Preparing Teacher Candidates to Meet the Needs of English Language Learners: The TELLs Certificate

A report on the development and implementation of the Teaching English Language Learners (TELLs) certificate program at Miami University, in Oxford Ohio

Ecological Risk Assessment for Highways in the Chesapeake Bay Watershed

The population of coastal counties in the United States is over six-fold higher than non-coastal counties and population density along the Atlantic coast is much greater than all other coasts in the nation. Many areas around the Chesapeake Bay watershed are participating in this growth and extensive interstate construction is planned for this region. A wide array of primary ecological risks to the Chesapeake Bay exists, and may be classified as biological, physical, or chemical. Biological risks range from physical threats to motorists and animals to genetic risks to local flora and fauna populations. Island biogeography theory can be used to predict species losses associated with highway construction and resultant limits to migration. Introduction of exotic species and loss of ecologically significant areas (e.g. wetlands) are included as biological risks. Physical risks are primarily associated with hydrology, erosion, and related water quality considerations. Chemical concerns can be described as either chronic, such as certain airborne pollutants, or acute, such as accidental or illegal discharges. Secondary risks associated with highway construction result from facilitated traffic flow. Included are a variety of effects resulting from urban sprawl, strip development, and economic development of adjacent areas. Some ecological risks have received legislative, and subsequently transportation department attention. However, most ecological risks do not affect the decision-making process.https://scholarworks.wm.edu/vimsbooks/1179/thumbnail.jp

Early Growth of Three Kingfish (Menticirrhus) Species Found in Coastal Waters of the Northern Gulf of Mexico

Southern kingfish (Menticirrhus americanus), gulf kingfish (M. littoralis), and northern kingfish (M. saxatilis) are members of the drum family (Sciaenidae) that are widespread in coastal habitats of the western Atlantic, including in the Gulf of Mexico (GOM). Despite their economic and ecological importance, little is known about growth of young kingfish. Young kingfish were collected from four different Mississippi shoreline habitats in 2005 and 2006; two associated with barrier islands and two along the mainland. Barrier island habitats included surf zones on the south shore and grass beds on the north shore. Mainland habitats were located along marsh-edges and sandy shorelines. Kingfish growth comparisons were made using analysis of covariance (ANCOVA) on 194 aged fish (127 M. americanus, 54 M. littoralis, and 13 M. saxatilis). Growth rates for all three species were generally similar ranging from about 0.7mm/day at 4-6 mm standard length (SL) to 1.9mm/day at 55-60mm SL. In 2005, M. americanus from marsh-edges grew significantly faster than those from sandy shorelines. Size-at-age of M. americanus and M. littoralis was significantly smaller in the spring than in the summer and fall, while both growth rate and size—at—age were similar in the summer and fall

Fertilizer Recommendations for the Rio Grande Plain.

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Perthes' disease of the hip: socioeconomic inequalities and the urban environment.

INTRODUCTION: Perthes' disease is a puzzling childhood hip disorder for which the aetiology is unknown. It is known to be associated with socioeconomic deprivation. Urban environments have also been implicated as a risk factor, however socioeconomic deprivation often occurs within urban environments and it is unclear if this association is the result of confounding. The objective of the current work was to gain a greater understanding of the influence of the urban/rural environment in Perthes' disease. METHODS: This was a descriptive observational study using the Scottish Morbidity Record, based in Scotland, UK using data from 2000-2010. A total of 443 patients with a discharge diagnosis of Perthes' disease were included. Socioeconomic deprivation was determined using the Scottish Index of Multiple Deprivation, and exposure to the 'urban environment' was recorded based on the Scottish Urban-Rural Classification. RESULTS: There was a strong association with socioeconomic deprivation, with rates among the most deprived quintile more than twice those of the most affluent (RR 2.1 (95% CI 1.5 to 2.9)). Urban areas had a greater rate of Perthes' disease discharges (RR 1.8 (95% CI 1.1 to 3.2)), though this was a reflection of greater deprivation in urban areas. Stratification for socioeconomic deprivation revealed similar discharge rates in urban and rural environments, suggesting that the aetiological determinants were not independently associated with urban environments. CONCLUSIONS: The occurrence of Perthes' disease within urban environments is high, yet this appears to be a reflection of higher socioeconomic deprivation exposure. Disease rates appear equivalent in similarly deprived urban and non-urban areas, suggesting that the determinant is not a consequence of the urban environment

Uniform-in-phase-space data selection with iterative normalizing flows

Improvements in computational and experimental capabilities are rapidly increasing the amount of scientific data that are routinely generated. In applications that are constrained by memory and computational intensity, excessively large datasets may hinder scientific discovery, making data reduction a critical component of data-driven methods. Datasets are growing in two directions: the number of data points and their dimensionality. Whereas dimension reduction typically aims at describing each data sample on lower-dimensional space, the focus here is on reducing the number of data points. A strategy is proposed to select data points such that they uniformly span the phase-space of the data. The algorithm proposed relies on estimating the probability map of the data and using it to construct an acceptance probability. An iterative method is used to accurately estimate the probability of the rare data points when only a small subset of the dataset is used to construct the probability map. Instead of binning the phase-space to estimate the probability map, its functional form is approximated with a normalizing flow. Therefore, the method naturally extends to high-dimensional datasets. The proposed framework is demonstrated as a viable pathway to enable data-efficient machine learning when abundant data are available

Summary of second annual MCBK public meeting: Mobilizing Computable Biomedical Knowledge—A movement to accelerate translation of knowledge into action

The volume of biomedical knowledge is growing exponentially and much of this knowledge is represented in computer executable formats, such as models, algorithms and programmatic code. There is a growing need to apply this knowledge to improve health in Learning Health Systems, health delivery organizations, and other settings. However, most organizations do not yet have the infrastructure required to consume and apply computable knowledge, and national policies and standards adoption are not sufficient to ensure that it is discoverable and used safely and fairly, nor is there widespread experience in the process of knowledge implementation as clinical decision support. The Mobilizing Computable Biomedical Knowledge (MCBK) community formed in 2016 to address these needs. This report summarizes the main outputs of the Second Annual MCBK public meeting, which was held at the National Institutes of Health on July 18‐19, 2019 and brought together over 150 participants from various domains to frame and address important dimensions for mobilizing CBK.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154970/1/lrh2-sup-0001-supinfo.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154970/2/lrh210222.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154970/3/lrh210222_am.pd

Science results from sixteen years of MRO SHARAD operations

In operation for >16 years to date, the Mars Reconnaissance Orbiter (MRO) Shallow Radar (SHARAD) sounder has acquired data at its nominal 300–450 m along-track and 3-km cross-track resolution covering >55% of the Martian surface, with nearly 100% overlap in coverage at that scale in the polar regions and in a number of smaller mid-latitude areas. While SHARAD data have opened a new window into understanding the interior structures and properties of Martian ices, volcanics, and sedimentary deposits up to a few kilometers in depth, they have also led to new revelations about the deeper interior and the behavior of the planet’s ionosphere. Here we summarize the data collected by SHARAD over this time period, the methods used in the analysis of that data, and the resulting scientific findings. The polar data are especially rich, revealing complex structures that comprise up to several dozen reflecting interfaces that extend to depths of 3 km, which inform the evolution of Martian climate in the late Amazonian period. SHARAD observations of mid-latitude lobate debris aprons and other glacier-like landforms detect strong basal reflections and low dielectric loss, confirming that they are icerich debris-covered glaciers. In other mid-latitude terrains, SHARAD data demonstrate the presence of widespread ground ices, likely at lower concentrations. SHARAD signals also probe non-icy materials, mapping out stacked lava flows, probing low-density materials thought to be ash-fall deposits, and occasionally penetrating sedimentary deposits, all of which reveal the structures and interior properties diagnostic of emplacement processes. SHARAD signals are impacted by their passage through the Martian ionosphere, revealing variations in time and space of the total electron content linked with the remanent magnetic field. Advanced techniques developed over the course of the mission, which include subband and super-resolution processing, coherent and incoherent summing, and three-dimensional (3D) radar imaging, are enabling new discoveries and extending the utility of the data. For 3D imaging, a cross-track spacing at the nominal 3-km resolution is more than sufficient to achieve good results, but finer spacing of 0.5 km or less significantly improves the spatially interpolated radar images. Recent electromagnetic modeling and a flight test show that SHARAD’s signal-to-noise ratio can be greatly improved with a large (~120◦) roll of the spacecraft to reduce interference with the spacecraft body. Both MRO and SHARAD are in remarkably fine working order, and the teams look forward to many more years in which to pursue improvements in coverage density, temporal variability in the ionosphere, and data quality that promise exciting new discoveries at Mars

Use of RE-AIM to develop a multi-media facilitation tool for the patient-centered medical home

<p>Abstract</p> <p>Background</p> <p>Much has been written about how the medical home model can enhance patient-centeredness, care continuity, and follow-up, but few comprehensive aids or resources exist to help practices accomplish these aims. The complexity of primary care can overwhelm those concerned with quality improvement.</p> <p>Methods</p> <p>The RE-AIM planning and evaluation model was used to develop a multimedia, multiple-health behavior tool with psychosocial assessment and feedback features to facilitate and guide patient-centered communication, care, and follow-up related to prevention and self-management of the most common adult chronic illnesses seen in primary care.</p> <p>Results</p> <p>The <it>Connection to Health </it>Patient Self-Management System, a web-based patient assessment and support resource, was developed using the RE-AIM factors of reach (<it>e.g</it>., allowing input and output via choice of different modalities), effectiveness (<it>e.g</it>., using evidence-based intervention strategies), adoption (<it>e.g</it>., assistance in integrating the system into practice workflows and permitting customization of the website and feedback materials by practice teams), implementation (<it>e.g</it>., identifying and targeting actionable priority behavioral and psychosocial issues for patients and teams), and maintenance/sustainability (<it>e.g</it>., integration with current National Committee for Quality Assurance recommendations and clinical pathways of care). <it>Connection to Health </it>can work on a variety of input and output platforms, and assesses and provides feedback on multiple health behaviors and multiple chronic conditions frequently managed in adult primary care. As such, it should help to make patient-healthcare team encounters more informed and patient-centered. Formative research with clinicians indicated that the program addressed a number of practical concerns and they appreciated the flexibility and how the <it>Connection to Health </it>program could be customized to their office.</p> <p>Conclusions</p> <p>This primary care practice tool based on an implementation science model has the potential to guide patients to more healthful behaviors and improved self-management of chronic conditions, while fostering effective and efficient communication between patients and their healthcare team. RE-AIM and similar models can help clinicians and media developers create practical products more likely to be widely adopted, feasible in busy medical practices, and able to produce public health impact.</p