Connection between visual arts and music: The painting and music of I-Uen Wang Hwang

This document explores the connection between the visual arts and music, particularly focusing on the similarity between visual and aural artistic expression by analyzing two sets of piano pieces composed by I-Uen Wang Hwang, a contemporary Taiwanese-American composer and artist. The piano pieces are Dream Garden, Series I and II (2000-2004) and Preludes for Piano (2016). Series I of Dream Garden contains two piano solo compositions based on a series of Hwang’s own watercolor works. Each composition has an analogous painting: “The Horn of the Plenty” and “Butterfly Orchid”. Series II includes two compositions written for two pianos: “Red and White” and “Fireworks”, which are also based on her watercolor paintings of flowers. “Each piano part has its own individual character with different timbres and rhythms, as if each part represented a different color or texture of the painting.”[1] Preludes for Piano is a new composition set that Hwang composed in 2016. There are three preludes, each prelude based on an abstract acrylic painting. My intention is to explore the connection between paintings and music by discussing the historical background of the two art forms, analyzing the selected music of Hwang in detail, and referring to other composers whose musical compositions were related and inspired by paintings. [1] I-Uen Wang Hwang, “Dream Garden”. Program notes for doctoral lecture recital. Yining Jiang. Harrisonburg: James Madison University Recital Hall, September 17, 2017

A new polygenic score for refractive error improves detection of children at risk of high myopia but not the prediction of those at risk of myopic macular degeneration

Background High myopia (HM), defined as a spherical equivalent refractive error (SER) ≤ −6.00 diopters (D), is a leading cause of sight impairment, through myopic macular degeneration (MMD). We aimed to derive an improved polygenic score (PGS) for predicting children at risk of HM and to test if a PGS is predictive of MMD after accounting for SER. Methods The PGS was derived from genome-wide association studies in participants of UK Biobank, CREAM Consortium, and Genetic Epidemiology Research on Adult Health and Aging. MMD severity was quantified by a deep learning algorithm. Prediction of HM was quantified as the area under the receiver operating curve (AUROC). Prediction of severe MMD was assessed by logistic regression. Findings In independent samples of European, African, South Asian and East Asian ancestry, the PGS explained 19% (95% confidence interval 17–21%), 2% (1–3%), 8% (7–10%) and 6% (3–9%) of the variation in SER, respectively. The AUROC for HM in these samples was 0.78 (0.75–0.81), 0.58 (0.53–0.64), 0.71 (0.69–0.74) and 0.67 (0.62–0.72), respectively. The PGS was not associated with the risk of MMD after accounting for SER: OR = 1.07 (0.92–1.24). Interpretation Performance of the PGS approached the level required for clinical utility in Europeans but not in other ancestries. A PGS for refractive error was not predictive of MMD risk once SER was accounted fo