Occupational Health Nursing - Musculoskeletal Disorders & Stretching

For employees who work in food processing plants, work related injuries can take a serious physical toll because of the continuous repetition of the tasks that they perform. Occupational health nurses work hard to encourage correct body mechanics in the workplace and are often the ones to treat those injuries. An internship at a food manufacturing plant allowed me to step into the shoes of an occupational health nurse and witness the difficulties that come with the position. The purpose of my position was to educate the food processing plant employees on proper ergonomics as well as create a stretching video to help decrease work related injuries. I learned that stretching throughout the workday was helpful, but the best ways to prevent injuries from occurring are proper ergonomics and body mechanics

Evaluating Best Practices in Group Mentoring: A Mixed Methods Study

Group mentoring is a resource-efficient and promising approach to youth intervention that allows for one or more adult mentors to interact with at least two youth for the purpose of fostering positive development (Dubois et al., 2011). Existing research identifies group mentoring as an effective intervention for improving socio-emotional and behavioral youth outcomes by promoting mentor-mentee relationship quality and positive group processes (e.g. group climate, group cohesion; Kuperminc, 2016). To date, most studies of group mentoring have focused on direct effects of program participation; thus, little is known about the program practices and group characteristics that may be associated with mentor-mentee relationship quality, group processes, and positive outcomes. Some potential key practices have been identified in the literature including mentor training, co-mentoring, interaction focus, and mentor-to-mentee ratio (Herrera et al., 2013; Karcher & Nakkula, 2010; Kuperminc & Thomason, 2013). The current mixed-methods study aimed to begin filling gaps in the group mentoring literature by examining group characteristics and practices that may contribute to positive youth outcomes. The study examined the hypothesis that mentor-mentee relationship quality and group processes mediate the associations between group characteristics (i.e., mentor training, co-mentoring, interaction focus, and mentor-to-mentee ratio) and youth outcomes (i.e., school belonging, self-efficacy, grade point average, earned academic credits). Results revealed preliminary evidence for the positive influence of smaller mentor-to-mentee ratio, mentor training attendance, and instrumental interaction focus on GPA (ratio and training) and group cohesion (instrumental focus), which emerged from mean difference testing. Multilevel structural equation modeling revealed that higher mentee ratings of mentor-mentee relationship quality were associated with increases in school belonging, and positive mentee-reported group climate was associated with increases in both school belonging and self-efficacy. These findings are discussed within the context of qualitative data from mentor and mentee focus groups

The Associations Between Multiple Dimensions of Acculturation and Adjustment Among Latino Youth from Immigrant Families

Acculturation includes cognitive, affective, and behavioral dimensions, but few studies have included all three, and little is known about the ways in which these dimensions interact with contextual factors to predict psychological and behavioral adjustment among Latino adolescents. The current study explored the strength of the associations between the three dimensions of acculturation and psychological and behavioral adjustment among Latino adolescents from immigrant families (N = 129). The study also investigated whether acculturative stress and time in the U.S. moderated these associations. Results indicated that higher levels of acculturative stress and lower levels of familism (a measure of the cognitive dimension of acculturation) predicted higher psychological distress. Bicultural identity (affective dimension) predicted higher behavioral competence. Age of arrival moderated the association between Language preference (behavioral dimension) and distress for English-dominant participants such that adolescent arrival was associated with less distress compared with arrival in early childhood

Towards Totally Asynchronous Primal-Dual Convex Optimization in Blocks

We present a parallelized primal-dual algorithm for solving constrained convex optimization problems. The algorithm is "block-based," in that vectors of primal and dual variables are partitioned into blocks, each of which is updated only by a single processor. We consider four possible forms of asynchrony: in updates to primal variables, updates to dual variables, communications of primal variables, and communications of dual variables. We explicitly construct a family of counterexamples to rule out permitting asynchronous communication of dual variables, though the other forms of asynchrony are permitted, all without requiring bounds on delays. A first-order update law is developed and shown to be robust to asynchrony. We then derive convergence rates to a Lagrangian saddle point in terms of the operations agents execute, without specifying any timing or pattern with which they must be executed. These convergence rates contain a synchronous algorithm as a special case and are used to quantify an "asynchrony penalty." Numerical results illustrate these developments

Totally Asynchronous Primal-Dual Convex Optimization in Blocks

We present a parallelized primal-dual algorithm for solving constrained convex optimization problems. The algorithm is "block-based," in that vectors of primal and dual variables are partitioned into blocks, each of which is updated only by a single processor. We consider four possible forms of asynchrony: in updates to primal variables, updates to dual variables, communications of primal variables, and communications of dual variables. We construct a family of explicit counterexamples to show the need to eliminate asynchronous communication of dual variables, though the other forms of asynchrony are permitted, all without requiring bounds on delays. A first-order primal-dual update law is developed and shown to be robust to asynchrony. We then derive convergence rates to a Lagrangian saddle point in terms of the operations agents execute, without specifying any timing or pattern with which they must be executed. These convergence rates include an "asynchrony penalty" that we quantify and present ways to mitigate. Numerical results illustrate these developments.Comment: arXiv admin note: text overlap with arXiv:2004.0514

Streamflow Sensitivity to Climate Warming and a Shift from Snowfall to Rainfall

As the climate warms, the fraction of precipitation falling as snow is expected to decrease. In snow-dominated mountainous regions, where reliance on snowpack and snowmelt is great, a reduction in snowfall fraction prompts us to examine downstream changes in streamflow and water resources. Shifts in precipitation phase are expected to alter the magnitude of ecosystem productivity, the timing of water resource availability, and, ultimately, the amount of annual streamflow. Here, I focus on the montane zone, which, in mid-latitude mountain ranges like the Rocky Mountains, is large and most vulnerable to changes in climate and warming. The objective of my study is to understand how climate warming, and associated shifts in evaporative demand and precipitation phase, will alter streamflow generation in the montane zone of the mid-latitude Rocky Mountains. The Distributed Hydrology Soil Vegetation Model is used to simulate streamflow within Gordon Gulch of the Boulder Creek Critical Zone Observatory, a watershed within the montane zone of the Colorado Front Range. I discover that streamflow decreases an average annual 37% under the influence of warming. But, on a seasonal time frame, streamflow increases in winter and spring months and decreases in summer and fall months. The presence of snow reveals a buffer-effect, decreasing the magnitude of streamflow loss compared to a snow-free environment. Unique to the montane zone, warming induces a shift in the timing of terrestrial water inputs from snowmelt and rainfall. In this context, terrestrial water inputs increase during a time of year when atmospheric water demand is relatively low, increasing the partitioning of terrestrial water inputs to streamflow. As a result, streamflow increases by 13% during winter and spring months, off-setting the net decrease in streamflow associated with warming. This off-setting effect has large implications for hydrological and ecological processes, and for water resource management across Earth’s mountainous regions

Changes in Snow Water Storage and Hydrologic Partitioning Across Western North America

Seasonal snowpack is an essential component in the Earth&rsquo;s hydrological cycle. About one-sixth of the global population relies on seasonal snowpack and glacier-derived runoff as a primary water resource. Snowmelt contributes to regional water supply, partially dictating the timing and volume of downstream water resources. Mountain snowpacks act as a natural &lsquo;water tower,&rsquo; storing winter precipitation until spring and summer months when downstream water demand is greatest. The magnitude and duration of regional snow water storage at the Earth&rsquo;s surface is thus a function of precipitation phase (as rainfall or snowfall) and the subsequent timing of water release, is unevenly distributed across regions, and is highly sensitive to climate changes. In mountainous western North America, hydrologic partitioning of catchment water inputs is likely sensitive to snow water storage, greatly influencing the volume and timing of downstream water resources. While previous works have studied the distribution of snow water equivalent (SWE) and trends in SWE, previous works have not evaluated the magnitude and duration of snow water storage. As a result, our understanding of how future changes in snowpacks will impact land surface hydrology is poorly understood. Hence, by evaluating trends in the magnitude and duration of snow water storage, and its impact on land surface hydrology, this dissertation adds substantively to the current literature. In this dissertation, I developed a snow water storage metric with a focus on surface water (i.e., above the soil layer), investigated historical and future changes in snow water storage, and related this metric to hydrologic partitioning, or the allocation of water inputs to streamflow (or evapotranspiration) across multiple spatial scales. After an overall introduction of the work (Chapter One), the second chapter of this dissertation is an overview of a newly developed snow water storage metric, which quantifies the differences in volume and timing between precipitation and surface water inputs (SWI, the daily summation of rainfall and snowmelt). Using precipitation forcings and modeled SWE outputs from the Variable Infiltration Capacity (VIC) model, I produced a Snow Storage Index (SSI) to quantify snow water storage volume and duration across western North America. I found that the average annual SSI has decreased (p&thinsp;&lt;&thinsp;0.01) from 1950-2013. By evaluating precipitation and SWI trends, I showed that the decrease in SSI was a result of significantly earlier SWI in spring months and comparable decreases in SWI later in the year. In mountainous regions where the SSI is declining, which includes &gt; 25% of the western North America study domain, snowmelt and rainfall have begun occurring earlier in the year, reducing the duration and magnitude of snow water storage. This is particularly evident in the Cascades and Southern Rockies. Additional declines in winter precipitation have reduced snow water storage in the Canadian and Northern Rockies. The sensitivity of the SSI depends on annual and seasonal temperature and precipitation variability and varies across different regional mountain ranges. As opposed to trends in SWE or snow fraction, the SSI represents the degree to which snow is delaying the timing (and magnitude) of SWI relative to precipitation. This lag between precipitation inputs and water availability is a fundamental component of the hydrologic cycle in snow-affected regions, offering a more hydrologically relevant perspective (than SWE trends, for example) on changes in water delivery and related climatic sensitivities for hydrologic and ecologic cycles and water resource management. In Chapter Three of this work, I related the SSI to hydrologic partitioning across the United States mountainous west. I discovered that the relationship between SSI and partitioning of incoming precipitation to streamflow is strongly and positively correlated within many ecoregions in the study domain. The ecoregions showing the strongest, positive correlations included: Cascades (r2 = 0.62), North Cascades (r2 = 0.61), Blue Mountains (r2 = 0.56), Canadian Rockies (r2 = 0.55), Idaho Batholith (r2 = 0.48), and Columbia Mountains / Northern Rockies (r2 = 0.45). The ratio of weekly SWI to weekly precipitation (SWI:P) was an equally strong predictor for hydrologic partitioning, particularly in mid-spring (e.g., March / April) and early summer (e.g., June / July) in the same mountainous ecoregions. When less water enters the soil system in spring months, and more in summer months, indicating a longer duration of water storage in the snowpack, more annual water inputs are partitioned to streamflow (maximum r2 across the same ecoregions = 0.62-0.74). Secondarily, when clustering ecoregions by climate and energy- vs. water-limitations, there was a strong and positive correlation between the SSI and hydrologic partitioning to streamflow in regions with greater energy-limitations, in both maritime (r2 = 0.57) and inter-mountain / continental (r2 = 0.42) climates. Relatively water-limited ecoregions, such as the Sierra Nevada, Middle Rockies, Wasatch / Uinta Mountains, and Southern Rockies, showed less sensitivity of hydrologic partitioning to the SSI, potentially due to relatively high aridity. As snow water storage decreases with warming, the timing of water delivery will change to varying degrees across the western United States, with large implications for hydrological and ecological processes and for water resource management across Earth&rsquo;s snow-influenced regions. In Chapter Four of this work, I used similar methodology to represent historical (control) and future (warming) snow water storage and hydrologic partitioning behavior and relationships at a smaller, alpine watershed in the Front Range of Colorado. Using the Distributed Hydrology Soil Vegetation Model and Weather Research and Forecasting Model-based projections of future climatic conditions, I generated a control and end-of-century warming simulation to compare snow water storage in the past and the future. Similar to the larger scale analyses in Chapters Two and Three, I found that areas where SSI was high experienced a decrease in snow water storage magnitude and duration in the warming (future) simulation, compared to the control (historical) simulation, due to increased rainfall and earlier snowmelt. Within both simulations, areas annually storing water as snow in larger volumes and for longer durations (i.e., greater SSI) partitioned more water to streamflow compared to areas of lower snow water storage (i.e., lower SSI), particularly within bare ground (r2 = 0.82 (control), 0.76 (warming)), alpine meadow (r2 = 0.71, 0.79) and closed shrub (r2 = 0.80, 0.72) vegetation types.On average across the catchment, the warming simulation showed decreased snow water storage (SSI: -0.11) from the control simulation (SSI: -0.07), resulting in a -57% change in SSI. Spatially, SSI percent change across the catchment ranged from -100% to +27%, with increases occurring in wind-scoured areas of the catchment where summer-dominant precipitation seasonality became more uniform. As such, using the Budyko framework, there was an average -10.2% change in the expected amount of precipitation that was partitioned to streamflow under warming conditions. Decreases in partitioning to streamflow with warming suggests that, particularly in cold, alpine regions, future streamflow losses may stress ecological, biological, and sociological dependents downstream, even at small, sub-catchment scales.</p

The association between city-level air pollution and frailty among the elderly population in China

This study is supported by China Scholarship Council (CSC), People's Republic of China and Population and Health Research Group, School of Geography and Sustainable Development, University of St Andrews, United Kingdom.A growing body of research suggests that air pollution negatively affects specific health outcomes, but how long- and short-term exposure to air pollution are associated with frailty is unclear. Using longitudinal data from adults aged 65 and over from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) linked with air quality index data, we model a frailty score according to the city-level of air pollution exposure, adjusting for individual socio-demographic factors and city-level indicators. All models show increased frailty with higher exposure to air pollution in one year prior to the interview, when controlling for short-term fluctuations. Moreover, elderly people living in areas where air pollution increased over the follow-up had larger increases in frailty scores than those where air pollution was relatively constant. The results suggest that air pollution plays a role in healthy ageing.PostprintPeer reviewe