• M&A Non-Consummation - A Strategic Option?

      Kotabe, Masaaki; Chi, Tailan; Hopkins, H. Donald; Reeb, David (Temple University. Libraries, 2009)
      This study examines the viability of treating M&A non-consummation decisions (NCDs) as strategic options. A review of published research in strategic management journals reveals that this topic has yet to undergo rigorous academic examination. Putting the M&A non-consummation phenomenon under a strategic management lens, this study asks the following research questions about the acquiring firm: 1) How does an M&A NCD affect the market value of firms? 2) Under what conditions does an M&A non-consummation enhance firms' value? 3) How can an NCD be executed so that it favorably affects the value of the firm? Study data were collected from numerous secondary sources such as CRSP, Ward's Business Directory, Lexis-Nexis Academic Database etc. The study sample size was 158 and for each NCD event, several variables were computed. With cumulative abnormal returns for a (-30, -1) pre-event period -- as a measure of firm performance -- as the dependent variable, multiple regression estimation used the following independent variables: strategic fit, relatedness, cultural fit, timing of NCD and coverage of NCDs. In estimating the regression models, confounding events were identified and controlled for. Several of the study hypotheses are supported, notably the hypotheses pertaining to cultural fit and timing of the NCD. Findings and implications are discussed. Taken as a whole, the study highlights the value of treating M&A NCDs as part of the repertoire of strategic options of acquiring firms.
    • MACBETH: FOR THE PURPOSE OF PROCESS

      Duer, Fred M.; Laine, Andrew; Kern, Daniel (Temple University. Libraries, 2014)
      This thesis paper will explain my set design process for Temple University's 2014 production of Macbeth. I will cover the steps from receiving the assignment to opening night and evaluate its purpose in my education toward a Master's of Fine Arts.
    • Machine Learning Algorithms for Characterization and Prediction of Protein Structural Properties

      Vucetic, Slobodan; Vucetic, Slobodan; Obradovic, Zoran; Zhang, Kai; Dunbrack, Roland L.; Carnevale, Vincenzo (Temple University. Libraries, 2019)
      Proteins are large biomolecules which are functional building blocks of living organisms. There are about 22,000 protein-coding genes in the human genome. Each gene encodes a unique protein sequence of a typical 100-1000 length which is built using a 20-letter alphabet of amino acids. Each protein folds up into a unique 3D shape that enables it to perform its function. Each protein structure consists of some number of helical segments, extended segments called sheets, and loops that connect these elements. In the last two decades, machine learning methods coupled with exponentially expanding biological knowledge databases and computational power are enabling significant progress in the field of computational biology. In this dissertation, I carry out machine learning research for three major interconnected problems to advance protein structural biology as a field. A separate chapter in this dissertation is devoted to each problem. After the three chapters I conclude this doctoral research with a summary and direction of our future work. Chapter 1 describes design, training and application of a convolutional neural network (SecNet) to achieve 84% accuracy for the 60-year-old problem of predicting protein secondary structure given a protein sequence. Our accuracy is 2-3% better than any previous result, which had only risen 5% in last 20 years. We identified the key factors for successful prediction in a detailed ablation study. A paper submitted for publication includes our secondary-structure prediction software, data set generation, and training and testing protocols [1]. Chapter 2 characterizes the design and development of a protocol for clustering of beta turns, i.e. short structural motifs responsible for U-turns in protein loops. We identified 18 turn types, 11 of which are newly described [2]. We also developed a turn library and cross-platform software for turn assignment in new structures. In Chapter 3 I build upon the results from these two problems and predict geometries in loops of unknown structure with custom Residual Neural Networks (ResNet). I demonstrate solid results on (a) locating turns and predicting 18 types and (b) prediction of backbone torsion angles in loops. Given the recent progress in machine learning, these two results provide a strong foundation for successful loop modeling and encourage us to develop a new loop structure prediction program, a critical step in protein structure prediction and modeling.
    • Machine learning and computation: exploring structure-property correlations in inorganic crystalline materials

      Yan, Qimin; Yan, Qimin; Perdew, John P.; Ruzsinzsky, Adrienn; Carnevale, Vincenzo (Temple University. Libraries, 2020)
      Kohn-Sham Density Functional Theory (DFT) has been the most successful tool to probe the electronic structure, mainly the ground-state total energies and densities of many condensed matter systems has led to the development of various databases such as Materials Project (MP), Inorganic Crystal Structure Database (ICSD), and many others. These databases ignited the interest of the material science community towards Machine Learning (ML), leading to the development of a new sub-field in material science called material-informatics, which aims to uncover the interrelation between known features and material properties. ML techniques can handle and identify relationships in complex and arbitrarily high-dimensional spaces data, which are almost impossible for human reasoning. Unlike DFT, the ML approach uses data from past computations or experiments. In many cases, ML models have shown their superiority over DFT in terms of accuracy and efficiency in predicting various physical and chemical properties of materials. The incorporation of material property data obtained from atomistic simulations is crucial important to make continuous progress in data-driven methods. In this direction, we use DFT with Perdew-Burke-Ernzerhof (PBE), and Heyd–Scuseria–Ernzerhof (HSE) functionals, to introduce a family of mono-layer isostructural semiconducting tellurides M2N2Te8, with M = {Ti, Zr, Hf} and N = {Si, Ge}. These compounds have been identified to possess direct band gaps that are tunable from 1.0 eV to 1.3 eV, which are well suited for photonics and optoelectronics applications. Additionally, in-plane transport behavior is observed, and small electron and hole (0.11-015 Me) masses are identified along the dominant transport direction. High carrier mobility is found in these compounds, which shows great promise for applications in high-speed electronic devices. Detailed analysis of electronic structures reveals the presence of metal center bicapped trigonal prism as the structural building blocks in these compounds; a common feature in most of the group V chalcogenides helps to understand the atomic origins of promising properties of this unique class of 2D telluride materials. Atomistic simulations based on DFT theory played a vital role in the development of data-driven materials discovery process. However, the resource-based constraints have limited the high-throughput discovery process by using DFT. The main motivation of our work towards the application of machine learning in material science is to assist the discovery process using available material property data in various databases. Incorporation of physical principles in a network-based machine learning (ML) architecture is a fundamental step toward the continued development of artificial intelligence for materials science and condensed matter physics. In this work, as inspired by the Pauling’s rule, we propose that structure motifs (polyhedral formed by cations and surrounding anions) in inorganic crystals can serve as a central input to a machine learning framework for crystalline inorganic materials. We demonstrated that an unsupervised learning algorithm Motif2Vec is able to convert the presence of structural motifs and their connections in a large set of crystalline compounds into unique vectors. The connections among complex materials can be largely determined by the presence of different structural motifs, and their clustering information is identified by our Motif2Vec algorithm. To demonstrate the novel use of structure motif information, we show that a motif-centric learning framework can be effectively created by combining motif information with the recently developed atom-based graph neural networks to form an atom-motif hybrid graph network (AMDNet). Taking advantage of node and edge information on both atomic and motif level, the AMDNet is more accurate than a single graph network in predicting electronic structure related material properties such as band gaps. The work illustrates the route toward the fundamental design of graph neural network learning architecture for complex materials properties by incorporating beyond-atom physical principles. Due to the limitations in resources, it is not feasible to synthesize hundreds of thousands of materials listed in various databases by experiment or compute their detailed properties by using various electronic structure codes and state-of-the-art computational tools. Hence, the identification of an alternative route to screen such databases is very desirable. If identified, this route would be very helpful in reducing the material search space for any application. Categorizing materials based on their structural building blocks is very important to study the underlying physics and to understand the possible mechanisms for any application. Based on structure motifs, we purpose a novel way to categorize, analyze, and visualize the material space called a material network. The connection between any two nodes in this network is determined by using the calculated similarity value (Tanimoto-coeffecient) between each motif and its surrounding information, encoded in terms of a feature vector of length 64. By mapping a known compound, the network thus constructed can be used to screen compounds for the desired application. All the connections of the mapped compound are identified and extracted as a subgraph for further analysis. In our test screening for the transparent conducting oxides (TCO), the proposed network is successful in identifying compounds that are already listed as TCO in the literature. Thus, this indicates its usefulness in reducing the search space for the new TCO materials and various applications. This motif-based material network can serve as an alternate route for functional material discovery and design.
    • MACHINE LEARNING-BASED ARTERIAL SPIN LABELING PERFUSION MRI SIGNAL PROCESSING

      Bai, Li; Wang, Ze; Kim, Albert; Lu, Xiaonan; Ji, Bo, 1982- (Temple University. Libraries, 2020)
      Arterial spin labeling (ASL) perfusion Magnetic Resonance Imaging (MRI) is a noninvasive technique for measuring quantitative cerebral blood flow (CBF) but subject to an inherently low signal-to-noise-ratio (SNR), resulting in a big challenge for data processing. Traditional post-processing methods have been proposed to reduce artifacts, suppress non-local noise, and remove outliers. However, these methods are based on either implicit or explicit models of the data, which may not be accurate and may change across subjects. Deep learning (DL) is an emerging machine learning technique that can learn a transform function from acquired data without using any explicit hypothesis about that function. Such flexibility may be particularly beneficial for ASL denoising. In this dissertation, three different machine learning-based methods are proposed to improve the image quality of ASL MRI: 1) a learning-from-noise method, which does not require noise-free references for DL training, was proposed for DL-based ASL denoising and BOLD-to-ASL prediction; 2) a novel deep learning neural network that combines dilated convolution and wide activation residual blocks was proposed to improve the image quality of ASL CBF while reducing ASL acquisition time; 3) a prior-guided and slice-wise adaptive outlier cleaning algorithm was developed for ASL MRI. In the first part of this dissertation, a learning-from-noise method is proposed for DL-based method for ASL denoising. The proposed learning-from-noise method shows that DL-based ASL denoising models can be trained using only noisy image pairs, without any deliberate post-processing for obtaining the quasi-noise-free reference during the training process. This learning-from-noise method can also be applied to DL-based ASL perfusion prediction from BOLD fMRI as ASL references are extremely noisy in this BOLD-to-ASL prediction. Experimental results demonstrate that this learning-from-noise method can reliably denoise ASL MRI and predict ASL perfusion from BOLD fMRI, result in improved signal-to-noise-ration (SNR) of ASL MRI. Moreover, by using this method, more training data can be generated, as it requires fewer samples to generate quasi-noise-free references, which is particularly useful when ASL CBF data are limited. In the second part of this dissertation, we propose a novel deep learning neural network, i.e., Dilated Wide Activation Network (DWAN), that is optimized for ASL denoising. Our method presents two novelties: first, we incorporated the wide activation residual blocks with a dilated convolution neural network to achieve improved denoising performance in term of several quantitative and qualitative measurements; second, we evaluated our proposed model given different inputs and references to show that our denoising model can be generalized to input with different levels of SNR and yields images with better quality than other methods. In the final part of this dissertation, a prior-guided and slice-wise adaptive outlier cleaning (PAOCSL) method is proposed to improve the original Adaptive Outlier Cleaning (AOC) method. Prior information guided reference CBF maps are used to avoid bias from extreme outliers in the early iterations of outlier cleaning, ensuring correct identification of the true outliers. Slice-wise outlier rejection is adapted to reserve slices with CBF values in the reasonable range even they are within the outlier volumes. Experimental results show that the proposed outlier cleaning method improves both CBF quantification quality and CBF measurement stability.
    • Macronutrient Activation of Endothelium Dependent Leukocyte Trafficking: Metabolic Implications

      Scalia, Rosario; Autieri, Michael V.; Houser, Steven R.; Kilpatrick, Laurie; Shore, Scott K.; Soprano, Dianne R. (Temple University. Libraries, 2015)
      Obesity and insulin resistance are characterized by elevated pro-inflammatory proteins in the blood and immune cell accumulation in the visceral adipose tissue. Resident leukocytes release tumor necrosis factor α (TNFα) and other inflammatory cytokines which stimulate adipocyte lipolysis, recruit leukocytes to adipose tissue, promote pro-inflammatory immune cell polarization, facilitate oxidative stress, and activate intracellular kinases which dull insulin signaling cascades in metabolic tissues. Immune cell mediated dysregulation of stromal and parenchymal cells has raised suspicion that insulin resistance is an immune disorder initiated by activated white blood cells with over-nutrition. Efforts to improve pathological metabolism by reducing inflammation have yielded mixed results in humans and animal models. The role of inflammation and immune cell accumulation in the visceral fat (VF) in the progression of insulin resistance remains presently debated. There is, however, a consensus that identifying the triggers for obesity and impaired insulin signaling is of the utmost importance. The goal of this report is to identify dietary fat absorption as a key initiator of inflammatory action and insulin desensitization which may be dampened by reducing immune cell accumulation in adipose tissue. To explore how lean, healthy organisms become obese and insulin resistant, we examined the inflammatory consequences of isocaloric but variable macronutrient loads in the VF of lean mice. Mice were administered single liquid meals composed of low-fat (10% fat) or high-fat (60% fat) diet and observed by intravital microscopy to quantify leukocyte-endothelium interactions in mesenteric postcapillary venules (MPCV) 1, 2, 3, and 4 hours after oral gavage. Leukocyte rolling and leukocyte adhesion were transiently elevated within 1 hour after feeding and returned to baseline levels 4 hours later. Endothelial cell surface expression of P-selectin (Psel), a rapidly activated cell adhesion molecule (CAM), confirmed that high-fat feeding induced Psel dependent leukocyte rolling through the VF microcirculation. Furthermore, leukocyte accumulation in the VF was modestly increased by a single high-fat meal (HFM). Repetitive high-fat diet (HFD) consumption for 24 hours prolonged elevated leukocyte-endothelium interactions and promoted neutrophil accumulation in the VF. The neutrophilic enzyme myeloperoxidase (MPO), a producer of the chlorinating agent hypochlorous acid, increased in abundance and activity in the VF of HFM fed mice. Elevated leukocyte-endothelium interactions, leukocyte infiltration, and MPO activity in VF were not observed in Psel deficient (Psel-/-) mice following lipid overload. To ascertain if MPO is required for sustained endothelial activation, leukocyte-endothelium interactions and leukocyte infiltration were monitored in high-fat fed MPO deficient (MPO-/-) mice. Similar to the Psel-/- mice, MPO-/- mice were protected from the inflammatory effects of high-fat feeding. Our data supports postprandial hyperlipemia as an inducer of transient and Psel dependent inflammatory reactions that are sustained by prolonged HFD consumption. To study whether early phase inflammatory interventions granted late phase metabolic improvements, wild-type (WT), Psel deficient (Psel-/-), and MPO deficient (MPO-/-) C57BL/6 mice were given ad libitum access to LFD (10% fat) or HFD (60% fat) for 12-16 weeks. All mouse groups given HFD became obese. Prolonged HFD consumption sustained elevated leukocyte-endothelium interactions in MPCVs and was accompanied by increased local and systemic TNFα in WT mice. High-fat fed WT mice were hyperglycemic, hyperinsulinemic, glucose intolerant, and insulin resistant compared to LFD fed controls. Psel-/- mice were protected from leukocyte-endothelium interactions as well as local and systemic TNFα accumulation despite extended HFD consumption. Surprisingly, high-fat fed Psel-/- mice were equally hyperglycemic, hyperinsulinemic, glucose intolerant, and insulin resistant as the inflamed, high-fat fed WT mice. MPO-/- mice were also protected from elevated systemic TNFα and gained slightly less weight than the other high-fat fed groups. While MPO-/- mice were hyperglycemic and glucose intolerant, they did have improved insulin stimulated glucose clearance. The data presented in this report demonstrates the pro-inflammatory nature of postprandial hyperlipemia and the insulin desensitizing nature of prolonged HFD consumption. Ablation of VF immune cell accumulation by Psel deletion is not sufficient for improving insulin signaling or glycemic control, which is consistent with prior reports. Deletion of MPO, however, did result in slightly less obesity and marginally improved insulin signaling. We conclude that while immune cell accumulation in the VF contributes to the progression of insulin resistance, it is not a prerequisite for metabolic pathology development.
    • Macroscopic Coupling Conditions with Partial Blocking for Highway Ramps

      Seibold, Benjamin; Klapper, Isaac; Piccoli, Benedetto, 1968- (Temple University. Libraries, 2015)
      We consider the Lighthill-Whitman-Richards traffic model on a network consisting of a highway with an off ramp, connected by a junction. We compare the known coupling conditions for the evolution of traffic at the junction and suggest a novel improvement to the existing conditions. That is, we resolve the spurious effects that arise in standard models, namely clogging of the main highway and vehicle destination changes. We achieve this by tracking vehicle density buildup in the form of a queue, which is modeled by an ODE. We define the solution to the Riemann problem at the junction using the supply and demand functions. The numerical approximation is carried out using a modified Godunov scheme, adjusted to take into account the effects of an emptying queue. Exact and numerical comparisons of the model with existing models verify that the number of vehicles who wish to exit are preserved and the nonphysical clogging of the main highway does not occur.
    • MAGNESIUM DIBORIDE (MGB2) THIN FILMS ON COPPER AND SILICON FOR RADIOFREQUENCY CAVITY AND ELECTRONIC APPLICATIONS

      Xi, Xiaoxing; Iavarone, Maria; Chen, Ke; Nassiri, Alireza (Temple University. Libraries, 2018)
      Magnesium diboride is a known material since the 1950s. However, superconductivity in MgB2 was discovered in 2001. Soon after the discovery of superconductivity in MgB2, there was a rush to understand its complex nature of superconductivity and other properties. However, current research in MgB2 is mainly focused on applications. MgB2 possesses excellent superconducting properties such as a high transition temperature (Tc) of 39 K, a high critical current density (Jc) of ~107 A·cm-2, a high thermodynamic critical field (Hc), absence of weak links at grain boundaries, etc. Because of these properties, it is considered one of the candidate materials for applications such as superconducting wires, superconducting radiofrequency (SRF) cavities, superconducting electronic devices, etc. SRF cavities play an important role in modern particle accelerators. The main objective of an SRF cavity is to accelerate charged particle beams. SRF cavities are characterized by two figures of merit: the quality factor (Q) and the accelerating gradient (Eacc). Q characterizes the energy efficiency of an RF cavity and Eacc is the average accelerating field of an RF cavity. The state-of-the-art SRF technology is based on niobium. It is a well-matured technology and it is reaching the theoretical limits on both Q and Eacc. Additionally, Nb cavities operate at 2 K, which requires large-scale liquid helium refrigeration and distribution systems. This adds substantial capital and operational costs for large particle accelerators such as HL-LHC and proposed ILC. Because of these reasons, new SRF materials with higher Q, higher Eacc, and higher operational temperatures are desired. Currently, few superconducting materials such as Nb3Sn and MgB2 are in the research and development process. Nb3Sn has a Tc of 18 K, which is significantly lower than the Tc of MgB2. MgB2-coated cavities are theoretically predicted to have higher Q and Eacc compared to Nb cavities. In addition, owing to its high Tc, MgB2-coated cavities are expected to operate above 4.2 K (20-25 K). Operation at around 20–25 K will allow the use of hydrogen- or neon-based cryocooler technology, eliminating the use of helium. This will substantially reduce the capital and operational cost of a MgB2-based accelerator. However, this will not be possible with Nb3Sn-based SRF cavities due to the low Tc of Nb3Sn. The main goal of the research presented in this thesis is to develop MgB2-coated copper superconducting radiofrequency cavities utilizing hybrid physical-chemical vapor deposition (HPCVD) technique. MgB2-coated Cu SRF cavities will have an added advantage due to the high thermal conductivity of the Cu. The excellent thermal conductivity of Cu enhances the heat transfer between the superconducting MgB2 layer and the cavity body, thus providing better resistance to thermal breakdown. RF characterization of MgB2–coated Cu is a crucial requirement because it is the first step toward the MgB2 –coated Cu SRF cavities. For these characterizations, small-sized samples (e.g., 2-inch diameter) are usually required. Among several MgB2 growth techniques, the HPCVD process produces the best quality MgB2 thin films. However, the growth of MgB2 films on Cu using the HPCVD technique is challenging as Mg, and Cu readily react to form several Mg-Cu alloys. Therefore, a new MgB2 growth process on Cu was developed by modifying the existing HPCVD process and in the new process, the deposition takes place at ~470 °C. With this new process, high-quality MgB2 thin films were successfully deposited on 2-inch diameter Cu discs, and these samples were characterized in terms of structural and superconducting properties. Surface morphology showed well-connected crystallites with no pinholes on the coating, and the cross-sectional studies showed conformal growth of MgB2 on Cu. The Tc of these samples were ~37 K and the ~107 A·cm-2 zero field Jc was observed. Most importantly, RF characterizations at 11.4 GHz showed Q close to 2 x 107 at 4 K, which was comparable to the Q of Nb. After successful RF testing of MgB2-coated Cu discs, this process was scaled up to coat 3 GHz Cu RF cavities. As the first step, a MgB2 thin film was synthesized on the inner wall of Cu tubes with dimensions (~1.5-inch inner diameter and 8-inch length), similar to a beam tube of a 3 GHz RF cavity. The MgB2 film on the Cu tubes showed conformal coating with Tc ~37 K. Next, the coating of the 3 GHz Cu test cavity was carried out. Cu test cavities were assembled using two half-cells pressed at Thomas Jefferson National Accelerator Facility (JLab) and two beam tubes machined at Temple University. The MgB2 film was successfully synthesized on the inner wall of 3 GHz test cavities and the MgB2 coating on the two half-cells showed uniform growth with Tc distributed around 35 K. However, slight damages to the cavity wall were observed and these damages were mainly due to the deformation of the Cu surface, caused by the formation of Mg-Cu alloy liquid. Current research is focused on developing damage-free MgB2-coated Cu RF cavities. In addition to MgB2 growth on Cu for SRF cavity applications, development of high-quality MgB2 thin film on Si substrates was carried out. This will be used in electronic device applications such as fabrication of hot-electron bolometers (HEB). An issue similar to the Mg-Cu reaction was observed with Si; Si and Mg react at elevated temperatures, forming Mg2Si, and this was observed at around 550°C. This reaction prevents the use of the HPCVD technique directly on Si. Previous attempts at synthesizing MgB2 films on Al2O3-buffered Si substrates at low temperatures (500–600°C) were reported. However, these films have shown extremely rough surfaces with poor superconducting properties. In this work, a ~220 nm-thick boron buffer layer was used to prevent the Mg-Si reaction, and it was observed that the boron was effective even above 700°C. High-quality MgB2 thin films were synthesized on boron-buffered Si substrates using the standard HPCVD technique. However, the resultant films showed enhanced roughness due to the polycrystalline growth. Ar ion milling at an ultra-low angle (1°) was used to smooth the MgB2 films, and the resultant films showed roughness comparable to epitaxial films grown on SiC substrates with a slight degrade in superconducting properties. Finally, Al ion implantation in the MgB2 thin film was studied and this project was carried out to synthesize MgB2 films with modified superconducting properties. In this study, 80 nm-thick MgB2 films were irradiated with a 75 keV Al ion beam. A 30 nm Au buffer layer was used on top of the MgB2 films in order to position the projected range of Al ions near the center of the MgB2 films. Al ion doses were kept between 2×1011–1×1016 atoms·cm-2. Superconducting properties and the structural properties of these Al ion irradiated films showed systematic change with the Al dose. Superconducting transition temperature decreased with increasing Al dose. Also, for the Al ion dose at or above 2 × 1014 atoms·cm-2, the irradiated samples did not show any superconducting transition. Al ion irradiated films showed an increase in the c-axis lattice parameter of MgB2 with increasing ion dose. These observed changes in the superconducting properties and structural properties of Al ion irradiated films can be attributed to the ion damage.
    • Magnesium Diboride Devices and Applications

      Chen, Ke; Tao, R. (Rongjia); Iavarone, Maria; Wolak, Matthaeus A. (Temple University. Libraries, 2018)
      Magnesium diboride MgB2 is an interesting material that was discovered to be a superconductor in 2001. It has a remarkably high critical temperature of 39 K which is much greater than was previously thought possible for a phonon-mediated superconductor. MgB2 was also the first material found to exhibit multiple gap superconductivity. It has two energy gaps, the pi gap with a value of 2.3 meV, and the sigma gap with a value of 7.1 meV. Both the high critical temperature and the multiple large energy gaps make MgB2 an attractive candidate for superconducting devices. While the initial discovery of MgB2 was accompanied by much excitement, the enthusiasm has mostly disappeared due to the lack of progress made in implementing MgB2 in practical devices. The aim of this thesis is to attempt to reinvigorate interest in this remarkable material through a study of a variety of practical superconducting devices made with MgB2 thin films grown by hybrid physical-chemical vapor deposition (HPCVD). Two different methods of fabricating MgB2 Josephson junctions are explored. The first is a sandwich type trilayer configuration with a barrier made by magnetron sputtered MgO. Junctions of this sort have been previously studied and implemented in a variety of devices. While they do show some attractive properties, the on-chip spread in critical current due to barrier non-uniformity was too high to be considered a viable option for use in many-junction devices. By developing a fabrication scheme which utilizes electron beam lithography, modest improvements were made in the on-chip parameter spread, and miniaturization of junction size yielded some insight into the non-uniform barriers. The second approach of creating MgB2 Josephson junctions utilized a planar geometry with a normal metal barrier created by irradiating nano-sized strips of the material with a focused helium ion beam. The properties of these junctions are investigated for different irradiation doses. This new technique is capable of producing high quality junctions and furthermore the parameter spread is greatly reduced as compared to the sandwich type junctions. While more research is necessary in order to increase the IcRn products, these junctions show promise for use in many-junction devices such as RSFQ circuits. Prior to this work, the largest substrates that could be coated with HPCVD grown MgB2 were 2" in diameter. A new chamber was designed and constructed which demonstrated the ability to coat substrates as large as 4". This scaled-up system was used to grow MgB2 films on 1 x 10 cm flexible substrates. A method of fabrication was developed which could pattern these 10 cm long samples into ribbon cables consisting of many high frequency transmission lines. This technology can be utilized to increase the cooling efficiency of cryogenic systems used for RSFQ systems which require many connections between low temperature and room temperature electronics. Finally, a method of producing MgB2 films with thicknesses as low as 8 nm was developed. This is achieved by first growing thicker films and using a low angle ion milling step to gradually reduce the film thickness while still maintaining well connected high quality films. A procedure was developed for fabricating meandering nanowires in these films with widths as low as 100 nm for use as superconducting nanowire single photon detectors (SNSPDs). A study of the transport properties of these devices is first presented. Measurements show low values of kinetic inductance which is ideal for high count rates in SNSPDs. The kinetic inductance measurements also yielded the first measurements of the penetration depth of MgB2 films in the ultra-thin regime. Devices made from these ultra-thin films were found to be photon sensitive by measurements made by our collaborators.
    • MAGNESIUM DIBORIDE JOSEPHSON JUNCTIONS FOR SUPERCONDUCTING DEVICES AND CIRCUITS

      Xi, Xiaoxing; Chen, Ke; Iavarone, Maria; Neretina, Svetlana (Temple University. Libraries, 2013)
      Superconductivity in magnesium diboride (MgB2) was first discovered in 2001. It is unique in that it has two superconducting gaps. The transition temperature of 39 K exceeded the maximum transition temperature thought to be possible through phonon mediated superconductivity. Through the study of MgB2, a general paradigm is being formulated to describe multi-gap superconductors. The paradigm includes inter-band and intra-band scattering between the gaps which can cause a smearing of the gap parameter over a distribution instead of a single value. Although each gap is individually thought to be well described by the BCS theory, the interaction between the two gaps causes complications in describing the overall superconducting properties of MgB2. The focus of this work was to lay the groundwork for an MgB2-based Josephson junction technology. This includes improving on a previously established baseline for all-MgB2 Josephson junctions, utilizing the Josephson Effect to experimentally verify a model pertaining to the two-gap nature of MgB2, specifically the magnetic penetration depth, and designing, fabricating, and testing multi-junction devices and circuits. The experiments in this work included fabrication of Josephson Junctions, DC superconducting quantum interference devices (SQUIDs), Josephson junction arrays, and a rapid single flux quantum (RSFQ) circuit. The junctions were all made utilizing the hybrid physical-chemical vapor deposition method, with an MgO sputtered barrier. The current process consists of three superconducting layers which are patterned using standard UV photolithography and etched with Ar ion milling. There were SQUIDS made with sensitivity to magnetic fields parallel to the film surface, which were used to measure the inductance of MgB2 microstrips. This inductance was used in design of more complicated devices as well as in calculating the magnetic penetration depth of MgB2, found to be about 40 nm at low temperature, in good agreement with a previously published theoretical model. Planar-type DC SQUIDs were also made to present the feasibility of the technology for application purposes. The large voltage modulation of over 500 μV at 15 K for these devices along with operation up to 37 K shows that MgB2 is a potential replacement for low temperature devices. The junction series arrays were fabricated with 100 junctions of equal size to present the ever-increasing robustness of the technology. The devices served well to measure the large property spread associated with these junctions and have been well established as a diagnostic tool for improving this spread. The culmination of this work was a basic RSFQ toggle flip flop circuit. A DC measurement of these circuits yielded digital operation up to 180 GHz at low temperature and about 63 GHz at 20 K. This is not yet near the potential limit of MgB2 established by the value of the superconducting gap parameters, but a huge success in showing that MgB2 is a viable option for pursuing superconducting digital electronics suitable for low power, cryogen-free operation.
    • Magnesium Diboride Superconducting Devices and Circuits

      Xi, Xiaoxing; Chen, Ke; Davidson, Bruce A.; Chopra, Harsh Deep (Temple University. Libraries, 2015)
      While magnesium diboride (MgB2) was first synthesized in the 1950s, MgB2’s superconductive properties were not discovered until 2001. It has the highest superconducting transition temperature of all the metallic superconductors at ~39 K at atmospheric pressure. MgB2 is also unique in that it has a two superconductive gaps, a pi gap at 2 meV and a sigma gap at 7.1 meV. There are a theoretical models discussing the inter- and intra- gap scattering of the superconductivity of MgB2 and the Josephson transport of MgB2 Josephson Junctions. The focus of this work is to further the study of all-MgB2 Josephson junctions and quantum interference device technology. This work discusses the transport in all-MgB2 Josephson junctions and designing, fabricating, and measuring multi-junction devices. The junctions studied include all-MgB2 sandwich-type Josephson junctions (one with TiB2 normal conducting barrier and another with an MgO insulating barrier). The junction MgB2 films were deposited by hyprid physical-vapor deposition and the junction barrier were deposited by sputtering. The junctions were patterned and etched with UV photolithography and argon ion milling. With the TiB2 barrier we studied Josephson transport by the proximity effect. With these junctions, we also observed complete suppression of the critical current by an applied magnetic field showing for the first time a leakage free barrier in an all-MgB2 Josephson junction with a single ultrathin barrier. We also studied junctions utilizing MgO barrier deposited by reactive sputtering which gave a larger characteristic voltage of 1-3 mV compared to TiB2 barriers. By connecting several SQUIDs with varying loop areas we developed of two types of superconducting quantum interference filters (SQIFs). The first SQIF designed with 21 SQUIDs connected in parallel and the SQUID loops are sensitive to magnetic fields applied parallel to the substrate. The SQUID loop areas were designed to vary in such a way that the voltage modulation gave a unique peak corresponding to the absolute value of the applied magnetic field. The SQIF shows an antipeak height of 0.25 mV with a transfer function of 16 V/T at 3 K. The lowest noise measured for this SQIF is 110 pT/Hz1/2. The second SQIF is designed with 17 SQUIDs in parallel and the SQUID loops are sensitive to magnetic field perpendicular to the substrate. This SQIF has shown improved voltage modulation with a peak height of 1 mV and a transfer function of 7800 V/T. The noise sensitivity was measured at 70 pT/Hz1/2. The sensitivity of the SQIF shows MgB2 potential superconductor to improve performance of current superconductive electronics. Utilizing known all-MgB2 junctions and SQUID parameters two rapid single flux quantum (RSFQ) circuits were designed and tested. A toggle flip flop (TFF) operating as a frequency divider was developed. The TFF design consisted of a Josephson transmission line, a splitter, and an interferometer (a DC SQUID). The TFF utilized an improved designed, compared to previous all-MgB2 TFFs, and showed operation up to 335 GHz at 7 K and operation up to 30 K. A low frequency set-reset flip flop (SRFF) was also developed to demonstrate RSFQ digital logic. The SRFF design includes a DC-SFQ converter, a Josephson transmission line, and an inductively coupled readout SQUID. The SRFF demonstrates proper digital logic by toggling between a high and low voltage state with a sequential set and reset input. While these developed devices are not close to the potential that MgB2 allows, they do show the promise MgB2 based devices have in making more sensitive and faster superconductive logic devices.
    • Magnetic Signature Estimation Using Neural Networks

      Biswas, Saroj K.; Ferrese, Frank; Higgins, Frank P.; Silage, Dennis (Temple University. Libraries, 2012)
      Ferrous objects in earth's magnetic field cause distortion in the surrounding ambient field. This distortion is a function of the object's material properties and geometry, and is known as the magnetic signature. As a precursor to first principle modeling of the phenomenon and a proof of concept, the goal of this research is to predict offboard magnetic signatures from on-board sensor data using a neural network. This allows magnetic signature analysis in applications where direct field measurements are inaccessible. Simulated magnetic environments are generated using MATLAB's Partial Differential Equation toolbox for a 2D geometry, specifically for a rectangular shell. The resulting data sets are used to train and validate the neural network, which is configured in two layers with ten neurons. Sensor data from within the shell is used as network inputs, and the off-board field values are used as targets. The neural network is trained using the Levenberg-Marquardt algorithm and the back propagation method by comparing the estimated off-board magnetic field intensity to the true value. This research also investigates sensitivity, scalability, and implementation issues of the neural network for signature estimation in a practical environment.
    • MAGNETISM IN A NUMBER OF METAL ORGANIC FRAMEWORKS (MOFs) WITH 1D AND 3D CHARACTERISTICS: AN EXPERIMENTAL AND ANALYTICAL STUDY

      Yuen, Tan; Lin, Chyan-Long; Riseborough, Peter; Li, Jing, Dr.; Myer, George H. (Temple University. Libraries, 2012)
      Metal Organic Frameworks (MOFs) exhibit many excellent physical properties including magnetic properties for potential applications in devices. More importantly for the subject of this thesis, MOFs are ideal for the realization of low dimensional magnetism because of the large selection of ligands connecting magnetic centers in making the framework. The materials studied in this thesis include ten magnetic MOFs of the form M(L1)(L2) [M = Cu, Ni, Co, Fe, Mn; L1 = NDC, bpdc, BDC, BODC, N3; L2 = DMF, H2O, TED, bpy]. Polycrystalline powder samples as well as single crystal samples were synthesized. Their crystal structures were determined, and their magnetic and thermodynamic properties were measured and analyzed. Eight of these materials were characterized as 1D magnets and two as 3D magnets. In the 1D case it is found that above Tm [the temperature at which the magnetic susceptibility χ(T) has a peak] the magnetic behavior of MOFs (S ≥ 1) can be well described with the Classical Fisher Model (CFM). Near and below TC the spins take a more definite orientation than allowed for in the CFM and hence the Ising Model (IM) was used for fitting. Both CFM and IM yield fairly consistent intrachain couplings (J) when applied in their appropriate temperature region. To estimate the interchain exchange (J′), the susceptibility for a magnetic chain in the mean field of neighboring chains is used. In all cases, as expected, the ratio of J to J′ was less than 10%. The special case of Cu(N3)2bpy (S = ½) was analyzed with the spin ½ IM. Although the specific heat data (Ctotal) for most of the 1D MOFs showed no clear phase transition, a low temperature fit to the electron-phonon specific heats yielded apparent heavy fermion-like &gamma values on the order of several hundred mJ/mol K2. The lattice specific heat (C lattice) was estimated using a Debye-Einstein hybrid model. Subtracting Clattice from Ctotal, magnetic specific heat (CM) with a broad peak characteristic of low dimensional magnetism was obtained. The peak in CM was at temperature near that expected from χ(T) fits. The J values obtained from the magnetic specific heat fits were in good agreement with those obtained from χ(T) fits. Once the magnetic specific heat was accounted for, γtakes values in the expected range of few mJ/mol K2. For 3D MOFs [Mn(N3)2bpy and Fe(N3)2bpy], the existence of long range canted antiferromagnetic ordering was observed in both magnetic and specific heat measurements with phase transitions at 38 K and 20 K in the case of Mn(N3)2bpy and Fe(N3)2bpy, respectively. These transition temperatures are considered fairly high for molecular based materials. In both Mn(N3)2bpy and Fe(N3)2bpy, the χ(T) data fit well to the Heisenberg model for a diamond-type network. The transition can clearly be seen with an abrupt increase in the magnetization below TC and a shift to a higher temperature in the specific heat when measured under an applied magnetic field. The systematic approach in this work led to the successful estimate of C lattice resulting in meaningful fitting of χ(T) and Cmagnetic to the appropriate theoretical models in magnetism. It also led the discovery of ferrimagnets or canted antiferromagnets M(N3)2bpy with large coercivity and rather high transition temperature. The results of this study have been published in three articles in the Journal of Applied physics, and two manuscripts are under preparation for submission [1-5].
    • Making an Avant-Garde Composition: Intersections of Composition Theory and Innovative Poetics

      Goldblatt, Eli; Harrington, Susanmarie; Osman, Jena; Wells, Susan, 1947- (Temple University. Libraries, 2011)
      The Making of an Avant-Garde Composition: Intersections of Composition Theory and Innovative Poetics, explores how current discussions in the field of Composition and Rhetoric intersect with the theories and practices of select members of the avant-garde poetry community, focusing on the issues of genre, identity, and language. It examines each of these issues by juxtaposing discussions of leading Composition and Rhetoric scholars with creative and critical work of avant-garde poets, identifying common concerns, and describing diverse approaches to creating innovative writing practices. It demonstrates the connections between Theresa Hak Kyung Cha's multilingual text, DICTEE, and recent scholarship by Min-Zhan Lu and A. Suresh Canagarajah on multilingual student writers in order to argue for more discussion of language politics and linguistic awareness in the composition classroom. It also outlines the connections between Harryette Mullen's creative and critical work and scholarship by Donna LeCourt and Roz Ivanic on writer identity to explore new approaches to interpreting and responding to student texts. Finally, it reads Susan Howe's The Midnight in conversation with leading genre theorists such as Amy Devitt and compositionists such as Robert Davis and Mark Shadle who argue for assigning multigenre papers.
    • Making Friends: Teacher Influence on Students' Peer Relationships

      Rotheram-Fuller, Erin; Farley, Frank; Cromley, Jennifer; DuCette, Joseph P.; Thurman, S. Kenneth (Temple University. Libraries, 2011)
      A total of 236 kindergarten to eighth grade students and 15 teachers from an elementary school in a northeastern U.S. city provided information about their perceptions of teacher involvement in students' peer relationships. Students provided additional information about classroom social networks. Both students and teachers indicated that they perceive teachers to be important in student peer relationships. None of the teacher characteristics (including teacher education, years of teaching, or ethnicity) were related to teacher perceptions of involvement in students' peer relationships. In lower grade groups (kindergarten to second grade), there were significant sex differences, with boys rating their teachers as more involved than girls; sex differences were not significant in either the middle (third to fifth grade) or upper (sixth to eighth grade) grade groups. As hypothesized, there were significant differences between grade groups, with students in the lower grades rating their teacher as more involved than students in either the middle or upper grade groups, and middle grade groups rating their teachers as more involved than the upper grade groups. Teacher and student perceptions of teacher involvement in students' peer relationships were then analyzed to determine whether these perceptions were related to classroom cohesiveness, as measured by social networks. The results were not significant, indicating that teacher and student perceptions of teacher involvement in students' peer relationships were not related to classroom social networks. This research provides a first look into both teacher and student perceptions into teacher involvement in classroom peer relationships, which school psychologists can use to help teachers construct supportive classroom environments. This research is a case study of one school, and therefore generalization from this sample is difficult. Future research should examine this element in schools of varying climate and region.
    • Making History: Applications of Digitization and Materialization Projects in Repositories

      Bruggeman, Seth C., 1975-; Finkel, Kenneth; Rizzo, Mary, 1975- (Temple University. Libraries, 2014)
      This project draws upon material culture, digital humanities, and archival theory and method in the service of public history investigations. After selecting an artifact and performing object analysis, I will digitize the artifact and materialize a new object. I will then perform another object analysis on the 3D printed object. This exercise will provide the familiar benefits of object analysis, but the decisions and interactions necessary to digitize and materialize the object provide a fresh perspective. I will propose approaches for performing similar investigations in repositories, along with a pedagogical argument for doing so. By emphasizing modularity, flexibility, and minimal capital requirements, I hope these approaches can be adapted to a variety of institutions and audiences. Researchers will reap the benefits of intellectual and emotional engagement, hands-on learning, and technological experimentation. Public historians will have the opportunity to engage in outreach and innovative education and exploration of their collections.
    • Making Sense of Change: Sexuality Transformation at Midlife

      Ericksen, Julia A., 1941-; Delaney, Kevin; Grasmuck, Sherri; Goode, Judith, 1939- (Temple University. Libraries, 2011)
      This research examines the sense-making activities of women who engage in intimate relationships with women following a significant period of heterosexual marriage. Using data gathered through interviews with 36 women, the study explores how subjects use common cultural ideas about sexuality to frame the stories they tell to explain their sexual histories. The idea that sexuality is something one is born with, rather than a choice is on the rise in the United States. This essentialist view in conjunction with cultural ideas about the timing at which sexuality is supposed to emerge implies that people should be "aware" of their sexuality at adolescence. For many of the women in the study that "normal" timing was not the case. In addition to the essentialist supposition is the notion the sexuality is binary. One is either heterosexual or one is the particular type of person known as the homosexual, a construct created in the 19th century that continues to be an important part of modern understandings of sexuality. Women who have spent significant time as heterosexuals and go on to have intimate relationships with women must contend with these cultural understandings as they try to make sense to themselves of a sexual story that seems to lie outside the bounds of that hegemonic narrative. Using modified grounded theory to analyze the collected interviews, four story types emerged. These four story types evinced different levels and types of commitment to the views of sexuality that exist in both the mainstream culture and the gay and lesbian community. They include "Always Knew" and "Retrospective" stories, which demonstrated a close commitment to the dominant narrative. The other two types - "Shifter" stories and "Left Fielder" stories - were more loosely connected to the ideas of essential and binary sexuality. As these stories emerged additional insights were provided in the form of the women's discussions of the impact of the social world in terms of lesbian invisibility, lesbian imagery, homophobia, and group or individual support for telling certain types of stories and/or taking on a lesbian identity. This study builds on, and adds to, scholarship in a number of areas. These include: narrative and identity; the social construction of sexuality; the changing nature of biography as people strive to make the past make sense of the present; and the influence of hegemonic cultural ideas in important areas of social and personal life. Additionally the study provides some insight into how heterosexuality is both a "goes without saying" sexuality route as well as a sometimes problematic achievement.
    • Making Water Pure: A History of Water Softening From Potash to Tide

      Roney, Jessica C. (Jessica Choppin), 1978-; Isenberg, Andrew C. (Andrew Christian); Lowe, Hilary Iris; Simon, Bryant; Smith-Howard, Kendra (Temple University. Libraries, 2020)
      Making Water Pure: A History of Water Softening from Potash to Tide, is a history of water softening in the United States from 1860 through 1970. Water’s materiality, specifically its tendency to dissolve geological features, consistently interfered with labor processes, especially those that relied on the use of soap or steam. For this reason, the management and control over the quality of water in both domestic and industrial spaces was regular and in many cases economically imperative. Nineteenth-century laborers dealt with hard water on the individual level. They experimented with a variety of different chemicals and methods, including the addition of lye, coffee, blood meal, and wool fiber to water. Throughout the twentieth century, the requirements of industrial efficiency as well as new consumer technologies demanded fast, easy, and standard ways to soften water. This motivated manufactures to produce mechanical water softening systems and synthetic chemicals. This dissertation traces this change and asserts that the history of getting water soft is a history of environmental control and management. Water softening is a lens through which to explore often overlooked actors in the history of managing nonhuman nature such as women, domestic workers, laborers, home economists, advertisers, and commercial chemists. Hard water is a thread that connects usually separate categories such as the home and the factory, industrial chemicals and household cleaners. The control over water was uneven and incomplete and allows for the exploration of the tensions intrinsic in the attempted mastery over nature. The regularity of making soft water reveals not only society’s relationship with water, but the social nature of water itself. Water is a product of ecological, social, and technological discourses and practices-- a hybrid of both environment and culture. To soften water was to make nature fit; it was an effort to standardize nonhuman nature so that it would cooperate with certain technologies, processes, and cultural assumptions.
    • Malebranche's Theodicy for Natural Evils

      Chamberlain, Colin; Gjesdal, Kristin; Wolfsdorf, David, 1969-; Newlands, Samuel (Temple University. Libraries, 2021)
      My dissertation examines Malebranche’s theodicy for natural evils (i.e., Malebranche’s reconciliation of the existence of God with the existence of natural evils). In Chapter 1, entitled “The Conceptual Possibility of Natural Evils,” I explain how Malebranche conceives of certain natural things (e.g., pains, deformities/monstrosities, and disasters) as natural evils. Chapter 1 is preliminary: it clarifies Malebranche’s conception of natural evils as certain deviations from the biological forms that agree with the dictates of God’s Reason or wisdom. In Chapter 2, entitled “The Physical Possibility of Natural Evils,” I explain how Malebranche’s God produces natural evils in the physical world. Similar to Chapter 1, Chapter 2 is preliminary: it clarifies the causal involvement of Malebranche’s God in His production of natural evils, and it therefore specifies His activities that are to be reconciled with His absolute perfection. In Chapter 3, entitled “The Theological Possibility of Natural Evils,” I reconstruct Malebranche’s theodicy for natural evils by explaining how Malebranche’s God – who is by definition absolutely perfect – performs the aforespecified activities that result in natural evils. On my reconstruction, Malebranche’s God is determined by His absolute perfection – His Reason or wisdom, more precisely – to bring about natural evils, so natural evils do not pose any threat to His absolute perfection, and, accordingly, the existence of God is reconciled with the existence of natural evils. In light of this examination of Malebranche’s theodicy for natural evils, I make clear Malebranche’s contribution to the early modern development of rationalism: Malebranche articulates the central role of God’s Reason or wisdom in determining the purposes and causal histories of natural things, which amounts to the rationalization of the normative and descriptive dimensions of nature, respectively.
    • MALOCCLUSION PREVALENCE IN A NORTH PHILADELPHIA ORTHODONTIC POPULATION

      Sciote, James J.; Godel, Jeffrey H.; Moore, John V., III (Temple University. Libraries, 2021)
      Objectives: This study aims to examine malocclusion traits of a racially diverse population to determine the validity of the malocclusion prevalence reported in the NHANES III survey. Additionally, the cephalometric database from the American Association of Orthodontists Foundation Legacy Collection (AAOF-LC) was used for skeletal malocclusion prevalence. The sample used data collected at the Temple University orthodontic screening clinic (TUKSoD) from 2012-2020.Methods: Malocclusion prevalence of the TUKSoD population (n=7713) was compared to the NHANES III (n=7000) and AAOF-LC (n=1198) for dental and skeletal traits respectively. The TUKSoD population is 51.5% Black, 38% Hispanic, 2.7% White, 1.1% Asian, 0.2% American-Indian, and 1.1% other; age range 6-78 (mean 21.05±10.47), 60.4% females/39.6% males. The AAOF-LC is comprised primarily of Caucasian patients; age range 1-47, 48% females/52% males. The NHANES III survey included Black, Caucasian, and Mexican-American participants, with results weighted to represent American population demographics. Traits were compared in the transverse (dental), vertical (dental/skeletal), and sagittal (dental/skeletal) planes. Prevalence was recorded as percentage of the total population. Results: Significant differences were found for all dental comparisons: Sagittal (Class-I,II,III; p=8.59E-7), Vertical (Open-bite/Deep-bite; p=1.53E-13), and Transverse (crossbites). Significant differences were found for all skeletal comparisons: Sagittal (Class-I,II,III; p=5.38E-6), and Vertical (Open-bite/Deep-bite; p=8.89E-5). Conclusion: TUKSoD serves a diverse patient population which has significantly different skeletal and dental malocclusion prevalence compared to the control populations. These differences are likely the result of the genetic influences underlying the demographics. As the NHANES III and AAOF-LC represent common standards, comparison to genetically heterogenous contemporary populations is challenging, underscoring the need for more personalized approaches to determining malocclusion demographic characteristics.