As one of the composers living in an era filled with innovations, Anatol Konstantinovich Lyadov (1855-1914) has been relatively ignored by scholars and pianists to date. He is an unusual composer with multiple characteristics: solitary but expressive, talented but indolent. His compositional style never lacked critics—especially with respect to his persistent preference of miniatures. Nonetheless, his piano works embody the breathtaking beauty of the composer’s independent musical ideas and colorful musical language. Compared with the flourishing, dazzling, and nationalized music from other composers living in the same era, these light, flowing musical pieces from Lyadov have irreplaceable value.

Through the study of these small-scale piano works, one finds important connections with the music of other renowned composers (e.g. Chopin and Scriabin), and the employment of traditional aspects such as Russian folk tones and fairy tales. Stylistically, Lyadov was a representative of 19th-century Romanticism; however, his compositional style changed during his late period (after 1900), presenting a unique use of dissonance.

The scholarly research on Lyadov’s piano works remains limited. Most of the related resources can be found only in the Russian music literature. No in-depth study or dissertation on the complete piano works of Lyadov could be located, and therefore my research paper is intended to provide useful information to piano performers and teachers, hopefully encouraging more study and performance of Lyadov’s piano works. Despite their lyrical melodies and deep emotion, these works are thus far relatively unpopular and unknown, with only a few played occasionally as encore pieces.

The game held by National Basketball Association (NBA) is the most popular basketball event on earth. Each year, tons of statistical data are generated from this industry. Meanwhile, managing teams, sports media, and scientists are digging deep into the data ocean. Recent research literature is reviewed with respect to whether NBA teams could be analyzed as connected networks. However, it becomes very time-consuming, if not impossible, for human labor to capture every detail of game events on court of large amount. In this study, an alternative method is proposed to parse public resources from NBA related websites to build degenerated game-wise flow graphs. Then, three different statistical techniques are tested to observe the network properties of such offensive strategy in terms of Home-Away team manner. In addition, a new algorithm is developed to infer real game ball distribution networks at the player level under low-rank constraints. The ball-passing degree matrix of one game is recovered to the optimal solution of low-rank ball transition network by constructing a convex operator. The experimental results on real NBA data demonstrate the effectiveness of the proposed algorithm.