Role Ambiguity and Team Cohesion in Division One Athletes

My study aims to discover the relationship between role ambiguity and team cohesion in a sports setting. I hypothesize that role ambiguity and team cohesion possess a negative correlation, that is, when team members experience role ambiguity, and then team cohesion is high. Alternatively, low levels of role ambiguity correlate with low levels of team cohesion. Ambiguity was measured using a multi-dimensional construct which included a) scope of responsibilities, b) behavior to carry out role responsibilities c) how role performance will be evaluated, and d) the consequences of failing to fulfill role responsibilities. In order to test my hypothesis, sixty-six Division One Athletes participated in an online questionnaire. The survey included questions regarding the four dimensions role-ambiguity, team cohesion, and demographics. The results showed a significant relationship between role ambiguity and team cohesion. In particular ambiguity related to scope of responsibilities and behavior needed to fulfill those responsibilities showed a significant relationship to team cohesion. My study suggests the importance of creating awareness about team roles and their effects on team cohesion. Implications of these findings and future research are further discussed

Mechanistic analysis and computer simulation of impact breakage of agglomerates: Effect of surface energy

Agglomerates are ubiquitous as intermediate or manufactured products in chemical, pharmaceutical and food industries. During handling and processing they may suffer breakage if they are weak. On the other hand, if they are too strong, their dispersion and disintegration could be difficult. The control of their mechanical strength is therefore highly desirable. However, the analysis of agglomerate strength is complex due to the large number of parameters that influence agglomerate behaviour, such as the primary particle size, density and elastic modulus, and the interparticle bond strength. A simple mechanistic model is presented here which relates the number of broken contacts in agglomerate due to impact velocity, interparticle adhesion energy and the particle properties of the particles forming the agglomerate. The model is based on the hypothesis that the energy used to break contacts during impact is proportional to the incident kinetic energy of the agglomerate. The damage ratio defined as the ratio of broken contacts to the initial number of bonds is shown to depend on the dimensionless group, Δ, in the form (ρV2D5/3E2/3)/ Γ5/3, where V is the impact velocity, E the elastic modulus, D the particle diameter, ρ the particle density and Γ the interface energy. This dimensionless group, Δ, incorporates the Weber number, (ρDV2/Γ), which was previously shown to be influential in agglomerate breakage, and may be presented in the form, Δ=WeIe2/3 , where Ie = ED/ Γ. The predicted dependency of the damage ratio on the surface energy has been tested using Distinct Element Method (DEM). Four different agglomerates have been formed and impacted against a target for three different values of the surface energy of the primary particles. The simulation results show that the effect of surface energy is better described by the above mechanistic model than by the Weber number alone, as previously used to characterise the impact strength of agglomerates

Containment experiments in vortex tubes with radial outflow and large superimposed axial flows

Containment tests of vortexes with radial outflow in basic vortex tube, and in axial-flow vortex tub

Practical methods of health behavior change: A discussion of two interventional studies

Programs designed to improve health outcomes do not always result in meaningful positive behavior change. Their efficacy may be limited by clinical resources and variation in motivation and learning style between patients. This presentation compares two studies: one aimed at improving the average daily step count of faculty and staff at the College of Saint Benedict through text message or social media encouragement, and one aimed at improving the bone health of female students through an online video or one-on-one provider-patient intervention. Both studies provide interesting comparisons of health interventions across different age groups, and between education versus motivation based behavior change. Both studies address the importance of applying research to the clinical setting. In the faculty/staff population, despite the absence of significant behavior change, 70.4 percent of participants who completed the post intervention survey reported text message and social media encouragement helped them be more active. Participants identified accountability as the main motivator for behavior change. Technology based health interventions may be important in making desirable health outcomes more accessible to patients and reduce the burden on health professionals. No gains in student learning in the education based intervention led to corresponding changes in behaviors. This provides some insights into the discordance between knowledge and behavior in college students, indicating a motivation instead of education based intervention may be more effective in this population. When considered together, the results of these two studies provide important insights for future research towards accessible behavior change

Evaluation of Motion Artifact Metrics for Coronary CT Angiography

Purpose This study quantified the performance of coronary artery motion artifact metrics relative to human observer ratings. Motion artifact metrics have been used as part of motion correction and best‐phase selection algorithms for Coronary Computed Tomography Angiography (CCTA). However, the lack of ground truth makes it difficult to validate how well the metrics quantify the level of motion artifact. This study investigated five motion artifact metrics, including two novel metrics, using a dynamic phantom, clinical CCTA images, and an observer study that provided ground‐truth motion artifact scores from a series of pairwise comparisons. Method Five motion artifact metrics were calculated for the coronary artery regions on both phantom and clinical CCTA images: positivity, entropy, normalized circularity, Fold Overlap Ratio (FOR), and Low‐Intensity Region Score (LIRS). CT images were acquired of a dynamic cardiac phantom that simulated cardiac motion and contained six iodine‐filled vessels of varying diameter and with regions of soft plaque and calcifications. Scans were repeated with different gantry start angles. Images were reconstructed at five phases of the motion cycle. Clinical images were acquired from 14 CCTA exams with patient heart rates ranging from 52 to 82 bpm. The vessel and shading artifacts were manually segmented by three readers and combined to create ground‐truth artifact regions. Motion artifact levels were also assessed by readers using a pairwise comparison method to establish a ground‐truth reader score. The Kendall\u27s Tau coefficients were calculated to evaluate the statistical agreement in ranking between the motion artifacts metrics and reader scores. Linear regression between the reader scores and the metrics was also performed. Results On phantom images, the Kendall\u27s Tau coefficients of the five motion artifact metrics were 0.50 (normalized circularity), 0.35 (entropy), 0.82 (positivity), 0.77 (FOR), 0.77(LIRS), where higher Kendall\u27s Tau signifies higher agreement. The FOR, LIRS, and transformed positivity (the fourth root of the positivity) were further evaluated in the study of clinical images. The Kendall\u27s Tau coefficients of the selected metrics were 0.59 (FOR), 0.53 (LIRS), and 0.21 (Transformed positivity). In the study of clinical data, a Motion Artifact Score, defined as the product of FOR and LIRS metrics, further improved agreement with reader scores, with a Kendall\u27s Tau coefficient of 0.65. Conclusion The metrics of FOR, LIRS, and the product of the two metrics provided the highest agreement in motion artifact ranking when compared to the readers, and the highest linear correlation to the reader scores. The validated motion artifact metrics may be useful for developing and evaluating methods to reduce motion in Coronary Computed Tomography Angiography (CCTA) images

Mathematics Is Biology's Next Microscope, Only Better; Biology Is Mathematics' Next Physics, Only Better

Joel Cohen offers a historical and prospective analysis of the relationship between mathematics and biolog

Going against the Grain: Overturning the received wisdom of a field takes not just strong evidence, but a strong personality. For one reproductive biologist, only time will tell whether such challenges are worth the risks in today's pressurized research climate.

A reproductive biologist's research at Massachusetts General Hospital in Boston has stoked a controversy about whether female mammals can renew egg cells

Conditions and Limitations on Learning in the Adaptive Management of Mallard Harvests

In 1995, the United States Fish and Wildlife Service adopted a protocol for the adaptive management of waterfowl hunting regulations (AHM) to help reduce uncertainty about the magnitude of sustainable harvests. To date, the AHM process has focused principally on the midcontinent population of mallards (Anas platyrhynchos), whose dynamics are described by 4 alternative models. Collectively, these models express uncertainty (or disagreement) about whether harvest is an additive or a compensatory form of mortality and whether the reproductive process is weakly or strongly density-dependent. Each model is associated with a probability or weight, which describes its relative ability to predict changes in population size. These Bayesian probabilities are updated annually using a comparison of population size predicted under each model with that observed by a monitoring program. The current AHM process is passively adaptive, in the sense that there is no a priori consideration of how harvest decisions might affect discrimination among models. We contrast this approach with an actively adaptive approach, in which harvest decisions are used in part to produce the learning needed to increase long-term management performance. Our investigation suggests that the passive approach is expected to perform nearly as well as an optimal actively adaptive approach, particularly considering the nature of the model set, management objectives and constraints, and current regulatory alternatives. We offer some comments about the nature of the biological hypotheses being tested and describe some of the inherent limitations on learning in the AHM process

Conditions and Limitations on Learning in the Adaptive Management of Mallard Harvests

In 1995, the United States Fish and Wildlife Service adopted a protocol for the adaptive management of waterfowl hunting regulations (AHM) to help reduce uncertainty about the magnitude of sustainable harvests. To date, the AHM process has focused principally on the midcontinent population of mallards (Anas platyrhynchos), whose dynamics are described by 4 alternative models. Collectively, these models express uncertainty (or disagreement) about whether harvest is an additive or a compensatory form of mortality and whether the reproductive process is weakly or strongly density-dependent. Each model is associated with a probability or weight, which describes its relative ability to predict changes in population size. These Bayesian probabilities are updated annually using a comparison of population size predicted under each model with that observed by a monitoring program. The current AHM process is passively adaptive, in the sense that there is no a priori consideration of how harvest decisions might affect discrimination among models. We contrast this approach with an actively adaptive approach, in which harvest decisions are used in part to produce the learning needed to increase long-term management performance. Our investigation suggests that the passive approach is expected to perform nearly as well as an optimal actively adaptive approach, particularly considering the nature of the model set, management objectives and constraints, and current regulatory alternatives. We offer some comments about the nature of the biological hypotheses being tested and describe some of the inherent limitations on learning in the AHM process

MossTalk Training for Word Retrieval: Generalization Across Semantic Categories

Little is known about the independent usefulness of MossTalk Words, a computerized training program for word retrieval, nor how training effects generalize to other untrained words. In a single-participant design, we investigated effects of independent training with MossTalk multi-mode matching exercises in four individuals with stroke-induced aphasia. Three of four participants improved in picture naming for trained words. One showed limited generalization to words in untrained semantic categories. Three improved in standardized testing, particularly for auditory comprehension, which is addressed in the matching exercises. Improvements are possible with independent training programs such as MossTalk Words