Annual Performance Reviews Of, For and By Faculty: A Qualitative Analysis of One Department's Experiences

Purpose: Although annual performance reviews and feedback are recommended for faculty development, best practices and faculty perceptions have not been documented. The authors sought to evaluate the process in one medical school department that established and has sustained an innovative review tradition for 25 years. Method: Content analysis of faculty reports and immersion/crystallization to analyze interviews. Results: Faculty reports described satisfaction and dissatisfaction; facilitators and barriers to goals; and requests for feedback, with community, collaboration and mentorship integral to all three. Interviewees emphasized practical challenges, the role of the mentor and the power of the review to establish community norms. Conclusion: Respondents generally found reviews constructive and supportive. The process informs departmental expectations and culture

The charismatic journey of mastery learning

A collection of articles in this issue examine the concept of mastery learning, underscoring that our journey is from a 19th-century construct for assuring skill development (i.e., completing a schedule of rotations driven by the calendar) to a 21st-century sequence of learning opportunities focused on acquiring mastery of special key competencies within clerkships or other activities. Mastery learning processes and standards have the potential to clarify learning goals and competency measurement issues in medical education. Although mastery learning methods originally focused on developing learners' competency with skillful procedures, the author of this Commentary posits that mastery learning methods may be usefully applied more extensively to broader domains of skillful practice, especially those practices that can be linked to outcomes of care. The transition to mastery-focused criteria for educational advancement is laudatory, but challenges will be encountered in the journey to mastery education. The author examines several of these potential challenges, including expansion of mastery learning approaches to effective but relational clinician advice-giving and counseling behaviors, developing criteria for choosing critical competencies that can be linked to outcomes, avoiding a excessively fragmented approach to mastery measurement, and dealing with "educational comorbidity.

Dynamics of the vortex-particle complexes bound to the free surface of superfluid helium

We present an experimental and theoretical study of the 2D dynamics of electrically charged nanoparticles trapped under a free surface of superfluid helium in a static vertical electric field. We focus on the dynamics of particles driven by the interaction with quantized vortices terminating at the free surface. We identify two types of particle trajectories and the associated vortex structures: vertical linear vortices pinned at the bottom of the container and half-ring vortices travelling along the free surface of the liquid

Dynamics of fine particles due to quantized vortices on the surface of superfluid 4^4He

Peculiar dynamics of a free surface of the superfluid 4He has been observed experimentally with a newly established technique utilizing a number of electrically charged fine metal particles trapped electrically at the surface by Moroshkin et al. They have reported that some portion of the particles exhibit some irregular motions and suggested the existence of quantized vortices interacting with the metal particles. We have conducted calculations with the vortex filament model, which turns out to support the idea of the vortex-particle interactions. The observed anomalous metal particle motions are roughly categorized into two types; (1) circular motions with specific frequencies, and (2) quasi-linear oscillations. The former ones seem to be explained once we consider a vertical vortex filament whose edges are terminated at the bottom and at a particle trapped at the surface. Although it is not yet clear whether all the anomalous motions are due to the quantum vortices, the vortices seem to play important roles for the motions.Comment: 7 pages, 10 figure

High frequency dynamics in liquid nickel: an IXS study

Owing to their large relatively thermal conductivity, peculiar, non-hydrodynamic features are expected to characterize the acoustic-like excitations observed in liquid metals. We report here an experimental study of collective modes in molten nickel, a case of exceptional geophysical interest for its relevance in Earth interior science. Our result shed light on previously reported contrasting evidences: in the explored energy-momentum region no deviation from the generalized hydrodynamic picture describing non conductive fluids are observed. Implications for high frequency transport properties in metallic fluids are discussed.Comment: 6 pages, 4 figures, to appear in "Journal of Chemical Physics

El alcance de nuestro viaje

Abstract not availabl

Neural architectures for fine-grained entity type classification

In this work, we investigate several neural network architectures for fine-grained entity type classification and make three key contributions. Despite being a natural comparison and addition, previous work on attentive neural architectures have not considered hand-crafted features and we combine these with learnt features and establish that they complement each other. Additionally, through quantitative analysis we establish that the attention mechanism learns to attend over syntactic heads and the phrase containing the mention, both of which are known to be strong hand-crafted features for our task. We introduce parameter sharing between labels through a hierarchical encoding method, that in lowdimensional projections show clear clusters for each type hierarchy. Lastly, despite using the same evaluation dataset, the literature frequently compare models trained using different data. We demonstrate that the choice of training data has a drastic impact on performance, which decreases by as much as 9.85% loose micro F1 score for a previously proposed method. Despite this discrepancy, our best model achieves state-of-the-art results with 75.36% loose micro F1 score on the well-established FIGER (GOLD) dataset and we report the best results for models trained using publicly available data for the OntoNotes dataset with 64.93% loose micro F1 score