高水平运动员运动损伤经历的现象学研究

采用开放式访谈法对损伤运动员康复过程中的三个阶段进行了访谈研究.运动员将在损伤后的第一周,损伤后的15～20天及损伤后的30天接受访谈.这三次开放性的访谈是让运动员在没有任何前提约束的情况下自由地谈论他们的经历.被试是美国东南部大学的NCAA一级运动员（5名）.对访谈结果的分析揭示了四个主题：视点情绪反应,损伤应对及人际关系和几个次级主题.结论：第一,运动损伤在很大程度上影响了运动员的生活;第二,运动损伤对于本研究中的每名运动员都是一次独特的经历;最后,通过多重现象访谈法给运动员提供了公开谈论他们损伤康复经验的机会.     

Understanding Campus and Community Relationships through Marriage and Family Metaphors: A Town-Gown Typology

In this article we argue that the scholarship on marriages and families provides invaluable insights into town-gown relationships. Marital typologies are used to generate insights into what happens between campus and community relationships over time, and a line of family scholarship provides some additional illumination about the ways in which institutions and municipalities can strike a healthy balance between meeting their idiosyncratic needs and pursuing shared goals and objectives. We use four case examples to illustrate the application of the typological structure, and these examples are followed by a discussion of implications for leadership on both sides of the town-gown relationship.     

Cool Collaborations: Designing a Better Library Experience

Academic libraries routinely partner with other campus units in such areas as information literacy or writing support. However, the Georgia Tech library collaborations described in this article step outside the norm in that librarians are involved throughout the process of designing the collaborative projects; the projects are integrated into the undergraduate curriculum and embrace the science, technology, and design campus focus; the library incurs little or no financial commitment; and projects are ongoing or have long-term effects. The projects continue to change campus perceptions of libraries and librarians, and they have made the library a sought after “cool” collaborator on campus.     

Micromixing visualization and quantification in a microscale multi-inlet vortex nanoprecipitation reactor using confocal-based reactive micro laser-induced fluorescence

A technique for visualizing and quantifying reactive mixing for laminar and turbulent flow in a microscale chemical reactor using confocal-based microscopic laser induced fluorescence (confocal μ-LIF) was demonstrated in a microscale multi-inlet vortex nanoprecipitation reactor. Unlike passive scalar μ-LIF, the reactive μ-LIF technique is able to visualize and quantify micromixing effects. The confocal imaging results indicated that the flow in the reactor was laminar and steady for inlet Reynolds numbers of 10, 53, and 93. Mixing and reaction were incomplete at each of these Reynolds numbers. The results also suggested that although mixing by diffusion was enhanced near the midplane of the reactor at Re_j = 53 and 93 due to very thin bands of acidic and basic fluid forming as the fluid spiraled towards the center of the reactor, near the top, and bottom walls of the reactor, the lower velocities due to fluid friction with the walls hindered the formation of these thin bands, and, thus, resulted in large regions of unmixed and unreacted fluid. At Re_j = 240, the flow was turbulent and unsteady. The mixing and reaction processes were still found to be incomplete even at this highest Reynolds number. At the reactor midplane, the flow images at Re_j = 240 showed unmixed base fluid near the center of the reactor, suggesting that just as in the Re_j = 53 and 93 cases, lower velocities near the top and bottom walls of the reactor hinder the mixing and rection of the acidic and basic streams. Ensemble averages of line-scan profiles for the Re_j = 240 were then calculated to provide statistical quantification of the microscale mixing in the reactor. These results further demonstrate that even at this highest Reynolds number investigated, mixing and reaction are incomplete. Visualization and quantification of micromixing using this reactive μ-LIF technique can prove useful in the validation of computational fluid dynamics models of micromixing within microscale chemical reactors.     

Chapter 5 Study Methods and Attitudes

A modified form of the Delphi Technique was used within the School of Education at the University of Northern Colorado to formulate a definition of effective college teaching. The resulting definition contained five major categories. These results were used to develop twenty-five profiles of fictitious faculty members. Participants were asked to separate these twenty-five profiles into five sets according to those most deserving of a promotion. Multiple linear regression was used to analyze these judgments to determine the priority placed on each of the major categories of the definition of effective teaching.     

Six Workforce Development Initiatives That are Laying the Pathway to Success

Workforce development interventions have historically been heavily driven by federal funding, much of which was designated towards short-term training programs (less than six months) and rarely involved interaction or collaboration among colleges. The resulting efforts by the colleges to improve, update, or expand their workforce development programs typically focused on short-term localized improvement, resulting in competition over limited resources and notable variation in the quality of these programs. This article explores the recent changes in how community colleges and funding bodies are approaching workforce development. This is done by exploring the following six recent workforce development initiatives: Bridges to Opportunity (2002–2008), Integrated Basic Education and Skills Training (I-BEST, 2004–present), Breaking Through (2006–present), Shifting Gears (2007–2011), Accelerating Opportunity (2011–present), and Completion by Design (2011–present). Each of these initiatives has made, and continue to make, significant contributions to our collective understanding of how to create and sustain workforce development programs at community colleges that meet the needs of both students and industry.     

Modeling Dynamic Functional Neuroimaging Data Using Structural Equation Modeling

The aims of this study were to present a method for developing a path analytic network model using data acquired from positron emission tomography. Regions of interest within the human brain were identified through quantitative activation likelihood estimation meta-analysis. Using this information, a “true” or population path model was then developed using Bayesian structural equation modeling. To evaluate the impact of sample size on parameter estimation bias, proportion of parameter replication coverage, and statistical power, a 2 group (clinical/control) × 6 (sample size: N = 10, N = 15, N = 20, N = 25, N = 50, N = 100) Markov chain Monte Carlo study was conducted. Results indicate that using a sample size of less than N = 15 per group will produce parameter estimates exhibiting bias greater than 5% and statistical power below .80.