Physical Sciences and Mathematics Commons^™

The Reveal: A Technical Study And Conservation Treatment Of An Overpaint Portrait, Camille Ferrer

Art Conservation Master's Projects

A severely damaged 19th-century oil painting depicting a portrait of a woman was treated at Patricia H. and E. Garman Art Conservation Department. A typed letter provided by the owner mentioned that it has been previously restored yet returned with unsatisfactory results. After further examination, the painting appeared to have been previously treated multiple times by different people. There was overpaint distinctly present on the face and later discovered to be present overall. The full state of condition of the painting was initially unknown due to the sum of the surface being overpainted. However, there were evidence of paint loss …

Excited State Processes In Radical Elaborated Platinum Donor-Acceptor Complexes, Sangita Paudel

Chemistry and Chemical Biology ETDs

Organo-transition metal complexes are being widely studied to understand their photophysical properties for their wide range of applications as efficient emitters in organic light emitting diodes (OLEDs), light emitting electrochemical cells (LEECs), etc. Cyclometalated organo-transition metal complexes such as cyclometalated square planar platinum(II) complexes are becoming suitable candidates for such applications because of their highly efficient luminescence. Understanding the excited properties of such complexes is useful in designing highly efficient and color tunable phosphors with desired excited state lifetimes. We aim to explore the influence of radical substituents on electronic structure, luminescence quantum efficiencies, and excited state lifetimes by synthesizing …

Rice Biomass Response To Various Phosphorus Fertilizers In A Phosphorus-Deficient Soil Under Simulated Furrow-Irrigation, Jonathan B. Brye

Crop, Soil and Environmental Sciences Undergraduate Honors Theses

Wastewater-recovered phosphorus (P), in the form of the mineral struvite (MgNH4PO4⋅6H2O), may provide a sustainable alternative to rapidly decreasing rock phosphate reserves. Struvite can be generated via chemical and/or electrochemical precipitation methods, potentially reducing the amount of P runoff to aquatic ecosystems. The objective of this greenhouse tub study was to evaluate the effects of chemically- and electrochemically precipitated struvite (CPST and ECST, respectively) on above- and belowground plant response in a hybrid rice cultivar (Gemini 214, RiceTec) grown using furrow-irrigation compared to other common fertilizer-P sources [i.e., triple super phosphate (TSP) and diammonium phosphate (DAP)] in a P-deficient silt …

Stability Of Quantum Computers, Samudra Dasgupta

Doctoral Dissertations

Quantum computing faces a persistent challenge with noise. This dissertation addresses the fundamental question of how to define and differentiate computational accuracy, result reproducibility, output stability, and device reliability amidst spatio-temporal non-stationarity in quantum registers. It explores characterizing spatial and temporal noise statistics, estimating performance limits via characterization data, mitigating time-varying quantum noise with adaptive algorithms, and understanding trade-offs when using unreliable devices. Sources of noise include interaction between qubits and the environment, as well as imperfections in implementing quantum logic gates, leading to decoherence (the loss of coherence) in quantum states. Quantum states' survival is brief, making reliable output …

Transiam: Aggregating Multi-Modal Visual Features With Locality For Medical Image Segmentation, Xuejian Li, Shiqiang Ma, Junhai Xu, Jijun Tang, Shengfeng He, Fei Guo

Research Collection School Of Computing and Information Systems

Automatic segmentation of medical images plays an important role in the diagnosis of diseases. On single-modal data, convolutional neural networks have demonstrated satisfactory performance. However, multi-modal data encompasses a greater amount of information rather than single-modal data. Multi-modal data can be effectively used to improve the segmentation accuracy of regions of interest by analyzing both spatial and temporal information. In this study, we propose a dual-path segmentation model for multi-modal medical images, named TranSiam. Taking into account that there is a significant diversity between the different modalities, TranSiam employs two parallel CNNs to extract the features which are specific to …

Simulated Annealing With Reinforcement Learning For The Set Team Orienteering Problem With Time Windows, Vincent F. Yu, Nabila Y. Salsabila, Shih-W Lin, Aldy Gunawan

Research Collection School Of Computing and Information Systems

This research investigates the Set Team Orienteering Problem with Time Windows (STOPTW), a new variant of the well-known Team Orienteering Problem with Time Windows and Set Orienteering Problem. In the STOPTW, customers are grouped into clusters. Each cluster is associated with a profit attainable when a customer in the cluster is visited within the customer's time window. A Mixed Integer Linear Programming model is formulated for STOPTW to maximizing total profit while adhering to time window constraints. Since STOPTW is an NP-hard problem, a Simulated Annealing with Reinforcement Learning (SARL) algorithm is developed. The proposed SARL incorporates the core concepts …

Recommendations With Minimum Exposure Guarantees: A Post-Processing Framework, Ramon Lopes, Rodrigo Alves, Antoine Ledent, Rodrygo L. T. Santos, Marius Kloft

Research Collection School Of Computing and Information Systems

Relevance-based ranking is a popular ingredient in recommenders, but it frequently struggles to meet fairness criteria because social and cultural norms may favor some item groups over others. For instance, some items might receive lower ratings due to some sort of bias (e.g. gender bias). A fair ranking should balance the exposure of items from advantaged and disadvantaged groups. To this end, we propose a novel post-processing framework to produce fair, exposure-aware recommendations. Our approach is based on an integer linear programming model maximizing the expected utility while satisfying a minimum exposure constraint. The model has fewer variables than previous …

On A Multivalued Prescribed Mean Curvature Problem And Inclusions Defined On Dual Spaces, Vy Khoi Le

Mathematics and Statistics Faculty Research & Creative Works

This article addresses two main objectives. First, it establishes a functional analytic framework and presents existence results for a quasilinear inclusion describing a prescribed mean curvature problem with homogeneous Dirichlet boundary conditions, involving a multivalued lower order term. The formulation of the problem is done in the space of functions with bounded variation. The second objective is to introduce a general existence theory for inclusions defined on nonreflexive Banach spaces, which is specifically applicable to the aforementioned prescribed mean curvature problem. This problem can be formulated as a multivalued variational inequality in the space of functions with bounded variation, which, …

Tropical Fish Study In Tahiti, French Polynesia, Miranda Brainard, Caitlyn Swango, Paityn Houglan, Richard Londraville

Williams Honors College, Honors Research Projects

In May of 2023, I embarked on an exciting research journey to Moorea, French Polynesia, alongside fellow students and faculty members from the University of Akron and Syracuse University. This expedition was part of the university-sponsored Tropical Vertebrate Biology course, where we delved into the exploration of various tropical species inhabiting the island, including sea urchins, geckos, and my primary focus, the blackspotted rockskipper.

My research team, composed of my co-authors and me, was particularly intrigued by the unique refuge-seeking behavior displayed by blackspotted rockskippers. These amphibious fish are renowned for their remarkable ability to inhabit tide pools and rocky …

Formulating An Efficient Statistical Test Using The Goodness Of Fit Approach With Applications To Real-Life Data, S. A. Qaid, S. E. Abo Youssef Prof., Mahmoud Mansour

Basic Science Engineering

Statistical tests are very important for researchers to make decisions. In particular, when the tests are non-parametric, they are of greater importance because they can be applied to a wide range of data sets regardless of knowing the distribution of these data. Researchers are therefore racing to obtain efficient tests for making good decisions based on the results of these tests. In this study, NBU (2)L was used based on the goodness of fit approach to present an efficient statistical test. The efficiency of the proposed test was computed, and the results were compared to those of other tests. Critical …

Multiscale Modelling Of Brain Networks And The Analysis Of Dynamic Processes In Neurodegenerative Disorders, Hina Shaheen

Theses and Dissertations (Comprehensive)

The complex nature of the human brain, with its intricate organic structure and multiscale spatio-temporal characteristics ranging from synapses to the entire brain, presents a major obstacle in brain modelling. Capturing this complexity poses a significant challenge for researchers. The complex interplay of coupled multiphysics and biochemical activities within this intricate system shapes the brain's capacity, functioning within a structure-function relationship that necessitates a specific mathematical framework. Advanced mathematical modelling approaches that incorporate the coupling of brain networks and the analysis of dynamic processes are essential for advancing therapeutic strategies aimed at treating neurodegenerative diseases (NDDs), which afflict millions of …

Predictive Power Of Wastewater For Nowcasting Infectious Disease Transmission: A Retrospective Case Study Of Five Sewershed Areas In Louisville, Kentucky, Fayette Klaassen, Rochelle H. Holm, Ted Smith, Ted Cohen, Aruni Bhatnagar, Nicolas A. Menzies

Faculty Scholarship

Background: Epidemiological nowcasting traditionally relies on count surveillance data. The availability and quality of such count data may vary over time, limiting representation of true infections. Wastewater data correlates with traditional surveillance data and may provide additional value for nowcasting disease trends. Methods: We obtained SARS-CoV-2 case, death, wastewater, and serosurvey data for Jefferson County, Kentucky (USA), between August 2020 and March 2021, and parameterized an existing nowcasting model using combinations of these data. We assessed the predictive performance and variability at the sewershed level and compared the effects of adding or replacing wastewater data to case and death reports. …

From Grain To Malt: Tracking Changes Of Ultra-Low-Gluten Barley Storage Proteins After Malting, Mahya Bahmani, Angéla Juhász, Utpal Bos, Mitchell G. Nye-Wood, Malcolm Blundell, Crispin A. Howitt, Michelle L. Colgrave

Research outputs 2022 to 2026

Barley (Hordeum vulgare L.) is a major cereal crop produced globally. Hordeins, the major storage proteins in barley, can trigger immune responses leading to celiac disease or symptoms associated with food allergy. Here, proteomics approaches were employed to investigate the proteome level changes of grain and malt from the malting barley cultivar, Sloop, and single-, double- and triple hordein-reduced lines. The triple hordein-reduced line is an ultra-low gluten barley cultivar, Kebari®. Using discovery proteomics, 2,688 and 3,034 proteins in the barley and malt samples were detected respectively. Through the application of targeted proteomics, a significant reduction in the quantity …

Dilf: Differentiable Rendering-Based Multi-View Image-Language Fusion For Zero-Shot 3d Shape Understanding, Xin Ning, Zaiyang Yu, Lusi Li, Weijun Li, Prayag Tiwari

Computer Science Faculty Publications

Zero-shot 3D shape understanding aims to recognize “unseen” 3D categories that are not present in training data. Recently, Contrastive Language–Image Pre-training (CLIP) has shown promising open-world performance in zero-shot 3D shape understanding tasks by information fusion among language and 3D modality. It first renders 3D objects into multiple 2D image views and then learns to understand the semantic relationships between the textual descriptions and images, enabling the model to generalize to new and unseen categories. However, existing studies in zero-shot 3D shape understanding rely on predefined rendering parameters, resulting in repetitive, redundant, and low-quality views. This limitation hinders the model’s …

Big Code Search: A Bibliography, Kisub Kim, Sankalp Ghatpande, Dongsun Kim, Xin Zhou, Kui Liu, Tegawende F. Bissyande, Jacques Klein, Traon Yves Le

Research Collection School Of Computing and Information Systems

Code search is an essential task in software development. Developers often search the internet and other code databases for necessary source code snippets to ease the development efforts. Code search techniques also help learn programming as novice programmers or students can quickly retrieve (hopefully good) examples already used in actual software projects. Given the recurrence of the code search activity in software development, there is an increasing interest in the research community. To improve the code search experience, the research community suggests many code search tools and techniques. These tools and techniques leverage several different ideas and claim a better …

Confined Feni Alloy Nanoparticles In Carbon Nanotubes For Photothermal Oxidative Dehydrogenation Of Ethane By Carbon Dioxide, Jinqiang Zhang, Meng Li, Xiaojie Tan, Lei Shi, Kun Xie, Xiaoli Zhao, Shuaijun Wang, Shiyong Zhao, Huayang Zhang, Xiaoguang Duan, Haijun Chen, Yuezhao Zhu, Mingbo Wu, Hongqi Sun, Shaobin Wang

Research outputs 2022 to 2026

Oxidative dehydrogenation of ethane with CO2 (ODEC) is an attractive reaction for reduction of carbon footprints and ethene production. In this work, we present photothermal catalysis on confined bimetal catalysts for ODEC. Carbon nanotubes confined non-noble bimetal alloy (i.e., CoNi@CNTs and FeNi@CNTs) catalysts were prepared and FeNi@CNTs showed effective performance in photothermal catalytic ODEC to ethene. Experiments and simulations reveal that UV and visible lights (420 – 490 nm) are responsible for ODEC and non-oxidative dehydrogenation of ethane, respectively, to ethene. Additionally, ODEC to ethene is preferred to C-C cracking to methane on FeNi@CNTs in light ( > 490 nm)-induced thermocatalysis. …

Single Night Surveys Of Moth Communities Can Serve As Ultra-Rapid Biodiversity Assessments, Daniel P. Duran, Matthew Timar, Blaine Rothauser

School of Earth & Environment Faculty Scholarship

Biodiversity conservation decisions are typically based on limited data and resources. For this reason, there is great interest in surveying taxa that may allow for a rapid assessment of the biodiversity at a site. Numerous taxa have been proposed and utilized for rapid assessments that allow for such a survey in a matter of weeks or less. Herein, we test the idea that nocturnal moths have many of the characteristics that make them ideal for such surveys, such as relative ease of identification, strong ecological association with specific plant species and habitats, high alpha diversity, extended seasonal activity, and ease …

Μakka: Mutation Testing For Actor Concurrency In Akka Using Real-World Bugs, Mohsen Moradi Moghadam, Mehdi Bagherzadeh, Raffi Takvor Khatchadourian Ph,D,, Hamid Bagheri

Publications and Research

Actor concurrency is becoming increasingly important in the real-world and mission-critical software. This requires these applications to be free from actor bugs, that occur in the real world, and have tests that are effective in finding these bugs. Mutation testing is a well-established technique that transforms an application to induce its likely bugs and evaluate the effectiveness of its tests in finding these bugs. Mutation testing is available for a broad spectrum of applications and their bugs, ranging from web to mobile to machine learning, and is used at scale in companies like Google and Facebook. However, there still is …

Perception Of Bias In Chatgpt: Analysis Of Social Media Data, Abdullah Wahbeh, Mohammad A. Al-Ramahi, Omar El-Gayar, Ahmed El Noshokaty, Tareq Nasralah

Computer Information Systems Faculty Publications

In this study, we aim to analyze the public perception of Twitter users with respect to the use of ChatGPT and the potential bias in its responses. Sentiment and emotion analysis were also analyzed. Analysis of 5,962 English tweets showed that Twitter users were concerned about six main types of biases, namely: political, ideological, data & algorithmic, gender, racial, cultural, and confirmation biases. Sentiment analysis showed that most of the users reflected a neutral sentiment, followed by negative and positive sentiment. Emotion analysis mainly reflected anger, disgust, and sadness with respect to bias concerns with ChatGPT use.

Energy Extraction, Or Lack Thereof, Nishanth Gudapati

Mathematics

The problem of stability of rotating black holes is the subject of a long standing research program since the 1960s and remains an unresolved problem in general relativity. A major obstacle in the black hole stability problem is that the energy of waves propagating through rotating black holes spacetimes is not necessarily positive-definite, due to the so called ergo-region. This is a serious complication that limits the efficacy of most mathematical techniques. In this expository article, we report that, despite the ergo-region, there exists a positive-definite total energy for axisymmetric Maxwell, gravitational and electrovacuum perturbations of Kerr and Kerr–Newman black …