University at Albany, State University of New York
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Academic Freedom and Free Speech in Crisis: Elite Educational Institutions Response to Student Protests After October 7th
Full text linkHigher education institutions establish themselves as academic communities for students to explore various perspectives and values. When controversial topics arise, such as the October 7th Hamas-Israeli attack, students have the First Amendment right to voice their opinion and critically analyze the world around them. When institutions place limitations on this freedom— either through restrictive speech codes, administrative interventions, or the suppression of certain viewpoints—they risk undermining the very purpose of education and critical inquiry. This puts into question the entire responsibilities of these institutions as they limit and suppress student demonstrations. My research is necessary because universities serve as a bastion of academic freedom where ideas can be exchanged. Students should be able to encounter and engage in a dialogue of different opinions so they can enhance academic discourse. If limits are put in place for free speech, it begs the question of what upholds the opportunity for students to explore different perspectives. It is important to investigate why in the aftermath of the October 7th Hamas-Israeli attack, universities retreated so dramatically in free speech. Through an analysis of financial records, student demographics, and protest data of the top 25 private and public universities, I aim to investigate the factors influencing schools\u27 decisions to either retreat from or uphold free speech on their campuses
Integrable Deformations, T-Dualities and Higher Order Corrections in String Theory
Full text linkThis thesis explores the interplay of hidden symmetries and dualities in string theory, with a particular emphasis on the role of T-duality. As a fundamental symmetry of string theory, T-duality offers a powerful lens through which one can study integrability, solution-generating techniques, and quantum corrections, all essential aspects of modern string theoretic frameworks.
A central focus of this work is the application of the duality covariant formalism of Double Field Theory (DFT) to address problems involving integrable deformations and higher-order quantum corrections. We examine how generalized integrable models can be embedded into DFT and how the formalism captures hidden symmetries often obscured in traditional approaches. We also develop a systematic method to generate new string backgrounds by extending non-Abelian T-duality transformations, uncovering deeper connections between group and coset dualities. These constructions not only generalize known techniques like TsT transformations but also suggest intriguing links to holography and integrability. We also investigate quantum corrections to supergravity backgrounds using the DFT framework and construct exact solutions beyond the leading order in α ′. The special class of geometries identified in this work offers a simplified setting to probe quantum consistency of dual backgrounds, with implications for extending the formalism to even higher orders
Characterization of Corticotropin Releasing Factor Receptor 2 in Stress-Regulating Regions of the Mouse Brain
Full text linkSex differences in the morphology of the brain are thought to underlie the sex differences we see in anxiety and depression, where women are twice as likely to be diagnosed when compared to men. Stress, or a disruption to homeostasis, can exacerbate these mood disorders. Corticotropin releasing factor (CRF), and its receptors, play an important role in regulating the stress response. Binding of CRF with CRFR2 has been shown to reduce behavioral and neuroendocrine stress responses, yet whether there are sex differences in CRFR2 expressing neurons and stress-induced activation of these neurons in mice is unknown, in part due to a lack of specific antibodies for CRFR2. Here, we use transgenic reporter mice (CRFR2-Cretdtom) and subject them to both an acute stressor and a chronic stress paradigm, in order to assess sex differences in CRFR2 cell number and the stress activation of CRFR2 cells.
Higher levels of androgens in males, acting through androgen receptors (AR), provide a protective mechanism against the development of mood disorders. Androgens regulate the responsiveness of the hypothalamic-pituitary-adrenal (HPA) axis as well as anxiety- and depressive-like behaviors. Therefore, we investigated whether CRFR2 expressing neurons co-express AR, and if a sex difference exists in co-expression. We also determined whether circulating androgens regulate CRFR2 levels or the stress activation of CRFR2 neurons, by gonadectomy or sham-operating male CRFR2-Cretdtom mice.
The paraventricular nucleus (PVN) of the hypothalamus is a critical component of the HPA axis and driver of stress-related behaviors. It is known that CRFR2 is expressed in the PVN, yet little is known about the phenotype of these neurons or the behaviors they might govern. Here, we investigated the chemical composition of PVN CRFR2 cells with several colocalization studies and looked at where these cells projected centrally and peripherally with two tracing studies. Further, we investigated the impact of ablating PVN CRFR2 neurons, which gives insight into the role that these cells play in governing anxiety-and depressive-like behaviors
Dynamics of Mesoscale Offshore Wind Flows from an Observational and Modeling Perspective: Implications for Offshore Wind Energy
Full text linkMid-latitude coastal regions of the United States, such as the New York Bight (NYB), are playing a major role in the development of offshore wind energy. However, mesoscale dynamics of local and regional circulations in these offshore waters are poorly understood. The sea breeze, especially in the NYB, will play a key role in the development of offshore wind energy, given the favorable wind speeds and high capacity factors during periods of peak demand. With limited vertical wind profile observations available offshore, the ability to accurately forecast and understand the spatiotemporal extent of the sea breeze and often associated low-level jet (LLJ) is limited. While models can qualitatively reproduce the sea breeze circulation and LLJ, at this point, their performance in accurately depicting these features is underwhelming. The goal of this dissertation is to better understand and forecast the mechanisms behind LLJ development during sea breeze events, the relationship to atmospheric stability, and the direct impact on offshore wind energy development (including energy generation, wind farm waking, and load reduction). This dissertation addresses the limitations in understanding mesoscale wind flows such as the NYB sea breeze and associated LLJ through both an observational and numerical modeling analysis.
An observationally based methodology is developed to objectively identify sea-breeze days and their associated LLJs between 2010 and 2020, identifying an average of 32 sea breeze days annually. Most frequent during the warm season months, sea breeze events feature wind consistently backing to the south and strengthening around 1800 UTC, increasing wind speeds most during hours coinciding with high energy demand. LLJs are often associated with a sea breeze, and typically occur 150–300 m above mean sea level (AMSL)
Using Numerical Weather Prediction (NWP), specifically the Weather Research and Forecasting (WRF) modeling system on select summertime sea breeze events, all with an associated LLJ, sensitivity analyses test 18 different WRF configurations to optimize model performance in the NYB. Sea surface temperatures (SSTs) are initialized in the model using the Operational Sea Surface Temperature and Ice Analysis (OSTIA). These extensive tests reveal the importance of fine tuning the model to the study region and targeted weather conditions, as small changes to physics settings can have a significant effect on overall model performance. It was determined that the Mellor–Yamada–Janjić (MYJ) planetary boundary layer scheme, combined with the Noah land surface model and the urban parameterization turned off, is best suited to model these mesoscale summertime phenomena.
As one of the main driving factors behind LLJ intensification is the air-sea temperature difference, the relationship between the sea breeze and cold water coastal upwelling, another warm season regional phenomenon, is considered. A common problem in understanding cold water coastal upwelling is that satellite datasets have resolution limitations that make it difficult to detect localized and episodic pockets of relatively cold water along the coastlines. To isolate the influence of upwelling on the sea breeze, the input OSTIA satellite data is edited along the New Jersey coastline to perform three experiments; “GradientUpwell”, characterized by extreme cold water upwelling along coastline, “NoUpwell”, where any upwelling is removed, and “WarmAll”, where SSTs are uniformly increased based on current trends and future climate projections. Results show that cold water coastal upwelling locally increases atmospheric stability, decreasing the height and increasing the magnitude of the LLJ while also increasing the overall strength and inland propagation of the sea breeze.
Moving forward, as wind energy areas in the NYB are built out, it is not only important to understand the resource but the implications of the sea breeze and LLJ on wind energy generation. While gross capacity factors can currently be estimated, the wake effects, especially under stable conditions (such as during sea breeze events), are largely unknown. A clear understanding of stability in offshore regions is still developing, as high-resolution thermodynamic profiles are uncommon. With such an important relationship between stability and long-range (\u3e 50 km) offshore wakes, it has become increasingly important to be able to reliably estimate stability conditions in offshore regions. At early stages in wind energy development it is necessary to rely on mesoscale models such as the WRF modeling system, to estimate both stability and wake lengths. Given that there are no observations over the NYB region that measure atmospheric stability or incorporate the impact of wind farms, to gain confidence in WRF\u27s ability to reproduce wake effects and potential losses, the model is validated from flight data over wind farms in North Sea. As thermal stability is critical to understanding wake length, using vertical profiles taken during the flights, different metrics are evaluated to determine the best way to parameterize atmospheric stability from the WRF model. Finding show that the bulk Richardson number derived from WRF can be used as a reliable metric to classify stability and that wake lengths are well represented under stable conditions. With a better understanding of limitations and reliability in WRF\u27s wake model, the analysis over the North sea can be translated to better predict wind farm impacts in the NYB
Women in the Environmental Movement: An Examination of Maternalistic Rhetoric and its Relationship to Modern Environmentalism in the 20th Century
Full text linkFrom 1942 to 1953, the Hooker Chemical Company decided that an abandoned canal in Niagara Falls was the perfect place to dump 22,000 tons of toxic chemical waste, a common disposal practice that was largely unregulated by the local government. The company covered the 16 acres of hazardous waste with clay and sold it to the Niagara Falls Board of Education in 1953 for one dollar. With a warning included in the property deed that mentioned the presence of chemical waste, the company was excluded from all future liability.2 In the decades to follow, a suburban community would flower around the Love Canal site, with hundreds of homes and an elementary school built on top of the former landfill. By the late 1970s, the smell of chemicals would follow people in and outside their homes. Residents began to notice goopy, black sludge seeping into their basements while backyards filled with oily puddles. Children playing in the schoolyard suffered from mysterious chemical burns and rocks would miraculously catch fire if skipped across the water. Most alarming however, were the troubling health issues, ranging from skin rashes and seizures to miscarriages, birth defects, and cancer.
The Dynamics of Mystical Experiences: Interaction Effects and Distinct Contributions of MEQ-30 Factors
Full text linkMany participants in clinical trials of psychedelic-assisted therapy (PAT) report mystical experiences. Researchers often use the 30-item Mystical Experience Questionnaire (MEQ-30) to measure mystical experiences. Several studies have validated a four-factor structure of the MEQ-30, but only as a subset of items within broader versions of the scale (e.g., MEQ-43). As such, the factor structure of the standalone MEQ-30 remains unvalidated in English. Additionally, some data suggest that certain factors might be more strongly associated with psychedelic-associated outcomes than others, which could provide insight to enhance the therapeutic potential of PAT. The aim of this study was to examine the factor structure of the standalone MEQ-30 and investigate the relationship between its individual factors, their two-way interactions, and recalled changes in wellbeing following a significant psychedelic experience. Participants (N=585) responded on Prolific and passed two attention check items. Our exploratory factor analysis (EFA) revealed a four-factor structure of the MEQ-30, but several items loaded onto multiple factors, indicating a weak replication. All factors except Transcendence of Time and Space predicted changes in wellbeing. Significant two-way interactions emerged between the Mystical and the Positive Mood factors, and Mystical and Ineffability factors. Results suggest that mystical experiences likely have a larger impact on wellbeing when they accompany positive mood, supporting efforts to enhance set and setting in PAT. This study emphasizes the potential value of examining the latent factors of the MEQ-30, but overlapping items should be reconsidered to enhance its psychometric soundness
Comparison of Methane Emission Quantification Methods at Landfills in New York State
No full textGreenhouse gas (GHG) emission increases are a consequence of global population rise and economic growth. It is well known that carbon dioxide is the dominant GHG by mass, but methane has received increasing attention recently due to its high warming potential and relatively short lifetime of about a decade. Methane has several different types of both natural and anthropogenic sources including wetlands, waste management, energy, agriculture and farming, and wildfires, which makes tracking and reducing methane emissions a complex problem. The emission rates of each of these sources are highly uncertain due to differing emission estimation methods, which can be divided into either bottom-up or top-down approaches. Bottom-up methods are process-based and use calculations and emission factors to extrapolate to larger scales while top-down methods use direct measurements and inverse modeling to estimate emissions of a facility or region and scale downward. While there is no clear answer to whether one is more accurate than the other given that both methods have their own uncertainties, past studies have shown that bottom-up methods (GHG inventories) have underestimated emissions across multiple sectors. This research focuses on comparing bottom-up and top-down methods across landfill and other source sector facilities in New York State (NYS), while also evaluating differences between the methods themselves. Specifically, several methods, including a Gaussian Plume Dispersion (GPD) method, mass balance approach using Gauss’s Theorem, and a ratio calculation, will be applied to mobile research laboratory (MRL) and aircraft measurements to estimate facility emission rates. These methods are evaluated relative to each other for efficacy and compared with the EPA’s self-reported GHG Emissions Inventory to assess inventory accuracy. While the aircraft mass balance estimate is generally considered reliable due to including most of the upper air measurements of the plume, there is still uncertainty due to the lack of measurements below the lowest flight level, which can leave out vital details on the plume concentration and wind flow. The observed aircraft methane emission rates at the sampled landfills ranged from 161–3440 kg h-1 and, on average, indicated an underreporting of the 2021 self-reported EPA Inventory by a factor of 2. The MRL methane emission estimates were calculated using the GPD method and mass balance approach with mixed results. The GPD estimates fared well compared to the aircraft estimates but were highly sensitive to sampling routes, distance, and stability class determination. The MRL mass balance estimates were calculated using two separate estimated plume heights with very different results, which highlights this method’s dependency on an accurate plume height estimation. The MRL emission rates were also mixed in how they compared with the self-reported EPA inventory. However, for two landfills, the observations were higher than the self-reported inventory using every method. Lastly, the ratio calculation method is beneficial for estimating the emission rate of a pollutant not included in the emissions inventory but is highly dependent on the reference pollutant. While this information is helpful and valuable, long-term measurements are necessary to achieve an emission rate representative of true conditions. The results from this study will help scientists, policymakers, and regulators in NYS and beyond with interpreting landfill measurement data, evaluating emission estimation methods and their applications, and assessing how well the inventory accounts for emissions
Essays on Health Economics
No full textThe first chapter examines relationships between physicians exposed to new drugs’ clinical trials and prescribing. Clinical trials benefit patients directly by providing novel treatments, but little is known about the indirect effects of clinical trials on physician prescribing through localized knowledge spillover. This study examines whether exposure to a clinical trial of a new drug in a physician’s local geographic area affects the physician’s propensity to prescribe the drug, i.e. a localized knowledge spillover from clinical trial sites to physician. Utilizing the Medicare Part D prescribing patterns of more than 10,000 physicians across 29 new cancer drugs approved by the US Food and Drug Administration between 2014 and 2019, I find that an exposure to clinical trials of new cancer drugs increases the likelihood that physicians prescribe these drugs by 0.18 percentage points, representing a 14% increase relative to the average prescribing rate. Notably, the localized knowledge spillovers are more pronounced when the proximate clinical trial site hosts the leading researcher of the clinical trial and the physician is affiliated with the proximate clinical trial site. There is no clear difference on the localized knowledge spillover between trials before and after FDA approval. Nonetheless, the localized knowledge spillover is stronger for physicians graduating from higher-ranked medical schools, and with more experienced physicians, and male physicians.
The second chapter investigates the geographical accessibility of preferred pharmacies in the Medicare Part D market (PDPs and MAPDs) from 2010 to 2024, quantifying disparities in average and additional distance to nearest preferred pharmacy, and cost-savings across ZCTAs stratified by rurality and racial/ethnic composition. While preferred pharmacy networks have expanded, particularly in the MAPD market, a significant access gap remains, with 31.8% of ZCTAs lacking a preferred pharmacy in 2024, disproportionately affecting areas with high white and American Indian/Alaska Native (AI/AN) populations. For beneficiaries with access, the cost-benefit trade-off is highly favorable: the average cost saving of approximately $5.09 outweighs the minor average additional distance of 0.87 miles. Nevertheless, a persistent and significant rural-urban disparity was confirmed by multivariate analysis, showing that rural ZCTAs face up to 1.5 times longer additional distances to preferred pharmacies (P \u3c 0.01) compared to urban areas. Furthermore, ZCTAs with higher proportions of Hispanic or Black residents experience slightly greater additional distances, suggesting gaps in network inclusion, while AI/AN areas face the longest overall distances but the highest cost-saving potential. These findings highlight that while preferred networks lower costs for many, the resulting access and travel burdens are unevenly distributed, underscoring the critical need for policymakers to monitor network structures to ensure equitable access to affordable medications across all Medicare beneficiary groups.
The third chapter investigates the evolving income gap experienced by people with disabilities (PWD) among the aging US workforce (1996–2018). It moves beyond static analyses by employing a dynamic Recentered Influence Function (RIF) - Oaxaca-Blinder decomposition in conjunction with the Erreygers Index (EI) to systematically partition the change in income-related disability inequality over two decades. The core innovation is the simultaneous inclusion of subjective (HRS-based) and objective (O*NET-based) job demands as covariates. Findings reveal a growing, pro-poor income inequality in disability status over the period, driven primarily by the Structure Effect—changes in the economic penalty associated with job requirements—rather than the Composition Effect (changes in the distribution of workers). Specifically, structural volatility is maintained by an intense, offsetting battle between the valuation of occupational demands, where changes in the returns to Objective Physical Effort and Stooping/Kneeling/Crouching requirements are the dominant structural forces. Contrasting subjective and objective measures reveals that while workers’ self-assessments of demands are often higher, it is the structural valuation of specific, objectively measured physical demands that overwhelmingly dictates the dynamics of income-related disability inequality.
In summary, this dissertation investigates the interconnected factors required for achieving health equity by analyzing three dimensions: information flow, geographic access, and labor market structure. Chapter 1 establishes that clinical trial sites act as key knowledge hubs, demonstrating how information about new medical technologies, specifically drug adoption, primarily flows through geographic networks. Chapter 2 shifts focus to resource distribution, highlighting the geographic unevenness of access to affordable drugs, with rural and minority communities facing specific barriers. Finally, Chapter 3 examines the relationship between work and disability, arguing that widening inequality is driven by labor market structures that disproportionately value certain job demands over others, thereby shaping long-term health and economic outcomes. Collectively, these findings underscore that attaining health equity is a multi-dimensional challenge requiring targeted interventions across information transmission networks, equitable geographic access to healthcare resources, and structural reform of the labor market that mediates health and economic well-being
Assessing the Association between Air Pollution and Adverse Cardiovascular Outcomes: A Focus on Stroke Hospitalizations and Cardiovascular Disease Readmissions
No full textBackground
Cardiovascular disease (CVD) is a leading cause of mortality and morbidity globally and in the United States. Additionally, CVD is a primary reason for hospital admission and imposes a significant economic burden. Ambient air pollution is recognized as a significant and preventable risk factor for CVD. While particulate matter (PM) as an air pollutant has been studied extensively, the research regarding ultrafine particles (UFPs or PM0.1) and their impact on health is lacking. This study aims to bridge the gap by examining the association of UFPs and adverse cardiovascular outcomes: Aim 1 investigates the association between air pollution (with a focus on UFPs) and stroke hospitalizations; Aim 2 assesses the impact of UFPs on CVD readmissions, including stroke-related hospital readmissions.
Methods
A time-stratified case-crossover design was utilized to assess the association between UFP exposure and health outcome in our study. The conditional logistic regression model was used to perform the time-stratified case-crossover study. Our health data source was from the New York State Department of Health Statewide Planning and Research Cooperative System (SPARCS). CVD was identified using International Classification of Diseases (ICD) codes with primary diagnosis codes for CVD from SPARCS. Our environmental data including air pollutants and meteorological factors were obtained from the data source simulated using a validated chemical transport model with aerosol microphysical simulation, GEOS-Chem/APM. All analyses were conducted using SAS 9.4 and R 4.3.
Results
Aim1: We found significantly positive associations between UFP exposure and overall strokes, but mainly in ischemic stroke (IS) (ERIQR range: 0.8% to 4.4%), not hemorrhagic stroke (HS). The adverse effects of UFPs were stronger for females, non-Hispanics, Blacks, older adults (especially 65-69 years) and during winter. We also found daily IS double-peak at 6 am and 8 pm. The UFP-IS threshold appeared to be when UFP count was around 6000 particles/cm3. While there were no significant differences in hospital stay lengths and total costs for high vs. low UFP exposures, the number of comorbidities were significantly higher on days with high UFP concentration (difference = 0.26, P \u3c 0.05).
Aim2: UFP exposure was positively associated with overall CVD readmissions for all readmission windows (30-, 60-, 90-, 180- and 360-day), with the highest association at lag0-6 days (ERIQR ranged from 4.4% to 6.2%, all P\u3c 0.05). The adverse effects of UFPs were stronger for male, Hispanics, White, adults aged 60 and older, those with Medicaid insurance, those who lived in NYC, and during winter. We also found the UFP impacts varied by CVD subtypes and their associated readmission windows.
Conclusion
UFPs had significant adverse effects on stroke hospitalizations and CVD readmissions. The effects varied by demographics and seasonality. The findings of this study highlight the importance of understanding the impact of UFP exposure to public health and provide evidence to guide air-pollution-related interventions
Effects of Formative Assessment on Students’ Regulation of Learning: A Meta-analysis
No full textDoes formative assessment (FA) promote self-regulated learning (SRL)? Theoretically, FA has long been believed to facilitate SRL due to their overlapping conceptual frameworks, yet empirical evidence has remained scattered and inconclusive. This study presents the first comprehensive, large-scale meta-analysis to examine whether, to what extent, for whom, and under what conditions FA enhances SRL.
Following a preregistered, PRISMA-guided protocol, we systematically searched the literature from 1998 to 2024 and synthesized 999 effect sizes from 138 studies (n = 23,293 students) using multilevel meta-analytic models that accounted for dependent effects. Across educational levels and contexts, FA, on average, demonstrated a statistically significant, positive impact on SRL (g= .46, 95% CI [.35, .58]). Moreover, FA was found to have statistically significant positive effects across all SRL components—cognitive processes, metacognition, motivational regulation, and regulation of behavior and context—though with considerable heterogeneity. Moreover, FA was found to have statistically significant positive effects across all SRL components—cognitive processes, metacognition, motivational regulation, and regulation of behavior and context—though with considerable heterogeneity.
A comprehensive set of theoretically derived moderators was examined to examine for whom and under what conditions FA most effectively promotes SRL. Two moderators, the type of SRL outcome measure and the number of feedback sources, emerged as statistically significant, suggesting that methodological choices and the integration of multiple feedback sources shape observed effects. While other intervention, learner, and contextual factors were not statistically significant, consistent descriptive patterns provide insights that may challenge several prevailing theoretical assumptions about the relationships between FA and SRL.
The credibility of outcome in primary studies was assessed using What Works Clearinghouse standards, and the certainty of synthesized evidence was rated with the GRADE framework. Although the overall effect was large, the certainty of evidence was rated low due to substantial heterogeneity, underscoring both the promise and fragility of the current evidence base.
Overall, this study lends robust empirical support to the long-held theoretical claim that FA promotes SRL development while advancing a refined theoretical and methodological agenda for future research. Implications are discussed for (a) educators in tailoring FA to support SRL, (b) policymakers in making evidence-based decisions, and (c) researchers in advancing more precise, transparent, and context-sensitive investigations