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Body image and distrust of science as predictors of dieting and disordered eating
No full textResearch has linked the widespread prevalence of dieting, despite its high cost and limited effectiveness, to body image issues, which are exacerbated by the ubiquitous promotion of diet culture. This research explores connections between distrust of science, body image, and the propensity for dieting and disordered eating. Two hundred twenty-five participants from a public university (N = 225, Mage = 20.03, SD = 4.45), had their dieting and disordered eating behaviors assessed using the Weight Control Behavior Scale (French et al., 1995). Body image was measured using the Body Appreciation Scale (Tylka & Wood-Barcalow, 2015) and the Body Surveillance and Shame subscales of the Objectified Body Consciousness Scale for Youth (OBC-Youth) (Lindberg et al., (2006). Distrust of science was evaluated with an adapted version of the Credibility of Science Scale (Hartman et al., 2017). It was found that distrust of science significantly predicted disordered eating behaviors and negative body image perceptions were significantly associated with an increased likelihood of engaging in disordered eating behaviors. These findings support past research that suggests body image predicts dieting behaviors and further indicates that distrust of science is a significant predictor of disordered eating practices.M.A.Includes bibliographical reference
A building centric urban digital twin for resiliency planning
No full textDigital twin technology, as an emerging modeling and simulation paradigm, holds significant potential for advancing flood risk management. However, the development of digital twins for flood mitigation relies on accurate and reliable building asset data as a foundational layer. Acquiring such data for numerous buildings remains challenging due to uncertainties in existing sources and methods.This study focuses on the built environment data layer of the digital twin, emphasizing the identification of spatial structural indicators critical for flood mitigation. It evaluates potential data sources and technologies, assessing their quality in terms of uncertainty, bias, and equity. The research begins by identifying key spatial structural indicators and corresponding capture methods, forming the basis for a framework to address data gaps, reduce uncertainties, and enhance completeness. This framework supports the creation of a robust urban digital twin to improve flood resilience at a city-wide scale.
The study introduces Levels of Detail (LoDs) as a method for abstracting complex building information into essential attributes, simplifying data management and analysis within the digital twin framework. It categorizes spatial indicators essential for flood risk assessment at varying levels of complexity and employs Bayesian linear regression to evaluate the impact of LoDs on flood mitigation decisions. A case study on Hurricane Ida in Manville, New Jersey, demonstrates the feasibility of this approach, showing improved prediction accuracy with higher LoDs.
To address the challenge of acquiring critical yet costly data, such as first-floor elevation (FFE), the study leverages inferencing and imputation techniques. Inferencing is applied by classifying buildings based on architectural typologies and utilizing data libraries to estimate missing FFE values. Additionally, geostatistical imputation is employed to predict the FFE of buildings where data collection is unavailable. These techniques significantly enhance the representation of urban structures in the digital twin, mitigating data acquisition challenges while ensuring accuracy across diverse urban and coastal environments. In summary, this research presents a systematic approach to developing a building-centric urban digital twin for flood resilience planning. By integrating spatial indicators, LoD abstraction, inferencing and imputation strategies, it enables accurate representation of urban structures, supports informed decision-making, and facilitates proactive measures to enhance resilience against flooding.Ph.D.Includes bibliographical reference
Space-time-modulated metamaterial antenna architectures for wireless communication applications
No full textOver the years, time-modulation technique has been employed to alter the radiation pattern of conventional antenna arrays by periodically connecting and disconnecting the antenna elements from the feed network using RF switches. On the other hand, metamaterials (MTMs), known as artificially engineered electromagnetic structures, consist of several sub-wavelength unit cells with unique properties such as negative propagation constant, which can be leveraged to develop a MTM antenna with appealing beamforming capabilities, offering a compelling alternative to complex phased-array architectures. We develop spacetime-modulated metamaterial (ST-MTM) transceiver architectures capable of generatingcontrollable harmonic frequencies, which facilitate a variety of beneficial functionalities. These include nonreciprocity enabling simultaneous transmission and reception of signals, harmonic beam scanning, and directional modulation to enhance physical-layer (PHY) security, serving as a potential alternative to traditional cryptographic methods in wireless
communication systems. In addition, the ST-MTM antenna is leveraged as a beamspace multiple-input multiple-output (MIMO) receiver, which facilitates the retrieval of information from multiple users at the same time. Specifically, the transmitted information of each user, located in a specific direction, can be retrieved from a distinct harmonic frequency component within the received spectrum.Ph.D.Includes bibliographical reference
Refugee perspectives on employment and mental health: a phenomenological qualitative exploration
No full textRefugees experience multiple challenges and adversities that cause significant psychological distress in the migration and resettlement process. The United States is host to refugees who arrive fleeing war, conflict, and persecution. The Refugee Act of 1980 created ‘The Federal Refugee Resettlement Program’ to provide for the effective resettlement of refugees and to assist them to achieve economic self-sufficiency as quickly as possible after arrival in the United States (Dept. Health & Human Services (HHS), 2020). Refugees are forced to flee and migrate in search of safety and stability. They arrive in the United States with a high adversity burden, often having experienced significant trauma, spending many years in the refugee camps or endlessly waiting to be accepted by the host. As they arrive, they are enrolled in employment programs with the primary goal of securing employment and financial self-sufficiency. In this process, their mental health status stemming from their migration histories is overlooked and left unaddressed. Experiencing traumatic stress adversely impacts their mental health and influences their employment outcomes.
Methods: I conducted a phenomenological study with 21 refugees from Afghanistan, Cuba, and Ukraine, resettling in New Jersey. Each participant engaged in an in-depth interview for 60 minutes guided by a semi-structured questionnaire. The study aimed at 1) exploring refugee perspectives on migration, mental health, and employment and 2) exploring employment as a protective factor that facilitates coping as refugees struggle and manage the pre-migration, migration, and post-migration traumas, thereby mitigating the negative impacts of forced migration. All data was collected, transcribed, and uploaded into Nvivo 12. The study utilized the stress and coping theory and the conservation of resources theory to help understand refugee experiences as they made meaning of the role of employment in their lives. The analytical process was complemented by an Interpretative Phenomenological Analysis (IPA), which prioritizes (a) a commitment to an understanding of the participant's point of view and (2) a psychological focus on personal meaning-making in specific contexts.
Findings: The study captured refugee voices on forced migration, mental health, and employment. The emergent themes in Aim 1. involved (1) refugees’ traumatic migration experiences, multiple losses, and yet, within these losses, the surfacing awareness of post-migration growth, (2) forced migration caused adverse mental health, isolation, and manifestations of traumatic stress, and finally, (3) within the context of these experiences, refugees make meaning of employment as a means of financial stability, deeply gratifying and a source of identity, self-worth, and growth, while promoting integration. The findings of Aim 2. relate to (1) Multiple post-migration stressors that interfere with employment decision-making making, and achievement of goals, (2) barriers to employment, including limited language proficiency, lack of support with credentialing and work authorizations, adequate employment opportunities, and lack of guidance and mentorship. Finally, in the second part of Aim 2. refugees engaged with employment as a resilience-promoting factor in their lives, helping them cope with the migration stressors.
Discussion and Implications: The findings in this study suggest that despite the challenges that refugees experience in securing sustainable employment, employment proves to be a resilience-promoting factor for refugees during this process. The Meaning-making and post-migration growth related to employment, the evolving experiences of dignity, hope, and connection reinforce the importance of employment in the lives of refugees resettling in the U.S. Employment as a critical coping strategy for refugees can be facilitated by investing in helping refugees develop English proficiency, focused employment support including guidance and mentorship, and mental health support as they seek sustainable employment. This dissertation underscores the importance of the close association between mental health and employment within the context of refugee resettlement. This study’s findings significantly inform policy and program development for refugees, and provide a deeper understanding of the refugee experience that can help improve mental health and employment outcomes and ultimately positively affect overall well-being.Ph.D.Includes bibliographical reference
Craving for drugs and food in daily life: an economic decision-making and computational modeling investigation
No full textCraving—the intense, specific desire for something—is a common part of our everyday experience. Most people report experiencing craving for chocolate and other palatable snacks. Craving (for drugs) is also a defining symptom of substance use disorders and predicts future drug use and relapse. In aiming to model the shared, defining features of food and drug craving in the laboratory, prior work has shown craving transforms subjective value for the object of craving (and similar choice options) in a multiplicative and time-bound fashion. Here, we investigated the generalizability of this laboratory signature of craving by simultaneously surveying different types of cravings and craving moments in participants’ daily lives. Treatment-engaged patients with opioid use disorder (OUD; N=67) and community control participants (N=49) took part in a 28- day experience sampling study. Each day, we asked participants to report on their momentary urge for opioids and food (sweet/savory), their immediate willingness-to-pay (subjective value) for opioids, a sweet, and a savory snack across different quantities, their current context, and past- hour exposure to drug use-associated cues. Consistent with our study goal, we captured participants’ data across a wide diversity of real-world contexts, and some of our OUD participants’ data in contexts known to provoke drug craving. Moments of drug urge were separable from sweet or savory urge moments in OUD participants, even though participants who desired opioids also tended to desire sweets. These urge moments predicted shifts in subjective value specific to the desired object: drug value by drug urge in OUD participants, and sweet value by sweet urge in both samples. Lastly, we used hidden Markov models to test whether craving moments can be reliably and formally captured under distinct craving “states” for each craving type, finding that our drug data could be well-characterized by a latent process where individuals transition between a “baseline” and a “drug craving” state marked by elevated drug urge and higher drug value. Our findings show that individuals experience craving-specific subjective value shifts in the real world where they can freely act on and be influenced by their environments. Combining this sampling design with computational modeling may provide a novel mechanism for treatment validation and allow us to infer a behavioral read-out of vulnerable moments that could be targeted with just-in-time interventions for behavior change.M.S.Includes bibliographical reference
Assessment and enhancement of asphalt pavement resilience to flooding
No full textGlobal climate change poses significant challenges to the durability and integrity of transportation infrastructure, with flooding being one of the most critical threats. Traditional flexible pavement, one of the most commonly used types worldwide, is particularly vulnerable to flooding. However, current pavement design does not account for the effects of flooding, which often accelerates pavement deterioration and leads to substantial repair and rehabilitation costs. With the increasing intensity and frequency of flooding in recent decades and the budget constraints from transportation agencies, it is crucial to evaluate and mitigate the flooding impact on flexible pavements. Such assessments are vital for incorporating flooding considerations into future pavement design processes, reducing environmental impacts and minimizing associated costs. This research assesses and enhances pavement resilience to flooding by analyzing the multifarious impacts of flooding on roadway pavement performance and proposing the corresponding mitigation strategies. It integrates the development of hydrological, mechanistic, and hydro-mechanical models with comprehensive laboratory experiments to achieve these objectives.The flooding impacts assessed in this research include surface inundation and subsurface saturation. The surface inundation can be divided into surface material degradation and hydraulic scouring. The material degradation caused by prolonged exposure to floodwater was evaluated through laboratory experiments on asphalt mixtures subjected to various inundation periods. Mechanical testing results revealed that the strength of surface material had reduced with the increase in soakage time. The surface hydraulic scouring effect, which occurs in saturated asphalt materials under traffic loading, was characterized by integrating hydro-mechanical model with laboratory testing. It was found that the magnitude of maximum pore water pressure (PWP), whether inside or at the interface of the asphalt materials with relatively high air voids, can range from 100 kPa to 300 kPa under various field conditions. This pressure is sufficient to significantly reduce both the indirect tensile strength and the interface shear strength under repeated loading.
Subsurface saturation effects can be categorized into subsurface weakening and subgrade erosion, both of which occur during the recovery period—from the receding of floodwater from the pavement surface to the restoration of subsurface material moisture levels to pre-flooding conditions. Evaluating subsurface saturation requires capturing the variations in subsurface saturation profiles during the inundation and recovery phases. In this research, these profiles were characterized by integrating laboratory experiments with hydrological modeling. Case analyses were performed on flooded pavement in Florida (FL) and North Carolina (NC). With saturation profile variations, a mechanistic model that considers the moisture-stress-suction dependency of unbound material modulus was used to calculate critical pavement responses during recovery. The effectiveness of this modulus model was justified by comparing predicted deflection with field measurements under FWD load. The critical pavement responses from the mechanistic model were further used for quantifying subsurface weakening damage. Analyses found that the asphalt fatigue cracking damage increased by 1.16 times in the FL case and 1.08 times in the NC case, while the subgrade rutting damage rose by 1.38 times in FL case and 1.82 times in NC case. On the other hand, with saturation profile variations, the hydro-mechanical model was adopted again to analyze the PWP at subgrade, which was further correlated with mass migration to indicate the subgrade erosion potential.
To mitigate flooding damage, this research proposed an inverted pavement structural design and post-flooding traffic operation strategies. Compared to conventional pavement, the increases in critical pavement responses for inverted pavement were significantly smaller after prolonged flooding, demonstrating its potential to enhance resilience against subsurface weakening. From the traffic operation perspective, falling weight deflectometer (FWD) deflections were correlated with critical pavement responses. By conducting FWD testing on pavement after flooding, damage ratios can be estimated and compared to agency-determined thresholds. Subsequently, measures such as imposing truck weight limits or controlling traffic volume can be implemented to reduce the damage caused by subsurface weakening.Ph.D.Includes bibliographical reference
Tracing charm through quark gluon plasma using jet tomography
No full textOne of the most commonly used probes to study the properties of the Quark Gluon Plasma (QGP) are highly collimated sprays of particles arising from the fragmentation of hard scattered partons, called jets. Jets are created at the initial hard scattering and interact strongly with the particles in the QGP medium to lose energy - this phenomenon is called jet quenching. Measurements in heavy ion collisions at RHIC (Relativistic Heavy Ion Collider) and LHC (Large Hadron Collider) have confirmed signs of jet quenching by measuring the yield suppression of inclusive charged jets reconstructed with a wide range of resolution parameters. Jet yield modification in the presence of the QGP is influenced by both elastic scattering and medium-induced gluon radiation (Bremsstrahlung), though the relative importance of these processes remains an open question. Jet suppression is also believed to depend on the initiating parton’s color charge, i.e. whether it’s a quark or a gluon. Studying heavy quark (charm and bottom) tagged jets, where the initiating parton is exclusively a quark, can thus provide additional constraints on the energy loss mechanisms for jets in the QGP, and add a valuable comparison to inclusive jets, which consist of both quark- and gluon-initiated jets. In addition, Quantum Chromodynamics (QCD) predicts that heavy quarks, due to their relatively large masses suffer less radiative energy loss compared to light quarks and gluons, even in vacuum due to the dead-cone effect and was recently measured by the ALICE experiment. Since heavy quarks are also produced much earlier than the QGP, they usually experience the full space-time evolution of the QGP medium, making them a great probe for QGP. Theoretical models predict significant interactions between the charm quark and the QGP medium, and measurements from ALICE and CMS experiments have started to shed light on the modifications to the charm tagged jets spectra and shape in the presence of QGP. At RHIC, lower energy jets closer to the charm mass are more easily accessible along with a smaller background energy density which causes less smearing of the reconstructed jets’ momenta. RHIC also probes a complementary region of the phase-space dominated by quark-initiated jets compared to the LHC energies where the population of quark and gluon dominated jets are comparable. Therefore, studying heavy flavor tagged jets at RHIC can provide unique insights into charm quark interactions with the QGP and is the main focus of this thesis. Measurements of charm jets tagged by their constituent D0 mesons are presented for the first time in Au + Au collisions at √sNN = 200 GeV. The data was collected by the STAR experiment at RHIC including the Heavy Flavor Tracker- a silicon based detector designed to improve secondary vertex resolution. D0 meson tagged jet yields are presented as functions of centrality, jet transverse momentum (pT,Jet), and transverse momentum fraction (z) for 5 0.7) show suppression in central collisions compared to peripheral ones in both pT,D0 intervals. However, soft fragmented jets (z < 0.7) exhibit consistent yields across centralities in the low pT,D0 interval. Within the current uncertainties, the level of jet yield suppression is found to be consistent across cone sizes R = 0.2, 0.3 and 0.4 for the pT,D0 interval - pT,D0 ∈ [1 − 10] GeV/c. Furthermore, no modification for radial profile of D0 mesons is observed for both low and high pT,D0 mesons in R = 0.4 jets. Model calculations that include both collisional and radiative energy losses for heavy quarks qualitatively agree with our measurements.Ph.D.Includes bibliographical reference
Deep learning for sequential decision-making problems in wireless systems
No full textThe recent advancements in deep learning, coupled with its integration into sequential decision-making frameworks such as dynamic programming, have transformed the approach to solving complex optimization problems in dynamic environments. In wireless systems, spanning both communication and sensing/localization, the need for intelligent and adaptive paradigms has grown increasingly critical. These systems operate in highly dynamic settings characterized by mobility, fluctuating channels, and varying performance demands, which render traditional myopic approaches inadequate. Deep learning enables the modeling of intricate dependencies, and its fusion with sequential decision-making frameworks allows for the approximation of optimal decision policies directly from data and system interactions. This combination facilitates adaptive responses to evolving conditions, making it essential for addressing the challenges and meeting the performance requirements of next-generation wireless networks. This dissertation develops deep learning-based sequential decision-making approaches for various settings and challenges in wireless sensing and communications. Specifically, it addresses the general problem of antenna/sensor selection for thin array design in wireless systems, a recurring issue tackled in prior work through supervised learning, convex optimization, or greedy methods. Here, the problem is reframed as a sequential decision-making task modeled as a deterministic Markov Decision Process. The Generative Flow Networks paradigm is adapted to learn an action-sampling policy, ensuring the probability of reaching each terminal state aligns with its reward. This approach outperforms greedy methods, convex optimization, and supervised learning across standard benchmarks. The second focus is mobile relay motion control. A deep reinforcement learning approach is proposed to optimize relay movement over time under spatiotemporally correlated channels, maximizing the cumulative SINR at the destination. The channel variability introduces high-frequency components into the optimal value function, addressed by integrating Fourier features into the neural network for improved value function estimation. The third setting involves designing Intelligent Reflective Surface (IRS) phase shift values for MISO communication systems under correlated channels. A deep reinforcement learning actor-critic method is developed, leveraging sufficient conditions on the critic's Neural Tangent Kernel to facilitate convergence under deep Q updates.Ph.D.Includes bibliographical reference
Turkish sentence processing: role of word order, case, meaning, and prosody
No full textThe research presented in this dissertation investigates the effects of word order, accusative case-marking, thematic reversibility, and prosodic informativity on sentence comprehension in Turkish. We investigate how the presence or absence of case marking, default word order, and thematically reversible arguments impact comprehension. Turkish provides a unique linguistic framework for this research due to its grammatical rules and word order/case-marking properties, enabling the creation of garden-path sentences for experimental evaluation. While previous psycholinguistic studies on Turkish have examined some of these variables, none have systematically investigated them simultaneously and with an audio task as we have done in ours. Experiments 1 and 2 suggest that even though certain sentence types like non-casemarked OVS sentences may be grammatical, scrambled word order and lack of accusative case-marking causes difficulty in comprehension. Sentences with the default word order were found to be easier to comprehend. Case-marking aided comprehension but did not have as significant an effect as anticipated. Thematic reversibility was identified as a crucial factor, with thematically irreversible arguments rendering non-casemarked OVS non-garden path sentences and significantly reducing processing difficulty. Our results also indicate that the additive benefit of cues diminishes in the presence of stronger cues, such as thematic reversibility overshadowing case-marking and word order. Experiments 3 and 4 demonstrated that prosodic information alone allows for high accuracy in judging word order, yet becomes less significant in the presence of stronger linguistic cues such as thematic reversibility, word order, or case-marking. Corpus analyses revealed that frequency-based models can predict sentence accuracy to a certain extent, though they fall short for garden-path sentences. These findings support a model of cue evaluation with diminishing returns, where the strongest cues dominate, and earlier cues are more informative than later cues. Future research would benefit from exploring additional factors like pragmatic context to understand their interaction with the word order, case-marking, thematic reversibility, and prosody.Ph.D.Includes bibliographical reference
Biomimetic scaffolds for vascularized bone regeneration in load-bearing bones
No full textSignificant bone loss due to trauma, infection, tumor invasion, or degenerative diseases often results in large bone defects that are challenging to treat. Typically, autografts or allografts are used to reconstruct these defects and promote bone regeneration. However, autografts are limited in availability and require additional harvesting surgeries, increasing pain and resulting in donor site morbidity, while allografts carry the risk of disease transmission and immune rejection. Synthetic grafts, particularly metallic and ceramic implants, have been explored as alternatives, but a mismatch in mechanical properties and poor integration with native bone have limited their success. These challenges were addressed by developing biodegradable, 3D-printed scaffolds that mimic trabecular and cortical architectures of native bone. The scaffolds were mineralized to promote osteogenesis, and prevascularized lumens were developed within the cortical osteons to promote angiogenesis. Mechanical testing showed that the compressive yield stress and compressive modulus values of the trabecular portion matched those of native trabecular bone, while the cortical portion demonstrated greater strength. The complete scaffold exhibited mechanical properties superior to trabecular bone but slightly below those of native whole bone. It was hypothesized that when used with existing surgical techniques that use internal or external fixation devices, these scaffolds would be sufficiently strong to allow immediate load bearing. The ability of the scaffolds to support capillary action was studied to develop cell-free scaffolds. The osteogenic and angiogenic capabilities were successfully tested in vitro, followed by in vivo evaluation of the scaffolds in a rabbit critical-sized radial defect load-sharing model. The mineralized, prevascularized scaffolds were implanted with and without the addition of autologous bone marrow, with allografts serving as controls. Progressive bone regeneration was observed through biweekly X-ray images and live CT imaging at 12, 16, and 20 weeks. Scaffolds seeded with bone marrow showed greater new bone infiltration into the scaffold structure. Histological analysis showed mineralized bone tissue growth within the scaffold and the presence of blood vessels. Positive immunostaining for CD31 and vWF further validated vascularization, which was observed in both scaffold groups. In allografts, vascularization was limited to the scaffold-native bone interfaces, with minimal vascularization in the middle portion, demonstrating that the scaffolds were more successful in promoting vascularized bone regeneration compared to the allografts.
By combining structural mimicry and biological functionality, these scaffolds address key challenges in bone tissue regeneration, offering a promising bone graft alternative for vascularized bone regeneration and load-bearing applications. Furthermore, this work demonstrates the feasibility of scaffolds that are easily scalable, cell-free, and compatible with existing surgical methods, facilitating seamless translation to clinical applications.Ph.D.Includes bibliographical reference