Telepath: Understanding Users from a Human Vision Perspective in Large-Scale Recommender Systems

Designing an e-commerce recommender system that serves hundreds of millions of active users is a daunting challenge. From a human vision perspective, there're two key factors that affect users' behaviors: items' attractiveness and their matching degree with users' interests. This paper proposes Telepath, a vision-based bionic recommender system model, which understands users from such perspective. Telepath is a combination of a convolutional neural network (CNN), a recurrent neural network (RNN) and deep neural networks (DNNs). Its CNN subnetwork simulates the human vision system to extract key visual signals of items' attractiveness and generate corresponding activations. Its RNN and DNN subnetworks simulate cerebral cortex to understand users' interest based on the activations generated from browsed items. In practice, the Telepath model has been launched to JD's recommender system and advertising system. For one of the major item recommendation blocks on the JD app, click-through rate (CTR), gross merchandise value (GMV) and orders have increased 1.59%, 8.16% and 8.71% respectively. For several major ads publishers of JD demand-side platform, CTR, GMV and return on investment have increased 6.58%, 61.72% and 65.57% respectively by the first launch, and further increased 2.95%, 41.75% and 41.37% respectively by the second launch.Comment: 8 pages, 11 figures, 1 tabl

System Design of a Cheetah Robot Toward Ultra-high Speed

High-speed legged locomotion pushes the limits of the most challenging problems of design and development of the mechanism, also the control and the perception method. The cheetah is an existence proof of concept of what we imitate for high-speed running, and provides us lots of inspiration on design. In this paper, a new model of a cheetah-like robot is developed using anatomical analysis and design. Inspired by a biological neural mechanism, we propose a novel control method for controlling the muscles' flexion and extension, and simulations demonstrate good biological properties and leg's trajectory. Next, a cheetah robot prototype is designed and assembled with pneumatic muscles, a musculoskeletal structure, an antagonistic muscle arrangement and a J-type cushioning foot. Finally, experiments of the robot legs swing and kick ground tests demonstrate its natural manner and validate the design of the robot. In the future, we will test the bounding behaviour of a real legged system

Research on the Obstacle Negotiation Strategy for the Heavy-duty Six-legged Robot based on Force Control

To make heavy-duty six-legged robots without environment reconstruction system negotiate obstacles after the earthquake successfully, an obstacle negotiation strategy is described in this paper. The reflection strategy is generated by the information of plantar force sensors and Bezier Curve is used to plan trajectory. As the heavy-duty six-legged robot has a large inertia, force controller is necessary to ensure the robot not to lose stability while negotiating obstacles. Impedance control is applied to reduce the impact of collision and active force control is applied to adjust the pose of the robot. The robot can walk through zones that are filled with obstacles automatically because of force control. Finally, the algorithm is verified in a simulation environment

Research on the Obstacle Negotiation Strategy for the Heavy-duty Six-legged Robot based on Force Control

To make heavy-duty six-legged robots without environment reconstruction system negotiate obstacles after the earthquake successfully, an obstacle negotiation strategy is described in this paper. The reflection strategy is generated by the information of plantar force sensors and Bezier Curve is used to plan trajectory. As the heavy-duty six-legged robot has a large inertia, force controller is necessary to ensure the robot not to lose stability while negotiating obstacles. Impedance control is applied to reduce the impact of collision and active force control is applied to adjust the pose of the robot. The robot can walk through zones that are filled with obstacles automatically because of force control. Finally, the algorithm is verified in a simulation environment

Learning the Metric of Task Constraint Manifolds for Constrained Motion Planning

Finding feasible motion for robots with high-dimensional configuration space is a fundamental problem in robotics. Sampling-based motion planning algorithms have been shown to be effective for these high-dimensional systems. However, robots are often subject to task constraints (e.g., keeping a glass of water upright, opening doors and coordinating operation with dual manipulators), which introduce significant challenges to sampling-based motion planners. In this work, we introduce a method to establish approximate model for constraint manifolds, and to compute an approximate metric for constraint manifolds. The manifold metric is combined with motion planning methods based on projection operations, which greatly improves the efficiency and success rate of motion planning tasks under constraints. The proposed method Approximate Graph-based Constrained Bi-direction Rapidly Exploring Tree (AG-CBiRRT), which improves upon CBiRRT, and CBiRRT were tested on several task constraints, highlighting the benefits of our approach for constrained motion planning tasks

Role of PCSK9 in sulforaphane attenuating palmitic acid-induced autophagic flux in hepatic cells

Objective To determine the effect and underlying mechanism of sulforaphane (SFN) on hepatocyte injury and autophagy. Methods HHL5 cells were treated with 200 μmol/L palmitic acid (PA) for 24 h to establish a hepatocyte injury model. Then the model was treated with 5 μmol/L SFN and co-cultured with 200 μmol/L PA for 24 h. So there were 3 groups of cells, that is, control group, PA group, and PA+SFN group. Cell viability, malonaldehyde (MDA) content, and production of reactive oxygen species (ROS) were measured with CCk-8 assay, MDA reagent kit, and CellROXTM Deep Red Reagent, respectively. qPCR was used to detect the transcription levels of IL-1β and TNF-α, and Western blotting was employed to measure the protein expression of SQSTM1 and LC3II. The total RNA of the cell was extracted by TRIzol reagent to sequence the whole gene transcriptome, and the RNA sequence was analyzed to figure out differentially expressed genes. And the results were subjected to Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Furthermore, HHL5 cells were pretreated with PCSK9 siRNA for 24 h, then the mRNA level of PCSK9 was measured by qPCR, and the expression of SQSTM1 and LC3 II were measured by Western blotting. Results Compared with the PA group, the cell survival rate was increased, and the levels of MDA and ROS were decreased significantly in the PA+SFN group (P < 0.05). The transcriptional levels of IL-1β and TNF-α were reduced obviously in the PA+SFN group (P < 0.05). The expression of SQSTM1 was decreased and that of LC3II was increased in the PA+SFN group. KEGG enrichment analysis suggested that differential expressed genes were enriched on the autophagy pathway. PCSK9 was selected as our candidate gene. Compared with the control group, the transcriptional level of PCSK9 was increased in the PA group, while was decreased significantly in the PA+SFN group (P < 0.05). The level was elevated in the PA group but decreased after SFN intervention. After PCSK9 knockdown, the ROS level in the PA group was decreased compared with that in the PA group without siPCSK9 treatment, which was consistent with the trend of SFN-induced ROS reduction. After PCSK9 knockdown, the expression level of LC3II was increased, which was consistent with the trend of SFN-induced autophagy flux recovery. Conclusion SFN can attenuate hepatocyte injury induced by PA, which may be related to the inhibition of PCSK9 at transcriptional level, thus regulating autophagic flux