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More Than A Milestone: Understanding Religious-Cultural Coming-of-Age Ceremonies in Contemporary America
No full textA Jaguar Eats a Human Eats a Mushroom (& That\u27s Okay With Me)
No full textHumanity—at least the humans who are engaged with Western society and thought—has a conceptual problem regarding nature. It has profound effects on the Earth, some of which are harmful to nonhumans, landscapes, and ourselves. The changes and devastation—namely climate-change induced humanitarian crises and species extinction—that the anthropocene has created can be partially attributed to a perception of the world that much of humanity holds as true: that we stand outside of nature, and are dominant over it. I propose that this thinking has limited humanity’s perceptions of truth. I am offering an alternative understanding of reality, such that humans are within nature, entangled and attached as a member of a greater web of relations, and further, that humans are not dominant over this web
The Architecture of Abuse: Physical Space and Systems of Oppression in In the Dream House
No full textUsing Network Statistics to Analyze Amazon Movie Reviews
No full textOnline reviews can significantly alter consumer behavior, especially on platforms like Amazon where user-generated content helps shape product perception. While traditional approaches focus on sentiment analysis or topic modeling, they often overlook the relational structure between the products and reviewers. In our study, we apply network analysis to uncover deeper patterns in Amazon movie reviews using a dataset obtained from the Stanford Network Analysis Project, which spans over a decade and contains millions of reviews. The goal is to uncover how reviewers interact with products and with each other, and identify meaningful relationships or patterns in movie reviews data. We construct a bipartite graph of users and movies, which is then projected into a movie network where nodes (movies) are connected if reviewed by the same user. We then explore the network’s characteristics through EDA and Exponential Random Graph Models (ERGMs). Our analysis reveals that the network is very compact, suggesting that many movies have been reviewed by the same Amazon user. We hope that this research can contribute to methodological approaches for analyzing large-scale bipartite networks and provides a foundation for further research in recommender systems, marketing, and behavioral analysis
Peroxisomal Disruptions at the Lipid Droplet Interface: Implications for Insulin Resistance
No full textTheories Beyond Theory Theory: Eco-Enactive Perspectives on Autism
No full textAutism is an extremely heterogeneous condition whose core symptomatology and etiology are still the subject of debate. The most recognized core symptoms of autism fall into two camps: social symptoms related to difficulties maintaining interpersonal interactions and relationships, and behavioral symptoms related to restricted interests, repetitive behaviors, and abnormal sensitivities to sensations. Classic theories of autism, including theory of mind theory, weak central coherence theory, and executive function theory, draw from different sources of psychological evidence to provide different explanations for these symptoms. This paper finds that no one of these established theories offers a holistic account of autism which comprehends each of its core symptoms, and that in their ensemble they suggest that different symptoms arise from different causes. They also struggle to explain autistic motor differences such as dyspraxia. This paper argues for the necessity of an alternative model for autism, and proposes an embodied approach which draws from the enactivist work of Hanne De Jaegher, who presents autism as an alternative cognitive style developing from dysfunctional patterns of social interaction in early childhood. This paper draws on interdisciplinary sources including the recently emerged “connectivome theory” of autism and the embodied cognitive paradigm of ecological psychology to amend De Jaegher’s account. Connectivome theory shows how connective tissue abnormalities significantly connected to autism could contribute to early dysfunctional interactions and constitute a biological influence on autistic development. The cognitive differences which constitute autism manifest in social skills, behaviors, perceptual biases and motor capacities simultaneously, according to enactivist and ecological cognitive science. Therefore this alternative, “eco-enactive” model of autism could more holistically explain the diverse symptomatology of the condition than classic theories, and could provide a clearer narrative for its developmental trajectory and biological risk factors.
Keywords: autism, enactivism, connectivome, ecological psycholog
Towards Noise-Resilient Few-Shot Learning: Optimizing Prototypes for Glioblastoma Classification
No full textFew-shot learning (FSL) with prototype-based methods offers an appealing solution for medical image classification, particularly for rare conditions with limited data. However, traditional prototypical networks struggle with data heterogeneity and bias, often focusing on irrelevant patterns rather than true discriminative features. We propose a novel metric-based optimization algorithm that enhances prototype selection in few-shot learning, evaluated on the challenging case of Glioblastoma (GBM) classification. Our method addresses the inherent heterogeneity of medical imaging data by intelligently selecting support sets that capture genuine pathological features while mitigating orientation and imaging technique biases. Experimental results demonstrate that our approach consistently outperforms baseline methods across varying noise conditions, achieving average improvements of 5.89% and 4.66% in classification accuracy over random sampling when applied to prototypical networks and IMP, respectively. The algorithm maintains computational efficiency while significantly enhancing robustness to data bias and noise, making it particularly valuable for medical imaging applications where data quality and representation vary substantially
Disruption of Peroxisomal Function in Intestinal Epithelial Cells: Implications for Enterocyte Formation
No full textFair Pay, Fair Play? Examining Gendered Housework Allocation Among Dual-Income Couples
No full textThis study examines how relative income influences the division of housework in married, heterosexual, dual-income couples using 2017 and 2021 PSID data. Grounded in bargaining theory and gender deviance neutralization, this analysis investigates whether traditional gendered patterns in housework allocation persist as household income dynamics shift and whether these patterns differ across subgroups, particularly between mothers and child-free wives. The results indicate that relative income significantly predicts housework hours for wives but not for husbands, and there is evidence of gender norms in domestic labor. While the 2017 findings are inconclusive regarding gender deviance neutralization, the 2021 results support its role, particularly for mothers. Additionally, age emerges as a significant predictor of housework for child-free women, suggesting generational shifts in domestic labor expectations. Across all models, women perform more housework than men, except for young child-free women. Household income, education, and race do not significantly affect housework allocation. These findings highlight the enduring influence of gendered expectations, particularly for mothers, and suggest that economic empowerment alone is insufficient to equalize housework distribution
Not Clique-bait: Algorithmic Approaches to the Maximum Clique Problem
No full textThe maximum clique problem is a well-studied challenge in graph theory with applications in network analysis, bioinformatics, and social network modeling. This paper examines four algorithms for solving the problem, comparing their efficiency, accuracy, and scalability. We consider both exact and approximate approaches, discussing their computational complexity and practical applications. Experimental results are presented to evaluate performance across different graph structures. Through this analysis, we highlight the trade-offs between optimality and computational feasibility, providing insight into the strengths and limitations of these algorithms