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Purpose: Musculoskeletal (MSK) screening tools can allow athletic trainers (AT) to focus prevention efforts by providing patient risk information. The purpose of this study is to examine lower extremity MSK screening tool practices and perceptions of ATs in traditional settings. Methods: A cross-sectional online survey was distributed to 4,937 full- and part-time collegiate and secondary school ATs randomly selected by the NATA. MSK screening tools were grouped into 7 categories: Range of Motion (ROM), Strength, Balance, Drop and Jump Landing (D/J Land), Double- and Single-Leg Hopping (D/S Hop), Movement Quality (MQual), and Injury History (History). For each screening tool category, questions assessed MSK screening tool usage, the perceived effectiveness of MSK screening tools to provide relevant injury risk and return to play (RTP) information, and MSK screening tools effect on decisions to implement prevention programs. Results: A total of 372 participants (female=215(48.4%), male=152(34.2%), age=35±10 years, experience=12±10 years, secondary school=194(52.2%), collegiate=178(47.8%)) completed the survey. Participants within our study indicated the used of the following screening tools categories in clinical practice: ROM=339(91.1%), Strength=342(91.9%), Balance=238(64.0%), D/J-Landing=134(36.0%), D/S-Hopping=233(62.6%), MQual=212(57.0%), History=316(85.0%), and None=18(4.8%). Conclusions: ATs in traditional settings indicate that they primarily use ROM, Strength, and History screening tools to gather information concerning LE injury risk and RTP. Implementation of screening tools most frequently occurred post-injury. Lastly, it seemed that intervention prescriptions were consistent regardless of screening tool used, suggesting blanket interventions prescription. This may have been do feelings of moderate effectiveness of these tools to determine injury risk.

Computer science students often evaluate the behavior of the code they write by running it on specific inputs and studying the outputs, and then apply their comprehension to a more general understanding of the code. While this is a good starting point in the student's career, successful graduates must be able to reason analytically about the code they create or encounter. They must be able to reason about the behavior of the code on arbitrary inputs, without running the code. Abstraction is central for such reasoning. In our quest to help students learn to reason abstractly and develop logically correct code, we have developed tools that rely on a verification engine. Code involves assignment, conditional, and loop statements, along with objects and operations. Reasoning activities involve symbolic reasoning with simple assertions and design-by-contract assertions such as pre-and post-conditions as well as loop invariants with data abstractions. Students progress from tracing and reading code to the design and implementation of code, all relying on abstraction for verification. This paper reports some key results and findings from associated studies spanning several years.

Climate change is expected to increase the frequency of flooding events and, thus, the risks of flood-related mortality and infrastructure damage. Global-scale assessments of future flooding from Earth system models based only on precipitation changes neglect important processes that occur within the land surface, particularly plant physiological responses to rising CO2. Higher CO2 can reduce stomatal conductance and transpiration, which may lead to increased soil moisture and runoff in some regions, promoting flooding even without changes in precipitation. Here we assess the relative impacts of plant physiological and radiative greenhouse effects on changes in daily runoff intensity over tropical continents using the Community Earth System Model. We find that extreme percentile rates increase significantly more than mean runoff in response to higher CO2. Plant physiological effects have a small impact on precipitation intensity but are a dominant driver of runoff intensification, contributing to one half of the 99th and one third of the 99.9th percentile runoff intensity changes.

Land–atmosphere (L–A) interactions are important for understanding convective processes, climate feedbacks, the development and perpetuation of droughts, heatwaves, pluvials, and other land-centered climate anomalies. Local L–A coupling (LoCo) metrics capture relevant L–A processes, highlighting the impact of soil and vegetation states on surface flux partitioning and the impact of surface fluxes on boundary layer (BL) growth and development and the entrainment of air above the BL. A primary goal of the Climate Process Team in the Coupling Land and Atmospheric Subgrid Parameterizations (CLASP) project is parameterizing and characterizing the impact of subgrid heterogeneity in global and regional Earth system models (ESMs) to improve the connection between land and atmospheric states and processes. A critical step in achieving that aim is the incorporation of L–A metrics, especially LoCo metrics, into climate model diagnostic process streams. However, because land–atmosphere interactions span timescales of minutes (e.g., turbulent fluxes), hours (e.g., BL growth and decay), days (e.g., soil moisture memory), and seasons (e.g., variability in behavioral regimes between soil moisture and latent heat flux), with multiple processes of interest happening in different geographic regions at different times of year, there is not a single metric that captures all the modes, means, and methods of interaction between the land and the atmosphere. And while monthly means of most of the LoCo-relevant variables are routinely saved from ESM simulations, data storage constraints typically preclude routine archival of the hourly data that would enable the calculation of all LoCo metrics. Here, we outline a reasonable data request that would allow for adequate characterization of sub-daily coupling processes between the land and the atmosphere, preserving enough sub-daily output to describe, analyze, and better understand L–A coupling in modern climate models. A secondary request involves embedding calculations within the models to determine mean properties in and above the BL to further improve characterization of model behavior. Higher-frequency model output will (i) allow for more direct comparison with observational field campaigns on process-relevant timescales, (ii) enable demonstration of inter-model spread in L–A coupling processes, and (iii) aid in targeted identification of sources of deficiencies and opportunities for improvement of the models. [ABSTRACT FROM AUTHOR]

This critical policy analysis is concerned with the discursive linguistic practices and social justice implications surrounding the passage of Florida's controversial "Parental Rights in Education Act" (PREA), which enacts limitations on classroom instruction involving topics related to gender and sexuality. Foregrounding this essay lays a call for social work scholarship to recognize the significance of the critical semiotic and post-structural turn in social science research, which evinces the importance of attending to the nuanced relationship between discourse, power, ideology, and identity formation. As a field espousing the tenets of social justice and commitments to the broader aims of social equality, social work holds an inherent investment in understanding the politics of language and, by extension, the language of emancipatory change. Informed by critical discourse analysis (CDA) and feminist post-structural thought, this analysis brings to the forefront the relevance of discourse, language, and semiotics as crucial objects of inquiry and seeks to examine what norms are in operation in the context of this legislation. What can discourse reveal about the nature of the social problem as postulated by PREA, and what discursive implications might it contain? Ultimately, this analysis contends that PREA represents a new threshold of educational and queer surveillance, best understood when bracketed by the ideologies of neoliberalism, cis-/heteropatriarchy, and the concomitant articulation of transphobia. [ABSTRACT FROM AUTHOR]

Land-atmosphere (L-A) interactions are important for understanding convective processes, climate feedbacks, the development and perpetuation of droughts, heatwaves, pluvials, and other land-centred climate anomalies. Local L-A coupling (LoCo) metrics capture relevant L-A processes, highlighting the impact of soil and vegetation states on surface flux partitioning, and the impact of surface fluxes on boundary layer (BL) growth, development, and entrainment of air above the BL. A primary goal of the Climate Process Team on Coupling Land and Atmospheric Subgrid Parameterizations (CLASP) is parameterizing and characterizing the impact of subgrid heterogeneity in global and regional earth system models (ESMs) to improve the connection between land and atmospheric states and processes. A critical step in achieving that aim is the incorporation of L-A metrics, especially LoCo metrics, into climate model diagnostic process streams. However, because land-atmosphere interactions span time scales of minutes (e.g., turbulent fluxes), hours (e.g., BL growth and decay), days (e.g., soil moisture memory), and seasons (e.g., variability of behavioural regimes between soil moisture and latent heat flux), with multiple processes of interest happening in different geographic regions at different times of year, there is not a single metric that captures all the modes, means, and methods of interaction between the land and the atmosphere. And while monthly means of most of the LoCo-relevant variables are routinely saved from ESM simulations, data storage constraints typically preclude routine archival of the hourly data that would enable the calculation of all LoCo metrics. Here we outline a reasonable data request that would allow for adequate characterization of sub-daily coupling processes between the land and the atmosphere, preserving enough sub-daily output to describe, analyse, and better understand L-A coupling in modern climate models. A secondary request involves embedding calculations within the models to determine mean properties in and above the BL to further improve characterization of model behaviour. Higher-frequency model output will (i) allow for more direct comparison with observational field campaigns on process-relevant time scales, (ii) enable demonstration of inter-model spread in L-A coupling processes, and (iii) aid in targeted identification of sources of deficiencies and opportunities for improvement of the models. [ABSTRACT FROM AUTHOR]

Background: Pain is one of the most common symptoms encountered in the healthcare system, and opioids are among the top three medications used to treat it. Understanding the reasoning behind physicians' opioid prescribing practices is vital to safe practice. The primary objective of our study was to describe pediatric emergency physicians' decision-making process when prescribing opioids for children's acute pain management. Methods: This study employed qualitative methodology, using one-on-one semi-structured interviews within a grounded theory analytic framework. We employed purposeful sampling to recruit pediatric emergency physicians from across Canada. Interviews were conducted by telephone (December 2019–January 2021). Transcript analysis occurred concurrently with data collection, supporting data saturation and theory development considerations. Results: Eleven interviews were completed with participants representing each of Canada's geographic regions. Nine major themes emerged: (1) practice setting and outpatient opioid use, (2) condition-specific considerations, (3) physician confidence in medical evidence, (4) pain assessment challenges, (5) patient and family perspectives, (6) opioid safety concerns, (7) personal biases and experiences, (8) personal practice context, and (9) the Opioid Crisis/media influence. Most clinicians felt that they limited opioid use to those who needed it most; all participants described challenges managing acute pain, emphasizing the need for accurate pain measurement and better guidelines, evidence-based data, and knowledge translation. Clinicians were more comfortable treating pain in the emergency department, compared to discharge prescribing. They recognized the importance of co-therapy with non-opioids and the need for opioid risk assessment when prescribing. A family centered approach was recognized as the goal of practice. Conclusion: Clinicians are less comfortable prescribing opioids to children for at-home use and find pain assessment and lack of clear guidelines to be barriers to pain care. Knowledge translation strategies for safer practice and optimal acute pain management could support responsible and judicious opioid use. [ABSTRACT FROM AUTHOR]

The Earth's land surface features spatial and temporal heterogeneity over a wide range of scales below those resolved by current Earth system models. State-of-the-art land and atmosphere models employ parameterizations to represent their subgrid heterogeneity, but the land-atmosphere coupling in ESMs typically operates on the grid scale. Communicating the information of the land surface heterogeneity with the overlying atmospheric boundary layer (ABL) remains a challenge in modeling land-atmosphere interactions. In order to account for the subgrid scale heterogeneity in land-atmosphere coupling, we implement a new coupling scheme in the Energy Exascale Earth System Model version 1 (E3SMv1) that uses adjusted surface variances and covariance of potential temperature and specific water content as the lower boundary condition for the atmosphere model. The new lower boundary condition accounts for both the variability of individual subgrid land surface patches and the inter-patch variability. E3SMv1 single-column model simulations over the Atmospheric Radiation Measurement (ARM) Southern Great Plain (SGP) site were performed to assess the impacts. We find that the new coupling parameterization increases the magnitude and diurnal cycle of the temperature variance and humidity variance in the lower ABL in non-precipitating days. The impacts are primarily attributed to subgrid inter-patch variability rather than variability of individual patches. These effects extend vertically from the surface to several levels in the lower ABL on clear days. We also find that accounting for surface heterogeneity increases low cloud cover and liquid water path. These cloud changes are associated with the change in cloud regime indicated by the skewness of the probability density function (PDF) of the subgrid vertical velocity. In precipitating days, the inter-patch variability reduces significantly, so that the impact of accounting for surface heterogeneity vanishes. These results highlight the importance of accounting for subgrid heterogeneity in land-atmosphere coupling in next generation Earth system models. [ABSTRACT FROM AUTHOR]