Physical Sciences and Mathematics Commons^™

Future-Oriented Coastal Protection: The Utility Of Living Shorelines Under Changing Climatic Conditions, Gabriella R. Dipetto, Donna Marie Bilkovic, Taylor M. Sloey, Erik S. Yando, Erik L. Walters

Biological Sciences Faculty Publications

An accumulation of novel nature-based shoreline management techniques have developed over the past two decades out of the continued need to protect waterfront land combined with an awareness of the relationship between healthy coastal ecosystems and human societies. Shoreline protection strategies such as living shorelines incorporate these nature-based approaches to simultaneously enhance ecosystem functioning while providing shoreline stabilization benefits. The continued role of these approaches into the future, however, will be challenged by a rapidly changing coastal environment. While living shorelines have received global attention and integration into climate policy and governance frameworks, the ability of shoreline systems to withstand …

Symbiodiniaceae Shifts Over The Last Decade On The Hottest Coral Reefs On Earth, Anna Fiesinger, Rachel Alderdice, Luigi Colin, Hannah Manns, Gabriela Perna, Kathryn H. Stankiewicz, Jacob J. Valenzuela, Line K. Bay, Daniel J. Barshis, Nitin S. Baliga, Iliana B. Baums, John A. Burt, Christian R. Voolstra

Biological Sciences Faculty Publications

Corals in the Persian/Arabian Gulf (PAG) are resilient to various stressors, whose levels exceed those of coral reefs globally. These corals thereby offer insight into mechanisms underlying thermal resilience, e.g., regarding the role of endosymbiotic microalgae in the family Symbiodiniaceae. Previous studies have identified the thermotolerant species Cladocopium thermophilum as broadly associated with corals in the southern PAG. However, algal-host specificity at the within-species level and the temporal stability of these associations are not well understood. Here we sampled two dominant stony corals (Porites harrisoni, n = 119 and Platygyra daedalea, n = 79) at three sites …

Summer Temperature Maxima Already Challenge Thermal Capacities Of Coral In The Southern Persian/Arabian Gulf, Rachel Alderdice, Gabriela Perna, Hannah Manns, Anna Fiesinger, Luigi Colin, Kathryn Stankiewicz, Kelly Gomez-Campo, Samantha Goyen, Line Bayse, Nitin Baliga, Jake Valenzuela, Iliana B. Baums, Daniel J. Barshis, John A. Burt, Christian R. Voolstra

Biological Sciences Faculty Publications

The future of coral reefs remains uncertain as intensifying ocean warming continues to drive coral decline and demise worldwide. Corals occurring in extreme environments such as the Persian/Arabian Gulf (PAG), the world’s warmest sea, represent a promising resource to study the genetic architecture of thermal tolerance. However, their thermal capacities remain unresolved. We applied short-term heat stress assays using the Coral Bleaching Automated Stress System (CBASS) to determine signatures of thermal tolerance from three common species (Porites harrisoni, Platygyra daedalea, and Cyphastrea microphthalma) across three sites (two in the extreme southern PAG and a more benign …

Carbon Dynamics Across The Mangrove-Tidal Flat Ecotone In A Tropical Seascape, E. S. Yando, I. J.B. Alemu, L. Kiah Eng, T. M. Sloey, M. Van Breugel, Bhatia N. Friess

Biological Sciences Faculty Publications

Mangroves and other blue carbon ecosystems are important for climate through the storage and sequestration of carbon. Most research estimates carbon dynamics by subsampling central portions of the ecosystem and are then upscales using habitat maps to patch, landscape, or regional levels. However, heterogeneity is rarely accounted for - particularly at edges. Further, adjacent tidal flat ecosystems have only recently been considered for carbon storage, but may be undervalued if areas where they transition with vegetated systems are not accounted for. To address the lack of information at coastal ecotones, we examined both soil carbon storage and carbon dioxide flux …

Commissioning Of Electron Blocks In Monaco And Diode Correction Factors, Sadaa Alotaibi

Electronic Theses and Dissertations 2020 - Present

This work examines the Elekta Monaco TPS Monte Carlo electron beam dose calculation model for electron treatment planning. The primary goals are to commission electron blocks and establish correction factors for diode measurements with the use of ion chamber output as references, improving dosimetric procedures and adhering to the AAPM for clinically acceptable precision. Output factor measurements of diodes were compared to ion chamber OFs on a 6 MeV to 15 MeV Elekta Versa HD linear accelerator. TPS calculations were held on the Monaco TPS system. To balance the computational costs and accuracy of the solution, grid sizes of 2 …

Ai Characterisations And Their Legal Implications, Jerrold Tsin Howe Soh

Research Collection Yong Pung How School Of Law

This chapter examines the difficult legal characterisation problems that artificially intelligent systems raise and explores how different characterisations of artificial intelligence (AI) shape practical legal outcomes. Three reasons are offered for the legal difficulty with characterising AI. First, answers to characterisation problems are inherently subjective and perspective-driven, particularly when the subject is an intangible technological system. Second, AI technology is especially difficult to define since the field typically proceeds on inexact anthropomorphic metaphors. Third, AI characterisation problems raise difficult sub-problems, particularly in determining how autonomous an AI system is. The chapter thus argues that a range of plausible AI characterisations …

Exploring Nitrate Reduction In A Saturated Riparian Buffer Through A Three-Dimensional Reactive Contaminant Transport Model In An Agricultural Area, Mcclean County Central Illinois, Franklin O. Ijigade

Theses and Dissertations

Saturated Riparian Buffers (SRBs) are engineered systems designed to remove nitrate and other pollutants from subsurface agricultural drainage water before it reaches a stream. This study utilizes a high-resolution coupled flow and reactive transport model to explore nitrate reduction and transformation in an SRB in glacial sediment. The influence of material heterogeneity on nitrate reduction and the effectiveness of the SRB was investigated. The study was conducted in an SRB located next to and receiving tile drainage water that ultimately drains into a 3^rd order stream (T3 stream) in central Illinois, USA. A three-dimensional steady groundwater flow model was …

The Development Of A One Pot, Two Reaction Synthetic Preparation Of 1,2,4-Oxadiazole, And Synthesis Of Ataluren, A Novel Drug In The Fight Against Duchenne Muscular Dystrophy. Efforts Towards The Synthesis Of A Potential Protease Inhibitor Against The Main Protease (3clpro) Of Covid-19, Austin J. Carter

Theses and Dissertations

1,2,4-Oxadiazoles are five-membered heterocyclic structures first synthesized by Tiemann and Krüger in 1884. Recent discoveries suggest an array of useful biological properties.In preparation of 1,2,4-oxadiazoles, the most prevalent precursors are amidoximes, which can be created via the reaction of nitriles with hydroxylamine hydrochloride and a base. The amidoximes are reacted with an activated carboxylic acid to yield an acylated intermediate. This intermediate can be exposed to a base to cyclize into the 1,2,4-oxadiazole. This thesis describes the efforts in combining these three steps into a unified one-pot synthesis.

Currently, there are a significant number of commercially available FDA approved and …

Analyzing Factors Influencing Employee Turnover In Tech Companies: A Predictive Modeling Approach, Shinjon Ghosh

Theses and Dissertations

Employee turnover poses substantial challenges for technology firms, and understanding its key drivers through predictive modeling is essential for developing effective retention strategies. This study investigates factors influencing employee turnover in technology companies by implementing a predictive modeling approach on the IBM HR Analytics Employee Attrition dataset. The research aims were identifying key factors contributing to employee attrition, developing predictive models to forecast turnover risk, and analyzing interactions among significant predictors. By examining a range of features, the results highlight significant variables (Over Time, Monthly Income, Marital Status, etc.) of attrition and offer actionable insights for developing targeted employee retention …

Asymmetric Synthesis Of The Hiv Protease Inhibitor Tmc-126 And An Anti-Malarial Agent Via A Titanium Tetrachloride Mediated Asymmetric Glycolate Aldol Addition Reaction. Redefining The Curtius Rearrangement Reaction Via Dehomologation Of Carboxylic Acids Bearing Alpha-Leaving Groups, Kweku Amaning Affram

Theses and Dissertations

Acquired Immune Deficiency Syndrome (AIDS) and malaria are two devastating infectious diseases caused by HIV and Plasmodium parasites. AIDS is caused by HIV-1 and HIV-2, transmitted through sexual contact, blood transfusions, needle sharing, and perinatal routes. Malaria, caused by plasmodium parasites through mosquito bites. Today, millions of people around the world have been infected with HIV and malaria and much research has been done to treat it. However, despite advancements in therapeutic options, these diseases remain a significant global health threat, particularly in developing countries due to the emergence of drug-resistant strains for both HIV and malaria complicating eradication efforts. …

On Higher Level Zhu Algebras Of N-Graded Vertex Algebras Associated With Simple Leibniz Algebras That Contain Sl2, Christian Soltermann

Theses and Dissertations

In this thesis, we study how the higher-level Zhu algebras of a vertex algebra reflect the structure of associated simple Leibniz algebras. In particular, we construct a vertex algebra from a vertex algebroid containing the simple Lie algebra sl₂ and analyze its higher level Zhu algebras. The irreducible modules of this vertex algebra were completely classified in [JY20b], but the structure of its indecomposable modules remains an open problem. Since modules for higher level Zhu algebras correspond to modules of vertex algebras, studying these algebras provides a method for understanding their broader representation theory.

The Impact Of Loss Function Topology On Gradient Descent, Robert B. Skudnig Jr.

Theses and Dissertations

Gradient descent is a popular optimization method that utilizes a model’s prediction error to iteratively improve its parameters for a given task. The functions that measure this error can be defined to align with the user’s goals and sometimes satisfy metric or norm properties. It is common for these functions to measure over Rn, but any differentiable space allows for gradient descent to occur. There has been some research investigating the influence of topological spaces on optimization methods, but it is a limited field of study. This thesis further explores this phenomenon by applying a transformation prediction model to multiple …

Neural Network Algorithm And Analysis For Multi-Label Ecg Data Classification, Akhil Raghava Kalal

Theses and Dissertations

Electrocardiogram (ECG) analysis is a fundamental diagnostic tool in cardiology, providing critical insights into cardiac function that directly impact patient care decisions and treatment outcomes. As healthcare systems face increasing demands, automated ECG interpretation using artificial intelligence offers promising solutions to improve diagnostic accuracy, reduce physicians workload, and enhance early detection of life threatening conditions.

This thesis compares two advanced deep learning architectures, CNN-GRU and Wide and Deep Transformer, for multi-label classification of 12-lead ECG data. Using data from the PhysioNet/Computing in Cardiology Challenge 2020, I evaluated both architectures across 27 different cardiac abnormalities. Results demonstrated that CNN-GRU architecture consistently …

Scaling Laws For Diffusion In Crystallized Plasma From Molecular Dynamics, Dany Yaacoub

Theses and Dissertations

Diffusion coefficients for crystallized Coulomb plasmas are essential microphysics input for modeling white dwarf cores and neutron star crusts. Solving for diffusion coefficients require running large molecular dynamics simulations with thousands of particles over millions of timesteps. The diffusion in a crystallized plasma has been largely ignored and is often taken to be zero in stellar evolution codes. We find that not only is this incorrect, but we find that the diffusion in a crystallized plasma can be modeled completely using a universal scaling law independent of screening. Our simulations also show that the dominant mode of diffusion in a …

Site-Specific Modification Of Antibodies Utilizing Microbial Transglutaminase For Improved Immunoassay Performance, Emily Beitello

Theses and Dissertations

Immobilization strategies used for fixing antibodies to solid phase surfaces significantly contribute to the antigen capture capacity and influences the performance and sensitivity of immunoassays. Traditional methodologies result in the random orientation and/or the weak attachment of immobilized antibodies. Different formats of immunoassays scope in applicability to many fields of research and everyday use. Improving the efficiency of immobilizing antibodies in immunoassays is a beneficial endeavor to increase assay sensitivity. Here, we investigated the use of enzyme-mediated conjugation of antibodies to facilitate a highly oriented immobilization. Microbial transglutaminase (mTG) catalyzes the covalent bond formation between a plethora of primary amine …

Application Of Floating Wetlands To Improve Urban Stream Quality, Daniel Chukwunonso Chukwudi

Theses and Dissertations

Urban streams, impacted by urbanization, often exhibit degraded water quality due to elevated nutrient levels, a phenomenon known as urban stream syndrome. This study evaluates the effectiveness of a floating wetland (FW) system in reducing nitrate as nitrogen (NO₃-N) and phosphate (PO₄³⁻) concentrations in a side canal of the Chicago River’s North Branch, adjacent to Goose Island, Chicago, IL, from 2018 to 2023. Using a five-year dataset, including new sampling from May to December 2023, the research addresses two questions: (1) Do FWs lower NO₃-N and PO₄³⁻ concentrations in urban streams? and (2) Do FWs exhibit seasonal differences in nutrient …

Distinct Composition-Dependent Topological Hall Effect In Mn2-Xznxsb, Md Rafique Un Nabi, Yue Li, Suzanne G.E. Te Velthuis, Santosh Karki Chhetri, Dinesh Upreti, Rabindra Basnet, Gokul Acharya, Charudatta Phatak, Jin Hu

Physics Faculty Publications and Presentations

Spintronics, an evolving interdisciplinary field at the intersection of magnetism and electronics, explores innovative applications of electron charge and spin properties for advanced electronic devices. The topological Hall effect (THE), a key component in spintronics, has gained significance due to emerging theories surrounding noncoplanar chiral spin textures. This study focuses on Mn_2-xZn_xSb, a material crystalizing in centrosymmetric space group with rich magnetic phases tunable by Zn contents. Through comprehensive magnetic and transport characterizations, we found that the high-Zn (x > 0.6) samples display THE which is enhanced with decreasing temperature, while THE in the low-Zn ( …

Reconfigurable Photonic Lattices Based On Atomic Coherence, Jiaqi Yuan, Shun Liang, Qingsong Yu, Chiangbao Li, Yanpeng Zhang, Min Xiao, Zhaoyang Zhang

Physics Faculty Publications and Presentations

The array of coupled optical waveguides, which is also viewed as a photonic lattice, can exhibit abundant photonic band structures depending on the desired spatial arrangements of involved waveguides. Studies of photonic lattices are usually performed in solid-state materials, where the required periodic susceptibilities can be achieved by employing the femtosecond laser direct-writing or optical induction method, and have spawned flourishing achievements in manipulating the behaviors of light. Recently, the concept of electromagnetically induced photonic lattice (EIPL) is proposed under the well-known electromagnetically induced transparency (EIT) in coherently prepared multilevel alkali-metal atomic systems, where the strong coupling beams producing EIT …

Electrochemical Observation And Ph Dependence Of All Three Expected Redox Couples In An Extremophilic Bifurcating Electron Transfer Flavoprotein With Fused Subunits, Debarati Das, Wassim El Housseini, Monica Brachi, Shelley D. Minteer, Anne Frances Miller

Chemistry Faculty Research & Creative Works

Bifurcating enzymes employ energy from a favorable electron transfer to drive unfavorable transfer of a second electron, thereby generating a more reactive product. They are therefore highly desirable in catalytic systems, for example, to drive challenging reactions such as nitrogen fixation. While most bifurcating enzymes contain air-sensitive metal centers, bifurcating electron transfer flavoproteins (bETFs) employ flavins. However, they have not been successfully deployed on electrodes. Herein, we demonstrate immobilization and expected thermodynamic reactivity of a bETF from a hyperthermophilic archaeon, Sulfolobus acidocaldarius (SaETF). SaETF differs from previously biochemically characterized bETFs in being a single protein, representing a concatenation of the …

Scalable Fabrication Of High-Payload Dendrimer-Based Nanoparticles For Targeted Atherosclerosis Therapy, Huari Kou, Lin Qi, Da Huang, Jiandong Wu, Honglan Shi, Hu Yang

Chemistry Faculty Research & Creative Works

Nanoparticle-based therapeutics hold promise for the treatment of atherosclerosis, but challenges such as low drug-loading capacity and a lack of scalable, controllable production hinder their clinical translation. Flash nanoprecipitation, a continuous synthesis method, offers a potential solution for scalable and reproducible nanoparticle production. In this study, we employed a custom-designed multi-inlet vortex mixer to perform cross-linking reaction-enabled flash nanoprecipitation, facilitating controlled and scalable synthesis of cross-linked Poly amidoamine (PAMAM) dendrimer nanoparticles. Notably, this approach allows simultaneous nanoparticle cross-linking and drug loading in a single step. The mannose moiety enabled specific targeting of macrophages via mannose receptors, enhancing the localization of …

Natural Capital Credit Risk Assessment In Agricultural Lending: An Approach Based On The Natural Capital Protocol, Francisco Ascui, Theodor Florian Cojoianu

Research Collection College of Integrative Studies

It is increasingly recognised that financial institutions have significant impacts and dependencies on natural capital – defined as the stock of the world’s renewable and non-renewable natural resources and ecosystems that yield flows of environmental goods and services, which directly and indirectly underpin the global economy and human wellbeing. Historically, many of these impacts and dependencies have been overlooked. The value of goods and services that nature provides ‘for free’ has often been ignored, and resources have typically been priced at their cost of extraction, rather than the cost of their replacement or substitution, which would promote more sustainable long-term …

Mapping The End Of Coal: How Policy Strength, Ownership, Finance Shape Global Plant Retirements, Jiwon Kim, Theodor Florian Cojoianu, Theodor F. Cojoianu, Maretno Agus Harjoto, Dariusz Wojcik

Research Collection College of Integrative Studies

This study examines how national environmental performance, institutional investor divestment from fossil fuels, investment in renewable energy, and ownership type influence the global phase-out of coal power plants, and whether these effects are constrained by geographical boundaries. Using data on coal plant retirements across 90 countries, we test whether domestic and cross-border factors shape the timing and likelihood of asset closure. We find that companies headquartered in countries with stronger environmental performance are more likely to retire domestic but not foreign plants. While institutional investors divestment is often assumed to exert cross-border influence, our findings show that divestment pressure by …

The Climate-Biodiversity-Pollution Nexus: The Pricing Of Environmental Credit Risks For European Industrial Polluters, Dominik Hirschbühl, Andrej Ceglar, Theodor Cojoianu, Tina Emambakhsh, Yifan Qi, Caterina Rho, Elsie Hu, Marco Petracco, Fabrizio Biganzoli, Alfred De Jager, Laura Garcia Herrero, Andrea Mandrici, Carlo Pasqua

Research Collection College of Integrative Studies

This study examines how euro area banks factor pollution-induced biodiversity risks into lending decisions, using data from 832 banks and 5,000 major polluters. Our results show that banks are increasingly pricing these risks by adjusting loan-to-value ratios and interest rates. Banks adjust lending conditions in line with EU pollution and biodiversity protection legislation, particularly for companies with large pollution footprints near biodiversity-protected areas or those contributing to Environmental Quality Standards failures of downstream surface waters. The former is driven primarily by banks’ adoption of biodiversity policies and public commitments to the Equator Principles, while the latter is a result of …

Meteorology, Weather And War In South East Asia: Malaya C. 1940-1960, Fiona Williamson

Research Collection College of Integrative Studies

This article interrogates the positioning of British colonial meteorology in Malaysia and Singapore from the 1940s to 1960. This period spanned a global conflict and an internecine war, effecting profound sociopolitical changes from which neither Malaysia nor Singapore would emerge the same. The meteorological services were essential to Britain's armed conflicts, providing vital weather information to the army, navy and, especially, the air forces, as well as supporting the aviation and shipping industry often in difficult and dangerous circumstances. This article argues that British military policy in South East Asia and the specific concerns of the colonial government in Malaya …

Leveraging Deep Learning Models And Social Media Data For Enhanced Situation Awareness In Disaster Management, Ademola Abdulganiyu Adesokan

Doctoral Dissertations

"In recent years, social media has become a crucial source of real-time data for disaster management, supporting emergency responses when traditional channels like 911 are overcrowded and overwhelmed. It offers authorities valuable data for developing effective strategies, especially when swift actions are essential to save lives. However, the informal language, ambiguous meanings, and irrelevant content on social media pose challenges to accurate classification and hinder the efficient extraction of disaster-relevant information, leading to inefficiencies in emergency response efforts.

This research focuses on seven key questions: i) How can we detect, classify, and analyze hate and offensive tweet emotions during large-scale …

Improving System-Level Outcomes Via Artificial Intelligence Decision Support In Kidney Utilization, Casey I. Canfield, Cihan H. Dagli, Daniel Burton Shank, Krista Lentine, Mark Schnitzler, Henry Randall, V. Sriram Siddhardh Nadendla, Brendon Cummiskey

Engineering Management and Systems Engineering Faculty Research & Creative Works

Transplantation provides patients suffering from end-stage kidney disease a better quality of life and long-term survival. However, over 20% of deceased donor kidneys are not utilized and never transplanted. While this is sometimes medically appropriate, this also reflects missed opportunities. We are designing Artificial Intelligence decision support for the kidney offer process to support both demand at the transplant center and supply at the organ procurement organization. This includes (1) developing deep learning models, (2) evaluating the effect of explainable interfaces, (3) improving fairness in the model output, (4) identifying factors that influence adoption decisions, and (5) conducting a randomized …

Spatial Analysis And Machine Learning Integration For Nutritional Status Mapping Using Ann And Random Forest Models, Desi Anis Anggraini, Fachrul Kurniawan, Fresy Nugroho, Meidya Koeshardianto, Mohammad Iqbal Bachtiar

Knowledge Engineering and Data Science

Nutritional problems among children under five remain a major public health challenge. This research seeks to create a spatially oriented system for evaluating and mapping nutritional status utilizing Artificial Neural Network (ANN) and Random Forest (RF) algorithms. Data obtained from the Sumenep District Health Office included age, weight, height, and gender variables. Both models were trained using a 70:30 data ratio and evaluated with accuracy, precision, recall, and F1-score metrics. The ANN model achieved an accuracy of 95.8%, while the RF model reached 97.7%. Classification results were visualized through a Geographic Information System (GIS) to illustrate spatial distribution and identify …

Time Series Forecasting With Lstm: An Extensive Content Analysis, Andri Pranolo, Xiaofeng Zhou, Yingchi Mao

Knowledge Engineering and Data Science

This paper presents a comprehensive bibliometric and content review of the trend, architecture, and application of long short-term memory (LSTM) models for time series forecasting. The study aims to provide insights into the overall statistics and distribution of papers focused on LSTM for forecasting. Additionally, the research questions address the most highly cited papers based on LSTM approaches in forecasting, the most productive journals in this field, and identifying trends, gaps, summary tasks and their performance, datasets availability, and future research directions for LSTM in forecasting. This paper is a comprehensive review of LSTM for forecasting from 2017 to 2023 …

From Data To Insight: A Machine Learning Approach In Classifying Dairy Cow Productivity Level And Identifying Important Influencing Variables, Fatkhurokhman Fauzi, Achmad Fauzan, Rhendy K P Widiyanto, Khairil Anwar Notodiputro, Bagus Sartono

Knowledge Engineering and Data Science

Identifying influential predictor variables is crucial for enhancing model interpretability in supervised classification. This study applies Permutation Variable Importance (PVI), a model-agnostic approach, to evaluate variable relevance after model fitting. Using data from the 2024 Indonesia Dairy Cow Productivity Survey, this research investigates five classification techniques: (1) Support Vector Machine (SVM), (2) Neural Network (NN), (3) k-Nearest Neighbors (kNN), (4) Naïve Bayes Classifier (NB), and (5) Logistic Regression (LR), to identify which method(s) yield the best performance based on evaluation metrics such as accuracy, sensitivity, and specificity. PVI is employed to identify the most influential predictor variables within the best-performing …

A Hybrid Soft Voting And Stacking-Based Meta-Learning Approach For Sentiment Analysis Of Bangkalan Batik, Moh. Imron Wahyudi, Lailil Muflikhah, Rizal Setya Perdana

Knowledge Engineering and Data Science

Sentiment analysis is an important field in Natural Language Processing (NLP) that focuses on processing consumer opinions to gain useful insights. The information generated from sentiment analysis can be used as a basis for business decision-making, service quality evaluation, and the formulation of more effective marketing strategies. In the local context, Bangkalan Batik, as one of Madura's distinctive cultural products, has high economic value and cultural identity. However, consumer reviews available online, for example through Google Maps, are still rarely utilized optimally by MSMEs as a source of strategic information. Therefore, this study was conducted to develop a sentiment classification …