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2021

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Articles 9871 - 9900 of 9963

Full-Text Articles in Engineering

Opinion Dynamics Of Stubborn Agents Under The Presence Of A Troll Asdifferential Game, Aykut Yildiz, Ari̇f Bülent Özgüler Jan 2021

Opinion Dynamics Of Stubborn Agents Under The Presence Of A Troll Asdifferential Game, Aykut Yildiz, Ari̇f Bülent Özgüler

Turkish Journal of Electrical Engineering and Computer Sciences

The question of whether opinions of stubborn agents result in Nash equilibrium under the presence of troll is investigated in this study. The opinion dynamics is modelled as a differential game played by n agents during a finite time horizon. Two types of agents, ordinary agents and troll, are considered in this game. Troll is treated as a malicious stubborn content maker who disagrees with every other agent. On the other hand, ordinary agents maintain cooperative communication with other ordinary agents and they disagree with the troll. Under this scenario, explicit expressions of opinion trajectories are obtained by applying Pontryagin?s …

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Brain Tumor Detection From Mri Images With Using Proposed Deep Learningmodel: The Partial Correlation-Based Channel Selection, Atinç Yilmaz Jan 2021

Brain Tumor Detection From Mri Images With Using Proposed Deep Learningmodel: The Partial Correlation-Based Channel Selection, Atinç Yilmaz

Turkish Journal of Electrical Engineering and Computer Sciences

A brain tumor is an abnormal growth of a mass or cell in the brain. Early diagnosis of the tumor significantly increases the chances of successful treatment. Artificial intelligence-based systems can detect the tumor in early stages. In this way, it could be possible to detect a tumor and resolve this problem that may endanger human life early. In the study, the partial correlation-based channel selection formula was presented that allowed the selection of the most prominent feature that differs from the other studies in the literature. Additionally, the multi-channel convolution structure was proposed for the feature network phase of …

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Benchmarking Of Deep Learning Algorithms For Skin Cancer Detection Based On Ahybrid Framework Of Entropy And Vikor Techniques, Baidaa Al-Bander, Qahtan M. Yas, Hussain Mahdi, Rwayda Kh. S. Al-Hamd Jan 2021

Benchmarking Of Deep Learning Algorithms For Skin Cancer Detection Based On Ahybrid Framework Of Entropy And Vikor Techniques, Baidaa Al-Bander, Qahtan M. Yas, Hussain Mahdi, Rwayda Kh. S. Al-Hamd

Turkish Journal of Electrical Engineering and Computer Sciences

Skin cancer is one of the most common cancers worldwide caused by excessive development of skin cells. Considering the rapid growth of the use of deep learning algorithms for skin cancer detection, selecting the optimal algorithm has become crucial to determining the efficiency of computer-aided diagnosis (CAD) systems developed for the healthcare sector. However, a sufficient number of criteria and parameters must be considered when selecting an ideal deep learning algorithm. A generally accepted method for benchmarking deep learning models for skin cancer classification is unavailable in the current literature. This paper presents a multi-criteria decision-making framework for evaluating and …

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A Deep Transfer Learning Based Model For Automatic Detection Of Covid-19from Chest X-Rays, Prateek Chhikara, Prakhar Gupta, Prabhjot Singh, Tarunpreet Bhatia Jan 2021

A Deep Transfer Learning Based Model For Automatic Detection Of Covid-19from Chest X-Rays, Prateek Chhikara, Prakhar Gupta, Prabhjot Singh, Tarunpreet Bhatia

Turkish Journal of Electrical Engineering and Computer Sciences

Deep learning in medical imaging has revolutionized the way we interpret medical data, as high computational devices' capabilities are far more than their creators. With the pandemic causing havoc for the second straight year, the findings in our paper will allow researchers worldwide to use and create state-of-the-art models to detect affected persons before it reaches the R number. The paper proposes an automated diagnostic tool using the deep learning models on chest x-rays as an input to reach a point where we surpass this pandemic (COVID-19 disease). A deep transfer learning-based model for automatic detection of COVID-19 from chest …

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Attention-Based End-To-End Cnn Framework For Content-Based X-Ray Imageretrieval, Şaban Öztürk, Adi Alhudhaif, Kemal Polat Jan 2021

Attention-Based End-To-End Cnn Framework For Content-Based X-Ray Imageretrieval, Şaban Öztürk, Adi Alhudhaif, Kemal Polat

Turkish Journal of Electrical Engineering and Computer Sciences

The widespread use of medical imaging devices allows deep analysis of diseases. However, the task of examining medical images increases the burden of specialist doctors. Computer-assisted systems provide an effective management tool that enables these images to be analyzed automatically. Although these tools are used for various purposes, today, they are moving towards retrieval systems to access increasing data quickly. In hospitals, the need for content-based image retrieval systems is seriously evident in order to store all images effectively and access them quickly when necessary. In this study, an attention-based end-to-end convolutional neural network (CNN)framework that can provide effective access …

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Classification Of P300 Based Brain Computer Interface Systems Using Longshort-Term Memory (Lstm) Neural Networks With Feature Fusion, Ali̇ Osman Selvi̇, Abdullah Feri̇koğlu, Derya Güzel Jan 2021

Classification Of P300 Based Brain Computer Interface Systems Using Longshort-Term Memory (Lstm) Neural Networks With Feature Fusion, Ali̇ Osman Selvi̇, Abdullah Feri̇koğlu, Derya Güzel

Turkish Journal of Electrical Engineering and Computer Sciences

Enabling to obtain brain activation signs, electroencephalography is currently used in many applications as a medical diagnostic method. Brain-computer interface (BCI) applications are developed to facilitate the lives of individuals who have not lost their brain functions yet have lost their motor and communication abilities. In this study, a BCI system is proposed to make classification using Bi-directional long short term memory (Bi-LSTM) neural networks. In the designed system, spectral entropy method including instantaneous frequency change of signal is used as feature fusion. In the study, electroencephalography (EEG) data of 10 participants are collected with Emotiv EPOC+ device using 2x2 …

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Mri Based Genomic Analysis Of Glioma Using Three Pathway Deep Convolutionalneural Network For Idh Classification, Sonal Gore, Jayant Jagtap Jan 2021

Mri Based Genomic Analysis Of Glioma Using Three Pathway Deep Convolutionalneural Network For Idh Classification, Sonal Gore, Jayant Jagtap

Turkish Journal of Electrical Engineering and Computer Sciences

As per 2016 updates by World Health Organization (WHO) on cancer disease, gliomas are categorized and further treated based on genomic mutations. The imaging modalities support a complimentary but immediate noninvasive diagnosis of cancer based on genetic mutations. Our aim is to train a deep convolutional neural network for isocitrate dehydrogenase (IDH) genotyping of glioma by auto-extracting the most discriminative features from magnetic resonance imaging (MRI) volumes. MR imaging data of total 217 patients were obtained from The Cancer Imaging Archives (TCIA) of high and low-grade gliomas. A 3-pathway convolutional neural network was trained for IDH classification. The multipath neural …

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Employing Deep Learning Architectures For Image-Based Automatic Cataractdiagnosis, Emrullah Acar, Ömer Türk, Ömer Faruk Ertuğrul, Erdoğan Aldemi̇r Jan 2021

Employing Deep Learning Architectures For Image-Based Automatic Cataractdiagnosis, Emrullah Acar, Ömer Türk, Ömer Faruk Ertuğrul, Erdoğan Aldemi̇r

Turkish Journal of Electrical Engineering and Computer Sciences

Various eye diseases affect the quality of human life severely and ultimately may result in complete vision loss. Ocular diseases manifest themselves through mostly visual indicators in the early or mature stages of the disease by showing abnormalities in optics disc, fovea, or other descriptive anatomical structures of the eye. Cataract is among the most harmful diseases that affects millions of people and the leading cause of public vision impairment. It shows major visual symptoms that can be employed for early detection before the hypermature stage. Automatic diagnosis systems intend to assist ophthalmological experts by mitigating the burden of manual …

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Evolution Of Histopathological Breast Cancer Images Classification Using Stochasticdilated Residual Ghost Model, Ramgopal Kashyap Jan 2021

Evolution Of Histopathological Breast Cancer Images Classification Using Stochasticdilated Residual Ghost Model, Ramgopal Kashyap

Turkish Journal of Electrical Engineering and Computer Sciences

Breast cancer detection is a complex problem to solve, and it is a topic that is still being studied. Deep learning-based models aid medical science by helping to classify benign and malignant cancers and saving lives. Breast cancer histopathological image classification (BreakHis) and breast cancer histopathological annotation and diagnosis (BreCaHAD) datasets are used in the proposed model. The study led to the resolution of four essential issues: 1) Addresses the color divergence issue caused by strain normalization during image generation 2) Data augmentation uses several factors like as flip, rotation, shift, resize, and gamma value in order to overcome overfitting …

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Medical Image Fusion With Convolutional Neural Network In Multiscaletransform Domain, Asan Abas, Hasan Erdi̇nç Koçer, Nurdan Baykan Jan 2021

Medical Image Fusion With Convolutional Neural Network In Multiscaletransform Domain, Asan Abas, Hasan Erdi̇nç Koçer, Nurdan Baykan

Turkish Journal of Electrical Engineering and Computer Sciences

Multimodal medical image fusion approaches have been commonly used to diagnose diseases and involve merging multiple images of different modes to achieve superior image quality and to reduce uncertainty and redundancy in order to increase the clinical applicability. In this paper, we proposed a new medical image fusion algorithm based on a convolutional neural network (CNN) to obtain a weight map for multiscale transform (curvelet/ non-subsampled shearlet transform) domains that enhance the textual and edge property. The aim of the method is achieving the best visualization and highest details in a single fused image without losing spectral and anatomical details. …

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New Normal: Cooperative Paradigm For Covid-19 Timely Detection Andcontainment Using Internet Of Things And Deep Learning, Farooque Hassan Kumbhar, Ali Hassan Syed, Soo Young Shin Jan 2021

New Normal: Cooperative Paradigm For Covid-19 Timely Detection Andcontainment Using Internet Of Things And Deep Learning, Farooque Hassan Kumbhar, Ali Hassan Syed, Soo Young Shin

Turkish Journal of Electrical Engineering and Computer Sciences

The spread of the novel coronavirus (COVID-19) has caused trillions of dollars of damages to the governments and health authorities by affecting the global economies. It is essential to identify, track and trace COVID-19 spread at its earliest detection. Timely action can not only reduce further spread but also help in providing an efficient medical response. Existing schemes rely on volunteer participation, and/or mobile traceability, which leads to delays in containing the spread. There is a need for an autonomous, connected, and centralized paradigm that can identify, trace and inform connected personals. We propose a novel connected Internet of Things …

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A Transfer Learning-Based Deep Learning Approach For Automated Covid-19diagnosis With Audio Data, Devri̇m Akgün, Abdullah Talha Kabakuş, Zehra Karapinar Şentürk, Arafat Şentürk, Enver Küçükkülahli Jan 2021

A Transfer Learning-Based Deep Learning Approach For Automated Covid-19diagnosis With Audio Data, Devri̇m Akgün, Abdullah Talha Kabakuş, Zehra Karapinar Şentürk, Arafat Şentürk, Enver Küçükkülahli

Turkish Journal of Electrical Engineering and Computer Sciences

The COVID-19 pandemic has caused millions of deaths and changed daily life globally. Countries have declared a half or full lockdown to prevent the spread of COVID-19. According to medical doctors, as many people as possible should be tested to identify their status, and corresponding actions then should be taken for COVID-19 positive cases. Despite the clear necessity of these medical tests, many countries are still struggling to acquire them. This fact clearly indicates the necessity of a large-scale, cheap, fast, and accurate alternative prescreening tool that can be used for the diagnosis of COVID-19 while waiting for the medical …

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Deep Hyperparameter Transfer Learning For Diabetic Retinopathy Classification, Mahesh Patil, Satyadhyan Chickerur, Yeshwanth Kumar V S, Vijayalakshmi Bakale, Shantala Giraddi, Vivekanand Roodagi, Yashaswini Kulkarni Jan 2021

Deep Hyperparameter Transfer Learning For Diabetic Retinopathy Classification, Mahesh Patil, Satyadhyan Chickerur, Yeshwanth Kumar V S, Vijayalakshmi Bakale, Shantala Giraddi, Vivekanand Roodagi, Yashaswini Kulkarni

Turkish Journal of Electrical Engineering and Computer Sciences

The detection of diabetic retinopathy (DR) in millions of diabetic patients across the globe is a challenging problem. Diagnosis of retinopathy is a lengthy and tedious process, requiring a medical professional to assess the individual fundus images of a patient's retina. This process can be automated by applying deep learning (DL) technology given a huge dataset. The problems associated with DL are the unavailability of a large dataset and their higher training time. The DL model's best performance is achieved using set of optimal hyperparameters (OHPs) obtained by performing costly iterations of hyperparameter optimization (HPO). These problems can be addressed …

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Detection Of Amyotrophic Lateral Sclerosis Disease By Variational Modedecomposition And Convolution Neural Network Methods From Event-Relatedpotential Signals, Fatma Lati̇foğlu, Firat Orhan Bulucu, Rami̇s İleri̇ Jan 2021

Detection Of Amyotrophic Lateral Sclerosis Disease By Variational Modedecomposition And Convolution Neural Network Methods From Event-Relatedpotential Signals, Fatma Lati̇foğlu, Firat Orhan Bulucu, Rami̇s İleri̇

Turkish Journal of Electrical Engineering and Computer Sciences

Amyotrophic lateral sclerosis (ALS), also known as motor neuron disease, is a neurological disease that occurs as a result of damage to the nerves in the brain and restriction of muscle movements. Electroencephalography (EEG) is the most common method used in brain imaging to study neurological disorders. Diagnosis of neurological disorders such as ALS, Parkinson's, attention deficit hyperactivity disorder is important in biomedical studies. In recent years, deep learning (DL) models have been started to be applied in the literature for the diagnosis of these diseases. In this study, event-related potentials (ERPs) were obtained from EEG signals obtained as a …

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Improved Cell Segmentation Using Deep Learning In Label-Free Optical Microscopyimages, Aydin Ayanzadeh, Özden Yalçin Özuysal, Devri̇m Pesen Okvur, Sevgi̇ Önal, Behçet Uğur Töreyi̇n, Devri̇m Ünay Jan 2021

Improved Cell Segmentation Using Deep Learning In Label-Free Optical Microscopyimages, Aydin Ayanzadeh, Özden Yalçin Özuysal, Devri̇m Pesen Okvur, Sevgi̇ Önal, Behçet Uğur Töreyi̇n, Devri̇m Ünay

Turkish Journal of Electrical Engineering and Computer Sciences

The recently popular deep neural networks (DNNs) have a significant effect on the improvement of segmentation accuracy from various perspectives, including robustness and completeness in comparison to conventional methods. We determined that the naive U-Net has some lacks in specific perspectives and there is high potential for further enhancements on the model. Therefore, we employed some modifications in different folds of the U-Net to overcome this problem. Based on the probable opportunity for improvement, we develop a novel architecture by using an alternative feature extractor in the encoder of U-Net and replacing the plain blocks with residual blocks in the …

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A Case Study: Influence Of Circuit Impedance On The Performance Of Class-E² Resonant Power Converter For Capacitive Wireless Power Transfer, Yashwanth Bezawada, Yucheng Zhang Jan 2021

A Case Study: Influence Of Circuit Impedance On The Performance Of Class-E² Resonant Power Converter For Capacitive Wireless Power Transfer, Yashwanth Bezawada, Yucheng Zhang

Electrical & Computer Engineering Faculty Publications

The evolution of power electronics led to rapid development in wireless charging technology; as a result, a single active switch topology was introduced. The present market utilizes inductive wireless power transfer (IPT); because of the disadvantages of cost, size, and safety concerns, research on wireless power transfer was diverted towards capacitive wireless power transfer (CPT). This paper studies the optimal impedance tracking of the capacitive wireless power transfer system for maximum power transfer. Compared to prior methods developed for maximum power point tracking in power control, this paper proposes a new approach by means of finding impedance characteristics of the …

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Charge Transport, Conductivity And Seebeck Coefficient In Pristine And Tcnq Loaded Preferentially Grown Metal Organic Frameworks, Xin Chen, Kai Zhang, Zeinab Mohammed Hassan, Engelbert Redel, Helmut Baumgart Jan 2021

Charge Transport, Conductivity And Seebeck Coefficient In Pristine And Tcnq Loaded Preferentially Grown Metal Organic Frameworks, Xin Chen, Kai Zhang, Zeinab Mohammed Hassan, Engelbert Redel, Helmut Baumgart

Electrical & Computer Engineering Faculty Publications

This investigation on Metal-Organic Framework (MOF) HUKUST-1 films focuses on comparing the undoped pristine state and with the case of doping by TCNQ infiltration of the MOF pore structure. We have determined the temperature dependent charge transport and p-type conductivity for HKUST-1 films. Furthermore, the electrical conductivity and the current-voltage characteristics have been characterized in detail. Because the most common forms of MOFs, bulk MOF powders, do not lend themselves easily to electrical characterization investigations, here in this study the electrical measurements were performed on dense, compact surface-anchored metal-organic framework (SURMOF) films. These monolithic, well-defined, and (001) preferentially oriented MOF …

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Ultrafast Thermal Modification Of Strong Coupling In An Organic Microcavity, Bin Liu, Vinod M. Menon, Matthew Y. Sfeir Jan 2021

Ultrafast Thermal Modification Of Strong Coupling In An Organic Microcavity, Bin Liu, Vinod M. Menon, Matthew Y. Sfeir

Publications and Research

There is growing interest in using strongly coupled organic microcavities to tune molecular dynamics, including the electronic and vibrational properties of molecules. However, very little attention has been paid to the utility of cavity polaritons as sensors for out-of-equilibrium phenomena, including thermal excitations. Here, we demonstrate that non-resonant infrared excitation of an organic microcavity system induces a transient response in the visible spectral range near the cavity polariton resonances. We show how these optical responses can be understood in terms of ultrafast heating of electrons in the metal cavity mirror, which modifies the effective refractive index and subsequently the strong …

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Theoretical Analysis Of Experimental Data Of Sodium Diffusion In Oxidized Molybdenum Thin Films, Orlando Ayala, Benjamin Belfore, Tasnuva Ashrafee, John Akwari, Grace Rajan, Shankar Karki, Deewakar Poudel, Sylvain Marsillac Jan 2021

Theoretical Analysis Of Experimental Data Of Sodium Diffusion In Oxidized Molybdenum Thin Films, Orlando Ayala, Benjamin Belfore, Tasnuva Ashrafee, John Akwari, Grace Rajan, Shankar Karki, Deewakar Poudel, Sylvain Marsillac

Engineering Technology Faculty Publications

In this work, the diffusion process of sodium (Na) in molybdenum (Mo) thin films while it was deposited on soda lime glass (SLG) was studied. A small amount of oxygen was present in the chamber while the direct-current (DC) magnetron sputtering was used for the deposition. The substrate temperatures were varied to observe its effect. Such molybdenum films, with or without oxidations, are often used in thin film solar cells, either as back contact or as hole transport layers. Secondary ion mass spectrometry (SIMS) was used to quantify the concentration of the species. A grain diffusion mechanistic model incorporating the …

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Cast Iron Drinking Water Pipe Biofilms Support Diverse Microbial Communities Containing Antibiotic Resistance Genes, Metal Resistance Genes, And Class 1 Integrons, Lee K. Kimbell, Emily Lou Lamartina, Anthony D. Kappell, Jingwan Huo, Yin Wang, Ryan J. Newton, Patrick J. Mcnamara Jan 2021

Cast Iron Drinking Water Pipe Biofilms Support Diverse Microbial Communities Containing Antibiotic Resistance Genes, Metal Resistance Genes, And Class 1 Integrons, Lee K. Kimbell, Emily Lou Lamartina, Anthony D. Kappell, Jingwan Huo, Yin Wang, Ryan J. Newton, Patrick J. Mcnamara

Civil and Environmental Engineering Faculty Research and Publications

Antimicrobial resistance is a well-documented public health concern. The role that drinking water distribution pipes have as sources of antibiotic resistance genes (ARGs) is not well known. Metals are a known stressor for antibiotic resistance development, implying that aging metal-pipe infrastructure could be a source of ARGs. The objective of this study was to determine if ARGs, metal resistance genes (MRGs), and intI1 were pervasive across various pipe biofilm sample types (biomass surfaces, pipe surfaces, corrosion tubercles, and under corrosion tubercles) and if the resistance genes associated with particular microbial taxa. Eight sample types in triplicate (n = …

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Calculation Of Real Evapotranspiration By The Application Of Metric Method On Landsat-8 Data, Ali Imanian, Majid Hashemi Tangestani, Adel Asadi, Mohammad Zare Jan 2021

Calculation Of Real Evapotranspiration By The Application Of Metric Method On Landsat-8 Data, Ali Imanian, Majid Hashemi Tangestani, Adel Asadi, Mohammad Zare

Michigan Tech Publications, Part 1

In geological remote sensing approaches for estimating evapotranspiration, METRIC method is among the most modern and precise approaches that many positive experiments have been reported regarding its applicability. In this study, the value of actual evapotranspiration (ET) occurred in Marvdasht farmlands, Fars province, Iran, was calculated instantaneously (hourly) and daily (24 hours), at 24 April 2017 using METRIC method and Lansat-8 data. In order to accuracy assessment of the results, estimated values were compared to the values calculated with Penman Monteith method in places that covers by alfafa crop. Our observations showed that ET values obtained via METRIC model on …

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Learning Adl Daily Routines With Spatiotemporal Neural Networks, Shan Gao, Ah-Hwee Tan, Rossi Setchi Jan 2021

Learning Adl Daily Routines With Spatiotemporal Neural Networks, Shan Gao, Ah-Hwee Tan, Rossi Setchi

Research Collection School Of Computing and Information Systems

The activities of daily living (ADLs) refer to the activities performed by individuals on a daily basis and are the indicators of a person’s habits, lifestyle, and wellbeing. Learning an individual’s ADL daily routines has significant value in the healthcare domain. Specifically, ADL recognition and inter-ADL pattern learning problems have been studied extensively in the past couple of decades. However, discovering the patterns performed in a day and clustering them into ADL daily routines has been a relatively unexplored research area. In this paper, a self-organizing neural network model, called the Spatiotemporal ADL Adaptive Resonance Theory (STADLART), is proposed for …

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A Data-Driven Method For Online Monitoring Tube Wall Thinning Process In Dynamic Noisy Environment, Chen Zhang, Jun Long Lim, Ouyang Liu, Aayush Madan, Yongwei Zhu, Shili Xiang, Kai Wu, Rebecca Yen-Ni Wong, Jiliang Eugene Phua, Karan M. Sabnani, Keng Boon Siah, Wenyu Jiang, Yixin Wang, Emily Jianzhong Hao, Hoi, Steven C. H. Jan 2021

A Data-Driven Method For Online Monitoring Tube Wall Thinning Process In Dynamic Noisy Environment, Chen Zhang, Jun Long Lim, Ouyang Liu, Aayush Madan, Yongwei Zhu, Shili Xiang, Kai Wu, Rebecca Yen-Ni Wong, Jiliang Eugene Phua, Karan M. Sabnani, Keng Boon Siah, Wenyu Jiang, Yixin Wang, Emily Jianzhong Hao, Hoi, Steven C. H.

Research Collection School Of Computing and Information Systems

Tube internal erosion, which corresponds to its wall thinning process, is one of the major safety concerns for tubes. Many sensing technologies have been developed to detect a tube wall thinning process. Among them, fiber Bragg grating (FBG) sensors are the most popular ones due to their precise measurement properties. Most of the current works focus on how to design different types of FBG sensors according to certain physical laws and only test their sensors in controlled laboratory conditions. However, in practice, an industrial system usually suffers from harsh and dynamic environmental conditions, and FBG signals are affected by many …

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Detection Of Subsurface, Nanometer-Scale Crystallographic Defects By Nonlinear Light Scattering And Localization, Farbod Shafiei, Tommaso Orzali, Alexey Vert, Mohammad-Ali Miri, Pui Yee Hung, Man Hoi Wong, Andrea Alù, Gennadi Bersuker, Michael C. Downer Jan 2021

Detection Of Subsurface, Nanometer-Scale Crystallographic Defects By Nonlinear Light Scattering And Localization, Farbod Shafiei, Tommaso Orzali, Alexey Vert, Mohammad-Ali Miri, Pui Yee Hung, Man Hoi Wong, Andrea Alù, Gennadi Bersuker, Michael C. Downer

Publications and Research

Heteroepitaxial crystalline films underlie many electronic and optical technologies but are prone to forming defects at their heterointerfaces. Atomic-scale defects such as threading dislocations that propagate into a film impede the flow of charge carriers and light degrading electrical/optical performance of devices. Diagnosis of subsurface defects traditionally requires time-consuming invasive techniques such as cross-sectional transmission electron microscopy. Using III–V films grown on Si, noninvasive, bench-top diagnosis of subsurface defects have been demonstrated by optical second-harmonic scanning probe microscope. A high-contrast pattern is observed of subwavelength “hot spots” caused by scattering and localization of fundamental light by defect scattering sites. Size …

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Secondary Risk Theory: Validation Of A Novel Model Of Protection Motivation, Christopher L. Cummings, Sonny Rosenthal, Wei Yi Kong Jan 2021

Secondary Risk Theory: Validation Of A Novel Model Of Protection Motivation, Christopher L. Cummings, Sonny Rosenthal, Wei Yi Kong

Research Collection College of Integrative Studies

Protection motivation theory states individuals conduct threat and coping appraisals when deciding how to respond to perceived risks. However, that model does not adequately explain today's risk culture, where engaging in recommended behaviors may create a separate set of real or perceived secondary risks. We argue for and then demonstrate the need for a new model accounting for a secondary threat appraisal, which we call secondary risk theory. In an online experiment, 1,246 participants indicated their intention to take a vaccine after reading about the likelihood and severity of side effects. We manipulated likelihood and severity in a 2 × …

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Position-Scanning Peptide Libraries As Particle Immunogens For Improving Cd8+ T-Cell Responses, Michael C. Vega Jan 2021

Position-Scanning Peptide Libraries As Particle Immunogens For Improving Cd8+ T-Cell Responses, Michael C. Vega

Faculty Articles, Papers, and Other Scholarship

Short peptides reflecting major histocompatibility complex (MHC) class I (MHC-I) epitopes frequently lack sufficient immunogenicity to induce robust antigen (Ag)-specific CD8+ T cell responses. In the current work, it is demonstrated that position-scanning peptide libraries themselves can serve as improved immunogens, inducing Ag-specific CD8+ T cells with greater frequency and function than the wild-type epitope. The approach involves displaying the entire position-scanning library onto immunogenic nanoliposomes. Each library contains the MHC-I epitope with a single randomized position. When a recently identified MHC-I epitope in the glycoprotein gp70 envelope protein of murine leukemia virus (MuLV) is assessed, only one …

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Aviation English Assessment And Training, Robert Fowler, Elizabeth Mathews, Jena Lynch, Jennifer Roberts M.A. Jan 2021

Aviation English Assessment And Training, Robert Fowler, Elizabeth Mathews, Jena Lynch, Jennifer Roberts M.A.

Publications

Due to a significant global increase in demand for air travel, there has been a corresponding increase in demand for ab initio flight training. Thousands of international flight students seek admission to collegiate aviation programs in the United States and Canada every year. These international flight students come to the United States and Canada because flight training is nonexistent in their native countries. In fact, flight training in most of these countries is impossible due to airspace restrictions and onerous regulations. If there is flight training available in these countries, the cost is usually prohibitive compared to the cost in …

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Perovskite Thin Films Annealed In Supercritical Fluids For Efficient Solar Cells, Gilbert Annohene Jan 2021

Perovskite Thin Films Annealed In Supercritical Fluids For Efficient Solar Cells, Gilbert Annohene

Theses and Dissertations

In the field of photovoltaics, scientists and researchers are working fervently to produce a combination of efficient, stable, low cost and scalable devices. Methylammonium lead trihalide perovskite has attracted intense interest due to its high photovoltaic performance, low cost, and ease of manufacture. Their high absorption coefficient, tunable bandgap, low-temperature processing, and abundant elemental constituent provide innumerable advantages over other thin film absorber materials. Since the perovskite film is the most important in the device, morphology, crystallization, compositional and interface engineering have been explored to boost its performance and stability. High temperatures necessary for crystallization of organic-inorganic hybrid perovskite films …

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A Mechanism Behind The Mechanotransduction Of Surface Characteristics In Osteoblasts, Otto J. Juhl Iv Jan 2021

A Mechanism Behind The Mechanotransduction Of Surface Characteristics In Osteoblasts, Otto J. Juhl Iv

Theses and Dissertations

Biomaterials for use in bone regeneration and healing range from metal and metal alloy implants to hydrogel-based solutions. These materials can be optimized to increase bone healing and integration by improving the mechanical and biological properties. Regardless of the material itself, the cell-substrate interaction is key to the success of the biomaterial once implanted. Substrate surface characteristics such as roughness, wettability, and particle density are well-known contributors to a substrate’s overall osteogenic potential, and therefore the substrate's overall success. Unfortunately, it is still unknown how these substrate surface characteristics are transduced into intracellular signals by cells, preventing specific tailoring of …

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Accident Tolerant Fuels Claddings And The Evolution Of Their Surface Characteristics Under Critical Heat Flux, Rajnikant V. Umretiya Jan 2021

Accident Tolerant Fuels Claddings And The Evolution Of Their Surface Characteristics Under Critical Heat Flux, Rajnikant V. Umretiya

Theses and Dissertations

Enhanced Accident Tolerant Fuels (ATFs) systems for light water reactors require higher temperature oxidation resistance in steam environments than the current UO2 – zirconium fuel system. Investigating the ATF materials’ surface properties is needed as they have evidenced to affect the Critical Heat Flux (CHF), which is an important parameter of the thermal-hydraulic performance required to provide safety margins. In this dissertation, the surface properties of FeCrAl alloys (APMT and C26M), Zircaloy-2, Zircaloy-4, and Cr-coating on Zircaloy-4 substrates produced by Physical Vapor Deposition (PVD) and Cold Spray (CS) were investigated according to their chemistry, topography, and wettability. The static …

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