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How do nuclear isomers influence the gamma-ray bursts in binary neutron star mergers?
Get PDFNeutron star mergers are astrophysical “gold mines,” synthesizing over half of the elements heavier than iron through rapid neutron capture nucleosynthesis. The observation of the binary neutron star merger GW170817, detected both in gravitational waves and electromagnetic radiation, marked a breakthrough. One electromagnetic component of this event, the gamma ray burst GRB 170817A, has an unresolved aspect: the characteristics of its prompt gamma-ray emission spectrum. In this work, we investigate that gamma-ray spectra in such GRBs may be influenced by de-excitations from isomeric transitions. Our study begins with a review of current knowledge on GRB structure and of r-process nucleosynthesis in neutron star collisions, focusing on the role of nuclear isomers in these settings. We then test our hypothesis by developing criteria to select representative isomers, based on known solar element abundances, for modeling GRB spectral characteristics. We integrate these criteria into an interactive web page, facilitating the construction and analysis of relevant gamma-ray spectra from isomeric transitions. Our analysis reveals that three isomers—90Zr, 207Pb, and 89Y—stand out for their potential to impact the prompt GRB spectrum due to their specific properties. This information allows us to incorporate nuclear isomer data into astrophysical simulations and calculate isomeric abundances generated by astrophysical r-processes in neutron star mergers and their imprint on the detected signal
Compassion fatigue in school principals as a contributing factor to school principal burnout
Get PDFIn recent years, within the United States and globally, workforce members who directly and tangentially treat and serve traumatized individuals have begun to experience an additional occupational hazard in the form of compassion fatigue.
Consistent school leadership can be a critical factor in increased student achievement and school-based performance outcomes. However, the principalship has become more physically and emotionally taxing due to increasing demands, duties, and expectations. Principal burnout has become a critical factor that has escalated principal turnover, often destabilizing a school community (Buckman, 2021). While many individual and organizational factors contribute to principal burnout but remain relatively unexamined, the purpose of this phenomenological study will be to analyze the factors that contribute to compassion fatigue as a contributing factor leading to burnout among principals in several districts on the East and West Coasts of the United States. Findings highlight the impact of compassion fatigue, potential principal attrition, and coping strategies, mechanisms, and resources to address compassion fatigue and principal burnout and attrition.
The researcher utilized non-experimental semi-structured interviews from a randomly selected sample of school principals in varied school districts within six states in the United States. The research data and study results are designed to support recommendations to local education agencies (LEAs) regarding the need to provide resources, counseling, and training to address, prevent, and overcome the negative emotional impact of the abovementioned phenomenon
Occupancy of the Little Grass Frog (Pseudacris ocularis), an overlooked longleaf endemic, in a managed landscape
Get PDFAmphibians are declining globally, with many declines associated with habitat loss. The longleaf pine (Pinus palustris) ecosystem historically covered most of the southeastern United States and supports a host of endemic amphibians. This ecosystem has declined by over 97% in the last two hundred years and many associated species have declined with it. The Little Grass Frog (Pseudacris ocularis) is a longleaf pine endemic anuran that has been understudied and under-surveyed; almost no information is known on the ecology of this species and no population studies have been conducted. My goals were to create an acoustic recognizer to detect Little Grass Frog calls, better understand the calling phenology of the species, and examine how historical land use and contemporary vegetation structure influence its occupancy. I used ARUs to collect anuran chorus data from wetlands in the South Carolina Coastal Plain. I conducted vegetation surveys in study wetland basins and terrestrial buffers to quantify the contemporary vegetation structure of each. I used historical aerial imagery and ground-truthing to establish historical land use occupancy covariates. In Chapter 1, I used two automated signal detection software to create three acoustic recognizers and their efficacy in detecting LGF calls. I used the best-performing recognizer, made in Raven Pro, to analyze acoustic data from 13 wetlands. I used LGF call detections from the recognizer output to establish occupancy in a single-season occupancy modeling framework. I used human-annotated test data to compare each recognizer\u27s accuracy, precision, and recall. The top-performing recognizer was applied to data collected with autonomous recording units to establish occupancy for Chapter 2. In Chapter 2, I used LGF call detections and single-season occupancy models to evaluate what factors influenced the detection probability and occupancy of Little Grass Frogs in the southern coastal plain of South Carolina. I created a recognizer in Raven Pro 1.6.4 (Cornell Lab of Ornithology, Ithica, N.Y.) that had high precision and was applied to audio files collected across 13 wetlands to establish occupancy. Calling detection was significantly higher when mean daily temperatures were higher, though the Little Grass Frog called throughout the year. Occupancy was associated with the prevalence of fire-dependent species in wetland buffer basal areas, suggesting that the LGF is sensitive to habitat disturbances in wetland buffers. These results confirm that Little Grass Frogs select terrestrial habitats similarly to other longleaf pine endemic species and should be managed similarly. Additionally, the results of this study indicate that the Little Grass Frog may be at higher risk of decline than previously expected, given their reliance on the longleaf pine ecosystem structure and warm breeding conditions in rainfed pools that will be impacted by increasing droughts in the face of climate change
Assessment of prestressed concrete beams: advancing non-destructive testing methods for enhanced bridge evaluation
Get PDFThe validity of non-destructive methods for evaluating transportation infrastructure conditions was explored in this study. The overarching objective is to assist in developing ideal protocols for bridge inspectors to determine the condition of reinforced concrete infrastructures and the remaining service life. A meticulous evaluation of a prestressed concrete beam decommissioned from a bridge listed in the West Virginia Division of Highways inventory was completed. The evaluation included determining the sizes, spacings, and location of reinforcement steel bars and prestressing tendons. The effort included generating a new computer code to automate the data post-processing, allowing for the automated identification of the location of reinforcement steel bars. The study was divided into four stages. A breakthrough ground-penetrating radar (GPR) technology was used in the first stage to evaluate and determine the overall reinforcement layout in the prestressed concrete beam. A novel approach to determine rebar diameter of reinforced concrete structures is introduced. The second stage focused on analyzing the effect of GPR scan offsets in identifying internal flaws and calculating the reinforcement depth, spacing, and concrete cover. The feasibility of automating the evaluation process by generating and employing a novel computer code was examined. Lastly, specific reinforced concrete slab areas were selected and the latest ultrasonic testing technology was employed to determine the rebar depth and diameter using a novel approach. This project assists in redefining concrete bridge evaluation procedures by providing precise information for reinforcement steel bars and prestressing tendons sizes, spacing, concrete cover, and other internal findings. The study outcomes shall assist state and federal agencies manage their transportation assets by allocating financial resources for bridge maintenance and rehabilitation
Thymidine phosphorylase is a promising target in SARS-CoV-2 spike protein-enhanced thrombosis
Get PDFThrombosis, as an underlying mechanism in cardiovascular diseases, is the leading global cause of death in the 21st century. Infection is a risk factor for thrombosis, and the coronavirus disease 2019 (COVID-19) pandemic has led to a rise in the incidence of thrombosis, thereby increasing mortality. In comparison to previous severe coronavirus outbreaks, rates of thrombosis in COVID-19 have been unprecedented. COVID-19 is caused by the novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The SARS-CoV-2 spike protein (SP), the key used to enter host cells, is implicated in thrombosis pathology, though mechanisms are not fully understood. The SARS-CoV-2 SP may also be involved in vaccine-induced immune thrombotic thrombocytopenia (VITT), a reaction to COVID-19 vaccination where deadly thromboses materialize. Discovering mechanism-based therapies for life-threatening diseases is paramount in minimizing off-target effects and maximizing positive responses to treatment. Thymidine phosphorylase (TYMP), a pyrimidine salvage pathway enzyme with novel prothrombotic function, has been identified by our lab as a target in COVID-19-associated thrombosis. This dissertation investigates SARS-CoV-2 SP-associated thrombosis using animal models, human tissue, blood studies, cell culture, and in-silico modeling, and shows the effectiveness of targeting TYMP to attenuate SP-promoted thrombosis. This dissertation aims to address knowledge gaps concerning the mechanistic impact of SP on thrombosis, establish a foundation for targeting TYMP as a potential therapeutic avenue, and unveil a novel interaction between SP and platelet factor 4 (PF4), which may bear implications for COVID-19-associated thrombosis and/or VITT
AI and its use in cancer treatment
Get PDFIntroduction: The introduction of Artificial Intelligence (AI) in the healthcare setting has promoted benefits in cancer treatment for many forms of cancer, especially breast cancer. This additional measure has brought a second set of eyes to medical images involving cancer diagnosis and treatment. Being regulated by the Food and Drug Administration, facilities utilize these tools increasingly. There is concern as to if the accuracy truly benefits the patient and if radiologists are solely relying on these additional methods.
Purpose of the Study: The purpose of this study was to analyze the use of AI in early breast cancer detection for patients in the U.S. and how it impacted patient mortality rates, the cost of treatment, and the duration of treatment.
Methodology: This study was a literature review. Three databases were used to collect a total of 62 sources. These sources were analyzed thoroughly and reduced to 30 sources that were fully utilized in the research writing. Of the sources utilized, 20 were used within the results section.
Results: The research showed quality measures such as breast cancer detection, differentiate between benign and malignant, survival rates, and cost effectiveness. An overall increase in sensitivity and accuracy were proven with the additional use of AI than readings without the utilization of this tool. Radiologist that used AI in comparison than using two radiologists, also increased the specificity of the reading report. False negative rates were decreased with the assistance of AI-assisted surgery.
Discussion/Conclusion: Cost effectiveness and overall improvement on the diagnostic imaging reports were increased with the utilization of AI assistance. Improving reading reports, along with the speed of results can decrease mortality rate. The findings were inconclusive as to whether there was a decrease in total treatment duration, due to an earlier detection rate. Farther patient data collection would need to have been collected to obtain this information