Digital Commons Network^™

A Phase Change Memory And Dram Based Framework For Energy-Efficient And High-Speed In-Memory Stochastic Computing, Supreeth Mysore

Theses and Dissertations--Electrical and Computer Engineering

Convolutional Neural Networks (CNNs) have proven to be highly effective in various fields related to Artificial Intelligence (AI) and Machine Learning (ML). However, the significant computational and memory requirements of CNNs make their processing highly compute and memory-intensive. In particular, the multiply-accumulate (MAC) operation, which is a fundamental building block of CNNs, requires enormous arithmetic operations. As the input dataset size increases, the traditional processor-centric von-Neumann computing architecture becomes ill-suited for CNN-based applications. This results in exponentially higher latency and energy costs, making the processing of CNNs highly challenging.

To overcome these challenges, researchers have explored the Processing-In Memory (PIM) …

Modeling The Early Visual System, Nicholas Lanning

Theses and Dissertations--Electrical and Computer Engineering

There are two encoding schema present in simple cells in the early visual system of vertebrates: the retinal simple cells activate highly when the receptive field contains a center surround stimulus, while the primary visual cortex’s (V1) simple cells activate highly when the receptive field contains visual edges. Work has been done in the past to enforce constraints on visual machine learning such that the retinal or V1 encoding is learned, but this work is often done to emulate retinal and V1 encoding in a vacuum. Recent work using convolutional neural networks focuses on anatomical constraints along with a supervised …

Increased Liver Stiffness Promotes Hepatitis B Progression By Impairing Innate Immunity In Ccl4-Induced Fibrotic Hbv+ Transgenic Mice, Grace Bybee, Youra Moeun, Weimin Wang, Kusum K. Kharbanda, Larisa Y. Poluektova, Srivatsan Kidambi, Natalia A. Osna, Murali Ganesan

Department of Chemical and Biomolecular Engineering: Faculty Publications

Background: Hepatitis B virus (HBV) infection develops as an acute or chronic liver disease, which progresses from steatosis, hepatitis, and fibrosis to end-stage liver diseases such as cirrhosis and hepatocellular carcinoma (HCC). An increased stromal stiffness accompanies fibrosis in chronic liver diseases and is considered a strong predictor for disease progression. The goal of this study was to establish the mechanisms by which enhanced liver stiffness regulates HBV infectivity in the fibrotic liver tissue. Methods: For in vitro studies, HBV-transfected HepG2.2.15 cells were cultured on polydimethylsiloxane gels coated by polyelectrolyte multilayer films of 2 kPa (soft) or 24 kPa (stiff) …

Mesenchymal Stromal Cells And Alpha-1 Antitrypsin Have A Strong Synergy In Modulating Inflammation And Its Resolution, Li Han, Xinran Wu, Ou Wang, Xiao Luan, William Velander, Michael Aynardi, E. Scott Halstead, Anthony S. Bonavia, Rong Jin, Guohong Li, Yulong Li, Yong Wang, Cheng Dong, Yuguo Lei

Department of Chemical and Biomolecular Engineering: Faculty Publications

Rationale: Trauma, surgery, and infection can cause severe inflammation. Both dysregulated inflammation intensity and duration can lead to significant tissue injuries, organ dysfunction, mortality, and morbidity. Anti-inflammatory drugs such as steroids and immunosuppressants can dampen inflammation intensity, but they derail inflammation resolution, compromise normal immunity, and have significant adverse effects. The natural inflammation regulator mesenchymal stromal cells (MSCs) have high therapeutic potential because of their unique capabilities to mitigate inflammation intensity, enhance normal immunity, and accelerate inflammation resolution and tissue healing. Furthermore, clinical studies have shown that MSCs are safe and effective. However, they are not potent enough, alone, to …

Impact Of Eastern Redcedar Encroachment On Water Resources In The Nebraska Sandhills, Yaser Kishawi, Aaron R. Mittelstet, Troy E. Gilmore, Dirac Twidwell, Tirthankar Roy, Nawaraj Shrestha

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Worldwide, tree or shrub dominated woodlands have encroached into herbaceous dominated grasslands. While very few studies have evaluated the impact of Eastern Redcedar (redcedar) encroachment on the water budget, none have analyzed the impact on water quality. In this study, we evaluated the impact of redcedar encroachment on the water budget in the Nebraska Sand Hills and how the decreased streamflow would increase nitrate and atrazine concentrations in the Platte River. We calibrated a Soil and Water Assessment Tool (SWAT model) for streamflow, recharge, and evapotranspiration. Using a moving window with a dilate morphological filter, encroachment scenarios of 11.9%, 16.1%, …

A Graduate-Level Field Course In Irrigation And Agricultural Water Management For An Immersive Learning Experience, Derek M. Heeren, László G. Hayde, Dean Eisenhauer, Peter G. Mccornick, Ali T. Mohammed, Aaron R. Mittelstet, Alan L. Boldt, Xin Qiao, David Mabie, Francisco Muñoz-Arriola

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Effective irrigation and agricultural water management (IAWM) is critical for food security and water security. A key requirement in designing, implementing and operation of IWM is the necessary knowledge and capacity on the farm, in the service industry and within the supply chain. Educational opportunities that not only teach the relevant principles of irrigated agriculture, but also the necessary applied skills are essential. An Irrigation Field Course was initiated by the IHE Delft Institute for Water Education (IHE Delft) and was later developed as a joint field course with IHE Delft, the University of Nebraska-Lincoln (UNL), and the Daugherty Water …

Complab V1.0: A Scalable Pore-Scale Model For Flow, Biogeochemistry, Microbial Metabolism, And Biofilm Dynamics, Heewon Jung, Hyun-Seob Song, Christof Meile

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Microbial activity and chemical reactions in porous media depend on the local conditions at the pore scale and can involve complex feedback with fluid flow and mass transport. We present a modeling framework that quantitatively accounts for the interactions between the bio(geo)chemical and physical processes and that can integrate genome-scale microbial metabolic information into a dynamically changing, spatially explicit representation of environmental conditions. The model couples a lattice Boltzmann implementation of Navier–Stokes (flow) and advection–diffusion-reaction (mass conservation) equations. Reaction formulations can include both kinetic rate expressions and flux balance analysis, thereby integrating reactive transport modeling and systems biology. We also …

Evaluating Management Zones And Crop-Sensing Relationships For Improved Irrigated Maize Nitrogen Management, Joel D. Crowther, John Parrish, Joe Luck, Richard Ferguson

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Active crop canopy sensors and management zones (MZ) are two methods of directing variable-rate, in-season nitrogen (N) fertilizer applications in maize (Zea mays L.). Researchers have suggested that integrating these two approaches may result in improved performance of sensor-based N application algorithms through increased N use efficiency and profitability. The objectives of this research study were to (1) identify soil and topographic variables that are related to in-season canopy reflectance and yield for soil-based MZ delineation and (2) determine if delineated MZ can identify areas with differential crop response to N fertilizer. N ramp blocks were placed end-to-end in field-length …

Agricultural Machinery Operator Monitoring System (Ag-Oms): A Machine Learning Approach For Real-Time Operator Safety Assessment, Terence Irumva, Herve Mwunguzi, Santosh Pitla, Bethany Lowndes, Aaron Yoder, Ka-Chun Siu

Department of Agricultural and Biological Systems Engineering: Faculty Publications

The 2015 CS-CASH (Central States Center for Agricultural Safety and Health, 2015) Injury Surveillance Surveys showed that around 19% of injuries to agricultural producers are related to tractors or large agricultural machinery, yet only a limited number of studies are found that address tools and methods for monitoring safety behaviors of agricultural machinery operators in real-time. The current safety behavior monitoring approaches require an in-person presence, which can be both time- and cost-inefficient, and the other available methods lack a feedback element to alert operators in realtime. As a result, the research presented in this study aimed to develop an …

Crop Stress Sensing And Plant Phenotyping Systems: A Review, Geng Bai, Yufeng Ge

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Enhancing resource use efficiency in agricultural field management and breeding high-performance crop varieties are crucial approaches for securing crop yield and mitigating negative environmental impact of crop production. Crop stress sensing and plant phenotyping systems are integral to variable-rate (VR) field management and high-throughput plant phenotyping (HTPP), with both sharing similarities in hardware and data processing techniques. Crop stress sensing systems for VR field management have been studied for decades, aiming to establish more sustainable management practices. Concurrently, significant advancements in HTPP system development have provided a technological foundation for reducing conventional phenotyping costs. In this paper, we present a …

Goniometer In The Air: Enabling Brdf Measurement Of Crop Canopies Using A Cable-Suspended Plant Phenotyping Platform, Geng Bai, Yufeng Ge, Bryan Leavitt, John Gamon, David Scoby

Department of Agricultural and Biological Systems Engineering: Faculty Publications

The Bidirectional Reflectance Distribution Function (BRDF) quantifies the distribution of the spectral reflectance of a target surface at various viewing and illumination angles. In-field measurement of the BRDF of vegetation canopies improves the characterization of offnadir measurements and informs radiative transfer models of canopy reflectance, where the Lambertian assumption does not hold. However, current field goniometers are unable to measure BRDF efficiently, especially for tall vegetation across the growing season because of the limitations of clearance, field accessibility, and flexibility of the sensor field of view. In this study, we explored the potential of using a large-scale cable-suspended field phenotyping …

Osc-Co2: Coattention And Cosegmentation Framework For Plant State Change With Multiple Features, Rubi Quiñones, Ashok Samal, Sruti Das Choudhury, Francisco Muñoz-Arriola

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Cosegmentation and coattention are extensions of traditional segmentation methods aimed at detecting a common object (or objects) in a group of images. Current cosegmentation and coattention methods are ineffective for objects, such as plants, that change their morphological state while being captured in different modalities and views. The Object State Change using Coattention-Cosegmentation (OSC-CO²) is an end-to-end unsupervised deep-learning framework that enhances traditional segmentation techniques, processing, analyzing, selecting, and combining suitable segmentation results that may contain most of our target object’s pixels, and then displaying a final segmented image. The framework leverages coattention-based convolutional neural networks (CNNs) and …

Clim4omics: A Geospatially Comprehensive Climate And Multi-Omics Database For Maize Phenotype Predictability In The United States And Canada, Parisa Sarzaeim, Francisco Muñoz-Arriola, Diego Jarquin, Hasnat Aslam, Natalia De Leon Gatti

Department of Agricultural and Biological Systems Engineering: Faculty Publications

The performance of numerical, statistical, and data-driven diagnostic and predictive crop production modeling relies heavily on data quality for input and calibration or validation processes. This study presents a comprehensive database and the analytics used to consolidate it as a homogeneous, consistent, multidimensional genotype, phenotypic, and environmental database for maize phenotype modeling, diagnostics, and prediction. The data used are obtained from the Genomes to Fields (G2F) initiative, which provides multiyear genomic (G), environmental (E), and phenotypic (P) datasets that can be used to train and test crop growth models to understand the genotype by environment (GxE) interaction phenomenon. A particular …

Estimating Battery Size Requirements For Tractor Electrification Of Row-Crop Planting Operations, Cheetown Liew, Andrew Donesky, Mark Freyhof, Ian Tempelmeyer, Santosh Kumar Pitla

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Power sources such as batteries, used for both on-road and off-road vehicles, are advancing at a rapid pace. Electric batteries are becoming more power dense, thus allowing them to be used as a power source to replace previous diesel or gasoline-powered systems. Efforts are underway to transition off-road agricultural vehicles from Internal Combustion Engine (ICE) vehicles to electric vehicles (EVs); however, the energy requirements of typical agricultural field operations need to be fully understood before such a transition can occur. Theoretical prediction equations available in the American Society of Agricultural and Biological Engineers (ASABE) standards or the use of engine …

Higher Concentrations Of Microplastics In Runoff From Biosolid-Amended Croplands Than Manure-Amended Croplands, Nasrin Naderi Beni, Shahab Karimifard, John Gilley, Tiffany Messer, Amy Schmidt, Shannon L. Bartelt-Hunt

Department of Civil and Environmental Engineering: Faculty Publications

Land-applied municipal biosolids, produced from municipal wastewater treatment sludge, contributes to microplastics contamination in agroecosystems. The impacts of biosolids on microplastic concentrations in agricultural soil have been previously investigated, however, the potential for microplastics transport from biosolid-amended croplands has not been previously quantified. In this study, manure and biosolids were applied to field plots, runoff was collected following natural precipitation events and the potential of bacterial biofilm to grow on different microplastic morphologies was investigated. Higher concentrations of microplastics were detected in runoff from plots with land-applied biosolid in comparison with manure-amended and control plots. Fibers and fragments were the …

Fusarium Graminearum Effector Fgnls1 Targets Plant Nuclei To Induce Wheat Head Blight, Guixia Hao, Todd A. Naumann, Hui Chen, Guihua Bai, Susan Mccormick, Hye-Seon Kim, Bin Tian, Harold N. Trick, Michael J. Naldrett, Robert Proctor

Nebraska Center for Biotechnology: Faculty and Staff Publications

Fusarium head blight (FHB) caused by Fusarium graminearum is one of the most devastating diseases of wheat and barley worldwide. Effectors suppress host immunity and promote disease development. The genome of F. graminearum contains hundreds of effectors with unknown function. Therefore, investigations of the functions of these effectors will facilitate developing novel strategies to enhance wheat resistance to FHB. We characterized a F. graminearum effector, FgNls1, containing a signal peptide and multiple eukaryotic nuclear localization signals. A fusion protein of green fluorescent protein and FgNls1 accumulated in plant cell nucleiwhen transiently expressed in Nicotiana benthamiana. FgNls1 suppressed …

Brain Activity Associated With Taste Stimulation: A Mechanism For Neuroplastic Change?, Angela M. Dietsch, Ross M. Westemeyer, Douglas H. Schultz

Department of Special Education and Communication Disorders: Faculty Publications

Purpose: Neuroplasticity may be enhanced by increasing brain activation and bloodflow in neural regions relevant to the target behavior.We administered precisely formulated and dosed taste stimuli to determine whether the associated brain activity patterns included areas that underlie swallowing control.

Methods: Five taste stimuli (unflavored, sour, sweet-sour, lemon, and orange suspensions) were administered in timing-regulated and temperature-controlled 3 mL doses via a customized pump/tubing system to 21 healthy adults during functional magnetic resonance imaging (fMRI). Whole-brain analyses of fMRI data assessed main effects of taste stimulation as well as differential effects of taste profile.

Results: Differences in …

College Of Computing And Engineering Graduate Catalog 2023-2024, Nova Southeastern University

College of Psychological Services / College of Psychology Postgraduate Student and Course Catalogs

No abstract provided.

Phosphorus Release And Recovery From Simulated Ferric Wastewater Sludge, Aseel Alnimer

Theses and Dissertations (Comprehensive)

Phosphorus (P) is a fundamental element necessary for all life forms and a key component in the fertilizer industry. Meanwhile, the excessive load of P to water bodies due to human activities has the potential to promote eutrophication. Wastewater treatment plants remove P either biologically or chemically and produce P rich sludge which could be a potential renewable source for P. At present, commercial technologies exist for P recovery from biological wastewater sludge. However, P recovery from chemical sludge particularly iron(III)-phosphate (Fe-P) sludge generated in chemical P removal plants that use iron(III) salts remains a challenge.

This study explored, in …

A Natural Language Processing Approach To Malware Classification, Ritik Mehta

Master's Projects

Many different machine learning and deep learning techniques have been successfully employed for malware detection and classification. Examples of popular learning techniques in the malware domain include Hidden Markov Models (HMM), Random Forests (RF), Convolutional Neural Networks (CNN), Support Vector Machines (SVM), and Recurrent Neural Networks (RNN) such as Long Short-Term Memory (LSTM) networks. In this research, we consider a hybrid architecture, where HMMs are trained on opcode sequences, and the resulting hidden states of these trained HMMs are used as feature vectors in various classifiers. In this context, extracting the HMM hidden state sequences can be viewed as a …

Metagenomic Survey Of Marine 16s Bacterial Communities Off Palmer Station In Antarctica, Daniel Salter

Master's Projects

This project surveys the metagenomic bacterial community composition in marine surface waters off Palmer Station, Western Antarctic Peninsula and correlates findings with temperature and salinity data. Marine bacterial communities play a vital role in nutrient cycling, but data on surface waters in this region are limited. Analyzing fifteen samples of 16S sequencing data from three austral summers, consistent dominance was observed by the classes Alphaproteobacteria, Gammaproteobacteria, and Flavobacteria. Correlation analysis confirmed significant relationships between taxa and environmental conditions. The observed trends suggest varying abilities of phyla to resist and adapt to changing environmental conditions. Notably, Alphaproteobacteria demonstrated adaptability to favorable …

Visual Scene Classification Using Ensemble Of Machine Learning Classifiers, Rahul Ranganath

Master's Projects

Visual scenes represent the comprehensive visual information observed in a particular environment. Whether natural landscapes, urban settings, or designed interiors, visual scenes encompass the arrangement of elements that individuals perceive through their visual senses. Visual search is perhaps one of the most typical jobs that we carry out several times a day. This is one of the main paradigms for researching visual attention. Many visual task models have been put forward in an effort to better understand visual attention. Fixations and the rapid movement of the eye - saccades, define visual exploration and visual search. When we subject viewers to …

Identification Of Copy Number Variations (Cnvs) Of Epigenetic Factors Related To The Progression Of Pancreatic Ductal Adenocarcinoma (Pdac), Pavithra Raju

Master's Projects

Pancreatic ductal adenocarcinoma (PDAC) is a formidable challenge in oncology due to its aggressive form and late-stage detection. PDAC is known to be influenced by various epigenetic factors like DNA methylation and histone modifications. This study focuses on copy number variations (CNVs) within epigenetic factors which for their role in early diagnosis. Thus, paving the way for identification of potential biomarkers. The epigenetic pipeline was extended based on CNVs and the CNV modified sequences extracted were compared with the wild type sequences of epigenetic PDAC genes. The epigenetic gene KCNJ11 with copy number gain of CNV id 46771406 was used …

Analyzing The Benthic Cover Of Crustose Coralline Algae Using Mask-R Cnn, Rachana Ravindra

Master's Projects

Coral reefs, supporting 25% of marine biodiversity, confront challenges from local and global impacts like overfishing, runoff, acidification, and warming. Crustose Coralline Algae (CCA), pivotal for reef structure and coral settlement, are underrepresented in research. Current methods like Coral Point Count with Excel Extensions (CPCe) have limitations, relying on image quality and being time-consuming. This paper proposes computer vision and Mask R-CNN, a supervised machine learning model, for CCA analysis in reef images, considering color, texture, and shape. Results indicate promise in clustering and classifying organisms. The innovative technology reduces manual labor, enhancing image analysis, simplifying the understanding of CCA’s …

Pygrapherconnect, Shubham Jain

Master's Projects

The evolving landscape of backend computational systems especially in biomedical research involving heavy data operations which have a gap of not being used properly. It is due to the lack of communication standard between the frontend and backend. This gap presents a problem to researchers who need to use the frontend for visualizing and manipulating their data but also want to do complex analysis. CAPRI a python-based backend system specializing in analyzing Evidential Reasoning data also has the same issue. This project offers a solution PyGrapherConnect module acting as a data conversion layer between CAPRI and PyGrapher, its frontend interface. …

Mild Cognitive Impairment And Alzheimer’S Disease Detection And Testing Interface (Mci-Addti) Modeller10.4 Integrating Structure-Function Prediction Modules, Grant Galileo Jacobson

Master's Projects

In the population of adult human patients who over express Beta and Tau Amyloids, it is unclear why 40% of them do not have Alzheimer’s Disease (AD), when all patients with AD have an overexpression of Beta and Tau Amyloids. The MCI-AD-DTI project’s epigenetic pipeline is an evolving computation tool that seeks epigenetic-related information related to the observed disparity. The MCI-AD-DTI’s epigenetic pipeline’s ability to identify mutations currently relies solely on PyPDB for verification of its protein functionality evaluation. The assessment process of the industry standard application, Modeller10.4, is independent from the current epigenetic pipeline’s protein evaluation algorithm. Thus, this …

Trihalomethane Formation Potentials From Effluent Of Different Wastewater Treatment Sources And Health Risk Assessment, Kangsadal Phlaengsattra

Chulalongkorn University Theses and Dissertations (Chula ETD)

This study aimed to investigate the levels of THMs and THM formation potentials (THMFP) in treated wastewater originating from different sources i.e., domestic, food-processing industry and hospital, and to evaluate the maximum potential carcinogenic risk through dermal exposure. The samples from each source were collected three times between June and August 2023. Dissolved organic carbon (DOC), ultraviolet absorbance at 254 nm (UV254), and specific ultraviolet absorbance (SUVA) were evaluated from the samples prior to and after disinfection with chlorine over 7 days. The results found that the concentration of DOC was highest in hospital effluent, with an average value of …

Enhancing The Performance Of Federated Learning With Diffusion Models: Leveraging Synthetic Data To Address Non-Iid Data Challenges, Karin Huangsuwan

Chulalongkorn University Theses and Dissertations (Chula ETD)

In the context of machine learning in healthcare, federated learning (FL) is frequently seen as an effective approach to tackling issues of data privacy and distribution. Nonetheless, many real-world datasets exhibit non-identical and independently distributed (non-IID) characteristics, meaning that data features vary across different institutions. This non-IID nature presents challenges for FL model convergence, such as client drifting, where model weights lean towards local optima rather than global optimum. To address these issues, we introduce a new framework called "FedDrip (Federated Learning with Diffusion Reinforcement at Pseudo-site)," which leverages diffusion-generated synthetic data to mitigate data-related problems in non-IID settings. Our …

การพัฒนาไฮโดรเจลเจลาตินที่มีอนุภาคนาโนทองคำ สำหรับการวัดปริมาณรังสี, ภาวิณี ชูสินธ์

Chulalongkorn University Theses and Dissertations (Chula ETD)

ปัจจุบันรังสีรักษามีบทบาทสำคัญในการช่วยรักษาโรคมะเร็ง โดยการให้ปริมาณรังสีสูงสุดที่เนื้อเยื่อมะเร็ง และก่อให้เกิดผลกระทบต่อเนื้อปกติน้อยที่สุด ดังนั้นความถูกต้องของปริมาณรังสีจึงเป็นสิ่งสำคัญ การวัดปริมาณรังสีเป็นสิ่งหนึ่งที่ช่วยยืนยันและสร้างความมั่นใจให้ผู้ป่วยได้ การศึกษาวิจัยนี้ได้พัฒนาอุปกรณ์การวัดปริมาณรังสีในรูปแบบไฮโดรเจลชนิดใหม่ สำหรับการวัดปริมาณรังสี ที่มีคุณลักษณะเฉพาะตัวในการขึ้นรูปได้หลายมิติ และมีความเข้ากันได้ทางชีวภาพจากพอลิเมอร์ธรรมชาติ เช่น เจลาตินและอะกราโรส ผสมกับสารละลายทองคำ โดยอาศัยนวัตกรรมนาโนเทคโนโลยี และการเปลี่ยนแปลงปฏิกิริยาทางเคมีของไฮโดรเจลเมื่อมีการฉายรังสี ทำให้เกิดการสังเคราะห์อนุภาคนาโนทองคำที่มีคุณสมบัติทางแสงที่โดดเด่นและเฉพาะตัวเชิงพื้นผิว ทำให้มองเห็นการเกิดการเปลี่ยนแปลงสีของไฮโดรเจลด้วยสายตาเปล่าได้อย่างรวดเร็วภายใน 10 นาที ภายหลังจากการได้รับรังสี รวมทั้งวัดค่าการดูดกลืนแสงในช่วงปริมาณรังสี 0-5 Gy ด้วยเทคนิคสเปกโตรโฟโตเมตรีที่ความยาวคลื่นดูดกลืนสูงสุดที่ 540 nm พบว่า ปฏิกิริยาทางเคมีภายในไฮโดรเจลเกิดขึ้นได้สมบูรณ์เมื่อได้รับรังสีผ่านไปแล้ว 2 ชั่วโมง โดยมีขีดความสามารถในวัดต่ำสุด คือ 0.37 Gy โดยมีความคงตัวของค่าการดูดกลืนแสงหลังจากได้รับรังสีไปแล้วนานถึง 7-14 วัน รวมทั้งให้ค่าความสัมพันธ์เชิงเส้นตรงของไฮโดรเจลเจลาตินและไฮโดรเจลเจลาตินผสมอะกราโรส เท่ากับ 0.9996 และ 0.9994 ตามลำดับ จากผลการทดลองนี้แสดงให้เห็นถึงความสามารถของไฮโดรเจลชนิดนี้ในการตอบสนองต่อรังสีที่รวดเร็ว ในช่วงปริมาณรังสีต่ำที่ใช้ทางคลินิค ที่มีความคงตัวและความถูกต้องแม่นยำสูง เหมาะสำหรับการนำไปประยุกต์ใช้ในงานรังสีรักษาต่อไป

Use Of Bioheat Modeling To Characterize And Optimize Implantable Medical Devices And Neuromodulation Technologies, Adantchede Louis Zannou

Dissertations and Theses

Medical device development includes prototyping, benchtop characterization, preclinical studies, and clinical trials. Understanding the limitations and potential adverse effects of medical devices prior to their administration in humans is a crucial first step. Optimizing medical devices is essential to employing technology and improving patients care. Computational modeling is widely adopted as a powerful tool to predict stimulation/recording parameter optimization, rapid electrode/device prototyping, investigating novel mechanism of action, and testing working principles of any medical devices. Many implantable neuromodulation technologies including Spinal Cord Stimulation (SCS), which provide substantial therapeutic benefit for patient population with lower back pain, produces heat via the …