Learning to Use Chopsticks in Diverse Gripping Styles

Learning dexterous manipulation skills is a long-standing challenge in computer graphics and robotics, especially when the task involves complex and delicate interactions between the hands, tools and objects. In this paper, we focus on chopsticks-based object relocation tasks, which are common yet demanding. The key to successful chopsticks skills is steady gripping of the sticks that also supports delicate maneuvers. We automatically discover physically valid chopsticks holding poses by Bayesian Optimization (BO) and Deep Reinforcement Learning (DRL), which works for multiple gripping styles and hand morphologies without the need of example data. Given as input the discovered gripping poses and desired objects to be moved, we build physics-based hand controllers to accomplish relocation tasks in two stages. First, kinematic trajectories are synthesized for the chopsticks and hand in a motion planning stage. The key components of our motion planner include a grasping model to select suitable chopsticks configurations for grasping the object, and a trajectory optimization module to generate collision-free chopsticks trajectories. Then we train physics-based hand controllers through DRL again to track the desired kinematic trajectories produced by the motion planner. We demonstrate the capabilities of our framework by relocating objects of various shapes and sizes, in diverse gripping styles and holding positions for multiple hand morphologies. Our system achieves faster learning speed and better control robustness, when compared to vanilla systems that attempt to learn chopstick-based skills without a gripping pose optimization module and/or without a kinematic motion planner

Direct Manipulation of quantum entanglement from the non-Hermitian nature of light-matter interaction

Biphoton process is an essential benchmark for quantum information science and technologies, while great efforts have been made to improve the coherence of the system for better quantum correlations. Nevertheless, we find that the non-Hermitian features induced by the atomic quantum interference could be well employed for the direct control of entanglement. We report the demonstration of exceptional point (EP) in biphotons by measuring the light-atom interaction as a natural non-Hermitian system, in which the electromagnetically induced transparency regime provides a powerful mechanism to precisely tune the non-Hermitian coupling strength. Such biphoton correlation is tuned within an unprecedented large range from Rabi oscillation to antibunching-exponential-decay, also indicating high-dimensional entanglement within the strong and weak light-matter coupling regimes. The EP at the transition point between the two regimes is clearly observed with the biphoton quantum correlation measurements, exhibiting a single exponential decay and manifesting the coalesced single eigenstate. Our results provide a unique method to realize the controllability of natural non-Hermitian processes without the assistance of artificial photonic structures, and paves the way for quantum control by manipulating the non-Hermitian features of the light-matter interaction

Detection of Hepatitis B virus in serum and liver of chickens

Hepatitis B virus (HBV) is one of the most important human pathogens. Its existence in food animals could present a significant threat to public health. The objective of this study was to determine if HBV is present in serum and liver of chickens. A total of 129 serum samples from broiler chickens were collected for the detection of HBV antigens and antibodies, and 193 liver samples were tested for HBV DNA sequence by PCR and for the existence of HBV antigens by immunohistochemistry. The overall prevalence of HBsAg, anti-HBs, anti-HBc was 28.68%, 53.49%, 17.05%, respectively, whereas HBeAg, anti-HBe were barely detectable. Three serum samples were found to be positive for both HBsAg and HBeAg. Further analysis of these samples with transmission electron microscopy (TEM) revealed two morphologic particles with 20 nm and 40 nm in diameter, which were similar to small spherical and Danes particles of HBV. The viral DNA sequence identified in two of the chicken livers shared 92.2% of one known HBV strain and 97.9% nucleotide sequence of another HBV strain. Our results showed the existence of HBV in chickens. This would present a significant risk to people who work with live chickens or chicken products if HBV found in chicken could be confirmed to be the same as human HBV

Direct generation of time-energy-entangled W triphotons in atomic vapor

Sources of entangled multiphotons are not only essential for fundamental tests of quantum foundations, but are also the cornerstone of a variety of optical quantum technologies today. Over past three decades, tremendous efforts have been devoted to creating multiphoton entanglement by multiplexing existing biphoton sources with linear optics and postselections. Different from all previous protocols, here we report, for the first time, the observation of continuous-mode time-energy-entangled W-class triphotons with an unprecedented generation rate directly through the process of spontaneous six-wave mixing (SSWM) in a four-level triple-Lambda atomic vapor cell. Facilitated by electromagnetically induced transparency and coherence control, our SSWM scheme enables versatile narrowband triphoton generation with many intriguing properties including long temporal coherence and controllable waveforms, ideal for implementing long-distance quantum communications, networking, and information processing by interfacing photons and atoms. Most importantly, our work paves a way for the development of a reliable and efficient genuine triphoton source, thus making the research on multiphoton entanglement within easy reach.Comment: welcome the comment

Case report: Rare novel MIPEP compound heterozygous variants presenting with hypertrophic cardiomyopathy, severe lactic acidosis and hypotonia in a Chinese infant

BackgroundMitochondrial intermediate peptidase, encoded by the MIPEP gene, is involved in the processing of precursor mitochondrial proteins related to oxidative phosphorylation. Only a few studies have shown that mutations in MIPEP can cause combined oxidative phosphorylation deficiency-31 (COXPD31), an autosomal recessive multisystem disorder associated with mitochondrial dysfunction. We report herein a rare case of an 8-month-old boy in China with hypertrophic cardiomyopathy (HCM), severe lactic acidosis, and hypotonia caused by novel MIPEP compound heterozygous variants.MethodsTrio-whole-exome sequencing and copy number variation sequencing were performed to identify mutated genetic loci. Sanger sequencing and quantitative real-time PCR were used to validate the candidate single nucleotide variants and copy number variants, respectively.ResultsThe proband was an 8-month-old boy with HCM, severe lactic acidosis, and hypotonia who died 2 months after his first admission. Two novel compound heterozygous variants, c.1081T > A (p. Tyr361Asn) and a whole deletion (Ex1-19 del), were found in the MIPEP gene, which were inherited from his healthy parents respectively. Additionally, his mitochondria DNA copy number was significantly reduced.ConclusionWe are the first to report a patient with rare MIPEP variants in China. Our findings expand the mutation spectrum of MIPEP, and provide insights into the genotype-phenotype relationship in COXPD31

Data-driven kinematic and dynamic models for character animation

Human motion plays a key role in the production of films, video games, virtual reality applications, and the control of humanoid robots. Unfortunately, it is hard to generate high quality human motion for character animation either manually or algorithmically. As a result, approaches based on motion capture data have become a central focus of character animation research in recent years. We observe three principal weaknesses in previous work using data-driven approaches for modelling human motion. First, basic balance behaviours and locomotion tasks are currently not well modelled. Second, the ability to produce high quality motion that is responsive to its environment is limited. Third, knowledge about human motor control is not well utilized. This thesis develops several techniques to generalize motion capture character animations to balance and respond. We focus on balance and locomotion tasks, with an emphasis on responding to disturbances, user interaction, and motor control integration. For this purpose, we investigate both kinematic and dynamic models. Kinematic models are intuitive and fast to construct, but have narrow generality, and thus require more data. A novel performance-driven animation interface to a motion database is developed, which allows a user to use foot pressure to control an avatar to balance in place, punch, kick, and step. We also present a virtual avatar that can respond to pushes, with the aid of a motion database of push responses. Consideration is given to dynamics using motion selection and adaption. Dynamic modelling using forward dynamics simulations requires solving difficult problems related to motor control, but permits wider generalization from given motion data. We first present a simple neuromuscular model that decomposes joint torques into feedforward and low-gain feedback components, and can deal with small perturbations that are assumed not to affect balance. To cope with large perturbations we develop explicit balance recovery strategies for a standing character that is pushed in any direction. Lastly, we present a simple continuous balance feedback mechanism that enables the control of a large variety of locomotion gaits for bipeds. Different locomotion tasks, including walking, running, and skipping, are constructed either manually or from motion capture examples. Feedforward torques can be learned from the feedback components, emulating a biological motor learning process that leads to more stable and natural motions with low gains. The results of this thesis demonstrate the potential of a new generation of more sophisticated kinematic and dynamic models of human motion.Science, Faculty ofComputer Science, Department ofGraduat