Digital Commons Network^™

Deepwhalenet: A Climate Change-Aware Fft-Based Neural Network For Underwater Passive Acoustic Monitoring, Nicholas Ryan Rasmussen

Dissertations and Theses

In the face of escalating climate threats, the conservation of whale species has become increasingly critical. Traditional acoustic monitoring methods, burdened by extensive pre-processing and post-processing, need more adaptability and efficiency for effective marine mammal surveillance. This study introduces DeepWhaleNet, a novel deep-learning framework tailored for Underwater Passive Acoustic Monitoring (UPAM). DeepWhaleNet is designed to streamline whale detection by directly analyzing raw log-power spectrograms, thus extracting essential acoustic features to conserve these endangered species. The framework employs an extensive short-time Fourier transform (STFT) for input processing and a customized ResNet-18 architecture for classification, distinguishing whale vocalizations from ambient noise and …

Development Of A Modular Lab Automation System With Applications To Animal And Bacteria Cell Culture, Timothy William Hartman

Dissertations and Theses

The challenges faced while executing wet lab protocols encourage the development of automation systems to come alongside human scientists. Today’s cutting-edge experiments involve complex protocols with precise measurements usually performed manually. Even simpler biological protocols can be tedious and prone to error, as was seen during the COVID-19 pandemic and society’s demand for high-volume, rapid sample analysis. Moreover, reproducibility suffers when there is excessive variability and insufficient data. Here, we leveraged the Stanford Biodesign process to develop a modular lab automation system and image analysis workflow to address challenges like these. This flagship automation platform at The University of South …

Classification Of Sow Postures Using Convolutional Neural Network And Depth Images, Md Towfiqur Rahman, Tami M. Brown-Brandl, Gary A. Rohrer, Sudhendu R. Sharma, Yeyin Shi

Department of Agricultural and Biological Systems Engineering: Faculty Publications

The United States swine industry reports an average preweaning mortality of approximately 16% where approximately 6% of them are attributed to piglets overlayed by sows. Detecting postural transitions and estimating sows’ time budgets for different postures are valuable information for breeders and engineering design of farrowing facilities to eventually reduce piglet death. Computer vision tools can help monitor changes in animal posture accurately and efficiently. To create a more robust system and eliminate varying lighting issues within a day including daytime/ nighttime differences, there is an advantage to using depth cameras over digital cameras. In this study, a computer vision …

Biom 3710: Physiological Systems And Modeling (Syllabus), Stephen Strain

Biomedical Engineering Syllabi Archive

Course Description: Fundamentals of control theory and mathematical modeling and analysis as applied to physiological systems.

Synthesis, Characterization, And Performance Assessment Of Reusable And Biodegradable Antimicrobial Polymeric Membranes For Aerosolized Pathogen Inactivation And Filtration, Ebuka Ogbuoji

Theses and Dissertations--Chemical and Materials Engineering

Air filtration technology has proven effective in purifying air by trapping particulates which can cause adverse health effects. High Efficiency Particulate Air (HEPA) filters, capable of capturing over 99.99% of PM_0.3, are recommended for critical applications. However, conventional non-woven HEPA filters rely on electrostatic interactions to trap smaller particles, which can deplete over time or after cleaning, reducing filtration efficiency and posing health risks. Additionally, these filters contribute to plastic waste.

This dissertation investigated the feasibility of using flat sheet polymeric membranes fabricated via nonsolvent-induced phase separation (NIPS) as reusable and biodegradable alternatives to commercially available non-biodegradable air …

Real-Time Detection Of Sea Turtles Using Uav And Neural Networks On Edge Devices, Jose A. Gonzalez Nunez, Jose G. Gonzalez Nunez, Mustafa I. Akbas, Patrick Currier, Nickolas D. Macchiarella

Journal of Aviation/Aerospace Education & Research

Sea turtle populations continue to diminish around the globe for various reasons. Therefore, the need for innovative solutions to monitor sea turtles has been increasing. This research paper focuses on an innovative application of artificial intelligence (AI) and machine learning (ML) together with unmanned aerial vehicles (UAV) to improve sea turtle conservation efforts. We outline the design, implementation, and evaluation of a system that deploys UAVs equipped with high-resolution cameras, coupled with a purpose-built neural network to recognize, classify, and monitor sea turtles. This project thus serves as a platform for understanding the wider applicability and limitations of this technology …

The Impact Of Dissolved Organic Matter On Photodegradation Rates, Byproduct Formations, And Degradation Pathways For Two Neonicotinoid Insecticides In Simulated River Waters, Josephus F. Borsuah, Tiffany L. Messer, Daniel D. Snow, Steven D. Comfort, Shannon Bartelt-Hunt

UK CARES Faculty Publications

The influences of dissolved organic matter (DOM) on neonicotinoid photochemical degradation and product formation in natural waters remain unclear, potentially impacting the sustainability of river systems. Therefore, our overall objective was to investigate the photodegradation mechanisms and phototransformation byproducts of two neonicotinoid pesticides, imidacloprid and thiamethoxam, under simulated sunlight at the microcosm scale, to assess the implications of DOM for insecticide degradation in rivers. Direct and indirect photolysis were investigated using twelve water matrices to identify possible reaction pathways with two DOM sources and three quenching agents. Imidacloprid, thiamethoxam, and potential degradants were measured, and reaction pathways identified. The photodegradation …

A Wearable Sensing System For High-Speed Interface Of Wide Range Electrochemical Sensor Array, Shanthala Lakshminarayana

Electrical Engineering Dissertations - Archive

Electrochemical sensing systems have emerged as indispensable tools in various fields due to their remarkable sensitivity, selectivity, and versatility. They play a pivotal role in modern research, industry, environmental monitoring, and healthcare devices. In environmental monitoring, these systems are deployed for detecting pollutants, heavy metals, and toxic gases, facilitating real-time monitoring, and ensuring environmental safety. Whereas, in the biomedical field, electrochemical sensing systems play a crucial role in diagnosing diseases, monitoring biomarkers etc, thereby revolutionizing healthcare practices.

Cost-effective wearable electrochemical sensing devices are significant for democratizing healthcare and improving public health outcomes. These devices enable continuous monitoring of physiological parameters, …

Development And Application Of Guided Mode Resonance Biosensor Platforms For Highly Sensitive And Real-Time Cell Killing Assays, Seyedmohsen Vaziri

Electrical Engineering Dissertations - Archive

In this work, we developed and investigated the cancer cell killing efficacy of different instances using real-time high-sensitivity measurements facilitated by Guided-Mode Resonance (GMR) sensors. The GMR biosensor technology detects shifts in the spectral peak caused by changes in the refractive index of the surrounding medium, offering a label-free method for monitoring cellular events.

A549 cell line wild type and HER2 knockout (lung cancer cells) were exposed to different concentrations of Triton X-100 and ADC (Herceptin with αHFc-CL-DMDM). The GMR-based cell killing assay demonstrated exceptional sensitivity and specificity, with shifts in wavelength exhibiting a robust correlation with cell viability and …

Bringing "Virtual" To "Reality": Enhancing Security And Usability On Vr System And Applications, Huadi Zhu

Computer Science and Engineering Dissertations - Archive

With the rapid advancements in computer science, electronics, optics, and related fields, virtual reality (VR) gradually penetrates into our daily lives, and is predicted to become a core technology in the near future. Despite its potentials, however, existing designs and solutions for VR applications remain at the infant stage, introducing limited usability and efficiency for real-world users. Besides, the increasing prevalence of VR presents new security and privacy threats due to the vast amount of information stored in or accessible through VR devices. To bridge this gap, we exploit and combine techniques from computer science and human biology, as well …

High Strain Rate Analysis Of 3d Printed Concrete As Compared To Conventionally Cast Concrete, Weston Mcleod Thomsen

Masters Theses

"3D Printed Concrete (3DPC) is a developing method of construction that has advantages over conventional methods, including formwork reduction, complex geometry, and expedited construction. This technology has potential benefits for the military when considering the austere environments that forward operating bases are built in. This study aims to assess 3DPC applications in protective structures that protect critical assets from explosive blasts. These protective structures experience a high-strain rate response during blast loading of the structure, and the effects of this have yet to be analyzed in the literature concerning 3DPC. With the lack of prior research, the focus here will …

Discrete Event Simulation (Des) In Swapping/Charging Of Battery Electric Vehicles In Underground Mining, Albert Einstein Amponsem

Masters Theses

"With climate change concerns escalating, international agreements such as the Kyoto Protocol, the US Presidential Policy, and the Paris Agreement aim to reduce greenhouse gas (GHG) emissions, targeting significant reductions by 2050. The mining sector, a notable contributor to GHG emissions primarily through diesel-powered material haulage, emits approximately 68 million tons of CO₂ annually. Transitioning to Battery Electric Trucks (BETs) presents a viable mitigation strategy by replacing diesel trucks with electric alternatives, thus eliminating CO₂ emissions.

However, the effectiveness of BETs hinges on optimized battery swapping and charging procedures. This study employs Discrete Event Simulation (DES), a computational …

Human Arm Stiffness Estimation Method Developed For Overground Physical Interaction Experiments: Experimental Validation And Perspectives For Future Applications, Tarani Kanth Kamma

Masters Theses

"To build a physically interactive robot for overground applications, it is crucial to first understand the biomechanics of humans underlying overground physical human-robot interaction (pHRI) tasks. Estimating human arm stiffness during overground interactive tasks is a promising first step toward this goal. For this, an arm stiffness estimation technique was developed in our previous works that consider the unique challenges involving overground pHRI, such as the need to estimate the arm stiffness from a short duration of data with fewer repetitions. In this work, our stiffness estimation method is further validated with a passive spring setup with known stiffness values, …

A Review Of Dielectric Barrier Discharge Cold Atmospheric Plasma For Surface Sterilization And Decontamination, Kolawole Adesina, Ta Chun Lin, Yue-Wern Huang, Marek Locmelis, Daoru Frank Han

Biological Sciences Faculty Research & Creative Works

Numerous investigations have shown that non-equilibrium discharges at atmospheric pressure, also known as "cold atmospheric plasma" (CAP) are efficient to remove biological contaminants from surfaces of a variety of materials. Recently, CAP has quickly advanced as a technique for microbial cleaning, wound healing, and cancer therapy due to the chemical and biologically active radicals it produces, known collectively as reactive oxygen and nitrogen species (RONS). This article reviews studies pertaining to one of the atmospheric plasma sources known as Dielectric Barrier Discharge (DBD) which has been widely used to treat materials with microbes for sterilization, disinfection, and decontamination purposes. To …

In Vitro Assessment Of The Anti-Biofilm Effectiveness Of Copper And Zinc Enhanced Borate Bioactive Glass Using Processed Microscopic Images, Sarah Fakher, David J. Westenberg

Biological Sciences Faculty Research & Creative Works

The escalating burden of nosocomial infections presents a formidable challenge to healthcare systems worldwide, leading to increased morbidity, prolonged hospital stays, and elevated healthcare costs. These infections are often resistant to conventional antibiotic therapies due to their association with biofilms which contribute to the persistence and resistance of pathogens. In addressing the challenge of biofilm-associated nosocomial infections, borate bioactive glasses (BBGs) have emerged as promising biomaterials. Doping these glasses with antimicrobial metals could potentially harness their antibacterial properties to prevent biofilm formation. This study undertakes a rigorous evaluation of the anti-biofilm efficacy of copper and zinc-doped BBGs by employing processed …

Advanced Detection Of Sars-Cov-2 And Omicron Variants Via Mxene-Graphene Hybrid Biosensors Utilizing Nucleic Acid Probes, Jiaoli Li, Yuwei Zhang, Congjie Wei, Yanxiao Li, Zhekun Peng, Hsin Yin Chuang, Logan Pearce, Adrianus Boon, Yue-Wern Huang, Dong Hyun Kim, Risheng Wang, Chenglin Wu

Biological Sciences Faculty Research & Creative Works

Low-cost biosensors that can rapidly and widely detect viruses are critical for faster diagnosis and treatment decision-making, especially for infections. The commonly used field-effect transistor is sensitive to the biomarker's detection but struggles with precise detection, particularly of nontargets such as ions and proteins. To overcome this limitation, we developed a field-effect transistor biosensor design based on MXene-graphene materials to increase the accuracy and sensitivity of virus detection. Based on the hybridization process between two complementary DNA strands, single-stranded nucleic acids were immobilized on the sensing surface via 3-aminopropyltriethoxysilane and glutaraldehyde to capture the nucleic acids of the target virus. …

Swosu Research And Scholarly Activity Fair 2024, Swosu Office Of Sponsored Programs

SWOSU Research and Scholarly Activity Fair Programs

On behalf of the members of the University Research and Scholarly Activity Committee (USRAC) and the Office of Sponsored Programs (OSP) at Southwestern Oklahoma State University (SWOSU) - Welcome to the Thirty-Second SWOSU Research and Scholarly Activity Fair! There are 61 poster presentations and 10 oral presentations involving over 100 student and faculty researchers, writers, presenters, artists, collaborators, and faculty sponsors encompassing activities from the SWOSU Departments of Biological Sciences, Chemistry & Physics, Engineering Technology, Kinesiology, Language & Literature, Mathematics, Music, Parks and Recreation Management, Pharmacy, Psychology, and Social Sciences.

Post-Fire Hydrologic Analysis: A Tale Of Two Severities, Kendra Fallon, Shawn J. Wheelock, Mojtaba Sadegh, Jennifer L. Pierce, James P. Mcnamara, Megan Cattau, Victor R. Baker

Civil Engineering Faculty Publications and Presentations

Addressing post-fire impacts largely depends on burn “severity.” A singular severity classification that encompasses the holistic effects of fire on all ecosystem processes does not currently exist. Lumping vegetation burn severity and soil burn severity into one metric, or using them interchangeably, can induce large inaccuracies and uncertainties in the intended ecosystem response to forcing. Often, burn “severity” reflects fire impacts on vegetation, which can be measured through remote sensing. Vegetation burn severity is likely more apropos for ecological research, whereas soil burn severity is more relevant for hydrological analyses. This paper reviews different remotely sensed vegetation severity products currently …

3d Flow Field Quantification In An Artery Model Using Optical Flow Method Based On Simulated Multi-Angle Angiography, Zifeng Yang, Hang Yi, Luke Bramlage, Bryan Ludwig

Mechanical and Materials Engineering Faculty Publications

3D flow field in a numerically simulated arterial model is quantified using the three-dimensional optical flow method based on simulated simultaneous multi-angle X-ray angiography of the blood flow with contrast agent perfusions.

Termite Gut Microbe (Tav5) Application To Pulp & Paper Wastewater And Sugarcane Bagasse: Enhancing Lignin Degradation And Methane Generation During Anaerobic Digestion, Doreen Ntiamoah-Asare, Melanie Sattler Ph.D, P.E.

Civil Engineering Dissertations - Archive

TAV5 is a bacterium strain of the family Opitutaceae from Termite-Associated Verrucomicrobium isolated from the hindgut of Reticulitermes Flavipes, the most common subterranean termite in North America. The genome of TAV5 contains genes coding for enzymes that could structurally modify lignin.

Pulp & paper wastewater and Sugarcane bagasse contain high levels of cellulose (44-46%) and hemicellulose (27-32% ), as well as lignin (17-23%) which is recalcitrant to biodegradation. The lignin tend to shield the cellulose and hemicellulose making them inaccessible for biodegradation.

TAV5 can breakdown lignin, making the cellulose and hemicellulose accessible to microorganisms for biodegradation into methane generation for …

Evaluation Of Transfer Learning Models On Traumatic Brain Injury Severity Classification, Ngoc Do, Daniel B. Hier, Tayo Obafemi-Ajayi

Electrical and Computer Engineering Faculty Research & Creative Works

After traumatic brain injury (TBI), clinicians use the Glasgow Coma Scale (GCS) to classify patients by severity and radiologists use the Rotterdam score and the Marshall score to classify CT scans by severity. This work investigates a viable efficient low-cost transfer learning model to use MRI images to predict GCS, Rotterdam, and Marshall severity class after TBI. The enhanced transfer learning model architecture integrates multiple fine-tuning steps in which a few layers of the pre-trained model is unfrozen in each iteration so that the neural network is able to learn layer by layer further aspects of the image for better …

Variation-Aware Non-Linear Mapping For Honey-Memristor Based Neuromorphic System, Harshvardhan Uppaluru, Md Mehedi Hasan Tanim, Md Omar Faruque, Mohammed Rafeeq Khan, Zoe Templin, Feng Zhao, Jinhui Wang

Electrical and Computer Engineering Faculty Research & Creative Works

Natural organic memristors are promising synapse candidates for neuromorphic systems due to their significant benefits, such as environmental sustainability, low production and disposal cost, non-volatile storage capability, and bio/CMOS-compatibility. In this paper, experimental evaluations of a neuromorphic system based on honey-memristors are reported. First, honey-memristors are manufactured and tested based on our in-house technology, and then the non-linear characteristics inherent to honey-memristors, which causes inaccurate weight updates and reduces the inference accuracy, are explored. A non-linear mapping (NMP) method is applied to mitigate the effects of non-linearity in honey-memristor, under different scenarios including multiple cycle-to-cycle variations and Analog-to-Digital Converter (ADC) …

Molecular Imaging Nanoprobes And Their Applications In Atherosclerosis Diagnosis, Huari Kou, Hu Yang

Chemical and Biochemical Engineering Faculty Research & Creative Works

Molecular imaging has undergone significant development in recent years for its excellent ability to image and quantify biologic processes at cellular and molecular levels. Its application is of significance in cardiovascular diseases, particularly in diagnosing them at early stages. Atherosclerosis is a complex, chronic, and progressive disease that can lead to serious consequences such as heart strokes or infarctions. Attempts have been made to detect atherosclerosis with molecular imaging modalities. Not only do imaging modalities develop rapidly, but research of relevant nanomaterials as imaging probes has also been increasingly studied in recent years. This review focuses on the latest developments …

Pharmacology Of Boldine: Summary Of The Field And Update On Recent Advances, Juan C. Sáez, Justin C. Burrell, Catherine M. Cahill, D. Kacy Cullen, Lakshmi A. Devi, Ryan J. Gilbert, Zachary A. Graham, Vadim J. Gurvich, Leif A. Havton, Ravi Iyengar, Rajesh Khanna, Edmund F. Palermo, Mustafa Siddiq, Carlos A. Toro, Walter Vasquez, Wei Zhao, Christopher P. Cardozo

Chemical and Biochemical Engineering Faculty Research & Creative Works

Over the past decade, boldine, a naturally occurring alkaloid found in several plant species including the Chilean Boldo tree, has garnered attention for its efficacy in rodent models of human disease. Some of the properties that have been attributed to boldine include antioxidant activities, neuroprotective and analgesic actions, hepatoprotective effects, anti-inflammatory actions, cardioprotective effects and anticancer potential. Compelling data now indicates that boldine blocks connexin (Cx) hemichannels (HCs) and that many if not all of its effects in rodent models of injury and disease are due to CxHC blockade. Here we provide an overview of boldine's pharmacological properties, including its …

Aggregation And Oligomerization Characterization Of Ss-Lactoglobulin Protein Using A Solid-State Nanopore Sensor, Mitu C. Acharjee, Brad Ledden, Brian Thomas, Xianglan He, Troy Messina, Jason Giurleo, David Talaga, Jiali Li

Physics Faculty Publications and Presentations

Protein aggregation is linked to many chronic and devastating neurodegenerative human diseases and is strongly associated with aging. This work demonstrates that protein aggregation and oligomerization can be evaluated by a solid-state nanopore method at the single molecule level. A silicon nitride nanopore sensor was used to characterize both the amyloidogenic and native-state oligomerization of a model protein ß-lactoglobulin variant A (βLGa). The findings from the nanopore measurements are validated against atomic force microscopy (AFM) and dynamic light scattering (DLS) data, comparing βLGa aggregation from the same samples at various stages. By calibrating with linear and circular dsDNA, this study …

Effect Of Bioactive Borate Glass On Printability And Physical Properties Of Hydrogels, Fateme Fayyazbakhsh, Mehedi H. Tusar, Yue-Wern Huang, Ming C. Leu

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Hydrogels are a key component in bioinks and biomaterial inks for bioprinting due to their biocompatibility and printability at room temperature. The research described in the present paper contributes to the advancement of bioprinting by studying the effect of bioactive borate glass (BBG) incorporated into hydrogels on printability and physical properties. In this study, we fabricated 3D-printed hydrogel scaffolds using gelatin and alginate hydrogel mixture incorporated with various amounts of BBG, a bio ceramic rich in therapeutic ions including boron, calcium, copper, and zinc. We investigated the effect of incorporating BBG on the density, viscosity, physical interactions, chemical structure, and …

Pleated Plasma Membrane Complex In Spermatids Of The Western Siren, Siren Nettingi (Caudata: Sirenidae), S.E. Trauth

Journal of the Arkansas Academy of Science

I investigated the pleated plasma membrane complex of linear folds and biflagellar entities in developing spermatids of the Western Siren, Siren nettingi. My primary goal was to reveal the ultrastructural morphology of these distinctive cellular folds (usually 8 in number) as they support the flagellar formation of biflagellated sperm found in this salamander and in other members in the family Sirenidae. My results reveal that the biflagellar components (2 sets of axonemes, undulating membranes, and axial fibers), termed biflagellar complex, develop between folds or are attached onto these folds. The folds themselves are transitory and do not directly contribute to …

การวิเคราะห์เชิงเศรษฐศาสตร์เทคโนโลยีของแนวทางการผลิตไฮโดรเจนสำหรับกระบวนการเปลี่ยนคาร์บอนไดออกไซด์เป็นเมทานอลและเปลี่ยนเมทานอลเป็นโอลิฟินส์, กันตภณ มานิมนต์

Chulalongkorn University Theses and Dissertations (Chula ETD)

อุตสาหกรรมปิโตรเคมีเป็นหนึ่งในแหล่งปล่อยก๊าซคาร์บอนไดออกไซด์ (CO2) คิดเป็นสัดส่วนใหญ่ของโลก โดยเฉพาะจากกระบวนการแครกเกอร์แนฟทาด้วยไอน้ำ (Steam Naphtha Cracking) การดักจับและใช้ประโยชน์จากคาร์บอน (Carbon Capture and Utilization: CCU) จึงเป็นแนวทางที่ได้รับความสนใจเพื่อลดการปล่อย CO2 หนึ่งในกระบวนการที่มีศักยภาพคือ ไฮโดรเจนของคาร์บอนไดออกไซด์ (Hydrogenation of CO2) เพื่อผลิตเมทานอล ซึ่งเมทานอลสามารถนำไปใช้เป็นวัตถุดิบในกระบวนการแปรรูปเป็นโอเลฟินส์ (Methanol-to-Olefins: MTO) ได้อีกด้วย งานวิจัยนี้ศึกษาแนวทางการผลิตไฮโดรเจนซึ่งเป็นสารตั้งต้นที่สำคัญของกระบวนการ โดยศึกษา3 ประเภท ได้แก่ ไฮโดรเจนสีเทา (Grey Hydrogen) จากกระบวนการ Steam Methane Reforming (SMR), Autothermal Reforming (ATR) และ SMR ร่วมกับ ATR, ไฮโดรเจนสีน้ำเงิน (Blue Hydrogen) และไฮโดรเจนสีเขียว (Green Hydrogen) จากกระบวนการอิเล็กโทรไลซิส (AEL) โดยทำการจำลองกระบวนการด้วย Aspen Plus และประเมินค่าเชิงเศรษฐศาสตร์ด้วยค่า LCOH (Levelized Cost of Hydrogen) ผลการศึกษาแสดงให้เห็นว่า ไฮโดรเจนสีเทาแบบ SMR มี LCOH ต่ำที่สุดที่ 1.03 USD/kg H2 แต่ปล่อย CO2 สูงสุด 13.44 kg CO2/kg H2 ขณะที่ไฮโดรเจนสีน้ำเงินให้การลด CO2 ที่ดีขึ้น 6.85 kg CO2/kg H2 ด้วยต้นทุนที่เพิ่มขึ้น 1.16 USD/kg H2 ส่วนไฮโดรเจนสีเขียวปล่อย CO2 ต่ำที่สุดแต่มีต้นทุนสูงสุดที่ 4.38 USD/kg H2 ดังนั้นการเลือกใช้แหล่งผลิตไฮโดรเจนที่เหมาะสมจึงมีผลโดยตรงต่อประสิทธิภาพและความยั่งยืนของกระบวนการผลิตเมทานอลและโอเลฟินส์ในอนาคต

Temperature Control In The Steam Methane Reformer Using Model Predictive Control Based On A Neural Network Model, Rasiq Dipta Alkindi

Chulalongkorn University Theses and Dissertations (Chula ETD)

Hydrogen is a critical energy vector, and magnetic heating reactors represent a promising production technology where current-induced magnetization raises system temperature. Due to the nonlinear and complex thermal dynamics, this study applies a hybrid Echo State Network (ESN) and Long Short-Term Memory (LSTM) model to capture system behavior, combining ESN’s nonlinear dynamic identification with LSTM’s ability to learn long-term dependencies. Hyperparameters were optimized for best performance at 30 reservoir nodes, 0.5 spectral radius, 0.9 connectivity, batch size 4, 50 LSTM units, and 60 epochs. The ESN-LSTM models with 3-input and 4-input feature sets were tested on three winding coil geometries …

Investigation Of Molecular Interactions In Electrocatalysis Using Atomic Force Microscopy, Parivat Phiphatbunyabhorn

Chulalongkorn University Theses and Dissertations (Chula ETD)

Electrocatalysis at the nanoscale is fundamentally governed by molecular interactions, but these processes remain poorly understood due to their difficulty to directly investigate and their complex nature. In this study, atomic force microscopy (AFM)-based force spectroscopy is employed to investigate interfacial forces and reactivity in two representative systems: the electrochemical deterioration and healing of Au nanothin films on n-type silicon and the electrocatalytic reduction of MEA-CO2 adduct on Cu electrocatalysts. In the Au nanothin film system, observing that surface degradation is mediated by anionic cluster interactions and modulated by intrinsic band bending and surface energy effects. Remarkably, 20-nm Au films …