Alloy nanoparticles have been extensively studied for decades. However, the synthesis and characterization of alloy nanoparticles are still posing significant challenges, leading to an increasing demand for in situ characterization techniques. Small-angle X-ray scattering (SAXS) is a powerful method for structural analysis of nanoparticles. As the SAXS signal is essentially the Fourier transform of the electron distribution, it provides structural information for the entire ensemble of nanoparticles. The development of SAXS has been facilitated by significant advances in synchrotron X-ray sources and data processing methods, leading to the development of the 3D-SAXS method, which enables the reconstruction of the 3D structures of particles from SAXS profiles.Although SAXS has the potential to be a powerful tool for investigating the internal structures of alloy nanoparticles, its application is hindered by the challenges posed by polydispersity, which can cause smearing effects that complicate the geometry recovery process. This dissertation presents a novel approach to overcome the problem of polydispersity in SAXS data analysis, thus demonstrating the utility of SAXS in investigating the internal electron density distributions of alloy nanoparticles. In Chapter 2, the SharPy algorithm is introduced as a size-refocusing program that reduces the smearing effect caused by polydispersity in SAXS data. SharPy is based on a penalized iterative regression approach to fit the pair distance distribution function (PDDF) with an estimated size distribution. It can provide detailed information about the shape of nanoparticles from the smeared SAXS signal under various scenarios and conditions. Chapter 3 investigates the simulated SAXS profiles of AuAg core-shell nanoparticles with varying size distribution, core-shell ratio, and degrees of alloying. It demonstrates the capability of SAXS in observing the electron density distribution of AuAg core-shell structures. These findings provide insights into the potential of SAXS as a reliable method for investigating the internal structures of alloy nanoparticles. Chapter 4 focuses on synthesizing and characterizing AuAg nanoparticles. Their SAXS profiles and PDDF analysis demonstrate that SAXS can distinguish between homogeneous and core-shell nanoparticle structures. In this chapter, the SharPy algorithm is first-time applied to real experimental data, demonstrating its ability to reveal the core-shell structure from a polydisperse nanoparticle system. Chapter 5 investigates the evolution of alloying AuAg nanoparticles through a combination of SAXS/PDDF analysis, 3D reconstruction, and molecular dynamics (MD) simulation. The study presents the 3D electron density distribution of alloying AuAg nanoparticles. The 3D reconstruction with electron density mapping provides a straightforward visualization of the electron density distribution pattern of the alloying AuAg nanoparticles. The success of the SAXS experiment lies in the development of the 3D-SAXS pipeline, which involves the use of SharPy and 3D reconstruction programs, making 3D SAXS a promising alternative to electron microscopy for visualizing the morphology of nanoparticle systems.

Social anxiety (SA) disorder is prevalent, chronic, and impairs quality of life. Typical onset occurs in early adolescence, when social relationships become more salient and complex. Difficulty learning from these newly complex, important interactions may potentiate SA. SA is associated with suboptimal adaptive learning rates in non-social and uncertain contexts. However, the impact of social contexts on learning during social interactions with peers in SA remains unknown. Enhanced SA symptoms while anticipating social feedback is associated with dysregulated engagement of neural circuits implicated in salience and reward processing, which are critical hubs for learning. Despite this overlap, the neural mechanisms that support learning from social feedback remain relatively unexplored in SA. To study the influence of social context and feedback on learning in SA, we paired computational modeling with a novel social interaction fMRI task to determine the extent to which peer value as well as the valence and predictability of peer feedback modulate the neural bases of social learning about peers and their relation to adolescent SA. Fifty-nine youth (age 10-15yrs) with a range of SA engaged in real-time social interactions with purported peers while undergoing an fMRI scan. Youth with clinically relevant SA learn to fear social interactions by emphasizing unexpected negative feedback, and discounting unexpected positive feedback, in predictably nice and unpredictable social contexts to rapidly adjust learning. More severe SA was associated with decreased engagement of salience, reward and cognitive control regions in predictably nice social contexts, and only engaged cognitive control regions in unpredictably mean social contexts. Results elucidate which aspects of the social context contribute to learning to fear social interactions on a neural and behavioral level that potentiate SA, which can inform specific intervention targets.

This dissertation investigates art and architecture surrounding the early modern outbreak of what is commonly understood to be syphilis, focusing predominantly on the Italian peninsula and Sicily. Adopting the early modern term mal francese, I consider the processes through which contemporary notions of health and healing reconciled the identification and management of a novel contagion during the sixteenth and seventeenth centuries. More specifically, prioritizing historical perspectives of disease and intersecting socioeconomic factors, the cross-disciplinary approach of my dissertation demonstrates the cultural impact of the mal francese outbreak through art and architecture that framed the emerging contagion as a chronic infirmity.Primary accounts or literature, together with art, architecture, and urban space yield crucial insights for understanding how past cultures reconciled health crises. Despite its conspicuous symptoms and prevalence during the early modern period, mal francese has received markedly less attention in art historical scholarship compared to plague or leprosy. My dissertation takes advantage of this lacuna in the scholarship in order to examine how the epidemic outbreak was encountered and interpreted. The framework of my dissertation responds to intellectual traditions in the history of science and medicine, relying on early modern concepts of infirmity to analyze the art and architecture of mal francese in the ambit of the Ospedale degli Incurabili network. My Introduction (Chapter 1) examines the emergence of mal francese from the perspective of early modern medical theory. In addition to a review of scholarship, I establish context for studying representations of infirmity and healing, and charitable healthcare reform during the period. Chapter 2 investigates representations of mal francese across media during the long sixteenth century. My discussion considers diverse examples based on descriptive primary accounts of evolving symptoms to discern how the visual arts registered combined social and medical perceptions of the infirmity. I assert that these collective works disclosed recognition about the nature of mal francese as a chronic infirmity, which disproportionately impacted vulnerable members of society despite the realities of its indiscriminate transmission. In Chapter 3, I elucidate the implementation of medical care for mal francese though visual and material culture. Although deemed incurable, contemporary medical practice held that symptoms of mal francese could at least be managed in individuals. In this chapter, I examine art that supported adaptions in traditional therapeutic interventions and the introduction of novel remedies for the contagion. Chapter 4 draws a connecting thread through the dissertation regarding the broader impact of the outbreak on public health measures. I consider parallel developments in healing environments for mal francese relative to ongoing reforms for institutional models of charitable assistance. In particular, I discuss the form and function of the Ospedali degli Incurabili branches in Venice (1522), Naples (1519), and Palermo (1533). The demographic features and dynamics of those centers, as port cities, presented unique challenges for public health and welfare following the mal francese outbreak. Despite compelling links, and contrasts, my study is the first to examine the healing environments of these Incurabili hospital branches together. Founded during the sixteenth century, I examine how the hospitals ensured long term shelter and specialized care for the sick poor afflicted with mal francese. The dissertation then concludes with a brief Coda to synthesize key observations about the impact of mal francese in early modern art and architecture. This dissertation contributes to the field in three main ways. First, I demonstrate that representations of mal francese were highly context-dependent due to formal and iconographic affinities to other infirmities, and with respect to contexts of production and reception. The emphasis on depicted signs or symptoms shifted to convey visual information while providing reassurance, creating distance, or identifying those at the center of a health and welfare crisis as symbols of charitable assistance and subjects of medical care. Second, healing imagery associated with the infirmity didn’t depict mal francese patients recovering from illness, but rather focused on the means for managing its symptoms. In particular, the introduction of guaiacum as a foreign specific used to treat mal francese prompted inventive representational strategies to frame the remedy as a medical innovation and miraculous cure. Finally, access to that therapeutic regimen varied with respect to the medical marketplace, due to issues of cost and functional space. However, new charitable institutions began to facilitate treatment for the growing numbers of sick poor. The Ospedali degli Incurabili were the greatest consumers of guaiacum in the Italian peninsula and Sicily. Each of the branches I discuss developed to support greater accommodations for a growing patient population, facilities that offered specialized treatment for mal francese, and urban renovations guided by contemporary public health goals. This reflected a continuation of earlier models in healthcare reform towards greater medicalization and capacity, but the trend appeared to hasten in these centers following the foundation of the Ospedali degli Incurabili.

Data-driven learning is a sub-discipline of corpus linguistics that makes use of the analyses and tools of corpus linguistics in foreign and second language classroom (Johns, 1991; Johns & King, 1991). With this approach, learners become researchers rather than passive recipients of language rules (Johns, 1991). This study was an investigation of the impact of this approach as a form of written corrective feedback for in-service teachers of English participating in an online writing course at a teacher training institute in Japan. Data-driven learning is commonly utilized in conventional, face-to-face classrooms, or computer lab settings in which there is close direction from the instructor on how to interpret the output of a corpus query. The purpose of this study was to investigate how data-driven learning can be implemented in a blended online environment by providing training to develop the participants’ corpus competence (Charles, 2011; Flowerdew, 2010), which is defined as the ability to interpret data obtained from querying a corpus. This competence has been associated with becoming familiar with corpus methods, which include interpreting concordances, and in turn can aid in accurately repairing writing errors. This training, while initially presented in a face-to-face session at the beginning of the course, was sustained with support from resources on the course’s Moodle website and my comments in Microsoft Word documents. In addition, I applied a fine-grained approach to the analysis of the to examine the quality of participants’ interpretation of concordances. The mixed method triangulation convergence design (Creswell & Plano Clark, 2007, 2011) used in this study was based on data from four sources to examine the effectiveness of data-driven learning in an online environment as well as to observe how the participants interpreted concordances. One data set involved an analysis of the participants’ responses in drafts of their own writing to concordance-based feedback. The participants were given a prefabricated concordance, which was a concordance I generated. That concordance was attached to an error in the participants’ document and the participants used the information provided by the concordance to repair their writing error. The resulting data set, which contains the concordance, along with before and after comparisons of the writers’ repairs, shows how the participants’ interpretations of concordances aided the repairs. With the evidence of several trials over the course of four writing assignments, it was possible to see how the participants used the supplied concordance to repair their writing errors and in turn revealed their degree of corpus competence. A second data set obtained from think-aloud protocols from select participants was utilized to reveal how they interpreted the concordance during an error-repair task. This data revealed what kind of thought processes or noticing that occurred in this task. A third piece of evidence was derived from data obtained from the Moodle website via log files and other resources such as online documents and training quizzes. The purpose was to document which resources the participants accessed relating to data-driven learning training to investigate if those resources aided in their development of corpus competence. The fourth piece of evidence was a quiz developed online to compare the participants with a standard set of items. The quiz was used to investigate which participants successfully or unsuccessfully interpreted the concordances. This instrument, which was analyzed with the Rasch model, allowed for further comparison between the participants’ skill of interpreting concordances. These four data sources were triangulated and in the final analysis cross-referenced to examine how data-driven learning can be successfully applied in a blended online learning environment and how the training of corpus competence aided the learners in interpreting the concordances.

The primary aim of this dissertation was to examine the implications of conceptualizing Foreign Direct Investment (FDI) as a multilateral and multilevel phenomenon. The first research study in the dissertation examines the implication of a multilateral perspective on FDI in our assessment of the relationship between inward FDI and the economic growth and development of the host countries. This study showed that inward FDI positively impacts the economic growth of the host countries in both the short and long term. The second research study focused on conceptualizing FDI as a multilevel phenomenon. The fundamental premise of this chapter was to explicitly acknowledge that even though the implications of FDI can be observed at the aggregate level, such as host countries, as was the case in the first research study, these consequences emerge from the decisions of the individual firms. Furthermore, the findings of this research study demonstrate that different levels of FDI are interconnected but have different implications for the firm’s performance. Drawing upon the existing literature, two considered levels were location-based FDI networks and interfirm collocation networks. Empirical analyses showed that location-based networks are characterized by agglomeration and lead to positive production externalities, while competitive interactions characterize interfirm collocation networks and lead to negative production externalities. Consequently, increasing agglomeration is associated with increasing production output, and increasing competitive interaction is associated with decreasing production output of the firms. In the last research study, we considered how different network externalities, as explicated in the previous chapter, impact the firms' strategic decision-making. This study shows that firm membership in the country-of-origin network helps them make better decisions, while membership in interform collocation networks worsens their decision-making abilities.

Urban landscapes are complex social-ecological systems comprising human and natural elements and their interactions. A key priority for research in these landscapes is understanding how humans affect the presence and abundance of wild organisms and how those organisms, in turn, provide ecosystem services that affect humans. In this dissertation, I use two field studies to understand the ecosystem services provided by urban animals in green spaces across Philadelphia and in a third study I investigate geographic bias in where urban animals have been studied in the United States. For the first study, I use a functional trait approach to examine how urban bird communities respond to landscape- and local-scale habitat and how community composition corresponds to potential ecosystem services. I show that the landscape-scale context of a green space has a stronger influence on species’ abundances than local-scale habitat. As a result, the effect traits associated with cultural and regulating ecosystem services varied strongly along the landscape-scale gradient of urbanization. Local-scale variation in habitat had little effect. The importance of landscape-scale habitat in driving the supply of bird-mediated ecosystem services underscores the importance of regional urban planning for green spaces.In the second study, I use a field experiment to determine the drivers of an understudied ecosystem service – the removal of littered food waste by birds and squirrels. I recorded food removal activity by animals in green spaces across Philadelphia and found that Eastern gray squirrels (Sciurus carolinensis) are the main driver of this service. With increased squirrel abundance, removal level is higher and is both initiated and completed more quickly. This service is also context dependent, such that more food is removed in urban parks and picnic areas, where animals are presumably accustomed to consuming anthropogenic foods. These results highlight the importance of animal behavior, and factors that affect it, for the supply of ecosystem services. In my third study, I take a geographic approach to identifying bias in the study of animals in urban landscapes. Our knowledge of urban ecosystems in the United States is based on hundreds of field studies and thousands of individual field sites, but the distribution of these sites has never been examined. I reviewed the literature and mapped field sites to assess geographic bias in the location of urban ecology field sites. At a national scale, I find that urban ecologists tend to work in larger cities, especially those that are less socioeconomically vulnerable (more affluent). I also find that the social-ecological attributes of the neighborhoods in which ecologists work depends on the framing of their study as well as the focal taxa and functional groups studied. Overall, the neighborhoods where marginalized people live are an underexplored segment of the urban landscape. This is the first study to identify geographic biases in urban ecology field sites and provides a basis for future urban ecology research that produces knowledge applicable to all cities and neighborhoods.

Companies face strategic trade-offs and contractual challenges in collaborative and competitive settings within the framework of institutional theory. Institutional theory focuses on the influence of formal and informal rules and norms that shape organizational behavior. This dissertation encompasses three distinct domains: co-creation in a multi-vendor setting, luxury e-commerce, and social media marketing. Drawing from the lens of institutional theory, the research explores how collaboration, competition, and isomorphism influence decision-making and outcomes in these domains. Each domain presents unique business problems, which are formulated into research questions, supported by relevant theories and literature, and addressed through analytical or empirical models. The findings from each chapter provide valuable managerial insights. In the first chapter, the focus is on collaborative value co-creation. The growing complexity of consulting, new product development, and information technology projects has led firms to increasingly adopt the strategy of collaborative value co-creation with their vendors. By analyzing the strategic interactions among a client, a primary vendor, and a potential secondary vendor, the research uncovers the trade-offs and dynamics that arise in these complex co-creation environments. Building on institutional theory, the study highlights how collaborative relationships in co-creation differ from traditional sourcing models. It reveals that the inclusion of a secondary vendor, even with lower efficiency, can be strategically beneficial for the client in certain scenarios. Conversely, there are situations where involving a more efficient second vendor may not be advantageous. These findings shed light on the institutional factors influencing decisions in collaborative environments. In the second chapter, I investigate the realm of luxury e-commerce and explore the pricing strategies adopted by luxury brands on multi-brand platforms. The study investigates the competition dynamics between luxury brands and e-commerce platforms.It addresses the optimal pricing strategies for luxury brands and examines whether allowing platform discounts aligns with institutional pressures. Luxury brands face a difficult trade-off between offering online discounts and maintaining their high-end brand image, which is often associated with price consistency across channels. On the other hand, e-commerce platforms struggle to assert control over pricing, which affects their ability to thrive in the market. Contrary to conventional wisdom, the research demonstrates that participating in platform discounts can be a viable strategy for luxury brands, even for high-valued products. Moreover, the analysis reveals the potential for pricing coordination across different channels. By considering market conditions and customer preferences, the study identifies factors that impact decision-making and profitability, contributing to the understanding of institutional influences in luxury e-commerce. In the third chapter, the research explores social media marketing in the context of the luxury fashion industry, focusing on the influence of isomorphism between competing brands. Grounded in institutional theory, the study employs machine learning techniques to analyze data from the social media platform of two prominent luxury brands. By examining content features and engagement rates, the research investigates the existence of isomorphic behavior among competing brands. The findings highlight similarities in content structures, approaches, and messaging strategies, indicative of isomorphism. However, the study also emphasizes the importance of differentiation in content strategy to create unique and distinctive brand identities. These insights offer valuable implications for firms seeking to enhance their social media marketing strategies within the institutional context. Overall, this dissertation integrates the perspectives of institutional theory across three interconnected chapters. By examining collaboration, competition, and isomorphism in co-creation, luxury e-commerce, and social media marketing, my research provides a comprehensive understanding of how institutional factors shape decision-making and outcomes in these domains. The findings contribute to the existing literature on institutional theory, offering practical insights for managers in navigating the complexities of collaborative and competitive environments, while aligning with prevailing institutional pressures. Additionally, the research opens avenues for future exploration into the interplay between institutions and strategic decision-making in various business contexts.

Sleep disturbances have been observed across the entire psychosis spectrum. Research has begun to focus on the clinical high risk (CHR) period for psychosis, as the presence of sleep disturbance can be examined separately from the effects of antipsychotic medication and is potentially a risk factor for later psychosis. Several studies have demonstrated a link between sleep disturbance and worsened positive symptoms in CHR individuals. However, sleep disturbance is not unique to the psychosis-spectrum and is well documented in individuals experiencing dissociation. Transdiagnostically, dissociation has been associated with poorer outcomes and reduced treatment response. Despite the established associations between these variables, their respective contributions to positive symptom severity in the CHR period has not yet been characterized. This study examined the separate and combined contributions of sleep quality and dissociation on positive symptom severity in a cross-sectional sample of individuals identified as being at CHR for psychosis. Hierarchical linear regression was conducted to examine the independent and additive influence of sleep quality and dissociation on unusual thought content, suspiciousness, and perceptual abnormalities. Finally, logistic regression was used to determine if sleep quality and dissociation increase odds of a CHR diagnosis. Analyses of indirect effects revealed a significant indirect effect of sleep disturbance on perceptual abnormalities through dissociation in the CHR group. In addition, both sleep disturbance and dissociation significantly contributed to a model predicting to perceptual abnormalities, also in the CHR group. In the total sample, both sleep quality and dissociation significantly increased the odds of a CHR diagnosis. These results suggest that dissociation plays a significant role in the sleep-attenuated positive psychotic symptom relationship in the CHR period, and as a result, could be a modifiable treatment target in these individuals.

With many kinds of personal information becoming available online in the past decades, this dissertation addresses the personal, managerial, and societal implications of personal information online that used to be private in the past. Essay One (Chapter 2) investigates the role of social information (such as names and profile photos) in racial discrimination against Blacks using a correspondence method on an online rental housing platform. It examines whether Blacks with non-Black-sounding names are discriminated against, compared to those with Black-sounding names or Whites, when race is signaled through profile photos. In addition, it studies whether building less complete profiles (e.g., using pseudonyms or not presenting profile photos) impartially hurts Blacks and Whites. Essay Two (Chapter 3) compares involuntary discovery and voluntary disclosure of personal information (invisible stigma) in a hiring context. It examines how the two modes of learning about job applicants’ social media differently influence hiring outcomes. Essay Three (Chapter 4) looks at party identity as antecedents of online privacy decisions for public safety such as personal data for contact tracing and crime detection. Additionally, it investigates two interventions that promote online privacy decisions for public safety when party identity is salient: deemphasis on party identity and recategorization as national identity. Overall, this dissertation contributes to the literature on information systems, social psychology, and economics by highlighting the role of digital technology in enabling a greater depth of identity disclosure and discovery and thus changing the landscape of perception and decision-making today.

Standard empirical models of operating efficiency (OE) and managerial ability (MA) assume a symmetric linear relation of OE and MA with firm performance. However, OE and MA metrics are likely to respond faster to a demand decrease than a demand increase due to cost stickiness and respond faster to negative returns than to positive returns due to accounting conservatism. As predicted, I find large asymmetries in the behavior of OE and MA measures. OE and MA in levels (changes) are 2.4 (1.4) times and 1.5 (1.6) times more sensitive to demand decreases than demand increases. Similarly, OE and MA levels (changes) are 1.7 (1.5) times and 3.6 (2.3) times more sensitive to negative returns than to positive returns. The incremental explanatory power of modeling asymmetry in OE and MA levels (changes) is 20.9% (39.5%) and 263.3% (27.6%), measured as incremental adjusted R2. Cross-sectionally, asymmetry in OE and MA varies with the determinants of cost stickiness: (1) asset intensity and (2) employee intensity. Moreover, the degree of asymmetry also varies with the determinants of accounting conservatism: (1) book-to-market value of equity, (2) leverage, and (3) market capitalization. In addition, demand decline (i.e., cost stickiness) and bad news (i.e., accounting conservatism) during prior and successive periods have an incremental impact on the asymmetry in OE and MA. The standard models of OE and MA do not control for these correlated-omitted variables or incorporate the cost stickiness and accounting conservatism asymmetries, which yield biased measurements and render incorrect regression estimates and inferences.