Astronomical seeing and ground-layer turbulence in the Canadian High Arctic

We report results of a two-year campaign of measurements, during arctic winter darkness, of optical turbulence in the atmospheric boundary-layer above the Polar Environment Atmospheric Laboratory in northern Ellesmere Island (latitude +80 deg N). The data reveal that the ground-layer turbulence in the Arctic is often quite weak, even at the comparatively-low 610 m altitude of this site. The median and 25th percentile ground-layer seeing, at a height of 20 m, are found to be 0.57 and 0.25 arcsec, respectively. When combined with a free-atmosphere component of 0.30 arcsec, the median and 25th percentile total seeing for this height is 0.68 and 0.42 arcsec respectively. The median total seeing from a height of 7 m is estimated to be 0.81 arcsec. These values are comparable to those found at the best high-altitude astronomical sites

Alien Registration- Theberge, Yvonne E. (Lebanon, York County)

https://digitalmaine.com/alien_docs/3442/thumbnail.jp

Regional Medical Campuses: A New Classification System

There is burgeoning belief that regional medical campuses (RMCs) are a significant part of the narrative about medical education and the health care workforce in the United States and Canada. Although RMCs are not new, in the recent years of medical education enrollment expansion, they have seen their numbers increase. Class expansion explains the rapid growth of RMCs in the past 10 years, but it does not adequately describe their function. Often, RMCs have missions that differ from their main campus, especially in the areas of rural and community medicine. The absence of an easy-to-use classification system has led to a lack of current research about RMCs as evidenced by the small number of articles in the current literature. The authors describe the process of the Group on Regional Medical Campuses used to develop attributes of a campus separate from the main campus that constitute a “classification” of a campus as an RMC. The system is broken into four models—basic science, clinical, longitudinal, and combined—and is linked to Liaison Committee on Medical Education standards. It is applicable to all schools and can be applied by any medical school dean or medical education researcher. The classification system paves the way for stakeholders to agree on a denominator of RMCs and conduct future research about their impact on medical education

The role of noise and dissipation in the hadronization of the quark-gluon plasma

We discuss the role of noise and dissipation in the explosive spinodal decomposition scenario of hadron production during the chiral transition after a high-energy heavy ion collision. We use a Langevin description inspired by nonequilibrium field theory to perform real-time lattice simulations of the behavior of the chiral fields. Preliminary results for the interplay between additive and multiplicative noise terms, as well as for non-Markovian corrections, are also presented.Comment: 8 pages, invited talk at the Workshop on Quark Gluon Plasma Thermalization, Vienna, August 10-12, 200

Physically Explainable Deep Learning for Convective Initiation Nowcasting Using GOES-16 Satellite Observations

Convection initiation (CI) nowcasting remains a challenging problem for both numerical weather prediction models and existing nowcasting algorithms. In this study, object-based probabilistic deep learning models are developed to predict CI based on multichannel infrared GOES-R satellite observations. The data come from patches surrounding potential CI events identified in Multi-Radar Multi-Sensor Doppler weather radar products over the Great Plains region from June and July 2020 and June 2021. An objective radar-based approach is used to identify these events. The deep learning models significantly outperform the classical logistic model at lead times up to 1 hour, especially on the false alarm ratio. Through case studies, the deep learning model exhibits the dependence on the characteristics of clouds and moisture at multiple levels. Model explanation further reveals the model's decision-making process with different baselines. The explanation results highlight the importance of moisture and cloud features at different levels depending on the choice of baseline. Our study demonstrates the advantage of using different baselines in further understanding model behavior and gaining scientific insights

The vertical distribution and biological transport of marine microplastics across the epipelagic and mesopelagic water column.

Plastic waste has been documented in nearly all types of marine environments and has been found in species spanning all levels of marine food webs. Within these marine environments, deep pelagic waters encompass the largest ecosystems on Earth. We lack a comprehensive understanding of the concentrations, cycling, and fate of plastic waste in sub-surface waters, constraining our ability to implement effective, large-scale policy and conservation strategies. We used remotely operated vehicles and engineered purpose-built samplers to collect and examine the distribution of microplastics in the Monterey Bay pelagic ecosystem at water column depths ranging from 5 to 1000 m. Laser Raman spectroscopy was used to identify microplastic particles collected from throughout the deep pelagic water column, with the highest concentrations present at depths between 200 and 600 m. Examination of two abundant particle feeders in this ecosystem, pelagic red crabs (Pleuroncodes planipes) and giant larvaceans (Bathochordaeus stygius), showed that microplastic particles readily flow from the environment into coupled water column and seafloor food webs. Our findings suggest that one of the largest and currently underappreciated reservoirs of marine microplastics may be contained within the water column and animal communities of the deep sea