Physical Sciences and Mathematics Commons^™

The Belle Ii Physics Book, E. Kou, P. Urquijo, W. Altmannshofer, F. Beajean, G. Bell, M. Beneke, I. I. Bigi, F. Bishara, M. Blanke, C. Bobeth, M. Bona, N. Brambilla, V. M. Braun, J. Brod, A. J. Buras, H. Y. Cheng, C. W. Chiang, M. Ciuchini, G. Colangelo, Milind Purohit, Et. Al.

Faculty Publications

No abstract provided.

Measurement Of The Integrated Luminosity Of The Phase 2 Data Of The Belle Ii Experiment, F. Abudinén, I. Adachi, P. Ahlburg, H. Aihara, N. Akopov, A. Aloisio, F. Ameli, L. Andricek, N. Anh Ky, D. M. Asner, H. Atmacan, T. Aushev, V. Aushev, T. Aziz, K. Azmi, V. Babu, S. Baehr, S. Bahinipati, A. M. Bakich, Milind Purohit, Et. Al.

Faculty Publications

From April to July 2018, a data sample at the peak energy of the Υ(4S) resonance was collected with the Belle II detector at the SuperKEKB electron-positron collider. This is the first data sample of the Belle II experiment. Using Bhabha and digamma events, we measure the integrated luminosity of the data sample to be (469.3±0.3±3.0) pb^-1, where the first uncertainty is statistical and the second is systematic. This work provides a basis for future luminosity measurements at Belle II.

Computational Screening Of New Perovskite Materials Using Transfer Learning And Deep Learning, Xiang Li, Yabo Dan, Rongzhi Dong, Zhuo Cao, Chengcheng Niu, Yuqi Song, Shaobo Li, Jianjun Hu

Faculty Publications

As one of the most studied materials, perovskites exhibit a wealth of superior properties that lead to diverse applications. Computational prediction of novel stable perovskite structures has big potential in the discovery of new materials for solar panels, superconductors, thermal electric, and catalytic materials, etc. By addressing one of the key obstacles of machine learning based materials discovery, the lack of sufficient training data, this paper proposes a transfer learning based approach that exploits the high accuracy of the machine learning model trained with physics-informed structural and elemental descriptors. This gradient boosting regressor model (the transfer learning model) allows us …

Search For B− → Λp⊽ ⊽ With The Babar Experiment, J. P. Lees, V. Poireau, V. Tisserand, E. Grauges, A. Palano, G. Eigen, D. N. Brown, Yu G. Kolomensky, M. Fritsch, H. Koch, T. Schroeder, R. Cheaib, C. Hearty, T. S. Mattison, J. A. Mckenna, R. Y. So, V. E. Blinov, A. R. Buzykaev, V. P. Druzhinin, Milind Purohit, Et. Al.

Faculty Publications

A search for the rare flavor-changing neutral current process B− → Λp̅ νv̅ using data from the BABAR experiment has been performed. A total of 424 fb⁻¹ of e⁺e⁻ collision data collected at the center-of-mass energy of the ϒ(4S) resonance is used in this study, corresponding to a sample of (471 ± 3) × 10⁶ BB̅ pairs. Signal B− → Λp̅ νv̅ candidates are identified by first fully reconstructing a B⁺ decay in one of many possible exclusive decays to hadronic final states, then examining detector activity that is not associated with …

Importance Of Refractory Ligands And Their Photodegradation For Iron Oceanic Inventories And Cycling, Christel Hassler, Damien Cabanes, Sonia Blanco-Ameijeiras, Sylvia G. Sander, Ronald Benner

Faculty Publications

Iron is an essential micronutrient that limits primary production in up to 40% of the surface ocean and influences carbon dioxide uptake and climate change. Dissolved iron is mostly associated with loosely characterised organic molecules, called ligands, which define key aspects of the iron cycle such as its residence time, distribution and bioavailability to plankton. Models based on in situ ligand distributions and the behaviour of purified compounds include long-lived ligands in the deep ocean, bioreactive ligands in the surface ocean and photochemical processes as important components of the iron cycle. Herein, we further characterise biologically refractory ligands in dissolved …

Machine Learning To Quantitate Neutrophil Netosis, Laila Elsherif, Noah Sciaky, Carrington A. Metts, Md. Modasshir, Ioannis Rekleitis, Christine A. Burris, Joshua A. Walker, Nadeem Ramadan, Tina M. Leisner, Stephen P. Holly, Martis W. Cowles, Kenneth I. Ataga, Joshua N. Cooper, Leslie V. Parise

Faculty Publications

We introduce machine learning (ML) to perform classifcation and quantitation of images of nuclei from human blood neutrophils. Here we assessed the use of convolutional neural networks (CNNs) using free, open source software to accurately quantitate neutrophil NETosis, a recently discovered process involved in multiple human diseases. CNNs achieved >94% in performance accuracy in diferentiating NETotic from non-NETotic cells and vastly facilitated dose-response analysis and screening of the NETotic response in neutrophils from patients. Using only features learned from nuclear morphology, CNNs can distinguish between NETosis and necrosis and between distinct NETosis signaling pathways, making them a precise tool for …

Molecular Properties Are A Primary Control On The Microbial Utilization Of Dissolved Organic Matter In The Ocean, Yuan Shen, Ronald Benner

Faculty Publications

The global ocean sequesters a large amount of reduced carbon in dissolved organic molecules that can persist for centuries to millennia. The persistence of dissolved organic carbon (DOC) in the deep ocean has been attributed to inherently refractory molecules and to low concentrations of molecules, but the relative roles of molecular properties and molecular concentrations remain uncertain. We investigate both of these possibilities using bioassay experiments with unfiltered seawater collected from five depths (50–1500 m) at the Bermuda Atlantic Time-Series Study site. The microbial utilization of compositionally distinct forms of seawater DOC at in situ and elevated concentrations was determined. …

Lorentz- And C P T -Violating Standard Model Extension In Chiral Perturbation Theory, Brett Altschul, Matthias R. Schindler

Faculty Publications

Lorentz and CPT violation in hadronic physics must be tied to symmetry violations at the underlying quark and gluon level. Chiral perturbation theory provides a method for translating novel operators that may appear in the Lagrange density for color-charged parton fields into equivalent forms for effective theories at the meson and baryon levels. We extend the application of this technique to the study of Lorentzviolating and potentially CPT-violating operators from the minimal standard model extension. For dimension-4 operators, there are nontrivial relations between the coefficients of baryon-level operators related to underlying quark and gluon operators with the same Lorentz structures. …

Observation Of Τ−→Π−ΝΤE+E− And Search For Τ−→Π−Ντμ+Μ−, Y. Jin, H. Aihara, D. Epifanov, I. Adachi, S. Ai. Said, D. M. Asner, V. Aulchenko, T. Aulchenko, T. Aushev, R. Ayad, V. Babu, I. Badhrees, S. Bahinipati, V. Bansal, P. Behera, M. Berger, V. Bhardwaj, T. Bilka, J. Biswal, Milind Purohit, Et. Al.

Faculty Publications

We present the first measurements of branching fractions of rare tau-lepton decays, τ−→π−ντℓ+ℓ− (ℓ=e or μ), using a data sample corresponding to 562 fb⁻¹ collected at a center-of-mass energy of 10.58 GeV with the Belle detector at the KEKB asymmetric-energy e⁺e⁻collider. The τ−→π⁻ν_τe⁺e⁻ decay is observed for the first time with 7.0σ significance. The partial branching fraction determined by the structure-dependent mechanisms mediated by either a vector or an axial-vector current for the mass region M_πee > 1.05 GeV=c² is measured to be B(τ⁻ → π …

First Measurement Of Neutrino Oscillation Parameters Using Neutrinos And Antineutrinos By Nova, M. A. Acero, P. Adamson, L. Aliaga, T. Alion, V. Allakhverdian, S. Altakarli, N. Anfimov, A. Antoshkin, A. Aurisano, A. Back, C. Backhouse, M. Baird, N. Balashov, P. Baldi, B. A. Bambah, S. Bashar, K. Bays, S. Bending, R. Bernstein, V. Bhatnagar, Roberto Petti, Et. Al.

Faculty Publications

The NOvA experiment has seen a 4.4σ signal of ⊽ _e appearance in a 2 GeV⊽_μ beam at a distance of 810 km. Using 12.33×10²⁰ protons on target delivered to the Fermilab NuMI neutrino beamline, the experiment recorded 27 ⊽_μ→⊽_e candidates with a background of 10.3 and 102⊽_μ→⊽_μ candidates. This new antineutrino data are combined with neutrino data to measure the parameters |Δm ² ₃₂ | = 2.48 ^+0.11 _-0.06 x 10 ^-3 eV² / c⁴ and sin² θ₂₃ in the ranges …

Cdse Quantum Dot Surface Chemistry Thermodynamics Via Isothermal Titration Calorimetry: An Emphasis On The Fundamentals, Megan Y. Gee

Theses and Dissertations

For several decades, the study and development of colloidal semiconductor nanocrystals, or quantum dots (QD), has become a rich field heralding improved integration into applications ranging from photovoltaics and photocatalysis to biomedical imaging and drug delivery. CdxSey is the most extensively studied QD system, however numerous compositional details still confound the nanocrystal field. Although CdSe QDs with native ligand coatings can show high fluorescence quantum yield and may be suitable for some applications, often times these original ligand layers are comprised of long aliphatic chains that preclude incorporation into biological matrices or severely impede charge transfer – depending on the …

Machine Learning Based Ultra High Carbon Steel Image Segmentation, Sumith Kuttiyil Suresh

Theses and Dissertations

Mechanical and structural properties of ultra-high carbon steel are determined by their microstructures composed of constituents such as pearlite and spheroidites. Locating micro constituents and quantitatively measuring its presence is key for material researchers to study the physical properties of the carbon steel materials. This micrograph analysis is currently done manually and subjectively by material scientists, which is tedious and time-consuming. Here we propose to apply the image segmentation algorithm called U-Net to achieve automated labeling of steel microstructures on a subset of ultra- high carbon steel image dataset containing pearlite and spheroidite as the primary micro constituents. Our work …

Frontiers In Fast Voltammetry: Novel Analytes And Applications, Jordan Holmes

Theses and Dissertations

Electrochemical sensors are beneficial towards the development and advancement of monitoring devices. As this type of technology progresses, so does our ability to create state-of-the-art sensing strategies to probe environmental and biological systems at the source. In the environment, it is essential to monitor particularly harmful contaminants like trace metals in order to better mitigate risk. Additionally, biological molecules are often times challenging to measure because matrices are complex and difficult to probe; Recent advancements in chemical ex vivo and in vivo sensing platforms have offered insight into physiological processes. The brain in particular requires a sophisticated, implantable sensor as …

Study Of Transition State Stabilization Using Molecular Rotors, Erik Carl Vik

Theses and Dissertations

Molecular devices that function as rotors and measurement devices are the main topic of this dissertation. Each study contains a device based on an N-phenylimide framework, which has restricted rotation about the N-C (imide-phenyl) single bond due to a steric clash from the imide carbonyl and the phenyl rings ortho substituent. In general, two ground states are observed by 1H NMR, which are separated by a single transition state (TS). Incorporation of non-covalent interactions into the TS led to measurable changes in the rate for rotation. While the molecules in this dissertation revealed details that could not have been predicted, …

Elucidating The Mechanism Of Bone Morphogenetic Protein (Bmp) -Mediated Sox2 Downregulation In Ovarian Cancer, Zainab Motolani Shonibare

Theses and Dissertations

Sex determining region Y-box 2 (Sox2) is a transcription factor essential for maintaining self-renewal and pluripotency of undifferentiated embryonic stem cells. Sox2 is involved in multiple processes of cancer cells, however, regulation of Sox2 expression and the consequences of that regulation in cancer remains elusive. Previously, we demonstrated that BMP9/GDF2 is significantly reduced in expression in ovarian cancer (OVCA) cells, methylated in patient tumors and, promoted anoikis resistance in both breast and OVCA cell lines. In an attempt to identify genes downstream of BMP9 that may provide anoikis resistance, transcriptomics was performed leading to the identification of Sox2, a developmental …

Person Identification With Convolutional Neural Networks, Kang Zheng

Theses and Dissertations

Person identification aims at matching persons across images or videos captured by different cameras, without requiring the presence of persons’ faces. It is an important problem in computer vision community and has many important real-world applica- tions, such as person search, security surveillance, and no-checkout stores. However, this problem is very challenging due to various factors, such as illumination varia- tion, view changes, human pose deformation, and occlusion. Traditional approaches generally focus on hand-crafting features and/or learning distance metrics for match- ing to tackle these challenges. With Convolutional Neural Networks (CNNs), feature extraction and metric learning can be combined in …

Semantic Segmentation Considering Image Degradation, Global Context, And Data Balancing, Dazhou Guo

Theses and Dissertations

Recently, semantic segmentation – assigning a categorical label to each pixel in an im- age – plays an important role in image understanding applications, e.g., autonomous driving, human-machine interaction and medical imaging. Semantic segmentation has made progress by using the deep convolutional neural networks, which are sur- passing the traditional methods by a large margin. Despite the success of the deep convolutional neural networks (CNNs), there remain three major challenges.

The first challenge is how to segment the degraded images semantically, i.e., de- graded image semantic segmentation. In general, image degradations increase the difficulty of semantic segmentation, usually leading to …

Learning The Land: Indians, Settlers, And Slaves In The Southern Borderlands, 1500-1850, William Cane West

Theses and Dissertations

Between 1500 and 1850, Native Americans, Europeans, and enslaved African Americans competed for territory within the landscape of the lower Arkansas Valley. The complex transitional environment between delta bottomlands, interior highlands, and Great Plains fostered the co-existence of competing Native and Euro-American claims to regional sovereignty and settlement well into the nineteenth century. The geopolitical divides often hinged on debates over environmental resources and scientific practices. Indigenous polities from the Mississippians to the Quapaws and Osages adapted to environmental changes to establish and maintain their borders in the face of European colonial presence. In the nineteenth century, Cherokees and white …

A Spatial Heterodyne Spectrometer For Raman Imaging And Remote Spectroscopy, Ashley Nicole Allen

Theses and Dissertations

Raman and Laser-Induced Breakdown Spectroscopy (LIBS) are optical techniques that provide information about the chemical makeup of a sample without any preparation or physical contact with it. For this reason, Raman and LIBS spectrometers are among the instruments selected for NASA’s Mars 2020 rover mission and are being considered for future missions to the Jovian moons, asteroids and comets. Such future missions will require smaller, more ruggedized Raman and LIBS spectrometers, and the new type of spectrometers discussed here, the spatial heterodyne Raman and LIBS spectrometers are being developed for this purpose. The SHS is a wide-field, Fourier transform, stationary …

Numerical Methods For A Class Of Reaction-Diffusion Equations With Free Boundaries, Shuang Liu

Theses and Dissertations

The spreading behavior of new or invasive species is a central topic in ecology. The modelings of free boundary problems are widely studied to better understand the nature of spreading behavior of new species. From mathematical modeling point of view, it is a challenge to perform numerical simulations of free boundary problems, due to the moving boundary, the stiffness of the system and topological changes.

In this work, we design numerical methods to investigate the spreading behavior of new species for a diffusive logistic model with a free boundary and a diffusive competition system with free boundaries. We develop a …

Cybersecurity Issues In The Context Of Cryptographic Shuffling Algorithms And Concept Drift: Challenges And Solutions, Hatim Alsuwat

Theses and Dissertations

In this dissertation, we investigate and address two kinds of data integrity threats. We first study the limitations of secure cryptographic shuffling algorithms regarding preservation of data dependencies. We then study the limitations of machine learning models regarding concept drift detection. We propose solutions to address these threats.

Shuffling Algorithms have been used to protect the confidentiality of sensitive data. However, these algorithms may not preserve data dependencies, such as functional de- pendencies and data-driven associations. We present two solutions for addressing these shortcomings: (1) Functional dependencies preserving shuffle, and (2) Data-driven asso- ciations preserving shuffle. For preserving functional dependencies, …

Macromolecular Engineering Of Biomass Polymers And Stimuli-Responsive Materials Towards Enhanced Thermomechanical Properties, Meghan E. Lamm

Theses and Dissertations

Commodity polymers are used in every aspect of daily life, and most of these polymeric materials are synthesized using petroleum-derived sources. There are direct environmental consequences to this petroleum dependence including greenhouse gas emissions and climate change. Biomass-based polymers show promise for the mitigation on negative environmental impact, in comparison with petroleum-derived counterparts. However, some biopolymers suffer from low chain entanglement due to bulky or long side chain structures, resulting in poor mechanical properties. In this dissertation work, macromolecular engineering is used to design biomass-derived polymers featuring a variety of structures and functionalities. Additionally, biopolymer properties (including thermomechanical enhancement) and …

Studies On The Mechanism And Application Of Steam Thermography, Raymond Gerard Belliveau Iii

Theses and Dissertations

The detection of blood on fabrics for forensic purposes is a widely studied topic in forensic science, and to that end, effort in this laboratory has been devoted to developing a thermal imaging method called steam thermography. Steam thermography is a method used to enhance chemical contrast in thermographic images by exposing a surface to water vapor during imaging. The exposure of water vapor to the surface generates heat, and can differentially increase the thermographically measured apparent temperature of imaged surfaces. This can result in thermographic contrast between surfaces with different chemical properties. Previously reported proposed mechanisms to describe the …

Heterogeneous Ozonation Of Model Drinking Water Contaminants Using Cbv-720 Zeolite, Benson Maxwell Solomon

Theses and Dissertations

Advanced Oxidation Processes (AOPs) are designed to remove aqueous organic contaminants through their reaction with hydroxyl radicals (HO∙). Ozone is classified as an AOP due to its ability to produce hydroxyl radicals, as well as its ability to oxidize a wide range of organic contaminants. Due to the unselective nature of hydroxyl radicals, many organic and inorganic co-solutes can act as scavengers, reducing the efficiency of an AOP. Here we show a probe system for testing the hypothesis that adsorptive ozonation of contaminants may yield a more selective environment that favors neutral contaminant oxidation over oxidation of co-solutes.

Initial experiments …

The Development Of Multi-Functional System That Combine Patterned Hydrogels, Plasmin-Degradable Nanoparticles And Stem Cells For Applications In Tissue Engineering And Growth Factors Delivery, Safaa I. Kader

Theses and Dissertations

This thesis spots the light on the development of a novel multi-functionalized system for application in tissue engineering and on-demand morphogens delivery. Three types of materials used in this study are synthetic polymer, biopolymer, and nanomaterials. Polyethylene glycol (PEG), a synthetic polymer was chosen in this study because of its high biocompatibility, non-immunogenicity, inert nature, ease of modification, and reduces protein denaturation to provide a wide range of physical and mechanical properties. Here, PEG is used one time as a hydrogel, linear polyethylene glycol-co-lactide (LPELA), and another time as peptide-PEG based nanoparticles (PxSPCP). Gelatin, a natural polymer has been widely …

Properties, Learning Algorithms, And Applications Of Chain Graphs And Bayesian Hypergraphs, Mohammad Ali Javidian

Theses and Dissertations

Probabilistic graphical models (PGMs) use graphs, either undirected, directed, or mixed, to represent possible dependencies among the variables of a multivariate probability distri- bution. PGMs, such as Bayesian networks and Markov networks, are now widely accepted as a powerful and mature framework for reasoning and decision making under uncertainty in knowledge-based systems. With the increase of their popularity, the range of graphical models being investigated and used has also expanded. Several types of graphs with dif- ferent conditional independence interpretations - also known as Markov properties - have been proposed and used in graphical models.

The graphical structure of a …

Designing, Constructing, And Employing Two-Dimensional Ultrafast Spectroscopy To Resolve Complex Kinetics, Jason R. Darvin

Theses and Dissertations

Multiple population-period transient spectroscopy (MUPPETS) is a two dimensional ultrafast time resolved spectroscopy technique. MUPPETS uses three pairs of optical pulses over two time periods to separate homogeneous and heterogeneous causes of rate dispersion. This dissertation details improvements to the MUPPETS optical assembly enabling measurements on systems that previously fell outside of the MUPPETS 2-ns time window. In addition, the theoretical groundwork is laid to unveil the hidden coordinate controlling rate exchange using 2D and 3D correlation functions.

The first project details improvements made to the MUPPETS assembly. A detailed method was developed to eliminate astigmatism, coma, and spherical aberration …

Studies Of Ch Activation In Unsaturated Amides And Esters By Trinuclear Metal Carbonyl Clusters Of Osmium, Morteza Maleki

Theses and Dissertations

The chemistry of the reaction of Os3(CO)10(NCCH3)2 with representatives of unsaturated amides and esters, RCOCHCH2 (R=(CH3)2N, CH3O) has been investigated. In these reactions, it has been observed that a CH bond on the β-carbon atom is readily activated by triosmium carbonyl clusters. The activation of β-carbon C-H bond in unsaturated amides and esters provides a robust platform for studying multicenter C-H bond transformations and for C-C bond formation via hydrogen shift and CO insertion processes. In this work, proposed mechanistic approaches have been taken in order to better understand and study the relationship between the characterized species. In addition, a …

Stacked Modelling Framework, Kareem Abdelfatah

Theses and Dissertations

The thesis develops a predictive modeling framework based on stacked Gaussian processes and applies it to two main applications in environmental and chemical en- gineering. First, a network of independently trained Gaussian processes (StackedGP) is introduced to obtain analytical predictions of quantities of interest (model out- puts) with quantified uncertainties. StackedGP framework supports component- based modeling in different fields such as environmental and chemical science, en- hances predictions of quantities of interest through a cascade of intermediate predic- tions usually addressed by cokriging, and propagates uncertainties through emulated dynamical systems driven by uncertain forcing variables. By using analytical first and …

Green Forest Businesses As A Method To Improve Communities In Unesco’S East Usambara Biosphere Reserve In Tanzania, Myoung Su Ko

Theses and Dissertations

A number of developing countries, especially those in Africa which have experienced former colonization, are still struggling with exploitation of their natural resources. Throughout the development of environmental management, the strategy of natural resource management has evolved from mistreating the environment for economic and social development, to separating human activities from the environment for extreme environmental protection, to ensuring the interaction between human life and environment for sustainable development. Although an abundance of natural resources, and particularly forests, exist in the protected areas, the residents in communities surrounding protected areas are usually economically and socially poor.

With this situation, the …