Modeling study on oil spill transport in the Great Lakes: The unignorable impact of ice cover.

The rise in oil trade and transportation has led to a continuous increase in the risk of oil spills, posing a serious worldwide concern. However, there is a lack of numerical models for predicting oil spill transport in freshwater, especially under icy conditions. To tackle this challenge, we developed a prediction system for oil with ice modeling by coupling the General NOAA Operational Modeling Environment (GNOME) model with the Great Lakes Operational Forecast System (GLOFS) model. Taking Lake Erie as a pilot study, we used observed drifter data to evaluate the performance of the coupled model. Additionally, we developed six hypothetical oil spill cases in Lake Erie, considering both with and without ice conditions during the freezing, stable, and melting seasons spanning from 2018 to 2022, to investigate the impacts of ice cover on oil spill processes. The results showed the effective performance of the coupled model system in capturing the movements of a deployed drifter. Through ensemble simulations, it was observed that the stable season with high-concentration ice had the most significant impact on limiting oil transport compared to the freezing and melting seasons, resulting in an oil-affected open water area of 49 km2 on day 5 with ice cover, while without ice cover it reached 183 km2. The stable season with high-concentration ice showed a notable reduction in the probability of oil presence in the risk map, whereas this reduction effect was less prominent during the freezing and melting seasons. Moreover, negative correlations between initial ice concentration and oil-affected open water area were consistent, especially on day 1 with a linear regression R-squared value of 0.94, potentially enabling rapid prediction. Overall, the coupled model system serves as a useful tool for simulating oil spills in the world's largest freshwater system, particularly under icy conditions, thus enhancing the formulation of effective emergency response strategies.

A review of failures of endoscopic treatment of vesicoureteral reflux with dextranomer microspheres.

PURPOSE: We evaluated the appearance of the mound of failed endoscopic dextranomer microsphere injections at the time of reinjection or open ureteral reimplantation. MATERIALS AND METHODS: We performed a multi-institutional study of 80 patients (97 ureters) who were diagnosed with vesicoureteral reflux and had failed endoscopic treatment with dextranomer microspheres. Observations of injected mound characteristics were made during the time of reinjection or at open ureteral reimplantation. Correlations were made with the pre-injection grade of reflux, volume of initial injection, number of punctures used for the initial injection and presence of symptoms of dysfunctional voiding. RESULTS: Examination of the failed injection sites before subsequent injections or open surgery revealed mound abnormalities in all but 13 of the 97 ureters. Of the cases 49% demonstrated a shifted mound, 22% an absent mound and 10% a loss of volume in the mound. Of the 13 patients with normal appearing mounds 7 had improved reflux grade, 3 had worsened grade and 3 had no change. Patients with dysfunctional voiding symptoms had a second injection failure rate of 44%, compared to a 13% rate in those without symptoms of voiding dysfunction. CONCLUSIONS: Most failures of endoscopic correction are associated with mound shifting. The presence of a perfect mound does not predict success. Dysfunctional voiding predicts a lower success rate after a second injection.

Identifying workers at risk for high health care expenditures: a short questionnaire.

The objective of this study was to create and measure the predictive accuracy of a brief questionnaire for screening new workers to identify those at increased risk for generating high health care insurance expenditures during the following year. Such an instrument could help health plans and providers intervene to mitigate the health risks of identified high-risk workers. We mailed a 53-item questionnaire to members of a "derivation cohort" (adult food processing workers, n = 15496) and obtained records of the eligible respondents' health insurance expenditures during the following year. Using multiple linear regression, we identified eight of the questions that predicted future expenditures most accurately, and created a formula to predict total expenditures from answers to these questions. To validate the formula's predictive accuracy, we used the eight-item questionnaire to survey two "validation cohorts" (transportation workers, n = 7445; and their dependents, n = 5562), inserted responses into the scoring formula, classified respondents into high-risk (top 10%) or low-risk (lower 90%) groupings, and then compared health insurance expenditures generated by the high- and low-risk groups during the following year. In the derivation cohort, age, sex, regular use of medications, frequent visits to physicians, and having arthritis, diabetes, cancer, or high cholesterol predicted future health care expenditures. In the worker and dependent validation cohorts, the respondents classified by the formula as high-risk generated insurance expenditures during the following year that were 2.4 and 1.8 times greater than those generated by the members of the low-risk groups (p < 0.001). An eight-item questionnaire and its scoring formula can identify high-risk groups of workers that will generate high health care expenditures during the following year. Healthcare organizations could use this questionnaire to help target new workers for care management and disease management interventions.