Obtaining high-quality magnetic and velocity fields through Stokes inversion is crucial in solar physics. In this paper, we present a new deep learning method, named Stacked Deep Neural Networks ...(SDNN), for inferring line-of-sight (LOS) velocities and Doppler widths from Stokes profiles collected by the Near InfraRed Imaging Spectropolarimeter (NIRIS) on the 1.6 m Goode Solar Telescope (GST) at the Big Bear Solar Observatory (BBSO). The training data of SDNN is prepared by a Milne-Eddington (ME) inversion code used by BBSO. We quantitatively assess SDNN, comparing its inversion results with those obtained by the ME inversion code and related machine learning (ML) algorithms such as multiple support vector regression, multilayer perceptrons and a pixel-level convolutional neural network. Major findings from our experimental study are summarized as follows. First, the SDNN-inferred LOS velocities are highly correlated to the ME-calculated ones with the Pearson product-moment correlation coefficient being close to 0.9 on average. Second, SDNN is faster, while producing smoother and cleaner LOS velocity and Doppler width maps, than the ME inversion code. Third, the maps produced by SDNN are closer to ME's maps than those from the related ML algorithms, demonstrating the better learning capability of SDNN than the ML algorithms. Finally, comparison between the inversion results of ME and SDNN based on GST/NIRIS and those from the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory in flare-prolific active region NOAA 12673 is presented. We also discuss extensions of SDNN for inferring vector magnetic fields with empirical evaluation.
PURPOSEThe University of California, San Francisco (UCSF), Haile T. Debas Academy of Medical Educators Innovations Funding program awards competitive grants to create novel curricula and faculty ...development programs, compare pedagogical approaches, and design learner assessment methods. The authors examined the principal investigators’ (PIs’) perceptions of the impact of these intramural grants on their careers and on medical education innovation.
METHODAt 12 months (project completion) and 24 months (follow-up), PIs submit a progress report describing the impact of their grant on their careers, work with collaborators, subsequent funding, project dissemination, and the UCSF curriculum. The authors analyzed these reports using qualitative thematic analysis and achieved consensus in coding and interpretation through discussion.
RESULTSFrom 2001 to 2012, the program funded 77 PIs to lead 103 projects, awarding over $2.2 million. The authors analyzed reports from 88 grants (85.4%) awarded to 68 PIs (88.3%). PIs noted that the funding led to accelerated promotion, expanded networking opportunities, enhanced knowledge and skills, more scholarly publications and presentations, extramural funding, and local and national recognition. They also reported that the funding improved their status in their departments, enhanced their careers as medical educators, laid the foundation for subsequent projects, and engaged an array of stakeholders, including trainees and junior faculty.
CONCLUSIONSThese modest intramural education grants not only created innovative, enduring programs but also promoted educators’ professional identity formation, fostered collaborations, supported junior faculty in finding their desired career paths, provided advancement opportunities, and raised the local and national profiles of recipients.
Solar flares, especially the M- and X-class flares, are often associated with coronal mass ejections (CMEs). They are the most important sources of space weather effects, that can severely impact the ...near-Earth environment. Thus it is essential to forecast flares (especially the M-and X-class ones) to mitigate their destructive and hazardous consequences. Here, we introduce several statistical and Machine Learning approaches to the prediction of the AR's Flare Index (FI) that quantifies the flare productivity of an AR by taking into account the numbers of different class flares within a certain time interval. Specifically, our sample includes 563 ARs appeared on solar disk from May 2010 to Dec 2017. The 25 magnetic parameters, provided by the Space-weather HMI Active Region Patches (SHARP) from Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO), characterize coronal magnetic energy stored in ARs by proxy and are used as the predictors. We investigate the relationship between these SHARP parameters and the FI of ARs with a machine-learning algorithm (spline regression) and the resampling method (Synthetic Minority Over-Sampling Technique for Regression with Gaussian Noise, short by SMOGN). Based on the established relationship, we are able to predict the value of FIs for a given AR within the next 1-day period. Compared with other 4 popular machine learning algorithms, our methods improve the accuracy of FI prediction, especially for large FI. In addition, we sort the importance of SHARP parameters by Borda Count method calculated from the ranks that are rendered by 9 different machine learning methods.
We have obtained Hubble Space Telescope STIS and NICMOS and Gemini/GPI scattered-light images of the HD 191089 debris disk. We identify two spatial components: a ring resembling the Kuiper Belt in ...radial extent (FWHM ∼ 25 au, centered at ∼46 au) and a halo extending to ∼640 au. We find that the halo is significantly bluer than the ring, consistent with the scenario that the ring serves as the "birth ring" for the smaller dust in the halo. We measure the scattering phase functions in the 30°-150° scattering-angle range and find that the halo dust is more forward- and backward-scattering than the ring dust. We measure a surface density power-law index of −0.68 0.04 for the halo, which indicates the slowdown of the radial outward motion of the dust. Using radiative transfer modeling, we attempt to simultaneously reproduce the (visible) total and (near-infrared) polarized intensity images of the birth ring. Our modeling leads to mutually inconsistent results, indicating that more complex models, such as the inclusion of more realistic aggregate particles, are needed.
This paper presents a case study for the new slumped glass façade at Tiffany’s flagship store in New York City. The undulating façade of slumped IGU’s encloses a new, three-story addition that sits ...atop the existing Tiffany & Company building. Taken as a whole, the new façade appears as though it were a semi-transparent and flexible curtain of wave fold drapes, suspended from the roof of the new addition and wrapping its north and west elevations. The IGU’s, many as tall as 5.2 meters, consist of slumped glass outer lites and flat glass inner lites, which are glazed onto steel-reinforced aluminum curtain wall frames. Each slumped glass lite is formed into a series of four, wave-like arcs of differing lengths and radii, with the glass periodically rotated 180 degrees to create a more complex and seemingly random wave pattern despite the similar underlying geometry. As with all slumped IGU’s, their successful performance was contingent on solving a series of engineering challenges unique to their design. The volume of air within the slumped IGU cavity is much larger than that of a traditional flat IGU, leading to increased stress on the glass due to changes in temperature and atmospheric pressure. Because the slumped geometry of the outer lite substantially increases its stiffness, changes in air cavity pressure can lead to substantial deflection of the flat inner lite. Therefore, the size of the airspace and thickness of the inner lite were designed to prevent contact with the outer lite. As the stiffness of the vertically oriented slumped glass waves will distribute more wind pressure to the top and bottom of the IGU’s, the width of the secondary structural seal was modified accordingly. Finally, because the slumped glass did not allow for heat treatment, it remains annealed, and the potential for thermal stress breakage was thoroughly investigated.
This project describes the trialling of a new form of cooperative learning strategy, in the form of a game known as EcoRangers. EcoRangers is a multi-player game designed to run on mobile phones, ...written specifically for education. EcoRangers is one of the first, if not the world's first, instances of this totally new genre of pedagogical tools (i.e. collaborative handheld educational games). In its current iteration EcoRangers is designed to help students practise skills of relevance to the social studies syllabus for Grades 9 and 10 in Singapore's education system, specifically through the pedagogical strategy known as the 'structured academic controversy', in which learners debate an open-ended problem from a variety of perspectives. The trialling was done in three secondary schools, among 50 Grade 9 students. These students were taken through two distinct fieldwork tasks in March-July 2004, with the game being introduced as part of a post-fieldwork activity.
Jeux collaboratifs sur portables en éducation
Ce projet décrit l'expérimentation d'une nouvelle forme de stratégie d'apprentissage coopératif sous la forme d'un jeu connu sous le nom d'EcoRangers.EcoRangers se joue à plusieurs.Il a été conçu pour fonctionner sur les téléphones portables et composé spécialement pour L'éducation. EcoRangers est un des premiers sinon le premier exemple au monde de cette catégorie d'outils pédagogiques (celle des jeux éducatifs collaboratifs portables) totalement nouvelle. Sous sa forme actuelle EcoRangers a été conçu pour aider les élèves à pratiquer des savoir faire correspondant au cursus de sciences sociales pour les classes 9 et 10 du système Singapourien(13-14 ans) et plus particulièrement la stratégie connue sous le nom de « controverse académique structurée » au cours de laquelle les apprenants débatent d'un problème ouvert en partant de perspectives différentes.L'expérience a été menée dans trois écoles secondaires avec 50 élèves de 9
e
.Ces élèves ont participé à deux tâches « de terrain » distinctes entre mars et juillet 2004,le jeu étant présenté comme faisant partie d'une activité « d'après-terrain ».
Gemeinschafliches Spielen auf Handhelds oder Handys als Unterricht
Das Projekt beschreibt den Versuch, eine neue Art von Gruppenlernen zu testen, die auf ein Spiel zurück greift, das EcoRangers genannt wird. Dies ist ein Spiel für mehrere Spieler, das auf Handys abläuft und ein Lernspiel ist. EcoRangers ist eines der ersten, wenn nicht sogar das erste Spiel in der Welt, dieser Art. In seiner gegenwärtigen Fassung hilft EcoRangers den Schuelern, Fertigkeiten im Bereich der Social Studies (Gemeinschaftskunde) einzuueben (Lehrplan für Stufe 9 und 10 in Singapur), insbesondere dadurch, dass die Strategie der 'strukturierten, akademischen Diskussion' angewendet wird, bei der die Schueler ein offenes Problem aus sehr unterschiedlichen Perspektiven besprechen. Der Versuch wurde in drei Schulen (Sek.II) durchgeführt, wobei 50 Schueler aus Stufe 9 waren. Diese wurden im Rahmen eines Aufenthalts im Gelaende (Maerz-Juli 2004) mit dem Spiel konfrontiert, das als eine Tätigkeit nach dem Arbeiten im Gelände eingefuehrt wurde.
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BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Drs. C. Jason Wang, Kathleen Conroy, and Barry Zuckerman argue that safety-net institutions should be reimbursed more per patient under any pay-for-quality scheme that is implemented.
In the U.S. ...health care system today, many hospitals have the market power to raise the prices of their services without showing evidence of improvements in the quality of care.
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In an effort to realign incentives, health care reformers are now proposing to link provider payments to quality of care and health outcomes. As we move toward such a payment system, however, we must ensure that reimbursement is adjusted for patients' coexisting conditions so that hospitals cannot get high marks for quality by choosing to treat only patients who are considered to be at low risk.
Although risk adjustment has . . .
Aiming to assess the progress and current challenges on the formidable problem of the prediction of solar energetic events since the COSPAR/ International Living With a Star (ILWS) Roadmap paper of ...Schrijver et al. (2015), we attempt an overview of the current status of global research efforts. By solar energetic events we refer to flares, coronal mass ejections (CMEs), and solar energetic particle (SEP) events. The emphasis, therefore, is on the prediction methods of solar flares and eruptions, as well as their associated SEP manifestations. This work complements the COSPAR International Space Weather Action Teams (ISWAT) review paper on the understanding of solar eruptions by Linton et al. (2023) (hereafter, ISWAT review papers are conventionally referred to as ’Cluster’ papers, given the ISWAT structure). Understanding solar flares and eruptions as instabilities occurring above the nominal background of solar activity is a core solar physics problem. We show that effectively predicting them stands on two pillars: physics and statistics. With statistical methods appearing at an increasing pace over the last 40 years, the last two decades have brought the critical realization that data science needs to be involved, as well, as volumes of diverse ground- and space-based data give rise to a Big Data landscape that cannot be handled, let alone processed, with conventional statistics. Dimensionality reduction in immense parameter spaces with the dual aim of both interpreting and forecasting solar energetic events has brought artificial intelligence (AI) methodologies, in variants of machine and deep learning, developed particularly for tackling Big Data problems. With interdisciplinarity firmly present, we outline an envisioned framework on which statistical and AI methodologies should be verified in terms of performance and validated against each other. We emphasize that a homogenized and streamlined method validation is another open challenge. The performance of the plethora of methods is typically far from perfect, with physical reasons to blame, besides practical shortcomings: imperfect data, data gaps and a lack of multiple, and meaningful, vantage points of solar observations. We briefly discuss these issues, too, that shape our desired short- and long-term objectives for an efficient future predictive capability. A central aim of this article is to trigger meaningful, targeted discussions that will compel the community to adopt standards for performance verification and validation, which could be maintained and enriched by institutions such as NASA’s Community Coordinated Modeling Center (CCMC) and the community-driven COSPAR/ISWAT initiative.
ABSTRACT We present H-band observations of β Pic with the Gemini Planet Imager's (GPI's) polarimetry mode that reveal the debris disk between ∼0 3 (6 AU) and ∼1 7 (33 AU), while simultaneously ...detecting β Pic b. The polarized disk image was fit with a dust density model combined with a Henyey-Greenstein scattering phase function. The best-fit model indicates a disk inclined to the line of sight ( ) with a position angle (PA) (slightly offset from the main outer disk, ), that extends from an inner disk radius of to well outside GPI's field of view. In addition, we present an updated orbit for β Pic b based on new astrometric measurements taken in GPI's spectroscopic mode spanning 14 months. The planet has a semimajor axis of , with an eccentricity The PA of the ascending node is offset from both the outer main disk and the inner disk seen in the GPI image. The orbital fit constrains the stellar mass of β Pic to Dynamical sculpting by β Pic b cannot easily account for the following three aspects of the inferred disk properties: (1) the modeled inner radius of the disk is farther out than expected if caused by β Pic b; (2) the mutual inclination of the inner disk and β Pic b is when it is expected to be closer to zero; and (3) the aspect ratio of the disk ( ) is larger than expected from interactions with β Pic b or self-stirring by the disk's parent bodies.
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