Physical Sciences and Mathematics Commons^™

Time-Resolved Crystallographic Analysis Of The Mechanism Of Formation Of The Mof Hkust-1, Cody Webb Jr

Dissertations - ALL

Metal-organic frameworks (MOFs) are a class of inorganic porous coordination compounds of interest for technically relevant applications including gas storage & sequestration, catalysis, and drug delivery (Chapter 2). The last decade has seen significant development in this field of coordination chemistry, and an extensive array of MOFs have been reported despite the lack of a comprehensive scheme for how these materials form. The development of novel MOFs is not a trivial task, as the synthesis of target MOFs is notably unpredictable, and experiments require extensive trial-and-error reactions with systematic manipulation of the synthetic variables. Ideally, a toolbox method based on …

Mathematics And Mental Health: An Interdisciplinary Analysis Of Ai In Counselor Education, Jennifer M. Hightower, Catrina A. May

Journal of Counselor Preparation and Supervision

Although use of Artificial Intelligence (AI) in mental health care has become increasingly common, many professional counselors remain under informed about foundational components of AI. Fundamental issues associated with AI, including model bias and the Black Box Problem, must be considered as these tools become integrated into the counseling profession. This manuscript provides an interdisciplinary, theoretical analysis of AI use in counseling and counselor education grounded in foundational knowledge of AI and the American Counseling Association’s recommendations for the ethical integration of AI (Butler et al., 2023). The paper summarizes these recommendations, establishes accessible definitions of AI terms, explains the …

Investigating Resilience Of Cyberattack Detection Using Lyapunov-Based Economic Model Predictive Control To Data Poisoning, Helen Durand, Akkarakaran Francis Leonard

Chemical Engineering and Materials Science Faculty Research Publications

Cyberattacks may be performed on process control systems due to their integration of networking and computing with physical systems. Prior work in our group has developed detection strategies for nonlinear systems under sensor, actuator, and combined sensor and actuator attacks which can ensure, under characterizable conditions, that attacks can be detected before they cause safety issues. However, this work did not take into account the potential that an attacker could attempt to provide data to a process that causes an attack to remain undetected but that also is consistent with different process dynamics than those which the process has. This …

Response Of Dynamic Processes With Control Implemented On A Noisy Quantum Computer, Shilpa Narashimhan, Dominic Messina, Henrique Oyama, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

A major challenge to determining the applicability (and potential outperformance over classical computers) of a quantum computer (QC) within chemical manufacturing processes is quantum noise. Computations by a QC are error-prone due to the influence of quantum noise inherent to the hardware. Errors in control inputs may destabilize a chemical process and lead to unsafe conditions for manufacturing personnel and the environment. The response of a process with control implemented on a QC to errors due to noise must be investigated thoroughly. In this work, the impacts of control input errors due to quantum noise on a process are modeled …

Heuristic Strategies For Process Stabilization Using Proportional Control Implemented By A Noisy Quantum Simulator, Keshav Kasturi Rangan, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Processing and storage demands of industrial processes are causing fields such as optimization, scheduling, and control to assess the effectiveness of quantum devices in their applications. A key objective of control systems is to ensure process safety. This paper focuses on the potential of quantum devices to compute control inputs that maintain system safety despite sources of nondeterminism inherent to currently available quantum devices (quantum noise). In our previous work, we employed a quantum simulator to assess whether a quantum implementation of a proportional (P) control law could stabilize a single-input/single-output system under quantum noise approximated from a real quantum …

Tools To Design Algorithms For Implementing Control Over Quantum Computers, Shilpa Narashimhan, Jihan Abou Halloun, Kip Nieman, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Quantum computers (QCs) may find future applications within control systems that operate manufacturing processes. For application within control engineering, quantum algorithm development must be led by control engineers. However, control engineers may face challenges in designing quantum algorithms for control engineering problems. In this work, we provide several path-finding studies that leverage engineering tools such as optimization, encryption, and computational "short-cuts" toward making algorithm design for QC easier for control engineers.

Does Bubble Nucleation Occur Heterogeneously In Magmas Feeding Explosive Rhyolite Eruptions? Insights From The Rock Magnetic Properties Of Pumice, Kelly N. Mccartney, Julia E. Hammer, Thomas Shea, Stefanie Brachfeld, Thomas Giacheetti, Bruce F. Houghton

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

Nanometer-scale titanomagnetite crystals have been detected in nominally aphyric rhyolite pumice, but whether they are numerous enough to impact bubble nucleation in explosive silicic volcanism was unresolved. This study examines sub-micron crystals using rock magnetic techniques, Rhyolite-MELTS modeling, and physical characterization. We analyzed pumice from four eruptions spanning wide ranges in intensity, storage depth, and bubble number density (1016 to 1013 m−3 liquid): 1060 CE Glass Mountain, 1912 CE Novarupta, 232 CE Taupo, and 0.45 Ma Pudahuel. Calculations assuming monospecific assemblages of 10 and 1,000 nm cubic particles yield titanomagnetite number densities of 1021 to 1013 m−3 dense rock equivalent, …

Dissolution Mechanism Of Nonionic Polyether Surfactants In Supercritical Co2, Ning Xu, Yanling Wang, Baojun Bai, Shizhang Cui, Zan Gao, Yu Zhang, Di Li, Wenjing Shi, Wenhui Ding, Peixu Ma

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Polyoxyethylene ether is an efficient CO₂-philic compound with significant potential applications in CO₂ flooding, which requires CO₂-philic surfactants with high solubility in supercritical CO₂ (scCO₂). This study elucidates the molecular and atomic-level dissolution mechanism of the fatty alcohol polyoxyethylene ether (AEO) in scCO₂ by combining phase-behavior experiments and molecular dynamics simulations. The solubility of AEO in scCO₂ is measured using a semiconductor laser. AEO containing three polyoxyethylene (EO) groups exhibited the highest solubility in scCO₂.The solubility of AEO in scCO₂ decreased with an increase in the number …

2025 August 21 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Weekly Drought Summaries

No abstract provided.

Re: Butte Priority Soils Operable Unit (Bpsou) Draft Final Bres No. 94 – Rialto Dump Reclamation Improvement (Ri) Field Sampling Plan (Fsp)., Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: Butte Priority Soils Operable Unit (Bpsou) Draft Final Insufficiently Reclaimed Sites Field Sampling And Investigation Plan (Fsp): Bres No. 177 – North Alice Culvert, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Comparative Modeling Of Nuclear Energy Consumption In The United States And France: An Optimized Structure-Adaptive Grey Model, Alae Chahid '25, Naima Shifa

Student Research

This study investigates nuclear energy consumption trends in the United States, and France by applying advanced time-series modeling and computational optimization techniques. Using annual consumption data from 2005 to 2023, the research compares the predictive accuracy under data scarcity of the AutoRegressive Integrated Moving Average (ARIMA), Grey Model (1,1,t), Grey Model(1,1,t²), and an Optimized Structure-Adaptive Grey Model (OSGM). This OSGM (1,1,_) the traditional Grey Model (1,1) by introducing time-dependent terms and parameter tuning through particle swarm optimization and Monte Carlo simulations. Models are trained and tested using an in-sample and out-of-sample period framework. Then, forecast accuracies are compared using Mean …

Re: Butte Priority Soils Operable Unit (Bpsou) Draft Final Insufficiently Reclaimed Sites Field Sampling Plan (Fsp): Bres No. 26 – Cripple Dump, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Reducing Residential Landscape Water Use In Utah: Technologies And Strategies, Maya Cottam, Kendall Becker, Katlyn Stemmler, Shital Poudyal, Wesley Crump, Lewis Kogan, Scott Hotaling

All Current Publications

Water conservation is a critical issue in Utah, and several actions are already underway to help lower residential landscape water use. Strategies include smart irrigation controllers, efficient sprinkler bodies and nozzles, drip irrigation systems, soil amendments that increase water-holding capacity, and drought-tolerant grass cultivars for lawns. While additional conservation efforts will be necessary to reach sustainable water management, statewide adoption of current programs can help reduce water use and loss.

Re: Butte Priority Soils Operable Unit (Bpsou) Draft Final Insufficiently Reclaimed Sites Field Sampling And Investigation Plan (Fsp): Bres No. 91 – Robert Emmett Dumps, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Large-Scale Flood Detection And Mapping In The Yangtze River Basin (2016–2021) Using Convolutional Neural Networks With Sentinel-1 Sar Images, Xuan Wu, Zhijie Zhang, Wanchang Zhang, Bangsheng An, Zhenghao Li, Rui Li, Qunli Chen

Environment and Society Faculty Publications

Synthetic Aperture Radar (SAR) technology offers unparalleled advantages by delivering high-quality images under all-weather conditions, enabling effective flood monitoring. This capability provides massive remote sensing data for flood mapping, while recent rapid advances in deep learning (DL) offer methodologies for large-scale flood mapping. However, the full potential of deep learning in large-scale flood monitoring utilizing remote sensing data remains largely untapped, necessitating further exploration of both data and methodologies. This paper presents an innovative approach that harnesses convolutional neural networks (CNNs) with Sentinel-1 SAR images for large-scale inundation detection and dynamic flood monitoring in the Yangtze River Basin (YRB). An …

Full-Stack Quantum Computing, Benjamin C A Morrison

Physics & Astronomy ETDs

Quantum computing is a promising tool for solving computational problems in several areas, including the simulation of physical and chemical systems. The design of practical quantum computing systems for these applications is a daunting task, requiring collaborative work by interdisciplinary teams considering different abstractions of the same systems. This dissertation presents work on the development of those abstractions, and on components that bridge multiple layers of abstraction. I first provide an introduction to quantum circuit model computation, error correction with stabilizer codes, and physics simulation algorithms. In joint work with the QSCOUT software team, I then describe the development of …

Universal Centralizers, Morita Abelianization, And Wonderful Models In Lie Theory, Peter Crooks

Funded Research Records

No abstract provided.

Detection Of Small Apple Targets Based On Improved Yolov5 In Natural Environments, Zilong Liu, Lei Zhang

Journal of System Simulation

Abstract: The distribution of apples usually features occlusion and small and dense targets. To address these issues, a target detection algorithm was proposed based on an improved YOLOv5 model. Specifically, this paper added the coordinate attention (CA) mechanism, receptive field block (RFB), and adaptively spatial feature fusion (ASFF) modules to the YOLOv5, enhancing the ability to detect small targets. Additionally, the proposed algorithm replaced the CIoU in YOLOv5 with SIoU to improve the target detection box's prediction accuracy. Finally, some normal convolutions were replaced with depthwise separable convolutions (DSC), effectively reducing the calculation burden. Experiment results show that the comprehensive …

Modeling The Importance Of Life Exposure Factors On Memory Performance In Diverse Older Adults: A Machine Learning Approach, Evan Fletcher, Marianne Chanti-Ketterl, Emily Hokett, Yi Lor, Umesh Venkatesan, Ruijia Chen, Omonigho M. Bubu, Rachel Whitmer, Paola Gilsanz, Zvinka Z. Zlatar

Moss-Magee Rehabilitation Papers

INTRODUCTION: Many health life exposure factors (LEFs) influence cognitive decline and dementia incidence, but their relative importance to episodic memory (an early indicator of cognitive decline) among diverse older adults is unclear. We used machine learning to rank LEFs for memory performance in a large and diverse US cohort.

METHODS: Kaiser Healthy Aging and Diverse Life Experiences (KHANDLE) and Study of Healthy Aging in African Americans (STAR), participants underwent neuropsychological testing and answered questionnaires about multiple LEFs. XGBoost and Shapley Additive exPlanation values ranked the importance of factors influencing cross-sectional episodic memory in the full sample and by sex and …

Scene Generation Method For Maritime Target Recognition Based On Detection Parameters, Yuxuan Run, Dezhen Yang, Yeyang Liu, Wei Deng, Xiangyu Xing, Yi Ren

Journal of System Simulation

Abstract: Traditional scene generation methods for maritime target recognition consider only the effects of different environments on the generated scene data, while overlooking the changes in scene information caused by sensor detection parameters, resulting in a lack of accuracy and authenticity in generated scenes. To address this issue, a detection parameter-based scene generation method for maritime target recognition was proposed. For the task of maritime target recognition, key detection parameters affecting scene generation quality and essential scene features were analyzed. An association relationship modeling method based on Bayesian networks was proposed to construct a mapping relationship model between scene features …

Ship Fire Prediction Method Based On Evidence Theory With Fuzzy Reward, Chunyu Yang, Chuang Zhang, Xiaofan Zhang

Journal of System Simulation

Abstract: A multi-source information fusion approach based on the dempster-shafer (D-S) evidence theory with a fuzzy reward-penalty mechanism was proposed to address the issues of underreporting and false reporting in the early prediction of ship fires. PyroSim was utilized to construct a ship's laboratory model for fire simulation. Variations in carbon monoxide, temperature, and smoke concentration were recorded for data acquisition, followed by the application of a sigmf function for membership assignment. By leveraging the classical D-S theory, a reward-penalty mechanism was applied in weighted evidence fusion. Reward-penalty factors were utilized to differentiate various basic probability assignments, with unified belief …

Research On Joint Simulation Of Special Vehicle Engine Operation Characteristics Based On Virtual Driving Scenarios, Xueyuan Xie, Chen Lin, Han Wu, Qinglan Zhao, Junfei Gao, Qiangguo Hao, Xinqian Zheng

Journal of System Simulation

Abstract: The preliminary design of the overall operation performance of diesel engines cannot be guided by actual vehicle driving tests, which hinders the improvement of the power development level and efficiency of special vehicles. By using the virtual visual simulation engine Unity3D, two virtual driving scenario models were established: a flat road scenario and an undulating road scenario. Based on the speed characteristic parameters of the engine, a diesel engine's operation performance output model was constructed. Combined with the transmission system model and the longitudinal dynamics model of the vehicle's center of mass, a straight vehicle driving dynamics model was …

Project-Based Learning With Odes: Modeling Straw Rocket Motion With Air Resistance, Viktoria Savatorova, Ethan Dyer, Aleksei Talonov

CODEE Journal

This paper presents a hands-on project that guides students through building and validating a mathematical model of projectile motion. The project starts with the idealized case of motion under gravity without air resistance and then introduces air drag : first as a linear force, and then as a nonlinear quadratic force, with the Reynolds number providing the justification for the quadratic model. Students perform experiments with vertical and angled launches, capturing and analyzing motion data using video analysis software. Vertical launch data allows parameter estimation via least squares fitting of the nonlinear drag model, yielding values for initial velocity and …

Revealing The Catalytic Mechanism Of The Fe(Ii)/2-Oxoglutarate-Dependent Human Epigenetic Modifying Enzyme Alkbh5, Fathima Hameed Cherilakkudy, Midhun George Thomas, Ann Varghese, Sodiq Waheed, Anandhu Krishnan, Vincenzo Venditti, Christopher J. Schofield, Deyu Li, Christo Christov, Tatyana Karabencheva-Christova

Michigan Tech Publications

ALKBH5 is one of only two known human non-heme Fe(II)/2-oxoglutarate-dependent oxygenases that catalyze the demethylation of N⁶-methyladenine (m⁶A) in single-stranded mRNA, underscoring its role in diverse cancers. Unlike its homolog, the fat mass and obesity-associated protein (FTO), which oxidizes m⁶A to a stable N⁶-hydroxymethyladenine (hm⁶A) intermediate, ALKBH5 demethylates m⁶A, yielding adenine and formaldehyde as products. Here, we integrate molecular dynamics simulations and quantum mechanics/molecular mechanics methods to elucidate ALKBH5’s complete catalytic mechanism. Two post-hydroxylation pathways were evaluated: a proton transfer pathway and a Schiff base formation pathway, with …

Tmco1 As An Endoplasmic Reticulum Calcium Load-Activated Channel: Mechanisms And Disease Implications, Jingbo Wang, Panpan Zhu, Zhuohang Li, Xiaohui Su, Mingzhu Qi, Aimin Zhou, Xiangying Kong

Chemistry Faculty Publications

Calcium ions (Ca2+) play a vital role in many biological processes. Transmembrane and coiled-coil domain 1 (TMCO1) has been characterized as an endoplasmic reticulum (ER) transmembrane protein in recent years. It keeps the cytoplasm and ER's Ca2+ homeostasis stable by acting as a novel calcium channel. Studies from different laboratories have revealed that the mutation or deficiency of TMCO1 is closely correlated with several diseases, including cerebro-facio-thoracic dysplasia (CFTD), glaucoma, premature ovarian failure (POF), osteoporosis, and cancer. Here, we review the characteristics of TMCO1 and its involvement in related diseases, which may provide useful information for developing therapeutic strategies for …

Degeneracies Of Triangulated Graphs, Allan Bickle

Theory & Applications of Graphs

A graph $G$ is $k$-degenerate if each subgraph has minimum degree

at most $k$. The degeneracy\textbf{ }$D\left(G\right)$ is the smallest

$k$ such that $G$ is $k$-degenerate. We determine the truth values

of four statements (using different quantifiers) about when a planar

graph $G$ with degeneracy $k$ has a triangulation with degeneracy

$l$. We characterize which 3-connected planar graphs can only be

triangulated to degeneracy 3. Then we consider analogous questions

for maximal planar bipartite graphs. We prove some structural results

on these graphs, including results on decomposition of planar graphs

into various types of bipartite graphs.

Simulation And Optimization Of Support Processes For Aircraft Fleet Launch Under Limited Resources, Feng Gong, Tao Jiang, Qin Zhang, Yu Liu

Journal of System Simulation

Abstract: To address the scheduling problem of aircraft fleet support processes under limited resources, a fleet support process optimization model that covered multiple aircraft, activities, and resource constraints was developed. An activity node graph model was used to establish the temporal logic, resource competition, and other constraints in the fleet support process, forming a "time – activity – resource" multidimensional optimization model. A genetic algorithm based on priority encoding was proposed, incorporating a serial decoding strategy and a dynamic penalty function to handle the complex constraints in the model, efficiently solving the optimization problem under complicated temporal and resource constraints. …

Short-Term Load Forecasting Based On Dual-Attention Temporal Convolutional Long Short-Term Memory Network, Lifen Li, Jinyue Zhang, Wangbin Cao, Huawei Mei

Journal of System Simulation

Abstract: In order to improve the accuracy of load forecasting and fully extract the hidden relationships between load and other characteristic factors, a load forecasting method based on dual-attention temporal convolutional LSTM network (DA-TCLSNet) was proposed. Correlation analysis was conducted on the dataset using the maximum information coefficient method to perform feature screening to reduce the computational cost of the model. The model input was constructed using a sliding window. The DATCLSNet forecasting model was constructed. The temporal convolutional layer extracted dependencies at different time scales and captured the nonlinear characteristics among variables such as load and weather. The multi-head …

Research On 3d Visualization Of Safety Monitoring And Early Warning For Steel Continuous Casting Scenarios, Wei Zhang, Wei Sheng, Yidan Cao, Tingsheng Zhao

Journal of System Simulation

Abstract: In order to improve the visualization and integration of production safety monitoring and fault warning, a three-dimensional (3D) visualization model architecture for whole-process industrial production safety monitoring and early warning for steel continuous casting scenarios was designed. By using 3ds Max and Unity3D, a multi-dimensional and multi-scale model was built, and functional modules such as visualization display and multi-level early warning for safety monitoring data were developed. By combining WebGL technology and Node. js runtime environment, the visualization of whole-process industrial production safety monitoring based on Web terminal was realized. The alarm threshold determination method for whole-process industrial production …