Now showing items 1-20 of 7394

    • On The Bayesian Multiple Index Models

      Zhao, Zhigen; Dong, Yuexiao; Mcalinn, Kenichiro; Wang, Xiaojing (Temple University. Libraries, 2022)
      In modern statistical applications when the dimension is relatively large, it is a common practice to reduce the dimension using methods such as principal component analysis (PCA), sliced inverse regression and others before applying any statistical models. In this article, we synthetically combine these two steps by considering three Bayesian multi-index models: Bayesian multi-index additive model (BMIAM) for continuous response variable, Bayesian single-index model for binary response variable, and Bayesian multi-index model for categorical response variable. The indexes are parametrized by the hyper-spherical coordinates. The ridge functions are modeled using the Bayesian B-splines, which could be easily extended to other non-parametric methods. We have shown that the posterior consistency holds under certain conditions for the BMIAM. Further, we have developed the Markov chain Monte Carlo (MCMC) algorithm to sample the posterior of the proposed methods. It has been demonstrated through both simulation and real data analysis that the proposed methods provide a reliable estimation of indexes, dimension reduction space and good predictions for the responses.

      Sciote, James J; Godel, Jeffrey H; Moore, John V (Temple University. Libraries, 2022)
      Introduction: The Modified Mallampati Tongue score is a quick and reliable method commonly used in anesthesiology to assess airway patency and predict the ease of intubation. Modified Mallampati Tongue scores range from I – IV with higher Mallampati scores being associated with more difficult intubations as well as increased sleep-disordered breathing, such as obstructive sleep apnea. The Mallampati Tongue score is determined by visibility of the oropharynx when the mouth is opened as wide as possible with the tongue maximally protruded and is directly affected by the position of the tongue. The tongue is an influential muscle to the craniofacial complex; it plays an essential role in the development of the dentoalveolar structures, and its position affects airway volume which influences natural head posture, which influences craniofacial growth. Objective: The primary aims of this study were to identify if any associations exist between Modified Mallampati Tongue scores (I-IV) and 1) craniofacial sagittal and vertical relationships of the jaws and 2) craniofacial head posture (including the postural relationships of the cervical vertebrae, hyoid bone, cranium, and tongue). A secondary aim was to identify if any associations exist between Modified Mallampati Tongue score and age, sex, or race/ethnicity. Methods: This retrospective study included 400 subjects from the Temple University Kornberg School of Dentistry Department of orthodontics who had pre-orthodontic treatment diagnostic records obtained from June 1st 2020 through September 1st 2021. Each patient’s Modified Mallampati Tongue score (I-IV) was recorded in an intraoral photograph of maximum mouth opening with tongue protrusion. All lateral cephalograms were traced in Dolphin Imaging and Amira Morphometrics Software by two examiners tracing 200 subjects each. The craniofacial morphological features were analyzed through the Steiner, Wits, and McNamara analyses for assessment of the sagittal relationships of the maxilla and mandible and by the Jarabak analysis for assessment of the vertical relationships and divergence. Craniofacial head posture was assessed through an analysis that represents the postural relationships of the cervical vertebrae, cranium, length/height of the tongue, and position of the hyoid bone. For statistical analysis, One-way ANOVA, Pearson’s correlation, and Chi-square tests were conducted. Probability values of <0.05 were considered significant. Results: Overall, this study included 400 subjects with ages ranging from 7-73 years old (mean age of 17.99 years), of which there were 288 females (72%) and 112 males (28%). Of the 400 subjects, 60% (241) were African American, 32% (127) Hispanic, 7% (26) Caucasian, and 2% (6) Asian. The most prevalent Modified Mallampati Tongue Score was III (142 subjects, 36%). Out of all of the craniofacial morphology and head posture variables compared against Modified Mallampati Tongue scores (I-IV), significant findings from the one-way ANOVA tests included vertical position of the hyoid bone to the neck, vertical position of the hyoid bone to the mandible, ANB, and Wits values. Higher Mallampati Tongue scores were associated with higher ANB and higher Wits values. Greater Mallampati scores were associated with increased vertical distance of the hyoid bone to the mandible and to the neck, meaning a lower position of the hyoid bone. In addition, correlations that were statistically significant given a 95% confidence interval, included significant positive correlations between Mallampati Tongue score and increased ANB, Wits, and distance of the hyoid to the mandible and to the neck. Pearson’s Correlation Index also showed a significant negative correlation between Mallampati Tongue scores and craniofacial morphology values for SNB and pogonion to nasion-perpendicular, showing that increased Modified Mallampati Tongue scores correlate with more retrognathic mandibles. When evaluating the results of the Chi-Square analyses, there were no significant differences between Modified Mallampati Tongue score and race/ethnicity or age, but there was a significant difference between genders showing that women were more likely to have lower Mallampati Tongue scores than men. Inter-examiner and intra-examiner reliability for the craniofacial head posture measurements, craniofacial morphology measurements, and Modified Mallampati Tongue scores were excellent (correlation coefficients: 0.84 – 0.99). Conclusions: This study reveals that a higher Modified Mallampati Tongue score correlates with higher ANB and Wits values, meaning that higher Modified Mallampati Tongue scores are associated with a Skeletal Class II relationship of the jaws, which could be due to retrognathic mandibular growth. In addition, a higher Modified Mallampati Tongue score is significantly associated with increased distance of the hyoid bone to the mandible and to the neck. This study also found women more likely to have lower Modified Mallampati Tongue scores than men. The results of this study allude to the potential for Mallampati Tongue scores to be used as predictors of Class II skeletal sagittal growth which would ultimately help with orthodontic treatment planning decisions and enhance overall treatment outcomes.

      Piera, Montserrat; Pueyo-Zoco, Victor; Lorenzino, Augusto; Guardiola-Griffiths, Cristina (Temple University. Libraries, 2022)
      This study examines interfaith relationships in Christian, Muslim, and Sephardic songbooks from Medieval Spain in connection with Foucault’s concepts of power and counter-conduct. These interreligious sexual and romantic interactions are addressed in various songs, although at a significantly lower rate in comparison to those which lack religious implications. This disparity points to act of (self) censorship by the poets and reflects the realities of their time. Moreover, there is a notable pattern of different textual mechanisms meant to allude to interfaith relationships as a way to defy established legal and religious codes on the Iberian Peninsula. This thesis analyzes mechanisms like symbolic and evocative poetic language as well as the partial or total absence of such relationships in the lyrics at hand, thereby revising these texts and offering new interpretations that ultimately reinforce the notion of cultural exchange of the Tres culturas.

      Nyquist, Jonathan; Toran, Laura; Buynevich, Ilya (Temple University. Libraries, 2022)
      Urbanized areas with increased amounts of impervious surfaces alter hydrologic systems by increasing stormwater runoff, decreasing infiltration, and reducing vegetation cover and evapotranspiration. Modeling hydrologic systems here is especially difficult due to the increased impervious land cover, which makes predicting processes such as urban streamflow and flooding challenging. By understanding the drivers of hydraulic processes, such as soil characteristics, bedrock depth, and land use, the quality and accuracy of models can be improved. The goal of this study was to use soil moisture loggers and electrical resistivity tomography (ERT) along the Pennypack Creek (Philadelphia, PA) to evaluate soil infiltration and bedrock depth in urban areas to ultimately access their impact on critical zone modeling. ERT was also used to validate or dispute recent seismic interpretations. Four study sites adjacent to Pennypack Creek were selected based on variations in underlying geology: Triassic basin sedimentary rock (Lukens), Paleozoic mafic gneiss (Meadow), Piedmont mica schist (Pine Road), and coastal plain weathered down to mica schist (Rhawn Street). Soil moisture sensors were installed at each site to a depth of up to 50 cm. ERT surveys were conducted at Pine Road and Rhawn Street sites. High infiltration variation at Pine Road and Meadow indicated macropores, which create preferential flow paths whereas low infiltration variation at Rhawn Street and Lukens indicated compaction associated with their land use (public parks). Comparing field capacity data to USDA soil type maps indicated the soil type was not a good predictor and in situ sampling was needed to estimate soil properties. ERT demonstrated bedrock was not shallow at the streambed as predicted by the seismic inversion and showed the need to corroborate depth to bedrock from seismic surveys beneath streams with resistivity inversions. Structure beneath the streambed was particularly noisy for the seismic surveys due to the flow of stream water. This study demonstrates that an accurate critical zone model, especially at urban sites, must rely on in situ investigation of hydrologic parameters based on land use, rather than assumptions of parameter values based on the underlying geology or soil type.
    • Density Functional Theory: van der Waals corrections, symmetry-sphericity and machine learning

      Perdew, John P.; Ruzsinszky, Adrienn; Yan, Qimin; Matsika, Spiridoula (Temple University. Libraries, 2022)
      van der Waals (vdW) or dispersion interaction dominates the weak bonding between the layers of a layered material or between a closed-shell molecule, monolayer, or multi-layered material and a solid surface. The computation of materials properties, including physical adsorption of closed-shell species on solid surfaces, must include a description of the intermediate and long-range parts of the vdW interaction. Calculation of the vdW interaction by correlated wave-functions or random-phase-approximation (RPA) methods is not computationally efficient enough to describe the large systems or supercells that arise in many adsorption problems. Standard semilocal density functional approximations (e.g., PBE and SCAN) to the exchange-correlation energy are more practical, but the long-range part is not included in them. The main purpose of this part of the research, and its main accomplishment, was to develop a computationally efficient intermediate- and long-range correction to semi-local density functionals that would include the needed level of detail. We introduced and applied a new approach, the damped Zaremba-Kohn (dZK) method, to semiconducting substrates of finite thickness. The method has been applied to the adsorption of a graphene monolayer on bulk graphite, bulk hexagonal boron nitride, and multilayer transition metal dichalcogenides (one to four layers of \ch{MoS_2}, \ch{WS_2}, \ch{MoSe_2}, and \ch{WSe_2}). Furthermore, we extended the model to molecules adsorbed on a curved cylindrical conducting surface and combined this model with semilocal density functionals; Calculations were made for the molecules: ammonia \ch{(NH_3)} and nitrogen dioxide \ch{(NO_2)} at two adsorption sites, using the PBE, SCAN, PBE+dZK, and SCAN+dZK methods.Turning now to the next part, we investigated several issues in density functional theory: the sensitivity to electron density of a hierarchy of nonempirical density functionals, the extent to which these density functionals approximate the exact functionals defined as constrained searches over wavefunctions versus ensembles, symmetry breaking and symmetry preservation, etc. We report results from several calculations with approximate density functionals which show that the total energies of non-spherical atoms are systematically lower than those for spherical atoms, a result which leads to appreciably improved molecular binding energies. In addition, we demonstrated that the energy consequences of the symmetry-breaking by self-consistent densities of open-shell atoms computed with approximate functionals are small, justifying their use to compute atomization energies of molecules and solids, and justifying the use of the results to test the accuracy of the approximations. Regarding the third part, our research presents a new approach to incorporate some exact constraints into machine learned density functionals (ML-DFT). ML-DFTs are one of the most exciting tools that have entered the material science toolbox in recent years. Recently, machine learning (ML) has been applied to parametrize exchange-correlation (XC) functionals without human domain knowledge by using kernel ridge regression (KRR), fully connected neural networks (NNs) and convolutional neural networks (CNNs). It is well-known that physical XC functionals must satisfy several exact conditions, such as coordinate scaling, spin scaling and derivative discontinuity. However, these exact conditions have not been incorporated implicitly into the machine learning modeling and pre-processing on large material datasets. In this work, we propose a schematic approach to incorporate a given physical constraint via contrastive learning. We then transfer the pretrained representation of electron density on an augmented molecular dataset which was generated by using the scaling property of exchange energy functionals based on the scaling factors chosen. The model with pretrained representation predicts exchange energies that satisfy the scaling relation, while the model trained on an unaugmented dataset gives poor predictions for the scaling-transformed electron density systems. Taken together, these findings suggest that pretraining task via contrastive learning can enhance the understanding of DFT theory for neural network models and generalize the application of NN-based XC functionals in a wide range of scenarios which are not always available experimentally but theoretically justified.
    • Dual-Mode Georadar Imaging of Biogenic Structures in Sand-Dominated Substrates

      Buynevich, Ilya V.; Nyquist, Jonathan E.; Terry, Dennis O. (Temple University. Libraries, 2022)
      Recognition of large biogenic sedimentary structures (burrows, nests), their differentiation from physical structures (small storm-surge channels, synsedimentary deformation, buried objects), as well as imaging bioturbation in real time remain key challenges in sedimentology and ichnology. To address these issues, this study focused on laboratory and field ground-penetrating radar (GPR) experiments using both traditional time-lapse mode (TLM) and a time-triggered mode (TTM). In three sets of laboratory experiments, substrate consisted of dry, well-mixed, moderately sorted, medium sand common for upper beach (berm/foredune) and aeolian settings. Targets simulating burrowing organisms were placed on a basal layer (L1) buried by ~20-cm-thick cover horizon (L2), both with near identical mean grain size (1.69 and 1.65 ϕ, respectively). Improvements were made to the experimental design, including an experiment with a saline balloon (vertical pull) and a ground-coupled antenna, at varied moisture levels (0%, 3.7%, and 29.5%). High-frequency (2300 MHz) surveys were captured in TTM while manually extracting the target (variable deformation rate; total time window: 20 seconds). Velocities of simulated deformation calculated from time-triggered radargrams have the potential to be used in the field and laboratory to quantify rates of subsurface bioturbation not available by direct observation. Sediment disruption was quantified using standard ImageJ-aided grayscale analysis to detect truncations (breaks in reflection continuity), with an increase of 10-28% relative to undeformed substrate. Similarly, area-based mean grayscale values increased between 8-16% for damp and saturated TLM surveys, respectively. Complementing the laboratory experiments, this research produced one of the first GPR databases of post-emergence sea turtle nests, ichnologically understudied and relatively complex biogenic structures. A simulated structure (Deauville Beach, DE) and two in situ post-emergence sea turtle nests (Sandbridge Beach, VA) were imaged with an 800 MHz antenna, complemented with sediment texture and magnetic susceptibility analyses. The Delaware experiment provided a reference dataset for a full ethological sequence of nesting and emergence, for comparison with few available studies. At Sandbridge, a clear anomaly was identified at the recent Kemp’s Ridley (Lepidochelys kempii) nesting site, including a V-shaped truncation (width: 0.3-0.5 m; depth: ~0.75-0.9 m). At another location, an older (2020) loggerhead (Caretta caretta) nest was imaged and characterized in a similar aeolian ramp setting, which is characterized by a unique combination of upper berm and aeolian granulometric statistics. Numerous ghost crab burrows, with some imaged during surveys, place sea turtle nests into the Psilonichnus ichnofacies, with overprinting representing a contemporary ichnocoenosis rather than a facies shift. This research has wide-ranging implications for: 1) nest recognition in ancient sequences through identification of diagnostic aeolian ramp packages with diagnostic deformation structures; 2) distinguishing nests from morphologically similar paleo-channels based on overall metrics (tiered components) and fill structure, and 3) conservation of endangered species, with novel applications for nest characterization and potential hatchling emergence monitoring.
    • HIV-1 Tat Affects Interorganelle Communication in HIV-Associated Neurocognitive Disorders (HAND)

      Sawaya, Bassel E.; Selzer, Michael E.; Ward, Sara J.; Whelan, Kelly A. (Temple University. Libraries, 2022)
      Among Human Immunodeficiency viruses (HIV), type-1 (HIV-1) is the most common worldwide and has the highest virulence and infectivity. Though the virus only infects a few cell types, the infection affects almost every organ system causing multiple comorbidities. One of the comorbidities is HIV-associated Neurocognitive Disorders (HAND). Interorganelle communication regulates many cellular functions including calcium exchange, lipid exchange, intracellular trafficking, and mitochondrial biogenesis. Interestingly, all these processes have been implicated in HAND suggesting that dysregulation of interorganelle communication plays a role in the progression of HAND. Using neuronal cell cultures, I show that mitochondrial-associated ER membranes (MAM)-associated protein and MAM-tethering protein expression and interactions are altered in the presence of the HIV-1 protein Tat. I also show, PTPIP51 and VAPB, two MAM-tethering proteins, expression is altered in the MAM fraction but not the whole cell fraction, indicating a localization problem. Phosphorylation of PTPIP51 has been shown to regulate the subcellular localization and I show that tyrosine phosphorylation is upregulated with Tat. In addition, I show that PTPIP51 binding with VAPB can be rescued with the addition of kinase inhibitors blocking PTPIP51 phosphorylation suggesting that Tat is altering the phosphorylation of PTPIP51 affecting its subcellular localization and binding to VAPB. Furthermore, I show that ER-Golgi communication is altered in the presence of Tat where there is an increase in the interactions between YIF1A and VAPB, two ER-Golgi tethering proteins. The altered iv interactions between MAM and ER-Golgi tethering proteins in the presence of Tat lead to the disruption of cellular pathways associated with dysfunctional interorganelle communication that can lead to neuronal dysfunction and can contribute to HAND.
    • Strengths and limitations of bioretention sorbent amendments to simultaneously remove metals, PAHs, and nutrients from urban stormwater runoff

      McKenzie, Erica R.; Suri, Rominder P.S.; Ryan, Robert J.; Ulrich, Bridget A. (Temple University. Libraries, 2022)
      Bioretention is increasingly being employed as a stormwater management tool in urban areas, with the intent of using infiltration to address both water quantity and quality concerns. However, bioretention soil media (BSM) has limited removal capacity for dissolved contaminants; hence, amendments may be justified to improve performance. In this study, the potential of five low-cost sorbents as BSM amendments – waste tire crumb rubber (WTCR), coconut coir fiber (CCF), blast furnace slag (BFS), biochar (BC) and iron coated biochar (FeBC) – were investigated for removing several classes of contaminants from simulated stormwater (SSW). The contaminated SSW contained a mixture of metals (Cr, Cd, Cu, Pb, Ni and Zn), nutrients (ammonium, nitrate, and phosphate) and PAHs (pyrene (PYR), phenanthrene (PHE), acenaphthylene (ACY) and naphthalene (NAP)). First, batch studies were used to investigate the sorption capacities, kinetics, and the effects of different water quality parameters on sorbents performance. Then, a long-term vegetated column study was conducted to investigate the performance of three amendments (CCF, WTCR, and BFS) under intermittent runoff condition considering different runoff intensities and antecedent dry periods (ADP). The long-term effects of amendments on plant health and infiltration rate of all media were also investigated. Finally, HYDRUS-1D and a cost model were used to investigate longevity and cost-effectiveness of all BSM. Batch test results revealed that among all sorbents, BC and FeBC were only effective for removing PAHs; CFF had high sorption capacity for both metals and PAHs; BFS was very effective for metals; and WTCR was effective for some of metals and PAHs. Metal removal by BFS occurred primarily via precipitation was due to the BFS mineral structure and high/alkaline pH. The effectiveness of CCF for removing both metals and PAHs was due to its lignocellulose structure and diverse functional groups. CCF could remove metals through several mechanisms including cation exchange, complexation, and electrostatic attraction, and remove PAHs through hydrophobic interaction. Biochar in this study had a highly aromatic structure with less O-containing functional groups, and PAHs were sorbed through hydrophobic pi-pi interactions. The selectivity orders of sorbents for the removal of different metals and PAHs were Cr~Cu~Pb > Ni > Cd > Zn and PYR > PHE > ACY > NAP. This selectivity was mainly caused by differences in properties of metal ions (e.g., ionic radius, hydrogen energy, etc.) and PAHs (e.g., hydrophobicity). Phosphate was removed by BFS due to its Al, Fe and Ca contents, but the other sorbents were ineffective for nutrient removal. Metals sorption capacity of sorbents was greater at higher pH, lower salinity and lower DOC; however, PAHs sorption capacity of sorbents was generally not sensitive to water quality parameters. Column experiments showed that almost all amended and non-amended BSM were able to remove > 99% of influent metals over the 7-month experiment period (except Zn in WTCR media). Cu and Cr effluent concentrations in all media (except BFS media) increased to ~ 10% of influent concentrations during heavy rainfall which was probably due to decomposition of Cu/Cr-organic matter complexes. All bioretention columns removed > 99% of PHE and PYR (higher molecular weight PAHs) regardless of rain intensity and ADP, while the performance of different media for removing the lower molecular weight PAHs (NAP and ACY) varied with the rain intensity, and removal decreased when larger storms were experimentally simulated. For nutrients, among all media, BFS-amended media had high phosphate removal capacity (> 90%). Nitrate removal in all columns was notably affected by changes in stormwater intensity and ADP, likely due to difference in degree of saturation and the potential that anoxic conditions were created, which are favorable for denitrification. All media were ineffective in ammonium removal, and ammonium production occurred throughout experiment which might be due to the lack of nitrifiers in the media. Hydraulic properties of all media were appropriate over the entire experiment. BFS-amended media had the greatest negative effect on plant health, while CCF-amended media was supportive for plants. The transport model results showed that the predicted metal breakthrough times (according to EPA criteria) for different media were 6 years for non-amended media, 7 years for WTCR media, 25 years for CCF media, and 70 years for BFS media. Modeling PAHs, nutrients and some metals (Cr and Cu) under intermittent flow conditions are complicated and other processes and models need to be investigated as future study. Finally, cost analysis results showed that among all bioretention media, CCF- and BFS-amended media with the lowest capital and maintenance costs were the most cost-effective BSM. This research will improve our understanding of BSM amendments that will improve water quality while simultaneously support bioretention system hydrologic function as well as estimating costs of bioretention systems for a long-term application.
    • School Diversity and the School Choice Ecosystem: Mixed Methods Evidence from Pennsylvania

      Cordes, Sarah A; Cucchiara, Maia; Fergus, Edward; Goyette, Kimberley (Temple University. Libraries, 2022)
      In the United States, students’ schooling experiences are shaped by racial and socioeconomic segregation, which is a powerful predictor of educational inequity. School choice has been touted as a remedy to school segregation and has been used widely in desegregation plans. To understand whether and how America’s expanding system of voluntary public school choice can support diversity, this sequential explanatory mixed-methods study explores how five public school choice programs—inter-district enrollment, intra-district enrollment, magnet schools, cyber charter schools, and brick and mortar charter schools—shape the composition of public schools in Pennsylvania. The quantitative phase uses seven years of student level data from Pennsylvania to examine how school choice participation influences neighborhood and choice school diversity and how school characteristics, including diversity, choice type, and specialty theme, are related to families’ school enrollment decisions. I find that school choice slightly exacerbates racial and socioeconomic segregation in urban communities, while suburban schools of choice are much more diverse than neighborhood schools. I also explore the transfer decisions of students in choice-rich environments: those with access to schools with a variety of demographic profiles, choice types, and specialty themes, and so whose choices are less constrained by supply. I find that that higher income families’ preferences for low poverty schools and divergent racial/ethnic preferences among Black and White families put segregating pressure on school systems. At the same time, the broad appeal of zoned schools and high schools with specialty themes represent promising strategies to promote school diversity in the context of school choice. The qualitative phase extends and explains quantitative findings with a comparative case study of two choice-rich city school districts. In Albertville City Schools, choice appeared to be exacerbating segregation while in Bedford Public Schools, neighborhood schools saw increasing diversity. In these two communities, school and district leaders felt competition from school choice and changed practices in response to that pressure. Bedford competed with a robust neighborhood school recruitment program which likely produced increases in diversity because of their diverse local population. While Bedford Public Schools had success attaining numeric diversity, they relied on diversity ideology—an organizational philosophy that celebrates diversity while maintaining internal systems of oppression. Diversity ideology prevented Bedford’s leaders from overturning existing hierarchies and so internal opportunity and achievement gaps persisted. In Albertville, no robust recruitment program emerged, in large part due to capacity and financial constraints. So while choice participation leveled off in Bedford, it continued to grow in Albertville, which may have exposed Albertville zoned schools to increasing segregating pressure from school choice. Though opportunities for numeric diversity were fewer in Albertville, leaders tended to reject diversity ideology and instead, recognize that school choice participation is driven by racialized and classed opportunity gaps. Albertville school and district leaders sought to compete by closing these gaps and increasing equity. Some schools located in Albertville competed by establishing homogeneous, affirming schools and others pursued holistic integration, though the scale of these efforts was limited. These cases illustrate that while local school choice practices can shape school diversity, leaders’ philosophies are critical determinants of whether or not numeric diversity provides a foundation for equitable, integrated schools.
    • Magnetic Induction Communication in Challenging Environments

      Kant, Krishna Dr.; Biswas, Saroj Dr.; Kim, Albert Dr.; Tan, Chiu C Dr. (Temple University. Libraries, 2022)
      Radio frequency (RF) communication, although most popular, is unsuitable for environments involving aqueous and animal/plant tissue media, cluttered environments (e.g., small regions with many radios), applications requiring extremely low power consumption, etc. For such environments, magnetic induction (MI) communication appears to be a viable new technology. It has many desirable properties for propagation in challenging environments. In this thesis, we have experimentally explored the use of Magnetic Induction (MI) based communications for communication through the body. Such communication modalities are essential for wireless communication between implanted therapeutic devices. RF is known to work poorly in this environment due to primarily an ionized aqueous propagation media. We have built a custom experimental testbed using magnetic coils and performed simulations of intrabody propagation for MI based communication using the Sim4Life package. Ultrasound (US) communications have been explored extensively for intra-body environments, and we compare MI against US as well. We experimentally showed that ultrasonic coupling (USC) works better than magnetic resonance coupling (MRC) for transmission through the body at 8 MHz frequency, as USC generates more power than MRC. We have also experimentally compared MR coupling against other forms of intra-body communication, such as galvanic and capacitive. We have done a deep in-depth study of in/on body simulation. According to those studies, the simulations work quite well, and yield a percentage error in the power received for USC as 3-4 %, while for MRC, as 4-5 %. The orientation of USC and MRC sensors causes only 1-2 % error, which doesn't have much impact.

      Kim, Seonhee; Cho, Seo-Hee; Barbe, Mary F; Selzer, Michael E; Thomas, Gareth M; Estarás, Conchi (Temple University. Libraries, 2022)
      Through mutations in the genes TSC1 and TSC2, the genetic disorder Tuberous Sclerosis Complex (TSC) causes begin tumors to develop in different organs across the body. Of the many ways that this disorder can manifest, the brain is one of the most commonly affected organs in TSC. Mutations in TSC1 or TSC2 result in mTORC1 hyperactivation and can impact how the brain forms early in development. Most patients with TSC exhibit seizures and over half display some level of intellectual disability, highlighting the impact that mTORC1 hyperactivation can have on brain function and cognition. However, despite our understanding of the genetic cause of TSC, the mechanisms downstream of TSC1/TSC2 and mTORC1 that mediate TSC neuropathology are not well understood. Therefore, additional study of the cellular and molecular underlying the aberrant neurodevelopment found in TSC and other mTOR-overactivation disorders (collectively known as mTORopathies) is necessary for further understanding of these disorders. Of the pathways that have been identified to interact with mTORC1, there has been great interest in understanding the relationship between mTORC1 and Hippo-YAP/TAZ signaling. The Hippo pathway is an evolutionarily considered pathway that is crucial for regulating organ size through its control of the transcriptional co-activators YAP/TAZ. As exhibited through study of the murine brain, hyperactivation of YAP/TAZ causes changes in how the cortex develops, with several features overlapping with mTORC1 hyperactivation (including aberrant neuronal migration, changes in neuron structure, and increased progenitor proliferation). While the relationship between mTORC1 and YAP/TAZ has been explored in other systems, its connection in the brain has yet to be explored. In Chapter 1 of this dissertation, I first review how TSC affects cortical development as a whole by addressing what is known about the specific cell types and signaling pathways that are affected this disorder. Of the signaling pathways described, the Hippo- YAP/TAZ pathway is discussed in particular detail, addressing its role not only in the context of TSC and in terms of its interaction with mTORC1 signaling, but also in terms of its general role in cortical development. In discussing these studies, I describe the phenotypes seen in different mouse models and in the human brain, allowing for the identification of pathological features that are common between species and between different Cre lines. Following this initial review, I present our experimental aims, hypotheses, and experimental overview for this project in Chapter 2. In Chapter 3, I describe our investigation into the role of YAP/TAZ in the abnormal neurodevelopment that occurs in TSC. Through our analysis of human cortical tuber samples, I demonstrate that YAP/TAZ are elevated at the protein level and that two of their established target genes, CYR61 and CCN2, are elevated at the mRNA and protein levels. Having demonstrated that YAP/TAZ levels and activity are elevated in cortical tuber samples, I next went on to establish whether YAP/TAZ are similarly changed in our TSC animal model. Examination of Emx1-Cre driven Tsc2 cKO mice showed that the level of Yap/Taz were significantly elevated at E16.5. Having established that both YAP/TAZ levels are elevated in our animal model, I next sought to determine whether concurrent genetic manipulation of Yap/Taz in our Tsc2 cKO animals would reduce the severity of neuropathology seen in these mice. Triple conditional knockout (tcKO) of Yap/Taz/Tsc2 was sufficient to mitigate several features seen with mTORC1 hyperactivation in the brain, including the cortical thickness increases, abnormal neuronal migration in the cortex, hippocampal lamination defects, and hypomyelination found in their single Tsc2 cKO counterparts. Overall, these findings provide additional evidence that mTORC1 hyperactivation positively regulates YAP/TAZ. For the first time, this study describes elevation of YAP/TAZ in the brains of individuals with TSC and in the brains of a TSC mouse model. Furthermore, I provide evidence that reduction of Yap/Taz may have a beneficial effect on neuropathology in TSC, highlighting an area for future research in the development of novel therapeutics for this disorder.
    • The Social Ecology of Character: British Naturalism and the Mid-Victorian Sensation Novel

      Logan, Peter M.; Joshi, Priya; Salazar, James; Brilmyer, S. Pearl (Temple University. Libraries, 2022)
      My dissertation tracks an emergent theory of character in the wake of the ecological turn in the mid-Victorian period. It identifies the connection between changing representations of character in the popular sensation novel and developments in contemporary psychology. “The Social Ecology of Character” tells the story of how the idea of character fundamentally changed as a result of the development and popularization of the theory of ecology, the burgeoning notion of organisms as plastic and dynamic, given form by the precarious balance between internal physiobiological expression and external social forces. Rather than an innate quality or the result of “blank slate” impressions, character was conceptualized as a dynamic nexus of internal and external pressures in constant adjustment to its physical and social environment. This, what I call, “ecology of character” is intelligible in the sensation novel, a genre born out of a complicated overlap between the perceived physiological effects on readers and the scandalous storylines and infamous for its complex relationship between character and plot. I demonstrate how the sensation novel dramatizes the dynamic interplay between the internal and external forces that determine psychological development. Drawing on an interdisciplinary combination of literary theory, history of psychology, philosophy of science, theories of realism, gender studies, and novel and periodical theory, my dissertation argues that the sensation genre brings to the foreground the effects of the mid-Victorian ecological turn on literary character and incubates a distinctly mid-Victorian British determinism that anticipates late nineteenth-century naturalism.
    • Coaching wIth Performance Feedback as Teacher Professional Development: A Single-Case Meta-Analysis

      Tobin, Renee M; Schneider, W Joel; Dowdy, Art; Tincani, Matt (Temple University. Libraries, 2022)
      Teacher coaching with performance feedback is widely used in single-case literature to train teachers to implement a variety of strategies and interventions in their classrooms. Meta-analyses of teacher coaching have been conducted in the group design literature and on studies examining the influence of coaching on teacher treatment integrity in the single-case literature. However, the present study is the first to examine the collective single-case effects of teacher coaching with performance feedback on generalizable and maintainable teacher skills that promote teacher effectiveness. A literature search and qualitative coding process yielded 52 single-case studies examining the influence of teacher coaching with performance feedback on teacher implementation of 13 categories of generalizable skills. Included studies used multiple baseline and multiple probe designs and were coded for a variety of qualitative study characteristics. All studies were rated for quality using adapted two-level standards from Ganz and Ayers (2018) and the What Works Clearinghouse standards. Log response ratios were calculated for effect size estimates. These effect sizes were then synthesized in three sets of multi-level models with random effects for studies and cases within studies. Overall, teacher performance feedback was found to result in a 227% change in teacher implementation of skills or strategies in the classroom. When multi-level models were subset by teacher skill, seven of the 13 dependent variable groups demonstrated significant results. Twelve predictors included in an overall model revealed non-significant moderating effects, including publication status and study quality. The present meta-analysis supports teacher coaching with performance feedback as an evidence-based professional development practice in the context of single-case research, although results may vary depending on teacher target behavior. Implications and suggestions for future research are discussed.

      Jones, Nora NJ (Temple University. Libraries, 2022)
      Bias and stereotypes around race, gender, sexuality, and class have been concepts that have and continue to plague medicine. Whether conscious or not, physicians have demonstrated bias when prescribing opioids to Black, Indigenous, and people of color (BIPOC) populations. These patients deserve proper pain control. In 2021, the CDC stated 75,673 people died in the United States from opioid overdose. Because of this, the medical community has an obligation to treat every patient equally and fairly regardless of their skin color or background. With the nature of pain as it is, there exists no clinical, objective measurement of pain. Currently, vulnerable populations, such as individuals with obstacles to self-advocacy, are being left to suffer through pain crises. Additional oversight and inclusion of healthcare equity is needed to combat this unethical gap in patient care. There are numerous ways to create pain management equity, in terms of conversations around pain along with the proper distribution of pain medication, especially opiates. The way to do this is through conversation and discussions around systemic racism and implicit bias. These can take the form of rounds or group discussions within a healthcare setting. There are many ways to combat this bias, but among the first should be discussion.
    • Communication-efficient Distributed Inference: Distributions, Approximation, and Improvement

      Tang, Cheng Yong; Chen, Yong; Dong, Yuexiao; Yang, Wei-Shih (Temple University. Libraries, 2022)
      In modern data science, it is common that large-scale data are stored and processed parallelly across a great number of locations. For reasons including confidentiality concerns, only limited data information from each parallel center is eligible to be transferred. To solve these problems more efficiently, a group of communication-efficient methods are being actively developed. The first part of our investigation is the distributions of the distributed M-estimators that require a one-step update, combining data information collected from all parallel centers. We reveal that the number of centers plays a critical role. When it is not small compared with the total sample size, a non-negligible impact occurs to the limiting distributions, which turn out to be mixtures involving products of normal random variables. Based on our analysis, we propose a multiplier-bootstrap method for approximating the distributions of these one-step updated estimators. Our second contribution is that we propose two communication-efficient Newton-type algorithms, combining the M-estimator and the gradient collected from each data center. They are created by constructing two Fisher information estimators globally with those communication-efficient statistics. Enjoying a higher rate of convergence, this framework improves upon existing Newton-like methods. Moreover, we present two bias-adjusted one-step distributed estimators. When the square of the center-wise sample size is of a greater magnitude than the total number of centers, they are as efficient as the global M-estimator asymptotically. The advantages of our methods are illustrated by extensive theoretical and empirical evidences.

      Krishnan, Jagan; Krishnan, Jayanthi; Krishnan, Jagan; Krishnan, Jayanthi; Liang, Yi; Park, Hyun; Wattal, Sunil (Temple University. Libraries, 2022)
      In May 2018, the European Union enacted the General Data Protection Regulation (GDPR). I examine its impact on firms’ internal information quality (IIQ) and operating efficiency in the United States. Although privacy regulations, such as GDPR, target one subset of firms’ information assets (i.e., personal data), academics and practitioners have emphasized the ability of these regulations to drive broad improvements in firms’ information management practices resulting in higher quality information available for decision making and, by extension, more efficient operations. At the same time, GDPR’s regulatory mandates are likely to burden operations. Using multiple modeling approaches to identify the effect of GDPR on US firms and a variety of IIQ proxies from financial reports and disclosures, I find that (a) GDPR leads to improvements in IIQ for impacted firms and (b) that these improvements in IIQ are beneficial to firm operations. However, the regulatory burden of GDPR has overwhelmed these benefits resulting in a negative net effect on firms’ operating efficiency.

      Patil, Chetan; Pleshko, Nancy; Kiani, Mohammad; Weitkamp, Hendrik; Jacobs, Daniel (Temple University. Libraries, 2022)
      Optical Diagnostic (OD) approaches are used to assist in real-time disease screening and estimation of physiological parameters. OD techniques such as pulse oximeters, transcutaneous bilirubinometers (TcB) and infrared thermometers have become key components for point-of-care clinical management. TcB is used to screen infants for extreme or prolonged neonatal jaundice (hyperbilirubinemia), a treatable condition that can result in permanent neurological impairment or death. Poor outcomes are common in low- and middle-income countries (LMIC), but rare in high-income countries, where access to newborn TcB screening is one of several factors that contributes to disparities. A low-cost, widely distributable approach for TcB could help expand newborn screening in LMICs. Due to the rapid global adoption of versatile smartphones with onboard camera modules, there is increased interest in transforming mobile phones into OD devices, including for the purpose of performing estimates of circulating bilirubin levels in order to expand access to transcutaneous bilirubinometry (TcB) for neonatal jaundice screening.In this dissertation, the feasibility of performing TcB using spatially resolved diffuse reflectance measurements acquired using a mobile phone is evaluated in human subject studies, as well as using theoretical modeling and optical phantom studies. In Aim 1 of this project, we report on the feasibility of a mobile phone-based TcB device and show the development of this device through Monte Carlo simulations. Theoretical models were constructed and utilized for predicting bilirubin levels and were then evaluated with a small pilot study. We extracted measurements of reflectance from multiple optimized spatial-offset regions of interest (ROIs) and a linear model was developed and cross-validated. This resulted in a correlation between total serum bilirubin and mobile phone-based TcB estimated bilirubin values, with R2 = 0.42 and Bland-Altman limits of agreement of +6.4 mg/dL to -7.0 mg/dL. These results report the feasibility of a mobile phone with a modified adapter that can be utilized to measure neonatal bilirubin values; thus creating a novel tool for neonatal jaundice screening in low-resource settings. Aim 2 reports further evaluation of a multi-device mobile phone-based TcB study, including calibration for inter-device variability. Measurements of reflectance were extracted from multiple optimized spatial-offset regions of interest (ROIs) and a linear model was developed and cross-validated. This resulted in a correlation between total serum bilirubin and mobile phone-based TcB estimated bilirubin values, with R2 = 0.28 and Bland-Altman limits of agreement of +9.2 mg/dL to -9.3 mg/dL. These results indicate that an adapter-based smartphone can be modified to measure neonatal bilirubin values for neonatal jaundice screening in low-resource settings. Finally, Aim 3 seeks to guide future developments and evaluate theoretical performance of spatially resolved diffuse reflectance image measurements for regression-based estimation of optical chromophores. We perform a phantom study to explore the impact that increased sample chromophore dimensional variability has on the predictive model correlation. Phantoms were created to simulate the variability of blood, bilirubin and melanin, and then images were captured with mobile phone-based TcB devices. Mean intensities of systematic selection regions of interest based on spatial and spectral images were used as predictive variables for multiple linear regression model construction. The results of this study suggest that 2d spatially resolved diffuse reflectance models benefit the most from unique spatial and spectral regions of interests.
    • Model-based analysis of fiber-optic extended-wavelength diffuse reflectance spectroscopy for nerve detection

      Patil, Chetan A.; Pleshko, Nancy; Lemay, Michel; Won, Chang-Hee; Kim, Albert (Temple University. Libraries, 2022)
      Optical spectroscopy is a real-time technique that holds promise as a potential surgical guidance tool. Fiber-optic diffuse reflectance spectroscopy (DRS) is a technique capable of intraoperative tissue differentiation. The common DRS focuses on estimating chromophore concentrations in the visible (VIS) wavelength range (400-1000 nm), where spectroscopic features of the blood, pigments, and tissue densities are present between 400 and 700 nm. Recently, extended-wavelength DRS (EWDRS), which extends the spectral window from the VIS through the short wave-infrared region (SWIR) up to 1800 nm, has emerged as a promising approach for identifying nerves and nerve bundles due to the SWIR including robust tissue absorption features associated with nerve-tissue related chromophores, including lipids, water and collagen proteins. One potential application of EWDRS is guiding minimally invasive surgical techniques, such as laparoscopy, where inadvertent injury to pelvic autonomic nerves (PANs) is a primary complication that can result in over 70% of patients suffering long-term side effects, including urinary incontinence and sexual dysfunction. There is a need for objective laparoscopic surgical guidance to precisely identify PANs from other tissues, and an improved basis for EWDRS development could assist clinical translation. Prior development of Fiber-optic DRS for tissue classification in the VIS greatly benefited from the application of modeling techniques for simulation of optical measurements, analysis, and fiber-probe design. Model-based analysis can inform fundamental understanding of measured signals in different measurement scenarios, such as the varying tissue morphologies possible in laparoscopic procedures, and guide application-specific fiber-probe design through comparison of unique illumination/collection geometries; however, the demonstration of these approaches in EWDRS is not widely reported. This dissertation focuses on the advancement of platforms for model-driven analysis of EWDRS for nerve identification. In order to advance the current state of EWDRS, a model-based characterization platform for analysis of a custom-developed fiber-optic EWDRS system was developed in Aim 1, which demonstrated agreement between data collected from optical phantoms, ex vivo microsurgical model, and Monte Carlo (MC) computational simulations of EWDRS measurements. In Aim 2, the model-based platform was used to perform a detailed analysis of two similar EWDRS fiber-optic probes, which indicated subtle differences in the depth-dependent measurement performance. Finally, in Aim 3, the custom EWDRS was prepared for adapting laparoscopic use to demonstrate laparoscopic measurement feasibility, including evaluation of placement variance and customized EWDRS package for short-distance transportation. The successful completion of this dissertation will enable improved analyses of EWDRS devices for a variety of future intraoperative applications.
    • Graph neural network and its applications

      Zhang, Kai; Ling, Haibin; He, Xubin; Yan, Qimin (Temple University. Libraries, 2022)
      There has been a growing number of non-Euclidean data generated with complex interactions among the objects from different fields, including computer vision, biochemistry, and material science, which is difficult for traditional machine learning algorithms to process. Hence Graph Neural Network (GNN) has gained popularity recently since it can easily handle the data of such graph structure. GNN uses message passing of information extracted by neural network among the nodes to update the node and graph information, thus getting a better understanding by incorporating both the topology and feature space and performs outstandingly on the task such as node or graph classification and link prediction. However, there are challenges remaining for methodologies and application of GNN: firstly, it is difficult and expensive to get high-quality annotation labels for each node in node classification by GNN, but the pseudo-label of nodes generated in graph contrastive learning is heuristic and error-prone; secondly, although there have been some studies on using GNN for an organic compound such as protein, studies are lacking on how to specifically apply GNN for inorganic physics material especially considering the unique interaction in its crystalline structure. In my research, I study both challenges and propose corresponding solutions. In this dissertation, I begin by briefly describing the methodology and application of GNN. In the second chapter, I propose a dynamically denoised contrastive loss on the graph to rectify the error-prone guidance of the pseudo-label generated. In the third chapter, I use GNN on the problem of property prediction of physics materials, which is a hard problem for traditional machine learning algorithms but appropriate for GNN since orbitals in the materials have strong interactions among them. There have been some applications of GNN in Multiple Object Tracking (MOT) and Single Object Tracking (SOT). However, existing MOT algorithms, whether they use GNN or not, often request prior knowledge of the tracking targets (e.g., pedestrians) and do not generalize well to unseen categories. Thus in the fourth chapter, I propose the benchmark and protocol of Generic Multiple Object Tracking, which requires little prior information.Similarly, the current SOT algorithm is limited by small or low-quality annotated benchmarks. Hence in the fifth chapter, I propose a densely-annotated high-quality Large-scale Single Object Tracking benchmark (LaSOT) to address such issues. On the other hand, it is a great challenge for humans, even medical experts, to identify the exact type of dental implant from a radiograph image. But such pixel-level differences can be captured by Convolutional Neural Network, and high accuracy is achieved. Finally, I conclude with a discussion of future work, including the use of graph contrastive learning on physics material property prediction and Generic Multiple Object Tracking.
    • Gun Violence: A Public Health Crisis The Role Physicians can Play in Keeping Communities Safe

      Cabey, Whitney V (Temple University. Libraries, 2022)
      Gun violence is a public health crisis in the United States. Research shows that violence functions similarly to a communicable disease. An exposure such as someone witnessing violence or being a victim of violence is a major risk factor to the exposed person becoming a perpetrator of violence themselves. Victims of gun violence are seen in emergency rooms at alarming rates and despite gun related deaths increasing over the past few decades, there is not a significant quantity of research on violence intervention. As physicians are key players in individual and community health, they have an ethical imperative to intervene. Both doctors and patients believe that physicians can play a role in addressing gun safety and risk of firearm injury. Gun violence interventions by physicians can be either preventative, working to avoid an initial firearm related injury, or interventional, working to avert additional firearm related injuries. Outpatient clinical attempts to prevent firearm injury can be modeled after pre-established methods like bicycle helmet safety screening. Inpatient or post injury methods include more comprehensive approaches that focus on breaking the cycle of violence and preventing reinjury. Gun violence is a public health crisis that requires physician action.