21794 research outputs found
Sort by
Deprivation Specific And Neurocognitive Correlates Of Children With Histories Of Early Deprivation And Atypical Social Communication Problems
No full textABSTRACT
DEPRIVATION SPECIFIC AND NEUROCOGNITIVE CORRELATES OF CHILDRENWITH HISTORIES OF EARLY DEPRIVATION AND ATYPICAL SOCIAL COMMUNICATION PROBLEMS
by
MARISA L. PALANCE
December 2023
Advisor: Dr. Francesca Pernice, Ph.D.Major: Educational Psychology Degree: Doctor of Philosophy The present study evaluated the effects of early deprivation on the neurocognitive and social outcomes of 137 children raised from birth in institutional settings and internationally adopted into the United States. Adoption from South/East Asia was associated with lower levels of atypical social behavior and higher levels of neurocognitive performance compared to children adopted from Eastern Europe and Northern Asia. Children adopted from Eastern Europe consistently displayed higher levels of withdrawn and atypical behavior, as well as reduced performance across cognitive, language, executive functioning, academic underachievement, executive functioning, and visual motor tasks. Higher levels of atypicality were also associated with longer durations of institutionalization and longer time in the adoptive home, academic underachievement in reading and math, and weaker receptive language abilities. Other cognitive factors and parental education level were not significant predictors of atypicality
Impact Of Process Parameters And Degradation On Product Quality In Fused Deposition Modeling
No full textFused Deposition Modeling (FDM) emerged as a popular additive manufacturing technique, finding applications across various industries to produce functional parts and industrial tooling. The key advantage of FDM lies in its ability to fabricate complex and free-form shapes that are challenging to create using conventional manufacturing methods. However, the optimal utilization of FDM relies on a comprehensive understanding of how (1) process parameters and (2) degradation factors influence the product quality metrics such as dimensional accuracy, mechanical properties, power consumption, fabrication duration, and material utilization. This constitutes a significant barrier to the industrial adoption of FDM processes, and limits lifetime of equipment. For this reason, there has been a growing interest in understanding the process control factors and machine degradation factors that influence the characteristics of produced parts. To date, state-of the-models either focus on a limited number of FDM process parameters or concentrates on a restricted set of response characteristics related to the key performance indicators (KPIs) of produced parts or reporting a number of monitoring failures techniques for AM processes. In addition, many of these studies also assume linear relationships between FDM process parameters.
This study presents an investigation of the impact of FDM process parameters (i.e., nozzle temperature, infill pattern, infill percentage, build orientation, layer thickness, and printing speed) on seven key performance indicators (KPIs) of parts produced: (1) energy consumption, (2) fabrication duration, (3) material used, (4) mechanical properties, and geometric accuracy (i.e., (5) flatness, (6) thickness deviation, and (7) root mean square (RMS)); using a comprehensive Design of Experiments methodology to characterize the relationships across these highly interdependent KPIs. Our experiments use a non-contact type measurement technique to evaluate the geometric accuracy of the 3D printed parts by extracting the 3D point cloud using CT scan. We examine the inter- action among these process parameters factors through a design of experiments approach, considering the non-linear relationships between FDM process parameters by estimating curvature to identify any underlying patterns or trends.
In this study, we also present a design of experiments (DOE) framework to investigate the influence of machine degradation conditions (i.e. nozzle blockages, gear wear) on FDM printing quality metrics (i.e. material used, mechanical properties, and geometric accuracy (i.e. flatness and root mean square)). We used an analysis procedure composed of two steps. The first steps uses parametric methods, specifically the analysis of variance (ANOVA), to identify which factors and their interactions are significant in influencing the KPIs and their level of performance. In cases where the assumptions of ANOVA or the model accuracy are not satisfied, the second step, a non-parametric approach, is employed. The second step uses association rules analysis, which involves extracting rules based on predictions made from a random forest model. These methodologies are used to analyze the data collected from the experiments and obtain meaningful insights without leading to biased or inaccurate results.The findings from this study can provide guidance for operators interesting in maintaining printing quality throughout the lifetime of the machines; by carefully orchestrating a balance between machine degradation severity and adjustments made to the process parameters. The proposed approach will extend the lifespan of FDM machines, optimize production quality, and promote sustainability in additive manufacturing
Investigation Of Medium And High Strength Aluminum Alloy Via Direct Laser Metal Deposition
No full textAluminum (Al), for its excellent strength-to-weight ratio, offers lightweight material replacement in many applications such as automotive, aerospace, and many other industrial applications. In the automotive industry, the demand for Al alloys has increased since the introduction of electric vehicles and the need for more fuel-efficient cars. In addition, the demand for Additive Manufacturing (AM)-specific Al alloys was projected to overtake the demand for Die-Cast and other types of alloys within the next five years. However, in the 2020 annual Aluminum Association report, only 22 Al alloys are registered for AM compared to 560 wrought Al alloys. Therefore, the need for new alloys, developed primarily for AM, has increased. 55% of research on the Al alloys fabricated by the AM process has been limited to binary Al-Si alloy systems due to challenges inherited within the AM process and alloy chemistry. Current traditional alloy design and development cycles require extensive iterations and resources during the initial stage, which are deemed to be inefficient. In addition, most medium and high-strength Al alloys consist of at least two or three elements as the major alloying elements, which adds to the complexity of the alloy design and development cycles. This research employed Laser Metal Deposition (LMD) as a versatile technique for alloy development. A new high-throughput alloy design and development methodology using LMD was presented and used for more efficient full-cycle data collection, feedback, and analysis.The high cooling rate and rapid solidification during the AM process produce a non-homogeneous microstructure that is substantially different from the equilibrium v microstructure. Therefore, binary alloy systems are more suitable for studying the effect of the AM process while changing the composition. A new fundamental understanding of the effect of rapid solidification on the non-equilibrium phase transformation was revealed for hypo-eutectic binary Al-xSi alloys using the newly proposed high-throughput alloy design and development methodology. It was found that the volume fraction of the Al-Si eutectic phase during the non-equilibrium solidification in Al-xSi alloys decreased compared to the calculated equilibrium phase, resulting in a shift of the eutectic point in the phase diagram. The eutectic point in the non-equilibrium Al-Si phase diagram is estimated to be around Al-23wt.%Si compared to Al-12.6 wt.%Si wt.% in the equilibrium phase diagram. In addition, the size and morphology of Si particles observed in the microstructures suggested that the formation of Si particles occurred in two stages during the solidification of the alloy: directly precipitate from the liquid before reaching the eutectic temperature, and Si particles formed from the eutectic reaction and the supersaturated Al matrix. Moreover, from the mechanical properties study of Al-xSi alloys in as-deposited conditions, the contribution of matrix (Al) in the overall ultimate tensile strength of these alloys was found to be 77% (MPa). This knowledge was extended from a binary Al-Si alloy system to a ternary Al-Mg-Si (Cu) alloy system that is widely used in automotive applications. Defect-free Al6000’s (AA6111) alloy was successfully deposited for the first time by the LMD process. In addition, an investigation of two deposition strategies, hatch and circular patterns, was conducted to identify the effect of the cooling rate. The circular pattern offered a more consistent cooling rate that eliminated the cracking issues in Al6000’s series during the vi AM process. A comprehensive comparative study for AA6111 was conducted for AM fabricated samples and the conventional Direct Chill (DC) Casted samples during a multi-stage rolling and heat treatment procedure. The thermodynamic simulation of the phase diagram for AA6111 suggested that the freezing range of the alloy is extended by 100 oC non-equilibrium condition for the AM process compared to the DC cast material. Moreover, from the microstructure evolution study, a secondary intermetallic phase that is rich in Fe and Mn was observed for both AM and DC cast material. This intermetallic phase contributes to the solid solution\u27s strengthening of the AA6111. However, the size and morphology of these particles vary from one material to the other during the rolling and heat treatment procedure. The mechanical properties of AM AA6111 were similar to DC cast in wrought conditions. However, the DC cast material was better by around 10% in yield and ultimate tensile strength due to the variation in the Fe and Mn between DC and AM compositions. This variation led to a lower concentration of intermetallic phases in the AM sample. Overall, the proposed high-throughput alloy design and development methodology using LMD allowed for more insight into the behavior and overall performance of the materials. A new fundamental knowledge of the effect of the AM process was revealed and studied from the manufacturing process and alloy chemistry perspectives
Adolescents’ Friendship Stability And Health Following The Transition To High School
No full textMy dissertation is comprised of two studies that examine the role of friendship stability in shaping adolescents’ mental and physical health outcomes. This dissertation uses data from Phase 1 and 2 of the Promoting Relationships and Identity Development in Education (PRIDE) study assessing adolescents’ well-being following the transition to high school. Expanding upon descriptive findings of adolescent friendship stability, Study 1 uses longitudinal paneled data from the first three years of high school (i.e., Phase 1) to examine whether adolescents’ friendship stability changes over the first three years of high school and how these changes are associated with mental and physical health outcomes later in high school. Latent growth curve model estimates revealed that adolescents’ friendships became increasingly less stable across high school, and these changes were not associated with mental and physical health outcomes. Results from Study 1 suggest that normative declines in friendship stability across high school are not undermining adolescents’ health. Building upon prior evidence documenting associations between adolescents’ daily friendship experiences and overall well-being, Study 2 tests whether changes in adolescents’ friendship stability across two weeks as well as day-to-day are associated with changes in their daily mental and physical health symptoms using 14 days of daily diary data in 11th grade (i.e., Phase 2). Multilevel modeling results showed that daily fluctuations in friendship stability are not associated with adolescents’ daily mental or physical health symptoms. These findings suggest that adolescents do not always stick with the same friends from one day to the next, and that this frequent change in the consistency of adolescents’ friendships is not harmful to their daily well-being. In examining friendship stability across years as well as days, the results of these studies further our understanding of how friendships change across adolescence and how these changes are not maladaptive for adolescents’ mental and physical health
Evidence Of Empathy In Rhetoric And Composition Studies: Tracing Empathy In The Writing Classroom, Discipline, And Beyond
No full textThis dissertation explores practices of empathy in rhetoric and composition studies, including the spaces of the classroom, scholarly publications, and the public. Considering empathy as relational in that it requires back and forth communication to seek understanding, this project describes concrete characteristics of empathy, explores how empathy is valued by the discipline of rhetoric and composition studies, and identifies how empathy is important to contemporary conversations about social issues in the public sphere
Targeting Underexplored Bacterial Folate And De Novo Purine Biosynthetic Pathways For The Development Of Novel Antimicrobial Agents
No full textABSTRACT
TARGETING UNDEREXPLORED BACTERIAL FOLATE AND DE NOVO PURINE BIOSYNTHETIC PATHWAYS FOR THE DEVELOPMENT OF NOVEL ANTIMICROBIAL AGENTS
by
MARCELLA F. SHARMA
August 2024
Advisor: Dr. Steven M. Firestine Major: Pharmaceutical Sciences Degree: Doctor of Philosophy One mechanism to develop novel antibacterial agents is to target critical pathways that are unique to bacteria. Two such pathways are the focus of this work: de novo purine biosynthesis, and para-aminobenzoic acid (PABA) biosynthesis. Previous studies have shown that both pathways are critical for bacterial growth and survival. De novo purine biosynthesis is responsible for the synthesis of new purine nucleotides. The pathway is present in both eukaryotes and prokaryotes; however, there is a divergence in the pathway between human and bacteria, yeast, and fungi. This difference is centered on the conversion of 5-aminoimidazole ribonucleotide (AIR) to 4-carboxy-5- aminoimidazole ribonucleotide (CAIR). In microbes, CAIR synthesis requires two unique enzymes, N5-CAIR synthetase (PurK) and N5-CAIR mutase (PurE); however, humans accomplish the same conversion using a single enzyme AIR carboxylase. While strong evidence has revealed the critical role PurE plays in the survival of bacteria, there are no drug-like and selective inhibitors of the enzyme. To address this problem, a 4,500- fragment library was screened using an optimized thermal binding assay against the E. coli enzyme. Six fragments that showed dose-dependent increases in melting temperature were identified. Five of the six fragments showed inhibition of PurE activity as measured by the CAIR decarboxylation assay. Interestingly, one of the fragments displayed sigmoidal Michaelis-Menten kinetics suggesting that the compound was an allosteric inhibitor of the enzyme. Surprisingly, the fragments identified in our screen are structurally related to fragments recently found to bind to the human AIR carboxylase enzyme. Folate biosynthesis is a well-known target for antibacterial agents. However, only two enzymes in the pathway have been targeted. A key component of folate biosynthesis is PABA, which is prepared from chorismate. This conversion requires two enzymes, aminodeoxychorismate synthase (ADCS), a heterodimeric protein and aminodeoxychorismate lyase (ADCL). Previous studies have shown that ADCS is critical for bacterial viability, and that inhibition of the enzyme is lethal to bacteria. Unfortunately, existing inhibitors of ADCS have limitations. To identify new inhibitors of ADCS, a novel, optimized thermal binding assay was developed. Using this assay, a diverse library of 2,400 molecules consisting of FDA approved drugs, natural products, and other bioactive agents were screened for binding agents. Twelve compounds were identified to have dose-dependent increases in melting temperature with Kd values ranging from 4.5 μM to 58 μM
Essays On The Urgent Care Market
Get PDFThis dissertation examines aspects of the urgent care market. We first explore the history and recent trends of urgent care, from its inception in the 1970 to its growing competition with primary care physicians and retail clinics in the 2010s. We examine aspects of how urgent care can impact a patient’s medical home and its use of pricing transparency that is sweeping the nation. We examine the growing need for patient convenience and flexibility in care with retail clinics encroaching the urgent care service space. We also cover the development of technology to better facility telehealth visits and to disrupt the traditional forms of medical care delivery. We then examine where urgent care centers are located using data from National Urgent Care Realty, controlling for socioeconomic and medical provider factors and proximity. We examine both site-specific and neighborhood characteristics at county and census tract levels. Our results indicate a strong location dependent relationship with local emergency departments, private health insurance, and similar-in-service limited urgent cares. At the county level, urgent care centers cluster in high population areas but tend to avoid direct competition with other urgent care centers and distinct differences in placement among affiliated and non-affiliated urgent care providers. Finally, we examine the impact medical providers have on urgent care center visits in Michigan metropolitan areas during the onset of the pandemic using foot-traffic Patterns data from SafeGraph. We first establish a patient catchment area based on a provider centric approach to each medical provider, then control for either market concentration or public medical access. We find that urgent care centers experienced a 21% decline in visits during the first three month of the pandemic. We also find evidence of medical providers benefiting being within areas with low market concentration and high public access to medical care. Urgent care centers have an asymmetric substitution effect between hospitals. Spillover and siphoning effect are present as medical providers rely on the presence and knowledge of other developers to develop patient volume, seen in the popularity of medical malls
Pleasurable Negotiations: Kink And Community In Early Modern Literature
No full textMy dissertation situates early modern British literature alongside the emerging field of kink studies. Although the origin of kink is often cited as the 1791 publication of the Marquis de Sade’s Justine, I suggest that there is an expansive history of kink dating back to the early modern period. My dissertation focuses specifically on kinky communities in early modern England to argue that communities, rather than sex acts or practices alone, are an integral aspect of early modern kinky practices. The first chapter analyzes representations of cuckold communities in early modern ballads. Early modern cuckolds are typically derided figures in the literature, but I suggest that many of these representations can be interpreted as celebratory and kinky. In the second chapter I argue that theater audiences often constitute a temporary community of voyeurs through a reading of metatheatrical commentary, antitheatrical pamphlets, and the drama of the period itself. In the third and fourth chapters, I turn from my focus on fixed, tangible communities to an exploration of the more abstract and nebulous through an analysis of the merchant economy and the origins of kinky props in the third chapter, and, finally, I suggest that nature itself is a form of eroticized community in the final chapter. This project seeks to legitimize kink not only as a literary and cultural lens, but also, and more importantly, it aims to securely situate kink identities within a queer framework in order to destigmatize the practice of kink
Zebrafish Gut Microbiome Structure And Swim Behavior After Vibrio Cholerae Colonization
No full textVibrio cholerae colonizes the upper small intestine in humans and causes cholera, an acute diarrheal disease spread via the fecal-oral route. Pandemic strains of V. cholerae can be divided into two biotypes: classical and El Tor. Zebrafish adults and larvae can be infected with cholera via immersion, and they maintain a complex gut microbiome throughout infection. El Tor is able to persist in its host for an extended period of time, and it is unclear how the gut microbiome is affected during infection. Long-term colonization may impact components of the gut-brain axis involved in zebrafish behavior. We aimed to characterize the zebrafish gut microbiome structure, and we assessed larval behavior during El Tor infection. We report that the adult zebrafish gut microbiome is significantly more diverse after El Tor colonization suggesting that the interplay among commensals and El Tor allows for long-term colonization. Larvae consistently cleared a Classical infection within 3-4 weeks, but the more persistent El Tor infection suggests the need for a matured immune system. Additionally, when larvae are infected with El Tor, movement is dampened in response to an auditory stimulus, but not a visual stimulus, suggesting a differential response in the gut-brain axis. There is a biotype-specific response that induces significant changes in zebrafish gut microbiome structure and larval behavior, and our established colonization and behavioral models can be used to further assess host-microbe interactions
Security Information And Event Management Optimization Using Deep Federated Learning In Cloud-Based Autonomous Cyber-Physical Systems
No full textThe integration of cloud-based technologies into Connected and Autonomous Vehicles (CAVs) is reshaping the field by combining Deep Federated Learning (DFL), Security Information and Event Management (SIEM), and cloud-dew computing. This solution leverages cloud-based resource provisioning, which is crucial for allocating scalable and efficient computational resources in a dynamic manner. These resources are essential for managing the intricate data and computing requirements of distributed systems, especially in the intelligent vehicle sector. This provisioning facilitates the efficient control of route mapping and cybersecurity in Connected Autonomous Vehicles (CAVs), guaranteeing the ability to process and make decisions in real-time.The research evaluates the reliability of cloud-based frameworks in Connected and Autonomous Vehicles (CAVs), focusing on using dynamic maps for generating secure, real-time paths. This approach highlights the importance of cloud technologies in updating dynamic map data for intelligent transportation systems. Central to this study is the cloud- dew computing architecture, which merges cloud computing\u27s extensive storage and processing capabilities with dew computing\u27s real-time, localized data handling at the end user\u27s edge. This two-tier system allows the cloud layer to manage large-scale processing and analytics, while the dew layer, closer to CAVs, handles immediate data processing tasks. This setup facilitates swift responses to real-time data, essential for the dynamic needs of autonomous vehicles. The seamless integration of both layers ensures efficient and timely updates to CAV navigation and cybersecurity, enhancing both data processing speed and security, a crucial aspect for the safety and reliability of autonomous vehicles and Cyber-Physical Systems (CPS). State-of-the-art deep learning techniques, including a custom Stacked Autoencoder and a Long Short-Term Memory Autoencoder (LSTM-AE), for cybersecurity and Intrusion Detection Systems (IDS). This model demonstrates exceptional proficiency in managing time-series data for self-governing systems, showcasing high accuracy and adaptability for on-road applications. Furthermore, the utilization of distributed processing is necessary for path planning, as it involves multiple cyber-physical systems. This entails employing both synchronous and asynchronous data parallelism approaches under the cloud-dew computing paradigm. An essential aspect of this study entails a comprehensive analysis of different processing units, evaluating their capacity to be scaled, their dependability, and their effectiveness. This assessment is vital for measuring the effectiveness of reducing training durations and optimizing the overall performance of the system. The selected methodology is crucial for protecting CAVs from rising cyber risks and guaranteeing the security and dependability of automated path planning, a vital element in the autonomous vehicle industry