20,768 research outputs found
"Dance has connected me to my voice": the value of reflection in establishing effective dance pedagogy.
A variety of teaching pedagogies are used to teach dance which is now a compulsory core subject in the Arts and also taught in physical education. In this paper, I argue for the importance of a learner-centred pedagogy grounded in reflective practice. This forms a basis for developing a teaching approach that not only enriches students' artistic learning but develops their confidence as dancers and as people. Based on ongoing research with student dancers, I suggest that using reflective practice in teaching dance not only challenges dance educators to keep their pedagogy dynamic, but also creates a space in which teachers can respond more effectively to the needs of particular groups or individual students
AX J0049.4-7323 - a close look at a neutron star interacting with a circumstellar disk
Detailed evidence on the system AX J0049.4-7323 is presented here to show how
the passage of the neutron star in the binary system disrupts the circumstellar
disk of the mass donor Be star. A similar effect is noted in three other
Be/X-ray binary systems. Together the observational data should provide
valuable tools for modelling these complex interactions.Comment: 4 pages, accepted for publication in MNRA
The First Five Minutes: Enhancing Simulation Education for First-Year Pediatric Residents
We are looking at the feasibility of redesigning the existing simulation education for first-year residents within the Children’s Hospital of Richmond at VCU’s pediatric residency program to increase learning opportunities and to enhance exposure to pediatric medical emergencies. Novel simulation scenarios were designed to provide an introduction to managing the first five minutes of commonly encountered emergencies on the inpatient wards. These shortened simulations allow for educational objectives to be tailored to the expected knowledge and responsibilities of first-year residents
Predicted and experimental performance of large-bore high-speed ball and roller bearings
The values of inner and outer race temperature, cage speed, and heat transferred to the lubricant or bearing power loss, calculated using the computer programs Shaberth and Cybean, with the corresponding experimental data for the large bore ball and roller bearings were compared. After the development of computer program, it is important that values calculated using such program are compared with actual bearing performance data to assess the programs predictive capability. Several comprehensive computer programs currently in use are capable of predicting rolling bearing operating and performance characteristics. These programs accept input data of bearing internal geometry, bearing material and lubricant properties, and bearing operating conditions. The programs solve several sets of equations that characterize rolling element bearings. The output produced typically consists of rolling element loads and Hertz stresses, operating contact angles, component speed, heat generation, local temperatures, bearing fatigue life, and power loss. Two of these programs, Shaberth and Cybean were developed
Machine Learning Configuration Interaction
We propose the concept of machine learning configuration interaction (MLCI)
whereby an artificial neural network is trained on-the-fly to predict important
new configurations in an iterative selected configuration interaction
procedure. We demonstrate that the neural network can discriminate between
important and unimportant configurations, that it has not been trained on, much
better than by chance. MLCI is then used to find compact wavefunctions for
carbon monoxide at both stretched and equilibrium geometries. We also consider
the multireference problem of the water molecule with elongated bonds. Results
are contrasted with those from other ways of selecting configurations:
first-order perturbation, random selection and Monte Carlo configuration
interaction. Compared with these other serial calculations, this prototype MLCI
is competitive in its accuracy, converges in significantly fewer iterations
than the stochastic approaches, and requires less time for the higher-accuracy
computations.Comment: This document is the unedited Author's version of a Submitted Work
that was subsequently accepted for publication in The Journal of Chemical
Theory and Computation, copyright American Chemical Society after peer
review. To access the final edited and published work see
https://pubs.acs.org/articlesonrequest/AOR-dANIFXJKzRAyR99E6hb
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