Design and Production of 3D Animation Short Film “Memories of the Post-80s”

“The memories of the post-80s” is a 2minutes and 8 seconds 3D animated short film which tells a story of a young man named Kai who born in the post-80s in China, living in a modern, high-tech environment, but falling into a fantasy dream and reminiscing about his simple and happy life as a child. The most important question expressed in this short film is whether a more convenient, high-tech, fast-paced modern life is proportional to people\u27s happiness index. The main reasons for this problem are multiple, such as working pressure, stressful life, repayment of loans, health, and so on. The boredom and indifference to modern life is a manifestation caused by multiple aspects of social life problems. Because of this invisible pressure, and also to form a sharp contrast with the differences of the times, the film\u27s author gathered many of the typical games and snacks as the main elements of childhood and brought them together to create a fantasy world full of the post-80s childhood memories which reflects how children spend their free time before the Internet and the self-media became popular to commemorate their special and wonderful time. This short film is presented in 3D. 3D is chosen to better show people\u27s feelings when playing games. Although the design of these games was mainly based on 2D, the mood of playing at that time was as immersive as the current 3D scene. And using 3d to express the dynamics of the game is more vivid and exaggerated. The author combines various fantasies of the author\u27s dreams around the game world. The purpose of creating in this form is to express the world in the memory of people in the post-80s, to express their mentality of escaping from the real world and their yearning for the unknown and wonderful world

Machine Learning Topological Invariants with Neural Networks

In this Letter we supervisedly train neural networks to distinguish different topological phases in the context of topological band insulators. After training with Hamiltonians of one-dimensional insulators with chiral symmetry, the neural network can predict their topological winding numbers with nearly 100% accuracy, even for Hamiltonians with larger winding numbers that are not included in the training data. These results show a remarkable success that the neural network can capture the global and nonlinear topological features of quantum phases from local inputs. By opening up the neural network, we confirm that the network does learn the discrete version of the winding number formula. We also make a couple of remarks regarding the role of the symmetry and the opposite effect of regularization techniques when applying machine learning to physical systems.Comment: 6 pages, 4 figures and 1 table + 2 pages of supplemental materia

Postmenopausal women with osteoporosis and osteoarthritis show different microstructural characteristics of trabecular bone in proximal tibia using high-resolution magnetic resonance imaging at 3 tesla

BACKGROUND: Osteoporosis (OP) and osteoarthritis (OA) are two common musculoskeletal disorders that affect the quality of life in aged people. An inverse relationship between OP and OA was proposed four decades ago. However, the difference in microstructure of the trabecular bone of these two disorders by high-resolution MRI (HR-MRI) has not been compared. The primary objective of the study is to explain the actual relationship between OA and OP based on differences between bone microstructure of these two diseases. The secondary objectives are to find out the significance of Euler number and its relationship with other structural parameters, and important role of HR-MRI to reveal the microstructure of trabecular bone directly. METHODS: Totally, 30 women with OP and 30 women with OA (n = 60) were included in this study. Primary OA of hip, knee, as well as spinal arthrosis were diagnosed according to plain X-ray film findings. Osteoporosis was defined based on the latest criteria of World Health Organization (WHO). Structural and textural parameters derived from HR-MRI images of proximal tibia were calculated and compared with special software. RESULTS: There were significant differences in apparent bone volume fraction, trabecular thickness, mean roundness, Euler number, entropy and inverse different moment between OP and OA patients. In OP group, apparent trabecular separation (Tb.Sp), inertia, absolute value and contrast were positively correlated with Euler number, whereas apparent trabecular number (Tb.N), mean trabecular area, inverse difference and inverse different moment were negatively correlated. Apparent trabecular bone volume fraction (BV/TV), mean trabecular area, mean trabecular perimeter and mean skeleton length negatively correlated with Euler number in OA group. Inverse different moment was the texture parameter, which influenced bone mineral density (BMD) of femoral neck, meanwhile contrast influenced BMD of both great trochanter and Ward’s triangle in OP group. While in OA group, Euler number was the exclusive parameter, which affected BMD of femoral neck and Ward’s triangle. CONCLUSIONS: We found significant differences in microstructure parameters derived from HR-MRI images between postmenopausal women with OP and OA. It convincingly supports the hypothesis that there might be an inverse relationship between OP and OA

Show, Attend and Read: A Simple and Strong Baseline for Irregular Text Recognition

Recognizing irregular text in natural scene images is challenging due to the large variance in text appearance, such as curvature, orientation and distortion. Most existing approaches rely heavily on sophisticated model designs and/or extra fine-grained annotations, which, to some extent, increase the difficulty in algorithm implementation and data collection. In this work, we propose an easy-to-implement strong baseline for irregular scene text recognition, using off-the-shelf neural network components and only word-level annotations. It is composed of a $31$-layer ResNet, an LSTM-based encoder-decoder framework and a 2-dimensional attention module. Despite its simplicity, the proposed method is robust and achieves state-of-the-art performance on both regular and irregular scene text recognition benchmarks. Code is available at: https://tinyurl.com/ShowAttendReadComment: Accepted to Proc. AAAI Conference on Artificial Intelligence 201