28068 research outputs found
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Quantification of Imaging Markers at Different MRI Contrast Weightings, Vasculature, and Across Field Strengths
No full textQuantitative MRI measures physical characteristics of tissue, which creates a set scale with units that allows longitudinal monitoring and cross-patient and cross-center studies. It enables earlier detection of disease, complements biopsy, and provides a clear numeric scale for differentiation of disease states. However, quantitative MRI acquisitions and post-processing are not trivial, which makes it hard to implement the clinical setting. This along with the variability in clinically used acquisitions and post-processing techniques leads to difficulty in establishing reliable, consistent, and accurate quantitative information. There is a critical need for rigorous validation of quantitative imaging biomarkers, both for current and novel quantitative imaging techniques. This dissertation seeks to both validate current quantitative MR imaging techniques and develop new ones in the heart and brain by: 1) examining the data variability and the loss in tag fidelity that occurs when quantitative cardiac tagging is incorrectly run post-Gadolinium injection; 2) quantifying the negative impact of unexpected relaxometric behavior observed in low field MR imaging for low inversion times during T1 mapping; 3) validating retrospectively calculated T1 as a biomarker for Multiple Sclerosis progression; 4) and prototyping an oxygen extraction fraction (OEF) mapping technique for the purpose of stroke prediction and establishment of a numeric scale for tissue health for stroke patients.Assessment of pre-Gadolinium and post-Gadolinium cardiac tag quality showed that post-Gadolinium tags are less saturated (p = 0.012) and have a wider range of saturation, contrast, and sharpness. This results in a loss of information in the late cardiac cycle and impeding quantification of myocardial function.Investigation of 64mT T1 mapping revealed unique relaxometric behavior in that at low inversion times (<250 ms), the signal response curve displayed an increase in signal intensity or a plateau in signal intensity dependent on T1 relaxation time. Inclusion of this increase or plateau in signal intensity negatively impacted T1 fitting algorithms, leading to their failure or incorrectly calculated T1 values. The maximum peak signal intensity before the null point was found to be 210 ms, which impacts current low field T1 mapping protocols which use an initial inversion time of 80-110 ms.Validation of retrospectively calculated T1 as a biomarker in Multiple Sclerosis revealed that T1 of normal appearing brain tissue correlates with measures of Multiple Sclerosis progression (EDSS, BPF, and disease duration) with normal appearing white matter T1 correlating with BPF (r = -0.49, p = 0.0018); putamen T1 correlating with EDSS (r = 0.48, p = 2.40e-03), with BPF (r = 0.69, p = 2.04e-06), and disease duration (r = -0.37; p = 0.02); and globus pallidus T1 correlating with disease duration (r = -0.42; p = 0.0093). Lesion T1 is reflective of MS severity whereas MTR is not.Finally, development of an oxygen extraction fraction (OEF) mapping technique showed that application of independent component analysis (ICA) to cardiac gated spiral-trajectory phase images yielded components that feature stenosis features observed in magnitude images. These ICA components form the basis of OEF mapping from phase images. This dissertation presents four studies that seek to improve either current quantitative MR imaging protocols in the heart, or to develop and validate new quantitative MR imaging techniques in the brain for the purpose of monitoring disease progression or predicting disease
Examination of Listeria monocytogenes survival in refrigerated chopped hard-boiled eggs and deli salads containing this ingredient
No full textPeeled hard-boiled eggs (HBEs) are widely favored by both consumers and food services due to their convenience. These HBEs are often chopped and incorporated into
various dishes such as deli salads. However, recent recalls of hard-boiled eggs have brought
attention to the risk of contamination with Listeria monocytogenes. Prepared HBEs are
typically subjected to antibacterial treatment to maintain product safety and quality. Citric
acid is a common antibacterial used in the food industry to treat the HBEs. Previous
research has determined that 2% citric acid treatment is effective against L. monocytogenes
on whole HBEs. This study examined the efficacy of citric acid on the reduction of L.
monocytogenes on chopped HBEs and in deli salads containing chopped HBEs. HBEs were
treated with 2% citric acid or water (untreated) by submersion for 24 h at 5°C. HBEs were
dried for 10 min, inoculated with a 4-strain cocktail of rifampicin-resistant L.
monocytogenes, at 1 (low-level inoculation) or 4 log CFU/HBE (high level-inoculation),
and allowed to dry for 10 min. Low-level inoculated HBEs were chopped and stored at 5,
10, or 15°C for 28 d. High-level inoculated HBEs were chopped and stored at 5, 10, and
25°C for 14 d. Low-level inoculated HBEs were also chopped and incorporated into potato,
tuna, chicken, or macaroni salad at a 1:6 ratio (HBE to other ingredients), or into egg salad
at a 7:1 ratio. Salads were stored at 5, 10, or 15°C for 28 d. The presence of L.
monocytogenes was determined at intervals during storage by enrichment with BLEB
and/or enumerated on BHIArif throughout storage. Triplicate samples were assessed for
each time point, and three independent trials were conducted. Data was analyzed by
Student’s T-test, ANOVA, and Fisher’s exact test, p≤0.05. For low-level inoculated
chopped HBEs, the L. monocytogenes population was significantly higher in untreated chopped HBEs (1.86±0.33 log CFU/g) as compared to treated chopped HBEs (1.47±0.27
log CFU/g) on day 14 at 15°C. On both untreated and treated chopped HBEs, there was no
significant difference in the population of L. monocytogenes up to 7 d. However, from 14
d, there was a significant increase in the growth of L. monocytogenes (1.86±0.33 to
2.18±0.35 log CFU/g on untreated chopped HBEs and 1.47±0.27 to 1.94±0.47 log CFU/g
for treated, respectively). For high-level inoculated HBEs, a higher L. monocytogenes
growth rate was observed on untreated chopped HBEs as compared to treated chopped
HBEs at 10 and 25°C. It was observed that treated chopped HBEs at 5°C took the longest
to reach 1 log CFU/g increase in the L. monocytogenes population (50 d) whereas,
untreated chopped HBEs at 25°C took the shortest (0.22 d). Untreated chopped HBEs
showed a significantly higher population of L. monocytogenes as compared to treated
chopped HBEs on 14 d at all storage temperatures. In deli salads containing chopped HBEs,
potato salad showed the highest growth of L. monocytogenes after 14 d, followed by
macaroni, egg, chicken, and tuna salad. The population of L. monocytogenes was the lowest
in tuna salad. L. monocytogenes was present throughout the storage period at all storage
temperatures. It was observed that 2% citric acid is more efficient in controlling the growth
of L. monocytogenes in chopped HBEs as compared to when those HBEs are incorporated
into deli salads. The findings contribute to the formulation of preventive measures and
standards aimed at guaranteeing the safety of HBEs
Exploring the role of perceived trustworthiness on leader humility's effectiveness
No full textOver the last decade, several studies have uncovered the value of leader humility; however, these findings fail to consider the contextual factors that may alter when and how humility plays a role. The current study looks to bridge this gap, by exploring how the effectiveness of perceived leader humility on follower outcomes (i.e., state learning goal orientation, feedback seeking behaviors, and employee engagement) is contingent upon follower perceptions of the leader’s trustworthiness. Data was collected from 160 leader-follower dyads across a variety of industries, using a cross-sectional design. Results from the study reinforced earlier findings that leader humility is often associated with positive follower outcomes such as seeking more feedback and reporting a higher learning goal orientation; however, these results were contingent upon how trustworthy they perceived the leader to be. Additionally, the study found evidence that perceptions of leader trustworthiness were related to group-based differences (e.g., age, gender). Together, these findings serve as a reminder that studying leader behaviors in isolation often risks simplifying the complex reality most leader’s face when trying to implement leader behaviors and skills
Agency and Pathway Thinking as Mediators of The Relationship Between Caregiver Burden And Life Satisfaction Among Family Caregivers Of People With Parkinson’s Disease: An Application Of Snyder’s Hope Theory
No full textIn the United States, there are 47.9 million caregivers providing care to family members with disabilities. Those providing care to someone who has Parkinson’s Disease (PD), a complex degenerative movement disorder, may have a unique caregiving experience, given that disease-related factors (e.g. motor and non-motor symptoms) can contribute to worsening caregiver burden and life satisfactions (LS). PD has an increasing incidence of 90,000 new cases per year, likely resulting in an increased need for caregivers. Caregiving research frequently focuses on the mediators between caregiver burden and LS including social support, coping skills, and appraisals. Research that has specifically focused on caregivers of people with PD (Pw/PD) is significantly limited. Hope is a “positive motivational characteristic comprised of agency and pathways thinking that can help facilitate drive towards one’s goal while also serving as a buffer against negative events” (Snyder et al.,1991). The goal of this study is to understand Snyder’s hope theory as it relates to caregiver burden and LS for caregivers of Pw/PD. Specifically, we hypothesized that (a) caregiver burden will be negatively correlated with agency thinking, pathways thinking, and LS among caregivers of Pw/PD. In addition, pathways thinking, and agency thinking will be positively associated with LS, and (b) agency thinking, and pathways thinking will mediate the relationship between caregiver burden and LS among caregivers of Pw/PD. The study sample consisted of 249 caregivers of Pw/PD who completed an online anonymous questionnaire. Correlations between agency and pathways thinking, LS, caregiver burden, and sociodemographic factors were evaluated. A parallel mediation analysis was run to evaluate the mediating roles of pathways and agency thinking in the relationship between caregiver burden and LS. Results indicated that LS was significantly and negatively correlated with caregiver burden. LS was significantly and positively correlated with both pathways and agency thinking. Pathways thinking had no indirect effect on the relationship of caregiver burden on LS. Agency thinking had a negative, indirect effect on the relationship suggesting that agency thinking partially mediated the relationship between caregiver burden and LS. Clinical implications and future directions are discussed
In situ EXAFS studies of novel Palladium-based anode catalysts for direct ethanol and formic acid fuel cells
No full textIn this work we made nanoscale uniform deposition of Pd based anode catalyst on the transition metal Au (with atomic ratio Pd:Au=1:10) support of direct liquid ethanol
fuel cells (DLEFCs) and direct liquid formic acid fuel cells (DLFAFCs). Synthesizing
with uniform dispersion and catalyst nanoparticle dimensions understand the role of Pd
reaction on its support in the direct EOR (ethanol oxidation reaction) and FOR (formic
acid reaction) pathways, we performed in situ Pd K-edge X-ray absorption spectroscopy
measurements as a function of potential using a custom-designed flow cell with the
catalyst deposited on the glassy carbon window. We did in-situ EXAFS to better
understand the reaction mechanism of Pd1@Au10 anode catalyst with EOR and AOR in
nanoscale. Compared EOR with FOR electrochemical performance showed Pd@Au&C
played better in ethanol than HCOOH and more stable which the the current density can
reach up to 1216.25 mA·mg-1 Pd of EOR with Pd1@Au10&C in 1M KOH+1M EtOH
(CH3CH2OH) on the ethanol fuel cells (DLEFCs), and 3.56 times higher of the EOR
current compared with commercial Pd@
Ultrasound Image Guided Robot Arm for Targeted Delivery of Therapeutic Drugs and MicroRNA for Cancer Therapy
No full textMolecular imaging has revolutionized medical diagnostics by providing detailed insights into biological processes at the molecular level within the living subject. Ultrasound Molecular Imaging (USMI) has emerged as a promising diagnostic imaging modality by utilizing targeted contrast agents to unveil crucial molecular information, including vascular biomarkers associated with cancer and other diseases. Despite its potential, the transition of Ultrasound Contrast Agents (UCA) from preclinical evaluation to FDA-approved clinical use faces challenges due to the short in vivo half-life of Micro-Bubbles (MBs), necessitating repeated administrations for comprehensive assessments. Moreover, conventional ultrasound imaging methods suffer from limited scanning areas and single-target focus, leading to low throughput in preclinical evaluations.This thesis addresses these challenges by proposing a robot-assisted whole-body scanning pipeline for preclinical evaluations in Ultrasound Molecular Imaging. By integrating a robotic arm into the imaging setup, this approach enhances scanning flexibility and precision, enabling scans across the entire body of a mouse. This extension of the imaging time window allows for comprehensive assessments without the need for repeated contrast agent administrations. Additionally, the ability to simultaneously scan multiple targets within the same session significantly increases the throughput of preclinical assessments, thereby improving the efficiency and reliability of Ultrasound Molecular Imaging in clinical translation
Improving Localization Safety for Landmark-Based LiDAR Localization System
No full textAutonomous ground robots have gained traction in various commercial applications, with established safety protocols covering subsystem reliability, control algorithm stability, path planning, and localization. This thesis specifically delves into the localizer, a critical component responsible for determining the vehicle’s state (e.g., position and orientation), assessing compliance with localization safety requirements, and proposing methods for enhancing localization safety.Within the robotics domain, diverse localizers are utilized, such as scan-matching techniques like normal distribution transformations (NDT), the iterative closest point (ICP) algorithm,probabilistic maps method, and semantic map-based localization.Notably, NDT stands out as a widely adopted standalone laser localization method, prevalent in autonomous driving software such as Autoware and Apollo platforms.In addition to the mentioned localizers, common state estimators include variants of Kalman Filter, particle filter-based, and factor graph-based estimators. The evaluation of localization performance typically involves quantifying the estimated state variance for these state estimators.While various localizer options exist, this study focuses on those utilizing extended Kalman filters and factor graph methods. Unlike methods like NDT and ICP algorithms, extended Kalman filters and factor graph based approaches guarantee bounding of estimated state uncertainty and have been extensively researched for integrity monitoring.Common variance analysis, employed for sensor readings and state estimators, has limitations, primarily focusing on non-faulted scenarios under nominal conditions. This approach proves impractical for real-world scenarios and falls short for safety-critical applications like autonomous vehicles (AVs).To overcome these limitations, this thesis utilizes a dedicated safety metric: integrity risk. Integrity risk assesses the reliability of a robot’s sensory readings and localization algorithm performance under both faulted and non-faulted conditions. With a proven track record in aviation, integrity risk has recently been applied to robotics applications, particularly for evaluating the safety of lidar localization.Despite the significance of improving localization integrity risk through laser landmark manipulation, this remains an under explored territory. Existing research on robot integrity risk primarily focuses on the vehicles themselves. To comprehensively understand the integrity risk of a lidar-based localization system, as addressed in this thesis, an exploration of lidar measurement faults’ modes is essential, a topic covered in this thesis.The primary contributions of this thesis include: A realistic error estimation method for state estimators in autonomous vehicles navigating using pole-shape lidar landmark maps, along with a compensatory method; A method for quantifying the risk associated with unmapped associations in urban environments, enhancing the realism of values provided by the integrity risk estimator; a novel approach to improve the localization integrity of autonomous vehicles equipped with lidar feature extractors in urban environments through minimal environmental modifications, mitigating the impact of unmapped association faults. Simulation results and experimental results are presented and discussed to illustrate the impact of each method, providing further insights into their contributions to localization safety
Large Language Model Based Machine Learning Techniques for Fake News Detection
No full textWith advanced technology, it’s widely recognized that everyone owns one or more personal devices. Consequently, people are evolving into content creators on social media or the streaming platforms sharing their personal ideas regardless of their education or expertise level. Distinguishing fake news is becoming increasingly crucial. However, the recent research only presents comparisons of detecting fake news between one or more models across different datasets. In this work, we applied Natural Language Processing (NLP) techniques with Naïve Bayes and DistilBERT machine learning method combing and augmenting four datasets. The results show that the balanced accuracy is higher than the average in the recent studies. This suggests that our approach holds for improving fake news detection in the era of widespread content creation
Quantification of Imaging Markers at Different MRI Contrast Weightings, Vasculature, and Across Field Strengths
No full textQuantitative MRI measures physical characteristics of tissue, which creates a set scale with units that allows longitudinal monitoring and cross-patient and cross-center studies. It enables earlier detection of disease, complements biopsy, and provides a clear numeric scale for differentiation of disease states. However, quantitative MRI acquisitions and post-processing are not trivial, which makes it hard to implement the clinical setting. This along with the variability in clinically used acquisitions and post-processing techniques leads to difficulty in establishing reliable, consistent, and accurate quantitative information. There is a critical need for rigorous validation of quantitative imaging biomarkers, both for current and novel quantitative imaging techniques. This dissertation seeks to both validate current quantitative MR imaging techniques and develop new ones in the heart and brain by: 1) examining the data variability and the loss in tag fidelity that occurs when quantitative cardiac tagging is incorrectly run post-Gadolinium injection; 2) quantifying the negative impact of unexpected relaxometric behavior observed in low field MR imaging for low inversion times during T1 mapping; 3) validating retrospectively calculated T1 as a biomarker for Multiple Sclerosis progression; 4) and prototyping an oxygen extraction fraction (OEF) mapping technique for the purpose of stroke prediction and establishment of a numeric scale for tissue health for stroke patients.Assessment of pre-Gadolinium and post-Gadolinium cardiac tag quality showed that post-Gadolinium tags are less saturated (p = 0.012) and have a wider range of saturation, contrast, and sharpness. This results in a loss of information in the late cardiac cycle and impeding quantification of myocardial function.Investigation of 64mT T1 mapping revealed unique relaxometric behavior in that at low inversion times (<250 ms), the signal response curve displayed an increase in signal intensity or a plateau in signal intensity dependent on T1 relaxation time. Inclusion of this increase or plateau in signal intensity negatively impacted T1 fitting algorithms, leading to their failure or incorrectly calculated T1 values. The maximum peak signal intensity before the null point was found to be 210 ms, which impacts current low field T1 mapping protocols which use an initial inversion time of 80-110 ms.Validation of retrospectively calculated T1 as a biomarker in Multiple Sclerosis revealed that T1 of normal appearing brain tissue correlates with measures of Multiple Sclerosis progression (EDSS, BPF, and disease duration) with normal appearing white matter T1 correlating with BPF (r = -0.49, p = 0.0018); putamen T1 correlating with EDSS (r = 0.48, p = 2.40e-03), with BPF (r = 0.69, p = 2.04e-06), and disease duration (r = -0.37; p = 0.02); and globus pallidus T1 correlating with disease duration (r = -0.42; p = 0.0093). Lesion T1 is reflective of MS severity whereas MTR is not.Finally, development of an oxygen extraction fraction (OEF) mapping technique showed that application of independent component analysis (ICA) to cardiac gated spiral-trajectory phase images yielded components that feature stenosis features observed in magnitude images. These ICA components form the basis of OEF mapping from phase images. This dissertation presents four studies that seek to improve either current quantitative MR imaging protocols in the heart, or to develop and validate new quantitative MR imaging techniques in the brain for the purpose of monitoring disease progression or predicting disease
Large-Signal Transient Stability and Control of Inverter-Based Resources
No full textRenewable generation, including solar photovoltaic (PV) systems, type 3 and 4 wind turbine generation systems (WTG), battery energy storage systems (BESS), as well as high voltage direct current (HVDC) and flexible alternating current (FACT) transmission system devices with increasing penetration level are being connected to the bulk power systems (BPS) via power electronic (PE) converters as the interface, referred to as the inverter-based resources (IBRs) on the transmission and sub-transmission levels or distributed energy resources (DERs) located on the distribution level. The IBR is almost entirely defined by the control algorithms and found to be more prone to experiencing large disturbances due to the lack of the conventional synchronous machine (SM) intrinsic synchronous characteristics and mechanical inertia, as well as being in smaller capacity sizes. Thus, these reasons motivate this dissertation to study the large-signal transient stability and control of IBRs for reliable grid integration and rapid grid transformation. For large-signal stability analysis methods, Lyapunov-based methods are the fundamental theory used to characterize the stability issues with analytical solutions, although other non-Lyapunov methods could also be very helpful. A main difficulty hindering the widespread adoption of the Lyapunov stability analysis method is the difficulty of finding the proper Lyapunov function candidate for a higher dimensional nonlinear system. The Port-Hamiltonian (PH) nonlinear control theory is explored in this dissertation as a promising theoretical framework solution addressing this challenging issue. A PH-based tracking and robust control method is proposed to facilitate the practical application of the PH framework in IBR controls. In addition, considering the typical grid-forming (GFM) IBR control with a first-order low pass filter (LPF) block is usually involved with control saturation function for protection purposes under abnormal operating conditions with anti-windup issue in practical implementation, a PH-based bounded LPF (PH-BLPF) control is proposed to incorporate this in the large-signal PH interconnection modeling framework while preserving the robust tracking Lyapunov stability with improved transient dynamic performance and stability margin.Moreover, specific real-world transient synchronization stability issues, such as the grid voltage large fault disturbance case, are studied. In addition, to meet the recent emerging IBR grid code requirements, such as the current magnitude limitation, grid support function, and fault recovery capability of GFM-VSCs, a virtual impedance-based current-limiting GFM control with enhanced transient stability and grid support is proposed