Biomechanics of judo backward breakfall for different throwing techniques in novice judokas

It is generally accepted that proper learning of the breakfall technique during early judo training is essential for attenuating the risk of judo-related head injury. Therefore, it is critical to understand the kinematics and head injury risks of breakfall motion to design a more safe and effective judo teaching paradigm that results in reduction of injury risk. We aimed to investigate the biomechanics of judo backward breakfalls by comparing osoto-gari and ouchi-gari in novice judokas. Twelve male novice judokas (age: 21.3 years, SD?=?0.6 years; height: 1.74?m, SD?=?0.04?m; body weight: 71.3, SD?=?6.4?kg; body mass index: 23.5, SD?=?2.3) volunteered to participate in this study. The kinematic data of the breakfall motion for both osoto-gari and ouchi-gari were collected using a three-dimensional motion analysis technique (200?Hz). We observed significant differences between the movement patterns for the two techniques, especially in the lower extremity movements. In addition, a significantly greater peak extension momentum (osoto-gari: 1.29, SD?=?0.23?kg?m^2?s^?1; ouchi-gari: 0.84, SD?=?0.29?kg?m^2?s^?1) and lower head position along the vertical axis (osoto-gari: 0.18, SD?=?0.05?m; ouchi-gari: 0.31, SD?=?0.08?m) with a large effect size were found in the breakfall for osoto-gari. Our results suggest that a different paradigm is needed for effectively teaching each breakfall technique that will enable us to substantially lower the risk of judo-related head injuries in novice judokas.     

Collaborative filtering for expansion of learner’s background knowledge in online language learning: does “top-down” processing improve vocabulary proficiency?

In recent years, collaborative filtering, a recommendation algorithm that incorporates a user’s data such as interest, has received worldwide attention as an advanced learning support system. However, accurate recommendations along with a user’s interest cannot be ideal as an effective learning environment. This study aims to develop and evaluate an online English vocabulary learning system using collaborative filtering that allows learners to learn English vocabulary while expanding their interests. The online learning environment recommends English news articles using information obtained from other users with similar interests. The learner then studies these recommended articles as a method of learning English. The results of a two-month experiment that compared this system to an earlier collaborative filtering system called “GroupLens” reveal that learners who used the collaborative filtering system developed in this study read various news articles and had significantly higher scores on topic-specific vocabulary tests than did those who used the previous system.     

An integrated teaching method of gross anatomy and computed tomography radiology

It is essential for medical students to learn and comprehend human anatomy in three dimensions (3D). With this in mind, a new system was designed in order to integrate anatomical dissections with diagnostic computed tomography (CT) radiology. Cadavers were scanned by CT scanners, and students then consulted the postmortem CT images during cadaver dissection to gain a better understanding of 3D human anatomy and diagnostic radiology. Students used handheld digital imaging and communications in medicine viewers at the bench‐side (OsiriX on iPod touch or iPad), which enabled “pixel‐to‐tissue” direct comparisons of CT images and cadavers. Students had lectures and workshops on diagnostic radiology, and they completed study assignments where they discussed findings in the anatomy laboratory compared with CT radiology findings. This teaching method for gross and radiological anatomy was used beginning in 2009, and it yielded strongly positive student perspectives and significant improvements in radiology skills in later clinical courses. Anat Sci Educ 7: 438–449. © 2014 American Association of Anatomists.     

论梁启超《清代学术概论》中的科学精神

在《清代学术概论》中,梁启超将清代思潮的变迁过程分成三个不同的阶段.而贯穿三个阶段他所予以重视的关键性精神即是“科学精神”.梁启超所关心的问题在于学问该如何得到发展,并且忧虑“致用”的主观动机容易介入研究过程,从而影响其客观性,因此,梁启超主张学者应避开去问所治的学问是否实用.“为学问而治学问”,这就是梁启超《清代学术概念》中所要表达的中心思想.梁启超深刻地体会到了政治权力主宰真理和正义的严酷现实,他所站到的非政治性立场本身就在政治社会环境中.《概论》在政治思想史学上具有深刻的意义.     

Kinematic comparison of the seoi-nage judo technique between elite and college athletes

This study sought to identify biomechanical factors that determine fast and skilful execution of the seoi-nage (shoulder throw) technique by comparing kinematics between elite and college judo athletes. Three-dimensional motion data were captured using a VICON-MX system with 18 cameras operating at 250 Hz as three male elite and seven male college judo athletes performed seoi-nage. No significant difference was found in motion phase time of the turning phase between the two groups, indicating that motion phase time is not necessarily a factor contributing quickness in seoi-nage. The maximum relative velocity of the whole body centre of mass along the anterior–posterior direction was significantly greater in the elite athletes (2.74 ± 0.33 m/s) than in the college athletes (1.62 ± 0.47 m/s) during the turning phase (p = 0.023). The overall angular velocity of the body part lines, particularly the arm line, tended to be greater in the elite athletes (p = 0.068). The results imply that the velocity of the thrower relative to the opponent in the forward drive and turning motion reflects high skill seoi-nage. Coaches should recognise the relative forward velocity as a factor that may contribute to a successful seoi-nage when teaching the judo throw technique.     

Fitting Structural Equation Model Trees and Latent Growth Curve Mixture Models in Longitudinal Designs: The Influence of Model Misspecification

When conducting longitudinal research, the investigation of between-individual differences in patterns of within-individual change can provide important insights. In this article, we use simulation methods to investigate the performance of a model-based exploratory data mining technique—structural equation model trees (SEM trees; Brandmaier, Oertzen, McArdle, & Lindenberger, 2013)—as a tool for detecting population heterogeneity. We use a latent-change score model as a data generation model and manipulate the precision of the information provided by a covariate about the true latent profile as well as other factors, including sample size, under the possible influences of model misspecifications. Simulation results show that, compared with latent growth curve mixture models, SEM trees might be very sensitive to model misspecification in estimating the number of classes. This can be attributed to the lower statistical power in identifying classes, resulting from smaller differences of parameters prescribed by the template model between classes.