Angular Momentum of a Brane-world Model

In this paper we discuss the properties of the general covariant angular momentum of a five-dimensional brane-world model. Through calculating the total angular momentum of this model, we are able to analyze the properties of the total angular momentum in the inflationary RS model. We show that the space-like components of the total angular momentum of are all zero while the others are non-zero, which agrees with the results from ordinary RS model.Comment: 8 pages; accepted by Chinese Physics

Benchmarking Deep Reinforcement Learning for Continuous Control

Recently, researchers have made significant progress combining the advances in deep learning for learning feature representations with reinforcement learning. Some notable examples include training agents to play Atari games based on raw pixel data and to acquire advanced manipulation skills using raw sensory inputs. However, it has been difficult to quantify progress in the domain of continuous control due to the lack of a commonly adopted benchmark. In this work, we present a benchmark suite of continuous control tasks, including classic tasks like cart-pole swing-up, tasks with very high state and action dimensionality such as 3D humanoid locomotion, tasks with partial observations, and tasks with hierarchical structure. We report novel findings based on the systematic evaluation of a range of implemented reinforcement learning algorithms. Both the benchmark and reference implementations are released at https://github.com/rllab/rllab in order to facilitate experimental reproducibility and to encourage adoption by other researchers.Comment: 14 pages, ICML 201

A 14-mW PLL-less receiver in 0.18-μm CMOS for Chinese electronic toll collection standard

This is the accepted manuscript version of the following article: Xiaofeng He, et al., “A 14-mW PLL-less receiver in 0.18-μm CMOS for Chinese electronic toll collection standard”, IEEE Transactions on Circuits and Systems II: Express Briefs, Vol. 61(10): 763-767, August 2014. The final published version is available at: http://ieeexplore.ieee.org/document/6871304/ © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The design of a 14-mW receiver without phase-locked loop for the Chinese electronic toll collection (ETC) system in a standard 0.18-μm CMOS process is presented in this brief. Since the previously published work was mainly based on vehicle-powered systems, low power consumption was not the primary goal of such a system. In contrast, the presented system is designed for a battery-powered system. Utilizing the presented receiver architecture, the entire receiver only consumes 7.8 mA, at the supply voltage of 1.8 V, which indicates a power saving of at least 38% compared with other state-of-the-art designs for the same application. To verify the performance, the bit error rate is measured to be better than 10-6, which well satisfies the Chinese ETC standard. Moreover, the sensitivity of the designed receiver can be readjusted to -50 dBm, which is required by the standard.Peer reviewe

InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets

This paper describes InfoGAN, an information-theoretic extension to the Generative Adversarial Network that is able to learn disentangled representations in a completely unsupervised manner. InfoGAN is a generative adversarial network that also maximizes the mutual information between a small subset of the latent variables and the observation. We derive a lower bound to the mutual information objective that can be optimized efficiently, and show that our training procedure can be interpreted as a variation of the Wake-Sleep algorithm. Specifically, InfoGAN successfully disentangles writing styles from digit shapes on the MNIST dataset, pose from lighting of 3D rendered images, and background digits from the central digit on the SVHN dataset. It also discovers visual concepts that include hair styles, presence/absence of eyeglasses, and emotions on the CelebA face dataset. Experiments show that InfoGAN learns interpretable representations that are competitive with representations learned by existing fully supervised methods

VIME: Variational Information Maximizing Exploration

Scalable and effective exploration remains a key challenge in reinforcement learning (RL). While there are methods with optimality guarantees in the setting of discrete state and action spaces, these methods cannot be applied in high-dimensional deep RL scenarios. As such, most contemporary RL relies on simple heuristics such as epsilon-greedy exploration or adding Gaussian noise to the controls. This paper introduces Variational Information Maximizing Exploration (VIME), an exploration strategy based on maximization of information gain about the agent's belief of environment dynamics. We propose a practical implementation, using variational inference in Bayesian neural networks which efficiently handles continuous state and action spaces. VIME modifies the MDP reward function, and can be applied with several different underlying RL algorithms. We demonstrate that VIME achieves significantly better performance compared to heuristic exploration methods across a variety of continuous control tasks and algorithms, including tasks with very sparse rewards.Comment: Published in Advances in Neural Information Processing Systems 29 (NIPS), pages 1109-111

Ureteric Obstruction Caused by a Migrated Intrauterine Device

AbstractWe present an extremely rare case of ureteric obstruction caused by a migrated intrauterine device. A 36-year-old female with complaints of almost 10 months left flank pain presented to our hospital. She used an IUD for contraception for 6 months after the birth of her first child. The IUD was not visible then. Ultrasonography (US) revealed that left severe hydronephrosis and upper ureterectasis. Pelvic computed tomography (CT) found that IUD was located very close to the lower ureter which was adjacent to the third anatomize physiological narrow. Laparoscopy was performed to remove the migrated IUD. After 5 months of surgery, left hydronephrosis was exacerbated. This time we chose to perform the ureterocystostomy to relieve the hydronephrosis. We reported this rare case to remind that we must keep alert to the loss of the IUD to prevent it may cause severe injury of the nearby organs. IUD must be carefully researched for possible perforation of the uterus and migration to the pelvic organs