A steepest descent calculation of RNA pseudoknots

We enumerate possible topologies of pseudoknots in single-stranded RNA molecules. We use a steepest-descent approximation in the large N matrix field theory, and a Feynman diagram formalism to describe the resulting pseudoknot structure

The Predictive Power of Teacher Practice in Explaining Student Growth

In recent years, states across the nation have increased their interest to develop specific teacher accountability measures and improve student achievement. On August 6, 2012, the state of New Jersey approved the TEACHNJ Act, which reformed tenure laws and linked student growth to a teacher’s evaluation. The ultimate goal of the TEACHNJ Act is to “raise student achievement by improving instruction through the adoption of evaluations that provide specific feedback to educators” (TEACHNJ Guide). The 2013-14 school year was the first full year of implementation, which included student growth percentile (SGP) scores as one component of a teacher’s evaluation. The purpose of this quantitative study was to examine the relationship between teacher practice and student growth. The study determined the probability that a student will have typical or high growth on the state assessment in relation to their teacher’s practice score based on classroom observations. Some of the essential questions regarding this research are as follows: Are teacher-level variables such as gender, ethnic background, and age significant predictors of student growth? Are school-level variables such as school performance status (Comprehensive schools, Target schools, and NonStatus schools) and percent of student subgroup ethnic composition significant predictors of student growth? How is student growth in language arts and mathematics impacted by a teacher’s effectiveness as measured by the practice score received, when one controls for teacher- and school-level characteristics? To what extent does the relationship between teacher effectiveness and student outcome vary from year two of AchieveNJ to year five of AchieveNJ? The sample population for the 2014-2015 school year will consist of 1132 students (n = 1132) with a valid language arts SGP and 1087 students (n = 1087) with a valid mathematics SGP. The sample population for the 2017-2018 school year consisted of 1484 students (n = 1484) with a valid language arts SGP and 1473 students (n = 1473) with a valid mathematics SGP. The study involved 12 to 14 schools with different grade configurations, performance status, and student ethnic composition. This study was a cross-sectional explanatory design in which logistic and hierarchical logistic regression methods were used to test the relationships between the dependent variable (student growth) and independent variables (teacher characteristics, school characteristics, teacher practice). The design consisted of three separate models used to answer four research questions. A logistic regression analysis will be used to analyze Model 1 (teacher characteristics on student growth) and Model 2 (school characteristics on student growth). In Model 3, a hierarchical logistic regression analysis was used to better interpret the impact of teacher practice and teacher and school characteristics on student growth. Research question four compared and analyzed the significant findings between Model 3 in the 2014-2015 school year and Model 3 in the 2017-2018 school year. This study will provide insight for educational leaders and policymakers on the positive relationship between teacher practice and student growth and recommends that this type of research continue to explore how other variables influence student learning growth based on how teachers deliver instruction

Say Sorry and Save: A Practical Argument for a Greater Role for Apologies in Medical Malpractice Law

This article examines both the potential benefits and detriments of the use of an apology in a legal setting. This article uses the specific environment surrounding a medical malpractice case to help illustrate how and why an apology should or should not be proffered by the Defendant. Ultimately, the reader of this article should have a solid understanding of how an apology can be admissible as evidence in the litigation of a medical malpractice lawsuit

The Predictive Power of Teacher Practice in Explaining Student Growth

In recent years, states across the nation have increased their interest to develop specific teacher accountability measures and improve student achievement. On August 6, 2012, the state of New Jersey approved the TEACHNJ Act, which reformed tenure laws and linked student growth to a teacher’s evaluation. The ultimate goal of the TEACHNJ Act is to “raise student achievement by improving instruction through the adoption of evaluations that provide specific feedback to educators” (TEACHNJ Guide). The 2013-14 school year was the first full year of implementation, which included student growth percentile (SGP) scores as one component of a teacher’s evaluation. The purpose of this quantitative study was to examine the relationship between teacher practice and student growth. The study determined the probability that a student will have typical or high growth on the state assessment in relation to their teacher’s practice score based on classroom observations. Some of the essential questions regarding this research are as follows: Are teacher-level variables such as gender, ethnic background, and age significant predictors of student growth? Are school-level variables such as school performance status (Comprehensive schools, Target schools, and NonStatus schools) and percent of student subgroup ethnic composition significant predictors of student growth? How is student growth in language arts and mathematics impacted by a teacher’s effectiveness as measured by the practice score received, when one controls for teacher- and school-level characteristics? To what extent does the relationship between teacher effectiveness and student outcome vary from year two of AchieveNJ to year five of AchieveNJ? The sample population for the 2014-2015 school year will consist of 1132 students (n = 1132) with a valid language arts SGP and 1087 students (n = 1087) with a valid mathematics SGP. The sample population for the 2017-2018 school year consisted of 1484 students (n = 1484) with a valid language arts SGP and 1473 students (n = 1473) with a valid mathematics SGP. The study involved 12 to 14 schools with different grade configurations, performance status, and student ethnic composition. This study was a cross-sectional explanatory design in which logistic and hierarchical logistic regression methods were used to test the relationships between the dependent variable (student growth) and independent variables (teacher characteristics, school characteristics, teacher practice). The design consisted of three separate models used to answer four research questions. A logistic regression analysis will be used to analyze Model 1 (teacher characteristics on student growth) and Model 2 (school characteristics on student growth). In Model 3, a hierarchical logistic regression analysis was used to better interpret the impact of teacher practice and teacher and school characteristics on student growth. Research question four compared and analyzed the significant findings between Model 3 in the 2014-2015 school year and Model 3 in the 2017-2018 school year. This study will provide insight for educational leaders and policymakers on the positive relationship between teacher practice and student growth and recommends that this type of research continue to explore how other variables influence student learning growth based on how teachers deliver instruction

CHARACTERIZING AND QUANTIFYING MARINE METHANE GAS SEEPS USING ACOUSTIC OBSERVATIONS AND BUBBLE DISSOLUTION MODELS

A method for characterizing and quantifying marine methane gas seeps along the U.S. Western Atlantic Margin was developed and applied to 70 free-gas seeps observed by the R/V Okeanos Explorer in 2012 and 2013, in water depths ranging from 300-2000 meters. Acoustic backscatter from an 18 kHz split-beam echo sounder and a 30 kHz multi-beam echo sounder provided information on the height to which the gas seeps rose from the seafloor. Profiles of the depth-dependent target strength and scattering strength were compared to models of the evolution of rising bubbles to help constrain the ultimate fate of the methane gas. To do so, a refined methodology was developed that decoupled the target strength of a bubble plume from the inherent background noise and reverberation in the ocean. This methodology was particularly useful for acoustically weak (i.e. low signal-to-noise ratio) seeps, and for examining the acoustic trends of seeps as their echo signature approached background noise levels. Comparisons of target strength profiles to models of bubble dissolution demonstrated that the parameters used in the model (e.g. gas transfer rate) are consistent with empirical observations

Investigating vaccine preventable diseases and outbreaks in Australia

Despite having a well-established and successful National Immunisation Program (NIP), vaccine preventable diseases continue to affect communities and result in large outbreaks in Australia. Because of the dynamic nature of vaccine preventable diseases, surveillance and monitoring of epidemiological trends are necessary for informing appropriate policy development and vaccine delivery. In this thesis, I present selected works under the theme of the epidemiology of vaccine preventable diseases which I conducted while placed at the National Centre for Immunisation Research and Surveillance (NCIRS) from March 2012-2014 as a Master of Philosophy Applied Epidemiology (MAE) Scholar. The works presented comprise my MAE requirements, of which a core component is to investigate an outbreak. My first outbreak investigation was a foodborne outbreak of staphylococcal gastroenteritis at an elite athletic event, where fried rice and chicken were suspected as the cause. The remainder of my MAE work related to vaccine preventable diseases and I participated in the public health response to a state-wide outbreak of measles, including a specific investigation to determine the source of infection for a cluster of four cases infected in a paediatric hospital Emergency Department (ED). I developed an algorithm for this contact tracing investigation, although the source of infection was never identified. Measles was also the subject of my applied epidemiological project, where I considered characteristics of measles in the post-elimination era with an emphasis on the role of healthcare setting transmissions in perpetuating outbreaks. In the 2012 outbreak, 16 individuals infected with measles transmitted the illness to 36 others in EDs and General Practice (GP) clinics. In addition, I examined the vaccine effectiveness of the measles vaccine that may allow outbreaks to persist in a setting of high vaccine coverage. I analysed pertussis trends in Australia from 2006-2012, which revealed that the average annual notification rate was more than 2.8 times that of the previous decade with a significant change in the pattern of age-specific incidence. The steepest increases in notification rates were among children less than 10 years, especially those 2-4 years and 6-9 years of age. Reasons for this shift include increased diagnostic testing and more rapid waning of effectiveness post vaccination with acellular vaccines compared to whole cell vaccines used in previous decades. The shift was exacerbated by cessation of the 18 month dose in the National Immunisation Program (NIP) from 2003. Lastly, I evaluated Australia's post-marketing surveillance for intussusception following the introduction of the rotavirus vaccines in 2007. The evaluation found that despite not having planned surveillance, Australian systems evolved to include several surveillance components that were more effective than the nation's passive adverse event following immunisation (AEFI) surveillance system at detecting cases and assessing causality. The work in this thesis contributed to the work of NCIRS and improves our understanding of the epidemiology of vaccine preventable diseases in Australia