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This dissertation explores the impact of diversity, intersectionality, and diversity management on job satisfaction within the federal workforce. The three constituent studies use disaggregated ethnoracial data from the Federal Employee Viewpoint Survey (FEVS) to examine the effects of demographic congruence, demographic heterogeneity, and perceptions of diversity management practices on the outcome variable of job satisfaction.
The first study tests the effects of demographic congruence (representation) and heterogeneity (diversity) on job satisfaction across federal agencies for members of different ethnoraces by employing mixed-effects models to a combination of 2020 FEVS data and FedScope data on agency-level demographics. Findings from this study show that increased demographic congruence is positively associated with job satisfaction for all minority groups and that demographic heterogeneity, in contrast, presents a more complex relationship, where initial increases in diversity are linked to lower job satisfaction but later rebound past a certain threshold. The second study explores how intersectional identities—race and gender—influence job satisfaction and are mediated by perceptions of DEI management. By using mixed-effects models on 2022 FEVS data, the results show that minority status is generally associated with higher job satisfaction but that gender and perceptions of DEI Management moderate this relationship. For all ethnoracial groups and genders, perceptions of positive DEI management—especially equity and inclusion—are positively associated with job satisfaction. The third study employs Random Forest models on 2022 FEVS data to predict job satisfaction based on demographic and job-related factors. All models achieve high predictive accuracy across various racial and gender subgroups, with intrinsic work experience, job inspiration, satisfaction with pay, and personal attachment to the organization emerging as the most influential factors for all. Noticeable differences between ethnoracial and intersectional groups emerge. These results highlight the potential for AI techniques to enhance public administration by offering practical tools for HR managers to proactively address issues related to employee satisfaction, especially as it pertains to specific populations.
This dissertation advances the theoretical understanding of social identity and diversity management while offering practical guidance for improving job satisfaction in the federal workforce. All three studies show that targeted and effective DEI management practices can improve employees' job satisfaction. As public managers respond to policy changes and adjust their approach to diversity, this research can help improve data-driven strategies to better address their workforces’ needs.
With the rise in antibiotic resistance (AR) and multidrug-resistant (MDR) bacteria, there is a need for novel antimicrobials that can exert antibacterial action via multiple mechanisms. Nanoparticles such as silver nanoparticles (AgNP) can serve as a potential alternative due to their unique optical and physiochemical properties along with their innate broad-spectrum antibacterial activity. AgNPs antibacterial property is associated with the release of silver ions (Ag+), which is a slow process taking up to days to achieve effective antibacterial levels. Recent findings indicate that combining photodynamic inactivation (PDI) with AgNP shows antibacterial synergy. This research is aimed at developing light-activated silver nanoparticles and investigating their light-responsive Ag+ release kinetics to understand their role in antibacterial synergy.
Herein, protoporphyrin IX conjugated on the AgNP surface (PpIX-AgNPs) was developed and Ag+ release kinetics were investigated to correlate the Ag+ release kinetics to the antibacterial synergy of PS-AgNP. These PpIX-AgNPs serve as excellent light-activated antimicrobial agents and this antibacterial action was demonstrated in antibiotic-resistant bacteria (ARBs). The antibacterial action of this light-activated PpIX-AgNP was further modulated by adopting a dual-step irradiation strategy to ensure the controlled release of Ag+. Finally, this research includes a preliminary study demonstrating the transport of nanoparticles within biofilms and light-activated inhibition of Vibrio cholerae biofilms. This research provides crucial knowledge for designing light-responsive silver-based antimicrobials for potential wound-healing applications.
Superoscillation is a physical phenomenon of the local oscillations of a band-limited signal that fluctuate faster than the fastest Fourier component of the signal. In recent years, superoscillation leads to a method of super-resolution imaging, named superoscillatory imaging, and plays an important role in many areas, such as remote sensing and biomedical research. This dissertation investigated a key lens element for achieving superoscillatory imaging. Then, a vector-superoscillatory field provided a solution to a major problem associated with superoscillatory imaging. Lastly, the partial coherence effect, specifically circular coherence, was studied for vortex beam propagation in free space and can be considered in the quality of superoscillatory imaging.
This dissertation work began by studying the existing methods for designing filters to create superoscillatory fields in the image plane. A design method by Smith and Gbur tailors a superoscillatory field in two dimensions, from which a filter is calculated with both an amplitude profile and a phase profile (a complex filter). Accordingly, the first study of this dissertation aimed to simplify a complex filter into a filter with only one profile: an amplitude profile or a phase profile, which make the filters fabrication-friendly. This study derived the mathematical formula for generating simplified filter profiles (leading to the same superoscillatory field by complex filters). A step-by-step example of creating such simplified filters was demonstrated by following this approach. Performance criteria of the designed filters were discussed, including but not limited to energy efficiency. The designed phase-only filter showed an energy efficiency same as that of the complex filter.
The second study of this dissertation provided a method to eliminate the sidelobes that are inevitable to superoscillatory fields and causes a problem to superoscillatory imaging. As light is a transverse electromagnetic wave, the orientation of scattering patterns of Rayleigh scatterers is polarization-dependent. Then, superoscillatory fields with two polarization states (referred to as vector superoscillatory fields) were created, so that the sidelobes can be avoided in the imaging process. This study proposed an imaging system with vector superoscillatory illumination. Super-resolved scattering images of Rayleigh scatterer patterns were simulated under a vector superoscillatory illumination, whose resolution surpassed those obtained from a conventional imaging system. A device was proposed for generating a vector-superoscillatory field.
Light sources with circular coherence have perfectly coherent points on any concentric rings of their transverse planes. In the third study, we investigated from their ability in carrying optical vortices in free space to the self-focusing effect. Circular coherence was imposed onto vortex beams (with spiral phase structures). The free-space propagation of circularly coherent vortex beams showed that optical vortices remained their positions on free-space propagation and the beams revealed a focal region. This study also provided a model for propagating rotationally symmetric beams using two-dimensional Hankel transform. The self-focusing effect of circular coherence can be considered on further reducing the spot size of a superoscillatory field.
These three studies together make the superoscillatory imaging technique have more potential to be implemented.
Emotional ambivalence – the experience of dual-valenced emotions – is becoming increasingly relevant to the process of leadership. Leaders are consistently faced with nuanced, complex situations that simultaneously elicit positive and negative emotions. Despite increased empirical investigations into leader emotional ambivalence at work (Rothman et al., 2017; Rothman & Melwani, 2017), leader emotion theorizing makes critical assumptions that limit understanding of the cognitive and social role of emotional ambivalence in the social process of leadership, including the leaders themselves and those that interact with leaders. I conduct a systematic literature review to show how past work conceptualizing emotional ambivalence as the experience of conflicting emotions and the default treatment of leader emotions as singular can be misleading. In this dissertation, I advance the definition of emotional ambivalence beyond emotional conflict and outline a new integrative process of leader emotions including the appraisal, experience, expression, and perception of complex emotions and their general outcomes.
This thesis explores advanced manipulation and control of light’s structure, focus-
ing on the degrees of freedom such as phase, polarization, and coherence. The research
primarily addresses the generation, propagation, and application of structured optical
beams, with significant implications for imaging, communication, particle manipula-
tion, microscopy, and quantum state engineering.
A key area of investigation is the use of orbital angular momentum (OAM) in optical
beams. These beams, characterized by a conserved topological charge, have shown
promise in free-space optical communication due to their resilience against amplitude
and phase disturbances. The research highlights the development of partially coherent
beams that maintain deterministic vortices at specific propagation distances, achieved
through fractional Fourier transforms (FracFTs) applied to Schell-model vortex beams
in the source plane.
Another significant focus is on polarization singularities in fields with two harmonic
frequencies, i.e. Lissajous singularities. The study reveals stable Lissajous singulari-
ties within the beam core, offering new opportunities in high-precision metrology and
secure communication. Additionally, Young’s interference experiment with bichro-
matic vector beams is simulated creating Lissajous-type polarization singularities,
enhancing the fundamental understanding of the conditions under which Lissajous
singularities can be created in interference.
This work integrates these findings into a comprehensive framework for structured
coherence beams, advancing theoretical models and experimental techniques. The
resulting beams demonstrate unprecedented control over intensity, phase, coherence,
and polarization, paving the way for innovative applications in optical science and
engineering.
Binary-phase diffraction gratings are optical components that distribute an incident light beam to diffraction-order directions, due to the periodic modulation of the refractive index within the grating volume. Gratings are essential components in fields like acousto-optics, holography, spectroscopy, and are typically fabricated using lithography. High-efficiency first-order gratings are particularly important in spectroscopy, since first-order spectral diffraction spatially separates the incident wavelengths to be measured. Designing a linear grating consists of iterations of numerical simulations for a given phase profile, to determine grating diffraction efficiencies. The inverse design process, specifying the efficiencies desired and obtaining the phase profile, is very challenging and can lead to unstable solutions. In this research effort, a two-step design process is used. The general parameter ranges are determined first based on design goals, and then more rigorous simulations are performed to “map-out” the diffraction efficiency as a function of a limited solution parameter-space search. The phase profile that matches the design goals is then chosen.
The first lithographic step in grating fabrication is to create a mask for the grating’s features on a photoresist and develop the device profile. Etching the features into the substrate with a reactive-ion plasma process results in a permanent optical component. The study addresses certain fabrication challenges in binary grating fabrication, associated with areal scaling from a 25×25 mm2 surface area to a much larger 101×101 mm2 desired component size. The greatest challenge is to achieve the proper etch depth for the device function, which is mitigated by multiple masking and etching steps.
The Littrow-mount configuration is commonly employed to enhance a grating’s first-order efficiency performance, but can cause ghost images due to light recombination, a problem often controlled with antireflective treatments. Part of the research effort presented here uses random antireflective surface structures (rARSS), which are randomly distributed conical nano-features, etched into dielectric surfaces to minimize their Fresnel reflectivity. These structures were fabricated and tested on cylindrical lenses and freeform elements, showing significant transmission enhancement in the visible spectrum, minimal wide-angle scattering losses, and no notable wavefront distortion. rARSS were then applied to proof-of-concept (POC) reactive-ion plasma-etched (RIPLE) gratings for the VIRUS2 spectrograph, which was designed for Littrow-mount configuration. The rARSS-treated gratings successfully suppressed the undesirable reflection from the zeroth-diffraction order, enhanced the transmitted first-order, and reduced Littrow ghost intensities to four orders of magnitude lower than the transmitted spectrum baseline.
In parallel, a grating beam splitting device composed of two alternating crossed-cell tile first-order diffraction gratings, oriented orthogonal to each-other, was fabricated to function as both a two-way and three-way beam splitter at oblique light incidence. The tiling spatially separates the first-diffraction orders of each grating cell group,
while it overlaps the undeflected zeroth-diffraction order, creating three light-splitting pathways in orthogonal directions in three-dimensions. Each grating type was optimized to separate light in the 1st− and 0th−diffraction order, in ratios 96:1 and 2:1 for the two-way and three-way beam splitter respectively. The result was the projection of three equal intensity spots in space for the three-way beam splitter, and two spots off the axial direction for the two-way a beam splitter.
Learning continuous functions parameterized by neural networks has become a novel paradigm for representing complex, high-dimensional data, offering many benefits like shift-invariance and resolution-independent representations. However, these models struggle with data that is discontinuous, noisy, non-linear, and ill-posed, largely due to their inability to capture diverse data characteristics in a unified manner. To overcome these challenges, we introduce Probabilistic Generative Neural Priors, a Bayesian-inspired regularization framework that integrates probabilistic generative models—such as Energy-based Models (EBMs), Score-based Diffusion Models (SBMs), and Variational Autoencoders (VAEs)—with task-specific neural networks like Neural Fields (NFs) and classification models. Our framework leverages generative models as probabilistic priors to provide essential information during inference network training, facilitating faster and more accurate predictions by directly utilizing the prior's outputs. We validate our approach through extensive experiments on a diverse set of applications, including non-linear physics-based partial differential equation (PDE) inverse problems, linear image inverse problems, physics-based topology optimization, and time-series classification. Our results show significant improvements in accuracy metrics, convergence speed, generalization and regularization performance compared to existing methods, across all considered applications.
Busyness, or how busy someone is, has increasingly become a topic of conversation in day-to-day life. Research has previously explored how people use their time and how people perceive their available time, or lack thereof, but there is no clear answer as to why people tell others that they are busy and what it is they are trying to accomplish by doing so. Drawing on impression management research, this paper proposes that people signal to others that they are busy so that the audience has a positive impression of them. The concept of the busyness facade is introduced, which includes behaviors and verbal statements that are intentionally enacted by individuals to signal to others that they have a lot to do or limited available time. Exactly how and why people engage in this busyness facade is explored in two studies using semi-structured interviews and an online, vignette survey. Overall, evidence is found for the existence of busyness facades and a better understanding of how people display busyness is gained, but the studies are unable to identify a clear motive for why busyness facades would be used as an impression management tactic. Additional findings and research directions are discussed.
Freeform optics offer improved optical systems, but their complex shapes challenge traditional measurement methods. Cost-effective solutions are needed, especially for applications where expensive methods are impractical. Non-interferometric methods are a good alternative, but their accuracy can be limited. This dissertation aims to develop an accessible calibration method that improves the accuracy of these methods and enables the measurement of both refractive and reflective elements. The results are presented in three articles. The first article focuses on the calibration method and a new metrology approach that directly measures ray deflections, simplifying the process. The second article analyzes a new technique for converting wavefront data to height information and proposes a calibration process to improve accuracy. The third article tackles the issue of parasitic reflections by using a data-driven approach. This work significantly advances ray trace-based optical metrology and has numerous applications, particularly in the measurement and alignment of freeform optics.
Causal modeling provides us with powerful counterfactual reasoning and interventional mechanisms to generate predictions under various what-if scenarios. Nevertheless, uncovering causal relationships from observational data presents a considerable challenge, as unobserved confounders, limited sample sizes, and variations in distributions can give rise to misleading cause-effect associations. Models relying on these relationships may perform poorly when spurious correlations do not hold in test cases. To mitigate these challenges, researchers augment causal learning with known causal relations. This dissertation first investigates the incorporation of domain knowledge in structure learning by introducing additional constraints that convey qualitative knowledge about causal relationships. The experimental designs are specifically equipped to evaluate the role of domain knowledge. Secondly, a concept-driven approach is implemented to determine the advantages of incorporating concept-level prior knowledge. Given the invariant nature of causal relationships, the study then showcases the broader applicability of incorporating domain knowledge by employing a machine learning method for learning adsorption energies, illustrating the advantages of harnessing domain knowledge to obtain invariant molecular representations in catalyst screening. Finally, a novel approach is introduced to enhance robustness and out-of-distribution generalization by leveraging gradient agreement across different environments to identify reliable features. Collectively, these experimental designs advance causal discovery and robust machine learning by utilizing prior knowledge and relational invariances, paving the way for future research on integrating domain knowledge and invariance principles into the learning process.
