Now showing items 21-40 of 9992

    • Invisalign ClinCheck Prescribed versus Performed Interproximal Reduction

      Godel, Jeffrey H.; Sciote, James J.; Doumit, Carmen (Temple University. Libraries, 2024-08)
      Objectives: Interproximal reduction is a technique used to reduce the mesiodistal dimension of teeth. Interproximal reduction is programmed into the Invisalign ClinCheck and should be reflected clinically. This study aimed to evaluate the initial, approved, and performed interproximal reduction to determine differences between what was planned and performed. Materials and Methods: 57 subjects had an initial and approved Invisalign ClinCheck over the study period. Patient number, dental arch, initial or approved Invisalign ClinCheck, interproximal location, and the amount of interproximal reduction were recorded. For 32 of 57 subjects with an additional intraoral scan prior to refinement, mesiodistal tooth width measurements were recorded using OrthoCAD software and digital caliper. Measurement difference between pre-treatment and refinement indicated the amount of interproximal reduction performed. Wilcoxon signed-rank tests were used to compare the initial, approved, and performed interproximal reduction. Results: There was a significant difference in interproximal reduction between the initial and approved Invisalign ClinCheck overall (p=0.00) and interproximal locations 6,15-19 (p<0.05), with an increased amount of interproximal reduction in the approved Invisalign ClinCheck according to median values. For those with an additional intraoral scan prior to refinement (n=32), there was a signficant difference in interproximal reduction between the initial and approved Invisalign ClinCheck for the maxillary arch (p=0.004). There was a signficant difference in interproximal reduction between the initial ClinCheck and measurement with a digital caliper for the maxillary and mandibular arches (p=0.02) with a median value of -0.1 mm. No other differences were found. The intra-examiner correlation was moderate (intraclass correlation = 0.589). Conclusions: There is significantly more interproximal reduction prescribed in the approved Invisalign ClinCheck than the initial ClinCheck, specifically between the maxillary central incisors and the mandibular incisors. However, there was no difference found between the initial ClinCheck interproximal reduction and performed interproximal reduction. This study found that significantly greater interproximal reduction is required than performed clinically.
    • HORROR-EVOKED AROUSAL AND AMYGDALA BIAS OF THE MEDIAL TEMPORAL LOBE

      Murty, Vishnu P.; Olson, Ingrid R.; Chein, Jason M.; Smith, David V.; Wimmer, Mathieu; Dunsmoor, Joseph (Temple University. Libraries, 2024-08)
      The ability to learn and predict threats in our environment has a direct impact onwhat and how we encode our experiences into future recollections. Experience of our daily lives has implications for how we eventually gain long-term memory, adaptive strategies to assess and foresee threats are crucial for survival. Yet, how humans encode threat-related experiences is difficult to study in terms of episodic memory (Clewett & Murty, 2019; Murty et al., 2012). From background literature, a model that focuses on brain-related modulation at encoding which then is found to impact the formation and recollection of episodic experience, our recent work has begun to characterize how threat-related arousal either enhances or disrupts temporal order memory (Cliver et al., 2024; Gregory & Murty, n.d.). In both behavioral (Study 1 and Study 2) and neuroimaging (Study 2) analyses to investigate the relationship between threat-related neural circuitry during encoding of short movie clips to test temporal order memory and temporal distance memory. We measured neural circuitry in the medial temporal lobe (MTL), including the amygdala sub-nuclei areas of the basolateral and the central-medial amygdala, the anterior and posterior hippocampus, and the perirhinal cortex. We present neural univariate signals of these regions of interest (ROIs), and functional connectivity between ROIs (basolateral and central-medial amygdala, anterior and posterior hippocampus, perirhinal cortex) to see successful temporal order memory performance and compression or expansion of temporal distance memory. This work highlights the importance of understanding neural processes of threat-related arousal encoding.
    • A Bayesian Inference/Maximum Entropy Approach for Optimization and Validation of Empirical Molecular Models

      Voelz, Vincent; Levy, Ronald M.; Carnevale, Vincenzo; Sharp, Kim A. (Temple University. Libraries, 2024-05)
      Accurate modeling of structural ensembles is essential for understanding molecular function, predicting molecular interactions, refining molecular potentials, protein engineering, drug discovery, and more. Here, we enhance molecular modeling through Bayesian Inference of Conformational Populations (BICePs), a highly versatile algorithm for reweighting simulated ensembles with experimental data. By incorporating replica-averaging, improved likelihood functions to better address systematic errors, and adopting variational optimization schemes, the utility of this algorithm in the refinement and validation of both structural ensembles and empirical models is unmatched. Utilizing a set of diverse experimental measurements, including NOE distances, chemical shifts, and vicinal J-coupling constants, we evaluated nine force fields for simulating the mini-protein chignolin, highlighting BICePs’ capability to correctly identify folded conformations and perform objective model selection. Additionally, we demonstrate how BICePs automates the parameterization of molecular potentials and forward models—computational frameworks that generate observable quantities—while properly accounting for all sources of random and systematic error. By reconciling prior knowledge of structural ensembles with solution-based experimental observations, BICePs not only offers a robust approach for evaluating the predictive accuracy of molecular models but also shows significant promise for future applications in computational chemistry and biophysics.
    • Antibiotic Movement through Heterogeneous Biofilms

      Queisser, Gillian; Seibold, Benjamin; Klapper, Isaac; Buttaro, Bettina A. (Temple University. Libraries, 2024-08)
      Biofilms are communities of microorganisms that can form in the human microbiome and on medical implants among other locations. These communities provide greater protection for their member cells resulting in an increase in resistance to antibiotic treatment and persistent infections. There are several factors that may contribute to antibiotic resistance of biofilms. These studies were done concurrently with biological experiments to test the hypothesis that dense, rigid structures within the biofilm may be an additional mechanism for protection from antibiotics. A computational tool and workflow was developed to analyze bead movement for the characterization of biofilm biomaterial properties including rigidity. With this tool, the analysis revealed that the amyloid, curli, confers rigidity in biofilms, thereby restricting bead movement. Greater movement of the beads is seen in biofilms lacking curli and biofilms that produced complex heterogeneous rigid structures. A new model was also developed that uses microscopy imaging data to simulate diffusion-reaction of antibiotics within heterogeneous biofilms. This model was used to investigate the effect of the dense, rigid structures on antibiotic treatment through test simulations and simulations using biological imaging data. These studies reveal various properties about the dense, rigid structures that confer protection.
    • THE HOSPITABLE THOUGHT THAT COUNTS: A TRIAD OF ESSAYS ON CONSCIOUSNESS ATTRIBUTION AND HOSPITABLENESS IN AI-ENABLED SERVICE PROVIDERS

      Lu, Lu; Ok, Chihyung (Michael); Wu, Luorong (Laurie); Wadhwa, Monica (Temple University. Libraries, 2024-08)
      The concept of “genuine hospitality” extends beyond the mere provision of tangible offerings and hospitable behaviors by the host. It requires true hospitableness on the part of the service providers themselves. However, like humans, can AI also serve as a provider capable of embodying hospitableness? This dissertation seeks to establish a comprehensive theoretical framework called the Consciousness Attribution Model of AI Hospitableness (CAMAH) which encompasses three interconnected aspects: (1) the mechanism of consciousness attribution by consumers towards AI-enabled service providers, (2) the necessity of such attributions in recognizing the symbolic value of AI hospitableness, and (3) a nuanced comparison between human and AI providers concerning their capacity to deliver genuine hospitability. Structured into three scholarly essays, this dissertation first undertakes a philosophical and conceptual exploration, culminating in the proposition of CAMAH. Extending the theoretical foundations established in Essay 1, the subsequent essays (2 and 3) delve into empirical investigations within specific service technology domains, focusing on service robots and AI avatars equipped with self-service technologies, respectively. The significance of this dissertation lies in its identification of a necessary condition for AI service providers to be recognized as hospitable hosts capable of imparting hospitality-oriented, symbolic value, while clearly delineating the key boundaries that distinguish AI service providers—notwithstanding their potential to equip with anthropomorphic behaviors/forms—to human counterparts.
    • Comparing Salzmann Index Inter-arch deviation among Medicaid Patients seeking orthodontic treatment in Pennsylvania

      Godel, Jeffrey H.; Sciote, James J.; Doumit, Carmen (Temple University. Libraries, 2024-06)
      Introduction: The Salzmann Evaluation Index (SEI) was chosen by the state of Pennsylvania to evaluate the treatment needs of prospective orthodontic patients and to help determine the allocation of funding for orthodontic treatment, with a score of 25 being the threshold for funding allocation. This study will compare the summed scores of the columns under the inter-arch deviation (IAD) rows, which represent eight types of malocclusion (overjet, overbite, anterior crossbite, anterior openbite, Class II, Class III, posterior crossbite, and posterior openbite) to determine whether there is a difference in the scores of those approved and denied orthodontic insurance coverage. Materials and Methods: 560 Patients with SEI >25, submitted for Medicaid orthodontic insurance approval from Temple University were stratified into “approved” (n=289) and “unapproved” (n=271) for treatment. Their mean IAD column scores (representing the malocclusions listed above) were compared and tested with Wilcoxon test for significance. Results: Anterior crossbite, anterior openbite, posterior crossbite, and posterior openbite were identified as significantly higher scores in the “approved” group compared to the “unapproved” group. Overjet, overbite, Class II, and Class III had no significant differences between approved and unapproved groups. Conclusions: Patients with anterior crossbite, anterior openbite, posterior crossbite, and posterior openbite may be more likely to receive coverage for orthodontic treatment by Medicaid insurance companies in Pennsylvania. Scores denoting presence of overjet, overbite, Class II, and Class III malocclusions were not different in patients approved and denied coverage for orthodontic treatment.
    • THREE ESSAYS ON THE DRIVERS OF FIRMS’ DECARBONIZATION STRATEGIES

      Mudambi, Ram, 1954-; Schifeling, Todd; Hill, Theodore L.; Basu, Sudipta, 1965- (Temple University. Libraries, 2024-08)
      Climate change is a critical issue, as emphasized by the latest Intergovernmental Panel on Climate Change report (2023). Business organizations significantly contribute to greenhouse gas emissions but also play a crucial role in developing decarbonization solutions. A surge in scholarly attention since the mid-2010s has provided valuable insights into the dynamic interplay between firms and climate change. Studies have quantified risks and assessed the impact of environmental practices, while others have examined proactive measures by firms in response to regulatory landscapes and stakeholder expectations. External stakeholders, including governments, shareholders, and business partners, play a pivotal role in steering firms toward low-carbon strategies. However, there remains a gap in understanding the true impact of firm strategies on ecosystem health – for example on firms’ carbon footprint. This research aims to explore the influence of various actors on firms' decarbonization strategies and explores how firms navigate their transition towards low carbon amid conflicting pressures from financial markets, governments, and corporate customers in global value chains. The first essay reviews the literature on the challenges faced by multinational companies (MNCs) when trying to implement more sustainable practices in their supply chains. The second essay empirically investigates MNCs' impact on their suppliers' environmental performance, highlighting the importance of scrutiny, enforcement and economic leverage. The third essay analyzes investor reactions to coal plant divestment announcements by U.S. electric utilities, revealing increasing investor support for divestment. Overall, this work contributes to the literature at the intersection between firms and the environment in a global transition context, by taking a multidisciplinary and integrative approach. It also offers valuable insights for managers and policymakers as it highlights the necessity to account for contextual dynamics (e.g., change in value among stakeholders), and the breadth of the issues at stake (e.g., greenhouse gas emissions are concentrated at the manufacturing stages) to design more efficient environmental strategies and policies.
    • THE IMPACT OF PERCEIVED MORALITY, NORMALITY, AND AGENCY ON FREE WILL ATTRIBUTIONS

      Karpinski, Andrew; Hantula, Donald A.; Helion, Chelsea; Weisberg, Robert W.; Xie, Hongling; Smith, David V. (Temple University. Libraries, 2024-05)
      Past research consistently shows that people widely believe human beings possess free will and share similar definitions of the concept. However, how individuals attribute free will to others varies significantly and depends on the context, though the factors that influence these evaluations remain unclear. This study explores the nuances of free will beliefs through two pilot studies and a main study. Pilot Study 1 analyzed free-response definitions of free will, identifying the most frequently cited elements as (1) ability to make a choice that was (2) consistent with one’s desires and (3) free of constraints. Pilot Study 2 utilized vignettes based on these definitions to investigate free will attributions, confirming the method’s effectiveness for future research. The main study aimed to test two theories: the motivated account, suggesting free will attributions increase with immoral actions, and the nom-violation account, proposing that nonconformist behaviors are seen as exercises of more free will, regardless of moral implications. Through a series of vignettes, the main study uncovered a complex pattern of free will attributions that both align with and challenge these theoretical perspectives. Initial vignettes explored the role of moral valence, revealing that both blameworthy and praiseworthy behaviors are attributed with more free will compared to neutral behaviors, thus contesting the idea that punitive desires solely underpin free will attributions. Further analysis indicated that there was relatively stronger support for the norm violation account, highlighting the significant role of perceived autonomy and desires on free will attributions. The main study expanded upon these frameworks by investigating the impact of behavioral expectations, uncovering that expected behaviors were often attributed with more free will than unexpected behaviors, particularly when unexpected actions could be attributed to situational pressures. These findings collectively offer a nuanced and contextually determined view of free will attributions, influenced by moral significance, norm deviation, and the core aspects of the folk concept of free will.
    • FROM LADY SOLDIERS TO BROTHERS IN ARMS: WOMEN IN THE UNITED STATES ARMED FORCES, 1972-1992

      Urwin, Gregory J. W., 1955-; Motyl, Katya; Neptune, Harvey R., 1970-; Stur, Heather Marie, 1975- (Temple University. Libraries, 2024-08)
      As the Vietnam War extended into the 1970s, concerns arose in Washington about the decreased number of men enlisting in the armed services. Conscription kept the ranks full temporarily, but the draft’s end precipitated a crisis. Due to the increased need for humanpower, the military broke with precedent and disbanded its female auxiliary organizations, admitting women as full-fledged members. This dissertation explores the first twenty years of women’s service after integration, from 1972 (the year that the last draft calls were issued) to 1992 (just after the First Gulf War) to examine the experiences of American women in uniform and how they affected a gendered military structure. In doing so, it argues that servicewomen were seen as both “ladies” and “brothers.” It explores how these contradictory identities affected women’s military experiences, striving to tell this story in the voices of the women involved by drawing on previous interdisciplinary scholarship, supplemented by archival research and oral historiesWomen’s experiences in the United States military were inherently different than men’s. This dissertation seeks to determine how concepts of gender changed in the military, and how those changes impacted servicewomen’s experiences. Just as important is an assessment of how female veterans viewed their own experiences after they returned to civilian life. Sexual harassment and assault will loom large as examples of some of the gendered obstacles women faced. Since those two transgressions concern power, not sex, most of these incidents involve men exerting control over women. This dissertation therefore looks at the ways in which sexual harassment and assault affected the lives of servicewomen: how the military and the women themselves conceptualized their experiences as gendered or not. Despite the marked change in servicewomen’s status, the Defense Department maintained a policy that pretended there was no role for them in combat. The United States would rather cling to the fantasy that women had not served under fire than admit that they were in dangerous situations. This dissertation offers case studies that challenge the fiction that women did not enter combat until the 21st century. Beginning with the invasion of Grenada, women saw themselves as warriors in a combat zone, regardless of the military’s blinkered point of view. In exploring women’s service during the 1980s and the First Gulf War, I am contributing to the recent historiographical trend that challenges the idea of women as noncombatants. These women’s roles, in fact, blurred the line between combatant and noncombatant. Setting the creation of the All-Volunteer Force (AVF) in the context of liberalized women’s participation in the armed services, this dissertation explores the unappreciated changes that transformed the military during the 1970s, 1980s, and early 1990s. While the AVF marked the beginning of increased opportunities for women in the United States military, the backlash against women that occurred in the 1980s did not impact only civilian affairs. The military therefore reflected both positive and negative changes that swept the civilian world. This dissertation will assess how women navigated those changes and explore why they occurred by attempting to create a comprehensive historical narrative of women’s military experiences that traces the service and lives of military women from the end of Selective Service through their active involvement in the First Gulf War.
    • Executive Functioning Skills and Social-Emotional Intervention Exposure as Predictors of Behavioral Outcomes in Kindergartners

      Tobin, Renée Margaret; Jiang, Xu (Psychologist); Schneider, W. Joel; Sandilos, Lia (Temple University. Libraries, 2024-08)
      This study used extant data to examine the role of executive functioning (EF) and intervention dosage in predicting student behavioral outcomes throughout a social-emotional intervention. Data were collected in 19 kindergarten classrooms in Midwest public schools during the 2010-2011 academic year. The sample included 260 students with approximately 49% (n = 126) identified by parents as female and approximately 52% (n = 134) identified by parents as male. Factor analyses and correlational analyses were conducted with all observed behaviors and with all rating scale and task-based EF measures to detect underlying constructs for analysis. However, neither the behaviors nor the rating scale EF measures demonstrated adequately sized correlations to justify combining them into composite variables. Therefore, rating scale EF measures were entered independently into analyses for individual behavioral outcomes. Generalized additive models (GAM) were used to determine the significance of increased exposure to the intervention and various rating scale and task-based measures of EF for prosocial (i.e., cooperative play, on-task, and helping) and maladaptive (i.e., disruptive, physically aggressive, and verbally aggressive) behaviors. Results indicate that some behavioral outcomes improved significantly during the intervention, while most were unaffected. Parent and teacher ratings were predictive of some behavioral outcomes; however, there was no evidence that task-based measures were significant predictors of any classroom behaviors. These results highlight the value and complexity of classroom behavioral observations, as well as the importance of improving understandings of which social-emotional curricula are most effective for addressing both prosocial and maladaptive behaviors, as well as the underlying mechanisms responsible for their efficacy.
    • ADVANCEMENTS IN ARTIFICIAL INTELLIGENCE AND COMPUTER VISION FOR DENTAL IMAGING ANALYSIS: SELF-SUPERVISED LEARNING INNOVATIONS

      Latecki, Longin; Shi, Xinghua Mindy; MacNeil, Stephen; DiPede, Louis (Temple University. Libraries, 2024-08)
      This dissertation explores the application of self-supervised learning methods in dental radiology to address the challenges posed by limited data availability for training deep learning models. The overarching goal is to enhance the efficiency and accuracy of automated systems for various dental diagnostic tasks, including teeth numbering, detection of dental restorations, orthodontic appliances, implant systems, marginal bone level, and dental caries from panoramic radiographs, CBCT images, intra-oral 3D scans, and dental radiographs. Key contributions include the development of several novel approaches: Self-supervised Learning for Dental Panoramic Radiographs: Utilizing SimMIM and UM-MAE with Swin Transformer, we achieved significant improvements in teeth detection and instance segmentation, increasing the average precision by 13.4% and 12.8%, respectively, over baseline methods. Self-Distillation Enhanced Self-supervised Learning (SD-SimMIM): Enhancing SimMIM with self-distillation loss, we improved performance on teeth numbering, dental restoration detection, and orthodontic appliance detection tasks, demonstrating superior outcomes compared to other methods. DentalMAE for Intra-oral 3D Scans: Extending the mesh masked autoencoder (MeshMAE), DentalMAE evaluates predicted deep embeddings of masked mesh triangles, yielding better generalization and higher accuracy in teeth segmentation tasks. DEMAE for Dental CBCT Images: Proposing the Deep Embedding MAE (DEMAE), which measures the closeness of predicted deep embeddings of masked patches to their originals, we achieved significant accuracy improvements in teeth segmentation from CBCT images. Masked Deep Embedding (MDE) for Implant Detection: By leveraging MIM, we developed MDE to enhance dental implant detection, creating a comprehensive Implant Design Dataset (IDD) with expert annotations, significantly boosting detection performance. Deep Embedding of Patches (DEP) for Bone Loss Assessment: An extension of MAE, DEP improved the accuracy of marginal bone level detection, supported by the creation of a Bone Loss Assessment Dataset (BLAD) with detailed annotations. Masked Deep Embedding of Patches (MDEP) for Caries Detection: This method enhanced dental caries detection performance, validated on the CariesXrays dataset, demonstrating higher precision and recall rates compared to traditional baselines. Through these innovations, the dissertation establishes the efficacy of self-supervised learning in overcoming data scarcity in dental imaging, offering promising AI-driven solutions for improved diagnostics and patient care in dentistry.
    • ASSESSMENT OF ANTIBACTERIAL EFFECT AND FLOWABILITY OF BIOCERAMIC SEALER MODIFIED WITH BaTiO3 NANOPARTICLES

      Orrego, Santiago; Orrego, Santiago; Yang, Maobin; Nissan, Roni (Temple University. Libraries, 2024-08)
      Introduction: One of the main causes of endodontic treatment failures is the persistence of microorganisms within the root canal systems. Piezoelectric materials, including barium titanate (BaTiO3), offer antibacterial effects. The aim of this project is to develop an endodontic sealer embedded with piezoelectric fillers for the prevention of root canal infections. Materials and methods: BaTiO3 particles were mixed with EndoSequence (BC) sealer in two concentrations (5% and 10%wt). Flowability test was conducted for each type of sealer according to ISO-6876 guidelines. The antibacterial evaluation was performed using an ex-vivo model. Single-rooted extracted teeth were instrumented, and canals were infected with Enterococcus faecalis for 7 days. Following the root canal treatment, the sealers (BC, BC+ BaTiO3-5%, BC+ BaTiO3-10%) were used for obturation. Untreated teeth were used as positive control. Specimens with BaTiO3 particles were subjected to compression cyclic loading to activate the piezoelectric charges and resemble mastication forces. Cell viability (CFU/mL) was used to determine the number of bacteria at the bonded interface of the sealant. ANOVA was used to evaluate the statistical differences among the groups. Results: The addition of BaTiO3 particles into BC Sealer resulted in a decrease in flowability (BC: 21.7 ± 0.55 mm, BC+ BaTiO3-5%:19.5 ± 0.50 mm, BC+ BaTiO3-10%:17.44 ± 0.40 mm). All sealers exhibited antibacterial properties. The addition of BaTiO3 nanoparticles significantly enhanced the antibacterial efficacy compared to BC sealer. However, there was no significant difference between the BC+BTO 5% and BC+BTO 10% groups (BC: 3.90 ± 0.27, while both the BC+BTO 5%: 3.31 ± 0.12, BC+BTO 10%: 3.01 ± 0.22). Conclusion: An antibacterial piezoelectric endodontic sealer was developed. Adding more than 5%w of BaTiO3 particles into BC sealers enhanced the antimicrobial efficacy. However, adding more than 10% of BaTiO3 negatively affects the sealer's flow properties.
    • Nano-enhanced Dialytic Fluid Purification System: Applications and Computational Fluid Dynamics Modeling of a Nanoadsorbent Slurry

      Tehrani, Rouzbeh Afsarmanesh; Tehrani, Rouzbeh Afsarmanesh; Pleshko, Nancy; Yuan, Heyang (Harry); Gillespie, Avrum; Obeid, Iyad, 1975-; Rowles, Stetson (Temple University. Libraries, 2024-08)
      Global water scarcity has necessitated the development of new technologies to provide clean and reliable water for the future. Current global infrastructure is insufficient to meet projected demand, and technologies that can provide efficient and low-cost water are urgently needed. Among the various water treatment methods developed over the years, adsorption has become a cost effective, easy to operate, and reliable method for water treatment. Nanoadsorption has emerged recently as an extension of traditional adsorption by combining the tried-and-true adsorption principles with unique material properties such as fast kinetics, large surface areas, and contaminant selectivity that can be used to remove a variety of contaminants. Unfortunately, these new adsorbents cannot be used in traditional adsorption settings such as columns and flow through systems because they cause high pressure drops, have poor mechanical strength, and are difficult to separate from water. In application, nanoadsorbents generally have been dispersed in water or embedded in macroscale hierarchical structures, but the risk of releasing contaminant containing nanoparticles into treated water necessitates a recovery or retention system. Nano enhanced dialytic purification involves utilizing a dialytic purification system that employs a membrane to separate a suspension of continuously recirculated nanomaterials from a stagnant solution or counterflowing stream of contaminated water. Contaminants diffuse down their concentration gradient, through the membrane, and into the nanomaterial suspension to be adsorbed. The nanomaterials are retained behind the membrane and act as a continual sink for the contaminants. This process was first exemplified in proof-of-concept experiments using a dialyzer with a single tubular membrane. Stagnant solutions of arsenic or lead were added into the lumen of the membrane and dialyzed using a flowing stream of ferrihydrite or hexagonal birnessite nanoparticles, respectively, over a three hour period. A greater than 90% removal was obtained from both experiments at sufficiently high adsorbent loading. The dialytic experiment between arsenic and ferrihydrite was compared to batch adsorption studies with a 94% removal efficiency at similar adsorbent loading. The dialytic experiment between lead and hexagonal birnessite was developed into a 2D axisymmetric CFD model using COMSOL Multiphysics® to study the process mathematically, and computational results were in good agreement with experimental data. The computational model was then extended to feature (for the first time) a 3D dialyzer with multiple working hollow fibers, counterflowing contaminant and adsorbent streams, and two treatment modalities – single-pass and multi-pass. These mass exchangers feature a larger surface area and improved diffusions rates over the single-fiber tubular membrane dialyzer. Methylene blue (MB) and powder activated carbon were used as the model contaminant and adsorbent. The computational model explored key parameters of the dialytic purification process and provided insight into the impact of parameter values on the overall removal of MB. Through these efforts, the dialytic purification process was successfully described mathematically, and the model can be used to explore real batch water treatment or pump and treat remediation applications to provide clean water for the future. The idea of utilizing nanoadsorbents retained behind a membrane to facilitate contaminant removal in a mass exchanger can also benefit analogous fields utilizing similar dialytic processes such as hemodialysis in the medical field and carbon dioxide removal in the petrochemical industry.
    • Stochastic Homogenization of Nonconvex Hamilton-Jacobi Equations in One Dimension

      Yilmaz, Atilla; Rider, Brian (Brian C.); Grabovsky, Yury; Futer, David; Kosygina, Elena (Temple University. Libraries, 2024-08)
      Hamilton-Jacobi equations are a class of partial differential equations that arise in many areas of science and engineering. Originating from classical mechanics, they are widely used in various fields such as optimal control theory, quantitative finance, and game theory. Stochastic homogenization is a phenomenon used to study the behavior of solutions to partial differential equations in stationary ergodic media, aiming to understand how these solutions average out or 'homogenize' over large scales. This process results in effective deterministic descriptions, called effective Hamiltonians, which capture the essential behavior of the system. We consider nonconvex Hamilton-Jacobi equations in one space dimension. We provide a fully constructive proof of homogenization, which yields a formula for the effective Hamiltonian. Our proof employs sublinear correctors, functions extensively discussed in the literature. The proof involves strong induction: we first show homogenization for our base cases, then use gluing processes to generalize the solution for the strong induction. Finally, we extend the result to a wide class of functions. We study the properties of the resulting effective Hamiltonian and investigate the occurrence of flat pieces. Additionally, we develop a Python-based computational tool that performs the same homogenization steps in a computing environment, returning the effective Hamiltonian along with its graph and properties.
    • Quantifying the sphere of influence: ecology and trophic dynamics of methane seep communities along the Pacific Costa Rican Margin

      Cordes, Erik E.; Cordes, Erik E.; Sanders, Robert W.; Freestone, Amy; Demopoulos, Amanda W. J. (Temple University. Libraries, 2024-05)
      Chemosynthetic ecosystems in the deep sea hold vast amounts of untapped energy that until recent decades have been largely unobtainable. With the growing demand for resources and constant advancements in technology, these ecosystems and the diverse communities that inhabit them now face increasing pressure from anthropogenic exploitation activities. Thus, employing effective management and conservation strategies to avoid devastating these long-lived communities is imperative. However, effective protection hinges on a thorough understanding of these ecosystems. Here, I present a number of studies conducted on methane seeps along the Pacific Costa Rican Margin (CRM), exploring various ecological dynamics and highlighting the unique biodiversity thriving there. These studies aim to address gaps in our knowledge regarding the “sphere of influence” surrounding chemosynthetic methane seeps, providing insights into the flow of energy within these ecosystems, their spatial dynamics and how they interact with background deep-sea habitats. In Chapter 2, I employ a novel seascape approach using systematic surveys of several actively seeping areas to characterize the seep communities and delineate distinct seep zones, testing for inter- and intraspecific differences in community structure. Our results reveal nuanced patterns in α and β diversity between sites and across different zones, driven largely by depth. Additionally, I identify transitional zones extending the spatial extent of the seeps by up to 300 meters, emphasizing the “sphere of influence” surrounding these ecosystems.
    • AN EXAMINATION OF HOW EUROCENTRIC DANCE HAS DISTORTED THE SELF-IMAGE OF BLACK WOMEN

      Flannery, Ifetayo M.; Anderson, Reynaldo, 1964- (Temple University. Libraries, 2024-05)
      Due to lack of research, the nuanced experiences of Black women training in the discipline of ballet, have been overlooked. As a result of lacking academic examination, the disorientation of Black women has continued at the hands of foundational and cultural principles found in Eurocentric ballet. This research is a qualitative study of scholarship paired with auto-ethnography to highlight the mental and physical damage Eurocentric ballet has caused Black women. The presented scholarship employed an afrocentric approach in an effort to accurately articulate and validate the experiences of Black ballerinas.
    • EMOTIONAL INTELLIGENCE TRAINING: FROM THE SCHOOL LEADERS' PERSPECTIVE

      Stull, Judith C., 1944-; DuCette, Joseph P.; Davis, James Earl, 1960-; Fiorello, Catherine A. (Temple University. Libraries, 2024-08)
      This dissertation was designed to explore how selected principals enrolled in the National College for Educational Leadership (NCEL) Emotional Intelligence training program perceive whether the training has influenced their practice. While serving in various capacities as an educational professional, I have developed a strong appreciation for the significance of effective leadership in ensuring quality education is achieved. This dissertation is based on using emotional intelligence theoretically to explore the constructs of effective leadership, establish a model for understanding leadership, and create a program to support the systematic development of educational leaders. This study uses a qualitative research design, employing interviews as the main data collection method. The research sample comprises ten participants (all principals are located in the small Caribbean Island of Jamaica). The approach employed by the researcher to analyze the data was the thematic analysis method, which identifies the common insights and themes exploring the participants' perception of the National College for Educational Leadership, Emotional Intelligence training module. The primary research question explored whether K-12 principals perceive emotional intelligence as useful for improving their leadership. The study's findings indicated that participants found the emotional intelligence training program valuable and believed it added value to the quality of their leadership. The principals that participated in the research reported specific behavioral changes attributable to their participation in the emotional intelligence training. The research presents a nuanced exploration of local principals and their perception of the emotional intelligence training they participated in. The study explores how emotional intelligence training adds value to their practice as educational leaders to effect educational transformation in their schools. The research also presents tangible recommendations for policymakers to improve the emotional intelligence training program.
    • Self-Regulation and Mathematics Achievement During the COVID-19 Pandemic

      Tobin, Renée Margaret; Schneider, W. Joel; Booth, Julie L.; Newton, Kristie Jones, 1973- (Temple University. Libraries, 2024-08)
      Self-regulation refers to a complex set of processes that control attentional, emotional, and behavioral impulses. Understandably, studies have shown that these processes have a significant impact on an individual’s success in school environments. Further, research has highlighted that self-regulation processes are developmental and dynamic, gradually shaped over time by experiences and environments. Thus, unexpected disruptions to environments and expected experiences can negatively impact the development of self-regulation and produce negative secondary consequences, such as learning loss. The COVID-19 pandemic brought about unexpected disruptions to the lives of most people. Emerging research demonstrates the toll the pandemic took on individuals' physical and mental health, work, connections to others, and finances. For a generation of students, there was an additional impact of school closures, shifts to online learning, and social distancing from peer groups. In the present study, I examined how COVID-19 related stress and impacts interacted with the self-regulation of students in grades four through ten. Utilizing data from an ongoing longitudinal study, I fitted a series of multilevel models to evaluate whether COVID-19 stressors and impacts were predictive of worse student self-regulation and whether this had a negative effect on students' mathematics competence as measured by their performance on grade level assessments. Results indicated that student self-regulation was a reliable and robust predictor of performance on grade-level mathematics competence measures. COVID-19 related impacts were associated with worse self-regulation, though COVID-19 stress did not have an effect on self-regulation. We found no evidence of significant interaction effects between COVID-19 related stress and impacts on the relationship between self-regulation and mathematics outcomes. This dissertation study contributes to a growing body of research aimed at understanding the far-reaching consequences of the COVID-19 pandemic, particularly for a generation of students whose learning, social, and home environments were disrupted. Future research should continue to examine self-regulation processes and learning consequences of COVID-19 as we are likely to observe ongoing effects for years to come.
    • SEMBRANDO JUNTAS: A MIXED-METHODS EXPLORATION OF GARDENING'S THERAPEUTIC POTENTIAL FOR ADOLESCENT LATINX FEMALES WITH MOOD DISORDERS

      Jones, Nora L. (Temple University. Libraries, 2024-08)
      In the midst of the youth mental health crisis in the United States, Latinx adolescent females are at particular risk of having a mood disorder while being simultaneously disproportionately less likely to access mental health care due to a multitude of structural barriers. Nature-based social prescribing, increasingly popular in primary care settings, refers to recommending participation in community programs to provide a multitude of beneficial effects, including improved mental health. Gardening is an example of one of these programs that has been well studied in adults with evidence of positive impacts on mental health. However, it is unclear whether gardening has similar positive impacts on high-risk groups such as adolescent Latinx females with mood disorders. Using mixed-methods, this pilot study explored the experiences of adolescent Latinx females with mood disorders as they participated in an 8-week-long gardening club intervention. Quantitative findings demonstrated statistically significant reductions in participant Strengths and Difficulties Questionnaire (SDQ) impact scores and conduct scores after participation in the intervention. Qualitative feedback from participants supported these results and identified additional positive impacts of participation including relational connection, knowledge acquisition, and appreciation of having a safe space to engage with others.
    • BALANCING THE SCALES OF PERFORMANCE: UNDERSTANDING THE COMPLEX ATTITUDES AND BEHAVIORS OF INDIVIDUAL GROUP PERFORMANCE IN HIGH-PERFORMANCE TEAMS

      Hill, Theodore L.; Andersson, Lynne Mary; Wray, Matt, 1964-; Blessley, Misty P. (Temple University. Libraries, 2024-05)
      High-Performance Teams (HPaTs) are vital for sustaining peak performance inhigh-stakes environments. This research investigation proposes a team model designed to sustain excellence by balancing team well-being, expertise, and interdependence. In searching for answers to understand HPaTs, this research led to the development of the Balanced Duality Model, which is a leadership tool that integrates individual behaviors into team dynamics, balancing personal contributions with collective output for optimal performance. By distinguishing the differences between diverse types of highperformance teams, by the stakes involved, expertise required, and environment, the model monitors the team as a leadership tool, to ensure excellence. The risk of failure can be catastrophic, making these teams toxic, insular, and arrogant. This attitude often leads to inefficient decision-making, compromised performance, and unethical behavior, creating an "above the law" mentality. The B-D Model addresses these challenges by emphasizing the need for continuous support from team members, leaders, and organizational resources. By focusing on psychological fitness and competencies, leaders can enhance individual performance and maintain group cohesion. This research offers a perspective on managing HPaTs with a primary focus on the delicate balance between individual well-being and sustained high performance and provides practical insights for leaders striving to build resilient, high-performing teams.