Defined Benefit versus Defined Contribution Pension Plans: What are the Real Tradeoffs?

Defined Benefit and Defined Contribution plans have significantly different characteristics with respect to the risks faced by employers and employees, the sensitivity of benefits to inflation, the flexibility of funding, and the importance of governmental supervision. In this paper, we examine some of the main tradeoffs involved in the choice between DB and DC plans. Our most general conclusion is that neither plan type can be said to wholly dominate the other from the perspective of employee welfare.The major advantage of DB plans is the potential they offer to provide a stable replacement rate of final income to workers. If the replacement rate is the relevant variable for worker retirement utility, then DB plans offer some degree of insurance against real wage risk. Of course, protection offered to workers is risk borne by the firm. As real wages change, funding rates must correspondingly adjust. However, to the extent that real wage risk is largely diversifiable to employers, and nondiversifiable to employees, the replacement rate stability should be viewed as an advantage of DB plans. The advantages of DC plans are most apparent during periods of inflation uncertainty. These are: the predictability of the value of pension wealth, the ability to invest in inflation-hedged portfolios rather than nominal DB annuities,and the fully-funded nature of the DC plan. Finally, the DC plan has the advantage that workers can more easily determine the true present value of the pension benefit they earn in any year, although they may have more incertainty about future pension-benefit flows at retirement. Measuring the present value of accruing defined benefits is difficult at best and imposes severe informational requirements on workers. Such difficulties could lead workers to misvalue their total compensation, and result in misinformed behavior.

Tracking Fecal Pollution Sources in the Upper Reaches of the Horse Creek Watershed in Aiken County, SC

The Horse Creek watershed in Aiken County, SC, is known for its history of high coliform pollution. Previous studies have identified one particular tributary, Sand River, as being a major contributor to the upper portions of the watershed, but the source(s) remain unknown. Sand River drains Hitchcock Woods, an urban forest that is heavily used by equestrians; is transected by both old and new sewer lines; and is surrounded by older homes, some of which depend upon aging septic systems. In addition, Sand River in Hitchcock Woods receives an enormous volume of stormflow from the downtown area during rain events. This study focused on fecal pollution in two of Sand River’s smaller tributaries, Calico Creek and Cuthbert Branch

Quantifying Nearshore Sea Turtle Densities: Applications of Unmanned Aerial Systems for Population Assessments

Although sea turtles face significant pressure from human activities, some populations are recovering due to conservation programs, bans on the trade of turtle products, and reductions in bycatch. While these trends are encouraging, the status of many populations remains unknown and scientific monitoring is needed to inform conservation and management decisions. To address these gaps, this study presents methods for using unmanned aerial systems (UAS) to conduct population assessments. Using a fixed-wing UAS and a modified strip-transect method, we conducted aerial surveys along a three-kilometer track line at Ostional, Costa Rica during a mass-nesting event of olive ridley turtles (Lepidochelys olivacea). We visually assessed images collected during six transects for sea turtle presence, resulting in 682 certain detections. A cumulative total of 1091 certain and probable turtles were detected in the collected imagery. Using these data, we calculate estimates of sea turtle density (km-2) in nearshore waters. After adjusting for both availability and perception biases, we developed a low-end estimate of 1299 ± 458 and a high-end estimate of 2086 ± 803 turtles per km-2. This pilot study illustrates how UAS can be used to conduct robust, safe, and cost-effective population assessments of sea turtle populations in coastal marine ecosystems

Applicant Selection to a Regional Medical Training Program: A Structural Analysis of Interviewer Assessments

Introduction: For regional campuses with specific program foci, assessing applicant fit necessarily extends beyond academic and professional factors. Based on assessments of applicants to a regional Rural Physician Leadership Program (RPLP), this study explores the relationship of academic and socio-demographic factors with interviewers’ ratings of: (1) likelihood of eventually practicing in a rural area of the state; and (2) overall acceptability to medical school. Methods: The study population consisted of 163 first-time RPLP applicants interviewed independently from 2009-2016 by two faculty members at both main and regional medical campuses. Path analysis was used to calculate direct, indirect, and total effects of applicants’ socio-demographic and academic characteristics on interviewers’ composite ratings. This study protocol (#17-0198-X3B) was approved as exempt by the governing Institutional Review Board; the authors report no conflicts of interest. Results: The combined influence of being an in-state resident with rural Appalachian origins, combined with undergraduate GPA, explained 40.7% of the variance in applicants’ predicted likelihood of practicing in rural Kentucky. In terms of applicant acceptability, the strongest direct effects were exerted by academic factors, GPA and total MCAT score, and the sole preceding endogenous variable: likelihood of rural in-state practice. However, two other background factors were modestly but significantly directly associated with overall acceptability: (1) age; and (2) residence. Specifying likelihood of rural practice as an intervening variable explained 42.5% of the variance in applicant acceptability and provided a good fit to the sample data (X2 = 3.19, df = 4, p = .526, CFI = 1.000, RLI = 1.018, RMSEA = .000). Conclusions: Interviewers appear to be assessing programmatic, mission-specific “fit” within the broader context of applicants’ abilities to navigate a demanding professional training curriculum. Future research should examine graduates’ eventual practice locations and intermediate academic performance as empirical validity of faculty interviewers’ assessments. Similarly, pre-professional pipeline efforts should better coordinate with training programs to provide consistent opportunities to nurture interest in mission-specific outcomes

Listeria Occurrence In Poultry Flocks: Detection and Potential Implications

Foodborne pathogens such as Salmonella, Campylobacter, Escherichia coli, and Listeria are a major concern within the food industry due to their pathogenic potential to cause infection. Of these, Listeria monocytogenes, possesses a high mortality rate (approximately 20%) and is considered one of the most dangerous foodborne pathogens. Although the usual reservoirs for Listeria transmission have been extensively studied, little is known about the relationship between Listeria and live poultry production. Sporadic and isolated cases of listeriosis have been attributed to poultry production and Listeria spp. have been isolated from all stages of poultry production and processing. Farm studies suggest that live birds may be an important vector and contributor to contamination of the processing environment and transmission of Listeria to consumers. Therefore, the purpose of this review is to highlight the occurrence, incidence, and potential systemic interactions of Listeria spp. with poultry

Multi-Object Tracking by Iteratively Associating Detections with Uniform Appearance for Trawl-Based Fishing Bycatch Monitoring

The aim of in-trawl catch monitoring for use in fishing operations is to detect, track and classify fish targets in real-time from video footage. Information gathered could be used to release unwanted bycatch in real-time. However, traditional multi-object tracking (MOT) methods have limitations, as they are developed for tracking vehicles or pedestrians with linear motions and diverse appearances, which are different from the scenarios such as livestock monitoring. Therefore, we propose a novel MOT method, built upon an existing observation-centric tracking algorithm, by adopting a new iterative association step to significantly boost the performance of tracking targets with a uniform appearance. The iterative association module is designed as an extendable component that can be merged into most existing tracking methods. Our method offers improved performance in tracking targets with uniform appearance and outperforms state-of-the-art techniques on our underwater fish datasets as well as the MOT17 dataset, without increasing latency nor sacrificing accuracy as measured by HOTA, MOTA, and IDF1 performance metrics