Why Engagement Matters in Sport Volunteer Motivation

Over the years, sport management scholars have been interested in sport volunteer research. Considering there is a heavy reliance on sport volunteers to successfully stage of sporting events, knowing how to recruit and retain these volunteers allows sport event managers and organizers to continue this success. One such way is through understanding the engagement of sport volunteers, specifically the influences of engagement. Through survey methodology, this study examined how engagement of 464 sport volunteers at college football bowl games influenced motivational aspects. Structural Equation Modeling found that meaningfulness and safety had a significant impact on love and purposive motivation through engagement, but there was no significant relationship with rewards. With these results in mind, there are implications for sport event organizers to remember when working with volunteers. Keywords: Human resource management, volunteer engagement, volunteer motivatio

How the Perception of Athletic Academic Services affects the overall College Experience of Freshmen Student-Athletes

More and more intercollegiate athletics programs are allocating strategic resources towards building attractive athletics facilities, lavish training and academic complexes, and high-quality support services. Strategic investments in these areas continue to be a high priority for major college athletics programs, all with the hopes of enhancing the overall college experience for student-athletes. As such, researchers have begun to examine the role these various support services play in the overall athletic program. In this aim, the present study seeks to understand how academic support services are successful in enhancing this experience. Findings indicate that freshmen student-athletes’ perceptions of service quality provided by their academic athletic services, influence satisfaction, student involvement, and emotional adjustment. Building from these findings, university athletic departments should reevaluate and adjust their academic services based on the perception of student-athletes and how the provided services influence their overall college experience

Characterization of the retinal proteome during rod photoreceptor genesis

<p>Abstract</p> <p>Background</p> <p>The process of rod photoreceptor genesis, cell fate determination and differentiation is complex and multi-factorial. Previous studies have defined a model of photoreceptor differentiation that relies on intrinsic changes within the presumptive photoreceptor cells as well as changes in surrounding tissue that are extrinsic to the cell. We have used a proteomics approach to identify proteins that are dynamically expressed in the mouse retina during rod genesis and differentiation.</p> <p>Findings</p> <p>A series of six developmental ages from E13 to P5 were used to define changes in retinal protein expression during rod photoreceptor genesis and early differentiation. Retinal proteins were separated by isoelectric focus point and molecular weight. Gels were analyzed for changes in protein spot intensity across developmental time. Protein spots that peaked in expression at E17, P0 and P5 were picked from gels for identification. There were 239 spots that were picked for identification based on their dynamic expression during the developmental period of maximal rod photoreceptor genesis and differentiation. Of the 239 spots, 60 of them were reliably identified and represented a single protein. Ten proteins were represented by multiple spots, suggesting they were post-translationally modified. Of the 42 unique dynamically expressed proteins identified, 16 had been previously reported to be associated with the developing retina.</p> <p>Conclusions</p> <p>Our results represent the first proteomics study of the developing mouse retina that includes prenatal development. We identified 26 dynamically expressed proteins in the developing mouse retina whose expression had not been previously associated with retinal development.</p

Electro-Magnetic Nucleon Form Factors and their Spectral Functions in Soliton Models

It is demonstrated that in simple soliton models essential features of the electro-magnetic nucleon form factors observed over three orders of magnitude in momentum transfer $t$ are naturally reproduced. The analysis shows that three basic ingredients are required: an extended object, partial coupling to vector mesons, and relativistic recoil corrections. We use for the extended object the standard skyrmion, one vector meson propagator for both isospin channels, and the relativistic boost to the Breit frame. Continuation to timelike $t$ leads to quite stable results for the spectral functions in the regime from the 2- or 3-pion threshold to about two rho masses. Especially the onset of the continuous part of the spectral functions at threshold can be reliably determined and there are strong analogies to the results imposed on dispersion theoretic approaches by the unitarity constraint.Comment: 24 pages, (RevTeX), 5 PS-figures; Data points in fig.2 and corresponding references added. Final version, to be published in Z.Physik

Knowledge-based gene expression classification via matrix factorization

Motivation: Modern machine learning methods based on matrix decomposition techniques, like independent component analysis (ICA) or non-negative matrix factorization (NMF), provide new and efficient analysis tools which are currently explored to analyze gene expression profiles. These exploratory feature extraction techniques yield expression modes (ICA) or metagenes (NMF). These extracted features are considered indicative of underlying regulatory processes. They can as well be applied to the classification of gene expression datasets by grouping samples into different categories for diagnostic purposes or group genes into functional categories for further investigation of related metabolic pathways and regulatory networks. Results: In this study we focus on unsupervised matrix factorization techniques and apply ICA and sparse NMF to microarray datasets. The latter monitor the gene expression levels of human peripheral blood cells during differentiation from monocytes to macrophages. We show that these tools are able to identify relevant signatures in the deduced component matrices and extract informative sets of marker genes from these gene expression profiles. The methods rely on the joint discriminative power of a set of marker genes rather than on single marker genes. With these sets of marker genes, corroborated by leave-one-out or random forest cross-validation, the datasets could easily be classified into related diagnostic categories. The latter correspond to either monocytes versus macrophages or healthy vs Niemann Pick C disease patients.Siemens AG, MunichDFG (Graduate College 638)DAAD (PPP Luso - Alem˜a and PPP Hispano - Alemanas