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Analysis Of Multiple Datasets for COVID-19 Prediction: A Machine Learning Approach
No full textSARS-CoV-2, the infectious disease known as COVID-19 resulted in one of the largest pandemics in modern history. Around the world, numerous datasets have been collected to aid researchers in understanding the disease and its epidemiology to allow for quick and efficient diagnosis of COVID-19. This dissertation attempts to investigate some of the datasets and their utility in construction of models for distinguishing COVID-19 from other conditions, such as influenza, based on symptoms. For this purpose, six datasets were investigated. These data sets include the COVID-19 Journal and Screening collected at George Mason University; the daily HealthCheck data that includes self-reported symptoms within the university population; the COVID-CARE Phase I and Phase II datasets which were collected and analyzed through collaboration between George Mason University and Virginia Commonwealth University; and the Case Surveillance Restricted Use Detailed Data from the U.S. Centers for Disease Control and Prevention (CDC) which represents a national database of records of individuals who tested positive for SARS-CoV-2. It is important to note that all of the investigated datasets are very small with the exception of the CDC dataset, Several machine learning methods were applied to the datasets to construct classification models for diagnosing COVID-19 based on symptoms and distinguishing it from other conditions. Temporal representations of data were investigated to see whether inclusion of information when symptoms occur helps in the classification task. The three basic representations include: Flat, in which no time component is added; First Day versus Delayed, in which symptoms present on the first day of illness are examined separately from those that happened later; and Sequential that encodes sequences in which symptoms present in an individual. Several variants of these representations were also studied. This dissertation is concluded by a simulation study that answers a hypothetical question of what could have been done with the data at different times during the pandemic. A week-by-week simulation was performed, and the results were compared
The Barriers to Black Unity: An Examination of the Relationship Between The National Pan-Hellenic Council and the Black Community
Get PDFThe National Pan-Hellenic Council (NPHC) was created to uplift the Black community and create a space in which Black people could thrive and succeed, at the same time the NPHC has been the dividing factor in the Black community. This study aims to explore the possible tensions between the NPHC and the broader Black community. This study begins by delving into the rich history behind the NPHC, Black Unity, and Black identity. The findings from the research present three themes: Clashing Identities, Neither by Any Other Oath, and Rejection. Concluding the research, I delve into a discussion around these themes and what these tensions mean for the Black community. Future research can expand upon the LGBTQ+ community and sorority life, as well as bring in more perspectives from current NPHC members themselves
Rhetoric of the Natural World: Temporal Tensions in Rhetoric After-the-Fact, Intergenerational Rhetoric, and Public Display
No full textThis work is embargoed by the author and will not be publicly available until May 2034.When discussing Climate Change, urban development, sustainable fishing, drought, or any other environmental concern, a rhetor invokes a visual and material sensibility that is inseparable from the medium of the message—the audience is meant to see or sense the bleached coral reefs, heaps of garbage from the ocean, or land ravaged by fire. Additionally, these visual and material appeals expose temporal tensions of environmental arguments—often the kairotic, or most opportune, moment to make an argument about the environment is after damage has already been done. Distressing data, photographs, or video footage are meant to move audiences emotionally and instill a sense of urgency. Persuasive arguments about the environment thus depend on problematic circumstances. Time, then, becomes a central player in environmental activism. This dissertation addresses the role of visual and material objects created by and for the public to make arguments about the natural world through three close analyses. These objects are studied through the lens of “rhetoric after-the-fact,” a term coined in this dissertation to describe a recurring pattern in environmental rhetorics that reflects on the nature of arguments and actions that are delivered too late. The first analysis examines the protest following the removal of sixteen willow oak trees from the George Mason University Fairfax, Virginia campus. Protesters drew images on the stumps to express their discontent after the trees had been removed, effectively voicing their feelings when no change could occur. The second example delves into the sculptures of the dinosaur models created by Benjamin Waterhouse Hawkins in collaboration with Richard Owen for a public display accompanying the Crystal Palace in London in 1854. The third analysis focuses on intergenerational rhetoric about the environment in illustrated children’s books. Each analysis highlights a visual and material argument about the natural world and the temporal tensions inherent in those arguments. Rhetoric after-the-fact immediately points to what has passed, what has been done or destroyed in the environment, while simultaneously directing viewers to the future, urging them to consider what is to come and what must be done about impending environmental disaster.2034-05-1
Prescription Waste Among Hospice Patients
Get PDFThe purpose of this dissertation is to assess Part D prescription waste in hospice patients, in three related studies. This dissertation seeks to characterize Part D prescription waste among linked Surveillance, Epidemiology, and End Results (SEER) Medicare and a random 5% sample of Medicare fee-for-service hospice patients by examining policy intervention impacts, assess the quantity and type of prescription medication at time of death, use a novel methodologies such as random forests to identify factors that influence the likelihood of such prescriptions on hand at time of death, and assess life expectancy as a factor in determining prescription lengths that reduce prescriptions on hand at death. Overview of Hospice and Part D ProgramsHospice was created with the goal of providing medical care that focuses on optimizing quality of life and mitigating suffering among people with terminal illness. For eligible Medicare patients, hospice is covered under the Medicare Part A insurance benefits and includes care for an individual’s terminal illness and related conditions. Hospice uses teams to provide doctor services, nursing care, medical supplies, prescription drugs, therapy (physical, occupational, and speech-language), social worker support, dietary counseling, grief counseling, and short-term inpatient or respite care. Medicare Part D is a voluntary prescription drug benefit provided by private insurance sponsors for a monthly premium. The program aims to make prescription medications more affordable and accessible to Medicare recipients. The benefit covers patient’s prescription drugs in most cases, but there are circumstances where drugs are covered instead under either Medicare Part A or Part B. One exception is when a patient elects hospice, and the prescription drugs related to the care of the terminal illness and conditions are covered under the Medicare Part A benefit. Medications unrelated to the patient’s terminal illness may still be obtained through the Part D benefits. In the past decade, hospice care has prioritized quality while aiming to reduce unnecessary waste. The Center for Medicare and Medicaid Services (CMS) defines waste as practices leading to unnecessary costs for the Medicare program. Since October 2010, CMS has issued several communications to Part D Sponsors and Hospice Providers highlighting the problem of Medicare paying for drugs under Part D that should be covered by hospice Medicare Part A. This inappropriate billing has led to significant costs and waste for the Medicare program. The following reviews the laws, practices, and/or guidelines CMS has published from 2008 to present providing historical context for understanding Part D prescription waste among hospice patients. Years 2008-2013In June 2008, the CMS through the Federal Registrar released the first major revision of Medicare Hospice Conditions of Participation (CoPs) since the Medicare Hospice Benefit was established in 1983. The major revision related to hospice patient’s prescriptions (including Part D medications) included: CFR-Explanation of Revision§ 418.106(e) Added clarification that reiterates the requirement that hospices must provide all drugs and supplies related to a patient’s terminal illness and related conditions and not expect patients to obtain drugs related to the terminal illness and related conditions through Medicare Part D. And that longstanding, preexisting conditions and comorbidities are included in the hospice bundle of services as written in the original implementing regulations of the Medicare hospice benefit. However, if a patient necessitates drugs unrelated to the terminal illness, they may seek coverage through Medicare Part D. CFR-Explanation of Revision § 418.54(c) Clarified the term “unnecessary drugs” as part of the content of the comprehensive assessment and reiterated that all medications should be included in the review in order to develop a plan of care. The ruling went on to clarify that as part of the drug profile review, the assessment should include a patient’s prescription and over-the-counter drugs in use, drug effectiveness, side effects, drug interactions, duplicate therapies, and under or overdosing. Following these changes and clarifications it wasn’t until October 2010 that CMS released a Memorandum entitled Preventing Part D Payment for Hospice Drugs. The memorandum indicated there were concerns that Part D sponsors were paying for drugs that should be the responsibility of the Medicare hospice provider. Guidelines were released directing Part D sponsors to communicate with their network pharmacies to ensure Medicare hospice drugs were not billed to Part D. CMS indicated they would provide best practices for doing so by late 2011. However, following an initial proposal (in February 2011), by April 2011 CMS issued as part of the Announcement of CY 2012 Medicare Advantage Capitation Rates and Medicare Advantage and Part D Payment Policies a section detailing the best practices for “Preventing Part D Payment for Hospice Drugs”. The practices recommended Part D sponsors utilize patient-level transaction reply reports (TRR) they had previously been receiving from CMS. These reports contained patient enrollment information and hospice election information. The best practices detailed how to utilize the included hospice indicators and data to ensure the claims processor is notified of an enrollee’s hospice election and that processes are in place to prevent Part D payment for hospice drugs. Then in June 2012, the Department of Health and Human Service, Office of the Inspect General (DHHS OIG) released a report titled “Medicare Could Be Paying Twice for Prescription Drugs for Hospice Patients” (which examined data from 2009). CMS concurred with two recommendations DHHS OIG made with regard to preventing the Part D benefit paying for medications already covered under the hospice Part A per diem payments. The accepted recommendations included: 1) Educating Part D sponsors, hospices, and pharmacies that it is inappropriate for Medicare Part D to pay for drugs related to hospice patients’ terminal illnesses; and 2) Requiring Part D sponsors to develop controls that prevent Part D from paying for drugs that are already covered under the per diem payments. Following additional TRR report guidance was provided by CMS in April 2013, CMS released a final rule in August 2013 requiring all Part D sponsors to have in place “means” to prevent duplicate payment of hospice medications as well as provided additional clarifications and explanations to sponsors, hospices, and pharmacies. CMS strongly recommended the Part D sponsors use of the TRR reports and have in place controls to prevent the reimbursement for hospice medications. CMS indicated using prior authorizations (PA) for all hospice medications through Part D was best practice but wasn’t required. However, CMS gave specific instruction for sponsors to implement PAs (or other approaches) for four categories of prescription drugs in hospice patients: analgesics, antinauseants, laxatives, and antianxiety drugs. These were identified by the DHHS OIG as typically used to treat the symptoms generally experienced by hospice patients during the end of life. CMS also provided additional guidance and practices for Part D sponsors, hospices, and pharmacies detailing terminal diagnosis and interrelated conditions. CMS reiterated the original intent of the hospice benefit was to have a Medicare benefit available that provided virtually all-inclusive care for terminally ill individuals, provide pain relief and symptom management, and offered the opportunity to die with dignity and comfort in one’s own home rather than in an institutional setting. At the end of 2013 in December, CMS released a memorandum seeking comments on new expectation for stakeholders related to "Part D Payment for Drugs for Beneficiaries Enrolled in Hospice". The memorandum provided a condensed overview of prior regulatory directives pertaining to the eligibility criteria and extent of benefits applicable to Medicare hospice services under Part A. CMS reiterated that patients should only very rarely be taking drugs that are not covered under the hospice per diem. CMS further stated that for prescription drugs to be covered under Part D when the enrollee has elected hospice, the drug must be for treatment of a condition that is completely unrelated to the terminal condition(s) or related conditions. In other words, the drug is unrelated to the terminal prognosis of the individual. In addition, CMS communicated new expectations for Part D sponsors, aimed at preventing duplicate payments for medications covered within the hospice benefit or waived due to the beneficiary’s hospice election. CMS expected for drugs covered under Part D for hospice patients to be extremely rare, the Part D sponsors should place patient-level PA requirements on the following four categories of prescription drugs: analgesics, antinauseants, laxatives, and antianxiety drugs for hospice patients to determine whether the drugs are coverable under Part D. The memorandum also provided guidance to Part D sponsors on making retrospective determinations of payment responsibility for drugs within these categories during the hospice election. The guidance to sponsors was to conduct outreach to the hospice provider to determine whether the drug is for treatment of a completely unrelated condition. CMS stated they expected the hospice provider to coordinate with the plan sponsor regarding these claims and provide the necessary written information, as requested by the sponsor. Years 2014-PresentIn March 2014, CMS issued guidance and established a standard Part D PA form, required for use by Part D sponsors, hospices, and prescribers. The following July, CMS issued a final rule memorandum regarding the “Determination of Payment Responsibility for Drugs for Hospice Patients”. In this final memorandum, CMS provided updates to the March 2014 PA form and explanatory documentation and communicated their expectation for its universal implementation of their guidance by October 1, 2014. In June 2015, the DHHS OIG issued a report titled "Ensuring the Integrity of Medicare Part D", providing a synthesis of investigations, audits, evaluations, and legal guidance related to weaknesses in the Part D program. It again identified highlights the 2012 DHHS OIG report discussing the inappropriate billing of hospice patient’s drugs in 2009 to Part D that should be covered by hospice Medicare Part A. The DHHS OIG followed that report with a March 2016 report titled “Hospices Inappropriately Billed Medicare Over 2 billion annually, in unused prescription medication, is being wasted in Medicare Part A long-term care facilities alone. A 2013 report by Visante found that around 14 million (approximately 1%) of all Part D prescriptions are wasted yearly. The study reported that most of this waste stems from therapy discontinuation, medication switching, dosage adjustments, and death. Regarding waste due to patient mortality, the study unearthed that, on average, patients had 50% of each prescription on hand at the time of their death. Goals of this DissertationThis dissertation seeks to characterize Part D prescription waste among SEER Medicare hospice patients by examining policy intervention impacts, assess the quantity and type of prescription medication at time of death, use a novel methodology such as random forests to identify factors that influence the likelihood of such prescriptions on hand at time of death, and assess life expectancy as a factor in determining prescription lengths that reduce prescriptions on hand at death compared to traditional prescribing methods. This will be accomplished through three related studies in hospice care and prescriptions. The first study will utilize generalized estimating equations (GEE) with negative binomial regression analysis to understand the effects of hospice patient Part D billing policy guidance on linked SEER Medicare data of male hospice patients with prostate cancer and their Part D prescriptions. The second study seeks to examine Part D prescriptions waste in linked SEER Medicare data of hospice patients, with breast; lung; pancreas; prostate; and stomach cancer and identify any predictive characteristics. The methodology for this study consists of calculating the type and amount of medication on hand at time of death and the associated costs by year and then conducting predictive analyses of characteristics that influence Part D prescriptions waste using machine learning techniques. The third study will develop and test rule-based prescription durations for Medicare patients in hospice, with a particular focus on those with a survival of 90 days or less. This work will inform the development of a decision support tool that will describe Part D prescription durations that reduce potential waste related to the amount of prescription medication on hand at death compared to traditional prescribing methods. The methodology will use Random Survival Forest (RSF) calibrated with median trapezoidal rule to develop survival estimates, to simulate clinician predicted survival, which the rule-based prescription durations were applied to. Medication on hand at time of death was calculated and the resulting waste was compared between the rule-based prescription lengths and provider durations. By employing generalized estimating equations, the first study was able to assess the (1) total monthly average prescriptions of all medications and (2) four categories of commonly prescribed hospice medications in pre-and-post policy guidance. This study investigated the effects of guidance issued by CMS on April 4, 2011, targeting providers to prevent the improper billing of prescription drugs for hospice patients’ terminal illness and related conditions to the Part D benefit. Using linked SEER Medicare data for male hospice patients between April 2009 and March 2013, the analysis found that hospice patients’ monthly average total Part D prescriptions decreased from 7.3 pre-policy guidance to 6.5 medications following the issuing of the guidance, while the four categories of hospice-specific medications decreased from 0.57 to 0.49. The findings of this study show that CMS’s guidance issued to providers to prevent the inappropriate billing of hospice patients’ prescriptions to the Part D benefit may lead to decreases in improper billing as observed in this sample. Summary statistics were applied in the second study to examine the type and quantity of Medicare Part D medications on hand at time of death in hospice patients. This analysis utilized a 5% subset of Medicare fee-for-service patient claims and linked SEER Medicare patient claims spanning from January 2015 to December 2019. Results indicated that cardiovascular medications accounted for 25% of prescriptions, followed by central nervous system medications at 20%. The mean prescription length was 36.65 days’ supply with a mean of 62.18 quantity dispensed. Prescriptions resulting in medication on hand at time of death on average were dispensed 72.69 days after a patient’s admission to hospice and resulted in a mean of 20.02 days’ supply and 34.18 quantity wasted. Additionally, the study evaluated the predictive accuracy of four classifiers in forecasting prescription waste at time of death, with Random Forest achieving the highest performance, boasting an area under the curve (AUC) exceeding 93%. Feature importance analysis revealed prescription days’ supply and quantity dispensed as the most influential factors. Even after removing these predictive features, Random Forest still demonstrated a respectable AUC of 73.5%. The study demonstrates that medication on hand at time of death in hospice patients can be predicted and supports additional research should be done to identify ways to reduce the waste. In the final study, rule-based prescription durations were developed and applied to each patient based on their simulated survival days. RSF calibrated with median trapezoidal rule was used to simulate clinician estimated patient survival days. Medication on hand at time of death was then calculated for the rule-based prescriptions and compared to the amount caused by the traditional clinician prescription durations. Two scenarios were conducted that compared the overage for (1) all prescriptions regardless of when the clinician determined prescription ended and (2) prescriptions where a threshold excluded prescriptions where either the clinician or rule-based prescriptions ended more than 3 days before the death date. In the initial scenario, the rule-based prescriptions reduced overage in 28% of cases, leading to a decrease of 29.1% to 36.1% in the amount of prescription medication on hand at the time of death. The second scenario saw similar success with the rule-based prescriptions reducing overage in 32% of cases, leading to a decrease of 32% to 45.5% in the amount of prescription waste. Overall, in this sample the rule-based initial and refill prescription durations were effective in reducing waste. The occurrence of Part D prescription waste in hospice has been well documented by CMS in memorandums and reports. However, few studies exist examining CMS implemented policy impacts to reduce waste, characteristics identification of Part D hospice prescription waste for predicting medication on hand at death, or novel methods to reduce medication waste at the source, i.e., the prescription. Each of these three related studies is significant in that it addresses a gap in hospice care and prescription waste using novel machine learning approaches. The first study is significant in it addresses how government policy guidance has impacted the inappropriate billing of Part D prescriptions in hospice patients. While CMS has documented decreases in billing of Part D prescriptions in hospice patients, no study or analysis exists that definitively ties the decrease and policy together. This study addresses this gap using a GEE with negative binomial regression will address this gap and has the potential to bolster the findings of CMS. The significance of the second study is twofold, as like the first paper, this study also addresses two gaps: 1) the review of Part D prescription waste patterns in hospice patients using individual hospice patient claim records, and 2) in its identification of characteristics that influence the likelihood of Part D prescription waste. Limited research exists in exploring the type, quantity, and costs of medications on hand at tim
Ground-based Light Curve Follow-up Validation observations of TESS object of interest TOI 5372.01
No full text“The purpose of this study is to further investigate TESS Object of Interest (TOI) 5372.01 through a ground based follow up, in order to determine whether it is a genuine exoplanet detection. We hope to validate the object using the transit photometry method in AstroImageJ. Through these methods, though we saw further indication of the existence of a transiting exoplanet, we were not able to fully verify its existence.
Using Species Distribution Models to Identify Refugia for Harlequin Frogs (Atelopus) in Panama
Get PDFThe disease chytridiomycosis, caused by the fungus Batrachochytrium dendrobatidis (Bd), is driving global amphibian decline, and Harlequin frogs in the genus Atelopus are among the most threatened amphibians. There are seven species of Atelopus that are native to Panama, and all are critically endangered or extinct, though five species are present in ex situ captive assurance colonies. Captive breeding is a temporary solution with the goal of reintroduction in the wild, yet Bd is still present in Panama and there are no methods to remove it from the environment. It is hypothesized that species distribution models (SDMs) could be used to identify areas of environmental refugia with low suitability for Bd where amphibians may be able to persist in the presence of the fungus. These locations could support relict amphibian populations or be used for reintroduction efforts. We used SDMs of Atelopus and Bd in Panama to explore this hypothesis and to identify potential areas for reintroduction. We built an SDM of Atelopus habitat suitability using climate data and historic Atelopus locations. We created our own high-resolution remotely sensed environmental dataset of daily meteorological values and used high-quality presence/absence survey data to build new Bd SDMs. We tested various time scales to evaluate how weather prior to testing affected Bd presence and intensity. We found that 15 days prior to sampling, inclusive of sampling date, was the most predictive time scale for Bd suitability. We also found that reasonable Bd SDMs can be built using infection intensity as well as basic presence/absence. We generated daily predictive maps of the probability of Bd occurrence in Panama from 2005-2018 and averaged them by season. Higher Bd suitability tended to be found at higher elevations, a pattern found in previous Bd studies. We created seasonal threshold Bd suitability maps and used a new dataset of relict Atelopus locations to examine the Bd suitability for those sites. For many sites, the models predicted that 1/3 or fewer of the seasons were suitable, suggesting that such sites may be appropriate for reintroduction. However, some relict Atelopus varius sites had very high suitability, indicating that these populations may be persisting with Bd. With this information on relict populations, we presented a methodology using seasonal Bd suitability and probability of Bd occurrence to identify locations in Panama that are mostly unsuitable or trending unsuitable for Bd. These areas may act as refugia that could support relict Atelopus populations or reintroduction efforts
Visual Thinking: A Study of Human-Centered and AI-Based Digital Painting
Get PDFPainting is a mode of expression that entails applying paint or other mediums to a surface, thereby translating a unique understanding of human abstraction and creative expression into visual form. The resulting artwork, whether it portrays realistic or fantastical themes, serves as a tangible manifestation of this process, featuring a complex layering of fundamental painting elements. However, current AI-based digital imaging technologies and commercial digital painting tools fail to fully account for this unique human mental model in their representation, generation, or editing of drawings. These tools process paintings similarly to other image types, such as photographs, at a very basic, pixel-level. Consequently, their outcomes are typically flat and end-to-end, lacking the ability to understand or precisely control a drawing from a higher-order perspective of painting elements (such as strokes, regions, or semantic levels). This level of understanding and control is often crucial for further processing or editing by the user. In this thesis, I aim to elucidate the problem space of digital painting research from the perspectives of Computer Graphics and Human-Computer Interaction. Utilizing a common framework of human understanding, the research is divided into three distinct projects. Firstly, the research began with sketch consolidation, focusing on drawings primarily composed of strokes or lines. I defined a comprehensive target space for the rough sketch cleanup task and developed a benchmark dataset used to evaluate seven state-of-the-art sketch cleanup methods. This analysis uncovered two fundamental sketch attributes and suggested several potential future research directions that align closely with the human drawing mental model. Secondly, building on the insights from the benchmark study, I focused on high-quality sketch vectorization. I established a project that achieves new state-of-the-art vectorization quality, particularly in areas with complex strokes or junctions. I introduced a novel approach to this task by formulating the vector paths extraction problem as implicit surface extraction. This method holds considerable potential for further improvement and could serve as a robust foundation for more advanced painting processing techniques in the future. Lastly, I proposed a drawing automation strategy aimed at identifying stages in the commercial comic drawing workflow that could be highly automated while preserving maximum creative freedom for artists. We developed a system that significantly reduces the artist's workload at the "comic flatting" stage, maintaining professional-level output quality. In conclusion, this thesis demonstrates the significant potential of digital painting research grounded in a human-centric perspective, highlighting its substantial academic and practical value
Reducing Readmission Rates Through Remote Monitoring: A Comprehensive Approach to Managing Heart Failure and Pneumonia
Get PDFThis thesis addresses the significant challenge of high hospital readmission rates in the U.S., with a specific focus on heart failure and pneumonia, and proposes remote monitoring as a viable solution to improve patient outcomes and reduce healthcare costs. Utilizing data from the Centers for Medicare & Medicaid Services, this study delves into the complex factors leading to readmissions, such as care coordination, medication management, and social determinants of health. It argues that remote monitoring—through mobile apps, wearable devices, and teleconsultations—can bridge the care gap post-discharge by allowing for continuous management, early detection of health issues, and greater patient engagement. Despite potential concerns around patient privacy, data security, and equity of access, the research suggests that remote monitoring offers a promising strategy to decrease readmission rates, highlighting the need for future research and policy shifts towards more technology-driven, patient-centric healthcare models
Understanding the Structure and Evolution of Coronal Mass Ejections using STEREO and Exploring their Magnetic Origin
No full textThis dissertation aims to advance our understanding of the structure and evolution of coronal mass ejections (CMEs) using innovative 3-D reconstruction techniques based on stereoscopic views of the Sun from multiple spacecraft distributed in the interplanetary space. Characterizing the CME structure and understanding the CME initiation have improved significantly in the last decade but remain challenging. The study of CMEs is of great importance both scientifically and practically. Originating from the Sun, CMEs are known to be the main driver of severe space weather near the Earth, which could damage the satellites, harm the astronauts, affect the GPS navigation and telecommunications, and even cause power outages. The Sun including transient CMEs has been routinely monitored by multiple instruments from multiple viewpoints in space, i.e., SOHO (since 1996) at the L1 Lagrange point along the Sun-Earth line, and off-the-Sun-Earth-line, STEREO/Ahead, STEREO/Behind (since 2006). The two latest missions, Parker Solar Probe (PSP) (2018) and Solar Orbiter (SolO) (2020) are the first to travel close to the Sun, providing new perspectives on the CME morphology. The main contributions of this dissertation work towards the CME study are (1) successfully developing a semi-automatic 3D reconstruction technique for CME morphology based on the Levenberg-Marquardt least-square minimization algorithm, (2) systematically quantifying the uncertainty of CME morphological parameters for individual CMEs based on observations from one, two and three viewpoints, (3) studying the morphological evolution of CMEs throughout the inner and outer corona with higher accuracy, (4) making improved Time-of-Arrival (ToA) prediction of CMEs arriving at the Earth, thus benefiting space weather prediction. We developed a 3D CME morphology fitting tool using a variety of geometric models, including the well-known Graduated Cylindrical Shell (GCS) model for the CME ejecta, the spheroid model for the CME-driven shock, and the traditional cone-shaped model. The least-square minimization approach, which is based on the existing MPFIT routine, allows a semi-automatic fitting, i.e., removing the need of the human observer’s manual adjustment of model parameters and visual inspection of the model and observations; this approach significantly reduces the subjective bias of human observers. Furthermore, this method, through its calculation of the covariance matrix of the model parameters, provides a robust estimate of the uncertainty of all model parameters. Note that the uncertainties could not be determined by the manual method. The tool is highly scalable and accommodates image data from EUV coronal imagers, coronagraphs, and heliospheric imagers onboard the twin STEREO spacecraft as well as those onboard SOHO. We applied this tool to fit different types of CMEs that were observed as halo, partial halo and limb events from the Earth and investigated the fitting parameters and their uncertainties when one, two and three viewpoints were adopted. Our study revealed the complex relations among the number of viewpoints, the type of CMEs, and the uncertainty of measurements for different model parameters. For example, the CME height and latitude parameters can be accurately measured by a single viewpoint as long as the CME was observed as a limb event but could not be accurately determined when observed as a halo. On the other hand, the parameters that govern the size of the CME need at least two viewpoints for a good fit. We also found that, regardless of the model used to recreate the CME geometry, after the addition of a second viewpoint off the Sun–Earth line, the uncertainties of the geometric parameters drop significantly, while the addition of the third viewpoint adds limited benefits. Our tool was also used to study the evolution of six CMEs from the inner to the outer corona. We tracked the CMEs from around 2 R⊙ to 15 R⊙ using GCS models. Our approach allows us to not only obtain the values of the CME geometric parameters, but also their uncertainties over time. The fits were done using one (each STEREO separately) and two viewpoints (both STEREO combined). All CMEs were observed as limb events from both instruments. Our work provided an accurate determination of the CME sizes and their evolution, including the ejecta radius and its expansion rate. We found that the CMEs undergo a phase of fast overexpansion until around 4 R⊙ and expand in a self-similar way after around 7-8 R⊙. Since our tool provides us with accurate measurements of the CME geometric parameters with specific uncertainties, we use our measurements as input to two different space weather prediction models in order to examine the role of CME measurements in the accuracy of space weather predictions. Currently, space weather prediction models do not use individualized uncertainties of the CME geometric parameters and their selection is only based on statistics. We used both the ENLIL model, the most widely used 3-D magnetohydrodynamic model for operational space weather prediction, and also an empirical model for this study. For the ENLIL model, we did not achieve great agreement between the predicted and actual ToAs for all three CMEs, indicating the prediction error is mostly due to the selection of the background solar wind speed, CME density or shape, i.e., the free parameters in the ENLIL models. When using the empirical model, we found we can achieve good results; One of the CMEs studied was well-observed by both STEREO and the difference between the actual and predicted ToA was only 15.6 minutes after the second viewpoint was added. We also report that we have good results even when only one viewpoint is used as long as the CME front is well-tracked at higher heights. These results indicate that our tool is robust and provides accurate fits. We also modified our technique so that it can use data from the Wide-Field Imager (WISPR) onboard Parker Solar Probe (PSP). PSP is the first mission to travel very close to the Sun. It provides a better view of the CME morphology, especially its internal structure thanks to the proximity of the spacecraft to the Sun. We fitted three CMEs observed by PSP/WISPR and SOHO/C3 and although more testing and validation is required, the results seems promising. In short, this dissertation work has developed an efficient, robust and less-biased semi-automatic CME morphology fitting tool, and we applied the tool to advance our understanding of the CME evolution and improve space weather prediction. In the near future, we plan to extend our work to data from the Solar Orbiter Heliospheric Imager (SoloHI) onboard Solar Orbiter (SolO), which, like WISPR provides a better view of the CME internal structure. Further, we will study the structure and evolution of the magnetic fields along the polarity inversion lines (PILs) of solar active regions using ground-based data from the 4-meter Daniel K. Inouye Solar Telescope (DKIST). We submitted a successful observations proposal and received data from DKIST, but the study was delayed due to data recalibrations
COMPUTATIONAL ANALYSIS OF T-LYMPHOCYTE ACTIVATION BY PEPTIDE ANTIGEN
Get PDFThe major histocompatibility complex (MHC) molecules are critical to the immune response because they recognize and differentiate between foreign antigens and host proteins. MHC Class I, found on the surface of most human cells and MHC Class II are found on antigen presenting cells which are a type of phagocyte MHC Class I, is restricted to macrophages and lymphocytes. MHC molecules play an important role in the demonstration of foreign antigens and play an important role the activation of T cells and are therefore a significant mechanism of adaptive immunity. Antigen Present Cells (APCs) do not present all likely epitopes to T cells but instead focus on only a range of the foremost antigenic or immunodominant epitopes. The idea behind this research work is to calculate physicochemical and structural properties of antigenic epitopes and to simulate receptor of MHC-II and antigenic peptides to understand the binding mechanism and their biological response in developing the vaccine. Replica exchange molecular dynamics (REMD) simulations produced conformational ensembles of protein structure of the epitope in immunogenic and non-immunogenic response. Obtained simulations output were inspected by machine learning approach based in MDPPM methods. Machine learning empowers a set of rules to examine further bundles of information by rapidly outcome key ingredients that distinct each variable for molecular dynamics as of the absolute volume of data produced during apiece simulation. Finally, using VMD dihedral angles of the protein backbone are to be retrieved for the different conformational change with the trajectories is analyzed different dynamics in the prediction model. The complete mean structural discoveries by taking raw torsional angles values and their trajectories have been classified with regards to antigenicity using MDPPM. This approach is advantageous for enumerating minor changes in the protein with respect to other methods and may have error. From the cluster we learn how global structural changes and the phi-psi backbone and other simulation data within the protein on the principal component data to evaluate immunogenic/ non-immunogenic response and accuracy