Adlerkronborg7008

We propose a method to discover differential equations describing the long-term dynamics of phenomena featuring a multiscale behavior in time, starting from measurements taken at the fast-scale. Our methodology is based on a synergetic combination of data assimilation (DA), used to estimate the parameters associated with the known fast-scale dynamics, and machine learning (ML), used to infer the laws underlying the slow-scale dynamics. Specifically, by exploiting the scale separation between the fast and the slow dynamics, we propose a decoupling of time scales that allows to drastically lower the computational burden. Then, we propose a ML algorithm that learns a parametric mathematical model from a collection of time series coming from the phenomenon to be modeled. LJH685 Moreover, we study the interpretability of the data-driven models obtained within the black-box learning framework proposed in this paper. In particular, we show that every model can be rewritten in infinitely many different equivalent ways, thus making intrinsically ill-posed the problem of learning a parametric differential equation starting from time series. Hence, we propose a strategy that allows to select a unique representative model in each equivalence class, thus enhancing the interpretability of the results. We demonstrate the effectiveness and noise-robustness of the proposed methods through several test cases, in which we reconstruct several differential models starting from time series generated through the models themselves. Finally, we show the results obtained for a test case in the cardiovascular modeling context, which sheds light on a promising field of application of the proposed methods.It is well established that agrochemicals can pose significant threats to native pollinators; however, relatively little is known about pollinator risks associated with agrochemicals that are used on beef cattle feed yards. Recently, feed yard-derived agrochemicals and those from row crop agriculture were quantified on wildflowers growing on the High Plains, USA. To better characterize pollinator risks on the High Plains, we collected colocated wildflowers and foraging bees across three field seasons for analytical determination of residual agrochemicals. Agrochemicals were detected and quantified on the majority of wildflowers (85%) and nearly half of bees (49%). Permethrin was the most frequently detected analyte on wildflowers (32%) and bees (17%). Flower hazard quotients and flower hazard indices were calculated to deterministically evaluate risk to foraging pollinators. Mean flower hazard quotients exceeded one for 5/16 analytes (31%), and flower hazard quotients calculated for 30% of wildflowers were greater than 50. Flower hazard quotients for clothianidin exceeded 400 for 14% of wildflowers, which portends conditions conducive to frequent bee mortalities. Flower hazard indices were greater on wildflowers from mid-July to mid-September as compared with wildflowers collected earlier in the summer, which coincides with row crop planting and increased prevalence of feed yard flies. Hazard quotients and hazard index values calculated from agrochemical residue data suggest that pollinators frequenting wildflowers near beef cattle feed yards and row crops on the High Plains are at risk from both individual sources, and more so when considered in combination. Integr Environ Assess Manag 2021;001-11. © 2021 SETAC.The use of natural habitats for coastal protection (also known as Nature-Based Solutions or NBS) in place of engineered structures like breakwaters and seawalls can yield a wide range of ecological and economic benefits. Despite these advantages, NBS are not commonly implemented for shoreline protection due to uncertainty over the amount of protection afforded by each unique feature and how protective capacity and ecological benefits are likely to change over time as NBS mature and adapt to changing environmental drivers. Here, we highlight the recent restoration of Swan Island in the Chesapeake Bay, Maryland, USA, and the collaborative approach used to evaluate post-construction performance, as a framework for quantitative evaluation of NBS projects. At Swan Island, 60 000 cubic yards of dredged sediment were used to elevate and restore the island's footprint with an emphasis on increasing its protective and ecological benefits and long-term resilience to sea-level rise. Five entities have leveraged resources to quantify the benefits and efficacy of island restoration by conducting pre- and post-restoration monitoring, which supports the development of an integrated, simulation model that includes three "measured" system parameters wave height, vegetative biomass, and island profile (i.e., elevations). The model will be used to predict island performance under a range of different system scenarios and used to inform adaptive management options. Results will demonstrate the efficacy of leveraging natural and engineered processes to restore island systems while providing a framework for quantifying NBS. Integr Environ Assess Manag 2021;001-7. © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). This article has been contributed to by US Government employees and their work is in the public domain in the USA.COVID-19 has upended medical practice and education, but has also catalyzed enhancements in the field. Early on, a local group of researchers united to investigate the impact of the pandemic on pediatric hematology oncology (PHO). From this group, a regional educational series was established, "virtual-Symposium of Pediatric Hematology/Oncology of New York" (v-SYMPHONY). The implementation of these endeavors while PHO fellowship applications are declining has highlighted our perceptions that education, mentoring, and career expectations are not keeping up with the needs of current trainees. We describe our regional experience joining together to further education and research, and reflect on the current landscape of PHO training and workforce.