perceived Discrimination and Well-Being
Get PDFBoth age and gender are personal characteristics that are at least in part outwardly visible and act as a category for social judgments (Cuddy & Fiske, 2002). The current study examined associations among individuals’ views on their aging, their gender typicality, well-being, and perceived discrimination. Research Question 1 asked whether views on aging and gender typicality interact to influence perceptions of discrimination; Research Question 2 explored the same potential interactions’ influence on well-being. Research Question 3 explored whether any interaction between views on aging and gender typicality and well-being was mediated by perceptions of discrimination. Participants represented the adult life span from ages 40-93(M = 53.43, N = 616) and were comprised of 56% women, and 85% White participants. Data was collected online via Prolific using self-report measures sent to their panelists. Results from Research Question 1 yielded two significant interactions. In the significant interaction between aging-related cognitions and gender roles and expectations, for participants who reported highly-gender-typical gender roles and expectations, those who also reported less positive aging-related cognitions reported more perceived discrimination, while those who reported more positive aging-related cognitions reported less perceived discrimination. In the second significant interaction for Research Question 1 between self-perceptions of aging and gender roles and expectations, if participants reported less positive self-perceptions of aging, they also reported worse discrimination, which was amplified for those who had lower levels of gender typicality. Results from Research Question 2 yielded one significant interaction between subjective age and gender self-concept; for participants who reported highly gender-typical gender self-concept, subjective age was less impactful on their well-being than for those who reported low gender-typical gender self-concept. For those individuals, a more positive subjective age (feeling younger than one’s chronological age) was associated with better well-being, and a more negative subjective age (feeling older than one’s chronological age) was associated with worse well-being. Results from Research Question 3 supported the hypothesis that there would be important links among all of these key variables, such that views on aging and gender typicality would interact to influence well-being, with perceptions of discrimination acting as a mediating variable; numerous significant associations supported this hypothesis. Despite important limitations, all hypotheses were partially supported, and future work should consider creating new measurements of gender that are not subject to the gender binary to measure gender in a more nuanced way. This work suggests that there are important associations among views on aging, gender typicality, perceived discrimination, and well-being that should be further explored
The role of synaptic zinc signaling in excitatory circuits of the mouse auditory cortex
Get PDFSynaptic zinc signaling modulates synaptic activity and is present in specific populations of cortical neurons, suggesting that synaptic zinc contributes to the diversity of intracortical synaptic microcircuits and their functional specificity. The pool of chelatable synaptic zinc is controlled by the zinc transport protein ZnT3, a protein which functions by moving free zinc into glutamatergic presynaptic vesicles, from which it is co-released with glutamate during synaptic transmission. Once synaptic zinc is released within the synaptic cleft, it acts on glutamate receptors on the post-synaptic spine, including ionotropic NMDA and AMPA receptors. While the inhibitory function of zinc on NMDA receptors is well-characterized, the nature of zinc’s modulatory effect on AMPA receptors is less well-known, with long-standing controversy in the field as to what specific roles zinc signaling plays in AMPA receptor function. To understand the role of zinc signaling in the cortex, we performed whole-cell patch-clamp recordings from intratelencephalic (IT)-type neurons and pyramidal tract (PT)-type neurons in layer 5 of the mouse auditory cortex during optogenetic stimulation of specific classes of presynaptic neurons. Our results show that synaptic zinc potentiates AMPAR function in a synapse-specific manner. Specifically, in IT-PT synapses we observed unidirectional potentiation of AMPA receptors by zinc, while in IT-IT synapses we observed potentiation which could be enhanced or suppressed.
Additionally, ZnT3 and ZnT3-dependent synaptically released zinc may also play a role in the specific functional properties and structure of dendritic spines. How ZnT3 and ZnT3-dependent zinc may contribute to spine morphology and function presents a gap in our understanding of the range of zinc functions. To understand how zinc signaling contributes to the function of synapses, we performed whole-cell patch clamp recordings of miniature excitatory postsynaptic currents (mEPSCs) from layer 5 PT-type corticocollicular neurons of wild type and ZnT3 knockout mice. Our results show that the constitutive loss of ZnT3 and ZnT3-dependent synaptically released zinc reduces mEPSC amplitudes in an age-dependent manner. We also utilized functional calcium imaging in this same population of neurons. These results showed that not all dendritic spine synapses are sensitive to zinc during activity.
This dissertation focuses on the cell-type specific effects of ZnT3-dependent synaptically released zinc on excitatory neurons in circuits of the mouse auditory cortex, and how ZnT3 and ZnT3-dependent synaptically released zinc function to determine the structural and functional properties of individual synapses. Our results provide insight into the contribution of zinc signaling to the functional specificity of cortical circuits and synaptic structure and function, as well as highlight the importance of further research to elucidate the wide range of signaling functions zinc may have across cell types and brain regions
Room Temperature Decarboxylative Amination Reactions of Carboxylic Acids
No full textAnilines are important structural motifs present in numerous natural products and pharmaceutically relevant compounds. Among the various synthetic strategies that have been developed, transition-metal-catalyzed cross-coupling reactions represent one of the most commonly employed methods for the formation of anilines. However, these approaches generally require pre-functionalized aryl coupling partners, and the utilization of more readily available, and structurally diverse coupling partners, such as carboxylic acids, would be desirable. Decarboxylative coupling reactions have garnered significant attention as an alternative approach to form new C-N bonds, and substantial progress has been made in this area. Nevertheless, these methods remain limited, with a predominant emphasis on the synthesis of substituted anilines rather than primary anilines.
This dissertation provides a concise overview of traditional and commonly used synthetic methods for primary aniline formation in chapter 1. It also discusses related advancements in decarboxylative amination approaches. It also highlights the different amine sources employed in those transformations. Chapter 2 details the development of a new decarboxylative amination reaction that operates under mild, metal-free conditions. The scope of this methodology is shown to encompass a broad range of aromatic and heteroaromatic carboxylic acids. Additionally, preliminary mechanistic investigations have been conducted to gain insights into the reaction pathway. The final chapter presents a broad survey of diverse sets of carboxylic acids explored under the decarboxylative amination conditions. Preliminary results indicate the successful decarboxylative amidation of α-oxo carboxylic acids, enabling the formation of primary amides under mild reaction conditions. The ability to form primary amides, which is an important motif in pharmaceuticals, under mild reaction conditions would provide an attractive method for the synthesis of new C(O)-N bonds
A Domain Adaptation Approach for Morphology-Independent Cell Instance Segmentation
Get PDFIn recent years, there has been an upward trend of utilizing deep learning to automate cell segmentation processes. As global storage capacities grow exponentially, so have microscopy data collections become larger and more frequent. To benefit from them, accurate and precise quantitative analysis tools like cell instance segmentation have become necessary. However, the highly variable nature of these data collections necessitates retraining segmentation models to maintain high accuracy on new data collections. This process is time-consuming and labor-intensive since a user must annotate much of the new data, usually under the supervision of a medical professional. The problem is further exacerbated when segmenting cells with elongated and non-convex morphology, like bacteria cells.
In mitigating these concerns, we propose reducing the amount of annotation and compute power needed to retrain the model by introducing a few-shot domain adaptation approach that requires the annotation of only one to five cells of the new data. First, we rely on a robust and precise segmentation method trained on extensive source data and capable of handling highly diverse cell morphologies. Second, we take a few-shot learning approach, where given a target dataset that is distributed differently from source data, we require a user to label only a minimal amount of target data. We then set up a contrastive prediction task by introducing new losses that pull the representation of positive samples in a target domain closer to samples of the same class in a source domain while simultaneously pushing them apart from negative source samples using kernels as a similarity measure. Furthermore, we comprehensively studied the best kernel composition method for combining kernels defined on two inhomogeneous pairs of quantities. Our approach quickly adapts the model to maintain high accuracy, and our results show a significant boost in accuracy after adaptation to very challenging bacteria datasets
Spiral Wave Teleportation and Multiplex Network Synchronization in Light Sensitive Belousov-Zhabotinsky Systems
Get PDFWe experimentally and computationally investigate dynamical behaviors in excitable and oscillatory media using light sensitive Belousov-Zhabotinsky (BZ) systems. These systems are not in a state of thermodynamic equilibrium, and have been proven to show various interesting phenomena including spatiotemporal patterns, self-organization, and chaos. We utilize the BZ reaction, a nonlinear chemical reaction, known for its relaxation-type oscillations, to explore the dynamics of these systems.
We examine spiral wave teleportation in an excitable media as an effective alternate defibrillation method. Spiral waves have emerged as a key phenomenon associated with the initiation and persistence of cardiac arrhythmias. Using a light sensitive experimental BZ system and low-energy perturbations, we transport spiral wave tips, as well as annihilate them. By targeting the refractory back of spiral waves, we initiate unidirectional waves in the excitable media. Our results demonstrate that with the appropriate application of the perturbation, we can effectively initiate, annihilate, and teleport spiral waves.
Additionally, we investigate synchronization behaviors in multiplex networks of coupled BZ oscillators. These oscillators are created by loading cation exchange beads with ruthenium catalyst and placing them in a catalyst-free BZ solution, where light is used for coupling. Phase response curves (PRCs) are utilized to quantify an oscillators’ response to light perturbations. In this study, we investigate a two-layer multiplex network of BZ oscillators, where each layer consists of a star network with a hub oscillator and five peripheral oscillators. We demonstrate that synchronization behavior can be observed in these multiplex star networks with varying strengths of inhibitory interlayer coupling