Student-Created Curricular and Co-Curricular Pathways Toward Participation in a Diverse Democracy

This study explored the ways in which undergraduate students intentionally navigate complex curricular and co-curricular choices in preparation for engaging in a diverse democracy. Our study examined these choices among students at a university that lacks formal structures to facilitate these choices. Four curricular and co-curricular pathways that exemplify particular forms of the student experience across disciplines emerged and are discussed.     

Optimization of oar blade design for improved performance in rowing

The aim of the present study was to find a more optimal blade design for rowing performance than the Big Blade, which has been shown to be less than optimal for propulsion. As well as the Big Blade, a flat Big Blade, a flat rectangular blade, and a rectangular blade with the same curvature and projected area as the Big Blade were tested in a water flume to determine their fluid dynamic characteristics at the full range of angles at which the oar blade might present itself to the water. Similarities were observed between the flat Big Blade and rectangular blades. However, the curved rectangular blade generated significantly more lift in the angle range 0-90 degrees than the curved Big Blade, although it was similar between 90 and 180 degrees. This difference was attributed to the shape of the upper and lower edges of the blade and their influence on the fluid flow around the blade. Although the influence of oar blade design on boat speed was not investigated here, the significant increases in fluid force coefficients for the curved rectangular blade suggest that this new oar blade design could elicit a practically significant improvement in rowing performance.     

Using the cumulative common log-odds ratio to identify differential item functioning of rating scale items in the exercise and sport sciences

One aspect of construct validity is the extent to which the measurement properties of a rating scale are invariant across the groups being compared. An increasingly used method for assessing between-group differences in the measurement properties of items of a scale is the framework of differential item functioning (DIF). In this paper we introduce the concept of DIF as a validation tool for scales used in physical education and exercise science, and illustrate the use of the cumulative common log-odds ratio for assessing the presence of DIF with data from the Exercise Imagery Inventory (EII; Giacobbi, Hausenblas, & Penfield, 2005).     

Relationships among creativity,intelligence, and achievement measures in upward bound students

Ninety-four disadvantaged, Upward Bound students were administered a test battery of the Otis Quick-Scoring Mental Ability Test, Preliminary Scholastic Aptitude Test, Guilford's tests of Expressional Fluency, Alternate Uses, and Consequences; and the Figural Form of the Torrance Tests of Creative Thinking. Significant sex differences favoring males were obtained for Otis I J(P < −025), PSAT-Verbal (p <.01), and PSAT-Quantitative (p <.001). Females excelled males on the figural elaboration score from the TTCT (p <.001). White disadvantaged students scored significantly higher than their Indian counterparts on Otis IQ (p <.05) and higher than their black counterparts on the PSAT-Quantitative (p <.01). White students also scored significantly higher than their Indian counterparts on Guilford-Consequences — Obvious (p <.05). A varimax rotation of the correlation matrix resulted in a two-factor solution defined by intelligence-achievement scores and figural creativity. Guilford creativity tests were more closely related to the intelligence-achievement factor, while the Torrance figural creativity test remained a distinct factor. The results are discussed in relation to previous studies of the creativity-intelligence distinction.     

Muscle co-activation and its influence on running performance and risk of injury in elite Kenyan runners

The relationship between muscle co-activation and energy cost of transport and risk of injury (initial loading rate and joint stiffness) has not been jointly studied. Fourteen elite Kenyan male runners were tested at two speeds (12 and 20 km · h^?1), where oxygen consumption, kinematic, kinetic and electromyography were recorded. Electromyography of seven lower limb muscles was recorded. Pre-activation and ground contact of agonist:antagonist co-activation was determined. All muscles displayed higher activity during pre-activation except rectus femoris (RF). Conversely, no differences were found during ground contact except for higher biceps femoris (BF) at 20 km · h^?1. Knee stiffness was correlated to RF–BF co-activation during both pre-activation and ground contact at both running speeds. However, energy cost of transport was only positively correlated to the above-mentioned muscle pairs at 20 km · h^?1 (r = 0620, P = 0.032; r = 0.682, P = 0.015, respectively). These findings emphasise the influence of neuromuscular control and performance and its support to musculoskeletal system to optimise function and modulate risk of injury. Further, neuromuscular activity during terminal swing is also important and necessary to execute and maintain performance.     

Real-time processing of social media with SENTINEL: A syndromic surveillance system incorporating deep learning for health classification

Interest in real-time syndromic surveillance based on social media data has greatly increased in recent years. The ability to detect disease outbreaks earlier than traditional methods would be highly useful for public health officials. This paper describes a software system which is built upon recent developments in machine learning and data processing to achieve this goal. The system is built from reusable modules integrated into data processing pipelines that are easily deployable and configurable. It applies deep learning to the problem of classifying health-related tweets and is able to do so with high accuracy. It has the capability to detect illness outbreaks from Twitter data and then to build up and display information about these outbreaks, including relevant news articles, to provide situational awareness. It also provides nowcasting functionality of current disease levels from previous clinical data combined with Twitter data.The preliminary results are promising, with the system being able to detect outbreaks of influenza-like illness symptoms which could then be confirmed by existing official sources. The Nowcasting module shows that using social media data can improve prediction for multiple diseases over simply using traditional data sources.