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Charting Reciprocity: The Mapping of Knowledge Production in Collaborative Community Networks
No full textAbstract
This dissertation reconceptualizes community-based literacy and writing practices as dynamic processes of reciprocal textual production grounded in feminist and Indigenous methodologies. It challenges traditional hierarchical structures by foregrounding community-generated epistemologies, emphasizing relational accountability, iterative reflexivity, and sustained ethical engagement. Using qualitative methods—including practitioner-created knowledge and social network maps and an analytical mapping method—the study explores how community practitioners strategically leverage their cultural identities and epistemological frameworks within collaborative writing and advocacy.Empirical case studies illustrate reciprocal knowledge production in action, showcasing intentional approaches such as oral storytelling, collaborative writing, and policy advocacy. Findings demonstrate how textual artifacts from reciprocal frameworks actively challenge institutional norms, redistribute power, and validate community epistemologies. The dissertation contributes new conceptual vocabulary and practical frameworks for explicitly operationalizing reciprocity in community-academic partnerships. Pedagogically, it provides actionable strategies for integrating reciprocal methodologies into writing curricula, cultivating inclusive and collaborative learning environments. Institutionally, it advocates for revisions in research protocols—especially within IRB processes—to ethically position community members as active co-creators of knowledge. In sum, this research promotes a critical and reflexive reimagining of composition studies, centering community-driven epistemologies to advance sustainable, equitable, and genuinely reciprocal knowledge production practices—tlamatiliztli ihuan nechicoliztli (knowledge and reciprocity)
She wrote too much : Overproduction and the Canonicity of Victorian Women Novelists
No full textThough the Victorian era is often viewed as “the age of female novelists,” many of the most prolific and popular women writers of the time have been belittled, ignored, and forgotten. While the feminist literary recovery work of the 1980s and 1990s has brought many of these women back into scholarly consciousness, they have still not gained the respect given to their more famous yet less prolific contemporaries: the Brontë sisters, George Eliot, and Elizabeth Gaskell. In this dissertation, I argue that the reason can be found in a criticism frequently applied to these women writers both in their own time and ours: “She wrote too much.” The overproduction critique rose out of Victorian biases about class and gender and encompasses three other major criticisms: the writer worked within popular genres, the writing was poor quality, and the writer wrote to make money rather than to create art. Women writers were often labelled as popular novelists writing for the lower classes while male writers were viewed as high culture novelists writing for an educated, upper-class audience. These biases have carried over into twentieth- and twenty-first-century criticism, resulting in the disparity found in the modern literary canon.My dissertation focuses on three women novelists from between the 1850s and 1880s: Margaret Oliphant, Charlotte Riddell, and Mary Elizabeth Braddon. Through close readings of their works, letters, and lives, I examine the accusations of overproduction faced by these authors, their responses to these accusations, and how these accusations have affected their reputation and canonicity over time. I also use a distant reading approach to show the overproduction critique as a systemic problem in the modern canonization of women writers. While the biases resulting in the overproduction critique began in the Victorian era, they were not left behind as time moved forward. By dismantling the overproduction critique and how it has been used to suppress Victorian women’s writing, my research asks readers to examine society’s negative attitudes toward the many modern women writers and artists who, like their nineteenth-century predecessors, are accused of writing too much
Logistic Regression and Cox Hazard Modeling with Sparse High Dimensional Data via Elastic Net Regularization and Graph-Guided Aggregation
No full textRare features are predictor variables with excessively low rates of nonzeros. It is not uncommon to encounter rare features in settings where data is quantified through one-hot encoding, such as text mining data or genomic data. Rare features pose problems for classic regression techniques due to instability of effect estimates. The problem is compoundedwhen the dimension of the feature space is high. Yan and Bien (2020) explored methods for aggregating rare features in high dimensions by leveraging side-information about relations between features that can be organized as a tree graph. While their work is restricted to standard Gaussian regression, we aim to attack the rare feature aggregation problem for the Generalized Linear Model (GLM) setting. Additionally, we explore the use of a more general graph structure by considering bipartite graph representations of known group memberships of effects
Consumptive and Energetic Responses of Fishes Under Pressure of Climate Change
No full textMarine organisms are confronted with warming waters due to climate change requiring species to exhibit responses to persist. For many fish, these responses have included range shifts to cooler waters, but are species-specific which may create further disruption through trophic mismatches. To identify potential mismatches and estimate their implications for the quality of consumption within major predators, analyses of predator stomach contents were integrated with reviews of organismal energetics and physiological parameter values. The energy density of prey that is consumed dictates the consequences of consumption, so having data expands general understanding of diet. To that end, published records (n = 134 sources) of energy density were integrated into a single database containing 2018 taxa. Diet collections were conducted by the Northeast Fisheries Science Center as part of the Spring and Fall Bottom Trawl Survey from the Northeast US Continental Shelf Large Marine Ecosystem (NEUS) community of fishes (n = 41 predator species). Individual diets (n = 369,540 diets) spanning decades (1973-2019) were used for a temporal analysis of feeding guild assignment, multivariate guild interrelatedness, and individual predator diet quality. Together, community analyses revealed a high degree of consistency in feeding behaviors as predators largely (\u3e87%) retained guild assignments, but declining inter-guild dispersion (p = 0.010) suggested that the community is being compressed. Individual predators by season showed similar patterns of compression based on diet breadth losses (83.0% of predators) which may have driven the decline in relative consumption and increased stomach emptiness further observed in many predators (79.6% and 44.0%, respectively). Pairing these observations of diet with the energy density database revealed that average diet energy densities were quite stable (no meaningful change for 61.0% of predators), thereby indicating no compensatory prey selectivity to prevent losses in absolute and relative energy consumption (54.2% and 66.1% of predators declining, respectively). Post-hoc analyses revealed that benthic-oriented predators experienced the most rapid decline on average, especially those from the Polychaete/Amphipod eaters guild, such as witch flounder or haddock. A comparison of species characteristics to parameters of bioenergetics models (n = 101 models) revealed them to be highly variable across taxa (n = 70 species), depending on the ecology of the species. Bioenergetic models also were used to calculated temperature windows across which growth occurs and a novel relative index of resilience. Whereas temperature windows varied widely between species (range 9 – 40°C), a relative index of resilience suggests that high sensitivity to warming was common 82.8% of models). My results suggest that diet quality for a broad community of predators has declined over the past ~50 years due to an apparent lack of feeding adaptiveness. The consequences of these declines may result in an acceleration of distribution shifts as consumption limitations are spatially variable due to and resulting in predator-prey spatial mismatch. These results indicate that the ability of predators to maintain trophic connections threatens marine ecosystems above and beyond warming waters alone and is important to consider to effectively manage fisheries experiencing such changes
Responding to range expansion: Assessing insect communities, tree decline symptoms, and tree mortality risk as the southern pine beetle moves north
No full textClimate change is shifting species distributions. In New England, warmer winters allow southern species to survive further north. The northward range expansion of the tree-killing southern pine beetle is the focus of this dissertation. Outbreaks of this beetle cause both ecological and economic damage, which threaten the globally rare pine barrens ecosystem. I used an interdisciplinary approach to study this insect: 1) I synthesized literature on the beetle’s natural enemies; 2) I used a suite of chemical attractants to investigate the insect community attracted to the beetle’s pheromones and assessed the diversity and abundance of its potential predators; 3) I employed and assessed hyperspectral remote sensing for detecting trees attacked by the beetle; and 4) I evaluated the risk of beetle outbreaks in northeastern National Parks, integrating multiple forestry techniques. Ultimately, this work will provide critical information to support natural resource managers’ decision-making in a rapidly changing climate
DYNAMIC DEFENSE STRATEGIES FOR FIELD PROGRAMMABLE GATE ARRAY (FPGA) SECURITY
No full textField Programmable Gate Arrays (FPGA) have gained popularity and usage in recent years, and they have been widely used in mission-critical applications. Due to its popularity, the security of FPGA has become a big concern. Most existing research on FPGA security focuses on hardware Trojans, side-channel attacks, and reverse engineering. The existing FPGA countermeasures against the attacks above are typically limited to the FPGA systems implemented in the old FPGA utilization model. An increase in cloud-based FPGA providers, third-party accelerator suppliers, and open-source FPGAdesign tools has changed the FPGA utilization model, which requires new security measures for modern FPGAs. This thesis investigates emerging security threats in modern FPGA usage, mainly focusing on FPGA Computer-Aided Design (CAD) tools and multi-tenant FPGA environments. This thesis also proposes dynamic, adaptive countermeasures to protect and update FPGA systems against traditional and emerging attacks. FPGA CAD tool is one of the entities in the FPGA design flow. The state-of-the-art efforts on FPGA CAD tool only protect FPGA systems from IP piracy and hardware tampering rather than improving attack resilience against CAD tool attacks. This thesis identifies and demonstrates critical security flaws in FPGA CAD tools related to IP encryption, design isolation, and current design countermeasure implementation. To thwart attacks originating from CAD tools, a dynamic partial reconfiguration-enabled design obfuscation (DPReDO) method is developed to strengthen the existing design obfuscation method by modifying the FPGA bitstream at runtime. DPReDO significantly reduces CAD Trojan hit rates by 80% compared to static obfuscation methods. Additionally, the increasing prevalence of FPGA-as-a-Service (FaaS) and cloud-based FPGA accelerators exposes multi-tenant FPGAs to remote, exploitable fault attacks, particularly Power Waster Circuit (PWC)-based attacks. Existing countermeasures fall short in addressing multi-source attacks and non-combinatorial PWCs. To address this, the thesis proposes Signal-Slowdown-based Fault Attack Mitigation (S2FAM), a dynamic approach that achieves a 100% detection rate for combinatorial and non-combinatorial PWC attacks. S2FAM also outperforms existing techniques in attack localization with a 25.2% improvement in precision. By analyzing security risks introduced by modern FPGA utilization models, this thesis establishes a comprehensive threat landscape and proposes novel, adaptive countermeasures that enhance the resilience of FPGA-based systems
Approval of Trump\u27s Handling of Economy Falls to All-Time Low in New Hampshire 11/19/2025
No full textSupport for President Trump\u27s handling of the economy continues to decline in New Hampshire, with tariffs most often cited as the reason. A slight majority support the deal to end the recent federal government shutdown, but more than two-thirds of Democrats oppose it. Bipartisan majorities believe furloughed federal workers and those who kept working during the shutdown should receive backpay, while half support extending Obamacare premium subsidies. Half of state residents disapprove of the recent sinking of suspected drug trafficking boats off the Venezuelan coast and nearly two-thirds oppose using the military to remove Venezuelan President Nicholas Maduro from power
Mass Residents Divided on Deal to End Shutdown, Support Extending Obamacare Premium Subsidies 11/19/2025
No full textMassachusetts residents are closely divided on the recent deal to end the federal government shutdown, with three-quarters of Democrats opposed. Most state residents support extending Obamacare premium subsidies, while nearly all support backpay for federal workers who were furloughed or continued working during the shutdown. Support for President Trump\u27s handling of the economy has declined, while approval of his handling of foreign policy remains low but has improved over recent months. Majorities in the state disapprove of sinking suspected drug trafficking boats off the Venezuelan coast and oppose attempting to remove Venezuelan President Nicholas Maduro from power
Despite Trump\u27s Urging, Majority of Connecticut Republicans Reject Abolishing Senate Filibuster 11/19/2025
No full textA majority of Connecticut Republicans oppose the U.S. Senate ending the filibuster rule, despite repeated requests by President Trump to do away with the long-standing practice. Trump also proposed eliminating mail-in voting nationwide, a proposal supported by state Republicans but rejected by nearly half of statewide residents. Connecticut residents overwhelmingly support federal workers who were furloughed or continued working during the shutdown receiving backpay while a majority support extending Obamacare premium subsidies. Approval of President Trump\u27s handling of the economy has declined, with tariffs cited as the reason by both those who approve and who disapprove. Half of Connecticut residents disapprove of recent strikes on suspected drug trafficking boats off the Venezuelan coast while a majority oppose trying to remove Venezuelan President Nicholas Maduro from power using the military
Virtual Machine, Real Threats: Demystifying Virtualization Obfuscation for Resilient Software Security
No full textSoftware obfuscation serves a dual purpose: It protects intellectual property and thwarts malware analysis, yet it can inadvertently enable advanced exploits and obstruct vulnerability discovery. This dissertation explores the multifaceted impact of obfuscation on software security, focusing primarily on virtualization-based obfuscators—widely recognized as among the most effective yet least understood forms of code obfuscation. This dissertation begins by demonstrating how conventional obfuscation can unintentionally facilitate sophisticated code-reuse attacks, enabling attackers to assemble more complex exploits. This dissertation then provides a systematic study of virtualization obfuscators, introducing a comprehensive taxonomy of VM diversification techniques, an automated tool to identify these techniques in real-world obfuscators, and an evaluation of how enhanced knowledge of VM internals can bolster deobfuscation. Finally, this dissertation investigates the challenge of vulnerability discovery in heavily virtualization obfuscated programs, proposing a hybrid fuzzing framework that combines runtime memory mutation and bottom-up fuzzing to effectively detect deep software flaws. By consolidating these efforts, this dissertation offers a roadmap for understanding, detecting, and mitigating modern obfuscation threats, ultimately empowering both the security research community and practitioners to build more resilient software