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Pleiotropic Functions of WIDE AWAKE in Circadian and Non-Circadian Regulation of Behavior
Full text linkConditioned fear learning is crucial for survival, as it enables animals to anticipate and react to potential threats based on past experiences. In this thesis, I investigate the role of mWAKE, previously studied as a clock-output molecule, in this process. First, I focus on mWAKE in the central amygdala (CeA) and characterize its expression and projections. These data revealed that mWAKE is expressed in multiple clusters of defined CeA neurons, including those that play key roles in fear learning and memory. Although conditioned fear learning has previously been described as a circadian-dependent process, I unexpectedly found that neither mWAKE, nor the core clock molecules PER2 or BMAL1, exhibit rhythmic expression in the CeA. Knockout of mWAKE in the CeA impairs fear learning and memory, indicating that mWAKE function is necessary for this process. Moreover, my data suggest that, while mWAKE is not under circadian control in the CeA, its expression is dependent on fear learning. Next, I examine the function of mWAKE in the suprachiasmatic nucleus (SCN) by conditionally knocking it out in this region. These data suggest that mWAKE is not required in the SCN for robust circadian rhythms. In collaboration with a labmate, I helped examine the function of the mWAKE in the lateral amygdala (LA). We found that mWAKE exhibits rhythmic expression in the LA and labels a local circadian oscillator in this brain region. These findings demonstrate that mWAKE plays a critical role in modulating emotion-dependent responses, in a circadian- or non-circadian manner. Overall, this study provides new insights into the functional significance of mWAKE in the amygdala and its broader implications for the temporal regulation of fear- and anxiety-related processes
ASSESSING THE IMPLEMENTATION OF COMPETENCY-BASED EDUCATION AND ITS INFLUENCE ON L2 SELF-EFFICACY AND MOTIVATION
No full textGrounded in Bronfenbrenner’s ecological systems theory, this convergent mixed‑methods study examined how competency‑based education (CBE) practices shape Chinese high‑school students’ L2 English self‑efficacy and motivation at a high school in Southeast China. Four research questions guided the inquiry, regarding (1) the effect of CBE exposure on L2 English self‑efficacy, (2) the influence of Western cultural identification on motivation, (3) the fidelity of CBE implementation in the school’s English as a Foreign Language (EFL) classes, and (4) the alignment of CBE teaching strategies with motivation research. Sixty‑five Grade 10–12 students completed a merged questionnaire that combined Wang’s (2004) English self‑efficacy scale, the American Institutes for Research’s CBE360 student experiences survey, and items measuring cultural internalization. Six English teachers completed the CBE360 teacher practices survey, and 232 time‑stamped events were captured during five non‑participatory classroom observations. Independent‑samples t‑tests and Pearson correlations revealed that students reporting higher CBE exposure demonstrated significantly greater L2 self‑efficacy (d = 0.65; r = .52, p < .001). Identification with Western cultural elements showed only a weak association with autonomous motivation (r = .26) and no significant relationship with attitudes toward English or confidence in use. Triangulation of student, teacher, and observational data exposed sizeable perception-practice gaps: Learning targets and mastery‑based pacing were rated as common yet observed in fewer than 3% of classroom moments. A review of the literature confirmed that core CBE strategies, when implemented well, are empirically linked to improvements in key motivational constructs, but uneven implementation dilutes their potential impact. Recommendations include targeted professional learning, policy realignment, and more systematic monitoring to help bridge the practice-perception gap in order to more fully realize CBE’s learning and motivational benefits
AI-Driven Policy Analysis: NLP And Multi-Level Modeling for Complex Systems
No full textPolicymakers today face an increasingly complex landscape marked by limited resources, fragmented information, and interdependent socio-environmental challenges. This dissertation develops a series of complementary methodologies that leverage natural language processing (NLP) and multi-level modeling to enhance different phases of the policy analysis cycle, from policy problem definition to intervention simulation.
The first part of the dissertation focuses on NLP for policy analysis. Using case studies such as the TRIPS waiver debate and the digital health policy discourse in India, it demonstrates how real-time text mining, topic modeling, and co-occurrence analysis can uncover shifts in stakeholder positions, identify emergent policy windows, and surface hidden dynamics within public narratives. Results show that NLP pipelines enable timely, structured insights into political framing but require careful attention to preprocessing choices and validation frameworks to avoid bias and misrepresentation.
The second part of the dissertation develops methods to simulate policy interventions in complex systems. To assess community resilience during health crises, we develop a pandemic-focused COPEWELL model using system dynamics to generate a community resilience index. For suicide prevention among Indigenous American youth, we construct a multi-level model that combines system dynamics with microsimulation to evaluate how variations in leadership commitment, funding levels, and program management affect the sustainability of interventions and the reduction of youth suicide risk. To explore adolescent dating relationships and substance use, we employ an attention-based neural network augmented with SHAP value analysis, identifying which behavioral and contextual factors most strongly predict relationship disruptions. To quantify the economic effects of climate anomalies, we build a multi-level ENSO-climate model that traces how El Niño and La Niña events propagate through agricultural production and influence broader macroeconomic indicators, revealing key feedback loops between environmental shocks and economic performance. These models provide insight into the co-evolution of human behavior, environmental shocks, and systemic feedback, while maintaining transparency and stakeholder relevance.
This thesis presents a broad applicability of NLP and multi-level modeling for policy analysis. It demonstrates how real-time text based policy insights and ,multi-level system simulations can support adaptive and transparent policymaking in complex socio environmental settings
FROM CLASSROOM DESIGN TO PEDAGOGICAL SUCCESS: ENHANCING TEACHERS’ ENVIRONMENTAL COMPETENCE AND EFFECTIVE TEACHING PRACTICES
Full text linkThe physical learning environment (PLE) is a valuable yet often overlooked educational resource that can shape student learning outcomes and pedagogical goals. Despite a growing body of research that affirms the impact of PLEs on student engagement and academic performance, many teachers lack the knowledge, confidence, and support to fully leverage their PLEs. This dissertation explores the concept of teacher environmental competence, a teacher’s ability and confidence to maximize the PLE for pedagogical effectiveness.
Anchored by Bronfenbrenner and Morris’s (2007) PPCT model, a comprehensive literature review explores the interaction between teachers and their PLEs, uncovering factors that influence the teachers’ environmental competence, including: culture, competition, historical design constraints, and teacher knowledge and beliefs about PLEs. Based on the literature review, a needs assessment conducted at an independent school employed a mixed-methods approach to assess teachers’ environmental competence. Findings from a facilities survey, focus group discussion, open-ended questionnaire, and Likert-scale question indicated that while teachers articulate the importance of PLE design, constraints such as limited training, funding, time, space limitations, and lack of institutional policies impede their ability to implement best practices. The needs assessment findings and a second, targeted literature review on teacher professional growth, broadly, and teacher use of learning spaces, specifically, informed development of a professional development (PD) proto address the gap between what teachers say and what they do with regard to their learning environments.
Drawing on research suggesting the inclusion of key design components critical for professional development to have a lasting impact on teachers’ professional practice, a year-long, cohort-based professional development program was designed with the focus of increasing teacher environmental competence. Key components of the program, illustrated in full, include action research, peer collaboration, one-on-one coaching, and structured reflection. The dissertation provides a detailed overview of the PD exemplar, including session outlines, learning activities, accompanying materials, video resources, and assessment tools. In the final section, a personal reflection on the product and process describes key insights that emerged during the design, including the role of teacher agency, contextual relevance, and inquiry as critical drivers of meaningful change in teacher environmental competence
Reassessing the CHRIS: An Evaluation of Proposed CA SHPO Online System as an Appropriate Consolidation of the California Historical Resources Information System
Full text linkSince 1972, the California Historical Resources Information System (CHRIS) has served as the official cultural resources inventory for the California State Historic Preservation Officer (SHPO) and the Office of Historic Preservation, but in the 30 year effort by SHPO inventories across the country to digitize their repositories and bring them online to enhance user access and data security, California has fallen far behind much of the nation. After making several attempts to standardize workflows and implement modernization plans since the mid-1990s, efforts are underway to develop a single consolidated digital inventory system called CA SHPO Online.
CA SHPO Online is currently being developed on the Arches heritage database management platform, an open-source software suite developed by Getty Conservation Institute in conjunction with the World Monuments Fund. Arches is built on platform of open-source software tools, including Elasticsearch, PostGreSQL and several OSGeo libraries, a departure from the CHRIS’ present proprietary Microsoft Access and Esri ArcGIS Desktop workflow. With the impending retirement of ArcGIS Desktop by Esri, a migration of the CHRIS’ workflow is necessary to ensure its data security and to avoid disruptions in its service capacity, but is Arches the appropriate platform? Further, is it secure enough to protect sensitive confidential archaeological resource data from unauthorized access while also allowing unrestricted online access to non-confidential historic built environment data?
This study evaluates the history of the CHRIS and its past streamlining efforts, the legal basis for SHPO inventories and their associated access restrictions, the appropriateness of Arches and its open-source components as management systems for confidential data on government servers and what gaps must a digital CHRIS inventory overcome to be successful in the eyes of external stakeholders
Oral history of Tina Queen, LaShella Bacon, Monique Martin, and Greta Goodwin
No full textIn this interview, Dr. Warren Hayman spoke with several members of the Dunbar Hopkins program including Tina (Lockett) Queen, LaShella (Stanfield) Bacon, Monique (Walston) Martin, and Greta Goodwin. This focus group centered on individuals who ended up in professional positions focused on education.
Tina graduated from Dunbar in 1990. She was one of a few students who also played sports; she played basketball and went on to secure a 4-year scholarship for basketball at Coppin State University, also gaining acceptance into the Helene Field Nursing School. She transitioned her major into Adaptive PE. Later, she began teaching physical education and health and has been in the field for 30 years. She is currently the Athletic Administrator at Reginald F. Lewis High School. Tina reflects that the Hopkins Dunbar program structure really worked for her, and she felt the students held each other accountable. Tina shares that “Dunbar was truly a family” and helped her develop into the person she is today. She explains her professional journey and mentions financial difficulties.
LaShella graduated from Dunbar in 1990 and is currently the Principal of Cross Country Elementary Middle School. She has been in education for 25 years and held many roles including teacher, instructional support, academic liaison, and principal. She attended Frostburg University to study physical therapy but ended up switching to psychology. She was a substance abuse counselor for several years, then went back to UMBC to get her master’s degree in education. LaShella speaks to how Dunbar was a family and that peers had a competitive spirit of excellence. She shares opportunities students had as part of the program including working at the Johns Hopkins Hospital and elaborates on how the program helped her once she reached college. She reflects on shifting her career to psychology and then education. She offers advice for today’s students: “Advocate for yourself, seek opportunities, get in front of people who could help you develop who you are. Don't be afraid to ask for help.”
Greta graduated from Dunbar in 1995. She went to North Carolina Agricultural and Technical State University where she majored in engineering but changed to biology. She then went to Morgan State University and became a science teacher. Greta reflects on her recent interests in pursuing nursing. She is currently the Principal at Mary E. Rodman Elementary School and has worked for Baltimore City Schools for 25 years. She shares that the Hopkins Dunbar program impacted her life by helping her understand what a good teacher should do and how to connect with students. She mentions a couple of teachers that helped her, Ms. Nash and Ms. Robinson. She encourages today’s students to keep their goals front and center, stating “you can do anything you want to do!”
Monique graduated from Dunbar in 1990. She has worked in education for nearly 30 years. She graduated from Bowie State University after studying elementary education and went on to get her master’s degree at Johns Hopkins University. Monique currently works supporting educational equity and justice for the Delaware Department of Education. She explains the many different roles she’s held, from Ohio to Georgia, and from Virginia to Maryland. She reflects that the Hopkins Dunbar program challenged her and was made up of members of the community. It helped her understand that every possibility she wanted to manifest was within her reach, which is not something she believed in before growing up in Baltimore. She shares that learning at JHU and JHH was fundamental to her and exposed her to folks like Dr. Levi Watkins and Dr. Ben Carson. Monique indicates that going into education for her was a revolutionary act. Each interviewee reflects on their continued personal connection with Dr. Hayman and offers advice for current Dunbar students
Cosmology Large Angular Scale Surveyor: From Instrumentation to Beyond the Standard Model
No full textLarge angular scale polarized microwave emission is key to probing both Galactic structure and cosmological phenomena. Polarized Galactic sources, including synchrotron, thermal dust, and potentially anomalous microwave emission, trace the Galactic magnetic field and the interstellar medium. A deeper understanding of the Galactic signal will aid in unraveling the polarized cosmic microwave background (CMB) through effective component separation. CMB E-modes at ℓ<20 offer strong constraints on the reionization optical depth, while B-modes potentially hold direct evidence of inflation through primordial gravitational waves. The Cosmology Large Angular Scale Surveyor (CLASS), located in the Atacama Desert of northern Chile, is a telescope array that surveys the sky with single-frequency-band telescopes centered at 40 GHz and 90 GHz, as well as a dual-band 150/220 GHz telescope. Ground-based observations face challenges in recovering large-scale information due to low-frequency 1/f variations from atmospheric, instrumental, and calibration drifts. CLASS maintains long-term stability via front-end polarization modulators. I will describe the design, fabrication, and performance of a new polarization modulator, the rotating reflective half-wave plate, which nearly doubles the linear-polarization mapping speed of the 90 GHz telescope and helps us better understand systematic errors from the modulation step. I will also present an analysis of polarized synchrotron radiation based on CLASS 40 GHz and WMAP K/Ka/Q-band (at 23/33/41 GHz) data, featuring sensitivity-improved polarization maps at 40 GHz and the spatial variation of the polarized Galactic synchrotron spectral index. Finally, I will look ahead to forecast CLASS and LiteBIRD's potential to corroborate four large angular scale temperature anomalies of CMB. We found that the ΛCDM model predicts weak correlations between T-mode and E-mode statistical tests for anomalies, suggesting that future polarization experiments will generate independent measurements that may firm up the significance of the anomalies in temperature, eventually shedding light beyond the ΛCDM model
ON THE EXCITATORY-INHIBITORY STRUCTURES IN NATURAL AND ARTIFICIAL INTELLIGENCE
No full textNatural intelligences (NIs) display remarkable learning efficiency --- adapting rapidly from limited experience --- whereas artificial intelligences (AIs) often rely on vast datasets and extensive computation. What inductive biases enable such disparity? This dissertation explores the role of biological wiring constraints --- particularly weight polarity --- in driving efficient learning and function representation in both brains and deep networks.
In Chapter 2, we investigate weight polarity, a structural prior shaped during development in natural systems, where synaptic weights retain fixed signs (excitatory or inhibitory) while magnitudes adapt during learning. We show that when polarity patterns are appropriately set a priori, artificial networks learn faster with fewer samples. However, we also delineate scenarios where fixing polarity casts a disadvantage.
In Chapter 3, we address the question: why do brains and deep networks have negative (inhibitory) weights? We leverage the universal approximator theorem and prove that networks with non-decreasing activation functions and non-negative weights are not universal approximators. This result provides the first general justification --- beyond function-specific explanations --- for the necessity of inhibitory connections in brains and negative weights in artificial networks, offering geometric insights into the functional limitations of purely excitatory architectures.
To further bridge structure with function, in Chapter 4, we develop XORness, a normative and testable measure of functional complexity. Using whole-brain electron microscopy (EM) connectomes of larval and adult Drosophila, we show that actual brain networks --- and synthetic networks with matched connectivity statistics --- exhibit high XORness, suggesting that evolution favors topologies capable of representing complex nonlinear functions. Specifically, our simulations predict that maximal functional complexity occurs at 72% and 79% excitatory neurons in larval and adult Drosophila, closely matching empirical estimates (67% and 74%, respectively). These optima also require higher connectivity in inhibitory neurons --- another feature corroborated by EM data.
Together, this work reveals how biological constraints on polarity shape the functional capacity of both natural and artificial intelligences
NAVIGATING THE PATH TO CEO: BARRIERS AND FACILITATORS FOR BLACK EXECUTIVES IN FORTUNE 500 COMPANIES
No full textBlack or African American professionals encounter substantial obstacles in attaining chief executive officer (CEO) roles within Fortune 500 corporations, despite possessing leadership ambitions and qualifications comparable to their White peers (Livingston & Pearce, 2009; Roberts & Mayo, 2019; Ray, 2019). Disparities underscore deeply rooted systemic inequalities reinforced through structural, cultural, and interpersonal mechanisms, which impede career progression at every organizational level. Significant barriers include limited access to top profit-and-loss (P&L) roles, racial bias in social and professional interactions, and broader systemic inequalities that contribute to the racial wealth gap. As of 2022, Black families held just 15.8% of the median wealth of White households, highlighting the economic effects of structural barriers. Addressing disparities is essential for promoting social mobility and could boost the U.S. economy by $1.5 trillion by 2028 (Hewlett & Ihezie, 2022; McKinsey Institute, 2019). This study, grounded in social dominance theory (SDT; Sidanius & Pratto, 1999), explores how legitimizing myths, racialized organizational hierarchies, meritocratic myths, and ethnic prejudice sustain exclusionary practices in corporate leadership. This research uses multiple methods, including surveys on social dominance, racial attitudes, resilience, workplace aggression, interviews, and DEIA policy analysis, to explore (1) barriers and facilitators to advancement, (2) the effects of race-based hiring and promotion on careers and salary, and (3) coping and resilience strategies in racialized workplaces. Findings reveal mechanisms that sustain racial hierarchies and offer recommendations for organizational change to challenge dominance-oriented cultures
Examining the performance of the Alaska Youth Risk Behavior Survey sugar-sweetened beverage items: A mixed methods evaluation
No full textBackground
Sugar-sweetened beverage (SSB) consumption can negatively affect health, and intake of these beverages is high among U.S. adolescents. In Alaska, the Youth Risk Behavior Survey (YRBS) has been used to monitor SSB consumption and support prevention efforts for over a decade, but the YRBS SSB items have not been evaluated in the state or local context.
Methods
A three-phase sequential mixed methods evaluation was used to examine the performance of four Alaska YRBS SSB items. First, cognitive interviews were conducted with Alaska high school students using a five-step data collection and analysis process. Next, a panel of experts reviewed the proposed revised items and made final revisions. In the last phase, the revised items and a calculated total SSB consumption measure were compared to reference data obtained through Automated Self-Administered 24-hour (ASA24) dietary recalls collected from Alaska high school students. Bland-Altman plots, Spearman rank correlation coefficients, and McNemar’s exact tests were compared to assess relative validity.
Results
Cognitive interviews (n = 22) revealed construct validity threats, particularly in the categorization of sports drinks, and measurement error related to the response option structure. Problems with terminology and example beverages were also detected. The expert review panel provided information on programmatic priorities, including the importance of the total SSB measure and one-time-per-day threshold. Revisions included a combined sports and energy drink item, collapsed response options, and changes to terminology and example beverages. Bland-Altman plots showed proportional bias, with the YRBS producing larger SSB consumption values than the ASA24 when consumption was low and smaller values when consumption increased. All Spearman rank correlation coefficients were statistically significant, ranging from 0.36 (soda) to 0.48 (other SSBs). Finally, at the one-time/beverage-per-day threshold, there was only a significant difference in proportions (YRBS – ASA24) for other SSBs (-19.8%, p < 0.001).
Conclusions
Findings from the cognitive interview and validation phases are consistent with previous research, and revisions to the items align with programmatic priorities of Alaska YRBS partners. The revised items also performed well when used to calculate total consumption at the one-time-per-day threshold. Future cognitive and psychometric testing in a variety of settings is warranted