Data augmentation based methods for estimating the parameters of the Feller-Pareto Distribution: Theory and applications

In income and wealth data modeling Pareto distribution and its several variants play an important role. Both univariate and multivariate variations of this model have been extensively used as a suitable model for various non-negative socio-economic variables, for pertinent details, see Arnold (2015). In this article, weconsider the most general Feller-Pareto (FP, in short) distribution, which subsumes all four types of Pareto distributions and show that it can be represented as a mixture of a conditional generalized gamma and an unconditional gamma distribution. Using this strategy, we consider a data augmentation based method (under the envelope of Bayesian paradigm) to estimate the parameters of the FP distribution. This mixture representation allows us to easily derive conditional Jeffery’s type non informative priors. For illustrative purposes, one data set is considered to exhibit the utility of the proposed method

Reveal Technologies: A Case Of Key Differences Between U.S. GAAP & IFRS And The Impact On Financial Performance Evaluation

This case gives students the opportunity to apply their knowledge of the differences between U.S. Generally Accepted Accounting Principles (GAAP) and International Financial Reporting Standards (IFRS) by making a series of adjustments to a company's U.S. GAAP basis account balances to reflect IFRS. Students then construct IFRS-based financial statements and compare financial performance measures for the company. Finally, students consider the effects of the different standards as a means of evaluating which gives more insight into the company's financial condition

Weight training practices and perspectives among cadet women at a senior military college

Weight training (WT) has been consistently shown to improve muscular ability among women, better preparing them to meet the demands of modern military service and overcome certain physiological challenges. Unfortunately, current training methods do not prioritize WT in most military populations, and women typically participate in WT at rates 20-30% lower than their male peers. The purpose of this study was to identify factors that influence WT participation among cadet women enrolled at a senior military college (SMC) to inform future programming, curriculum, facilities, or policies. First, a survey was administered to cadet women (n = 92) to characterize their WT participation and perceptions. Then, cadet women (n = 11) were interviewed to explore their perspectives on barriers, facilitators, and strategies for participation. Although WT is not often featured in twice per week institute-led physical training, 77% of cadet women reported participating in WT at least 2 days/wk and 49% reported = 3 days/wk. Athletes and women who planned to pursue military service after graduation reported higher rates of WT. Analysis of the interviews illuminated three themes: building reputation, “it’s on multiple fronts,” and “having to adapt.” WT was valued to support military readiness and build reputation in a male-dominated sphere emphasizing physicality. Cadet women’s perceived competence and strength were tied to reputation concerns. Time and space constraints included high academic course loads and extracurricular responsibilities associated with SMCs, coupled with limited facilities and equipment. Based on the views of cadet women in this study and low reported enrollment of women in current WT offerings, it is recommended that the institution provide additional educational resources and opportunities (e.g., workshops or women-only courses) as early as possible in a cadetship

School engagement and Interpersonal–Psychological Theory of Suicide: Identity groups differences

The Interpersonal–Psychological Theory of Suicide (IPTS) is a framework for understanding suicidality, yet there is little connection of IPTS to school environment, or exploration of this model within various populations. In this article, we conduct a cross-sectional assessment in a high school to understand the relationships between student engagement, IPTS, and suicidal behavior, to provide guidance for counseling professionals to target prevention and intervention efforts to increase effectiveness. A total of 1081 high school students participated in the current study. While perceived burdensomeness was found to moderate the relationship of some aspects of student engagement to suicidal behavior, nuances existed in risk factors to suicidal behavior for various identity groups within the school. Findings have implications for prevention and intervention efforts that would be most effective for students with diverse backgrounds

Student Perspectives On Chemistry Support Course, Success, and Barriers

There is a student success gap for underrepresented, first-generation, and transfer students shown in their increased DFW rates for General Chemistry 1. However, they demonstrate higher levels of resilience in continuing through a chemistry degree path, suggesting the first General Chemistry course is the barrier. A co-requisite support course (BASE) designed to reduce barriers in these categories by Building Student Assurance, Security, and Engagement is one solution to increase student success in General Chemistry. Appalachian State University began offering a one-hour support course in Fall 2021 to increase success in the first semester of General Chemistry. The course offers support with both chemistry material and success skills through activities designed to increase student skills and involvement. Data collected over five semesters shows the % DFW rates of students enrolled in the support course (34.4%) are similar to all students in the first-semester General Chemistry course (35.4%). However, the % DFW rates are lower than the historical rates for students in underrepresented groups, which indicates the support course may increase student success. Current research examines the student perspective to understand how the support course prompts student growth with data collection in both the Fall 2023 and Spring 2024 semesters

Improving Education Provided to Patients on the Interaction of Sugammadex and Hormonal

Background: Sugammadex is a medication used to rapidly reverse the effects of rocuronium and vecuronium by encapsulating and physiologically inactivating it. Although sugammadex has a high affinity for rocuronium and vecuronium, it can also encapsulate progesterone and estrogen, thereby decreasing the effectiveness of progesterone hormonal contraceptives and increasing the risk of unintended pregnancy. It is recommended that patients on hormonal contraceptives use a non-hormonal birth control backup method for seven days after receiving sugammadex. Approximately 65% of women of reproductive age in the United States are currently using some form of hormonal contraception (CDC, 2020). The percentage of ambulatory surgical cases specifically performed on women also increased by 1.1% between the years 2000 and 2014 (CDC, 202). This increase in the utilization of sugammadex and increase in female surgical cases suggests that the number of patients affected by this medication interaction will likely continue to increase. Patients on hormonal contraceptives who receive sugammadex perioperatively are provided education on this interaction, however, this education is routinely provided postoperatively, following the administration of anesthesia. Following anesthesia, a patient’s memory may be impaired, and they may not remember the instructions provided. Providing patient education preoperatively improves patient recall. Purpose: The purpose of this quality improvement project was to improve patient?recall of provided education on the interaction of sugammadex and hormonal contraceptives by having anesthesia providers provide this education prior to the administration of anesthetic medications. Methods: Patients using hormonal contraceptives that were anticipated to receive sugammadex perioperatively were provided patient education by an anesthesia provider preoperatively in addition to routine postoperative instructions provided by the nursing staff. Patients on hormonal contraceptives that received sugammadex were contacted postoperatively by phone to assess their recall of provided education. Results: Thirty-three percent of patients receiving postoperative instructions only on the interaction of sugammadex and hormonal contraceptives were able to recall receiving that education. In patients also provided this education preoperatively, 23% were able to recall receiving that education. Recommendations and Conclusion: Patient education provided preoperatively by the anesthesia provider did not improve patient recall of receiving this education. Further study is recommended to determine the best method(s) of educating patients on the implications of the interaction between sugammadex and hormonal contraceptives

Interventions to Increase Osteoporosis Screening in Patients with Seizure Disorder on Antiepileptic Medications

People with epilepsy (PWE) are at above-average risk for fracture due to the biochemical bone changes that result from the use of antiepileptic drugs (AEDs). Osteoporotic fractures can lead to considerable morbidity and mortality while simultaneously having negative effects on healthcare cost. There is no recommended routine screening for osteoporosis in people who are at high risk for osteoporotic fractures for other reasons except being female and post-menopausal

Utilizing biometric mouthguards to detect mild traumatic brain injuries in American football: Investigating the correlation between brain strain and cognitive function to enhance player safety

Traumatic Brain Injuries (TBIs) are a persistent concern in American football, posing significant risks to players' long-term health and cognitive function. This thesis explores the intricate dynamics of TBIs in football, with a focus on leveraging instrumented mouthguards (iMGs) and brain strain modeling to enhance player safety. The study builds upon the evolving literature by integrating wearable sensors to gather data on head impacts, facilitating the modeling of brain kinematics and assessment of injury potential. Through the utilization of iMGs and cognitive function tests, the research aims to provide a holistic framework for evaluating and mitigating TBIs. Data collected from the 2023 Western Carolina University Football season revealed the effectiveness of iMG brain modeling in forecasting associated cognitive impairments, particularly when axonal damage is focused in the ventricles and cerebellum. Strain in these regions were found to have roughly a 52% to 57% greater prediction percentage than the other regions. Additionally, the study identified a linear acceleration value of 30Gs as indicative of mild TBIs, even in the absence of noticeable symptoms. The findings underscore the capability of iMGs to detect and quantify axonal damage from TBIs, offering valuable insights for coaches, trainers, and medical professionals to mitigate these injuries in American football. While the study marks significant progress in linking iMG data to cognitive function across various brain regions, further research is warranted to expand participant quantity and refine cognitive testing methodologies. Nevertheless, this thesis contributes to advancing instrumented mouthguard technology, cognitive function testing, and brain modeling, paving the way for continued exploration and advancements in TBI detection and prevention strategie

Utilizing the Constrained K-Means Algorithm and Pre-Class GitHub Contribution Statistics for Forming Student Teams

In modern software engineering education, team formation is crucial for mimicking real-world collaborative scenarios and boosting project-based learning outcomes. This paper introduces a simple, innovative, and universally adaptable method for forming student teams within a software engineering class. We utilize publicly available pre-class GitHub metrics as our input variables (e.g., number of commits, pull requests, code size, etc.). For team formation, the constrained k-means algorithm is employed. This algorithm embracesdomain-specific constraints, ensuring the resulting teams not only resonate with the inherent data clusters but also meet educational requirements. Preliminary results suggest that our methodology yields teams with a harmonious blend of skills, experiences, and collaborative potentials, thereby setting the stage for enhanced project success and enriched learning experiences. Quantitative analyses show that teams formed via our approach outperform both randomly assembled teams and student self-selected teams concerning project grades. Moreover, teams created using our method also display a reduced standard deviation in grades, suggesting a more consistent performance across the board

Development of an explicit bias scale for law enforcement

This study investigated the development and utility of the Explicit Bias Scale for Law Enforcement Officers (EBLEO), designed to measure and quantify explicit racial bias in public safety members as part of a pre-employment battery. This measure was derived largely derived from the Symbolic Racism Scale (Henry and Sears, 2002) and featured new questions, restructured content based on research into the intersection of criminal justice and explicit racial bias, and expanded content drawn from other areas of racial prejudice or discriminatory attitudes such as Intercultural Sensitivity. In this study, the EBLEO was subjected to item level scrutiny and broad measures of internal consistency and performance based on data collected from three separate samples (N = 135). The measure was then compared to the original Symbolic Racism Scale, along with secondary yet related measures and constructs such as Social Dominance, Dark Triad personality traits, Five Factor Model (FFM) personality traits, and Social Desirability. The EBLEO rendered an overall Cronbach’s alpha of .942 and correlated highly with the Symbolic Racism scale. Hierarchical regression identified social dominance, conservative political orientation, the FFM trait of openness to experience, and social desirability as key predictors in the model. Exploratory factor analysis rendered a six-factor model that accounted for roughly 60% of the variance, with the first two factors being the largest. Results and relevance to the study of explicit racial bias and how this relates to law enforcement pre-employment screenings are discussed