Beethoven’s compositional approaches to meter and rhythm as evidenced in Op. 127 and its extant sketches

Despite many scholars having explored Beethoven’s compositional rhythmic processes, no systematic study has been done in this regard for the sketches for String Quartet Op. 127, and any mention of rhythm in the current literature tends to be incidental. I combine the theories of Rothstein, Krebs and others, an approach that has been more effective in understanding the changes during the compositional process from metrical and hypermetrical perspectives. I examine how Beethoven’s rhythmic patterns add to both musical coherence and contrast. My thesis demonstrates that Beethoven’s starting point is usually a conventional 8- or 16-measure phrase; later, according to the sketches, he makes rhythmic adjustments, such as grouping dissonances, expansions, or displacements, using a variety of parameters. Also added later are rhythmic patterns that individualize each of the four instruments. These processes are found throughout the two movements studied. Therefore, rhythm and its manipulations are used as unifying features

Does School Quality Affect Real Estate Prices? The Effect of Top-Tier Elementary Schools on Property Prices in Shanghai

This study adapted the hedonic pricing model and inspected how varying elementary school quality affects property prices in Shanghai. Because the variation of school quality appeared before the capitalization of the housing market, the obtained results suggest a causal relationship. The data set comprises top-tier elementary school information from eWOM, the yearly school attendance zones published by the government, and the Shanghai Existing Property Index, which has a sample of similarly structured apartments. Main results show that prices on average increase 41.9% more in the top-tier school districts under the standardized housing system, and range from 15.5% to 69.7% among different districts in urban Shanghai

Intersubband Transitions in Lead Halide Perovskite-Based Quantum Wells for Mid-Infrared Detectors

Due to their excellent optical and electrical properties as well as versatile growth and fabrication processes, lead halide perovskites have been widely considered as promising candidates for green energy and opto-electronic related applications. Here, we investigate their potential applications at infrared wavelengths by modeling the intersubband transitions in lead halide perovskite-based quantum well systems. Both single-well and double-well structures are studied and their energy levels as well as the corresponding wavefunctions and intersubband transition energies are calculated by solving the one-dimensional Schr\"odinger equations. By adjusting the quantum well and barrier thicknesses, we are able to tune the intersubband transition energies to cover a broad range of infrared wavelengths. We also find that the lead-halide perovskite-based quantum wells possess high absorption coefficients, which are beneficial for their potential applications in infrared photodetectors. The widely tunable transition energies and high absorption coefficients of the perovskite-based quantum well systems, combined with their unique material and electrical properties, may enable an alternative material system for the development of infrared photodetectors.Comment: 24 pages, 5 figure

Improvement of two-way continuous-variable quantum key distribution using optical amplifiers

The imperfections of a receiver's detector affect the performance of two-way continuous-variable quantum key distribution protocols and are difficult to adjust in practical situations. We propose a method to improve the performance of two-way continuous-variable quantum key distribution by adding a parameter-adjustable optical amplifier at the receiver. A security analysis is derived against a two-mode collective entangling cloner attack. Our simulations show that the proposed method can improve the performance of protocols as long as the inherent noise of the amplifier is lower than a critical value, defined as the tolerable amplifier noise. Furthermore, the optimal performance can approach the scenario where a perfect detector is used.Comment: 14 pages, 7 figure

DVGG: Deep Variational Grasp Generation for Dextrous Manipulation

Grasping with anthropomorphic robotic hands involves much more hand-object interactions compared to parallel-jaw grippers. Modeling hand-object interactions is essential to the study of multi-finger hand dextrous manipulation. This work presents DVGG, an efficient grasp generation network that takes single-view observation as input and predicts high-quality grasp configurations for unknown objects. In general, our generative model consists of three components: 1) Point cloud completion for the target object based on the partial observation; 2) Diverse sets of grasps generation given the complete point cloud; 3) Iterative grasp pose refinement for physically plausible grasp optimization. To train our model, we build a large-scale grasping dataset that contains about 300 common object models with 1.5M annotated grasps in simulation. Experiments in simulation show that our model can predict robust grasp poses with a wide variety and high success rate. Real robot platform experiments demonstrate that the model trained on our dataset performs well in the real world. Remarkably, our method achieves a grasp success rate of 70.7\% for novel objects in the real robot platform, which is a significant improvement over the baseline methods.Comment: Accepted by Robotics and Automation Letters (RA-L, 2021