Generalized gravity model for human migration

The gravity model (GM) analogous to Newton's law of universal gravitation has successfully described the flow between different spatial regions, such as human migration, traffic flows, international economic trades, etc. This simple but powerful approach relies only on the 'mass' factor represented by the scale of the regions and the 'geometrical' factor represented by the geographical distance. However, when the population has a subpopulation structure distinguished by different attributes, the estimation of the flow solely from the coarse-grained geographical factors in the GM causes the loss of differential geographical information for each attribute. To exploit the full information contained in the geographical information of subpopulation structure, we generalize the GM for population flow by explicitly harnessing the subpopulation properties characterized by both attributes and geography. As a concrete example, we examine the marriage patterns between the bride and the groom clans of Korea in the past. By exploiting more refined geographical and clan information, our generalized GM properly describes the real data, a part of which could not be explained by the conventional GM. Therefore, we would like to emphasize the necessity of using our generalized version of the GM, when the information on such nongeographical subpopulation structures is available.Comment: 14 pages, 6 figures, 2 table

The Origin of Star Formation in Early-type Galaxies Inferred from Spatially Resolved Spectroscopy

We investigate the origin of star formation activity in early-type galaxies with current star formation using spatially resolved spectroscopic data from the Mapping Nearby Galaxies at APO (MaNGA) in the Sloan Digital Sky Survey (SDSS). We first identify star-forming early-type galaxies from the SDSS sample, which are morphologically early-type but show current star formation activity in their optical spectra. We then construct comparison samples with different combinations of star formation activity and morphology, which include star-forming late-type galaxies, quiescent early-type galaxies and quiescent late-type galaxies. Our analysis of the optical spectra reveals that the star-forming early-type galaxies have two distinctive episodes of star formation, which is similar to late-type galaxies but different from quiescent early-type galaxies with a single star formation episode. Star-forming early-type galaxies have properties in common with star-forming late-type galaxies, which include stellar population, gas and dust content, mass and environment. However, the physical properties of star-forming early-type galaxies derived from spatially resolved spectroscopy differ from those of star-forming late-type galaxies in the sense that the gas in star-forming early-type galaxies is more concentrated than their stars, and is often kinematically misaligned with stars. The age gradient of star-forming early-type galaxies also differs from those of star-forming late-type galaxies. Our findings suggest that the current star formation in star-forming early-type galaxies has an external origin including galaxy mergers or accretion gas from the cosmic web.Comment: 19 pages, 12 figures, Accepted for publication in Ap

Does Objective Structured Clinical Examinations Score Reflect the Clinical Reasoning Ability of Medical Students?

Abstract:BackgroundClinical reasoning ability is an important factor in a physician's competence and thus should be taught and tested in medical schools. Medical schools generally use objective structured clinical examinations (OSCE) to measure the clinical competency of medical students. However, it is unknown whether OSCE can also evaluate clinical reasoning ability. In this study, the authors investigated whether OSCE scores reflected students' clinical reasoning abilities.MethodsSixty-five fourth-year medical students participated in this study. Medical students completed the OSCE with 4 cases using standardized patients. For assessment of clinical reasoning, students were asked to list differential diagnoses and the findings that were compatible or not compatible with each diagnosis. The OSCE score (score of patient encounter), diagnostic accuracy score, clinical reasoning score, clinical knowledge score and grade point average (GPA) were obtained for each student, and correlation analysis was performed.ResultsClinical reasoning score was significantly correlated with diagnostic accuracy and GPA (correlation coefficient = 0.258 and 0.380; P = 0.038 and 0.002, respectively) but not with OSCE score or clinical knowledge score (correlation coefficient = 0.137 and 0.242; P = 0.276 and 0.052, respectively). Total OSCE score was not significantly correlated with clinical knowledge test score, clinical reasoning score, diagnostic accuracy score or GPA.ConclusionsOSCE score from patient encounters did not reflect the clinical reasoning abilities of the medical students in this study. The evaluation of medical students' clinical reasoning abilities through OSCE should be strengthened